miladalsh/processed_scinews_dataset · Datasets at Hugging Face

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Background Individuals infected with SARS-CoV-2 vary greatly in their disease severity, ranging from asymptomatic infection to severe disease. The regulation of gene expression is an important mechanism in the host immune response and can modulate the outcome of the disease. miRNAs play important roles in post-transcriptional regulation with consequences on downstream molecular and cellular host immune response processes. The nature and magnitude of miRNA perturbations associated with blood phenotypes and intensive care unit (ICU) admission in COVID-19 are poorly understood. Results We combined multi-omics profiling—genotyping, miRNA and RNA expression, measured at the time of hospital admission soon after the onset of COVID-19 symptoms—with phenotypes from electronic health records to understand how miRNA expression contributes to variation in disease severity in a diverse cohort of 259 unvaccinated patients in Abu Dhabi, United Arab Emirates. We analyzed 62 clinical variables and expression levels of 632 miRNAs measured at admission and identified 97 miRNAs associated with 8 blood phenotypes significantly associated with later ICU admission. Integrative miRNA-mRNA cross-correlation analysis identified multiple miRNA-mRNA-blood endophenotype associations and revealed the effect of miR-143-3p on neutrophil count mediated by the expression of its target gene BCL2. We report 168 significant cis -miRNA expression quantitative trait loci, 57 of which implicate miRNAs associated with either ICU admission or a blood endophenotype. Conclusions This systems genetics study has given rise to a genomic picture of the architecture of whole blood miRNAs in unvaccinated COVID-19 patients and pinpoints post-transcriptional regulation as a potential mechanism that impacts blood traits underlying COVID-19 severity. The results also highlight the impact of host genetic regulatory control of miRNA expression in early stages of COVID-19 disease. Introduction The three years since the emergence of SARS-CoV-2 have brought unprecedented progress in our scientific understanding of the SARS-CoV-2 infection and COVID-19 disease. However, one overarching question remains: why do individuals infected with SARS-CoV-2 vary in their clinical symptomatology, from asymptomatic infection to severe, and oftentimes, lethal disease [ 1 , 2 ]? The answer to this complex question lies in layers of genetic, biological, environmental, and social factors. Previous studies have found that both men and older patients, as well as those with underlying medical conditions such as diabetes, hypertension and obesity are at a higher risk for severe disease, requirement of intensive care and death [ 3 - 6 ]. Studies have also identified a number of blood phenotypes associated with severe disease, including elevated levels of D-dimers, C-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR), Interleukin 6 (IL-6), IL-10, lactate dehydrogenase (LDH), procalcitonin and albumin [ 7 - 14 ]. Neutrophils have been found to play a critical role in the pathophysiology of COVID-19 [ 15 - 17 ], with activation of circulating neutrophils—as observed in transcriptomic data—pinpointed as a predictor of clinical illness in COVID-19 [ 18 , 19 ]. Genetic variation has also been shown to influence COVID-19 susceptibility, severity and clinical outcomes [ 20 , 21 ]. While there has been extensive research to unpack the different sources of variation that influence COVID-19 disease severity, only a few studies to date have focused on the potential roles of human-encoded microRNA (miRNA). miRNAs are a class of small, non-coding RNAs that regulate gene expression by binding to complementary mRNA transcripts to either block translation or mark the target mRNA for degradation [ 22 , 23 ]. miRNAs can regulate both neighboring or distal genes; one miRNA can regulate either one or multiple genes; and multiple miRNAs can target the same gene in either a synergistic or antagonistic manner [ 24 ]. Since regulated miRNA expression is crucial for the differentiation, activation and survival of immune cells [ 25 ], dysregulated miRNA expression can be indicative of aberrant immune function, and has been implicated in numerous diseases including cancers, inflammatory disorders and malaria [ 26 - 28 ]. miRNA expression is also influenced by host genetics, with a few studies describing genetic variation associated with miRNA expression in healthy donors and disease contexts like malaria and cancer [ 29 - 32 ]. Despite the contributions of miRNAs to immune function, our understanding of the roles of miRNAs in response to SARS-CoV-2 is still in its nascency. There are a number of studies (reviewed in Geraylow et al. [ 33 ]) that have identified aberrant miRNA expression during COVID-19 disease progression. Farr and colleagues reported the differential expression of 55 miRNAs between COVID-19 patients during the early stage of disease and healthy donors matched for age and gender [ 34 ]; Fernández-Pato and colleagues identified 200 differentially expressed miRNAs between COVID-19 patients and healthy controls which were also correlated with proinflammatory cytokines such as IL-6, IL-12, IP-10, and TNFɑ [ 35 ]; Pinacchio and colleagues highlighted increased levels of miR-122a and miR-146a in the serum of COVID-19 patients compared to controls, and reported a negative correlation between miR-146a and Interferon alpha-inducible protein 27 (IFI-27) [ 36 ]; de Gonzalo-Calvo et al. identified 10 miRNAs that were dysregulated in hospitalized patients admitted to the intensive care unit (ICU), compared to patients that did not require ICU care, reported correlations between miRNA levels and length of ICU stay, and found that the expression of miR-192-5p and miR-323a-3p differentiated ICU non-survivors from survivors [ 37 ]; Li and colleagues used mendelian randomization to pinpoint two miRNAs (hsa-miR-30a-3p and hsa-miR-139-5p) as potentially causal for COVID-19 severity [ 38 ]; and early in the pandemic, Kim and colleagues identified five miRNAs (hsa-miR-15b-5p, hsa-miR-195-5p, hsa-miR-221-3p, hsa-miR-140-3p, and hsa-miR-422a) predicted to commonly bind the SARS-CoV, MERS-CoV and SARS-CoV-2 viruses, and showed that they were differentially expressed in hamster lung tissues before and after SARS-CoV-2 infection [ 39 ]. Importantly, many of the miRNAs highlighted across these studies were shown to be enriched in inflammatory and antiviral immune response pathways [ 33 ]. Another set of studies have focused on uncovering the mechanisms behind miRNA regulation. Latini and colleagues showed a functional role for hsa-let7b-5p in modulating levels of ACE2 and DPP4—two receptors that play an important role in the onset and progression of", "role": "user" }, { "content": "A team of researchers at NYU Abu Dhabi, led by Associate Professor of Biology Youssef Idaghdour and working in collaboration with clinicians at several Abu Dhabi hospitals, investigated the association between microRNAs, a class of small RNA molecules that regulate genes, and COVID-19 severity among 259 unvaccinated COVID-19 patients living in Abu Dhabi. The team identified microRNAs that are associated with a weakened immune response and admission to ICU. During this process, they created the first genomic picture of the architecture of blood microRNAs in unvaccinated COVID-19 patients from the Middle East, North Africa, and South Asia regions whose populations are consistently underrepresented in genomics research. The researchers identified changes in microRNAs at the early stages of infection that are associated with specific blood traits and immune cell death, allowing the virus to evade the immune system and proliferate. The results of the system's genetics study demonstrate that a patient's genetic make-up affects immune function and disease severity, offering new insights into how patient prognosis and treatment can be improved. Given the diversity of the sample, there is promise that these findings can be applied to approximately 30% of the world's population who reside in the MENA region and South Asia. In the study titled \"Systems genetics identifies miRNA‑mediated regulation of host response in COVID‑19,\" published in the journal Human Genomics, the research team presents the results of the analysis of multiple omics datasets—genotypes, miRNA, and mRNA expression of patients at the time of hospital admission, combined with phenotypes from electronic health records. The researchers analyzed 62 clinical variables and expression levels of 632 miRNAs measured at hospital admission, as well as identified 97 miRNAs associated with eight blood phenotypes significantly associated with ICU admission. \"These findings improve our understanding of why some patients withstand COVID-19 better than others,\" said Idaghdour. \"This study demonstrates that microRNAs are promising biomarkers for disease severity, more broadly, and targets for therapeutic interventions. The methods of this study can be applied to other populations to further our understanding of how gene regulation can serve as a core mechanism that impacts COVID-19 and, potentially, severity of other infections.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Background Individuals infected with SARS-CoV-2 vary greatly in their disease severity, ranging from asymptomatic infection to severe disease. The regulation of gene expression is an important mechanism in the host immune response and can modulate the outcome of the disease. miRNAs play important roles in post-transcriptional regulation with consequences on downstream molecular and cellular host immune response processes. The nature and magnitude of miRNA perturbations associated with blood phenotypes and intensive care unit (ICU) admission in COVID-19 are poorly understood. Results We combined multi-omics profiling—genotyping, miRNA and RNA expression, measured at the time of hospital admission soon after the onset of COVID-19 symptoms—with phenotypes from electronic health records to understand how miRNA expression contributes to variation in disease severity in a diverse cohort of 259 unvaccinated patients in Abu Dhabi, United Arab Emirates. We analyzed 62 clinical variables and expression levels of 632 miRNAs measured at admission and identified 97 miRNAs associated with 8 blood phenotypes significantly associated with later ICU admission. Integrative miRNA-mRNA cross-correlation analysis identified multiple miRNA-mRNA-blood endophenotype associations and revealed the effect of miR-143-3p on neutrophil count mediated by the expression of its target gene BCL2. We report 168 significant cis -miRNA expression quantitative trait loci, 57 of which implicate miRNAs associated with either ICU admission or a blood endophenotype. Conclusions This systems genetics study has given rise to a genomic picture of the architecture of whole blood miRNAs in unvaccinated COVID-19 patients and pinpoints post-transcriptional regulation as a potential mechanism that impacts blood traits underlying COVID-19 severity. The results also highlight the impact of host genetic regulatory control of miRNA expression in early stages of COVID-19 disease. Introduction The three years since the emergence of SARS-CoV-2 have brought unprecedented progress in our scientific understanding of the SARS-CoV-2 infection and COVID-19 disease. However, one overarching question remains: why do individuals infected with SARS-CoV-2 vary in their clinical symptomatology, from asymptomatic infection to severe, and oftentimes, lethal disease [ 1 , 2 ]? The answer to this complex question lies in layers of genetic, biological, environmental, and social factors. Previous studies have found that both men and older patients, as well as those with underlying medical conditions such as diabetes, hypertension and obesity are at a higher risk for severe disease, requirement of intensive care and death [ 3 - 6 ]. Studies have also identified a number of blood phenotypes associated with severe disease, including elevated levels of D-dimers, C-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR), Interleukin 6 (IL-6), IL-10, lactate dehydrogenase (LDH), procalcitonin and albumin [ 7 - 14 ]. Neutrophils have been found to play a critical role in the pathophysiology of COVID-19 [ 15 - 17 ], with activation of circulating neutrophils—as observed in transcriptomic data—pinpointed as a predictor of clinical illness in COVID-19 [ 18 , 19 ]. Genetic variation has also been shown to influence COVID-19 susceptibility, severity and clinical outcomes [ 20 , 21 ]. While there has been extensive research to unpack the different sources of variation that influence COVID-19 disease severity, only a few studies to date have focused on the potential roles of human-encoded microRNA (miRNA). miRNAs are a class of small, non-coding RNAs that regulate gene expression by binding to complementary mRNA transcripts to either block translation or mark the target mRNA for degradation [ 22 , 23 ]. miRNAs can regulate both neighboring or distal genes; one miRNA can regulate either one or multiple genes; and multiple miRNAs can target the same gene in either a synergistic or antagonistic manner [ 24 ]. Since regulated miRNA expression is crucial for the differentiation, activation and survival of immune cells [ 25 ], dysregulated miRNA expression can be indicative of aberrant immune function, and has been implicated in numerous diseases including cancers, inflammatory disorders and malaria [ 26 - 28 ]. miRNA expression is also influenced by host genetics, with a few studies describing genetic variation associated with miRNA expression in healthy donors and disease contexts like malaria and cancer [ 29 - 32 ]. Despite the contributions of miRNAs to immune function, our understanding of the roles of miRNAs in response to SARS-CoV-2 is still in its nascency. There are a number of studies (reviewed in Geraylow et al. [ 33 ]) that have identified aberrant miRNA expression during COVID-19 disease progression. Farr and colleagues reported the differential expression of 55 miRNAs between COVID-19 patients during the early stage of disease and healthy donors matched for age and gender [ 34 ]; Fernández-Pato and colleagues identified 200 differentially expressed miRNAs between COVID-19 patients and healthy controls which were also correlated with proinflammatory cytokines such as IL-6, IL-12, IP-10, and TNFɑ [ 35 ]; Pinacchio and colleagues highlighted increased levels of miR-122a and miR-146a in the serum of COVID-19 patients compared to controls, and reported a negative correlation between miR-146a and Interferon alpha-inducible protein 27 (IFI-27) [ 36 ]; de Gonzalo-Calvo et al. identified 10 miRNAs that were dysregulated in hospitalized patients admitted to the intensive care unit (ICU), compared to patients that did not require ICU care, reported correlations between miRNA levels and length of ICU stay, and found that the expression of miR-192-5p and miR-323a-3p differentiated ICU non-survivors from survivors [ 37 ]; Li and colleagues used mendelian randomization to pinpoint two miRNAs (hsa-miR-30a-3p and hsa-miR-139-5p) as potentially causal for COVID-19 severity [ 38 ]; and early in the pandemic, Kim and colleagues identified five miRNAs (hsa-miR-15b-5p, hsa-miR-195-5p, hsa-miR-221-3p, hsa-miR-140-3p, and hsa-miR-422a) predicted to commonly bind the SARS-CoV, MERS-CoV and SARS-CoV-2 viruses, and showed that they were differentially expressed in hamster lung tissues before and after SARS-CoV-2 infection [ 39 ]. Importantly, many of the miRNAs highlighted across these studies were shown to be enriched in inflammatory and antiviral immune response pathways [ 33 ]. Another set of studies have focused on uncovering the mechanisms behind miRNA regulation. Latini and colleagues showed a functional role for hsa-let7b-5p in modulating levels of ACE2 and DPP4—two receptors that play an important role in the onset and progression of<|im_end|> <|im_start|>assistant A team of researchers at NYU Abu Dhabi, led by Associate Professor of Biology Youssef Idaghdour and working in collaboration with clinicians at several Abu Dhabi hospitals, investigated the association between microRNAs, a class of small RNA molecules that regulate genes, and COVID-19 severity among 259 unvaccinated COVID-19 patients living in Abu Dhabi. The team identified microRNAs that are associated with a weakened immune response and admission to ICU. During this process, they created the first genomic picture of the architecture of blood microRNAs in unvaccinated COVID-19 patients from the Middle East, North Africa, and South Asia regions whose populations are consistently underrepresented in genomics research. The researchers identified changes in microRNAs at the early stages of infection that are associated with specific blood traits and immune cell death, allowing the virus to evade the immune system and proliferate. The results of the system's genetics study demonstrate that a patient's genetic make-up affects immune function and disease severity, offering new insights into how patient prognosis and treatment can be improved. Given the diversity of the sample, there is promise that these findings can be applied to approximately 30% of the world's population who reside in the MENA region and South Asia. In the study titled "Systems genetics identifies miRNA‑mediated regulation of host response in COVID‑19," published in the journal Human Genomics, the research team presents the results of the analysis of multiple omics datasets—genotypes, miRNA, and mRNA expression of patients at the time of hospital admission, combined with phenotypes from electronic health records. The researchers analyzed 62 clinical variables and expression levels of 632 miRNAs measured at hospital admission, as well as identified 97 miRNAs associated with eight blood phenotypes significantly associated with ICU admission. "These findings improve our understanding of why some patients withstand COVID-19 better than others," said Idaghdour. "This study demonstrates that microRNAs are promising biomarkers for disease severity, more broadly, and targets for therapeutic interventions. The methods of this study can be applied to other populations to further our understanding of how gene regulation can serve as a core mechanism that impacts COVID-19 and, potentially, severity of other infections." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 25837, 62525, 29374, 449, 328, 17485, 87271, 53, 12, 17, 13592, 19407, 304, 872, 8624, 31020, 11, 24950, 505, 97354, 13795, 19405, 311, 15748, 8624, 13, 578, 19812, 315, 15207, 7645, 374, 459, 3062, 17383, 304, 279, 3552, 22852, 2077, 323, 649, 1491, 6468, 279, 15632, 315, 279, 8624, 13, 9686, 51295, 2170, 1514, 3062, 13073, 304, 1772, 39160, 1479, 278, 19812, 449, 16296, 389, 52452, 31206, 323, 35693, 3552, 22852, 2077, 11618, 13, 578, 7138, 323, 26703, 315, 9686, 31820, 18713, 9225, 811, 5938, 449, 6680, 14345, 22583, 323, 37295, 2512, 5089, 320, 1341, 52, 8, 26360, 304, 20562, 12, 777, 527, 31555, 16365, 13, 18591, 1226, 11093, 7447, 12, 24203, 56186, 2345, 4469, 67247, 11, 9686, 31820, 323, 41214, 7645, 11, 17303, 520, 279, 892, 315, 8952, 26360, 5246, 1306, 279, 42080, 315, 20562, 12, 777, 13803, 81902, 14345, 22583, 505, 14683, 2890, 7576, 311, 3619, 1268, 9686, 31820, 7645, 44072, 311, 23851, 304, 8624, 31020, 304, 264, 17226, 41944, 315, 220, 15537, 653, 85, 4575, 15846, 6978, 304, 31229, 73879, 11, 3723, 10989, 49801, 13, 1226, 30239, 220, 5538, 14830, 7482, 323, 7645, 5990, 315, 220, 20775, 9686, 51295, 2170, 17303, 520, 26360, 323, 11054, 220, 3534, 9686, 51295, 2170, 5938, 449, 220, 23, 6680, 14345, 22583, 12207, 5938, 449, 3010, 85015, 26360, 13, 30101, 1413, 9686, 31820, 1474, 31820, 5425, 46713, 23013, 6492, 11054, 5361, 9686, 31820, 1474, 31820, 94003, 842, 5237, 268, 4249, 30257, 323, 10675, 279, 2515, 315, 9686, 49, 12, 10290, 12, 18, 79, 389, 26878, 22761, 321, 1797, 78926, 555, 279, 7645, 315, 1202, 2218, 15207, 426, 3218, 17, 13, 1226, 1934, 220, 8953, 5199, 67504, 482, 8318, 31820, 7645, 47616, 18027, 1353, 72, 11, 220, 3226, 315, 902, 3242, 49895, 9686, 51295, 2170, 5938, 449, 3060, 85015, 26360, 477, 264, 6680, 842, 5237, 268, 4249, 13, 1221, 24436, 1115, 6067, 56104, 4007, 706, 2728, 10205, 311, 264, 81064, 6945, 315, 279, 18112, 315, 4459, 6680, 9686, 51295, 2170, 304, 653, 85, 4575, 15846, 20562, 12, 777, 6978, 323, 9160, 7862, 1772, 39160, 1479, 278, 19812, 439, 264, 4754, 17383, 430, 25949, 6680, 25022, 16940, 20562, 12, 777, 31020, 13, 578, 3135, 1101, 11415, 279, 5536, 315, 3552, 19465, 23331, 2585, 315, 9686, 31820, 7645, 304, 4216, 18094, 315, 20562, 12, 777, 8624, 13, 29438, 578, 2380, 1667, 2533, 279, 49179, 315, 328, 17485, 87271, 53, 12, 17, 617, 7263, 31069, 5208, 304, 1057, 12624, 8830, 315, 279, 328, 17485, 87271, 53, 12, 17, 19405, 323, 20562, 12, 777, 8624, 13, 4452, 11, 832, 98536, 3488, 8625, 25, 3249, 656, 7931, 29374, 449, 328, 17485, 87271, 53, 12, 17, 13592, 304, 872, 14830, 49648, 75014, 11, 505, 97354, 13795, 19405, 311, 15748, 11, 323, 43146, 92455, 11, 45089, 8624, 510, 220, 16, 1174, 220, 17, 2331, 30, 578, 4320, 311, 420, 6485, 3488, 15812, 304, 13931, 315, 19465, 11, 24156, 11, 12434, 11, 323, 3674, 9547, 13, 30013, 7978, 617, 1766, 430, 2225, 3026, 323, 9191, 6978, 11, 439, 1664, 439, 1884, 449, 16940, 6593, 4787, 1778, 439, 20335, 11, 63308, 323, 33048, 527, 520, 264, 5190, 5326, 369, 15748, 8624, 11, 16686, 315, 37295, 2512, 323, 4648, 510, 220, 18, 482, 220, 21, 21087, 19241, 617, 1101, 11054, 264, 1396, 315, 6680, 14345, 22583, 5938, 449, 15748, 8624, 11, 2737, 32389, 5990, 315, 423, 1773, 68997, 11, 356, 31696, 535, 13128, 320, 9150, 47, 705, 26878, 22761, 321, 4791, 12, 398, 56102, 79759, 11595, 320, 45, 20721, 705, 5783, 273, 3178, 258, 220, 21, 320, 1750, 12, 21, 705, 11598, 12, 605, 11, 51644, 349, 409, 67229, 4469, 521, 320, 12615, 39, 705, 463, 27684, 63537, 258, 323, 8176, 258, 510, 220, 22, 482, 220, 975, 21087, 4275, 332, 22761, 8839, 617, 1027, 1766, 311, 1514, 264, 9200, 3560, 304, 279, 1853, 85404, 31226, 315, 20562, 12, 777, 510, 220, 868, 482, 220, 1114, 10881, 449, 15449, 315, 54828, 26878, 22761, 8839, 60654, 13468, 304, 36815, 3151, 828, 2345, 13576, 2837, 291, 439, 264, 62254, 315, 14830, 17563, 304, 20562, 12, 777, 510, 220, 972, 1174, 220, 777, 21087, 75226, 23851, 706, 1101, 1027, 6982, 311, 10383, 20562, 12, 777, 88636, 11, 31020, 323, 14830, 20124, 510, 220, 508, 1174, 220, 1691, 21087, 6104, 1070, 706, 1027, 16781, 3495, 311, 32165, 279, 2204, 8336, 315, 23851, 430, 10383, 20562, 12, 777, 8624, 31020, 11, 1193, 264, 2478, 7978, 311, 2457, 617, 10968, 389, 279, 4754, 13073, 315, 3823, 93362, 8162, 31820, 320, 8318, 31820, 570, 9686, 51295, 2170, 527, 264, 538, 315, 2678, 11, 2536, 1824, 3785, 46916, 2170, 430, 37377, 15207, 7645, 555, 11212, 311, 58535, 78872, 61412, 311, 3060, 2565, 14807, 477, 1906, 279, 2218, 78872, 369, 53568, 510, 220, 1313, 1174, 220, 1419, 21087, 9686, 51295, 2170, 649, 37377, 2225, 42617, 477, 1612, 278, 21389, 26, 832, 9686, 31820, 649, 37377, 3060, 832, 477, 5361, 21389, 26, 323, 5361, 9686, 51295, 2170, 649, 2218, 279, 1890, 15207, 304, 3060, 264, 80526, 4633, 477, 43215, 4633, 11827, 510, 220, 1187, 21087, 8876, 35319, 9686, 31820, 7645, 374, 16996, 369, 279, 60038, 11, 15449, 323, 20237, 315, 22852, 7917, 510, 220, 914, 10881, 22709, 81722, 9686, 31820, 7645, 649, 387, 64005, 315, 82102, 519, 22852, 734, 11, 323, 706, 1027, 69702, 304, 12387, 19338, 2737, 51423, 11, 47288, 24673, 323, 69263, 510, 220, 1627, 482, 220, 1591, 21087, 9686, 31820, 7645, 374, 1101, 28160, 555, 3552, 56104, 11, 449, 264, 2478, 7978, 23524, 19465, 23851, 5938, 449, 9686, 31820, 7645, 304, 9498, 33149, 323, 8624, 38697, 1093, 69263, 323, 9572, 510, 220, 1682, 482, 220, 843, 21087, 18185, 279, 19564, 315, 9686, 51295, 2170, 311, 22852, 734, 11, 1057, 8830, 315, 279, 13073, 315, 9686, 51295, 2170, 304, 2077, 311, 328, 17485, 87271, 53, 12, 17, 374, 2103, 304, 1202, 308, 5171, 2301, 13, 2684, 527, 264, 1396, 315, 7978, 320, 19981, 291, 304, 20524, 352, 10516, 1880, 453, 13, 510, 220, 1644, 42673, 430, 617, 11054, 82102, 519, 9686, 31820, 7645, 2391, 20562, 12, 777, 8624, 33824, 13, 75006, 323, 18105, 5068, 279, 41264, 7645, 315, 220, 2131, 9686, 51295, 2170, 1990, 20562, 12, 777, 6978, 2391, 279, 4216, 6566, 315, 8624, 323, 9498, 33149, 18545, 369, 4325, 323, 10026, 510, 220, 1958, 13385, 27077, 78146, 9483, 4428, 323, 18105, 11054, 220, 1049, 2204, 34575, 13605, 9686, 51295, 2170, 1990, 20562, 12, 777, 6978, 323, 9498, 11835, 902, 1051, 1101, 49393, 449, 463, 258, 55097, 83185, 1572, 1778, 439, 11598, 12, 21, 11, 11598, 12, 717, 11, 6933, 12, 605, 11, 323, 32023, 37, 133, 239, 510, 220, 1758, 13385, 17929, 582, 53501, 323, 18105, 27463, 7319, 5990, 315, 9686, 49, 12, 8259, 64, 323, 9686, 49, 12, 10465, 64, 304, 279, 41529, 315, 20562, 12, 777, 6978, 7863, 311, 11835, 11, 323, 5068, 264, 8389, 26670, 1990, 9686, 49, 12, 10465, 64, 323, 5783, 809, 263, 8451, 18251, 1791, 1260, 13128, 220, 1544, 320, 35088, 12, 1544, 8, 510, 220, 1927, 13385, 409, 33555, 12812, 76450, 3415, 1880, 453, 13, 11054, 220, 605, 9686, 51295, 2170, 430, 1051, 22709, 81722, 304, 70340, 6978, 16584, 311, 279, 37295, 2512, 5089, 320, 1341, 52, 705, 7863, 311, 6978, 430, 1550, 539, 1397, 85015, 2512, 11, 5068, 69916, 1990, 9686, 31820, 5990, 323, 3160, 315, 85015, 4822, 11, 323, 1766, 430, 279, 7645, 315, 9686, 49, 12, 5926, 12, 20, 79, 323, 9686, 49, 12, 15726, 64, 12, 18, 79, 89142, 85015, 2536, 68806, 85, 86493, 505, 32696, 510, 220, 1806, 13385, 14851, 323, 18105, 1511, 45876, 70664, 4288, 2065, 311, 67638, 1403, 9686, 51295, 2170, 320, 5104, 64, 1474, 72, 49, 12, 966, 64, 12, 18, 79, 323, 305, 9258, 1474, 72, 49, 12, 10125, 12, 20, 79, 8, 439, 13893, 59557, 369, 20562, 12, 777, 31020, 510, 220, 1987, 13385, 323, 4216, 304, 279, 28522, 11, 13818, 323, 18105, 11054, 4330, 9686, 51295, 2170, 320, 5104, 64, 1474, 72, 49, 12, 868, 65, 12, 20, 79, 11, 305, 9258, 1474, 72, 49, 12, 6280, 12, 20, 79, 11, 305, 9258, 1474, 72, 49, 12, 12425, 12, 18, 79, 11, 305, 9258, 1474, 72, 49, 12, 6860, 12, 18, 79, 11, 323, 305, 9258, 1474, 72, 49, 12, 16460, 64, 8, 19698, 311, 17037, 10950, 279, 328, 17485, 87271, 53, 11, 386, 4419, 87271, 53, 323, 328, 17485, 87271, 53, 12, 17, 42068, 11, 323, 8710, 430, 814, 1051, 2204, 34575, 13605, 304, 13824, 3751, 21271, 39881, 1603, 323, 1306, 328, 17485, 87271, 53, 12, 17, 19405, 510, 220, 2137, 21087, 13516, 18007, 11, 1690, 315, 279, 9686, 51295, 2170, 27463, 4028, 1521, 7978, 1051, 6982, 311, 387, 69671, 304, 47288, 323, 3276, 344, 37478, 22852, 2077, 44014, 510, 220, 1644, 21087, 13596, 743, 315, 7978, 617, 10968, 389, 45063, 287, 279, 24717, 4920, 9686, 31820, 19812, 13, 10128, 6729, 323, 18105, 8710, 264, 16003, 3560, 369, 305, 9258, 12, 1169, 22, 65, 12, 20, 79, 304, 1491, 15853, 5990, 315, 41906, 17, 323, 423, 4505, 19, 2345, 20375, 44540, 430, 1514, 459, 3062, 3560, 304, 279, 42080, 323, 33824, 315, 128257, 198, 128256, 78191, 198, 32, 2128, 315, 12074, 520, 12551, 52, 31229, 73879, 11, 6197, 555, 33468, 17054, 315, 40023, 816, 46651, 69, 5336, 351, 16373, 414, 323, 3318, 304, 20632, 449, 78545, 520, 3892, 31229, 73879, 24461, 11, 27313, 279, 15360, 1990, 8162, 51295, 2170, 11, 264, 538, 315, 2678, 41214, 35715, 430, 37377, 21389, 11, 323, 20562, 12, 777, 31020, 4315, 220, 15537, 653, 85, 4575, 15846, 20562, 12, 777, 6978, 5496, 304, 31229, 73879, 13, 578, 2128, 11054, 8162, 51295, 2170, 430, 527, 5938, 449, 264, 58764, 22852, 2077, 323, 26360, 311, 85015, 13, 12220, 420, 1920, 11, 814, 3549, 279, 1176, 81064, 6945, 315, 279, 18112, 315, 6680, 8162, 51295, 2170, 304, 653, 85, 4575, 15846, 20562, 12, 777, 6978, 505, 279, 12877, 6460, 11, 4892, 10384, 11, 323, 4987, 13936, 13918, 6832, 22673, 527, 21356, 1234, 53859, 304, 4173, 24203, 3495, 13, 578, 12074, 11054, 4442, 304, 8162, 51295, 2170, 520, 279, 4216, 18094, 315, 19405, 430, 527, 5938, 449, 3230, 6680, 25022, 323, 22852, 2849, 4648, 11, 10923, 279, 17188, 311, 77753, 279, 22852, 1887, 323, 43036, 349, 13, 578, 3135, 315, 279, 1887, 596, 56104, 4007, 20461, 430, 264, 8893, 596, 19465, 1304, 5352, 22223, 22852, 734, 323, 8624, 31020, 11, 10209, 502, 26793, 1139, 1268, 8893, 95350, 323, 6514, 649, 387, 13241, 13, 16644, 279, 20057, 315, 279, 6205, 11, 1070, 374, 11471, 430, 1521, 14955, 649, 387, 9435, 311, 13489, 220, 966, 4, 315, 279, 1917, 596, 7187, 889, 48383, 304, 279, 69028, 32, 5654, 323, 4987, 13936, 13, 763, 279, 4007, 25891, 330, 49165, 56104, 36611, 9686, 31820, 57064, 4503, 660, 19812, 315, 3552, 2077, 304, 20562, 57064, 777, 1359, 4756, 304, 279, 8486, 11344, 9500, 24203, 11, 279, 3495, 2128, 18911, 279, 3135, 315, 279, 6492, 315, 5361, 8019, 1233, 30525, 2345, 4469, 22583, 11, 9686, 31820, 11, 323, 78872, 7645, 315, 6978, 520, 279, 892, 315, 8952, 26360, 11, 11093, 449, 14345, 22583, 505, 14683, 2890, 7576, 13, 578, 12074, 30239, 220, 5538, 14830, 7482, 323, 7645, 5990, 315, 220, 20775, 9686, 51295, 2170, 17303, 520, 8952, 26360, 11, 439, 1664, 439, 11054, 220, 3534, 9686, 51295, 2170, 5938, 449, 8223, 6680, 14345, 22583, 12207, 5938, 449, 85015, 26360, 13, 330, 9673, 14955, 7417, 1057, 8830, 315, 3249, 1063, 6978, 51571, 20562, 12, 777, 2731, 1109, 3885, 1359, 1071, 5336, 351, 16373, 414, 13, 330, 2028, 4007, 32216, 430, 8162, 51295, 2170, 527, 26455, 39538, 91141, 369, 8624, 31020, 11, 810, 44029, 11, 323, 11811, 369, 37471, 39455, 13, 578, 5528, 315, 420, 4007, 649, 387, 9435, 311, 1023, 22673, 311, 4726, 1057, 8830, 315, 1268, 15207, 19812, 649, 8854, 439, 264, 6332, 17383, 430, 25949, 20562, 12, 777, 323, 11, 13893, 11, 31020, 315, 1023, 30020, 1210, 220, 128257, 198 ]

1,999

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Increasing prevalence and severity of multi-drug-resistant (MDR) bacterial infections has necessitated novel antibacterial strategies. Ideally, new approaches would target bacterial pathogens while exerting selection for reduced pathogenesis when these bacteria inevitably evolve resistance to therapeutic intervention. As an example of such a management strategy, we isolated a lytic bacteriophage, OMKO1, (family Myoviridae ) of Pseudomonas aeruginosa that utilizes the outer membrane porin M (OprM) of the multidrug efflux systems MexAB and MexXY as a receptor-binding site. Results show that phage selection produces an evolutionary trade-off in MDR P. aeruginosa , whereby the evolution of bacterial resistance to phage attack changes the efflux pump mechanism, causing increased sensitivity to drugs from several antibiotic classes. Although modern phage therapy is still in its infancy, we conclude that phages, such as OMKO1, represent a new approach to phage therapy where bacteriophages exert selection for MDR bacteria to become increasingly sensitive to traditional antibiotics. This approach, using phages as targeted antibacterials, could extend the lifetime of our current antibiotics and potentially reduce the incidence of antibiotic resistant infections. Introduction Widespread and inappropriate uses of chemical antibiotics have selected for multi-drug resistant (MDR) bacterial pathogens, presenting more frequently in human infections and contributing significantly to morbidity 1 , 2 , 3 , 4 . Some bacteria even show evolved resistance to ‘drugs of last resort’, resulting in emergent strains that are pan-drug-resistant (PDR) 5 . One example is the Gram-negative bacterium Pseudomonas aeruginosa , a prevalent opportunistic MDR pathogen that is poised to become a common PDR disease problem. Humans readily encounter P. aeruginosa , which thrives in both natural and artificial environments, varying from lakes and estuaries to hospitals and household sink drains 6 . P. aeruginosa causes biofilm-mediated infections, including catheter associated urinary tract infections, ventilator associated pneumonia and infections related to mechanical heart valves, stents, grafts and sutures 7 , 8 . Individuals with cystic fibrosis, severe burns, surgical wounds and/or compromised immunity are particularly at risk for P. aeruginosa infections, especially acquired in hospitals 9 , 10 , 11 . P. aeruginosa infections are notoriously difficult to manage due to low antibiotic permeability of the outer membrane and mechanisms of antibiotic resistance that allow cross resistance to multiple classes and types of antibiotics. Arguably, the most problematic of these mechanisms is antibiotic drug efflux via m ulti-drug e fflu x (Mex) systems, which extrude different antibiotics that permeate the cell. Mex systems contain three components that function via active transport to move numerous molecules, including antibiotics, out of the cell: an antiporter that functions as a transporter (e.g., MexB, MexY), an outer membrane protein that forms a surface-exposed channel (e.g., OprM) and a periplasmic membrane fusion protein that links the two proteins (e.g., MexA, MexX) 12 . Because efflux systems such as MexAB-OprM and MexXY-OprM are able to efflux multiple classes of antibiotics 13 and are major contributors to increased antibiotic resistance 12 , 13 , 14 , 15 , 16 , there is a pressing need to develop alternative methods for the management of antibiotic efflux of MDR P. aeruginosa 17 . One alternative for treating MDR bacterial infections is phage therapy: the use of lytic (virulent) bacteriophages (bacteria-specific viruses) as self-amplifying ‘drugs’ that specifically target and kill bacteria 18 , 19 , 20 . Lytic phages bind to one or more specific receptors on the surfaces of particular bacterial hosts 18 , 20 , 21 , allowing for a targeted approach to treating bacterial infections which predated widespread use of broad-spectrum chemical antibiotics 22 . Due to the recent precipitous rise in antibiotic resistance, phage therapy has seen revitalized interest among Western physicians 23 , buoyed by successful clinical trials demonstrating safety and efficacy 21 , 24 . However, an obvious limitation to phage therapy is the abundant evidence that bacteria readily evolve resistance to phage infection 25 , 26 . While multiple mechanisms of phage resistance exist, phage attachment to a receptor binding-site exerts selection pressure for bacteria to alter or down-regulate expression of the receptor, thereby escaping phage infection 25 . Given the certainty of evolved phage-resistance, modern approaches to phage therapy must acknowledge and capitalize on this inevitability. Genetic trade-offs are often observed in biology, where organisms evolve one trait that improves fitness (a relative advantage in reproduction or survival), while simultaneously suffering reduced performance in another trait 27 , 28 , 29 . Here we propose an evolutionary-based strategy that forces a genetic trade-off: utilize phages that drive MDR bacterial pathogens to evolve increased phage resistance by suffering increased sensitivity to chemical antibiotics. Thus, this approach to phage therapy should be doubly effective; success is achieved when phage lyse the target bacterium and success is also achieved when bacteria evolve phage resistance because they suffer increased sensitivity to antibiotics. We predicted that phage binding to surface-exposed OprM of the MexAB and MexXY systems of MDR P. aeruginosa would exert selection for bacteria to evolve phage resistance, while impairing the relative effectiveness of these efflux pumps to extrude chemical antibiotics. We obtained samples from six natural sources (sewage, soil, lakes, rivers, streams, compost) and enriched for phages that could infect P. aeruginosa strains PA01 and PA14, two widely used MDR P. aeruginosa models 30 , 31 , 32 , 33 . This effort yielded 42 naturally isolated phages that successfully infected both strains of MDR P. aeruginosa . To test if any of these phages could bind to OprM of MexAB and MexXY efflux systems, we used a transposon knockout collection of bacterial mutants derived from P. aeruginosa strain PA01 34 . These assays determined which bacterial mutants failed to support phage infection, because such mutants lacked the surface-expressed protein necessary for phage infection. The assays measured the efficiency of plating (EOP), defined as the ratio of phage titer (plaque-forming units [pfu] per mL) on the knockout host relative to titer on the unaltered PA01 host. EOP ≈ 1.0 would indicate that the protein associated with the knocked out gene was irrelevant for phage binding,", "role": "user" }, { "content": "Yale researchers were fishing for a new weapon against antibiotic resistance and found one floating in a Connecticut pond, they report May 26 in the journal Scientific Reports. The virus called a bacteriophage, found in Dodge Pond in East Lyme, attacks a common multi-drug resistant bacterial pathogen called Pseudomonas aeruginosa, which can lethally infect people with compromised immune systems. In a neat evolutionary trick, the virus attaches to the cell membrane where bacteria pump out antibiotics, a system that had originally evolved to resist antibiotics. The presence of the virus in turn leads to evolutionary changes in the bacterial membrane that makes this pumping mechanism less efficient. This makes bacteria once more susceptible to existing antibiotics. \"We have been looking for natural products that are useful in combating important pathogens,\" said Paul Turner, professor and chair of the Department of Ecology and Evolutionary Biology. \"What's neat about this virus is it binds to something the organism needs to become pathogenic, and backs it into an evolutionary corner such that it becomes more sensitive to currently failing antibiotics.\" The virus should help preserve our limited antibiotic arsenal in combating deadly bacteria, he said. This \"phage\" therapy could be used in conjunction with antibiotics to treat dangerous P. aeruginosa infections that afflict patients with severe burns, surgical wounds, cystic fibrosis, and other conditions that compromise the immune system. Turner also noted that other phages hold promise to combat bacterial pathogens that cause economic losses in plant and animal agriculture, and those that contaminate pipes and equipment such as bioreactors in food manufacturing.. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Increasing prevalence and severity of multi-drug-resistant (MDR) bacterial infections has necessitated novel antibacterial strategies. Ideally, new approaches would target bacterial pathogens while exerting selection for reduced pathogenesis when these bacteria inevitably evolve resistance to therapeutic intervention. As an example of such a management strategy, we isolated a lytic bacteriophage, OMKO1, (family Myoviridae ) of Pseudomonas aeruginosa that utilizes the outer membrane porin M (OprM) of the multidrug efflux systems MexAB and MexXY as a receptor-binding site. Results show that phage selection produces an evolutionary trade-off in MDR P. aeruginosa , whereby the evolution of bacterial resistance to phage attack changes the efflux pump mechanism, causing increased sensitivity to drugs from several antibiotic classes. Although modern phage therapy is still in its infancy, we conclude that phages, such as OMKO1, represent a new approach to phage therapy where bacteriophages exert selection for MDR bacteria to become increasingly sensitive to traditional antibiotics. This approach, using phages as targeted antibacterials, could extend the lifetime of our current antibiotics and potentially reduce the incidence of antibiotic resistant infections. Introduction Widespread and inappropriate uses of chemical antibiotics have selected for multi-drug resistant (MDR) bacterial pathogens, presenting more frequently in human infections and contributing significantly to morbidity 1 , 2 , 3 , 4 . Some bacteria even show evolved resistance to ‘drugs of last resort’, resulting in emergent strains that are pan-drug-resistant (PDR) 5 . One example is the Gram-negative bacterium Pseudomonas aeruginosa , a prevalent opportunistic MDR pathogen that is poised to become a common PDR disease problem. Humans readily encounter P. aeruginosa , which thrives in both natural and artificial environments, varying from lakes and estuaries to hospitals and household sink drains 6 . P. aeruginosa causes biofilm-mediated infections, including catheter associated urinary tract infections, ventilator associated pneumonia and infections related to mechanical heart valves, stents, grafts and sutures 7 , 8 . Individuals with cystic fibrosis, severe burns, surgical wounds and/or compromised immunity are particularly at risk for P. aeruginosa infections, especially acquired in hospitals 9 , 10 , 11 . P. aeruginosa infections are notoriously difficult to manage due to low antibiotic permeability of the outer membrane and mechanisms of antibiotic resistance that allow cross resistance to multiple classes and types of antibiotics. Arguably, the most problematic of these mechanisms is antibiotic drug efflux via m ulti-drug e fflu x (Mex) systems, which extrude different antibiotics that permeate the cell. Mex systems contain three components that function via active transport to move numerous molecules, including antibiotics, out of the cell: an antiporter that functions as a transporter (e.g., MexB, MexY), an outer membrane protein that forms a surface-exposed channel (e.g., OprM) and a periplasmic membrane fusion protein that links the two proteins (e.g., MexA, MexX) 12 . Because efflux systems such as MexAB-OprM and MexXY-OprM are able to efflux multiple classes of antibiotics 13 and are major contributors to increased antibiotic resistance 12 , 13 , 14 , 15 , 16 , there is a pressing need to develop alternative methods for the management of antibiotic efflux of MDR P. aeruginosa 17 . One alternative for treating MDR bacterial infections is phage therapy: the use of lytic (virulent) bacteriophages (bacteria-specific viruses) as self-amplifying ‘drugs’ that specifically target and kill bacteria 18 , 19 , 20 . Lytic phages bind to one or more specific receptors on the surfaces of particular bacterial hosts 18 , 20 , 21 , allowing for a targeted approach to treating bacterial infections which predated widespread use of broad-spectrum chemical antibiotics 22 . Due to the recent precipitous rise in antibiotic resistance, phage therapy has seen revitalized interest among Western physicians 23 , buoyed by successful clinical trials demonstrating safety and efficacy 21 , 24 . However, an obvious limitation to phage therapy is the abundant evidence that bacteria readily evolve resistance to phage infection 25 , 26 . While multiple mechanisms of phage resistance exist, phage attachment to a receptor binding-site exerts selection pressure for bacteria to alter or down-regulate expression of the receptor, thereby escaping phage infection 25 . Given the certainty of evolved phage-resistance, modern approaches to phage therapy must acknowledge and capitalize on this inevitability. Genetic trade-offs are often observed in biology, where organisms evolve one trait that improves fitness (a relative advantage in reproduction or survival), while simultaneously suffering reduced performance in another trait 27 , 28 , 29 . Here we propose an evolutionary-based strategy that forces a genetic trade-off: utilize phages that drive MDR bacterial pathogens to evolve increased phage resistance by suffering increased sensitivity to chemical antibiotics. Thus, this approach to phage therapy should be doubly effective; success is achieved when phage lyse the target bacterium and success is also achieved when bacteria evolve phage resistance because they suffer increased sensitivity to antibiotics. We predicted that phage binding to surface-exposed OprM of the MexAB and MexXY systems of MDR P. aeruginosa would exert selection for bacteria to evolve phage resistance, while impairing the relative effectiveness of these efflux pumps to extrude chemical antibiotics. We obtained samples from six natural sources (sewage, soil, lakes, rivers, streams, compost) and enriched for phages that could infect P. aeruginosa strains PA01 and PA14, two widely used MDR P. aeruginosa models 30 , 31 , 32 , 33 . This effort yielded 42 naturally isolated phages that successfully infected both strains of MDR P. aeruginosa . To test if any of these phages could bind to OprM of MexAB and MexXY efflux systems, we used a transposon knockout collection of bacterial mutants derived from P. aeruginosa strain PA01 34 . These assays determined which bacterial mutants failed to support phage infection, because such mutants lacked the surface-expressed protein necessary for phage infection. The assays measured the efficiency of plating (EOP), defined as the ratio of phage titer (plaque-forming units [pfu] per mL) on the knockout host relative to titer on the unaltered PA01 host. EOP ≈ 1.0 would indicate that the protein associated with the knocked out gene was irrelevant for phage binding,<|im_end|> <|im_start|>assistant Yale researchers were fishing for a new weapon against antibiotic resistance and found one floating in a Connecticut pond, they report May 26 in the journal Scientific Reports. The virus called a bacteriophage, found in Dodge Pond in East Lyme, attacks a common multi-drug resistant bacterial pathogen called Pseudomonas aeruginosa, which can lethally infect people with compromised immune systems. In a neat evolutionary trick, the virus attaches to the cell membrane where bacteria pump out antibiotics, a system that had originally evolved to resist antibiotics. The presence of the virus in turn leads to evolutionary changes in the bacterial membrane that makes this pumping mechanism less efficient. This makes bacteria once more susceptible to existing antibiotics. "We have been looking for natural products that are useful in combating important pathogens," said Paul Turner, professor and chair of the Department of Ecology and Evolutionary Biology. "What's neat about this virus is it binds to something the organism needs to become pathogenic, and backs it into an evolutionary corner such that it becomes more sensitive to currently failing antibiotics." The virus should help preserve our limited antibiotic arsenal in combating deadly bacteria, he said. This "phage" therapy could be used in conjunction with antibiotics to treat dangerous P. aeruginosa infections that afflict patients with severe burns, surgical wounds, cystic fibrosis, and other conditions that compromise the immune system. Turner also noted that other phages hold promise to combat bacterial pathogens that cause economic losses in plant and animal agriculture, and those that contaminate pipes and equipment such as bioreactors in food manufacturing.. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 74540, 38009, 323, 31020, 315, 7447, 19158, 773, 47056, 320, 6204, 49, 8, 45964, 30020, 706, 4541, 33337, 11775, 21196, 71034, 15174, 13, 67801, 11, 502, 20414, 1053, 2218, 45964, 78284, 1418, 43844, 287, 6727, 369, 11293, 1853, 52379, 994, 1521, 24032, 40605, 38680, 13957, 311, 37471, 21623, 13, 1666, 459, 3187, 315, 1778, 264, 6373, 8446, 11, 584, 25181, 264, 14869, 29150, 17854, 72, 99054, 11, 507, 45240, 46, 16, 11, 320, 19521, 3092, 869, 404, 114405, 883, 315, 393, 40512, 35685, 300, 34548, 3715, 12252, 430, 60880, 279, 16335, 39654, 4247, 258, 386, 320, 46, 652, 44, 8, 315, 279, 64486, 73047, 3369, 63959, 6067, 9553, 1905, 323, 9553, 16760, 439, 264, 35268, 65500, 2816, 13, 18591, 1501, 430, 1343, 425, 6727, 19159, 459, 41993, 6696, 12744, 304, 386, 7842, 393, 13, 34548, 3715, 12252, 1174, 49001, 279, 15740, 315, 45964, 13957, 311, 1343, 425, 3440, 4442, 279, 3369, 63959, 14155, 17383, 11, 14718, 7319, 27541, 311, 11217, 505, 3892, 60595, 6989, 13, 10541, 6617, 1343, 425, 15419, 374, 2103, 304, 1202, 86617, 11, 584, 32194, 430, 1343, 1154, 11, 1778, 439, 507, 45240, 46, 16, 11, 4097, 264, 502, 5603, 311, 1343, 425, 15419, 1405, 17854, 72, 5237, 1154, 43844, 6727, 369, 386, 7842, 24032, 311, 3719, 15098, 16614, 311, 8776, 46850, 13, 1115, 5603, 11, 1701, 1343, 1154, 439, 17550, 21196, 2540, 10522, 11, 1436, 13334, 279, 19569, 315, 1057, 1510, 46850, 323, 13893, 8108, 279, 39775, 315, 60595, 31785, 30020, 13, 29438, 468, 3422, 21376, 323, 33781, 5829, 315, 11742, 46850, 617, 4183, 369, 7447, 19158, 773, 31785, 320, 6204, 49, 8, 45964, 78284, 11, 32644, 810, 14134, 304, 3823, 30020, 323, 29820, 12207, 311, 93144, 19025, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 662, 4427, 24032, 1524, 1501, 28995, 13957, 311, 3451, 3696, 13602, 315, 1566, 22541, 20182, 13239, 304, 7425, 306, 42400, 430, 527, 7363, 19158, 773, 47056, 320, 47, 7842, 8, 220, 20, 662, 3861, 3187, 374, 279, 29937, 62035, 17854, 2411, 393, 40512, 35685, 300, 34548, 3715, 12252, 1174, 264, 46941, 86954, 4633, 386, 7842, 1853, 11968, 430, 374, 54946, 311, 3719, 264, 4279, 393, 7842, 8624, 3575, 13, 66094, 31368, 13123, 393, 13, 34548, 3715, 12252, 1174, 902, 8983, 1924, 304, 2225, 5933, 323, 21075, 22484, 11, 29865, 505, 44236, 323, 1826, 84, 5548, 311, 24461, 323, 14048, 19868, 79750, 220, 21, 662, 393, 13, 34548, 3715, 12252, 11384, 17332, 31255, 82076, 30020, 11, 2737, 31747, 1430, 5938, 72735, 42929, 30020, 11, 71702, 859, 5938, 69329, 323, 30020, 5552, 311, 22936, 4851, 64100, 11, 357, 812, 11, 69413, 82, 323, 35312, 1439, 220, 22, 1174, 220, 23, 662, 62525, 449, 63581, 292, 16178, 63412, 11, 15748, 44154, 11, 34933, 34254, 323, 5255, 44500, 40368, 527, 8104, 520, 5326, 369, 393, 13, 34548, 3715, 12252, 30020, 11, 5423, 19426, 304, 24461, 220, 24, 1174, 220, 605, 1174, 220, 806, 662, 393, 13, 34548, 3715, 12252, 30020, 527, 73835, 5107, 311, 10299, 4245, 311, 3428, 60595, 55424, 2968, 315, 279, 16335, 39654, 323, 24717, 315, 60595, 13957, 430, 2187, 5425, 13957, 311, 5361, 6989, 323, 4595, 315, 46850, 13, 7793, 32764, 11, 279, 1455, 36033, 315, 1521, 24717, 374, 60595, 5623, 3369, 63959, 4669, 296, 220, 7213, 19158, 773, 384, 282, 27256, 865, 320, 52665, 8, 6067, 11, 902, 11741, 799, 2204, 46850, 430, 55424, 349, 279, 2849, 13, 9553, 6067, 6782, 2380, 6956, 430, 734, 4669, 4642, 7710, 311, 3351, 12387, 35715, 11, 2737, 46850, 11, 704, 315, 279, 2849, 25, 459, 7294, 90332, 430, 5865, 439, 264, 73565, 320, 68, 1326, 2637, 9553, 33, 11, 9553, 56, 705, 459, 16335, 39654, 13128, 430, 7739, 264, 7479, 10397, 3950, 5613, 320, 68, 1326, 2637, 78618, 44, 8, 323, 264, 824, 10567, 10753, 292, 39654, 37608, 13128, 430, 7902, 279, 1403, 28896, 320, 68, 1326, 2637, 9553, 32, 11, 9553, 55, 8, 220, 717, 662, 9393, 3369, 63959, 6067, 1778, 439, 9553, 1905, 24540, 652, 44, 323, 9553, 16760, 24540, 652, 44, 527, 3025, 311, 3369, 63959, 5361, 6989, 315, 46850, 220, 1032, 323, 527, 3682, 20965, 311, 7319, 60595, 13957, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 1070, 374, 264, 26422, 1205, 311, 2274, 10778, 5528, 369, 279, 6373, 315, 60595, 3369, 63959, 315, 386, 7842, 393, 13, 34548, 3715, 12252, 220, 1114, 662, 3861, 10778, 369, 27723, 386, 7842, 45964, 30020, 374, 1343, 425, 15419, 25, 279, 1005, 315, 14869, 29150, 320, 46957, 29580, 8, 17854, 72, 5237, 1154, 320, 65, 78852, 19440, 42068, 8, 439, 659, 33317, 501, 7922, 3451, 3696, 13602, 529, 430, 11951, 2218, 323, 5622, 24032, 220, 972, 1174, 220, 777, 1174, 220, 508, 662, 16333, 29150, 1343, 1154, 10950, 311, 832, 477, 810, 3230, 44540, 389, 279, 27529, 315, 4040, 45964, 18939, 220, 972, 1174, 220, 508, 1174, 220, 1691, 1174, 10923, 369, 264, 17550, 5603, 311, 27723, 45964, 30020, 902, 864, 3661, 24716, 1005, 315, 7353, 1355, 39806, 11742, 46850, 220, 1313, 662, 24586, 311, 279, 3293, 36841, 50855, 10205, 304, 60595, 13957, 11, 1343, 425, 15419, 706, 3970, 79955, 1534, 2802, 4315, 11104, 35944, 220, 1419, 1174, 75720, 291, 555, 6992, 14830, 19622, 45296, 7296, 323, 41265, 220, 1691, 1174, 220, 1187, 662, 4452, 11, 459, 8196, 20893, 311, 1343, 425, 15419, 374, 279, 44611, 6029, 430, 24032, 31368, 38680, 13957, 311, 1343, 425, 19405, 220, 914, 1174, 220, 1627, 662, 6104, 5361, 24717, 315, 1343, 425, 13957, 3073, 11, 1343, 425, 20581, 311, 264, 35268, 11212, 29654, 506, 15916, 6727, 7410, 369, 24032, 311, 11857, 477, 1523, 33263, 6468, 7645, 315, 279, 35268, 11, 28592, 53754, 1343, 425, 19405, 220, 914, 662, 16644, 279, 44743, 315, 28995, 1343, 425, 11849, 4011, 11, 6617, 20414, 311, 1343, 425, 15419, 2011, 25670, 323, 53825, 389, 420, 21314, 275, 2968, 13, 75226, 6696, 65039, 527, 3629, 13468, 304, 34458, 11, 1405, 44304, 38680, 832, 18027, 430, 36050, 17479, 320, 64, 8844, 9610, 304, 39656, 477, 20237, 705, 1418, 25291, 16066, 11293, 5178, 304, 2500, 18027, 220, 1544, 1174, 220, 1591, 1174, 220, 1682, 662, 5810, 584, 30714, 459, 41993, 6108, 8446, 430, 8603, 264, 19465, 6696, 12744, 25, 29166, 1343, 1154, 430, 6678, 386, 7842, 45964, 78284, 311, 38680, 7319, 1343, 425, 13957, 555, 16066, 7319, 27541, 311, 11742, 46850, 13, 14636, 11, 420, 5603, 311, 1343, 425, 15419, 1288, 387, 94989, 7524, 26, 2450, 374, 17427, 994, 1343, 425, 14869, 325, 279, 2218, 17854, 2411, 323, 2450, 374, 1101, 17427, 994, 24032, 38680, 1343, 425, 13957, 1606, 814, 7831, 7319, 27541, 311, 46850, 13, 1226, 19698, 430, 1343, 425, 11212, 311, 7479, 10397, 3950, 78618, 44, 315, 279, 9553, 1905, 323, 9553, 16760, 6067, 315, 386, 7842, 393, 13, 34548, 3715, 12252, 1053, 43844, 6727, 369, 24032, 311, 38680, 1343, 425, 13957, 11, 1418, 38974, 287, 279, 8844, 27375, 315, 1521, 3369, 63959, 43875, 311, 11741, 799, 11742, 46850, 13, 1226, 12457, 10688, 505, 4848, 5933, 8336, 320, 325, 86, 425, 11, 17614, 11, 44236, 11, 36617, 11, 23914, 11, 57823, 8, 323, 69671, 369, 1343, 1154, 430, 1436, 34527, 393, 13, 34548, 3715, 12252, 42400, 13174, 1721, 323, 13174, 975, 11, 1403, 13882, 1511, 386, 7842, 393, 13, 34548, 3715, 12252, 4211, 220, 966, 1174, 220, 2148, 1174, 220, 843, 1174, 220, 1644, 662, 1115, 5149, 58487, 220, 2983, 18182, 25181, 1343, 1154, 430, 7946, 29374, 2225, 42400, 315, 386, 7842, 393, 13, 34548, 3715, 12252, 662, 2057, 1296, 422, 904, 315, 1521, 1343, 1154, 1436, 10950, 311, 78618, 44, 315, 9553, 1905, 323, 9553, 16760, 3369, 63959, 6067, 11, 584, 1511, 264, 1380, 981, 263, 77173, 4526, 315, 45964, 88754, 14592, 505, 393, 13, 34548, 3715, 12252, 26800, 13174, 1721, 220, 1958, 662, 4314, 99592, 11075, 902, 45964, 88754, 4745, 311, 1862, 1343, 425, 19405, 11, 1606, 1778, 88754, 49101, 279, 7479, 10397, 14655, 13128, 5995, 369, 1343, 425, 19405, 13, 578, 99592, 17303, 279, 15374, 315, 628, 1113, 320, 36, 3143, 705, 4613, 439, 279, 11595, 315, 1343, 425, 259, 2058, 320, 501, 20234, 8627, 287, 8316, 510, 16276, 84, 60, 824, 65170, 8, 389, 279, 77173, 3552, 8844, 311, 259, 2058, 389, 279, 653, 278, 34259, 13174, 1721, 3552, 13, 469, 3143, 118792, 220, 16, 13, 15, 1053, 13519, 430, 279, 13128, 5938, 449, 279, 33085, 704, 15207, 574, 40815, 369, 1343, 425, 11212, 11, 128257, 198, 128256, 78191, 198, 56, 1604, 12074, 1051, 20543, 369, 264, 502, 10500, 2403, 60595, 13957, 323, 1766, 832, 19596, 304, 264, 31461, 36670, 11, 814, 1934, 3297, 220, 1627, 304, 279, 8486, 38130, 29140, 13, 578, 17188, 2663, 264, 17854, 72, 99054, 11, 1766, 304, 43981, 71965, 304, 6460, 94216, 11, 8951, 264, 4279, 7447, 19158, 773, 31785, 45964, 1853, 11968, 2663, 393, 40512, 35685, 300, 34548, 3715, 12252, 11, 902, 649, 98522, 750, 34527, 1274, 449, 44500, 22852, 6067, 13, 763, 264, 29585, 41993, 14397, 11, 279, 17188, 85603, 311, 279, 2849, 39654, 1405, 24032, 14155, 704, 46850, 11, 264, 1887, 430, 1047, 13517, 28995, 311, 22884, 46850, 13, 578, 9546, 315, 279, 17188, 304, 2543, 11767, 311, 41993, 4442, 304, 279, 45964, 39654, 430, 3727, 420, 53226, 17383, 2753, 11297, 13, 1115, 3727, 24032, 3131, 810, 47281, 311, 6484, 46850, 13, 330, 1687, 617, 1027, 3411, 369, 5933, 3956, 430, 527, 5505, 304, 96178, 3062, 78284, 1359, 1071, 7043, 34131, 11, 14561, 323, 10716, 315, 279, 6011, 315, 78375, 323, 38321, 661, 40023, 13, 330, 3923, 596, 29585, 922, 420, 17188, 374, 433, 58585, 311, 2555, 279, 47120, 3966, 311, 3719, 1853, 29569, 11, 323, 28678, 433, 1139, 459, 41993, 9309, 1778, 430, 433, 9221, 810, 16614, 311, 5131, 22109, 46850, 1210, 578, 17188, 1288, 1520, 21813, 1057, 7347, 60595, 58031, 304, 96178, 25114, 24032, 11, 568, 1071, 13, 1115, 330, 764, 425, 1, 15419, 1436, 387, 1511, 304, 32546, 449, 46850, 311, 4322, 11660, 393, 13, 34548, 3715, 12252, 30020, 430, 95623, 6978, 449, 15748, 44154, 11, 34933, 34254, 11, 63581, 292, 16178, 63412, 11, 323, 1023, 4787, 430, 30485, 279, 22852, 1887, 13, 34131, 1101, 10555, 430, 1023, 1343, 1154, 3412, 11471, 311, 12896, 45964, 78284, 430, 5353, 7100, 18151, 304, 6136, 323, 10065, 30029, 11, 323, 1884, 430, 687, 309, 3357, 32275, 323, 7241, 1778, 439, 6160, 461, 21846, 304, 3691, 15266, 497, 220, 128257, 198 ]

1,744

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Photoreceptor loss is the final common endpoint in most retinopathies that lead to irreversible blindness, and there are no effective treatments to restore vision 1 , 2 . Chemical reprogramming of fibroblasts offers an opportunity to reverse vision loss; however, the generation of sensory neuronal subtypes such as photoreceptors remains a challenge. Here we report that the administration of a set of five small molecules can chemically induce the transformation of fibroblasts into rod photoreceptor-like cells. The transplantation of these chemically induced photoreceptor-like cells (CiPCs) into the subretinal space of rod degeneration mice (homozygous for rd1 , also known as Pde6b ) leads to partial restoration of the pupil reflex and visual function. We show that mitonuclear communication is a key determining factor for the reprogramming of fibroblasts into CiPCs. Specifically, treatment with these five compounds leads to the translocation of AXIN2 to the mitochondria, which results in the production of reactive oxygen species, the activation of NF-κB and the upregulation of Ascl1 . We anticipate that CiPCs could have therapeutic potential for restoring vision. Main Many retinopathies—such as age-related macular degeneration, diabetic retinopathy and retinitis pigmentosa—ultimately result in the loss of retinal neurons, which leads to irreversible vision loss 1 , 2 . Stem-cell therapy, using embryonic stem cells or induced pluripotent stem cells, is a promising strategy to replace lost retinal cells and improve vision 3 , 4 . However, protocols for the derivation of candidate replacement cells are cumbersome and time consuming, presenting a challenge for their use in clinical therapy 5 , 6 , 7 , 8 . Direct reprogramming—using ectopic transcription factors and chemicals—bypasses the requirement for pluripotent cells and has resulted in the generation of neurons, astrocytes and cardiomyocytes; however, the pharmacological conversion of photoreceptors using this method has not been realized 9 , 10 , 11 , 12 , 13 . ASCL1, a powerful proneural transcription factor, has been reported to reprogram glial cells into photoreceptors 14 , 15 , 16 . An improved mechanistic understanding of direct reprogramming may lead to the generation of new cell types. Here we identify a set of five small molecules that can induce fibroblasts to become functional CiPCs without the need for pluripotent cells or viral transcription factors. We demonstrate that CiPCs restore pupil reflex and vision when transplanted into the subretinal space of rd1 mice, a mouse model of retinal degeneration. Moreover, our mechanistic analysis reveals an AXIN2–NF-κB–ASCL1 pathway that promotes retinal lineage during reprogramming and identifies mitochondria as a signalling hub in the orchestration of cell fate conversion. A set of five compounds transforms fibroblasts to CiPCs To generate CiPCs, we used mouse embryonic fibroblasts (MEFs) derived from a transgenic Nrl –GFP mouse, in which the Nrl promoter drives expression of eGFP specifically in rod photoreceptors 17 , 18 . We began by testing an established combination of four small molecules—valproic acid (V), CHIR99021 (a GSK3 inhibitor) (C), RepSox (R) and forskolin (F), together denoted VCRF—that is known to convert fibroblasts into neurons, but only a few of the resultant cells were Nrl –GFP positive 12 . Various small molecules and culture conditions were attempted (Supplementary Table 5 ), and we found that the Wnt/β-catenin pathway inhibitor IWR1 (I)—in combination with VCRF and STR (Sonic hedgehog, taurine and retinoic acid)—was able to substantially improve the efficiency of conversion of MEFs into Nrl –GFP + cells (Fig. 1a, b ). STR was added on day 8 of reprogramming, to promote and support the formation of photoreceptors after photoreceptor-specifying transcription factors—such as RORβ, ASCL1, PIAS3—were upregulated 14 , 19 , 20 , 21 , 22 (Fig. 1l , Supplementary Tables 1 , 2 ). Similarly, human adult dermal fibroblasts (HADF), and human fetal lung fibroblasts transduced with a Nrl– DsRed reporter, were also converted into CiPCs (Fig. 1f–h, j , Extended Data Fig. 1a, b , Supplementary Fig. 2 , Supplementary Table 6 ). We next tested the small molecules individually and in various combinations, and observed that they failed to generate as many Nrl –GFP + cells (Extended Data Fig. 1c, d ). We conclude that all five compounds in combination can efficiently convert fibroblasts into NRL - expressing CiPCs. Fig. 1: Conversion of fibroblasts and the molecular characterization of CiPCs. a , Protocol for the reprogramming of mouse fibroblasts into CiPCs. MC, medium change; PIM, photoreceptor induction medium; PDM, photoreceptor differentiation medium. b , Images of CiPCs expressing Nrl –GFP on day 11 and day 16. Scale bars 14.4 μm c , Images of CiPCs expressing CRX on day 11. Scale bars 14.4 μm d , FACS purification of reprogrammed Nrl –GFP + CiPCs (0.2%). e , PCR with reverse transcription reveals the expression of the indicated photoreceptor-specific genes in mouse. For gel source data, see Supplementary Fig. 2a, b . f , Protocol for the reprogramming of HADFs into CiPCs. g , Quantitative PCR (qPCR) analysis (fold change compared with HADF) CiPCs after reprogramming from HADF, showing increased expression of photoreceptor-specific genes. Data are presented as mean ± s.e.m. of n = 3 independently treated biological replicates. h , Micrograph of NRL-stained CiPCs after conversion from HADF. Scale bars 33 μm i , Principal component analysis for all RNA-seq samples ( n = 3 samples for each). j , Images of CiPCs after conversion from HADF at day 10. Rcvrn, recoverin; Rho, rhodopsin.Scale bars 14.4 μm k , Heat map of RNA-seq data for the indicated photoreceptor genes. RI, reprogramming intermediate. l , Heat map of RNA-seq data for the expression of the indicated genes that express retinal transcription factors during CiPC conversion. Experiments in b , h , i were repeated three times with similar results and the experiments in c , d , were repeated twice with similar results. CPM, counts per million. Source Data Full size image Next, Nrl –GFP + CiPCs were purified by fluorescence-activated cell sorting (FACS) and subject to transcriptomic analysis, which revealed the expression of early retinal neuronal markers (CHX10 and OTX2) and photoreceptor markers", "role": "user" }, { "content": "Researchers have discovered a technique for directly reprogramming skin cells into light-sensing rod photoreceptors used for vision. The lab-made rods enabled blind mice to detect light after the cells were transplanted into the animals' eyes. The work, funded by the National Eye Institute (NEI), published April 15 in Nature. Up until now, researchers have replaced dying photoreceptors in animal models by creating stem cells from skin or blood cells, programming those stem cells to become photoreceptors, which are then transplanted into the back of the eye. In the new study, scientists show that it is possible to skip the stem-cell intermediary step and directly reprogram skins cells into photoreceptors for transplantation into the retina. \"This is the first study to show that direct, chemical reprogramming can produce retinal-like cells, which gives us a new and faster strategy for developing therapies for age-related macular degeneration and other retinal disorders caused by the loss of photoreceptors,\" said Anand Swaroop, Ph.D., senior investigator in the NEI Neurobiology, Neurodegeneration, and Repair Laboratory, which characterized the reprogrammed rod photoreceptor cells by gene expression analysis. \"Of immediate benefit will be the ability to quickly develop disease models so we can study mechanisms of disease. The new strategy will also help us design better cell replacement approaches,\" he said. Scientists have studied induced pluripotent stem (iPS) cells with intense interest over the past decade. IPSCs are developed in a lab from adult cells —rather than fetal tissue— and can be used to make nearly any type of replacement cell or tissue. But iPS cell reprogramming protocols can take six months before cells or tissues are ready for transplantation. By contrast, the direct reprogramming described in the current study coaxed skin cells into functional photoreceptors ready for transplantation in only 10 days. The researchers demonstrated their technique in mouse eyes, using both mouse- and human-derived skin cells. \"Our technique goes directly from skin cell to photoreceptor without the need for stem cells in between,\" said the study's lead investigator, Sai Chavala, M.D., CEO and president of CIRC Therapeutics and the Center for Retina Innovation. Chavala is also director of retina services at KE Eye Centers of Texas and a professor of surgery at Texas Christian University and University of North Texas Health Science Center (UNTHSC) School of Medicine, Fort Worth. Direct reprogramming involves bathing the skin cells in a cocktail of five small molecule compounds that together chemically mediate the molecular pathways relevant for rod photoreceptor cell fate. The result are rod photoreceptors that mimic native rods in appearance and function. The researchers performed gene expression profiling, which showed that the genes expressed by the new cells were similar to those expressed by real rod photoreceptors. At the same time, genes relevant to skin cell function had been downregulated. The researchers transplanted the cells into mice with retinal degeneration and then tested their pupillary reflexes, which is a measure of photoreceptor function after transplantation. Under low-light conditions, constriction of the pupil is dependent on rod photoreceptor function. Within a month of transplantation, six of 14 (43%) animals showed robust pupil constriction under low light compared to none of the untreated controls. Moreover, treated mice with pupil constriction were significantly more likely to seek out and spend time in dark spaces compared with treated mice with no pupil response and untreated controls. Preference for dark spaces is a behavior that requires vision and reflects the mouse's natural tendency to seek out safe, dark locations as opposed to light ones. \"Even mice with severely advanced retinal degeneration, with little chance of having living photoreceptors remaining, responded to transplantation. Such findings suggest that the observed improvements were due to the lab-made photoreceptors rather than to an ancillary effect that supported the health of the host's existing photoreceptors,\" said the study's first author Biraj Mahato, Ph.D., research scientist, UNTHSC. Three months after transplantation, immunofluorescence studies confirmed the survival of the lab-made photoreceptors, as well as their synaptic connections to neurons in the inner retina. Further research is needed to optimize the protocol to increase the number of functional transplanted photoreceptors. \"Importantly, the researchers worked out how this direct reprogramming is mediated at the cellular level. These insights will help researchers apply the technique not only to the retina, but to many other cell types,\" Swaroop said. \"If efficiency of this direct conversion can be improved, this may significantly reduce the time it takes to develop a potential cell therapy product or disease model,\" said Kapil Bharti, Ph.D., senior investigator and head of the Ocular and Stem Cell Translational Research Section at NEI. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Photoreceptor loss is the final common endpoint in most retinopathies that lead to irreversible blindness, and there are no effective treatments to restore vision 1 , 2 . Chemical reprogramming of fibroblasts offers an opportunity to reverse vision loss; however, the generation of sensory neuronal subtypes such as photoreceptors remains a challenge. Here we report that the administration of a set of five small molecules can chemically induce the transformation of fibroblasts into rod photoreceptor-like cells. The transplantation of these chemically induced photoreceptor-like cells (CiPCs) into the subretinal space of rod degeneration mice (homozygous for rd1 , also known as Pde6b ) leads to partial restoration of the pupil reflex and visual function. We show that mitonuclear communication is a key determining factor for the reprogramming of fibroblasts into CiPCs. Specifically, treatment with these five compounds leads to the translocation of AXIN2 to the mitochondria, which results in the production of reactive oxygen species, the activation of NF-κB and the upregulation of Ascl1 . We anticipate that CiPCs could have therapeutic potential for restoring vision. Main Many retinopathies—such as age-related macular degeneration, diabetic retinopathy and retinitis pigmentosa—ultimately result in the loss of retinal neurons, which leads to irreversible vision loss 1 , 2 . Stem-cell therapy, using embryonic stem cells or induced pluripotent stem cells, is a promising strategy to replace lost retinal cells and improve vision 3 , 4 . However, protocols for the derivation of candidate replacement cells are cumbersome and time consuming, presenting a challenge for their use in clinical therapy 5 , 6 , 7 , 8 . Direct reprogramming—using ectopic transcription factors and chemicals—bypasses the requirement for pluripotent cells and has resulted in the generation of neurons, astrocytes and cardiomyocytes; however, the pharmacological conversion of photoreceptors using this method has not been realized 9 , 10 , 11 , 12 , 13 . ASCL1, a powerful proneural transcription factor, has been reported to reprogram glial cells into photoreceptors 14 , 15 , 16 . An improved mechanistic understanding of direct reprogramming may lead to the generation of new cell types. Here we identify a set of five small molecules that can induce fibroblasts to become functional CiPCs without the need for pluripotent cells or viral transcription factors. We demonstrate that CiPCs restore pupil reflex and vision when transplanted into the subretinal space of rd1 mice, a mouse model of retinal degeneration. Moreover, our mechanistic analysis reveals an AXIN2–NF-κB–ASCL1 pathway that promotes retinal lineage during reprogramming and identifies mitochondria as a signalling hub in the orchestration of cell fate conversion. A set of five compounds transforms fibroblasts to CiPCs To generate CiPCs, we used mouse embryonic fibroblasts (MEFs) derived from a transgenic Nrl –GFP mouse, in which the Nrl promoter drives expression of eGFP specifically in rod photoreceptors 17 , 18 . We began by testing an established combination of four small molecules—valproic acid (V), CHIR99021 (a GSK3 inhibitor) (C), RepSox (R) and forskolin (F), together denoted VCRF—that is known to convert fibroblasts into neurons, but only a few of the resultant cells were Nrl –GFP positive 12 . Various small molecules and culture conditions were attempted (Supplementary Table 5 ), and we found that the Wnt/β-catenin pathway inhibitor IWR1 (I)—in combination with VCRF and STR (Sonic hedgehog, taurine and retinoic acid)—was able to substantially improve the efficiency of conversion of MEFs into Nrl –GFP + cells (Fig. 1a, b ). STR was added on day 8 of reprogramming, to promote and support the formation of photoreceptors after photoreceptor-specifying transcription factors—such as RORβ, ASCL1, PIAS3—were upregulated 14 , 19 , 20 , 21 , 22 (Fig. 1l , Supplementary Tables 1 , 2 ). Similarly, human adult dermal fibroblasts (HADF), and human fetal lung fibroblasts transduced with a Nrl– DsRed reporter, were also converted into CiPCs (Fig. 1f–h, j , Extended Data Fig. 1a, b , Supplementary Fig. 2 , Supplementary Table 6 ). We next tested the small molecules individually and in various combinations, and observed that they failed to generate as many Nrl –GFP + cells (Extended Data Fig. 1c, d ). We conclude that all five compounds in combination can efficiently convert fibroblasts into NRL - expressing CiPCs. Fig. 1: Conversion of fibroblasts and the molecular characterization of CiPCs. a , Protocol for the reprogramming of mouse fibroblasts into CiPCs. MC, medium change; PIM, photoreceptor induction medium; PDM, photoreceptor differentiation medium. b , Images of CiPCs expressing Nrl –GFP on day 11 and day 16. Scale bars 14.4 μm c , Images of CiPCs expressing CRX on day 11. Scale bars 14.4 μm d , FACS purification of reprogrammed Nrl –GFP + CiPCs (0.2%). e , PCR with reverse transcription reveals the expression of the indicated photoreceptor-specific genes in mouse. For gel source data, see Supplementary Fig. 2a, b . f , Protocol for the reprogramming of HADFs into CiPCs. g , Quantitative PCR (qPCR) analysis (fold change compared with HADF) CiPCs after reprogramming from HADF, showing increased expression of photoreceptor-specific genes. Data are presented as mean ± s.e.m. of n = 3 independently treated biological replicates. h , Micrograph of NRL-stained CiPCs after conversion from HADF. Scale bars 33 μm i , Principal component analysis for all RNA-seq samples ( n = 3 samples for each). j , Images of CiPCs after conversion from HADF at day 10. Rcvrn, recoverin; Rho, rhodopsin.Scale bars 14.4 μm k , Heat map of RNA-seq data for the indicated photoreceptor genes. RI, reprogramming intermediate. l , Heat map of RNA-seq data for the expression of the indicated genes that express retinal transcription factors during CiPC conversion. Experiments in b , h , i were repeated three times with similar results and the experiments in c , d , were repeated twice with similar results. CPM, counts per million. Source Data Full size image Next, Nrl –GFP + CiPCs were purified by fluorescence-activated cell sorting (FACS) and subject to transcriptomic analysis, which revealed the expression of early retinal neuronal markers (CHX10 and OTX2) and photoreceptor markers<|im_end|> <|im_start|>assistant Researchers have discovered a technique for directly reprogramming skin cells into light-sensing rod photoreceptors used for vision. The lab-made rods enabled blind mice to detect light after the cells were transplanted into the animals' eyes. The work, funded by the National Eye Institute (NEI), published April 15 in Nature. Up until now, researchers have replaced dying photoreceptors in animal models by creating stem cells from skin or blood cells, programming those stem cells to become photoreceptors, which are then transplanted into the back of the eye. In the new study, scientists show that it is possible to skip the stem-cell intermediary step and directly reprogram skins cells into photoreceptors for transplantation into the retina. "This is the first study to show that direct, chemical reprogramming can produce retinal-like cells, which gives us a new and faster strategy for developing therapies for age-related macular degeneration and other retinal disorders caused by the loss of photoreceptors," said Anand Swaroop, Ph.D., senior investigator in the NEI Neurobiology, Neurodegeneration, and Repair Laboratory, which characterized the reprogrammed rod photoreceptor cells by gene expression analysis. "Of immediate benefit will be the ability to quickly develop disease models so we can study mechanisms of disease. The new strategy will also help us design better cell replacement approaches," he said. Scientists have studied induced pluripotent stem (iPS) cells with intense interest over the past decade. IPSCs are developed in a lab from adult cells —rather than fetal tissue— and can be used to make nearly any type of replacement cell or tissue. But iPS cell reprogramming protocols can take six months before cells or tissues are ready for transplantation. By contrast, the direct reprogramming described in the current study coaxed skin cells into functional photoreceptors ready for transplantation in only 10 days. The researchers demonstrated their technique in mouse eyes, using both mouse- and human-derived skin cells. "Our technique goes directly from skin cell to photoreceptor without the need for stem cells in between," said the study's lead investigator, Sai Chavala, M.D., CEO and president of CIRC Therapeutics and the Center for Retina Innovation. Chavala is also director of retina services at KE Eye Centers of Texas and a professor of surgery at Texas Christian University and University of North Texas Health Science Center (UNTHSC) School of Medicine, Fort Worth. Direct reprogramming involves bathing the skin cells in a cocktail of five small molecule compounds that together chemically mediate the molecular pathways relevant for rod photoreceptor cell fate. The result are rod photoreceptors that mimic native rods in appearance and function. The researchers performed gene expression profiling, which showed that the genes expressed by the new cells were similar to those expressed by real rod photoreceptors. At the same time, genes relevant to skin cell function had been downregulated. The researchers transplanted the cells into mice with retinal degeneration and then tested their pupillary reflexes, which is a measure of photoreceptor function after transplantation. Under low-light conditions, constriction of the pupil is dependent on rod photoreceptor function. Within a month of transplantation, six of 14 (43%) animals showed robust pupil constriction under low light compared to none of the untreated controls. Moreover, treated mice with pupil constriction were significantly more likely to seek out and spend time in dark spaces compared with treated mice with no pupil response and untreated controls. Preference for dark spaces is a behavior that requires vision and reflects the mouse's natural tendency to seek out safe, dark locations as opposed to light ones. "Even mice with severely advanced retinal degeneration, with little chance of having living photoreceptors remaining, responded to transplantation. Such findings suggest that the observed improvements were due to the lab-made photoreceptors rather than to an ancillary effect that supported the health of the host's existing photoreceptors," said the study's first author Biraj Mahato, Ph.D., research scientist, UNTHSC. Three months after transplantation, immunofluorescence studies confirmed the survival of the lab-made photoreceptors, as well as their synaptic connections to neurons in the inner retina. Further research is needed to optimize the protocol to increase the number of functional transplanted photoreceptors. "Importantly, the researchers worked out how this direct reprogramming is mediated at the cellular level. These insights will help researchers apply the technique not only to the retina, but to many other cell types," Swaroop said. "If efficiency of this direct conversion can be improved, this may significantly reduce the time it takes to develop a potential cell therapy product or disease model," said Kapil Bharti, Ph.D., senior investigator and head of the Ocular and Stem Cell Translational Research Section at NEI. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 18235, 461, 15709, 4814, 374, 279, 1620, 4279, 15233, 304, 1455, 2160, 258, 36211, 552, 430, 3063, 311, 93294, 85515, 11, 323, 1070, 527, 912, 7524, 22972, 311, 15301, 11376, 220, 16, 1174, 220, 17, 662, 36424, 312, 92726, 315, 16178, 299, 2067, 12019, 6209, 459, 6776, 311, 10134, 11376, 4814, 26, 4869, 11, 279, 9659, 315, 49069, 79402, 1207, 9426, 1778, 439, 4604, 461, 58650, 8625, 264, 8815, 13, 5810, 584, 1934, 430, 279, 8735, 315, 264, 743, 315, 4330, 2678, 35715, 649, 8590, 2740, 49853, 279, 18475, 315, 16178, 299, 2067, 12019, 1139, 21236, 4604, 461, 15709, 12970, 7917, 13, 578, 98702, 315, 1521, 8590, 2740, 36572, 4604, 461, 15709, 12970, 7917, 320, 61719, 4977, 82, 8, 1139, 279, 1207, 2171, 992, 3634, 315, 21236, 5367, 17699, 24548, 320, 71, 16279, 4341, 70, 788, 369, 23527, 16, 1174, 1101, 3967, 439, 393, 451, 21, 65, 883, 11767, 311, 7276, 35093, 315, 279, 61072, 33766, 323, 9302, 734, 13, 1226, 1501, 430, 5568, 263, 9834, 10758, 374, 264, 1401, 26679, 8331, 369, 279, 312, 92726, 315, 16178, 299, 2067, 12019, 1139, 32744, 4977, 82, 13, 45863, 11, 6514, 449, 1521, 4330, 32246, 11767, 311, 279, 1380, 2588, 315, 41811, 691, 17, 311, 279, 55042, 4298, 11, 902, 3135, 304, 279, 5788, 315, 56563, 24463, 9606, 11, 279, 15449, 315, 45827, 12, 68437, 33, 323, 279, 709, 1610, 2987, 315, 1666, 566, 16, 662, 1226, 48248, 430, 32744, 4977, 82, 1436, 617, 37471, 4754, 369, 50203, 11376, 13, 4802, 9176, 2160, 258, 36211, 552, 2345, 21470, 439, 4325, 14228, 9155, 1299, 5367, 17699, 11, 71975, 2160, 258, 54042, 323, 2160, 2381, 285, 77678, 12252, 2345, 495, 7253, 1121, 304, 279, 4814, 315, 2160, 992, 34313, 11, 902, 11767, 311, 93294, 11376, 4814, 220, 16, 1174, 220, 17, 662, 81948, 33001, 15419, 11, 1701, 44481, 14338, 19646, 7917, 477, 36572, 60217, 575, 64632, 19646, 7917, 11, 374, 264, 26455, 8446, 311, 8454, 5675, 2160, 992, 7917, 323, 7417, 11376, 220, 18, 1174, 220, 19, 662, 4452, 11, 32885, 369, 279, 96354, 315, 9322, 14039, 7917, 527, 96190, 323, 892, 35208, 11, 32644, 264, 8815, 369, 872, 1005, 304, 14830, 15419, 220, 20, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 662, 7286, 312, 92726, 2345, 985, 77594, 25847, 46940, 9547, 323, 26333, 2345, 65, 51011, 288, 279, 16686, 369, 60217, 575, 64632, 7917, 323, 706, 19543, 304, 279, 9659, 315, 34313, 11, 47804, 11377, 2392, 323, 73151, 5650, 57878, 26, 4869, 11, 279, 36449, 5848, 14747, 315, 4604, 461, 58650, 1701, 420, 1749, 706, 539, 1027, 15393, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 662, 5871, 3218, 16, 11, 264, 8147, 38097, 4269, 46940, 8331, 11, 706, 1027, 5068, 311, 312, 15252, 2840, 532, 7917, 1139, 4604, 461, 58650, 220, 975, 1174, 220, 868, 1174, 220, 845, 662, 1556, 13241, 7852, 4633, 8830, 315, 2167, 312, 92726, 1253, 3063, 311, 279, 9659, 315, 502, 2849, 4595, 13, 5810, 584, 10765, 264, 743, 315, 4330, 2678, 35715, 430, 649, 49853, 16178, 299, 2067, 12019, 311, 3719, 16003, 32744, 4977, 82, 2085, 279, 1205, 369, 60217, 575, 64632, 7917, 477, 29962, 46940, 9547, 13, 1226, 20461, 430, 32744, 4977, 82, 15301, 61072, 33766, 323, 11376, 994, 1380, 501, 7719, 1139, 279, 1207, 2171, 992, 3634, 315, 23527, 16, 24548, 11, 264, 8814, 1646, 315, 2160, 992, 5367, 17699, 13, 23674, 11, 1057, 7852, 4633, 6492, 21667, 459, 41811, 691, 17, 4235, 39167, 12, 68437, 33, 4235, 1950, 3218, 16, 38970, 430, 39990, 2160, 992, 65009, 2391, 312, 92726, 323, 36611, 55042, 4298, 439, 264, 91977, 19240, 304, 279, 70984, 2214, 315, 2849, 25382, 14747, 13, 362, 743, 315, 4330, 32246, 29575, 16178, 299, 2067, 12019, 311, 32744, 4977, 82, 2057, 7068, 32744, 4977, 82, 11, 584, 1511, 8814, 44481, 14338, 16178, 299, 2067, 12019, 320, 7614, 49400, 8, 14592, 505, 264, 1380, 89305, 452, 2438, 1389, 38, 11960, 8814, 11, 304, 902, 279, 452, 2438, 66642, 20722, 7645, 315, 384, 38, 11960, 11951, 304, 21236, 4604, 461, 58650, 220, 1114, 1174, 220, 972, 662, 1226, 6137, 555, 7649, 459, 9749, 10824, 315, 3116, 2678, 35715, 2345, 838, 782, 292, 13935, 320, 53, 705, 6969, 2871, 19146, 1691, 320, 64, 480, 16074, 18, 70785, 8, 320, 34, 705, 3402, 4516, 87, 320, 49, 8, 323, 84452, 37737, 320, 37, 705, 3871, 3453, 9437, 650, 9150, 37, 41128, 374, 3967, 311, 5625, 16178, 299, 2067, 12019, 1139, 34313, 11, 719, 1193, 264, 2478, 315, 279, 84913, 7917, 1051, 452, 2438, 1389, 38, 11960, 6928, 220, 717, 662, 40741, 2678, 35715, 323, 7829, 4787, 1051, 17644, 320, 10254, 67082, 6771, 220, 20, 7026, 323, 584, 1766, 430, 279, 468, 406, 14, 52355, 1824, 13827, 258, 38970, 70785, 358, 18408, 16, 320, 40, 68850, 258, 10824, 449, 650, 9150, 37, 323, 12428, 320, 50, 14338, 42766, 61722, 11, 259, 4202, 483, 323, 2160, 3394, 292, 13935, 68850, 16514, 3025, 311, 32302, 7417, 279, 15374, 315, 14747, 315, 386, 15229, 82, 1139, 452, 2438, 1389, 38, 11960, 489, 7917, 320, 30035, 13, 220, 16, 64, 11, 293, 7609, 12428, 574, 3779, 389, 1938, 220, 23, 315, 312, 92726, 11, 311, 12192, 323, 1862, 279, 18488, 315, 4604, 461, 58650, 1306, 4604, 461, 15709, 58894, 7922, 46940, 9547, 2345, 21470, 439, 432, 878, 52355, 11, 5871, 3218, 16, 11, 23396, 1950, 18, 2345, 52898, 709, 81722, 220, 975, 1174, 220, 777, 1174, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 320, 30035, 13, 220, 16, 75, 1174, 99371, 43252, 220, 16, 1174, 220, 17, 7609, 35339, 11, 3823, 6822, 2761, 14991, 16178, 299, 2067, 12019, 320, 39, 92363, 705, 323, 3823, 63746, 21271, 16178, 299, 2067, 12019, 1380, 54478, 449, 264, 452, 2438, 4235, 423, 82, 6161, 19496, 11, 1051, 1101, 16489, 1139, 32744, 4977, 82, 320, 30035, 13, 220, 16, 69, 4235, 71, 11, 503, 1174, 41665, 2956, 23966, 13, 220, 16, 64, 11, 293, 1174, 99371, 23966, 13, 220, 17, 1174, 99371, 6771, 220, 21, 7609, 1226, 1828, 12793, 279, 2678, 35715, 32399, 323, 304, 5370, 28559, 11, 323, 13468, 430, 814, 4745, 311, 7068, 439, 1690, 452, 2438, 1389, 38, 11960, 489, 7917, 320, 54290, 2956, 23966, 13, 220, 16, 66, 11, 294, 7609, 1226, 32194, 430, 682, 4330, 32246, 304, 10824, 649, 30820, 5625, 16178, 299, 2067, 12019, 1139, 95254, 482, 37810, 32744, 4977, 82, 13, 23966, 13, 220, 16, 25, 43609, 315, 16178, 299, 2067, 12019, 323, 279, 31206, 60993, 315, 32744, 4977, 82, 13, 264, 1174, 25590, 369, 279, 312, 92726, 315, 8814, 16178, 299, 2067, 12019, 1139, 32744, 4977, 82, 13, 21539, 11, 11298, 2349, 26, 393, 1829, 11, 4604, 461, 15709, 38156, 11298, 26, 393, 8561, 11, 4604, 461, 15709, 60038, 11298, 13, 293, 1174, 12041, 315, 32744, 4977, 82, 37810, 452, 2438, 1389, 38, 11960, 389, 1938, 220, 806, 323, 1938, 220, 845, 13, 25635, 16283, 220, 975, 13, 19, 33983, 76, 272, 1174, 12041, 315, 32744, 4977, 82, 37810, 12904, 55, 389, 1938, 220, 806, 13, 25635, 16283, 220, 975, 13, 19, 33983, 76, 294, 1174, 435, 63787, 94536, 315, 312, 15252, 2106, 452, 2438, 1389, 38, 11960, 489, 32744, 4977, 82, 320, 15, 13, 17, 53172, 384, 1174, 67791, 449, 10134, 46940, 21667, 279, 7645, 315, 279, 16717, 4604, 461, 15709, 19440, 21389, 304, 8814, 13, 1789, 18316, 2592, 828, 11, 1518, 99371, 23966, 13, 220, 17, 64, 11, 293, 662, 282, 1174, 25590, 369, 279, 312, 92726, 315, 473, 1846, 49400, 1139, 32744, 4977, 82, 13, 342, 1174, 32541, 22018, 67791, 320, 80, 74256, 8, 6492, 320, 20557, 2349, 7863, 449, 473, 92363, 8, 32744, 4977, 82, 1306, 312, 92726, 505, 473, 92363, 11, 9204, 7319, 7645, 315, 4604, 461, 15709, 19440, 21389, 13, 2956, 527, 10666, 439, 3152, 20903, 274, 1770, 749, 13, 315, 308, 284, 220, 18, 29235, 12020, 24156, 29641, 988, 13, 305, 1174, 18654, 4539, 315, 95254, 5594, 2692, 32744, 4977, 82, 1306, 14747, 505, 473, 92363, 13, 25635, 16283, 220, 1644, 33983, 76, 602, 1174, 37409, 3777, 6492, 369, 682, 41214, 7962, 80, 10688, 320, 308, 284, 220, 18, 10688, 369, 1855, 570, 503, 1174, 12041, 315, 32744, 4977, 82, 1306, 14747, 505, 473, 92363, 520, 1938, 220, 605, 13, 432, 13423, 36722, 11, 11993, 258, 26, 432, 6292, 11, 22408, 347, 3806, 258, 52932, 16283, 220, 975, 13, 19, 33983, 76, 597, 1174, 27162, 2472, 315, 41214, 7962, 80, 828, 369, 279, 16717, 4604, 461, 15709, 21389, 13, 48597, 11, 312, 92726, 29539, 13, 326, 1174, 27162, 2472, 315, 41214, 7962, 80, 828, 369, 279, 7645, 315, 279, 16717, 21389, 430, 3237, 2160, 992, 46940, 9547, 2391, 32744, 4977, 14747, 13, 1398, 50732, 304, 293, 1174, 305, 1174, 602, 1051, 11763, 2380, 3115, 449, 4528, 3135, 323, 279, 21896, 304, 272, 1174, 294, 1174, 1051, 11763, 11157, 449, 4528, 3135, 13, 356, 8971, 11, 14921, 824, 3610, 13, 8922, 2956, 8797, 1404, 2217, 9479, 11, 452, 2438, 1389, 38, 11960, 489, 32744, 4977, 82, 1051, 92600, 555, 97332, 12, 31262, 2849, 29373, 320, 37, 63787, 8, 323, 3917, 311, 36815, 3151, 6492, 11, 902, 10675, 279, 7645, 315, 4216, 2160, 992, 79402, 24915, 320, 2198, 55, 605, 323, 8775, 55, 17, 8, 323, 4604, 461, 15709, 24915, 128257, 198, 128256, 78191, 198, 60210, 617, 11352, 264, 15105, 369, 6089, 312, 92726, 6930, 7917, 1139, 3177, 1355, 49205, 21236, 4604, 461, 58650, 1511, 369, 11376, 13, 578, 10278, 27975, 58000, 9147, 18507, 24548, 311, 11388, 3177, 1306, 279, 7917, 1051, 1380, 501, 7719, 1139, 279, 10099, 6, 6548, 13, 578, 990, 11, 24853, 555, 279, 5165, 28929, 10181, 320, 4031, 40, 705, 4756, 5936, 220, 868, 304, 22037, 13, 3216, 3156, 1457, 11, 12074, 617, 12860, 23069, 4604, 461, 58650, 304, 10065, 4211, 555, 6968, 19646, 7917, 505, 6930, 477, 6680, 7917, 11, 15840, 1884, 19646, 7917, 311, 3719, 4604, 461, 58650, 11, 902, 527, 1243, 1380, 501, 7719, 1139, 279, 1203, 315, 279, 8071, 13, 763, 279, 502, 4007, 11, 14248, 1501, 430, 433, 374, 3284, 311, 10936, 279, 19646, 33001, 95170, 3094, 323, 6089, 312, 15252, 51050, 7917, 1139, 4604, 461, 58650, 369, 98702, 1139, 279, 84827, 13, 330, 2028, 374, 279, 1176, 4007, 311, 1501, 430, 2167, 11, 11742, 312, 92726, 649, 8356, 2160, 992, 12970, 7917, 11, 902, 6835, 603, 264, 502, 323, 10819, 8446, 369, 11469, 52312, 369, 4325, 14228, 9155, 1299, 5367, 17699, 323, 1023, 2160, 992, 24673, 9057, 555, 279, 4814, 315, 4604, 461, 58650, 1359, 1071, 1556, 438, 4593, 17606, 454, 11, 2405, 920, 2637, 10195, 49581, 304, 279, 8014, 40, 32359, 81162, 11, 32359, 451, 81157, 11, 323, 28266, 32184, 11, 902, 32971, 279, 312, 15252, 2106, 21236, 4604, 461, 15709, 7917, 555, 15207, 7645, 6492, 13, 330, 2173, 14247, 8935, 690, 387, 279, 5845, 311, 6288, 2274, 8624, 4211, 779, 584, 649, 4007, 24717, 315, 8624, 13, 578, 502, 8446, 690, 1101, 1520, 603, 2955, 2731, 2849, 14039, 20414, 1359, 568, 1071, 13, 57116, 617, 20041, 36572, 60217, 575, 64632, 19646, 320, 72, 5119, 8, 7917, 449, 19428, 2802, 927, 279, 3347, 13515, 13, 6933, 3624, 82, 527, 8040, 304, 264, 10278, 505, 6822, 7917, 2001, 74303, 1109, 63746, 20438, 2345, 323, 649, 387, 1511, 311, 1304, 7154, 904, 955, 315, 14039, 2849, 477, 20438, 13, 2030, 602, 5119, 2849, 312, 92726, 32885, 649, 1935, 4848, 4038, 1603, 7917, 477, 39881, 527, 5644, 369, 98702, 13, 3296, 13168, 11, 279, 2167, 312, 92726, 7633, 304, 279, 1510, 4007, 1080, 52551, 6930, 7917, 1139, 16003, 4604, 461, 58650, 5644, 369, 98702, 304, 1193, 220, 605, 2919, 13, 578, 12074, 21091, 872, 15105, 304, 8814, 6548, 11, 1701, 2225, 8814, 12, 323, 3823, 72286, 6930, 7917, 13, 330, 8140, 15105, 5900, 6089, 505, 6930, 2849, 311, 4604, 461, 15709, 2085, 279, 1205, 369, 19646, 7917, 304, 1990, 1359, 1071, 279, 4007, 596, 3063, 49581, 11, 71841, 921, 402, 6181, 11, 386, 920, 2637, 12432, 323, 4872, 315, 356, 52940, 23258, 88886, 323, 279, 5955, 369, 10608, 2259, 38710, 13, 921, 402, 6181, 374, 1101, 7690, 315, 84827, 3600, 520, 11337, 28929, 41991, 315, 8421, 323, 264, 14561, 315, 15173, 520, 8421, 9052, 3907, 323, 3907, 315, 4892, 8421, 6401, 10170, 5955, 320, 1899, 3701, 3624, 8, 6150, 315, 19152, 11, 11246, 37246, 13, 7286, 312, 92726, 18065, 73509, 279, 6930, 7917, 304, 264, 41010, 315, 4330, 2678, 43030, 32246, 430, 3871, 8590, 2740, 1812, 6629, 279, 31206, 44014, 9959, 369, 21236, 4604, 461, 15709, 2849, 25382, 13, 578, 1121, 527, 21236, 4604, 461, 58650, 430, 56459, 10068, 58000, 304, 11341, 323, 734, 13, 578, 12074, 10887, 15207, 7645, 56186, 11, 902, 8710, 430, 279, 21389, 13605, 555, 279, 502, 7917, 1051, 4528, 311, 1884, 13605, 555, 1972, 21236, 4604, 461, 58650, 13, 2468, 279, 1890, 892, 11, 21389, 9959, 311, 6930, 2849, 734, 1047, 1027, 1523, 81722, 13, 578, 12074, 1380, 501, 7719, 279, 7917, 1139, 24548, 449, 2160, 992, 5367, 17699, 323, 1243, 12793, 872, 15241, 35605, 33766, 288, 11, 902, 374, 264, 6767, 315, 4604, 461, 15709, 734, 1306, 98702, 13, 9636, 3428, 18179, 4787, 11, 19477, 2538, 315, 279, 61072, 374, 18222, 389, 21236, 4604, 461, 15709, 734, 13, 25218, 264, 2305, 315, 98702, 11, 4848, 315, 220, 975, 320, 3391, 11587, 10099, 8710, 22514, 61072, 19477, 2538, 1234, 3428, 3177, 7863, 311, 7000, 315, 279, 83920, 11835, 13, 23674, 11, 12020, 24548, 449, 61072, 19477, 2538, 1051, 12207, 810, 4461, 311, 6056, 704, 323, 8493, 892, 304, 6453, 12908, 7863, 449, 12020, 24548, 449, 912, 61072, 2077, 323, 83920, 11835, 13, 49905, 369, 6453, 12908, 374, 264, 7865, 430, 7612, 11376, 323, 27053, 279, 8814, 596, 5933, 31954, 311, 6056, 704, 6220, 11, 6453, 10687, 439, 16475, 311, 3177, 6305, 13, 330, 13461, 24548, 449, 35906, 11084, 2160, 992, 5367, 17699, 11, 449, 2697, 6140, 315, 3515, 5496, 4604, 461, 58650, 9861, 11, 16846, 311, 98702, 13, 15483, 14955, 4284, 430, 279, 13468, 18637, 1051, 4245, 311, 279, 10278, 27975, 4604, 461, 58650, 4856, 1109, 311, 459, 46845, 35605, 2515, 430, 7396, 279, 2890, 315, 279, 3552, 596, 6484, 4604, 461, 58650, 1359, 1071, 279, 4007, 596, 1176, 3229, 37919, 1662, 16566, 4428, 11, 2405, 920, 2637, 3495, 28568, 11, 6781, 3701, 3624, 13, 14853, 4038, 1306, 98702, 11, 33119, 1073, 10036, 4692, 36634, 7978, 11007, 279, 20237, 315, 279, 10278, 27975, 4604, 461, 58650, 11, 439, 1664, 439, 872, 99827, 13537, 311, 34313, 304, 279, 9358, 84827, 13, 15903, 3495, 374, 4460, 311, 30536, 279, 11766, 311, 5376, 279, 1396, 315, 16003, 1380, 501, 7719, 4604, 461, 58650, 13, 330, 11772, 18007, 11, 279, 12074, 6575, 704, 1268, 420, 2167, 312, 92726, 374, 78926, 520, 279, 35693, 2237, 13, 4314, 26793, 690, 1520, 12074, 3881, 279, 15105, 539, 1193, 311, 279, 84827, 11, 719, 311, 1690, 1023, 2849, 4595, 1359, 4593, 17606, 454, 1071, 13, 330, 2746, 15374, 315, 420, 2167, 14747, 649, 387, 13241, 11, 420, 1253, 12207, 8108, 279, 892, 433, 5097, 311, 2274, 264, 4754, 2849, 15419, 2027, 477, 8624, 1646, 1359, 1071, 32765, 321, 31930, 68641, 11, 2405, 920, 2637, 10195, 49581, 323, 2010, 315, 279, 507, 22077, 323, 81948, 14299, 4149, 75, 1697, 8483, 11360, 520, 8014, 40, 13, 220, 128257, 198 ]

2,560

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Deforestation associated with the initial settlement of New Zealand is a dramatic example of how humans can alter landscapes through fire. However, evidence linking early human presence and land-cover change is inferential in most continental sites. We employed a multi-proxy approach to reconstruct anthropogenic land use in New Zealand’s South Island over the last millennium using fecal and plant sterols as indicators of human activity and monosaccharide anhydrides, polycyclic aromatic hydrocarbons, charcoal and pollen as tracers of fire and vegetation change in lake-sediment cores. Our data provide a direct record of local human presence in Lake Kirkpatrick and Lake Diamond watersheds at the time of deforestation and a new and stronger case of human agency linked with forest clearance. The first detection of human presence matches charcoal and biomarker evidence for initial burning at c. AD 1350. Sterols decreased shortly after to values suggesting the sporadic presence of people and then rose to unprecedented levels after the European settlement. Our results confirm that initial human arrival in New Zealand was associated with brief and intense burning activities. Testing our approach in a context of well-established fire history provides a new tool for understanding cause-effect relationships in more complex continental reconstructions. Introduction Humans have altered landscapes around the world for thousands of years through their use of fire 1 . However, the intensity and extent of anthropogenic burning in many regions remains unresolved 2 . Most reconstructions of past fire regimes focus on variations in the concentration of charcoal particles preserved in the sediments of lakes and other natural wetlands. Such records disclose the occurrence of fire and variations in the frequency and timing of biomass burning, but they are unable to discern whether ignitions originate from natural or human causes. Finding methods for disentangling naturally caused fires from those deliberately started by people remains one of the great challenges in paleofire science 1 , 2 . Times and places where past fire activity and vegetation depart from trends that can be explained by climate alone are often used as indirect evidence for anthropogenic burning. Identifying past human presence in particular watersheds has generally relied on archeological data, but few locations offer a clear archeological signal of local fire use. As a result, linking past changes in vegetation and fire with human activity is largely inferential 3 , 4 . One of the most dramatic examples of prehistoric anthropogenic burning occurs in New Zealand, where charcoal and pollen records provide incontrovertible evidence of unprecedented fire activity and native forest decline coinciding with the arrival of people at c. AD 1280 5 , 6 , 7 , 8 . Results from modeling studies that examine vegetation-fire feedbacks attribute the rapid environmental change to small-scale positive feedbacks between fire and the post-fire establishment of high flammability shrublands that enable subsequent burning 9 , 10 . Humans, as a new source of ignition, thus triggered a conversion of forest to a more fire-prone shrubland/grassland. This reconstruction, however, is based on charcoal and pollen data alone, and in the absence of archeological evidence of burning it is not possible to determine if humans were present in a particular watershed at the time of a fire event, or if the timing of their activities coincided with the loss of forest 11 , 12 . Here we provide direct evidence of brief but intense intervals of local human activity in two New Zealand watersheds at the same time as other proxies show fire and deforestation. We utilize specific molecular markers to provide a continuous record of human presence, fire activity and land use in the South Island of New Zealand during the last millennium. We determined polycyclic aromatic hydrocarbons (PAHs), monosaccharide anhydrides (MAs), fecal and plant sterols fluxes in sediment cores from Lake Kirkpatrick (45.03° S, 168.57° E) and Lake Diamond (44.65° S, 168.96° E) (Fig. 1 ) to compare with pollen and charcoal records and paleoclimate information. The three MA compounds (levoglucosan, mannosan and galactosan) are formed from cellulose and hemicellulose combustion 13 and the seventeen PAHs (Table S1 ) are tracers for incomplete combustion of organic matter 14 . MAs and PAHs can travel medium to long distances in association with the fine fraction of aerosol particles 15 , 16 and ultimately reach lake sediments through wet and dry deposition 17 . Their signal in lakes complements the macroscopic charcoal (pieces > 125 μm) signal of local fires by providing fire information at regional scales. In Lake Kirkpatrick and Lake Diamond, we also employ two 5β-stanols originating from human feces (coprostanol and epi-coprostanol) 18 to trace human presence in the catchments. Two Δ 5 -sterols (cholesterol and sitosterol) and two 5α-stanols (cholestanol and sitostanol) are used as additional land-use proxies, as these markers account for terrigenous input to the lake and the chemical conditions of sediments 19 , 20 (Table S2 ). Figure 1 Map of the sampling locations. ( a ) Diamond Lake in the Lake Wanaka area and sampling location. ( b ) Lake Kirkpatrick in the Lake Wakatipu area and sampling location. Contains data sourced from the LINZ Data Service licensed for reuse under CC BY 3.0 ( ). Full size image Fire Record Prior to initial human settlement c. AD 1280, fluxes of charcoal and biomarkers in Lake Kirkpatrick and Lake Diamond were nearly undetectable (Fig. 2 ). The lack of large charcoal particles (>125 µm in diameter) testifies to the near-absence of fire in the surrounding Lophozonia -podocarp forests which is typical of records from the region 5 . The presence of extremely low values of molecular fire tracers (PAH total flux < 1 ng cm −2 yr −1 , MA total flux < 4 ng cm −2 yr −1 ) prior to human arrival is attributed to small fires in drier settings in New Zealand or to background atmospheric deposition from distant fires in southeastern Australia and post-depositional processes 21 , 22 , 23 . Figure 2 Multi-proxy comparison. ( a – c ) Fecal sterols, total PAH", "role": "user" }, { "content": "It is now possible to tell the story of mankind's presence and evolution on the planet by analyzing trends in soil and sediment accumulation of fecal sterols, chemical compounds which are crucial in human physiology. Scientists at Ca' Foscari University of Venice and the Institute for the Dynamics of Environmental Processes of the National Research Council (CNR-IDPA) have identified and dated traces of sterols within the sediments of two New Zealand lakes, thus proving the presence of the Maori people who, starting from around 1280, colonized the two oceanic islands and cleared them of forests in just a few decades to make space for fields and pastures. The study has just been published in the scientific journal Scientific Reports. The analyses were carried out in the laboratories of Venice on cores of sediment taken from lakes Diamond and Kirkpatrick, located on New Zealand's South Island. By analyzing the microparticles of coal and pollen, researchers had already found evidence of significant forest fires as well as of sudden changes to the New Zealand landscape during the fourteenth century, when the deforested areas made space available for grass and shrubs to grow quickly and in a manner that was without precedent. Archaeological and paleoecological evidence quite conclusively attribute the deforestation to the Maori people, but this new study provides definitive scientific proof of their arrival in the area and of the enormous impact that a group of so few individuals had on the native forest in a very short time, to the extent that it was irreversibly jeopardized. In addition, the research demonstrates the validity of the method tested by the Italian researchers for reconstructing the history of humankind's presence in a given region. \"Lakes collect traces of the feces of populations that have lived in surrounding areas, and these are deposited on the lake floors,\" explains Elena Argiriadis, postdoc at the Department of Environmental Sciences, Informatics and Statistics at Ca' Foscari, one of the authors of the study, \"offering a continuous recording of the centuries of human presence. The concentration of coprostanol, the sterol most abundant in human feces, graphs a trend which over time nearly matches that of fire-related biomarkers, with a peak between 1345 and 1365 approximately, and is consistent with the profound environmental transformation which took place in New Zealand following the arrival of theMaori.\" Lake Diamond, New Zealand, ph. Credit: Dave McWethy / Montana State University \"This research is part of a series of studies on mankind's impact, through our history and prehistory, on environment and climate, analyzing biomarkers archived within ice or sediment extracts from all over the planet (the Early Human Impact project, funded by the European Research Council),\" explains Carlo Barbante, professor of Analytical Chemistry at Ca' Foscari and director of the CNR-IDPA. \"Traces of human excrement also tell of the Europeans' arrival on the southern island of New Zealand, starting in the 1800s. The exponential growth in the concentration of fecal sterols vividly demonstrates the rapid increase in the population of the area, which has been ongoing since the beginning of the nineteenth century. The method can now be applied to nearby lake sediments and soils, in which the history of human settlement is not so well-documented as in the case of New Zealand, helping to map the movements of populations over time.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Deforestation associated with the initial settlement of New Zealand is a dramatic example of how humans can alter landscapes through fire. However, evidence linking early human presence and land-cover change is inferential in most continental sites. We employed a multi-proxy approach to reconstruct anthropogenic land use in New Zealand’s South Island over the last millennium using fecal and plant sterols as indicators of human activity and monosaccharide anhydrides, polycyclic aromatic hydrocarbons, charcoal and pollen as tracers of fire and vegetation change in lake-sediment cores. Our data provide a direct record of local human presence in Lake Kirkpatrick and Lake Diamond watersheds at the time of deforestation and a new and stronger case of human agency linked with forest clearance. The first detection of human presence matches charcoal and biomarker evidence for initial burning at c. AD 1350. Sterols decreased shortly after to values suggesting the sporadic presence of people and then rose to unprecedented levels after the European settlement. Our results confirm that initial human arrival in New Zealand was associated with brief and intense burning activities. Testing our approach in a context of well-established fire history provides a new tool for understanding cause-effect relationships in more complex continental reconstructions. Introduction Humans have altered landscapes around the world for thousands of years through their use of fire 1 . However, the intensity and extent of anthropogenic burning in many regions remains unresolved 2 . Most reconstructions of past fire regimes focus on variations in the concentration of charcoal particles preserved in the sediments of lakes and other natural wetlands. Such records disclose the occurrence of fire and variations in the frequency and timing of biomass burning, but they are unable to discern whether ignitions originate from natural or human causes. Finding methods for disentangling naturally caused fires from those deliberately started by people remains one of the great challenges in paleofire science 1 , 2 . Times and places where past fire activity and vegetation depart from trends that can be explained by climate alone are often used as indirect evidence for anthropogenic burning. Identifying past human presence in particular watersheds has generally relied on archeological data, but few locations offer a clear archeological signal of local fire use. As a result, linking past changes in vegetation and fire with human activity is largely inferential 3 , 4 . One of the most dramatic examples of prehistoric anthropogenic burning occurs in New Zealand, where charcoal and pollen records provide incontrovertible evidence of unprecedented fire activity and native forest decline coinciding with the arrival of people at c. AD 1280 5 , 6 , 7 , 8 . Results from modeling studies that examine vegetation-fire feedbacks attribute the rapid environmental change to small-scale positive feedbacks between fire and the post-fire establishment of high flammability shrublands that enable subsequent burning 9 , 10 . Humans, as a new source of ignition, thus triggered a conversion of forest to a more fire-prone shrubland/grassland. This reconstruction, however, is based on charcoal and pollen data alone, and in the absence of archeological evidence of burning it is not possible to determine if humans were present in a particular watershed at the time of a fire event, or if the timing of their activities coincided with the loss of forest 11 , 12 . Here we provide direct evidence of brief but intense intervals of local human activity in two New Zealand watersheds at the same time as other proxies show fire and deforestation. We utilize specific molecular markers to provide a continuous record of human presence, fire activity and land use in the South Island of New Zealand during the last millennium. We determined polycyclic aromatic hydrocarbons (PAHs), monosaccharide anhydrides (MAs), fecal and plant sterols fluxes in sediment cores from Lake Kirkpatrick (45.03° S, 168.57° E) and Lake Diamond (44.65° S, 168.96° E) (Fig. 1 ) to compare with pollen and charcoal records and paleoclimate information. The three MA compounds (levoglucosan, mannosan and galactosan) are formed from cellulose and hemicellulose combustion 13 and the seventeen PAHs (Table S1 ) are tracers for incomplete combustion of organic matter 14 . MAs and PAHs can travel medium to long distances in association with the fine fraction of aerosol particles 15 , 16 and ultimately reach lake sediments through wet and dry deposition 17 . Their signal in lakes complements the macroscopic charcoal (pieces > 125 μm) signal of local fires by providing fire information at regional scales. In Lake Kirkpatrick and Lake Diamond, we also employ two 5β-stanols originating from human feces (coprostanol and epi-coprostanol) 18 to trace human presence in the catchments. Two Δ 5 -sterols (cholesterol and sitosterol) and two 5α-stanols (cholestanol and sitostanol) are used as additional land-use proxies, as these markers account for terrigenous input to the lake and the chemical conditions of sediments 19 , 20 (Table S2 ). Figure 1 Map of the sampling locations. ( a ) Diamond Lake in the Lake Wanaka area and sampling location. ( b ) Lake Kirkpatrick in the Lake Wakatipu area and sampling location. Contains data sourced from the LINZ Data Service licensed for reuse under CC BY 3.0 ( ). Full size image Fire Record Prior to initial human settlement c. AD 1280, fluxes of charcoal and biomarkers in Lake Kirkpatrick and Lake Diamond were nearly undetectable (Fig. 2 ). The lack of large charcoal particles (>125 µm in diameter) testifies to the near-absence of fire in the surrounding Lophozonia -podocarp forests which is typical of records from the region 5 . The presence of extremely low values of molecular fire tracers (PAH total flux < 1 ng cm −2 yr −1 , MA total flux < 4 ng cm −2 yr −1 ) prior to human arrival is attributed to small fires in drier settings in New Zealand or to background atmospheric deposition from distant fires in southeastern Australia and post-depositional processes 21 , 22 , 23 . Figure 2 Multi-proxy comparison. ( a – c ) Fecal sterols, total PAH<|im_end|> <|im_start|>assistant It is now possible to tell the story of mankind's presence and evolution on the planet by analyzing trends in soil and sediment accumulation of fecal sterols, chemical compounds which are crucial in human physiology. Scientists at Ca' Foscari University of Venice and the Institute for the Dynamics of Environmental Processes of the National Research Council (CNR-IDPA) have identified and dated traces of sterols within the sediments of two New Zealand lakes, thus proving the presence of the Maori people who, starting from around 1280, colonized the two oceanic islands and cleared them of forests in just a few decades to make space for fields and pastures. The study has just been published in the scientific journal Scientific Reports. The analyses were carried out in the laboratories of Venice on cores of sediment taken from lakes Diamond and Kirkpatrick, located on New Zealand's South Island. By analyzing the microparticles of coal and pollen, researchers had already found evidence of significant forest fires as well as of sudden changes to the New Zealand landscape during the fourteenth century, when the deforested areas made space available for grass and shrubs to grow quickly and in a manner that was without precedent. Archaeological and paleoecological evidence quite conclusively attribute the deforestation to the Maori people, but this new study provides definitive scientific proof of their arrival in the area and of the enormous impact that a group of so few individuals had on the native forest in a very short time, to the extent that it was irreversibly jeopardized. In addition, the research demonstrates the validity of the method tested by the Italian researchers for reconstructing the history of humankind's presence in a given region. "Lakes collect traces of the feces of populations that have lived in surrounding areas, and these are deposited on the lake floors," explains Elena Argiriadis, postdoc at the Department of Environmental Sciences, Informatics and Statistics at Ca' Foscari, one of the authors of the study, "offering a continuous recording of the centuries of human presence. The concentration of coprostanol, the sterol most abundant in human feces, graphs a trend which over time nearly matches that of fire-related biomarkers, with a peak between 1345 and 1365 approximately, and is consistent with the profound environmental transformation which took place in New Zealand following the arrival of theMaori." Lake Diamond, New Zealand, ph. Credit: Dave McWethy / Montana State University "This research is part of a series of studies on mankind's impact, through our history and prehistory, on environment and climate, analyzing biomarkers archived within ice or sediment extracts from all over the planet (the Early Human Impact project, funded by the European Research Council)," explains Carlo Barbante, professor of Analytical Chemistry at Ca' Foscari and director of the CNR-IDPA. "Traces of human excrement also tell of the Europeans' arrival on the southern island of New Zealand, starting in the 1800s. The exponential growth in the concentration of fecal sterols vividly demonstrates the rapid increase in the population of the area, which has been ongoing since the beginning of the nineteenth century. The method can now be applied to nearby lake sediments and soils, in which the history of human settlement is not so well-documented as in the case of New Zealand, helping to map the movements of populations over time." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 3979, 97893, 5938, 449, 279, 2926, 17516, 315, 1561, 17340, 374, 264, 22520, 3187, 315, 1268, 12966, 649, 11857, 55890, 1555, 4027, 13, 4452, 11, 6029, 31799, 4216, 3823, 9546, 323, 4363, 76465, 2349, 374, 24499, 2335, 304, 1455, 58636, 6732, 13, 1226, 20011, 264, 7447, 84801, 5603, 311, 44928, 41416, 29569, 4363, 1005, 304, 1561, 17340, 753, 4987, 10951, 927, 279, 1566, 89785, 1701, 55061, 278, 323, 6136, 22562, 3145, 439, 34824, 315, 3823, 5820, 323, 1647, 437, 582, 1799, 579, 459, 8671, 67, 18746, 11, 1499, 3418, 66404, 82688, 17055, 7063, 47620, 11, 61203, 323, 79784, 439, 490, 73797, 315, 4027, 323, 54832, 2349, 304, 22553, 1355, 291, 3904, 36804, 13, 5751, 828, 3493, 264, 2167, 3335, 315, 2254, 3823, 9546, 304, 11940, 32446, 65320, 323, 11940, 25328, 21160, 71, 6910, 520, 279, 892, 315, 711, 97893, 323, 264, 502, 323, 16643, 1162, 315, 3823, 9266, 10815, 449, 13952, 36654, 13, 578, 1176, 18468, 315, 3823, 9546, 9248, 61203, 323, 39538, 13152, 6029, 369, 2926, 20252, 520, 272, 13, 9827, 220, 8878, 15, 13, 27155, 3145, 25983, 20193, 1306, 311, 2819, 23377, 279, 62016, 37314, 9546, 315, 1274, 323, 1243, 16392, 311, 31069, 5990, 1306, 279, 7665, 17516, 13, 5751, 3135, 7838, 430, 2926, 3823, 19163, 304, 1561, 17340, 574, 5938, 449, 10015, 323, 19428, 20252, 7640, 13, 27866, 1057, 5603, 304, 264, 2317, 315, 1664, 64868, 4027, 3925, 5825, 264, 502, 5507, 369, 8830, 5353, 23937, 12135, 304, 810, 6485, 58636, 16456, 20232, 13, 29438, 66094, 617, 29852, 55890, 2212, 279, 1917, 369, 9214, 315, 1667, 1555, 872, 1005, 315, 4027, 220, 16, 662, 4452, 11, 279, 21261, 323, 13112, 315, 41416, 29569, 20252, 304, 1690, 13918, 8625, 81261, 220, 17, 662, 7648, 16456, 20232, 315, 3347, 4027, 61911, 5357, 389, 27339, 304, 279, 20545, 315, 61203, 19252, 34683, 304, 279, 11163, 12843, 315, 44236, 323, 1023, 5933, 14739, 8329, 13, 15483, 7576, 36333, 279, 32659, 315, 4027, 323, 27339, 304, 279, 11900, 323, 18912, 315, 58758, 20252, 11, 719, 814, 527, 12153, 311, 42645, 3508, 5335, 6055, 82316, 505, 5933, 477, 3823, 11384, 13, 43897, 5528, 369, 834, 306, 91204, 18182, 9057, 27176, 505, 1884, 36192, 3940, 555, 1274, 8625, 832, 315, 279, 2294, 11774, 304, 28639, 86582, 8198, 220, 16, 1174, 220, 17, 662, 8691, 323, 7634, 1405, 3347, 4027, 5820, 323, 54832, 11776, 505, 18845, 430, 649, 387, 11497, 555, 10182, 7636, 527, 3629, 1511, 439, 25636, 6029, 369, 41416, 29569, 20252, 13, 23322, 7922, 3347, 3823, 9546, 304, 4040, 21160, 71, 6910, 706, 8965, 41013, 389, 802, 1557, 5848, 828, 11, 719, 2478, 10687, 3085, 264, 2867, 802, 1557, 5848, 8450, 315, 2254, 4027, 1005, 13, 1666, 264, 1121, 11, 31799, 3347, 4442, 304, 54832, 323, 4027, 449, 3823, 5820, 374, 14090, 24499, 2335, 220, 18, 1174, 220, 19, 662, 3861, 315, 279, 1455, 22520, 10507, 315, 864, 74416, 41416, 29569, 20252, 13980, 304, 1561, 17340, 11, 1405, 61203, 323, 79784, 7576, 3493, 72625, 1653, 1260, 6029, 315, 31069, 4027, 5820, 323, 10068, 13952, 18174, 23828, 6714, 449, 279, 19163, 315, 1274, 520, 272, 13, 9827, 220, 4386, 15, 220, 20, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 662, 18591, 505, 34579, 7978, 430, 21635, 54832, 57369, 11302, 82, 7180, 279, 11295, 12434, 2349, 311, 2678, 13230, 6928, 11302, 82, 1990, 4027, 323, 279, 1772, 57369, 21967, 315, 1579, 1344, 8836, 2968, 14362, 392, 8329, 430, 7431, 17876, 20252, 220, 24, 1174, 220, 605, 662, 66094, 11, 439, 264, 502, 2592, 315, 60692, 11, 8617, 22900, 264, 14747, 315, 13952, 311, 264, 810, 4027, 27748, 606, 14362, 392, 1974, 41436, 395, 1974, 13, 1115, 43738, 11, 4869, 11, 374, 3196, 389, 61203, 323, 79784, 828, 7636, 11, 323, 304, 279, 19821, 315, 802, 1557, 5848, 6029, 315, 20252, 433, 374, 539, 3284, 311, 8417, 422, 12966, 1051, 3118, 304, 264, 4040, 92456, 520, 279, 892, 315, 264, 4027, 1567, 11, 477, 422, 279, 18912, 315, 872, 7640, 23828, 4591, 449, 279, 4814, 315, 13952, 220, 806, 1174, 220, 717, 662, 5810, 584, 3493, 2167, 6029, 315, 10015, 719, 19428, 28090, 315, 2254, 3823, 5820, 304, 1403, 1561, 17340, 21160, 71, 6910, 520, 279, 1890, 892, 439, 1023, 60465, 1501, 4027, 323, 711, 97893, 13, 1226, 29166, 3230, 31206, 24915, 311, 3493, 264, 19815, 3335, 315, 3823, 9546, 11, 4027, 5820, 323, 4363, 1005, 304, 279, 4987, 10951, 315, 1561, 17340, 2391, 279, 1566, 89785, 13, 1226, 11075, 1499, 3418, 66404, 82688, 17055, 7063, 47620, 320, 8201, 39, 82, 705, 1647, 437, 582, 1799, 579, 459, 8671, 67, 18746, 320, 44, 2170, 705, 55061, 278, 323, 6136, 22562, 3145, 31405, 288, 304, 59132, 36804, 505, 11940, 32446, 65320, 320, 1774, 13, 2839, 11877, 328, 11, 220, 8953, 13, 3226, 11877, 469, 8, 323, 11940, 25328, 320, 2096, 13, 2397, 11877, 328, 11, 220, 8953, 13, 4161, 11877, 469, 8, 320, 30035, 13, 220, 16, 883, 311, 9616, 449, 79784, 323, 61203, 7576, 323, 28639, 62868, 3509, 2038, 13, 578, 2380, 9917, 32246, 320, 3532, 98347, 1791, 437, 276, 11, 893, 37491, 276, 323, 15730, 533, 437, 276, 8, 527, 14454, 505, 70002, 974, 323, 305, 8274, 616, 360, 974, 59333, 220, 1032, 323, 279, 82497, 13174, 39, 82, 320, 2620, 328, 16, 883, 527, 490, 73797, 369, 33243, 59333, 315, 17808, 5030, 220, 975, 662, 386, 2170, 323, 13174, 39, 82, 649, 5944, 11298, 311, 1317, 27650, 304, 15360, 449, 279, 7060, 19983, 315, 49825, 337, 19252, 220, 868, 1174, 220, 845, 323, 13967, 5662, 22553, 11163, 12843, 1555, 14739, 323, 9235, 65374, 220, 1114, 662, 11205, 8450, 304, 44236, 1946, 1392, 279, 18563, 58510, 61203, 320, 47568, 871, 220, 6549, 33983, 76, 8, 8450, 315, 2254, 27176, 555, 8405, 4027, 2038, 520, 15481, 29505, 13, 763, 11940, 32446, 65320, 323, 11940, 25328, 11, 584, 1101, 3539, 1403, 220, 20, 52355, 5594, 276, 3145, 71373, 505, 3823, 55061, 288, 320, 38828, 299, 24986, 337, 323, 384, 2554, 1824, 47026, 24986, 337, 8, 220, 972, 311, 11917, 3823, 9546, 304, 279, 2339, 1392, 13, 9220, 82263, 220, 20, 482, 3751, 3145, 320, 971, 273, 33282, 323, 2503, 11975, 337, 8, 323, 1403, 220, 20, 19481, 5594, 276, 3145, 320, 971, 273, 24986, 337, 323, 2503, 537, 39710, 8, 527, 1511, 439, 5217, 4363, 25700, 60465, 11, 439, 1521, 24915, 2759, 369, 7317, 26424, 1988, 311, 279, 22553, 323, 279, 11742, 4787, 315, 11163, 12843, 220, 777, 1174, 220, 508, 320, 2620, 328, 17, 7609, 19575, 220, 16, 5135, 315, 279, 25936, 10687, 13, 320, 264, 883, 25328, 11940, 304, 279, 11940, 72118, 13637, 3158, 323, 25936, 3813, 13, 320, 293, 883, 11940, 32446, 65320, 304, 279, 11940, 86637, 266, 575, 84, 3158, 323, 25936, 3813, 13, 31911, 828, 42211, 505, 279, 65889, 57, 2956, 5475, 16383, 369, 27068, 1234, 13844, 7866, 220, 18, 13, 15, 320, 7609, 8797, 1404, 2217, 6785, 13896, 32499, 311, 2926, 3823, 17516, 272, 13, 9827, 220, 4386, 15, 11, 31405, 288, 315, 61203, 323, 39538, 91141, 304, 11940, 32446, 65320, 323, 11940, 25328, 1051, 7154, 2073, 13478, 481, 320, 30035, 13, 220, 17, 7609, 578, 6996, 315, 3544, 61203, 19252, 77952, 6549, 64012, 76, 304, 23899, 8, 1296, 9803, 311, 279, 3221, 97510, 768, 315, 4027, 304, 279, 14932, 445, 5237, 9700, 21947, 482, 40173, 511, 8035, 36658, 902, 374, 14595, 315, 7576, 505, 279, 5654, 220, 20, 662, 578, 9546, 315, 9193, 3428, 2819, 315, 31206, 4027, 490, 73797, 320, 8201, 39, 2860, 31405, 366, 220, 16, 7933, 10166, 25173, 17, 43438, 25173, 16, 1174, 9917, 2860, 31405, 366, 220, 19, 7933, 10166, 25173, 17, 43438, 25173, 16, 883, 4972, 311, 3823, 19163, 374, 30706, 311, 2678, 27176, 304, 294, 7401, 5110, 304, 1561, 17340, 477, 311, 4092, 45475, 65374, 505, 29827, 27176, 304, 83209, 8494, 323, 1772, 6953, 981, 3079, 11618, 220, 1691, 1174, 220, 1313, 1174, 220, 1419, 662, 19575, 220, 17, 17896, 84801, 12593, 13, 320, 264, 1389, 272, 883, 435, 98298, 22562, 3145, 11, 2860, 13174, 39, 128257, 198, 128256, 78191, 198, 2181, 374, 1457, 3284, 311, 3371, 279, 3446, 315, 43384, 596, 9546, 323, 15740, 389, 279, 11841, 555, 42118, 18845, 304, 17614, 323, 59132, 46835, 315, 55061, 278, 22562, 3145, 11, 11742, 32246, 902, 527, 16996, 304, 3823, 78152, 13, 57116, 520, 14751, 6, 435, 24366, 2850, 3907, 315, 56750, 323, 279, 10181, 369, 279, 53711, 315, 25027, 63403, 315, 279, 5165, 8483, 9251, 320, 34, 27416, 54465, 8201, 8, 617, 11054, 323, 30105, 35483, 315, 22562, 3145, 2949, 279, 11163, 12843, 315, 1403, 1561, 17340, 44236, 11, 8617, 39858, 279, 9546, 315, 279, 11583, 13915, 1274, 889, 11, 6041, 505, 2212, 220, 4386, 15, 11, 15235, 1534, 279, 1403, 18435, 292, 30100, 323, 23803, 1124, 315, 36658, 304, 1120, 264, 2478, 11026, 311, 1304, 3634, 369, 5151, 323, 3347, 1439, 13, 578, 4007, 706, 1120, 1027, 4756, 304, 279, 12624, 8486, 38130, 29140, 13, 578, 29060, 1051, 11953, 704, 304, 279, 70760, 315, 56750, 389, 36804, 315, 59132, 4529, 505, 44236, 25328, 323, 32446, 65320, 11, 7559, 389, 1561, 17340, 596, 4987, 10951, 13, 3296, 42118, 279, 19748, 897, 16641, 315, 11756, 323, 79784, 11, 12074, 1047, 2736, 1766, 6029, 315, 5199, 13952, 27176, 439, 1664, 439, 315, 11210, 4442, 311, 279, 1561, 17340, 18921, 2391, 279, 3116, 46487, 9478, 11, 994, 279, 711, 461, 24836, 5789, 1903, 3634, 2561, 369, 16763, 323, 14362, 16115, 311, 3139, 6288, 323, 304, 264, 11827, 430, 574, 2085, 47891, 13, 66102, 5848, 323, 28639, 78, 762, 5848, 6029, 5115, 84082, 3210, 7180, 279, 711, 97893, 311, 279, 11583, 13915, 1274, 11, 719, 420, 502, 4007, 5825, 45813, 12624, 11311, 315, 872, 19163, 304, 279, 3158, 323, 315, 279, 23205, 5536, 430, 264, 1912, 315, 779, 2478, 7931, 1047, 389, 279, 10068, 13952, 304, 264, 1633, 2875, 892, 11, 311, 279, 13112, 430, 433, 574, 25912, 3078, 6623, 53132, 1534, 13, 763, 5369, 11, 279, 3495, 32216, 279, 32939, 315, 279, 1749, 12793, 555, 279, 15155, 12074, 369, 44928, 287, 279, 3925, 315, 2854, 70370, 596, 9546, 304, 264, 2728, 5654, 13, 330, 43, 2094, 6667, 35483, 315, 279, 55061, 288, 315, 22673, 430, 617, 12439, 304, 14932, 5789, 11, 323, 1521, 527, 54568, 389, 279, 22553, 27035, 1359, 15100, 69675, 7793, 21336, 329, 285, 11, 1772, 5349, 520, 279, 6011, 315, 25027, 23199, 11, 31701, 29470, 323, 25647, 520, 14751, 6, 435, 24366, 2850, 11, 832, 315, 279, 12283, 315, 279, 4007, 11, 330, 1885, 4776, 264, 19815, 14975, 315, 279, 24552, 315, 3823, 9546, 13, 578, 20545, 315, 6293, 299, 24986, 337, 11, 279, 22562, 337, 1455, 44611, 304, 3823, 55061, 288, 11, 40099, 264, 9327, 902, 927, 892, 7154, 9248, 430, 315, 4027, 14228, 39538, 91141, 11, 449, 264, 16557, 1990, 220, 9565, 20, 323, 220, 9795, 20, 13489, 11, 323, 374, 13263, 449, 279, 28254, 12434, 18475, 902, 3952, 2035, 304, 1561, 17340, 2768, 279, 19163, 315, 279, 30635, 13915, 1210, 11940, 25328, 11, 1561, 17340, 11, 1343, 13, 16666, 25, 20851, 4584, 54, 774, 88, 611, 37105, 3314, 3907, 330, 2028, 3495, 374, 961, 315, 264, 4101, 315, 7978, 389, 43384, 596, 5536, 11, 1555, 1057, 3925, 323, 864, 19375, 11, 389, 4676, 323, 10182, 11, 42118, 39538, 91141, 53093, 2949, 10054, 477, 59132, 49062, 505, 682, 927, 279, 11841, 320, 1820, 23591, 11344, 29680, 2447, 11, 24853, 555, 279, 7665, 8483, 9251, 36493, 15100, 58870, 47142, 5048, 11, 14561, 315, 38527, 35758, 42846, 520, 14751, 6, 435, 24366, 2850, 323, 7690, 315, 279, 25914, 49, 54465, 8201, 13, 330, 1305, 2492, 315, 3823, 506, 13785, 1101, 3371, 315, 279, 51607, 6, 19163, 389, 279, 18561, 13218, 315, 1561, 17340, 11, 6041, 304, 279, 220, 5245, 15, 82, 13, 578, 59855, 6650, 304, 279, 20545, 315, 55061, 278, 22562, 3145, 43120, 398, 32216, 279, 11295, 5376, 304, 279, 7187, 315, 279, 3158, 11, 902, 706, 1027, 14529, 2533, 279, 7314, 315, 279, 66089, 9478, 13, 578, 1749, 649, 1457, 387, 9435, 311, 14373, 22553, 11163, 12843, 323, 69561, 11, 304, 902, 279, 3925, 315, 3823, 17516, 374, 539, 779, 1664, 1773, 37784, 439, 304, 279, 1162, 315, 1561, 17340, 11, 10695, 311, 2472, 279, 19567, 315, 22673, 927, 892, 1210, 220, 128257, 198 ]

2,058

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Ecosystem functions are regulated by compositional and functional traits of bacterial communities, shaped by stochastic and deterministic processes. Biogeographical studies have revealed microbial community taxonomy in a given ecosystem to change alongside varying environmental characteristics. Considering that stable functional traits are essential for community stability, we hypothesize that contrasting environmental conditions affect microbial taxonomy rather than function in a model system, testing this in three geographically distinct mangrove forests subjected to intense animal bioturbation (a shared deterministic force). Using a metabarcoding approach combined with sediment microprofiling and biochemistry, we examined vertical and radial sediment profiles of burrows belonging to the pantropical fiddler crab (subfamily Gelasiminae ) in three contrasting mangrove environments across a broad latitudinal range (total samples = 432). Each mangrove was environmentally distinct, reflected in taxonomically different bacterial communities, but communities consistently displayed the same spatial stratification (a halo effect) around the burrow which invariably determined the retention of similar inferred functional community traits independent of the local environment. Introduction Biogeography of microorganisms is determined largely by stochastic processes 1 , 2 , 3 , but deterministic processes, essentially related to their ecological niche, are now known to play a significant role in shaping community composition in a given system 4 , 5 , 6 . The unsurmountable importance of microorganisms as the drivers of global biochemical cycles 7 is reflected in their broad taxonomic and metabolic functional diversity 8 . For many of their diverse metabolic functions, microbial communities exhibit functional redundancy, whereby different taxa are able to perform the same metabolic function 9 , 10 , 11 , for example nitrogen cycling in soil 12 and methanogenesis in bioreactors 13 . For this reason, more recent studies of microbial community structure have tended to focus on functional structure rather than taxonomic structure, with a general consensus of the decoupling of some metabolic functions with taxonomic composition in various environments 14 , 15 , i.e., the conditions of the environment hold more weight in shaping functional group distribution than that of taxonomic composition. Microbial community traits have been compared from the local to continental scale with diversity in both taxonomy and functionality being attributed, across the range of spatial scales, to native environmental conditions 8 . However, due to constraints such as the availability of electron acceptors and heterogeneity in, for example, pH, temperature and salinity 16 , environmental drivers do not explain well the variation in taxonomic composition observed in systems with similar environmental conditions: a pattern which has been observed across many marine and terrestrial systems 10 , 12 , 17 . In a system with the same physico-biochemical features (bromeliad aquatic plants), Louca et al . 10 observed intersystem taxonomic, but not functional, variations in the microbial communities that were not completely explained by the different environmental characteristics. Recently, variation in oceanic environmental conditions was described to be responsible for structuring the function of the marine microbial community, while these conditions were only able to weakly explain taxonomic variation within functional groups 15 . Ecological resilience, and the capacity of a system to adapt to change, is positively influenced by higher functional community diversification, such as denitrifiers or carbon degraders, and increased taxonomic diversification within these functional groups 18 , 19 . Here we hypothesize that in the same model system under contrasting local environmental conditions, such as those occurring across large biogeographical ranges, broad and fine scale microbial functional and interaction patterns, rather than taxonomy, should be conserved around a consistent source of selective pressure. To test this hypothesis, we studied mangrove sediments subjected to the deterministic selective pressure of intense animal bioturbation, a process known to enhance biological activity and modify physical and chemical properties of sediment 20 , 21 , 22 . Mangrove forests are sites of strong environmental selection due to the intrinsic characteristics of intertidal environments and the prevalence of bioturbating organisms that, through the creation of burrows, impose a selective pressure at the interface of aquatic and terrestrial habitats 23 associated with microbial hotspots 24 . Thus, mangrove sediment is an ideal system to explore spatial changes in microbial community traits. Using a fiddler crab burrow as our model, we extended our study over a broad geographical (latitudinal) range to encompass contrasting environments. Results Our geographic range encompassed the sites Thuwal, Farasan and Mngazana (Fig. 1a ), in which we radially sampled sediment ‘Fractions’ around burrows and in surface, subsurface and deep sediment. The mangrove stands in Thuwal, Farasan and Mngazana displayed diverse sediment characteristics in terms of biogeochemistry, metal content and grain size (Supplementary Fig. S1 , Supplementary Table S1 and Supplementary File S2 ). Accordingly, PCoA of bacterial OTU composition segregated the three geographical sites into distinct groups, accounting for 49.9% of dissimilarity in community composition between sites (Fig. 1b ). A significant effect of ‘Site’ ( P = 0.0001) and ‘Burrow’ ( P = 0.0138) was observed on biogeochemistry (PERMANOVA, Supplementary Table S1 ). Sulphate, nitrite and nitrate contributed 76.4% to dissimilarity between Farasan and Thuwal sediment (SIMPER), with nitrite and nitrate being higher in Farasan and sulphate being higher in Thuwal. POC, PON, phosphate and silicate contributed 55.6% to dissimilarity between Mngazana and Thuwal (SIMPER), with the former being more abundant in Thuwal, while PON, phosphate and silicate were more abundant in Mngazana. PIC, phosphate, PON and silicate contributed 67.2% to dissimilarity between Mngazana and Farasan (SIMPER), with PIC being more abundant in Farasan, and phosphate, PON and silicate being more abundant in Mngazana. Figure 1 Study site variation. ( a) Map of study sites: a - Thuwal, b - Farasan, c - Mngazana; (b) Principal coordinates analysis of total bacterial OTU assemblages categorized by site (n = 384); (c) Distance-based redundancy analysis (db-RDA) showing significant biogeochemical drivers of bacterial community composition at each site. Full size image Site-specific bacterial assemblages correlated with site-specific physico-chemical characteristics (Fig. 1c , Supplementary Fig. S2 , Supplementary Table S2 ). Across the three mangrove forests, POC, PON, PIN, nitrate, nitrite and silicate significantly explained bacterial community", "role": "user" }, { "content": "The types of bacteria living in and around fiddler crab burrows vary widely between mangroves, but their functional activities are remarkably similar. The types of bacteria present in and around mangrove fiddler crab burrows in three different geographic locations were compared by KAUST researchers. They found that the crabs' burrowing activity changed the sediment in a way that attracted different types of bacteria across the three locations: however, the bacteria performed similar functions, such as aerobic respiration, and potential ecological services, such as turnover of organic matter. \"Mangrove crabs act like ecosystem engineers: Their burrows create radial, halo-like microbiological and geochemical modifications to the surrounding sediment compared with soil that has been left undisturbed,\" says Jenny Booth, the first author of the study. \"This effect was similar in all three locations, with the burrow-dwelling bacteria being taxonomically different but functionally similar,\" she adds. Microorganisms play important roles in driving global biochemical cycles, such as the nitrogen cycle, in which nitrogen—a building block of proteins and nucleic acids— circulates among the earth, the atmosphere and marine ecosystems. A dense population of fiddler crabs grazes at low tide in Mngazana, South Africa. Credit: Marco Fusi Microbial ecologist Daniele Daffonchio and his team at KAUST's Red Sea Research Centerhypothesized that bacteria present within the same model system had similar functions, rather than similar taxonomy, even when these systems existed in very different local environmental conditions. To test this, they sampled the sediment in and around the burrows created by mangrove-dwelling fiddler crabs in two locations on the Saudi Red Sea and a third in South Africa. The researchers say their findings could be explained by the fact that burrowing leads to similar changes in the sediment regardless of location. Crabs typically bring sediment up from deeper layers onto the surface and vice versa. This sediment mixing changes the biochemical composition of the surrounding sediment, creating a hotspot of oxidative reactions and changing the types of bacteria living there. Burrow sediment, for example, has more bacteria that use oxygen for respiration, while the surrounding bulk soils have more bacteria that employ anaerobic respiration mechanisms. Sediment mixing also increases nutrient availability, and thus bacterial activity, within the burrow soils. Farasan Island mangrove forest in southwestern Saudi Arabia, one of the three study sites. Credit: Marco Fusi The researchers estimate that the halo-like ring of biochemical and microbial changes that extend a small distance around the fiddler crab burrows can influence up to 35 percent of mangrove sediment. In Kenyan mangroves, where burrow density is very high, this effect can influence almost 80 percent of the sediment. \"We predict that the bioturbation effect of crabs and similar burrowing species has a large overall impact on mangrove ecosystems by altering the nature of the sediment's microbiome. These changes ultimately govern environmental processes, like carbon and nutrient fluxes, in this coastal ecosystem,\" says Daffonchio. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Ecosystem functions are regulated by compositional and functional traits of bacterial communities, shaped by stochastic and deterministic processes. Biogeographical studies have revealed microbial community taxonomy in a given ecosystem to change alongside varying environmental characteristics. Considering that stable functional traits are essential for community stability, we hypothesize that contrasting environmental conditions affect microbial taxonomy rather than function in a model system, testing this in three geographically distinct mangrove forests subjected to intense animal bioturbation (a shared deterministic force). Using a metabarcoding approach combined with sediment microprofiling and biochemistry, we examined vertical and radial sediment profiles of burrows belonging to the pantropical fiddler crab (subfamily Gelasiminae ) in three contrasting mangrove environments across a broad latitudinal range (total samples = 432). Each mangrove was environmentally distinct, reflected in taxonomically different bacterial communities, but communities consistently displayed the same spatial stratification (a halo effect) around the burrow which invariably determined the retention of similar inferred functional community traits independent of the local environment. Introduction Biogeography of microorganisms is determined largely by stochastic processes 1 , 2 , 3 , but deterministic processes, essentially related to their ecological niche, are now known to play a significant role in shaping community composition in a given system 4 , 5 , 6 . The unsurmountable importance of microorganisms as the drivers of global biochemical cycles 7 is reflected in their broad taxonomic and metabolic functional diversity 8 . For many of their diverse metabolic functions, microbial communities exhibit functional redundancy, whereby different taxa are able to perform the same metabolic function 9 , 10 , 11 , for example nitrogen cycling in soil 12 and methanogenesis in bioreactors 13 . For this reason, more recent studies of microbial community structure have tended to focus on functional structure rather than taxonomic structure, with a general consensus of the decoupling of some metabolic functions with taxonomic composition in various environments 14 , 15 , i.e., the conditions of the environment hold more weight in shaping functional group distribution than that of taxonomic composition. Microbial community traits have been compared from the local to continental scale with diversity in both taxonomy and functionality being attributed, across the range of spatial scales, to native environmental conditions 8 . However, due to constraints such as the availability of electron acceptors and heterogeneity in, for example, pH, temperature and salinity 16 , environmental drivers do not explain well the variation in taxonomic composition observed in systems with similar environmental conditions: a pattern which has been observed across many marine and terrestrial systems 10 , 12 , 17 . In a system with the same physico-biochemical features (bromeliad aquatic plants), Louca et al . 10 observed intersystem taxonomic, but not functional, variations in the microbial communities that were not completely explained by the different environmental characteristics. Recently, variation in oceanic environmental conditions was described to be responsible for structuring the function of the marine microbial community, while these conditions were only able to weakly explain taxonomic variation within functional groups 15 . Ecological resilience, and the capacity of a system to adapt to change, is positively influenced by higher functional community diversification, such as denitrifiers or carbon degraders, and increased taxonomic diversification within these functional groups 18 , 19 . Here we hypothesize that in the same model system under contrasting local environmental conditions, such as those occurring across large biogeographical ranges, broad and fine scale microbial functional and interaction patterns, rather than taxonomy, should be conserved around a consistent source of selective pressure. To test this hypothesis, we studied mangrove sediments subjected to the deterministic selective pressure of intense animal bioturbation, a process known to enhance biological activity and modify physical and chemical properties of sediment 20 , 21 , 22 . Mangrove forests are sites of strong environmental selection due to the intrinsic characteristics of intertidal environments and the prevalence of bioturbating organisms that, through the creation of burrows, impose a selective pressure at the interface of aquatic and terrestrial habitats 23 associated with microbial hotspots 24 . Thus, mangrove sediment is an ideal system to explore spatial changes in microbial community traits. Using a fiddler crab burrow as our model, we extended our study over a broad geographical (latitudinal) range to encompass contrasting environments. Results Our geographic range encompassed the sites Thuwal, Farasan and Mngazana (Fig. 1a ), in which we radially sampled sediment ‘Fractions’ around burrows and in surface, subsurface and deep sediment. The mangrove stands in Thuwal, Farasan and Mngazana displayed diverse sediment characteristics in terms of biogeochemistry, metal content and grain size (Supplementary Fig. S1 , Supplementary Table S1 and Supplementary File S2 ). Accordingly, PCoA of bacterial OTU composition segregated the three geographical sites into distinct groups, accounting for 49.9% of dissimilarity in community composition between sites (Fig. 1b ). A significant effect of ‘Site’ ( P = 0.0001) and ‘Burrow’ ( P = 0.0138) was observed on biogeochemistry (PERMANOVA, Supplementary Table S1 ). Sulphate, nitrite and nitrate contributed 76.4% to dissimilarity between Farasan and Thuwal sediment (SIMPER), with nitrite and nitrate being higher in Farasan and sulphate being higher in Thuwal. POC, PON, phosphate and silicate contributed 55.6% to dissimilarity between Mngazana and Thuwal (SIMPER), with the former being more abundant in Thuwal, while PON, phosphate and silicate were more abundant in Mngazana. PIC, phosphate, PON and silicate contributed 67.2% to dissimilarity between Mngazana and Farasan (SIMPER), with PIC being more abundant in Farasan, and phosphate, PON and silicate being more abundant in Mngazana. Figure 1 Study site variation. ( a) Map of study sites: a - Thuwal, b - Farasan, c - Mngazana; (b) Principal coordinates analysis of total bacterial OTU assemblages categorized by site (n = 384); (c) Distance-based redundancy analysis (db-RDA) showing significant biogeochemical drivers of bacterial community composition at each site. Full size image Site-specific bacterial assemblages correlated with site-specific physico-chemical characteristics (Fig. 1c , Supplementary Fig. S2 , Supplementary Table S2 ). Across the three mangrove forests, POC, PON, PIN, nitrate, nitrite and silicate significantly explained bacterial community<|im_end|> <|im_start|>assistant The types of bacteria living in and around fiddler crab burrows vary widely between mangroves, but their functional activities are remarkably similar. The types of bacteria present in and around mangrove fiddler crab burrows in three different geographic locations were compared by KAUST researchers. They found that the crabs' burrowing activity changed the sediment in a way that attracted different types of bacteria across the three locations: however, the bacteria performed similar functions, such as aerobic respiration, and potential ecological services, such as turnover of organic matter. "Mangrove crabs act like ecosystem engineers: Their burrows create radial, halo-like microbiological and geochemical modifications to the surrounding sediment compared with soil that has been left undisturbed," says Jenny Booth, the first author of the study. "This effect was similar in all three locations, with the burrow-dwelling bacteria being taxonomically different but functionally similar," she adds. Microorganisms play important roles in driving global biochemical cycles, such as the nitrogen cycle, in which nitrogen—a building block of proteins and nucleic acids— circulates among the earth, the atmosphere and marine ecosystems. A dense population of fiddler crabs grazes at low tide in Mngazana, South Africa. Credit: Marco Fusi Microbial ecologist Daniele Daffonchio and his team at KAUST's Red Sea Research Centerhypothesized that bacteria present within the same model system had similar functions, rather than similar taxonomy, even when these systems existed in very different local environmental conditions. To test this, they sampled the sediment in and around the burrows created by mangrove-dwelling fiddler crabs in two locations on the Saudi Red Sea and a third in South Africa. The researchers say their findings could be explained by the fact that burrowing leads to similar changes in the sediment regardless of location. Crabs typically bring sediment up from deeper layers onto the surface and vice versa. This sediment mixing changes the biochemical composition of the surrounding sediment, creating a hotspot of oxidative reactions and changing the types of bacteria living there. Burrow sediment, for example, has more bacteria that use oxygen for respiration, while the surrounding bulk soils have more bacteria that employ anaerobic respiration mechanisms. Sediment mixing also increases nutrient availability, and thus bacterial activity, within the burrow soils. Farasan Island mangrove forest in southwestern Saudi Arabia, one of the three study sites. Credit: Marco Fusi The researchers estimate that the halo-like ring of biochemical and microbial changes that extend a small distance around the fiddler crab burrows can influence up to 35 percent of mangrove sediment. In Kenyan mangroves, where burrow density is very high, this effect can influence almost 80 percent of the sediment. "We predict that the bioturbation effect of crabs and similar burrowing species has a large overall impact on mangrove ecosystems by altering the nature of the sediment's microbiome. These changes ultimately govern environmental processes, like carbon and nutrient fluxes, in this coastal ecosystem," says Daffonchio. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 469, 24168, 5865, 527, 35319, 555, 40321, 3079, 323, 16003, 25022, 315, 45964, 10977, 11, 27367, 555, 96340, 323, 73449, 11618, 13, 12371, 41632, 32277, 7978, 617, 10675, 75418, 4029, 72906, 304, 264, 2728, 26031, 311, 2349, 16662, 29865, 12434, 17910, 13, 56877, 430, 15528, 16003, 25022, 527, 7718, 369, 4029, 20334, 11, 584, 22601, 27985, 430, 75055, 12434, 4787, 7958, 75418, 72906, 4856, 1109, 734, 304, 264, 1646, 1887, 11, 7649, 420, 304, 2380, 3980, 65031, 12742, 51296, 51515, 36658, 38126, 311, 19428, 10065, 6160, 354, 65916, 320, 64, 6222, 73449, 5457, 570, 12362, 264, 20208, 8362, 3785, 5603, 11093, 449, 59132, 8162, 22579, 8138, 323, 17332, 52755, 11, 584, 25078, 12414, 323, 57936, 59132, 21542, 315, 7951, 1849, 33152, 311, 279, 26346, 51172, 282, 1810, 1565, 60512, 320, 2008, 19521, 480, 40843, 318, 125887, 883, 304, 2380, 75055, 51296, 51515, 22484, 4028, 264, 7353, 6987, 13138, 992, 2134, 320, 5143, 10688, 284, 220, 16739, 570, 9062, 51296, 51515, 574, 57340, 12742, 11, 27000, 304, 3827, 14609, 2740, 2204, 45964, 10977, 11, 719, 10977, 21356, 12882, 279, 1890, 29079, 44397, 2461, 320, 64, 71812, 2515, 8, 2212, 279, 7951, 654, 902, 74614, 11075, 279, 38231, 315, 4528, 68695, 16003, 4029, 25022, 9678, 315, 279, 2254, 4676, 13, 29438, 12371, 41632, 5814, 315, 8162, 76991, 374, 11075, 14090, 555, 96340, 11618, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 719, 73449, 11618, 11, 16168, 5552, 311, 872, 50953, 35149, 11, 527, 1457, 3967, 311, 1514, 264, 5199, 3560, 304, 46620, 4029, 18528, 304, 264, 2728, 1887, 220, 19, 1174, 220, 20, 1174, 220, 21, 662, 578, 69217, 16966, 481, 12939, 315, 8162, 76991, 439, 279, 12050, 315, 3728, 93532, 25492, 220, 22, 374, 27000, 304, 872, 7353, 3827, 48228, 323, 41861, 16003, 20057, 220, 23, 662, 1789, 1690, 315, 872, 17226, 41861, 5865, 11, 75418, 10977, 31324, 16003, 90473, 11, 49001, 2204, 77314, 527, 3025, 311, 2804, 279, 1890, 41861, 734, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 369, 3187, 47503, 33162, 304, 17614, 220, 717, 323, 21747, 276, 52379, 304, 6160, 461, 21846, 220, 1032, 662, 1789, 420, 2944, 11, 810, 3293, 7978, 315, 75418, 4029, 6070, 617, 49890, 311, 5357, 389, 16003, 6070, 4856, 1109, 3827, 48228, 6070, 11, 449, 264, 4689, 24811, 315, 279, 1654, 283, 12127, 315, 1063, 41861, 5865, 449, 3827, 48228, 18528, 304, 5370, 22484, 220, 975, 1174, 220, 868, 1174, 602, 1770, 2637, 279, 4787, 315, 279, 4676, 3412, 810, 4785, 304, 46620, 16003, 1912, 8141, 1109, 430, 315, 3827, 48228, 18528, 13, 18654, 48059, 4029, 25022, 617, 1027, 7863, 505, 279, 2254, 311, 58636, 5569, 449, 20057, 304, 2225, 72906, 323, 15293, 1694, 30706, 11, 4028, 279, 2134, 315, 29079, 29505, 11, 311, 10068, 12434, 4787, 220, 23, 662, 4452, 11, 4245, 311, 17413, 1778, 439, 279, 18539, 315, 17130, 4287, 1105, 323, 30548, 76730, 304, 11, 369, 3187, 11, 37143, 11, 9499, 323, 4371, 13797, 220, 845, 1174, 12434, 12050, 656, 539, 10552, 1664, 279, 23851, 304, 3827, 48228, 18528, 13468, 304, 6067, 449, 4528, 12434, 4787, 25, 264, 5497, 902, 706, 1027, 13468, 4028, 1690, 29691, 323, 80492, 6067, 220, 605, 1174, 220, 717, 1174, 220, 1114, 662, 763, 264, 1887, 449, 279, 1890, 4571, 4042, 1481, 822, 32056, 4519, 320, 65, 442, 12574, 329, 72491, 11012, 705, 9928, 936, 1880, 453, 662, 220, 605, 13468, 82019, 615, 3827, 48228, 11, 719, 539, 16003, 11, 27339, 304, 279, 75418, 10977, 430, 1051, 539, 6724, 11497, 555, 279, 2204, 12434, 17910, 13, 42096, 11, 23851, 304, 18435, 292, 12434, 4787, 574, 7633, 311, 387, 8647, 369, 2080, 1711, 279, 734, 315, 279, 29691, 75418, 4029, 11, 1418, 1521, 4787, 1051, 1193, 3025, 311, 7621, 398, 10552, 3827, 48228, 23851, 2949, 16003, 5315, 220, 868, 662, 37211, 5848, 56062, 11, 323, 279, 8824, 315, 264, 1887, 311, 10737, 311, 2349, 11, 374, 40646, 28160, 555, 5190, 16003, 4029, 21797, 2461, 11, 1778, 439, 3453, 22288, 12099, 477, 12782, 409, 911, 6527, 11, 323, 7319, 3827, 48228, 21797, 2461, 2949, 1521, 16003, 5315, 220, 972, 1174, 220, 777, 662, 5810, 584, 22601, 27985, 430, 304, 279, 1890, 1646, 1887, 1234, 75055, 2254, 12434, 4787, 11, 1778, 439, 1884, 31965, 4028, 3544, 6160, 41632, 32277, 21986, 11, 7353, 323, 7060, 5569, 75418, 16003, 323, 16628, 12912, 11, 4856, 1109, 72906, 11, 1288, 387, 1615, 2841, 2212, 264, 13263, 2592, 315, 44010, 7410, 13, 2057, 1296, 420, 31178, 11, 584, 20041, 51296, 51515, 11163, 12843, 38126, 311, 279, 73449, 44010, 7410, 315, 19428, 10065, 6160, 354, 65916, 11, 264, 1920, 3967, 311, 18885, 24156, 5820, 323, 5719, 7106, 323, 11742, 6012, 315, 59132, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 662, 60148, 51515, 36658, 527, 6732, 315, 3831, 12434, 6727, 4245, 311, 279, 47701, 17910, 315, 958, 25453, 278, 22484, 323, 279, 38009, 315, 6160, 354, 9225, 1113, 44304, 430, 11, 1555, 279, 9886, 315, 7951, 1849, 11, 33330, 264, 44010, 7410, 520, 279, 3834, 315, 72491, 323, 80492, 71699, 220, 1419, 5938, 449, 75418, 4106, 68110, 220, 1187, 662, 14636, 11, 51296, 51515, 59132, 374, 459, 10728, 1887, 311, 13488, 29079, 4442, 304, 75418, 4029, 25022, 13, 12362, 264, 282, 1810, 1565, 60512, 7951, 654, 439, 1057, 1646, 11, 584, 11838, 1057, 4007, 927, 264, 7353, 54001, 320, 5641, 13138, 992, 8, 2134, 311, 38632, 75055, 22484, 13, 18591, 5751, 46139, 2134, 38632, 291, 279, 6732, 36992, 27495, 11, 13759, 46488, 323, 386, 983, 1394, 3444, 320, 30035, 13, 220, 16, 64, 7026, 304, 902, 584, 9038, 34575, 49976, 59132, 3451, 79156, 5247, 529, 2212, 7951, 1849, 323, 304, 7479, 11, 5258, 10730, 323, 5655, 59132, 13, 578, 51296, 51515, 13656, 304, 36992, 27495, 11, 13759, 46488, 323, 386, 983, 1394, 3444, 12882, 17226, 59132, 17910, 304, 3878, 315, 6160, 540, 25634, 52755, 11, 9501, 2262, 323, 24875, 1404, 320, 10254, 67082, 23966, 13, 328, 16, 1174, 99371, 6771, 328, 16, 323, 99371, 2958, 328, 17, 7609, 63909, 11, 6812, 78, 32, 315, 45964, 8775, 52, 18528, 92398, 279, 2380, 54001, 6732, 1139, 12742, 5315, 11, 24043, 369, 220, 2491, 13, 24, 4, 315, 14091, 318, 49325, 304, 4029, 18528, 1990, 6732, 320, 30035, 13, 220, 16, 65, 7609, 362, 5199, 2515, 315, 3451, 18060, 529, 320, 393, 284, 220, 15, 13, 931, 16, 8, 323, 3451, 62339, 654, 529, 320, 393, 284, 220, 15, 13, 16368, 23, 8, 574, 13468, 389, 6160, 540, 25634, 52755, 320, 9851, 23111, 46, 13114, 11, 99371, 6771, 328, 16, 7609, 46962, 764, 349, 11, 25719, 1269, 323, 25719, 7853, 20162, 220, 4767, 13, 19, 4, 311, 14091, 318, 49325, 1990, 13759, 46488, 323, 36992, 27495, 59132, 320, 47716, 9851, 705, 449, 25719, 1269, 323, 25719, 7853, 1694, 5190, 304, 13759, 46488, 323, 83778, 349, 1694, 5190, 304, 36992, 27495, 13, 393, 7767, 11, 393, 715, 11, 79106, 323, 5554, 8630, 20162, 220, 2131, 13, 21, 4, 311, 14091, 318, 49325, 1990, 386, 983, 1394, 3444, 323, 36992, 27495, 320, 47716, 9851, 705, 449, 279, 4846, 1694, 810, 44611, 304, 36992, 27495, 11, 1418, 393, 715, 11, 79106, 323, 5554, 8630, 1051, 810, 44611, 304, 386, 983, 1394, 3444, 13, 61706, 11, 79106, 11, 393, 715, 323, 5554, 8630, 20162, 220, 3080, 13, 17, 4, 311, 14091, 318, 49325, 1990, 386, 983, 1394, 3444, 323, 13759, 46488, 320, 47716, 9851, 705, 449, 61706, 1694, 810, 44611, 304, 13759, 46488, 11, 323, 79106, 11, 393, 715, 323, 5554, 8630, 1694, 810, 44611, 304, 386, 983, 1394, 3444, 13, 19575, 220, 16, 19723, 2816, 23851, 13, 320, 264, 8, 5135, 315, 4007, 6732, 25, 264, 482, 36992, 27495, 11, 293, 482, 13759, 46488, 11, 272, 482, 386, 983, 1394, 3444, 26, 320, 65, 8, 37409, 14259, 6492, 315, 2860, 45964, 8775, 52, 439, 28111, 1154, 71974, 555, 2816, 320, 77, 284, 220, 12910, 1237, 320, 66, 8, 32235, 6108, 90473, 6492, 320, 2042, 11151, 6486, 8, 9204, 5199, 6160, 540, 25634, 32056, 12050, 315, 45964, 4029, 18528, 520, 1855, 2816, 13, 8797, 1404, 2217, 13207, 19440, 45964, 439, 28111, 1154, 49393, 449, 2816, 19440, 4571, 4042, 12, 32056, 17910, 320, 30035, 13, 220, 16, 66, 1174, 99371, 23966, 13, 328, 17, 1174, 99371, 6771, 328, 17, 7609, 58237, 279, 2380, 51296, 51515, 36658, 11, 393, 7767, 11, 393, 715, 11, 28228, 11, 25719, 7853, 11, 25719, 1269, 323, 5554, 8630, 12207, 11497, 45964, 4029, 128257, 198, 128256, 78191, 198, 791, 4595, 315, 24032, 5496, 304, 323, 2212, 282, 1810, 1565, 60512, 7951, 1849, 13592, 13882, 1990, 51296, 299, 2396, 11, 719, 872, 16003, 7640, 527, 49723, 4528, 13, 578, 4595, 315, 24032, 3118, 304, 323, 2212, 51296, 51515, 282, 1810, 1565, 60512, 7951, 1849, 304, 2380, 2204, 46139, 10687, 1051, 7863, 555, 90078, 8721, 12074, 13, 2435, 1766, 430, 279, 1589, 3518, 6, 7951, 25156, 5820, 5614, 279, 59132, 304, 264, 1648, 430, 29123, 2204, 4595, 315, 24032, 4028, 279, 2380, 10687, 25, 4869, 11, 279, 24032, 10887, 4528, 5865, 11, 1778, 439, 91490, 594, 29579, 11, 323, 4754, 50953, 3600, 11, 1778, 439, 48639, 315, 17808, 5030, 13, 330, 44, 526, 51515, 1589, 3518, 1180, 1093, 26031, 25175, 25, 11205, 7951, 1849, 1893, 57936, 11, 71812, 12970, 53499, 5848, 323, 28681, 32056, 29882, 311, 279, 14932, 59132, 7863, 449, 17614, 430, 706, 1027, 2163, 2073, 380, 75325, 1359, 2795, 52179, 64370, 11, 279, 1176, 3229, 315, 279, 4007, 13, 330, 2028, 2515, 574, 4528, 304, 682, 2380, 10687, 11, 449, 279, 7951, 654, 1773, 86, 6427, 24032, 1694, 3827, 14609, 2740, 2204, 719, 734, 750, 4528, 1359, 1364, 11621, 13, 18654, 76991, 1514, 3062, 13073, 304, 10043, 3728, 93532, 25492, 11, 1778, 439, 279, 47503, 11008, 11, 304, 902, 47503, 29096, 4857, 2565, 315, 28896, 323, 31484, 292, 33969, 2345, 4319, 24031, 4315, 279, 9578, 11, 279, 16975, 323, 29691, 61951, 13, 362, 29050, 7187, 315, 282, 1810, 1565, 1589, 3518, 51933, 288, 520, 3428, 43038, 304, 386, 983, 1394, 3444, 11, 4987, 10384, 13, 16666, 25, 35281, 435, 53913, 18654, 48059, 12208, 16549, 11824, 25641, 423, 2715, 263, 53501, 323, 813, 2128, 520, 90078, 8721, 596, 3816, 15379, 8483, 5955, 71, 60400, 83979, 430, 24032, 3118, 2949, 279, 1890, 1646, 1887, 1047, 4528, 5865, 11, 4856, 1109, 4528, 72906, 11, 1524, 994, 1521, 6067, 25281, 304, 1633, 2204, 2254, 12434, 4787, 13, 2057, 1296, 420, 11, 814, 49976, 279, 59132, 304, 323, 2212, 279, 7951, 1849, 3549, 555, 51296, 51515, 1773, 86, 6427, 282, 1810, 1565, 1589, 3518, 304, 1403, 10687, 389, 279, 18387, 3816, 15379, 323, 264, 4948, 304, 4987, 10384, 13, 578, 12074, 2019, 872, 14955, 1436, 387, 11497, 555, 279, 2144, 430, 7951, 25156, 11767, 311, 4528, 4442, 304, 279, 59132, 15851, 315, 3813, 13, 4656, 3518, 11383, 4546, 59132, 709, 505, 19662, 13931, 8800, 279, 7479, 323, 17192, 46391, 13, 1115, 59132, 27890, 4442, 279, 93532, 18528, 315, 279, 14932, 59132, 11, 6968, 264, 80310, 315, 79401, 25481, 323, 10223, 279, 4595, 315, 24032, 5496, 1070, 13, 12649, 654, 59132, 11, 369, 3187, 11, 706, 810, 24032, 430, 1005, 24463, 369, 594, 29579, 11, 1418, 279, 14932, 20155, 69561, 617, 810, 24032, 430, 3539, 41390, 261, 31906, 594, 29579, 24717, 13, 36378, 3904, 27890, 1101, 12992, 50123, 18539, 11, 323, 8617, 45964, 5820, 11, 2949, 279, 7951, 654, 69561, 13, 13759, 46488, 10951, 51296, 51515, 13952, 304, 99911, 18387, 23931, 11, 832, 315, 279, 2380, 4007, 6732, 13, 16666, 25, 35281, 435, 53913, 578, 12074, 16430, 430, 279, 71812, 12970, 10264, 315, 93532, 323, 75418, 4442, 430, 13334, 264, 2678, 6138, 2212, 279, 282, 1810, 1565, 60512, 7951, 1849, 649, 10383, 709, 311, 220, 1758, 3346, 315, 51296, 51515, 59132, 13, 763, 14594, 8503, 51296, 299, 2396, 11, 1405, 7951, 654, 17915, 374, 1633, 1579, 11, 420, 2515, 649, 10383, 4661, 220, 1490, 3346, 315, 279, 59132, 13, 330, 1687, 7168, 430, 279, 6160, 354, 65916, 2515, 315, 1589, 3518, 323, 4528, 7951, 25156, 9606, 706, 264, 3544, 8244, 5536, 389, 51296, 51515, 61951, 555, 60923, 279, 7138, 315, 279, 59132, 596, 53499, 638, 13, 4314, 4442, 13967, 2633, 12434, 11618, 11, 1093, 12782, 323, 50123, 31405, 288, 11, 304, 420, 35335, 26031, 1359, 2795, 423, 2715, 263, 53501, 13, 220, 128257, 198 ]

2,057

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Subsurface contamination due to excessive nutrient surpluses is a persistent and widespread problem in agricultural areas across Europe. The vulnerability of a particular location to pollution from reactive solutes, such as nitrate, is determined by the interplay between hydrologic transport and biogeochemical transformations. Current studies on the controls of subsurface vulnerability do not consider the transient behaviour of transport dynamics in the root zone. Here, using state-of-the-art hydrologic simulations driven by observed hydroclimatic forcing, we demonstrate the strong spatiotemporal heterogeneity of hydrologic transport dynamics and reveal that these dynamics are primarily controlled by the hydroclimatic gradient of the aridity index across Europe. Contrasting the space-time dynamics of transport times with reactive timescales of denitrification in soil indicate that ~75% of the cultivated areas across Europe are potentially vulnerable to nitrate leaching for at least one-third of the year. We find that neglecting the transient nature of transport and reaction timescale results in a great underestimation of the extent of vulnerable regions by almost 50%. Therefore, future vulnerability and risk assessment studies must account for the transient behaviour of transport and biogeochemical transformation processes. Introduction Despite >15 years of water quality protection implementation under the EU Water Framework Directive (EU-WFD 1 ), the most recent EU-WFD report 2 concludes that the majority of European water bodies do not meet the European Union’s minimum target, with threats coming from a wide range of pollutants. Among these, excess nitrate from agricultural areas was highlighted as a major concern 3 , 4 , 5 , 6 , 7 , 8 . Consequently, the European Nitrate Directive 9 —itself an integral part of the EU-WFD—designates nitrate vulnerable zones (NVZs) as areas at risk from agricultural nitrate pollution and requires prompt actions to improve nitrate management. A number of indices have been developed to delineate these zones 10 , 11 , 12 , 13 . While these indices differ in their conceptual and implementation modes, they are often based on a weighted combination of temporally invariant environmental parameters (e.g., terrain slope, land cover and subsurface properties, mean precipitation). A framework for the delineation of such NVZs based on an integrated understanding of the complex and dynamic interplay between hydrologic transport and biogeochemical turnover is still missing. A major challenge for such a framework is to capture the hydrologic transport capacity or the intrinsic vulnerability to subsurface contamination by diffuse pollutants 11 , 14 . Subsurface transport is particularly elusive and uncertain due to its complex flow patterns. To account for this uncertainty, research has focused on the statistical characterization of transport dynamics through travel-time distributions (TTDs), which capture the journey of water and dissolved solutes through a given subsurface compartment 15 , 16 , 17 , 18 , 19 , 20 . Much work has been based on steady-state TTDs, however, more recently, studies have started to acknowledge the transient nature of TTDs 21 , 22 , 23 , 24 , 25 , 26 , 27 . Typically, such studies have focused on empirical observations at the catchment scale or at a limited number of densely gauged small-scale catchments. While transport dynamics have recently been investigated at larger-scales 28 , there are, however, no studies that systematically examine the transient nature of travel times, identify the main driving forces, and connect them to the reactive behavior of (diffuse) pollutants at regional to continental scales. This information would be relevant for management and decision making. To address this gap, we provide a Europe-wide assessment of hydrologic transport behavior as an integrated measure of the intrinsic vulnerability to subsurface contamination by diffuse pollutants (e.g., nitrate). We then use the case of widespread nitrate contamination across arable lands in Europe to show the unrecognized importance of the transient nature of hydrologic transport in previous vulnerability and risk assessments. Our analysis is based on state-of-the-art continental-scale hydrologic simulations driven by meteorological observations over the period of 1950–2015 combined with the recent theoretical developments for characterizing the transient nature of hydrologic transport dynamics 21 , 22 , 26 , 27 at high spatial and temporal resolutions (0.25 ∘ and daily timescale; see “Methods”). We focus on the root zone because it is the interface between the land surface and deeper subsurface. This zone is the most dynamic and active part of the subsurface and acts as both a hydrologic and a biogeochemical filter, determining the delivery and turnover of surface inputs and the partitioning of flow paths to near and deeper subsurface waters 29 , 30 , 31 . The rooting depth varies across European landscapes depending on, among other geophysical attributes, vegetation types and groundwater table depth 32 . However, our focus in this vulnerability assessment is limited to arable landscapes, we therefore account for the dynamics of the first meter of soil that mostly coincides with the rooting zone for arable lands 33 . We use the dimensionless Damköhler number 34 , 35 , 36 to link the hydrologic and biogeochemical timescales (see “Methods”) and provide an objective measure for the large-scale vulnerability assessment of subsurface nitrate contamination. Our study therefore focuses on Europe-wide vulnerability assessment, i.e., the potential for (excess) nitrate leaching from the root zone to deeper in the subsurface (i.e., vadose zone below rooting depth). We demonstrate the oversimplified (static) nature of previous vulnerability assessment approaches by highlighting the relevance of the transient nature of transport dynamics, and we discuss its ramifications for future assessment and subsequent policy decisions. Our continental-scale analysis demonstrates strong spatiotemporal heterogeneity of hydrologic transport dynamics pronounced throughout the European landscapes, and we show that the (static) vulnerability assessment approach that does not account for such transient features greatly underestimates the extent of vulnerable areas prone to subsurface contamination by excess nitrate leaching. Results and discussion Space-time variability of hydrologic transport times Our continental-scale hydrologic simulations show large space-time heterogeneity in the inferred TTDs, which illustrates the complex, non-linear, and transient nature of transport dynamics in the root zone (Fig. 1 ; see also Supplementary Video). The large spread among the", "role": "user" }, { "content": "Nutrient contamination of groundwater as a result of nitrogen-based fertilizers is a problem in many places in Europe. Calculations by a team of scientists led by the UFZ have shown that over a period of at least four months per year, nitrate can leach into the groundwater and surface water on about three-quarters of Europe's agricultural land. The proportion of areas at risk from nitrate leaching is thus almost twice as large as previously assumed. In agriculture, nitrogen-based fertilizers are often not applied in a way that is appropriate to the location and use. If the level is too high, the plants do not fully take up the nitrogen. As a result, the excess nitrogen is leached into the groundwater and surface water as nitrate—a problem that occurs in several EU countries. For example, in 2018, the European Court of Justice (ECJ) condemned EU countries including Germany for breaching the EU Nitrates Directive. Last year, the EU Commission reminded Germany to implement the ECJ ruling. How much of the nitrogen applied through fertilization can enter the groundwater and surface water as nitrate or is denitrified (i.e. converted to molecular nitrogen and nitrogen oxides and released into the air) depends, among other things, on complex processes in the soil. A team of UFZ researchers and U.S. partners led by hydrologist Dr. Rohini Kumar have now analyzed in more detail which processes determine the fate of excess nitrogen. The focus is on hydrological and biogeochemical processes in the root zone (i.e. the area that extends from the surface of the soil down to a depth of one meter). \"The root zone is the most dynamic and active part of the subsoil, where soil moisture, evaporation and dry/wet phases prominently take effect,\" says Kumar. It acts as both a hydroclimatic and biogeochemical filter between the surface and the deeper subsurface layers. The vulnerability of agricultural land to nitrate leaching has so far been described using static information on land use, soils, and the topography of the landscape, combined with mean precipitation and groundwater levels—without taking into account of their temporal variability. \"However, precipitation and temperatures change daily. This affects evaporation and soil water and ultimately the retention time and water transport to deeper layers. Mean values, as used to describe the static condition, are therefore less appropriate from today's perspective,\" explains Kumar. The researchers therefore use a dynamic approach to calculate how long the dissolved nitrate could remain in the root zone before it leach down to deeper levels. They combine the mHM (mesoscale hydrologic model) developed at the UFZ with calculations of the daily change of water retention and nitrate in the root zone as well as denitrification. With the help of the mHM, scientists can simulate the spatio-temporal distribution of hydrological dynamics as well as transport dynamics occurring in the root zone throughout Europe to the day for the past 65 years. With the new approach, the UFZ researchers conclude that for at least four months per year, almost 75% of Europe's agricultural land is vulnerable to nitrate leaching into groundwater and surface waters. If the static approach is used, this proportion is only 42%. \"Because the spatial-temporal dynamics of water transport have not been taken into account in the vulnerability assessment of delimiting nitrate vulnerable zones, the spatial extent of nitrate vulnerable areas is grossly underestimated,\" concludes co-author and UFZ hydrogeologist Dr. Andreas Musolff. This concerns, among others, areas in the east and north-east of Germany, the Iberian Peninsula, and some Eastern European countries. According to the UFZ researchers, the new findings could better aid to risk management of nitrogen in agriculture. \"Farmers could use the more precise information to more precisely adjust their fertilizer regimes, thereby ensuring that as little nitrate as possible is present in the soil during the particularly critical months,\" says Musolff. This would prevent additional nitrate from entering the groundwater and surface waters. \"This study focussing on the soil zone is a starting point for a comprehensive risk assessment of nitrate loads in the groundwater and surface water. It will be followed by further research on transport and denitrification in the subsoil, groundwater and the surface-waters,\" says Kumar. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Subsurface contamination due to excessive nutrient surpluses is a persistent and widespread problem in agricultural areas across Europe. The vulnerability of a particular location to pollution from reactive solutes, such as nitrate, is determined by the interplay between hydrologic transport and biogeochemical transformations. Current studies on the controls of subsurface vulnerability do not consider the transient behaviour of transport dynamics in the root zone. Here, using state-of-the-art hydrologic simulations driven by observed hydroclimatic forcing, we demonstrate the strong spatiotemporal heterogeneity of hydrologic transport dynamics and reveal that these dynamics are primarily controlled by the hydroclimatic gradient of the aridity index across Europe. Contrasting the space-time dynamics of transport times with reactive timescales of denitrification in soil indicate that ~75% of the cultivated areas across Europe are potentially vulnerable to nitrate leaching for at least one-third of the year. We find that neglecting the transient nature of transport and reaction timescale results in a great underestimation of the extent of vulnerable regions by almost 50%. Therefore, future vulnerability and risk assessment studies must account for the transient behaviour of transport and biogeochemical transformation processes. Introduction Despite >15 years of water quality protection implementation under the EU Water Framework Directive (EU-WFD 1 ), the most recent EU-WFD report 2 concludes that the majority of European water bodies do not meet the European Union’s minimum target, with threats coming from a wide range of pollutants. Among these, excess nitrate from agricultural areas was highlighted as a major concern 3 , 4 , 5 , 6 , 7 , 8 . Consequently, the European Nitrate Directive 9 —itself an integral part of the EU-WFD—designates nitrate vulnerable zones (NVZs) as areas at risk from agricultural nitrate pollution and requires prompt actions to improve nitrate management. A number of indices have been developed to delineate these zones 10 , 11 , 12 , 13 . While these indices differ in their conceptual and implementation modes, they are often based on a weighted combination of temporally invariant environmental parameters (e.g., terrain slope, land cover and subsurface properties, mean precipitation). A framework for the delineation of such NVZs based on an integrated understanding of the complex and dynamic interplay between hydrologic transport and biogeochemical turnover is still missing. A major challenge for such a framework is to capture the hydrologic transport capacity or the intrinsic vulnerability to subsurface contamination by diffuse pollutants 11 , 14 . Subsurface transport is particularly elusive and uncertain due to its complex flow patterns. To account for this uncertainty, research has focused on the statistical characterization of transport dynamics through travel-time distributions (TTDs), which capture the journey of water and dissolved solutes through a given subsurface compartment 15 , 16 , 17 , 18 , 19 , 20 . Much work has been based on steady-state TTDs, however, more recently, studies have started to acknowledge the transient nature of TTDs 21 , 22 , 23 , 24 , 25 , 26 , 27 . Typically, such studies have focused on empirical observations at the catchment scale or at a limited number of densely gauged small-scale catchments. While transport dynamics have recently been investigated at larger-scales 28 , there are, however, no studies that systematically examine the transient nature of travel times, identify the main driving forces, and connect them to the reactive behavior of (diffuse) pollutants at regional to continental scales. This information would be relevant for management and decision making. To address this gap, we provide a Europe-wide assessment of hydrologic transport behavior as an integrated measure of the intrinsic vulnerability to subsurface contamination by diffuse pollutants (e.g., nitrate). We then use the case of widespread nitrate contamination across arable lands in Europe to show the unrecognized importance of the transient nature of hydrologic transport in previous vulnerability and risk assessments. Our analysis is based on state-of-the-art continental-scale hydrologic simulations driven by meteorological observations over the period of 1950–2015 combined with the recent theoretical developments for characterizing the transient nature of hydrologic transport dynamics 21 , 22 , 26 , 27 at high spatial and temporal resolutions (0.25 ∘ and daily timescale; see “Methods”). We focus on the root zone because it is the interface between the land surface and deeper subsurface. This zone is the most dynamic and active part of the subsurface and acts as both a hydrologic and a biogeochemical filter, determining the delivery and turnover of surface inputs and the partitioning of flow paths to near and deeper subsurface waters 29 , 30 , 31 . The rooting depth varies across European landscapes depending on, among other geophysical attributes, vegetation types and groundwater table depth 32 . However, our focus in this vulnerability assessment is limited to arable landscapes, we therefore account for the dynamics of the first meter of soil that mostly coincides with the rooting zone for arable lands 33 . We use the dimensionless Damköhler number 34 , 35 , 36 to link the hydrologic and biogeochemical timescales (see “Methods”) and provide an objective measure for the large-scale vulnerability assessment of subsurface nitrate contamination. Our study therefore focuses on Europe-wide vulnerability assessment, i.e., the potential for (excess) nitrate leaching from the root zone to deeper in the subsurface (i.e., vadose zone below rooting depth). We demonstrate the oversimplified (static) nature of previous vulnerability assessment approaches by highlighting the relevance of the transient nature of transport dynamics, and we discuss its ramifications for future assessment and subsequent policy decisions. Our continental-scale analysis demonstrates strong spatiotemporal heterogeneity of hydrologic transport dynamics pronounced throughout the European landscapes, and we show that the (static) vulnerability assessment approach that does not account for such transient features greatly underestimates the extent of vulnerable areas prone to subsurface contamination by excess nitrate leaching. Results and discussion Space-time variability of hydrologic transport times Our continental-scale hydrologic simulations show large space-time heterogeneity in the inferred TTDs, which illustrates the complex, non-linear, and transient nature of transport dynamics in the root zone (Fig. 1 ; see also Supplementary Video). The large spread among the<|im_end|> <|im_start|>assistant Nutrient contamination of groundwater as a result of nitrogen-based fertilizers is a problem in many places in Europe. Calculations by a team of scientists led by the UFZ have shown that over a period of at least four months per year, nitrate can leach into the groundwater and surface water on about three-quarters of Europe's agricultural land. The proportion of areas at risk from nitrate leaching is thus almost twice as large as previously assumed. In agriculture, nitrogen-based fertilizers are often not applied in a way that is appropriate to the location and use. If the level is too high, the plants do not fully take up the nitrogen. As a result, the excess nitrogen is leached into the groundwater and surface water as nitrate—a problem that occurs in several EU countries. For example, in 2018, the European Court of Justice (ECJ) condemned EU countries including Germany for breaching the EU Nitrates Directive. Last year, the EU Commission reminded Germany to implement the ECJ ruling. How much of the nitrogen applied through fertilization can enter the groundwater and surface water as nitrate or is denitrified (i.e. converted to molecular nitrogen and nitrogen oxides and released into the air) depends, among other things, on complex processes in the soil. A team of UFZ researchers and U.S. partners led by hydrologist Dr. Rohini Kumar have now analyzed in more detail which processes determine the fate of excess nitrogen. The focus is on hydrological and biogeochemical processes in the root zone (i.e. the area that extends from the surface of the soil down to a depth of one meter). "The root zone is the most dynamic and active part of the subsoil, where soil moisture, evaporation and dry/wet phases prominently take effect," says Kumar. It acts as both a hydroclimatic and biogeochemical filter between the surface and the deeper subsurface layers. The vulnerability of agricultural land to nitrate leaching has so far been described using static information on land use, soils, and the topography of the landscape, combined with mean precipitation and groundwater levels—without taking into account of their temporal variability. "However, precipitation and temperatures change daily. This affects evaporation and soil water and ultimately the retention time and water transport to deeper layers. Mean values, as used to describe the static condition, are therefore less appropriate from today's perspective," explains Kumar. The researchers therefore use a dynamic approach to calculate how long the dissolved nitrate could remain in the root zone before it leach down to deeper levels. They combine the mHM (mesoscale hydrologic model) developed at the UFZ with calculations of the daily change of water retention and nitrate in the root zone as well as denitrification. With the help of the mHM, scientists can simulate the spatio-temporal distribution of hydrological dynamics as well as transport dynamics occurring in the root zone throughout Europe to the day for the past 65 years. With the new approach, the UFZ researchers conclude that for at least four months per year, almost 75% of Europe's agricultural land is vulnerable to nitrate leaching into groundwater and surface waters. If the static approach is used, this proportion is only 42%. "Because the spatial-temporal dynamics of water transport have not been taken into account in the vulnerability assessment of delimiting nitrate vulnerable zones, the spatial extent of nitrate vulnerable areas is grossly underestimated," concludes co-author and UFZ hydrogeologist Dr. Andreas Musolff. This concerns, among others, areas in the east and north-east of Germany, the Iberian Peninsula, and some Eastern European countries. According to the UFZ researchers, the new findings could better aid to risk management of nitrogen in agriculture. "Farmers could use the more precise information to more precisely adjust their fertilizer regimes, thereby ensuring that as little nitrate as possible is present in the soil during the particularly critical months," says Musolff. This would prevent additional nitrate from entering the groundwater and surface waters. "This study focussing on the soil zone is a starting point for a comprehensive risk assessment of nitrate loads in the groundwater and surface water. It will be followed by further research on transport and denitrification in the subsoil, groundwater and the surface-waters," says Kumar. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 3804, 40846, 47810, 4245, 311, 27639, 50123, 1765, 501, 4881, 374, 264, 26048, 323, 24716, 3575, 304, 29149, 5789, 4028, 4606, 13, 578, 34104, 315, 264, 4040, 3813, 311, 25793, 505, 56563, 2092, 2142, 11, 1778, 439, 25719, 7853, 11, 374, 11075, 555, 279, 958, 1387, 1990, 17055, 25205, 7710, 323, 6160, 540, 25634, 32056, 54070, 13, 9303, 7978, 389, 279, 11835, 315, 5258, 10730, 34104, 656, 539, 2980, 279, 41658, 17432, 315, 7710, 30295, 304, 279, 3789, 10353, 13, 5810, 11, 1701, 1614, 8838, 10826, 38921, 17055, 25205, 47590, 16625, 555, 13468, 17055, 566, 318, 780, 25957, 11, 584, 20461, 279, 3831, 993, 9491, 354, 3342, 10020, 30548, 76730, 315, 17055, 25205, 7710, 30295, 323, 16805, 430, 1521, 30295, 527, 15871, 14400, 555, 279, 17055, 566, 318, 780, 20779, 315, 279, 802, 19025, 1963, 4028, 4606, 13, 35341, 15067, 279, 3634, 7394, 30295, 315, 7710, 3115, 449, 56563, 3115, 31296, 315, 3453, 22288, 2461, 304, 17614, 13519, 430, 4056, 2075, 4, 315, 279, 67166, 5789, 4028, 4606, 527, 13893, 20134, 311, 25719, 7853, 514, 12092, 369, 520, 3325, 832, 30277, 315, 279, 1060, 13, 1226, 1505, 430, 39332, 287, 279, 41658, 7138, 315, 7710, 323, 13010, 3115, 2296, 3135, 304, 264, 2294, 1234, 478, 5582, 315, 279, 13112, 315, 20134, 13918, 555, 4661, 220, 1135, 14697, 15636, 11, 3938, 34104, 323, 5326, 15813, 7978, 2011, 2759, 369, 279, 41658, 17432, 315, 7710, 323, 6160, 540, 25634, 32056, 18475, 11618, 13, 29438, 18185, 871, 868, 1667, 315, 3090, 4367, 9313, 8292, 1234, 279, 10013, 10164, 24686, 57852, 320, 39907, 13299, 14938, 220, 16, 7026, 279, 1455, 3293, 10013, 13299, 14938, 1934, 220, 17, 45537, 430, 279, 8857, 315, 7665, 3090, 13162, 656, 539, 3449, 279, 7665, 9323, 753, 8187, 2218, 11, 449, 18208, 5108, 505, 264, 7029, 2134, 315, 83661, 13, 22395, 1521, 11, 13937, 25719, 7853, 505, 29149, 5789, 574, 27463, 439, 264, 3682, 4747, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 662, 53123, 11, 279, 7665, 50616, 7853, 57852, 220, 24, 2001, 275, 726, 459, 26154, 961, 315, 279, 10013, 13299, 14938, 2345, 25894, 988, 25719, 7853, 20134, 26467, 320, 37426, 57, 82, 8, 439, 5789, 520, 5326, 505, 29149, 25719, 7853, 25793, 323, 7612, 10137, 6299, 311, 7417, 25719, 7853, 6373, 13, 362, 1396, 315, 15285, 617, 1027, 8040, 311, 91784, 349, 1521, 26467, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 662, 6104, 1521, 15285, 1782, 304, 872, 44901, 323, 8292, 20362, 11, 814, 527, 3629, 3196, 389, 264, 37924, 10824, 315, 19502, 750, 58720, 12434, 5137, 320, 68, 1326, 2637, 25911, 31332, 11, 4363, 3504, 323, 5258, 10730, 6012, 11, 3152, 61050, 570, 362, 12914, 369, 279, 91784, 367, 315, 1778, 25464, 57, 82, 3196, 389, 459, 18751, 8830, 315, 279, 6485, 323, 8915, 958, 1387, 1990, 17055, 25205, 7710, 323, 6160, 540, 25634, 32056, 48639, 374, 2103, 7554, 13, 362, 3682, 8815, 369, 1778, 264, 12914, 374, 311, 12602, 279, 17055, 25205, 7710, 8824, 477, 279, 47701, 34104, 311, 5258, 10730, 47810, 555, 55517, 83661, 220, 806, 1174, 220, 975, 662, 3804, 40846, 7710, 374, 8104, 66684, 323, 36218, 4245, 311, 1202, 6485, 6530, 12912, 13, 2057, 2759, 369, 420, 27924, 11, 3495, 706, 10968, 389, 279, 29564, 60993, 315, 7710, 30295, 1555, 5944, 7394, 43785, 320, 15249, 68050, 705, 902, 12602, 279, 11879, 315, 3090, 323, 56767, 2092, 2142, 1555, 264, 2728, 5258, 10730, 44598, 220, 868, 1174, 220, 845, 1174, 220, 1114, 1174, 220, 972, 1174, 220, 777, 1174, 220, 508, 662, 24191, 990, 706, 1027, 3196, 389, 24981, 21395, 350, 17417, 82, 11, 4869, 11, 810, 6051, 11, 7978, 617, 3940, 311, 25670, 279, 41658, 7138, 315, 350, 17417, 82, 220, 1691, 1174, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 1174, 220, 1627, 1174, 220, 1544, 662, 46402, 11, 1778, 7978, 617, 10968, 389, 46763, 24654, 520, 279, 2339, 479, 5569, 477, 520, 264, 7347, 1396, 315, 97617, 13819, 773, 291, 2678, 13230, 2339, 1392, 13, 6104, 7710, 30295, 617, 6051, 1027, 27313, 520, 8294, 1355, 31296, 220, 1591, 1174, 1070, 527, 11, 4869, 11, 912, 7978, 430, 60826, 21635, 279, 41658, 7138, 315, 5944, 3115, 11, 10765, 279, 1925, 10043, 8603, 11, 323, 4667, 1124, 311, 279, 56563, 7865, 315, 320, 13798, 817, 8, 83661, 520, 15481, 311, 58636, 29505, 13, 1115, 2038, 1053, 387, 9959, 369, 6373, 323, 5597, 3339, 13, 2057, 2686, 420, 13225, 11, 584, 3493, 264, 4606, 25480, 15813, 315, 17055, 25205, 7710, 7865, 439, 459, 18751, 6767, 315, 279, 47701, 34104, 311, 5258, 10730, 47810, 555, 55517, 83661, 320, 68, 1326, 2637, 25719, 7853, 570, 1226, 1243, 1005, 279, 1162, 315, 24716, 25719, 7853, 47810, 4028, 802, 481, 12098, 304, 4606, 311, 1501, 279, 97239, 12939, 315, 279, 41658, 7138, 315, 17055, 25205, 7710, 304, 3766, 34104, 323, 5326, 41300, 13, 5751, 6492, 374, 3196, 389, 1614, 8838, 10826, 38921, 58636, 13230, 17055, 25205, 47590, 16625, 555, 42142, 5848, 24654, 927, 279, 4261, 315, 220, 6280, 15, 4235, 679, 20, 11093, 449, 279, 3293, 32887, 26006, 369, 3752, 4954, 279, 41658, 7138, 315, 17055, 25205, 7710, 30295, 220, 1691, 1174, 220, 1313, 1174, 220, 1627, 1174, 220, 1544, 520, 1579, 29079, 323, 37015, 43595, 320, 15, 13, 914, 12264, 246, 323, 7446, 3115, 2296, 26, 1518, 1054, 18337, 65312, 1226, 5357, 389, 279, 3789, 10353, 1606, 433, 374, 279, 3834, 1990, 279, 4363, 7479, 323, 19662, 5258, 10730, 13, 1115, 10353, 374, 279, 1455, 8915, 323, 4642, 961, 315, 279, 5258, 10730, 323, 14385, 439, 2225, 264, 17055, 25205, 323, 264, 6160, 540, 25634, 32056, 4141, 11, 26679, 279, 9889, 323, 48639, 315, 7479, 11374, 323, 279, 17071, 287, 315, 6530, 13006, 311, 3221, 323, 19662, 5258, 10730, 21160, 220, 1682, 1174, 220, 966, 1174, 220, 2148, 662, 578, 87438, 8149, 35327, 4028, 7665, 55890, 11911, 389, 11, 4315, 1023, 3980, 91004, 8365, 11, 54832, 4595, 323, 72329, 2007, 8149, 220, 843, 662, 4452, 11, 1057, 5357, 304, 420, 34104, 15813, 374, 7347, 311, 802, 481, 55890, 11, 584, 9093, 2759, 369, 279, 30295, 315, 279, 1176, 23819, 315, 17614, 430, 10213, 23828, 3422, 449, 279, 87438, 10353, 369, 802, 481, 12098, 220, 1644, 662, 1226, 1005, 279, 13167, 1752, 16758, 74152, 71, 1565, 1396, 220, 1958, 1174, 220, 1758, 1174, 220, 1927, 311, 2723, 279, 17055, 25205, 323, 6160, 540, 25634, 32056, 3115, 31296, 320, 4151, 1054, 18337, 33611, 323, 3493, 459, 16945, 6767, 369, 279, 3544, 13230, 34104, 15813, 315, 5258, 10730, 25719, 7853, 47810, 13, 5751, 4007, 9093, 24400, 389, 4606, 25480, 34104, 15813, 11, 602, 1770, 2637, 279, 4754, 369, 320, 327, 1140, 8, 25719, 7853, 514, 12092, 505, 279, 3789, 10353, 311, 19662, 304, 279, 5258, 10730, 320, 72, 1770, 2637, 71952, 974, 10353, 3770, 87438, 8149, 570, 1226, 20461, 279, 17918, 74937, 320, 2020, 8, 7138, 315, 3766, 34104, 15813, 20414, 555, 39686, 279, 41961, 315, 279, 41658, 7138, 315, 7710, 30295, 11, 323, 584, 4358, 1202, 85450, 369, 3938, 15813, 323, 17876, 4947, 11429, 13, 5751, 58636, 13230, 6492, 32216, 3831, 993, 9491, 354, 3342, 10020, 30548, 76730, 315, 17055, 25205, 7710, 30295, 38617, 6957, 279, 7665, 55890, 11, 323, 584, 1501, 430, 279, 320, 2020, 8, 34104, 15813, 5603, 430, 1587, 539, 2759, 369, 1778, 41658, 4519, 19407, 1234, 478, 48571, 279, 13112, 315, 20134, 5789, 38097, 311, 5258, 10730, 47810, 555, 13937, 25719, 7853, 514, 12092, 13, 18591, 323, 10430, 11746, 7394, 54709, 315, 17055, 25205, 7710, 3115, 5751, 58636, 13230, 17055, 25205, 47590, 1501, 3544, 3634, 7394, 30548, 76730, 304, 279, 68695, 350, 17417, 82, 11, 902, 46480, 279, 6485, 11, 2536, 62399, 11, 323, 41658, 7138, 315, 7710, 30295, 304, 279, 3789, 10353, 320, 30035, 13, 220, 16, 2652, 1518, 1101, 99371, 8519, 570, 578, 3544, 9041, 4315, 279, 128257, 198, 128256, 78191, 198, 79570, 13283, 47810, 315, 72329, 439, 264, 1121, 315, 47503, 6108, 36214, 12509, 374, 264, 3575, 304, 1690, 7634, 304, 4606, 13, 32459, 811, 555, 264, 2128, 315, 14248, 6197, 555, 279, 69692, 57, 617, 6982, 430, 927, 264, 4261, 315, 520, 3325, 3116, 4038, 824, 1060, 11, 25719, 7853, 649, 514, 613, 1139, 279, 72329, 323, 7479, 3090, 389, 922, 2380, 83641, 315, 4606, 596, 29149, 4363, 13, 578, 21801, 315, 5789, 520, 5326, 505, 25719, 7853, 514, 12092, 374, 8617, 4661, 11157, 439, 3544, 439, 8767, 19655, 13, 763, 30029, 11, 47503, 6108, 36214, 12509, 527, 3629, 539, 9435, 304, 264, 1648, 430, 374, 8475, 311, 279, 3813, 323, 1005, 13, 1442, 279, 2237, 374, 2288, 1579, 11, 279, 11012, 656, 539, 7373, 1935, 709, 279, 47503, 13, 1666, 264, 1121, 11, 279, 13937, 47503, 374, 514, 3939, 1139, 279, 72329, 323, 7479, 3090, 439, 25719, 7853, 29096, 3575, 430, 13980, 304, 3892, 10013, 5961, 13, 1789, 3187, 11, 304, 220, 679, 23, 11, 279, 7665, 7301, 315, 12007, 320, 7650, 41, 8, 39025, 10013, 5961, 2737, 10057, 369, 5395, 12092, 279, 10013, 452, 22288, 988, 57852, 13, 8155, 1060, 11, 279, 10013, 9849, 31256, 10057, 311, 4305, 279, 21283, 41, 17864, 13, 2650, 1790, 315, 279, 47503, 9435, 1555, 36214, 2065, 649, 3810, 279, 72329, 323, 7479, 3090, 439, 25719, 7853, 477, 374, 3453, 22288, 1908, 320, 72, 1770, 13, 16489, 311, 31206, 47503, 323, 47503, 19488, 3422, 323, 6004, 1139, 279, 3805, 8, 14117, 11, 4315, 1023, 2574, 11, 389, 6485, 11618, 304, 279, 17614, 13, 362, 2128, 315, 69692, 57, 12074, 323, 549, 815, 13, 8717, 6197, 555, 17055, 848, 380, 2999, 13, 42087, 6729, 41240, 617, 1457, 30239, 304, 810, 7872, 902, 11618, 8417, 279, 25382, 315, 13937, 47503, 13, 578, 5357, 374, 389, 17055, 31356, 323, 6160, 540, 25634, 32056, 11618, 304, 279, 3789, 10353, 320, 72, 1770, 13, 279, 3158, 430, 2289, 505, 279, 7479, 315, 279, 17614, 1523, 311, 264, 8149, 315, 832, 23819, 570, 330, 791, 3789, 10353, 374, 279, 1455, 8915, 323, 4642, 961, 315, 279, 1207, 708, 321, 11, 1405, 17614, 32257, 11, 3721, 96649, 323, 9235, 6458, 295, 35530, 74088, 1935, 2515, 1359, 2795, 41240, 13, 1102, 14385, 439, 2225, 264, 17055, 566, 318, 780, 323, 6160, 540, 25634, 32056, 4141, 1990, 279, 7479, 323, 279, 19662, 5258, 10730, 13931, 13, 578, 34104, 315, 29149, 4363, 311, 25719, 7853, 514, 12092, 706, 779, 3117, 1027, 7633, 1701, 1118, 2038, 389, 4363, 1005, 11, 69561, 11, 323, 279, 1948, 5814, 315, 279, 18921, 11, 11093, 449, 3152, 61050, 323, 72329, 5990, 2345, 30096, 4737, 1139, 2759, 315, 872, 37015, 54709, 13, 330, 11458, 11, 61050, 323, 20472, 2349, 7446, 13, 1115, 22223, 3721, 96649, 323, 17614, 3090, 323, 13967, 279, 38231, 892, 323, 3090, 7710, 311, 19662, 13931, 13, 16729, 2819, 11, 439, 1511, 311, 7664, 279, 1118, 3044, 11, 527, 9093, 2753, 8475, 505, 3432, 596, 13356, 1359, 15100, 41240, 13, 578, 12074, 9093, 1005, 264, 8915, 5603, 311, 11294, 1268, 1317, 279, 56767, 25719, 7853, 1436, 7293, 304, 279, 3789, 10353, 1603, 433, 514, 613, 1523, 311, 19662, 5990, 13, 2435, 16343, 279, 296, 53248, 320, 9004, 437, 2296, 17055, 25205, 1646, 8, 8040, 520, 279, 69692, 57, 449, 29217, 315, 279, 7446, 2349, 315, 3090, 38231, 323, 25719, 7853, 304, 279, 3789, 10353, 439, 1664, 439, 3453, 22288, 2461, 13, 3161, 279, 1520, 315, 279, 296, 53248, 11, 14248, 649, 38553, 279, 993, 6400, 69290, 10020, 8141, 315, 17055, 31356, 30295, 439, 1664, 439, 7710, 30295, 31965, 304, 279, 3789, 10353, 6957, 4606, 311, 279, 1938, 369, 279, 3347, 220, 2397, 1667, 13, 3161, 279, 502, 5603, 11, 279, 69692, 57, 12074, 32194, 430, 369, 520, 3325, 3116, 4038, 824, 1060, 11, 4661, 220, 2075, 4, 315, 4606, 596, 29149, 4363, 374, 20134, 311, 25719, 7853, 514, 12092, 1139, 72329, 323, 7479, 21160, 13, 1442, 279, 1118, 5603, 374, 1511, 11, 420, 21801, 374, 1193, 220, 2983, 14697, 330, 18433, 279, 29079, 69290, 10020, 30295, 315, 3090, 7710, 617, 539, 1027, 4529, 1139, 2759, 304, 279, 34104, 15813, 315, 1624, 2408, 287, 25719, 7853, 20134, 26467, 11, 279, 29079, 13112, 315, 25719, 7853, 20134, 5789, 374, 20547, 398, 87136, 1359, 45537, 1080, 43802, 323, 69692, 57, 17055, 713, 16549, 2999, 13, 51162, 5444, 337, 544, 13, 1115, 10742, 11, 4315, 3885, 11, 5789, 304, 279, 11226, 323, 10411, 40607, 315, 10057, 11, 279, 358, 655, 1122, 50714, 11, 323, 1063, 18516, 7665, 5961, 13, 10771, 311, 279, 69692, 57, 12074, 11, 279, 502, 14955, 1436, 2731, 12576, 311, 5326, 6373, 315, 47503, 304, 30029, 13, 330, 72094, 388, 1436, 1005, 279, 810, 24473, 2038, 311, 810, 24559, 7652, 872, 65391, 61911, 11, 28592, 23391, 430, 439, 2697, 25719, 7853, 439, 3284, 374, 3118, 304, 279, 17614, 2391, 279, 8104, 9200, 4038, 1359, 2795, 5444, 337, 544, 13, 1115, 1053, 5471, 5217, 25719, 7853, 505, 16661, 279, 72329, 323, 7479, 21160, 13, 330, 2028, 4007, 8413, 1892, 287, 389, 279, 17614, 10353, 374, 264, 6041, 1486, 369, 264, 16195, 5326, 15813, 315, 25719, 7853, 21577, 304, 279, 72329, 323, 7479, 3090, 13, 1102, 690, 387, 8272, 555, 4726, 3495, 389, 7710, 323, 3453, 22288, 2461, 304, 279, 1207, 708, 321, 11, 72329, 323, 279, 7479, 2695, 11796, 1359, 2795, 41240, 13, 220, 128257, 198 ]

2,229

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Guidelines Hypothesis Interesting Images Letter New Book Received Obituary Opinion Perspective Proceeding Paper Project Report Protocol Registered Report Reply Retraction Short Note Study Protocol Systematic Review Technical Note Tutorial Viewpoint All Article Types Advanced Search Section All Sections Cancer Biomarkers Cancer Causes, Screening and Diagnosis Cancer Drug Development Cancer Epidemiology and Prevention Cancer Immunology and Immunotherapy Cancer Informatics and Big Data Cancer Metastasis Cancer Pathophysiology Cancer Therapy Clinical Trials of Cancer Infectious Agents and Cancer Methods and Technologies Development Molecular Cancer Biology Pediatric Oncology Systematic Review or Meta-Analysis in Cancer Research Transplant Oncology and Cancer Nursing Care Tumor Microenvironment All Sections Special Issue All Special Issues \"The 10th International MDM2 Workshop\"—Opening Up New Avenues for MDM2 and p53 Research T Cells and Myeloid Cells in Cancer Immunotherapy Helicobacter pylori Associated Cancer TP53 in Solid Tumors and Hematological Malignancies How Does Obesity Cause Cancer? Methylation Changes in Early Stage Non-small Cell Lung Cancer: New Evidences, Methodological Approaches and Applications Cancer and Liposomes 10th Anniversary of Cancers—Targeted Therapies for Ovarian Cancer Treatment from Bench to Bedside 2nd Edition: Adolescent and Young Adult Oncology 2nd Edition: Advances in the Management of Thyroid Cancer 2nd Edition: Colorectal Cancers 2nd Edition: Combination and Innovative Therapies for Pancreatic Cancer 2nd Edition: Estrogen Receptor-Positive (ER+) Breast Cancers 2nd Edition: New Perspectives of Ocular Oncology 2nd Edition: Resistance Mechanisms in Malignant Brain Tumors 3rd Etnean Occupational Medicine Workshop—Breast Cancer and Work 3D Cell Culture Cancer Models: Development and Applications A Deeper Dive into Signaling Pathways in Cancers A Selection of Papers from the Cancer Therapy 2021 Virtual Scientific Meeting A Selection of Papers from the Meeting on Cancer Science and Targeted Therapy Conference A Special Issue on Tumor Stroma Actionable Mutations in Lung Cancer Acute Myeloid Leukemia Acute Myeloid Leukemia (AML) Acute Myeloid Leukemia: From Diagnosis to Treatment Acute Myeloid Leukemia: The Future Is Bright Acute Promyelocytic Leukemia Acute Promyelocytic Leukemia (APML) Adaptation Strategies of Circulating Tumor Cells Adhesion and Integrins Adjuvant Chemotherapy for Colorectal Cancer Adrenocortical Carcinoma Advance and New Insights in Bladder Cancer Advance in Colorectal Cancer: A Themed Issue in Honor of Prof. Bengt Glimelius Advance in Computational Methods in Cancer Research Advance in Morbidity and Survivorship of Breast Cancer Advance in Supportive and Palliative Care in Cancer Advance Research in Thrombosis and Hematologic Malignancies Advanced Cancer Nanotheranostics Advanced Neuroendocrine Tumors Advanced NSCLC with Oncogene Addiction: An Ongoing Revolution Advanced Ovarian Cancer Advanced Pancreatic Cancer Advanced Prostate Cancer: From Bench to Bedside Advanced Research in Cancer Initiation and Early Detection Advanced Research in Glycoproteins and Cancer Advanced Research in Oncology in 2022 Advanced Research in Oncology in 2023 Advanced Research in Organs-on-a-Chip and Cancer Advanced Research in Pancreatic Ductal Adenocarcinoma Advanced Therapies for Hematological Cancers Advances and Research Progress in Hepatocellular Carcinoma Advances in Adrenocortical Carcinoma Research: Diagnosis, Treatment and Prognosis Advances in Antitumor Molecular-Targeted Agents of Urological Cancers Advances in Bone Metastatic Cancer Research Advances in Breast Cancer Brain Metastases Advances in Breast Cancer: A Themed Issue in Honor of Prof. Fernando Schmitt Advances in Breast Cancer: From Pathogenesis to Therapy Advances in Cancer Chemoprevention Advances in Cancer Cachexia Advances in Cancer Data and Statistics Advances in Cancer Disparities Advances in Cancer Epigenetics Advances in Cancer Radiotherapy Advances in Cancer Stem Cell Research Advances in Chordoma Advances in Chronic Lymphocytic Leukaemia (CLL) Research Advances in Diagnosis and Treatment for Bone and Soft Tissue Sarcoma Advances in Diagnosis, Treatment and Management of Endocrine Neoplasms Advances in Diagnostics and Treatment of Head and Neck Cancer Advances in Endometrial Cancer: From Pathogenesis, Pathology Diagnosis and Molecular Classification to Targeted Therapy Advances in Experimental Radiotherapy Advances in Follicular Lymphoma Advances in Genetic and Molecular Approaches to Skin Cancer Advances in Genetics and Epigenetics of Bladder Cancer Advances in Gynecological Oncology: From Pathogenesis to Therapy Advances in Head and Neck Cancer Research Advances in Head and Neck Squamous Cell Carcinoma Advances in Hematological Neoplasms: A Wide Perspective on the 2022 WHO and International Consensus Classifications Advances in HPB/GI Imaging Advances in Human-Papillomavirus-Related Squamous Cell Carcinoma: From Pathogenesis to Treatment Advances in Integrins in Cancer Advances in Locally Advanced and Metastatic Kidney Cancer Advances in Lymphoma, Plasma Cell Myeloma, and Leukemia Diagnostics Advances in Modern Radiation Oncology Advances in Neuroendocrine Neoplasms Advances in NK/T-cell Lymphoma, Epidemiology, Biology and Therapy Advances in Oral Cancers and Precancers Advances in Our Understanding of ALK-Related Cancers: A Selection of Papers from the Joint Annual Meeting of the European Research Initiative for ALK-Related Malignancies (ERIA) and the European Union Marie Curie European Training Network ALKATRAS Advances in Pancreatic Cancer Research Advances in Pancreatic Ductal Adenocarcinoma Diagnosis and Treatment Advances in Papillary Thyroid Cancer Research Advances in Parathyroid Carcinoma: From Bench to Bedside Advances in Plasma Cell Dyscrasias Advances in Precision Medicine: Targeting Known and Emerging Oncogenic Targets in Lung Cancer Advances in Research, Diagnosis and Treatment of Brain Metastases Advances in Salivary Gland Carcinoma Advances in Soft Tissue and Bone Sarcoma Advances in Stimuli-Responsive Nanostructures for Cancer Therapy and Diagnosis Advances in Surgical Management of Colorectal Liver Metastases: Toward a Better Patient Selection, Lower Surgical Stress, and Multidisciplinary Approach Advances in the biological responses to radiation-induced DNA damage: A selection of papers from the Joint 43rd European Radiation Research Society (ERRS) and 20th German Society for Biological Radiation Research (GBS) Annual Meetings Advances in the Diagnosis, Prognosis and Treatment of Diffuse Large B-cell Lymphoma Advances in the Management of Hepatocellular Carcinoma Advances in the Management of Oligometastatic Disease in Non-colorectal Non-neuroendocrine Tumors Advances in the Management of Thyroid Cancer Advances in Thoracic Carcinoma and Translational Research Advances in Thoracic Oncology Advances in Thymic Tumors Advances in Translational Ovarian Cancer Research Advances in Translational Research for Soft Tissue Sarcomas Advances in Treatment for Hepatobiliary and Pancreatic Cancers: Multi-Disciplinary Strategies and Outcome Evaluation Advances in Treatment of Rare Tumors Advances in Triple-Negative Breast Cancer Advances in Tumor Angiogenesis Advances of Brain Mapping in Cancer Research Advances in Head and Neck Cancer Biology and Clinical Management Advances in In Vivo Quantitative and Qualitative Imaging Characterization of Gliomas", "role": "user" }, { "content": "A new article from Liverpool ocular researchers demonstrates that small uveal (intraocular) melanomas are not always harmless, as the current paradigm suggests. Instead, a reasonable proportion of them have molecular genetic alterations, which categorizes them as highly metastatic tumors. The article recommends that they should not be observed but rather treated immediately, to improve patients' chances of survival. The paper shows that uveal melanoma patients with small tumors, when treated within a certain time frame in Liverpool, do indeed have improved outcomes. The study was undertaken by researchers at Liverpool Ocular Oncology Center based at Liverpool University Hospitals NHS Foundation Trust, the Liverpool Ocular Oncology Research Group (LOORG) at the University of Liverpool and with Professor Bertil Damato, formerly of Liverpool and now based at the Ocular Oncology Service at Moorfields Eye Hospital, London. First author Dr. Rumana Hussain, of Liverpool Ocular Oncology Center, said: \"Uveal melanoma is a potentially lethal disease, with a 50% mortality rate from metastatic disease. However, traditionally, small lesions have been monitored rather than treated as it was considered that these are less likely to cause metastatic spread and that local treatment does not influence outcome. \"Liverpool is one of the only ocular oncology centers in the world that offers prognostic biopsies to all of its melanoma patients, and we have therefore collected a large molecular genetic cohort of small tumors. This is the first study to show that over a quarter of these smaller uveal melanomas have lethal genetic mutations, and suggests that we may be able to influence patient survival and mortality outcomes with earlier treatment of these small melanomas. This will cause a massive shift in the approach to such patients, both in terms of management of their primary tumor, but also in terms of the consideration of prognostic biopsies in small ocular cancers.\" The Liverpool Ocular Oncology Research Group's mission is to conduct high quality basic, translational and clinical research into the pathogenesis and treatment of adult ocular tumors that will improve patient care and survival. Together with Dr. Helen Kalirai, Professor Sarah Coupland leads the basic science and translational research portfolio, in addition to being a diagnostic Consultant Pathologist at the Liverpool University Hospitals Foundation Trust. Sarah leads one of the four NHSE supra-regional Ophthalmic Pathology services, and has led the molecular oncology prognostication service for around 10 years. Professor Heinrich Heimann leads the clinical research portfolio of the LOORG and heads the Liverpool Ocular Oncology Center. Professor Sarah Coupland said: \"Since the early 1990s it was clear that uveal melanomas could be divided into differing genetic prognostic groups. This has become even more definitive through studies such as The Cancer Genome Atlas Uveal Melanoma study, to which LOORG significantly contributed. These past analyses, however, were based mainly on large tumors, and very few genetic investigations have been undertaken on small uveal melanomas, which erroneously have all been labeled as 'safe'. Our study using a unique collection of tiny intraocular biopsies of small uveal melanomas with follow-up clinical data, shows that they too can be broken down into 'good' and 'bad' tumors. Instead of watching the latter, they can be treated earlier and thereby increase significantly the chance of cure for these patients\". ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Guidelines Hypothesis Interesting Images Letter New Book Received Obituary Opinion Perspective Proceeding Paper Project Report Protocol Registered Report Reply Retraction Short Note Study Protocol Systematic Review Technical Note Tutorial Viewpoint All Article Types Advanced Search Section All Sections Cancer Biomarkers Cancer Causes, Screening and Diagnosis Cancer Drug Development Cancer Epidemiology and Prevention Cancer Immunology and Immunotherapy Cancer Informatics and Big Data Cancer Metastasis Cancer Pathophysiology Cancer Therapy Clinical Trials of Cancer Infectious Agents and Cancer Methods and Technologies Development Molecular Cancer Biology Pediatric Oncology Systematic Review or Meta-Analysis in Cancer Research Transplant Oncology and Cancer Nursing Care Tumor Microenvironment All Sections Special Issue All Special Issues "The 10th International MDM2 Workshop"—Opening Up New Avenues for MDM2 and p53 Research T Cells and Myeloid Cells in Cancer Immunotherapy Helicobacter pylori Associated Cancer TP53 in Solid Tumors and Hematological Malignancies How Does Obesity Cause Cancer? Methylation Changes in Early Stage Non-small Cell Lung Cancer: New Evidences, Methodological Approaches and Applications Cancer and Liposomes 10th Anniversary of Cancers—Targeted Therapies for Ovarian Cancer Treatment from Bench to Bedside 2nd Edition: Adolescent and Young Adult Oncology 2nd Edition: Advances in the Management of Thyroid Cancer 2nd Edition: Colorectal Cancers 2nd Edition: Combination and Innovative Therapies for Pancreatic Cancer 2nd Edition: Estrogen Receptor-Positive (ER+) Breast Cancers 2nd Edition: New Perspectives of Ocular Oncology 2nd Edition: Resistance Mechanisms in Malignant Brain Tumors 3rd Etnean Occupational Medicine Workshop—Breast Cancer and Work 3D Cell Culture Cancer Models: Development and Applications A Deeper Dive into Signaling Pathways in Cancers A Selection of Papers from the Cancer Therapy 2021 Virtual Scientific Meeting A Selection of Papers from the Meeting on Cancer Science and Targeted Therapy Conference A Special Issue on Tumor Stroma Actionable Mutations in Lung Cancer Acute Myeloid Leukemia Acute Myeloid Leukemia (AML) Acute Myeloid Leukemia: From Diagnosis to Treatment Acute Myeloid Leukemia: The Future Is Bright Acute Promyelocytic Leukemia Acute Promyelocytic Leukemia (APML) Adaptation Strategies of Circulating Tumor Cells Adhesion and Integrins Adjuvant Chemotherapy for Colorectal Cancer Adrenocortical Carcinoma Advance and New Insights in Bladder Cancer Advance in Colorectal Cancer: A Themed Issue in Honor of Prof. Bengt Glimelius Advance in Computational Methods in Cancer Research Advance in Morbidity and Survivorship of Breast Cancer Advance in Supportive and Palliative Care in Cancer Advance Research in Thrombosis and Hematologic Malignancies Advanced Cancer Nanotheranostics Advanced Neuroendocrine Tumors Advanced NSCLC with Oncogene Addiction: An Ongoing Revolution Advanced Ovarian Cancer Advanced Pancreatic Cancer Advanced Prostate Cancer: From Bench to Bedside Advanced Research in Cancer Initiation and Early Detection Advanced Research in Glycoproteins and Cancer Advanced Research in Oncology in 2022 Advanced Research in Oncology in 2023 Advanced Research in Organs-on-a-Chip and Cancer Advanced Research in Pancreatic Ductal Adenocarcinoma Advanced Therapies for Hematological Cancers Advances and Research Progress in Hepatocellular Carcinoma Advances in Adrenocortical Carcinoma Research: Diagnosis, Treatment and Prognosis Advances in Antitumor Molecular-Targeted Agents of Urological Cancers Advances in Bone Metastatic Cancer Research Advances in Breast Cancer Brain Metastases Advances in Breast Cancer: A Themed Issue in Honor of Prof. Fernando Schmitt Advances in Breast Cancer: From Pathogenesis to Therapy Advances in Cancer Chemoprevention Advances in Cancer Cachexia Advances in Cancer Data and Statistics Advances in Cancer Disparities Advances in Cancer Epigenetics Advances in Cancer Radiotherapy Advances in Cancer Stem Cell Research Advances in Chordoma Advances in Chronic Lymphocytic Leukaemia (CLL) Research Advances in Diagnosis and Treatment for Bone and Soft Tissue Sarcoma Advances in Diagnosis, Treatment and Management of Endocrine Neoplasms Advances in Diagnostics and Treatment of Head and Neck Cancer Advances in Endometrial Cancer: From Pathogenesis, Pathology Diagnosis and Molecular Classification to Targeted Therapy Advances in Experimental Radiotherapy Advances in Follicular Lymphoma Advances in Genetic and Molecular Approaches to Skin Cancer Advances in Genetics and Epigenetics of Bladder Cancer Advances in Gynecological Oncology: From Pathogenesis to Therapy Advances in Head and Neck Cancer Research Advances in Head and Neck Squamous Cell Carcinoma Advances in Hematological Neoplasms: A Wide Perspective on the 2022 WHO and International Consensus Classifications Advances in HPB/GI Imaging Advances in Human-Papillomavirus-Related Squamous Cell Carcinoma: From Pathogenesis to Treatment Advances in Integrins in Cancer Advances in Locally Advanced and Metastatic Kidney Cancer Advances in Lymphoma, Plasma Cell Myeloma, and Leukemia Diagnostics Advances in Modern Radiation Oncology Advances in Neuroendocrine Neoplasms Advances in NK/T-cell Lymphoma, Epidemiology, Biology and Therapy Advances in Oral Cancers and Precancers Advances in Our Understanding of ALK-Related Cancers: A Selection of Papers from the Joint Annual Meeting of the European Research Initiative for ALK-Related Malignancies (ERIA) and the European Union Marie Curie European Training Network ALKATRAS Advances in Pancreatic Cancer Research Advances in Pancreatic Ductal Adenocarcinoma Diagnosis and Treatment Advances in Papillary Thyroid Cancer Research Advances in Parathyroid Carcinoma: From Bench to Bedside Advances in Plasma Cell Dyscrasias Advances in Precision Medicine: Targeting Known and Emerging Oncogenic Targets in Lung Cancer Advances in Research, Diagnosis and Treatment of Brain Metastases Advances in Salivary Gland Carcinoma Advances in Soft Tissue and Bone Sarcoma Advances in Stimuli-Responsive Nanostructures for Cancer Therapy and Diagnosis Advances in Surgical Management of Colorectal Liver Metastases: Toward a Better Patient Selection, Lower Surgical Stress, and Multidisciplinary Approach Advances in the biological responses to radiation-induced DNA damage: A selection of papers from the Joint 43rd European Radiation Research Society (ERRS) and 20th German Society for Biological Radiation Research (GBS) Annual Meetings Advances in the Diagnosis, Prognosis and Treatment of Diffuse Large B-cell Lymphoma Advances in the Management of Hepatocellular Carcinoma Advances in the Management of Oligometastatic Disease in Non-colorectal Non-neuroendocrine Tumors Advances in the Management of Thyroid Cancer Advances in Thoracic Carcinoma and Translational Research Advances in Thoracic Oncology Advances in Thymic Tumors Advances in Translational Ovarian Cancer Research Advances in Translational Research for Soft Tissue Sarcomas Advances in Treatment for Hepatobiliary and Pancreatic Cancers: Multi-Disciplinary Strategies and Outcome Evaluation Advances in Treatment of Rare Tumors Advances in Triple-Negative Breast Cancer Advances in Tumor Angiogenesis Advances of Brain Mapping in Cancer Research Advances in Head and Neck Cancer Biology and Clinical Management Advances in In Vivo Quantitative and Qualitative Imaging Characterization of Gliomas<|im_end|> <|im_start|>assistant A new article from Liverpool ocular researchers demonstrates that small uveal (intraocular) melanomas are not always harmless, as the current paradigm suggests. Instead, a reasonable proportion of them have molecular genetic alterations, which categorizes them as highly metastatic tumors. The article recommends that they should not be observed but rather treated immediately, to improve patients' chances of survival. The paper shows that uveal melanoma patients with small tumors, when treated within a certain time frame in Liverpool, do indeed have improved outcomes. The study was undertaken by researchers at Liverpool Ocular Oncology Center based at Liverpool University Hospitals NHS Foundation Trust, the Liverpool Ocular Oncology Research Group (LOORG) at the University of Liverpool and with Professor Bertil Damato, formerly of Liverpool and now based at the Ocular Oncology Service at Moorfields Eye Hospital, London. First author Dr. Rumana Hussain, of Liverpool Ocular Oncology Center, said: "Uveal melanoma is a potentially lethal disease, with a 50% mortality rate from metastatic disease. However, traditionally, small lesions have been monitored rather than treated as it was considered that these are less likely to cause metastatic spread and that local treatment does not influence outcome. "Liverpool is one of the only ocular oncology centers in the world that offers prognostic biopsies to all of its melanoma patients, and we have therefore collected a large molecular genetic cohort of small tumors. This is the first study to show that over a quarter of these smaller uveal melanomas have lethal genetic mutations, and suggests that we may be able to influence patient survival and mortality outcomes with earlier treatment of these small melanomas. This will cause a massive shift in the approach to such patients, both in terms of management of their primary tumor, but also in terms of the consideration of prognostic biopsies in small ocular cancers." The Liverpool Ocular Oncology Research Group's mission is to conduct high quality basic, translational and clinical research into the pathogenesis and treatment of adult ocular tumors that will improve patient care and survival. Together with Dr. Helen Kalirai, Professor Sarah Coupland leads the basic science and translational research portfolio, in addition to being a diagnostic Consultant Pathologist at the Liverpool University Hospitals Foundation Trust. Sarah leads one of the four NHSE supra-regional Ophthalmic Pathology services, and has led the molecular oncology prognostication service for around 10 years. Professor Heinrich Heimann leads the clinical research portfolio of the LOORG and heads the Liverpool Ocular Oncology Center. Professor Sarah Coupland said: "Since the early 1990s it was clear that uveal melanomas could be divided into differing genetic prognostic groups. This has become even more definitive through studies such as The Cancer Genome Atlas Uveal Melanoma study, to which LOORG significantly contributed. These past analyses, however, were based mainly on large tumors, and very few genetic investigations have been undertaken on small uveal melanomas, which erroneously have all been labeled as 'safe'. Our study using a unique collection of tiny intraocular biopsies of small uveal melanomas with follow-up clinical data, shows that they too can be broken down into 'good' and 'bad' tumors. Instead of watching the latter, they can be treated earlier and thereby increase significantly the chance of cure for these patients". <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 48528, 39515, 78, 13491, 71770, 12041, 27757, 1561, 6017, 39517, 507, 4590, 3620, 60767, 70288, 41870, 287, 18343, 5907, 8423, 25590, 36639, 8423, 18321, 10608, 16597, 10928, 7181, 19723, 25590, 744, 780, 10506, 27766, 7181, 49107, 2806, 2837, 2052, 13659, 21431, 21844, 7694, 11360, 2052, 60137, 26211, 91608, 91141, 26211, 74105, 11, 70189, 323, 95452, 26211, 26166, 11050, 26211, 88953, 2508, 323, 36947, 26211, 67335, 2508, 323, 67335, 42811, 26211, 31701, 29470, 323, 6295, 2956, 26211, 6344, 561, 10949, 26211, 8092, 85404, 31226, 26211, 40143, 33135, 70544, 315, 26211, 88911, 1245, 51354, 323, 26211, 19331, 323, 25579, 11050, 60825, 26211, 40023, 95936, 77854, 2508, 744, 780, 10506, 477, 16197, 12, 27671, 304, 26211, 8483, 4149, 21494, 77854, 2508, 323, 26211, 46353, 10852, 350, 69361, 18654, 24175, 2052, 60137, 9984, 26292, 2052, 9984, 37543, 330, 791, 220, 605, 339, 7327, 386, 8561, 17, 36202, 66101, 52398, 3216, 1561, 362, 46469, 369, 386, 8561, 17, 323, 281, 4331, 8483, 350, 59190, 323, 3092, 301, 590, 59190, 304, 26211, 67335, 42811, 16183, 292, 677, 2540, 35385, 13915, 26475, 26211, 30170, 4331, 304, 22925, 350, 372, 1105, 323, 33924, 266, 5848, 386, 6750, 32737, 2650, 12838, 95171, 45446, 26211, 30, 57175, 79933, 29240, 304, 23591, 22891, 11842, 34859, 14299, 78336, 26211, 25, 1561, 469, 1325, 2436, 11, 6872, 5848, 19157, 14576, 323, 32625, 26211, 323, 42239, 58375, 220, 605, 339, 47898, 315, 356, 32842, 2345, 6531, 291, 23258, 391, 552, 369, 507, 959, 1122, 26211, 31969, 505, 36358, 311, 13394, 3002, 220, 17, 303, 14398, 25, 98582, 323, 13566, 22919, 77854, 2508, 220, 17, 303, 14398, 25, 91958, 304, 279, 9744, 315, 67675, 1607, 26211, 220, 17, 303, 14398, 25, 4349, 461, 95081, 356, 32842, 220, 17, 303, 14398, 25, 86956, 323, 98669, 23258, 391, 552, 369, 11233, 846, 780, 26211, 220, 17, 303, 14398, 25, 9589, 26252, 1050, 15709, 12, 36590, 320, 643, 37297, 57598, 356, 32842, 220, 17, 303, 14398, 25, 1561, 94985, 315, 507, 22077, 77854, 2508, 220, 17, 303, 14398, 25, 40980, 28901, 13978, 304, 386, 6750, 519, 31417, 350, 372, 1105, 220, 18, 6634, 19421, 818, 276, 85255, 19152, 36202, 2345, 51329, 561, 26211, 323, 5664, 220, 18, 35, 14299, 21023, 26211, 27972, 25, 11050, 323, 32625, 362, 1611, 10653, 89617, 1139, 7220, 6260, 8092, 2336, 304, 356, 32842, 362, 25117, 315, 45231, 505, 279, 26211, 40143, 220, 2366, 16, 21382, 38130, 30155, 362, 25117, 315, 45231, 505, 279, 30155, 389, 26211, 10170, 323, 13791, 291, 40143, 15217, 362, 9984, 26292, 389, 350, 69361, 800, 58084, 5703, 481, 32328, 811, 304, 78336, 26211, 6515, 1088, 3092, 301, 590, 2009, 3178, 22689, 6515, 1088, 3092, 301, 590, 2009, 3178, 22689, 320, 32202, 8, 6515, 1088, 3092, 301, 590, 2009, 3178, 22689, 25, 5659, 95452, 311, 31969, 6515, 1088, 3092, 301, 590, 2009, 3178, 22689, 25, 578, 12781, 2209, 27508, 6515, 1088, 18042, 88, 301, 511, 70504, 2009, 3178, 22689, 6515, 1088, 18042, 88, 301, 511, 70504, 2009, 3178, 22689, 320, 2599, 2735, 8, 59531, 367, 56619, 315, 16741, 15853, 350, 69361, 59190, 2467, 59738, 323, 30101, 1354, 2467, 8783, 77282, 19531, 42811, 369, 4349, 461, 95081, 26211, 2467, 1466, 511, 371, 950, 3341, 18595, 7942, 47396, 323, 1561, 73137, 304, 2563, 21473, 26211, 47396, 304, 4349, 461, 95081, 26211, 25, 362, 666, 16809, 26292, 304, 43044, 315, 8626, 13, 26316, 83, 480, 4763, 301, 9334, 47396, 304, 93028, 19331, 304, 26211, 8483, 47396, 304, 8613, 65, 19025, 323, 65580, 5383, 315, 57598, 26211, 47396, 304, 9365, 535, 323, 72460, 54679, 10852, 304, 26211, 47396, 8483, 304, 666, 442, 65, 10934, 323, 33924, 266, 39227, 386, 6750, 32737, 21844, 26211, 33242, 1605, 276, 537, 1233, 21844, 32359, 408, 78738, 350, 372, 1105, 21844, 3119, 3218, 34, 449, 77854, 34224, 79790, 25, 1556, 507, 86171, 22910, 21844, 507, 959, 1122, 26211, 21844, 11233, 846, 780, 26211, 21844, 1322, 2513, 26211, 25, 5659, 36358, 311, 13394, 3002, 21844, 8483, 304, 26211, 16065, 7246, 323, 23591, 58453, 21844, 8483, 304, 79183, 38828, 5646, 1354, 323, 26211, 21844, 8483, 304, 77854, 2508, 304, 220, 2366, 17, 21844, 8483, 304, 77854, 2508, 304, 220, 2366, 18, 21844, 8483, 304, 34806, 598, 10539, 7561, 30653, 575, 323, 26211, 21844, 8483, 304, 11233, 846, 780, 423, 670, 278, 2467, 268, 511, 8362, 258, 7942, 21844, 23258, 391, 552, 369, 33924, 266, 5848, 356, 32842, 91958, 323, 8483, 16418, 304, 61245, 266, 511, 54230, 3341, 18595, 7942, 91958, 304, 2467, 1466, 511, 371, 950, 3341, 18595, 7942, 8483, 25, 95452, 11, 31969, 323, 1322, 5010, 10934, 91958, 304, 6898, 275, 69361, 60825, 12, 6531, 291, 51354, 315, 549, 299, 31356, 356, 32842, 91958, 304, 46701, 6344, 561, 780, 26211, 8483, 91958, 304, 57598, 26211, 31417, 6344, 561, 2315, 91958, 304, 57598, 26211, 25, 362, 666, 16809, 26292, 304, 43044, 315, 8626, 13, 51485, 5124, 24621, 91958, 304, 57598, 26211, 25, 5659, 8092, 52379, 311, 40143, 91958, 304, 26211, 19531, 454, 265, 7611, 91958, 304, 26211, 356, 613, 327, 689, 91958, 304, 26211, 2956, 323, 25647, 91958, 304, 26211, 4185, 1768, 1385, 91958, 304, 26211, 11266, 6569, 25265, 91958, 304, 26211, 13792, 46755, 91958, 304, 26211, 81948, 14299, 8483, 91958, 304, 921, 541, 7942, 91958, 304, 73782, 445, 32800, 511, 70504, 2009, 26261, 22689, 320, 3218, 43, 8, 8483, 91958, 304, 95452, 323, 31969, 369, 46701, 323, 25046, 350, 11407, 13951, 82945, 91958, 304, 95452, 11, 31969, 323, 9744, 315, 4060, 78738, 4275, 454, 14833, 1026, 91958, 304, 7923, 15920, 323, 31969, 315, 11452, 323, 44055, 26211, 91958, 304, 4060, 4512, 6757, 26211, 25, 5659, 8092, 52379, 11, 8092, 2508, 95452, 323, 60825, 55982, 311, 13791, 291, 40143, 91958, 304, 57708, 13792, 46755, 91958, 304, 40555, 416, 1299, 445, 32800, 7942, 91958, 304, 75226, 323, 60825, 19157, 14576, 311, 28049, 26211, 91958, 304, 84386, 323, 11266, 6569, 25265, 315, 2563, 21473, 26211, 91958, 304, 480, 75030, 5848, 77854, 2508, 25, 5659, 8092, 52379, 311, 40143, 91958, 304, 11452, 323, 44055, 26211, 8483, 91958, 304, 11452, 323, 44055, 20685, 23333, 14299, 3341, 18595, 7942, 91958, 304, 33924, 266, 5848, 4275, 454, 14833, 1026, 25, 362, 33845, 70288, 389, 279, 220, 2366, 17, 40312, 323, 7327, 7440, 13940, 3308, 7174, 91958, 304, 12478, 33, 16169, 40, 65606, 91958, 304, 11344, 9483, 391, 484, 316, 24713, 12, 11948, 20685, 23333, 14299, 3341, 18595, 7942, 25, 5659, 8092, 52379, 311, 31969, 91958, 304, 30101, 1354, 304, 26211, 91958, 304, 13914, 750, 21844, 323, 6344, 561, 780, 32666, 3520, 26211, 91958, 304, 445, 32800, 7942, 11, 65632, 14299, 3092, 301, 7942, 11, 323, 2009, 3178, 22689, 7923, 15920, 91958, 304, 18766, 90326, 77854, 2508, 91958, 304, 32359, 408, 78738, 4275, 454, 14833, 1026, 91958, 304, 71163, 17146, 33001, 445, 32800, 7942, 11, 88953, 2508, 11, 40023, 323, 40143, 91958, 304, 54501, 356, 32842, 323, 42770, 32842, 91958, 304, 5751, 46551, 315, 8927, 42, 12, 11948, 356, 32842, 25, 362, 25117, 315, 45231, 505, 279, 30833, 25992, 30155, 315, 279, 7665, 8483, 38756, 369, 8927, 42, 12, 11948, 386, 6750, 32737, 320, 643, 5987, 8, 323, 279, 7665, 9323, 33116, 13182, 648, 7665, 16543, 8304, 8927, 42, 835, 49, 1950, 91958, 304, 11233, 846, 780, 26211, 8483, 91958, 304, 11233, 846, 780, 423, 670, 278, 2467, 268, 511, 8362, 258, 7942, 95452, 323, 31969, 91958, 304, 32743, 35605, 67675, 1607, 26211, 8483, 91958, 304, 4366, 19682, 1607, 3341, 18595, 7942, 25, 5659, 36358, 311, 13394, 3002, 91958, 304, 65632, 14299, 65142, 5192, 300, 3557, 91958, 304, 52459, 19152, 25, 13791, 287, 49386, 323, 86148, 77854, 29569, 86047, 304, 78336, 26211, 91958, 304, 8483, 11, 95452, 323, 31969, 315, 31417, 6344, 561, 2315, 91958, 304, 8375, 344, 661, 480, 1974, 3341, 18595, 7942, 91958, 304, 25046, 350, 11407, 323, 46701, 13951, 82945, 91958, 304, 71872, 24520, 12, 79895, 64051, 47194, 369, 26211, 40143, 323, 95452, 91958, 304, 71212, 9744, 315, 4349, 461, 95081, 22617, 6344, 561, 2315, 25, 41493, 569, 264, 24327, 30024, 25117, 11, 28636, 71212, 51568, 11, 323, 22950, 307, 3510, 44550, 54184, 91958, 304, 279, 24156, 14847, 311, 25407, 38973, 15922, 5674, 25, 362, 6727, 315, 16064, 505, 279, 30833, 220, 3391, 6634, 7665, 90326, 8483, 13581, 320, 2716, 50, 8, 323, 220, 508, 339, 6063, 13581, 369, 63711, 90326, 8483, 320, 5494, 50, 8, 25992, 86683, 91958, 304, 279, 95452, 11, 1322, 5010, 10934, 323, 31969, 315, 29469, 817, 20902, 426, 33001, 445, 32800, 7942, 91958, 304, 279, 9744, 315, 61245, 266, 511, 54230, 3341, 18595, 7942, 91958, 304, 279, 9744, 315, 507, 7864, 4512, 561, 780, 31974, 304, 11842, 20024, 461, 95081, 11842, 41078, 2868, 408, 78738, 350, 372, 1105, 91958, 304, 279, 9744, 315, 67675, 1607, 26211, 91958, 304, 29550, 94257, 3341, 18595, 7942, 323, 4149, 75, 1697, 8483, 91958, 304, 29550, 94257, 77854, 2508, 91958, 304, 666, 1631, 292, 350, 372, 1105, 91958, 304, 4149, 75, 1697, 507, 959, 1122, 26211, 8483, 91958, 304, 4149, 75, 1697, 8483, 369, 25046, 350, 11407, 13951, 884, 300, 91958, 304, 31969, 369, 61245, 266, 677, 35546, 323, 11233, 846, 780, 356, 32842, 25, 17896, 9607, 3510, 44550, 56619, 323, 95709, 40388, 91958, 304, 31969, 315, 36059, 350, 372, 1105, 91958, 304, 37749, 11500, 15410, 57598, 26211, 91958, 304, 350, 69361, 7568, 72, 52379, 91958, 315, 31417, 39546, 304, 26211, 8483, 91958, 304, 11452, 323, 44055, 26211, 40023, 323, 33135, 9744, 91958, 304, 763, 89268, 32541, 22018, 323, 20143, 22018, 65606, 16007, 2065, 315, 480, 747, 23063, 128257, 198, 128256, 78191, 198, 32, 502, 4652, 505, 25715, 18274, 1299, 12074, 32216, 430, 2678, 577, 41711, 320, 258, 2221, 68797, 8, 68012, 23063, 527, 539, 2744, 53997, 11, 439, 279, 1510, 49340, 13533, 13, 12361, 11, 264, 13579, 21801, 315, 1124, 617, 31206, 19465, 61086, 11, 902, 22824, 4861, 1124, 439, 7701, 68370, 780, 56071, 13, 578, 4652, 40912, 430, 814, 1288, 539, 387, 13468, 719, 4856, 12020, 7214, 11, 311, 7417, 6978, 6, 17393, 315, 20237, 13, 578, 5684, 5039, 430, 577, 41711, 68012, 7942, 6978, 449, 2678, 56071, 11, 994, 12020, 2949, 264, 3738, 892, 4124, 304, 25715, 11, 656, 13118, 617, 13241, 20124, 13, 578, 4007, 574, 45179, 555, 12074, 520, 25715, 507, 22077, 77854, 2508, 5955, 3196, 520, 25715, 3907, 85397, 37381, 5114, 17236, 11, 279, 25715, 507, 22077, 77854, 2508, 8483, 5856, 320, 1623, 46027, 8, 520, 279, 3907, 315, 25715, 323, 449, 17054, 51775, 321, 16758, 4428, 11, 34833, 315, 25715, 323, 1457, 3196, 520, 279, 507, 22077, 77854, 2508, 5475, 520, 84548, 9184, 28929, 15429, 11, 7295, 13, 5629, 3229, 2999, 13, 46332, 3444, 80081, 467, 11, 315, 25715, 507, 22077, 77854, 2508, 5955, 11, 1071, 25, 330, 52, 41711, 68012, 7942, 374, 264, 13893, 45089, 8624, 11, 449, 264, 220, 1135, 4, 29528, 4478, 505, 68370, 780, 8624, 13, 4452, 11, 36342, 11, 2678, 63324, 617, 1027, 41223, 4856, 1109, 12020, 439, 433, 574, 6646, 430, 1521, 527, 2753, 4461, 311, 5353, 68370, 780, 9041, 323, 430, 2254, 6514, 1587, 539, 10383, 15632, 13, 330, 93705, 374, 832, 315, 279, 1193, 18274, 1299, 78970, 2508, 19169, 304, 279, 1917, 430, 6209, 63903, 537, 292, 6160, 3806, 552, 311, 682, 315, 1202, 68012, 7942, 6978, 11, 323, 584, 617, 9093, 14890, 264, 3544, 31206, 19465, 41944, 315, 2678, 56071, 13, 1115, 374, 279, 1176, 4007, 311, 1501, 430, 927, 264, 8502, 315, 1521, 9333, 577, 41711, 68012, 23063, 617, 45089, 19465, 34684, 11, 323, 13533, 430, 584, 1253, 387, 3025, 311, 10383, 8893, 20237, 323, 29528, 20124, 449, 6931, 6514, 315, 1521, 2678, 68012, 23063, 13, 1115, 690, 5353, 264, 11191, 6541, 304, 279, 5603, 311, 1778, 6978, 11, 2225, 304, 3878, 315, 6373, 315, 872, 6156, 36254, 11, 719, 1101, 304, 3878, 315, 279, 18361, 315, 63903, 537, 292, 6160, 3806, 552, 304, 2678, 18274, 1299, 51423, 1210, 578, 25715, 507, 22077, 77854, 2508, 8483, 5856, 596, 9131, 374, 311, 6929, 1579, 4367, 6913, 11, 12215, 1697, 323, 14830, 3495, 1139, 279, 1853, 52379, 323, 6514, 315, 6822, 18274, 1299, 56071, 430, 690, 7417, 8893, 2512, 323, 20237, 13, 32255, 449, 2999, 13, 43881, 27930, 404, 2192, 11, 17054, 21077, 18733, 501, 438, 11767, 279, 6913, 8198, 323, 12215, 1697, 3495, 20136, 11, 304, 5369, 311, 1694, 264, 15439, 56546, 8092, 16549, 520, 279, 25715, 3907, 85397, 5114, 17236, 13, 21077, 11767, 832, 315, 279, 3116, 35931, 937, 67655, 33263, 4001, 507, 81937, 292, 8092, 2508, 3600, 11, 323, 706, 6197, 279, 31206, 78970, 2508, 63903, 537, 20901, 2532, 369, 2212, 220, 605, 1667, 13, 17054, 64782, 14172, 1283, 318, 1036, 11767, 279, 14830, 3495, 20136, 315, 279, 5125, 46027, 323, 14971, 279, 25715, 507, 22077, 77854, 2508, 5955, 13, 17054, 21077, 18733, 501, 438, 1071, 25, 330, 12834, 279, 4216, 220, 2550, 15, 82, 433, 574, 2867, 430, 577, 41711, 68012, 23063, 1436, 387, 18255, 1139, 61469, 19465, 63903, 537, 292, 5315, 13, 1115, 706, 3719, 1524, 810, 45813, 1555, 7978, 1778, 439, 578, 26211, 82917, 43443, 549, 41711, 11220, 276, 7942, 4007, 11, 311, 902, 5125, 46027, 12207, 20162, 13, 4314, 3347, 29060, 11, 4869, 11, 1051, 3196, 14918, 389, 3544, 56071, 11, 323, 1633, 2478, 19465, 26969, 617, 1027, 45179, 389, 2678, 577, 41711, 68012, 23063, 11, 902, 58889, 7162, 617, 682, 1027, 30929, 439, 364, 19193, 4527, 5751, 4007, 1701, 264, 5016, 4526, 315, 13987, 50938, 68797, 6160, 3806, 552, 315, 2678, 577, 41711, 68012, 23063, 449, 1833, 5352, 14830, 828, 11, 5039, 430, 814, 2288, 649, 387, 11102, 1523, 1139, 364, 19045, 6, 323, 364, 14176, 6, 56071, 13, 12361, 315, 10307, 279, 15629, 11, 814, 649, 387, 12020, 6931, 323, 28592, 5376, 12207, 279, 6140, 315, 27208, 369, 1521, 6978, 3343, 220, 128257, 198 ]

2,287

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Clinically, osteoarthritis (OA) pain is significantly associated with synovial inflammation. Identification of the mechanisms driving inflammation could reveal new targets to relieve this prevalent pain state. Herein, a role of polyadenylation in OA synovial samples was investigated, and the potential of the polyadenylation inhibitor cordycepin (3’ deoxyadenosine) to inhibit inflammation as well as to reduce pain and structural OA progression were studied. Joint tissues from people with OA with high or low grade inflammation and non-arthritic post-mortem controls were analysed for the polyadenylation factor CPSF4 and inflammatory markers. Effects of cordycepin on pain behavior and joint pathology were studied in models of OA (intra-articular injection of monosodium iodoacetate in rats and surgical destabilisation of the medial meniscus in mice). Human monocyte-derived macrophages and a mouse macrophage cell line were used to determine effects of cordycepin on nuclear localisation of the inflammatory transcription factor NFĸB and polyadenylation factors (WDR33 and CPSF4). CPSF4 and NFκB expression were increased in synovia from OA patients with high grade inflammation. Cordycepin reduced pain behaviour, synovial inflammation and joint pathology in both OA models. Stimulation of macrophages induced nuclear localisation of NFĸB and polyadenylation factors, effects inhibited by cordycepin. Knockdown of polyadenylation factors also prevented nuclear localisation of NFĸB. The increased expression of polyadenylation factors in OA synovia indicates a new target for analgesia treatments. This is supported by the finding that polyadenylation factors are required for inflammation in macrophages and by the fact that the polyadenylation inhibitor cordycepin attenuates pain and pathology in models of OA. Introduction Osteoarthritis (OA) is a common chronic age-related joint disease, with a significant inflammatory component 1 , 2 , 3 , 4 , and is a leading cause of pain and disability 5 . The pathophysiology of pain in OA is complex. Treatment options are largely limited to lifestyle changes (diet and exercise) and reducing pain with non-steroidal anti-inflammatory drugs [NSAIDS] or opioids which have limited efficacy and problematic side effects. As a result, joint replacement surgery is a common outcome. OA pathology includes synovitis, cartilage damage, osteophytes and subchondral bone changes. The most prevalent symptom of OA is pain, which is associated with inflammation 6 , 7 . Macrophages play a major role in driving synovitis which in turn augments the progression of OA pathogenesis 3 . The nuclear factor kappa B (NF-ĸB) family of transcription factors mediates activation of inflammatory gene expression and is upregulated in chronic inflammatory states such as OA 8 . Upon inflammatory signaling, these transcription factors translocate into the nucleus and trigger the expression of a wide range of immunomodulatory, angiogenic and proliferative factors 9 . Differentiation of osteoclasts involved in bone remodelling is also NFkB-dependent 10 . Cordycepin (3′deoxyadenosine) is an active compound from the caterpillar fungus Cordyceps militaris 11 . The biochemical pathway for cordycepin is well described, once inside the cell it is converted to cordycepin triphosphate (cordyTP) which inhibits the last two steps in messenger RNA synthesis, cleavage and polyadenylation, both in nuclear extracts and tissue culture 12 , 13 . Incorporation of cordyTP into the poly(A) tail traps a protein complex on the incomplete mRNA. This complex includes the polyadenylation factors cleavage and polyadenylation specificity factor subunit 4 (CPSF4) and WD repeat-containing protein 33 (WDR33), as well as other proteins such as nuclear export factors 14 , 15 , 16 . Although it is evident that cordyTP is a polyadenylation inhibitor, other targets of cordycepin, such as adenosine receptors have been proposed 17 , 18 . Previously we showed that cordycepin specifically inhibits inflammatory gene expression in human airway smooth muscle cells. The effects of cordycepin in these cells were consistent with an inhibition of polyadenylation 19 , making this process a putative target for novel anti-inflammatory drugs. Cordycepin has effects on both cartilage and bone, reducing chondrocyte hypertrophy in vitro via down-regulation of runt-related transcription factor 2 (Runx2), matrix metalloproteinases (MMPS) −3 and −13 as well as a disintegrin and metalloproteinase with thrombospondin motifs ( ADAMTS) -4 and -5 20 , 21 , 22 , 23 . Both in vitro and in vivo studies support potential benefits of cordycepin treatment in preventing bone loss through inhibition of osteoclast differentiation and having osteoprotective effects during osteoporosis 24 , 25 , 26 , 27 . Intra-articular knee injection of cordycepin for a period of 4 to 8 weeks ameliorated cartilage damage in osteoarthritic mice 28 , however neither pain or inflammation endpoints were reported 28 . Synovial inflammation is associated with cartilage damage and bone changes in OA, and is significantly associated with joint pain. Anti-inflammatory activity of cordycepin is evident in murine macrophages in vitro and attributed to the repression of NF-ĸB dependent gene expression 19 , 29 , 30 , 31 . However, it is unknown if the effects of cordycepin on inflammation in macrophages can be attributed to effects in polyadenylation or whether this is true in vivo . Identification of the mechanisms driving synovial inflammation have the potential to reveal new targets to relieve OA pain. Here we investigated whether there is evidence for changes in polyadenylation factors in clinical OA synovial samples, and then the potential of the polyadenylation inhibitor cordycepin to reduce pain and structural OA progression and inflammation. Our findings identify polyadenylation as a novel target for analgesic and disease modifying drugs for OA. Materials and Methods Reagents and antibodies All reagents were purchased from Sigma-Aldrich unless otherwise stated. The following antibodies were obtained from Abcam, MMP13 (39012), osterix (22552), VEGF (46154) and nestin (18102). DRAQ5, NFκB p65 (4764) and nestin (47607) antibodies were purchased from Cell Signalling Technology Inc. WDR33 (374466) and ADAMTS5 (83186) antibodies were purchased from Santa Cruz Biotech. CPSF4 antibody was obtained from Protein Tech. PCNA (M0879) and CD68 (M0814) antibodies were obtained from Dako. Alkaline phosphatase and peroxidase kits as well as secondary antibodies were obtained from Vector Labs. MCSF was obtained from R&D Systems. RANKL was obtained from Peprotech. Rodent models of OA Studies were in accordance with UK Home Office Animals (Scientific Procedures) Act", "role": "user" }, { "content": "A substance from a fungus that infects caterpillars could offer new treatment hope for sufferers of osteoarthritis according to new research. Cordycepin is an active compound isolated from the caterpillar fungus Cordyceps militaris and has proved to be effective in treating osteoarthritis by blocking inflammation in a new way, through reducing a process called polyadenylation. The research was undertaken by scientists from the University of Nottingham and supported by funding from Versus Arthritis. The findings have been published today in Scientific Reports. Dr. Cornelia De Moor from the University of Nottingham's School of Pharmacy led the study and said: \"The natural compound cordycepin is derived from a caterpillar fungus which is famous in the Far East for its medicinal properties. In this paper we show that orally administrated cordycepin reduces pain and halts disease progression in animal models of osteoarthritis. Intriguingly, it does this by a different mechanism than any other known anti-inflammatory painkiller, through affecting the last step of making a messenger RNA, polyadenylation. This means that medicines derived from cordycepin may help patients for whom other treatments have failed. We hope that cordycepin will prove to be the founder of a new class of pain killer, the polyadenylation inhibitors. There is a long way to go before a cordycepin derived medicine reaches patients, but our work is very promising we are very excited about the prospects.\" Reducing pain and damage Osteoarthritis (OA) is a common chronic age-related joint disease, with approximately a third of people over the age of 45 seeking treatment for the disease. In osteoarthritis, the cartilage becomes flaky and rough and small pieces break off to form loose bodies in the fluid that lubricates the joint called synovial fluid. This causes irritation and inflammation of the synovial membrane. The loss of cartilage leaves bones unprotected and vulnerable to damage. In this new study it was found that there is an increased expression of polyadenylation factor CPSF4 associated with synovial inflammation in osteoarthritis. CPSF4 and another polyadenylation factor are required for the activation the key inflammatory cells, the macrophages. Administering cordycepin represses the activity of the polyadenylation factors and suppresses inflammation in macrophages. Cordycepin treatment reduced pain behaviour and structural damage in rats and mice with osteoarthritis, supporting a role of polyadenylation in osteoarthritis progression, inflammatory gene expression and pain. Possible new treatment options Treatment options for this painful and debilitating disease are largely limited to lifestyle changes and reducing pain with non-steroidal anti-inflammatory drugs [NSAIDS] or opioids which have limited efficacy and come with problematic side effects. As a result, joint replacement surgery is a common outcome. The results from this new research provides the possibility of a more effective treatment for osteoarthritis suffers that is less toxic, so will have reduced side effects for patients. Dr. Stephen Simpson from Versus Arthritis said: \"Persistent pain is life changing for people with arthritis. This is not good enough and so we are delighted to support this research that has led to these fascinating findings. Previous work by this group has shown this compound has anti-inflammatory effects and in the latest studies support understanding of how this works on cells responsible for inflammation. Although in its early stages, the study has great potential for helping people suffering pain of musculoskeletal conditions and demonstrates the high value and impact of novel discovery-led research on understanding and treating diseases.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Clinically, osteoarthritis (OA) pain is significantly associated with synovial inflammation. Identification of the mechanisms driving inflammation could reveal new targets to relieve this prevalent pain state. Herein, a role of polyadenylation in OA synovial samples was investigated, and the potential of the polyadenylation inhibitor cordycepin (3’ deoxyadenosine) to inhibit inflammation as well as to reduce pain and structural OA progression were studied. Joint tissues from people with OA with high or low grade inflammation and non-arthritic post-mortem controls were analysed for the polyadenylation factor CPSF4 and inflammatory markers. Effects of cordycepin on pain behavior and joint pathology were studied in models of OA (intra-articular injection of monosodium iodoacetate in rats and surgical destabilisation of the medial meniscus in mice). Human monocyte-derived macrophages and a mouse macrophage cell line were used to determine effects of cordycepin on nuclear localisation of the inflammatory transcription factor NFĸB and polyadenylation factors (WDR33 and CPSF4). CPSF4 and NFκB expression were increased in synovia from OA patients with high grade inflammation. Cordycepin reduced pain behaviour, synovial inflammation and joint pathology in both OA models. Stimulation of macrophages induced nuclear localisation of NFĸB and polyadenylation factors, effects inhibited by cordycepin. Knockdown of polyadenylation factors also prevented nuclear localisation of NFĸB. The increased expression of polyadenylation factors in OA synovia indicates a new target for analgesia treatments. This is supported by the finding that polyadenylation factors are required for inflammation in macrophages and by the fact that the polyadenylation inhibitor cordycepin attenuates pain and pathology in models of OA. Introduction Osteoarthritis (OA) is a common chronic age-related joint disease, with a significant inflammatory component 1 , 2 , 3 , 4 , and is a leading cause of pain and disability 5 . The pathophysiology of pain in OA is complex. Treatment options are largely limited to lifestyle changes (diet and exercise) and reducing pain with non-steroidal anti-inflammatory drugs [NSAIDS] or opioids which have limited efficacy and problematic side effects. As a result, joint replacement surgery is a common outcome. OA pathology includes synovitis, cartilage damage, osteophytes and subchondral bone changes. The most prevalent symptom of OA is pain, which is associated with inflammation 6 , 7 . Macrophages play a major role in driving synovitis which in turn augments the progression of OA pathogenesis 3 . The nuclear factor kappa B (NF-ĸB) family of transcription factors mediates activation of inflammatory gene expression and is upregulated in chronic inflammatory states such as OA 8 . Upon inflammatory signaling, these transcription factors translocate into the nucleus and trigger the expression of a wide range of immunomodulatory, angiogenic and proliferative factors 9 . Differentiation of osteoclasts involved in bone remodelling is also NFkB-dependent 10 . Cordycepin (3′deoxyadenosine) is an active compound from the caterpillar fungus Cordyceps militaris 11 . The biochemical pathway for cordycepin is well described, once inside the cell it is converted to cordycepin triphosphate (cordyTP) which inhibits the last two steps in messenger RNA synthesis, cleavage and polyadenylation, both in nuclear extracts and tissue culture 12 , 13 . Incorporation of cordyTP into the poly(A) tail traps a protein complex on the incomplete mRNA. This complex includes the polyadenylation factors cleavage and polyadenylation specificity factor subunit 4 (CPSF4) and WD repeat-containing protein 33 (WDR33), as well as other proteins such as nuclear export factors 14 , 15 , 16 . Although it is evident that cordyTP is a polyadenylation inhibitor, other targets of cordycepin, such as adenosine receptors have been proposed 17 , 18 . Previously we showed that cordycepin specifically inhibits inflammatory gene expression in human airway smooth muscle cells. The effects of cordycepin in these cells were consistent with an inhibition of polyadenylation 19 , making this process a putative target for novel anti-inflammatory drugs. Cordycepin has effects on both cartilage and bone, reducing chondrocyte hypertrophy in vitro via down-regulation of runt-related transcription factor 2 (Runx2), matrix metalloproteinases (MMPS) −3 and −13 as well as a disintegrin and metalloproteinase with thrombospondin motifs ( ADAMTS) -4 and -5 20 , 21 , 22 , 23 . Both in vitro and in vivo studies support potential benefits of cordycepin treatment in preventing bone loss through inhibition of osteoclast differentiation and having osteoprotective effects during osteoporosis 24 , 25 , 26 , 27 . Intra-articular knee injection of cordycepin for a period of 4 to 8 weeks ameliorated cartilage damage in osteoarthritic mice 28 , however neither pain or inflammation endpoints were reported 28 . Synovial inflammation is associated with cartilage damage and bone changes in OA, and is significantly associated with joint pain. Anti-inflammatory activity of cordycepin is evident in murine macrophages in vitro and attributed to the repression of NF-ĸB dependent gene expression 19 , 29 , 30 , 31 . However, it is unknown if the effects of cordycepin on inflammation in macrophages can be attributed to effects in polyadenylation or whether this is true in vivo . Identification of the mechanisms driving synovial inflammation have the potential to reveal new targets to relieve OA pain. Here we investigated whether there is evidence for changes in polyadenylation factors in clinical OA synovial samples, and then the potential of the polyadenylation inhibitor cordycepin to reduce pain and structural OA progression and inflammation. Our findings identify polyadenylation as a novel target for analgesic and disease modifying drugs for OA. Materials and Methods Reagents and antibodies All reagents were purchased from Sigma-Aldrich unless otherwise stated. The following antibodies were obtained from Abcam, MMP13 (39012), osterix (22552), VEGF (46154) and nestin (18102). DRAQ5, NFκB p65 (4764) and nestin (47607) antibodies were purchased from Cell Signalling Technology Inc. WDR33 (374466) and ADAMTS5 (83186) antibodies were purchased from Santa Cruz Biotech. CPSF4 antibody was obtained from Protein Tech. PCNA (M0879) and CD68 (M0814) antibodies were obtained from Dako. Alkaline phosphatase and peroxidase kits as well as secondary antibodies were obtained from Vector Labs. MCSF was obtained from R&D Systems. RANKL was obtained from Peprotech. Rodent models of OA Studies were in accordance with UK Home Office Animals (Scientific Procedures) Act<|im_end|> <|im_start|>assistant A substance from a fungus that infects caterpillars could offer new treatment hope for sufferers of osteoarthritis according to new research. Cordycepin is an active compound isolated from the caterpillar fungus Cordyceps militaris and has proved to be effective in treating osteoarthritis by blocking inflammation in a new way, through reducing a process called polyadenylation. The research was undertaken by scientists from the University of Nottingham and supported by funding from Versus Arthritis. The findings have been published today in Scientific Reports. Dr. Cornelia De Moor from the University of Nottingham's School of Pharmacy led the study and said: "The natural compound cordycepin is derived from a caterpillar fungus which is famous in the Far East for its medicinal properties. In this paper we show that orally administrated cordycepin reduces pain and halts disease progression in animal models of osteoarthritis. Intriguingly, it does this by a different mechanism than any other known anti-inflammatory painkiller, through affecting the last step of making a messenger RNA, polyadenylation. This means that medicines derived from cordycepin may help patients for whom other treatments have failed. We hope that cordycepin will prove to be the founder of a new class of pain killer, the polyadenylation inhibitors. There is a long way to go before a cordycepin derived medicine reaches patients, but our work is very promising we are very excited about the prospects." Reducing pain and damage Osteoarthritis (OA) is a common chronic age-related joint disease, with approximately a third of people over the age of 45 seeking treatment for the disease. In osteoarthritis, the cartilage becomes flaky and rough and small pieces break off to form loose bodies in the fluid that lubricates the joint called synovial fluid. This causes irritation and inflammation of the synovial membrane. The loss of cartilage leaves bones unprotected and vulnerable to damage. In this new study it was found that there is an increased expression of polyadenylation factor CPSF4 associated with synovial inflammation in osteoarthritis. CPSF4 and another polyadenylation factor are required for the activation the key inflammatory cells, the macrophages. Administering cordycepin represses the activity of the polyadenylation factors and suppresses inflammation in macrophages. Cordycepin treatment reduced pain behaviour and structural damage in rats and mice with osteoarthritis, supporting a role of polyadenylation in osteoarthritis progression, inflammatory gene expression and pain. Possible new treatment options Treatment options for this painful and debilitating disease are largely limited to lifestyle changes and reducing pain with non-steroidal anti-inflammatory drugs [NSAIDS] or opioids which have limited efficacy and come with problematic side effects. As a result, joint replacement surgery is a common outcome. The results from this new research provides the possibility of a more effective treatment for osteoarthritis suffers that is less toxic, so will have reduced side effects for patients. Dr. Stephen Simpson from Versus Arthritis said: "Persistent pain is life changing for people with arthritis. This is not good enough and so we are delighted to support this research that has led to these fascinating findings. Previous work by this group has shown this compound has anti-inflammatory effects and in the latest studies support understanding of how this works on cells responsible for inflammation. Although in its early stages, the study has great potential for helping people suffering pain of musculoskeletal conditions and demonstrates the high value and impact of novel discovery-led research on understanding and treating diseases." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 18905, 2740, 11, 52368, 78, 277, 40485, 320, 42439, 8, 6784, 374, 12207, 5938, 449, 6925, 869, 532, 37140, 13, 59776, 315, 279, 24717, 10043, 37140, 1436, 16805, 502, 11811, 311, 48839, 420, 46941, 6784, 1614, 13, 5810, 258, 11, 264, 3560, 315, 10062, 21825, 79933, 304, 81542, 6925, 869, 532, 10688, 574, 27313, 11, 323, 279, 4754, 315, 279, 10062, 21825, 79933, 70785, 23125, 88, 346, 13576, 320, 18, 529, 409, 61263, 21825, 437, 483, 8, 311, 69033, 37140, 439, 1664, 439, 311, 8108, 6784, 323, 24693, 81542, 33824, 1051, 20041, 13, 30833, 39881, 505, 1274, 449, 81542, 449, 1579, 477, 3428, 12239, 37140, 323, 2536, 12, 47601, 50308, 1772, 90653, 336, 11835, 1051, 67458, 369, 279, 10062, 21825, 79933, 8331, 72884, 37, 19, 323, 47288, 24915, 13, 30246, 315, 23125, 88, 346, 13576, 389, 6784, 7865, 323, 10496, 77041, 1051, 20041, 304, 4211, 315, 81542, 320, 258, 2221, 38921, 24553, 26127, 315, 1647, 437, 47876, 602, 6132, 68323, 349, 304, 32510, 323, 34933, 72257, 8082, 315, 279, 97348, 3026, 3510, 355, 304, 24548, 570, 11344, 1647, 79759, 72286, 18563, 764, 1154, 323, 264, 8814, 18563, 764, 425, 2849, 1584, 1051, 1511, 311, 8417, 6372, 315, 23125, 88, 346, 13576, 389, 11499, 2254, 8082, 315, 279, 47288, 46940, 8331, 45827, 128, 116, 33, 323, 10062, 21825, 79933, 9547, 320, 54, 7842, 1644, 323, 72884, 37, 19, 570, 72884, 37, 19, 323, 45827, 68437, 33, 7645, 1051, 7319, 304, 6925, 869, 689, 505, 81542, 6978, 449, 1579, 12239, 37140, 13, 37987, 88, 346, 13576, 11293, 6784, 17432, 11, 6925, 869, 532, 37140, 323, 10496, 77041, 304, 2225, 81542, 4211, 13, 800, 61461, 315, 18563, 764, 1154, 36572, 11499, 2254, 8082, 315, 45827, 128, 116, 33, 323, 10062, 21825, 79933, 9547, 11, 6372, 99669, 555, 23125, 88, 346, 13576, 13, 64894, 2996, 315, 10062, 21825, 79933, 9547, 1101, 32098, 11499, 2254, 8082, 315, 45827, 128, 116, 33, 13, 578, 7319, 7645, 315, 10062, 21825, 79933, 9547, 304, 81542, 6925, 869, 689, 15151, 264, 502, 2218, 369, 3260, 4282, 689, 22972, 13, 1115, 374, 7396, 555, 279, 9455, 430, 10062, 21825, 79933, 9547, 527, 2631, 369, 37140, 304, 18563, 764, 1154, 323, 555, 279, 2144, 430, 279, 10062, 21825, 79933, 70785, 23125, 88, 346, 13576, 57732, 988, 6784, 323, 77041, 304, 4211, 315, 81542, 13, 29438, 507, 5455, 78, 277, 40485, 320, 42439, 8, 374, 264, 4279, 21249, 4325, 14228, 10496, 8624, 11, 449, 264, 5199, 47288, 3777, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 1174, 323, 374, 264, 6522, 5353, 315, 6784, 323, 28353, 220, 20, 662, 578, 1853, 85404, 31226, 315, 6784, 304, 81542, 374, 6485, 13, 31969, 2671, 527, 14090, 7347, 311, 19433, 4442, 320, 94942, 323, 10368, 8, 323, 18189, 6784, 449, 2536, 12, 3751, 71916, 7294, 67595, 11217, 510, 2507, 32, 26696, 60, 477, 84460, 902, 617, 7347, 41265, 323, 36033, 3185, 6372, 13, 1666, 264, 1121, 11, 10496, 14039, 15173, 374, 264, 4279, 15632, 13, 81542, 77041, 5764, 6925, 869, 20000, 11, 7558, 88076, 5674, 11, 52368, 118930, 2392, 323, 1207, 331, 2159, 3545, 17685, 4442, 13, 578, 1455, 46941, 49648, 315, 81542, 374, 6784, 11, 902, 374, 5938, 449, 37140, 220, 21, 1174, 220, 22, 662, 7553, 22761, 1154, 1514, 264, 3682, 3560, 304, 10043, 6925, 869, 20000, 902, 304, 2543, 19861, 1392, 279, 33824, 315, 81542, 1853, 52379, 220, 18, 662, 578, 11499, 8331, 85095, 426, 320, 39167, 12, 128, 116, 33, 8, 3070, 315, 46940, 9547, 25098, 988, 15449, 315, 47288, 15207, 7645, 323, 374, 709, 81722, 304, 21249, 47288, 5415, 1778, 439, 81542, 220, 23, 662, 30538, 47288, 43080, 11, 1521, 46940, 9547, 1380, 23207, 1139, 279, 62607, 323, 8346, 279, 7645, 315, 264, 7029, 2134, 315, 33119, 316, 347, 38220, 11, 92962, 29569, 323, 43036, 1413, 9547, 220, 24, 662, 34496, 7246, 315, 52368, 511, 4354, 82, 6532, 304, 17685, 1323, 347, 6427, 374, 1101, 45827, 82624, 43918, 220, 605, 662, 37987, 88, 346, 13576, 320, 18, 39615, 451, 61263, 21825, 437, 483, 8, 374, 459, 4642, 24549, 505, 279, 29068, 77602, 79902, 37987, 88, 346, 1725, 5440, 42960, 220, 806, 662, 578, 93532, 38970, 369, 23125, 88, 346, 13576, 374, 1664, 7633, 11, 3131, 4871, 279, 2849, 433, 374, 16489, 311, 23125, 88, 346, 13576, 2463, 764, 93473, 320, 32089, 88, 4334, 8, 902, 20747, 1220, 279, 1566, 1403, 7504, 304, 50596, 41214, 39975, 11, 11551, 68256, 323, 10062, 21825, 79933, 11, 2225, 304, 11499, 49062, 323, 20438, 7829, 220, 717, 1174, 220, 1032, 662, 54804, 367, 315, 23125, 88, 4334, 1139, 279, 10062, 4444, 8, 9986, 45660, 264, 13128, 6485, 389, 279, 33243, 78872, 13, 1115, 6485, 5764, 279, 10062, 21825, 79933, 9547, 11551, 68256, 323, 10062, 21825, 79933, 76041, 8331, 1207, 3928, 220, 19, 320, 34, 5119, 37, 19, 8, 323, 64712, 13454, 93871, 13128, 220, 1644, 320, 54, 7842, 1644, 705, 439, 1664, 439, 1023, 28896, 1778, 439, 11499, 7637, 9547, 220, 975, 1174, 220, 868, 1174, 220, 845, 662, 10541, 433, 374, 30576, 430, 23125, 88, 4334, 374, 264, 10062, 21825, 79933, 70785, 11, 1023, 11811, 315, 23125, 88, 346, 13576, 11, 1778, 439, 1008, 71970, 483, 44540, 617, 1027, 11223, 220, 1114, 1174, 220, 972, 662, 59787, 584, 8710, 430, 23125, 88, 346, 13576, 11951, 20747, 1220, 47288, 15207, 7645, 304, 3823, 3805, 3195, 11113, 16124, 7917, 13, 578, 6372, 315, 23125, 88, 346, 13576, 304, 1521, 7917, 1051, 13263, 449, 459, 61478, 315, 10062, 21825, 79933, 220, 777, 1174, 3339, 420, 1920, 264, 2231, 1413, 2218, 369, 11775, 7294, 67595, 11217, 13, 37987, 88, 346, 13576, 706, 6372, 389, 2225, 7558, 88076, 323, 17685, 11, 18189, 523, 2159, 299, 11377, 668, 48855, 58175, 304, 55004, 4669, 1523, 33263, 2987, 315, 1629, 83, 14228, 46940, 8331, 220, 17, 320, 6869, 87, 17, 705, 6303, 9501, 385, 79565, 2315, 320, 8195, 5119, 8, 25173, 18, 323, 25173, 1032, 439, 1664, 439, 264, 834, 81829, 258, 323, 9501, 385, 79565, 521, 449, 84664, 79548, 3595, 258, 84989, 320, 9827, 1428, 10155, 8, 482, 19, 323, 482, 20, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 1174, 220, 1419, 662, 11995, 304, 55004, 323, 304, 41294, 7978, 1862, 4754, 7720, 315, 23125, 88, 346, 13576, 6514, 304, 27252, 17685, 4814, 1555, 61478, 315, 52368, 511, 4354, 60038, 323, 3515, 52368, 454, 4744, 96978, 6372, 2391, 52368, 89766, 10934, 220, 1187, 1174, 220, 914, 1174, 220, 1627, 1174, 220, 1544, 662, 763, 2221, 38921, 24553, 22095, 26127, 315, 23125, 88, 346, 13576, 369, 264, 4261, 315, 220, 19, 311, 220, 23, 5672, 126641, 2521, 660, 7558, 88076, 5674, 304, 52368, 78, 47601, 50308, 24548, 220, 1591, 1174, 4869, 14188, 6784, 477, 37140, 37442, 1051, 5068, 220, 1591, 662, 24028, 869, 532, 37140, 374, 5938, 449, 7558, 88076, 5674, 323, 17685, 4442, 304, 81542, 11, 323, 374, 12207, 5938, 449, 10496, 6784, 13, 23853, 67595, 5820, 315, 23125, 88, 346, 13576, 374, 30576, 304, 8309, 483, 18563, 764, 1154, 304, 55004, 323, 30706, 311, 279, 72498, 315, 45827, 12, 128, 116, 33, 18222, 15207, 7645, 220, 777, 1174, 220, 1682, 1174, 220, 966, 1174, 220, 2148, 662, 4452, 11, 433, 374, 9987, 422, 279, 6372, 315, 23125, 88, 346, 13576, 389, 37140, 304, 18563, 764, 1154, 649, 387, 30706, 311, 6372, 304, 10062, 21825, 79933, 477, 3508, 420, 374, 837, 304, 41294, 662, 59776, 315, 279, 24717, 10043, 6925, 869, 532, 37140, 617, 279, 4754, 311, 16805, 502, 11811, 311, 48839, 81542, 6784, 13, 5810, 584, 27313, 3508, 1070, 374, 6029, 369, 4442, 304, 10062, 21825, 79933, 9547, 304, 14830, 81542, 6925, 869, 532, 10688, 11, 323, 1243, 279, 4754, 315, 279, 10062, 21825, 79933, 70785, 23125, 88, 346, 13576, 311, 8108, 6784, 323, 24693, 81542, 33824, 323, 37140, 13, 5751, 14955, 10765, 10062, 21825, 79933, 439, 264, 11775, 2218, 369, 3260, 4282, 292, 323, 8624, 47141, 11217, 369, 81542, 13, 32009, 323, 19331, 1050, 55975, 323, 59854, 2052, 312, 55975, 1051, 15075, 505, 50637, 6830, 509, 14172, 7389, 6062, 11224, 13, 578, 2768, 59854, 1051, 12457, 505, 3765, 11860, 11, 90304, 1032, 320, 15515, 717, 705, 297, 3751, 953, 320, 11057, 4103, 705, 650, 9560, 37, 320, 19608, 4370, 8, 323, 23634, 258, 320, 10562, 2437, 570, 423, 5726, 48, 20, 11, 45827, 68437, 33, 281, 2397, 320, 22191, 19, 8, 323, 23634, 258, 320, 22191, 2589, 8, 59854, 1051, 15075, 505, 14299, 7220, 17157, 12053, 4953, 13, 468, 7842, 1644, 320, 18265, 21404, 8, 323, 9827, 1428, 10155, 20, 320, 25009, 4218, 8, 59854, 1051, 15075, 505, 16376, 21510, 12371, 59196, 13, 72884, 37, 19, 63052, 574, 12457, 505, 49475, 17829, 13, 6812, 7476, 320, 44, 27311, 24, 8, 323, 11325, 2614, 320, 44, 22534, 19, 8, 59854, 1051, 12457, 505, 25673, 78, 13, 1708, 36641, 483, 33088, 266, 521, 323, 824, 85078, 521, 32596, 439, 1664, 439, 14580, 59854, 1051, 12457, 505, 4290, 41740, 13, 94293, 37, 574, 12457, 505, 432, 33465, 15264, 13, 432, 16395, 43, 574, 12457, 505, 54086, 5646, 331, 13, 13611, 306, 4211, 315, 81542, 19241, 1051, 304, 18859, 449, 6560, 5492, 8410, 47966, 320, 51665, 1104, 75111, 8, 3298, 128257, 198, 128256, 78191, 198, 32, 20278, 505, 264, 79902, 430, 34527, 82, 29068, 50946, 1590, 1436, 3085, 502, 6514, 3987, 369, 96460, 315, 52368, 78, 277, 40485, 4184, 311, 502, 3495, 13, 37987, 88, 346, 13576, 374, 459, 4642, 24549, 25181, 505, 279, 29068, 77602, 79902, 37987, 88, 346, 1725, 5440, 42960, 323, 706, 19168, 311, 387, 7524, 304, 27723, 52368, 78, 277, 40485, 555, 22978, 37140, 304, 264, 502, 1648, 11, 1555, 18189, 264, 1920, 2663, 10062, 21825, 79933, 13, 578, 3495, 574, 45179, 555, 14248, 505, 279, 3907, 315, 67659, 323, 7396, 555, 11006, 505, 25187, 355, 1676, 40485, 13, 578, 14955, 617, 1027, 4756, 3432, 304, 38130, 29140, 13, 2999, 13, 22036, 37029, 1611, 84548, 505, 279, 3907, 315, 67659, 596, 6150, 315, 48175, 6197, 279, 4007, 323, 1071, 25, 330, 791, 5933, 24549, 23125, 88, 346, 13576, 374, 14592, 505, 264, 29068, 77602, 79902, 902, 374, 11495, 304, 279, 13759, 6460, 369, 1202, 58041, 6012, 13, 763, 420, 5684, 584, 1501, 430, 98122, 11398, 660, 23125, 88, 346, 13576, 26338, 6784, 323, 15104, 2641, 8624, 33824, 304, 10065, 4211, 315, 52368, 78, 277, 40485, 13, 61894, 343, 7623, 398, 11, 433, 1587, 420, 555, 264, 2204, 17383, 1109, 904, 1023, 3967, 7294, 67595, 6784, 73178, 11, 1555, 28987, 279, 1566, 3094, 315, 3339, 264, 50596, 41214, 11, 10062, 21825, 79933, 13, 1115, 3445, 430, 39653, 14592, 505, 23125, 88, 346, 13576, 1253, 1520, 6978, 369, 8884, 1023, 22972, 617, 4745, 13, 1226, 3987, 430, 23125, 88, 346, 13576, 690, 12391, 311, 387, 279, 19533, 315, 264, 502, 538, 315, 6784, 25534, 11, 279, 10062, 21825, 79933, 68642, 13, 2684, 374, 264, 1317, 1648, 311, 733, 1603, 264, 23125, 88, 346, 13576, 14592, 16088, 25501, 6978, 11, 719, 1057, 990, 374, 1633, 26455, 584, 527, 1633, 12304, 922, 279, 27949, 1210, 3816, 59144, 6784, 323, 5674, 507, 5455, 78, 277, 40485, 320, 42439, 8, 374, 264, 4279, 21249, 4325, 14228, 10496, 8624, 11, 449, 13489, 264, 4948, 315, 1274, 927, 279, 4325, 315, 220, 1774, 11125, 6514, 369, 279, 8624, 13, 763, 52368, 78, 277, 40485, 11, 279, 7558, 88076, 9221, 1344, 29200, 323, 11413, 323, 2678, 9863, 1464, 1022, 311, 1376, 20784, 13162, 304, 279, 15962, 430, 54494, 988, 279, 10496, 2663, 6925, 869, 532, 15962, 13, 1115, 11384, 66510, 323, 37140, 315, 279, 6925, 869, 532, 39654, 13, 578, 4814, 315, 7558, 88076, 11141, 25896, 94451, 323, 20134, 311, 5674, 13, 763, 420, 502, 4007, 433, 574, 1766, 430, 1070, 374, 459, 7319, 7645, 315, 10062, 21825, 79933, 8331, 72884, 37, 19, 5938, 449, 6925, 869, 532, 37140, 304, 52368, 78, 277, 40485, 13, 72884, 37, 19, 323, 2500, 10062, 21825, 79933, 8331, 527, 2631, 369, 279, 15449, 279, 1401, 47288, 7917, 11, 279, 18563, 764, 1154, 13, 7735, 1601, 287, 23125, 88, 346, 13576, 312, 1911, 288, 279, 5820, 315, 279, 10062, 21825, 79933, 9547, 323, 28321, 288, 37140, 304, 18563, 764, 1154, 13, 37987, 88, 346, 13576, 6514, 11293, 6784, 17432, 323, 24693, 5674, 304, 32510, 323, 24548, 449, 52368, 78, 277, 40485, 11, 12899, 264, 3560, 315, 10062, 21825, 79933, 304, 52368, 78, 277, 40485, 33824, 11, 47288, 15207, 7645, 323, 6784, 13, 37207, 502, 6514, 2671, 31969, 2671, 369, 420, 26175, 323, 92890, 8624, 527, 14090, 7347, 311, 19433, 4442, 323, 18189, 6784, 449, 2536, 12, 3751, 71916, 7294, 67595, 11217, 510, 2507, 32, 26696, 60, 477, 84460, 902, 617, 7347, 41265, 323, 2586, 449, 36033, 3185, 6372, 13, 1666, 264, 1121, 11, 10496, 14039, 15173, 374, 264, 4279, 15632, 13, 578, 3135, 505, 420, 502, 3495, 5825, 279, 13336, 315, 264, 810, 7524, 6514, 369, 52368, 78, 277, 40485, 47521, 430, 374, 2753, 21503, 11, 779, 690, 617, 11293, 3185, 6372, 369, 6978, 13, 2999, 13, 18587, 35766, 505, 25187, 355, 1676, 40485, 1071, 25, 330, 54294, 6784, 374, 2324, 10223, 369, 1274, 449, 55652, 13, 1115, 374, 539, 1695, 3403, 323, 779, 584, 527, 35072, 311, 1862, 420, 3495, 430, 706, 6197, 311, 1521, 27387, 14955, 13, 30013, 990, 555, 420, 1912, 706, 6982, 420, 24549, 706, 7294, 67595, 6372, 323, 304, 279, 5652, 7978, 1862, 8830, 315, 1268, 420, 4375, 389, 7917, 8647, 369, 37140, 13, 10541, 304, 1202, 4216, 18094, 11, 279, 4007, 706, 2294, 4754, 369, 10695, 1274, 16066, 6784, 315, 3167, 79134, 86255, 4787, 323, 32216, 279, 1579, 907, 323, 5536, 315, 11775, 18841, 35054, 3495, 389, 8830, 323, 27723, 19338, 1210, 220, 128257, 198 ]

2,286

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Emerging evidence highlights a critical relationship between gut microbiota and neurocognitive development. Excessive consumption of sugar and other unhealthy dietary factors during early life developmental periods yields changes in the gut microbiome as well as neurocognitive impairments. However, it is unclear whether these two outcomes are functionally connected. Here we explore whether excessive early life consumption of added sugars negatively impacts memory function via the gut microbiome. Rats were given free access to a sugar-sweetened beverage (SSB) during the adolescent stage of development. Memory function and anxiety-like behavior were assessed during adulthood and gut bacterial and brain transcriptome analyses were conducted. Taxa-specific microbial enrichment experiments examined the functional relationship between sugar-induced microbiome changes and neurocognitive and brain transcriptome outcomes. Chronic early life sugar consumption impaired adult hippocampal-dependent memory function without affecting body weight or anxiety-like behavior. Adolescent SSB consumption during adolescence also altered the gut microbiome, including elevated abundance of two species in the genus Parabacteroides ( P. distasonis and P. johnsonii ) that were negatively correlated with hippocampal function. Transferred enrichment of these specific bacterial taxa in adolescent rats impaired hippocampal-dependent memory during adulthood. Hippocampus transcriptome analyses revealed that early life sugar consumption altered gene expression in intracellular kinase and synaptic neurotransmitter signaling pathways, whereas Parabacteroides microbial enrichment altered gene expression in pathways associated with metabolic function, neurodegenerative disease, and dopaminergic signaling. Collectively these results identify a role for microbiota “dysbiosis” in mediating the detrimental effects of early life unhealthy dietary factors on hippocampal-dependent memory function. Introduction The gut microbiome has recently been implicated in modulating neurocognitive development and consequent functioning 1 , 2 , 3 , 4 . Early life developmental periods represent critical windows for the impact of indigenous gut microbes on the brain, as evidenced by the reversal of behavioral and neurochemical abnormalities in germ free rodents when inoculated with conventional microbiota during early life, but not during adulthood 5 , 6 , 7 . Dietary factors are a critical determinant of gut microbiota diversity and can alter gut bacterial communities, as evident from the microbial plasticity observed in response to pre- and probiotic treatment, as well as the “dysbiosis” resulting from consuming unhealthy, yet palatable foods that are associated with obesity and metabolic disorders (e.g., Western diet; foods high in saturated fatty acids and added sugar) 8 . In addition to altering the gut microbiota, consumption of Western dietary factors yields long-lasting memory impairments, and these effects are more pronounced when consumed during early life developmental periods vs. during adulthood 9 , 10 , 11 . Whether diet-induced changes in specific bacterial populations are functionally related to altered early life neurocognitive outcomes, however, is poorly understood. The hippocampus, which is well known for its role in spatial and episodic memory and more recently for regulating learned and social aspects of food intake control 12 , 13 , 14 , 15 , 16 , 17 , is particularly vulnerable to the deleterious effects of Western dietary factors 9 , 18 , 19 . During the juvenile and adolescent stages of development, a time when the brain is rapidly developing, consumption of diets high in saturated fat and sugar 20 , 21 , 22 or sugar alone 23 , 24 , 25 , 26 impairs hippocampal function while in some cases preserving memory processes that do not rely on the hippocampus. While several putative underlying mechanisms have been investigated, the precise biological pathways linking dietary factors to neurocognitive dysfunction remain largely undetermined 11 . Here we aimed to determine whether sugar-induced alterations in gut microbiota during early life are causally related to hippocampal-dependent memory impairments observed during adulthood. Methods and materials Experimental subjects Juvenile male Sprague Dawley rats (Envigo; arrival postnatal day (PN) 26–28; 50–70 g) were housed individually in standard conditions with a 12:12 light/dark cycle. All rats had ad libitum access to water and Lab Diet 5001 (PMI Nutrition International, Brentwood, MO; 29.8 % kcal from protein, 13.4% kcal from fat, 56.7% kcal from carbohydrate), with modifications where noted. Treatment group sizes for Aim 1 experiments are derived from power analyses conducted in Statistica Software (V7) based on our published data, pilot data, and relevant publications in the literature. All experiments were performed in accordance with the approval of the Animal Care and Use Committee at the University of Southern California. Experiment 1 Twenty-one juvenile male rats (PN 26–28) were divided into two groups with equal bodyweight and given ad libitum access to (1) 11% weight-by-volume (w/v) solution containing monosaccharide ratio of 65% fructose and 35% glucose in reverse osmosis-filtered water (SUG; n = 11) or 2) or an extra bottle of reverse osmosis-filtered water (CTL; n = 10). This solution was chosen to model commonly consumed sugar-sweetened beverages (SSBs) in humans in terms of both caloric content and monosaccharide ratio 27 . In addition, all rats were given ad libitum access to water and standard rat chow. Food intake, solution intake, and body weights were monitored thrice-weekly except were prohibited due to behavioral testing. At PN 60, rats underwent Novel Object in Context (NOIC) testing, to measure hippocampal-dependent episodic contextual memory. At PN 67 rats underwent anxiety-like behavior testing in the Zero Maze, followed by body composition testing at PN 70 and an intraperitoneal glucose tolerance test (IP GTT) at PN 84. All behavioral procedures were run at the same time each day (4–6 h into the light cycle). Investigators were blind to animal groups when scoring the behavioral tasks such that the scorers did not know which animal was in which group. Fecal and cecal samples were collected prior to sacrifice at PN 104. In a separate cohort of juvenile male rats ( n = 6/group) animals were treated as above, but on PN day 60 rats were tested in the Novel Object Recognition (NOR) and Open Field (OF) tasks, with two days in between tasks. Animals were sacrificed and tissue punches were collected from the dorsal hippocampus on PN day 65. Tissue punches were flash-frozen in a beaker filled with isopentane", "role": "user" }, { "content": "Sugar practically screams from the shelves of your grocery store, especially those products marketed to kids. Children are the highest consumers of added sugar, even as high-sugar diets have been linked to health effects like obesity and heart disease and even impaired memory function. However, less is known about how high sugar consumption during childhood affects the development of the brain, specifically a region known to be critically important for learning and memory called the hippocampus. New research led by a University of Georgia faculty member in collaboration with a University of Southern California research group has shown in a rodent model that daily consumption of sugar-sweetened beverages during adolescence impairs performance on a learning and memory task during adulthood. The group further showed that changes in the bacteria in the gut may be the key to the sugar-induced memory impairment. Supporting this possibility, they found that similar memory deficits were observed even when the bacteria, called Parabacteroides, were experimentally enriched in the guts of animals that had never consumed sugar. \"Early life sugar increased Parabacteroides levels, and the higher the levels of Parabacteroides, the worse the animals did in the task,\" said Emily Noble, assistant professor in the UGA College of Family and Consumer Sciences who served as first author on the paper. \"We found that the bacteria alone was sufficient to impair memory in the same way as sugar, but it also impaired other types of memory functions as well.\" Guidelines recommend limiting sugar The Dietary Guidelines for Americans, a joint publication of the U.S. Departments of Agriculture and of Health and Human Services, recommends limiting added sugars to less than 10 percent of calories per day. Data from the Centers for Disease Control and Prevention show Americans between the ages 9-18 exceed that recommendation, the bulk of the calories coming from sugar-sweetened beverages. Considering the role the hippocampus plays in a variety of cognitive functions and the fact the area is still developing into late adolescence, researchers sought to understand more about its vulnerability to a high-sugar diet via gut microbiota. Juvenile rats were given their normal chow and an 11% sugar solution, which is comparable to commercially available sugar-sweetened beverages. Researchers then had the rats perform a hippocampus-dependent memory task designed to measure episodic contextual memory, or remembering the context where they had seen a familiar object before. \"We found that rats that consumed sugar in early life had an impaired capacity to discriminate that an object was novel to a specific context, a task the rats that were not given sugar were able to do,\" Noble said. A second memory task measured basic recognition memory, a hippocampal-independent memory function that involves the animals' ability to recognize something they had seen previously. In this task, sugar had no effect on the animals' recognition memory. \"Early life sugar consumption seems to selectively impair their hippocampal learning and memory,\" Noble said. Additional analyses determined that high sugar consumption led to elevated levels of Parabacteroides in the gut microbiome, the more than 100 trillion microorganisms in the gastrointestinal tract that play a role in human health and disease. To better identify the mechanism by which the bacteria impacted memory and learning, researchers experimentally increased levels of Parabacteroides in the microbiome of rats that had never consumed sugar. Those animals showed impairments in both hippocampal dependent and hippocampal-independent memory tasks. \"(The bacteria) induced some cognitive deficits on its own,\" Noble said. Noble said future research is needed to better identify specific pathways by which this gut-brain signaling operates. \"The question now is how do these populations of bacteria in the gut alter the development of the brain?\" Noble said. \"Identifying how the bacteria in the gut are impacting brain development will tell us about what sort of internal environment the brain needs in order to grow in a healthy way.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Emerging evidence highlights a critical relationship between gut microbiota and neurocognitive development. Excessive consumption of sugar and other unhealthy dietary factors during early life developmental periods yields changes in the gut microbiome as well as neurocognitive impairments. However, it is unclear whether these two outcomes are functionally connected. Here we explore whether excessive early life consumption of added sugars negatively impacts memory function via the gut microbiome. Rats were given free access to a sugar-sweetened beverage (SSB) during the adolescent stage of development. Memory function and anxiety-like behavior were assessed during adulthood and gut bacterial and brain transcriptome analyses were conducted. Taxa-specific microbial enrichment experiments examined the functional relationship between sugar-induced microbiome changes and neurocognitive and brain transcriptome outcomes. Chronic early life sugar consumption impaired adult hippocampal-dependent memory function without affecting body weight or anxiety-like behavior. Adolescent SSB consumption during adolescence also altered the gut microbiome, including elevated abundance of two species in the genus Parabacteroides ( P. distasonis and P. johnsonii ) that were negatively correlated with hippocampal function. Transferred enrichment of these specific bacterial taxa in adolescent rats impaired hippocampal-dependent memory during adulthood. Hippocampus transcriptome analyses revealed that early life sugar consumption altered gene expression in intracellular kinase and synaptic neurotransmitter signaling pathways, whereas Parabacteroides microbial enrichment altered gene expression in pathways associated with metabolic function, neurodegenerative disease, and dopaminergic signaling. Collectively these results identify a role for microbiota “dysbiosis” in mediating the detrimental effects of early life unhealthy dietary factors on hippocampal-dependent memory function. Introduction The gut microbiome has recently been implicated in modulating neurocognitive development and consequent functioning 1 , 2 , 3 , 4 . Early life developmental periods represent critical windows for the impact of indigenous gut microbes on the brain, as evidenced by the reversal of behavioral and neurochemical abnormalities in germ free rodents when inoculated with conventional microbiota during early life, but not during adulthood 5 , 6 , 7 . Dietary factors are a critical determinant of gut microbiota diversity and can alter gut bacterial communities, as evident from the microbial plasticity observed in response to pre- and probiotic treatment, as well as the “dysbiosis” resulting from consuming unhealthy, yet palatable foods that are associated with obesity and metabolic disorders (e.g., Western diet; foods high in saturated fatty acids and added sugar) 8 . In addition to altering the gut microbiota, consumption of Western dietary factors yields long-lasting memory impairments, and these effects are more pronounced when consumed during early life developmental periods vs. during adulthood 9 , 10 , 11 . Whether diet-induced changes in specific bacterial populations are functionally related to altered early life neurocognitive outcomes, however, is poorly understood. The hippocampus, which is well known for its role in spatial and episodic memory and more recently for regulating learned and social aspects of food intake control 12 , 13 , 14 , 15 , 16 , 17 , is particularly vulnerable to the deleterious effects of Western dietary factors 9 , 18 , 19 . During the juvenile and adolescent stages of development, a time when the brain is rapidly developing, consumption of diets high in saturated fat and sugar 20 , 21 , 22 or sugar alone 23 , 24 , 25 , 26 impairs hippocampal function while in some cases preserving memory processes that do not rely on the hippocampus. While several putative underlying mechanisms have been investigated, the precise biological pathways linking dietary factors to neurocognitive dysfunction remain largely undetermined 11 . Here we aimed to determine whether sugar-induced alterations in gut microbiota during early life are causally related to hippocampal-dependent memory impairments observed during adulthood. Methods and materials Experimental subjects Juvenile male Sprague Dawley rats (Envigo; arrival postnatal day (PN) 26–28; 50–70 g) were housed individually in standard conditions with a 12:12 light/dark cycle. All rats had ad libitum access to water and Lab Diet 5001 (PMI Nutrition International, Brentwood, MO; 29.8 % kcal from protein, 13.4% kcal from fat, 56.7% kcal from carbohydrate), with modifications where noted. Treatment group sizes for Aim 1 experiments are derived from power analyses conducted in Statistica Software (V7) based on our published data, pilot data, and relevant publications in the literature. All experiments were performed in accordance with the approval of the Animal Care and Use Committee at the University of Southern California. Experiment 1 Twenty-one juvenile male rats (PN 26–28) were divided into two groups with equal bodyweight and given ad libitum access to (1) 11% weight-by-volume (w/v) solution containing monosaccharide ratio of 65% fructose and 35% glucose in reverse osmosis-filtered water (SUG; n = 11) or 2) or an extra bottle of reverse osmosis-filtered water (CTL; n = 10). This solution was chosen to model commonly consumed sugar-sweetened beverages (SSBs) in humans in terms of both caloric content and monosaccharide ratio 27 . In addition, all rats were given ad libitum access to water and standard rat chow. Food intake, solution intake, and body weights were monitored thrice-weekly except were prohibited due to behavioral testing. At PN 60, rats underwent Novel Object in Context (NOIC) testing, to measure hippocampal-dependent episodic contextual memory. At PN 67 rats underwent anxiety-like behavior testing in the Zero Maze, followed by body composition testing at PN 70 and an intraperitoneal glucose tolerance test (IP GTT) at PN 84. All behavioral procedures were run at the same time each day (4–6 h into the light cycle). Investigators were blind to animal groups when scoring the behavioral tasks such that the scorers did not know which animal was in which group. Fecal and cecal samples were collected prior to sacrifice at PN 104. In a separate cohort of juvenile male rats ( n = 6/group) animals were treated as above, but on PN day 60 rats were tested in the Novel Object Recognition (NOR) and Open Field (OF) tasks, with two days in between tasks. Animals were sacrificed and tissue punches were collected from the dorsal hippocampus on PN day 65. Tissue punches were flash-frozen in a beaker filled with isopentane<|im_end|> <|im_start|>assistant Sugar practically screams from the shelves of your grocery store, especially those products marketed to kids. Children are the highest consumers of added sugar, even as high-sugar diets have been linked to health effects like obesity and heart disease and even impaired memory function. However, less is known about how high sugar consumption during childhood affects the development of the brain, specifically a region known to be critically important for learning and memory called the hippocampus. New research led by a University of Georgia faculty member in collaboration with a University of Southern California research group has shown in a rodent model that daily consumption of sugar-sweetened beverages during adolescence impairs performance on a learning and memory task during adulthood. The group further showed that changes in the bacteria in the gut may be the key to the sugar-induced memory impairment. Supporting this possibility, they found that similar memory deficits were observed even when the bacteria, called Parabacteroides, were experimentally enriched in the guts of animals that had never consumed sugar. "Early life sugar increased Parabacteroides levels, and the higher the levels of Parabacteroides, the worse the animals did in the task," said Emily Noble, assistant professor in the UGA College of Family and Consumer Sciences who served as first author on the paper. "We found that the bacteria alone was sufficient to impair memory in the same way as sugar, but it also impaired other types of memory functions as well." Guidelines recommend limiting sugar The Dietary Guidelines for Americans, a joint publication of the U.S. Departments of Agriculture and of Health and Human Services, recommends limiting added sugars to less than 10 percent of calories per day. Data from the Centers for Disease Control and Prevention show Americans between the ages 9-18 exceed that recommendation, the bulk of the calories coming from sugar-sweetened beverages. Considering the role the hippocampus plays in a variety of cognitive functions and the fact the area is still developing into late adolescence, researchers sought to understand more about its vulnerability to a high-sugar diet via gut microbiota. Juvenile rats were given their normal chow and an 11% sugar solution, which is comparable to commercially available sugar-sweetened beverages. Researchers then had the rats perform a hippocampus-dependent memory task designed to measure episodic contextual memory, or remembering the context where they had seen a familiar object before. "We found that rats that consumed sugar in early life had an impaired capacity to discriminate that an object was novel to a specific context, a task the rats that were not given sugar were able to do," Noble said. A second memory task measured basic recognition memory, a hippocampal-independent memory function that involves the animals' ability to recognize something they had seen previously. In this task, sugar had no effect on the animals' recognition memory. "Early life sugar consumption seems to selectively impair their hippocampal learning and memory," Noble said. Additional analyses determined that high sugar consumption led to elevated levels of Parabacteroides in the gut microbiome, the more than 100 trillion microorganisms in the gastrointestinal tract that play a role in human health and disease. To better identify the mechanism by which the bacteria impacted memory and learning, researchers experimentally increased levels of Parabacteroides in the microbiome of rats that had never consumed sugar. Those animals showed impairments in both hippocampal dependent and hippocampal-independent memory tasks. "(The bacteria) induced some cognitive deficits on its own," Noble said. Noble said future research is needed to better identify specific pathways by which this gut-brain signaling operates. "The question now is how do these populations of bacteria in the gut alter the development of the brain?" Noble said. "Identifying how the bacteria in the gut are impacting brain development will tell us about what sort of internal environment the brain needs in order to grow in a healthy way." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 86148, 6029, 22020, 264, 9200, 5133, 1990, 18340, 53499, 6217, 323, 18247, 66, 51549, 4500, 13, 1398, 87728, 15652, 315, 13465, 323, 1023, 53808, 34625, 9547, 2391, 4216, 2324, 48006, 18852, 36508, 4442, 304, 279, 18340, 53499, 638, 439, 1664, 439, 18247, 66, 51549, 38974, 1392, 13, 4452, 11, 433, 374, 25420, 3508, 1521, 1403, 20124, 527, 734, 750, 8599, 13, 5810, 584, 13488, 3508, 27639, 4216, 2324, 15652, 315, 3779, 70913, 48291, 25949, 5044, 734, 4669, 279, 18340, 53499, 638, 13, 432, 1900, 1051, 2728, 1949, 2680, 311, 264, 13465, 1355, 4589, 6901, 43450, 320, 1242, 33, 8, 2391, 279, 36088, 6566, 315, 4500, 13, 14171, 734, 323, 18547, 12970, 7865, 1051, 32448, 2391, 64033, 323, 18340, 45964, 323, 8271, 36815, 638, 29060, 1051, 13375, 13, 15545, 64, 19440, 75418, 70272, 21896, 25078, 279, 16003, 5133, 1990, 13465, 38973, 53499, 638, 4442, 323, 18247, 66, 51549, 323, 8271, 36815, 638, 20124, 13, 73782, 4216, 2324, 13465, 15652, 50160, 6822, 71206, 1141, 278, 43918, 5044, 734, 2085, 28987, 2547, 4785, 477, 18547, 12970, 7865, 13, 98582, 328, 17094, 15652, 2391, 83909, 1101, 29852, 279, 18340, 53499, 638, 11, 2737, 32389, 37492, 315, 1403, 9606, 304, 279, 64677, 4366, 370, 2540, 590, 288, 320, 393, 13, 1612, 1525, 285, 323, 393, 13, 40742, 942, 3893, 883, 430, 1051, 48291, 49393, 449, 71206, 1141, 278, 734, 13, 4149, 5671, 70272, 315, 1521, 3230, 45964, 77314, 304, 36088, 32510, 50160, 71206, 1141, 278, 43918, 5044, 2391, 64033, 13, 75463, 511, 44651, 36815, 638, 29060, 10675, 430, 4216, 2324, 13465, 15652, 29852, 15207, 7645, 304, 10805, 65441, 82160, 323, 99827, 90351, 16517, 43080, 44014, 11, 20444, 4366, 370, 2540, 590, 288, 75418, 70272, 29852, 15207, 7645, 304, 44014, 5938, 449, 41861, 734, 11, 18247, 451, 7642, 1413, 8624, 11, 323, 27420, 8778, 75439, 43080, 13, 21153, 3210, 1521, 3135, 10765, 264, 3560, 369, 53499, 6217, 1054, 67, 1065, 70728, 285, 863, 304, 1812, 23747, 279, 65069, 6372, 315, 4216, 2324, 53808, 34625, 9547, 389, 71206, 1141, 278, 43918, 5044, 734, 13, 29438, 578, 18340, 53499, 638, 706, 6051, 1027, 69702, 304, 1491, 15853, 18247, 66, 51549, 4500, 323, 12777, 306, 31301, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 662, 23591, 2324, 48006, 18852, 4097, 9200, 11276, 369, 279, 5536, 315, 39678, 18340, 80727, 389, 279, 8271, 11, 439, 69457, 555, 279, 59214, 315, 36695, 323, 18247, 32056, 75815, 304, 82986, 1949, 94209, 994, 87018, 7913, 449, 21349, 53499, 6217, 2391, 4216, 2324, 11, 719, 539, 2391, 64033, 220, 20, 1174, 220, 21, 1174, 220, 22, 662, 83808, 9547, 527, 264, 9200, 88060, 315, 18340, 53499, 6217, 20057, 323, 649, 11857, 18340, 45964, 10977, 11, 439, 30576, 505, 279, 75418, 12466, 488, 13468, 304, 2077, 311, 864, 12, 323, 3650, 62114, 6514, 11, 439, 1664, 439, 279, 1054, 67, 1065, 70728, 285, 863, 13239, 505, 35208, 53808, 11, 3686, 11091, 15436, 15657, 430, 527, 5938, 449, 33048, 323, 41861, 24673, 320, 68, 1326, 2637, 11104, 10173, 26, 15657, 1579, 304, 50585, 40085, 33969, 323, 3779, 13465, 8, 220, 23, 662, 763, 5369, 311, 60923, 279, 18340, 53499, 6217, 11, 15652, 315, 11104, 34625, 9547, 36508, 1317, 65265, 5044, 38974, 1392, 11, 323, 1521, 6372, 527, 810, 38617, 994, 27073, 2391, 4216, 2324, 48006, 18852, 6296, 13, 2391, 64033, 220, 24, 1174, 220, 605, 1174, 220, 806, 662, 13440, 10173, 38973, 4442, 304, 3230, 45964, 22673, 527, 734, 750, 5552, 311, 29852, 4216, 2324, 18247, 66, 51549, 20124, 11, 4869, 11, 374, 31555, 16365, 13, 578, 71206, 44651, 11, 902, 374, 1664, 3967, 369, 1202, 3560, 304, 29079, 323, 67594, 53860, 5044, 323, 810, 6051, 369, 58499, 9687, 323, 3674, 13878, 315, 3691, 23730, 2585, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 1174, 374, 8104, 20134, 311, 279, 60393, 466, 1245, 6372, 315, 11104, 34625, 9547, 220, 24, 1174, 220, 972, 1174, 220, 777, 662, 12220, 279, 48770, 323, 36088, 18094, 315, 4500, 11, 264, 892, 994, 279, 8271, 374, 19019, 11469, 11, 15652, 315, 41943, 1579, 304, 50585, 8834, 323, 13465, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 477, 13465, 7636, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 1174, 220, 1627, 3242, 4825, 71206, 1141, 278, 734, 1418, 304, 1063, 5157, 47995, 5044, 11618, 430, 656, 539, 17631, 389, 279, 71206, 44651, 13, 6104, 3892, 2231, 1413, 16940, 24717, 617, 1027, 27313, 11, 279, 24473, 24156, 44014, 31799, 34625, 9547, 311, 18247, 66, 51549, 32403, 7293, 14090, 2073, 47737, 220, 806, 662, 5810, 584, 20034, 311, 8417, 3508, 13465, 38973, 61086, 304, 18340, 53499, 6217, 2391, 4216, 2324, 527, 25540, 750, 5552, 311, 71206, 1141, 278, 43918, 5044, 38974, 1392, 13468, 2391, 64033, 13, 19331, 323, 7384, 57708, 15223, 22410, 40204, 8762, 15883, 4768, 37851, 3258, 32510, 320, 14696, 7992, 26, 19163, 1772, 74439, 1938, 320, 18378, 8, 220, 1627, 4235, 1591, 26, 220, 1135, 4235, 2031, 342, 8, 1051, 52258, 32399, 304, 5410, 4787, 449, 264, 220, 717, 25, 717, 3177, 3529, 847, 11008, 13, 2052, 32510, 1047, 1008, 3127, 275, 372, 2680, 311, 3090, 323, 11868, 27304, 220, 2636, 16, 320, 8971, 40, 39700, 7327, 11, 47431, 6798, 11, 11672, 26, 220, 1682, 13, 23, 1034, 96103, 505, 13128, 11, 220, 1032, 13, 19, 4, 96103, 505, 8834, 11, 220, 3487, 13, 22, 4, 96103, 505, 67732, 705, 449, 29882, 1405, 10555, 13, 31969, 1912, 12562, 369, 71715, 220, 16, 21896, 527, 14592, 505, 2410, 29060, 13375, 304, 12442, 87359, 4476, 320, 53, 22, 8, 3196, 389, 1057, 4756, 828, 11, 18178, 828, 11, 323, 9959, 29085, 304, 279, 17649, 13, 2052, 21896, 1051, 10887, 304, 18859, 449, 279, 14765, 315, 279, 21995, 10852, 323, 5560, 10554, 520, 279, 3907, 315, 16642, 7188, 13, 47893, 220, 16, 44956, 19101, 48770, 8762, 32510, 320, 18378, 220, 1627, 4235, 1591, 8, 1051, 18255, 1139, 1403, 5315, 449, 6273, 2547, 4870, 323, 2728, 1008, 3127, 275, 372, 2680, 311, 320, 16, 8, 220, 806, 4, 4785, 14656, 67868, 320, 86, 5574, 8, 6425, 8649, 1647, 437, 582, 1799, 579, 11595, 315, 220, 2397, 4, 1448, 87873, 323, 220, 1758, 4, 34323, 304, 10134, 2709, 8801, 285, 33548, 291, 3090, 320, 50, 3014, 26, 308, 284, 220, 806, 8, 477, 220, 17, 8, 477, 459, 5066, 16893, 315, 10134, 2709, 8801, 285, 33548, 291, 3090, 320, 24813, 26, 308, 284, 220, 605, 570, 1115, 6425, 574, 12146, 311, 1646, 17037, 27073, 13465, 1355, 4589, 6901, 47497, 320, 1242, 75307, 8, 304, 12966, 304, 3878, 315, 2225, 1652, 27456, 2262, 323, 1647, 437, 582, 1799, 579, 11595, 220, 1544, 662, 763, 5369, 11, 682, 32510, 1051, 2728, 1008, 3127, 275, 372, 2680, 311, 3090, 323, 5410, 11494, 523, 363, 13, 12369, 23730, 11, 6425, 23730, 11, 323, 2547, 14661, 1051, 41223, 8983, 560, 30609, 398, 3734, 1051, 27010, 4245, 311, 36695, 7649, 13, 2468, 63001, 220, 1399, 11, 32510, 55093, 53976, 3075, 304, 9805, 320, 9173, 1341, 8, 7649, 11, 311, 6767, 71206, 1141, 278, 43918, 67594, 53860, 66251, 5044, 13, 2468, 63001, 220, 3080, 32510, 55093, 18547, 12970, 7865, 7649, 304, 279, 18811, 66191, 11, 8272, 555, 2547, 18528, 7649, 520, 63001, 220, 2031, 323, 459, 10805, 3271, 85166, 278, 34323, 25065, 1296, 320, 3378, 12177, 51, 8, 520, 63001, 220, 5833, 13, 2052, 36695, 16346, 1051, 1629, 520, 279, 1890, 892, 1855, 1938, 320, 19, 4235, 21, 305, 1139, 279, 3177, 11008, 570, 96852, 1051, 18507, 311, 10065, 5315, 994, 20413, 279, 36695, 9256, 1778, 430, 279, 62195, 388, 1550, 539, 1440, 902, 10065, 574, 304, 902, 1912, 13, 435, 98298, 323, 272, 98298, 10688, 1051, 14890, 4972, 311, 28235, 520, 63001, 220, 6849, 13, 763, 264, 8821, 41944, 315, 48770, 8762, 32510, 320, 308, 284, 220, 21, 54489, 8, 10099, 1051, 12020, 439, 3485, 11, 719, 389, 63001, 1938, 220, 1399, 32510, 1051, 12793, 304, 279, 53976, 3075, 48698, 320, 45, 878, 8, 323, 5377, 8771, 320, 12766, 8, 9256, 11, 449, 1403, 2919, 304, 1990, 9256, 13, 47966, 1051, 67904, 323, 20438, 61851, 1051, 14890, 505, 279, 96146, 71206, 44651, 389, 63001, 1938, 220, 2397, 13, 350, 11407, 61851, 1051, 8381, 2269, 43340, 304, 264, 387, 4506, 10409, 449, 374, 454, 306, 2194, 128257, 198, 128256, 78191, 198, 84514, 32367, 61108, 505, 279, 36310, 315, 701, 30687, 3637, 11, 5423, 1884, 3956, 61149, 311, 6980, 13, 15394, 527, 279, 8592, 13723, 315, 3779, 13465, 11, 1524, 439, 1579, 1355, 8734, 41943, 617, 1027, 10815, 311, 2890, 6372, 1093, 33048, 323, 4851, 8624, 323, 1524, 50160, 5044, 734, 13, 4452, 11, 2753, 374, 3967, 922, 1268, 1579, 13465, 15652, 2391, 20587, 22223, 279, 4500, 315, 279, 8271, 11, 11951, 264, 5654, 3967, 311, 387, 41440, 3062, 369, 6975, 323, 5044, 2663, 279, 71206, 44651, 13, 1561, 3495, 6197, 555, 264, 3907, 315, 16272, 22291, 4562, 304, 20632, 449, 264, 3907, 315, 16642, 7188, 3495, 1912, 706, 6982, 304, 264, 21236, 306, 1646, 430, 7446, 15652, 315, 13465, 1355, 4589, 6901, 47497, 2391, 83909, 3242, 4825, 5178, 389, 264, 6975, 323, 5044, 3465, 2391, 64033, 13, 578, 1912, 4726, 8710, 430, 4442, 304, 279, 24032, 304, 279, 18340, 1253, 387, 279, 1401, 311, 279, 13465, 38973, 5044, 53317, 13, 75096, 420, 13336, 11, 814, 1766, 430, 4528, 5044, 57096, 1051, 13468, 1524, 994, 279, 24032, 11, 2663, 4366, 370, 2540, 590, 288, 11, 1051, 9526, 750, 69671, 304, 279, 65973, 315, 10099, 430, 1047, 2646, 27073, 13465, 13, 330, 42298, 2324, 13465, 7319, 4366, 370, 2540, 590, 288, 5990, 11, 323, 279, 5190, 279, 5990, 315, 4366, 370, 2540, 590, 288, 11, 279, 11201, 279, 10099, 1550, 304, 279, 3465, 1359, 1071, 35266, 49687, 11, 18328, 14561, 304, 279, 549, 16519, 9304, 315, 12517, 323, 26262, 23199, 889, 10434, 439, 1176, 3229, 389, 279, 5684, 13, 330, 1687, 1766, 430, 279, 24032, 7636, 574, 14343, 311, 38974, 5044, 304, 279, 1890, 1648, 439, 13465, 11, 719, 433, 1101, 50160, 1023, 4595, 315, 5044, 5865, 439, 1664, 1210, 48528, 7079, 33994, 13465, 578, 83808, 48528, 369, 9053, 11, 264, 10496, 17009, 315, 279, 549, 815, 13, 85608, 315, 37963, 323, 315, 6401, 323, 11344, 8471, 11, 40912, 33994, 3779, 70913, 311, 2753, 1109, 220, 605, 3346, 315, 25247, 824, 1938, 13, 2956, 505, 279, 41991, 369, 31974, 7935, 323, 36947, 1501, 9053, 1990, 279, 17051, 220, 24, 12, 972, 12771, 430, 28782, 11, 279, 20155, 315, 279, 25247, 5108, 505, 13465, 1355, 4589, 6901, 47497, 13, 56877, 279, 3560, 279, 71206, 44651, 11335, 304, 264, 8205, 315, 25702, 5865, 323, 279, 2144, 279, 3158, 374, 2103, 11469, 1139, 3389, 83909, 11, 12074, 16495, 311, 3619, 810, 922, 1202, 34104, 311, 264, 1579, 1355, 8734, 10173, 4669, 18340, 53499, 6217, 13, 22410, 40204, 32510, 1051, 2728, 872, 4725, 523, 363, 323, 459, 220, 806, 4, 13465, 6425, 11, 902, 374, 30139, 311, 54453, 2561, 13465, 1355, 4589, 6901, 47497, 13, 59250, 1243, 1047, 279, 32510, 2804, 264, 71206, 44651, 43918, 5044, 3465, 6319, 311, 6767, 67594, 53860, 66251, 5044, 11, 477, 48384, 279, 2317, 1405, 814, 1047, 3970, 264, 11537, 1665, 1603, 13, 330, 1687, 1766, 430, 32510, 430, 27073, 13465, 304, 4216, 2324, 1047, 459, 50160, 8824, 311, 60541, 430, 459, 1665, 574, 11775, 311, 264, 3230, 2317, 11, 264, 3465, 279, 32510, 430, 1051, 539, 2728, 13465, 1051, 3025, 311, 656, 1359, 49687, 1071, 13, 362, 2132, 5044, 3465, 17303, 6913, 18324, 5044, 11, 264, 71206, 1141, 278, 98885, 5044, 734, 430, 18065, 279, 10099, 6, 5845, 311, 15641, 2555, 814, 1047, 3970, 8767, 13, 763, 420, 3465, 11, 13465, 1047, 912, 2515, 389, 279, 10099, 6, 18324, 5044, 13, 330, 42298, 2324, 13465, 15652, 5084, 311, 82775, 38974, 872, 71206, 1141, 278, 6975, 323, 5044, 1359, 49687, 1071, 13, 24086, 29060, 11075, 430, 1579, 13465, 15652, 6197, 311, 32389, 5990, 315, 4366, 370, 2540, 590, 288, 304, 279, 18340, 53499, 638, 11, 279, 810, 1109, 220, 1041, 32610, 8162, 76991, 304, 279, 80311, 42929, 430, 1514, 264, 3560, 304, 3823, 2890, 323, 8624, 13, 2057, 2731, 10765, 279, 17383, 555, 902, 279, 24032, 40028, 5044, 323, 6975, 11, 12074, 9526, 750, 7319, 5990, 315, 4366, 370, 2540, 590, 288, 304, 279, 53499, 638, 315, 32510, 430, 1047, 2646, 27073, 13465, 13, 13266, 10099, 8710, 38974, 1392, 304, 2225, 71206, 1141, 278, 18222, 323, 71206, 1141, 278, 98885, 5044, 9256, 13, 12262, 791, 24032, 8, 36572, 1063, 25702, 57096, 389, 1202, 1866, 1359, 49687, 1071, 13, 49687, 1071, 3938, 3495, 374, 4460, 311, 2731, 10765, 3230, 44014, 555, 902, 420, 18340, 31217, 467, 43080, 27149, 13, 330, 791, 3488, 1457, 374, 1268, 656, 1521, 22673, 315, 24032, 304, 279, 18340, 11857, 279, 4500, 315, 279, 8271, 7673, 49687, 1071, 13, 330, 29401, 7922, 1268, 279, 24032, 304, 279, 18340, 527, 74055, 8271, 4500, 690, 3371, 603, 922, 1148, 3460, 315, 5419, 4676, 279, 8271, 3966, 304, 2015, 311, 3139, 304, 264, 9498, 1648, 1210, 220, 128257, 198 ]

2,181

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The quantum Rabi model describes the fundamental mechanism of light-matter interaction. It consists of a two-level atom or qubit coupled to a quantized harmonic mode via a transversal interaction. In the weak coupling regime, it reduces to the well-known Jaynes–Cummings model by applying a rotating wave approximation. The rotating wave approximation breaks down in the ultra-strong coupling regime, where the effective coupling strength g is comparable to the energy ω of the bosonic mode, and remarkable features in the system dynamics are revealed. Here we demonstrate an analog quantum simulation of an effective quantum Rabi model in the ultra-strong coupling regime, achieving a relative coupling ratio of g / ω ~ 0.6. The quantum hardware of the simulator is a superconducting circuit embedded in a cQED setup. We observe fast and periodic quantum state collapses and revivals of the initial qubit state, being the most distinct signature of the synthesized model. Introduction Finding solutions to many quantum problems is a very challenging task 1 . The reason is the exponentially large number of degrees of freedom in a quantum system, requiring computational power and memory that easily exceed the capabilities of present classical computers. A yet to be demonstrated universal digital quantum computer of sufficient size would be capable of efficiently solving most quantum problems 1 , 2 . A more feasible approach to achieve a computational speedup in the near future is quantum simulation 1 , 2 , 3 . In the framework of analog quantum simulation, a tailored and well-controllable artificial quantum system is mapped onto a quantum problem of interest in order to mimic its dynamics. Since the same equations of motion hold for both systems, the solution of the underlying quantum problem is inferred by observing the time evolution of the artificially built model system, while making use of its intrinsic quantumness. This scheme may be applied to the simulation of complex quantum problems, in the spirit originally proposed by Feynman 1 . Quantum simulation was performed on various experimental platforms. Examples of analog quantum simulation are the study of fermionic transport 4 and magnetism 5 with cold atoms and the simulation of a quantum magnet and the Dirac equation with trapped ions 6 , 7 . The exploration of non-equilibrium physics was proposed with an on-chip quantum simulator based on superconducting circuits 8 , 9 . Digital simulation schemes with superconducting devices were demonstrated for fermionic models 10 and spin systems 11 . The quantum Rabi model in quantum optics describes the interaction between a two-level atom and a single quantized harmonic oscillator mode 12 , 13 . In the weak coupling regime, which may still be strong in the sense of quantum electrodynamics (QED), a rotating wave approximation (RWA) can be applied and the Rabi model reduces to the Jaynes–Cummings model 14 , which captures most relevant scenarios in cavity and circuit QED. In the ultra-strong coupling (USC) and deep strong coupling regimes, where the coupling strength is comparable to the mode energies 15 , the counter rotating terms in the interaction Hamiltonian can no longer be neglected and the RWA breaks down. As a consequence, the total excitation number in the quantum Rabi model is not conserved. Except for one recent paradigm of finding an exact solution 16 , an analytically closed solution of the quantum Rabi model does not exist due to the lack of a second conserved quantity which renders it non-integrable. The quantum Rabi model, in particular in the USC regime and beyond, exhibits non-classical features and rising interest in it is inspired by strong advances of experimental capabilities 15 , 17 , 18 , 19 . The specific spectral features of the USC regime and the consequent breakdown of the RWA were previously observed with a superconducting circuit by implementing an increased physical coupling strength 20 , 21 . A similar approach involving a flux qubit coupled to a single-mode resonator allowed to access the deep strong coupling regime in a closed system 22 . The USC regime was reached before by dynamically modulating the flux bias of a superconducting qubit, reaching a coupling strength of about 0.1 of the effective resonator frequency 23 . In our approach, we engineer an effective quantum Rabi Hamiltonian with an analog quantum simulation scheme based on the application of microwave Rabi drive tones. By a decrease of the subsystem energies, the USC condition is satisfied in the effective rotating frame, allowing to observe the distinct model dynamics. The scheme may be a route to efficiently generate non-classical cavity states 24 , 25 , 26 and may be extended to explore relevant physical models such as the Dirac equation in (1 + 1) dimensions. Its characteristic dynamics is expected to display a Zitterbewegung in the spacial quadrature of the bosonic mode 27 . This dynamics has been observed with trapped ions 7 , likewise based on a Hamiltonian that is closely related to the USC Rabi model. It has been shown recently that a quantum phase transition, typically requiring a continuum of modes, can appear already in the quantum Rabi model under appropriate conditions 28 . The experimental challenge is projected to the coupling requirements in the model which may be accomplished with the simulation scheme presented. This can be a starting point to experimentally investigate critical phenomena in a small and well-controlled quantum system 29 . With a digital simulation approach, the dynamics of the quantum Rabi model in USC conditions was similarly studied very recently 30 . In our experiment we simulate the quantum Rabi model in the USC regime achieving a relative coupling strength of up to 0.6. Dependent on our experimental parameters, we observe periodically recurring quantum state collapses and revivals in the qubit dynamics, being a distinct signature of USC. The collapse-revival dynamics appears most clearly in the absence of the qubit energy term in the model, according to the expectation from master equation simulations. In addition, we use our device to simulate the full quantum Rabi", "role": "user" }, { "content": "Hurricanes, traffic jams, demographic development – to predict the effect of such events, computer simulations are required. Many processes in nature, however, are so complicated that conventional computers fail. Quantum simulators may solve this problem. One of the basic phenomena in nature is the interaction between light and matter in photosynthesis. Physicists of Karlsruhe Institute of Technology (KIT) have now made a big step towards quantum mechanics understanding of plant metabolism. This is reported in the Nature Communications journal. \"A quantum simulator is the preliminary stage of a quantum computer. Contrary to a quantum computer, however, it is not able to make any calculations, but is designed for the solution of a certain problem,\" says Jochen Braumüller of KIT's Physikalisches Institut (Institute of Physics). As the high efficiency of photosynthesis cannot be understood completely with classical physical theories, researchers like Braumüller use a quantum model. Together with scientists of the Institut für Theoretische Festkörperphysik (TFP, Institute for Theoretical Solid-State Physics), he demonstrated for the first time in an experiment that quantum simulations of the interaction between light and matter work in principle. The interaction between light and matter in photosynthesis can be described as an interaction of photons of light with the atoms of matter on the microscopic level. The high efficiency of this mechanism of nearly 100 percent suggests that it is subject to rules of quantum physics, which is difficult to simulate with classical computers and simple bits. In standard computing, information is represented by a switch that can store information as zero or one. Quantum bits, by contrast, are able to assume the states of zero and one at the same time according to quantum physics rules. Hence, quantum computers or the simpler quantum simulators can solve the problem more quickly and efficiently. Braumüller and his co-authors have now developed one of the first functioning components for a quantum simulator of light-matter interaction: Superconducting circuits as quantum bits represent the atoms, while electromagnetic resonators represent the photons. The physicists succeeded in producing an effect with the quantum bit and the resonator assuming two opposite states at the same time. \"Qubit and resonator are coupled,\" says Michael Marthaler of KIT's TFP. \"This is also the reason for the exponentially improved calculation capacity compared to classical computers.\" Fulfilling of this fundamental principle of quantum mechanics has demonstrated feasibility of analog quantum simulation with superconducting circuits, the researchers say. As a next step, they plan to extend their system via many other building blocks. \"Classical simulation of this extended system would take longer than the age of the universe,\" says Martin Weides, who has been heading a working group at KIT's Physikalisches Institut since 2015. If the planned quantum mechanics simulation is successful, this will be a \"milestone on the way towards a universal quantum computer.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The quantum Rabi model describes the fundamental mechanism of light-matter interaction. It consists of a two-level atom or qubit coupled to a quantized harmonic mode via a transversal interaction. In the weak coupling regime, it reduces to the well-known Jaynes–Cummings model by applying a rotating wave approximation. The rotating wave approximation breaks down in the ultra-strong coupling regime, where the effective coupling strength g is comparable to the energy ω of the bosonic mode, and remarkable features in the system dynamics are revealed. Here we demonstrate an analog quantum simulation of an effective quantum Rabi model in the ultra-strong coupling regime, achieving a relative coupling ratio of g / ω ~ 0.6. The quantum hardware of the simulator is a superconducting circuit embedded in a cQED setup. We observe fast and periodic quantum state collapses and revivals of the initial qubit state, being the most distinct signature of the synthesized model. Introduction Finding solutions to many quantum problems is a very challenging task 1 . The reason is the exponentially large number of degrees of freedom in a quantum system, requiring computational power and memory that easily exceed the capabilities of present classical computers. A yet to be demonstrated universal digital quantum computer of sufficient size would be capable of efficiently solving most quantum problems 1 , 2 . A more feasible approach to achieve a computational speedup in the near future is quantum simulation 1 , 2 , 3 . In the framework of analog quantum simulation, a tailored and well-controllable artificial quantum system is mapped onto a quantum problem of interest in order to mimic its dynamics. Since the same equations of motion hold for both systems, the solution of the underlying quantum problem is inferred by observing the time evolution of the artificially built model system, while making use of its intrinsic quantumness. This scheme may be applied to the simulation of complex quantum problems, in the spirit originally proposed by Feynman 1 . Quantum simulation was performed on various experimental platforms. Examples of analog quantum simulation are the study of fermionic transport 4 and magnetism 5 with cold atoms and the simulation of a quantum magnet and the Dirac equation with trapped ions 6 , 7 . The exploration of non-equilibrium physics was proposed with an on-chip quantum simulator based on superconducting circuits 8 , 9 . Digital simulation schemes with superconducting devices were demonstrated for fermionic models 10 and spin systems 11 . The quantum Rabi model in quantum optics describes the interaction between a two-level atom and a single quantized harmonic oscillator mode 12 , 13 . In the weak coupling regime, which may still be strong in the sense of quantum electrodynamics (QED), a rotating wave approximation (RWA) can be applied and the Rabi model reduces to the Jaynes–Cummings model 14 , which captures most relevant scenarios in cavity and circuit QED. In the ultra-strong coupling (USC) and deep strong coupling regimes, where the coupling strength is comparable to the mode energies 15 , the counter rotating terms in the interaction Hamiltonian can no longer be neglected and the RWA breaks down. As a consequence, the total excitation number in the quantum Rabi model is not conserved. Except for one recent paradigm of finding an exact solution 16 , an analytically closed solution of the quantum Rabi model does not exist due to the lack of a second conserved quantity which renders it non-integrable. The quantum Rabi model, in particular in the USC regime and beyond, exhibits non-classical features and rising interest in it is inspired by strong advances of experimental capabilities 15 , 17 , 18 , 19 . The specific spectral features of the USC regime and the consequent breakdown of the RWA were previously observed with a superconducting circuit by implementing an increased physical coupling strength 20 , 21 . A similar approach involving a flux qubit coupled to a single-mode resonator allowed to access the deep strong coupling regime in a closed system 22 . The USC regime was reached before by dynamically modulating the flux bias of a superconducting qubit, reaching a coupling strength of about 0.1 of the effective resonator frequency 23 . In our approach, we engineer an effective quantum Rabi Hamiltonian with an analog quantum simulation scheme based on the application of microwave Rabi drive tones. By a decrease of the subsystem energies, the USC condition is satisfied in the effective rotating frame, allowing to observe the distinct model dynamics. The scheme may be a route to efficiently generate non-classical cavity states 24 , 25 , 26 and may be extended to explore relevant physical models such as the Dirac equation in (1 + 1) dimensions. Its characteristic dynamics is expected to display a Zitterbewegung in the spacial quadrature of the bosonic mode 27 . This dynamics has been observed with trapped ions 7 , likewise based on a Hamiltonian that is closely related to the USC Rabi model. It has been shown recently that a quantum phase transition, typically requiring a continuum of modes, can appear already in the quantum Rabi model under appropriate conditions 28 . The experimental challenge is projected to the coupling requirements in the model which may be accomplished with the simulation scheme presented. This can be a starting point to experimentally investigate critical phenomena in a small and well-controlled quantum system 29 . With a digital simulation approach, the dynamics of the quantum Rabi model in USC conditions was similarly studied very recently 30 . In our experiment we simulate the quantum Rabi model in the USC regime achieving a relative coupling strength of up to 0.6. Dependent on our experimental parameters, we observe periodically recurring quantum state collapses and revivals in the qubit dynamics, being a distinct signature of USC. The collapse-revival dynamics appears most clearly in the absence of the qubit energy term in the model, according to the expectation from master equation simulations. In addition, we use our device to simulate the full quantum Rabi<|im_end|> <|im_start|>assistant Hurricanes, traffic jams, demographic development – to predict the effect of such events, computer simulations are required. Many processes in nature, however, are so complicated that conventional computers fail. Quantum simulators may solve this problem. One of the basic phenomena in nature is the interaction between light and matter in photosynthesis. Physicists of Karlsruhe Institute of Technology (KIT) have now made a big step towards quantum mechanics understanding of plant metabolism. This is reported in the Nature Communications journal. "A quantum simulator is the preliminary stage of a quantum computer. Contrary to a quantum computer, however, it is not able to make any calculations, but is designed for the solution of a certain problem," says Jochen Braumüller of KIT's Physikalisches Institut (Institute of Physics). As the high efficiency of photosynthesis cannot be understood completely with classical physical theories, researchers like Braumüller use a quantum model. Together with scientists of the Institut für Theoretische Festkörperphysik (TFP, Institute for Theoretical Solid-State Physics), he demonstrated for the first time in an experiment that quantum simulations of the interaction between light and matter work in principle. The interaction between light and matter in photosynthesis can be described as an interaction of photons of light with the atoms of matter on the microscopic level. The high efficiency of this mechanism of nearly 100 percent suggests that it is subject to rules of quantum physics, which is difficult to simulate with classical computers and simple bits. In standard computing, information is represented by a switch that can store information as zero or one. Quantum bits, by contrast, are able to assume the states of zero and one at the same time according to quantum physics rules. Hence, quantum computers or the simpler quantum simulators can solve the problem more quickly and efficiently. Braumüller and his co-authors have now developed one of the first functioning components for a quantum simulator of light-matter interaction: Superconducting circuits as quantum bits represent the atoms, while electromagnetic resonators represent the photons. The physicists succeeded in producing an effect with the quantum bit and the resonator assuming two opposite states at the same time. "Qubit and resonator are coupled," says Michael Marthaler of KIT's TFP. "This is also the reason for the exponentially improved calculation capacity compared to classical computers." Fulfilling of this fundamental principle of quantum mechanics has demonstrated feasibility of analog quantum simulation with superconducting circuits, the researchers say. As a next step, they plan to extend their system via many other building blocks. "Classical simulation of this extended system would take longer than the age of the universe," says Martin Weides, who has been heading a working group at KIT's Physikalisches Institut since 2015. If the planned quantum mechanics simulation is successful, this will be a "milestone on the way towards a universal quantum computer." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 31228, 432, 26140, 1646, 16964, 279, 16188, 17383, 315, 3177, 1474, 1683, 16628, 13, 1102, 17610, 315, 264, 1403, 11852, 19670, 477, 2874, 60320, 34356, 311, 264, 10484, 1534, 82341, 3941, 4669, 264, 1380, 3078, 278, 16628, 13, 763, 279, 7621, 59086, 17942, 11, 433, 26338, 311, 279, 1664, 22015, 19455, 4978, 4235, 34, 83533, 1646, 555, 19486, 264, 42496, 12330, 57304, 13, 578, 42496, 12330, 57304, 18808, 1523, 304, 279, 24955, 96857, 59086, 17942, 11, 1405, 279, 7524, 59086, 8333, 342, 374, 30139, 311, 279, 4907, 117774, 315, 279, 43746, 14338, 3941, 11, 323, 23649, 4519, 304, 279, 1887, 30295, 527, 10675, 13, 5810, 584, 20461, 459, 24291, 31228, 19576, 315, 459, 7524, 31228, 432, 26140, 1646, 304, 279, 24955, 96857, 59086, 17942, 11, 32145, 264, 8844, 59086, 11595, 315, 342, 611, 117774, 4056, 220, 15, 13, 21, 13, 578, 31228, 12035, 315, 279, 42991, 374, 264, 2307, 77752, 287, 16622, 23711, 304, 264, 272, 48, 1507, 6642, 13, 1226, 23846, 5043, 323, 39445, 31228, 1614, 87458, 323, 5891, 18734, 315, 279, 2926, 2874, 60320, 1614, 11, 1694, 279, 1455, 12742, 12223, 315, 279, 92106, 1646, 13, 29438, 43897, 10105, 311, 1690, 31228, 5435, 374, 264, 1633, 17436, 3465, 220, 16, 662, 578, 2944, 374, 279, 75251, 3544, 1396, 315, 12628, 315, 11542, 304, 264, 31228, 1887, 11, 23537, 55580, 2410, 323, 5044, 430, 6847, 12771, 279, 17357, 315, 3118, 29924, 19002, 13, 362, 3686, 311, 387, 21091, 20789, 7528, 31228, 6500, 315, 14343, 1404, 1053, 387, 13171, 315, 30820, 22581, 1455, 31228, 5435, 220, 16, 1174, 220, 17, 662, 362, 810, 43303, 5603, 311, 11322, 264, 55580, 4732, 455, 304, 279, 3221, 3938, 374, 31228, 19576, 220, 16, 1174, 220, 17, 1174, 220, 18, 662, 763, 279, 12914, 315, 24291, 31228, 19576, 11, 264, 41891, 323, 1664, 35172, 69855, 21075, 31228, 1887, 374, 24784, 8800, 264, 31228, 3575, 315, 2802, 304, 2015, 311, 56459, 1202, 30295, 13, 8876, 279, 1890, 39006, 315, 11633, 3412, 369, 2225, 6067, 11, 279, 6425, 315, 279, 16940, 31228, 3575, 374, 68695, 555, 46071, 279, 892, 15740, 315, 279, 78220, 5918, 1646, 1887, 11, 1418, 3339, 1005, 315, 1202, 47701, 31228, 2136, 13, 1115, 13155, 1253, 387, 9435, 311, 279, 19576, 315, 6485, 31228, 5435, 11, 304, 279, 9090, 13517, 11223, 555, 89320, 77, 1543, 220, 16, 662, 56413, 19576, 574, 10887, 389, 5370, 22772, 15771, 13, 26379, 315, 24291, 31228, 19576, 527, 279, 4007, 315, 81682, 21427, 7710, 220, 19, 323, 33297, 2191, 220, 20, 449, 9439, 33299, 323, 279, 19576, 315, 264, 31228, 33297, 323, 279, 31194, 582, 24524, 449, 31691, 65125, 220, 21, 1174, 220, 22, 662, 578, 27501, 315, 2536, 63359, 46780, 22027, 574, 11223, 449, 459, 389, 11843, 575, 31228, 42991, 3196, 389, 2307, 77752, 287, 46121, 220, 23, 1174, 220, 24, 662, 14434, 19576, 31956, 449, 2307, 77752, 287, 7766, 1051, 21091, 369, 81682, 21427, 4211, 220, 605, 323, 12903, 6067, 220, 806, 662, 578, 31228, 432, 26140, 1646, 304, 31228, 70985, 16964, 279, 16628, 1990, 264, 1403, 11852, 19670, 323, 264, 3254, 10484, 1534, 82341, 84741, 3941, 220, 717, 1174, 220, 1032, 662, 763, 279, 7621, 59086, 17942, 11, 902, 1253, 2103, 387, 3831, 304, 279, 5647, 315, 31228, 4135, 24409, 51248, 320, 48, 1507, 705, 264, 42496, 12330, 57304, 320, 49, 27486, 8, 649, 387, 9435, 323, 279, 432, 26140, 1646, 26338, 311, 279, 19455, 4978, 4235, 34, 83533, 1646, 220, 975, 1174, 902, 41255, 1455, 9959, 26350, 304, 56429, 323, 16622, 1229, 1507, 13, 763, 279, 24955, 96857, 59086, 320, 2078, 34, 8, 323, 5655, 3831, 59086, 61911, 11, 1405, 279, 59086, 8333, 374, 30139, 311, 279, 3941, 49969, 220, 868, 1174, 279, 5663, 42496, 3878, 304, 279, 16628, 24051, 1122, 649, 912, 5129, 387, 51533, 323, 279, 432, 27486, 18808, 1523, 13, 1666, 264, 29774, 11, 279, 2860, 3521, 7709, 1396, 304, 279, 31228, 432, 26140, 1646, 374, 539, 1615, 2841, 13, 38267, 369, 832, 3293, 49340, 315, 9455, 459, 4839, 6425, 220, 845, 1174, 459, 8678, 83, 2740, 8036, 6425, 315, 279, 31228, 432, 26140, 1646, 1587, 539, 3073, 4245, 311, 279, 6996, 315, 264, 2132, 1615, 2841, 12472, 902, 45382, 433, 2536, 20653, 14750, 481, 13, 578, 31228, 432, 26140, 1646, 11, 304, 4040, 304, 279, 44379, 17942, 323, 7953, 11, 50829, 2536, 15144, 950, 4519, 323, 16448, 2802, 304, 433, 374, 14948, 555, 3831, 31003, 315, 22772, 17357, 220, 868, 1174, 220, 1114, 1174, 220, 972, 1174, 220, 777, 662, 578, 3230, 57077, 4519, 315, 279, 44379, 17942, 323, 279, 12777, 306, 31085, 315, 279, 432, 27486, 1051, 8767, 13468, 449, 264, 2307, 77752, 287, 16622, 555, 25976, 459, 7319, 7106, 59086, 8333, 220, 508, 1174, 220, 1691, 662, 362, 4528, 5603, 16239, 264, 31405, 2874, 60320, 34356, 311, 264, 3254, 15331, 29280, 859, 5535, 311, 2680, 279, 5655, 3831, 59086, 17942, 304, 264, 8036, 1887, 220, 1313, 662, 578, 44379, 17942, 574, 8813, 1603, 555, 43111, 1491, 15853, 279, 31405, 15837, 315, 264, 2307, 77752, 287, 2874, 60320, 11, 19261, 264, 59086, 8333, 315, 922, 220, 15, 13, 16, 315, 279, 7524, 29280, 859, 11900, 220, 1419, 662, 763, 1057, 5603, 11, 584, 24490, 459, 7524, 31228, 432, 26140, 24051, 1122, 449, 459, 24291, 31228, 19576, 13155, 3196, 389, 279, 3851, 315, 42374, 432, 26140, 6678, 43076, 13, 3296, 264, 18979, 315, 279, 53885, 49969, 11, 279, 44379, 3044, 374, 20097, 304, 279, 7524, 42496, 4124, 11, 10923, 311, 23846, 279, 12742, 1646, 30295, 13, 578, 13155, 1253, 387, 264, 6149, 311, 30820, 7068, 2536, 15144, 950, 56429, 5415, 220, 1187, 1174, 220, 914, 1174, 220, 1627, 323, 1253, 387, 11838, 311, 13488, 9959, 7106, 4211, 1778, 439, 279, 31194, 582, 24524, 304, 320, 16, 489, 220, 16, 8, 15696, 13, 11699, 29683, 30295, 374, 3685, 311, 3113, 264, 1901, 3328, 83036, 797, 2234, 304, 279, 993, 33211, 30236, 1598, 315, 279, 43746, 14338, 3941, 220, 1544, 662, 1115, 30295, 706, 1027, 13468, 449, 31691, 65125, 220, 22, 1174, 39022, 3196, 389, 264, 24051, 1122, 430, 374, 15499, 5552, 311, 279, 44379, 432, 26140, 1646, 13, 1102, 706, 1027, 6982, 6051, 430, 264, 31228, 10474, 9320, 11, 11383, 23537, 264, 86901, 315, 20362, 11, 649, 5101, 2736, 304, 279, 31228, 432, 26140, 1646, 1234, 8475, 4787, 220, 1591, 662, 578, 22772, 8815, 374, 28448, 311, 279, 59086, 8670, 304, 279, 1646, 902, 1253, 387, 27332, 449, 279, 19576, 13155, 10666, 13, 1115, 649, 387, 264, 6041, 1486, 311, 9526, 750, 19874, 9200, 44247, 304, 264, 2678, 323, 1664, 41370, 31228, 1887, 220, 1682, 662, 3161, 264, 7528, 19576, 5603, 11, 279, 30295, 315, 279, 31228, 432, 26140, 1646, 304, 44379, 4787, 574, 30293, 20041, 1633, 6051, 220, 966, 662, 763, 1057, 9526, 584, 38553, 279, 31228, 432, 26140, 1646, 304, 279, 44379, 17942, 32145, 264, 8844, 59086, 8333, 315, 709, 311, 220, 15, 13, 21, 13, 4241, 29293, 389, 1057, 22772, 5137, 11, 584, 23846, 48582, 46350, 31228, 1614, 87458, 323, 5891, 18734, 304, 279, 2874, 60320, 30295, 11, 1694, 264, 12742, 12223, 315, 44379, 13, 578, 18678, 5621, 85, 4023, 30295, 8111, 1455, 9539, 304, 279, 19821, 315, 279, 2874, 60320, 4907, 4751, 304, 279, 1646, 11, 4184, 311, 279, 31293, 505, 7491, 24524, 47590, 13, 763, 5369, 11, 584, 1005, 1057, 3756, 311, 38553, 279, 2539, 31228, 432, 26140, 128257, 198, 128256, 78191, 198, 98428, 56295, 11, 9629, 90398, 11, 38462, 4500, 1389, 311, 7168, 279, 2515, 315, 1778, 4455, 11, 6500, 47590, 527, 2631, 13, 9176, 11618, 304, 7138, 11, 4869, 11, 527, 779, 17395, 430, 21349, 19002, 3775, 13, 56413, 1675, 42391, 1253, 11886, 420, 3575, 13, 3861, 315, 279, 6913, 44247, 304, 7138, 374, 279, 16628, 1990, 3177, 323, 5030, 304, 7397, 74767, 13, 13101, 292, 1705, 315, 13528, 94509, 10181, 315, 12053, 320, 80891, 8, 617, 1457, 1903, 264, 2466, 3094, 7119, 31228, 30126, 8830, 315, 6136, 39097, 13, 1115, 374, 5068, 304, 279, 22037, 26545, 8486, 13, 330, 32, 31228, 42991, 374, 279, 33269, 6566, 315, 264, 31228, 6500, 13, 35341, 661, 311, 264, 31228, 6500, 11, 4869, 11, 433, 374, 539, 3025, 311, 1304, 904, 29217, 11, 719, 374, 6319, 369, 279, 6425, 315, 264, 3738, 3575, 1359, 2795, 622, 55636, 26531, 372, 2448, 56056, 315, 735, 964, 596, 13101, 1609, 35965, 8696, 96562, 320, 644, 7815, 315, 28415, 570, 1666, 279, 1579, 15374, 315, 7397, 74767, 4250, 387, 16365, 6724, 449, 29924, 7106, 26018, 11, 12074, 1093, 26531, 372, 2448, 56056, 1005, 264, 31228, 1646, 13, 32255, 449, 14248, 315, 279, 96562, 7328, 578, 18673, 10782, 39750, 74, 76124, 42305, 1609, 320, 11042, 47, 11, 10181, 369, 578, 91867, 22925, 87615, 28415, 705, 568, 21091, 369, 279, 1176, 892, 304, 459, 9526, 430, 31228, 47590, 315, 279, 16628, 1990, 3177, 323, 5030, 990, 304, 17966, 13, 578, 16628, 1990, 3177, 323, 5030, 304, 7397, 74767, 649, 387, 7633, 439, 459, 16628, 315, 89235, 315, 3177, 449, 279, 33299, 315, 5030, 389, 279, 90090, 2237, 13, 578, 1579, 15374, 315, 420, 17383, 315, 7154, 220, 1041, 3346, 13533, 430, 433, 374, 3917, 311, 5718, 315, 31228, 22027, 11, 902, 374, 5107, 311, 38553, 449, 29924, 19002, 323, 4382, 9660, 13, 763, 5410, 25213, 11, 2038, 374, 15609, 555, 264, 3480, 430, 649, 3637, 2038, 439, 7315, 477, 832, 13, 56413, 9660, 11, 555, 13168, 11, 527, 3025, 311, 9855, 279, 5415, 315, 7315, 323, 832, 520, 279, 1890, 892, 4184, 311, 31228, 22027, 5718, 13, 32140, 11, 31228, 19002, 477, 279, 35388, 31228, 1675, 42391, 649, 11886, 279, 3575, 810, 6288, 323, 30820, 13, 26531, 372, 2448, 56056, 323, 813, 1080, 34603, 1105, 617, 1457, 8040, 832, 315, 279, 1176, 31301, 6956, 369, 264, 31228, 42991, 315, 3177, 1474, 1683, 16628, 25, 7445, 77752, 287, 46121, 439, 31228, 9660, 4097, 279, 33299, 11, 1418, 66669, 29280, 3046, 4097, 279, 89235, 13, 578, 98417, 26399, 304, 17843, 459, 2515, 449, 279, 31228, 2766, 323, 279, 29280, 859, 26619, 1403, 14329, 5415, 520, 279, 1890, 892, 13, 330, 48, 60320, 323, 29280, 859, 527, 34356, 1359, 2795, 8096, 2947, 339, 13412, 315, 735, 964, 596, 350, 11960, 13, 330, 2028, 374, 1101, 279, 2944, 369, 279, 75251, 13241, 22702, 8824, 7863, 311, 29924, 19002, 1210, 48550, 7712, 287, 315, 420, 16188, 17966, 315, 31228, 30126, 706, 21091, 69543, 315, 24291, 31228, 19576, 449, 2307, 77752, 287, 46121, 11, 279, 12074, 2019, 13, 1666, 264, 1828, 3094, 11, 814, 3197, 311, 13334, 872, 1887, 4669, 1690, 1023, 4857, 10215, 13, 330, 1999, 950, 19576, 315, 420, 11838, 1887, 1053, 1935, 5129, 1109, 279, 4325, 315, 279, 15861, 1359, 2795, 11826, 1226, 3422, 11, 889, 706, 1027, 14836, 264, 3318, 1912, 520, 735, 964, 596, 13101, 1609, 35965, 8696, 96562, 2533, 220, 679, 20, 13, 1442, 279, 13205, 31228, 30126, 19576, 374, 6992, 11, 420, 690, 387, 264, 330, 67697, 11046, 389, 279, 1648, 7119, 264, 20789, 31228, 6500, 1210, 220, 128257, 198 ]

1,843

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Transition metal dichalcogenide moiré bilayers with spatially periodic potentials have emerged as a highly tunable platform for studying both electronic 1 , 2 , 3 , 4 , 5 , 6 and excitonic 4 , 7 , 8 , 9 , 10 , 11 , 12 , 13 phenomena. The power of these systems lies in the combination of strong Coulomb interactions with the capability of controlling the charge number in a moiré potential trap. Electronically, exotic charge orders at both integer and fractional fillings have been discovered 2 , 5 . However, the impact of charging effects on excitons trapped in moiré potentials is poorly understood. Here, we report the observation of moiré trions and their doping-dependent photoluminescence polarization in H-stacked MoSe 2 /WSe 2 heterobilayers. We find that as moiré traps are filled with either electrons or holes, new sets of interlayer exciton photoluminescence peaks with narrow linewidths emerge about 7 meV below the energy of the neutral moiré excitons. Circularly polarized photoluminescence reveals switching from co-circular to cross-circular polarizations as moiré excitons go from being negatively charged and neutral to positively charged. This switching results from the competition between valley-flip and spin-flip energy relaxation pathways of photo-excited electrons during interlayer trion formation. Our results offer a starting point for engineering both bosonic and fermionic many-body effects based on moiré excitons 14 . Main Heterostructures of monolayer semiconductors offer a powerful platform to explore light–matter interactions. Using MoSe 2 /WSe 2 heterobilayers as an example, a type II band alignment leads to interlayer excitons with long population and polarization lifetimes 15 . With careful stacking to produce atomically clean heterostructure interfaces, a moiré superlattice can be formed with a periodically varying interlayer separation and electronic bandgap 16 , 17 . This periodic potential modulation of the electronic structure in real space functions as an ordered nanodot array and fundamentally modifies the interlayer exciton properties 8 , 9 , 10 , 11 , 12 , 18 , 19 , 20 , 21 . Quantum-dot-like moiré exciton photoluminescence (PL) with twist-angle control of valley polarization and Landé g -factor has been reported 10 , 12 , 13 . Strong photon anti-bunching of moiré excitons has also been observed 13 , implying its potential for quantum optoelectronic applications. In addition to hexagonal moiré superlattices, strain-induced one-dimensional moiré structures have been identified 9 , which lead to linearly polarized moiré exciton luminescence, in contrast with the circularly polarized luminescence of the unstrained heterobilayers. Besides moiré excitons, their charged counterparts, such as trions add a new dimension to controlling the interactions between excitons in the moiré traps (Fig. 1a ). Unlike bosonic particles (excitons), the charged counterparts, trions, obey fermionic statistics. Transport properties and responses to electric and magnetic fields are significantly different between the two classes of particles. In addition to dipolar interaction, the trions can interact with each other through the long-range Coulomb interaction. The realization of charged moiré excitons is important for allowing an optically accessible platform to explore fermionic many-body effects. However, while rapid progress has been made in characterizing neutral moiré interlayer excitons, their charged counterparts remain elusive. It is unclear whether moiré trions exist, and, if so, how they compare to neutral excitons. Fig. 1: Moiré trions are formed with electrostatic gating. a , Schematics of neutral and charged excitons in moiré traps. b , Schematics of double-BN encapsulated devices with dual graphite gates. c , PL intensity plot as a function of doping and photon energy. At both electron and hole doping, new sets of peaks form at ~7 meV lower energy, with a rapid drop in the PL intensity of the charge neutral moiré exciton. Insets depict the charge configuration of both neutral and charged excitons. V g , gate voltage; a.u., arbitrary units. d , Temperature-dependent PL intensity plot at a fixed hole doping, showing the shallow potential of moiré traps. Inset is the PL spectrum collected at 1.6 K. e , PL spectrum of negative moiré trions versus electric field applied out-of-plane with fixed doping. Source data Full size image In this work, we demonstrate formation of interlayer moiré trions in superlattices formed by stacked WSe 2 and MoSe 2 monolayers. Through electrostatic gating, we find that once the sample is electron- or hole-doped, new sets of moiré trion PL peaks appear ~7 meV lower in energy with respect to charge neutral moiré excitons. The Zeeman splitting of oppositely polarized trion PL peaks is consistent with electron–hole valley-pairing under H-type alignment. In addition, the spin optical polarization of the emitter is tuned with doping. When the system is hole doped, valley polarization of the positively charged moiré trion is inverted compared to both neutral excitons and negatively charged trions. Such polarization inversion arises from the competition between spin-flip but valley-conserved and spin-conserved but valley-flipped relaxation channels of electrons in the formation of interlayer trions. The population lifetimes of moiré trions and excitons are also measured by time-resolved PL. Combining polarization-resolved excitation and detection, the valley polarization lifetime is found to be hundreds of nanoseconds. The structure of the device with a dual-gated geometry is shown in Fig. 1b . The WSe 2 /MoSe 2 heterobilayer is assembled using standard dry-transfer techniques with hexagonal boron nitride (BN) encapsulation and semi-transparent thin graphite top and bottom gates to independently control doping and vertical electric field effects. Edge contacts are used to connect both MoSe 2 and WSe 2 layers. All samples are H-stacked, that is, with nearly 60 o twist angle. For the device presented in the main text, the moiré lattice constant is about 11–12 nm, as determined by piezoresponse force microscopy 9 , 22 (Supplementary Fig. S 1 ). Multiple devices have been studied and show consistent results. All measurements are performed with laser excitation at 1.713 eV (close to the WSe 2 A exciton resonance) at a temperature of 1.6 K, unless otherwise specified. We first describe PL measurements of interlayer moiré excitons as a function of doping (Fig. 1c ).", "role": "user" }, { "content": "In physics, the moiré pattern is a specific geometrical design in which sets of straight or curved lines are superposed on top of each other. Recent studies have found that bilayers of transition metal dichalcogenide materials arranged in moiré patterns could be particularly promising for studying electronic phenomena and excitons (i.e., concentrations of energy in crystals formed by an excited electron and an associated hole). Transition metal dichalcogenide moiré bilayers have advantageous characteristics for studying both electronic and excitonic physical phenomena, including strong Coulomb interactions. Past research studies have successfully used these systems to make several interesting discoveries, such as exotic charge orders at both integer and fractional fillings. Researchers at University of Washington and other institutes worldwide have recently carried out a study specifically examining a Transition metal dichalcogenide moiré system comprised of molybdenum diselenide (MoSe2)/tungsten diselenide (WSe2) heterobilayers, Their paper, published in Nature Nanotechnology, reports the observation of moiré-arranged trions (i.e., localized excitations consisting of three charged particles) in H-stacked MoSe2/WSe2 heterobilayers. \"Periodic moiré potential naturally occurs in transitional metal dichalcogenides moiré superlattices. Several years ago, we envisioned that the periodic potential can function as arrays of quantum dots,\" Wang Yao, one of the researchers who carried out the study, told TechXplore. \"Based on this idea, our team demonstrated charge neutral moiré excitons in twisted MoSe2/WSe2 heterobilayers in 2019.\" The work builds on the group's previous studies focusing on transitional metal dichalcogenides moiré superlattices. While in their past research, the team was able to observe charge-neutral moiré excitons in twisted MoSe2/WSe2 heterobilayers, in their new study, they tried to add the electrostatic control of the carrier density to the same moiré system. This ultimately enabled them to realize charged moiré excitons, which are also known as moiré trions. \"In our experiments, we measured the light emission from the heterolayers we examined,\" Xu explained. \"By focusing on emission properties (linewidth, polarization, intensity, energy etc) as a function of carrier doping, magnetic field and temperature, we were able to identify moiré trions.\" The findings could have important implications for the future development of new nanotechnology, as well as for the study of excitonic phenomena. In their future work, the team hopes to utilize moiré systems to investigate different physical phenomena. \"We showed that moiré potential can also trap charged excitons,\" Xu said. \"Combined with the charge neutral ones, the heterobilayer can be used as a platform for studying both bosonic and fermionic many-body effects based on moiré excitons. In our next studies, we plan to study both equilibrium and non-equilibrium many body effects based on the moiré systems.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Transition metal dichalcogenide moiré bilayers with spatially periodic potentials have emerged as a highly tunable platform for studying both electronic 1 , 2 , 3 , 4 , 5 , 6 and excitonic 4 , 7 , 8 , 9 , 10 , 11 , 12 , 13 phenomena. The power of these systems lies in the combination of strong Coulomb interactions with the capability of controlling the charge number in a moiré potential trap. Electronically, exotic charge orders at both integer and fractional fillings have been discovered 2 , 5 . However, the impact of charging effects on excitons trapped in moiré potentials is poorly understood. Here, we report the observation of moiré trions and their doping-dependent photoluminescence polarization in H-stacked MoSe 2 /WSe 2 heterobilayers. We find that as moiré traps are filled with either electrons or holes, new sets of interlayer exciton photoluminescence peaks with narrow linewidths emerge about 7 meV below the energy of the neutral moiré excitons. Circularly polarized photoluminescence reveals switching from co-circular to cross-circular polarizations as moiré excitons go from being negatively charged and neutral to positively charged. This switching results from the competition between valley-flip and spin-flip energy relaxation pathways of photo-excited electrons during interlayer trion formation. Our results offer a starting point for engineering both bosonic and fermionic many-body effects based on moiré excitons 14 . Main Heterostructures of monolayer semiconductors offer a powerful platform to explore light–matter interactions. Using MoSe 2 /WSe 2 heterobilayers as an example, a type II band alignment leads to interlayer excitons with long population and polarization lifetimes 15 . With careful stacking to produce atomically clean heterostructure interfaces, a moiré superlattice can be formed with a periodically varying interlayer separation and electronic bandgap 16 , 17 . This periodic potential modulation of the electronic structure in real space functions as an ordered nanodot array and fundamentally modifies the interlayer exciton properties 8 , 9 , 10 , 11 , 12 , 18 , 19 , 20 , 21 . Quantum-dot-like moiré exciton photoluminescence (PL) with twist-angle control of valley polarization and Landé g -factor has been reported 10 , 12 , 13 . Strong photon anti-bunching of moiré excitons has also been observed 13 , implying its potential for quantum optoelectronic applications. In addition to hexagonal moiré superlattices, strain-induced one-dimensional moiré structures have been identified 9 , which lead to linearly polarized moiré exciton luminescence, in contrast with the circularly polarized luminescence of the unstrained heterobilayers. Besides moiré excitons, their charged counterparts, such as trions add a new dimension to controlling the interactions between excitons in the moiré traps (Fig. 1a ). Unlike bosonic particles (excitons), the charged counterparts, trions, obey fermionic statistics. Transport properties and responses to electric and magnetic fields are significantly different between the two classes of particles. In addition to dipolar interaction, the trions can interact with each other through the long-range Coulomb interaction. The realization of charged moiré excitons is important for allowing an optically accessible platform to explore fermionic many-body effects. However, while rapid progress has been made in characterizing neutral moiré interlayer excitons, their charged counterparts remain elusive. It is unclear whether moiré trions exist, and, if so, how they compare to neutral excitons. Fig. 1: Moiré trions are formed with electrostatic gating. a , Schematics of neutral and charged excitons in moiré traps. b , Schematics of double-BN encapsulated devices with dual graphite gates. c , PL intensity plot as a function of doping and photon energy. At both electron and hole doping, new sets of peaks form at ~7 meV lower energy, with a rapid drop in the PL intensity of the charge neutral moiré exciton. Insets depict the charge configuration of both neutral and charged excitons. V g , gate voltage; a.u., arbitrary units. d , Temperature-dependent PL intensity plot at a fixed hole doping, showing the shallow potential of moiré traps. Inset is the PL spectrum collected at 1.6 K. e , PL spectrum of negative moiré trions versus electric field applied out-of-plane with fixed doping. Source data Full size image In this work, we demonstrate formation of interlayer moiré trions in superlattices formed by stacked WSe 2 and MoSe 2 monolayers. Through electrostatic gating, we find that once the sample is electron- or hole-doped, new sets of moiré trion PL peaks appear ~7 meV lower in energy with respect to charge neutral moiré excitons. The Zeeman splitting of oppositely polarized trion PL peaks is consistent with electron–hole valley-pairing under H-type alignment. In addition, the spin optical polarization of the emitter is tuned with doping. When the system is hole doped, valley polarization of the positively charged moiré trion is inverted compared to both neutral excitons and negatively charged trions. Such polarization inversion arises from the competition between spin-flip but valley-conserved and spin-conserved but valley-flipped relaxation channels of electrons in the formation of interlayer trions. The population lifetimes of moiré trions and excitons are also measured by time-resolved PL. Combining polarization-resolved excitation and detection, the valley polarization lifetime is found to be hundreds of nanoseconds. The structure of the device with a dual-gated geometry is shown in Fig. 1b . The WSe 2 /MoSe 2 heterobilayer is assembled using standard dry-transfer techniques with hexagonal boron nitride (BN) encapsulation and semi-transparent thin graphite top and bottom gates to independently control doping and vertical electric field effects. Edge contacts are used to connect both MoSe 2 and WSe 2 layers. All samples are H-stacked, that is, with nearly 60 o twist angle. For the device presented in the main text, the moiré lattice constant is about 11–12 nm, as determined by piezoresponse force microscopy 9 , 22 (Supplementary Fig. S 1 ). Multiple devices have been studied and show consistent results. All measurements are performed with laser excitation at 1.713 eV (close to the WSe 2 A exciton resonance) at a temperature of 1.6 K, unless otherwise specified. We first describe PL measurements of interlayer moiré excitons as a function of doping (Fig. 1c ).<|im_end|> <|im_start|>assistant In physics, the moiré pattern is a specific geometrical design in which sets of straight or curved lines are superposed on top of each other. Recent studies have found that bilayers of transition metal dichalcogenide materials arranged in moiré patterns could be particularly promising for studying electronic phenomena and excitons (i.e., concentrations of energy in crystals formed by an excited electron and an associated hole). Transition metal dichalcogenide moiré bilayers have advantageous characteristics for studying both electronic and excitonic physical phenomena, including strong Coulomb interactions. Past research studies have successfully used these systems to make several interesting discoveries, such as exotic charge orders at both integer and fractional fillings. Researchers at University of Washington and other institutes worldwide have recently carried out a study specifically examining a Transition metal dichalcogenide moiré system comprised of molybdenum diselenide (MoSe2)/tungsten diselenide (WSe2) heterobilayers, Their paper, published in Nature Nanotechnology, reports the observation of moiré-arranged trions (i.e., localized excitations consisting of three charged particles) in H-stacked MoSe2/WSe2 heterobilayers. "Periodic moiré potential naturally occurs in transitional metal dichalcogenides moiré superlattices. Several years ago, we envisioned that the periodic potential can function as arrays of quantum dots," Wang Yao, one of the researchers who carried out the study, told TechXplore. "Based on this idea, our team demonstrated charge neutral moiré excitons in twisted MoSe2/WSe2 heterobilayers in 2019." The work builds on the group's previous studies focusing on transitional metal dichalcogenides moiré superlattices. While in their past research, the team was able to observe charge-neutral moiré excitons in twisted MoSe2/WSe2 heterobilayers, in their new study, they tried to add the electrostatic control of the carrier density to the same moiré system. This ultimately enabled them to realize charged moiré excitons, which are also known as moiré trions. "In our experiments, we measured the light emission from the heterolayers we examined," Xu explained. "By focusing on emission properties (linewidth, polarization, intensity, energy etc) as a function of carrier doping, magnetic field and temperature, we were able to identify moiré trions." The findings could have important implications for the future development of new nanotechnology, as well as for the study of excitonic phenomena. In their future work, the team hopes to utilize moiré systems to investigate different physical phenomena. "We showed that moiré potential can also trap charged excitons," Xu said. "Combined with the charge neutral ones, the heterobilayer can be used as a platform for studying both bosonic and fermionic many-body effects based on moiré excitons. In our next studies, we plan to study both equilibrium and non-equilibrium many body effects based on the moiré systems." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 38821, 9501, 29953, 17356, 11968, 579, 4647, 404, 978, 20934, 5184, 449, 29079, 398, 39445, 95358, 617, 22763, 439, 264, 7701, 11716, 481, 5452, 369, 21630, 2225, 14683, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 323, 25435, 14338, 220, 19, 1174, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 44247, 13, 578, 2410, 315, 1521, 6067, 15812, 304, 279, 10824, 315, 3831, 67948, 2925, 22639, 449, 279, 23099, 315, 26991, 279, 6900, 1396, 304, 264, 4647, 404, 978, 4754, 23709, 13, 77976, 2740, 11, 39418, 6900, 10373, 520, 2225, 7698, 323, 69309, 5266, 826, 617, 1027, 11352, 220, 17, 1174, 220, 20, 662, 4452, 11, 279, 5536, 315, 23468, 6372, 389, 25435, 2439, 31691, 304, 4647, 404, 978, 95358, 374, 31555, 16365, 13, 5810, 11, 584, 1934, 279, 22695, 315, 4647, 404, 978, 490, 919, 323, 872, 97928, 43918, 4604, 1152, 1572, 36634, 83245, 304, 473, 5594, 11440, 6178, 1542, 220, 17, 611, 54, 1542, 220, 17, 30548, 29029, 5184, 13, 1226, 1505, 430, 439, 4647, 404, 978, 45660, 527, 10409, 449, 3060, 57678, 477, 20349, 11, 502, 7437, 315, 958, 10546, 25435, 263, 4604, 1152, 1572, 36634, 40035, 449, 15376, 48947, 82, 34044, 922, 220, 22, 757, 53, 3770, 279, 4907, 315, 279, 21277, 4647, 404, 978, 25435, 2439, 13, 46861, 398, 25685, 1534, 4604, 1152, 1572, 36634, 21667, 28865, 505, 1080, 1824, 22190, 311, 5425, 1824, 22190, 25685, 8200, 439, 4647, 404, 978, 25435, 2439, 733, 505, 1694, 48291, 11684, 323, 21277, 311, 40646, 11684, 13, 1115, 28865, 3135, 505, 279, 10937, 1990, 34681, 12556, 575, 323, 12903, 12556, 575, 4907, 43685, 44014, 315, 6685, 98033, 1639, 57678, 2391, 958, 10546, 490, 290, 18488, 13, 5751, 3135, 3085, 264, 6041, 1486, 369, 15009, 2225, 43746, 14338, 323, 81682, 21427, 1690, 9534, 6372, 3196, 389, 4647, 404, 978, 25435, 2439, 220, 975, 662, 4802, 473, 1430, 78, 47194, 315, 1647, 337, 1155, 5347, 1965, 1076, 1105, 3085, 264, 8147, 5452, 311, 13488, 3177, 4235, 60065, 22639, 13, 12362, 6178, 1542, 220, 17, 611, 54, 1542, 220, 17, 30548, 29029, 5184, 439, 459, 3187, 11, 264, 955, 8105, 7200, 17632, 11767, 311, 958, 10546, 25435, 2439, 449, 1317, 7187, 323, 83245, 10345, 7034, 220, 868, 662, 3161, 16994, 75172, 311, 8356, 19670, 2740, 4335, 30548, 78, 7993, 25066, 11, 264, 4647, 404, 978, 2307, 75, 32891, 649, 387, 14454, 449, 264, 48582, 29865, 958, 10546, 25768, 323, 14683, 7200, 42510, 220, 845, 1174, 220, 1114, 662, 1115, 39445, 4754, 67547, 315, 279, 14683, 6070, 304, 1972, 3634, 5865, 439, 459, 11713, 20622, 347, 354, 1358, 323, 43593, 84049, 279, 958, 10546, 25435, 263, 6012, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 972, 1174, 220, 777, 1174, 220, 508, 1174, 220, 1691, 662, 56413, 82002, 12970, 4647, 404, 978, 25435, 263, 4604, 1152, 1572, 36634, 320, 2989, 8, 449, 27744, 35481, 2585, 315, 34681, 83245, 323, 11680, 978, 342, 482, 38691, 706, 1027, 5068, 220, 605, 1174, 220, 717, 1174, 220, 1032, 662, 27191, 69010, 7294, 1481, 3265, 287, 315, 4647, 404, 978, 25435, 2439, 706, 1101, 1027, 13468, 220, 1032, 1174, 73967, 1202, 4754, 369, 31228, 3469, 4748, 772, 8535, 8522, 13, 763, 5369, 311, 12651, 24346, 4647, 404, 978, 2307, 75, 1617, 1238, 11, 26800, 38973, 832, 33520, 4647, 404, 978, 14726, 617, 1027, 11054, 220, 24, 1174, 902, 3063, 311, 13790, 398, 25685, 1534, 4647, 404, 978, 25435, 263, 41263, 1572, 36634, 11, 304, 13168, 449, 279, 28029, 398, 25685, 1534, 41263, 1572, 36634, 315, 279, 653, 58827, 30548, 29029, 5184, 13, 31909, 4647, 404, 978, 25435, 2439, 11, 872, 11684, 38495, 11, 1778, 439, 490, 919, 923, 264, 502, 13167, 311, 26991, 279, 22639, 1990, 25435, 2439, 304, 279, 4647, 404, 978, 45660, 320, 30035, 13, 220, 16, 64, 7609, 27140, 43746, 14338, 19252, 320, 40541, 275, 2439, 705, 279, 11684, 38495, 11, 490, 919, 11, 41701, 81682, 21427, 13443, 13, 17159, 6012, 323, 14847, 311, 9249, 323, 24924, 5151, 527, 12207, 2204, 1990, 279, 1403, 6989, 315, 19252, 13, 763, 5369, 311, 24522, 7569, 16628, 11, 279, 490, 919, 649, 16681, 449, 1855, 1023, 1555, 279, 1317, 31608, 67948, 2925, 16628, 13, 578, 49803, 315, 11684, 4647, 404, 978, 25435, 2439, 374, 3062, 369, 10923, 459, 3469, 2740, 15987, 5452, 311, 13488, 81682, 21427, 1690, 9534, 6372, 13, 4452, 11, 1418, 11295, 5208, 706, 1027, 1903, 304, 3752, 4954, 21277, 4647, 404, 978, 958, 10546, 25435, 2439, 11, 872, 11684, 38495, 7293, 66684, 13, 1102, 374, 25420, 3508, 4647, 404, 978, 490, 919, 3073, 11, 323, 11, 422, 779, 11, 1268, 814, 9616, 311, 21277, 25435, 2439, 13, 23966, 13, 220, 16, 25, 6178, 404, 978, 490, 919, 527, 14454, 449, 25396, 2020, 74499, 13, 264, 1174, 328, 2464, 29470, 315, 21277, 323, 11684, 25435, 2439, 304, 4647, 404, 978, 45660, 13, 293, 1174, 328, 2464, 29470, 315, 2033, 7826, 45, 43669, 7913, 7766, 449, 19091, 95273, 35634, 13, 272, 1174, 10528, 21261, 7234, 439, 264, 734, 315, 97928, 323, 69010, 4907, 13, 2468, 2225, 17130, 323, 14512, 97928, 11, 502, 7437, 315, 40035, 1376, 520, 4056, 22, 757, 53, 4827, 4907, 11, 449, 264, 11295, 6068, 304, 279, 10528, 21261, 315, 279, 6900, 21277, 4647, 404, 978, 25435, 263, 13, 76467, 43504, 279, 6900, 6683, 315, 2225, 21277, 323, 11684, 25435, 2439, 13, 650, 342, 1174, 18618, 22465, 26, 264, 11895, 2637, 25142, 8316, 13, 294, 1174, 38122, 43918, 10528, 21261, 7234, 520, 264, 8521, 14512, 97928, 11, 9204, 279, 26682, 4754, 315, 4647, 404, 978, 45660, 13, 763, 751, 374, 279, 10528, 20326, 14890, 520, 220, 16, 13, 21, 735, 13, 384, 1174, 10528, 20326, 315, 8389, 4647, 404, 978, 490, 919, 19579, 9249, 2115, 9435, 704, 8838, 90649, 449, 8521, 97928, 13, 8922, 828, 8797, 1404, 2217, 763, 420, 990, 11, 584, 20461, 18488, 315, 958, 10546, 4647, 404, 978, 490, 919, 304, 2307, 75, 1617, 1238, 14454, 555, 42415, 468, 1542, 220, 17, 323, 6178, 1542, 220, 17, 1647, 337, 5184, 13, 17331, 25396, 2020, 74499, 11, 584, 1505, 430, 3131, 279, 6205, 374, 17130, 12, 477, 14512, 1773, 16771, 11, 502, 7437, 315, 4647, 404, 978, 490, 290, 10528, 40035, 5101, 4056, 22, 757, 53, 4827, 304, 4907, 449, 5201, 311, 6900, 21277, 4647, 404, 978, 25435, 2439, 13, 578, 10120, 16357, 45473, 315, 8081, 275, 989, 25685, 1534, 490, 290, 10528, 40035, 374, 13263, 449, 17130, 4235, 31520, 34681, 2320, 1334, 287, 1234, 473, 10827, 17632, 13, 763, 5369, 11, 279, 12903, 29393, 83245, 315, 279, 48363, 374, 33519, 449, 97928, 13, 3277, 279, 1887, 374, 14512, 294, 16771, 11, 34681, 83245, 315, 279, 40646, 11684, 4647, 404, 978, 490, 290, 374, 47801, 7863, 311, 2225, 21277, 25435, 2439, 323, 48291, 11684, 490, 919, 13, 15483, 83245, 47588, 48282, 505, 279, 10937, 1990, 12903, 12556, 575, 719, 34681, 69604, 2841, 323, 12903, 69604, 2841, 719, 34681, 12556, 6586, 43685, 12006, 315, 57678, 304, 279, 18488, 315, 958, 10546, 490, 919, 13, 578, 7187, 10345, 7034, 315, 4647, 404, 978, 490, 919, 323, 25435, 2439, 527, 1101, 17303, 555, 892, 11849, 8905, 10528, 13, 23262, 5859, 83245, 11849, 8905, 3521, 7709, 323, 18468, 11, 279, 34681, 83245, 19569, 374, 1766, 311, 387, 11758, 315, 20622, 76989, 13, 578, 6070, 315, 279, 3756, 449, 264, 19091, 2427, 660, 17484, 374, 6982, 304, 23966, 13, 220, 16, 65, 662, 578, 468, 1542, 220, 17, 611, 26694, 1542, 220, 17, 30548, 29029, 1155, 374, 35105, 1701, 5410, 9235, 93791, 12823, 449, 12651, 24346, 32732, 263, 25719, 1425, 320, 15967, 8, 43669, 2987, 323, 18768, 75318, 15792, 95273, 1948, 323, 5740, 35634, 311, 29235, 2585, 97928, 323, 12414, 9249, 2115, 6372, 13, 10564, 19015, 527, 1511, 311, 4667, 2225, 6178, 1542, 220, 17, 323, 468, 1542, 220, 17, 13931, 13, 2052, 10688, 527, 473, 5594, 11440, 11, 430, 374, 11, 449, 7154, 220, 1399, 297, 27744, 9392, 13, 1789, 279, 3756, 10666, 304, 279, 1925, 1495, 11, 279, 4647, 404, 978, 55372, 6926, 374, 922, 220, 806, 4235, 717, 26807, 11, 439, 11075, 555, 4447, 13028, 2376, 5457, 92914, 220, 24, 1174, 220, 1313, 320, 10254, 67082, 23966, 13, 328, 220, 16, 7609, 29911, 7766, 617, 1027, 20041, 323, 1501, 13263, 3135, 13, 2052, 22323, 527, 10887, 449, 21120, 3521, 7709, 520, 220, 16, 13, 22977, 384, 53, 320, 5669, 311, 279, 468, 1542, 220, 17, 362, 25435, 263, 58081, 8, 520, 264, 9499, 315, 220, 16, 13, 21, 735, 11, 7389, 6062, 5300, 13, 1226, 1176, 7664, 10528, 22323, 315, 958, 10546, 4647, 404, 978, 25435, 2439, 439, 264, 734, 315, 97928, 320, 30035, 13, 220, 16, 66, 7609, 128257, 198, 128256, 78191, 198, 644, 22027, 11, 279, 4647, 404, 978, 5497, 374, 264, 3230, 69086, 12381, 2955, 304, 902, 7437, 315, 7833, 477, 50264, 5238, 527, 2307, 3950, 389, 1948, 315, 1855, 1023, 13, 35390, 7978, 617, 1766, 430, 20934, 5184, 315, 9320, 9501, 29953, 17356, 11968, 579, 7384, 28902, 304, 4647, 404, 978, 12912, 1436, 387, 8104, 26455, 369, 21630, 14683, 44247, 323, 25435, 2439, 320, 72, 1770, 2637, 32466, 315, 4907, 304, 48473, 14454, 555, 459, 12304, 17130, 323, 459, 5938, 14512, 570, 38821, 9501, 29953, 17356, 11968, 579, 4647, 404, 978, 20934, 5184, 617, 76824, 17910, 369, 21630, 2225, 14683, 323, 25435, 14338, 7106, 44247, 11, 2737, 3831, 67948, 2925, 22639, 13, 24561, 3495, 7978, 617, 7946, 1511, 1521, 6067, 311, 1304, 3892, 7185, 54098, 11, 1778, 439, 39418, 6900, 10373, 520, 2225, 7698, 323, 69309, 5266, 826, 13, 59250, 520, 3907, 315, 6652, 323, 1023, 94812, 15603, 617, 6051, 11953, 704, 264, 4007, 11951, 38936, 264, 38821, 9501, 29953, 17356, 11968, 579, 4647, 404, 978, 1887, 40056, 315, 296, 5849, 65, 5294, 372, 834, 8564, 579, 320, 26694, 1542, 17, 5738, 83, 2234, 16172, 834, 8564, 579, 320, 54, 1542, 17, 8, 30548, 29029, 5184, 11, 11205, 5684, 11, 4756, 304, 22037, 33242, 52536, 11, 6821, 279, 22695, 315, 4647, 404, 978, 12, 1138, 3811, 490, 919, 320, 72, 1770, 2637, 44589, 25435, 811, 31706, 315, 2380, 11684, 19252, 8, 304, 473, 5594, 11440, 6178, 1542, 17, 22964, 1542, 17, 30548, 29029, 5184, 13, 330, 24684, 292, 4647, 404, 978, 4754, 18182, 13980, 304, 66743, 9501, 29953, 17356, 11968, 3422, 4647, 404, 978, 2307, 75, 1617, 1238, 13, 26778, 1667, 4227, 11, 584, 74389, 430, 279, 39445, 4754, 649, 734, 439, 18893, 315, 31228, 32094, 1359, 29346, 91030, 11, 832, 315, 279, 12074, 889, 11953, 704, 279, 4007, 11, 3309, 17829, 55, 79, 20763, 13, 330, 29815, 389, 420, 4623, 11, 1057, 2128, 21091, 6900, 21277, 4647, 404, 978, 25435, 2439, 304, 38817, 6178, 1542, 17, 22964, 1542, 17, 30548, 29029, 5184, 304, 220, 679, 24, 1210, 578, 990, 22890, 389, 279, 1912, 596, 3766, 7978, 21760, 389, 66743, 9501, 29953, 17356, 11968, 3422, 4647, 404, 978, 2307, 75, 1617, 1238, 13, 6104, 304, 872, 3347, 3495, 11, 279, 2128, 574, 3025, 311, 23846, 6900, 92322, 4647, 404, 978, 25435, 2439, 304, 38817, 6178, 1542, 17, 22964, 1542, 17, 30548, 29029, 5184, 11, 304, 872, 502, 4007, 11, 814, 6818, 311, 923, 279, 25396, 2020, 2585, 315, 279, 19115, 17915, 311, 279, 1890, 4647, 404, 978, 1887, 13, 1115, 13967, 9147, 1124, 311, 13383, 11684, 4647, 404, 978, 25435, 2439, 11, 902, 527, 1101, 3967, 439, 4647, 404, 978, 490, 919, 13, 330, 644, 1057, 21896, 11, 584, 17303, 279, 3177, 41353, 505, 279, 30548, 337, 5184, 584, 25078, 1359, 57514, 11497, 13, 330, 1383, 21760, 389, 41353, 6012, 320, 58312, 11, 83245, 11, 21261, 11, 4907, 5099, 8, 439, 264, 734, 315, 19115, 97928, 11, 24924, 2115, 323, 9499, 11, 584, 1051, 3025, 311, 10765, 4647, 404, 978, 490, 919, 1210, 578, 14955, 1436, 617, 3062, 25127, 369, 279, 3938, 4500, 315, 502, 20622, 52536, 11, 439, 1664, 439, 369, 279, 4007, 315, 25435, 14338, 44247, 13, 763, 872, 3938, 990, 11, 279, 2128, 16388, 311, 29166, 4647, 404, 978, 6067, 311, 19874, 2204, 7106, 44247, 13, 330, 1687, 8710, 430, 4647, 404, 978, 4754, 649, 1101, 23709, 11684, 25435, 2439, 1359, 57514, 1071, 13, 330, 95368, 449, 279, 6900, 21277, 6305, 11, 279, 30548, 29029, 1155, 649, 387, 1511, 439, 264, 5452, 369, 21630, 2225, 43746, 14338, 323, 81682, 21427, 1690, 9534, 6372, 3196, 389, 4647, 404, 978, 25435, 2439, 13, 763, 1057, 1828, 7978, 11, 584, 3197, 311, 4007, 2225, 56411, 323, 2536, 63359, 46780, 1690, 2547, 6372, 3196, 389, 279, 4647, 404, 978, 6067, 1210, 220, 128257, 198 ]

2,128

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Cytoplasmic dynein is a dimeric AAA + motor protein that performs critical roles in eukaryotic cells by moving along microtubules using ATP. Here using cryo-electron microscopy we directly observe the structure of Dictyostelium discoideum dynein dimers on microtubules at near-physiological ATP concentrations. They display remarkable flexibility at a hinge close to the microtubule binding domain (the stalkhead) producing a wide range of head positions. About half the molecules have the two heads separated from one another, with both leading and trailing motors attached to the microtubule. The other half have the two heads and stalks closely superposed in a front-to-back arrangement of the AAA + rings, suggesting specific contact between the heads. All stalks point towards the microtubule minus end. Mean stalk angles depend on the separation between their stalkheads, which allows estimation of inter-head tension. These findings provide a structural framework for understanding dynein’s directionality and unusual stepping behaviour. Introduction Dyneins are a group of motor proteins that move along microtubules (MTs) to cause the beating of the axoneme in cilia and flagella and to perform vital and diverse transport and tethering roles in the cytoplasm of eukaryotic cells, for instance transporting mRNA, growth factors and β-amyloid precursor protein 1 , 2 . Dynein also transports the nucleus in neurons, which is essential to human development and maintenance of healthy neuronal activities 3 , 4 . Growing numbers of neurodegenerative diseases and developmental problems are now known to result from mutations in dynein or dynein-binding proteins 5 , 6 , and dynein-mediated processes are implicated in cancer 7 . So, in addition to its intrinsic interest, understanding dynein mechanism is critical for future treatment of disease. Dyneins have an unusual structure in which each ring-like ATPase head attaches to the MT via a slender, coiled-coil stalk at the tip of which is a small, globular, MT-binding subdomain that we term the stalkhead. (The stalkhead has also been called the MT binding domain (MTBD) but the meaning of MTBD is ambiguous for axonemal dyneins, since the stalkhead binds to one MT doublet and the tail binds to an adjacent doublet; by contrast, ‘stalkhead’ is intuitively understood and more concise.) The atomic structure of the motor domain is known 8 , 9 , 10 . The heart of the motor domain is a AAA + superfamily mechano-enzyme 11 , in which six AAA + motifs form a ring that hydrolyses ATP 1 . Associated with the AAA + ring (hereafter simply ‘ring’) is a C-terminal sequence that is implicated in determining the stall force and run length of the motor 12 , 13 , and that is unusually short in the much-studied yeast dynein 13 , 14 . Cytoplasmic dynein includes two identical heavy chains, each forming tail and motor domains ( Fig. 1a ) 1 . The complex N-terminal tail incorporates additional polypeptides, binds cargoes and dimerizes the motors 15 , 16 , 17 . Between the tail and ring is the linker 18 that provides the power stroke of the motor 19 by switching from bent (primed) to straight (unprimed) 8 , 9 , 10 , 20 . The ring, C-terminal sequence and linker together constitute the head, from which the stalk extends ( Fig. 1a ) 21 . Figure 1: Cryo-EM of dimeric dynein motors bound to MTs in 2 mM Mg-ATP. ( a ) Domains in the amino acid sequence of D. discoideum dynein heavy chain and (right) cartoon depicting the domain architecture of the dimer. The N-terminal tail (residues 1-1387, brown) dimerizes the motor in vivo . The motor includes six AAA + modules: AAA1 (blue)-AAA6 (red). Stalk and stalkhead emerges from AAA4, the strut from AAA5 and sequence numbers indicate the invariant prolines at the stalk-stalkhead junction. Linker (magenta and pale grey) and C-terminal domain (black) lie on opposite faces of the AAA + ring. Proposed moving part of the linker (L, magenta) is indicated. ( b ) Recombinant chimeric dynein dimerized by GST and with stalkhead from human axonemal dynein heavy chain 7; (right) cartoon depicting this dimer. ( c – e ) Cryo-EM of GST-380H7 mixed with MT and ∼ 2 mM Mg-ATP. Contrast is inverted (protein is pale) and dynein’s stepping direction (to the MT minus end) is towards the right in all Figures. ( c ) Dynein particles are crowded along the sides of the MT; such regions were not further analysed. ( d ) In sparse regions of less densely decorated MTs can be seen ‘superposed’ dimers (arrows) in which only a single ring is visible. ( e ) Enlarged view showing ‘superposed’ dimer (single arrow), an ‘offset’ dimer in which both rings are visible (double arrow) and a group of dimers comprising more than two rings (arrowhead). ( f ) Pixel values calculated from the head domains relative to adjacent MT (see Supplementary Fig. 4 ) of offset and superposed dimers and of monomers (mean±s.e.m.). ( g , h ) Image analysis of dimers stringently isolated on the MT surface (see text). Average (upper panel) and variance (lower panel) images of MT-aligned offset dimers ( g ) and superposed dimers ( h ) with MT at the top. Higher variance is darker grey. In offset dimer average ( g ) only one ring is apparent but the second ring’s variable position is revealed in the variance image (arrows). ( i ) Monomeric dynein bound in the absence of nucleotide. Average appears closer to MT than dimers because some particles were attached to MT protofilaments lying closer to the MT axis in this view. Scale bars, ( c – e ) 40 nm; ( g - i ) 20 nm. Full size image Individual cytoplasmic dynein dimers can make runs of many steps along a MT, that is, they are processive. For many dyneins, the processive molecule includes a complex between the tail and other proteins or protein complexes such as BicD and dynactin 22 , 23 . For yeast and Dictyostelium dyneins, replacement of the tail with glutathione", "role": "user" }, { "content": "The first images of motor proteins in action are published in the journal Nature Communications today. These proteins are vital to complex life, forming the transport infrastructure that allows different parts of cells to specialise in particular functions. Until now, the way they move has never been directly observed. Researchers at the University of Leeds and in Japan used electron microscopes to capture images of the largest type of motor protein, called dynein, during the act of stepping along its molecular track. Dr Stan Burgess, at the University of Leeds' School of Molecular and Cellular Biology, who led the research team, said: \"Dynein has two identical motors tied together and it moves along a molecular track called a microtubule. It drives itself along the track by alternately grabbing hold of a binding site, executing a power stroke, then letting go, like a person swinging on monkey bars. \"Previously, dynein movement had only been tracked by attaching fluorescent molecules to the proteins and observing the fluorescence using very powerful light microscopes. It was a bit like tracking vehicles from space with GPS. It told us where they were, their speed and for how long they ran, stopped and so on, but we couldn't see the molecules in action themselves. These are the first images of these vital processes.\" An understanding of motor proteins is important to medical research because of their fundamental role in complex cellular life. Many viruses hijack motor proteins to hitch a ride to the nucleus for replication. Cell division is driven by motor proteins and so insights into their mechanics could be relevant to cancer research. Some motor neurone diseases are also associated with disruption of motor protein traffic. Credit: Nature Communications DOI: 10.1038/ncomms9179 The team at Leeds, working within the world-leading Astbury Centre for Structural Molecular Biology, combined purified microtubules with purified dynein motors and added the chemical fuel ATP (adenosine triphosphate) to power the motor. Dr Hiroshi Imai, now Assistant Professor in the Department of Biological Sciences at Chuo University, Japan, carried out the experiments while working at the University of Leeds. He explained: \"We set the dyneins running along their tracks and then we froze them in 'mid-stride' by cooling them at about a million degrees a second, fast enough to prevent the water from forming ice crystals as it solidified. Then using a cryo-electron microscope we took many thousands of images of the motors caught during the act of stepping. By combining many images of individual motors, we were able to sharpen up our picture of the dynein and build up a dynamic idea of how it moved. It is a bit like figuring out how to swing along monkey bars by studying photographs of many people swinging on them.\" Dr Burgess said: \"Our most striking discovery was the existence of a hinge between the long, thin stalk and the 'grappling hook', like the wrist between a human arm and hand. This allows a lot of variation in the angle of attachment of the motor to its track. \"Each of the two arms of a dynein motor protein is about 25 nanometres (0.000025 millimetre) long, while the binding sites it attaches to are only 8 nanometres apart. That means dynein can reach not only the next rung but the one after that and the one after that and appears to give it flexibility in how it moves along the 'track'.\" Dynein is not only the biggest but also the most versatile of the motor proteins in living cells and, like all motor proteins, is vital to life. Motor proteins transport cargoes and hold many cellular components in position within the cell. For instance, dynein is responsible for carrying messages from the tips of active nerve cells back to the nucleus and these messages keep the nerve cells alive. Credit: Nature Communications DOI: 10.1038/ncomms9179 Co-author Peter Knight, Professor of Molecular Contractility in the University of Leeds' School of Molecular and Cellular Biology, said: \"If a cell is like a city, these are like the truckers on its road and rail networks. If you didn't have a transport system, you couldn't have specialised regions. Every part of the cell would be doing the same thing and that would mean you could not have complex life.\" \"Dynein is the multi-purpose vehicle of cellular transport. Other motor proteins, called kinesins and myosins, are much smaller and have specific functions, but dynein can turn its hand to a lot of different of functions,\" Professor Knight said. For instance, in the motor neurone connecting the central nervous system to the big toe—which is a single cell a metre long— dynein provides the transport from the toe back to the nucleus. Another vital role is in the movement of cells. Credit: Nature Communications DOI: 10.1038/ncomms9179 Dr Burgess said: \"During brain development, neurones must crawl into their correct position and dynein molecules in this instance grab hold of the nucleus and pull it along with the moving mass of the cell. If they didn't, the nucleus would be left behind and the cytoplasm would crawl away.\" The study involved researchers from the University of Leeds and Japan's Waseda and Osaka universities, as well as the Quantitative Biology Center at Japan's Riken research institute and the Japan Science and Technology Agency (JST). The research was funded by the Human Frontiers Science Program and the Biotechnology and Biological Sciences Research Council (BBSRC). ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Cytoplasmic dynein is a dimeric AAA + motor protein that performs critical roles in eukaryotic cells by moving along microtubules using ATP. Here using cryo-electron microscopy we directly observe the structure of Dictyostelium discoideum dynein dimers on microtubules at near-physiological ATP concentrations. They display remarkable flexibility at a hinge close to the microtubule binding domain (the stalkhead) producing a wide range of head positions. About half the molecules have the two heads separated from one another, with both leading and trailing motors attached to the microtubule. The other half have the two heads and stalks closely superposed in a front-to-back arrangement of the AAA + rings, suggesting specific contact between the heads. All stalks point towards the microtubule minus end. Mean stalk angles depend on the separation between their stalkheads, which allows estimation of inter-head tension. These findings provide a structural framework for understanding dynein’s directionality and unusual stepping behaviour. Introduction Dyneins are a group of motor proteins that move along microtubules (MTs) to cause the beating of the axoneme in cilia and flagella and to perform vital and diverse transport and tethering roles in the cytoplasm of eukaryotic cells, for instance transporting mRNA, growth factors and β-amyloid precursor protein 1 , 2 . Dynein also transports the nucleus in neurons, which is essential to human development and maintenance of healthy neuronal activities 3 , 4 . Growing numbers of neurodegenerative diseases and developmental problems are now known to result from mutations in dynein or dynein-binding proteins 5 , 6 , and dynein-mediated processes are implicated in cancer 7 . So, in addition to its intrinsic interest, understanding dynein mechanism is critical for future treatment of disease. Dyneins have an unusual structure in which each ring-like ATPase head attaches to the MT via a slender, coiled-coil stalk at the tip of which is a small, globular, MT-binding subdomain that we term the stalkhead. (The stalkhead has also been called the MT binding domain (MTBD) but the meaning of MTBD is ambiguous for axonemal dyneins, since the stalkhead binds to one MT doublet and the tail binds to an adjacent doublet; by contrast, ‘stalkhead’ is intuitively understood and more concise.) The atomic structure of the motor domain is known 8 , 9 , 10 . The heart of the motor domain is a AAA + superfamily mechano-enzyme 11 , in which six AAA + motifs form a ring that hydrolyses ATP 1 . Associated with the AAA + ring (hereafter simply ‘ring’) is a C-terminal sequence that is implicated in determining the stall force and run length of the motor 12 , 13 , and that is unusually short in the much-studied yeast dynein 13 , 14 . Cytoplasmic dynein includes two identical heavy chains, each forming tail and motor domains ( Fig. 1a ) 1 . The complex N-terminal tail incorporates additional polypeptides, binds cargoes and dimerizes the motors 15 , 16 , 17 . Between the tail and ring is the linker 18 that provides the power stroke of the motor 19 by switching from bent (primed) to straight (unprimed) 8 , 9 , 10 , 20 . The ring, C-terminal sequence and linker together constitute the head, from which the stalk extends ( Fig. 1a ) 21 . Figure 1: Cryo-EM of dimeric dynein motors bound to MTs in 2 mM Mg-ATP. ( a ) Domains in the amino acid sequence of D. discoideum dynein heavy chain and (right) cartoon depicting the domain architecture of the dimer. The N-terminal tail (residues 1-1387, brown) dimerizes the motor in vivo . The motor includes six AAA + modules: AAA1 (blue)-AAA6 (red). Stalk and stalkhead emerges from AAA4, the strut from AAA5 and sequence numbers indicate the invariant prolines at the stalk-stalkhead junction. Linker (magenta and pale grey) and C-terminal domain (black) lie on opposite faces of the AAA + ring. Proposed moving part of the linker (L, magenta) is indicated. ( b ) Recombinant chimeric dynein dimerized by GST and with stalkhead from human axonemal dynein heavy chain 7; (right) cartoon depicting this dimer. ( c – e ) Cryo-EM of GST-380H7 mixed with MT and ∼ 2 mM Mg-ATP. Contrast is inverted (protein is pale) and dynein’s stepping direction (to the MT minus end) is towards the right in all Figures. ( c ) Dynein particles are crowded along the sides of the MT; such regions were not further analysed. ( d ) In sparse regions of less densely decorated MTs can be seen ‘superposed’ dimers (arrows) in which only a single ring is visible. ( e ) Enlarged view showing ‘superposed’ dimer (single arrow), an ‘offset’ dimer in which both rings are visible (double arrow) and a group of dimers comprising more than two rings (arrowhead). ( f ) Pixel values calculated from the head domains relative to adjacent MT (see Supplementary Fig. 4 ) of offset and superposed dimers and of monomers (mean±s.e.m.). ( g , h ) Image analysis of dimers stringently isolated on the MT surface (see text). Average (upper panel) and variance (lower panel) images of MT-aligned offset dimers ( g ) and superposed dimers ( h ) with MT at the top. Higher variance is darker grey. In offset dimer average ( g ) only one ring is apparent but the second ring’s variable position is revealed in the variance image (arrows). ( i ) Monomeric dynein bound in the absence of nucleotide. Average appears closer to MT than dimers because some particles were attached to MT protofilaments lying closer to the MT axis in this view. Scale bars, ( c – e ) 40 nm; ( g - i ) 20 nm. Full size image Individual cytoplasmic dynein dimers can make runs of many steps along a MT, that is, they are processive. For many dyneins, the processive molecule includes a complex between the tail and other proteins or protein complexes such as BicD and dynactin 22 , 23 . For yeast and Dictyostelium dyneins, replacement of the tail with glutathione<|im_end|> <|im_start|>assistant The first images of motor proteins in action are published in the journal Nature Communications today. These proteins are vital to complex life, forming the transport infrastructure that allows different parts of cells to specialise in particular functions. Until now, the way they move has never been directly observed. Researchers at the University of Leeds and in Japan used electron microscopes to capture images of the largest type of motor protein, called dynein, during the act of stepping along its molecular track. Dr Stan Burgess, at the University of Leeds' School of Molecular and Cellular Biology, who led the research team, said: "Dynein has two identical motors tied together and it moves along a molecular track called a microtubule. It drives itself along the track by alternately grabbing hold of a binding site, executing a power stroke, then letting go, like a person swinging on monkey bars. "Previously, dynein movement had only been tracked by attaching fluorescent molecules to the proteins and observing the fluorescence using very powerful light microscopes. It was a bit like tracking vehicles from space with GPS. It told us where they were, their speed and for how long they ran, stopped and so on, but we couldn't see the molecules in action themselves. These are the first images of these vital processes." An understanding of motor proteins is important to medical research because of their fundamental role in complex cellular life. Many viruses hijack motor proteins to hitch a ride to the nucleus for replication. Cell division is driven by motor proteins and so insights into their mechanics could be relevant to cancer research. Some motor neurone diseases are also associated with disruption of motor protein traffic. Credit: Nature Communications DOI: 10.1038/ncomms9179 The team at Leeds, working within the world-leading Astbury Centre for Structural Molecular Biology, combined purified microtubules with purified dynein motors and added the chemical fuel ATP (adenosine triphosphate) to power the motor. Dr Hiroshi Imai, now Assistant Professor in the Department of Biological Sciences at Chuo University, Japan, carried out the experiments while working at the University of Leeds. He explained: "We set the dyneins running along their tracks and then we froze them in 'mid-stride' by cooling them at about a million degrees a second, fast enough to prevent the water from forming ice crystals as it solidified. Then using a cryo-electron microscope we took many thousands of images of the motors caught during the act of stepping. By combining many images of individual motors, we were able to sharpen up our picture of the dynein and build up a dynamic idea of how it moved. It is a bit like figuring out how to swing along monkey bars by studying photographs of many people swinging on them." Dr Burgess said: "Our most striking discovery was the existence of a hinge between the long, thin stalk and the 'grappling hook', like the wrist between a human arm and hand. This allows a lot of variation in the angle of attachment of the motor to its track. "Each of the two arms of a dynein motor protein is about 25 nanometres (0.000025 millimetre) long, while the binding sites it attaches to are only 8 nanometres apart. That means dynein can reach not only the next rung but the one after that and the one after that and appears to give it flexibility in how it moves along the 'track'." Dynein is not only the biggest but also the most versatile of the motor proteins in living cells and, like all motor proteins, is vital to life. Motor proteins transport cargoes and hold many cellular components in position within the cell. For instance, dynein is responsible for carrying messages from the tips of active nerve cells back to the nucleus and these messages keep the nerve cells alive. Credit: Nature Communications DOI: 10.1038/ncomms9179 Co-author Peter Knight, Professor of Molecular Contractility in the University of Leeds' School of Molecular and Cellular Biology, said: "If a cell is like a city, these are like the truckers on its road and rail networks. If you didn't have a transport system, you couldn't have specialised regions. Every part of the cell would be doing the same thing and that would mean you could not have complex life." "Dynein is the multi-purpose vehicle of cellular transport. Other motor proteins, called kinesins and myosins, are much smaller and have specific functions, but dynein can turn its hand to a lot of different of functions," Professor Knight said. For instance, in the motor neurone connecting the central nervous system to the big toe—which is a single cell a metre long— dynein provides the transport from the toe back to the nucleus. Another vital role is in the movement of cells. Credit: Nature Communications DOI: 10.1038/ncomms9179 Dr Burgess said: "During brain development, neurones must crawl into their correct position and dynein molecules in this instance grab hold of the nucleus and pull it along with the moving mass of the cell. If they didn't, the nucleus would be left behind and the cytoplasm would crawl away." The study involved researchers from the University of Leeds and Japan's Waseda and Osaka universities, as well as the Quantitative Biology Center at Japan's Riken research institute and the Japan Science and Technology Agency (JST). The research was funded by the Human Frontiers Science Program and the Biotechnology and Biological Sciences Research Council (BBSRC). <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 18221, 99705, 10753, 292, 14282, 818, 258, 374, 264, 294, 3212, 292, 48197, 489, 9048, 13128, 430, 27772, 9200, 13073, 304, 384, 3178, 661, 14546, 7917, 555, 7366, 3235, 8162, 83, 392, 2482, 1701, 67656, 13, 5810, 1701, 16106, 78, 37081, 2298, 92914, 584, 6089, 23846, 279, 6070, 315, 30226, 88, 117700, 2411, 54969, 579, 372, 14282, 818, 258, 5213, 388, 389, 8162, 83, 392, 2482, 520, 3221, 12, 42305, 41314, 67656, 32466, 13, 2435, 3113, 23649, 25152, 520, 264, 76693, 3345, 311, 279, 8162, 83, 392, 1130, 11212, 8106, 320, 1820, 55972, 2025, 8, 17843, 264, 7029, 2134, 315, 2010, 10093, 13, 10180, 4376, 279, 35715, 617, 279, 1403, 14971, 19180, 505, 832, 2500, 11, 449, 2225, 6522, 323, 28848, 38424, 12673, 311, 279, 8162, 83, 392, 1130, 13, 578, 1023, 4376, 617, 279, 1403, 14971, 323, 55972, 82, 15499, 2307, 3950, 304, 264, 4156, 4791, 15825, 27204, 315, 279, 48197, 489, 25562, 11, 23377, 3230, 3729, 1990, 279, 14971, 13, 2052, 55972, 82, 1486, 7119, 279, 8162, 83, 392, 1130, 28382, 842, 13, 16729, 55972, 27030, 6904, 389, 279, 25768, 1990, 872, 55972, 36910, 11, 902, 6276, 42304, 315, 958, 27488, 24408, 13, 4314, 14955, 3493, 264, 24693, 12914, 369, 8830, 14282, 818, 258, 753, 5216, 2786, 323, 19018, 36567, 17432, 13, 29438, 43048, 818, 1354, 527, 264, 1912, 315, 9048, 28896, 430, 3351, 3235, 8162, 83, 392, 2482, 320, 8673, 82, 8, 311, 5353, 279, 27242, 315, 279, 3944, 263, 3981, 304, 272, 25045, 323, 5292, 6985, 323, 311, 2804, 16595, 323, 17226, 7710, 323, 80665, 287, 13073, 304, 279, 9693, 99705, 10753, 315, 384, 3178, 661, 14546, 7917, 11, 369, 2937, 67757, 78872, 11, 6650, 9547, 323, 34318, 12, 27322, 52196, 71261, 13128, 220, 16, 1174, 220, 17, 662, 43048, 818, 258, 1101, 69169, 279, 62607, 304, 34313, 11, 902, 374, 7718, 311, 3823, 4500, 323, 13709, 315, 9498, 79402, 7640, 220, 18, 1174, 220, 19, 662, 60780, 5219, 315, 18247, 451, 7642, 1413, 19338, 323, 48006, 5435, 527, 1457, 3967, 311, 1121, 505, 34684, 304, 14282, 818, 258, 477, 14282, 818, 258, 65500, 28896, 220, 20, 1174, 220, 21, 1174, 323, 14282, 818, 258, 82076, 11618, 527, 69702, 304, 9572, 220, 22, 662, 2100, 11, 304, 5369, 311, 1202, 47701, 2802, 11, 8830, 14282, 818, 258, 17383, 374, 9200, 369, 3938, 6514, 315, 8624, 13, 43048, 818, 1354, 617, 459, 19018, 6070, 304, 902, 1855, 10264, 12970, 67656, 521, 2010, 85603, 311, 279, 19629, 4669, 264, 73342, 11, 1080, 2230, 23283, 321, 55972, 520, 279, 11813, 315, 902, 374, 264, 2678, 11, 13509, 1299, 11, 19629, 65500, 1207, 12482, 430, 584, 4751, 279, 55972, 2025, 13, 320, 791, 55972, 2025, 706, 1101, 1027, 2663, 279, 19629, 11212, 8106, 320, 8673, 9740, 8, 719, 279, 7438, 315, 19629, 9740, 374, 55861, 369, 3944, 263, 336, 278, 14282, 818, 1354, 11, 2533, 279, 55972, 2025, 58585, 311, 832, 19629, 2033, 83, 323, 279, 9986, 58585, 311, 459, 24894, 2033, 83, 26, 555, 13168, 11, 3451, 90849, 2025, 529, 374, 97301, 3210, 16365, 323, 810, 64694, 6266, 578, 25524, 6070, 315, 279, 9048, 8106, 374, 3967, 220, 23, 1174, 220, 24, 1174, 220, 605, 662, 578, 4851, 315, 279, 9048, 8106, 374, 264, 48197, 489, 2307, 19521, 84596, 5770, 12, 65728, 220, 806, 1174, 304, 902, 4848, 48197, 489, 84989, 1376, 264, 10264, 430, 17055, 398, 9459, 67656, 220, 16, 662, 26475, 449, 279, 48197, 489, 10264, 320, 6881, 10924, 5042, 3451, 12928, 96206, 374, 264, 356, 91723, 8668, 430, 374, 69702, 304, 26679, 279, 43793, 5457, 323, 1629, 3160, 315, 279, 9048, 220, 717, 1174, 220, 1032, 1174, 323, 430, 374, 57899, 2875, 304, 279, 1790, 5594, 664, 1142, 41580, 14282, 818, 258, 220, 1032, 1174, 220, 975, 662, 18221, 99705, 10753, 292, 14282, 818, 258, 5764, 1403, 20086, 8987, 27271, 11, 1855, 30164, 9986, 323, 9048, 31576, 320, 23966, 13, 220, 16, 64, 883, 220, 16, 662, 578, 6485, 452, 91723, 9986, 52924, 5217, 1499, 500, 74489, 11, 58585, 62762, 7217, 323, 294, 3212, 4861, 279, 38424, 220, 868, 1174, 220, 845, 1174, 220, 1114, 662, 28232, 279, 9986, 323, 10264, 374, 279, 86845, 220, 972, 430, 5825, 279, 2410, 12943, 315, 279, 9048, 220, 777, 555, 28865, 505, 30280, 320, 18375, 291, 8, 311, 7833, 320, 359, 18375, 291, 8, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 508, 662, 578, 10264, 11, 356, 91723, 8668, 323, 86845, 3871, 35256, 279, 2010, 11, 505, 902, 279, 55972, 2289, 320, 23966, 13, 220, 16, 64, 883, 220, 1691, 662, 19575, 220, 16, 25, 43805, 78, 12, 2783, 315, 294, 3212, 292, 14282, 818, 258, 38424, 6965, 311, 19629, 82, 304, 220, 17, 84317, 73693, 12, 835, 47, 13, 320, 264, 883, 21414, 1771, 304, 279, 42500, 13935, 8668, 315, 423, 13, 54969, 579, 372, 14282, 818, 258, 8987, 8957, 323, 320, 1315, 8, 31449, 60794, 279, 8106, 18112, 315, 279, 294, 3212, 13, 578, 452, 91723, 9986, 320, 417, 307, 1157, 220, 16, 12, 10350, 22, 11, 14198, 8, 294, 3212, 4861, 279, 9048, 304, 41294, 662, 578, 9048, 5764, 4848, 48197, 489, 13761, 25, 48197, 16, 320, 12481, 7435, 51207, 21, 320, 1171, 570, 800, 1727, 323, 55972, 2025, 59696, 505, 48197, 19, 11, 279, 83443, 505, 48197, 20, 323, 8668, 5219, 13519, 279, 58720, 463, 8128, 520, 279, 55972, 5594, 1727, 2025, 49341, 13, 6074, 261, 320, 76, 48162, 323, 28639, 20366, 8, 323, 356, 91723, 8106, 320, 11708, 8, 10457, 389, 14329, 12580, 315, 279, 48197, 489, 10264, 13, 99983, 7366, 961, 315, 279, 86845, 320, 43, 11, 4983, 16985, 8, 374, 16717, 13, 320, 293, 883, 4158, 2925, 86396, 523, 3212, 292, 14282, 818, 258, 294, 3212, 1534, 555, 33934, 323, 449, 55972, 2025, 505, 3823, 3944, 263, 336, 278, 14282, 818, 258, 8987, 8957, 220, 22, 26, 320, 1315, 8, 31449, 60794, 420, 294, 3212, 13, 320, 272, 1389, 384, 883, 43805, 78, 12, 2783, 315, 33934, 12, 13897, 39, 22, 9709, 449, 19629, 323, 12264, 120, 220, 17, 84317, 73693, 12, 835, 47, 13, 91148, 374, 47801, 320, 79565, 374, 28639, 8, 323, 14282, 818, 258, 753, 36567, 5216, 320, 998, 279, 19629, 28382, 842, 8, 374, 7119, 279, 1314, 304, 682, 69356, 13, 320, 272, 883, 43048, 818, 258, 19252, 527, 39313, 3235, 279, 11314, 315, 279, 19629, 26, 1778, 13918, 1051, 539, 4726, 67458, 13, 320, 294, 883, 763, 34544, 13918, 315, 2753, 97617, 37109, 19629, 82, 649, 387, 3970, 3451, 9712, 3950, 529, 5213, 388, 320, 277, 1849, 8, 304, 902, 1193, 264, 3254, 10264, 374, 9621, 13, 320, 384, 883, 2998, 27995, 291, 1684, 9204, 3451, 9712, 3950, 529, 294, 3212, 320, 15698, 18404, 705, 459, 3451, 3255, 529, 294, 3212, 304, 902, 2225, 25562, 527, 9621, 320, 4429, 18404, 8, 323, 264, 1912, 315, 5213, 388, 46338, 810, 1109, 1403, 25562, 320, 6172, 2025, 570, 320, 282, 883, 28569, 2819, 16997, 505, 279, 2010, 31576, 8844, 311, 24894, 19629, 320, 4151, 99371, 23966, 13, 220, 19, 883, 315, 4445, 323, 2307, 3950, 5213, 388, 323, 315, 1647, 69638, 320, 14622, 38121, 82, 1770, 749, 36434, 320, 342, 1174, 305, 883, 4758, 6492, 315, 5213, 388, 925, 4501, 25181, 389, 279, 19629, 7479, 320, 4151, 1495, 570, 24478, 320, 13886, 7090, 8, 323, 33373, 320, 15115, 7090, 8, 5448, 315, 19629, 98551, 4445, 5213, 388, 320, 342, 883, 323, 2307, 3950, 5213, 388, 320, 305, 883, 449, 19629, 520, 279, 1948, 13, 35321, 33373, 374, 40130, 20366, 13, 763, 4445, 294, 3212, 5578, 320, 342, 883, 1193, 832, 10264, 374, 10186, 719, 279, 2132, 10264, 753, 3977, 2361, 374, 10675, 304, 279, 33373, 2217, 320, 277, 1849, 570, 320, 602, 883, 3206, 316, 11893, 14282, 818, 258, 6965, 304, 279, 19821, 315, 31484, 69044, 13, 24478, 8111, 12401, 311, 19629, 1109, 5213, 388, 1606, 1063, 19252, 1051, 12673, 311, 19629, 18940, 12723, 24469, 21078, 12401, 311, 279, 19629, 8183, 304, 420, 1684, 13, 25635, 16283, 11, 320, 272, 1389, 384, 883, 220, 1272, 26807, 26, 320, 342, 482, 602, 883, 220, 508, 26807, 13, 8797, 1404, 2217, 30440, 9693, 99705, 10753, 292, 14282, 818, 258, 5213, 388, 649, 1304, 8640, 315, 1690, 7504, 3235, 264, 19629, 11, 430, 374, 11, 814, 527, 1920, 535, 13, 1789, 1690, 14282, 818, 1354, 11, 279, 1920, 535, 43030, 5764, 264, 6485, 1990, 279, 9986, 323, 1023, 28896, 477, 13128, 69125, 1778, 439, 426, 292, 35, 323, 32170, 533, 258, 220, 1313, 1174, 220, 1419, 662, 1789, 41580, 323, 30226, 88, 117700, 2411, 14282, 818, 1354, 11, 14039, 315, 279, 9986, 449, 35169, 589, 6473, 128257, 198, 128256, 78191, 198, 791, 1176, 5448, 315, 9048, 28896, 304, 1957, 527, 4756, 304, 279, 8486, 22037, 26545, 3432, 13, 4314, 28896, 527, 16595, 311, 6485, 2324, 11, 30164, 279, 7710, 14054, 430, 6276, 2204, 5596, 315, 7917, 311, 3361, 1082, 304, 4040, 5865, 13, 30070, 1457, 11, 279, 1648, 814, 3351, 706, 2646, 1027, 6089, 13468, 13, 59250, 520, 279, 3907, 315, 52629, 323, 304, 6457, 1511, 17130, 8162, 82025, 311, 12602, 5448, 315, 279, 7928, 955, 315, 9048, 13128, 11, 2663, 14282, 818, 258, 11, 2391, 279, 1180, 315, 36567, 3235, 1202, 31206, 3839, 13, 2999, 15560, 98567, 11, 520, 279, 3907, 315, 52629, 6, 6150, 315, 60825, 323, 88207, 40023, 11, 889, 6197, 279, 3495, 2128, 11, 1071, 25, 330, 35, 82808, 258, 706, 1403, 20086, 38424, 17791, 3871, 323, 433, 11031, 3235, 264, 31206, 3839, 2663, 264, 8162, 83, 392, 1130, 13, 1102, 20722, 5196, 3235, 279, 3839, 555, 7064, 2718, 50030, 3412, 315, 264, 11212, 2816, 11, 31320, 264, 2410, 12943, 11, 1243, 20806, 733, 11, 1093, 264, 1732, 55060, 389, 39803, 16283, 13, 330, 83039, 11, 14282, 818, 258, 7351, 1047, 1193, 1027, 34156, 555, 72908, 74864, 35715, 311, 279, 28896, 323, 46071, 279, 97332, 1701, 1633, 8147, 3177, 8162, 82025, 13, 1102, 574, 264, 2766, 1093, 15194, 11731, 505, 3634, 449, 24229, 13, 1102, 3309, 603, 1405, 814, 1051, 11, 872, 4732, 323, 369, 1268, 1317, 814, 10837, 11, 10717, 323, 779, 389, 11, 719, 584, 7846, 956, 1518, 279, 35715, 304, 1957, 5694, 13, 4314, 527, 279, 1176, 5448, 315, 1521, 16595, 11618, 1210, 1556, 8830, 315, 9048, 28896, 374, 3062, 311, 6593, 3495, 1606, 315, 872, 16188, 3560, 304, 6485, 35693, 2324, 13, 9176, 42068, 22130, 474, 9048, 28896, 311, 59207, 264, 12141, 311, 279, 62607, 369, 48891, 13, 14299, 13096, 374, 16625, 555, 9048, 28896, 323, 779, 26793, 1139, 872, 30126, 1436, 387, 9959, 311, 9572, 3495, 13, 4427, 9048, 21850, 606, 19338, 527, 1101, 5938, 449, 44219, 315, 9048, 13128, 9629, 13, 16666, 25, 22037, 26545, 59670, 25, 220, 605, 13, 6889, 23, 9809, 884, 1026, 24391, 24, 578, 2128, 520, 52629, 11, 3318, 2949, 279, 1917, 69475, 20717, 20176, 14821, 369, 73800, 60825, 40023, 11, 11093, 92600, 8162, 83, 392, 2482, 449, 92600, 14282, 818, 258, 38424, 323, 3779, 279, 11742, 10633, 67656, 320, 21825, 437, 483, 2463, 764, 93473, 8, 311, 2410, 279, 9048, 13, 2999, 57392, 60521, 358, 77585, 11, 1457, 22103, 17054, 304, 279, 6011, 315, 63711, 23199, 520, 921, 24012, 3907, 11, 6457, 11, 11953, 704, 279, 21896, 1418, 3318, 520, 279, 3907, 315, 52629, 13, 1283, 11497, 25, 330, 1687, 743, 279, 14282, 818, 1354, 4401, 3235, 872, 14242, 323, 1243, 584, 90109, 1124, 304, 364, 16497, 42728, 579, 6, 555, 28015, 1124, 520, 922, 264, 3610, 12628, 264, 2132, 11, 5043, 3403, 311, 5471, 279, 3090, 505, 30164, 10054, 48473, 439, 433, 6573, 1908, 13, 5112, 1701, 264, 16106, 78, 37081, 2298, 73757, 584, 3952, 1690, 9214, 315, 5448, 315, 279, 38424, 10791, 2391, 279, 1180, 315, 36567, 13, 3296, 35271, 1690, 5448, 315, 3927, 38424, 11, 584, 1051, 3025, 311, 57463, 709, 1057, 6945, 315, 279, 14282, 818, 258, 323, 1977, 709, 264, 8915, 4623, 315, 1268, 433, 7882, 13, 1102, 374, 264, 2766, 1093, 48309, 704, 1268, 311, 19336, 3235, 39803, 16283, 555, 21630, 25232, 315, 1690, 1274, 55060, 389, 1124, 1210, 2999, 98567, 1071, 25, 330, 8140, 1455, 21933, 18841, 574, 279, 14209, 315, 264, 76693, 1990, 279, 1317, 11, 15792, 55972, 323, 279, 364, 911, 391, 12127, 9903, 518, 1093, 279, 33271, 1990, 264, 3823, 6916, 323, 1450, 13, 1115, 6276, 264, 2763, 315, 23851, 304, 279, 9392, 315, 20581, 315, 279, 9048, 311, 1202, 3839, 13, 330, 4959, 315, 279, 1403, 11977, 315, 264, 14282, 818, 258, 9048, 13128, 374, 922, 220, 914, 20622, 4512, 417, 320, 15, 13, 931, 18070, 2606, 318, 47987, 8, 1317, 11, 1418, 279, 11212, 6732, 433, 85603, 311, 527, 1193, 220, 23, 20622, 4512, 417, 10980, 13, 3011, 3445, 14282, 818, 258, 649, 5662, 539, 1193, 279, 1828, 1629, 70, 719, 279, 832, 1306, 430, 323, 279, 832, 1306, 430, 323, 8111, 311, 3041, 433, 25152, 304, 1268, 433, 11031, 3235, 279, 364, 13432, 6, 1210, 43048, 818, 258, 374, 539, 1193, 279, 8706, 719, 1101, 279, 1455, 33045, 315, 279, 9048, 28896, 304, 5496, 7917, 323, 11, 1093, 682, 9048, 28896, 11, 374, 16595, 311, 2324, 13, 18079, 28896, 7710, 62762, 7217, 323, 3412, 1690, 35693, 6956, 304, 2361, 2949, 279, 2849, 13, 1789, 2937, 11, 14282, 818, 258, 374, 8647, 369, 15691, 6743, 505, 279, 10631, 315, 4642, 32015, 7917, 1203, 311, 279, 62607, 323, 1521, 6743, 2567, 279, 32015, 7917, 13989, 13, 16666, 25, 22037, 26545, 59670, 25, 220, 605, 13, 6889, 23, 9809, 884, 1026, 24391, 24, 3623, 43802, 11291, 23844, 11, 17054, 315, 60825, 19735, 1429, 304, 279, 3907, 315, 52629, 6, 6150, 315, 60825, 323, 88207, 40023, 11, 1071, 25, 330, 2746, 264, 2849, 374, 1093, 264, 3363, 11, 1521, 527, 1093, 279, 11092, 388, 389, 1202, 5754, 323, 13881, 14488, 13, 1442, 499, 3287, 956, 617, 264, 7710, 1887, 11, 499, 7846, 956, 617, 89004, 13918, 13, 7357, 961, 315, 279, 2849, 1053, 387, 3815, 279, 1890, 3245, 323, 430, 1053, 3152, 499, 1436, 539, 617, 6485, 2324, 1210, 330, 35, 82808, 258, 374, 279, 7447, 59338, 7458, 315, 35693, 7710, 13, 7089, 9048, 28896, 11, 2663, 597, 1572, 1354, 323, 856, 437, 1354, 11, 527, 1790, 9333, 323, 617, 3230, 5865, 11, 719, 14282, 818, 258, 649, 2543, 1202, 1450, 311, 264, 2763, 315, 2204, 315, 5865, 1359, 17054, 23844, 1071, 13, 1789, 2937, 11, 304, 279, 9048, 21850, 606, 21583, 279, 8792, 23418, 1887, 311, 279, 2466, 31316, 50004, 374, 264, 3254, 2849, 264, 82673, 1317, 2345, 14282, 818, 258, 5825, 279, 7710, 505, 279, 31316, 1203, 311, 279, 62607, 13, 13596, 16595, 3560, 374, 304, 279, 7351, 315, 7917, 13, 16666, 25, 22037, 26545, 59670, 25, 220, 605, 13, 6889, 23, 9809, 884, 1026, 24391, 24, 2999, 98567, 1071, 25, 330, 16397, 8271, 4500, 11, 21850, 3233, 2011, 46764, 1139, 872, 4495, 2361, 323, 14282, 818, 258, 35715, 304, 420, 2937, 11894, 3412, 315, 279, 62607, 323, 6958, 433, 3235, 449, 279, 7366, 3148, 315, 279, 2849, 13, 1442, 814, 3287, 956, 11, 279, 62607, 1053, 387, 2163, 4920, 323, 279, 9693, 99705, 10753, 1053, 46764, 3201, 1210, 578, 4007, 6532, 12074, 505, 279, 3907, 315, 52629, 323, 6457, 596, 468, 1503, 64, 323, 88085, 23978, 11, 439, 1664, 439, 279, 32541, 22018, 40023, 5955, 520, 6457, 596, 432, 37533, 3495, 44798, 323, 279, 6457, 10170, 323, 12053, 16784, 320, 41, 790, 570, 578, 3495, 574, 24853, 555, 279, 11344, 15248, 4918, 10170, 6826, 323, 279, 12371, 52536, 323, 63711, 23199, 8483, 9251, 320, 33, 7497, 7532, 570, 220, 128257, 198 ]

2,603

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Crucial to the successful conservation of endangered species is the overlap of their ranges with protected areas. We analyzed protected areas in the continental USA to assess the extent to which they covered the ranges of endangered tetrapods. We show that in 80% of ecoregions, protected areas offer equal (25%) or worse (55%) protection for species than if their locations were chosen at random. Additionally, we demonstrate that it is possible to achieve sufficient protection for 100% of the USA’s endangered tetrapods through targeted protection of undeveloped public and private lands. Our results highlight that the USA is likely to fall short of its commitments to halting biodiversity loss unless more considerable investments in both public and private land conservation are made. Introduction In 2010, 194 countries committed to halting biodiversity loss by adopting the Aichi Biodiversity Targets and Sustainable Development Goals 1 . Crucial to the success of this commitment is the protection of important habitat to support terrestrial and aquatic biodiversity. Highly protected areas (e.g., national monuments, national parks, and wilderness areas) that heavily restrict anthropogenic activities are the current mainstay for biodiversity conservation because, in general, well managed and effectively placed protected areas have been shown to increase species richness and abundance relative to unprotected areas 2 , 3 , 4 , 5 . As a result, the spatial extent of protected areas is used to monitor global progress towards achieving Aichi Biodiversity Targets and Sustainable Development Goals, and Aichi Target 11 specifically identified that 17% of terrestrial areas and inland waters needed to be protected by 2020 1 . Unfortunately, as 2019 came to a close only 15.2% of global land was located within protected areas 6 . In 2020, the Convention on Biological Diversity (CBD) will adopt a new global biodiversity framework for the post-2020 era with new targets set for 2050. To develop this new framework, the CBD will need to review its successes and failures with the previous framework. One of the major criticisms of Aichi Target 11 is that it is an area-based target that can be met with little relevance to the protection of biodiversity 7 . Although the designation of a protected area counts towards Aichi Target 11, protected areas do not have to be designated with the primary goal of protecting biodiversity. This is especially true in countries such as the United States of America (USA) where protected areas have historically been designated for reasons other than biodiversity, such as cultural and historical significance 8 , or lack of agricultural value 9 . As a result, recent analyses have brought into question whether existing protected areas are actually improving the conservation status of imperiled species 3 , 4 , and whether they should effectively be counted towards reaching Aichi Target 11. To determine the extent to which current protected areas are aiding in the protection of imperiled species and how much additional land is required to protect species, we must understand the overlap between protected areas and species ranges. Given that the ultimate goal of achieving Aichi Target 11 is to protect biodiversity and the services it provides, new lands added to reach current and future targets should be designated with the specific goal of protecting biodiversity, especially threatened and endangered species. Currently, only 7.1% of the USA’s land is in a highly protected status that is managed to preserve biodiversity 8 , 10 . The most common pathway by which the government designates new lands as protected is through the conversion of existing public land to a protected status [e.g., the conversion of Bureau of Land Management (BLM) land to a National Monument or Wilderness Area] 11 . However, the political appetite for the conversion of public lands to highly protected areas is not always favorable 12 . Furthermore, the availability of public lands for conversion to protected areas may be limited. For example, ~ 95% of the land in the state of Texas, USA, is privately owned. These political and logistical obstacles may mean that private lands such as conservation easements may need to take a more prominent role in meeting conservation targets in the USA 13 , 14 . Our study aimed to assess how current protected areas in the continental USA are contributing to the protection of its most imperiled species, and how the conversion of existing public and private lands to a highly protected status can aid the USA further in safeguarding those species. We used a null modeling approach 15 , 16 to analyze whether current protected areas include threatened and endangered species and sub-species (hereon referred to as ‘endangered species’) better than if they had been placed at random. We then assessed how many endangered species had 30% of their range inside the current layout of protected areas. In the absence of species-specific population viability analysis, a rule of thumb suggests that 30% of a species’ range must be protected for it to persist in the wild 17 . We then further analyzed whether or not the capacity to protect more endangered species exists through the targeted conversion of undeveloped public and private lands to a highly protected status. For all of our assessments, we use an ecoregion-based approach, as ecoregions have been shown to represent the broadest inclusion of diverse habitats and species 18 . Results and discussion While biodiversity conservation is cited as a priority for many existing highly protected areas, our null modeling results indicate that the placement of protected areas in the USA has largely failed to include at-risk species. For a large number of ecoregions, especially in the western states, we found that endangered species currently have less of their range contained within protected areas than if these areas had been placed at random (Fig. 1 a). Across the entire continental USA, we found that highly protected areas in 55% of ecoregions were worse at protecting the ranges of endangered species than if their location had been chosen at random within the same ecoregion (Fig. 1", "role": "user" }, { "content": "In 1872 the United States created Yellowstone, the first National Park in the world. Since then many more parks, monuments, preserves, wildernesses and other protected areas have been created in the USA. Protected areas, like Yellowstone, are invaluable, but are they actually effective at preserving endangered species? And if not, how can future protected areas do better? A team of ecologists at Utah State University published a study in Scientific Reports to answer these questions. They used computer models to determine if protected areas in the USA preserve enough land inhabited by endangered species to adequately ensure their future survival in the wild. As it is, the situation is problematic: Of the 159 endangered mammal, bird, reptile and amphibian species in the continental USA only 21 are adequately preserved by existing protected areas. Creating new protected areas on public land is fraught with obstacles. Many protected areas are designated based on scenic beauty or lack of agricultural value and these criteria don't necessarily benefit at-risk species. Unfavorable political climates can also present problems. Trisha Atwood, Assistant Professor in the Department of Watershed Sciences and Ecology Center, and study co-author explained, \"There has been a huge political push in the USA to reduce protected areas such as National Monuments. However, our results suggest that we not only need to increase the spatial coverage of protected areas in the USA, but we also need to ensure that we are protecting the places that contain critical habitat for endangered species.\" Another obstacle is the limited availability of public land. For example, in the state of Texas 95% of the land is privately owned. And according to the study even if all federal and state public lands were given protected area status more than half of the at-risk species in the USA would still be in danger of extinction. \"We are not suggesting that protected areas are doing a bad job,\" said Edward Hammill, Assistant Professor in the Department of Watershed Sciences and Ecology Center and study co-author, \"what we are suggesting is that there are many opportunities to increase protection.\" One of those opportunities is the creation of conservation easements on private land. Conservation easements are voluntary, legal agreements that restrict future development on private land. In exchange for contributing to conservation efforts, land owners retain their property rights and can receive tax benefits. One of the most important findings from the study is that with the help of private land owners the USA has not lost the capacity to adequately protect 100% of its endangered species. \"It is unlikely that adequate conservation of endangered species will be achieved by increasing federal protected areas,\" said Hammill. \"Our research highlights that private land owners represent an alternative route to achieving conservation goals.\" Atwood concluded, \"These findings give me hope that we can still make a change for the better. But, if we are going to win the fight against extinction we are going to need the help of private land owners.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Crucial to the successful conservation of endangered species is the overlap of their ranges with protected areas. We analyzed protected areas in the continental USA to assess the extent to which they covered the ranges of endangered tetrapods. We show that in 80% of ecoregions, protected areas offer equal (25%) or worse (55%) protection for species than if their locations were chosen at random. Additionally, we demonstrate that it is possible to achieve sufficient protection for 100% of the USA’s endangered tetrapods through targeted protection of undeveloped public and private lands. Our results highlight that the USA is likely to fall short of its commitments to halting biodiversity loss unless more considerable investments in both public and private land conservation are made. Introduction In 2010, 194 countries committed to halting biodiversity loss by adopting the Aichi Biodiversity Targets and Sustainable Development Goals 1 . Crucial to the success of this commitment is the protection of important habitat to support terrestrial and aquatic biodiversity. Highly protected areas (e.g., national monuments, national parks, and wilderness areas) that heavily restrict anthropogenic activities are the current mainstay for biodiversity conservation because, in general, well managed and effectively placed protected areas have been shown to increase species richness and abundance relative to unprotected areas 2 , 3 , 4 , 5 . As a result, the spatial extent of protected areas is used to monitor global progress towards achieving Aichi Biodiversity Targets and Sustainable Development Goals, and Aichi Target 11 specifically identified that 17% of terrestrial areas and inland waters needed to be protected by 2020 1 . Unfortunately, as 2019 came to a close only 15.2% of global land was located within protected areas 6 . In 2020, the Convention on Biological Diversity (CBD) will adopt a new global biodiversity framework for the post-2020 era with new targets set for 2050. To develop this new framework, the CBD will need to review its successes and failures with the previous framework. One of the major criticisms of Aichi Target 11 is that it is an area-based target that can be met with little relevance to the protection of biodiversity 7 . Although the designation of a protected area counts towards Aichi Target 11, protected areas do not have to be designated with the primary goal of protecting biodiversity. This is especially true in countries such as the United States of America (USA) where protected areas have historically been designated for reasons other than biodiversity, such as cultural and historical significance 8 , or lack of agricultural value 9 . As a result, recent analyses have brought into question whether existing protected areas are actually improving the conservation status of imperiled species 3 , 4 , and whether they should effectively be counted towards reaching Aichi Target 11. To determine the extent to which current protected areas are aiding in the protection of imperiled species and how much additional land is required to protect species, we must understand the overlap between protected areas and species ranges. Given that the ultimate goal of achieving Aichi Target 11 is to protect biodiversity and the services it provides, new lands added to reach current and future targets should be designated with the specific goal of protecting biodiversity, especially threatened and endangered species. Currently, only 7.1% of the USA’s land is in a highly protected status that is managed to preserve biodiversity 8 , 10 . The most common pathway by which the government designates new lands as protected is through the conversion of existing public land to a protected status [e.g., the conversion of Bureau of Land Management (BLM) land to a National Monument or Wilderness Area] 11 . However, the political appetite for the conversion of public lands to highly protected areas is not always favorable 12 . Furthermore, the availability of public lands for conversion to protected areas may be limited. For example, ~ 95% of the land in the state of Texas, USA, is privately owned. These political and logistical obstacles may mean that private lands such as conservation easements may need to take a more prominent role in meeting conservation targets in the USA 13 , 14 . Our study aimed to assess how current protected areas in the continental USA are contributing to the protection of its most imperiled species, and how the conversion of existing public and private lands to a highly protected status can aid the USA further in safeguarding those species. We used a null modeling approach 15 , 16 to analyze whether current protected areas include threatened and endangered species and sub-species (hereon referred to as ‘endangered species’) better than if they had been placed at random. We then assessed how many endangered species had 30% of their range inside the current layout of protected areas. In the absence of species-specific population viability analysis, a rule of thumb suggests that 30% of a species’ range must be protected for it to persist in the wild 17 . We then further analyzed whether or not the capacity to protect more endangered species exists through the targeted conversion of undeveloped public and private lands to a highly protected status. For all of our assessments, we use an ecoregion-based approach, as ecoregions have been shown to represent the broadest inclusion of diverse habitats and species 18 . Results and discussion While biodiversity conservation is cited as a priority for many existing highly protected areas, our null modeling results indicate that the placement of protected areas in the USA has largely failed to include at-risk species. For a large number of ecoregions, especially in the western states, we found that endangered species currently have less of their range contained within protected areas than if these areas had been placed at random (Fig. 1 a). Across the entire continental USA, we found that highly protected areas in 55% of ecoregions were worse at protecting the ranges of endangered species than if their location had been chosen at random within the same ecoregion (Fig. 1<|im_end|> <|im_start|>assistant In 1872 the United States created Yellowstone, the first National Park in the world. Since then many more parks, monuments, preserves, wildernesses and other protected areas have been created in the USA. Protected areas, like Yellowstone, are invaluable, but are they actually effective at preserving endangered species? And if not, how can future protected areas do better? A team of ecologists at Utah State University published a study in Scientific Reports to answer these questions. They used computer models to determine if protected areas in the USA preserve enough land inhabited by endangered species to adequately ensure their future survival in the wild. As it is, the situation is problematic: Of the 159 endangered mammal, bird, reptile and amphibian species in the continental USA only 21 are adequately preserved by existing protected areas. Creating new protected areas on public land is fraught with obstacles. Many protected areas are designated based on scenic beauty or lack of agricultural value and these criteria don't necessarily benefit at-risk species. Unfavorable political climates can also present problems. Trisha Atwood, Assistant Professor in the Department of Watershed Sciences and Ecology Center, and study co-author explained, "There has been a huge political push in the USA to reduce protected areas such as National Monuments. However, our results suggest that we not only need to increase the spatial coverage of protected areas in the USA, but we also need to ensure that we are protecting the places that contain critical habitat for endangered species." Another obstacle is the limited availability of public land. For example, in the state of Texas 95% of the land is privately owned. And according to the study even if all federal and state public lands were given protected area status more than half of the at-risk species in the USA would still be in danger of extinction. "We are not suggesting that protected areas are doing a bad job," said Edward Hammill, Assistant Professor in the Department of Watershed Sciences and Ecology Center and study co-author, "what we are suggesting is that there are many opportunities to increase protection." One of those opportunities is the creation of conservation easements on private land. Conservation easements are voluntary, legal agreements that restrict future development on private land. In exchange for contributing to conservation efforts, land owners retain their property rights and can receive tax benefits. One of the most important findings from the study is that with the help of private land owners the USA has not lost the capacity to adequately protect 100% of its endangered species. "It is unlikely that adequate conservation of endangered species will be achieved by increasing federal protected areas," said Hammill. "Our research highlights that private land owners represent an alternative route to achieving conservation goals." Atwood concluded, "These findings give me hope that we can still make a change for the better. But, if we are going to win the fight against extinction we are going to need the help of private land owners." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 76104, 532, 311, 279, 6992, 29711, 315, 52356, 9606, 374, 279, 28347, 315, 872, 21986, 449, 2682, 5789, 13, 1226, 30239, 2682, 5789, 304, 279, 58636, 7427, 311, 8720, 279, 13112, 311, 902, 814, 9960, 279, 21986, 315, 52356, 28953, 4714, 30797, 13, 1226, 1501, 430, 304, 220, 1490, 4, 315, 384, 2202, 70, 919, 11, 2682, 5789, 3085, 6273, 320, 914, 11587, 477, 11201, 320, 2131, 11587, 9313, 369, 9606, 1109, 422, 872, 10687, 1051, 12146, 520, 4288, 13, 23212, 11, 584, 20461, 430, 433, 374, 3284, 311, 11322, 14343, 9313, 369, 220, 1041, 4, 315, 279, 7427, 753, 52356, 28953, 4714, 30797, 1555, 17550, 9313, 315, 59995, 1851, 291, 586, 323, 879, 12098, 13, 5751, 3135, 11415, 430, 279, 7427, 374, 4461, 311, 4498, 2875, 315, 1202, 42356, 311, 15104, 1303, 73119, 4814, 7389, 810, 24779, 22538, 304, 2225, 586, 323, 879, 4363, 29711, 527, 1903, 13, 29438, 763, 220, 679, 15, 11, 220, 6393, 5961, 11411, 311, 15104, 1303, 73119, 4814, 555, 48810, 279, 362, 41652, 426, 3205, 3050, 86047, 323, 61593, 11050, 55293, 220, 16, 662, 76104, 532, 311, 279, 2450, 315, 420, 15507, 374, 279, 9313, 315, 3062, 39646, 311, 1862, 80492, 323, 72491, 73119, 13, 53485, 2682, 5789, 320, 68, 1326, 2637, 5426, 63003, 11, 5426, 27943, 11, 323, 49362, 5789, 8, 430, 17345, 9067, 41416, 29569, 7640, 527, 279, 1510, 1925, 60021, 369, 73119, 29711, 1606, 11, 304, 4689, 11, 1664, 9152, 323, 13750, 9277, 2682, 5789, 617, 1027, 6982, 311, 5376, 9606, 90030, 323, 37492, 8844, 311, 94451, 5789, 220, 17, 1174, 220, 18, 1174, 220, 19, 1174, 220, 20, 662, 1666, 264, 1121, 11, 279, 29079, 13112, 315, 2682, 5789, 374, 1511, 311, 8891, 3728, 5208, 7119, 32145, 362, 41652, 426, 3205, 3050, 86047, 323, 61593, 11050, 55293, 11, 323, 362, 41652, 13791, 220, 806, 11951, 11054, 430, 220, 1114, 4, 315, 80492, 5789, 323, 77289, 21160, 4460, 311, 387, 2682, 555, 220, 2366, 15, 220, 16, 662, 19173, 11, 439, 220, 679, 24, 3782, 311, 264, 3345, 1193, 220, 868, 13, 17, 4, 315, 3728, 4363, 574, 7559, 2949, 2682, 5789, 220, 21, 662, 763, 220, 2366, 15, 11, 279, 26958, 389, 63711, 66071, 320, 85571, 8, 690, 11142, 264, 502, 3728, 73119, 12914, 369, 279, 1772, 12, 2366, 15, 11639, 449, 502, 11811, 743, 369, 220, 10866, 15, 13, 2057, 2274, 420, 502, 12914, 11, 279, 22834, 690, 1205, 311, 3477, 1202, 48188, 323, 28950, 449, 279, 3766, 12914, 13, 3861, 315, 279, 3682, 63836, 315, 362, 41652, 13791, 220, 806, 374, 430, 433, 374, 459, 3158, 6108, 2218, 430, 649, 387, 2322, 449, 2697, 41961, 311, 279, 9313, 315, 73119, 220, 22, 662, 10541, 279, 43851, 315, 264, 2682, 3158, 14921, 7119, 362, 41652, 13791, 220, 806, 11, 2682, 5789, 656, 539, 617, 311, 387, 24073, 449, 279, 6156, 5915, 315, 22973, 73119, 13, 1115, 374, 5423, 837, 304, 5961, 1778, 439, 279, 3723, 4273, 315, 5270, 320, 25342, 8, 1405, 2682, 5789, 617, 35901, 1027, 24073, 369, 8125, 1023, 1109, 73119, 11, 1778, 439, 13042, 323, 13970, 26431, 220, 23, 1174, 477, 6996, 315, 29149, 907, 220, 24, 662, 1666, 264, 1121, 11, 3293, 29060, 617, 7263, 1139, 3488, 3508, 6484, 2682, 5789, 527, 3604, 18899, 279, 29711, 2704, 315, 17190, 2230, 9606, 220, 18, 1174, 220, 19, 1174, 323, 3508, 814, 1288, 13750, 387, 31094, 7119, 19261, 362, 41652, 13791, 220, 806, 13, 2057, 8417, 279, 13112, 311, 902, 1510, 2682, 5789, 527, 86387, 304, 279, 9313, 315, 17190, 2230, 9606, 323, 1268, 1790, 5217, 4363, 374, 2631, 311, 6144, 9606, 11, 584, 2011, 3619, 279, 28347, 1990, 2682, 5789, 323, 9606, 21986, 13, 16644, 430, 279, 17139, 5915, 315, 32145, 362, 41652, 13791, 220, 806, 374, 311, 6144, 73119, 323, 279, 3600, 433, 5825, 11, 502, 12098, 3779, 311, 5662, 1510, 323, 3938, 11811, 1288, 387, 24073, 449, 279, 3230, 5915, 315, 22973, 73119, 11, 5423, 21699, 323, 52356, 9606, 13, 25122, 11, 1193, 220, 22, 13, 16, 4, 315, 279, 7427, 753, 4363, 374, 304, 264, 7701, 2682, 2704, 430, 374, 9152, 311, 21813, 73119, 220, 23, 1174, 220, 605, 662, 578, 1455, 4279, 38970, 555, 902, 279, 3109, 2955, 988, 502, 12098, 439, 2682, 374, 1555, 279, 14747, 315, 6484, 586, 4363, 311, 264, 2682, 2704, 510, 68, 1326, 2637, 279, 14747, 315, 22555, 315, 11680, 9744, 320, 9574, 44, 8, 4363, 311, 264, 5165, 72377, 477, 85192, 12299, 60, 220, 806, 662, 4452, 11, 279, 5054, 38575, 369, 279, 14747, 315, 586, 12098, 311, 7701, 2682, 5789, 374, 539, 2744, 37849, 220, 717, 662, 24296, 11, 279, 18539, 315, 586, 12098, 369, 14747, 311, 2682, 5789, 1253, 387, 7347, 13, 1789, 3187, 11, 4056, 220, 2721, 4, 315, 279, 4363, 304, 279, 1614, 315, 8421, 11, 7427, 11, 374, 38171, 13234, 13, 4314, 5054, 323, 96968, 32116, 1253, 3152, 430, 879, 12098, 1778, 439, 29711, 2593, 3808, 1253, 1205, 311, 1935, 264, 810, 21102, 3560, 304, 6574, 29711, 11811, 304, 279, 7427, 220, 1032, 1174, 220, 975, 662, 5751, 4007, 20034, 311, 8720, 1268, 1510, 2682, 5789, 304, 279, 58636, 7427, 527, 29820, 311, 279, 9313, 315, 1202, 1455, 17190, 2230, 9606, 11, 323, 1268, 279, 14747, 315, 6484, 586, 323, 879, 12098, 311, 264, 7701, 2682, 2704, 649, 12576, 279, 7427, 4726, 304, 49071, 287, 1884, 9606, 13, 1226, 1511, 264, 854, 34579, 5603, 220, 868, 1174, 220, 845, 311, 24564, 3508, 1510, 2682, 5789, 2997, 21699, 323, 52356, 9606, 323, 1207, 58894, 552, 320, 6881, 263, 14183, 311, 439, 3451, 408, 97409, 9606, 96206, 2731, 1109, 422, 814, 1047, 1027, 9277, 520, 4288, 13, 1226, 1243, 32448, 1268, 1690, 52356, 9606, 1047, 220, 966, 4, 315, 872, 2134, 4871, 279, 1510, 6932, 315, 2682, 5789, 13, 763, 279, 19821, 315, 9606, 19440, 7187, 68507, 6492, 11, 264, 6037, 315, 25015, 13533, 430, 220, 966, 4, 315, 264, 9606, 529, 2134, 2011, 387, 2682, 369, 433, 311, 23135, 304, 279, 8545, 220, 1114, 662, 1226, 1243, 4726, 30239, 3508, 477, 539, 279, 8824, 311, 6144, 810, 52356, 9606, 6866, 1555, 279, 17550, 14747, 315, 59995, 1851, 291, 586, 323, 879, 12098, 311, 264, 7701, 2682, 2704, 13, 1789, 682, 315, 1057, 41300, 11, 584, 1005, 459, 384, 2202, 70, 290, 6108, 5603, 11, 439, 384, 2202, 70, 919, 617, 1027, 6982, 311, 4097, 279, 7353, 478, 28286, 315, 17226, 71699, 323, 9606, 220, 972, 662, 18591, 323, 10430, 6104, 73119, 29711, 374, 22628, 439, 264, 10844, 369, 1690, 6484, 7701, 2682, 5789, 11, 1057, 854, 34579, 3135, 13519, 430, 279, 22165, 315, 2682, 5789, 304, 279, 7427, 706, 14090, 4745, 311, 2997, 520, 46570, 9606, 13, 1789, 264, 3544, 1396, 315, 384, 2202, 70, 919, 11, 5423, 304, 279, 19001, 5415, 11, 584, 1766, 430, 52356, 9606, 5131, 617, 2753, 315, 872, 2134, 13282, 2949, 2682, 5789, 1109, 422, 1521, 5789, 1047, 1027, 9277, 520, 4288, 320, 30035, 13, 220, 16, 264, 570, 58237, 279, 4553, 58636, 7427, 11, 584, 1766, 430, 7701, 2682, 5789, 304, 220, 2131, 4, 315, 384, 2202, 70, 919, 1051, 11201, 520, 22973, 279, 21986, 315, 52356, 9606, 1109, 422, 872, 3813, 1047, 1027, 12146, 520, 4288, 2949, 279, 1890, 384, 2202, 70, 290, 320, 30035, 13, 220, 16, 128257, 198, 128256, 78191, 198, 644, 220, 9674, 17, 279, 3723, 4273, 3549, 96179, 11, 279, 1176, 5165, 5657, 304, 279, 1917, 13, 8876, 1243, 1690, 810, 27943, 11, 63003, 11, 75998, 11, 49362, 288, 323, 1023, 2682, 5789, 617, 1027, 3549, 304, 279, 7427, 13, 38095, 5789, 11, 1093, 96179, 11, 527, 56193, 11, 719, 527, 814, 3604, 7524, 520, 47995, 52356, 9606, 30, 1628, 422, 539, 11, 1268, 649, 3938, 2682, 5789, 656, 2731, 30, 362, 2128, 315, 12208, 22012, 520, 23195, 3314, 3907, 4756, 264, 4007, 304, 38130, 29140, 311, 4320, 1521, 4860, 13, 2435, 1511, 6500, 4211, 311, 8417, 422, 2682, 5789, 304, 279, 7427, 21813, 3403, 4363, 70598, 555, 52356, 9606, 311, 49672, 6106, 872, 3938, 20237, 304, 279, 8545, 13, 1666, 433, 374, 11, 279, 6671, 374, 36033, 25, 5046, 279, 220, 11068, 52356, 36041, 278, 11, 12224, 11, 64873, 458, 323, 89022, 1122, 9606, 304, 279, 58636, 7427, 1193, 220, 1691, 527, 49672, 34683, 555, 6484, 2682, 5789, 13, 32406, 502, 2682, 5789, 389, 586, 4363, 374, 97059, 449, 32116, 13, 9176, 2682, 5789, 527, 24073, 3196, 389, 62081, 13444, 477, 6996, 315, 29149, 907, 323, 1521, 13186, 1541, 956, 14647, 8935, 520, 46570, 9606, 13, 1252, 75060, 481, 5054, 92399, 649, 1101, 3118, 5435, 13, 1183, 36040, 2468, 6798, 11, 22103, 17054, 304, 279, 6011, 315, 47978, 42109, 23199, 323, 78375, 5955, 11, 323, 4007, 1080, 43802, 11497, 11, 330, 3947, 706, 1027, 264, 6908, 5054, 4585, 304, 279, 7427, 311, 8108, 2682, 5789, 1778, 439, 5165, 3206, 2901, 13, 4452, 11, 1057, 3135, 4284, 430, 584, 539, 1193, 1205, 311, 5376, 279, 29079, 10401, 315, 2682, 5789, 304, 279, 7427, 11, 719, 584, 1101, 1205, 311, 6106, 430, 584, 527, 22973, 279, 7634, 430, 6782, 9200, 39646, 369, 52356, 9606, 1210, 13596, 33287, 374, 279, 7347, 18539, 315, 586, 4363, 13, 1789, 3187, 11, 304, 279, 1614, 315, 8421, 220, 2721, 4, 315, 279, 4363, 374, 38171, 13234, 13, 1628, 4184, 311, 279, 4007, 1524, 422, 682, 6918, 323, 1614, 586, 12098, 1051, 2728, 2682, 3158, 2704, 810, 1109, 4376, 315, 279, 520, 46570, 9606, 304, 279, 7427, 1053, 2103, 387, 304, 8137, 315, 52609, 13, 330, 1687, 527, 539, 23377, 430, 2682, 5789, 527, 3815, 264, 3958, 2683, 1359, 1071, 22653, 74447, 484, 11, 22103, 17054, 304, 279, 6011, 315, 47978, 42109, 23199, 323, 78375, 5955, 323, 4007, 1080, 43802, 11, 330, 12840, 584, 527, 23377, 374, 430, 1070, 527, 1690, 10708, 311, 5376, 9313, 1210, 3861, 315, 1884, 10708, 374, 279, 9886, 315, 29711, 2593, 3808, 389, 879, 4363, 13, 45435, 2593, 3808, 527, 37079, 11, 5897, 20038, 430, 9067, 3938, 4500, 389, 879, 4363, 13, 763, 9473, 369, 29820, 311, 29711, 9045, 11, 4363, 7980, 14389, 872, 3424, 3268, 323, 649, 5371, 3827, 7720, 13, 3861, 315, 279, 1455, 3062, 14955, 505, 279, 4007, 374, 430, 449, 279, 1520, 315, 879, 4363, 7980, 279, 7427, 706, 539, 5675, 279, 8824, 311, 49672, 6144, 220, 1041, 4, 315, 1202, 52356, 9606, 13, 330, 2181, 374, 17821, 430, 26613, 29711, 315, 52356, 9606, 690, 387, 17427, 555, 7859, 6918, 2682, 5789, 1359, 1071, 74447, 484, 13, 330, 8140, 3495, 22020, 430, 879, 4363, 7980, 4097, 459, 10778, 6149, 311, 32145, 29711, 9021, 1210, 2468, 6798, 20536, 11, 330, 9673, 14955, 3041, 757, 3987, 430, 584, 649, 2103, 1304, 264, 2349, 369, 279, 2731, 13, 2030, 11, 422, 584, 527, 2133, 311, 3243, 279, 4465, 2403, 52609, 584, 527, 2133, 311, 1205, 279, 1520, 315, 879, 4363, 7980, 1210, 220, 128257, 198 ]

1,828

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Marked uncertainty in California (CA) precipitation projections challenges their use in adaptation planning in the region already experiencing severe water stress. Under global warming, a westerly jet extension in the North Pacific analogous to the El Niño-like teleconnection has been suggested as a key mechanism for CA winter precipitation changes. However, this teleconnection has not been reconciled with the well-known El Niño-like warming response or the controversial role of internal variability in the precipitation uncertainty. Here we find that internal variability contributes > 70% and > 50% of uncertainty in the CA precipitation changes and the El Niño-like warming, respectively, based on analysis of 318 climate simulations from several multi-model and large ensembles. The Interdecadal Pacific Oscillation plays a key role in each contribution and in connecting the two via the westerly jet extension. This unifying understanding of the role of internal variability in CA precipitation provides critical guidance for reducing and communicating uncertainty to inform adaptation planning. Introduction Located on the western edge of the North America continent and influenced by the Pacific storm tracks, California (CA) has a distinct precipitation annual cycle, with a large fraction of precipitation falling within the winter season (December–January–February). Hence, winter precipitation is vital to the agriculture, ecosystems, and water resources in the region. Despite the very certain sign of precipitation frequency and intensity changes from multimodel ensembles, with decreased frequency and increased intensity, large uncertainty in the changes of annual or winter CA precipitation amount is evident due to the superposition of these two opposite contributions 1 , 2 , 3 , 4 . Influenced by both tropical forcing and mid-latitude westerlies 5 , the intermodel spreads of both the signs and magnitudes of CA precipitation changes under warming are large 2 , 3 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 . Climate model projection uncertainty has been robustly partitioned into its different sources at global scale 14 , 15 , but such partitioning may be highly variable at local-to-regional scale. Understanding the fractional contribution of uncertainty from different sources is important for informing the use of climate projections for regional adaptation planning. The total uncertainty conflates contributions of uncertainty from internal variability, the model response to forcing, and the emission scenarios 14 , 15 , 16 , 17 . With climate change projections conditioned on the emission scenarios, which are developed based on storylines of socioeconomic changes with no probabilities assigned, progress can be made in understanding uncertainty by focusing on the internal variability and model response uncertainty. We emphasize the decomposition of uncertainty into components of externally forced vs. internal variability because uncertainty in the response to external forcing is an important and potentially reducible uncertainty factor for targeted future research through model development and observational constraints. Although uncertainty from internal variability is irreducible, improving the decadal prediction of the relevant internal modes may also potentially reduce uncertainty in predicting the decadal trends in CA precipitation in the near future. Separating the uncertainties caused by the model response and internal variability is difficult in traditional multimodel ensembles from the Coupled Model Intercomparison Project phase 5 (CMIP5; ref. 18 ) and phase 6 (CMIP6; ref. 19 ), as most models only include a small number of realizations, which can not faithfully represent the range of internal variability 20 . While selecting subsets of the CMIP models may reduce model uncertainty to provide more consistent projections of future CA precipitation 11 , 21 , the internal variability is even more under-represented by the smaller subsets of models. The advent of large ensembles from several climate models presents an opportunity for isolating the internal variability from the model response uncertainty 22 . Internal variability, which arises from processes intrinsic to the atmosphere, the ocean, and the coupled ocean-atmosphere system via dynamic and thermodynamic interactions, makes an appreciable contribution to the precipitation changes on a decadal timescale 17 , 23 , especially at smaller spatial scales 24 . The dominant effect of internal variability in the 2010–2015 CA megadrought has been broadly recognized 25 , 26 , although anthropogenic warming is argued to enhance the probability of severe drought 27 , 28 . The Interdecadal Pacific Oscillation (IPO), or Pacific Decadal Oscillation (PDO), is a leading mode of internal variability at the decadal timescale featuring sea surface temperature (SST) variability in the Pacific Ocean. The IPO can be viewed as a manifestation of the integrated influences of the Pacific Ocean, including the El Niño-Southern Oscillation (ENSO) 29 , 30 . As described in previous studies 31 , 32 , 33 , the IPO impact on CA precipitation is manifested via the interdecadal modulation of ENSO teleconnections. Based on 21 CMIP3 models, a study 17 suggested that more than half of the intermodel spread in the precipitation changes under global warming over most of the extratropical regions are contributed by internal variability, which is estimated based on a single set of large ensemble simulations. In contrast, based on 36 CMIP5 models, another study 34 concluded that internal variability does not contribute substantially to the intermodel spread over broad regions, including CA. Similar conclusions were obtained by comparing the intermodel range from CMIP5 models with the intermember range from a single set of large ensemble simulations 11 . These controversial results motivate a need to combine the CMIP5 and CMIP6 models with several large ensemble simulations to quantify the contribution of internal variability to the total uncertainty of CA precipitation changes. Physically, future changes in CA winter precipitation under warming are related to an eastward extension of the North Pacific westerly jet that steers more storms towards CA, analogous to the El Niño-like teleconnection 7 , 11 , 34 . However, previous studies 7 , 11 , 12 , 34 based on CMIP5 models could not establish a close intermodel relationship between the CA precipitation changes and the El Niño-like warming (i.e., stronger SST warming in the tropical eastern Pacific relative to the western Pacific) under", "role": "user" }, { "content": "Over the past 40 years, winters in California have become drier. This is a problem for the region's agricultural operations, as farmers rely on winter precipitation to irrigate their crops. Determining if California will continue getting drier, or if the trend will reverse, has implications for its millions of residents. But so far, climate models that account for changes in greenhouse gases and other human activities have had trouble reproducing California's observed drying trends. When climate models project the future or simulate the past, they can't agree on long-term precipitation trends. Researchers at Pacific Northwest National Laboratory (PNNL) want to know why because these mixed results aren't very useful for future water resource planning. \"When we see these large uncertainties in model simulations and projections, we have to ask whether or not the models are up for the task,\" said Ruby Leung, a Battelle Fellow and atmospheric scientist at PNNL. \"One challenge with modeling California is that long-term natural cycles heavily affect its precipitation.\" These cycles range from years long, like El Niño and La Niña, to decades long, like the Interdecadal Pacific Oscillation (IPO). They represent natural variability associated with sea surface temperature patterns in the Pacific Ocean and affect winter precipitation in California. But how much of a role do they play in spawning uncertainty in California's precipitation projections? A big one, it turns out. Results from Leung and a PNNL team show that natural cycles are responsible for >70 percent of the uncertainty in model simulations of precipitation trends over the past 40 years. By isolating the effects of the natural cycles, scientists can focus on improving models to reduce the remaining uncertainty related to how greenhouse gases and other human activities affect climate. The impact of ensembles With more computing power, researchers can now run large sets of simulations called large ensemble simulations. To produce them, researchers run climate models from 40–100 times with minor differences in their starting conditions. Because everything except for the starting conditions remains the same, these ensembles provide a unique representation of natural variability. Modeling centers around the world also run simulations that contribute toward multi-model ensembles. These represent the total uncertainty due to both natural variability and model uncertainty. Leung and her team analyzed three ensemble simulations generated by three different climate models and two multi-model ensembles of two recent climate model generations. They wanted to determine the sources of uncertainty in the projections of California precipitation. What they found surprised them. The team found that natural climate cycles were responsible for roughly 70 percent of the total uncertainty in model simulations of California precipitation trends in the past 40 years. That leaves 30 percent of the uncertainty for how models represent human influence on climate. \"We know that natural cycles have major impacts on California's climate, but we didn't think that they would dominate the total uncertainty in climate simulations to this extent,\" said Leung. \"This result shows the importance of large ensemble simulations for isolating human influence on climate, which may be small compared to natural cycles in some regions.\" Natural cycles versus human impacts Of the natural cycles that influence California's climate, the IPO is one of the most important. Its decades-long phases help determine if California is in a wetting or drying trend. The team's results point to its substantial role in California's drying over the past 40 years. Currently, climate models have limited skill in predicting the transition between the IPO phases—especially decades from now. Therefore, future projections of California precipitation have large uncertainty due to IPO cycles. So where does that leave human-induced changes, like warming and increasing greenhouse gases? They still play a substantial role in shaping the future climate and weather. As greenhouse gases continue to accumulate in the atmosphere and the ocean's large heat capacity catches up with increasing temperatures, warming and its effects will become more pronounced. \"Natural variability, such as the IPO, is like background noise,\" said Leung. \"Although that noise is substantial, the climate response to rising concentrations of greenhouse gases is a signal that grows over time. Focusing our efforts on reducing model disagreement for this signal is impactful, particularly when looking to the far future.\" Understanding the extent to which natural and external factors affect California precipitation helps researchers better contextualize their projections. This knowledge helps modelers explain why their models might be missing the mark in simulating past observed trends. Scientists can then communicate more nuanced results to people planning California's water future. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Marked uncertainty in California (CA) precipitation projections challenges their use in adaptation planning in the region already experiencing severe water stress. Under global warming, a westerly jet extension in the North Pacific analogous to the El Niño-like teleconnection has been suggested as a key mechanism for CA winter precipitation changes. However, this teleconnection has not been reconciled with the well-known El Niño-like warming response or the controversial role of internal variability in the precipitation uncertainty. Here we find that internal variability contributes > 70% and > 50% of uncertainty in the CA precipitation changes and the El Niño-like warming, respectively, based on analysis of 318 climate simulations from several multi-model and large ensembles. The Interdecadal Pacific Oscillation plays a key role in each contribution and in connecting the two via the westerly jet extension. This unifying understanding of the role of internal variability in CA precipitation provides critical guidance for reducing and communicating uncertainty to inform adaptation planning. Introduction Located on the western edge of the North America continent and influenced by the Pacific storm tracks, California (CA) has a distinct precipitation annual cycle, with a large fraction of precipitation falling within the winter season (December–January–February). Hence, winter precipitation is vital to the agriculture, ecosystems, and water resources in the region. Despite the very certain sign of precipitation frequency and intensity changes from multimodel ensembles, with decreased frequency and increased intensity, large uncertainty in the changes of annual or winter CA precipitation amount is evident due to the superposition of these two opposite contributions 1 , 2 , 3 , 4 . Influenced by both tropical forcing and mid-latitude westerlies 5 , the intermodel spreads of both the signs and magnitudes of CA precipitation changes under warming are large 2 , 3 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 . Climate model projection uncertainty has been robustly partitioned into its different sources at global scale 14 , 15 , but such partitioning may be highly variable at local-to-regional scale. Understanding the fractional contribution of uncertainty from different sources is important for informing the use of climate projections for regional adaptation planning. The total uncertainty conflates contributions of uncertainty from internal variability, the model response to forcing, and the emission scenarios 14 , 15 , 16 , 17 . With climate change projections conditioned on the emission scenarios, which are developed based on storylines of socioeconomic changes with no probabilities assigned, progress can be made in understanding uncertainty by focusing on the internal variability and model response uncertainty. We emphasize the decomposition of uncertainty into components of externally forced vs. internal variability because uncertainty in the response to external forcing is an important and potentially reducible uncertainty factor for targeted future research through model development and observational constraints. Although uncertainty from internal variability is irreducible, improving the decadal prediction of the relevant internal modes may also potentially reduce uncertainty in predicting the decadal trends in CA precipitation in the near future. Separating the uncertainties caused by the model response and internal variability is difficult in traditional multimodel ensembles from the Coupled Model Intercomparison Project phase 5 (CMIP5; ref. 18 ) and phase 6 (CMIP6; ref. 19 ), as most models only include a small number of realizations, which can not faithfully represent the range of internal variability 20 . While selecting subsets of the CMIP models may reduce model uncertainty to provide more consistent projections of future CA precipitation 11 , 21 , the internal variability is even more under-represented by the smaller subsets of models. The advent of large ensembles from several climate models presents an opportunity for isolating the internal variability from the model response uncertainty 22 . Internal variability, which arises from processes intrinsic to the atmosphere, the ocean, and the coupled ocean-atmosphere system via dynamic and thermodynamic interactions, makes an appreciable contribution to the precipitation changes on a decadal timescale 17 , 23 , especially at smaller spatial scales 24 . The dominant effect of internal variability in the 2010–2015 CA megadrought has been broadly recognized 25 , 26 , although anthropogenic warming is argued to enhance the probability of severe drought 27 , 28 . The Interdecadal Pacific Oscillation (IPO), or Pacific Decadal Oscillation (PDO), is a leading mode of internal variability at the decadal timescale featuring sea surface temperature (SST) variability in the Pacific Ocean. The IPO can be viewed as a manifestation of the integrated influences of the Pacific Ocean, including the El Niño-Southern Oscillation (ENSO) 29 , 30 . As described in previous studies 31 , 32 , 33 , the IPO impact on CA precipitation is manifested via the interdecadal modulation of ENSO teleconnections. Based on 21 CMIP3 models, a study 17 suggested that more than half of the intermodel spread in the precipitation changes under global warming over most of the extratropical regions are contributed by internal variability, which is estimated based on a single set of large ensemble simulations. In contrast, based on 36 CMIP5 models, another study 34 concluded that internal variability does not contribute substantially to the intermodel spread over broad regions, including CA. Similar conclusions were obtained by comparing the intermodel range from CMIP5 models with the intermember range from a single set of large ensemble simulations 11 . These controversial results motivate a need to combine the CMIP5 and CMIP6 models with several large ensemble simulations to quantify the contribution of internal variability to the total uncertainty of CA precipitation changes. Physically, future changes in CA winter precipitation under warming are related to an eastward extension of the North Pacific westerly jet that steers more storms towards CA, analogous to the El Niño-like teleconnection 7 , 11 , 34 . However, previous studies 7 , 11 , 12 , 34 based on CMIP5 models could not establish a close intermodel relationship between the CA precipitation changes and the El Niño-like warming (i.e., stronger SST warming in the tropical eastern Pacific relative to the western Pacific) under<|im_end|> <|im_start|>assistant Over the past 40 years, winters in California have become drier. This is a problem for the region's agricultural operations, as farmers rely on winter precipitation to irrigate their crops. Determining if California will continue getting drier, or if the trend will reverse, has implications for its millions of residents. But so far, climate models that account for changes in greenhouse gases and other human activities have had trouble reproducing California's observed drying trends. When climate models project the future or simulate the past, they can't agree on long-term precipitation trends. Researchers at Pacific Northwest National Laboratory (PNNL) want to know why because these mixed results aren't very useful for future water resource planning. "When we see these large uncertainties in model simulations and projections, we have to ask whether or not the models are up for the task," said Ruby Leung, a Battelle Fellow and atmospheric scientist at PNNL. "One challenge with modeling California is that long-term natural cycles heavily affect its precipitation." These cycles range from years long, like El Niño and La Niña, to decades long, like the Interdecadal Pacific Oscillation (IPO). They represent natural variability associated with sea surface temperature patterns in the Pacific Ocean and affect winter precipitation in California. But how much of a role do they play in spawning uncertainty in California's precipitation projections? A big one, it turns out. Results from Leung and a PNNL team show that natural cycles are responsible for >70 percent of the uncertainty in model simulations of precipitation trends over the past 40 years. By isolating the effects of the natural cycles, scientists can focus on improving models to reduce the remaining uncertainty related to how greenhouse gases and other human activities affect climate. The impact of ensembles With more computing power, researchers can now run large sets of simulations called large ensemble simulations. To produce them, researchers run climate models from 40–100 times with minor differences in their starting conditions. Because everything except for the starting conditions remains the same, these ensembles provide a unique representation of natural variability. Modeling centers around the world also run simulations that contribute toward multi-model ensembles. These represent the total uncertainty due to both natural variability and model uncertainty. Leung and her team analyzed three ensemble simulations generated by three different climate models and two multi-model ensembles of two recent climate model generations. They wanted to determine the sources of uncertainty in the projections of California precipitation. What they found surprised them. The team found that natural climate cycles were responsible for roughly 70 percent of the total uncertainty in model simulations of California precipitation trends in the past 40 years. That leaves 30 percent of the uncertainty for how models represent human influence on climate. "We know that natural cycles have major impacts on California's climate, but we didn't think that they would dominate the total uncertainty in climate simulations to this extent," said Leung. "This result shows the importance of large ensemble simulations for isolating human influence on climate, which may be small compared to natural cycles in some regions." Natural cycles versus human impacts Of the natural cycles that influence California's climate, the IPO is one of the most important. Its decades-long phases help determine if California is in a wetting or drying trend. The team's results point to its substantial role in California's drying over the past 40 years. Currently, climate models have limited skill in predicting the transition between the IPO phases—especially decades from now. Therefore, future projections of California precipitation have large uncertainty due to IPO cycles. So where does that leave human-induced changes, like warming and increasing greenhouse gases? They still play a substantial role in shaping the future climate and weather. As greenhouse gases continue to accumulate in the atmosphere and the ocean's large heat capacity catches up with increasing temperatures, warming and its effects will become more pronounced. "Natural variability, such as the IPO, is like background noise," said Leung. "Although that noise is substantial, the climate response to rising concentrations of greenhouse gases is a signal that grows over time. Focusing our efforts on reducing model disagreement for this signal is impactful, particularly when looking to the far future." Understanding the extent to which natural and external factors affect California precipitation helps researchers better contextualize their projections. This knowledge helps modelers explain why their models might be missing the mark in simulating past observed trends. Scientists can then communicate more nuanced results to people planning California's water future. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 4488, 291, 27924, 304, 7188, 320, 5158, 8, 61050, 41579, 11774, 872, 1005, 304, 34185, 9293, 304, 279, 5654, 2736, 25051, 15748, 3090, 8631, 13, 9636, 3728, 24808, 11, 264, 289, 5302, 398, 17004, 9070, 304, 279, 4892, 16867, 79283, 311, 279, 4072, 22652, 14871, 12970, 8122, 7898, 706, 1027, 12090, 439, 264, 1401, 17383, 369, 9362, 12688, 61050, 4442, 13, 4452, 11, 420, 8122, 7898, 706, 539, 1027, 32545, 2230, 449, 279, 1664, 22015, 4072, 22652, 14871, 12970, 24808, 2077, 477, 279, 20733, 3560, 315, 5419, 54709, 304, 279, 61050, 27924, 13, 5810, 584, 1505, 430, 5419, 54709, 44072, 871, 220, 2031, 4, 323, 871, 220, 1135, 4, 315, 27924, 304, 279, 9362, 61050, 4442, 323, 279, 4072, 22652, 14871, 12970, 24808, 11, 15947, 11, 3196, 389, 6492, 315, 220, 17592, 10182, 47590, 505, 3892, 7447, 29344, 323, 3544, 665, 41794, 13, 578, 5783, 8332, 51588, 16867, 56736, 67184, 11335, 264, 1401, 3560, 304, 1855, 19035, 323, 304, 21583, 279, 1403, 4669, 279, 289, 5302, 398, 17004, 9070, 13, 1115, 653, 7922, 8830, 315, 279, 3560, 315, 5419, 54709, 304, 9362, 61050, 5825, 9200, 19351, 369, 18189, 323, 42247, 27924, 311, 6179, 34185, 9293, 13, 29438, 42867, 389, 279, 19001, 6964, 315, 279, 4892, 5270, 32843, 323, 28160, 555, 279, 16867, 13766, 14242, 11, 7188, 320, 5158, 8, 706, 264, 12742, 61050, 9974, 11008, 11, 449, 264, 3544, 19983, 315, 61050, 16054, 2949, 279, 12688, 3280, 320, 33246, 4235, 33327, 4235, 33877, 570, 32140, 11, 12688, 61050, 374, 16595, 311, 279, 30029, 11, 61951, 11, 323, 3090, 5070, 304, 279, 5654, 13, 18185, 279, 1633, 3738, 1879, 315, 61050, 11900, 323, 21261, 4442, 505, 80149, 725, 665, 41794, 11, 449, 25983, 11900, 323, 7319, 21261, 11, 3544, 27924, 304, 279, 4442, 315, 9974, 477, 12688, 9362, 61050, 3392, 374, 30576, 4245, 311, 279, 2307, 3571, 315, 1521, 1403, 14329, 19564, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 662, 88654, 5886, 555, 2225, 35148, 25957, 323, 5209, 2922, 17584, 289, 5302, 49201, 220, 20, 1174, 279, 958, 2590, 43653, 315, 2225, 279, 12195, 323, 8622, 21237, 315, 9362, 61050, 4442, 1234, 24808, 527, 3544, 220, 17, 1174, 220, 18, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 662, 31636, 1646, 22343, 27924, 706, 1027, 22514, 398, 17071, 291, 1139, 1202, 2204, 8336, 520, 3728, 5569, 220, 975, 1174, 220, 868, 1174, 719, 1778, 17071, 287, 1253, 387, 7701, 3977, 520, 2254, 4791, 33263, 4001, 5569, 13, 46551, 279, 69309, 19035, 315, 27924, 505, 2204, 8336, 374, 3062, 369, 63025, 279, 1005, 315, 10182, 41579, 369, 15481, 34185, 9293, 13, 578, 2860, 27924, 83977, 988, 19564, 315, 27924, 505, 5419, 54709, 11, 279, 1646, 2077, 311, 25957, 11, 323, 279, 41353, 26350, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 662, 3161, 10182, 2349, 41579, 66731, 389, 279, 41353, 26350, 11, 902, 527, 8040, 3196, 389, 3446, 8128, 315, 80431, 4442, 449, 912, 49316, 12893, 11, 5208, 649, 387, 1903, 304, 8830, 27924, 555, 21760, 389, 279, 5419, 54709, 323, 1646, 2077, 27924, 13, 1226, 47032, 279, 66266, 315, 27924, 1139, 6956, 315, 69442, 9770, 6296, 13, 5419, 54709, 1606, 27924, 304, 279, 2077, 311, 9434, 25957, 374, 459, 3062, 323, 13893, 3679, 66, 1260, 27924, 8331, 369, 17550, 3938, 3495, 1555, 1646, 4500, 323, 90380, 17413, 13, 10541, 27924, 505, 5419, 54709, 374, 25912, 79385, 11, 18899, 279, 1654, 51588, 20212, 315, 279, 9959, 5419, 20362, 1253, 1101, 13893, 8108, 27924, 304, 52997, 279, 1654, 51588, 18845, 304, 9362, 61050, 304, 279, 3221, 3938, 13, 34199, 1113, 279, 69867, 9057, 555, 279, 1646, 2077, 323, 5419, 54709, 374, 5107, 304, 8776, 80149, 725, 665, 41794, 505, 279, 18733, 50185, 5008, 5783, 55805, 5907, 10474, 220, 20, 320, 10190, 3378, 20, 26, 2098, 13, 220, 972, 883, 323, 10474, 220, 21, 320, 10190, 3378, 21, 26, 2098, 13, 220, 777, 7026, 439, 1455, 4211, 1193, 2997, 264, 2678, 1396, 315, 1972, 8200, 11, 902, 649, 539, 94176, 4097, 279, 2134, 315, 5419, 54709, 220, 508, 662, 6104, 27397, 75605, 315, 279, 18582, 3378, 4211, 1253, 8108, 1646, 27924, 311, 3493, 810, 13263, 41579, 315, 3938, 9362, 61050, 220, 806, 1174, 220, 1691, 1174, 279, 5419, 54709, 374, 1524, 810, 1234, 5621, 29844, 291, 555, 279, 9333, 75605, 315, 4211, 13, 578, 11599, 315, 3544, 665, 41794, 505, 3892, 10182, 4211, 18911, 459, 6776, 369, 13399, 1113, 279, 5419, 54709, 505, 279, 1646, 2077, 27924, 220, 1313, 662, 15774, 54709, 11, 902, 48282, 505, 11618, 47701, 311, 279, 16975, 11, 279, 18435, 11, 323, 279, 34356, 18435, 29883, 8801, 8182, 1887, 4669, 8915, 323, 30945, 61002, 22639, 11, 3727, 459, 9989, 2205, 19035, 311, 279, 61050, 4442, 389, 264, 1654, 51588, 3115, 2296, 220, 1114, 1174, 220, 1419, 1174, 5423, 520, 9333, 29079, 29505, 220, 1187, 662, 578, 25462, 2515, 315, 5419, 54709, 304, 279, 220, 679, 15, 4235, 679, 20, 9362, 19262, 329, 6478, 706, 1027, 44029, 15324, 220, 914, 1174, 220, 1627, 1174, 8051, 41416, 29569, 24808, 374, 18784, 311, 18885, 279, 19463, 315, 15748, 37846, 220, 1544, 1174, 220, 1591, 662, 578, 5783, 8332, 51588, 16867, 56736, 67184, 320, 40, 2089, 705, 477, 16867, 3799, 51588, 56736, 67184, 320, 37376, 705, 374, 264, 6522, 3941, 315, 5419, 54709, 520, 279, 1654, 51588, 3115, 2296, 16850, 9581, 7479, 9499, 320, 50, 790, 8, 54709, 304, 279, 16867, 22302, 13, 578, 67992, 649, 387, 19894, 439, 264, 64050, 315, 279, 18751, 34453, 315, 279, 16867, 22302, 11, 2737, 279, 4072, 22652, 14871, 6354, 283, 6456, 56736, 67184, 320, 965, 14202, 8, 220, 1682, 1174, 220, 966, 662, 1666, 7633, 304, 3766, 7978, 220, 2148, 1174, 220, 843, 1174, 220, 1644, 1174, 279, 67992, 5536, 389, 9362, 61050, 374, 79754, 4669, 279, 958, 8332, 51588, 67547, 315, 469, 2507, 46, 8122, 51086, 13, 20817, 389, 220, 1691, 18582, 3378, 18, 4211, 11, 264, 4007, 220, 1114, 12090, 430, 810, 1109, 4376, 315, 279, 958, 2590, 9041, 304, 279, 61050, 4442, 1234, 3728, 24808, 927, 1455, 315, 279, 11741, 266, 51172, 13918, 527, 20162, 555, 5419, 54709, 11, 902, 374, 13240, 3196, 389, 264, 3254, 743, 315, 3544, 40126, 47590, 13, 763, 13168, 11, 3196, 389, 220, 1927, 18582, 3378, 20, 4211, 11, 2500, 4007, 220, 1958, 20536, 430, 5419, 54709, 1587, 539, 17210, 32302, 311, 279, 958, 2590, 9041, 927, 7353, 13918, 11, 2737, 9362, 13, 22196, 31342, 1051, 12457, 555, 27393, 279, 958, 2590, 2134, 505, 18582, 3378, 20, 4211, 449, 279, 958, 9792, 2134, 505, 264, 3254, 743, 315, 3544, 40126, 47590, 220, 806, 662, 4314, 20733, 3135, 62425, 264, 1205, 311, 16343, 279, 18582, 3378, 20, 323, 18582, 3378, 21, 4211, 449, 3892, 3544, 40126, 47590, 311, 76498, 279, 19035, 315, 5419, 54709, 311, 279, 2860, 27924, 315, 9362, 61050, 4442, 13, 13101, 2740, 11, 3938, 4442, 304, 9362, 12688, 61050, 1234, 24808, 527, 5552, 311, 459, 11226, 1637, 9070, 315, 279, 4892, 16867, 289, 5302, 398, 17004, 430, 4179, 388, 810, 44583, 7119, 9362, 11, 79283, 311, 279, 4072, 22652, 14871, 12970, 8122, 7898, 220, 22, 1174, 220, 806, 1174, 220, 1958, 662, 4452, 11, 3766, 7978, 220, 22, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1958, 3196, 389, 18582, 3378, 20, 4211, 1436, 539, 5813, 264, 3345, 958, 2590, 5133, 1990, 279, 9362, 61050, 4442, 323, 279, 4072, 22652, 14871, 12970, 24808, 320, 72, 1770, 2637, 16643, 92516, 24808, 304, 279, 35148, 24024, 16867, 8844, 311, 279, 19001, 16867, 8, 1234, 128257, 198, 128256, 78191, 198, 1959, 279, 3347, 220, 1272, 1667, 11, 86082, 304, 7188, 617, 3719, 294, 7401, 13, 1115, 374, 264, 3575, 369, 279, 5654, 596, 29149, 7677, 11, 439, 20957, 17631, 389, 12688, 61050, 311, 53105, 349, 872, 31665, 13, 36007, 287, 422, 7188, 690, 3136, 3794, 294, 7401, 11, 477, 422, 279, 9327, 690, 10134, 11, 706, 25127, 369, 1202, 11990, 315, 11062, 13, 2030, 779, 3117, 11, 10182, 4211, 430, 2759, 369, 4442, 304, 37647, 45612, 323, 1023, 3823, 7640, 617, 1047, 12544, 14843, 6253, 7188, 596, 13468, 46479, 18845, 13, 3277, 10182, 4211, 2447, 279, 3938, 477, 38553, 279, 3347, 11, 814, 649, 956, 7655, 389, 1317, 9860, 61050, 18845, 13, 59250, 520, 16867, 40505, 5165, 32184, 320, 47, 9944, 43, 8, 1390, 311, 1440, 3249, 1606, 1521, 9709, 3135, 7784, 956, 1633, 5505, 369, 3938, 3090, 5211, 9293, 13, 330, 4599, 584, 1518, 1521, 3544, 69867, 304, 1646, 47590, 323, 41579, 11, 584, 617, 311, 2610, 3508, 477, 539, 279, 4211, 527, 709, 369, 279, 3465, 1359, 1071, 24658, 2009, 2234, 11, 264, 33267, 6853, 37946, 323, 45475, 28568, 520, 393, 9944, 43, 13, 330, 4054, 8815, 449, 34579, 7188, 374, 430, 1317, 9860, 5933, 25492, 17345, 7958, 1202, 61050, 1210, 4314, 25492, 2134, 505, 1667, 1317, 11, 1093, 4072, 22652, 14871, 323, 5034, 22652, 18829, 11, 311, 11026, 1317, 11, 1093, 279, 5783, 8332, 51588, 16867, 56736, 67184, 320, 40, 2089, 570, 2435, 4097, 5933, 54709, 5938, 449, 9581, 7479, 9499, 12912, 304, 279, 16867, 22302, 323, 7958, 12688, 61050, 304, 7188, 13, 2030, 1268, 1790, 315, 264, 3560, 656, 814, 1514, 304, 79529, 27924, 304, 7188, 596, 61050, 41579, 30, 362, 2466, 832, 11, 433, 10800, 704, 13, 18591, 505, 2009, 2234, 323, 264, 393, 9944, 43, 2128, 1501, 430, 5933, 25492, 527, 8647, 369, 871, 2031, 3346, 315, 279, 27924, 304, 1646, 47590, 315, 61050, 18845, 927, 279, 3347, 220, 1272, 1667, 13, 3296, 13399, 1113, 279, 6372, 315, 279, 5933, 25492, 11, 14248, 649, 5357, 389, 18899, 4211, 311, 8108, 279, 9861, 27924, 5552, 311, 1268, 37647, 45612, 323, 1023, 3823, 7640, 7958, 10182, 13, 578, 5536, 315, 665, 41794, 3161, 810, 25213, 2410, 11, 12074, 649, 1457, 1629, 3544, 7437, 315, 47590, 2663, 3544, 40126, 47590, 13, 2057, 8356, 1124, 11, 12074, 1629, 10182, 4211, 505, 220, 1272, 4235, 1041, 3115, 449, 9099, 12062, 304, 872, 6041, 4787, 13, 9393, 4395, 3734, 369, 279, 6041, 4787, 8625, 279, 1890, 11, 1521, 665, 41794, 3493, 264, 5016, 13340, 315, 5933, 54709, 13, 77349, 19169, 2212, 279, 1917, 1101, 1629, 47590, 430, 17210, 9017, 7447, 29344, 665, 41794, 13, 4314, 4097, 279, 2860, 27924, 4245, 311, 2225, 5933, 54709, 323, 1646, 27924, 13, 2009, 2234, 323, 1077, 2128, 30239, 2380, 40126, 47590, 8066, 555, 2380, 2204, 10182, 4211, 323, 1403, 7447, 29344, 665, 41794, 315, 1403, 3293, 10182, 1646, 22540, 13, 2435, 4934, 311, 8417, 279, 8336, 315, 27924, 304, 279, 41579, 315, 7188, 61050, 13, 3639, 814, 1766, 14792, 1124, 13, 578, 2128, 1766, 430, 5933, 10182, 25492, 1051, 8647, 369, 17715, 220, 2031, 3346, 315, 279, 2860, 27924, 304, 1646, 47590, 315, 7188, 61050, 18845, 304, 279, 3347, 220, 1272, 1667, 13, 3011, 11141, 220, 966, 3346, 315, 279, 27924, 369, 1268, 4211, 4097, 3823, 10383, 389, 10182, 13, 330, 1687, 1440, 430, 5933, 25492, 617, 3682, 25949, 389, 7188, 596, 10182, 11, 719, 584, 3287, 956, 1781, 430, 814, 1053, 41836, 279, 2860, 27924, 304, 10182, 47590, 311, 420, 13112, 1359, 1071, 2009, 2234, 13, 330, 2028, 1121, 5039, 279, 12939, 315, 3544, 40126, 47590, 369, 13399, 1113, 3823, 10383, 389, 10182, 11, 902, 1253, 387, 2678, 7863, 311, 5933, 25492, 304, 1063, 13918, 1210, 18955, 25492, 19579, 3823, 25949, 5046, 279, 5933, 25492, 430, 10383, 7188, 596, 10182, 11, 279, 67992, 374, 832, 315, 279, 1455, 3062, 13, 11699, 11026, 24725, 35530, 1520, 8417, 422, 7188, 374, 304, 264, 14739, 1303, 477, 46479, 9327, 13, 578, 2128, 596, 3135, 1486, 311, 1202, 12190, 3560, 304, 7188, 596, 46479, 927, 279, 3347, 220, 1272, 1667, 13, 25122, 11, 10182, 4211, 617, 7347, 10151, 304, 52997, 279, 9320, 1990, 279, 67992, 35530, 2345, 36046, 11026, 505, 1457, 13, 15636, 11, 3938, 41579, 315, 7188, 61050, 617, 3544, 27924, 4245, 311, 67992, 25492, 13, 2100, 1405, 1587, 430, 5387, 3823, 38973, 4442, 11, 1093, 24808, 323, 7859, 37647, 45612, 30, 2435, 2103, 1514, 264, 12190, 3560, 304, 46620, 279, 3938, 10182, 323, 9282, 13, 1666, 37647, 45612, 3136, 311, 47376, 304, 279, 16975, 323, 279, 18435, 596, 3544, 8798, 8824, 38934, 709, 449, 7859, 20472, 11, 24808, 323, 1202, 6372, 690, 3719, 810, 38617, 13, 330, 55381, 54709, 11, 1778, 439, 279, 67992, 11, 374, 1093, 4092, 12248, 1359, 1071, 2009, 2234, 13, 330, 16179, 430, 12248, 374, 12190, 11, 279, 10182, 2077, 311, 16448, 32466, 315, 37647, 45612, 374, 264, 8450, 430, 28815, 927, 892, 13, 435, 87595, 1057, 9045, 389, 18189, 1646, 62646, 369, 420, 8450, 374, 98990, 11, 8104, 994, 3411, 311, 279, 3117, 3938, 1210, 46551, 279, 13112, 311, 902, 5933, 323, 9434, 9547, 7958, 7188, 61050, 8779, 12074, 2731, 66251, 553, 872, 41579, 13, 1115, 6677, 8779, 1646, 388, 10552, 3249, 872, 4211, 2643, 387, 7554, 279, 1906, 304, 1675, 15853, 3347, 13468, 18845, 13, 57116, 649, 1243, 19570, 810, 82891, 3135, 311, 1274, 9293, 7188, 596, 3090, 3938, 13, 220, 128257, 198 ]

2,191

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Anthropogenic atmospheric carbon dioxide (CO 2 ) is being absorbed by seawater resulting in increasingly acidic oceans, a process known as ocean acidification (OA). OA is thought to have largely deleterious effects on marine invertebrates, primarily impacting early life stages and consequently, their recruitment and species’ survival. Most research in this field has been limited to short-term, single-species and single-life stage studies, making it difficult to determine which taxa will be evolutionarily successful under OA conditions. We circumvent these limitations by relating the dominance and distribution of the known polychaete worm species living in a naturally acidic seawater vent system to their life history strategies. These data are coupled with breeding experiments, showing all dominant species in this natural system exhibit parental care. Our results provide evidence supporting the idea that long-term survival of marine species in acidic conditions is related to life history strategies where eggs are kept in protected maternal environments (brooders) or where larvae have no free swimming phases (direct developers). Our findings are the first to formally validate the hypothesis that species with life history strategies linked to parental care are more protected in an acidifying ocean compared to their relatives employing broadcast spawning and pelagic larval development. Introduction We focused on the unique coastal vent ecosystem of Ischia island (Italy), where underwater CO 2 volcanic emissions interact with a seagrass and rocky reef habitat 1 . CO 2 bubbling from the seafloor drives the seawater pH down to equal to or lower than business-as-usual IPCC projections for 2100 (pH 6.5–7.8 1 , 2 ), effectively creating a “chemical island” approximately 2,000 years old 3 . Our biological focus is on polychaete worms, as they are an abundant taxonomic group in the vents 1 . Their consistent vent-dominance and the trends seen in their seasonal abundances indicate the possibility of either multi- and/or transgenerational exposure 4 , 5 , 6 , 7 . Furthermore, the group exhibits highly diverse reproductive and developmental modes 8 . We related the type of early life history strategies employed by species living in the vents with their known distribution and abundances 1 , 5 , 6 . We found twelve of the total thirteen species with known reproductive characteristics colonizing high CO 2 vent areas to be brooding or direct developers (eggs kept in protected maternal environment/no free-swimming larval phases). Ten had higher abundances in the venting areas than in nearby ambient CO 2 areas ( Table 1 ). The exception was one species, morphologically appearing to be Platynereis dumerilii (Audouin & Milne-Edwards, 1834), the only broadcast spawning pelagic developer with higher abundances in the vents 5 , 7 , 9 . Table 1 Early life-history strategies of all polychaete species present in the lowest pH vent site. Full size table The observation that brooding polychaete species dominate the CO 2 vent areas, along with evidence for physiological and genetic adaptation in vent-inhabiting Platynereis dumerilii 6 , prompted further examination of this particular species. To determine whether these adaptations have led to reproductive isolation, we attempted to crossbreed Platynereis individuals collected from within the vent sites with those collected from control sites outside the vent sites, in the laboratory. A male from the control population in the initial stages of transforming into a pelagic, swimming reproductive P. dumerilii was introduced into a container with an immature adult Platynereis sp. from the vent population. Within two hours, the male prompted this vent-originating worm to develop large yellow eggs, likely a pheromone-induced response between the two sexes 10 . These eggs filled the female body cavity and were five times larger than the average P. dumerilii eggs. The female proceeded to build a complex tube structure consisting of inner microtubes where she deposited large, fertilized eggs that immediately stopped developing ( Fig. 1 ). Figure 1 a . Initial cross-breeding activity with (top) Platynereis dumerilii male transforming into a pelagic, swimming epitoke full of sperm and (below) the Platynereis massiliensis female developing large yellow yolky eggs, (250 μm in diameter); b . Female inside tube laying and moving 74 eggs into inner brood tubes after 12 h of pairing with the male; c . Close-up of inner-parental mucus tubes holding large yellow eggs. Scale: 0.5 mm. Full size image We matched the reproductive description of the female’s brooding behaviour to the parent’s genetic identities using a COI barcoding approach (Supplementary Methods). While the COI sequence of the pelagic form was only 0.7% different from the published sequence of P. dumerilii , the brooding form’s sequence was 26% different, indicating that it represents a separate species. Observational results confirm that the female found in the vents is actually Platynereis massiliensis (Moquin-Tandon, 1869), a sibling species of P. dumerilii 11 . These two sibling species are morphologically indistinguishable as immature adults but are easily discernible upon maturation, having evolved opposing reproduction modes with morphologically different gametes 11 , 12 . Platynereis massiliensis are protandric sequential hermaphrodites that first mature as males and fertilize a female partner’s eggs laid inside a brood tube. The female then dies and the male continues ventilating and protecting the developing embryos inside the tube as they develop into young worms 11 , after which the father changes sex and the process is repeated in the next reproductive event. Platynereis dumerilii have separate sexes and maturation invokes morphological changes allowing the benthic forms to leave their tubes and swarm in a single spawning event in the surface water. Adults swim to the surface, in synchronization with the full moon, in a pheromone-induced search for the opposite sex 11 , 13 . They then release their gametes and die. Fertilization occurs in the sea water and the larvae go through a subsequent six-week pelagic phase 10 . Our COI analysis provides the first genetic record for P. massiliensis , as well as a genetic template to match previously sequenced individuals from both inside and outside the venting areas to their correct species identity. We did this using published sequence data", "role": "user" }, { "content": "Marine organisms living in acidified waters exhibit a tendency to nurture their offspring to a greater extent than those in more regular conditions. Researchers at Plymouth University have found that polychaete worms located around volcanic vents in the Mediterranean grow and develop their eggs within the protection of the family unit - in contrast to closely-related species that release them into the water column to fend for themselves. The scientists say the findings could provide an important insight into how organisms might adjust to increasing levels of carbon dioxide in the sea - and the ramifications that might have for future biodiversity. Their report - published in Scientific Reports - was based on field research off the island of Ischia in Italy and lab-work in which the breeding patterns of the worms were observed at closer quarters. Noelle Lucey, a researcher within Plymouth University's Marine Institute, and of the University of Pavia, said: \"One of the most interesting annelid worms here typically grows to around 3cm in length and is found on the seafloor. It was previously thought that their breeding is triggered by a full moon, when they swim up to the surface and release - or 'broadcast' - their eggs. But our studies at the CO2 vents off Ischia have found something very different: those species living near the volcanic vents, in waters rich in carbon dioxide, seem to have adapted to the harsher conditions by brooding their offspring.\" The team found that 12 of the 13 species that had colonized the vent area exhibited brooding characteristics, most notably producing fewer and larger eggs that were usually retained within some form of protective sac. Ten of those species were in higher abundance around the vents than in the ambient areas surrounding them - some by a ratio as high as nine-to-one. The observation that brooding worms dominated the CO2 vent areas, and existing evidence of physiological and genetic adaptation in vent-inhabiting species, prompted the researchers to take immature adult Platynereis dumerilii specimens and attempt to cross breed them in the laboratory. A male - taken from the ambient control area - and a female - from the vent zone - almost immediately began to breed. But instead of the typical broadcast pattern, the eggs produced were five times larger than the average and were laid in a complex tube structure or brooding pouch. When genetic analysis was conducted, it became clear that worms from inside the CO2 vents were from a sibling species of Platynereis massiliensis, one that has diverged from Platynereis dumerilii in the recent past - confirming that all of the polychaete species are brooders of some sort. Dr Piero Calosi, from the University of Quebec in Rimouski, Canada, said: \"Our study confirms the idea that marine organisms have evolved brooding characteristics in response to environmental stresses, such as ocean acidification.\" On the breadth and importance of their study Dr Chiara Lombardi, from ENEA, Italy, said: \"Studies like ours can help substantially advance our predictive ability on the fate of marine biodiversity simply based on species characteristic, such as their reproductive strategy.\" Ms Lucey added: \"This study brings us one step closer to understanding which marine species will be more resilient to climate changes. In fact, our work helps in establishing a fundamental principle to be used to guide decisions on the conservation of marine ecosystems and to help better manage the fisheries and aquaculture industries.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Anthropogenic atmospheric carbon dioxide (CO 2 ) is being absorbed by seawater resulting in increasingly acidic oceans, a process known as ocean acidification (OA). OA is thought to have largely deleterious effects on marine invertebrates, primarily impacting early life stages and consequently, their recruitment and species’ survival. Most research in this field has been limited to short-term, single-species and single-life stage studies, making it difficult to determine which taxa will be evolutionarily successful under OA conditions. We circumvent these limitations by relating the dominance and distribution of the known polychaete worm species living in a naturally acidic seawater vent system to their life history strategies. These data are coupled with breeding experiments, showing all dominant species in this natural system exhibit parental care. Our results provide evidence supporting the idea that long-term survival of marine species in acidic conditions is related to life history strategies where eggs are kept in protected maternal environments (brooders) or where larvae have no free swimming phases (direct developers). Our findings are the first to formally validate the hypothesis that species with life history strategies linked to parental care are more protected in an acidifying ocean compared to their relatives employing broadcast spawning and pelagic larval development. Introduction We focused on the unique coastal vent ecosystem of Ischia island (Italy), where underwater CO 2 volcanic emissions interact with a seagrass and rocky reef habitat 1 . CO 2 bubbling from the seafloor drives the seawater pH down to equal to or lower than business-as-usual IPCC projections for 2100 (pH 6.5–7.8 1 , 2 ), effectively creating a “chemical island” approximately 2,000 years old 3 . Our biological focus is on polychaete worms, as they are an abundant taxonomic group in the vents 1 . Their consistent vent-dominance and the trends seen in their seasonal abundances indicate the possibility of either multi- and/or transgenerational exposure 4 , 5 , 6 , 7 . Furthermore, the group exhibits highly diverse reproductive and developmental modes 8 . We related the type of early life history strategies employed by species living in the vents with their known distribution and abundances 1 , 5 , 6 . We found twelve of the total thirteen species with known reproductive characteristics colonizing high CO 2 vent areas to be brooding or direct developers (eggs kept in protected maternal environment/no free-swimming larval phases). Ten had higher abundances in the venting areas than in nearby ambient CO 2 areas ( Table 1 ). The exception was one species, morphologically appearing to be Platynereis dumerilii (Audouin & Milne-Edwards, 1834), the only broadcast spawning pelagic developer with higher abundances in the vents 5 , 7 , 9 . Table 1 Early life-history strategies of all polychaete species present in the lowest pH vent site. Full size table The observation that brooding polychaete species dominate the CO 2 vent areas, along with evidence for physiological and genetic adaptation in vent-inhabiting Platynereis dumerilii 6 , prompted further examination of this particular species. To determine whether these adaptations have led to reproductive isolation, we attempted to crossbreed Platynereis individuals collected from within the vent sites with those collected from control sites outside the vent sites, in the laboratory. A male from the control population in the initial stages of transforming into a pelagic, swimming reproductive P. dumerilii was introduced into a container with an immature adult Platynereis sp. from the vent population. Within two hours, the male prompted this vent-originating worm to develop large yellow eggs, likely a pheromone-induced response between the two sexes 10 . These eggs filled the female body cavity and were five times larger than the average P. dumerilii eggs. The female proceeded to build a complex tube structure consisting of inner microtubes where she deposited large, fertilized eggs that immediately stopped developing ( Fig. 1 ). Figure 1 a . Initial cross-breeding activity with (top) Platynereis dumerilii male transforming into a pelagic, swimming epitoke full of sperm and (below) the Platynereis massiliensis female developing large yellow yolky eggs, (250 μm in diameter); b . Female inside tube laying and moving 74 eggs into inner brood tubes after 12 h of pairing with the male; c . Close-up of inner-parental mucus tubes holding large yellow eggs. Scale: 0.5 mm. Full size image We matched the reproductive description of the female’s brooding behaviour to the parent’s genetic identities using a COI barcoding approach (Supplementary Methods). While the COI sequence of the pelagic form was only 0.7% different from the published sequence of P. dumerilii , the brooding form’s sequence was 26% different, indicating that it represents a separate species. Observational results confirm that the female found in the vents is actually Platynereis massiliensis (Moquin-Tandon, 1869), a sibling species of P. dumerilii 11 . These two sibling species are morphologically indistinguishable as immature adults but are easily discernible upon maturation, having evolved opposing reproduction modes with morphologically different gametes 11 , 12 . Platynereis massiliensis are protandric sequential hermaphrodites that first mature as males and fertilize a female partner’s eggs laid inside a brood tube. The female then dies and the male continues ventilating and protecting the developing embryos inside the tube as they develop into young worms 11 , after which the father changes sex and the process is repeated in the next reproductive event. Platynereis dumerilii have separate sexes and maturation invokes morphological changes allowing the benthic forms to leave their tubes and swarm in a single spawning event in the surface water. Adults swim to the surface, in synchronization with the full moon, in a pheromone-induced search for the opposite sex 11 , 13 . They then release their gametes and die. Fertilization occurs in the sea water and the larvae go through a subsequent six-week pelagic phase 10 . Our COI analysis provides the first genetic record for P. massiliensis , as well as a genetic template to match previously sequenced individuals from both inside and outside the venting areas to their correct species identity. We did this using published sequence data<|im_end|> <|im_start|>assistant Marine organisms living in acidified waters exhibit a tendency to nurture their offspring to a greater extent than those in more regular conditions. Researchers at Plymouth University have found that polychaete worms located around volcanic vents in the Mediterranean grow and develop their eggs within the protection of the family unit - in contrast to closely-related species that release them into the water column to fend for themselves. The scientists say the findings could provide an important insight into how organisms might adjust to increasing levels of carbon dioxide in the sea - and the ramifications that might have for future biodiversity. Their report - published in Scientific Reports - was based on field research off the island of Ischia in Italy and lab-work in which the breeding patterns of the worms were observed at closer quarters. Noelle Lucey, a researcher within Plymouth University's Marine Institute, and of the University of Pavia, said: "One of the most interesting annelid worms here typically grows to around 3cm in length and is found on the seafloor. It was previously thought that their breeding is triggered by a full moon, when they swim up to the surface and release - or 'broadcast' - their eggs. But our studies at the CO2 vents off Ischia have found something very different: those species living near the volcanic vents, in waters rich in carbon dioxide, seem to have adapted to the harsher conditions by brooding their offspring." The team found that 12 of the 13 species that had colonized the vent area exhibited brooding characteristics, most notably producing fewer and larger eggs that were usually retained within some form of protective sac. Ten of those species were in higher abundance around the vents than in the ambient areas surrounding them - some by a ratio as high as nine-to-one. The observation that brooding worms dominated the CO2 vent areas, and existing evidence of physiological and genetic adaptation in vent-inhabiting species, prompted the researchers to take immature adult Platynereis dumerilii specimens and attempt to cross breed them in the laboratory. A male - taken from the ambient control area - and a female - from the vent zone - almost immediately began to breed. But instead of the typical broadcast pattern, the eggs produced were five times larger than the average and were laid in a complex tube structure or brooding pouch. When genetic analysis was conducted, it became clear that worms from inside the CO2 vents were from a sibling species of Platynereis massiliensis, one that has diverged from Platynereis dumerilii in the recent past - confirming that all of the polychaete species are brooders of some sort. Dr Piero Calosi, from the University of Quebec in Rimouski, Canada, said: "Our study confirms the idea that marine organisms have evolved brooding characteristics in response to environmental stresses, such as ocean acidification." On the breadth and importance of their study Dr Chiara Lombardi, from ENEA, Italy, said: "Studies like ours can help substantially advance our predictive ability on the fate of marine biodiversity simply based on species characteristic, such as their reproductive strategy." Ms Lucey added: "This study brings us one step closer to understanding which marine species will be more resilient to climate changes. In fact, our work helps in establishing a fundamental principle to be used to guide decisions on the conservation of marine ecosystems and to help better manage the fisheries and aquaculture industries." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 70384, 29569, 45475, 12782, 40589, 320, 8445, 220, 17, 883, 374, 1694, 42101, 555, 67329, 977, 13239, 304, 15098, 84903, 54280, 11, 264, 1920, 3967, 439, 18435, 13935, 2461, 320, 42439, 570, 81542, 374, 3463, 311, 617, 14090, 60393, 466, 1245, 6372, 389, 29691, 304, 65932, 99868, 11, 15871, 74055, 4216, 2324, 18094, 323, 52394, 11, 872, 34102, 323, 9606, 529, 20237, 13, 7648, 3495, 304, 420, 2115, 706, 1027, 7347, 311, 2875, 9860, 11, 3254, 58894, 552, 323, 3254, 26928, 6566, 7978, 11, 3339, 433, 5107, 311, 8417, 902, 77314, 690, 387, 15740, 6751, 6992, 1234, 81542, 4787, 13, 1226, 10408, 688, 1521, 9669, 555, 23343, 279, 44592, 323, 8141, 315, 279, 3967, 1499, 5759, 64, 7870, 35311, 9606, 5496, 304, 264, 18182, 84903, 67329, 977, 10594, 1887, 311, 872, 2324, 3925, 15174, 13, 4314, 828, 527, 34356, 449, 40308, 21896, 11, 9204, 682, 25462, 9606, 304, 420, 5933, 1887, 31324, 46679, 2512, 13, 5751, 3135, 3493, 6029, 12899, 279, 4623, 430, 1317, 9860, 20237, 315, 29691, 9606, 304, 84903, 4787, 374, 5552, 311, 2324, 3925, 15174, 1405, 19335, 527, 8774, 304, 2682, 50150, 22484, 320, 15222, 53598, 8, 477, 1405, 83861, 617, 912, 1949, 24269, 35530, 320, 20384, 13707, 570, 5751, 14955, 527, 279, 1176, 311, 37402, 9788, 279, 31178, 430, 9606, 449, 2324, 3925, 15174, 10815, 311, 46679, 2512, 527, 810, 2682, 304, 459, 13935, 7922, 18435, 7863, 311, 872, 29658, 51297, 13195, 79529, 323, 12077, 13070, 45555, 838, 4500, 13, 29438, 1226, 10968, 389, 279, 5016, 35335, 10594, 26031, 315, 2209, 90646, 13218, 320, 71603, 705, 1405, 46474, 7432, 220, 17, 67164, 20748, 16681, 449, 264, 513, 69405, 395, 323, 56617, 71145, 39646, 220, 16, 662, 7432, 220, 17, 78869, 9894, 505, 279, 513, 2642, 4081, 20722, 279, 67329, 977, 37143, 1523, 311, 6273, 311, 477, 4827, 1109, 2626, 33534, 26766, 940, 95661, 41579, 369, 220, 8848, 15, 320, 79, 39, 220, 21, 13, 20, 4235, 22, 13, 23, 220, 16, 1174, 220, 17, 7026, 13750, 6968, 264, 1054, 32056, 13218, 863, 13489, 220, 17, 11, 931, 1667, 2362, 220, 18, 662, 5751, 24156, 5357, 374, 389, 1499, 5759, 64, 7870, 63000, 11, 439, 814, 527, 459, 44611, 3827, 48228, 1912, 304, 279, 81307, 220, 16, 662, 11205, 13263, 10594, 1773, 8129, 685, 323, 279, 18845, 3970, 304, 872, 36899, 23325, 3095, 13519, 279, 13336, 315, 3060, 7447, 12, 323, 5255, 1380, 7642, 1697, 14675, 220, 19, 1174, 220, 20, 1174, 220, 21, 1174, 220, 22, 662, 24296, 11, 279, 1912, 50829, 7701, 17226, 42889, 323, 48006, 20362, 220, 23, 662, 1226, 5552, 279, 955, 315, 4216, 2324, 3925, 15174, 20011, 555, 9606, 5496, 304, 279, 81307, 449, 872, 3967, 8141, 323, 23325, 3095, 220, 16, 1174, 220, 20, 1174, 220, 21, 662, 1226, 1766, 30335, 315, 279, 2860, 61759, 9606, 449, 3967, 42889, 17910, 15235, 4954, 1579, 7432, 220, 17, 10594, 5789, 311, 387, 2967, 3785, 477, 2167, 13707, 320, 797, 5981, 8774, 304, 2682, 50150, 4676, 34200, 1949, 62979, 41133, 45555, 838, 35530, 570, 18165, 1047, 5190, 23325, 3095, 304, 279, 10594, 287, 5789, 1109, 304, 14373, 35288, 7432, 220, 17, 5789, 320, 6771, 220, 16, 7609, 578, 4788, 574, 832, 9606, 11, 27448, 30450, 26449, 311, 387, 87742, 1910, 486, 285, 294, 3471, 321, 3893, 320, 54049, 283, 258, 612, 10357, 818, 12, 2782, 4102, 11, 220, 10750, 19, 705, 279, 1193, 13195, 79529, 12077, 13070, 16131, 449, 5190, 23325, 3095, 304, 279, 81307, 220, 20, 1174, 220, 22, 1174, 220, 24, 662, 6771, 220, 16, 23591, 2324, 62474, 15174, 315, 682, 1499, 5759, 64, 7870, 9606, 3118, 304, 279, 15821, 37143, 10594, 2816, 13, 8797, 1404, 2007, 578, 22695, 430, 2967, 3785, 1499, 5759, 64, 7870, 9606, 41836, 279, 7432, 220, 17, 10594, 5789, 11, 3235, 449, 6029, 369, 53194, 323, 19465, 34185, 304, 10594, 3502, 10796, 5977, 87742, 1910, 486, 285, 294, 3471, 321, 3893, 220, 21, 1174, 29746, 4726, 24481, 315, 420, 4040, 9606, 13, 2057, 8417, 3508, 1521, 77765, 617, 6197, 311, 42889, 31398, 11, 584, 17644, 311, 5425, 21152, 291, 87742, 1910, 486, 285, 7931, 14890, 505, 2949, 279, 10594, 6732, 449, 1884, 14890, 505, 2585, 6732, 4994, 279, 10594, 6732, 11, 304, 279, 27692, 13, 362, 8762, 505, 279, 2585, 7187, 304, 279, 2926, 18094, 315, 46890, 1139, 264, 12077, 13070, 11, 24269, 42889, 393, 13, 294, 3471, 321, 3893, 574, 11784, 1139, 264, 5593, 449, 459, 86525, 6822, 87742, 1910, 486, 285, 993, 13, 505, 279, 10594, 7187, 13, 25218, 1403, 4207, 11, 279, 8762, 29746, 420, 10594, 67903, 1113, 35311, 311, 2274, 3544, 14071, 19335, 11, 4461, 264, 1343, 261, 316, 606, 38973, 2077, 1990, 279, 1403, 76032, 220, 605, 662, 4314, 19335, 10409, 279, 8954, 2547, 56429, 323, 1051, 4330, 3115, 8294, 1109, 279, 5578, 393, 13, 294, 3471, 321, 3893, 19335, 13, 578, 8954, 45374, 311, 1977, 264, 6485, 14019, 6070, 31706, 315, 9358, 8162, 83, 51725, 1405, 1364, 54568, 3544, 11, 36214, 1534, 19335, 430, 7214, 10717, 11469, 320, 23966, 13, 220, 16, 7609, 19575, 220, 16, 264, 662, 4220, 5425, 93008, 16490, 5820, 449, 320, 3565, 8, 87742, 1910, 486, 285, 294, 3471, 321, 3893, 8762, 46890, 1139, 264, 12077, 13070, 11, 24269, 67422, 4845, 2539, 315, 40699, 323, 320, 54277, 8, 279, 87742, 1910, 486, 285, 3148, 4008, 87778, 8954, 11469, 3544, 14071, 94582, 8050, 19335, 11, 320, 5154, 33983, 76, 304, 23899, 1237, 293, 662, 29738, 4871, 14019, 35744, 323, 7366, 220, 5728, 19335, 1139, 9358, 2967, 347, 34083, 1306, 220, 717, 305, 315, 48813, 449, 279, 8762, 26, 272, 662, 13330, 5352, 315, 9358, 47536, 278, 296, 38601, 34083, 10168, 3544, 14071, 19335, 13, 25635, 25, 220, 15, 13, 20, 9653, 13, 8797, 1404, 2217, 1226, 18545, 279, 42889, 4096, 315, 279, 8954, 753, 2967, 3785, 17432, 311, 279, 2748, 753, 19465, 40521, 1701, 264, 7432, 40, 3703, 49467, 5603, 320, 10254, 67082, 19331, 570, 6104, 279, 7432, 40, 8668, 315, 279, 12077, 13070, 1376, 574, 1193, 220, 15, 13, 22, 4, 2204, 505, 279, 4756, 8668, 315, 393, 13, 294, 3471, 321, 3893, 1174, 279, 2967, 3785, 1376, 753, 8668, 574, 220, 1627, 4, 2204, 11, 19392, 430, 433, 11105, 264, 8821, 9606, 13, 31943, 1697, 3135, 7838, 430, 279, 8954, 1766, 304, 279, 81307, 374, 3604, 87742, 1910, 486, 285, 3148, 4008, 87778, 320, 26694, 36444, 9469, 11283, 11, 220, 9714, 24, 705, 264, 45323, 9606, 315, 393, 13, 294, 3471, 321, 3893, 220, 806, 662, 4314, 1403, 45323, 9606, 527, 27448, 30450, 1280, 89747, 481, 439, 86525, 12884, 719, 527, 6847, 42645, 1260, 5304, 5634, 2060, 11, 3515, 28995, 31322, 39656, 20362, 449, 27448, 30450, 2204, 9192, 96281, 220, 806, 1174, 220, 717, 662, 87742, 1910, 486, 285, 3148, 4008, 87778, 527, 1760, 438, 2265, 52100, 1077, 76, 1366, 24409, 3695, 430, 1176, 15196, 439, 25000, 323, 36214, 553, 264, 8954, 8427, 753, 19335, 17551, 4871, 264, 2967, 347, 14019, 13, 578, 8954, 1243, 8898, 323, 279, 8762, 9731, 71702, 1113, 323, 22973, 279, 11469, 89873, 4871, 279, 14019, 439, 814, 2274, 1139, 3995, 63000, 220, 806, 1174, 1306, 902, 279, 7126, 4442, 1877, 323, 279, 1920, 374, 11763, 304, 279, 1828, 42889, 1567, 13, 87742, 1910, 486, 285, 294, 3471, 321, 3893, 617, 8821, 76032, 323, 5634, 2060, 67151, 27448, 5848, 4442, 10923, 279, 293, 21341, 292, 7739, 311, 5387, 872, 34083, 323, 61941, 304, 264, 3254, 79529, 1567, 304, 279, 7479, 3090, 13, 58338, 16587, 311, 279, 7479, 11, 304, 59012, 449, 279, 2539, 18266, 11, 304, 264, 1343, 261, 316, 606, 38973, 2778, 369, 279, 14329, 1877, 220, 806, 1174, 220, 1032, 662, 2435, 1243, 4984, 872, 9192, 96281, 323, 2815, 13, 435, 86795, 2065, 13980, 304, 279, 9581, 3090, 323, 279, 83861, 733, 1555, 264, 17876, 4848, 30609, 12077, 13070, 10474, 220, 605, 662, 5751, 7432, 40, 6492, 5825, 279, 1176, 19465, 3335, 369, 393, 13, 3148, 4008, 87778, 1174, 439, 1664, 439, 264, 19465, 3896, 311, 2489, 8767, 11506, 5886, 7931, 505, 2225, 4871, 323, 4994, 279, 10594, 287, 5789, 311, 872, 4495, 9606, 9764, 13, 1226, 1550, 420, 1701, 4756, 8668, 828, 128257, 198, 128256, 78191, 198, 12331, 483, 44304, 5496, 304, 13935, 1908, 21160, 31324, 264, 31954, 311, 79530, 872, 46471, 311, 264, 7191, 13112, 1109, 1884, 304, 810, 5912, 4787, 13, 59250, 520, 72098, 3907, 617, 1766, 430, 1499, 5759, 64, 7870, 63000, 7559, 2212, 67164, 81307, 304, 279, 38785, 3139, 323, 2274, 872, 19335, 2949, 279, 9313, 315, 279, 3070, 5089, 482, 304, 13168, 311, 15499, 14228, 9606, 430, 4984, 1124, 1139, 279, 3090, 3330, 311, 95127, 369, 5694, 13, 578, 14248, 2019, 279, 14955, 1436, 3493, 459, 3062, 20616, 1139, 1268, 44304, 2643, 7652, 311, 7859, 5990, 315, 12782, 40589, 304, 279, 9581, 482, 323, 279, 85450, 430, 2643, 617, 369, 3938, 73119, 13, 11205, 1934, 482, 4756, 304, 38130, 29140, 482, 574, 3196, 389, 2115, 3495, 1022, 279, 13218, 315, 2209, 90646, 304, 15704, 323, 10278, 29721, 304, 902, 279, 40308, 12912, 315, 279, 63000, 1051, 13468, 520, 12401, 32573, 13, 2360, 6853, 445, 10743, 88, 11, 264, 32185, 2949, 72098, 3907, 596, 23820, 10181, 11, 323, 315, 279, 3907, 315, 393, 35102, 11, 1071, 25, 330, 4054, 315, 279, 1455, 7185, 3008, 301, 307, 63000, 1618, 11383, 28815, 311, 2212, 220, 18, 6358, 304, 3160, 323, 374, 1766, 389, 279, 513, 2642, 4081, 13, 1102, 574, 8767, 3463, 430, 872, 40308, 374, 22900, 555, 264, 2539, 18266, 11, 994, 814, 16587, 709, 311, 279, 7479, 323, 4984, 482, 477, 364, 55262, 6, 482, 872, 19335, 13, 2030, 1057, 7978, 520, 279, 7432, 17, 81307, 1022, 2209, 90646, 617, 1766, 2555, 1633, 2204, 25, 1884, 9606, 5496, 3221, 279, 67164, 81307, 11, 304, 21160, 9257, 304, 12782, 40589, 11, 2873, 311, 617, 30464, 311, 279, 25984, 261, 4787, 555, 2967, 3785, 872, 46471, 1210, 578, 2128, 1766, 430, 220, 717, 315, 279, 220, 1032, 9606, 430, 1047, 15235, 1534, 279, 10594, 3158, 51713, 2967, 3785, 17910, 11, 1455, 35146, 17843, 17162, 323, 8294, 19335, 430, 1051, 6118, 35363, 2949, 1063, 1376, 315, 29219, 11347, 13, 18165, 315, 1884, 9606, 1051, 304, 5190, 37492, 2212, 279, 81307, 1109, 304, 279, 35288, 5789, 14932, 1124, 482, 1063, 555, 264, 11595, 439, 1579, 439, 11888, 4791, 19101, 13, 578, 22695, 430, 2967, 3785, 63000, 30801, 279, 7432, 17, 10594, 5789, 11, 323, 6484, 6029, 315, 53194, 323, 19465, 34185, 304, 10594, 3502, 10796, 5977, 9606, 11, 29746, 279, 12074, 311, 1935, 86525, 6822, 87742, 1910, 486, 285, 294, 3471, 321, 3893, 57749, 323, 4879, 311, 5425, 28875, 1124, 304, 279, 27692, 13, 362, 8762, 482, 4529, 505, 279, 35288, 2585, 3158, 482, 323, 264, 8954, 482, 505, 279, 10594, 10353, 482, 4661, 7214, 6137, 311, 28875, 13, 2030, 4619, 315, 279, 14595, 13195, 5497, 11, 279, 19335, 9124, 1051, 4330, 3115, 8294, 1109, 279, 5578, 323, 1051, 17551, 304, 264, 6485, 14019, 6070, 477, 2967, 3785, 56952, 13, 3277, 19465, 6492, 574, 13375, 11, 433, 6244, 2867, 430, 63000, 505, 4871, 279, 7432, 17, 81307, 1051, 505, 264, 45323, 9606, 315, 87742, 1910, 486, 285, 3148, 4008, 87778, 11, 832, 430, 706, 37441, 3640, 505, 87742, 1910, 486, 285, 294, 3471, 321, 3893, 304, 279, 3293, 3347, 482, 50096, 430, 682, 315, 279, 1499, 5759, 64, 7870, 9606, 527, 2967, 53598, 315, 1063, 3460, 13, 2999, 21377, 78, 3400, 31824, 11, 505, 279, 3907, 315, 35195, 304, 52479, 788, 6780, 11, 7008, 11, 1071, 25, 330, 8140, 4007, 43496, 279, 4623, 430, 29691, 44304, 617, 28995, 2967, 3785, 17910, 304, 2077, 311, 12434, 59623, 11, 1778, 439, 18435, 13935, 2461, 1210, 1952, 279, 58321, 323, 12939, 315, 872, 4007, 2999, 34382, 5169, 63918, 37489, 11, 505, 469, 4031, 32, 11, 15704, 11, 1071, 25, 330, 94607, 1093, 11604, 649, 1520, 32302, 12178, 1057, 60336, 5845, 389, 279, 25382, 315, 29691, 73119, 5042, 3196, 389, 9606, 29683, 11, 1778, 439, 872, 42889, 8446, 1210, 16450, 445, 10743, 88, 3779, 25, 330, 2028, 4007, 12716, 603, 832, 3094, 12401, 311, 8830, 902, 29691, 9606, 690, 387, 810, 59780, 311, 10182, 4442, 13, 763, 2144, 11, 1057, 990, 8779, 304, 31692, 264, 16188, 17966, 311, 387, 1511, 311, 8641, 11429, 389, 279, 29711, 315, 29691, 61951, 323, 311, 1520, 2731, 10299, 279, 82596, 323, 15715, 582, 10745, 19647, 1210, 220, 128257, 198 ]

2,076

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The tumor-forming disease fibropapillomatosis (FP) has afflicted sea turtle populations for decades with no clear cause. A lineage of α -herpesviruses associated with these tumors has existed for millennia, suggesting environmental factors are responsible for its recent epidemiology. In previous work, we described how herpesviruses could cause FP tumors through a metabolic influx of arginine. We demonstrated the disease prevails in chronically eutrophied coastal waters, and that turtles foraging in these sites might consume arginine-enriched macroalgae. Here, we test the idea using High-Performance Liquid Chromatography (HPLC) to describe the amino acid profiles of green turtle ( Chelonia mydas ) tumors and five common forage species of macroalgae from a range of eutrophic states. Tumors were notably elevated in glycine, proline, alanine, arginine, and serine and depleted in lysine when compared to baseline samples. All macroalgae from eutrophic locations had elevated arginine, and all species preferentially stored environmental nitrogen as arginine even at oligotrophic sites. From these results, we estimate adult turtles foraging at eutrophied sites increase their arginine intake 17–26 g daily, up to 14 times the background level. Arginine nitrogen increased with total macroalgae nitrogen and watershed nitrogen, and the invasive rhodophyte Hypnea musciformis significantly outperformed all other species in this respect. Our results confirm that eutrophication substantially increases the arginine content of macroalgae, which may metabolically promote latent herpesviruses and cause FP tumors in green turtles. Cite this as Van Houtan KS, Smith CM, Dailer ML, Kawachi M. 2014 . Eutrophication and the dietary promotion of sea turtle tumors . PeerJ 2 : e602 Main article text Introduction Fibropapillomatosis (FP) is a chronic and often lethal tumor-forming disease in sea turtles ( Fig. 1A ). It became a panzootic in green turtles in the 1980s, prompting concern that it was a serious threat to their global conservation ( Chaloupka et al., 2008 ; Herbst, 1994 ). Though most green turtle population indices have increased steadily since ( Seminoff et al., 2014 ), the disease remains prevalent and in several locations its incidence is still increasing ( Van Houtan, Hargrove & Balazs, 2010 ). Advances in understanding the cause of FP have recently centered on environmental factors, with diverse lines of evidence from genomics to epidemiology supporting this hypothesis ( Aguirre & Lutz, 2004 ; dos Santos et al., 2010 ; Ene et al., 2005 ; Herbst et al., 2004 ; Van Houtan, Hargrove & Balazs, 2010 ). The ecological promotion of the disease is made further interesting as FP tumors have a proposed viral origin. Figure 1: (A) Juvenile green turtle ( Chelonia mydas ) severely afflicted with fibropapillomatosis, a tumor-forming disease associated with α -herpesviruses. Photo: August 2012 Makena, Maui (credit: Chris Stankis, Flickr/Bluewavechris). (B) Amino acid profiles from turtle tissues show fibropapilloma tumors are notably enriched in glycine, proline and arginine, and depleted in lysine. Glycine is a known tumor biomarker; proline aids herpesvirus infections; and arginine and lysine promote and inhibit herpesviruses, respectively. Bars represent the average difference between tumor and baseline tissue for 12 individual turtles, percent changes from baseline percent total protein listed in parentheses, error bars are SEM. Bar color indicates P values from two-tailed paired t -tests. (C) Underlying histograms for arginine content in baseline and tumor tissue samples, bars are raw values, curves are smoothed trend. Download full-size image DOI: 10.7717/peerj.602/fig-1 Early studies discovered DNA from α -herpesviruses in FP tumors, but found adjacent tissues from diseased turtles, as well as samples from clinically healthy turtles, to be free of herpes DNA ( Lackovich et al., 1999 ; Lu et al., 2000 ; Quackenbush et al., 1998 ). Though further progress has been limited by an inability to develop viral cultures, recent work with next generation genomic techniques have made important contributions. These studies ( Alfaro-Núñez & Gilbert, 2014 ; Page-Karjian et al., 2012 ) found herpesvirus DNA to be rather ubiquitous—occurring in all hard-shelled sea turtles, in all populations tested, and even prevalent in clinically healthy turtles. If α -herpesviruses are the origin of FP, this represents a classic herpesvirus scenario where infections are pervasive, but latent or subclinical, in the host population ( Stevens & Cook, 1971 ; Umbach et al., 2008 ) and revealing of its etymology from the Greek ε ρπης , meaning “to creep”. With this in mind, we recently described the epidemiological link between this disease and coastal eutrophication, detailing how green turtles could literally be eating themselves sick ( Hall et al., 2007 ), activating latent herpes infections and promoting tumors by foraging on arginine-enriched macroalgae. A model built on this hypothesis ( Van Houtan, Hargrove & Balazs, 2010 ) explained 72% of the spatial variability of the disease across the Hawaiian Islands while offering a detailed explanation of the disease that connects turtle ecology, plant physiology (e.g., Raven & Taylor, 2003 ), and herpes biology to known management problems of nutrient pollution and invasive species. At the forefront, this proposed pathway focuses on the role arginine might have in promoting FP tumors. A significant body of evidence supports this. In many chronic diseases, arginine is implicated in cell inflammation and immune dysfunction ( Peranzoni et al., 2008 ) and in promoting viral tumors ( Mannick et al., 1994 ). But arginine is specifically important for herpesviruses. Laboratory studies demonstrate that herpes infections require arginine, being stunted in its absence ( Inglis, 1968 ; Mikami, Onuma & Hayashi, 1974 ; Olshevsky & Becker, 1970 ) and diminished when it is deprived ( Mistry et al., 2001 ). Subsequent research revealed that arginine is a principal component of glycoproteins in the outer viral envelope of herpesviruses. These glycoproteins are conserved across a wide variety of herpesviruses ( Alfaro-Núñez, 2014 ) and are critical to the herpes life cycle as they facilitate localization, fusion, and entrance to host cell nuclei ( Hibbard & Sandri-Goldin, 1995 ; Klyachkin & Geraghty, 2008 ). Beyond its significance for herpesviruses, arginine is an emerging focus of human cancer treatments as well. Cancer tumors lacking enzymes that synthesize arginine", "role": "user" }, { "content": "Hawai'i's sea turtles are afflicted with chronic and often lethal tumors caused by consuming non-native algae \"superweeds\" along coastlines where nutrient pollution is unchecked. The disease that causes these tumors is considered the leading cause of death in endangered green sea turtles. The new research was just published in the scientific journal PeerJ. Turtles that graze on blooms of invasive seaweeds end up with a diet that is rich in a particular amino acid, arginine, which promotes the virus that creates the tumors. Scientists at the University of Hawai'i at Mānoa and their NOAA colleague estimate that adult turtles foraging at high-nutrient grazing sites increase their arginine intake 17–26 g daily, up to 14 times the background level. \"For years, local ocean lovers have known that our green turtles have had awful tumors on their heads, eyes and front flippers,\" said UH Mānoa Marine Biology Professor Celia Smith, who worked with Kyle S. Van Houton of NOAA's Turtle Research Program on this study. \"Many hypotheses were offered to explain the tumors, but we kept coming back to the observation that urban reefs—those near dense populations—are the sites with greater numbers of sick turtles. We had no mechanism for this disease.\" More than 60 percent of turtles in Kāne'ohe Bay have been observed to bear tumors. Kihei, Maui, has been called a \"ground zero\" for fibropapillomatosis, the disease that is caused by a herpes virus and manifests as tumors in turtles. Humans appear unaffected by the disease. Van Houtan and colleagues previously described an epidemiological link between tumors and coastal eutrophication, that is, the enrichment of coastal waters with nutrients from land-based sources of pollution such as wastewater or agricultural fertilizers. This new study analyzed the actual tissues from tumored green turtles and the amounts of arginine in the dominant algae forage species from across Hawai'i. The analysis revealed remarkably high levels of arginine in tissues of invasive seaweeds harvested under nutrient-rich conditions, such as those affected by nitrogen from land-based pollution. These are the same conditions that promote algal blooms. The non-native algae \"superweeds\" grow so quickly when fertilized that some can double their weight in a period of two days. When found on typical healthy reefs with low nutrient inputs, the same invasive algae species had lower levels of amino acids, even though arginine levels were still elevated. A native algae species and favorite food of the green sea turtle called Pterocladiella capillacea did not synthesize anomalously high levels of arginine under low nitrogen conditions. \"I've never had a research project where so many different tools have been used to evaluate a hypothesis and, in every case, the same complex answer is returned: excess nutrients in coastal waters drive blooms of specific invasive algae,\" Smith said. \"These weeds then grow rapidly, dominate shallow water ecosystems, and store high levels of arginine in their tissues that trigger tumor growth for the grazing turtle population. Few could have imagined that an algal bloom could have such consequences up the food chain.\" Smith and her colleagues, including UH Mānoa's Meghan L. Dailer and Migiwa S. Kawachi, note that eutrophication of coastal waters goes beyond its influence on green turtle populations. Eutrophication is also associated with coral reef declines. \"The native species we have as our limu, fish and corals evolved for millions of years in low nutrient environments,\" Smith said. \"Any added nitrogen that enters our tropical coasts begins to alter the fundamental competition among species. With too much nutrient input, as we have seen on Maui, new dynamics of fast growth by non-native superweeds occurs. These weeds take over our reefs, and we tend to lose our native species.\" The biggest losers might be the gentle sea turtles, who are not looking beyond their next algae snack. \"The honu, or green turtles, have a special status in Hawai'i—culturally and federally,\" Smith said. \"But to prevent them from consuming superweeds that promote these tumors—their greatest known source of mortality, we need to manage aggressively all land-based sources nutrient pollution and to restore the turtle's native diet.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The tumor-forming disease fibropapillomatosis (FP) has afflicted sea turtle populations for decades with no clear cause. A lineage of α -herpesviruses associated with these tumors has existed for millennia, suggesting environmental factors are responsible for its recent epidemiology. In previous work, we described how herpesviruses could cause FP tumors through a metabolic influx of arginine. We demonstrated the disease prevails in chronically eutrophied coastal waters, and that turtles foraging in these sites might consume arginine-enriched macroalgae. Here, we test the idea using High-Performance Liquid Chromatography (HPLC) to describe the amino acid profiles of green turtle ( Chelonia mydas ) tumors and five common forage species of macroalgae from a range of eutrophic states. Tumors were notably elevated in glycine, proline, alanine, arginine, and serine and depleted in lysine when compared to baseline samples. All macroalgae from eutrophic locations had elevated arginine, and all species preferentially stored environmental nitrogen as arginine even at oligotrophic sites. From these results, we estimate adult turtles foraging at eutrophied sites increase their arginine intake 17–26 g daily, up to 14 times the background level. Arginine nitrogen increased with total macroalgae nitrogen and watershed nitrogen, and the invasive rhodophyte Hypnea musciformis significantly outperformed all other species in this respect. Our results confirm that eutrophication substantially increases the arginine content of macroalgae, which may metabolically promote latent herpesviruses and cause FP tumors in green turtles. Cite this as Van Houtan KS, Smith CM, Dailer ML, Kawachi M. 2014 . Eutrophication and the dietary promotion of sea turtle tumors . PeerJ 2 : e602 Main article text Introduction Fibropapillomatosis (FP) is a chronic and often lethal tumor-forming disease in sea turtles ( Fig. 1A ). It became a panzootic in green turtles in the 1980s, prompting concern that it was a serious threat to their global conservation ( Chaloupka et al., 2008 ; Herbst, 1994 ). Though most green turtle population indices have increased steadily since ( Seminoff et al., 2014 ), the disease remains prevalent and in several locations its incidence is still increasing ( Van Houtan, Hargrove & Balazs, 2010 ). Advances in understanding the cause of FP have recently centered on environmental factors, with diverse lines of evidence from genomics to epidemiology supporting this hypothesis ( Aguirre & Lutz, 2004 ; dos Santos et al., 2010 ; Ene et al., 2005 ; Herbst et al., 2004 ; Van Houtan, Hargrove & Balazs, 2010 ). The ecological promotion of the disease is made further interesting as FP tumors have a proposed viral origin. Figure 1: (A) Juvenile green turtle ( Chelonia mydas ) severely afflicted with fibropapillomatosis, a tumor-forming disease associated with α -herpesviruses. Photo: August 2012 Makena, Maui (credit: Chris Stankis, Flickr/Bluewavechris). (B) Amino acid profiles from turtle tissues show fibropapilloma tumors are notably enriched in glycine, proline and arginine, and depleted in lysine. Glycine is a known tumor biomarker; proline aids herpesvirus infections; and arginine and lysine promote and inhibit herpesviruses, respectively. Bars represent the average difference between tumor and baseline tissue for 12 individual turtles, percent changes from baseline percent total protein listed in parentheses, error bars are SEM. Bar color indicates P values from two-tailed paired t -tests. (C) Underlying histograms for arginine content in baseline and tumor tissue samples, bars are raw values, curves are smoothed trend. Download full-size image DOI: 10.7717/peerj.602/fig-1 Early studies discovered DNA from α -herpesviruses in FP tumors, but found adjacent tissues from diseased turtles, as well as samples from clinically healthy turtles, to be free of herpes DNA ( Lackovich et al., 1999 ; Lu et al., 2000 ; Quackenbush et al., 1998 ). Though further progress has been limited by an inability to develop viral cultures, recent work with next generation genomic techniques have made important contributions. These studies ( Alfaro-Núñez & Gilbert, 2014 ; Page-Karjian et al., 2012 ) found herpesvirus DNA to be rather ubiquitous—occurring in all hard-shelled sea turtles, in all populations tested, and even prevalent in clinically healthy turtles. If α -herpesviruses are the origin of FP, this represents a classic herpesvirus scenario where infections are pervasive, but latent or subclinical, in the host population ( Stevens & Cook, 1971 ; Umbach et al., 2008 ) and revealing of its etymology from the Greek ε ρπης , meaning “to creep”. With this in mind, we recently described the epidemiological link between this disease and coastal eutrophication, detailing how green turtles could literally be eating themselves sick ( Hall et al., 2007 ), activating latent herpes infections and promoting tumors by foraging on arginine-enriched macroalgae. A model built on this hypothesis ( Van Houtan, Hargrove & Balazs, 2010 ) explained 72% of the spatial variability of the disease across the Hawaiian Islands while offering a detailed explanation of the disease that connects turtle ecology, plant physiology (e.g., Raven & Taylor, 2003 ), and herpes biology to known management problems of nutrient pollution and invasive species. At the forefront, this proposed pathway focuses on the role arginine might have in promoting FP tumors. A significant body of evidence supports this. In many chronic diseases, arginine is implicated in cell inflammation and immune dysfunction ( Peranzoni et al., 2008 ) and in promoting viral tumors ( Mannick et al., 1994 ). But arginine is specifically important for herpesviruses. Laboratory studies demonstrate that herpes infections require arginine, being stunted in its absence ( Inglis, 1968 ; Mikami, Onuma & Hayashi, 1974 ; Olshevsky & Becker, 1970 ) and diminished when it is deprived ( Mistry et al., 2001 ). Subsequent research revealed that arginine is a principal component of glycoproteins in the outer viral envelope of herpesviruses. These glycoproteins are conserved across a wide variety of herpesviruses ( Alfaro-Núñez, 2014 ) and are critical to the herpes life cycle as they facilitate localization, fusion, and entrance to host cell nuclei ( Hibbard & Sandri-Goldin, 1995 ; Klyachkin & Geraghty, 2008 ). Beyond its significance for herpesviruses, arginine is an emerging focus of human cancer treatments as well. Cancer tumors lacking enzymes that synthesize arginine<|im_end|> <|im_start|>assistant Hawai'i's sea turtles are afflicted with chronic and often lethal tumors caused by consuming non-native algae "superweeds" along coastlines where nutrient pollution is unchecked. The disease that causes these tumors is considered the leading cause of death in endangered green sea turtles. The new research was just published in the scientific journal PeerJ. Turtles that graze on blooms of invasive seaweeds end up with a diet that is rich in a particular amino acid, arginine, which promotes the virus that creates the tumors. Scientists at the University of Hawai'i at Mānoa and their NOAA colleague estimate that adult turtles foraging at high-nutrient grazing sites increase their arginine intake 17–26 g daily, up to 14 times the background level. "For years, local ocean lovers have known that our green turtles have had awful tumors on their heads, eyes and front flippers," said UH Mānoa Marine Biology Professor Celia Smith, who worked with Kyle S. Van Houton of NOAA's Turtle Research Program on this study. "Many hypotheses were offered to explain the tumors, but we kept coming back to the observation that urban reefs—those near dense populations—are the sites with greater numbers of sick turtles. We had no mechanism for this disease." More than 60 percent of turtles in Kāne'ohe Bay have been observed to bear tumors. Kihei, Maui, has been called a "ground zero" for fibropapillomatosis, the disease that is caused by a herpes virus and manifests as tumors in turtles. Humans appear unaffected by the disease. Van Houtan and colleagues previously described an epidemiological link between tumors and coastal eutrophication, that is, the enrichment of coastal waters with nutrients from land-based sources of pollution such as wastewater or agricultural fertilizers. This new study analyzed the actual tissues from tumored green turtles and the amounts of arginine in the dominant algae forage species from across Hawai'i. The analysis revealed remarkably high levels of arginine in tissues of invasive seaweeds harvested under nutrient-rich conditions, such as those affected by nitrogen from land-based pollution. These are the same conditions that promote algal blooms. The non-native algae "superweeds" grow so quickly when fertilized that some can double their weight in a period of two days. When found on typical healthy reefs with low nutrient inputs, the same invasive algae species had lower levels of amino acids, even though arginine levels were still elevated. A native algae species and favorite food of the green sea turtle called Pterocladiella capillacea did not synthesize anomalously high levels of arginine under low nitrogen conditions. "I've never had a research project where so many different tools have been used to evaluate a hypothesis and, in every case, the same complex answer is returned: excess nutrients in coastal waters drive blooms of specific invasive algae," Smith said. "These weeds then grow rapidly, dominate shallow water ecosystems, and store high levels of arginine in their tissues that trigger tumor growth for the grazing turtle population. Few could have imagined that an algal bloom could have such consequences up the food chain." Smith and her colleagues, including UH Mānoa's Meghan L. Dailer and Migiwa S. Kawachi, note that eutrophication of coastal waters goes beyond its influence on green turtle populations. Eutrophication is also associated with coral reef declines. "The native species we have as our limu, fish and corals evolved for millions of years in low nutrient environments," Smith said. "Any added nitrogen that enters our tropical coasts begins to alter the fundamental competition among species. With too much nutrient input, as we have seen on Maui, new dynamics of fast growth by non-native superweeds occurs. These weeds take over our reefs, and we tend to lose our native species." The biggest losers might be the gentle sea turtles, who are not looking beyond their next algae snack. "The honu, or green turtles, have a special status in Hawai'i—culturally and federally," Smith said. "But to prevent them from consuming superweeds that promote these tumors—their greatest known source of mortality, we need to manage aggressively all land-based sources nutrient pollution and to restore the turtle's native diet." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 36254, 8627, 287, 8624, 16178, 897, 391, 484, 81868, 10934, 320, 11960, 8, 706, 92268, 9581, 37189, 22673, 369, 11026, 449, 912, 2867, 5353, 13, 362, 65009, 315, 19581, 482, 1964, 20975, 46957, 4881, 5938, 449, 1521, 56071, 706, 25281, 369, 96731, 11, 23377, 12434, 9547, 527, 8647, 369, 1202, 3293, 62057, 2508, 13, 763, 3766, 990, 11, 584, 7633, 1268, 70085, 46957, 4881, 1436, 5353, 34651, 56071, 1555, 264, 41861, 53952, 315, 1417, 83334, 13, 1226, 21091, 279, 8624, 8031, 6341, 304, 27076, 2740, 384, 332, 22761, 1142, 35335, 21160, 11, 323, 430, 72503, 369, 4210, 304, 1521, 6732, 2643, 25024, 1417, 83334, 21430, 14172, 291, 18563, 24823, 6043, 13, 5810, 11, 584, 1296, 279, 4623, 1701, 5234, 12, 35891, 42358, 35318, 266, 5814, 320, 39, 2989, 34, 8, 311, 7664, 279, 42500, 13935, 21542, 315, 6307, 37189, 320, 921, 301, 21947, 856, 35989, 883, 56071, 323, 4330, 4279, 369, 425, 9606, 315, 18563, 24823, 6043, 505, 264, 2134, 315, 384, 332, 42810, 5415, 13, 350, 372, 1105, 1051, 35146, 32389, 304, 72157, 483, 11, 463, 1074, 11, 73662, 483, 11, 1417, 83334, 11, 323, 1446, 483, 323, 79266, 304, 84495, 483, 994, 7863, 311, 26954, 10688, 13, 2052, 18563, 24823, 6043, 505, 384, 332, 42810, 10687, 1047, 32389, 1417, 83334, 11, 323, 682, 9606, 10932, 31668, 9967, 12434, 47503, 439, 1417, 83334, 1524, 520, 55984, 354, 42810, 6732, 13, 5659, 1521, 3135, 11, 584, 16430, 6822, 72503, 369, 4210, 520, 384, 332, 22761, 1142, 6732, 5376, 872, 1417, 83334, 23730, 220, 1114, 4235, 1627, 342, 7446, 11, 709, 311, 220, 975, 3115, 279, 4092, 2237, 13, 7793, 83334, 47503, 7319, 449, 2860, 18563, 24823, 6043, 47503, 323, 92456, 47503, 11, 323, 279, 53354, 22408, 347, 5237, 79461, 39515, 33252, 3167, 66, 7398, 285, 12207, 704, 716, 10365, 682, 1023, 9606, 304, 420, 5201, 13, 5751, 3135, 7838, 430, 384, 332, 22761, 20901, 32302, 12992, 279, 1417, 83334, 2262, 315, 18563, 24823, 6043, 11, 902, 1253, 28168, 2740, 12192, 42767, 70085, 46957, 4881, 323, 5353, 34651, 56071, 304, 6307, 72503, 13, 356, 635, 420, 439, 13000, 473, 412, 276, 47474, 11, 9259, 18582, 11, 423, 39882, 20187, 11, 51616, 31464, 386, 13, 220, 679, 19, 662, 469, 332, 22761, 20901, 323, 279, 34625, 20862, 315, 9581, 37189, 56071, 662, 46247, 41, 220, 17, 551, 384, 20224, 4802, 4652, 1495, 29438, 43564, 897, 391, 484, 81868, 10934, 320, 11960, 8, 374, 264, 21249, 323, 3629, 45089, 36254, 8627, 287, 8624, 304, 9581, 72503, 320, 23966, 13, 220, 16, 32, 7609, 1102, 6244, 264, 7363, 89, 1944, 292, 304, 6307, 72503, 304, 279, 220, 3753, 15, 82, 11, 50745, 4747, 430, 433, 574, 264, 6129, 6023, 311, 872, 3728, 29711, 320, 921, 278, 13649, 4657, 1880, 453, 2637, 220, 1049, 23, 2652, 6385, 25604, 11, 220, 2550, 19, 7609, 18056, 1455, 6307, 37189, 7187, 15285, 617, 7319, 43071, 2533, 320, 14582, 258, 1885, 1880, 453, 2637, 220, 679, 19, 7026, 279, 8624, 8625, 46941, 323, 304, 3892, 10687, 1202, 39775, 374, 2103, 7859, 320, 13000, 473, 412, 276, 11, 473, 867, 51515, 612, 19984, 1394, 82, 11, 220, 679, 15, 7609, 91958, 304, 8830, 279, 5353, 315, 34651, 617, 6051, 31288, 389, 12434, 9547, 11, 449, 17226, 5238, 315, 6029, 505, 4173, 24203, 311, 62057, 2508, 12899, 420, 31178, 320, 4701, 21581, 265, 612, 445, 34097, 11, 220, 1049, 19, 2652, 8924, 48723, 1880, 453, 2637, 220, 679, 15, 2652, 469, 818, 1880, 453, 2637, 220, 1049, 20, 2652, 6385, 25604, 1880, 453, 2637, 220, 1049, 19, 2652, 13000, 473, 412, 276, 11, 473, 867, 51515, 612, 19984, 1394, 82, 11, 220, 679, 15, 7609, 578, 50953, 20862, 315, 279, 8624, 374, 1903, 4726, 7185, 439, 34651, 56071, 617, 264, 11223, 29962, 6371, 13, 19575, 220, 16, 25, 320, 32, 8, 22410, 40204, 6307, 37189, 320, 921, 301, 21947, 856, 35989, 883, 35906, 92268, 449, 16178, 897, 391, 484, 81868, 10934, 11, 264, 36254, 8627, 287, 8624, 5938, 449, 19581, 482, 1964, 20975, 46957, 4881, 13, 11064, 25, 6287, 220, 679, 17, 386, 3448, 64, 11, 93550, 320, 24193, 25, 11517, 800, 1201, 285, 11, 55458, 14, 10544, 31498, 331, 6091, 570, 320, 33, 8, 362, 32924, 13935, 21542, 505, 37189, 39881, 1501, 16178, 897, 391, 484, 7942, 56071, 527, 35146, 69671, 304, 72157, 483, 11, 463, 1074, 323, 1417, 83334, 11, 323, 79266, 304, 84495, 483, 13, 79183, 66, 483, 374, 264, 3967, 36254, 39538, 13152, 26, 463, 1074, 52797, 70085, 85, 17402, 30020, 26, 323, 1417, 83334, 323, 84495, 483, 12192, 323, 69033, 70085, 46957, 4881, 11, 15947, 13, 57206, 4097, 279, 5578, 6811, 1990, 36254, 323, 26954, 20438, 369, 220, 717, 3927, 72503, 11, 3346, 4442, 505, 26954, 3346, 2860, 13128, 10212, 304, 75075, 11, 1493, 16283, 527, 46544, 13, 4821, 1933, 15151, 393, 2819, 505, 1403, 2442, 5805, 35526, 259, 482, 24781, 13, 320, 34, 8, 9636, 6852, 86745, 369, 1417, 83334, 2262, 304, 26954, 323, 36254, 20438, 10688, 11, 16283, 527, 7257, 2819, 11, 37033, 527, 93939, 9327, 13, 8745, 2539, 7321, 2217, 59670, 25, 220, 605, 13, 24876, 22, 14, 16944, 73, 13, 20224, 14, 915, 12, 16, 23591, 7978, 11352, 15922, 505, 19581, 482, 1964, 20975, 46957, 4881, 304, 34651, 56071, 11, 719, 1766, 24894, 39881, 505, 6759, 1503, 72503, 11, 439, 1664, 439, 10688, 505, 70432, 9498, 72503, 11, 311, 387, 1949, 315, 70085, 15922, 320, 68502, 51214, 1880, 453, 2637, 220, 2550, 24, 2652, 18866, 1880, 453, 2637, 220, 1049, 15, 2652, 3489, 474, 268, 65, 1136, 1880, 453, 2637, 220, 2550, 23, 7609, 18056, 4726, 5208, 706, 1027, 7347, 555, 459, 38550, 311, 2274, 29962, 27833, 11, 3293, 990, 449, 1828, 9659, 81064, 12823, 617, 1903, 3062, 19564, 13, 4314, 7978, 320, 66868, 17606, 11500, 6792, 5771, 10333, 612, 46092, 11, 220, 679, 19, 2652, 5874, 16222, 277, 82991, 1880, 453, 2637, 220, 679, 17, 883, 1766, 70085, 85, 17402, 15922, 311, 387, 4856, 64564, 2345, 511, 46839, 304, 682, 2653, 7666, 15556, 9581, 72503, 11, 304, 682, 22673, 12793, 11, 323, 1524, 46941, 304, 70432, 9498, 72503, 13, 1442, 19581, 482, 1964, 20975, 46957, 4881, 527, 279, 6371, 315, 34651, 11, 420, 11105, 264, 11670, 70085, 85, 17402, 15398, 1405, 30020, 527, 71867, 11, 719, 42767, 477, 1207, 91899, 11, 304, 279, 3552, 7187, 320, 36177, 612, 12797, 11, 220, 4468, 16, 2652, 67059, 613, 1880, 453, 2637, 220, 1049, 23, 883, 323, 31720, 315, 1202, 1880, 99174, 505, 279, 18341, 60247, 17839, 223, 49345, 100370, 1174, 7438, 1054, 998, 28182, 11453, 3161, 420, 304, 4059, 11, 584, 6051, 7633, 279, 62057, 5848, 2723, 1990, 420, 8624, 323, 35335, 384, 332, 22761, 20901, 11, 45293, 1268, 6307, 72503, 1436, 16280, 387, 12459, 5694, 14363, 320, 11166, 1880, 453, 2637, 220, 1049, 22, 7026, 72192, 42767, 70085, 30020, 323, 22923, 56071, 555, 369, 4210, 389, 1417, 83334, 21430, 14172, 291, 18563, 24823, 6043, 13, 362, 1646, 5918, 389, 420, 31178, 320, 13000, 473, 412, 276, 11, 473, 867, 51515, 612, 19984, 1394, 82, 11, 220, 679, 15, 883, 11497, 220, 5332, 4, 315, 279, 29079, 54709, 315, 279, 8624, 4028, 279, 59103, 23028, 1418, 10209, 264, 11944, 16540, 315, 279, 8624, 430, 34161, 37189, 72546, 11, 6136, 78152, 320, 68, 1326, 2637, 46207, 612, 16844, 11, 220, 1049, 18, 7026, 323, 70085, 34458, 311, 3967, 6373, 5435, 315, 50123, 25793, 323, 53354, 9606, 13, 2468, 279, 52301, 11, 420, 11223, 38970, 24400, 389, 279, 3560, 1417, 83334, 2643, 617, 304, 22923, 34651, 56071, 13, 362, 5199, 2547, 315, 6029, 11815, 420, 13, 763, 1690, 21249, 19338, 11, 1417, 83334, 374, 69702, 304, 2849, 37140, 323, 22852, 32403, 320, 3700, 12341, 21446, 1880, 453, 2637, 220, 1049, 23, 883, 323, 304, 22923, 29962, 56071, 320, 30960, 875, 1880, 453, 2637, 220, 2550, 19, 7609, 2030, 1417, 83334, 374, 11951, 3062, 369, 70085, 46957, 4881, 13, 32184, 7978, 20461, 430, 70085, 30020, 1397, 1417, 83334, 11, 1694, 357, 28736, 304, 1202, 19821, 320, 763, 6200, 285, 11, 220, 5162, 23, 2652, 43342, 10830, 11, 1952, 13722, 612, 18276, 31478, 11, 220, 4468, 19, 2652, 507, 4835, 81913, 27782, 612, 78484, 11, 220, 4468, 15, 883, 323, 54182, 994, 433, 374, 62683, 320, 386, 5050, 1880, 453, 2637, 220, 1049, 16, 7609, 3804, 72457, 3495, 10675, 430, 1417, 83334, 374, 264, 12717, 3777, 315, 37807, 38828, 5646, 1354, 304, 279, 16335, 29962, 35498, 315, 70085, 46957, 4881, 13, 4314, 37807, 38828, 5646, 1354, 527, 1615, 2841, 4028, 264, 7029, 8205, 315, 70085, 46957, 4881, 320, 66868, 17606, 11500, 6792, 5771, 10333, 11, 220, 679, 19, 883, 323, 527, 9200, 311, 279, 70085, 2324, 11008, 439, 814, 28696, 53404, 11, 37608, 11, 323, 20396, 311, 3552, 2849, 97192, 320, 92836, 67019, 612, 8847, 462, 12279, 820, 258, 11, 220, 2550, 20, 2652, 735, 398, 613, 8148, 612, 20524, 351, 427, 88, 11, 220, 1049, 23, 7609, 31886, 1202, 26431, 369, 70085, 46957, 4881, 11, 1417, 83334, 374, 459, 24084, 5357, 315, 3823, 9572, 22972, 439, 1664, 13, 26211, 56071, 32161, 56067, 430, 6925, 27985, 1417, 83334, 128257, 198, 128256, 78191, 198, 39, 37069, 63650, 596, 9581, 72503, 527, 92268, 449, 21249, 323, 3629, 45089, 56071, 9057, 555, 35208, 2536, 15971, 68951, 330, 9712, 906, 6910, 1, 3235, 13962, 8128, 1405, 50123, 25793, 374, 54291, 13, 578, 8624, 430, 11384, 1521, 56071, 374, 6646, 279, 6522, 5353, 315, 4648, 304, 52356, 6307, 9581, 72503, 13, 578, 502, 3495, 574, 1120, 4756, 304, 279, 12624, 8486, 46247, 41, 13, 350, 52214, 430, 28699, 3059, 389, 92889, 315, 53354, 67329, 68, 6910, 842, 709, 449, 264, 10173, 430, 374, 9257, 304, 264, 4040, 42500, 13935, 11, 1417, 83334, 11, 902, 39990, 279, 17188, 430, 11705, 279, 56071, 13, 57116, 520, 279, 3907, 315, 22153, 63650, 520, 386, 31757, 2201, 64, 323, 872, 86748, 37444, 16430, 430, 6822, 72503, 369, 4210, 520, 1579, 5392, 332, 13283, 84550, 6732, 5376, 872, 1417, 83334, 23730, 220, 1114, 4235, 1627, 342, 7446, 11, 709, 311, 220, 975, 3115, 279, 4092, 2237, 13, 330, 2520, 1667, 11, 2254, 18435, 33218, 617, 3967, 430, 1057, 6307, 72503, 617, 1047, 25629, 56071, 389, 872, 14971, 11, 6548, 323, 4156, 1344, 32997, 1359, 1071, 549, 39, 386, 31757, 2201, 64, 23820, 40023, 17054, 356, 37029, 9259, 11, 889, 6575, 449, 31359, 328, 13, 13000, 473, 412, 263, 315, 86748, 596, 67906, 8483, 6826, 389, 420, 4007, 13, 330, 8607, 74513, 1051, 9076, 311, 10552, 279, 56071, 11, 719, 584, 8774, 5108, 1203, 311, 279, 22695, 430, 16036, 92822, 2345, 54719, 3221, 29050, 22673, 83872, 279, 6732, 449, 7191, 5219, 315, 14363, 72503, 13, 1226, 1047, 912, 17383, 369, 420, 8624, 1210, 4497, 1109, 220, 1399, 3346, 315, 72503, 304, 735, 31757, 818, 94572, 383, 9332, 617, 1027, 13468, 311, 11984, 56071, 13, 30558, 61952, 11, 93550, 11, 706, 1027, 2663, 264, 330, 1993, 7315, 1, 369, 16178, 897, 391, 484, 81868, 10934, 11, 279, 8624, 430, 374, 9057, 555, 264, 70085, 17188, 323, 84332, 439, 56071, 304, 72503, 13, 66094, 5101, 78622, 555, 279, 8624, 13, 13000, 473, 412, 276, 323, 18105, 8767, 7633, 459, 62057, 5848, 2723, 1990, 56071, 323, 35335, 384, 332, 22761, 20901, 11, 430, 374, 11, 279, 70272, 315, 35335, 21160, 449, 37493, 505, 4363, 6108, 8336, 315, 25793, 1778, 439, 77681, 477, 29149, 36214, 12509, 13, 1115, 502, 4007, 30239, 279, 5150, 39881, 505, 15756, 3093, 6307, 72503, 323, 279, 15055, 315, 1417, 83334, 304, 279, 25462, 68951, 369, 425, 9606, 505, 4028, 22153, 63650, 13, 578, 6492, 10675, 49723, 1579, 5990, 315, 1417, 83334, 304, 39881, 315, 53354, 67329, 68, 6910, 67572, 1234, 50123, 41947, 4787, 11, 1778, 439, 1884, 11754, 555, 47503, 505, 4363, 6108, 25793, 13, 4314, 527, 279, 1890, 4787, 430, 12192, 453, 16876, 92889, 13, 578, 2536, 15971, 68951, 330, 9712, 906, 6910, 1, 3139, 779, 6288, 994, 36214, 1534, 430, 1063, 649, 2033, 872, 4785, 304, 264, 4261, 315, 1403, 2919, 13, 3277, 1766, 389, 14595, 9498, 92822, 449, 3428, 50123, 11374, 11, 279, 1890, 53354, 68951, 9606, 1047, 4827, 5990, 315, 42500, 33969, 11, 1524, 3582, 1417, 83334, 5990, 1051, 2103, 32389, 13, 362, 10068, 68951, 9606, 323, 7075, 3691, 315, 279, 6307, 9581, 37189, 2663, 393, 466, 62868, 2836, 6985, 2107, 484, 83682, 1550, 539, 6925, 27985, 70673, 7162, 1579, 5990, 315, 1417, 83334, 1234, 3428, 47503, 4787, 13, 330, 40, 3077, 2646, 1047, 264, 3495, 2447, 1405, 779, 1690, 2204, 7526, 617, 1027, 1511, 311, 15806, 264, 31178, 323, 11, 304, 1475, 1162, 11, 279, 1890, 6485, 4320, 374, 6052, 25, 13937, 37493, 304, 35335, 21160, 6678, 92889, 315, 3230, 53354, 68951, 1359, 9259, 1071, 13, 330, 9673, 70535, 1243, 3139, 19019, 11, 41836, 26682, 3090, 61951, 11, 323, 3637, 1579, 5990, 315, 1417, 83334, 304, 872, 39881, 430, 8346, 36254, 6650, 369, 279, 84550, 37189, 7187, 13, 44015, 1436, 617, 35706, 430, 459, 453, 16876, 52554, 1436, 617, 1778, 16296, 709, 279, 3691, 8957, 1210, 9259, 323, 1077, 18105, 11, 2737, 549, 39, 386, 31757, 2201, 64, 596, 80134, 445, 13, 423, 39882, 323, 386, 30637, 10196, 328, 13, 51616, 31464, 11, 5296, 430, 384, 332, 22761, 20901, 315, 35335, 21160, 5900, 7953, 1202, 10383, 389, 6307, 37189, 22673, 13, 469, 332, 22761, 20901, 374, 1101, 5938, 449, 53103, 71145, 58054, 13, 330, 791, 10068, 9606, 584, 617, 439, 1057, 4671, 84, 11, 7795, 323, 1867, 1147, 28995, 369, 11990, 315, 1667, 304, 3428, 50123, 22484, 1359, 9259, 1071, 13, 330, 8780, 3779, 47503, 430, 29933, 1057, 35148, 1080, 12019, 12302, 311, 11857, 279, 16188, 10937, 4315, 9606, 13, 3161, 2288, 1790, 50123, 1988, 11, 439, 584, 617, 3970, 389, 93550, 11, 502, 30295, 315, 5043, 6650, 555, 2536, 15971, 2307, 906, 6910, 13980, 13, 4314, 70535, 1935, 927, 1057, 92822, 11, 323, 584, 8541, 311, 9229, 1057, 10068, 9606, 1210, 578, 8706, 68456, 2643, 387, 279, 22443, 9581, 72503, 11, 889, 527, 539, 3411, 7953, 872, 1828, 68951, 40459, 13, 330, 791, 5954, 84, 11, 477, 6307, 72503, 11, 617, 264, 3361, 2704, 304, 22153, 63650, 2345, 93113, 43024, 323, 80637, 1359, 9259, 1071, 13, 330, 4071, 311, 5471, 1124, 505, 35208, 2307, 906, 6910, 430, 12192, 1521, 56071, 22416, 404, 12474, 3967, 2592, 315, 29528, 11, 584, 1205, 311, 10299, 49139, 682, 4363, 6108, 8336, 50123, 25793, 323, 311, 15301, 279, 37189, 596, 10068, 10173, 1210, 220, 128257, 198 ]

2,415

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Background The current taxonomy of the African giraffe ( Giraffa camelopardalis ) is primarily based on pelage pattern and geographic distribution, and nine subspecies are currently recognized. Although genetic studies have been conducted, their resolution is low, mainly due to limited sampling. Detailed knowledge about the genetic variation and phylogeography of the South African giraffe ( G. c. giraffa ) and the Angolan giraffe ( G. c. angolensis ) is lacking. We investigate genetic variation among giraffe matrilines by increased sampling, with a focus on giraffe key areas in southern Africa. Results The 1,562 nucleotides long mitochondrial DNA dataset (cytochrome b and partial control region) comprises 138 parsimony informative sites among 161 giraffe individuals from eight populations. We additionally included two okapis as an outgroup. The analyses of the maternally inherited sequences reveal a deep divergence between northern and southern giraffe populations in Africa, and a general pattern of distinct matrilineal clades corresponding to their geographic distribution. Divergence time estimates among giraffe populations place the deepest splits at several hundred thousand years ago. Conclusions Our increased sampling in southern Africa suggests that the distribution ranges of the Angolan and South African giraffe need to be redefined. Knowledge about the phylogeography and genetic variation of these two maternal lineages is crucial for the development of appropriate management strategies. Background For more than 250 years, giraffe ( Giraffa camelopardalis ) taxonomy has attracted interest among scientists [ 1 ]-[ 3 ]. The descriptions of the nine giraffe subspecies are primarily based on pelage patterns, characteristics of ossicones and their geographic distribution across the African continent [ 4 ],[ 5 ]. However, the inconsistent pelage recognition has confused taxonomical assignments due to its high variability [ 6 ]-[ 8 ]. Recent efforts using molecular genetic techniques are beginning to clarify giraffe taxonomy [ 9 ]-[ 11 ]. In contrast to studies on elephant [ 12 ],[ 13 ], and other African wildlife [ 14 ],[ 15 ], a range-wide genetic analysis of giraffe is lacking [ 9 ]-[ 11 ]. A phylogenetic study using data of six subspecies (Angolan giraffe ( G. c. angolensis ), South African giraffe ( G. c. giraffa ), West African giraffe ( G. c. peralta ), reticulated giraffe ( G. c. reticulata ), Rothschild’s giraffe ( G. c. rothschildi ) and Masai giraffe ( G. c. tippelskirchi )) based on nuclear microsatellites and mitochondrial (mt) DNA sequences suggested that some of the subspecies may actually represent distinct species [ 9 ]. Another study of the giraffe subspecies historically classified as Thornicroft’s giraffe ( G. c. thornicrofti ), which is restricted to Zambia’s South Luangwa valley, showed that this population has a distinct mtDNA haplotype that is nested within the clade of Masai giraffe [ 11 ]. Genetic analysis suggested that the Kordofan giraffe ( G. c. antiquorum ) in Central Africa is closely related to the West African giraffe [ 10 ], while the relationship of the Nubian giraffe ( G. c. camelopardalis ) is unclear due to a lack of any genetic analyses. In southern Africa, two subspecies of giraffe live in close proximity. South African giraffe have been reported to occur naturally throughout southern Botswana, southern Zimbabwe, southwestern Mozambique, northern South Africa and southeastern Namibia [ 7 ]. Giraffe of northwestern and north-central Namibia have been categorized as Angolan giraffe [ 1 ],[ 16 ] but the taxonomic classification of giraffe from northern Botswana and northeastern Namibia remains uncertain. Angolan giraffe is thought to occur also in southern Zambia, western Zimbabwe and central Botswana [ 16 ]. Both giraffe populations have historically been classified as either G. c. giraffa or G. c. angolensis , or most recently as a hybrid of G. giraffa / G. angolensis , depending on the taxonomic reference [ 6 ],[ 8 ]. The uncertainty of giraffe taxonomy in southern Africa affects conservation efforts, as individuals are being translocated both within and between different populations and countries across Africa without knowledge of the taxonomical status. Frequently, these translocations are driven by economic reasons for improving regional tourism rather than biodiversity conservation [ 17 ]. Conservation policies depend on reliable information about the taxonomic status and about genetic variability of locally adapted populations. Clarifying the relationship and distribution of the Angolan and South African giraffe is therefore particularly relevant for conservation efforts of the newly established Kavango-Zambezi Transfrontier Conservation Area (KAZA) that includes northeastern Namibia and northern Botswana. Although no targeted census of giraffe has been conducted, the size of Botswana’s northern giraffe population is estimated to have dropped over the last decade from >10,000 to <4,000 individuals [ 18 ]. The number of giraffe in Bwabwata National Park in Namibia was decimated in the 1970s and 1980s due to illegal hunting but has recovered since then to >150 individuals [ 19 ]. We here present a population genetic analysis of mitochondrial cytochrome b (cytb) and partial control region (CR) sequences for eight of the nine currently described giraffe subspecies. Our sampling focuses on geographic regions that have not been analyzed before, particularly in southern Africa: Namibia (Bwabwata National Park – BNP, Etosha National Park – ENP) and Botswana (Chobe National Park – CNP, Moremi Game Reserve – MGR, Nxai Pans – NXP, Vumbura Concession – V, Central Kalahari Game Reserve – CKGR), but also central Africa’s Democratic Republic of Congo (Garamba National Park – GNP) (Table 1 , Additional file 1 : Table S1). Our dense sampling includes many key areas of the giraffe distribution range in southern Africa and therefore allows for a high-resolution analysis of the phylogeography of South African and Angolan giraffe. Furthermore, it allows assessing the impact of a “cryptic” rift valley, which runs northeast to southwest across Botswana from Zambia [ 20 ],[ 21 ], potentially having acted as a barrier to giraffe dispersal. Table 1 Origin , abbreviation , number of individuals ( N ) and subspecies designation of analyzed giraffe sequences Full size table Results Mitochondrial DNA sequences from the cytochrome b (cytb) gene", "role": "user" }, { "content": "The Giraffe (Giraffa camelopardalis), a symbol of the African savanna and a fixed item on every safari's agenda, is a fascinating animal. However, contrary to many of the continent's other wild animals, these long-necked giants are still rather poorly studied. Based on their markings, distribution and genome, nine subspecies are recognized – including the two subspecies Angola Giraffe (Giraffa c. angolensis) and South African Giraffe (Giraffa c. giraffa). South African Giraffes occur farther north than previously assumed Like most other giraffes, these subspecies are now mainly found in nature reserves. Until recently, scientists assumed a clear demarcation of their ranges: Angola Giraffes occur in Namibia and northern Botswana, while South African Giraffes reside in southern Botswana and South Africa. \"However, according to our studies, the distribution areas prove to be much more complex. South African Giraffes also occur in northeastern Namibia and northern Botswana, and Angola Giraffes can be found in northwestern Namibia and southern Botswana, as well,\" explains the study's author, Friederike Bock from the Biodiversity and Climate Research Center (BiK-F). A look at the new distribution map reveals the presence of a population of Angola Giraffes in the Central Kalahari Game Reserve, the world's second-largest national park, quasi nestled between two populations of the South African Giraffe, with both subspecies living side by side. Subspecies were the result of early geographic separation According to the research team, the fact that two genetically distinct subspecies could develop within the same region may be explained by the local geographic conditions that prevailed approximately 500,000 to two million years ago. Back then, the mountain range along the East African Rift Valley was sinking, creating vast wetlands and lakes, such as the paleo lake Makgadikgadi. According to Professor Dr. Axel Janke from the BiK-F, \"these large bodies of water may have separated the populations for long periods of time. Moreover, female giraffes likely do not migrate across long distances, thereby contributing to a clear separation of the maternal lines.\" Today, there no longer exist any barriers that prevent the possible mingling of both subspecies; an investigation of these processes is however subject to further genetic analyses. Angola and South African Giraffes can be uniquely identified by their maternal gene profile For the study, the researchers created a profile of the subspecies' mitochondrial DNA, using tissue samples from about 160 giraffes from various populations across the entire African continent. On the basis of this genetic material, inherited from the maternal side, the often similarly marked subspecies can be uniquely identified genetically and the relationships between various populations can be clearly demonstrated. \"Our focus was on giraffes in southern Africa, in particular in Botswana and South Africa. There, we sampled populations that had not been genetically analyzed before,\" says Bock. New insights enable improved protection measures for the giraffe According to estimates by the World Conservation Organization IUCN, the world's giraffe population is about 100,000 individuals – showing a decreasing trend. In Botswana alone, the population has dwindled by more than half in recent years. In order to achieve effective protection measures that will preserve the majority of the giraffe's subspecies, it is indispensable to gain knowledge that allows their reliable identification as well as detailed information regarding their distribution. The surprising results concerning the distribution of the two subspecies in Namibia and Botswana emphasize the importance of additional taxonomic research on all giraffe subspecies. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Background The current taxonomy of the African giraffe ( Giraffa camelopardalis ) is primarily based on pelage pattern and geographic distribution, and nine subspecies are currently recognized. Although genetic studies have been conducted, their resolution is low, mainly due to limited sampling. Detailed knowledge about the genetic variation and phylogeography of the South African giraffe ( G. c. giraffa ) and the Angolan giraffe ( G. c. angolensis ) is lacking. We investigate genetic variation among giraffe matrilines by increased sampling, with a focus on giraffe key areas in southern Africa. Results The 1,562 nucleotides long mitochondrial DNA dataset (cytochrome b and partial control region) comprises 138 parsimony informative sites among 161 giraffe individuals from eight populations. We additionally included two okapis as an outgroup. The analyses of the maternally inherited sequences reveal a deep divergence between northern and southern giraffe populations in Africa, and a general pattern of distinct matrilineal clades corresponding to their geographic distribution. Divergence time estimates among giraffe populations place the deepest splits at several hundred thousand years ago. Conclusions Our increased sampling in southern Africa suggests that the distribution ranges of the Angolan and South African giraffe need to be redefined. Knowledge about the phylogeography and genetic variation of these two maternal lineages is crucial for the development of appropriate management strategies. Background For more than 250 years, giraffe ( Giraffa camelopardalis ) taxonomy has attracted interest among scientists [ 1 ]-[ 3 ]. The descriptions of the nine giraffe subspecies are primarily based on pelage patterns, characteristics of ossicones and their geographic distribution across the African continent [ 4 ],[ 5 ]. However, the inconsistent pelage recognition has confused taxonomical assignments due to its high variability [ 6 ]-[ 8 ]. Recent efforts using molecular genetic techniques are beginning to clarify giraffe taxonomy [ 9 ]-[ 11 ]. In contrast to studies on elephant [ 12 ],[ 13 ], and other African wildlife [ 14 ],[ 15 ], a range-wide genetic analysis of giraffe is lacking [ 9 ]-[ 11 ]. A phylogenetic study using data of six subspecies (Angolan giraffe ( G. c. angolensis ), South African giraffe ( G. c. giraffa ), West African giraffe ( G. c. peralta ), reticulated giraffe ( G. c. reticulata ), Rothschild’s giraffe ( G. c. rothschildi ) and Masai giraffe ( G. c. tippelskirchi )) based on nuclear microsatellites and mitochondrial (mt) DNA sequences suggested that some of the subspecies may actually represent distinct species [ 9 ]. Another study of the giraffe subspecies historically classified as Thornicroft’s giraffe ( G. c. thornicrofti ), which is restricted to Zambia’s South Luangwa valley, showed that this population has a distinct mtDNA haplotype that is nested within the clade of Masai giraffe [ 11 ]. Genetic analysis suggested that the Kordofan giraffe ( G. c. antiquorum ) in Central Africa is closely related to the West African giraffe [ 10 ], while the relationship of the Nubian giraffe ( G. c. camelopardalis ) is unclear due to a lack of any genetic analyses. In southern Africa, two subspecies of giraffe live in close proximity. South African giraffe have been reported to occur naturally throughout southern Botswana, southern Zimbabwe, southwestern Mozambique, northern South Africa and southeastern Namibia [ 7 ]. Giraffe of northwestern and north-central Namibia have been categorized as Angolan giraffe [ 1 ],[ 16 ] but the taxonomic classification of giraffe from northern Botswana and northeastern Namibia remains uncertain. Angolan giraffe is thought to occur also in southern Zambia, western Zimbabwe and central Botswana [ 16 ]. Both giraffe populations have historically been classified as either G. c. giraffa or G. c. angolensis , or most recently as a hybrid of G. giraffa / G. angolensis , depending on the taxonomic reference [ 6 ],[ 8 ]. The uncertainty of giraffe taxonomy in southern Africa affects conservation efforts, as individuals are being translocated both within and between different populations and countries across Africa without knowledge of the taxonomical status. Frequently, these translocations are driven by economic reasons for improving regional tourism rather than biodiversity conservation [ 17 ]. Conservation policies depend on reliable information about the taxonomic status and about genetic variability of locally adapted populations. Clarifying the relationship and distribution of the Angolan and South African giraffe is therefore particularly relevant for conservation efforts of the newly established Kavango-Zambezi Transfrontier Conservation Area (KAZA) that includes northeastern Namibia and northern Botswana. Although no targeted census of giraffe has been conducted, the size of Botswana’s northern giraffe population is estimated to have dropped over the last decade from >10,000 to <4,000 individuals [ 18 ]. The number of giraffe in Bwabwata National Park in Namibia was decimated in the 1970s and 1980s due to illegal hunting but has recovered since then to >150 individuals [ 19 ]. We here present a population genetic analysis of mitochondrial cytochrome b (cytb) and partial control region (CR) sequences for eight of the nine currently described giraffe subspecies. Our sampling focuses on geographic regions that have not been analyzed before, particularly in southern Africa: Namibia (Bwabwata National Park – BNP, Etosha National Park – ENP) and Botswana (Chobe National Park – CNP, Moremi Game Reserve – MGR, Nxai Pans – NXP, Vumbura Concession – V, Central Kalahari Game Reserve – CKGR), but also central Africa’s Democratic Republic of Congo (Garamba National Park – GNP) (Table 1 , Additional file 1 : Table S1). Our dense sampling includes many key areas of the giraffe distribution range in southern Africa and therefore allows for a high-resolution analysis of the phylogeography of South African and Angolan giraffe. Furthermore, it allows assessing the impact of a “cryptic” rift valley, which runs northeast to southwest across Botswana from Zambia [ 20 ],[ 21 ], potentially having acted as a barrier to giraffe dispersal. Table 1 Origin , abbreviation , number of individuals ( N ) and subspecies designation of analyzed giraffe sequences Full size table Results Mitochondrial DNA sequences from the cytochrome b (cytb) gene<|im_end|> <|im_start|>assistant The Giraffe (Giraffa camelopardalis), a symbol of the African savanna and a fixed item on every safari's agenda, is a fascinating animal. However, contrary to many of the continent's other wild animals, these long-necked giants are still rather poorly studied. Based on their markings, distribution and genome, nine subspecies are recognized – including the two subspecies Angola Giraffe (Giraffa c. angolensis) and South African Giraffe (Giraffa c. giraffa). South African Giraffes occur farther north than previously assumed Like most other giraffes, these subspecies are now mainly found in nature reserves. Until recently, scientists assumed a clear demarcation of their ranges: Angola Giraffes occur in Namibia and northern Botswana, while South African Giraffes reside in southern Botswana and South Africa. "However, according to our studies, the distribution areas prove to be much more complex. South African Giraffes also occur in northeastern Namibia and northern Botswana, and Angola Giraffes can be found in northwestern Namibia and southern Botswana, as well," explains the study's author, Friederike Bock from the Biodiversity and Climate Research Center (BiK-F). A look at the new distribution map reveals the presence of a population of Angola Giraffes in the Central Kalahari Game Reserve, the world's second-largest national park, quasi nestled between two populations of the South African Giraffe, with both subspecies living side by side. Subspecies were the result of early geographic separation According to the research team, the fact that two genetically distinct subspecies could develop within the same region may be explained by the local geographic conditions that prevailed approximately 500,000 to two million years ago. Back then, the mountain range along the East African Rift Valley was sinking, creating vast wetlands and lakes, such as the paleo lake Makgadikgadi. According to Professor Dr. Axel Janke from the BiK-F, "these large bodies of water may have separated the populations for long periods of time. Moreover, female giraffes likely do not migrate across long distances, thereby contributing to a clear separation of the maternal lines." Today, there no longer exist any barriers that prevent the possible mingling of both subspecies; an investigation of these processes is however subject to further genetic analyses. Angola and South African Giraffes can be uniquely identified by their maternal gene profile For the study, the researchers created a profile of the subspecies' mitochondrial DNA, using tissue samples from about 160 giraffes from various populations across the entire African continent. On the basis of this genetic material, inherited from the maternal side, the often similarly marked subspecies can be uniquely identified genetically and the relationships between various populations can be clearly demonstrated. "Our focus was on giraffes in southern Africa, in particular in Botswana and South Africa. There, we sampled populations that had not been genetically analyzed before," says Bock. New insights enable improved protection measures for the giraffe According to estimates by the World Conservation Organization IUCN, the world's giraffe population is about 100,000 individuals – showing a decreasing trend. In Botswana alone, the population has dwindled by more than half in recent years. In order to achieve effective protection measures that will preserve the majority of the giraffe's subspecies, it is indispensable to gain knowledge that allows their reliable identification as well as detailed information regarding their distribution. The surprising results concerning the distribution of the two subspecies in Namibia and Botswana emphasize the importance of additional taxonomic research on all giraffe subspecies. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 25837, 578, 1510, 72906, 315, 279, 11904, 41389, 38880, 320, 48035, 2715, 64, 50252, 33029, 35965, 883, 374, 15871, 3196, 389, 12077, 425, 5497, 323, 46139, 8141, 11, 323, 11888, 5258, 89721, 527, 5131, 15324, 13, 10541, 19465, 7978, 617, 1027, 13375, 11, 872, 11175, 374, 3428, 11, 14918, 4245, 311, 7347, 25936, 13, 63765, 6677, 922, 279, 19465, 23851, 323, 37555, 385, 713, 5814, 315, 279, 4987, 11904, 41389, 38880, 320, 480, 13, 272, 13, 41389, 2715, 64, 883, 323, 279, 7568, 38872, 41389, 38880, 320, 480, 13, 272, 13, 6590, 337, 87778, 883, 374, 32161, 13, 1226, 19874, 19465, 23851, 4315, 41389, 38880, 5634, 31660, 1572, 555, 7319, 25936, 11, 449, 264, 5357, 389, 41389, 38880, 1401, 5789, 304, 18561, 10384, 13, 18591, 578, 220, 16, 11, 19242, 31484, 354, 3422, 1317, 72061, 15922, 10550, 320, 11377, 998, 33002, 293, 323, 7276, 2585, 5654, 8, 41095, 220, 10350, 10364, 65556, 39319, 6732, 4315, 220, 10718, 41389, 38880, 7931, 505, 8223, 22673, 13, 1226, 37938, 5343, 1403, 5509, 14041, 439, 459, 704, 4166, 13, 578, 29060, 315, 279, 5634, 944, 750, 28088, 24630, 16805, 264, 5655, 82258, 1990, 18671, 323, 18561, 41389, 38880, 22673, 304, 10384, 11, 323, 264, 4689, 5497, 315, 12742, 5634, 81, 27658, 278, 1206, 3536, 12435, 311, 872, 46139, 8141, 13, 423, 1553, 29355, 892, 17989, 4315, 41389, 38880, 22673, 2035, 279, 51621, 41567, 520, 3892, 7895, 16579, 1667, 4227, 13, 1221, 24436, 5751, 7319, 25936, 304, 18561, 10384, 13533, 430, 279, 8141, 21986, 315, 279, 7568, 38872, 323, 4987, 11904, 41389, 38880, 1205, 311, 387, 312, 9910, 13, 33025, 922, 279, 37555, 385, 713, 5814, 323, 19465, 23851, 315, 1521, 1403, 50150, 1584, 1154, 374, 16996, 369, 279, 4500, 315, 8475, 6373, 15174, 13, 25837, 1789, 810, 1109, 220, 5154, 1667, 11, 41389, 38880, 320, 48035, 2715, 64, 50252, 33029, 35965, 883, 72906, 706, 29123, 2802, 4315, 14248, 510, 220, 16, 2331, 42095, 220, 18, 21087, 578, 28887, 315, 279, 11888, 41389, 38880, 5258, 89721, 527, 15871, 3196, 389, 12077, 425, 12912, 11, 17910, 315, 31159, 1965, 288, 323, 872, 46139, 8141, 4028, 279, 11904, 32843, 510, 220, 19, 10881, 58, 220, 20, 21087, 4452, 11, 279, 40240, 12077, 425, 18324, 706, 22568, 3827, 14609, 950, 32272, 4245, 311, 1202, 1579, 54709, 510, 220, 21, 2331, 42095, 220, 23, 21087, 35390, 9045, 1701, 31206, 19465, 12823, 527, 7314, 311, 38263, 41389, 38880, 72906, 510, 220, 24, 2331, 42095, 220, 806, 21087, 763, 13168, 311, 7978, 389, 46840, 510, 220, 717, 10881, 58, 220, 1032, 10881, 323, 1023, 11904, 30405, 510, 220, 975, 10881, 58, 220, 868, 10881, 264, 2134, 25480, 19465, 6492, 315, 41389, 38880, 374, 32161, 510, 220, 24, 2331, 42095, 220, 806, 21087, 362, 37555, 86945, 5411, 4007, 1701, 828, 315, 4848, 5258, 89721, 320, 10976, 38872, 41389, 38880, 320, 480, 13, 272, 13, 6590, 337, 87778, 7026, 4987, 11904, 41389, 38880, 320, 480, 13, 272, 13, 41389, 2715, 64, 7026, 4410, 11904, 41389, 38880, 320, 480, 13, 272, 13, 824, 69151, 7026, 2160, 292, 7913, 41389, 38880, 320, 480, 13, 272, 13, 2160, 292, 360, 460, 7026, 97015, 3124, 753, 41389, 38880, 320, 480, 13, 272, 13, 938, 17323, 3124, 72, 883, 323, 20459, 2192, 41389, 38880, 320, 480, 13, 272, 13, 259, 2877, 2053, 69031, 14946, 12254, 3196, 389, 11499, 8162, 37568, 42760, 323, 72061, 320, 2562, 8, 15922, 24630, 12090, 430, 1063, 315, 279, 5258, 89721, 1253, 3604, 4097, 12742, 9606, 510, 220, 24, 21087, 13596, 4007, 315, 279, 41389, 38880, 5258, 89721, 35901, 21771, 439, 78024, 2823, 728, 753, 41389, 38880, 320, 480, 13, 272, 13, 270, 1540, 2823, 728, 72, 7026, 902, 374, 22486, 311, 95104, 753, 4987, 18866, 526, 10196, 34681, 11, 8710, 430, 420, 7187, 706, 264, 12742, 12232, 56420, 46900, 75, 4249, 430, 374, 24997, 2949, 279, 1206, 1037, 315, 20459, 2192, 41389, 38880, 510, 220, 806, 21087, 75226, 6492, 12090, 430, 279, 735, 541, 1073, 276, 41389, 38880, 320, 480, 13, 272, 13, 61386, 34106, 883, 304, 10913, 10384, 374, 15499, 5552, 311, 279, 4410, 11904, 41389, 38880, 510, 220, 605, 10881, 1418, 279, 5133, 315, 279, 452, 392, 1122, 41389, 38880, 320, 480, 13, 272, 13, 50252, 33029, 35965, 883, 374, 25420, 4245, 311, 264, 6996, 315, 904, 19465, 29060, 13, 763, 18561, 10384, 11, 1403, 5258, 89721, 315, 41389, 38880, 3974, 304, 3345, 37843, 13, 4987, 11904, 41389, 38880, 617, 1027, 5068, 311, 12446, 18182, 6957, 18561, 23869, 94810, 11, 18561, 52320, 11, 99911, 52543, 90929, 11, 18671, 4987, 10384, 323, 83209, 31074, 67337, 510, 220, 22, 21087, 48035, 38880, 315, 10411, 31382, 323, 10411, 85181, 31074, 67337, 617, 1027, 71974, 439, 7568, 38872, 41389, 38880, 510, 220, 16, 10881, 58, 220, 845, 2331, 719, 279, 3827, 48228, 24790, 315, 41389, 38880, 505, 18671, 23869, 94810, 323, 87244, 31074, 67337, 8625, 36218, 13, 7568, 38872, 41389, 38880, 374, 3463, 311, 12446, 1101, 304, 18561, 95104, 11, 19001, 52320, 323, 8792, 23869, 94810, 510, 220, 845, 21087, 11995, 41389, 38880, 22673, 617, 35901, 1027, 21771, 439, 3060, 480, 13, 272, 13, 41389, 2715, 64, 477, 480, 13, 272, 13, 6590, 337, 87778, 1174, 477, 1455, 6051, 439, 264, 26038, 315, 480, 13, 41389, 2715, 64, 611, 480, 13, 6590, 337, 87778, 1174, 11911, 389, 279, 3827, 48228, 5905, 510, 220, 21, 10881, 58, 220, 23, 21087, 578, 27924, 315, 41389, 38880, 72906, 304, 18561, 10384, 22223, 29711, 9045, 11, 439, 7931, 527, 1694, 1380, 40563, 2225, 2949, 323, 1990, 2204, 22673, 323, 5961, 4028, 10384, 2085, 6677, 315, 279, 3827, 14609, 950, 2704, 13, 93720, 11, 1521, 1380, 32409, 527, 16625, 555, 7100, 8125, 369, 18899, 15481, 32083, 4856, 1109, 73119, 29711, 510, 220, 1114, 21087, 45435, 10396, 6904, 389, 15062, 2038, 922, 279, 3827, 48228, 2704, 323, 922, 19465, 54709, 315, 24392, 30464, 22673, 13, 31181, 7922, 279, 5133, 323, 8141, 315, 279, 7568, 38872, 323, 4987, 11904, 41389, 38880, 374, 9093, 8104, 9959, 369, 29711, 9045, 315, 279, 13945, 9749, 735, 402, 5281, 11419, 309, 1395, 8510, 4149, 7096, 1291, 45435, 12299, 320, 42, 24476, 32, 8, 430, 5764, 87244, 31074, 67337, 323, 18671, 23869, 94810, 13, 10541, 912, 17550, 44702, 315, 41389, 38880, 706, 1027, 13375, 11, 279, 1404, 315, 23869, 94810, 753, 18671, 41389, 38880, 7187, 374, 13240, 311, 617, 12504, 927, 279, 1566, 13515, 505, 871, 605, 11, 931, 311, 366, 19, 11, 931, 7931, 510, 220, 972, 21087, 578, 1396, 315, 41389, 38880, 304, 426, 86, 370, 86, 460, 5165, 5657, 304, 31074, 67337, 574, 1654, 7292, 304, 279, 220, 4468, 15, 82, 323, 220, 3753, 15, 82, 4245, 311, 12079, 23330, 719, 706, 26403, 2533, 1243, 311, 871, 3965, 7931, 510, 220, 777, 21087, 1226, 1618, 3118, 264, 7187, 19465, 6492, 315, 72061, 9693, 998, 33002, 293, 320, 11377, 18894, 8, 323, 7276, 2585, 5654, 320, 9150, 8, 24630, 369, 8223, 315, 279, 11888, 5131, 7633, 41389, 38880, 5258, 89721, 13, 5751, 25936, 24400, 389, 46139, 13918, 430, 617, 539, 1027, 30239, 1603, 11, 8104, 304, 18561, 10384, 25, 31074, 67337, 320, 33, 86, 370, 86, 460, 5165, 5657, 1389, 426, 27321, 11, 19421, 437, 4317, 5165, 5657, 1389, 5301, 47, 8, 323, 23869, 94810, 320, 1163, 15784, 5165, 5657, 1389, 25914, 47, 11, 4497, 8318, 4140, 25820, 1389, 386, 8796, 11, 82147, 2192, 393, 598, 1389, 452, 28475, 11, 650, 3635, 5808, 1221, 26540, 1389, 650, 11, 10913, 27930, 1494, 2850, 4140, 25820, 1389, 31166, 8796, 705, 719, 1101, 8792, 10384, 753, 11650, 5545, 315, 54932, 320, 38, 640, 4749, 5165, 5657, 1389, 480, 27321, 8, 320, 2620, 220, 16, 1174, 24086, 1052, 220, 16, 551, 6771, 328, 16, 570, 5751, 29050, 25936, 5764, 1690, 1401, 5789, 315, 279, 41389, 38880, 8141, 2134, 304, 18561, 10384, 323, 9093, 6276, 369, 264, 1579, 64036, 6492, 315, 279, 37555, 385, 713, 5814, 315, 4987, 11904, 323, 7568, 38872, 41389, 38880, 13, 24296, 11, 433, 6276, 47614, 279, 5536, 315, 264, 1054, 49225, 292, 863, 78257, 34681, 11, 902, 8640, 41929, 311, 54085, 4028, 23869, 94810, 505, 95104, 510, 220, 508, 10881, 58, 220, 1691, 10881, 13893, 3515, 31532, 439, 264, 22881, 311, 41389, 38880, 79835, 278, 13, 6771, 220, 16, 17554, 1174, 72578, 1174, 1396, 315, 7931, 320, 452, 883, 323, 5258, 89721, 43851, 315, 30239, 41389, 38880, 24630, 8797, 1404, 2007, 18591, 22515, 47517, 6757, 15922, 24630, 505, 279, 9693, 998, 33002, 293, 320, 11377, 18894, 8, 15207, 128257, 198, 128256, 78191, 198, 791, 48035, 38880, 320, 38, 404, 2715, 64, 50252, 33029, 35965, 705, 264, 7891, 315, 279, 11904, 11427, 12930, 323, 264, 8521, 1537, 389, 1475, 83406, 596, 18909, 11, 374, 264, 27387, 10065, 13, 4452, 11, 26102, 311, 1690, 315, 279, 32843, 596, 1023, 8545, 10099, 11, 1521, 1317, 96533, 291, 46309, 527, 2103, 4856, 31555, 20041, 13, 20817, 389, 872, 65172, 11, 8141, 323, 33869, 11, 11888, 5258, 89721, 527, 15324, 1389, 2737, 279, 1403, 5258, 89721, 98792, 48035, 38880, 320, 38, 404, 2715, 64, 272, 13, 6590, 337, 87778, 8, 323, 4987, 11904, 48035, 38880, 320, 38, 404, 2715, 64, 272, 13, 41389, 2715, 64, 570, 4987, 11904, 48035, 2715, 288, 12446, 43726, 10411, 1109, 8767, 19655, 9086, 1455, 1023, 41389, 2715, 288, 11, 1521, 5258, 89721, 527, 1457, 14918, 1766, 304, 7138, 30600, 13, 30070, 6051, 11, 14248, 19655, 264, 2867, 2486, 8362, 367, 315, 872, 21986, 25, 98792, 48035, 2715, 288, 12446, 304, 31074, 67337, 323, 18671, 23869, 94810, 11, 1418, 4987, 11904, 48035, 2715, 288, 48383, 304, 18561, 23869, 94810, 323, 4987, 10384, 13, 330, 11458, 11, 4184, 311, 1057, 7978, 11, 279, 8141, 5789, 12391, 311, 387, 1790, 810, 6485, 13, 4987, 11904, 48035, 2715, 288, 1101, 12446, 304, 87244, 31074, 67337, 323, 18671, 23869, 94810, 11, 323, 98792, 48035, 2715, 288, 649, 387, 1766, 304, 10411, 31382, 31074, 67337, 323, 18561, 23869, 94810, 11, 439, 1664, 1359, 15100, 279, 4007, 596, 3229, 11, 31351, 261, 3043, 426, 1197, 505, 279, 426, 3205, 3050, 323, 31636, 8483, 5955, 320, 37196, 42, 7424, 570, 362, 1427, 520, 279, 502, 8141, 2472, 21667, 279, 9546, 315, 264, 7187, 315, 98792, 48035, 2715, 288, 304, 279, 10913, 27930, 1494, 2850, 4140, 25820, 11, 279, 1917, 596, 2132, 68067, 5426, 6246, 11, 48844, 89777, 1990, 1403, 22673, 315, 279, 4987, 11904, 48035, 38880, 11, 449, 2225, 5258, 89721, 5496, 3185, 555, 3185, 13, 3804, 43590, 1051, 279, 1121, 315, 4216, 46139, 25768, 10771, 311, 279, 3495, 2128, 11, 279, 2144, 430, 1403, 52033, 12742, 5258, 89721, 1436, 2274, 2949, 279, 1890, 5654, 1253, 387, 11497, 555, 279, 2254, 46139, 4787, 430, 85814, 13489, 220, 2636, 11, 931, 311, 1403, 3610, 1667, 4227, 13, 6984, 1243, 11, 279, 16700, 2134, 3235, 279, 6460, 11904, 57427, 13345, 574, 62193, 11, 6968, 13057, 14739, 8329, 323, 44236, 11, 1778, 439, 279, 28639, 78, 22553, 40424, 70, 329, 1609, 70, 2836, 13, 10771, 311, 17054, 2999, 13, 87779, 4448, 441, 505, 279, 12371, 42, 7424, 11, 330, 45010, 3544, 13162, 315, 3090, 1253, 617, 19180, 279, 22673, 369, 1317, 18852, 315, 892, 13, 23674, 11, 8954, 41389, 2715, 288, 4461, 656, 539, 45666, 4028, 1317, 27650, 11, 28592, 29820, 311, 264, 2867, 25768, 315, 279, 50150, 5238, 1210, 11450, 11, 1070, 912, 5129, 3073, 904, 30740, 430, 5471, 279, 3284, 73259, 2785, 315, 2225, 5258, 89721, 26, 459, 8990, 315, 1521, 11618, 374, 4869, 3917, 311, 4726, 19465, 29060, 13, 98792, 323, 4987, 11904, 48035, 2715, 288, 649, 387, 42329, 11054, 555, 872, 50150, 15207, 5643, 1789, 279, 4007, 11, 279, 12074, 3549, 264, 5643, 315, 279, 5258, 89721, 6, 72061, 15922, 11, 1701, 20438, 10688, 505, 922, 220, 6330, 41389, 2715, 288, 505, 5370, 22673, 4028, 279, 4553, 11904, 32843, 13, 1952, 279, 8197, 315, 420, 19465, 3769, 11, 28088, 505, 279, 50150, 3185, 11, 279, 3629, 30293, 13160, 5258, 89721, 649, 387, 42329, 11054, 52033, 323, 279, 12135, 1990, 5370, 22673, 649, 387, 9539, 21091, 13, 330, 8140, 5357, 574, 389, 41389, 2715, 288, 304, 18561, 10384, 11, 304, 4040, 304, 23869, 94810, 323, 4987, 10384, 13, 2684, 11, 584, 49976, 22673, 430, 1047, 539, 1027, 52033, 30239, 1603, 1359, 2795, 426, 1197, 13, 1561, 26793, 7431, 13241, 9313, 11193, 369, 279, 41389, 38880, 10771, 311, 17989, 555, 279, 4435, 45435, 21021, 358, 5576, 45, 11, 279, 1917, 596, 41389, 38880, 7187, 374, 922, 220, 1041, 11, 931, 7931, 1389, 9204, 264, 44649, 9327, 13, 763, 23869, 94810, 7636, 11, 279, 7187, 706, 83222, 839, 555, 810, 1109, 4376, 304, 3293, 1667, 13, 763, 2015, 311, 11322, 7524, 9313, 11193, 430, 690, 21813, 279, 8857, 315, 279, 41389, 38880, 596, 5258, 89721, 11, 433, 374, 64284, 311, 8895, 6677, 430, 6276, 872, 15062, 22654, 439, 1664, 439, 11944, 2038, 9002, 872, 8141, 13, 578, 15206, 3135, 18815, 279, 8141, 315, 279, 1403, 5258, 89721, 304, 31074, 67337, 323, 23869, 94810, 47032, 279, 12939, 315, 5217, 3827, 48228, 3495, 389, 682, 41389, 38880, 5258, 89721, 13, 220, 128257, 198 ]

2,180

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Background Effective disease management depends on timely and accurate diagnosis to guide control measures. The capacity to distinguish between individuals in a pathogen population with specific properties such as fungicide resistance, toxin production and virulence profiles is often essential to inform disease management approaches. The genomics revolution has led to technologies that can rapidly produce high-resolution genotypic information to define individual variants of a pathogen species. However, their application to complex fungal pathogens has remained limited due to the frequent inability to culture these pathogens in the absence of their host and their large genome sizes. Results Here, we describe the development of Mobile And Real-time PLant disEase (MARPLE) diagnostics, a portable, genomics-based, point-of-care approach specifically tailored to identify individual strains of complex fungal plant pathogens. We used targeted sequencing to overcome limitations associated with the size of fungal genomes and their often obligately biotrophic nature. Focusing on the wheat yellow rust pathogen, Puccinia striiformis f.sp. tritici ( Pst ), we demonstrate that our approach can be used to rapidly define individual strains, assign strains to distinct genetic lineages that have been shown to correlate tightly with their virulence profiles and monitor genes of importance. Conclusions MARPLE diagnostics enables rapid identification of individual pathogen strains and has the potential to monitor those with specific properties such as fungicide resistance directly from field-collected infected plant tissue in situ. Generating results within 48 h of field sampling, this new strategy has far-reaching implications for tracking plant health threats. Background Rapid and accurate point-of-care (PoC) diagnostics facilitate early intervention during plant disease outbreaks and enable disease management decisions that limit the spread of plant health threats. PoC diagnostics involve portable equipment that can be used in-field to rapidly confirm disease outbreaks and provide actionable information [ 1 ]. At present, conventional plant disease diagnostics rely on visible inspections of disease symptoms followed by basic laboratory tests through culturing and pathogenicity assays [ 2 ]. Unfortunately, these conventional methods tend to be subjective, time-consuming, labour-intensive and reliant on specialised expertise and equipment, providing only limited phenotypic information [ 3 ]. These factors limit their utility in PoC diagnosis. Recent alternative approaches have focused on serological and nucleic acid assays [ 4 ]. Polyclonal and monoclonal antisera are frequently used to detect plant pathogens using techniques such as enzyme-linked immunosorbent assay (ELISA), immunostrip assays and immunoblotting [ 5 ]. In addition, following a flurry of PCR-based diagnostic tests in the 1980s, the advent of the loop-mediated isothermal amplification (LAMP) assay at the turn of the twenty-first century provided the first rapid nucleic acid amplification method to accurately diagnose pathogens in situ in real time [ 6 ]. Both serological and DNA-based methods typically require high initial financial investments and specialised expertise to develop new assays, are limited in sample capacity, frequently are not reliable at the asymptomatic stage, and provide limited information beyond the species level [ 1 ]. The capacity to distinguish between individuals in a pathogen population with specific properties such as fungicide resistance, toxin production and virulence profiles is often essential to inform disease management approaches. In the past two decades, the genomics revolution has led to technologies that can rapidly generate genome-scale genetic information to define individual variants of a pathogen species [ 4 ]. These emerging, data-driven, PoC diagnostic tools have the potential to rapidly track shifting pathogen populations in near real-time, providing copious genetic information at the strain level that can be used in early warning systems and disease forecasting. The value of portable genomic-based diagnostics and surveillance was first illustrated during emergent human health outbreaks. For instance, during the Ebola crisis in West Africa in 2015, genome sequencing of the virus was carried out in situ on the first portable genome sequencer, the Oxford Nanopore Technologies MinION sequencer [ 7 ] . The resulting real-time genomic information on evolutionary rates and epidemiological trends revealed frequent transmission across the Guinea border [ 7 ], which informed subsequent disease control measures. For plant diseases, a similar approach in the laboratory environment successfully identified Plum pox virus and ‘ Candidatus Liberibacter asiaticus’, which causes citrus greening in infected insect and plant tissues [ 8 ], exemplifying the potential for the development of portable genomic-based diagnostics for plant health threats. However, for higher-order fungal pathogens which constitute the largest and most widely dispersed group of plant pathogens [ 9 ], the utility of mobile genomic-based PoC diagnostics remains to be fully realised. The sheer size of fungal genomes, which can be tens or even hundreds of thousands of times larger than viral genomes, makes full-genome or whole-transcriptome sequencing on portable sequencing devices currently prohibitively expensive. In this study, we developed an approach for generating high-throughput sequencing data in situ from the complex obligately biotrophic fungal pathogen Puccinia striiformis f. sp. tritici ( Pst ). Pst is a basidiomycete and heterokaryotic fungus that causes wheat yellow rust disease, which is a constant and significant threat to wheat production worldwide [ 10 ]. We demonstrate herein that our approach can be used to rapidly define individual Pst strains, assign strains to distinct genetic lineages that have been shown to correlate tightly with their virulence profiles [ 11 ], and monitor mutations in genes of importance. As Pst is an obligate biotroph, the genetic material of the pathogen and plant have to be analysed together in field-collected infected samples. Furthermore, the pathogen’s genome is more than 10,000 times larger than that of, for instance, the Ebola virus. To address these complexities, we first utilised a comparative genomics approach to define genomic regions of high variability between pathogen strains that could then be amplified for sequencing directly from field-infected wheat samples on the mobile nanopore sequencer. This new approach thereby circumvents the need to carry out lengthy in-lab processes of purification and multiplication of isolates prior to high molecular weight DNA extraction that is a requirement for full genome sequencing. This targeted sequencing approach also reduced the complexity and amount of data generated per sample,", "role": "user" }, { "content": "Scientists have created a new mobile surveillance technique to rapidly diagnose one of agriculture's oldest enemies—wheat rusts. Using a hand-held DNA sequencing device, they can define the precise strain of the wheat rust fungus in a farmer's field within just 48 hours of collecting samples. This gives researchers worldwide vital time needed to spot and control emerging epidemics. The wheat rust fungi have threatened wheat production almost since the dawn of agriculture and harvests in all major wheat growing areas worldwide remain under threat. The best defense is to grow wheat varieties resistant to infection, but over time, new strains of rust develop that lead to new epidemics. The best way to stay ahead of the rusts is to quickly identify and track the disease in the field. The paper, \"MARPLE, a point-of-care, strain-level disease diagnostics and surveillance tool for complex fungal pathogens,\" in BMC Biology shows how a research partnership reduced the speed of diagnostics from many months in high-end labs, to just 2 days from the side of an Ethiopian field. \"Knowing which strain you have, is critical information that can be incorporated into early warning systems and results in more effective control of disease outbreaks in farmer's fields\" said Dr. Dave Hodson, a rust pathologist at CIMMYT in Ethiopia and co-author. \"The challenge is that tracking the wheat rusts is not as simple as you would expect. There are many different strains, all with unique characteristics that cannot be told apart without lengthy in-lab tests. Consequently, identifying which ones are a threat can take many, many months, likely by which time the infection has spread.\" said Dr. Diane Saunders, lead author and Group Leader at the John Innes Centre. The new MARPLE (Mobile And Real-time PLant disEase) diagnostic platform the researchers created, targets parts of the rust genetic code that can be sequenced on the portable MinION sequencing platform from Oxford Nanopore. \"This helps us tell strains apart and quickly recognize those we've seen before or spot new ones that could be a new threat.\" said first author Dr. Guru Radhakrishnan from the John Innes Centre. \"What started as a proof of concept is now already being used in the field,\" said Dr. Saunders, \"this development will enable increased surveillance of crop disease pressure and more targeted control.\" Part of the challenge for wheat farmers is that they are in a constant game of cat and mouse with the disease. Knowing which wheat rust strains are in the local area can feed into advising which wheat varieties are safest to grow. \"Finally, with this project we can bring the latest technology to field sites to inform not just the researchers but also the farmers,\" said Tadessa Daba, Director, Agricultural Biotechnology Research Directorate, EIAR. Credit: John Innes Centre Saving time is not the only benefit, the MARPLE diagnostics method can also be carried out anywhere. Previously if researchers at field sites wanted to test a suspected infected sample, they would have to ship it to a handful of specialist labs frequently overseas. The MARPLE diagnostics method was formulated to operate directly in the field. This in itself can be challenging with intermittent electricity, no internet access in remote locations and a lack of refrigeration for lab reagents. Yet, if the pipeline was to function at these research stations, it needed to work despite these barriers. The new platform takes protocols that normally require a lot of equipment and expertise and brings it to a level where you require less facilities or specialist knowledge. \"We've tried to make as few cold chain elements as possible,\" said Ph.D. student and co-author Nicola Cook, \"with simple steps that you can perform with chemicals that are readily available locally,\" This combined speed and self-reliance allows in-country research groups to coordinate more closely with government ministries and national breeding programs which work to protect the local farmers. As a proof of principle, the entire platform from field sample to strain level result was conducted in Holeta, Ethiopia in September last year. The research group demonstrated the MARPLE diagnostics pipeline operating successfully beside a wheat field, from the back of a Landcruiser. \"I'm really highly impressed with this project,\" said Tesfaye Disasa, Director of Biosciences Institute, EIAR, \"it introduces new technology into the country as well as the capacity building it brings to the institute.\" For their work on creating the MARPLE platform, the team were awarded Innovator of the Year award for international impact from the Biotechnology and Biological Sciences Research Council in May this year. Following this award and through the support of the CGIAR Inspire challenge and the Delivering Genetic Gain in Wheat Project, a further four field stations across Ethiopia will be setup to use the MARPLE mobile lab. \"This is real national and international work that ultimately helps the resource-poor farmers\" said Dr. Badada Girima, Rust Pathologist, Delivering Genetic Gain in Wheat program. The paper outlines the steps that were taken to deliver this combined computational and experimental framework. It is hoped that by publishing this process, similar surveillance methods could be developed for other complex fungal pathogens that pose threats to plant, animal and human health. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Background Effective disease management depends on timely and accurate diagnosis to guide control measures. The capacity to distinguish between individuals in a pathogen population with specific properties such as fungicide resistance, toxin production and virulence profiles is often essential to inform disease management approaches. The genomics revolution has led to technologies that can rapidly produce high-resolution genotypic information to define individual variants of a pathogen species. However, their application to complex fungal pathogens has remained limited due to the frequent inability to culture these pathogens in the absence of their host and their large genome sizes. Results Here, we describe the development of Mobile And Real-time PLant disEase (MARPLE) diagnostics, a portable, genomics-based, point-of-care approach specifically tailored to identify individual strains of complex fungal plant pathogens. We used targeted sequencing to overcome limitations associated with the size of fungal genomes and their often obligately biotrophic nature. Focusing on the wheat yellow rust pathogen, Puccinia striiformis f.sp. tritici ( Pst ), we demonstrate that our approach can be used to rapidly define individual strains, assign strains to distinct genetic lineages that have been shown to correlate tightly with their virulence profiles and monitor genes of importance. Conclusions MARPLE diagnostics enables rapid identification of individual pathogen strains and has the potential to monitor those with specific properties such as fungicide resistance directly from field-collected infected plant tissue in situ. Generating results within 48 h of field sampling, this new strategy has far-reaching implications for tracking plant health threats. Background Rapid and accurate point-of-care (PoC) diagnostics facilitate early intervention during plant disease outbreaks and enable disease management decisions that limit the spread of plant health threats. PoC diagnostics involve portable equipment that can be used in-field to rapidly confirm disease outbreaks and provide actionable information [ 1 ]. At present, conventional plant disease diagnostics rely on visible inspections of disease symptoms followed by basic laboratory tests through culturing and pathogenicity assays [ 2 ]. Unfortunately, these conventional methods tend to be subjective, time-consuming, labour-intensive and reliant on specialised expertise and equipment, providing only limited phenotypic information [ 3 ]. These factors limit their utility in PoC diagnosis. Recent alternative approaches have focused on serological and nucleic acid assays [ 4 ]. Polyclonal and monoclonal antisera are frequently used to detect plant pathogens using techniques such as enzyme-linked immunosorbent assay (ELISA), immunostrip assays and immunoblotting [ 5 ]. In addition, following a flurry of PCR-based diagnostic tests in the 1980s, the advent of the loop-mediated isothermal amplification (LAMP) assay at the turn of the twenty-first century provided the first rapid nucleic acid amplification method to accurately diagnose pathogens in situ in real time [ 6 ]. Both serological and DNA-based methods typically require high initial financial investments and specialised expertise to develop new assays, are limited in sample capacity, frequently are not reliable at the asymptomatic stage, and provide limited information beyond the species level [ 1 ]. The capacity to distinguish between individuals in a pathogen population with specific properties such as fungicide resistance, toxin production and virulence profiles is often essential to inform disease management approaches. In the past two decades, the genomics revolution has led to technologies that can rapidly generate genome-scale genetic information to define individual variants of a pathogen species [ 4 ]. These emerging, data-driven, PoC diagnostic tools have the potential to rapidly track shifting pathogen populations in near real-time, providing copious genetic information at the strain level that can be used in early warning systems and disease forecasting. The value of portable genomic-based diagnostics and surveillance was first illustrated during emergent human health outbreaks. For instance, during the Ebola crisis in West Africa in 2015, genome sequencing of the virus was carried out in situ on the first portable genome sequencer, the Oxford Nanopore Technologies MinION sequencer [ 7 ] . The resulting real-time genomic information on evolutionary rates and epidemiological trends revealed frequent transmission across the Guinea border [ 7 ], which informed subsequent disease control measures. For plant diseases, a similar approach in the laboratory environment successfully identified Plum pox virus and ‘ Candidatus Liberibacter asiaticus’, which causes citrus greening in infected insect and plant tissues [ 8 ], exemplifying the potential for the development of portable genomic-based diagnostics for plant health threats. However, for higher-order fungal pathogens which constitute the largest and most widely dispersed group of plant pathogens [ 9 ], the utility of mobile genomic-based PoC diagnostics remains to be fully realised. The sheer size of fungal genomes, which can be tens or even hundreds of thousands of times larger than viral genomes, makes full-genome or whole-transcriptome sequencing on portable sequencing devices currently prohibitively expensive. In this study, we developed an approach for generating high-throughput sequencing data in situ from the complex obligately biotrophic fungal pathogen Puccinia striiformis f. sp. tritici ( Pst ). Pst is a basidiomycete and heterokaryotic fungus that causes wheat yellow rust disease, which is a constant and significant threat to wheat production worldwide [ 10 ]. We demonstrate herein that our approach can be used to rapidly define individual Pst strains, assign strains to distinct genetic lineages that have been shown to correlate tightly with their virulence profiles [ 11 ], and monitor mutations in genes of importance. As Pst is an obligate biotroph, the genetic material of the pathogen and plant have to be analysed together in field-collected infected samples. Furthermore, the pathogen’s genome is more than 10,000 times larger than that of, for instance, the Ebola virus. To address these complexities, we first utilised a comparative genomics approach to define genomic regions of high variability between pathogen strains that could then be amplified for sequencing directly from field-infected wheat samples on the mobile nanopore sequencer. This new approach thereby circumvents the need to carry out lengthy in-lab processes of purification and multiplication of isolates prior to high molecular weight DNA extraction that is a requirement for full genome sequencing. This targeted sequencing approach also reduced the complexity and amount of data generated per sample,<|im_end|> <|im_start|>assistant Scientists have created a new mobile surveillance technique to rapidly diagnose one of agriculture's oldest enemies—wheat rusts. Using a hand-held DNA sequencing device, they can define the precise strain of the wheat rust fungus in a farmer's field within just 48 hours of collecting samples. This gives researchers worldwide vital time needed to spot and control emerging epidemics. The wheat rust fungi have threatened wheat production almost since the dawn of agriculture and harvests in all major wheat growing areas worldwide remain under threat. The best defense is to grow wheat varieties resistant to infection, but over time, new strains of rust develop that lead to new epidemics. The best way to stay ahead of the rusts is to quickly identify and track the disease in the field. The paper, "MARPLE, a point-of-care, strain-level disease diagnostics and surveillance tool for complex fungal pathogens," in BMC Biology shows how a research partnership reduced the speed of diagnostics from many months in high-end labs, to just 2 days from the side of an Ethiopian field. "Knowing which strain you have, is critical information that can be incorporated into early warning systems and results in more effective control of disease outbreaks in farmer's fields" said Dr. Dave Hodson, a rust pathologist at CIMMYT in Ethiopia and co-author. "The challenge is that tracking the wheat rusts is not as simple as you would expect. There are many different strains, all with unique characteristics that cannot be told apart without lengthy in-lab tests. Consequently, identifying which ones are a threat can take many, many months, likely by which time the infection has spread." said Dr. Diane Saunders, lead author and Group Leader at the John Innes Centre. The new MARPLE (Mobile And Real-time PLant disEase) diagnostic platform the researchers created, targets parts of the rust genetic code that can be sequenced on the portable MinION sequencing platform from Oxford Nanopore. "This helps us tell strains apart and quickly recognize those we've seen before or spot new ones that could be a new threat." said first author Dr. Guru Radhakrishnan from the John Innes Centre. "What started as a proof of concept is now already being used in the field," said Dr. Saunders, "this development will enable increased surveillance of crop disease pressure and more targeted control." Part of the challenge for wheat farmers is that they are in a constant game of cat and mouse with the disease. Knowing which wheat rust strains are in the local area can feed into advising which wheat varieties are safest to grow. "Finally, with this project we can bring the latest technology to field sites to inform not just the researchers but also the farmers," said Tadessa Daba, Director, Agricultural Biotechnology Research Directorate, EIAR. Credit: John Innes Centre Saving time is not the only benefit, the MARPLE diagnostics method can also be carried out anywhere. Previously if researchers at field sites wanted to test a suspected infected sample, they would have to ship it to a handful of specialist labs frequently overseas. The MARPLE diagnostics method was formulated to operate directly in the field. This in itself can be challenging with intermittent electricity, no internet access in remote locations and a lack of refrigeration for lab reagents. Yet, if the pipeline was to function at these research stations, it needed to work despite these barriers. The new platform takes protocols that normally require a lot of equipment and expertise and brings it to a level where you require less facilities or specialist knowledge. "We've tried to make as few cold chain elements as possible," said Ph.D. student and co-author Nicola Cook, "with simple steps that you can perform with chemicals that are readily available locally," This combined speed and self-reliance allows in-country research groups to coordinate more closely with government ministries and national breeding programs which work to protect the local farmers. As a proof of principle, the entire platform from field sample to strain level result was conducted in Holeta, Ethiopia in September last year. The research group demonstrated the MARPLE diagnostics pipeline operating successfully beside a wheat field, from the back of a Landcruiser. "I'm really highly impressed with this project," said Tesfaye Disasa, Director of Biosciences Institute, EIAR, "it introduces new technology into the country as well as the capacity building it brings to the institute." For their work on creating the MARPLE platform, the team were awarded Innovator of the Year award for international impact from the Biotechnology and Biological Sciences Research Council in May this year. Following this award and through the support of the CGIAR Inspire challenge and the Delivering Genetic Gain in Wheat Project, a further four field stations across Ethiopia will be setup to use the MARPLE mobile lab. "This is real national and international work that ultimately helps the resource-poor farmers" said Dr. Badada Girima, Rust Pathologist, Delivering Genetic Gain in Wheat program. The paper outlines the steps that were taken to deliver this combined computational and experimental framework. It is hoped that by publishing this process, similar surveillance methods could be developed for other complex fungal pathogens that pose threats to plant, animal and human health. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 25837, 48023, 8624, 6373, 14117, 389, 32100, 323, 13687, 23842, 311, 8641, 2585, 11193, 13, 578, 8824, 311, 33137, 1990, 7931, 304, 264, 1853, 11968, 7187, 449, 3230, 6012, 1778, 439, 34698, 14842, 13957, 11, 98534, 5788, 323, 9043, 59566, 21542, 374, 3629, 7718, 311, 6179, 8624, 6373, 20414, 13, 578, 4173, 24203, 14110, 706, 6197, 311, 14645, 430, 649, 19019, 8356, 1579, 64036, 4173, 37941, 292, 2038, 311, 7124, 3927, 27103, 315, 264, 1853, 11968, 9606, 13, 4452, 11, 872, 3851, 311, 6485, 95447, 78284, 706, 14958, 7347, 4245, 311, 279, 21420, 38550, 311, 7829, 1521, 78284, 304, 279, 19821, 315, 872, 3552, 323, 872, 3544, 33869, 12562, 13, 18591, 5810, 11, 584, 7664, 279, 4500, 315, 13716, 1628, 8976, 7394, 10528, 519, 834, 69284, 320, 61761, 9705, 8, 50518, 11, 264, 23665, 11, 4173, 24203, 6108, 11, 1486, 8838, 41206, 5603, 11951, 41891, 311, 10765, 3927, 42400, 315, 6485, 95447, 6136, 78284, 13, 1226, 1511, 17550, 62119, 311, 23075, 9669, 5938, 449, 279, 1404, 315, 95447, 85381, 323, 872, 3629, 12611, 2718, 6160, 354, 42810, 7138, 13, 435, 87595, 389, 279, 34153, 14071, 23941, 1853, 11968, 11, 393, 14912, 91550, 6076, 7398, 285, 282, 8740, 13, 490, 275, 3457, 320, 393, 267, 7026, 584, 20461, 430, 1057, 5603, 649, 387, 1511, 311, 19019, 7124, 3927, 42400, 11, 9993, 42400, 311, 12742, 19465, 1584, 1154, 430, 617, 1027, 6982, 311, 81584, 40069, 449, 872, 9043, 59566, 21542, 323, 8891, 21389, 315, 12939, 13, 1221, 24436, 38599, 9705, 50518, 20682, 11295, 22654, 315, 3927, 1853, 11968, 42400, 323, 706, 279, 4754, 311, 8891, 1884, 449, 3230, 6012, 1778, 439, 34698, 14842, 13957, 6089, 505, 2115, 20024, 2258, 29374, 6136, 20438, 304, 10109, 13, 97554, 3135, 2949, 220, 2166, 305, 315, 2115, 25936, 11, 420, 502, 8446, 706, 3117, 87248, 25127, 369, 15194, 6136, 2890, 18208, 13, 25837, 48090, 323, 13687, 1486, 8838, 41206, 320, 34004, 34, 8, 50518, 28696, 4216, 21623, 2391, 6136, 8624, 77871, 323, 7431, 8624, 6373, 11429, 430, 4017, 279, 9041, 315, 6136, 2890, 18208, 13, 14128, 34, 50518, 21736, 23665, 7241, 430, 649, 387, 1511, 304, 19677, 311, 19019, 7838, 8624, 77871, 323, 3493, 92178, 2038, 510, 220, 16, 21087, 2468, 3118, 11, 21349, 6136, 8624, 50518, 17631, 389, 9621, 58074, 315, 8624, 13803, 8272, 555, 6913, 27692, 7177, 1555, 4612, 1711, 323, 1853, 29569, 488, 99592, 510, 220, 17, 21087, 19173, 11, 1521, 21349, 5528, 8541, 311, 387, 44122, 11, 892, 70840, 11, 23791, 88092, 323, 89227, 389, 89004, 19248, 323, 7241, 11, 8405, 1193, 7347, 14345, 37941, 292, 2038, 510, 220, 18, 21087, 4314, 9547, 4017, 872, 15919, 304, 14128, 34, 23842, 13, 35390, 10778, 20414, 617, 10968, 389, 1446, 5848, 323, 31484, 292, 13935, 99592, 510, 220, 19, 21087, 3735, 6310, 25180, 323, 96157, 12490, 278, 65617, 2473, 527, 14134, 1511, 311, 11388, 6136, 78284, 1701, 12823, 1778, 439, 49242, 55514, 33119, 437, 30986, 306, 65033, 320, 2818, 35301, 705, 33119, 537, 4664, 99592, 323, 33119, 677, 9363, 1303, 510, 220, 20, 21087, 763, 5369, 11, 2768, 264, 88563, 315, 67791, 6108, 15439, 7177, 304, 279, 220, 3753, 15, 82, 11, 279, 11599, 315, 279, 6471, 82076, 374, 91096, 23201, 2461, 320, 43, 16407, 8, 65033, 520, 279, 2543, 315, 279, 17510, 38043, 9478, 3984, 279, 1176, 11295, 31484, 292, 13935, 23201, 2461, 1749, 311, 30357, 58681, 78284, 304, 10109, 304, 1972, 892, 510, 220, 21, 21087, 11995, 1446, 5848, 323, 15922, 6108, 5528, 11383, 1397, 1579, 2926, 6020, 22538, 323, 89004, 19248, 311, 2274, 502, 99592, 11, 527, 7347, 304, 6205, 8824, 11, 14134, 527, 539, 15062, 520, 279, 97354, 13795, 6566, 11, 323, 3493, 7347, 2038, 7953, 279, 9606, 2237, 510, 220, 16, 21087, 578, 8824, 311, 33137, 1990, 7931, 304, 264, 1853, 11968, 7187, 449, 3230, 6012, 1778, 439, 34698, 14842, 13957, 11, 98534, 5788, 323, 9043, 59566, 21542, 374, 3629, 7718, 311, 6179, 8624, 6373, 20414, 13, 763, 279, 3347, 1403, 11026, 11, 279, 4173, 24203, 14110, 706, 6197, 311, 14645, 430, 649, 19019, 7068, 33869, 13230, 19465, 2038, 311, 7124, 3927, 27103, 315, 264, 1853, 11968, 9606, 510, 220, 19, 21087, 4314, 24084, 11, 828, 32505, 11, 14128, 34, 15439, 7526, 617, 279, 4754, 311, 19019, 3839, 32931, 1853, 11968, 22673, 304, 3221, 1972, 7394, 11, 8405, 6293, 1245, 19465, 2038, 520, 279, 26800, 2237, 430, 649, 387, 1511, 304, 4216, 10163, 6067, 323, 8624, 79482, 13, 578, 907, 315, 23665, 81064, 6108, 50518, 323, 22156, 574, 1176, 36762, 2391, 7425, 306, 3823, 2890, 77871, 13, 1789, 2937, 11, 2391, 279, 48082, 11501, 304, 4410, 10384, 304, 220, 679, 20, 11, 33869, 62119, 315, 279, 17188, 574, 11953, 704, 304, 10109, 389, 279, 1176, 23665, 33869, 11506, 20099, 11, 279, 26275, 33242, 454, 461, 25579, 3468, 1294, 11506, 20099, 510, 220, 22, 2331, 662, 578, 13239, 1972, 7394, 81064, 2038, 389, 41993, 7969, 323, 62057, 5848, 18845, 10675, 21420, 18874, 4028, 279, 48903, 3973, 510, 220, 22, 10881, 902, 16369, 17876, 8624, 2585, 11193, 13, 1789, 6136, 19338, 11, 264, 4528, 5603, 304, 279, 27692, 4676, 7946, 11054, 84409, 3273, 87, 17188, 323, 3451, 94916, 1015, 95397, 581, 2540, 47731, 780, 355, 20182, 902, 11384, 60290, 2886, 6147, 304, 29374, 27080, 323, 6136, 39881, 510, 220, 23, 10881, 39039, 7922, 279, 4754, 369, 279, 4500, 315, 23665, 81064, 6108, 50518, 369, 6136, 2890, 18208, 13, 4452, 11, 369, 5190, 24747, 95447, 78284, 902, 35256, 279, 7928, 323, 1455, 13882, 77810, 1912, 315, 6136, 78284, 510, 220, 24, 10881, 279, 15919, 315, 6505, 81064, 6108, 14128, 34, 50518, 8625, 311, 387, 7373, 41193, 13, 578, 33638, 1404, 315, 95447, 85381, 11, 902, 649, 387, 22781, 477, 1524, 11758, 315, 9214, 315, 3115, 8294, 1109, 29962, 85381, 11, 3727, 2539, 37564, 638, 477, 4459, 39160, 1250, 638, 62119, 389, 23665, 62119, 7766, 5131, 48486, 3210, 11646, 13, 763, 420, 4007, 11, 584, 8040, 459, 5603, 369, 24038, 1579, 43847, 631, 62119, 828, 304, 10109, 505, 279, 6485, 12611, 2718, 6160, 354, 42810, 95447, 1853, 11968, 393, 14912, 91550, 6076, 7398, 285, 282, 13, 993, 13, 490, 275, 3457, 320, 393, 267, 7609, 393, 267, 374, 264, 3122, 12558, 316, 3418, 7870, 323, 30548, 564, 661, 14546, 79902, 430, 11384, 34153, 14071, 23941, 8624, 11, 902, 374, 264, 6926, 323, 5199, 6023, 311, 34153, 5788, 15603, 510, 220, 605, 21087, 1226, 20461, 36881, 430, 1057, 5603, 649, 387, 1511, 311, 19019, 7124, 3927, 393, 267, 42400, 11, 9993, 42400, 311, 12742, 19465, 1584, 1154, 430, 617, 1027, 6982, 311, 81584, 40069, 449, 872, 9043, 59566, 21542, 510, 220, 806, 10881, 323, 8891, 34684, 304, 21389, 315, 12939, 13, 1666, 393, 267, 374, 459, 12611, 349, 6160, 354, 22761, 11, 279, 19465, 3769, 315, 279, 1853, 11968, 323, 6136, 617, 311, 387, 67458, 3871, 304, 2115, 20024, 2258, 29374, 10688, 13, 24296, 11, 279, 1853, 11968, 753, 33869, 374, 810, 1109, 220, 605, 11, 931, 3115, 8294, 1109, 430, 315, 11, 369, 2937, 11, 279, 48082, 17188, 13, 2057, 2686, 1521, 84140, 11, 584, 1176, 4186, 4147, 264, 55394, 4173, 24203, 5603, 311, 7124, 81064, 13918, 315, 1579, 54709, 1990, 1853, 11968, 42400, 430, 1436, 1243, 387, 83598, 369, 62119, 6089, 505, 2115, 48336, 1599, 34153, 10688, 389, 279, 6505, 76307, 461, 11506, 20099, 13, 1115, 502, 5603, 28592, 10408, 48764, 279, 1205, 311, 6920, 704, 35306, 304, 2922, 370, 11618, 315, 94536, 323, 47544, 315, 13399, 988, 4972, 311, 1579, 31206, 4785, 15922, 33289, 430, 374, 264, 16686, 369, 2539, 33869, 62119, 13, 1115, 17550, 62119, 5603, 1101, 11293, 279, 23965, 323, 3392, 315, 828, 8066, 824, 6205, 11, 128257, 198, 128256, 78191, 198, 72326, 617, 3549, 264, 502, 6505, 22156, 15105, 311, 19019, 58681, 832, 315, 30029, 596, 24417, 14207, 2345, 86, 20559, 23941, 82, 13, 12362, 264, 1450, 58606, 15922, 62119, 3756, 11, 814, 649, 7124, 279, 24473, 26800, 315, 279, 34153, 23941, 79902, 304, 264, 37500, 596, 2115, 2949, 1120, 220, 2166, 4207, 315, 26984, 10688, 13, 1115, 6835, 12074, 15603, 16595, 892, 4460, 311, 7858, 323, 2585, 24084, 28817, 38305, 13, 578, 34153, 23941, 81540, 617, 21699, 34153, 5788, 4661, 2533, 279, 39493, 315, 30029, 323, 24322, 82, 304, 682, 3682, 34153, 7982, 5789, 15603, 7293, 1234, 6023, 13, 578, 1888, 9232, 374, 311, 3139, 34153, 36680, 31785, 311, 19405, 11, 719, 927, 892, 11, 502, 42400, 315, 23941, 2274, 430, 3063, 311, 502, 28817, 38305, 13, 578, 1888, 1648, 311, 4822, 8469, 315, 279, 23941, 82, 374, 311, 6288, 10765, 323, 3839, 279, 8624, 304, 279, 2115, 13, 578, 5684, 11, 330, 61761, 9705, 11, 264, 1486, 8838, 41206, 11, 26800, 11852, 8624, 50518, 323, 22156, 5507, 369, 6485, 95447, 78284, 1359, 304, 82806, 40023, 5039, 1268, 264, 3495, 15664, 11293, 279, 4732, 315, 50518, 505, 1690, 4038, 304, 1579, 13368, 51048, 11, 311, 1120, 220, 17, 2919, 505, 279, 3185, 315, 459, 96634, 2115, 13, 330, 96621, 902, 26800, 499, 617, 11, 374, 9200, 2038, 430, 649, 387, 32762, 1139, 4216, 10163, 6067, 323, 3135, 304, 810, 7524, 2585, 315, 8624, 77871, 304, 37500, 596, 5151, 1, 1071, 2999, 13, 20851, 52034, 942, 11, 264, 23941, 1853, 16549, 520, 83464, 19708, 51, 304, 60457, 323, 1080, 43802, 13, 330, 791, 8815, 374, 430, 15194, 279, 34153, 23941, 82, 374, 539, 439, 4382, 439, 499, 1053, 1755, 13, 2684, 527, 1690, 2204, 42400, 11, 682, 449, 5016, 17910, 430, 4250, 387, 3309, 10980, 2085, 35306, 304, 2922, 370, 7177, 13, 53123, 11, 25607, 902, 6305, 527, 264, 6023, 649, 1935, 1690, 11, 1690, 4038, 11, 4461, 555, 902, 892, 279, 19405, 706, 9041, 1210, 1071, 2999, 13, 54190, 78317, 11, 3063, 3229, 323, 5856, 23896, 520, 279, 3842, 763, 4978, 14821, 13, 578, 502, 38599, 9705, 320, 18876, 1628, 8976, 7394, 10528, 519, 834, 69284, 8, 15439, 5452, 279, 12074, 3549, 11, 11811, 5596, 315, 279, 23941, 19465, 2082, 430, 649, 387, 11506, 5886, 389, 279, 23665, 3468, 1294, 62119, 5452, 505, 26275, 33242, 454, 461, 13, 330, 2028, 8779, 603, 3371, 42400, 10980, 323, 6288, 15641, 1884, 584, 3077, 3970, 1603, 477, 7858, 502, 6305, 430, 1436, 387, 264, 502, 6023, 1210, 1071, 1176, 3229, 2999, 13, 63079, 21254, 71, 587, 95007, 19285, 505, 279, 3842, 763, 4978, 14821, 13, 330, 3923, 3940, 439, 264, 11311, 315, 7434, 374, 1457, 2736, 1694, 1511, 304, 279, 2115, 1359, 1071, 2999, 13, 78317, 11, 330, 576, 4500, 690, 7431, 7319, 22156, 315, 19641, 8624, 7410, 323, 810, 17550, 2585, 1210, 3744, 315, 279, 8815, 369, 34153, 20957, 374, 430, 814, 527, 304, 264, 6926, 1847, 315, 8415, 323, 8814, 449, 279, 8624, 13, 58733, 902, 34153, 23941, 42400, 527, 304, 279, 2254, 3158, 649, 5510, 1139, 63779, 902, 34153, 36680, 527, 62844, 311, 3139, 13, 330, 24901, 11, 449, 420, 2447, 584, 649, 4546, 279, 5652, 5557, 311, 2115, 6732, 311, 6179, 539, 1120, 279, 12074, 719, 1101, 279, 20957, 1359, 1071, 350, 329, 26577, 423, 12273, 11, 10783, 11, 60134, 12371, 52536, 8483, 94466, 11, 93911, 946, 13, 16666, 25, 3842, 763, 4978, 14821, 49538, 892, 374, 539, 279, 1193, 8935, 11, 279, 38599, 9705, 50518, 1749, 649, 1101, 387, 11953, 704, 12660, 13, 59787, 422, 12074, 520, 2115, 6732, 4934, 311, 1296, 264, 24740, 29374, 6205, 11, 814, 1053, 617, 311, 8448, 433, 311, 264, 23810, 315, 24687, 51048, 14134, 25355, 13, 578, 38599, 9705, 50518, 1749, 574, 60394, 311, 14816, 6089, 304, 279, 2115, 13, 1115, 304, 5196, 649, 387, 17436, 449, 75568, 18200, 11, 912, 7757, 2680, 304, 8870, 10687, 323, 264, 6996, 315, 30477, 367, 369, 10278, 312, 55975, 13, 14968, 11, 422, 279, 15660, 574, 311, 734, 520, 1521, 3495, 17789, 11, 433, 4460, 311, 990, 8994, 1521, 30740, 13, 578, 502, 5452, 5097, 32885, 430, 14614, 1397, 264, 2763, 315, 7241, 323, 19248, 323, 12716, 433, 311, 264, 2237, 1405, 499, 1397, 2753, 13077, 477, 24687, 6677, 13, 330, 1687, 3077, 6818, 311, 1304, 439, 2478, 9439, 8957, 5540, 439, 3284, 1359, 1071, 2405, 920, 13, 5575, 323, 1080, 43802, 79541, 12797, 11, 330, 4291, 4382, 7504, 430, 499, 649, 2804, 449, 26333, 430, 527, 31368, 2561, 24392, 1359, 1115, 11093, 4732, 323, 659, 5621, 747, 685, 6276, 304, 56971, 3495, 5315, 311, 16580, 810, 15499, 449, 3109, 90124, 323, 5426, 40308, 7620, 902, 990, 311, 6144, 279, 2254, 20957, 13, 1666, 264, 11311, 315, 17966, 11, 279, 4553, 5452, 505, 2115, 6205, 311, 26800, 2237, 1121, 574, 13375, 304, 17723, 49251, 11, 60457, 304, 6250, 1566, 1060, 13, 578, 3495, 1912, 21091, 279, 38599, 9705, 50518, 15660, 10565, 7946, 30488, 264, 34153, 2115, 11, 505, 279, 1203, 315, 264, 11680, 66, 2739, 12329, 13, 330, 40, 2846, 2216, 7701, 25408, 449, 420, 2447, 1359, 1071, 23971, 69, 61055, 4185, 15790, 11, 10783, 315, 77948, 5979, 2436, 10181, 11, 93911, 946, 11, 330, 275, 40019, 502, 5557, 1139, 279, 3224, 439, 1664, 439, 279, 8824, 4857, 433, 12716, 311, 279, 44798, 1210, 1789, 872, 990, 389, 6968, 279, 38599, 9705, 5452, 11, 279, 2128, 1051, 22034, 55947, 859, 315, 279, 9941, 10292, 369, 6625, 5536, 505, 279, 12371, 52536, 323, 63711, 23199, 8483, 9251, 304, 3297, 420, 1060, 13, 23548, 420, 10292, 323, 1555, 279, 1862, 315, 279, 64527, 946, 31016, 556, 8815, 323, 279, 65752, 287, 75226, 50809, 304, 56738, 5907, 11, 264, 4726, 3116, 2115, 17789, 4028, 60457, 690, 387, 6642, 311, 1005, 279, 38599, 9705, 6505, 10278, 13, 330, 2028, 374, 1972, 5426, 323, 6625, 990, 430, 13967, 8779, 279, 5211, 2320, 10922, 20957, 1, 1071, 2999, 13, 11717, 2649, 48035, 7675, 11, 34889, 8092, 16549, 11, 65752, 287, 75226, 50809, 304, 56738, 2068, 13, 578, 5684, 50729, 279, 7504, 430, 1051, 4529, 311, 6493, 420, 11093, 55580, 323, 22772, 12914, 13, 1102, 374, 26253, 430, 555, 23763, 420, 1920, 11, 4528, 22156, 5528, 1436, 387, 8040, 369, 1023, 6485, 95447, 78284, 430, 17477, 18208, 311, 6136, 11, 10065, 323, 3823, 2890, 13, 220, 128257, 198 ]

2,343

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Intestinal microbiota metabolism of choline and phosphatidylcholine produces trimethylamine (TMA), which is further metabolized to a proatherogenic species, trimethylamine- N -oxide (TMAO). We demonstrate here that metabolism by intestinal microbiota of dietary l -carnitine, a trimethylamine abundant in red meat, also produces TMAO and accelerates atherosclerosis in mice. Omnivorous human subjects produced more TMAO than did vegans or vegetarians following ingestion of l -carnitine through a microbiota-dependent mechanism. The presence of specific bacterial taxa in human feces was associated with both plasma TMAO concentration and dietary status. Plasma l -carnitine levels in subjects undergoing cardiac evaluation ( n = 2,595) predicted increased risks for both prevalent cardiovascular disease (CVD) and incident major adverse cardiac events (myocardial infarction, stroke or death), but only among subjects with concurrently high TMAO levels. Chronic dietary l -carnitine supplementation in mice altered cecal microbial composition, markedly enhanced synthesis of TMA and TMAO, and increased atherosclerosis, but this did not occur if intestinal microbiota was concurrently suppressed. In mice with an intact intestinal microbiota, dietary supplementation with TMAO or either carnitine or choline reduced in vivo reverse cholesterol transport. Intestinal microbiota may thus contribute to the well-established link between high levels of red meat consumption and CVD risk. Main The high level of meat consumption in the developed world is linked to CVD risk, presumably owing to the large content of saturated fats and cholesterol in meat 1 , 2 . However, a recent meta-analysis of prospective cohort studies showed no association between dietary saturated fat intake and CVD, prompting the suggestion that other environmental exposures linked to increased meat consumption are responsible 3 . In fact, the suspicion that the cholesterol and saturated fat content of red meat may not be sufficiently high enough to account for the observed association between CVD and meat consumption has stimulated investigation of alternative disease-promoting exposures that accompany dietary meat ingestion, such as high salt content or heterocyclic compounds generated during cooking 4 , 5 . To our knowledge, no studies have yet explored the participation of commensal intestinal microbiota in modifying the diet-host interaction with reference to red meat consumption. The microbiota of humans has been linked to intestinal health, immune function, bioactivation of nutrients and vitamins, and, more recently, complex disease phenotypes such as obesity and insulin resistance 6 , 7 , 8 . We recently reported a pathway in both humans and mice linking microbiota metabolism of dietary choline and phosphatidylcholine to CVD pathogenesis 9 . Choline, a trimethylamine-containing compound and part of the head group of phosphatidylcholine, is metabolized by gut microbiota to produce an intermediate compound known as TMA ( Fig. 1a ). TMA is rapidly further oxidized by hepatic flavin monooxygenases to form TMAO, which is proatherogenic and associated with cardiovascular risks. These findings raise the possibility that other dietary nutrients possessing a trimethylamine structure may also generate TMAO from gut microbiota and promote accelerated atherosclerosis. TMAO has been proposed to induce upregulation of macrophage scavenger receptors and thereby potentially contribute to enhanced “forward cholesterol transport.” 10 . Whether TMAO is linked to the development of accelerated atherosclerosis through additional mechanisms, and which specific microbial species contribute to TMAO formation, have not been fully clarified. Figure 1: TMAO production from l -carnitine is a microbiota-dependent process in humans. ( a ) Structure of carnitine and scheme of carnitine and choline metabolism to TMAO. l -Carnitine and choline are both dietary trimethylamines that can be metabolized by microbiota to TMA. TMA is then further oxidized to TMAO by flavin monooxygenases (FMOs). ( b ) Scheme of the human l -carnitine challenge test. After a 12-h overnight fast, subjects received a capsule of d3-(methyl)-carnitine (250 mg) alone, or in some cases (as in data for the subject shown) also an 8-ounce steak (estimated 180 mg l -carnitine), whereupon serial plasma and 24-h urine samples were obtained for TMA and TMAO analyses (visit 1). After a weeklong regimen of oral broad-spectrum antibiotics to suppress the intestinal microbiota, the challenge was repeated (visit 2), and then again a final third time after a ≥3-week period to permit repopulation of intestinal microbiota (visit 3). ( c , d ) LC-MS/MS chromatograms of plasma TMAO ( c ) and d3-TMAO ( d ) in an omnivorous subject using specific precursor → product ion transitions indicated at t = 8 h for each visit. ( e ) Stable-isotope-dilution LC-MS/MS time course measurements of d3-labeled TMAO and carnitine in plasma collected from sequential venous blood draws at the indicated time points. Data shown in c – e are from a representative female omnivorous subject who underwent carnitine challenge. Data are organized vertically to correspond with the visit schedule indicated in b . Full size image l -carnitine is an abundant nutrient in red meat and contains a trimethylamine structure similar to that of choline ( Fig. 1a ). Although dietary ingestion is a major source of l -carnitine in omnivores, it is also endogenously produced in mammals from lysine and serves an essential function in transporting fatty acids into the mitochondrial compartment 10 , 11 . l -Carnitine ingestion and supplementation in industrialized societies have markedly increased 12 . Whether there are potential health risks associated with the rapidly growing practice of consuming l -carnitine supplements has not been evaluated. Herein we examine the gut microbiota–dependent metabolism of l -carnitine to produce TMAO in both rodents and humans (omnivores and vegans or vegetarians). Using isotope tracer studies in humans, clinical studies to examine the effects on cardiovascular disease risk, and animal models including germ-free mice, we demonstrate a role for gut microbiota metabolism of l -carnitine in atherosclerosis pathogenesis. We show that TMAO, and its dietary precursors choline and carnitine, suppress reverse cholesterol transport (RCT) through gut microbiota–dependent mechanisms in vivo . Finally, we define microbial taxa in feces of humans whose proportions are associated with both dietary carnitine ingestion and plasma TMAO concentrations. We also show microbial compositional changes in mice associated with chronic carnitine ingestion and a consequent", "role": "user" }, { "content": "A compound abundant in red meat and added as a supplement to popular energy drinks has been found to promote atherosclerosis – or the hardening or clogging of the arteries – according to Cleveland Clinic research published online this week in the journal Nature Medicine. The study shows that bacteria living in the human digestive tract metabolize the compound carnitine, turning it into trimethylamine-N-oxide (TMAO), a metabolite the researchers previously linked in a 2011 study to the promotion of atherosclerosis in humans. Further, the research finds that a diet high in carnitine promotes the growth of the bacteria that metabolize carnitine, compounding the problem by producing even more of the artery-clogging TMAO. The research team was led by Stanley Hazen, M.D., Ph.D., Vice Chair of Translational Research for the Lerner Research Institute and section head of Preventive Cardiology & Rehabilitation in the Miller Family Heart and Vascular Institute at Cleveland Clinic, and Robert Koeth, a medical student at the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University. The study tested the carnitine and TMAO levels of omnivores, vegans and vegetarians, and examined the clinical data of 2,595 patients undergoing elective cardiac evaluations. They also examined the cardiac effects of a carnitine-enhanced diet in normal mice compared to mice with suppressed levels of gut microbes, and discovered that TMAO alters cholesterol metabolism at multiple levels, explaining how it enhances atherosclerosis. The researchers found that increased carnitine levels in patients predicted increased risks for cardiovascular disease and major cardiac events like heart attack, stroke and death, but only in subjects with concurrently high TMAO levels. Additionally, they found specific gut microbe types in subjects associated with both plasma TMAO levels and dietary patterns, and that baseline TMAO levels were significantly lower among vegans and vegetarians than omnivores. Remarkably, vegans and vegetarians, even after consuming a large amount of carnitine, did not produce significant levels of the microbe product TMAO, whereas omnivores consuming the same amount of carnitine did. \"The bacteria living in our digestive tracts are dictated by our long-term dietary patterns,\" Hazen said. \"A diet high in carnitine actually shifts our gut microbe composition to those that like carnitine, making meat eaters even more susceptible to forming TMAO and its artery-clogging effects. Meanwhile, vegans and vegetarians have a significantly reduced capacity to synthesize TMAO from carnitine, which may explain the cardiovascular health benefits of these diets.\" Prior research has shown that a diet with frequent red meat consumption is associated with increased cardiovascular disease risk, but that the cholesterol and saturated fat content in red meat does not appear to be enough to explain the increased cardiovascular risks. This discrepancy has been attributed to genetic differences, a high salt diet that is often associated with red meat consumption, and even possibly the cooking process, among other explanations. But Hazen says this new research suggests a new connection between red meat and cardiovascular disease. \"This process is different in everyone, depending on the gut microbe metabolism of the individual,\" he says. \"Carnitine metabolism suggests a new way to help explain why a diet rich in red meat promotes atherosclerosis.\" While carnitine is naturally occurring in red meats, including beef, venison, lamb, mutton, duck, and pork, it's also a dietary supplement available in pill form and a common ingredient in energy drinks. With this new research in mind, Hazen cautions that more research needs to be done to examine the safety of chronic carnitine supplementation. \"Carnitine is not an essential nutrient; our body naturally produces all we need,\" he says. \"We need to examine the safety of chronically consuming carnitine supplements as we've shown that, under some conditions, it can foster the growth of bacteria that produce TMAO and potentially clog arteries.\" This study is the latest in a line of research by Hazen and his colleagues exploring how gut microbes can contribute to atherosclerosis, uncovering new and unexpected pathways involved in heart disease. In a 2011 Nature study, they first discovered that people are not predisposed to cardiovascular disease solely because of their genetic make-up, but also based on how the micro-organisms in their digestive tracts metabolize lecithin, a compound with a structure similar to carnitine. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Intestinal microbiota metabolism of choline and phosphatidylcholine produces trimethylamine (TMA), which is further metabolized to a proatherogenic species, trimethylamine- N -oxide (TMAO). We demonstrate here that metabolism by intestinal microbiota of dietary l -carnitine, a trimethylamine abundant in red meat, also produces TMAO and accelerates atherosclerosis in mice. Omnivorous human subjects produced more TMAO than did vegans or vegetarians following ingestion of l -carnitine through a microbiota-dependent mechanism. The presence of specific bacterial taxa in human feces was associated with both plasma TMAO concentration and dietary status. Plasma l -carnitine levels in subjects undergoing cardiac evaluation ( n = 2,595) predicted increased risks for both prevalent cardiovascular disease (CVD) and incident major adverse cardiac events (myocardial infarction, stroke or death), but only among subjects with concurrently high TMAO levels. Chronic dietary l -carnitine supplementation in mice altered cecal microbial composition, markedly enhanced synthesis of TMA and TMAO, and increased atherosclerosis, but this did not occur if intestinal microbiota was concurrently suppressed. In mice with an intact intestinal microbiota, dietary supplementation with TMAO or either carnitine or choline reduced in vivo reverse cholesterol transport. Intestinal microbiota may thus contribute to the well-established link between high levels of red meat consumption and CVD risk. Main The high level of meat consumption in the developed world is linked to CVD risk, presumably owing to the large content of saturated fats and cholesterol in meat 1 , 2 . However, a recent meta-analysis of prospective cohort studies showed no association between dietary saturated fat intake and CVD, prompting the suggestion that other environmental exposures linked to increased meat consumption are responsible 3 . In fact, the suspicion that the cholesterol and saturated fat content of red meat may not be sufficiently high enough to account for the observed association between CVD and meat consumption has stimulated investigation of alternative disease-promoting exposures that accompany dietary meat ingestion, such as high salt content or heterocyclic compounds generated during cooking 4 , 5 . To our knowledge, no studies have yet explored the participation of commensal intestinal microbiota in modifying the diet-host interaction with reference to red meat consumption. The microbiota of humans has been linked to intestinal health, immune function, bioactivation of nutrients and vitamins, and, more recently, complex disease phenotypes such as obesity and insulin resistance 6 , 7 , 8 . We recently reported a pathway in both humans and mice linking microbiota metabolism of dietary choline and phosphatidylcholine to CVD pathogenesis 9 . Choline, a trimethylamine-containing compound and part of the head group of phosphatidylcholine, is metabolized by gut microbiota to produce an intermediate compound known as TMA ( Fig. 1a ). TMA is rapidly further oxidized by hepatic flavin monooxygenases to form TMAO, which is proatherogenic and associated with cardiovascular risks. These findings raise the possibility that other dietary nutrients possessing a trimethylamine structure may also generate TMAO from gut microbiota and promote accelerated atherosclerosis. TMAO has been proposed to induce upregulation of macrophage scavenger receptors and thereby potentially contribute to enhanced “forward cholesterol transport.” 10 . Whether TMAO is linked to the development of accelerated atherosclerosis through additional mechanisms, and which specific microbial species contribute to TMAO formation, have not been fully clarified. Figure 1: TMAO production from l -carnitine is a microbiota-dependent process in humans. ( a ) Structure of carnitine and scheme of carnitine and choline metabolism to TMAO. l -Carnitine and choline are both dietary trimethylamines that can be metabolized by microbiota to TMA. TMA is then further oxidized to TMAO by flavin monooxygenases (FMOs). ( b ) Scheme of the human l -carnitine challenge test. After a 12-h overnight fast, subjects received a capsule of d3-(methyl)-carnitine (250 mg) alone, or in some cases (as in data for the subject shown) also an 8-ounce steak (estimated 180 mg l -carnitine), whereupon serial plasma and 24-h urine samples were obtained for TMA and TMAO analyses (visit 1). After a weeklong regimen of oral broad-spectrum antibiotics to suppress the intestinal microbiota, the challenge was repeated (visit 2), and then again a final third time after a ≥3-week period to permit repopulation of intestinal microbiota (visit 3). ( c , d ) LC-MS/MS chromatograms of plasma TMAO ( c ) and d3-TMAO ( d ) in an omnivorous subject using specific precursor → product ion transitions indicated at t = 8 h for each visit. ( e ) Stable-isotope-dilution LC-MS/MS time course measurements of d3-labeled TMAO and carnitine in plasma collected from sequential venous blood draws at the indicated time points. Data shown in c – e are from a representative female omnivorous subject who underwent carnitine challenge. Data are organized vertically to correspond with the visit schedule indicated in b . Full size image l -carnitine is an abundant nutrient in red meat and contains a trimethylamine structure similar to that of choline ( Fig. 1a ). Although dietary ingestion is a major source of l -carnitine in omnivores, it is also endogenously produced in mammals from lysine and serves an essential function in transporting fatty acids into the mitochondrial compartment 10 , 11 . l -Carnitine ingestion and supplementation in industrialized societies have markedly increased 12 . Whether there are potential health risks associated with the rapidly growing practice of consuming l -carnitine supplements has not been evaluated. Herein we examine the gut microbiota–dependent metabolism of l -carnitine to produce TMAO in both rodents and humans (omnivores and vegans or vegetarians). Using isotope tracer studies in humans, clinical studies to examine the effects on cardiovascular disease risk, and animal models including germ-free mice, we demonstrate a role for gut microbiota metabolism of l -carnitine in atherosclerosis pathogenesis. We show that TMAO, and its dietary precursors choline and carnitine, suppress reverse cholesterol transport (RCT) through gut microbiota–dependent mechanisms in vivo . Finally, we define microbial taxa in feces of humans whose proportions are associated with both dietary carnitine ingestion and plasma TMAO concentrations. We also show microbial compositional changes in mice associated with chronic carnitine ingestion and a consequent<|im_end|> <|im_start|>assistant A compound abundant in red meat and added as a supplement to popular energy drinks has been found to promote atherosclerosis – or the hardening or clogging of the arteries – according to Cleveland Clinic research published online this week in the journal Nature Medicine. The study shows that bacteria living in the human digestive tract metabolize the compound carnitine, turning it into trimethylamine-N-oxide (TMAO), a metabolite the researchers previously linked in a 2011 study to the promotion of atherosclerosis in humans. Further, the research finds that a diet high in carnitine promotes the growth of the bacteria that metabolize carnitine, compounding the problem by producing even more of the artery-clogging TMAO. The research team was led by Stanley Hazen, M.D., Ph.D., Vice Chair of Translational Research for the Lerner Research Institute and section head of Preventive Cardiology & Rehabilitation in the Miller Family Heart and Vascular Institute at Cleveland Clinic, and Robert Koeth, a medical student at the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University. The study tested the carnitine and TMAO levels of omnivores, vegans and vegetarians, and examined the clinical data of 2,595 patients undergoing elective cardiac evaluations. They also examined the cardiac effects of a carnitine-enhanced diet in normal mice compared to mice with suppressed levels of gut microbes, and discovered that TMAO alters cholesterol metabolism at multiple levels, explaining how it enhances atherosclerosis. The researchers found that increased carnitine levels in patients predicted increased risks for cardiovascular disease and major cardiac events like heart attack, stroke and death, but only in subjects with concurrently high TMAO levels. Additionally, they found specific gut microbe types in subjects associated with both plasma TMAO levels and dietary patterns, and that baseline TMAO levels were significantly lower among vegans and vegetarians than omnivores. Remarkably, vegans and vegetarians, even after consuming a large amount of carnitine, did not produce significant levels of the microbe product TMAO, whereas omnivores consuming the same amount of carnitine did. "The bacteria living in our digestive tracts are dictated by our long-term dietary patterns," Hazen said. "A diet high in carnitine actually shifts our gut microbe composition to those that like carnitine, making meat eaters even more susceptible to forming TMAO and its artery-clogging effects. Meanwhile, vegans and vegetarians have a significantly reduced capacity to synthesize TMAO from carnitine, which may explain the cardiovascular health benefits of these diets." Prior research has shown that a diet with frequent red meat consumption is associated with increased cardiovascular disease risk, but that the cholesterol and saturated fat content in red meat does not appear to be enough to explain the increased cardiovascular risks. This discrepancy has been attributed to genetic differences, a high salt diet that is often associated with red meat consumption, and even possibly the cooking process, among other explanations. But Hazen says this new research suggests a new connection between red meat and cardiovascular disease. "This process is different in everyone, depending on the gut microbe metabolism of the individual," he says. "Carnitine metabolism suggests a new way to help explain why a diet rich in red meat promotes atherosclerosis." While carnitine is naturally occurring in red meats, including beef, venison, lamb, mutton, duck, and pork, it's also a dietary supplement available in pill form and a common ingredient in energy drinks. With this new research in mind, Hazen cautions that more research needs to be done to examine the safety of chronic carnitine supplementation. "Carnitine is not an essential nutrient; our body naturally produces all we need," he says. "We need to examine the safety of chronically consuming carnitine supplements as we've shown that, under some conditions, it can foster the growth of bacteria that produce TMAO and potentially clog arteries." This study is the latest in a line of research by Hazen and his colleagues exploring how gut microbes can contribute to atherosclerosis, uncovering new and unexpected pathways involved in heart disease. In a 2011 Nature study, they first discovered that people are not predisposed to cardiovascular disease solely because of their genetic make-up, but also based on how the micro-organisms in their digestive tracts metabolize lecithin, a compound with a structure similar to carnitine. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 1357, 65050, 53499, 6217, 39097, 315, 523, 22671, 323, 33088, 266, 307, 4010, 331, 22671, 19159, 11259, 42972, 20588, 320, 51, 4940, 705, 902, 374, 4726, 28168, 1534, 311, 264, 463, 1894, 29569, 9606, 11, 11259, 42972, 20588, 12, 452, 482, 55189, 320, 51, 4940, 46, 570, 1226, 20461, 1618, 430, 39097, 555, 63900, 53499, 6217, 315, 34625, 326, 482, 66, 1923, 275, 483, 11, 264, 11259, 42972, 20588, 44611, 304, 2579, 13339, 11, 1101, 19159, 350, 4940, 46, 323, 14511, 988, 264, 91882, 91711, 304, 24548, 13, 90934, 344, 20857, 3823, 15223, 9124, 810, 350, 4940, 46, 1109, 1550, 48438, 598, 477, 13294, 30627, 2768, 88447, 315, 326, 482, 66, 1923, 275, 483, 1555, 264, 53499, 6217, 43918, 17383, 13, 578, 9546, 315, 3230, 45964, 77314, 304, 3823, 55061, 288, 574, 5938, 449, 2225, 32426, 350, 4940, 46, 20545, 323, 34625, 2704, 13, 65632, 326, 482, 66, 1923, 275, 483, 5990, 304, 15223, 47397, 47345, 16865, 320, 308, 284, 220, 17, 11, 22754, 8, 19698, 7319, 15635, 369, 2225, 46941, 41713, 8624, 320, 34, 12757, 8, 323, 10672, 3682, 31959, 47345, 4455, 320, 2465, 74378, 532, 4225, 277, 407, 11, 12943, 477, 4648, 705, 719, 1193, 4315, 15223, 449, 79126, 1579, 350, 4940, 46, 5990, 13, 73782, 34625, 326, 482, 66, 1923, 275, 483, 73796, 304, 24548, 29852, 272, 98298, 75418, 18528, 11, 88101, 24872, 39975, 315, 350, 4940, 323, 350, 4940, 46, 11, 323, 7319, 264, 91882, 91711, 11, 719, 420, 1550, 539, 12446, 422, 63900, 53499, 6217, 574, 79126, 56089, 13, 763, 24548, 449, 459, 35539, 63900, 53499, 6217, 11, 34625, 73796, 449, 350, 4940, 46, 477, 3060, 39438, 275, 483, 477, 523, 22671, 11293, 304, 41294, 10134, 39086, 7710, 13, 1357, 65050, 53499, 6217, 1253, 8617, 17210, 311, 279, 1664, 64868, 2723, 1990, 1579, 5990, 315, 2579, 13339, 15652, 323, 356, 12757, 5326, 13, 4802, 578, 1579, 2237, 315, 13339, 15652, 304, 279, 8040, 1917, 374, 10815, 311, 356, 12757, 5326, 11, 36548, 56612, 311, 279, 3544, 2262, 315, 50585, 50127, 323, 39086, 304, 13339, 220, 16, 1174, 220, 17, 662, 4452, 11, 264, 3293, 8999, 56536, 315, 33547, 41944, 7978, 8710, 912, 15360, 1990, 34625, 50585, 8834, 23730, 323, 356, 12757, 11, 50745, 279, 24710, 430, 1023, 12434, 70530, 10815, 311, 7319, 13339, 15652, 527, 8647, 220, 18, 662, 763, 2144, 11, 279, 38141, 430, 279, 39086, 323, 50585, 8834, 2262, 315, 2579, 13339, 1253, 539, 387, 40044, 1579, 3403, 311, 2759, 369, 279, 13468, 15360, 1990, 356, 12757, 323, 13339, 15652, 706, 81471, 8990, 315, 10778, 8624, 66271, 11780, 70530, 430, 19780, 34625, 13339, 88447, 11, 1778, 439, 1579, 12290, 2262, 477, 30548, 511, 66404, 32246, 8066, 2391, 17677, 220, 19, 1174, 220, 20, 662, 2057, 1057, 6677, 11, 912, 7978, 617, 3686, 36131, 279, 20852, 315, 1081, 729, 278, 63900, 53499, 6217, 304, 47141, 279, 10173, 39689, 16628, 449, 5905, 311, 2579, 13339, 15652, 13, 578, 53499, 6217, 315, 12966, 706, 1027, 10815, 311, 63900, 2890, 11, 22852, 734, 11, 17332, 23863, 315, 37493, 323, 46192, 11, 323, 11, 810, 6051, 11, 6485, 8624, 14345, 22583, 1778, 439, 33048, 323, 32152, 13957, 220, 21, 1174, 220, 22, 1174, 220, 23, 662, 1226, 6051, 5068, 264, 38970, 304, 2225, 12966, 323, 24548, 31799, 53499, 6217, 39097, 315, 34625, 523, 22671, 323, 33088, 266, 307, 4010, 331, 22671, 311, 356, 12757, 1853, 52379, 220, 24, 662, 921, 22671, 11, 264, 11259, 42972, 20588, 93871, 24549, 323, 961, 315, 279, 2010, 1912, 315, 33088, 266, 307, 4010, 331, 22671, 11, 374, 28168, 1534, 555, 18340, 53499, 6217, 311, 8356, 459, 29539, 24549, 3967, 439, 350, 4940, 320, 23966, 13, 220, 16, 64, 7609, 350, 4940, 374, 19019, 4726, 36172, 1534, 555, 80445, 780, 18779, 258, 1647, 2689, 19472, 2315, 311, 1376, 350, 4940, 46, 11, 902, 374, 463, 1894, 29569, 323, 5938, 449, 41713, 15635, 13, 4314, 14955, 4933, 279, 13336, 430, 1023, 34625, 37493, 60662, 264, 11259, 42972, 20588, 6070, 1253, 1101, 7068, 350, 4940, 46, 505, 18340, 53499, 6217, 323, 12192, 49858, 264, 91882, 91711, 13, 350, 4940, 46, 706, 1027, 11223, 311, 49853, 709, 1610, 2987, 315, 18563, 764, 425, 83750, 10214, 44540, 323, 28592, 13893, 17210, 311, 24872, 1054, 13741, 39086, 7710, 2029, 220, 605, 662, 13440, 350, 4940, 46, 374, 10815, 311, 279, 4500, 315, 49858, 264, 91882, 91711, 1555, 5217, 24717, 11, 323, 902, 3230, 75418, 9606, 17210, 311, 350, 4940, 46, 18488, 11, 617, 539, 1027, 7373, 65876, 13, 19575, 220, 16, 25, 350, 4940, 46, 5788, 505, 326, 482, 66, 1923, 275, 483, 374, 264, 53499, 6217, 43918, 1920, 304, 12966, 13, 320, 264, 883, 29696, 315, 39438, 275, 483, 323, 13155, 315, 39438, 275, 483, 323, 523, 22671, 39097, 311, 350, 4940, 46, 13, 326, 482, 34, 1923, 275, 483, 323, 523, 22671, 527, 2225, 34625, 11259, 42972, 97081, 430, 649, 387, 28168, 1534, 555, 53499, 6217, 311, 350, 4940, 13, 350, 4940, 374, 1243, 4726, 36172, 1534, 311, 350, 4940, 46, 555, 18779, 258, 1647, 2689, 19472, 2315, 320, 37, 10754, 82, 570, 320, 293, 883, 44881, 315, 279, 3823, 326, 482, 66, 1923, 275, 483, 8815, 1296, 13, 4740, 264, 220, 717, 2902, 25402, 5043, 11, 15223, 4036, 264, 48739, 315, 294, 18, 8172, 76, 42972, 7435, 66, 1923, 275, 483, 320, 5154, 14060, 8, 7636, 11, 477, 304, 1063, 5157, 320, 300, 304, 828, 369, 279, 3917, 6982, 8, 1101, 459, 220, 23, 12, 9933, 50059, 320, 45329, 220, 5245, 14060, 326, 482, 66, 1923, 275, 483, 705, 1405, 59723, 6275, 32426, 323, 220, 1187, 2902, 40335, 10688, 1051, 12457, 369, 350, 4940, 323, 350, 4940, 46, 29060, 320, 28560, 220, 16, 570, 4740, 264, 2046, 4930, 68128, 315, 21308, 7353, 1355, 39806, 46850, 311, 28321, 279, 63900, 53499, 6217, 11, 279, 8815, 574, 11763, 320, 28560, 220, 17, 705, 323, 1243, 1578, 264, 1620, 4948, 892, 1306, 264, 63247, 18, 30609, 4261, 311, 11810, 2109, 454, 2987, 315, 63900, 53499, 6217, 320, 28560, 220, 18, 570, 320, 272, 1174, 294, 883, 31971, 12, 4931, 14, 4931, 98284, 56485, 315, 32426, 350, 4940, 46, 320, 272, 883, 323, 294, 18, 9469, 4940, 46, 320, 294, 883, 304, 459, 50197, 344, 20857, 3917, 1701, 3230, 71261, 11651, 2027, 28772, 34692, 16717, 520, 259, 284, 220, 23, 305, 369, 1855, 4034, 13, 320, 384, 883, 84441, 31530, 51782, 1773, 321, 1516, 31971, 12, 4931, 14, 4931, 892, 3388, 22323, 315, 294, 18, 2922, 23121, 350, 4940, 46, 323, 39438, 275, 483, 304, 32426, 14890, 505, 52100, 11457, 788, 6680, 27741, 520, 279, 16717, 892, 3585, 13, 2956, 6982, 304, 272, 1389, 384, 527, 505, 264, 18740, 8954, 50197, 344, 20857, 3917, 889, 55093, 39438, 275, 483, 8815, 13, 2956, 527, 17057, 52035, 311, 8024, 449, 279, 4034, 9899, 16717, 304, 293, 662, 8797, 1404, 2217, 326, 482, 66, 1923, 275, 483, 374, 459, 44611, 50123, 304, 2579, 13339, 323, 5727, 264, 11259, 42972, 20588, 6070, 4528, 311, 430, 315, 523, 22671, 320, 23966, 13, 220, 16, 64, 7609, 10541, 34625, 88447, 374, 264, 3682, 2592, 315, 326, 482, 66, 1923, 275, 483, 304, 50197, 344, 4692, 11, 433, 374, 1101, 842, 11968, 7162, 9124, 304, 56669, 505, 84495, 483, 323, 17482, 459, 7718, 734, 304, 67757, 40085, 33969, 1139, 279, 72061, 44598, 220, 605, 1174, 220, 806, 662, 326, 482, 34, 1923, 275, 483, 88447, 323, 73796, 304, 13076, 1534, 34775, 617, 88101, 7319, 220, 717, 662, 13440, 1070, 527, 4754, 2890, 15635, 5938, 449, 279, 19019, 7982, 6725, 315, 35208, 326, 482, 66, 1923, 275, 483, 33690, 706, 539, 1027, 26126, 13, 5810, 258, 584, 21635, 279, 18340, 53499, 6217, 4235, 38655, 39097, 315, 326, 482, 66, 1923, 275, 483, 311, 8356, 350, 4940, 46, 304, 2225, 94209, 323, 12966, 320, 316, 77, 344, 4692, 323, 48438, 598, 477, 13294, 30627, 570, 12362, 374, 51782, 65406, 7978, 304, 12966, 11, 14830, 7978, 311, 21635, 279, 6372, 389, 41713, 8624, 5326, 11, 323, 10065, 4211, 2737, 82986, 12862, 24548, 11, 584, 20461, 264, 3560, 369, 18340, 53499, 6217, 39097, 315, 326, 482, 66, 1923, 275, 483, 304, 264, 91882, 91711, 1853, 52379, 13, 1226, 1501, 430, 350, 4940, 46, 11, 323, 1202, 34625, 5956, 34291, 523, 22671, 323, 39438, 275, 483, 11, 28321, 10134, 39086, 7710, 320, 75936, 8, 1555, 18340, 53499, 6217, 4235, 38655, 24717, 304, 41294, 662, 17830, 11, 584, 7124, 75418, 77314, 304, 55061, 288, 315, 12966, 6832, 49892, 527, 5938, 449, 2225, 34625, 39438, 275, 483, 88447, 323, 32426, 350, 4940, 46, 32466, 13, 1226, 1101, 1501, 75418, 40321, 3079, 4442, 304, 24548, 5938, 449, 21249, 39438, 275, 483, 88447, 323, 264, 12777, 306, 128257, 198, 128256, 78191, 198, 32, 24549, 44611, 304, 2579, 13339, 323, 3779, 439, 264, 22822, 311, 5526, 4907, 21662, 706, 1027, 1766, 311, 12192, 264, 91882, 91711, 1389, 477, 279, 2653, 6147, 477, 272, 26330, 315, 279, 85648, 1389, 4184, 311, 24372, 40324, 3495, 4756, 2930, 420, 2046, 304, 279, 8486, 22037, 19152, 13, 578, 4007, 5039, 430, 24032, 5496, 304, 279, 3823, 60071, 42929, 28168, 553, 279, 24549, 39438, 275, 483, 11, 13353, 433, 1139, 11259, 42972, 20588, 11500, 12, 55189, 320, 51, 4940, 46, 705, 264, 28168, 635, 279, 12074, 8767, 10815, 304, 264, 220, 679, 16, 4007, 311, 279, 20862, 315, 264, 91882, 91711, 304, 12966, 13, 15903, 11, 279, 3495, 14035, 430, 264, 10173, 1579, 304, 39438, 275, 483, 39990, 279, 6650, 315, 279, 24032, 430, 28168, 553, 39438, 275, 483, 11, 1391, 13900, 279, 3575, 555, 17843, 1524, 810, 315, 279, 65415, 1824, 26330, 350, 4940, 46, 13, 578, 3495, 2128, 574, 6197, 555, 31552, 32595, 268, 11, 386, 920, 2637, 2405, 920, 2637, 23270, 16478, 315, 4149, 75, 1697, 8483, 369, 279, 445, 42472, 8483, 10181, 323, 3857, 2010, 315, 39168, 535, 6938, 31226, 612, 81318, 304, 279, 17472, 12517, 18449, 323, 650, 50804, 10181, 520, 24372, 40324, 11, 323, 8563, 30417, 774, 11, 264, 6593, 5575, 520, 279, 24372, 40324, 445, 42472, 9304, 315, 19152, 315, 11799, 11104, 25820, 3907, 13, 578, 4007, 12793, 279, 39438, 275, 483, 323, 350, 4940, 46, 5990, 315, 50197, 344, 4692, 11, 48438, 598, 323, 13294, 30627, 11, 323, 25078, 279, 14830, 828, 315, 220, 17, 11, 22754, 6978, 47397, 98590, 47345, 56181, 13, 2435, 1101, 25078, 279, 47345, 6372, 315, 264, 39438, 275, 483, 84182, 4979, 10173, 304, 4725, 24548, 7863, 311, 24548, 449, 56089, 5990, 315, 18340, 80727, 11, 323, 11352, 430, 350, 4940, 46, 88687, 39086, 39097, 520, 5361, 5990, 11, 26073, 1268, 433, 57924, 264, 91882, 91711, 13, 578, 12074, 1766, 430, 7319, 39438, 275, 483, 5990, 304, 6978, 19698, 7319, 15635, 369, 41713, 8624, 323, 3682, 47345, 4455, 1093, 4851, 3440, 11, 12943, 323, 4648, 11, 719, 1193, 304, 15223, 449, 79126, 1579, 350, 4940, 46, 5990, 13, 23212, 11, 814, 1766, 3230, 18340, 8162, 1395, 4595, 304, 15223, 5938, 449, 2225, 32426, 350, 4940, 46, 5990, 323, 34625, 12912, 11, 323, 430, 26954, 350, 4940, 46, 5990, 1051, 12207, 4827, 4315, 48438, 598, 323, 13294, 30627, 1109, 50197, 344, 4692, 13, 83833, 2915, 11, 48438, 598, 323, 13294, 30627, 11, 1524, 1306, 35208, 264, 3544, 3392, 315, 39438, 275, 483, 11, 1550, 539, 8356, 5199, 5990, 315, 279, 8162, 1395, 2027, 350, 4940, 46, 11, 20444, 50197, 344, 4692, 35208, 279, 1890, 3392, 315, 39438, 275, 483, 1550, 13, 330, 791, 24032, 5496, 304, 1057, 60071, 490, 11613, 527, 81498, 555, 1057, 1317, 9860, 34625, 12912, 1359, 32595, 268, 1071, 13, 330, 32, 10173, 1579, 304, 39438, 275, 483, 3604, 29735, 1057, 18340, 8162, 1395, 18528, 311, 1884, 430, 1093, 39438, 275, 483, 11, 3339, 13339, 8343, 388, 1524, 810, 47281, 311, 30164, 350, 4940, 46, 323, 1202, 65415, 1824, 26330, 6372, 13, 26982, 11, 48438, 598, 323, 13294, 30627, 617, 264, 12207, 11293, 8824, 311, 6925, 27985, 350, 4940, 46, 505, 39438, 275, 483, 11, 902, 1253, 10552, 279, 41713, 2890, 7720, 315, 1521, 41943, 1210, 32499, 3495, 706, 6982, 430, 264, 10173, 449, 21420, 2579, 13339, 15652, 374, 5938, 449, 7319, 41713, 8624, 5326, 11, 719, 430, 279, 39086, 323, 50585, 8834, 2262, 304, 2579, 13339, 1587, 539, 5101, 311, 387, 3403, 311, 10552, 279, 7319, 41713, 15635, 13, 1115, 79105, 706, 1027, 30706, 311, 19465, 12062, 11, 264, 1579, 12290, 10173, 430, 374, 3629, 5938, 449, 2579, 13339, 15652, 11, 323, 1524, 11000, 279, 17677, 1920, 11, 4315, 1023, 41941, 13, 2030, 32595, 268, 2795, 420, 502, 3495, 13533, 264, 502, 3717, 1990, 2579, 13339, 323, 41713, 8624, 13, 330, 2028, 1920, 374, 2204, 304, 5127, 11, 11911, 389, 279, 18340, 8162, 1395, 39097, 315, 279, 3927, 1359, 568, 2795, 13, 330, 34, 1923, 275, 483, 39097, 13533, 264, 502, 1648, 311, 1520, 10552, 3249, 264, 10173, 9257, 304, 2579, 13339, 39990, 264, 91882, 91711, 1210, 6104, 39438, 275, 483, 374, 18182, 31965, 304, 2579, 63875, 11, 2737, 25309, 11, 11457, 3416, 11, 39406, 11, 296, 973, 11, 37085, 11, 323, 36167, 11, 433, 596, 1101, 264, 34625, 22822, 2561, 304, 15530, 1376, 323, 264, 4279, 25795, 304, 4907, 21662, 13, 3161, 420, 502, 3495, 304, 4059, 11, 32595, 268, 2211, 4065, 430, 810, 3495, 3966, 311, 387, 2884, 311, 21635, 279, 7296, 315, 21249, 39438, 275, 483, 73796, 13, 330, 34, 1923, 275, 483, 374, 539, 459, 7718, 50123, 26, 1057, 2547, 18182, 19159, 682, 584, 1205, 1359, 568, 2795, 13, 330, 1687, 1205, 311, 21635, 279, 7296, 315, 27076, 2740, 35208, 39438, 275, 483, 33690, 439, 584, 3077, 6982, 430, 11, 1234, 1063, 4787, 11, 433, 649, 31087, 279, 6650, 315, 24032, 430, 8356, 350, 4940, 46, 323, 13893, 272, 848, 85648, 1210, 1115, 4007, 374, 279, 5652, 304, 264, 1584, 315, 3495, 555, 32595, 268, 323, 813, 18105, 24919, 1268, 18340, 80727, 649, 17210, 311, 264, 91882, 91711, 11, 45063, 287, 502, 323, 16907, 44014, 6532, 304, 4851, 8624, 13, 763, 264, 220, 679, 16, 22037, 4007, 11, 814, 1176, 11352, 430, 1274, 527, 539, 80632, 3950, 311, 41713, 8624, 21742, 1606, 315, 872, 19465, 1304, 5352, 11, 719, 1101, 3196, 389, 1268, 279, 8162, 12, 76991, 304, 872, 60071, 490, 11613, 28168, 553, 514, 66, 411, 258, 11, 264, 24549, 449, 264, 6070, 4528, 311, 39438, 275, 483, 13, 220, 128257, 198 ]

2,395

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The emergence of new bacterial pathogens is a continuing challenge for agriculture and food safety. Salmonella Typhimurium is a major cause of foodborne illness worldwide, with pigs a major zoonotic reservoir. Two phylogenetically distinct variants, U288 and ST34, emerged in UK pigs around the same time but present different risk to food safety. Here we show using genomic epidemiology that ST34 accounts for over half of all S . Typhimurium infections in people while U288 less than 2%. That the U288 clade evolved in the recent past by acquiring AMR genes, indels in the virulence plasmid pU288-1, and accumulation of loss-of-function polymorphisms in coding sequences. U288 replicates more slowly and is more sensitive to desiccation than ST34 isolates and exhibited distinct pathogenicity in the murine model of colitis and in pigs. U288 infection was more disseminated in the lymph nodes while ST34 were recovered in greater numbers in the intestinal contents. These data are consistent with the evolution of S . Typhimurium U288 adaptation to pigs that may determine their reduced zoonotic potential. Introduction Emergence of infectious diseases presents new challenges for the management of human and livestock health, with substantial human and economic costs through morbidity and mortality, and lost productivity in agriculture. The emergence of 335 human infectious diseases between 1945 and 2004 was dominated by zoonoses of bacterial aetiological agents. 1 A total of 10 of the 335 emergent infectious diseases during this period were Salmonella enterica and several more have been reported since, including S. enterica serotype Typhimurium ( S . Typhimurium) ST313 associated with invasive non-typhoidal Salmonella (iNTS) disease in sub-Saharan Africa, and extensively drug resistant (XDR) S . Typhi. 2 , 3 , 4 Salmonella was estimated to have caused around 87 million human infections resulting in approximately 1.2 million deaths globally in the year 2010. Non-typhoidal Salmonella alone has the greatest impact on health with 4 million disability adjusted life years lost, the greatest burden on human health among foodborne diseases. 5 Pigs are one of the major zoonotic reservoirs, with 10–20% of human salmonellosis in Europe attributable to them. 6 , 7 An understanding of the evolutionary processes leading to the emergence of new infectious diseases has the potential to improve pathogen diagnostics and surveillance, and guide policy and interventions aimed at decreasing the burden of human and animal infection. The genus Salmonella consists of over 2500 different serovars that have diverse host ranges, pathogenicity and risk to human health. One of these serovars, S . Typhimurium (including monophasic variants), has consistently been a dominant serovar in pigs globally, and currently accounts for around two thirds of isolates in the UK. 8 , 9 Despite the ostensibly stable prevalence of S . Typhimurium in pig populations over time, the epidemiological record indicates a dynamic process where distinct variants, identified by phage typing, increase and decrease in prevalence over time. 8 Since the middle of the 20 th century in Europe the dominant phage types were definitive type 9 (DT9), DT204, DT104 and most recently DT193 that is a monophasic S . Typhimurium ( S . 1 ,4,[5],12:i:-) with sequence type 34 (ST34). 10 , 11 At their peak incidence, each accounted for over half of all human isolates of S . Typhimurium. Phage typing has been useful for surveillance and outbreak detection, but only provides limited information about the relationship of the Salmonella isolates due to their polyphyletic nature and potential for rapid changes in phage type as a result of mutations and horizontal gene transfer. 12 Nonetheless, sub-genomic and whole genome sequence analysis confirmed that the emergence of new phage types over time does represent the emergence of distinct clonal groups. 13 , 14 The drivers of their emergence and the consequences for human and animal health are largely unknown. Since around the year 2003, S . Typhimurium isolates of U288 and DT193 have dominated UK pigs. 8 U288 appeared in UK pig populations around 2003 followed around the year 2006 by monophasic S . Typhimurium ( S . 1 ,4,[5],12:i:-) ST34 rapidly emerging in pig populations around the world. 8 , 15 , 16 U288 and ST34 co-existed in the UK pig population and together accounted for around 80% of isolates. 17 Despite, approximately half of all pork consumed in the UK being from UK pig herds, 18 since its emergence U288 have rarely been isolated from human infections in the UK. 17 In contrast, by the year 2013 in the UK over half of all S . Typhimurium infections in the UK were due to ST34, reflecting its capacity to be transmitted through the food chain and cause human infections. 19 , 20 U288 is not a definitive type and the designation is not widely adopted outside of the UK. Consequently, the prevalence of U288 outside of the UK is unclear. However, we previously detected U288 in pigs in Ireland, 21 a study reported that it was widespread in Danish Pig herds, 22 and was present in Italy. 23 A baseline survey reported prevalence of 21.2% and 30.5% in mesenteric lymph nodes and caecal contents for UK slaughter pigs in studies from 2007 to 2013, respectively. 24 , 25 It is believed that contamination of pig carcasses with faeces and gut contents at slaughter, and the ability of Salmonella to spread from the gut to other organs, results in contamination of meat products that enter the food chain and pose a risk to humans if improperly handled or cooked. However, the relative risk from contamination of meat by gut contents during slaughter or from tissue colonised by Salmonella prior to slaughter is not known and could be affected by differences in pathogenesis depending on the genotype of Salmonella involved. Survival of Salmonella in food depends upon adaptive response to environmental stresses including osmotic stress from biocides and desiccation, antimicrobial activity of preservatives and fluctuating temperatures during storage or cooking. In order to cause disease, Salmonella may also need to replicate in food to achieve a population size able", "role": "user" }, { "content": "Variants of concern (VOCs) and variants of interest (VOIs) have become familiar terms due to the current pandemic, but variants of familiar pathogens such as salmonella also present a threat to human and animal health. To better understand the different threats these variants pose, a collaboration led by Professor Rob Kingsley from the Quadram Institute and Professor Mark Stevens from the Roslin Institute working with scientists from the Earlham Institute has focused on common variants of salmonella present in pigs in the UK. Their findings, published recently in the journal Communications Biology, has shown that despite being extremely closely related, variants can have very different effects on the health of the pig and also on the risks they pose to food safety. Salmonella Typhimurium is one of the most common types of salmonella. It is a major cause of human gastroenteritis, notably from consuming undercooked pork products or as a result of cross-contamination of foods consumed raw. This bacterial pathogen is also a concern to the pork industry as it can affect the health, productivity and welfare of pigs. Salmonella Typhimurium is relatively common in pig herds globally, and processes implemented in abattoirs are designed to prevent contamination of meat destined for the food chain. Bacterial pathogens continually evolve to exploit new ecological niches. Human activity, including agricultural practices and how we use medicines and antibiotics may drive the emergence of new variants. Understanding exactly how this happens is crucial to countering the consequences of new variants on human and animal health, and the answers lie in the genes of the bacteria. Genome sequencing can read all of an organisms genes and can help by resolving relationships between variants, identifying variants that are evolving as they enter a new niche, and pinpointing potential functional changes that affect their ability to cause disease or survive in the food chain. The team worked with Public Health England and the Animal and Plant Health Agency and to examine salmonella isolates from human clinical infections during routine diagnostics or from animals during routine surveillance, with funding from the Biotechnology and Biological Sciences Research Council, part of UKRI. Using whole genome sequencing the research team found that two types of S. Typhimurium, dubbed U288 and ST34, have been circulating in UK pigs since 2003. Surprisingly, U288 are rarely associated with human infection, while ST34 account for over half of all S. Typhimurium infections from all sources, not just pigs. What is more, the two types of salmonella infected pigs differently, resulting in distinct levels of colonisation of the intestine and surrounding tissue, and disease severity in the first few days after infection. The U288 variant grew more slowly in the lab and was more sensitive to stress associated with desiccation. These characteristics may affect its ability to survive in the food chain. Inspection of changes in the genome sequence of U288 indicated that this variant emerged by a unique set of changes that occurred within a short period of time, probably between the years 1980 and 2000. The researchers believe that these changes hold the key to understanding how this variant interacts differently with pigs during infections, in the lab, and potentially the food chain. \"We have seen these types of changes before in variants of salmonella that have become adapted to specific host species and cause a more invasive disease, including the type of salmonella that causes typhoid fever in people but does not affect other species,\" said Prof. Rob Kingsley, a group leader at the Quadram Institute and Professor of Microbiology at the University of East Anglia. \"One of the interesting findings is just how rapidly pathogens can adapt, and how even a few genomic changes can lead to very different disease outcomes,\" said Dr. Matt Bawn a researcher involved in the study based at both the Earlham Institute and Quadram Institute. Prof. Stevens, chair of microbial pathogenesis and a deputy director at The Roslin Institute, University of Edinburgh, added \"Understanding how variants of salmonella emerge and pinpointing the genetic signatures responsible for adaptation to different hosts and the ability to produce disease will provide opportunities to improve diagnostics and surveillance. In turn this will help to predict the risk that salmonella variants pose to animal health and food safety.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The emergence of new bacterial pathogens is a continuing challenge for agriculture and food safety. Salmonella Typhimurium is a major cause of foodborne illness worldwide, with pigs a major zoonotic reservoir. Two phylogenetically distinct variants, U288 and ST34, emerged in UK pigs around the same time but present different risk to food safety. Here we show using genomic epidemiology that ST34 accounts for over half of all S . Typhimurium infections in people while U288 less than 2%. That the U288 clade evolved in the recent past by acquiring AMR genes, indels in the virulence plasmid pU288-1, and accumulation of loss-of-function polymorphisms in coding sequences. U288 replicates more slowly and is more sensitive to desiccation than ST34 isolates and exhibited distinct pathogenicity in the murine model of colitis and in pigs. U288 infection was more disseminated in the lymph nodes while ST34 were recovered in greater numbers in the intestinal contents. These data are consistent with the evolution of S . Typhimurium U288 adaptation to pigs that may determine their reduced zoonotic potential. Introduction Emergence of infectious diseases presents new challenges for the management of human and livestock health, with substantial human and economic costs through morbidity and mortality, and lost productivity in agriculture. The emergence of 335 human infectious diseases between 1945 and 2004 was dominated by zoonoses of bacterial aetiological agents. 1 A total of 10 of the 335 emergent infectious diseases during this period were Salmonella enterica and several more have been reported since, including S. enterica serotype Typhimurium ( S . Typhimurium) ST313 associated with invasive non-typhoidal Salmonella (iNTS) disease in sub-Saharan Africa, and extensively drug resistant (XDR) S . Typhi. 2 , 3 , 4 Salmonella was estimated to have caused around 87 million human infections resulting in approximately 1.2 million deaths globally in the year 2010. Non-typhoidal Salmonella alone has the greatest impact on health with 4 million disability adjusted life years lost, the greatest burden on human health among foodborne diseases. 5 Pigs are one of the major zoonotic reservoirs, with 10–20% of human salmonellosis in Europe attributable to them. 6 , 7 An understanding of the evolutionary processes leading to the emergence of new infectious diseases has the potential to improve pathogen diagnostics and surveillance, and guide policy and interventions aimed at decreasing the burden of human and animal infection. The genus Salmonella consists of over 2500 different serovars that have diverse host ranges, pathogenicity and risk to human health. One of these serovars, S . Typhimurium (including monophasic variants), has consistently been a dominant serovar in pigs globally, and currently accounts for around two thirds of isolates in the UK. 8 , 9 Despite the ostensibly stable prevalence of S . Typhimurium in pig populations over time, the epidemiological record indicates a dynamic process where distinct variants, identified by phage typing, increase and decrease in prevalence over time. 8 Since the middle of the 20 th century in Europe the dominant phage types were definitive type 9 (DT9), DT204, DT104 and most recently DT193 that is a monophasic S . Typhimurium ( S . 1 ,4,[5],12:i:-) with sequence type 34 (ST34). 10 , 11 At their peak incidence, each accounted for over half of all human isolates of S . Typhimurium. Phage typing has been useful for surveillance and outbreak detection, but only provides limited information about the relationship of the Salmonella isolates due to their polyphyletic nature and potential for rapid changes in phage type as a result of mutations and horizontal gene transfer. 12 Nonetheless, sub-genomic and whole genome sequence analysis confirmed that the emergence of new phage types over time does represent the emergence of distinct clonal groups. 13 , 14 The drivers of their emergence and the consequences for human and animal health are largely unknown. Since around the year 2003, S . Typhimurium isolates of U288 and DT193 have dominated UK pigs. 8 U288 appeared in UK pig populations around 2003 followed around the year 2006 by monophasic S . Typhimurium ( S . 1 ,4,[5],12:i:-) ST34 rapidly emerging in pig populations around the world. 8 , 15 , 16 U288 and ST34 co-existed in the UK pig population and together accounted for around 80% of isolates. 17 Despite, approximately half of all pork consumed in the UK being from UK pig herds, 18 since its emergence U288 have rarely been isolated from human infections in the UK. 17 In contrast, by the year 2013 in the UK over half of all S . Typhimurium infections in the UK were due to ST34, reflecting its capacity to be transmitted through the food chain and cause human infections. 19 , 20 U288 is not a definitive type and the designation is not widely adopted outside of the UK. Consequently, the prevalence of U288 outside of the UK is unclear. However, we previously detected U288 in pigs in Ireland, 21 a study reported that it was widespread in Danish Pig herds, 22 and was present in Italy. 23 A baseline survey reported prevalence of 21.2% and 30.5% in mesenteric lymph nodes and caecal contents for UK slaughter pigs in studies from 2007 to 2013, respectively. 24 , 25 It is believed that contamination of pig carcasses with faeces and gut contents at slaughter, and the ability of Salmonella to spread from the gut to other organs, results in contamination of meat products that enter the food chain and pose a risk to humans if improperly handled or cooked. However, the relative risk from contamination of meat by gut contents during slaughter or from tissue colonised by Salmonella prior to slaughter is not known and could be affected by differences in pathogenesis depending on the genotype of Salmonella involved. Survival of Salmonella in food depends upon adaptive response to environmental stresses including osmotic stress from biocides and desiccation, antimicrobial activity of preservatives and fluctuating temperatures during storage or cooking. In order to cause disease, Salmonella may also need to replicate in food to achieve a population size able<|im_end|> <|im_start|>assistant Variants of concern (VOCs) and variants of interest (VOIs) have become familiar terms due to the current pandemic, but variants of familiar pathogens such as salmonella also present a threat to human and animal health. To better understand the different threats these variants pose, a collaboration led by Professor Rob Kingsley from the Quadram Institute and Professor Mark Stevens from the Roslin Institute working with scientists from the Earlham Institute has focused on common variants of salmonella present in pigs in the UK. Their findings, published recently in the journal Communications Biology, has shown that despite being extremely closely related, variants can have very different effects on the health of the pig and also on the risks they pose to food safety. Salmonella Typhimurium is one of the most common types of salmonella. It is a major cause of human gastroenteritis, notably from consuming undercooked pork products or as a result of cross-contamination of foods consumed raw. This bacterial pathogen is also a concern to the pork industry as it can affect the health, productivity and welfare of pigs. Salmonella Typhimurium is relatively common in pig herds globally, and processes implemented in abattoirs are designed to prevent contamination of meat destined for the food chain. Bacterial pathogens continually evolve to exploit new ecological niches. Human activity, including agricultural practices and how we use medicines and antibiotics may drive the emergence of new variants. Understanding exactly how this happens is crucial to countering the consequences of new variants on human and animal health, and the answers lie in the genes of the bacteria. Genome sequencing can read all of an organisms genes and can help by resolving relationships between variants, identifying variants that are evolving as they enter a new niche, and pinpointing potential functional changes that affect their ability to cause disease or survive in the food chain. The team worked with Public Health England and the Animal and Plant Health Agency and to examine salmonella isolates from human clinical infections during routine diagnostics or from animals during routine surveillance, with funding from the Biotechnology and Biological Sciences Research Council, part of UKRI. Using whole genome sequencing the research team found that two types of S. Typhimurium, dubbed U288 and ST34, have been circulating in UK pigs since 2003. Surprisingly, U288 are rarely associated with human infection, while ST34 account for over half of all S. Typhimurium infections from all sources, not just pigs. What is more, the two types of salmonella infected pigs differently, resulting in distinct levels of colonisation of the intestine and surrounding tissue, and disease severity in the first few days after infection. The U288 variant grew more slowly in the lab and was more sensitive to stress associated with desiccation. These characteristics may affect its ability to survive in the food chain. Inspection of changes in the genome sequence of U288 indicated that this variant emerged by a unique set of changes that occurred within a short period of time, probably between the years 1980 and 2000. The researchers believe that these changes hold the key to understanding how this variant interacts differently with pigs during infections, in the lab, and potentially the food chain. "We have seen these types of changes before in variants of salmonella that have become adapted to specific host species and cause a more invasive disease, including the type of salmonella that causes typhoid fever in people but does not affect other species," said Prof. Rob Kingsley, a group leader at the Quadram Institute and Professor of Microbiology at the University of East Anglia. "One of the interesting findings is just how rapidly pathogens can adapt, and how even a few genomic changes can lead to very different disease outcomes," said Dr. Matt Bawn a researcher involved in the study based at both the Earlham Institute and Quadram Institute. Prof. Stevens, chair of microbial pathogenesis and a deputy director at The Roslin Institute, University of Edinburgh, added "Understanding how variants of salmonella emerge and pinpointing the genetic signatures responsible for adaptation to different hosts and the ability to produce disease will provide opportunities to improve diagnostics and surveillance. In turn this will help to predict the risk that salmonella variants pose to animal health and food safety." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 49179, 315, 502, 45964, 78284, 374, 264, 14691, 8815, 369, 30029, 323, 3691, 7296, 13, 62826, 6985, 14221, 764, 318, 324, 2411, 374, 264, 3682, 5353, 315, 3691, 32096, 17563, 15603, 11, 449, 49910, 264, 3682, 1167, 9186, 14546, 45512, 13, 9220, 37555, 86945, 37774, 12742, 27103, 11, 549, 15287, 323, 4015, 1958, 11, 22763, 304, 6560, 49910, 2212, 279, 1890, 892, 719, 3118, 2204, 5326, 311, 3691, 7296, 13, 5810, 584, 1501, 1701, 81064, 62057, 2508, 430, 4015, 1958, 9815, 369, 927, 4376, 315, 682, 328, 662, 14221, 764, 318, 324, 2411, 30020, 304, 1274, 1418, 549, 15287, 2753, 1109, 220, 17, 14697, 3011, 279, 549, 15287, 1206, 1037, 28995, 304, 279, 3293, 3347, 555, 42990, 6912, 49, 21389, 11, 1280, 2053, 304, 279, 9043, 59566, 628, 10753, 307, 281, 52, 15287, 12, 16, 11, 323, 46835, 315, 4814, 8838, 34849, 46033, 16751, 13978, 304, 11058, 24630, 13, 549, 15287, 29641, 988, 810, 14297, 323, 374, 810, 16614, 311, 951, 48738, 367, 1109, 4015, 1958, 13399, 988, 323, 51713, 12742, 1853, 29569, 488, 304, 279, 8309, 483, 1646, 315, 1400, 20000, 323, 304, 49910, 13, 549, 15287, 19405, 574, 810, 34000, 52299, 304, 279, 43745, 7954, 1418, 4015, 1958, 1051, 26403, 304, 7191, 5219, 304, 279, 63900, 8970, 13, 4314, 828, 527, 13263, 449, 279, 15740, 315, 328, 662, 14221, 764, 318, 324, 2411, 549, 15287, 34185, 311, 49910, 430, 1253, 8417, 872, 11293, 1167, 9186, 14546, 4754, 13, 29438, 21185, 29355, 315, 50600, 19338, 18911, 502, 11774, 369, 279, 6373, 315, 3823, 323, 51876, 2890, 11, 449, 12190, 3823, 323, 7100, 7194, 1555, 93144, 19025, 323, 29528, 11, 323, 5675, 26206, 304, 30029, 13, 578, 49179, 315, 220, 16596, 3823, 50600, 19338, 1990, 220, 6393, 20, 323, 220, 1049, 19, 574, 30801, 555, 1167, 9186, 20274, 315, 45964, 264, 295, 41314, 13307, 13, 220, 16, 362, 2860, 315, 220, 605, 315, 279, 220, 16596, 7425, 306, 50600, 19338, 2391, 420, 4261, 1051, 62826, 6985, 3810, 3074, 323, 3892, 810, 617, 1027, 5068, 2533, 11, 2737, 328, 13, 3810, 3074, 1446, 4249, 14221, 764, 318, 324, 2411, 320, 328, 662, 14221, 764, 318, 324, 2411, 8, 4015, 15231, 5938, 449, 53354, 2536, 12, 1919, 764, 71916, 62826, 6985, 320, 72, 6542, 50, 8, 8624, 304, 1207, 97519, 10384, 11, 323, 42817, 5623, 31785, 320, 55, 7842, 8, 328, 662, 14221, 17247, 13, 220, 17, 1174, 220, 18, 1174, 220, 19, 62826, 6985, 574, 13240, 311, 617, 9057, 2212, 220, 4044, 3610, 3823, 30020, 13239, 304, 13489, 220, 16, 13, 17, 3610, 16779, 31550, 304, 279, 1060, 220, 679, 15, 13, 11842, 12, 1919, 764, 71916, 62826, 6985, 7636, 706, 279, 12474, 5536, 389, 2890, 449, 220, 19, 3610, 28353, 24257, 2324, 1667, 5675, 11, 279, 12474, 23104, 389, 3823, 2890, 4315, 3691, 32096, 19338, 13, 220, 20, 393, 14801, 527, 832, 315, 279, 3682, 1167, 9186, 14546, 45512, 82, 11, 449, 220, 605, 4235, 508, 4, 315, 3823, 41420, 301, 2353, 285, 304, 4606, 71526, 311, 1124, 13, 220, 21, 1174, 220, 22, 1556, 8830, 315, 279, 41993, 11618, 6522, 311, 279, 49179, 315, 502, 50600, 19338, 706, 279, 4754, 311, 7417, 1853, 11968, 50518, 323, 22156, 11, 323, 8641, 4947, 323, 39455, 20034, 520, 44649, 279, 23104, 315, 3823, 323, 10065, 19405, 13, 578, 64677, 62826, 6985, 17610, 315, 927, 220, 5154, 15, 2204, 1446, 869, 1590, 430, 617, 17226, 3552, 21986, 11, 1853, 29569, 488, 323, 5326, 311, 3823, 2890, 13, 3861, 315, 1521, 1446, 869, 1590, 11, 328, 662, 14221, 764, 318, 324, 2411, 320, 16564, 1647, 454, 4752, 292, 27103, 705, 706, 21356, 1027, 264, 25462, 1446, 869, 277, 304, 49910, 31550, 11, 323, 5131, 9815, 369, 2212, 1403, 94237, 315, 13399, 988, 304, 279, 6560, 13, 220, 23, 1174, 220, 24, 18185, 279, 81594, 15528, 38009, 315, 328, 662, 14221, 764, 318, 324, 2411, 304, 24623, 22673, 927, 892, 11, 279, 62057, 5848, 3335, 15151, 264, 8915, 1920, 1405, 12742, 27103, 11, 11054, 555, 1343, 425, 20061, 11, 5376, 323, 18979, 304, 38009, 927, 892, 13, 220, 23, 8876, 279, 6278, 315, 279, 220, 508, 270, 9478, 304, 4606, 279, 25462, 1343, 425, 4595, 1051, 45813, 955, 220, 24, 320, 10822, 24, 705, 26065, 7854, 11, 26065, 6849, 323, 1455, 6051, 26065, 7285, 430, 374, 264, 1647, 454, 4752, 292, 328, 662, 14221, 764, 318, 324, 2411, 320, 328, 662, 220, 16, 1174, 19, 17706, 20, 1145, 717, 15007, 11184, 8, 449, 8668, 955, 220, 1958, 320, 790, 1958, 570, 220, 605, 1174, 220, 806, 2468, 872, 16557, 39775, 11, 1855, 41853, 369, 927, 4376, 315, 682, 3823, 13399, 988, 315, 328, 662, 14221, 764, 318, 324, 2411, 13, 2405, 425, 20061, 706, 1027, 5505, 369, 22156, 323, 31188, 18468, 11, 719, 1193, 5825, 7347, 2038, 922, 279, 5133, 315, 279, 62826, 6985, 13399, 988, 4245, 311, 872, 10062, 764, 982, 29150, 7138, 323, 4754, 369, 11295, 4442, 304, 1343, 425, 955, 439, 264, 1121, 315, 34684, 323, 16600, 15207, 8481, 13, 220, 717, 56733, 11, 1207, 37564, 3151, 323, 4459, 33869, 8668, 6492, 11007, 430, 279, 49179, 315, 502, 1343, 425, 4595, 927, 892, 1587, 4097, 279, 49179, 315, 12742, 1206, 25180, 5315, 13, 220, 1032, 1174, 220, 975, 578, 12050, 315, 872, 49179, 323, 279, 16296, 369, 3823, 323, 10065, 2890, 527, 14090, 9987, 13, 8876, 2212, 279, 1060, 220, 1049, 18, 11, 328, 662, 14221, 764, 318, 324, 2411, 13399, 988, 315, 549, 15287, 323, 26065, 7285, 617, 30801, 6560, 49910, 13, 220, 23, 549, 15287, 9922, 304, 6560, 24623, 22673, 2212, 220, 1049, 18, 8272, 2212, 279, 1060, 220, 1049, 21, 555, 1647, 454, 4752, 292, 328, 662, 14221, 764, 318, 324, 2411, 320, 328, 662, 220, 16, 1174, 19, 17706, 20, 1145, 717, 15007, 11184, 8, 4015, 1958, 19019, 24084, 304, 24623, 22673, 2212, 279, 1917, 13, 220, 23, 1174, 220, 868, 1174, 220, 845, 549, 15287, 323, 4015, 1958, 1080, 10397, 13539, 304, 279, 6560, 24623, 7187, 323, 3871, 41853, 369, 2212, 220, 1490, 4, 315, 13399, 988, 13, 220, 1114, 18185, 11, 13489, 4376, 315, 682, 36167, 27073, 304, 279, 6560, 1694, 505, 6560, 24623, 1077, 5469, 11, 220, 972, 2533, 1202, 49179, 549, 15287, 617, 19029, 1027, 25181, 505, 3823, 30020, 304, 279, 6560, 13, 220, 1114, 763, 13168, 11, 555, 279, 1060, 220, 679, 18, 304, 279, 6560, 927, 4376, 315, 682, 328, 662, 14221, 764, 318, 324, 2411, 30020, 304, 279, 6560, 1051, 4245, 311, 4015, 1958, 11, 42852, 1202, 8824, 311, 387, 34699, 1555, 279, 3691, 8957, 323, 5353, 3823, 30020, 13, 220, 777, 1174, 220, 508, 549, 15287, 374, 539, 264, 45813, 955, 323, 279, 43851, 374, 539, 13882, 18306, 4994, 315, 279, 6560, 13, 53123, 11, 279, 38009, 315, 549, 15287, 4994, 315, 279, 6560, 374, 25420, 13, 4452, 11, 584, 8767, 16914, 549, 15287, 304, 49910, 304, 14990, 11, 220, 1691, 264, 4007, 5068, 430, 433, 574, 24716, 304, 44780, 49654, 1077, 5469, 11, 220, 1313, 323, 574, 3118, 304, 15704, 13, 220, 1419, 362, 26954, 10795, 5068, 38009, 315, 220, 1691, 13, 17, 4, 323, 220, 966, 13, 20, 4, 304, 11083, 1992, 292, 43745, 7954, 323, 2211, 98298, 8970, 369, 6560, 40856, 49910, 304, 7978, 505, 220, 1049, 22, 311, 220, 679, 18, 11, 15947, 13, 220, 1187, 1174, 220, 914, 1102, 374, 11846, 430, 47810, 315, 24623, 75566, 52090, 449, 2267, 762, 288, 323, 18340, 8970, 520, 40856, 11, 323, 279, 5845, 315, 62826, 6985, 311, 9041, 505, 279, 18340, 311, 1023, 36853, 11, 3135, 304, 47810, 315, 13339, 3956, 430, 3810, 279, 3691, 8957, 323, 17477, 264, 5326, 311, 12966, 422, 75298, 18073, 477, 30205, 13, 4452, 11, 279, 8844, 5326, 505, 47810, 315, 13339, 555, 18340, 8970, 2391, 40856, 477, 505, 20438, 15235, 4147, 555, 62826, 6985, 4972, 311, 40856, 374, 539, 3967, 323, 1436, 387, 11754, 555, 12062, 304, 1853, 52379, 11911, 389, 279, 80285, 315, 62826, 6985, 6532, 13, 54451, 315, 62826, 6985, 304, 3691, 14117, 5304, 48232, 2077, 311, 12434, 59623, 2737, 125452, 14546, 8631, 505, 6160, 511, 3422, 323, 951, 48738, 367, 11, 79312, 83059, 5820, 315, 1685, 79629, 323, 39388, 54643, 20472, 2391, 5942, 477, 17677, 13, 763, 2015, 311, 5353, 8624, 11, 62826, 6985, 1253, 1101, 1205, 311, 46113, 304, 3691, 311, 11322, 264, 7187, 1404, 3025, 128257, 198, 128256, 78191, 198, 57235, 1821, 315, 4747, 320, 53, 7767, 82, 8, 323, 27103, 315, 2802, 320, 11417, 3957, 8, 617, 3719, 11537, 3878, 4245, 311, 279, 1510, 28522, 11, 719, 27103, 315, 11537, 78284, 1778, 439, 41420, 6985, 1101, 3118, 264, 6023, 311, 3823, 323, 10065, 2890, 13, 2057, 2731, 3619, 279, 2204, 18208, 1521, 27103, 17477, 11, 264, 20632, 6197, 555, 17054, 4997, 24980, 3258, 505, 279, 39118, 2453, 10181, 323, 17054, 4488, 36177, 505, 279, 16870, 3817, 10181, 3318, 449, 14248, 505, 279, 48510, 5721, 10181, 706, 10968, 389, 4279, 27103, 315, 41420, 6985, 3118, 304, 49910, 304, 279, 6560, 13, 11205, 14955, 11, 4756, 6051, 304, 279, 8486, 26545, 40023, 11, 706, 6982, 430, 8994, 1694, 9193, 15499, 5552, 11, 27103, 649, 617, 1633, 2204, 6372, 389, 279, 2890, 315, 279, 24623, 323, 1101, 389, 279, 15635, 814, 17477, 311, 3691, 7296, 13, 62826, 6985, 14221, 764, 318, 324, 2411, 374, 832, 315, 279, 1455, 4279, 4595, 315, 41420, 6985, 13, 1102, 374, 264, 3682, 5353, 315, 3823, 59349, 1992, 20000, 11, 35146, 505, 35208, 1234, 99797, 36167, 3956, 477, 439, 264, 1121, 315, 5425, 35172, 27935, 315, 15657, 27073, 7257, 13, 1115, 45964, 1853, 11968, 374, 1101, 264, 4747, 311, 279, 36167, 5064, 439, 433, 649, 7958, 279, 2890, 11, 26206, 323, 23460, 315, 49910, 13, 62826, 6985, 14221, 764, 318, 324, 2411, 374, 12309, 4279, 304, 24623, 1077, 5469, 31550, 11, 323, 11618, 11798, 304, 671, 17173, 17260, 527, 6319, 311, 5471, 47810, 315, 13339, 51687, 369, 279, 3691, 8957, 13, 426, 71034, 78284, 35611, 38680, 311, 33294, 502, 50953, 58971, 288, 13, 11344, 5820, 11, 2737, 29149, 12659, 323, 1268, 584, 1005, 39653, 323, 46850, 1253, 6678, 279, 49179, 315, 502, 27103, 13, 46551, 7041, 1268, 420, 8741, 374, 16996, 311, 1797, 4776, 279, 16296, 315, 502, 27103, 389, 3823, 323, 10065, 2890, 11, 323, 279, 11503, 10457, 304, 279, 21389, 315, 279, 24032, 13, 82917, 62119, 649, 1373, 682, 315, 459, 44304, 21389, 323, 649, 1520, 555, 53583, 12135, 1990, 27103, 11, 25607, 27103, 430, 527, 42028, 439, 814, 3810, 264, 502, 35149, 11, 323, 67638, 287, 4754, 16003, 4442, 430, 7958, 872, 5845, 311, 5353, 8624, 477, 18167, 304, 279, 3691, 8957, 13, 578, 2128, 6575, 449, 3142, 6401, 9635, 323, 279, 21995, 323, 18317, 6401, 16784, 323, 311, 21635, 41420, 6985, 13399, 988, 505, 3823, 14830, 30020, 2391, 14348, 50518, 477, 505, 10099, 2391, 14348, 22156, 11, 449, 11006, 505, 279, 12371, 52536, 323, 63711, 23199, 8483, 9251, 11, 961, 315, 6560, 4403, 13, 12362, 4459, 33869, 62119, 279, 3495, 2128, 1766, 430, 1403, 4595, 315, 328, 13, 14221, 764, 318, 324, 2411, 11, 42160, 549, 15287, 323, 4015, 1958, 11, 617, 1027, 54828, 304, 6560, 49910, 2533, 220, 1049, 18, 13, 8242, 49264, 11, 549, 15287, 527, 19029, 5938, 449, 3823, 19405, 11, 1418, 4015, 1958, 2759, 369, 927, 4376, 315, 682, 328, 13, 14221, 764, 318, 324, 2411, 30020, 505, 682, 8336, 11, 539, 1120, 49910, 13, 3639, 374, 810, 11, 279, 1403, 4595, 315, 41420, 6985, 29374, 49910, 22009, 11, 13239, 304, 12742, 5990, 315, 15235, 8082, 315, 279, 92234, 323, 14932, 20438, 11, 323, 8624, 31020, 304, 279, 1176, 2478, 2919, 1306, 19405, 13, 578, 549, 15287, 11678, 14264, 810, 14297, 304, 279, 10278, 323, 574, 810, 16614, 311, 8631, 5938, 449, 951, 48738, 367, 13, 4314, 17910, 1253, 7958, 1202, 5845, 311, 18167, 304, 279, 3691, 8957, 13, 67046, 315, 4442, 304, 279, 33869, 8668, 315, 549, 15287, 16717, 430, 420, 11678, 22763, 555, 264, 5016, 743, 315, 4442, 430, 10222, 2949, 264, 2875, 4261, 315, 892, 11, 4762, 1990, 279, 1667, 220, 3753, 15, 323, 220, 1049, 15, 13, 578, 12074, 4510, 430, 1521, 4442, 3412, 279, 1401, 311, 8830, 1268, 420, 11678, 84261, 22009, 449, 49910, 2391, 30020, 11, 304, 279, 10278, 11, 323, 13893, 279, 3691, 8957, 13, 330, 1687, 617, 3970, 1521, 4595, 315, 4442, 1603, 304, 27103, 315, 41420, 6985, 430, 617, 3719, 30464, 311, 3230, 3552, 9606, 323, 5353, 264, 810, 53354, 8624, 11, 2737, 279, 955, 315, 41420, 6985, 430, 11384, 13892, 764, 590, 34653, 304, 1274, 719, 1587, 539, 7958, 1023, 9606, 1359, 1071, 8626, 13, 4997, 24980, 3258, 11, 264, 1912, 7808, 520, 279, 39118, 2453, 10181, 323, 17054, 315, 18654, 81162, 520, 279, 3907, 315, 6460, 7568, 24235, 13, 330, 4054, 315, 279, 7185, 14955, 374, 1120, 1268, 19019, 78284, 649, 10737, 11, 323, 1268, 1524, 264, 2478, 81064, 4442, 649, 3063, 311, 1633, 2204, 8624, 20124, 1359, 1071, 2999, 13, 13678, 426, 6513, 264, 32185, 6532, 304, 279, 4007, 3196, 520, 2225, 279, 48510, 5721, 10181, 323, 39118, 2453, 10181, 13, 8626, 13, 36177, 11, 10716, 315, 75418, 1853, 52379, 323, 264, 27158, 7690, 520, 578, 16870, 3817, 10181, 11, 3907, 315, 41406, 11, 3779, 330, 71251, 1268, 27103, 315, 41420, 6985, 34044, 323, 67638, 287, 279, 19465, 33728, 8647, 369, 34185, 311, 2204, 18939, 323, 279, 5845, 311, 8356, 8624, 690, 3493, 10708, 311, 7417, 50518, 323, 22156, 13, 763, 2543, 420, 690, 1520, 311, 7168, 279, 5326, 430, 41420, 6985, 27103, 17477, 311, 10065, 2890, 323, 3691, 7296, 1210, 220, 128257, 198 ]

2,275

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Post-ingestive nutrient signals to the brain regulate eating behaviour in rodents, and impaired responses to these signals have been associated with pathological feeding behaviour and obesity. To study this in humans, we performed a single-blinded, randomized, controlled, crossover study in 30 humans with a healthy body weight (females N = 12, males N = 18) and 30 humans with obesity (females N = 18, males N = 12). We assessed the effect of intragastric glucose, lipid and water (noncaloric isovolumetric control) infusions on the primary endpoints cerebral neuronal activity and striatal dopamine release, as well as on the secondary endpoints plasma hormones and glucose, hunger scores and caloric intake. To study whether impaired responses in participants with obesity would be partially reversible with diet-induced weight loss, imaging was repeated after 10% diet-induced weight loss. We show that intragastric glucose and lipid infusions induce orosensory-independent and preference-independent, nutrient-specific cerebral neuronal activity and striatal dopamine release in lean participants. In contrast, participants with obesity have severely impaired brain responses to post-ingestive nutrients. Importantly, the impaired neuronal responses are not restored after diet-induced weight loss. Impaired neuronal responses to nutritional signals may contribute to overeating and obesity, and ongoing resistance to post-ingestive nutrient signals after significant weight loss may in part explain the high rate of weight regain after successful weight loss. Main The orosensory effects of food have long been identified as the primary driving force behind food intake beyond homeostatic needs 1 , 2 . In addition to the palatability of nutrients, increasing evidence shows a potent role for signals that arise after the ingestion of food—so-called post-ingestive nutrient signals—in the regulation of eating behaviour 3 . For instance, Trpm5 −/− mice that lack sweet taste transduction still develop a clear preference for sucrose over noncaloric solutions 4 , indicating a calorie-dependent and taste-independent effect on food intake. Other studies show that mice are receptive to appetition, the process of flavour conditioning associated with intragastric infusion of nutrients 5 , 6 . Several post-ingestive nutrient signals convey the presence of nutrients in the gastrointestinal tract to the brain and may contribute to the regulation of eating behaviour via the gut–brain axis. Firstly, gastrointestinal vagal nerve afferents are stimulated upon the presence of nutrients and mediate anorexigenic effects via the brainstem to several downstream brain regions 7 , 8 . Secondly, nutrients in the gastrointestinal lumen induce an endocrine response and facilitate the digestion, absorption and subsequent metabolism of nutrients. The post-ingestive endocrine response includes, but is not limited to, enhanced release of insulin from pancreatic beta cells, glucagon-like peptide-1 (GLP-1) from intestinal L cells 9 , 10 , and suppressed release of ghrelin from gastric X/A-like cells 11 . Gastrointestinal vagal nerve afferents and multiple brain regions express receptors for these hormones, but the exact mechanisms by which insulin and GLP-1 mediate anorexigenic effects and ghrelin mediates orexigenic effects remain to be elucidated 12 . Finally, changes in the concentrations of nutrients and/or metabolites in the portal or systemic circulation provide a direct post-ingestive signal of nutrient availability for different brain regions involved in the central regulation of food intake 13 , 14 . While the post-ingestive signals induced by glucose versus lipid consumption differ in several aspects, administration of both carbohydrate and lipid promotes the release of striatal dopamine in rodents 7 , 15 . The striatum is involved in the rewarding and motivational aspects of food intake 7 , 13 . A study in humans without obesity reported a biphasic striatal dopamine response immediately and approximately 20 min following the consumption of a milkshake solution, which was hypothesized to reflect both an immediate orosensory and delayed post-ingestive response 16 . In rodents, striatal dopamine release is positively and proportionally related to intragastric fat infusions, and intact striatal dopamine signalling is required to reduce subsequent caloric intake in proportion to the amount of fat directly infused into the stomach 17 . Interestingly, long-term exposure to a high-fat diet resulted in an impaired striatal dopaminergic response to an intragastric lipid infusion 18 . Taken together, these studies demonstrate that, (i) in addition to direct gustatory effects of nutrients, post-ingestive nutrient signals contribute to the regulation of feeding behaviour; and (ii) impaired striatal dopamine signalling after prolonged exposure to high-calorie nutrients may promote subsequent overeating and obesity. Despite these intriguing mostly preclinical studies, little is known about the role of post-ingestive nutrient signals in human physiology or obesity development. A few studies have assessed the response of the brain to the isolated, orosensory-independent, post-ingestive effects of glucose or dodecanoate (a C12 fatty acid) by means of intragastric infusions using functional magnetic resonance imaging (fMRI) 19 , 20 , 21 . The intragastric glucose infusion decreased blood oxygen level-dependent (BOLD) signal in the striatum and several other brain regions, including the brainstem, hypothalamus and thalamus 19 . The intragastric dodecanoate infusion increased BOLD signal in the brainstem, pons, hypothalamus, cerebellum and motor cortical areas 20 , 21 . However, these studies were conducted in participants without obesity and did not assess the effect of such intragastric infusions on striatal dopamine release. Given the devastating impact of obesity worldwide, it is highly relevant to determine whether post-ingestive nutrient signals and/or the subsequent striatal dopamine response are impaired in humans with obesity. On the basis of the available data, we hypothesized that intragastric infusions of glucose and lipid modulate cerebral neuronal activity and striatal dopamine release in lean humans and that these responses are impaired in humans with obesity. Finally, we hypothesized that an impaired response to post-ingestive nutrient signals is partially reversible with diet-induced weight loss. In this regard, we have previously demonstrated that obesity-associated changes in the striatal dopamine system are partially reversed by bariatric surgery-induced weight loss in women 22 . To test our hypotheses, we recruited lean individuals and individuals with obesity and evaluated the effects of direct, intragastric infusions of tap water (isovolumetric and noncaloric control), glucose and lipids on cerebral neuronal activity using fMRI and on striatal dopamine", "role": "user" }, { "content": "Brain responses to specific nutrients are diminished in individuals with obesity and are not improved after weight loss, according to a study led by Amsterdam UMC and Yale University, published today in Nature Metabolism. \"Our findings suggest that long-lasting brain adaptations occur in individuals with obesity, which could affect eating behavior. We found that those with obesity released less dopamine in an area of the brain important for the motivational aspect of food intake compared to people with a healthy bodyweight. Dopamine is involved in the rewarding feelings of food intake,\" says Mireille Serlie, lead researcher and Professor of Endocrinology at Amsterdam UMC. \"The subjects with obesity also showed reduced responsivity in brain activity upon infusion of nutrients into the stomach. Overall, these findings suggest that sensing of nutrients in the stomach and gut and/or of nutritional signals is reduced in obesity and this might have profound consequences for food intake.\" Food intake is dependent on the integration of complex metabolic and neuronal signals between the brain and several organs, including the gut and nutritional signals in the blood. This network triggers sensations of hunger and satiation, regulates food intake as well as the motivation to look for food. While these processes are increasingly better understood in animals, including in the context of metabolic diseases such as obesity, much less is known about what happens in humans. Partly due to the difficulty in designing experimental setups in the clinic that could shed light on to these mechanisms. In order to address this lack of knowledge, Serlie, who is also a professor at Yale, and colleagues from both institutions designed a controlled trial. This trial consisted of infusing specific nutrients directly into the stomach of 30 participants with a healthy bodyweight and 30 individuals with obesity, while simultaneously measuring their brain activity through the use of MRI and dopamine release using SPECT scans. While the participants with a healthy bodyweight displayed specific patterns of brain activity and dopamine release after nutrient infusion, these responses were severely blunted in participants with obesity. Moreover, 10% body weight loss (following a 12-week diet) was not sufficient to restore these brain responses in individuals with obesity, suggesting long-lasting brain adaptations occur in the context of obesity and remain even after weight loss is achieved. \"The fact that these responses in the brain are not restored after weight loss, may explain why most people regain weight after initially successful weight loss,\" concludes Serlie. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Post-ingestive nutrient signals to the brain regulate eating behaviour in rodents, and impaired responses to these signals have been associated with pathological feeding behaviour and obesity. To study this in humans, we performed a single-blinded, randomized, controlled, crossover study in 30 humans with a healthy body weight (females N = 12, males N = 18) and 30 humans with obesity (females N = 18, males N = 12). We assessed the effect of intragastric glucose, lipid and water (noncaloric isovolumetric control) infusions on the primary endpoints cerebral neuronal activity and striatal dopamine release, as well as on the secondary endpoints plasma hormones and glucose, hunger scores and caloric intake. To study whether impaired responses in participants with obesity would be partially reversible with diet-induced weight loss, imaging was repeated after 10% diet-induced weight loss. We show that intragastric glucose and lipid infusions induce orosensory-independent and preference-independent, nutrient-specific cerebral neuronal activity and striatal dopamine release in lean participants. In contrast, participants with obesity have severely impaired brain responses to post-ingestive nutrients. Importantly, the impaired neuronal responses are not restored after diet-induced weight loss. Impaired neuronal responses to nutritional signals may contribute to overeating and obesity, and ongoing resistance to post-ingestive nutrient signals after significant weight loss may in part explain the high rate of weight regain after successful weight loss. Main The orosensory effects of food have long been identified as the primary driving force behind food intake beyond homeostatic needs 1 , 2 . In addition to the palatability of nutrients, increasing evidence shows a potent role for signals that arise after the ingestion of food—so-called post-ingestive nutrient signals—in the regulation of eating behaviour 3 . For instance, Trpm5 −/− mice that lack sweet taste transduction still develop a clear preference for sucrose over noncaloric solutions 4 , indicating a calorie-dependent and taste-independent effect on food intake. Other studies show that mice are receptive to appetition, the process of flavour conditioning associated with intragastric infusion of nutrients 5 , 6 . Several post-ingestive nutrient signals convey the presence of nutrients in the gastrointestinal tract to the brain and may contribute to the regulation of eating behaviour via the gut–brain axis. Firstly, gastrointestinal vagal nerve afferents are stimulated upon the presence of nutrients and mediate anorexigenic effects via the brainstem to several downstream brain regions 7 , 8 . Secondly, nutrients in the gastrointestinal lumen induce an endocrine response and facilitate the digestion, absorption and subsequent metabolism of nutrients. The post-ingestive endocrine response includes, but is not limited to, enhanced release of insulin from pancreatic beta cells, glucagon-like peptide-1 (GLP-1) from intestinal L cells 9 , 10 , and suppressed release of ghrelin from gastric X/A-like cells 11 . Gastrointestinal vagal nerve afferents and multiple brain regions express receptors for these hormones, but the exact mechanisms by which insulin and GLP-1 mediate anorexigenic effects and ghrelin mediates orexigenic effects remain to be elucidated 12 . Finally, changes in the concentrations of nutrients and/or metabolites in the portal or systemic circulation provide a direct post-ingestive signal of nutrient availability for different brain regions involved in the central regulation of food intake 13 , 14 . While the post-ingestive signals induced by glucose versus lipid consumption differ in several aspects, administration of both carbohydrate and lipid promotes the release of striatal dopamine in rodents 7 , 15 . The striatum is involved in the rewarding and motivational aspects of food intake 7 , 13 . A study in humans without obesity reported a biphasic striatal dopamine response immediately and approximately 20 min following the consumption of a milkshake solution, which was hypothesized to reflect both an immediate orosensory and delayed post-ingestive response 16 . In rodents, striatal dopamine release is positively and proportionally related to intragastric fat infusions, and intact striatal dopamine signalling is required to reduce subsequent caloric intake in proportion to the amount of fat directly infused into the stomach 17 . Interestingly, long-term exposure to a high-fat diet resulted in an impaired striatal dopaminergic response to an intragastric lipid infusion 18 . Taken together, these studies demonstrate that, (i) in addition to direct gustatory effects of nutrients, post-ingestive nutrient signals contribute to the regulation of feeding behaviour; and (ii) impaired striatal dopamine signalling after prolonged exposure to high-calorie nutrients may promote subsequent overeating and obesity. Despite these intriguing mostly preclinical studies, little is known about the role of post-ingestive nutrient signals in human physiology or obesity development. A few studies have assessed the response of the brain to the isolated, orosensory-independent, post-ingestive effects of glucose or dodecanoate (a C12 fatty acid) by means of intragastric infusions using functional magnetic resonance imaging (fMRI) 19 , 20 , 21 . The intragastric glucose infusion decreased blood oxygen level-dependent (BOLD) signal in the striatum and several other brain regions, including the brainstem, hypothalamus and thalamus 19 . The intragastric dodecanoate infusion increased BOLD signal in the brainstem, pons, hypothalamus, cerebellum and motor cortical areas 20 , 21 . However, these studies were conducted in participants without obesity and did not assess the effect of such intragastric infusions on striatal dopamine release. Given the devastating impact of obesity worldwide, it is highly relevant to determine whether post-ingestive nutrient signals and/or the subsequent striatal dopamine response are impaired in humans with obesity. On the basis of the available data, we hypothesized that intragastric infusions of glucose and lipid modulate cerebral neuronal activity and striatal dopamine release in lean humans and that these responses are impaired in humans with obesity. Finally, we hypothesized that an impaired response to post-ingestive nutrient signals is partially reversible with diet-induced weight loss. In this regard, we have previously demonstrated that obesity-associated changes in the striatal dopamine system are partially reversed by bariatric surgery-induced weight loss in women 22 . To test our hypotheses, we recruited lean individuals and individuals with obesity and evaluated the effects of direct, intragastric infusions of tap water (isovolumetric and noncaloric control), glucose and lipids on cerebral neuronal activity using fMRI and on striatal dopamine<|im_end|> <|im_start|>assistant Brain responses to specific nutrients are diminished in individuals with obesity and are not improved after weight loss, according to a study led by Amsterdam UMC and Yale University, published today in Nature Metabolism. "Our findings suggest that long-lasting brain adaptations occur in individuals with obesity, which could affect eating behavior. We found that those with obesity released less dopamine in an area of the brain important for the motivational aspect of food intake compared to people with a healthy bodyweight. Dopamine is involved in the rewarding feelings of food intake," says Mireille Serlie, lead researcher and Professor of Endocrinology at Amsterdam UMC. "The subjects with obesity also showed reduced responsivity in brain activity upon infusion of nutrients into the stomach. Overall, these findings suggest that sensing of nutrients in the stomach and gut and/or of nutritional signals is reduced in obesity and this might have profound consequences for food intake." Food intake is dependent on the integration of complex metabolic and neuronal signals between the brain and several organs, including the gut and nutritional signals in the blood. This network triggers sensations of hunger and satiation, regulates food intake as well as the motivation to look for food. While these processes are increasingly better understood in animals, including in the context of metabolic diseases such as obesity, much less is known about what happens in humans. Partly due to the difficulty in designing experimental setups in the clinic that could shed light on to these mechanisms. In order to address this lack of knowledge, Serlie, who is also a professor at Yale, and colleagues from both institutions designed a controlled trial. This trial consisted of infusing specific nutrients directly into the stomach of 30 participants with a healthy bodyweight and 30 individuals with obesity, while simultaneously measuring their brain activity through the use of MRI and dopamine release using SPECT scans. While the participants with a healthy bodyweight displayed specific patterns of brain activity and dopamine release after nutrient infusion, these responses were severely blunted in participants with obesity. Moreover, 10% body weight loss (following a 12-week diet) was not sufficient to restore these brain responses in individuals with obesity, suggesting long-lasting brain adaptations occur in the context of obesity and remain even after weight loss is achieved. "The fact that these responses in the brain are not restored after weight loss, may explain why most people regain weight after initially successful weight loss," concludes Serlie. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 3962, 85005, 478, 535, 50123, 17738, 311, 279, 8271, 37377, 12459, 17432, 304, 94209, 11, 323, 50160, 14847, 311, 1521, 17738, 617, 1027, 5938, 449, 89961, 26040, 17432, 323, 33048, 13, 2057, 4007, 420, 304, 12966, 11, 584, 10887, 264, 3254, 16677, 17003, 11, 47341, 11, 14400, 11, 49480, 4007, 304, 220, 966, 12966, 449, 264, 9498, 2547, 4785, 320, 69, 87503, 452, 284, 220, 717, 11, 25000, 452, 284, 220, 972, 8, 323, 220, 966, 12966, 449, 33048, 320, 69, 87503, 452, 284, 220, 972, 11, 25000, 452, 284, 220, 717, 570, 1226, 32448, 279, 2515, 315, 10805, 12748, 496, 292, 34323, 11, 68700, 323, 3090, 320, 6414, 5531, 27456, 374, 869, 1152, 16743, 2585, 8, 4225, 36807, 389, 279, 6156, 37442, 60745, 79402, 5820, 323, 6076, 4306, 66128, 4984, 11, 439, 1664, 439, 389, 279, 14580, 37442, 32426, 44315, 323, 34323, 11, 34906, 12483, 323, 1652, 27456, 23730, 13, 2057, 4007, 3508, 50160, 14847, 304, 13324, 449, 33048, 1053, 387, 26310, 81193, 449, 10173, 38973, 4785, 4814, 11, 32758, 574, 11763, 1306, 220, 605, 4, 10173, 38973, 4785, 4814, 13, 1226, 1501, 430, 10805, 12748, 496, 292, 34323, 323, 68700, 4225, 36807, 49853, 477, 437, 729, 683, 98885, 323, 22698, 98885, 11, 50123, 19440, 60745, 79402, 5820, 323, 6076, 4306, 66128, 4984, 304, 16025, 13324, 13, 763, 13168, 11, 13324, 449, 33048, 617, 35906, 50160, 8271, 14847, 311, 1772, 85005, 478, 535, 37493, 13, 13516, 18007, 11, 279, 50160, 79402, 14847, 527, 539, 28101, 1306, 10173, 38973, 4785, 4814, 13, 14727, 25260, 79402, 14847, 311, 43226, 17738, 1253, 17210, 311, 927, 91955, 323, 33048, 11, 323, 14529, 13957, 311, 1772, 85005, 478, 535, 50123, 17738, 1306, 5199, 4785, 4814, 1253, 304, 961, 10552, 279, 1579, 4478, 315, 4785, 49655, 1306, 6992, 4785, 4814, 13, 4802, 578, 477, 437, 729, 683, 6372, 315, 3691, 617, 1317, 1027, 11054, 439, 279, 6156, 10043, 5457, 4920, 3691, 23730, 7953, 2162, 537, 780, 3966, 220, 16, 1174, 220, 17, 662, 763, 5369, 311, 279, 11091, 2143, 1429, 315, 37493, 11, 7859, 6029, 5039, 264, 36875, 3560, 369, 17738, 430, 31889, 1306, 279, 88447, 315, 3691, 2345, 708, 19434, 1772, 85005, 478, 535, 50123, 17738, 49525, 279, 19812, 315, 12459, 17432, 220, 18, 662, 1789, 2937, 11, 1183, 5298, 20, 25173, 14, 34363, 24548, 430, 6996, 10437, 12945, 1380, 23985, 2103, 2274, 264, 2867, 22698, 369, 11405, 25888, 927, 2536, 5531, 27456, 10105, 220, 19, 1174, 19392, 264, 52703, 43918, 323, 12945, 98885, 2515, 389, 3691, 23730, 13, 7089, 7978, 1501, 430, 24548, 527, 88651, 311, 30168, 684, 11, 279, 1920, 315, 47697, 35121, 5938, 449, 10805, 12748, 496, 292, 71308, 315, 37493, 220, 20, 1174, 220, 21, 662, 26778, 1772, 85005, 478, 535, 50123, 17738, 20599, 279, 9546, 315, 37493, 304, 279, 80311, 42929, 311, 279, 8271, 323, 1253, 17210, 311, 279, 19812, 315, 12459, 17432, 4669, 279, 18340, 4235, 54160, 8183, 13, 77795, 11, 80311, 17764, 278, 32015, 264, 3018, 812, 527, 81471, 5304, 279, 9546, 315, 37493, 323, 1812, 6629, 459, 114340, 6569, 292, 6372, 4669, 279, 8271, 65188, 311, 3892, 52452, 8271, 13918, 220, 22, 1174, 220, 23, 662, 72131, 11, 37493, 304, 279, 80311, 326, 28999, 49853, 459, 842, 78738, 2077, 323, 28696, 279, 74502, 11, 44225, 323, 17876, 39097, 315, 37493, 13, 578, 1772, 85005, 478, 535, 842, 78738, 2077, 5764, 11, 719, 374, 539, 7347, 311, 11, 24872, 4984, 315, 32152, 505, 98144, 13746, 7917, 11, 30217, 6241, 12970, 72249, 12, 16, 320, 3910, 47, 12, 16, 8, 505, 63900, 445, 7917, 220, 24, 1174, 220, 605, 1174, 323, 56089, 4984, 315, 37224, 265, 3817, 505, 89385, 1630, 10576, 12970, 7917, 220, 806, 662, 480, 23834, 71558, 17764, 278, 32015, 264, 3018, 812, 323, 5361, 8271, 13918, 3237, 44540, 369, 1521, 44315, 11, 719, 279, 4839, 24717, 555, 902, 32152, 323, 5705, 47, 12, 16, 1812, 6629, 459, 114340, 6569, 292, 6372, 323, 37224, 265, 3817, 25098, 988, 16536, 87, 6569, 292, 6372, 7293, 311, 387, 97298, 660, 220, 717, 662, 17830, 11, 4442, 304, 279, 32466, 315, 37493, 323, 5255, 28168, 3695, 304, 279, 24007, 477, 46417, 35855, 3493, 264, 2167, 1772, 85005, 478, 535, 8450, 315, 50123, 18539, 369, 2204, 8271, 13918, 6532, 304, 279, 8792, 19812, 315, 3691, 23730, 220, 1032, 1174, 220, 975, 662, 6104, 279, 1772, 85005, 478, 535, 17738, 36572, 555, 34323, 19579, 68700, 15652, 1782, 304, 3892, 13878, 11, 8735, 315, 2225, 67732, 323, 68700, 39990, 279, 4984, 315, 6076, 4306, 66128, 304, 94209, 220, 22, 1174, 220, 868, 662, 578, 6076, 27349, 374, 6532, 304, 279, 42093, 323, 88459, 13878, 315, 3691, 23730, 220, 22, 1174, 220, 1032, 662, 362, 4007, 304, 12966, 2085, 33048, 5068, 264, 29978, 4752, 292, 6076, 4306, 66128, 2077, 7214, 323, 13489, 220, 508, 1332, 2768, 279, 15652, 315, 264, 14403, 30761, 6425, 11, 902, 574, 22601, 83979, 311, 8881, 2225, 459, 14247, 477, 437, 729, 683, 323, 23540, 1772, 85005, 478, 535, 2077, 220, 845, 662, 763, 94209, 11, 6076, 4306, 66128, 4984, 374, 40646, 323, 21801, 750, 5552, 311, 10805, 12748, 496, 292, 8834, 4225, 36807, 11, 323, 35539, 6076, 4306, 66128, 91977, 374, 2631, 311, 8108, 17876, 1652, 27456, 23730, 304, 21801, 311, 279, 3392, 315, 8834, 6089, 72903, 1139, 279, 23152, 220, 1114, 662, 58603, 11, 1317, 9860, 14675, 311, 264, 1579, 64354, 10173, 19543, 304, 459, 50160, 6076, 4306, 27420, 8778, 75439, 2077, 311, 459, 10805, 12748, 496, 292, 68700, 71308, 220, 972, 662, 57074, 3871, 11, 1521, 7978, 20461, 430, 11, 320, 72, 8, 304, 5369, 311, 2167, 30914, 5382, 6372, 315, 37493, 11, 1772, 85005, 478, 535, 50123, 17738, 17210, 311, 279, 19812, 315, 26040, 17432, 26, 323, 320, 3893, 8, 50160, 6076, 4306, 66128, 91977, 1306, 44387, 14675, 311, 1579, 49236, 30303, 37493, 1253, 12192, 17876, 927, 91955, 323, 33048, 13, 18185, 1521, 41765, 10213, 864, 91899, 7978, 11, 2697, 374, 3967, 922, 279, 3560, 315, 1772, 85005, 478, 535, 50123, 17738, 304, 3823, 78152, 477, 33048, 4500, 13, 362, 2478, 7978, 617, 32448, 279, 2077, 315, 279, 8271, 311, 279, 25181, 11, 477, 437, 729, 683, 98885, 11, 1772, 85005, 478, 535, 6372, 315, 34323, 477, 294, 536, 69377, 349, 320, 64, 356, 717, 40085, 13935, 8, 555, 3445, 315, 10805, 12748, 496, 292, 4225, 36807, 1701, 16003, 24924, 58081, 32758, 320, 69, 79770, 8, 220, 777, 1174, 220, 508, 1174, 220, 1691, 662, 578, 10805, 12748, 496, 292, 34323, 71308, 25983, 6680, 24463, 2237, 43918, 320, 33, 8021, 8, 8450, 304, 279, 6076, 27349, 323, 3892, 1023, 8271, 13918, 11, 2737, 279, 8271, 65188, 11, 45455, 17243, 355, 323, 270, 17243, 355, 220, 777, 662, 578, 10805, 12748, 496, 292, 294, 536, 69377, 349, 71308, 7319, 426, 8021, 8450, 304, 279, 8271, 65188, 11, 281, 2439, 11, 45455, 17243, 355, 11, 28091, 17696, 372, 323, 9048, 83619, 5789, 220, 508, 1174, 220, 1691, 662, 4452, 11, 1521, 7978, 1051, 13375, 304, 13324, 2085, 33048, 323, 1550, 539, 8720, 279, 2515, 315, 1778, 10805, 12748, 496, 292, 4225, 36807, 389, 6076, 4306, 66128, 4984, 13, 16644, 279, 33318, 5536, 315, 33048, 15603, 11, 433, 374, 7701, 9959, 311, 8417, 3508, 1772, 85005, 478, 535, 50123, 17738, 323, 5255, 279, 17876, 6076, 4306, 66128, 2077, 527, 50160, 304, 12966, 449, 33048, 13, 1952, 279, 8197, 315, 279, 2561, 828, 11, 584, 22601, 83979, 430, 10805, 12748, 496, 292, 4225, 36807, 315, 34323, 323, 68700, 1491, 6468, 60745, 79402, 5820, 323, 6076, 4306, 66128, 4984, 304, 16025, 12966, 323, 430, 1521, 14847, 527, 50160, 304, 12966, 449, 33048, 13, 17830, 11, 584, 22601, 83979, 430, 459, 50160, 2077, 311, 1772, 85005, 478, 535, 50123, 17738, 374, 26310, 81193, 449, 10173, 38973, 4785, 4814, 13, 763, 420, 5363, 11, 584, 617, 8767, 21091, 430, 33048, 75968, 4442, 304, 279, 6076, 4306, 66128, 1887, 527, 26310, 28537, 555, 293, 41979, 2265, 15173, 38973, 4785, 4814, 304, 3278, 220, 1313, 662, 2057, 1296, 1057, 74513, 11, 584, 45425, 16025, 7931, 323, 7931, 449, 33048, 323, 26126, 279, 6372, 315, 2167, 11, 10805, 12748, 496, 292, 4225, 36807, 315, 15596, 3090, 320, 285, 869, 1152, 16743, 323, 2536, 5531, 27456, 2585, 705, 34323, 323, 19588, 3447, 389, 60745, 79402, 5820, 1701, 282, 79770, 323, 389, 6076, 4306, 66128, 128257, 198, 128256, 78191, 198, 66177, 14847, 311, 3230, 37493, 527, 54182, 304, 7931, 449, 33048, 323, 527, 539, 13241, 1306, 4785, 4814, 11, 4184, 311, 264, 4007, 6197, 555, 38841, 549, 11865, 323, 44552, 3907, 11, 4756, 3432, 304, 22037, 6344, 53904, 2191, 13, 330, 8140, 14955, 4284, 430, 1317, 65265, 8271, 77765, 12446, 304, 7931, 449, 33048, 11, 902, 1436, 7958, 12459, 7865, 13, 1226, 1766, 430, 1884, 449, 33048, 6004, 2753, 66128, 304, 459, 3158, 315, 279, 8271, 3062, 369, 279, 88459, 13189, 315, 3691, 23730, 7863, 311, 1274, 449, 264, 9498, 2547, 4870, 13, 97674, 20588, 374, 6532, 304, 279, 42093, 16024, 315, 3691, 23730, 1359, 2795, 386, 556, 4618, 8409, 11828, 11, 3063, 32185, 323, 17054, 315, 4060, 91153, 2508, 520, 38841, 549, 11865, 13, 330, 791, 15223, 449, 33048, 1101, 8710, 11293, 4294, 1968, 304, 8271, 5820, 5304, 71308, 315, 37493, 1139, 279, 23152, 13, 28993, 11, 1521, 14955, 4284, 430, 60199, 315, 37493, 304, 279, 23152, 323, 18340, 323, 5255, 315, 43226, 17738, 374, 11293, 304, 33048, 323, 420, 2643, 617, 28254, 16296, 369, 3691, 23730, 1210, 12369, 23730, 374, 18222, 389, 279, 18052, 315, 6485, 41861, 323, 79402, 17738, 1990, 279, 8271, 323, 3892, 36853, 11, 2737, 279, 18340, 323, 43226, 17738, 304, 279, 6680, 13, 1115, 4009, 31854, 72597, 315, 34906, 323, 7731, 7246, 11, 80412, 3691, 23730, 439, 1664, 439, 279, 25835, 311, 1427, 369, 3691, 13, 6104, 1521, 11618, 527, 15098, 2731, 16365, 304, 10099, 11, 2737, 304, 279, 2317, 315, 41861, 19338, 1778, 439, 33048, 11, 1790, 2753, 374, 3967, 922, 1148, 8741, 304, 12966, 13, 3744, 398, 4245, 311, 279, 17250, 304, 30829, 22772, 84823, 304, 279, 28913, 430, 1436, 25351, 3177, 389, 311, 1521, 24717, 13, 763, 2015, 311, 2686, 420, 6996, 315, 6677, 11, 8409, 11828, 11, 889, 374, 1101, 264, 14561, 520, 44552, 11, 323, 18105, 505, 2225, 14673, 6319, 264, 14400, 9269, 13, 1115, 9269, 44660, 315, 4225, 985, 3230, 37493, 6089, 1139, 279, 23152, 315, 220, 966, 13324, 449, 264, 9498, 2547, 4870, 323, 220, 966, 7931, 449, 33048, 11, 1418, 25291, 30090, 872, 8271, 5820, 1555, 279, 1005, 315, 52460, 323, 66128, 4984, 1701, 328, 7433, 43739, 13, 6104, 279, 13324, 449, 264, 9498, 2547, 4870, 12882, 3230, 12912, 315, 8271, 5820, 323, 66128, 4984, 1306, 50123, 71308, 11, 1521, 14847, 1051, 35906, 1529, 28736, 304, 13324, 449, 33048, 13, 23674, 11, 220, 605, 4, 2547, 4785, 4814, 320, 44018, 264, 220, 717, 30609, 10173, 8, 574, 539, 14343, 311, 15301, 1521, 8271, 14847, 304, 7931, 449, 33048, 11, 23377, 1317, 65265, 8271, 77765, 12446, 304, 279, 2317, 315, 33048, 323, 7293, 1524, 1306, 4785, 4814, 374, 17427, 13, 330, 791, 2144, 430, 1521, 14847, 304, 279, 8271, 527, 539, 28101, 1306, 4785, 4814, 11, 1253, 10552, 3249, 1455, 1274, 49655, 4785, 1306, 15453, 6992, 4785, 4814, 1359, 45537, 8409, 11828, 13, 220, 128257, 198 ]

1,886

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Reconstructing diet is critical to understanding hominin adaptations. Isotopic and functional morphological analyses of early hominins are compatible with consumption of hard foods, such as mechanically-protected seeds, but dental microwear analyses are not. The protective shells surrounding seeds are thought to induce complex enamel surface textures characterized by heavy pitting, but these are absent on the teeth of most early hominins. Here we report nanowear experiments showing that the hardest woody shells – the hardest tissues made by dicotyledonous plants – cause very minor damage to enamel but are themselves heavily abraded (worn) in the process. Thus, hard plant tissues do not regularly create pits on enamel surfaces despite high forces clearly being associated with their oral processing. We conclude that hard plant tissues barely influence microwear textures and the exploitation of seeds from graminoid plants such as grasses and sedges could have formed a critical element in the dietary ecology of hominins. Introduction Early hominin craniodental morphologies, evolving before cooking or sophisticated extra-oral food processing, represent adaptations to diet, but profound disagreement persists about the specific foods that drove evolutionary change. Isotopic evidence demonstrates that, starting in the mid-Pliocene (circa 3.5 million years ago) and continuing into the Pleistocene, the composition of hominin diets broadened. In most hominin species, it shifted over this period from consumption almost exclusively of C 3 vegetation (circa 85% of diet) to encompassing a moderate-to-large proportion of C 4 plant material (35–77% of diet) 1 , 2 . Although isotopic evidence indicates the photosynthetic pathway of carbon fixation, these data do not directly indicate the exact dietary source of such a signal. Enriched carbon implies early hominins ate either C 4 grasses, sedges or the animals that consumed these same graminoid plants 1 , 3 . However, predictions of what plant part may have contributed to such a signal vary: some authors suggest leaves 1 , 3 , while others focus on energy-rich plant storage organs such as corms or bulbs 4 . Here we advocate the case for seeds. These various plant parts differ in their mechanical properties and thus promote contrasting selection pressures on tooth morphology. Mechanical analyses of australopith teeth and jaws indicate that they were capable of generating high bite forces 5 , 6 with their very thick tooth enamel both strengthening their teeth and prolonging their functional life 7 , 8 , 9 . In particular, the low blunt cusps of australopith molars would be more resistant to fracture against hard foods, as exemplified by the woody casings of what are thus ‘mechanically protected’ plant embryos (Fig. 1 ) 10 . Whether this casing is derived from the seed integuments or the fruit endocarp, we call this a ‘mechanically-protected seed’ here. This feeding association contrasts with primates that typically have long sharp crests on their teeth as adaptations to eat tough compliant foods like leaves 7 , 8 , 11 , 12 . However, the morphological signal in australopiths seems to be at odds with the microwear signal conveyed in the surface texture of wear facets in hominin teeth. Figure 1 A schematic drawing of seeds mechanically protected by lignified woody tissue. ( a ) Large seeds of some dicotyledonous plants are protected by a woody seed shell. ( b ) Even small seeds of monocotyledons have lignified pericarps protecting the seed within. Full size image Conventional interpretations of dental microwear in primates suggest that a diet consisting of a large proportion of hard objects would produce a surface texture with a high complexity. Complexity is essentially a measure of the surface roughness, with wear facets demonstrating high complexity often associated with deep and elaborate scars 13 . Although there is variation in the microwear signals of Plio-Pleistocene hominins, in general, the wear facets of most early hominin teeth exhibit low to moderate complexity 1 , 14 . One notable exception from this trend is that of Paranthropus robustus which in some cases exhibits high surface texture complexity 1 . However, most australopiths tend to exhibit light surface striations that, in several species, are not strongly directed in parallel 1 . This lack of surface texture complexity is more in keeping with what one would expect from a primate that eats a considerable amount of tough compliant material, such as leaves, although extant primate folivores tend to exhibit surface textures with parallel oriented striations 15 . The apparent mismatch between morphology and microwear has fuelled a continual and at times heated debate about early hominin diets. Nowhere is this disparity more salient than for Paranthropus boisei whose highly derived, robust morphology has earned it the epithet “nutcracker man”, stemming from a predicted diet laden with hard objects 5 . Yet microwear studies have indicated this same species did not routinely eat hard objects and that its dentition was used for the processing of softer, tougher foods 3 . Resolution of these radically different interpretations requires an evaluation of the mechanics of microwear formation. Currently, there are little to no experimental data on sliding contacts between particles of woody plant material, such as pieces of seed shell, and enamel. Such particles represent the hardest plant tissues and, based on mechanical models of wear 16 , such tissues should not impart much damage on teeth. However, if particles of lignified plant tissue are unable to produce the deep or elaborate scars on enamel it seems unlikely that feeding on dietary items, such as mechanically protected seeds, would produce the complex surfaces textures predicted by traditional interpretations of dental microwear. It is plausible then that the presence or absence of complex surface textures measured in microwear analysis of tooth facets may not directly reflect the consumption of hard foods, but instead echo levels and types of dietary abrasives 17 . Here we present data on nanowear experiments investigating the interaction between heavily lignified plant tissue and enamel. We demonstrate that although the densest woody tissue can mark enamel surfaces it cannot produce deep elaborate features on the tooth surfaces. Further, by", "role": "user" }, { "content": "Go ahead, take a big bite. Hard plant foods may have made up a larger part of early human ancestors' diet than currently presumed, according to a new experimental study of modern tooth enamel from Washington University in St. Louis. Scientists often look at microscopic damage to teeth to infer what an animal was eating. This new research—using experiments looking at microscopic interactions between food particles and enamel—demonstrates that even the hardest plant tissues scarcely wear down primate teeth. The results have implications for reconstructing diet, and potentially for our interpretation of the fossil record of human evolution, researchers said. \"We found that hard plant tissues such as the shells of nuts and seeds barely influence microwear textures on teeth,\" said Adam van Casteren, lecturer in biological anthropology in Arts & Sciences, the first author of the new study in Scientific Reports. David S. Strait, professor of physical anthropology, is a co-author. Traditionally, eating hard foods is thought to damage teeth by producing microscopic pits. \"But if teeth don't demonstrate elaborate pits and scars, this doesn't necessarily rule out the consumption of hard food items,\" van Casteren said. Humans diverged from non-human apes about seven million years ago in Africa. The new study addresses an ongoing debate surrounding what some early human ancestors, the australopiths, were eating. These hominin species had very large teeth and jaws, and likely huge chewing muscles. \"All these morphological attributes seem to indicate they had the ability to produce large bite forces, and therefore likely chomped down on a diet of hard or bulky food items such as nuts, seeds or underground resources like tubers,\" van Casteren said. But most fossil australopith teeth don't show the kind of microscopic wear that would be expected in this scenario. The researchers decided to test it out. Previous mechanical experiments had shown how grit—literally, pieces of quartz rock—produces deep scratches on flat tooth surfaces, using a device that mimicked the microscopic interactions of particles on teeth. But there was little to no experimental data on what happens to tooth enamel when it comes in contact with actual woody plant material. For this study, the researchers attached tiny pieces of seed shells to a probe that they dragged across enamel from a Bornean orangutan molar tooth. They made 16 \"slides\" representing contacts between the enamel and three different seed shells from woody plants that are part of modern primate diets. The researchers dragged the seeds against enamel at forces comparable to any chewing action. The seed fragments made no large pits, scratches or fractures in the enamel, the researchers found. There were a few shallow grooves, but the scientists saw nothing that indicated that hard plant tissues could contribute meaningfully to dental microwear. The seed fragments themselves, however, showed signs of degradation from being rubbed against the enamel. This information is useful for anthropologists who are left with only fossils to try to reconstruct ancient diets. \"Our approach is not to look for correlations between the types of microscopic marks on teeth and foods being eaten—but instead to understand the underlying mechanics of how these scars on tooth surface are formed,\" van Casteren said. \"If we can fathom these fundamental concepts, we can generate more accurate pictures of what fossil hominins were eating.\" So those big australopith jaws could have been put to use chewing on large amounts of seeds—without scarring teeth. \"And that makes perfect sense in terms of the shape of their teeth\" said Peter Lucas, a co-author at the Smithsonian Tropical Research Institute, \"because the blunt low-cusped form of their molars are ideal for that purpose.\" \"When consuming many very small hard seeds, large bite forces are likely to be required to mill all the grains,\" van Casteren said. \"In the light of our new findings, it is plausible that small, hard objects like grass seeds or sedge nutlets were a dietary resource for early hominins.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Reconstructing diet is critical to understanding hominin adaptations. Isotopic and functional morphological analyses of early hominins are compatible with consumption of hard foods, such as mechanically-protected seeds, but dental microwear analyses are not. The protective shells surrounding seeds are thought to induce complex enamel surface textures characterized by heavy pitting, but these are absent on the teeth of most early hominins. Here we report nanowear experiments showing that the hardest woody shells – the hardest tissues made by dicotyledonous plants – cause very minor damage to enamel but are themselves heavily abraded (worn) in the process. Thus, hard plant tissues do not regularly create pits on enamel surfaces despite high forces clearly being associated with their oral processing. We conclude that hard plant tissues barely influence microwear textures and the exploitation of seeds from graminoid plants such as grasses and sedges could have formed a critical element in the dietary ecology of hominins. Introduction Early hominin craniodental morphologies, evolving before cooking or sophisticated extra-oral food processing, represent adaptations to diet, but profound disagreement persists about the specific foods that drove evolutionary change. Isotopic evidence demonstrates that, starting in the mid-Pliocene (circa 3.5 million years ago) and continuing into the Pleistocene, the composition of hominin diets broadened. In most hominin species, it shifted over this period from consumption almost exclusively of C 3 vegetation (circa 85% of diet) to encompassing a moderate-to-large proportion of C 4 plant material (35–77% of diet) 1 , 2 . Although isotopic evidence indicates the photosynthetic pathway of carbon fixation, these data do not directly indicate the exact dietary source of such a signal. Enriched carbon implies early hominins ate either C 4 grasses, sedges or the animals that consumed these same graminoid plants 1 , 3 . However, predictions of what plant part may have contributed to such a signal vary: some authors suggest leaves 1 , 3 , while others focus on energy-rich plant storage organs such as corms or bulbs 4 . Here we advocate the case for seeds. These various plant parts differ in their mechanical properties and thus promote contrasting selection pressures on tooth morphology. Mechanical analyses of australopith teeth and jaws indicate that they were capable of generating high bite forces 5 , 6 with their very thick tooth enamel both strengthening their teeth and prolonging their functional life 7 , 8 , 9 . In particular, the low blunt cusps of australopith molars would be more resistant to fracture against hard foods, as exemplified by the woody casings of what are thus ‘mechanically protected’ plant embryos (Fig. 1 ) 10 . Whether this casing is derived from the seed integuments or the fruit endocarp, we call this a ‘mechanically-protected seed’ here. This feeding association contrasts with primates that typically have long sharp crests on their teeth as adaptations to eat tough compliant foods like leaves 7 , 8 , 11 , 12 . However, the morphological signal in australopiths seems to be at odds with the microwear signal conveyed in the surface texture of wear facets in hominin teeth. Figure 1 A schematic drawing of seeds mechanically protected by lignified woody tissue. ( a ) Large seeds of some dicotyledonous plants are protected by a woody seed shell. ( b ) Even small seeds of monocotyledons have lignified pericarps protecting the seed within. Full size image Conventional interpretations of dental microwear in primates suggest that a diet consisting of a large proportion of hard objects would produce a surface texture with a high complexity. Complexity is essentially a measure of the surface roughness, with wear facets demonstrating high complexity often associated with deep and elaborate scars 13 . Although there is variation in the microwear signals of Plio-Pleistocene hominins, in general, the wear facets of most early hominin teeth exhibit low to moderate complexity 1 , 14 . One notable exception from this trend is that of Paranthropus robustus which in some cases exhibits high surface texture complexity 1 . However, most australopiths tend to exhibit light surface striations that, in several species, are not strongly directed in parallel 1 . This lack of surface texture complexity is more in keeping with what one would expect from a primate that eats a considerable amount of tough compliant material, such as leaves, although extant primate folivores tend to exhibit surface textures with parallel oriented striations 15 . The apparent mismatch between morphology and microwear has fuelled a continual and at times heated debate about early hominin diets. Nowhere is this disparity more salient than for Paranthropus boisei whose highly derived, robust morphology has earned it the epithet “nutcracker man”, stemming from a predicted diet laden with hard objects 5 . Yet microwear studies have indicated this same species did not routinely eat hard objects and that its dentition was used for the processing of softer, tougher foods 3 . Resolution of these radically different interpretations requires an evaluation of the mechanics of microwear formation. Currently, there are little to no experimental data on sliding contacts between particles of woody plant material, such as pieces of seed shell, and enamel. Such particles represent the hardest plant tissues and, based on mechanical models of wear 16 , such tissues should not impart much damage on teeth. However, if particles of lignified plant tissue are unable to produce the deep or elaborate scars on enamel it seems unlikely that feeding on dietary items, such as mechanically protected seeds, would produce the complex surfaces textures predicted by traditional interpretations of dental microwear. It is plausible then that the presence or absence of complex surface textures measured in microwear analysis of tooth facets may not directly reflect the consumption of hard foods, but instead echo levels and types of dietary abrasives 17 . Here we present data on nanowear experiments investigating the interaction between heavily lignified plant tissue and enamel. We demonstrate that although the densest woody tissue can mark enamel surfaces it cannot produce deep elaborate features on the tooth surfaces. Further, by<|im_end|> <|im_start|>assistant Go ahead, take a big bite. Hard plant foods may have made up a larger part of early human ancestors' diet than currently presumed, according to a new experimental study of modern tooth enamel from Washington University in St. Louis. Scientists often look at microscopic damage to teeth to infer what an animal was eating. This new research—using experiments looking at microscopic interactions between food particles and enamel—demonstrates that even the hardest plant tissues scarcely wear down primate teeth. The results have implications for reconstructing diet, and potentially for our interpretation of the fossil record of human evolution, researchers said. "We found that hard plant tissues such as the shells of nuts and seeds barely influence microwear textures on teeth," said Adam van Casteren, lecturer in biological anthropology in Arts & Sciences, the first author of the new study in Scientific Reports. David S. Strait, professor of physical anthropology, is a co-author. Traditionally, eating hard foods is thought to damage teeth by producing microscopic pits. "But if teeth don't demonstrate elaborate pits and scars, this doesn't necessarily rule out the consumption of hard food items," van Casteren said. Humans diverged from non-human apes about seven million years ago in Africa. The new study addresses an ongoing debate surrounding what some early human ancestors, the australopiths, were eating. These hominin species had very large teeth and jaws, and likely huge chewing muscles. "All these morphological attributes seem to indicate they had the ability to produce large bite forces, and therefore likely chomped down on a diet of hard or bulky food items such as nuts, seeds or underground resources like tubers," van Casteren said. But most fossil australopith teeth don't show the kind of microscopic wear that would be expected in this scenario. The researchers decided to test it out. Previous mechanical experiments had shown how grit—literally, pieces of quartz rock—produces deep scratches on flat tooth surfaces, using a device that mimicked the microscopic interactions of particles on teeth. But there was little to no experimental data on what happens to tooth enamel when it comes in contact with actual woody plant material. For this study, the researchers attached tiny pieces of seed shells to a probe that they dragged across enamel from a Bornean orangutan molar tooth. They made 16 "slides" representing contacts between the enamel and three different seed shells from woody plants that are part of modern primate diets. The researchers dragged the seeds against enamel at forces comparable to any chewing action. The seed fragments made no large pits, scratches or fractures in the enamel, the researchers found. There were a few shallow grooves, but the scientists saw nothing that indicated that hard plant tissues could contribute meaningfully to dental microwear. The seed fragments themselves, however, showed signs of degradation from being rubbed against the enamel. This information is useful for anthropologists who are left with only fossils to try to reconstruct ancient diets. "Our approach is not to look for correlations between the types of microscopic marks on teeth and foods being eaten—but instead to understand the underlying mechanics of how these scars on tooth surface are formed," van Casteren said. "If we can fathom these fundamental concepts, we can generate more accurate pictures of what fossil hominins were eating." So those big australopith jaws could have been put to use chewing on large amounts of seeds—without scarring teeth. "And that makes perfect sense in terms of the shape of their teeth" said Peter Lucas, a co-author at the Smithsonian Tropical Research Institute, "because the blunt low-cusped form of their molars are ideal for that purpose." "When consuming many very small hard seeds, large bite forces are likely to be required to mill all the grains," van Casteren said. "In the light of our new findings, it is plausible that small, hard objects like grass seeds or sedge nutlets were a dietary resource for early hominins." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 1050, 7750, 287, 10173, 374, 9200, 311, 8830, 5105, 65544, 77765, 13, 2209, 354, 25847, 323, 16003, 27448, 5848, 29060, 315, 4216, 5105, 258, 1354, 527, 18641, 449, 15652, 315, 2653, 15657, 11, 1778, 439, 99097, 12, 5883, 19595, 11, 719, 29106, 19748, 654, 686, 29060, 527, 539, 13, 578, 29219, 44054, 14932, 19595, 527, 3463, 311, 49853, 6485, 92848, 7479, 30953, 32971, 555, 8987, 281, 15154, 11, 719, 1521, 527, 28310, 389, 279, 18311, 315, 1455, 4216, 5105, 258, 1354, 13, 5810, 584, 1934, 20622, 363, 686, 21896, 9204, 430, 279, 37554, 24670, 1094, 44054, 1389, 279, 37554, 39881, 1903, 555, 21945, 354, 7756, 263, 788, 11012, 1389, 5353, 1633, 9099, 5674, 311, 92848, 719, 527, 5694, 17345, 671, 13584, 291, 320, 86, 1540, 8, 304, 279, 1920, 13, 14636, 11, 2653, 6136, 39881, 656, 539, 15870, 1893, 63008, 389, 92848, 27529, 8994, 1579, 8603, 9539, 1694, 5938, 449, 872, 21308, 8863, 13, 1226, 32194, 430, 2653, 6136, 39881, 20025, 10383, 19748, 654, 686, 30953, 323, 279, 40761, 315, 19595, 505, 1099, 8778, 590, 11012, 1778, 439, 16763, 288, 323, 11163, 4282, 1436, 617, 14454, 264, 9200, 2449, 304, 279, 34625, 72546, 315, 5105, 258, 1354, 13, 29438, 23591, 5105, 65544, 70637, 3205, 6430, 27448, 9268, 11, 42028, 1603, 17677, 477, 27877, 5066, 12, 10020, 3691, 8863, 11, 4097, 77765, 311, 10173, 11, 719, 28254, 62646, 67145, 922, 279, 3230, 15657, 430, 23980, 41993, 2349, 13, 2209, 354, 25847, 6029, 32216, 430, 11, 6041, 304, 279, 5209, 9483, 747, 78782, 320, 58132, 936, 220, 18, 13, 20, 3610, 1667, 4227, 8, 323, 14691, 1139, 279, 33540, 380, 78782, 11, 279, 18528, 315, 5105, 65544, 41943, 7353, 6901, 13, 763, 1455, 5105, 65544, 9606, 11, 433, 30073, 927, 420, 4261, 505, 15652, 4661, 24121, 315, 356, 220, 18, 54832, 320, 58132, 936, 220, 5313, 4, 315, 10173, 8, 311, 38632, 287, 264, 24070, 4791, 40248, 21801, 315, 356, 220, 19, 6136, 3769, 320, 1758, 4235, 2813, 4, 315, 10173, 8, 220, 16, 1174, 220, 17, 662, 10541, 69551, 25847, 6029, 15151, 279, 7397, 1910, 18015, 38970, 315, 12782, 84862, 11, 1521, 828, 656, 539, 6089, 13519, 279, 4839, 34625, 2592, 315, 1778, 264, 8450, 13, 2998, 14172, 291, 12782, 24897, 4216, 5105, 258, 1354, 30912, 3060, 356, 220, 19, 16763, 288, 11, 11163, 4282, 477, 279, 10099, 430, 27073, 1521, 1890, 1099, 8778, 590, 11012, 220, 16, 1174, 220, 18, 662, 4452, 11, 20492, 315, 1148, 6136, 961, 1253, 617, 20162, 311, 1778, 264, 8450, 13592, 25, 1063, 12283, 4284, 11141, 220, 16, 1174, 220, 18, 1174, 1418, 3885, 5357, 389, 4907, 41947, 6136, 5942, 36853, 1778, 439, 272, 494, 82, 477, 54320, 220, 19, 662, 5810, 584, 29115, 279, 1162, 369, 19595, 13, 4314, 5370, 6136, 5596, 1782, 304, 872, 22936, 6012, 323, 8617, 12192, 75055, 6727, 40850, 389, 26588, 79612, 13, 51684, 29060, 315, 264, 5523, 454, 411, 18311, 323, 82356, 13519, 430, 814, 1051, 13171, 315, 24038, 1579, 23556, 8603, 220, 20, 1174, 220, 21, 449, 872, 1633, 12314, 26588, 92848, 2225, 48513, 872, 18311, 323, 33482, 287, 872, 16003, 2324, 220, 22, 1174, 220, 23, 1174, 220, 24, 662, 763, 4040, 11, 279, 3428, 49770, 81070, 1725, 315, 264, 5523, 454, 411, 22337, 1590, 1053, 387, 810, 31785, 311, 59904, 2403, 2653, 15657, 11, 439, 39039, 1908, 555, 279, 24670, 1094, 4865, 826, 315, 1148, 527, 8617, 3451, 2727, 5776, 2740, 2682, 529, 6136, 89873, 320, 30035, 13, 220, 16, 883, 220, 605, 662, 13440, 420, 74444, 374, 14592, 505, 279, 10533, 5503, 2901, 477, 279, 14098, 842, 511, 8035, 11, 584, 1650, 420, 264, 3451, 2727, 5776, 2740, 12, 5883, 10533, 529, 1618, 13, 1115, 26040, 15360, 83379, 449, 9036, 988, 430, 11383, 617, 1317, 17676, 1922, 37379, 389, 872, 18311, 439, 77765, 311, 8343, 11292, 49798, 15657, 1093, 11141, 220, 22, 1174, 220, 23, 1174, 220, 806, 1174, 220, 717, 662, 4452, 11, 279, 27448, 5848, 8450, 304, 264, 5523, 454, 411, 82, 5084, 311, 387, 520, 21448, 449, 279, 19748, 654, 686, 8450, 73897, 304, 279, 7479, 10651, 315, 10051, 62814, 304, 5105, 65544, 18311, 13, 19575, 220, 16, 362, 68144, 13633, 315, 19595, 99097, 2682, 555, 72700, 1908, 24670, 1094, 20438, 13, 320, 264, 883, 20902, 19595, 315, 1063, 21945, 354, 7756, 263, 788, 11012, 527, 2682, 555, 264, 24670, 1094, 10533, 12811, 13, 320, 293, 883, 7570, 2678, 19595, 315, 96157, 354, 7756, 2439, 617, 72700, 1908, 824, 292, 277, 1725, 22973, 279, 10533, 2949, 13, 8797, 1404, 2217, 1221, 44322, 58689, 315, 29106, 19748, 654, 686, 304, 9036, 988, 4284, 430, 264, 10173, 31706, 315, 264, 3544, 21801, 315, 2653, 6302, 1053, 8356, 264, 7479, 10651, 449, 264, 1579, 23965, 13, 71718, 374, 16168, 264, 6767, 315, 279, 7479, 11413, 2136, 11, 449, 10051, 62814, 45296, 1579, 23965, 3629, 5938, 449, 5655, 323, 37067, 61699, 220, 1032, 662, 10541, 1070, 374, 23851, 304, 279, 19748, 654, 686, 17738, 315, 393, 26205, 9483, 273, 380, 78782, 5105, 258, 1354, 11, 304, 4689, 11, 279, 10051, 62814, 315, 1455, 4216, 5105, 65544, 18311, 31324, 3428, 311, 24070, 23965, 220, 16, 1174, 220, 975, 662, 3861, 28289, 4788, 505, 420, 9327, 374, 430, 315, 4366, 32329, 897, 355, 22514, 355, 902, 304, 1063, 5157, 50829, 1579, 7479, 10651, 23965, 220, 16, 662, 4452, 11, 1455, 264, 5523, 454, 411, 82, 8541, 311, 31324, 3177, 7479, 6076, 811, 430, 11, 304, 3892, 9606, 11, 527, 539, 16917, 15910, 304, 15638, 220, 16, 662, 1115, 6996, 315, 7479, 10651, 23965, 374, 810, 304, 10494, 449, 1148, 832, 1053, 1755, 505, 264, 550, 3509, 430, 50777, 264, 24779, 3392, 315, 11292, 49798, 3769, 11, 1778, 439, 11141, 11, 8051, 1327, 519, 550, 3509, 9630, 344, 4692, 8541, 311, 31324, 7479, 30953, 449, 15638, 42208, 6076, 811, 220, 868, 662, 578, 10186, 36401, 1990, 79612, 323, 19748, 654, 686, 706, 10633, 839, 264, 77975, 323, 520, 3115, 32813, 11249, 922, 4216, 5105, 65544, 41943, 13, 4800, 6881, 374, 420, 66949, 810, 4371, 1188, 1109, 369, 4366, 32329, 897, 355, 712, 1082, 72, 6832, 7701, 14592, 11, 22514, 79612, 706, 15662, 433, 279, 64779, 295, 1054, 24217, 5192, 9881, 893, 9520, 77044, 505, 264, 19698, 10173, 82787, 449, 2653, 6302, 220, 20, 662, 14968, 19748, 654, 686, 7978, 617, 16717, 420, 1890, 9606, 1550, 539, 40076, 8343, 2653, 6302, 323, 430, 1202, 18653, 684, 574, 1511, 369, 279, 8863, 315, 64230, 11, 49331, 15657, 220, 18, 662, 38216, 315, 1521, 61127, 2204, 58689, 7612, 459, 16865, 315, 279, 30126, 315, 19748, 654, 686, 18488, 13, 25122, 11, 1070, 527, 2697, 311, 912, 22772, 828, 389, 34932, 19015, 1990, 19252, 315, 24670, 1094, 6136, 3769, 11, 1778, 439, 9863, 315, 10533, 12811, 11, 323, 92848, 13, 15483, 19252, 4097, 279, 37554, 6136, 39881, 323, 11, 3196, 389, 22936, 4211, 315, 10051, 220, 845, 1174, 1778, 39881, 1288, 539, 70772, 1790, 5674, 389, 18311, 13, 4452, 11, 422, 19252, 315, 72700, 1908, 6136, 20438, 527, 12153, 311, 8356, 279, 5655, 477, 37067, 61699, 389, 92848, 433, 5084, 17821, 430, 26040, 389, 34625, 3673, 11, 1778, 439, 99097, 2682, 19595, 11, 1053, 8356, 279, 6485, 27529, 30953, 19698, 555, 8776, 58689, 315, 29106, 19748, 654, 686, 13, 1102, 374, 50434, 1243, 430, 279, 9546, 477, 19821, 315, 6485, 7479, 30953, 17303, 304, 19748, 654, 686, 6492, 315, 26588, 62814, 1253, 539, 6089, 8881, 279, 15652, 315, 2653, 15657, 11, 719, 4619, 1722, 5990, 323, 4595, 315, 34625, 59681, 1924, 220, 1114, 662, 5810, 584, 3118, 828, 389, 20622, 363, 686, 21896, 24834, 279, 16628, 1990, 17345, 72700, 1908, 6136, 20438, 323, 92848, 13, 1226, 20461, 430, 8051, 279, 29050, 267, 24670, 1094, 20438, 649, 1906, 92848, 27529, 433, 4250, 8356, 5655, 37067, 4519, 389, 279, 26588, 27529, 13, 15903, 11, 555, 128257, 198, 128256, 78191, 198, 11087, 8469, 11, 1935, 264, 2466, 23556, 13, 11481, 6136, 15657, 1253, 617, 1903, 709, 264, 8294, 961, 315, 4216, 3823, 38618, 6, 10173, 1109, 5131, 62357, 11, 4184, 311, 264, 502, 22772, 4007, 315, 6617, 26588, 92848, 505, 6652, 3907, 304, 800, 13, 12140, 13, 57116, 3629, 1427, 520, 90090, 5674, 311, 18311, 311, 24499, 1148, 459, 10065, 574, 12459, 13, 1115, 502, 3495, 2345, 985, 21896, 3411, 520, 90090, 22639, 1990, 3691, 19252, 323, 92848, 2345, 67, 7439, 496, 988, 430, 1524, 279, 37554, 6136, 39881, 80987, 10051, 1523, 550, 3509, 18311, 13, 578, 3135, 617, 25127, 369, 44928, 287, 10173, 11, 323, 13893, 369, 1057, 23692, 315, 279, 31376, 3335, 315, 3823, 15740, 11, 12074, 1071, 13, 330, 1687, 1766, 430, 2653, 6136, 39881, 1778, 439, 279, 44054, 315, 31049, 323, 19595, 20025, 10383, 19748, 654, 686, 30953, 389, 18311, 1359, 1071, 15387, 5355, 356, 2352, 268, 11, 72235, 304, 24156, 95044, 304, 17979, 612, 23199, 11, 279, 1176, 3229, 315, 279, 502, 4007, 304, 38130, 29140, 13, 6941, 328, 13, 83163, 11, 14561, 315, 7106, 95044, 11, 374, 264, 1080, 43802, 13, 15415, 17868, 11, 12459, 2653, 15657, 374, 3463, 311, 5674, 18311, 555, 17843, 90090, 63008, 13, 330, 4071, 422, 18311, 1541, 956, 20461, 37067, 63008, 323, 61699, 11, 420, 3250, 956, 14647, 6037, 704, 279, 15652, 315, 2653, 3691, 3673, 1359, 5355, 356, 2352, 268, 1071, 13, 66094, 37441, 3640, 505, 2536, 70095, 1469, 288, 922, 8254, 3610, 1667, 4227, 304, 10384, 13, 578, 502, 4007, 14564, 459, 14529, 11249, 14932, 1148, 1063, 4216, 3823, 38618, 11, 279, 264, 5523, 454, 411, 82, 11, 1051, 12459, 13, 4314, 5105, 65544, 9606, 1047, 1633, 3544, 18311, 323, 82356, 11, 323, 4461, 6908, 75477, 24569, 13, 330, 2460, 1521, 27448, 5848, 8365, 2873, 311, 13519, 814, 1047, 279, 5845, 311, 8356, 3544, 23556, 8603, 11, 323, 9093, 4461, 523, 316, 7018, 1523, 389, 264, 10173, 315, 2653, 477, 78921, 3691, 3673, 1778, 439, 31049, 11, 19595, 477, 26326, 5070, 1093, 15286, 388, 1359, 5355, 356, 2352, 268, 1071, 13, 2030, 1455, 31376, 264, 5523, 454, 411, 18311, 1541, 956, 1501, 279, 3169, 315, 90090, 10051, 430, 1053, 387, 3685, 304, 420, 15398, 13, 578, 12074, 6773, 311, 1296, 433, 704, 13, 30013, 22936, 21896, 1047, 6982, 1268, 42018, 2345, 69191, 750, 11, 9863, 315, 52255, 7091, 2345, 8723, 1634, 5655, 66839, 389, 10269, 26588, 27529, 11, 1701, 264, 3756, 430, 28003, 19011, 279, 90090, 22639, 315, 19252, 389, 18311, 13, 2030, 1070, 574, 2697, 311, 912, 22772, 828, 389, 1148, 8741, 311, 26588, 92848, 994, 433, 4131, 304, 3729, 449, 5150, 24670, 1094, 6136, 3769, 13, 1789, 420, 4007, 11, 279, 12074, 12673, 13987, 9863, 315, 10533, 44054, 311, 264, 22477, 430, 814, 38247, 4028, 92848, 505, 264, 426, 17334, 276, 50707, 49624, 296, 7569, 26588, 13, 2435, 1903, 220, 845, 330, 66921, 1, 14393, 19015, 1990, 279, 92848, 323, 2380, 2204, 10533, 44054, 505, 24670, 1094, 11012, 430, 527, 961, 315, 6617, 550, 3509, 41943, 13, 578, 12074, 38247, 279, 19595, 2403, 92848, 520, 8603, 30139, 311, 904, 75477, 1957, 13, 578, 10533, 35603, 1903, 912, 3544, 63008, 11, 66839, 477, 78332, 304, 279, 92848, 11, 279, 12074, 1766, 13, 2684, 1051, 264, 2478, 26682, 10707, 10296, 11, 719, 279, 14248, 5602, 4400, 430, 16717, 430, 2653, 6136, 39881, 1436, 17210, 7438, 3725, 311, 29106, 19748, 654, 686, 13, 578, 10533, 35603, 5694, 11, 4869, 11, 8710, 12195, 315, 53568, 505, 1694, 67854, 2403, 279, 92848, 13, 1115, 2038, 374, 5505, 369, 41416, 22012, 889, 527, 2163, 449, 1193, 81473, 311, 1456, 311, 44928, 14154, 41943, 13, 330, 8140, 5603, 374, 539, 311, 1427, 369, 69916, 1990, 279, 4595, 315, 90090, 15785, 389, 18311, 323, 15657, 1694, 35661, 38542, 4619, 311, 3619, 279, 16940, 30126, 315, 1268, 1521, 61699, 389, 26588, 7479, 527, 14454, 1359, 5355, 356, 2352, 268, 1071, 13, 330, 2746, 584, 649, 282, 73555, 1521, 16188, 19476, 11, 584, 649, 7068, 810, 13687, 9364, 315, 1148, 31376, 5105, 258, 1354, 1051, 12459, 1210, 2100, 1884, 2466, 264, 5523, 454, 411, 82356, 1436, 617, 1027, 2231, 311, 1005, 75477, 389, 3544, 15055, 315, 19595, 2345, 30096, 1156, 20450, 18311, 13, 330, 3112, 430, 3727, 4832, 5647, 304, 3878, 315, 279, 6211, 315, 872, 18311, 1, 1071, 11291, 32103, 11, 264, 1080, 43802, 520, 279, 89289, 71343, 8483, 10181, 11, 330, 28753, 279, 49770, 3428, 1824, 355, 7018, 1376, 315, 872, 22337, 1590, 527, 10728, 369, 430, 7580, 1210, 330, 4599, 35208, 1690, 1633, 2678, 2653, 19595, 11, 3544, 23556, 8603, 527, 4461, 311, 387, 2631, 311, 2606, 682, 279, 41936, 1359, 5355, 356, 2352, 268, 1071, 13, 330, 644, 279, 3177, 315, 1057, 502, 14955, 11, 433, 374, 50434, 430, 2678, 11, 2653, 6302, 1093, 16763, 19595, 477, 274, 7334, 10184, 10145, 1051, 264, 34625, 5211, 369, 4216, 5105, 258, 1354, 1210, 220, 128257, 198 ]

2,141

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract In mammals, specification of the three major germ layers occurs during gastrulation, when cells ingressing through the primitive streak differentiate into the precursor cells of major organ systems. However, the molecular mechanisms underlying this process remain unclear, as numbers of gastrulating cells are very limited. In the mouse embryo at embryonic day 6.5, cells located at the junction between the extra-embryonic region and the epiblast on the posterior side of the embryo undergo an epithelial-to-mesenchymal transition and ingress through the primitive streak. Subsequently, cells migrate, either surrounding the prospective ectoderm contributing to the embryo proper, or into the extra-embryonic region to form the yolk sac, umbilical cord and placenta. Fate mapping has shown that mature tissues such as blood and heart originate from specific regions of the pre-gastrula epiblast 1 , but the plasticity of cells within the embryo and the function of key cell-type-specific transcription factors remain unclear. Here we analyse 1,205 cells from the epiblast and nascent Flk1 + mesoderm of gastrulating mouse embryos using single-cell RNA sequencing, representing the first transcriptome-wide in vivo view of early mesoderm formation during mammalian gastrulation. Additionally, using knockout mice, we study the function of Tal1, a key haematopoietic transcription factor, and demonstrate, contrary to previous studies performed using retrospective assays 2 , 3 , that Tal1 knockout does not immediately bias precursor cells towards a cardiac fate. Main Traditional experimental approaches for genome-scale analysis rely on large numbers of input cells and therefore cannot be applied to study early lineage diversification directly in the embryo. To address this, we used single-cell transcriptomics to investigate mesodermal lineage diversification towards the haematopoietic system in 1,205 single cells covering a time course from early gastrulation at embryonic day (E)6.5 to the generation of primitive red blood cells at E7.75 ( Fig. 1a and Extended Data Figs 1a and 2a ). Using previously published metrics (Methods), we observed that the data were of high quality. Five hundred and one single-cell transcriptomes were obtained from cells taken from dissected distal halves of E6.5 embryos sorted for viability only, which contain all of the epiblast cells, including the developing primitive streak, and a limited number of visceral endoderm and extra-embryonic ectoderm cells. From E7.0, embryos were staged according to anatomical features (Methods) as primitive streak, neural plate and head fold. The VEGF receptor Flk1 ( Kdr ) was used to capture cells as it marks much of the developing mesoderm 4 . During subsequent blood development, Flk1 is downregulated and CD41 ( Itga2b ) is upregulated 5 . We therefore also sampled cells expressing both markers and CD41 alone at the neural plate and head fold stages ( Fig. 1a and Extended Data Figs 1b and 2a ), giving a total of 138 cells from E7.0 (primitive streak), 259 from E7.5 (neural plate) and 307 from E7.75 (head fold). Figure 1: Single-cell transcriptomics identifies ten populations relevant to early mesodermal development. a , Whole-mount images and schematics of E6.5–7.75 embryo sections. Colours indicate approximate locations of sorted cells. Anterior, left; posterior, right. Scale bars, 200 μm. b , Heatmap showing key genes distinguishing ten clusters. Coloured bars indicate assigned cluster (top), stage (middle: turquoise, E6.5; purple, primitive streak (E7.0); green, neural plate (E7.5); red, head fold (E7.75)) and the sorted population (bottom: green, E6.5 epiblast; blue, Flk1 + ; turquoise, Flk1 + CD41 + ; red, Flk1 − CD41 + ). c , t-SNE of all 1,205 cells coloured by embryonic stage, and ( d ) according to clusters in b . PowerPoint slide Full size image After rigorous quality control, 2,085 genes were identified as having significantly more heterogeneous expression across the 1,205 cells than expected by chance ( Extended Data Fig. 2b–d ). Unsupervised hierarchical clustering in conjunction with a dynamic hybrid cut (Methods) yielded ten robust clusters with varying contributions from the different embryonic stages ( Fig. 1b , Extended Data Fig. 3 , Methods and cell numbers in Extended Data Fig. 3h ). Using t-distributed stochastic neighbour embedding (t-SNE) dimensionality reduction to visualize the data, three major groups were observed: one comprising almost all E6.5 cells, another mainly consisting of earlier primitive streak and neural plate stage cells, and a third containing predominantly later head fold stage cells ( Fig. 1c ). Importantly, clusters were coherent with the t-SNE visualization except for the small cluster 5 ( Fig. 1d ). The expression of key marker genes allowed us to assign identities to each cluster: visceral endoderm, extra-embryonic ectoderm, epiblast, early mesodermal progenitors, posterior mesoderm, endothelium, blood progenitors, primitive erythrocytes, allantoic mesoderm and pharyngeal mesoderm ( Fig. 1b , Extended Data Figs 3h and 4 ). Because of the limited cell numbers and lack of markers for their prospective isolation, conventional bulk transcriptome analysis of these key populations has never before been attempted. Since the T-box transcription factor Brachyury—encoded by the T gene—marks the nascent primitive streak 6 , we investigated the gene expression programs associated with T induction in the E6.5 cells (cluster 3). T expression was restricted to a distinct subset of epiblast cells found closest to cluster 4 ( Fig. 1d and Extended Data Fig. 5b ), with rare isolated cells within the bulk of the epiblast population also expressing moderate levels, consistent with priming events for single gastrulation-associated genes. T expression correlated with other gastrulation-associated genes including Mixl1 and Mesp1 ( Fig. 2a ), with Mesp1 highly expressed only in the small subset of cells situated at the pole of the E6.5 epiblast cluster (association of T and Mesp1 expression: P value 3 × 10 −15 , Fisher’s exact test). We also observed a subset of cells distinct from the T + / Mesp1 + population, which expressed Foxa2 , suggestive of endodermal priming 7 ( Extended Data Fig. 5d ). Figure 2: Transcriptional program associated with T induction in E6.5 epiblast cells. a , t-SNE of the 481 E6.5 cells in cluster 3. Points are coloured by expression of T (Brachyury) and Mixl1 , Mesp1 and Frzb .", "role": "user" }, { "content": "In the first genome-scale experiment of its kind, researchers have gained new insights into how a mouse embryo first begins to transform from a ball of unfocussed cells into a small, structured entity. Published in Nature, the single-cell genomics study was led by the European Bioinformatics Institute (EMBL-EBI) and the Wellcome Trust-MRC Cambridge Stem Cell Institute. Gastrulation is the point when an animal's whole body plan is set, just before individual organs start to develop. Understanding this point in very early development is vital to understanding how animals develop and how things go wrong. One of the biggest challenges in studying gastrulation is the very small number of cells that make up an embryo at this stage. \"If we want to better understand the natural world around us, one of the fundamental questions is, how do animals develop?\" says Bertie Gottgens, Research Group Leader at the Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute. \"How do you turn from an egg into an animal, with all sorts of tissues? Many of the things that go wrong, like birth defects, are caused by problems in early development. We need to have an atlas of normal development for comparison when things go wrong.\" Today, thanks to advances in single-cell sequencing, the team was able to analyse over 1000 individual cells of gastrulating mouse embryos. The result is an atlas of gene expression during very early, healthy mammalian development. \"Single-cell technologies are a major change over what we've used before - we can now make direct observations to see what's going on during the earliest stages of development,\" says John Marioni, Research Group Leader at EMBL-EBI, the Wellcome Trust Sanger Institute and the University of Cambridge. \"We can look at individual cells and see the whole set of genes that are active at stages of development, which until now have been very difficult to access. Once we have that, we can take cells from embryos in which some genetic factors are not working properly at a specific developmental stage, and map them to the healthy atlas to better understand what might be happening.\" To illustrate the usefulness of the atlas, the team studied what happened when a genetic factor essential for the formation of blood cells was removed. \"It wasn't what we expected at all. We found that cells which in healthy embryos would commit to becoming blood cells would actually become confused in the embryos lacking the key gene, effectively getting stuck,\" says John. \"What is so exciting about this is that it demonstrates how we can now look at the very small number of cells that are actually making the decision at the precise time point when the decision is being made. It gives us a completely different perspective on development.\" \"What is really exciting for me is that we can look at things that we know are important but were never able to see before - perhaps like people felt when they got hold of a microscope for the first time, suddenly seeing worlds they'd never thought of,\" says Bertie. \"This is just the beginning of how single cell genomics will transform our understanding of early development.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract In mammals, specification of the three major germ layers occurs during gastrulation, when cells ingressing through the primitive streak differentiate into the precursor cells of major organ systems. However, the molecular mechanisms underlying this process remain unclear, as numbers of gastrulating cells are very limited. In the mouse embryo at embryonic day 6.5, cells located at the junction between the extra-embryonic region and the epiblast on the posterior side of the embryo undergo an epithelial-to-mesenchymal transition and ingress through the primitive streak. Subsequently, cells migrate, either surrounding the prospective ectoderm contributing to the embryo proper, or into the extra-embryonic region to form the yolk sac, umbilical cord and placenta. Fate mapping has shown that mature tissues such as blood and heart originate from specific regions of the pre-gastrula epiblast 1 , but the plasticity of cells within the embryo and the function of key cell-type-specific transcription factors remain unclear. Here we analyse 1,205 cells from the epiblast and nascent Flk1 + mesoderm of gastrulating mouse embryos using single-cell RNA sequencing, representing the first transcriptome-wide in vivo view of early mesoderm formation during mammalian gastrulation. Additionally, using knockout mice, we study the function of Tal1, a key haematopoietic transcription factor, and demonstrate, contrary to previous studies performed using retrospective assays 2 , 3 , that Tal1 knockout does not immediately bias precursor cells towards a cardiac fate. Main Traditional experimental approaches for genome-scale analysis rely on large numbers of input cells and therefore cannot be applied to study early lineage diversification directly in the embryo. To address this, we used single-cell transcriptomics to investigate mesodermal lineage diversification towards the haematopoietic system in 1,205 single cells covering a time course from early gastrulation at embryonic day (E)6.5 to the generation of primitive red blood cells at E7.75 ( Fig. 1a and Extended Data Figs 1a and 2a ). Using previously published metrics (Methods), we observed that the data were of high quality. Five hundred and one single-cell transcriptomes were obtained from cells taken from dissected distal halves of E6.5 embryos sorted for viability only, which contain all of the epiblast cells, including the developing primitive streak, and a limited number of visceral endoderm and extra-embryonic ectoderm cells. From E7.0, embryos were staged according to anatomical features (Methods) as primitive streak, neural plate and head fold. The VEGF receptor Flk1 ( Kdr ) was used to capture cells as it marks much of the developing mesoderm 4 . During subsequent blood development, Flk1 is downregulated and CD41 ( Itga2b ) is upregulated 5 . We therefore also sampled cells expressing both markers and CD41 alone at the neural plate and head fold stages ( Fig. 1a and Extended Data Figs 1b and 2a ), giving a total of 138 cells from E7.0 (primitive streak), 259 from E7.5 (neural plate) and 307 from E7.75 (head fold). Figure 1: Single-cell transcriptomics identifies ten populations relevant to early mesodermal development. a , Whole-mount images and schematics of E6.5–7.75 embryo sections. Colours indicate approximate locations of sorted cells. Anterior, left; posterior, right. Scale bars, 200 μm. b , Heatmap showing key genes distinguishing ten clusters. Coloured bars indicate assigned cluster (top), stage (middle: turquoise, E6.5; purple, primitive streak (E7.0); green, neural plate (E7.5); red, head fold (E7.75)) and the sorted population (bottom: green, E6.5 epiblast; blue, Flk1 + ; turquoise, Flk1 + CD41 + ; red, Flk1 − CD41 + ). c , t-SNE of all 1,205 cells coloured by embryonic stage, and ( d ) according to clusters in b . PowerPoint slide Full size image After rigorous quality control, 2,085 genes were identified as having significantly more heterogeneous expression across the 1,205 cells than expected by chance ( Extended Data Fig. 2b–d ). Unsupervised hierarchical clustering in conjunction with a dynamic hybrid cut (Methods) yielded ten robust clusters with varying contributions from the different embryonic stages ( Fig. 1b , Extended Data Fig. 3 , Methods and cell numbers in Extended Data Fig. 3h ). Using t-distributed stochastic neighbour embedding (t-SNE) dimensionality reduction to visualize the data, three major groups were observed: one comprising almost all E6.5 cells, another mainly consisting of earlier primitive streak and neural plate stage cells, and a third containing predominantly later head fold stage cells ( Fig. 1c ). Importantly, clusters were coherent with the t-SNE visualization except for the small cluster 5 ( Fig. 1d ). The expression of key marker genes allowed us to assign identities to each cluster: visceral endoderm, extra-embryonic ectoderm, epiblast, early mesodermal progenitors, posterior mesoderm, endothelium, blood progenitors, primitive erythrocytes, allantoic mesoderm and pharyngeal mesoderm ( Fig. 1b , Extended Data Figs 3h and 4 ). Because of the limited cell numbers and lack of markers for their prospective isolation, conventional bulk transcriptome analysis of these key populations has never before been attempted. Since the T-box transcription factor Brachyury—encoded by the T gene—marks the nascent primitive streak 6 , we investigated the gene expression programs associated with T induction in the E6.5 cells (cluster 3). T expression was restricted to a distinct subset of epiblast cells found closest to cluster 4 ( Fig. 1d and Extended Data Fig. 5b ), with rare isolated cells within the bulk of the epiblast population also expressing moderate levels, consistent with priming events for single gastrulation-associated genes. T expression correlated with other gastrulation-associated genes including Mixl1 and Mesp1 ( Fig. 2a ), with Mesp1 highly expressed only in the small subset of cells situated at the pole of the E6.5 epiblast cluster (association of T and Mesp1 expression: P value 3 × 10 −15 , Fisher’s exact test). We also observed a subset of cells distinct from the T + / Mesp1 + population, which expressed Foxa2 , suggestive of endodermal priming 7 ( Extended Data Fig. 5d ). Figure 2: Transcriptional program associated with T induction in E6.5 epiblast cells. a , t-SNE of the 481 E6.5 cells in cluster 3. Points are coloured by expression of T (Brachyury) and Mixl1 , Mesp1 and Frzb .<|im_end|> <|im_start|>assistant In the first genome-scale experiment of its kind, researchers have gained new insights into how a mouse embryo first begins to transform from a ball of unfocussed cells into a small, structured entity. Published in Nature, the single-cell genomics study was led by the European Bioinformatics Institute (EMBL-EBI) and the Wellcome Trust-MRC Cambridge Stem Cell Institute. Gastrulation is the point when an animal's whole body plan is set, just before individual organs start to develop. Understanding this point in very early development is vital to understanding how animals develop and how things go wrong. One of the biggest challenges in studying gastrulation is the very small number of cells that make up an embryo at this stage. "If we want to better understand the natural world around us, one of the fundamental questions is, how do animals develop?" says Bertie Gottgens, Research Group Leader at the Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute. "How do you turn from an egg into an animal, with all sorts of tissues? Many of the things that go wrong, like birth defects, are caused by problems in early development. We need to have an atlas of normal development for comparison when things go wrong." Today, thanks to advances in single-cell sequencing, the team was able to analyse over 1000 individual cells of gastrulating mouse embryos. The result is an atlas of gene expression during very early, healthy mammalian development. "Single-cell technologies are a major change over what we've used before - we can now make direct observations to see what's going on during the earliest stages of development," says John Marioni, Research Group Leader at EMBL-EBI, the Wellcome Trust Sanger Institute and the University of Cambridge. "We can look at individual cells and see the whole set of genes that are active at stages of development, which until now have been very difficult to access. Once we have that, we can take cells from embryos in which some genetic factors are not working properly at a specific developmental stage, and map them to the healthy atlas to better understand what might be happening." To illustrate the usefulness of the atlas, the team studied what happened when a genetic factor essential for the formation of blood cells was removed. "It wasn't what we expected at all. We found that cells which in healthy embryos would commit to becoming blood cells would actually become confused in the embryos lacking the key gene, effectively getting stuck," says John. "What is so exciting about this is that it demonstrates how we can now look at the very small number of cells that are actually making the decision at the precise time point when the decision is being made. It gives us a completely different perspective on development." "What is really exciting for me is that we can look at things that we know are important but were never able to see before - perhaps like people felt when they got hold of a microscope for the first time, suddenly seeing worlds they'd never thought of," says Bertie. "This is just the beginning of how single cell genomics will transform our understanding of early development." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 763, 56669, 11, 26185, 315, 279, 2380, 3682, 82986, 13931, 13980, 2391, 56780, 2987, 11, 994, 7917, 6892, 57881, 1555, 279, 28694, 30314, 54263, 1139, 279, 71261, 7917, 315, 3682, 2942, 6067, 13, 4452, 11, 279, 31206, 24717, 16940, 420, 1920, 7293, 25420, 11, 439, 5219, 315, 56780, 15853, 7917, 527, 1633, 7347, 13, 763, 279, 8814, 87701, 520, 44481, 14338, 1938, 220, 21, 13, 20, 11, 7917, 7559, 520, 279, 49341, 1990, 279, 5066, 12, 9034, 894, 14338, 5654, 323, 279, 4248, 581, 4354, 389, 279, 46000, 3185, 315, 279, 87701, 37771, 459, 64779, 59544, 4791, 1474, 288, 20345, 1631, 278, 9320, 323, 79659, 1555, 279, 28694, 30314, 13, 3804, 39742, 11, 7917, 45666, 11, 3060, 14932, 279, 33547, 77594, 347, 4289, 29820, 311, 279, 87701, 6300, 11, 477, 1139, 279, 5066, 12, 9034, 894, 14338, 5654, 311, 1376, 279, 379, 23427, 11347, 11, 37781, 321, 950, 23125, 323, 29960, 16985, 13, 60025, 13021, 706, 6982, 430, 15196, 39881, 1778, 439, 6680, 323, 4851, 82316, 505, 3230, 13918, 315, 279, 864, 2427, 21100, 5724, 4248, 581, 4354, 220, 16, 1174, 719, 279, 12466, 488, 315, 7917, 2949, 279, 87701, 323, 279, 734, 315, 1401, 2849, 10827, 19440, 46940, 9547, 7293, 25420, 13, 5810, 584, 49586, 220, 16, 11, 10866, 7917, 505, 279, 4248, 581, 4354, 323, 17580, 1189, 3061, 74, 16, 489, 11083, 347, 4289, 315, 56780, 15853, 8814, 89873, 1701, 3254, 33001, 41214, 62119, 11, 14393, 279, 1176, 36815, 638, 25480, 304, 41294, 1684, 315, 4216, 11083, 347, 4289, 18488, 2391, 36041, 10700, 56780, 2987, 13, 23212, 11, 1701, 77173, 24548, 11, 584, 4007, 279, 734, 315, 18051, 16, 11, 264, 1401, 6520, 43698, 56809, 3978, 292, 46940, 8331, 11, 323, 20461, 11, 26102, 311, 3766, 7978, 10887, 1701, 79929, 99592, 220, 17, 1174, 220, 18, 1174, 430, 18051, 16, 77173, 1587, 539, 7214, 15837, 71261, 7917, 7119, 264, 47345, 25382, 13, 4802, 46560, 22772, 20414, 369, 33869, 13230, 6492, 17631, 389, 3544, 5219, 315, 1988, 7917, 323, 9093, 4250, 387, 9435, 311, 4007, 4216, 65009, 21797, 2461, 6089, 304, 279, 87701, 13, 2057, 2686, 420, 11, 584, 1511, 3254, 33001, 36815, 24203, 311, 19874, 11083, 347, 18558, 65009, 21797, 2461, 7119, 279, 6520, 43698, 56809, 3978, 292, 1887, 304, 220, 16, 11, 10866, 3254, 7917, 18702, 264, 892, 3388, 505, 4216, 56780, 2987, 520, 44481, 14338, 1938, 320, 36, 8, 21, 13, 20, 311, 279, 9659, 315, 28694, 2579, 6680, 7917, 520, 469, 22, 13, 2075, 320, 23966, 13, 220, 16, 64, 323, 41665, 2956, 435, 14801, 220, 16, 64, 323, 220, 17, 64, 7609, 12362, 8767, 4756, 17150, 320, 18337, 705, 584, 13468, 430, 279, 828, 1051, 315, 1579, 4367, 13, 21594, 7895, 323, 832, 3254, 33001, 36815, 20969, 1051, 12457, 505, 7917, 4529, 505, 75050, 291, 1612, 278, 75212, 315, 469, 21, 13, 20, 89873, 10839, 369, 68507, 1193, 11, 902, 6782, 682, 315, 279, 4248, 581, 4354, 7917, 11, 2737, 279, 11469, 28694, 30314, 11, 323, 264, 7347, 1396, 315, 89116, 842, 347, 4289, 323, 5066, 12, 9034, 894, 14338, 77594, 347, 4289, 7917, 13, 5659, 469, 22, 13, 15, 11, 89873, 1051, 51157, 4184, 311, 75893, 950, 4519, 320, 18337, 8, 439, 28694, 30314, 11, 30828, 12235, 323, 2010, 11816, 13, 578, 650, 9560, 37, 35268, 3061, 74, 16, 320, 735, 3696, 883, 574, 1511, 311, 12602, 7917, 439, 433, 15785, 1790, 315, 279, 11469, 11083, 347, 4289, 220, 19, 662, 12220, 17876, 6680, 4500, 11, 3061, 74, 16, 374, 1523, 81722, 323, 11325, 3174, 320, 1102, 6885, 17, 65, 883, 374, 709, 81722, 220, 20, 662, 1226, 9093, 1101, 49976, 7917, 37810, 2225, 24915, 323, 11325, 3174, 7636, 520, 279, 30828, 12235, 323, 2010, 11816, 18094, 320, 23966, 13, 220, 16, 64, 323, 41665, 2956, 435, 14801, 220, 16, 65, 323, 220, 17, 64, 7026, 7231, 264, 2860, 315, 220, 10350, 7917, 505, 469, 22, 13, 15, 320, 74548, 30314, 705, 220, 15537, 505, 469, 22, 13, 20, 320, 818, 4269, 12235, 8, 323, 220, 14777, 505, 469, 22, 13, 2075, 320, 2025, 11816, 570, 19575, 220, 16, 25, 11579, 33001, 36815, 24203, 36611, 5899, 22673, 9959, 311, 4216, 11083, 347, 18558, 4500, 13, 264, 1174, 41593, 60688, 5448, 323, 20225, 29470, 315, 469, 21, 13, 20, 4235, 22, 13, 2075, 87701, 14491, 13, 4349, 2530, 13519, 45968, 10687, 315, 10839, 7917, 13, 6898, 14917, 11, 2163, 26, 46000, 11, 1314, 13, 25635, 16283, 11, 220, 1049, 33983, 76, 13, 293, 1174, 27162, 2235, 9204, 1401, 21389, 86055, 5899, 28066, 13, 4349, 21020, 16283, 13519, 12893, 10879, 320, 3565, 705, 6566, 320, 20231, 25, 97047, 11, 469, 21, 13, 20, 26, 25977, 11, 28694, 30314, 320, 36, 22, 13, 15, 1237, 6307, 11, 30828, 12235, 320, 36, 22, 13, 20, 1237, 2579, 11, 2010, 11816, 320, 36, 22, 13, 2075, 595, 323, 279, 10839, 7187, 320, 15205, 25, 6307, 11, 469, 21, 13, 20, 4248, 581, 4354, 26, 6437, 11, 3061, 74, 16, 489, 2652, 97047, 11, 3061, 74, 16, 489, 11325, 3174, 489, 2652, 2579, 11, 3061, 74, 16, 25173, 11325, 3174, 489, 7609, 272, 1174, 259, 6354, 4031, 315, 682, 220, 16, 11, 10866, 7917, 58919, 555, 44481, 14338, 6566, 11, 323, 320, 294, 883, 4184, 311, 28066, 304, 293, 662, 54600, 15332, 8797, 1404, 2217, 4740, 47999, 4367, 2585, 11, 220, 17, 11, 24646, 21389, 1051, 11054, 439, 3515, 12207, 810, 98882, 7645, 4028, 279, 220, 16, 11, 10866, 7917, 1109, 3685, 555, 6140, 320, 41665, 2956, 23966, 13, 220, 17, 65, 4235, 67, 7609, 1252, 13066, 79090, 70994, 59454, 304, 32546, 449, 264, 8915, 26038, 4018, 320, 18337, 8, 58487, 5899, 22514, 28066, 449, 29865, 19564, 505, 279, 2204, 44481, 14338, 18094, 320, 23966, 13, 220, 16, 65, 1174, 41665, 2956, 23966, 13, 220, 18, 1174, 19331, 323, 2849, 5219, 304, 41665, 2956, 23966, 13, 220, 18, 71, 7609, 12362, 259, 1773, 26204, 96340, 22686, 40188, 320, 83, 6354, 4031, 8, 13167, 2786, 14278, 311, 51187, 279, 828, 11, 2380, 3682, 5315, 1051, 13468, 25, 832, 46338, 4661, 682, 469, 21, 13, 20, 7917, 11, 2500, 14918, 31706, 315, 6931, 28694, 30314, 323, 30828, 12235, 6566, 7917, 11, 323, 264, 4948, 8649, 47904, 3010, 2010, 11816, 6566, 7917, 320, 23966, 13, 220, 16, 66, 7609, 13516, 18007, 11, 28066, 1051, 56887, 449, 279, 259, 6354, 4031, 42148, 3734, 369, 279, 2678, 10879, 220, 20, 320, 23966, 13, 220, 16, 67, 7609, 578, 7645, 315, 1401, 11381, 21389, 5535, 603, 311, 9993, 40521, 311, 1855, 10879, 25, 89116, 842, 347, 4289, 11, 5066, 12, 9034, 894, 14338, 77594, 347, 4289, 11, 4248, 581, 4354, 11, 4216, 11083, 347, 18558, 84360, 12170, 11, 46000, 11083, 347, 4289, 11, 93329, 301, 2411, 11, 6680, 84360, 12170, 11, 28694, 89357, 93210, 11377, 2392, 11, 682, 13873, 292, 11083, 347, 4289, 323, 1343, 661, 85590, 278, 11083, 347, 4289, 320, 23966, 13, 220, 16, 65, 1174, 41665, 2956, 435, 14801, 220, 18, 71, 323, 220, 19, 7609, 9393, 315, 279, 7347, 2849, 5219, 323, 6996, 315, 24915, 369, 872, 33547, 31398, 11, 21349, 20155, 36815, 638, 6492, 315, 1521, 1401, 22673, 706, 2646, 1603, 1027, 17644, 13, 8876, 279, 350, 12913, 46940, 8331, 3320, 613, 88, 3431, 2345, 19889, 555, 279, 350, 15207, 2345, 15914, 279, 17580, 1189, 28694, 30314, 220, 21, 1174, 584, 27313, 279, 15207, 7645, 7620, 5938, 449, 350, 38156, 304, 279, 469, 21, 13, 20, 7917, 320, 19386, 220, 18, 570, 350, 7645, 574, 22486, 311, 264, 12742, 27084, 315, 4248, 581, 4354, 7917, 1766, 18585, 311, 10879, 220, 19, 320, 23966, 13, 220, 16, 67, 323, 41665, 2956, 23966, 13, 220, 20, 65, 7026, 449, 9024, 25181, 7917, 2949, 279, 20155, 315, 279, 4248, 581, 4354, 7187, 1101, 37810, 24070, 5990, 11, 13263, 449, 9036, 287, 4455, 369, 3254, 56780, 2987, 75968, 21389, 13, 350, 7645, 49393, 449, 1023, 56780, 2987, 75968, 21389, 2737, 19771, 75, 16, 323, 386, 25632, 16, 320, 23966, 13, 220, 17, 64, 7026, 449, 386, 25632, 16, 7701, 13605, 1193, 304, 279, 2678, 27084, 315, 7917, 31183, 520, 279, 26078, 315, 279, 469, 21, 13, 20, 4248, 581, 4354, 10879, 320, 55565, 315, 350, 323, 386, 25632, 16, 7645, 25, 393, 907, 220, 18, 25800, 220, 605, 25173, 868, 1174, 36604, 753, 4839, 1296, 570, 1226, 1101, 13468, 264, 27084, 315, 7917, 12742, 505, 279, 350, 489, 611, 386, 25632, 16, 489, 7187, 11, 902, 13605, 13585, 64, 17, 1174, 99578, 315, 842, 347, 18558, 9036, 287, 220, 22, 320, 41665, 2956, 23966, 13, 220, 20, 67, 7609, 19575, 220, 17, 25, 4149, 1479, 278, 2068, 5938, 449, 350, 38156, 304, 469, 21, 13, 20, 4248, 581, 4354, 7917, 13, 264, 1174, 259, 6354, 4031, 315, 279, 220, 21235, 469, 21, 13, 20, 7917, 304, 10879, 220, 18, 13, 21387, 527, 58919, 555, 7645, 315, 350, 320, 6971, 613, 88, 3431, 8, 323, 19771, 75, 16, 1174, 386, 25632, 16, 323, 2939, 26397, 662, 128257, 198, 128256, 78191, 198, 644, 279, 1176, 33869, 13230, 9526, 315, 1202, 3169, 11, 12074, 617, 18661, 502, 26793, 1139, 1268, 264, 8814, 87701, 1176, 12302, 311, 5276, 505, 264, 5041, 315, 9662, 511, 59942, 7917, 1139, 264, 2678, 11, 34030, 5502, 13, 30114, 304, 22037, 11, 279, 3254, 33001, 4173, 24203, 4007, 574, 6197, 555, 279, 7665, 24432, 98588, 10181, 320, 2783, 9574, 12, 8428, 40, 8, 323, 279, 8489, 2063, 17236, 5364, 7532, 24562, 81948, 14299, 10181, 13, 18879, 496, 2987, 374, 279, 1486, 994, 459, 10065, 596, 4459, 2547, 3197, 374, 743, 11, 1120, 1603, 3927, 36853, 1212, 311, 2274, 13, 46551, 420, 1486, 304, 1633, 4216, 4500, 374, 16595, 311, 8830, 1268, 10099, 2274, 323, 1268, 2574, 733, 5076, 13, 3861, 315, 279, 8706, 11774, 304, 21630, 56780, 2987, 374, 279, 1633, 2678, 1396, 315, 7917, 430, 1304, 709, 459, 87701, 520, 420, 6566, 13, 330, 2746, 584, 1390, 311, 2731, 3619, 279, 5933, 1917, 2212, 603, 11, 832, 315, 279, 16188, 4860, 374, 11, 1268, 656, 10099, 2274, 7673, 2795, 51775, 648, 69109, 59405, 11, 8483, 5856, 23896, 520, 279, 8489, 2063, 17236, 482, 13235, 8483, 9251, 24562, 81948, 14299, 10181, 13, 330, 4438, 656, 499, 2543, 505, 459, 19151, 1139, 459, 10065, 11, 449, 682, 21522, 315, 39881, 30, 9176, 315, 279, 2574, 430, 733, 5076, 11, 1093, 7342, 42655, 11, 527, 9057, 555, 5435, 304, 4216, 4500, 13, 1226, 1205, 311, 617, 459, 62032, 315, 4725, 4500, 369, 12593, 994, 2574, 733, 5076, 1210, 11450, 11, 9523, 311, 31003, 304, 3254, 33001, 62119, 11, 279, 2128, 574, 3025, 311, 49586, 927, 220, 1041, 15, 3927, 7917, 315, 56780, 15853, 8814, 89873, 13, 578, 1121, 374, 459, 62032, 315, 15207, 7645, 2391, 1633, 4216, 11, 9498, 36041, 10700, 4500, 13, 330, 11126, 33001, 14645, 527, 264, 3682, 2349, 927, 1148, 584, 3077, 1511, 1603, 482, 584, 649, 1457, 1304, 2167, 24654, 311, 1518, 1148, 596, 2133, 389, 2391, 279, 30758, 18094, 315, 4500, 1359, 2795, 3842, 2947, 19350, 11, 8483, 5856, 23896, 520, 469, 8578, 43, 12, 8428, 40, 11, 279, 8489, 2063, 17236, 328, 4091, 10181, 323, 279, 3907, 315, 24562, 13, 330, 1687, 649, 1427, 520, 3927, 7917, 323, 1518, 279, 4459, 743, 315, 21389, 430, 527, 4642, 520, 18094, 315, 4500, 11, 902, 3156, 1457, 617, 1027, 1633, 5107, 311, 2680, 13, 9843, 584, 617, 430, 11, 584, 649, 1935, 7917, 505, 89873, 304, 902, 1063, 19465, 9547, 527, 539, 3318, 10489, 520, 264, 3230, 48006, 6566, 11, 323, 2472, 1124, 311, 279, 9498, 62032, 311, 2731, 3619, 1148, 2643, 387, 12765, 1210, 2057, 41468, 279, 76964, 315, 279, 62032, 11, 279, 2128, 20041, 1148, 7077, 994, 264, 19465, 8331, 7718, 369, 279, 18488, 315, 6680, 7917, 574, 7108, 13, 330, 2181, 5828, 956, 1148, 584, 3685, 520, 682, 13, 1226, 1766, 430, 7917, 902, 304, 9498, 89873, 1053, 5379, 311, 10671, 6680, 7917, 1053, 3604, 3719, 22568, 304, 279, 89873, 32161, 279, 1401, 15207, 11, 13750, 3794, 16075, 1359, 2795, 3842, 13, 330, 3923, 374, 779, 13548, 922, 420, 374, 430, 433, 32216, 1268, 584, 649, 1457, 1427, 520, 279, 1633, 2678, 1396, 315, 7917, 430, 527, 3604, 3339, 279, 5597, 520, 279, 24473, 892, 1486, 994, 279, 5597, 374, 1694, 1903, 13, 1102, 6835, 603, 264, 6724, 2204, 13356, 389, 4500, 1210, 330, 3923, 374, 2216, 13548, 369, 757, 374, 430, 584, 649, 1427, 520, 2574, 430, 584, 1440, 527, 3062, 719, 1051, 2646, 3025, 311, 1518, 1603, 482, 8530, 1093, 1274, 6612, 994, 814, 2751, 3412, 315, 264, 73757, 369, 279, 1176, 892, 11, 15187, 9298, 24800, 814, 4265, 2646, 3463, 315, 1359, 2795, 51775, 648, 13, 330, 2028, 374, 1120, 279, 7314, 315, 1268, 3254, 2849, 4173, 24203, 690, 5276, 1057, 8830, 315, 4216, 4500, 1210, 220, 128257, 198 ]

2,148

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Galaxies with stellar masses as high as roughly 10 11 solar masses have been identified 1 , 2 , 3 out to redshifts z of roughly 6, around 1 billion years after the Big Bang. It has been difficult to find massive galaxies at even earlier times, as the Balmer break region, which is needed for accurate mass estimates, is redshifted to wavelengths beyond 2.5 μm. Here we make use of the 1–5 μm coverage of the James Webb Space Telescope early release observations to search for intrinsically red galaxies in the first roughly 750 million years of cosmic history. In the survey area, we find six candidate massive galaxies (stellar mass more than 10 10 solar masses) at 7.4 ≤ z ≤ 9.1, 500–700 Myr after the Big Bang, including one galaxy with a possible stellar mass of roughly 10 11 solar masses. If verified with spectroscopy, the stellar mass density in massive galaxies would be much higher than anticipated from previous studies on the basis of rest-frame ultraviolet-selected samples. Main The galaxies were identified in the first observations of the James Webb Space Telescope (JWST) Cosmic Evolution Early Release Science (CEERS) program. This program obtained multiband images at 1–5 μm with the Near-Infrared Camera (NIRCam) in a ‘blank’ field, chosen to overlap with existing Hubble Space Telescope (HST) imaging. The total area covered by these initial data is roughly 40 arcmin 2 . The data were obtained from the Mikulski Archive for Space Telescopes (MAST) archive and reduced using the Grizli pipeline 4 . A catalogue of sources was created, starting with detection in a deep combined F277W + F356W + F444W image (see Methods for details). A total of 42,729 objects are in this parent catalogue. We selected candidate massive galaxies at high redshifts by identifying objects that have two redshifted breaks in their spectral energy distributions (SEDs), the λ rest = 1,216 Å Lyman break and the λ rest of roughly 3,600 Å Balmer break. This selection ensures that the redshift probability distributions are well constrained, have no secondary solutions at lower redshifts and that we include galaxies that have potentially high mass-to-light (M/L) ratios. Specifically, we require that objects are not detected at optical wavelengths, blue in the near-infrared with F150W–F277W is less than 0.7, red at longer wavelengths with F277W–F444W is more than 1.0 and brighter than F444W is less than 27 AB units in magnitude. After visual inspection to remove obvious artefacts (such as diffraction spikes), this selection produced 13 galaxies with the sought-for ‘double-break’ SEDs. Next, redshifts and stellar masses were determined with three widely used techniques, taking the contribution of strong emission lines to the rest-frame optical photometry explicitly into account 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 . We use the EAZY code 16 (with extra strong emission-line templates), the Prospector-α framework 17 and five configurations of the Bagpipes SED-fitting code to explore systematics due to modelling assumptions. The seven individual mass and redshift measurements of the 13 galaxies are listed in the Methods section. We adopt fiducial masses and redshifts by taking the median value for each galaxy. We note that these masses and redshifts are not definitive and that all galaxies should be considered candidates. As shown in Fig. 1 , all 13 objects have photometric redshifts 6.5 < z < 9.1. Six of the 13 have fiducial masses greater than 10 10 M ☉ (Salpeter initial mass function (IMF)) and multiband images and SEDs of these galaxies are shown in Figs. 2 and 3 . Their photometric redshifts range from z = 7.4 to z = 9.1. The model fits are generally excellent, and in several cases clearly demonstrate that rest-frame optical emission lines contribute to the continuum emission. These lines can be so strong in young galaxies that they can dominate the broad-band fluxes redwards of the location of the Balmer break 6 , 7 , 8 , 14 , 18 , and Spitzer/IRAC detections of optical continuum breaks in galaxies at z ≳ 5 have been challenging to interpret 3 , 5 , 19 , 20 , 21 , 22 , 23 , 24 . With JWST, this ambiguity is largely resolved due to the dense wavelength coverage of the NIRCam filters and the inclusion of relatively narrow emission-line-sensitive filter F410M (ref. 25 ), which falls within the F444W band, although the uncertainties are such that alternative solutions with lower masses may exist 14 . The brightest galaxy in the sample, 38094, is at z = 7.5 and may have a mass that is as high as M * ≅ 1 × 10 11 M ☉ , more massive than the present-day Milky Way. It has two nearby companions with a similar break in their optical to near-infrared SEDs, suggesting that the galaxy may be in a group. Fig. 1: Redshifts and tentative stellar masses of double-break selected galaxies. Shown in grey circles are EAZY-determined redshifts and stellar masses using emission-line enhanced templates (Salpeter IMF) for objects with SNR > 8 in the F444W band. Fiducial redshifts and masses of the bright galaxies (F444W < 27 AB) that satisfy our double-break selection are shown by the large red symbols. Uncertainties are the 16th–84th percentiles of the posterior probability distribution. All galaxies have photometric redshifts 6.5 < z < 9.1. Six galaxies are candidate massive galaxies with fiducial M * > 10 10 M ☉ . Full size image Fig. 2: Images of the six galaxies with the highest apparent masses as a function of wavelength. The fiducial stellar masses of the galaxies are (log( M * / M ☉ ) > 10). Each cut-out has a size of 2.4″ × 2.4″. The filters range from the 0.6 μm F606W filter of HST /ACS to the 4.4 μm F444W JWST/NIRCam filter. The galaxies are undetected in the optical filters, blue in the short-wavelength NIRCam filters and red in the long-wavelength NIRCam", "role": "user" }, { "content": "The James Webb Space Telescope has spotted six massive galaxies that emerged not long after the Big Bang, a study said Wednesday, surprising scientists by forming at a speed that contradicts our current understanding of the universe. Since becoming operational last July, the Webb telescope has been peering farther than ever before into the universe's distant reaches—which also means it is looking back in time. For its latest discovery, the telescope spied galaxies from between 500 to 700 years million years after the Big Bang 13.8 billion years ago, meaning the universe was under five percent of its current age. Webb's NIRCam instrument, which operates in the near infrared wavelength invisible to the naked eye, observed the six galaxies in a little-known region of the sky, according to a study published in the journal Nature. Two of the galaxies had previously been spotted by the Hubble Space Telescope but were so faint in those images that they went unnoticed. These six new \"candidate galaxies\", so-called because their discovery still needs to be confirmed by other measurements, contain many more stars than scientists expected. One galaxy is even believed to have around 100 billion stars. That would make it around the size of the Milky Way, which is \"crazy,\" the study's first author Ivo Labbe told AFP. 'Off a cliff' It took our home galaxy the entire life of the universe for all its stars to assemble. For this young galaxy to achieve the same growth in just 700 million years, it would have had to grow around 20 times faster than the Milky Way, said Labbe, a researcher at Australia's Swinburne University of Technology. For there to be such massive galaxies so soon after the Big Bang goes against the current cosmological model which represents science's best understanding of how the universe works. \"According to theory, galaxies grow slowly from very small beginnings at early times,\" Labbe said, adding that such galaxies were expected to be between 10 to 100 times smaller. Inching towards the Big Bang: The James Webb telescope peers deep into space and time. But the size of these galaxies \"really go off a cliff,\" he said. What could be going on? One suspect is mysterious dark matter, which makes up a sizeable amount of the Universe. While much about dark matter remains unknown, scientists believe it plays a key role in the formation of galaxies. When dark matter \"clumps\" together into a halo, it attracts gas from the surrounding universe which in turn forms a galaxy and its stars, Labbe said. But this process is supposed to take a long time, and \"in the early universe, there's just not that many clumps of dark matter,\" he said. 'Model is cracking' The newly discovered galaxies could indicate that things sped up far faster in the early universe than previously thought, allowing stars to form \"much more efficiently,\" said David Elbaz, an astrophysicist at the French Atomic Energy Commission not involved in the research. This could be linked to recent signs that the universe itself is expanding faster than we once believed, he added. This subject sparks fierce debate among cosmologists, making this latest discovery \"all the more exciting, because it is one more indication that the model is cracking,\" Elbaz said. Elbaz is one of many scientists working on the European Space Agency's Euclid space telescope, which is scheduled to launch in July to join Webb in space. Euclid's mission is to uncover the secrets of dark matter and dark energy—and it could also help solve this latest mystery, Elbaz said. Labbe referred to the \"black swan theory\", under which just one unexpected event can overturn our previous understanding—such as when Europeans saw the first black swans in Australia. He called the galaxies \"six black swans—if even one of them turns out to be true, then it means we have to change our theories.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Galaxies with stellar masses as high as roughly 10 11 solar masses have been identified 1 , 2 , 3 out to redshifts z of roughly 6, around 1 billion years after the Big Bang. It has been difficult to find massive galaxies at even earlier times, as the Balmer break region, which is needed for accurate mass estimates, is redshifted to wavelengths beyond 2.5 μm. Here we make use of the 1–5 μm coverage of the James Webb Space Telescope early release observations to search for intrinsically red galaxies in the first roughly 750 million years of cosmic history. In the survey area, we find six candidate massive galaxies (stellar mass more than 10 10 solar masses) at 7.4 ≤ z ≤ 9.1, 500–700 Myr after the Big Bang, including one galaxy with a possible stellar mass of roughly 10 11 solar masses. If verified with spectroscopy, the stellar mass density in massive galaxies would be much higher than anticipated from previous studies on the basis of rest-frame ultraviolet-selected samples. Main The galaxies were identified in the first observations of the James Webb Space Telescope (JWST) Cosmic Evolution Early Release Science (CEERS) program. This program obtained multiband images at 1–5 μm with the Near-Infrared Camera (NIRCam) in a ‘blank’ field, chosen to overlap with existing Hubble Space Telescope (HST) imaging. The total area covered by these initial data is roughly 40 arcmin 2 . The data were obtained from the Mikulski Archive for Space Telescopes (MAST) archive and reduced using the Grizli pipeline 4 . A catalogue of sources was created, starting with detection in a deep combined F277W + F356W + F444W image (see Methods for details). A total of 42,729 objects are in this parent catalogue. We selected candidate massive galaxies at high redshifts by identifying objects that have two redshifted breaks in their spectral energy distributions (SEDs), the λ rest = 1,216 Å Lyman break and the λ rest of roughly 3,600 Å Balmer break. This selection ensures that the redshift probability distributions are well constrained, have no secondary solutions at lower redshifts and that we include galaxies that have potentially high mass-to-light (M/L) ratios. Specifically, we require that objects are not detected at optical wavelengths, blue in the near-infrared with F150W–F277W is less than 0.7, red at longer wavelengths with F277W–F444W is more than 1.0 and brighter than F444W is less than 27 AB units in magnitude. After visual inspection to remove obvious artefacts (such as diffraction spikes), this selection produced 13 galaxies with the sought-for ‘double-break’ SEDs. Next, redshifts and stellar masses were determined with three widely used techniques, taking the contribution of strong emission lines to the rest-frame optical photometry explicitly into account 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 . We use the EAZY code 16 (with extra strong emission-line templates), the Prospector-α framework 17 and five configurations of the Bagpipes SED-fitting code to explore systematics due to modelling assumptions. The seven individual mass and redshift measurements of the 13 galaxies are listed in the Methods section. We adopt fiducial masses and redshifts by taking the median value for each galaxy. We note that these masses and redshifts are not definitive and that all galaxies should be considered candidates. As shown in Fig. 1 , all 13 objects have photometric redshifts 6.5 < z < 9.1. Six of the 13 have fiducial masses greater than 10 10 M ☉ (Salpeter initial mass function (IMF)) and multiband images and SEDs of these galaxies are shown in Figs. 2 and 3 . Their photometric redshifts range from z = 7.4 to z = 9.1. The model fits are generally excellent, and in several cases clearly demonstrate that rest-frame optical emission lines contribute to the continuum emission. These lines can be so strong in young galaxies that they can dominate the broad-band fluxes redwards of the location of the Balmer break 6 , 7 , 8 , 14 , 18 , and Spitzer/IRAC detections of optical continuum breaks in galaxies at z ≳ 5 have been challenging to interpret 3 , 5 , 19 , 20 , 21 , 22 , 23 , 24 . With JWST, this ambiguity is largely resolved due to the dense wavelength coverage of the NIRCam filters and the inclusion of relatively narrow emission-line-sensitive filter F410M (ref. 25 ), which falls within the F444W band, although the uncertainties are such that alternative solutions with lower masses may exist 14 . The brightest galaxy in the sample, 38094, is at z = 7.5 and may have a mass that is as high as M * ≅ 1 × 10 11 M ☉ , more massive than the present-day Milky Way. It has two nearby companions with a similar break in their optical to near-infrared SEDs, suggesting that the galaxy may be in a group. Fig. 1: Redshifts and tentative stellar masses of double-break selected galaxies. Shown in grey circles are EAZY-determined redshifts and stellar masses using emission-line enhanced templates (Salpeter IMF) for objects with SNR > 8 in the F444W band. Fiducial redshifts and masses of the bright galaxies (F444W < 27 AB) that satisfy our double-break selection are shown by the large red symbols. Uncertainties are the 16th–84th percentiles of the posterior probability distribution. All galaxies have photometric redshifts 6.5 < z < 9.1. Six galaxies are candidate massive galaxies with fiducial M * > 10 10 M ☉ . Full size image Fig. 2: Images of the six galaxies with the highest apparent masses as a function of wavelength. The fiducial stellar masses of the galaxies are (log( M * / M ☉ ) > 10). Each cut-out has a size of 2.4″ × 2.4″. The filters range from the 0.6 μm F606W filter of HST /ACS to the 4.4 μm F444W JWST/NIRCam filter. The galaxies are undetected in the optical filters, blue in the short-wavelength NIRCam filters and red in the long-wavelength NIRCam<|im_end|> <|im_start|>assistant The James Webb Space Telescope has spotted six massive galaxies that emerged not long after the Big Bang, a study said Wednesday, surprising scientists by forming at a speed that contradicts our current understanding of the universe. Since becoming operational last July, the Webb telescope has been peering farther than ever before into the universe's distant reaches—which also means it is looking back in time. For its latest discovery, the telescope spied galaxies from between 500 to 700 years million years after the Big Bang 13.8 billion years ago, meaning the universe was under five percent of its current age. Webb's NIRCam instrument, which operates in the near infrared wavelength invisible to the naked eye, observed the six galaxies in a little-known region of the sky, according to a study published in the journal Nature. Two of the galaxies had previously been spotted by the Hubble Space Telescope but were so faint in those images that they went unnoticed. These six new "candidate galaxies", so-called because their discovery still needs to be confirmed by other measurements, contain many more stars than scientists expected. One galaxy is even believed to have around 100 billion stars. That would make it around the size of the Milky Way, which is "crazy," the study's first author Ivo Labbe told AFP. 'Off a cliff' It took our home galaxy the entire life of the universe for all its stars to assemble. For this young galaxy to achieve the same growth in just 700 million years, it would have had to grow around 20 times faster than the Milky Way, said Labbe, a researcher at Australia's Swinburne University of Technology. For there to be such massive galaxies so soon after the Big Bang goes against the current cosmological model which represents science's best understanding of how the universe works. "According to theory, galaxies grow slowly from very small beginnings at early times," Labbe said, adding that such galaxies were expected to be between 10 to 100 times smaller. Inching towards the Big Bang: The James Webb telescope peers deep into space and time. But the size of these galaxies "really go off a cliff," he said. What could be going on? One suspect is mysterious dark matter, which makes up a sizeable amount of the Universe. While much about dark matter remains unknown, scientists believe it plays a key role in the formation of galaxies. When dark matter "clumps" together into a halo, it attracts gas from the surrounding universe which in turn forms a galaxy and its stars, Labbe said. But this process is supposed to take a long time, and "in the early universe, there's just not that many clumps of dark matter," he said. 'Model is cracking' The newly discovered galaxies could indicate that things sped up far faster in the early universe than previously thought, allowing stars to form "much more efficiently," said David Elbaz, an astrophysicist at the French Atomic Energy Commission not involved in the research. This could be linked to recent signs that the universe itself is expanding faster than we once believed, he added. This subject sparks fierce debate among cosmologists, making this latest discovery "all the more exciting, because it is one more indication that the model is cracking," Elbaz said. Elbaz is one of many scientists working on the European Space Agency's Euclid space telescope, which is scheduled to launch in July to join Webb in space. Euclid's mission is to uncover the secrets of dark matter and dark energy—and it could also help solve this latest mystery, Elbaz said. Labbe referred to the "black swan theory", under which just one unexpected event can overturn our previous understanding—such as when Europeans saw the first black swans in Australia. He called the galaxies "six black swans—if even one of them turns out to be true, then it means we have to change our theories." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 10845, 58088, 449, 48317, 32738, 439, 1579, 439, 17715, 220, 605, 220, 806, 13238, 32738, 617, 1027, 11054, 220, 16, 1174, 220, 17, 1174, 220, 18, 704, 311, 2579, 13724, 82, 1167, 315, 17715, 220, 21, 11, 2212, 220, 16, 7239, 1667, 1306, 279, 6295, 17343, 13, 1102, 706, 1027, 5107, 311, 1505, 11191, 66017, 520, 1524, 6931, 3115, 11, 439, 279, 19984, 1195, 1464, 5654, 11, 902, 374, 4460, 369, 13687, 3148, 17989, 11, 374, 2579, 13724, 291, 311, 93959, 7953, 220, 17, 13, 20, 33983, 76, 13, 5810, 584, 1304, 1005, 315, 279, 220, 16, 4235, 20, 33983, 76, 10401, 315, 279, 7957, 55488, 11746, 87062, 4216, 4984, 24654, 311, 2778, 369, 10805, 1354, 2740, 2579, 66017, 304, 279, 1176, 17715, 220, 11711, 3610, 1667, 315, 55801, 3925, 13, 763, 279, 10795, 3158, 11, 584, 1505, 4848, 9322, 11191, 66017, 320, 78393, 3148, 810, 1109, 220, 605, 220, 605, 13238, 32738, 8, 520, 220, 22, 13, 19, 38394, 1167, 38394, 220, 24, 13, 16, 11, 220, 2636, 4235, 7007, 3092, 81, 1306, 279, 6295, 17343, 11, 2737, 832, 34261, 449, 264, 3284, 48317, 3148, 315, 17715, 220, 605, 220, 806, 13238, 32738, 13, 1442, 24884, 449, 66425, 51856, 11, 279, 48317, 3148, 17915, 304, 11191, 66017, 1053, 387, 1790, 5190, 1109, 30199, 505, 3766, 7978, 389, 279, 8197, 315, 2800, 47867, 37232, 85311, 46340, 10688, 13, 4802, 578, 66017, 1051, 11054, 304, 279, 1176, 24654, 315, 279, 7957, 55488, 11746, 87062, 320, 41, 54, 790, 8, 95789, 38321, 23591, 17836, 10170, 320, 2152, 4419, 8, 2068, 13, 1115, 2068, 12457, 2814, 88463, 5448, 520, 220, 16, 4235, 20, 33983, 76, 449, 279, 31494, 32600, 82482, 14669, 320, 45, 2871, 26479, 8, 304, 264, 3451, 10399, 529, 2115, 11, 12146, 311, 28347, 449, 6484, 473, 14942, 11746, 87062, 320, 39, 790, 8, 32758, 13, 578, 2860, 3158, 9960, 555, 1521, 2926, 828, 374, 17715, 220, 1272, 15952, 1083, 220, 17, 662, 578, 828, 1051, 12457, 505, 279, 43342, 360, 33639, 30802, 369, 11746, 2722, 64631, 19031, 320, 4940, 790, 8, 18624, 323, 11293, 1701, 279, 2895, 450, 747, 15660, 220, 19, 662, 362, 49639, 315, 8336, 574, 3549, 11, 6041, 449, 18468, 304, 264, 5655, 11093, 435, 16367, 54, 489, 435, 18349, 54, 489, 435, 14870, 54, 2217, 320, 4151, 19331, 369, 3649, 570, 362, 2860, 315, 220, 2983, 11, 22194, 6302, 527, 304, 420, 2748, 49639, 13, 1226, 4183, 9322, 11191, 66017, 520, 1579, 2579, 13724, 82, 555, 25607, 6302, 430, 617, 1403, 2579, 13724, 291, 18808, 304, 872, 57077, 4907, 43785, 320, 20890, 82, 705, 279, 49438, 2800, 284, 220, 16, 11, 12463, 80352, 16333, 1543, 1464, 323, 279, 49438, 2800, 315, 17715, 220, 18, 11, 5067, 80352, 19984, 1195, 1464, 13, 1115, 6727, 26420, 430, 279, 2579, 13724, 19463, 43785, 527, 1664, 54852, 11, 617, 912, 14580, 10105, 520, 4827, 2579, 13724, 82, 323, 430, 584, 2997, 66017, 430, 617, 13893, 1579, 3148, 4791, 18179, 320, 44, 7586, 8, 42338, 13, 45863, 11, 584, 1397, 430, 6302, 527, 539, 16914, 520, 29393, 93959, 11, 6437, 304, 279, 3221, 3502, 82482, 449, 435, 3965, 54, 4235, 37, 16367, 54, 374, 2753, 1109, 220, 15, 13, 22, 11, 2579, 520, 5129, 93959, 449, 435, 16367, 54, 4235, 37, 14870, 54, 374, 810, 1109, 220, 16, 13, 15, 323, 53657, 1109, 435, 14870, 54, 374, 2753, 1109, 220, 1544, 14469, 8316, 304, 26703, 13, 4740, 9302, 26767, 311, 4148, 8196, 52448, 69153, 320, 21470, 439, 3722, 16597, 51760, 705, 420, 6727, 9124, 220, 1032, 66017, 449, 279, 16495, 15548, 3451, 4429, 35449, 529, 328, 1507, 82, 13, 9479, 11, 2579, 13724, 82, 323, 48317, 32738, 1051, 11075, 449, 2380, 13882, 1511, 12823, 11, 4737, 279, 19035, 315, 3831, 41353, 5238, 311, 279, 2800, 47867, 29393, 4604, 7133, 21650, 1139, 2759, 220, 20, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 662, 1226, 1005, 279, 469, 74652, 2082, 220, 845, 320, 4291, 5066, 3831, 41353, 8614, 20506, 705, 279, 32134, 19534, 12, 19481, 12914, 220, 1114, 323, 4330, 33483, 315, 279, 20287, 87820, 328, 1507, 2269, 15154, 2082, 311, 13488, 1887, 29470, 4245, 311, 61966, 32946, 13, 578, 8254, 3927, 3148, 323, 2579, 13724, 22323, 315, 279, 220, 1032, 66017, 527, 10212, 304, 279, 19331, 3857, 13, 1226, 11142, 33204, 1791, 532, 32738, 323, 2579, 13724, 82, 555, 4737, 279, 23369, 907, 369, 1855, 34261, 13, 1226, 5296, 430, 1521, 32738, 323, 2579, 13724, 82, 527, 539, 45813, 323, 430, 682, 66017, 1288, 387, 6646, 11426, 13, 1666, 6982, 304, 23966, 13, 220, 16, 1174, 682, 220, 1032, 6302, 617, 4604, 24264, 2579, 13724, 82, 220, 21, 13, 20, 366, 1167, 366, 220, 24, 13, 16, 13, 19198, 315, 279, 220, 1032, 617, 33204, 1791, 532, 32738, 7191, 1109, 220, 605, 220, 605, 386, 26182, 231, 320, 17691, 79, 1430, 2926, 3148, 734, 320, 1829, 37, 595, 323, 2814, 88463, 5448, 323, 328, 1507, 82, 315, 1521, 66017, 527, 6982, 304, 435, 14801, 13, 220, 17, 323, 220, 18, 662, 11205, 4604, 24264, 2579, 13724, 82, 2134, 505, 1167, 284, 220, 22, 13, 19, 311, 1167, 284, 220, 24, 13, 16, 13, 578, 1646, 18809, 527, 8965, 9250, 11, 323, 304, 3892, 5157, 9539, 20461, 430, 2800, 47867, 29393, 41353, 5238, 17210, 311, 279, 86901, 41353, 13, 4314, 5238, 649, 387, 779, 3831, 304, 3995, 66017, 430, 814, 649, 41836, 279, 7353, 68775, 31405, 288, 2579, 4102, 315, 279, 3813, 315, 279, 19984, 1195, 1464, 220, 21, 1174, 220, 22, 1174, 220, 23, 1174, 220, 975, 1174, 220, 972, 1174, 323, 3165, 21114, 14, 2871, 1741, 89727, 315, 29393, 86901, 18808, 304, 66017, 520, 1167, 21784, 111, 220, 20, 617, 1027, 17436, 311, 14532, 220, 18, 1174, 220, 20, 1174, 220, 777, 1174, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 662, 3161, 96576, 790, 11, 420, 72868, 374, 14090, 20250, 4245, 311, 279, 29050, 46406, 10401, 315, 279, 99854, 26479, 13711, 323, 279, 28286, 315, 12309, 15376, 41353, 8614, 57767, 4141, 435, 14487, 44, 320, 1116, 13, 220, 914, 7026, 902, 17503, 2949, 279, 435, 14870, 54, 7200, 11, 8051, 279, 69867, 527, 1778, 430, 10778, 10105, 449, 4827, 32738, 1253, 3073, 220, 975, 662, 578, 72021, 34261, 304, 279, 6205, 11, 220, 13897, 6281, 11, 374, 520, 1167, 284, 220, 22, 13, 20, 323, 1253, 617, 264, 3148, 430, 374, 439, 1579, 439, 386, 353, 21784, 227, 220, 16, 25800, 220, 605, 220, 806, 386, 26182, 231, 1174, 810, 11191, 1109, 279, 3118, 11477, 89819, 12424, 13, 1102, 706, 1403, 14373, 41957, 449, 264, 4528, 1464, 304, 872, 29393, 311, 3221, 3502, 82482, 328, 1507, 82, 11, 23377, 430, 279, 34261, 1253, 387, 304, 264, 1912, 13, 23966, 13, 220, 16, 25, 3816, 13724, 82, 323, 76220, 48317, 32738, 315, 2033, 35449, 4183, 66017, 13, 1443, 785, 304, 20366, 26432, 527, 469, 74652, 1773, 47737, 2579, 13724, 82, 323, 48317, 32738, 1701, 41353, 8614, 24872, 20506, 320, 17691, 79, 1430, 60170, 8, 369, 6302, 449, 18407, 49, 871, 220, 23, 304, 279, 435, 14870, 54, 7200, 13, 435, 307, 1791, 532, 2579, 13724, 82, 323, 32738, 315, 279, 10107, 66017, 320, 37, 14870, 54, 366, 220, 1544, 14469, 8, 430, 27651, 1057, 2033, 35449, 6727, 527, 6982, 555, 279, 3544, 2579, 18210, 13, 29879, 531, 62124, 527, 279, 220, 845, 339, 4235, 5833, 339, 3346, 3742, 315, 279, 46000, 19463, 8141, 13, 2052, 66017, 617, 4604, 24264, 2579, 13724, 82, 220, 21, 13, 20, 366, 1167, 366, 220, 24, 13, 16, 13, 19198, 66017, 527, 9322, 11191, 66017, 449, 33204, 1791, 532, 386, 353, 871, 220, 605, 220, 605, 386, 26182, 231, 662, 8797, 1404, 2217, 23966, 13, 220, 17, 25, 12041, 315, 279, 4848, 66017, 449, 279, 8592, 10186, 32738, 439, 264, 734, 315, 46406, 13, 578, 33204, 1791, 532, 48317, 32738, 315, 279, 66017, 527, 320, 848, 7, 386, 353, 611, 386, 26182, 231, 883, 871, 220, 605, 570, 9062, 4018, 9994, 706, 264, 1404, 315, 220, 17, 13, 19, 22308, 25800, 220, 17, 13, 19, 22308, 13, 578, 13711, 2134, 505, 279, 220, 15, 13, 21, 33983, 76, 435, 20213, 54, 4141, 315, 473, 790, 611, 63787, 311, 279, 220, 19, 13, 19, 33983, 76, 435, 14870, 54, 96576, 790, 20906, 2871, 26479, 4141, 13, 578, 66017, 527, 2073, 295, 1599, 304, 279, 29393, 13711, 11, 6437, 304, 279, 2875, 2695, 35961, 99854, 26479, 13711, 323, 2579, 304, 279, 1317, 2695, 35961, 99854, 26479, 128257, 198, 128256, 78191, 198, 791, 7957, 55488, 11746, 87062, 706, 30652, 4848, 11191, 66017, 430, 22763, 539, 1317, 1306, 279, 6295, 17343, 11, 264, 4007, 1071, 8079, 11, 15206, 14248, 555, 30164, 520, 264, 4732, 430, 23093, 31095, 1057, 1510, 8830, 315, 279, 15861, 13, 8876, 10671, 25605, 1566, 5887, 11, 279, 55488, 56925, 706, 1027, 1069, 4776, 43726, 1109, 3596, 1603, 1139, 279, 15861, 596, 29827, 25501, 50004, 1101, 3445, 433, 374, 3411, 1203, 304, 892, 13, 1789, 1202, 5652, 18841, 11, 279, 56925, 993, 1142, 66017, 505, 1990, 220, 2636, 311, 220, 7007, 1667, 3610, 1667, 1306, 279, 6295, 17343, 220, 1032, 13, 23, 7239, 1667, 4227, 11, 7438, 279, 15861, 574, 1234, 4330, 3346, 315, 1202, 1510, 4325, 13, 55488, 596, 99854, 26479, 14473, 11, 902, 27149, 304, 279, 3221, 59141, 46406, 30547, 311, 279, 19557, 8071, 11, 13468, 279, 4848, 66017, 304, 264, 2697, 22015, 5654, 315, 279, 13180, 11, 4184, 311, 264, 4007, 4756, 304, 279, 8486, 22037, 13, 9220, 315, 279, 66017, 1047, 8767, 1027, 30652, 555, 279, 473, 14942, 11746, 87062, 719, 1051, 779, 38678, 304, 1884, 5448, 430, 814, 4024, 78023, 13, 4314, 4848, 502, 330, 47374, 66017, 498, 779, 19434, 1606, 872, 18841, 2103, 3966, 311, 387, 11007, 555, 1023, 22323, 11, 6782, 1690, 810, 9958, 1109, 14248, 3685, 13, 3861, 34261, 374, 1524, 11846, 311, 617, 2212, 220, 1041, 7239, 9958, 13, 3011, 1053, 1304, 433, 2212, 279, 1404, 315, 279, 89819, 12424, 11, 902, 374, 330, 66, 12350, 1359, 279, 4007, 596, 1176, 3229, 358, 3415, 11868, 1395, 3309, 27746, 13, 364, 4699, 264, 44106, 6, 1102, 3952, 1057, 2162, 34261, 279, 4553, 2324, 315, 279, 15861, 369, 682, 1202, 9958, 311, 42840, 13, 1789, 420, 3995, 34261, 311, 11322, 279, 1890, 6650, 304, 1120, 220, 7007, 3610, 1667, 11, 433, 1053, 617, 1047, 311, 3139, 2212, 220, 508, 3115, 10819, 1109, 279, 89819, 12424, 11, 1071, 11868, 1395, 11, 264, 32185, 520, 8494, 596, 4593, 258, 22464, 68, 3907, 315, 12053, 13, 1789, 1070, 311, 387, 1778, 11191, 66017, 779, 5246, 1306, 279, 6295, 17343, 5900, 2403, 279, 1510, 56754, 5848, 1646, 902, 11105, 8198, 596, 1888, 8830, 315, 1268, 279, 15861, 4375, 13, 330, 11439, 311, 10334, 11, 66017, 3139, 14297, 505, 1633, 2678, 67482, 520, 4216, 3115, 1359, 11868, 1395, 1071, 11, 7999, 430, 1778, 66017, 1051, 3685, 311, 387, 1990, 220, 605, 311, 220, 1041, 3115, 9333, 13, 763, 28075, 7119, 279, 6295, 17343, 25, 578, 7957, 55488, 56925, 26081, 5655, 1139, 3634, 323, 892, 13, 2030, 279, 1404, 315, 1521, 66017, 330, 54760, 733, 1022, 264, 44106, 1359, 568, 1071, 13, 3639, 1436, 387, 2133, 389, 30, 3861, 15562, 374, 26454, 6453, 5030, 11, 902, 3727, 709, 264, 1404, 481, 3392, 315, 279, 29849, 13, 6104, 1790, 922, 6453, 5030, 8625, 9987, 11, 14248, 4510, 433, 11335, 264, 1401, 3560, 304, 279, 18488, 315, 66017, 13, 3277, 6453, 5030, 330, 566, 12055, 1, 3871, 1139, 264, 71812, 11, 433, 61191, 6962, 505, 279, 14932, 15861, 902, 304, 2543, 7739, 264, 34261, 323, 1202, 9958, 11, 11868, 1395, 1071, 13, 2030, 420, 1920, 374, 10171, 311, 1935, 264, 1317, 892, 11, 323, 330, 258, 279, 4216, 15861, 11, 1070, 596, 1120, 539, 430, 1690, 1206, 12055, 315, 6453, 5030, 1359, 568, 1071, 13, 364, 1747, 374, 52829, 6, 578, 13945, 11352, 66017, 1436, 13519, 430, 2574, 86710, 709, 3117, 10819, 304, 279, 4216, 15861, 1109, 8767, 3463, 11, 10923, 9958, 311, 1376, 330, 59178, 810, 30820, 1359, 1071, 6941, 4072, 43673, 11, 459, 12025, 22761, 1065, 292, 380, 520, 279, 8753, 31416, 12634, 9849, 539, 6532, 304, 279, 3495, 13, 1115, 1436, 387, 10815, 311, 3293, 12195, 430, 279, 15861, 5196, 374, 24050, 10819, 1109, 584, 3131, 11846, 11, 568, 3779, 13, 1115, 3917, 76883, 42442, 11249, 4315, 56754, 22012, 11, 3339, 420, 5652, 18841, 330, 543, 279, 810, 13548, 11, 1606, 433, 374, 832, 810, 28137, 430, 279, 1646, 374, 52829, 1359, 4072, 43673, 1071, 13, 4072, 43673, 374, 832, 315, 1690, 14248, 3318, 389, 279, 7665, 11746, 16784, 596, 22730, 76144, 3634, 56925, 11, 902, 374, 13847, 311, 7195, 304, 5887, 311, 5249, 55488, 304, 3634, 13, 22730, 76144, 596, 9131, 374, 311, 45063, 279, 24511, 315, 6453, 5030, 323, 6453, 4907, 17223, 433, 1436, 1101, 1520, 11886, 420, 5652, 23347, 11, 4072, 43673, 1071, 13, 11868, 1395, 14183, 311, 279, 330, 11708, 2064, 276, 10334, 498, 1234, 902, 1120, 832, 16907, 1567, 649, 67687, 1057, 3766, 8830, 2345, 21470, 439, 994, 51607, 5602, 279, 1176, 3776, 2064, 598, 304, 8494, 13, 1283, 2663, 279, 66017, 330, 51464, 3776, 2064, 598, 90863, 1524, 832, 315, 1124, 10800, 704, 311, 387, 837, 11, 1243, 433, 3445, 584, 617, 311, 2349, 1057, 26018, 1210, 220, 128257, 198 ]

2,254

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Predisposition to Alzheimer’s disease (AD) may arise from lipid metabolism perturbation, however, the underlying mechanism remains elusive. Here, we identify ATPase family AAA-domain containing protein 3A (ATAD3A), a mitochondrial AAA-ATPase, as a molecular switch that links cholesterol metabolism impairment to AD phenotypes. In neuronal models of AD, the 5XFAD mouse model and post-mortem AD brains, ATAD3A is oligomerized and accumulated at the mitochondria-associated ER membranes (MAMs), where it induces cholesterol accumulation by inhibiting gene expression of CYP46A1, an enzyme governing brain cholesterol clearance. ATAD3A and CYP46A1 cooperate to promote APP processing and synaptic loss. Suppressing ATAD3A oligomerization by heterozygous ATAD3A knockout or pharmacological inhibition with DA1 restores neuronal CYP46A1 levels, normalizes brain cholesterol turnover and MAM integrity, suppresses APP processing and synaptic loss, and consequently reduces AD neuropathology and cognitive deficits in AD transgenic mice. These findings reveal a role for ATAD3A oligomerization in AD pathogenesis and suggest ATAD3A as a potential therapeutic target for AD. Introduction Alzheimer’s disease (AD) is the most common age-dependent neurodegenerative disease with unknown etiology. AD is characterized by the accumulation of amyloid deposition, neurofibrillary tangles, synaptic loss, and progressive cognitive decline 1 . Since the discovery of AD over 100 years ago, the underlying mechanisms of cellular damage and cognitive deficits remain elusive. As a result, current AD therapies are poorly effective and limited to acetylcholine or N-methyl-D-aspartate glutamatergic mechanisms that provide only mild symptomatic benefit and fail to slow disease progression 2 . Thus, the identification of novel therapeutic targets is imperative for developing disease-modifying therapies. Mitochondria and endoplasmic reticulum (ER) are highly interconnected. They physically interact to form specific microdomains called mitochondria-associated ER membranes (MAMs), where the outer mitochondrial membrane is close to the ER (i.e., within 10–30 nm) 3 . The MAMs are involved in many key metabolic functions 4 , including cholesterol metabolism 5 , lipid synthesis and trafficking 6 , mitochondrial dynamics 7 , calcium homeostasis 8 , and autophagy 9 . All these functions are altered in neurodegenerative diseases, including AD. Indeed, the integrity of the MAMs is significantly impaired in AD animal models and patients, manifesting as a hyperconnectivity of the MAMs 8 , 10 . MAM-resident proteins inositol 1,4,5‐trisphosphate receptor (IP3R) and long-chain acyl-CoA synthetase (FACL4) increase in various AD experimental models and the postmortem brains of AD patients 11 , 12 . Polymorphisms in mitofusin 2 and sigma non-opioid intracellular 1-receptor 1 (SigmaR1), two MAM proteins, correlate with the risk of developing AD 13 , 14 . Moreover, the amyloid precursor protein (APP) processing γ-secretases, presenilin-1 and presenilin-2, are highly enriched in the MAMs relative to other cell compartments, such as the plasma membrane, mitochondria, and ER 10 . These findings highlight the role of MAMs in amyloidogenesis. In addition, the ɛ4 allele of apolipoprotein E, the most common genetic risk factor of late-onset AD, upregulates MAM activity 15 . Thus, perturbed MAMs are a key event in AD pathogenesis and may serve as a common convergent neurodegenerative mechanism 16 . However, the factors that induce MAM hyperconnectivity in AD are poorly understood, and whether manipulation of impaired MAMs affects AD progression has not been explored. Perturbations in lipid homeostasis are another feature of AD. Accumulation of cholesterol has been observed in senile plaques and affected brain areas of AD patients 17 , and is associated with region-specific loss of synapses 18 . A growing number of animal studies have consistently demonstrated that hypercholesterolemia leads to dysfunction of the cholinergic system, cognitive deficits, and amyloid and tau pathology 19 , 20 , all of which strongly support a role for cholesterol disturbance in AD. In familial and sporadic AD subjects, increased cholesterol esters can be detected in the lipid raft-like MAMs 10 . Hyperactivity of MAM tethering causes cholesterol accumulation and synaptic loss and is associated with cognitive deficits 21 . In addition, the cleaved product of APP (i.e., C99) accumulates at MAMs, where it impairs mitochondrial bioenergetics, disrupts cellular lipid homeostasis, and causes alterations in membrane lipid composition commonly observed during AD pathogenesis 22 , 23 . Despite these findings, the mechanism that links MAM impairment, cholesterol accumulation, and amyloidogenesis in AD remains elusive. ATPase family AAA-domain containing protein 3A (ATAD3A) is a nuclear-encoded mitochondrial membrane protein that belongs to the AAA + -ATPase protein family. ATAD3A has a unique structure with a C-terminus that includes a conserved ATPase and is located in the mitochondrial matrix and an N-terminus associated with the MAMs via its proline-rich motif 24 , 25 . ATAD3A can regulate mitochondrial dynamics and maintain mitochondrial DNA (mtDNA) stability 25 , 26 , 27 . MAMs are a specialized subdomain of the ER with lipid raft features and rich in cholesterol and sphingomyelin 28 . Because of its unique localization on the MAMs, ATAD3A may regulate cholesterol trafficking through an unknown mechanism 26 . While global knockout of ATAD3A is embryonic lethal 29 , selective loss of ATAD3A in mouse skeletal muscle disrupts mtDNA integrity and impairs cholesterol trafficking 30 . Thus, by connecting two subcellular organelles (the mitochondria and ER) via the MAMs, ATAD3A simultaneously regulates mitochondrial structure integrity and cholesterol metabolism. The dysregulation of both these processes is observed in the early stage of AD. Patients deficient in ATAD3A develop neurodegenerative conditions associated with axonal neuropathy 31 , elevated free cholesterol, decreased expression of genes involved in cholesterol metabolism 26 , and spastic paraplegia 32 . More recently, we reported that in the fatal and inherited neurodegenerative condition of Huntington’s disease (HD), ATAD3A oligomerizes and accumulates at the contact sites of mitochondria and induces mitochondrial fragmentation, mitochondrial genome instability, and bioenergetic failure 27 . Moreover, blocking ATAD3A oligomerization by DA1, a peptide inhibitor, reduces HD pathology in various HD models 27 . Thus, ATAD3A may play an important role in the initiation and progression of neurodegeneration. However, whether ATAD3A is activated in AD and its exact roles in MAM hyperconnectivity and cholesterol disturbance underlying AD are unknown. In this study, we reported that ATAD3A oligomerization increased at the", "role": "user" }, { "content": "About 11% of the U.S. population 65 and older has been diagnosed with Alzheimer's disease (AD), the most common form of dementia that results in memory loss and cognitive impairment, according to the Alzheimer's Association. And the World Health Organization predicts the number of people living with Alzheimer's will grow by millions each year. Despite decades of research, scientists don't fully understand what causes the brain condition. And there is no known therapeutic treatment. But a new study published recently in Nature Communications by a team of researchers from the Case Western Reserve University School of Medicine suggests a key protein molecule plays a major role in the accumulation of brain cholesterol, triggering the development of Alzheimer's. The lab of Xin Qi, professor of physiology and biophysics at the School of Medicine, developed and patented a peptide inhibitor earlier in hopes of treating AD and Huntington's disease. She said this study found that mice, when treated with the peptide inhibitor, demonstrated 50% restored memory function, based on testing such as navigating mazes. The impact of Alzheimer's disease AD is an age-related neurodegenerative disorder that results in progressive cell death, leading to memory loss and cognitive dysfunction. The numbers around the disease are staggering—more than 5.7 million people have AD, and that group is estimated to reach 14 million by 2050, according to the Alzheimer's Association. That number is expected to balloon to 16 million by 2050. The cost of annual out-of-pocket healthcare for Alzheimer's totals more than $250 billion. Understanding the pathology Risk factors that contribute to AD include vascular diseases that impact the heart and blood vessels. While some risk factors are well known—aging, for example—others, such as brain cholesterol, play a key role in understanding how the disease develops. Brain cells communicate through cholesterol-rich cell membranes, a process that occurs naturally and is essential for healthy brain function. Research shows the brain contains 23-25% of the body's cholesterol. \"Cholesterol accumulates in the brain and causes damage to the neuron—it's long been understood as playing a role in Alzheimer's disease pathology,\" Qi said. \"However, what causes the cholesterol accumulation in the brain continues to be unknown and could hold answers.\" The study The paper is the result of more than five years of research into the role of brain cholesterol and its relationship with AD. The researchers set out to tackle two main questions: What role does brain cholesterol play in the disease? How can this new pathway be used for future treatment options? Qi, the paper's senior author, said the study centered on the protein coding gene, ATAD3A. Much is unknown about how the protein functions within neurodegenerative diseases. \"In Huntington's disease, the molecule ATAD3A becomes hyperactive and is oligomerized (repeated), which is a cause of the disease,\" Qi said. \"We worked with data scientists to see if ATAD3A also has a link to Alzheimer's disease and, to our surprise, we found that the molecule is a top candidate linked to Alzheimer's.\" From there, researchers gathered data by analyzing models and found a pathway linking ATAD3A and brain cholesterol. The researchers found that once ATAD3A forms repeating similar or identical parts through a process called oligomerization, it suppresses another protein called CYP46A1. The new protein then prevents cholesterol from being metabolized in the brain, meaning it accumulates. Researchers have linked the accumulation of brain cholesterol to disease progression in neurodegenerative diseases. The findings The data shows that ATAD3A—especially during oligomerization—could be the cause of AD development. With a possible target identified, Qi believes the next step to treatment lies in peptide inhibitors, which bind to ATAD3A and block it in action. \"Models treated with the peptide showed improved performance on the memory tests,\" Qi said. \"They showed increased memory retention, stronger cognitive activity and up to 50% restored damage to the memory.\" This means that targeting ATAD3A oligomerization can likely slow the progression of Alzheimer's disease, Qi said. Further testing is underway. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Predisposition to Alzheimer’s disease (AD) may arise from lipid metabolism perturbation, however, the underlying mechanism remains elusive. Here, we identify ATPase family AAA-domain containing protein 3A (ATAD3A), a mitochondrial AAA-ATPase, as a molecular switch that links cholesterol metabolism impairment to AD phenotypes. In neuronal models of AD, the 5XFAD mouse model and post-mortem AD brains, ATAD3A is oligomerized and accumulated at the mitochondria-associated ER membranes (MAMs), where it induces cholesterol accumulation by inhibiting gene expression of CYP46A1, an enzyme governing brain cholesterol clearance. ATAD3A and CYP46A1 cooperate to promote APP processing and synaptic loss. Suppressing ATAD3A oligomerization by heterozygous ATAD3A knockout or pharmacological inhibition with DA1 restores neuronal CYP46A1 levels, normalizes brain cholesterol turnover and MAM integrity, suppresses APP processing and synaptic loss, and consequently reduces AD neuropathology and cognitive deficits in AD transgenic mice. These findings reveal a role for ATAD3A oligomerization in AD pathogenesis and suggest ATAD3A as a potential therapeutic target for AD. Introduction Alzheimer’s disease (AD) is the most common age-dependent neurodegenerative disease with unknown etiology. AD is characterized by the accumulation of amyloid deposition, neurofibrillary tangles, synaptic loss, and progressive cognitive decline 1 . Since the discovery of AD over 100 years ago, the underlying mechanisms of cellular damage and cognitive deficits remain elusive. As a result, current AD therapies are poorly effective and limited to acetylcholine or N-methyl-D-aspartate glutamatergic mechanisms that provide only mild symptomatic benefit and fail to slow disease progression 2 . Thus, the identification of novel therapeutic targets is imperative for developing disease-modifying therapies. Mitochondria and endoplasmic reticulum (ER) are highly interconnected. They physically interact to form specific microdomains called mitochondria-associated ER membranes (MAMs), where the outer mitochondrial membrane is close to the ER (i.e., within 10–30 nm) 3 . The MAMs are involved in many key metabolic functions 4 , including cholesterol metabolism 5 , lipid synthesis and trafficking 6 , mitochondrial dynamics 7 , calcium homeostasis 8 , and autophagy 9 . All these functions are altered in neurodegenerative diseases, including AD. Indeed, the integrity of the MAMs is significantly impaired in AD animal models and patients, manifesting as a hyperconnectivity of the MAMs 8 , 10 . MAM-resident proteins inositol 1,4,5‐trisphosphate receptor (IP3R) and long-chain acyl-CoA synthetase (FACL4) increase in various AD experimental models and the postmortem brains of AD patients 11 , 12 . Polymorphisms in mitofusin 2 and sigma non-opioid intracellular 1-receptor 1 (SigmaR1), two MAM proteins, correlate with the risk of developing AD 13 , 14 . Moreover, the amyloid precursor protein (APP) processing γ-secretases, presenilin-1 and presenilin-2, are highly enriched in the MAMs relative to other cell compartments, such as the plasma membrane, mitochondria, and ER 10 . These findings highlight the role of MAMs in amyloidogenesis. In addition, the ɛ4 allele of apolipoprotein E, the most common genetic risk factor of late-onset AD, upregulates MAM activity 15 . Thus, perturbed MAMs are a key event in AD pathogenesis and may serve as a common convergent neurodegenerative mechanism 16 . However, the factors that induce MAM hyperconnectivity in AD are poorly understood, and whether manipulation of impaired MAMs affects AD progression has not been explored. Perturbations in lipid homeostasis are another feature of AD. Accumulation of cholesterol has been observed in senile plaques and affected brain areas of AD patients 17 , and is associated with region-specific loss of synapses 18 . A growing number of animal studies have consistently demonstrated that hypercholesterolemia leads to dysfunction of the cholinergic system, cognitive deficits, and amyloid and tau pathology 19 , 20 , all of which strongly support a role for cholesterol disturbance in AD. In familial and sporadic AD subjects, increased cholesterol esters can be detected in the lipid raft-like MAMs 10 . Hyperactivity of MAM tethering causes cholesterol accumulation and synaptic loss and is associated with cognitive deficits 21 . In addition, the cleaved product of APP (i.e., C99) accumulates at MAMs, where it impairs mitochondrial bioenergetics, disrupts cellular lipid homeostasis, and causes alterations in membrane lipid composition commonly observed during AD pathogenesis 22 , 23 . Despite these findings, the mechanism that links MAM impairment, cholesterol accumulation, and amyloidogenesis in AD remains elusive. ATPase family AAA-domain containing protein 3A (ATAD3A) is a nuclear-encoded mitochondrial membrane protein that belongs to the AAA + -ATPase protein family. ATAD3A has a unique structure with a C-terminus that includes a conserved ATPase and is located in the mitochondrial matrix and an N-terminus associated with the MAMs via its proline-rich motif 24 , 25 . ATAD3A can regulate mitochondrial dynamics and maintain mitochondrial DNA (mtDNA) stability 25 , 26 , 27 . MAMs are a specialized subdomain of the ER with lipid raft features and rich in cholesterol and sphingomyelin 28 . Because of its unique localization on the MAMs, ATAD3A may regulate cholesterol trafficking through an unknown mechanism 26 . While global knockout of ATAD3A is embryonic lethal 29 , selective loss of ATAD3A in mouse skeletal muscle disrupts mtDNA integrity and impairs cholesterol trafficking 30 . Thus, by connecting two subcellular organelles (the mitochondria and ER) via the MAMs, ATAD3A simultaneously regulates mitochondrial structure integrity and cholesterol metabolism. The dysregulation of both these processes is observed in the early stage of AD. Patients deficient in ATAD3A develop neurodegenerative conditions associated with axonal neuropathy 31 , elevated free cholesterol, decreased expression of genes involved in cholesterol metabolism 26 , and spastic paraplegia 32 . More recently, we reported that in the fatal and inherited neurodegenerative condition of Huntington’s disease (HD), ATAD3A oligomerizes and accumulates at the contact sites of mitochondria and induces mitochondrial fragmentation, mitochondrial genome instability, and bioenergetic failure 27 . Moreover, blocking ATAD3A oligomerization by DA1, a peptide inhibitor, reduces HD pathology in various HD models 27 . Thus, ATAD3A may play an important role in the initiation and progression of neurodegeneration. However, whether ATAD3A is activated in AD and its exact roles in MAM hyperconnectivity and cholesterol disturbance underlying AD are unknown. In this study, we reported that ATAD3A oligomerization increased at the<|im_end|> <|im_start|>assistant About 11% of the U.S. population 65 and older has been diagnosed with Alzheimer's disease (AD), the most common form of dementia that results in memory loss and cognitive impairment, according to the Alzheimer's Association. And the World Health Organization predicts the number of people living with Alzheimer's will grow by millions each year. Despite decades of research, scientists don't fully understand what causes the brain condition. And there is no known therapeutic treatment. But a new study published recently in Nature Communications by a team of researchers from the Case Western Reserve University School of Medicine suggests a key protein molecule plays a major role in the accumulation of brain cholesterol, triggering the development of Alzheimer's. The lab of Xin Qi, professor of physiology and biophysics at the School of Medicine, developed and patented a peptide inhibitor earlier in hopes of treating AD and Huntington's disease. She said this study found that mice, when treated with the peptide inhibitor, demonstrated 50% restored memory function, based on testing such as navigating mazes. The impact of Alzheimer's disease AD is an age-related neurodegenerative disorder that results in progressive cell death, leading to memory loss and cognitive dysfunction. The numbers around the disease are staggering—more than 5.7 million people have AD, and that group is estimated to reach 14 million by 2050, according to the Alzheimer's Association. That number is expected to balloon to 16 million by 2050. The cost of annual out-of-pocket healthcare for Alzheimer's totals more than $250 billion. Understanding the pathology Risk factors that contribute to AD include vascular diseases that impact the heart and blood vessels. While some risk factors are well known—aging, for example—others, such as brain cholesterol, play a key role in understanding how the disease develops. Brain cells communicate through cholesterol-rich cell membranes, a process that occurs naturally and is essential for healthy brain function. Research shows the brain contains 23-25% of the body's cholesterol. "Cholesterol accumulates in the brain and causes damage to the neuron—it's long been understood as playing a role in Alzheimer's disease pathology," Qi said. "However, what causes the cholesterol accumulation in the brain continues to be unknown and could hold answers." The study The paper is the result of more than five years of research into the role of brain cholesterol and its relationship with AD. The researchers set out to tackle two main questions: What role does brain cholesterol play in the disease? How can this new pathway be used for future treatment options? Qi, the paper's senior author, said the study centered on the protein coding gene, ATAD3A. Much is unknown about how the protein functions within neurodegenerative diseases. "In Huntington's disease, the molecule ATAD3A becomes hyperactive and is oligomerized (repeated), which is a cause of the disease," Qi said. "We worked with data scientists to see if ATAD3A also has a link to Alzheimer's disease and, to our surprise, we found that the molecule is a top candidate linked to Alzheimer's." From there, researchers gathered data by analyzing models and found a pathway linking ATAD3A and brain cholesterol. The researchers found that once ATAD3A forms repeating similar or identical parts through a process called oligomerization, it suppresses another protein called CYP46A1. The new protein then prevents cholesterol from being metabolized in the brain, meaning it accumulates. Researchers have linked the accumulation of brain cholesterol to disease progression in neurodegenerative diseases. The findings The data shows that ATAD3A—especially during oligomerization—could be the cause of AD development. With a possible target identified, Qi believes the next step to treatment lies in peptide inhibitors, which bind to ATAD3A and block it in action. "Models treated with the peptide showed improved performance on the memory tests," Qi said. "They showed increased memory retention, stronger cognitive activity and up to 50% restored damage to the memory." This means that targeting ATAD3A oligomerization can likely slow the progression of Alzheimer's disease, Qi said. Further testing is underway. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 393, 22496, 3571, 311, 44531, 753, 8624, 320, 1846, 8, 1253, 31889, 505, 68700, 39097, 18713, 65916, 11, 4869, 11, 279, 16940, 17383, 8625, 66684, 13, 5810, 11, 584, 10765, 67656, 521, 3070, 48197, 73894, 8649, 13128, 220, 18, 32, 320, 835, 1846, 18, 32, 705, 264, 72061, 48197, 12, 835, 47, 521, 11, 439, 264, 31206, 3480, 430, 7902, 39086, 39097, 53317, 311, 9827, 14345, 22583, 13, 763, 79402, 4211, 315, 9827, 11, 279, 220, 20, 67238, 1846, 8814, 1646, 323, 1772, 90653, 336, 9827, 35202, 11, 7520, 1846, 18, 32, 374, 55984, 26429, 1534, 323, 41165, 520, 279, 55042, 4298, 75968, 27590, 79348, 320, 44, 1428, 82, 705, 1405, 433, 90974, 39086, 46835, 555, 20747, 5977, 15207, 7645, 315, 356, 10158, 2790, 32, 16, 11, 459, 49242, 10217, 8271, 39086, 36654, 13, 7520, 1846, 18, 32, 323, 356, 10158, 2790, 32, 16, 47903, 311, 12192, 18395, 8863, 323, 99827, 4814, 13, 87898, 287, 7520, 1846, 18, 32, 55984, 26429, 2065, 555, 30548, 76523, 70, 788, 7520, 1846, 18, 32, 77173, 477, 36449, 5848, 61478, 449, 25561, 16, 88855, 79402, 356, 10158, 2790, 32, 16, 5990, 11, 4725, 4861, 8271, 39086, 48639, 323, 386, 1428, 17025, 11, 28321, 288, 18395, 8863, 323, 99827, 4814, 11, 323, 52394, 26338, 9827, 98666, 589, 2508, 323, 25702, 57096, 304, 9827, 1380, 89305, 24548, 13, 4314, 14955, 16805, 264, 3560, 369, 7520, 1846, 18, 32, 55984, 26429, 2065, 304, 9827, 1853, 52379, 323, 4284, 7520, 1846, 18, 32, 439, 264, 4754, 37471, 2218, 369, 9827, 13, 29438, 44531, 753, 8624, 320, 1846, 8, 374, 279, 1455, 4279, 4325, 43918, 18247, 451, 7642, 1413, 8624, 449, 9987, 1880, 31226, 13, 9827, 374, 32971, 555, 279, 46835, 315, 64383, 52196, 65374, 11, 18247, 69, 10892, 35605, 259, 17694, 11, 99827, 4814, 11, 323, 23053, 25702, 18174, 220, 16, 662, 8876, 279, 18841, 315, 9827, 927, 220, 1041, 1667, 4227, 11, 279, 16940, 24717, 315, 35693, 5674, 323, 25702, 57096, 7293, 66684, 13, 1666, 264, 1121, 11, 1510, 9827, 52312, 527, 31555, 7524, 323, 7347, 311, 1645, 87348, 331, 22671, 477, 452, 1474, 42972, 9607, 33534, 4581, 349, 35169, 309, 977, 70, 292, 24717, 430, 3493, 1193, 23900, 12104, 13795, 8935, 323, 3775, 311, 6435, 8624, 33824, 220, 17, 662, 14636, 11, 279, 22654, 315, 11775, 37471, 11811, 374, 48696, 369, 11469, 8624, 17515, 7922, 52312, 13, 22515, 47517, 4298, 323, 842, 56178, 10753, 292, 2160, 292, 16903, 320, 643, 8, 527, 7701, 83416, 13, 2435, 22655, 16681, 311, 1376, 3230, 8162, 60721, 2663, 55042, 4298, 75968, 27590, 79348, 320, 44, 1428, 82, 705, 1405, 279, 16335, 72061, 39654, 374, 3345, 311, 279, 27590, 320, 72, 1770, 2637, 2949, 220, 605, 4235, 966, 26807, 8, 220, 18, 662, 578, 386, 1428, 82, 527, 6532, 304, 1690, 1401, 41861, 5865, 220, 19, 1174, 2737, 39086, 39097, 220, 20, 1174, 68700, 39975, 323, 34563, 220, 21, 1174, 72061, 30295, 220, 22, 1174, 35719, 2162, 537, 10949, 220, 23, 1174, 323, 3154, 5237, 82770, 220, 24, 662, 2052, 1521, 5865, 527, 29852, 304, 18247, 451, 7642, 1413, 19338, 11, 2737, 9827, 13, 23150, 11, 279, 17025, 315, 279, 386, 1428, 82, 374, 12207, 50160, 304, 9827, 10065, 4211, 323, 6978, 11, 14794, 287, 439, 264, 17508, 6595, 1968, 315, 279, 386, 1428, 82, 220, 23, 1174, 220, 605, 662, 386, 1428, 11849, 1748, 28896, 304, 437, 27094, 220, 16, 11, 19, 11, 20, 31021, 376, 285, 764, 93473, 35268, 320, 3378, 18, 49, 8, 323, 1317, 66286, 1645, 4010, 87271, 32, 43998, 295, 521, 320, 37, 56493, 19, 8, 5376, 304, 5370, 9827, 22772, 4211, 323, 279, 1772, 93711, 336, 35202, 315, 9827, 6978, 220, 806, 1174, 220, 717, 662, 3735, 1631, 16751, 13978, 304, 5568, 1073, 355, 258, 220, 17, 323, 20868, 2536, 30592, 72, 590, 10805, 65441, 220, 16, 5621, 15709, 220, 16, 320, 63116, 49, 16, 705, 1403, 386, 1428, 28896, 11, 81584, 449, 279, 5326, 315, 11469, 9827, 220, 1032, 1174, 220, 975, 662, 23674, 11, 279, 64383, 52196, 71261, 13128, 320, 15049, 8, 8863, 63127, 69992, 2315, 11, 1685, 268, 123550, 12, 16, 323, 1685, 268, 123550, 12, 17, 11, 527, 7701, 69671, 304, 279, 386, 1428, 82, 8844, 311, 1023, 2849, 87352, 11, 1778, 439, 279, 32426, 39654, 11, 55042, 4298, 11, 323, 27590, 220, 605, 662, 4314, 14955, 11415, 279, 3560, 315, 386, 1428, 82, 304, 64383, 52196, 52379, 13, 763, 5369, 11, 279, 220, 133, 249, 19, 70510, 315, 1469, 337, 80482, 91748, 469, 11, 279, 1455, 4279, 19465, 5326, 8331, 315, 3389, 10539, 751, 9827, 11, 709, 1610, 24031, 386, 1428, 5820, 220, 868, 662, 14636, 11, 18713, 75325, 386, 1428, 82, 527, 264, 1401, 1567, 304, 9827, 1853, 52379, 323, 1253, 8854, 439, 264, 4279, 19873, 16149, 18247, 451, 7642, 1413, 17383, 220, 845, 662, 4452, 11, 279, 9547, 430, 49853, 386, 1428, 17508, 6595, 1968, 304, 9827, 527, 31555, 16365, 11, 323, 3508, 34786, 315, 50160, 386, 1428, 82, 22223, 9827, 33824, 706, 539, 1027, 36131, 13, 82884, 9225, 811, 304, 68700, 2162, 537, 10949, 527, 2500, 4668, 315, 9827, 13, 80625, 2987, 315, 39086, 706, 1027, 13468, 304, 6252, 458, 40852, 14295, 323, 11754, 8271, 5789, 315, 9827, 6978, 220, 1114, 1174, 323, 374, 5938, 449, 5654, 19440, 4814, 315, 6925, 79390, 220, 972, 662, 362, 7982, 1396, 315, 10065, 7978, 617, 21356, 21091, 430, 17508, 971, 273, 3751, 71958, 689, 11767, 311, 32403, 315, 279, 523, 37737, 75439, 1887, 11, 25702, 57096, 11, 323, 64383, 52196, 323, 32923, 77041, 220, 777, 1174, 220, 508, 1174, 682, 315, 902, 16917, 1862, 264, 3560, 369, 39086, 65858, 304, 9827, 13, 763, 98304, 323, 62016, 37314, 9827, 15223, 11, 7319, 39086, 1826, 388, 649, 387, 16914, 304, 279, 68700, 53555, 12970, 386, 1428, 82, 220, 605, 662, 33832, 7323, 315, 386, 1428, 80665, 287, 11384, 39086, 46835, 323, 99827, 4814, 323, 374, 5938, 449, 25702, 57096, 220, 1691, 662, 763, 5369, 11, 279, 11551, 4234, 2027, 315, 18395, 320, 72, 1770, 2637, 356, 1484, 8, 15783, 24031, 520, 386, 1428, 82, 11, 1405, 433, 3242, 4825, 72061, 17332, 804, 456, 1233, 11, 24927, 82, 35693, 68700, 2162, 537, 10949, 11, 323, 11384, 61086, 304, 39654, 68700, 18528, 17037, 13468, 2391, 9827, 1853, 52379, 220, 1313, 1174, 220, 1419, 662, 18185, 1521, 14955, 11, 279, 17383, 430, 7902, 386, 1428, 53317, 11, 39086, 46835, 11, 323, 64383, 52196, 52379, 304, 9827, 8625, 66684, 13, 67656, 521, 3070, 48197, 73894, 8649, 13128, 220, 18, 32, 320, 835, 1846, 18, 32, 8, 374, 264, 11499, 93362, 72061, 39654, 13128, 430, 17623, 311, 279, 48197, 489, 482, 835, 47, 521, 13128, 3070, 13, 7520, 1846, 18, 32, 706, 264, 5016, 6070, 449, 264, 356, 12, 23827, 355, 430, 5764, 264, 1615, 2841, 67656, 521, 323, 374, 7559, 304, 279, 72061, 6303, 323, 459, 452, 12, 23827, 355, 5938, 449, 279, 386, 1428, 82, 4669, 1202, 463, 1074, 41947, 60612, 220, 1187, 1174, 220, 914, 662, 7520, 1846, 18, 32, 649, 37377, 72061, 30295, 323, 10519, 72061, 15922, 320, 2562, 56420, 8, 20334, 220, 914, 1174, 220, 1627, 1174, 220, 1544, 662, 386, 1428, 82, 527, 264, 28175, 1207, 12482, 315, 279, 27590, 449, 68700, 53555, 4519, 323, 9257, 304, 39086, 323, 42822, 287, 5650, 33830, 220, 1591, 662, 9393, 315, 1202, 5016, 53404, 389, 279, 386, 1428, 82, 11, 7520, 1846, 18, 32, 1253, 37377, 39086, 34563, 1555, 459, 9987, 17383, 220, 1627, 662, 6104, 3728, 77173, 315, 7520, 1846, 18, 32, 374, 44481, 14338, 45089, 220, 1682, 1174, 44010, 4814, 315, 7520, 1846, 18, 32, 304, 8814, 69397, 16124, 24927, 82, 12232, 56420, 17025, 323, 3242, 4825, 39086, 34563, 220, 966, 662, 14636, 11, 555, 21583, 1403, 1207, 5997, 1299, 1262, 2444, 645, 320, 1820, 55042, 4298, 323, 27590, 8, 4669, 279, 386, 1428, 82, 11, 7520, 1846, 18, 32, 25291, 80412, 72061, 6070, 17025, 323, 39086, 39097, 13, 578, 22709, 1610, 2987, 315, 2225, 1521, 11618, 374, 13468, 304, 279, 4216, 6566, 315, 9827, 13, 44430, 87544, 304, 7520, 1846, 18, 32, 2274, 18247, 451, 7642, 1413, 4787, 5938, 449, 3944, 25180, 98666, 19682, 220, 2148, 1174, 32389, 1949, 39086, 11, 25983, 7645, 315, 21389, 6532, 304, 39086, 39097, 220, 1627, 1174, 323, 993, 5174, 1370, 391, 1978, 689, 220, 843, 662, 4497, 6051, 11, 584, 5068, 430, 304, 279, 19094, 323, 28088, 18247, 451, 7642, 1413, 3044, 315, 75851, 753, 8624, 320, 19694, 705, 7520, 1846, 18, 32, 55984, 26429, 4861, 323, 15783, 24031, 520, 279, 3729, 6732, 315, 55042, 4298, 323, 90974, 72061, 88452, 11, 72061, 33869, 56399, 11, 323, 17332, 804, 36324, 8060, 220, 1544, 662, 23674, 11, 22978, 7520, 1846, 18, 32, 55984, 26429, 2065, 555, 25561, 16, 11, 264, 72249, 70785, 11, 26338, 12445, 77041, 304, 5370, 12445, 4211, 220, 1544, 662, 14636, 11, 7520, 1846, 18, 32, 1253, 1514, 459, 3062, 3560, 304, 279, 61568, 323, 33824, 315, 18247, 451, 81157, 13, 4452, 11, 3508, 7520, 1846, 18, 32, 374, 22756, 304, 9827, 323, 1202, 4839, 13073, 304, 386, 1428, 17508, 6595, 1968, 323, 39086, 65858, 16940, 9827, 527, 9987, 13, 763, 420, 4007, 11, 584, 5068, 430, 7520, 1846, 18, 32, 55984, 26429, 2065, 7319, 520, 279, 128257, 198, 128256, 78191, 198, 10714, 220, 806, 4, 315, 279, 549, 815, 13, 7187, 220, 2397, 323, 9191, 706, 1027, 29704, 449, 44531, 596, 8624, 320, 1846, 705, 279, 1455, 4279, 1376, 315, 52857, 430, 3135, 304, 5044, 4814, 323, 25702, 53317, 11, 4184, 311, 279, 44531, 596, 10229, 13, 1628, 279, 4435, 6401, 21021, 56978, 279, 1396, 315, 1274, 5496, 449, 44531, 596, 690, 3139, 555, 11990, 1855, 1060, 13, 18185, 11026, 315, 3495, 11, 14248, 1541, 956, 7373, 3619, 1148, 11384, 279, 8271, 3044, 13, 1628, 1070, 374, 912, 3967, 37471, 6514, 13, 2030, 264, 502, 4007, 4756, 6051, 304, 22037, 26545, 555, 264, 2128, 315, 12074, 505, 279, 11799, 11104, 25820, 3907, 6150, 315, 19152, 13533, 264, 1401, 13128, 43030, 11335, 264, 3682, 3560, 304, 279, 46835, 315, 8271, 39086, 11, 52605, 279, 4500, 315, 44531, 596, 13, 578, 10278, 315, 70761, 58094, 11, 14561, 315, 78152, 323, 6160, 5237, 17688, 520, 279, 6150, 315, 19152, 11, 8040, 323, 63712, 264, 72249, 70785, 6931, 304, 16388, 315, 27723, 9827, 323, 75851, 596, 8624, 13, 3005, 1071, 420, 4007, 1766, 430, 24548, 11, 994, 12020, 449, 279, 72249, 70785, 11, 21091, 220, 1135, 4, 28101, 5044, 734, 11, 3196, 389, 7649, 1778, 439, 60499, 296, 74885, 13, 578, 5536, 315, 44531, 596, 8624, 9827, 374, 459, 4325, 14228, 18247, 451, 7642, 1413, 19823, 430, 3135, 304, 23053, 2849, 4648, 11, 6522, 311, 5044, 4814, 323, 25702, 32403, 13, 578, 5219, 2212, 279, 8624, 527, 55944, 2345, 6518, 1109, 220, 20, 13, 22, 3610, 1274, 617, 9827, 11, 323, 430, 1912, 374, 13240, 311, 5662, 220, 975, 3610, 555, 220, 10866, 15, 11, 4184, 311, 279, 44531, 596, 10229, 13, 3011, 1396, 374, 3685, 311, 47856, 311, 220, 845, 3610, 555, 220, 10866, 15, 13, 578, 2853, 315, 9974, 704, 8838, 99436, 18985, 369, 44531, 596, 44745, 810, 1109, 400, 5154, 7239, 13, 46551, 279, 77041, 32388, 9547, 430, 17210, 311, 9827, 2997, 64603, 19338, 430, 5536, 279, 4851, 323, 6680, 31080, 13, 6104, 1063, 5326, 9547, 527, 1664, 3967, 2345, 4210, 11, 369, 3187, 2345, 59961, 11, 1778, 439, 8271, 39086, 11, 1514, 264, 1401, 3560, 304, 8830, 1268, 279, 8624, 39671, 13, 31417, 7917, 19570, 1555, 39086, 41947, 2849, 79348, 11, 264, 1920, 430, 13980, 18182, 323, 374, 7718, 369, 9498, 8271, 734, 13, 8483, 5039, 279, 8271, 5727, 220, 1419, 12, 914, 4, 315, 279, 2547, 596, 39086, 13, 330, 1163, 35244, 15783, 24031, 304, 279, 8271, 323, 11384, 5674, 311, 279, 49384, 44603, 596, 1317, 1027, 16365, 439, 5737, 264, 3560, 304, 44531, 596, 8624, 77041, 1359, 58094, 1071, 13, 330, 11458, 11, 1148, 11384, 279, 39086, 46835, 304, 279, 8271, 9731, 311, 387, 9987, 323, 1436, 3412, 11503, 1210, 578, 4007, 578, 5684, 374, 279, 1121, 315, 810, 1109, 4330, 1667, 315, 3495, 1139, 279, 3560, 315, 8271, 39086, 323, 1202, 5133, 449, 9827, 13, 578, 12074, 743, 704, 311, 22118, 1403, 1925, 4860, 25, 3639, 3560, 1587, 8271, 39086, 1514, 304, 279, 8624, 30, 2650, 649, 420, 502, 38970, 387, 1511, 369, 3938, 6514, 2671, 30, 58094, 11, 279, 5684, 596, 10195, 3229, 11, 1071, 279, 4007, 31288, 389, 279, 13128, 11058, 15207, 11, 7520, 1846, 18, 32, 13, 24191, 374, 9987, 922, 1268, 279, 13128, 5865, 2949, 18247, 451, 7642, 1413, 19338, 13, 330, 644, 75851, 596, 8624, 11, 279, 43030, 7520, 1846, 18, 32, 9221, 17508, 3104, 323, 374, 55984, 26429, 1534, 320, 265, 43054, 705, 902, 374, 264, 5353, 315, 279, 8624, 1359, 58094, 1071, 13, 330, 1687, 6575, 449, 828, 14248, 311, 1518, 422, 7520, 1846, 18, 32, 1101, 706, 264, 2723, 311, 44531, 596, 8624, 323, 11, 311, 1057, 13051, 11, 584, 1766, 430, 279, 43030, 374, 264, 1948, 9322, 10815, 311, 44531, 596, 1210, 5659, 1070, 11, 12074, 20802, 828, 555, 42118, 4211, 323, 1766, 264, 38970, 31799, 7520, 1846, 18, 32, 323, 8271, 39086, 13, 578, 12074, 1766, 430, 3131, 7520, 1846, 18, 32, 7739, 40916, 4528, 477, 20086, 5596, 1555, 264, 1920, 2663, 55984, 26429, 2065, 11, 433, 28321, 288, 2500, 13128, 2663, 356, 10158, 2790, 32, 16, 13, 578, 502, 13128, 1243, 29034, 39086, 505, 1694, 28168, 1534, 304, 279, 8271, 11, 7438, 433, 15783, 24031, 13, 59250, 617, 10815, 279, 46835, 315, 8271, 39086, 311, 8624, 33824, 304, 18247, 451, 7642, 1413, 19338, 13, 578, 14955, 578, 828, 5039, 430, 7520, 1846, 18, 32, 2345, 36046, 2391, 55984, 26429, 2065, 2345, 29177, 387, 279, 5353, 315, 9827, 4500, 13, 3161, 264, 3284, 2218, 11054, 11, 58094, 13919, 279, 1828, 3094, 311, 6514, 15812, 304, 72249, 68642, 11, 902, 10950, 311, 7520, 1846, 18, 32, 323, 2565, 433, 304, 1957, 13, 330, 17399, 12020, 449, 279, 72249, 8710, 13241, 5178, 389, 279, 5044, 7177, 1359, 58094, 1071, 13, 330, 7009, 8710, 7319, 5044, 38231, 11, 16643, 25702, 5820, 323, 709, 311, 220, 1135, 4, 28101, 5674, 311, 279, 5044, 1210, 1115, 3445, 430, 25103, 7520, 1846, 18, 32, 55984, 26429, 2065, 649, 4461, 6435, 279, 33824, 315, 44531, 596, 8624, 11, 58094, 1071, 13, 15903, 7649, 374, 38199, 13, 220, 128257, 198 ]

2,406

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Approximately 100,000 individuals in the United States currently await kidney transplantation, and 400,000 individuals live with end-stage kidney disease requiring hemodialysis. The creation of a transplantable graft to permanently replace kidney function would address donor organ shortage and the morbidity associated with immunosuppression. Such a bioengineered graft must have the kidney's architecture and function and permit perfusion, filtration, secretion, absorption and drainage of urine. We decellularized rat, porcine and human kidneys by detergent perfusion, yielding acellular scaffolds with vascular, cortical and medullary architecture, a collecting system and ureters. To regenerate functional tissue, we seeded rat kidney scaffolds with epithelial and endothelial cells and perfused these cell-seeded constructs in a whole-organ bioreactor. The resulting grafts produced rudimentary urine in vitro when perfused through their intrinsic vascular bed. When transplanted in an orthotopic position in rat, the grafts were perfused by the recipient's circulation and produced urine through the ureteral conduit in vivo . Main Nearly 1 million patients in the United States live with end-stage renal disease (ESRD), with over 100,000 new diagnoses every year 1 . Although hemodialysis has increased the survival of patients with ESRD, transplantation remains the only available curative treatment. About 18,000 kidney transplants are performed per year in the United States 1 , yet approximately 100,000 Americans currently await a donor kidney 2 . Stagnant donor organ numbers have increased waiting times to over 3 years and waitlist mortality to 5–10%. Despite advances in renal transplant immunology 3 , 20% of recipients will experience an episode of acute rejection within 5 years of transplantation, and approximately 40% of recipients will die or lose graft function within 10 years after transplantation. Creation of a bioengineered kidney could theoretically bypass these problems by providing an autologous graft on demand. Hemofiltration and hemodialysis use an acellular semipermeable membrane to substitute the native kidney's functions. Several attempts have been made to bioengineer viable tubular structures to further supplement hemofiltration with cell-dependent functions 4 , 5 . When hemofiltration devices have been combined with bioengineered renal tubules, the resulting bioartificial kidney replaced renal function in uremic dogs 6 and temporarily improved renal function in patients with acute renal failure 7 , 8 . In an alternative approach, kidney primordia have been shown to develop into functional organs in vivo and prolong life when transplanted into anephric rats 9 . Devices to make renal-assist devices more portable 10 or even implantable 11 have reached the stage of preclinical evaluation and hold tremendous promise for improving the quality of life of patients in end-stage renal failure. Autologous urinary tract tissue generated from biocompatible matrix and patient-derived cells has been used clinically for bladder augmentation 12 . A key step toward a fully implantable, permanent graft is the development of a biocompatible scaffold that facilitates cell engraftment and function and allows full recipient integration through blood perfusion. On the basis of our previous experience with whole-organ heart 13 and lung 14 extracellular matrix (ECM) scaffolds, we hypothesized that the native kidney ECM could provide such a scaffold for subsequent cell seeding. In previous studies, detergents were used to remove cells from native kidney ECM while preserving the biomechanical properties and matrix protein characteristics in tissue slices 15 and whole organs 16 , 17 , 18 , 19 . We therefore decellularized kidneys using detergent perfusion to create whole-organ scaffolds with intact and perfusable vascular, glomerular and tubular compartments. We repopulated the decellularized kidney scaffolds with endothelial and epithelial cells. In vitro biomimetic culture using arterial perfusion led to the formation of functional renal grafts. To test in vivo host integration and function, we transplanted bioengineered kidneys in an orthotopic position and documented urine production. Results Perfusion decellularization of cadaveric kidneys We decellularized cadaveric rat kidneys using renal artery perfusion with 1% sodium dodecyl sulfate (SDS) at a constant pressure of 40 mm Hg ( Fig. 1a ). Histology of the acellular kidneys showed preservation of tissue architecture and the complete removal of nuclei and cellular components ( Fig. 1b ). Perfusion decellularization preserved the structure and composition of the renal ECM, which is integral in filtration (glomerular basement membrane), secretion and reabsorption (tubular basement membrane). As has been seen with other tissues 13 , 14 , the arterial elastic fiber network remained preserved in acellular cortical and medullary parenchyma. Immunohistochemical staining confirmed the presence of key ECM components such as laminin and collagen IV in a physiologic distribution, for example, in the acellular glomerular basement membrane ( Fig. 1c,d ). The microarchitecture of the lobulated glomerular basement membrane with the capillary and mesangial matrix extending from the centrilobular stalk remained intact. Acellular glomeruli were further encompassed by a multilayered corrugated and continuous Bowman's capsule basement membrane ( Fig. 1e,f ). Tubular basement membranes remained preserved, with dentate evaginations extending into the proximal tubular lumen. SDS, deionized water and Triton X-100 reduced the total DNA content per kidney to less than 10% ( Fig. 1g ). After washing with PBS, SDS was undetectable in the acellular kidney scaffolds. Concentrations of total collagen and glycosaminoglycans in the ECM were preserved at levels not significantly different from those in cadaveric kidney tissue ( Fig. 1h ). To confirm the scalability of the perfusion decellularization protocol to kidneys of large animals and humans, we successfully decellularized porcine and human kidneys using a similar perfusion protocol ( Fig. 2a–d ). We confirmed preservation of perfusable channels along a hierarchical vascular bed by dye perfusion in a manner similar to that in our previous experiments with perfusion of decellularized hearts and lungs 13 , 14 ( Supplementary Fig. 1 ). Functional testing of acellular kidney scaffolds by perfusion of the vasculature with modified Krebs-Henseleit solution under physiologic perfusion pressure resulted in production of a filtrate that was high in protein, glucose and electrolytes, suggesting hydrostatic filtration across glomerular and tubular basement membranes with loss of macromolecular sieving and active reabsorption. Figure 1: Perfusion decellularization of whole rat kidneys. ( a ) Time-lapse photographs of a cadaveric rat kidney undergoing", "role": "user" }, { "content": "Bioengineered rat kidneys developed by Massachusetts General Hospital (MGH) investigators successfully produced urine both in a laboratory apparatus and after being transplanted into living animals. In their report, receiving advance online publication in Nature Medicine, the research team describes building functional replacement kidneys on the structure of donor organs from which living cells had been stripped, an approach previously used to create bioartificial hearts, lungs and livers. \"What is unique about this approach is that the native organ's architecture is preserved, so that the resulting graft can be transplanted just like a donor kidney and connected to the recipient's vascular and urinary systems,\" says Harald Ott, MD, PhD, of the MGH Center for Regenerative Medicine, senior author of the Nature Medicine article. \"If this technology can be scaled to human-sized grafts, patients suffering from renal failure who are currently waiting for donor kidneys or who are not transplant candidates could theoretically receive new organs derived from their own cells.\" Around 18,000 kidney transplants are performed in the U.S. each year, but 100,000 Americans with end-stage kidney disease are still waiting for a donor organ. Even those fortunate enough to receive a transplant face a lifetime of immunosuppressive drugs, which pose many health risks and cannot totally eliminate the incidence of eventual organ rejection. The approach used in this study to engineer donor organs, based on a technology that Ott discovered as a research fellow at the University of Minnesota, involves stripping the living cells from a donor organ with a detergent solution and then repopulating the collagen scaffold that remains with the appropriate cell type – in this instance human endothelial cells to replace the lining of the vascular system and kidney cells from newborn rats. The research team first decellularized rat kidneys to confirm that the organ's complex structures would be preserved. They also showed the technique worked on a larger scale by stripping cells from pig and human kidneys. Making sure the appropriate cells were seeded into the correct portions of the collagen scaffold required delivering vascular cells through the renal artery and kidney cells through the ureter. Precisely adjusting the pressures of the solutions enabled the cells to be dispersed throughout the whole organs, which were then cultured in a bioreactor for up to 12 days. The researchers first tested the repopulated organs in a device that passed blood through its vascular system and drained off any urine, which revealed evidence of limited filtering of blood, molecular activity and urine production. This is a previously decellularized rat kidney after reseeding with endothelial cells, to repopulate the organ's vascular system, and neonatal kidney cells. Credit: Massachusetts General Hospital Center for Regenerative Medicine Bioengineered kidneys transplanted into living rats from which one kidney had been removed began producing urine as soon as the blood supply was restored, with no evidence of bleeding or clot formation. The overall function of the regenerated organs was significantly reduced compared with that of normal, healthy kidneys, something the researchers believe may be attributed to the immaturity of the neonatal cells used to repopulate the scaffolding. \"Further refinement of the cell types used for seeding and additional maturation in culture may allow us to achieve a more functional organ,\" says Ott. \"Based on this inital proof of principle, we hope that bioengineered kidneys will someday be able to fully replace kidney function just as donor kidneys do. In an ideal world, such grafts could be produced 'on demand\" from a patient's own cells, helping us overcome both the organ shortage and the need for chronic immunosuppression. We're now investigating methods of deriving the necessary cell types from patient-derived cells and refining the cell-seeding and organ culture methods to handle human-sized organs.\" Ott's team focuses on the regeneration of hearts, lungs, kidneys and grafts made of composite tissues, while other teams – including one from the MGH Center for Engineering in Medicine – are using the decellularization technique to develop replacement livers. Lead author of the Nature Medicine paper is Jeremy Song, MGH Center for Regenerative Medicine; additional co-authors are Jacques Guyette, PhD, Sarah Gilpin, PhD, Gabriel Gonzalez, PhD, and Joseph Vacanti, MD, all of the MGH Center for Regenerative Medicine. The study was supported by National Institute of Health Director's New Innovator Award DP2 OD008749-01. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Approximately 100,000 individuals in the United States currently await kidney transplantation, and 400,000 individuals live with end-stage kidney disease requiring hemodialysis. The creation of a transplantable graft to permanently replace kidney function would address donor organ shortage and the morbidity associated with immunosuppression. Such a bioengineered graft must have the kidney's architecture and function and permit perfusion, filtration, secretion, absorption and drainage of urine. We decellularized rat, porcine and human kidneys by detergent perfusion, yielding acellular scaffolds with vascular, cortical and medullary architecture, a collecting system and ureters. To regenerate functional tissue, we seeded rat kidney scaffolds with epithelial and endothelial cells and perfused these cell-seeded constructs in a whole-organ bioreactor. The resulting grafts produced rudimentary urine in vitro when perfused through their intrinsic vascular bed. When transplanted in an orthotopic position in rat, the grafts were perfused by the recipient's circulation and produced urine through the ureteral conduit in vivo . Main Nearly 1 million patients in the United States live with end-stage renal disease (ESRD), with over 100,000 new diagnoses every year 1 . Although hemodialysis has increased the survival of patients with ESRD, transplantation remains the only available curative treatment. About 18,000 kidney transplants are performed per year in the United States 1 , yet approximately 100,000 Americans currently await a donor kidney 2 . Stagnant donor organ numbers have increased waiting times to over 3 years and waitlist mortality to 5–10%. Despite advances in renal transplant immunology 3 , 20% of recipients will experience an episode of acute rejection within 5 years of transplantation, and approximately 40% of recipients will die or lose graft function within 10 years after transplantation. Creation of a bioengineered kidney could theoretically bypass these problems by providing an autologous graft on demand. Hemofiltration and hemodialysis use an acellular semipermeable membrane to substitute the native kidney's functions. Several attempts have been made to bioengineer viable tubular structures to further supplement hemofiltration with cell-dependent functions 4 , 5 . When hemofiltration devices have been combined with bioengineered renal tubules, the resulting bioartificial kidney replaced renal function in uremic dogs 6 and temporarily improved renal function in patients with acute renal failure 7 , 8 . In an alternative approach, kidney primordia have been shown to develop into functional organs in vivo and prolong life when transplanted into anephric rats 9 . Devices to make renal-assist devices more portable 10 or even implantable 11 have reached the stage of preclinical evaluation and hold tremendous promise for improving the quality of life of patients in end-stage renal failure. Autologous urinary tract tissue generated from biocompatible matrix and patient-derived cells has been used clinically for bladder augmentation 12 . A key step toward a fully implantable, permanent graft is the development of a biocompatible scaffold that facilitates cell engraftment and function and allows full recipient integration through blood perfusion. On the basis of our previous experience with whole-organ heart 13 and lung 14 extracellular matrix (ECM) scaffolds, we hypothesized that the native kidney ECM could provide such a scaffold for subsequent cell seeding. In previous studies, detergents were used to remove cells from native kidney ECM while preserving the biomechanical properties and matrix protein characteristics in tissue slices 15 and whole organs 16 , 17 , 18 , 19 . We therefore decellularized kidneys using detergent perfusion to create whole-organ scaffolds with intact and perfusable vascular, glomerular and tubular compartments. We repopulated the decellularized kidney scaffolds with endothelial and epithelial cells. In vitro biomimetic culture using arterial perfusion led to the formation of functional renal grafts. To test in vivo host integration and function, we transplanted bioengineered kidneys in an orthotopic position and documented urine production. Results Perfusion decellularization of cadaveric kidneys We decellularized cadaveric rat kidneys using renal artery perfusion with 1% sodium dodecyl sulfate (SDS) at a constant pressure of 40 mm Hg ( Fig. 1a ). Histology of the acellular kidneys showed preservation of tissue architecture and the complete removal of nuclei and cellular components ( Fig. 1b ). Perfusion decellularization preserved the structure and composition of the renal ECM, which is integral in filtration (glomerular basement membrane), secretion and reabsorption (tubular basement membrane). As has been seen with other tissues 13 , 14 , the arterial elastic fiber network remained preserved in acellular cortical and medullary parenchyma. Immunohistochemical staining confirmed the presence of key ECM components such as laminin and collagen IV in a physiologic distribution, for example, in the acellular glomerular basement membrane ( Fig. 1c,d ). The microarchitecture of the lobulated glomerular basement membrane with the capillary and mesangial matrix extending from the centrilobular stalk remained intact. Acellular glomeruli were further encompassed by a multilayered corrugated and continuous Bowman's capsule basement membrane ( Fig. 1e,f ). Tubular basement membranes remained preserved, with dentate evaginations extending into the proximal tubular lumen. SDS, deionized water and Triton X-100 reduced the total DNA content per kidney to less than 10% ( Fig. 1g ). After washing with PBS, SDS was undetectable in the acellular kidney scaffolds. Concentrations of total collagen and glycosaminoglycans in the ECM were preserved at levels not significantly different from those in cadaveric kidney tissue ( Fig. 1h ). To confirm the scalability of the perfusion decellularization protocol to kidneys of large animals and humans, we successfully decellularized porcine and human kidneys using a similar perfusion protocol ( Fig. 2a–d ). We confirmed preservation of perfusable channels along a hierarchical vascular bed by dye perfusion in a manner similar to that in our previous experiments with perfusion of decellularized hearts and lungs 13 , 14 ( Supplementary Fig. 1 ). Functional testing of acellular kidney scaffolds by perfusion of the vasculature with modified Krebs-Henseleit solution under physiologic perfusion pressure resulted in production of a filtrate that was high in protein, glucose and electrolytes, suggesting hydrostatic filtration across glomerular and tubular basement membranes with loss of macromolecular sieving and active reabsorption. Figure 1: Perfusion decellularization of whole rat kidneys. ( a ) Time-lapse photographs of a cadaveric rat kidney undergoing<|im_end|> <|im_start|>assistant Bioengineered rat kidneys developed by Massachusetts General Hospital (MGH) investigators successfully produced urine both in a laboratory apparatus and after being transplanted into living animals. In their report, receiving advance online publication in Nature Medicine, the research team describes building functional replacement kidneys on the structure of donor organs from which living cells had been stripped, an approach previously used to create bioartificial hearts, lungs and livers. "What is unique about this approach is that the native organ's architecture is preserved, so that the resulting graft can be transplanted just like a donor kidney and connected to the recipient's vascular and urinary systems," says Harald Ott, MD, PhD, of the MGH Center for Regenerative Medicine, senior author of the Nature Medicine article. "If this technology can be scaled to human-sized grafts, patients suffering from renal failure who are currently waiting for donor kidneys or who are not transplant candidates could theoretically receive new organs derived from their own cells." Around 18,000 kidney transplants are performed in the U.S. each year, but 100,000 Americans with end-stage kidney disease are still waiting for a donor organ. Even those fortunate enough to receive a transplant face a lifetime of immunosuppressive drugs, which pose many health risks and cannot totally eliminate the incidence of eventual organ rejection. The approach used in this study to engineer donor organs, based on a technology that Ott discovered as a research fellow at the University of Minnesota, involves stripping the living cells from a donor organ with a detergent solution and then repopulating the collagen scaffold that remains with the appropriate cell type – in this instance human endothelial cells to replace the lining of the vascular system and kidney cells from newborn rats. The research team first decellularized rat kidneys to confirm that the organ's complex structures would be preserved. They also showed the technique worked on a larger scale by stripping cells from pig and human kidneys. Making sure the appropriate cells were seeded into the correct portions of the collagen scaffold required delivering vascular cells through the renal artery and kidney cells through the ureter. Precisely adjusting the pressures of the solutions enabled the cells to be dispersed throughout the whole organs, which were then cultured in a bioreactor for up to 12 days. The researchers first tested the repopulated organs in a device that passed blood through its vascular system and drained off any urine, which revealed evidence of limited filtering of blood, molecular activity and urine production. This is a previously decellularized rat kidney after reseeding with endothelial cells, to repopulate the organ's vascular system, and neonatal kidney cells. Credit: Massachusetts General Hospital Center for Regenerative Medicine Bioengineered kidneys transplanted into living rats from which one kidney had been removed began producing urine as soon as the blood supply was restored, with no evidence of bleeding or clot formation. The overall function of the regenerated organs was significantly reduced compared with that of normal, healthy kidneys, something the researchers believe may be attributed to the immaturity of the neonatal cells used to repopulate the scaffolding. "Further refinement of the cell types used for seeding and additional maturation in culture may allow us to achieve a more functional organ," says Ott. "Based on this inital proof of principle, we hope that bioengineered kidneys will someday be able to fully replace kidney function just as donor kidneys do. In an ideal world, such grafts could be produced 'on demand" from a patient's own cells, helping us overcome both the organ shortage and the need for chronic immunosuppression. We're now investigating methods of deriving the necessary cell types from patient-derived cells and refining the cell-seeding and organ culture methods to handle human-sized organs." Ott's team focuses on the regeneration of hearts, lungs, kidneys and grafts made of composite tissues, while other teams – including one from the MGH Center for Engineering in Medicine – are using the decellularization technique to develop replacement livers. Lead author of the Nature Medicine paper is Jeremy Song, MGH Center for Regenerative Medicine; additional co-authors are Jacques Guyette, PhD, Sarah Gilpin, PhD, Gabriel Gonzalez, PhD, and Joseph Vacanti, MD, all of the MGH Center for Regenerative Medicine. The study was supported by National Institute of Health Director's New Innovator Award DP2 OD008749-01. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 79904, 220, 1041, 11, 931, 7931, 304, 279, 3723, 4273, 5131, 2597, 39042, 98702, 11, 323, 220, 3443, 11, 931, 7931, 3974, 449, 842, 51256, 39042, 8624, 23537, 17728, 90169, 4548, 13, 578, 9886, 315, 264, 43929, 481, 69413, 311, 31859, 8454, 39042, 734, 1053, 2686, 35558, 2942, 39259, 323, 279, 93144, 19025, 5938, 449, 33119, 437, 455, 4099, 13, 15483, 264, 17332, 8680, 12616, 69413, 2011, 617, 279, 39042, 596, 18112, 323, 734, 323, 11810, 22535, 7713, 11, 76038, 11, 87067, 11, 44225, 323, 58592, 315, 40335, 13, 1226, 1654, 54230, 1534, 11494, 11, 4247, 66, 483, 323, 3823, 81960, 555, 91234, 22535, 7713, 11, 78504, 1645, 54230, 57250, 18938, 449, 64603, 11, 83619, 323, 1812, 620, 661, 18112, 11, 264, 26984, 1887, 323, 53560, 5153, 13, 2057, 80551, 16003, 20438, 11, 584, 90916, 11494, 39042, 57250, 18938, 449, 64779, 59544, 323, 93329, 59544, 7917, 323, 22535, 2656, 1521, 2849, 7962, 31035, 57327, 304, 264, 4459, 12, 8629, 6160, 461, 5739, 13, 578, 13239, 69413, 82, 9124, 68330, 75643, 40335, 304, 55004, 994, 22535, 2656, 1555, 872, 47701, 64603, 4950, 13, 3277, 1380, 501, 7719, 304, 459, 30299, 354, 25847, 2361, 304, 11494, 11, 279, 69413, 82, 1051, 22535, 2656, 555, 279, 22458, 596, 35855, 323, 9124, 40335, 1555, 279, 53560, 466, 278, 77635, 304, 41294, 662, 4802, 49669, 220, 16, 3610, 6978, 304, 279, 3723, 4273, 3974, 449, 842, 51256, 63915, 8624, 320, 1600, 37790, 705, 449, 927, 220, 1041, 11, 931, 502, 85488, 1475, 1060, 220, 16, 662, 10541, 17728, 90169, 4548, 706, 7319, 279, 20237, 315, 6978, 449, 469, 14899, 35, 11, 98702, 8625, 279, 1193, 2561, 2917, 1413, 6514, 13, 10180, 220, 972, 11, 931, 39042, 1380, 64805, 527, 10887, 824, 1060, 304, 279, 3723, 4273, 220, 16, 1174, 3686, 13489, 220, 1041, 11, 931, 9053, 5131, 2597, 264, 35558, 39042, 220, 17, 662, 800, 3326, 519, 35558, 2942, 5219, 617, 7319, 8748, 3115, 311, 927, 220, 18, 1667, 323, 3868, 1638, 29528, 311, 220, 20, 4235, 605, 14697, 18185, 31003, 304, 63915, 43929, 33119, 2508, 220, 18, 1174, 220, 508, 4, 315, 34876, 690, 3217, 459, 9417, 315, 30883, 38001, 2949, 220, 20, 1667, 315, 98702, 11, 323, 13489, 220, 1272, 4, 315, 34876, 690, 2815, 477, 9229, 69413, 734, 2949, 220, 605, 1667, 1306, 98702, 13, 35386, 315, 264, 17332, 8680, 12616, 39042, 1436, 63234, 31818, 1521, 5435, 555, 8405, 459, 3154, 1640, 788, 69413, 389, 7631, 13, 33924, 1073, 37704, 367, 323, 17728, 90169, 4548, 1005, 459, 1645, 54230, 5347, 13154, 2727, 481, 39654, 311, 28779, 279, 10068, 39042, 596, 5865, 13, 26778, 13865, 617, 1027, 1903, 311, 17332, 8680, 261, 31528, 15286, 1299, 14726, 311, 4726, 22822, 17728, 1073, 37704, 367, 449, 2849, 43918, 5865, 220, 19, 1174, 220, 20, 662, 3277, 17728, 1073, 37704, 367, 7766, 617, 1027, 11093, 449, 17332, 8680, 12616, 63915, 15286, 2482, 11, 279, 13239, 17332, 472, 16895, 39042, 12860, 63915, 734, 304, 53560, 21914, 12875, 220, 21, 323, 28191, 13241, 63915, 734, 304, 6978, 449, 30883, 63915, 8060, 220, 22, 1174, 220, 23, 662, 763, 459, 10778, 5603, 11, 39042, 9036, 541, 689, 617, 1027, 6982, 311, 2274, 1139, 16003, 36853, 304, 41294, 323, 33482, 2324, 994, 1380, 501, 7719, 1139, 459, 24453, 2265, 32510, 220, 24, 662, 41477, 311, 1304, 63915, 35915, 380, 7766, 810, 23665, 220, 605, 477, 1524, 46460, 481, 220, 806, 617, 8813, 279, 6566, 315, 864, 91899, 16865, 323, 3412, 28040, 11471, 369, 18899, 279, 4367, 315, 2324, 315, 6978, 304, 842, 51256, 63915, 8060, 13, 9648, 1640, 788, 72735, 42929, 20438, 8066, 505, 6160, 12255, 38179, 6303, 323, 8893, 72286, 7917, 706, 1027, 1511, 70432, 369, 62564, 79885, 220, 717, 662, 362, 1401, 3094, 9017, 264, 7373, 46460, 481, 11, 15690, 69413, 374, 279, 4500, 315, 264, 6160, 12255, 38179, 85552, 430, 73633, 2849, 665, 33050, 728, 479, 323, 734, 323, 6276, 2539, 22458, 18052, 1555, 6680, 22535, 7713, 13, 1952, 279, 8197, 315, 1057, 3766, 3217, 449, 4459, 12, 8629, 4851, 220, 1032, 323, 21271, 220, 975, 11741, 65441, 6303, 320, 7650, 44, 8, 57250, 18938, 11, 584, 22601, 83979, 430, 279, 10068, 39042, 80700, 1436, 3493, 1778, 264, 85552, 369, 17876, 2849, 95515, 13, 763, 3766, 7978, 11, 4130, 70, 812, 1051, 1511, 311, 4148, 7917, 505, 10068, 39042, 80700, 1418, 47995, 279, 84710, 5776, 950, 6012, 323, 6303, 13128, 17910, 304, 20438, 35354, 220, 868, 323, 4459, 36853, 220, 845, 1174, 220, 1114, 1174, 220, 972, 1174, 220, 777, 662, 1226, 9093, 1654, 54230, 1534, 81960, 1701, 91234, 22535, 7713, 311, 1893, 4459, 12, 8629, 57250, 18938, 449, 35539, 323, 22535, 23620, 64603, 11, 2840, 26429, 1299, 323, 15286, 1299, 87352, 13, 1226, 2109, 454, 7913, 279, 1654, 54230, 1534, 39042, 57250, 18938, 449, 93329, 59544, 323, 64779, 59544, 7917, 13, 763, 55004, 39538, 318, 5411, 7829, 1701, 80935, 22535, 7713, 6197, 311, 279, 18488, 315, 16003, 63915, 69413, 82, 13, 2057, 1296, 304, 41294, 3552, 18052, 323, 734, 11, 584, 1380, 501, 7719, 17332, 8680, 12616, 81960, 304, 459, 30299, 354, 25847, 2361, 323, 27470, 40335, 5788, 13, 18591, 3700, 55665, 1654, 54230, 2065, 315, 19973, 7403, 292, 81960, 1226, 1654, 54230, 1534, 19973, 7403, 292, 11494, 81960, 1701, 63915, 65415, 22535, 7713, 449, 220, 16, 4, 39695, 294, 536, 66, 4010, 89418, 320, 5608, 50, 8, 520, 264, 6926, 7410, 315, 220, 1272, 9653, 473, 70, 320, 23966, 13, 220, 16, 64, 7609, 67005, 2508, 315, 279, 1645, 54230, 81960, 8710, 46643, 315, 20438, 18112, 323, 279, 4686, 17065, 315, 97192, 323, 35693, 6956, 320, 23966, 13, 220, 16, 65, 7609, 3700, 55665, 1654, 54230, 2065, 34683, 279, 6070, 323, 18528, 315, 279, 63915, 80700, 11, 902, 374, 26154, 304, 76038, 320, 76146, 1299, 31741, 39654, 705, 87067, 323, 312, 3518, 66181, 320, 83, 392, 1299, 31741, 39654, 570, 1666, 706, 1027, 3970, 449, 1023, 39881, 220, 1032, 1174, 220, 975, 1174, 279, 80935, 36573, 24722, 4009, 14958, 34683, 304, 1645, 54230, 83619, 323, 1812, 620, 661, 39040, 331, 1631, 64, 13, 67335, 2319, 26407, 32056, 88896, 11007, 279, 9546, 315, 1401, 80700, 6956, 1778, 439, 79533, 258, 323, 71313, 17244, 304, 264, 4571, 72, 39227, 8141, 11, 369, 3187, 11, 304, 279, 1645, 54230, 2840, 26429, 1299, 31741, 39654, 320, 23966, 13, 220, 16, 66, 12260, 7609, 578, 8162, 81519, 315, 279, 41253, 7913, 2840, 26429, 1299, 31741, 39654, 449, 279, 2107, 35605, 323, 11083, 526, 532, 6303, 33459, 505, 279, 2960, 31660, 677, 1299, 55972, 14958, 35539, 13, 362, 5997, 1299, 2840, 26429, 24520, 1051, 4726, 38632, 291, 555, 264, 2814, 321, 1155, 291, 45453, 773, 660, 323, 19815, 85696, 596, 48739, 31741, 39654, 320, 23966, 13, 220, 16, 68, 17514, 7609, 40640, 1299, 31741, 79348, 14958, 34683, 11, 449, 18653, 349, 3721, 351, 12922, 33459, 1139, 279, 22267, 2931, 15286, 1299, 326, 28999, 13, 96712, 11, 409, 290, 1534, 3090, 323, 85283, 263, 1630, 12, 1041, 11293, 279, 2860, 15922, 2262, 824, 39042, 311, 2753, 1109, 220, 605, 4, 320, 23966, 13, 220, 16, 70, 7609, 4740, 28786, 449, 60145, 11, 96712, 574, 2073, 13478, 481, 304, 279, 1645, 54230, 39042, 57250, 18938, 13, 62261, 81, 811, 315, 2860, 71313, 323, 37807, 9594, 8778, 540, 398, 66, 598, 304, 279, 80700, 1051, 34683, 520, 5990, 539, 12207, 2204, 505, 1884, 304, 19973, 7403, 292, 39042, 20438, 320, 23966, 13, 220, 16, 71, 7609, 2057, 7838, 279, 94840, 315, 279, 22535, 7713, 1654, 54230, 2065, 11766, 311, 81960, 315, 3544, 10099, 323, 12966, 11, 584, 7946, 1654, 54230, 1534, 4247, 66, 483, 323, 3823, 81960, 1701, 264, 4528, 22535, 7713, 11766, 320, 23966, 13, 220, 17, 64, 4235, 67, 7609, 1226, 11007, 46643, 315, 22535, 23620, 12006, 3235, 264, 70994, 64603, 4950, 555, 54631, 22535, 7713, 304, 264, 11827, 4528, 311, 430, 304, 1057, 3766, 21896, 449, 22535, 7713, 315, 1654, 54230, 1534, 23492, 323, 45274, 220, 1032, 1174, 220, 975, 320, 99371, 23966, 13, 220, 16, 7609, 55550, 7649, 315, 1645, 54230, 39042, 57250, 18938, 555, 22535, 7713, 315, 279, 44496, 3395, 1598, 449, 11041, 30718, 1302, 11529, 1137, 273, 275, 6425, 1234, 4571, 72, 39227, 22535, 7713, 7410, 19543, 304, 5788, 315, 264, 51791, 349, 430, 574, 1579, 304, 13128, 11, 34323, 323, 73396, 2392, 11, 23377, 17055, 2020, 76038, 4028, 2840, 26429, 1299, 323, 15286, 1299, 31741, 79348, 449, 4814, 315, 9155, 442, 43943, 10112, 4504, 323, 4642, 312, 3518, 66181, 13, 19575, 220, 16, 25, 3700, 55665, 1654, 54230, 2065, 315, 4459, 11494, 81960, 13, 320, 264, 883, 4212, 2922, 7629, 25232, 315, 264, 19973, 7403, 292, 11494, 39042, 47397, 128257, 198, 128256, 78191, 198, 60360, 8680, 12616, 11494, 81960, 8040, 555, 22108, 3331, 15429, 320, 33039, 39, 8, 26453, 7946, 9124, 40335, 2225, 304, 264, 27692, 41705, 323, 1306, 1694, 1380, 501, 7719, 1139, 5496, 10099, 13, 763, 872, 1934, 11, 12588, 12178, 2930, 17009, 304, 22037, 19152, 11, 279, 3495, 2128, 16964, 4857, 16003, 14039, 81960, 389, 279, 6070, 315, 35558, 36853, 505, 902, 5496, 7917, 1047, 1027, 37779, 11, 459, 5603, 8767, 1511, 311, 1893, 17332, 472, 16895, 23492, 11, 45274, 323, 326, 1986, 13, 330, 3923, 374, 5016, 922, 420, 5603, 374, 430, 279, 10068, 2942, 596, 18112, 374, 34683, 11, 779, 430, 279, 13239, 69413, 649, 387, 1380, 501, 7719, 1120, 1093, 264, 35558, 39042, 323, 8599, 311, 279, 22458, 596, 64603, 323, 72735, 6067, 1359, 2795, 5340, 4852, 24881, 11, 14306, 11, 30661, 11, 315, 279, 386, 45776, 5955, 369, 3263, 75989, 19152, 11, 10195, 3229, 315, 279, 22037, 19152, 4652, 13, 330, 2746, 420, 5557, 649, 387, 31790, 311, 3823, 28935, 69413, 82, 11, 6978, 16066, 505, 63915, 8060, 889, 527, 5131, 8748, 369, 35558, 81960, 477, 889, 527, 539, 43929, 11426, 1436, 63234, 5371, 502, 36853, 14592, 505, 872, 1866, 7917, 1210, 33916, 220, 972, 11, 931, 39042, 1380, 64805, 527, 10887, 304, 279, 549, 815, 13, 1855, 1060, 11, 719, 220, 1041, 11, 931, 9053, 449, 842, 51256, 39042, 8624, 527, 2103, 8748, 369, 264, 35558, 2942, 13, 7570, 1884, 40510, 3403, 311, 5371, 264, 43929, 3663, 264, 19569, 315, 33119, 437, 455, 69563, 11217, 11, 902, 17477, 1690, 2890, 15635, 323, 4250, 12756, 22472, 279, 39775, 315, 42835, 2942, 38001, 13, 578, 5603, 1511, 304, 420, 4007, 311, 24490, 35558, 36853, 11, 3196, 389, 264, 5557, 430, 24881, 11352, 439, 264, 3495, 12637, 520, 279, 3907, 315, 19461, 11, 18065, 67770, 279, 5496, 7917, 505, 264, 35558, 2942, 449, 264, 91234, 6425, 323, 1243, 2109, 454, 15853, 279, 71313, 85552, 430, 8625, 449, 279, 8475, 2849, 955, 1389, 304, 420, 2937, 3823, 93329, 59544, 7917, 311, 8454, 279, 36471, 315, 279, 64603, 1887, 323, 39042, 7917, 505, 46397, 32510, 13, 578, 3495, 2128, 1176, 1654, 54230, 1534, 11494, 81960, 311, 7838, 430, 279, 2942, 596, 6485, 14726, 1053, 387, 34683, 13, 2435, 1101, 8710, 279, 15105, 6575, 389, 264, 8294, 5569, 555, 67770, 7917, 505, 24623, 323, 3823, 81960, 13, 25274, 2771, 279, 8475, 7917, 1051, 90916, 1139, 279, 4495, 19885, 315, 279, 71313, 85552, 2631, 24944, 64603, 7917, 1555, 279, 63915, 65415, 323, 39042, 7917, 1555, 279, 53560, 466, 13, 42770, 285, 989, 43468, 279, 40850, 315, 279, 10105, 9147, 279, 7917, 311, 387, 77810, 6957, 279, 4459, 36853, 11, 902, 1051, 1243, 89948, 304, 264, 6160, 461, 5739, 369, 709, 311, 220, 717, 2919, 13, 578, 12074, 1176, 12793, 279, 2109, 454, 7913, 36853, 304, 264, 3756, 430, 5946, 6680, 1555, 1202, 64603, 1887, 323, 61508, 1022, 904, 40335, 11, 902, 10675, 6029, 315, 7347, 30770, 315, 6680, 11, 31206, 5820, 323, 40335, 5788, 13, 1115, 374, 264, 8767, 1654, 54230, 1534, 11494, 39042, 1306, 312, 325, 16490, 449, 93329, 59544, 7917, 11, 311, 2109, 454, 6468, 279, 2942, 596, 64603, 1887, 11, 323, 47752, 4306, 39042, 7917, 13, 16666, 25, 22108, 3331, 15429, 5955, 369, 3263, 75989, 19152, 24432, 8680, 12616, 81960, 1380, 501, 7719, 1139, 5496, 32510, 505, 902, 832, 39042, 1047, 1027, 7108, 6137, 17843, 40335, 439, 5246, 439, 279, 6680, 8312, 574, 28101, 11, 449, 912, 6029, 315, 35763, 477, 94263, 18488, 13, 578, 8244, 734, 315, 279, 71453, 36853, 574, 12207, 11293, 7863, 449, 430, 315, 4725, 11, 9498, 81960, 11, 2555, 279, 12074, 4510, 1253, 387, 30706, 311, 279, 4998, 38954, 315, 279, 47752, 4306, 7917, 1511, 311, 2109, 454, 6468, 279, 57250, 15345, 13, 330, 31428, 74013, 315, 279, 2849, 4595, 1511, 369, 95515, 323, 5217, 5634, 2060, 304, 7829, 1253, 2187, 603, 311, 11322, 264, 810, 16003, 2942, 1359, 2795, 24881, 13, 330, 29815, 389, 420, 304, 2223, 11311, 315, 17966, 11, 584, 3987, 430, 17332, 8680, 12616, 81960, 690, 54108, 387, 3025, 311, 7373, 8454, 39042, 734, 1120, 439, 35558, 81960, 656, 13, 763, 459, 10728, 1917, 11, 1778, 69413, 82, 1436, 387, 9124, 364, 263, 7631, 1, 505, 264, 8893, 596, 1866, 7917, 11, 10695, 603, 23075, 2225, 279, 2942, 39259, 323, 279, 1205, 369, 21249, 33119, 437, 455, 4099, 13, 1226, 2351, 1457, 24834, 5528, 315, 49189, 279, 5995, 2849, 4595, 505, 8893, 72286, 7917, 323, 74285, 279, 2849, 7962, 16490, 323, 2942, 7829, 5528, 311, 3790, 3823, 28935, 36853, 1210, 24881, 596, 2128, 24400, 389, 279, 60517, 315, 23492, 11, 45274, 11, 81960, 323, 69413, 82, 1903, 315, 28814, 39881, 11, 1418, 1023, 7411, 1389, 2737, 832, 505, 279, 386, 45776, 5955, 369, 17005, 304, 19152, 1389, 527, 1701, 279, 1654, 54230, 2065, 15105, 311, 2274, 14039, 326, 1986, 13, 30982, 3229, 315, 279, 22037, 19152, 5684, 374, 28217, 19508, 11, 386, 45776, 5955, 369, 3263, 75989, 19152, 26, 5217, 1080, 34603, 1105, 527, 64850, 26340, 6672, 11, 30661, 11, 21077, 21456, 13576, 11, 30661, 11, 39843, 52186, 11, 30661, 11, 323, 15466, 31626, 15719, 11, 14306, 11, 682, 315, 279, 386, 45776, 5955, 369, 3263, 75989, 19152, 13, 578, 4007, 574, 7396, 555, 5165, 10181, 315, 6401, 10783, 596, 1561, 55947, 859, 17768, 32857, 17, 53832, 11436, 25541, 12, 1721, 13, 220, 128257, 198 ]

2,345

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Minimizing the spread of viruses in the environment is the first defence line when fighting outbreaks and pandemics, but the current COVID-19 pandemic demonstrates how difficult this is on a global scale, particularly in a sustainable and environmentally friendly way. Here we introduce and develop a sustainable and biodegradable antiviral filtration membrane composed of amyloid nanofibrils made from food-grade milk proteins and iron oxyhydroxide nanoparticles synthesized in situ from iron salts by simple pH tuning. Thus, all the membrane components are made of environmentally friendly, non-toxic and widely available materials. The membrane has outstanding efficacy against a broad range of viruses, which include enveloped, non-enveloped, airborne and waterborne viruses, such as SARS-CoV-2, H1N1 (the influenza A virus strain responsible for the swine flu pandemic in 2009) and enterovirus 71 (a non-enveloped virus resistant to harsh conditions, such as highly acidic pH), which highlights a possible role in fighting the current and future viral outbreaks and pandemics. Main The current ongoing COVID-19 pandemic illustrates the importance of valid therapeutic tools 1 , but also the notable lack of technologies capable of fighting the spread of viruses in the environment. Many viruses diffuse and transmit in the environment in water, some in their bulk form (waterborne viruses) 2 , 3 , 4 and others in small droplets suspended in the air (airborne viruses) 5 , 6 , 7 , 8 , 9 . A key defence strategy against infectious diseases is always the prevention of pathogen transmission from an infected person to an uninfected one. This is achieved by using masks, gloves, physical barriers and disinfection, which introduces other challenges on a global scale, such as achieving the goal in a fully sustainable and environmentally friendly way 10 , 11 , 12 . In particular, the COVID-19 pandemic revealed the paradox that, although both technological and scientific knowledge are available to develop a vaccine within the record time of less than a year 13 , 14 , there is still a lack of preparedness to fight the rapid spread of new viruses until such vaccines are developed and a substantial portion of the population is vaccinated 15 . Without the appropriate readiness, viruses spread widely and rapidly and, eventually, new virus strains emerge via mutations 16 , 17 , which could potentially confer resistance to vaccines that target the original strain or increase the virulence of the virus, and possibly lead to an endless vicious cycle. Viruses can spread through many different routes, but mostly through fomites 18 , small water droplets 5 , 6 , 7 , 8 , 9 and bulk water bodies (which include wastewater) 2 , 3 , 4 . Proper hand hygiene serves as a very effective practice against the spread of infections through fomites 19 . In all the other cases, however, virus inactivation must be tackled in the hosting fluid, and the overarching strategy is then to target the virus in its surrounding aqueous environment, may this be in the form of microscopic suspended water droplets or bulk waters. For airborne viruses, suitable face masks, although effective, pose the risk of further dissemination of the viruses when improperly handled 20 and/or disposed 21 , 22 . Additionally, the generated plastic waste eventually emerges as a parallel environmental problem, especially in times of pandemics 10 , 11 , 12 . For waterborne viruses, and despite decades-long technological developments, contaminated drinking water is still responsible for 500,000 annual deaths, of which more than half occur in children under five years of age 23 . Non-enveloped enteric viruses, such as enteroviruses, adenoviruses and rotaviruses, can cause gastrointestinal infections with diseases such as diarrhoea and dysentery. It is estimated that ~40% of often-fatal childhood diarrhoea in developing countries is connected to viral agents 24 . Non-enveloped viruses can persist in water bodies for long periods of time 25 and can resist even some of the harshest treatments 26 , 27 . This challenge is not only exclusive to unfavoured communities, but extends also to countries with state-of-the-art water and wastewater treatment facilities 2 . Furthermore, even enveloped viruses, such as influenza viruses and coronaviruses, which were often regarded as unstable in water environments, have now been shown to remain highly infective for long times in bulk water bodies 28 , 29 : SARS-CoV-2, for example, can retain its infectivity for longer than seven days in tap water and wastewater at room temperature 30 . Therefore, the development of efficient barriers against the spread of viruses via diffusing environmental fluids becomes crucial if global contamination is to be prevented. In spite of decades of scientific and technological development, no existing technology can universally eliminate viruses from water, unless it is extremely energy intensive (for example, reverse osmosis) 31 or starts to pose the risk of toxicity towards humans and the environment (for example, silver-based technologies) 32 , 33 . All these limitations render the existing technologies obsolete facing global challenges such as pandemics. To address such a challenge, we developed an antiviral membrane trap composed of amyloid nanofibrils obtained from a food-grade milk protein, β-lactoglobulin (BLG), modified in situ with iron oxyhydroxide nanoparticles (NPs) (Fig. 1a ). The conversion of BLG monomers into a network of amyloid fibrils (AFs) is a straightforward process achieved by simply lowering the pH to 2.0 with simultaneous heating up to 90 °C; afterwards, the iron oxyhydroxide NPs are precipitated directly on the formed network of AFs by raising the pH in the presence of FeCl 3 ·6H 2 O. Figure 1b shows a schematic of the process; the detailed chemical analysis and composition of the iron NPs as studied by X-ray photoelectron spectroscopy (XPS) reveals the presence of both iron( ii) and iron( iii) oxide and iron chloride species that coexist with the majority of iron oxyhydroxide NPs (Supplementary Fig. 1 ). By depositing the produced material on a porous solid support, we obtained a filtration membrane composed of an intricate network of BLG AFs decorated by Fe oxyhydroxide NPs a few nanometres", "role": "user" }, { "content": "Viruses can spread not only via droplets or aerosols like the new coronavirus, but in water, too. In fact, some potentially dangerous pathogens of gastrointestinal diseases are water-borne viruses. To date, such viruses have been removed from water using nanofiltration or reverse osmosis, but at high cost and severe impact on the environment. For example, nanofilters for viruses are made of petroleum-based raw materials, while reverse osmosis requires a relatively large amount of energy. Environmentally friendly membrane developed Now an international team of researchers led by Raffaele Mezzenga, Professor of Food & Soft Materials at ETH Zurich, has developed a new water filter membrane that is both highly effective and environmentally friendly. To manufacture it, the researchers used natural raw materials. The filter membrane works on the same principle that Mezzenga and his colleagues developed for removing heavy or precious metals from water. They create the membrane using denatured whey proteins that assemble into minute filaments called amyloid fibrils. In this instance, the researchers have combined this fibril scaffold with nanoparticles of iron hydroxide (Fe-O-HO). Manufacturing the membrane is relatively simple. To produce the fibrils, whey proteins derived from milk processing are added to acid and heated to 90 degrees Celsius. This causes the proteins to extend and attach to each other, forming fibrils. The nanoparticles can be produced in the same reaction vessel as the fibrils: the researchers raise the pH and add iron salt, causing the mixture to disintegrate into iron hydroxide nanoparticles, which attach to the amyloid fibrils. For this application, Mezzenga and his colleagues used cellulose to support the membrane. This combination of amyloid fibrils and iron hydroxide nanoparticles makes the membrane a highly effective and efficient trap for various viruses present in water. The positively charged iron oxide electrostatically attracts the negatively charged viruses and inactivates them. Amyloid fibrils alone wouldn't be able to do this because, like the viral particles, they are also negatively charged at neutral pH. However, the fibrils are the ideal matrix for the iron oxide nanoparticles. Various viruses eliminated highly efficiently The membrane eliminates a wide range of water-borne viruses, including nonenveloped adenoviruses, retroviruses and enteroviruses. This third group can cause dangerous gastrointestinal infections, which kill around half a million people—often young children in developing and emerging countries—every year. Enteroviruses are extremely tough and acid-resistant and remain in the water for a very long time, so the filter membrane should be particularly attractive to poorer countries as a way to help prevent such infections. Moreover, the membrane also eliminates H1N1 flu viruses and even the new SARS-CoV-2 virus from the water with great efficiency. In filtered samples, the concentration of the two viruses was below the detection limit, which is equivalent to almost complete elimination of these pathogens. \"We are aware that the new coronavirus is predominantly transmitted via droplets and aerosols, but in fact, even on this scale, the virus requires being surrounded by water. The fact that we can remove it very efficiently from water impressively underlines the broad applicability of our membrane,\" says Mezzenga. While the membrane is primarily designed for use in wastewater treatment plants or for drinking water treatment, it could also be used in air filtration systems or even in masks. Since it consists exclusively of ecologically sound materials, it could simply be composted after use—and its production requires minimum energy. These traits give it an excellent environmental footprint, as the researchers also point out in their study. Because the filtration is passive, it requires no additional energy, which makes its operation carbon neutral and of possible use in any social context, from urban to rural communities. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Minimizing the spread of viruses in the environment is the first defence line when fighting outbreaks and pandemics, but the current COVID-19 pandemic demonstrates how difficult this is on a global scale, particularly in a sustainable and environmentally friendly way. Here we introduce and develop a sustainable and biodegradable antiviral filtration membrane composed of amyloid nanofibrils made from food-grade milk proteins and iron oxyhydroxide nanoparticles synthesized in situ from iron salts by simple pH tuning. Thus, all the membrane components are made of environmentally friendly, non-toxic and widely available materials. The membrane has outstanding efficacy against a broad range of viruses, which include enveloped, non-enveloped, airborne and waterborne viruses, such as SARS-CoV-2, H1N1 (the influenza A virus strain responsible for the swine flu pandemic in 2009) and enterovirus 71 (a non-enveloped virus resistant to harsh conditions, such as highly acidic pH), which highlights a possible role in fighting the current and future viral outbreaks and pandemics. Main The current ongoing COVID-19 pandemic illustrates the importance of valid therapeutic tools 1 , but also the notable lack of technologies capable of fighting the spread of viruses in the environment. Many viruses diffuse and transmit in the environment in water, some in their bulk form (waterborne viruses) 2 , 3 , 4 and others in small droplets suspended in the air (airborne viruses) 5 , 6 , 7 , 8 , 9 . A key defence strategy against infectious diseases is always the prevention of pathogen transmission from an infected person to an uninfected one. This is achieved by using masks, gloves, physical barriers and disinfection, which introduces other challenges on a global scale, such as achieving the goal in a fully sustainable and environmentally friendly way 10 , 11 , 12 . In particular, the COVID-19 pandemic revealed the paradox that, although both technological and scientific knowledge are available to develop a vaccine within the record time of less than a year 13 , 14 , there is still a lack of preparedness to fight the rapid spread of new viruses until such vaccines are developed and a substantial portion of the population is vaccinated 15 . Without the appropriate readiness, viruses spread widely and rapidly and, eventually, new virus strains emerge via mutations 16 , 17 , which could potentially confer resistance to vaccines that target the original strain or increase the virulence of the virus, and possibly lead to an endless vicious cycle. Viruses can spread through many different routes, but mostly through fomites 18 , small water droplets 5 , 6 , 7 , 8 , 9 and bulk water bodies (which include wastewater) 2 , 3 , 4 . Proper hand hygiene serves as a very effective practice against the spread of infections through fomites 19 . In all the other cases, however, virus inactivation must be tackled in the hosting fluid, and the overarching strategy is then to target the virus in its surrounding aqueous environment, may this be in the form of microscopic suspended water droplets or bulk waters. For airborne viruses, suitable face masks, although effective, pose the risk of further dissemination of the viruses when improperly handled 20 and/or disposed 21 , 22 . Additionally, the generated plastic waste eventually emerges as a parallel environmental problem, especially in times of pandemics 10 , 11 , 12 . For waterborne viruses, and despite decades-long technological developments, contaminated drinking water is still responsible for 500,000 annual deaths, of which more than half occur in children under five years of age 23 . Non-enveloped enteric viruses, such as enteroviruses, adenoviruses and rotaviruses, can cause gastrointestinal infections with diseases such as diarrhoea and dysentery. It is estimated that ~40% of often-fatal childhood diarrhoea in developing countries is connected to viral agents 24 . Non-enveloped viruses can persist in water bodies for long periods of time 25 and can resist even some of the harshest treatments 26 , 27 . This challenge is not only exclusive to unfavoured communities, but extends also to countries with state-of-the-art water and wastewater treatment facilities 2 . Furthermore, even enveloped viruses, such as influenza viruses and coronaviruses, which were often regarded as unstable in water environments, have now been shown to remain highly infective for long times in bulk water bodies 28 , 29 : SARS-CoV-2, for example, can retain its infectivity for longer than seven days in tap water and wastewater at room temperature 30 . Therefore, the development of efficient barriers against the spread of viruses via diffusing environmental fluids becomes crucial if global contamination is to be prevented. In spite of decades of scientific and technological development, no existing technology can universally eliminate viruses from water, unless it is extremely energy intensive (for example, reverse osmosis) 31 or starts to pose the risk of toxicity towards humans and the environment (for example, silver-based technologies) 32 , 33 . All these limitations render the existing technologies obsolete facing global challenges such as pandemics. To address such a challenge, we developed an antiviral membrane trap composed of amyloid nanofibrils obtained from a food-grade milk protein, β-lactoglobulin (BLG), modified in situ with iron oxyhydroxide nanoparticles (NPs) (Fig. 1a ). The conversion of BLG monomers into a network of amyloid fibrils (AFs) is a straightforward process achieved by simply lowering the pH to 2.0 with simultaneous heating up to 90 °C; afterwards, the iron oxyhydroxide NPs are precipitated directly on the formed network of AFs by raising the pH in the presence of FeCl 3 ·6H 2 O. Figure 1b shows a schematic of the process; the detailed chemical analysis and composition of the iron NPs as studied by X-ray photoelectron spectroscopy (XPS) reveals the presence of both iron( ii) and iron( iii) oxide and iron chloride species that coexist with the majority of iron oxyhydroxide NPs (Supplementary Fig. 1 ). By depositing the produced material on a porous solid support, we obtained a filtration membrane composed of an intricate network of BLG AFs decorated by Fe oxyhydroxide NPs a few nanometres<|im_end|> <|im_start|>assistant Viruses can spread not only via droplets or aerosols like the new coronavirus, but in water, too. In fact, some potentially dangerous pathogens of gastrointestinal diseases are water-borne viruses. To date, such viruses have been removed from water using nanofiltration or reverse osmosis, but at high cost and severe impact on the environment. For example, nanofilters for viruses are made of petroleum-based raw materials, while reverse osmosis requires a relatively large amount of energy. Environmentally friendly membrane developed Now an international team of researchers led by Raffaele Mezzenga, Professor of Food & Soft Materials at ETH Zurich, has developed a new water filter membrane that is both highly effective and environmentally friendly. To manufacture it, the researchers used natural raw materials. The filter membrane works on the same principle that Mezzenga and his colleagues developed for removing heavy or precious metals from water. They create the membrane using denatured whey proteins that assemble into minute filaments called amyloid fibrils. In this instance, the researchers have combined this fibril scaffold with nanoparticles of iron hydroxide (Fe-O-HO). Manufacturing the membrane is relatively simple. To produce the fibrils, whey proteins derived from milk processing are added to acid and heated to 90 degrees Celsius. This causes the proteins to extend and attach to each other, forming fibrils. The nanoparticles can be produced in the same reaction vessel as the fibrils: the researchers raise the pH and add iron salt, causing the mixture to disintegrate into iron hydroxide nanoparticles, which attach to the amyloid fibrils. For this application, Mezzenga and his colleagues used cellulose to support the membrane. This combination of amyloid fibrils and iron hydroxide nanoparticles makes the membrane a highly effective and efficient trap for various viruses present in water. The positively charged iron oxide electrostatically attracts the negatively charged viruses and inactivates them. Amyloid fibrils alone wouldn't be able to do this because, like the viral particles, they are also negatively charged at neutral pH. However, the fibrils are the ideal matrix for the iron oxide nanoparticles. Various viruses eliminated highly efficiently The membrane eliminates a wide range of water-borne viruses, including nonenveloped adenoviruses, retroviruses and enteroviruses. This third group can cause dangerous gastrointestinal infections, which kill around half a million people—often young children in developing and emerging countries—every year. Enteroviruses are extremely tough and acid-resistant and remain in the water for a very long time, so the filter membrane should be particularly attractive to poorer countries as a way to help prevent such infections. Moreover, the membrane also eliminates H1N1 flu viruses and even the new SARS-CoV-2 virus from the water with great efficiency. In filtered samples, the concentration of the two viruses was below the detection limit, which is equivalent to almost complete elimination of these pathogens. "We are aware that the new coronavirus is predominantly transmitted via droplets and aerosols, but in fact, even on this scale, the virus requires being surrounded by water. The fact that we can remove it very efficiently from water impressively underlines the broad applicability of our membrane," says Mezzenga. While the membrane is primarily designed for use in wastewater treatment plants or for drinking water treatment, it could also be used in air filtration systems or even in masks. Since it consists exclusively of ecologically sound materials, it could simply be composted after use—and its production requires minimum energy. These traits give it an excellent environmental footprint, as the researchers also point out in their study. Because the filtration is passive, it requires no additional energy, which makes its operation carbon neutral and of possible use in any social context, from urban to rural communities. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 3468, 318, 4954, 279, 9041, 315, 42068, 304, 279, 4676, 374, 279, 1176, 23682, 1584, 994, 11039, 77871, 323, 12495, 38305, 11, 719, 279, 1510, 20562, 12, 777, 28522, 32216, 1268, 5107, 420, 374, 389, 264, 3728, 5569, 11, 8104, 304, 264, 22556, 323, 57340, 11919, 1648, 13, 5810, 584, 19678, 323, 2274, 264, 22556, 323, 6160, 536, 78130, 3276, 344, 37478, 76038, 39654, 24306, 315, 64383, 52196, 20622, 1073, 10892, 8839, 1903, 505, 3691, 41327, 14403, 28896, 323, 11245, 99690, 67229, 87, 579, 94753, 92106, 304, 10109, 505, 11245, 78235, 555, 4382, 37143, 42438, 13, 14636, 11, 682, 279, 39654, 6956, 527, 1903, 315, 57340, 11919, 11, 2536, 4791, 14668, 323, 13882, 2561, 7384, 13, 578, 39654, 706, 19310, 41265, 2403, 264, 7353, 2134, 315, 42068, 11, 902, 2997, 54285, 291, 11, 2536, 21430, 1851, 291, 11, 70863, 323, 3090, 32096, 42068, 11, 1778, 439, 328, 17485, 87271, 53, 12, 17, 11, 473, 16, 45, 16, 320, 1820, 62937, 362, 17188, 26800, 8647, 369, 279, 2064, 483, 20236, 28522, 304, 220, 1049, 24, 8, 323, 3810, 869, 17402, 220, 6028, 320, 64, 2536, 21430, 1851, 291, 17188, 31785, 311, 25984, 4787, 11, 1778, 439, 7701, 84903, 37143, 705, 902, 22020, 264, 3284, 3560, 304, 11039, 279, 1510, 323, 3938, 29962, 77871, 323, 12495, 38305, 13, 4802, 578, 1510, 14529, 20562, 12, 777, 28522, 46480, 279, 12939, 315, 2764, 37471, 7526, 220, 16, 1174, 719, 1101, 279, 28289, 6996, 315, 14645, 13171, 315, 11039, 279, 9041, 315, 42068, 304, 279, 4676, 13, 9176, 42068, 55517, 323, 30382, 304, 279, 4676, 304, 3090, 11, 1063, 304, 872, 20155, 1376, 320, 13284, 32096, 42068, 8, 220, 17, 1174, 220, 18, 1174, 220, 19, 323, 3885, 304, 2678, 7118, 90592, 22340, 304, 279, 3805, 320, 1334, 32096, 42068, 8, 220, 20, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 1174, 220, 24, 662, 362, 1401, 23682, 8446, 2403, 50600, 19338, 374, 2744, 279, 27344, 315, 1853, 11968, 18874, 505, 459, 29374, 1732, 311, 459, 653, 13885, 1599, 832, 13, 1115, 374, 17427, 555, 1701, 27227, 11, 36516, 11, 7106, 30740, 323, 64842, 13421, 11, 902, 40019, 1023, 11774, 389, 264, 3728, 5569, 11, 1778, 439, 32145, 279, 5915, 304, 264, 7373, 22556, 323, 57340, 11919, 1648, 220, 605, 1174, 220, 806, 1174, 220, 717, 662, 763, 4040, 11, 279, 20562, 12, 777, 28522, 10675, 279, 52313, 430, 11, 8051, 2225, 30116, 323, 12624, 6677, 527, 2561, 311, 2274, 264, 25474, 2949, 279, 3335, 892, 315, 2753, 1109, 264, 1060, 220, 1032, 1174, 220, 975, 1174, 1070, 374, 2103, 264, 6996, 315, 10235, 2136, 311, 4465, 279, 11295, 9041, 315, 502, 42068, 3156, 1778, 40300, 527, 8040, 323, 264, 12190, 13651, 315, 279, 7187, 374, 70558, 220, 868, 662, 17586, 279, 8475, 62792, 11, 42068, 9041, 13882, 323, 19019, 323, 11, 9778, 11, 502, 17188, 42400, 34044, 4669, 34684, 220, 845, 1174, 220, 1114, 1174, 902, 1436, 13893, 49843, 13957, 311, 40300, 430, 2218, 279, 4113, 26800, 477, 5376, 279, 9043, 59566, 315, 279, 17188, 11, 323, 11000, 3063, 311, 459, 26762, 43510, 11008, 13, 9734, 4881, 649, 9041, 1555, 1690, 2204, 11543, 11, 719, 10213, 1555, 282, 316, 3695, 220, 972, 1174, 2678, 3090, 7118, 90592, 220, 20, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 1174, 220, 24, 323, 20155, 3090, 13162, 320, 8370, 2997, 77681, 8, 220, 17, 1174, 220, 18, 1174, 220, 19, 662, 65658, 1450, 53056, 17482, 439, 264, 1633, 7524, 6725, 2403, 279, 9041, 315, 30020, 1555, 282, 316, 3695, 220, 777, 662, 763, 682, 279, 1023, 5157, 11, 4869, 11, 17188, 304, 23863, 2011, 387, 82457, 304, 279, 20256, 15962, 11, 323, 279, 98536, 8446, 374, 1243, 311, 2218, 279, 17188, 304, 1202, 14932, 66300, 788, 4676, 11, 1253, 420, 387, 304, 279, 1376, 315, 90090, 22340, 3090, 7118, 90592, 477, 20155, 21160, 13, 1789, 70863, 42068, 11, 14791, 3663, 27227, 11, 8051, 7524, 11, 17477, 279, 5326, 315, 4726, 87764, 315, 279, 42068, 994, 75298, 18073, 220, 508, 323, 5255, 26655, 220, 1691, 1174, 220, 1313, 662, 23212, 11, 279, 8066, 12466, 12571, 9778, 59696, 439, 264, 15638, 12434, 3575, 11, 5423, 304, 3115, 315, 12495, 38305, 220, 605, 1174, 220, 806, 1174, 220, 717, 662, 1789, 3090, 32096, 42068, 11, 323, 8994, 11026, 24725, 30116, 26006, 11, 52673, 16558, 3090, 374, 2103, 8647, 369, 220, 2636, 11, 931, 9974, 16779, 11, 315, 902, 810, 1109, 4376, 12446, 304, 2911, 1234, 4330, 1667, 315, 4325, 220, 1419, 662, 11842, 21430, 1851, 291, 3810, 292, 42068, 11, 1778, 439, 3810, 869, 404, 4881, 11, 100213, 869, 404, 4881, 323, 5868, 113765, 4881, 11, 649, 5353, 80311, 30020, 449, 19338, 1778, 439, 58705, 77035, 64, 323, 22709, 306, 727, 13, 1102, 374, 13240, 430, 4056, 1272, 4, 315, 3629, 2269, 4306, 20587, 58705, 77035, 64, 304, 11469, 5961, 374, 8599, 311, 29962, 13307, 220, 1187, 662, 11842, 21430, 1851, 291, 42068, 649, 23135, 304, 3090, 13162, 369, 1317, 18852, 315, 892, 220, 914, 323, 649, 22884, 1524, 1063, 315, 279, 305, 1590, 6536, 22972, 220, 1627, 1174, 220, 1544, 662, 1115, 8815, 374, 539, 1193, 14079, 311, 9662, 402, 21020, 10977, 11, 719, 2289, 1101, 311, 5961, 449, 1614, 8838, 10826, 38921, 3090, 323, 77681, 6514, 13077, 220, 17, 662, 24296, 11, 1524, 54285, 291, 42068, 11, 1778, 439, 62937, 42068, 323, 22760, 113765, 4881, 11, 902, 1051, 3629, 27458, 439, 45311, 304, 3090, 22484, 11, 617, 1457, 1027, 6982, 311, 7293, 7701, 34527, 535, 369, 1317, 3115, 304, 20155, 3090, 13162, 220, 1591, 1174, 220, 1682, 551, 328, 17485, 87271, 53, 12, 17, 11, 369, 3187, 11, 649, 14389, 1202, 34527, 1968, 369, 5129, 1109, 8254, 2919, 304, 15596, 3090, 323, 77681, 520, 3130, 9499, 220, 966, 662, 15636, 11, 279, 4500, 315, 11297, 30740, 2403, 279, 9041, 315, 42068, 4669, 3722, 985, 12434, 56406, 9221, 16996, 422, 3728, 47810, 374, 311, 387, 32098, 13, 763, 34781, 315, 11026, 315, 12624, 323, 30116, 4500, 11, 912, 6484, 5557, 649, 61528, 22472, 42068, 505, 3090, 11, 7389, 433, 374, 9193, 4907, 37295, 320, 2000, 3187, 11, 10134, 2709, 8801, 285, 8, 220, 2148, 477, 8638, 311, 17477, 279, 5326, 315, 58011, 7119, 12966, 323, 279, 4676, 320, 2000, 3187, 11, 15310, 6108, 14645, 8, 220, 843, 1174, 220, 1644, 662, 2052, 1521, 9669, 3219, 279, 6484, 14645, 47166, 13176, 3728, 11774, 1778, 439, 12495, 38305, 13, 2057, 2686, 1778, 264, 8815, 11, 584, 8040, 459, 3276, 344, 37478, 39654, 23709, 24306, 315, 64383, 52196, 20622, 1073, 10892, 8839, 12457, 505, 264, 3691, 41327, 14403, 13128, 11, 34318, 2922, 533, 76525, 24292, 320, 9574, 38, 705, 11041, 304, 10109, 449, 11245, 99690, 67229, 87, 579, 94753, 320, 45, 21051, 8, 320, 30035, 13, 220, 16, 64, 7609, 578, 14747, 315, 15195, 38, 1647, 69638, 1139, 264, 4009, 315, 64383, 52196, 95235, 8839, 320, 8440, 82, 8, 374, 264, 31439, 1920, 17427, 555, 5042, 46301, 279, 37143, 311, 220, 17, 13, 15, 449, 58632, 24494, 709, 311, 220, 1954, 37386, 34, 26, 27905, 11, 279, 11245, 99690, 67229, 87, 579, 452, 21051, 527, 36841, 33337, 6089, 389, 279, 14454, 4009, 315, 20479, 82, 555, 19054, 279, 37143, 304, 279, 9546, 315, 3926, 5176, 220, 18, 9787, 21, 39, 220, 17, 507, 13, 19575, 220, 16, 65, 5039, 264, 68144, 315, 279, 1920, 26, 279, 11944, 11742, 6492, 323, 18528, 315, 279, 11245, 452, 21051, 439, 20041, 555, 1630, 30630, 6685, 75603, 66425, 51856, 320, 55, 5119, 8, 21667, 279, 9546, 315, 2225, 11245, 7, 14799, 8, 323, 11245, 7, 63193, 8, 51180, 323, 11245, 82882, 9606, 430, 1080, 29675, 449, 279, 8857, 315, 11245, 99690, 67229, 87, 579, 452, 21051, 320, 10254, 67082, 23966, 13, 220, 16, 7609, 3296, 16946, 287, 279, 9124, 3769, 389, 264, 94761, 6573, 1862, 11, 584, 12457, 264, 76038, 39654, 24306, 315, 459, 57216, 4009, 315, 15195, 38, 20479, 82, 37109, 555, 3926, 99690, 67229, 87, 579, 452, 21051, 264, 2478, 20622, 4512, 417, 128257, 198, 128256, 78191, 198, 50135, 4881, 649, 9041, 539, 1193, 4669, 7118, 90592, 477, 49825, 3145, 1093, 279, 502, 33333, 11, 719, 304, 3090, 11, 2288, 13, 763, 2144, 11, 1063, 13893, 11660, 78284, 315, 80311, 19338, 527, 3090, 1481, 17334, 42068, 13, 2057, 2457, 11, 1778, 42068, 617, 1027, 7108, 505, 3090, 1701, 20622, 1073, 37704, 367, 477, 10134, 2709, 8801, 285, 11, 719, 520, 1579, 2853, 323, 15748, 5536, 389, 279, 4676, 13, 1789, 3187, 11, 20622, 1073, 8782, 369, 42068, 527, 1903, 315, 60063, 6108, 7257, 7384, 11, 1418, 10134, 2709, 8801, 285, 7612, 264, 12309, 3544, 3392, 315, 4907, 13, 11847, 750, 11919, 39654, 8040, 4800, 459, 6625, 2128, 315, 12074, 6197, 555, 432, 2715, 6043, 273, 2206, 10616, 75675, 11, 17054, 315, 12369, 612, 25046, 32009, 520, 38842, 72826, 11, 706, 8040, 264, 502, 3090, 4141, 39654, 430, 374, 2225, 7701, 7524, 323, 57340, 11919, 13, 2057, 30847, 433, 11, 279, 12074, 1511, 5933, 7257, 7384, 13, 578, 4141, 39654, 4375, 389, 279, 1890, 17966, 430, 2206, 10616, 75675, 323, 813, 18105, 8040, 369, 18054, 8987, 477, 27498, 37182, 505, 3090, 13, 2435, 1893, 279, 39654, 1701, 3453, 1598, 67, 15240, 88, 28896, 430, 42840, 1139, 9568, 1488, 24469, 2663, 64383, 52196, 95235, 8839, 13, 763, 420, 2937, 11, 279, 12074, 617, 11093, 420, 95235, 321, 85552, 449, 94753, 315, 11245, 17055, 87, 579, 320, 6251, 24540, 11529, 46, 570, 42177, 279, 39654, 374, 12309, 4382, 13, 2057, 8356, 279, 95235, 8839, 11, 15240, 88, 28896, 14592, 505, 14403, 8863, 527, 3779, 311, 13935, 323, 32813, 311, 220, 1954, 12628, 62447, 13, 1115, 11384, 279, 28896, 311, 13334, 323, 15866, 311, 1855, 1023, 11, 30164, 95235, 8839, 13, 578, 94753, 649, 387, 9124, 304, 279, 1890, 13010, 27274, 439, 279, 95235, 8839, 25, 279, 12074, 4933, 279, 37143, 323, 923, 11245, 12290, 11, 14718, 279, 21655, 311, 834, 396, 58117, 1139, 11245, 17055, 87, 579, 94753, 11, 902, 15866, 311, 279, 64383, 52196, 95235, 8839, 13, 1789, 420, 3851, 11, 2206, 10616, 75675, 323, 813, 18105, 1511, 70002, 974, 311, 1862, 279, 39654, 13, 1115, 10824, 315, 64383, 52196, 95235, 8839, 323, 11245, 17055, 87, 579, 94753, 3727, 279, 39654, 264, 7701, 7524, 323, 11297, 23709, 369, 5370, 42068, 3118, 304, 3090, 13, 578, 40646, 11684, 11245, 51180, 25396, 2020, 750, 61191, 279, 48291, 11684, 42068, 323, 304, 9035, 988, 1124, 13, 29793, 52196, 95235, 8839, 7636, 8434, 956, 387, 3025, 311, 656, 420, 1606, 11, 1093, 279, 29962, 19252, 11, 814, 527, 1101, 48291, 11684, 520, 21277, 37143, 13, 4452, 11, 279, 95235, 8839, 527, 279, 10728, 6303, 369, 279, 11245, 51180, 94753, 13, 40741, 42068, 34373, 7701, 30820, 578, 39654, 60944, 264, 7029, 2134, 315, 3090, 1481, 17334, 42068, 11, 2737, 2536, 268, 1851, 291, 100213, 869, 404, 4881, 11, 17189, 46957, 4881, 323, 3810, 869, 404, 4881, 13, 1115, 4948, 1912, 649, 5353, 11660, 80311, 30020, 11, 902, 5622, 2212, 4376, 264, 3610, 1274, 2345, 61917, 3995, 2911, 304, 11469, 323, 24084, 5961, 2345, 30115, 1060, 13, 11502, 869, 404, 4881, 527, 9193, 11292, 323, 13935, 47056, 323, 7293, 304, 279, 3090, 369, 264, 1633, 1317, 892, 11, 779, 279, 4141, 39654, 1288, 387, 8104, 19411, 311, 66281, 5961, 439, 264, 1648, 311, 1520, 5471, 1778, 30020, 13, 23674, 11, 279, 39654, 1101, 60944, 473, 16, 45, 16, 20236, 42068, 323, 1524, 279, 502, 328, 17485, 87271, 53, 12, 17, 17188, 505, 279, 3090, 449, 2294, 15374, 13, 763, 18797, 10688, 11, 279, 20545, 315, 279, 1403, 42068, 574, 3770, 279, 18468, 4017, 11, 902, 374, 13890, 311, 4661, 4686, 44032, 315, 1521, 78284, 13, 330, 1687, 527, 8010, 430, 279, 502, 33333, 374, 47904, 34699, 4669, 7118, 90592, 323, 49825, 3145, 11, 719, 304, 2144, 11, 1524, 389, 420, 5569, 11, 279, 17188, 7612, 1694, 23712, 555, 3090, 13, 578, 2144, 430, 584, 649, 4148, 433, 1633, 30820, 505, 3090, 10098, 3210, 1234, 8128, 279, 7353, 4666, 2968, 315, 1057, 39654, 1359, 2795, 2206, 10616, 75675, 13, 6104, 279, 39654, 374, 15871, 6319, 369, 1005, 304, 77681, 6514, 11012, 477, 369, 16558, 3090, 6514, 11, 433, 1436, 1101, 387, 1511, 304, 3805, 76038, 6067, 477, 1524, 304, 27227, 13, 8876, 433, 17610, 24121, 315, 12208, 30450, 5222, 7384, 11, 433, 1436, 5042, 387, 57823, 291, 1306, 1005, 17223, 1202, 5788, 7612, 8187, 4907, 13, 4314, 25022, 3041, 433, 459, 9250, 12434, 43972, 11, 439, 279, 12074, 1101, 1486, 704, 304, 872, 4007, 13, 9393, 279, 76038, 374, 28979, 11, 433, 7612, 912, 5217, 4907, 11, 902, 3727, 1202, 5784, 12782, 21277, 323, 315, 3284, 1005, 304, 904, 3674, 2317, 11, 505, 16036, 311, 19624, 10977, 13, 220, 128257, 198 ]

2,134

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract A global priority for the behavioural sciences is to develop cost-effective, scalable interventions that could improve the academic outcomes of adolescents at a population level, but no such interventions have so far been evaluated in a population-generalizable sample. Here we show that a short (less than one hour), online growth mindset intervention—which teaches that intellectual abilities can be developed—improved grades among lower-achieving students and increased overall enrolment to advanced mathematics courses in a nationally representative sample of students in secondary education in the United States. Notably, the study identified school contexts that sustained the effects of the growth mindset intervention: the intervention changed grades when peer norms aligned with the messages of the intervention. Confidence in the conclusions of this study comes from independent data collection and processing, pre-registration of analyses, and corroboration of results by a blinded Bayesian analysis. Main About 20% of students in the United States will not finish high school on time 1 . These students are at a high risk of poverty, poor health and early mortality in the current global economy 2 , 3 , 4 . Indeed, a Lancet commission concluded that improving secondary education outcomes for adolescents “presents the single best investment for health and wellbeing” 5 . The transition to secondary school represents an important period of flexibility in the educational trajectories of adolescents 6 . In the United States, the grades of students tend to decrease during the transition to the ninth grade (age 14–15 years, UK year 10), and often do not recover 7 . When such students underperform in or opt out of rigorous coursework, they are far less likely to leave secondary school prepared for college or university or for advanced courses in college or university 8 , 9 . In this way, early problems in the transition to secondary school can compound over time into large differences in human capital in adulthood. One way to improve academic success across the transition to secondary school is through social–psychological interventions, which change how adolescents think or feel about themselves and their schoolwork and thereby encourage students to take advantage of learning opportunities in school 10 , 11 . The specific intervention evaluated here—a growth mindset of intelligence intervention—addresses the beliefs of adolescents about the nature of intelligence, leading students to see intellectual abilities not as fixed but as capable of growth in response to dedicated effort, trying new strategies and seeking help when appropriate 12 , 13 , 14 , 15 , 16 . This can be especially important in a society that conveys a fixed mindset (a view that intelligence is fixed), which can imply that feeling challenged and having to put in effort means that one is not naturally talented and is unlikely to succeed 12 . The growth mindset intervention communicates a memorable metaphor: that the brain is like a muscle that grows stronger and smarter when it undergoes rigorous learning experiences 14 . Adolescents hear the metaphor in the context of the neuroscience of learning, they reflect on ways to strengthen their brains through schoolwork, and they internalize the message by teaching it to a future first-year ninth grade student who is struggling at the start of the year. The intervention can lead to sustained academic improvement through self-reinforcing cycles of motivation and learning-oriented behaviour. For example, a growth mindset can motivate students to take on more rigorous learning experiences and to persist when encountering difficulties. Their behaviour may then be reinforced by the school context, such as more positive and learning-oriented responses from peers or instructors 10 , 17 . Initial intervention studies with adolescents taught a growth mindset in multi-session (for example, eight classroom sessions 15 ), interactive workshops delivered by highly trained adults; however, these were not readily scalable. Subsequent growth mindset interventions were briefer and self-administered online, although lower effect sizes were, of course, expected. Nonetheless, previous randomized evaluations, including a pre-registered replication, found that online growth mindset interventions improved grades for the targeted group of students in secondary education who previously showed lower achievement 13 , 16 , 18 . These findings are important because previously low-achieving students are the group that shows the steepest decline in grades during the transition to secondary school 19 , and these findings are consistent with theory because a growth mindset should be most beneficial for students confronting challenges 20 . Here we report the results of the National Study of Learning Mindsets, which examined the effects of a short, online growth mindset intervention in a nationally representative sample of high schools in the United States (Fig. 1 ). With this unique dataset we tested the hypotheses that the intervention would improve grades among lower-achieving students and overall uptake of advanced courses in this national sample. Fig. 1: Design of the National Study of Learning Mindsets. Between August and November 2015, 82% of schools delivered the intervention; the remaining 18% delivered the intervention in January or February of 2016. Asterisk indicates that the median number of days between sessions 1 and 2 among schools implementing the intervention in the autumn was 21 days; for spring-implementing schools it was 27 days. The coin-tossing symbol indicates that random assignment was made during session 1. The tick symbol indicates that a comprehensive analysis plan was pre-registered at . The blind-eye symbol indicates that, first, teachers and researchers were kept blinded to students’ random assignment to condition, and, second, the Bayesian, machine-learning robustness tests were conducted by analysts who at the time were blinded to study hypotheses and to the identities of the variables. Full size image A focus on heterogeneity The study was also designed with the purpose of understanding for whom and under what conditions the growth mindset intervention improves grades. That is, it examined potential sources of cross-site treatment effect heterogeneity. One reason why understanding heterogeneity of effects is important is because most interventions that are effective in initial efficacy trials go on to show weaker or no effects when they are scaled", "role": "user" }, { "content": "Boosting academic success does not have to derive from new teachers or curriculum; it can also come from changing students' attitudes about their abilities through a short online intervention, according to the latest findings from the National Study of Learning Mindsets published in Nature on Aug. 7. The experimental study involved more than 12,000 ninth graders in a national, representative sample of 76 public high schools across the United States. It showed that an intervention emphasizing a growth mindset—the belief that intellectual abilities are not fixed but can be developed—can improve key predictors of high school graduation and college success, especially when a school's culture supports the treatment message. \"The research cemented a striking finding from multiple earlier studies: A short intervention can change the unlikely outcome of adolescents' grades many months later,\" said David Yeager, the study's lead author and an associate professor of psychology at The University of Texas at Austin. \"It also showed us something new: Higher-achieving students don't get higher grades after the program, but they are more likely to take harder classes that set them up for long-term success.\" According to U.S. federal government statistics, nearly 20% of students in the U.S. do not finish high school on time. These students are also at an increased risk of poverty, poor health and early mortality. The transition to high school represents an important transition point in adolescents' paths toward high school completion. Building on prior research, researchers found that two 25-minute online sessions, administered at the beginning of high school, can help students develop a growth mindset by reshaping their attitudes about their abilities. Researchers found that both lower- and higher-achieving students benefited academically from the program, even into their sophomore year. On average, lower-achieving students who took the program earned 0.10 higher grade points in core academic subjects such as math, English, science and social studies. Additionally, the intervention reduced the proportion of these students with a D or F average in these courses by more than 5 percentage points. The intervention also increased the likelihood students took Algebra II or higher in 10th grade by 3 percentage points among both higher- and lower-achieving students. \"These effects are substantial when compared to the most successful large-scale, lengthy and rigorously evaluated interventions with adolescents in the educational research literature,\" Yeager said. \"They are particularly notable given the low cost and high fidelity of the online program. But the growth mindset program isn't a magic bullet. Its effectiveness depends a lot on the school context.\" In medium- to low-performing schools with norms that encouraged students to take on more challenging coursework, lower-achieving students who received the intervention improved 0.15 grade points in core courses and 0.17 grade points in STEM courses. \"Motivation and learning don't just happen in a student's head; they depend on the resources and learning opportunities present in the school's environment, including the extent to which challenging coursework is available to students,\" Yeager said. \"A mindset intervention is like planting a seed; it grows to fruition in fertile soil. Now that we have shown this in a national study, it will propel us into a new era of mindset research. That era will focus on both the mindset of the student and the culture and climate of the classroom. We have our eyes set on preparing teachers to support students' beliefs that they can grow and learn.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract A global priority for the behavioural sciences is to develop cost-effective, scalable interventions that could improve the academic outcomes of adolescents at a population level, but no such interventions have so far been evaluated in a population-generalizable sample. Here we show that a short (less than one hour), online growth mindset intervention—which teaches that intellectual abilities can be developed—improved grades among lower-achieving students and increased overall enrolment to advanced mathematics courses in a nationally representative sample of students in secondary education in the United States. Notably, the study identified school contexts that sustained the effects of the growth mindset intervention: the intervention changed grades when peer norms aligned with the messages of the intervention. Confidence in the conclusions of this study comes from independent data collection and processing, pre-registration of analyses, and corroboration of results by a blinded Bayesian analysis. Main About 20% of students in the United States will not finish high school on time 1 . These students are at a high risk of poverty, poor health and early mortality in the current global economy 2 , 3 , 4 . Indeed, a Lancet commission concluded that improving secondary education outcomes for adolescents “presents the single best investment for health and wellbeing” 5 . The transition to secondary school represents an important period of flexibility in the educational trajectories of adolescents 6 . In the United States, the grades of students tend to decrease during the transition to the ninth grade (age 14–15 years, UK year 10), and often do not recover 7 . When such students underperform in or opt out of rigorous coursework, they are far less likely to leave secondary school prepared for college or university or for advanced courses in college or university 8 , 9 . In this way, early problems in the transition to secondary school can compound over time into large differences in human capital in adulthood. One way to improve academic success across the transition to secondary school is through social–psychological interventions, which change how adolescents think or feel about themselves and their schoolwork and thereby encourage students to take advantage of learning opportunities in school 10 , 11 . The specific intervention evaluated here—a growth mindset of intelligence intervention—addresses the beliefs of adolescents about the nature of intelligence, leading students to see intellectual abilities not as fixed but as capable of growth in response to dedicated effort, trying new strategies and seeking help when appropriate 12 , 13 , 14 , 15 , 16 . This can be especially important in a society that conveys a fixed mindset (a view that intelligence is fixed), which can imply that feeling challenged and having to put in effort means that one is not naturally talented and is unlikely to succeed 12 . The growth mindset intervention communicates a memorable metaphor: that the brain is like a muscle that grows stronger and smarter when it undergoes rigorous learning experiences 14 . Adolescents hear the metaphor in the context of the neuroscience of learning, they reflect on ways to strengthen their brains through schoolwork, and they internalize the message by teaching it to a future first-year ninth grade student who is struggling at the start of the year. The intervention can lead to sustained academic improvement through self-reinforcing cycles of motivation and learning-oriented behaviour. For example, a growth mindset can motivate students to take on more rigorous learning experiences and to persist when encountering difficulties. Their behaviour may then be reinforced by the school context, such as more positive and learning-oriented responses from peers or instructors 10 , 17 . Initial intervention studies with adolescents taught a growth mindset in multi-session (for example, eight classroom sessions 15 ), interactive workshops delivered by highly trained adults; however, these were not readily scalable. Subsequent growth mindset interventions were briefer and self-administered online, although lower effect sizes were, of course, expected. Nonetheless, previous randomized evaluations, including a pre-registered replication, found that online growth mindset interventions improved grades for the targeted group of students in secondary education who previously showed lower achievement 13 , 16 , 18 . These findings are important because previously low-achieving students are the group that shows the steepest decline in grades during the transition to secondary school 19 , and these findings are consistent with theory because a growth mindset should be most beneficial for students confronting challenges 20 . Here we report the results of the National Study of Learning Mindsets, which examined the effects of a short, online growth mindset intervention in a nationally representative sample of high schools in the United States (Fig. 1 ). With this unique dataset we tested the hypotheses that the intervention would improve grades among lower-achieving students and overall uptake of advanced courses in this national sample. Fig. 1: Design of the National Study of Learning Mindsets. Between August and November 2015, 82% of schools delivered the intervention; the remaining 18% delivered the intervention in January or February of 2016. Asterisk indicates that the median number of days between sessions 1 and 2 among schools implementing the intervention in the autumn was 21 days; for spring-implementing schools it was 27 days. The coin-tossing symbol indicates that random assignment was made during session 1. The tick symbol indicates that a comprehensive analysis plan was pre-registered at . The blind-eye symbol indicates that, first, teachers and researchers were kept blinded to students’ random assignment to condition, and, second, the Bayesian, machine-learning robustness tests were conducted by analysts who at the time were blinded to study hypotheses and to the identities of the variables. Full size image A focus on heterogeneity The study was also designed with the purpose of understanding for whom and under what conditions the growth mindset intervention improves grades. That is, it examined potential sources of cross-site treatment effect heterogeneity. One reason why understanding heterogeneity of effects is important is because most interventions that are effective in initial efficacy trials go on to show weaker or no effects when they are scaled<|im_end|> <|im_start|>assistant Boosting academic success does not have to derive from new teachers or curriculum; it can also come from changing students' attitudes about their abilities through a short online intervention, according to the latest findings from the National Study of Learning Mindsets published in Nature on Aug. 7. The experimental study involved more than 12,000 ninth graders in a national, representative sample of 76 public high schools across the United States. It showed that an intervention emphasizing a growth mindset—the belief that intellectual abilities are not fixed but can be developed—can improve key predictors of high school graduation and college success, especially when a school's culture supports the treatment message. "The research cemented a striking finding from multiple earlier studies: A short intervention can change the unlikely outcome of adolescents' grades many months later," said David Yeager, the study's lead author and an associate professor of psychology at The University of Texas at Austin. "It also showed us something new: Higher-achieving students don't get higher grades after the program, but they are more likely to take harder classes that set them up for long-term success." According to U.S. federal government statistics, nearly 20% of students in the U.S. do not finish high school on time. These students are also at an increased risk of poverty, poor health and early mortality. The transition to high school represents an important transition point in adolescents' paths toward high school completion. Building on prior research, researchers found that two 25-minute online sessions, administered at the beginning of high school, can help students develop a growth mindset by reshaping their attitudes about their abilities. Researchers found that both lower- and higher-achieving students benefited academically from the program, even into their sophomore year. On average, lower-achieving students who took the program earned 0.10 higher grade points in core academic subjects such as math, English, science and social studies. Additionally, the intervention reduced the proportion of these students with a D or F average in these courses by more than 5 percentage points. The intervention also increased the likelihood students took Algebra II or higher in 10th grade by 3 percentage points among both higher- and lower-achieving students. "These effects are substantial when compared to the most successful large-scale, lengthy and rigorously evaluated interventions with adolescents in the educational research literature," Yeager said. "They are particularly notable given the low cost and high fidelity of the online program. But the growth mindset program isn't a magic bullet. Its effectiveness depends a lot on the school context." In medium- to low-performing schools with norms that encouraged students to take on more challenging coursework, lower-achieving students who received the intervention improved 0.15 grade points in core courses and 0.17 grade points in STEM courses. "Motivation and learning don't just happen in a student's head; they depend on the resources and learning opportunities present in the school's environment, including the extent to which challenging coursework is available to students," Yeager said. "A mindset intervention is like planting a seed; it grows to fruition in fertile soil. Now that we have shown this in a national study, it will propel us into a new era of mindset research. That era will focus on both the mindset of the student and the culture and climate of the classroom. We have our eyes set on preparing teachers to support students' beliefs that they can grow and learn." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 362, 3728, 10844, 369, 279, 88979, 36788, 374, 311, 2274, 2853, 53421, 11, 69311, 39455, 430, 1436, 7417, 279, 14584, 20124, 315, 51516, 520, 264, 7187, 2237, 11, 719, 912, 1778, 39455, 617, 779, 3117, 1027, 26126, 304, 264, 7187, 69097, 8499, 6205, 13, 5810, 584, 1501, 430, 264, 2875, 320, 1752, 1109, 832, 6596, 705, 2930, 6650, 40543, 21623, 50004, 33992, 430, 20207, 18000, 649, 387, 8040, 2345, 318, 96608, 28711, 4315, 4827, 12, 45620, 4504, 4236, 323, 7319, 8244, 66466, 479, 311, 11084, 38696, 14307, 304, 264, 40343, 18740, 6205, 315, 4236, 304, 14580, 6873, 304, 279, 3723, 4273, 13, 2876, 2915, 11, 279, 4007, 11054, 2978, 38697, 430, 29759, 279, 6372, 315, 279, 6650, 40543, 21623, 25, 279, 21623, 5614, 28711, 994, 14734, 40851, 27210, 449, 279, 6743, 315, 279, 21623, 13, 87424, 304, 279, 31342, 315, 420, 4007, 4131, 505, 9678, 828, 4526, 323, 8863, 11, 864, 99798, 315, 29060, 11, 323, 1867, 23576, 7769, 315, 3135, 555, 264, 90216, 99234, 6492, 13, 4802, 10180, 220, 508, 4, 315, 4236, 304, 279, 3723, 4273, 690, 539, 6381, 1579, 2978, 389, 892, 220, 16, 662, 4314, 4236, 527, 520, 264, 1579, 5326, 315, 19542, 11, 8009, 2890, 323, 4216, 29528, 304, 279, 1510, 3728, 8752, 220, 17, 1174, 220, 18, 1174, 220, 19, 662, 23150, 11, 264, 39634, 295, 12396, 20536, 430, 18899, 14580, 6873, 20124, 369, 51516, 1054, 79, 9773, 279, 3254, 1888, 9341, 369, 2890, 323, 57930, 863, 220, 20, 662, 578, 9320, 311, 14580, 2978, 11105, 459, 3062, 4261, 315, 25152, 304, 279, 16627, 86648, 315, 51516, 220, 21, 662, 763, 279, 3723, 4273, 11, 279, 28711, 315, 4236, 8541, 311, 18979, 2391, 279, 9320, 311, 279, 43641, 12239, 320, 425, 220, 975, 4235, 868, 1667, 11, 6560, 1060, 220, 605, 705, 323, 3629, 656, 539, 11993, 220, 22, 662, 3277, 1778, 4236, 1234, 29588, 304, 477, 3469, 704, 315, 47999, 75533, 11, 814, 527, 3117, 2753, 4461, 311, 5387, 14580, 2978, 10235, 369, 7926, 477, 12374, 477, 369, 11084, 14307, 304, 7926, 477, 12374, 220, 23, 1174, 220, 24, 662, 763, 420, 1648, 11, 4216, 5435, 304, 279, 9320, 311, 14580, 2978, 649, 24549, 927, 892, 1139, 3544, 12062, 304, 3823, 6864, 304, 64033, 13, 3861, 1648, 311, 7417, 14584, 2450, 4028, 279, 9320, 311, 14580, 2978, 374, 1555, 3674, 4235, 92109, 5848, 39455, 11, 902, 2349, 1268, 51516, 1781, 477, 2733, 922, 5694, 323, 872, 2978, 1816, 323, 28592, 15253, 4236, 311, 1935, 9610, 315, 6975, 10708, 304, 2978, 220, 605, 1174, 220, 806, 662, 578, 3230, 21623, 26126, 1618, 29096, 6650, 40543, 315, 11478, 21623, 2345, 54889, 279, 21463, 315, 51516, 922, 279, 7138, 315, 11478, 11, 6522, 4236, 311, 1518, 20207, 18000, 539, 439, 8521, 719, 439, 13171, 315, 6650, 304, 2077, 311, 12514, 5149, 11, 4560, 502, 15174, 323, 11125, 1520, 994, 8475, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 1174, 220, 845, 662, 1115, 649, 387, 5423, 3062, 304, 264, 8396, 430, 390, 50369, 264, 8521, 40543, 320, 64, 1684, 430, 11478, 374, 8521, 705, 902, 649, 34608, 430, 8430, 29991, 323, 3515, 311, 2231, 304, 5149, 3445, 430, 832, 374, 539, 18182, 23944, 323, 374, 17821, 311, 12265, 220, 717, 662, 578, 6650, 40543, 21623, 92606, 264, 33596, 46450, 25, 430, 279, 8271, 374, 1093, 264, 16124, 430, 28815, 16643, 323, 47578, 994, 433, 37771, 288, 47999, 6975, 11704, 220, 975, 662, 63737, 39428, 6865, 279, 46450, 304, 279, 2317, 315, 279, 93048, 315, 6975, 11, 814, 8881, 389, 5627, 311, 20259, 872, 35202, 1555, 2978, 1816, 11, 323, 814, 5419, 553, 279, 1984, 555, 12917, 433, 311, 264, 3938, 1176, 4771, 43641, 12239, 5575, 889, 374, 20558, 520, 279, 1212, 315, 279, 1060, 13, 578, 21623, 649, 3063, 311, 29759, 14584, 16048, 1555, 659, 5621, 258, 42596, 25492, 315, 25835, 323, 6975, 36185, 17432, 13, 1789, 3187, 11, 264, 6650, 40543, 649, 62425, 4236, 311, 1935, 389, 810, 47999, 6975, 11704, 323, 311, 23135, 994, 92372, 27129, 13, 11205, 17432, 1253, 1243, 387, 49680, 555, 279, 2978, 2317, 11, 1778, 439, 810, 6928, 323, 6975, 36185, 14847, 505, 26081, 477, 54918, 220, 605, 1174, 220, 1114, 662, 4220, 21623, 7978, 449, 51516, 15972, 264, 6650, 40543, 304, 7447, 58281, 320, 2000, 3187, 11, 8223, 24978, 16079, 220, 868, 7026, 21416, 35936, 12886, 555, 7701, 16572, 12884, 26, 4869, 11, 1521, 1051, 539, 31368, 69311, 13, 3804, 72457, 6650, 40543, 39455, 1051, 293, 7379, 809, 323, 659, 28324, 1601, 291, 2930, 11, 8051, 4827, 2515, 12562, 1051, 11, 315, 3388, 11, 3685, 13, 56733, 11, 3766, 47341, 56181, 11, 2737, 264, 864, 12, 36009, 48891, 11, 1766, 430, 2930, 6650, 40543, 39455, 13241, 28711, 369, 279, 17550, 1912, 315, 4236, 304, 14580, 6873, 889, 8767, 8710, 4827, 26501, 220, 1032, 1174, 220, 845, 1174, 220, 972, 662, 4314, 14955, 527, 3062, 1606, 8767, 3428, 12, 45620, 4504, 4236, 527, 279, 1912, 430, 5039, 279, 357, 2176, 30223, 18174, 304, 28711, 2391, 279, 9320, 311, 14580, 2978, 220, 777, 1174, 323, 1521, 14955, 527, 13263, 449, 10334, 1606, 264, 6650, 40543, 1288, 387, 1455, 24629, 369, 4236, 75867, 11774, 220, 508, 662, 5810, 584, 1934, 279, 3135, 315, 279, 5165, 19723, 315, 21579, 23754, 5022, 11, 902, 25078, 279, 6372, 315, 264, 2875, 11, 2930, 6650, 40543, 21623, 304, 264, 40343, 18740, 6205, 315, 1579, 8853, 304, 279, 3723, 4273, 320, 30035, 13, 220, 16, 7609, 3161, 420, 5016, 10550, 584, 12793, 279, 74513, 430, 279, 21623, 1053, 7417, 28711, 4315, 4827, 12, 45620, 4504, 4236, 323, 8244, 69575, 315, 11084, 14307, 304, 420, 5426, 6205, 13, 23966, 13, 220, 16, 25, 7127, 315, 279, 5165, 19723, 315, 21579, 23754, 5022, 13, 28232, 6287, 323, 6841, 220, 679, 20, 11, 220, 6086, 4, 315, 8853, 12886, 279, 21623, 26, 279, 9861, 220, 972, 4, 12886, 279, 21623, 304, 6186, 477, 7552, 315, 220, 679, 21, 13, 68598, 3267, 15151, 430, 279, 23369, 1396, 315, 2919, 1990, 16079, 220, 16, 323, 220, 17, 4315, 8853, 25976, 279, 21623, 304, 279, 42774, 574, 220, 1691, 2919, 26, 369, 10683, 38025, 2833, 287, 8853, 433, 574, 220, 1544, 2919, 13, 578, 16652, 2442, 3746, 287, 7891, 15151, 430, 4288, 16720, 574, 1903, 2391, 3882, 220, 16, 13, 578, 9525, 7891, 15151, 430, 264, 16195, 6492, 3197, 574, 864, 12, 36009, 520, 662, 578, 18507, 47797, 7891, 15151, 430, 11, 1176, 11, 13639, 323, 12074, 1051, 8774, 90216, 311, 4236, 529, 4288, 16720, 311, 3044, 11, 323, 11, 2132, 11, 279, 99234, 11, 5780, 71856, 22514, 2136, 7177, 1051, 13375, 555, 31499, 889, 520, 279, 892, 1051, 90216, 311, 4007, 74513, 323, 311, 279, 40521, 315, 279, 7482, 13, 8797, 1404, 2217, 362, 5357, 389, 30548, 76730, 578, 4007, 574, 1101, 6319, 449, 279, 7580, 315, 8830, 369, 8884, 323, 1234, 1148, 4787, 279, 6650, 40543, 21623, 36050, 28711, 13, 3011, 374, 11, 433, 25078, 4754, 8336, 315, 5425, 29654, 6514, 2515, 30548, 76730, 13, 3861, 2944, 3249, 8830, 30548, 76730, 315, 6372, 374, 3062, 374, 1606, 1455, 39455, 430, 527, 7524, 304, 2926, 41265, 19622, 733, 389, 311, 1501, 43383, 477, 912, 6372, 994, 814, 527, 31790, 128257, 198, 128256, 78191, 198, 53463, 287, 14584, 2450, 1587, 539, 617, 311, 43530, 505, 502, 13639, 477, 30676, 26, 433, 649, 1101, 2586, 505, 10223, 4236, 6, 33726, 922, 872, 18000, 1555, 264, 2875, 2930, 21623, 11, 4184, 311, 279, 5652, 14955, 505, 279, 5165, 19723, 315, 21579, 23754, 5022, 4756, 304, 22037, 389, 5033, 13, 220, 22, 13, 578, 22772, 4007, 6532, 810, 1109, 220, 717, 11, 931, 43641, 6117, 388, 304, 264, 5426, 11, 18740, 6205, 315, 220, 4767, 586, 1579, 8853, 4028, 279, 3723, 4273, 13, 1102, 8710, 430, 459, 21623, 82003, 264, 6650, 40543, 22416, 16801, 430, 20207, 18000, 527, 539, 8521, 719, 649, 387, 8040, 2345, 4919, 7417, 1401, 95222, 315, 1579, 2978, 39554, 323, 7926, 2450, 11, 5423, 994, 264, 2978, 596, 7829, 11815, 279, 6514, 1984, 13, 330, 791, 3495, 24532, 291, 264, 21933, 9455, 505, 5361, 6931, 7978, 25, 362, 2875, 21623, 649, 2349, 279, 17821, 15632, 315, 51516, 6, 28711, 1690, 4038, 3010, 1359, 1071, 6941, 32269, 1435, 11, 279, 4007, 596, 3063, 3229, 323, 459, 22712, 14561, 315, 31018, 520, 578, 3907, 315, 8421, 520, 19816, 13, 330, 2181, 1101, 8710, 603, 2555, 502, 25, 35321, 12, 45620, 4504, 4236, 1541, 956, 636, 5190, 28711, 1306, 279, 2068, 11, 719, 814, 527, 810, 4461, 311, 1935, 16127, 6989, 430, 743, 1124, 709, 369, 1317, 9860, 2450, 1210, 10771, 311, 549, 815, 13, 6918, 3109, 13443, 11, 7154, 220, 508, 4, 315, 4236, 304, 279, 549, 815, 13, 656, 539, 6381, 1579, 2978, 389, 892, 13, 4314, 4236, 527, 1101, 520, 459, 7319, 5326, 315, 19542, 11, 8009, 2890, 323, 4216, 29528, 13, 578, 9320, 311, 1579, 2978, 11105, 459, 3062, 9320, 1486, 304, 51516, 6, 13006, 9017, 1579, 2978, 9954, 13, 17283, 389, 4972, 3495, 11, 12074, 1766, 430, 1403, 220, 914, 24401, 2930, 16079, 11, 38018, 520, 279, 7314, 315, 1579, 2978, 11, 649, 1520, 4236, 2274, 264, 6650, 40543, 555, 64793, 14550, 872, 33726, 922, 872, 18000, 13, 59250, 1766, 430, 2225, 4827, 12, 323, 5190, 12, 45620, 4504, 4236, 56128, 10623, 336, 2740, 505, 279, 2068, 11, 1524, 1139, 872, 51498, 1060, 13, 1952, 5578, 11, 4827, 12, 45620, 4504, 4236, 889, 3952, 279, 2068, 15662, 220, 15, 13, 605, 5190, 12239, 3585, 304, 6332, 14584, 15223, 1778, 439, 7033, 11, 6498, 11, 8198, 323, 3674, 7978, 13, 23212, 11, 279, 21623, 11293, 279, 21801, 315, 1521, 4236, 449, 264, 423, 477, 435, 5578, 304, 1521, 14307, 555, 810, 1109, 220, 20, 11668, 3585, 13, 578, 21623, 1101, 7319, 279, 29736, 4236, 3952, 77543, 8105, 477, 5190, 304, 220, 605, 339, 12239, 555, 220, 18, 11668, 3585, 4315, 2225, 5190, 12, 323, 4827, 12, 45620, 4504, 4236, 13, 330, 9673, 6372, 527, 12190, 994, 7863, 311, 279, 1455, 6992, 3544, 13230, 11, 35306, 323, 78477, 7162, 26126, 39455, 449, 51516, 304, 279, 16627, 3495, 17649, 1359, 32269, 1435, 1071, 13, 330, 7009, 527, 8104, 28289, 2728, 279, 3428, 2853, 323, 1579, 83604, 315, 279, 2930, 2068, 13, 2030, 279, 6650, 40543, 2068, 4536, 956, 264, 11204, 17889, 13, 11699, 27375, 14117, 264, 2763, 389, 279, 2978, 2317, 1210, 763, 11298, 12, 311, 3428, 17453, 55857, 8853, 449, 40851, 430, 21190, 4236, 311, 1935, 389, 810, 17436, 75533, 11, 4827, 12, 45620, 4504, 4236, 889, 4036, 279, 21623, 13241, 220, 15, 13, 868, 12239, 3585, 304, 6332, 14307, 323, 220, 15, 13, 1114, 12239, 3585, 304, 64182, 14307, 13, 330, 61032, 40227, 323, 6975, 1541, 956, 1120, 3621, 304, 264, 5575, 596, 2010, 26, 814, 6904, 389, 279, 5070, 323, 6975, 10708, 3118, 304, 279, 2978, 596, 4676, 11, 2737, 279, 13112, 311, 902, 17436, 75533, 374, 2561, 311, 4236, 1359, 32269, 1435, 1071, 13, 330, 32, 40543, 21623, 374, 1093, 48114, 264, 10533, 26, 433, 28815, 311, 94706, 304, 70225, 17614, 13, 4800, 430, 584, 617, 6982, 420, 304, 264, 5426, 4007, 11, 433, 690, 89483, 603, 1139, 264, 502, 11639, 315, 40543, 3495, 13, 3011, 11639, 690, 5357, 389, 2225, 279, 40543, 315, 279, 5575, 323, 279, 7829, 323, 10182, 315, 279, 24978, 13, 1226, 617, 1057, 6548, 743, 389, 20646, 13639, 311, 1862, 4236, 6, 21463, 430, 814, 649, 3139, 323, 4048, 1210, 220, 128257, 198 ]

1,926

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Parkinson’s dementia is characterised by changes in perception and thought, and preceded by visual dysfunction, making this a useful surrogate for dementia risk. Structural and functional connectivity changes are seen in humans with Parkinson’s disease, but the organisational principles are not known. We used resting-state fMRI and diffusion-weighted imaging to examine changes in structural-functional connectivity coupling in patients with Parkinson’s disease, and those at risk of dementia. We identified two organisational gradients to structural-functional connectivity decoupling: anterior-to-posterior and unimodal-to-transmodal, with stronger structural-functional connectivity coupling in anterior, unimodal areas and weakened towards posterior, transmodal regions. Next, we related spatial patterns of decoupling to expression of neurotransmitter receptors. We found that dopaminergic and serotonergic transmission relates to decoupling in Parkinson’s overall, but instead, serotonergic, cholinergic and noradrenergic transmission relates to decoupling in patients with visual dysfunction. Our findings provide a framework to explain the specific disorders of consciousness in Parkinson’s dementia, and the neurotransmitter systems that underlie these. Introduction Dementia associated with Parkinson’s disease (PD) is characterised by changes in cognition and perception, including visual hallucinations, delusions and fluctuations in attention 1 , 2 . It is often preceded and accompanied by visual dysfunction 3 , 4 , 5 and linked to hypometabolism in posterior brain regions 6 . High-order visual dysfunction, in particular, is associated with worse cognition at 1-year follow up 7 . Although PD is characterised by Lewy body inclusions, the neural correlates of cognitive impairment in PD and specifically the structural and functional changes remain unclear 8 . Perception and action, whether in health or disease, depends on connections between brain regions. In general, it is assumed that there is a relationship between the strength of a structural connection between two brain areas and the strength of the corresponding functional connection 9 . However, it has recently emerged that this relationship between structural–functional connectivity is not uniform across the healthy human brain but organised with clear hierarchical and cyto-architectural principles 9 . Specifically, there is close structural–functional coupling (SC–FC coupling) in primary sensory (unimodal) cortices, with divergence at the apices of processing hierarchies (transmodal association cortices), in networks such as the default mode network (DMN) 10 , 11 , 12 . One theory for this is that relative decoupling in higher-order areas allows abstract reasoning, protected from the more granular signalling in earlier stages of sensory processing 13 . Changes in SC–FC coupling occur during brain maturation 10 but also in psychiatric 14 , 15 and neurological disease 16 , 17 , 18 , 19 , and maybe particularly relevant to cognition: individual differences in coupling reflect differences in cognition 20 , 21 and higher SC–FC coupling in prefrontal cortex is associated with improved executive function 10 . Therefore, loss of SC–FC coupling might be expected in PD, especially in subtypes linked with higher risk of dementia. Neuroimaging studies have provided important insights separately into structural and functional connectivity alterations in PD 22 , 23 , 24 . Diffusion-weighted imaging revealed structural alterations in tracts including the corpus callosum and thalamo-cortical connections in PD with cognitive impairment 25 , 26 , 27 , 28 , 29 and those with visual dysfunction (higher dementia risk) 30 . Resting-state functional MRI (rsfMRI) studies have identified changes in functional connectivity between frontal and visuospatial regions 31 , 32 and frontal regions and the posterior cingulate 7 , 32 in PD with cognitive impairment. These studies provide useful insights into the network-level dysfunction contributing to cognitive impairment in PD, however, the question of how structural changes impact on brain function is unresolved. We hypothesised that the relationship between structural–functional coupling across the brain would be systematically modified in PD and that this pattern of decoupling would occur along with one of two hypothesised directions: (1) across the unimodal–transmodal hierarchical gradient of SC–FC decoupling that is seen in health with more transmodal regions becoming even more decoupled in PD 10 , 11 , 12 , 33 ; or (2) along the anterior-to-posterior (A–P) axis with decoupling more prominent in posterior regions. This hypothesis was based on the posterior distribution of metabolic and connectivity changes seen in PD 25 , 30 , 34 , 35 , 36 . We used rsfMRI and diffusion-weighted imaging to investigate changes in whole-brain structural connectivity–functional connectivity coupling (SC–FC coupling) in 88 patients with PD (of whom 33 had visual dysfunction and higher dementia risk) and 30 age-matched controls. We found widespread decoupling in PD compared to controls but a more focal pattern affecting the insula in PD with visual dysfunction compared with those with normal visual function. Next, we evaluated the specific pattern of decoupling in PD and found that this occurred across both a unimodal–transmodal and anterior–posterior axes. Finally, we examined whether changes in SC–FC coupling are related to underlying differences in expression of specific neurotransmitters in an exploratory analysis. Although PD is classically associated with the altered dopaminergic transmission, recent evidence implicates other neurotransmitter systems: cholinergic transmission 37 , 38 , 39 is affected in PD dementia and both reduced occipital GABA levels 40 and altered noradrenergic transmission 41 have been implicated in cognitive impairment in PD. We show that dopamine transmission, although central to motor aspects of PD, may have a less important role in PD dementia, as neurotransmitter systems other than dopamine were correlated with the SC–FC decoupling found in PD with visual dysfunction. Results To characterise how structural–functional connectivity (SC–FC) coupling changes in PD, we quantified the degree to which a brain region’s structural connectivity relates to coordinated fluctuations in neural activity between-regions. For each participant, two weighted, undirected connectivity matrices were derived using the same parcellation 42 comprised of 400 cortical brain regions: a structural connectivity matrix derived from diffusion-weighted imaging and a functional connectivity matrix derived from resting-state functional MRI (rsfMRI) data. SC–FC coupling was measured as the Spearman rank correlation between the structural and functional connectivity profiles of each region. An overview of the study methodology is seen in Fig. 1 . Fig. 1: Overview of the study methodology.", "role": "user" }, { "content": "Simple vision tests can predict which people with Parkinson's disease will develop cognitive impairment and possible dementia 18 months later, according to a new study by UCL researchers. The study, published in Movement Disorders, adds to evidence that vision changes precede the cognitive decline that occurs in many, but not all, people with Parkinson's. In another new study published today in Communications Biology, the same research team found that structural and functional connections of brain regions become decoupled throughout the entire brain in people with Parkinson's disease, particularly among people with vision problems. The two studies together show how losses and changes to the brain's wiring underlie the cognitive impairment experienced by many people with Parkinson's disease. Lead author Dr. Angeliki Zarkali (Dementia Research Centre, UCL Queen Square Institute of Neurology) said: \"We have found that people with Parkinson's disease who have visual problems are more likely to get dementia, and that appears to be explained by underlying changes to their brain wiring. \"Vision tests might provide us with a window of opportunity to predict Parkinson's dementia before it begins, which may help us find ways to stop the cognitive decline before it's too late.\" For the Movement Disorders paper, published earlier this month, the researchers studied 77 people with Parkinson's disease and found that simple vision tests predicted who would go on to get dementia after a year and a half. Dementia is a common, debilitating aspect of Parkinson's disease, estimated to affect roughly 50% of people within 10 years of a Parkinson's diagnosis. These longitudinal findings add weight to previous studies that were done at one time point, which had suggested that performance in vision tests, involving commonly used eye charts and skewed images of cats and dogs, was linked to the risk of cognitive decline. The new study also found that those who went on to develop Parkinson's dementia had losses in the wiring of the brain, including in areas relating to vision and memory. The researchers used recently developed methods to analyse finely detailed MRI scans, enabling them to pick up the damage to the brain's white matter. The researchers identified white matter damage to some of the long-distance wiring connecting the front and back of the brain, which helps the brain to function as a cohesive whole network. The Communications Biology study involved 88 people with Parkinson's disease (33 of whom had visual dysfunction and were thus judged to have a high risk of dementia) and 30 healthy adults as a control group, whose brains were imaged using MRI scans. In the healthy brain, there is a correlation between how strong the structural (physical) connections between two regions are, and how much those two regions are connected functionally. That coupling is not uniform across the brain, as there is some degree of decoupling in the healthy brain, particularly in areas involved in higher-order processing, which might provide the flexibility to enable abstract reasoning. Too much decoupling appears to be linked to poor outcomes. The researchers found that people with Parkinson's disease exhibited a higher degree of decoupling across the whole brain. Areas at the back of the brain, and less specialized areas, had the most decoupling in Parkinson's patients. Parkinson's patients with visual dysfunction had more decoupling in some, but not all brain regions, particularly in memory-related regions in the temporal lobe. The research team also found changes to the levels of some neurotransmitters (chemical messengers) in people at risk of cognitive decline, suggesting that receptors for those transmitters may be potential targets for new drug treatments for Parkinson's dementia. Notably, while dopamine is known to be implicated in Parkinson's, the researchers found that other neurotransmitters—acetylcholine, serotonin and noradrenaline—were particularly affected in people at risk of cognitive decline. Dr. Angeliki said: \"The two papers together help us to understand what's going on in the brains of people with Parkinson's who experience cognitive decline, as it appears to be driven by a breakdown in the wiring that connects different brain regions.\" Dr. Rimona Weil (UCL Queen Square Institute of Neurology), senior author of both papers, said: \"Our findings could be valuable for clinical trials, by showing that vision tests can help us identify who we should be targeting for trials of new drugs that might be able to slow Parkinson's. And ultimately if effective treatments are found, then these simple tests may help us identify who will benefit from which treatments.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Parkinson’s dementia is characterised by changes in perception and thought, and preceded by visual dysfunction, making this a useful surrogate for dementia risk. Structural and functional connectivity changes are seen in humans with Parkinson’s disease, but the organisational principles are not known. We used resting-state fMRI and diffusion-weighted imaging to examine changes in structural-functional connectivity coupling in patients with Parkinson’s disease, and those at risk of dementia. We identified two organisational gradients to structural-functional connectivity decoupling: anterior-to-posterior and unimodal-to-transmodal, with stronger structural-functional connectivity coupling in anterior, unimodal areas and weakened towards posterior, transmodal regions. Next, we related spatial patterns of decoupling to expression of neurotransmitter receptors. We found that dopaminergic and serotonergic transmission relates to decoupling in Parkinson’s overall, but instead, serotonergic, cholinergic and noradrenergic transmission relates to decoupling in patients with visual dysfunction. Our findings provide a framework to explain the specific disorders of consciousness in Parkinson’s dementia, and the neurotransmitter systems that underlie these. Introduction Dementia associated with Parkinson’s disease (PD) is characterised by changes in cognition and perception, including visual hallucinations, delusions and fluctuations in attention 1 , 2 . It is often preceded and accompanied by visual dysfunction 3 , 4 , 5 and linked to hypometabolism in posterior brain regions 6 . High-order visual dysfunction, in particular, is associated with worse cognition at 1-year follow up 7 . Although PD is characterised by Lewy body inclusions, the neural correlates of cognitive impairment in PD and specifically the structural and functional changes remain unclear 8 . Perception and action, whether in health or disease, depends on connections between brain regions. In general, it is assumed that there is a relationship between the strength of a structural connection between two brain areas and the strength of the corresponding functional connection 9 . However, it has recently emerged that this relationship between structural–functional connectivity is not uniform across the healthy human brain but organised with clear hierarchical and cyto-architectural principles 9 . Specifically, there is close structural–functional coupling (SC–FC coupling) in primary sensory (unimodal) cortices, with divergence at the apices of processing hierarchies (transmodal association cortices), in networks such as the default mode network (DMN) 10 , 11 , 12 . One theory for this is that relative decoupling in higher-order areas allows abstract reasoning, protected from the more granular signalling in earlier stages of sensory processing 13 . Changes in SC–FC coupling occur during brain maturation 10 but also in psychiatric 14 , 15 and neurological disease 16 , 17 , 18 , 19 , and maybe particularly relevant to cognition: individual differences in coupling reflect differences in cognition 20 , 21 and higher SC–FC coupling in prefrontal cortex is associated with improved executive function 10 . Therefore, loss of SC–FC coupling might be expected in PD, especially in subtypes linked with higher risk of dementia. Neuroimaging studies have provided important insights separately into structural and functional connectivity alterations in PD 22 , 23 , 24 . Diffusion-weighted imaging revealed structural alterations in tracts including the corpus callosum and thalamo-cortical connections in PD with cognitive impairment 25 , 26 , 27 , 28 , 29 and those with visual dysfunction (higher dementia risk) 30 . Resting-state functional MRI (rsfMRI) studies have identified changes in functional connectivity between frontal and visuospatial regions 31 , 32 and frontal regions and the posterior cingulate 7 , 32 in PD with cognitive impairment. These studies provide useful insights into the network-level dysfunction contributing to cognitive impairment in PD, however, the question of how structural changes impact on brain function is unresolved. We hypothesised that the relationship between structural–functional coupling across the brain would be systematically modified in PD and that this pattern of decoupling would occur along with one of two hypothesised directions: (1) across the unimodal–transmodal hierarchical gradient of SC–FC decoupling that is seen in health with more transmodal regions becoming even more decoupled in PD 10 , 11 , 12 , 33 ; or (2) along the anterior-to-posterior (A–P) axis with decoupling more prominent in posterior regions. This hypothesis was based on the posterior distribution of metabolic and connectivity changes seen in PD 25 , 30 , 34 , 35 , 36 . We used rsfMRI and diffusion-weighted imaging to investigate changes in whole-brain structural connectivity–functional connectivity coupling (SC–FC coupling) in 88 patients with PD (of whom 33 had visual dysfunction and higher dementia risk) and 30 age-matched controls. We found widespread decoupling in PD compared to controls but a more focal pattern affecting the insula in PD with visual dysfunction compared with those with normal visual function. Next, we evaluated the specific pattern of decoupling in PD and found that this occurred across both a unimodal–transmodal and anterior–posterior axes. Finally, we examined whether changes in SC–FC coupling are related to underlying differences in expression of specific neurotransmitters in an exploratory analysis. Although PD is classically associated with the altered dopaminergic transmission, recent evidence implicates other neurotransmitter systems: cholinergic transmission 37 , 38 , 39 is affected in PD dementia and both reduced occipital GABA levels 40 and altered noradrenergic transmission 41 have been implicated in cognitive impairment in PD. We show that dopamine transmission, although central to motor aspects of PD, may have a less important role in PD dementia, as neurotransmitter systems other than dopamine were correlated with the SC–FC decoupling found in PD with visual dysfunction. Results To characterise how structural–functional connectivity (SC–FC) coupling changes in PD, we quantified the degree to which a brain region’s structural connectivity relates to coordinated fluctuations in neural activity between-regions. For each participant, two weighted, undirected connectivity matrices were derived using the same parcellation 42 comprised of 400 cortical brain regions: a structural connectivity matrix derived from diffusion-weighted imaging and a functional connectivity matrix derived from resting-state functional MRI (rsfMRI) data. SC–FC coupling was measured as the Spearman rank correlation between the structural and functional connectivity profiles of each region. An overview of the study methodology is seen in Fig. 1 . Fig. 1: Overview of the study methodology.<|im_end|> <|im_start|>assistant Simple vision tests can predict which people with Parkinson's disease will develop cognitive impairment and possible dementia 18 months later, according to a new study by UCL researchers. The study, published in Movement Disorders, adds to evidence that vision changes precede the cognitive decline that occurs in many, but not all, people with Parkinson's. In another new study published today in Communications Biology, the same research team found that structural and functional connections of brain regions become decoupled throughout the entire brain in people with Parkinson's disease, particularly among people with vision problems. The two studies together show how losses and changes to the brain's wiring underlie the cognitive impairment experienced by many people with Parkinson's disease. Lead author Dr. Angeliki Zarkali (Dementia Research Centre, UCL Queen Square Institute of Neurology) said: "We have found that people with Parkinson's disease who have visual problems are more likely to get dementia, and that appears to be explained by underlying changes to their brain wiring. "Vision tests might provide us with a window of opportunity to predict Parkinson's dementia before it begins, which may help us find ways to stop the cognitive decline before it's too late." For the Movement Disorders paper, published earlier this month, the researchers studied 77 people with Parkinson's disease and found that simple vision tests predicted who would go on to get dementia after a year and a half. Dementia is a common, debilitating aspect of Parkinson's disease, estimated to affect roughly 50% of people within 10 years of a Parkinson's diagnosis. These longitudinal findings add weight to previous studies that were done at one time point, which had suggested that performance in vision tests, involving commonly used eye charts and skewed images of cats and dogs, was linked to the risk of cognitive decline. The new study also found that those who went on to develop Parkinson's dementia had losses in the wiring of the brain, including in areas relating to vision and memory. The researchers used recently developed methods to analyse finely detailed MRI scans, enabling them to pick up the damage to the brain's white matter. The researchers identified white matter damage to some of the long-distance wiring connecting the front and back of the brain, which helps the brain to function as a cohesive whole network. The Communications Biology study involved 88 people with Parkinson's disease (33 of whom had visual dysfunction and were thus judged to have a high risk of dementia) and 30 healthy adults as a control group, whose brains were imaged using MRI scans. In the healthy brain, there is a correlation between how strong the structural (physical) connections between two regions are, and how much those two regions are connected functionally. That coupling is not uniform across the brain, as there is some degree of decoupling in the healthy brain, particularly in areas involved in higher-order processing, which might provide the flexibility to enable abstract reasoning. Too much decoupling appears to be linked to poor outcomes. The researchers found that people with Parkinson's disease exhibited a higher degree of decoupling across the whole brain. Areas at the back of the brain, and less specialized areas, had the most decoupling in Parkinson's patients. Parkinson's patients with visual dysfunction had more decoupling in some, but not all brain regions, particularly in memory-related regions in the temporal lobe. The research team also found changes to the levels of some neurotransmitters (chemical messengers) in people at risk of cognitive decline, suggesting that receptors for those transmitters may be potential targets for new drug treatments for Parkinson's dementia. Notably, while dopamine is known to be implicated in Parkinson's, the researchers found that other neurotransmitters—acetylcholine, serotonin and noradrenaline—were particularly affected in people at risk of cognitive decline. Dr. Angeliki said: "The two papers together help us to understand what's going on in the brains of people with Parkinson's who experience cognitive decline, as it appears to be driven by a breakdown in the wiring that connects different brain regions." Dr. Rimona Weil (UCL Queen Square Institute of Neurology), senior author of both papers, said: "Our findings could be valuable for clinical trials, by showing that vision tests can help us identify who we should be targeting for trials of new drugs that might be able to slow Parkinson's. And ultimately if effective treatments are found, then these simple tests may help us identify who will benefit from which treatments." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 62145, 753, 52857, 374, 3752, 4147, 555, 4442, 304, 21063, 323, 3463, 11, 323, 53580, 555, 9302, 32403, 11, 3339, 420, 264, 5505, 73950, 369, 52857, 5326, 13, 73800, 323, 16003, 31357, 4442, 527, 3970, 304, 12966, 449, 62145, 753, 8624, 11, 719, 279, 21874, 1697, 16565, 527, 539, 3967, 13, 1226, 1511, 41219, 21395, 282, 79770, 323, 58430, 12923, 291, 32758, 311, 21635, 4442, 304, 24693, 99616, 31357, 59086, 304, 6978, 449, 62145, 753, 8624, 11, 323, 1884, 520, 5326, 315, 52857, 13, 1226, 11054, 1403, 21874, 1697, 53249, 311, 24693, 99616, 31357, 1654, 283, 12127, 25, 37229, 4791, 25414, 14917, 323, 653, 318, 58697, 4791, 39160, 5785, 11, 449, 16643, 24693, 99616, 31357, 59086, 304, 37229, 11, 653, 318, 58697, 5789, 323, 58764, 7119, 46000, 11, 1380, 5785, 13918, 13, 9479, 11, 584, 5552, 29079, 12912, 315, 1654, 283, 12127, 311, 7645, 315, 90351, 16517, 44540, 13, 1226, 1766, 430, 27420, 8778, 75439, 323, 1446, 26934, 75439, 18874, 36716, 311, 1654, 283, 12127, 304, 62145, 753, 8244, 11, 719, 4619, 11, 1446, 26934, 75439, 11, 523, 37737, 75439, 323, 6463, 329, 265, 39624, 292, 18874, 36716, 311, 1654, 283, 12127, 304, 6978, 449, 9302, 32403, 13, 5751, 14955, 3493, 264, 12914, 311, 10552, 279, 3230, 24673, 315, 25917, 304, 62145, 753, 52857, 11, 323, 279, 90351, 16517, 6067, 430, 1234, 11828, 1521, 13, 29438, 423, 46744, 5938, 449, 62145, 753, 8624, 320, 23891, 8, 374, 3752, 4147, 555, 4442, 304, 75310, 323, 21063, 11, 2737, 9302, 59123, 12922, 11, 1624, 36807, 323, 65649, 304, 6666, 220, 16, 1174, 220, 17, 662, 1102, 374, 3629, 53580, 323, 24895, 555, 9302, 32403, 220, 18, 1174, 220, 19, 1174, 220, 20, 323, 10815, 311, 9950, 4512, 53904, 2191, 304, 46000, 8271, 13918, 220, 21, 662, 5234, 24747, 9302, 32403, 11, 304, 4040, 11, 374, 5938, 449, 11201, 75310, 520, 220, 16, 4771, 1833, 709, 220, 22, 662, 10541, 27572, 374, 3752, 4147, 555, 17638, 88, 2547, 304, 24436, 11, 279, 30828, 97303, 315, 25702, 53317, 304, 27572, 323, 11951, 279, 24693, 323, 16003, 4442, 7293, 25420, 220, 23, 662, 86950, 323, 1957, 11, 3508, 304, 2890, 477, 8624, 11, 14117, 389, 13537, 1990, 8271, 13918, 13, 763, 4689, 11, 433, 374, 19655, 430, 1070, 374, 264, 5133, 1990, 279, 8333, 315, 264, 24693, 3717, 1990, 1403, 8271, 5789, 323, 279, 8333, 315, 279, 12435, 16003, 3717, 220, 24, 662, 4452, 11, 433, 706, 6051, 22763, 430, 420, 5133, 1990, 24693, 4235, 50328, 31357, 374, 539, 14113, 4028, 279, 9498, 3823, 8271, 719, 39433, 449, 2867, 70994, 323, 9693, 998, 12, 1132, 8525, 4269, 16565, 220, 24, 662, 45863, 11, 1070, 374, 3345, 24693, 4235, 50328, 59086, 320, 3624, 4235, 6897, 59086, 8, 304, 6156, 49069, 320, 359, 318, 58697, 8, 23100, 1238, 11, 449, 82258, 520, 279, 1469, 1238, 315, 8863, 12694, 1132, 552, 320, 1485, 5785, 15360, 23100, 1238, 705, 304, 14488, 1778, 439, 279, 1670, 3941, 4009, 320, 8561, 45, 8, 220, 605, 1174, 220, 806, 1174, 220, 717, 662, 3861, 10334, 369, 420, 374, 430, 8844, 1654, 283, 12127, 304, 5190, 24747, 5789, 6276, 8278, 33811, 11, 2682, 505, 279, 810, 16109, 1299, 91977, 304, 6931, 18094, 315, 49069, 8863, 220, 1032, 662, 29240, 304, 7683, 4235, 6897, 59086, 12446, 2391, 8271, 5634, 2060, 220, 605, 719, 1101, 304, 47657, 220, 975, 1174, 220, 868, 323, 64908, 8624, 220, 845, 1174, 220, 1114, 1174, 220, 972, 1174, 220, 777, 1174, 323, 7344, 8104, 9959, 311, 75310, 25, 3927, 12062, 304, 59086, 8881, 12062, 304, 75310, 220, 508, 1174, 220, 1691, 323, 5190, 7683, 4235, 6897, 59086, 304, 864, 7096, 278, 49370, 374, 5938, 449, 13241, 11145, 734, 220, 605, 662, 15636, 11, 4814, 315, 7683, 4235, 6897, 59086, 2643, 387, 3685, 304, 27572, 11, 5423, 304, 1207, 9426, 10815, 449, 5190, 5326, 315, 52857, 13, 32359, 318, 4210, 7978, 617, 3984, 3062, 26793, 26214, 1139, 24693, 323, 16003, 31357, 61086, 304, 27572, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 662, 29469, 7713, 12923, 291, 32758, 10675, 24693, 61086, 304, 490, 11613, 2737, 279, 43194, 1652, 385, 1264, 323, 270, 17243, 78, 1824, 371, 950, 13537, 304, 27572, 449, 25702, 53317, 220, 914, 1174, 220, 1627, 1174, 220, 1544, 1174, 220, 1591, 1174, 220, 1682, 323, 1884, 449, 9302, 32403, 320, 90447, 52857, 5326, 8, 220, 966, 662, 9240, 287, 21395, 16003, 52460, 320, 5544, 69, 79770, 8, 7978, 617, 11054, 4442, 304, 16003, 31357, 1990, 66746, 323, 2145, 84808, 33514, 13918, 220, 2148, 1174, 220, 843, 323, 66746, 13918, 323, 279, 46000, 272, 287, 6468, 220, 22, 1174, 220, 843, 304, 27572, 449, 25702, 53317, 13, 4314, 7978, 3493, 5505, 26793, 1139, 279, 4009, 11852, 32403, 29820, 311, 25702, 53317, 304, 27572, 11, 4869, 11, 279, 3488, 315, 1268, 24693, 4442, 5536, 389, 8271, 734, 374, 81261, 13, 1226, 22601, 6509, 4147, 430, 279, 5133, 1990, 24693, 4235, 50328, 59086, 4028, 279, 8271, 1053, 387, 60826, 11041, 304, 27572, 323, 430, 420, 5497, 315, 1654, 283, 12127, 1053, 12446, 3235, 449, 832, 315, 1403, 22601, 6509, 4147, 18445, 25, 320, 16, 8, 4028, 279, 653, 318, 58697, 4235, 1485, 5785, 70994, 20779, 315, 7683, 4235, 6897, 1654, 283, 12127, 430, 374, 3970, 304, 2890, 449, 810, 1380, 5785, 13918, 10671, 1524, 810, 1654, 283, 50185, 304, 27572, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1644, 2652, 477, 320, 17, 8, 3235, 279, 37229, 4791, 25414, 14917, 320, 32, 4235, 47, 8, 8183, 449, 1654, 283, 12127, 810, 21102, 304, 46000, 13918, 13, 1115, 31178, 574, 3196, 389, 279, 46000, 8141, 315, 41861, 323, 31357, 4442, 3970, 304, 27572, 220, 914, 1174, 220, 966, 1174, 220, 1958, 1174, 220, 1758, 1174, 220, 1927, 662, 1226, 1511, 10242, 69, 79770, 323, 58430, 12923, 291, 32758, 311, 19874, 4442, 304, 4459, 31217, 467, 24693, 31357, 4235, 50328, 31357, 59086, 320, 3624, 4235, 6897, 59086, 8, 304, 220, 2421, 6978, 449, 27572, 320, 1073, 8884, 220, 1644, 1047, 9302, 32403, 323, 5190, 52857, 5326, 8, 323, 220, 966, 4325, 1474, 35344, 11835, 13, 1226, 1766, 24716, 1654, 283, 12127, 304, 27572, 7863, 311, 11835, 719, 264, 810, 42199, 5497, 28987, 279, 1672, 5724, 304, 27572, 449, 9302, 32403, 7863, 449, 1884, 449, 4725, 9302, 734, 13, 9479, 11, 584, 26126, 279, 3230, 5497, 315, 1654, 283, 12127, 304, 27572, 323, 1766, 430, 420, 10222, 4028, 2225, 264, 653, 318, 58697, 4235, 1485, 5785, 323, 37229, 4235, 2252, 14917, 25776, 13, 17830, 11, 584, 25078, 3508, 4442, 304, 7683, 4235, 6897, 59086, 527, 5552, 311, 16940, 12062, 304, 7645, 315, 3230, 90351, 83189, 304, 459, 48539, 5382, 6492, 13, 10541, 27572, 374, 538, 2740, 5938, 449, 279, 29852, 27420, 8778, 75439, 18874, 11, 3293, 6029, 92195, 988, 1023, 90351, 16517, 6067, 25, 523, 37737, 75439, 18874, 220, 1806, 1174, 220, 1987, 1174, 220, 2137, 374, 11754, 304, 27572, 52857, 323, 2225, 11293, 3056, 575, 2223, 480, 57650, 5990, 220, 1272, 323, 29852, 6463, 329, 265, 39624, 292, 18874, 220, 3174, 617, 1027, 69702, 304, 25702, 53317, 304, 27572, 13, 1226, 1501, 430, 66128, 18874, 11, 8051, 8792, 311, 9048, 13878, 315, 27572, 11, 1253, 617, 264, 2753, 3062, 3560, 304, 27572, 52857, 11, 439, 90351, 16517, 6067, 1023, 1109, 66128, 1051, 49393, 449, 279, 7683, 4235, 6897, 1654, 283, 12127, 1766, 304, 27572, 449, 9302, 32403, 13, 18591, 2057, 3752, 1082, 1268, 24693, 4235, 50328, 31357, 320, 3624, 4235, 6897, 8, 59086, 4442, 304, 27572, 11, 584, 10484, 1908, 279, 8547, 311, 902, 264, 8271, 5654, 753, 24693, 31357, 36716, 311, 47672, 65649, 304, 30828, 5820, 1990, 33263, 919, 13, 1789, 1855, 25923, 11, 1403, 37924, 11, 2073, 75712, 31357, 36295, 1051, 14592, 1701, 279, 1890, 1370, 5997, 367, 220, 2983, 40056, 315, 220, 3443, 83619, 8271, 13918, 25, 264, 24693, 31357, 6303, 14592, 505, 58430, 12923, 291, 32758, 323, 264, 16003, 31357, 6303, 14592, 505, 41219, 21395, 16003, 52460, 320, 5544, 69, 79770, 8, 828, 13, 7683, 4235, 6897, 59086, 574, 17303, 439, 279, 78537, 1543, 7222, 26670, 1990, 279, 24693, 323, 16003, 31357, 21542, 315, 1855, 5654, 13, 1556, 24131, 315, 279, 4007, 38152, 374, 3970, 304, 23966, 13, 220, 16, 662, 23966, 13, 220, 16, 25, 35907, 315, 279, 4007, 38152, 13, 128257, 198, 128256, 78191, 198, 16778, 11376, 7177, 649, 7168, 902, 1274, 449, 62145, 596, 8624, 690, 2274, 25702, 53317, 323, 3284, 52857, 220, 972, 4038, 3010, 11, 4184, 311, 264, 502, 4007, 555, 549, 3218, 12074, 13, 578, 4007, 11, 4756, 304, 29098, 73133, 11, 11621, 311, 6029, 430, 11376, 4442, 16599, 68, 279, 25702, 18174, 430, 13980, 304, 1690, 11, 719, 539, 682, 11, 1274, 449, 62145, 596, 13, 763, 2500, 502, 4007, 4756, 3432, 304, 26545, 40023, 11, 279, 1890, 3495, 2128, 1766, 430, 24693, 323, 16003, 13537, 315, 8271, 13918, 3719, 1654, 283, 50185, 6957, 279, 4553, 8271, 304, 1274, 449, 62145, 596, 8624, 11, 8104, 4315, 1274, 449, 11376, 5435, 13, 578, 1403, 7978, 3871, 1501, 1268, 18151, 323, 4442, 311, 279, 8271, 596, 19358, 1234, 11828, 279, 25702, 53317, 10534, 555, 1690, 1274, 449, 62145, 596, 8624, 13, 30982, 3229, 2999, 13, 23950, 7723, 1901, 847, 8115, 320, 35, 46744, 8483, 14821, 11, 549, 3218, 16657, 15992, 10181, 315, 32359, 36781, 8, 1071, 25, 330, 1687, 617, 1766, 430, 1274, 449, 62145, 596, 8624, 889, 617, 9302, 5435, 527, 810, 4461, 311, 636, 52857, 11, 323, 430, 8111, 311, 387, 11497, 555, 16940, 4442, 311, 872, 8271, 19358, 13, 330, 69162, 7177, 2643, 3493, 603, 449, 264, 3321, 315, 6776, 311, 7168, 62145, 596, 52857, 1603, 433, 12302, 11, 902, 1253, 1520, 603, 1505, 5627, 311, 3009, 279, 25702, 18174, 1603, 433, 596, 2288, 3389, 1210, 1789, 279, 29098, 73133, 5684, 11, 4756, 6931, 420, 2305, 11, 279, 12074, 20041, 220, 2813, 1274, 449, 62145, 596, 8624, 323, 1766, 430, 4382, 11376, 7177, 19698, 889, 1053, 733, 389, 311, 636, 52857, 1306, 264, 1060, 323, 264, 4376, 13, 423, 46744, 374, 264, 4279, 11, 92890, 13189, 315, 62145, 596, 8624, 11, 13240, 311, 7958, 17715, 220, 1135, 4, 315, 1274, 2949, 220, 605, 1667, 315, 264, 62145, 596, 23842, 13, 4314, 68102, 14955, 923, 4785, 311, 3766, 7978, 430, 1051, 2884, 520, 832, 892, 1486, 11, 902, 1047, 12090, 430, 5178, 304, 11376, 7177, 11, 16239, 17037, 1511, 8071, 27223, 323, 87572, 5448, 315, 19987, 323, 12875, 11, 574, 10815, 311, 279, 5326, 315, 25702, 18174, 13, 578, 502, 4007, 1101, 1766, 430, 1884, 889, 4024, 389, 311, 2274, 62145, 596, 52857, 1047, 18151, 304, 279, 19358, 315, 279, 8271, 11, 2737, 304, 5789, 23343, 311, 11376, 323, 5044, 13, 578, 12074, 1511, 6051, 8040, 5528, 311, 49586, 61802, 11944, 52460, 43739, 11, 28462, 1124, 311, 3820, 709, 279, 5674, 311, 279, 8271, 596, 4251, 5030, 13, 578, 12074, 11054, 4251, 5030, 5674, 311, 1063, 315, 279, 1317, 74908, 19358, 21583, 279, 4156, 323, 1203, 315, 279, 8271, 11, 902, 8779, 279, 8271, 311, 734, 439, 264, 87516, 4459, 4009, 13, 578, 26545, 40023, 4007, 6532, 220, 2421, 1274, 449, 62145, 596, 8624, 320, 1644, 315, 8884, 1047, 9302, 32403, 323, 1051, 8617, 45487, 311, 617, 264, 1579, 5326, 315, 52857, 8, 323, 220, 966, 9498, 12884, 439, 264, 2585, 1912, 11, 6832, 35202, 1051, 737, 3359, 1701, 52460, 43739, 13, 763, 279, 9498, 8271, 11, 1070, 374, 264, 26670, 1990, 1268, 3831, 279, 24693, 320, 47692, 8, 13537, 1990, 1403, 13918, 527, 11, 323, 1268, 1790, 1884, 1403, 13918, 527, 8599, 734, 750, 13, 3011, 59086, 374, 539, 14113, 4028, 279, 8271, 11, 439, 1070, 374, 1063, 8547, 315, 1654, 283, 12127, 304, 279, 9498, 8271, 11, 8104, 304, 5789, 6532, 304, 5190, 24747, 8863, 11, 902, 2643, 3493, 279, 25152, 311, 7431, 8278, 33811, 13, 25619, 1790, 1654, 283, 12127, 8111, 311, 387, 10815, 311, 8009, 20124, 13, 578, 12074, 1766, 430, 1274, 449, 62145, 596, 8624, 51713, 264, 5190, 8547, 315, 1654, 283, 12127, 4028, 279, 4459, 8271, 13, 56816, 520, 279, 1203, 315, 279, 8271, 11, 323, 2753, 28175, 5789, 11, 1047, 279, 1455, 1654, 283, 12127, 304, 62145, 596, 6978, 13, 62145, 596, 6978, 449, 9302, 32403, 1047, 810, 1654, 283, 12127, 304, 1063, 11, 719, 539, 682, 8271, 13918, 11, 8104, 304, 5044, 14228, 13918, 304, 279, 37015, 326, 15784, 13, 578, 3495, 2128, 1101, 1766, 4442, 311, 279, 5990, 315, 1063, 90351, 83189, 320, 32056, 9622, 15232, 8, 304, 1274, 520, 5326, 315, 25702, 18174, 11, 23377, 430, 44540, 369, 1884, 1380, 83189, 1253, 387, 4754, 11811, 369, 502, 5623, 22972, 369, 62145, 596, 52857, 13, 2876, 2915, 11, 1418, 66128, 374, 3967, 311, 387, 69702, 304, 62145, 596, 11, 279, 12074, 1766, 430, 1023, 90351, 83189, 2345, 582, 87348, 331, 22671, 11, 77130, 323, 6463, 329, 47738, 483, 2345, 52898, 8104, 11754, 304, 1274, 520, 5326, 315, 25702, 18174, 13, 2999, 13, 23950, 7723, 1071, 25, 330, 791, 1403, 16064, 3871, 1520, 603, 311, 3619, 1148, 596, 2133, 389, 304, 279, 35202, 315, 1274, 449, 62145, 596, 889, 3217, 25702, 18174, 11, 439, 433, 8111, 311, 387, 16625, 555, 264, 31085, 304, 279, 19358, 430, 34161, 2204, 8271, 13918, 1210, 2999, 13, 52479, 6863, 1226, 321, 320, 52, 3218, 16657, 15992, 10181, 315, 32359, 36781, 705, 10195, 3229, 315, 2225, 16064, 11, 1071, 25, 330, 8140, 14955, 1436, 387, 15525, 369, 14830, 19622, 11, 555, 9204, 430, 11376, 7177, 649, 1520, 603, 10765, 889, 584, 1288, 387, 25103, 369, 19622, 315, 502, 11217, 430, 2643, 387, 3025, 311, 6435, 62145, 596, 13, 1628, 13967, 422, 7524, 22972, 527, 1766, 11, 1243, 1521, 4382, 7177, 1253, 1520, 603, 10765, 889, 690, 8935, 505, 902, 22972, 1210, 220, 128257, 198 ]

2,302

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Molecular semiconductors are increasingly used in devices, but understanding of elementary nanoscopic processes in molecular film growth is in its infancy. Here we use real-time in situ specular and diffuse X-ray scattering in combination with kinetic Monte Carlo simulations to study C 60 nucleation and multilayer growth. We determine a self-consistent set of energy parameters describing both intra- and interlayer diffusion processes in C 60 growth. This approach yields an effective Ehrlich–Schwoebel barrier of E ES =110 meV, diffusion barrier of E D =540 meV and binding energy of E B =130 meV. Analysing the particle-resolved dynamics, we find that the lateral diffusion is similar to colloids, but characterized by an atom-like Schwoebel barrier. Our results contribute to a fundamental understanding of molecular growth processes in a system, which forms an important intermediate case between atoms and colloids. Introduction Understanding the growth of molecular materials such as the prototypical molecular semiconductor fullerene C 60 (refs 1 , 2 ) on surfaces is an indispensable prerequisite for the rational design of complex nanomaterials from molecular building blocks, as well as for optimizing the performance in thin-film-based applications such as solar cells 3 , 4 , 5 and organic light-emitting diodes 6 , 7 . So far, molecular self-assembly and growth 8 has often been described by scaling laws to describe surface roughening and evolving island densities 9 , 10 . On a molecular level, a range of studies have elucidated the kinetics of diffusion and nucleation (see, for example, refs 11 , 12 , 13 , 14 , 15 , 16 ) and the Ehrlich–Schwoebel barrier for interlayer transport across a molecular step edge 11 , 17 , 18 (see Fig. 1). In the last decades, the energy barriers for atomic growth have been refined to take into account the local neighbourhood during multilayer growth, for example, by including concerted gliding of islands or by distinguishing between different step-edge orientations 19 , 20 , 21 , 22 . Yet to date, there is no organic compound for which even the ‘minimal’ set of the three parameters diffusion barrier, lateral binding energy and Ehrlich–Schwoebel barrier have been simultaneously quantified to describe multilayer molecular growth. Therefore, predictive simulations of the rate- and temperature-dependent morphology in molecular multilayer growth have so far been impossible, contrary to the situation for elemental atomic systems 23 , 24 , 25 and colloids 26 , 27 , 28 . Importantly, C 60 exhibits properties in between those of atoms and colloids, which makes it a test case of fundamental relevance. On one hand, its van der Waals diameter of 1 nm 29 is closer to atomic dimensions than to the μm length scale of colloidal systems. On the other hand, C 60 resembles colloids with its short-range nature of the effective centre-of-mass interactions 30 , which decay as −1/ r 9 with r being the centre-of-mass separation stemming from the averaged van der Waals interactions (approximately −1/ r 6 ) between the individual carbon interaction sites 31 . These forces between atomic, molecular or colloidal building blocks are of prime importance for kinetic growth processes, similar to their role in equilibrium phase behaviour and self-assembly 32 , 33 . For example, C 60 lacks a stable equilibrium liquid phase 30 , contrary to most elemental atomic systems. C 60 is therefore not only relevant for device applications, but also an important, fundamentally unique material bridging atoms and colloids. From the experimental side, a particular challenge in studying C 60 growth is that post-growth changes make the interruption of this non-equilibrium process to image different growth stages potentially misleading. It is therefore essential to use in situ real-time techniques. In this article, we employ the combination of specular X-ray growth oscillations 34 with real-time diffuse X-ray scattering 35 , 36 to simultaneously follow the vertical and lateral morphology during growth. Further understanding on a nanoscale level is provided by kinetic Monte Carlo (KMC) simulations of coarse-grained C 60 molecules without internal degrees of freedom. Then, the three relevant parameters determined by a fit of the data are the Ehrlich–Schwoebel barrier, the surface diffusion barrier and the lateral binding energy (see Fig. 1 ). With these parameters alone, we achieve quantitative agreement with the experimental data, enabling us to predict the rate-, temperature- and thickness dependency of the film morphology. Moreover, our analysis demonstrates that the short interaction range of C 60 as compared with atoms affects the relative heights of diffusion barrier and binding energy and results in comparatively long diffusion times. However, unlike the colloidal systems, C 60 has a true energetic Ehrlich–Schwoebel barrier, rather than the pseudobarrier that colloids display 26 . Figure 1: Surface processes in C 60 growth. The diffusion barrier E D , binding energy E B and Ehrlich–Schwoebel barrier E ES determine island nucleation and interlayer transport in multilayer growth. Included are numerical values determined by fitting the experiment using KMC simulations. Full size image Results Experimental results for the layer-by-layer growth of C 60 on mica For a comprehensive understanding of the processes during growth, the surface morphology has to be measured on the molecular length scale with an experimental time resolution that is fast compared with the minute timescale of the deposition of a monolayer. Interrupting growth to take a series of real-space microscopy images can be problematic, as the kinetics can be altered. For our system of C 60 on top of a closed first C 60 layer on mica, this route is indeed impossible because of quick dewetting effects characterized by a time constant of ~10 min. Also, in situ low-energy electron microscopy unfortunately—while very successfully used in a range of studies 37 , 38 —cannot be applied due to charging effects on mica. Therefore, we use X-ray scattering that can be performed non-invasively during growth and yields time-resolved information about the layer formation. This is extracted through specular reflectivity measurements at the so-called anti-Bragg position of C 60 (see Fig. 2a ) corresponding to half the Bragg", "role": "user" }, { "content": "Using DESY's ultrabright X-ray source PETRA III, researchers have observed in real-time how football-shaped carbon molecules arrange themselves into ultra-smooth layers. Together with theoretical simulations, the investigation reveals the fundamentals of this growth process for the first time in detail, as the team around Sebastian Bommel (DESY and Humboldt Universität zu Berlin) and Nicola Kleppmann (Technische Universität Berlin) reports in the scientific journal Nature Communications. This knowledge will eventually enable scientists to tailor nanostructures from these carbon molecules for certain applications, which play an increasing role in the promising field of plastic electronics. The team consisted of scientists from Humboldt-Universität zu Berlin, Technische Universität Berlin, Universität Tübingen and DESY. The scientists studied so called buckyballs. Buckyballs are spherical molecules, which consist of 60 carbon atoms (C60). Because they are reminiscent of American architect Richard Buckminster Fuller's geodesic domes, they were christened buckminsterfullerenes or \"buckyballs\" for short. With their structure of alternating pentagons and hexagons, they also resemble tiny molecular footballs. Using DESY's X-ray source PETRA III, the researchers observed how buckyballs settle on a substrate from a molecular vapour. In fact, one layer after another, the carbon molecules grow predominantly in islands only one molecule high and barely form tower-like structures..\"The first layer is 99% complete before 1% of the second layer is formed,\" explains DESY researcher Bommel, who is completing his doctorate in Prof. Stefan Kowarik's group at the Humboldt Universität zu Berlin. This is how extremely smooth layers form. \"To really observe the growth process in real-time, we needed to measure the surfaces on a molecular level faster than a single layer grows, which takes place in about a minute,\" says co-author Dr. Stephan Roth, head of the P03 measuring station, where the experiments were carried out. \"X-ray investigations are well suited, as they can trace the growth process in detail.\" \"In order to understand the evolution of the surface morphology at the molecular level, we carried out extensive simulations in a non-equilibrium system. These describe the entire growth process of C60 molecules into a lattice structure,\" explains Kleppmann, PhD student in Prof. Sabine Klapp's group at the Institute of Theoretical Physics, Technische Universität Berlin. \"Our results provide fundamental insights into the molecular growth processes of a system that forms an important link between the world of atoms and that of colloids.\" Through the combination of experimental observations and theoretical simulations, the scientists determined for the first time three major energy parameters simultaneously for such a system: the binding energy between the football molecules, the so-called \"diffusion barrier,\" which a molecule must overcome if it wants to move on the surface, and the Ehrlich-Schwoebel barrier, which a molecule must overcome if it lands on an island and wants to hop down from that island. \"With these values, we now really understand for the first time how such nanostructures come into existence,\" stresses Bommel. \"Using this knowledge, it is conceivable that these structures can selectively be grown in the future: How must I change my temperature and deposition rate parameters so that an island of a particular size will grow. This could, for example, be interesting for organic solar cells, which contain C60.\" The researchers intend to explore the growth of other molecular systems in the future using the same methods. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Molecular semiconductors are increasingly used in devices, but understanding of elementary nanoscopic processes in molecular film growth is in its infancy. Here we use real-time in situ specular and diffuse X-ray scattering in combination with kinetic Monte Carlo simulations to study C 60 nucleation and multilayer growth. We determine a self-consistent set of energy parameters describing both intra- and interlayer diffusion processes in C 60 growth. This approach yields an effective Ehrlich–Schwoebel barrier of E ES =110 meV, diffusion barrier of E D =540 meV and binding energy of E B =130 meV. Analysing the particle-resolved dynamics, we find that the lateral diffusion is similar to colloids, but characterized by an atom-like Schwoebel barrier. Our results contribute to a fundamental understanding of molecular growth processes in a system, which forms an important intermediate case between atoms and colloids. Introduction Understanding the growth of molecular materials such as the prototypical molecular semiconductor fullerene C 60 (refs 1 , 2 ) on surfaces is an indispensable prerequisite for the rational design of complex nanomaterials from molecular building blocks, as well as for optimizing the performance in thin-film-based applications such as solar cells 3 , 4 , 5 and organic light-emitting diodes 6 , 7 . So far, molecular self-assembly and growth 8 has often been described by scaling laws to describe surface roughening and evolving island densities 9 , 10 . On a molecular level, a range of studies have elucidated the kinetics of diffusion and nucleation (see, for example, refs 11 , 12 , 13 , 14 , 15 , 16 ) and the Ehrlich–Schwoebel barrier for interlayer transport across a molecular step edge 11 , 17 , 18 (see Fig. 1). In the last decades, the energy barriers for atomic growth have been refined to take into account the local neighbourhood during multilayer growth, for example, by including concerted gliding of islands or by distinguishing between different step-edge orientations 19 , 20 , 21 , 22 . Yet to date, there is no organic compound for which even the ‘minimal’ set of the three parameters diffusion barrier, lateral binding energy and Ehrlich–Schwoebel barrier have been simultaneously quantified to describe multilayer molecular growth. Therefore, predictive simulations of the rate- and temperature-dependent morphology in molecular multilayer growth have so far been impossible, contrary to the situation for elemental atomic systems 23 , 24 , 25 and colloids 26 , 27 , 28 . Importantly, C 60 exhibits properties in between those of atoms and colloids, which makes it a test case of fundamental relevance. On one hand, its van der Waals diameter of 1 nm 29 is closer to atomic dimensions than to the μm length scale of colloidal systems. On the other hand, C 60 resembles colloids with its short-range nature of the effective centre-of-mass interactions 30 , which decay as −1/ r 9 with r being the centre-of-mass separation stemming from the averaged van der Waals interactions (approximately −1/ r 6 ) between the individual carbon interaction sites 31 . These forces between atomic, molecular or colloidal building blocks are of prime importance for kinetic growth processes, similar to their role in equilibrium phase behaviour and self-assembly 32 , 33 . For example, C 60 lacks a stable equilibrium liquid phase 30 , contrary to most elemental atomic systems. C 60 is therefore not only relevant for device applications, but also an important, fundamentally unique material bridging atoms and colloids. From the experimental side, a particular challenge in studying C 60 growth is that post-growth changes make the interruption of this non-equilibrium process to image different growth stages potentially misleading. It is therefore essential to use in situ real-time techniques. In this article, we employ the combination of specular X-ray growth oscillations 34 with real-time diffuse X-ray scattering 35 , 36 to simultaneously follow the vertical and lateral morphology during growth. Further understanding on a nanoscale level is provided by kinetic Monte Carlo (KMC) simulations of coarse-grained C 60 molecules without internal degrees of freedom. Then, the three relevant parameters determined by a fit of the data are the Ehrlich–Schwoebel barrier, the surface diffusion barrier and the lateral binding energy (see Fig. 1 ). With these parameters alone, we achieve quantitative agreement with the experimental data, enabling us to predict the rate-, temperature- and thickness dependency of the film morphology. Moreover, our analysis demonstrates that the short interaction range of C 60 as compared with atoms affects the relative heights of diffusion barrier and binding energy and results in comparatively long diffusion times. However, unlike the colloidal systems, C 60 has a true energetic Ehrlich–Schwoebel barrier, rather than the pseudobarrier that colloids display 26 . Figure 1: Surface processes in C 60 growth. The diffusion barrier E D , binding energy E B and Ehrlich–Schwoebel barrier E ES determine island nucleation and interlayer transport in multilayer growth. Included are numerical values determined by fitting the experiment using KMC simulations. Full size image Results Experimental results for the layer-by-layer growth of C 60 on mica For a comprehensive understanding of the processes during growth, the surface morphology has to be measured on the molecular length scale with an experimental time resolution that is fast compared with the minute timescale of the deposition of a monolayer. Interrupting growth to take a series of real-space microscopy images can be problematic, as the kinetics can be altered. For our system of C 60 on top of a closed first C 60 layer on mica, this route is indeed impossible because of quick dewetting effects characterized by a time constant of ~10 min. Also, in situ low-energy electron microscopy unfortunately—while very successfully used in a range of studies 37 , 38 —cannot be applied due to charging effects on mica. Therefore, we use X-ray scattering that can be performed non-invasively during growth and yields time-resolved information about the layer formation. This is extracted through specular reflectivity measurements at the so-called anti-Bragg position of C 60 (see Fig. 2a ) corresponding to half the Bragg<|im_end|> <|im_start|>assistant Using DESY's ultrabright X-ray source PETRA III, researchers have observed in real-time how football-shaped carbon molecules arrange themselves into ultra-smooth layers. Together with theoretical simulations, the investigation reveals the fundamentals of this growth process for the first time in detail, as the team around Sebastian Bommel (DESY and Humboldt Universität zu Berlin) and Nicola Kleppmann (Technische Universität Berlin) reports in the scientific journal Nature Communications. This knowledge will eventually enable scientists to tailor nanostructures from these carbon molecules for certain applications, which play an increasing role in the promising field of plastic electronics. The team consisted of scientists from Humboldt-Universität zu Berlin, Technische Universität Berlin, Universität Tübingen and DESY. The scientists studied so called buckyballs. Buckyballs are spherical molecules, which consist of 60 carbon atoms (C60). Because they are reminiscent of American architect Richard Buckminster Fuller's geodesic domes, they were christened buckminsterfullerenes or "buckyballs" for short. With their structure of alternating pentagons and hexagons, they also resemble tiny molecular footballs. Using DESY's X-ray source PETRA III, the researchers observed how buckyballs settle on a substrate from a molecular vapour. In fact, one layer after another, the carbon molecules grow predominantly in islands only one molecule high and barely form tower-like structures.."The first layer is 99% complete before 1% of the second layer is formed," explains DESY researcher Bommel, who is completing his doctorate in Prof. Stefan Kowarik's group at the Humboldt Universität zu Berlin. This is how extremely smooth layers form. "To really observe the growth process in real-time, we needed to measure the surfaces on a molecular level faster than a single layer grows, which takes place in about a minute," says co-author Dr. Stephan Roth, head of the P03 measuring station, where the experiments were carried out. "X-ray investigations are well suited, as they can trace the growth process in detail." "In order to understand the evolution of the surface morphology at the molecular level, we carried out extensive simulations in a non-equilibrium system. These describe the entire growth process of C60 molecules into a lattice structure," explains Kleppmann, PhD student in Prof. Sabine Klapp's group at the Institute of Theoretical Physics, Technische Universität Berlin. "Our results provide fundamental insights into the molecular growth processes of a system that forms an important link between the world of atoms and that of colloids." Through the combination of experimental observations and theoretical simulations, the scientists determined for the first time three major energy parameters simultaneously for such a system: the binding energy between the football molecules, the so-called "diffusion barrier," which a molecule must overcome if it wants to move on the surface, and the Ehrlich-Schwoebel barrier, which a molecule must overcome if it lands on an island and wants to hop down from that island. "With these values, we now really understand for the first time how such nanostructures come into existence," stresses Bommel. "Using this knowledge, it is conceivable that these structures can selectively be grown in the future: How must I change my temperature and deposition rate parameters so that an island of a particular size will grow. This could, for example, be interesting for organic solar cells, which contain C60." The researchers intend to explore the growth of other molecular systems in the future using the same methods. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 60825, 5347, 1965, 1076, 1105, 527, 15098, 1511, 304, 7766, 11, 719, 8830, 315, 36256, 20622, 84667, 11618, 304, 31206, 4632, 6650, 374, 304, 1202, 86617, 13, 5810, 584, 1005, 1972, 7394, 304, 10109, 86517, 323, 55517, 1630, 30630, 72916, 304, 10824, 449, 71423, 46867, 58870, 47590, 311, 4007, 356, 220, 1399, 31484, 367, 323, 2814, 321, 1155, 6650, 13, 1226, 8417, 264, 659, 69604, 18620, 743, 315, 4907, 5137, 23524, 2225, 50938, 12, 323, 958, 10546, 58430, 11618, 304, 356, 220, 1399, 6650, 13, 1115, 5603, 36508, 459, 7524, 469, 4171, 6915, 4235, 31224, 1146, 3141, 301, 22881, 315, 469, 19844, 284, 5120, 757, 53, 11, 58430, 22881, 315, 469, 423, 284, 17048, 757, 53, 323, 11212, 4907, 315, 469, 426, 284, 5894, 757, 53, 13, 20017, 1065, 287, 279, 19320, 11849, 8905, 30295, 11, 584, 1505, 430, 279, 45569, 58430, 374, 4528, 311, 82048, 3447, 11, 719, 32971, 555, 459, 19670, 12970, 5124, 1146, 3141, 301, 22881, 13, 5751, 3135, 17210, 311, 264, 16188, 8830, 315, 31206, 6650, 11618, 304, 264, 1887, 11, 902, 7739, 459, 3062, 29539, 1162, 1990, 33299, 323, 82048, 3447, 13, 29438, 46551, 279, 6650, 315, 31206, 7384, 1778, 439, 279, 1760, 88167, 31206, 87836, 88018, 1994, 356, 220, 1399, 320, 16541, 220, 16, 1174, 220, 17, 883, 389, 27529, 374, 459, 64284, 80884, 369, 279, 25442, 2955, 315, 6485, 20622, 316, 2229, 82, 505, 31206, 4857, 10215, 11, 439, 1664, 439, 369, 74142, 279, 5178, 304, 15792, 2269, 9672, 6108, 8522, 1778, 439, 13238, 7917, 220, 18, 1174, 220, 19, 1174, 220, 20, 323, 17808, 3177, 37612, 15154, 1891, 2601, 220, 21, 1174, 220, 22, 662, 2100, 3117, 11, 31206, 659, 12, 15343, 323, 6650, 220, 23, 706, 3629, 1027, 7633, 555, 28041, 7016, 311, 7664, 7479, 11413, 6147, 323, 42028, 13218, 90816, 220, 24, 1174, 220, 605, 662, 1952, 264, 31206, 2237, 11, 264, 2134, 315, 7978, 617, 97298, 660, 279, 91468, 315, 58430, 323, 31484, 367, 320, 4151, 11, 369, 3187, 11, 44243, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 1174, 220, 845, 883, 323, 279, 469, 4171, 6915, 4235, 31224, 1146, 3141, 301, 22881, 369, 958, 10546, 7710, 4028, 264, 31206, 3094, 6964, 220, 806, 1174, 220, 1114, 1174, 220, 972, 320, 4151, 23966, 13, 220, 16, 570, 763, 279, 1566, 11026, 11, 279, 4907, 30740, 369, 25524, 6650, 617, 1027, 38291, 311, 1935, 1139, 2759, 279, 2254, 40442, 2391, 2814, 321, 1155, 6650, 11, 369, 3187, 11, 555, 2737, 97666, 2840, 6714, 315, 30100, 477, 555, 86055, 1990, 2204, 3094, 48448, 89935, 220, 777, 1174, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 662, 14968, 311, 2457, 11, 1070, 374, 912, 17808, 24549, 369, 902, 1524, 279, 3451, 93707, 529, 743, 315, 279, 2380, 5137, 58430, 22881, 11, 45569, 11212, 4907, 323, 469, 4171, 6915, 4235, 31224, 1146, 3141, 301, 22881, 617, 1027, 25291, 10484, 1908, 311, 7664, 2814, 321, 1155, 31206, 6650, 13, 15636, 11, 60336, 47590, 315, 279, 4478, 12, 323, 9499, 43918, 79612, 304, 31206, 2814, 321, 1155, 6650, 617, 779, 3117, 1027, 12266, 11, 26102, 311, 279, 6671, 369, 62235, 25524, 6067, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 323, 82048, 3447, 220, 1627, 1174, 220, 1544, 1174, 220, 1591, 662, 13516, 18007, 11, 356, 220, 1399, 50829, 6012, 304, 1990, 1884, 315, 33299, 323, 82048, 3447, 11, 902, 3727, 433, 264, 1296, 1162, 315, 16188, 41961, 13, 1952, 832, 1450, 11, 1202, 5355, 2761, 29614, 1147, 23899, 315, 220, 16, 26807, 220, 1682, 374, 12401, 311, 25524, 15696, 1109, 311, 279, 33983, 76, 3160, 5569, 315, 82048, 26966, 6067, 13, 1952, 279, 1023, 1450, 11, 356, 220, 1399, 53291, 82048, 3447, 449, 1202, 2875, 31608, 7138, 315, 279, 7524, 12541, 8838, 1474, 395, 22639, 220, 966, 1174, 902, 31815, 439, 25173, 16, 14, 436, 220, 24, 449, 436, 1694, 279, 12541, 8838, 1474, 395, 25768, 77044, 505, 279, 37956, 5355, 2761, 29614, 1147, 22639, 320, 97836, 25173, 16, 14, 436, 220, 21, 883, 1990, 279, 3927, 12782, 16628, 6732, 220, 2148, 662, 4314, 8603, 1990, 25524, 11, 31206, 477, 82048, 26966, 4857, 10215, 527, 315, 10461, 12939, 369, 71423, 6650, 11618, 11, 4528, 311, 872, 3560, 304, 56411, 10474, 17432, 323, 659, 12, 15343, 220, 843, 1174, 220, 1644, 662, 1789, 3187, 11, 356, 220, 1399, 37856, 264, 15528, 56411, 14812, 10474, 220, 966, 1174, 26102, 311, 1455, 62235, 25524, 6067, 13, 356, 220, 1399, 374, 9093, 539, 1193, 9959, 369, 3756, 8522, 11, 719, 1101, 459, 3062, 11, 43593, 5016, 3769, 77847, 3252, 33299, 323, 82048, 3447, 13, 5659, 279, 22772, 3185, 11, 264, 4040, 8815, 304, 21630, 356, 220, 1399, 6650, 374, 430, 1772, 2427, 19632, 4442, 1304, 279, 75103, 315, 420, 2536, 63359, 46780, 1920, 311, 2217, 2204, 6650, 18094, 13893, 38309, 13, 1102, 374, 9093, 7718, 311, 1005, 304, 10109, 1972, 7394, 12823, 13, 763, 420, 4652, 11, 584, 3539, 279, 10824, 315, 86517, 1630, 30630, 6650, 43524, 811, 220, 1958, 449, 1972, 7394, 55517, 1630, 30630, 72916, 220, 1758, 1174, 220, 1927, 311, 25291, 1833, 279, 12414, 323, 45569, 79612, 2391, 6650, 13, 15903, 8830, 389, 264, 20622, 437, 2296, 2237, 374, 3984, 555, 71423, 46867, 58870, 320, 42, 11865, 8, 47590, 315, 50347, 25313, 2692, 356, 220, 1399, 35715, 2085, 5419, 12628, 315, 11542, 13, 5112, 11, 279, 2380, 9959, 5137, 11075, 555, 264, 5052, 315, 279, 828, 527, 279, 469, 4171, 6915, 4235, 31224, 1146, 3141, 301, 22881, 11, 279, 7479, 58430, 22881, 323, 279, 45569, 11212, 4907, 320, 4151, 23966, 13, 220, 16, 7609, 3161, 1521, 5137, 7636, 11, 584, 11322, 47616, 9306, 449, 279, 22772, 828, 11, 28462, 603, 311, 7168, 279, 4478, 37619, 9499, 12, 323, 26839, 24999, 315, 279, 4632, 79612, 13, 23674, 11, 1057, 6492, 32216, 430, 279, 2875, 16628, 2134, 315, 356, 220, 1399, 439, 7863, 449, 33299, 22223, 279, 8844, 36394, 315, 58430, 22881, 323, 11212, 4907, 323, 3135, 304, 71561, 1317, 58430, 3115, 13, 4452, 11, 20426, 279, 82048, 26966, 6067, 11, 356, 220, 1399, 706, 264, 837, 45955, 469, 4171, 6915, 4235, 31224, 1146, 3141, 301, 22881, 11, 4856, 1109, 279, 51743, 32493, 7401, 430, 82048, 3447, 3113, 220, 1627, 662, 19575, 220, 16, 25, 28061, 11618, 304, 356, 220, 1399, 6650, 13, 578, 58430, 22881, 469, 423, 1174, 11212, 4907, 469, 426, 323, 469, 4171, 6915, 4235, 31224, 1146, 3141, 301, 22881, 469, 19844, 8417, 13218, 31484, 367, 323, 958, 10546, 7710, 304, 2814, 321, 1155, 6650, 13, 47064, 527, 35876, 2819, 11075, 555, 27442, 279, 9526, 1701, 735, 11865, 47590, 13, 8797, 1404, 2217, 18591, 57708, 3135, 369, 279, 6324, 14656, 48435, 6650, 315, 356, 220, 1399, 389, 296, 3074, 1789, 264, 16195, 8830, 315, 279, 11618, 2391, 6650, 11, 279, 7479, 79612, 706, 311, 387, 17303, 389, 279, 31206, 3160, 5569, 449, 459, 22772, 892, 11175, 430, 374, 5043, 7863, 449, 279, 9568, 3115, 2296, 315, 279, 65374, 315, 264, 1647, 337, 1155, 13, 22933, 287, 6650, 311, 1935, 264, 4101, 315, 1972, 29047, 92914, 5448, 649, 387, 36033, 11, 439, 279, 91468, 649, 387, 29852, 13, 1789, 1057, 1887, 315, 356, 220, 1399, 389, 1948, 315, 264, 8036, 1176, 356, 220, 1399, 6324, 389, 296, 3074, 11, 420, 6149, 374, 13118, 12266, 1606, 315, 4062, 67532, 52189, 6372, 32971, 555, 264, 892, 6926, 315, 4056, 605, 1332, 13, 7429, 11, 304, 10109, 3428, 65487, 17130, 92914, 26907, 2345, 3556, 1633, 7946, 1511, 304, 264, 2134, 315, 7978, 220, 1806, 1174, 220, 1987, 2001, 34360, 387, 9435, 4245, 311, 23468, 6372, 389, 296, 3074, 13, 15636, 11, 584, 1005, 1630, 30630, 72916, 430, 649, 387, 10887, 2536, 3502, 4378, 3210, 2391, 6650, 323, 36508, 892, 11849, 8905, 2038, 922, 279, 6324, 18488, 13, 1115, 374, 28532, 1555, 86517, 8881, 1968, 22323, 520, 279, 779, 19434, 7294, 7826, 4193, 70, 2361, 315, 356, 220, 1399, 320, 4151, 23966, 13, 220, 17, 64, 883, 12435, 311, 4376, 279, 3320, 16094, 128257, 198, 128256, 78191, 198, 16834, 13022, 56, 596, 37232, 370, 1315, 1630, 30630, 2592, 50359, 5726, 14767, 11, 12074, 617, 13468, 304, 1972, 7394, 1268, 9141, 35831, 12782, 35715, 31993, 5694, 1139, 24955, 4773, 6627, 13931, 13, 32255, 449, 32887, 47590, 11, 279, 8990, 21667, 279, 57940, 315, 420, 6650, 1920, 369, 279, 1176, 892, 304, 7872, 11, 439, 279, 2128, 2212, 44609, 426, 20372, 301, 320, 1170, 18923, 323, 88409, 94144, 15915, 37714, 6529, 20437, 8, 323, 79541, 27446, 604, 18022, 320, 29356, 10782, 15915, 37714, 20437, 8, 6821, 304, 279, 12624, 8486, 22037, 26545, 13, 1115, 6677, 690, 9778, 7431, 14248, 311, 52056, 51593, 47194, 505, 1521, 12782, 35715, 369, 3738, 8522, 11, 902, 1514, 459, 7859, 3560, 304, 279, 26455, 2115, 315, 12466, 31591, 13, 578, 2128, 44660, 315, 14248, 505, 88409, 94144, 12, 65715, 37714, 6529, 20437, 11, 7146, 10782, 15915, 37714, 20437, 11, 15915, 37714, 350, 2448, 7278, 268, 323, 13022, 56, 13, 578, 14248, 20041, 779, 2663, 22786, 88, 46618, 13, 426, 10279, 46618, 527, 65251, 35715, 11, 902, 6824, 315, 220, 1399, 12782, 33299, 320, 34, 1399, 570, 9393, 814, 527, 56085, 315, 3778, 11726, 12131, 27156, 41478, 71569, 596, 3980, 2601, 292, 4824, 288, 11, 814, 1051, 26853, 6901, 22786, 41478, 9054, 17848, 288, 477, 330, 65, 10279, 46618, 1, 369, 2875, 13, 3161, 872, 6070, 315, 73462, 20801, 351, 2439, 323, 12651, 351, 2439, 11, 814, 1101, 52280, 13987, 31206, 9141, 82, 13, 12362, 13022, 56, 596, 1630, 30630, 2592, 50359, 5726, 14767, 11, 279, 12074, 13468, 1268, 22786, 88, 46618, 25760, 389, 264, 54057, 505, 264, 31206, 68857, 414, 13, 763, 2144, 11, 832, 6324, 1306, 2500, 11, 279, 12782, 35715, 3139, 47904, 304, 30100, 1193, 832, 43030, 1579, 323, 20025, 1376, 21970, 12970, 14726, 38526, 791, 1176, 6324, 374, 220, 1484, 4, 4686, 1603, 220, 16, 4, 315, 279, 2132, 6324, 374, 14454, 1359, 15100, 13022, 56, 32185, 426, 20372, 301, 11, 889, 374, 27666, 813, 10896, 349, 304, 8626, 13, 50002, 735, 363, 277, 1609, 596, 1912, 520, 279, 88409, 94144, 15915, 37714, 6529, 20437, 13, 1115, 374, 1268, 9193, 11113, 13931, 1376, 13, 330, 1271, 2216, 23846, 279, 6650, 1920, 304, 1972, 7394, 11, 584, 4460, 311, 6767, 279, 27529, 389, 264, 31206, 2237, 10819, 1109, 264, 3254, 6324, 28815, 11, 902, 5097, 2035, 304, 922, 264, 9568, 1359, 2795, 1080, 43802, 2999, 13, 39464, 37512, 11, 2010, 315, 279, 393, 2839, 30090, 8216, 11, 1405, 279, 21896, 1051, 11953, 704, 13, 330, 55, 30630, 26969, 527, 1664, 32599, 11, 439, 814, 649, 11917, 279, 6650, 1920, 304, 7872, 1210, 330, 644, 2015, 311, 3619, 279, 15740, 315, 279, 7479, 79612, 520, 279, 31206, 2237, 11, 584, 11953, 704, 16781, 47590, 304, 264, 2536, 63359, 46780, 1887, 13, 4314, 7664, 279, 4553, 6650, 1920, 315, 356, 1399, 35715, 1139, 264, 55372, 6070, 1359, 15100, 27446, 604, 18022, 11, 30661, 5575, 304, 8626, 13, 21252, 483, 29041, 680, 596, 1912, 520, 279, 10181, 315, 578, 91867, 28415, 11, 7146, 10782, 15915, 37714, 20437, 13, 330, 8140, 3135, 3493, 16188, 26793, 1139, 279, 31206, 6650, 11618, 315, 264, 1887, 430, 7739, 459, 3062, 2723, 1990, 279, 1917, 315, 33299, 323, 430, 315, 82048, 3447, 1210, 17331, 279, 10824, 315, 22772, 24654, 323, 32887, 47590, 11, 279, 14248, 11075, 369, 279, 1176, 892, 2380, 3682, 4907, 5137, 25291, 369, 1778, 264, 1887, 25, 279, 11212, 4907, 1990, 279, 9141, 35715, 11, 279, 779, 19434, 330, 13798, 7713, 22881, 1359, 902, 264, 43030, 2011, 23075, 422, 433, 6944, 311, 3351, 389, 279, 7479, 11, 323, 279, 469, 4171, 6915, 6354, 331, 1146, 3141, 301, 22881, 11, 902, 264, 43030, 2011, 23075, 422, 433, 12098, 389, 459, 13218, 323, 6944, 311, 7598, 1523, 505, 430, 13218, 13, 330, 2409, 1521, 2819, 11, 584, 1457, 2216, 3619, 369, 279, 1176, 892, 1268, 1778, 51593, 47194, 2586, 1139, 14209, 1359, 59623, 426, 20372, 301, 13, 330, 16834, 420, 6677, 11, 433, 374, 95883, 430, 1521, 14726, 649, 82775, 387, 15042, 304, 279, 3938, 25, 2650, 2011, 358, 2349, 856, 9499, 323, 65374, 4478, 5137, 779, 430, 459, 13218, 315, 264, 4040, 1404, 690, 3139, 13, 1115, 1436, 11, 369, 3187, 11, 387, 7185, 369, 17808, 13238, 7917, 11, 902, 6782, 356, 1399, 1210, 578, 12074, 30730, 311, 13488, 279, 6650, 315, 1023, 31206, 6067, 304, 279, 3938, 1701, 279, 1890, 5528, 13, 220, 128257, 198 ]

2,087

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract A new taxon of chasmosaurine ceratopsid demonstrates unexpected disparity in parietosquamosal frill shape among ceratopsid dinosaurs early in their evolutionary radiation. The new taxon is described based on two apomorphic squamosals collected from approximately time equivalent (approximately 77 million years old) sections of the upper Judith River Formation, Montana, and the lower Dinosaur Park Formation of Dinosaur Provincial Park, Alberta. It is referred to Chasmosaurinae based on the inferred elongate morphology. The typical chasmosaurine squamosal forms an obtuse triangle in dorsal view that tapers towards the posterolateral corner of the frill. In the dorsal view of the new taxon, the lateral margin of the squamosal is hatchet-shaped with the posterior portion modified into a constricted narrow bar that would have supported the lateral margin of a robust parietal. The new taxon represents the oldest chasmosaurine from Canada, and the first pre-Maastrichtian ceratopsid to have been collected on both sides of the Canada–US border, with a minimum north–south range of 380 km. This squamosal morphology would have given the frill of the new taxon a unique dorsal profile that represents evolutionary experimentation in frill signalling near the origin of chasmosaurine ceratopsids and reinforces biogeographic differences between northern and southern faunal provinces in the Campanian of North America. Access provided by DEAL DE / Springer Compact Clearingstelle Uni Freiburg _ Working on a manuscript? Avoid the common mistakes Introduction Ceratopsidae is a diverse clade of large bodied horned dinosaurs known from a well-sampled fossil record that spans the last 20 million years of the Mesozoic (Dodson et al. 2004 ). Ceratopsids are common in the Campanian–Maastrichtian deposits of western North America, where they range geographically from Coahuila, Mexico in the south ( Coahuilaceratops magnacuerna ; Loewen et al. 2010 ), to northern Alaska in the North ( Pachyrhinosaurus perotorum ; Fiorillo and Tykoski 2012 ). Marked latitudinal differences between the dinosaur faunas of the late Campanian has led to the recognition of northern (Wyoming and north) and southern (Utah and south) faunal provinces adjacent to the Western Interior Seaway during this time (Lehman 1987 , 1997 ; Sampson et al. 2010 ). Ceratopsians reached their maximum diversity during the Campanian and provide some of the strongest evidence for provinciality in Late Cretaceous dinosaurs (Sampson et al. 2010 , 2013 ; Farke 2013 ; Ryan 2013 ). Ceratopsidae consists of two major subclades that form a basal dichotomy of Centrosaurinae, or the ‘short-frilled’ ceratopsids, and Chasmosaurinae, which generally have relatively longer, less adorned frills. The two clades have traditionally been easily distinguished by the size and shape of their squamosals, which form the lateral segments of the parieto squamosal frill. Centrosaurines have broad, rectangular squamosals with typically concave contact surfaces (in adult-sized elements) for the parietal on the medial margin of the element. In contrast, chasmosaurines have an elongate, triangular squamosal with a corresponding contact surface for the parietal on the medioventral margin of the posterior squamosal. A recent morphometric study has confirmed that the distinctive squamosal shape of each subfamily is very conservative, with some minor proportional differences within each subfamily (Maiorino et al. 2013 ). Chasmosaurinae, in particular, exhibit little variation in squamosal shape, with little clear differentiation among taxa. Despite the importance of the parietosquamosal frill in ceratopsian systematics, the shape and ornamentation of the parietal appears to have been the locus of evolution within Ceratopsidae, with many taxa being diagnosed exclusively from this element. The squamosal defines the lateral shape of the frill and reflects more general differences in frill structure within the subfamilies; its conservative morphology suggests that this aspect of the frill was generally stable within each subfamily. A remarkable new chasmosaurine ceratopsid is described based on material collected from approximately time equivalent middle Campanian exposures of the Judith River Formation of Montana and the Dinosaur Park Formation of Alberta (Fig. 1 ). The new taxon is represented by two well-preserved squamosals and reveals previously unknown disparity in ceratopsid frill shape. It departs significantly from the conservative frill shape currently known in ceratopsids by an unusual modification of the squamosal that results in a hatchet-shaped lateral frill margin, rather than the convex-to-straight lateral margins that characterise all other known taxa. The new, apparently rare, taxon provides additional support for the faunal differentiation of northern and southern biogeographic provinces on Laramidia during the late Campanian. It also suggests that the evolutionary origin of the derived elongate triangular squamosal of chasmosaurs may have been more complex than previously believed. Fig. 1 Locality map of UALVP 54559 from the Dinosaur Park Formation of Dinosaur Provincial Park, Alberta, and ROM 64222 from the Judith River Formation of Montana. Alberta and Montana are silhouetted in black on the North America inset map. Google Earth image insets: Google, Digital Globe (Dinosaur Provincial Park) and Google, USDA Farm Service Agency (Montana) Full size image Institutional Abbreviations ROM, Royal Ontario Museum, Toronto, Canada UALVP, University of Alberta, Laboratory for Vertebrate Paleontology, Edmonton, Canada Systematic Paleontology Ornithischia Seeley 1888 Ceratopsia Marsh 1890 Neoceratopsia Sereno 1986 Ceratopsidae Marsh 1888 Chasmosaurinae Lambe 1915 Mercuriceratops gen. nov. urn:lsid:zoobank.org:act:70D4C099-1A46-4192-B8A1-D134E49D4861 Type species Mercuriceratops gemini sp. nov. Diagnosis Same as for species, by monotypy Mercuriceratops gemini sp. nov. urn:lsid:zoobank.org:act:70D4C099-1A46-4192-B8A1-D134E49D4861 Holotype ROM 64222: An almost complete right squamosal (Fig. 2a–d ) Fig. 2 Mercuriceratops gemini squamosal. ROM 64222 (holotype) in a , c line drawing and photograph of dorsal view; b , d line drawing and photograph of ventral view. Inset reconstruction of M. gemini in lateral view. es# episquamosal #. Scale bar = 20 cm Full size image Etymology Mercuri , in reference to winged helmet of the Roman messenger god Mercury, and ‘ceratops’, meaning horned face, a common suffix for genera of ceratopsid dinosaurs. Close carriage return. Gemini , from mythology, the twins Castor and Pollux were transformed into the constellation Gemini, referring to the twin specimens from Alberta and Montana. Referred material UALVP 54559, an incomplete right squamosal (Fig. 3a and b ). Fig. 3 Mercuriceratops gemini squamosal. UALVP 54559 (paratype) in a dorsal and b ventral views. es#", "role": "user" }, { "content": "Scientists have named a new species of horned dinosaur (ceratopsian) based on fossils collected from Montana in the United States and Alberta, Canada. Mercuriceratops (mer-cure-E-sare-ah-tops) gemini was approximately 6 meters (20 feet) long and weighed more than 2 tons. It lived about 77 million years ago during the Late Cretaceous Period. Research describing the new species is published online in the journal Naturwissenschaften. Mercuriceratops (Mercuri + ceratops) means \"Mercury horned-face,\" referring to the wing-like ornamentation on its head that resembles the wings on the helmet of the Roman god, Mercury. The name \"gemini\" refers to the almost identical twin specimens found in north central Montana and the UNESCO World Heritage Site, Dinosaur Provincial Park, in Alberta, Canada. Mercuriceratops had a parrot-like beak and probably had two long brow horns above its eyes. It was a plant-eating dinosaur. \"Mercuriceratops took a unique evolutionary path that shaped the large frill on the back of its skull into protruding wings like the decorative fins on classic 1950s cars. It definitively would have stood out from the herd during the Late Cretaceous,\" said lead author Dr. Michael Ryan, curator of vertebrate paleontology at The Cleveland Museum of Natural History. \"Horned dinosaurs in North America used their elaborate skull ornamentation to identify each other and to attract mates—not just for protection from predators. The wing-like protrusions on the sides of its frill may have offered male Mercuriceratops a competitive advantage in attracting mates.\" This image depicts Mercuriceratops gemini skull fossils from the right side of the frill. Credit: Naturwissenschaften \"The butterfly-shaped frill, or neck shield, of Mercuriceratops is unlike anything we have seen before,\" said co-author Dr. David Evans, curator of vertebrate palaeontology at the Royal Ontario Museum. \"Mercuriceratops shows that evolution gave rise to much greater variation in horned dinosaur headgear than we had previously suspected.\" The new dinosaur is described from skull fragments from two individuals collected from the Judith River Formation of Montana and the Dinosaur Park Formation of Alberta. The Montana specimen was originally collected on private land and acquired by the Royal Ontario Museum. The Alberta specimen was collected by Susan Owen-Kagen, a preparator in Dr. Philip Currie's lab at the University of Alberta. \"Susan showed me her specimen during one of my trips to Alberta,\" said Ryan. \"When I saw it, I instantly recognized it as being from the same type of dinosaur that the Royal Ontario Museum had from Montana.\" The Alberta specimen confirmed that the fossil from Montana was not a pathological specimen, nor had it somehow been distorted during the process of fossilization,\" said Dr. Philip Currie, professor and Canada research chair in dinosaur paleobiology at the University of Alberta. \"The two fossils—squamosal bones from the side of the frill—have all the features you would expect, just presented in a unique shape.\" Artist reconstruction of Mercuriceratops gemini, a new species of horned dinosaur that had wing-shaped ornamentation on the sides of its skull. Credit: Danielle Dufault \"This discovery of a previously unknown species in relatively well-studied rocks underscores that we still have many more new species of dinosaurs to left to find,\" said co-author Dr. Mark Loewen, research associate at the Natural History Museum of Utah. This dinosaur is just the latest in a series of new finds being made by Ryan and Evans as part of their Southern Alberta Dinosaur Project, which is designed to fill in gaps in our knowledge of Late Cretaceous dinosaurs and study their evolution. This project focuses on the paleontology of some of oldest dinosaur-bearing rocks in Alberta and the neighbouring rocks of northern Montana that are of the same age. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract A new taxon of chasmosaurine ceratopsid demonstrates unexpected disparity in parietosquamosal frill shape among ceratopsid dinosaurs early in their evolutionary radiation. The new taxon is described based on two apomorphic squamosals collected from approximately time equivalent (approximately 77 million years old) sections of the upper Judith River Formation, Montana, and the lower Dinosaur Park Formation of Dinosaur Provincial Park, Alberta. It is referred to Chasmosaurinae based on the inferred elongate morphology. The typical chasmosaurine squamosal forms an obtuse triangle in dorsal view that tapers towards the posterolateral corner of the frill. In the dorsal view of the new taxon, the lateral margin of the squamosal is hatchet-shaped with the posterior portion modified into a constricted narrow bar that would have supported the lateral margin of a robust parietal. The new taxon represents the oldest chasmosaurine from Canada, and the first pre-Maastrichtian ceratopsid to have been collected on both sides of the Canada–US border, with a minimum north–south range of 380 km. This squamosal morphology would have given the frill of the new taxon a unique dorsal profile that represents evolutionary experimentation in frill signalling near the origin of chasmosaurine ceratopsids and reinforces biogeographic differences between northern and southern faunal provinces in the Campanian of North America. Access provided by DEAL DE / Springer Compact Clearingstelle Uni Freiburg _ Working on a manuscript? Avoid the common mistakes Introduction Ceratopsidae is a diverse clade of large bodied horned dinosaurs known from a well-sampled fossil record that spans the last 20 million years of the Mesozoic (Dodson et al. 2004 ). Ceratopsids are common in the Campanian–Maastrichtian deposits of western North America, where they range geographically from Coahuila, Mexico in the south ( Coahuilaceratops magnacuerna ; Loewen et al. 2010 ), to northern Alaska in the North ( Pachyrhinosaurus perotorum ; Fiorillo and Tykoski 2012 ). Marked latitudinal differences between the dinosaur faunas of the late Campanian has led to the recognition of northern (Wyoming and north) and southern (Utah and south) faunal provinces adjacent to the Western Interior Seaway during this time (Lehman 1987 , 1997 ; Sampson et al. 2010 ). Ceratopsians reached their maximum diversity during the Campanian and provide some of the strongest evidence for provinciality in Late Cretaceous dinosaurs (Sampson et al. 2010 , 2013 ; Farke 2013 ; Ryan 2013 ). Ceratopsidae consists of two major subclades that form a basal dichotomy of Centrosaurinae, or the ‘short-frilled’ ceratopsids, and Chasmosaurinae, which generally have relatively longer, less adorned frills. The two clades have traditionally been easily distinguished by the size and shape of their squamosals, which form the lateral segments of the parieto squamosal frill. Centrosaurines have broad, rectangular squamosals with typically concave contact surfaces (in adult-sized elements) for the parietal on the medial margin of the element. In contrast, chasmosaurines have an elongate, triangular squamosal with a corresponding contact surface for the parietal on the medioventral margin of the posterior squamosal. A recent morphometric study has confirmed that the distinctive squamosal shape of each subfamily is very conservative, with some minor proportional differences within each subfamily (Maiorino et al. 2013 ). Chasmosaurinae, in particular, exhibit little variation in squamosal shape, with little clear differentiation among taxa. Despite the importance of the parietosquamosal frill in ceratopsian systematics, the shape and ornamentation of the parietal appears to have been the locus of evolution within Ceratopsidae, with many taxa being diagnosed exclusively from this element. The squamosal defines the lateral shape of the frill and reflects more general differences in frill structure within the subfamilies; its conservative morphology suggests that this aspect of the frill was generally stable within each subfamily. A remarkable new chasmosaurine ceratopsid is described based on material collected from approximately time equivalent middle Campanian exposures of the Judith River Formation of Montana and the Dinosaur Park Formation of Alberta (Fig. 1 ). The new taxon is represented by two well-preserved squamosals and reveals previously unknown disparity in ceratopsid frill shape. It departs significantly from the conservative frill shape currently known in ceratopsids by an unusual modification of the squamosal that results in a hatchet-shaped lateral frill margin, rather than the convex-to-straight lateral margins that characterise all other known taxa. The new, apparently rare, taxon provides additional support for the faunal differentiation of northern and southern biogeographic provinces on Laramidia during the late Campanian. It also suggests that the evolutionary origin of the derived elongate triangular squamosal of chasmosaurs may have been more complex than previously believed. Fig. 1 Locality map of UALVP 54559 from the Dinosaur Park Formation of Dinosaur Provincial Park, Alberta, and ROM 64222 from the Judith River Formation of Montana. Alberta and Montana are silhouetted in black on the North America inset map. Google Earth image insets: Google, Digital Globe (Dinosaur Provincial Park) and Google, USDA Farm Service Agency (Montana) Full size image Institutional Abbreviations ROM, Royal Ontario Museum, Toronto, Canada UALVP, University of Alberta, Laboratory for Vertebrate Paleontology, Edmonton, Canada Systematic Paleontology Ornithischia Seeley 1888 Ceratopsia Marsh 1890 Neoceratopsia Sereno 1986 Ceratopsidae Marsh 1888 Chasmosaurinae Lambe 1915 Mercuriceratops gen. nov. urn:lsid:zoobank.org:act:70D4C099-1A46-4192-B8A1-D134E49D4861 Type species Mercuriceratops gemini sp. nov. Diagnosis Same as for species, by monotypy Mercuriceratops gemini sp. nov. urn:lsid:zoobank.org:act:70D4C099-1A46-4192-B8A1-D134E49D4861 Holotype ROM 64222: An almost complete right squamosal (Fig. 2a–d ) Fig. 2 Mercuriceratops gemini squamosal. ROM 64222 (holotype) in a , c line drawing and photograph of dorsal view; b , d line drawing and photograph of ventral view. Inset reconstruction of M. gemini in lateral view. es# episquamosal #. Scale bar = 20 cm Full size image Etymology Mercuri , in reference to winged helmet of the Roman messenger god Mercury, and ‘ceratops’, meaning horned face, a common suffix for genera of ceratopsid dinosaurs. Close carriage return. Gemini , from mythology, the twins Castor and Pollux were transformed into the constellation Gemini, referring to the twin specimens from Alberta and Montana. Referred material UALVP 54559, an incomplete right squamosal (Fig. 3a and b ). Fig. 3 Mercuriceratops gemini squamosal. UALVP 54559 (paratype) in a dorsal and b ventral views. es#<|im_end|> <|im_start|>assistant Scientists have named a new species of horned dinosaur (ceratopsian) based on fossils collected from Montana in the United States and Alberta, Canada. Mercuriceratops (mer-cure-E-sare-ah-tops) gemini was approximately 6 meters (20 feet) long and weighed more than 2 tons. It lived about 77 million years ago during the Late Cretaceous Period. Research describing the new species is published online in the journal Naturwissenschaften. Mercuriceratops (Mercuri + ceratops) means "Mercury horned-face," referring to the wing-like ornamentation on its head that resembles the wings on the helmet of the Roman god, Mercury. The name "gemini" refers to the almost identical twin specimens found in north central Montana and the UNESCO World Heritage Site, Dinosaur Provincial Park, in Alberta, Canada. Mercuriceratops had a parrot-like beak and probably had two long brow horns above its eyes. It was a plant-eating dinosaur. "Mercuriceratops took a unique evolutionary path that shaped the large frill on the back of its skull into protruding wings like the decorative fins on classic 1950s cars. It definitively would have stood out from the herd during the Late Cretaceous," said lead author Dr. Michael Ryan, curator of vertebrate paleontology at The Cleveland Museum of Natural History. "Horned dinosaurs in North America used their elaborate skull ornamentation to identify each other and to attract mates—not just for protection from predators. The wing-like protrusions on the sides of its frill may have offered male Mercuriceratops a competitive advantage in attracting mates." This image depicts Mercuriceratops gemini skull fossils from the right side of the frill. Credit: Naturwissenschaften "The butterfly-shaped frill, or neck shield, of Mercuriceratops is unlike anything we have seen before," said co-author Dr. David Evans, curator of vertebrate palaeontology at the Royal Ontario Museum. "Mercuriceratops shows that evolution gave rise to much greater variation in horned dinosaur headgear than we had previously suspected." The new dinosaur is described from skull fragments from two individuals collected from the Judith River Formation of Montana and the Dinosaur Park Formation of Alberta. The Montana specimen was originally collected on private land and acquired by the Royal Ontario Museum. The Alberta specimen was collected by Susan Owen-Kagen, a preparator in Dr. Philip Currie's lab at the University of Alberta. "Susan showed me her specimen during one of my trips to Alberta," said Ryan. "When I saw it, I instantly recognized it as being from the same type of dinosaur that the Royal Ontario Museum had from Montana." The Alberta specimen confirmed that the fossil from Montana was not a pathological specimen, nor had it somehow been distorted during the process of fossilization," said Dr. Philip Currie, professor and Canada research chair in dinosaur paleobiology at the University of Alberta. "The two fossils—squamosal bones from the side of the frill—have all the features you would expect, just presented in a unique shape." Artist reconstruction of Mercuriceratops gemini, a new species of horned dinosaur that had wing-shaped ornamentation on the sides of its skull. Credit: Danielle Dufault "This discovery of a previously unknown species in relatively well-studied rocks underscores that we still have many more new species of dinosaurs to left to find," said co-author Dr. Mark Loewen, research associate at the Natural History Museum of Utah. This dinosaur is just the latest in a series of new finds being made by Ryan and Evans as part of their Southern Alberta Dinosaur Project, which is designed to fill in gaps in our knowledge of Late Cretaceous dinosaurs and study their evolution. This project focuses on the paleontology of some of oldest dinosaur-bearing rocks in Alberta and the neighbouring rocks of northern Montana that are of the same age. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 362, 502, 3827, 263, 315, 523, 300, 8801, 4202, 483, 10362, 266, 3806, 307, 32216, 16907, 66949, 304, 1370, 3978, 437, 447, 10808, 278, 1448, 484, 6211, 4315, 10362, 266, 3806, 307, 65375, 4216, 304, 872, 41993, 25407, 13, 578, 502, 3827, 263, 374, 7633, 3196, 389, 1403, 1469, 71017, 8330, 10808, 1147, 14890, 505, 13489, 892, 13890, 320, 97836, 220, 2813, 3610, 1667, 2362, 8, 14491, 315, 279, 8582, 79193, 11188, 72466, 11, 37105, 11, 323, 279, 4827, 423, 89247, 5657, 72466, 315, 423, 89247, 80795, 5657, 11, 33654, 13, 1102, 374, 14183, 311, 921, 300, 8801, 4202, 125887, 3196, 389, 279, 68695, 74595, 349, 79612, 13, 578, 14595, 523, 300, 8801, 4202, 483, 8330, 10808, 278, 7739, 459, 4615, 817, 22217, 304, 96146, 1684, 430, 259, 9724, 7119, 279, 23163, 337, 19715, 9309, 315, 279, 1448, 484, 13, 763, 279, 96146, 1684, 315, 279, 502, 3827, 263, 11, 279, 45569, 4850, 315, 279, 8330, 10808, 278, 374, 44355, 295, 35831, 449, 279, 46000, 13651, 11041, 1139, 264, 390, 74172, 15376, 3703, 430, 1053, 617, 7396, 279, 45569, 4850, 315, 264, 22514, 1370, 3978, 278, 13, 578, 502, 3827, 263, 11105, 279, 24417, 523, 300, 8801, 4202, 483, 505, 7008, 11, 323, 279, 1176, 864, 5364, 5418, 496, 4970, 1122, 10362, 266, 3806, 307, 311, 617, 1027, 14890, 389, 2225, 11314, 315, 279, 7008, 4235, 2078, 3973, 11, 449, 264, 8187, 10411, 4235, 67584, 2134, 315, 220, 13897, 13437, 13, 1115, 8330, 10808, 278, 79612, 1053, 617, 2728, 279, 1448, 484, 315, 279, 502, 3827, 263, 264, 5016, 96146, 5643, 430, 11105, 41993, 66196, 304, 1448, 484, 91977, 3221, 279, 6371, 315, 523, 300, 8801, 4202, 483, 10362, 266, 3806, 3447, 323, 95593, 6160, 41632, 12968, 12062, 1990, 18671, 323, 18561, 2267, 26663, 41021, 304, 279, 8215, 857, 1122, 315, 4892, 5270, 13, 9742, 3984, 555, 26571, 3467, 611, 67915, 55882, 12292, 287, 267, 6853, 49966, 7730, 581, 5673, 721, 22938, 389, 264, 47913, 30, 35106, 279, 4279, 21294, 29438, 28764, 266, 3806, 114405, 374, 264, 17226, 1206, 1037, 315, 3544, 30111, 1142, 21281, 291, 65375, 3967, 505, 264, 1664, 1355, 66107, 31376, 3335, 430, 45395, 279, 1566, 220, 508, 3610, 1667, 315, 279, 36684, 96614, 292, 320, 91563, 942, 1880, 453, 13, 220, 1049, 19, 7609, 28764, 266, 3806, 3447, 527, 4279, 304, 279, 8215, 857, 1122, 4235, 44, 5418, 496, 4970, 1122, 34751, 315, 19001, 4892, 5270, 11, 1405, 814, 2134, 3980, 65031, 505, 3623, 27793, 10746, 11, 12550, 304, 279, 10007, 320, 3623, 27793, 321, 9779, 266, 3806, 8622, 582, 84, 47628, 2652, 6621, 365, 268, 1880, 453, 13, 220, 679, 15, 7026, 311, 18671, 28366, 304, 279, 4892, 320, 393, 613, 11160, 71, 15570, 43613, 824, 10088, 372, 2652, 100103, 22532, 323, 14221, 57778, 6780, 220, 679, 17, 7609, 4488, 291, 6987, 13138, 992, 12062, 1990, 279, 63989, 2267, 59364, 315, 279, 3389, 8215, 857, 1122, 706, 6197, 311, 279, 18324, 315, 18671, 320, 68007, 18238, 323, 10411, 8, 323, 18561, 320, 61220, 1494, 323, 10007, 8, 2267, 26663, 41021, 24894, 311, 279, 11104, 29958, 1369, 14075, 2391, 420, 892, 320, 2356, 71, 1543, 220, 3753, 22, 1174, 220, 2550, 22, 2652, 91274, 942, 1880, 453, 13, 220, 679, 15, 7609, 28764, 266, 3806, 5493, 8813, 872, 7340, 20057, 2391, 279, 8215, 857, 1122, 323, 3493, 1063, 315, 279, 31005, 6029, 369, 36031, 488, 304, 36931, 356, 2171, 77140, 65375, 320, 50, 1141, 942, 1880, 453, 13, 220, 679, 15, 1174, 220, 679, 18, 2652, 13759, 441, 220, 679, 18, 2652, 13960, 220, 679, 18, 7609, 28764, 266, 3806, 114405, 17610, 315, 1403, 3682, 1207, 566, 3536, 430, 1376, 264, 80710, 29953, 85995, 315, 5838, 3714, 4202, 125887, 11, 477, 279, 3451, 8846, 51478, 4473, 529, 10362, 266, 3806, 3447, 11, 323, 921, 300, 8801, 4202, 125887, 11, 902, 8965, 617, 12309, 5129, 11, 2753, 84273, 1448, 3385, 13, 578, 1403, 1206, 3536, 617, 36342, 1027, 6847, 39575, 555, 279, 1404, 323, 6211, 315, 872, 8330, 10808, 1147, 11, 902, 1376, 279, 45569, 21282, 315, 279, 1370, 3978, 78, 8330, 10808, 278, 1448, 484, 13, 5838, 3714, 4202, 1572, 617, 7353, 11, 52524, 8330, 10808, 1147, 449, 11383, 3613, 525, 3729, 27529, 320, 258, 6822, 28935, 5540, 8, 369, 279, 1370, 3978, 278, 389, 279, 97348, 4850, 315, 279, 2449, 13, 763, 13168, 11, 523, 300, 8801, 4202, 1572, 617, 459, 74595, 349, 11, 66594, 8330, 10808, 278, 449, 264, 12435, 3729, 7479, 369, 279, 1370, 3978, 278, 389, 279, 49779, 688, 3545, 4850, 315, 279, 46000, 8330, 10808, 278, 13, 362, 3293, 27448, 24264, 4007, 706, 11007, 430, 279, 35947, 8330, 10808, 278, 6211, 315, 1855, 1207, 19521, 374, 1633, 15692, 11, 449, 1063, 9099, 55272, 12062, 2949, 1855, 1207, 19521, 320, 44, 2192, 269, 3394, 1880, 453, 13, 220, 679, 18, 7609, 921, 300, 8801, 4202, 125887, 11, 304, 4040, 11, 31324, 2697, 23851, 304, 8330, 10808, 278, 6211, 11, 449, 2697, 2867, 60038, 4315, 77314, 13, 18185, 279, 12939, 315, 279, 1370, 3978, 437, 447, 10808, 278, 1448, 484, 304, 10362, 266, 3806, 1122, 1887, 29470, 11, 279, 6211, 323, 79760, 367, 315, 279, 1370, 3978, 278, 8111, 311, 617, 1027, 279, 79257, 315, 15740, 2949, 28764, 266, 3806, 114405, 11, 449, 1690, 77314, 1694, 29704, 24121, 505, 420, 2449, 13, 578, 8330, 10808, 278, 19170, 279, 45569, 6211, 315, 279, 1448, 484, 323, 27053, 810, 4689, 12062, 304, 1448, 484, 6070, 2949, 279, 1207, 69, 60004, 26, 1202, 15692, 79612, 13533, 430, 420, 13189, 315, 279, 1448, 484, 574, 8965, 15528, 2949, 1855, 1207, 19521, 13, 362, 23649, 502, 523, 300, 8801, 4202, 483, 10362, 266, 3806, 307, 374, 7633, 3196, 389, 3769, 14890, 505, 13489, 892, 13890, 6278, 8215, 857, 1122, 70530, 315, 279, 79193, 11188, 72466, 315, 37105, 323, 279, 423, 89247, 5657, 72466, 315, 33654, 320, 30035, 13, 220, 16, 7609, 578, 502, 3827, 263, 374, 15609, 555, 1403, 1664, 2320, 52202, 8330, 10808, 1147, 323, 21667, 8767, 9987, 66949, 304, 10362, 266, 3806, 307, 1448, 484, 6211, 13, 1102, 2219, 7183, 12207, 505, 279, 15692, 1448, 484, 6211, 5131, 3967, 304, 10362, 266, 3806, 3447, 555, 459, 19018, 17466, 315, 279, 8330, 10808, 278, 430, 3135, 304, 264, 44355, 295, 35831, 45569, 1448, 484, 4850, 11, 4856, 1109, 279, 67030, 4791, 42728, 7538, 45569, 37682, 430, 3752, 1082, 682, 1023, 3967, 77314, 13, 578, 502, 11, 14132, 9024, 11, 3827, 263, 5825, 5217, 1862, 369, 279, 2267, 26663, 60038, 315, 18671, 323, 18561, 6160, 41632, 12968, 41021, 389, 445, 640, 87800, 2391, 279, 3389, 8215, 857, 1122, 13, 1102, 1101, 13533, 430, 279, 41993, 6371, 315, 279, 14592, 74595, 349, 66594, 8330, 10808, 278, 315, 523, 300, 8801, 64, 1759, 1253, 617, 1027, 810, 6485, 1109, 8767, 11846, 13, 23966, 13, 220, 16, 13914, 2786, 2472, 315, 549, 984, 13683, 220, 20749, 2946, 505, 279, 423, 89247, 5657, 72466, 315, 423, 89247, 80795, 5657, 11, 33654, 11, 323, 31786, 220, 22266, 1313, 505, 279, 79193, 11188, 72466, 315, 37105, 13, 33654, 323, 37105, 527, 5554, 18664, 295, 6702, 304, 3776, 389, 279, 4892, 5270, 55959, 2472, 13, 5195, 9420, 2217, 99169, 25, 5195, 11, 14434, 41910, 320, 35, 89247, 80795, 5657, 8, 323, 5195, 11, 61091, 18945, 5475, 16784, 320, 35515, 3444, 8, 8797, 1404, 2217, 98984, 27063, 7430, 17583, 31786, 11, 16591, 21193, 16730, 11, 14974, 11, 7008, 549, 984, 13683, 11, 3907, 315, 33654, 11, 32184, 369, 650, 14140, 65216, 12629, 63333, 11, 46387, 11, 7008, 744, 780, 12629, 63333, 88939, 411, 16438, 689, 3580, 3258, 220, 9367, 23, 28764, 266, 3806, 689, 40163, 220, 9378, 15, 4275, 511, 261, 266, 3806, 689, 8409, 12052, 220, 3753, 21, 28764, 266, 3806, 114405, 40163, 220, 9367, 23, 921, 300, 8801, 4202, 125887, 33794, 1395, 220, 7529, 20, 8930, 2407, 13296, 266, 3806, 4173, 13, 6747, 13, 66967, 25, 4835, 307, 25, 13028, 677, 1201, 2726, 25, 533, 25, 2031, 35, 19, 34, 26513, 12, 16, 32, 2790, 12, 19391, 17, 7826, 23, 32, 16, 9607, 9565, 36, 2491, 35, 21511, 16, 4078, 9606, 8930, 2407, 13296, 266, 3806, 19269, 6729, 993, 13, 6747, 13, 95452, 26823, 439, 369, 9606, 11, 555, 1647, 37941, 88, 8930, 2407, 13296, 266, 3806, 19269, 6729, 993, 13, 6747, 13, 66967, 25, 4835, 307, 25, 13028, 677, 1201, 2726, 25, 533, 25, 2031, 35, 19, 34, 26513, 12, 16, 32, 2790, 12, 19391, 17, 7826, 23, 32, 16, 9607, 9565, 36, 2491, 35, 21511, 16, 16071, 4249, 31786, 220, 22266, 1313, 25, 1556, 4661, 4686, 1314, 8330, 10808, 278, 320, 30035, 13, 220, 17, 64, 4235, 67, 883, 23966, 13, 220, 17, 8930, 2407, 13296, 266, 3806, 19269, 6729, 8330, 10808, 278, 13, 31786, 220, 22266, 1313, 320, 8619, 4249, 8, 304, 264, 1174, 272, 1584, 13633, 323, 10512, 315, 96146, 1684, 26, 293, 1174, 294, 1584, 13633, 323, 10512, 315, 10594, 3545, 1684, 13, 763, 751, 43738, 315, 386, 13, 19269, 6729, 304, 45569, 1684, 13, 1560, 2, 67594, 447, 10808, 278, 674, 13, 25635, 3703, 284, 220, 508, 10166, 8797, 1404, 2217, 19421, 99174, 8930, 2407, 72, 1174, 304, 5905, 311, 20611, 291, 32635, 315, 279, 13041, 50596, 10087, 44662, 11, 323, 3451, 3913, 266, 3806, 20182, 7438, 21281, 291, 3663, 11, 264, 4279, 21166, 369, 84535, 315, 10362, 266, 3806, 307, 65375, 13, 13330, 52547, 471, 13, 86811, 1174, 505, 59492, 11, 279, 44736, 11514, 269, 323, 25385, 2249, 1051, 24411, 1139, 279, 83486, 86811, 11, 22797, 311, 279, 28497, 57749, 505, 33654, 323, 37105, 13, 1050, 5671, 3769, 549, 984, 13683, 220, 20749, 2946, 11, 459, 33243, 1314, 8330, 10808, 278, 320, 30035, 13, 220, 18, 64, 323, 293, 7609, 23966, 13, 220, 18, 8930, 2407, 13296, 266, 3806, 19269, 6729, 8330, 10808, 278, 13, 549, 984, 13683, 220, 20749, 2946, 320, 1768, 20764, 8, 304, 264, 96146, 323, 293, 10594, 3545, 6325, 13, 1560, 2, 128257, 198, 128256, 78191, 198, 72326, 617, 7086, 264, 502, 9606, 315, 21281, 291, 63989, 320, 3913, 266, 3806, 1122, 8, 3196, 389, 81473, 14890, 505, 37105, 304, 279, 3723, 4273, 323, 33654, 11, 7008, 13, 8930, 2407, 13296, 266, 3806, 320, 1195, 1824, 554, 13737, 1355, 548, 12, 1494, 2442, 3806, 8, 19269, 6729, 574, 13489, 220, 21, 20645, 320, 508, 7693, 8, 1317, 323, 47712, 810, 1109, 220, 17, 20181, 13, 1102, 12439, 922, 220, 2813, 3610, 1667, 4227, 2391, 279, 36931, 356, 2171, 77140, 26572, 13, 8483, 23524, 279, 502, 9606, 374, 4756, 2930, 304, 279, 8486, 40549, 86, 80848, 268, 13, 8930, 2407, 13296, 266, 3806, 320, 27814, 2407, 72, 489, 10362, 266, 3806, 8, 3445, 330, 27814, 26533, 21281, 291, 30188, 1359, 22797, 311, 279, 20611, 12970, 79760, 367, 389, 1202, 2010, 430, 53291, 279, 27296, 389, 279, 32635, 315, 279, 13041, 10087, 11, 44662, 13, 578, 836, 330, 35203, 6729, 1, 19813, 311, 279, 4661, 20086, 28497, 57749, 1766, 304, 10411, 8792, 37105, 323, 279, 81876, 4435, 34243, 13207, 11, 423, 89247, 80795, 5657, 11, 304, 33654, 11, 7008, 13, 8930, 2407, 13296, 266, 3806, 1047, 264, 1370, 4744, 12970, 387, 587, 323, 4762, 1047, 1403, 1317, 60375, 61084, 3485, 1202, 6548, 13, 1102, 574, 264, 6136, 5773, 1113, 63989, 13, 330, 27814, 2407, 13296, 266, 3806, 3952, 264, 5016, 41993, 1853, 430, 27367, 279, 3544, 1448, 484, 389, 279, 1203, 315, 1202, 35113, 1139, 81458, 51867, 27296, 1093, 279, 46536, 66079, 389, 11670, 220, 6280, 15, 82, 9515, 13, 1102, 31388, 3210, 1053, 617, 14980, 704, 505, 279, 59213, 2391, 279, 36931, 356, 2171, 77140, 1359, 1071, 3063, 3229, 2999, 13, 8096, 13960, 11, 87805, 315, 67861, 65216, 28639, 63333, 520, 578, 24372, 16730, 315, 18955, 11346, 13, 330, 39, 1540, 291, 65375, 304, 4892, 5270, 1511, 872, 37067, 35113, 79760, 367, 311, 10765, 1855, 1023, 323, 311, 9504, 55616, 63938, 1120, 369, 9313, 505, 56217, 13, 578, 20611, 12970, 81458, 36807, 389, 279, 11314, 315, 1202, 1448, 484, 1253, 617, 9076, 8762, 8930, 2407, 13296, 266, 3806, 264, 15022, 9610, 304, 51647, 55616, 1210, 1115, 2217, 62991, 8930, 2407, 13296, 266, 3806, 19269, 6729, 35113, 81473, 505, 279, 1314, 3185, 315, 279, 1448, 484, 13, 16666, 25, 40549, 86, 80848, 268, 330, 791, 56269, 35831, 1448, 484, 11, 477, 13272, 20858, 11, 315, 8930, 2407, 13296, 266, 3806, 374, 20426, 4205, 584, 617, 3970, 1603, 1359, 1071, 1080, 43802, 2999, 13, 6941, 30563, 11, 87805, 315, 67861, 65216, 11091, 6043, 63333, 520, 279, 16591, 21193, 16730, 13, 330, 27814, 2407, 13296, 266, 3806, 5039, 430, 15740, 6688, 10205, 311, 1790, 7191, 23851, 304, 21281, 291, 63989, 2010, 55827, 1109, 584, 1047, 8767, 24740, 1210, 578, 502, 63989, 374, 7633, 505, 35113, 35603, 505, 1403, 7931, 14890, 505, 279, 79193, 11188, 72466, 315, 37105, 323, 279, 423, 89247, 5657, 72466, 315, 33654, 13, 578, 37105, 58184, 574, 13517, 14890, 389, 879, 4363, 323, 19426, 555, 279, 16591, 21193, 16730, 13, 578, 33654, 58184, 574, 14890, 555, 31033, 47809, 16222, 8703, 11, 264, 10073, 859, 304, 2999, 13, 26241, 13182, 7379, 596, 10278, 520, 279, 3907, 315, 33654, 13, 330, 86383, 8710, 757, 1077, 58184, 2391, 832, 315, 856, 23277, 311, 33654, 1359, 1071, 13960, 13, 330, 4599, 358, 5602, 433, 11, 358, 22571, 15324, 433, 439, 1694, 505, 279, 1890, 955, 315, 63989, 430, 279, 16591, 21193, 16730, 1047, 505, 37105, 1210, 578, 33654, 58184, 11007, 430, 279, 31376, 505, 37105, 574, 539, 264, 89961, 58184, 11, 6463, 1047, 433, 17354, 1027, 62236, 2391, 279, 1920, 315, 31376, 2065, 1359, 1071, 2999, 13, 26241, 13182, 7379, 11, 14561, 323, 7008, 3495, 10716, 304, 63989, 28639, 18843, 2508, 520, 279, 3907, 315, 33654, 13, 330, 791, 1403, 81473, 2345, 98507, 10808, 278, 25896, 505, 279, 3185, 315, 279, 1448, 484, 2345, 19553, 682, 279, 4519, 499, 1053, 1755, 11, 1120, 10666, 304, 264, 5016, 6211, 1210, 29459, 43738, 315, 8930, 2407, 13296, 266, 3806, 19269, 6729, 11, 264, 502, 9606, 315, 21281, 291, 63989, 430, 1047, 20611, 35831, 79760, 367, 389, 279, 11314, 315, 1202, 35113, 13, 16666, 25, 72716, 423, 1739, 957, 330, 2028, 18841, 315, 264, 8767, 9987, 9606, 304, 12309, 1664, 5594, 664, 1142, 23902, 72890, 430, 584, 2103, 617, 1690, 810, 502, 9606, 315, 65375, 311, 2163, 311, 1505, 1359, 1071, 1080, 43802, 2999, 13, 4488, 6621, 365, 268, 11, 3495, 22712, 520, 279, 18955, 11346, 16730, 315, 23195, 13, 1115, 63989, 374, 1120, 279, 5652, 304, 264, 4101, 315, 502, 14035, 1694, 1903, 555, 13960, 323, 30563, 439, 961, 315, 872, 16642, 33654, 423, 89247, 5907, 11, 902, 374, 6319, 311, 5266, 304, 33251, 304, 1057, 6677, 315, 36931, 356, 2171, 77140, 65375, 323, 4007, 872, 15740, 13, 1115, 2447, 24400, 389, 279, 28639, 63333, 315, 1063, 315, 24417, 63989, 92253, 23902, 304, 33654, 323, 279, 62027, 23902, 315, 18671, 37105, 430, 527, 315, 279, 1890, 4325, 13, 220, 128257, 198 ]

2,495

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Seroepidemiological studies aim to understand population-level exposure and immunity to infectious diseases. Their results are normally presented as binary outcomes describing the presence or absence of pathogen-specific antibody, despite the fact that many assays measure continuous quantities. A population’s natural distribution of antibody titers to an endemic infectious disease may include information on multiple serological states – naiveté, recent infection, non-recent infection, childhood infection – depending on the disease in question and the acquisition and waning patterns of immunity. In this study, we investigate 20,152 general-population serum samples from southern Vietnam collected between 2009 and 2013 from which we report antibody titers to the influenza virus HA1 protein using a continuous titer measurement from a protein microarray assay. We describe the distributions of antibody titers to subtypes 2009 H1N1 and H3N2. Using a model selection approach to fit mixture distributions, we show that 2009 H1N1 antibody titers fall into four titer subgroups and that H3N2 titers fall into three subgroups. For H1N1, our interpretation is that the two highest-titer subgroups correspond to recent and historical infection, which is consistent with 2009 pandemic attack rates. Similar interpretations are available for H3N2, but right-censoring of titers makes these interpretations difficult to validate. Introduction The distribution of antibodies in a human population is a fossil imprint of the population’s past exposure to infectious disease. If individuals’ antibody concentrations can be measured accurately, they can be used to infer both the size and timing of past epidemics. The two key post-epidemic processes that need to be measured to make this inference possible are the rate of antibody acquisition and the rate of antibody waning. The rate of antibody acquisition post-infection is rapid (weeks) for most viral pathogens, but more difficult to measure for more complex pathogens that present the immune system with a diverse set of antigens. The rate of antibody waning, however, is rarely measured even for viral pathogens. To correctly translate a population’s antibody titer distribution to its epidemic history, accurate measures of both these rates are necessary. To validate that this reconstruction has been done correctly, a large cohort with long-term follow-up and precise antibody measurements would be required. Studies like these are difficult to run and difficult to find in the scientific literature – both in methodological development and field implementation. Further complicating the issue is that antibody measurements are rarely 100% specific, and that low-level cross-reactive antibodies often are ignored by setting a cut-off for positivity. To begin investigating what an antibody distribution can tell us about a population’s epidemic history, we initiated a large-scale time-structured serological survey 1 , 2 and an observational clinical study that includes repeat patient follow-ups to measure rates of antibody waning 3 ; the results of the serological survey are presented here. Influenza A virus was chosen as the pathogen of interest as ( i ) it is an important, globally-circulating human pathogen, ( ii ) influenza is well characterized antigenically, ( iii ) a precise and repeatable serological assay was available, and ( iv ) the human population receives almost no influenza vaccination in our study location of southern Vietnam. The first aim of this study was to move away from the binary approach to serology – which classifies individuals as seropositive or seronegative 4 , 5 , 6 , 7 , 8 – and to describe the underlying structure of a general-population antibody-titer distribution by assuming that an individual can belong to any number of serological states. The rationale for a detailed descriptive analysis of antibody titer distributions is that titer groups or titer ranges may be able to provide differentiating information on the type of infection, e.g. recent versus non-recent infections, or primary versus non-primary. The binary approach of classifying individuals as seropositive and seronegative is not as informative as it could be given the richness of some serological datasets, and it is already known to have two practical drawbacks. First, the cutoff value for seropositivity is typically calibrated from a group of patients with confirmed acute infection, by collecting convalescent serum samples a few weeks or a few months after symptoms onset. This means that the correct application of the cut-off value is the identification of recent symptomatic infections rather than any past infections. Thus, applying this threshold to a population-wide serological cross-section will likely result in an underestimate of the seroprevalence. Second, binary classification in serology results in incorrect or inconclusive classifications for samples with borderline measurements 8 , 9 , 10 . Non-binary analyses of serological data are present in the literature for a range of pathogens 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 including influenza virus 19 , 20 , but very few of these studies are able to look at non-vaccinated populations and none have the scale and precision presented here. In the present study, we analyze a large set of general-population serum samples collected as residual serum from biochemistry and haemotology labs in four hospitals in southern Vietnam, from 2009 to 2013. Using a zero-inflated mixture modeling approach, we allow for up to seven serological states. To account for the large sample size in our model selection procedure, we use the Bayesian Information Criterion, and to avoid inference of spurious serological states we set additional criteria to ensure that inferred titer groups are epidemiologically meaningful. We hypothesized that serological classification of influenza antibody titers would be non-binary and that age and lineage exposure (H1N1 only) would be associated with certain titer groups. We found that H1N1 antibody titer distribution are best classified into four titer groups, that H3N2 is best classified into three groups, and that censoring may have prevented a complete classification of H3N2 titers. Results A total of 20,152 sera were collected and tested for antibody concentrations by protein microarray. The samples represent patients attending hospitals in four cities – Ho Chi Minh City (n = 5788), Nha Trang (n = 5630), Buon Ma Thuot (n = 4144), and Hue (n", "role": "user" }, { "content": "The amount of influenza-specific antibodies present in an individual's blood can indicate not only if they experienced the flu, but potentially when—a finding that could improve disease monitoring in the tropics, where flu season is unending. In the largest study of its kind, an international team, led by researchers from the Oxford University Clinical Research Unit in Ho Chi Minh City, Vietnam, the Erasmus Medical Centre in Rotterdam, Netherlands, and Penn State University, identified antibody concentrations that correspond to recent and past exposure to the flu strain H1N1—the strain involved in the 2009 flu pandemic. A paper describing the research is published in a July issue of the journal Scientific Reports. \"Disease outbreaks and epidemics are often monitored by counting individuals who show symptoms of infection, but this only captures people who are sick enough to be identified,\" said Maciej Boni, associate professor of biology at Penn State and a lead author of the paper. \"With blood samples, you can capture everyone that ever was infected because individuals are not able to hide their antibody signals.\" Antibodies defend against viral attack, and their numbers spike in the presence of an infection like influenza. Approximately one month after infection, the number of flu-specific antibodies in the blood begins to decrease, but some antibodies continue to circulate long after the virus has cleared. In the past, scientists have measured the concentration of antibodies remaining to identify whether an individual has been exposed to the virus, but the results of these tests have typically been limited to describing the presence or absence of past infection. \"In this study we showed that there is a lot more information in measurements of antibody concentration than just presence or absence,\" said Boni. \"Our results show that antibody concentration should be able to provide information about the timing of past influenza infection.\" This information is especially valuable in tropical climates. \"In temperate regions like the United States, we might collect blood samples when the flu season is over to see what percentage of people were infected during that flu season,\" Boni explains. \"But in the tropics there is no flu season—it may be constantly circulating or it could come in waves. If all you measure is the presence or absence of antibodies, you can't determine when those individuals were infected.\" Colorized micrograph of particles of the influenza strain H1N1, which was involved in the 2009 flu pandemic. Credit: National Institute of Allergy and Infectious Diseases, National Institutes of Health The research team analyzed over 20,000 blood samples from four hospitals in southern Vietnam, taken every two months between 2009 to 2013. \"This is the largest study of its kind, and custom statistical methods needed to be developed for this analysis,\" said Nguyen Thi Duy Nhat, graduate student at Oxford University Clinical Research Unit at the time of the study and first author of the paper. This immense undertaking will allow the team to map out the H1N1 flu strain's dynamics in the tropics in the next phase of their research. \"The 2009 influenza pandemic taught us the importance of understanding the history of exposure in the community as a factor of a pandemic's impact,\" said Marion Koopmans, head of the Department of Viroscience at the Erasmus Medical Centre and a lead author of the study. \"Here, we introduce a novel approach that measures a population's exposure history to currently circulating viruses. This work will help us assess who is most at risk during a new influenza outbreak.\" The research team defined four categories of H1N1-specific antibody concentrations. The highest concentrations indicate exposure to H1N1 within the last six months, the second highest concentrations indicate exposure greater than six months prior, and the lowest two categories of concentrations indicate no previous exposure to the virus. Use of these categories could allow public health officials in other tropical locations to determine infection rates of H1N1 with systematic sampling, for example, by screening a subset of the population every January to determine the previous year's infection rate. The researchers used a protein microarray—a high-throughput large-scale test that measures interactions of large numbers of proteins in parallel—to measure antibody concentrations. Developed in the Netherlands, this relatively new technique allows precise antibody measurements with very small volumes of blood. \"This protein microarray has high reproducibility and can provide specificity to 16 different influenza strains,\" said Erwin de Bruin, senior laboratory technician at Erasmus Medical Centre and an author of the study. \"The small volume of blood required provides a simpler way to perform large epidemiological studies.\" \"This microarray, and the additional information about time of infection from antibody concentrations, could change how we monitor disease in the tropics,\" adds Boni. \"Currently, public health systems monitor antibodies after an outbreak or for the purpose of research, but most of the monitoring effort focuses on symptoms through hospital-based surveillance. By next decade, we may be able to perform regular surveillance of blood, which would give us a better picture of the diseases circulating through a population. This kind of surveillance is especially important in tropical countries where a lot of novel viruses emerge.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Seroepidemiological studies aim to understand population-level exposure and immunity to infectious diseases. Their results are normally presented as binary outcomes describing the presence or absence of pathogen-specific antibody, despite the fact that many assays measure continuous quantities. A population’s natural distribution of antibody titers to an endemic infectious disease may include information on multiple serological states – naiveté, recent infection, non-recent infection, childhood infection – depending on the disease in question and the acquisition and waning patterns of immunity. In this study, we investigate 20,152 general-population serum samples from southern Vietnam collected between 2009 and 2013 from which we report antibody titers to the influenza virus HA1 protein using a continuous titer measurement from a protein microarray assay. We describe the distributions of antibody titers to subtypes 2009 H1N1 and H3N2. Using a model selection approach to fit mixture distributions, we show that 2009 H1N1 antibody titers fall into four titer subgroups and that H3N2 titers fall into three subgroups. For H1N1, our interpretation is that the two highest-titer subgroups correspond to recent and historical infection, which is consistent with 2009 pandemic attack rates. Similar interpretations are available for H3N2, but right-censoring of titers makes these interpretations difficult to validate. Introduction The distribution of antibodies in a human population is a fossil imprint of the population’s past exposure to infectious disease. If individuals’ antibody concentrations can be measured accurately, they can be used to infer both the size and timing of past epidemics. The two key post-epidemic processes that need to be measured to make this inference possible are the rate of antibody acquisition and the rate of antibody waning. The rate of antibody acquisition post-infection is rapid (weeks) for most viral pathogens, but more difficult to measure for more complex pathogens that present the immune system with a diverse set of antigens. The rate of antibody waning, however, is rarely measured even for viral pathogens. To correctly translate a population’s antibody titer distribution to its epidemic history, accurate measures of both these rates are necessary. To validate that this reconstruction has been done correctly, a large cohort with long-term follow-up and precise antibody measurements would be required. Studies like these are difficult to run and difficult to find in the scientific literature – both in methodological development and field implementation. Further complicating the issue is that antibody measurements are rarely 100% specific, and that low-level cross-reactive antibodies often are ignored by setting a cut-off for positivity. To begin investigating what an antibody distribution can tell us about a population’s epidemic history, we initiated a large-scale time-structured serological survey 1 , 2 and an observational clinical study that includes repeat patient follow-ups to measure rates of antibody waning 3 ; the results of the serological survey are presented here. Influenza A virus was chosen as the pathogen of interest as ( i ) it is an important, globally-circulating human pathogen, ( ii ) influenza is well characterized antigenically, ( iii ) a precise and repeatable serological assay was available, and ( iv ) the human population receives almost no influenza vaccination in our study location of southern Vietnam. The first aim of this study was to move away from the binary approach to serology – which classifies individuals as seropositive or seronegative 4 , 5 , 6 , 7 , 8 – and to describe the underlying structure of a general-population antibody-titer distribution by assuming that an individual can belong to any number of serological states. The rationale for a detailed descriptive analysis of antibody titer distributions is that titer groups or titer ranges may be able to provide differentiating information on the type of infection, e.g. recent versus non-recent infections, or primary versus non-primary. The binary approach of classifying individuals as seropositive and seronegative is not as informative as it could be given the richness of some serological datasets, and it is already known to have two practical drawbacks. First, the cutoff value for seropositivity is typically calibrated from a group of patients with confirmed acute infection, by collecting convalescent serum samples a few weeks or a few months after symptoms onset. This means that the correct application of the cut-off value is the identification of recent symptomatic infections rather than any past infections. Thus, applying this threshold to a population-wide serological cross-section will likely result in an underestimate of the seroprevalence. Second, binary classification in serology results in incorrect or inconclusive classifications for samples with borderline measurements 8 , 9 , 10 . Non-binary analyses of serological data are present in the literature for a range of pathogens 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 including influenza virus 19 , 20 , but very few of these studies are able to look at non-vaccinated populations and none have the scale and precision presented here. In the present study, we analyze a large set of general-population serum samples collected as residual serum from biochemistry and haemotology labs in four hospitals in southern Vietnam, from 2009 to 2013. Using a zero-inflated mixture modeling approach, we allow for up to seven serological states. To account for the large sample size in our model selection procedure, we use the Bayesian Information Criterion, and to avoid inference of spurious serological states we set additional criteria to ensure that inferred titer groups are epidemiologically meaningful. We hypothesized that serological classification of influenza antibody titers would be non-binary and that age and lineage exposure (H1N1 only) would be associated with certain titer groups. We found that H1N1 antibody titer distribution are best classified into four titer groups, that H3N2 is best classified into three groups, and that censoring may have prevented a complete classification of H3N2 titers. Results A total of 20,152 sera were collected and tested for antibody concentrations by protein microarray. The samples represent patients attending hospitals in four cities – Ho Chi Minh City (n = 5788), Nha Trang (n = 5630), Buon Ma Thuot (n = 4144), and Hue (n<|im_end|> <|im_start|>assistant The amount of influenza-specific antibodies present in an individual's blood can indicate not only if they experienced the flu, but potentially when—a finding that could improve disease monitoring in the tropics, where flu season is unending. In the largest study of its kind, an international team, led by researchers from the Oxford University Clinical Research Unit in Ho Chi Minh City, Vietnam, the Erasmus Medical Centre in Rotterdam, Netherlands, and Penn State University, identified antibody concentrations that correspond to recent and past exposure to the flu strain H1N1—the strain involved in the 2009 flu pandemic. A paper describing the research is published in a July issue of the journal Scientific Reports. "Disease outbreaks and epidemics are often monitored by counting individuals who show symptoms of infection, but this only captures people who are sick enough to be identified," said Maciej Boni, associate professor of biology at Penn State and a lead author of the paper. "With blood samples, you can capture everyone that ever was infected because individuals are not able to hide their antibody signals." Antibodies defend against viral attack, and their numbers spike in the presence of an infection like influenza. Approximately one month after infection, the number of flu-specific antibodies in the blood begins to decrease, but some antibodies continue to circulate long after the virus has cleared. In the past, scientists have measured the concentration of antibodies remaining to identify whether an individual has been exposed to the virus, but the results of these tests have typically been limited to describing the presence or absence of past infection. "In this study we showed that there is a lot more information in measurements of antibody concentration than just presence or absence," said Boni. "Our results show that antibody concentration should be able to provide information about the timing of past influenza infection." This information is especially valuable in tropical climates. "In temperate regions like the United States, we might collect blood samples when the flu season is over to see what percentage of people were infected during that flu season," Boni explains. "But in the tropics there is no flu season—it may be constantly circulating or it could come in waves. If all you measure is the presence or absence of antibodies, you can't determine when those individuals were infected." Colorized micrograph of particles of the influenza strain H1N1, which was involved in the 2009 flu pandemic. Credit: National Institute of Allergy and Infectious Diseases, National Institutes of Health The research team analyzed over 20,000 blood samples from four hospitals in southern Vietnam, taken every two months between 2009 to 2013. "This is the largest study of its kind, and custom statistical methods needed to be developed for this analysis," said Nguyen Thi Duy Nhat, graduate student at Oxford University Clinical Research Unit at the time of the study and first author of the paper. This immense undertaking will allow the team to map out the H1N1 flu strain's dynamics in the tropics in the next phase of their research. "The 2009 influenza pandemic taught us the importance of understanding the history of exposure in the community as a factor of a pandemic's impact," said Marion Koopmans, head of the Department of Viroscience at the Erasmus Medical Centre and a lead author of the study. "Here, we introduce a novel approach that measures a population's exposure history to currently circulating viruses. This work will help us assess who is most at risk during a new influenza outbreak." The research team defined four categories of H1N1-specific antibody concentrations. The highest concentrations indicate exposure to H1N1 within the last six months, the second highest concentrations indicate exposure greater than six months prior, and the lowest two categories of concentrations indicate no previous exposure to the virus. Use of these categories could allow public health officials in other tropical locations to determine infection rates of H1N1 with systematic sampling, for example, by screening a subset of the population every January to determine the previous year's infection rate. The researchers used a protein microarray—a high-throughput large-scale test that measures interactions of large numbers of proteins in parallel—to measure antibody concentrations. Developed in the Netherlands, this relatively new technique allows precise antibody measurements with very small volumes of blood. "This protein microarray has high reproducibility and can provide specificity to 16 different influenza strains," said Erwin de Bruin, senior laboratory technician at Erasmus Medical Centre and an author of the study. "The small volume of blood required provides a simpler way to perform large epidemiological studies." "This microarray, and the additional information about time of infection from antibody concentrations, could change how we monitor disease in the tropics," adds Boni. "Currently, public health systems monitor antibodies after an outbreak or for the purpose of research, but most of the monitoring effort focuses on symptoms through hospital-based surveillance. By next decade, we may be able to perform regular surveillance of blood, which would give us a better picture of the diseases circulating through a population. This kind of surveillance is especially important in tropical countries where a lot of novel viruses emerge." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 328, 2382, 752, 307, 22530, 5848, 7978, 9395, 311, 3619, 7187, 11852, 14675, 323, 40368, 311, 50600, 19338, 13, 11205, 3135, 527, 14614, 10666, 439, 8026, 20124, 23524, 279, 9546, 477, 19821, 315, 1853, 11968, 19440, 63052, 11, 8994, 279, 2144, 430, 1690, 99592, 6767, 19815, 33776, 13, 362, 7187, 753, 5933, 8141, 315, 63052, 8305, 388, 311, 459, 96013, 50600, 8624, 1253, 2997, 2038, 389, 5361, 1446, 5848, 5415, 1389, 4415, 99754, 978, 11, 3293, 19405, 11, 2536, 5621, 1189, 19405, 11, 20587, 19405, 1389, 11911, 389, 279, 8624, 304, 3488, 323, 279, 24279, 323, 289, 44159, 12912, 315, 40368, 13, 763, 420, 4007, 11, 584, 19874, 220, 508, 11, 9756, 4689, 41352, 2987, 41529, 10688, 505, 18561, 23315, 14890, 1990, 220, 1049, 24, 323, 220, 679, 18, 505, 902, 584, 1934, 63052, 8305, 388, 311, 279, 62937, 17188, 42416, 16, 13128, 1701, 264, 19815, 259, 2058, 19179, 505, 264, 13128, 8162, 1686, 65033, 13, 1226, 7664, 279, 43785, 315, 63052, 8305, 388, 311, 1207, 9426, 220, 1049, 24, 473, 16, 45, 16, 323, 473, 18, 45, 17, 13, 12362, 264, 1646, 6727, 5603, 311, 5052, 21655, 43785, 11, 584, 1501, 430, 220, 1049, 24, 473, 16, 45, 16, 63052, 8305, 388, 4498, 1139, 3116, 259, 2058, 1207, 17171, 323, 430, 473, 18, 45, 17, 8305, 388, 4498, 1139, 2380, 1207, 17171, 13, 1789, 473, 16, 45, 16, 11, 1057, 23692, 374, 430, 279, 1403, 8592, 2442, 2058, 1207, 17171, 8024, 311, 3293, 323, 13970, 19405, 11, 902, 374, 13263, 449, 220, 1049, 24, 28522, 3440, 7969, 13, 22196, 58689, 527, 2561, 369, 473, 18, 45, 17, 11, 719, 1314, 1824, 3890, 287, 315, 8305, 388, 3727, 1521, 58689, 5107, 311, 9788, 13, 29438, 578, 8141, 315, 59854, 304, 264, 3823, 7187, 374, 264, 31376, 79967, 315, 279, 7187, 753, 3347, 14675, 311, 50600, 8624, 13, 1442, 7931, 529, 63052, 32466, 649, 387, 17303, 30357, 11, 814, 649, 387, 1511, 311, 24499, 2225, 279, 1404, 323, 18912, 315, 3347, 28817, 38305, 13, 578, 1403, 1401, 1772, 12, 752, 307, 8274, 11618, 430, 1205, 311, 387, 17303, 311, 1304, 420, 45478, 3284, 527, 279, 4478, 315, 63052, 24279, 323, 279, 4478, 315, 63052, 289, 44159, 13, 578, 4478, 315, 63052, 24279, 1772, 3502, 13421, 374, 11295, 320, 82089, 8, 369, 1455, 29962, 78284, 11, 719, 810, 5107, 311, 6767, 369, 810, 6485, 78284, 430, 3118, 279, 22852, 1887, 449, 264, 17226, 743, 315, 68937, 729, 13, 578, 4478, 315, 63052, 289, 44159, 11, 4869, 11, 374, 19029, 17303, 1524, 369, 29962, 78284, 13, 2057, 12722, 15025, 264, 7187, 753, 63052, 259, 2058, 8141, 311, 1202, 42620, 3925, 11, 13687, 11193, 315, 2225, 1521, 7969, 527, 5995, 13, 2057, 9788, 430, 420, 43738, 706, 1027, 2884, 12722, 11, 264, 3544, 41944, 449, 1317, 9860, 1833, 5352, 323, 24473, 63052, 22323, 1053, 387, 2631, 13, 19241, 1093, 1521, 527, 5107, 311, 1629, 323, 5107, 311, 1505, 304, 279, 12624, 17649, 1389, 2225, 304, 1749, 5848, 4500, 323, 2115, 8292, 13, 15903, 69226, 1113, 279, 4360, 374, 430, 63052, 22323, 527, 19029, 220, 1041, 4, 3230, 11, 323, 430, 3428, 11852, 5425, 31696, 535, 59854, 3629, 527, 12305, 555, 6376, 264, 4018, 12744, 369, 98042, 13, 2057, 3240, 24834, 1148, 459, 63052, 8141, 649, 3371, 603, 922, 264, 7187, 753, 42620, 3925, 11, 584, 33230, 264, 3544, 13230, 892, 12, 52243, 1446, 5848, 10795, 220, 16, 1174, 220, 17, 323, 459, 90380, 14830, 4007, 430, 5764, 13454, 8893, 1833, 27859, 311, 6767, 7969, 315, 63052, 289, 44159, 220, 18, 2652, 279, 3135, 315, 279, 1446, 5848, 10795, 527, 10666, 1618, 13, 763, 1517, 10529, 4458, 362, 17188, 574, 12146, 439, 279, 1853, 11968, 315, 2802, 439, 320, 602, 883, 433, 374, 459, 3062, 11, 31550, 1824, 2496, 15853, 3823, 1853, 11968, 11, 320, 14799, 883, 62937, 374, 1664, 32971, 83089, 2740, 11, 320, 63193, 883, 264, 24473, 323, 13454, 481, 1446, 5848, 65033, 574, 2561, 11, 323, 320, 17967, 883, 279, 3823, 7187, 21879, 4661, 912, 62937, 47165, 304, 1057, 4007, 3813, 315, 18561, 23315, 13, 578, 1176, 9395, 315, 420, 4007, 574, 311, 3351, 3201, 505, 279, 8026, 5603, 311, 1446, 2508, 1389, 902, 538, 9803, 7931, 439, 1446, 454, 437, 3486, 477, 1446, 606, 70, 1413, 220, 19, 1174, 220, 20, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 1389, 323, 311, 7664, 279, 16940, 6070, 315, 264, 4689, 41352, 2987, 63052, 2442, 2058, 8141, 555, 26619, 430, 459, 3927, 649, 9352, 311, 904, 1396, 315, 1446, 5848, 5415, 13, 578, 57916, 369, 264, 11944, 53944, 6492, 315, 63052, 259, 2058, 43785, 374, 430, 259, 2058, 5315, 477, 259, 2058, 21986, 1253, 387, 3025, 311, 3493, 2204, 23747, 2038, 389, 279, 955, 315, 19405, 11, 384, 1326, 13, 3293, 19579, 2536, 5621, 1189, 30020, 11, 477, 6156, 19579, 2536, 9999, 13, 578, 8026, 5603, 315, 538, 7922, 7931, 439, 1446, 454, 437, 3486, 323, 1446, 606, 70, 1413, 374, 539, 439, 39319, 439, 433, 1436, 387, 2728, 279, 90030, 315, 1063, 1446, 5848, 30525, 11, 323, 433, 374, 2736, 3967, 311, 617, 1403, 15325, 89173, 13, 5629, 11, 279, 45379, 907, 369, 1446, 454, 437, 18546, 374, 11383, 86085, 505, 264, 1912, 315, 6978, 449, 11007, 30883, 19405, 11, 555, 26984, 5804, 3916, 1189, 41529, 10688, 264, 2478, 5672, 477, 264, 2478, 4038, 1306, 13803, 42080, 13, 1115, 3445, 430, 279, 4495, 3851, 315, 279, 4018, 12744, 907, 374, 279, 22654, 315, 3293, 12104, 13795, 30020, 4856, 1109, 904, 3347, 30020, 13, 14636, 11, 19486, 420, 12447, 311, 264, 7187, 25480, 1446, 5848, 5425, 22327, 690, 4461, 1121, 304, 459, 79583, 315, 279, 1446, 454, 265, 838, 768, 13, 10657, 11, 8026, 24790, 304, 1446, 2508, 3135, 304, 15465, 477, 28093, 8500, 96771, 369, 10688, 449, 89614, 22323, 220, 23, 1174, 220, 24, 1174, 220, 605, 662, 11842, 95939, 29060, 315, 1446, 5848, 828, 527, 3118, 304, 279, 17649, 369, 264, 2134, 315, 78284, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 1174, 220, 972, 2737, 62937, 17188, 220, 777, 1174, 220, 508, 1174, 719, 1633, 2478, 315, 1521, 7978, 527, 3025, 311, 1427, 520, 2536, 8437, 4575, 15846, 22673, 323, 7000, 617, 279, 5569, 323, 16437, 10666, 1618, 13, 763, 279, 3118, 4007, 11, 584, 24564, 264, 3544, 743, 315, 4689, 41352, 2987, 41529, 10688, 14890, 439, 33247, 41529, 505, 17332, 52755, 323, 6520, 336, 354, 2508, 51048, 304, 3116, 24461, 304, 18561, 23315, 11, 505, 220, 1049, 24, 311, 220, 679, 18, 13, 12362, 264, 7315, 3502, 1517, 660, 21655, 34579, 5603, 11, 584, 2187, 369, 709, 311, 8254, 1446, 5848, 5415, 13, 2057, 2759, 369, 279, 3544, 6205, 1404, 304, 1057, 1646, 6727, 10537, 11, 584, 1005, 279, 99234, 8245, 69500, 11, 323, 311, 5766, 45478, 315, 993, 28626, 1446, 5848, 5415, 584, 743, 5217, 13186, 311, 6106, 430, 68695, 259, 2058, 5315, 527, 62057, 30450, 23222, 13, 1226, 22601, 83979, 430, 1446, 5848, 24790, 315, 62937, 63052, 8305, 388, 1053, 387, 2536, 95939, 323, 430, 4325, 323, 65009, 14675, 320, 39, 16, 45, 16, 1193, 8, 1053, 387, 5938, 449, 3738, 259, 2058, 5315, 13, 1226, 1766, 430, 473, 16, 45, 16, 63052, 259, 2058, 8141, 527, 1888, 21771, 1139, 3116, 259, 2058, 5315, 11, 430, 473, 18, 45, 17, 374, 1888, 21771, 1139, 2380, 5315, 11, 323, 430, 40065, 287, 1253, 617, 32098, 264, 4686, 24790, 315, 473, 18, 45, 17, 8305, 388, 13, 18591, 362, 2860, 315, 220, 508, 11, 9756, 35737, 1051, 14890, 323, 12793, 369, 63052, 32466, 555, 13128, 8162, 1686, 13, 578, 10688, 4097, 6978, 24096, 24461, 304, 3116, 9919, 1389, 17723, 34382, 93255, 4409, 320, 77, 284, 220, 22915, 23, 705, 121659, 121027, 320, 77, 284, 220, 21789, 15, 705, 28326, 263, 11583, 36992, 354, 320, 77, 284, 220, 17448, 19, 705, 323, 67051, 320, 77, 128257, 198, 128256, 78191, 198, 791, 3392, 315, 62937, 19440, 59854, 3118, 304, 459, 3927, 596, 6680, 649, 13519, 539, 1193, 422, 814, 10534, 279, 20236, 11, 719, 13893, 994, 29096, 9455, 430, 1436, 7417, 8624, 16967, 304, 279, 21965, 1233, 11, 1405, 20236, 3280, 374, 653, 2518, 13, 763, 279, 7928, 4007, 315, 1202, 3169, 11, 459, 6625, 2128, 11, 6197, 555, 12074, 505, 279, 26275, 3907, 33135, 8483, 8113, 304, 17723, 34382, 93255, 4409, 11, 23315, 11, 279, 9939, 82888, 13235, 14821, 304, 98877, 11, 26746, 11, 323, 13813, 3314, 3907, 11, 11054, 63052, 32466, 430, 8024, 311, 3293, 323, 3347, 14675, 311, 279, 20236, 26800, 473, 16, 45, 16, 22416, 26800, 6532, 304, 279, 220, 1049, 24, 20236, 28522, 13, 362, 5684, 23524, 279, 3495, 374, 4756, 304, 264, 5887, 4360, 315, 279, 8486, 38130, 29140, 13, 330, 35, 56407, 77871, 323, 28817, 38305, 527, 3629, 41223, 555, 26060, 7931, 889, 1501, 13803, 315, 19405, 11, 719, 420, 1193, 41255, 1274, 889, 527, 14363, 3403, 311, 387, 11054, 1359, 1071, 7553, 57647, 13789, 72, 11, 22712, 14561, 315, 34458, 520, 13813, 3314, 323, 264, 3063, 3229, 315, 279, 5684, 13, 330, 2409, 6680, 10688, 11, 499, 649, 12602, 5127, 430, 3596, 574, 29374, 1606, 7931, 527, 539, 3025, 311, 10477, 872, 63052, 17738, 1210, 95951, 10233, 10726, 2403, 29962, 3440, 11, 323, 872, 5219, 37393, 304, 279, 9546, 315, 459, 19405, 1093, 62937, 13, 79904, 832, 2305, 1306, 19405, 11, 279, 1396, 315, 20236, 19440, 59854, 304, 279, 6680, 12302, 311, 18979, 11, 719, 1063, 59854, 3136, 311, 4319, 6468, 1317, 1306, 279, 17188, 706, 23803, 13, 763, 279, 3347, 11, 14248, 617, 17303, 279, 20545, 315, 59854, 9861, 311, 10765, 3508, 459, 3927, 706, 1027, 15246, 311, 279, 17188, 11, 719, 279, 3135, 315, 1521, 7177, 617, 11383, 1027, 7347, 311, 23524, 279, 9546, 477, 19821, 315, 3347, 19405, 13, 330, 644, 420, 4007, 584, 8710, 430, 1070, 374, 264, 2763, 810, 2038, 304, 22323, 315, 63052, 20545, 1109, 1120, 9546, 477, 19821, 1359, 1071, 13789, 72, 13, 330, 8140, 3135, 1501, 430, 63052, 20545, 1288, 387, 3025, 311, 3493, 2038, 922, 279, 18912, 315, 3347, 62937, 19405, 1210, 1115, 2038, 374, 5423, 15525, 304, 35148, 92399, 13, 330, 644, 6940, 349, 13918, 1093, 279, 3723, 4273, 11, 584, 2643, 6667, 6680, 10688, 994, 279, 20236, 3280, 374, 927, 311, 1518, 1148, 11668, 315, 1274, 1051, 29374, 2391, 430, 20236, 3280, 1359, 13789, 72, 15100, 13, 330, 4071, 304, 279, 21965, 1233, 1070, 374, 912, 20236, 3280, 44603, 1253, 387, 15320, 54828, 477, 433, 1436, 2586, 304, 17301, 13, 1442, 682, 499, 6767, 374, 279, 9546, 477, 19821, 315, 59854, 11, 499, 649, 956, 8417, 994, 1884, 7931, 1051, 29374, 1210, 3562, 1534, 8162, 4539, 315, 19252, 315, 279, 62937, 26800, 473, 16, 45, 16, 11, 902, 574, 6532, 304, 279, 220, 1049, 24, 20236, 28522, 13, 16666, 25, 5165, 10181, 315, 2052, 43043, 323, 88911, 1245, 70674, 11, 5165, 73828, 315, 6401, 578, 3495, 2128, 30239, 927, 220, 508, 11, 931, 6680, 10688, 505, 3116, 24461, 304, 18561, 23315, 11, 4529, 1475, 1403, 4038, 1990, 220, 1049, 24, 311, 220, 679, 18, 13, 330, 2028, 374, 279, 7928, 4007, 315, 1202, 3169, 11, 323, 2587, 29564, 5528, 4460, 311, 387, 8040, 369, 420, 6492, 1359, 1071, 64261, 60223, 125486, 452, 9379, 11, 19560, 5575, 520, 26275, 3907, 33135, 8483, 8113, 520, 279, 892, 315, 279, 4007, 323, 1176, 3229, 315, 279, 5684, 13, 1115, 38883, 49326, 690, 2187, 279, 2128, 311, 2472, 704, 279, 473, 16, 45, 16, 20236, 26800, 596, 30295, 304, 279, 21965, 1233, 304, 279, 1828, 10474, 315, 872, 3495, 13, 330, 791, 220, 1049, 24, 62937, 28522, 15972, 603, 279, 12939, 315, 8830, 279, 3925, 315, 14675, 304, 279, 4029, 439, 264, 8331, 315, 264, 28522, 596, 5536, 1359, 1071, 56679, 30417, 454, 70991, 11, 2010, 315, 279, 6011, 315, 650, 8869, 40657, 520, 279, 9939, 82888, 13235, 14821, 323, 264, 3063, 3229, 315, 279, 4007, 13, 330, 8586, 11, 584, 19678, 264, 11775, 5603, 430, 11193, 264, 7187, 596, 14675, 3925, 311, 5131, 54828, 42068, 13, 1115, 990, 690, 1520, 603, 8720, 889, 374, 1455, 520, 5326, 2391, 264, 502, 62937, 31188, 1210, 578, 3495, 2128, 4613, 3116, 11306, 315, 473, 16, 45, 16, 19440, 63052, 32466, 13, 578, 8592, 32466, 13519, 14675, 311, 473, 16, 45, 16, 2949, 279, 1566, 4848, 4038, 11, 279, 2132, 8592, 32466, 13519, 14675, 7191, 1109, 4848, 4038, 4972, 11, 323, 279, 15821, 1403, 11306, 315, 32466, 13519, 912, 3766, 14675, 311, 279, 17188, 13, 5560, 315, 1521, 11306, 1436, 2187, 586, 2890, 7510, 304, 1023, 35148, 10687, 311, 8417, 19405, 7969, 315, 473, 16, 45, 16, 449, 37538, 25936, 11, 369, 3187, 11, 555, 23061, 264, 27084, 315, 279, 7187, 1475, 6186, 311, 8417, 279, 3766, 1060, 596, 19405, 4478, 13, 578, 12074, 1511, 264, 13128, 8162, 1686, 29096, 1579, 43847, 631, 3544, 13230, 1296, 430, 11193, 22639, 315, 3544, 5219, 315, 28896, 304, 15638, 50617, 6767, 63052, 32466, 13, 80110, 304, 279, 26746, 11, 420, 12309, 502, 15105, 6276, 24473, 63052, 22323, 449, 1633, 2678, 27378, 315, 6680, 13, 330, 2028, 13128, 8162, 1686, 706, 1579, 53823, 7697, 3225, 323, 649, 3493, 76041, 311, 220, 845, 2204, 62937, 42400, 1359, 1071, 9939, 7678, 409, 19215, 258, 11, 10195, 27692, 54611, 520, 9939, 82888, 13235, 14821, 323, 459, 3229, 315, 279, 4007, 13, 330, 791, 2678, 8286, 315, 6680, 2631, 5825, 264, 35388, 1648, 311, 2804, 3544, 62057, 5848, 7978, 1210, 330, 2028, 8162, 1686, 11, 323, 279, 5217, 2038, 922, 892, 315, 19405, 505, 63052, 32466, 11, 1436, 2349, 1268, 584, 8891, 8624, 304, 279, 21965, 1233, 1359, 11621, 13789, 72, 13, 330, 34814, 11, 586, 2890, 6067, 8891, 59854, 1306, 459, 31188, 477, 369, 279, 7580, 315, 3495, 11, 719, 1455, 315, 279, 16967, 5149, 24400, 389, 13803, 1555, 8952, 6108, 22156, 13, 3296, 1828, 13515, 11, 584, 1253, 387, 3025, 311, 2804, 5912, 22156, 315, 6680, 11, 902, 1053, 3041, 603, 264, 2731, 6945, 315, 279, 19338, 54828, 1555, 264, 7187, 13, 1115, 3169, 315, 22156, 374, 5423, 3062, 304, 35148, 5961, 1405, 264, 2763, 315, 11775, 42068, 34044, 1210, 220, 128257, 198 ]

2,378

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Imaging the activity of neurons that are widely distributed across brain regions deep in scattering tissue at high speed remains challenging. Here, we introduce an open-source system with Dual Independent Enhanced Scan Engines for Large field-of-view Two-Photon imaging (Diesel2p). Combining optical design, adaptive optics, and temporal multiplexing, the system offers subcellular resolution over a large field-of-view of ~25 mm 2 , encompassing distances up to 7 mm, with independent scan engines. We demonstrate the flexibility and various use cases of this system for calcium imaging of neurons in the living brain. Introduction Two-photon microscopy 1 has enabled subcellular resolution functional imaging of neural activity deep in scattering tissue, including mammalian brains 2 . However, conventional microscopes provide subcellular resolution over only small fields-of-view (FOVs), ~Ø0.5 mm. This limitation precludes measurements of neural activity distributed across cortical areas that are millimeters apart (Fig. 1a ). Obtaining subcellular resolution over a large FOV involves scaling up the dimensions of the objective lens and other optics, due to the Smith-Helmholtz invariant, also known as the optical invariant 3 , 4 , 5 , 6 . However, that is only half of the solution. Since high light intensities are required for efficient multiphoton excitation, two-photon imaging is typically implemented as a point-scanning approach, where an excitation laser beam is scanned over the tissue. Thus, each voxel sampled entails a time cost, and the scan engine design constrains the temporal resolution 7 . Temporal multiplexing of simultaneously scanned beams can increase throughput 8 , and these can have either a fixed configuration 9 , 10 , 11 , or can be reconfigured during the experiment axially 12 , 13 , 14 or axially and laterally 15 , 16 . However, these simultaneously scanned, or “yoked”, multi-beam configurations strongly constrain sampling, because they preclude varying the scan parameters among the multiplexed beams. Optimal scan parameters (e.g., frame rate, scan region size) vary across distributed neural circuitry and experimental requirements, but yoked scanning requires using the same scan parameters for all beams. Therefore, a system featuring both a large imaging volume and independent multi-region imaging is needed, and can enable new experiments. Fig. 1: Diesel2p system features, layout, and performance benchmarks. a Functional cortical areas in the mouse brain are widely distributed. A field-of-view (FOV) of Ø5 mm can encompass multiple brain areas, and independent scan engines can capture ongoing neural activity in multiple cortical areas simultaneously with optimized scan parameters. b Two imaging beams are temporally multiplexed and independently positioned in XY using two sets of resonant-galvo-galvo scan engines. First, overall power is attenuated using a half-wave plate (λ/2 WP) and a polarizing beam splitting cube (PBS). A 2X beam expander (1:2 BE) enlarges the beam for the clear aperture of the deformable mirrors adaptive optics (AO). A custom single-prism pre-chirper offsets system dispersion to maintain transform-limited pulses at the focal plane. A second λ/2 WP and PBS pair divides the beam into two pathways. Pathway 2 (s-polarization in orange) passes to a delay arm where it travels 1.87 m further than Pathway 1 using mirrors, thus delaying it by 6.25 ns relative to Pathway 1 (p-polarization in blue). Both pathways each proceed to deformable mirrors for adjusting the focal plane and correcting optical aberrations before being directed to resonant-galvo-galvo scan engines. All scanning mirrors are optically relayed to each other. Each pathway then passes through a scan lens before being combined with a beam recombination relay. A tube lens and an infrared-reflective dichroic mirror relay the two multiplexed beams onto the back aperture of the objective. Fluorescence (green) is directed to a photomultiplier tube (PMT) via an assembly of collection lenses (CL1, CL2, CL3). c An oblique view of a 3-D model of the system and its footprint. d A top view with the arrangement of the two scan engines highlighted. e Plot of the model Strehl ratio across the scan area indicates diffraction limited performance (Strehl ratio > 0.8) across ~25 mm 2 , significantly larger than the area of the dashed 5-mm diameter circle (~19.6 mm 2 ) by ~28%. f Multiphoton excitation PSF measurements were made with subresolution beads (0.2 µm) in agar under a coverslip at three depths and four locations, for both of the AO-equipped, temporally multiplexed beam pathways. FWHM of the Gaussian fits for measurements from the fluorescence beads radially and axially are calculated and plotted. Eight beads ( n = 8) at each locations are measured, except that there are 7 beads ( n = 7) measured on axis at the depth of 500 µm. Data are presented as mean values ± S.D. g XY images of a calibrated, structured fluorescent sample with a periodic line pattern (5 lines per millimeter) in two orientations acquired under the full scan range of the system. Each image shows 25 lines on the top edge (left image) and on the left edge (right image), receptively, verifying a 5 × 5 mm FOV. h The XZ image along the orange dashed line and the YZ image along green dashed line in ( g ) are also plotted. The imaging pattern is colinear with the straight lines, suggesting a flat field both in x and y directions across the FOV. Full size image In this work, we develop a system with a large FOV, subcellular resolution, and dual independent scan engines for highly flexible, asymmetric multi-point sampling of distributed neural circuitry. Here, we present a custom two-photon system with dual scan engines that can operate completely independently. Each arm has optical access to the same large imaging volume (~25 mm 2 FOV) over which subcellular resolution is maintained in scattering tissue to typical 2-photon imaging depths. These two arms use adaptive optics (AO) for wavefront shaping, temporal multiplexing for simultaneous imaging, and polarization optics for beam recombination. Due to the independence of the arms, and the use of polarization optics for beam combining, the input lasers can come from the same source or different sources (multi-wavelength). Moreover, each arm can use multiple", "role": "user" }, { "content": "Advancing our understanding of the human brain will require new insights into how neural circuitry works in mammals, including laboratory mice. These investigations require monitoring brain activity with a microscope that provides resolution high enough to see individual neurons and their neighbors. Two-photon fluorescence microscopy has significantly enhanced researchers' ability to do just that, and the lab of Spencer LaVere Smith, an associate professor in the Department of Electrical and Computer Engineering at UC Santa Barbara, is a hotbed of research for advancing the technology. As principal investigator on the five-year, $9 million NSF-funded Next Generation Multiphoton Neuroimaging Consortium (Nemonic) hub, which was born of President Obama's BRAIN Initiative and is headquartered at UCSB, Smith is working to \"push the frontiers of multi-photon microscopy for neuroscience research.\" In the Nov. 17 issue of Nature Communications, Smith and his co-authors report the development of a new microscope they describe as \"Dual Independent Enhanced Scan Engines for Large Field-of-view Two-Photon imaging (Diesel2p).\" Their two-photon microscope provides unprecedented brain-imaging ability. The device has the largest field of view (up to 25 square millimeters) of any such instrument, allowing it to provide subcellular resolution of multiple areas of the brain. \"We're optimizing for three things: resolution to see individual neurons, a field of view to capture multiple brain regions simultaneously, and imaging speed to capture changes in neuron activity during behavior,\" Smith explained. \"The events that we're interested in imaging last less than a second, so we don't have time to move the microscope; we have to get everything in one shot, while still making sure that the optics can focus ultrafast pulses of laser light.\" The powerful lasers that drive two-photon imaging systems, each costing about $250,000, deliver ultrafast, ultra-intense pulses of light, each of which is more than a billion times brighter than sunlight, and lasts 0.0001 nanosecond. A single beam, with 80 million pulses per second, is split into two wholly independent scan engine arms, enabling the microscope to scan two regions simultaneously, with each configured to different imaging parameters. In previous iterations of the instrument, the two lasers were yoked and configured to the same parameters, an arrangement that strongly constrains sampling. Optimal scan parameters, such as frame rate and scan region size, vary across distributed neural circuitry and experimental requirements, and the new instrument allows for different scan parameters to be used for both beams. The new device, which incorporates several custom-designed and custom-manufactured elements, including the optical relays, the scan lens, the tube lens and the objective lens, is already being broadly adopted for its ability to provide high-speed imaging of neural activity in widely scattered brain regions. Smith is committed to ensuring open access to the instrument. Long before this new paper was published, he and his co-authors released a preprint that included the engineering details needed to replicate it. They also shared the technology with colleagues at Boston University, where researchers in Jerry Chen's lab have already made modifications to suit their own experiments. \"This is exciting,\" Smith said. \"They didn't have to start from scratch like we did. They could build off of our work. Jerry's paper was published back-to-back with ours, and two companies, INSS and CoSys, have sold systems based on our designs. Since there is no patent, and won't be, this technology is free for all to use and modify however they see fit.\" Two-photon microscopy is a specialized type of fluorescent microscopy. To perform such work in Smith's lab, researchers genetically engineer mice so that their neurons contain a fluorescent indicator of neuron activity. The indicator was made by combining a fluorescent protein from jellyfish and a calcium-binding protein that exists in nature. The approach leverages the brief, orders-of-magnitude increase in calcium that a neuron experiences when firing. When the laser is pointed at the neuron, and the neuron is firing, calcium comes in, the protein finds the calcium and, ultimately, fluoresces. Two-photon imaging enhances fluorescence microscopy by employing the quantum behavior of photons in a way that prevents a considerable amount of out-of-focus fluorescence light from being generated. In normal optical microscopy, the light from the source used to excite the sample enters it in a way that produces a vertical cone of light that narrows down to the target focus area, and then an inverted cone below that point. Any light that is not at the narrowest point is out of focus. The light in a two-photon microscope behaves differently, creating a single point of light (and no cones of light) that is in sharp focus, eliminating all out-of-focus light from reaching the imaging lens. \"The image reveals only light from that plane we're looking at, without much background signal from above or below the plane,\" Smith explained. \"The brain has optical properties and a texture like butter; it's full of lipids and aqueous solutions that make it hard to see through. With normal optical imaging, you can see only the very top of the brain. Two-photon imaging allows us to image deeper down and still attain sub-cellular resolution.\" Another advantage of two-photon excitation light is that it uses lower-energy, longer-wavelength light (in the near-infrared range). Such light scatters less when passing through tissue, so it can be sharply focused deeper into tissue. Moreover, the lower-energy light is less damaging to the sample than shorter wavelengths, such as ultraviolet light. Smith's lab tested the device in experiments on mice, observing their brains while they performed tasks such as watching videos or navigating virtual reality environments. Each mouse has received a glass implant in its skull, providing a literal window for the microscope into its brain. \"I'm motivated by trying to understand the computational principles in neural circuitry that let us do interesting things that we can't currently replicate in machines,\" he said. \"We can build a machine to do a lot of things better than we can. But for other things, we can't. We train teenagers to drive cars, but self-driving cars fail in a wide array of situations where humans do not. The systems we use for deep learning are based on insights from the brain, but they are only a few insights, and not the whole story. They work pretty well, but are still fragile. By comparison, I can put a mouse in a room where it has never been, and it will run to someplace where I can't reach it. It won't run into any walls. It does this super reliably and runs on about a watt of power. \"There are interesting computational principles that we cannot yet replicate in human-made machines that exist in the brains of mice,\" Smith continued, \"and I want to start to uncover that. It's why I wanted to build this microscope.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Imaging the activity of neurons that are widely distributed across brain regions deep in scattering tissue at high speed remains challenging. Here, we introduce an open-source system with Dual Independent Enhanced Scan Engines for Large field-of-view Two-Photon imaging (Diesel2p). Combining optical design, adaptive optics, and temporal multiplexing, the system offers subcellular resolution over a large field-of-view of ~25 mm 2 , encompassing distances up to 7 mm, with independent scan engines. We demonstrate the flexibility and various use cases of this system for calcium imaging of neurons in the living brain. Introduction Two-photon microscopy 1 has enabled subcellular resolution functional imaging of neural activity deep in scattering tissue, including mammalian brains 2 . However, conventional microscopes provide subcellular resolution over only small fields-of-view (FOVs), ~Ø0.5 mm. This limitation precludes measurements of neural activity distributed across cortical areas that are millimeters apart (Fig. 1a ). Obtaining subcellular resolution over a large FOV involves scaling up the dimensions of the objective lens and other optics, due to the Smith-Helmholtz invariant, also known as the optical invariant 3 , 4 , 5 , 6 . However, that is only half of the solution. Since high light intensities are required for efficient multiphoton excitation, two-photon imaging is typically implemented as a point-scanning approach, where an excitation laser beam is scanned over the tissue. Thus, each voxel sampled entails a time cost, and the scan engine design constrains the temporal resolution 7 . Temporal multiplexing of simultaneously scanned beams can increase throughput 8 , and these can have either a fixed configuration 9 , 10 , 11 , or can be reconfigured during the experiment axially 12 , 13 , 14 or axially and laterally 15 , 16 . However, these simultaneously scanned, or “yoked”, multi-beam configurations strongly constrain sampling, because they preclude varying the scan parameters among the multiplexed beams. Optimal scan parameters (e.g., frame rate, scan region size) vary across distributed neural circuitry and experimental requirements, but yoked scanning requires using the same scan parameters for all beams. Therefore, a system featuring both a large imaging volume and independent multi-region imaging is needed, and can enable new experiments. Fig. 1: Diesel2p system features, layout, and performance benchmarks. a Functional cortical areas in the mouse brain are widely distributed. A field-of-view (FOV) of Ø5 mm can encompass multiple brain areas, and independent scan engines can capture ongoing neural activity in multiple cortical areas simultaneously with optimized scan parameters. b Two imaging beams are temporally multiplexed and independently positioned in XY using two sets of resonant-galvo-galvo scan engines. First, overall power is attenuated using a half-wave plate (λ/2 WP) and a polarizing beam splitting cube (PBS). A 2X beam expander (1:2 BE) enlarges the beam for the clear aperture of the deformable mirrors adaptive optics (AO). A custom single-prism pre-chirper offsets system dispersion to maintain transform-limited pulses at the focal plane. A second λ/2 WP and PBS pair divides the beam into two pathways. Pathway 2 (s-polarization in orange) passes to a delay arm where it travels 1.87 m further than Pathway 1 using mirrors, thus delaying it by 6.25 ns relative to Pathway 1 (p-polarization in blue). Both pathways each proceed to deformable mirrors for adjusting the focal plane and correcting optical aberrations before being directed to resonant-galvo-galvo scan engines. All scanning mirrors are optically relayed to each other. Each pathway then passes through a scan lens before being combined with a beam recombination relay. A tube lens and an infrared-reflective dichroic mirror relay the two multiplexed beams onto the back aperture of the objective. Fluorescence (green) is directed to a photomultiplier tube (PMT) via an assembly of collection lenses (CL1, CL2, CL3). c An oblique view of a 3-D model of the system and its footprint. d A top view with the arrangement of the two scan engines highlighted. e Plot of the model Strehl ratio across the scan area indicates diffraction limited performance (Strehl ratio > 0.8) across ~25 mm 2 , significantly larger than the area of the dashed 5-mm diameter circle (~19.6 mm 2 ) by ~28%. f Multiphoton excitation PSF measurements were made with subresolution beads (0.2 µm) in agar under a coverslip at three depths and four locations, for both of the AO-equipped, temporally multiplexed beam pathways. FWHM of the Gaussian fits for measurements from the fluorescence beads radially and axially are calculated and plotted. Eight beads ( n = 8) at each locations are measured, except that there are 7 beads ( n = 7) measured on axis at the depth of 500 µm. Data are presented as mean values ± S.D. g XY images of a calibrated, structured fluorescent sample with a periodic line pattern (5 lines per millimeter) in two orientations acquired under the full scan range of the system. Each image shows 25 lines on the top edge (left image) and on the left edge (right image), receptively, verifying a 5 × 5 mm FOV. h The XZ image along the orange dashed line and the YZ image along green dashed line in ( g ) are also plotted. The imaging pattern is colinear with the straight lines, suggesting a flat field both in x and y directions across the FOV. Full size image In this work, we develop a system with a large FOV, subcellular resolution, and dual independent scan engines for highly flexible, asymmetric multi-point sampling of distributed neural circuitry. Here, we present a custom two-photon system with dual scan engines that can operate completely independently. Each arm has optical access to the same large imaging volume (~25 mm 2 FOV) over which subcellular resolution is maintained in scattering tissue to typical 2-photon imaging depths. These two arms use adaptive optics (AO) for wavefront shaping, temporal multiplexing for simultaneous imaging, and polarization optics for beam recombination. Due to the independence of the arms, and the use of polarization optics for beam combining, the input lasers can come from the same source or different sources (multi-wavelength). Moreover, each arm can use multiple<|im_end|> <|im_start|>assistant Advancing our understanding of the human brain will require new insights into how neural circuitry works in mammals, including laboratory mice. These investigations require monitoring brain activity with a microscope that provides resolution high enough to see individual neurons and their neighbors. Two-photon fluorescence microscopy has significantly enhanced researchers' ability to do just that, and the lab of Spencer LaVere Smith, an associate professor in the Department of Electrical and Computer Engineering at UC Santa Barbara, is a hotbed of research for advancing the technology. As principal investigator on the five-year, $9 million NSF-funded Next Generation Multiphoton Neuroimaging Consortium (Nemonic) hub, which was born of President Obama's BRAIN Initiative and is headquartered at UCSB, Smith is working to "push the frontiers of multi-photon microscopy for neuroscience research." In the Nov. 17 issue of Nature Communications, Smith and his co-authors report the development of a new microscope they describe as "Dual Independent Enhanced Scan Engines for Large Field-of-view Two-Photon imaging (Diesel2p)." Their two-photon microscope provides unprecedented brain-imaging ability. The device has the largest field of view (up to 25 square millimeters) of any such instrument, allowing it to provide subcellular resolution of multiple areas of the brain. "We're optimizing for three things: resolution to see individual neurons, a field of view to capture multiple brain regions simultaneously, and imaging speed to capture changes in neuron activity during behavior," Smith explained. "The events that we're interested in imaging last less than a second, so we don't have time to move the microscope; we have to get everything in one shot, while still making sure that the optics can focus ultrafast pulses of laser light." The powerful lasers that drive two-photon imaging systems, each costing about $250,000, deliver ultrafast, ultra-intense pulses of light, each of which is more than a billion times brighter than sunlight, and lasts 0.0001 nanosecond. A single beam, with 80 million pulses per second, is split into two wholly independent scan engine arms, enabling the microscope to scan two regions simultaneously, with each configured to different imaging parameters. In previous iterations of the instrument, the two lasers were yoked and configured to the same parameters, an arrangement that strongly constrains sampling. Optimal scan parameters, such as frame rate and scan region size, vary across distributed neural circuitry and experimental requirements, and the new instrument allows for different scan parameters to be used for both beams. The new device, which incorporates several custom-designed and custom-manufactured elements, including the optical relays, the scan lens, the tube lens and the objective lens, is already being broadly adopted for its ability to provide high-speed imaging of neural activity in widely scattered brain regions. Smith is committed to ensuring open access to the instrument. Long before this new paper was published, he and his co-authors released a preprint that included the engineering details needed to replicate it. They also shared the technology with colleagues at Boston University, where researchers in Jerry Chen's lab have already made modifications to suit their own experiments. "This is exciting," Smith said. "They didn't have to start from scratch like we did. They could build off of our work. Jerry's paper was published back-to-back with ours, and two companies, INSS and CoSys, have sold systems based on our designs. Since there is no patent, and won't be, this technology is free for all to use and modify however they see fit." Two-photon microscopy is a specialized type of fluorescent microscopy. To perform such work in Smith's lab, researchers genetically engineer mice so that their neurons contain a fluorescent indicator of neuron activity. The indicator was made by combining a fluorescent protein from jellyfish and a calcium-binding protein that exists in nature. The approach leverages the brief, orders-of-magnitude increase in calcium that a neuron experiences when firing. When the laser is pointed at the neuron, and the neuron is firing, calcium comes in, the protein finds the calcium and, ultimately, fluoresces. Two-photon imaging enhances fluorescence microscopy by employing the quantum behavior of photons in a way that prevents a considerable amount of out-of-focus fluorescence light from being generated. In normal optical microscopy, the light from the source used to excite the sample enters it in a way that produces a vertical cone of light that narrows down to the target focus area, and then an inverted cone below that point. Any light that is not at the narrowest point is out of focus. The light in a two-photon microscope behaves differently, creating a single point of light (and no cones of light) that is in sharp focus, eliminating all out-of-focus light from reaching the imaging lens. "The image reveals only light from that plane we're looking at, without much background signal from above or below the plane," Smith explained. "The brain has optical properties and a texture like butter; it's full of lipids and aqueous solutions that make it hard to see through. With normal optical imaging, you can see only the very top of the brain. Two-photon imaging allows us to image deeper down and still attain sub-cellular resolution." Another advantage of two-photon excitation light is that it uses lower-energy, longer-wavelength light (in the near-infrared range). Such light scatters less when passing through tissue, so it can be sharply focused deeper into tissue. Moreover, the lower-energy light is less damaging to the sample than shorter wavelengths, such as ultraviolet light. Smith's lab tested the device in experiments on mice, observing their brains while they performed tasks such as watching videos or navigating virtual reality environments. Each mouse has received a glass implant in its skull, providing a literal window for the microscope into its brain. "I'm motivated by trying to understand the computational principles in neural circuitry that let us do interesting things that we can't currently replicate in machines," he said. "We can build a machine to do a lot of things better than we can. But for other things, we can't. We train teenagers to drive cars, but self-driving cars fail in a wide array of situations where humans do not. The systems we use for deep learning are based on insights from the brain, but they are only a few insights, and not the whole story. They work pretty well, but are still fragile. By comparison, I can put a mouse in a room where it has never been, and it will run to someplace where I can't reach it. It won't run into any walls. It does this super reliably and runs on about a watt of power. "There are interesting computational principles that we cannot yet replicate in human-made machines that exist in the brains of mice," Smith continued, "and I want to start to uncover that. It's why I wanted to build this microscope." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 65606, 279, 5820, 315, 34313, 430, 527, 13882, 4332, 4028, 8271, 13918, 5655, 304, 72916, 20438, 520, 1579, 4732, 8625, 17436, 13, 5810, 11, 584, 19678, 459, 1825, 31874, 1887, 449, 34759, 22765, 62549, 32208, 95418, 369, 20902, 2115, 8838, 23318, 9220, 12, 94150, 32758, 320, 48889, 301, 17, 79, 570, 23262, 5859, 29393, 2955, 11, 48232, 70985, 11, 323, 37015, 12842, 2635, 287, 11, 279, 1887, 6209, 1207, 5997, 1299, 11175, 927, 264, 3544, 2115, 8838, 23318, 315, 4056, 914, 9653, 220, 17, 1174, 38632, 287, 27650, 709, 311, 220, 22, 9653, 11, 449, 9678, 8737, 21787, 13, 1226, 20461, 279, 25152, 323, 5370, 1005, 5157, 315, 420, 1887, 369, 35719, 32758, 315, 34313, 304, 279, 5496, 8271, 13, 29438, 9220, 63837, 26934, 92914, 220, 16, 706, 9147, 1207, 5997, 1299, 11175, 16003, 32758, 315, 30828, 5820, 5655, 304, 72916, 20438, 11, 2737, 36041, 10700, 35202, 220, 17, 662, 4452, 11, 21349, 8162, 82025, 3493, 1207, 5997, 1299, 11175, 927, 1193, 2678, 5151, 8838, 23318, 320, 3873, 52837, 705, 4056, 115554, 15, 13, 20, 9653, 13, 1115, 20893, 864, 7548, 22323, 315, 30828, 5820, 4332, 4028, 83619, 5789, 430, 527, 2606, 55336, 10980, 320, 30035, 13, 220, 16, 64, 7609, 57747, 2101, 1207, 5997, 1299, 11175, 927, 264, 3544, 22512, 53, 18065, 28041, 709, 279, 15696, 315, 279, 16945, 18848, 323, 1023, 70985, 11, 4245, 311, 279, 9259, 11529, 24037, 71, 6312, 89, 58720, 11, 1101, 3967, 439, 279, 29393, 58720, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 662, 4452, 11, 430, 374, 1193, 4376, 315, 279, 6425, 13, 8876, 1579, 3177, 25228, 1385, 527, 2631, 369, 11297, 12842, 10847, 263, 3521, 7709, 11, 1403, 63837, 26934, 32758, 374, 11383, 11798, 439, 264, 1486, 31419, 6073, 5603, 11, 1405, 459, 3521, 7709, 21120, 24310, 374, 48548, 927, 279, 20438, 13, 14636, 11, 1855, 61284, 49976, 71204, 264, 892, 2853, 11, 323, 279, 8737, 4817, 2955, 19477, 1771, 279, 37015, 11175, 220, 22, 662, 20539, 10020, 12842, 2635, 287, 315, 25291, 48548, 51045, 649, 5376, 64862, 220, 23, 1174, 323, 1521, 649, 617, 3060, 264, 8521, 6683, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 477, 649, 387, 312, 82543, 2391, 279, 9526, 3944, 34575, 220, 717, 1174, 220, 1032, 1174, 220, 975, 477, 3944, 34575, 323, 3010, 750, 220, 868, 1174, 220, 845, 662, 4452, 11, 1521, 25291, 48548, 11, 477, 1054, 88, 11059, 9520, 7447, 15502, 309, 33483, 16917, 80799, 25936, 11, 1606, 814, 864, 866, 29865, 279, 8737, 5137, 4315, 279, 12842, 2635, 291, 51045, 13, 16963, 2931, 8737, 5137, 320, 68, 1326, 2637, 4124, 4478, 11, 8737, 5654, 1404, 8, 13592, 4028, 4332, 30828, 16622, 894, 323, 22772, 8670, 11, 719, 379, 11059, 36201, 7612, 1701, 279, 1890, 8737, 5137, 369, 682, 51045, 13, 15636, 11, 264, 1887, 16850, 2225, 264, 3544, 32758, 8286, 323, 9678, 7447, 61779, 32758, 374, 4460, 11, 323, 649, 7431, 502, 21896, 13, 23966, 13, 220, 16, 25, 54894, 17, 79, 1887, 4519, 11, 6932, 11, 323, 5178, 63119, 13, 264, 55550, 83619, 5789, 304, 279, 8814, 8271, 527, 13882, 4332, 13, 362, 2115, 8838, 23318, 320, 3873, 53, 8, 315, 90043, 20, 9653, 649, 38632, 5361, 8271, 5789, 11, 323, 9678, 8737, 21787, 649, 12602, 14529, 30828, 5820, 304, 5361, 83619, 5789, 25291, 449, 34440, 8737, 5137, 13, 293, 9220, 32758, 51045, 527, 19502, 750, 12842, 2635, 291, 323, 29235, 35328, 304, 58419, 1701, 1403, 7437, 315, 29280, 519, 2427, 278, 3415, 2427, 278, 3415, 8737, 21787, 13, 5629, 11, 8244, 2410, 374, 57732, 660, 1701, 264, 4376, 89354, 12235, 320, 34586, 14, 17, 24134, 8, 323, 264, 25685, 4954, 24310, 45473, 24671, 320, 83609, 570, 362, 220, 17, 55, 24310, 1367, 8363, 320, 16, 25, 17, 7354, 8, 41039, 288, 279, 24310, 369, 279, 2867, 58101, 315, 279, 79212, 481, 41585, 48232, 70985, 320, 19268, 570, 362, 2587, 3254, 27748, 2191, 864, 11843, 404, 716, 36146, 1887, 86712, 311, 10519, 5276, 2922, 32611, 66557, 520, 279, 42199, 11277, 13, 362, 2132, 49438, 14, 17, 24134, 323, 60145, 6857, 65928, 279, 24310, 1139, 1403, 44014, 13, 8092, 3195, 220, 17, 320, 82, 2320, 7569, 2065, 304, 19087, 8, 16609, 311, 264, 7781, 6916, 1405, 433, 35292, 220, 16, 13, 4044, 296, 4726, 1109, 8092, 3195, 220, 16, 1701, 41585, 11, 8617, 80430, 433, 555, 220, 21, 13, 914, 12548, 8844, 311, 8092, 3195, 220, 16, 320, 79, 2320, 7569, 2065, 304, 6437, 570, 11995, 44014, 1855, 10570, 311, 79212, 481, 41585, 369, 43468, 279, 42199, 11277, 323, 82475, 29393, 82102, 811, 1603, 1694, 15910, 311, 29280, 519, 2427, 278, 3415, 2427, 278, 3415, 8737, 21787, 13, 2052, 36201, 41585, 527, 3469, 2740, 32951, 291, 311, 1855, 1023, 13, 9062, 38970, 1243, 16609, 1555, 264, 8737, 18848, 1603, 1694, 11093, 449, 264, 24310, 312, 76128, 32951, 13, 362, 14019, 18848, 323, 459, 59141, 12, 36013, 535, 29953, 299, 292, 18327, 32951, 279, 1403, 12842, 2635, 291, 51045, 8800, 279, 1203, 58101, 315, 279, 16945, 13, 61626, 4692, 36634, 320, 13553, 8, 374, 15910, 311, 264, 4604, 316, 7213, 8034, 14019, 320, 47, 8673, 8, 4669, 459, 14956, 315, 4526, 36057, 320, 3218, 16, 11, 7121, 17, 11, 7121, 18, 570, 272, 1556, 1536, 37526, 1684, 315, 264, 220, 18, 9607, 1646, 315, 279, 1887, 323, 1202, 43972, 13, 294, 362, 1948, 1684, 449, 279, 27204, 315, 279, 1403, 8737, 21787, 27463, 13, 384, 27124, 315, 279, 1646, 800, 11310, 75, 11595, 4028, 279, 8737, 3158, 15151, 3722, 16597, 7347, 5178, 320, 626, 11310, 75, 11595, 871, 220, 15, 13, 23, 8, 4028, 4056, 914, 9653, 220, 17, 1174, 12207, 8294, 1109, 279, 3158, 315, 279, 67822, 220, 20, 49675, 23899, 12960, 31857, 777, 13, 21, 9653, 220, 17, 883, 555, 4056, 1591, 14697, 282, 59812, 10847, 263, 3521, 7709, 11659, 37, 22323, 1051, 1903, 449, 1207, 56856, 55308, 320, 15, 13, 17, 64012, 76, 8, 304, 70479, 1234, 264, 14861, 34215, 520, 2380, 43957, 323, 3116, 10687, 11, 369, 2225, 315, 279, 66369, 88202, 11, 19502, 750, 12842, 2635, 291, 24310, 44014, 13, 435, 20484, 44, 315, 279, 49668, 18809, 369, 22323, 505, 279, 97332, 55308, 9038, 34575, 323, 3944, 34575, 527, 16997, 323, 68683, 13, 36944, 55308, 320, 308, 284, 220, 23, 8, 520, 1855, 10687, 527, 17303, 11, 3734, 430, 1070, 527, 220, 22, 55308, 320, 308, 284, 220, 22, 8, 17303, 389, 8183, 520, 279, 8149, 315, 220, 2636, 64012, 76, 13, 2956, 527, 10666, 439, 3152, 2819, 20903, 328, 920, 13, 342, 58419, 5448, 315, 264, 86085, 11, 34030, 74864, 6205, 449, 264, 39445, 1584, 5497, 320, 20, 5238, 824, 2606, 26402, 8, 304, 1403, 89935, 19426, 1234, 279, 2539, 8737, 2134, 315, 279, 1887, 13, 9062, 2217, 5039, 220, 914, 5238, 389, 279, 1948, 6964, 320, 2414, 2217, 8, 323, 389, 279, 2163, 6964, 320, 1315, 2217, 705, 29918, 3210, 11, 69963, 264, 220, 20, 25800, 220, 20, 9653, 22512, 53, 13, 305, 578, 1630, 57, 2217, 3235, 279, 19087, 67822, 1584, 323, 279, 816, 57, 2217, 3235, 6307, 67822, 1584, 304, 320, 342, 883, 527, 1101, 68683, 13, 578, 32758, 5497, 374, 1400, 90021, 449, 279, 7833, 5238, 11, 23377, 264, 10269, 2115, 2225, 304, 865, 323, 379, 18445, 4028, 279, 22512, 53, 13, 8797, 1404, 2217, 763, 420, 990, 11, 584, 2274, 264, 1887, 449, 264, 3544, 22512, 53, 11, 1207, 5997, 1299, 11175, 11, 323, 19091, 9678, 8737, 21787, 369, 7701, 19303, 11, 97929, 7447, 16983, 25936, 315, 4332, 30828, 16622, 894, 13, 5810, 11, 584, 3118, 264, 2587, 1403, 63837, 26934, 1887, 449, 19091, 8737, 21787, 430, 649, 14816, 6724, 29235, 13, 9062, 6916, 706, 29393, 2680, 311, 279, 1890, 3544, 32758, 8286, 31857, 914, 9653, 220, 17, 22512, 53, 8, 927, 902, 1207, 5997, 1299, 11175, 374, 18908, 304, 72916, 20438, 311, 14595, 220, 17, 63837, 26934, 32758, 43957, 13, 4314, 1403, 11977, 1005, 48232, 70985, 320, 19268, 8, 369, 12330, 7096, 46620, 11, 37015, 12842, 2635, 287, 369, 58632, 32758, 11, 323, 83245, 70985, 369, 24310, 312, 76128, 13, 24586, 311, 279, 24589, 315, 279, 11977, 11, 323, 279, 1005, 315, 83245, 70985, 369, 24310, 35271, 11, 279, 1988, 72475, 649, 2586, 505, 279, 1890, 2592, 477, 2204, 8336, 320, 27364, 2695, 35961, 570, 23674, 11, 1855, 6916, 649, 1005, 5361, 128257, 198, 128256, 78191, 198, 24350, 9151, 1057, 8830, 315, 279, 3823, 8271, 690, 1397, 502, 26793, 1139, 1268, 30828, 16622, 894, 4375, 304, 56669, 11, 2737, 27692, 24548, 13, 4314, 26969, 1397, 16967, 8271, 5820, 449, 264, 73757, 430, 5825, 11175, 1579, 3403, 311, 1518, 3927, 34313, 323, 872, 19228, 13, 9220, 63837, 26934, 97332, 92914, 706, 12207, 24872, 12074, 6, 5845, 311, 656, 1120, 430, 11, 323, 279, 10278, 315, 36221, 5034, 53, 486, 9259, 11, 459, 22712, 14561, 304, 279, 6011, 315, 45034, 323, 17863, 17005, 520, 31613, 16376, 32207, 11, 374, 264, 4106, 2788, 315, 3495, 369, 44169, 279, 5557, 13, 1666, 12717, 49581, 389, 279, 4330, 4771, 11, 400, 24, 3610, 80628, 50701, 9479, 24367, 59812, 10847, 263, 32359, 318, 4210, 73547, 320, 45, 39901, 8, 19240, 11, 902, 574, 9405, 315, 4900, 7250, 596, 74863, 691, 38756, 323, 374, 81296, 520, 80346, 33, 11, 9259, 374, 3318, 311, 330, 9254, 279, 4156, 4918, 315, 7447, 63837, 26934, 92914, 369, 93048, 3495, 1210, 763, 279, 4723, 13, 220, 1114, 4360, 315, 22037, 26545, 11, 9259, 323, 813, 1080, 34603, 1105, 1934, 279, 4500, 315, 264, 502, 73757, 814, 7664, 439, 330, 86174, 22765, 62549, 32208, 95418, 369, 20902, 8771, 8838, 23318, 9220, 12, 94150, 32758, 320, 48889, 301, 17, 79, 41418, 11205, 1403, 63837, 26934, 73757, 5825, 31069, 8271, 38025, 4210, 5845, 13, 578, 3756, 706, 279, 7928, 2115, 315, 1684, 320, 455, 311, 220, 914, 9518, 2606, 55336, 8, 315, 904, 1778, 14473, 11, 10923, 433, 311, 3493, 1207, 5997, 1299, 11175, 315, 5361, 5789, 315, 279, 8271, 13, 330, 1687, 2351, 74142, 369, 2380, 2574, 25, 11175, 311, 1518, 3927, 34313, 11, 264, 2115, 315, 1684, 311, 12602, 5361, 8271, 13918, 25291, 11, 323, 32758, 4732, 311, 12602, 4442, 304, 49384, 5820, 2391, 7865, 1359, 9259, 11497, 13, 330, 791, 4455, 430, 584, 2351, 8173, 304, 32758, 1566, 2753, 1109, 264, 2132, 11, 779, 584, 1541, 956, 617, 892, 311, 3351, 279, 73757, 26, 584, 617, 311, 636, 4395, 304, 832, 6689, 11, 1418, 2103, 3339, 2771, 430, 279, 70985, 649, 5357, 24955, 9533, 66557, 315, 21120, 3177, 1210, 578, 8147, 72475, 430, 6678, 1403, 63837, 26934, 32758, 6067, 11, 1855, 54824, 922, 400, 5154, 11, 931, 11, 6493, 24955, 9533, 11, 24955, 20653, 1137, 66557, 315, 3177, 11, 1855, 315, 902, 374, 810, 1109, 264, 7239, 3115, 53657, 1109, 40120, 11, 323, 40758, 220, 15, 13, 931, 16, 20622, 974, 1321, 13, 362, 3254, 24310, 11, 449, 220, 1490, 3610, 66557, 824, 2132, 11, 374, 6859, 1139, 1403, 42241, 9678, 8737, 4817, 11977, 11, 28462, 279, 73757, 311, 8737, 1403, 13918, 25291, 11, 449, 1855, 20336, 311, 2204, 32758, 5137, 13, 763, 3766, 26771, 315, 279, 14473, 11, 279, 1403, 72475, 1051, 379, 11059, 323, 20336, 311, 279, 1890, 5137, 11, 459, 27204, 430, 16917, 19477, 1771, 25936, 13, 16963, 2931, 8737, 5137, 11, 1778, 439, 4124, 4478, 323, 8737, 5654, 1404, 11, 13592, 4028, 4332, 30828, 16622, 894, 323, 22772, 8670, 11, 323, 279, 502, 14473, 6276, 369, 2204, 8737, 5137, 311, 387, 1511, 369, 2225, 51045, 13, 578, 502, 3756, 11, 902, 52924, 3892, 2587, 69956, 323, 2587, 21110, 4830, 3149, 5540, 11, 2737, 279, 29393, 1375, 954, 11, 279, 8737, 18848, 11, 279, 14019, 18848, 323, 279, 16945, 18848, 11, 374, 2736, 1694, 44029, 18306, 369, 1202, 5845, 311, 3493, 1579, 30699, 32758, 315, 30828, 5820, 304, 13882, 38067, 8271, 13918, 13, 9259, 374, 11411, 311, 23391, 1825, 2680, 311, 279, 14473, 13, 5843, 1603, 420, 502, 5684, 574, 4756, 11, 568, 323, 813, 1080, 34603, 1105, 6004, 264, 864, 1374, 430, 5343, 279, 15009, 3649, 4460, 311, 46113, 433, 13, 2435, 1101, 6222, 279, 5557, 449, 18105, 520, 10406, 3907, 11, 1405, 12074, 304, 29808, 25507, 596, 10278, 617, 2736, 1903, 29882, 311, 7937, 872, 1866, 21896, 13, 330, 2028, 374, 13548, 1359, 9259, 1071, 13, 330, 7009, 3287, 956, 617, 311, 1212, 505, 19307, 1093, 584, 1550, 13, 2435, 1436, 1977, 1022, 315, 1057, 990, 13, 29808, 596, 5684, 574, 4756, 1203, 4791, 15825, 449, 11604, 11, 323, 1403, 5220, 11, 2006, 1242, 323, 3623, 33892, 11, 617, 6216, 6067, 3196, 389, 1057, 14769, 13, 8876, 1070, 374, 912, 25589, 11, 323, 2834, 956, 387, 11, 420, 5557, 374, 1949, 369, 682, 311, 1005, 323, 5719, 4869, 814, 1518, 5052, 1210, 9220, 63837, 26934, 92914, 374, 264, 28175, 955, 315, 74864, 92914, 13, 2057, 2804, 1778, 990, 304, 9259, 596, 10278, 11, 12074, 52033, 24490, 24548, 779, 430, 872, 34313, 6782, 264, 74864, 21070, 315, 49384, 5820, 13, 578, 21070, 574, 1903, 555, 35271, 264, 74864, 13128, 505, 52441, 18668, 323, 264, 35719, 65500, 13128, 430, 6866, 304, 7138, 13, 578, 5603, 28605, 1154, 279, 10015, 11, 10373, 8838, 1474, 35815, 5376, 304, 35719, 430, 264, 49384, 11704, 994, 23677, 13, 3277, 279, 21120, 374, 14618, 520, 279, 49384, 11, 323, 279, 49384, 374, 23677, 11, 35719, 4131, 304, 11, 279, 13128, 14035, 279, 35719, 323, 11, 13967, 11, 51881, 1634, 13, 9220, 63837, 26934, 32758, 57924, 97332, 92914, 555, 51297, 279, 31228, 7865, 315, 89235, 304, 264, 1648, 430, 29034, 264, 24779, 3392, 315, 704, 8838, 80564, 97332, 3177, 505, 1694, 8066, 13, 763, 4725, 29393, 92914, 11, 279, 3177, 505, 279, 2592, 1511, 311, 3521, 635, 279, 6205, 29933, 433, 304, 264, 1648, 430, 19159, 264, 12414, 22949, 315, 3177, 430, 44669, 1849, 1523, 311, 279, 2218, 5357, 3158, 11, 323, 1243, 459, 47801, 22949, 3770, 430, 1486, 13, 5884, 3177, 430, 374, 539, 520, 279, 15376, 478, 1486, 374, 704, 315, 5357, 13, 578, 3177, 304, 264, 1403, 63837, 26934, 73757, 74157, 22009, 11, 6968, 264, 3254, 1486, 315, 3177, 320, 438, 912, 87992, 315, 3177, 8, 430, 374, 304, 17676, 5357, 11, 40599, 682, 704, 8838, 80564, 3177, 505, 19261, 279, 32758, 18848, 13, 330, 791, 2217, 21667, 1193, 3177, 505, 430, 11277, 584, 2351, 3411, 520, 11, 2085, 1790, 4092, 8450, 505, 3485, 477, 3770, 279, 11277, 1359, 9259, 11497, 13, 330, 791, 8271, 706, 29393, 6012, 323, 264, 10651, 1093, 14432, 26, 433, 596, 2539, 315, 19588, 3447, 323, 66300, 788, 10105, 430, 1304, 433, 2653, 311, 1518, 1555, 13, 3161, 4725, 29393, 32758, 11, 499, 649, 1518, 1193, 279, 1633, 1948, 315, 279, 8271, 13, 9220, 63837, 26934, 32758, 6276, 603, 311, 2217, 19662, 1523, 323, 2103, 36861, 1207, 33001, 1299, 11175, 1210, 13596, 9610, 315, 1403, 63837, 26934, 3521, 7709, 3177, 374, 430, 433, 5829, 4827, 65487, 11, 5129, 2695, 35961, 3177, 320, 258, 279, 3221, 3502, 82482, 2134, 570, 15483, 3177, 1156, 10385, 2753, 994, 12579, 1555, 20438, 11, 779, 433, 649, 387, 46473, 10968, 19662, 1139, 20438, 13, 23674, 11, 279, 4827, 65487, 3177, 374, 2753, 34446, 311, 279, 6205, 1109, 24210, 93959, 11, 1778, 439, 37232, 85311, 3177, 13, 9259, 596, 10278, 12793, 279, 3756, 304, 21896, 389, 24548, 11, 46071, 872, 35202, 1418, 814, 10887, 9256, 1778, 439, 10307, 6946, 477, 60499, 4200, 8903, 22484, 13, 9062, 8814, 706, 4036, 264, 9168, 46460, 304, 1202, 35113, 11, 8405, 264, 24016, 3321, 369, 279, 73757, 1139, 1202, 8271, 13, 330, 40, 2846, 27762, 555, 4560, 311, 3619, 279, 55580, 16565, 304, 30828, 16622, 894, 430, 1095, 603, 656, 7185, 2574, 430, 584, 649, 956, 5131, 46113, 304, 12933, 1359, 568, 1071, 13, 330, 1687, 649, 1977, 264, 5780, 311, 656, 264, 2763, 315, 2574, 2731, 1109, 584, 649, 13, 2030, 369, 1023, 2574, 11, 584, 649, 956, 13, 1226, 5542, 37719, 311, 6678, 9515, 11, 719, 659, 60811, 9515, 3775, 304, 264, 7029, 1358, 315, 15082, 1405, 12966, 656, 539, 13, 578, 6067, 584, 1005, 369, 5655, 6975, 527, 3196, 389, 26793, 505, 279, 8271, 11, 719, 814, 527, 1193, 264, 2478, 26793, 11, 323, 539, 279, 4459, 3446, 13, 2435, 990, 5128, 1664, 11, 719, 527, 2103, 45350, 13, 3296, 12593, 11, 358, 649, 2231, 264, 8814, 304, 264, 3130, 1405, 433, 706, 2646, 1027, 11, 323, 433, 690, 1629, 311, 1063, 2050, 1405, 358, 649, 956, 5662, 433, 13, 1102, 2834, 956, 1629, 1139, 904, 14620, 13, 1102, 1587, 420, 2307, 57482, 323, 8640, 389, 922, 264, 67272, 315, 2410, 13, 330, 3947, 527, 7185, 55580, 16565, 430, 584, 4250, 3686, 46113, 304, 3823, 27975, 12933, 430, 3073, 304, 279, 35202, 315, 24548, 1359, 9259, 8738, 11, 330, 438, 358, 1390, 311, 1212, 311, 45063, 430, 13, 1102, 596, 3249, 358, 4934, 311, 1977, 420, 73757, 1210, 220, 128257, 198 ]

2,816

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The electrochemical conversion of carbon dioxide and water into useful products is a major challenge in facilitating a closed carbon cycle. Here we report a cobalt protoporphyrin immobilized on a pyrolytic graphite electrode that reduces carbon dioxide in an aqueous acidic solution at relatively low overpotential (0.5 V), with an efficiency and selectivity comparable to the best porphyrin-based electrocatalyst in the literature. While carbon monoxide is the main reduction product, we also observe methane as by-product. The results of our detailed pH-dependent studies are explained consistently by a mechanism in which carbon dioxide is activated by the cobalt protoporphyrin through the stabilization of a radical intermediate, which acts as Brønsted base. The basic character of this intermediate explains how the carbon dioxide reduction circumvents a concerted proton–electron transfer mechanism, in contrast to hydrogen evolution. Our results and their mechanistic interpretations suggest strategies for designing improved catalysts. Introduction The efficient electrochemical reduction of carbon dioxide to a fuel with a high-energy density would be a major step forward in the introduction of a CO 2 neutral energy cycle, as it would allow for the direct low-temperature conversion of photo-generated electrical current to stored chemical energy, in a manner very similar to the way nature stores solar energy. Plants fix CO 2 from the atmosphere by photosynthesis in an enzymatic complex called Rubisco, which selectively binds CO 2 and inserts it into existing carbon chains by reductive carboxylation. The high-energy electrons necessary for this process are photo-generated by photosystem II. Synthetic catalysts for the electrocatalytic reduction of CO 2 , which could facilitate such an artificial CO 2 neutral redox cycle, have been studied for many decades 1 , 2 , 3 , 4 . A main challenge in electrochemical CO 2 reduction is to develop catalysts that are capable of reducing CO 2 beyond the two-electron products carbon monoxide (CO), formic acid (HCOOH), and oxalate (C 2 O 4 2− ). Unfortunately, the formation of reduction products requiring four or more electrons is invariably associated with considerable overpotentials due to the multiple intermediates involved in the reaction mechanisms 5 (although more reduced products often have higher stability and correspondingly more positive equilibrium potentials). Metallic copper is unique in producing significant amounts of high-energy multi-electron transfer products such as methane, ethylene and ethanol 3 , 6 , 7 . Molecular catalysts that are capable of reducing CO 2 to a product different from one of the above-mentioned two-electron products are much less common and typically involve a strong interaction with the working electrode 8 . A second important challenge in CO 2 electrocatalysis concerns the suppression of the concomitant evolution of hydrogen, which is a dominant side reaction for CO 2 reduction from aqueous electrolytes. Strategies for suppressing hydrogen evolution typically involve working with high(er) CO 2 to proton ratios, such as high CO 2 pressures or solvents with a higher CO 2 solubility. Recent fundamental and theoretical work has reconsidered porphyrin-based molecular catalysts for electrochemical CO 2 reduction. Tripkovic et al . 9 have performed extensive density functional theory calculations of metal-functionalized porphyrin-like graphene surfaces, and predicted the potential formation of methane and methanol from CO 2 . Costentin et al . 10 considered ligand modifications of iron-based porphyrins and found that local proton sources built into the porphyrin ring give rise to high activity and good Faradaic efficiency (FE) for the reduction of CO 2 to CO in a mixed DMF–water solvent. In fact, it has been known since the early 1980s that cobalt (Co)-based macrocyclic complexes, either in solution or adsorbed onto carbon electrodes, act as effective electrocatalysts for CO 2 reduction, producing CO, HCOOH, methanol and methane, although at relatively high overpotential and with varying selectivity 11 , 12 , 13 , 14 , 15 . Herein, we report on the electrochemical reduction of CO 2 to CO and methane, as well as smaller amounts of HCOOH and methanol, on a simple Co protoporphyrin molecular catalyst immobilized onto a pyrolytic graphite (PG) electrode in a purely aqueous electrolyte solution. Previous similar work using immobilized Co porphyrins or Co phthalocyanines has shown the capability of Co-based catalysts to achieve a high FE towards CO, which is highly sensitive to pH and potential 16 , 17 , 18 . Our work confirms that immobilized Co-based porphyrins are good CO 2 reduction electrocatalysts capable of producing multi-electron products such as methane and methanol. More significantly, our work underscores the important role of pH in steering the catalytic activity and selectivity towards CO and CH 4 , especially in the very narrow pH=1–3 range in the absence of coordinating anions. This high sensitivity to pH is explained by a mechanism highlighting the important role of the initial electron transfer in activating CO 2 electrochemically. We also demonstrate how such a mechanism for CO 2 reduction manifests experimentally and how this property can be exploited to suppress concomitant hydrogen evolution. Furthermore, we show that the overpotential and corresponding turnover frequency (TOF) for CO 2 reduction of our catalyst compare favourably to the best molecular porphyrin-based catalyst in the literature 10 . Therefore, we believe that these insights may have significant implications for the design of new and improved molecular catalyst electrodes and for the formulation of optimized process conditions for efficient electrochemical CO 2 reduction to CO as well as to products reduced to a more significant degree. Results Voltammetry and online electrochemical mass spectrometry The Co protoporphyrin-coated PG (CoPP-PG) electrode was prepared following a procedure described earlier 19 and was detailed in the Methods section. In situ electrochemical scanning tunnelling microscopy and atomic force microscopy images of iron and zinc protoporphyrins on basal plane graphite electrodes by Tao et al . 20 suggest that these molecules form monolayer films on the electrode with the molecules lying flat. The blank cyclic voltammograms of the PG electrode, the CoPP-PG electrode in 0.1 M HClO 4 and the voltammetry of the dissolved CoPP in the same electrolyte are compared in Supplementary Fig. 1 .", "role": "user" }, { "content": "A discovery made in Leiden helps not only to make natural gas from CO2 but also to store renewable energy. Research by Professor Marc Koper and PhD student Jing Shen shows how this process can be implemented in a cost-effective and controllable way. The conversion of the greenhouse gas CO2 into natural gas is achieved using a chemical process in which CO2 is bubbled through an acid solution. The solution contains a graphite electrode – to which a small negative voltage is applied – with a cobalt-porphyrin catalyst attached to it. It was already known that this catalyst can convert CO2 into carbon monoxide and methane, but the reaction always released unwanted hydrogen. In their investigation, Koper and Shen show for the first time how the process works. They therefore know exactly what the best acidity degree is in order to minimise the amount of hydrogen and to convert as much CO2 as possible into natural gas. Common materials An added benefit is that the catalyst is entirely made up of common materials. Cobalt porphyrin is a part of vitamin B12, while the graphite for the electrode is similar to a pencil lead. Therefore the catalyst only costs a few euros. Comparable methods of converting CO2 into methane often use rare and expensive metals, such as platinum. Realising a dream Koper hopes that this discovery will bring his dream a little closer to realisation: to convert CO2 and water, the by-products of fuels, into new energy or building blocks for the chemical industry. If this can be achieved using solar energy, this process will also offer a method of storing renewable energy. Using renewable energy efficiently 'We're generating more and more electricity using solar panels and windmills, but that energy is by no means always used straight away,' Koper explains. 'In Germany, for example, too much renewable electricity is generated sometimes, so you want to store it. That is the most important potential application of our research: to use renewable energy efficiently by converting water and CO2 into valuable products.' A fundamentally different way Still, Koper thinks that it will take a while to get to that point. 'This is something for the long term and it could be another fifty years before we have a method that makes valuable products and is also robust, scalable and cost-effective. But I'm nevertheless convinced that this is the way to go. It will not be easy, but this discovery is helpful. We have to find a fundamentally different way to manage energy, and our discovery can contribute to that.' ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The electrochemical conversion of carbon dioxide and water into useful products is a major challenge in facilitating a closed carbon cycle. Here we report a cobalt protoporphyrin immobilized on a pyrolytic graphite electrode that reduces carbon dioxide in an aqueous acidic solution at relatively low overpotential (0.5 V), with an efficiency and selectivity comparable to the best porphyrin-based electrocatalyst in the literature. While carbon monoxide is the main reduction product, we also observe methane as by-product. The results of our detailed pH-dependent studies are explained consistently by a mechanism in which carbon dioxide is activated by the cobalt protoporphyrin through the stabilization of a radical intermediate, which acts as Brønsted base. The basic character of this intermediate explains how the carbon dioxide reduction circumvents a concerted proton–electron transfer mechanism, in contrast to hydrogen evolution. Our results and their mechanistic interpretations suggest strategies for designing improved catalysts. Introduction The efficient electrochemical reduction of carbon dioxide to a fuel with a high-energy density would be a major step forward in the introduction of a CO 2 neutral energy cycle, as it would allow for the direct low-temperature conversion of photo-generated electrical current to stored chemical energy, in a manner very similar to the way nature stores solar energy. Plants fix CO 2 from the atmosphere by photosynthesis in an enzymatic complex called Rubisco, which selectively binds CO 2 and inserts it into existing carbon chains by reductive carboxylation. The high-energy electrons necessary for this process are photo-generated by photosystem II. Synthetic catalysts for the electrocatalytic reduction of CO 2 , which could facilitate such an artificial CO 2 neutral redox cycle, have been studied for many decades 1 , 2 , 3 , 4 . A main challenge in electrochemical CO 2 reduction is to develop catalysts that are capable of reducing CO 2 beyond the two-electron products carbon monoxide (CO), formic acid (HCOOH), and oxalate (C 2 O 4 2− ). Unfortunately, the formation of reduction products requiring four or more electrons is invariably associated with considerable overpotentials due to the multiple intermediates involved in the reaction mechanisms 5 (although more reduced products often have higher stability and correspondingly more positive equilibrium potentials). Metallic copper is unique in producing significant amounts of high-energy multi-electron transfer products such as methane, ethylene and ethanol 3 , 6 , 7 . Molecular catalysts that are capable of reducing CO 2 to a product different from one of the above-mentioned two-electron products are much less common and typically involve a strong interaction with the working electrode 8 . A second important challenge in CO 2 electrocatalysis concerns the suppression of the concomitant evolution of hydrogen, which is a dominant side reaction for CO 2 reduction from aqueous electrolytes. Strategies for suppressing hydrogen evolution typically involve working with high(er) CO 2 to proton ratios, such as high CO 2 pressures or solvents with a higher CO 2 solubility. Recent fundamental and theoretical work has reconsidered porphyrin-based molecular catalysts for electrochemical CO 2 reduction. Tripkovic et al . 9 have performed extensive density functional theory calculations of metal-functionalized porphyrin-like graphene surfaces, and predicted the potential formation of methane and methanol from CO 2 . Costentin et al . 10 considered ligand modifications of iron-based porphyrins and found that local proton sources built into the porphyrin ring give rise to high activity and good Faradaic efficiency (FE) for the reduction of CO 2 to CO in a mixed DMF–water solvent. In fact, it has been known since the early 1980s that cobalt (Co)-based macrocyclic complexes, either in solution or adsorbed onto carbon electrodes, act as effective electrocatalysts for CO 2 reduction, producing CO, HCOOH, methanol and methane, although at relatively high overpotential and with varying selectivity 11 , 12 , 13 , 14 , 15 . Herein, we report on the electrochemical reduction of CO 2 to CO and methane, as well as smaller amounts of HCOOH and methanol, on a simple Co protoporphyrin molecular catalyst immobilized onto a pyrolytic graphite (PG) electrode in a purely aqueous electrolyte solution. Previous similar work using immobilized Co porphyrins or Co phthalocyanines has shown the capability of Co-based catalysts to achieve a high FE towards CO, which is highly sensitive to pH and potential 16 , 17 , 18 . Our work confirms that immobilized Co-based porphyrins are good CO 2 reduction electrocatalysts capable of producing multi-electron products such as methane and methanol. More significantly, our work underscores the important role of pH in steering the catalytic activity and selectivity towards CO and CH 4 , especially in the very narrow pH=1–3 range in the absence of coordinating anions. This high sensitivity to pH is explained by a mechanism highlighting the important role of the initial electron transfer in activating CO 2 electrochemically. We also demonstrate how such a mechanism for CO 2 reduction manifests experimentally and how this property can be exploited to suppress concomitant hydrogen evolution. Furthermore, we show that the overpotential and corresponding turnover frequency (TOF) for CO 2 reduction of our catalyst compare favourably to the best molecular porphyrin-based catalyst in the literature 10 . Therefore, we believe that these insights may have significant implications for the design of new and improved molecular catalyst electrodes and for the formulation of optimized process conditions for efficient electrochemical CO 2 reduction to CO as well as to products reduced to a more significant degree. Results Voltammetry and online electrochemical mass spectrometry The Co protoporphyrin-coated PG (CoPP-PG) electrode was prepared following a procedure described earlier 19 and was detailed in the Methods section. In situ electrochemical scanning tunnelling microscopy and atomic force microscopy images of iron and zinc protoporphyrins on basal plane graphite electrodes by Tao et al . 20 suggest that these molecules form monolayer films on the electrode with the molecules lying flat. The blank cyclic voltammograms of the PG electrode, the CoPP-PG electrode in 0.1 M HClO 4 and the voltammetry of the dissolved CoPP in the same electrolyte are compared in Supplementary Fig. 1 .<|im_end|> <|im_start|>assistant A discovery made in Leiden helps not only to make natural gas from CO2 but also to store renewable energy. Research by Professor Marc Koper and PhD student Jing Shen shows how this process can be implemented in a cost-effective and controllable way. The conversion of the greenhouse gas CO2 into natural gas is achieved using a chemical process in which CO2 is bubbled through an acid solution. The solution contains a graphite electrode – to which a small negative voltage is applied – with a cobalt-porphyrin catalyst attached to it. It was already known that this catalyst can convert CO2 into carbon monoxide and methane, but the reaction always released unwanted hydrogen. In their investigation, Koper and Shen show for the first time how the process works. They therefore know exactly what the best acidity degree is in order to minimise the amount of hydrogen and to convert as much CO2 as possible into natural gas. Common materials An added benefit is that the catalyst is entirely made up of common materials. Cobalt porphyrin is a part of vitamin B12, while the graphite for the electrode is similar to a pencil lead. Therefore the catalyst only costs a few euros. Comparable methods of converting CO2 into methane often use rare and expensive metals, such as platinum. Realising a dream Koper hopes that this discovery will bring his dream a little closer to realisation: to convert CO2 and water, the by-products of fuels, into new energy or building blocks for the chemical industry. If this can be achieved using solar energy, this process will also offer a method of storing renewable energy. Using renewable energy efficiently 'We're generating more and more electricity using solar panels and windmills, but that energy is by no means always used straight away,' Koper explains. 'In Germany, for example, too much renewable electricity is generated sometimes, so you want to store it. That is the most important potential application of our research: to use renewable energy efficiently by converting water and CO2 into valuable products.' A fundamentally different way Still, Koper thinks that it will take a while to get to that point. 'This is something for the long term and it could be another fifty years before we have a method that makes valuable products and is also robust, scalable and cost-effective. But I'm nevertheless convinced that this is the way to go. It will not be easy, but this discovery is helpful. We have to find a fundamentally different way to manage energy, and our discovery can contribute to that.' <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 25396, 32056, 14747, 315, 12782, 40589, 323, 3090, 1139, 5505, 3956, 374, 264, 3682, 8815, 304, 68365, 264, 8036, 12782, 11008, 13, 5810, 584, 1934, 264, 34928, 3223, 1760, 454, 16751, 11160, 258, 77441, 1534, 389, 264, 4611, 299, 398, 29150, 95273, 72048, 430, 26338, 12782, 40589, 304, 459, 66300, 788, 84903, 6425, 520, 12309, 3428, 927, 93036, 320, 15, 13, 20, 650, 705, 449, 459, 15374, 323, 3373, 1968, 30139, 311, 279, 1888, 4247, 764, 11160, 258, 6108, 25396, 66, 4306, 599, 304, 279, 17649, 13, 6104, 12782, 1647, 55189, 374, 279, 1925, 14278, 2027, 11, 584, 1101, 23846, 61083, 439, 555, 29745, 13, 578, 3135, 315, 1057, 11944, 37143, 43918, 7978, 527, 11497, 21356, 555, 264, 17383, 304, 902, 12782, 40589, 374, 22756, 555, 279, 34928, 3223, 1760, 454, 16751, 11160, 258, 1555, 279, 83938, 315, 264, 18336, 29539, 11, 902, 14385, 439, 3320, 6282, 77, 24836, 2385, 13, 578, 6913, 3752, 315, 420, 29539, 15100, 1268, 279, 12782, 40589, 14278, 10408, 48764, 264, 97666, 82586, 4235, 75603, 8481, 17383, 11, 304, 13168, 311, 35784, 15740, 13, 5751, 3135, 323, 872, 7852, 4633, 58689, 4284, 15174, 369, 30829, 13241, 51483, 82, 13, 29438, 578, 11297, 25396, 32056, 14278, 315, 12782, 40589, 311, 264, 10633, 449, 264, 1579, 65487, 17915, 1053, 387, 264, 3682, 3094, 4741, 304, 279, 17219, 315, 264, 7432, 220, 17, 21277, 4907, 11008, 11, 439, 433, 1053, 2187, 369, 279, 2167, 3428, 12, 35658, 14747, 315, 6685, 16581, 20314, 1510, 311, 9967, 11742, 4907, 11, 304, 264, 11827, 1633, 4528, 311, 279, 1648, 7138, 10756, 13238, 4907, 13, 50298, 5155, 7432, 220, 17, 505, 279, 16975, 555, 7397, 74767, 304, 459, 32011, 780, 6485, 2663, 13134, 9652, 11, 902, 82775, 58585, 7432, 220, 17, 323, 50398, 433, 1139, 6484, 12782, 27271, 555, 312, 68243, 1841, 2054, 79933, 13, 578, 1579, 65487, 57678, 5995, 369, 420, 1920, 527, 6685, 16581, 555, 7397, 615, 8105, 13, 75928, 51483, 82, 369, 279, 25396, 66, 4306, 70504, 14278, 315, 7432, 220, 17, 1174, 902, 1436, 28696, 1778, 459, 21075, 7432, 220, 17, 21277, 2579, 5241, 11008, 11, 617, 1027, 20041, 369, 1690, 11026, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 662, 362, 1925, 8815, 304, 25396, 32056, 7432, 220, 17, 14278, 374, 311, 2274, 51483, 82, 430, 527, 13171, 315, 18189, 7432, 220, 17, 7953, 279, 1403, 37081, 2298, 3956, 12782, 1647, 55189, 320, 8445, 705, 1376, 292, 13935, 320, 39, 8445, 47861, 705, 323, 19488, 278, 349, 320, 34, 220, 17, 507, 220, 19, 220, 17, 34363, 7609, 19173, 11, 279, 18488, 315, 14278, 3956, 23537, 3116, 477, 810, 57678, 374, 74614, 5938, 449, 24779, 927, 19644, 8643, 4245, 311, 279, 5361, 55275, 988, 6532, 304, 279, 13010, 24717, 220, 20, 320, 37241, 810, 11293, 3956, 3629, 617, 5190, 20334, 323, 8024, 11559, 810, 6928, 56411, 95358, 570, 87971, 24166, 374, 5016, 304, 17843, 5199, 15055, 315, 1579, 65487, 7447, 37081, 2298, 8481, 3956, 1778, 439, 61083, 11, 8537, 64651, 323, 62772, 220, 18, 1174, 220, 21, 1174, 220, 22, 662, 60825, 51483, 82, 430, 527, 13171, 315, 18189, 7432, 220, 17, 311, 264, 2027, 2204, 505, 832, 315, 279, 3485, 12, 37691, 1403, 37081, 2298, 3956, 527, 1790, 2753, 4279, 323, 11383, 21736, 264, 3831, 16628, 449, 279, 3318, 72048, 220, 23, 662, 362, 2132, 3062, 8815, 304, 7432, 220, 17, 25396, 66, 4306, 4548, 10742, 279, 46735, 315, 279, 390, 884, 52044, 15740, 315, 35784, 11, 902, 374, 264, 25462, 3185, 13010, 369, 7432, 220, 17, 14278, 505, 66300, 788, 73396, 2392, 13, 56619, 369, 98795, 35784, 15740, 11383, 21736, 3318, 449, 1579, 94548, 8, 7432, 220, 17, 311, 82586, 42338, 11, 1778, 439, 1579, 7432, 220, 17, 40850, 477, 2092, 48764, 449, 264, 5190, 7432, 220, 17, 2092, 392, 1429, 13, 35390, 16188, 323, 32887, 990, 706, 40175, 291, 4247, 764, 11160, 258, 6108, 31206, 51483, 82, 369, 25396, 32056, 7432, 220, 17, 14278, 13, 27852, 74, 41145, 1880, 453, 662, 220, 24, 617, 10887, 16781, 17915, 16003, 10334, 29217, 315, 9501, 99616, 1534, 4247, 764, 11160, 258, 12970, 66192, 27529, 11, 323, 19698, 279, 4754, 18488, 315, 61083, 323, 21747, 39710, 505, 7432, 220, 17, 662, 11443, 44509, 1880, 453, 662, 220, 605, 6646, 29413, 438, 29882, 315, 11245, 6108, 4247, 764, 11160, 1354, 323, 1766, 430, 2254, 82586, 8336, 5918, 1139, 279, 4247, 764, 11160, 258, 10264, 3041, 10205, 311, 1579, 5820, 323, 1695, 13759, 2649, 292, 15374, 320, 11673, 8, 369, 279, 14278, 315, 7432, 220, 17, 311, 7432, 304, 264, 9709, 20804, 37, 4235, 13284, 69996, 13, 763, 2144, 11, 433, 706, 1027, 3967, 2533, 279, 4216, 220, 3753, 15, 82, 430, 34928, 3223, 320, 7489, 7435, 31039, 18563, 66, 66404, 69125, 11, 3060, 304, 6425, 477, 14058, 269, 2788, 8800, 12782, 80390, 11, 1180, 439, 7524, 25396, 66, 4306, 99335, 369, 7432, 220, 17, 14278, 11, 17843, 7432, 11, 473, 8445, 47861, 11, 21747, 39710, 323, 61083, 11, 8051, 520, 12309, 1579, 927, 93036, 323, 449, 29865, 3373, 1968, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 662, 5810, 258, 11, 584, 1934, 389, 279, 25396, 32056, 14278, 315, 7432, 220, 17, 311, 7432, 323, 61083, 11, 439, 1664, 439, 9333, 15055, 315, 473, 8445, 47861, 323, 21747, 39710, 11, 389, 264, 4382, 3623, 1760, 454, 16751, 11160, 258, 31206, 51483, 77441, 1534, 8800, 264, 4611, 299, 398, 29150, 95273, 320, 11637, 8, 72048, 304, 264, 32227, 66300, 788, 73396, 668, 6425, 13, 30013, 4528, 990, 1701, 77441, 1534, 3623, 4247, 764, 11160, 1354, 477, 3623, 1343, 31392, 511, 8503, 1572, 706, 6982, 279, 23099, 315, 3623, 6108, 51483, 82, 311, 11322, 264, 1579, 29031, 7119, 7432, 11, 902, 374, 7701, 16614, 311, 37143, 323, 4754, 220, 845, 1174, 220, 1114, 1174, 220, 972, 662, 5751, 990, 43496, 430, 77441, 1534, 3623, 6108, 4247, 764, 11160, 1354, 527, 1695, 7432, 220, 17, 14278, 25396, 66, 4306, 99335, 13171, 315, 17843, 7447, 37081, 2298, 3956, 1778, 439, 61083, 323, 21747, 39710, 13, 4497, 12207, 11, 1057, 990, 72890, 279, 3062, 3560, 315, 37143, 304, 33277, 279, 34454, 70504, 5820, 323, 3373, 1968, 7119, 7432, 323, 6969, 220, 19, 1174, 5423, 304, 279, 1633, 15376, 37143, 28, 16, 4235, 18, 2134, 304, 279, 19821, 315, 66515, 459, 919, 13, 1115, 1579, 27541, 311, 37143, 374, 11497, 555, 264, 17383, 39686, 279, 3062, 3560, 315, 279, 2926, 17130, 8481, 304, 72192, 7432, 220, 17, 25396, 2464, 2740, 13, 1226, 1101, 20461, 1268, 1778, 264, 17383, 369, 7432, 220, 17, 14278, 84332, 9526, 750, 323, 1268, 420, 3424, 649, 387, 51763, 311, 28321, 390, 884, 52044, 35784, 15740, 13, 24296, 11, 584, 1501, 430, 279, 927, 93036, 323, 12435, 48639, 11900, 320, 5319, 37, 8, 369, 7432, 220, 17, 14278, 315, 1057, 51483, 9616, 12617, 2915, 311, 279, 1888, 31206, 4247, 764, 11160, 258, 6108, 51483, 304, 279, 17649, 220, 605, 662, 15636, 11, 584, 4510, 430, 1521, 26793, 1253, 617, 5199, 25127, 369, 279, 2955, 315, 502, 323, 13241, 31206, 51483, 80390, 323, 369, 279, 55986, 315, 34440, 1920, 4787, 369, 11297, 25396, 32056, 7432, 220, 17, 14278, 311, 7432, 439, 1664, 439, 311, 3956, 11293, 311, 264, 810, 5199, 8547, 13, 18591, 66489, 309, 33342, 323, 2930, 25396, 32056, 3148, 9618, 442, 15501, 578, 3623, 1760, 454, 16751, 11160, 258, 23283, 660, 31144, 320, 7489, 4505, 9483, 38, 8, 72048, 574, 10235, 2768, 264, 10537, 7633, 6931, 220, 777, 323, 574, 11944, 304, 279, 19331, 3857, 13, 763, 10109, 25396, 32056, 36201, 11716, 77, 6427, 92914, 323, 25524, 5457, 92914, 5448, 315, 11245, 323, 49601, 1760, 454, 16751, 11160, 1354, 389, 80710, 11277, 95273, 80390, 555, 60608, 1880, 453, 662, 220, 508, 4284, 430, 1521, 35715, 1376, 1647, 337, 1155, 12631, 389, 279, 72048, 449, 279, 35715, 21078, 10269, 13, 578, 10321, 77102, 16798, 8836, 56485, 315, 279, 31144, 72048, 11, 279, 3623, 4505, 9483, 38, 72048, 304, 220, 15, 13, 16, 386, 473, 5176, 46, 220, 19, 323, 279, 16798, 309, 33342, 315, 279, 56767, 3623, 4505, 304, 279, 1890, 73396, 668, 527, 7863, 304, 99371, 23966, 13, 220, 16, 662, 128257, 198, 128256, 78191, 198, 32, 18841, 1903, 304, 2009, 12770, 8779, 539, 1193, 311, 1304, 5933, 6962, 505, 7432, 17, 719, 1101, 311, 3637, 33268, 4907, 13, 8483, 555, 17054, 19412, 735, 3376, 323, 30661, 5575, 86539, 58880, 5039, 1268, 420, 1920, 649, 387, 11798, 304, 264, 2853, 53421, 323, 687, 69855, 1648, 13, 578, 14747, 315, 279, 37647, 6962, 7432, 17, 1139, 5933, 6962, 374, 17427, 1701, 264, 11742, 1920, 304, 902, 7432, 17, 374, 90712, 839, 1555, 459, 13935, 6425, 13, 578, 6425, 5727, 264, 95273, 72048, 1389, 311, 902, 264, 2678, 8389, 22465, 374, 9435, 1389, 449, 264, 34928, 3223, 2320, 16751, 11160, 258, 51483, 12673, 311, 433, 13, 1102, 574, 2736, 3967, 430, 420, 51483, 649, 5625, 7432, 17, 1139, 12782, 1647, 55189, 323, 61083, 11, 719, 279, 13010, 2744, 6004, 36021, 35784, 13, 763, 872, 8990, 11, 735, 3376, 323, 58880, 1501, 369, 279, 1176, 892, 1268, 279, 1920, 4375, 13, 2435, 9093, 1440, 7041, 1148, 279, 1888, 98026, 8547, 374, 304, 2015, 311, 97087, 279, 3392, 315, 35784, 323, 311, 5625, 439, 1790, 7432, 17, 439, 3284, 1139, 5933, 6962, 13, 7874, 7384, 1556, 3779, 8935, 374, 430, 279, 51483, 374, 11622, 1903, 709, 315, 4279, 7384, 13, 47051, 3223, 4247, 764, 11160, 258, 374, 264, 961, 315, 28170, 426, 717, 11, 1418, 279, 95273, 369, 279, 72048, 374, 4528, 311, 264, 47218, 3063, 13, 15636, 279, 51483, 1193, 7194, 264, 2478, 33588, 13, 59206, 5528, 315, 34537, 7432, 17, 1139, 61083, 3629, 1005, 9024, 323, 11646, 37182, 11, 1778, 439, 63327, 13, 8976, 3876, 264, 8063, 735, 3376, 16388, 430, 420, 18841, 690, 4546, 813, 8063, 264, 2697, 12401, 311, 1972, 8082, 25, 311, 5625, 7432, 17, 323, 3090, 11, 279, 555, 68973, 315, 40373, 11, 1139, 502, 4907, 477, 4857, 10215, 369, 279, 11742, 5064, 13, 1442, 420, 649, 387, 17427, 1701, 13238, 4907, 11, 420, 1920, 690, 1101, 3085, 264, 1749, 315, 28672, 33268, 4907, 13, 12362, 33268, 4907, 30820, 364, 1687, 2351, 24038, 810, 323, 810, 18200, 1701, 13238, 21988, 323, 10160, 76, 3385, 11, 719, 430, 4907, 374, 555, 912, 3445, 2744, 1511, 7833, 3201, 2965, 735, 3376, 15100, 13, 364, 644, 10057, 11, 369, 3187, 11, 2288, 1790, 33268, 18200, 374, 8066, 7170, 11, 779, 499, 1390, 311, 3637, 433, 13, 3011, 374, 279, 1455, 3062, 4754, 3851, 315, 1057, 3495, 25, 311, 1005, 33268, 4907, 30820, 555, 34537, 3090, 323, 7432, 17, 1139, 15525, 3956, 3238, 362, 43593, 2204, 1648, 16782, 11, 735, 3376, 15849, 430, 433, 690, 1935, 264, 1418, 311, 636, 311, 430, 1486, 13, 364, 2028, 374, 2555, 369, 279, 1317, 4751, 323, 433, 1436, 387, 2500, 33517, 1667, 1603, 584, 617, 264, 1749, 430, 3727, 15525, 3956, 323, 374, 1101, 22514, 11, 69311, 323, 2853, 53421, 13, 2030, 358, 2846, 38330, 22954, 430, 420, 374, 279, 1648, 311, 733, 13, 1102, 690, 539, 387, 4228, 11, 719, 420, 18841, 374, 11190, 13, 1226, 617, 311, 1505, 264, 43593, 2204, 1648, 311, 10299, 4907, 11, 323, 1057, 18841, 649, 17210, 311, 430, 3238, 220, 128257, 198 ]

1,898

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Single-molecule surface-enhanced Raman spectroscopy (SERS) has attracted increasing interest for chemical and biochemical sensing. Many conventional substrates have a broad distribution of SERS enhancements, which compromise reproducibility and result in slow response times for single-molecule detection. Here we report a smart plasmonic sensor that can reversibly trap a single molecule at hotspots for rapid single-molecule detection. The sensor was fabricated through electrostatic self-assembly of gold nanoparticles onto a gold/silica-coated silicon substrate, producing a high yield of uniformly distributed hotspots on the surface. The hotspots were isolated with a monolayer of a thermoresponsive polymer (poly( N -isopropylacrylamide)), which act as gates for molecular trapping at the hotspots. The sensor shows not only a good SERS reproducibility but also a capability to repetitively trap and release molecules for single-molecular sensing. The single-molecule sensitivity is experimentally verified using SERS spectral blinking and bianalyte methods. Introduction Surface-enhanced Raman spectroscopy (SERS) is one of the few techniques that are capable of detecting and identifying chemical and biological compounds with single-molecule sensitivity 1 , 2 , 3 , 4 , 5 , 6 . This technique takes advantage of plasmonic (metal) nanostructures to amplify Raman signals. A unique feature of these metal nanostructures is they show a resonant oscillation of their conduction electrons on light irradiation. This light-matter interaction leads to an enormous electromagnetic field enhancement in the close vicinity of the metal surfaces. The field enhancement is particularly strong at sharp corners or tips 1 , 7 , interparticle gaps 8 , 9 , 10 , 11 , 12 , 13 and nanoscale pores 4 , 14 typically referred to as ‘hotspots’. Although the importance of hotspots has been both experimentally and theoretically demonstrated for SERS sensing 1 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , the fraction of analytes adsorbed to the hotspots for a conventional SERS substrate is extremely small due to the low spatial occupation of hotspots per unit area 14 , 15 . For example, a silver film-over-nanosphere SERS substrate showed a wide distribution of SERS enhancement factors (EFs) ranging from 2.8 × 10 4 to > 1 × 10 10 (ref. 15 ). Yet, the hottest spots, with SERS EFs larger than 10 9 , only accounted for 63 out of a million of total Raman-active sites 15 . There is therefore a prevailing need for the development of innovative SERS substrates that have a large number of uniformly distributed hotspots and the analyte molecules can be confined only at the hotspots. Several concepts have been developed with the aim to adsorb target analytes only at the hotspots 16 . The most straightforward one is the isolation of hotspots with a chemically inert material. Diebold et al. 17 developed a near-field optical lithography method to isolate hotspots on a macroscopic SERS substrate composed of an array of nanocones covered by a thin layer of a photoresist. The excitation of the nanocones with a laser scanning across the substrate results in a strong near field at the tips of the cones (that is, hotspots), which causes preferential exposure of the photoresist at the hotspots. The removal of the exposed photoresist yields a substrate for which only the hotspots are available as binding sites. A requirement for detection in such a sensor however is the analytes having a strong affinity for the metal. A promising alternative approach is the analyte trapping at hotspots. Hu et al. 18 demonstrated a molecular trap based on gold-coated flexible polymer fingers for SERS sensing. The tips of these gold nanofingers were brought together by the capillary force of solvent evaporation, resulting in molecules trapped between the tips 18 . This drying process inevitably results in the deposition of analytes outside the hotspots. Álvarez-Puebla et al. 19 developed a more controllable trapping system made of microgels. These microgels are composed of stimuli-responsive polymer-coated gold nanoparticles (AuNPs). The polymer shell either swelled or collapsed when responding to the external temperature. This change in volume was utilized as a means to trap the analytes and get them close to the metal surface, where the electromagnetic field is significantly enhanced. However, the overall SERS enhancement from these individual colloidal nanoparticles (NPs) is usually insufficient for single-molecule detection. To date, many complex plasmonic nanostructures, such as film-coupled metallic NPs (also referred as to NPs-on-mirror) 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , metal NP assemblies 2 , 3 , 6 , 7 , 8 , 9 , 10 , 11 , 12 and porous metal films 4 , 14 have been fabricated for SERS applications. Among all of these, film-coupled metallic NPs are of special interest for two reasons. First, the simplicity of this system makes it an ideal model for theoretical simulation studies 24 , 25 , 26 , 27 . Second, it has been shown that such a system enables SERS-based single-molecule detection 23 . In this work, we develop a smart plasmonic molecular trap based on a well-established film-coupled AuNP system on a silica-coated silicon optical interference substrate and demonstrate a gating mechanism to control the trapping and release of analytes at the particle–substrate gaps (that is, hotspots) for SERS-based single-molecule detection. Silica-coated silicon substrates are chosen as the silica layer can generate an additional SERS enhancement up to 50 times due to an interference effect 29 . The hotspots of the molecular trap developed here are isolated with a self-assembled monolayer of thermoresponsive polymer, which acts as gates for the reversible molecular trapping at the hotspots. The trapped molecules can be subsequently released after SERS sensing. This reversible trapping process makes it possible to detect an abundance of analytes in one measurement but also to reuse the SERS substrate multiple times. Results Sensor fabrication The fabrication of the smart plasmonic molecular traps and their SERS sensing mechanism are schematically illustrated in Fig. 1 . Gold/silica-coated silicon substrates were fabricated by evaporation of a 15-nm gold film on", "role": "user" }, { "content": "Australian and Italian researchers have developed a smart sensor that can detect single molecules in chemical and biological compounds – a highly valued function in medicine, security and defence. The researchers from the University of New South Wales, Swinburne University of Technology, Monash University and the University of Parma in Italy used a chemical and biochemical sensing technique called surface-enhanced Raman spectroscopy (SERS), which is used to understand more about the make-up of materials. They were able to greatly amplify the technique's performance by taking advantage of metal nanostructures, which help generate 'hotspots' in close proximity to the metal surfaces. The sensor was created using gold nanoparticles which self-assemble onto a gold- and silica-coated silicon base. This approach means the nanoparticles find the perfect spacing to achieve lots of uniformly distributed hotspots on the surface. The hotspots also used a heat responsive polymer which acted as a gate to trap molecules, but importantly also allow them to be released down the track. \"The sensor shows not only a good SERS reproducibility but also the ability to repetitively catch and release molecules for single-molecular sensing,\" postdoctoral fellow at Swinburne's Centre for Micro-Photonics, Dr Lorenzo Rosa, said. \"This reversible trapping process makes it possible to detect an abundance of analytes in one measurement, but also to reuse the SERS substrate multiple times.\" The technique used in this work has various applications for other measurement and detection systems sensitive to humidity, pH and light. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Single-molecule surface-enhanced Raman spectroscopy (SERS) has attracted increasing interest for chemical and biochemical sensing. Many conventional substrates have a broad distribution of SERS enhancements, which compromise reproducibility and result in slow response times for single-molecule detection. Here we report a smart plasmonic sensor that can reversibly trap a single molecule at hotspots for rapid single-molecule detection. The sensor was fabricated through electrostatic self-assembly of gold nanoparticles onto a gold/silica-coated silicon substrate, producing a high yield of uniformly distributed hotspots on the surface. The hotspots were isolated with a monolayer of a thermoresponsive polymer (poly( N -isopropylacrylamide)), which act as gates for molecular trapping at the hotspots. The sensor shows not only a good SERS reproducibility but also a capability to repetitively trap and release molecules for single-molecular sensing. The single-molecule sensitivity is experimentally verified using SERS spectral blinking and bianalyte methods. Introduction Surface-enhanced Raman spectroscopy (SERS) is one of the few techniques that are capable of detecting and identifying chemical and biological compounds with single-molecule sensitivity 1 , 2 , 3 , 4 , 5 , 6 . This technique takes advantage of plasmonic (metal) nanostructures to amplify Raman signals. A unique feature of these metal nanostructures is they show a resonant oscillation of their conduction electrons on light irradiation. This light-matter interaction leads to an enormous electromagnetic field enhancement in the close vicinity of the metal surfaces. The field enhancement is particularly strong at sharp corners or tips 1 , 7 , interparticle gaps 8 , 9 , 10 , 11 , 12 , 13 and nanoscale pores 4 , 14 typically referred to as ‘hotspots’. Although the importance of hotspots has been both experimentally and theoretically demonstrated for SERS sensing 1 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , the fraction of analytes adsorbed to the hotspots for a conventional SERS substrate is extremely small due to the low spatial occupation of hotspots per unit area 14 , 15 . For example, a silver film-over-nanosphere SERS substrate showed a wide distribution of SERS enhancement factors (EFs) ranging from 2.8 × 10 4 to > 1 × 10 10 (ref. 15 ). Yet, the hottest spots, with SERS EFs larger than 10 9 , only accounted for 63 out of a million of total Raman-active sites 15 . There is therefore a prevailing need for the development of innovative SERS substrates that have a large number of uniformly distributed hotspots and the analyte molecules can be confined only at the hotspots. Several concepts have been developed with the aim to adsorb target analytes only at the hotspots 16 . The most straightforward one is the isolation of hotspots with a chemically inert material. Diebold et al. 17 developed a near-field optical lithography method to isolate hotspots on a macroscopic SERS substrate composed of an array of nanocones covered by a thin layer of a photoresist. The excitation of the nanocones with a laser scanning across the substrate results in a strong near field at the tips of the cones (that is, hotspots), which causes preferential exposure of the photoresist at the hotspots. The removal of the exposed photoresist yields a substrate for which only the hotspots are available as binding sites. A requirement for detection in such a sensor however is the analytes having a strong affinity for the metal. A promising alternative approach is the analyte trapping at hotspots. Hu et al. 18 demonstrated a molecular trap based on gold-coated flexible polymer fingers for SERS sensing. The tips of these gold nanofingers were brought together by the capillary force of solvent evaporation, resulting in molecules trapped between the tips 18 . This drying process inevitably results in the deposition of analytes outside the hotspots. Álvarez-Puebla et al. 19 developed a more controllable trapping system made of microgels. These microgels are composed of stimuli-responsive polymer-coated gold nanoparticles (AuNPs). The polymer shell either swelled or collapsed when responding to the external temperature. This change in volume was utilized as a means to trap the analytes and get them close to the metal surface, where the electromagnetic field is significantly enhanced. However, the overall SERS enhancement from these individual colloidal nanoparticles (NPs) is usually insufficient for single-molecule detection. To date, many complex plasmonic nanostructures, such as film-coupled metallic NPs (also referred as to NPs-on-mirror) 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , metal NP assemblies 2 , 3 , 6 , 7 , 8 , 9 , 10 , 11 , 12 and porous metal films 4 , 14 have been fabricated for SERS applications. Among all of these, film-coupled metallic NPs are of special interest for two reasons. First, the simplicity of this system makes it an ideal model for theoretical simulation studies 24 , 25 , 26 , 27 . Second, it has been shown that such a system enables SERS-based single-molecule detection 23 . In this work, we develop a smart plasmonic molecular trap based on a well-established film-coupled AuNP system on a silica-coated silicon optical interference substrate and demonstrate a gating mechanism to control the trapping and release of analytes at the particle–substrate gaps (that is, hotspots) for SERS-based single-molecule detection. Silica-coated silicon substrates are chosen as the silica layer can generate an additional SERS enhancement up to 50 times due to an interference effect 29 . The hotspots of the molecular trap developed here are isolated with a self-assembled monolayer of thermoresponsive polymer, which acts as gates for the reversible molecular trapping at the hotspots. The trapped molecules can be subsequently released after SERS sensing. This reversible trapping process makes it possible to detect an abundance of analytes in one measurement but also to reuse the SERS substrate multiple times. Results Sensor fabrication The fabrication of the smart plasmonic molecular traps and their SERS sensing mechanism are schematically illustrated in Fig. 1 . Gold/silica-coated silicon substrates were fabricated by evaporation of a 15-nm gold film on<|im_end|> <|im_start|>assistant Australian and Italian researchers have developed a smart sensor that can detect single molecules in chemical and biological compounds – a highly valued function in medicine, security and defence. The researchers from the University of New South Wales, Swinburne University of Technology, Monash University and the University of Parma in Italy used a chemical and biochemical sensing technique called surface-enhanced Raman spectroscopy (SERS), which is used to understand more about the make-up of materials. They were able to greatly amplify the technique's performance by taking advantage of metal nanostructures, which help generate 'hotspots' in close proximity to the metal surfaces. The sensor was created using gold nanoparticles which self-assemble onto a gold- and silica-coated silicon base. This approach means the nanoparticles find the perfect spacing to achieve lots of uniformly distributed hotspots on the surface. The hotspots also used a heat responsive polymer which acted as a gate to trap molecules, but importantly also allow them to be released down the track. "The sensor shows not only a good SERS reproducibility but also the ability to repetitively catch and release molecules for single-molecular sensing," postdoctoral fellow at Swinburne's Centre for Micro-Photonics, Dr Lorenzo Rosa, said. "This reversible trapping process makes it possible to detect an abundance of analytes in one measurement, but also to reuse the SERS substrate multiple times." The technique used in this work has various applications for other measurement and detection systems sensitive to humidity, pH and light. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 11579, 1474, 55269, 7479, 84182, 4979, 432, 13005, 66425, 51856, 320, 50, 4419, 8, 706, 29123, 7859, 2802, 369, 11742, 323, 93532, 60199, 13, 9176, 21349, 16146, 988, 617, 264, 7353, 8141, 315, 328, 4419, 59629, 11, 902, 30485, 53823, 7697, 3225, 323, 1121, 304, 6435, 2077, 3115, 369, 3254, 1474, 55269, 18468, 13, 5810, 584, 1934, 264, 7941, 628, 300, 74689, 12271, 430, 649, 17888, 6623, 23709, 264, 3254, 43030, 520, 4106, 68110, 369, 11295, 3254, 1474, 55269, 18468, 13, 578, 12271, 574, 70554, 1555, 25396, 2020, 659, 12, 15343, 315, 6761, 94753, 8800, 264, 6761, 2754, 321, 3074, 23283, 660, 51692, 54057, 11, 17843, 264, 1579, 7692, 315, 78909, 4332, 4106, 68110, 389, 279, 7479, 13, 578, 4106, 68110, 1051, 25181, 449, 264, 1647, 337, 1155, 315, 264, 30945, 4692, 14555, 47393, 320, 34535, 7, 452, 482, 285, 454, 897, 4010, 582, 894, 24705, 579, 5850, 902, 1180, 439, 35634, 369, 31206, 93669, 520, 279, 4106, 68110, 13, 578, 12271, 5039, 539, 1193, 264, 1695, 328, 4419, 53823, 7697, 3225, 719, 1101, 264, 23099, 311, 27427, 275, 3210, 23709, 323, 4984, 35715, 369, 3254, 1474, 43943, 60199, 13, 578, 3254, 1474, 55269, 27541, 374, 9526, 750, 24884, 1701, 328, 4419, 57077, 85122, 323, 97589, 5893, 668, 5528, 13, 29438, 28061, 84182, 4979, 432, 13005, 66425, 51856, 320, 50, 4419, 8, 374, 832, 315, 279, 2478, 12823, 430, 527, 13171, 315, 54626, 323, 25607, 11742, 323, 24156, 32246, 449, 3254, 1474, 55269, 27541, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 662, 1115, 15105, 5097, 9610, 315, 628, 300, 74689, 320, 55108, 8, 51593, 47194, 311, 97168, 432, 13005, 17738, 13, 362, 5016, 4668, 315, 1521, 9501, 51593, 47194, 374, 814, 1501, 264, 29280, 519, 43524, 367, 315, 872, 390, 23985, 57678, 389, 3177, 76327, 367, 13, 1115, 3177, 1474, 1683, 16628, 11767, 311, 459, 23205, 66669, 2115, 27886, 304, 279, 3345, 53851, 315, 279, 9501, 27529, 13, 578, 2115, 27886, 374, 8104, 3831, 520, 17676, 24359, 477, 10631, 220, 16, 1174, 220, 22, 1174, 958, 43079, 33251, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 323, 20622, 437, 2296, 72028, 220, 19, 1174, 220, 975, 11383, 14183, 311, 439, 3451, 10847, 68110, 24535, 10541, 279, 12939, 315, 4106, 68110, 706, 1027, 2225, 9526, 750, 323, 63234, 21091, 369, 328, 4419, 60199, 220, 16, 1174, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 279, 19983, 315, 8678, 2392, 14058, 269, 2788, 311, 279, 4106, 68110, 369, 264, 21349, 328, 4419, 54057, 374, 9193, 2678, 4245, 311, 279, 3428, 29079, 30747, 315, 4106, 68110, 824, 5089, 3158, 220, 975, 1174, 220, 868, 662, 1789, 3187, 11, 264, 15310, 4632, 29352, 5392, 44705, 8182, 328, 4419, 54057, 8710, 264, 7029, 8141, 315, 328, 4419, 27886, 9547, 320, 15229, 82, 8, 24950, 505, 220, 17, 13, 23, 25800, 220, 605, 220, 19, 311, 871, 220, 16, 25800, 220, 605, 220, 605, 320, 1116, 13, 220, 868, 7609, 14968, 11, 279, 38391, 19300, 11, 449, 328, 4419, 45090, 82, 8294, 1109, 220, 605, 220, 24, 1174, 1193, 41853, 369, 220, 5495, 704, 315, 264, 3610, 315, 2860, 432, 13005, 32344, 6732, 220, 868, 662, 2684, 374, 9093, 264, 61129, 1205, 369, 279, 4500, 315, 18699, 328, 4419, 16146, 988, 430, 617, 264, 3544, 1396, 315, 78909, 4332, 4106, 68110, 323, 279, 8678, 668, 35715, 649, 387, 45408, 1193, 520, 279, 4106, 68110, 13, 26778, 19476, 617, 1027, 8040, 449, 279, 9395, 311, 14058, 30986, 2218, 8678, 2392, 1193, 520, 279, 4106, 68110, 220, 845, 662, 578, 1455, 31439, 832, 374, 279, 31398, 315, 4106, 68110, 449, 264, 8590, 2740, 81073, 3769, 13, 8574, 15168, 1880, 453, 13, 220, 1114, 8040, 264, 3221, 19677, 29393, 46282, 5814, 1749, 311, 43223, 4106, 68110, 389, 264, 18563, 58510, 328, 4419, 54057, 24306, 315, 459, 1358, 315, 51593, 444, 288, 9960, 555, 264, 15792, 6324, 315, 264, 6685, 417, 380, 13, 578, 3521, 7709, 315, 279, 51593, 444, 288, 449, 264, 21120, 36201, 4028, 279, 54057, 3135, 304, 264, 3831, 3221, 2115, 520, 279, 10631, 315, 279, 87992, 320, 9210, 374, 11, 4106, 68110, 705, 902, 11384, 10932, 2335, 14675, 315, 279, 6685, 417, 380, 520, 279, 4106, 68110, 13, 578, 17065, 315, 279, 15246, 6685, 417, 380, 36508, 264, 54057, 369, 902, 1193, 279, 4106, 68110, 527, 2561, 439, 11212, 6732, 13, 362, 16686, 369, 18468, 304, 1778, 264, 12271, 4869, 374, 279, 8678, 2392, 3515, 264, 3831, 51552, 369, 279, 9501, 13, 362, 26455, 10778, 5603, 374, 279, 8678, 668, 93669, 520, 4106, 68110, 13, 22546, 1880, 453, 13, 220, 972, 21091, 264, 31206, 23709, 3196, 389, 6761, 23283, 660, 19303, 47393, 19779, 369, 328, 4419, 60199, 13, 578, 10631, 315, 1521, 6761, 20622, 1073, 14437, 1051, 7263, 3871, 555, 279, 2107, 35605, 5457, 315, 69996, 3721, 96649, 11, 13239, 304, 35715, 31691, 1990, 279, 10631, 220, 972, 662, 1115, 46479, 1920, 40605, 3135, 304, 279, 65374, 315, 8678, 2392, 4994, 279, 4106, 68110, 13, 43912, 22580, 39614, 9483, 361, 65826, 1880, 453, 13, 220, 777, 8040, 264, 810, 687, 69855, 93669, 1887, 1903, 315, 8162, 70, 2053, 13, 4314, 8162, 70, 2053, 527, 24306, 315, 56688, 21638, 47393, 23283, 660, 6761, 94753, 320, 66432, 45, 21051, 570, 578, 47393, 12811, 3060, 2064, 15556, 477, 29368, 994, 30438, 311, 279, 9434, 9499, 13, 1115, 2349, 304, 8286, 574, 34716, 439, 264, 3445, 311, 23709, 279, 8678, 2392, 323, 636, 1124, 3345, 311, 279, 9501, 7479, 11, 1405, 279, 66669, 2115, 374, 12207, 24872, 13, 4452, 11, 279, 8244, 328, 4419, 27886, 505, 1521, 3927, 82048, 26966, 94753, 320, 45, 21051, 8, 374, 6118, 39413, 369, 3254, 1474, 55269, 18468, 13, 2057, 2457, 11, 1690, 6485, 628, 300, 74689, 51593, 47194, 11, 1778, 439, 4632, 1824, 283, 50185, 46258, 452, 21051, 320, 19171, 14183, 439, 311, 452, 21051, 10539, 1474, 29912, 8, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 1174, 220, 1627, 1174, 220, 1544, 1174, 220, 1591, 1174, 9501, 44340, 62407, 220, 17, 1174, 220, 18, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 323, 94761, 9501, 12631, 220, 19, 1174, 220, 975, 617, 1027, 70554, 369, 328, 4419, 8522, 13, 22395, 682, 315, 1521, 11, 4632, 1824, 283, 50185, 46258, 452, 21051, 527, 315, 3361, 2802, 369, 1403, 8125, 13, 5629, 11, 279, 40075, 315, 420, 1887, 3727, 433, 459, 10728, 1646, 369, 32887, 19576, 7978, 220, 1187, 1174, 220, 914, 1174, 220, 1627, 1174, 220, 1544, 662, 10657, 11, 433, 706, 1027, 6982, 430, 1778, 264, 1887, 20682, 328, 4419, 6108, 3254, 1474, 55269, 18468, 220, 1419, 662, 763, 420, 990, 11, 584, 2274, 264, 7941, 628, 300, 74689, 31206, 23709, 3196, 389, 264, 1664, 64868, 4632, 1824, 283, 50185, 33150, 27321, 1887, 389, 264, 77889, 23283, 660, 51692, 29393, 32317, 54057, 323, 20461, 264, 74499, 17383, 311, 2585, 279, 93669, 323, 4984, 315, 8678, 2392, 520, 279, 19320, 4235, 29714, 349, 33251, 320, 9210, 374, 11, 4106, 68110, 8, 369, 328, 4419, 6108, 3254, 1474, 55269, 18468, 13, 8211, 3074, 23283, 660, 51692, 16146, 988, 527, 12146, 439, 279, 77889, 6324, 649, 7068, 459, 5217, 328, 4419, 27886, 709, 311, 220, 1135, 3115, 4245, 311, 459, 32317, 2515, 220, 1682, 662, 578, 4106, 68110, 315, 279, 31206, 23709, 8040, 1618, 527, 25181, 449, 264, 659, 33534, 26994, 1647, 337, 1155, 315, 30945, 4692, 14555, 47393, 11, 902, 14385, 439, 35634, 369, 279, 81193, 31206, 93669, 520, 279, 4106, 68110, 13, 578, 31691, 35715, 649, 387, 28520, 6004, 1306, 328, 4419, 60199, 13, 1115, 81193, 93669, 1920, 3727, 433, 3284, 311, 11388, 459, 37492, 315, 8678, 2392, 304, 832, 19179, 719, 1101, 311, 27068, 279, 328, 4419, 54057, 5361, 3115, 13, 18591, 31145, 59251, 578, 59251, 315, 279, 7941, 628, 300, 74689, 31206, 45660, 323, 872, 328, 4419, 60199, 17383, 527, 20225, 7167, 36762, 304, 23966, 13, 220, 16, 662, 7573, 2754, 321, 3074, 23283, 660, 51692, 16146, 988, 1051, 70554, 555, 3721, 96649, 315, 264, 220, 868, 5392, 76, 6761, 4632, 389, 128257, 198, 128256, 78191, 198, 75341, 323, 15155, 12074, 617, 8040, 264, 7941, 12271, 430, 649, 11388, 3254, 35715, 304, 11742, 323, 24156, 32246, 1389, 264, 7701, 33647, 734, 304, 16088, 11, 4868, 323, 23682, 13, 578, 12074, 505, 279, 3907, 315, 1561, 4987, 23782, 11, 4593, 258, 22464, 68, 3907, 315, 12053, 11, 3206, 1003, 3907, 323, 279, 3907, 315, 4366, 1764, 304, 15704, 1511, 264, 11742, 323, 93532, 60199, 15105, 2663, 7479, 84182, 4979, 432, 13005, 66425, 51856, 320, 50, 4419, 705, 902, 374, 1511, 311, 3619, 810, 922, 279, 1304, 5352, 315, 7384, 13, 2435, 1051, 3025, 311, 19407, 97168, 279, 15105, 596, 5178, 555, 4737, 9610, 315, 9501, 51593, 47194, 11, 902, 1520, 7068, 364, 10847, 68110, 6, 304, 3345, 37843, 311, 279, 9501, 27529, 13, 578, 12271, 574, 3549, 1701, 6761, 94753, 902, 659, 33534, 16167, 8800, 264, 6761, 12, 323, 77889, 23283, 660, 51692, 2385, 13, 1115, 5603, 3445, 279, 94753, 1505, 279, 4832, 27032, 311, 11322, 10283, 315, 78909, 4332, 4106, 68110, 389, 279, 7479, 13, 578, 4106, 68110, 1101, 1511, 264, 8798, 27078, 47393, 902, 31532, 439, 264, 18618, 311, 23709, 35715, 11, 719, 23659, 1101, 2187, 1124, 311, 387, 6004, 1523, 279, 3839, 13, 330, 791, 12271, 5039, 539, 1193, 264, 1695, 328, 4419, 53823, 7697, 3225, 719, 1101, 279, 5845, 311, 27427, 275, 3210, 2339, 323, 4984, 35715, 369, 3254, 1474, 43943, 60199, 1359, 1772, 38083, 278, 12637, 520, 4593, 258, 22464, 68, 596, 14821, 369, 18654, 12, 94150, 1233, 11, 2999, 74500, 47930, 11, 1071, 13, 330, 2028, 81193, 93669, 1920, 3727, 433, 3284, 311, 11388, 459, 37492, 315, 8678, 2392, 304, 832, 19179, 11, 719, 1101, 311, 27068, 279, 328, 4419, 54057, 5361, 3115, 1210, 578, 15105, 1511, 304, 420, 990, 706, 5370, 8522, 369, 1023, 19179, 323, 18468, 6067, 16614, 311, 38193, 11, 37143, 323, 3177, 13, 220, 128257, 198 ]

1,724

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract American football has both the highest rate of concussion incidences as well as the highest number of concussions of all contact sports due to both the number of athletes and nature of the sport. Recent research has linked concussions with long term health complications such as chronic traumatic encephalopathy and early onset Alzheimer’s. Understanding the mechanical characteristics of concussive impacts is critical to help protect athletes from these debilitating diseases and is now possible using helmet-based sensor systems. To date, real time on-field measurement of head impacts has been almost exclusively measured by devices that rely on accelerometers or gyroscopes attached to the player’s helmet, or embedded in a mouth guard. These systems monitor motion of the head or helmet, but do not directly measure impact energy. This paper evaluates the accuracy of a novel, multifunctional foam-based sensor that replaces a portion of the helmet foam to measure impact. All modified helmets were tested using a National Operating Committee Standards for Athletic Equipment-style drop tower with a total of 24 drop tests (4 locations with 6 impact energies). The impacts were evaluated using a headform, instrumented with a tri-axial accelerometer, mounted to a Hybrid III neck assembly. The resultant accelerations were evaluated for both the peak acceleration and the severity indices. These data were then compared to the voltage response from multiple Nano Composite Foam sensors located throughout the helmet. The foam sensor system proved to be accurate in measuring both the HIC and Gadd severity index, as well as peak acceleration while also providing additional details that were previously difficult to obtain, such as impact energy. Access provided by Universität des es, -und Working on a manuscript? Avoid the common mistakes Introduction Concussions due to contact sports have received a great deal of attention in recent years. For decades, the dangers were ignored or misunderstood, but with scientific data showing they are more dangerous than originally assumed, they can no longer be overlooked. 11 , 13 , 20 , 21 , 22 Younger athletes are believed to be more susceptible to concussion than older athletes and can have severe, acute, and long-term complications that are not found in their older counterparts. 2 , 35 , 36 Furthermore, it has been found that young athletes do not consistently self-report concussion, or concussion related symptoms, with some studies showing only 21% self-reporting. 43 A recent study found that out of 20 high school sports football had the highest incidence of concussion with an injury rate of 22.9 concussions per 10,000 athletic exposures, defined as one athlete participating in one athletic practice or competition. 30 Many scholars and medical professionals are looking for ways to more effectively quantify both the frequency and severity of impacts the players are experiencing. 6 , 7 , 8 , 31 , 39 , 45 With an increased understanding of athlete exposure throughout a game and even over a player’s career, medical professionals and helmet designers can better identify and protect against injury. Real time impact detection has become a reality with the introduction of consumer-based accelerometer systems. 46 Wearable devices have been developed to measure and/or calculate the head’s linear and angular acceleration during impact. These devices vary in their design and function, but generally depend on several different accelerometers and gyroscopes. These sensors have been directly implemented into helmets, patches (adhered to the skin), earplugs, skullcaps, mouthpieces, or chinstraps. 3 , 9 , 25 , 28 , 34 , 38 , 44 The accuracy in determining location and severity of impacts of each implementation has become the focus of researchers. 40 One system that is often included in studies is Riddell’s Head Impact Telemetry System, or HITS. 9 , 23 Riddell’s HIT system has been used in studies to determine severity and frequency of head impacts during a full season of play. 27 , 37 These data are then used to determine the effectiveness of efforts to reduce athlete concussion risk. These systems are experiencing a low adoption rate due to several factors: the expense (HITS costs $1,200 per helmet), difficulty of operation, and the limited number of helmets that are compatible with the system. Many of the current football impact measurement systems are mounted directly into or on the helmet and almost exclusively use accelerometers. These systems have been shown to overestimate head motion and head exposure. 4 , 29 Some systems, including the HITS, have attempted to reduce this disparity by using accelerometers that are pressed to the head with springs to maintain constant contact. 10 Furthermore, it has been shown that helmet fit can affect the accuracy of the HIT system. 27 Some systems attempt to directly measure head acceleration through closer contact with the head in the form of mouth guards, patches, or skull caps. 5 , 24 , 40 Some systems, such as Riddell’s Insight and Shockbox’s impact detection system, make no attempt in overcoming this disparity through design; it is assumed it is accomplished through post-processing. These issues are not easy to overcome and have been widely overlooked in previous work. The most widely accepted mobile gold standard helmet sensor is Riddell’s HITS. 9 , 10 Duma et al., demonstrate that Riddell’s HITS was capable of real-time measurement of impacts during football practice and games. HITS correlated well with a helmet-equipped Hybrid III dummy instrumented with an accelerometer array ( R 2 = 0.97). 10 Other systems have shown similar results by different implementations. 1 , 3 , 25 , 40 However, HITS only works with two different Riddell helmets. Additionally, the other systems mentioned must be calibrated for each helmet based on where the sensor is placed on the helmet. This paper seeks to evaluate the accuracy of a new NCF-based sensor that could be adapted into existing helmet designs. An ideal system would be compatible with any helmet type and provide measurement of impact directly experienced by the head. Materials and Methods Nano Composite Foam (NCF) Sensors This paper demonstrates the use of a new type", "role": "user" }, { "content": "Most football fans have seen players get hit so hard they can barely walk back to the sideline. All too often, those players are back on the field just a few plays later, despite suffering what appears to be a head injury. While football-related concussions have been top of mind in recent years, people have struggled to create technology to accurately measure them in real time. Enter BYU mechanical engineering Ph.D. student, Jake Merrell, and a team of researchers across three BYU departments. Merrell and others have developed and tested a nano composite smartfoam that can be placed inside a football helmet (and pads) to more accurately test the impact and power of hits. The foam measures the impact of a hit via electrical signals. The data is collected in real time and sent wirelessly to the tablet or device of a coach or trainer on the sidelines. A coach can know within seconds how hard a player has been hit and whether or not they should be concerned about a concussion. \"The standard measurement systems on the market today directly measure the acceleration, but just measuring the acceleration is not enough and can even be erroneous,\" Merrell said. \"Our XOnano smartfoam sensors measure much more than just acceleration, which we see as a vital key to better diagnose head injuries.\" The foam, which replaces the standard helmet foam, measures a composite of acceleration, impact energy and impact velocity to determine impact severity and location of impact, all with 90 percent accuracy, according to research published by Merrell in the Annals of Biomedical Engineering. To date, no one—not even the NFL—has been able to successfully measure the impact energy and velocity of a collision, which are two data points necessary to accurately measure whether a player is at risk of a concussion or not. Football shoulder pads with smartfoam from BYU. Credit: BYU Here's how the BYU smartfoam works: When the foam is compressed, nickel nano-particles rub against the foam, creating static electric charge, similar to when you rub a balloon against your hair. That charge is then collected through a conductive electrode in the foam, measured by a microcomputer, and transmitted to a computer or smart device. A hard hit spikes the voltage, while small impacts result in a reduced spike in voltage. Merrell is excited for the future of his smart foam technology as companies incorporate it into their products. Merrell and Xenith created shoulder pads with the impact sensing technology, and a company producing taekwondo vests has also started using the smartfoam to score fights and train athletes. Merrell worked with researchers in the mechanical engineering, exercise science and statistics departments at BYU on the nano composite foam. Mechanical engineering professors David Fullwood and Anton Bowden, exercise science professor Matthew Seeley, and statistics professor William Christensen were all coauthors on the study. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract American football has both the highest rate of concussion incidences as well as the highest number of concussions of all contact sports due to both the number of athletes and nature of the sport. Recent research has linked concussions with long term health complications such as chronic traumatic encephalopathy and early onset Alzheimer’s. Understanding the mechanical characteristics of concussive impacts is critical to help protect athletes from these debilitating diseases and is now possible using helmet-based sensor systems. To date, real time on-field measurement of head impacts has been almost exclusively measured by devices that rely on accelerometers or gyroscopes attached to the player’s helmet, or embedded in a mouth guard. These systems monitor motion of the head or helmet, but do not directly measure impact energy. This paper evaluates the accuracy of a novel, multifunctional foam-based sensor that replaces a portion of the helmet foam to measure impact. All modified helmets were tested using a National Operating Committee Standards for Athletic Equipment-style drop tower with a total of 24 drop tests (4 locations with 6 impact energies). The impacts were evaluated using a headform, instrumented with a tri-axial accelerometer, mounted to a Hybrid III neck assembly. The resultant accelerations were evaluated for both the peak acceleration and the severity indices. These data were then compared to the voltage response from multiple Nano Composite Foam sensors located throughout the helmet. The foam sensor system proved to be accurate in measuring both the HIC and Gadd severity index, as well as peak acceleration while also providing additional details that were previously difficult to obtain, such as impact energy. Access provided by Universität des es, -und Working on a manuscript? Avoid the common mistakes Introduction Concussions due to contact sports have received a great deal of attention in recent years. For decades, the dangers were ignored or misunderstood, but with scientific data showing they are more dangerous than originally assumed, they can no longer be overlooked. 11 , 13 , 20 , 21 , 22 Younger athletes are believed to be more susceptible to concussion than older athletes and can have severe, acute, and long-term complications that are not found in their older counterparts. 2 , 35 , 36 Furthermore, it has been found that young athletes do not consistently self-report concussion, or concussion related symptoms, with some studies showing only 21% self-reporting. 43 A recent study found that out of 20 high school sports football had the highest incidence of concussion with an injury rate of 22.9 concussions per 10,000 athletic exposures, defined as one athlete participating in one athletic practice or competition. 30 Many scholars and medical professionals are looking for ways to more effectively quantify both the frequency and severity of impacts the players are experiencing. 6 , 7 , 8 , 31 , 39 , 45 With an increased understanding of athlete exposure throughout a game and even over a player’s career, medical professionals and helmet designers can better identify and protect against injury. Real time impact detection has become a reality with the introduction of consumer-based accelerometer systems. 46 Wearable devices have been developed to measure and/or calculate the head’s linear and angular acceleration during impact. These devices vary in their design and function, but generally depend on several different accelerometers and gyroscopes. These sensors have been directly implemented into helmets, patches (adhered to the skin), earplugs, skullcaps, mouthpieces, or chinstraps. 3 , 9 , 25 , 28 , 34 , 38 , 44 The accuracy in determining location and severity of impacts of each implementation has become the focus of researchers. 40 One system that is often included in studies is Riddell’s Head Impact Telemetry System, or HITS. 9 , 23 Riddell’s HIT system has been used in studies to determine severity and frequency of head impacts during a full season of play. 27 , 37 These data are then used to determine the effectiveness of efforts to reduce athlete concussion risk. These systems are experiencing a low adoption rate due to several factors: the expense (HITS costs $1,200 per helmet), difficulty of operation, and the limited number of helmets that are compatible with the system. Many of the current football impact measurement systems are mounted directly into or on the helmet and almost exclusively use accelerometers. These systems have been shown to overestimate head motion and head exposure. 4 , 29 Some systems, including the HITS, have attempted to reduce this disparity by using accelerometers that are pressed to the head with springs to maintain constant contact. 10 Furthermore, it has been shown that helmet fit can affect the accuracy of the HIT system. 27 Some systems attempt to directly measure head acceleration through closer contact with the head in the form of mouth guards, patches, or skull caps. 5 , 24 , 40 Some systems, such as Riddell’s Insight and Shockbox’s impact detection system, make no attempt in overcoming this disparity through design; it is assumed it is accomplished through post-processing. These issues are not easy to overcome and have been widely overlooked in previous work. The most widely accepted mobile gold standard helmet sensor is Riddell’s HITS. 9 , 10 Duma et al., demonstrate that Riddell’s HITS was capable of real-time measurement of impacts during football practice and games. HITS correlated well with a helmet-equipped Hybrid III dummy instrumented with an accelerometer array ( R 2 = 0.97). 10 Other systems have shown similar results by different implementations. 1 , 3 , 25 , 40 However, HITS only works with two different Riddell helmets. Additionally, the other systems mentioned must be calibrated for each helmet based on where the sensor is placed on the helmet. This paper seeks to evaluate the accuracy of a new NCF-based sensor that could be adapted into existing helmet designs. An ideal system would be compatible with any helmet type and provide measurement of impact directly experienced by the head. Materials and Methods Nano Composite Foam (NCF) Sensors This paper demonstrates the use of a new type<|im_end|> <|im_start|>assistant Most football fans have seen players get hit so hard they can barely walk back to the sideline. All too often, those players are back on the field just a few plays later, despite suffering what appears to be a head injury. While football-related concussions have been top of mind in recent years, people have struggled to create technology to accurately measure them in real time. Enter BYU mechanical engineering Ph.D. student, Jake Merrell, and a team of researchers across three BYU departments. Merrell and others have developed and tested a nano composite smartfoam that can be placed inside a football helmet (and pads) to more accurately test the impact and power of hits. The foam measures the impact of a hit via electrical signals. The data is collected in real time and sent wirelessly to the tablet or device of a coach or trainer on the sidelines. A coach can know within seconds how hard a player has been hit and whether or not they should be concerned about a concussion. "The standard measurement systems on the market today directly measure the acceleration, but just measuring the acceleration is not enough and can even be erroneous," Merrell said. "Our XOnano smartfoam sensors measure much more than just acceleration, which we see as a vital key to better diagnose head injuries." The foam, which replaces the standard helmet foam, measures a composite of acceleration, impact energy and impact velocity to determine impact severity and location of impact, all with 90 percent accuracy, according to research published by Merrell in the Annals of Biomedical Engineering. To date, no one—not even the NFL—has been able to successfully measure the impact energy and velocity of a collision, which are two data points necessary to accurately measure whether a player is at risk of a concussion or not. Football shoulder pads with smartfoam from BYU. Credit: BYU Here's how the BYU smartfoam works: When the foam is compressed, nickel nano-particles rub against the foam, creating static electric charge, similar to when you rub a balloon against your hair. That charge is then collected through a conductive electrode in the foam, measured by a microcomputer, and transmitted to a computer or smart device. A hard hit spikes the voltage, while small impacts result in a reduced spike in voltage. Merrell is excited for the future of his smart foam technology as companies incorporate it into their products. Merrell and Xenith created shoulder pads with the impact sensing technology, and a company producing taekwondo vests has also started using the smartfoam to score fights and train athletes. Merrell worked with researchers in the mechanical engineering, exercise science and statistics departments at BYU on the nano composite foam. Mechanical engineering professors David Fullwood and Anton Bowden, exercise science professor Matthew Seeley, and statistics professor William Christensen were all coauthors on the study. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 3778, 9141, 706, 2225, 279, 8592, 4478, 315, 69006, 62960, 2436, 439, 1664, 439, 279, 8592, 1396, 315, 3613, 39833, 315, 682, 3729, 10034, 4245, 311, 2225, 279, 1396, 315, 23579, 323, 7138, 315, 279, 10775, 13, 35390, 3495, 706, 10815, 3613, 39833, 449, 1317, 4751, 2890, 36505, 1778, 439, 21249, 54286, 665, 59822, 278, 54042, 323, 4216, 42080, 44531, 753, 13, 46551, 279, 22936, 17910, 315, 3613, 1892, 535, 25949, 374, 9200, 311, 1520, 6144, 23579, 505, 1521, 92890, 19338, 323, 374, 1457, 3284, 1701, 32635, 6108, 12271, 6067, 13, 2057, 2457, 11, 1972, 892, 389, 19677, 19179, 315, 2010, 25949, 706, 1027, 4661, 24121, 17303, 555, 7766, 430, 17631, 389, 14511, 33504, 477, 67968, 82025, 12673, 311, 279, 2851, 753, 32635, 11, 477, 23711, 304, 264, 11013, 7771, 13, 4314, 6067, 8891, 11633, 315, 279, 2010, 477, 32635, 11, 719, 656, 539, 6089, 6767, 5536, 4907, 13, 1115, 5684, 67349, 279, 13708, 315, 264, 11775, 11, 62387, 600, 278, 32183, 6108, 12271, 430, 41800, 264, 13651, 315, 279, 32635, 32183, 311, 6767, 5536, 13, 2052, 11041, 65720, 1051, 12793, 1701, 264, 5165, 36233, 10554, 35653, 369, 51506, 20849, 11549, 6068, 21970, 449, 264, 2860, 315, 220, 1187, 6068, 7177, 320, 19, 10687, 449, 220, 21, 5536, 49969, 570, 578, 25949, 1051, 26126, 1701, 264, 2010, 630, 11, 14473, 291, 449, 264, 2463, 12, 710, 532, 97848, 11, 22563, 311, 264, 50727, 14767, 13272, 14956, 13, 578, 84913, 14511, 811, 1051, 26126, 369, 2225, 279, 16557, 31903, 323, 279, 31020, 15285, 13, 4314, 828, 1051, 1243, 7863, 311, 279, 22465, 2077, 505, 5361, 64051, 41739, 77556, 26148, 7559, 6957, 279, 32635, 13, 578, 32183, 12271, 1887, 19168, 311, 387, 13687, 304, 30090, 2225, 279, 473, 1341, 323, 480, 723, 31020, 1963, 11, 439, 1664, 439, 16557, 31903, 1418, 1101, 8405, 5217, 3649, 430, 1051, 8767, 5107, 311, 6994, 11, 1778, 439, 5536, 4907, 13, 9742, 3984, 555, 15915, 37714, 951, 1560, 11, 482, 1263, 22938, 389, 264, 47913, 30, 35106, 279, 4279, 21294, 29438, 63798, 39833, 4245, 311, 3729, 10034, 617, 4036, 264, 2294, 3568, 315, 6666, 304, 3293, 1667, 13, 1789, 11026, 11, 279, 37064, 1051, 12305, 477, 73956, 11, 719, 449, 12624, 828, 9204, 814, 527, 810, 11660, 1109, 13517, 19655, 11, 814, 649, 912, 5129, 387, 45536, 13, 220, 806, 1174, 220, 1032, 1174, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 13566, 261, 23579, 527, 11846, 311, 387, 810, 47281, 311, 69006, 1109, 9191, 23579, 323, 649, 617, 15748, 11, 30883, 11, 323, 1317, 9860, 36505, 430, 527, 539, 1766, 304, 872, 9191, 38495, 13, 220, 17, 1174, 220, 1758, 1174, 220, 1927, 24296, 11, 433, 706, 1027, 1766, 430, 3995, 23579, 656, 539, 21356, 659, 48511, 69006, 11, 477, 69006, 5552, 13803, 11, 449, 1063, 7978, 9204, 1193, 220, 1691, 4, 659, 48511, 287, 13, 220, 3391, 362, 3293, 4007, 1766, 430, 704, 315, 220, 508, 1579, 2978, 10034, 9141, 1047, 279, 8592, 39775, 315, 69006, 449, 459, 11134, 4478, 315, 220, 1313, 13, 24, 3613, 39833, 824, 220, 605, 11, 931, 29703, 70530, 11, 4613, 439, 832, 34880, 24435, 304, 832, 29703, 6725, 477, 10937, 13, 220, 966, 9176, 31839, 323, 6593, 15749, 527, 3411, 369, 5627, 311, 810, 13750, 76498, 2225, 279, 11900, 323, 31020, 315, 25949, 279, 4311, 527, 25051, 13, 220, 21, 1174, 220, 22, 1174, 220, 23, 1174, 220, 2148, 1174, 220, 2137, 1174, 220, 1774, 3161, 459, 7319, 8830, 315, 34880, 14675, 6957, 264, 1847, 323, 1524, 927, 264, 2851, 753, 7076, 11, 6593, 15749, 323, 32635, 26897, 649, 2731, 10765, 323, 6144, 2403, 11134, 13, 8976, 892, 5536, 18468, 706, 3719, 264, 8903, 449, 279, 17219, 315, 11761, 6108, 97848, 6067, 13, 220, 2790, 42162, 481, 7766, 617, 1027, 8040, 311, 6767, 323, 5255, 11294, 279, 2010, 753, 13790, 323, 20932, 31903, 2391, 5536, 13, 4314, 7766, 13592, 304, 872, 2955, 323, 734, 11, 719, 8965, 6904, 389, 3892, 2204, 14511, 33504, 323, 67968, 82025, 13, 4314, 26148, 617, 1027, 6089, 11798, 1139, 65720, 11, 29760, 320, 329, 1964, 291, 311, 279, 6930, 705, 2487, 501, 13602, 11, 35113, 49333, 11, 11013, 47568, 11, 477, 46175, 496, 2690, 13, 220, 18, 1174, 220, 24, 1174, 220, 914, 1174, 220, 1591, 1174, 220, 1958, 1174, 220, 1987, 1174, 220, 2096, 578, 13708, 304, 26679, 3813, 323, 31020, 315, 25949, 315, 1855, 8292, 706, 3719, 279, 5357, 315, 12074, 13, 220, 1272, 3861, 1887, 430, 374, 3629, 5343, 304, 7978, 374, 432, 1810, 616, 753, 11452, 29680, 2722, 37058, 744, 11, 477, 473, 14813, 13, 220, 24, 1174, 220, 1419, 432, 1810, 616, 753, 79503, 1887, 706, 1027, 1511, 304, 7978, 311, 8417, 31020, 323, 11900, 315, 2010, 25949, 2391, 264, 2539, 3280, 315, 1514, 13, 220, 1544, 1174, 220, 1806, 4314, 828, 527, 1243, 1511, 311, 8417, 279, 27375, 315, 9045, 311, 8108, 34880, 69006, 5326, 13, 4314, 6067, 527, 25051, 264, 3428, 25375, 4478, 4245, 311, 3892, 9547, 25, 279, 20900, 320, 39, 14813, 7194, 400, 16, 11, 1049, 824, 32635, 705, 17250, 315, 5784, 11, 323, 279, 7347, 1396, 315, 65720, 430, 527, 18641, 449, 279, 1887, 13, 9176, 315, 279, 1510, 9141, 5536, 19179, 6067, 527, 22563, 6089, 1139, 477, 389, 279, 32635, 323, 4661, 24121, 1005, 14511, 33504, 13, 4314, 6067, 617, 1027, 6982, 311, 927, 41230, 2010, 11633, 323, 2010, 14675, 13, 220, 19, 1174, 220, 1682, 4427, 6067, 11, 2737, 279, 473, 14813, 11, 617, 17644, 311, 8108, 420, 66949, 555, 1701, 14511, 33504, 430, 527, 17770, 311, 279, 2010, 449, 42242, 311, 10519, 6926, 3729, 13, 220, 605, 24296, 11, 433, 706, 1027, 6982, 430, 32635, 5052, 649, 7958, 279, 13708, 315, 279, 79503, 1887, 13, 220, 1544, 4427, 6067, 4879, 311, 6089, 6767, 2010, 31903, 1555, 12401, 3729, 449, 279, 2010, 304, 279, 1376, 315, 11013, 27270, 11, 29760, 11, 477, 35113, 19079, 13, 220, 20, 1174, 220, 1187, 1174, 220, 1272, 4427, 6067, 11, 1778, 439, 432, 1810, 616, 753, 72071, 323, 48083, 2054, 753, 5536, 18468, 1887, 11, 1304, 912, 4879, 304, 74017, 420, 66949, 1555, 2955, 26, 433, 374, 19655, 433, 374, 27332, 1555, 1772, 70293, 13, 4314, 4819, 527, 539, 4228, 311, 23075, 323, 617, 1027, 13882, 45536, 304, 3766, 990, 13, 578, 1455, 13882, 11928, 6505, 6761, 5410, 32635, 12271, 374, 432, 1810, 616, 753, 473, 14813, 13, 220, 24, 1174, 220, 605, 423, 13722, 1880, 453, 2637, 20461, 430, 432, 1810, 616, 753, 473, 14813, 574, 13171, 315, 1972, 7394, 19179, 315, 25949, 2391, 9141, 6725, 323, 3953, 13, 473, 14813, 49393, 1664, 449, 264, 32635, 88202, 50727, 14767, 17741, 14473, 291, 449, 459, 97848, 1358, 320, 432, 220, 17, 284, 220, 15, 13, 3534, 570, 220, 605, 7089, 6067, 617, 6982, 4528, 3135, 555, 2204, 39437, 13, 220, 16, 1174, 220, 18, 1174, 220, 914, 1174, 220, 1272, 4452, 11, 473, 14813, 1193, 4375, 449, 1403, 2204, 432, 1810, 616, 65720, 13, 23212, 11, 279, 1023, 6067, 9932, 2011, 387, 86085, 369, 1855, 32635, 3196, 389, 1405, 279, 12271, 374, 9277, 389, 279, 32635, 13, 1115, 5684, 26737, 311, 15806, 279, 13708, 315, 264, 502, 452, 9847, 6108, 12271, 430, 1436, 387, 30464, 1139, 6484, 32635, 14769, 13, 1556, 10728, 1887, 1053, 387, 18641, 449, 904, 32635, 955, 323, 3493, 19179, 315, 5536, 6089, 10534, 555, 279, 2010, 13, 32009, 323, 19331, 64051, 41739, 77556, 320, 45, 9847, 8, 95520, 1115, 5684, 32216, 279, 1005, 315, 264, 502, 955, 128257, 198, 128256, 78191, 198, 13622, 9141, 7359, 617, 3970, 4311, 636, 4295, 779, 2653, 814, 649, 20025, 4321, 1203, 311, 279, 80053, 13, 2052, 2288, 3629, 11, 1884, 4311, 527, 1203, 389, 279, 2115, 1120, 264, 2478, 11335, 3010, 11, 8994, 16066, 1148, 8111, 311, 387, 264, 2010, 11134, 13, 6104, 9141, 14228, 3613, 39833, 617, 1027, 1948, 315, 4059, 304, 3293, 1667, 11, 1274, 617, 28214, 311, 1893, 5557, 311, 30357, 6767, 1124, 304, 1972, 892, 13, 11502, 93454, 22936, 15009, 2405, 920, 13, 5575, 11, 33172, 8930, 16684, 11, 323, 264, 2128, 315, 12074, 4028, 2380, 93454, 26280, 13, 8930, 16684, 323, 3885, 617, 8040, 323, 12793, 264, 51593, 28814, 7941, 831, 309, 430, 649, 387, 9277, 4871, 264, 9141, 32635, 320, 438, 37095, 8, 311, 810, 30357, 1296, 279, 5536, 323, 2410, 315, 13280, 13, 578, 32183, 11193, 279, 5536, 315, 264, 4295, 4669, 20314, 17738, 13, 578, 828, 374, 14890, 304, 1972, 892, 323, 3288, 9244, 16117, 311, 279, 21354, 477, 3756, 315, 264, 7395, 477, 29994, 389, 279, 70513, 13, 362, 7395, 649, 1440, 2949, 6622, 1268, 2653, 264, 2851, 706, 1027, 4295, 323, 3508, 477, 539, 814, 1288, 387, 11920, 922, 264, 69006, 13, 330, 791, 5410, 19179, 6067, 389, 279, 3157, 3432, 6089, 6767, 279, 31903, 11, 719, 1120, 30090, 279, 31903, 374, 539, 3403, 323, 649, 1524, 387, 77772, 1359, 8930, 16684, 1071, 13, 330, 8140, 1630, 1966, 5770, 7941, 831, 309, 26148, 6767, 1790, 810, 1109, 1120, 31903, 11, 902, 584, 1518, 439, 264, 16595, 1401, 311, 2731, 58681, 2010, 15319, 1210, 578, 32183, 11, 902, 41800, 279, 5410, 32635, 32183, 11, 11193, 264, 28814, 315, 31903, 11, 5536, 4907, 323, 5536, 15798, 311, 8417, 5536, 31020, 323, 3813, 315, 5536, 11, 682, 449, 220, 1954, 3346, 13708, 11, 4184, 311, 3495, 4756, 555, 8930, 16684, 304, 279, 9489, 1147, 315, 12371, 61860, 17005, 13, 2057, 2457, 11, 912, 832, 63938, 1524, 279, 12873, 2345, 4752, 1027, 3025, 311, 7946, 6767, 279, 5536, 4907, 323, 15798, 315, 264, 19277, 11, 902, 527, 1403, 828, 3585, 5995, 311, 30357, 6767, 3508, 264, 2851, 374, 520, 5326, 315, 264, 69006, 477, 539, 13, 21424, 17308, 37095, 449, 7941, 831, 309, 505, 93454, 13, 16666, 25, 93454, 5810, 596, 1268, 279, 93454, 7941, 831, 309, 4375, 25, 3277, 279, 32183, 374, 31749, 11, 52349, 51593, 2320, 16641, 10485, 2403, 279, 32183, 11, 6968, 1118, 9249, 6900, 11, 4528, 311, 994, 499, 10485, 264, 47856, 2403, 701, 7013, 13, 3011, 6900, 374, 1243, 14890, 1555, 264, 6929, 535, 72048, 304, 279, 32183, 11, 17303, 555, 264, 8162, 44211, 11, 323, 34699, 311, 264, 6500, 477, 7941, 3756, 13, 362, 2653, 4295, 51760, 279, 22465, 11, 1418, 2678, 25949, 1121, 304, 264, 11293, 37393, 304, 22465, 13, 8930, 16684, 374, 12304, 369, 279, 3938, 315, 813, 7941, 32183, 5557, 439, 5220, 33435, 433, 1139, 872, 3956, 13, 8930, 16684, 323, 49329, 411, 3549, 17308, 37095, 449, 279, 5536, 60199, 5557, 11, 323, 264, 2883, 17843, 9637, 1247, 86, 36071, 98373, 706, 1101, 3940, 1701, 279, 7941, 831, 309, 311, 5573, 28533, 323, 5542, 23579, 13, 8930, 16684, 6575, 449, 12074, 304, 279, 22936, 15009, 11, 10368, 8198, 323, 13443, 26280, 520, 93454, 389, 279, 51593, 28814, 32183, 13, 51684, 15009, 45724, 6941, 8797, 6798, 323, 17958, 18943, 5294, 11, 10368, 8198, 14561, 19475, 3580, 3258, 11, 323, 13443, 14561, 12656, 3771, 35117, 1051, 682, 1080, 48105, 389, 279, 4007, 13, 220, 128257, 198 ]

1,848

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract To better understand how network structure shapes intelligent behavior, we developed a learning algorithm that we used to build personalized brain network models for 650 Human Connectome Project participants. We found that participants with higher intelligence scores took more time to solve difficult problems, and that slower solvers had higher average functional connectivity. With simulations we identified a mechanistic link between functional connectivity, intelligence, processing speed and brain synchrony for trading accuracy with speed in dependence of excitation-inhibition balance. Reduced synchrony led decision-making circuits to quickly jump to conclusions, while higher synchrony allowed for better integration of evidence and more robust working memory. Strict tests were applied to ensure reproducibility and generality of the obtained results. Here, we identify links between brain structure and function that enable to learn connectome topology from noninvasive recordings and map it to inter-individual differences in behavior, suggesting broad utility for research and clinical applications. Introduction Do intelligent people think faster? Strong correlations between reaction times and intellectual performance support this idea, providing a cornerstone for intelligence research for over one century 1 , 2 , 3 , 4 , 5 , 6 . Here, we show an important exception in empirical data and provide an explanation based on brain simulation (Supplementary Movie 1 ). Participants with higher intelligence were only faster when the test was simple. Conversely, in hard tests that required problem solving over several seconds or minutes without time limit, participants with higher intelligence used more, not less time to arrive at correct solutions. We reproduced this link between reaction time and performance in personalized multi-scale brain network models 7 , 8 (BNMs) that couple each participant’s structural white-matter connectivity (SC) with a generic neural circuit for decision-making (DM) and working memory (WM). Simulation results indicate that decision-making speed is traded with accuracy, resembling influential theories from the fields of economy and psychology on fast and slow thinking 9 . Intelligence is here defined as the performance in psychometric tests in cognitive domains like verbal comprehension, perceptual reasoning or working memory. A consistent finding is that individuals who perform well in one domain tend to perform well in the others, which led to the derivation of a general factor of intelligence called g -factor 10 . While the g -factor also targets learned skills like verbal fluency, the term fluid intelligence (FI) refers to abilities related to solving new problems independently of acquired knowledge 11 . Reaction time (RT) as a measure of cognitive processing speed provides strong evidence in support of the idea that people are more intelligent because they have faster brains 2 . A meta-analysis over 172 studies and 53,542 participants reported strong negative correlations between general intelligence and diverse measures of RT 6 . RT and intelligence are also linked over the lifespan: RT increases with age and is strongly correlated with decline in other domains 5 , 12 . Intriguingly, RT is a more powerful predictor of death than well-known risk factors like hypertension, obesity, or resting heart rate: RT is the second most important predictor of death after smoking 13 and explains two-thirds of the relationship between general intelligence and death 14 . After adjusting for smoking, education, and social class, RT was an even stronger predictor of death than intelligence. However, these results do not imply that PS is the causal factor underlying intelligence: an important counterargument is that training and improving PS does not transfer to untrained measures 15 . We found that participants with higher intelligence were only quicker when responding to simple questions, while they took more time to solve hard questions. This became apparent in the Penn Matrix Reasoning Test (PMAT), which consists of a series of increasingly difficult pattern matching tasks for quantifying FI 11 . While PS tests are typically so simple that people would not make any errors if given enough time, FI tests like PMAT can be unsolvable even without time limit. PMAT requires to infer hidden rules that govern the figure, which involves a recursive decomposition of complex problems into easier subproblems, forming a hierarchy of DM processes 11 . To solve the problem, it is required to make decisions about tentative solution paths while storing previous progress in WM. Sub-problems higher up in the hierarchy need to be held longer in WM as evidence from lower in the hierarchy needs to be integrated later in time 11 . Therefore, taking decisions on higher-level problems must be held out until evidence from sub-problems was integrated to not prematurely jump to a conclusion. This form of cognition can be contrasted with the flexibility required by PS tests where it is actually advantageous if decisions do not rely on extensive accumulation of evidence and memories can be flexibly overwritten. Here, by closely fitting brain models to each subject’s functional connectivity (FC), we identify a fast mode of cognition for rapid decision-making and flexible working memory and contrast it with a slow mode of cognition that supports prolonged integration of information and more stable working memory. Importantly, by identifying a smooth and monotonous relationship between structural and functional neural network architecture it was possible to devise a network fitting algorithm that allows to simultaneously and precisely control the state of synchronization between every pair of network nodes, allowing to tune each connection from full antisynchronization to full synchronization, enabling a close reproduction of whole-brain subject-specific FC. In the following, we first provide behavioral findings that link intelligence test results with processing speed and FC (Fig. 1 and Table 1 ). Then we demonstrate a computational framework for closely fitting BNMs to personal FC (Figs. 2 and 3 ), and subsequently explain the empirical data based on the in silico identified biological candidate mechanisms (Figs. 4 – 6 and Supplementary Figures). For the fitting we created a parameter learning algorithm that makes use of our observation that FC and synchronization between two simulated brain areas can be smoothly and monotonically tuned via their long-range excitation-inhibition balance (E/I-ratio). We then", "role": "user" }, { "content": "Do intelligent people think faster? Researchers at the BIH and Charité—Universitätsmedizin Berlin, together with a colleague from Barcelona, made the surprising finding that participants with higher intelligence scores were only quicker when tackling simple tasks, while they took longer to solve difficult problems than subjects with lower IQ scores. In personalized brain simulations of the 650 participants, the researchers could determine that brains with reduced synchrony between brain areas literally \"jump to conclusions\" when making decisions, rather than waiting until upstream brain regions could complete the processing steps needed to solve the problem. In fact, the brain models for higher score participants also needed more time to solve challenging tasks but made fewer errors. The scientists have now published their findings in the journal Nature Communications. There are 100 billion or so neurons in the human brain. Each one of them is connected to an estimated 1,000 neighboring or distant neurons. This unfathomable network is the key to the brain's amazing capabilities, but it is also what makes it so difficult to understand how the brain works. Prof. Petra Ritter, head of the Brain Simulation Section at the Berlin Institute of Health at Charité (BIH) and at the Department of Neurology and Experimental Neurology of Charité—Universitätsmedizin Berlin, simulates the human brain using computers. \"We want to understand how the brain's decision-making processes work and why different people make different decisions,\" she says, describing the current project. Personalized brain models To simulate the mechanisms of the human brain, Ritter and her team use digital data from brain scans like magnetic resonance imaging (MRI) as well as mathematical models based on theoretical knowledge about biological processes. This initially results in a \"general\" human brain model. The scientists then refine this model using data from individual people, thus creating \"personalized brain models.\" For the present study, the scientists worked with data from 650 participants of the Human Connectome Project, a U.S. initiative that has been studying neural connections in the human brain since September 2010. \"It's the right excitation-inhibition balance of neurons that influences decision-making and more or less enables a person to solve problems,\" explains Ritter. Her team knew how participants fared on extensive cognitive tests and what their IQ scores were. Correlations between intelligence, RTs and FC. a, b Group-average g-factor (30 groups, based on g-factor, N = 650 subjects) versus RT for correct responses in PMAT questions #1 (very easy, p=4.0×10−6p=4.0×10−6p=4.0\\times {10}^{-6}) and #24 (very hard, p=3.0×10−6p=3.0×10−6p=3.0\\times {10}^{-6}). c, d Group-average and subject-level correlations between g/PMAT24_A_CR and the RT for correct responses in each individual PMAT question. Subjects with higher g/PMAT24_A_CR were quicker to correctly answer easy questions, but they took more time to correctly answer hard questions (questions sorted according to increasing difficulty; sign of correlation flips at question #9). e Group-average g-factor versus mean FC (20 groups, based on g-factor, N = 650 subjects, p=0.13p=0.13p=0.13). f Group-average PMAT24_A_RTCR versus mean FC (20 groups, based on PMAT24_A_RTCR, N = 650 subjects, p=6.9×10−7p=6.9×10−7p=6.9\\times {10}^{-7}). g, h Group-average (20 groups, based on PMAT24_A_RTCR) and subject-level correlations between mean FC and RT for correct responses in each PMAT question. Subjects that took more time to correctly answer test questions had a higher FC, independent of whether the question was easy or hard. P values of two-sided Pearson’s correlation test: *p < 0.05, **p < 0.01, ***p < 0.001; including only p values that remained significant after controlling for multiple comparisons using the Benjamini–Hochberg procedure with a False Discovery Rate of 0.1. Credit: Nature Communications (2023). DOI: 10.1038/s41467-023-38626-y Artificial brains behave like their biological counterparts \"We can reproduce the activity of individual brains very efficiently,\" says Ritter. \"We found out in the process that these in silico brains behave differently from one another—and in the same way as their biological counterparts. Our virtual avatars match the intellectual performance and reaction times of their biological analogues.\" Interestingly, the \"slower\" brains in both the humans and the models were more synchronized, i.e., in time with one other. This greater synchrony allowed neural circuits in the frontal lobe to hold off on decisions longer than brains that were less well coordinated. The models revealed how reduced temporal coordination results in the information required for decision-making neither being available when needed nor stored in working memory. Gathering evidence takes time—and leads to correct decisions Resting-state functional MRI scans showed that slower solvers had higher average functional connectivity, or temporal synchrony, between their brain regions. In personalized brain simulations of the 650 participants, the researchers could determine that brains with reduced functional connectivity literally \"jump to conclusions\" when making decisions, rather than waiting until upstream brain regions could complete the processing steps needed to solve the problem. Participants were asked to identify logical rules in a series of patterns. These rules became increasingly complex with each task and thus more difficult to decipher. In everyday terms, an easy task would consist of quickly braking at a red light, while a hard task would require methodically working out the best route on a road map. In the model, a so-called winner-take-all competition occurs between different neural groups involved in a decision, with the neural groups for which there is stronger evidence prevailing. Yet in the case of complex decisions, such evidence is often not clear enough for quick decision-making, literally forcing the neural groups to jump to conclusions. \"Synchronization, i.e., the formation of functional networks in the brain, alters the properties of working memory and thus the ability to 'endure' prolonged periods without a decision,\" explains Michael Schirner, lead author of the study and a scientist in Ritter's lab. \"In more challenging tasks, you have to store previous progress in working memory while you explore other solution paths and then integrate these into each other. This gathering of evidence for a particular solution may sometimes takes longer, but it also leads to better results. We were able to use the model to show how excitation-inhibition balance at the global level of the whole brain network affects decision-making and working memory at the more granular level of individual neural groups.\" Findings are interesting for treatment planning Ritter is pleased that the results observed in the computer-based \"brain avatars\" match the results seen in \"real\" healthy subjects. After all, her main interest is in helping patients affected by neurodegenerative diseases like dementia and Parkinson's disease. \"The simulation technology used in this study has made significant strides, and can be used to improve personalized in silico planning of surgical and drug interventions as well as therapeutic brain stimulation. For example, a physician can already use a computer simulation to assess which intervention or drug might work best for a particular patient and would have the fewest side effects.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract To better understand how network structure shapes intelligent behavior, we developed a learning algorithm that we used to build personalized brain network models for 650 Human Connectome Project participants. We found that participants with higher intelligence scores took more time to solve difficult problems, and that slower solvers had higher average functional connectivity. With simulations we identified a mechanistic link between functional connectivity, intelligence, processing speed and brain synchrony for trading accuracy with speed in dependence of excitation-inhibition balance. Reduced synchrony led decision-making circuits to quickly jump to conclusions, while higher synchrony allowed for better integration of evidence and more robust working memory. Strict tests were applied to ensure reproducibility and generality of the obtained results. Here, we identify links between brain structure and function that enable to learn connectome topology from noninvasive recordings and map it to inter-individual differences in behavior, suggesting broad utility for research and clinical applications. Introduction Do intelligent people think faster? Strong correlations between reaction times and intellectual performance support this idea, providing a cornerstone for intelligence research for over one century 1 , 2 , 3 , 4 , 5 , 6 . Here, we show an important exception in empirical data and provide an explanation based on brain simulation (Supplementary Movie 1 ). Participants with higher intelligence were only faster when the test was simple. Conversely, in hard tests that required problem solving over several seconds or minutes without time limit, participants with higher intelligence used more, not less time to arrive at correct solutions. We reproduced this link between reaction time and performance in personalized multi-scale brain network models 7 , 8 (BNMs) that couple each participant’s structural white-matter connectivity (SC) with a generic neural circuit for decision-making (DM) and working memory (WM). Simulation results indicate that decision-making speed is traded with accuracy, resembling influential theories from the fields of economy and psychology on fast and slow thinking 9 . Intelligence is here defined as the performance in psychometric tests in cognitive domains like verbal comprehension, perceptual reasoning or working memory. A consistent finding is that individuals who perform well in one domain tend to perform well in the others, which led to the derivation of a general factor of intelligence called g -factor 10 . While the g -factor also targets learned skills like verbal fluency, the term fluid intelligence (FI) refers to abilities related to solving new problems independently of acquired knowledge 11 . Reaction time (RT) as a measure of cognitive processing speed provides strong evidence in support of the idea that people are more intelligent because they have faster brains 2 . A meta-analysis over 172 studies and 53,542 participants reported strong negative correlations between general intelligence and diverse measures of RT 6 . RT and intelligence are also linked over the lifespan: RT increases with age and is strongly correlated with decline in other domains 5 , 12 . Intriguingly, RT is a more powerful predictor of death than well-known risk factors like hypertension, obesity, or resting heart rate: RT is the second most important predictor of death after smoking 13 and explains two-thirds of the relationship between general intelligence and death 14 . After adjusting for smoking, education, and social class, RT was an even stronger predictor of death than intelligence. However, these results do not imply that PS is the causal factor underlying intelligence: an important counterargument is that training and improving PS does not transfer to untrained measures 15 . We found that participants with higher intelligence were only quicker when responding to simple questions, while they took more time to solve hard questions. This became apparent in the Penn Matrix Reasoning Test (PMAT), which consists of a series of increasingly difficult pattern matching tasks for quantifying FI 11 . While PS tests are typically so simple that people would not make any errors if given enough time, FI tests like PMAT can be unsolvable even without time limit. PMAT requires to infer hidden rules that govern the figure, which involves a recursive decomposition of complex problems into easier subproblems, forming a hierarchy of DM processes 11 . To solve the problem, it is required to make decisions about tentative solution paths while storing previous progress in WM. Sub-problems higher up in the hierarchy need to be held longer in WM as evidence from lower in the hierarchy needs to be integrated later in time 11 . Therefore, taking decisions on higher-level problems must be held out until evidence from sub-problems was integrated to not prematurely jump to a conclusion. This form of cognition can be contrasted with the flexibility required by PS tests where it is actually advantageous if decisions do not rely on extensive accumulation of evidence and memories can be flexibly overwritten. Here, by closely fitting brain models to each subject’s functional connectivity (FC), we identify a fast mode of cognition for rapid decision-making and flexible working memory and contrast it with a slow mode of cognition that supports prolonged integration of information and more stable working memory. Importantly, by identifying a smooth and monotonous relationship between structural and functional neural network architecture it was possible to devise a network fitting algorithm that allows to simultaneously and precisely control the state of synchronization between every pair of network nodes, allowing to tune each connection from full antisynchronization to full synchronization, enabling a close reproduction of whole-brain subject-specific FC. In the following, we first provide behavioral findings that link intelligence test results with processing speed and FC (Fig. 1 and Table 1 ). Then we demonstrate a computational framework for closely fitting BNMs to personal FC (Figs. 2 and 3 ), and subsequently explain the empirical data based on the in silico identified biological candidate mechanisms (Figs. 4 – 6 and Supplementary Figures). For the fitting we created a parameter learning algorithm that makes use of our observation that FC and synchronization between two simulated brain areas can be smoothly and monotonically tuned via their long-range excitation-inhibition balance (E/I-ratio). We then<|im_end|> <|im_start|>assistant Do intelligent people think faster? Researchers at the BIH and Charité—Universitätsmedizin Berlin, together with a colleague from Barcelona, made the surprising finding that participants with higher intelligence scores were only quicker when tackling simple tasks, while they took longer to solve difficult problems than subjects with lower IQ scores. In personalized brain simulations of the 650 participants, the researchers could determine that brains with reduced synchrony between brain areas literally "jump to conclusions" when making decisions, rather than waiting until upstream brain regions could complete the processing steps needed to solve the problem. In fact, the brain models for higher score participants also needed more time to solve challenging tasks but made fewer errors. The scientists have now published their findings in the journal Nature Communications. There are 100 billion or so neurons in the human brain. Each one of them is connected to an estimated 1,000 neighboring or distant neurons. This unfathomable network is the key to the brain's amazing capabilities, but it is also what makes it so difficult to understand how the brain works. Prof. Petra Ritter, head of the Brain Simulation Section at the Berlin Institute of Health at Charité (BIH) and at the Department of Neurology and Experimental Neurology of Charité—Universitätsmedizin Berlin, simulates the human brain using computers. "We want to understand how the brain's decision-making processes work and why different people make different decisions," she says, describing the current project. Personalized brain models To simulate the mechanisms of the human brain, Ritter and her team use digital data from brain scans like magnetic resonance imaging (MRI) as well as mathematical models based on theoretical knowledge about biological processes. This initially results in a "general" human brain model. The scientists then refine this model using data from individual people, thus creating "personalized brain models." For the present study, the scientists worked with data from 650 participants of the Human Connectome Project, a U.S. initiative that has been studying neural connections in the human brain since September 2010. "It's the right excitation-inhibition balance of neurons that influences decision-making and more or less enables a person to solve problems," explains Ritter. Her team knew how participants fared on extensive cognitive tests and what their IQ scores were. Correlations between intelligence, RTs and FC. a, b Group-average g-factor (30 groups, based on g-factor, N = 650 subjects) versus RT for correct responses in PMAT questions #1 (very easy, p=4.0×10−6p=4.0×10−6p=4.0\times {10}^{-6}) and #24 (very hard, p=3.0×10−6p=3.0×10−6p=3.0\times {10}^{-6}). c, d Group-average and subject-level correlations between g/PMAT24_A_CR and the RT for correct responses in each individual PMAT question. Subjects with higher g/PMAT24_A_CR were quicker to correctly answer easy questions, but they took more time to correctly answer hard questions (questions sorted according to increasing difficulty; sign of correlation flips at question #9). e Group-average g-factor versus mean FC (20 groups, based on g-factor, N = 650 subjects, p=0.13p=0.13p=0.13). f Group-average PMAT24_A_RTCR versus mean FC (20 groups, based on PMAT24_A_RTCR, N = 650 subjects, p=6.9×10−7p=6.9×10−7p=6.9\times {10}^{-7}). g, h Group-average (20 groups, based on PMAT24_A_RTCR) and subject-level correlations between mean FC and RT for correct responses in each PMAT question. Subjects that took more time to correctly answer test questions had a higher FC, independent of whether the question was easy or hard. P values of two-sided Pearson’s correlation test: *p < 0.05, **p < 0.01, ***p < 0.001; including only p values that remained significant after controlling for multiple comparisons using the Benjamini–Hochberg procedure with a False Discovery Rate of 0.1. Credit: Nature Communications (2023). DOI: 10.1038/s41467-023-38626-y Artificial brains behave like their biological counterparts "We can reproduce the activity of individual brains very efficiently," says Ritter. "We found out in the process that these in silico brains behave differently from one another—and in the same way as their biological counterparts. Our virtual avatars match the intellectual performance and reaction times of their biological analogues." Interestingly, the "slower" brains in both the humans and the models were more synchronized, i.e., in time with one other. This greater synchrony allowed neural circuits in the frontal lobe to hold off on decisions longer than brains that were less well coordinated. The models revealed how reduced temporal coordination results in the information required for decision-making neither being available when needed nor stored in working memory. Gathering evidence takes time—and leads to correct decisions Resting-state functional MRI scans showed that slower solvers had higher average functional connectivity, or temporal synchrony, between their brain regions. In personalized brain simulations of the 650 participants, the researchers could determine that brains with reduced functional connectivity literally "jump to conclusions" when making decisions, rather than waiting until upstream brain regions could complete the processing steps needed to solve the problem. Participants were asked to identify logical rules in a series of patterns. These rules became increasingly complex with each task and thus more difficult to decipher. In everyday terms, an easy task would consist of quickly braking at a red light, while a hard task would require methodically working out the best route on a road map. In the model, a so-called winner-take-all competition occurs between different neural groups involved in a decision, with the neural groups for which there is stronger evidence prevailing. Yet in the case of complex decisions, such evidence is often not clear enough for quick decision-making, literally forcing the neural groups to jump to conclusions. "Synchronization, i.e., the formation of functional networks in the brain, alters the properties of working memory and thus the ability to 'endure' prolonged periods without a decision," explains Michael Schirner, lead author of the study and a scientist in Ritter's lab. "In more challenging tasks, you have to store previous progress in working memory while you explore other solution paths and then integrate these into each other. This gathering of evidence for a particular solution may sometimes takes longer, but it also leads to better results. We were able to use the model to show how excitation-inhibition balance at the global level of the whole brain network affects decision-making and working memory at the more granular level of individual neural groups." Findings are interesting for treatment planning Ritter is pleased that the results observed in the computer-based "brain avatars" match the results seen in "real" healthy subjects. After all, her main interest is in helping patients affected by neurodegenerative diseases like dementia and Parkinson's disease. "The simulation technology used in this study has made significant strides, and can be used to improve personalized in silico planning of surgical and drug interventions as well as therapeutic brain stimulation. For example, a physician can already use a computer simulation to assess which intervention or drug might work best for a particular patient and would have the fewest side effects." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 2057, 2731, 3619, 1268, 4009, 6070, 21483, 25530, 7865, 11, 584, 8040, 264, 6975, 12384, 430, 584, 1511, 311, 1977, 35649, 8271, 4009, 4211, 369, 220, 13655, 11344, 13313, 638, 5907, 13324, 13, 1226, 1766, 430, 13324, 449, 5190, 11478, 12483, 3952, 810, 892, 311, 11886, 5107, 5435, 11, 323, 430, 29493, 2092, 3078, 1047, 5190, 5578, 16003, 31357, 13, 3161, 47590, 584, 11054, 264, 7852, 4633, 2723, 1990, 16003, 31357, 11, 11478, 11, 8863, 4732, 323, 8271, 14453, 88, 369, 11380, 13708, 449, 4732, 304, 44393, 315, 3521, 7709, 3502, 60073, 8335, 13, 80569, 14453, 88, 6197, 5597, 28846, 46121, 311, 6288, 7940, 311, 31342, 11, 1418, 5190, 14453, 88, 5535, 369, 2731, 18052, 315, 6029, 323, 810, 22514, 3318, 5044, 13, 53981, 7177, 1051, 9435, 311, 6106, 53823, 7697, 3225, 323, 1803, 2786, 315, 279, 12457, 3135, 13, 5810, 11, 584, 10765, 7902, 1990, 8271, 6070, 323, 734, 430, 7431, 311, 4048, 4667, 638, 45982, 505, 2536, 258, 78134, 38140, 323, 2472, 433, 311, 958, 18251, 17246, 12062, 304, 7865, 11, 23377, 7353, 15919, 369, 3495, 323, 14830, 8522, 13, 29438, 3234, 25530, 1274, 1781, 10819, 30, 27191, 69916, 1990, 13010, 3115, 323, 20207, 5178, 1862, 420, 4623, 11, 8405, 264, 82575, 369, 11478, 3495, 369, 927, 832, 9478, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 662, 5810, 11, 584, 1501, 459, 3062, 4788, 304, 46763, 828, 323, 3493, 459, 16540, 3196, 389, 8271, 19576, 320, 10254, 67082, 14270, 220, 16, 7609, 52878, 449, 5190, 11478, 1051, 1193, 10819, 994, 279, 1296, 574, 4382, 13, 82671, 11, 304, 2653, 7177, 430, 2631, 3575, 22581, 927, 3892, 6622, 477, 4520, 2085, 892, 4017, 11, 13324, 449, 5190, 11478, 1511, 810, 11, 539, 2753, 892, 311, 17782, 520, 4495, 10105, 13, 1226, 55717, 420, 2723, 1990, 13010, 892, 323, 5178, 304, 35649, 7447, 13230, 8271, 4009, 4211, 220, 22, 1174, 220, 23, 320, 15967, 22365, 8, 430, 5743, 1855, 25923, 753, 24693, 4251, 1474, 1683, 31357, 320, 3624, 8, 449, 264, 14281, 30828, 16622, 369, 5597, 28846, 320, 8561, 8, 323, 3318, 5044, 320, 15565, 570, 44220, 3135, 13519, 430, 5597, 28846, 4732, 374, 31207, 449, 13708, 11, 71707, 32549, 26018, 505, 279, 5151, 315, 8752, 323, 31018, 389, 5043, 323, 6435, 7422, 220, 24, 662, 22107, 374, 1618, 4613, 439, 279, 5178, 304, 8841, 24264, 7177, 304, 25702, 31576, 1093, 36870, 62194, 11, 78632, 940, 33811, 477, 3318, 5044, 13, 362, 13263, 9455, 374, 430, 7931, 889, 2804, 1664, 304, 832, 8106, 8541, 311, 2804, 1664, 304, 279, 3885, 11, 902, 6197, 311, 279, 96354, 315, 264, 4689, 8331, 315, 11478, 2663, 342, 482, 38691, 220, 605, 662, 6104, 279, 342, 482, 38691, 1101, 11811, 9687, 7512, 1093, 36870, 20236, 2301, 11, 279, 4751, 15962, 11478, 320, 19991, 8, 19813, 311, 18000, 5552, 311, 22581, 502, 5435, 29235, 315, 19426, 6677, 220, 806, 662, 67941, 892, 320, 5463, 8, 439, 264, 6767, 315, 25702, 8863, 4732, 5825, 3831, 6029, 304, 1862, 315, 279, 4623, 430, 1274, 527, 810, 25530, 1606, 814, 617, 10819, 35202, 220, 17, 662, 362, 8999, 56536, 927, 220, 10861, 7978, 323, 220, 4331, 11, 21791, 13324, 5068, 3831, 8389, 69916, 1990, 4689, 11478, 323, 17226, 11193, 315, 10860, 220, 21, 662, 10860, 323, 11478, 527, 1101, 10815, 927, 279, 61961, 25, 10860, 12992, 449, 4325, 323, 374, 16917, 49393, 449, 18174, 304, 1023, 31576, 220, 20, 1174, 220, 717, 662, 61894, 343, 7623, 398, 11, 10860, 374, 264, 810, 8147, 62254, 315, 4648, 1109, 1664, 22015, 5326, 9547, 1093, 63308, 11, 33048, 11, 477, 41219, 4851, 4478, 25, 10860, 374, 279, 2132, 1455, 3062, 62254, 315, 4648, 1306, 20149, 220, 1032, 323, 15100, 1403, 45726, 315, 279, 5133, 1990, 4689, 11478, 323, 4648, 220, 975, 662, 4740, 43468, 369, 20149, 11, 6873, 11, 323, 3674, 538, 11, 10860, 574, 459, 1524, 16643, 62254, 315, 4648, 1109, 11478, 13, 4452, 11, 1521, 3135, 656, 539, 34608, 430, 11659, 374, 279, 59557, 8331, 16940, 11478, 25, 459, 3062, 5663, 14819, 374, 430, 4967, 323, 18899, 11659, 1587, 539, 8481, 311, 653, 36822, 11193, 220, 868, 662, 1226, 1766, 430, 13324, 449, 5190, 11478, 1051, 1193, 39392, 994, 30438, 311, 4382, 4860, 11, 1418, 814, 3952, 810, 892, 311, 11886, 2653, 4860, 13, 1115, 6244, 10186, 304, 279, 13813, 11892, 27857, 287, 3475, 320, 8971, 835, 705, 902, 17610, 315, 264, 4101, 315, 15098, 5107, 5497, 12864, 9256, 369, 10484, 7922, 51635, 220, 806, 662, 6104, 11659, 7177, 527, 11383, 779, 4382, 430, 1274, 1053, 539, 1304, 904, 6103, 422, 2728, 3403, 892, 11, 51635, 7177, 1093, 5975, 835, 649, 387, 7120, 89197, 1524, 2085, 892, 4017, 13, 5975, 835, 7612, 311, 24499, 8340, 5718, 430, 2633, 279, 7216, 11, 902, 18065, 264, 31919, 66266, 315, 6485, 5435, 1139, 8831, 1207, 96440, 11, 30164, 264, 30022, 315, 20804, 11618, 220, 806, 662, 2057, 11886, 279, 3575, 11, 433, 374, 2631, 311, 1304, 11429, 922, 76220, 6425, 13006, 1418, 28672, 3766, 5208, 304, 24030, 13, 3804, 10039, 22442, 5190, 709, 304, 279, 30022, 1205, 311, 387, 5762, 5129, 304, 24030, 439, 6029, 505, 4827, 304, 279, 30022, 3966, 311, 387, 18751, 3010, 304, 892, 220, 806, 662, 15636, 11, 4737, 11429, 389, 5190, 11852, 5435, 2011, 387, 5762, 704, 3156, 6029, 505, 1207, 10039, 22442, 574, 18751, 311, 539, 89019, 7940, 311, 264, 17102, 13, 1115, 1376, 315, 75310, 649, 387, 13168, 291, 449, 279, 25152, 2631, 555, 11659, 7177, 1405, 433, 374, 3604, 76824, 422, 11429, 656, 539, 17631, 389, 16781, 46835, 315, 6029, 323, 19459, 649, 387, 5882, 6623, 60273, 13, 5810, 11, 555, 15499, 27442, 8271, 4211, 311, 1855, 3917, 753, 16003, 31357, 320, 6897, 705, 584, 10765, 264, 5043, 3941, 315, 75310, 369, 11295, 5597, 28846, 323, 19303, 3318, 5044, 323, 13168, 433, 449, 264, 6435, 3941, 315, 75310, 430, 11815, 44387, 18052, 315, 2038, 323, 810, 15528, 3318, 5044, 13, 13516, 18007, 11, 555, 25607, 264, 11113, 323, 1647, 26934, 788, 5133, 1990, 24693, 323, 16003, 30828, 4009, 18112, 433, 574, 3284, 311, 53165, 264, 4009, 27442, 12384, 430, 6276, 311, 25291, 323, 24559, 2585, 279, 1614, 315, 59012, 1990, 1475, 6857, 315, 4009, 7954, 11, 10923, 311, 26306, 1855, 3717, 505, 2539, 65617, 69029, 311, 2539, 59012, 11, 28462, 264, 3345, 39656, 315, 4459, 31217, 467, 3917, 19440, 16396, 13, 763, 279, 2768, 11, 584, 1176, 3493, 36695, 14955, 430, 2723, 11478, 1296, 3135, 449, 8863, 4732, 323, 16396, 320, 30035, 13, 220, 16, 323, 6771, 220, 16, 7609, 5112, 584, 20461, 264, 55580, 12914, 369, 15499, 27442, 46416, 22365, 311, 4443, 16396, 320, 37, 14801, 13, 220, 17, 323, 220, 18, 7026, 323, 28520, 10552, 279, 46763, 828, 3196, 389, 279, 304, 5554, 4042, 11054, 24156, 9322, 24717, 320, 37, 14801, 13, 220, 19, 1389, 220, 21, 323, 99371, 69356, 570, 1789, 279, 27442, 584, 3549, 264, 5852, 6975, 12384, 430, 3727, 1005, 315, 1057, 22695, 430, 16396, 323, 59012, 1990, 1403, 46836, 8271, 5789, 649, 387, 39511, 323, 1647, 26934, 2740, 33519, 4669, 872, 1317, 31608, 3521, 7709, 3502, 60073, 8335, 320, 36, 39251, 3880, 6400, 570, 1226, 1243, 128257, 198, 128256, 78191, 198, 5519, 25530, 1274, 1781, 10819, 30, 59250, 520, 279, 48153, 39, 323, 4969, 13109, 2345, 65715, 65421, 2641, 2106, 78071, 20437, 11, 3871, 449, 264, 37444, 505, 28035, 11, 1903, 279, 15206, 9455, 430, 13324, 449, 5190, 11478, 12483, 1051, 1193, 39392, 994, 57911, 4382, 9256, 11, 1418, 814, 3952, 5129, 311, 11886, 5107, 5435, 1109, 15223, 449, 4827, 37811, 12483, 13, 763, 35649, 8271, 47590, 315, 279, 220, 13655, 13324, 11, 279, 12074, 1436, 8417, 430, 35202, 449, 11293, 14453, 88, 1990, 8271, 5789, 16280, 330, 44396, 311, 31342, 1, 994, 3339, 11429, 11, 4856, 1109, 8748, 3156, 42830, 8271, 13918, 1436, 4686, 279, 8863, 7504, 4460, 311, 11886, 279, 3575, 13, 763, 2144, 11, 279, 8271, 4211, 369, 5190, 5573, 13324, 1101, 4460, 810, 892, 311, 11886, 17436, 9256, 719, 1903, 17162, 6103, 13, 578, 14248, 617, 1457, 4756, 872, 14955, 304, 279, 8486, 22037, 26545, 13, 2684, 527, 220, 1041, 7239, 477, 779, 34313, 304, 279, 3823, 8271, 13, 9062, 832, 315, 1124, 374, 8599, 311, 459, 13240, 220, 16, 11, 931, 42617, 477, 29827, 34313, 13, 1115, 9662, 73555, 481, 4009, 374, 279, 1401, 311, 279, 8271, 596, 8056, 17357, 11, 719, 433, 374, 1101, 1148, 3727, 433, 779, 5107, 311, 3619, 1268, 279, 8271, 4375, 13, 8626, 13, 85037, 432, 3328, 11, 2010, 315, 279, 31417, 44220, 11360, 520, 279, 20437, 10181, 315, 6401, 520, 4969, 13109, 320, 8768, 39, 8, 323, 520, 279, 6011, 315, 32359, 36781, 323, 57708, 32359, 36781, 315, 4969, 13109, 2345, 65715, 65421, 2641, 2106, 78071, 20437, 11, 1675, 24031, 279, 3823, 8271, 1701, 19002, 13, 330, 1687, 1390, 311, 3619, 1268, 279, 8271, 596, 5597, 28846, 11618, 990, 323, 3249, 2204, 1274, 1304, 2204, 11429, 1359, 1364, 2795, 11, 23524, 279, 1510, 2447, 13, 19758, 1534, 8271, 4211, 2057, 38553, 279, 24717, 315, 279, 3823, 8271, 11, 432, 3328, 323, 1077, 2128, 1005, 7528, 828, 505, 8271, 43739, 1093, 24924, 58081, 32758, 320, 79770, 8, 439, 1664, 439, 37072, 4211, 3196, 389, 32887, 6677, 922, 24156, 11618, 13, 1115, 15453, 3135, 304, 264, 330, 25615, 1, 3823, 8271, 1646, 13, 578, 14248, 1243, 46464, 420, 1646, 1701, 828, 505, 3927, 1274, 11, 8617, 6968, 330, 30712, 1534, 8271, 4211, 1210, 1789, 279, 3118, 4007, 11, 279, 14248, 6575, 449, 828, 505, 220, 13655, 13324, 315, 279, 11344, 13313, 638, 5907, 11, 264, 549, 815, 13, 20770, 430, 706, 1027, 21630, 30828, 13537, 304, 279, 3823, 8271, 2533, 6250, 220, 679, 15, 13, 330, 2181, 596, 279, 1314, 3521, 7709, 3502, 60073, 8335, 315, 34313, 430, 34453, 5597, 28846, 323, 810, 477, 2753, 20682, 264, 1732, 311, 11886, 5435, 1359, 15100, 432, 3328, 13, 6385, 2128, 7020, 1268, 13324, 282, 1636, 389, 16781, 25702, 7177, 323, 1148, 872, 37811, 12483, 1051, 13, 4563, 66434, 1990, 11478, 11, 10860, 82, 323, 16396, 13, 264, 11, 293, 5856, 78526, 342, 75197, 320, 966, 5315, 11, 3196, 389, 342, 75197, 11, 452, 284, 220, 13655, 15223, 8, 19579, 10860, 369, 4495, 14847, 304, 5975, 835, 4860, 674, 16, 320, 1225, 4228, 11, 281, 28, 19, 13, 15, 18028, 605, 34363, 21, 79, 28, 19, 13, 15, 18028, 605, 34363, 21, 79, 28, 19, 13, 15, 5061, 1769, 314, 605, 92, 88310, 21, 5525, 323, 674, 1187, 320, 1225, 2653, 11, 281, 28, 18, 13, 15, 18028, 605, 34363, 21, 79, 28, 18, 13, 15, 18028, 605, 34363, 21, 79, 28, 18, 13, 15, 5061, 1769, 314, 605, 92, 88310, 21, 17041, 272, 11, 294, 5856, 78526, 323, 3917, 11852, 69916, 1990, 342, 14, 8971, 835, 1187, 1596, 25305, 323, 279, 10860, 369, 4495, 14847, 304, 1855, 3927, 5975, 835, 3488, 13, 65818, 449, 5190, 342, 14, 8971, 835, 1187, 1596, 25305, 1051, 39392, 311, 12722, 4320, 4228, 4860, 11, 719, 814, 3952, 810, 892, 311, 12722, 4320, 2653, 4860, 320, 17800, 10839, 4184, 311, 7859, 17250, 26, 1879, 315, 26670, 86286, 520, 3488, 674, 24, 570, 384, 5856, 78526, 342, 75197, 19579, 3152, 16396, 320, 508, 5315, 11, 3196, 389, 342, 75197, 11, 452, 284, 220, 13655, 15223, 11, 281, 28, 15, 13, 1032, 79, 28, 15, 13, 1032, 79, 28, 15, 13, 1032, 570, 282, 5856, 78526, 5975, 835, 1187, 1596, 80045, 49, 19579, 3152, 16396, 320, 508, 5315, 11, 3196, 389, 5975, 835, 1187, 1596, 80045, 49, 11, 452, 284, 220, 13655, 15223, 11, 281, 28, 21, 13, 24, 18028, 605, 34363, 22, 79, 28, 21, 13, 24, 18028, 605, 34363, 22, 79, 28, 21, 13, 24, 5061, 1769, 314, 605, 92, 88310, 22, 17041, 342, 11, 305, 5856, 78526, 320, 508, 5315, 11, 3196, 389, 5975, 835, 1187, 1596, 80045, 49, 8, 323, 3917, 11852, 69916, 1990, 3152, 16396, 323, 10860, 369, 4495, 14847, 304, 1855, 5975, 835, 3488, 13, 65818, 430, 3952, 810, 892, 311, 12722, 4320, 1296, 4860, 1047, 264, 5190, 16396, 11, 9678, 315, 3508, 279, 3488, 574, 4228, 477, 2653, 13, 393, 2819, 315, 1403, 50858, 59642, 753, 26670, 1296, 25, 353, 79, 366, 220, 15, 13, 2304, 11, 3146, 79, 366, 220, 15, 13, 1721, 11, 17601, 79, 366, 220, 15, 13, 4119, 26, 2737, 1193, 281, 2819, 430, 14958, 5199, 1306, 26991, 369, 5361, 36595, 1701, 279, 7505, 44811, 6729, 4235, 39, 5059, 7881, 10537, 449, 264, 3641, 39193, 20359, 315, 220, 15, 13, 16, 13, 16666, 25, 22037, 26545, 320, 2366, 18, 570, 59670, 25, 220, 605, 13, 6889, 23, 2754, 17448, 3080, 12, 20063, 12, 16481, 1627, 12303, 59294, 35202, 36792, 1093, 872, 24156, 38495, 330, 1687, 649, 23645, 279, 5820, 315, 3927, 35202, 1633, 30820, 1359, 2795, 432, 3328, 13, 330, 1687, 1766, 704, 304, 279, 1920, 430, 1521, 304, 5554, 4042, 35202, 36792, 22009, 505, 832, 2500, 17223, 304, 279, 1890, 1648, 439, 872, 24156, 38495, 13, 5751, 4200, 1860, 44958, 2489, 279, 20207, 5178, 323, 13010, 3115, 315, 872, 24156, 24291, 1157, 1210, 58603, 11, 279, 330, 3306, 1223, 1, 35202, 304, 2225, 279, 12966, 323, 279, 4211, 1051, 810, 22183, 11, 602, 1770, 2637, 304, 892, 449, 832, 1023, 13, 1115, 7191, 14453, 88, 5535, 30828, 46121, 304, 279, 66746, 326, 15784, 311, 3412, 1022, 389, 11429, 5129, 1109, 35202, 430, 1051, 2753, 1664, 47672, 13, 578, 4211, 10675, 1268, 11293, 37015, 38793, 3135, 304, 279, 2038, 2631, 369, 5597, 28846, 14188, 1694, 2561, 994, 4460, 6463, 9967, 304, 3318, 5044, 13, 76685, 6029, 5097, 892, 17223, 11767, 311, 4495, 11429, 9240, 287, 21395, 16003, 52460, 43739, 8710, 430, 29493, 2092, 3078, 1047, 5190, 5578, 16003, 31357, 11, 477, 37015, 14453, 88, 11, 1990, 872, 8271, 13918, 13, 763, 35649, 8271, 47590, 315, 279, 220, 13655, 13324, 11, 279, 12074, 1436, 8417, 430, 35202, 449, 11293, 16003, 31357, 16280, 330, 44396, 311, 31342, 1, 994, 3339, 11429, 11, 4856, 1109, 8748, 3156, 42830, 8271, 13918, 1436, 4686, 279, 8863, 7504, 4460, 311, 11886, 279, 3575, 13, 52878, 1051, 4691, 311, 10765, 20406, 5718, 304, 264, 4101, 315, 12912, 13, 4314, 5718, 6244, 15098, 6485, 449, 1855, 3465, 323, 8617, 810, 5107, 311, 75277, 13, 763, 18254, 3878, 11, 459, 4228, 3465, 1053, 6824, 315, 6288, 73588, 520, 264, 2579, 3177, 11, 1418, 264, 2653, 3465, 1053, 1397, 1749, 2740, 3318, 704, 279, 1888, 6149, 389, 264, 5754, 2472, 13, 763, 279, 1646, 11, 264, 779, 19434, 13946, 2442, 731, 23148, 10937, 13980, 1990, 2204, 30828, 5315, 6532, 304, 264, 5597, 11, 449, 279, 30828, 5315, 369, 902, 1070, 374, 16643, 6029, 61129, 13, 14968, 304, 279, 1162, 315, 6485, 11429, 11, 1778, 6029, 374, 3629, 539, 2867, 3403, 369, 4062, 5597, 28846, 11, 16280, 25957, 279, 30828, 5315, 311, 7940, 311, 31342, 13, 330, 50, 69029, 11, 602, 1770, 2637, 279, 18488, 315, 16003, 14488, 304, 279, 8271, 11, 88687, 279, 6012, 315, 3318, 5044, 323, 8617, 279, 5845, 311, 364, 408, 554, 6, 44387, 18852, 2085, 264, 5597, 1359, 15100, 8096, 5124, 404, 1215, 11, 3063, 3229, 315, 279, 4007, 323, 264, 28568, 304, 432, 3328, 596, 10278, 13, 330, 644, 810, 17436, 9256, 11, 499, 617, 311, 3637, 3766, 5208, 304, 3318, 5044, 1418, 499, 13488, 1023, 6425, 13006, 323, 1243, 32172, 1521, 1139, 1855, 1023, 13, 1115, 23738, 315, 6029, 369, 264, 4040, 6425, 1253, 7170, 5097, 5129, 11, 719, 433, 1101, 11767, 311, 2731, 3135, 13, 1226, 1051, 3025, 311, 1005, 279, 1646, 311, 1501, 1268, 3521, 7709, 3502, 60073, 8335, 520, 279, 3728, 2237, 315, 279, 4459, 8271, 4009, 22223, 5597, 28846, 323, 3318, 5044, 520, 279, 810, 16109, 1299, 2237, 315, 3927, 30828, 5315, 1210, 7531, 826, 527, 7185, 369, 6514, 9293, 432, 3328, 374, 18949, 430, 279, 3135, 13468, 304, 279, 6500, 6108, 330, 54160, 1860, 44958, 1, 2489, 279, 3135, 3970, 304, 330, 8110, 1, 9498, 15223, 13, 4740, 682, 11, 1077, 1925, 2802, 374, 304, 10695, 6978, 11754, 555, 18247, 451, 7642, 1413, 19338, 1093, 52857, 323, 62145, 596, 8624, 13, 330, 791, 19576, 5557, 1511, 304, 420, 4007, 706, 1903, 5199, 37387, 11, 323, 649, 387, 1511, 311, 7417, 35649, 304, 5554, 4042, 9293, 315, 34933, 323, 5623, 39455, 439, 1664, 439, 37471, 8271, 41959, 13, 1789, 3187, 11, 264, 28378, 649, 2736, 1005, 264, 6500, 19576, 311, 8720, 902, 21623, 477, 5623, 2643, 990, 1888, 369, 264, 4040, 8893, 323, 1053, 617, 279, 2478, 478, 3185, 6372, 1210, 220, 128257, 198 ]

2,771

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Schizophrenia is a common disease with a complex aetiology, probably involving multiple and heterogeneous genetic factors. Here, by analysing the exome sequences of 2,536 schizophrenia cases and 2,543 controls, we demonstrate a polygenic burden primarily arising from rare (less than 1 in 10,000), disruptive mutations distributed across many genes. Particularly enriched gene sets include the voltage-gated calcium ion channel and the signalling complex formed by the activity-regulated cytoskeleton-associated scaffold protein (ARC) of the postsynaptic density, sets previously implicated by genome-wide association and copy-number variation studies. Similar to reports in autism, targets of the fragile X mental retardation protein (FMRP, product of FMR1 ) are enriched for case mutations. No individual gene-based test achieves significance after correction for multiple testing and we do not detect any alleles of moderately low frequency (approximately 0.5 to 1 per cent) and moderately large effect. Taken together, these data suggest that population-based exome sequencing can discover risk alleles and complements established gene-mapping paradigms in neuropsychiatric disease. Main Genetic studies of schizophrenia (MIM 181500) have demonstrated a substantial heritability 1 , 2 that reflects common and rare alleles at many loci. Genome-wide association studies (GWAS) continue to uncover common single nucleotide polymorphisms (SNPs) at novel loci 3 . Rare or de novo genic deletions and duplications (copy-number variants (CNVs)) have been firmly established, including risk variants at 22q11.2, 15q13.3 and 1q21.1 (refs 4 , 5 ). One notable outcome of these large-scale, genome-wide investigations is the degree of polygenicity, consistent with thousands of genes and non-coding loci harbouring risk alleles 3 , 6 , 7 , 8 , 9 . Nonetheless, progress has been made in implicating biological systems and quantifying shared genetics among related psychiatric disorders (for example, refs 10 , 11 ), such as identifying common variants in calcium ion channel genes affecting schizophrenia and bipolar disorder 12 and de novo CNVs affecting genes encoding members of the postsynaptic density (PSD) proteome 13 , in particular members of the neuronal ARC protein and N -methyl- d -aspartate receptor (NMDAR) postsynaptic signalling complexes. Here we apply massively parallel short-read sequencing to assay a substantial portion of variation that previously was essentially invisible: rare coding point mutations (single nucleotide variants (SNVs)) and small insertions and deletions (indels). Although previous schizophrenia studies have applied sequencing, the results have been inconclusive, reflecting limited sample sizes or a focus on small numbers of candidate genes 14 , 15 , 16 , 17 . Exome-sequencing studies of de novo mutations published to date have neither demonstrated an increased rate in schizophrenia, nor conclusively implicated individual genes 18 , 19 , although some data suggest a link with particular classes of gene, such as those with higher brain expression in early fetal life 19 . De novo studies in intellectual disability 20 , 21 and autism 22 , 23 , 24 , 25 have, however, made considerable progress in identifying large-effect alleles and the underlying gene networks. In this study, we sought to identify the alleles, genes or gene networks that harbour rare coding variants of moderate or large effect on risk for schizophrenia by exome sequencing 5,079 individuals, selected from a Swedish sample of more than 11,000 individuals. Previous analyses of the full sample ( Supplementary Information section 1) have demonstrated an enriched burden of rare CNVs and a polygenic common variant component 3 . We generated high-coverage exome sequence to ensure sufficient sensitivity to detect and genotype alleles observed in only one heterozygous individual (singletons, implying an allele frequency of ∼ 1 in 10,000, although the true population frequency will typically be rarer). The high baseline rate of rare, neutral mutations makes it difficult to detect rare alleles that increase risk for common diseases 26 . Although power can be increased by jointly testing groups of variants in a gene 27 , association testing across all genes is likely to be under-powered at current sample sizes. Indeed, a recent application of population-based exome sequencing in autism did not identify genes 28 , despite moderately large sample size and the success of the de novo paradigm. Furthermore, many confirmed results from candidate-gene sequencing studies of nonpsychiatric disease still fall short of exome-wide significance 29 . We therefore adopted a top-down strategy in which we studied a large set of genes with a higher likelihood of having a role in schizophrenia, on the basis of existing genetic evidence ( Supplementary Information section 7). We focused on ∼ 2,500 genes implicated by unbiased, large-scale genome-wide screens, including GWAS, CNV and de novo SNV studies, testing for enrichment of rare alleles in cases. To prioritize individual genes, we characterized emerging signals with respect to the genes and frequency and type of mutations. We coordinated analysis with an independent trio exome-sequencing study (Fromer et al. 30 , this issue) and note key points of convergence below. After alignment and variant calling of all samples jointly, we removed 11 subjects with low-quality data along with likely spurious sites and genotypes ( Supplementary Information sections 2 and 3). Per individual, 93% of targeted bases were covered at ≥10-fold (81% at ≥30-fold). The final data set comprised 2,536 cases and 2,543 controls ( Extended Data Table 1a and Extended Data Fig. 1a ). Cases and controls had similar technical sequencing metrics, including total coverage, proportion of deeply covered targets, and overall proportion of non-reference alleles ( Extended Data Table 1b ). We observed 635,944 coding and splice-site passing variants of which 56% were singletons. Using Sanger sequencing and Exome Chip data on these samples, we determined high specificity and sensitivity for singletons ( Supplementary Information section 3). We annotated variants with respect to RefSeq and combined five in silico algorithms to predict missense deleteriousness ( Extended Data Table 1c and Supplementary Information section 4). As expected, allelic types more likely to affect protein function showed greater constraint: 69% of nonsense variants were singletons, compared to 58% of missense and 51% of silent variants. Primary analyses tested (1) disruptive variants (nonsense, essential splice site and frameshifts, n", "role": "user" }, { "content": "Researchers from the Broad Institute and several partnering institutions have taken a closer look at the human genome to learn more about the genetic underpinnings of schizophrenia. In two studies published this week in Nature, scientists analyzed the exomes, or protein-coding regions, of people with schizophrenia and their healthy counterparts, pinpointing the sites of mutations and identifying patterns that reveal clues about the biology underlying the disorder. One study compared gene sequences from 2,500 people with schizophrenia to 2,500 healthy individuals from the same population. The second study looked for new mutations that might have occurred in protein coding genes by examining gene sequences from more than 600 schizophrenia trios (individuals with the disorder and their unaffected mothers and fathers). Both studies yielded further evidence that the disorder arises from the combined effects of many genes – a condition known as \"polygenicity.\" The studies also suggest that genetic alterations tended to cluster in a few networks of functionally-related genes. Schizophrenia, a psychiatric disorder often characterized by hallucinations, paranoia, and a breakdown of thought processes, is known to be highly heritable. It affects roughly 1 percent of all adults, and individuals with immediate relatives who suffer from the disorder are at approximately ten times greater risk. While this high rate of heritability has long been recognized, previous genetic studies have struggled to identify specific genes that cause schizophrenia. The two current studies, which are the largest of their kind to date, looked for mutations that were effectively invisible in previous studies: they detected changes at the scale of single nucleotides – substitutions, insertions, or deletions of individual bases or \"letters\" in the genetic code. \"Despite the considerable sample sizes, no individual gene could be unambiguously implicated in either study. Taken as a group, however, genes involved in neural function and development showed greater rates of disruptive mutations in patients,\" explained Broad senior associate member Shaun Purcell, who played key roles in both studies. \"That finding is sobering but also revealing: it suggests that many genes underlie risk for schizophrenia and so any two patients are unlikely to share the same profile of risk genes.\" Purcell, who is also a research scientist at Massachusetts General Hospital (MGH) and an associate professor of psychiatry at Mount Sinai's Icahn School of Medicine, served as first author of one of the papers (Purcell et al.), which compared the exomes of individuals with schizophrenia with those from healthy individuals from the same population in Sweden. The researchers involved in the work hailed from nine institutions, including the Broad, Mount Sinai, and MGH. The second paper (Fromer et al.) reported similar findings. That study, which was conducted by a multi-institutional collaboration that included the Broad Institute's Stanley Center for Psychiatric Research, Mount Sinai, Cardiff University, the Wellcome Trust Sanger Institute, and six other research institutions, looked for de novo mutations – alterations in an offspring's genome that do not exist in the genomes of the parents, and therefore cannot be attributed to heredity. Such mutations account for roughly 5 percent of schizophrenia cases. Both studies found that mutations were distributed across many genes, and the research teams discovered similar patterns in the distribution of mutations across gene networks. Many of the genes that bore mutations shared common functions: they tended to be part of gene networks that govern synaptic function, including the voltage-gated calcium ion channel, which is involved in signaling between cells in the brain, and the cytoskeletal (ARC) protein complex, which plays a role in synaptic plasticity, a function essential to learning and memory. \"From a scientific standpoint, it's reassuring to see different methods of studying the genetics of schizophrenia converge on the same sets of genes. These varied approaches are pointing toward the same underlying biology, which can be followed up in future research,\" said Steven McCarroll, who was an author on both papers. McCarroll is director of genetics for the Broad's Stanley Center for Psychiatric Research and a professor in genetics at Harvard Medical School. The analysis of de novo mutations also revealed significant overlap between those found in schizophrenia and de novo mutations previously linked to autism and intellectual disability, a finding that may influence the approach researchers take in follow-up studies. The authors argue that both papers demonstrate that genome sequencing will continue to be a powerful tool in the study of schizophrenia, though many more samples will need to be sequenced before the genetics of this complex disorder can be fully understood. \"Few facts have been firmly established about the molecular or cellular causes of schizophrenia, and that's because many traditional scientific approaches can't be used to study the disorder: you can't grow it in a dish, and there aren't very good animal models for it,\" McCarroll explained. \"We think that genomes are the path out of the darkness, and that these studies and others like them will ultimately provide the molecular clues we will need to map out the pathophysiology of the disorder.\" Stanley Center director Steven Hyman and Ed Scolnick, the Stanley Center's chief scientist, thanked the institutions that collaborated on the studies. \"The genetic analysis of schizophrenia is yielding remarkably promising results because scientists around the world have worked collaboratively for years to recruit and study the large number of patients and comparison subjects needed to pick out rare genetic variants associated schizophrenia against the staggeringly complex background genetic variation that characterizes humanity. Phrases like 'finding needles in haystacks' do not begin to do justice to this shared global effort,\" Hyman said. Scolnick emphasized that this collaboration is accelerating research that will ultimately benefit patients. \"The exome sequencing data in these papers together with ongoing whole-genome association studies in patients with schizophrenia are helping to unravel the pathogenesis of this devastating illness,\" Scolnick said. \"This work is building a roadmap which will inexorably lead to better treatments for patients and families.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Schizophrenia is a common disease with a complex aetiology, probably involving multiple and heterogeneous genetic factors. Here, by analysing the exome sequences of 2,536 schizophrenia cases and 2,543 controls, we demonstrate a polygenic burden primarily arising from rare (less than 1 in 10,000), disruptive mutations distributed across many genes. Particularly enriched gene sets include the voltage-gated calcium ion channel and the signalling complex formed by the activity-regulated cytoskeleton-associated scaffold protein (ARC) of the postsynaptic density, sets previously implicated by genome-wide association and copy-number variation studies. Similar to reports in autism, targets of the fragile X mental retardation protein (FMRP, product of FMR1 ) are enriched for case mutations. No individual gene-based test achieves significance after correction for multiple testing and we do not detect any alleles of moderately low frequency (approximately 0.5 to 1 per cent) and moderately large effect. Taken together, these data suggest that population-based exome sequencing can discover risk alleles and complements established gene-mapping paradigms in neuropsychiatric disease. Main Genetic studies of schizophrenia (MIM 181500) have demonstrated a substantial heritability 1 , 2 that reflects common and rare alleles at many loci. Genome-wide association studies (GWAS) continue to uncover common single nucleotide polymorphisms (SNPs) at novel loci 3 . Rare or de novo genic deletions and duplications (copy-number variants (CNVs)) have been firmly established, including risk variants at 22q11.2, 15q13.3 and 1q21.1 (refs 4 , 5 ). One notable outcome of these large-scale, genome-wide investigations is the degree of polygenicity, consistent with thousands of genes and non-coding loci harbouring risk alleles 3 , 6 , 7 , 8 , 9 . Nonetheless, progress has been made in implicating biological systems and quantifying shared genetics among related psychiatric disorders (for example, refs 10 , 11 ), such as identifying common variants in calcium ion channel genes affecting schizophrenia and bipolar disorder 12 and de novo CNVs affecting genes encoding members of the postsynaptic density (PSD) proteome 13 , in particular members of the neuronal ARC protein and N -methyl- d -aspartate receptor (NMDAR) postsynaptic signalling complexes. Here we apply massively parallel short-read sequencing to assay a substantial portion of variation that previously was essentially invisible: rare coding point mutations (single nucleotide variants (SNVs)) and small insertions and deletions (indels). Although previous schizophrenia studies have applied sequencing, the results have been inconclusive, reflecting limited sample sizes or a focus on small numbers of candidate genes 14 , 15 , 16 , 17 . Exome-sequencing studies of de novo mutations published to date have neither demonstrated an increased rate in schizophrenia, nor conclusively implicated individual genes 18 , 19 , although some data suggest a link with particular classes of gene, such as those with higher brain expression in early fetal life 19 . De novo studies in intellectual disability 20 , 21 and autism 22 , 23 , 24 , 25 have, however, made considerable progress in identifying large-effect alleles and the underlying gene networks. In this study, we sought to identify the alleles, genes or gene networks that harbour rare coding variants of moderate or large effect on risk for schizophrenia by exome sequencing 5,079 individuals, selected from a Swedish sample of more than 11,000 individuals. Previous analyses of the full sample ( Supplementary Information section 1) have demonstrated an enriched burden of rare CNVs and a polygenic common variant component 3 . We generated high-coverage exome sequence to ensure sufficient sensitivity to detect and genotype alleles observed in only one heterozygous individual (singletons, implying an allele frequency of ∼ 1 in 10,000, although the true population frequency will typically be rarer). The high baseline rate of rare, neutral mutations makes it difficult to detect rare alleles that increase risk for common diseases 26 . Although power can be increased by jointly testing groups of variants in a gene 27 , association testing across all genes is likely to be under-powered at current sample sizes. Indeed, a recent application of population-based exome sequencing in autism did not identify genes 28 , despite moderately large sample size and the success of the de novo paradigm. Furthermore, many confirmed results from candidate-gene sequencing studies of nonpsychiatric disease still fall short of exome-wide significance 29 . We therefore adopted a top-down strategy in which we studied a large set of genes with a higher likelihood of having a role in schizophrenia, on the basis of existing genetic evidence ( Supplementary Information section 7). We focused on ∼ 2,500 genes implicated by unbiased, large-scale genome-wide screens, including GWAS, CNV and de novo SNV studies, testing for enrichment of rare alleles in cases. To prioritize individual genes, we characterized emerging signals with respect to the genes and frequency and type of mutations. We coordinated analysis with an independent trio exome-sequencing study (Fromer et al. 30 , this issue) and note key points of convergence below. After alignment and variant calling of all samples jointly, we removed 11 subjects with low-quality data along with likely spurious sites and genotypes ( Supplementary Information sections 2 and 3). Per individual, 93% of targeted bases were covered at ≥10-fold (81% at ≥30-fold). The final data set comprised 2,536 cases and 2,543 controls ( Extended Data Table 1a and Extended Data Fig. 1a ). Cases and controls had similar technical sequencing metrics, including total coverage, proportion of deeply covered targets, and overall proportion of non-reference alleles ( Extended Data Table 1b ). We observed 635,944 coding and splice-site passing variants of which 56% were singletons. Using Sanger sequencing and Exome Chip data on these samples, we determined high specificity and sensitivity for singletons ( Supplementary Information section 3). We annotated variants with respect to RefSeq and combined five in silico algorithms to predict missense deleteriousness ( Extended Data Table 1c and Supplementary Information section 4). As expected, allelic types more likely to affect protein function showed greater constraint: 69% of nonsense variants were singletons, compared to 58% of missense and 51% of silent variants. Primary analyses tested (1) disruptive variants (nonsense, essential splice site and frameshifts, n<|im_end|> <|im_start|>assistant Researchers from the Broad Institute and several partnering institutions have taken a closer look at the human genome to learn more about the genetic underpinnings of schizophrenia. In two studies published this week in Nature, scientists analyzed the exomes, or protein-coding regions, of people with schizophrenia and their healthy counterparts, pinpointing the sites of mutations and identifying patterns that reveal clues about the biology underlying the disorder. One study compared gene sequences from 2,500 people with schizophrenia to 2,500 healthy individuals from the same population. The second study looked for new mutations that might have occurred in protein coding genes by examining gene sequences from more than 600 schizophrenia trios (individuals with the disorder and their unaffected mothers and fathers). Both studies yielded further evidence that the disorder arises from the combined effects of many genes – a condition known as "polygenicity." The studies also suggest that genetic alterations tended to cluster in a few networks of functionally-related genes. Schizophrenia, a psychiatric disorder often characterized by hallucinations, paranoia, and a breakdown of thought processes, is known to be highly heritable. It affects roughly 1 percent of all adults, and individuals with immediate relatives who suffer from the disorder are at approximately ten times greater risk. While this high rate of heritability has long been recognized, previous genetic studies have struggled to identify specific genes that cause schizophrenia. The two current studies, which are the largest of their kind to date, looked for mutations that were effectively invisible in previous studies: they detected changes at the scale of single nucleotides – substitutions, insertions, or deletions of individual bases or "letters" in the genetic code. "Despite the considerable sample sizes, no individual gene could be unambiguously implicated in either study. Taken as a group, however, genes involved in neural function and development showed greater rates of disruptive mutations in patients," explained Broad senior associate member Shaun Purcell, who played key roles in both studies. "That finding is sobering but also revealing: it suggests that many genes underlie risk for schizophrenia and so any two patients are unlikely to share the same profile of risk genes." Purcell, who is also a research scientist at Massachusetts General Hospital (MGH) and an associate professor of psychiatry at Mount Sinai's Icahn School of Medicine, served as first author of one of the papers (Purcell et al.), which compared the exomes of individuals with schizophrenia with those from healthy individuals from the same population in Sweden. The researchers involved in the work hailed from nine institutions, including the Broad, Mount Sinai, and MGH. The second paper (Fromer et al.) reported similar findings. That study, which was conducted by a multi-institutional collaboration that included the Broad Institute's Stanley Center for Psychiatric Research, Mount Sinai, Cardiff University, the Wellcome Trust Sanger Institute, and six other research institutions, looked for de novo mutations – alterations in an offspring's genome that do not exist in the genomes of the parents, and therefore cannot be attributed to heredity. Such mutations account for roughly 5 percent of schizophrenia cases. Both studies found that mutations were distributed across many genes, and the research teams discovered similar patterns in the distribution of mutations across gene networks. Many of the genes that bore mutations shared common functions: they tended to be part of gene networks that govern synaptic function, including the voltage-gated calcium ion channel, which is involved in signaling between cells in the brain, and the cytoskeletal (ARC) protein complex, which plays a role in synaptic plasticity, a function essential to learning and memory. "From a scientific standpoint, it's reassuring to see different methods of studying the genetics of schizophrenia converge on the same sets of genes. These varied approaches are pointing toward the same underlying biology, which can be followed up in future research," said Steven McCarroll, who was an author on both papers. McCarroll is director of genetics for the Broad's Stanley Center for Psychiatric Research and a professor in genetics at Harvard Medical School. The analysis of de novo mutations also revealed significant overlap between those found in schizophrenia and de novo mutations previously linked to autism and intellectual disability, a finding that may influence the approach researchers take in follow-up studies. The authors argue that both papers demonstrate that genome sequencing will continue to be a powerful tool in the study of schizophrenia, though many more samples will need to be sequenced before the genetics of this complex disorder can be fully understood. "Few facts have been firmly established about the molecular or cellular causes of schizophrenia, and that's because many traditional scientific approaches can't be used to study the disorder: you can't grow it in a dish, and there aren't very good animal models for it," McCarroll explained. "We think that genomes are the path out of the darkness, and that these studies and others like them will ultimately provide the molecular clues we will need to map out the pathophysiology of the disorder." Stanley Center director Steven Hyman and Ed Scolnick, the Stanley Center's chief scientist, thanked the institutions that collaborated on the studies. "The genetic analysis of schizophrenia is yielding remarkably promising results because scientists around the world have worked collaboratively for years to recruit and study the large number of patients and comparison subjects needed to pick out rare genetic variants associated schizophrenia against the staggeringly complex background genetic variation that characterizes humanity. Phrases like 'finding needles in haystacks' do not begin to do justice to this shared global effort," Hyman said. Scolnick emphasized that this collaboration is accelerating research that will ultimately benefit patients. "The exome sequencing data in these papers together with ongoing whole-genome association studies in patients with schizophrenia are helping to unravel the pathogenesis of this devastating illness," Scolnick said. "This work is building a roadmap which will inexorably lead to better treatments for patients and families." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 5124, 46412, 689, 374, 264, 4279, 8624, 449, 264, 6485, 264, 295, 31226, 11, 4762, 16239, 5361, 323, 98882, 19465, 9547, 13, 5810, 11, 555, 22209, 287, 279, 506, 638, 24630, 315, 220, 17, 11, 21600, 58533, 5157, 323, 220, 17, 11, 19642, 11835, 11, 584, 20461, 264, 10062, 89305, 23104, 15871, 40986, 505, 9024, 320, 1752, 1109, 220, 16, 304, 220, 605, 11, 931, 705, 62642, 34684, 4332, 4028, 1690, 21389, 13, 97485, 69671, 15207, 7437, 2997, 279, 22465, 2427, 660, 35719, 28772, 5613, 323, 279, 91977, 6485, 14454, 555, 279, 5820, 33263, 7913, 9693, 43681, 28193, 75968, 85552, 13128, 320, 47572, 8, 315, 279, 8158, 1910, 53274, 17915, 11, 7437, 8767, 69702, 555, 33869, 25480, 15360, 323, 3048, 26939, 23851, 7978, 13, 22196, 311, 6821, 304, 38281, 11, 11811, 315, 279, 45350, 1630, 10723, 77072, 367, 13128, 320, 37, 18953, 47, 11, 2027, 315, 435, 18953, 16, 883, 527, 69671, 369, 1162, 34684, 13, 2360, 3927, 15207, 6108, 1296, 83691, 26431, 1306, 27358, 369, 5361, 7649, 323, 584, 656, 539, 11388, 904, 98260, 315, 70351, 3428, 11900, 320, 97836, 220, 15, 13, 20, 311, 220, 16, 824, 2960, 8, 323, 70351, 3544, 2515, 13, 57074, 3871, 11, 1521, 828, 4284, 430, 7187, 6108, 506, 638, 62119, 649, 7142, 5326, 98260, 323, 1946, 1392, 9749, 15207, 1474, 3713, 28417, 343, 1026, 304, 21143, 98438, 23336, 8624, 13, 4802, 75226, 7978, 315, 58533, 320, 44, 1829, 220, 10562, 2636, 8, 617, 21091, 264, 12190, 1077, 275, 2968, 220, 16, 1174, 220, 17, 430, 27053, 4279, 323, 9024, 98260, 520, 1690, 1353, 72, 13, 82917, 25480, 15360, 7978, 320, 63665, 1950, 8, 3136, 311, 45063, 4279, 3254, 31484, 69044, 46033, 16751, 13978, 320, 19503, 21051, 8, 520, 11775, 1353, 72, 220, 18, 662, 36059, 477, 409, 39423, 4173, 292, 19825, 919, 323, 27444, 811, 320, 8728, 26939, 27103, 320, 29768, 52837, 595, 617, 1027, 32620, 9749, 11, 2737, 5326, 27103, 520, 220, 1313, 80, 806, 13, 17, 11, 220, 868, 80, 1032, 13, 18, 323, 220, 16, 80, 1691, 13, 16, 320, 16541, 220, 19, 1174, 220, 20, 7609, 3861, 28289, 15632, 315, 1521, 3544, 13230, 11, 33869, 25480, 26969, 374, 279, 8547, 315, 10062, 4469, 62791, 11, 13263, 449, 9214, 315, 21389, 323, 2536, 1824, 3785, 1353, 72, 75742, 287, 5326, 98260, 220, 18, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 1174, 220, 24, 662, 56733, 11, 5208, 706, 1027, 1903, 304, 92195, 1113, 24156, 6067, 323, 10484, 7922, 6222, 56104, 4315, 5552, 47657, 24673, 320, 2000, 3187, 11, 44243, 220, 605, 1174, 220, 806, 7026, 1778, 439, 25607, 4279, 27103, 304, 35719, 28772, 5613, 21389, 28987, 58533, 323, 65919, 19823, 220, 717, 323, 409, 39423, 25914, 52837, 28987, 21389, 11418, 3697, 315, 279, 8158, 1910, 53274, 17915, 320, 5119, 35, 8, 5541, 638, 220, 1032, 1174, 304, 4040, 3697, 315, 279, 79402, 71444, 13128, 323, 452, 482, 76, 42972, 12, 294, 482, 300, 4581, 349, 35268, 320, 45, 6204, 946, 8, 8158, 1910, 53274, 91977, 69125, 13, 5810, 584, 3881, 64807, 15638, 2875, 29906, 62119, 311, 65033, 264, 12190, 13651, 315, 23851, 430, 8767, 574, 16168, 30547, 25, 9024, 11058, 1486, 34684, 320, 15698, 31484, 69044, 27103, 320, 19503, 52837, 595, 323, 2678, 5774, 919, 323, 19825, 919, 320, 485, 2053, 570, 10541, 3766, 58533, 7978, 617, 9435, 62119, 11, 279, 3135, 617, 1027, 28093, 8500, 11, 42852, 7347, 6205, 12562, 477, 264, 5357, 389, 2678, 5219, 315, 9322, 21389, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 662, 1398, 638, 12, 6741, 11627, 7978, 315, 409, 39423, 34684, 4756, 311, 2457, 617, 14188, 21091, 459, 7319, 4478, 304, 58533, 11, 6463, 84082, 3210, 69702, 3927, 21389, 220, 972, 1174, 220, 777, 1174, 8051, 1063, 828, 4284, 264, 2723, 449, 4040, 6989, 315, 15207, 11, 1778, 439, 1884, 449, 5190, 8271, 7645, 304, 4216, 63746, 2324, 220, 777, 662, 1611, 39423, 7978, 304, 20207, 28353, 220, 508, 1174, 220, 1691, 323, 38281, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 617, 11, 4869, 11, 1903, 24779, 5208, 304, 25607, 3544, 23937, 98260, 323, 279, 16940, 15207, 14488, 13, 763, 420, 4007, 11, 584, 16495, 311, 10765, 279, 98260, 11, 21389, 477, 15207, 14488, 430, 75742, 9024, 11058, 27103, 315, 24070, 477, 3544, 2515, 389, 5326, 369, 58533, 555, 506, 638, 62119, 220, 20, 11, 27407, 7931, 11, 4183, 505, 264, 31209, 6205, 315, 810, 1109, 220, 806, 11, 931, 7931, 13, 30013, 29060, 315, 279, 2539, 6205, 320, 99371, 8245, 3857, 220, 16, 8, 617, 21091, 459, 69671, 23104, 315, 9024, 25914, 52837, 323, 264, 10062, 89305, 4279, 11678, 3777, 220, 18, 662, 1226, 8066, 1579, 12, 55350, 506, 638, 8668, 311, 6106, 14343, 27541, 311, 11388, 323, 80285, 98260, 13468, 304, 1193, 832, 30548, 76523, 70, 788, 3927, 320, 15698, 35511, 11, 73967, 459, 70510, 11900, 315, 12264, 120, 220, 16, 304, 220, 605, 11, 931, 11, 8051, 279, 837, 7187, 11900, 690, 11383, 387, 436, 61570, 570, 578, 1579, 26954, 4478, 315, 9024, 11, 21277, 34684, 3727, 433, 5107, 311, 11388, 9024, 98260, 430, 5376, 5326, 369, 4279, 19338, 220, 1627, 662, 10541, 2410, 649, 387, 7319, 555, 53258, 7649, 5315, 315, 27103, 304, 264, 15207, 220, 1544, 1174, 15360, 7649, 4028, 682, 21389, 374, 4461, 311, 387, 1234, 41503, 520, 1510, 6205, 12562, 13, 23150, 11, 264, 3293, 3851, 315, 7187, 6108, 506, 638, 62119, 304, 38281, 1550, 539, 10765, 21389, 220, 1591, 1174, 8994, 70351, 3544, 6205, 1404, 323, 279, 2450, 315, 279, 409, 39423, 49340, 13, 24296, 11, 1690, 11007, 3135, 505, 9322, 2427, 1994, 62119, 7978, 315, 2536, 92109, 23336, 8624, 2103, 4498, 2875, 315, 506, 638, 25480, 26431, 220, 1682, 662, 1226, 9093, 18306, 264, 1948, 15220, 8446, 304, 902, 584, 20041, 264, 3544, 743, 315, 21389, 449, 264, 5190, 29736, 315, 3515, 264, 3560, 304, 58533, 11, 389, 279, 8197, 315, 6484, 19465, 6029, 320, 99371, 8245, 3857, 220, 22, 570, 1226, 10968, 389, 12264, 120, 220, 17, 11, 2636, 21389, 69702, 555, 74315, 11, 3544, 13230, 33869, 25480, 15670, 11, 2737, 42353, 1950, 11, 25914, 53, 323, 409, 39423, 18407, 53, 7978, 11, 7649, 369, 70272, 315, 9024, 98260, 304, 5157, 13, 2057, 63652, 3927, 21389, 11, 584, 32971, 24084, 17738, 449, 5201, 311, 279, 21389, 323, 11900, 323, 955, 315, 34684, 13, 1226, 47672, 6492, 449, 459, 9678, 35062, 506, 638, 12, 6741, 11627, 4007, 320, 3915, 261, 1880, 453, 13, 220, 966, 1174, 420, 4360, 8, 323, 5296, 1401, 3585, 315, 56541, 3770, 13, 4740, 17632, 323, 11678, 8260, 315, 682, 10688, 53258, 11, 584, 7108, 220, 806, 15223, 449, 3428, 22867, 828, 3235, 449, 4461, 993, 28626, 6732, 323, 4173, 22583, 320, 99371, 8245, 14491, 220, 17, 323, 220, 18, 570, 3700, 3927, 11, 220, 6365, 4, 315, 17550, 23963, 1051, 9960, 520, 63247, 605, 24325, 320, 5932, 4, 520, 63247, 966, 24325, 570, 578, 1620, 828, 743, 40056, 220, 17, 11, 21600, 5157, 323, 220, 17, 11, 19642, 11835, 320, 41665, 2956, 6771, 220, 16, 64, 323, 41665, 2956, 23966, 13, 220, 16, 64, 7609, 47124, 323, 11835, 1047, 4528, 11156, 62119, 17150, 11, 2737, 2860, 10401, 11, 21801, 315, 17693, 9960, 11811, 11, 323, 8244, 21801, 315, 2536, 73723, 98260, 320, 41665, 2956, 6771, 220, 16, 65, 7609, 1226, 13468, 220, 22276, 11, 25687, 11058, 323, 89390, 29654, 12579, 27103, 315, 902, 220, 3487, 4, 1051, 3254, 35511, 13, 12362, 328, 4091, 62119, 323, 1398, 638, 32013, 828, 389, 1521, 10688, 11, 584, 11075, 1579, 76041, 323, 27541, 369, 3254, 35511, 320, 99371, 8245, 3857, 220, 18, 570, 1226, 63951, 27103, 449, 5201, 311, 8718, 20794, 323, 11093, 4330, 304, 5554, 4042, 26249, 311, 7168, 3194, 1137, 60393, 466, 1245, 2136, 320, 41665, 2956, 6771, 220, 16, 66, 323, 99371, 8245, 3857, 220, 19, 570, 1666, 3685, 11, 12584, 416, 4595, 810, 4461, 311, 7958, 13128, 734, 8710, 7191, 22295, 25, 220, 3076, 4, 315, 41902, 27103, 1051, 3254, 35511, 11, 7863, 311, 220, 2970, 4, 315, 3194, 1137, 323, 220, 3971, 4, 315, 21737, 27103, 13, 26150, 29060, 12793, 320, 16, 8, 62642, 27103, 320, 77, 98833, 11, 7718, 89390, 2816, 323, 14418, 48933, 82, 11, 308, 128257, 198, 128256, 78191, 198, 60210, 505, 279, 16273, 10181, 323, 3892, 70220, 14673, 617, 4529, 264, 12401, 1427, 520, 279, 3823, 33869, 311, 4048, 810, 922, 279, 19465, 1234, 79, 6258, 826, 315, 58533, 13, 763, 1403, 7978, 4756, 420, 2046, 304, 22037, 11, 14248, 30239, 279, 506, 20969, 11, 477, 13128, 1824, 3785, 13918, 11, 315, 1274, 449, 58533, 323, 872, 9498, 38495, 11, 67638, 287, 279, 6732, 315, 34684, 323, 25607, 12912, 430, 16805, 43775, 922, 279, 34458, 16940, 279, 19823, 13, 3861, 4007, 7863, 15207, 24630, 505, 220, 17, 11, 2636, 1274, 449, 58533, 311, 220, 17, 11, 2636, 9498, 7931, 505, 279, 1890, 7187, 13, 578, 2132, 4007, 7111, 369, 502, 34684, 430, 2643, 617, 10222, 304, 13128, 11058, 21389, 555, 38936, 15207, 24630, 505, 810, 1109, 220, 5067, 58533, 2463, 437, 320, 55977, 82, 449, 279, 19823, 323, 872, 78622, 27698, 323, 40317, 570, 11995, 7978, 58487, 4726, 6029, 430, 279, 19823, 48282, 505, 279, 11093, 6372, 315, 1690, 21389, 1389, 264, 3044, 3967, 439, 330, 34535, 4469, 62791, 1210, 578, 7978, 1101, 4284, 430, 19465, 61086, 49890, 311, 10879, 304, 264, 2478, 14488, 315, 734, 750, 14228, 21389, 13, 5124, 46412, 689, 11, 264, 47657, 19823, 3629, 32971, 555, 59123, 12922, 11, 83544, 11, 323, 264, 31085, 315, 3463, 11618, 11, 374, 3967, 311, 387, 7701, 1077, 15729, 13, 1102, 22223, 17715, 220, 16, 3346, 315, 682, 12884, 11, 323, 7931, 449, 14247, 29658, 889, 7831, 505, 279, 19823, 527, 520, 13489, 5899, 3115, 7191, 5326, 13, 6104, 420, 1579, 4478, 315, 1077, 275, 2968, 706, 1317, 1027, 15324, 11, 3766, 19465, 7978, 617, 28214, 311, 10765, 3230, 21389, 430, 5353, 58533, 13, 578, 1403, 1510, 7978, 11, 902, 527, 279, 7928, 315, 872, 3169, 311, 2457, 11, 7111, 369, 34684, 430, 1051, 13750, 30547, 304, 3766, 7978, 25, 814, 16914, 4442, 520, 279, 5569, 315, 3254, 31484, 354, 3422, 1389, 94750, 11, 5774, 919, 11, 477, 19825, 919, 315, 3927, 23963, 477, 330, 21731, 1, 304, 279, 19465, 2082, 13, 330, 20397, 279, 24779, 6205, 12562, 11, 912, 3927, 15207, 1436, 387, 653, 3042, 27843, 7162, 69702, 304, 3060, 4007, 13, 57074, 439, 264, 1912, 11, 4869, 11, 21389, 6532, 304, 30828, 734, 323, 4500, 8710, 7191, 7969, 315, 62642, 34684, 304, 6978, 1359, 11497, 16273, 10195, 22712, 4562, 77371, 14874, 5997, 11, 889, 6476, 1401, 13073, 304, 2225, 7978, 13, 330, 4897, 9455, 374, 50505, 287, 719, 1101, 31720, 25, 433, 13533, 430, 1690, 21389, 1234, 11828, 5326, 369, 58533, 323, 779, 904, 1403, 6978, 527, 17821, 311, 4430, 279, 1890, 5643, 315, 5326, 21389, 1210, 14874, 5997, 11, 889, 374, 1101, 264, 3495, 28568, 520, 22108, 3331, 15429, 320, 33039, 39, 8, 323, 459, 22712, 14561, 315, 46876, 894, 520, 10640, 79985, 596, 358, 936, 25105, 6150, 315, 19152, 11, 10434, 439, 1176, 3229, 315, 832, 315, 279, 16064, 320, 47, 324, 5997, 1880, 453, 25390, 902, 7863, 279, 506, 20969, 315, 7931, 449, 58533, 449, 1884, 505, 9498, 7931, 505, 279, 1890, 7187, 304, 24067, 13, 578, 12074, 6532, 304, 279, 990, 64895, 505, 11888, 14673, 11, 2737, 279, 16273, 11, 10640, 79985, 11, 323, 386, 45776, 13, 578, 2132, 5684, 320, 3915, 261, 1880, 453, 6266, 5068, 4528, 14955, 13, 3011, 4007, 11, 902, 574, 13375, 555, 264, 7447, 3502, 10663, 278, 20632, 430, 5343, 279, 16273, 10181, 596, 31552, 5955, 369, 17680, 23336, 8483, 11, 10640, 79985, 11, 61692, 3907, 11, 279, 8489, 2063, 17236, 328, 4091, 10181, 11, 323, 4848, 1023, 3495, 14673, 11, 7111, 369, 409, 39423, 34684, 1389, 61086, 304, 459, 46471, 596, 33869, 430, 656, 539, 3073, 304, 279, 85381, 315, 279, 6699, 11, 323, 9093, 4250, 387, 30706, 311, 1077, 291, 488, 13, 15483, 34684, 2759, 369, 17715, 220, 20, 3346, 315, 58533, 5157, 13, 11995, 7978, 1766, 430, 34684, 1051, 4332, 4028, 1690, 21389, 11, 323, 279, 3495, 7411, 11352, 4528, 12912, 304, 279, 8141, 315, 34684, 4028, 15207, 14488, 13, 9176, 315, 279, 21389, 430, 39786, 34684, 6222, 4279, 5865, 25, 814, 49890, 311, 387, 961, 315, 15207, 14488, 430, 2633, 99827, 734, 11, 2737, 279, 22465, 2427, 660, 35719, 28772, 5613, 11, 902, 374, 6532, 304, 43080, 1990, 7917, 304, 279, 8271, 11, 323, 279, 9693, 43681, 86255, 320, 47572, 8, 13128, 6485, 11, 902, 11335, 264, 3560, 304, 99827, 12466, 488, 11, 264, 734, 7718, 311, 6975, 323, 5044, 13, 330, 3915, 264, 12624, 51882, 11, 433, 596, 82964, 311, 1518, 2204, 5528, 315, 21630, 279, 56104, 315, 58533, 80867, 389, 279, 1890, 7437, 315, 21389, 13, 4314, 28830, 20414, 527, 22364, 9017, 279, 1890, 16940, 34458, 11, 902, 649, 387, 8272, 709, 304, 3938, 3495, 1359, 1071, 24565, 4584, 9028, 1119, 11, 889, 574, 459, 3229, 389, 2225, 16064, 13, 4584, 9028, 1119, 374, 7690, 315, 56104, 369, 279, 16273, 596, 31552, 5955, 369, 17680, 23336, 8483, 323, 264, 14561, 304, 56104, 520, 25996, 13235, 6150, 13, 578, 6492, 315, 409, 39423, 34684, 1101, 10675, 5199, 28347, 1990, 1884, 1766, 304, 58533, 323, 409, 39423, 34684, 8767, 10815, 311, 38281, 323, 20207, 28353, 11, 264, 9455, 430, 1253, 10383, 279, 5603, 12074, 1935, 304, 1833, 5352, 7978, 13, 578, 12283, 18046, 430, 2225, 16064, 20461, 430, 33869, 62119, 690, 3136, 311, 387, 264, 8147, 5507, 304, 279, 4007, 315, 58533, 11, 3582, 1690, 810, 10688, 690, 1205, 311, 387, 11506, 5886, 1603, 279, 56104, 315, 420, 6485, 19823, 649, 387, 7373, 16365, 13, 330, 72204, 13363, 617, 1027, 32620, 9749, 922, 279, 31206, 477, 35693, 11384, 315, 58533, 11, 323, 430, 596, 1606, 1690, 8776, 12624, 20414, 649, 956, 387, 1511, 311, 4007, 279, 19823, 25, 499, 649, 956, 3139, 433, 304, 264, 12269, 11, 323, 1070, 7784, 956, 1633, 1695, 10065, 4211, 369, 433, 1359, 4584, 9028, 1119, 11497, 13, 330, 1687, 1781, 430, 85381, 527, 279, 1853, 704, 315, 279, 27394, 11, 323, 430, 1521, 7978, 323, 3885, 1093, 1124, 690, 13967, 3493, 279, 31206, 43775, 584, 690, 1205, 311, 2472, 704, 279, 1853, 85404, 31226, 315, 279, 19823, 1210, 31552, 5955, 7690, 24565, 10320, 1543, 323, 3279, 328, 2119, 21035, 11, 279, 31552, 5955, 596, 10388, 28568, 11, 57595, 279, 14673, 430, 78174, 389, 279, 7978, 13, 330, 791, 19465, 6492, 315, 58533, 374, 78504, 49723, 26455, 3135, 1606, 14248, 2212, 279, 1917, 617, 6575, 11430, 8046, 369, 1667, 311, 20927, 323, 4007, 279, 3544, 1396, 315, 6978, 323, 12593, 15223, 4460, 311, 3820, 704, 9024, 19465, 27103, 5938, 58533, 2403, 279, 40256, 11559, 6485, 4092, 19465, 23851, 430, 3752, 4861, 22706, 13, 2405, 27663, 1093, 364, 68287, 57267, 304, 89547, 82, 6, 656, 539, 3240, 311, 656, 12437, 311, 420, 6222, 3728, 5149, 1359, 10320, 1543, 1071, 13, 328, 2119, 21035, 46728, 430, 420, 20632, 374, 69741, 3495, 430, 690, 13967, 8935, 6978, 13, 330, 791, 506, 638, 62119, 828, 304, 1521, 16064, 3871, 449, 14529, 4459, 37564, 638, 15360, 7978, 304, 6978, 449, 58533, 527, 10695, 311, 75073, 279, 1853, 52379, 315, 420, 33318, 17563, 1359, 328, 2119, 21035, 1071, 13, 330, 2028, 990, 374, 4857, 264, 69917, 902, 690, 55981, 269, 2915, 3063, 311, 2731, 22972, 369, 6978, 323, 8689, 1210, 220, 128257, 198 ]

2,588

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Squeezing of the electromagnetic vacuum is an essential metrological technique used to reduce quantum noise in applications spanning gravitational wave detection, biological microscopy and quantum information science. In superconducting circuits, the resonator-based Josephson-junction parametric amplifiers conventionally used to generate squeezed microwaves are constrained by a narrow bandwidth and low dynamic range. Here we develop a dual-pump, broadband Josephson travelling-wave parametric amplifier that combines a phase-sensitive extinction ratio of 56 dB with single-mode squeezing on par with the best resonator-based squeezers. We also demonstrate two-mode squeezing at microwave frequencies with bandwidth in the gigahertz range that is almost two orders of magnitude wider than that of contemporary resonator-based squeezers. Our amplifier is capable of simultaneously creating entangled microwave photon pairs with large frequency separation, with potential applications including high-fidelity qubit readout, quantum illumination and teleportation. Main Heisenberg’s uncertainty principle establishes the attainable measurement precision, the ‘standard quantum limit’ (SQL), for isotropically distributed vacuum fluctuations in the quadratures of the electromagnetic (EM) field 1 , 2 , 3 . Squeezing the EM field at a single frequency—single-mode squeezing—decreases the fluctuations of one quadrature below that of the vacuum at the expense of larger fluctuations in the other quadrature, thereby enabling a phase-sensitive means to beat the SQL. Squeezing can also generate quantum entanglement between observables at two distinct frequencies, producing two-mode squeezed states. Since its first experimental demonstration in 1985 (ref. 4 ), squeezing has become a resource for applications in quantum optics 5 , quantum information 6 and precision measurement 7 . The Josephson parametric amplifier (JPA) is a conventional approach to generate squeezed microwave photons (Fig. 1a ). JPA squeezers use a narrowband resonator and its resonant-enhanced circulating field to increase the interaction between photons and a single or few Josephson junctions. Josephson junctions are superconducting circuit elements with an inherently strong inductive nonlinearity with respect to the current traversing them. This is the nonlinearity that enables parametric amplification. However, the relatively large circulating field in JPAs strongly drives the nonlinearity of individual junctions, leading to unwanted higher-order nonlinear processes and saturation that impact squeezing performance 8 , 9 , 10 , 11 , 12 , 13 . Moreover, photon number fluctuations in the pump tone could lead to additional noise that reduces squeezing performance 14 . Fig. 1: Josephson travelling-wave parametric amplifier dispersion-engineered for a bichromatic pump. a , Circuit schematic of a conventional JPA. The resonant-enhancement of the field produces a narrowband frequency response. b , A repeating section of the dual-pump JTWPA. We can identify the L – C ladder that forms a 50-Ω transmission line from lumped elements and the two phase-matching resonators for dispersion-engineering. c , Degenerate four-wave mixing. d , Non-degenerate four-wave mixing. The picture shows the special case when the signal and idler are at the same frequency ω c at the centre between the two pumps. Pairs of two-mode squeezed photons (signal and idler) are created at frequencies symmetric about the centre frequency ω c . When the two photons are frequency-degenerate at ω c , this is referred to as single-mode squeezing. e , Micrograph of a 5-mm × 5-mm JTWPA chip. f , Magnified view of the structure showing the low-frequency lumped-element phase-matching resonator (blue), capacitors to ground C g (orange), high-frequency lumped-element phase-matching resonator (purple) and Josephson junctions (red). The colour-coded elements correspond to the circuit schematic in b . g , The JTWPA in the presence of a bichromatic pump transforms the vacuum field at the input into a squeezed field at the output through non-degenerate four-wave mixing. Full size image Several alternative approaches have been developed that address some of these limitations. For example, the impedance engineering of resonator-based JPAs has increased the bandwidth to the 0.5–0.8-GHz range 15 , 16 , but these devices still have a dynamic range limited to −110 to −100 dBm and sub-gigahertz bandwidth. Alternative approaches using superconducting nonlinear asymmetric inductive elements (SNAILs) for both resonant 17 , 18 , 19 and travelling-wave 20 , 21 parametric amplification feature a higher dynamic range in the −100 to −90-dBm range. However, both architectures require a magnetic field bias, making them subject to magnetic-field noise. Furthermore, the resonant version remains narrowband, and one travelling-wave approach 21 requires additional shunt resistors, which introduce dissipation and unwanted noise. So far, both approaches have been limited to 2–3-dB single-mode and two-mode squeezing. High kinetic inductance wiring has been used in place of Josephson junctions to realize the nonlinearity needed for both resonant 22 and travelling-wave parametric amplification 23 , 24 with higher dynamic range. However, the relatively weak nonlinearity of the wiring translates to a much larger requisite pump power to operate the devices, and the travelling-wave parametric amplifiers have larger gain ripple due to impedance variations on the long (up to 2 m) lines. Furthermore, although a single-mode quadrature noise (variance) reduction has been demonstrated in narrowband resonant nanowire devices, their degree of squeezing in decibels has yet to be quantified using a calibrated noise source 22 . Squeezing always involves two modes, a ‘signal’ and an ‘idler’. We note that there are finite bandwidths associated with measurement in experimental settings. To clarify the terminology used in this Article and draw comparison with other previous works, we define ‘two-mode’ as when the signal and idler are non-degenerate and their mode separation is much larger than the measurement bandwidth | ω s − ω i | ≫ B meas , and ‘single-mode’ as when the signal and idler are both nominally degenerate and within the measurement bandwidth | ω s − ω i | ≤ B meas . In this Article, we demonstrate a broadband single-mode and two-mode microwave squeezer using a dispersion-engineered, dual-pump Josephson travelling-wave parametric amplifier (JTWPA). As shown in Fig. 1b , the JTWPA contains a repeating structure called a unit cell, comprising a Josephson junction (red)—a nonlinear inductor—and a shunt capacitor (orange). Because their physical dimensions (tens of micrometres) are small compared to the operating wavelength (tens of millimetres) in the gigahertz", "role": "user" }, { "content": "A certain amount of noise is inherent in any quantum system. For instance, when researchers want to read information from a quantum computer, which harnesses quantum mechanical phenomena to solve certain problems too complex for classical computers, the same quantum mechanics also imparts a minimum level of unavoidable error that limits the accuracy of the measurements. Scientists can effectively get around this limitation by using \"parametric\" amplification to \"squeeze\" the noise—a quantum phenomenon that decreases the noise affecting one variable while increasing the noise that affects its conjugate partner. While the total amount of noise remains the same, it is effectively redistributed. Researchers can then make more accurate measurements by looking only at the lower-noise variable. A team of researchers from MIT and elsewhere has now developed a new superconducting parametric amplifier that operates with the gain of previous narrowband squeezers while achieving quantum squeezing over much larger bandwidths. Their work is the first to demonstrate squeezing over a broad frequency bandwidth of up to 1.75 gigahertz while maintaining a high degree of squeezing (selective noise reduction). In comparison, previous microwave parametric amplifiers generally achieved bandwidths of only 100 megahertz or less. This new broadband device may enable scientists to read out quantum information much more efficiently, leading to faster and more accurate quantum systems. By reducing the error in measurements, this architecture could be utilized in multiqubit systems or other metrological applications that demand extreme precision. \"As the field of quantum computing grows, and the number of qubits in these systems increases to thousands or more, we will need broadband amplification. With our architecture, with just one amplifier you could theoretically read out thousands of qubits at the same time,\" says electrical engineering and computer science graduate student Jack Qiu, who is a member of the Engineering Quantum Systems Group and lead author of the paper detailing this advance. The senior authors are William D. Oliver, the Henry Ellis Warren professor of electrical engineering and computer science and of physics, director of the Center for Quantum Engineering, and associate director of the Research Laboratory of Electronics; and Kevin P. O'Brien, the Emanuel E. Landsman Career Development professor of electrical engineering and computer science. The paper will appear in Nature Physics. Squeezing noise below the standard quantum limit Superconducting quantum circuits, like quantum bits or \"qubits,\" process and transfer information in quantum systems. This information is carried by microwave electromagnetic signals comprising photons. But these signals can be extremely weak, so researchers use amplifiers to boost the signal level such that clean measurements can be made. However, a quantum property known as the Heisenberg Uncertainty Principle requires a minimum amount of noise be added during the amplification process, leading to the \"standard quantum limit\" of background noise. However, a special device, called a Josephson parametric amplifier, can reduce the added noise by \"squeezing\" it below the fundamental limit by effectively redistributing it elsewhere. Quantum information is represented in the conjugate variables, for example, the amplitude and phase of electromagnetic waves. However, in many instances, researchers need only measure one of these variables—the amplitude or the phase—to determine the quantum state of the system. In these instances, they can \"squeeze the noise,\" lowering it for one variable, say amplitude, while raising it for the other, in this case phase. The total amount of noise stays the same due to Heisenberg's Uncertainty Principle, but its distribution can be shaped in such a way that less noisy measurements are possible on one of the variables. A conventional Josephson parametric amplifier is resonator-based: It's like an echo chamber with a superconducting nonlinear element called a Josephson junction in the middle. Photons enter the echo chamber and bounce around to interact with the same Josephson junction multiple times. In this environment, the system nonlinearity—realized by the Josephson junction—is enhanced and leads to parametric amplification and squeezing. But, since the photons traverse the same Josephson junction many times before exiting, the junction is stressed. As a result, both the bandwidth and the maximum signal the resonator-based amplifier can accommodate is limited. The MIT researchers took a different approach. Instead of embedding a single or a few Josephson junctions inside a resonator, they chained more than 3,000 junctions together, creating what is known as a Josephson traveling-wave parametric amplifier. Photons interact with each other as they travel from junction to junction, resulting in noise squeezing without stressing any single junction. Their traveling-wave system can tolerate much higher-power signals than resonator-based Josephson amplifiers without the bandwidth constraint of the resonator, leading to broadband amplification and high levels of squeezing, Qiu says. \"You can think of this system as a really long optical fiber, another type of distributed nonlinear parametric amplifier. And, we can push to 10,000 junctions or more. This is an extensible system, as opposed to the resonant architecture,\" he says. Nearly noiseless amplification A pair of pump photons enters the device, serving as the energy source. Researchers can tune the frequency of photons coming from each pump to generate squeezing at the desired signal frequency. For instance, if they want to squeeze a 6-gigahertz signal, they would adjust the pumps to send photons at 5 and 7 gigahertz, respectively. When the pump photons interact inside the device, they combine to produce an amplified signal with a frequency right in the middle of the two pumps. This is a special process of a more generic phenomenon called nonlinear wave mixing. \"Squeezing of the noise results from a two-photon quantum interference effect that arises during the parametric process,\" he explains. This architecture enabled them to reduce the noise power by a factor 10 below the fundamental quantum limit while operating with 3.5 gigahertz of amplification bandwidth—a frequency range that is almost two orders of magnitude higher than previous devices. Their device also demonstrates broadband generation of entangled photon pairs, which could enable researchers to read out quantum information more efficiently with a much higher signal-to-noise ratio, Qiu says. While Qiu and his collaborators are excited by these results, he says there is still room for improvement. The materials they used to fabricate the amplifier introduce some microwave loss, which can reduce performance. Moving forward, they are exploring different fabrication methods that could improve the insertion loss. \"This work is not meant to be a standalone project. It has tremendous potential if you apply it to other quantum systems— to interface with a qubit system to enhance the readout, or to entangle qubits, or extend the device operating frequency range to be utilized in dark matter detection and improve its detection efficiency. This is essentially like a blueprint for future work,\" he says. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Squeezing of the electromagnetic vacuum is an essential metrological technique used to reduce quantum noise in applications spanning gravitational wave detection, biological microscopy and quantum information science. In superconducting circuits, the resonator-based Josephson-junction parametric amplifiers conventionally used to generate squeezed microwaves are constrained by a narrow bandwidth and low dynamic range. Here we develop a dual-pump, broadband Josephson travelling-wave parametric amplifier that combines a phase-sensitive extinction ratio of 56 dB with single-mode squeezing on par with the best resonator-based squeezers. We also demonstrate two-mode squeezing at microwave frequencies with bandwidth in the gigahertz range that is almost two orders of magnitude wider than that of contemporary resonator-based squeezers. Our amplifier is capable of simultaneously creating entangled microwave photon pairs with large frequency separation, with potential applications including high-fidelity qubit readout, quantum illumination and teleportation. Main Heisenberg’s uncertainty principle establishes the attainable measurement precision, the ‘standard quantum limit’ (SQL), for isotropically distributed vacuum fluctuations in the quadratures of the electromagnetic (EM) field 1 , 2 , 3 . Squeezing the EM field at a single frequency—single-mode squeezing—decreases the fluctuations of one quadrature below that of the vacuum at the expense of larger fluctuations in the other quadrature, thereby enabling a phase-sensitive means to beat the SQL. Squeezing can also generate quantum entanglement between observables at two distinct frequencies, producing two-mode squeezed states. Since its first experimental demonstration in 1985 (ref. 4 ), squeezing has become a resource for applications in quantum optics 5 , quantum information 6 and precision measurement 7 . The Josephson parametric amplifier (JPA) is a conventional approach to generate squeezed microwave photons (Fig. 1a ). JPA squeezers use a narrowband resonator and its resonant-enhanced circulating field to increase the interaction between photons and a single or few Josephson junctions. Josephson junctions are superconducting circuit elements with an inherently strong inductive nonlinearity with respect to the current traversing them. This is the nonlinearity that enables parametric amplification. However, the relatively large circulating field in JPAs strongly drives the nonlinearity of individual junctions, leading to unwanted higher-order nonlinear processes and saturation that impact squeezing performance 8 , 9 , 10 , 11 , 12 , 13 . Moreover, photon number fluctuations in the pump tone could lead to additional noise that reduces squeezing performance 14 . Fig. 1: Josephson travelling-wave parametric amplifier dispersion-engineered for a bichromatic pump. a , Circuit schematic of a conventional JPA. The resonant-enhancement of the field produces a narrowband frequency response. b , A repeating section of the dual-pump JTWPA. We can identify the L – C ladder that forms a 50-Ω transmission line from lumped elements and the two phase-matching resonators for dispersion-engineering. c , Degenerate four-wave mixing. d , Non-degenerate four-wave mixing. The picture shows the special case when the signal and idler are at the same frequency ω c at the centre between the two pumps. Pairs of two-mode squeezed photons (signal and idler) are created at frequencies symmetric about the centre frequency ω c . When the two photons are frequency-degenerate at ω c , this is referred to as single-mode squeezing. e , Micrograph of a 5-mm × 5-mm JTWPA chip. f , Magnified view of the structure showing the low-frequency lumped-element phase-matching resonator (blue), capacitors to ground C g (orange), high-frequency lumped-element phase-matching resonator (purple) and Josephson junctions (red). The colour-coded elements correspond to the circuit schematic in b . g , The JTWPA in the presence of a bichromatic pump transforms the vacuum field at the input into a squeezed field at the output through non-degenerate four-wave mixing. Full size image Several alternative approaches have been developed that address some of these limitations. For example, the impedance engineering of resonator-based JPAs has increased the bandwidth to the 0.5–0.8-GHz range 15 , 16 , but these devices still have a dynamic range limited to −110 to −100 dBm and sub-gigahertz bandwidth. Alternative approaches using superconducting nonlinear asymmetric inductive elements (SNAILs) for both resonant 17 , 18 , 19 and travelling-wave 20 , 21 parametric amplification feature a higher dynamic range in the −100 to −90-dBm range. However, both architectures require a magnetic field bias, making them subject to magnetic-field noise. Furthermore, the resonant version remains narrowband, and one travelling-wave approach 21 requires additional shunt resistors, which introduce dissipation and unwanted noise. So far, both approaches have been limited to 2–3-dB single-mode and two-mode squeezing. High kinetic inductance wiring has been used in place of Josephson junctions to realize the nonlinearity needed for both resonant 22 and travelling-wave parametric amplification 23 , 24 with higher dynamic range. However, the relatively weak nonlinearity of the wiring translates to a much larger requisite pump power to operate the devices, and the travelling-wave parametric amplifiers have larger gain ripple due to impedance variations on the long (up to 2 m) lines. Furthermore, although a single-mode quadrature noise (variance) reduction has been demonstrated in narrowband resonant nanowire devices, their degree of squeezing in decibels has yet to be quantified using a calibrated noise source 22 . Squeezing always involves two modes, a ‘signal’ and an ‘idler’. We note that there are finite bandwidths associated with measurement in experimental settings. To clarify the terminology used in this Article and draw comparison with other previous works, we define ‘two-mode’ as when the signal and idler are non-degenerate and their mode separation is much larger than the measurement bandwidth | ω s − ω i | ≫ B meas , and ‘single-mode’ as when the signal and idler are both nominally degenerate and within the measurement bandwidth | ω s − ω i | ≤ B meas . In this Article, we demonstrate a broadband single-mode and two-mode microwave squeezer using a dispersion-engineered, dual-pump Josephson travelling-wave parametric amplifier (JTWPA). As shown in Fig. 1b , the JTWPA contains a repeating structure called a unit cell, comprising a Josephson junction (red)—a nonlinear inductor—and a shunt capacitor (orange). Because their physical dimensions (tens of micrometres) are small compared to the operating wavelength (tens of millimetres) in the gigahertz<|im_end|> <|im_start|>assistant A certain amount of noise is inherent in any quantum system. For instance, when researchers want to read information from a quantum computer, which harnesses quantum mechanical phenomena to solve certain problems too complex for classical computers, the same quantum mechanics also imparts a minimum level of unavoidable error that limits the accuracy of the measurements. Scientists can effectively get around this limitation by using "parametric" amplification to "squeeze" the noise—a quantum phenomenon that decreases the noise affecting one variable while increasing the noise that affects its conjugate partner. While the total amount of noise remains the same, it is effectively redistributed. Researchers can then make more accurate measurements by looking only at the lower-noise variable. A team of researchers from MIT and elsewhere has now developed a new superconducting parametric amplifier that operates with the gain of previous narrowband squeezers while achieving quantum squeezing over much larger bandwidths. Their work is the first to demonstrate squeezing over a broad frequency bandwidth of up to 1.75 gigahertz while maintaining a high degree of squeezing (selective noise reduction). In comparison, previous microwave parametric amplifiers generally achieved bandwidths of only 100 megahertz or less. This new broadband device may enable scientists to read out quantum information much more efficiently, leading to faster and more accurate quantum systems. By reducing the error in measurements, this architecture could be utilized in multiqubit systems or other metrological applications that demand extreme precision. "As the field of quantum computing grows, and the number of qubits in these systems increases to thousands or more, we will need broadband amplification. With our architecture, with just one amplifier you could theoretically read out thousands of qubits at the same time," says electrical engineering and computer science graduate student Jack Qiu, who is a member of the Engineering Quantum Systems Group and lead author of the paper detailing this advance. The senior authors are William D. Oliver, the Henry Ellis Warren professor of electrical engineering and computer science and of physics, director of the Center for Quantum Engineering, and associate director of the Research Laboratory of Electronics; and Kevin P. O'Brien, the Emanuel E. Landsman Career Development professor of electrical engineering and computer science. The paper will appear in Nature Physics. Squeezing noise below the standard quantum limit Superconducting quantum circuits, like quantum bits or "qubits," process and transfer information in quantum systems. This information is carried by microwave electromagnetic signals comprising photons. But these signals can be extremely weak, so researchers use amplifiers to boost the signal level such that clean measurements can be made. However, a quantum property known as the Heisenberg Uncertainty Principle requires a minimum amount of noise be added during the amplification process, leading to the "standard quantum limit" of background noise. However, a special device, called a Josephson parametric amplifier, can reduce the added noise by "squeezing" it below the fundamental limit by effectively redistributing it elsewhere. Quantum information is represented in the conjugate variables, for example, the amplitude and phase of electromagnetic waves. However, in many instances, researchers need only measure one of these variables—the amplitude or the phase—to determine the quantum state of the system. In these instances, they can "squeeze the noise," lowering it for one variable, say amplitude, while raising it for the other, in this case phase. The total amount of noise stays the same due to Heisenberg's Uncertainty Principle, but its distribution can be shaped in such a way that less noisy measurements are possible on one of the variables. A conventional Josephson parametric amplifier is resonator-based: It's like an echo chamber with a superconducting nonlinear element called a Josephson junction in the middle. Photons enter the echo chamber and bounce around to interact with the same Josephson junction multiple times. In this environment, the system nonlinearity—realized by the Josephson junction—is enhanced and leads to parametric amplification and squeezing. But, since the photons traverse the same Josephson junction many times before exiting, the junction is stressed. As a result, both the bandwidth and the maximum signal the resonator-based amplifier can accommodate is limited. The MIT researchers took a different approach. Instead of embedding a single or a few Josephson junctions inside a resonator, they chained more than 3,000 junctions together, creating what is known as a Josephson traveling-wave parametric amplifier. Photons interact with each other as they travel from junction to junction, resulting in noise squeezing without stressing any single junction. Their traveling-wave system can tolerate much higher-power signals than resonator-based Josephson amplifiers without the bandwidth constraint of the resonator, leading to broadband amplification and high levels of squeezing, Qiu says. "You can think of this system as a really long optical fiber, another type of distributed nonlinear parametric amplifier. And, we can push to 10,000 junctions or more. This is an extensible system, as opposed to the resonant architecture," he says. Nearly noiseless amplification A pair of pump photons enters the device, serving as the energy source. Researchers can tune the frequency of photons coming from each pump to generate squeezing at the desired signal frequency. For instance, if they want to squeeze a 6-gigahertz signal, they would adjust the pumps to send photons at 5 and 7 gigahertz, respectively. When the pump photons interact inside the device, they combine to produce an amplified signal with a frequency right in the middle of the two pumps. This is a special process of a more generic phenomenon called nonlinear wave mixing. "Squeezing of the noise results from a two-photon quantum interference effect that arises during the parametric process," he explains. This architecture enabled them to reduce the noise power by a factor 10 below the fundamental quantum limit while operating with 3.5 gigahertz of amplification bandwidth—a frequency range that is almost two orders of magnitude higher than previous devices. Their device also demonstrates broadband generation of entangled photon pairs, which could enable researchers to read out quantum information more efficiently with a much higher signal-to-noise ratio, Qiu says. While Qiu and his collaborators are excited by these results, he says there is still room for improvement. The materials they used to fabricate the amplifier introduce some microwave loss, which can reduce performance. Moving forward, they are exploring different fabrication methods that could improve the insertion loss. "This work is not meant to be a standalone project. It has tremendous potential if you apply it to other quantum systems— to interface with a qubit system to enhance the readout, or to entangle qubits, or extend the device operating frequency range to be utilized in dark matter detection and improve its detection efficiency. This is essentially like a blueprint for future work," he says. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 328, 593, 10333, 287, 315, 279, 66669, 29302, 374, 459, 7718, 34582, 31356, 15105, 1511, 311, 8108, 31228, 12248, 304, 8522, 56886, 71019, 12330, 18468, 11, 24156, 92914, 323, 31228, 2038, 8198, 13, 763, 2307, 77752, 287, 46121, 11, 279, 29280, 859, 6108, 15466, 942, 13636, 600, 1719, 16743, 23201, 12099, 21977, 750, 1511, 311, 7068, 65262, 19748, 654, 4798, 527, 54852, 555, 264, 15376, 34494, 323, 3428, 8915, 2134, 13, 5810, 584, 2274, 264, 19091, 2320, 1538, 11, 41925, 15466, 942, 31829, 89354, 1719, 16743, 61166, 430, 33511, 264, 10474, 57767, 52609, 11595, 315, 220, 3487, 44868, 449, 3254, 15331, 88807, 389, 1370, 449, 279, 1888, 29280, 859, 6108, 44846, 388, 13, 1226, 1101, 20461, 1403, 15331, 88807, 520, 42374, 34873, 449, 34494, 304, 279, 23401, 1494, 59037, 2134, 430, 374, 4661, 1403, 10373, 315, 26703, 22622, 1109, 430, 315, 19225, 29280, 859, 6108, 44846, 388, 13, 5751, 61166, 374, 13171, 315, 25291, 6968, 1218, 40040, 42374, 69010, 13840, 449, 3544, 11900, 25768, 11, 449, 4754, 8522, 2737, 1579, 2269, 46201, 2874, 60320, 1373, 412, 11, 31228, 77052, 323, 50589, 367, 13, 4802, 1283, 24004, 7881, 753, 27924, 17966, 64664, 279, 36861, 481, 19179, 16437, 11, 279, 3451, 20885, 31228, 4017, 529, 320, 6827, 705, 369, 69551, 897, 2740, 4332, 29302, 65649, 304, 279, 30236, 2859, 315, 279, 66669, 320, 2783, 8, 2115, 220, 16, 1174, 220, 17, 1174, 220, 18, 662, 328, 593, 10333, 287, 279, 17329, 2115, 520, 264, 3254, 11900, 2345, 15698, 15331, 88807, 2345, 451, 846, 2315, 279, 65649, 315, 832, 30236, 1598, 3770, 430, 315, 279, 29302, 520, 279, 20900, 315, 8294, 65649, 304, 279, 1023, 30236, 1598, 11, 28592, 28462, 264, 10474, 57767, 3445, 311, 9567, 279, 8029, 13, 328, 593, 10333, 287, 649, 1101, 7068, 31228, 1218, 526, 1001, 1990, 9466, 4893, 520, 1403, 12742, 34873, 11, 17843, 1403, 15331, 65262, 5415, 13, 8876, 1202, 1176, 22772, 30816, 304, 220, 3753, 20, 320, 1116, 13, 220, 19, 7026, 88807, 706, 3719, 264, 5211, 369, 8522, 304, 31228, 70985, 220, 20, 1174, 31228, 2038, 220, 21, 323, 16437, 19179, 220, 22, 662, 578, 15466, 942, 1719, 16743, 61166, 320, 41, 8201, 8, 374, 264, 21349, 5603, 311, 7068, 65262, 42374, 89235, 320, 30035, 13, 220, 16, 64, 7609, 622, 8201, 44846, 388, 1005, 264, 15376, 7198, 29280, 859, 323, 1202, 29280, 519, 84182, 4979, 54828, 2115, 311, 5376, 279, 16628, 1990, 89235, 323, 264, 3254, 477, 2478, 15466, 942, 49341, 82, 13, 15466, 942, 49341, 82, 527, 2307, 77752, 287, 16622, 5540, 449, 459, 49188, 3831, 304, 68243, 2536, 1074, 10981, 449, 5201, 311, 279, 1510, 30517, 287, 1124, 13, 1115, 374, 279, 2536, 1074, 10981, 430, 20682, 1719, 16743, 23201, 2461, 13, 4452, 11, 279, 12309, 3544, 54828, 2115, 304, 49880, 2170, 16917, 20722, 279, 2536, 1074, 10981, 315, 3927, 49341, 82, 11, 6522, 311, 36021, 5190, 24747, 75098, 11618, 323, 50843, 430, 5536, 88807, 5178, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 662, 23674, 11, 69010, 1396, 65649, 304, 279, 14155, 16630, 1436, 3063, 311, 5217, 12248, 430, 26338, 88807, 5178, 220, 975, 662, 23966, 13, 220, 16, 25, 15466, 942, 31829, 89354, 1719, 16743, 61166, 86712, 50725, 12616, 369, 264, 293, 718, 99866, 14155, 13, 264, 1174, 28317, 68144, 315, 264, 21349, 622, 8201, 13, 578, 29280, 519, 84182, 16887, 315, 279, 2115, 19159, 264, 15376, 7198, 11900, 2077, 13, 293, 1174, 362, 40916, 3857, 315, 279, 19091, 2320, 1538, 622, 48169, 8201, 13, 1226, 649, 10765, 279, 445, 1389, 356, 36865, 430, 7739, 264, 220, 1135, 12, 101418, 18874, 1584, 505, 49629, 291, 5540, 323, 279, 1403, 10474, 1474, 33024, 29280, 3046, 369, 86712, 50725, 4776, 13, 272, 1174, 58337, 13523, 3116, 89354, 27890, 13, 294, 1174, 11842, 6953, 19927, 3116, 89354, 27890, 13, 578, 6945, 5039, 279, 3361, 1162, 994, 279, 8450, 323, 887, 1565, 527, 520, 279, 1890, 11900, 117774, 272, 520, 279, 12541, 1990, 279, 1403, 43875, 13, 393, 4825, 315, 1403, 15331, 65262, 89235, 320, 27720, 323, 887, 1565, 8, 527, 3549, 520, 34873, 55443, 922, 279, 12541, 11900, 117774, 272, 662, 3277, 279, 1403, 89235, 527, 11900, 6953, 19927, 520, 117774, 272, 1174, 420, 374, 14183, 311, 439, 3254, 15331, 88807, 13, 384, 1174, 18654, 4539, 315, 264, 220, 20, 49675, 25800, 220, 20, 49675, 622, 48169, 8201, 16797, 13, 282, 1174, 20918, 1908, 1684, 315, 279, 6070, 9204, 279, 3428, 79412, 49629, 291, 29552, 10474, 1474, 33024, 29280, 859, 320, 12481, 705, 23878, 12170, 311, 5015, 356, 342, 320, 35264, 705, 1579, 79412, 49629, 291, 29552, 10474, 1474, 33024, 29280, 859, 320, 57607, 8, 323, 15466, 942, 49341, 82, 320, 1171, 570, 578, 12745, 87411, 5540, 8024, 311, 279, 16622, 68144, 304, 293, 662, 342, 1174, 578, 622, 48169, 8201, 304, 279, 9546, 315, 264, 293, 718, 99866, 14155, 29575, 279, 29302, 2115, 520, 279, 1988, 1139, 264, 65262, 2115, 520, 279, 2612, 1555, 2536, 6953, 19927, 3116, 89354, 27890, 13, 8797, 1404, 2217, 26778, 10778, 20414, 617, 1027, 8040, 430, 2686, 1063, 315, 1521, 9669, 13, 1789, 3187, 11, 279, 91048, 15009, 315, 29280, 859, 6108, 49880, 2170, 706, 7319, 279, 34494, 311, 279, 220, 15, 13, 20, 4235, 15, 13, 23, 12279, 11732, 2134, 220, 868, 1174, 220, 845, 1174, 719, 1521, 7766, 2103, 617, 264, 8915, 2134, 7347, 311, 25173, 5120, 311, 25173, 1041, 44868, 76, 323, 1207, 2427, 343, 1494, 59037, 34494, 13, 42209, 20414, 1701, 2307, 77752, 287, 75098, 97929, 304, 68243, 5540, 320, 19503, 6093, 82, 8, 369, 2225, 29280, 519, 220, 1114, 1174, 220, 972, 1174, 220, 777, 323, 31829, 89354, 220, 508, 1174, 220, 1691, 1719, 16743, 23201, 2461, 4668, 264, 5190, 8915, 2134, 304, 279, 25173, 1041, 311, 25173, 1954, 1773, 33, 76, 2134, 13, 4452, 11, 2225, 78335, 1397, 264, 24924, 2115, 15837, 11, 3339, 1124, 3917, 311, 24924, 19677, 12248, 13, 24296, 11, 279, 29280, 519, 2373, 8625, 15376, 7198, 11, 323, 832, 31829, 89354, 5603, 220, 1691, 7612, 5217, 559, 3935, 22884, 1105, 11, 902, 19678, 14091, 49686, 323, 36021, 12248, 13, 2100, 3117, 11, 2225, 20414, 617, 1027, 7347, 311, 220, 17, 4235, 18, 1773, 33, 3254, 15331, 323, 1403, 15331, 88807, 13, 5234, 71423, 304, 1076, 685, 19358, 706, 1027, 1511, 304, 2035, 315, 15466, 942, 49341, 82, 311, 13383, 279, 2536, 1074, 10981, 4460, 369, 2225, 29280, 519, 220, 1313, 323, 31829, 89354, 1719, 16743, 23201, 2461, 220, 1419, 1174, 220, 1187, 449, 5190, 8915, 2134, 13, 4452, 11, 279, 12309, 7621, 2536, 1074, 10981, 315, 279, 19358, 48018, 311, 264, 1790, 8294, 82780, 14155, 2410, 311, 14816, 279, 7766, 11, 323, 279, 31829, 89354, 1719, 16743, 23201, 12099, 617, 8294, 8895, 70725, 4245, 311, 91048, 27339, 389, 279, 1317, 320, 455, 311, 220, 17, 296, 8, 5238, 13, 24296, 11, 8051, 264, 3254, 15331, 30236, 1598, 12248, 320, 959, 5397, 8, 14278, 706, 1027, 21091, 304, 15376, 7198, 29280, 519, 20622, 363, 556, 7766, 11, 872, 8547, 315, 88807, 304, 1654, 581, 2053, 706, 3686, 311, 387, 10484, 1908, 1701, 264, 86085, 12248, 2592, 220, 1313, 662, 328, 593, 10333, 287, 2744, 18065, 1403, 20362, 11, 264, 3451, 27720, 529, 323, 459, 3451, 307, 1565, 24535, 1226, 5296, 430, 1070, 527, 35326, 34494, 82, 5938, 449, 19179, 304, 22772, 5110, 13, 2057, 38263, 279, 57726, 1511, 304, 420, 13659, 323, 4128, 12593, 449, 1023, 3766, 4375, 11, 584, 7124, 3451, 20375, 15331, 529, 439, 994, 279, 8450, 323, 887, 1565, 527, 2536, 6953, 19927, 323, 872, 3941, 25768, 374, 1790, 8294, 1109, 279, 19179, 34494, 765, 117774, 274, 25173, 117774, 602, 765, 21784, 104, 426, 7038, 1174, 323, 3451, 15698, 15331, 529, 439, 994, 279, 8450, 323, 887, 1565, 527, 2225, 25194, 750, 5367, 13523, 323, 2949, 279, 19179, 34494, 765, 117774, 274, 25173, 117774, 602, 765, 38394, 426, 7038, 662, 763, 420, 13659, 11, 584, 20461, 264, 41925, 3254, 15331, 323, 1403, 15331, 42374, 274, 17548, 7215, 1701, 264, 86712, 50725, 12616, 11, 19091, 2320, 1538, 15466, 942, 31829, 89354, 1719, 16743, 61166, 320, 41, 48169, 8201, 570, 1666, 6982, 304, 23966, 13, 220, 16, 65, 1174, 279, 622, 48169, 8201, 5727, 264, 40916, 6070, 2663, 264, 5089, 2849, 11, 46338, 264, 15466, 942, 49341, 320, 1171, 68850, 64, 75098, 304, 36869, 17223, 264, 559, 3935, 85525, 320, 35264, 570, 9393, 872, 7106, 15696, 320, 83, 729, 315, 19748, 442, 295, 417, 8, 527, 2678, 7863, 311, 279, 10565, 46406, 320, 83, 729, 315, 2606, 86366, 417, 8, 304, 279, 23401, 1494, 59037, 128257, 198, 128256, 78191, 198, 32, 3738, 3392, 315, 12248, 374, 38088, 304, 904, 31228, 1887, 13, 1789, 2937, 11, 994, 12074, 1390, 311, 1373, 2038, 505, 264, 31228, 6500, 11, 902, 33508, 288, 31228, 22936, 44247, 311, 11886, 3738, 5435, 2288, 6485, 369, 29924, 19002, 11, 279, 1890, 31228, 30126, 1101, 3242, 7183, 264, 8187, 2237, 315, 84116, 1493, 430, 13693, 279, 13708, 315, 279, 22323, 13, 57116, 649, 13750, 636, 2212, 420, 20893, 555, 1701, 330, 913, 16743, 1, 23201, 2461, 311, 330, 53013, 1, 279, 12248, 29096, 31228, 25885, 430, 43154, 279, 12248, 28987, 832, 3977, 1418, 7859, 279, 12248, 430, 22223, 1202, 64380, 349, 8427, 13, 6104, 279, 2860, 3392, 315, 12248, 8625, 279, 1890, 11, 433, 374, 13750, 74494, 13, 59250, 649, 1243, 1304, 810, 13687, 22323, 555, 3411, 1193, 520, 279, 4827, 29466, 1082, 3977, 13, 362, 2128, 315, 12074, 505, 15210, 323, 18403, 706, 1457, 8040, 264, 502, 2307, 77752, 287, 1719, 16743, 61166, 430, 27149, 449, 279, 8895, 315, 3766, 15376, 7198, 44846, 388, 1418, 32145, 31228, 88807, 927, 1790, 8294, 34494, 82, 13, 11205, 990, 374, 279, 1176, 311, 20461, 88807, 927, 264, 7353, 11900, 34494, 315, 709, 311, 220, 16, 13, 2075, 23401, 1494, 59037, 1418, 20958, 264, 1579, 8547, 315, 88807, 320, 1779, 535, 12248, 14278, 570, 763, 12593, 11, 3766, 42374, 1719, 16743, 23201, 12099, 8965, 17427, 34494, 82, 315, 1193, 220, 1041, 19262, 1494, 59037, 477, 2753, 13, 1115, 502, 41925, 3756, 1253, 7431, 14248, 311, 1373, 704, 31228, 2038, 1790, 810, 30820, 11, 6522, 311, 10819, 323, 810, 13687, 31228, 6067, 13, 3296, 18189, 279, 1493, 304, 22323, 11, 420, 18112, 1436, 387, 34716, 304, 7447, 80, 60320, 6067, 477, 1023, 34582, 31356, 8522, 430, 7631, 14560, 16437, 13, 330, 2170, 279, 2115, 315, 31228, 25213, 28815, 11, 323, 279, 1396, 315, 2874, 82502, 304, 1521, 6067, 12992, 311, 9214, 477, 810, 11, 584, 690, 1205, 41925, 23201, 2461, 13, 3161, 1057, 18112, 11, 449, 1120, 832, 61166, 499, 1436, 63234, 1373, 704, 9214, 315, 2874, 82502, 520, 279, 1890, 892, 1359, 2795, 20314, 15009, 323, 6500, 8198, 19560, 5575, 7762, 1229, 19260, 11, 889, 374, 264, 4562, 315, 279, 17005, 56413, 15264, 5856, 323, 3063, 3229, 315, 279, 5684, 45293, 420, 12178, 13, 578, 10195, 12283, 527, 12656, 423, 13, 31346, 11, 279, 18063, 44707, 26713, 14561, 315, 20314, 15009, 323, 6500, 8198, 323, 315, 22027, 11, 7690, 315, 279, 5955, 369, 56413, 17005, 11, 323, 22712, 7690, 315, 279, 8483, 32184, 315, 38784, 26, 323, 16768, 393, 13, 507, 62561, 11, 279, 77760, 469, 13, 38523, 1543, 41576, 11050, 14561, 315, 20314, 15009, 323, 6500, 8198, 13, 578, 5684, 690, 5101, 304, 22037, 28415, 13, 328, 593, 10333, 287, 12248, 3770, 279, 5410, 31228, 4017, 7445, 77752, 287, 31228, 46121, 11, 1093, 31228, 9660, 477, 330, 80, 82502, 1359, 1920, 323, 8481, 2038, 304, 31228, 6067, 13, 1115, 2038, 374, 11953, 555, 42374, 66669, 17738, 46338, 89235, 13, 2030, 1521, 17738, 649, 387, 9193, 7621, 11, 779, 12074, 1005, 23201, 12099, 311, 7916, 279, 8450, 2237, 1778, 430, 4335, 22323, 649, 387, 1903, 13, 4452, 11, 264, 31228, 3424, 3967, 439, 279, 1283, 24004, 7881, 29879, 81246, 82086, 7612, 264, 8187, 3392, 315, 12248, 387, 3779, 2391, 279, 23201, 2461, 1920, 11, 6522, 311, 279, 330, 20885, 31228, 4017, 1, 315, 4092, 12248, 13, 4452, 11, 264, 3361, 3756, 11, 2663, 264, 15466, 942, 1719, 16743, 61166, 11, 649, 8108, 279, 3779, 12248, 555, 330, 82, 593, 10333, 287, 1, 433, 3770, 279, 16188, 4017, 555, 13750, 8873, 10831, 433, 18403, 13, 56413, 2038, 374, 15609, 304, 279, 64380, 349, 7482, 11, 369, 3187, 11, 279, 45209, 323, 10474, 315, 66669, 17301, 13, 4452, 11, 304, 1690, 13422, 11, 12074, 1205, 1193, 6767, 832, 315, 1521, 7482, 22416, 45209, 477, 279, 10474, 50617, 8417, 279, 31228, 1614, 315, 279, 1887, 13, 763, 1521, 13422, 11, 814, 649, 330, 53013, 279, 12248, 1359, 46301, 433, 369, 832, 3977, 11, 2019, 45209, 11, 1418, 19054, 433, 369, 279, 1023, 11, 304, 420, 1162, 10474, 13, 578, 2860, 3392, 315, 12248, 27656, 279, 1890, 4245, 311, 1283, 24004, 7881, 596, 29879, 81246, 82086, 11, 719, 1202, 8141, 649, 387, 27367, 304, 1778, 264, 1648, 430, 2753, 50380, 22323, 527, 3284, 389, 832, 315, 279, 7482, 13, 362, 21349, 15466, 942, 1719, 16743, 61166, 374, 29280, 859, 6108, 25, 1102, 596, 1093, 459, 1722, 25199, 449, 264, 2307, 77752, 287, 75098, 2449, 2663, 264, 15466, 942, 49341, 304, 279, 6278, 13, 18235, 2439, 3810, 279, 1722, 25199, 323, 34782, 2212, 311, 16681, 449, 279, 1890, 15466, 942, 49341, 5361, 3115, 13, 763, 420, 4676, 11, 279, 1887, 2536, 1074, 10981, 2345, 8110, 1534, 555, 279, 15466, 942, 49341, 55434, 24872, 323, 11767, 311, 1719, 16743, 23201, 2461, 323, 88807, 13, 2030, 11, 2533, 279, 89235, 38646, 279, 1890, 15466, 942, 49341, 1690, 3115, 1603, 45848, 11, 279, 49341, 374, 32647, 13, 1666, 264, 1121, 11, 2225, 279, 34494, 323, 279, 7340, 8450, 279, 29280, 859, 6108, 61166, 649, 29376, 374, 7347, 13, 578, 15210, 12074, 3952, 264, 2204, 5603, 13, 12361, 315, 40188, 264, 3254, 477, 264, 2478, 15466, 942, 49341, 82, 4871, 264, 29280, 859, 11, 814, 68069, 810, 1109, 220, 18, 11, 931, 49341, 82, 3871, 11, 6968, 1148, 374, 3967, 439, 264, 15466, 942, 21646, 89354, 1719, 16743, 61166, 13, 18235, 2439, 16681, 449, 1855, 1023, 439, 814, 5944, 505, 49341, 311, 49341, 11, 13239, 304, 12248, 88807, 2085, 94791, 904, 3254, 49341, 13, 11205, 21646, 89354, 1887, 649, 50134, 1790, 5190, 27624, 17738, 1109, 29280, 859, 6108, 15466, 942, 23201, 12099, 2085, 279, 34494, 22295, 315, 279, 29280, 859, 11, 6522, 311, 41925, 23201, 2461, 323, 1579, 5990, 315, 88807, 11, 1229, 19260, 2795, 13, 330, 2675, 649, 1781, 315, 420, 1887, 439, 264, 2216, 1317, 29393, 24722, 11, 2500, 955, 315, 4332, 75098, 1719, 16743, 61166, 13, 1628, 11, 584, 649, 4585, 311, 220, 605, 11, 931, 49341, 82, 477, 810, 13, 1115, 374, 459, 1327, 37864, 1887, 11, 439, 16475, 311, 279, 29280, 519, 18112, 1359, 568, 2795, 13, 49669, 12248, 1752, 23201, 2461, 362, 6857, 315, 14155, 89235, 29933, 279, 3756, 11, 13788, 439, 279, 4907, 2592, 13, 59250, 649, 26306, 279, 11900, 315, 89235, 5108, 505, 1855, 14155, 311, 7068, 88807, 520, 279, 12974, 8450, 11900, 13, 1789, 2937, 11, 422, 814, 1390, 311, 37663, 264, 220, 21, 2427, 343, 1494, 59037, 8450, 11, 814, 1053, 7652, 279, 43875, 311, 3708, 89235, 520, 220, 20, 323, 220, 22, 23401, 1494, 59037, 11, 15947, 13, 3277, 279, 14155, 89235, 16681, 4871, 279, 3756, 11, 814, 16343, 311, 8356, 459, 83598, 8450, 449, 264, 11900, 1314, 304, 279, 6278, 315, 279, 1403, 43875, 13, 1115, 374, 264, 3361, 1920, 315, 264, 810, 14281, 25885, 2663, 75098, 12330, 27890, 13, 330, 50, 593, 10333, 287, 315, 279, 12248, 3135, 505, 264, 1403, 63837, 26934, 31228, 32317, 2515, 430, 48282, 2391, 279, 1719, 16743, 1920, 1359, 568, 15100, 13, 1115, 18112, 9147, 1124, 311, 8108, 279, 12248, 2410, 555, 264, 8331, 220, 605, 3770, 279, 16188, 31228, 4017, 1418, 10565, 449, 220, 18, 13, 20, 23401, 1494, 59037, 315, 23201, 2461, 34494, 29096, 11900, 2134, 430, 374, 4661, 1403, 10373, 315, 26703, 5190, 1109, 3766, 7766, 13, 11205, 3756, 1101, 32216, 41925, 9659, 315, 1218, 40040, 69010, 13840, 11, 902, 1436, 7431, 12074, 311, 1373, 704, 31228, 2038, 810, 30820, 449, 264, 1790, 5190, 8450, 4791, 29466, 1082, 11595, 11, 1229, 19260, 2795, 13, 6104, 1229, 19260, 323, 813, 79119, 527, 12304, 555, 1521, 3135, 11, 568, 2795, 1070, 374, 2103, 3130, 369, 16048, 13, 578, 7384, 814, 1511, 311, 13354, 349, 279, 61166, 19678, 1063, 42374, 4814, 11, 902, 649, 8108, 5178, 13, 38727, 4741, 11, 814, 527, 24919, 2204, 59251, 5528, 430, 1436, 7417, 279, 37027, 4814, 13, 330, 2028, 990, 374, 539, 8967, 311, 387, 264, 44488, 2447, 13, 1102, 706, 28040, 4754, 422, 499, 3881, 433, 311, 1023, 31228, 6067, 2345, 311, 3834, 449, 264, 2874, 60320, 1887, 311, 18885, 279, 1373, 412, 11, 477, 311, 1218, 4134, 2874, 82502, 11, 477, 13334, 279, 3756, 10565, 11900, 2134, 311, 387, 34716, 304, 6453, 5030, 18468, 323, 7417, 1202, 18468, 15374, 13, 1115, 374, 16168, 1093, 264, 54029, 369, 3938, 990, 1359, 568, 2795, 13, 220, 128257, 198 ]

2,838

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The evolutionary history of extant hominoids (humans and apes) remains poorly understood. The African fossil record during the crucial time period, the Miocene epoch, largely comprises isolated jaws and teeth, and little is known about ape cranial evolution. Here we report on the, to our knowledge, most complete fossil ape cranium yet described, recovered from the 13 million-year-old Middle Miocene site of Napudet, Kenya. The infant specimen, KNM-NP 59050, is assigned to a new species of Nyanzapithecus on the basis of its unerupted permanent teeth, visualized by synchrotron imaging. Its ear canal has a fully ossified tubular ectotympanic, a derived feature linking the species with crown catarrhines. Although it resembles some hylobatids in aspects of its morphology and dental development, it possesses no definitive hylobatid synapomorphies. The combined evidence suggests that nyanzapithecines were stem hominoids close to the origin of extant apes, and that hylobatid-like facial features evolved multiple times during catarrhine evolution. Main Hominoids underwent a major evolutionary radiation during the Miocene epoch, with over 40 widely recognized species in at least 30 genera 1 . Despite this multitude of taxa, only about one-third are known from any cranial remains, and no more than half a dozen preserve any substantial portion beyond the face and palate 2 . Thus, much about hominoid cranial evolution remains poorly understood, especially with respect to the ancestral morphology that gave rise to the clade containing extant apes and humans. Importantly, the African fossil record lacks any reasonably complete hominoid crania between 17 and 7 million years (Myr) ago, and no cranial specimens are known at all from between 14 and 10 Myr (refs 3 , 4 , 5 , 6 ), greatly hampering the analysis of hominoid evolution. The KNM-NP 59050 cranium reported here was recovered from Napudet (South Turkana, Kenya) and dated to 13 Myr; it thus falls within this critical, yet poorly represented, period. The infant specimen is nearly complete, but is missing the deciduous dental crowns ( Fig. 1a–d and Extended Data Fig. 1a–f ). The unerupted adult dentition, brain endocast, and bony labyrinths were visualized using propagation phase-contrast X-ray synchrotron microtomography (PPC-SR-μCT; Fig. 1e–h ) 7 . The crown morphology of the fully formed I 1 s and M 1 s, as well as the partly formed M 2 s ( Fig. 2 and Supplementary Data 1 ), indicate that the specimen warrants attribution to a new species in the genus Nyanzapithecus . Figure 1: KNM-NP 59050. a – d , Specimen as preserved in anterior view ( a ), superior view ( b ), inferior view ( c ), and left lateral view ( d ). e – h , Three-dimensional visualizations based on X-ray microtomography, in views matching a – d , and with the bone rendered transparent to show the deciduous dental roots (beige), the unerupted permanent tooth crowns (grey), the bony labyrinths (green), and the endocast (blue transparent in e – g and beige in h ; the olfactory fossa marked by the blue line placed directly underneath). Scale bar, 5 cm. PowerPoint slide Full size image Figure 2: Unerupted permanent dentition. a – g , Three-dimensional X-ray microtomography-based visualization of the left I 1 to M 2 , respectively, shown from left to right in occlusal, mesial, lingual, distal, buccal/labial views. h – n , The right I 1 to M 2 as shown for the left side. In occlusal view, the lingual side of the crown is down. Scale bar, 5 mm. PowerPoint slide Full size image Systematic palaeontology Order Primates Linneaus, 1758 Suborder Anthropoidea Mivart, 1864 Infraorder Catarrhini Geoffroy, 1812 Superfamily Hominoidea Gray, 1825 Subfamily Nyanzapithecinae Harrison, 2002 Genus Nyanzapithecus Harrison, 1986 Nyanzapithecus alesi sp. nov. Etymology. Specific name taken from the Turkana word for ancestor, Ales . Holotype. KNM-NP 59050, an almost complete infant cranium preserving fully formed but unerupted I 1 and M 1 crowns, as well as partly formed crowns of all other permanent teeth, except the not yet initiated M 3 s. Locality and horizon. Napudet (2° 57′ N, 35° 52′ E), Turkana Basin, Kenya, Emunyan Beds, Brown Bedded Tuffs ( Extended Data Fig. 2a ). Geological age. 13 Myr. Diagnosis. A large species of Nyanzapithecus , with M 1 significantly larger than in N. pickfordi ( P < 0.05), N. harrisoni ( P < 0.01), and probably N. vancouveringorum ( Fig. 3a and Extended Data Table 1a ; one-tailed t -test, Bonferroni corrected). The upper molars of N. alesi differ from those of N. vancouveringorum in being more waisted, and in having higher and more inflated molar cusps, a very restricted trigon, and a mesial shelf. N. alesi differs from N. vancouveringorum and N. harrisoni in having an M 1 with a paracone approximately the same size as the metacone, and a protocone much larger than the hypocone. A reduced lingual cingulum also distinguishes N. alesi from N. harrisoni , but not from either N. vancoveringorum or N. pickfordi . N. alesi further differs from N. pickfordi in that the prehypocrista of the M 1 meets the base of the protocone rather than the crista obliqua. Figure 3: Dental metric comparisons of KNM-NP 59050. a , M 1 area (maximum mesiodistal × maximum buccolingual) compared with that of published Nyanzapithecus species. b , M 1 shape (maximum mesiodistal/maximum buccolingual, MD/BL) compared with extant and fossil hominoids. KNM-NP 59050 (dashed line) falls exclusively within the nyanzapithecine range among fossils. c , Relative I 1 size (I 1 maximum mesiodistal/M 1 maximum mesiodistal) compared with extant and fossil hominoids. Nyanzapithecus , including KNM-NP 59050, falls closest to Symphalangus . Samples are given in Supplementary Data 2 . For each sample the mean, the range between the first and third quartiles (box), and the highest and lowest values (whiskers) are indicated, with small ticks marking measured values in the sample. PowerPoint slide Full size image Cranial morphology KNM-NP 59050 is a nearly complete but somewhat distorted cranium of an infant primate ( Fig. 1 ). The cranium is slightly", "role": "user" }, { "content": "The discovery in Kenya of a remarkably complete fossil ape skull reveals what the common ancestor of all living apes and humans may have looked like. The find, announced in the scientific journal Nature on August 10th, belongs to an infant that lived about 13 million years ago. The research was done by an international team led by Isaiah Nengo of Stony Brook University-affiliated Turkana Basin Institute and De Anza College. Among living primates, humans are most closely related to the apes, including chimpanzees, gorillas, orangutans and gibbons. Our common ancestor with chimpanzees lived in Africa 6 to 7 million years ago, and many spectacular fossil finds have revealed how humans evolved since then. In contrast, little is known about the evolution of the common ancestors of living apes and humans before 10 million years ago. Relevant fossils are scarce, consisting mostly of isolated teeth and partial jaw bones. It has therefore been difficult to find answers to two fundamental questions: Did the common ancestor of living apes and humans originate in Africa, and what did these early ancestors look like? Now these questions can be more fully addressed because the newly discovered ape fossil, nicknamed Alesi by its discoverers, and known by its museum number KNM-NP 59050, comes from a critical time period in the African past. In 2014, it was spotted by Kenyan fossil hunter John Ekusi in 13 million-year-old rock layers in the Napudet area, west of Lake Turkana in northern Kenya. \"The Napudet locality offers us a rare glimpse of an African landscape 13 million years ago,\" says Craig S. Feibel of Rutgers University-New Brunswick. \"A nearby volcano buried the forest where the baby ape lived, preserving the fossil and countless trees. It also provided us with the critical volcanic minerals by which we were able to date the fossil.\" A 3-D animation of the Alesi skull, computed from the European Synchrotron Radiation Facility (ESRF) microtomographic data. It shows first the skull in solid 3-D rendering, then transparent surface rendering is used to show the endocast shape (light blue), the internal ears (green) and the permanent teeth germs (grey and brown). Credit: Paul Tafforeau / ESRF The fossil is the skull of an infant, and it is the most complete extinct ape skull known in the fossil record. Many of the most informative parts of the skull are preserved inside the fossil, and to make these visible the team used an extremely sensitive form of 3D X-ray imaging at the synchrotron facility in Grenoble, France. \"We were able to reveal the brain cavity, the inner ears and the unerupted adult teeth with their daily record of growth lines,\" says Paul Tafforeau of the European Synchrotron Radiation Facility. \"The quality of our images was so good that we could establish from the teeth that the infant was about 1 year and 4 months old when it died.\" The unerupted adult teeth inside the infant ape's skull also indicate that the specimen belonged to a new species, Nyanzapithecus alesi. The species name is taken from the Turkana word for ancestor \"ales.\" \"Until now, all Nyanzapithecus species were only known from teeth and it was an open question whether or not they were even apes,\" notes John Fleagle of Stony Brook University. \"Importantly, the cranium has fully developed bony ear tubes, an important feature linking it with living apes,\" adds Ellen Miller of Wake Forest University. Alesi's skull is about the size of a lemon, and with its notably small snout it looks most like a baby gibbon. \"This gives the initial impression that it is an extinct gibbon,\" observes Chris Gilbert of Hunter College, New York. \"However, our analyses show that this appearance is not exclusively found in gibbons, and it evolved multiple times among extinct apes, monkeys, and their relatives.\" Primate paleontologist Isaiah Nengo talks about the day the 13 million-year-old ape fossil skull was discovered. Credit: Isaiah Nengo. Audio © Origin Stories Podcast and The Leakey Foundation. That the new species was certainly not gibbon-like in the way it behaved could be shown from the balance organ inside the inner ears. \"Gibbons are well known for their fast and acrobatic behavior in trees,\" says Fred Spoor of University College London and the Max Planck Institute of Evolutionary Anthropology, \"but the inner ears of Alesi show that it would have had a much more cautious way of moving around.\" \"Nyanzapithecus alesi was part of a group of primates that existed in Africa for over 10 million years,\" concludes lead author Isaiah Nengo. \"What the discovery of Alesi shows is that this group was close to the origin of living apes and humans and that this origin was African.\" Alesi after attached sandstone rock was partially removed at the Turkana Basin Insitute, near Lodwar, Kenya. Credit: © Isaiah Nengo, Photo by Christopher Kiarie ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The evolutionary history of extant hominoids (humans and apes) remains poorly understood. The African fossil record during the crucial time period, the Miocene epoch, largely comprises isolated jaws and teeth, and little is known about ape cranial evolution. Here we report on the, to our knowledge, most complete fossil ape cranium yet described, recovered from the 13 million-year-old Middle Miocene site of Napudet, Kenya. The infant specimen, KNM-NP 59050, is assigned to a new species of Nyanzapithecus on the basis of its unerupted permanent teeth, visualized by synchrotron imaging. Its ear canal has a fully ossified tubular ectotympanic, a derived feature linking the species with crown catarrhines. Although it resembles some hylobatids in aspects of its morphology and dental development, it possesses no definitive hylobatid synapomorphies. The combined evidence suggests that nyanzapithecines were stem hominoids close to the origin of extant apes, and that hylobatid-like facial features evolved multiple times during catarrhine evolution. Main Hominoids underwent a major evolutionary radiation during the Miocene epoch, with over 40 widely recognized species in at least 30 genera 1 . Despite this multitude of taxa, only about one-third are known from any cranial remains, and no more than half a dozen preserve any substantial portion beyond the face and palate 2 . Thus, much about hominoid cranial evolution remains poorly understood, especially with respect to the ancestral morphology that gave rise to the clade containing extant apes and humans. Importantly, the African fossil record lacks any reasonably complete hominoid crania between 17 and 7 million years (Myr) ago, and no cranial specimens are known at all from between 14 and 10 Myr (refs 3 , 4 , 5 , 6 ), greatly hampering the analysis of hominoid evolution. The KNM-NP 59050 cranium reported here was recovered from Napudet (South Turkana, Kenya) and dated to 13 Myr; it thus falls within this critical, yet poorly represented, period. The infant specimen is nearly complete, but is missing the deciduous dental crowns ( Fig. 1a–d and Extended Data Fig. 1a–f ). The unerupted adult dentition, brain endocast, and bony labyrinths were visualized using propagation phase-contrast X-ray synchrotron microtomography (PPC-SR-μCT; Fig. 1e–h ) 7 . The crown morphology of the fully formed I 1 s and M 1 s, as well as the partly formed M 2 s ( Fig. 2 and Supplementary Data 1 ), indicate that the specimen warrants attribution to a new species in the genus Nyanzapithecus . Figure 1: KNM-NP 59050. a – d , Specimen as preserved in anterior view ( a ), superior view ( b ), inferior view ( c ), and left lateral view ( d ). e – h , Three-dimensional visualizations based on X-ray microtomography, in views matching a – d , and with the bone rendered transparent to show the deciduous dental roots (beige), the unerupted permanent tooth crowns (grey), the bony labyrinths (green), and the endocast (blue transparent in e – g and beige in h ; the olfactory fossa marked by the blue line placed directly underneath). Scale bar, 5 cm. PowerPoint slide Full size image Figure 2: Unerupted permanent dentition. a – g , Three-dimensional X-ray microtomography-based visualization of the left I 1 to M 2 , respectively, shown from left to right in occlusal, mesial, lingual, distal, buccal/labial views. h – n , The right I 1 to M 2 as shown for the left side. In occlusal view, the lingual side of the crown is down. Scale bar, 5 mm. PowerPoint slide Full size image Systematic palaeontology Order Primates Linneaus, 1758 Suborder Anthropoidea Mivart, 1864 Infraorder Catarrhini Geoffroy, 1812 Superfamily Hominoidea Gray, 1825 Subfamily Nyanzapithecinae Harrison, 2002 Genus Nyanzapithecus Harrison, 1986 Nyanzapithecus alesi sp. nov. Etymology. Specific name taken from the Turkana word for ancestor, Ales . Holotype. KNM-NP 59050, an almost complete infant cranium preserving fully formed but unerupted I 1 and M 1 crowns, as well as partly formed crowns of all other permanent teeth, except the not yet initiated M 3 s. Locality and horizon. Napudet (2° 57′ N, 35° 52′ E), Turkana Basin, Kenya, Emunyan Beds, Brown Bedded Tuffs ( Extended Data Fig. 2a ). Geological age. 13 Myr. Diagnosis. A large species of Nyanzapithecus , with M 1 significantly larger than in N. pickfordi ( P < 0.05), N. harrisoni ( P < 0.01), and probably N. vancouveringorum ( Fig. 3a and Extended Data Table 1a ; one-tailed t -test, Bonferroni corrected). The upper molars of N. alesi differ from those of N. vancouveringorum in being more waisted, and in having higher and more inflated molar cusps, a very restricted trigon, and a mesial shelf. N. alesi differs from N. vancouveringorum and N. harrisoni in having an M 1 with a paracone approximately the same size as the metacone, and a protocone much larger than the hypocone. A reduced lingual cingulum also distinguishes N. alesi from N. harrisoni , but not from either N. vancoveringorum or N. pickfordi . N. alesi further differs from N. pickfordi in that the prehypocrista of the M 1 meets the base of the protocone rather than the crista obliqua. Figure 3: Dental metric comparisons of KNM-NP 59050. a , M 1 area (maximum mesiodistal × maximum buccolingual) compared with that of published Nyanzapithecus species. b , M 1 shape (maximum mesiodistal/maximum buccolingual, MD/BL) compared with extant and fossil hominoids. KNM-NP 59050 (dashed line) falls exclusively within the nyanzapithecine range among fossils. c , Relative I 1 size (I 1 maximum mesiodistal/M 1 maximum mesiodistal) compared with extant and fossil hominoids. Nyanzapithecus , including KNM-NP 59050, falls closest to Symphalangus . Samples are given in Supplementary Data 2 . For each sample the mean, the range between the first and third quartiles (box), and the highest and lowest values (whiskers) are indicated, with small ticks marking measured values in the sample. PowerPoint slide Full size image Cranial morphology KNM-NP 59050 is a nearly complete but somewhat distorted cranium of an infant primate ( Fig. 1 ). The cranium is slightly<|im_end|> <|im_start|>assistant The discovery in Kenya of a remarkably complete fossil ape skull reveals what the common ancestor of all living apes and humans may have looked like. The find, announced in the scientific journal Nature on August 10th, belongs to an infant that lived about 13 million years ago. The research was done by an international team led by Isaiah Nengo of Stony Brook University-affiliated Turkana Basin Institute and De Anza College. Among living primates, humans are most closely related to the apes, including chimpanzees, gorillas, orangutans and gibbons. Our common ancestor with chimpanzees lived in Africa 6 to 7 million years ago, and many spectacular fossil finds have revealed how humans evolved since then. In contrast, little is known about the evolution of the common ancestors of living apes and humans before 10 million years ago. Relevant fossils are scarce, consisting mostly of isolated teeth and partial jaw bones. It has therefore been difficult to find answers to two fundamental questions: Did the common ancestor of living apes and humans originate in Africa, and what did these early ancestors look like? Now these questions can be more fully addressed because the newly discovered ape fossil, nicknamed Alesi by its discoverers, and known by its museum number KNM-NP 59050, comes from a critical time period in the African past. In 2014, it was spotted by Kenyan fossil hunter John Ekusi in 13 million-year-old rock layers in the Napudet area, west of Lake Turkana in northern Kenya. "The Napudet locality offers us a rare glimpse of an African landscape 13 million years ago," says Craig S. Feibel of Rutgers University-New Brunswick. "A nearby volcano buried the forest where the baby ape lived, preserving the fossil and countless trees. It also provided us with the critical volcanic minerals by which we were able to date the fossil." A 3-D animation of the Alesi skull, computed from the European Synchrotron Radiation Facility (ESRF) microtomographic data. It shows first the skull in solid 3-D rendering, then transparent surface rendering is used to show the endocast shape (light blue), the internal ears (green) and the permanent teeth germs (grey and brown). Credit: Paul Tafforeau / ESRF The fossil is the skull of an infant, and it is the most complete extinct ape skull known in the fossil record. Many of the most informative parts of the skull are preserved inside the fossil, and to make these visible the team used an extremely sensitive form of 3D X-ray imaging at the synchrotron facility in Grenoble, France. "We were able to reveal the brain cavity, the inner ears and the unerupted adult teeth with their daily record of growth lines," says Paul Tafforeau of the European Synchrotron Radiation Facility. "The quality of our images was so good that we could establish from the teeth that the infant was about 1 year and 4 months old when it died." The unerupted adult teeth inside the infant ape's skull also indicate that the specimen belonged to a new species, Nyanzapithecus alesi. The species name is taken from the Turkana word for ancestor "ales." "Until now, all Nyanzapithecus species were only known from teeth and it was an open question whether or not they were even apes," notes John Fleagle of Stony Brook University. "Importantly, the cranium has fully developed bony ear tubes, an important feature linking it with living apes," adds Ellen Miller of Wake Forest University. Alesi's skull is about the size of a lemon, and with its notably small snout it looks most like a baby gibbon. "This gives the initial impression that it is an extinct gibbon," observes Chris Gilbert of Hunter College, New York. "However, our analyses show that this appearance is not exclusively found in gibbons, and it evolved multiple times among extinct apes, monkeys, and their relatives." Primate paleontologist Isaiah Nengo talks about the day the 13 million-year-old ape fossil skull was discovered. Credit: Isaiah Nengo. Audio © Origin Stories Podcast and The Leakey Foundation. That the new species was certainly not gibbon-like in the way it behaved could be shown from the balance organ inside the inner ears. "Gibbons are well known for their fast and acrobatic behavior in trees," says Fred Spoor of University College London and the Max Planck Institute of Evolutionary Anthropology, "but the inner ears of Alesi show that it would have had a much more cautious way of moving around." "Nyanzapithecus alesi was part of a group of primates that existed in Africa for over 10 million years," concludes lead author Isaiah Nengo. "What the discovery of Alesi shows is that this group was close to the origin of living apes and humans and that this origin was African." Alesi after attached sandstone rock was partially removed at the Turkana Basin Insitute, near Lodwar, Kenya. Credit: © Isaiah Nengo, Photo by Christopher Kiarie <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 41993, 3925, 315, 1327, 519, 5105, 258, 17390, 320, 28400, 598, 323, 1469, 288, 8, 8625, 31555, 16365, 13, 578, 11904, 31376, 3335, 2391, 279, 16996, 892, 4261, 11, 279, 21402, 78782, 16746, 11, 14090, 41095, 25181, 82356, 323, 18311, 11, 323, 2697, 374, 3967, 922, 85980, 70637, 532, 15740, 13, 5810, 584, 1934, 389, 279, 11, 311, 1057, 6677, 11, 1455, 4686, 31376, 85980, 1589, 35822, 3686, 7633, 11, 26403, 505, 279, 220, 1032, 3610, 4771, 6418, 12877, 21402, 78782, 2816, 315, 29576, 664, 295, 11, 37766, 13, 578, 31383, 58184, 11, 32392, 44, 11500, 47, 220, 20615, 1135, 11, 374, 12893, 311, 264, 502, 9606, 315, 452, 8503, 93471, 275, 42750, 355, 389, 279, 8197, 315, 1202, 653, 261, 7717, 291, 15690, 18311, 11, 9302, 1534, 555, 6925, 331, 299, 35785, 32758, 13, 11699, 2487, 40021, 706, 264, 7373, 31159, 1908, 15286, 1299, 77594, 354, 1631, 19621, 11, 264, 14592, 4668, 31799, 279, 9606, 449, 27631, 8415, 1138, 71, 1572, 13, 10541, 433, 53291, 1063, 6409, 1718, 266, 3447, 304, 13878, 315, 1202, 79612, 323, 29106, 4500, 11, 433, 50326, 912, 45813, 6409, 1718, 266, 307, 6925, 391, 316, 16751, 552, 13, 578, 11093, 6029, 13533, 430, 308, 8503, 93471, 275, 42750, 1572, 1051, 19646, 5105, 258, 17390, 3345, 311, 279, 6371, 315, 1327, 519, 1469, 288, 11, 323, 430, 6409, 1718, 266, 307, 12970, 28900, 4519, 28995, 5361, 3115, 2391, 8415, 1138, 71, 483, 15740, 13, 4802, 473, 8129, 17390, 55093, 264, 3682, 41993, 25407, 2391, 279, 21402, 78782, 16746, 11, 449, 927, 220, 1272, 13882, 15324, 9606, 304, 520, 3325, 220, 966, 84535, 220, 16, 662, 18185, 420, 49068, 315, 77314, 11, 1193, 922, 832, 30277, 527, 3967, 505, 904, 70637, 532, 8625, 11, 323, 912, 810, 1109, 4376, 264, 21030, 21813, 904, 12190, 13651, 7953, 279, 3663, 323, 77338, 220, 17, 662, 14636, 11, 1790, 922, 5105, 258, 590, 70637, 532, 15740, 8625, 31555, 16365, 11, 5423, 449, 5201, 311, 279, 78771, 79612, 430, 6688, 10205, 311, 279, 1206, 1037, 8649, 1327, 519, 1469, 288, 323, 12966, 13, 13516, 18007, 11, 279, 11904, 31376, 3335, 37856, 904, 29546, 4686, 5105, 258, 590, 1589, 9345, 1990, 220, 1114, 323, 220, 22, 3610, 1667, 320, 5159, 81, 8, 4227, 11, 323, 912, 70637, 532, 57749, 527, 3967, 520, 682, 505, 1990, 220, 975, 323, 220, 605, 3092, 81, 320, 16541, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 7026, 19407, 13824, 61818, 279, 6492, 315, 5105, 258, 590, 15740, 13, 578, 32392, 44, 11500, 47, 220, 20615, 1135, 1589, 35822, 5068, 1618, 574, 26403, 505, 29576, 664, 295, 320, 26070, 21187, 3444, 11, 37766, 8, 323, 30105, 311, 220, 1032, 3092, 81, 26, 433, 8617, 17503, 2949, 420, 9200, 11, 3686, 31555, 15609, 11, 4261, 13, 578, 31383, 58184, 374, 7154, 4686, 11, 719, 374, 7554, 279, 70493, 9373, 29106, 9460, 4511, 320, 23966, 13, 220, 16, 64, 4235, 67, 323, 41665, 2956, 23966, 13, 220, 16, 64, 4235, 69, 7609, 578, 653, 261, 7717, 291, 6822, 18653, 684, 11, 8271, 842, 511, 561, 11, 323, 293, 3633, 326, 58437, 17323, 1051, 9302, 1534, 1701, 54743, 10474, 12, 85324, 1630, 30630, 6925, 331, 299, 35785, 8162, 38501, 5814, 320, 4505, 34, 6354, 49, 12, 44223, 1182, 26, 23966, 13, 220, 16, 68, 4235, 71, 883, 220, 22, 662, 578, 27631, 79612, 315, 279, 7373, 14454, 358, 220, 16, 274, 323, 386, 220, 16, 274, 11, 439, 1664, 439, 279, 28135, 14454, 386, 220, 17, 274, 320, 23966, 13, 220, 17, 323, 99371, 2956, 220, 16, 7026, 13519, 430, 279, 58184, 55688, 63124, 311, 264, 502, 9606, 304, 279, 64677, 452, 8503, 93471, 275, 42750, 355, 662, 19575, 220, 16, 25, 32392, 44, 11500, 47, 220, 20615, 1135, 13, 264, 1389, 294, 1174, 11197, 27236, 439, 34683, 304, 37229, 1684, 320, 264, 7026, 16757, 1684, 320, 293, 7026, 38279, 1684, 320, 272, 7026, 323, 2163, 45569, 1684, 320, 294, 7609, 384, 1389, 305, 1174, 14853, 33520, 9302, 8200, 3196, 389, 1630, 30630, 8162, 38501, 5814, 11, 304, 6325, 12864, 264, 1389, 294, 1174, 323, 449, 279, 17685, 23188, 18300, 311, 1501, 279, 70493, 9373, 29106, 20282, 320, 1395, 7404, 705, 279, 653, 261, 7717, 291, 15690, 26588, 9460, 4511, 320, 35671, 705, 279, 293, 3633, 326, 58437, 17323, 320, 13553, 705, 323, 279, 842, 511, 561, 320, 12481, 18300, 304, 384, 1389, 342, 323, 79365, 304, 305, 2652, 279, 8492, 22348, 26495, 64, 13160, 555, 279, 6437, 1584, 9277, 6089, 30456, 570, 25635, 3703, 11, 220, 20, 10166, 13, 54600, 15332, 8797, 1404, 2217, 19575, 220, 17, 25, 549, 1215, 7717, 291, 15690, 18653, 684, 13, 264, 1389, 342, 1174, 14853, 33520, 1630, 30630, 8162, 38501, 5814, 6108, 42148, 315, 279, 2163, 358, 220, 16, 311, 386, 220, 17, 1174, 15947, 11, 6982, 505, 2163, 311, 1314, 304, 18274, 4256, 278, 11, 11083, 532, 11, 38172, 940, 11, 1612, 278, 11, 1048, 641, 278, 95298, 532, 6325, 13, 305, 1389, 308, 1174, 578, 1314, 358, 220, 16, 311, 386, 220, 17, 439, 6982, 369, 279, 2163, 3185, 13, 763, 18274, 4256, 278, 1684, 11, 279, 38172, 940, 3185, 315, 279, 27631, 374, 1523, 13, 25635, 3703, 11, 220, 20, 9653, 13, 54600, 15332, 8797, 1404, 2217, 744, 780, 11091, 6043, 63333, 7365, 36283, 988, 8732, 818, 12119, 11, 220, 10005, 23, 3804, 1382, 70384, 78, 42877, 386, 344, 472, 11, 220, 9714, 19, 15268, 969, 1382, 17810, 1138, 71, 6729, 51530, 3433, 11, 220, 10562, 17, 7445, 19521, 13525, 3394, 42877, 24255, 11, 220, 10828, 20, 3804, 19521, 452, 8503, 93471, 275, 42750, 125887, 36627, 11, 220, 1049, 17, 9500, 355, 452, 8503, 93471, 275, 42750, 355, 36627, 11, 220, 3753, 21, 452, 8503, 93471, 275, 42750, 355, 264, 76995, 993, 13, 6747, 13, 19421, 99174, 13, 29362, 836, 4529, 505, 279, 21187, 3444, 3492, 369, 46831, 11, 362, 645, 662, 16071, 4249, 13, 32392, 44, 11500, 47, 220, 20615, 1135, 11, 459, 4661, 4686, 31383, 1589, 35822, 47995, 7373, 14454, 719, 653, 261, 7717, 291, 358, 220, 16, 323, 386, 220, 16, 9460, 4511, 11, 439, 1664, 439, 28135, 14454, 9460, 4511, 315, 682, 1023, 15690, 18311, 11, 3734, 279, 539, 3686, 33230, 386, 220, 18, 274, 13, 13914, 2786, 323, 35174, 13, 29576, 664, 295, 320, 17, 11877, 220, 3226, 39615, 452, 11, 220, 1758, 11877, 220, 4103, 39615, 469, 705, 21187, 3444, 61358, 11, 37766, 11, 5867, 359, 8503, 67354, 11, 10690, 13394, 9988, 350, 33668, 320, 41665, 2956, 23966, 13, 220, 17, 64, 7609, 80850, 4325, 13, 220, 1032, 3092, 81, 13, 95452, 13, 362, 3544, 9606, 315, 452, 8503, 93471, 275, 42750, 355, 1174, 449, 386, 220, 16, 12207, 8294, 1109, 304, 452, 13, 3820, 8350, 72, 320, 393, 366, 220, 15, 13, 2304, 705, 452, 13, 305, 51103, 72, 320, 393, 366, 220, 15, 13, 1721, 705, 323, 4762, 452, 13, 348, 21104, 287, 34106, 320, 23966, 13, 220, 18, 64, 323, 41665, 2956, 6771, 220, 16, 64, 2652, 832, 2442, 5805, 259, 482, 1985, 11, 13789, 69, 618, 21446, 37065, 570, 578, 8582, 22337, 1590, 315, 452, 13, 264, 76995, 1782, 505, 1884, 315, 452, 13, 348, 21104, 287, 34106, 304, 1694, 810, 10667, 13539, 11, 323, 304, 3515, 5190, 323, 810, 70954, 296, 7569, 81070, 1725, 11, 264, 1633, 22486, 54033, 263, 11, 323, 264, 11083, 532, 28745, 13, 452, 13, 264, 76995, 44642, 505, 452, 13, 348, 21104, 287, 34106, 323, 452, 13, 305, 51103, 72, 304, 3515, 459, 386, 220, 16, 449, 264, 3429, 59182, 13489, 279, 1890, 1404, 439, 279, 8999, 59182, 11, 323, 264, 18940, 59182, 1790, 8294, 1109, 279, 22601, 59182, 13, 362, 11293, 38172, 940, 272, 287, 16903, 1101, 19512, 21168, 452, 13, 264, 76995, 505, 452, 13, 305, 51103, 72, 1174, 719, 539, 505, 3060, 452, 13, 5355, 93013, 34106, 477, 452, 13, 3820, 8350, 72, 662, 452, 13, 264, 76995, 4726, 44642, 505, 452, 13, 3820, 8350, 72, 304, 430, 279, 864, 79343, 511, 2889, 64, 315, 279, 386, 220, 16, 20628, 279, 2385, 315, 279, 18940, 59182, 4856, 1109, 279, 1589, 9265, 1536, 41093, 64, 13, 19575, 220, 18, 25, 48804, 18767, 36595, 315, 32392, 44, 11500, 47, 220, 20615, 1135, 13, 264, 1174, 386, 220, 16, 3158, 320, 40287, 11083, 3205, 380, 278, 25800, 7340, 1048, 641, 85669, 940, 8, 7863, 449, 430, 315, 4756, 452, 8503, 93471, 275, 42750, 355, 9606, 13, 293, 1174, 386, 220, 16, 6211, 320, 40287, 11083, 3205, 380, 278, 14, 40287, 1048, 641, 85669, 940, 11, 14306, 14, 9574, 8, 7863, 449, 1327, 519, 323, 31376, 5105, 258, 17390, 13, 32392, 44, 11500, 47, 220, 20615, 1135, 320, 67, 13883, 1584, 8, 17503, 24121, 2949, 279, 308, 8503, 93471, 275, 42750, 483, 2134, 4315, 81473, 13, 272, 1174, 40502, 358, 220, 16, 1404, 320, 40, 220, 16, 7340, 11083, 3205, 380, 278, 10482, 220, 16, 7340, 11083, 3205, 380, 278, 8, 7863, 449, 1327, 519, 323, 31376, 5105, 258, 17390, 13, 452, 8503, 93471, 275, 42750, 355, 1174, 2737, 32392, 44, 11500, 47, 220, 20615, 1135, 11, 17503, 18585, 311, 11629, 764, 278, 526, 355, 662, 59450, 527, 2728, 304, 99371, 2956, 220, 17, 662, 1789, 1855, 6205, 279, 3152, 11, 279, 2134, 1990, 279, 1176, 323, 4948, 41376, 3742, 320, 2054, 705, 323, 279, 8592, 323, 15821, 2819, 320, 1336, 3267, 388, 8, 527, 16717, 11, 449, 2678, 31057, 36024, 17303, 2819, 304, 279, 6205, 13, 54600, 15332, 8797, 1404, 2217, 67530, 532, 79612, 32392, 44, 11500, 47, 220, 20615, 1135, 374, 264, 7154, 4686, 719, 14738, 62236, 1589, 35822, 315, 459, 31383, 550, 3509, 320, 23966, 13, 220, 16, 7609, 578, 1589, 35822, 374, 10284, 128257, 198, 128256, 78191, 198, 791, 18841, 304, 37766, 315, 264, 49723, 4686, 31376, 85980, 35113, 21667, 1148, 279, 4279, 46831, 315, 682, 5496, 1469, 288, 323, 12966, 1253, 617, 7111, 1093, 13, 578, 1505, 11, 7376, 304, 279, 12624, 8486, 22037, 389, 6287, 220, 605, 339, 11, 17623, 311, 459, 31383, 430, 12439, 922, 220, 1032, 3610, 1667, 4227, 13, 578, 3495, 574, 2884, 555, 459, 6625, 2128, 6197, 555, 64530, 452, 65753, 315, 36219, 88, 15978, 3907, 71260, 54873, 21187, 3444, 61358, 10181, 323, 1611, 1556, 4458, 9304, 13, 22395, 5496, 9036, 988, 11, 12966, 527, 1455, 15499, 5552, 311, 279, 1469, 288, 11, 2737, 99425, 3059, 288, 11, 46298, 34344, 11, 50707, 332, 598, 323, 78427, 47620, 13, 5751, 4279, 46831, 449, 99425, 3059, 288, 12439, 304, 10384, 220, 21, 311, 220, 22, 3610, 1667, 4227, 11, 323, 1690, 28809, 31376, 14035, 617, 10675, 1268, 12966, 28995, 2533, 1243, 13, 763, 13168, 11, 2697, 374, 3967, 922, 279, 15740, 315, 279, 4279, 38618, 315, 5496, 1469, 288, 323, 12966, 1603, 220, 605, 3610, 1667, 4227, 13, 88516, 81473, 527, 59290, 11, 31706, 10213, 315, 25181, 18311, 323, 7276, 16942, 25896, 13, 1102, 706, 9093, 1027, 5107, 311, 1505, 11503, 311, 1403, 16188, 4860, 25, 14910, 279, 4279, 46831, 315, 5496, 1469, 288, 323, 12966, 82316, 304, 10384, 11, 323, 1148, 1550, 1521, 4216, 38618, 1427, 1093, 30, 4800, 1521, 4860, 649, 387, 810, 7373, 20669, 1606, 279, 13945, 11352, 85980, 31376, 11, 90234, 362, 76995, 555, 1202, 7142, 388, 11, 323, 3967, 555, 1202, 24925, 1396, 32392, 44, 11500, 47, 220, 20615, 1135, 11, 4131, 505, 264, 9200, 892, 4261, 304, 279, 11904, 3347, 13, 763, 220, 679, 19, 11, 433, 574, 30652, 555, 14594, 8503, 31376, 40827, 3842, 50088, 53913, 304, 220, 1032, 3610, 4771, 6418, 7091, 13931, 304, 279, 29576, 664, 295, 3158, 11, 9909, 315, 11940, 21187, 3444, 304, 18671, 37766, 13, 330, 791, 29576, 664, 295, 69187, 6209, 603, 264, 9024, 40942, 315, 459, 11904, 18921, 220, 1032, 3610, 1667, 4227, 1359, 2795, 29517, 328, 13, 3926, 69695, 315, 72091, 3907, 90837, 61250, 13, 330, 32, 14373, 66306, 28016, 279, 13952, 1405, 279, 8945, 85980, 12439, 11, 47995, 279, 31376, 323, 28701, 12690, 13, 1102, 1101, 3984, 603, 449, 279, 9200, 67164, 34072, 555, 902, 584, 1051, 3025, 311, 2457, 279, 31376, 1210, 362, 220, 18, 9607, 10571, 315, 279, 362, 76995, 35113, 11, 25157, 505, 279, 7665, 24028, 331, 299, 35785, 90326, 47750, 320, 1600, 18077, 8, 8162, 38501, 12968, 828, 13, 1102, 5039, 1176, 279, 35113, 304, 6573, 220, 18, 9607, 21568, 11, 1243, 18300, 7479, 21568, 374, 1511, 311, 1501, 279, 842, 511, 561, 6211, 320, 4238, 6437, 705, 279, 5419, 25212, 320, 13553, 8, 323, 279, 15690, 18311, 17684, 1026, 320, 35671, 323, 14198, 570, 16666, 25, 7043, 350, 2715, 461, 2933, 611, 469, 14899, 37, 578, 31376, 374, 279, 35113, 315, 459, 31383, 11, 323, 433, 374, 279, 1455, 4686, 69918, 85980, 35113, 3967, 304, 279, 31376, 3335, 13, 9176, 315, 279, 1455, 39319, 5596, 315, 279, 35113, 527, 34683, 4871, 279, 31376, 11, 323, 311, 1304, 1521, 9621, 279, 2128, 1511, 459, 9193, 16614, 1376, 315, 220, 18, 35, 1630, 30630, 32758, 520, 279, 6925, 331, 299, 35785, 12764, 304, 39224, 51093, 11, 9822, 13, 330, 1687, 1051, 3025, 311, 16805, 279, 8271, 56429, 11, 279, 9358, 25212, 323, 279, 653, 261, 7717, 291, 6822, 18311, 449, 872, 7446, 3335, 315, 6650, 5238, 1359, 2795, 7043, 350, 2715, 461, 2933, 315, 279, 7665, 24028, 331, 299, 35785, 90326, 47750, 13, 330, 791, 4367, 315, 1057, 5448, 574, 779, 1695, 430, 584, 1436, 5813, 505, 279, 18311, 430, 279, 31383, 574, 922, 220, 16, 1060, 323, 220, 19, 4038, 2362, 994, 433, 8636, 1210, 578, 653, 261, 7717, 291, 6822, 18311, 4871, 279, 31383, 85980, 596, 35113, 1101, 13519, 430, 279, 58184, 46959, 311, 264, 502, 9606, 11, 452, 8503, 93471, 275, 42750, 355, 264, 76995, 13, 578, 9606, 836, 374, 4529, 505, 279, 21187, 3444, 3492, 369, 46831, 330, 3916, 1210, 330, 25503, 1457, 11, 682, 452, 8503, 93471, 275, 42750, 355, 9606, 1051, 1193, 3967, 505, 18311, 323, 433, 574, 459, 1825, 3488, 3508, 477, 539, 814, 1051, 1524, 1469, 288, 1359, 8554, 3842, 47790, 33774, 315, 36219, 88, 15978, 3907, 13, 330, 11772, 18007, 11, 279, 1589, 35822, 706, 7373, 8040, 293, 3633, 2487, 34083, 11, 459, 3062, 4668, 31799, 433, 449, 5496, 1469, 288, 1359, 11621, 47685, 17472, 315, 41674, 20585, 3907, 13, 362, 76995, 596, 35113, 374, 922, 279, 1404, 315, 264, 30564, 11, 323, 449, 1202, 35146, 2678, 4224, 412, 433, 5992, 1455, 1093, 264, 8945, 342, 36180, 13, 330, 2028, 6835, 279, 2926, 21455, 430, 433, 374, 459, 69918, 342, 36180, 1359, 81299, 11517, 46092, 315, 24008, 9304, 11, 1561, 4356, 13, 330, 11458, 11, 1057, 29060, 1501, 430, 420, 11341, 374, 539, 24121, 1766, 304, 78427, 47620, 11, 323, 433, 28995, 5361, 3115, 4315, 69918, 1469, 288, 11, 61820, 11, 323, 872, 29658, 1210, 2394, 3509, 28639, 546, 16549, 64530, 452, 65753, 13739, 922, 279, 1938, 279, 220, 1032, 3610, 4771, 6418, 85980, 31376, 35113, 574, 11352, 13, 16666, 25, 64530, 452, 65753, 13, 12632, 7388, 17554, 30129, 30869, 323, 578, 2009, 731, 88, 5114, 13, 3011, 279, 502, 9606, 574, 7995, 539, 342, 36180, 12970, 304, 279, 1648, 433, 89831, 1436, 387, 6982, 505, 279, 8335, 2942, 4871, 279, 9358, 25212, 13, 330, 38, 581, 47620, 527, 1664, 3967, 369, 872, 5043, 323, 1645, 23576, 780, 7865, 304, 12690, 1359, 2795, 28588, 3165, 10922, 315, 3907, 9304, 7295, 323, 279, 7639, 9878, 377, 10181, 315, 38321, 661, 70384, 2508, 11, 330, 8248, 279, 9358, 25212, 315, 362, 76995, 1501, 430, 433, 1053, 617, 1047, 264, 1790, 810, 46878, 1648, 315, 7366, 2212, 1210, 330, 45, 8503, 93471, 275, 42750, 355, 264, 76995, 574, 961, 315, 264, 1912, 315, 9036, 988, 430, 25281, 304, 10384, 369, 927, 220, 605, 3610, 1667, 1359, 45537, 3063, 3229, 64530, 452, 65753, 13, 330, 3923, 279, 18841, 315, 362, 76995, 5039, 374, 430, 420, 1912, 574, 3345, 311, 279, 6371, 315, 5496, 1469, 288, 323, 12966, 323, 430, 420, 6371, 574, 11904, 1210, 362, 76995, 1306, 12673, 9462, 11046, 7091, 574, 26310, 7108, 520, 279, 21187, 3444, 61358, 9925, 275, 1088, 11, 3221, 89040, 11710, 11, 37766, 13, 16666, 25, 7388, 64530, 452, 65753, 11, 11064, 555, 26035, 735, 13884, 648, 220, 128257, 198 ]

2,711

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Background The TARGIT-A trial reported risk-adapted targeted intraoperative radiotherapy (TARGIT-IORT) during lumpectomy for breast cancer to be as effective as whole-breast external beam radiotherapy (EBRT). Here, we present further detailed analyses. Methods In total, 2298 women (≥45 years, invasive ductal carcinoma ≤3.5 cm, cN0–N1) were randomised. We investigated the impact of tumour size, grade, ER, PgR, HER2 and lymph node status on local recurrence-free survival, and of local recurrence on distant relapse and mortality. We analysed the predictive factors for recommending supplemental EBRT after TARGIT-IORT as part of the risk-adapted approach, using regression modelling. Non-breast cancer mortality was compared between TARGIT-IORT plus EBRT vs. EBRT. Results Local recurrence-free survival was no different between TARGIT-IORT and EBRT, in every tumour subgroup. Unlike in the EBRT arm, local recurrence in the TARGIT-IORT arm was not a predictor of a higher risk of distant relapse or death. Our new predictive tool for recommending supplemental EBRT after TARGIT-IORT is at . Non-breast cancer mortality was significantly lower in the TARGIT-IORT arm, even when patients received supplemental EBRT, HR 0.38 (95% CI 0.17–0.88) P = 0.0091. Conclusion TARGIT-IORT is as effective as EBRT in all subgroups. Local recurrence after TARGIT-IORT, unlike after EBRT, has a good prognosis. TARGIT-IORT might have a beneficial abscopal effect. Trial registration ISRCTN34086741 (21/7/2004), NCT00983684 (24/9/2009). Introduction Most patients with breast cancer are suitable for treatment with breast-conserving surgery and adjuvant radiotherapy, rather than total mastectomy. Based on the hypothesis that adjuvant radiotherapy for women with early breast cancer could be limited to the tumour bed and given immediately during breast-conserving surgery (lumpectomy), we developed the concept of TARGeted Intraoperative radioTherapy (TARGIT-IORT). 1 , 2 , 3 , 4 , 5 , 6 TARGIT-IORT aims to achieve an accurately-positioned and rapid form of tumour-bed irradiation, focussed on the target tissues alone, sparing normal tissues and organs such as heart, lung, skin and chest wall structures from unnecessary and potentially damaging radiation treatment. We designed the TARGIT-A randomised trial to test this concept by comparing risk-adapted TARGIT-IORT with conventional whole-breast external beam radiotherapy over several weeks (EBRT). 3 , 7 , 8 The study received ethics approval from the Joint University College London and University College London Hospital committees of ethics of human research (99/0307). The accrual was from March 2000 to June 2012. The long-term results of the trial are described separately and show that TARGIT-IORT is as effective as whole-breast external beam radiotherapy (EBRT) for all breast cancer outcomes, with a significant reduction in mortality from causes other than breast cancer. 9 The trial eligibility was not confined to low-risk patients: they needed to be 45 years or older, with invasive ductal carcinoma that was suitable for breast conservation and preferably less than 3.5 cm in size and unifocal on clinical examination and conventional imaging. Having a grade 3 cancer, involved nodes or higher risk receptor status, did not exclude the patient from participating. Therefore, a large number of patients in each category of higher risk were included, allowing meaningful subgroup analysis. In addition, the follow-up of the TARGIT-A trial was long, with a large number of patients having follow-up for at least 5 years ( n = 2048) and 10 years ( n = 741). So, the number of events for local recurrences and deaths after long-term follow-up were expected to be large enough to assess the prognostic significance of local recurrence. As specified in the protocol, treatment was given using a risk-adapted approach, which meant that patients allocated to receive TARGIT-IORT were recommended to also receive supplemental EBRT, if they were postoperatively found to have specific unsuspected tumour characteristics, in which case the TARGIT-IORT served as a tumour-bed boost. The protocol specified three such factors—an unexpected diagnosis of invasive lobular carcinoma, presence of extensive intraductal component (>25%) and positive margins. Pragmatically, each centre was allowed to pre-specify such criteria and they recorded them in the ‘treatment policy document’ before they started recruitment. Therefore, for an individual case, the use of supplemental EBRT depended on a combination of several factors discussed in the post-operative multidisciplinary team meeting (tumour board). Having known the use of supplemental EBRT within the trial (about 20% of cases) and with the knowledge of the tumour factors, a regression model could be created. This risk-adapted approach also offers an opportunity for another type of analysis investigating the mechanism of the difference we found in non-breast cancer mortality during the main analysis. 9 One needs to recognise that the use of supplemental EBRT after TARGIT-IORT was prompted by specific features of the primary breast cancer. Therefore, there should be no reason for the risk of non-breast cancer mortality to be different between patients who received TARGIT + EBRT vs. those who received EBRT. Since both groups received EBRT, and if the difference was because of EBRT toxicity alone, there should be no difference found in non-breast cancer mortality in this comparison. This paper addresses four important aspects of the trial of TARGIT-IORT vs. EBRT, in which 2298 patients were randomised after their needle biopsy and before any surgical excision of cancer to receive either risk-adapted TARGIT-IORT delivered during the initial excision of cancer, or EBRT. These are: (a) outcome as per well-recognised tumour subgroups, (b) prognostic importance of local recurrence, (c) a predictive model for the use of supplemental EBRT after TARGIT-IORT and (d) an exploration seeking explanation for the differences in non-breast cancer mortality found between the two randomised arms. Methods Data from the TARGIT-A trial ( n = 2298) comparing risk-adapted TARGIT-IORT given during lumpectomy vs. EBRT were used for these analyses. 9 The TARGIT-A trial protocol ( ), including the details of eligibility, methodology and statistical methods, sample size calculations, the process of random allocation, has been previously described. 7 , 8 , 9 Eligible patients diagnosed with invasive malignancy by needle biopsy were randomly assigned before their surgery, in a 1:1 ratio, to receive either a risk-adapted approach using single-dose TARGIT-IORT or EBRT as per standard schedules over several weeks, with", "role": "user" }, { "content": "A breast cancer therapy that requires just one shot of radiotherapy is as effective as traditional radiotherapy, and avoids potential damage to nearby organs, according to a paper by UCL experts. The results, published in the British Journal of Cancer, mean that eight out of ten patients who receive the treatment, TARGIT-IORT, will not need a long course of post-operative external beam radiotherapy (EBRT). These results strengthen and expand previously published outcomes. Patients who received the treatment are less likely to go on to experience fatal cardiovascular disease such as heart attacks, lung problems or other cancers. As well as avoiding scattered radiation from EBRT that can damage nearby vital organs, delivering TARGIT-IORT during the lumpectomy procedure seems to lower the likelihood of death if patients do go on to develop cardiovascular disease, protecting in a drug-like manner. This was the case even when EBRT was also given post-operatively, and is thought to be because the treatment changes the microenvironment in the lumpectomy wound. The researchers say that delivering radiation immediately to the site where the tumor was can reduce the adverse effects of surgical trauma make the site less conducive for cancer growth and could have an 'abscopal' (distant) effect. This is where a treatment such as radiotherapy has a positive effect on tissue away from the operation site, which is increasingly recognized as a beneficial immunological action. Previous studies have shown that the treatment has fewer radiation-related side effects compared with conventional whole breast radiotherapy, with less pain, a superior cosmetic outcome with fewer changes to the breast as a whole and a better quality of life. Lead author Professor Jayant Vaidya (UCL Surgery & Interventional Science) said: \"With TARGIT-IORT, women can have their surgery and radiation treatment for breast cancer at the same time. This reduces the amount of time spent in hospital and enables women to recover more quickly, meaning they can get back to their lives more quickly.\" TARGIT-IORT is delivered immediately after tumor removal (lumpectomy), and under the same anesthetic, via a small ball-shaped device placed inside the breast, directly where the cancer had been. The single-dose treatment lasts for around 20-30 minutes and replaces the need for extra hospital visits in eight out of ten cases. Further tumor subgroup analysis also found that there was a significant overall survival benefit with TARGIT-IORT in patients with grade 1 or 2 cancer. Professor Vaidya added: \"These new results make it clear that the TARGIT-IORT is effective in all tumor subgroups of invasive duct cancer, the most common type of breast cancer. Our new online tool can help clinicians make a decision about additional radiotherapy (recommended in a small proportion of cases) for each individual patient. \"The finding that fewer deaths are from the avoidance of scattered radiation and the possible abscopal effect of TARGIT-IORT is important and should fuel further research, opening doors to new treatments.\" For the clinical trial, which started in March 2000, 2,298 women aged 45 or over with invasive breast cancer and a tumor up to 3.5cm in diameter were randomly assigned to receive either TARGIT-IORT during lumpectomy or post-operative EBRT. The trial was designed and run from UCL, involved 32 hospitals and medical centers in ten countries: the UK, France, Germany, Italy, Norway, Poland, Switzerland, the U.S., Canada and Australia. Professor Michael Baum (UCL Surgery & Interventional Science) said: These results are the highest level of evidence proving not only the effectiveness of TARGIT-IORT but confirming that it avoids deaths from other causes. \"The new data is biologically very interesting and the new tools will make its application in routine clinical practice much easier. I am pleased that it will benefit thousands of breast cancer patients around the world.\" Professor Jeffrey S Tobias (Professor of Clinical Oncology, UCL and UCLH) said: With \"TARGIT-IORT, the majority of patients presenting with early localized breast cancer will never need any further radiotherapy. \"They will avoid all the side effects of whole breast radiotherapy. The chance of remaining free of local recurrence (in the breast itself) is the same as with traditional treatment, but our new analysis shows that even if they do get a local relapse, it will not detract from an excellent prognosis—as good as not having a relapse—a rather different state of affairs from the more serious outlook if this were to happen after EBRT.\" To date, 45,000 patients in 260 centers in 38 countries have received TARGIT-IORT). The clinicians hope that following the latest results, more patients can be offered the treatment both in the UK and around the world instead of EBRT. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Background The TARGIT-A trial reported risk-adapted targeted intraoperative radiotherapy (TARGIT-IORT) during lumpectomy for breast cancer to be as effective as whole-breast external beam radiotherapy (EBRT). Here, we present further detailed analyses. Methods In total, 2298 women (≥45 years, invasive ductal carcinoma ≤3.5 cm, cN0–N1) were randomised. We investigated the impact of tumour size, grade, ER, PgR, HER2 and lymph node status on local recurrence-free survival, and of local recurrence on distant relapse and mortality. We analysed the predictive factors for recommending supplemental EBRT after TARGIT-IORT as part of the risk-adapted approach, using regression modelling. Non-breast cancer mortality was compared between TARGIT-IORT plus EBRT vs. EBRT. Results Local recurrence-free survival was no different between TARGIT-IORT and EBRT, in every tumour subgroup. Unlike in the EBRT arm, local recurrence in the TARGIT-IORT arm was not a predictor of a higher risk of distant relapse or death. Our new predictive tool for recommending supplemental EBRT after TARGIT-IORT is at . Non-breast cancer mortality was significantly lower in the TARGIT-IORT arm, even when patients received supplemental EBRT, HR 0.38 (95% CI 0.17–0.88) P = 0.0091. Conclusion TARGIT-IORT is as effective as EBRT in all subgroups. Local recurrence after TARGIT-IORT, unlike after EBRT, has a good prognosis. TARGIT-IORT might have a beneficial abscopal effect. Trial registration ISRCTN34086741 (21/7/2004), NCT00983684 (24/9/2009). Introduction Most patients with breast cancer are suitable for treatment with breast-conserving surgery and adjuvant radiotherapy, rather than total mastectomy. Based on the hypothesis that adjuvant radiotherapy for women with early breast cancer could be limited to the tumour bed and given immediately during breast-conserving surgery (lumpectomy), we developed the concept of TARGeted Intraoperative radioTherapy (TARGIT-IORT). 1 , 2 , 3 , 4 , 5 , 6 TARGIT-IORT aims to achieve an accurately-positioned and rapid form of tumour-bed irradiation, focussed on the target tissues alone, sparing normal tissues and organs such as heart, lung, skin and chest wall structures from unnecessary and potentially damaging radiation treatment. We designed the TARGIT-A randomised trial to test this concept by comparing risk-adapted TARGIT-IORT with conventional whole-breast external beam radiotherapy over several weeks (EBRT). 3 , 7 , 8 The study received ethics approval from the Joint University College London and University College London Hospital committees of ethics of human research (99/0307). The accrual was from March 2000 to June 2012. The long-term results of the trial are described separately and show that TARGIT-IORT is as effective as whole-breast external beam radiotherapy (EBRT) for all breast cancer outcomes, with a significant reduction in mortality from causes other than breast cancer. 9 The trial eligibility was not confined to low-risk patients: they needed to be 45 years or older, with invasive ductal carcinoma that was suitable for breast conservation and preferably less than 3.5 cm in size and unifocal on clinical examination and conventional imaging. Having a grade 3 cancer, involved nodes or higher risk receptor status, did not exclude the patient from participating. Therefore, a large number of patients in each category of higher risk were included, allowing meaningful subgroup analysis. In addition, the follow-up of the TARGIT-A trial was long, with a large number of patients having follow-up for at least 5 years ( n = 2048) and 10 years ( n = 741). So, the number of events for local recurrences and deaths after long-term follow-up were expected to be large enough to assess the prognostic significance of local recurrence. As specified in the protocol, treatment was given using a risk-adapted approach, which meant that patients allocated to receive TARGIT-IORT were recommended to also receive supplemental EBRT, if they were postoperatively found to have specific unsuspected tumour characteristics, in which case the TARGIT-IORT served as a tumour-bed boost. The protocol specified three such factors—an unexpected diagnosis of invasive lobular carcinoma, presence of extensive intraductal component (>25%) and positive margins. Pragmatically, each centre was allowed to pre-specify such criteria and they recorded them in the ‘treatment policy document’ before they started recruitment. Therefore, for an individual case, the use of supplemental EBRT depended on a combination of several factors discussed in the post-operative multidisciplinary team meeting (tumour board). Having known the use of supplemental EBRT within the trial (about 20% of cases) and with the knowledge of the tumour factors, a regression model could be created. This risk-adapted approach also offers an opportunity for another type of analysis investigating the mechanism of the difference we found in non-breast cancer mortality during the main analysis. 9 One needs to recognise that the use of supplemental EBRT after TARGIT-IORT was prompted by specific features of the primary breast cancer. Therefore, there should be no reason for the risk of non-breast cancer mortality to be different between patients who received TARGIT + EBRT vs. those who received EBRT. Since both groups received EBRT, and if the difference was because of EBRT toxicity alone, there should be no difference found in non-breast cancer mortality in this comparison. This paper addresses four important aspects of the trial of TARGIT-IORT vs. EBRT, in which 2298 patients were randomised after their needle biopsy and before any surgical excision of cancer to receive either risk-adapted TARGIT-IORT delivered during the initial excision of cancer, or EBRT. These are: (a) outcome as per well-recognised tumour subgroups, (b) prognostic importance of local recurrence, (c) a predictive model for the use of supplemental EBRT after TARGIT-IORT and (d) an exploration seeking explanation for the differences in non-breast cancer mortality found between the two randomised arms. Methods Data from the TARGIT-A trial ( n = 2298) comparing risk-adapted TARGIT-IORT given during lumpectomy vs. EBRT were used for these analyses. 9 The TARGIT-A trial protocol ( ), including the details of eligibility, methodology and statistical methods, sample size calculations, the process of random allocation, has been previously described. 7 , 8 , 9 Eligible patients diagnosed with invasive malignancy by needle biopsy were randomly assigned before their surgery, in a 1:1 ratio, to receive either a risk-adapted approach using single-dose TARGIT-IORT or EBRT as per standard schedules over several weeks, with<|im_end|> <|im_start|>assistant A breast cancer therapy that requires just one shot of radiotherapy is as effective as traditional radiotherapy, and avoids potential damage to nearby organs, according to a paper by UCL experts. The results, published in the British Journal of Cancer, mean that eight out of ten patients who receive the treatment, TARGIT-IORT, will not need a long course of post-operative external beam radiotherapy (EBRT). These results strengthen and expand previously published outcomes. Patients who received the treatment are less likely to go on to experience fatal cardiovascular disease such as heart attacks, lung problems or other cancers. As well as avoiding scattered radiation from EBRT that can damage nearby vital organs, delivering TARGIT-IORT during the lumpectomy procedure seems to lower the likelihood of death if patients do go on to develop cardiovascular disease, protecting in a drug-like manner. This was the case even when EBRT was also given post-operatively, and is thought to be because the treatment changes the microenvironment in the lumpectomy wound. The researchers say that delivering radiation immediately to the site where the tumor was can reduce the adverse effects of surgical trauma make the site less conducive for cancer growth and could have an 'abscopal' (distant) effect. This is where a treatment such as radiotherapy has a positive effect on tissue away from the operation site, which is increasingly recognized as a beneficial immunological action. Previous studies have shown that the treatment has fewer radiation-related side effects compared with conventional whole breast radiotherapy, with less pain, a superior cosmetic outcome with fewer changes to the breast as a whole and a better quality of life. Lead author Professor Jayant Vaidya (UCL Surgery & Interventional Science) said: "With TARGIT-IORT, women can have their surgery and radiation treatment for breast cancer at the same time. This reduces the amount of time spent in hospital and enables women to recover more quickly, meaning they can get back to their lives more quickly." TARGIT-IORT is delivered immediately after tumor removal (lumpectomy), and under the same anesthetic, via a small ball-shaped device placed inside the breast, directly where the cancer had been. The single-dose treatment lasts for around 20-30 minutes and replaces the need for extra hospital visits in eight out of ten cases. Further tumor subgroup analysis also found that there was a significant overall survival benefit with TARGIT-IORT in patients with grade 1 or 2 cancer. Professor Vaidya added: "These new results make it clear that the TARGIT-IORT is effective in all tumor subgroups of invasive duct cancer, the most common type of breast cancer. Our new online tool can help clinicians make a decision about additional radiotherapy (recommended in a small proportion of cases) for each individual patient. "The finding that fewer deaths are from the avoidance of scattered radiation and the possible abscopal effect of TARGIT-IORT is important and should fuel further research, opening doors to new treatments." For the clinical trial, which started in March 2000, 2,298 women aged 45 or over with invasive breast cancer and a tumor up to 3.5cm in diameter were randomly assigned to receive either TARGIT-IORT during lumpectomy or post-operative EBRT. The trial was designed and run from UCL, involved 32 hospitals and medical centers in ten countries: the UK, France, Germany, Italy, Norway, Poland, Switzerland, the U.S., Canada and Australia. Professor Michael Baum (UCL Surgery & Interventional Science) said: These results are the highest level of evidence proving not only the effectiveness of TARGIT-IORT but confirming that it avoids deaths from other causes. "The new data is biologically very interesting and the new tools will make its application in routine clinical practice much easier. I am pleased that it will benefit thousands of breast cancer patients around the world." Professor Jeffrey S Tobias (Professor of Clinical Oncology, UCL and UCLH) said: With "TARGIT-IORT, the majority of patients presenting with early localized breast cancer will never need any further radiotherapy. "They will avoid all the side effects of whole breast radiotherapy. The chance of remaining free of local recurrence (in the breast itself) is the same as with traditional treatment, but our new analysis shows that even if they do get a local relapse, it will not detract from an excellent prognosis—as good as not having a relapse—a rather different state of affairs from the more serious outlook if this were to happen after EBRT." To date, 45,000 patients in 260 centers in 38 countries have received TARGIT-IORT). The clinicians hope that following the latest results, more patients can be offered the treatment both in the UK and around the world instead of EBRT. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 25837, 578, 350, 7734, 964, 6830, 9269, 5068, 5326, 26831, 2756, 291, 17550, 50938, 43719, 9063, 46755, 320, 51, 7734, 964, 22197, 2938, 8, 2391, 41263, 1002, 5650, 369, 17659, 9572, 311, 387, 439, 7524, 439, 4459, 93008, 561, 9434, 24310, 9063, 46755, 320, 8428, 5463, 570, 5810, 11, 584, 3118, 4726, 11944, 29060, 13, 19331, 763, 2860, 11, 220, 14378, 23, 3278, 320, 120156, 1774, 1667, 11, 53354, 45339, 278, 89468, 38394, 18, 13, 20, 10166, 11, 272, 45, 15, 4235, 45, 16, 8, 1051, 4288, 4147, 13, 1226, 27313, 279, 5536, 315, 15756, 414, 1404, 11, 12239, 11, 27590, 11, 98365, 49, 11, 16019, 17, 323, 43745, 2494, 2704, 389, 2254, 76293, 12862, 20237, 11, 323, 315, 2254, 76293, 389, 29827, 1375, 7629, 323, 29528, 13, 1226, 67458, 279, 60336, 9547, 369, 65774, 69051, 50242, 5463, 1306, 350, 7734, 964, 22197, 2938, 439, 961, 315, 279, 5326, 26831, 2756, 291, 5603, 11, 1701, 31649, 61966, 13, 11842, 93008, 561, 9572, 29528, 574, 7863, 1990, 350, 7734, 964, 22197, 2938, 5636, 50242, 5463, 6296, 13, 50242, 5463, 13, 18591, 8949, 76293, 12862, 20237, 574, 912, 2204, 1990, 350, 7734, 964, 22197, 2938, 323, 50242, 5463, 11, 304, 1475, 15756, 414, 81215, 13, 27140, 304, 279, 50242, 5463, 6916, 11, 2254, 76293, 304, 279, 350, 7734, 964, 22197, 2938, 6916, 574, 539, 264, 62254, 315, 264, 5190, 5326, 315, 29827, 1375, 7629, 477, 4648, 13, 5751, 502, 60336, 5507, 369, 65774, 69051, 50242, 5463, 1306, 350, 7734, 964, 22197, 2938, 374, 520, 662, 11842, 93008, 561, 9572, 29528, 574, 12207, 4827, 304, 279, 350, 7734, 964, 22197, 2938, 6916, 11, 1524, 994, 6978, 4036, 69051, 50242, 5463, 11, 23096, 220, 15, 13, 1987, 320, 2721, 4, 21351, 220, 15, 13, 1114, 4235, 15, 13, 2421, 8, 393, 284, 220, 15, 13, 13858, 16, 13, 74977, 350, 7734, 964, 22197, 2938, 374, 439, 7524, 439, 50242, 5463, 304, 682, 1207, 17171, 13, 8949, 76293, 1306, 350, 7734, 964, 22197, 2938, 11, 20426, 1306, 50242, 5463, 11, 706, 264, 1695, 95350, 13, 350, 7734, 964, 22197, 2938, 2643, 617, 264, 24629, 671, 2445, 58079, 2515, 13, 41574, 12506, 3507, 75936, 45, 13679, 26013, 3174, 320, 1691, 14, 22, 14, 1049, 19, 705, 452, 1182, 13858, 25192, 5833, 320, 1187, 14, 24, 14, 1049, 24, 570, 29438, 7648, 6978, 449, 17659, 9572, 527, 14791, 369, 6514, 449, 17659, 69604, 20073, 15173, 323, 1008, 8783, 77282, 9063, 46755, 11, 4856, 1109, 2860, 19218, 72783, 13, 20817, 389, 279, 31178, 430, 1008, 8783, 77282, 9063, 46755, 369, 3278, 449, 4216, 17659, 9572, 1436, 387, 7347, 311, 279, 15756, 414, 4950, 323, 2728, 7214, 2391, 17659, 69604, 20073, 15173, 320, 108606, 1002, 5650, 705, 584, 8040, 279, 7434, 315, 75674, 1991, 291, 763, 2221, 43719, 9063, 1016, 261, 9864, 320, 51, 7734, 964, 22197, 2938, 570, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 350, 7734, 964, 22197, 2938, 22262, 311, 11322, 459, 30357, 34624, 291, 323, 11295, 1376, 315, 15756, 414, 49607, 76327, 367, 11, 8413, 59942, 389, 279, 2218, 39881, 7636, 11, 96055, 4725, 39881, 323, 36853, 1778, 439, 4851, 11, 21271, 11, 6930, 323, 15489, 7147, 14726, 505, 26225, 323, 13893, 34446, 25407, 6514, 13, 1226, 6319, 279, 350, 7734, 964, 6830, 4288, 4147, 9269, 311, 1296, 420, 7434, 555, 27393, 5326, 26831, 2756, 291, 350, 7734, 964, 22197, 2938, 449, 21349, 4459, 93008, 561, 9434, 24310, 9063, 46755, 927, 3892, 5672, 320, 8428, 5463, 570, 220, 18, 1174, 220, 22, 1174, 220, 23, 578, 4007, 4036, 32008, 14765, 505, 279, 30833, 3907, 9304, 7295, 323, 3907, 9304, 7295, 15429, 42547, 315, 32008, 315, 3823, 3495, 320, 1484, 14, 14649, 22, 570, 578, 86659, 940, 574, 505, 5587, 220, 1049, 15, 311, 5651, 220, 679, 17, 13, 578, 1317, 9860, 3135, 315, 279, 9269, 527, 7633, 26214, 323, 1501, 430, 350, 7734, 964, 22197, 2938, 374, 439, 7524, 439, 4459, 93008, 561, 9434, 24310, 9063, 46755, 320, 8428, 5463, 8, 369, 682, 17659, 9572, 20124, 11, 449, 264, 5199, 14278, 304, 29528, 505, 11384, 1023, 1109, 17659, 9572, 13, 220, 24, 578, 9269, 41734, 574, 539, 45408, 311, 3428, 46570, 6978, 25, 814, 4460, 311, 387, 220, 1774, 1667, 477, 9191, 11, 449, 53354, 45339, 278, 89468, 430, 574, 14791, 369, 17659, 29711, 323, 52754, 2753, 1109, 220, 18, 13, 20, 10166, 304, 1404, 323, 653, 333, 3768, 389, 14830, 24481, 323, 21349, 32758, 13, 20636, 264, 12239, 220, 18, 9572, 11, 6532, 7954, 477, 5190, 5326, 35268, 2704, 11, 1550, 539, 22429, 279, 8893, 505, 24435, 13, 15636, 11, 264, 3544, 1396, 315, 6978, 304, 1855, 5699, 315, 5190, 5326, 1051, 5343, 11, 10923, 23222, 81215, 6492, 13, 763, 5369, 11, 279, 1833, 5352, 315, 279, 350, 7734, 964, 6830, 9269, 574, 1317, 11, 449, 264, 3544, 1396, 315, 6978, 3515, 1833, 5352, 369, 520, 3325, 220, 20, 1667, 320, 308, 284, 220, 7854, 23, 8, 323, 220, 605, 1667, 320, 308, 284, 220, 25021, 570, 2100, 11, 279, 1396, 315, 4455, 369, 2254, 1421, 34346, 323, 16779, 1306, 1317, 9860, 1833, 5352, 1051, 3685, 311, 387, 3544, 3403, 311, 8720, 279, 63903, 537, 292, 26431, 315, 2254, 76293, 13, 1666, 5300, 304, 279, 11766, 11, 6514, 574, 2728, 1701, 264, 5326, 26831, 2756, 291, 5603, 11, 902, 8967, 430, 6978, 20816, 311, 5371, 350, 7734, 964, 22197, 2938, 1051, 11349, 311, 1101, 5371, 69051, 50242, 5463, 11, 422, 814, 1051, 1772, 3376, 8046, 1766, 311, 617, 3230, 92651, 4136, 15756, 414, 17910, 11, 304, 902, 1162, 279, 350, 7734, 964, 22197, 2938, 10434, 439, 264, 15756, 414, 49607, 7916, 13, 578, 11766, 5300, 2380, 1778, 9547, 85366, 16907, 23842, 315, 53354, 41253, 1299, 89468, 11, 9546, 315, 16781, 10805, 329, 670, 278, 3777, 77952, 914, 11587, 323, 6928, 37682, 13, 2394, 351, 76, 7167, 11, 1855, 12541, 574, 5535, 311, 864, 58894, 1463, 1778, 13186, 323, 814, 12715, 1124, 304, 279, 3451, 83, 35320, 4947, 2246, 529, 1603, 814, 3940, 34102, 13, 15636, 11, 369, 459, 3927, 1162, 11, 279, 1005, 315, 69051, 50242, 5463, 79101, 389, 264, 10824, 315, 3892, 9547, 14407, 304, 279, 1772, 90093, 64486, 3510, 44550, 2128, 6574, 320, 83, 372, 414, 4580, 570, 20636, 3967, 279, 1005, 315, 69051, 50242, 5463, 2949, 279, 9269, 320, 9274, 220, 508, 4, 315, 5157, 8, 323, 449, 279, 6677, 315, 279, 15756, 414, 9547, 11, 264, 31649, 1646, 1436, 387, 3549, 13, 1115, 5326, 26831, 2756, 291, 5603, 1101, 6209, 459, 6776, 369, 2500, 955, 315, 6492, 24834, 279, 17383, 315, 279, 6811, 584, 1766, 304, 2536, 93008, 561, 9572, 29528, 2391, 279, 1925, 6492, 13, 220, 24, 3861, 3966, 311, 44917, 430, 279, 1005, 315, 69051, 50242, 5463, 1306, 350, 7734, 964, 22197, 2938, 574, 29746, 555, 3230, 4519, 315, 279, 6156, 17659, 9572, 13, 15636, 11, 1070, 1288, 387, 912, 2944, 369, 279, 5326, 315, 2536, 93008, 561, 9572, 29528, 311, 387, 2204, 1990, 6978, 889, 4036, 350, 7734, 964, 489, 50242, 5463, 6296, 13, 1884, 889, 4036, 50242, 5463, 13, 8876, 2225, 5315, 4036, 50242, 5463, 11, 323, 422, 279, 6811, 574, 1606, 315, 50242, 5463, 58011, 7636, 11, 1070, 1288, 387, 912, 6811, 1766, 304, 2536, 93008, 561, 9572, 29528, 304, 420, 12593, 13, 1115, 5684, 14564, 3116, 3062, 13878, 315, 279, 9269, 315, 350, 7734, 964, 22197, 2938, 6296, 13, 50242, 5463, 11, 304, 902, 220, 14378, 23, 6978, 1051, 4288, 4147, 1306, 872, 31409, 99647, 323, 1603, 904, 34933, 3521, 1854, 315, 9572, 311, 5371, 3060, 5326, 26831, 2756, 291, 350, 7734, 964, 22197, 2938, 12886, 2391, 279, 2926, 3521, 1854, 315, 9572, 11, 477, 50242, 5463, 13, 4314, 527, 25, 320, 64, 8, 15632, 439, 824, 1664, 12, 34551, 4147, 15756, 414, 1207, 17171, 11, 320, 65, 8, 63903, 537, 292, 12939, 315, 2254, 76293, 11, 320, 66, 8, 264, 60336, 1646, 369, 279, 1005, 315, 69051, 50242, 5463, 1306, 350, 7734, 964, 22197, 2938, 323, 320, 67, 8, 459, 27501, 11125, 16540, 369, 279, 12062, 304, 2536, 93008, 561, 9572, 29528, 1766, 1990, 279, 1403, 4288, 4147, 11977, 13, 19331, 2956, 505, 279, 350, 7734, 964, 6830, 9269, 320, 308, 284, 220, 14378, 23, 8, 27393, 5326, 26831, 2756, 291, 350, 7734, 964, 22197, 2938, 2728, 2391, 41263, 1002, 5650, 6296, 13, 50242, 5463, 1051, 1511, 369, 1521, 29060, 13, 220, 24, 578, 350, 7734, 964, 6830, 9269, 11766, 320, 7026, 2737, 279, 3649, 315, 41734, 11, 38152, 323, 29564, 5528, 11, 6205, 1404, 29217, 11, 279, 1920, 315, 4288, 24691, 11, 706, 1027, 8767, 7633, 13, 220, 22, 1174, 220, 23, 1174, 220, 24, 69124, 1260, 6978, 29704, 449, 53354, 60327, 6709, 555, 31409, 99647, 1051, 27716, 12893, 1603, 872, 15173, 11, 304, 264, 220, 16, 25, 16, 11595, 11, 311, 5371, 3060, 264, 5326, 26831, 2756, 291, 5603, 1701, 3254, 1773, 974, 350, 7734, 964, 22197, 2938, 477, 50242, 5463, 439, 824, 5410, 37869, 927, 3892, 5672, 11, 449, 128257, 198, 128256, 78191, 198, 32, 17659, 9572, 15419, 430, 7612, 1120, 832, 6689, 315, 9063, 46755, 374, 439, 7524, 439, 8776, 9063, 46755, 11, 323, 55952, 4754, 5674, 311, 14373, 36853, 11, 4184, 311, 264, 5684, 555, 549, 3218, 11909, 13, 578, 3135, 11, 4756, 304, 279, 8013, 10139, 315, 26211, 11, 3152, 430, 8223, 704, 315, 5899, 6978, 889, 5371, 279, 6514, 11, 350, 7734, 964, 22197, 2938, 11, 690, 539, 1205, 264, 1317, 3388, 315, 1772, 90093, 9434, 24310, 9063, 46755, 320, 8428, 5463, 570, 4314, 3135, 20259, 323, 9407, 8767, 4756, 20124, 13, 44430, 889, 4036, 279, 6514, 527, 2753, 4461, 311, 733, 389, 311, 3217, 19094, 41713, 8624, 1778, 439, 4851, 8951, 11, 21271, 5435, 477, 1023, 51423, 13, 1666, 1664, 439, 31526, 38067, 25407, 505, 50242, 5463, 430, 649, 5674, 14373, 16595, 36853, 11, 24944, 350, 7734, 964, 22197, 2938, 2391, 279, 41263, 1002, 5650, 10537, 5084, 311, 4827, 279, 29736, 315, 4648, 422, 6978, 656, 733, 389, 311, 2274, 41713, 8624, 11, 22973, 304, 264, 5623, 12970, 11827, 13, 1115, 574, 279, 1162, 1524, 994, 50242, 5463, 574, 1101, 2728, 1772, 59655, 8046, 11, 323, 374, 3463, 311, 387, 1606, 279, 6514, 4442, 279, 8162, 24175, 304, 279, 41263, 1002, 5650, 27653, 13, 578, 12074, 2019, 430, 24944, 25407, 7214, 311, 279, 2816, 1405, 279, 36254, 574, 649, 8108, 279, 31959, 6372, 315, 34933, 30988, 1304, 279, 2816, 2753, 95561, 369, 9572, 6650, 323, 1436, 617, 459, 364, 370, 2445, 58079, 6, 320, 67, 11451, 8, 2515, 13, 1115, 374, 1405, 264, 6514, 1778, 439, 9063, 46755, 706, 264, 6928, 2515, 389, 20438, 3201, 505, 279, 5784, 2816, 11, 902, 374, 15098, 15324, 439, 264, 24629, 33119, 5848, 1957, 13, 30013, 7978, 617, 6982, 430, 279, 6514, 706, 17162, 25407, 14228, 3185, 6372, 7863, 449, 21349, 4459, 17659, 9063, 46755, 11, 449, 2753, 6784, 11, 264, 16757, 46552, 15632, 449, 17162, 4442, 311, 279, 17659, 439, 264, 4459, 323, 264, 2731, 4367, 315, 2324, 13, 30982, 3229, 17054, 19455, 519, 650, 3864, 7911, 320, 52, 3218, 48190, 612, 71678, 278, 10170, 8, 1071, 25, 330, 2409, 350, 7734, 964, 22197, 2938, 11, 3278, 649, 617, 872, 15173, 323, 25407, 6514, 369, 17659, 9572, 520, 279, 1890, 892, 13, 1115, 26338, 279, 3392, 315, 892, 7543, 304, 8952, 323, 20682, 3278, 311, 11993, 810, 6288, 11, 7438, 814, 649, 636, 1203, 311, 872, 6439, 810, 6288, 1210, 350, 7734, 964, 22197, 2938, 374, 12886, 7214, 1306, 36254, 17065, 320, 108606, 1002, 5650, 705, 323, 1234, 279, 1890, 459, 71109, 11, 4669, 264, 2678, 5041, 35831, 3756, 9277, 4871, 279, 17659, 11, 6089, 1405, 279, 9572, 1047, 1027, 13, 578, 3254, 1773, 974, 6514, 40758, 369, 2212, 220, 508, 12, 966, 4520, 323, 41800, 279, 1205, 369, 5066, 8952, 21728, 304, 8223, 704, 315, 5899, 5157, 13, 15903, 36254, 81215, 6492, 1101, 1766, 430, 1070, 574, 264, 5199, 8244, 20237, 8935, 449, 350, 7734, 964, 22197, 2938, 304, 6978, 449, 12239, 220, 16, 477, 220, 17, 9572, 13, 17054, 650, 3864, 7911, 3779, 25, 330, 9673, 502, 3135, 1304, 433, 2867, 430, 279, 350, 7734, 964, 22197, 2938, 374, 7524, 304, 682, 36254, 1207, 17171, 315, 53354, 45339, 9572, 11, 279, 1455, 4279, 955, 315, 17659, 9572, 13, 5751, 502, 2930, 5507, 649, 1520, 78545, 1304, 264, 5597, 922, 5217, 9063, 46755, 320, 86447, 304, 264, 2678, 21801, 315, 5157, 8, 369, 1855, 3927, 8893, 13, 330, 791, 9455, 430, 17162, 16779, 527, 505, 279, 65411, 315, 38067, 25407, 323, 279, 3284, 671, 2445, 58079, 2515, 315, 350, 7734, 964, 22197, 2938, 374, 3062, 323, 1288, 10633, 4726, 3495, 11, 8736, 14365, 311, 502, 22972, 1210, 1789, 279, 14830, 9269, 11, 902, 3940, 304, 5587, 220, 1049, 15, 11, 220, 17, 11, 17690, 3278, 20330, 220, 1774, 477, 927, 449, 53354, 17659, 9572, 323, 264, 36254, 709, 311, 220, 18, 13, 20, 6358, 304, 23899, 1051, 27716, 12893, 311, 5371, 3060, 350, 7734, 964, 22197, 2938, 2391, 41263, 1002, 5650, 477, 1772, 90093, 50242, 5463, 13, 578, 9269, 574, 6319, 323, 1629, 505, 549, 3218, 11, 6532, 220, 843, 24461, 323, 6593, 19169, 304, 5899, 5961, 25, 279, 6560, 11, 9822, 11, 10057, 11, 15704, 11, 32603, 11, 28702, 11, 30221, 11, 279, 549, 815, 2637, 7008, 323, 8494, 13, 17054, 8096, 83320, 320, 52, 3218, 48190, 612, 71678, 278, 10170, 8, 1071, 25, 4314, 3135, 527, 279, 8592, 2237, 315, 6029, 39858, 539, 1193, 279, 27375, 315, 350, 7734, 964, 22197, 2938, 719, 50096, 430, 433, 55952, 16779, 505, 1023, 11384, 13, 330, 791, 502, 828, 374, 6160, 30450, 1633, 7185, 323, 279, 502, 7526, 690, 1304, 1202, 3851, 304, 14348, 14830, 6725, 1790, 8831, 13, 358, 1097, 18949, 430, 433, 690, 8935, 9214, 315, 17659, 9572, 6978, 2212, 279, 1917, 1210, 17054, 42107, 328, 80102, 320, 48120, 315, 33135, 77854, 2508, 11, 549, 3218, 323, 549, 3218, 39, 8, 1071, 25, 3161, 330, 51, 7734, 964, 22197, 2938, 11, 279, 8857, 315, 6978, 32644, 449, 4216, 44589, 17659, 9572, 690, 2646, 1205, 904, 4726, 9063, 46755, 13, 330, 7009, 690, 5766, 682, 279, 3185, 6372, 315, 4459, 17659, 9063, 46755, 13, 578, 6140, 315, 9861, 1949, 315, 2254, 76293, 320, 258, 279, 17659, 5196, 8, 374, 279, 1890, 439, 449, 8776, 6514, 11, 719, 1057, 502, 6492, 5039, 430, 1524, 422, 814, 656, 636, 264, 2254, 1375, 7629, 11, 433, 690, 539, 35453, 533, 505, 459, 9250, 95350, 60654, 1695, 439, 539, 3515, 264, 1375, 7629, 29096, 4856, 2204, 1614, 315, 22747, 505, 279, 810, 6129, 36721, 422, 420, 1051, 311, 3621, 1306, 50242, 5463, 1210, 2057, 2457, 11, 220, 1774, 11, 931, 6978, 304, 220, 11387, 19169, 304, 220, 1987, 5961, 617, 4036, 350, 7734, 964, 22197, 2938, 570, 578, 78545, 3987, 430, 2768, 279, 5652, 3135, 11, 810, 6978, 649, 387, 9076, 279, 6514, 2225, 304, 279, 6560, 323, 2212, 279, 1917, 4619, 315, 50242, 5463, 13, 220, 128257, 198 ]

2,512

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Chronic erosion in Hawaii causes beach loss, damages homes and infrastructure, and endangers critical habitat. These problems will likely worsen with increased sea level rise (SLR). We forecast future coastal change by combining historical shoreline trends with projected accelerations in SLR (IPCC RCP8.5) using the Davidson-Arnott profile model. The resulting erosion hazard zones are overlain on aerial photos and other GIS layers to provide a tool for identifying assets exposed to future coastal erosion. We estimate rates and distances of shoreline change for ten study sites across the Hawaiian Islands. Excluding one beach (Kailua) historically dominated by accretion, approximately 92 and 96 % of the shorelines studied are projected to retreat by 2050 and 2100, respectively. Most projections (~80 %) range between 1–24 m of landward movement by 2050 (relative to 2005) and 4–60 m by 2100, except at Kailua which is projected to begin receding around 2050. Compared to projections based only on historical extrapolation, those that include accelerated SLR have an average 5.4 ± 0.4 m (±standard deviation of the average) of additional shoreline recession by 2050 and 18.7 ± 1.5 m of additional recession by 2100. Due to increasing SLR, the average shoreline recession by 2050 is nearly twice the historical extrapolation, and by 2100 it is nearly 2.5 times the historical extrapolation. Our approach accounts for accretion and long-term sediment processes (based on historical trends) in projecting future shoreline position. However, it does not incorporate potential future changes in nearshore hydrodynamics associated with accelerated SLR. Access provided by DEAL DE / Springer Compact Clearingstelle Uni Freiburg _ Working on a manuscript? Avoid the common mistakes 1 Introduction Coastal erosion negatively affects Hawaii’s tourism-based economy, limits public beach access and cultural practices, and damages homes, infrastructure, and critical habitats for endangered wildlife. Fletcher et al. ( 2013 ) found that seventy percent of all sandy shoreline on the islands of Oahu, Maui, and Kauai are chronically eroding; nine percent of these shorelines were completely lost to erosion during their 80-year analysis period. As global mean sea level is predicted to rise dramatically over the next century (Church et al. 2013 ; Kopp et al. 2014 ), government officials, nonprofit groups, and property owners wonder how increased sea level rise (SLR) will affect their ongoing struggle to manage retreating shorelines. Tidal records indicate that the Hawaiian Islands of Maui, Oahu, and Kauai have experienced at least a century of relative SLR at rates from 1.50 to 2.32 mm/y. Romine et al. ( 2013 ) investigated shoreline trends on islands with different SLR rates and concluded that SLR is linked to coastal erosion in Hawaii. However, shoreline change rates around each island vary greatly (erosion rates up to −1.8 ± 0.3 m/year and accretion rates up to 1.7 ± 0.6 m/year; Romine and Fletcher 2013 ), where segments of erosion and accretion were separated by tens to hundreds of meters alongshore despite rather homogeneous island-wide SLR trends. This suggests that the influence of SLR on shoreline change is presently minor compared with sediment availability (sum of sources and sinks) related to human impacts and persistent physical processes such as eolian transport, cross-shore transport, and gradients in longshore sediment transport. Future accelerated SLR is expected to have an increased effect on coastal morphology (Stive 2004 ) and to promote erosion of numerous Hawaiian beaches (Romine et al. 2013 ). The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5; 2013) projects 0.52–0.98 m of SLR by 2100 relative to 1986–2005 for Representative Concentration Pathway (RCP) 8.5 (the “business as usual” scenario; Church et al. 2013 ). This gives a rate during 2080–2100 of 8–16 mm/year, up to an order of magnitude larger than the Honolulu tide gauge SLR rate (1.50 ± 0.25 mm/year; ) for the previous century (1905–2006) when the Honolulu SLR trend was similar to the estimated global mean trend (e.g., 1.7 ± 0.2 mm/year; Church and White 2011 ). The current IPCC projections may underestimate SLR because they do not include the results of recent studies indicating increased ice melt for Greenland (Helm et al. 2014 ) and West Antarctica (Joughin et al. 2014 ; Rignot et al. 2014 ). Sediment transport, and thus shoreline migration, is the result of multiple nonlinear processes that dynamically interact with existing morphology over a variety of time and spatial scales (Stive et al. 2002 ; Hanson et al. 2003 ). As a result of increased SLR, sediment-deficient low-lying coastal areas will experience enhanced erosion and inundation determined by sediment availability and local coastal slope. Beaches will be further shaped by changes in sediment transport patterns as a result of higher water levels over fringing reefs (Grady et al. 2013 ), climate-related modifications in reef geomorphology and sediment production (Perry et al. 2011 ), and changes in storminess and wave climate (Aucan et al. 2012 ). Numerical models have the potential to describe beach evolution more accurately than long-term trends, but often require data at spatial and temporal densities that are not available. Such methods are therefore difficult to apply to the multidecadal timescales that are the focus of this paper (Hanson et al. 2003 ). For baseline assessment over large coastal regions, it is therefore necessary to develop empirical methods that provide a first-order approximation of erosion exposure and its uncertainty. Communicating hazard uncertainty to coastal managers (Pilkey et al. 1993 ; Thieler et al. 2000 ; Pilkey and Cooper 2004 , etc.) enables them to make decisions based on levels of risk. It also helps coastal mangers understand that as new data become available, updated projections will replace old ones (Pilkey and Cooper 2004 ). Historical data are commonly used to provide long-term information on coastal erosion (Fig. 1 ), but extrapolating historical trends is insufficient given the projected accelerations in SLR. Hwang ( 2005 ) suggests multiplying the historical trend by a SLR adjustment factor, such as 10 %, and then extrapolating the adjusted trend. Although easy to implement, this approach does not allow for acceleration", "role": "user" }, { "content": "Chronic erosion dominates the sandy beaches of Hawai'i, causing beach loss as it damages homes, infrastructure and critical habitat. Researchers have long understood that global sea level rise will affect the rate of coastal erosion. However, new research from scientists at UH Mānoa and the state Department of Land and Natural Resources brings into clearer focus just how dramatically Hawai'i's beaches might change. For the study, published this week in Natural Hazards, the research team developed a simple model to assess future erosion hazards under higher sea levels – taking into account historical changes of Hawai'i shorelines and the projected acceleration of sea level rise reported from the Intergovernmental Panel on Climate Change (IPCC). The results indicate that coastal erosion of Hawai'i's beaches may double by mid-century. Like the majority of Hawaiʻi's sandy beaches, most shorelines at the 10 study sites on Kauaʻi, Oʻahu and Maui are currently retreating. If these beaches were to follow current trends, an average 20 to 40 feet of shoreline recession would be expected by 2050 and 2100, respectively. \"When we modeled future shoreline change with the increased rates of sea level rise (SLR) projected under the IPCC's 'business as usual' scenario, we found that increased SLR causes an average 16 to 20 feet of additional shoreline retreat by 2050, and an average of nearly 60 feet of additional retreat by 2100,\" said Tiffany Anderson, lead author and post-doctoral researcher at the UHM School of Ocean and Earth Science and Technology. \"This means that the average amount of shoreline recession roughly doubles by 2050 with increased SLR, compared to historical extrapolation alone. By 2100, it is nearly 2.5 times the historical extrapolation. Further, our results indicate that approximately 92% and 96% of the shorelines will be retreating by 2050 and 2100, respectively, except at Kailua, Oʻahu, which is projected to begin retreating by mid-century.\" The model accounts for accretion of sand onto beaches and long-term sediment processes in making projections of future shoreline position. As part of ongoing research, the resulting erosion hazard zones are overlain on aerial photos and other geographic layers in a geographic information system to provide a tool for identifying resources, infrastructure and property exposed to future coastal erosion. \"This study demonstrates a methodology that can be used by many shoreline communities to assess their exposure to coastal erosion resulting from the climate crisis,\" said Chip Fletcher, Associate Dean at the UHM School of Ocean and Earth Science and Technology and co-author of the paper. Mapping historical shoreline change provides useful data for assessing exposure to future erosion hazards, even if the rate of sea level rise changes in the future. The predicted increase in erosion will threaten thousands of homes, many miles of roadway and other assets in Hawai'i. Globally the asset exposure to erosion is enormous. \"With these new results, government agencies can begin to develop adaptation strategies, including new policies, for safely developing the shoreline,\" said Anderson. To further improve the estimates of climate impacts, the next step for the team of researchers will be to combine the new model with assessments of increased flooding by waves. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Chronic erosion in Hawaii causes beach loss, damages homes and infrastructure, and endangers critical habitat. These problems will likely worsen with increased sea level rise (SLR). We forecast future coastal change by combining historical shoreline trends with projected accelerations in SLR (IPCC RCP8.5) using the Davidson-Arnott profile model. The resulting erosion hazard zones are overlain on aerial photos and other GIS layers to provide a tool for identifying assets exposed to future coastal erosion. We estimate rates and distances of shoreline change for ten study sites across the Hawaiian Islands. Excluding one beach (Kailua) historically dominated by accretion, approximately 92 and 96 % of the shorelines studied are projected to retreat by 2050 and 2100, respectively. Most projections (~80 %) range between 1–24 m of landward movement by 2050 (relative to 2005) and 4–60 m by 2100, except at Kailua which is projected to begin receding around 2050. Compared to projections based only on historical extrapolation, those that include accelerated SLR have an average 5.4 ± 0.4 m (±standard deviation of the average) of additional shoreline recession by 2050 and 18.7 ± 1.5 m of additional recession by 2100. Due to increasing SLR, the average shoreline recession by 2050 is nearly twice the historical extrapolation, and by 2100 it is nearly 2.5 times the historical extrapolation. Our approach accounts for accretion and long-term sediment processes (based on historical trends) in projecting future shoreline position. However, it does not incorporate potential future changes in nearshore hydrodynamics associated with accelerated SLR. Access provided by DEAL DE / Springer Compact Clearingstelle Uni Freiburg _ Working on a manuscript? Avoid the common mistakes 1 Introduction Coastal erosion negatively affects Hawaii’s tourism-based economy, limits public beach access and cultural practices, and damages homes, infrastructure, and critical habitats for endangered wildlife. Fletcher et al. ( 2013 ) found that seventy percent of all sandy shoreline on the islands of Oahu, Maui, and Kauai are chronically eroding; nine percent of these shorelines were completely lost to erosion during their 80-year analysis period. As global mean sea level is predicted to rise dramatically over the next century (Church et al. 2013 ; Kopp et al. 2014 ), government officials, nonprofit groups, and property owners wonder how increased sea level rise (SLR) will affect their ongoing struggle to manage retreating shorelines. Tidal records indicate that the Hawaiian Islands of Maui, Oahu, and Kauai have experienced at least a century of relative SLR at rates from 1.50 to 2.32 mm/y. Romine et al. ( 2013 ) investigated shoreline trends on islands with different SLR rates and concluded that SLR is linked to coastal erosion in Hawaii. However, shoreline change rates around each island vary greatly (erosion rates up to −1.8 ± 0.3 m/year and accretion rates up to 1.7 ± 0.6 m/year; Romine and Fletcher 2013 ), where segments of erosion and accretion were separated by tens to hundreds of meters alongshore despite rather homogeneous island-wide SLR trends. This suggests that the influence of SLR on shoreline change is presently minor compared with sediment availability (sum of sources and sinks) related to human impacts and persistent physical processes such as eolian transport, cross-shore transport, and gradients in longshore sediment transport. Future accelerated SLR is expected to have an increased effect on coastal morphology (Stive 2004 ) and to promote erosion of numerous Hawaiian beaches (Romine et al. 2013 ). The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5; 2013) projects 0.52–0.98 m of SLR by 2100 relative to 1986–2005 for Representative Concentration Pathway (RCP) 8.5 (the “business as usual” scenario; Church et al. 2013 ). This gives a rate during 2080–2100 of 8–16 mm/year, up to an order of magnitude larger than the Honolulu tide gauge SLR rate (1.50 ± 0.25 mm/year; ) for the previous century (1905–2006) when the Honolulu SLR trend was similar to the estimated global mean trend (e.g., 1.7 ± 0.2 mm/year; Church and White 2011 ). The current IPCC projections may underestimate SLR because they do not include the results of recent studies indicating increased ice melt for Greenland (Helm et al. 2014 ) and West Antarctica (Joughin et al. 2014 ; Rignot et al. 2014 ). Sediment transport, and thus shoreline migration, is the result of multiple nonlinear processes that dynamically interact with existing morphology over a variety of time and spatial scales (Stive et al. 2002 ; Hanson et al. 2003 ). As a result of increased SLR, sediment-deficient low-lying coastal areas will experience enhanced erosion and inundation determined by sediment availability and local coastal slope. Beaches will be further shaped by changes in sediment transport patterns as a result of higher water levels over fringing reefs (Grady et al. 2013 ), climate-related modifications in reef geomorphology and sediment production (Perry et al. 2011 ), and changes in storminess and wave climate (Aucan et al. 2012 ). Numerical models have the potential to describe beach evolution more accurately than long-term trends, but often require data at spatial and temporal densities that are not available. Such methods are therefore difficult to apply to the multidecadal timescales that are the focus of this paper (Hanson et al. 2003 ). For baseline assessment over large coastal regions, it is therefore necessary to develop empirical methods that provide a first-order approximation of erosion exposure and its uncertainty. Communicating hazard uncertainty to coastal managers (Pilkey et al. 1993 ; Thieler et al. 2000 ; Pilkey and Cooper 2004 , etc.) enables them to make decisions based on levels of risk. It also helps coastal mangers understand that as new data become available, updated projections will replace old ones (Pilkey and Cooper 2004 ). Historical data are commonly used to provide long-term information on coastal erosion (Fig. 1 ), but extrapolating historical trends is insufficient given the projected accelerations in SLR. Hwang ( 2005 ) suggests multiplying the historical trend by a SLR adjustment factor, such as 10 %, and then extrapolating the adjusted trend. Although easy to implement, this approach does not allow for acceleration<|im_end|> <|im_start|>assistant Chronic erosion dominates the sandy beaches of Hawai'i, causing beach loss as it damages homes, infrastructure and critical habitat. Researchers have long understood that global sea level rise will affect the rate of coastal erosion. However, new research from scientists at UH Mānoa and the state Department of Land and Natural Resources brings into clearer focus just how dramatically Hawai'i's beaches might change. For the study, published this week in Natural Hazards, the research team developed a simple model to assess future erosion hazards under higher sea levels – taking into account historical changes of Hawai'i shorelines and the projected acceleration of sea level rise reported from the Intergovernmental Panel on Climate Change (IPCC). The results indicate that coastal erosion of Hawai'i's beaches may double by mid-century. Like the majority of Hawaiʻi's sandy beaches, most shorelines at the 10 study sites on Kauaʻi, Oʻahu and Maui are currently retreating. If these beaches were to follow current trends, an average 20 to 40 feet of shoreline recession would be expected by 2050 and 2100, respectively. "When we modeled future shoreline change with the increased rates of sea level rise (SLR) projected under the IPCC's 'business as usual' scenario, we found that increased SLR causes an average 16 to 20 feet of additional shoreline retreat by 2050, and an average of nearly 60 feet of additional retreat by 2100," said Tiffany Anderson, lead author and post-doctoral researcher at the UHM School of Ocean and Earth Science and Technology. "This means that the average amount of shoreline recession roughly doubles by 2050 with increased SLR, compared to historical extrapolation alone. By 2100, it is nearly 2.5 times the historical extrapolation. Further, our results indicate that approximately 92% and 96% of the shorelines will be retreating by 2050 and 2100, respectively, except at Kailua, Oʻahu, which is projected to begin retreating by mid-century." The model accounts for accretion of sand onto beaches and long-term sediment processes in making projections of future shoreline position. As part of ongoing research, the resulting erosion hazard zones are overlain on aerial photos and other geographic layers in a geographic information system to provide a tool for identifying resources, infrastructure and property exposed to future coastal erosion. "This study demonstrates a methodology that can be used by many shoreline communities to assess their exposure to coastal erosion resulting from the climate crisis," said Chip Fletcher, Associate Dean at the UHM School of Ocean and Earth Science and Technology and co-author of the paper. Mapping historical shoreline change provides useful data for assessing exposure to future erosion hazards, even if the rate of sea level rise changes in the future. The predicted increase in erosion will threaten thousands of homes, many miles of roadway and other assets in Hawai'i. Globally the asset exposure to erosion is enormous. "With these new results, government agencies can begin to develop adaptation strategies, including new policies, for safely developing the shoreline," said Anderson. To further improve the estimates of climate impacts, the next step for the team of researchers will be to combine the new model with assessments of increased flooding by waves. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 73782, 58097, 304, 28621, 11384, 11573, 4814, 11, 26186, 10632, 323, 14054, 11, 323, 842, 14381, 9200, 39646, 13, 4314, 5435, 690, 4461, 47293, 268, 449, 7319, 9581, 2237, 10205, 320, 8143, 49, 570, 1226, 18057, 3938, 35335, 2349, 555, 35271, 13970, 99164, 18845, 449, 28448, 14511, 811, 304, 17216, 49, 320, 3378, 3791, 432, 7269, 23, 13, 20, 8, 1701, 279, 54345, 6830, 36722, 1751, 5643, 1646, 13, 578, 13239, 58097, 31397, 26467, 527, 29204, 467, 389, 41884, 7397, 323, 1023, 83471, 13931, 311, 3493, 264, 5507, 369, 25607, 12032, 15246, 311, 3938, 35335, 58097, 13, 1226, 16430, 7969, 323, 27650, 315, 99164, 2349, 369, 5899, 4007, 6732, 4028, 279, 59103, 23028, 13, 1398, 11150, 832, 11573, 320, 42, 607, 4381, 8, 35901, 30801, 555, 1046, 2171, 290, 11, 13489, 220, 6083, 323, 220, 4161, 1034, 315, 279, 31284, 8128, 20041, 527, 28448, 311, 31114, 555, 220, 10866, 15, 323, 220, 8848, 15, 11, 15947, 13, 7648, 41579, 31857, 1490, 1034, 8, 2134, 1990, 220, 16, 4235, 1187, 296, 315, 4363, 1637, 7351, 555, 220, 10866, 15, 320, 21064, 311, 220, 1049, 20, 8, 323, 220, 19, 4235, 1399, 296, 555, 220, 8848, 15, 11, 3734, 520, 735, 607, 4381, 902, 374, 28448, 311, 3240, 1421, 16490, 2212, 220, 10866, 15, 13, 59813, 311, 41579, 3196, 1193, 389, 13970, 71462, 367, 11, 1884, 430, 2997, 49858, 17216, 49, 617, 459, 5578, 220, 20, 13, 19, 20903, 220, 15, 13, 19, 296, 320, 38121, 20885, 38664, 315, 279, 5578, 8, 315, 5217, 99164, 39621, 555, 220, 10866, 15, 323, 220, 972, 13, 22, 20903, 220, 16, 13, 20, 296, 315, 5217, 39621, 555, 220, 8848, 15, 13, 24586, 311, 7859, 17216, 49, 11, 279, 5578, 99164, 39621, 555, 220, 10866, 15, 374, 7154, 11157, 279, 13970, 71462, 367, 11, 323, 555, 220, 8848, 15, 433, 374, 7154, 220, 17, 13, 20, 3115, 279, 13970, 71462, 367, 13, 5751, 5603, 9815, 369, 1046, 2171, 290, 323, 1317, 9860, 59132, 11618, 320, 31039, 389, 13970, 18845, 8, 304, 82382, 3938, 99164, 2361, 13, 4452, 11, 433, 1587, 539, 33435, 4754, 3938, 4442, 304, 3221, 29526, 17055, 67, 51248, 5938, 449, 49858, 17216, 49, 13, 9742, 3984, 555, 26571, 3467, 611, 67915, 55882, 12292, 287, 267, 6853, 49966, 7730, 581, 5673, 721, 22938, 389, 264, 47913, 30, 35106, 279, 4279, 21294, 220, 16, 29438, 72658, 58097, 48291, 22223, 28621, 753, 32083, 6108, 8752, 11, 13693, 586, 11573, 2680, 323, 13042, 12659, 11, 323, 26186, 10632, 11, 14054, 11, 323, 9200, 71699, 369, 52356, 30405, 13, 69168, 1880, 453, 13, 320, 220, 679, 18, 883, 1766, 430, 71049, 3346, 315, 682, 68539, 99164, 389, 279, 30100, 315, 507, 27793, 11, 93550, 11, 323, 735, 2933, 2192, 527, 27076, 2740, 2781, 3785, 26, 11888, 3346, 315, 1521, 31284, 8128, 1051, 6724, 5675, 311, 58097, 2391, 872, 220, 1490, 4771, 6492, 4261, 13, 1666, 3728, 3152, 9581, 2237, 374, 19698, 311, 10205, 29057, 927, 279, 1828, 9478, 320, 84910, 1880, 453, 13, 220, 679, 18, 2652, 735, 4880, 1880, 453, 13, 220, 679, 19, 7026, 3109, 7510, 11, 33184, 5315, 11, 323, 3424, 7980, 5895, 1268, 7319, 9581, 2237, 10205, 320, 8143, 49, 8, 690, 7958, 872, 14529, 14993, 311, 10299, 2160, 73910, 31284, 8128, 13, 350, 26966, 7576, 13519, 430, 279, 59103, 23028, 315, 93550, 11, 507, 27793, 11, 323, 735, 2933, 2192, 617, 10534, 520, 3325, 264, 9478, 315, 8844, 17216, 49, 520, 7969, 505, 220, 16, 13, 1135, 311, 220, 17, 13, 843, 9653, 27589, 13, 12036, 483, 1880, 453, 13, 320, 220, 679, 18, 883, 27313, 99164, 18845, 389, 30100, 449, 2204, 17216, 49, 7969, 323, 20536, 430, 17216, 49, 374, 10815, 311, 35335, 58097, 304, 28621, 13, 4452, 11, 99164, 2349, 7969, 2212, 1855, 13218, 13592, 19407, 320, 6398, 290, 7969, 709, 311, 25173, 16, 13, 23, 20903, 220, 15, 13, 18, 296, 86000, 323, 1046, 2171, 290, 7969, 709, 311, 220, 16, 13, 22, 20903, 220, 15, 13, 21, 296, 86000, 26, 12036, 483, 323, 69168, 220, 679, 18, 7026, 1405, 21282, 315, 58097, 323, 1046, 2171, 290, 1051, 19180, 555, 22781, 311, 11758, 315, 20645, 3235, 29526, 8994, 4856, 87282, 13218, 25480, 17216, 49, 18845, 13, 1115, 13533, 430, 279, 10383, 315, 17216, 49, 389, 99164, 2349, 374, 50801, 9099, 7863, 449, 59132, 18539, 320, 1264, 315, 8336, 323, 58052, 8, 5552, 311, 3823, 25949, 323, 26048, 7106, 11618, 1778, 439, 384, 89108, 7710, 11, 5425, 7666, 461, 7710, 11, 323, 53249, 304, 1317, 29526, 59132, 7710, 13, 12781, 49858, 17216, 49, 374, 3685, 311, 617, 459, 7319, 2515, 389, 35335, 79612, 320, 626, 535, 220, 1049, 19, 883, 323, 311, 12192, 58097, 315, 12387, 59103, 35909, 320, 45459, 483, 1880, 453, 13, 220, 679, 18, 7609, 578, 1357, 2431, 26112, 278, 19482, 389, 31636, 10604, 320, 3378, 3791, 8, 23690, 37357, 8423, 320, 946, 20, 26, 220, 679, 18, 8, 7224, 220, 15, 13, 4103, 4235, 15, 13, 3264, 296, 315, 17216, 49, 555, 220, 8848, 15, 8844, 311, 220, 3753, 21, 4235, 1049, 20, 369, 38366, 62261, 2214, 8092, 3195, 320, 49, 7269, 8, 220, 23, 13, 20, 320, 1820, 1054, 27243, 439, 13783, 863, 15398, 26, 9441, 1880, 453, 13, 220, 679, 18, 7609, 1115, 6835, 264, 4478, 2391, 220, 12171, 15, 4235, 8848, 15, 315, 220, 23, 4235, 845, 9653, 86000, 11, 709, 311, 459, 2015, 315, 26703, 8294, 1109, 279, 82640, 43038, 31990, 17216, 49, 4478, 320, 16, 13, 1135, 20903, 220, 15, 13, 914, 9653, 86000, 26, 883, 369, 279, 3766, 9478, 320, 7028, 20, 4235, 1049, 21, 8, 994, 279, 82640, 17216, 49, 9327, 574, 4528, 311, 279, 13240, 3728, 3152, 9327, 320, 68, 1326, 2637, 220, 16, 13, 22, 20903, 220, 15, 13, 17, 9653, 86000, 26, 9441, 323, 5929, 220, 679, 16, 7609, 578, 1510, 95661, 41579, 1253, 79583, 17216, 49, 1606, 814, 656, 539, 2997, 279, 3135, 315, 3293, 7978, 19392, 7319, 10054, 30099, 369, 73778, 320, 39, 24037, 1880, 453, 13, 220, 679, 19, 883, 323, 4410, 72787, 320, 41, 1409, 258, 1880, 453, 13, 220, 679, 19, 2652, 432, 625, 354, 1880, 453, 13, 220, 679, 19, 7609, 36378, 3904, 7710, 11, 323, 8617, 99164, 12172, 11, 374, 279, 1121, 315, 5361, 75098, 11618, 430, 43111, 16681, 449, 6484, 79612, 927, 264, 8205, 315, 892, 323, 29079, 29505, 320, 626, 535, 1880, 453, 13, 220, 1049, 17, 2652, 76313, 1880, 453, 13, 220, 1049, 18, 7609, 1666, 264, 1121, 315, 7319, 17216, 49, 11, 59132, 29899, 5499, 3428, 12, 6852, 35335, 5789, 690, 3217, 24872, 58097, 323, 92629, 367, 11075, 555, 59132, 18539, 323, 2254, 35335, 31332, 13, 13011, 288, 690, 387, 4726, 27367, 555, 4442, 304, 59132, 7710, 12912, 439, 264, 1121, 315, 5190, 3090, 5990, 927, 1448, 24992, 92822, 320, 6600, 7759, 1880, 453, 13, 220, 679, 18, 7026, 10182, 14228, 29882, 304, 71145, 28355, 16751, 2508, 323, 59132, 5788, 320, 47, 5515, 1880, 453, 13, 220, 679, 16, 7026, 323, 4442, 304, 13766, 1918, 323, 12330, 10182, 320, 32, 1791, 276, 1880, 453, 13, 220, 679, 17, 7609, 48224, 950, 4211, 617, 279, 4754, 311, 7664, 11573, 15740, 810, 30357, 1109, 1317, 9860, 18845, 11, 719, 3629, 1397, 828, 520, 29079, 323, 37015, 90816, 430, 527, 539, 2561, 13, 15483, 5528, 527, 9093, 5107, 311, 3881, 311, 279, 2814, 579, 35555, 278, 3115, 31296, 430, 527, 279, 5357, 315, 420, 5684, 320, 39, 37645, 1880, 453, 13, 220, 1049, 18, 7609, 1789, 26954, 15813, 927, 3544, 35335, 13918, 11, 433, 374, 9093, 5995, 311, 2274, 46763, 5528, 430, 3493, 264, 1176, 24747, 57304, 315, 58097, 14675, 323, 1202, 27924, 13, 16838, 1113, 31397, 27924, 311, 35335, 20258, 320, 47, 321, 798, 1880, 453, 13, 220, 2550, 18, 2652, 60223, 8023, 1880, 453, 13, 220, 1049, 15, 2652, 37451, 798, 323, 24421, 220, 1049, 19, 1174, 5099, 6266, 20682, 1124, 311, 1304, 11429, 3196, 389, 5990, 315, 5326, 13, 1102, 1101, 8779, 35335, 296, 14381, 3619, 430, 439, 502, 828, 3719, 2561, 11, 6177, 41579, 690, 8454, 2362, 6305, 320, 47, 321, 798, 323, 24421, 220, 1049, 19, 7609, 41143, 828, 527, 17037, 1511, 311, 3493, 1317, 9860, 2038, 389, 35335, 58097, 320, 30035, 13, 220, 16, 7026, 719, 71462, 1113, 13970, 18845, 374, 39413, 2728, 279, 28448, 14511, 811, 304, 17216, 49, 13, 473, 71652, 320, 220, 1049, 20, 883, 13533, 85292, 279, 13970, 9327, 555, 264, 17216, 49, 28174, 8331, 11, 1778, 439, 220, 605, 127036, 323, 1243, 71462, 1113, 279, 24257, 9327, 13, 10541, 4228, 311, 4305, 11, 420, 5603, 1587, 539, 2187, 369, 31903, 128257, 198, 128256, 78191, 198, 1163, 8535, 58097, 83978, 279, 68539, 35909, 315, 22153, 63650, 11, 14718, 11573, 4814, 439, 433, 26186, 10632, 11, 14054, 323, 9200, 39646, 13, 59250, 617, 1317, 16365, 430, 3728, 9581, 2237, 10205, 690, 7958, 279, 4478, 315, 35335, 58097, 13, 4452, 11, 502, 3495, 505, 14248, 520, 549, 39, 386, 31757, 2201, 64, 323, 279, 1614, 6011, 315, 11680, 323, 18955, 16607, 12716, 1139, 49479, 5357, 1120, 1268, 29057, 22153, 63650, 596, 35909, 2643, 2349, 13, 1789, 279, 4007, 11, 4756, 420, 2046, 304, 18955, 32595, 2402, 11, 279, 3495, 2128, 8040, 264, 4382, 1646, 311, 8720, 3938, 58097, 52642, 1234, 5190, 9581, 5990, 1389, 4737, 1139, 2759, 13970, 4442, 315, 22153, 63650, 31284, 8128, 323, 279, 28448, 31903, 315, 9581, 2237, 10205, 5068, 505, 279, 1357, 2431, 26112, 278, 19482, 389, 31636, 10604, 320, 3378, 3791, 570, 578, 3135, 13519, 430, 35335, 58097, 315, 22153, 63650, 596, 35909, 1253, 2033, 555, 5209, 34457, 13, 9086, 279, 8857, 315, 22153, 134, 119, 72, 596, 68539, 35909, 11, 1455, 31284, 8128, 520, 279, 220, 605, 4007, 6732, 389, 735, 2933, 64, 134, 119, 72, 11, 507, 134, 119, 27793, 323, 93550, 527, 5131, 2160, 73910, 13, 1442, 1521, 35909, 1051, 311, 1833, 1510, 18845, 11, 459, 5578, 220, 508, 311, 220, 1272, 7693, 315, 99164, 39621, 1053, 387, 3685, 555, 220, 10866, 15, 323, 220, 8848, 15, 11, 15947, 13, 330, 4599, 584, 62653, 3938, 99164, 2349, 449, 279, 7319, 7969, 315, 9581, 2237, 10205, 320, 8143, 49, 8, 28448, 1234, 279, 95661, 596, 364, 27243, 439, 13783, 6, 15398, 11, 584, 1766, 430, 7319, 17216, 49, 11384, 459, 5578, 220, 845, 311, 220, 508, 7693, 315, 5217, 99164, 31114, 555, 220, 10866, 15, 11, 323, 459, 5578, 315, 7154, 220, 1399, 7693, 315, 5217, 31114, 555, 220, 8848, 15, 1359, 1071, 68573, 21293, 11, 3063, 3229, 323, 1772, 30659, 5009, 278, 32185, 520, 279, 549, 53248, 6150, 315, 22302, 323, 9420, 10170, 323, 12053, 13, 330, 2028, 3445, 430, 279, 5578, 3392, 315, 99164, 39621, 17715, 40396, 555, 220, 10866, 15, 449, 7319, 17216, 49, 11, 7863, 311, 13970, 71462, 367, 7636, 13, 3296, 220, 8848, 15, 11, 433, 374, 7154, 220, 17, 13, 20, 3115, 279, 13970, 71462, 367, 13, 15903, 11, 1057, 3135, 13519, 430, 13489, 220, 6083, 4, 323, 220, 4161, 4, 315, 279, 31284, 8128, 690, 387, 2160, 73910, 555, 220, 10866, 15, 323, 220, 8848, 15, 11, 15947, 11, 3734, 520, 735, 607, 4381, 11, 507, 134, 119, 27793, 11, 902, 374, 28448, 311, 3240, 2160, 73910, 555, 5209, 34457, 1210, 578, 1646, 9815, 369, 1046, 2171, 290, 315, 9462, 8800, 35909, 323, 1317, 9860, 59132, 11618, 304, 3339, 41579, 315, 3938, 99164, 2361, 13, 1666, 961, 315, 14529, 3495, 11, 279, 13239, 58097, 31397, 26467, 527, 29204, 467, 389, 41884, 7397, 323, 1023, 46139, 13931, 304, 264, 46139, 2038, 1887, 311, 3493, 264, 5507, 369, 25607, 5070, 11, 14054, 323, 3424, 15246, 311, 3938, 35335, 58097, 13, 330, 2028, 4007, 32216, 264, 38152, 430, 649, 387, 1511, 555, 1690, 99164, 10977, 311, 8720, 872, 14675, 311, 35335, 58097, 13239, 505, 279, 10182, 11501, 1359, 1071, 32013, 69168, 11, 33468, 25028, 520, 279, 549, 53248, 6150, 315, 22302, 323, 9420, 10170, 323, 12053, 323, 1080, 43802, 315, 279, 5684, 13, 39546, 13970, 99164, 2349, 5825, 5505, 828, 369, 47614, 14675, 311, 3938, 58097, 52642, 11, 1524, 422, 279, 4478, 315, 9581, 2237, 10205, 4442, 304, 279, 3938, 13, 578, 19698, 5376, 304, 58097, 690, 40250, 9214, 315, 10632, 11, 1690, 8931, 315, 82211, 323, 1023, 12032, 304, 22153, 63650, 13, 63388, 750, 279, 9513, 14675, 311, 58097, 374, 23205, 13, 330, 2409, 1521, 502, 3135, 11, 3109, 13607, 649, 3240, 311, 2274, 34185, 15174, 11, 2737, 502, 10396, 11, 369, 21676, 11469, 279, 99164, 1359, 1071, 21293, 13, 2057, 4726, 7417, 279, 17989, 315, 10182, 25949, 11, 279, 1828, 3094, 369, 279, 2128, 315, 12074, 690, 387, 311, 16343, 279, 502, 1646, 449, 41300, 315, 7319, 39262, 555, 17301, 13, 220, 128257, 198 ]

2,131

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Dynamic shape-morphing soft materials systems are ubiquitous in living organisms; they are also of rapidly increasing relevance to emerging technologies in soft machines 1 , 2 , 3 , flexible electronics 4 , 5 and smart medicines 6 . Soft matter equipped with responsive components can switch between designed shapes or structures, but cannot support the types of dynamic morphing capabilities needed to reproduce natural, continuous processes of interest for many applications 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 . Challenges lie in the development of schemes to reprogram target shapes after fabrication, especially when complexities associated with the operating physics and disturbances from the environment can stop the use of deterministic theoretical models to guide inverse design and control strategies 25 , 26 , 27 , 28 , 29 , 30 . Here we present a mechanical metasurface constructed from a matrix of filamentary metal traces, driven by reprogrammable, distributed Lorentz forces that follow from the passage of electrical currents in the presence of a static magnetic field. The resulting system demonstrates complex, dynamic morphing capabilities with response times within 0.1 second. Implementing an in situ stereo-imaging feedback strategy with a digitally controlled actuation scheme guided by an optimization algorithm yields surfaces that can follow a self-evolving inverse design to morph into a wide range of three-dimensional target shapes with high precision, including an ability to morph against extrinsic or intrinsic perturbations. These concepts support a data-driven approach to the design of dynamic soft matter, with many unique characteristics. Main Soft matter that can dynamically reconfigure its shape upon interactions with environment or perceptions of information is thriving 31 . Pioneering studies rely on an exploitation of responsive materials (for example, liquid crystal elastomers 8 , 9 , dielectric elastomers 10 , responsive hydrogels 11 , 12 , 13 and others 14 ) and multimaterial structures 7 , 15 to enable large deformation, but face challenges in implementing fast control to refined structures. The design of a shape-morphing process usually requires a prerequisite modelling effort to be programmed into the fabrication process, and this is therefore hard to reprogram on-the-fly (for example, 3D printing 7 , 11 , 19 , 24 , 30 , magnetization 19 , 32 , laser or wafer-jet cutting 26 , 27 , 33 , and mechanical buckling 25 ). The desire to shift shapes among a number of configurations invites investigations of various architectures and programmable stimuli (for example, temperature 8 , light 34 , 35 , magnetic field 20 , 36 , electric field 10 and Lorentz-force actuation 22 , 23 , 37 ). Traditional inverse design of the input–output relationships in the resulting non-linear and high-dimensional system can, however, lead to difficulties in establishing analytical solutions or problems of high computational costs. Also, existing computer-aided methods usually leave the inclusion of imperfections, damages or coupling between the system and the unforeseen environment. Incorporating instant feedback is necessary for the morphing process to see the deployment scheme to precisely account for specific, multifunctional or time-varying requirements 38 . Programmable electromagnetic actuation A materials architecture consisting of a mesh of optimized, planar conductive features operating in a magnetic field and with programmable control over distributions of electrical current, as introduced here, presents an intriguing set of opportunities. The metasurface takes the form of interconnected, serpentine-shaped beams that consist of a thin conductive layer of gold (Au, thickness h Au = 0.3 µm, width b Au = 130 µm) encapsulated by polyimide (PI, thickness h PI = 7.5 μm, width b PI = 160 μm) (see Methods section ‘Sample fabrication’, Supplementary Fig. 1 and Supplementary Note 1 for details). The intersections of the beams form an N × M mesh as shown in Fig. 1a ( N = M = 4, sample size L = W = 18.0 mm, column and row serpentine beam length L N / M = 3.60 mm). A tailored design ensures sufficiently large, fast and reversible out-of-plane deformation ( u / L ≈ 30%) (in-plane deformation less than 0.01 L ; response time less than 0.07 s) of the serpentine beam, driven by a modest electric current ( I < 27.5 mA) in an approximately uniform magnetic field B (magnitude B = 224 ± 16 mT) (see Extended Data Fig. 1 , Supplementary Figs. 2 – 6 and Supplementary Notes 2 – 5 for details). An analytical model validated by experiment can be used to guide design choices for a tunable electromagnetic response in a broad range of magnetic field strengths (for example, B reduced to 25 mT; see Extended Data Fig. 2 and Supplementary Note 3.1 ). Figure 1b shows that independent voltages ( V = { V j }) of size 2( N + M ) applied to the peripheral ports define the distribution of current density ( J ) in the conductive network (see Methods section ‘Digital control’ and Supplementary Fig. 7 for details) and therefore control the Lorentz force, F EM = J × B . The spatially distributed actuation F EM ( J ) determines the local, out-of-plane ( Z direction) deformations ( u = { u i }, where u i is the displacement of the i th node) of the sample in a magnetic field B aligned with its diagonal, enabling a large set of accessible three-dimensional (3D) shapes from the same precursor structure. Fig. 1: Mechanical metasurfaces driven by reprogrammable electromagnetic actuation. a , Schematic illustration (enlarged view) of a representative square mesh sample constructed from the serpentine beams consisting of thin PI and Au layers. b , Schematic illustration of a 4 × 4 sample placed in a magnetic field (in-plane with the sample in a diagonal direction). Portal voltages define the current density distribution ( J ) in the sample and hence control the local Lorentz-force actuation. c , FEA provides", "role": "user" }, { "content": "Engineers at Duke University have developed a scalable soft surface that can continuously reshape itself to mimic objects in nature. Relying on electromagnetic actuation, mechanical modeling and machine learning to form new configurations, the surface can even learn to adapt to hindrances such as broken elements, unexpected constraints or changing environments. The research appears online September 21 in the journal Nature. \"We're motivated by the idea of controlling material properties or mechanical behaviors of an engineered object on the fly, which could be useful for applications like soft robotics, augmented reality, biomimetic materials, and subject-specific wearables,\" said Xiaoyue Ni, assistant professor of mechanical engineering and materials science at Duke. \"We are focusing on engineering the shape of matter that hasn't been predetermined, which is a pretty tall task to achieve, especially for soft materials.\" Watch this thin, flexible material teach itself to mimic ocean waves and flexing palms in real-time. Relying on electromagnetic actuation, mechanical modeling and machine learning to form new configurations, the surface can even learn to adapt to hindrances such as broken elements, unexpected constraints or changing environments. Credit: Veronique Koch, Duke University Previous work on morphing matter, according to Ni, hasn't typically been programmable; it's been programmed instead. That is, soft surfaces equipped with designed active elements can shift their shapes between few shapes, like a piece of origami, in response to light or heat or other stimuli triggers. In contrast, Ni and her laboratory wanted to create something much more controllable that could morph and reconfigure as often as it likes into any physically possible shapes. To create such a surface, the researchers started by laying out a grid of snake-like beams made of a thin layer of gold encapsulated by a thin polymer layer. The individual beams are just eight micrometers thick—about the thickness of a cotton fiber—and less than a millimeter wide. The lightness of the beams allows magnetic forces to easily and rapidly deform them. To generate local forces, the surface is put into a low-level static magnetic field. Voltage changes create a complex but easily predictable electrical current along the golden grid, driving the out-of-plane displacement of the grid. \"This is the first artificial soft surface that is fast enough to accurately mimic a continuous shape-shifting process in nature,\" Ni said. \"One key advance is the structural design that enables an unusual linear relationship between the electrical inputs and the resulting shape, which makes it easy to figure out how to apply voltages to achieve a wide variety of target shapes.\" The new \"metasurface\" shows off a wide array of morphing and mimicking skills. It creates bulges that rise and move around the surface like a cat trying to find its way out from under a blanket, oscillating wave patterns, and a convincing replication of a liquid drop dripping and plopping onto a solid surface. And it produces these shapes and behaviors at any speed or acceleration desired, meaning it can reimagine that trapped cat or dripped droplet in slow motion or fast forward. With cameras monitoring the morphing surface, the contortionist surface can also learn to recreate shapes and patterns on its own. By slowly adjusting the applied voltages, a learning algorithm takes in 3D imaging feedback and figures out what effects the different inputs have on the metasurface's shape. In the paper, a human palm spotted with 16 black dots slowly shifts under a camera, and the surface mirrors the movements perfectly. \"The control doesn't have to know anything about the physics of the materials, it just takes small steps and watches to see if it's getting closer to the target or not,\" Ni said. \"It currently takes about two minutes to achieve a new shape, but we hope to eventually improve the feedback system and learning algorithm to the point that it's nearly real-time.\" Because the surface teaches itself to move through trial and error, it can also adapt to damage, unexpected physical constraints or environmental change. In one experiment, it quickly learns to mimic a bulging mound despite one of its beams being cut. In another, it manages to mimic a similar shape despite a weight being attached to one of the grid's nodes. There are many immediate opportunities to extend the scale and configuration of the soft surface. For example, an array of surfaces can scale the size up to that of a touching screen. Or fabrication techniques with higher precision can scale the size down to one millimeter, making it more suitable for biomedical applications. Moving forward, Ni wants to create robotic metasurfaces with integrated shape-sensing functions to perform real-time shape mimicking of complex, dynamic surfaces in nature, such as the water ripples, fish fins or the human face. The lab may also look into embedding more components into the prototype, such as on-board power sources, sensors, computational resources or wireless communication capabilities. \"Along with the pursuit of creating programmable and robotic materials, we envision future materials will be able to alter themselves to serve functions dynamically and interactively,\" said Ni. \"Such materials can sense and perceive requirements or information from the users, and transform and adapt according to the real-time needs of their specific performance, just like the microbots in Big Hero 6. The soft surface may find applications as a teleoperated robot, dynamic 3D display, camouflage, exoskeleton or other smart, functional surfaces that can work in harsh, unpredictable environments.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Dynamic shape-morphing soft materials systems are ubiquitous in living organisms; they are also of rapidly increasing relevance to emerging technologies in soft machines 1 , 2 , 3 , flexible electronics 4 , 5 and smart medicines 6 . Soft matter equipped with responsive components can switch between designed shapes or structures, but cannot support the types of dynamic morphing capabilities needed to reproduce natural, continuous processes of interest for many applications 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 . Challenges lie in the development of schemes to reprogram target shapes after fabrication, especially when complexities associated with the operating physics and disturbances from the environment can stop the use of deterministic theoretical models to guide inverse design and control strategies 25 , 26 , 27 , 28 , 29 , 30 . Here we present a mechanical metasurface constructed from a matrix of filamentary metal traces, driven by reprogrammable, distributed Lorentz forces that follow from the passage of electrical currents in the presence of a static magnetic field. The resulting system demonstrates complex, dynamic morphing capabilities with response times within 0.1 second. Implementing an in situ stereo-imaging feedback strategy with a digitally controlled actuation scheme guided by an optimization algorithm yields surfaces that can follow a self-evolving inverse design to morph into a wide range of three-dimensional target shapes with high precision, including an ability to morph against extrinsic or intrinsic perturbations. These concepts support a data-driven approach to the design of dynamic soft matter, with many unique characteristics. Main Soft matter that can dynamically reconfigure its shape upon interactions with environment or perceptions of information is thriving 31 . Pioneering studies rely on an exploitation of responsive materials (for example, liquid crystal elastomers 8 , 9 , dielectric elastomers 10 , responsive hydrogels 11 , 12 , 13 and others 14 ) and multimaterial structures 7 , 15 to enable large deformation, but face challenges in implementing fast control to refined structures. The design of a shape-morphing process usually requires a prerequisite modelling effort to be programmed into the fabrication process, and this is therefore hard to reprogram on-the-fly (for example, 3D printing 7 , 11 , 19 , 24 , 30 , magnetization 19 , 32 , laser or wafer-jet cutting 26 , 27 , 33 , and mechanical buckling 25 ). The desire to shift shapes among a number of configurations invites investigations of various architectures and programmable stimuli (for example, temperature 8 , light 34 , 35 , magnetic field 20 , 36 , electric field 10 and Lorentz-force actuation 22 , 23 , 37 ). Traditional inverse design of the input–output relationships in the resulting non-linear and high-dimensional system can, however, lead to difficulties in establishing analytical solutions or problems of high computational costs. Also, existing computer-aided methods usually leave the inclusion of imperfections, damages or coupling between the system and the unforeseen environment. Incorporating instant feedback is necessary for the morphing process to see the deployment scheme to precisely account for specific, multifunctional or time-varying requirements 38 . Programmable electromagnetic actuation A materials architecture consisting of a mesh of optimized, planar conductive features operating in a magnetic field and with programmable control over distributions of electrical current, as introduced here, presents an intriguing set of opportunities. The metasurface takes the form of interconnected, serpentine-shaped beams that consist of a thin conductive layer of gold (Au, thickness h Au = 0.3 µm, width b Au = 130 µm) encapsulated by polyimide (PI, thickness h PI = 7.5 μm, width b PI = 160 μm) (see Methods section ‘Sample fabrication’, Supplementary Fig. 1 and Supplementary Note 1 for details). The intersections of the beams form an N × M mesh as shown in Fig. 1a ( N = M = 4, sample size L = W = 18.0 mm, column and row serpentine beam length L N / M = 3.60 mm). A tailored design ensures sufficiently large, fast and reversible out-of-plane deformation ( u / L ≈ 30%) (in-plane deformation less than 0.01 L ; response time less than 0.07 s) of the serpentine beam, driven by a modest electric current ( I < 27.5 mA) in an approximately uniform magnetic field B (magnitude B = 224 ± 16 mT) (see Extended Data Fig. 1 , Supplementary Figs. 2 – 6 and Supplementary Notes 2 – 5 for details). An analytical model validated by experiment can be used to guide design choices for a tunable electromagnetic response in a broad range of magnetic field strengths (for example, B reduced to 25 mT; see Extended Data Fig. 2 and Supplementary Note 3.1 ). Figure 1b shows that independent voltages ( V = { V j }) of size 2( N + M ) applied to the peripheral ports define the distribution of current density ( J ) in the conductive network (see Methods section ‘Digital control’ and Supplementary Fig. 7 for details) and therefore control the Lorentz force, F EM = J × B . The spatially distributed actuation F EM ( J ) determines the local, out-of-plane ( Z direction) deformations ( u = { u i }, where u i is the displacement of the i th node) of the sample in a magnetic field B aligned with its diagonal, enabling a large set of accessible three-dimensional (3D) shapes from the same precursor structure. Fig. 1: Mechanical metasurfaces driven by reprogrammable electromagnetic actuation. a , Schematic illustration (enlarged view) of a representative square mesh sample constructed from the serpentine beams consisting of thin PI and Au layers. b , Schematic illustration of a 4 × 4 sample placed in a magnetic field (in-plane with the sample in a diagonal direction). Portal voltages define the current density distribution ( J ) in the sample and hence control the local Lorentz-force actuation. c , FEA provides<|im_end|> <|im_start|>assistant Engineers at Duke University have developed a scalable soft surface that can continuously reshape itself to mimic objects in nature. Relying on electromagnetic actuation, mechanical modeling and machine learning to form new configurations, the surface can even learn to adapt to hindrances such as broken elements, unexpected constraints or changing environments. The research appears online September 21 in the journal Nature. "We're motivated by the idea of controlling material properties or mechanical behaviors of an engineered object on the fly, which could be useful for applications like soft robotics, augmented reality, biomimetic materials, and subject-specific wearables," said Xiaoyue Ni, assistant professor of mechanical engineering and materials science at Duke. "We are focusing on engineering the shape of matter that hasn't been predetermined, which is a pretty tall task to achieve, especially for soft materials." Watch this thin, flexible material teach itself to mimic ocean waves and flexing palms in real-time. Relying on electromagnetic actuation, mechanical modeling and machine learning to form new configurations, the surface can even learn to adapt to hindrances such as broken elements, unexpected constraints or changing environments. Credit: Veronique Koch, Duke University Previous work on morphing matter, according to Ni, hasn't typically been programmable; it's been programmed instead. That is, soft surfaces equipped with designed active elements can shift their shapes between few shapes, like a piece of origami, in response to light or heat or other stimuli triggers. In contrast, Ni and her laboratory wanted to create something much more controllable that could morph and reconfigure as often as it likes into any physically possible shapes. To create such a surface, the researchers started by laying out a grid of snake-like beams made of a thin layer of gold encapsulated by a thin polymer layer. The individual beams are just eight micrometers thick—about the thickness of a cotton fiber—and less than a millimeter wide. The lightness of the beams allows magnetic forces to easily and rapidly deform them. To generate local forces, the surface is put into a low-level static magnetic field. Voltage changes create a complex but easily predictable electrical current along the golden grid, driving the out-of-plane displacement of the grid. "This is the first artificial soft surface that is fast enough to accurately mimic a continuous shape-shifting process in nature," Ni said. "One key advance is the structural design that enables an unusual linear relationship between the electrical inputs and the resulting shape, which makes it easy to figure out how to apply voltages to achieve a wide variety of target shapes." The new "metasurface" shows off a wide array of morphing and mimicking skills. It creates bulges that rise and move around the surface like a cat trying to find its way out from under a blanket, oscillating wave patterns, and a convincing replication of a liquid drop dripping and plopping onto a solid surface. And it produces these shapes and behaviors at any speed or acceleration desired, meaning it can reimagine that trapped cat or dripped droplet in slow motion or fast forward. With cameras monitoring the morphing surface, the contortionist surface can also learn to recreate shapes and patterns on its own. By slowly adjusting the applied voltages, a learning algorithm takes in 3D imaging feedback and figures out what effects the different inputs have on the metasurface's shape. In the paper, a human palm spotted with 16 black dots slowly shifts under a camera, and the surface mirrors the movements perfectly. "The control doesn't have to know anything about the physics of the materials, it just takes small steps and watches to see if it's getting closer to the target or not," Ni said. "It currently takes about two minutes to achieve a new shape, but we hope to eventually improve the feedback system and learning algorithm to the point that it's nearly real-time." Because the surface teaches itself to move through trial and error, it can also adapt to damage, unexpected physical constraints or environmental change. In one experiment, it quickly learns to mimic a bulging mound despite one of its beams being cut. In another, it manages to mimic a similar shape despite a weight being attached to one of the grid's nodes. There are many immediate opportunities to extend the scale and configuration of the soft surface. For example, an array of surfaces can scale the size up to that of a touching screen. Or fabrication techniques with higher precision can scale the size down to one millimeter, making it more suitable for biomedical applications. Moving forward, Ni wants to create robotic metasurfaces with integrated shape-sensing functions to perform real-time shape mimicking of complex, dynamic surfaces in nature, such as the water ripples, fish fins or the human face. The lab may also look into embedding more components into the prototype, such as on-board power sources, sensors, computational resources or wireless communication capabilities. "Along with the pursuit of creating programmable and robotic materials, we envision future materials will be able to alter themselves to serve functions dynamically and interactively," said Ni. "Such materials can sense and perceive requirements or information from the users, and transform and adapt according to the real-time needs of their specific performance, just like the microbots in Big Hero 6. The soft surface may find applications as a teleoperated robot, dynamic 3D display, camouflage, exoskeleton or other smart, functional surfaces that can work in harsh, unpredictable environments." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 22648, 6211, 1474, 16751, 287, 8579, 7384, 6067, 527, 64564, 304, 5496, 44304, 26, 814, 527, 1101, 315, 19019, 7859, 41961, 311, 24084, 14645, 304, 8579, 12933, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 19303, 31591, 220, 19, 1174, 220, 20, 323, 7941, 39653, 220, 21, 662, 25046, 5030, 19167, 449, 27078, 6956, 649, 3480, 1990, 6319, 21483, 477, 14726, 11, 719, 4250, 1862, 279, 4595, 315, 8915, 27448, 287, 17357, 4460, 311, 23645, 5933, 11, 19815, 11618, 315, 2802, 369, 1690, 8522, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 1174, 220, 972, 1174, 220, 777, 1174, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 662, 69778, 10457, 304, 279, 4500, 315, 31956, 311, 312, 15252, 2218, 21483, 1306, 59251, 11, 5423, 994, 84140, 5938, 449, 279, 10565, 22027, 323, 85160, 505, 279, 4676, 649, 3009, 279, 1005, 315, 73449, 32887, 4211, 311, 8641, 29049, 2955, 323, 2585, 15174, 220, 914, 1174, 220, 1627, 1174, 220, 1544, 1174, 220, 1591, 1174, 220, 1682, 1174, 220, 966, 662, 5810, 584, 3118, 264, 22936, 2322, 300, 10730, 20968, 505, 264, 6303, 315, 91880, 661, 9501, 35483, 11, 16625, 555, 312, 15252, 76, 481, 11, 4332, 54333, 406, 89, 8603, 430, 1833, 505, 279, 21765, 315, 20314, 60701, 304, 279, 9546, 315, 264, 1118, 24924, 2115, 13, 578, 13239, 1887, 32216, 6485, 11, 8915, 27448, 287, 17357, 449, 2077, 3115, 2949, 220, 15, 13, 16, 2132, 13, 32175, 287, 459, 304, 10109, 39052, 38025, 4210, 11302, 8446, 449, 264, 68878, 14400, 1180, 4090, 13155, 33687, 555, 459, 26329, 12384, 36508, 27529, 430, 649, 1833, 264, 659, 91345, 20222, 29049, 2955, 311, 27448, 1139, 264, 7029, 2134, 315, 2380, 33520, 2218, 21483, 449, 1579, 16437, 11, 2737, 459, 5845, 311, 27448, 2403, 11741, 28692, 477, 47701, 18713, 9225, 811, 13, 4314, 19476, 1862, 264, 828, 32505, 5603, 311, 279, 2955, 315, 8915, 8579, 5030, 11, 449, 1690, 5016, 17910, 13, 4802, 25046, 5030, 430, 649, 43111, 312, 21678, 1202, 6211, 5304, 22639, 449, 4676, 477, 51866, 315, 2038, 374, 53414, 220, 2148, 662, 393, 6473, 4776, 7978, 17631, 389, 459, 40761, 315, 27078, 7384, 320, 2000, 3187, 11, 14812, 26110, 92185, 69638, 220, 23, 1174, 220, 24, 1174, 2815, 47262, 92185, 69638, 220, 605, 1174, 27078, 17055, 70, 2053, 220, 806, 1174, 220, 717, 1174, 220, 1032, 323, 3885, 220, 975, 883, 323, 80149, 2229, 14726, 220, 22, 1174, 220, 868, 311, 7431, 3544, 91621, 11, 719, 3663, 11774, 304, 25976, 5043, 2585, 311, 38291, 14726, 13, 578, 2955, 315, 264, 6211, 1474, 16751, 287, 1920, 6118, 7612, 264, 80884, 61966, 5149, 311, 387, 56168, 1139, 279, 59251, 1920, 11, 323, 420, 374, 9093, 2653, 311, 312, 15252, 389, 10826, 83985, 320, 2000, 3187, 11, 220, 18, 35, 18991, 220, 22, 1174, 220, 806, 1174, 220, 777, 1174, 220, 1187, 1174, 220, 966, 1174, 33297, 2065, 220, 777, 1174, 220, 843, 1174, 21120, 477, 10667, 809, 13636, 295, 14713, 220, 1627, 1174, 220, 1544, 1174, 220, 1644, 1174, 323, 22936, 22786, 2785, 220, 914, 7609, 578, 12876, 311, 6541, 21483, 4315, 264, 1396, 315, 33483, 45510, 26969, 315, 5370, 78335, 323, 56586, 481, 56688, 320, 2000, 3187, 11, 9499, 220, 23, 1174, 3177, 220, 1958, 1174, 220, 1758, 1174, 24924, 2115, 220, 508, 1174, 220, 1927, 1174, 9249, 2115, 220, 605, 323, 54333, 406, 89, 81149, 1180, 4090, 220, 1313, 1174, 220, 1419, 1174, 220, 1806, 7609, 46560, 29049, 2955, 315, 279, 1988, 4235, 3081, 12135, 304, 279, 13239, 2536, 62399, 323, 1579, 33520, 1887, 649, 11, 4869, 11, 3063, 311, 27129, 304, 31692, 44064, 10105, 477, 5435, 315, 1579, 55580, 7194, 13, 7429, 11, 6484, 6500, 12, 3864, 291, 5528, 6118, 5387, 279, 28286, 315, 17190, 25384, 11, 26186, 477, 59086, 1990, 279, 1887, 323, 279, 96691, 29412, 4676, 13, 54804, 1113, 9888, 11302, 374, 5995, 369, 279, 27448, 287, 1920, 311, 1518, 279, 24047, 13155, 311, 24559, 2759, 369, 3230, 11, 62387, 600, 278, 477, 892, 8437, 661, 287, 8670, 220, 1987, 662, 75010, 481, 66669, 1180, 4090, 362, 7384, 18112, 31706, 315, 264, 11546, 315, 34440, 11, 3197, 277, 6929, 535, 4519, 10565, 304, 264, 24924, 2115, 323, 449, 56586, 481, 2585, 927, 43785, 315, 20314, 1510, 11, 439, 11784, 1618, 11, 18911, 459, 41765, 743, 315, 10708, 13, 578, 2322, 300, 10730, 5097, 279, 1376, 315, 83416, 11, 1446, 79, 27970, 35831, 51045, 430, 6824, 315, 264, 15792, 6929, 535, 6324, 315, 6761, 320, 66432, 11, 26839, 305, 33150, 284, 220, 15, 13, 18, 64012, 76, 11, 2430, 293, 33150, 284, 220, 5894, 64012, 76, 8, 43669, 7913, 555, 10062, 318, 579, 320, 1932, 11, 26839, 305, 23396, 284, 220, 22, 13, 20, 33983, 76, 11, 2430, 293, 23396, 284, 220, 6330, 33983, 76, 8, 320, 4151, 19331, 3857, 3451, 18031, 59251, 20182, 99371, 23966, 13, 220, 16, 323, 99371, 7181, 220, 16, 369, 3649, 570, 578, 65357, 315, 279, 51045, 1376, 459, 452, 25800, 386, 11546, 439, 6982, 304, 23966, 13, 220, 16, 64, 320, 452, 284, 386, 284, 220, 19, 11, 6205, 1404, 445, 284, 468, 284, 220, 972, 13, 15, 9653, 11, 3330, 323, 2872, 1446, 79, 27970, 24310, 3160, 445, 452, 611, 386, 284, 220, 18, 13, 1399, 9653, 570, 362, 41891, 2955, 26420, 40044, 3544, 11, 5043, 323, 81193, 704, 8838, 90649, 91621, 320, 577, 611, 445, 118792, 220, 966, 11587, 320, 258, 90649, 91621, 2753, 1109, 220, 15, 13, 1721, 445, 2652, 2077, 892, 2753, 1109, 220, 15, 13, 2589, 274, 8, 315, 279, 1446, 79, 27970, 24310, 11, 16625, 555, 264, 27946, 9249, 1510, 320, 358, 366, 220, 1544, 13, 20, 99877, 8, 304, 459, 13489, 14113, 24924, 2115, 426, 320, 97364, 426, 284, 220, 10697, 20903, 220, 845, 296, 51, 8, 320, 4151, 41665, 2956, 23966, 13, 220, 16, 1174, 99371, 435, 14801, 13, 220, 17, 1389, 220, 21, 323, 99371, 18559, 220, 17, 1389, 220, 20, 369, 3649, 570, 1556, 44064, 1646, 33432, 555, 9526, 649, 387, 1511, 311, 8641, 2955, 11709, 369, 264, 11716, 481, 66669, 2077, 304, 264, 7353, 2134, 315, 24924, 2115, 36486, 320, 2000, 3187, 11, 426, 11293, 311, 220, 914, 296, 51, 26, 1518, 41665, 2956, 23966, 13, 220, 17, 323, 99371, 7181, 220, 18, 13, 16, 7609, 19575, 220, 16, 65, 5039, 430, 9678, 16798, 1154, 320, 650, 284, 314, 650, 503, 6547, 315, 1404, 220, 17, 7, 452, 489, 386, 883, 9435, 311, 279, 35688, 20946, 7124, 279, 8141, 315, 1510, 17915, 320, 622, 883, 304, 279, 6929, 535, 4009, 320, 4151, 19331, 3857, 3451, 39212, 2585, 529, 323, 99371, 23966, 13, 220, 22, 369, 3649, 8, 323, 9093, 2585, 279, 54333, 406, 89, 5457, 11, 435, 17329, 284, 622, 25800, 426, 662, 578, 29079, 398, 4332, 1180, 4090, 435, 17329, 320, 622, 883, 27667, 279, 2254, 11, 704, 8838, 90649, 320, 1901, 5216, 8, 79212, 811, 320, 577, 284, 314, 577, 602, 2529, 1405, 577, 602, 374, 279, 44153, 315, 279, 602, 270, 2494, 8, 315, 279, 6205, 304, 264, 24924, 2115, 426, 27210, 449, 1202, 38336, 11, 28462, 264, 3544, 743, 315, 15987, 2380, 33520, 320, 18, 35, 8, 21483, 505, 279, 1890, 71261, 6070, 13, 23966, 13, 220, 16, 25, 51684, 2322, 300, 324, 7760, 16625, 555, 312, 15252, 76, 481, 66669, 1180, 4090, 13, 264, 1174, 328, 82149, 40134, 320, 268, 27995, 291, 1684, 8, 315, 264, 18740, 9518, 11546, 6205, 20968, 505, 279, 1446, 79, 27970, 51045, 31706, 315, 15792, 23396, 323, 33150, 13931, 13, 293, 1174, 328, 82149, 40134, 315, 264, 220, 19, 25800, 220, 19, 6205, 9277, 304, 264, 24924, 2115, 320, 258, 90649, 449, 279, 6205, 304, 264, 38336, 5216, 570, 34831, 16798, 1154, 7124, 279, 1510, 17915, 8141, 320, 622, 883, 304, 279, 6205, 323, 16472, 2585, 279, 2254, 54333, 406, 89, 81149, 1180, 4090, 13, 272, 1174, 435, 19657, 5825, 128257, 198, 128256, 78191, 198, 4674, 388, 520, 27453, 3907, 617, 8040, 264, 69311, 8579, 7479, 430, 649, 31978, 44909, 5196, 311, 56459, 6302, 304, 7138, 13, 432, 989, 287, 389, 66669, 1180, 4090, 11, 22936, 34579, 323, 5780, 6975, 311, 1376, 502, 33483, 11, 279, 7479, 649, 1524, 4048, 311, 10737, 311, 48419, 95597, 1778, 439, 11102, 5540, 11, 16907, 17413, 477, 10223, 22484, 13, 578, 3495, 8111, 2930, 6250, 220, 1691, 304, 279, 8486, 22037, 13, 330, 1687, 2351, 27762, 555, 279, 4623, 315, 26991, 3769, 6012, 477, 22936, 28198, 315, 459, 46036, 1665, 389, 279, 11722, 11, 902, 1436, 387, 5505, 369, 8522, 1093, 8579, 74706, 11, 57088, 8903, 11, 39538, 318, 5411, 7384, 11, 323, 3917, 19440, 10051, 4893, 1359, 1071, 41235, 2303, 361, 22652, 11, 18328, 14561, 315, 22936, 15009, 323, 7384, 8198, 520, 27453, 13, 330, 1687, 527, 21760, 389, 15009, 279, 6211, 315, 5030, 430, 12775, 956, 1027, 87010, 11, 902, 374, 264, 5128, 16615, 3465, 311, 11322, 11, 5423, 369, 8579, 7384, 1210, 10573, 420, 15792, 11, 19303, 3769, 4639, 5196, 311, 56459, 18435, 17301, 323, 5882, 287, 75818, 304, 1972, 7394, 13, 432, 989, 287, 389, 66669, 1180, 4090, 11, 22936, 34579, 323, 5780, 6975, 311, 1376, 502, 33483, 11, 279, 7479, 649, 1524, 4048, 311, 10737, 311, 48419, 95597, 1778, 439, 11102, 5540, 11, 16907, 17413, 477, 10223, 22484, 13, 16666, 25, 6383, 263, 2428, 40593, 11, 27453, 3907, 30013, 990, 389, 27448, 287, 5030, 11, 4184, 311, 22652, 11, 12775, 956, 11383, 1027, 56586, 481, 26, 433, 596, 1027, 56168, 4619, 13, 3011, 374, 11, 8579, 27529, 19167, 449, 6319, 4642, 5540, 649, 6541, 872, 21483, 1990, 2478, 21483, 11, 1093, 264, 6710, 315, 2780, 10830, 11, 304, 2077, 311, 3177, 477, 8798, 477, 1023, 56688, 31854, 13, 763, 13168, 11, 22652, 323, 1077, 27692, 4934, 311, 1893, 2555, 1790, 810, 687, 69855, 430, 1436, 27448, 323, 312, 21678, 439, 3629, 439, 433, 13452, 1139, 904, 22655, 3284, 21483, 13, 2057, 1893, 1778, 264, 7479, 11, 279, 12074, 3940, 555, 35744, 704, 264, 5950, 315, 26332, 12970, 51045, 1903, 315, 264, 15792, 6324, 315, 6761, 43669, 7913, 555, 264, 15792, 47393, 6324, 13, 578, 3927, 51045, 527, 1120, 8223, 19748, 442, 2481, 12314, 2345, 9274, 279, 26839, 315, 264, 24428, 24722, 17223, 2753, 1109, 264, 2606, 26402, 7029, 13, 578, 3177, 2136, 315, 279, 51045, 6276, 24924, 8603, 311, 6847, 323, 19019, 79212, 1124, 13, 2057, 7068, 2254, 8603, 11, 279, 7479, 374, 2231, 1139, 264, 3428, 11852, 1118, 24924, 2115, 13, 62038, 4442, 1893, 264, 6485, 719, 6847, 45207, 20314, 1510, 3235, 279, 21411, 5950, 11, 10043, 279, 704, 8838, 90649, 44153, 315, 279, 5950, 13, 330, 2028, 374, 279, 1176, 21075, 8579, 7479, 430, 374, 5043, 3403, 311, 30357, 56459, 264, 19815, 6211, 7666, 18148, 1920, 304, 7138, 1359, 22652, 1071, 13, 330, 4054, 1401, 12178, 374, 279, 24693, 2955, 430, 20682, 459, 19018, 13790, 5133, 1990, 279, 20314, 11374, 323, 279, 13239, 6211, 11, 902, 3727, 433, 4228, 311, 7216, 704, 1268, 311, 3881, 16798, 1154, 311, 11322, 264, 7029, 8205, 315, 2218, 21483, 1210, 578, 502, 330, 4150, 300, 10730, 1, 5039, 1022, 264, 7029, 1358, 315, 27448, 287, 323, 28003, 16671, 7512, 13, 1102, 11705, 7173, 4282, 430, 10205, 323, 3351, 2212, 279, 7479, 1093, 264, 8415, 4560, 311, 1505, 1202, 1648, 704, 505, 1234, 264, 39139, 11, 43524, 1113, 12330, 12912, 11, 323, 264, 40661, 48891, 315, 264, 14812, 6068, 77315, 323, 113042, 10964, 8800, 264, 6573, 7479, 13, 1628, 433, 19159, 1521, 21483, 323, 28198, 520, 904, 4732, 477, 31903, 12974, 11, 7438, 433, 649, 45087, 24281, 430, 31691, 8415, 477, 50511, 7069, 7118, 11053, 304, 6435, 11633, 477, 5043, 4741, 13, 3161, 18632, 16967, 279, 27448, 287, 7479, 11, 279, 687, 26973, 380, 7479, 649, 1101, 4048, 311, 53875, 21483, 323, 12912, 389, 1202, 1866, 13, 3296, 14297, 43468, 279, 9435, 16798, 1154, 11, 264, 6975, 12384, 5097, 304, 220, 18, 35, 32758, 11302, 323, 12678, 704, 1148, 6372, 279, 2204, 11374, 617, 389, 279, 2322, 300, 10730, 596, 6211, 13, 763, 279, 5684, 11, 264, 3823, 33552, 30652, 449, 220, 845, 3776, 32094, 14297, 29735, 1234, 264, 6382, 11, 323, 279, 7479, 41585, 279, 19567, 14268, 13, 330, 791, 2585, 3250, 956, 617, 311, 1440, 4205, 922, 279, 22027, 315, 279, 7384, 11, 433, 1120, 5097, 2678, 7504, 323, 32860, 311, 1518, 422, 433, 596, 3794, 12401, 311, 279, 2218, 477, 539, 1359, 22652, 1071, 13, 330, 2181, 5131, 5097, 922, 1403, 4520, 311, 11322, 264, 502, 6211, 11, 719, 584, 3987, 311, 9778, 7417, 279, 11302, 1887, 323, 6975, 12384, 311, 279, 1486, 430, 433, 596, 7154, 1972, 7394, 1210, 9393, 279, 7479, 33992, 5196, 311, 3351, 1555, 9269, 323, 1493, 11, 433, 649, 1101, 10737, 311, 5674, 11, 16907, 7106, 17413, 477, 12434, 2349, 13, 763, 832, 9526, 11, 433, 6288, 47310, 311, 56459, 264, 7173, 3252, 73266, 8994, 832, 315, 1202, 51045, 1694, 4018, 13, 763, 2500, 11, 433, 29972, 311, 56459, 264, 4528, 6211, 8994, 264, 4785, 1694, 12673, 311, 832, 315, 279, 5950, 596, 7954, 13, 2684, 527, 1690, 14247, 10708, 311, 13334, 279, 5569, 323, 6683, 315, 279, 8579, 7479, 13, 1789, 3187, 11, 459, 1358, 315, 27529, 649, 5569, 279, 1404, 709, 311, 430, 315, 264, 31687, 4264, 13, 2582, 59251, 12823, 449, 5190, 16437, 649, 5569, 279, 1404, 1523, 311, 832, 2606, 26402, 11, 3339, 433, 810, 14791, 369, 94612, 8522, 13, 38727, 4741, 11, 22652, 6944, 311, 1893, 59101, 2322, 300, 324, 7760, 449, 18751, 6211, 1355, 49205, 5865, 311, 2804, 1972, 7394, 6211, 28003, 16671, 315, 6485, 11, 8915, 27529, 304, 7138, 11, 1778, 439, 279, 3090, 436, 51660, 11, 7795, 66079, 477, 279, 3823, 3663, 13, 578, 10278, 1253, 1101, 1427, 1139, 40188, 810, 6956, 1139, 279, 25018, 11, 1778, 439, 389, 53955, 2410, 8336, 11, 26148, 11, 55580, 5070, 477, 21401, 10758, 17357, 13, 330, 50909, 449, 279, 33436, 315, 6968, 56586, 481, 323, 59101, 7384, 11, 584, 48146, 3938, 7384, 690, 387, 3025, 311, 11857, 5694, 311, 8854, 5865, 43111, 323, 16681, 3210, 1359, 1071, 22652, 13, 330, 21365, 7384, 649, 5647, 323, 45493, 8670, 477, 2038, 505, 279, 3932, 11, 323, 5276, 323, 10737, 4184, 311, 279, 1972, 7394, 3966, 315, 872, 3230, 5178, 11, 1120, 1093, 279, 8162, 63005, 304, 6295, 16905, 220, 21, 13, 578, 8579, 7479, 1253, 1505, 8522, 439, 264, 8122, 3376, 660, 12585, 11, 8915, 220, 18, 35, 3113, 11, 88068, 11, 506, 437, 28193, 477, 1023, 7941, 11, 16003, 27529, 430, 649, 990, 304, 25984, 11, 50235, 22484, 1210, 220, 128257, 198 ]

2,465

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Optical coherence tomography (OCT) is a widely used non-invasive biomedical imaging modality that can rapidly provide volumetric images of samples. Here, we present a deep learning-based image reconstruction framework that can generate swept-source OCT (SS-OCT) images using undersampled spectral data, without any spatial aliasing artifacts. This neural network-based image reconstruction does not require any hardware changes to the optical setup and can be easily integrated with existing swept-source or spectral-domain OCT systems to reduce the amount of raw spectral data to be acquired. To show the efficacy of this framework, we trained and blindly tested a deep neural network using mouse embryo samples imaged by an SS-OCT system. Using 2-fold undersampled spectral data (i.e., 640 spectral points per A-line), the trained neural network can blindly reconstruct 512 A-lines in 0.59 ms using multiple graphics-processing units (GPUs), removing spatial aliasing artifacts due to spectral undersampling, also presenting a very good match to the images of the same samples, reconstructed using the full spectral OCT data (i.e., 1280 spectral points per A-line). We also successfully demonstrate that this framework can be further extended to process 3× undersampled spectral data per A-line, with some performance degradation in the reconstructed image quality compared to 2× spectral undersampling. Furthermore, an A-line-optimized undersampling method is presented by jointly optimizing the spectral sampling locations and the corresponding image reconstruction network, which improved the overall imaging performance using less spectral data points per A-line compared to 2× or 3× spectral undersampling results. This deep learning-enabled image reconstruction approach can be broadly used in various forms of spectral-domain OCT systems, helping to increase their imaging speed without sacrificing image resolution and signal-to-noise ratio. Introduction Optical coherence tomography (OCT) is a non-invasive imaging modality that can provide three-dimensional (3D) information of optical scattering properties of biological samples. The first generation of OCT systems were based on time-domain (TD) imaging 1 , using mechanical path-length scanning. However, the relatively slow data acquisition speed of the early TDOCT systems partially limited their applicability for in vivo imaging applications. The introduction of the Fourier Domain (FD) OCT techniques 2 , 3 with higher sensitivity 4 , 5 has contributed to a dramatic increase in imaging speed and quality 6 . Modern FDOCT systems can routinely achieve line rates of 50–400 kHz 7 , 8 , 9 , 10 , 11 , 12 and there have been recent research efforts to further improve the speed of A-scans to tens of MHz 13 , 14 . Some of these advances employed hardware modifications to the optical set-up to improve OCT imaging speed and quality, and focused on, e.g., improving the OCT system design, including improvements in high-speed sources 13 , 15 , 16 , also opening up new applications such as single-shot elastography 17 and others 18 , 19 , 20 . Recently, we have experienced the emergence of deep-learning-based image reconstruction and enhancement methods 21 , 22 , 23 to advance optical microscopy techniques, performing e.g., image super resolution 23 , 24 , 25 , 26 , 27 , 28 , autofocusing 29 , 30 , 31 , depth of field enhancement 32 , 33 , 34 , holographic image reconstruction, and phase recovery 35 , 36 , 37 , 38 , among many others 39 , 40 , 41 , 42 . Inspired by these applications of deep learning and neural networks in optical microscopy, here we demonstrate the use of deep learning to reconstruct swept-source OCT (SS-OCT) images using undersampled spectral data points. Without the need to perform any hardware modifications to an existing SS-OCT system, we show that a trained neural network can rapidly process undersampled spectral data and match, at its output, the image quality of standard SS-OCT reconstructions of the same samples that used 2-fold more spectral data per A-line. A major challenge in reducing the number of spectral data points in an OCT system without sacrificing resolution is the aliasing artifacts introduced by undersampling. According to the Nyquist sampling theorem, the maximum axial depth within the tissue that can be imaged without spatial aliasing is proportional to 43 : $$z_{\\max } \\propto \\left| {\\frac{\\pi }{{2 \\cdot \\delta _{\\mathrm{s}}k}}} \\right| = \\left| {\\frac{{\\lambda _0^2}}{{4 \\cdot \\delta _{\\mathrm{s}}\\lambda }}} \\right|$$ (1) where δ s k is the spectral sampling interval in k space, δ s λ is the wavelength sampling interval, and λ 0 is the central wavelength. When the spectral sampling interval increases, it reduces the maximum depth that can be imaged without spatial aliasing artifacts. In our approach, we first reconstructed each A-line with 2× less spectral data (eliminating every other spectral sample), which resulted in severe spatial aliasing artifacts. We then trained a deep neural network to remove these aliasing artifacts that are introduced by spectral undersampling, matching the image reconstruction results that used all the available spectral data points. To demonstrate the success of this deep learning-based OCT image reconstruction approach, we used an SS-OCT 3 system to image murine embryo samples. The trained neural network successfully generalized, and removed the spatial aliasing artifacts in the reconstructed images of new embryo samples that were never seen by the network before. We further extended this framework to process 3× undersampled spectral data per A-line, and showed that it can be used to remove even more severe aliasing artifacts that are introduced by 3× spectral undersampling, although at the cost of some degradation in the reconstructed image quality compared to 2× spectral undersampling results. As an alternative approach, we also introduced an A-line-optimized spectral sampling framework to further reduce the acquired spectral data per A-line. The spectral sampling locations and the corresponding OCT image reconstruction network were jointly optimized during the training process, allowing this method to use less spectral data, while achieving better image reconstruction performance compared to 2× or 3× spectral undersampling results. In addition to overcoming spectral undersampling related image artifacts, the inference time of the deep neural network is also optimized, achieving an average image reconstruction time of 6.73 ms for 512 A-lines,", "role": "user" }, { "content": "Optical coherence tomography (OCT) is a non-invasive imaging method that can provide 3D information of biological samples. The first generation of OCT systems were based on time-domain imaging, using a mechanical scanning set-up. However, the relatively slow data acquisition speed of these earlier time-domain OCT systems partially limited their use for imaging live specimen. The introduction of the spectral-domain OCT techniques with higher sensitivity has contributed to a dramatic increase in imaging speed and quality. OCT is now widely used in diagnostic medicine, for example in ophthalmology, to noninvasively obtain detailed 3D images of the retina and underlying tissue structure. In a new paper published in Light: Science & Applications, a team of UCLA and University of Houston (UH) scientists have developed a deep learning-based OCT image reconstruction method that can successfully generate 3D images of tissue specimen using significantly less spectral data than normally required. Using standard image reconstruction methods employed in OCT, undersampled spectral data, where some of the spectral measurements are omitted, would result in severe spatial artifacts in the reconstructed images, obscuring 3D information and structural details of the sample to be visualized. In their new approach, UCLA and UH researchers trained a neural network using deep learning to rapidly reconstruct 3D images of tissue samples with much less spectral data than normally acquired in a typical OCT system, successfully removing the spatial artifacts observed in standard image reconstruction methods. The efficacy and robustness of this new method was demonstrated by imaging various human and mouse tissue samples using 3-fold less spectral data captured by a state-of-the-art swept-source OCT system. Running on graphics processing units (GPUs), the neural network successfully eliminated severe spatial artifacts due to undersampling and omission of most spectral data points in less than one-thousandth of a second for an OCT image that is composed of 512 depth scans (A-lines). \"These results highlight the transformative potential of this neural network-based OCT image reconstruction framework, which can be easily integrated with various spectral domain OCT systems, to improve their 3D imaging speed without sacrificing resolution or signal-to-noise of the reconstructed images,\" said Dr. Aydogan Ozcan, the Chancellor's Professor of Electrical and Computer Engineering at UCLA and an associate director of the California NanoSystems Institute, who is the senior corresponding author of the work. This research was led by Dr. Ozcan, in collaboration with Dr. Kirill Larin, a Professor of Biomedical Engineering at University of Houston. The other authors of this work are Yijie Zhang, Tairan Liu, Manmohan Singh, Ege Çetintaş, and Yair Rivenson. Dr. Ozcan also has UCLA faculty appointments in bioengineering and surgery, and is an HHMI Professor. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Optical coherence tomography (OCT) is a widely used non-invasive biomedical imaging modality that can rapidly provide volumetric images of samples. Here, we present a deep learning-based image reconstruction framework that can generate swept-source OCT (SS-OCT) images using undersampled spectral data, without any spatial aliasing artifacts. This neural network-based image reconstruction does not require any hardware changes to the optical setup and can be easily integrated with existing swept-source or spectral-domain OCT systems to reduce the amount of raw spectral data to be acquired. To show the efficacy of this framework, we trained and blindly tested a deep neural network using mouse embryo samples imaged by an SS-OCT system. Using 2-fold undersampled spectral data (i.e., 640 spectral points per A-line), the trained neural network can blindly reconstruct 512 A-lines in 0.59 ms using multiple graphics-processing units (GPUs), removing spatial aliasing artifacts due to spectral undersampling, also presenting a very good match to the images of the same samples, reconstructed using the full spectral OCT data (i.e., 1280 spectral points per A-line). We also successfully demonstrate that this framework can be further extended to process 3× undersampled spectral data per A-line, with some performance degradation in the reconstructed image quality compared to 2× spectral undersampling. Furthermore, an A-line-optimized undersampling method is presented by jointly optimizing the spectral sampling locations and the corresponding image reconstruction network, which improved the overall imaging performance using less spectral data points per A-line compared to 2× or 3× spectral undersampling results. This deep learning-enabled image reconstruction approach can be broadly used in various forms of spectral-domain OCT systems, helping to increase their imaging speed without sacrificing image resolution and signal-to-noise ratio. Introduction Optical coherence tomography (OCT) is a non-invasive imaging modality that can provide three-dimensional (3D) information of optical scattering properties of biological samples. The first generation of OCT systems were based on time-domain (TD) imaging 1 , using mechanical path-length scanning. However, the relatively slow data acquisition speed of the early TDOCT systems partially limited their applicability for in vivo imaging applications. The introduction of the Fourier Domain (FD) OCT techniques 2 , 3 with higher sensitivity 4 , 5 has contributed to a dramatic increase in imaging speed and quality 6 . Modern FDOCT systems can routinely achieve line rates of 50–400 kHz 7 , 8 , 9 , 10 , 11 , 12 and there have been recent research efforts to further improve the speed of A-scans to tens of MHz 13 , 14 . Some of these advances employed hardware modifications to the optical set-up to improve OCT imaging speed and quality, and focused on, e.g., improving the OCT system design, including improvements in high-speed sources 13 , 15 , 16 , also opening up new applications such as single-shot elastography 17 and others 18 , 19 , 20 . Recently, we have experienced the emergence of deep-learning-based image reconstruction and enhancement methods 21 , 22 , 23 to advance optical microscopy techniques, performing e.g., image super resolution 23 , 24 , 25 , 26 , 27 , 28 , autofocusing 29 , 30 , 31 , depth of field enhancement 32 , 33 , 34 , holographic image reconstruction, and phase recovery 35 , 36 , 37 , 38 , among many others 39 , 40 , 41 , 42 . Inspired by these applications of deep learning and neural networks in optical microscopy, here we demonstrate the use of deep learning to reconstruct swept-source OCT (SS-OCT) images using undersampled spectral data points. Without the need to perform any hardware modifications to an existing SS-OCT system, we show that a trained neural network can rapidly process undersampled spectral data and match, at its output, the image quality of standard SS-OCT reconstructions of the same samples that used 2-fold more spectral data per A-line. A major challenge in reducing the number of spectral data points in an OCT system without sacrificing resolution is the aliasing artifacts introduced by undersampling. According to the Nyquist sampling theorem, the maximum axial depth within the tissue that can be imaged without spatial aliasing is proportional to 43 : $$z_{\max } \propto \left| {\frac{\pi }{{2 \cdot \delta _{\mathrm{s}}k}}} \right| = \left| {\frac{{\lambda _0^2}}{{4 \cdot \delta _{\mathrm{s}}\lambda }}} \right|$$ (1) where δ s k is the spectral sampling interval in k space, δ s λ is the wavelength sampling interval, and λ 0 is the central wavelength. When the spectral sampling interval increases, it reduces the maximum depth that can be imaged without spatial aliasing artifacts. In our approach, we first reconstructed each A-line with 2× less spectral data (eliminating every other spectral sample), which resulted in severe spatial aliasing artifacts. We then trained a deep neural network to remove these aliasing artifacts that are introduced by spectral undersampling, matching the image reconstruction results that used all the available spectral data points. To demonstrate the success of this deep learning-based OCT image reconstruction approach, we used an SS-OCT 3 system to image murine embryo samples. The trained neural network successfully generalized, and removed the spatial aliasing artifacts in the reconstructed images of new embryo samples that were never seen by the network before. We further extended this framework to process 3× undersampled spectral data per A-line, and showed that it can be used to remove even more severe aliasing artifacts that are introduced by 3× spectral undersampling, although at the cost of some degradation in the reconstructed image quality compared to 2× spectral undersampling results. As an alternative approach, we also introduced an A-line-optimized spectral sampling framework to further reduce the acquired spectral data per A-line. The spectral sampling locations and the corresponding OCT image reconstruction network were jointly optimized during the training process, allowing this method to use less spectral data, while achieving better image reconstruction performance compared to 2× or 3× spectral undersampling results. In addition to overcoming spectral undersampling related image artifacts, the inference time of the deep neural network is also optimized, achieving an average image reconstruction time of 6.73 ms for 512 A-lines,<|im_end|> <|im_start|>assistant Optical coherence tomography (OCT) is a non-invasive imaging method that can provide 3D information of biological samples. The first generation of OCT systems were based on time-domain imaging, using a mechanical scanning set-up. However, the relatively slow data acquisition speed of these earlier time-domain OCT systems partially limited their use for imaging live specimen. The introduction of the spectral-domain OCT techniques with higher sensitivity has contributed to a dramatic increase in imaging speed and quality. OCT is now widely used in diagnostic medicine, for example in ophthalmology, to noninvasively obtain detailed 3D images of the retina and underlying tissue structure. In a new paper published in Light: Science & Applications, a team of UCLA and University of Houston (UH) scientists have developed a deep learning-based OCT image reconstruction method that can successfully generate 3D images of tissue specimen using significantly less spectral data than normally required. Using standard image reconstruction methods employed in OCT, undersampled spectral data, where some of the spectral measurements are omitted, would result in severe spatial artifacts in the reconstructed images, obscuring 3D information and structural details of the sample to be visualized. In their new approach, UCLA and UH researchers trained a neural network using deep learning to rapidly reconstruct 3D images of tissue samples with much less spectral data than normally acquired in a typical OCT system, successfully removing the spatial artifacts observed in standard image reconstruction methods. The efficacy and robustness of this new method was demonstrated by imaging various human and mouse tissue samples using 3-fold less spectral data captured by a state-of-the-art swept-source OCT system. Running on graphics processing units (GPUs), the neural network successfully eliminated severe spatial artifacts due to undersampling and omission of most spectral data points in less than one-thousandth of a second for an OCT image that is composed of 512 depth scans (A-lines). "These results highlight the transformative potential of this neural network-based OCT image reconstruction framework, which can be easily integrated with various spectral domain OCT systems, to improve their 3D imaging speed without sacrificing resolution or signal-to-noise of the reconstructed images," said Dr. Aydogan Ozcan, the Chancellor's Professor of Electrical and Computer Engineering at UCLA and an associate director of the California NanoSystems Institute, who is the senior corresponding author of the work. This research was led by Dr. Ozcan, in collaboration with Dr. Kirill Larin, a Professor of Biomedical Engineering at University of Houston. The other authors of this work are Yijie Zhang, Tairan Liu, Manmohan Singh, Ege Çetintaş, and Yair Rivenson. Dr. Ozcan also has UCLA faculty appointments in bioengineering and surgery, and is an HHMI Professor. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 75939, 78925, 10390, 5814, 320, 46, 1182, 8, 374, 264, 13882, 1511, 2536, 3502, 78134, 94612, 32758, 1491, 2786, 430, 649, 19019, 3493, 63920, 16743, 5448, 315, 10688, 13, 5810, 11, 584, 3118, 264, 5655, 6975, 6108, 2217, 43738, 12914, 430, 649, 7068, 41323, 31874, 67277, 320, 1242, 24540, 1182, 8, 5448, 1701, 26445, 66107, 57077, 828, 11, 2085, 904, 29079, 15904, 287, 36136, 13, 1115, 30828, 4009, 6108, 2217, 43738, 1587, 539, 1397, 904, 12035, 4442, 311, 279, 29393, 6642, 323, 649, 387, 6847, 18751, 449, 6484, 41323, 31874, 477, 57077, 73894, 67277, 6067, 311, 8108, 279, 3392, 315, 7257, 57077, 828, 311, 387, 19426, 13, 2057, 1501, 279, 41265, 315, 420, 12914, 11, 584, 16572, 323, 89447, 12793, 264, 5655, 30828, 4009, 1701, 8814, 87701, 10688, 737, 3359, 555, 459, 18679, 24540, 1182, 1887, 13, 12362, 220, 17, 24325, 26445, 66107, 57077, 828, 320, 72, 1770, 2637, 220, 14033, 57077, 3585, 824, 362, 8614, 705, 279, 16572, 30828, 4009, 649, 89447, 44928, 220, 8358, 362, 84463, 304, 220, 15, 13, 2946, 10030, 1701, 5361, 14515, 70293, 8316, 320, 25434, 3642, 705, 18054, 29079, 15904, 287, 36136, 4245, 311, 57077, 26445, 30809, 11, 1101, 32644, 264, 1633, 1695, 2489, 311, 279, 5448, 315, 279, 1890, 10688, 11, 83104, 1701, 279, 2539, 57077, 67277, 828, 320, 72, 1770, 2637, 220, 4386, 15, 57077, 3585, 824, 362, 8614, 570, 1226, 1101, 7946, 20461, 430, 420, 12914, 649, 387, 4726, 11838, 311, 1920, 220, 18, 18028, 26445, 66107, 57077, 828, 824, 362, 8614, 11, 449, 1063, 5178, 53568, 304, 279, 83104, 2217, 4367, 7863, 311, 220, 17, 18028, 57077, 26445, 30809, 13, 24296, 11, 459, 362, 8614, 12, 99968, 26445, 30809, 1749, 374, 10666, 555, 53258, 74142, 279, 57077, 25936, 10687, 323, 279, 12435, 2217, 43738, 4009, 11, 902, 13241, 279, 8244, 32758, 5178, 1701, 2753, 57077, 828, 3585, 824, 362, 8614, 7863, 311, 220, 17, 18028, 477, 220, 18, 18028, 57077, 26445, 30809, 3135, 13, 1115, 5655, 6975, 55292, 2217, 43738, 5603, 649, 387, 44029, 1511, 304, 5370, 7739, 315, 57077, 73894, 67277, 6067, 11, 10695, 311, 5376, 872, 32758, 4732, 2085, 73128, 2217, 11175, 323, 8450, 4791, 29466, 1082, 11595, 13, 29438, 75939, 78925, 10390, 5814, 320, 46, 1182, 8, 374, 264, 2536, 3502, 78134, 32758, 1491, 2786, 430, 649, 3493, 2380, 33520, 320, 18, 35, 8, 2038, 315, 29393, 72916, 6012, 315, 24156, 10688, 13, 578, 1176, 9659, 315, 67277, 6067, 1051, 3196, 389, 892, 73894, 320, 17417, 8, 32758, 220, 16, 1174, 1701, 22936, 1853, 30425, 36201, 13, 4452, 11, 279, 12309, 6435, 828, 24279, 4732, 315, 279, 4216, 350, 5989, 1182, 6067, 26310, 7347, 872, 4666, 2968, 369, 304, 41294, 32758, 8522, 13, 578, 17219, 315, 279, 90054, 21749, 320, 14938, 8, 67277, 12823, 220, 17, 1174, 220, 18, 449, 5190, 27541, 220, 19, 1174, 220, 20, 706, 20162, 311, 264, 22520, 5376, 304, 32758, 4732, 323, 4367, 220, 21, 662, 18766, 435, 5989, 1182, 6067, 649, 40076, 11322, 1584, 7969, 315, 220, 1135, 4235, 3443, 70726, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 323, 1070, 617, 1027, 3293, 3495, 9045, 311, 4726, 7417, 279, 4732, 315, 362, 31419, 598, 311, 22781, 315, 37594, 220, 1032, 1174, 220, 975, 662, 4427, 315, 1521, 31003, 20011, 12035, 29882, 311, 279, 29393, 743, 5352, 311, 7417, 67277, 32758, 4732, 323, 4367, 11, 323, 10968, 389, 11, 384, 1326, 2637, 18899, 279, 67277, 1887, 2955, 11, 2737, 18637, 304, 1579, 30699, 8336, 220, 1032, 1174, 220, 868, 1174, 220, 845, 1174, 1101, 8736, 709, 502, 8522, 1778, 439, 3254, 64630, 92185, 5814, 220, 1114, 323, 3885, 220, 972, 1174, 220, 777, 1174, 220, 508, 662, 42096, 11, 584, 617, 10534, 279, 49179, 315, 5655, 71856, 6108, 2217, 43738, 323, 27886, 5528, 220, 1691, 1174, 220, 1313, 1174, 220, 1419, 311, 12178, 29393, 92914, 12823, 11, 16785, 384, 1326, 2637, 2217, 2307, 11175, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 1174, 220, 1627, 1174, 220, 1544, 1174, 220, 1591, 1174, 45545, 87595, 220, 1682, 1174, 220, 966, 1174, 220, 2148, 1174, 8149, 315, 2115, 27886, 220, 843, 1174, 220, 1644, 1174, 220, 1958, 1174, 72927, 79173, 2217, 43738, 11, 323, 10474, 13654, 220, 1758, 1174, 220, 1927, 1174, 220, 1806, 1174, 220, 1987, 1174, 4315, 1690, 3885, 220, 2137, 1174, 220, 1272, 1174, 220, 3174, 1174, 220, 2983, 662, 65925, 555, 1521, 8522, 315, 5655, 6975, 323, 30828, 14488, 304, 29393, 92914, 11, 1618, 584, 20461, 279, 1005, 315, 5655, 6975, 311, 44928, 41323, 31874, 67277, 320, 1242, 24540, 1182, 8, 5448, 1701, 26445, 66107, 57077, 828, 3585, 13, 17586, 279, 1205, 311, 2804, 904, 12035, 29882, 311, 459, 6484, 18679, 24540, 1182, 1887, 11, 584, 1501, 430, 264, 16572, 30828, 4009, 649, 19019, 1920, 26445, 66107, 57077, 828, 323, 2489, 11, 520, 1202, 2612, 11, 279, 2217, 4367, 315, 5410, 18679, 24540, 1182, 16456, 20232, 315, 279, 1890, 10688, 430, 1511, 220, 17, 24325, 810, 57077, 828, 824, 362, 8614, 13, 362, 3682, 8815, 304, 18189, 279, 1396, 315, 57077, 828, 3585, 304, 459, 67277, 1887, 2085, 73128, 11175, 374, 279, 15904, 287, 36136, 11784, 555, 26445, 30809, 13, 10771, 311, 279, 37832, 56409, 25936, 58917, 11, 279, 7340, 98280, 8149, 2949, 279, 20438, 430, 649, 387, 737, 3359, 2085, 29079, 15904, 287, 374, 55272, 311, 220, 3391, 551, 27199, 89, 15511, 59, 2880, 335, 1144, 782, 59091, 1144, 2414, 91, 29252, 38118, 36802, 2554, 335, 3052, 17, 1144, 51953, 1144, 20869, 721, 36802, 92650, 85486, 3500, 74, 76642, 1144, 1315, 91, 284, 1144, 2414, 91, 29252, 38118, 3052, 59, 13231, 721, 15, 61, 17, 78386, 19, 1144, 51953, 1144, 20869, 721, 36802, 92650, 85486, 3500, 59, 13231, 99001, 1144, 1315, 91, 14415, 320, 16, 8, 1405, 70434, 274, 597, 374, 279, 57077, 25936, 10074, 304, 597, 3634, 11, 70434, 274, 49438, 374, 279, 46406, 25936, 10074, 11, 323, 49438, 220, 15, 374, 279, 8792, 46406, 13, 3277, 279, 57077, 25936, 10074, 12992, 11, 433, 26338, 279, 7340, 8149, 430, 649, 387, 737, 3359, 2085, 29079, 15904, 287, 36136, 13, 763, 1057, 5603, 11, 584, 1176, 83104, 1855, 362, 8614, 449, 220, 17, 18028, 2753, 57077, 828, 320, 40895, 16252, 1475, 1023, 57077, 6205, 705, 902, 19543, 304, 15748, 29079, 15904, 287, 36136, 13, 1226, 1243, 16572, 264, 5655, 30828, 4009, 311, 4148, 1521, 15904, 287, 36136, 430, 527, 11784, 555, 57077, 26445, 30809, 11, 12864, 279, 2217, 43738, 3135, 430, 1511, 682, 279, 2561, 57077, 828, 3585, 13, 2057, 20461, 279, 2450, 315, 420, 5655, 6975, 6108, 67277, 2217, 43738, 5603, 11, 584, 1511, 459, 18679, 24540, 1182, 220, 18, 1887, 311, 2217, 8309, 483, 87701, 10688, 13, 578, 16572, 30828, 4009, 7946, 67217, 11, 323, 7108, 279, 29079, 15904, 287, 36136, 304, 279, 83104, 5448, 315, 502, 87701, 10688, 430, 1051, 2646, 3970, 555, 279, 4009, 1603, 13, 1226, 4726, 11838, 420, 12914, 311, 1920, 220, 18, 18028, 26445, 66107, 57077, 828, 824, 362, 8614, 11, 323, 8710, 430, 433, 649, 387, 1511, 311, 4148, 1524, 810, 15748, 15904, 287, 36136, 430, 527, 11784, 555, 220, 18, 18028, 57077, 26445, 30809, 11, 8051, 520, 279, 2853, 315, 1063, 53568, 304, 279, 83104, 2217, 4367, 7863, 311, 220, 17, 18028, 57077, 26445, 30809, 3135, 13, 1666, 459, 10778, 5603, 11, 584, 1101, 11784, 459, 362, 8614, 12, 99968, 57077, 25936, 12914, 311, 4726, 8108, 279, 19426, 57077, 828, 824, 362, 8614, 13, 578, 57077, 25936, 10687, 323, 279, 12435, 67277, 2217, 43738, 4009, 1051, 53258, 34440, 2391, 279, 4967, 1920, 11, 10923, 420, 1749, 311, 1005, 2753, 57077, 828, 11, 1418, 32145, 2731, 2217, 43738, 5178, 7863, 311, 220, 17, 18028, 477, 220, 18, 18028, 57077, 26445, 30809, 3135, 13, 763, 5369, 311, 74017, 57077, 26445, 30809, 5552, 2217, 36136, 11, 279, 45478, 892, 315, 279, 5655, 30828, 4009, 374, 1101, 34440, 11, 32145, 459, 5578, 2217, 43738, 892, 315, 220, 21, 13, 5958, 10030, 369, 220, 8358, 362, 84463, 11, 128257, 198, 128256, 78191, 198, 22078, 950, 78925, 10390, 5814, 320, 46, 1182, 8, 374, 264, 2536, 3502, 78134, 32758, 1749, 430, 649, 3493, 220, 18, 35, 2038, 315, 24156, 10688, 13, 578, 1176, 9659, 315, 67277, 6067, 1051, 3196, 389, 892, 73894, 32758, 11, 1701, 264, 22936, 36201, 743, 5352, 13, 4452, 11, 279, 12309, 6435, 828, 24279, 4732, 315, 1521, 6931, 892, 73894, 67277, 6067, 26310, 7347, 872, 1005, 369, 32758, 3974, 58184, 13, 578, 17219, 315, 279, 57077, 73894, 67277, 12823, 449, 5190, 27541, 706, 20162, 311, 264, 22520, 5376, 304, 32758, 4732, 323, 4367, 13, 67277, 374, 1457, 13882, 1511, 304, 15439, 16088, 11, 369, 3187, 304, 297, 81937, 2508, 11, 311, 2536, 258, 4378, 3210, 6994, 11944, 220, 18, 35, 5448, 315, 279, 84827, 323, 16940, 20438, 6070, 13, 763, 264, 502, 5684, 4756, 304, 8828, 25, 10170, 612, 32625, 11, 264, 2128, 315, 50751, 323, 3907, 315, 16386, 320, 52, 39, 8, 14248, 617, 8040, 264, 5655, 6975, 6108, 67277, 2217, 43738, 1749, 430, 649, 7946, 7068, 220, 18, 35, 5448, 315, 20438, 58184, 1701, 12207, 2753, 57077, 828, 1109, 14614, 2631, 13, 12362, 5410, 2217, 43738, 5528, 20011, 304, 67277, 11, 26445, 66107, 57077, 828, 11, 1405, 1063, 315, 279, 57077, 22323, 527, 40542, 11, 1053, 1121, 304, 15748, 29079, 36136, 304, 279, 83104, 5448, 11, 26730, 1711, 220, 18, 35, 2038, 323, 24693, 3649, 315, 279, 6205, 311, 387, 9302, 1534, 13, 763, 872, 502, 5603, 11, 50751, 323, 549, 39, 12074, 16572, 264, 30828, 4009, 1701, 5655, 6975, 311, 19019, 44928, 220, 18, 35, 5448, 315, 20438, 10688, 449, 1790, 2753, 57077, 828, 1109, 14614, 19426, 304, 264, 14595, 67277, 1887, 11, 7946, 18054, 279, 29079, 36136, 13468, 304, 5410, 2217, 43738, 5528, 13, 578, 41265, 323, 22514, 2136, 315, 420, 502, 1749, 574, 21091, 555, 32758, 5370, 3823, 323, 8814, 20438, 10688, 1701, 220, 18, 24325, 2753, 57077, 828, 17439, 555, 264, 1614, 8838, 10826, 38921, 41323, 31874, 67277, 1887, 13, 29125, 389, 14515, 8863, 8316, 320, 25434, 3642, 705, 279, 30828, 4009, 7946, 34373, 15748, 29079, 36136, 4245, 311, 26445, 30809, 323, 84218, 315, 1455, 57077, 828, 3585, 304, 2753, 1109, 832, 7716, 52949, 339, 315, 264, 2132, 369, 459, 67277, 2217, 430, 374, 24306, 315, 220, 8358, 8149, 43739, 320, 32, 84463, 570, 330, 9673, 3135, 11415, 279, 87435, 4754, 315, 420, 30828, 4009, 6108, 67277, 2217, 43738, 12914, 11, 902, 649, 387, 6847, 18751, 449, 5370, 57077, 8106, 67277, 6067, 11, 311, 7417, 872, 220, 18, 35, 32758, 4732, 2085, 73128, 11175, 477, 8450, 4791, 29466, 1082, 315, 279, 83104, 5448, 1359, 1071, 2999, 13, 24852, 18964, 276, 36704, 4919, 11, 279, 48063, 596, 17054, 315, 45034, 323, 17863, 17005, 520, 50751, 323, 459, 22712, 7690, 315, 279, 7188, 64051, 49165, 10181, 11, 889, 374, 279, 10195, 12435, 3229, 315, 279, 990, 13, 1115, 3495, 574, 6197, 555, 2999, 13, 36704, 4919, 11, 304, 20632, 449, 2999, 13, 26608, 484, 32404, 258, 11, 264, 17054, 315, 12371, 61860, 17005, 520, 3907, 315, 16386, 13, 578, 1023, 12283, 315, 420, 990, 527, 816, 3251, 648, 37120, 11, 350, 1334, 276, 38805, 11, 2418, 76, 57572, 27992, 11, 469, 713, 64105, 295, 34569, 7370, 11, 323, 816, 1334, 51768, 34237, 13, 2999, 13, 36704, 4919, 1101, 706, 50751, 22291, 37256, 304, 17332, 99015, 323, 15173, 11, 323, 374, 459, 25788, 9972, 17054, 13, 220, 128257, 198 ]

1,924

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The cooperative Jahn–Teller effect (CJTE) refers to the correlation of distortions arising from individual Jahn–Teller centres in complex compounds 1 , 2 . The effect usually induces strong coupling between the static or dynamic charge, orbital and magnetic ordering, which has been related to many important phenomena such as colossal magnetoresistance 1 , 3 and superconductivity 1 , 4 . Here we report a Na 5/8 MnO 2 superstructure with a pronounced static CJTE that is coupled to an unusual Na vacancy ordering. We visualize this coupled distortion and Na ordering down to the atomic scale. The Mn planes are periodically distorted by a charge modulation on the Mn stripes, which in turn drives an unusually large displacement of some Na ions through long-ranged Na–O–Mn 3+ –O–Na interactions into a highly distorted octahedral site. At lower temperatures, magnetic order appears, in which Mn atomic stripes with different magnetic couplings are interwoven with each other. Our work demonstrates the strong interaction between alkali ordering, displacement, and electronic and magnetic structure, and underlines the important role that structural details play in determining electronic behaviour. Main NaTMO 2 (TM = 3 d transition metal ions) compounds with alternating Na and TM layers have been studied extensively for their potential application in rechargeable batteries 5 , 6 , 7 or as the parent materials of the superconductive cobaltate 5 , 8 , 9 , 10 . Na can be electrochemically and reversibly removed from these materials creating Na x TMO 2 (0 < x < 1) compounds in a process called de-intercalation. Superstructures due to Na-vacancy (V Na ) ordering have been observed and identified to be dominated by the electrostatic interactions in Na x VO 2 (ref. 6 ) and Na x CoO 2 (refs 5 , 8 ). However, Na x MnO 2 is expected to be more complicated as it mixes Mn 3+ ions, which exhibit one of the largest Jahn–Teller distortions in transition metal compounds, and forms antiferromagnetic (AF) Mn 3+ atomic stripes 11 , 12 , 13 , with Mn 4+ ions, which are not Jahn–Teller active and can form ferromagnetic or AF nearest-neighbour couplings, depending on the competition between different direct and indirect exchange mechanisms 14 . As such, Na x MnO 2 is well suited to study the interplay between the V Na ordering, CJTE and the magnetic properties. There have been continuous efforts to directly visualize the CJTE using scanning/transmission electron microscopy 3 , 15 , 16 , 17 (S/TEM). Here, electron diffraction, synchrotron X-ray diffraction (XRD), density functional theory (DFT) and aberration-corrected atomic-resolution STEM imaging are used to determine the superstructure of electrochemically formed Na 5/8 MnO 2 , and to visualize in sodium intercalation compounds the cooperative distortion of the Mn Jahn–Teller centres and their coupling to Na ordering. Rather than being dominated by electrostatic interactions, we show here direct experimental evidence from STEM imaging that the superstructure in Na 5/8 MnO 2 is mainly controlled by Jahn–Teller distortions which induce specific long-ranged Na–V Na interactions through Mn charge and d -orbital orderings. We use neutron powder diffraction, magnetic susceptibility measurements and DFT computations to demonstrate that a ‘magnetic stripe sandwich’ structure is formed at low temperatures, which causes a pronounced change of the magnetic properties. Electrochemical Na removal from NaMnO 2 initially is known to occur through a two-phase reaction, forming a new phase Na x MnO 2 (ref. 18 ). Figure 1a,b shows the structure of conventional monoclinic NaMnO 2 , which is used to index the electron diffraction patterns of Na x MnO 2 shown in Fig. 1c–e . The formation of a superstructure is clear from the (200), (1–22), (12–2) diffraction spots. In the Z -contrast image shown in Fig. 2b , each dot corresponds to either a Na or Mn atomic stripe projected along the [010] or b direction. The periodic intensity modulation of one bright and three dark dots in the Na plane is proportional to the Na concentration in these stripes. The superstructure hkl peaks and STEM Z -contrast information efficiently limit the possible Na orderings in this compound. To determine a unique order, we performed an exhaustive search of the possible superstructures in the supercells up to 32 formula units for several x values in Na x MnO 2 . The only superstructure that matches all of the electron diffractions and STEM images occurs at x = 5/8. The synchrotron XRD refinement ( Supplementary Fig. 1 and Tables 2 and 3 ) was performed on this particular superstructure model starting with DFT relaxed ion coordinates and shows a good fit. Furthermore, DFT calculations show that this superstructure has the lowest energy among the 300 different Na arrangements that we calculated for x = 5/8, with its energy below the tie line connecting the two lowest energy structures at neighbouring Na compositions, indicating that it is thermodynamically stable ( Supplementary Fig. 2 ). On the basis of the experimental and computational data, we conclude that this Na 5/8 MnO 2 superstructure is the new phase formed in the first voltage plateau when Na is de-intercalated from NaMnO 2 (ref. 18 ). It is worth noting that the Na-vacancy arrangement with the lowest electrostatic energy (labelled as Ewald_0 in Supplementary Fig. 2 ) at x = 5/8 is significantly higher in energy, indicating that the electrostatic interactions do not dominate in this structure. Figure 1: Superstructure hkl spots in electron diffraction patterns show the ordering of Na + in Na x MnO 2 . a , The monoclinic structure (C2/m) of pristine NaMnO 2 with the conventional definition of the lattice parameters. The direction of the Jahn–Teller distortion is marked by the white arrows. The grey arrow shows the [011] direction, and the (200) plane is in green. b , Structure looking along [011]. The green, blue and red lines are the [011] projections of (200), (1–22) and (12–2) planes, respectively. c – e , The experimental electron diffraction patterns along [011], [001] and [010] show consistently", "role": "user" }, { "content": "Analysis of a manganese-based crystal by scientists at the National Institute of Standards and Technology (NIST) and the Massachusetts Institute of Technology (MIT) has produced the first clear picture of its molecular structure. The findings could help explain the magnetic and electronic behavior of the whole family of crystals, many of which have potential for use in batteries. The family of crystals it belongs to has no formal name, but it has three branches, each of which is built around manganese, cobalt or iron—transition metals that can have different magnetic and charge properties. But regardless of family branch, its members share a common characteristic: They all store chemical energy in the form of sodium, atoms of which can easily flow into and out of the layers of the crystal when electric current is applied, a talent potentially useful in rechargeable batteries. Other members of this family can do a lot of things in addition to energy storage that interest manufacturers: Some are low-temperature superconductors, while others can convert heat into electricity. The trouble is that all of them are, on the molecular level, messy. Their structures are so convoluted that scientists can't easily figure out why they do what they do, making it hard for a manufacturer to improve their performance. Fortunately, this particular manganese crystal is an exception. \"It's the one stable compound we know of in the manganese branch that has a perfect crystal lattice structure,\" says Jeff Lynn of the NIST Center for Neutron Research (NCNR). \"That perfection means we can isolate all its internal electronic and magnetic interactions and see them clearly. So now, we can start exploring how to make those sodium atoms more movable.\" Team members from MIT made the material and performed analysis using state-of-the-art lab techniques such as electron microscopy, but they needed help from the NCNR's neutron beams to tease out the interactions between its individual atoms. The effort showed that the crystal was unusual for reasons beyond its structural perfection. Its layers absorb sodium in a fashion rarely seen in nature: In each layer, one \"stripe\" of atoms fills up completely with sodium, then the next three stripes fill up only halfway before another full stripe appears. Lynn says the pattern is caused by different charges and magnetic moments that manganese atoms possess in different parts of the crystal, a feature revealed by analysis of the NCNR data. \"This particular crystal is probably not the one you'd use in a battery or some other application, it just permits us to understand what's happening with its internal structure and magnetism for the first time,\" Lynn says. \"Now we have a basis for tailoring the properties of these materials by changing up the transition metals and changing the sodium content. We no longer have to hunt around in the dark and hope.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The cooperative Jahn–Teller effect (CJTE) refers to the correlation of distortions arising from individual Jahn–Teller centres in complex compounds 1 , 2 . The effect usually induces strong coupling between the static or dynamic charge, orbital and magnetic ordering, which has been related to many important phenomena such as colossal magnetoresistance 1 , 3 and superconductivity 1 , 4 . Here we report a Na 5/8 MnO 2 superstructure with a pronounced static CJTE that is coupled to an unusual Na vacancy ordering. We visualize this coupled distortion and Na ordering down to the atomic scale. The Mn planes are periodically distorted by a charge modulation on the Mn stripes, which in turn drives an unusually large displacement of some Na ions through long-ranged Na–O–Mn 3+ –O–Na interactions into a highly distorted octahedral site. At lower temperatures, magnetic order appears, in which Mn atomic stripes with different magnetic couplings are interwoven with each other. Our work demonstrates the strong interaction between alkali ordering, displacement, and electronic and magnetic structure, and underlines the important role that structural details play in determining electronic behaviour. Main NaTMO 2 (TM = 3 d transition metal ions) compounds with alternating Na and TM layers have been studied extensively for their potential application in rechargeable batteries 5 , 6 , 7 or as the parent materials of the superconductive cobaltate 5 , 8 , 9 , 10 . Na can be electrochemically and reversibly removed from these materials creating Na x TMO 2 (0 < x < 1) compounds in a process called de-intercalation. Superstructures due to Na-vacancy (V Na ) ordering have been observed and identified to be dominated by the electrostatic interactions in Na x VO 2 (ref. 6 ) and Na x CoO 2 (refs 5 , 8 ). However, Na x MnO 2 is expected to be more complicated as it mixes Mn 3+ ions, which exhibit one of the largest Jahn–Teller distortions in transition metal compounds, and forms antiferromagnetic (AF) Mn 3+ atomic stripes 11 , 12 , 13 , with Mn 4+ ions, which are not Jahn–Teller active and can form ferromagnetic or AF nearest-neighbour couplings, depending on the competition between different direct and indirect exchange mechanisms 14 . As such, Na x MnO 2 is well suited to study the interplay between the V Na ordering, CJTE and the magnetic properties. There have been continuous efforts to directly visualize the CJTE using scanning/transmission electron microscopy 3 , 15 , 16 , 17 (S/TEM). Here, electron diffraction, synchrotron X-ray diffraction (XRD), density functional theory (DFT) and aberration-corrected atomic-resolution STEM imaging are used to determine the superstructure of electrochemically formed Na 5/8 MnO 2 , and to visualize in sodium intercalation compounds the cooperative distortion of the Mn Jahn–Teller centres and their coupling to Na ordering. Rather than being dominated by electrostatic interactions, we show here direct experimental evidence from STEM imaging that the superstructure in Na 5/8 MnO 2 is mainly controlled by Jahn–Teller distortions which induce specific long-ranged Na–V Na interactions through Mn charge and d -orbital orderings. We use neutron powder diffraction, magnetic susceptibility measurements and DFT computations to demonstrate that a ‘magnetic stripe sandwich’ structure is formed at low temperatures, which causes a pronounced change of the magnetic properties. Electrochemical Na removal from NaMnO 2 initially is known to occur through a two-phase reaction, forming a new phase Na x MnO 2 (ref. 18 ). Figure 1a,b shows the structure of conventional monoclinic NaMnO 2 , which is used to index the electron diffraction patterns of Na x MnO 2 shown in Fig. 1c–e . The formation of a superstructure is clear from the (200), (1–22), (12–2) diffraction spots. In the Z -contrast image shown in Fig. 2b , each dot corresponds to either a Na or Mn atomic stripe projected along the [010] or b direction. The periodic intensity modulation of one bright and three dark dots in the Na plane is proportional to the Na concentration in these stripes. The superstructure hkl peaks and STEM Z -contrast information efficiently limit the possible Na orderings in this compound. To determine a unique order, we performed an exhaustive search of the possible superstructures in the supercells up to 32 formula units for several x values in Na x MnO 2 . The only superstructure that matches all of the electron diffractions and STEM images occurs at x = 5/8. The synchrotron XRD refinement ( Supplementary Fig. 1 and Tables 2 and 3 ) was performed on this particular superstructure model starting with DFT relaxed ion coordinates and shows a good fit. Furthermore, DFT calculations show that this superstructure has the lowest energy among the 300 different Na arrangements that we calculated for x = 5/8, with its energy below the tie line connecting the two lowest energy structures at neighbouring Na compositions, indicating that it is thermodynamically stable ( Supplementary Fig. 2 ). On the basis of the experimental and computational data, we conclude that this Na 5/8 MnO 2 superstructure is the new phase formed in the first voltage plateau when Na is de-intercalated from NaMnO 2 (ref. 18 ). It is worth noting that the Na-vacancy arrangement with the lowest electrostatic energy (labelled as Ewald_0 in Supplementary Fig. 2 ) at x = 5/8 is significantly higher in energy, indicating that the electrostatic interactions do not dominate in this structure. Figure 1: Superstructure hkl spots in electron diffraction patterns show the ordering of Na + in Na x MnO 2 . a , The monoclinic structure (C2/m) of pristine NaMnO 2 with the conventional definition of the lattice parameters. The direction of the Jahn–Teller distortion is marked by the white arrows. The grey arrow shows the [011] direction, and the (200) plane is in green. b , Structure looking along [011]. The green, blue and red lines are the [011] projections of (200), (1–22) and (12–2) planes, respectively. c – e , The experimental electron diffraction patterns along [011], [001] and [010] show consistently<|im_end|> <|im_start|>assistant Analysis of a manganese-based crystal by scientists at the National Institute of Standards and Technology (NIST) and the Massachusetts Institute of Technology (MIT) has produced the first clear picture of its molecular structure. The findings could help explain the magnetic and electronic behavior of the whole family of crystals, many of which have potential for use in batteries. The family of crystals it belongs to has no formal name, but it has three branches, each of which is built around manganese, cobalt or iron—transition metals that can have different magnetic and charge properties. But regardless of family branch, its members share a common characteristic: They all store chemical energy in the form of sodium, atoms of which can easily flow into and out of the layers of the crystal when electric current is applied, a talent potentially useful in rechargeable batteries. Other members of this family can do a lot of things in addition to energy storage that interest manufacturers: Some are low-temperature superconductors, while others can convert heat into electricity. The trouble is that all of them are, on the molecular level, messy. Their structures are so convoluted that scientists can't easily figure out why they do what they do, making it hard for a manufacturer to improve their performance. Fortunately, this particular manganese crystal is an exception. "It's the one stable compound we know of in the manganese branch that has a perfect crystal lattice structure," says Jeff Lynn of the NIST Center for Neutron Research (NCNR). "That perfection means we can isolate all its internal electronic and magnetic interactions and see them clearly. So now, we can start exploring how to make those sodium atoms more movable." Team members from MIT made the material and performed analysis using state-of-the-art lab techniques such as electron microscopy, but they needed help from the NCNR's neutron beams to tease out the interactions between its individual atoms. The effort showed that the crystal was unusual for reasons beyond its structural perfection. Its layers absorb sodium in a fashion rarely seen in nature: In each layer, one "stripe" of atoms fills up completely with sodium, then the next three stripes fill up only halfway before another full stripe appears. Lynn says the pattern is caused by different charges and magnetic moments that manganese atoms possess in different parts of the crystal, a feature revealed by analysis of the NCNR data. "This particular crystal is probably not the one you'd use in a battery or some other application, it just permits us to understand what's happening with its internal structure and magnetism for the first time," Lynn says. "Now we have a basis for tailoring the properties of these materials by changing up the transition metals and changing the sodium content. We no longer have to hunt around in the dark and hope." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 48566, 622, 30660, 4235, 51, 7218, 2515, 320, 34, 41, 2505, 8, 19813, 311, 279, 26670, 315, 70584, 919, 40986, 505, 3927, 622, 30660, 4235, 51, 7218, 36282, 304, 6485, 32246, 220, 16, 1174, 220, 17, 662, 578, 2515, 6118, 90974, 3831, 59086, 1990, 279, 1118, 477, 8915, 6900, 11, 65691, 323, 24924, 22106, 11, 902, 706, 1027, 5552, 311, 1690, 3062, 44247, 1778, 439, 97937, 33297, 4692, 4011, 220, 16, 1174, 220, 18, 323, 2307, 77752, 1968, 220, 16, 1174, 220, 19, 662, 5810, 584, 1934, 264, 13106, 220, 20, 14, 23, 57831, 46, 220, 17, 2307, 7993, 449, 264, 38617, 1118, 61976, 2505, 430, 374, 34356, 311, 459, 19018, 13106, 62562, 22106, 13, 1226, 51187, 420, 34356, 50971, 323, 13106, 22106, 1523, 311, 279, 25524, 5569, 13, 578, 57831, 25761, 527, 48582, 62236, 555, 264, 6900, 67547, 389, 279, 57831, 55788, 11, 902, 304, 2543, 20722, 459, 57899, 3544, 44153, 315, 1063, 13106, 65125, 1555, 1317, 3880, 3811, 13106, 4235, 46, 4235, 44, 77, 220, 18, 10, 1389, 46, 4235, 16589, 22639, 1139, 264, 7701, 62236, 18998, 1494, 36620, 2816, 13, 2468, 4827, 20472, 11, 24924, 2015, 8111, 11, 304, 902, 57831, 25524, 55788, 449, 2204, 24924, 4020, 81402, 527, 958, 86, 16651, 449, 1855, 1023, 13, 5751, 990, 32216, 279, 3831, 16628, 1990, 58998, 8115, 22106, 11, 44153, 11, 323, 14683, 323, 24924, 6070, 11, 323, 1234, 8128, 279, 3062, 3560, 430, 24693, 3649, 1514, 304, 26679, 14683, 17432, 13, 4802, 13106, 51, 10754, 220, 17, 320, 22809, 284, 220, 18, 294, 9320, 9501, 65125, 8, 32246, 449, 73462, 13106, 323, 24929, 13931, 617, 1027, 20041, 42817, 369, 872, 4754, 3851, 304, 47923, 481, 27360, 220, 20, 1174, 220, 21, 1174, 220, 22, 477, 439, 279, 2748, 7384, 315, 279, 2307, 444, 68243, 34928, 3223, 349, 220, 20, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 662, 13106, 649, 387, 25396, 2464, 2740, 323, 17888, 6623, 7108, 505, 1521, 7384, 6968, 13106, 865, 350, 10754, 220, 17, 320, 15, 366, 865, 366, 220, 16, 8, 32246, 304, 264, 1920, 2663, 409, 45994, 5531, 367, 13, 7445, 47194, 4245, 311, 13106, 8437, 582, 6709, 320, 53, 13106, 883, 22106, 617, 1027, 13468, 323, 11054, 311, 387, 30801, 555, 279, 25396, 2020, 22639, 304, 13106, 865, 44752, 220, 17, 320, 1116, 13, 220, 21, 883, 323, 13106, 865, 3623, 46, 220, 17, 320, 16541, 220, 20, 1174, 220, 23, 7609, 4452, 11, 13106, 865, 57831, 46, 220, 17, 374, 3685, 311, 387, 810, 17395, 439, 433, 63526, 57831, 220, 18, 10, 65125, 11, 902, 31324, 832, 315, 279, 7928, 622, 30660, 4235, 51, 7218, 70584, 919, 304, 9320, 9501, 32246, 11, 323, 7739, 3276, 11691, 442, 39100, 320, 8440, 8, 57831, 220, 18, 10, 25524, 55788, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 449, 57831, 220, 19, 10, 65125, 11, 902, 527, 539, 622, 30660, 4235, 51, 7218, 4642, 323, 649, 1376, 18728, 442, 39100, 477, 20479, 24379, 41078, 47918, 4020, 81402, 11, 11911, 389, 279, 10937, 1990, 2204, 2167, 323, 25636, 9473, 24717, 220, 975, 662, 1666, 1778, 11, 13106, 865, 57831, 46, 220, 17, 374, 1664, 32599, 311, 4007, 279, 958, 1387, 1990, 279, 650, 13106, 22106, 11, 61976, 2505, 323, 279, 24924, 6012, 13, 2684, 617, 1027, 19815, 9045, 311, 6089, 51187, 279, 61976, 2505, 1701, 36201, 81221, 2796, 17130, 92914, 220, 18, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 320, 50, 14, 21695, 570, 5810, 11, 17130, 3722, 16597, 11, 6925, 331, 299, 35785, 1630, 30630, 3722, 16597, 320, 55, 37790, 705, 17915, 16003, 10334, 320, 35, 4082, 8, 323, 82102, 367, 1824, 28132, 291, 25524, 64036, 64182, 32758, 527, 1511, 311, 8417, 279, 2307, 7993, 315, 25396, 2464, 2740, 14454, 13106, 220, 20, 14, 23, 57831, 46, 220, 17, 1174, 323, 311, 51187, 304, 39695, 958, 5531, 367, 32246, 279, 48566, 50971, 315, 279, 57831, 622, 30660, 4235, 51, 7218, 36282, 323, 872, 59086, 311, 13106, 22106, 13, 26848, 1109, 1694, 30801, 555, 25396, 2020, 22639, 11, 584, 1501, 1618, 2167, 22772, 6029, 505, 64182, 32758, 430, 279, 2307, 7993, 304, 13106, 220, 20, 14, 23, 57831, 46, 220, 17, 374, 14918, 14400, 555, 622, 30660, 4235, 51, 7218, 70584, 919, 902, 49853, 3230, 1317, 3880, 3811, 13106, 4235, 53, 13106, 22639, 1555, 57831, 6900, 323, 294, 482, 30986, 2223, 2015, 826, 13, 1226, 1005, 73404, 17138, 3722, 16597, 11, 24924, 88636, 22323, 323, 423, 4082, 83699, 311, 20461, 430, 264, 3451, 76, 39100, 46642, 28974, 529, 6070, 374, 14454, 520, 3428, 20472, 11, 902, 11384, 264, 38617, 2349, 315, 279, 24924, 6012, 13, 69390, 32056, 13106, 17065, 505, 13106, 44, 77, 46, 220, 17, 15453, 374, 3967, 311, 12446, 1555, 264, 1403, 82710, 13010, 11, 30164, 264, 502, 10474, 13106, 865, 57831, 46, 220, 17, 320, 1116, 13, 220, 972, 7609, 19575, 220, 16, 64, 8568, 5039, 279, 6070, 315, 21349, 96157, 3817, 292, 13106, 44, 77, 46, 220, 17, 1174, 902, 374, 1511, 311, 1963, 279, 17130, 3722, 16597, 12912, 315, 13106, 865, 57831, 46, 220, 17, 6982, 304, 23966, 13, 220, 16, 66, 4235, 68, 662, 578, 18488, 315, 264, 2307, 7993, 374, 2867, 505, 279, 320, 1049, 705, 320, 16, 4235, 1313, 705, 320, 717, 4235, 17, 8, 3722, 16597, 19300, 13, 763, 279, 1901, 482, 85324, 2217, 6982, 304, 23966, 13, 220, 17, 65, 1174, 1855, 13046, 34310, 311, 3060, 264, 13106, 477, 57831, 25524, 46642, 28448, 3235, 279, 510, 7755, 60, 477, 293, 5216, 13, 578, 39445, 21261, 67547, 315, 832, 10107, 323, 2380, 6453, 32094, 304, 279, 13106, 11277, 374, 55272, 311, 279, 13106, 20545, 304, 1521, 55788, 13, 578, 2307, 7993, 305, 10784, 40035, 323, 64182, 1901, 482, 85324, 2038, 30820, 4017, 279, 3284, 13106, 2015, 826, 304, 420, 24549, 13, 2057, 8417, 264, 5016, 2015, 11, 584, 10887, 459, 73603, 2778, 315, 279, 3284, 2307, 47194, 304, 279, 2307, 37791, 709, 311, 220, 843, 15150, 8316, 369, 3892, 865, 2819, 304, 13106, 865, 57831, 46, 220, 17, 662, 578, 1193, 2307, 7993, 430, 9248, 682, 315, 279, 17130, 3722, 969, 5247, 323, 64182, 5448, 13980, 520, 865, 284, 220, 20, 14, 23, 13, 578, 6925, 331, 299, 35785, 1630, 37790, 74013, 320, 99371, 23966, 13, 220, 16, 323, 43252, 220, 17, 323, 220, 18, 883, 574, 10887, 389, 420, 4040, 2307, 7993, 1646, 6041, 449, 423, 4082, 31467, 28772, 14259, 323, 5039, 264, 1695, 5052, 13, 24296, 11, 423, 4082, 29217, 1501, 430, 420, 2307, 7993, 706, 279, 15821, 4907, 4315, 279, 220, 3101, 2204, 13106, 28904, 430, 584, 16997, 369, 865, 284, 220, 20, 14, 23, 11, 449, 1202, 4907, 3770, 279, 18623, 1584, 21583, 279, 1403, 15821, 4907, 14726, 520, 62027, 13106, 62644, 11, 19392, 430, 433, 374, 30945, 72931, 2740, 15528, 320, 99371, 23966, 13, 220, 17, 7609, 1952, 279, 8197, 315, 279, 22772, 323, 55580, 828, 11, 584, 32194, 430, 420, 13106, 220, 20, 14, 23, 57831, 46, 220, 17, 2307, 7993, 374, 279, 502, 10474, 14454, 304, 279, 1176, 22465, 65388, 994, 13106, 374, 409, 45994, 5531, 660, 505, 13106, 44, 77, 46, 220, 17, 320, 1116, 13, 220, 972, 7609, 1102, 374, 5922, 27401, 430, 279, 13106, 8437, 582, 6709, 27204, 449, 279, 15821, 25396, 2020, 4907, 320, 1530, 839, 439, 469, 54006, 62, 15, 304, 99371, 23966, 13, 220, 17, 883, 520, 865, 284, 220, 20, 14, 23, 374, 12207, 5190, 304, 4907, 11, 19392, 430, 279, 25396, 2020, 22639, 656, 539, 41836, 304, 420, 6070, 13, 19575, 220, 16, 25, 7445, 7993, 305, 10784, 19300, 304, 17130, 3722, 16597, 12912, 1501, 279, 22106, 315, 13106, 489, 304, 13106, 865, 57831, 46, 220, 17, 662, 264, 1174, 578, 96157, 3817, 292, 6070, 320, 34, 17, 3262, 8, 315, 66085, 13106, 44, 77, 46, 220, 17, 449, 279, 21349, 7419, 315, 279, 55372, 5137, 13, 578, 5216, 315, 279, 622, 30660, 4235, 51, 7218, 50971, 374, 13160, 555, 279, 4251, 38057, 13, 578, 20366, 18404, 5039, 279, 510, 10731, 60, 5216, 11, 323, 279, 320, 1049, 8, 11277, 374, 304, 6307, 13, 293, 1174, 29696, 3411, 3235, 510, 10731, 948, 578, 6307, 11, 6437, 323, 2579, 5238, 527, 279, 510, 10731, 60, 41579, 315, 320, 1049, 705, 320, 16, 4235, 1313, 8, 323, 320, 717, 4235, 17, 8, 25761, 11, 15947, 13, 272, 1389, 384, 1174, 578, 22772, 17130, 3722, 16597, 12912, 3235, 510, 10731, 1145, 510, 4119, 60, 323, 510, 7755, 60, 1501, 21356, 128257, 198, 128256, 78191, 198, 27671, 315, 264, 87934, 6108, 26110, 555, 14248, 520, 279, 5165, 10181, 315, 35653, 323, 12053, 320, 45, 3931, 8, 323, 279, 22108, 10181, 315, 12053, 320, 18836, 8, 706, 9124, 279, 1176, 2867, 6945, 315, 1202, 31206, 6070, 13, 578, 14955, 1436, 1520, 10552, 279, 24924, 323, 14683, 7865, 315, 279, 4459, 3070, 315, 48473, 11, 1690, 315, 902, 617, 4754, 369, 1005, 304, 27360, 13, 578, 3070, 315, 48473, 433, 17623, 311, 706, 912, 16287, 836, 11, 719, 433, 706, 2380, 23962, 11, 1855, 315, 902, 374, 5918, 2212, 87934, 11, 34928, 3223, 477, 11245, 2345, 21086, 37182, 430, 649, 617, 2204, 24924, 323, 6900, 6012, 13, 2030, 15851, 315, 3070, 9046, 11, 1202, 3697, 4430, 264, 4279, 29683, 25, 2435, 682, 3637, 11742, 4907, 304, 279, 1376, 315, 39695, 11, 33299, 315, 902, 649, 6847, 6530, 1139, 323, 704, 315, 279, 13931, 315, 279, 26110, 994, 9249, 1510, 374, 9435, 11, 264, 11005, 13893, 5505, 304, 47923, 481, 27360, 13, 7089, 3697, 315, 420, 3070, 649, 656, 264, 2763, 315, 2574, 304, 5369, 311, 4907, 5942, 430, 2802, 17032, 25, 4427, 527, 3428, 12, 35658, 2307, 77752, 1105, 11, 1418, 3885, 649, 5625, 8798, 1139, 18200, 13, 578, 12544, 374, 430, 682, 315, 1124, 527, 11, 389, 279, 31206, 2237, 11, 46946, 13, 11205, 14726, 527, 779, 5804, 337, 2844, 430, 14248, 649, 956, 6847, 7216, 704, 3249, 814, 656, 1148, 814, 656, 11, 3339, 433, 2653, 369, 264, 14290, 311, 7417, 872, 5178, 13, 42536, 11, 420, 4040, 87934, 26110, 374, 459, 4788, 13, 330, 2181, 596, 279, 832, 15528, 24549, 584, 1440, 315, 304, 279, 87934, 9046, 430, 706, 264, 4832, 26110, 55372, 6070, 1359, 2795, 12149, 45638, 315, 279, 452, 3931, 5955, 369, 4275, 75248, 8483, 320, 10153, 27416, 570, 330, 4897, 39143, 3445, 584, 649, 43223, 682, 1202, 5419, 14683, 323, 24924, 22639, 323, 1518, 1124, 9539, 13, 2100, 1457, 11, 584, 649, 1212, 24919, 1268, 311, 1304, 1884, 39695, 33299, 810, 83679, 1210, 8068, 3697, 505, 15210, 1903, 279, 3769, 323, 10887, 6492, 1701, 1614, 8838, 10826, 38921, 10278, 12823, 1778, 439, 17130, 92914, 11, 719, 814, 4460, 1520, 505, 279, 20660, 27416, 596, 73404, 51045, 311, 67126, 704, 279, 22639, 1990, 1202, 3927, 33299, 13, 578, 5149, 8710, 430, 279, 26110, 574, 19018, 369, 8125, 7953, 1202, 24693, 39143, 13, 11699, 13931, 35406, 39695, 304, 264, 11401, 19029, 3970, 304, 7138, 25, 763, 1855, 6324, 11, 832, 330, 62333, 1, 315, 33299, 41687, 709, 6724, 449, 39695, 11, 1243, 279, 1828, 2380, 55788, 5266, 709, 1193, 42436, 1603, 2500, 2539, 46642, 8111, 13, 45638, 2795, 279, 5497, 374, 9057, 555, 2204, 10405, 323, 24924, 14269, 430, 87934, 33299, 15575, 304, 2204, 5596, 315, 279, 26110, 11, 264, 4668, 10675, 555, 6492, 315, 279, 20660, 27416, 828, 13, 330, 2028, 4040, 26110, 374, 4762, 539, 279, 832, 499, 4265, 1005, 304, 264, 11863, 477, 1063, 1023, 3851, 11, 433, 1120, 29790, 603, 311, 3619, 1148, 596, 12765, 449, 1202, 5419, 6070, 323, 33297, 2191, 369, 279, 1176, 892, 1359, 45638, 2795, 13, 330, 7184, 584, 617, 264, 8197, 369, 9986, 5620, 279, 6012, 315, 1521, 7384, 555, 10223, 709, 279, 9320, 37182, 323, 10223, 279, 39695, 2262, 13, 1226, 912, 5129, 617, 311, 19614, 2212, 304, 279, 6453, 323, 3987, 1210, 220, 128257, 198 ]

1,993

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract T follicular helper (T FH ) cells are a distinct type of CD4 + T cells that are essential for most antibody and B lymphocyte responses. T FH cell regulation and dysregulation is involved in a range of diseases. Bcl-6 is the lineage-defining transcription factor of T FH cells and its activity is essential for T FH cell differentiation and function. However, how Bcl-6 controls T FH biology has largely remained unclear, at least in part due to the intrinsic challenges of connecting repressors to gene upregulation in complex cell types with multiple possible differentiation fates. Multiple competing models were tested here by a series of experimental approaches to determine that Bcl-6 exhibits negative autoregulation and controls pleiotropic attributes of T FH differentiation and function, including migration, costimulation, inhibitory receptors and cytokines, via multiple repressor-of-repressor gene circuits. Main The formation of germinal centers (GCs) is essential for the development of high-affinity memory B cells and antibody-secreting long-lived plasma cells in response to pathogen infections or vaccinations 1 . Follicular helper T cells (T FH ) provide key signals to antigen-specific B cells for the development of germinal center B (B GC ) cells 1 , 2 . CD4 + T cells receiving T FH inductive signals upregulate Bcl-6, the lineage-defining transcription factor (TF) of T FH cells 3 , 4 , 5 . Upregulation of Bcl-6 is associated with expression of the chemokine receptor CXCR5 and reduction of CCR7 and PSGL1, among other molecules, allowing for migration to the T cell-B cell (T-B) border and GCs 1 , the sites at which T FH and then GC-T FH cells interact with antigen-specific B cells. T FH and GC-T FH cells express many surface and secreted molecules that serve as positive markers and contribute to the differentiation (ICOS, IL-6Rα and PD-1), migration (CXCR5 and CD69), and function (IL-21, IL-4, CXCL13, SAP, ICOS, PD-1, CD200 and CD40L) of T FH and GC-T FH cells. GC-T FH cells provide IL-21, IL-4 and CD40L that are required for B GC cell survival, proliferation and somatic hypermutation 1 , 2 , 6 . Bcl-6 function is critical in T FH differentiation 3 , 4 , 5 . Multiple TFs in addition to Bcl-6 have been identified that regulate T FH differentiation 2 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 . Inhibition of Blimp-1 (encoded by Prdm1 ) by Bcl-6 is required for T FH differentiation 3 . Tcf-1 and Lef-1 are involved in early induction of Bcl-6 and repression of Blimp-1 (refs. 19 , 20 , 21 ). Downregulation of Id2 leads to the release of E protein TFs such as E2A and Ascl2 (refs. 22 , 23 ), which is important for CXCR5 expression. Whereas the importance of Bcl-6 in T FH cell development is clear, the way in which Bcl-6 controls T FH cell biology is still unclear. Two studies using Bcl-6 chromatin immunoprecipitation with sequencing (ChIP–seq) in human GC-T FH cells and murine T FH cells provided insights into Bcl-6-bound genes 24 , 25 , but functional roles have remained largely untested, and there is no consensus on a mechanistic model of how Bcl-6 regulates T FH cell biology. Bcl-6 and Blimp-1 are reciprocal antagonistic regulators of the genetic loci of each other 3 . That interaction provides a powerful mechanism for a genetic switch in cell differentiation, as coexpression of Bcl-6 and Blimp-1 is a metastable state 26 . However, from an experimentalist perspective, their mutual antagonism confounds experimental designs to probe Bcl-6 (and Blimp-1) functions in CD4 + T cells. Additionally, the putative nature of Bcl-6 as a repressor in CD4 + T cells adds an extra layer of complexity to understanding gene regulation, as many signature T FH genes are upregulated in the presence of Bcl-6. In this study, we took a first-principles-based approach to define and test hypothetical models of how Bcl-6 may control T FH biology. Results T FH differentiation is not a default pathway One proposed model of T FH differentiation is that T FH differentiation is the default pathway for naive CD4 + T cells activated by antigen presenting cells. In this model, the primary role of Bcl-6 would be to inhibit Blimp-1 to allow activated CD4 + T cells to undergo a default T FH differentiation pathway 27 (Extended Data Fig. 1a,b ). We tested this model by using Bcl6 f/f Prdm1 f/f Cre CD4 mice. If T FH differentiation is a default setting in activated CD4 + T cells, then when Blimp-1 is absent Bcl-6 would not be required. CD45.1 + SMARTA cells from Bcl6 f/f Prdm1 f/f Cre CD4 mice were transferred into C57BL/6J (B6) mice, as were SMARTA cells from wild-type (WT), Bcl6 f/f Cre CD4 , or Prdm1 f/f Cre CD4 mice. Host mice were immunized with keyhole limpet hemocyanin (KLH) conjugated with lymphocytic choriomeningitis virus (LCMV) glycoprotein 61–80 peptide (KLH–gp 61 ) in alum + cGAMP adjuvant (Fig. 1a and Extended Data Fig. 1c,d ). WT SMARTA cells differentiated into non-T FH (CXCR5 lo SLAM hi ), T FH (CXCR5 + SLAM lo or CXCR5 + PSGL1 int/lo ) and GC-T FH cells (CXCR5 hi PSGL1 lo or CXCR5 hi PD-1 hi ) after KLH–gp 61 immunization (Fig. 1b ). Prdm1 f/f Cre CD4 SMARTA cells predominantly differentiated into T FH and GC-T FH cells. Bcl6 f/f Cre CD4 CD4 + T cells did not differentiate into T FH cells 3 , 28 . Notably, Bcl6 f/f Prdm1 f/f Cre CD4 CD4 + T cells failed to differentiate into T FH and GC-T FH cells. Similar results were observed in the context of an acute viral infection ( Supplementary Note ; Extended Data Fig. 1e–g ). Adoptive transfer of Bcl6 f/f Prdm1 f/f Cre CD4 SMARTA cells demonstrated that the T FH differentiation defect was antigen-specific and CD4 + T cell-intrinsic 29 . Signature T FH surface markers were examined to", "role": "user" }, { "content": "Scientists at the La Jolla Institute for Immunology (LJI) have discovered a potential new way to better fight a range of infectious diseases, cancers and even autoimmune diseases. The new study, published recently in Nature Immunology, shows how a protein works as a \"master regulator\" in the immune system. The research is an important step toward designing vaccines and therapies that can \"switch on\" the immune cells that help produce disease-fighting antibodies. Scientists may also be able to \"switch off\" these cells to counteract immune cells dysfunction in autoimmune diseases. \"This cell type (Tfh cells) sometimes does bad things in autoimmune diseases—particularly autoantibody diseases like lupus, rheumatoid arthritis and Sjogren's syndrome,\" says LJI investigator Shane Crotty, Ph.D., who led the new research. \"So, hopefully, our fundamental knowledge about the circuitry of this cell can help us understand how to turn it off in autoimmune diseases.\" Crotty's laboratory studies key immune system players, such as different kinds of helper T cells. In 2009, his laboratory published work showing that a protein called Bcl6 controls how helper T cells differentiate to do different jobs in the body. They found that Bcl6 prompts helper T cells to become T follicular helper (Tfh) cells, which work with B cells to produce powerful antibodies. This was an important breakthrough, but Crotty's lab still wanted to know: What exactly was Bcl6 doing to Tfh cells? Answering this question could open the door to controlling immune responses. \"There is great interest in the use of Tfh-cell-associated biology for enhancement of vaccines,\" says Crotty. \"There is also great interest in targeting Tfh cell-associated biology for therapeutic interventions in human autoimmune diseases, allergies, atherosclerosis, organ transplants and cancer.\" For the new study, Crotty led a complex effort to test competing theories for how Bcl6 controls Tfh. The researchers used mouse models and a range of genetic sequencing tools to determine that Tfh cells actually need Bcl6 to even exist. Looking closer, the researchers found that Bcl6 acts mainly as a repressor in helper T cells, meaning that it blocks the expression of other proteins in these cells through a series of genetic switches, which they mapped. These new maps show that Bcl6 controls a \"double negative circuit.\" Crotty explains, \"The protein Bcl6 switches this cell type on, but it is a protein that is only known to switch things off. So, we did a lot of experiments to figure out that it controls cells by a series of double negatives. It turns off genes that turn off other genes.\" Bcl6 blocks the expression of two proteins that normally stop Tfh cell differentiation. When Bcl6 does its job, helper T cells are free to become Tfh cells when the body needs them. The new research gives scientists a guide to how they could potentially switch Bcl6 on or off to control immune responses, says Crotty. \"Increasing emphasis will surely now be placed on how to apply that knowledge to Tfh-related therapeutics,\" he adds. The body also uses the kinds of genetic circuits controlled by Bcl6 to stay healthy and not produce antibodies that mistakenly attack the body's own cells. \"The system needs to self-correct and stop the attack. If an immune response is needed to fight off a pathogen, the body needs to reset itself and return to a steady state,\" Crotty says. But deficiencies in this Bcl6-Tfh system can lead to autoimmunity or immunodeficiency. The new research suggests that tweaking immune responses through Bcl6 could also help control autoimmune diseases such as multiple sclerosis and type 1 diabetes. Via Bcl6, Tfh can theoretically also be tuned down to treat allergies, rejection from transplanted organs, and to help prevent atherosclerosis. \"Heart disease is now understood to have a large immunological component, as in too much inflammation,\" Crotty says. Better cancer treatments could also include tweaking Tfh to decrease unwanted immune responses to therapy, he adds. Crotty adds that the way Bcl6 operates to control positive Tfh gene expression may represent a model by which to study other puzzling biological switches. \"We had to do a lot of genetics to connect the dots, but this double negative circuit may actually be the way many immune system cells get controlled,\" he says. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract T follicular helper (T FH ) cells are a distinct type of CD4 + T cells that are essential for most antibody and B lymphocyte responses. T FH cell regulation and dysregulation is involved in a range of diseases. Bcl-6 is the lineage-defining transcription factor of T FH cells and its activity is essential for T FH cell differentiation and function. However, how Bcl-6 controls T FH biology has largely remained unclear, at least in part due to the intrinsic challenges of connecting repressors to gene upregulation in complex cell types with multiple possible differentiation fates. Multiple competing models were tested here by a series of experimental approaches to determine that Bcl-6 exhibits negative autoregulation and controls pleiotropic attributes of T FH differentiation and function, including migration, costimulation, inhibitory receptors and cytokines, via multiple repressor-of-repressor gene circuits. Main The formation of germinal centers (GCs) is essential for the development of high-affinity memory B cells and antibody-secreting long-lived plasma cells in response to pathogen infections or vaccinations 1 . Follicular helper T cells (T FH ) provide key signals to antigen-specific B cells for the development of germinal center B (B GC ) cells 1 , 2 . CD4 + T cells receiving T FH inductive signals upregulate Bcl-6, the lineage-defining transcription factor (TF) of T FH cells 3 , 4 , 5 . Upregulation of Bcl-6 is associated with expression of the chemokine receptor CXCR5 and reduction of CCR7 and PSGL1, among other molecules, allowing for migration to the T cell-B cell (T-B) border and GCs 1 , the sites at which T FH and then GC-T FH cells interact with antigen-specific B cells. T FH and GC-T FH cells express many surface and secreted molecules that serve as positive markers and contribute to the differentiation (ICOS, IL-6Rα and PD-1), migration (CXCR5 and CD69), and function (IL-21, IL-4, CXCL13, SAP, ICOS, PD-1, CD200 and CD40L) of T FH and GC-T FH cells. GC-T FH cells provide IL-21, IL-4 and CD40L that are required for B GC cell survival, proliferation and somatic hypermutation 1 , 2 , 6 . Bcl-6 function is critical in T FH differentiation 3 , 4 , 5 . Multiple TFs in addition to Bcl-6 have been identified that regulate T FH differentiation 2 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 . Inhibition of Blimp-1 (encoded by Prdm1 ) by Bcl-6 is required for T FH differentiation 3 . Tcf-1 and Lef-1 are involved in early induction of Bcl-6 and repression of Blimp-1 (refs. 19 , 20 , 21 ). Downregulation of Id2 leads to the release of E protein TFs such as E2A and Ascl2 (refs. 22 , 23 ), which is important for CXCR5 expression. Whereas the importance of Bcl-6 in T FH cell development is clear, the way in which Bcl-6 controls T FH cell biology is still unclear. Two studies using Bcl-6 chromatin immunoprecipitation with sequencing (ChIP–seq) in human GC-T FH cells and murine T FH cells provided insights into Bcl-6-bound genes 24 , 25 , but functional roles have remained largely untested, and there is no consensus on a mechanistic model of how Bcl-6 regulates T FH cell biology. Bcl-6 and Blimp-1 are reciprocal antagonistic regulators of the genetic loci of each other 3 . That interaction provides a powerful mechanism for a genetic switch in cell differentiation, as coexpression of Bcl-6 and Blimp-1 is a metastable state 26 . However, from an experimentalist perspective, their mutual antagonism confounds experimental designs to probe Bcl-6 (and Blimp-1) functions in CD4 + T cells. Additionally, the putative nature of Bcl-6 as a repressor in CD4 + T cells adds an extra layer of complexity to understanding gene regulation, as many signature T FH genes are upregulated in the presence of Bcl-6. In this study, we took a first-principles-based approach to define and test hypothetical models of how Bcl-6 may control T FH biology. Results T FH differentiation is not a default pathway One proposed model of T FH differentiation is that T FH differentiation is the default pathway for naive CD4 + T cells activated by antigen presenting cells. In this model, the primary role of Bcl-6 would be to inhibit Blimp-1 to allow activated CD4 + T cells to undergo a default T FH differentiation pathway 27 (Extended Data Fig. 1a,b ). We tested this model by using Bcl6 f/f Prdm1 f/f Cre CD4 mice. If T FH differentiation is a default setting in activated CD4 + T cells, then when Blimp-1 is absent Bcl-6 would not be required. CD45.1 + SMARTA cells from Bcl6 f/f Prdm1 f/f Cre CD4 mice were transferred into C57BL/6J (B6) mice, as were SMARTA cells from wild-type (WT), Bcl6 f/f Cre CD4 , or Prdm1 f/f Cre CD4 mice. Host mice were immunized with keyhole limpet hemocyanin (KLH) conjugated with lymphocytic choriomeningitis virus (LCMV) glycoprotein 61–80 peptide (KLH–gp 61 ) in alum + cGAMP adjuvant (Fig. 1a and Extended Data Fig. 1c,d ). WT SMARTA cells differentiated into non-T FH (CXCR5 lo SLAM hi ), T FH (CXCR5 + SLAM lo or CXCR5 + PSGL1 int/lo ) and GC-T FH cells (CXCR5 hi PSGL1 lo or CXCR5 hi PD-1 hi ) after KLH–gp 61 immunization (Fig. 1b ). Prdm1 f/f Cre CD4 SMARTA cells predominantly differentiated into T FH and GC-T FH cells. Bcl6 f/f Cre CD4 CD4 + T cells did not differentiate into T FH cells 3 , 28 . Notably, Bcl6 f/f Prdm1 f/f Cre CD4 CD4 + T cells failed to differentiate into T FH and GC-T FH cells. Similar results were observed in the context of an acute viral infection ( Supplementary Note ; Extended Data Fig. 1e–g ). Adoptive transfer of Bcl6 f/f Prdm1 f/f Cre CD4 SMARTA cells demonstrated that the T FH differentiation defect was antigen-specific and CD4 + T cell-intrinsic 29 . Signature T FH surface markers were examined to<|im_end|> <|im_start|>assistant Scientists at the La Jolla Institute for Immunology (LJI) have discovered a potential new way to better fight a range of infectious diseases, cancers and even autoimmune diseases. The new study, published recently in Nature Immunology, shows how a protein works as a "master regulator" in the immune system. The research is an important step toward designing vaccines and therapies that can "switch on" the immune cells that help produce disease-fighting antibodies. Scientists may also be able to "switch off" these cells to counteract immune cells dysfunction in autoimmune diseases. "This cell type (Tfh cells) sometimes does bad things in autoimmune diseases—particularly autoantibody diseases like lupus, rheumatoid arthritis and Sjogren's syndrome," says LJI investigator Shane Crotty, Ph.D., who led the new research. "So, hopefully, our fundamental knowledge about the circuitry of this cell can help us understand how to turn it off in autoimmune diseases." Crotty's laboratory studies key immune system players, such as different kinds of helper T cells. In 2009, his laboratory published work showing that a protein called Bcl6 controls how helper T cells differentiate to do different jobs in the body. They found that Bcl6 prompts helper T cells to become T follicular helper (Tfh) cells, which work with B cells to produce powerful antibodies. This was an important breakthrough, but Crotty's lab still wanted to know: What exactly was Bcl6 doing to Tfh cells? Answering this question could open the door to controlling immune responses. "There is great interest in the use of Tfh-cell-associated biology for enhancement of vaccines," says Crotty. "There is also great interest in targeting Tfh cell-associated biology for therapeutic interventions in human autoimmune diseases, allergies, atherosclerosis, organ transplants and cancer." For the new study, Crotty led a complex effort to test competing theories for how Bcl6 controls Tfh. The researchers used mouse models and a range of genetic sequencing tools to determine that Tfh cells actually need Bcl6 to even exist. Looking closer, the researchers found that Bcl6 acts mainly as a repressor in helper T cells, meaning that it blocks the expression of other proteins in these cells through a series of genetic switches, which they mapped. These new maps show that Bcl6 controls a "double negative circuit." Crotty explains, "The protein Bcl6 switches this cell type on, but it is a protein that is only known to switch things off. So, we did a lot of experiments to figure out that it controls cells by a series of double negatives. It turns off genes that turn off other genes." Bcl6 blocks the expression of two proteins that normally stop Tfh cell differentiation. When Bcl6 does its job, helper T cells are free to become Tfh cells when the body needs them. The new research gives scientists a guide to how they could potentially switch Bcl6 on or off to control immune responses, says Crotty. "Increasing emphasis will surely now be placed on how to apply that knowledge to Tfh-related therapeutics," he adds. The body also uses the kinds of genetic circuits controlled by Bcl6 to stay healthy and not produce antibodies that mistakenly attack the body's own cells. "The system needs to self-correct and stop the attack. If an immune response is needed to fight off a pathogen, the body needs to reset itself and return to a steady state," Crotty says. But deficiencies in this Bcl6-Tfh system can lead to autoimmunity or immunodeficiency. The new research suggests that tweaking immune responses through Bcl6 could also help control autoimmune diseases such as multiple sclerosis and type 1 diabetes. Via Bcl6, Tfh can theoretically also be tuned down to treat allergies, rejection from transplanted organs, and to help prevent atherosclerosis. "Heart disease is now understood to have a large immunological component, as in too much inflammation," Crotty says. Better cancer treatments could also include tweaking Tfh to decrease unwanted immune responses to therapy, he adds. Crotty adds that the way Bcl6 operates to control positive Tfh gene expression may represent a model by which to study other puzzling biological switches. "We had to do a lot of genetics to connect the dots, but this double negative circuit may actually be the way many immune system cells get controlled," he says. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 350, 82714, 1299, 13438, 320, 51, 82298, 883, 7917, 527, 264, 12742, 955, 315, 11325, 19, 489, 350, 7917, 430, 527, 7718, 369, 1455, 63052, 323, 426, 43745, 79759, 14847, 13, 350, 82298, 2849, 19812, 323, 22709, 1610, 2987, 374, 6532, 304, 264, 2134, 315, 19338, 13, 426, 566, 12, 21, 374, 279, 65009, 29899, 5859, 46940, 8331, 315, 350, 82298, 7917, 323, 1202, 5820, 374, 7718, 369, 350, 82298, 2849, 60038, 323, 734, 13, 4452, 11, 1268, 426, 566, 12, 21, 11835, 350, 82298, 34458, 706, 14090, 14958, 25420, 11, 520, 3325, 304, 961, 4245, 311, 279, 47701, 11774, 315, 21583, 312, 1911, 1105, 311, 15207, 709, 1610, 2987, 304, 6485, 2849, 4595, 449, 5361, 3284, 60038, 282, 988, 13, 29911, 27260, 4211, 1051, 12793, 1618, 555, 264, 4101, 315, 22772, 20414, 311, 8417, 430, 426, 566, 12, 21, 50829, 8389, 3154, 461, 70, 2987, 323, 11835, 7245, 11345, 45036, 8365, 315, 350, 82298, 60038, 323, 734, 11, 2737, 12172, 11, 2853, 61461, 11, 20747, 10843, 44540, 323, 83185, 1572, 11, 4669, 5361, 312, 57320, 8838, 5621, 57320, 15207, 46121, 13, 4802, 578, 18488, 315, 82986, 992, 19169, 320, 23710, 82, 8, 374, 7718, 369, 279, 4500, 315, 1579, 71260, 13797, 5044, 426, 7917, 323, 63052, 7962, 846, 1303, 1317, 62954, 32426, 7917, 304, 2077, 311, 1853, 11968, 30020, 477, 91971, 220, 16, 662, 40555, 416, 1299, 13438, 350, 7917, 320, 51, 82298, 883, 3493, 1401, 17738, 311, 83089, 19440, 426, 7917, 369, 279, 4500, 315, 82986, 992, 4219, 426, 320, 33, 23186, 883, 7917, 220, 16, 1174, 220, 17, 662, 11325, 19, 489, 350, 7917, 12588, 350, 82298, 304, 68243, 17738, 709, 1610, 6468, 426, 566, 12, 21, 11, 279, 65009, 29899, 5859, 46940, 8331, 320, 11042, 8, 315, 350, 82298, 7917, 220, 18, 1174, 220, 19, 1174, 220, 20, 662, 3216, 1610, 2987, 315, 426, 566, 12, 21, 374, 5938, 449, 7645, 315, 279, 8590, 564, 483, 35268, 49583, 9150, 20, 323, 14278, 315, 356, 9150, 22, 323, 11659, 3910, 16, 11, 4315, 1023, 35715, 11, 10923, 369, 12172, 311, 279, 350, 2849, 7826, 2849, 320, 51, 7826, 8, 3973, 323, 23186, 82, 220, 16, 1174, 279, 6732, 520, 902, 350, 82298, 323, 1243, 23186, 9469, 82298, 7917, 16681, 449, 83089, 19440, 426, 7917, 13, 350, 82298, 323, 23186, 9469, 82298, 7917, 3237, 1690, 7479, 323, 6367, 291, 35715, 430, 8854, 439, 6928, 24915, 323, 17210, 311, 279, 60038, 320, 1341, 3204, 11, 11598, 12, 21, 49, 19481, 323, 27572, 12, 16, 705, 12172, 320, 66340, 9150, 20, 323, 11325, 3076, 705, 323, 734, 320, 1750, 12, 1691, 11, 11598, 12, 19, 11, 49583, 3218, 1032, 11, 37321, 11, 19845, 3204, 11, 27572, 12, 16, 11, 11325, 1049, 323, 11325, 1272, 43, 8, 315, 350, 82298, 323, 23186, 9469, 82298, 7917, 13, 23186, 9469, 82298, 7917, 3493, 11598, 12, 1691, 11, 11598, 12, 19, 323, 11325, 1272, 43, 430, 527, 2631, 369, 426, 23186, 2849, 20237, 11, 53840, 323, 1794, 780, 17508, 32071, 220, 16, 1174, 220, 17, 1174, 220, 21, 662, 426, 566, 12, 21, 734, 374, 9200, 304, 350, 82298, 60038, 220, 18, 1174, 220, 19, 1174, 220, 20, 662, 29911, 30245, 82, 304, 5369, 311, 426, 566, 12, 21, 617, 1027, 11054, 430, 37377, 350, 82298, 60038, 220, 17, 1174, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 1174, 220, 972, 662, 763, 60073, 315, 2563, 6802, 12, 16, 320, 19889, 555, 2394, 14170, 16, 883, 555, 426, 566, 12, 21, 374, 2631, 369, 350, 82298, 60038, 220, 18, 662, 350, 9991, 12, 16, 323, 445, 830, 12, 16, 527, 6532, 304, 4216, 38156, 315, 426, 566, 12, 21, 323, 72498, 315, 2563, 6802, 12, 16, 320, 16541, 13, 220, 777, 1174, 220, 508, 1174, 220, 1691, 7609, 6419, 1610, 2987, 315, 5336, 17, 11767, 311, 279, 4984, 315, 469, 13128, 30245, 82, 1778, 439, 469, 17, 32, 323, 1666, 566, 17, 320, 16541, 13, 220, 1313, 1174, 220, 1419, 7026, 902, 374, 3062, 369, 49583, 9150, 20, 7645, 13, 61695, 279, 12939, 315, 426, 566, 12, 21, 304, 350, 82298, 2849, 4500, 374, 2867, 11, 279, 1648, 304, 902, 426, 566, 12, 21, 11835, 350, 82298, 2849, 34458, 374, 2103, 25420, 13, 9220, 7978, 1701, 426, 566, 12, 21, 22083, 15111, 33119, 454, 2827, 575, 7709, 449, 62119, 320, 1163, 3378, 4235, 13565, 8, 304, 3823, 23186, 9469, 82298, 7917, 323, 8309, 483, 350, 82298, 7917, 3984, 26793, 1139, 426, 566, 12, 21, 50962, 21389, 220, 1187, 1174, 220, 914, 1174, 719, 16003, 13073, 617, 14958, 14090, 653, 76036, 11, 323, 1070, 374, 912, 24811, 389, 264, 7852, 4633, 1646, 315, 1268, 426, 566, 12, 21, 80412, 350, 82298, 2849, 34458, 13, 426, 566, 12, 21, 323, 2563, 6802, 12, 16, 527, 87298, 43215, 4633, 40242, 315, 279, 19465, 1353, 72, 315, 1855, 1023, 220, 18, 662, 3011, 16628, 5825, 264, 8147, 17383, 369, 264, 19465, 3480, 304, 2849, 60038, 11, 439, 1080, 29199, 315, 426, 566, 12, 21, 323, 2563, 6802, 12, 16, 374, 264, 68370, 481, 1614, 220, 1627, 662, 4452, 11, 505, 459, 22772, 380, 13356, 11, 872, 27848, 43215, 2191, 2389, 3171, 22772, 14769, 311, 22477, 426, 566, 12, 21, 320, 438, 2563, 6802, 12, 16, 8, 5865, 304, 11325, 19, 489, 350, 7917, 13, 23212, 11, 279, 2231, 1413, 7138, 315, 426, 566, 12, 21, 439, 264, 312, 57320, 304, 11325, 19, 489, 350, 7917, 11621, 459, 5066, 6324, 315, 23965, 311, 8830, 15207, 19812, 11, 439, 1690, 12223, 350, 82298, 21389, 527, 709, 81722, 304, 279, 9546, 315, 426, 566, 12, 21, 13, 763, 420, 4007, 11, 584, 3952, 264, 1176, 27748, 5824, 645, 6108, 5603, 311, 7124, 323, 1296, 59159, 4211, 315, 1268, 426, 566, 12, 21, 1253, 2585, 350, 82298, 34458, 13, 18591, 350, 82298, 60038, 374, 539, 264, 1670, 38970, 3861, 11223, 1646, 315, 350, 82298, 60038, 374, 430, 350, 82298, 60038, 374, 279, 1670, 38970, 369, 50765, 11325, 19, 489, 350, 7917, 22756, 555, 83089, 32644, 7917, 13, 763, 420, 1646, 11, 279, 6156, 3560, 315, 426, 566, 12, 21, 1053, 387, 311, 69033, 2563, 6802, 12, 16, 311, 2187, 22756, 11325, 19, 489, 350, 7917, 311, 37771, 264, 1670, 350, 82298, 60038, 38970, 220, 1544, 320, 54290, 2956, 23966, 13, 220, 16, 64, 8568, 7609, 1226, 12793, 420, 1646, 555, 1701, 426, 566, 21, 282, 6801, 2394, 14170, 16, 282, 6801, 7948, 11325, 19, 24548, 13, 1442, 350, 82298, 60038, 374, 264, 1670, 6376, 304, 22756, 11325, 19, 489, 350, 7917, 11, 1243, 994, 2563, 6802, 12, 16, 374, 28310, 426, 566, 12, 21, 1053, 539, 387, 2631, 13, 11325, 1774, 13, 16, 489, 80708, 32, 7917, 505, 426, 566, 21, 282, 6801, 2394, 14170, 16, 282, 6801, 7948, 11325, 19, 24548, 1051, 23217, 1139, 356, 3226, 9574, 14, 21, 41, 320, 33, 21, 8, 24548, 11, 439, 1051, 80708, 32, 7917, 505, 8545, 10827, 320, 18961, 705, 426, 566, 21, 282, 6801, 7948, 11325, 19, 1174, 477, 2394, 14170, 16, 282, 6801, 7948, 11325, 19, 24548, 13, 16492, 24548, 1051, 33119, 1534, 449, 1401, 31520, 4671, 7005, 17728, 511, 8503, 258, 320, 54083, 39, 8, 64380, 660, 449, 43745, 511, 70504, 523, 13915, 316, 6147, 20000, 17188, 320, 8724, 67726, 8, 37807, 38828, 91748, 220, 5547, 4235, 1490, 72249, 320, 54083, 39, 4235, 22650, 220, 5547, 883, 304, 34060, 489, 272, 38, 16407, 1008, 8783, 77282, 320, 30035, 13, 220, 16, 64, 323, 41665, 2956, 23966, 13, 220, 16, 66, 12260, 7609, 59199, 80708, 32, 7917, 89142, 1139, 2536, 9469, 82298, 320, 66340, 9150, 20, 781, 17216, 1428, 15960, 7026, 350, 82298, 320, 66340, 9150, 20, 489, 17216, 1428, 781, 477, 49583, 9150, 20, 489, 11659, 3910, 16, 528, 107861, 883, 323, 23186, 9469, 82298, 7917, 320, 66340, 9150, 20, 15960, 11659, 3910, 16, 781, 477, 49583, 9150, 20, 15960, 27572, 12, 16, 15960, 883, 1306, 68810, 39, 4235, 22650, 220, 5547, 33119, 2065, 320, 30035, 13, 220, 16, 65, 7609, 2394, 14170, 16, 282, 6801, 7948, 11325, 19, 80708, 32, 7917, 47904, 89142, 1139, 350, 82298, 323, 23186, 9469, 82298, 7917, 13, 426, 566, 21, 282, 6801, 7948, 11325, 19, 11325, 19, 489, 350, 7917, 1550, 539, 54263, 1139, 350, 82298, 7917, 220, 18, 1174, 220, 1591, 662, 2876, 2915, 11, 426, 566, 21, 282, 6801, 2394, 14170, 16, 282, 6801, 7948, 11325, 19, 11325, 19, 489, 350, 7917, 4745, 311, 54263, 1139, 350, 82298, 323, 23186, 9469, 82298, 7917, 13, 22196, 3135, 1051, 13468, 304, 279, 2317, 315, 459, 30883, 29962, 19405, 320, 99371, 7181, 2652, 41665, 2956, 23966, 13, 220, 16, 68, 4235, 70, 7609, 86380, 535, 8481, 315, 426, 566, 21, 282, 6801, 2394, 14170, 16, 282, 6801, 7948, 11325, 19, 80708, 32, 7917, 21091, 430, 279, 350, 82298, 60038, 23011, 574, 83089, 19440, 323, 11325, 19, 489, 350, 2849, 3502, 46102, 220, 1682, 662, 33332, 350, 82298, 7479, 24915, 1051, 25078, 311, 128257, 198, 128256, 78191, 198, 72326, 520, 279, 5034, 622, 43783, 10181, 369, 67335, 2508, 320, 43, 46164, 8, 617, 11352, 264, 4754, 502, 1648, 311, 2731, 4465, 264, 2134, 315, 50600, 19338, 11, 51423, 323, 1524, 88191, 19338, 13, 578, 502, 4007, 11, 4756, 6051, 304, 22037, 67335, 2508, 11, 5039, 1268, 264, 13128, 4375, 439, 264, 330, 13943, 40704, 1, 304, 279, 22852, 1887, 13, 578, 3495, 374, 459, 3062, 3094, 9017, 30829, 40300, 323, 52312, 430, 649, 330, 17790, 389, 1, 279, 22852, 7917, 430, 1520, 8356, 8624, 2269, 45850, 59854, 13, 57116, 1253, 1101, 387, 3025, 311, 330, 17790, 1022, 1, 1521, 7917, 311, 5663, 533, 22852, 7917, 32403, 304, 88191, 19338, 13, 330, 2028, 2849, 955, 320, 51, 32204, 7917, 8, 7170, 1587, 3958, 2574, 304, 88191, 19338, 2345, 74039, 3313, 519, 581, 1094, 19338, 1093, 99889, 355, 11, 68132, 46313, 590, 55652, 323, 328, 73, 540, 1466, 596, 28439, 1359, 2795, 445, 46164, 49581, 51075, 356, 4744, 1919, 11, 2405, 920, 2637, 889, 6197, 279, 502, 3495, 13, 330, 4516, 11, 23127, 11, 1057, 16188, 6677, 922, 279, 16622, 894, 315, 420, 2849, 649, 1520, 603, 3619, 1268, 311, 2543, 433, 1022, 304, 88191, 19338, 1210, 356, 4744, 1919, 596, 27692, 7978, 1401, 22852, 1887, 4311, 11, 1778, 439, 2204, 13124, 315, 13438, 350, 7917, 13, 763, 220, 1049, 24, 11, 813, 27692, 4756, 990, 9204, 430, 264, 13128, 2663, 426, 566, 21, 11835, 1268, 13438, 350, 7917, 54263, 311, 656, 2204, 7032, 304, 279, 2547, 13, 2435, 1766, 430, 426, 566, 21, 52032, 13438, 350, 7917, 311, 3719, 350, 82714, 1299, 13438, 320, 51, 32204, 8, 7917, 11, 902, 990, 449, 426, 7917, 311, 8356, 8147, 59854, 13, 1115, 574, 459, 3062, 42445, 11, 719, 356, 4744, 1919, 596, 10278, 2103, 4934, 311, 1440, 25, 3639, 7041, 574, 426, 566, 21, 3815, 311, 350, 32204, 7917, 30, 22559, 287, 420, 3488, 1436, 1825, 279, 6134, 311, 26991, 22852, 14847, 13, 330, 3947, 374, 2294, 2802, 304, 279, 1005, 315, 350, 32204, 33001, 75968, 34458, 369, 27886, 315, 40300, 1359, 2795, 356, 4744, 1919, 13, 330, 3947, 374, 1101, 2294, 2802, 304, 25103, 350, 32204, 2849, 75968, 34458, 369, 37471, 39455, 304, 3823, 88191, 19338, 11, 58742, 11, 264, 91882, 91711, 11, 2942, 1380, 64805, 323, 9572, 1210, 1789, 279, 502, 4007, 11, 356, 4744, 1919, 6197, 264, 6485, 5149, 311, 1296, 27260, 26018, 369, 1268, 426, 566, 21, 11835, 350, 32204, 13, 578, 12074, 1511, 8814, 4211, 323, 264, 2134, 315, 19465, 62119, 7526, 311, 8417, 430, 350, 32204, 7917, 3604, 1205, 426, 566, 21, 311, 1524, 3073, 13, 21815, 12401, 11, 279, 12074, 1766, 430, 426, 566, 21, 14385, 14918, 439, 264, 312, 57320, 304, 13438, 350, 7917, 11, 7438, 430, 433, 10215, 279, 7645, 315, 1023, 28896, 304, 1521, 7917, 1555, 264, 4101, 315, 19465, 32267, 11, 902, 814, 24784, 13, 4314, 502, 14370, 1501, 430, 426, 566, 21, 11835, 264, 330, 4429, 8389, 16622, 1210, 356, 4744, 1919, 15100, 11, 330, 791, 13128, 426, 566, 21, 32267, 420, 2849, 955, 389, 11, 719, 433, 374, 264, 13128, 430, 374, 1193, 3967, 311, 3480, 2574, 1022, 13, 2100, 11, 584, 1550, 264, 2763, 315, 21896, 311, 7216, 704, 430, 433, 11835, 7917, 555, 264, 4101, 315, 2033, 75185, 13, 1102, 10800, 1022, 21389, 430, 2543, 1022, 1023, 21389, 1210, 426, 566, 21, 10215, 279, 7645, 315, 1403, 28896, 430, 14614, 3009, 350, 32204, 2849, 60038, 13, 3277, 426, 566, 21, 1587, 1202, 2683, 11, 13438, 350, 7917, 527, 1949, 311, 3719, 350, 32204, 7917, 994, 279, 2547, 3966, 1124, 13, 578, 502, 3495, 6835, 14248, 264, 8641, 311, 1268, 814, 1436, 13893, 3480, 426, 566, 21, 389, 477, 1022, 311, 2585, 22852, 14847, 11, 2795, 356, 4744, 1919, 13, 330, 81782, 25679, 690, 22225, 1457, 387, 9277, 389, 1268, 311, 3881, 430, 6677, 311, 350, 32204, 14228, 9139, 88886, 1359, 568, 11621, 13, 578, 2547, 1101, 5829, 279, 13124, 315, 19465, 46121, 14400, 555, 426, 566, 21, 311, 4822, 9498, 323, 539, 8356, 59854, 430, 77634, 3440, 279, 2547, 596, 1866, 7917, 13, 330, 791, 1887, 3966, 311, 659, 1824, 28132, 323, 3009, 279, 3440, 13, 1442, 459, 22852, 2077, 374, 4460, 311, 4465, 1022, 264, 1853, 11968, 11, 279, 2547, 3966, 311, 7738, 5196, 323, 471, 311, 264, 24981, 1614, 1359, 356, 4744, 1919, 2795, 13, 2030, 72946, 304, 420, 426, 566, 21, 9469, 32204, 1887, 649, 3063, 311, 3313, 12828, 2498, 477, 33119, 98677, 10603, 13, 578, 502, 3495, 13533, 430, 89347, 22852, 14847, 1555, 426, 566, 21, 1436, 1101, 1520, 2585, 88191, 19338, 1778, 439, 5361, 91357, 323, 955, 220, 16, 20335, 13, 45899, 426, 566, 21, 11, 350, 32204, 649, 63234, 1101, 387, 33519, 1523, 311, 4322, 58742, 11, 38001, 505, 1380, 501, 7719, 36853, 11, 323, 311, 1520, 5471, 264, 91882, 91711, 13, 330, 46484, 8624, 374, 1457, 16365, 311, 617, 264, 3544, 33119, 5848, 3777, 11, 439, 304, 2288, 1790, 37140, 1359, 356, 4744, 1919, 2795, 13, 24327, 9572, 22972, 1436, 1101, 2997, 89347, 350, 32204, 311, 18979, 36021, 22852, 14847, 311, 15419, 11, 568, 11621, 13, 356, 4744, 1919, 11621, 430, 279, 1648, 426, 566, 21, 27149, 311, 2585, 6928, 350, 32204, 15207, 7645, 1253, 4097, 264, 1646, 555, 902, 311, 4007, 1023, 32854, 2785, 24156, 32267, 13, 330, 1687, 1047, 311, 656, 264, 2763, 315, 56104, 311, 4667, 279, 32094, 11, 719, 420, 2033, 8389, 16622, 1253, 3604, 387, 279, 1648, 1690, 22852, 1887, 7917, 636, 14400, 1359, 568, 2795, 13, 220, 128257, 198 ]

2,455

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The recent emergence of B.1.1.529, the Omicron variant 1 , 2 , has raised concerns of escape from protection by vaccines and therapeutic antibodies. A key test for potential countermeasures against B.1.1.529 is their activity in preclinical rodent models of respiratory tract disease. Here, using the collaborative network of the SARS-CoV-2 Assessment of Viral Evolution (SAVE) programme of the National Institute of Allergy and Infectious Diseases (NIAID), we evaluated the ability of several B.1.1.529 isolates to cause infection and disease in immunocompetent and human ACE2 (hACE2)-expressing mice and hamsters. Despite modelling data indicating that B.1.1.529 spike can bind more avidly to mouse ACE2 (refs. 3 , 4 ), we observed less infection by B.1.1.529 in 129, C57BL/6, BALB/c and K18-hACE2 transgenic mice than by previous SARS-CoV-2 variants, with limited weight loss and lower viral burden in the upper and lower respiratory tracts. In wild-type and hACE2 transgenic hamsters, lung infection, clinical disease and pathology with B.1.1.529 were also milder than with historical isolates or other SARS-CoV-2 variants of concern. Overall, experiments from the SAVE/NIAID network with several B.1.1.529 isolates demonstrate attenuated lung disease in rodents, which parallels preliminary human clinical data. Main Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic resulting in millions of deaths worldwide. The extensive morbidity and mortality made the development of vaccines, antibody-based countermeasures and antiviral agents a global health priority. As part of this process, several models of SARS-CoV-2 infection and lung pathogenesis were developed in animals for rapid testing 5 . Remarkably, several highly effective vaccines and therapeutics were deployed with billions of doses given worldwide. Although these measures markedly reduced hospitalizations and deaths, their efficacy has been jeopardized by the emergence of SARS-CoV-2 variants with mutations in the spike gene. The SARS-CoV-2 spike protein engages angiotensin-converting enzyme 2 (ACE2) on the surface of human cells to facilitate entry and infection of cells 6 . Upon cell attachment, spike proteins are cleaved by host proteases into S1 and S2 fragments. The S1 protein includes the amino-terminal (NTD) and receptor-binding (RBD) domains. The RBD is the target of many potently neutralizing monoclonal 7 , 8 , 9 , 10 , 11 and serum polyclonal 12 antibodies. Although SARS-CoV-2 spike proteins from strains early in the pandemic bound to ACE2 from several animal species (for example, hamster, ferret and nonhuman primates), they did not bind mouse ACE2, which explained why laboratory strains of mice could not be infected by SARS-CoV-2 (refs. 6 , 13 ); indeed, mice could become susceptible through expression of hACE2 via a transgene 14 , 15 , 16 or viral vector 17 , 18 , or under regulation of the mouse ACE2 promoter 19 , 20 , 21 . Later in the pandemic, several strains acquired a mouse-adapting spike substitution (N501Y), which allowed engagement of mouse ACE2 and productive infection of mice without hACE2 expression 22 , 23 , 24 . In late November 2021, the Omicron (B.1.1.529) variant emerged. This variant has the largest number (>30) of substitutions, deletions or insertions in the spike protein described so far, raising concerns of escape from protection by vaccines and therapeutic monoclonal antibodies. B.1.1.529 isolates have many changes in the RBD (G339D, R346K, S371L, S373P, S375F, K417N, N440K, G446S, S477N, T478K, E484A, Q493R, G496S, Q498R, N501Y and Y505H). The N501Y substitution along with changes at sites (K417, E484, Q493, Q498 and N501) associated with mouse adaptation 25 , 26 , 27 , 28 , 29 , 30 indicated that B.1.1.529 should infect mice 3 . One study speculated that the progenitor of B.1.1.529 jumped from humans to mice, and then back into humans 4 . In support of this, B.1.1.529 RBD binds to mouse ACE2 (ref. 31 ). Last, hamsters have been a valuable animal model for assessing countermeasures against SARS-CoV-2 and variants. Hamsters are susceptible to SARS-CoV-2 infection and show similar pathological changes to those seen in lung tissues from COVID-19 patients 5 , 32 , 33 . Here, using data from several laboratories of the SAVE/NIAID consortium (Supplementary Table 1 ), we report on the infectivity of several B.1.1.529 isolates in mice and hamsters, two key rodent models of SARS-CoV-2 infection and pathogenesis. B.1.1.529 infection in mice Because of the presence of several amino acid alterations that are considered mouse adapting, we predicted that B.1.1.529 should infect immunocompetent mice and cause lung disease as seen with other recombinant strains (WA1/2020 N501Y) or variants (for example, B.1.351) containing N501Y substitutions. We first tested B.1.1.529 in 129 mice. Two of our laboratories independently inoculated 6–8-week-old or 10–20-week-old 129 mice with 10 4 , 10 5 or 10 6 infectious units (plaque-forming units (PFU) or focus-forming units (FFU)) of three different B.1.1.529 strains (Supplementary Tables 1 and 2 ). As 129 mice sustain 10 to 15% loss of body weight 3 to 4 days post infection (dpi) yet recover and gain weight beginning at 5 dpi (refs. 22 , 34 ) with SARS-CoV-2 strains encoding N501Y substitutions 34 , we assessed weight change with B.1.1.529 at 3 and 4 dpi. However, after inoculation with B.1.1.529, 129 mice failed to lose weight (Fig. 1a ). Similarly, aged (10- to 14-month-old) C57BL/6 mice also did not lose weight after B.1.1.529 infection, whereas those infected with B.1.351 did (Fig. 1a ). Fig. 1: B.1.1.529 is less pathogenic in mice. a , Left: weight change in mock-infected mice ( n = 4) or mice inoculated with B.1.1.529 + A701V ( n = 5), B.1.1.529 ( n = 3) or B.1.351 ( n = 3). Middle: weight change in mice inoculated with B.1.1.529 or B.1.351 ( n = 5) (** P = 0.0075, *** P = 0.0006, **** P < 0.0001). Right: weight change in mice inoculated with B.1.1.529 ( n = 4), B.1.1.7 ( n = 10) or B.1.351 ( n = 18). Comparison between B.1.351 and B.1.1.529: * P = 0.0151, *** P = 0.0003 (3 dpi) and 0.0006 (4 dpi). Mean ± s.e.m. b , Viral RNA level in mice inoculated with B.1.1.529", "role": "user" }, { "content": "When South African scientists announced in November that they had identified a new variant of the virus that causes COVID-19, they also reported two worrying details: one, that this new variant's genome was strikingly different from that of any previous variant, containing dozens of mutations compared with the original virus that emerged in 2019; and two, that the new variant—dubbed omicron—was spreading like wildfire. The world needed to know quickly how well COVID-19 immunity—either from vaccination or prior infection—and therapies would hold up against this new variant. Researchers at Washington University School of Medicine in St. Louis, led by Michael S. Diamond, MD, Ph.D., the Herbert S. Gasser Professor of Medicine, immediately started investigating the new variant of SARS-CoV-2, the virus that causes COVID-19. Within a few weeks, they had data showing that omicron was a mixed bag: It could resist most antibody-based therapeutics, but it was less able to cause severe lung disease, at least in mice and hamsters. \"What omicron demonstrates is that a virus's intrinsic pathogenicity—its ability to cause disease—is just one factor you have to consider in the context of a pandemic,\" said Diamond, also a professor of molecular microbiology and of pathology & immunology. \"The omicron variant is less pathogenic, but it's not not pathogenic. It can still cause severe disease, and it still kills people. When you have huge numbers of people getting infected in a short period of time, even if only a small fraction get seriously ill, it can still be enough to overwhelm the health-care system. Add that to the fact that many of our antibody therapies have lost effectiveness, and you get the crisis we've seen this winter.\" Diamond worked with Jacco Boon, Ph.D., an associate professor of medicine, of molecular microbiology, and of pathology & immunology, and colleagues at the SARS-CoV-2 Assessment of Viral Evolution (SAVE) Program to investigate omicron's capacity to cause severe disease. The SAVE Program was established by the National Institute of Allergy and Infectious Diseases to rapidly characterize emerging variants and monitor their potential impact on COVID-19 vaccines, therapeutics and diagnostics. The omicron wave peaked first in South Africa. Early reports from the country indicated that the huge wave of infections was followed by a surprisingly small wave of hospitalizations and deaths. This encouraging news suggested that omicron might cause milder disease than previous variants. But the South African and U.S. populations are very different. South Africa is much younger, and has a lower vaccination rate but a higher rate of prior infection, and a different pattern of high-risk health conditions. It was unclear whether the U.S. would follow the same path as South Africa. To separate the role of the virus itself from population factors such as average age and pre-existing immunity, Boon, Diamond and colleagues studied animals infected with the variant. The group tested omicron variants from three people in four strains of mice and two strains of hamsters. For comparison, they infected separate groups of animals with the original strain of SARS-CoV-2 or the beta variant, which emerged in South Africa in fall 2020. Beta caused a large wave of infections in South Africa in 2020 before spreading globally. People infected with beta were more likely to become severely ill and require hospitalization than those infected with other variants. Compared with animals infected with the original strain or with the beta variant, animals infected with omicron lost less weight, had less virus in their noses and lungs, had lower levels of inflammation, and lost less respiratory function. \"Omicron virus is milder in every rodent model of COVID-19 disease that we tested,\" Boon said. \"This suggests that it may also be less capable of causing severe disease in people, although we can't say for certain because people, obviously, are very different from mice and hamsters. But just because it might be milder doesn't mean it's harmless. People are still being hospitalized and dying every day, so it's important to continue taking precautions against infection.\" The disease-severity study was published in Nature, with co-corresponding authors Boon, Diamond and Yoshihiro Kawaoka, DVM, Ph.D., a professor of virology at the University of Wisconsin-Madison. Meanwhile, Diamond also began investigating omicron's ability to resist antibody-based therapeutics. The virus that causes COVID-19 uses its spike protein to get inside cells. Because of the critical importance of spike to the virus, all COVID-19 vaccines and antibody-based therapies used in the U.S. target the protein. Omicron has 30 mutations in its spike gene, enough to make scientists worry that some anti-spike antibodies might fail against omicron's very different spike protein. Diamond, along with staff scientist and first author Laura VanBlargan, Ph.D., and colleagues tested all antibodies then authorized by the Food and Drug Administration to treat or prevent COVID-19—including antibodies made by AstraZeneca, Celltrion, Eli Lilly, Regeneron and Vir Biotechnology—for their ability to prevent the omicron variant from infecting cells. The antibodies were tested individually and in the combinations they were authorized to be used. Most of the antibodies were much less potent against omicron than against the original virus. Many failed completely. Only Vir's antibody, known as sotrovimab, retained the power to neutralize the omicron variant. These data, published in Nature Medicine in January, contributed to a growing stack of evidence that many antibody-based COVID-19 therapies fail to help people sick with omicron. As omicron became the dominant variant in January, accounting for nearly all COVID-19 cases in the U.S., the FDA withdrew authorization for all antibody-based COVID-19 therapeutics except sotrovimab. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The recent emergence of B.1.1.529, the Omicron variant 1 , 2 , has raised concerns of escape from protection by vaccines and therapeutic antibodies. A key test for potential countermeasures against B.1.1.529 is their activity in preclinical rodent models of respiratory tract disease. Here, using the collaborative network of the SARS-CoV-2 Assessment of Viral Evolution (SAVE) programme of the National Institute of Allergy and Infectious Diseases (NIAID), we evaluated the ability of several B.1.1.529 isolates to cause infection and disease in immunocompetent and human ACE2 (hACE2)-expressing mice and hamsters. Despite modelling data indicating that B.1.1.529 spike can bind more avidly to mouse ACE2 (refs. 3 , 4 ), we observed less infection by B.1.1.529 in 129, C57BL/6, BALB/c and K18-hACE2 transgenic mice than by previous SARS-CoV-2 variants, with limited weight loss and lower viral burden in the upper and lower respiratory tracts. In wild-type and hACE2 transgenic hamsters, lung infection, clinical disease and pathology with B.1.1.529 were also milder than with historical isolates or other SARS-CoV-2 variants of concern. Overall, experiments from the SAVE/NIAID network with several B.1.1.529 isolates demonstrate attenuated lung disease in rodents, which parallels preliminary human clinical data. Main Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic resulting in millions of deaths worldwide. The extensive morbidity and mortality made the development of vaccines, antibody-based countermeasures and antiviral agents a global health priority. As part of this process, several models of SARS-CoV-2 infection and lung pathogenesis were developed in animals for rapid testing 5 . Remarkably, several highly effective vaccines and therapeutics were deployed with billions of doses given worldwide. Although these measures markedly reduced hospitalizations and deaths, their efficacy has been jeopardized by the emergence of SARS-CoV-2 variants with mutations in the spike gene. The SARS-CoV-2 spike protein engages angiotensin-converting enzyme 2 (ACE2) on the surface of human cells to facilitate entry and infection of cells 6 . Upon cell attachment, spike proteins are cleaved by host proteases into S1 and S2 fragments. The S1 protein includes the amino-terminal (NTD) and receptor-binding (RBD) domains. The RBD is the target of many potently neutralizing monoclonal 7 , 8 , 9 , 10 , 11 and serum polyclonal 12 antibodies. Although SARS-CoV-2 spike proteins from strains early in the pandemic bound to ACE2 from several animal species (for example, hamster, ferret and nonhuman primates), they did not bind mouse ACE2, which explained why laboratory strains of mice could not be infected by SARS-CoV-2 (refs. 6 , 13 ); indeed, mice could become susceptible through expression of hACE2 via a transgene 14 , 15 , 16 or viral vector 17 , 18 , or under regulation of the mouse ACE2 promoter 19 , 20 , 21 . Later in the pandemic, several strains acquired a mouse-adapting spike substitution (N501Y), which allowed engagement of mouse ACE2 and productive infection of mice without hACE2 expression 22 , 23 , 24 . In late November 2021, the Omicron (B.1.1.529) variant emerged. This variant has the largest number (>30) of substitutions, deletions or insertions in the spike protein described so far, raising concerns of escape from protection by vaccines and therapeutic monoclonal antibodies. B.1.1.529 isolates have many changes in the RBD (G339D, R346K, S371L, S373P, S375F, K417N, N440K, G446S, S477N, T478K, E484A, Q493R, G496S, Q498R, N501Y and Y505H). The N501Y substitution along with changes at sites (K417, E484, Q493, Q498 and N501) associated with mouse adaptation 25 , 26 , 27 , 28 , 29 , 30 indicated that B.1.1.529 should infect mice 3 . One study speculated that the progenitor of B.1.1.529 jumped from humans to mice, and then back into humans 4 . In support of this, B.1.1.529 RBD binds to mouse ACE2 (ref. 31 ). Last, hamsters have been a valuable animal model for assessing countermeasures against SARS-CoV-2 and variants. Hamsters are susceptible to SARS-CoV-2 infection and show similar pathological changes to those seen in lung tissues from COVID-19 patients 5 , 32 , 33 . Here, using data from several laboratories of the SAVE/NIAID consortium (Supplementary Table 1 ), we report on the infectivity of several B.1.1.529 isolates in mice and hamsters, two key rodent models of SARS-CoV-2 infection and pathogenesis. B.1.1.529 infection in mice Because of the presence of several amino acid alterations that are considered mouse adapting, we predicted that B.1.1.529 should infect immunocompetent mice and cause lung disease as seen with other recombinant strains (WA1/2020 N501Y) or variants (for example, B.1.351) containing N501Y substitutions. We first tested B.1.1.529 in 129 mice. Two of our laboratories independently inoculated 6–8-week-old or 10–20-week-old 129 mice with 10 4 , 10 5 or 10 6 infectious units (plaque-forming units (PFU) or focus-forming units (FFU)) of three different B.1.1.529 strains (Supplementary Tables 1 and 2 ). As 129 mice sustain 10 to 15% loss of body weight 3 to 4 days post infection (dpi) yet recover and gain weight beginning at 5 dpi (refs. 22 , 34 ) with SARS-CoV-2 strains encoding N501Y substitutions 34 , we assessed weight change with B.1.1.529 at 3 and 4 dpi. However, after inoculation with B.1.1.529, 129 mice failed to lose weight (Fig. 1a ). Similarly, aged (10- to 14-month-old) C57BL/6 mice also did not lose weight after B.1.1.529 infection, whereas those infected with B.1.351 did (Fig. 1a ). Fig. 1: B.1.1.529 is less pathogenic in mice. a , Left: weight change in mock-infected mice ( n = 4) or mice inoculated with B.1.1.529 + A701V ( n = 5), B.1.1.529 ( n = 3) or B.1.351 ( n = 3). Middle: weight change in mice inoculated with B.1.1.529 or B.1.351 ( n = 5) (** P = 0.0075, *** P = 0.0006, **** P < 0.0001). Right: weight change in mice inoculated with B.1.1.529 ( n = 4), B.1.1.7 ( n = 10) or B.1.351 ( n = 18). Comparison between B.1.351 and B.1.1.529: * P = 0.0151, *** P = 0.0003 (3 dpi) and 0.0006 (4 dpi). Mean ± s.e.m. b , Viral RNA level in mice inoculated with B.1.1.529<|im_end|> <|im_start|>assistant When South African scientists announced in November that they had identified a new variant of the virus that causes COVID-19, they also reported two worrying details: one, that this new variant's genome was strikingly different from that of any previous variant, containing dozens of mutations compared with the original virus that emerged in 2019; and two, that the new variant—dubbed omicron—was spreading like wildfire. The world needed to know quickly how well COVID-19 immunity—either from vaccination or prior infection—and therapies would hold up against this new variant. Researchers at Washington University School of Medicine in St. Louis, led by Michael S. Diamond, MD, Ph.D., the Herbert S. Gasser Professor of Medicine, immediately started investigating the new variant of SARS-CoV-2, the virus that causes COVID-19. Within a few weeks, they had data showing that omicron was a mixed bag: It could resist most antibody-based therapeutics, but it was less able to cause severe lung disease, at least in mice and hamsters. "What omicron demonstrates is that a virus's intrinsic pathogenicity—its ability to cause disease—is just one factor you have to consider in the context of a pandemic," said Diamond, also a professor of molecular microbiology and of pathology & immunology. "The omicron variant is less pathogenic, but it's not not pathogenic. It can still cause severe disease, and it still kills people. When you have huge numbers of people getting infected in a short period of time, even if only a small fraction get seriously ill, it can still be enough to overwhelm the health-care system. Add that to the fact that many of our antibody therapies have lost effectiveness, and you get the crisis we've seen this winter." Diamond worked with Jacco Boon, Ph.D., an associate professor of medicine, of molecular microbiology, and of pathology & immunology, and colleagues at the SARS-CoV-2 Assessment of Viral Evolution (SAVE) Program to investigate omicron's capacity to cause severe disease. The SAVE Program was established by the National Institute of Allergy and Infectious Diseases to rapidly characterize emerging variants and monitor their potential impact on COVID-19 vaccines, therapeutics and diagnostics. The omicron wave peaked first in South Africa. Early reports from the country indicated that the huge wave of infections was followed by a surprisingly small wave of hospitalizations and deaths. This encouraging news suggested that omicron might cause milder disease than previous variants. But the South African and U.S. populations are very different. South Africa is much younger, and has a lower vaccination rate but a higher rate of prior infection, and a different pattern of high-risk health conditions. It was unclear whether the U.S. would follow the same path as South Africa. To separate the role of the virus itself from population factors such as average age and pre-existing immunity, Boon, Diamond and colleagues studied animals infected with the variant. The group tested omicron variants from three people in four strains of mice and two strains of hamsters. For comparison, they infected separate groups of animals with the original strain of SARS-CoV-2 or the beta variant, which emerged in South Africa in fall 2020. Beta caused a large wave of infections in South Africa in 2020 before spreading globally. People infected with beta were more likely to become severely ill and require hospitalization than those infected with other variants. Compared with animals infected with the original strain or with the beta variant, animals infected with omicron lost less weight, had less virus in their noses and lungs, had lower levels of inflammation, and lost less respiratory function. "Omicron virus is milder in every rodent model of COVID-19 disease that we tested," Boon said. "This suggests that it may also be less capable of causing severe disease in people, although we can't say for certain because people, obviously, are very different from mice and hamsters. But just because it might be milder doesn't mean it's harmless. People are still being hospitalized and dying every day, so it's important to continue taking precautions against infection." The disease-severity study was published in Nature, with co-corresponding authors Boon, Diamond and Yoshihiro Kawaoka, DVM, Ph.D., a professor of virology at the University of Wisconsin-Madison. Meanwhile, Diamond also began investigating omicron's ability to resist antibody-based therapeutics. The virus that causes COVID-19 uses its spike protein to get inside cells. Because of the critical importance of spike to the virus, all COVID-19 vaccines and antibody-based therapies used in the U.S. target the protein. Omicron has 30 mutations in its spike gene, enough to make scientists worry that some anti-spike antibodies might fail against omicron's very different spike protein. Diamond, along with staff scientist and first author Laura VanBlargan, Ph.D., and colleagues tested all antibodies then authorized by the Food and Drug Administration to treat or prevent COVID-19—including antibodies made by AstraZeneca, Celltrion, Eli Lilly, Regeneron and Vir Biotechnology—for their ability to prevent the omicron variant from infecting cells. The antibodies were tested individually and in the combinations they were authorized to be used. Most of the antibodies were much less potent against omicron than against the original virus. Many failed completely. Only Vir's antibody, known as sotrovimab, retained the power to neutralize the omicron variant. These data, published in Nature Medicine in January, contributed to a growing stack of evidence that many antibody-based COVID-19 therapies fail to help people sick with omicron. As omicron became the dominant variant in January, accounting for nearly all COVID-19 cases in the U.S., the FDA withdrew authorization for all antibody-based COVID-19 therapeutics except sotrovimab. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 3293, 49179, 315, 426, 13, 16, 13, 16, 13, 21618, 11, 279, 19116, 292, 2298, 11678, 220, 16, 1174, 220, 17, 1174, 706, 9408, 10742, 315, 12731, 505, 9313, 555, 40300, 323, 37471, 59854, 13, 362, 1401, 1296, 369, 4754, 5663, 2727, 24368, 2403, 426, 13, 16, 13, 16, 13, 21618, 374, 872, 5820, 304, 864, 91899, 21236, 306, 4211, 315, 42631, 42929, 8624, 13, 5810, 11, 1701, 279, 40806, 4009, 315, 279, 328, 17485, 87271, 53, 12, 17, 37357, 315, 9734, 278, 38321, 320, 67210, 8, 18629, 315, 279, 5165, 10181, 315, 2052, 43043, 323, 88911, 1245, 70674, 320, 45, 5987, 926, 705, 584, 26126, 279, 5845, 315, 3892, 426, 13, 16, 13, 16, 13, 21618, 13399, 988, 311, 5353, 19405, 323, 8624, 304, 33119, 12255, 7005, 306, 323, 3823, 41906, 17, 320, 71, 5693, 17, 7435, 14107, 287, 24548, 323, 13824, 12855, 13, 18185, 61966, 828, 19392, 430, 426, 13, 16, 13, 16, 13, 21618, 37393, 649, 10950, 810, 56653, 398, 311, 8814, 41906, 17, 320, 16541, 13, 220, 18, 1174, 220, 19, 7026, 584, 13468, 2753, 19405, 555, 426, 13, 16, 13, 16, 13, 21618, 304, 220, 9748, 11, 356, 3226, 9574, 14, 21, 11, 70245, 33, 2971, 323, 735, 972, 2902, 5693, 17, 1380, 89305, 24548, 1109, 555, 3766, 328, 17485, 87271, 53, 12, 17, 27103, 11, 449, 7347, 4785, 4814, 323, 4827, 29962, 23104, 304, 279, 8582, 323, 4827, 42631, 490, 11613, 13, 763, 8545, 10827, 323, 305, 5693, 17, 1380, 89305, 13824, 12855, 11, 21271, 19405, 11, 14830, 8624, 323, 77041, 449, 426, 13, 16, 13, 16, 13, 21618, 1051, 1101, 296, 21439, 1109, 449, 13970, 13399, 988, 477, 1023, 328, 17485, 87271, 53, 12, 17, 27103, 315, 4747, 13, 28993, 11, 21896, 505, 279, 51722, 20906, 5987, 926, 4009, 449, 3892, 426, 13, 16, 13, 16, 13, 21618, 13399, 988, 20461, 57732, 660, 21271, 8624, 304, 94209, 11, 902, 72474, 33269, 3823, 14830, 828, 13, 4802, 1369, 19846, 30883, 42631, 28439, 33333, 220, 17, 320, 50, 17485, 87271, 53, 12, 17, 8, 706, 9057, 264, 28522, 13239, 304, 11990, 315, 16779, 15603, 13, 578, 16781, 93144, 19025, 323, 29528, 1903, 279, 4500, 315, 40300, 11, 63052, 6108, 5663, 2727, 24368, 323, 3276, 344, 37478, 13307, 264, 3728, 2890, 10844, 13, 1666, 961, 315, 420, 1920, 11, 3892, 4211, 315, 328, 17485, 87271, 53, 12, 17, 19405, 323, 21271, 1853, 52379, 1051, 8040, 304, 10099, 369, 11295, 7649, 220, 20, 662, 83833, 2915, 11, 3892, 7701, 7524, 40300, 323, 9139, 88886, 1051, 27167, 449, 33151, 315, 35130, 2728, 15603, 13, 10541, 1521, 11193, 88101, 11293, 8952, 8200, 323, 16779, 11, 872, 41265, 706, 1027, 53132, 1534, 555, 279, 49179, 315, 328, 17485, 87271, 53, 12, 17, 27103, 449, 34684, 304, 279, 37393, 15207, 13, 578, 328, 17485, 87271, 53, 12, 17, 37393, 13128, 69589, 6590, 11345, 729, 258, 15204, 50517, 49242, 220, 17, 320, 5693, 17, 8, 389, 279, 7479, 315, 3823, 7917, 311, 28696, 4441, 323, 19405, 315, 7917, 220, 21, 662, 30538, 2849, 20581, 11, 37393, 28896, 527, 11551, 4234, 555, 3552, 5541, 2315, 1139, 328, 16, 323, 328, 17, 35603, 13, 578, 328, 16, 13128, 5764, 279, 42500, 91723, 320, 6542, 35, 8, 323, 35268, 65500, 320, 49, 9740, 8, 31576, 13, 578, 432, 9740, 374, 279, 2218, 315, 1690, 3419, 4501, 21277, 4954, 96157, 12490, 278, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 323, 41529, 1499, 6310, 25180, 220, 717, 59854, 13, 10541, 328, 17485, 87271, 53, 12, 17, 37393, 28896, 505, 42400, 4216, 304, 279, 28522, 6965, 311, 41906, 17, 505, 3892, 10065, 9606, 320, 2000, 3187, 11, 13824, 3751, 11, 18728, 2171, 323, 2536, 26380, 9036, 988, 705, 814, 1550, 539, 10950, 8814, 41906, 17, 11, 902, 11497, 3249, 27692, 42400, 315, 24548, 1436, 539, 387, 29374, 555, 328, 17485, 87271, 53, 12, 17, 320, 16541, 13, 220, 21, 1174, 220, 1032, 7048, 13118, 11, 24548, 1436, 3719, 47281, 1555, 7645, 315, 305, 5693, 17, 4669, 264, 1380, 43471, 220, 975, 1174, 220, 868, 1174, 220, 845, 477, 29962, 4724, 220, 1114, 1174, 220, 972, 1174, 477, 1234, 19812, 315, 279, 8814, 41906, 17, 66642, 220, 777, 1174, 220, 508, 1174, 220, 1691, 662, 25929, 304, 279, 28522, 11, 3892, 42400, 19426, 264, 8814, 26831, 391, 1303, 37393, 50068, 320, 45, 14408, 56, 705, 902, 5535, 20392, 315, 8814, 41906, 17, 323, 27331, 19405, 315, 24548, 2085, 305, 5693, 17, 7645, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 662, 763, 3389, 6841, 220, 2366, 16, 11, 279, 19116, 292, 2298, 320, 33, 13, 16, 13, 16, 13, 21618, 8, 11678, 22763, 13, 1115, 11678, 706, 279, 7928, 1396, 77952, 966, 8, 315, 94750, 11, 19825, 919, 477, 5774, 919, 304, 279, 37393, 13128, 7633, 779, 3117, 11, 19054, 10742, 315, 12731, 505, 9313, 555, 40300, 323, 37471, 96157, 12490, 278, 59854, 13, 426, 13, 16, 13, 16, 13, 21618, 13399, 988, 617, 1690, 4442, 304, 279, 432, 9740, 320, 38, 17887, 35, 11, 432, 18061, 42, 11, 328, 18650, 43, 11, 328, 18017, 47, 11, 328, 12935, 37, 11, 735, 19561, 45, 11, 452, 14868, 42, 11, 480, 20385, 50, 11, 328, 21144, 45, 11, 350, 22086, 42, 11, 469, 20339, 32, 11, 1229, 22741, 49, 11, 480, 19447, 50, 11, 1229, 21962, 49, 11, 452, 14408, 56, 323, 816, 17786, 39, 570, 578, 452, 14408, 56, 50068, 3235, 449, 4442, 520, 6732, 320, 42, 19561, 11, 469, 20339, 11, 1229, 22741, 11, 1229, 21962, 323, 452, 14408, 8, 5938, 449, 8814, 34185, 220, 914, 1174, 220, 1627, 1174, 220, 1544, 1174, 220, 1591, 1174, 220, 1682, 1174, 220, 966, 16717, 430, 426, 13, 16, 13, 16, 13, 21618, 1288, 34527, 24548, 220, 18, 662, 3861, 4007, 74877, 430, 279, 84360, 1960, 315, 426, 13, 16, 13, 16, 13, 21618, 27096, 505, 12966, 311, 24548, 11, 323, 1243, 1203, 1139, 12966, 220, 19, 662, 763, 1862, 315, 420, 11, 426, 13, 16, 13, 16, 13, 21618, 432, 9740, 58585, 311, 8814, 41906, 17, 320, 1116, 13, 220, 2148, 7609, 8155, 11, 13824, 12855, 617, 1027, 264, 15525, 10065, 1646, 369, 47614, 5663, 2727, 24368, 2403, 328, 17485, 87271, 53, 12, 17, 323, 27103, 13, 9777, 12855, 527, 47281, 311, 328, 17485, 87271, 53, 12, 17, 19405, 323, 1501, 4528, 89961, 4442, 311, 1884, 3970, 304, 21271, 39881, 505, 20562, 12, 777, 6978, 220, 20, 1174, 220, 843, 1174, 220, 1644, 662, 5810, 11, 1701, 828, 505, 3892, 70760, 315, 279, 51722, 20906, 5987, 926, 75094, 320, 10254, 67082, 6771, 220, 16, 7026, 584, 1934, 389, 279, 34527, 1968, 315, 3892, 426, 13, 16, 13, 16, 13, 21618, 13399, 988, 304, 24548, 323, 13824, 12855, 11, 1403, 1401, 21236, 306, 4211, 315, 328, 17485, 87271, 53, 12, 17, 19405, 323, 1853, 52379, 13, 426, 13, 16, 13, 16, 13, 21618, 19405, 304, 24548, 9393, 315, 279, 9546, 315, 3892, 42500, 13935, 61086, 430, 527, 6646, 8814, 70817, 11, 584, 19698, 430, 426, 13, 16, 13, 16, 13, 21618, 1288, 34527, 33119, 12255, 7005, 306, 24548, 323, 5353, 21271, 8624, 439, 3970, 449, 1023, 38301, 7006, 519, 42400, 320, 27486, 16, 14, 2366, 15, 452, 14408, 56, 8, 477, 27103, 320, 2000, 3187, 11, 426, 13, 16, 13, 18113, 8, 8649, 452, 14408, 56, 94750, 13, 1226, 1176, 12793, 426, 13, 16, 13, 16, 13, 21618, 304, 220, 9748, 24548, 13, 9220, 315, 1057, 70760, 29235, 87018, 7913, 220, 21, 4235, 23, 30609, 6418, 477, 220, 605, 4235, 508, 30609, 6418, 220, 9748, 24548, 449, 220, 605, 220, 19, 1174, 220, 605, 220, 20, 477, 220, 605, 220, 21, 50600, 8316, 320, 501, 20234, 8627, 287, 8316, 320, 20280, 52, 8, 477, 5357, 8627, 287, 8316, 320, 1785, 52, 595, 315, 2380, 2204, 426, 13, 16, 13, 16, 13, 21618, 42400, 320, 10254, 67082, 43252, 220, 16, 323, 220, 17, 7609, 1666, 220, 9748, 24548, 14201, 220, 605, 311, 220, 868, 4, 4814, 315, 2547, 4785, 220, 18, 311, 220, 19, 2919, 1772, 19405, 320, 79129, 8, 3686, 11993, 323, 8895, 4785, 7314, 520, 220, 20, 51842, 320, 16541, 13, 220, 1313, 1174, 220, 1958, 883, 449, 328, 17485, 87271, 53, 12, 17, 42400, 11418, 452, 14408, 56, 94750, 220, 1958, 1174, 584, 32448, 4785, 2349, 449, 426, 13, 16, 13, 16, 13, 21618, 520, 220, 18, 323, 220, 19, 51842, 13, 4452, 11, 1306, 87018, 2987, 449, 426, 13, 16, 13, 16, 13, 21618, 11, 220, 9748, 24548, 4745, 311, 9229, 4785, 320, 30035, 13, 220, 16, 64, 7609, 35339, 11, 20330, 320, 605, 12, 311, 220, 975, 23086, 6418, 8, 356, 3226, 9574, 14, 21, 24548, 1101, 1550, 539, 9229, 4785, 1306, 426, 13, 16, 13, 16, 13, 21618, 19405, 11, 20444, 1884, 29374, 449, 426, 13, 16, 13, 18113, 1550, 320, 30035, 13, 220, 16, 64, 7609, 23966, 13, 220, 16, 25, 426, 13, 16, 13, 16, 13, 21618, 374, 2753, 1853, 29569, 304, 24548, 13, 264, 1174, 14043, 25, 4785, 2349, 304, 8018, 48336, 1599, 24548, 320, 308, 284, 220, 19, 8, 477, 24548, 87018, 7913, 449, 426, 13, 16, 13, 16, 13, 21618, 489, 362, 19597, 53, 320, 308, 284, 220, 20, 705, 426, 13, 16, 13, 16, 13, 21618, 320, 308, 284, 220, 18, 8, 477, 426, 13, 16, 13, 18113, 320, 308, 284, 220, 18, 570, 12877, 25, 4785, 2349, 304, 24548, 87018, 7913, 449, 426, 13, 16, 13, 16, 13, 21618, 477, 426, 13, 16, 13, 18113, 320, 308, 284, 220, 20, 8, 77596, 393, 284, 220, 15, 13, 11194, 20, 11, 17601, 393, 284, 220, 15, 13, 931, 21, 11, 31804, 393, 366, 220, 15, 13, 931, 16, 570, 10291, 25, 4785, 2349, 304, 24548, 87018, 7913, 449, 426, 13, 16, 13, 16, 13, 21618, 320, 308, 284, 220, 19, 705, 426, 13, 16, 13, 16, 13, 22, 320, 308, 284, 220, 605, 8, 477, 426, 13, 16, 13, 18113, 320, 308, 284, 220, 972, 570, 43551, 1990, 426, 13, 16, 13, 18113, 323, 426, 13, 16, 13, 16, 13, 21618, 25, 353, 393, 284, 220, 15, 13, 16037, 16, 11, 17601, 393, 284, 220, 15, 13, 931, 18, 320, 18, 51842, 8, 323, 220, 15, 13, 931, 21, 320, 19, 51842, 570, 16729, 20903, 274, 1770, 749, 13, 293, 1174, 9734, 278, 41214, 2237, 304, 24548, 87018, 7913, 449, 426, 13, 16, 13, 16, 13, 21618, 128257, 198, 128256, 78191, 198, 4599, 4987, 11904, 14248, 7376, 304, 6841, 430, 814, 1047, 11054, 264, 502, 11678, 315, 279, 17188, 430, 11384, 20562, 12, 777, 11, 814, 1101, 5068, 1403, 40876, 3649, 25, 832, 11, 430, 420, 502, 11678, 596, 33869, 574, 21933, 398, 2204, 505, 430, 315, 904, 3766, 11678, 11, 8649, 22700, 315, 34684, 7863, 449, 279, 4113, 17188, 430, 22763, 304, 220, 679, 24, 26, 323, 1403, 11, 430, 279, 502, 11678, 2345, 121988, 2788, 8019, 292, 2298, 2345, 16514, 31135, 1093, 93225, 13, 578, 1917, 4460, 311, 1440, 6288, 1268, 1664, 20562, 12, 777, 40368, 2345, 50998, 505, 47165, 477, 4972, 19405, 17223, 52312, 1053, 3412, 709, 2403, 420, 502, 11678, 13, 59250, 520, 6652, 3907, 6150, 315, 19152, 304, 800, 13, 12140, 11, 6197, 555, 8096, 328, 13, 25328, 11, 14306, 11, 2405, 920, 2637, 279, 58463, 328, 13, 480, 34858, 17054, 315, 19152, 11, 7214, 3940, 24834, 279, 502, 11678, 315, 328, 17485, 87271, 53, 12, 17, 11, 279, 17188, 430, 11384, 20562, 12, 777, 13, 25218, 264, 2478, 5672, 11, 814, 1047, 828, 9204, 430, 8019, 292, 2298, 574, 264, 9709, 9145, 25, 1102, 1436, 22884, 1455, 63052, 6108, 9139, 88886, 11, 719, 433, 574, 2753, 3025, 311, 5353, 15748, 21271, 8624, 11, 520, 3325, 304, 24548, 323, 13824, 12855, 13, 330, 3923, 8019, 292, 2298, 32216, 374, 430, 264, 17188, 596, 47701, 1853, 29569, 488, 2345, 1220, 5845, 311, 5353, 8624, 55434, 1120, 832, 8331, 499, 617, 311, 2980, 304, 279, 2317, 315, 264, 28522, 1359, 1071, 25328, 11, 1101, 264, 14561, 315, 31206, 53499, 2508, 323, 315, 77041, 612, 33119, 2508, 13, 330, 791, 8019, 292, 2298, 11678, 374, 2753, 1853, 29569, 11, 719, 433, 596, 539, 539, 1853, 29569, 13, 1102, 649, 2103, 5353, 15748, 8624, 11, 323, 433, 2103, 29910, 1274, 13, 3277, 499, 617, 6908, 5219, 315, 1274, 3794, 29374, 304, 264, 2875, 4261, 315, 892, 11, 1524, 422, 1193, 264, 2678, 19983, 636, 14243, 5986, 11, 433, 649, 2103, 387, 3403, 311, 96848, 279, 2890, 41206, 1887, 13, 2758, 430, 311, 279, 2144, 430, 1690, 315, 1057, 63052, 52312, 617, 5675, 27375, 11, 323, 499, 636, 279, 11501, 584, 3077, 3970, 420, 12688, 1210, 25328, 6575, 449, 15385, 1030, 2577, 263, 11, 2405, 920, 2637, 459, 22712, 14561, 315, 16088, 11, 315, 31206, 53499, 2508, 11, 323, 315, 77041, 612, 33119, 2508, 11, 323, 18105, 520, 279, 328, 17485, 87271, 53, 12, 17, 37357, 315, 9734, 278, 38321, 320, 67210, 8, 6826, 311, 19874, 8019, 292, 2298, 596, 8824, 311, 5353, 15748, 8624, 13, 578, 51722, 6826, 574, 9749, 555, 279, 5165, 10181, 315, 2052, 43043, 323, 88911, 1245, 70674, 311, 19019, 70755, 24084, 27103, 323, 8891, 872, 4754, 5536, 389, 20562, 12, 777, 40300, 11, 9139, 88886, 323, 50518, 13, 578, 8019, 292, 2298, 12330, 78292, 1176, 304, 4987, 10384, 13, 23591, 6821, 505, 279, 3224, 16717, 430, 279, 6908, 12330, 315, 30020, 574, 8272, 555, 264, 29392, 2678, 12330, 315, 8952, 8200, 323, 16779, 13, 1115, 26921, 3754, 12090, 430, 8019, 292, 2298, 2643, 5353, 296, 21439, 8624, 1109, 3766, 27103, 13, 2030, 279, 4987, 11904, 323, 549, 815, 13, 22673, 527, 1633, 2204, 13, 4987, 10384, 374, 1790, 14992, 11, 323, 706, 264, 4827, 47165, 4478, 719, 264, 5190, 4478, 315, 4972, 19405, 11, 323, 264, 2204, 5497, 315, 1579, 46570, 2890, 4787, 13, 1102, 574, 25420, 3508, 279, 549, 815, 13, 1053, 1833, 279, 1890, 1853, 439, 4987, 10384, 13, 2057, 8821, 279, 3560, 315, 279, 17188, 5196, 505, 7187, 9547, 1778, 439, 5578, 4325, 323, 864, 50457, 40368, 11, 2577, 263, 11, 25328, 323, 18105, 20041, 10099, 29374, 449, 279, 11678, 13, 578, 1912, 12793, 8019, 292, 2298, 27103, 505, 2380, 1274, 304, 3116, 42400, 315, 24548, 323, 1403, 42400, 315, 13824, 12855, 13, 1789, 12593, 11, 814, 29374, 8821, 5315, 315, 10099, 449, 279, 4113, 26800, 315, 328, 17485, 87271, 53, 12, 17, 477, 279, 13746, 11678, 11, 902, 22763, 304, 4987, 10384, 304, 4498, 220, 2366, 15, 13, 35343, 9057, 264, 3544, 12330, 315, 30020, 304, 4987, 10384, 304, 220, 2366, 15, 1603, 31135, 31550, 13, 9029, 29374, 449, 13746, 1051, 810, 4461, 311, 3719, 35906, 5986, 323, 1397, 8952, 2065, 1109, 1884, 29374, 449, 1023, 27103, 13, 59813, 449, 10099, 29374, 449, 279, 4113, 26800, 477, 449, 279, 13746, 11678, 11, 10099, 29374, 449, 8019, 292, 2298, 5675, 2753, 4785, 11, 1047, 2753, 17188, 304, 872, 97814, 323, 45274, 11, 1047, 4827, 5990, 315, 37140, 11, 323, 5675, 2753, 42631, 734, 13, 330, 46, 21914, 2298, 17188, 374, 296, 21439, 304, 1475, 21236, 306, 1646, 315, 20562, 12, 777, 8624, 430, 584, 12793, 1359, 2577, 263, 1071, 13, 330, 2028, 13533, 430, 433, 1253, 1101, 387, 2753, 13171, 315, 14718, 15748, 8624, 304, 1274, 11, 8051, 584, 649, 956, 2019, 369, 3738, 1606, 1274, 11, 14224, 11, 527, 1633, 2204, 505, 24548, 323, 13824, 12855, 13, 2030, 1120, 1606, 433, 2643, 387, 296, 21439, 3250, 956, 3152, 433, 596, 53997, 13, 9029, 527, 2103, 1694, 70340, 323, 23069, 1475, 1938, 11, 779, 433, 596, 3062, 311, 3136, 4737, 61003, 2403, 19405, 1210, 578, 8624, 7962, 27570, 4007, 574, 4756, 304, 22037, 11, 449, 1080, 46713, 6961, 287, 12283, 2577, 263, 11, 25328, 323, 90742, 86238, 735, 14406, 31866, 11, 423, 11435, 11, 2405, 920, 2637, 264, 14561, 315, 3355, 299, 36781, 520, 279, 3907, 315, 21073, 5364, 329, 3416, 13, 26982, 11, 25328, 1101, 6137, 24834, 8019, 292, 2298, 596, 5845, 311, 22884, 63052, 6108, 9139, 88886, 13, 578, 17188, 430, 11384, 20562, 12, 777, 5829, 1202, 37393, 13128, 311, 636, 4871, 7917, 13, 9393, 315, 279, 9200, 12939, 315, 37393, 311, 279, 17188, 11, 682, 20562, 12, 777, 40300, 323, 63052, 6108, 52312, 1511, 304, 279, 549, 815, 13, 2218, 279, 13128, 13, 19116, 292, 2298, 706, 220, 966, 34684, 304, 1202, 37393, 15207, 11, 3403, 311, 1304, 14248, 11196, 430, 1063, 7294, 1355, 65546, 59854, 2643, 3775, 2403, 8019, 292, 2298, 596, 1633, 2204, 37393, 13128, 13, 25328, 11, 3235, 449, 5687, 28568, 323, 1176, 3229, 30928, 13000, 5028, 867, 276, 11, 2405, 920, 2637, 323, 18105, 12793, 682, 59854, 1243, 19144, 555, 279, 12369, 323, 26166, 17128, 311, 4322, 477, 5471, 20562, 12, 777, 76070, 59854, 1903, 555, 362, 13645, 86792, 23637, 11, 14299, 376, 290, 11, 34362, 82934, 11, 3263, 804, 263, 323, 9734, 12371, 52536, 72318, 872, 5845, 311, 5471, 279, 8019, 292, 2298, 11678, 505, 34527, 287, 7917, 13, 578, 59854, 1051, 12793, 32399, 323, 304, 279, 28559, 814, 1051, 19144, 311, 387, 1511, 13, 7648, 315, 279, 59854, 1051, 1790, 2753, 36875, 2403, 8019, 292, 2298, 1109, 2403, 279, 4113, 17188, 13, 9176, 4745, 6724, 13, 8442, 9734, 596, 63052, 11, 3967, 439, 274, 354, 40494, 318, 370, 11, 35363, 279, 2410, 311, 21277, 553, 279, 8019, 292, 2298, 11678, 13, 4314, 828, 11, 4756, 304, 22037, 19152, 304, 6186, 11, 20162, 311, 264, 7982, 5729, 315, 6029, 430, 1690, 63052, 6108, 20562, 12, 777, 52312, 3775, 311, 1520, 1274, 14363, 449, 8019, 292, 2298, 13, 1666, 8019, 292, 2298, 6244, 279, 25462, 11678, 304, 6186, 11, 24043, 369, 7154, 682, 20562, 12, 777, 5157, 304, 279, 549, 815, 2637, 279, 30473, 62765, 24645, 369, 682, 63052, 6108, 20562, 12, 777, 9139, 88886, 3734, 274, 354, 40494, 318, 370, 13, 220, 128257, 198 ]

2,982

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract RNA viruses are characterized by a high mutation rate, a buffer against environmental change. Nevertheless, the means by which random mutation improves viral fitness is not well characterized. Here we report the X-ray crystal structure of the receptor-binding domain (RBD) of the human coronavirus, HCoV-229E, in complex with the ectodomain of its receptor, aminopeptidase N (APN). Three extended loops are solely responsible for receptor binding and the evolution of HCoV-229E and its close relatives is accompanied by changing loop–receptor interactions. Phylogenetic analysis shows that the natural HCoV-229E receptor-binding loop variation observed defines six RBD classes whose viruses have successively replaced each other in the human population over the past 50 years. These RBD classes differ in their affinity for APN and their ability to bind an HCoV-229E neutralizing antibody. Together, our results provide a model for alphacoronavirus adaptation and evolution based on the use of extended loops for receptor binding. Introduction Coronaviruses are enveloped, positive-stranded RNA viruses that cause a number of respiratory, gastrointestinal, and neurological diseases in birds and mammals 1 , 2 . The coronaviruses all possess a common ancestor and four different genera (alpha, beta, gamma, and delta) that collectively use at least four different glycoproteins and acetylated sialic acids as host receptors or attachment factors have evolved 3 , 4 , 5 . Four coronaviruses, HCoV-229E, HCoV-NL63, HCoV-OC43, and HCoV-HKU1 circulate in the human population and collectively they are responsible for a significant percentage of the common cold as well as more severe respiratory disease in vulnerable populations 6 , 7 . HCoV-229E and HCoV-NL63 are both alphacoronaviruses and although closely related, they have evolved to use two different receptors, aminopeptidase N (APN) and angiotensin converting enzyme 2 (ACE2), respectively 8 , 9 . The more distantly related betacoronaviruses, HCoV-OC43 and HCoV-HKU1, are less well characterized and although HCoV-OC43 uses 9- O -acetylsialic acid as its receptor 10 , the receptor for HCoV-HKU1 has not yet been determined 11 , 12 , 13 . Recent zoonotic transmission of betacoronaviruses from bats is responsible for SARS and MERS, and in these cases infection is associated with much more serious disease and high rates of mortality 14 , 15 , 16 . Like HCoV-NL63, SARS-CoV uses ACE2 17 as its receptor and the observation that MERS-CoV uses dipeptidyl peptidase 4 18 highlights the fact that coronaviruses with new receptor specificities continue to arise. The coronavirus spike protein (S-protein) is a trimeric single-pass membrane protein that mediates receptor binding and fusion of the viral and host cell membranes 19 . It is a type-1 viral fusion protein possessing two regions, the S1 region that contains the receptor-binding domain (RBD) and the S2 region that contains the fusion peptide and heptad repeats involved in membrane fusion 20 , 21 , 22 , 23 , 24 , 25 . The coronavirus S-protein is also a major target of neutralizing antibodies and one outcome of host-induced neutralizing antibodies is the selection of viral variants capable of evading them, a process known to drive variation 26 , 27 , 28 . As shown by both in vivo and in vitro studies, changes in host, host cell type, cross-species transmission, receptor expression levels, serial passage, and tissue culture conditions can also drive viral variation 29 , 30 , 31 , 32 , 33 . RNA viruses are characterized by a high mutation rate, a property serving as a buffer against environmental change 34 . A host-elicited immune response, the introduction of antiviral drugs, and the transmission to a new species provide important examples of environmental change 35 . Nevertheless, the means by which random mutations lead to viral variants with increased fitness and enhanced survival in the new environment are not well characterized. Given their wide host range, diverse receptor usage and ongoing zoonotic transmission to humans, the coronaviruses provide an important system for studying RNA virus adaptation and evolution. The alphacoronavirus, HCoV-229E, is particularly valuable as it circulates in the human population and a sequence database of natural variants isolated over the past fifty years is available. Moreover, changes in sequence and serology have suggested that HCoV-229E is changing over time in the human population 36 , 37 , 38 . Reported here is the X-ray structure of the HCoV-229E RBD in complex with human APN (hAPN). The structure shows that receptor binding is mediated solely by three extended loops, a feature shared by HCoV-NL63 and the closely related porcine respiratory coronavirus, PRCoV. It also shows that the HCoV-229E RBD binds at a site on hAPN that differs from the site where the PRCoV RBD binds on porcine APN (pAPN), evidence of an ability of the RBD to acquire novel receptor interactions. Remarkably, we find that the natural HCoV-229E sequence variation observed over the past fifty years is highly skewed to the receptor-binding loops. Moreover, we find that the loop variation defines six RBD classes (Classes I–VI) whose viruses have successively replaced each other in the human population. These RBD classes differ in their affinity for hAPN and their ability to be bound by a neutralizing antibody elicited by the HCoV-229E reference strain (Class I). Taken together, our results provide a model for alphacoronavirus adaptation and evolution stemming from the use of extended loops for receptor binding. Results Characterization of the HCoV-229E RBD interaction with hAPN To define the limits of the HCoV-229E RBD, we expressed a series of soluble S-protein fragments and measured their affinity to a soluble fragment (residues 66–967) 39 of hAPN, the HCoV-229E receptor. The smallest S-protein fragment made (residues 293–435) bound hAPN with an affinity ( K d of 0.43 ± 0.1 µM) similar to that of the entire S1 region (residues 17–560) (Table 1 , Supplementary Fig. 1A , B) and this fragment was used in the structure determination. To confirm the importance of the HCoV-229E RBD–hAPN interaction for viral infection, we showed that both the RBD and the hAPN ectodomain inhibited viral infection in a cell-based assay (Fig. 1a, b, c ). Table 1 Analysis", "role": "user" }, { "content": "Common cold season is back, which has people wondering why we catch the same virus, year after year. Why don't we ever develop immunity against the common cold? Professor Pierre Talbot at INRS has known about the incredible variability of coronaviruses for some time. They're responsible for the common cold as well as many other infections, including neurological diseases. Along with his research associate Marc Desforges, Professor Talbot worked on a study recently published in Nature Communications about the ways in which coronaviruses adapt and evolve, becoming ever more effective at infecting hosts without being defeated by the immune system. The small, spiky spheres, the coronaviruses are closely monitored by public health agencies, since they're able to be transmitted between species and some have a high potential mortality rate. Both SARS and MERS are caused by coronaviruses. Their ability to adapt to new environments seems due in part to the spikes on the surface of the virus—more specifically, a small, strategic part of the proteins that form those spikes. The spikes are made up of S proteins (S for spike). A specific part of the spike seems to allow the virus to attach itself to host cells. The spike's RBD (receptor binding domain), which initiates the interaction between cell and virus, is essential for infection. But RBDs are targeted by antibodies that neutralize the virus and allow the immune system to flush it out of the host's system. Coronaviruses are thus faced with an evolutionary problem. They can't infect cells without an RBD, which needs to be exposed so that it can latch onto cells. But the RBD needs to be masked to avoid being targeted by antibodies. In response, the coronavirus has developed a mechanism that helps it survive, and thrive. The RBD is made up of three parts that vary widely between strains. Thanks to this variation, antibodies are unable to detect new strains, whereas RBDs retain—and even improve—their affinity for the target cell. Plus, RBDs alternate between visible and masked states. To gain this insight, a group of researchers including Professor Talbot studied the alphacoronavirus HCoV-229E and, more specifically, the interaction between its RBD and aminopeptidase N (APN)—the host cell protein the RBD latches onto. The team crystallized the multiprotein complex and then analyzed the structures of both proteins. By observing the RBD's structure up close, the team was able to identify the three long loops that latch onto APN. As analyses of these viruses over the last fifty years have shown, these loops are virtually the only thing that varies from one strain to the next. The experiments demonstrate that the changes observed in the loops modulate an RBD's affinity with APN. The variants that have the greatest affinity are also likely to be better at infecting host cells, which helps them spread. Six different classes of HCoV-229E have popped up over the years, each with a greater RBD-APN affinity than the last. This discovery adds to our understanding of the evolution of coronaviruses and could lead to similar analyses of other coronaviruses. Although there are many elements left to explain, the RBD seems to be an important feature that must be monitored as we follow the adaptive evolution of these viruses and assess their ability to infect. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract RNA viruses are characterized by a high mutation rate, a buffer against environmental change. Nevertheless, the means by which random mutation improves viral fitness is not well characterized. Here we report the X-ray crystal structure of the receptor-binding domain (RBD) of the human coronavirus, HCoV-229E, in complex with the ectodomain of its receptor, aminopeptidase N (APN). Three extended loops are solely responsible for receptor binding and the evolution of HCoV-229E and its close relatives is accompanied by changing loop–receptor interactions. Phylogenetic analysis shows that the natural HCoV-229E receptor-binding loop variation observed defines six RBD classes whose viruses have successively replaced each other in the human population over the past 50 years. These RBD classes differ in their affinity for APN and their ability to bind an HCoV-229E neutralizing antibody. Together, our results provide a model for alphacoronavirus adaptation and evolution based on the use of extended loops for receptor binding. Introduction Coronaviruses are enveloped, positive-stranded RNA viruses that cause a number of respiratory, gastrointestinal, and neurological diseases in birds and mammals 1 , 2 . The coronaviruses all possess a common ancestor and four different genera (alpha, beta, gamma, and delta) that collectively use at least four different glycoproteins and acetylated sialic acids as host receptors or attachment factors have evolved 3 , 4 , 5 . Four coronaviruses, HCoV-229E, HCoV-NL63, HCoV-OC43, and HCoV-HKU1 circulate in the human population and collectively they are responsible for a significant percentage of the common cold as well as more severe respiratory disease in vulnerable populations 6 , 7 . HCoV-229E and HCoV-NL63 are both alphacoronaviruses and although closely related, they have evolved to use two different receptors, aminopeptidase N (APN) and angiotensin converting enzyme 2 (ACE2), respectively 8 , 9 . The more distantly related betacoronaviruses, HCoV-OC43 and HCoV-HKU1, are less well characterized and although HCoV-OC43 uses 9- O -acetylsialic acid as its receptor 10 , the receptor for HCoV-HKU1 has not yet been determined 11 , 12 , 13 . Recent zoonotic transmission of betacoronaviruses from bats is responsible for SARS and MERS, and in these cases infection is associated with much more serious disease and high rates of mortality 14 , 15 , 16 . Like HCoV-NL63, SARS-CoV uses ACE2 17 as its receptor and the observation that MERS-CoV uses dipeptidyl peptidase 4 18 highlights the fact that coronaviruses with new receptor specificities continue to arise. The coronavirus spike protein (S-protein) is a trimeric single-pass membrane protein that mediates receptor binding and fusion of the viral and host cell membranes 19 . It is a type-1 viral fusion protein possessing two regions, the S1 region that contains the receptor-binding domain (RBD) and the S2 region that contains the fusion peptide and heptad repeats involved in membrane fusion 20 , 21 , 22 , 23 , 24 , 25 . The coronavirus S-protein is also a major target of neutralizing antibodies and one outcome of host-induced neutralizing antibodies is the selection of viral variants capable of evading them, a process known to drive variation 26 , 27 , 28 . As shown by both in vivo and in vitro studies, changes in host, host cell type, cross-species transmission, receptor expression levels, serial passage, and tissue culture conditions can also drive viral variation 29 , 30 , 31 , 32 , 33 . RNA viruses are characterized by a high mutation rate, a property serving as a buffer against environmental change 34 . A host-elicited immune response, the introduction of antiviral drugs, and the transmission to a new species provide important examples of environmental change 35 . Nevertheless, the means by which random mutations lead to viral variants with increased fitness and enhanced survival in the new environment are not well characterized. Given their wide host range, diverse receptor usage and ongoing zoonotic transmission to humans, the coronaviruses provide an important system for studying RNA virus adaptation and evolution. The alphacoronavirus, HCoV-229E, is particularly valuable as it circulates in the human population and a sequence database of natural variants isolated over the past fifty years is available. Moreover, changes in sequence and serology have suggested that HCoV-229E is changing over time in the human population 36 , 37 , 38 . Reported here is the X-ray structure of the HCoV-229E RBD in complex with human APN (hAPN). The structure shows that receptor binding is mediated solely by three extended loops, a feature shared by HCoV-NL63 and the closely related porcine respiratory coronavirus, PRCoV. It also shows that the HCoV-229E RBD binds at a site on hAPN that differs from the site where the PRCoV RBD binds on porcine APN (pAPN), evidence of an ability of the RBD to acquire novel receptor interactions. Remarkably, we find that the natural HCoV-229E sequence variation observed over the past fifty years is highly skewed to the receptor-binding loops. Moreover, we find that the loop variation defines six RBD classes (Classes I–VI) whose viruses have successively replaced each other in the human population. These RBD classes differ in their affinity for hAPN and their ability to be bound by a neutralizing antibody elicited by the HCoV-229E reference strain (Class I). Taken together, our results provide a model for alphacoronavirus adaptation and evolution stemming from the use of extended loops for receptor binding. Results Characterization of the HCoV-229E RBD interaction with hAPN To define the limits of the HCoV-229E RBD, we expressed a series of soluble S-protein fragments and measured their affinity to a soluble fragment (residues 66–967) 39 of hAPN, the HCoV-229E receptor. The smallest S-protein fragment made (residues 293–435) bound hAPN with an affinity ( K d of 0.43 ± 0.1 µM) similar to that of the entire S1 region (residues 17–560) (Table 1 , Supplementary Fig. 1A , B) and this fragment was used in the structure determination. To confirm the importance of the HCoV-229E RBD–hAPN interaction for viral infection, we showed that both the RBD and the hAPN ectodomain inhibited viral infection in a cell-based assay (Fig. 1a, b, c ). Table 1 Analysis<|im_end|> <|im_start|>assistant Common cold season is back, which has people wondering why we catch the same virus, year after year. Why don't we ever develop immunity against the common cold? Professor Pierre Talbot at INRS has known about the incredible variability of coronaviruses for some time. They're responsible for the common cold as well as many other infections, including neurological diseases. Along with his research associate Marc Desforges, Professor Talbot worked on a study recently published in Nature Communications about the ways in which coronaviruses adapt and evolve, becoming ever more effective at infecting hosts without being defeated by the immune system. The small, spiky spheres, the coronaviruses are closely monitored by public health agencies, since they're able to be transmitted between species and some have a high potential mortality rate. Both SARS and MERS are caused by coronaviruses. Their ability to adapt to new environments seems due in part to the spikes on the surface of the virus—more specifically, a small, strategic part of the proteins that form those spikes. The spikes are made up of S proteins (S for spike). A specific part of the spike seems to allow the virus to attach itself to host cells. The spike's RBD (receptor binding domain), which initiates the interaction between cell and virus, is essential for infection. But RBDs are targeted by antibodies that neutralize the virus and allow the immune system to flush it out of the host's system. Coronaviruses are thus faced with an evolutionary problem. They can't infect cells without an RBD, which needs to be exposed so that it can latch onto cells. But the RBD needs to be masked to avoid being targeted by antibodies. In response, the coronavirus has developed a mechanism that helps it survive, and thrive. The RBD is made up of three parts that vary widely between strains. Thanks to this variation, antibodies are unable to detect new strains, whereas RBDs retain—and even improve—their affinity for the target cell. Plus, RBDs alternate between visible and masked states. To gain this insight, a group of researchers including Professor Talbot studied the alphacoronavirus HCoV-229E and, more specifically, the interaction between its RBD and aminopeptidase N (APN)—the host cell protein the RBD latches onto. The team crystallized the multiprotein complex and then analyzed the structures of both proteins. By observing the RBD's structure up close, the team was able to identify the three long loops that latch onto APN. As analyses of these viruses over the last fifty years have shown, these loops are virtually the only thing that varies from one strain to the next. The experiments demonstrate that the changes observed in the loops modulate an RBD's affinity with APN. The variants that have the greatest affinity are also likely to be better at infecting host cells, which helps them spread. Six different classes of HCoV-229E have popped up over the years, each with a greater RBD-APN affinity than the last. This discovery adds to our understanding of the evolution of coronaviruses and could lead to similar analyses of other coronaviruses. Although there are many elements left to explain, the RBD seems to be an important feature that must be monitored as we follow the adaptive evolution of these viruses and assess their ability to infect. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 41214, 42068, 527, 32971, 555, 264, 1579, 27472, 4478, 11, 264, 4240, 2403, 12434, 2349, 13, 35053, 11, 279, 3445, 555, 902, 4288, 27472, 36050, 29962, 17479, 374, 539, 1664, 32971, 13, 5810, 584, 1934, 279, 1630, 30630, 26110, 6070, 315, 279, 35268, 65500, 8106, 320, 49, 9740, 8, 315, 279, 3823, 33333, 11, 473, 7489, 53, 12, 14378, 36, 11, 304, 6485, 449, 279, 77594, 347, 3199, 315, 1202, 35268, 11, 264, 1083, 2862, 418, 307, 521, 452, 320, 2599, 45, 570, 14853, 11838, 30853, 527, 21742, 8647, 369, 35268, 11212, 323, 279, 15740, 315, 473, 7489, 53, 12, 14378, 36, 323, 1202, 3345, 29658, 374, 24895, 555, 10223, 6471, 4235, 265, 15709, 22639, 13, 93682, 86945, 5411, 6492, 5039, 430, 279, 5933, 473, 7489, 53, 12, 14378, 36, 35268, 65500, 6471, 23851, 13468, 19170, 4848, 432, 9740, 6989, 6832, 42068, 617, 2450, 3210, 12860, 1855, 1023, 304, 279, 3823, 7187, 927, 279, 3347, 220, 1135, 1667, 13, 4314, 432, 9740, 6989, 1782, 304, 872, 51552, 369, 10314, 45, 323, 872, 5845, 311, 10950, 459, 473, 7489, 53, 12, 14378, 36, 21277, 4954, 63052, 13, 32255, 11, 1057, 3135, 3493, 264, 1646, 369, 65695, 582, 85950, 24713, 34185, 323, 15740, 3196, 389, 279, 1005, 315, 11838, 30853, 369, 35268, 11212, 13, 29438, 48183, 113765, 4881, 527, 54285, 291, 11, 6928, 42728, 6601, 41214, 42068, 430, 5353, 264, 1396, 315, 42631, 11, 80311, 11, 323, 64908, 19338, 304, 20229, 323, 56669, 220, 16, 1174, 220, 17, 662, 578, 22760, 113765, 4881, 682, 15575, 264, 4279, 46831, 323, 3116, 2204, 84535, 320, 7288, 11, 13746, 11, 22350, 11, 323, 9665, 8, 430, 45925, 1005, 520, 3325, 3116, 2204, 37807, 38828, 5646, 1354, 323, 1645, 2676, 22851, 274, 532, 292, 33969, 439, 3552, 44540, 477, 20581, 9547, 617, 28995, 220, 18, 1174, 220, 19, 1174, 220, 20, 662, 13625, 22760, 113765, 4881, 11, 473, 7489, 53, 12, 14378, 36, 11, 473, 7489, 53, 11500, 43, 5495, 11, 473, 7489, 53, 12, 7767, 3391, 11, 323, 473, 7489, 53, 11529, 42, 52, 16, 4319, 6468, 304, 279, 3823, 7187, 323, 45925, 814, 527, 8647, 369, 264, 5199, 11668, 315, 279, 4279, 9439, 439, 1664, 439, 810, 15748, 42631, 8624, 304, 20134, 22673, 220, 21, 1174, 220, 22, 662, 473, 7489, 53, 12, 14378, 36, 323, 473, 7489, 53, 11500, 43, 5495, 527, 2225, 65695, 582, 85950, 113765, 4881, 323, 8051, 15499, 5552, 11, 814, 617, 28995, 311, 1005, 1403, 2204, 44540, 11, 264, 1083, 2862, 418, 307, 521, 452, 320, 2599, 45, 8, 323, 6590, 11345, 729, 258, 34537, 49242, 220, 17, 320, 5693, 17, 705, 15947, 220, 23, 1174, 220, 24, 662, 578, 810, 1612, 18007, 5552, 1297, 582, 85950, 113765, 4881, 11, 473, 7489, 53, 12, 7767, 3391, 323, 473, 7489, 53, 11529, 42, 52, 16, 11, 527, 2753, 1664, 32971, 323, 8051, 473, 7489, 53, 12, 7767, 3391, 5829, 220, 24, 12, 507, 482, 582, 2676, 4835, 532, 292, 13935, 439, 1202, 35268, 220, 605, 1174, 279, 35268, 369, 473, 7489, 53, 11529, 42, 52, 16, 706, 539, 3686, 1027, 11075, 220, 806, 1174, 220, 717, 1174, 220, 1032, 662, 35390, 1167, 9186, 14546, 18874, 315, 1297, 582, 85950, 113765, 4881, 505, 43308, 374, 8647, 369, 328, 17485, 323, 386, 4419, 11, 323, 304, 1521, 5157, 19405, 374, 5938, 449, 1790, 810, 6129, 8624, 323, 1579, 7969, 315, 29528, 220, 975, 1174, 220, 868, 1174, 220, 845, 662, 9086, 473, 7489, 53, 11500, 43, 5495, 11, 328, 17485, 87271, 53, 5829, 41906, 17, 220, 1114, 439, 1202, 35268, 323, 279, 22695, 430, 386, 4419, 87271, 53, 5829, 1891, 375, 418, 307, 4010, 1069, 418, 307, 521, 220, 19, 220, 972, 22020, 279, 2144, 430, 22760, 113765, 4881, 449, 502, 35268, 3230, 1385, 3136, 311, 31889, 13, 578, 33333, 37393, 13128, 320, 50, 10039, 39340, 8, 374, 264, 490, 3212, 292, 3254, 48067, 39654, 13128, 430, 25098, 988, 35268, 11212, 323, 37608, 315, 279, 29962, 323, 3552, 2849, 79348, 220, 777, 662, 1102, 374, 264, 955, 12, 16, 29962, 37608, 13128, 60662, 1403, 13918, 11, 279, 328, 16, 5654, 430, 5727, 279, 35268, 65500, 8106, 320, 49, 9740, 8, 323, 279, 328, 17, 5654, 430, 5727, 279, 37608, 72249, 323, 568, 418, 329, 44694, 6532, 304, 39654, 37608, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 662, 578, 33333, 328, 10039, 39340, 374, 1101, 264, 3682, 2218, 315, 21277, 4954, 59854, 323, 832, 15632, 315, 3552, 38973, 21277, 4954, 59854, 374, 279, 6727, 315, 29962, 27103, 13171, 315, 3721, 2277, 1124, 11, 264, 1920, 3967, 311, 6678, 23851, 220, 1627, 1174, 220, 1544, 1174, 220, 1591, 662, 1666, 6982, 555, 2225, 304, 41294, 323, 304, 55004, 7978, 11, 4442, 304, 3552, 11, 3552, 2849, 955, 11, 5425, 58894, 552, 18874, 11, 35268, 7645, 5990, 11, 6275, 21765, 11, 323, 20438, 7829, 4787, 649, 1101, 6678, 29962, 23851, 220, 1682, 1174, 220, 966, 1174, 220, 2148, 1174, 220, 843, 1174, 220, 1644, 662, 41214, 42068, 527, 32971, 555, 264, 1579, 27472, 4478, 11, 264, 3424, 13788, 439, 264, 4240, 2403, 12434, 2349, 220, 1958, 662, 362, 3552, 12, 43723, 1639, 22852, 2077, 11, 279, 17219, 315, 3276, 344, 37478, 11217, 11, 323, 279, 18874, 311, 264, 502, 9606, 3493, 3062, 10507, 315, 12434, 2349, 220, 1758, 662, 35053, 11, 279, 3445, 555, 902, 4288, 34684, 3063, 311, 29962, 27103, 449, 7319, 17479, 323, 24872, 20237, 304, 279, 502, 4676, 527, 539, 1664, 32971, 13, 16644, 872, 7029, 3552, 2134, 11, 17226, 35268, 10648, 323, 14529, 1167, 9186, 14546, 18874, 311, 12966, 11, 279, 22760, 113765, 4881, 3493, 459, 3062, 1887, 369, 21630, 41214, 17188, 34185, 323, 15740, 13, 578, 65695, 582, 85950, 24713, 11, 473, 7489, 53, 12, 14378, 36, 11, 374, 8104, 15525, 439, 433, 4319, 24031, 304, 279, 3823, 7187, 323, 264, 8668, 4729, 315, 5933, 27103, 25181, 927, 279, 3347, 33517, 1667, 374, 2561, 13, 23674, 11, 4442, 304, 8668, 323, 1446, 2508, 617, 12090, 430, 473, 7489, 53, 12, 14378, 36, 374, 10223, 927, 892, 304, 279, 3823, 7187, 220, 1927, 1174, 220, 1806, 1174, 220, 1987, 662, 79711, 1618, 374, 279, 1630, 30630, 6070, 315, 279, 473, 7489, 53, 12, 14378, 36, 432, 9740, 304, 6485, 449, 3823, 10314, 45, 320, 71, 2599, 45, 570, 578, 6070, 5039, 430, 35268, 11212, 374, 78926, 21742, 555, 2380, 11838, 30853, 11, 264, 4668, 6222, 555, 473, 7489, 53, 11500, 43, 5495, 323, 279, 15499, 5552, 4247, 66, 483, 42631, 33333, 11, 8743, 7489, 53, 13, 1102, 1101, 5039, 430, 279, 473, 7489, 53, 12, 14378, 36, 432, 9740, 58585, 520, 264, 2816, 389, 305, 2599, 45, 430, 44642, 505, 279, 2816, 1405, 279, 8743, 7489, 53, 432, 9740, 58585, 389, 4247, 66, 483, 10314, 45, 320, 79, 2599, 45, 705, 6029, 315, 459, 5845, 315, 279, 432, 9740, 311, 21953, 11775, 35268, 22639, 13, 83833, 2915, 11, 584, 1505, 430, 279, 5933, 473, 7489, 53, 12, 14378, 36, 8668, 23851, 13468, 927, 279, 3347, 33517, 1667, 374, 7701, 87572, 311, 279, 35268, 65500, 30853, 13, 23674, 11, 584, 1505, 430, 279, 6471, 23851, 19170, 4848, 432, 9740, 6989, 320, 20678, 358, 4235, 26376, 8, 6832, 42068, 617, 2450, 3210, 12860, 1855, 1023, 304, 279, 3823, 7187, 13, 4314, 432, 9740, 6989, 1782, 304, 872, 51552, 369, 305, 2599, 45, 323, 872, 5845, 311, 387, 6965, 555, 264, 21277, 4954, 63052, 95360, 1639, 555, 279, 473, 7489, 53, 12, 14378, 36, 5905, 26800, 320, 1999, 358, 570, 57074, 3871, 11, 1057, 3135, 3493, 264, 1646, 369, 65695, 582, 85950, 24713, 34185, 323, 15740, 77044, 505, 279, 1005, 315, 11838, 30853, 369, 35268, 11212, 13, 18591, 16007, 2065, 315, 279, 473, 7489, 53, 12, 14378, 36, 432, 9740, 16628, 449, 305, 2599, 45, 2057, 7124, 279, 13693, 315, 279, 473, 7489, 53, 12, 14378, 36, 432, 9740, 11, 584, 13605, 264, 4101, 315, 88045, 328, 10039, 39340, 35603, 323, 17303, 872, 51552, 311, 264, 88045, 12569, 320, 417, 307, 1157, 220, 2287, 4235, 27134, 8, 220, 2137, 315, 305, 2599, 45, 11, 279, 473, 7489, 53, 12, 14378, 36, 35268, 13, 578, 25655, 328, 10039, 39340, 12569, 1903, 320, 417, 307, 1157, 220, 17313, 4235, 19305, 8, 6965, 305, 2599, 45, 449, 459, 51552, 320, 735, 294, 315, 220, 15, 13, 3391, 20903, 220, 15, 13, 16, 64012, 44, 8, 4528, 311, 430, 315, 279, 4553, 328, 16, 5654, 320, 417, 307, 1157, 220, 1114, 4235, 17698, 8, 320, 2620, 220, 16, 1174, 99371, 23966, 13, 220, 16, 32, 1174, 426, 8, 323, 420, 12569, 574, 1511, 304, 279, 6070, 26314, 13, 2057, 7838, 279, 12939, 315, 279, 473, 7489, 53, 12, 14378, 36, 432, 9740, 4235, 71, 2599, 45, 16628, 369, 29962, 19405, 11, 584, 8710, 430, 2225, 279, 432, 9740, 323, 279, 305, 2599, 45, 77594, 347, 3199, 99669, 29962, 19405, 304, 264, 2849, 6108, 65033, 320, 30035, 13, 220, 16, 64, 11, 293, 11, 272, 7609, 6771, 220, 16, 18825, 128257, 198, 128256, 78191, 198, 11076, 9439, 3280, 374, 1203, 11, 902, 706, 1274, 20910, 3249, 584, 2339, 279, 1890, 17188, 11, 1060, 1306, 1060, 13, 8595, 1541, 956, 584, 3596, 2274, 40368, 2403, 279, 4279, 9439, 30, 17054, 38077, 18051, 6465, 520, 2006, 11706, 706, 3967, 922, 279, 15400, 54709, 315, 22760, 113765, 4881, 369, 1063, 892, 13, 2435, 2351, 8647, 369, 279, 4279, 9439, 439, 1664, 439, 1690, 1023, 30020, 11, 2737, 64908, 19338, 13, 32944, 449, 813, 3495, 22712, 19412, 3959, 69, 81875, 11, 17054, 18051, 6465, 6575, 389, 264, 4007, 6051, 4756, 304, 22037, 26545, 922, 279, 5627, 304, 902, 22760, 113765, 4881, 10737, 323, 38680, 11, 10671, 3596, 810, 7524, 520, 34527, 287, 18939, 2085, 1694, 24164, 555, 279, 22852, 1887, 13, 578, 2678, 11, 993, 106493, 66818, 11, 279, 22760, 113765, 4881, 527, 15499, 41223, 555, 586, 2890, 13607, 11, 2533, 814, 2351, 3025, 311, 387, 34699, 1990, 9606, 323, 1063, 617, 264, 1579, 4754, 29528, 4478, 13, 11995, 328, 17485, 323, 386, 4419, 527, 9057, 555, 22760, 113765, 4881, 13, 11205, 5845, 311, 10737, 311, 502, 22484, 5084, 4245, 304, 961, 311, 279, 51760, 389, 279, 7479, 315, 279, 17188, 2345, 6518, 11951, 11, 264, 2678, 11, 19092, 961, 315, 279, 28896, 430, 1376, 1884, 51760, 13, 578, 51760, 527, 1903, 709, 315, 328, 28896, 320, 50, 369, 37393, 570, 362, 3230, 961, 315, 279, 37393, 5084, 311, 2187, 279, 17188, 311, 15866, 5196, 311, 3552, 7917, 13, 578, 37393, 596, 432, 9740, 320, 265, 15709, 11212, 8106, 705, 902, 12961, 988, 279, 16628, 1990, 2849, 323, 17188, 11, 374, 7718, 369, 19405, 13, 2030, 432, 9740, 82, 527, 17550, 555, 59854, 430, 21277, 553, 279, 17188, 323, 2187, 279, 22852, 1887, 311, 18698, 433, 704, 315, 279, 3552, 596, 1887, 13, 48183, 113765, 4881, 527, 8617, 17011, 449, 459, 41993, 3575, 13, 2435, 649, 956, 34527, 7917, 2085, 459, 432, 9740, 11, 902, 3966, 311, 387, 15246, 779, 430, 433, 649, 58026, 8800, 7917, 13, 2030, 279, 432, 9740, 3966, 311, 387, 43248, 311, 5766, 1694, 17550, 555, 59854, 13, 763, 2077, 11, 279, 33333, 706, 8040, 264, 17383, 430, 8779, 433, 18167, 11, 323, 41972, 13, 578, 432, 9740, 374, 1903, 709, 315, 2380, 5596, 430, 13592, 13882, 1990, 42400, 13, 11361, 311, 420, 23851, 11, 59854, 527, 12153, 311, 11388, 502, 42400, 11, 20444, 432, 9740, 82, 14389, 17223, 1524, 7417, 22416, 404, 51552, 369, 279, 2218, 2849, 13, 12623, 11, 432, 9740, 82, 25631, 1990, 9621, 323, 43248, 5415, 13, 2057, 8895, 420, 20616, 11, 264, 1912, 315, 12074, 2737, 17054, 18051, 6465, 20041, 279, 65695, 582, 85950, 24713, 473, 7489, 53, 12, 14378, 36, 323, 11, 810, 11951, 11, 279, 16628, 1990, 1202, 432, 9740, 323, 264, 1083, 2862, 418, 307, 521, 452, 320, 2599, 45, 68850, 1820, 3552, 2849, 13128, 279, 432, 9740, 326, 9296, 8800, 13, 578, 2128, 64568, 1534, 279, 12842, 91748, 6485, 323, 1243, 30239, 279, 14726, 315, 2225, 28896, 13, 3296, 46071, 279, 432, 9740, 596, 6070, 709, 3345, 11, 279, 2128, 574, 3025, 311, 10765, 279, 2380, 1317, 30853, 430, 58026, 8800, 10314, 45, 13, 1666, 29060, 315, 1521, 42068, 927, 279, 1566, 33517, 1667, 617, 6982, 11, 1521, 30853, 527, 21907, 279, 1193, 3245, 430, 35327, 505, 832, 26800, 311, 279, 1828, 13, 578, 21896, 20461, 430, 279, 4442, 13468, 304, 279, 30853, 1491, 6468, 459, 432, 9740, 596, 51552, 449, 10314, 45, 13, 578, 27103, 430, 617, 279, 12474, 51552, 527, 1101, 4461, 311, 387, 2731, 520, 34527, 287, 3552, 7917, 11, 902, 8779, 1124, 9041, 13, 19198, 2204, 6989, 315, 473, 7489, 53, 12, 14378, 36, 617, 43333, 709, 927, 279, 1667, 11, 1855, 449, 264, 7191, 432, 9740, 12, 2599, 45, 51552, 1109, 279, 1566, 13, 1115, 18841, 11621, 311, 1057, 8830, 315, 279, 15740, 315, 22760, 113765, 4881, 323, 1436, 3063, 311, 4528, 29060, 315, 1023, 22760, 113765, 4881, 13, 10541, 1070, 527, 1690, 5540, 2163, 311, 10552, 11, 279, 432, 9740, 5084, 311, 387, 459, 3062, 4668, 430, 2011, 387, 41223, 439, 584, 1833, 279, 48232, 15740, 315, 1521, 42068, 323, 8720, 872, 5845, 311, 34527, 13, 220, 128257, 198 ]

2,219

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability. Introduction How mean historical and future climate change affects crop yields has received a great deal of attention 1 , 2 , 3 , 4 , 5 . However, how variations in climate impact crop yield, and how they vary over time, has received less attention 6 , 7 . This is important both to help us understand how climate and crop yields are linked over time and also for ensuring future food security. In particular, low-yield variability leads to stable farmer incomes 8 , 9 , 10 and food supply 1 , 11 , and prevents price spikes that have disproportionate adverse impacts on the globally food-insecure who are mostly farmers 12 , 13 . In this study, we ask how much of the year-to-year variability in observed crop yields is associated with variations in climate across global croplands? Further, we investigate which climatic variables—those related to warmth and growing season length, or those related to rainfall and moisture availability—best explain variations in yield across the world? Previous analyses that have examined how crop yields and climate were related 3 , 14 , 15 , 16 , 17 have typically used national and regional data. For example, global studies are typically at the country scale 1 , and provide little insight on the spatial patterns of the within-country impacts. In contrast, analysis at the subnational 16 , sub-subnational 2 or local sites is available for specific countries only, and thus, provide little insight on global patterns. Our study uses newly available temporal geospatial data on crop harvested area and yields of four major crops (maize, rice, wheat and soybean) across 13,500 different political units of the world 12 , 13 —a major (>50x) increase in the level of spatial detail from previous analyses that examined how crop yields and climate were related 3 , 14 , 15 , 16 , 17 . Similar to other studies 1 , 2 , we examine the recent historical period (1979–2008) but across these 13,500 different political units of the world 12 , 13 . The increased spatial resolution helps to identify where, and how strongly, climate variability is correlated with variations in crop yield in each of these political units. Given multiple breadbaskets across the globe and globally traded commodities, our study provides a consistent investigation of the differences both within and across regions. To examine how observed variations in yields were related to climate variations, we used the Climate Research Unit’s (CRU) 18 gridded monthly data, and then re-mapped the data to the ~13,500 political units where yield was measured. We explored a range of statistical models relating observed de-trended variations in temperature and precipitation during a crop’s growing season and annual conditions to the observed de-trended variations in yields at each political unit. Next we selected the ‘best-fit’ model, and then conducted F -tests to determine the goodness-of-fit of the selected model against the null model that assumes random climate variability. We conducted this analysis at each of the tracked 13,500 political units to draw conclusions on how much of the crop yield variability was explained by climate variability. Different aspects of climate variability—temperature, precipitation, and the interaction of the two—may affect crop growth and resultant productivity disproportionately. We classified how yield variability was related to either normal or extreme fluctuations in temperature or precipitation variability—or their interactions. Here, linear and squared terms represent normal and extreme variation, respectively, for example 1 , 5 , 16 . The ‘best-fit’ model at each political unit was classified into one of seven broad categories and then mapped globally: models where the yield variability was explained by (i) normal temperature or (ii) normal precipitation variations, but not both; models where the yield variability was explained by (iii) normal and extreme temperature or (iv) normal and extreme precipitation variations, but not both; (v) where yield variability was explained by extreme temperature or (vi) extreme precipitation variations, but not both; and (vii) temperature and precipitation terms and their combinations due to interactions between temperature and precipitation. We further developed reduced models of temperature and precipitation and mapped them at each political unit. The resulting global maps, which identify where and to what degree normal and extreme climate variability explains yield variability, and quantifies them, can be used to target research into causal relations between yield and climate variability, and eventually policy interventions to stabilize farmer incomes and food supply. Averaged globally over areas with significant relationships, we find that 32–39% of the maize, rice, wheat and soybean year-to-year yield variability was explained by climate variability. This translates into climate explained annual production fluctuations of ~22 million tons, ~3 million tons, ~9 million tons and ~2 million tons for maize, rice, wheat and soybean, respectively. Our spatially detailed assessment of the relationship between climate variability and yield variability shows distinct spatial patterns in the relative effects of temperature, precipitation and their interaction within and across regions. Results Yield variability We first establish where and by how much crop yields varied within countries and then identify how much of the year-to-year variation in", "role": "user" }, { "content": "What impact will future climate change have on food supply? That depends in part on the extent to which variations in crop yield are attributable to variations in climate. A new report from researchers at the University of Minnesota Institute on the Environment has found that climate variability historically accounts for one-third of yield variability for maize, rice, wheat and soybeans worldwide—the equivalent of 36 million metric tons of food each year. This provides valuable information planners and policy makers can use to target efforts to stabilize farmer income and food supply and so boost food security in a warming world. The work was published today in the journal Nature Communications by Deepak Ray, James Gerber, Graham MacDonald and Paul West of IonE's Global Landscapes Initiative.The researchers looked at newly available production statistics for maize, rice, wheat and soybean from 13,500 political units around the world between 1979 and 2008, along with precipitation and temperature data. The team used these data to calculate year-to-year fluctuations and estimate how much of the yield variability could be attributed to climate variability. About 32 to 39 percent of year-to-year variability for the four crops could be explained by climate variability. This is substantial—the equivalent of 22 million metric tons of maize, 3 million metric tons of rice, 9 million metric tons of wheat, and 2 million metric tons of soybeans per year.The links between climate and yield variability differed among regions. Climate variability explained much of yield variability in some of the most productive regions, but far less in low-yielding regions. \"This means that really productive areas contribute to food security by having a bumper crop when the weather is favorable but can be hit really hard when the weather is bad and contribute disproportionately to global food insecurity,\" says Ray. \"At the other end of the spectrum, low-yielding regions seem to be more resilient to bad-weather years but don't see big gains when the weather is ideal.\" Some regions, such as in parts of Asia and Africa, showed little correlation between climate variability and yield variability. More than 60 percent of the yield variability can be explained by climate variability in regions that are important producers of major crops, including the Midwestern U.S., the North China Plains, western Europe and Japan.Depicted as global maps, the results show where and how much climate variability explains yield variability. The research team is now looking at historical records to see whether the variability attributable to climate has changed over time—and if so, what aspects of climate are most pertinent. \"Yield variability can be a big problem from both economic and food supply standpoints,\" Ray said. \"The results of this study and our follow-up work can be used to improve food system stability around the world by identifying hot spots of food insecurity today as well as those likely to be exacerbated by climate change in the future.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability. Introduction How mean historical and future climate change affects crop yields has received a great deal of attention 1 , 2 , 3 , 4 , 5 . However, how variations in climate impact crop yield, and how they vary over time, has received less attention 6 , 7 . This is important both to help us understand how climate and crop yields are linked over time and also for ensuring future food security. In particular, low-yield variability leads to stable farmer incomes 8 , 9 , 10 and food supply 1 , 11 , and prevents price spikes that have disproportionate adverse impacts on the globally food-insecure who are mostly farmers 12 , 13 . In this study, we ask how much of the year-to-year variability in observed crop yields is associated with variations in climate across global croplands? Further, we investigate which climatic variables—those related to warmth and growing season length, or those related to rainfall and moisture availability—best explain variations in yield across the world? Previous analyses that have examined how crop yields and climate were related 3 , 14 , 15 , 16 , 17 have typically used national and regional data. For example, global studies are typically at the country scale 1 , and provide little insight on the spatial patterns of the within-country impacts. In contrast, analysis at the subnational 16 , sub-subnational 2 or local sites is available for specific countries only, and thus, provide little insight on global patterns. Our study uses newly available temporal geospatial data on crop harvested area and yields of four major crops (maize, rice, wheat and soybean) across 13,500 different political units of the world 12 , 13 —a major (>50x) increase in the level of spatial detail from previous analyses that examined how crop yields and climate were related 3 , 14 , 15 , 16 , 17 . Similar to other studies 1 , 2 , we examine the recent historical period (1979–2008) but across these 13,500 different political units of the world 12 , 13 . The increased spatial resolution helps to identify where, and how strongly, climate variability is correlated with variations in crop yield in each of these political units. Given multiple breadbaskets across the globe and globally traded commodities, our study provides a consistent investigation of the differences both within and across regions. To examine how observed variations in yields were related to climate variations, we used the Climate Research Unit’s (CRU) 18 gridded monthly data, and then re-mapped the data to the ~13,500 political units where yield was measured. We explored a range of statistical models relating observed de-trended variations in temperature and precipitation during a crop’s growing season and annual conditions to the observed de-trended variations in yields at each political unit. Next we selected the ‘best-fit’ model, and then conducted F -tests to determine the goodness-of-fit of the selected model against the null model that assumes random climate variability. We conducted this analysis at each of the tracked 13,500 political units to draw conclusions on how much of the crop yield variability was explained by climate variability. Different aspects of climate variability—temperature, precipitation, and the interaction of the two—may affect crop growth and resultant productivity disproportionately. We classified how yield variability was related to either normal or extreme fluctuations in temperature or precipitation variability—or their interactions. Here, linear and squared terms represent normal and extreme variation, respectively, for example 1 , 5 , 16 . The ‘best-fit’ model at each political unit was classified into one of seven broad categories and then mapped globally: models where the yield variability was explained by (i) normal temperature or (ii) normal precipitation variations, but not both; models where the yield variability was explained by (iii) normal and extreme temperature or (iv) normal and extreme precipitation variations, but not both; (v) where yield variability was explained by extreme temperature or (vi) extreme precipitation variations, but not both; and (vii) temperature and precipitation terms and their combinations due to interactions between temperature and precipitation. We further developed reduced models of temperature and precipitation and mapped them at each political unit. The resulting global maps, which identify where and to what degree normal and extreme climate variability explains yield variability, and quantifies them, can be used to target research into causal relations between yield and climate variability, and eventually policy interventions to stabilize farmer incomes and food supply. Averaged globally over areas with significant relationships, we find that 32–39% of the maize, rice, wheat and soybean year-to-year yield variability was explained by climate variability. This translates into climate explained annual production fluctuations of ~22 million tons, ~3 million tons, ~9 million tons and ~2 million tons for maize, rice, wheat and soybean, respectively. Our spatially detailed assessment of the relationship between climate variability and yield variability shows distinct spatial patterns in the relative effects of temperature, precipitation and their interaction within and across regions. Results Yield variability We first establish where and by how much crop yields varied within countries and then identify how much of the year-to-year variation in<|im_end|> <|im_start|>assistant What impact will future climate change have on food supply? That depends in part on the extent to which variations in crop yield are attributable to variations in climate. A new report from researchers at the University of Minnesota Institute on the Environment has found that climate variability historically accounts for one-third of yield variability for maize, rice, wheat and soybeans worldwide—the equivalent of 36 million metric tons of food each year. This provides valuable information planners and policy makers can use to target efforts to stabilize farmer income and food supply and so boost food security in a warming world. The work was published today in the journal Nature Communications by Deepak Ray, James Gerber, Graham MacDonald and Paul West of IonE's Global Landscapes Initiative.The researchers looked at newly available production statistics for maize, rice, wheat and soybean from 13,500 political units around the world between 1979 and 2008, along with precipitation and temperature data. The team used these data to calculate year-to-year fluctuations and estimate how much of the yield variability could be attributed to climate variability. About 32 to 39 percent of year-to-year variability for the four crops could be explained by climate variability. This is substantial—the equivalent of 22 million metric tons of maize, 3 million metric tons of rice, 9 million metric tons of wheat, and 2 million metric tons of soybeans per year.The links between climate and yield variability differed among regions. Climate variability explained much of yield variability in some of the most productive regions, but far less in low-yielding regions. "This means that really productive areas contribute to food security by having a bumper crop when the weather is favorable but can be hit really hard when the weather is bad and contribute disproportionately to global food insecurity," says Ray. "At the other end of the spectrum, low-yielding regions seem to be more resilient to bad-weather years but don't see big gains when the weather is ideal." Some regions, such as in parts of Asia and Africa, showed little correlation between climate variability and yield variability. More than 60 percent of the yield variability can be explained by climate variability in regions that are important producers of major crops, including the Midwestern U.S., the North China Plains, western Europe and Japan.Depicted as global maps, the results show where and how much climate variability explains yield variability. The research team is now looking at historical records to see whether the variability attributable to climate has changed over time—and if so, what aspects of climate are most pertinent. "Yield variability can be a big problem from both economic and food supply standpoints," Ray said. "The results of this study and our follow-up work can be used to improve food system stability around the world by identifying hot spots of food insecurity today as well as those likely to be exacerbated by climate change in the future." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 9176, 7978, 617, 25078, 279, 3560, 315, 3152, 10182, 2349, 304, 30029, 11, 719, 459, 8830, 315, 279, 10383, 315, 958, 12, 64709, 10182, 27339, 389, 19641, 36508, 304, 2204, 13918, 8625, 66684, 13, 1226, 1005, 11944, 19641, 13443, 892, 4101, 369, 4056, 1032, 11, 2636, 5054, 8316, 311, 21635, 1268, 3293, 10182, 54709, 6197, 311, 27339, 304, 93307, 11, 20228, 11, 34153, 323, 29839, 17937, 19641, 36508, 15603, 13, 6104, 1063, 5789, 1501, 912, 5199, 10383, 315, 10182, 54709, 11, 304, 12190, 5789, 315, 279, 3728, 16385, 65, 49240, 11, 871, 1399, 4, 315, 279, 7692, 54709, 649, 387, 11497, 555, 10182, 54709, 13, 63388, 750, 11, 10182, 54709, 9815, 369, 17715, 264, 4948, 31857, 843, 4235, 2137, 11587, 315, 279, 13468, 7692, 54709, 13, 5751, 4007, 42329, 46480, 29079, 12912, 304, 279, 5133, 1990, 10182, 54709, 323, 19641, 7692, 54709, 11, 39686, 1405, 27339, 304, 9499, 11, 61050, 477, 872, 16628, 10552, 7692, 54709, 13, 1226, 4358, 1401, 12050, 369, 279, 13468, 27339, 311, 2218, 4726, 3495, 323, 4947, 39455, 59547, 7119, 88239, 3938, 19641, 5788, 505, 10182, 54709, 13, 29438, 2650, 3152, 13970, 323, 3938, 10182, 2349, 22223, 19641, 36508, 706, 4036, 264, 2294, 3568, 315, 6666, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 1174, 220, 20, 662, 4452, 11, 1268, 27339, 304, 10182, 5536, 19641, 7692, 11, 323, 1268, 814, 13592, 927, 892, 11, 706, 4036, 2753, 6666, 220, 21, 1174, 220, 22, 662, 1115, 374, 3062, 2225, 311, 1520, 603, 3619, 1268, 10182, 323, 19641, 36508, 527, 10815, 927, 892, 323, 1101, 369, 23391, 3938, 3691, 4868, 13, 763, 4040, 11, 3428, 12303, 823, 54709, 11767, 311, 15528, 37500, 46791, 220, 23, 1174, 220, 24, 1174, 220, 605, 323, 3691, 8312, 220, 16, 1174, 220, 806, 1174, 323, 29034, 3430, 51760, 430, 617, 80153, 31959, 25949, 389, 279, 31550, 3691, 3502, 26189, 889, 527, 10213, 20957, 220, 717, 1174, 220, 1032, 662, 763, 420, 4007, 11, 584, 2610, 1268, 1790, 315, 279, 1060, 4791, 4771, 54709, 304, 13468, 19641, 36508, 374, 5938, 449, 27339, 304, 10182, 4028, 3728, 14425, 501, 2914, 30, 15903, 11, 584, 19874, 902, 11323, 780, 7482, 2345, 54719, 5552, 311, 41463, 323, 7982, 3280, 3160, 11, 477, 1884, 5552, 311, 53958, 323, 32257, 18539, 2345, 16241, 10552, 27339, 304, 7692, 4028, 279, 1917, 30, 30013, 29060, 430, 617, 25078, 1268, 19641, 36508, 323, 10182, 1051, 5552, 220, 18, 1174, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 617, 11383, 1511, 5426, 323, 15481, 828, 13, 1789, 3187, 11, 3728, 7978, 527, 11383, 520, 279, 3224, 5569, 220, 16, 1174, 323, 3493, 2697, 20616, 389, 279, 29079, 12912, 315, 279, 2949, 56971, 25949, 13, 763, 13168, 11, 6492, 520, 279, 1207, 42240, 220, 845, 1174, 1207, 18451, 42240, 220, 17, 477, 2254, 6732, 374, 2561, 369, 3230, 5961, 1193, 11, 323, 8617, 11, 3493, 2697, 20616, 389, 3728, 12912, 13, 5751, 4007, 5829, 13945, 2561, 37015, 3980, 437, 33514, 828, 389, 19641, 67572, 3158, 323, 36508, 315, 3116, 3682, 31665, 320, 1764, 553, 11, 20228, 11, 34153, 323, 29839, 17937, 8, 4028, 220, 1032, 11, 2636, 2204, 5054, 8316, 315, 279, 1917, 220, 717, 1174, 220, 1032, 2001, 64, 3682, 77952, 1135, 87, 8, 5376, 304, 279, 2237, 315, 29079, 7872, 505, 3766, 29060, 430, 25078, 1268, 19641, 36508, 323, 10182, 1051, 5552, 220, 18, 1174, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 662, 22196, 311, 1023, 7978, 220, 16, 1174, 220, 17, 1174, 584, 21635, 279, 3293, 13970, 4261, 320, 4468, 24, 4235, 1049, 23, 8, 719, 4028, 1521, 220, 1032, 11, 2636, 2204, 5054, 8316, 315, 279, 1917, 220, 717, 1174, 220, 1032, 662, 578, 7319, 29079, 11175, 8779, 311, 10765, 1405, 11, 323, 1268, 16917, 11, 10182, 54709, 374, 49393, 449, 27339, 304, 19641, 7692, 304, 1855, 315, 1521, 5054, 8316, 13, 16644, 5361, 16385, 65, 49240, 4028, 279, 24867, 323, 31550, 31207, 51967, 11, 1057, 4007, 5825, 264, 13263, 8990, 315, 279, 12062, 2225, 2949, 323, 4028, 13918, 13, 2057, 21635, 1268, 13468, 27339, 304, 36508, 1051, 5552, 311, 10182, 27339, 11, 584, 1511, 279, 31636, 8483, 8113, 753, 320, 9150, 52, 8, 220, 972, 1099, 1810, 291, 15438, 828, 11, 323, 1243, 312, 1474, 5795, 279, 828, 311, 279, 4056, 1032, 11, 2636, 5054, 8316, 1405, 7692, 574, 17303, 13, 1226, 36131, 264, 2134, 315, 29564, 4211, 23343, 13468, 409, 2442, 9484, 291, 27339, 304, 9499, 323, 61050, 2391, 264, 19641, 753, 7982, 3280, 323, 9974, 4787, 311, 279, 13468, 409, 2442, 9484, 291, 27339, 304, 36508, 520, 1855, 5054, 5089, 13, 9479, 584, 4183, 279, 3451, 16241, 50660, 529, 1646, 11, 323, 1243, 13375, 435, 482, 24781, 311, 8417, 279, 39526, 8838, 50660, 315, 279, 4183, 1646, 2403, 279, 854, 1646, 430, 22204, 4288, 10182, 54709, 13, 1226, 13375, 420, 6492, 520, 1855, 315, 279, 34156, 220, 1032, 11, 2636, 5054, 8316, 311, 4128, 31342, 389, 1268, 1790, 315, 279, 19641, 7692, 54709, 574, 11497, 555, 10182, 54709, 13, 34496, 13878, 315, 10182, 54709, 2345, 35658, 11, 61050, 11, 323, 279, 16628, 315, 279, 1403, 2345, 18864, 7958, 19641, 6650, 323, 84913, 26206, 73152, 13, 1226, 21771, 1268, 7692, 54709, 574, 5552, 311, 3060, 4725, 477, 14560, 65649, 304, 9499, 477, 61050, 54709, 51749, 872, 22639, 13, 5810, 11, 13790, 323, 53363, 3878, 4097, 4725, 323, 14560, 23851, 11, 15947, 11, 369, 3187, 220, 16, 1174, 220, 20, 1174, 220, 845, 662, 578, 3451, 16241, 50660, 529, 1646, 520, 1855, 5054, 5089, 574, 21771, 1139, 832, 315, 8254, 7353, 11306, 323, 1243, 24784, 31550, 25, 4211, 1405, 279, 7692, 54709, 574, 11497, 555, 320, 72, 8, 4725, 9499, 477, 320, 3893, 8, 4725, 61050, 27339, 11, 719, 539, 2225, 26, 4211, 1405, 279, 7692, 54709, 574, 11497, 555, 320, 35694, 8, 4725, 323, 14560, 9499, 477, 320, 344, 8, 4725, 323, 14560, 61050, 27339, 11, 719, 539, 2225, 26, 320, 85, 8, 1405, 7692, 54709, 574, 11497, 555, 14560, 9499, 477, 320, 10176, 8, 14560, 61050, 27339, 11, 719, 539, 2225, 26, 323, 320, 85, 3893, 8, 9499, 323, 61050, 3878, 323, 872, 28559, 4245, 311, 22639, 1990, 9499, 323, 61050, 13, 1226, 4726, 8040, 11293, 4211, 315, 9499, 323, 61050, 323, 24784, 1124, 520, 1855, 5054, 5089, 13, 578, 13239, 3728, 14370, 11, 902, 10765, 1405, 323, 311, 1148, 8547, 4725, 323, 14560, 10182, 54709, 15100, 7692, 54709, 11, 323, 10484, 9803, 1124, 11, 649, 387, 1511, 311, 2218, 3495, 1139, 59557, 4398, 1990, 7692, 323, 10182, 54709, 11, 323, 9778, 4947, 39455, 311, 70236, 37500, 46791, 323, 3691, 8312, 13, 362, 424, 3359, 31550, 927, 5789, 449, 5199, 12135, 11, 584, 1505, 430, 220, 843, 4235, 2137, 4, 315, 279, 93307, 11, 20228, 11, 34153, 323, 29839, 17937, 1060, 4791, 4771, 7692, 54709, 574, 11497, 555, 10182, 54709, 13, 1115, 48018, 1139, 10182, 11497, 9974, 5788, 65649, 315, 4056, 1313, 3610, 20181, 11, 4056, 18, 3610, 20181, 11, 4056, 24, 3610, 20181, 323, 4056, 17, 3610, 20181, 369, 93307, 11, 20228, 11, 34153, 323, 29839, 17937, 11, 15947, 13, 5751, 29079, 398, 11944, 15813, 315, 279, 5133, 1990, 10182, 54709, 323, 7692, 54709, 5039, 12742, 29079, 12912, 304, 279, 8844, 6372, 315, 9499, 11, 61050, 323, 872, 16628, 2949, 323, 4028, 13918, 13, 18591, 78478, 54709, 1226, 1176, 5813, 1405, 323, 555, 1268, 1790, 19641, 36508, 28830, 2949, 5961, 323, 1243, 10765, 1268, 1790, 315, 279, 1060, 4791, 4771, 23851, 304, 128257, 198, 128256, 78191, 198, 3923, 5536, 690, 3938, 10182, 2349, 617, 389, 3691, 8312, 30, 3011, 14117, 304, 961, 389, 279, 13112, 311, 902, 27339, 304, 19641, 7692, 527, 71526, 311, 27339, 304, 10182, 13, 362, 502, 1934, 505, 12074, 520, 279, 3907, 315, 19461, 10181, 389, 279, 11847, 706, 1766, 430, 10182, 54709, 35901, 9815, 369, 832, 30277, 315, 7692, 54709, 369, 93307, 11, 20228, 11, 34153, 323, 29839, 28440, 15603, 22416, 13890, 315, 220, 1927, 3610, 18767, 20181, 315, 3691, 1855, 1060, 13, 1115, 5825, 15525, 2038, 68552, 323, 4947, 29414, 649, 1005, 311, 2218, 9045, 311, 70236, 37500, 8070, 323, 3691, 8312, 323, 779, 7916, 3691, 4868, 304, 264, 24808, 1917, 13, 578, 990, 574, 4756, 3432, 304, 279, 8486, 22037, 26545, 555, 18682, 587, 13558, 11, 7957, 20524, 655, 11, 26181, 81973, 323, 7043, 4410, 315, 45905, 36, 596, 8121, 11680, 2445, 9521, 38756, 11829, 12074, 7111, 520, 13945, 2561, 5788, 13443, 369, 93307, 11, 20228, 11, 34153, 323, 29839, 17937, 505, 220, 1032, 11, 2636, 5054, 8316, 2212, 279, 1917, 1990, 220, 4468, 24, 323, 220, 1049, 23, 11, 3235, 449, 61050, 323, 9499, 828, 13, 578, 2128, 1511, 1521, 828, 311, 11294, 1060, 4791, 4771, 65649, 323, 16430, 1268, 1790, 315, 279, 7692, 54709, 1436, 387, 30706, 311, 10182, 54709, 13, 10180, 220, 843, 311, 220, 2137, 3346, 315, 1060, 4791, 4771, 54709, 369, 279, 3116, 31665, 1436, 387, 11497, 555, 10182, 54709, 13, 1115, 374, 12190, 22416, 13890, 315, 220, 1313, 3610, 18767, 20181, 315, 93307, 11, 220, 18, 3610, 18767, 20181, 315, 20228, 11, 220, 24, 3610, 18767, 20181, 315, 34153, 11, 323, 220, 17, 3610, 18767, 20181, 315, 29839, 28440, 824, 1060, 11829, 7902, 1990, 10182, 323, 7692, 54709, 89075, 4315, 13918, 13, 31636, 54709, 11497, 1790, 315, 7692, 54709, 304, 1063, 315, 279, 1455, 27331, 13918, 11, 719, 3117, 2753, 304, 3428, 12303, 100092, 13918, 13, 330, 2028, 3445, 430, 2216, 27331, 5789, 17210, 311, 3691, 4868, 555, 3515, 264, 59985, 19641, 994, 279, 9282, 374, 37849, 719, 649, 387, 4295, 2216, 2653, 994, 279, 9282, 374, 3958, 323, 17210, 73152, 311, 3728, 3691, 74935, 1359, 2795, 13558, 13, 330, 1688, 279, 1023, 842, 315, 279, 20326, 11, 3428, 12303, 100092, 13918, 2873, 311, 387, 810, 59780, 311, 3958, 12, 15561, 1667, 719, 1541, 956, 1518, 2466, 20192, 994, 279, 9282, 374, 10728, 1210, 4427, 13918, 11, 1778, 439, 304, 5596, 315, 13936, 323, 10384, 11, 8710, 2697, 26670, 1990, 10182, 54709, 323, 7692, 54709, 13, 4497, 1109, 220, 1399, 3346, 315, 279, 7692, 54709, 649, 387, 11497, 555, 10182, 54709, 304, 13918, 430, 527, 3062, 24190, 315, 3682, 31665, 11, 2737, 279, 14013, 31382, 549, 815, 2637, 279, 4892, 5734, 63911, 11, 19001, 4606, 323, 6457, 35948, 13060, 439, 3728, 14370, 11, 279, 3135, 1501, 1405, 323, 1268, 1790, 10182, 54709, 15100, 7692, 54709, 13, 578, 3495, 2128, 374, 1457, 3411, 520, 13970, 7576, 311, 1518, 3508, 279, 54709, 71526, 311, 10182, 706, 5614, 927, 892, 17223, 422, 779, 11, 1148, 13878, 315, 10182, 527, 1455, 62623, 13, 330, 56, 823, 54709, 649, 387, 264, 2466, 3575, 505, 2225, 7100, 323, 3691, 8312, 2559, 7862, 1359, 13558, 1071, 13, 330, 791, 3135, 315, 420, 4007, 323, 1057, 1833, 5352, 990, 649, 387, 1511, 311, 7417, 3691, 1887, 20334, 2212, 279, 1917, 555, 25607, 4106, 19300, 315, 3691, 74935, 3432, 439, 1664, 439, 1884, 4461, 311, 387, 92541, 555, 10182, 2349, 304, 279, 3938, 1210, 220, 128257, 198 ]

1,851

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract A mass production route to single-atom catalysts (SACs) is crucial for their end use application. To date, the direct fabrication of SACs via a simple and economic manufacturing route remains a challenge, with current approaches relying on convoluted processes using expensive components. Here, a straightforward and cost-effective three-dimensional (3D) printing approach is developed to fabricate a library of SACs. Despite changing synthetic parameters, including centre transition metal atom, metal loading, coordination environment and spatial geometry, the products show similar atomic dispersion nature of single metal sites, demonstrating the generality of the approach. The 3D-printed SACs exhibited excellent activity and stability in the nitrate reduction reaction. It is expected that this 3D-printing technique can be used as a method for large-scale commercial production of SACs, thus enabling the use of these materials in a broad spectrum of industrial applications. Main Single-atom catalysts (SACs) are materials with isolated metal atoms as active sites, anchored by surrounding coordination species of solid supports 1 , 2 . Advantages include high atom economy and tunable coordination properties, giving potential for numerous applications 3 , 4 , 5 , 6 , 7 , 8 , 9 . Developing universal synthesis approaches to achieve scale production of SACs is a prerequisite for successful implementation of these catalysts in practical applications 1 . A simple and economic general synthesis approach for scale production of SACs is vital for downstream commercialization 1 , 10 , 11 . Currently, the chemical synthesis strategies of SACs can be divided into two major categories: ‘top-down’ and ‘bottom-up’ strategies 1 , 12 , 13 , 14 , 15 . A typical ‘top-down’ strategy includes the initial creation of defects on substrates and the subsequent anchoring of metal atoms to surface vacancies 13 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 . The ‘bottom-up’ strategy begins with the preparation of host materials, such as microporous crystalline frameworks or synthetic polymers. Afterwards, SACs can be achieved through the confinement of molecular complexes in hosts and subsequent post-integration process to remove the ligands of metal complexes 14 , 17 , 25 , 26 , 27 , 28 . However, both synthetic strategies require complex wet-chemistry processes, for example the complex defect-construction process or the sophisticated host-material preparation process, hindering scale production of SACs 16 , 29 , 30 , 31 , 32 , 33 , 34 . In addition, the presence of elaborate substrates and costly precursors (for example, complicated ligands or expensive artificial polymers) notably increases the overall cost of manufacturing SACs 1 , 35 . Apart from chemical synthesis strategies, the pathways of mechanochemical abrasion, thermal shockwave and laser irradiation can serve as versatile approaches to synthesize SACs 36 , 37 , 38 , 39 . But customized settings or specific equipment can be required for applying these approaches 36 . Therefore, a straightforward and cost-effective universal synthesis approach for scale production of SACs is desired but remains challenging 1 , 10 , 11 . Recently, three-dimensional (3D) printing techniques have been developed as unique manufacturing routes for mass production of targeted products. The use of 3D-printing has been considered a simple approach as it can directly fabricate target materials and avoid complex wet-chemistry processes 40 , 41 . In contrast to conventional subtractive manufacturing process, 3D-printing techniques work more economically by effectively eliminating the generation of waste materials during the manufacturing process 40 , 41 , 42 . Introduction of cheaper 3D-printing machines and an increasing number of commercially available printable materials offer easily accessible opportunities to substantially reduce the overall cost of final products 40 , 41 , 42 , 43 , 44 . Additionally, 3D-printing can automatically and efficiently construct materials with customized geometric designs from millimetres to beyond metre scale, paving a pathway for industrial-scale production 44 , 45 , 46 , 47 . However, despite the popularity of 3D-printing techniques, mainly in the biomedical field, its application in SAC production remains elusive. Herein, we report a universal 3D-printing synthesis approach to directly construct a library of SACs. By mixing the printing ink with transition metal precursors, a straightforward 3D-printing approach was developed to synthesize various SACs. Minimal alteration of the atomic dispersion was seen with synthetic variations on centre atoms, loadings of the centre atoms, coordination environments and spatial geometries, demonstrating the universality of this approach. The employment of natural polymers, including gelatin and gelatin methacryloyl (GelMA), as printing ink offers an accessible and affordable route 32 , 33 . Furthermore, the automatic and direct fabrication of centimetre-size SAC precursors avoids complicated wet-chemistry processes. These two merits of reduced costs and added convenience identify its great potential for mass production of SACs. In addition, as a proof-of-concept, the performance of 3D-printed SACs was evaluated by a nitrate reduction reaction, showcasing their potential application as electrocatalysts. Results and discussion Synthesis and structural characterization of Fe3DSAC As shown in Fig. 1a , several steps are involved in the 3D-printing approach. Initially, the hydrogel containing gelatin and GelMA was mixed with the corresponding transition metal precursors to formulate the printing ink. The 3D structure was directly and automatically constructed by the 3D-printing technique (a typical printing process is shown in the Supplementary Video 1 ). Afterwards, the as-printed sample was freeze-dried to remove residual water. Then, the 3D-printed SACs were achieved through the pyrolysis process of as-dried samples to anchor metal single atoms onto the gelatin/GelMA-derived carbon. To further elucidate the fabrication process, we take the synthesis of Fe 3D-printed SAC with a precursor hole size of 1.0 mm (denoted as Fe3DSAC or Fe3DSAC 1.0 mm) as an example. In this process, Fe(acac) 3 was employed as the Fe single-atom precursor. As shown in Fig. 1b , the 3D centimetre-size precursor was constructed via 3D-printing technique. Typical scanning electron microscopy (SEM) and the corresponding energy dispersive X-ray (EDX) images of the typical as-pyrolysis product with hole size of 2.0 mm, shown in Fig. 1c and Supplementary Fig. 1 ,", "role": "user" }, { "content": "A large international collaboration led by Prof Shizhang Qiao, an Australian Laureate Fellow at the University of Adelaide has developed a straightforward and cost-effective synthesizing approach using a 3D printing technique to produce single-atom catalysts (SACs)—potentially paving the way for large-scale commercial production with broad industrial applications. The research has been published in Nature Synthesis. The team mailed in samples to the Australian Synchrotron during the COVID lockdown for materials characterization using the X-ray absorption spectroscopy (XAS) beamline. A catalyst is a substance that is designed to drive a specific chemical reaction to convert chemicals to other, less harmful, valuable industrial products. The efficiency at which a given catalyst aids the reaction is often found to be determined by its surface area. For example, a bulk metallic cobalt foil may aid in chemical reductions, but the same number of cobalt atoms in the form of nanoparticles would be significantly more efficient given the greater surface area available for the reaction to take place. Taken to its extreme, single-atom catalysts (SACs) refer to individual metal atoms, not bonding to metal but often dispersed uniformly on a fixed substrate (such as carbon), offering the highest possible value of atom economy. The ideal atom economy, known as 100% atom economy, for a chemical reaction is a process in which all reactant atoms are found in the desired product. Synthesis procedure for 3D-printed SACs. Credit: Xie, F., Cui, X., Zhi, X. et al. A general approach to 3D-printed single-atom catalysts. Nat. Synth (2023) The isolated metal atoms have unique and novel physical and chemical properties, driving efficient and tailored catalytic reactions with extremely high catalytic activity. However, current production methods of wet-chemical processes, mechano-chemical abrasion, thermal shockwave, and laser irradiation are considered complex, costly and impractical for mass production. \"We have developed a synthesis approach that allows the use of 3D printing to fabricate single-atom catalysts. Our method has the potential to be more cost-effective and simpler than current approaches,\" explained Prof. Qiao. 3D printing allows the customization of geometric designs from millimeters to meters, which is important for industrial applications. The combination of 3D printing and single-atom catalysts provides a promising but simplified way to manufacture SACs at different scales. \"This novel combination has the potential to advance Australia's status as a global leader in tackling the effects of climate change and help us take the lead in new techniques to make chemicals that benefit society,\" said Prof. Qiao. Dr Bernt Johannessen at the X-ray absorption spectroscopy beamline at ANSTO's Australian Synchrotron. Credit: Australian Nuclear Science and Technology Organisation (ANSTO) Senior scientist Dr. Bernt Johannessen, also a co-author on the paper and long-time collaborator, carried out measurements on the XAS beamline for the research team across multiple beamtime allocations (and multiple COVID lockdowns). \"Pleasingly, we were able to confirm that the 3D printing technique had produced a material consisting of isolated single atom sites as opposed to nanoparticles or clusters of atoms. The instrument allows us to differentiate between cobalt bonding to light elements, like carbon, or cobalt bonding to other cobalt to form nanoparticles,\" confirmed by Dr. Johannessen. \"The larger clusters you have, the less effective they will be as single-atom catalysts, so the confirmation of the isolated nature of single-atom sites is crucial to the project conclusions and potential industrial applications. \"The XAS Beamline at ANSTO has been integral to a number of high-profile studies in this field over the past several years now, and we are looking forward to seeing how our user community continues to grow over the years ahead.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract A mass production route to single-atom catalysts (SACs) is crucial for their end use application. To date, the direct fabrication of SACs via a simple and economic manufacturing route remains a challenge, with current approaches relying on convoluted processes using expensive components. Here, a straightforward and cost-effective three-dimensional (3D) printing approach is developed to fabricate a library of SACs. Despite changing synthetic parameters, including centre transition metal atom, metal loading, coordination environment and spatial geometry, the products show similar atomic dispersion nature of single metal sites, demonstrating the generality of the approach. The 3D-printed SACs exhibited excellent activity and stability in the nitrate reduction reaction. It is expected that this 3D-printing technique can be used as a method for large-scale commercial production of SACs, thus enabling the use of these materials in a broad spectrum of industrial applications. Main Single-atom catalysts (SACs) are materials with isolated metal atoms as active sites, anchored by surrounding coordination species of solid supports 1 , 2 . Advantages include high atom economy and tunable coordination properties, giving potential for numerous applications 3 , 4 , 5 , 6 , 7 , 8 , 9 . Developing universal synthesis approaches to achieve scale production of SACs is a prerequisite for successful implementation of these catalysts in practical applications 1 . A simple and economic general synthesis approach for scale production of SACs is vital for downstream commercialization 1 , 10 , 11 . Currently, the chemical synthesis strategies of SACs can be divided into two major categories: ‘top-down’ and ‘bottom-up’ strategies 1 , 12 , 13 , 14 , 15 . A typical ‘top-down’ strategy includes the initial creation of defects on substrates and the subsequent anchoring of metal atoms to surface vacancies 13 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 . The ‘bottom-up’ strategy begins with the preparation of host materials, such as microporous crystalline frameworks or synthetic polymers. Afterwards, SACs can be achieved through the confinement of molecular complexes in hosts and subsequent post-integration process to remove the ligands of metal complexes 14 , 17 , 25 , 26 , 27 , 28 . However, both synthetic strategies require complex wet-chemistry processes, for example the complex defect-construction process or the sophisticated host-material preparation process, hindering scale production of SACs 16 , 29 , 30 , 31 , 32 , 33 , 34 . In addition, the presence of elaborate substrates and costly precursors (for example, complicated ligands or expensive artificial polymers) notably increases the overall cost of manufacturing SACs 1 , 35 . Apart from chemical synthesis strategies, the pathways of mechanochemical abrasion, thermal shockwave and laser irradiation can serve as versatile approaches to synthesize SACs 36 , 37 , 38 , 39 . But customized settings or specific equipment can be required for applying these approaches 36 . Therefore, a straightforward and cost-effective universal synthesis approach for scale production of SACs is desired but remains challenging 1 , 10 , 11 . Recently, three-dimensional (3D) printing techniques have been developed as unique manufacturing routes for mass production of targeted products. The use of 3D-printing has been considered a simple approach as it can directly fabricate target materials and avoid complex wet-chemistry processes 40 , 41 . In contrast to conventional subtractive manufacturing process, 3D-printing techniques work more economically by effectively eliminating the generation of waste materials during the manufacturing process 40 , 41 , 42 . Introduction of cheaper 3D-printing machines and an increasing number of commercially available printable materials offer easily accessible opportunities to substantially reduce the overall cost of final products 40 , 41 , 42 , 43 , 44 . Additionally, 3D-printing can automatically and efficiently construct materials with customized geometric designs from millimetres to beyond metre scale, paving a pathway for industrial-scale production 44 , 45 , 46 , 47 . However, despite the popularity of 3D-printing techniques, mainly in the biomedical field, its application in SAC production remains elusive. Herein, we report a universal 3D-printing synthesis approach to directly construct a library of SACs. By mixing the printing ink with transition metal precursors, a straightforward 3D-printing approach was developed to synthesize various SACs. Minimal alteration of the atomic dispersion was seen with synthetic variations on centre atoms, loadings of the centre atoms, coordination environments and spatial geometries, demonstrating the universality of this approach. The employment of natural polymers, including gelatin and gelatin methacryloyl (GelMA), as printing ink offers an accessible and affordable route 32 , 33 . Furthermore, the automatic and direct fabrication of centimetre-size SAC precursors avoids complicated wet-chemistry processes. These two merits of reduced costs and added convenience identify its great potential for mass production of SACs. In addition, as a proof-of-concept, the performance of 3D-printed SACs was evaluated by a nitrate reduction reaction, showcasing their potential application as electrocatalysts. Results and discussion Synthesis and structural characterization of Fe3DSAC As shown in Fig. 1a , several steps are involved in the 3D-printing approach. Initially, the hydrogel containing gelatin and GelMA was mixed with the corresponding transition metal precursors to formulate the printing ink. The 3D structure was directly and automatically constructed by the 3D-printing technique (a typical printing process is shown in the Supplementary Video 1 ). Afterwards, the as-printed sample was freeze-dried to remove residual water. Then, the 3D-printed SACs were achieved through the pyrolysis process of as-dried samples to anchor metal single atoms onto the gelatin/GelMA-derived carbon. To further elucidate the fabrication process, we take the synthesis of Fe 3D-printed SAC with a precursor hole size of 1.0 mm (denoted as Fe3DSAC or Fe3DSAC 1.0 mm) as an example. In this process, Fe(acac) 3 was employed as the Fe single-atom precursor. As shown in Fig. 1b , the 3D centimetre-size precursor was constructed via 3D-printing technique. Typical scanning electron microscopy (SEM) and the corresponding energy dispersive X-ray (EDX) images of the typical as-pyrolysis product with hole size of 2.0 mm, shown in Fig. 1c and Supplementary Fig. 1 ,<|im_end|> <|im_start|>assistant A large international collaboration led by Prof Shizhang Qiao, an Australian Laureate Fellow at the University of Adelaide has developed a straightforward and cost-effective synthesizing approach using a 3D printing technique to produce single-atom catalysts (SACs)—potentially paving the way for large-scale commercial production with broad industrial applications. The research has been published in Nature Synthesis. The team mailed in samples to the Australian Synchrotron during the COVID lockdown for materials characterization using the X-ray absorption spectroscopy (XAS) beamline. A catalyst is a substance that is designed to drive a specific chemical reaction to convert chemicals to other, less harmful, valuable industrial products. The efficiency at which a given catalyst aids the reaction is often found to be determined by its surface area. For example, a bulk metallic cobalt foil may aid in chemical reductions, but the same number of cobalt atoms in the form of nanoparticles would be significantly more efficient given the greater surface area available for the reaction to take place. Taken to its extreme, single-atom catalysts (SACs) refer to individual metal atoms, not bonding to metal but often dispersed uniformly on a fixed substrate (such as carbon), offering the highest possible value of atom economy. The ideal atom economy, known as 100% atom economy, for a chemical reaction is a process in which all reactant atoms are found in the desired product. Synthesis procedure for 3D-printed SACs. Credit: Xie, F., Cui, X., Zhi, X. et al. A general approach to 3D-printed single-atom catalysts. Nat. Synth (2023) The isolated metal atoms have unique and novel physical and chemical properties, driving efficient and tailored catalytic reactions with extremely high catalytic activity. However, current production methods of wet-chemical processes, mechano-chemical abrasion, thermal shockwave, and laser irradiation are considered complex, costly and impractical for mass production. "We have developed a synthesis approach that allows the use of 3D printing to fabricate single-atom catalysts. Our method has the potential to be more cost-effective and simpler than current approaches," explained Prof. Qiao. 3D printing allows the customization of geometric designs from millimeters to meters, which is important for industrial applications. The combination of 3D printing and single-atom catalysts provides a promising but simplified way to manufacture SACs at different scales. "This novel combination has the potential to advance Australia's status as a global leader in tackling the effects of climate change and help us take the lead in new techniques to make chemicals that benefit society," said Prof. Qiao. Dr Bernt Johannessen at the X-ray absorption spectroscopy beamline at ANSTO's Australian Synchrotron. Credit: Australian Nuclear Science and Technology Organisation (ANSTO) Senior scientist Dr. Bernt Johannessen, also a co-author on the paper and long-time collaborator, carried out measurements on the XAS beamline for the research team across multiple beamtime allocations (and multiple COVID lockdowns). "Pleasingly, we were able to confirm that the 3D printing technique had produced a material consisting of isolated single atom sites as opposed to nanoparticles or clusters of atoms. The instrument allows us to differentiate between cobalt bonding to light elements, like carbon, or cobalt bonding to other cobalt to form nanoparticles," confirmed by Dr. Johannessen. "The larger clusters you have, the less effective they will be as single-atom catalysts, so the confirmation of the isolated nature of single-atom sites is crucial to the project conclusions and potential industrial applications. "The XAS Beamline at ANSTO has been integral to a number of high-profile studies in this field over the past several years now, and we are looking forward to seeing how our user community continues to grow over the years ahead." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 362, 3148, 5788, 6149, 311, 3254, 12, 22612, 51483, 82, 320, 50, 1741, 82, 8, 374, 16996, 369, 872, 842, 1005, 3851, 13, 2057, 2457, 11, 279, 2167, 59251, 315, 91033, 82, 4669, 264, 4382, 323, 7100, 15266, 6149, 8625, 264, 8815, 11, 449, 1510, 20414, 39661, 389, 5804, 337, 2844, 11618, 1701, 11646, 6956, 13, 5810, 11, 264, 31439, 323, 2853, 53421, 2380, 33520, 320, 18, 35, 8, 18991, 5603, 374, 8040, 311, 13354, 349, 264, 6875, 315, 91033, 82, 13, 18185, 10223, 28367, 5137, 11, 2737, 12541, 9320, 9501, 19670, 11, 9501, 8441, 11, 38793, 4676, 323, 29079, 17484, 11, 279, 3956, 1501, 4528, 25524, 86712, 7138, 315, 3254, 9501, 6732, 11, 45296, 279, 1803, 2786, 315, 279, 5603, 13, 578, 220, 18, 35, 43245, 291, 91033, 82, 51713, 9250, 5820, 323, 20334, 304, 279, 25719, 7853, 14278, 13010, 13, 1102, 374, 3685, 430, 420, 220, 18, 35, 43245, 287, 15105, 649, 387, 1511, 439, 264, 1749, 369, 3544, 13230, 8518, 5788, 315, 91033, 82, 11, 8617, 28462, 279, 1005, 315, 1521, 7384, 304, 264, 7353, 20326, 315, 13076, 8522, 13, 4802, 11579, 12, 22612, 51483, 82, 320, 50, 1741, 82, 8, 527, 7384, 449, 25181, 9501, 33299, 439, 4642, 6732, 11, 78219, 555, 14932, 38793, 9606, 315, 6573, 11815, 220, 16, 1174, 220, 17, 662, 12605, 38886, 2997, 1579, 19670, 8752, 323, 11716, 481, 38793, 6012, 11, 7231, 4754, 369, 12387, 8522, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 1174, 220, 24, 662, 81745, 20789, 39975, 20414, 311, 11322, 5569, 5788, 315, 91033, 82, 374, 264, 80884, 369, 6992, 8292, 315, 1521, 51483, 82, 304, 15325, 8522, 220, 16, 662, 362, 4382, 323, 7100, 4689, 39975, 5603, 369, 5569, 5788, 315, 91033, 82, 374, 16595, 369, 52452, 8518, 2065, 220, 16, 1174, 220, 605, 1174, 220, 806, 662, 25122, 11, 279, 11742, 39975, 15174, 315, 91033, 82, 649, 387, 18255, 1139, 1403, 3682, 11306, 25, 3451, 3565, 15220, 529, 323, 3451, 15205, 5352, 529, 15174, 220, 16, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 662, 362, 14595, 3451, 3565, 15220, 529, 8446, 5764, 279, 2926, 9886, 315, 42655, 389, 16146, 988, 323, 279, 17876, 34330, 5620, 315, 9501, 33299, 311, 7479, 67751, 220, 1032, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 1174, 220, 972, 1174, 220, 777, 1174, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 662, 578, 3451, 15205, 5352, 529, 8446, 12302, 449, 279, 18459, 315, 3552, 7384, 11, 1778, 439, 19748, 897, 20857, 64568, 483, 49125, 477, 28367, 46033, 388, 13, 87640, 11, 91033, 82, 649, 387, 17427, 1555, 279, 66678, 315, 31206, 69125, 304, 18939, 323, 17876, 1772, 20653, 17831, 1920, 311, 4148, 279, 29413, 2914, 315, 9501, 69125, 220, 975, 1174, 220, 1114, 1174, 220, 914, 1174, 220, 1627, 1174, 220, 1544, 1174, 220, 1591, 662, 4452, 11, 2225, 28367, 15174, 1397, 6485, 14739, 12, 52755, 11618, 11, 369, 3187, 279, 6485, 23011, 15204, 3099, 1920, 477, 279, 27877, 3552, 68418, 18459, 1920, 11, 48419, 4776, 5569, 5788, 315, 91033, 82, 220, 845, 1174, 220, 1682, 1174, 220, 966, 1174, 220, 2148, 1174, 220, 843, 1174, 220, 1644, 1174, 220, 1958, 662, 763, 5369, 11, 279, 9546, 315, 37067, 16146, 988, 323, 34348, 5956, 34291, 320, 2000, 3187, 11, 17395, 29413, 2914, 477, 11646, 21075, 46033, 388, 8, 35146, 12992, 279, 8244, 2853, 315, 15266, 91033, 82, 220, 16, 1174, 220, 1758, 662, 35802, 505, 11742, 39975, 15174, 11, 279, 44014, 315, 84596, 5770, 32056, 59681, 290, 11, 29487, 10988, 31498, 323, 21120, 76327, 367, 649, 8854, 439, 33045, 20414, 311, 6925, 27985, 91033, 82, 220, 1927, 1174, 220, 1806, 1174, 220, 1987, 1174, 220, 2137, 662, 2030, 32789, 5110, 477, 3230, 7241, 649, 387, 2631, 369, 19486, 1521, 20414, 220, 1927, 662, 15636, 11, 264, 31439, 323, 2853, 53421, 20789, 39975, 5603, 369, 5569, 5788, 315, 91033, 82, 374, 12974, 719, 8625, 17436, 220, 16, 1174, 220, 605, 1174, 220, 806, 662, 42096, 11, 2380, 33520, 320, 18, 35, 8, 18991, 12823, 617, 1027, 8040, 439, 5016, 15266, 11543, 369, 3148, 5788, 315, 17550, 3956, 13, 578, 1005, 315, 220, 18, 35, 43245, 287, 706, 1027, 6646, 264, 4382, 5603, 439, 433, 649, 6089, 13354, 349, 2218, 7384, 323, 5766, 6485, 14739, 12, 52755, 11618, 220, 1272, 1174, 220, 3174, 662, 763, 13168, 311, 21349, 33356, 535, 15266, 1920, 11, 220, 18, 35, 43245, 287, 12823, 990, 810, 47379, 555, 13750, 40599, 279, 9659, 315, 12571, 7384, 2391, 279, 15266, 1920, 220, 1272, 1174, 220, 3174, 1174, 220, 2983, 662, 29438, 315, 23917, 220, 18, 35, 43245, 287, 12933, 323, 459, 7859, 1396, 315, 54453, 2561, 43095, 7384, 3085, 6847, 15987, 10708, 311, 32302, 8108, 279, 8244, 2853, 315, 1620, 3956, 220, 1272, 1174, 220, 3174, 1174, 220, 2983, 1174, 220, 3391, 1174, 220, 2096, 662, 23212, 11, 220, 18, 35, 43245, 287, 649, 9651, 323, 30820, 9429, 7384, 449, 32789, 53584, 14769, 505, 2606, 86366, 417, 311, 7953, 82673, 5569, 11, 82568, 264, 38970, 369, 13076, 13230, 5788, 220, 2096, 1174, 220, 1774, 1174, 220, 2790, 1174, 220, 2618, 662, 4452, 11, 8994, 279, 23354, 315, 220, 18, 35, 43245, 287, 12823, 11, 14918, 304, 279, 94612, 2115, 11, 1202, 3851, 304, 91033, 5788, 8625, 66684, 13, 5810, 258, 11, 584, 1934, 264, 20789, 220, 18, 35, 43245, 287, 39975, 5603, 311, 6089, 9429, 264, 6875, 315, 91033, 82, 13, 3296, 27890, 279, 18991, 27513, 449, 9320, 9501, 5956, 34291, 11, 264, 31439, 220, 18, 35, 43245, 287, 5603, 574, 8040, 311, 6925, 27985, 5370, 91033, 82, 13, 76212, 73681, 315, 279, 25524, 86712, 574, 3970, 449, 28367, 27339, 389, 12541, 33299, 11, 2865, 826, 315, 279, 12541, 33299, 11, 38793, 22484, 323, 29079, 69086, 4108, 11, 45296, 279, 11159, 2786, 315, 420, 5603, 13, 578, 14740, 315, 5933, 46033, 388, 11, 2737, 18316, 15111, 323, 18316, 15111, 21747, 582, 894, 2032, 75, 320, 38, 301, 4940, 705, 439, 18991, 27513, 6209, 459, 15987, 323, 17049, 6149, 220, 843, 1174, 220, 1644, 662, 24296, 11, 279, 17392, 323, 2167, 59251, 315, 2960, 318, 47987, 7321, 91033, 5956, 34291, 55952, 17395, 14739, 12, 52755, 11618, 13, 4314, 1403, 50932, 315, 11293, 7194, 323, 3779, 19679, 10765, 1202, 2294, 4754, 369, 3148, 5788, 315, 91033, 82, 13, 763, 5369, 11, 439, 264, 11311, 8838, 15204, 1512, 11, 279, 5178, 315, 220, 18, 35, 43245, 291, 91033, 82, 574, 26126, 555, 264, 25719, 7853, 14278, 13010, 11, 67908, 872, 4754, 3851, 439, 25396, 66, 4306, 99335, 13, 18591, 323, 10430, 24028, 13491, 323, 24693, 60993, 315, 3926, 18, 6061, 1741, 1666, 6982, 304, 23966, 13, 220, 16, 64, 1174, 3892, 7504, 527, 6532, 304, 279, 220, 18, 35, 43245, 287, 5603, 13, 59656, 11, 279, 17055, 29952, 8649, 18316, 15111, 323, 45482, 4940, 574, 9709, 449, 279, 12435, 9320, 9501, 5956, 34291, 311, 89959, 279, 18991, 27513, 13, 578, 220, 18, 35, 6070, 574, 6089, 323, 9651, 20968, 555, 279, 220, 18, 35, 43245, 287, 15105, 320, 64, 14595, 18991, 1920, 374, 6982, 304, 279, 99371, 8519, 220, 16, 7609, 87640, 11, 279, 439, 43245, 291, 6205, 574, 31030, 1773, 4588, 311, 4148, 33247, 3090, 13, 5112, 11, 279, 220, 18, 35, 43245, 291, 91033, 82, 1051, 17427, 1555, 279, 4611, 299, 398, 14744, 1920, 315, 439, 1773, 4588, 10688, 311, 17543, 9501, 3254, 33299, 8800, 279, 18316, 15111, 16169, 301, 4940, 72286, 12782, 13, 2057, 4726, 97298, 349, 279, 59251, 1920, 11, 584, 1935, 279, 39975, 315, 3926, 220, 18, 35, 43245, 291, 91033, 449, 264, 71261, 14512, 1404, 315, 220, 16, 13, 15, 9653, 320, 5294, 9437, 439, 3926, 18, 6061, 1741, 477, 3926, 18, 6061, 1741, 220, 16, 13, 15, 9653, 8, 439, 459, 3187, 13, 763, 420, 1920, 11, 3926, 49496, 582, 8, 220, 18, 574, 20011, 439, 279, 3926, 3254, 12, 22612, 71261, 13, 1666, 6982, 304, 23966, 13, 220, 16, 65, 1174, 279, 220, 18, 35, 2960, 318, 47987, 7321, 71261, 574, 20968, 4669, 220, 18, 35, 43245, 287, 15105, 13, 74025, 36201, 17130, 92914, 320, 84839, 8, 323, 279, 12435, 4907, 13262, 53453, 1630, 30630, 320, 1507, 55, 8, 5448, 315, 279, 14595, 439, 2320, 67910, 398, 14744, 2027, 449, 14512, 1404, 315, 220, 17, 13, 15, 9653, 11, 6982, 304, 23966, 13, 220, 16, 66, 323, 99371, 23966, 13, 220, 16, 1174, 128257, 198, 128256, 78191, 198, 32, 3544, 6625, 20632, 6197, 555, 8626, 1443, 450, 21313, 1229, 23332, 11, 459, 13673, 33767, 349, 37946, 520, 279, 3907, 315, 50301, 706, 8040, 264, 31439, 323, 2853, 53421, 52389, 4954, 5603, 1701, 264, 220, 18, 35, 18991, 15105, 311, 8356, 3254, 12, 22612, 51483, 82, 320, 50, 1741, 82, 68850, 19644, 31668, 82568, 279, 1648, 369, 3544, 13230, 8518, 5788, 449, 7353, 13076, 8522, 13, 578, 3495, 706, 1027, 4756, 304, 22037, 24028, 13491, 13, 578, 2128, 76310, 304, 10688, 311, 279, 13673, 24028, 331, 299, 35785, 2391, 279, 20562, 51235, 369, 7384, 60993, 1701, 279, 1630, 30630, 44225, 66425, 51856, 320, 55, 1950, 8, 24310, 1074, 13, 362, 51483, 374, 264, 20278, 430, 374, 6319, 311, 6678, 264, 3230, 11742, 13010, 311, 5625, 26333, 311, 1023, 11, 2753, 28856, 11, 15525, 13076, 3956, 13, 578, 15374, 520, 902, 264, 2728, 51483, 52797, 279, 13010, 374, 3629, 1766, 311, 387, 11075, 555, 1202, 7479, 3158, 13, 1789, 3187, 11, 264, 20155, 46258, 34928, 3223, 47499, 1253, 12576, 304, 11742, 47311, 11, 719, 279, 1890, 1396, 315, 34928, 3223, 33299, 304, 279, 1376, 315, 94753, 1053, 387, 12207, 810, 11297, 2728, 279, 7191, 7479, 3158, 2561, 369, 279, 13010, 311, 1935, 2035, 13, 57074, 311, 1202, 14560, 11, 3254, 12, 22612, 51483, 82, 320, 50, 1741, 82, 8, 8464, 311, 3927, 9501, 33299, 11, 539, 64186, 311, 9501, 719, 3629, 77810, 78909, 389, 264, 8521, 54057, 320, 21470, 439, 12782, 705, 10209, 279, 8592, 3284, 907, 315, 19670, 8752, 13, 578, 10728, 19670, 8752, 11, 3967, 439, 220, 1041, 4, 19670, 8752, 11, 369, 264, 11742, 13010, 374, 264, 1920, 304, 902, 682, 14085, 519, 33299, 527, 1766, 304, 279, 12974, 2027, 13, 24028, 13491, 10537, 369, 220, 18, 35, 43245, 291, 91033, 82, 13, 16666, 25, 1630, 648, 11, 435, 2637, 356, 2005, 11, 1630, 2637, 1901, 6151, 11, 1630, 13, 1880, 453, 13, 362, 4689, 5603, 311, 220, 18, 35, 43245, 291, 3254, 12, 22612, 51483, 82, 13, 24772, 13, 24028, 339, 320, 2366, 18, 8, 578, 25181, 9501, 33299, 617, 5016, 323, 11775, 7106, 323, 11742, 6012, 11, 10043, 11297, 323, 41891, 34454, 70504, 25481, 449, 9193, 1579, 34454, 70504, 5820, 13, 4452, 11, 1510, 5788, 5528, 315, 14739, 12, 32056, 11618, 11, 84596, 5770, 12, 32056, 59681, 290, 11, 29487, 10988, 31498, 11, 323, 21120, 76327, 367, 527, 6646, 6485, 11, 34348, 323, 23356, 37119, 369, 3148, 5788, 13, 330, 1687, 617, 8040, 264, 39975, 5603, 430, 6276, 279, 1005, 315, 220, 18, 35, 18991, 311, 13354, 349, 3254, 12, 22612, 51483, 82, 13, 5751, 1749, 706, 279, 4754, 311, 387, 810, 2853, 53421, 323, 35388, 1109, 1510, 20414, 1359, 11497, 8626, 13, 1229, 23332, 13, 220, 18, 35, 18991, 6276, 279, 49141, 315, 53584, 14769, 505, 2606, 55336, 311, 20645, 11, 902, 374, 3062, 369, 13076, 8522, 13, 578, 10824, 315, 220, 18, 35, 18991, 323, 3254, 12, 22612, 51483, 82, 5825, 264, 26455, 719, 44899, 1648, 311, 30847, 91033, 82, 520, 2204, 29505, 13, 330, 2028, 11775, 10824, 706, 279, 4754, 311, 12178, 8494, 596, 2704, 439, 264, 3728, 7808, 304, 57911, 279, 6372, 315, 10182, 2349, 323, 1520, 603, 1935, 279, 3063, 304, 502, 12823, 311, 1304, 26333, 430, 8935, 8396, 1359, 1071, 8626, 13, 1229, 23332, 13, 2999, 9084, 406, 88964, 39909, 520, 279, 1630, 30630, 44225, 66425, 51856, 24310, 1074, 520, 2147, 790, 46, 596, 13673, 24028, 331, 299, 35785, 13, 16666, 25, 13673, 38544, 10170, 323, 12053, 47843, 320, 1111, 790, 46, 8, 19903, 28568, 2999, 13, 9084, 406, 88964, 39909, 11, 1101, 264, 1080, 43802, 389, 279, 5684, 323, 1317, 7394, 11430, 859, 11, 11953, 704, 22323, 389, 279, 1630, 1950, 24310, 1074, 369, 279, 3495, 2128, 4028, 5361, 24310, 1712, 70742, 320, 438, 5361, 20562, 51235, 82, 570, 330, 47, 84652, 398, 11, 584, 1051, 3025, 311, 7838, 430, 279, 220, 18, 35, 18991, 15105, 1047, 9124, 264, 3769, 31706, 315, 25181, 3254, 19670, 6732, 439, 16475, 311, 94753, 477, 28066, 315, 33299, 13, 578, 14473, 6276, 603, 311, 54263, 1990, 34928, 3223, 64186, 311, 3177, 5540, 11, 1093, 12782, 11, 477, 34928, 3223, 64186, 311, 1023, 34928, 3223, 311, 1376, 94753, 1359, 11007, 555, 2999, 13, 88964, 39909, 13, 330, 791, 8294, 28066, 499, 617, 11, 279, 2753, 7524, 814, 690, 387, 439, 3254, 12, 22612, 51483, 82, 11, 779, 279, 20109, 315, 279, 25181, 7138, 315, 3254, 12, 22612, 6732, 374, 16996, 311, 279, 2447, 31342, 323, 4754, 13076, 8522, 13, 330, 791, 1630, 1950, 51230, 1074, 520, 2147, 790, 46, 706, 1027, 26154, 311, 264, 1396, 315, 1579, 25171, 7978, 304, 420, 2115, 927, 279, 3347, 3892, 1667, 1457, 11, 323, 584, 527, 3411, 4741, 311, 9298, 1268, 1057, 1217, 4029, 9731, 311, 3139, 927, 279, 1667, 8469, 1210, 220, 128257, 198 ]

2,237

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Computer-aided drug discovery has been around for decades, although the past few years have seen a tectonic shift towards embracing computational technologies in both academia and pharma. This shift is largely defined by the flood of data on ligand properties and binding to therapeutic targets and their 3D structures, abundant computing capacities and the advent of on-demand virtual libraries of drug-like small molecules in their billions. Taking full advantage of these resources requires fast computational methods for effective ligand screening. This includes structure-based virtual screening of gigascale chemical spaces, further facilitated by fast iterative screening approaches. Highly synergistic are developments in deep learning predictions of ligand properties and target activities in lieu of receptor structure. Here we review recent advances in ligand discovery technologies, their potential for reshaping the whole process of drug discovery and development, as well as the challenges they encounter. We also discuss how the rapid identification of highly diverse, potent, target-selective and drug-like ligands to protein targets can democratize the drug discovery process, presenting new opportunities for the cost-effective development of safer and more effective small-molecule treatments. Main Despite amazing progress in basic life sciences and biotechnology, drug discovery and development (DDD) remain slow and expensive, taking on average approximately 15 years and approximately US$2 billion to make a small-molecule drug 1 . Although it is accepted that clinical studies are the priciest part of the development of each drug, most time-saving and cost-saving opportunities reside in the earlier discovery and preclinical stages. Preclinical efforts themselves account for more than 43% of expenses in pharma, in addition to major public funding 1 , driven by the high attrition rate at every step from target selection to hit identification and lead optimization to the selection of clinical candidates. Moreover, the high failure rate in clinical trials (currently 90%) 2 is largely explained by issues rooted in early discovery such as inadequate target validation or suboptimal ligand properties. Finding fast and accessible ways to discover more diverse pools of higher-quality chemical probes, hits and leads with optimal absorption, distribution, metabolism, excretion and toxicology (ADMET) and pharmacokinetics (PK) profiles at the early stages of DDD would improve outcomes in preclinical and clinical studies and facilitate more effective, accessible and safer drugs. The concept of computer-aided drug discovery 3 was developed in the 1970s and popularized by Fortune magazine in 1981, and has since been through several cycles of hype and disillusionment 4 . There have been success stories along the way 5 and, in general, computer-assisted approaches have become an integral, yet modest, part of the drug discovery process 6 , 7 . In the past few years, however, several scientific and technological breakthroughs resulted in a tectonic shift towards embracing computational approaches as a key driving force for drug discovery in both academia and industry. Pharmaceutical and biotech companies are expanding their computational drug discovery efforts or hiring their first computational chemists. Numerous new and established drug discovery companies have raised billions in the past few years with business models that heavily rely on a combination of advanced physics-based molecular modelling with deep learning (DL) and artificial intelligence (AI) 8 . Although it is too early yet to expect approved drugs from the most recent computationally driven discovery efforts, they are producing a growing number of clinical candidates, with some campaigns specifically claiming target-to-lead times as low as 1–2 months 9 , 10 , or target-to-clinic time under 1 year 11 . Are these the signs of a major shift in the role that computational approaches have in drug discovery or just another round of the hype cycle? Let us look at the key factors defining the recent changes (Fig. 1 ). First, the structural revolution—from automation in crystallography 12 to microcrystallography 13 , 14 and most recently cryo-electron microscopy technology 15 , 16 —has made it possible to reveal 3D structures for the majority of clinically relevant targets, often in a state or molecular complex relevant to its biological function. Especially impressive has been the recent structural turnaround for G protein-coupled receptors (GPCRs) 17 and other membrane proteins that mediate the action of more than 50% of drugs 18 , providing 3D templates for ligand screening and lead optimization. The second factor is a rapid and marked expansion of drug-like chemical space, easily accessible for hit and lead discovery. Just a few years ago, this space was limited to several million on-shelf compounds from vendors and in-house screening libraries in pharma. Now, screening can be done with ultra-large virtual libraries and chemical spaces of drug-like compounds, which can be readily made on-demand, rapidly growing beyond billions of compounds 19 , and even larger generative spaces with theoretically predicted synthesizability (Box 1 ). The third factor involves emerging computational approaches that strive to take full advantage of the abundance of 3D structures and ligand data, supported by the broad availability of cloud and graphics processing unit (GPU) computing resources to support these methods at scale. This includes structure-based virtual screening of ultra-large libraries 20 , 21 , 22 , using accelerated 23 , 24 , 25 and modular 26 screening approaches, as well as recent growth of data-driven machine learning (ML) and DL methods for predicting ADMET and PK properties and activities 27 . Fig. 1: Key factors driving VLS technology breakthroughs for generation of high-quality hits and leads. a , More than 200,000 protein structures in the PDB, plus private collections, have more than 90% of protein families covered with high-resolution X-ray and more recently cryo-electron microscopy structures, often in distinct functional states, with remaining gaps also filled by homology or AlphaFold2 models. b , The chemical space available for screening and fast synthesis has grown from about 10 7 on-shelf compounds in 2015 to more than 3 × 10 10 on-demand compounds in 2022, and can be rapidly expanded beyond 10 15 diverse and novel compounds. c , Computational methods for VLS include advances in fast flexible docking, modular fragment-based algorithms, DL models and hybrid", "role": "user" }, { "content": "Artificial intelligence can generate poems and essays, create responsive game characters, analyze vast amounts of data and detect patterns that the human eye might miss. Imagine what AI could do for drug discovery, traditionally a time-consuming, expensive process from the bench to the bedside. Experts see great promise in a complementary approach using AI and structure-based drug discovery, a computational method that relies on knowledge of 3D structures of biological targets. We recently caught up with Vsevolod \"Seva\" Katritch, associate professor of quantitative and computational biology and chemistry at the USC Dornsife College of Letters, Arts and Sciences and the USC Michelson Center for Convergent Bioscience. Katritch is the co-director of the Center for New Technologies in Drug Discovery and Development (CNT3D) at the USC Michelson Center and the lead author of a new review paper published in Nature. The paper, co-authored by USC research scientist Anastasiia Sadybekov, describes how computational approaches will streamline drug discovery. We're on the cusp of major advances in drug discovery. What brings us to this moment? There has been a seismic shift in computational drug discovery in the last few years: an explosion of data availability on clinically relevant, human-protein structures—and molecules that bind them, enormous chemical libraries of drug-like molecules, almost unlimited computing power and new, more efficient computational methods. The newest excitement is about AI-based drug discovery, but what's even more powerful is a combination of AI and structure-based drug discovery, with both approaches synergistically complementing each other. How has drug discovery been done in the past? Traditional drug discovery is mostly a trial-and-error venture. It's slow and expensive, taking an average of 15 years and $2 billion. There's a high attrition rate at every step, from target selection to lead optimization. The most opportunities for time and cost savings reside in the earlier discovery and preclinical stages. What takes place in the early stage? Let's use a lock-and-key analogy. The target receptor is the lock, and the drug that blocks or activates this receptor is a key for this lock. (Of course, the caveat is that in biology nothing is black or white, so some of the working keys switch the lock better than others, and lock is a bit malleable too.) Here's an example. Lipitor, the bestselling drug of all time, targets an enzyme involved in the synthesis of cholesterol in the liver. A receptor on the enzyme is the lock. Lipitor is the key, fitting into the lock and blocking the activity of the enzyme, triggering a series of events that decrease blood levels of bad cholesterol. Now, computational approaches allow us to digitally model many billions and even trillions of virtual keys and predict which ones are likely to be good keys. Only a few dozen of the best candidate keys are chemically synthesized and tested. This sounds much more efficient If the model is good, this process yields better results than traditional trial-and-error testing of millions of random keys. This reduces the physical requirements for synthesis of compounds and testing them more than thousandsfold, while often arriving at better results, as demonstrated by our work and work of many other groups working in this field. Can you explain the difference between the two main computational approaches, structure-based and AI-based? Following the lock-and-key analogy, the structure-based approach takes advantage of our detailed understanding of the lock's structure. If the 3D, physical structure of the lock is known, we can use virtual methods to predict the structure of a key that matches the lock. The machine learning, or AI-based approach, works best when many keys are already known for our target lock or other similar locks. AI can then analyze this mixture of similar locks and keys and predict the keys that are most likely to fit our target. It does not need exact knowledge of the lock structure, but it needs a large collection of relevant keys. Thus, the structure-based and AI-based approaches are applicable in different cases and complement each other. Are there any computational limits to this process? When testing billions and trillions of virtual compounds on cloud computers, computational costs themselves can become a bottleneck. A modular, giga-scale screening technology allows us to speed up and reduce cost dramatically by virtually predicting good parts of the key, combine them together, sort of building the key from several parts. For a 10 billion-compound library, this drops the computational costs from millions of dollars to hundreds, and it allows further scale-ups to trillions of compounds. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Computer-aided drug discovery has been around for decades, although the past few years have seen a tectonic shift towards embracing computational technologies in both academia and pharma. This shift is largely defined by the flood of data on ligand properties and binding to therapeutic targets and their 3D structures, abundant computing capacities and the advent of on-demand virtual libraries of drug-like small molecules in their billions. Taking full advantage of these resources requires fast computational methods for effective ligand screening. This includes structure-based virtual screening of gigascale chemical spaces, further facilitated by fast iterative screening approaches. Highly synergistic are developments in deep learning predictions of ligand properties and target activities in lieu of receptor structure. Here we review recent advances in ligand discovery technologies, their potential for reshaping the whole process of drug discovery and development, as well as the challenges they encounter. We also discuss how the rapid identification of highly diverse, potent, target-selective and drug-like ligands to protein targets can democratize the drug discovery process, presenting new opportunities for the cost-effective development of safer and more effective small-molecule treatments. Main Despite amazing progress in basic life sciences and biotechnology, drug discovery and development (DDD) remain slow and expensive, taking on average approximately 15 years and approximately US$2 billion to make a small-molecule drug 1 . Although it is accepted that clinical studies are the priciest part of the development of each drug, most time-saving and cost-saving opportunities reside in the earlier discovery and preclinical stages. Preclinical efforts themselves account for more than 43% of expenses in pharma, in addition to major public funding 1 , driven by the high attrition rate at every step from target selection to hit identification and lead optimization to the selection of clinical candidates. Moreover, the high failure rate in clinical trials (currently 90%) 2 is largely explained by issues rooted in early discovery such as inadequate target validation or suboptimal ligand properties. Finding fast and accessible ways to discover more diverse pools of higher-quality chemical probes, hits and leads with optimal absorption, distribution, metabolism, excretion and toxicology (ADMET) and pharmacokinetics (PK) profiles at the early stages of DDD would improve outcomes in preclinical and clinical studies and facilitate more effective, accessible and safer drugs. The concept of computer-aided drug discovery 3 was developed in the 1970s and popularized by Fortune magazine in 1981, and has since been through several cycles of hype and disillusionment 4 . There have been success stories along the way 5 and, in general, computer-assisted approaches have become an integral, yet modest, part of the drug discovery process 6 , 7 . In the past few years, however, several scientific and technological breakthroughs resulted in a tectonic shift towards embracing computational approaches as a key driving force for drug discovery in both academia and industry. Pharmaceutical and biotech companies are expanding their computational drug discovery efforts or hiring their first computational chemists. Numerous new and established drug discovery companies have raised billions in the past few years with business models that heavily rely on a combination of advanced physics-based molecular modelling with deep learning (DL) and artificial intelligence (AI) 8 . Although it is too early yet to expect approved drugs from the most recent computationally driven discovery efforts, they are producing a growing number of clinical candidates, with some campaigns specifically claiming target-to-lead times as low as 1–2 months 9 , 10 , or target-to-clinic time under 1 year 11 . Are these the signs of a major shift in the role that computational approaches have in drug discovery or just another round of the hype cycle? Let us look at the key factors defining the recent changes (Fig. 1 ). First, the structural revolution—from automation in crystallography 12 to microcrystallography 13 , 14 and most recently cryo-electron microscopy technology 15 , 16 —has made it possible to reveal 3D structures for the majority of clinically relevant targets, often in a state or molecular complex relevant to its biological function. Especially impressive has been the recent structural turnaround for G protein-coupled receptors (GPCRs) 17 and other membrane proteins that mediate the action of more than 50% of drugs 18 , providing 3D templates for ligand screening and lead optimization. The second factor is a rapid and marked expansion of drug-like chemical space, easily accessible for hit and lead discovery. Just a few years ago, this space was limited to several million on-shelf compounds from vendors and in-house screening libraries in pharma. Now, screening can be done with ultra-large virtual libraries and chemical spaces of drug-like compounds, which can be readily made on-demand, rapidly growing beyond billions of compounds 19 , and even larger generative spaces with theoretically predicted synthesizability (Box 1 ). The third factor involves emerging computational approaches that strive to take full advantage of the abundance of 3D structures and ligand data, supported by the broad availability of cloud and graphics processing unit (GPU) computing resources to support these methods at scale. This includes structure-based virtual screening of ultra-large libraries 20 , 21 , 22 , using accelerated 23 , 24 , 25 and modular 26 screening approaches, as well as recent growth of data-driven machine learning (ML) and DL methods for predicting ADMET and PK properties and activities 27 . Fig. 1: Key factors driving VLS technology breakthroughs for generation of high-quality hits and leads. a , More than 200,000 protein structures in the PDB, plus private collections, have more than 90% of protein families covered with high-resolution X-ray and more recently cryo-electron microscopy structures, often in distinct functional states, with remaining gaps also filled by homology or AlphaFold2 models. b , The chemical space available for screening and fast synthesis has grown from about 10 7 on-shelf compounds in 2015 to more than 3 × 10 10 on-demand compounds in 2022, and can be rapidly expanded beyond 10 15 diverse and novel compounds. c , Computational methods for VLS include advances in fast flexible docking, modular fragment-based algorithms, DL models and hybrid<|im_end|> <|im_start|>assistant Artificial intelligence can generate poems and essays, create responsive game characters, analyze vast amounts of data and detect patterns that the human eye might miss. Imagine what AI could do for drug discovery, traditionally a time-consuming, expensive process from the bench to the bedside. Experts see great promise in a complementary approach using AI and structure-based drug discovery, a computational method that relies on knowledge of 3D structures of biological targets. We recently caught up with Vsevolod "Seva" Katritch, associate professor of quantitative and computational biology and chemistry at the USC Dornsife College of Letters, Arts and Sciences and the USC Michelson Center for Convergent Bioscience. Katritch is the co-director of the Center for New Technologies in Drug Discovery and Development (CNT3D) at the USC Michelson Center and the lead author of a new review paper published in Nature. The paper, co-authored by USC research scientist Anastasiia Sadybekov, describes how computational approaches will streamline drug discovery. We're on the cusp of major advances in drug discovery. What brings us to this moment? There has been a seismic shift in computational drug discovery in the last few years: an explosion of data availability on clinically relevant, human-protein structures—and molecules that bind them, enormous chemical libraries of drug-like molecules, almost unlimited computing power and new, more efficient computational methods. The newest excitement is about AI-based drug discovery, but what's even more powerful is a combination of AI and structure-based drug discovery, with both approaches synergistically complementing each other. How has drug discovery been done in the past? Traditional drug discovery is mostly a trial-and-error venture. It's slow and expensive, taking an average of 15 years and $2 billion. There's a high attrition rate at every step, from target selection to lead optimization. The most opportunities for time and cost savings reside in the earlier discovery and preclinical stages. What takes place in the early stage? Let's use a lock-and-key analogy. The target receptor is the lock, and the drug that blocks or activates this receptor is a key for this lock. (Of course, the caveat is that in biology nothing is black or white, so some of the working keys switch the lock better than others, and lock is a bit malleable too.) Here's an example. Lipitor, the bestselling drug of all time, targets an enzyme involved in the synthesis of cholesterol in the liver. A receptor on the enzyme is the lock. Lipitor is the key, fitting into the lock and blocking the activity of the enzyme, triggering a series of events that decrease blood levels of bad cholesterol. Now, computational approaches allow us to digitally model many billions and even trillions of virtual keys and predict which ones are likely to be good keys. Only a few dozen of the best candidate keys are chemically synthesized and tested. This sounds much more efficient If the model is good, this process yields better results than traditional trial-and-error testing of millions of random keys. This reduces the physical requirements for synthesis of compounds and testing them more than thousandsfold, while often arriving at better results, as demonstrated by our work and work of many other groups working in this field. Can you explain the difference between the two main computational approaches, structure-based and AI-based? Following the lock-and-key analogy, the structure-based approach takes advantage of our detailed understanding of the lock's structure. If the 3D, physical structure of the lock is known, we can use virtual methods to predict the structure of a key that matches the lock. The machine learning, or AI-based approach, works best when many keys are already known for our target lock or other similar locks. AI can then analyze this mixture of similar locks and keys and predict the keys that are most likely to fit our target. It does not need exact knowledge of the lock structure, but it needs a large collection of relevant keys. Thus, the structure-based and AI-based approaches are applicable in different cases and complement each other. Are there any computational limits to this process? When testing billions and trillions of virtual compounds on cloud computers, computational costs themselves can become a bottleneck. A modular, giga-scale screening technology allows us to speed up and reduce cost dramatically by virtually predicting good parts of the key, combine them together, sort of building the key from several parts. For a 10 billion-compound library, this drops the computational costs from millions of dollars to hundreds, and it allows further scale-ups to trillions of compounds. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 17863, 12, 3864, 291, 5623, 18841, 706, 1027, 2212, 369, 11026, 11, 8051, 279, 3347, 2478, 1667, 617, 3970, 264, 259, 440, 14338, 6541, 7119, 56501, 55580, 14645, 304, 2225, 67671, 323, 1343, 20306, 13, 1115, 6541, 374, 14090, 4613, 555, 279, 18197, 315, 828, 389, 29413, 438, 6012, 323, 11212, 311, 37471, 11811, 323, 872, 220, 18, 35, 14726, 11, 44611, 25213, 59539, 323, 279, 11599, 315, 389, 57364, 4200, 20797, 315, 5623, 12970, 2678, 35715, 304, 872, 33151, 13, 36925, 2539, 9610, 315, 1521, 5070, 7612, 5043, 55580, 5528, 369, 7524, 29413, 438, 23061, 13, 1115, 5764, 6070, 6108, 4200, 23061, 315, 23401, 300, 2296, 11742, 12908, 11, 4726, 72849, 555, 5043, 87975, 23061, 20414, 13, 53485, 80526, 4633, 527, 26006, 304, 5655, 6975, 20492, 315, 29413, 438, 6012, 323, 2218, 7640, 304, 39381, 315, 35268, 6070, 13, 5810, 584, 3477, 3293, 31003, 304, 29413, 438, 18841, 14645, 11, 872, 4754, 369, 64793, 14550, 279, 4459, 1920, 315, 5623, 18841, 323, 4500, 11, 439, 1664, 439, 279, 11774, 814, 13123, 13, 1226, 1101, 4358, 1268, 279, 11295, 22654, 315, 7701, 17226, 11, 36875, 11, 2218, 21090, 535, 323, 5623, 12970, 29413, 2914, 311, 13128, 11811, 649, 97167, 553, 279, 5623, 18841, 1920, 11, 32644, 502, 10708, 369, 279, 2853, 53421, 4500, 315, 30549, 323, 810, 7524, 2678, 1474, 55269, 22972, 13, 4802, 18185, 8056, 5208, 304, 6913, 2324, 36788, 323, 6160, 52536, 11, 5623, 18841, 323, 4500, 320, 92461, 8, 7293, 6435, 323, 11646, 11, 4737, 389, 5578, 13489, 220, 868, 1667, 323, 13489, 2326, 3, 17, 7239, 311, 1304, 264, 2678, 1474, 55269, 5623, 220, 16, 662, 10541, 433, 374, 11928, 430, 14830, 7978, 527, 279, 550, 3457, 478, 961, 315, 279, 4500, 315, 1855, 5623, 11, 1455, 892, 59085, 323, 2853, 59085, 10708, 48383, 304, 279, 6931, 18841, 323, 864, 91899, 18094, 13, 5075, 91899, 9045, 5694, 2759, 369, 810, 1109, 220, 3391, 4, 315, 18512, 304, 1343, 20306, 11, 304, 5369, 311, 3682, 586, 11006, 220, 16, 1174, 16625, 555, 279, 1579, 6510, 684, 4478, 520, 1475, 3094, 505, 2218, 6727, 311, 4295, 22654, 323, 3063, 26329, 311, 279, 6727, 315, 14830, 11426, 13, 23674, 11, 279, 1579, 8060, 4478, 304, 14830, 19622, 320, 59302, 220, 1954, 11587, 220, 17, 374, 14090, 11497, 555, 4819, 41976, 304, 4216, 18841, 1778, 439, 46579, 2218, 10741, 477, 1207, 2985, 2931, 29413, 438, 6012, 13, 43897, 5043, 323, 15987, 5627, 311, 7142, 810, 17226, 34239, 315, 5190, 22867, 11742, 63610, 11, 13280, 323, 11767, 449, 23669, 44225, 11, 8141, 11, 39097, 11, 506, 89790, 323, 21503, 2508, 320, 1846, 45975, 8, 323, 36449, 79117, 25265, 320, 23037, 8, 21542, 520, 279, 4216, 18094, 315, 423, 4195, 1053, 7417, 20124, 304, 864, 91899, 323, 14830, 7978, 323, 28696, 810, 7524, 11, 15987, 323, 30549, 11217, 13, 578, 7434, 315, 6500, 12, 3864, 291, 5623, 18841, 220, 18, 574, 8040, 304, 279, 220, 4468, 15, 82, 323, 5526, 1534, 555, 46331, 14756, 304, 220, 3753, 16, 11, 323, 706, 2533, 1027, 1555, 3892, 25492, 315, 45990, 323, 98009, 479, 220, 19, 662, 2684, 617, 1027, 2450, 7493, 3235, 279, 1648, 220, 20, 323, 11, 304, 4689, 11, 6500, 35915, 13539, 20414, 617, 3719, 459, 26154, 11, 3686, 27946, 11, 961, 315, 279, 5623, 18841, 1920, 220, 21, 1174, 220, 22, 662, 763, 279, 3347, 2478, 1667, 11, 4869, 11, 3892, 12624, 323, 30116, 42445, 82, 19543, 304, 264, 259, 440, 14338, 6541, 7119, 56501, 55580, 20414, 439, 264, 1401, 10043, 5457, 369, 5623, 18841, 304, 2225, 67671, 323, 5064, 13, 59373, 323, 6160, 59196, 5220, 527, 24050, 872, 55580, 5623, 18841, 9045, 477, 24009, 872, 1176, 55580, 8590, 1705, 13, 86915, 502, 323, 9749, 5623, 18841, 5220, 617, 9408, 33151, 304, 279, 3347, 2478, 1667, 449, 2626, 4211, 430, 17345, 17631, 389, 264, 10824, 315, 11084, 22027, 6108, 31206, 61966, 449, 5655, 6975, 320, 16931, 8, 323, 21075, 11478, 320, 15836, 8, 220, 23, 662, 10541, 433, 374, 2288, 4216, 3686, 311, 1755, 12054, 11217, 505, 279, 1455, 3293, 3801, 30154, 16625, 18841, 9045, 11, 814, 527, 17843, 264, 7982, 1396, 315, 14830, 11426, 11, 449, 1063, 21343, 11951, 21039, 2218, 4791, 12, 27152, 3115, 439, 3428, 439, 220, 16, 4235, 17, 4038, 220, 24, 1174, 220, 605, 1174, 477, 2218, 4791, 31717, 93435, 892, 1234, 220, 16, 1060, 220, 806, 662, 8886, 1521, 279, 12195, 315, 264, 3682, 6541, 304, 279, 3560, 430, 55580, 20414, 617, 304, 5623, 18841, 477, 1120, 2500, 4883, 315, 279, 45990, 11008, 30, 6914, 603, 1427, 520, 279, 1401, 9547, 27409, 279, 3293, 4442, 320, 30035, 13, 220, 16, 7609, 5629, 11, 279, 24693, 14110, 88958, 33762, 304, 26110, 848, 1976, 88, 220, 717, 311, 8162, 5192, 14272, 848, 1976, 88, 220, 1032, 1174, 220, 975, 323, 1455, 6051, 16106, 78, 37081, 2298, 92914, 5557, 220, 868, 1174, 220, 845, 2001, 4752, 1903, 433, 3284, 311, 16805, 220, 18, 35, 14726, 369, 279, 8857, 315, 70432, 9959, 11811, 11, 3629, 304, 264, 1614, 477, 31206, 6485, 9959, 311, 1202, 24156, 734, 13, 36625, 16358, 706, 1027, 279, 3293, 24693, 67610, 369, 480, 13128, 1824, 283, 50185, 44540, 320, 70341, 43427, 8, 220, 1114, 323, 1023, 39654, 28896, 430, 1812, 6629, 279, 1957, 315, 810, 1109, 220, 1135, 4, 315, 11217, 220, 972, 1174, 8405, 220, 18, 35, 20506, 369, 29413, 438, 23061, 323, 3063, 26329, 13, 578, 2132, 8331, 374, 264, 11295, 323, 13160, 14800, 315, 5623, 12970, 11742, 3634, 11, 6847, 15987, 369, 4295, 323, 3063, 18841, 13, 4702, 264, 2478, 1667, 4227, 11, 420, 3634, 574, 7347, 311, 3892, 3610, 389, 7666, 491, 32246, 505, 29629, 323, 304, 37002, 23061, 20797, 304, 1343, 20306, 13, 4800, 11, 23061, 649, 387, 2884, 449, 24955, 40248, 4200, 20797, 323, 11742, 12908, 315, 5623, 12970, 32246, 11, 902, 649, 387, 31368, 1903, 389, 57364, 11, 19019, 7982, 7953, 33151, 315, 32246, 220, 777, 1174, 323, 1524, 8294, 1803, 1413, 12908, 449, 63234, 19698, 52389, 450, 2968, 320, 1642, 220, 16, 7609, 578, 4948, 8331, 18065, 24084, 55580, 20414, 430, 37106, 311, 1935, 2539, 9610, 315, 279, 37492, 315, 220, 18, 35, 14726, 323, 29413, 438, 828, 11, 7396, 555, 279, 7353, 18539, 315, 9624, 323, 14515, 8863, 5089, 320, 50991, 8, 25213, 5070, 311, 1862, 1521, 5528, 520, 5569, 13, 1115, 5764, 6070, 6108, 4200, 23061, 315, 24955, 40248, 20797, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 1174, 1701, 49858, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 323, 44993, 220, 1627, 23061, 20414, 11, 439, 1664, 439, 3293, 6650, 315, 828, 32505, 5780, 6975, 320, 2735, 8, 323, 34075, 5528, 369, 52997, 86101, 1372, 323, 25864, 6012, 323, 7640, 220, 1544, 662, 23966, 13, 220, 16, 25, 5422, 9547, 10043, 650, 7416, 5557, 42445, 82, 369, 9659, 315, 1579, 22867, 13280, 323, 11767, 13, 264, 1174, 4497, 1109, 220, 1049, 11, 931, 13128, 14726, 304, 279, 393, 3590, 11, 5636, 879, 15661, 11, 617, 810, 1109, 220, 1954, 4, 315, 13128, 8689, 9960, 449, 1579, 64036, 1630, 30630, 323, 810, 6051, 16106, 78, 37081, 2298, 92914, 14726, 11, 3629, 304, 12742, 16003, 5415, 11, 449, 9861, 33251, 1101, 10409, 555, 5105, 2508, 477, 25737, 76636, 17, 4211, 13, 293, 1174, 578, 11742, 3634, 2561, 369, 23061, 323, 5043, 39975, 706, 15042, 505, 922, 220, 605, 220, 22, 389, 7666, 491, 32246, 304, 220, 679, 20, 311, 810, 1109, 220, 18, 25800, 220, 605, 220, 605, 389, 57364, 32246, 304, 220, 2366, 17, 11, 323, 649, 387, 19019, 17626, 7953, 220, 605, 220, 868, 17226, 323, 11775, 32246, 13, 272, 1174, 93028, 5528, 369, 650, 7416, 2997, 31003, 304, 5043, 19303, 89310, 11, 44993, 12569, 6108, 26249, 11, 34075, 4211, 323, 26038, 128257, 198, 128256, 78191, 198, 9470, 16895, 11478, 649, 7068, 45319, 323, 23691, 11, 1893, 27078, 1847, 5885, 11, 24564, 13057, 15055, 315, 828, 323, 11388, 12912, 430, 279, 3823, 8071, 2643, 3194, 13, 38891, 1148, 15592, 1436, 656, 369, 5623, 18841, 11, 36342, 264, 892, 70840, 11, 11646, 1920, 505, 279, 13731, 311, 279, 96803, 13, 51859, 1518, 2294, 11471, 304, 264, 58535, 5603, 1701, 15592, 323, 6070, 6108, 5623, 18841, 11, 264, 55580, 1749, 430, 34744, 389, 6677, 315, 220, 18, 35, 14726, 315, 24156, 11811, 13, 1226, 6051, 10791, 709, 449, 650, 325, 12821, 347, 330, 1542, 6723, 1, 17816, 92689, 11, 22712, 14561, 315, 47616, 323, 55580, 34458, 323, 30903, 520, 279, 44379, 423, 44129, 1643, 9304, 315, 45397, 11, 17979, 323, 23199, 323, 279, 44379, 5384, 22110, 5955, 369, 1221, 424, 16149, 77948, 66, 1873, 13, 17816, 92689, 374, 279, 1080, 44624, 269, 315, 279, 5955, 369, 1561, 25579, 304, 26166, 39193, 323, 11050, 320, 98354, 18, 35, 8, 520, 279, 44379, 5384, 22110, 5955, 323, 279, 3063, 3229, 315, 264, 502, 3477, 5684, 4756, 304, 22037, 13, 578, 5684, 11, 1080, 96471, 555, 44379, 3495, 28568, 94425, 10426, 689, 328, 7759, 77614, 869, 11, 16964, 1268, 55580, 20414, 690, 82703, 5623, 18841, 13, 1226, 2351, 389, 279, 272, 30863, 315, 3682, 31003, 304, 5623, 18841, 13, 3639, 12716, 603, 311, 420, 4545, 30, 2684, 706, 1027, 264, 72579, 6541, 304, 55580, 5623, 18841, 304, 279, 1566, 2478, 1667, 25, 459, 25176, 315, 828, 18539, 389, 70432, 9959, 11, 3823, 10039, 39340, 14726, 17223, 35715, 430, 10950, 1124, 11, 23205, 11742, 20797, 315, 5623, 12970, 35715, 11, 4661, 27862, 25213, 2410, 323, 502, 11, 810, 11297, 55580, 5528, 13, 578, 24519, 28361, 374, 922, 15592, 6108, 5623, 18841, 11, 719, 1148, 596, 1524, 810, 8147, 374, 264, 10824, 315, 15592, 323, 6070, 6108, 5623, 18841, 11, 449, 2225, 20414, 80526, 38210, 23606, 287, 1855, 1023, 13, 2650, 706, 5623, 18841, 1027, 2884, 304, 279, 3347, 30, 46560, 5623, 18841, 374, 10213, 264, 9269, 9976, 19453, 26255, 13, 1102, 596, 6435, 323, 11646, 11, 4737, 459, 5578, 315, 220, 868, 1667, 323, 400, 17, 7239, 13, 2684, 596, 264, 1579, 6510, 684, 4478, 520, 1475, 3094, 11, 505, 2218, 6727, 311, 3063, 26329, 13, 578, 1455, 10708, 369, 892, 323, 2853, 19523, 48383, 304, 279, 6931, 18841, 323, 864, 91899, 18094, 13, 3639, 5097, 2035, 304, 279, 4216, 6566, 30, 6914, 596, 1005, 264, 5409, 9976, 16569, 56203, 13, 578, 2218, 35268, 374, 279, 5409, 11, 323, 279, 5623, 430, 10215, 477, 75042, 420, 35268, 374, 264, 1401, 369, 420, 5409, 13, 320, 2173, 3388, 11, 279, 87151, 374, 430, 304, 34458, 4400, 374, 3776, 477, 4251, 11, 779, 1063, 315, 279, 3318, 7039, 3480, 279, 5409, 2731, 1109, 3885, 11, 323, 5409, 374, 264, 2766, 296, 5164, 481, 2288, 6266, 5810, 596, 459, 3187, 13, 42239, 1960, 11, 279, 72002, 5623, 315, 682, 892, 11, 11811, 459, 49242, 6532, 304, 279, 39975, 315, 39086, 304, 279, 26587, 13, 362, 35268, 389, 279, 49242, 374, 279, 5409, 13, 42239, 1960, 374, 279, 1401, 11, 27442, 1139, 279, 5409, 323, 22978, 279, 5820, 315, 279, 49242, 11, 52605, 264, 4101, 315, 4455, 430, 18979, 6680, 5990, 315, 3958, 39086, 13, 4800, 11, 55580, 20414, 2187, 603, 311, 68878, 1646, 1690, 33151, 323, 1524, 490, 91387, 315, 4200, 7039, 323, 7168, 902, 6305, 527, 4461, 311, 387, 1695, 7039, 13, 8442, 264, 2478, 21030, 315, 279, 1888, 9322, 7039, 527, 8590, 2740, 92106, 323, 12793, 13, 1115, 10578, 1790, 810, 11297, 1442, 279, 1646, 374, 1695, 11, 420, 1920, 36508, 2731, 3135, 1109, 8776, 9269, 9976, 19453, 7649, 315, 11990, 315, 4288, 7039, 13, 1115, 26338, 279, 7106, 8670, 369, 39975, 315, 32246, 323, 7649, 1124, 810, 1109, 9214, 20557, 11, 1418, 3629, 33111, 520, 2731, 3135, 11, 439, 21091, 555, 1057, 990, 323, 990, 315, 1690, 1023, 5315, 3318, 304, 420, 2115, 13, 3053, 499, 10552, 279, 6811, 1990, 279, 1403, 1925, 55580, 20414, 11, 6070, 6108, 323, 15592, 6108, 30, 23548, 279, 5409, 9976, 16569, 56203, 11, 279, 6070, 6108, 5603, 5097, 9610, 315, 1057, 11944, 8830, 315, 279, 5409, 596, 6070, 13, 1442, 279, 220, 18, 35, 11, 7106, 6070, 315, 279, 5409, 374, 3967, 11, 584, 649, 1005, 4200, 5528, 311, 7168, 279, 6070, 315, 264, 1401, 430, 9248, 279, 5409, 13, 578, 5780, 6975, 11, 477, 15592, 6108, 5603, 11, 4375, 1888, 994, 1690, 7039, 527, 2736, 3967, 369, 1057, 2218, 5409, 477, 1023, 4528, 32776, 13, 15592, 649, 1243, 24564, 420, 21655, 315, 4528, 32776, 323, 7039, 323, 7168, 279, 7039, 430, 527, 1455, 4461, 311, 5052, 1057, 2218, 13, 1102, 1587, 539, 1205, 4839, 6677, 315, 279, 5409, 6070, 11, 719, 433, 3966, 264, 3544, 4526, 315, 9959, 7039, 13, 14636, 11, 279, 6070, 6108, 323, 15592, 6108, 20414, 527, 8581, 304, 2204, 5157, 323, 23606, 1855, 1023, 13, 8886, 1070, 904, 55580, 13693, 311, 420, 1920, 30, 3277, 7649, 33151, 323, 490, 91387, 315, 4200, 32246, 389, 9624, 19002, 11, 55580, 7194, 5694, 649, 3719, 264, 88938, 13, 362, 44993, 11, 342, 16960, 13230, 23061, 5557, 6276, 603, 311, 4732, 709, 323, 8108, 2853, 29057, 555, 21907, 52997, 1695, 5596, 315, 279, 1401, 11, 16343, 1124, 3871, 11, 3460, 315, 4857, 279, 1401, 505, 3892, 5596, 13, 1789, 264, 220, 605, 7239, 63250, 801, 6875, 11, 420, 21701, 279, 55580, 7194, 505, 11990, 315, 11441, 311, 11758, 11, 323, 433, 6276, 4726, 5569, 27859, 311, 490, 91387, 315, 32246, 13, 220, 128257, 198 ]

2,235

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Fish skeletal remains recovered from two archaeological sites dated in the Middle Holocene of Tierra del Fuego (Argentina) were analysed to describe habitat use patterns by hake in the past and predict changes in a warmer world. Mitochondrial DNA was successfully extracted and amplified from 42 out of 45 first vertebra from ancient hake and phylogenetic analysis assigned all haplotypes to Argentine hake ( Merluccius hubbsi ). According to osteometry, the Argentine hake recovered from the archaeological site were likely adults ranging 37.2–58.1 cm in standard length. C and N stable isotope analysis showed that currently Argentine hake use foraging grounds deeper than those of Patagonian blenny and pink cusk-eel. Argentine hake, however, had a much broader isotopic niche during the Middle Holocene, when a large part of the population foraged much shallower than contemporary pink cusk-eel. The overall evidence suggests the presence of large numbers of Argentine hake onshore Tierra del Fuego during the Middle Holocene, which allowed exploitation by hunter-gatherer-fisher groups devoid of fishing technology. Interestingly, average SST off Tierra del Fuego during the Middle Holocene was higher than currently (11 °C vs 7 °C) and matched SST in the current southernmost onshore spawning aggregations, at latitude 47 °S. This indicates that increasing SST resulting from global warming will likely result into an increased abundance of adult Argentine hake onshore Tierra del Fuego, as during the Middle Holocene. Furthermore, stable isotope ratios from mollusc shells confirmed a much higher marine primary productivity during the Middle Holocene off Tierra del Fuego. Access provided by MPDL Services gGmbH c/o Max Planck Digital Library Working on a manuscript? Avoid the common mistakes Introduction Global warming will modify fish distribution and abundance around the world, with tropical and subtropical species expanding poleward (Perry et al. 2005 ; Hiddink and Ter Hofstede 2008 ; Simpson et al. 2011 ), while those inhabiting colder regions are expected to change their depth range (Perry et al. 2005 ; Simpson et al. 2011 ). As a result, food web structure and dynamics are also expected to change (Hoegh-Guldberg and Bruno 2010 ; Simpson et al. 2011 ; Bas et al. 2019 ). Making precise predictions, however, about the consequences of global warming is challenging without a broad historical perspective (Swetnam et al. 1999 ; Jackson et al. 2001 ; Lotze et al. 2011 ; Friedlander et al. 2014 ). The South-Western Atlantic Ocean is inhabited by two species of hake: the Argentine hake Merluccius hubbsi (Marini, 1933) and the Southern hake Merluccius australis (Hutton, 1872), which both support important commercial fisheries (Bezzi et al. 1995 ; Cousseau and Perrotta 1998 ; Bertolotti et al. 2001 ; Lloris et al. 2005 ). Commercial hake fishing began in Argentina in the 1960s and targeted mainly Argentine hake. Commercial fishing for Southern hake started in the 1990s, when shallow water stocks of Argentine hake were declining (Lloris et al. 2005 ). Both species are similar in morphology and biology, but the Southern hake is tightly linked to the cold Malvinas current, whereas the Argentine hake prevails on warmer waters over the continental shelf (Cousseau and Perrotta 1998 ; Lloris et al. 2005 ). Furthermore, the abundance of Argentine hake declines sharply south of 52 °S and coastal summer spawning aggregations do not exist south of 47 °S (Bezzi et al. 1995 ; Díaz de Astarloa et al. 2011 ), where annual average SST is 11 °C (Rivas 2010 ). This suggests that in a warmer world, the Argentine hake could expand southward and replace the Southern hake off Tierra del Fuego. The zooarchaeological record of ancient fishing societies offers an opportunity to explore changes through time on issues such as age-length relationships (Leach and Davidson 2001 ; Bolle et al. 2004 ), geographic distribution (Enghoff et al. 2007 ; Scartascini and Volpedo 2013 ; Bas et al. 2019 ) and trophic position (Zenteno et al. 2015 ; Braje et al. 2017 ; Szpak et al. 2018 ; Bas et al. 2019 ). The fish remains left by societies living in the warmer periods of the Holocene are particularly interesting since they offer a glimpse to a plausible future in the context of global warming (Bas et al. 2019 ). The zooarchaeological record of Tierra del Fuego dates to the Early Holocene and hake ( Merluccius sp.) abound in many archaeological sites since the Middle Holocene (Torres 2009 ; Santiago 2013 ; Zangrando et al. 2016 ). According to a diversity of proxies, climate and SST during the Middle Holocene in the southernmost tip of South America were warmer than today (Bujalesky 2007 ; Shevenell et al. 2011 ; Caniupán et al. 2014 ). Currently, annual average SST off Tierra del Fuego is 7 °C (Rivas 2010 ), but was as high as 11–12 °C at 53 °S during the Middle Holocene (Caniupán et al. 2014 ). Therefore, data on the biology of hake during the Middle Holocene can inform predictions of the future distributions of both species. The recovery of 9000 skeletal elements from an unknown number of hake specimens from Río Chico 1 archaeological site (Santiago 2013 ), clearly demonstrates the existence of a huge coastal population of at least one hake species off north-eastern Tierra del Fuego during the Middle Holocene. That population has since disappeared and morphological analysis cannot distinguish the skeletal elements of Argentine and Southern hake other than hyomandibular and urohyal bones (Lloris et al. 2005 ). Therefore, the species of hake recovered from Río Chico 1 remains unknown and, nothing is known about the habitat where the Río Chico 1 hake were captured. The strong winds and currents in this region, coupled with the absence of sailing technology during the Middle Holocene suggest that aboriginal hunter-gatherer-fisher groups likely captured hake onshore, but hard evidence is missing. Stable isotope analysis can be informative about the habitat used by ancient hake, but detailed studies comparing the stable isotope ratios from sympatric Argentine and Southern hakes have not yet been published and the comparison of", "role": "user" }, { "content": "Global warming will modify the distribution and abundance of fish worldwide, with effects on the structure and dynamics of food networks. However, making precise predictions on the consequences of this global phenomenon is hard without having a wide historical perspective. A study carried out at the University of Barcelona and the Southern Centre for Scientific Research (CADIC-CONICET, Argentina), analyzed the potential implications in the distribution of the Argentinian hake (Merluccius hubbsi), caused by the warming of marine waters. The study is based on the analysis of the structure of the marine ecosystems from 6,000 to 500 years ago, when temperatures were warmer than now. The results show this species could expand towards south and reach the coast of the South America extreme southern area, like it happened in the past. According to the researchers, this approach allows researchers to make predictions on the transformations to be caused by the climate change in the marine environment with important ecogical and economic implications. The study, published in the journal Oecologia, is part of the doctoral thesis by the researcher Maria Bas, member of CADIC-CONICET and the Biodiversity Research Institute (IRBio) of the University of Barcelona, co-supervised by the tenure-track 2 lecturer Lluís Cardona, from the Research Groups on Large Marine Vertebrates at the Department of Evolutionary Biology, Ecology and Environmental Sciences of the Faculty of Biology and IRBio, and by the expert Ivan Briz i Godino, from CADIC-CONICET. York University (United Kingdom) and British Columbia University (Canada) have also taken part in the study. The Middle Holocene, a plausible view of the future Researchers focused on the Atlantic coast of Isla Grande in Tierra del Fuego, in the extreme south of Argentina, where the hake is a key species for industrial fisheries. They collected samples from two archaeological sites dating from the Middle Holocene, that is, between 6,000 and 500 years ago, a period when temperatures would be analogous to those we are heading to in the future -according to climate models. \"Remains from fish that lived in the warmest periods of the Holocene are specially interesting since they offer a plausible view of the future in the context of global warming. At the moment, the average annual temperature of the sea surface in Tierra del Fuego is about 7ºC, but during the Middle Holocene it reached 11 and 12ºC. Therefore, data on the biology of the hake during this period can provide information on the distribution of this species in a near future,\" note the authors. The presence of remains from other models of hake in the archaeological site Río Chico 1, in the north of Tierra del Fuego (Argentina), show the existence of a large population of hake in the northern east of Tierra del Fuego during the Middle Holocene. Since then, this population has disappeared due to the cooling temperatures, and their habitat remained unknown. Changes in the distribution of the Argentinian hake In order to discover the habitat of these fish, the first step in the study was to identify the remains through the mitochondrial DNA analysis and make a reconstruction of the size of old models. Then, researchers used the technique of carbon and nitrogen stable isotope analysis to study changes in the trophic position and the use of the habitat over time. This technique enables researchers to get information on the food intake, and the environment of the species that lived in a recent past, since the information is registered in the bone isotopic signal. Results show that Argentinian hake that lived in the Atlantic coast of Tierra del Fuego during the Middle Holocene had a broader isotopic niche and fed in more coastal habitats compared to those in current times. \"This information, combined with strong winds and currents of the region, together with the lack of sailing technology during the Middle Holocene suggest that groups of aboriginal hunter-fisher-gatherers were likely to fish in the shore,\" note the authors. If the environmental conditions of a warmer world coincide with what prevails in the Middle Holocene, the Argentinian hake could be more abundant in the continental Argentinian platform of Tierra del Fuego. \"From a fishing perspective, this situation suggests a potential increase of resources in shallow waters regarding Tierra del Fuego with important changes in the fishing industry in this region,\" highlights Lluís Cardona. According to the researchers, this methodology can be used with other species and in other areas of the planet. \"In the future, we would like to know the changes that have taken place in the distribution and ecological niche of the hake and the cod in European waters,\" concludes the researcher. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Fish skeletal remains recovered from two archaeological sites dated in the Middle Holocene of Tierra del Fuego (Argentina) were analysed to describe habitat use patterns by hake in the past and predict changes in a warmer world. Mitochondrial DNA was successfully extracted and amplified from 42 out of 45 first vertebra from ancient hake and phylogenetic analysis assigned all haplotypes to Argentine hake ( Merluccius hubbsi ). According to osteometry, the Argentine hake recovered from the archaeological site were likely adults ranging 37.2–58.1 cm in standard length. C and N stable isotope analysis showed that currently Argentine hake use foraging grounds deeper than those of Patagonian blenny and pink cusk-eel. Argentine hake, however, had a much broader isotopic niche during the Middle Holocene, when a large part of the population foraged much shallower than contemporary pink cusk-eel. The overall evidence suggests the presence of large numbers of Argentine hake onshore Tierra del Fuego during the Middle Holocene, which allowed exploitation by hunter-gatherer-fisher groups devoid of fishing technology. Interestingly, average SST off Tierra del Fuego during the Middle Holocene was higher than currently (11 °C vs 7 °C) and matched SST in the current southernmost onshore spawning aggregations, at latitude 47 °S. This indicates that increasing SST resulting from global warming will likely result into an increased abundance of adult Argentine hake onshore Tierra del Fuego, as during the Middle Holocene. Furthermore, stable isotope ratios from mollusc shells confirmed a much higher marine primary productivity during the Middle Holocene off Tierra del Fuego. Access provided by MPDL Services gGmbH c/o Max Planck Digital Library Working on a manuscript? Avoid the common mistakes Introduction Global warming will modify fish distribution and abundance around the world, with tropical and subtropical species expanding poleward (Perry et al. 2005 ; Hiddink and Ter Hofstede 2008 ; Simpson et al. 2011 ), while those inhabiting colder regions are expected to change their depth range (Perry et al. 2005 ; Simpson et al. 2011 ). As a result, food web structure and dynamics are also expected to change (Hoegh-Guldberg and Bruno 2010 ; Simpson et al. 2011 ; Bas et al. 2019 ). Making precise predictions, however, about the consequences of global warming is challenging without a broad historical perspective (Swetnam et al. 1999 ; Jackson et al. 2001 ; Lotze et al. 2011 ; Friedlander et al. 2014 ). The South-Western Atlantic Ocean is inhabited by two species of hake: the Argentine hake Merluccius hubbsi (Marini, 1933) and the Southern hake Merluccius australis (Hutton, 1872), which both support important commercial fisheries (Bezzi et al. 1995 ; Cousseau and Perrotta 1998 ; Bertolotti et al. 2001 ; Lloris et al. 2005 ). Commercial hake fishing began in Argentina in the 1960s and targeted mainly Argentine hake. Commercial fishing for Southern hake started in the 1990s, when shallow water stocks of Argentine hake were declining (Lloris et al. 2005 ). Both species are similar in morphology and biology, but the Southern hake is tightly linked to the cold Malvinas current, whereas the Argentine hake prevails on warmer waters over the continental shelf (Cousseau and Perrotta 1998 ; Lloris et al. 2005 ). Furthermore, the abundance of Argentine hake declines sharply south of 52 °S and coastal summer spawning aggregations do not exist south of 47 °S (Bezzi et al. 1995 ; Díaz de Astarloa et al. 2011 ), where annual average SST is 11 °C (Rivas 2010 ). This suggests that in a warmer world, the Argentine hake could expand southward and replace the Southern hake off Tierra del Fuego. The zooarchaeological record of ancient fishing societies offers an opportunity to explore changes through time on issues such as age-length relationships (Leach and Davidson 2001 ; Bolle et al. 2004 ), geographic distribution (Enghoff et al. 2007 ; Scartascini and Volpedo 2013 ; Bas et al. 2019 ) and trophic position (Zenteno et al. 2015 ; Braje et al. 2017 ; Szpak et al. 2018 ; Bas et al. 2019 ). The fish remains left by societies living in the warmer periods of the Holocene are particularly interesting since they offer a glimpse to a plausible future in the context of global warming (Bas et al. 2019 ). The zooarchaeological record of Tierra del Fuego dates to the Early Holocene and hake ( Merluccius sp.) abound in many archaeological sites since the Middle Holocene (Torres 2009 ; Santiago 2013 ; Zangrando et al. 2016 ). According to a diversity of proxies, climate and SST during the Middle Holocene in the southernmost tip of South America were warmer than today (Bujalesky 2007 ; Shevenell et al. 2011 ; Caniupán et al. 2014 ). Currently, annual average SST off Tierra del Fuego is 7 °C (Rivas 2010 ), but was as high as 11–12 °C at 53 °S during the Middle Holocene (Caniupán et al. 2014 ). Therefore, data on the biology of hake during the Middle Holocene can inform predictions of the future distributions of both species. The recovery of 9000 skeletal elements from an unknown number of hake specimens from Río Chico 1 archaeological site (Santiago 2013 ), clearly demonstrates the existence of a huge coastal population of at least one hake species off north-eastern Tierra del Fuego during the Middle Holocene. That population has since disappeared and morphological analysis cannot distinguish the skeletal elements of Argentine and Southern hake other than hyomandibular and urohyal bones (Lloris et al. 2005 ). Therefore, the species of hake recovered from Río Chico 1 remains unknown and, nothing is known about the habitat where the Río Chico 1 hake were captured. The strong winds and currents in this region, coupled with the absence of sailing technology during the Middle Holocene suggest that aboriginal hunter-gatherer-fisher groups likely captured hake onshore, but hard evidence is missing. Stable isotope analysis can be informative about the habitat used by ancient hake, but detailed studies comparing the stable isotope ratios from sympatric Argentine and Southern hakes have not yet been published and the comparison of<|im_end|> <|im_start|>assistant Global warming will modify the distribution and abundance of fish worldwide, with effects on the structure and dynamics of food networks. However, making precise predictions on the consequences of this global phenomenon is hard without having a wide historical perspective. A study carried out at the University of Barcelona and the Southern Centre for Scientific Research (CADIC-CONICET, Argentina), analyzed the potential implications in the distribution of the Argentinian hake (Merluccius hubbsi), caused by the warming of marine waters. The study is based on the analysis of the structure of the marine ecosystems from 6,000 to 500 years ago, when temperatures were warmer than now. The results show this species could expand towards south and reach the coast of the South America extreme southern area, like it happened in the past. According to the researchers, this approach allows researchers to make predictions on the transformations to be caused by the climate change in the marine environment with important ecogical and economic implications. The study, published in the journal Oecologia, is part of the doctoral thesis by the researcher Maria Bas, member of CADIC-CONICET and the Biodiversity Research Institute (IRBio) of the University of Barcelona, co-supervised by the tenure-track 2 lecturer Lluís Cardona, from the Research Groups on Large Marine Vertebrates at the Department of Evolutionary Biology, Ecology and Environmental Sciences of the Faculty of Biology and IRBio, and by the expert Ivan Briz i Godino, from CADIC-CONICET. York University (United Kingdom) and British Columbia University (Canada) have also taken part in the study. The Middle Holocene, a plausible view of the future Researchers focused on the Atlantic coast of Isla Grande in Tierra del Fuego, in the extreme south of Argentina, where the hake is a key species for industrial fisheries. They collected samples from two archaeological sites dating from the Middle Holocene, that is, between 6,000 and 500 years ago, a period when temperatures would be analogous to those we are heading to in the future -according to climate models. "Remains from fish that lived in the warmest periods of the Holocene are specially interesting since they offer a plausible view of the future in the context of global warming. At the moment, the average annual temperature of the sea surface in Tierra del Fuego is about 7ºC, but during the Middle Holocene it reached 11 and 12ºC. Therefore, data on the biology of the hake during this period can provide information on the distribution of this species in a near future," note the authors. The presence of remains from other models of hake in the archaeological site Río Chico 1, in the north of Tierra del Fuego (Argentina), show the existence of a large population of hake in the northern east of Tierra del Fuego during the Middle Holocene. Since then, this population has disappeared due to the cooling temperatures, and their habitat remained unknown. Changes in the distribution of the Argentinian hake In order to discover the habitat of these fish, the first step in the study was to identify the remains through the mitochondrial DNA analysis and make a reconstruction of the size of old models. Then, researchers used the technique of carbon and nitrogen stable isotope analysis to study changes in the trophic position and the use of the habitat over time. This technique enables researchers to get information on the food intake, and the environment of the species that lived in a recent past, since the information is registered in the bone isotopic signal. Results show that Argentinian hake that lived in the Atlantic coast of Tierra del Fuego during the Middle Holocene had a broader isotopic niche and fed in more coastal habitats compared to those in current times. "This information, combined with strong winds and currents of the region, together with the lack of sailing technology during the Middle Holocene suggest that groups of aboriginal hunter-fisher-gatherers were likely to fish in the shore," note the authors. If the environmental conditions of a warmer world coincide with what prevails in the Middle Holocene, the Argentinian hake could be more abundant in the continental Argentinian platform of Tierra del Fuego. "From a fishing perspective, this situation suggests a potential increase of resources in shallow waters regarding Tierra del Fuego with important changes in the fishing industry in this region," highlights Lluís Cardona. According to the researchers, this methodology can be used with other species and in other areas of the planet. "In the future, we would like to know the changes that have taken place in the distribution and ecological niche of the hake and the cod in European waters," concludes the researcher. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 17019, 69397, 8625, 26403, 505, 1403, 69637, 6732, 30105, 304, 279, 12877, 16071, 78782, 315, 23126, 14210, 1624, 435, 27779, 320, 96517, 8, 1051, 67458, 311, 7664, 39646, 1005, 12912, 555, 305, 731, 304, 279, 3347, 323, 7168, 4442, 304, 264, 46039, 1917, 13, 22515, 47517, 6757, 15922, 574, 7946, 28532, 323, 83598, 505, 220, 2983, 704, 315, 220, 1774, 1176, 5309, 51313, 505, 14154, 305, 731, 323, 37555, 86945, 5411, 6492, 12893, 682, 46900, 9363, 1842, 311, 82822, 305, 731, 320, 8930, 10036, 641, 9334, 19240, 1302, 72, 7609, 10771, 311, 52368, 7133, 11, 279, 82822, 305, 731, 26403, 505, 279, 69637, 2816, 1051, 4461, 12884, 24950, 220, 1806, 13, 17, 4235, 2970, 13, 16, 10166, 304, 5410, 3160, 13, 356, 323, 452, 15528, 374, 51782, 6492, 8710, 430, 5131, 82822, 305, 731, 1005, 369, 4210, 21319, 19662, 1109, 1884, 315, 7281, 6241, 1122, 1529, 18314, 323, 18718, 272, 33879, 5773, 301, 13, 82822, 305, 731, 11, 4869, 11, 1047, 264, 1790, 27927, 69551, 25847, 35149, 2391, 279, 12877, 16071, 78782, 11, 994, 264, 3544, 961, 315, 279, 7187, 369, 3359, 1790, 4985, 1223, 1109, 19225, 18718, 272, 33879, 5773, 301, 13, 578, 8244, 6029, 13533, 279, 9546, 315, 3544, 5219, 315, 82822, 305, 731, 389, 29526, 23126, 14210, 1624, 435, 27779, 2391, 279, 12877, 16071, 78782, 11, 902, 5535, 40761, 555, 40827, 2427, 1894, 261, 2269, 39672, 5315, 76939, 315, 20543, 5557, 13, 58603, 11, 5578, 92516, 1022, 23126, 14210, 1624, 435, 27779, 2391, 279, 12877, 16071, 78782, 574, 5190, 1109, 5131, 320, 806, 37386, 34, 6296, 220, 22, 37386, 34, 8, 323, 18545, 92516, 304, 279, 1510, 18561, 3646, 389, 29526, 79529, 26263, 811, 11, 520, 21518, 220, 2618, 37386, 50, 13, 1115, 15151, 430, 7859, 92516, 13239, 505, 3728, 24808, 690, 4461, 1121, 1139, 459, 7319, 37492, 315, 6822, 82822, 305, 731, 389, 29526, 23126, 14210, 1624, 435, 27779, 11, 439, 2391, 279, 12877, 16071, 78782, 13, 24296, 11, 15528, 374, 51782, 42338, 505, 55509, 26089, 44054, 11007, 264, 1790, 5190, 29691, 6156, 26206, 2391, 279, 12877, 16071, 78782, 1022, 23126, 14210, 1624, 435, 27779, 13, 9742, 3984, 555, 9599, 16931, 8471, 342, 38, 32198, 272, 20886, 7639, 9878, 377, 14434, 11896, 22938, 389, 264, 47913, 30, 35106, 279, 4279, 21294, 29438, 8121, 24808, 690, 5719, 7795, 8141, 323, 37492, 2212, 279, 1917, 11, 449, 35148, 323, 42129, 51172, 9606, 24050, 26078, 1637, 320, 47, 5515, 1880, 453, 13, 220, 1049, 20, 2652, 473, 1810, 771, 323, 10335, 72812, 267, 15686, 220, 1049, 23, 2652, 35766, 1880, 453, 13, 220, 679, 16, 7026, 1418, 1884, 26318, 5977, 76214, 13918, 527, 3685, 311, 2349, 872, 8149, 2134, 320, 47, 5515, 1880, 453, 13, 220, 1049, 20, 2652, 35766, 1880, 453, 13, 220, 679, 16, 7609, 1666, 264, 1121, 11, 3691, 3566, 6070, 323, 30295, 527, 1101, 3685, 311, 2349, 320, 49078, 797, 71, 12279, 37668, 7881, 323, 52210, 220, 679, 15, 2652, 35766, 1880, 453, 13, 220, 679, 16, 2652, 15004, 1880, 453, 13, 220, 679, 24, 7609, 25274, 24473, 20492, 11, 4869, 11, 922, 279, 16296, 315, 3728, 24808, 374, 17436, 2085, 264, 7353, 13970, 13356, 320, 13521, 295, 12682, 1880, 453, 13, 220, 2550, 24, 2652, 13972, 1880, 453, 13, 220, 1049, 16, 2652, 22503, 3059, 1880, 453, 13, 220, 679, 16, 2652, 31351, 35103, 1880, 453, 13, 220, 679, 19, 7609, 578, 4987, 61861, 944, 23179, 22302, 374, 70598, 555, 1403, 9606, 315, 305, 731, 25, 279, 82822, 305, 731, 8930, 10036, 641, 9334, 19240, 1302, 72, 320, 12331, 6729, 11, 220, 7285, 18, 8, 323, 279, 16642, 305, 731, 8930, 10036, 641, 9334, 264, 5523, 285, 320, 39, 973, 11, 220, 9674, 17, 705, 902, 2225, 1862, 3062, 8518, 82596, 320, 3513, 89, 8510, 1880, 453, 13, 220, 2550, 20, 2652, 356, 46651, 2933, 323, 3700, 4744, 2629, 220, 2550, 23, 2652, 51775, 337, 42327, 1880, 453, 13, 220, 1049, 16, 2652, 445, 9761, 285, 1880, 453, 13, 220, 1049, 20, 7609, 28943, 305, 731, 20543, 6137, 304, 32164, 304, 279, 220, 5162, 15, 82, 323, 17550, 14918, 82822, 305, 731, 13, 28943, 20543, 369, 16642, 305, 731, 3940, 304, 279, 220, 2550, 15, 82, 11, 994, 26682, 3090, 23301, 315, 82822, 305, 731, 1051, 43848, 320, 43, 9761, 285, 1880, 453, 13, 220, 1049, 20, 7609, 11995, 9606, 527, 4528, 304, 79612, 323, 34458, 11, 719, 279, 16642, 305, 731, 374, 40069, 10815, 311, 279, 9439, 8560, 9799, 300, 1510, 11, 20444, 279, 82822, 305, 731, 8031, 6341, 389, 46039, 21160, 927, 279, 58636, 28745, 320, 34, 46651, 2933, 323, 3700, 4744, 2629, 220, 2550, 23, 2652, 445, 9761, 285, 1880, 453, 13, 220, 1049, 20, 7609, 24296, 11, 279, 37492, 315, 82822, 305, 731, 58054, 46473, 10007, 315, 220, 4103, 37386, 50, 323, 35335, 7474, 79529, 26263, 811, 656, 539, 3073, 10007, 315, 220, 2618, 37386, 50, 320, 3513, 89, 8510, 1880, 453, 13, 220, 2550, 20, 2652, 423, 2483, 1394, 409, 362, 12134, 385, 64, 1880, 453, 13, 220, 679, 16, 7026, 1405, 9974, 5578, 92516, 374, 220, 806, 37386, 34, 320, 49, 39924, 220, 679, 15, 7609, 1115, 13533, 430, 304, 264, 46039, 1917, 11, 279, 82822, 305, 731, 1436, 9407, 10007, 1637, 323, 8454, 279, 16642, 305, 731, 1022, 23126, 14210, 1624, 435, 27779, 13, 578, 42014, 1132, 6043, 5848, 3335, 315, 14154, 20543, 34775, 6209, 459, 6776, 311, 13488, 4442, 1555, 892, 389, 4819, 1778, 439, 4325, 30425, 12135, 320, 2356, 613, 323, 54345, 220, 1049, 16, 2652, 25007, 273, 1880, 453, 13, 220, 1049, 19, 7026, 46139, 8141, 320, 1737, 876, 1885, 1880, 453, 13, 220, 1049, 22, 2652, 2522, 472, 5171, 6729, 323, 11119, 53594, 220, 679, 18, 2652, 15004, 1880, 453, 13, 220, 679, 24, 883, 323, 8348, 764, 292, 2361, 320, 57, 306, 12052, 1880, 453, 13, 220, 679, 20, 2652, 26531, 3841, 1880, 453, 13, 220, 679, 22, 2652, 45290, 72089, 1880, 453, 13, 220, 679, 23, 2652, 15004, 1880, 453, 13, 220, 679, 24, 7609, 578, 7795, 8625, 2163, 555, 34775, 5496, 304, 279, 46039, 18852, 315, 279, 16071, 78782, 527, 8104, 7185, 2533, 814, 3085, 264, 40942, 311, 264, 50434, 3938, 304, 279, 2317, 315, 3728, 24808, 320, 34703, 1880, 453, 13, 220, 679, 24, 7609, 578, 42014, 1132, 6043, 5848, 3335, 315, 23126, 14210, 1624, 435, 27779, 13003, 311, 279, 23591, 16071, 78782, 323, 305, 731, 320, 8930, 10036, 641, 9334, 993, 6266, 87690, 304, 1690, 69637, 6732, 2533, 279, 12877, 16071, 78782, 320, 33450, 417, 220, 1049, 24, 2652, 55678, 220, 679, 18, 2652, 1901, 526, 81, 4988, 1880, 453, 13, 220, 679, 21, 7609, 10771, 311, 264, 20057, 315, 60465, 11, 10182, 323, 92516, 2391, 279, 12877, 16071, 78782, 304, 279, 18561, 3646, 11813, 315, 4987, 5270, 1051, 46039, 1109, 3432, 320, 33, 9832, 3916, 8050, 220, 1049, 22, 2652, 3005, 1055, 616, 1880, 453, 13, 220, 679, 16, 2652, 3053, 72, 455, 11644, 1880, 453, 13, 220, 679, 19, 7609, 25122, 11, 9974, 5578, 92516, 1022, 23126, 14210, 1624, 435, 27779, 374, 220, 22, 37386, 34, 320, 49, 39924, 220, 679, 15, 7026, 719, 574, 439, 1579, 439, 220, 806, 4235, 717, 37386, 34, 520, 220, 4331, 37386, 50, 2391, 279, 12877, 16071, 78782, 320, 34, 5676, 455, 11644, 1880, 453, 13, 220, 679, 19, 7609, 15636, 11, 828, 389, 279, 34458, 315, 305, 731, 2391, 279, 12877, 16071, 78782, 649, 6179, 20492, 315, 279, 3938, 43785, 315, 2225, 9606, 13, 578, 13654, 315, 220, 7467, 15, 69397, 5540, 505, 459, 9987, 1396, 315, 305, 731, 57749, 505, 432, 42825, 921, 4042, 220, 16, 69637, 2816, 320, 50, 44074, 220, 679, 18, 7026, 9539, 32216, 279, 14209, 315, 264, 6908, 35335, 7187, 315, 520, 3325, 832, 305, 731, 9606, 1022, 10411, 40607, 944, 23126, 14210, 1624, 435, 27779, 2391, 279, 12877, 16071, 78782, 13, 3011, 7187, 706, 2533, 29496, 323, 27448, 5848, 6492, 4250, 33137, 279, 69397, 5540, 315, 82822, 323, 16642, 305, 731, 1023, 1109, 6409, 316, 438, 581, 1299, 323, 577, 299, 8671, 278, 25896, 320, 43, 9761, 285, 1880, 453, 13, 220, 1049, 20, 7609, 15636, 11, 279, 9606, 315, 305, 731, 26403, 505, 432, 42825, 921, 4042, 220, 16, 8625, 9987, 323, 11, 4400, 374, 3967, 922, 279, 39646, 1405, 279, 432, 42825, 921, 4042, 220, 16, 305, 731, 1051, 17439, 13, 578, 3831, 29592, 323, 60701, 304, 420, 5654, 11, 34356, 449, 279, 19821, 315, 51129, 5557, 2391, 279, 12877, 16071, 78782, 4284, 430, 671, 10090, 40827, 2427, 1894, 261, 2269, 39672, 5315, 4461, 17439, 305, 731, 389, 29526, 11, 719, 2653, 6029, 374, 7554, 13, 84441, 374, 51782, 6492, 649, 387, 39319, 922, 279, 39646, 1511, 555, 14154, 305, 731, 11, 719, 11944, 7978, 27393, 279, 15528, 374, 51782, 42338, 505, 22176, 266, 2265, 82822, 323, 16642, 305, 2094, 617, 539, 3686, 1027, 4756, 323, 279, 12593, 315, 128257, 198, 128256, 78191, 198, 11907, 24808, 690, 5719, 279, 8141, 323, 37492, 315, 7795, 15603, 11, 449, 6372, 389, 279, 6070, 323, 30295, 315, 3691, 14488, 13, 4452, 11, 3339, 24473, 20492, 389, 279, 16296, 315, 420, 3728, 25885, 374, 2653, 2085, 3515, 264, 7029, 13970, 13356, 13, 362, 4007, 11953, 704, 520, 279, 3907, 315, 28035, 323, 279, 16642, 14821, 369, 38130, 8483, 320, 49670, 1341, 12, 5910, 1341, 1372, 11, 32164, 705, 30239, 279, 4754, 25127, 304, 279, 8141, 315, 279, 7793, 44509, 1122, 305, 731, 320, 27814, 10036, 641, 9334, 19240, 1302, 72, 705, 9057, 555, 279, 24808, 315, 29691, 21160, 13, 578, 4007, 374, 3196, 389, 279, 6492, 315, 279, 6070, 315, 279, 29691, 61951, 505, 220, 21, 11, 931, 311, 220, 2636, 1667, 4227, 11, 994, 20472, 1051, 46039, 1109, 1457, 13, 578, 3135, 1501, 420, 9606, 1436, 9407, 7119, 10007, 323, 5662, 279, 13962, 315, 279, 4987, 5270, 14560, 18561, 3158, 11, 1093, 433, 7077, 304, 279, 3347, 13, 10771, 311, 279, 12074, 11, 420, 5603, 6276, 12074, 311, 1304, 20492, 389, 279, 54070, 311, 387, 9057, 555, 279, 10182, 2349, 304, 279, 29691, 4676, 449, 3062, 12208, 540, 950, 323, 7100, 25127, 13, 578, 4007, 11, 4756, 304, 279, 8486, 507, 762, 39073, 11, 374, 961, 315, 279, 74657, 17850, 555, 279, 32185, 23880, 15004, 11, 4562, 315, 48365, 1341, 12, 5910, 1341, 1372, 323, 279, 426, 3205, 3050, 8483, 10181, 320, 2871, 60360, 8, 315, 279, 3907, 315, 28035, 11, 1080, 59615, 79090, 555, 279, 40061, 54566, 220, 17, 72235, 445, 10036, 24315, 6938, 6863, 11, 505, 279, 8483, 35680, 389, 20902, 23820, 650, 14140, 99868, 520, 279, 6011, 315, 38321, 661, 40023, 11, 78375, 323, 25027, 23199, 315, 279, 42904, 315, 40023, 323, 16646, 60360, 11, 323, 555, 279, 6335, 42521, 3320, 450, 602, 4359, 3394, 11, 505, 48365, 1341, 12, 5910, 1341, 1372, 13, 4356, 3907, 320, 23175, 15422, 8, 323, 8013, 19326, 3907, 320, 37031, 8, 617, 1101, 4529, 961, 304, 279, 4007, 13, 578, 12877, 16071, 78782, 11, 264, 50434, 1684, 315, 279, 3938, 59250, 10968, 389, 279, 23179, 13962, 315, 2209, 4355, 37623, 304, 23126, 14210, 1624, 435, 27779, 11, 304, 279, 14560, 10007, 315, 32164, 11, 1405, 279, 305, 731, 374, 264, 1401, 9606, 369, 13076, 82596, 13, 2435, 14890, 10688, 505, 1403, 69637, 6732, 5029, 505, 279, 12877, 16071, 78782, 11, 430, 374, 11, 1990, 220, 21, 11, 931, 323, 220, 2636, 1667, 4227, 11, 264, 4261, 994, 20472, 1053, 387, 79283, 311, 1884, 584, 527, 14836, 311, 304, 279, 3938, 482, 74946, 311, 10182, 4211, 13, 330, 6728, 1771, 505, 7795, 430, 12439, 304, 279, 8369, 478, 18852, 315, 279, 16071, 78782, 527, 35426, 7185, 2533, 814, 3085, 264, 50434, 1684, 315, 279, 3938, 304, 279, 2317, 315, 3728, 24808, 13, 2468, 279, 4545, 11, 279, 5578, 9974, 9499, 315, 279, 9581, 7479, 304, 23126, 14210, 1624, 435, 27779, 374, 922, 220, 22, 29300, 34, 11, 719, 2391, 279, 12877, 16071, 78782, 433, 8813, 220, 806, 323, 220, 717, 29300, 34, 13, 15636, 11, 828, 389, 279, 34458, 315, 279, 305, 731, 2391, 420, 4261, 649, 3493, 2038, 389, 279, 8141, 315, 420, 9606, 304, 264, 3221, 3938, 1359, 5296, 279, 12283, 13, 578, 9546, 315, 8625, 505, 1023, 4211, 315, 305, 731, 304, 279, 69637, 2816, 432, 42825, 921, 4042, 220, 16, 11, 304, 279, 10411, 315, 23126, 14210, 1624, 435, 27779, 320, 96517, 705, 1501, 279, 14209, 315, 264, 3544, 7187, 315, 305, 731, 304, 279, 18671, 11226, 315, 23126, 14210, 1624, 435, 27779, 2391, 279, 12877, 16071, 78782, 13, 8876, 1243, 11, 420, 7187, 706, 29496, 4245, 311, 279, 28015, 20472, 11, 323, 872, 39646, 14958, 9987, 13, 29240, 304, 279, 8141, 315, 279, 7793, 44509, 1122, 305, 731, 763, 2015, 311, 7142, 279, 39646, 315, 1521, 7795, 11, 279, 1176, 3094, 304, 279, 4007, 574, 311, 10765, 279, 8625, 1555, 279, 72061, 15922, 6492, 323, 1304, 264, 43738, 315, 279, 1404, 315, 2362, 4211, 13, 5112, 11, 12074, 1511, 279, 15105, 315, 12782, 323, 47503, 15528, 374, 51782, 6492, 311, 4007, 4442, 304, 279, 8348, 764, 292, 2361, 323, 279, 1005, 315, 279, 39646, 927, 892, 13, 1115, 15105, 20682, 12074, 311, 636, 2038, 389, 279, 3691, 23730, 11, 323, 279, 4676, 315, 279, 9606, 430, 12439, 304, 264, 3293, 3347, 11, 2533, 279, 2038, 374, 9879, 304, 279, 17685, 69551, 25847, 8450, 13, 18591, 1501, 430, 7793, 44509, 1122, 305, 731, 430, 12439, 304, 279, 23179, 13962, 315, 23126, 14210, 1624, 435, 27779, 2391, 279, 12877, 16071, 78782, 1047, 264, 27927, 69551, 25847, 35149, 323, 23114, 304, 810, 35335, 71699, 7863, 311, 1884, 304, 1510, 3115, 13, 330, 2028, 2038, 11, 11093, 449, 3831, 29592, 323, 60701, 315, 279, 5654, 11, 3871, 449, 279, 6996, 315, 51129, 5557, 2391, 279, 12877, 16071, 78782, 4284, 430, 5315, 315, 671, 10090, 40827, 2269, 39672, 2427, 1894, 388, 1051, 4461, 311, 7795, 304, 279, 31284, 1359, 5296, 279, 12283, 13, 1442, 279, 12434, 4787, 315, 264, 46039, 1917, 72359, 449, 1148, 8031, 6341, 304, 279, 12877, 16071, 78782, 11, 279, 7793, 44509, 1122, 305, 731, 1436, 387, 810, 44611, 304, 279, 58636, 7793, 44509, 1122, 5452, 315, 23126, 14210, 1624, 435, 27779, 13, 330, 3915, 264, 20543, 13356, 11, 420, 6671, 13533, 264, 4754, 5376, 315, 5070, 304, 26682, 21160, 9002, 23126, 14210, 1624, 435, 27779, 449, 3062, 4442, 304, 279, 20543, 5064, 304, 420, 5654, 1359, 22020, 445, 10036, 24315, 6938, 6863, 13, 10771, 311, 279, 12074, 11, 420, 38152, 649, 387, 1511, 449, 1023, 9606, 323, 304, 1023, 5789, 315, 279, 11841, 13, 330, 644, 279, 3938, 11, 584, 1053, 1093, 311, 1440, 279, 4442, 430, 617, 4529, 2035, 304, 279, 8141, 323, 50953, 35149, 315, 279, 305, 731, 323, 279, 20950, 304, 7665, 21160, 1359, 45537, 279, 32185, 13, 220, 128257, 198 ]

2,476

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Microporous annealed particle (MAP) scaffolds are flowable, in situ crosslinked, microporous scaffolds composed of microgel building blocks and were previously shown to accelerate wound healing. To promote more extensive tissue ingrowth before scaffold degradation, we aimed to slow MAP degradation by switching the chirality of the crosslinking peptides from l - to d -amino acids. Unexpectedly, despite showing the predicted slower enzymatic degradation in vitro, d -peptide crosslinked MAP hydrogel ( d -MAP) hastened material degradation in vivo and imparted significant tissue regeneration to healed cutaneous wounds, including increased tensile strength and hair neogenesis. MAP scaffolds recruit IL-33 type 2 myeloid cells, which is amplified in the presence of d -peptides. Remarkably, d -MAP elicited significant antigen-specific immunity against the d -chiral peptides, and an intact adaptive immune system was required for the hydrogel-induced skin regeneration. These findings demonstrate that the generation of an adaptive immune response from a biomaterial is sufficient to induce cutaneous regenerative healing despite faster scaffold degradation. Main The goal of regenerative medicine is to restore tissue function back to physiological activity. For biomaterial scaffolds, the optimal strategy to achieve this requires balancing material degradation with tissue regrowth. Clinical and patient factors contribute to a wide variation in chemical and physical parameters in situ, which makes striking a degradative–regenerative balance particularly difficult. Our recent development of a flowable, granular biomaterial, that is, a microporous annealed particle (MAP) gel, provides a new approach to make the balance more feasible 1 . The MAP gel is composed of randomly packed microsphere building blocks with a continuous network of interconnected micrometre-scale void spaces that allows for the infiltration of surrounding tissue without the prerequisite of material degradation 1 , 2 . This unique design resulted in improved tissue closure and improved vascularization relative to a nanoporous (but chemically equivalent formulation) hydrogel in a cutaneous wound model 1 . Mechanical support to the growing tissue by scaffolds is inherently impacted by the degradation rate of the scaffold 3 . For MAP scaffolds, degradation leads to a slow loss of porosity and reduced tissue ingrowth prior to dissolution. We hypothesized that slowing the degradation rate of MAP scaffolds would maintain the porosity and influence both wound closure rate and regenerated tissue quality. Changing the chirality of peptide moieties leads to a diminished degradation rate by endogenously present enzymes 4 , 5 . The use of chirality was made more attractive by the fact that polypeptides of d -enantiomeric amino acids do not typically elicit a robust immune response and are considered poorly immunogenic 5 . Previously, we used amino acid chirality to tune the proteolysis rate of peptide nanocapsules for the controlled release of encapsulated growth factors 4 . Therefore, we chose to use an analogous approach to slow the enzymatic degradation of our MAP scaffold by switching the chirality of the peptide crosslinker (for example, l - to d -chirality at the site of matrix metalloprotease (MMP)-mediated bond cleavage). We hypothesized that this approach would maintain the hydrogel microenvironment (for example, charge-based interactions and hydrophobicity) as it increased the long-term hydrogel integrity to allow a full infiltration of cells, and thus provide a greater integration of the entire construct with the host tissue. In the current study, we investigated how MAP hydrogels crosslinked with either d - or l -amino acid crosslinking peptides affect wound healing and skin regenerative responses using murine wound models. We provide evidence that activation of specific immune responses by the d -amino acid crosslinked MAP hydrogels elicits skin regeneration. Although immunity undoubtedly activates the foreign body response and eventual fibrosis of some implanted biomaterials 6 , 7 , the activation of the correct immune responses may enhance the regenerative ability of a biomaterial 8 , 9 . d -chiral crosslinker peptides slow MAP degradation in vitro We first used enantiomeric peptides to change the degradation rate without changing the initial material properties (for example, hydrophobicity, mesh size and charge) of the hydrogel 4 . All amino acids at the site of the enzymatic cleavage for the MMP-degradable peptide were changed to d -amino acids (Ac-GCRDGPQ d GI d W d GQDRCG-NH 2 , d -peptide). We matched the stiffness (that is, storage modulus) by rheology of both the d -peptide MAP ( d -MAP) and l -peptide ( l -MAP) formulations to that used in our previous MAP-based cutaneous application (~500 Pa; Fig. 1a ). After formulation optimization, we generated the microsphere particles using a previously published microfluidic technique 1 . Following the application of collagenase I to l -MAP, d -MAP or a 50% mixture of d -MAP and l -MAP (1:1 l/d -MAP), the l -MAP hydrogel degraded within minutes, whereas the degradation of the d -MAP by itself or within a mixture with l -MAP was minimal even after one hour (Fig. 1b and Supplementary Fig. 1 ). Fig. 1: d -MAP hydrogel degradation is enhanced in wounds of SKH1 hairless mice. a , Rheological characterization of MAP hydrogels composed of l or d -peptide crosslinked microgels. The r ratio (ratio of sulfydryl (SH) to vinyl sulfone (VS)) used to form the microgels was changed to arrive at the same storage modulus for both l - and d -MAP scaffolds. NS, no statistical significance between the l -MAP scaffold to the d -MAP scaffold indicated using a two-tailed Student’s t -test. b , Fabricated l- or d- hydrogels were tested for in vitro enzymolysis behaviour through exposure to a solution of collagenase I (5 U ml –1 ). c – f , Representative low-power view of H&E sections from healed skin 21 days after splinted excisional wounding in SKH1 mice treated by from sham ( c ), l -MAP ( d ), d -MAP ( e ) and a 1:1 mixture of l -MAP and d -MAP ( f ). g – i , Histologic quantification of dermal thickness including gels ( g ) (mm), hair follicles ( h ) and sebaceous glands ( i ). Each point represents the average", "role": "user" }, { "content": "Researchers at Duke University and the University of California, Los Angeles, have developed a biomaterial that significantly reduces scar formation after wounding, leading to more effective skin healing. This new material, which quickly degrades once the wound has closed, demonstrates that activating an adaptive immune response can trigger regenerative wound healing, leaving behind stronger and healthier healed skin. This work builds on the team's previous research with hydrogel scaffolds, which create a structure to support tissue growth, accelerating wound healing. In their new study, the team showed that a modified version of this hydrogel activates a regenerative immune response, which can potentially help heal skin injuries like burns, cuts, diabetic ulcers and other wounds that normally heal with significant scars that are more susceptible to reinjury. This research appears online on November 9, 2020 in the journal Nature Materials. \"The body forms scar tissue as fast as possible to reduce the chance of infection, to reduce pain, and, in larger wounds, to avoid water loss through evaporation,\" said Maani Archang, a first author on the paper and an MD/Ph.D. student in the Scumpia and Di Carlo labs at UCLA. \"It's a natural process of wound healing.\" Current wound-healing hydrogels available for clinical use sit on the surface of the wound, where they act as a dressing and help prevent the wound from drying out. That in turn helps the wound heal faster, generally via scar formation. In their 2015 Nature Materials paper, the research team, helmed by Duke's Tatiana Segura and UCLA's Dino Di Carlo, developed microporous annealed particle (MAP) hydrogels, which are a microparticle-based biomaterial that can integrate into the wound rather than sit on the skin's surface. The beads within the MAP gel link together but leave open spaces, creating a porous structure that provides a support for cells as they grow across the wound site. As the wound closes, the gel slowly dissolves, leaving behind healed skin. Although the MAP hydrogels allowed for rapid cellular growth and faster repair, the team noticed that the healed skin had limited complex structures like hair follicles and sebaceous glands. The team was curious whether they could alter their biomaterial to improve the quality of the healed skin. \"Previously we'd seen that as the wound started to heal, the MAP gel started to lose porosity, which limited how the tissue could grow through the structure,\" says Don Griffin, an assistant professor at the University of Virginia who is a first author on the paper and a former postdoctoral fellow in the Segura Lab. \"We hypothesized that slowing down the degradation rate of the MAP scaffold would prevent the pores from closing and provide additional support to the tissue as it grows, which would improve the tissue's quality.\" Rather than create an entirely new gel with new materials, the team instead focused on the chemical linker that allowed the scaffold to be naturally broken down by the body. In their original MAP gels, this chemical linker is composed of an amino acid sequence taken from the body's own structural proteins and arranged in a chemical orientation called L chirality. Because this peptide sequence and orientation is common throughout the body, this helps the gel avoid triggering a strong immune response, but it also enables ready degradation through naturally present enzymes. \"Our body has evolved to recognize and degrade this amino acid structure, so we theorized that if we flipped the structure to its mirror image, which is D chirality, the body would have a harder time degrading the scaffold,\" said Segura, a professor of biomedical engineering at Duke. \"But when we put the hydrogel into a mouse wound, the updated gel ended up doing the exact opposite.\" The updated material integrated into the wound and supported the tissue as the wound closed. But instead of lasting longer, the team discovered that the new gel had almost entirely disappeared from the wound site, leaving behind just a few particles. However, the healed skin turned out to be stronger and included complex skin structures that are typically absent in scars. After further investigation, the researchers discovered that the reason for the stronger healing—despite the lack of longevity—was a different immune response to the gel. After a skin injury, the body's innate immune response is immediately activated to ensure that any foreign substances that enter the body are quickly destroyed. If substances can escape this first immune response, the body's adaptive immune response kicks in, which identifies and targets the invading material with more specificity. Because the original MAP gel was made with the common L peptide structure, it generated a mild innate immune response. But when the team placed the reformulated gel into a wound, the foreign D chirality activated the adaptive immune system, which created antibodies and activated cells including macrophages that targeted and cleared out the gel more quickly after the wound closed. \"There are two types of immune responses that can occur after injury—a destructive response and a more mild regenerative response,\" said Scumpia, an assistant professor in the division of dermatology at UCLA Health and the West Los Angeles VA Medical Center. \"When most biomaterials are placed in the body, they are walled off by the immune system and eventually degraded or destroyed. But in this study, the immune response to the gel induced a regenerative response in the healed tissue.\" \"This study shows us that activating the immune system can be used to tilt the balance of wound healing from tissue destruction and scar formation to tissue repair and skin regeneration,\" said Segura. Working with Maksim Plikus, a regenerative tissue expert at the University of California, Irvine, the team also confirmed that key structures, like hair follicles and sebaceous glands, were correctly forming over the scaffold. When the team dug into the mechanism, they found that the cells of the adaptive immune system are required for this regenerative response. As the team continues to study the regenerative immune response to their gel, they are also exploring the possibility of using the new MAP hydrogel as an immunomodulatory platform. \"The team is now exploring the best way to release immune signals from the gel to either induce skin regeneration or develop the hydrogel as a vaccine platform,\" said Scumpia. \"I am excited about the possibility of designing materials that can directly interact with the immune system to support tissue regeneration\" said Segura. \"This is a new approach for us.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Microporous annealed particle (MAP) scaffolds are flowable, in situ crosslinked, microporous scaffolds composed of microgel building blocks and were previously shown to accelerate wound healing. To promote more extensive tissue ingrowth before scaffold degradation, we aimed to slow MAP degradation by switching the chirality of the crosslinking peptides from l - to d -amino acids. Unexpectedly, despite showing the predicted slower enzymatic degradation in vitro, d -peptide crosslinked MAP hydrogel ( d -MAP) hastened material degradation in vivo and imparted significant tissue regeneration to healed cutaneous wounds, including increased tensile strength and hair neogenesis. MAP scaffolds recruit IL-33 type 2 myeloid cells, which is amplified in the presence of d -peptides. Remarkably, d -MAP elicited significant antigen-specific immunity against the d -chiral peptides, and an intact adaptive immune system was required for the hydrogel-induced skin regeneration. These findings demonstrate that the generation of an adaptive immune response from a biomaterial is sufficient to induce cutaneous regenerative healing despite faster scaffold degradation. Main The goal of regenerative medicine is to restore tissue function back to physiological activity. For biomaterial scaffolds, the optimal strategy to achieve this requires balancing material degradation with tissue regrowth. Clinical and patient factors contribute to a wide variation in chemical and physical parameters in situ, which makes striking a degradative–regenerative balance particularly difficult. Our recent development of a flowable, granular biomaterial, that is, a microporous annealed particle (MAP) gel, provides a new approach to make the balance more feasible 1 . The MAP gel is composed of randomly packed microsphere building blocks with a continuous network of interconnected micrometre-scale void spaces that allows for the infiltration of surrounding tissue without the prerequisite of material degradation 1 , 2 . This unique design resulted in improved tissue closure and improved vascularization relative to a nanoporous (but chemically equivalent formulation) hydrogel in a cutaneous wound model 1 . Mechanical support to the growing tissue by scaffolds is inherently impacted by the degradation rate of the scaffold 3 . For MAP scaffolds, degradation leads to a slow loss of porosity and reduced tissue ingrowth prior to dissolution. We hypothesized that slowing the degradation rate of MAP scaffolds would maintain the porosity and influence both wound closure rate and regenerated tissue quality. Changing the chirality of peptide moieties leads to a diminished degradation rate by endogenously present enzymes 4 , 5 . The use of chirality was made more attractive by the fact that polypeptides of d -enantiomeric amino acids do not typically elicit a robust immune response and are considered poorly immunogenic 5 . Previously, we used amino acid chirality to tune the proteolysis rate of peptide nanocapsules for the controlled release of encapsulated growth factors 4 . Therefore, we chose to use an analogous approach to slow the enzymatic degradation of our MAP scaffold by switching the chirality of the peptide crosslinker (for example, l - to d -chirality at the site of matrix metalloprotease (MMP)-mediated bond cleavage). We hypothesized that this approach would maintain the hydrogel microenvironment (for example, charge-based interactions and hydrophobicity) as it increased the long-term hydrogel integrity to allow a full infiltration of cells, and thus provide a greater integration of the entire construct with the host tissue. In the current study, we investigated how MAP hydrogels crosslinked with either d - or l -amino acid crosslinking peptides affect wound healing and skin regenerative responses using murine wound models. We provide evidence that activation of specific immune responses by the d -amino acid crosslinked MAP hydrogels elicits skin regeneration. Although immunity undoubtedly activates the foreign body response and eventual fibrosis of some implanted biomaterials 6 , 7 , the activation of the correct immune responses may enhance the regenerative ability of a biomaterial 8 , 9 . d -chiral crosslinker peptides slow MAP degradation in vitro We first used enantiomeric peptides to change the degradation rate without changing the initial material properties (for example, hydrophobicity, mesh size and charge) of the hydrogel 4 . All amino acids at the site of the enzymatic cleavage for the MMP-degradable peptide were changed to d -amino acids (Ac-GCRDGPQ d GI d W d GQDRCG-NH 2 , d -peptide). We matched the stiffness (that is, storage modulus) by rheology of both the d -peptide MAP ( d -MAP) and l -peptide ( l -MAP) formulations to that used in our previous MAP-based cutaneous application (~500 Pa; Fig. 1a ). After formulation optimization, we generated the microsphere particles using a previously published microfluidic technique 1 . Following the application of collagenase I to l -MAP, d -MAP or a 50% mixture of d -MAP and l -MAP (1:1 l/d -MAP), the l -MAP hydrogel degraded within minutes, whereas the degradation of the d -MAP by itself or within a mixture with l -MAP was minimal even after one hour (Fig. 1b and Supplementary Fig. 1 ). Fig. 1: d -MAP hydrogel degradation is enhanced in wounds of SKH1 hairless mice. a , Rheological characterization of MAP hydrogels composed of l or d -peptide crosslinked microgels. The r ratio (ratio of sulfydryl (SH) to vinyl sulfone (VS)) used to form the microgels was changed to arrive at the same storage modulus for both l - and d -MAP scaffolds. NS, no statistical significance between the l -MAP scaffold to the d -MAP scaffold indicated using a two-tailed Student’s t -test. b , Fabricated l- or d- hydrogels were tested for in vitro enzymolysis behaviour through exposure to a solution of collagenase I (5 U ml –1 ). c – f , Representative low-power view of H&E sections from healed skin 21 days after splinted excisional wounding in SKH1 mice treated by from sham ( c ), l -MAP ( d ), d -MAP ( e ) and a 1:1 mixture of l -MAP and d -MAP ( f ). g – i , Histologic quantification of dermal thickness including gels ( g ) (mm), hair follicles ( h ) and sebaceous glands ( i ). Each point represents the average<|im_end|> <|im_start|>assistant Researchers at Duke University and the University of California, Los Angeles, have developed a biomaterial that significantly reduces scar formation after wounding, leading to more effective skin healing. This new material, which quickly degrades once the wound has closed, demonstrates that activating an adaptive immune response can trigger regenerative wound healing, leaving behind stronger and healthier healed skin. This work builds on the team's previous research with hydrogel scaffolds, which create a structure to support tissue growth, accelerating wound healing. In their new study, the team showed that a modified version of this hydrogel activates a regenerative immune response, which can potentially help heal skin injuries like burns, cuts, diabetic ulcers and other wounds that normally heal with significant scars that are more susceptible to reinjury. This research appears online on November 9, 2020 in the journal Nature Materials. "The body forms scar tissue as fast as possible to reduce the chance of infection, to reduce pain, and, in larger wounds, to avoid water loss through evaporation," said Maani Archang, a first author on the paper and an MD/Ph.D. student in the Scumpia and Di Carlo labs at UCLA. "It's a natural process of wound healing." Current wound-healing hydrogels available for clinical use sit on the surface of the wound, where they act as a dressing and help prevent the wound from drying out. That in turn helps the wound heal faster, generally via scar formation. In their 2015 Nature Materials paper, the research team, helmed by Duke's Tatiana Segura and UCLA's Dino Di Carlo, developed microporous annealed particle (MAP) hydrogels, which are a microparticle-based biomaterial that can integrate into the wound rather than sit on the skin's surface. The beads within the MAP gel link together but leave open spaces, creating a porous structure that provides a support for cells as they grow across the wound site. As the wound closes, the gel slowly dissolves, leaving behind healed skin. Although the MAP hydrogels allowed for rapid cellular growth and faster repair, the team noticed that the healed skin had limited complex structures like hair follicles and sebaceous glands. The team was curious whether they could alter their biomaterial to improve the quality of the healed skin. "Previously we'd seen that as the wound started to heal, the MAP gel started to lose porosity, which limited how the tissue could grow through the structure," says Don Griffin, an assistant professor at the University of Virginia who is a first author on the paper and a former postdoctoral fellow in the Segura Lab. "We hypothesized that slowing down the degradation rate of the MAP scaffold would prevent the pores from closing and provide additional support to the tissue as it grows, which would improve the tissue's quality." Rather than create an entirely new gel with new materials, the team instead focused on the chemical linker that allowed the scaffold to be naturally broken down by the body. In their original MAP gels, this chemical linker is composed of an amino acid sequence taken from the body's own structural proteins and arranged in a chemical orientation called L chirality. Because this peptide sequence and orientation is common throughout the body, this helps the gel avoid triggering a strong immune response, but it also enables ready degradation through naturally present enzymes. "Our body has evolved to recognize and degrade this amino acid structure, so we theorized that if we flipped the structure to its mirror image, which is D chirality, the body would have a harder time degrading the scaffold," said Segura, a professor of biomedical engineering at Duke. "But when we put the hydrogel into a mouse wound, the updated gel ended up doing the exact opposite." The updated material integrated into the wound and supported the tissue as the wound closed. But instead of lasting longer, the team discovered that the new gel had almost entirely disappeared from the wound site, leaving behind just a few particles. However, the healed skin turned out to be stronger and included complex skin structures that are typically absent in scars. After further investigation, the researchers discovered that the reason for the stronger healing—despite the lack of longevity—was a different immune response to the gel. After a skin injury, the body's innate immune response is immediately activated to ensure that any foreign substances that enter the body are quickly destroyed. If substances can escape this first immune response, the body's adaptive immune response kicks in, which identifies and targets the invading material with more specificity. Because the original MAP gel was made with the common L peptide structure, it generated a mild innate immune response. But when the team placed the reformulated gel into a wound, the foreign D chirality activated the adaptive immune system, which created antibodies and activated cells including macrophages that targeted and cleared out the gel more quickly after the wound closed. "There are two types of immune responses that can occur after injury—a destructive response and a more mild regenerative response," said Scumpia, an assistant professor in the division of dermatology at UCLA Health and the West Los Angeles VA Medical Center. "When most biomaterials are placed in the body, they are walled off by the immune system and eventually degraded or destroyed. But in this study, the immune response to the gel induced a regenerative response in the healed tissue." "This study shows us that activating the immune system can be used to tilt the balance of wound healing from tissue destruction and scar formation to tissue repair and skin regeneration," said Segura. Working with Maksim Plikus, a regenerative tissue expert at the University of California, Irvine, the team also confirmed that key structures, like hair follicles and sebaceous glands, were correctly forming over the scaffold. When the team dug into the mechanism, they found that the cells of the adaptive immune system are required for this regenerative response. As the team continues to study the regenerative immune response to their gel, they are also exploring the possibility of using the new MAP hydrogel as an immunomodulatory platform. "The team is now exploring the best way to release immune signals from the gel to either induce skin regeneration or develop the hydrogel as a vaccine platform," said Scumpia. "I am excited about the possibility of designing materials that can directly interact with the immune system to support tissue regeneration" said Segura. "This is a new approach for us." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 28095, 897, 20857, 86997, 5962, 19320, 320, 18082, 8, 57250, 18938, 527, 6530, 481, 11, 304, 10109, 5425, 44233, 11, 19748, 897, 20857, 57250, 18938, 24306, 315, 8162, 29952, 4857, 10215, 323, 1051, 8767, 6982, 311, 43880, 27653, 21730, 13, 2057, 12192, 810, 16781, 20438, 6892, 19632, 1603, 85552, 53568, 11, 584, 20034, 311, 6435, 28322, 53568, 555, 28865, 279, 71546, 2786, 315, 279, 5425, 2125, 287, 96434, 505, 326, 482, 311, 294, 482, 309, 3394, 33969, 13, 71500, 398, 11, 8994, 9204, 279, 19698, 29493, 32011, 780, 53568, 304, 55004, 11, 294, 482, 375, 47309, 5425, 44233, 28322, 17055, 29952, 320, 294, 482, 18082, 8, 34143, 6901, 3769, 53568, 304, 41294, 323, 70772, 291, 5199, 20438, 60517, 311, 62320, 4018, 18133, 34254, 11, 2737, 7319, 22781, 458, 8333, 323, 7013, 841, 52379, 13, 28322, 57250, 18938, 20927, 11598, 12, 1644, 955, 220, 17, 856, 301, 590, 7917, 11, 902, 374, 83598, 304, 279, 9546, 315, 294, 482, 375, 74489, 13, 83833, 2915, 11, 294, 482, 18082, 95360, 1639, 5199, 83089, 19440, 40368, 2403, 279, 294, 482, 331, 37478, 96434, 11, 323, 459, 35539, 48232, 22852, 1887, 574, 2631, 369, 279, 17055, 29952, 38973, 6930, 60517, 13, 4314, 14955, 20461, 430, 279, 9659, 315, 459, 48232, 22852, 2077, 505, 264, 39538, 2229, 374, 14343, 311, 49853, 4018, 18133, 1239, 75989, 21730, 8994, 10819, 85552, 53568, 13, 4802, 578, 5915, 315, 1239, 75989, 16088, 374, 311, 15301, 20438, 734, 1203, 311, 53194, 5820, 13, 1789, 39538, 2229, 57250, 18938, 11, 279, 23669, 8446, 311, 11322, 420, 7612, 44463, 3769, 53568, 449, 20438, 1239, 19632, 13, 33135, 323, 8893, 9547, 17210, 311, 264, 7029, 23851, 304, 11742, 323, 7106, 5137, 304, 10109, 11, 902, 3727, 21933, 264, 409, 6902, 1413, 4235, 1610, 75989, 8335, 8104, 5107, 13, 5751, 3293, 4500, 315, 264, 6530, 481, 11, 16109, 1299, 39538, 2229, 11, 430, 374, 11, 264, 19748, 897, 20857, 86997, 5962, 19320, 320, 18082, 8, 18316, 11, 5825, 264, 502, 5603, 311, 1304, 279, 8335, 810, 43303, 220, 16, 662, 578, 28322, 18316, 374, 24306, 315, 27716, 19937, 8162, 88510, 4857, 10215, 449, 264, 19815, 4009, 315, 83416, 19748, 442, 47987, 13230, 742, 12908, 430, 6276, 369, 279, 98835, 315, 14932, 20438, 2085, 279, 80884, 315, 3769, 53568, 220, 16, 1174, 220, 17, 662, 1115, 5016, 2955, 19543, 304, 13241, 20438, 22722, 323, 13241, 64603, 2065, 8844, 311, 264, 76307, 20857, 320, 8248, 8590, 2740, 13890, 55986, 8, 17055, 29952, 304, 264, 4018, 18133, 27653, 1646, 220, 16, 662, 51684, 1862, 311, 279, 7982, 20438, 555, 57250, 18938, 374, 49188, 40028, 555, 279, 53568, 4478, 315, 279, 85552, 220, 18, 662, 1789, 28322, 57250, 18938, 11, 53568, 11767, 311, 264, 6435, 4814, 315, 4247, 22828, 323, 11293, 20438, 6892, 19632, 4972, 311, 81359, 13, 1226, 22601, 83979, 430, 48408, 279, 53568, 4478, 315, 28322, 57250, 18938, 1053, 10519, 279, 4247, 22828, 323, 10383, 2225, 27653, 22722, 4478, 323, 71453, 20438, 4367, 13, 51269, 279, 71546, 2786, 315, 72249, 4647, 32606, 11767, 311, 264, 54182, 53568, 4478, 555, 842, 11968, 7162, 3118, 56067, 220, 19, 1174, 220, 20, 662, 578, 1005, 315, 71546, 2786, 574, 1903, 810, 19411, 555, 279, 2144, 430, 1499, 500, 74489, 315, 294, 482, 268, 15719, 316, 11893, 42500, 33969, 656, 539, 11383, 658, 19195, 264, 22514, 22852, 2077, 323, 527, 6646, 31555, 33119, 29569, 220, 20, 662, 59787, 11, 584, 1511, 42500, 13935, 71546, 2786, 311, 26306, 279, 5541, 337, 4548, 4478, 315, 72249, 20622, 511, 2690, 2482, 369, 279, 14400, 4984, 315, 43669, 7913, 6650, 9547, 220, 19, 662, 15636, 11, 584, 14896, 311, 1005, 459, 79283, 5603, 311, 6435, 279, 32011, 780, 53568, 315, 1057, 28322, 85552, 555, 28865, 279, 71546, 2786, 315, 279, 72249, 5425, 2125, 261, 320, 2000, 3187, 11, 326, 482, 311, 294, 482, 331, 404, 2786, 520, 279, 2816, 315, 6303, 9501, 385, 782, 668, 521, 320, 44, 5901, 7435, 4503, 660, 11049, 11551, 68256, 570, 1226, 22601, 83979, 430, 420, 5603, 1053, 10519, 279, 17055, 29952, 8162, 24175, 320, 2000, 3187, 11, 6900, 6108, 22639, 323, 17055, 764, 31906, 488, 8, 439, 433, 7319, 279, 1317, 9860, 17055, 29952, 17025, 311, 2187, 264, 2539, 98835, 315, 7917, 11, 323, 8617, 3493, 264, 7191, 18052, 315, 279, 4553, 9429, 449, 279, 3552, 20438, 13, 763, 279, 1510, 4007, 11, 584, 27313, 1268, 28322, 17055, 70, 2053, 5425, 44233, 449, 3060, 294, 482, 477, 326, 482, 309, 3394, 13935, 5425, 2125, 287, 96434, 7958, 27653, 21730, 323, 6930, 1239, 75989, 14847, 1701, 8309, 483, 27653, 4211, 13, 1226, 3493, 6029, 430, 15449, 315, 3230, 22852, 14847, 555, 279, 294, 482, 309, 3394, 13935, 5425, 44233, 28322, 17055, 70, 2053, 658, 51650, 6930, 60517, 13, 10541, 40368, 38048, 75042, 279, 7362, 2547, 2077, 323, 42835, 16178, 63412, 315, 1063, 95956, 39538, 2229, 82, 220, 21, 1174, 220, 22, 1174, 279, 15449, 315, 279, 4495, 22852, 14847, 1253, 18885, 279, 1239, 75989, 5845, 315, 264, 39538, 2229, 220, 23, 1174, 220, 24, 662, 294, 482, 331, 37478, 5425, 2125, 261, 96434, 6435, 28322, 53568, 304, 55004, 1226, 1176, 1511, 665, 15719, 316, 11893, 96434, 311, 2349, 279, 53568, 4478, 2085, 10223, 279, 2926, 3769, 6012, 320, 2000, 3187, 11, 17055, 764, 31906, 488, 11, 11546, 1404, 323, 6900, 8, 315, 279, 17055, 29952, 220, 19, 662, 2052, 42500, 33969, 520, 279, 2816, 315, 279, 32011, 780, 11551, 68256, 369, 279, 90304, 6953, 78130, 72249, 1051, 5614, 311, 294, 482, 309, 3394, 33969, 320, 11916, 12279, 9150, 35, 25434, 48, 294, 49609, 294, 468, 294, 480, 48, 35, 7532, 38, 11500, 39, 220, 17, 1174, 294, 482, 375, 47309, 570, 1226, 18545, 279, 70334, 320, 9210, 374, 11, 5942, 75124, 8, 555, 68132, 2508, 315, 2225, 279, 294, 482, 375, 47309, 28322, 320, 294, 482, 18082, 8, 323, 326, 482, 375, 47309, 320, 326, 482, 18082, 8, 98077, 311, 430, 1511, 304, 1057, 3766, 28322, 6108, 4018, 18133, 3851, 31857, 2636, 16056, 26, 23966, 13, 220, 16, 64, 7609, 4740, 55986, 26329, 11, 584, 8066, 279, 8162, 88510, 19252, 1701, 264, 8767, 4756, 8162, 67125, 292, 15105, 220, 16, 662, 23548, 279, 3851, 315, 71313, 521, 358, 311, 326, 482, 18082, 11, 294, 482, 18082, 477, 264, 220, 1135, 4, 21655, 315, 294, 482, 18082, 323, 326, 482, 18082, 320, 16, 25, 16, 326, 3529, 482, 18082, 705, 279, 326, 482, 18082, 17055, 29952, 91978, 2949, 4520, 11, 20444, 279, 53568, 315, 279, 294, 482, 18082, 555, 5196, 477, 2949, 264, 21655, 449, 326, 482, 18082, 574, 17832, 1524, 1306, 832, 6596, 320, 30035, 13, 220, 16, 65, 323, 99371, 23966, 13, 220, 16, 7609, 23966, 13, 220, 16, 25, 294, 482, 18082, 17055, 29952, 53568, 374, 24872, 304, 34254, 315, 12343, 39, 16, 7013, 1752, 24548, 13, 264, 1174, 71636, 5848, 60993, 315, 28322, 17055, 70, 2053, 24306, 315, 326, 477, 294, 482, 375, 47309, 5425, 44233, 8162, 70, 2053, 13, 578, 436, 11595, 320, 46458, 315, 40769, 41221, 894, 75, 320, 8758, 8, 311, 34549, 40769, 606, 320, 27142, 595, 1511, 311, 1376, 279, 8162, 70, 2053, 574, 5614, 311, 17782, 520, 279, 1890, 5942, 75124, 369, 2225, 326, 482, 323, 294, 482, 18082, 57250, 18938, 13, 3119, 11, 912, 29564, 26431, 1990, 279, 326, 482, 18082, 85552, 311, 279, 294, 482, 18082, 85552, 16717, 1701, 264, 1403, 2442, 5805, 11988, 753, 259, 482, 1985, 13, 293, 1174, 37407, 660, 326, 12, 477, 294, 12, 17055, 70, 2053, 1051, 12793, 369, 304, 55004, 32011, 337, 4548, 17432, 1555, 14675, 311, 264, 6425, 315, 71313, 521, 358, 320, 20, 549, 16116, 1389, 16, 7609, 272, 1389, 282, 1174, 38366, 3428, 27624, 1684, 315, 473, 69248, 14491, 505, 62320, 6930, 220, 1691, 2919, 1306, 12786, 396, 291, 3521, 1854, 278, 289, 13900, 304, 12343, 39, 16, 24548, 12020, 555, 505, 72976, 320, 272, 7026, 326, 482, 18082, 320, 294, 7026, 294, 482, 18082, 320, 384, 883, 323, 264, 220, 16, 25, 16, 21655, 315, 326, 482, 18082, 323, 294, 482, 18082, 320, 282, 7609, 342, 1389, 602, 1174, 67005, 39227, 10484, 2461, 315, 2761, 14991, 26839, 2737, 342, 2053, 320, 342, 883, 320, 3906, 705, 7013, 82714, 645, 320, 305, 883, 323, 103382, 77140, 82375, 320, 602, 7609, 9062, 1486, 11105, 279, 5578, 128257, 198, 128256, 78191, 198, 60210, 520, 27453, 3907, 323, 279, 3907, 315, 7188, 11, 9853, 12167, 11, 617, 8040, 264, 39538, 2229, 430, 12207, 26338, 23087, 18488, 1306, 289, 13900, 11, 6522, 311, 810, 7524, 6930, 21730, 13, 1115, 502, 3769, 11, 902, 6288, 409, 23142, 3131, 279, 27653, 706, 8036, 11, 32216, 430, 72192, 459, 48232, 22852, 2077, 649, 8346, 1239, 75989, 27653, 21730, 11, 9564, 4920, 16643, 323, 39345, 62320, 6930, 13, 1115, 990, 22890, 389, 279, 2128, 596, 3766, 3495, 449, 17055, 29952, 57250, 18938, 11, 902, 1893, 264, 6070, 311, 1862, 20438, 6650, 11, 69741, 27653, 21730, 13, 763, 872, 502, 4007, 11, 279, 2128, 8710, 430, 264, 11041, 2373, 315, 420, 17055, 29952, 75042, 264, 1239, 75989, 22852, 2077, 11, 902, 649, 13893, 1520, 27661, 6930, 15319, 1093, 44154, 11, 15455, 11, 71975, 8725, 17254, 323, 1023, 34254, 430, 14614, 27661, 449, 5199, 61699, 430, 527, 810, 47281, 311, 15601, 42861, 13, 1115, 3495, 8111, 2930, 389, 6841, 220, 24, 11, 220, 2366, 15, 304, 279, 8486, 22037, 32009, 13, 330, 791, 2547, 7739, 23087, 20438, 439, 5043, 439, 3284, 311, 8108, 279, 6140, 315, 19405, 11, 311, 8108, 6784, 11, 323, 11, 304, 8294, 34254, 11, 311, 5766, 3090, 4814, 1555, 3721, 96649, 1359, 1071, 11583, 5676, 9683, 526, 11, 264, 1176, 3229, 389, 279, 5684, 323, 459, 14306, 14, 3438, 920, 13, 5575, 304, 279, 2522, 1538, 689, 323, 7923, 58870, 51048, 520, 50751, 13, 330, 2181, 596, 264, 5933, 1920, 315, 27653, 21730, 1210, 9303, 27653, 38435, 6260, 17055, 70, 2053, 2561, 369, 14830, 1005, 2503, 389, 279, 7479, 315, 279, 27653, 11, 1405, 814, 1180, 439, 264, 32623, 323, 1520, 5471, 279, 27653, 505, 46479, 704, 13, 3011, 304, 2543, 8779, 279, 27653, 27661, 10819, 11, 8965, 4669, 23087, 18488, 13, 763, 872, 220, 679, 20, 22037, 32009, 5684, 11, 279, 3495, 2128, 11, 11591, 2106, 555, 27453, 596, 63567, 12699, 17652, 5808, 323, 50751, 596, 423, 3394, 7923, 58870, 11, 8040, 19748, 897, 20857, 86997, 5962, 19320, 320, 18082, 8, 17055, 70, 2053, 11, 902, 527, 264, 19748, 897, 7203, 6108, 39538, 2229, 430, 649, 32172, 1139, 279, 27653, 4856, 1109, 2503, 389, 279, 6930, 596, 7479, 13, 578, 55308, 2949, 279, 28322, 18316, 2723, 3871, 719, 5387, 1825, 12908, 11, 6968, 264, 94761, 6070, 430, 5825, 264, 1862, 369, 7917, 439, 814, 3139, 4028, 279, 27653, 2816, 13, 1666, 279, 27653, 34350, 11, 279, 18316, 14297, 14091, 18685, 11, 9564, 4920, 62320, 6930, 13, 10541, 279, 28322, 17055, 70, 2053, 5535, 369, 11295, 35693, 6650, 323, 10819, 13023, 11, 279, 2128, 14000, 430, 279, 62320, 6930, 1047, 7347, 6485, 14726, 1093, 7013, 82714, 645, 323, 103382, 77140, 82375, 13, 578, 2128, 574, 22999, 3508, 814, 1436, 11857, 872, 39538, 2229, 311, 7417, 279, 4367, 315, 279, 62320, 6930, 13, 330, 83039, 584, 4265, 3970, 430, 439, 279, 27653, 3940, 311, 27661, 11, 279, 28322, 18316, 3940, 311, 9229, 4247, 22828, 11, 902, 7347, 1268, 279, 20438, 1436, 3139, 1555, 279, 6070, 1359, 2795, 4418, 41496, 11, 459, 18328, 14561, 520, 279, 3907, 315, 13286, 889, 374, 264, 1176, 3229, 389, 279, 5684, 323, 264, 4846, 1772, 38083, 278, 12637, 304, 279, 17652, 5808, 11868, 13, 330, 1687, 22601, 83979, 430, 48408, 1523, 279, 53568, 4478, 315, 279, 28322, 85552, 1053, 5471, 279, 72028, 505, 15676, 323, 3493, 5217, 1862, 311, 279, 20438, 439, 433, 28815, 11, 902, 1053, 7417, 279, 20438, 596, 4367, 1210, 26848, 1109, 1893, 459, 11622, 502, 18316, 449, 502, 7384, 11, 279, 2128, 4619, 10968, 389, 279, 11742, 86845, 430, 5535, 279, 85552, 311, 387, 18182, 11102, 1523, 555, 279, 2547, 13, 763, 872, 4113, 28322, 342, 2053, 11, 420, 11742, 86845, 374, 24306, 315, 459, 42500, 13935, 8668, 4529, 505, 279, 2547, 596, 1866, 24693, 28896, 323, 28902, 304, 264, 11742, 17140, 2663, 445, 71546, 2786, 13, 9393, 420, 72249, 8668, 323, 17140, 374, 4279, 6957, 279, 2547, 11, 420, 8779, 279, 18316, 5766, 52605, 264, 3831, 22852, 2077, 11, 719, 433, 1101, 20682, 5644, 53568, 1555, 18182, 3118, 56067, 13, 330, 8140, 2547, 706, 28995, 311, 15641, 323, 96630, 420, 42500, 13935, 6070, 11, 779, 584, 46820, 1534, 430, 422, 584, 47180, 279, 6070, 311, 1202, 18327, 2217, 11, 902, 374, 423, 71546, 2786, 11, 279, 2547, 1053, 617, 264, 16127, 892, 409, 33359, 279, 85552, 1359, 1071, 17652, 5808, 11, 264, 14561, 315, 94612, 15009, 520, 27453, 13, 330, 4071, 994, 584, 2231, 279, 17055, 29952, 1139, 264, 8814, 27653, 11, 279, 6177, 18316, 9670, 709, 3815, 279, 4839, 14329, 1210, 578, 6177, 3769, 18751, 1139, 279, 27653, 323, 7396, 279, 20438, 439, 279, 27653, 8036, 13, 2030, 4619, 315, 29869, 5129, 11, 279, 2128, 11352, 430, 279, 502, 18316, 1047, 4661, 11622, 29496, 505, 279, 27653, 2816, 11, 9564, 4920, 1120, 264, 2478, 19252, 13, 4452, 11, 279, 62320, 6930, 6656, 704, 311, 387, 16643, 323, 5343, 6485, 6930, 14726, 430, 527, 11383, 28310, 304, 61699, 13, 4740, 4726, 8990, 11, 279, 12074, 11352, 430, 279, 2944, 369, 279, 16643, 21730, 2345, 5919, 6100, 279, 6996, 315, 58219, 2345, 16514, 264, 2204, 22852, 2077, 311, 279, 18316, 13, 4740, 264, 6930, 11134, 11, 279, 2547, 596, 65070, 22852, 2077, 374, 7214, 22756, 311, 6106, 430, 904, 7362, 33155, 430, 3810, 279, 2547, 527, 6288, 14763, 13, 1442, 33155, 649, 12731, 420, 1176, 22852, 2077, 11, 279, 2547, 596, 48232, 22852, 2077, 37350, 304, 11, 902, 36611, 323, 11811, 279, 83631, 3769, 449, 810, 76041, 13, 9393, 279, 4113, 28322, 18316, 574, 1903, 449, 279, 4279, 445, 72249, 6070, 11, 433, 8066, 264, 23900, 65070, 22852, 2077, 13, 2030, 994, 279, 2128, 9277, 279, 15180, 7913, 18316, 1139, 264, 27653, 11, 279, 7362, 423, 71546, 2786, 22756, 279, 48232, 22852, 1887, 11, 902, 3549, 59854, 323, 22756, 7917, 2737, 18563, 764, 1154, 430, 17550, 323, 23803, 704, 279, 18316, 810, 6288, 1306, 279, 27653, 8036, 13, 330, 3947, 527, 1403, 4595, 315, 22852, 14847, 430, 649, 12446, 1306, 11134, 29096, 40652, 2077, 323, 264, 810, 23900, 1239, 75989, 2077, 1359, 1071, 2522, 1538, 689, 11, 459, 18328, 14561, 304, 279, 13096, 315, 61485, 2508, 520, 50751, 6401, 323, 279, 4410, 9853, 12167, 21571, 13235, 5955, 13, 330, 4599, 1455, 39538, 2229, 82, 527, 9277, 304, 279, 2547, 11, 814, 527, 289, 4841, 1022, 555, 279, 22852, 1887, 323, 9778, 91978, 477, 14763, 13, 2030, 304, 420, 4007, 11, 279, 22852, 2077, 311, 279, 18316, 36572, 264, 1239, 75989, 2077, 304, 279, 62320, 20438, 1210, 330, 2028, 4007, 5039, 603, 430, 72192, 279, 22852, 1887, 649, 387, 1511, 311, 37300, 279, 8335, 315, 27653, 21730, 505, 20438, 19814, 323, 23087, 18488, 311, 20438, 13023, 323, 6930, 60517, 1359, 1071, 17652, 5808, 13, 22938, 449, 386, 10011, 318, 393, 7792, 355, 11, 264, 1239, 75989, 20438, 6335, 520, 279, 3907, 315, 7188, 11, 72385, 11, 279, 2128, 1101, 11007, 430, 1401, 14726, 11, 1093, 7013, 82714, 645, 323, 103382, 77140, 82375, 11, 1051, 12722, 30164, 927, 279, 85552, 13, 3277, 279, 2128, 44120, 1139, 279, 17383, 11, 814, 1766, 430, 279, 7917, 315, 279, 48232, 22852, 1887, 527, 2631, 369, 420, 1239, 75989, 2077, 13, 1666, 279, 2128, 9731, 311, 4007, 279, 1239, 75989, 22852, 2077, 311, 872, 18316, 11, 814, 527, 1101, 24919, 279, 13336, 315, 1701, 279, 502, 28322, 17055, 29952, 439, 459, 33119, 316, 347, 38220, 5452, 13, 330, 791, 2128, 374, 1457, 24919, 279, 1888, 1648, 311, 4984, 22852, 17738, 505, 279, 18316, 311, 3060, 49853, 6930, 60517, 477, 2274, 279, 17055, 29952, 439, 264, 25474, 5452, 1359, 1071, 2522, 1538, 689, 13, 330, 40, 1097, 12304, 922, 279, 13336, 315, 30829, 7384, 430, 649, 6089, 16681, 449, 279, 22852, 1887, 311, 1862, 20438, 60517, 1, 1071, 17652, 5808, 13, 330, 2028, 374, 264, 502, 5603, 369, 603, 1210, 220, 128257, 198 ]

2,702

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Surface acoustic waves (SAWs) strongly modulate the shallow electric potential in piezoelectric materials. In semiconductor heterostructures such as GaAs/AlGaAs, SAWs can thus be employed to transfer individual electrons between distant quantum dots. This transfer mechanism makes SAW technologies a promising candidate to convey quantum information through a circuit of quantum logic gates. Here we present two essential building blocks of such a SAW-driven quantum circuit. First, we implement a directional coupler allowing to partition a flying electron arbitrarily into two paths of transportation. Second, we demonstrate a triggered single-electron source enabling synchronisation of the SAW-driven sending process. Exceeding a single-shot transfer efficiency of 99%, we show that a SAW-driven integrated circuit is feasible with single electrons on a large scale. Our results pave the way to perform quantum logic operations with flying electron qubits. Introduction DiVincenzo’s criteria for realising a quantum computer address the transmission of quantum information between stationary nodes 1 . Several approaches have demonstrated successful transmission of quantum states in solid-state devices such as in quantum dot (QD) arrays 2 , 3 , 4 , 5 , coupled QDs in quantum Hall edge channels 6 or microwave-coupled superconducting qubits 7 , 8 . In semiconductor heterostructures, surface acoustic waves (SAWs) offer a particularly interesting platform to transmit quantum information. Thanks to the shallow electric potential modulation on a piezoelectric substrate, a SAW forms a train of moving QDs along a depleted transport channel. This SAW train allows to drag single charge carriers from one side of such a quantum rail to the other. Employing stationary QDs as electron source and receiver, a single electron has been sent back and forth several micrometre long tracks with a transfer efficiency of about 92% 9 , 10 . Recently, SAW-driven transfer of individual spin polarised electrons has been reported 11 . These advances support the idea of a SAW-driven quantum circuit enabling the implementation of electron-quantum-optics experiments 12 , 13 , 14 and quantum computation schemes at the single-particle level 15 , 16 , 17 , 18 , 19 . The core of such a quantum circuit is a tunable beam-splitter permitting the coherent partitioning and coupling of single-flying electrons. In the past, coherent quantum phenomena such as the Hanbury-Brown–Twiss or the Hong–Ou–Mandel effect have been observed by analysing fluctuations in current through a beam-splitter structure 20 , 21 . Inspired by these experiments, a refined beam-splitter geometry has been developed to demonstrate the basic principles of flying charge qubit manipulations in a Mach–Zehnder interferometry set-up with a continuous stream of ballistic electrons 22 , 23 . This progress moreover opened up the way for precise transmission-phase measurements of QD states 24 , 25 , 26 and detailed studies on quantum phenomena such as the Kondo effect 27 , 28 . Considering the coherence times in stationary charge 29 , 30 , 31 , 32 or spin qubits 33 , 34 , 35 , it should be possible to use a surface-gate-defined beam-splitter component to implement quantum logic gates in GaAs-based heterostructures for solitary flying electron qubits. First steps in this directions have already been achieved via the demonstration of electron-quantum-optics experiments such as Hong–Ou–Mandel interference 12 , 36 or quantum state tomography 37 , 38 , 39 . To perform quantum logic operations 40 with a solitary flying electron qubit that is defined via charge or spin, besides coherent propagation of the electron wave function and single-shot detection, it will be further necessary to establish an experimental frame allowing adiabatic transport of the respective two-level system. Owing to the electrostatic isolation from the Fermi sea, SAW-driven single-electron transport is promising to demonstrate quantum logic operations with a flying electron qubit in a beam-splitter set-up. In this work we investigate the feasibility of such a beam-splitter set-up for SAW-driven single-shot transfer of a solitary electron. For this purpose, we couple a pair of quantum rails by a tunnel-barrier and partition an electron in flight into the two output channels of the circuit. Modelling the experimental results of this directional-coupler operation with quantum mechanical simulations, we deliver insight into the quantum state of the SAW-transported electron and provide a clear route to maintain adiabatic transport along a tunnel-coupled region of quantum rails. In order to realise quantum logic gates, where a pair of electrons is made to interact in flight, it is further necessary to synchronise the sending process. For this purpose, we demonstrate a SAW-driven single-electron source that is triggered by a voltage pulse on a timescale of picoseconds. Results A sound-driven single-electron circuit The sample is realised via surface electrodes forming a depleted potential landscape in the two-dimensional electron gas (2DEG) of a GaAs/AlGaAs heterostructure. An interdigital transducer (IDT) is used to send a finite SAW train towards our single-electron circuit as shown schematically in Fig. 1 a. A scanning-electron-microscopy (SEM) image of the investigated single-electron circuit is shown in Fig. 1 b. The device consists of two 22-µm-long quantum rails that are coupled along a region of 2 µm by a tunnel-barrier, which is defined by a 20 nm -wide surface gate. The SAW train allows the transport of a single electron from one gate-defined QD (source) to another stationary QD (receiver) through the circuit of coupled quantum rails (QR). Figure 1 c shows a zoom on the lower receiver QD with indications of the electrical connections. To detect the presence of an electron, a quantum point contact (QPC) is placed next to each QD. By biasing this QPC at a sensitive working point, an electron leaving or entering the QD can be detected by a jump in the current \${I}_{{\\rm{QPC}}}\$ 41 . Fig. 1 Sound-driven circuit of coupled quantum rails. a Schematic of the experimental set-up. An interdigital transducer (IDT) launches a SAW train towards the single-electron circuit, which is realised via metallic surface gates in a GaAs/AlGaAs heterostructure. b SEM image of the quantum rails (QR) with indications of the transport paths, U and L, and the voltages to control the coupling region. c SEM", "role": "user" }, { "content": "Researchers have successfully used sound waves to control quantum information in a single electron, a significant step towards efficient, robust quantum computers made from semiconductors. The international team, including researchers from the University of Cambridge, sent high-frequency sound waves across a modified semiconductor device to direct the behaviour of a single electron, with efficiencies in excess of 99 percent. The results are reported in the journal Nature Communications. A quantum computer would be able to solve previously unsolvable computational problems by taking advantage of the strange behaviour of particles at the subatomic scale, and quantum phenomena such as entanglement and superposition. However, precisely controlling the behaviour of quantum particles is a mammoth task. \"What would make a quantum computer so powerful is its ability to scale exponentially,\" said co-author Hugo Lepage, a Ph.D. candidate in Cambridge's Cavendish Laboratory, who performed the theoretical work for the current study. \"In a classical computer, to double the amount of information you have to double the number of bits. But in a quantum computer, you'd only need to add one more quantum bit, or qubit, to double the information.\" Last month, researchers from Google claimed to have reached 'quantum supremacy', the point at which a quantum computer can perform calculations beyond the capacity of the most powerful supercomputers. However, the quantum computers which Google, IBM and others are developing are based on superconducting loops, which are complex circuits and, like all quantum systems, are highly fragile. \"The smallest fluctuation or deviation will corrupt the quantum information contained in the phases and currents of the loops,\" said Lepage. \"This is still very new technology and expansion beyond the intermediate scale may require us to go down to the single particle level.\" Instead of superconducting loops, the quantum information in the quantum computer Lepage and his colleagues are devising use the 'spin' of an electron—its inherent angular momentum, which can be up or down—to store quantum information. \"Harnessing spin to power a functioning quantum computer is a more scalable approach than using superconductivity, and we believe that using spin could lead to a quantum computer which is far more robust, since spin interactions are set by the laws of nature,\" said Lepage. Using spin allows the quantum information to be more easily integrated with existing systems. The device developed in the current work is based on widely-used semiconductors with some minor modifications. The device, which was tested experimentally by Lepage's co-authors from the Institut Néel, measures just a few millionths of a metre long. The researchers laid metallic gates over a semiconductor and applied a voltage, which generated a complex electric field. The researchers then directed high-frequency sound waves over the device, causing it to vibrate and distort, like a tiny earthquake. As the sound waves propagate, they trap the electrons, pushing them through the device in a very precise way, as if the electrons are 'surfing' on the sound waves. The researchers were able to control the behaviour of a single electron with 99.5 percent efficiency. \"To control a single electron in this way is already difficult, but to get to a point where we can have a working quantum computer, we need to be able to control multiple electrons, which get exponentially more difficult as the qubits start to interact with each other,\" said Lepage. In the coming months, the researchers will begin testing the device with multiple electrons, which would bring a working quantum computer another step closer. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Surface acoustic waves (SAWs) strongly modulate the shallow electric potential in piezoelectric materials. In semiconductor heterostructures such as GaAs/AlGaAs, SAWs can thus be employed to transfer individual electrons between distant quantum dots. This transfer mechanism makes SAW technologies a promising candidate to convey quantum information through a circuit of quantum logic gates. Here we present two essential building blocks of such a SAW-driven quantum circuit. First, we implement a directional coupler allowing to partition a flying electron arbitrarily into two paths of transportation. Second, we demonstrate a triggered single-electron source enabling synchronisation of the SAW-driven sending process. Exceeding a single-shot transfer efficiency of 99%, we show that a SAW-driven integrated circuit is feasible with single electrons on a large scale. Our results pave the way to perform quantum logic operations with flying electron qubits. Introduction DiVincenzo’s criteria for realising a quantum computer address the transmission of quantum information between stationary nodes 1 . Several approaches have demonstrated successful transmission of quantum states in solid-state devices such as in quantum dot (QD) arrays 2 , 3 , 4 , 5 , coupled QDs in quantum Hall edge channels 6 or microwave-coupled superconducting qubits 7 , 8 . In semiconductor heterostructures, surface acoustic waves (SAWs) offer a particularly interesting platform to transmit quantum information. Thanks to the shallow electric potential modulation on a piezoelectric substrate, a SAW forms a train of moving QDs along a depleted transport channel. This SAW train allows to drag single charge carriers from one side of such a quantum rail to the other. Employing stationary QDs as electron source and receiver, a single electron has been sent back and forth several micrometre long tracks with a transfer efficiency of about 92% 9 , 10 . Recently, SAW-driven transfer of individual spin polarised electrons has been reported 11 . These advances support the idea of a SAW-driven quantum circuit enabling the implementation of electron-quantum-optics experiments 12 , 13 , 14 and quantum computation schemes at the single-particle level 15 , 16 , 17 , 18 , 19 . The core of such a quantum circuit is a tunable beam-splitter permitting the coherent partitioning and coupling of single-flying electrons. In the past, coherent quantum phenomena such as the Hanbury-Brown–Twiss or the Hong–Ou–Mandel effect have been observed by analysing fluctuations in current through a beam-splitter structure 20 , 21 . Inspired by these experiments, a refined beam-splitter geometry has been developed to demonstrate the basic principles of flying charge qubit manipulations in a Mach–Zehnder interferometry set-up with a continuous stream of ballistic electrons 22 , 23 . This progress moreover opened up the way for precise transmission-phase measurements of QD states 24 , 25 , 26 and detailed studies on quantum phenomena such as the Kondo effect 27 , 28 . Considering the coherence times in stationary charge 29 , 30 , 31 , 32 or spin qubits 33 , 34 , 35 , it should be possible to use a surface-gate-defined beam-splitter component to implement quantum logic gates in GaAs-based heterostructures for solitary flying electron qubits. First steps in this directions have already been achieved via the demonstration of electron-quantum-optics experiments such as Hong–Ou–Mandel interference 12 , 36 or quantum state tomography 37 , 38 , 39 . To perform quantum logic operations 40 with a solitary flying electron qubit that is defined via charge or spin, besides coherent propagation of the electron wave function and single-shot detection, it will be further necessary to establish an experimental frame allowing adiabatic transport of the respective two-level system. Owing to the electrostatic isolation from the Fermi sea, SAW-driven single-electron transport is promising to demonstrate quantum logic operations with a flying electron qubit in a beam-splitter set-up. In this work we investigate the feasibility of such a beam-splitter set-up for SAW-driven single-shot transfer of a solitary electron. For this purpose, we couple a pair of quantum rails by a tunnel-barrier and partition an electron in flight into the two output channels of the circuit. Modelling the experimental results of this directional-coupler operation with quantum mechanical simulations, we deliver insight into the quantum state of the SAW-transported electron and provide a clear route to maintain adiabatic transport along a tunnel-coupled region of quantum rails. In order to realise quantum logic gates, where a pair of electrons is made to interact in flight, it is further necessary to synchronise the sending process. For this purpose, we demonstrate a SAW-driven single-electron source that is triggered by a voltage pulse on a timescale of picoseconds. Results A sound-driven single-electron circuit The sample is realised via surface electrodes forming a depleted potential landscape in the two-dimensional electron gas (2DEG) of a GaAs/AlGaAs heterostructure. An interdigital transducer (IDT) is used to send a finite SAW train towards our single-electron circuit as shown schematically in Fig. 1 a. A scanning-electron-microscopy (SEM) image of the investigated single-electron circuit is shown in Fig. 1 b. The device consists of two 22-µm-long quantum rails that are coupled along a region of 2 µm by a tunnel-barrier, which is defined by a 20 nm -wide surface gate. The SAW train allows the transport of a single electron from one gate-defined QD (source) to another stationary QD (receiver) through the circuit of coupled quantum rails (QR). Figure 1 c shows a zoom on the lower receiver QD with indications of the electrical connections. To detect the presence of an electron, a quantum point contact (QPC) is placed next to each QD. By biasing this QPC at a sensitive working point, an electron leaving or entering the QD can be detected by a jump in the current ${I}_{{\rm{QPC}}}$ 41 . Fig. 1 Sound-driven circuit of coupled quantum rails. a Schematic of the experimental set-up. An interdigital transducer (IDT) launches a SAW train towards the single-electron circuit, which is realised via metallic surface gates in a GaAs/AlGaAs heterostructure. b SEM image of the quantum rails (QR) with indications of the transport paths, U and L, and the voltages to control the coupling region. c SEM<|im_end|> <|im_start|>assistant Researchers have successfully used sound waves to control quantum information in a single electron, a significant step towards efficient, robust quantum computers made from semiconductors. The international team, including researchers from the University of Cambridge, sent high-frequency sound waves across a modified semiconductor device to direct the behaviour of a single electron, with efficiencies in excess of 99 percent. The results are reported in the journal Nature Communications. A quantum computer would be able to solve previously unsolvable computational problems by taking advantage of the strange behaviour of particles at the subatomic scale, and quantum phenomena such as entanglement and superposition. However, precisely controlling the behaviour of quantum particles is a mammoth task. "What would make a quantum computer so powerful is its ability to scale exponentially," said co-author Hugo Lepage, a Ph.D. candidate in Cambridge's Cavendish Laboratory, who performed the theoretical work for the current study. "In a classical computer, to double the amount of information you have to double the number of bits. But in a quantum computer, you'd only need to add one more quantum bit, or qubit, to double the information." Last month, researchers from Google claimed to have reached 'quantum supremacy', the point at which a quantum computer can perform calculations beyond the capacity of the most powerful supercomputers. However, the quantum computers which Google, IBM and others are developing are based on superconducting loops, which are complex circuits and, like all quantum systems, are highly fragile. "The smallest fluctuation or deviation will corrupt the quantum information contained in the phases and currents of the loops," said Lepage. "This is still very new technology and expansion beyond the intermediate scale may require us to go down to the single particle level." Instead of superconducting loops, the quantum information in the quantum computer Lepage and his colleagues are devising use the 'spin' of an electron—its inherent angular momentum, which can be up or down—to store quantum information. "Harnessing spin to power a functioning quantum computer is a more scalable approach than using superconductivity, and we believe that using spin could lead to a quantum computer which is far more robust, since spin interactions are set by the laws of nature," said Lepage. Using spin allows the quantum information to be more easily integrated with existing systems. The device developed in the current work is based on widely-used semiconductors with some minor modifications. The device, which was tested experimentally by Lepage's co-authors from the Institut Néel, measures just a few millionths of a metre long. The researchers laid metallic gates over a semiconductor and applied a voltage, which generated a complex electric field. The researchers then directed high-frequency sound waves over the device, causing it to vibrate and distort, like a tiny earthquake. As the sound waves propagate, they trap the electrons, pushing them through the device in a very precise way, as if the electrons are 'surfing' on the sound waves. The researchers were able to control the behaviour of a single electron with 99.5 percent efficiency. "To control a single electron in this way is already difficult, but to get to a point where we can have a working quantum computer, we need to be able to control multiple electrons, which get exponentially more difficult as the qubits start to interact with each other," said Lepage. In the coming months, the researchers will begin testing the device with multiple electrons, which would bring a working quantum computer another step closer. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 28061, 45166, 17301, 320, 7934, 75833, 8, 16917, 1491, 6468, 279, 26682, 9249, 4754, 304, 4447, 89, 4748, 47262, 7384, 13, 763, 87836, 30548, 78, 47194, 1778, 439, 18879, 2170, 14, 2149, 81888, 2170, 11, 328, 14757, 82, 649, 8617, 387, 20011, 311, 8481, 3927, 57678, 1990, 29827, 31228, 32094, 13, 1115, 8481, 17383, 3727, 328, 14757, 14645, 264, 26455, 9322, 311, 20599, 31228, 2038, 1555, 264, 16622, 315, 31228, 12496, 35634, 13, 5810, 584, 3118, 1403, 7718, 4857, 10215, 315, 1778, 264, 328, 14757, 32505, 31228, 16622, 13, 5629, 11, 584, 4305, 264, 73945, 4020, 13206, 10923, 311, 17071, 264, 16706, 17130, 86757, 1139, 1403, 13006, 315, 18386, 13, 10657, 11, 584, 20461, 264, 22900, 3254, 37081, 2298, 2592, 28462, 14453, 8082, 315, 279, 328, 14757, 32505, 11889, 1920, 13, 1398, 4739, 287, 264, 3254, 64630, 8481, 15374, 315, 220, 1484, 13689, 584, 1501, 430, 264, 328, 14757, 32505, 18751, 16622, 374, 43303, 449, 3254, 57678, 389, 264, 3544, 5569, 13, 5751, 3135, 94123, 279, 1648, 311, 2804, 31228, 12496, 7677, 449, 16706, 17130, 2874, 82502, 13, 29438, 7923, 53, 2910, 268, 13028, 753, 13186, 369, 1972, 3876, 264, 31228, 6500, 2686, 279, 18874, 315, 31228, 2038, 1990, 53735, 7954, 220, 16, 662, 26778, 20414, 617, 21091, 6992, 18874, 315, 31228, 5415, 304, 6573, 21395, 7766, 1778, 439, 304, 31228, 13046, 320, 48, 35, 8, 18893, 220, 17, 1174, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 34356, 1229, 68050, 304, 31228, 11166, 6964, 12006, 220, 21, 477, 42374, 1824, 283, 50185, 2307, 77752, 287, 2874, 82502, 220, 22, 1174, 220, 23, 662, 763, 87836, 30548, 78, 47194, 11, 7479, 45166, 17301, 320, 7934, 75833, 8, 3085, 264, 8104, 7185, 5452, 311, 30382, 31228, 2038, 13, 11361, 311, 279, 26682, 9249, 4754, 67547, 389, 264, 4447, 89, 4748, 47262, 54057, 11, 264, 328, 14757, 7739, 264, 5542, 315, 7366, 1229, 68050, 3235, 264, 79266, 7710, 5613, 13, 1115, 328, 14757, 5542, 6276, 311, 11161, 3254, 6900, 35991, 505, 832, 3185, 315, 1778, 264, 31228, 13881, 311, 279, 1023, 13, 21445, 287, 53735, 1229, 68050, 439, 17130, 2592, 323, 14291, 11, 264, 3254, 17130, 706, 1027, 3288, 1203, 323, 13544, 3892, 19748, 442, 47987, 1317, 14242, 449, 264, 8481, 15374, 315, 922, 220, 6083, 4, 220, 24, 1174, 220, 605, 662, 42096, 11, 328, 14757, 32505, 8481, 315, 3927, 12903, 25685, 4147, 57678, 706, 1027, 5068, 220, 806, 662, 4314, 31003, 1862, 279, 4623, 315, 264, 328, 14757, 32505, 31228, 16622, 28462, 279, 8292, 315, 17130, 12, 31548, 372, 57212, 1233, 21896, 220, 717, 1174, 220, 1032, 1174, 220, 975, 323, 31228, 35547, 31956, 520, 279, 3254, 2320, 7203, 2237, 220, 868, 1174, 220, 845, 1174, 220, 1114, 1174, 220, 972, 1174, 220, 777, 662, 578, 6332, 315, 1778, 264, 31228, 16622, 374, 264, 11716, 481, 24310, 79512, 466, 62174, 279, 56887, 17071, 287, 323, 59086, 315, 3254, 2269, 6852, 57678, 13, 763, 279, 3347, 11, 56887, 31228, 44247, 1778, 439, 279, 21296, 20176, 7826, 4935, 4235, 23662, 1056, 477, 279, 19730, 4235, 46, 84, 4235, 44, 38221, 2515, 617, 1027, 13468, 555, 22209, 287, 65649, 304, 1510, 1555, 264, 24310, 79512, 466, 6070, 220, 508, 1174, 220, 1691, 662, 65925, 555, 1521, 21896, 11, 264, 38291, 24310, 79512, 466, 17484, 706, 1027, 8040, 311, 20461, 279, 6913, 16565, 315, 16706, 6900, 2874, 60320, 14951, 7607, 304, 264, 18798, 4235, 57, 2701, 910, 41305, 7133, 743, 5352, 449, 264, 19815, 4365, 315, 60633, 57678, 220, 1313, 1174, 220, 1419, 662, 1115, 5208, 44643, 9107, 709, 279, 1648, 369, 24473, 18874, 82710, 22323, 315, 1229, 35, 5415, 220, 1187, 1174, 220, 914, 1174, 220, 1627, 323, 11944, 7978, 389, 31228, 44247, 1778, 439, 279, 735, 36071, 2515, 220, 1544, 1174, 220, 1591, 662, 56877, 279, 78925, 3115, 304, 53735, 6900, 220, 1682, 1174, 220, 966, 1174, 220, 2148, 1174, 220, 843, 477, 12903, 2874, 82502, 220, 1644, 1174, 220, 1958, 1174, 220, 1758, 1174, 433, 1288, 387, 3284, 311, 1005, 264, 7479, 2427, 349, 39817, 24310, 79512, 466, 3777, 311, 4305, 31228, 12496, 35634, 304, 18879, 2170, 6108, 30548, 78, 47194, 369, 58229, 16706, 17130, 2874, 82502, 13, 5629, 7504, 304, 420, 18445, 617, 2736, 1027, 17427, 4669, 279, 30816, 315, 17130, 12, 31548, 372, 57212, 1233, 21896, 1778, 439, 19730, 4235, 46, 84, 4235, 44, 38221, 32317, 220, 717, 1174, 220, 1927, 477, 31228, 1614, 10390, 5814, 220, 1806, 1174, 220, 1987, 1174, 220, 2137, 662, 2057, 2804, 31228, 12496, 7677, 220, 1272, 449, 264, 58229, 16706, 17130, 2874, 60320, 430, 374, 4613, 4669, 6900, 477, 12903, 11, 28858, 56887, 54743, 315, 279, 17130, 12330, 734, 323, 3254, 64630, 18468, 11, 433, 690, 387, 4726, 5995, 311, 5813, 459, 22772, 4124, 10923, 1008, 72, 370, 780, 7710, 315, 279, 20081, 1403, 11852, 1887, 13, 507, 24510, 311, 279, 25396, 2020, 31398, 505, 279, 99362, 72, 9581, 11, 328, 14757, 32505, 3254, 37081, 2298, 7710, 374, 26455, 311, 20461, 31228, 12496, 7677, 449, 264, 16706, 17130, 2874, 60320, 304, 264, 24310, 79512, 466, 743, 5352, 13, 763, 420, 990, 584, 19874, 279, 69543, 315, 1778, 264, 24310, 79512, 466, 743, 5352, 369, 328, 14757, 32505, 3254, 64630, 8481, 315, 264, 58229, 17130, 13, 1789, 420, 7580, 11, 584, 5743, 264, 6857, 315, 31228, 43700, 555, 264, 26711, 16150, 7401, 323, 17071, 459, 17130, 304, 11213, 1139, 279, 1403, 2612, 12006, 315, 279, 16622, 13, 5768, 6427, 279, 22772, 3135, 315, 420, 73945, 1824, 283, 13206, 5784, 449, 31228, 22936, 47590, 11, 584, 6493, 20616, 1139, 279, 31228, 1614, 315, 279, 328, 14757, 12, 27543, 291, 17130, 323, 3493, 264, 2867, 6149, 311, 10519, 1008, 72, 370, 780, 7710, 3235, 264, 26711, 1824, 283, 50185, 5654, 315, 31228, 43700, 13, 763, 2015, 311, 39256, 31228, 12496, 35634, 11, 1405, 264, 6857, 315, 57678, 374, 1903, 311, 16681, 304, 11213, 11, 433, 374, 4726, 5995, 311, 14453, 1082, 279, 11889, 1920, 13, 1789, 420, 7580, 11, 584, 20461, 264, 328, 14757, 32505, 3254, 37081, 2298, 2592, 430, 374, 22900, 555, 264, 22465, 28334, 389, 264, 3115, 2296, 315, 10532, 76989, 13, 18591, 362, 5222, 32505, 3254, 37081, 2298, 16622, 578, 6205, 374, 41193, 4669, 7479, 80390, 30164, 264, 79266, 4754, 18921, 304, 279, 1403, 33520, 17130, 6962, 320, 17, 1170, 38, 8, 315, 264, 18879, 2170, 14, 2149, 81888, 2170, 30548, 78, 7993, 13, 1556, 958, 58369, 1380, 30038, 320, 926, 51, 8, 374, 1511, 311, 3708, 264, 35326, 328, 14757, 5542, 7119, 1057, 3254, 37081, 2298, 16622, 439, 6982, 20225, 7167, 304, 23966, 13, 220, 16, 264, 13, 362, 36201, 37081, 2298, 1474, 2823, 51856, 320, 84839, 8, 2217, 315, 279, 27313, 3254, 37081, 2298, 16622, 374, 6982, 304, 23966, 13, 220, 16, 293, 13, 578, 3756, 17610, 315, 1403, 220, 1313, 12, 74148, 76, 24725, 31228, 43700, 430, 527, 34356, 3235, 264, 5654, 315, 220, 17, 64012, 76, 555, 264, 26711, 16150, 7401, 11, 902, 374, 4613, 555, 264, 220, 508, 26807, 482, 9328, 7479, 18618, 13, 578, 328, 14757, 5542, 6276, 279, 7710, 315, 264, 3254, 17130, 505, 832, 18618, 39817, 1229, 35, 320, 2484, 8, 311, 2500, 53735, 1229, 35, 320, 38653, 8, 1555, 279, 16622, 315, 34356, 31228, 43700, 320, 31565, 570, 19575, 220, 16, 272, 5039, 264, 15932, 389, 279, 4827, 14291, 1229, 35, 449, 56190, 315, 279, 20314, 13537, 13, 2057, 11388, 279, 9546, 315, 459, 17130, 11, 264, 31228, 1486, 3729, 320, 48, 4977, 8, 374, 9277, 1828, 311, 1855, 1229, 35, 13, 3296, 15837, 287, 420, 1229, 4977, 520, 264, 16614, 3318, 1486, 11, 459, 17130, 9564, 477, 16661, 279, 1229, 35, 649, 387, 16914, 555, 264, 7940, 304, 279, 1510, 1144, 2358, 40, 20009, 3052, 59, 8892, 90, 48, 4977, 3500, 11281, 8, 220, 3174, 662, 23966, 13, 220, 16, 14936, 32505, 16622, 315, 34356, 31228, 43700, 13, 264, 328, 82149, 315, 279, 22772, 743, 5352, 13, 1556, 958, 58369, 1380, 30038, 320, 926, 51, 8, 38175, 264, 328, 14757, 5542, 7119, 279, 3254, 37081, 2298, 16622, 11, 902, 374, 41193, 4669, 46258, 7479, 35634, 304, 264, 18879, 2170, 14, 2149, 81888, 2170, 30548, 78, 7993, 13, 293, 46544, 2217, 315, 279, 31228, 43700, 320, 31565, 8, 449, 56190, 315, 279, 7710, 13006, 11, 549, 323, 445, 11, 323, 279, 16798, 1154, 311, 2585, 279, 59086, 5654, 13, 272, 46544, 128257, 198, 128256, 78191, 198, 60210, 617, 7946, 1511, 5222, 17301, 311, 2585, 31228, 2038, 304, 264, 3254, 17130, 11, 264, 5199, 3094, 7119, 11297, 11, 22514, 31228, 19002, 1903, 505, 5347, 1965, 1076, 1105, 13, 578, 6625, 2128, 11, 2737, 12074, 505, 279, 3907, 315, 24562, 11, 3288, 1579, 79412, 5222, 17301, 4028, 264, 11041, 87836, 3756, 311, 2167, 279, 17432, 315, 264, 3254, 17130, 11, 449, 92126, 304, 13937, 315, 220, 1484, 3346, 13, 578, 3135, 527, 5068, 304, 279, 8486, 22037, 26545, 13, 362, 31228, 6500, 1053, 387, 3025, 311, 11886, 8767, 7120, 89197, 55580, 5435, 555, 4737, 9610, 315, 279, 15234, 17432, 315, 19252, 520, 279, 1207, 6756, 5569, 11, 323, 31228, 44247, 1778, 439, 1218, 526, 1001, 323, 2307, 3571, 13, 4452, 11, 24559, 26991, 279, 17432, 315, 31228, 19252, 374, 264, 33820, 68504, 3465, 13, 330, 3923, 1053, 1304, 264, 31228, 6500, 779, 8147, 374, 1202, 5845, 311, 5569, 75251, 1359, 1071, 1080, 43802, 52194, 121688, 425, 11, 264, 2405, 920, 13, 9322, 304, 24562, 596, 52166, 408, 819, 32184, 11, 889, 10887, 279, 32887, 990, 369, 279, 1510, 4007, 13, 330, 644, 264, 29924, 6500, 11, 311, 2033, 279, 3392, 315, 2038, 499, 617, 311, 2033, 279, 1396, 315, 9660, 13, 2030, 304, 264, 31228, 6500, 11, 499, 4265, 1193, 1205, 311, 923, 832, 810, 31228, 2766, 11, 477, 2874, 60320, 11, 311, 2033, 279, 2038, 1210, 8155, 2305, 11, 12074, 505, 5195, 11922, 311, 617, 8813, 364, 31548, 372, 65503, 518, 279, 1486, 520, 902, 264, 31228, 6500, 649, 2804, 29217, 7953, 279, 8824, 315, 279, 1455, 8147, 2307, 66047, 388, 13, 4452, 11, 279, 31228, 19002, 902, 5195, 11, 29022, 323, 3885, 527, 11469, 527, 3196, 389, 2307, 77752, 287, 30853, 11, 902, 527, 6485, 46121, 323, 11, 1093, 682, 31228, 6067, 11, 527, 7701, 45350, 13, 330, 791, 25655, 39388, 4090, 477, 38664, 690, 22681, 279, 31228, 2038, 13282, 304, 279, 35530, 323, 60701, 315, 279, 30853, 1359, 1071, 121688, 425, 13, 330, 2028, 374, 2103, 1633, 502, 5557, 323, 14800, 7953, 279, 29539, 5569, 1253, 1397, 603, 311, 733, 1523, 311, 279, 3254, 19320, 2237, 1210, 12361, 315, 2307, 77752, 287, 30853, 11, 279, 31228, 2038, 304, 279, 31228, 6500, 121688, 425, 323, 813, 18105, 527, 98233, 287, 1005, 279, 364, 42682, 6, 315, 459, 17130, 2345, 1220, 38088, 20932, 24151, 11, 902, 649, 387, 709, 477, 1523, 50617, 3637, 31228, 2038, 13, 330, 75348, 287, 12903, 311, 2410, 264, 31301, 31228, 6500, 374, 264, 810, 69311, 5603, 1109, 1701, 2307, 77752, 1968, 11, 323, 584, 4510, 430, 1701, 12903, 1436, 3063, 311, 264, 31228, 6500, 902, 374, 3117, 810, 22514, 11, 2533, 12903, 22639, 527, 743, 555, 279, 7016, 315, 7138, 1359, 1071, 121688, 425, 13, 12362, 12903, 6276, 279, 31228, 2038, 311, 387, 810, 6847, 18751, 449, 6484, 6067, 13, 578, 3756, 8040, 304, 279, 1510, 990, 374, 3196, 389, 13882, 69621, 5347, 1965, 1076, 1105, 449, 1063, 9099, 29882, 13, 578, 3756, 11, 902, 574, 12793, 9526, 750, 555, 121688, 425, 596, 1080, 34603, 1105, 505, 279, 96562, 452, 978, 301, 11, 11193, 1120, 264, 2478, 3610, 17323, 315, 264, 82673, 1317, 13, 578, 12074, 17551, 46258, 35634, 927, 264, 87836, 323, 9435, 264, 22465, 11, 902, 8066, 264, 6485, 9249, 2115, 13, 578, 12074, 1243, 15910, 1579, 79412, 5222, 17301, 927, 279, 3756, 11, 14718, 433, 311, 348, 44192, 323, 70584, 11, 1093, 264, 13987, 38413, 13, 1666, 279, 5222, 17301, 58514, 11, 814, 23709, 279, 57678, 11, 17919, 1124, 1555, 279, 3756, 304, 264, 1633, 24473, 1648, 11, 439, 422, 279, 57678, 527, 364, 78960, 287, 6, 389, 279, 5222, 17301, 13, 578, 12074, 1051, 3025, 311, 2585, 279, 17432, 315, 264, 3254, 17130, 449, 220, 1484, 13, 20, 3346, 15374, 13, 330, 1271, 2585, 264, 3254, 17130, 304, 420, 1648, 374, 2736, 5107, 11, 719, 311, 636, 311, 264, 1486, 1405, 584, 649, 617, 264, 3318, 31228, 6500, 11, 584, 1205, 311, 387, 3025, 311, 2585, 5361, 57678, 11, 902, 636, 75251, 810, 5107, 439, 279, 2874, 82502, 1212, 311, 16681, 449, 1855, 1023, 1359, 1071, 121688, 425, 13, 763, 279, 5108, 4038, 11, 279, 12074, 690, 3240, 7649, 279, 3756, 449, 5361, 57678, 11, 902, 1053, 4546, 264, 3318, 31228, 6500, 2500, 3094, 12401, 13, 220, 128257, 198 ]

2,128

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract This study examined the association between dietary Vitamin K1 intake with fracture-related hospitalizations over 14.5 years in community-dwelling older Australian women ( n = 1373, ≥70 years). Dietary Vitamin K1 intake at baseline (1998) was estimated using a validated food frequency questionnaire and a new Australian Vitamin K nutrient database, which was supplemented with published data. Over 14.5 years, any fracture ( n = 404, 28.3%) and hip fracture ( n = 153, 10.7%) related hospitalizations were captured using linked health data. Plasma Vitamin D status (25OHD) and the ratio of undercarboxylated osteocalcin (ucOC) to total osteocalcin (tOC) from serum was assessed at baseline. Estimates of dietary Vitamin K1 intake were supported by a significant inverse association with ucOC : tOC; a marker of Vitamin K status ( r = −0.12, p < 0.001). Compared to women with the lowest Vitamin K1 intake (Quartile 1, <61 μg d −1 ), women with the highest Vitamin K1 intake (Quartile 4, ≥99 μg d −1 ) had lower hazards for any fracture- (HR 0.69 95%CI 0.52–0.91, p < 0.001) and hip fracture-related hospitalization (HR 0.51 95%CI 0.32–0.79, p < 0.001), independent of 25OHD levels, as part of multivariable-adjusted analysis. Spline analysis suggested a nadir in the relative hazard for any fracture-related hospitalizations at a Vitamin K1 intake of approximately 100 μg day −1 . For hip fractures, a similar relationship was apparent. Higher dietary Vitamin K1 is associated with lower long-term risk for any fracture- and hip fracture-related hospitalizations in community-dwelling older women. Introduction Osteoporotic fractures, especially hip fractures, often result in longstanding disability and compromised independence together with increased mortality risk. 1 Although best known for its role in blood coagulation, epidemiological investigation and clinical trials suggest that Vitamin K intake is important for skeletal health. 2–6 Basic studies of Vitamin K have supported the clinical data by identifying a critical role in the γ-carboxylation of the Vitamin K dependant bone proteins, including osteocalcin (OC). 7 Specifically, OC is produced by osteoblasts and is believed to improve bone toughness, 7 which is essential for preventing fractures. The two major forms of OC are carboxylated OC (cOC) and undercarboxylated OC (ucOC), with the former linked to bone integrity. 8 The ratio of ucOC to total OC (tOC) is known to be inversely associated with dietary Vitamin K intake. 9 Cell biology studies have also identified other actions of Vitamin K on bone separate from γ-carboxylation. 10 Two main forms of Vitamin K in the diet include Vitamin K1 (phylloquinone; PK) and Vitamin K2 (menaquinones; MKs), including its different isoforms such as MK4 to MK13. Green leafy vegetables and their oils are rich sources of Vitamin K1, while dietary Vitamin K2 is obtained from animal products including meats, eggs, and cheeses. 11 In the diet, about 90% of total Vitamin K intake is estimated to come from PK. 12 From a public health perspective, when considering the well-established health benefits of higher vegetable intake, this is an important consideration when promoting dietary guidelines specific to Vitamin K. Nevertheless, the 2021 update on Vitamin K nutrition by the National Institute of Health highlights uncertainty regarding the importance of Vitamin K for fracture prevention. 13 Nutrient Reference Values for total Vitamin K intake have been set at 70 and 60 μg d −1 for Australian men and women, respectively, based on median intakes of the Australian population. 14 Such guidelines are comparable to Europe 15 but slightly lower than the USA. 16 However, the aforementioned intakes, especially in Australia, may be insufficient to support optimal bone metabolism. 9 Our previous clinical trial found that increasing daily intake of Vitamin K1-rich vegetables over four weeks significantly reduced tOC, suggesting improved bone metabolism in healthy adults. 9 This implies that Vitamin K1 could play an important role in bone health and fracture prevention. As such, the aim of this study was to investigate the relationship between dietary Vitamin K1 intake, using a newly developed Australian Vitamin K food database, with long-term fracture risk in community-dwelling older Australian women. We also sought to determine whether there were dose-dependent thresholds for dietary Vitamin K1 intakes to be associated with lower fracture risk. Materials and methods Participants A 5-year, double-blind, randomised controlled trial of daily calcium supplementation to prevent fracture in women (Calcium Intake Fracture Outcome Study, CAIFOS) commenced in 1998. Women ( n = 1500, aged ≥70) with (i) an expected survival beyond 5 years and (ii) not receiving any medication (including hormone replacement therapy) known to affect bone metabolism 17 were recruited using electoral roll. After CAIFOS, participants were invited to be part of two 5-year follow-up observational studies, leading to a total follow-up of 14.5 years; the Perth Longitudinal Study of Aging in Women (PLSAW). 1485 women completed a food frequency questionnaire at baseline and those with implausible energy intakes (<2100 kJ [500 kcal] or >14 700 kJ [3500 kcal]) ( n = 17/1485, 1.1%) or undertaking Vitamin D supplementation (due to its link with fracture, 18 n = 39/1485) were excluded. A further 45 women taking warfarin were excluded due to warfarin interfering with Vitamin K metabolism. 19 Women missing covariates were also excluded ( n = 11). The current study included 1373 women (ESI Fig. 1 † ) for the primary analysis. The 1271 women who had a measurement of total plasma 25OHD at baseline were included in analyses where 25OHD was included as a covariate. Written informed consent was obtained from all women. The Human Ethics Committee of the University of Western Australia provided ethical approval. Both CAIFOS and PLSAW complied with the Declaration of Helsinki and were retrospectively registered on the Australian New Zealand Clinical Trials Registry (#ACTRN12615000750583 and #ACTRN12617000640303). Linked data ethics approval was provided by the Human Research Ethics Committee of the Western Australian Department of Health (#2009/24). STROBE for observational studies were adhered to for this work. Dietary intake A self-administered, semiquantitative food frequency questionnaire (FFQ) developed and validated by the Cancer Council of Victoria was used to determine", "role": "user" }, { "content": "Breaking bones can be life changing events—especially as we age, when hip fractures can become particularly damaging and result in disability, compromised independence and a higher mortality risk. But research from Edith Cowan University's Nutrition and Health Innovation Research Institute has revealed there may be something you can do to help reduce your risk of fractures later in life. In collaboration with the University of Western Australia, the study looked at the relationship between fracture-related hospitalizations and vitamin K1 intake in almost 1,400 older Australian women over a 14.5-year period from the Perth Longitudinal Study of Aging Women. It found women who ate more than 100 micrograms of vitamin K1 consumption—equivalent to about 125g of dark leafy vegetables, or one-to-two serves of vegetables—were 31% less likely to have any fracture compared to participants who consumed less than 60 micrograms per day, which is the current vitamin K adequate intake guideline in Australia for women. There were even more positive results regarding hip fractures, with those who ate the most vitamin K1 cutting their risk of hospitalization almost in half (49%). Study lead Dr. Marc Sim said the results were further evidence of the benefits of vitamin K1, which has also been shown to enhance cardiovascular health. \"Our results are independent of many established factors for fracture rates, including body mass index, calcium intake, Vitamin D status and prevalent disease,\" he said. \"Basic studies of vitamin K1 have identified a critical role in the carboxylation of the vitamin K1-dependant bone proteins such as osteocalcin, which is believed to improve bone toughness. \"A previous ECU trial indicates dietary vitamin K1 intakes of less than 100 micrograms per day may be too low for this carboxylation. \"Vitamin K1 may also promote bone health by inhibiting various bone resorbing agents.\" So, what should we eat, and how much? Dr. Sim said eating more than 100 micrograms of vitamin K1 daily was ideal—and, happily, it isn't too difficult to do. \"Consuming this much daily vitamin K1 can easily be achieved by consuming between 75–150g, equivalent to one to two serves, of vegetables such as spinach, kale, broccoli and cabbage,\" he said. \"It's another reason to follow public health guidelines, which advocate higher vegetable intake including one to two serves of green leafy vegetables—which is in-line with our study's recommendations.\" The study is published in Food & Function. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract This study examined the association between dietary Vitamin K1 intake with fracture-related hospitalizations over 14.5 years in community-dwelling older Australian women ( n = 1373, ≥70 years). Dietary Vitamin K1 intake at baseline (1998) was estimated using a validated food frequency questionnaire and a new Australian Vitamin K nutrient database, which was supplemented with published data. Over 14.5 years, any fracture ( n = 404, 28.3%) and hip fracture ( n = 153, 10.7%) related hospitalizations were captured using linked health data. Plasma Vitamin D status (25OHD) and the ratio of undercarboxylated osteocalcin (ucOC) to total osteocalcin (tOC) from serum was assessed at baseline. Estimates of dietary Vitamin K1 intake were supported by a significant inverse association with ucOC : tOC; a marker of Vitamin K status ( r = −0.12, p < 0.001). Compared to women with the lowest Vitamin K1 intake (Quartile 1, <61 μg d −1 ), women with the highest Vitamin K1 intake (Quartile 4, ≥99 μg d −1 ) had lower hazards for any fracture- (HR 0.69 95%CI 0.52–0.91, p < 0.001) and hip fracture-related hospitalization (HR 0.51 95%CI 0.32–0.79, p < 0.001), independent of 25OHD levels, as part of multivariable-adjusted analysis. Spline analysis suggested a nadir in the relative hazard for any fracture-related hospitalizations at a Vitamin K1 intake of approximately 100 μg day −1 . For hip fractures, a similar relationship was apparent. Higher dietary Vitamin K1 is associated with lower long-term risk for any fracture- and hip fracture-related hospitalizations in community-dwelling older women. Introduction Osteoporotic fractures, especially hip fractures, often result in longstanding disability and compromised independence together with increased mortality risk. 1 Although best known for its role in blood coagulation, epidemiological investigation and clinical trials suggest that Vitamin K intake is important for skeletal health. 2–6 Basic studies of Vitamin K have supported the clinical data by identifying a critical role in the γ-carboxylation of the Vitamin K dependant bone proteins, including osteocalcin (OC). 7 Specifically, OC is produced by osteoblasts and is believed to improve bone toughness, 7 which is essential for preventing fractures. The two major forms of OC are carboxylated OC (cOC) and undercarboxylated OC (ucOC), with the former linked to bone integrity. 8 The ratio of ucOC to total OC (tOC) is known to be inversely associated with dietary Vitamin K intake. 9 Cell biology studies have also identified other actions of Vitamin K on bone separate from γ-carboxylation. 10 Two main forms of Vitamin K in the diet include Vitamin K1 (phylloquinone; PK) and Vitamin K2 (menaquinones; MKs), including its different isoforms such as MK4 to MK13. Green leafy vegetables and their oils are rich sources of Vitamin K1, while dietary Vitamin K2 is obtained from animal products including meats, eggs, and cheeses. 11 In the diet, about 90% of total Vitamin K intake is estimated to come from PK. 12 From a public health perspective, when considering the well-established health benefits of higher vegetable intake, this is an important consideration when promoting dietary guidelines specific to Vitamin K. Nevertheless, the 2021 update on Vitamin K nutrition by the National Institute of Health highlights uncertainty regarding the importance of Vitamin K for fracture prevention. 13 Nutrient Reference Values for total Vitamin K intake have been set at 70 and 60 μg d −1 for Australian men and women, respectively, based on median intakes of the Australian population. 14 Such guidelines are comparable to Europe 15 but slightly lower than the USA. 16 However, the aforementioned intakes, especially in Australia, may be insufficient to support optimal bone metabolism. 9 Our previous clinical trial found that increasing daily intake of Vitamin K1-rich vegetables over four weeks significantly reduced tOC, suggesting improved bone metabolism in healthy adults. 9 This implies that Vitamin K1 could play an important role in bone health and fracture prevention. As such, the aim of this study was to investigate the relationship between dietary Vitamin K1 intake, using a newly developed Australian Vitamin K food database, with long-term fracture risk in community-dwelling older Australian women. We also sought to determine whether there were dose-dependent thresholds for dietary Vitamin K1 intakes to be associated with lower fracture risk. Materials and methods Participants A 5-year, double-blind, randomised controlled trial of daily calcium supplementation to prevent fracture in women (Calcium Intake Fracture Outcome Study, CAIFOS) commenced in 1998. Women ( n = 1500, aged ≥70) with (i) an expected survival beyond 5 years and (ii) not receiving any medication (including hormone replacement therapy) known to affect bone metabolism 17 were recruited using electoral roll. After CAIFOS, participants were invited to be part of two 5-year follow-up observational studies, leading to a total follow-up of 14.5 years; the Perth Longitudinal Study of Aging in Women (PLSAW). 1485 women completed a food frequency questionnaire at baseline and those with implausible energy intakes (<2100 kJ [500 kcal] or >14 700 kJ [3500 kcal]) ( n = 17/1485, 1.1%) or undertaking Vitamin D supplementation (due to its link with fracture, 18 n = 39/1485) were excluded. A further 45 women taking warfarin were excluded due to warfarin interfering with Vitamin K metabolism. 19 Women missing covariates were also excluded ( n = 11). The current study included 1373 women (ESI Fig. 1 † ) for the primary analysis. The 1271 women who had a measurement of total plasma 25OHD at baseline were included in analyses where 25OHD was included as a covariate. Written informed consent was obtained from all women. The Human Ethics Committee of the University of Western Australia provided ethical approval. Both CAIFOS and PLSAW complied with the Declaration of Helsinki and were retrospectively registered on the Australian New Zealand Clinical Trials Registry (#ACTRN12615000750583 and #ACTRN12617000640303). Linked data ethics approval was provided by the Human Research Ethics Committee of the Western Australian Department of Health (#2009/24). STROBE for observational studies were adhered to for this work. Dietary intake A self-administered, semiquantitative food frequency questionnaire (FFQ) developed and validated by the Cancer Council of Victoria was used to determine<|im_end|> <|im_start|>assistant Breaking bones can be life changing events—especially as we age, when hip fractures can become particularly damaging and result in disability, compromised independence and a higher mortality risk. But research from Edith Cowan University's Nutrition and Health Innovation Research Institute has revealed there may be something you can do to help reduce your risk of fractures later in life. In collaboration with the University of Western Australia, the study looked at the relationship between fracture-related hospitalizations and vitamin K1 intake in almost 1,400 older Australian women over a 14.5-year period from the Perth Longitudinal Study of Aging Women. It found women who ate more than 100 micrograms of vitamin K1 consumption—equivalent to about 125g of dark leafy vegetables, or one-to-two serves of vegetables—were 31% less likely to have any fracture compared to participants who consumed less than 60 micrograms per day, which is the current vitamin K adequate intake guideline in Australia for women. There were even more positive results regarding hip fractures, with those who ate the most vitamin K1 cutting their risk of hospitalization almost in half (49%). Study lead Dr. Marc Sim said the results were further evidence of the benefits of vitamin K1, which has also been shown to enhance cardiovascular health. "Our results are independent of many established factors for fracture rates, including body mass index, calcium intake, Vitamin D status and prevalent disease," he said. "Basic studies of vitamin K1 have identified a critical role in the carboxylation of the vitamin K1-dependant bone proteins such as osteocalcin, which is believed to improve bone toughness. "A previous ECU trial indicates dietary vitamin K1 intakes of less than 100 micrograms per day may be too low for this carboxylation. "Vitamin K1 may also promote bone health by inhibiting various bone resorbing agents." So, what should we eat, and how much? Dr. Sim said eating more than 100 micrograms of vitamin K1 daily was ideal—and, happily, it isn't too difficult to do. "Consuming this much daily vitamin K1 can easily be achieved by consuming between 75–150g, equivalent to one to two serves, of vegetables such as spinach, kale, broccoli and cabbage," he said. "It's another reason to follow public health guidelines, which advocate higher vegetable intake including one to two serves of green leafy vegetables—which is in-line with our study's recommendations." The study is published in Food & Function. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 1115, 4007, 25078, 279, 15360, 1990, 34625, 45774, 735, 16, 23730, 449, 59904, 14228, 8952, 8200, 927, 220, 975, 13, 20, 1667, 304, 4029, 1773, 86, 6427, 9191, 13673, 3278, 320, 308, 284, 220, 10148, 18, 11, 63247, 2031, 1667, 570, 83808, 45774, 735, 16, 23730, 520, 26954, 320, 2550, 23, 8, 574, 13240, 1701, 264, 33432, 3691, 11900, 48964, 323, 264, 502, 13673, 45774, 735, 50123, 4729, 11, 902, 574, 89804, 449, 4756, 828, 13, 6193, 220, 975, 13, 20, 1667, 11, 904, 59904, 320, 308, 284, 220, 7507, 11, 220, 1591, 13, 18, 11587, 323, 18638, 59904, 320, 308, 284, 220, 9800, 11, 220, 605, 13, 22, 11587, 5552, 8952, 8200, 1051, 17439, 1701, 10815, 2890, 828, 13, 65632, 45774, 423, 2704, 320, 914, 46, 19694, 8, 323, 279, 11595, 315, 1234, 7063, 2054, 4010, 660, 52368, 3768, 18595, 320, 1791, 7767, 8, 311, 2860, 52368, 3768, 18595, 320, 83, 7767, 8, 505, 41529, 574, 32448, 520, 26954, 13, 95619, 315, 34625, 45774, 735, 16, 23730, 1051, 7396, 555, 264, 5199, 29049, 15360, 449, 26805, 7767, 551, 259, 7767, 26, 264, 11381, 315, 45774, 735, 2704, 320, 436, 284, 25173, 15, 13, 717, 11, 281, 366, 220, 15, 13, 4119, 570, 59813, 311, 3278, 449, 279, 15821, 45774, 735, 16, 23730, 320, 2232, 472, 458, 220, 16, 11, 366, 5547, 33983, 70, 294, 25173, 16, 7026, 3278, 449, 279, 8592, 45774, 735, 16, 23730, 320, 2232, 472, 458, 220, 19, 11, 63247, 1484, 33983, 70, 294, 25173, 16, 883, 1047, 4827, 52642, 369, 904, 59904, 12, 320, 17526, 220, 15, 13, 3076, 220, 2721, 4, 11487, 220, 15, 13, 4103, 4235, 15, 13, 5925, 11, 281, 366, 220, 15, 13, 4119, 8, 323, 18638, 59904, 14228, 8952, 2065, 320, 17526, 220, 15, 13, 3971, 220, 2721, 4, 11487, 220, 15, 13, 843, 4235, 15, 13, 4643, 11, 281, 366, 220, 15, 13, 4119, 705, 9678, 315, 220, 914, 46, 19694, 5990, 11, 439, 961, 315, 2814, 57498, 2205, 60684, 291, 6492, 13, 328, 32539, 6492, 12090, 264, 34634, 404, 304, 279, 8844, 31397, 369, 904, 59904, 14228, 8952, 8200, 520, 264, 45774, 735, 16, 23730, 315, 13489, 220, 1041, 33983, 70, 1938, 25173, 16, 662, 1789, 18638, 78332, 11, 264, 4528, 5133, 574, 10186, 13, 35321, 34625, 45774, 735, 16, 374, 5938, 449, 4827, 1317, 9860, 5326, 369, 904, 59904, 12, 323, 18638, 59904, 14228, 8952, 8200, 304, 4029, 1773, 86, 6427, 9191, 3278, 13, 29438, 507, 5455, 89766, 14546, 78332, 11, 5423, 18638, 78332, 11, 3629, 1121, 304, 74229, 28353, 323, 44500, 24589, 3871, 449, 7319, 29528, 5326, 13, 220, 16, 10541, 1888, 3967, 369, 1202, 3560, 304, 6680, 1080, 351, 2987, 11, 62057, 5848, 8990, 323, 14830, 19622, 4284, 430, 45774, 735, 23730, 374, 3062, 369, 69397, 2890, 13, 220, 17, 4235, 21, 14967, 7978, 315, 45774, 735, 617, 7396, 279, 14830, 828, 555, 25607, 264, 9200, 3560, 304, 279, 63127, 24948, 2054, 79933, 315, 279, 45774, 735, 6904, 519, 17685, 28896, 11, 2737, 52368, 3768, 18595, 320, 7767, 570, 220, 22, 45863, 11, 32967, 374, 9124, 555, 52368, 677, 4354, 82, 323, 374, 11846, 311, 7417, 17685, 77318, 11, 220, 22, 902, 374, 7718, 369, 27252, 78332, 13, 578, 1403, 3682, 7739, 315, 32967, 527, 1841, 2054, 4010, 660, 32967, 320, 66, 7767, 8, 323, 1234, 7063, 2054, 4010, 660, 32967, 320, 1791, 7767, 705, 449, 279, 4846, 10815, 311, 17685, 17025, 13, 220, 23, 578, 11595, 315, 26805, 7767, 311, 2860, 32967, 320, 83, 7767, 8, 374, 3967, 311, 387, 65683, 989, 5938, 449, 34625, 45774, 735, 23730, 13, 220, 24, 14299, 34458, 7978, 617, 1101, 11054, 1023, 6299, 315, 45774, 735, 389, 17685, 8821, 505, 63127, 24948, 2054, 79933, 13, 220, 605, 9220, 1925, 7739, 315, 45774, 735, 304, 279, 10173, 2997, 45774, 735, 16, 320, 110231, 385, 36444, 606, 26, 25864, 8, 323, 45774, 735, 17, 320, 5794, 64, 36444, 3233, 26, 27957, 82, 705, 2737, 1202, 2204, 34556, 10008, 1778, 439, 27957, 19, 311, 27957, 1032, 13, 7997, 16312, 88, 24822, 323, 872, 32462, 527, 9257, 8336, 315, 45774, 735, 16, 11, 1418, 34625, 45774, 735, 17, 374, 12457, 505, 10065, 3956, 2737, 63875, 11, 19335, 11, 323, 98564, 13, 220, 806, 763, 279, 10173, 11, 922, 220, 1954, 4, 315, 2860, 45774, 735, 23730, 374, 13240, 311, 2586, 505, 25864, 13, 220, 717, 5659, 264, 586, 2890, 13356, 11, 994, 13126, 279, 1664, 64868, 2890, 7720, 315, 5190, 36581, 23730, 11, 420, 374, 459, 3062, 18361, 994, 22923, 34625, 17959, 3230, 311, 45774, 735, 13, 35053, 11, 279, 220, 2366, 16, 2713, 389, 45774, 735, 26677, 555, 279, 5165, 10181, 315, 6401, 22020, 27924, 9002, 279, 12939, 315, 45774, 735, 369, 59904, 27344, 13, 220, 1032, 18878, 13283, 17650, 26028, 369, 2860, 45774, 735, 23730, 617, 1027, 743, 520, 220, 2031, 323, 220, 1399, 33983, 70, 294, 25173, 16, 369, 13673, 3026, 323, 3278, 11, 15947, 11, 3196, 389, 23369, 528, 2094, 315, 279, 13673, 7187, 13, 220, 975, 15483, 17959, 527, 30139, 311, 4606, 220, 868, 719, 10284, 4827, 1109, 279, 7427, 13, 220, 845, 4452, 11, 279, 46752, 528, 2094, 11, 5423, 304, 8494, 11, 1253, 387, 39413, 311, 1862, 23669, 17685, 39097, 13, 220, 24, 5751, 3766, 14830, 9269, 1766, 430, 7859, 7446, 23730, 315, 45774, 735, 16, 41947, 24822, 927, 3116, 5672, 12207, 11293, 259, 7767, 11, 23377, 13241, 17685, 39097, 304, 9498, 12884, 13, 220, 24, 1115, 24897, 430, 45774, 735, 16, 1436, 1514, 459, 3062, 3560, 304, 17685, 2890, 323, 59904, 27344, 13, 1666, 1778, 11, 279, 9395, 315, 420, 4007, 574, 311, 19874, 279, 5133, 1990, 34625, 45774, 735, 16, 23730, 11, 1701, 264, 13945, 8040, 13673, 45774, 735, 3691, 4729, 11, 449, 1317, 9860, 59904, 5326, 304, 4029, 1773, 86, 6427, 9191, 13673, 3278, 13, 1226, 1101, 16495, 311, 8417, 3508, 1070, 1051, 19660, 43918, 57240, 369, 34625, 45774, 735, 16, 528, 2094, 311, 387, 5938, 449, 4827, 59904, 5326, 13, 32009, 323, 5528, 52878, 362, 220, 20, 4771, 11, 2033, 95449, 11, 4288, 4147, 14400, 9269, 315, 7446, 35719, 73796, 311, 5471, 59904, 304, 3278, 320, 48268, 2411, 1357, 731, 2939, 533, 554, 95709, 19723, 11, 9362, 2843, 3204, 8, 65362, 304, 220, 2550, 23, 13, 11215, 320, 308, 284, 220, 3965, 15, 11, 20330, 63247, 2031, 8, 449, 320, 72, 8, 459, 3685, 20237, 7953, 220, 20, 1667, 323, 320, 3893, 8, 539, 12588, 904, 24099, 320, 16564, 36908, 14039, 15419, 8, 3967, 311, 7958, 17685, 39097, 220, 1114, 1051, 45425, 1701, 34941, 6638, 13, 4740, 9362, 2843, 3204, 11, 13324, 1051, 18719, 311, 387, 961, 315, 1403, 220, 20, 4771, 1833, 5352, 90380, 7978, 11, 6522, 311, 264, 2860, 1833, 5352, 315, 220, 975, 13, 20, 1667, 26, 279, 50544, 5843, 13138, 992, 19723, 315, 77188, 304, 11215, 320, 2989, 7934, 54, 570, 220, 10410, 20, 3278, 8308, 264, 3691, 11900, 48964, 520, 26954, 323, 1884, 449, 11866, 43736, 4907, 528, 2094, 23246, 8848, 15, 597, 41, 510, 2636, 96103, 60, 477, 871, 975, 220, 7007, 597, 41, 510, 8652, 15, 96103, 2526, 320, 308, 284, 220, 1114, 14, 10410, 20, 11, 220, 16, 13, 16, 11587, 477, 49326, 45774, 423, 73796, 320, 24567, 311, 1202, 2723, 449, 59904, 11, 220, 972, 308, 284, 220, 2137, 14, 10410, 20, 8, 1051, 28544, 13, 362, 4726, 220, 1774, 3278, 4737, 4208, 24470, 258, 1051, 28544, 4245, 311, 4208, 24470, 258, 75387, 449, 45774, 735, 39097, 13, 220, 777, 11215, 7554, 22590, 2850, 988, 1051, 1101, 28544, 320, 308, 284, 220, 806, 570, 578, 1510, 4007, 5343, 220, 10148, 18, 3278, 320, 1600, 40, 23966, 13, 220, 16, 124232, 883, 369, 279, 6156, 6492, 13, 578, 220, 6804, 16, 3278, 889, 1047, 264, 19179, 315, 2860, 32426, 220, 914, 46, 19694, 520, 26954, 1051, 5343, 304, 29060, 1405, 220, 914, 46, 19694, 574, 5343, 439, 264, 22590, 50759, 13, 34991, 16369, 14771, 574, 12457, 505, 682, 3278, 13, 578, 11344, 50281, 10554, 315, 279, 3907, 315, 11104, 8494, 3984, 31308, 14765, 13, 11995, 9362, 2843, 3204, 323, 393, 7416, 14757, 84864, 449, 279, 42021, 315, 77434, 323, 1051, 77653, 3210, 9879, 389, 279, 13673, 1561, 17340, 33135, 70544, 33212, 30183, 6966, 51295, 9390, 3965, 11194, 17786, 6069, 323, 674, 6966, 51295, 9390, 8258, 11030, 13074, 2839, 570, 13415, 828, 32008, 14765, 574, 3984, 555, 279, 11344, 8483, 50281, 10554, 315, 279, 11104, 13673, 6011, 315, 6401, 30183, 1049, 24, 14, 1187, 570, 4015, 1308, 11855, 369, 90380, 7978, 1051, 36051, 291, 311, 369, 420, 990, 13, 83808, 23730, 362, 659, 28324, 1601, 291, 11, 5347, 5118, 519, 22018, 3691, 11900, 48964, 320, 1785, 48, 8, 8040, 323, 33432, 555, 279, 26211, 9251, 315, 23225, 574, 1511, 311, 8417, 128257, 198, 128256, 78191, 198, 61279, 25896, 649, 387, 2324, 10223, 4455, 2345, 36046, 439, 584, 4325, 11, 994, 18638, 78332, 649, 3719, 8104, 34446, 323, 1121, 304, 28353, 11, 44500, 24589, 323, 264, 5190, 29528, 5326, 13, 2030, 3495, 505, 3279, 411, 22607, 276, 3907, 596, 39700, 323, 6401, 38710, 8483, 10181, 706, 10675, 1070, 1253, 387, 2555, 499, 649, 656, 311, 1520, 8108, 701, 5326, 315, 78332, 3010, 304, 2324, 13, 763, 20632, 449, 279, 3907, 315, 11104, 8494, 11, 279, 4007, 7111, 520, 279, 5133, 1990, 59904, 14228, 8952, 8200, 323, 28170, 735, 16, 23730, 304, 4661, 220, 16, 11, 3443, 9191, 13673, 3278, 927, 264, 220, 975, 13, 20, 4771, 4261, 505, 279, 50544, 5843, 13138, 992, 19723, 315, 77188, 11215, 13, 1102, 1766, 3278, 889, 30912, 810, 1109, 220, 1041, 8162, 51870, 315, 28170, 735, 16, 15652, 2345, 26378, 12031, 311, 922, 220, 6549, 70, 315, 6453, 16312, 88, 24822, 11, 477, 832, 4791, 38502, 17482, 315, 24822, 2345, 52898, 220, 2148, 4, 2753, 4461, 311, 617, 904, 59904, 7863, 311, 13324, 889, 27073, 2753, 1109, 220, 1399, 8162, 51870, 824, 1938, 11, 902, 374, 279, 1510, 28170, 735, 26613, 23730, 73545, 304, 8494, 369, 3278, 13, 2684, 1051, 1524, 810, 6928, 3135, 9002, 18638, 78332, 11, 449, 1884, 889, 30912, 279, 1455, 28170, 735, 16, 14713, 872, 5326, 315, 8952, 2065, 4661, 304, 4376, 320, 2491, 53172, 19723, 3063, 2999, 13, 19412, 4567, 1071, 279, 3135, 1051, 4726, 6029, 315, 279, 7720, 315, 28170, 735, 16, 11, 902, 706, 1101, 1027, 6982, 311, 18885, 41713, 2890, 13, 330, 8140, 3135, 527, 9678, 315, 1690, 9749, 9547, 369, 59904, 7969, 11, 2737, 2547, 3148, 1963, 11, 35719, 23730, 11, 45774, 423, 2704, 323, 46941, 8624, 1359, 568, 1071, 13, 330, 16323, 7978, 315, 28170, 735, 16, 617, 11054, 264, 9200, 3560, 304, 279, 1841, 2054, 79933, 315, 279, 28170, 735, 16, 36814, 519, 17685, 28896, 1778, 439, 52368, 3768, 18595, 11, 902, 374, 11846, 311, 7417, 17685, 77318, 13, 330, 32, 3766, 469, 17218, 9269, 15151, 34625, 28170, 735, 16, 528, 2094, 315, 2753, 1109, 220, 1041, 8162, 51870, 824, 1938, 1253, 387, 2288, 3428, 369, 420, 1841, 2054, 79933, 13, 330, 53, 76652, 735, 16, 1253, 1101, 12192, 17685, 2890, 555, 20747, 5977, 5370, 17685, 594, 269, 7278, 13307, 1210, 2100, 11, 1148, 1288, 584, 8343, 11, 323, 1268, 1790, 30, 2999, 13, 4567, 1071, 12459, 810, 1109, 220, 1041, 8162, 51870, 315, 28170, 735, 16, 7446, 574, 10728, 17223, 11, 37875, 11, 433, 4536, 956, 2288, 5107, 311, 656, 13, 330, 43066, 287, 420, 1790, 7446, 28170, 735, 16, 649, 6847, 387, 17427, 555, 35208, 1990, 220, 2075, 4235, 3965, 70, 11, 13890, 311, 832, 311, 1403, 17482, 11, 315, 24822, 1778, 439, 68798, 11, 63577, 11, 79276, 323, 74873, 1359, 568, 1071, 13, 330, 2181, 596, 2500, 2944, 311, 1833, 586, 2890, 17959, 11, 902, 29115, 5190, 36581, 23730, 2737, 832, 311, 1403, 17482, 315, 6307, 16312, 88, 24822, 50004, 374, 304, 8614, 449, 1057, 4007, 596, 19075, 1210, 578, 4007, 374, 4756, 304, 12369, 612, 5830, 13, 220, 128257, 198 ]

2,000

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Background T zone lymphoma (TZL), a histologic variant of peripheral T cell lymphoma, represents about 12% of all canine lymphomas. Golden Retrievers appear predisposed, representing over 40% of TZL cases. Prior research found that asymptomatic aged Golden Retrievers frequently have populations of T zone-like cells (phenotypically identical to TZL) of undetermined significance (TZUS), potentially representing a pre-clinical state. These findings suggest a genetic risk factor for this disease and caused us to investigate potential genes of interest using a genome-wide association study of privately-owned U.S. Golden Retrievers. Results Dogs were categorized as TZL ( n = 95), TZUS ( n = 142), or control ( n = 101) using flow cytometry and genotyped using the Illumina CanineHD BeadChip. Using a mixed linear model adjusting for population stratification, we found association with genome-wide significance in regions on chromosomes 8 and 14. The chromosome 14 peak included four SNPs (Odds Ratio = 1.18–1.19, p = .3 × 10 − 5 –5.1 × 10 − 5 ) near three hyaluronidase genes ( SPAM1, HYAL4, and HYALP1 ). Targeted resequencing of this region using a custom sequence capture array identified missense mutations in all three genes; the variant in SPAM1 was predicted to be damaging. These mutations were also associated with risk for mast cell tumors among Golden Retrievers in an unrelated study. The chromosome 8 peak contained 7 SNPs (Odds Ratio = 1.24–1.42, p = 2.7 × 10 − 7 –7.5 × 10 − 5 ) near genes involved in thyroid hormone regulation ( DIO2 and TSHR ). A prior study from our laboratory found hypothyroidism is inversely associated with TZL risk. No coding mutations were found with targeted resequencing but identified variants may play a regulatory role for all or some of the genes. Conclusions The pathogenesis of canine TZL may be related to hyaluronan breakdown and subsequent production of pro-inflammatory and pro-oncogenic byproducts. The association on chromosome 8 may indicate thyroid hormone is involved in TZL development, consistent with findings from a previous study evaluating epidemiologic risk factors for TZL. Future work is needed to elucidate these mechanisms. Background T zone lymphoma (TZL), a histologic variant of peripheral T cell lymphoma (PTCL), accounts for about 12% of all canine lymphomas [ 1 , 2 ] but is almost never seen in human patients. In dogs, this disease follows an indolent course with average survival of > 2 years independent of treatment, compared to < 1 year with most other lymphoma subtypes [ 3 , 4 , 5 ]. TZL can be readily diagnosed by histopathology or by flow cytometric identification of a homogeneous expansion of T cells lacking expression of CD45, a pan-leukocyte surface marker [ 3 , 6 , 7 ]. Previously, we observed that > 30% of Golden Retrievers without lymphocytosis or lymphadenopathy have T cells phenotypically similar (lacking CD45 expression) to TZL in their blood [ 8 ]; as we are unsure of the clinical relevance of this finding, we have adopted the term T zone-like cells of undetermined significance (TZUS) for these dogs [ 9 ]. We hypothesize that TZUS may represent a pre-clinical state that could undergo neoplastic transformation and progress to overt TZL. Few studies have investigated the pathogenesis of canine TZL. We recently reported that both hypothyroidism and omega-3 supplementation are associated with decreased odds of TZL [ 9 ]. It has also been noted that over 40% of TZL cases are Golden Retrievers [ 3 ]. This finding suggests a genetic predisposition for TZL and caused us to pursue a study to identify potential pathways of interest. To date, no studies have agnostically evaluated germline risk for PTCL in dogs or humans. The objective of this study was to identify genetic risk factors for canine TZL using a genome-wide association study (GWAS) and subsequent targeted sequencing. This aim of this study is to provide insight into the etiology and underlying risk for developing this disease. Results The source population included 95 TZL cases (ages 7–14 years), 142 TZUS dogs > 9 years old (dogs with no clinical signs of TZL, but > 1% of T cells were CD5 + CD45 − ), and 101 control dogs > 9 years old (dogs with no clinical signs of TZL and no CD5 + CD45 − T cells). Sixteen dogs were removed due to low genotyping rate (< 97.5%; 7 TZL, 5 TZUS, 4 controls) and 6 were removed due to suspected European origin (2 TZUS, 4 controls). After quality filtering a final dataset of 267 dogs (79 TZL, 108 TZUS, 80 controls), and 110,405 single nucleotide polymorphism (SNPs) were used for association analyses. TZUS and controls indistinguishable by GWAS When the combined TZL and TZUS group was compared to controls, no p -values were outside the 95% confidence interval threshold on the quantile-quantile (QQ)-plot (Additional file 1 A). In contrast, when TZL were compared to the combined TZUS and control group, a group of SNPs significantly deviated from the expected distribution (Fig. 1 ). Supporting this, pairwise GWAS of TZL versus controls and TZL versus TZUS had suggestive associations for this group of SNPs, despite none of the p -values falling outside the 95% confidence interval (CI) on the QQ-plot (Additional file 1 B and C). This implies TZUS and controls are similar, and the enhanced power from combining them as a reference group allows those SNPs to reach genome-wide significance. In contrast, the TZUS versus control comparison did not share any suggestive SNPs with the TZL versus control comparison, as would be expected if TZL and TZUS were similar. We thus chose to combine TZUS and controls for our main analysis and will reference it as the “TZL versus all” comparison for the remainder of the paper. Fig. 1 GWA for TZL cases vs. combined reference (TZUS + controls). Left, QQ-plot demonstrating observed p -values deviate from the expected at a significance level of p < 10 − 4 . Shaded area indicates 95% confidence interval. Right, Manhattan plot showing peaks that are", "role": "user" }, { "content": "A genetic mutation might be the reason dogs with hypothyroidism are less likely to develop T-zone lymphoma (TZL). That's the finding from Morris Animal Foundation-funded researchers at Colorado State University who tried to identify genetic risk factors for TZL using a genome-wide association study (GWAS) and subsequent targeted sequencing. They recently published their results in the journal BMC Genomics. \"Golden retrievers are predisposed to so many cancers,\" said Dr. Julia Labadie, Morris Animal Foundation epidemiologist, who conducted the study as part of her doctoral work. \"Any piece of the puzzle we can solve to help us understand why, can really help this breed. Of course, golden retrievers aren't the only dogs getting this cancer, so what we learn has implications for all dogs at risk for TZL.\" The published study is a follow up to a 2019 publication from the same team that examined associations of environment and health history among golden retrievers with TZL. The team found that both hypothyroidism and omega-3 supplementation are associated with decreased risk of TZL and suggested a genetic predisposition for TZL. \"This gives us one more piece of information which we can add to future studies to ultimately help us understand why dogs get this and other cancers,\" said Dr. Janet Patterson-Kane, Morris Animal Foundation Chief Scientific Officer. \"With continued research, we are making progress toward the development of preventive measures, earlier diagnosis and successful treatments.\" The team used a subset of banked blood samples from the original study to look more closely for a genetic explanation for their initial findings. The samples used were from 95 dogs that were positive for TZL, 142 from dogs that possessed T-zone like cells that may have been precancerous, and 101 from a control group of dogs that were at least 9 years old and did not have the disease. Researchers extracted DNA from each sample and genotyped them to identify areas in the dogs' chromosomes that were associated with having or not having the disease. One region of interest was found in chromosome 8, which has an association with thyroid hormone regulation. While variation in the genes associated with thyroid function has not yet been confirmed, identifying the region containing thyroid hormone genes in the genetic risk factor study as well as hypothyroidism in the environmental risk factor study strongly suggests that this area of the dog's genome is an important clue to the underlying causes of T-zone lymphoma. \"This study illustrates the value of combined genetic and environmental risk factor analysis, because identifying hypothyroidism in the environmental study, as well as a genetic region that governs thyroid function in the genetic study, highlights the importance of this part of the dog genome in this disease,\" said Dr. Anne Avery, Professor, Department of Microbiology, Immunology and Pathology at Colorado State University. \"The relevant genes may be the thyroid function genes themselves, or other genes in the region, but the strong evidence from the combined studies about the importance of this genetic region means that we can be confident that further focus on this area will be fruitful.\" The CSU team also found four variants on chromosome 14 that were associated with an increased risk of TZL. These same variants were previously found to be associated with risk for mast cell tumors among golden retrievers, which could suggest a shared mechanism underlying development of the two cancers. This unrelated study from the Broad Institute used similar genotyping methods. The CSU team didn't find that dogs with the chromosomal variants were likely to have both tumors, though. T-zone lymphoma is a slowly progressive form of the cancer that usually develops in older dogs, comprising about 12% of canine lymphoma cases. It is far more prevalent in golden retrievers than any other breed, with golden retrievers representing over 40% of all reported cases. Most of the golden retrievers in this study's control group were drawn from Morris Animal Foundation's Canine Lifetime Health Project. This is a registry of dogs whose owners are interested in participating in clinical trials and other studies to improve canine health. Many of the dogs entered into the registry during the recruitment phase of Morris Animal Foundation's Golden Retriever Lifetime Study, but were too old to participate in the Study at the time of their enrollment. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Background T zone lymphoma (TZL), a histologic variant of peripheral T cell lymphoma, represents about 12% of all canine lymphomas. Golden Retrievers appear predisposed, representing over 40% of TZL cases. Prior research found that asymptomatic aged Golden Retrievers frequently have populations of T zone-like cells (phenotypically identical to TZL) of undetermined significance (TZUS), potentially representing a pre-clinical state. These findings suggest a genetic risk factor for this disease and caused us to investigate potential genes of interest using a genome-wide association study of privately-owned U.S. Golden Retrievers. Results Dogs were categorized as TZL ( n = 95), TZUS ( n = 142), or control ( n = 101) using flow cytometry and genotyped using the Illumina CanineHD BeadChip. Using a mixed linear model adjusting for population stratification, we found association with genome-wide significance in regions on chromosomes 8 and 14. The chromosome 14 peak included four SNPs (Odds Ratio = 1.18–1.19, p = .3 × 10 − 5 –5.1 × 10 − 5 ) near three hyaluronidase genes ( SPAM1, HYAL4, and HYALP1 ). Targeted resequencing of this region using a custom sequence capture array identified missense mutations in all three genes; the variant in SPAM1 was predicted to be damaging. These mutations were also associated with risk for mast cell tumors among Golden Retrievers in an unrelated study. The chromosome 8 peak contained 7 SNPs (Odds Ratio = 1.24–1.42, p = 2.7 × 10 − 7 –7.5 × 10 − 5 ) near genes involved in thyroid hormone regulation ( DIO2 and TSHR ). A prior study from our laboratory found hypothyroidism is inversely associated with TZL risk. No coding mutations were found with targeted resequencing but identified variants may play a regulatory role for all or some of the genes. Conclusions The pathogenesis of canine TZL may be related to hyaluronan breakdown and subsequent production of pro-inflammatory and pro-oncogenic byproducts. The association on chromosome 8 may indicate thyroid hormone is involved in TZL development, consistent with findings from a previous study evaluating epidemiologic risk factors for TZL. Future work is needed to elucidate these mechanisms. Background T zone lymphoma (TZL), a histologic variant of peripheral T cell lymphoma (PTCL), accounts for about 12% of all canine lymphomas [ 1 , 2 ] but is almost never seen in human patients. In dogs, this disease follows an indolent course with average survival of > 2 years independent of treatment, compared to < 1 year with most other lymphoma subtypes [ 3 , 4 , 5 ]. TZL can be readily diagnosed by histopathology or by flow cytometric identification of a homogeneous expansion of T cells lacking expression of CD45, a pan-leukocyte surface marker [ 3 , 6 , 7 ]. Previously, we observed that > 30% of Golden Retrievers without lymphocytosis or lymphadenopathy have T cells phenotypically similar (lacking CD45 expression) to TZL in their blood [ 8 ]; as we are unsure of the clinical relevance of this finding, we have adopted the term T zone-like cells of undetermined significance (TZUS) for these dogs [ 9 ]. We hypothesize that TZUS may represent a pre-clinical state that could undergo neoplastic transformation and progress to overt TZL. Few studies have investigated the pathogenesis of canine TZL. We recently reported that both hypothyroidism and omega-3 supplementation are associated with decreased odds of TZL [ 9 ]. It has also been noted that over 40% of TZL cases are Golden Retrievers [ 3 ]. This finding suggests a genetic predisposition for TZL and caused us to pursue a study to identify potential pathways of interest. To date, no studies have agnostically evaluated germline risk for PTCL in dogs or humans. The objective of this study was to identify genetic risk factors for canine TZL using a genome-wide association study (GWAS) and subsequent targeted sequencing. This aim of this study is to provide insight into the etiology and underlying risk for developing this disease. Results The source population included 95 TZL cases (ages 7–14 years), 142 TZUS dogs > 9 years old (dogs with no clinical signs of TZL, but > 1% of T cells were CD5 + CD45 − ), and 101 control dogs > 9 years old (dogs with no clinical signs of TZL and no CD5 + CD45 − T cells). Sixteen dogs were removed due to low genotyping rate (< 97.5%; 7 TZL, 5 TZUS, 4 controls) and 6 were removed due to suspected European origin (2 TZUS, 4 controls). After quality filtering a final dataset of 267 dogs (79 TZL, 108 TZUS, 80 controls), and 110,405 single nucleotide polymorphism (SNPs) were used for association analyses. TZUS and controls indistinguishable by GWAS When the combined TZL and TZUS group was compared to controls, no p -values were outside the 95% confidence interval threshold on the quantile-quantile (QQ)-plot (Additional file 1 A). In contrast, when TZL were compared to the combined TZUS and control group, a group of SNPs significantly deviated from the expected distribution (Fig. 1 ). Supporting this, pairwise GWAS of TZL versus controls and TZL versus TZUS had suggestive associations for this group of SNPs, despite none of the p -values falling outside the 95% confidence interval (CI) on the QQ-plot (Additional file 1 B and C). This implies TZUS and controls are similar, and the enhanced power from combining them as a reference group allows those SNPs to reach genome-wide significance. In contrast, the TZUS versus control comparison did not share any suggestive SNPs with the TZL versus control comparison, as would be expected if TZL and TZUS were similar. We thus chose to combine TZUS and controls for our main analysis and will reference it as the “TZL versus all” comparison for the remainder of the paper. Fig. 1 GWA for TZL cases vs. combined reference (TZUS + controls). Left, QQ-plot demonstrating observed p -values deviate from the expected at a significance level of p < 10 − 4 . Shaded area indicates 95% confidence interval. Right, Manhattan plot showing peaks that are<|im_end|> <|im_start|>assistant A genetic mutation might be the reason dogs with hypothyroidism are less likely to develop T-zone lymphoma (TZL). That's the finding from Morris Animal Foundation-funded researchers at Colorado State University who tried to identify genetic risk factors for TZL using a genome-wide association study (GWAS) and subsequent targeted sequencing. They recently published their results in the journal BMC Genomics. "Golden retrievers are predisposed to so many cancers," said Dr. Julia Labadie, Morris Animal Foundation epidemiologist, who conducted the study as part of her doctoral work. "Any piece of the puzzle we can solve to help us understand why, can really help this breed. Of course, golden retrievers aren't the only dogs getting this cancer, so what we learn has implications for all dogs at risk for TZL." The published study is a follow up to a 2019 publication from the same team that examined associations of environment and health history among golden retrievers with TZL. The team found that both hypothyroidism and omega-3 supplementation are associated with decreased risk of TZL and suggested a genetic predisposition for TZL. "This gives us one more piece of information which we can add to future studies to ultimately help us understand why dogs get this and other cancers," said Dr. Janet Patterson-Kane, Morris Animal Foundation Chief Scientific Officer. "With continued research, we are making progress toward the development of preventive measures, earlier diagnosis and successful treatments." The team used a subset of banked blood samples from the original study to look more closely for a genetic explanation for their initial findings. The samples used were from 95 dogs that were positive for TZL, 142 from dogs that possessed T-zone like cells that may have been precancerous, and 101 from a control group of dogs that were at least 9 years old and did not have the disease. Researchers extracted DNA from each sample and genotyped them to identify areas in the dogs' chromosomes that were associated with having or not having the disease. One region of interest was found in chromosome 8, which has an association with thyroid hormone regulation. While variation in the genes associated with thyroid function has not yet been confirmed, identifying the region containing thyroid hormone genes in the genetic risk factor study as well as hypothyroidism in the environmental risk factor study strongly suggests that this area of the dog's genome is an important clue to the underlying causes of T-zone lymphoma. "This study illustrates the value of combined genetic and environmental risk factor analysis, because identifying hypothyroidism in the environmental study, as well as a genetic region that governs thyroid function in the genetic study, highlights the importance of this part of the dog genome in this disease," said Dr. Anne Avery, Professor, Department of Microbiology, Immunology and Pathology at Colorado State University. "The relevant genes may be the thyroid function genes themselves, or other genes in the region, but the strong evidence from the combined studies about the importance of this genetic region means that we can be confident that further focus on this area will be fruitful." The CSU team also found four variants on chromosome 14 that were associated with an increased risk of TZL. These same variants were previously found to be associated with risk for mast cell tumors among golden retrievers, which could suggest a shared mechanism underlying development of the two cancers. This unrelated study from the Broad Institute used similar genotyping methods. The CSU team didn't find that dogs with the chromosomal variants were likely to have both tumors, though. T-zone lymphoma is a slowly progressive form of the cancer that usually develops in older dogs, comprising about 12% of canine lymphoma cases. It is far more prevalent in golden retrievers than any other breed, with golden retrievers representing over 40% of all reported cases. Most of the golden retrievers in this study's control group were drawn from Morris Animal Foundation's Canine Lifetime Health Project. This is a registry of dogs whose owners are interested in participating in clinical trials and other studies to improve canine health. Many of the dogs entered into the registry during the recruitment phase of Morris Animal Foundation's Golden Retriever Lifetime Study, but were too old to participate in the Study at the time of their enrollment. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 25837, 350, 10353, 43745, 7942, 320, 91526, 43, 705, 264, 13034, 39227, 11678, 315, 35688, 350, 2849, 43745, 7942, 11, 11105, 922, 220, 717, 4, 315, 682, 76082, 43745, 23063, 13, 18288, 20035, 3078, 5101, 80632, 3950, 11, 14393, 927, 220, 1272, 4, 315, 88205, 43, 5157, 13, 32499, 3495, 1766, 430, 97354, 13795, 20330, 18288, 20035, 3078, 14134, 617, 22673, 315, 350, 10353, 12970, 7917, 320, 15112, 37941, 2740, 20086, 311, 88205, 43, 8, 315, 2073, 47737, 26431, 320, 91526, 2078, 705, 13893, 14393, 264, 864, 31717, 258, 950, 1614, 13, 4314, 14955, 4284, 264, 19465, 5326, 8331, 369, 420, 8624, 323, 9057, 603, 311, 19874, 4754, 21389, 315, 2802, 1701, 264, 33869, 25480, 15360, 4007, 315, 38171, 29799, 549, 815, 13, 18288, 20035, 3078, 13, 18591, 39525, 1051, 71974, 439, 88205, 43, 320, 308, 284, 220, 2721, 705, 88205, 2078, 320, 308, 284, 220, 10239, 705, 477, 2585, 320, 308, 284, 220, 4645, 8, 1701, 6530, 79909, 7133, 323, 4173, 354, 33601, 1701, 279, 61720, 2259, 3053, 483, 19694, 2893, 329, 57517, 13, 12362, 264, 9709, 13790, 1646, 43468, 369, 7187, 44397, 2461, 11, 584, 1766, 15360, 449, 33869, 25480, 26431, 304, 13918, 389, 83181, 220, 23, 323, 220, 975, 13, 578, 51815, 220, 975, 16557, 5343, 3116, 18407, 21051, 320, 46, 34750, 51848, 284, 220, 16, 13, 972, 4235, 16, 13, 777, 11, 281, 284, 662, 18, 25800, 220, 605, 25173, 220, 20, 1389, 20, 13, 16, 25800, 220, 605, 25173, 220, 20, 883, 3221, 2380, 6409, 278, 37190, 307, 521, 21389, 320, 9440, 1428, 16, 11, 64352, 984, 19, 11, 323, 64352, 984, 47, 16, 7609, 13791, 291, 312, 6741, 11627, 315, 420, 5654, 1701, 264, 2587, 8668, 12602, 1358, 11054, 3194, 1137, 34684, 304, 682, 2380, 21389, 26, 279, 11678, 304, 9440, 1428, 16, 574, 19698, 311, 387, 34446, 13, 4314, 34684, 1051, 1101, 5938, 449, 5326, 369, 19218, 2849, 56071, 4315, 18288, 20035, 3078, 304, 459, 46305, 4007, 13, 578, 51815, 220, 23, 16557, 13282, 220, 22, 18407, 21051, 320, 46, 34750, 51848, 284, 220, 16, 13, 1187, 4235, 16, 13, 2983, 11, 281, 284, 220, 17, 13, 22, 25800, 220, 605, 25173, 220, 22, 1389, 22, 13, 20, 25800, 220, 605, 25173, 220, 20, 883, 3221, 21389, 6532, 304, 54060, 36908, 19812, 320, 423, 3895, 17, 323, 350, 8758, 49, 7609, 362, 4972, 4007, 505, 1057, 27692, 1766, 9950, 29671, 1607, 2191, 374, 65683, 989, 5938, 449, 88205, 43, 5326, 13, 2360, 11058, 34684, 1051, 1766, 449, 17550, 312, 6741, 11627, 719, 11054, 27103, 1253, 1514, 264, 23331, 3560, 369, 682, 477, 1063, 315, 279, 21389, 13, 1221, 24436, 578, 1853, 52379, 315, 76082, 88205, 43, 1253, 387, 5552, 311, 6409, 278, 37190, 276, 31085, 323, 17876, 5788, 315, 463, 67595, 323, 463, 10539, 66, 29569, 555, 10354, 13, 578, 15360, 389, 51815, 220, 23, 1253, 13519, 54060, 36908, 374, 6532, 304, 88205, 43, 4500, 11, 13263, 449, 14955, 505, 264, 3766, 4007, 38663, 62057, 39227, 5326, 9547, 369, 88205, 43, 13, 12781, 990, 374, 4460, 311, 97298, 349, 1521, 24717, 13, 25837, 350, 10353, 43745, 7942, 320, 91526, 43, 705, 264, 13034, 39227, 11678, 315, 35688, 350, 2849, 43745, 7942, 320, 2898, 3218, 705, 9815, 369, 922, 220, 717, 4, 315, 682, 76082, 43745, 23063, 510, 220, 16, 1174, 220, 17, 2331, 719, 374, 4661, 2646, 3970, 304, 3823, 6978, 13, 763, 12875, 11, 420, 8624, 11263, 459, 1280, 337, 306, 3388, 449, 5578, 20237, 315, 871, 220, 17, 1667, 9678, 315, 6514, 11, 7863, 311, 366, 220, 16, 1060, 449, 1455, 1023, 43745, 7942, 1207, 9426, 510, 220, 18, 1174, 220, 19, 1174, 220, 20, 21087, 88205, 43, 649, 387, 31368, 29704, 555, 13034, 36211, 2508, 477, 555, 6530, 79909, 24264, 22654, 315, 264, 87282, 14800, 315, 350, 7917, 32161, 7645, 315, 11325, 1774, 11, 264, 7363, 31307, 3178, 79759, 7479, 11381, 510, 220, 18, 1174, 220, 21, 1174, 220, 22, 21087, 59787, 11, 584, 13468, 430, 871, 220, 966, 4, 315, 18288, 20035, 3078, 2085, 43745, 511, 16820, 10934, 477, 43745, 21825, 54042, 617, 350, 7917, 14345, 37941, 2740, 4528, 320, 75, 9162, 11325, 1774, 7645, 8, 311, 88205, 43, 304, 872, 6680, 510, 220, 23, 13385, 439, 584, 527, 44003, 315, 279, 14830, 41961, 315, 420, 9455, 11, 584, 617, 18306, 279, 4751, 350, 10353, 12970, 7917, 315, 2073, 47737, 26431, 320, 91526, 2078, 8, 369, 1521, 12875, 510, 220, 24, 21087, 1226, 22601, 27985, 430, 88205, 2078, 1253, 4097, 264, 864, 31717, 258, 950, 1614, 430, 1436, 37771, 841, 454, 52279, 18475, 323, 5208, 311, 43661, 88205, 43, 13, 44015, 7978, 617, 27313, 279, 1853, 52379, 315, 76082, 88205, 43, 13, 1226, 6051, 5068, 430, 2225, 9950, 29671, 1607, 2191, 323, 34998, 12, 18, 73796, 527, 5938, 449, 25983, 21448, 315, 88205, 43, 510, 220, 24, 21087, 1102, 706, 1101, 1027, 10555, 430, 927, 220, 1272, 4, 315, 88205, 43, 5157, 527, 18288, 20035, 3078, 510, 220, 18, 21087, 1115, 9455, 13533, 264, 19465, 80632, 3571, 369, 88205, 43, 323, 9057, 603, 311, 23564, 264, 4007, 311, 10765, 4754, 44014, 315, 2802, 13, 2057, 2457, 11, 912, 7978, 617, 945, 32557, 2740, 26126, 17684, 1029, 483, 5326, 369, 19932, 3218, 304, 12875, 477, 12966, 13, 578, 16945, 315, 420, 4007, 574, 311, 10765, 19465, 5326, 9547, 369, 76082, 88205, 43, 1701, 264, 33869, 25480, 15360, 4007, 320, 63665, 1950, 8, 323, 17876, 17550, 62119, 13, 1115, 9395, 315, 420, 4007, 374, 311, 3493, 20616, 1139, 279, 1880, 31226, 323, 16940, 5326, 369, 11469, 420, 8624, 13, 18591, 578, 2592, 7187, 5343, 220, 2721, 88205, 43, 5157, 320, 1154, 220, 22, 4235, 975, 1667, 705, 220, 10239, 88205, 2078, 12875, 871, 220, 24, 1667, 2362, 320, 81134, 449, 912, 14830, 12195, 315, 88205, 43, 11, 719, 871, 220, 16, 4, 315, 350, 7917, 1051, 11325, 20, 489, 11325, 1774, 25173, 7026, 323, 220, 4645, 2585, 12875, 871, 220, 24, 1667, 2362, 320, 81134, 449, 912, 14830, 12195, 315, 88205, 43, 323, 912, 11325, 20, 489, 11325, 1774, 25173, 350, 7917, 570, 19198, 15247, 12875, 1051, 7108, 4245, 311, 3428, 4173, 67247, 4478, 23246, 220, 3534, 13, 20, 16571, 220, 22, 88205, 43, 11, 220, 20, 88205, 2078, 11, 220, 19, 11835, 8, 323, 220, 21, 1051, 7108, 4245, 311, 24740, 7665, 6371, 320, 17, 88205, 2078, 11, 220, 19, 11835, 570, 4740, 4367, 30770, 264, 1620, 10550, 315, 220, 16567, 12875, 320, 4643, 88205, 43, 11, 220, 6640, 88205, 2078, 11, 220, 1490, 11835, 705, 323, 220, 5120, 11, 16408, 3254, 31484, 69044, 46033, 53907, 320, 19503, 21051, 8, 1051, 1511, 369, 15360, 29060, 13, 88205, 2078, 323, 11835, 1280, 89747, 481, 555, 42353, 1950, 3277, 279, 11093, 88205, 43, 323, 88205, 2078, 1912, 574, 7863, 311, 11835, 11, 912, 281, 482, 3745, 1051, 4994, 279, 220, 2721, 4, 12410, 10074, 12447, 389, 279, 10484, 458, 12, 31548, 458, 320, 49126, 7435, 4569, 320, 30119, 1052, 220, 16, 362, 570, 763, 13168, 11, 994, 88205, 43, 1051, 7863, 311, 279, 11093, 88205, 2078, 323, 2585, 1912, 11, 264, 1912, 315, 18407, 21051, 12207, 3567, 10234, 505, 279, 3685, 8141, 320, 30035, 13, 220, 16, 7609, 75096, 420, 11, 93859, 42353, 1950, 315, 88205, 43, 19579, 11835, 323, 88205, 43, 19579, 88205, 2078, 1047, 99578, 30257, 369, 420, 1912, 315, 18407, 21051, 11, 8994, 7000, 315, 279, 281, 482, 3745, 16054, 4994, 279, 220, 2721, 4, 12410, 10074, 320, 11487, 8, 389, 279, 74215, 12, 4569, 320, 30119, 1052, 220, 16, 426, 323, 356, 570, 1115, 24897, 88205, 2078, 323, 11835, 527, 4528, 11, 323, 279, 24872, 2410, 505, 35271, 1124, 439, 264, 5905, 1912, 6276, 1884, 18407, 21051, 311, 5662, 33869, 25480, 26431, 13, 763, 13168, 11, 279, 88205, 2078, 19579, 2585, 12593, 1550, 539, 4430, 904, 99578, 18407, 21051, 449, 279, 88205, 43, 19579, 2585, 12593, 11, 439, 1053, 387, 3685, 422, 88205, 43, 323, 88205, 2078, 1051, 4528, 13, 1226, 8617, 14896, 311, 16343, 88205, 2078, 323, 11835, 369, 1057, 1925, 6492, 323, 690, 5905, 433, 439, 279, 1054, 91526, 43, 19579, 682, 863, 12593, 369, 279, 27410, 315, 279, 5684, 13, 23966, 13, 220, 16, 480, 27486, 369, 88205, 43, 5157, 6296, 13, 11093, 5905, 320, 91526, 2078, 489, 11835, 570, 14043, 11, 74215, 12, 4569, 45296, 13468, 281, 482, 3745, 3567, 6629, 505, 279, 3685, 520, 264, 26431, 2237, 315, 281, 366, 220, 605, 25173, 220, 19, 662, 1443, 14589, 3158, 15151, 220, 2721, 4, 12410, 10074, 13, 10291, 11, 29890, 7234, 9204, 40035, 430, 527, 128257, 198, 128256, 78191, 198, 32, 19465, 27472, 2643, 387, 279, 2944, 12875, 449, 9950, 29671, 1607, 2191, 527, 2753, 4461, 311, 2274, 350, 78863, 43745, 7942, 320, 91526, 43, 570, 3011, 596, 279, 9455, 505, 30283, 21995, 5114, 50701, 12074, 520, 15745, 3314, 3907, 889, 6818, 311, 10765, 19465, 5326, 9547, 369, 88205, 43, 1701, 264, 33869, 25480, 15360, 4007, 320, 63665, 1950, 8, 323, 17876, 17550, 62119, 13, 2435, 6051, 4756, 872, 3135, 304, 279, 8486, 82806, 9500, 24203, 13, 330, 60890, 10992, 3078, 527, 80632, 3950, 311, 779, 1690, 51423, 1359, 1071, 2999, 13, 40394, 11868, 329, 648, 11, 30283, 21995, 5114, 62057, 16549, 11, 889, 13375, 279, 4007, 439, 961, 315, 1077, 74657, 990, 13, 330, 8780, 6710, 315, 279, 25649, 584, 649, 11886, 311, 1520, 603, 3619, 3249, 11, 649, 2216, 1520, 420, 28875, 13, 5046, 3388, 11, 21411, 10992, 3078, 7784, 956, 279, 1193, 12875, 3794, 420, 9572, 11, 779, 1148, 584, 4048, 706, 25127, 369, 682, 12875, 520, 5326, 369, 88205, 43, 1210, 578, 4756, 4007, 374, 264, 1833, 709, 311, 264, 220, 679, 24, 17009, 505, 279, 1890, 2128, 430, 25078, 30257, 315, 4676, 323, 2890, 3925, 4315, 21411, 10992, 3078, 449, 88205, 43, 13, 578, 2128, 1766, 430, 2225, 9950, 29671, 1607, 2191, 323, 34998, 12, 18, 73796, 527, 5938, 449, 25983, 5326, 315, 88205, 43, 323, 12090, 264, 19465, 80632, 3571, 369, 88205, 43, 13, 330, 2028, 6835, 603, 832, 810, 6710, 315, 2038, 902, 584, 649, 923, 311, 3938, 7978, 311, 13967, 1520, 603, 3619, 3249, 12875, 636, 420, 323, 1023, 51423, 1359, 1071, 2999, 13, 54765, 58734, 16222, 2194, 11, 30283, 21995, 5114, 14681, 38130, 20148, 13, 330, 2409, 8738, 3495, 11, 584, 527, 3339, 5208, 9017, 279, 4500, 315, 71123, 11193, 11, 6931, 23842, 323, 6992, 22972, 1210, 578, 2128, 1511, 264, 27084, 315, 6201, 291, 6680, 10688, 505, 279, 4113, 4007, 311, 1427, 810, 15499, 369, 264, 19465, 16540, 369, 872, 2926, 14955, 13, 578, 10688, 1511, 1051, 505, 220, 2721, 12875, 430, 1051, 6928, 369, 88205, 43, 11, 220, 10239, 505, 12875, 430, 43890, 350, 78863, 1093, 7917, 430, 1253, 617, 1027, 5956, 11967, 788, 11, 323, 220, 4645, 505, 264, 2585, 1912, 315, 12875, 430, 1051, 520, 3325, 220, 24, 1667, 2362, 323, 1550, 539, 617, 279, 8624, 13, 59250, 28532, 15922, 505, 1855, 6205, 323, 4173, 354, 33601, 1124, 311, 10765, 5789, 304, 279, 12875, 6, 83181, 430, 1051, 5938, 449, 3515, 477, 539, 3515, 279, 8624, 13, 3861, 5654, 315, 2802, 574, 1766, 304, 51815, 220, 23, 11, 902, 706, 459, 15360, 449, 54060, 36908, 19812, 13, 6104, 23851, 304, 279, 21389, 5938, 449, 54060, 734, 706, 539, 3686, 1027, 11007, 11, 25607, 279, 5654, 8649, 54060, 36908, 21389, 304, 279, 19465, 5326, 8331, 4007, 439, 1664, 439, 9950, 29671, 1607, 2191, 304, 279, 12434, 5326, 8331, 4007, 16917, 13533, 430, 420, 3158, 315, 279, 5679, 596, 33869, 374, 459, 3062, 31089, 311, 279, 16940, 11384, 315, 350, 78863, 43745, 7942, 13, 330, 2028, 4007, 46480, 279, 907, 315, 11093, 19465, 323, 12434, 5326, 8331, 6492, 11, 1606, 25607, 9950, 29671, 1607, 2191, 304, 279, 12434, 4007, 11, 439, 1664, 439, 264, 19465, 5654, 430, 2633, 82, 54060, 734, 304, 279, 19465, 4007, 11, 22020, 279, 12939, 315, 420, 961, 315, 279, 5679, 33869, 304, 420, 8624, 1359, 1071, 2999, 13, 29026, 68580, 11, 17054, 11, 6011, 315, 18654, 81162, 11, 67335, 2508, 323, 8092, 2508, 520, 15745, 3314, 3907, 13, 330, 791, 9959, 21389, 1253, 387, 279, 54060, 734, 21389, 5694, 11, 477, 1023, 21389, 304, 279, 5654, 11, 719, 279, 3831, 6029, 505, 279, 11093, 7978, 922, 279, 12939, 315, 420, 19465, 5654, 3445, 430, 584, 649, 387, 16913, 430, 4726, 5357, 389, 420, 3158, 690, 387, 89684, 1210, 578, 10211, 52, 2128, 1101, 1766, 3116, 27103, 389, 51815, 220, 975, 430, 1051, 5938, 449, 459, 7319, 5326, 315, 88205, 43, 13, 4314, 1890, 27103, 1051, 8767, 1766, 311, 387, 5938, 449, 5326, 369, 19218, 2849, 56071, 4315, 21411, 10992, 3078, 11, 902, 1436, 4284, 264, 6222, 17383, 16940, 4500, 315, 279, 1403, 51423, 13, 1115, 46305, 4007, 505, 279, 16273, 10181, 1511, 4528, 4173, 67247, 5528, 13, 578, 10211, 52, 2128, 3287, 956, 1505, 430, 12875, 449, 279, 22083, 96108, 27103, 1051, 4461, 311, 617, 2225, 56071, 11, 3582, 13, 350, 78863, 43745, 7942, 374, 264, 14297, 23053, 1376, 315, 279, 9572, 430, 6118, 39671, 304, 9191, 12875, 11, 46338, 922, 220, 717, 4, 315, 76082, 43745, 7942, 5157, 13, 1102, 374, 3117, 810, 46941, 304, 21411, 10992, 3078, 1109, 904, 1023, 28875, 11, 449, 21411, 10992, 3078, 14393, 927, 220, 1272, 4, 315, 682, 5068, 5157, 13, 7648, 315, 279, 21411, 10992, 3078, 304, 420, 4007, 596, 2585, 1912, 1051, 15107, 505, 30283, 21995, 5114, 596, 3053, 483, 65452, 6401, 5907, 13, 1115, 374, 264, 19989, 315, 12875, 6832, 7980, 527, 8173, 304, 24435, 304, 14830, 19622, 323, 1023, 7978, 311, 7417, 76082, 2890, 13, 9176, 315, 279, 12875, 10862, 1139, 279, 19989, 2391, 279, 34102, 10474, 315, 30283, 21995, 5114, 596, 18288, 10608, 462, 2099, 65452, 19723, 11, 719, 1051, 2288, 2362, 311, 16136, 304, 279, 19723, 520, 279, 892, 315, 872, 39148, 13, 220, 128257, 198 ]

2,315

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Due to its large northward heat transport, the Atlantic meridional overturning circulation influences both weather and climate at the mid-latitude Northern Hemisphere. Here we use a state-of-the-art global weather/climate modeling system with high resolution (GFDL CM4C192) to quantify this influence focusing on the U.S. extreme cold weather during winter. We perform a control simulation and the water-hosing experiment to obtain two climate states with and without a vigorous Atlantic meridional overturning circulation. We find that in the control simulation with an overturning circulation, the U.S. east of the Rockies is a region characterized by intense north-south heat exchange in the atmosphere during winter. Without the northward heat transport by the overturning circulation in the hosing experiment, this channel of atmospheric heat exchange becomes even more active through the Bjerknes compensation mechanism. Over the U.S., extreme cold weather intensifies disproportionately compared with the mean climate response after the shutdown of the overturning circulation. Our results suggest that an active overturning circulation in the present-day climate likely makes the U.S. winter less harsh and extreme. Introduction The important role of the Atlantic Meridional Overturning Circulation (AMOC) in the climate system has been extensively studied 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 . Without an AMOC and associated northward heat transport, northern and western Europe could be much colder 1 , 2 , 5 , 6 , 9 , the Arctic sea ice could expand 1 , the Inter-Tropical Convergence Zone (ITCZ) could shift southward 3 , 5 , 9 , and sea level along the East Coast of North America could be higher 12 . Compared with these changes in the mean climate, the impact of AMOC on extreme weather has not been investigated systematically and sufficiently thus far. One reason is that previous generations of global climate model were particularly designed for studies on large-scale, long-term climate, rather than on daily weather at the local scale, which requires high resolution, frequent data output, regional focus, and so on. Nonetheless, several recent studies have shown that a slowdown of AMOC could contribute to summer heatwaves over Europe 13 , 14 , flooding and droughts 15 , stronger and more active Atlantic hurricanes 16 , 17 and extratropical storms 18 . During the past decade, the Geophysical Fluid Dynamics Laboratory (GFDL) of NOAA has been working towards a unified and seamless modeling system suitable for studying both weather and climate, as well as their complex interactions under the same umbrella. The recent progress in model development and the rapid growth of supercomputer power have provided better tools to tackle important weather-climate issues. Here, we use the high resolution version (C192) of the global coupled modeling system, GFDL CM4 19 , 20 , 21 , 22 , 23 (see the “Methods” section), to investigate the influence of AMOC on the U.S. extreme cold weather during winter. As low-frequency high-impact events, extreme cold snaps could be disastrous ( ), particularly for the U.S. southern states with typical mild temperatures during winter 24 , 25 . Results Control simulation and water-hosing experiment with GFDL CM4C192 Under the 1950 radiative forcing, a long, centennial timescale control simulation has been carried out with CM4C192 as part of the GFDL’s participation in the High Resolution Model Intercomparison Project 26 . Due to the refined resolution for both the atmosphere (0.5°) and ocean (0.25°), synoptic-scale phenomena are better simulated by CM4C192, including hurricanes and severe winter storms, atmospheric rivers and blocking, ocean eddies and jets, storm surge and coastal flooding, etc 12 , 19 , 20 , 21 , 23 . In addition, the simulated AMOC has a mean strength of about 18 Sv (1 Sv = 10 6 m 3 s −1 ) at 26°N, compared well with observations 19 , 23 (Supplementary Fig. 1a ). To investigate the impact of AMOC on mid-latitude weather, we consider an idealized case by obtaining a climate state without an active AMOC while keeping everything else the same. To do so, we perform the typical water-hosing experiment by imposing a 0.6 Sv freshwater addition over the northern North Atlantic 1 , 3 (see the “Methods” section for more details). This experimental design should lead to strong and quick signals with a clear and definite attribution to AMOC, thereby avoiding complication by other factors. In addition, the high resolution coupled model is computationally expensive, which currently prevents long, transient, and ensemble simulations. In response to the freshwater perturbation, the AMOC almost shuts down in about 20 years (Supplementary Fig. 1b , c ). The atmosphere in the Northern Hemisphere approaches a new quasi-equilibrium state after year 20. In the following analysis, we compare years 21–100 of the hosing experiment with the 100-year control run to identify response characteristics of daily weather to the AMOC shutdown. Energy transport across 40°N and Bjerknes compensation between the ocean and atmosphere In the control run of CM4C192, the atmosphere and ocean work together to transport up to 5.7 Petawatts (PW, or 10 15 Watts) annual heat poleward to compensate the differential solar heating between the low and high latitudes 27 , 28 , 29 (Fig. 1a, b and Supplementary Fig. 2 ). In the Northern Hemisphere, the maximum total transport occurs at about 40°N. At mid-latitudes, the atmosphere is highly efficient at mixing different temperatures and transporting heat poleward through fast-moving turbulent weather systems, especially during winter. For the annual mean, the oceanic transport of about 0.8 PW at 40°N, largely due to AMOC 16 , 30 , 31 , is by far smaller than its atmospheric counterpart of 4.8 PW, but nonetheless represents an enormous amount of heat in global energy balance (Fig. 1 ). It should be noted that CM4C192 likely underestimates the northward heat transport in the Atlantic. The simulated maximum transport of about 1 PW at 26°N is lower than the recent observational estimate of about 1.3 PW 16 , 31 (Fig. 1c ). We consider", "role": "user" }, { "content": "Throughout Earth's oceans runs a conveyor belt of water. Its churning is powered by differences in the water's temperature and saltiness, and weather patterns around the world are regulated by its activity. A pair of researchers studied the Atlantic portion of this worldwide conveyor belt called the Atlantic Meridional Overturning Circulation, or AMOC, and found that winter weather in the United States critically depends on this conveyor belt-like system. As the AMOC slows because of climate change, the U.S. will experience more extreme cold winter weather. The study, published in the journal Communications Earth & Environment, was led by Jianjun Yin, an associate professor in the University of Arizona Department of Geosciences and co-authored by Ming Zhao, a physical scientist at the National Oceanic and Atmospheric Administration's Geophysical Fluid Dynamics Laboratory. AMOC works like this: Warm water travels north in the upper Atlantic Ocean and releases heat into the atmosphere at high latitudes. As the water cools, it becomes denser, which causes it to sink into the deep ocean where it flows back south. \"This circulation transports an enormous amount of heat northward in the ocean,\" Yin said. \"The magnitude is on the order of 1 petawatts, or 10 to the 15 power watts. Right now, the energy consumption by the entire world is about 20 terawatts, or 10 to the 12 power watts. So, 1 petawatt is enough to run about 50 civilizations.\" But as the climate warms, so does the ocean surface. At the same time, the Greenland ice sheet experiences melting, which dumps more freshwater into the ocean. Both warming and freshening of the water can reduce surface water density and inhibit the sinking of the water, slowing the AMOC. If the AMOC slows, so does the northward heat transport. This is important because the equator receives more energy from the sun than the poles. Both the atmosphere and ocean work to transport energy from low latitudes to high latitudes. If the ocean can't transport as much heat northward, then the atmosphere must instead transport more heat through more extreme weather processes at mid-latitudes. When the atmosphere moves heat northward, cold air is displaced from the poles and pushed to lower latitudes, reaching places as far south as the U.S. southern border. \"Think of it as two highways connecting two big cities,\" Yin said. \"If one is shut down, the other one gets more traffic. In the atmosphere, the traffic is the daily weather. So, if the ocean heat transport slows or shuts down, the weather becomes more extreme.\" Yin said the study was motivated by the extreme cold weather Texas experienced in February. \"In Houston, the daily temperature dropped to 40 degrees Fahrenheit below the normal,\" Yin said. \"That's the typical range of a summer/winter temperature difference. It made Texas feel like the Arctic. This kind of extreme winter weather happened several times in the U.S. during recent years, so the scientific community has been working to understand the mechanism behind these extreme events.\" The crisis in Texas caused widespread and catastrophic power outages, and the National Oceanic and Atmospheric Administration estimated that socioeconomic damages totaled $20 billion. Yin was curious about the role the ocean played in the extreme weather event. Yin and Zhao used a state-of-the-art, high-resolution global climate model to measure the influence of the AMOC on U.S. extreme cold weather. They ran the model twice, first looking at today's climate with a functioning AMOC. They then adjusted the model by inputting enough freshwater into the high-latitude North Atlantic to shut down the AMOC. The difference revealed the role of the AMOC in extreme cold weather. They found that without the AMOC and its northward heat transport, extremely cold winter weather intensifies in the U.S. According to recent observational studies, the AMOC has weakened in past decades. Climate models project it will get even weaker in response to increased greenhouse gases in the atmosphere. \"But there is uncertainty about the magnitude of the weakening, because at this point, we don't know exactly how much the Greenland ice sheet will melt,\" Yin said. \"How much it melts depends on the greenhouse gas emissions.\" The researchers also didn't take into account in their model the effects of human-caused global warming, but that's an area of interest for the future, Yin said. \"We basically just turn off the AMOC (in the model) to look at the response by extreme weather,\" he said. \"Next, we want to factor in the greenhouse gases and look at the combined effects of the AMOC slowdown and global warming on extreme cold weather.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Due to its large northward heat transport, the Atlantic meridional overturning circulation influences both weather and climate at the mid-latitude Northern Hemisphere. Here we use a state-of-the-art global weather/climate modeling system with high resolution (GFDL CM4C192) to quantify this influence focusing on the U.S. extreme cold weather during winter. We perform a control simulation and the water-hosing experiment to obtain two climate states with and without a vigorous Atlantic meridional overturning circulation. We find that in the control simulation with an overturning circulation, the U.S. east of the Rockies is a region characterized by intense north-south heat exchange in the atmosphere during winter. Without the northward heat transport by the overturning circulation in the hosing experiment, this channel of atmospheric heat exchange becomes even more active through the Bjerknes compensation mechanism. Over the U.S., extreme cold weather intensifies disproportionately compared with the mean climate response after the shutdown of the overturning circulation. Our results suggest that an active overturning circulation in the present-day climate likely makes the U.S. winter less harsh and extreme. Introduction The important role of the Atlantic Meridional Overturning Circulation (AMOC) in the climate system has been extensively studied 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 . Without an AMOC and associated northward heat transport, northern and western Europe could be much colder 1 , 2 , 5 , 6 , 9 , the Arctic sea ice could expand 1 , the Inter-Tropical Convergence Zone (ITCZ) could shift southward 3 , 5 , 9 , and sea level along the East Coast of North America could be higher 12 . Compared with these changes in the mean climate, the impact of AMOC on extreme weather has not been investigated systematically and sufficiently thus far. One reason is that previous generations of global climate model were particularly designed for studies on large-scale, long-term climate, rather than on daily weather at the local scale, which requires high resolution, frequent data output, regional focus, and so on. Nonetheless, several recent studies have shown that a slowdown of AMOC could contribute to summer heatwaves over Europe 13 , 14 , flooding and droughts 15 , stronger and more active Atlantic hurricanes 16 , 17 and extratropical storms 18 . During the past decade, the Geophysical Fluid Dynamics Laboratory (GFDL) of NOAA has been working towards a unified and seamless modeling system suitable for studying both weather and climate, as well as their complex interactions under the same umbrella. The recent progress in model development and the rapid growth of supercomputer power have provided better tools to tackle important weather-climate issues. Here, we use the high resolution version (C192) of the global coupled modeling system, GFDL CM4 19 , 20 , 21 , 22 , 23 (see the “Methods” section), to investigate the influence of AMOC on the U.S. extreme cold weather during winter. As low-frequency high-impact events, extreme cold snaps could be disastrous ( ), particularly for the U.S. southern states with typical mild temperatures during winter 24 , 25 . Results Control simulation and water-hosing experiment with GFDL CM4C192 Under the 1950 radiative forcing, a long, centennial timescale control simulation has been carried out with CM4C192 as part of the GFDL’s participation in the High Resolution Model Intercomparison Project 26 . Due to the refined resolution for both the atmosphere (0.5°) and ocean (0.25°), synoptic-scale phenomena are better simulated by CM4C192, including hurricanes and severe winter storms, atmospheric rivers and blocking, ocean eddies and jets, storm surge and coastal flooding, etc 12 , 19 , 20 , 21 , 23 . In addition, the simulated AMOC has a mean strength of about 18 Sv (1 Sv = 10 6 m 3 s −1 ) at 26°N, compared well with observations 19 , 23 (Supplementary Fig. 1a ). To investigate the impact of AMOC on mid-latitude weather, we consider an idealized case by obtaining a climate state without an active AMOC while keeping everything else the same. To do so, we perform the typical water-hosing experiment by imposing a 0.6 Sv freshwater addition over the northern North Atlantic 1 , 3 (see the “Methods” section for more details). This experimental design should lead to strong and quick signals with a clear and definite attribution to AMOC, thereby avoiding complication by other factors. In addition, the high resolution coupled model is computationally expensive, which currently prevents long, transient, and ensemble simulations. In response to the freshwater perturbation, the AMOC almost shuts down in about 20 years (Supplementary Fig. 1b , c ). The atmosphere in the Northern Hemisphere approaches a new quasi-equilibrium state after year 20. In the following analysis, we compare years 21–100 of the hosing experiment with the 100-year control run to identify response characteristics of daily weather to the AMOC shutdown. Energy transport across 40°N and Bjerknes compensation between the ocean and atmosphere In the control run of CM4C192, the atmosphere and ocean work together to transport up to 5.7 Petawatts (PW, or 10 15 Watts) annual heat poleward to compensate the differential solar heating between the low and high latitudes 27 , 28 , 29 (Fig. 1a, b and Supplementary Fig. 2 ). In the Northern Hemisphere, the maximum total transport occurs at about 40°N. At mid-latitudes, the atmosphere is highly efficient at mixing different temperatures and transporting heat poleward through fast-moving turbulent weather systems, especially during winter. For the annual mean, the oceanic transport of about 0.8 PW at 40°N, largely due to AMOC 16 , 30 , 31 , is by far smaller than its atmospheric counterpart of 4.8 PW, but nonetheless represents an enormous amount of heat in global energy balance (Fig. 1 ). It should be noted that CM4C192 likely underestimates the northward heat transport in the Atlantic. The simulated maximum transport of about 1 PW at 26°N is lower than the recent observational estimate of about 1.3 PW 16 , 31 (Fig. 1c ). We consider<|im_end|> <|im_start|>assistant Throughout Earth's oceans runs a conveyor belt of water. Its churning is powered by differences in the water's temperature and saltiness, and weather patterns around the world are regulated by its activity. A pair of researchers studied the Atlantic portion of this worldwide conveyor belt called the Atlantic Meridional Overturning Circulation, or AMOC, and found that winter weather in the United States critically depends on this conveyor belt-like system. As the AMOC slows because of climate change, the U.S. will experience more extreme cold winter weather. The study, published in the journal Communications Earth & Environment, was led by Jianjun Yin, an associate professor in the University of Arizona Department of Geosciences and co-authored by Ming Zhao, a physical scientist at the National Oceanic and Atmospheric Administration's Geophysical Fluid Dynamics Laboratory. AMOC works like this: Warm water travels north in the upper Atlantic Ocean and releases heat into the atmosphere at high latitudes. As the water cools, it becomes denser, which causes it to sink into the deep ocean where it flows back south. "This circulation transports an enormous amount of heat northward in the ocean," Yin said. "The magnitude is on the order of 1 petawatts, or 10 to the 15 power watts. Right now, the energy consumption by the entire world is about 20 terawatts, or 10 to the 12 power watts. So, 1 petawatt is enough to run about 50 civilizations." But as the climate warms, so does the ocean surface. At the same time, the Greenland ice sheet experiences melting, which dumps more freshwater into the ocean. Both warming and freshening of the water can reduce surface water density and inhibit the sinking of the water, slowing the AMOC. If the AMOC slows, so does the northward heat transport. This is important because the equator receives more energy from the sun than the poles. Both the atmosphere and ocean work to transport energy from low latitudes to high latitudes. If the ocean can't transport as much heat northward, then the atmosphere must instead transport more heat through more extreme weather processes at mid-latitudes. When the atmosphere moves heat northward, cold air is displaced from the poles and pushed to lower latitudes, reaching places as far south as the U.S. southern border. "Think of it as two highways connecting two big cities," Yin said. "If one is shut down, the other one gets more traffic. In the atmosphere, the traffic is the daily weather. So, if the ocean heat transport slows or shuts down, the weather becomes more extreme." Yin said the study was motivated by the extreme cold weather Texas experienced in February. "In Houston, the daily temperature dropped to 40 degrees Fahrenheit below the normal," Yin said. "That's the typical range of a summer/winter temperature difference. It made Texas feel like the Arctic. This kind of extreme winter weather happened several times in the U.S. during recent years, so the scientific community has been working to understand the mechanism behind these extreme events." The crisis in Texas caused widespread and catastrophic power outages, and the National Oceanic and Atmospheric Administration estimated that socioeconomic damages totaled $20 billion. Yin was curious about the role the ocean played in the extreme weather event. Yin and Zhao used a state-of-the-art, high-resolution global climate model to measure the influence of the AMOC on U.S. extreme cold weather. They ran the model twice, first looking at today's climate with a functioning AMOC. They then adjusted the model by inputting enough freshwater into the high-latitude North Atlantic to shut down the AMOC. The difference revealed the role of the AMOC in extreme cold weather. They found that without the AMOC and its northward heat transport, extremely cold winter weather intensifies in the U.S. According to recent observational studies, the AMOC has weakened in past decades. Climate models project it will get even weaker in response to increased greenhouse gases in the atmosphere. "But there is uncertainty about the magnitude of the weakening, because at this point, we don't know exactly how much the Greenland ice sheet will melt," Yin said. "How much it melts depends on the greenhouse gas emissions." The researchers also didn't take into account in their model the effects of human-caused global warming, but that's an area of interest for the future, Yin said. "We basically just turn off the AMOC (in the model) to look at the response by extreme weather," he said. "Next, we want to factor in the greenhouse gases and look at the combined effects of the AMOC slowdown and global warming on extreme cold weather." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 24586, 311, 1202, 3544, 10411, 1637, 8798, 7710, 11, 279, 23179, 4809, 307, 4001, 67687, 287, 35855, 34453, 2225, 9282, 323, 10182, 520, 279, 5209, 2922, 17584, 17355, 96878, 13, 5810, 584, 1005, 264, 1614, 8838, 10826, 38921, 3728, 9282, 57031, 3509, 34579, 1887, 449, 1579, 11175, 320, 38, 14938, 43, 18582, 19, 34, 5926, 8, 311, 76498, 420, 10383, 21760, 389, 279, 549, 815, 13, 14560, 9439, 9282, 2391, 12688, 13, 1226, 2804, 264, 2585, 19576, 323, 279, 3090, 2902, 14759, 9526, 311, 6994, 1403, 10182, 5415, 449, 323, 2085, 264, 71920, 23179, 4809, 307, 4001, 67687, 287, 35855, 13, 1226, 1505, 430, 304, 279, 2585, 19576, 449, 459, 67687, 287, 35855, 11, 279, 549, 815, 13, 11226, 315, 279, 80151, 374, 264, 5654, 32971, 555, 19428, 10411, 1355, 2969, 8798, 9473, 304, 279, 16975, 2391, 12688, 13, 17586, 279, 10411, 1637, 8798, 7710, 555, 279, 67687, 287, 35855, 304, 279, 305, 14759, 9526, 11, 420, 5613, 315, 45475, 8798, 9473, 9221, 1524, 810, 4642, 1555, 279, 69841, 17172, 4978, 20448, 17383, 13, 6193, 279, 549, 815, 2637, 14560, 9439, 9282, 25228, 9803, 73152, 7863, 449, 279, 3152, 10182, 2077, 1306, 279, 24700, 315, 279, 67687, 287, 35855, 13, 5751, 3135, 4284, 430, 459, 4642, 67687, 287, 35855, 304, 279, 3118, 11477, 10182, 4461, 3727, 279, 549, 815, 13, 12688, 2753, 25984, 323, 14560, 13, 29438, 578, 3062, 3560, 315, 279, 23179, 8930, 307, 4001, 6193, 413, 287, 16741, 2987, 320, 1428, 7767, 8, 304, 279, 10182, 1887, 706, 1027, 42817, 20041, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 662, 17586, 459, 6912, 7767, 323, 5938, 10411, 1637, 8798, 7710, 11, 18671, 323, 19001, 4606, 1436, 387, 1790, 76214, 220, 16, 1174, 220, 17, 1174, 220, 20, 1174, 220, 21, 1174, 220, 24, 1174, 279, 37518, 9581, 10054, 1436, 9407, 220, 16, 1174, 279, 5783, 9469, 51172, 1221, 81848, 22967, 320, 964, 34, 57, 8, 1436, 6541, 10007, 1637, 220, 18, 1174, 220, 20, 1174, 220, 24, 1174, 323, 9581, 2237, 3235, 279, 6460, 16377, 315, 4892, 5270, 1436, 387, 5190, 220, 717, 662, 59813, 449, 1521, 4442, 304, 279, 3152, 10182, 11, 279, 5536, 315, 6912, 7767, 389, 14560, 9282, 706, 539, 1027, 27313, 60826, 323, 40044, 8617, 3117, 13, 3861, 2944, 374, 430, 3766, 22540, 315, 3728, 10182, 1646, 1051, 8104, 6319, 369, 7978, 389, 3544, 13230, 11, 1317, 9860, 10182, 11, 4856, 1109, 389, 7446, 9282, 520, 279, 2254, 5569, 11, 902, 7612, 1579, 11175, 11, 21420, 828, 2612, 11, 15481, 5357, 11, 323, 779, 389, 13, 56733, 11, 3892, 3293, 7978, 617, 6982, 430, 264, 75017, 315, 6912, 7767, 1436, 17210, 311, 7474, 8798, 58365, 927, 4606, 220, 1032, 1174, 220, 975, 1174, 39262, 323, 37846, 82, 220, 868, 1174, 16643, 323, 810, 4642, 23179, 90127, 220, 845, 1174, 220, 1114, 323, 11741, 266, 51172, 44583, 220, 972, 662, 12220, 279, 3347, 13515, 11, 279, 4323, 91004, 60696, 53711, 32184, 320, 38, 14938, 43, 8, 315, 86748, 706, 1027, 3318, 7119, 264, 43790, 323, 47970, 34579, 1887, 14791, 369, 21630, 2225, 9282, 323, 10182, 11, 439, 1664, 439, 872, 6485, 22639, 1234, 279, 1890, 48998, 13, 578, 3293, 5208, 304, 1646, 4500, 323, 279, 11295, 6650, 315, 2307, 44211, 2410, 617, 3984, 2731, 7526, 311, 22118, 3062, 9282, 31717, 3509, 4819, 13, 5810, 11, 584, 1005, 279, 1579, 11175, 2373, 320, 34, 5926, 8, 315, 279, 3728, 34356, 34579, 1887, 11, 480, 14938, 43, 18582, 19, 220, 777, 1174, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 1174, 220, 1419, 320, 4151, 279, 1054, 18337, 863, 3857, 705, 311, 19874, 279, 10383, 315, 6912, 7767, 389, 279, 549, 815, 13, 14560, 9439, 9282, 2391, 12688, 13, 1666, 3428, 79412, 1579, 12, 58400, 4455, 11, 14560, 9439, 52404, 1436, 387, 53057, 320, 7026, 8104, 369, 279, 549, 815, 13, 18561, 5415, 449, 14595, 23900, 20472, 2391, 12688, 220, 1187, 1174, 220, 914, 662, 18591, 7935, 19576, 323, 3090, 2902, 14759, 9526, 449, 480, 14938, 43, 18582, 19, 34, 5926, 9636, 279, 220, 6280, 15, 12164, 1413, 25957, 11, 264, 1317, 11, 2960, 32331, 3115, 2296, 2585, 19576, 706, 1027, 11953, 704, 449, 18582, 19, 34, 5926, 439, 961, 315, 279, 480, 14938, 43, 753, 20852, 304, 279, 5234, 38216, 5008, 5783, 55805, 5907, 220, 1627, 662, 24586, 311, 279, 38291, 11175, 369, 2225, 279, 16975, 320, 15, 13, 20, 11877, 8, 323, 18435, 320, 15, 13, 914, 11877, 705, 6925, 94783, 13230, 44247, 527, 2731, 46836, 555, 18582, 19, 34, 5926, 11, 2737, 90127, 323, 15748, 12688, 44583, 11, 45475, 36617, 323, 22978, 11, 18435, 1608, 67, 552, 323, 44305, 11, 13766, 22531, 323, 35335, 39262, 11, 5099, 220, 717, 1174, 220, 777, 1174, 220, 508, 1174, 220, 1691, 1174, 220, 1419, 662, 763, 5369, 11, 279, 46836, 6912, 7767, 706, 264, 3152, 8333, 315, 922, 220, 972, 64705, 320, 16, 64705, 284, 220, 605, 220, 21, 296, 220, 18, 274, 25173, 16, 883, 520, 220, 1627, 121571, 11, 7863, 1664, 449, 24654, 220, 777, 1174, 220, 1419, 320, 10254, 67082, 23966, 13, 220, 16, 64, 7609, 2057, 19874, 279, 5536, 315, 6912, 7767, 389, 5209, 2922, 17584, 9282, 11, 584, 2980, 459, 10728, 1534, 1162, 555, 19546, 264, 10182, 1614, 2085, 459, 4642, 6912, 7767, 1418, 10494, 4395, 775, 279, 1890, 13, 2057, 656, 779, 11, 584, 2804, 279, 14595, 3090, 2902, 14759, 9526, 555, 49941, 264, 220, 15, 13, 21, 64705, 80744, 5369, 927, 279, 18671, 4892, 23179, 220, 16, 1174, 220, 18, 320, 4151, 279, 1054, 18337, 863, 3857, 369, 810, 3649, 570, 1115, 22772, 2955, 1288, 3063, 311, 3831, 323, 4062, 17738, 449, 264, 2867, 323, 44870, 63124, 311, 6912, 7767, 11, 28592, 31526, 86919, 555, 1023, 9547, 13, 763, 5369, 11, 279, 1579, 11175, 34356, 1646, 374, 3801, 30154, 11646, 11, 902, 5131, 29034, 1317, 11, 41658, 11, 323, 40126, 47590, 13, 763, 2077, 311, 279, 80744, 18713, 65916, 11, 279, 6912, 7767, 4661, 89678, 1523, 304, 922, 220, 508, 1667, 320, 10254, 67082, 23966, 13, 220, 16, 65, 1174, 272, 7609, 578, 16975, 304, 279, 17355, 96878, 20414, 264, 502, 48844, 63359, 46780, 1614, 1306, 1060, 220, 508, 13, 763, 279, 2768, 6492, 11, 584, 9616, 1667, 220, 1691, 4235, 1041, 315, 279, 305, 14759, 9526, 449, 279, 220, 1041, 4771, 2585, 1629, 311, 10765, 2077, 17910, 315, 7446, 9282, 311, 279, 6912, 7767, 24700, 13, 12634, 7710, 4028, 220, 1272, 121571, 323, 69841, 17172, 4978, 20448, 1990, 279, 18435, 323, 16975, 763, 279, 2585, 1629, 315, 18582, 19, 34, 5926, 11, 279, 16975, 323, 18435, 990, 3871, 311, 7710, 709, 311, 220, 20, 13, 22, 11586, 675, 21658, 320, 69223, 11, 477, 220, 605, 220, 868, 59336, 8, 9974, 8798, 26078, 1637, 311, 46794, 279, 41264, 13238, 24494, 1990, 279, 3428, 323, 1579, 6987, 21237, 220, 1544, 1174, 220, 1591, 1174, 220, 1682, 320, 30035, 13, 220, 16, 64, 11, 293, 323, 99371, 23966, 13, 220, 17, 7609, 763, 279, 17355, 96878, 11, 279, 7340, 2860, 7710, 13980, 520, 922, 220, 1272, 121571, 13, 2468, 5209, 99514, 21237, 11, 279, 16975, 374, 7701, 11297, 520, 27890, 2204, 20472, 323, 67757, 8798, 26078, 1637, 1555, 5043, 86572, 83321, 9282, 6067, 11, 5423, 2391, 12688, 13, 1789, 279, 9974, 3152, 11, 279, 18435, 292, 7710, 315, 922, 220, 15, 13, 23, 59393, 520, 220, 1272, 121571, 11, 14090, 4245, 311, 6912, 7767, 220, 845, 1174, 220, 966, 1174, 220, 2148, 1174, 374, 555, 3117, 9333, 1109, 1202, 45475, 45116, 315, 220, 19, 13, 23, 59393, 11, 719, 38913, 11105, 459, 23205, 3392, 315, 8798, 304, 3728, 4907, 8335, 320, 30035, 13, 220, 16, 7609, 1102, 1288, 387, 10555, 430, 18582, 19, 34, 5926, 4461, 1234, 478, 48571, 279, 10411, 1637, 8798, 7710, 304, 279, 23179, 13, 578, 46836, 7340, 7710, 315, 922, 220, 16, 59393, 520, 220, 1627, 121571, 374, 4827, 1109, 279, 3293, 90380, 16430, 315, 922, 220, 16, 13, 18, 59393, 220, 845, 1174, 220, 2148, 320, 30035, 13, 220, 16, 66, 7609, 1226, 2980, 128257, 198, 128256, 78191, 198, 60105, 9420, 596, 54280, 8640, 264, 50241, 19671, 315, 3090, 13, 11699, 523, 54444, 374, 23134, 555, 12062, 304, 279, 3090, 596, 9499, 323, 12290, 1918, 11, 323, 9282, 12912, 2212, 279, 1917, 527, 35319, 555, 1202, 5820, 13, 362, 6857, 315, 12074, 20041, 279, 23179, 13651, 315, 420, 15603, 50241, 19671, 2663, 279, 23179, 8930, 307, 4001, 6193, 413, 287, 16741, 2987, 11, 477, 6912, 7767, 11, 323, 1766, 430, 12688, 9282, 304, 279, 3723, 4273, 41440, 14117, 389, 420, 50241, 19671, 12970, 1887, 13, 1666, 279, 6912, 7767, 70270, 1606, 315, 10182, 2349, 11, 279, 549, 815, 13, 690, 3217, 810, 14560, 9439, 12688, 9282, 13, 578, 4007, 11, 4756, 304, 279, 8486, 26545, 9420, 612, 11847, 11, 574, 6197, 555, 88404, 58781, 83958, 11, 459, 22712, 14561, 304, 279, 3907, 315, 17368, 6011, 315, 4323, 85728, 2436, 323, 1080, 96471, 555, 56983, 70381, 11, 264, 7106, 28568, 520, 279, 5165, 22302, 292, 323, 87597, 17128, 596, 4323, 91004, 60696, 53711, 32184, 13, 6912, 7767, 4375, 1093, 420, 25, 46863, 3090, 35292, 10411, 304, 279, 8582, 23179, 22302, 323, 19786, 8798, 1139, 279, 16975, 520, 1579, 6987, 21237, 13, 1666, 279, 3090, 1080, 3145, 11, 433, 9221, 39950, 261, 11, 902, 11384, 433, 311, 19868, 1139, 279, 5655, 18435, 1405, 433, 28555, 1203, 10007, 13, 330, 2028, 35855, 69169, 459, 23205, 3392, 315, 8798, 10411, 1637, 304, 279, 18435, 1359, 83958, 1071, 13, 330, 791, 26703, 374, 389, 279, 2015, 315, 220, 16, 6896, 675, 21658, 11, 477, 220, 605, 311, 279, 220, 868, 2410, 72122, 13, 10291, 1457, 11, 279, 4907, 15652, 555, 279, 4553, 1917, 374, 922, 220, 508, 2024, 675, 21658, 11, 477, 220, 605, 311, 279, 220, 717, 2410, 72122, 13, 2100, 11, 220, 16, 6896, 675, 1617, 374, 3403, 311, 1629, 922, 220, 1135, 86569, 1210, 2030, 439, 279, 10182, 4208, 1026, 11, 779, 1587, 279, 18435, 7479, 13, 2468, 279, 1890, 892, 11, 279, 73778, 10054, 11071, 11704, 50684, 11, 902, 61481, 810, 80744, 1139, 279, 18435, 13, 11995, 24808, 323, 7878, 6147, 315, 279, 3090, 649, 8108, 7479, 3090, 17915, 323, 69033, 279, 62193, 315, 279, 3090, 11, 48408, 279, 6912, 7767, 13, 1442, 279, 6912, 7767, 70270, 11, 779, 1587, 279, 10411, 1637, 8798, 7710, 13, 1115, 374, 3062, 1606, 279, 3312, 859, 21879, 810, 4907, 505, 279, 7160, 1109, 279, 51879, 13, 11995, 279, 16975, 323, 18435, 990, 311, 7710, 4907, 505, 3428, 6987, 21237, 311, 1579, 6987, 21237, 13, 1442, 279, 18435, 649, 956, 7710, 439, 1790, 8798, 10411, 1637, 11, 1243, 279, 16975, 2011, 4619, 7710, 810, 8798, 1555, 810, 14560, 9282, 11618, 520, 5209, 99514, 21237, 13, 3277, 279, 16975, 11031, 8798, 10411, 1637, 11, 9439, 3805, 374, 49246, 505, 279, 51879, 323, 15753, 311, 4827, 6987, 21237, 11, 19261, 7634, 439, 3117, 10007, 439, 279, 549, 815, 13, 18561, 3973, 13, 330, 39787, 315, 433, 439, 1403, 60395, 21583, 1403, 2466, 9919, 1359, 83958, 1071, 13, 330, 2746, 832, 374, 9495, 1523, 11, 279, 1023, 832, 5334, 810, 9629, 13, 763, 279, 16975, 11, 279, 9629, 374, 279, 7446, 9282, 13, 2100, 11, 422, 279, 18435, 8798, 7710, 70270, 477, 89678, 1523, 11, 279, 9282, 9221, 810, 14560, 1210, 83958, 1071, 279, 4007, 574, 27762, 555, 279, 14560, 9439, 9282, 8421, 10534, 304, 7552, 13, 330, 644, 16386, 11, 279, 7446, 9499, 12504, 311, 220, 1272, 12628, 69823, 3770, 279, 4725, 1359, 83958, 1071, 13, 330, 4897, 596, 279, 14595, 2134, 315, 264, 7474, 6458, 2295, 9499, 6811, 13, 1102, 1903, 8421, 2733, 1093, 279, 37518, 13, 1115, 3169, 315, 14560, 12688, 9282, 7077, 3892, 3115, 304, 279, 549, 815, 13, 2391, 3293, 1667, 11, 779, 279, 12624, 4029, 706, 1027, 3318, 311, 3619, 279, 17383, 4920, 1521, 14560, 4455, 1210, 578, 11501, 304, 8421, 9057, 24716, 323, 54677, 2410, 704, 1154, 11, 323, 279, 5165, 22302, 292, 323, 87597, 17128, 13240, 430, 80431, 26186, 89518, 400, 508, 7239, 13, 83958, 574, 22999, 922, 279, 3560, 279, 18435, 6476, 304, 279, 14560, 9282, 1567, 13, 83958, 323, 70381, 1511, 264, 1614, 8838, 10826, 38921, 11, 1579, 64036, 3728, 10182, 1646, 311, 6767, 279, 10383, 315, 279, 6912, 7767, 389, 549, 815, 13, 14560, 9439, 9282, 13, 2435, 10837, 279, 1646, 11157, 11, 1176, 3411, 520, 3432, 596, 10182, 449, 264, 31301, 6912, 7767, 13, 2435, 1243, 24257, 279, 1646, 555, 1988, 1303, 3403, 80744, 1139, 279, 1579, 2922, 17584, 4892, 23179, 311, 9495, 1523, 279, 6912, 7767, 13, 578, 6811, 10675, 279, 3560, 315, 279, 6912, 7767, 304, 14560, 9439, 9282, 13, 2435, 1766, 430, 2085, 279, 6912, 7767, 323, 1202, 10411, 1637, 8798, 7710, 11, 9193, 9439, 12688, 9282, 25228, 9803, 304, 279, 549, 815, 13, 10771, 311, 3293, 90380, 7978, 11, 279, 6912, 7767, 706, 58764, 304, 3347, 11026, 13, 31636, 4211, 2447, 433, 690, 636, 1524, 43383, 304, 2077, 311, 7319, 37647, 45612, 304, 279, 16975, 13, 330, 4071, 1070, 374, 27924, 922, 279, 26703, 315, 279, 83526, 11, 1606, 520, 420, 1486, 11, 584, 1541, 956, 1440, 7041, 1268, 1790, 279, 73778, 10054, 11071, 690, 30099, 1359, 83958, 1071, 13, 330, 4438, 1790, 433, 99191, 14117, 389, 279, 37647, 6962, 20748, 1210, 578, 12074, 1101, 3287, 956, 1935, 1139, 2759, 304, 872, 1646, 279, 6372, 315, 3823, 51877, 2656, 3728, 24808, 11, 719, 430, 596, 459, 3158, 315, 2802, 369, 279, 3938, 11, 83958, 1071, 13, 330, 1687, 13524, 1120, 2543, 1022, 279, 6912, 7767, 320, 258, 279, 1646, 8, 311, 1427, 520, 279, 2077, 555, 14560, 9282, 1359, 568, 1071, 13, 330, 5971, 11, 584, 1390, 311, 8331, 304, 279, 37647, 45612, 323, 1427, 520, 279, 11093, 6372, 315, 279, 6912, 7767, 75017, 323, 3728, 24808, 389, 14560, 9439, 9282, 1210, 220, 128257, 198 ]

2,347

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The interaction of ultra-intense laser pulses with matter opened the way to generate the shortest light pulses available nowadays in the attosecond regime. Ionized solid surfaces, also called plasma mirrors, are promising tools to enhance the potential of attosecond sources in terms of photon energy, photon number and duration especially at relativistic laser intensities. Although the production of isolated attosecond pulses and the understanding of the underlying interactions represent a fundamental step towards the realization of such sources, these are challenging and have not yet been demonstrated. Here, we present laser-waveform-dependent high-order harmonic radiation in the extreme ultraviolet spectral range supporting well-isolated attosecond pulses, and utilize spectral interferometry to understand its relativistic generation mechanism. This unique interpretation of the measured spectra provides access to unrevealed temporal and spatial properties such as spectral phase difference between attosecond pulses and field-driven plasma surface motion during the process. Introduction The investigation and control of ultrafast physical processes in nature call for ever shorter flashes of light. The present state of the art is high-order harmonic generation (HHG) from gas medium 1 , providing extreme ultraviolet (XUV) and X-ray pulses with durations in the attosecond regime, the temporal scale of electron motion in atoms and molecules. An alternative is represented by HHG from plasma mirrors (PMs) 2 , 3 . Its main advantage over gas HHG is the potential to utilize lasers with ultrahigh peak power and thus produce bright attosecond light pulses with orders of magnitude of higher energy and shorter wavelength. Such high-energy attosecond light sources will satisfy the challenging needs of attosecond XUV nonlinear optics for XUV-pump–XUV-probe experiments 4 . There have been many advances in the past two decades in understanding and developing attosecond light sources using PMs. So far, three distinct mechanisms of HHG from PMs have been identified. Coherent wake emission (CWE) 5 below relativistic laser intensities and relativistically oscillating mirror (ROM) 6 , 7 , 8 , 9 are compared in the experiment and clearly differentiated from each other 10 , 11 . The ROM model predicts a power law decay of the harmonic spectrum with the harmonic order with an exponent of −8/3. However, there exist different alternative models describing this last regime and providing different exponents 12 , 13 , 14 , 15 . Recently, a third mechanism termed coherent synchrotron emission 16 or relativistic electronic spring model 17 , 18 , 19 was proposed and experimentally identified with its characteristic spectral signatures 20 . CWE provides temporally coherent and synchronized XUV harmonics resulting in attosecond temporal bunching 21 , 22 but with a chirp related to sub-laser-cycle dynamics of plasma electrons 23 , which makes it less attractive for applications. The good spatial coherence of the laser is preserved during the CWE process 24 . To date, ROM was observed up to multi-keV 25 , 26 energy in good agreement with theoretical predictions 9 . It is shown to provide well beamed radiation 27 , 28 and diffraction-limited focusing 29 , 30 . The motion of the plasma surface during the interaction (denting) influences the harmonic beam divergence 31 and reduces the coherence length of ROM harmonics 32 . The generation condition is controlled by the plasma scale length to optimize the harmonic yield 33 , 34 , 35 , 36 and to change the spacing between pulses in an attosecond pulse train (attotrain) 37 . Furthermore, utilizing similar control, harmonics provide spatial information about structured plasma surfaces via ptychographic imaging 38 . Engineering the instantaneous waveform with two-color driving field control is also proposed and used to enhance high-harmonic yield 39 , 40 . For future applications of these light sources, isolated attosecond pulses (APs) are superior to an attotrain. For this reason, different polarization gating techniques were proposed for many-cycle laser pulses 41 , 42 , 43 , which have large intensity losses. Owing to the advent of intense few-cycle laser drivers with high contrast 44 , 45 , 46 , 47 , however, direct isolation is within reach through intensity gating 48 , 49 , 50 . In these cases 49 , an attotrain is produced containing a well isolated AP with very high isolation degree (defined as main-to-side pulse temporal intensity ratio), which still presents apparent modulation in its corresponding spectrum. A natural property determining the waveform of these few-cycle laser pulses is the carrier-envelope phase (CEP) ϕ CEP (see Methods). CEP dependence and control of CWE harmonics was already demonstrated 51 and isolation was reached with tilting the pulse front of the intense few-cycle driver laser and thus producing a manifold of isolated APs propagating in different directions 52 . Although high harmonics from few-cycle driver are expected to be waveform dependent 49 , neither this CEP dependence nor isolated APs have been achieved in the relativistic generation regime before. In this article, we present laser-field-dependent emission of high-order harmonics from a ROM driven by a two-cycle laser. For certain CEP values, this harmonic radiation supports a strongly isolated AP. An analysis based on spectral interferometry (SI) reveals the spectral phase difference between the pulses and the spectrum of the individual pulses in the attotrain. This information allows determining the temporal spacing and relative contrast between individual APs in a few-pulse attotrain as well as the denting of the reflecting solid-density PM 31 . The simultaneous measurement of the laser waveform provides clear demonstration of the CEP dependence of the underlying relativistic laser–plasma interaction. Results Experiment description The experimental set-up is shown in Fig. 1 . The multi-terawatt (multi-TW) peak power Light Wave Synthesizer 20 (LWS-20) 44 was used as a laser source with a low-intensity PM for contrast improvement 45 by a factor of 300. It provided a pulse energy of 40 mJ on-target after losses, which was focused with an off-axis parabolic (OAP) mirror to d FWHM = 1.3 μm, in an angle of incidence α inc = 55°, and p -polarization. Focus size and quality were controlled using a microscope objective, which can replace the", "role": "user" }, { "content": "When a dense sheet of electrons is accelerated to almost the speed of light, it acts as a reflective surface. Such a 'plasma mirror' can be used to manipulate light. Now an international team of physicists from the Max Planck Institute of Quantum Optics, LMU Munich, and Umeå University in Sweden have characterized this plasma-mirror effect in detail, and exploited it to generate isolated, high-intensity attosecond light flashes. An attosecond lasts for a billionth of a billionth (10-18) of a second. The interaction between extremely powerful laser pulses and matter has opened up entirely new approaches to the generation of ultrashort light flashes lasting for only a few hundred attoseconds. These extraordinarily brief pulses can in turn be used to probe the dynamics of ultrafast physical phenomena at sub-atomic scales. The standard method used to create attosecond pulses is based on the interaction of near-infrared laser light with the electrons in atoms of noble gases such as neon or argon. Now researchers at the Laboratory for Attosecond Physics at the Max Planck Institute of Quantum Optics in Garching and Munich's Ludwig Maximilians University (LMU), in collaboration with colleagues at Umeå University, have successfully implemented a new strategy for the generation of isolated attosecond light pulses. In the first step, extremely powerful femtosecond (10-15 sec) laser pulses are allowed to interact with glass. The laser light vaporizes the glass surface, ionizing its constituent atoms and accelerating the liberated electrons to velocities equivalent to an appreciable fraction of the speed of light. The resulting high-density plasma made up of rapidly moving electrons, which propagates in the same direction as the pulsed laser light, acts like a mirror. Once the electrons have attained velocities that approach the speed of light they become relativistic, and begin to oscillate in response to the laser field. The ensuing periodic deformation of the plasma mirror interacts with the reflected light wave to give rise to isolated attosecond pulses. These pulses have an estimated duration of approximately 200 as and wavelengths in the extreme ultraviolet region of the spectrum (20-30 nanometers, 40-60 eV). In contrast to attosecond pulses generated with longer laser pulses, those produced by the plasma-mirror effect and laser pulses that have a duration of few optical cycles can be precisely controlled with the waveform. This also allowed the researchers to observe the time course of the generation process, i.e. the oscillation of the plasma mirror. Importantly, these pulses are much more intense, i.e. contain far more photons, than those obtainable with the standard procedure. The increased intensity makes it possible to carry out still more precise measurements of the behaviour of subatomic particles in real time. Attosecond light pulses are primarily used to map electron motions, and thus provide insights into the dynamics of fundamental processes within atoms. The higher the intensity of the attosecond light flashes, the more information can be gleaned about the motions of particles within matter. With the practical demonstration of the plasma-mirror effect to generate bright attosecond light pulses, the authors of the new study have developed a technology, which will enable physicists to probe even deeper into the mysteries of the quantum world. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The interaction of ultra-intense laser pulses with matter opened the way to generate the shortest light pulses available nowadays in the attosecond regime. Ionized solid surfaces, also called plasma mirrors, are promising tools to enhance the potential of attosecond sources in terms of photon energy, photon number and duration especially at relativistic laser intensities. Although the production of isolated attosecond pulses and the understanding of the underlying interactions represent a fundamental step towards the realization of such sources, these are challenging and have not yet been demonstrated. Here, we present laser-waveform-dependent high-order harmonic radiation in the extreme ultraviolet spectral range supporting well-isolated attosecond pulses, and utilize spectral interferometry to understand its relativistic generation mechanism. This unique interpretation of the measured spectra provides access to unrevealed temporal and spatial properties such as spectral phase difference between attosecond pulses and field-driven plasma surface motion during the process. Introduction The investigation and control of ultrafast physical processes in nature call for ever shorter flashes of light. The present state of the art is high-order harmonic generation (HHG) from gas medium 1 , providing extreme ultraviolet (XUV) and X-ray pulses with durations in the attosecond regime, the temporal scale of electron motion in atoms and molecules. An alternative is represented by HHG from plasma mirrors (PMs) 2 , 3 . Its main advantage over gas HHG is the potential to utilize lasers with ultrahigh peak power and thus produce bright attosecond light pulses with orders of magnitude of higher energy and shorter wavelength. Such high-energy attosecond light sources will satisfy the challenging needs of attosecond XUV nonlinear optics for XUV-pump–XUV-probe experiments 4 . There have been many advances in the past two decades in understanding and developing attosecond light sources using PMs. So far, three distinct mechanisms of HHG from PMs have been identified. Coherent wake emission (CWE) 5 below relativistic laser intensities and relativistically oscillating mirror (ROM) 6 , 7 , 8 , 9 are compared in the experiment and clearly differentiated from each other 10 , 11 . The ROM model predicts a power law decay of the harmonic spectrum with the harmonic order with an exponent of −8/3. However, there exist different alternative models describing this last regime and providing different exponents 12 , 13 , 14 , 15 . Recently, a third mechanism termed coherent synchrotron emission 16 or relativistic electronic spring model 17 , 18 , 19 was proposed and experimentally identified with its characteristic spectral signatures 20 . CWE provides temporally coherent and synchronized XUV harmonics resulting in attosecond temporal bunching 21 , 22 but with a chirp related to sub-laser-cycle dynamics of plasma electrons 23 , which makes it less attractive for applications. The good spatial coherence of the laser is preserved during the CWE process 24 . To date, ROM was observed up to multi-keV 25 , 26 energy in good agreement with theoretical predictions 9 . It is shown to provide well beamed radiation 27 , 28 and diffraction-limited focusing 29 , 30 . The motion of the plasma surface during the interaction (denting) influences the harmonic beam divergence 31 and reduces the coherence length of ROM harmonics 32 . The generation condition is controlled by the plasma scale length to optimize the harmonic yield 33 , 34 , 35 , 36 and to change the spacing between pulses in an attosecond pulse train (attotrain) 37 . Furthermore, utilizing similar control, harmonics provide spatial information about structured plasma surfaces via ptychographic imaging 38 . Engineering the instantaneous waveform with two-color driving field control is also proposed and used to enhance high-harmonic yield 39 , 40 . For future applications of these light sources, isolated attosecond pulses (APs) are superior to an attotrain. For this reason, different polarization gating techniques were proposed for many-cycle laser pulses 41 , 42 , 43 , which have large intensity losses. Owing to the advent of intense few-cycle laser drivers with high contrast 44 , 45 , 46 , 47 , however, direct isolation is within reach through intensity gating 48 , 49 , 50 . In these cases 49 , an attotrain is produced containing a well isolated AP with very high isolation degree (defined as main-to-side pulse temporal intensity ratio), which still presents apparent modulation in its corresponding spectrum. A natural property determining the waveform of these few-cycle laser pulses is the carrier-envelope phase (CEP) ϕ CEP (see Methods). CEP dependence and control of CWE harmonics was already demonstrated 51 and isolation was reached with tilting the pulse front of the intense few-cycle driver laser and thus producing a manifold of isolated APs propagating in different directions 52 . Although high harmonics from few-cycle driver are expected to be waveform dependent 49 , neither this CEP dependence nor isolated APs have been achieved in the relativistic generation regime before. In this article, we present laser-field-dependent emission of high-order harmonics from a ROM driven by a two-cycle laser. For certain CEP values, this harmonic radiation supports a strongly isolated AP. An analysis based on spectral interferometry (SI) reveals the spectral phase difference between the pulses and the spectrum of the individual pulses in the attotrain. This information allows determining the temporal spacing and relative contrast between individual APs in a few-pulse attotrain as well as the denting of the reflecting solid-density PM 31 . The simultaneous measurement of the laser waveform provides clear demonstration of the CEP dependence of the underlying relativistic laser–plasma interaction. Results Experiment description The experimental set-up is shown in Fig. 1 . The multi-terawatt (multi-TW) peak power Light Wave Synthesizer 20 (LWS-20) 44 was used as a laser source with a low-intensity PM for contrast improvement 45 by a factor of 300. It provided a pulse energy of 40 mJ on-target after losses, which was focused with an off-axis parabolic (OAP) mirror to d FWHM = 1.3 μm, in an angle of incidence α inc = 55°, and p -polarization. Focus size and quality were controlled using a microscope objective, which can replace the<|im_end|> <|im_start|>assistant When a dense sheet of electrons is accelerated to almost the speed of light, it acts as a reflective surface. Such a 'plasma mirror' can be used to manipulate light. Now an international team of physicists from the Max Planck Institute of Quantum Optics, LMU Munich, and Umeå University in Sweden have characterized this plasma-mirror effect in detail, and exploited it to generate isolated, high-intensity attosecond light flashes. An attosecond lasts for a billionth of a billionth (10-18) of a second. The interaction between extremely powerful laser pulses and matter has opened up entirely new approaches to the generation of ultrashort light flashes lasting for only a few hundred attoseconds. These extraordinarily brief pulses can in turn be used to probe the dynamics of ultrafast physical phenomena at sub-atomic scales. The standard method used to create attosecond pulses is based on the interaction of near-infrared laser light with the electrons in atoms of noble gases such as neon or argon. Now researchers at the Laboratory for Attosecond Physics at the Max Planck Institute of Quantum Optics in Garching and Munich's Ludwig Maximilians University (LMU), in collaboration with colleagues at Umeå University, have successfully implemented a new strategy for the generation of isolated attosecond light pulses. In the first step, extremely powerful femtosecond (10-15 sec) laser pulses are allowed to interact with glass. The laser light vaporizes the glass surface, ionizing its constituent atoms and accelerating the liberated electrons to velocities equivalent to an appreciable fraction of the speed of light. The resulting high-density plasma made up of rapidly moving electrons, which propagates in the same direction as the pulsed laser light, acts like a mirror. Once the electrons have attained velocities that approach the speed of light they become relativistic, and begin to oscillate in response to the laser field. The ensuing periodic deformation of the plasma mirror interacts with the reflected light wave to give rise to isolated attosecond pulses. These pulses have an estimated duration of approximately 200 as and wavelengths in the extreme ultraviolet region of the spectrum (20-30 nanometers, 40-60 eV). In contrast to attosecond pulses generated with longer laser pulses, those produced by the plasma-mirror effect and laser pulses that have a duration of few optical cycles can be precisely controlled with the waveform. This also allowed the researchers to observe the time course of the generation process, i.e. the oscillation of the plasma mirror. Importantly, these pulses are much more intense, i.e. contain far more photons, than those obtainable with the standard procedure. The increased intensity makes it possible to carry out still more precise measurements of the behaviour of subatomic particles in real time. Attosecond light pulses are primarily used to map electron motions, and thus provide insights into the dynamics of fundamental processes within atoms. The higher the intensity of the attosecond light flashes, the more information can be gleaned about the motions of particles within matter. With the practical demonstration of the plasma-mirror effect to generate bright attosecond light pulses, the authors of the new study have developed a technology, which will enable physicists to probe even deeper into the mysteries of the quantum world. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 16628, 315, 24955, 20653, 1137, 21120, 66557, 449, 5030, 9107, 279, 1648, 311, 7068, 279, 40243, 3177, 66557, 2561, 46877, 304, 279, 1651, 974, 1321, 17942, 13, 45905, 1534, 6573, 27529, 11, 1101, 2663, 32426, 41585, 11, 527, 26455, 7526, 311, 18885, 279, 4754, 315, 1651, 974, 1321, 8336, 304, 3878, 315, 69010, 4907, 11, 69010, 1396, 323, 8250, 5423, 520, 59425, 4633, 21120, 25228, 1385, 13, 10541, 279, 5788, 315, 25181, 1651, 974, 1321, 66557, 323, 279, 8830, 315, 279, 16940, 22639, 4097, 264, 16188, 3094, 7119, 279, 49803, 315, 1778, 8336, 11, 1521, 527, 17436, 323, 617, 539, 3686, 1027, 21091, 13, 5810, 11, 584, 3118, 21120, 89354, 630, 43918, 1579, 24747, 82341, 25407, 304, 279, 14560, 37232, 85311, 57077, 2134, 12899, 1664, 31530, 81619, 1651, 974, 1321, 66557, 11, 323, 29166, 57077, 41305, 7133, 311, 3619, 1202, 59425, 4633, 9659, 17383, 13, 1115, 5016, 23692, 315, 279, 17303, 63697, 5825, 2680, 311, 38223, 588, 5962, 37015, 323, 29079, 6012, 1778, 439, 57077, 10474, 6811, 1990, 1651, 974, 1321, 66557, 323, 2115, 32505, 32426, 7479, 11633, 2391, 279, 1920, 13, 29438, 578, 8990, 323, 2585, 315, 24955, 9533, 7106, 11618, 304, 7138, 1650, 369, 3596, 24210, 62385, 315, 3177, 13, 578, 3118, 1614, 315, 279, 1989, 374, 1579, 24747, 82341, 9659, 320, 24056, 38, 8, 505, 6962, 11298, 220, 16, 1174, 8405, 14560, 37232, 85311, 320, 55, 23042, 8, 323, 1630, 30630, 66557, 449, 90204, 304, 279, 1651, 974, 1321, 17942, 11, 279, 37015, 5569, 315, 17130, 11633, 304, 33299, 323, 35715, 13, 1556, 10778, 374, 15609, 555, 25788, 38, 505, 32426, 41585, 320, 8971, 82, 8, 220, 17, 1174, 220, 18, 662, 11699, 1925, 9610, 927, 6962, 25788, 38, 374, 279, 4754, 311, 29166, 72475, 449, 37232, 1494, 1108, 16557, 2410, 323, 8617, 8356, 10107, 1651, 974, 1321, 3177, 66557, 449, 10373, 315, 26703, 315, 5190, 4907, 323, 24210, 46406, 13, 15483, 1579, 65487, 1651, 974, 1321, 3177, 8336, 690, 27651, 279, 17436, 3966, 315, 1651, 974, 1321, 1630, 23042, 75098, 70985, 369, 1630, 23042, 2320, 1538, 4235, 55, 23042, 10039, 1395, 21896, 220, 19, 662, 2684, 617, 1027, 1690, 31003, 304, 279, 3347, 1403, 11026, 304, 8830, 323, 11469, 1651, 974, 1321, 3177, 8336, 1701, 5975, 82, 13, 2100, 3117, 11, 2380, 12742, 24717, 315, 25788, 38, 505, 5975, 82, 617, 1027, 11054, 13, 3623, 38638, 15508, 41353, 320, 34, 12739, 8, 220, 20, 3770, 59425, 4633, 21120, 25228, 1385, 323, 59425, 38210, 43524, 1113, 18327, 320, 3442, 8, 220, 21, 1174, 220, 22, 1174, 220, 23, 1174, 220, 24, 527, 7863, 304, 279, 9526, 323, 9539, 89142, 505, 1855, 1023, 220, 605, 1174, 220, 806, 662, 578, 31786, 1646, 56978, 264, 2410, 2383, 31815, 315, 279, 82341, 20326, 449, 279, 82341, 2015, 449, 459, 28790, 315, 25173, 23, 14, 18, 13, 4452, 11, 1070, 3073, 2204, 10778, 4211, 23524, 420, 1566, 17942, 323, 8405, 2204, 506, 2767, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 662, 42096, 11, 264, 4948, 17383, 61937, 56887, 6925, 331, 299, 35785, 41353, 220, 845, 477, 59425, 4633, 14683, 10683, 1646, 220, 1114, 1174, 220, 972, 1174, 220, 777, 574, 11223, 323, 9526, 750, 11054, 449, 1202, 29683, 57077, 33728, 220, 508, 662, 51960, 5825, 19502, 750, 56887, 323, 22183, 1630, 23042, 18249, 1233, 13239, 304, 1651, 974, 1321, 37015, 15860, 287, 220, 1691, 1174, 220, 1313, 719, 449, 264, 71546, 79, 5552, 311, 1207, 2922, 12351, 78790, 30295, 315, 32426, 57678, 220, 1419, 1174, 902, 3727, 433, 2753, 19411, 369, 8522, 13, 578, 1695, 29079, 78925, 315, 279, 21120, 374, 34683, 2391, 279, 51960, 1920, 220, 1187, 662, 2057, 2457, 11, 31786, 574, 13468, 709, 311, 7447, 12, 441, 53, 220, 914, 1174, 220, 1627, 4907, 304, 1695, 9306, 449, 32887, 20492, 220, 24, 662, 1102, 374, 6982, 311, 3493, 1664, 387, 3690, 25407, 220, 1544, 1174, 220, 1591, 323, 3722, 16597, 2922, 32611, 21760, 220, 1682, 1174, 220, 966, 662, 578, 11633, 315, 279, 32426, 7479, 2391, 279, 16628, 320, 55923, 287, 8, 34453, 279, 82341, 24310, 82258, 220, 2148, 323, 26338, 279, 78925, 3160, 315, 31786, 18249, 1233, 220, 843, 662, 578, 9659, 3044, 374, 14400, 555, 279, 32426, 5569, 3160, 311, 30536, 279, 82341, 7692, 220, 1644, 1174, 220, 1958, 1174, 220, 1758, 1174, 220, 1927, 323, 311, 2349, 279, 27032, 1990, 66557, 304, 459, 1651, 974, 1321, 28334, 5542, 320, 1617, 354, 30193, 8, 220, 1806, 662, 24296, 11, 35988, 4528, 2585, 11, 18249, 1233, 3493, 29079, 2038, 922, 34030, 32426, 27529, 4669, 281, 1919, 331, 12968, 32758, 220, 1987, 662, 17005, 279, 96219, 73464, 449, 1403, 8048, 10043, 2115, 2585, 374, 1101, 11223, 323, 1511, 311, 18885, 1579, 2902, 277, 74689, 7692, 220, 2137, 1174, 220, 1272, 662, 1789, 3938, 8522, 315, 1521, 3177, 8336, 11, 25181, 1651, 974, 1321, 66557, 320, 2599, 82, 8, 527, 16757, 311, 459, 1651, 354, 30193, 13, 1789, 420, 2944, 11, 2204, 83245, 74499, 12823, 1051, 11223, 369, 1690, 78790, 21120, 66557, 220, 3174, 1174, 220, 2983, 1174, 220, 3391, 1174, 902, 617, 3544, 21261, 18151, 13, 507, 24510, 311, 279, 11599, 315, 19428, 2478, 78790, 21120, 12050, 449, 1579, 13168, 220, 2096, 1174, 220, 1774, 1174, 220, 2790, 1174, 220, 2618, 1174, 4869, 11, 2167, 31398, 374, 2949, 5662, 1555, 21261, 74499, 220, 2166, 1174, 220, 2491, 1174, 220, 1135, 662, 763, 1521, 5157, 220, 2491, 1174, 459, 1651, 354, 30193, 374, 9124, 8649, 264, 1664, 25181, 10314, 449, 1633, 1579, 31398, 8547, 320, 9910, 439, 1925, 4791, 25034, 28334, 37015, 21261, 11595, 705, 902, 2103, 18911, 10186, 67547, 304, 1202, 12435, 20326, 13, 362, 5933, 3424, 26679, 279, 73464, 315, 1521, 2478, 78790, 21120, 66557, 374, 279, 19115, 64625, 10474, 320, 2152, 47, 8, 17839, 243, 356, 9377, 320, 4151, 19331, 570, 356, 9377, 44393, 323, 2585, 315, 51960, 18249, 1233, 574, 2736, 21091, 220, 3971, 323, 31398, 574, 8813, 449, 10478, 1303, 279, 28334, 4156, 315, 279, 19428, 2478, 78790, 5696, 21120, 323, 8617, 17843, 264, 73929, 315, 25181, 10314, 82, 17425, 1113, 304, 2204, 18445, 220, 4103, 662, 10541, 1579, 18249, 1233, 505, 2478, 78790, 5696, 527, 3685, 311, 387, 73464, 18222, 220, 2491, 1174, 14188, 420, 356, 9377, 44393, 6463, 25181, 10314, 82, 617, 1027, 17427, 304, 279, 59425, 4633, 9659, 17942, 1603, 13, 763, 420, 4652, 11, 584, 3118, 21120, 19677, 43918, 41353, 315, 1579, 24747, 18249, 1233, 505, 264, 31786, 16625, 555, 264, 1403, 78790, 21120, 13, 1789, 3738, 356, 9377, 2819, 11, 420, 82341, 25407, 11815, 264, 16917, 25181, 10314, 13, 1556, 6492, 3196, 389, 57077, 41305, 7133, 320, 14137, 8, 21667, 279, 57077, 10474, 6811, 1990, 279, 66557, 323, 279, 20326, 315, 279, 3927, 66557, 304, 279, 1651, 354, 30193, 13, 1115, 2038, 6276, 26679, 279, 37015, 27032, 323, 8844, 13168, 1990, 3927, 10314, 82, 304, 264, 2478, 2320, 17660, 1651, 354, 30193, 439, 1664, 439, 279, 18653, 287, 315, 279, 42852, 6573, 89131, 5975, 220, 2148, 662, 578, 58632, 19179, 315, 279, 21120, 73464, 5825, 2867, 30816, 315, 279, 356, 9377, 44393, 315, 279, 16940, 59425, 4633, 21120, 4235, 501, 23390, 16628, 13, 18591, 47893, 4096, 578, 22772, 743, 5352, 374, 6982, 304, 23966, 13, 220, 16, 662, 578, 7447, 12, 466, 675, 1617, 320, 27364, 9469, 54, 8, 16557, 2410, 8828, 32418, 24028, 6509, 3213, 220, 508, 320, 43, 7585, 12, 508, 8, 220, 2096, 574, 1511, 439, 264, 21120, 2592, 449, 264, 3428, 20653, 8127, 5975, 369, 13168, 16048, 220, 1774, 555, 264, 8331, 315, 220, 3101, 13, 1102, 3984, 264, 28334, 4907, 315, 220, 1272, 296, 41, 389, 18996, 1306, 18151, 11, 902, 574, 10968, 449, 459, 1022, 36421, 1370, 57565, 320, 46, 2599, 8, 18327, 311, 294, 435, 20484, 44, 284, 220, 16, 13, 18, 33983, 76, 11, 304, 459, 9392, 315, 39775, 19581, 3709, 284, 220, 2131, 11877, 11, 323, 281, 482, 79, 7569, 2065, 13, 26891, 1404, 323, 4367, 1051, 14400, 1701, 264, 73757, 16945, 11, 902, 649, 8454, 279, 128257, 198, 128256, 78191, 198, 4599, 264, 29050, 11071, 315, 57678, 374, 49858, 311, 4661, 279, 4732, 315, 3177, 11, 433, 14385, 439, 264, 52828, 7479, 13, 15483, 264, 364, 501, 23390, 18327, 6, 649, 387, 1511, 311, 37735, 3177, 13, 4800, 459, 6625, 2128, 315, 98417, 505, 279, 7639, 9878, 377, 10181, 315, 56413, 16963, 1233, 11, 47514, 52, 47304, 11, 323, 549, 2727, 3870, 3907, 304, 24067, 617, 32971, 420, 32426, 1474, 29912, 2515, 304, 7872, 11, 323, 51763, 433, 311, 7068, 25181, 11, 1579, 20653, 8127, 1651, 974, 1321, 3177, 62385, 13, 1556, 1651, 974, 1321, 40758, 369, 264, 7239, 339, 315, 264, 7239, 339, 320, 605, 12, 972, 8, 315, 264, 2132, 13, 578, 16628, 1990, 9193, 8147, 21120, 66557, 323, 5030, 706, 9107, 709, 11622, 502, 20414, 311, 279, 9659, 315, 37232, 1003, 371, 3177, 62385, 29869, 369, 1193, 264, 2478, 7895, 1651, 76989, 13, 4314, 76024, 10015, 66557, 649, 304, 2543, 387, 1511, 311, 22477, 279, 30295, 315, 24955, 9533, 7106, 44247, 520, 1207, 12, 6756, 29505, 13, 578, 5410, 1749, 1511, 311, 1893, 1651, 974, 1321, 66557, 374, 3196, 389, 279, 16628, 315, 3221, 3502, 82482, 21120, 3177, 449, 279, 57678, 304, 33299, 315, 35482, 45612, 1778, 439, 47752, 477, 1417, 263, 13, 4800, 12074, 520, 279, 32184, 369, 7867, 974, 1321, 28415, 520, 279, 7639, 9878, 377, 10181, 315, 56413, 16963, 1233, 304, 480, 83385, 323, 47304, 596, 85550, 56625, 26707, 3907, 320, 11237, 52, 705, 304, 20632, 449, 18105, 520, 549, 2727, 3870, 3907, 11, 617, 7946, 11798, 264, 502, 8446, 369, 279, 9659, 315, 25181, 1651, 974, 1321, 3177, 66557, 13, 763, 279, 1176, 3094, 11, 9193, 8147, 5103, 83, 974, 1321, 320, 605, 12, 868, 5819, 8, 21120, 66557, 527, 5535, 311, 16681, 449, 9168, 13, 578, 21120, 3177, 38752, 4861, 279, 9168, 7479, 11, 28772, 4954, 1202, 75164, 33299, 323, 69741, 279, 85855, 57678, 311, 75157, 13890, 311, 459, 9989, 2205, 19983, 315, 279, 4732, 315, 3177, 13, 578, 13239, 1579, 89131, 32426, 1903, 709, 315, 19019, 7366, 57678, 11, 902, 17425, 988, 304, 279, 1890, 5216, 439, 279, 7893, 32424, 21120, 3177, 11, 14385, 1093, 264, 18327, 13, 9843, 279, 57678, 617, 63260, 75157, 430, 5603, 279, 4732, 315, 3177, 814, 3719, 59425, 4633, 11, 323, 3240, 311, 43524, 349, 304, 2077, 311, 279, 21120, 2115, 13, 578, 72758, 39445, 91621, 315, 279, 32426, 18327, 84261, 449, 279, 27000, 3177, 12330, 311, 3041, 10205, 311, 25181, 1651, 974, 1321, 66557, 13, 4314, 66557, 617, 459, 13240, 8250, 315, 13489, 220, 1049, 439, 323, 93959, 304, 279, 14560, 37232, 85311, 5654, 315, 279, 20326, 320, 508, 12, 966, 20622, 33504, 11, 220, 1272, 12, 1399, 384, 53, 570, 763, 13168, 311, 1651, 974, 1321, 66557, 8066, 449, 5129, 21120, 66557, 11, 1884, 9124, 555, 279, 32426, 1474, 29912, 2515, 323, 21120, 66557, 430, 617, 264, 8250, 315, 2478, 29393, 25492, 649, 387, 24559, 14400, 449, 279, 73464, 13, 1115, 1101, 5535, 279, 12074, 311, 23846, 279, 892, 3388, 315, 279, 9659, 1920, 11, 602, 1770, 13, 279, 43524, 367, 315, 279, 32426, 18327, 13, 13516, 18007, 11, 1521, 66557, 527, 1790, 810, 19428, 11, 602, 1770, 13, 6782, 3117, 810, 89235, 11, 1109, 1884, 6994, 481, 449, 279, 5410, 10537, 13, 578, 7319, 21261, 3727, 433, 3284, 311, 6920, 704, 2103, 810, 24473, 22323, 315, 279, 17432, 315, 1207, 6756, 19252, 304, 1972, 892, 13, 7867, 974, 1321, 3177, 66557, 527, 15871, 1511, 311, 2472, 17130, 54245, 11, 323, 8617, 3493, 26793, 1139, 279, 30295, 315, 16188, 11618, 2949, 33299, 13, 578, 5190, 279, 21261, 315, 279, 1651, 974, 1321, 3177, 62385, 11, 279, 810, 2038, 649, 387, 95116, 291, 922, 279, 54245, 315, 19252, 2949, 5030, 13, 3161, 279, 15325, 30816, 315, 279, 32426, 1474, 29912, 2515, 311, 7068, 10107, 1651, 974, 1321, 3177, 66557, 11, 279, 12283, 315, 279, 502, 4007, 617, 8040, 264, 5557, 11, 902, 690, 7431, 98417, 311, 22477, 1524, 19662, 1139, 279, 57700, 315, 279, 31228, 1917, 13, 220, 128257, 198 ]

2,025

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The solar neighbourhood is the closest and most easily studied sample of the Galactic interstellar medium, an understanding of which is essential for models of star formation and galaxy evolution. Observations of an unexpectedly intense diffuse flux of easily absorbed 1/4-kiloelectronvolt X-rays 1 , 2 , coupled with the discovery that interstellar space within about a hundred parsecs of the Sun is almost completely devoid of cool absorbing gas 3 , led to a picture of a ‘local cavity’ filled with X-ray-emitting hot gas, dubbed the local hot bubble 4 , 5 , 6 . This model was recently challenged by suggestions that the emission could instead be readily produced within the Solar System by heavy solar-wind ions exchanging electrons with neutral H and He in interplanetary space 7 , 8 , 9 , 10 , 11 , potentially removing the major piece of evidence for the local existence of million-degree gas within the Galactic disk 12 , 13 , 14 , 15 . Here we report observations showing that the total solar-wind charge-exchange contribution is approximately 40 per cent of the 1/4-keV flux in the Galactic plane. The fact that the measured flux is not dominated by charge exchange supports the notion of a million-degree hot bubble extending about a hundred parsecs from the Sun. Main When the highly ionized solar wind interacts with neutral gas, an electron may hop from a neutral to an outer orbital of an ion, in what is known as charge exchange. The electron then cascades to the ground state of the ion, often emitting soft X-rays in the process 16 . The calculations of X-ray intensity from solar-wind charge exchange depend on limited information about heavy ion fluxes and even more uncertain atomic cross-sections. The ‘Diffuse X-rays from the Local galaxy’ (DXL) sounding rocket mission 17 was launched from the White Sands Missile Range in New Mexico, USA, on 12 December 2012 to make an empirical measurement of the charge exchange flux by observing a region of higher interplanetary neutral density (with a correspondingly higher charge exchange rate) called the ‘helium focusing cone’. Neutral interstellar gas flows at about 25 km s −1 through the Solar System owing to the motion of the Sun through a small interstellar cloud. This material, mostly hydrogen atoms but about 15% helium, flows from the Galactic direction (longitude l , latitude b ) ≈ (3°, 16°), placing Earth downstream of the Sun in early December 18 . The trajectories of the neutral interstellar helium atoms are governed primarily by gravity, executing hyperbolic Keplerian orbits and forming a relatively high-density focusing cone downstream of the Sun about 6° below the ecliptic plane ( Fig. 1 ) 19 . Interstellar hydrogen, on the other hand, is also strongly affected by radiation pressure and photoionization: radiation pressure balances gravity, reducing the focusing effect, while photoionization creates a neutral hydrogen cavity around the Sun. Figure 1: The He focusing cone. Modelled interstellar He density (blue is low density; red is high density) showing the He focusing cone. Keplerian He orbits, Earth’s orbit, and the DXL and ROSAT observing geometries are also shown. PowerPoint slide Full size image The early December launch of DXL placed the He focusing cone near the zenith at midnight. The 7° field of view was scanned slowly back and forth across one side of the cone and more rapidly in a full circle to test the consistency of the derived charge exchange contribution in other directions and to make measurements of the detector particle background while DXL was looking towards Earth ( Extended Data Fig. 1 ). Figure 2 shows the ROSAT All Sky Survey 1/4-keV map 20 (R12 band) with the paths of the DXL slow scan (red) and fast scan (white) overplotted. The ROSAT observation of the slow-scan region was performed in September 1990 when the line of sight was about one astronomical unit (the Earth–Sun distance, 1 au ) away from, and parallel to, the He cone, so its charge exchange contribution was not strongly affected by the cone enhancement ( Fig. 1 ). Figure 2: The DXL scan path. ROSAT all-sky survey map in the 1/4-keV (R12) energy band, shown in Galactic coordinates (contours are labelled in degrees) with l = 180°, b = 0° at the centre. The colour scale shows flux intensity. The units are ROSAT units, RU. The DXL scan path is the white band with the slow portion shown in red. The black line is the 90° horizon for the DXL flight. The width of the band represents the half-power diameter of the instrument beam. PowerPoint slide Full size image For this analysis, we chose pulse height limits for both of the DXL proportional counters (Counter-I and Counter-II) to match the pulse heights of the ROSAT 1/4-keV band as closely as possible ( Extended Data Fig. 2 ). This energy range is dominated by and contains most of the emission from solar-wind charge exchange and/or the local hot bubble. To quantify the solar-wind charge exchange emission we compared both DXL and ROSAT count rates to well determined models of the interplanetary neutral distribution along the lines of sight for both sets of measurements ( Fig. 3 ) 17 , 21 . Figure 4 shows the DXL and ROSAT count rates along the DXL scan path as functions of Galactic longitude. The figure shows the combined Counter-I and Counter-II count rates (black dots) during the DXL scan and the ROSAT 1/4-keV count rates in the same directions (blue solid line). The best fit to the DXL total count rate (red solid line), and the solar-wind charge exchange contributions to DXL (red dashed line) and ROSAT (blue dashed line) rates are also shown (see Table 1 for best-fit parameters: the model shown corresponds to the second column). There is potentially an additional contribution from charge exchange between the solar-wind ions and the geocoronal hydrogen surrounding Earth, which tracks the short-term variations in solar-wind flux. Time variations of a few days", "role": "user" }, { "content": "I spent this past weekend backpacking in Rocky Mountain National Park, where although the snow-swept peaks and the dangerously close wildlife were staggering, the night sky stood in triumph. Without a fire, the stars, a few planets, and the surprisingly bright Milky Way provided the only light to guide our way. But the night sky as seen by the human eye is relatively dark. Little visible light stretching across the cosmos from stars, nebulae, and galaxies actually reaches Earth. The entire night sky as seen by an X-ray detector, however, glows faintly. The origins of the soft X-ray glow permeating the sky have been highly debated for the past 50 years. But new findings show that it comes from both inside and outside the Solar System. Decades of mapping the sky in X-rays with energies around 250 electron volts—about 100 times the energy of visible light—revealed soft emission across the sky. And astronomers have long searched for its source. At first, astronomers proposed a \"local hot bubble\" of gas—likely carved by a nearby supernova explosion during the past 20 million years—to explain the X-ray background. Improved measurements made it increasingly clear that the Sun resides in a region where interstellar gas is unusually sparse. But the local bubble explanation was challenged when astronomers realized that comets were an unexpected source of soft X-rays. In fact, this process, known as solar wind charge exchange, can occur anywhere atoms interact with solar wind ions. Colors indicate the density of interstellar helium near Earth and its enhancement in a downstream cone as the neutral atoms respond to the sun’s gravity (blue is low density, red is high). Also shown are the observing angles for DXL and ROSAT. Credit: NASA’s Goddard Space Flight Center After this discovery, astronomers turned their eyes to within the Solar System and began to wonder whether the X-ray background might be produced by the ionized particles in the solar wind colliding with diffuse interplanetary gas. In order to solve the outstanding mystery, a team of astronomers led by Massimilliano Galeazzi from the University of Miami developed an X-ray instrument capable of taking the necessary measurements. Galeazzi and colleagues rebuilt, tested, calibrated, and adapted X-ray detectors originally designed by the University of Wisconsin and flown on sounding rockets in the 1970s. The mission was named DXL, for Diffuse X-ray emission from the Local Galaxy. On Dec. 12, 2012, DXL launched from the White Sands Missile Range in New Mexico atop a NASA Black Brant IX sounding rocket. It reached a peak altitude of 160 miles and spent a total of five minutes above Earth's atmosphere. The data collected show that the emission is dominated by the local hot bubble, with, at most, 40 percent originating from within the Solar System. \"This is a significant discovery,\" said lead author Massimiliano Galeazzi from the University of Miami in a press release. \"Specifically, the existence or nonexistence of the local bubble affects our understanding of the galaxy in the proximity to the Sun and can be used as foundation for future models of the Galaxy structure.\" It's now clear that the Solar System is currently passing through a small cloud of cold interstellar gas as it moves through the Milky Way. The cloud's neutral hydrogen and helium atoms stream through the Solar System at about 56,000 mph (90,000 km/h). The hydrogen atoms quickly ionize, but the helium atoms travel at a path largely governed by the Sun's gravity. This creates a helium focusing cone—a breeze focused downstream from the Sun—with a much greater density of neutral atoms. These easily collide with solar wind ions and emit soft X-rays. The confirmation of the local hot bubble is a significant development in our understanding of the interstellar medium, which is crucial for understanding star formation and galaxy evolution. \"The DXL team is an extraordinary example of cross-disciplinary science, bringing together astrophysicists, planetary scientists, and heliophysicists,\" said coauthor F. Scott Porter from NASA's Goddard Space Flight Center. \"It's unusual but very rewarding when scientists with such diverse interests come together to produce such groundbreaking results.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The solar neighbourhood is the closest and most easily studied sample of the Galactic interstellar medium, an understanding of which is essential for models of star formation and galaxy evolution. Observations of an unexpectedly intense diffuse flux of easily absorbed 1/4-kiloelectronvolt X-rays 1 , 2 , coupled with the discovery that interstellar space within about a hundred parsecs of the Sun is almost completely devoid of cool absorbing gas 3 , led to a picture of a ‘local cavity’ filled with X-ray-emitting hot gas, dubbed the local hot bubble 4 , 5 , 6 . This model was recently challenged by suggestions that the emission could instead be readily produced within the Solar System by heavy solar-wind ions exchanging electrons with neutral H and He in interplanetary space 7 , 8 , 9 , 10 , 11 , potentially removing the major piece of evidence for the local existence of million-degree gas within the Galactic disk 12 , 13 , 14 , 15 . Here we report observations showing that the total solar-wind charge-exchange contribution is approximately 40 per cent of the 1/4-keV flux in the Galactic plane. The fact that the measured flux is not dominated by charge exchange supports the notion of a million-degree hot bubble extending about a hundred parsecs from the Sun. Main When the highly ionized solar wind interacts with neutral gas, an electron may hop from a neutral to an outer orbital of an ion, in what is known as charge exchange. The electron then cascades to the ground state of the ion, often emitting soft X-rays in the process 16 . The calculations of X-ray intensity from solar-wind charge exchange depend on limited information about heavy ion fluxes and even more uncertain atomic cross-sections. The ‘Diffuse X-rays from the Local galaxy’ (DXL) sounding rocket mission 17 was launched from the White Sands Missile Range in New Mexico, USA, on 12 December 2012 to make an empirical measurement of the charge exchange flux by observing a region of higher interplanetary neutral density (with a correspondingly higher charge exchange rate) called the ‘helium focusing cone’. Neutral interstellar gas flows at about 25 km s −1 through the Solar System owing to the motion of the Sun through a small interstellar cloud. This material, mostly hydrogen atoms but about 15% helium, flows from the Galactic direction (longitude l , latitude b ) ≈ (3°, 16°), placing Earth downstream of the Sun in early December 18 . The trajectories of the neutral interstellar helium atoms are governed primarily by gravity, executing hyperbolic Keplerian orbits and forming a relatively high-density focusing cone downstream of the Sun about 6° below the ecliptic plane ( Fig. 1 ) 19 . Interstellar hydrogen, on the other hand, is also strongly affected by radiation pressure and photoionization: radiation pressure balances gravity, reducing the focusing effect, while photoionization creates a neutral hydrogen cavity around the Sun. Figure 1: The He focusing cone. Modelled interstellar He density (blue is low density; red is high density) showing the He focusing cone. Keplerian He orbits, Earth’s orbit, and the DXL and ROSAT observing geometries are also shown. PowerPoint slide Full size image The early December launch of DXL placed the He focusing cone near the zenith at midnight. The 7° field of view was scanned slowly back and forth across one side of the cone and more rapidly in a full circle to test the consistency of the derived charge exchange contribution in other directions and to make measurements of the detector particle background while DXL was looking towards Earth ( Extended Data Fig. 1 ). Figure 2 shows the ROSAT All Sky Survey 1/4-keV map 20 (R12 band) with the paths of the DXL slow scan (red) and fast scan (white) overplotted. The ROSAT observation of the slow-scan region was performed in September 1990 when the line of sight was about one astronomical unit (the Earth–Sun distance, 1 au ) away from, and parallel to, the He cone, so its charge exchange contribution was not strongly affected by the cone enhancement ( Fig. 1 ). Figure 2: The DXL scan path. ROSAT all-sky survey map in the 1/4-keV (R12) energy band, shown in Galactic coordinates (contours are labelled in degrees) with l = 180°, b = 0° at the centre. The colour scale shows flux intensity. The units are ROSAT units, RU. The DXL scan path is the white band with the slow portion shown in red. The black line is the 90° horizon for the DXL flight. The width of the band represents the half-power diameter of the instrument beam. PowerPoint slide Full size image For this analysis, we chose pulse height limits for both of the DXL proportional counters (Counter-I and Counter-II) to match the pulse heights of the ROSAT 1/4-keV band as closely as possible ( Extended Data Fig. 2 ). This energy range is dominated by and contains most of the emission from solar-wind charge exchange and/or the local hot bubble. To quantify the solar-wind charge exchange emission we compared both DXL and ROSAT count rates to well determined models of the interplanetary neutral distribution along the lines of sight for both sets of measurements ( Fig. 3 ) 17 , 21 . Figure 4 shows the DXL and ROSAT count rates along the DXL scan path as functions of Galactic longitude. The figure shows the combined Counter-I and Counter-II count rates (black dots) during the DXL scan and the ROSAT 1/4-keV count rates in the same directions (blue solid line). The best fit to the DXL total count rate (red solid line), and the solar-wind charge exchange contributions to DXL (red dashed line) and ROSAT (blue dashed line) rates are also shown (see Table 1 for best-fit parameters: the model shown corresponds to the second column). There is potentially an additional contribution from charge exchange between the solar-wind ions and the geocoronal hydrogen surrounding Earth, which tracks the short-term variations in solar-wind flux. Time variations of a few days<|im_end|> <|im_start|>assistant I spent this past weekend backpacking in Rocky Mountain National Park, where although the snow-swept peaks and the dangerously close wildlife were staggering, the night sky stood in triumph. Without a fire, the stars, a few planets, and the surprisingly bright Milky Way provided the only light to guide our way. But the night sky as seen by the human eye is relatively dark. Little visible light stretching across the cosmos from stars, nebulae, and galaxies actually reaches Earth. The entire night sky as seen by an X-ray detector, however, glows faintly. The origins of the soft X-ray glow permeating the sky have been highly debated for the past 50 years. But new findings show that it comes from both inside and outside the Solar System. Decades of mapping the sky in X-rays with energies around 250 electron volts—about 100 times the energy of visible light—revealed soft emission across the sky. And astronomers have long searched for its source. At first, astronomers proposed a "local hot bubble" of gas—likely carved by a nearby supernova explosion during the past 20 million years—to explain the X-ray background. Improved measurements made it increasingly clear that the Sun resides in a region where interstellar gas is unusually sparse. But the local bubble explanation was challenged when astronomers realized that comets were an unexpected source of soft X-rays. In fact, this process, known as solar wind charge exchange, can occur anywhere atoms interact with solar wind ions. Colors indicate the density of interstellar helium near Earth and its enhancement in a downstream cone as the neutral atoms respond to the sun’s gravity (blue is low density, red is high). Also shown are the observing angles for DXL and ROSAT. Credit: NASA’s Goddard Space Flight Center After this discovery, astronomers turned their eyes to within the Solar System and began to wonder whether the X-ray background might be produced by the ionized particles in the solar wind colliding with diffuse interplanetary gas. In order to solve the outstanding mystery, a team of astronomers led by Massimilliano Galeazzi from the University of Miami developed an X-ray instrument capable of taking the necessary measurements. Galeazzi and colleagues rebuilt, tested, calibrated, and adapted X-ray detectors originally designed by the University of Wisconsin and flown on sounding rockets in the 1970s. The mission was named DXL, for Diffuse X-ray emission from the Local Galaxy. On Dec. 12, 2012, DXL launched from the White Sands Missile Range in New Mexico atop a NASA Black Brant IX sounding rocket. It reached a peak altitude of 160 miles and spent a total of five minutes above Earth's atmosphere. The data collected show that the emission is dominated by the local hot bubble, with, at most, 40 percent originating from within the Solar System. "This is a significant discovery," said lead author Massimiliano Galeazzi from the University of Miami in a press release. "Specifically, the existence or nonexistence of the local bubble affects our understanding of the galaxy in the proximity to the Sun and can be used as foundation for future models of the Galaxy structure." It's now clear that the Solar System is currently passing through a small cloud of cold interstellar gas as it moves through the Milky Way. The cloud's neutral hydrogen and helium atoms stream through the Solar System at about 56,000 mph (90,000 km/h). The hydrogen atoms quickly ionize, but the helium atoms travel at a path largely governed by the Sun's gravity. This creates a helium focusing cone—a breeze focused downstream from the Sun—with a much greater density of neutral atoms. These easily collide with solar wind ions and emit soft X-rays. The confirmation of the local hot bubble is a significant development in our understanding of the interstellar medium, which is crucial for understanding star formation and galaxy evolution. "The DXL team is an extraordinary example of cross-disciplinary science, bringing together astrophysicists, planetary scientists, and heliophysicists," said coauthor F. Scott Porter from NASA's Goddard Space Flight Center. "It's unusual but very rewarding when scientists with such diverse interests come together to produce such groundbreaking results." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 13238, 40442, 374, 279, 18585, 323, 1455, 6847, 20041, 6205, 315, 279, 76317, 958, 78393, 11298, 11, 459, 8830, 315, 902, 374, 7718, 369, 4211, 315, 6917, 18488, 323, 34261, 15740, 13, 31943, 811, 315, 459, 51709, 19428, 55517, 31405, 315, 6847, 42101, 220, 16, 14, 19, 12934, 321, 4748, 70329, 97371, 1630, 82817, 220, 16, 1174, 220, 17, 1174, 34356, 449, 279, 18841, 430, 958, 78393, 3634, 2949, 922, 264, 7895, 4820, 4942, 315, 279, 8219, 374, 4661, 6724, 76939, 315, 7155, 70275, 6962, 220, 18, 1174, 6197, 311, 264, 6945, 315, 264, 3451, 2497, 56429, 529, 10409, 449, 1630, 30630, 37612, 15154, 4106, 6962, 11, 42160, 279, 2254, 4106, 24529, 220, 19, 1174, 220, 20, 1174, 220, 21, 662, 1115, 1646, 574, 6051, 29991, 555, 18726, 430, 279, 41353, 1436, 4619, 387, 31368, 9124, 2949, 279, 25450, 744, 555, 8987, 13238, 2695, 485, 65125, 79531, 57678, 449, 21277, 473, 323, 1283, 304, 958, 10609, 16238, 3634, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 13893, 18054, 279, 3682, 6710, 315, 6029, 369, 279, 2254, 14209, 315, 3610, 38775, 6962, 2949, 279, 76317, 13668, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 662, 5810, 584, 1934, 24654, 9204, 430, 279, 2860, 13238, 2695, 485, 6900, 10397, 3455, 19035, 374, 13489, 220, 1272, 824, 2960, 315, 279, 220, 16, 14, 19, 12, 441, 53, 31405, 304, 279, 76317, 11277, 13, 578, 2144, 430, 279, 17303, 31405, 374, 539, 30801, 555, 6900, 9473, 11815, 279, 23035, 315, 264, 3610, 38775, 4106, 24529, 33459, 922, 264, 7895, 4820, 4942, 505, 279, 8219, 13, 4802, 3277, 279, 7701, 28772, 1534, 13238, 10160, 84261, 449, 21277, 6962, 11, 459, 17130, 1253, 7598, 505, 264, 21277, 311, 459, 16335, 65691, 315, 459, 28772, 11, 304, 1148, 374, 3967, 439, 6900, 9473, 13, 578, 17130, 1243, 76057, 3536, 311, 279, 5015, 1614, 315, 279, 28772, 11, 3629, 90556, 8579, 1630, 82817, 304, 279, 1920, 220, 845, 662, 578, 29217, 315, 1630, 30630, 21261, 505, 13238, 2695, 485, 6900, 9473, 6904, 389, 7347, 2038, 922, 8987, 28772, 31405, 288, 323, 1524, 810, 36218, 25524, 5425, 22327, 82, 13, 578, 3451, 22499, 817, 1630, 82817, 505, 279, 8949, 34261, 529, 320, 17001, 43, 8, 49227, 25294, 9131, 220, 1114, 574, 11887, 505, 279, 5929, 79270, 68870, 16842, 304, 1561, 12550, 11, 7427, 11, 389, 220, 717, 6790, 220, 679, 17, 311, 1304, 459, 46763, 19179, 315, 279, 6900, 9473, 31405, 555, 46071, 264, 5654, 315, 5190, 958, 10609, 16238, 21277, 17915, 320, 4291, 264, 8024, 11559, 5190, 6900, 9473, 4478, 8, 2663, 279, 3451, 50222, 2411, 21760, 22949, 24535, 59794, 958, 78393, 6962, 28555, 520, 922, 220, 914, 13437, 274, 25173, 16, 1555, 279, 25450, 744, 56612, 311, 279, 11633, 315, 279, 8219, 1555, 264, 2678, 958, 78393, 9624, 13, 1115, 3769, 11, 10213, 35784, 33299, 719, 922, 220, 868, 4, 97607, 11, 28555, 505, 279, 76317, 5216, 320, 26524, 326, 1174, 21518, 293, 883, 118792, 320, 18, 11877, 11, 220, 845, 11877, 705, 25012, 9420, 52452, 315, 279, 8219, 304, 4216, 6790, 220, 972, 662, 578, 86648, 315, 279, 21277, 958, 78393, 97607, 33299, 527, 27800, 15871, 555, 24128, 11, 31320, 17508, 65, 7918, 98843, 1122, 86228, 323, 30164, 264, 12309, 1579, 89131, 21760, 22949, 52452, 315, 279, 8219, 922, 220, 21, 11877, 3770, 279, 61058, 11696, 292, 11277, 320, 23966, 13, 220, 16, 883, 220, 777, 662, 5783, 78393, 35784, 11, 389, 279, 1023, 1450, 11, 374, 1101, 16917, 11754, 555, 25407, 7410, 323, 6685, 290, 2065, 25, 25407, 7410, 39954, 24128, 11, 18189, 279, 21760, 2515, 11, 1418, 6685, 290, 2065, 11705, 264, 21277, 35784, 56429, 2212, 279, 8219, 13, 19575, 220, 16, 25, 578, 1283, 21760, 22949, 13, 5008, 839, 958, 78393, 1283, 17915, 320, 12481, 374, 3428, 17915, 26, 2579, 374, 1579, 17915, 8, 9204, 279, 1283, 21760, 22949, 13, 98843, 1122, 1283, 86228, 11, 9420, 753, 27605, 11, 323, 279, 31908, 43, 323, 38517, 835, 46071, 69086, 4108, 527, 1101, 6982, 13, 54600, 15332, 8797, 1404, 2217, 578, 4216, 6790, 7195, 315, 31908, 43, 9277, 279, 1283, 21760, 22949, 3221, 279, 99529, 520, 33433, 13, 578, 220, 22, 11877, 2115, 315, 1684, 574, 48548, 14297, 1203, 323, 13544, 4028, 832, 3185, 315, 279, 22949, 323, 810, 19019, 304, 264, 2539, 12960, 311, 1296, 279, 29237, 315, 279, 14592, 6900, 9473, 19035, 304, 1023, 18445, 323, 311, 1304, 22323, 315, 279, 32314, 19320, 4092, 1418, 31908, 43, 574, 3411, 7119, 9420, 320, 41665, 2956, 23966, 13, 220, 16, 7609, 19575, 220, 17, 5039, 279, 38517, 835, 2052, 15064, 24507, 220, 16, 14, 19, 12, 441, 53, 2472, 220, 508, 320, 49, 717, 7200, 8, 449, 279, 13006, 315, 279, 31908, 43, 6435, 8737, 320, 1171, 8, 323, 5043, 8737, 320, 5902, 8, 927, 501, 15889, 13, 578, 38517, 835, 22695, 315, 279, 6435, 1355, 4919, 5654, 574, 10887, 304, 6250, 220, 2550, 15, 994, 279, 1584, 315, 14254, 574, 922, 832, 87283, 5089, 320, 1820, 9420, 4235, 31192, 6138, 11, 220, 16, 8065, 883, 3201, 505, 11, 323, 15638, 311, 11, 279, 1283, 22949, 11, 779, 1202, 6900, 9473, 19035, 574, 539, 16917, 11754, 555, 279, 22949, 27886, 320, 23966, 13, 220, 16, 7609, 19575, 220, 17, 25, 578, 31908, 43, 8737, 1853, 13, 38517, 835, 682, 1355, 8050, 10795, 2472, 304, 279, 220, 16, 14, 19, 12, 441, 53, 320, 49, 717, 8, 4907, 7200, 11, 6982, 304, 76317, 14259, 320, 778, 2530, 527, 61336, 304, 12628, 8, 449, 326, 284, 220, 5245, 11877, 11, 293, 284, 220, 15, 11877, 520, 279, 12541, 13, 578, 12745, 5569, 5039, 31405, 21261, 13, 578, 8316, 527, 38517, 835, 8316, 11, 69925, 13, 578, 31908, 43, 8737, 1853, 374, 279, 4251, 7200, 449, 279, 6435, 13651, 6982, 304, 2579, 13, 578, 3776, 1584, 374, 279, 220, 1954, 11877, 35174, 369, 279, 31908, 43, 11213, 13, 578, 2430, 315, 279, 7200, 11105, 279, 4376, 27624, 23899, 315, 279, 14473, 24310, 13, 54600, 15332, 8797, 1404, 2217, 1789, 420, 6492, 11, 584, 14896, 28334, 2673, 13693, 369, 2225, 315, 279, 31908, 43, 55272, 32632, 320, 14431, 22197, 323, 20315, 76644, 8, 311, 2489, 279, 28334, 36394, 315, 279, 38517, 835, 220, 16, 14, 19, 12, 441, 53, 7200, 439, 15499, 439, 3284, 320, 41665, 2956, 23966, 13, 220, 17, 7609, 1115, 4907, 2134, 374, 30801, 555, 323, 5727, 1455, 315, 279, 41353, 505, 13238, 2695, 485, 6900, 9473, 323, 5255, 279, 2254, 4106, 24529, 13, 2057, 76498, 279, 13238, 2695, 485, 6900, 9473, 41353, 584, 7863, 2225, 31908, 43, 323, 38517, 835, 1797, 7969, 311, 1664, 11075, 4211, 315, 279, 958, 10609, 16238, 21277, 8141, 3235, 279, 5238, 315, 14254, 369, 2225, 7437, 315, 22323, 320, 23966, 13, 220, 18, 883, 220, 1114, 1174, 220, 1691, 662, 19575, 220, 19, 5039, 279, 31908, 43, 323, 38517, 835, 1797, 7969, 3235, 279, 31908, 43, 8737, 1853, 439, 5865, 315, 76317, 21155, 13, 578, 7216, 5039, 279, 11093, 20315, 22197, 323, 20315, 76644, 1797, 7969, 320, 11708, 32094, 8, 2391, 279, 31908, 43, 8737, 323, 279, 38517, 835, 220, 16, 14, 19, 12, 441, 53, 1797, 7969, 304, 279, 1890, 18445, 320, 12481, 6573, 1584, 570, 578, 1888, 5052, 311, 279, 31908, 43, 2860, 1797, 4478, 320, 1171, 6573, 1584, 705, 323, 279, 13238, 2695, 485, 6900, 9473, 19564, 311, 31908, 43, 320, 1171, 67822, 1584, 8, 323, 38517, 835, 320, 12481, 67822, 1584, 8, 7969, 527, 1101, 6982, 320, 4151, 6771, 220, 16, 369, 1888, 50660, 5137, 25, 279, 1646, 6982, 34310, 311, 279, 2132, 3330, 570, 2684, 374, 13893, 459, 5217, 19035, 505, 6900, 9473, 1990, 279, 13238, 2695, 485, 65125, 323, 279, 3980, 511, 269, 25180, 35784, 14932, 9420, 11, 902, 14242, 279, 2875, 9860, 27339, 304, 13238, 2695, 485, 31405, 13, 4212, 27339, 315, 264, 2478, 2919, 128257, 198, 128256, 78191, 198, 40, 7543, 420, 3347, 9178, 34236, 287, 304, 48641, 19149, 5165, 5657, 11, 1405, 8051, 279, 12056, 1355, 906, 418, 40035, 323, 279, 59594, 3345, 30405, 1051, 55944, 11, 279, 3814, 13180, 14980, 304, 38586, 13, 17586, 264, 4027, 11, 279, 9958, 11, 264, 2478, 33975, 11, 323, 279, 29392, 10107, 89819, 12424, 3984, 279, 1193, 3177, 311, 8641, 1057, 1648, 13, 2030, 279, 3814, 13180, 439, 3970, 555, 279, 3823, 8071, 374, 12309, 6453, 13, 15013, 9621, 3177, 42949, 4028, 279, 83645, 505, 9958, 11, 81967, 5724, 68, 11, 323, 66017, 3604, 25501, 9420, 13, 578, 4553, 3814, 13180, 439, 3970, 555, 459, 1630, 30630, 32314, 11, 4869, 11, 2840, 4336, 38678, 398, 13, 578, 33472, 315, 279, 8579, 1630, 30630, 37066, 55424, 1113, 279, 13180, 617, 1027, 7701, 59674, 369, 279, 3347, 220, 1135, 1667, 13, 2030, 502, 14955, 1501, 430, 433, 4131, 505, 2225, 4871, 323, 4994, 279, 25450, 744, 13, 3799, 3536, 315, 13021, 279, 13180, 304, 1630, 82817, 449, 49969, 2212, 220, 5154, 17130, 87167, 2345, 9274, 220, 1041, 3115, 279, 4907, 315, 9621, 3177, 2345, 92076, 5962, 8579, 41353, 4028, 279, 13180, 13, 1628, 87887, 617, 1317, 27600, 369, 1202, 2592, 13, 2468, 1176, 11, 87887, 11223, 264, 330, 2497, 4106, 24529, 1, 315, 6962, 2345, 14617, 49267, 555, 264, 14373, 39887, 12949, 25176, 2391, 279, 3347, 220, 508, 3610, 1667, 50617, 10552, 279, 1630, 30630, 4092, 13, 59223, 22323, 1903, 433, 15098, 2867, 430, 279, 8219, 54068, 304, 264, 5654, 1405, 958, 78393, 6962, 374, 57899, 34544, 13, 2030, 279, 2254, 24529, 16540, 574, 29991, 994, 87887, 15393, 430, 470, 1441, 1051, 459, 16907, 2592, 315, 8579, 1630, 82817, 13, 763, 2144, 11, 420, 1920, 11, 3967, 439, 13238, 10160, 6900, 9473, 11, 649, 12446, 12660, 33299, 16681, 449, 13238, 10160, 65125, 13, 9718, 13519, 279, 17915, 315, 958, 78393, 97607, 3221, 9420, 323, 1202, 27886, 304, 264, 52452, 22949, 439, 279, 21277, 33299, 6013, 311, 279, 7160, 753, 24128, 320, 12481, 374, 3428, 17915, 11, 2579, 374, 1579, 570, 7429, 6982, 527, 279, 46071, 27030, 369, 31908, 43, 323, 38517, 835, 13, 16666, 25, 22146, 753, 4359, 67, 569, 11746, 27675, 5955, 4740, 420, 18841, 11, 87887, 6656, 872, 6548, 311, 2949, 279, 25450, 744, 323, 6137, 311, 5895, 3508, 279, 1630, 30630, 4092, 2643, 387, 9124, 555, 279, 28772, 1534, 19252, 304, 279, 13238, 10160, 4631, 6714, 449, 55517, 958, 10609, 16238, 6962, 13, 763, 2015, 311, 11886, 279, 19310, 23347, 11, 264, 2128, 315, 87887, 6197, 555, 9346, 318, 484, 13389, 79332, 72418, 505, 279, 3907, 315, 18045, 8040, 459, 1630, 30630, 14473, 13171, 315, 4737, 279, 5995, 22323, 13, 79332, 72418, 323, 18105, 60685, 11, 12793, 11, 86085, 11, 323, 30464, 1630, 30630, 69087, 13517, 6319, 555, 279, 3907, 315, 21073, 323, 53850, 389, 49227, 53098, 304, 279, 220, 4468, 15, 82, 13, 578, 9131, 574, 7086, 31908, 43, 11, 369, 29469, 817, 1630, 30630, 41353, 505, 279, 8949, 20238, 13, 1952, 3799, 13, 220, 717, 11, 220, 679, 17, 11, 31908, 43, 11887, 505, 279, 5929, 79270, 68870, 16842, 304, 1561, 12550, 47088, 264, 22146, 5348, 3320, 519, 40812, 49227, 25294, 13, 1102, 8813, 264, 16557, 36958, 315, 220, 6330, 8931, 323, 7543, 264, 2860, 315, 4330, 4520, 3485, 9420, 596, 16975, 13, 578, 828, 14890, 1501, 430, 279, 41353, 374, 30801, 555, 279, 2254, 4106, 24529, 11, 449, 11, 520, 1455, 11, 220, 1272, 3346, 71373, 505, 2949, 279, 25450, 744, 13, 330, 2028, 374, 264, 5199, 18841, 1359, 1071, 3063, 3229, 9346, 318, 321, 13389, 79332, 72418, 505, 279, 3907, 315, 18045, 304, 264, 3577, 4984, 13, 330, 48614, 750, 11, 279, 14209, 477, 2536, 93772, 315, 279, 2254, 24529, 22223, 1057, 8830, 315, 279, 34261, 304, 279, 37843, 311, 279, 8219, 323, 649, 387, 1511, 439, 16665, 369, 3938, 4211, 315, 279, 20238, 6070, 1210, 1102, 596, 1457, 2867, 430, 279, 25450, 744, 374, 5131, 12579, 1555, 264, 2678, 9624, 315, 9439, 958, 78393, 6962, 439, 433, 11031, 1555, 279, 89819, 12424, 13, 578, 9624, 596, 21277, 35784, 323, 97607, 33299, 4365, 1555, 279, 25450, 744, 520, 922, 220, 3487, 11, 931, 35061, 320, 1954, 11, 931, 13437, 7682, 570, 578, 35784, 33299, 6288, 28772, 553, 11, 719, 279, 97607, 33299, 5944, 520, 264, 1853, 14090, 27800, 555, 279, 8219, 596, 24128, 13, 1115, 11705, 264, 97607, 21760, 22949, 29096, 46385, 10968, 52452, 505, 279, 8219, 81902, 264, 1790, 7191, 17915, 315, 21277, 33299, 13, 4314, 6847, 67190, 449, 13238, 10160, 65125, 323, 17105, 8579, 1630, 82817, 13, 578, 20109, 315, 279, 2254, 4106, 24529, 374, 264, 5199, 4500, 304, 1057, 8830, 315, 279, 958, 78393, 11298, 11, 902, 374, 16996, 369, 8830, 6917, 18488, 323, 34261, 15740, 13, 330, 791, 31908, 43, 2128, 374, 459, 24674, 3187, 315, 5425, 52765, 44550, 8198, 11, 12967, 3871, 12025, 22761, 1065, 292, 1705, 11, 62938, 14248, 11, 323, 11591, 72, 85404, 292, 1705, 1359, 1071, 1080, 3170, 435, 13, 10016, 39037, 505, 22146, 596, 4359, 67, 569, 11746, 27675, 5955, 13, 330, 2181, 596, 19018, 719, 1633, 42093, 994, 14248, 449, 1778, 17226, 12034, 2586, 3871, 311, 8356, 1778, 64955, 3135, 1210, 220, 128257, 198 ]

2,200

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Background Acute kidney injury (AKI) occurs frequently in critically ill patients and is associated with adverse outcomes. Cellular mechanisms underlying AKI and kidney cell responses to injury remain incompletely understood. Methods We performed single-nuclei transcriptomics, bulk transcriptomics, molecular imaging studies, and conventional histology on kidney tissues from 8 individuals with severe AKI (stage 2 or 3 according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria). Specimens were obtained within 1–2 h after individuals had succumbed to critical illness associated with respiratory infections, with 4 of 8 individuals diagnosed with COVID-19. Control kidney tissues were obtained post-mortem or after nephrectomy from individuals without AKI. Results High-depth single cell-resolved gene expression data of human kidneys affected by AKI revealed enrichment of novel injury-associated cell states within the major cell types of the tubular epithelium, in particular in proximal tubules, thick ascending limbs, and distal convoluted tubules. Four distinct, hierarchically interconnected injured cell states were distinguishable and characterized by transcriptome patterns associated with oxidative stress, hypoxia, interferon response, and epithelial-to-mesenchymal transition, respectively. Transcriptome differences between individuals with AKI were driven primarily by the cell type-specific abundance of these four injury subtypes rather than by private molecular responses. AKI-associated changes in gene expression between individuals with and without COVID-19 were similar. Conclusions The study provides an extensive resource of the cell type-specific transcriptomic responses associated with critical illness-associated AKI in humans, highlighting recurrent disease-associated signatures and inter-individual heterogeneity. Personalized molecular disease assessment in human AKI may foster the development of tailored therapies. Background Acute kidney injury (AKI) is a frequently observed clinical syndrome, which associates with high morbidity and mortality [ 1 , 2 , 3 , 4 , 5 , 6 ]. More than 10% of all hospitalized individuals and more than 50% of critically ill individuals admitted to intensive care units develop AKI [ 2 , 3 , 7 ]. Despite its extensive clinical and economic impact, AKI therapy is largely limited to best supportive care and kidney replacement therapies (hemodialysis or hemofiltration) in patients with advanced kidney failure [ 8 , 9 , 10 ]. Targeted therapies preventing AKI or fostering recovery from AKI are still missing. Numerous attempts have been made using animal models and human samples to uncover underlying mechanisms of AKI, to identify therapeutic targets and to identify disease biomarkers [ 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. However, studies in a controlled clinical setting with cell type-specific gene expression resolution of human AKI are lacking. Although AKI is uniformly defined by changes in serum creatinine levels and/or urinary output, previous studies suggest a vast underlying heterogeneity and complexity of AKI with an unknown number of AKI subtypes, suggesting that personalized approaches in the treatment of AKI may be needed [ 15 , 18 , 19 , 20 ]. Most recently, the question of AKI subtypes was intensively debated when high incidence rates of AKI were observed in individuals with COVID-19 [ 21 , 22 , 23 , 24 ]. In particular, the question was raised whether COVID-19 entails a specific molecular subtype of AKI, through either renal viral tropism or other systemic effects [ 25 , 26 , 27 , 28 , 29 ]. Single-cell gene expression approaches provide powerful tools to investigate cell type-specific changes and cellular interactions and thus may help to delineate potential molecular subtypes of AKI. Recent mouse studies underlined the potential of single cell resolution for our understanding of AKI and revealed new molecular cell states associated with AKI [ 11 , 12 , 30 ]. Here, we present a comparative single-cell census of the human kidney in individuals with critical illness-associated AKI compared to controls without AKI. Methods Study cohort For this study, we collected post mortem biopsies from eight patients with AKI and 4 control patients. AKI patients (sample names AKI 1–8) were enrolled in the study if they showed clinical criteria of severe AKI (as defined by KDIGO criteria for AKI stage 2 or stage 3) within 5 days prior to sampling and if they developed AKI in a clinical setting of critical illness, severe respiratory infections, and systemic inflammation. All post mortem samples were collected on intensive care units of Charité-medizin in Berlin, Germany. The four control samples are comprised of three specimens from tumor-adjacent normal tissues (samples names Control-TN 1–3) and three post mortem biopsy specimens of one brain-dead patient from three different time points (15, 60, and 120 min after cessation of circulation, sample names Control-15 min, Control-60 min, Control-120 min) to account for post mortem effects. Samples Control-TN1-3 were collected during elective tumor nephrectomies performed at Charité-medizin in collaboration with the Department of Urology. The remaining control samples (post mortem biopsies) represented by samples Control-15 min, Control-60 min, and Control-120 min were collected on an intensive care unit of Charité-medizin. Specimen collection After consent of next of kin, post mortem biopsies were collected using 18G biopsy needles within 2 h from death from individuals who had died in a clinical setting of critical illness on intensive care units of Charité-medizin Berlin (ethics approval EA2/045/18). Control tissue from tumor-adjacent normal tissue of tumor nephrectomies was collected during tumor nephrectomies (ethics approval EA4/026/18). Kidney specimens were either stored in pre-cooled RNAlater at 4 °C for 24 h and then stored at − 80 °C (for snRNA-seq) or in 4% formaldehyde (for histopathological studies and in situ hybridizations). Single-nuclei sequencing Kidney specimen subjected to snRNA-seq were kept at 4 °C at all times. All specimens were treated as described in detail in Leiz et al. [ 31 ]. Main steps included are as follows: Specimens were thoroughly minced in nuclear lysis buffer 1 (nuclear lysis buffer (Sigma) + Ribolock (1U/µl) + VRC (10 mM)) and homogenized using a dounce homogenizer with pastel A (Sigma D8938-1SET), filtered (100 µm), homogenized again (douncer with pastel B), filtered through a 35-µm strainer, and centrifuged (5 min, 500 g). The pellet was then resuspended in nuclear lysis buffer 2 (nuclear lysis buffer + Ribolock", "role": "user" }, { "content": "Acute kidney injury (AKI) is a frequent complication associated with various diseases and particularly affects patients on intensive care units. However, the mechanisms underlying AKI are incompletely understood. Just recently, an interdisciplinary research team has used single-cell sequencing techniques to uncover the molecular processes associated with AKI. Reporting in Genome Medicine and Kidney International, they describe novel gene expression patterns of injured kidney cells that may lead to new therapeutic approaches and strategies for biomarker discovery. The studies were conducted in close collaboration between Charité—Universitätsmedizin Berlin; the Berlin Institute for Medical Systems Biology (BIMSB) of the Max Delbrück Center; the German Rheumatism Research Center Berlin (DRFZ), a Leibniz Institute; and the Hannover Medical School. The kidneys are among the most important organs in the human body. They filter waste products from the blood, control body fluid composition and blood pressure, influence energy metabolism, and produce vital hormones. If kidney function is impaired—as is the case in AKI—there can be severe consequences. \"AKI is a frequent and serious complication in critically ill patients, affecting about half of our intensive care unit patients,\" says Dr. Jan Klocke of Charité's Department of Nephrology and Medical Intensive Care. \"The condition is often underestimated, despite the fact that AKI is associated with increased mortality and patients can suffer permanent damage, even complete loss of kidney function.\" AKI can accompany a wide range of diseases. It often occurs in conjunction with cardiovascular diseases or severe infectious diseases such as COVID-19, but also after surgical interventions or in association with drug treatment. There are often no concrete treatment options. \"We try to stabilize affected patients, but so far it is usually not possible to reverse the destructive processes in the kidney with targeted treatments,\" says Dr. Hinze, who played a key role in supervising one of the studies at Charité and the Max Delbrück Center and now works at the Hannover Medical School. \"Up to now, little has been known about which mechanisms are at play in the kidney cells. The aim of our studies was to shed some light on this, with the long-term goal of improving the treatment provided to our patients in the clinic.\" AKI is often triggered by an insufficient supply of blood to the kidneys, causing the cells there to no longer receive sufficient oxygen and nutrients—and to react with stress. The cells go into a kind of alarm mode and produce signal substances that can lead to inflammatory and remodeling processes (fibrosis) in the surrounding tissue. It is known from animal model studies that epithelial cells—the cells that line the fine renal tubules—are involved in these inflammatory and fibrotic processes. This was demonstrated using a novel state-of the-art method called single-cell sequencing, which enables researchers to create a detailed profile of the molecular gene expression profiles of thousands of individual cells. But what happens on the cellular level in human AKI? This is the question that research teams led by Dr. Hinze and Dr. Klocke set out to investigate. The two recently published studies are among the first to ever investigate the molecular processes in AKI using single-cell technologies in human kidney cells. The scientists examined cells taken from tissue and urine samples of more than 40 patients and analyzed the molecular patterns of more than 140,000 cells using state-of-the-art bioinformatics approaches. \"Single-cell sequencing allows us to virtually zoom into each cell and see which genes are active in that cell at that point in time,\" explains Dr. Hinze. \"From this, we can determine whether that particular kidney cell is currently functioning normally, is under stress, or is about to die. This cutting-edge technology gives us an understanding of AKI in unprecedented detail.\" The team was also able to show that different cell types of the kidney react quite differently to AKI, with the strongest response observed in the epithelial cells of the renal tubules. These are the smallest functional units of the kidney and consist of several segments. It was known from animal models that epithelial cells of a specific early renal tubule segment were mainly affected by AKI. However, the results of the latest studies on human kidney cells have revealed that the epithelial cells of almost all tubule segments are involved in the injury processes. \"This illustrates once again how important it is that we study human systems and learn to understand them better,\" says Dr. Hinze. \"In the different types of epithelial cells, we were able to identify certain molecular patterns that occurred in all patients with AKI, but at individual abundances. In the future, these findings could help doctors to better assess the risk for severe disease progression.\" In clinical practice, physicians ideally need a fast, non-invasive, and precise testing method to clearly diagnose AKI at an early stage. In order to get closer to this vision for the future, Dr. Klocke started searching for epithelial cells in urine samples. Hardly any cells are found in the urine of healthy people. But in those with AKI, epithelial cells detach from the renal tubule and are excreted into the urine. However, since cells do not survive in urine for long, there were initial doubts as to whether the cells would still be intact and whether their molecular state could even be measured using single-cell sequencing. \"We processed the urine samples within four to six hours, and it actually worked very well,\" says Dr. Klocke. The researchers were able to determine from which segment of the renal tubules the cells came from and which genetic programs they had activated in response to kidney damage. \"The information provided by the cells from the urine samples matched that of the corresponding cells from tissue samples,\" says Dr. Klocke. \"Thus, urine provides us with an uncomplicated and patient-friendly method of obtaining sample material for further investigations—in order to identify biomarkers and, in the long term, perhaps reduce or even replace kidney biopsies.\" With the two current studies, the research team has provided completely new insights into the cellular mechanisms in AKI using single cell sequencing as well as promising approaches for future diagnostic procedures and personalized therapies. In further studies, they plan to enroll a larger number of patients, investigate the cellular responses in different underlying diseases, and uncover other fundamental molecular mechanisms of AKI using cell cultures. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Background Acute kidney injury (AKI) occurs frequently in critically ill patients and is associated with adverse outcomes. Cellular mechanisms underlying AKI and kidney cell responses to injury remain incompletely understood. Methods We performed single-nuclei transcriptomics, bulk transcriptomics, molecular imaging studies, and conventional histology on kidney tissues from 8 individuals with severe AKI (stage 2 or 3 according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria). Specimens were obtained within 1–2 h after individuals had succumbed to critical illness associated with respiratory infections, with 4 of 8 individuals diagnosed with COVID-19. Control kidney tissues were obtained post-mortem or after nephrectomy from individuals without AKI. Results High-depth single cell-resolved gene expression data of human kidneys affected by AKI revealed enrichment of novel injury-associated cell states within the major cell types of the tubular epithelium, in particular in proximal tubules, thick ascending limbs, and distal convoluted tubules. Four distinct, hierarchically interconnected injured cell states were distinguishable and characterized by transcriptome patterns associated with oxidative stress, hypoxia, interferon response, and epithelial-to-mesenchymal transition, respectively. Transcriptome differences between individuals with AKI were driven primarily by the cell type-specific abundance of these four injury subtypes rather than by private molecular responses. AKI-associated changes in gene expression between individuals with and without COVID-19 were similar. Conclusions The study provides an extensive resource of the cell type-specific transcriptomic responses associated with critical illness-associated AKI in humans, highlighting recurrent disease-associated signatures and inter-individual heterogeneity. Personalized molecular disease assessment in human AKI may foster the development of tailored therapies. Background Acute kidney injury (AKI) is a frequently observed clinical syndrome, which associates with high morbidity and mortality [ 1 , 2 , 3 , 4 , 5 , 6 ]. More than 10% of all hospitalized individuals and more than 50% of critically ill individuals admitted to intensive care units develop AKI [ 2 , 3 , 7 ]. Despite its extensive clinical and economic impact, AKI therapy is largely limited to best supportive care and kidney replacement therapies (hemodialysis or hemofiltration) in patients with advanced kidney failure [ 8 , 9 , 10 ]. Targeted therapies preventing AKI or fostering recovery from AKI are still missing. Numerous attempts have been made using animal models and human samples to uncover underlying mechanisms of AKI, to identify therapeutic targets and to identify disease biomarkers [ 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. However, studies in a controlled clinical setting with cell type-specific gene expression resolution of human AKI are lacking. Although AKI is uniformly defined by changes in serum creatinine levels and/or urinary output, previous studies suggest a vast underlying heterogeneity and complexity of AKI with an unknown number of AKI subtypes, suggesting that personalized approaches in the treatment of AKI may be needed [ 15 , 18 , 19 , 20 ]. Most recently, the question of AKI subtypes was intensively debated when high incidence rates of AKI were observed in individuals with COVID-19 [ 21 , 22 , 23 , 24 ]. In particular, the question was raised whether COVID-19 entails a specific molecular subtype of AKI, through either renal viral tropism or other systemic effects [ 25 , 26 , 27 , 28 , 29 ]. Single-cell gene expression approaches provide powerful tools to investigate cell type-specific changes and cellular interactions and thus may help to delineate potential molecular subtypes of AKI. Recent mouse studies underlined the potential of single cell resolution for our understanding of AKI and revealed new molecular cell states associated with AKI [ 11 , 12 , 30 ]. Here, we present a comparative single-cell census of the human kidney in individuals with critical illness-associated AKI compared to controls without AKI. Methods Study cohort For this study, we collected post mortem biopsies from eight patients with AKI and 4 control patients. AKI patients (sample names AKI 1–8) were enrolled in the study if they showed clinical criteria of severe AKI (as defined by KDIGO criteria for AKI stage 2 or stage 3) within 5 days prior to sampling and if they developed AKI in a clinical setting of critical illness, severe respiratory infections, and systemic inflammation. All post mortem samples were collected on intensive care units of Charité-medizin in Berlin, Germany. The four control samples are comprised of three specimens from tumor-adjacent normal tissues (samples names Control-TN 1–3) and three post mortem biopsy specimens of one brain-dead patient from three different time points (15, 60, and 120 min after cessation of circulation, sample names Control-15 min, Control-60 min, Control-120 min) to account for post mortem effects. Samples Control-TN1-3 were collected during elective tumor nephrectomies performed at Charité-medizin in collaboration with the Department of Urology. The remaining control samples (post mortem biopsies) represented by samples Control-15 min, Control-60 min, and Control-120 min were collected on an intensive care unit of Charité-medizin. Specimen collection After consent of next of kin, post mortem biopsies were collected using 18G biopsy needles within 2 h from death from individuals who had died in a clinical setting of critical illness on intensive care units of Charité-medizin Berlin (ethics approval EA2/045/18). Control tissue from tumor-adjacent normal tissue of tumor nephrectomies was collected during tumor nephrectomies (ethics approval EA4/026/18). Kidney specimens were either stored in pre-cooled RNAlater at 4 °C for 24 h and then stored at − 80 °C (for snRNA-seq) or in 4% formaldehyde (for histopathological studies and in situ hybridizations). Single-nuclei sequencing Kidney specimen subjected to snRNA-seq were kept at 4 °C at all times. All specimens were treated as described in detail in Leiz et al. [ 31 ]. Main steps included are as follows: Specimens were thoroughly minced in nuclear lysis buffer 1 (nuclear lysis buffer (Sigma) + Ribolock (1U/µl) + VRC (10 mM)) and homogenized using a dounce homogenizer with pastel A (Sigma D8938-1SET), filtered (100 µm), homogenized again (douncer with pastel B), filtered through a 35-µm strainer, and centrifuged (5 min, 500 g). The pellet was then resuspended in nuclear lysis buffer 2 (nuclear lysis buffer + Ribolock<|im_end|> <|im_start|>assistant Acute kidney injury (AKI) is a frequent complication associated with various diseases and particularly affects patients on intensive care units. However, the mechanisms underlying AKI are incompletely understood. Just recently, an interdisciplinary research team has used single-cell sequencing techniques to uncover the molecular processes associated with AKI. Reporting in Genome Medicine and Kidney International, they describe novel gene expression patterns of injured kidney cells that may lead to new therapeutic approaches and strategies for biomarker discovery. The studies were conducted in close collaboration between Charité—Universitätsmedizin Berlin; the Berlin Institute for Medical Systems Biology (BIMSB) of the Max Delbrück Center; the German Rheumatism Research Center Berlin (DRFZ), a Leibniz Institute; and the Hannover Medical School. The kidneys are among the most important organs in the human body. They filter waste products from the blood, control body fluid composition and blood pressure, influence energy metabolism, and produce vital hormones. If kidney function is impaired—as is the case in AKI—there can be severe consequences. "AKI is a frequent and serious complication in critically ill patients, affecting about half of our intensive care unit patients," says Dr. Jan Klocke of Charité's Department of Nephrology and Medical Intensive Care. "The condition is often underestimated, despite the fact that AKI is associated with increased mortality and patients can suffer permanent damage, even complete loss of kidney function." AKI can accompany a wide range of diseases. It often occurs in conjunction with cardiovascular diseases or severe infectious diseases such as COVID-19, but also after surgical interventions or in association with drug treatment. There are often no concrete treatment options. "We try to stabilize affected patients, but so far it is usually not possible to reverse the destructive processes in the kidney with targeted treatments," says Dr. Hinze, who played a key role in supervising one of the studies at Charité and the Max Delbrück Center and now works at the Hannover Medical School. "Up to now, little has been known about which mechanisms are at play in the kidney cells. The aim of our studies was to shed some light on this, with the long-term goal of improving the treatment provided to our patients in the clinic." AKI is often triggered by an insufficient supply of blood to the kidneys, causing the cells there to no longer receive sufficient oxygen and nutrients—and to react with stress. The cells go into a kind of alarm mode and produce signal substances that can lead to inflammatory and remodeling processes (fibrosis) in the surrounding tissue. It is known from animal model studies that epithelial cells—the cells that line the fine renal tubules—are involved in these inflammatory and fibrotic processes. This was demonstrated using a novel state-of the-art method called single-cell sequencing, which enables researchers to create a detailed profile of the molecular gene expression profiles of thousands of individual cells. But what happens on the cellular level in human AKI? This is the question that research teams led by Dr. Hinze and Dr. Klocke set out to investigate. The two recently published studies are among the first to ever investigate the molecular processes in AKI using single-cell technologies in human kidney cells. The scientists examined cells taken from tissue and urine samples of more than 40 patients and analyzed the molecular patterns of more than 140,000 cells using state-of-the-art bioinformatics approaches. "Single-cell sequencing allows us to virtually zoom into each cell and see which genes are active in that cell at that point in time," explains Dr. Hinze. "From this, we can determine whether that particular kidney cell is currently functioning normally, is under stress, or is about to die. This cutting-edge technology gives us an understanding of AKI in unprecedented detail." The team was also able to show that different cell types of the kidney react quite differently to AKI, with the strongest response observed in the epithelial cells of the renal tubules. These are the smallest functional units of the kidney and consist of several segments. It was known from animal models that epithelial cells of a specific early renal tubule segment were mainly affected by AKI. However, the results of the latest studies on human kidney cells have revealed that the epithelial cells of almost all tubule segments are involved in the injury processes. "This illustrates once again how important it is that we study human systems and learn to understand them better," says Dr. Hinze. "In the different types of epithelial cells, we were able to identify certain molecular patterns that occurred in all patients with AKI, but at individual abundances. In the future, these findings could help doctors to better assess the risk for severe disease progression." In clinical practice, physicians ideally need a fast, non-invasive, and precise testing method to clearly diagnose AKI at an early stage. In order to get closer to this vision for the future, Dr. Klocke started searching for epithelial cells in urine samples. Hardly any cells are found in the urine of healthy people. But in those with AKI, epithelial cells detach from the renal tubule and are excreted into the urine. However, since cells do not survive in urine for long, there were initial doubts as to whether the cells would still be intact and whether their molecular state could even be measured using single-cell sequencing. "We processed the urine samples within four to six hours, and it actually worked very well," says Dr. Klocke. The researchers were able to determine from which segment of the renal tubules the cells came from and which genetic programs they had activated in response to kidney damage. "The information provided by the cells from the urine samples matched that of the corresponding cells from tissue samples," says Dr. Klocke. "Thus, urine provides us with an uncomplicated and patient-friendly method of obtaining sample material for further investigations—in order to identify biomarkers and, in the long term, perhaps reduce or even replace kidney biopsies." With the two current studies, the research team has provided completely new insights into the cellular mechanisms in AKI using single cell sequencing as well as promising approaches for future diagnostic procedures and personalized therapies. In further studies, they plan to enroll a larger number of patients, investigate the cellular responses in different underlying diseases, and uncover other fundamental molecular mechanisms of AKI using cell cultures. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 25837, 6515, 1088, 39042, 11134, 320, 12173, 40, 8, 13980, 14134, 304, 41440, 5986, 6978, 323, 374, 5938, 449, 31959, 20124, 13, 88207, 24717, 16940, 31672, 40, 323, 39042, 2849, 14847, 311, 11134, 7293, 53990, 50268, 16365, 13, 19331, 1226, 10887, 3254, 5392, 22935, 72, 36815, 24203, 11, 20155, 36815, 24203, 11, 31206, 32758, 7978, 11, 323, 21349, 13034, 2508, 389, 39042, 39881, 505, 220, 23, 7931, 449, 15748, 31672, 40, 320, 21406, 220, 17, 477, 220, 18, 4184, 311, 32666, 3520, 31974, 25, 22728, 4504, 8121, 4470, 6716, 320, 90709, 61589, 8, 13186, 570, 11197, 46697, 1051, 12457, 2949, 220, 16, 4235, 17, 305, 1306, 7931, 1047, 20639, 99696, 311, 9200, 17563, 5938, 449, 42631, 30020, 11, 449, 220, 19, 315, 220, 23, 7931, 29704, 449, 20562, 12, 777, 13, 7935, 39042, 39881, 1051, 12457, 1772, 90653, 336, 477, 1306, 44964, 2921, 5650, 505, 7931, 2085, 31672, 40, 13, 18591, 5234, 31410, 3254, 2849, 11849, 8905, 15207, 7645, 828, 315, 3823, 81960, 11754, 555, 31672, 40, 10675, 70272, 315, 11775, 11134, 75968, 2849, 5415, 2949, 279, 3682, 2849, 4595, 315, 279, 15286, 1299, 64779, 301, 2411, 11, 304, 4040, 304, 22267, 2931, 15286, 2482, 11, 12314, 36488, 49695, 11, 323, 1612, 278, 5804, 337, 2844, 15286, 2482, 13, 13625, 12742, 11, 12694, 1132, 2740, 83416, 15902, 2849, 5415, 1051, 33137, 481, 323, 32971, 555, 36815, 638, 12912, 5938, 449, 79401, 8631, 11, 9950, 5241, 689, 11, 41305, 263, 2077, 11, 323, 64779, 59544, 4791, 1474, 288, 20345, 1631, 278, 9320, 11, 15947, 13, 91403, 638, 12062, 1990, 7931, 449, 31672, 40, 1051, 16625, 15871, 555, 279, 2849, 955, 19440, 37492, 315, 1521, 3116, 11134, 1207, 9426, 4856, 1109, 555, 879, 31206, 14847, 13, 31672, 40, 75968, 4442, 304, 15207, 7645, 1990, 7931, 449, 323, 2085, 20562, 12, 777, 1051, 4528, 13, 1221, 24436, 578, 4007, 5825, 459, 16781, 5211, 315, 279, 2849, 955, 19440, 36815, 3151, 14847, 5938, 449, 9200, 17563, 75968, 31672, 40, 304, 12966, 11, 39686, 65174, 8624, 75968, 33728, 323, 958, 18251, 17246, 30548, 76730, 13, 19758, 1534, 31206, 8624, 15813, 304, 3823, 31672, 40, 1253, 31087, 279, 4500, 315, 41891, 52312, 13, 25837, 6515, 1088, 39042, 11134, 320, 12173, 40, 8, 374, 264, 14134, 13468, 14830, 28439, 11, 902, 40531, 449, 1579, 93144, 19025, 323, 29528, 510, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 21087, 4497, 1109, 220, 605, 4, 315, 682, 70340, 7931, 323, 810, 1109, 220, 1135, 4, 315, 41440, 5986, 7931, 16584, 311, 37295, 2512, 8316, 2274, 31672, 40, 510, 220, 17, 1174, 220, 18, 1174, 220, 22, 21087, 18185, 1202, 16781, 14830, 323, 7100, 5536, 11, 31672, 40, 15419, 374, 14090, 7347, 311, 1888, 33445, 2512, 323, 39042, 14039, 52312, 320, 30132, 90169, 4548, 477, 17728, 1073, 37704, 367, 8, 304, 6978, 449, 11084, 39042, 8060, 510, 220, 23, 1174, 220, 24, 1174, 220, 605, 21087, 13791, 291, 52312, 27252, 31672, 40, 477, 86644, 13654, 505, 31672, 40, 527, 2103, 7554, 13, 86915, 13865, 617, 1027, 1903, 1701, 10065, 4211, 323, 3823, 10688, 311, 45063, 16940, 24717, 315, 31672, 40, 11, 311, 10765, 37471, 11811, 323, 311, 10765, 8624, 39538, 91141, 510, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 21087, 4452, 11, 7978, 304, 264, 14400, 14830, 6376, 449, 2849, 955, 19440, 15207, 7645, 11175, 315, 3823, 31672, 40, 527, 32161, 13, 10541, 31672, 40, 374, 78909, 4613, 555, 4442, 304, 41529, 6184, 83334, 5990, 323, 5255, 72735, 2612, 11, 3766, 7978, 4284, 264, 13057, 16940, 30548, 76730, 323, 23965, 315, 31672, 40, 449, 459, 9987, 1396, 315, 31672, 40, 1207, 9426, 11, 23377, 430, 35649, 20414, 304, 279, 6514, 315, 31672, 40, 1253, 387, 4460, 510, 220, 868, 1174, 220, 972, 1174, 220, 777, 1174, 220, 508, 21087, 7648, 6051, 11, 279, 3488, 315, 31672, 40, 1207, 9426, 574, 25228, 3210, 59674, 994, 1579, 39775, 7969, 315, 31672, 40, 1051, 13468, 304, 7931, 449, 20562, 12, 777, 510, 220, 1691, 1174, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 21087, 763, 4040, 11, 279, 3488, 574, 9408, 3508, 20562, 12, 777, 71204, 264, 3230, 31206, 53582, 315, 31672, 40, 11, 1555, 3060, 63915, 29962, 21965, 2191, 477, 1023, 46417, 6372, 510, 220, 914, 1174, 220, 1627, 1174, 220, 1544, 1174, 220, 1591, 1174, 220, 1682, 21087, 11579, 33001, 15207, 7645, 20414, 3493, 8147, 7526, 311, 19874, 2849, 955, 19440, 4442, 323, 35693, 22639, 323, 8617, 1253, 1520, 311, 91784, 349, 4754, 31206, 1207, 9426, 315, 31672, 40, 13, 35390, 8814, 7978, 1234, 15472, 279, 4754, 315, 3254, 2849, 11175, 369, 1057, 8830, 315, 31672, 40, 323, 10675, 502, 31206, 2849, 5415, 5938, 449, 31672, 40, 510, 220, 806, 1174, 220, 717, 1174, 220, 966, 21087, 5810, 11, 584, 3118, 264, 55394, 3254, 33001, 44702, 315, 279, 3823, 39042, 304, 7931, 449, 9200, 17563, 75968, 31672, 40, 7863, 311, 11835, 2085, 31672, 40, 13, 19331, 19723, 41944, 1789, 420, 4007, 11, 584, 14890, 1772, 10237, 336, 6160, 3806, 552, 505, 8223, 6978, 449, 31672, 40, 323, 220, 19, 2585, 6978, 13, 31672, 40, 6978, 320, 13925, 5144, 31672, 40, 220, 16, 4235, 23, 8, 1051, 37191, 304, 279, 4007, 422, 814, 8710, 14830, 13186, 315, 15748, 31672, 40, 320, 300, 4613, 555, 64090, 61589, 13186, 369, 31672, 40, 6566, 220, 17, 477, 6566, 220, 18, 8, 2949, 220, 20, 2919, 4972, 311, 25936, 323, 422, 814, 8040, 31672, 40, 304, 264, 14830, 6376, 315, 9200, 17563, 11, 15748, 42631, 30020, 11, 323, 46417, 37140, 13, 2052, 1772, 10237, 336, 10688, 1051, 14890, 389, 37295, 2512, 8316, 315, 4969, 13109, 45872, 78071, 304, 20437, 11, 10057, 13, 578, 3116, 2585, 10688, 527, 40056, 315, 2380, 57749, 505, 36254, 12, 25770, 18680, 4725, 39881, 320, 42218, 5144, 7935, 9469, 45, 220, 16, 4235, 18, 8, 323, 2380, 1772, 10237, 336, 99647, 57749, 315, 832, 8271, 6953, 329, 8893, 505, 2380, 2204, 892, 3585, 320, 868, 11, 220, 1399, 11, 323, 220, 4364, 1332, 1306, 83460, 315, 35855, 11, 6205, 5144, 7935, 12, 868, 1332, 11, 7935, 12, 1399, 1332, 11, 7935, 12, 4364, 1332, 8, 311, 2759, 369, 1772, 10237, 336, 6372, 13, 59450, 7935, 9469, 45, 16, 12, 18, 1051, 14890, 2391, 98590, 36254, 44964, 2921, 316, 552, 10887, 520, 4969, 13109, 45872, 78071, 304, 20632, 449, 279, 6011, 315, 549, 299, 36781, 13, 578, 9861, 2585, 10688, 320, 2252, 10237, 336, 6160, 3806, 552, 8, 15609, 555, 10688, 7935, 12, 868, 1332, 11, 7935, 12, 1399, 1332, 11, 323, 7935, 12, 4364, 1332, 1051, 14890, 389, 459, 37295, 2512, 5089, 315, 4969, 13109, 45872, 78071, 13, 11197, 27236, 4526, 4740, 14771, 315, 1828, 315, 24890, 11, 1772, 10237, 336, 6160, 3806, 552, 1051, 14890, 1701, 220, 972, 38, 99647, 57267, 2949, 220, 17, 305, 505, 4648, 505, 7931, 889, 1047, 8636, 304, 264, 14830, 6376, 315, 9200, 17563, 389, 37295, 2512, 8316, 315, 4969, 13109, 45872, 78071, 20437, 320, 774, 1233, 14765, 39462, 17, 14, 23785, 14, 972, 570, 7935, 20438, 505, 36254, 12, 25770, 18680, 4725, 20438, 315, 36254, 44964, 2921, 316, 552, 574, 14890, 2391, 36254, 44964, 2921, 316, 552, 320, 774, 1233, 14765, 39462, 19, 14, 21641, 14, 972, 570, 32666, 3520, 57749, 1051, 3060, 9967, 304, 864, 23283, 42831, 46916, 2149, 977, 520, 220, 19, 37386, 34, 369, 220, 1187, 305, 323, 1243, 9967, 520, 25173, 220, 1490, 37386, 34, 320, 2000, 4224, 31820, 7962, 80, 8, 477, 304, 220, 19, 4, 16287, 86836, 320, 2000, 13034, 36211, 5848, 7978, 323, 304, 10109, 26038, 8200, 570, 11579, 5392, 22935, 72, 62119, 32666, 3520, 58184, 38126, 311, 4224, 31820, 7962, 80, 1051, 8774, 520, 220, 19, 37386, 34, 520, 682, 3115, 13, 2052, 57749, 1051, 12020, 439, 7633, 304, 7872, 304, 2009, 450, 1880, 453, 13, 510, 220, 2148, 21087, 4802, 7504, 5343, 527, 439, 11263, 25, 11197, 46697, 1051, 27461, 94927, 304, 11499, 326, 4548, 4240, 220, 16, 320, 77, 9834, 326, 4548, 4240, 320, 63116, 8, 489, 64205, 337, 1197, 320, 16, 52, 14, 74148, 75, 8, 489, 650, 7532, 320, 605, 84317, 595, 323, 5105, 11968, 1534, 1701, 264, 294, 9933, 5105, 11968, 3213, 449, 3347, 301, 362, 320, 63116, 423, 26088, 23, 12, 16, 6008, 705, 18797, 320, 1041, 64012, 76, 705, 5105, 11968, 1534, 1578, 320, 67, 80845, 449, 3347, 301, 426, 705, 18797, 1555, 264, 220, 1758, 12, 74148, 76, 610, 1780, 11, 323, 74182, 773, 291, 320, 20, 1332, 11, 220, 2636, 342, 570, 578, 68510, 574, 1243, 594, 67449, 304, 11499, 326, 4548, 4240, 220, 17, 320, 77, 9834, 326, 4548, 4240, 489, 64205, 337, 1197, 128257, 198, 128256, 78191, 198, 11916, 1088, 39042, 11134, 320, 12173, 40, 8, 374, 264, 21420, 86919, 5938, 449, 5370, 19338, 323, 8104, 22223, 6978, 389, 37295, 2512, 8316, 13, 4452, 11, 279, 24717, 16940, 31672, 40, 527, 53990, 50268, 16365, 13, 4702, 6051, 11, 459, 88419, 3495, 2128, 706, 1511, 3254, 33001, 62119, 12823, 311, 45063, 279, 31206, 11618, 5938, 449, 31672, 40, 13, 47793, 304, 82917, 19152, 323, 32666, 3520, 7327, 11, 814, 7664, 11775, 15207, 7645, 12912, 315, 15902, 39042, 7917, 430, 1253, 3063, 311, 502, 37471, 20414, 323, 15174, 369, 39538, 13152, 18841, 13, 578, 7978, 1051, 13375, 304, 3345, 20632, 1990, 4969, 13109, 2345, 65715, 65421, 2641, 2106, 78071, 20437, 26, 279, 20437, 10181, 369, 13235, 15264, 40023, 320, 33, 1829, 17094, 8, 315, 279, 7639, 7462, 1347, 19919, 5955, 26, 279, 6063, 71636, 46313, 2191, 8483, 5955, 20437, 320, 7842, 37, 57, 705, 264, 2009, 581, 77, 450, 10181, 26, 323, 279, 28829, 2017, 13235, 6150, 13, 578, 81960, 527, 4315, 279, 1455, 3062, 36853, 304, 279, 3823, 2547, 13, 2435, 4141, 12571, 3956, 505, 279, 6680, 11, 2585, 2547, 15962, 18528, 323, 6680, 7410, 11, 10383, 4907, 39097, 11, 323, 8356, 16595, 44315, 13, 1442, 39042, 734, 374, 50160, 60654, 374, 279, 1162, 304, 31672, 40, 2345, 19041, 649, 387, 15748, 16296, 13, 330, 12173, 40, 374, 264, 21420, 323, 6129, 86919, 304, 41440, 5986, 6978, 11, 28987, 922, 4376, 315, 1057, 37295, 2512, 5089, 6978, 1359, 2795, 2999, 13, 4448, 735, 1039, 68, 315, 4969, 13109, 596, 6011, 315, 452, 24453, 299, 36781, 323, 13235, 1357, 4114, 10852, 13, 330, 791, 3044, 374, 3629, 87136, 11, 8994, 279, 2144, 430, 31672, 40, 374, 5938, 449, 7319, 29528, 323, 6978, 649, 7831, 15690, 5674, 11, 1524, 4686, 4814, 315, 39042, 734, 1210, 31672, 40, 649, 19780, 264, 7029, 2134, 315, 19338, 13, 1102, 3629, 13980, 304, 32546, 449, 41713, 19338, 477, 15748, 50600, 19338, 1778, 439, 20562, 12, 777, 11, 719, 1101, 1306, 34933, 39455, 477, 304, 15360, 449, 5623, 6514, 13, 2684, 527, 3629, 912, 14509, 6514, 2671, 13, 330, 1687, 1456, 311, 70236, 11754, 6978, 11, 719, 779, 3117, 433, 374, 6118, 539, 3284, 311, 10134, 279, 40652, 11618, 304, 279, 39042, 449, 17550, 22972, 1359, 2795, 2999, 13, 50733, 3059, 11, 889, 6476, 264, 1401, 3560, 304, 15945, 3876, 832, 315, 279, 7978, 520, 4969, 13109, 323, 279, 7639, 7462, 1347, 19919, 5955, 323, 1457, 4375, 520, 279, 28829, 2017, 13235, 6150, 13, 330, 2378, 311, 1457, 11, 2697, 706, 1027, 3967, 922, 902, 24717, 527, 520, 1514, 304, 279, 39042, 7917, 13, 578, 9395, 315, 1057, 7978, 574, 311, 25351, 1063, 3177, 389, 420, 11, 449, 279, 1317, 9860, 5915, 315, 18899, 279, 6514, 3984, 311, 1057, 6978, 304, 279, 28913, 1210, 31672, 40, 374, 3629, 22900, 555, 459, 39413, 8312, 315, 6680, 311, 279, 81960, 11, 14718, 279, 7917, 1070, 311, 912, 5129, 5371, 14343, 24463, 323, 37493, 17223, 311, 14085, 449, 8631, 13, 578, 7917, 733, 1139, 264, 3169, 315, 17035, 3941, 323, 8356, 8450, 33155, 430, 649, 3063, 311, 47288, 323, 70430, 11618, 320, 76426, 63412, 8, 304, 279, 14932, 20438, 13, 1102, 374, 3967, 505, 10065, 1646, 7978, 430, 64779, 59544, 7917, 22416, 7917, 430, 1584, 279, 7060, 63915, 15286, 2482, 83872, 6532, 304, 1521, 47288, 323, 16178, 4744, 292, 11618, 13, 1115, 574, 21091, 1701, 264, 11775, 1614, 8838, 279, 38921, 1749, 2663, 3254, 33001, 62119, 11, 902, 20682, 12074, 311, 1893, 264, 11944, 5643, 315, 279, 31206, 15207, 7645, 21542, 315, 9214, 315, 3927, 7917, 13, 2030, 1148, 8741, 389, 279, 35693, 2237, 304, 3823, 31672, 40, 30, 1115, 374, 279, 3488, 430, 3495, 7411, 6197, 555, 2999, 13, 50733, 3059, 323, 2999, 13, 735, 1039, 68, 743, 704, 311, 19874, 13, 578, 1403, 6051, 4756, 7978, 527, 4315, 279, 1176, 311, 3596, 19874, 279, 31206, 11618, 304, 31672, 40, 1701, 3254, 33001, 14645, 304, 3823, 39042, 7917, 13, 578, 14248, 25078, 7917, 4529, 505, 20438, 323, 40335, 10688, 315, 810, 1109, 220, 1272, 6978, 323, 30239, 279, 31206, 12912, 315, 810, 1109, 220, 6860, 11, 931, 7917, 1701, 1614, 8838, 10826, 38921, 17332, 98588, 20414, 13, 330, 11126, 33001, 62119, 6276, 603, 311, 21907, 15932, 1139, 1855, 2849, 323, 1518, 902, 21389, 527, 4642, 304, 430, 2849, 520, 430, 1486, 304, 892, 1359, 15100, 2999, 13, 50733, 3059, 13, 330, 3915, 420, 11, 584, 649, 8417, 3508, 430, 4040, 39042, 2849, 374, 5131, 31301, 14614, 11, 374, 1234, 8631, 11, 477, 374, 922, 311, 2815, 13, 1115, 14713, 48448, 5557, 6835, 603, 459, 8830, 315, 31672, 40, 304, 31069, 7872, 1210, 578, 2128, 574, 1101, 3025, 311, 1501, 430, 2204, 2849, 4595, 315, 279, 39042, 14085, 5115, 22009, 311, 31672, 40, 11, 449, 279, 31005, 2077, 13468, 304, 279, 64779, 59544, 7917, 315, 279, 63915, 15286, 2482, 13, 4314, 527, 279, 25655, 16003, 8316, 315, 279, 39042, 323, 6824, 315, 3892, 21282, 13, 1102, 574, 3967, 505, 10065, 4211, 430, 64779, 59544, 7917, 315, 264, 3230, 4216, 63915, 15286, 1130, 10449, 1051, 14918, 11754, 555, 31672, 40, 13, 4452, 11, 279, 3135, 315, 279, 5652, 7978, 389, 3823, 39042, 7917, 617, 10675, 430, 279, 64779, 59544, 7917, 315, 4661, 682, 15286, 1130, 21282, 527, 6532, 304, 279, 11134, 11618, 13, 330, 2028, 46480, 3131, 1578, 1268, 3062, 433, 374, 430, 584, 4007, 3823, 6067, 323, 4048, 311, 3619, 1124, 2731, 1359, 2795, 2999, 13, 50733, 3059, 13, 330, 644, 279, 2204, 4595, 315, 64779, 59544, 7917, 11, 584, 1051, 3025, 311, 10765, 3738, 31206, 12912, 430, 10222, 304, 682, 6978, 449, 31672, 40, 11, 719, 520, 3927, 23325, 3095, 13, 763, 279, 3938, 11, 1521, 14955, 1436, 1520, 16410, 311, 2731, 8720, 279, 5326, 369, 15748, 8624, 33824, 1210, 763, 14830, 6725, 11, 35944, 50663, 1205, 264, 5043, 11, 2536, 3502, 78134, 11, 323, 24473, 7649, 1749, 311, 9539, 58681, 31672, 40, 520, 459, 4216, 6566, 13, 763, 2015, 311, 636, 12401, 311, 420, 11376, 369, 279, 3938, 11, 2999, 13, 735, 1039, 68, 3940, 15389, 369, 64779, 59544, 7917, 304, 40335, 10688, 13, 11481, 398, 904, 7917, 527, 1766, 304, 279, 40335, 315, 9498, 1274, 13, 2030, 304, 1884, 449, 31672, 40, 11, 64779, 59544, 7917, 47881, 505, 279, 63915, 15286, 1130, 323, 527, 506, 4523, 291, 1139, 279, 40335, 13, 4452, 11, 2533, 7917, 656, 539, 18167, 304, 40335, 369, 1317, 11, 1070, 1051, 2926, 40017, 439, 311, 3508, 279, 7917, 1053, 2103, 387, 35539, 323, 3508, 872, 31206, 1614, 1436, 1524, 387, 17303, 1701, 3254, 33001, 62119, 13, 330, 1687, 15590, 279, 40335, 10688, 2949, 3116, 311, 4848, 4207, 11, 323, 433, 3604, 6575, 1633, 1664, 1359, 2795, 2999, 13, 735, 1039, 68, 13, 578, 12074, 1051, 3025, 311, 8417, 505, 902, 10449, 315, 279, 63915, 15286, 2482, 279, 7917, 3782, 505, 323, 902, 19465, 7620, 814, 1047, 22756, 304, 2077, 311, 39042, 5674, 13, 330, 791, 2038, 3984, 555, 279, 7917, 505, 279, 40335, 10688, 18545, 430, 315, 279, 12435, 7917, 505, 20438, 10688, 1359, 2795, 2999, 13, 735, 1039, 68, 13, 330, 45600, 11, 40335, 5825, 603, 449, 459, 66637, 14040, 323, 8893, 22658, 1749, 315, 19546, 6205, 3769, 369, 4726, 26969, 49525, 2015, 311, 10765, 39538, 91141, 323, 11, 304, 279, 1317, 4751, 11, 8530, 8108, 477, 1524, 8454, 39042, 6160, 3806, 552, 1210, 3161, 279, 1403, 1510, 7978, 11, 279, 3495, 2128, 706, 3984, 6724, 502, 26793, 1139, 279, 35693, 24717, 304, 31672, 40, 1701, 3254, 2849, 62119, 439, 1664, 439, 26455, 20414, 369, 3938, 15439, 16346, 323, 35649, 52312, 13, 763, 4726, 7978, 11, 814, 3197, 311, 52880, 264, 8294, 1396, 315, 6978, 11, 19874, 279, 35693, 14847, 304, 2204, 16940, 19338, 11, 323, 45063, 1023, 16188, 31206, 24717, 315, 31672, 40, 1701, 2849, 27833, 13, 220, 128257, 198 ]

2,768

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Networks offer an intuitive visual representation of complex systems. Important network characteristics can often be recognized by eye and, in turn, patterns that stand out visually often have a meaningful interpretation. In conventional network layout algorithms, however, the precise determinants of a node’s position within a layout are difficult to decipher and to control. Here we propose an approach for directly encoding arbitrary structural or functional network characteristics into node positions. We introduce a series of two- and three-dimensional layouts, benchmark their efficiency for model networks, and demonstrate their power for elucidating structure-to-function relationships in large-scale biological networks. Main Networks are used to investigate a wide range of technological, social and biological systems 1 . Key factors for their success are the availability of powerful mathematical and computational analysis tools, but also their intuitive visual interpretation. For example, the central position of genes within molecular networks indicates essential cellular processes 2 , densely connected clusters represent functional complexes 3 , and global patterns, such as the ring-like architecture of co-regulation networks, have been found to reflect principles of cellular organization 4 . However, the full potential of network visualizations for exploring complex systems is limited by several conceptual and practical challenges. (1) Networks do not have a natural two- or three-dimensional (2D or 3D) embedding. Any network layout thus involves a choice of which aspects of the high-dimensional pairwise relationships are visually represented, and which are not. (2) In widely used layout algorithms, such as force-directed methods, this choice is made in an implicit and thus intransparent fashion, often based on subjective, esthetic criteria. This lack of a clear relationship between structural network characteristics and node positioning makes the resulting layouts difficult to interpret. (3) Likewise, there are no layout algorithms available that allow for explicitly representing a given network characteristic. (4) Finally, the big size of many real-world networks is a key limiting factor for producing comprehensible layouts, leading to proverbial hair-ball visualizations. In this Brief Communication we introduce a framework for generating network layouts that address these challenges by using dimensionality reduction to directly encode network properties into node positions. Not only can structural network properties be visually encoded in this fashion, but also external information reflecting the functional characteristics of nodes or links. We propose the following procedure (Fig. 1a ). For a given network, we first compile a set of F features for each of N nodes, incorporating any structural or functional characteristic we wish to be visually reflected in the final layout. The resulting ( N × F ) feature matrix is then converted into an ( N × N ) similarity matrix, which serves as input to dimensionality reduction methods to compute 2D or 3D embeddings. These embeddings can either be used directly as node coordinates, resulting in network layouts we termed portraits. Alternately, embeddings on 2D surfaces can be further extended towards 3D topographic or geodesic maps by using the third dimension for an additional variable of choice. The topographic map extends a flat 2D embedding by an additional z coordinate, and geodesic maps introduce an additional radial coordinate in spherical embeddings. In total, our framework thus offers four different maps in two and three dimensions (Fig. 1b ). The key advantage of our framework, offering both versatility and interpretability, is its ability to incorporate and explicitly display various desired node characteristics or node pair relationships. We implemented five examples that demonstrate the diversity of potential layouts. (1) The global layout uses network propagation for an efficient, high-resolution representation of pairwise network distances. (2) The local layout emphasizes similar connection patterns between node pairs. (3) The importance layout combines several metrics for the overall importance of a node, such as degree, betweenness, closeness and eigenvector centrality. (4) Functional layouts depict node similarities according to external node features. (5) Combined layouts allow for tuning between layouts that are dominated by either structural or functional features. Fig. 1: Framework of interpretable network maps. a , Overview. A node similarity matrix reflecting any network features to be visually represented is embedded into 2D or 3D geometries using dimensionality reduction methods. b , Schematic depiction of the resulting four types of network map: 2D and 3D network portraits directly use the outputs of the dimensionality reduction; topographic and geodesic maps incorporate an additional z or radial variable, respectively. c , The network models used for benchmarking: Cayley tree, cubic grid and torus lattice. d – f , Model network portraits based on global ( d ), local ( e ) and importance ( f ) layouts. The global layouts recapitulate the expected global shape according to pairwise node distances. The local layouts reveal bi- and multipartite network structures. The importance layouts cluster nodes with similar structural importance. g , Comparison of network-based and Euclidean layout distance for all node pairs in a cubic grid ( N = 1,000) for the global layout, two force-directed algorithms and node2vec. All layouts achieve high correlation (Pearson’s ρ glob = 0.99, ρ node2vec = 0.97, ρ force,nx = 0.97, ρ force,igraph = 0.98). Boxes summarize values of all n node pairs at network distance d , with n ranging from n = 4 at distance d = 27 (for corner node pairs) to n = 46,852 for d = 9. Whiskers denote the values for the minimum, first, second and third quartiles and maximum. h , Comparison of the final correlations for cubic grids of increasing size when limiting the wall clock running time of the algorithms to the running time of the global layout. i , Computational wall times that the respective algorithms require to achieve the same correlation as the global layout for cube grids of increasing size. Source data Full size image To illustrate and benchmark our framework, we first applied it to easily interpretable model networks: (1) a Cayley tree, (2) a cubic grid and (3) a torus lattice (Fig. 1c ). The Cayley tree is organized in hierarchical levels. All nodes except for those in", "role": "user" }, { "content": "Researchers at Cornell Tech have created a new approach to helping survivors of domestic abuse stop assailants from hacking into their devices and social media to surveil, harass and hurt them. The model focuses on \"continuity of care,\" so clients experience a seamless relationship with one volunteer tech consultant over time, similar to a health care setting. It matches survivors with consultants who understand their needs and establish trust, offers survivors multiple ways to safely communicate with consultants, and securely stores their tech abuse history and concerns. \"Personal data management in tech abuse is a complex thing that can't always be 'solved' in a single half-hour visit,\" said Emily Tseng, a doctoral student and lead author on a paper about the model. \"Most of the approaches that exist in tech support are limited by a one-size-fits-all protocol more akin to an emergency room than a primary care provider.\" Tseng will present the paper \"Care Infrastructure for Digital Security in Intimate Partner Violence\" in April at the ACM CHI Conference on Human Factors in Computing Systems in New Orleans. Tseng and her colleagues at Cornell Tech's Clinic to End Tech Abuse developed the new approach in partnership with New York City's Mayor's Office to End Domestic and Gender-Based Violence. Their research draws on eight months of data, as well as interviews with volunteer technology consultants and experts on intimate partner violence (IPV). \"This work provides an honest look at both the benefits and burdens of running a volunteer technology consultant service for IPV survivors, as well as the challenges that arise as we work to safely provide computer security advice as care,\" said co-author Nicola Dell, associate professor at Cornell Tech's Jacobs Technion-Cornell Institute. \"Our hope is that our experiences will be valuable for others who are interested in helping at-risk communities experiencing computer insecurity.\" Survivors can experience many forms of gender-based violence, including technology facilitated abuse, said Cecile Noel, commissioner of the Mayor's Office to End Domestic and Gender-Based Violence. \"Cornell Tech's groundbreaking program not only helps survivors experiencing technology abuse but is also working to better understand how people misuse technology so that we can create better protections for survivors,\" Noel said. \"We are proud of the critical role our longstanding partner Cornell Tech plays in improving the lives of survivors.\" Tech abuse often exists within a larger web of harm, Tseng said. \"In an ideal world, the people on the \"Geek Squad' would be able to treat tech abuse with the sensitivity of a social worker.\" Assailants can abuse their victims through tech including spyware, also known as stalkerware, and through inappropriate use of location-tracking features in phones and other devices. They harass their former partners on social media, such as by posting private photos and posing as their victims to alienate family and friends. Abusers can also hack into email accounts and change recovery emails and phone numbers to their own, potentially devastating their victims' careers. In previous models, counselors remained anonymous, impacting their ability to build trust with survivors. Short, one-time appointments were not long enough to address clients' needs. And appointments took place at a specific time; survivors who could not leave their homes or find a safe, private place to take a call were unable to access services and couldn't reach counselors at other times. It can be frustrating and even re-traumatizing for survivors to share their stories with new consultants at each appointment, Tseng said. One of the team's larger goals is to offer survivors more peace of mind and feelings of empowerment—that they have the tools to handle future challenges. \"With technology, there are so many ways to remain entangled with your abuser even after you've physically and romantically left the relationship,\" Tseng said. One tricky element is determining how much support is realistic. While a one-time \"urgent care\" visit is probably insufficient, prolonged engagement would be unsustainable for consultants and the clinic as a whole. \"In several cases, consultants ended up working with clients over many appointments stretching on for weeks or months,\" Tseng said. As a next step, she wants to explore additional ways to evaluate ongoing security-care relations from the perspective of survivors, particularly people from marginalized communities. Dell co-created the Clinic to End Tech Abuse with Thomas Ristenpart, associate professor at Cornell Tech; both Dell and Ristenpart are also affiliated with the Cornell Ann S. Bowers College of Computing and Information Science. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Networks offer an intuitive visual representation of complex systems. Important network characteristics can often be recognized by eye and, in turn, patterns that stand out visually often have a meaningful interpretation. In conventional network layout algorithms, however, the precise determinants of a node’s position within a layout are difficult to decipher and to control. Here we propose an approach for directly encoding arbitrary structural or functional network characteristics into node positions. We introduce a series of two- and three-dimensional layouts, benchmark their efficiency for model networks, and demonstrate their power for elucidating structure-to-function relationships in large-scale biological networks. Main Networks are used to investigate a wide range of technological, social and biological systems 1 . Key factors for their success are the availability of powerful mathematical and computational analysis tools, but also their intuitive visual interpretation. For example, the central position of genes within molecular networks indicates essential cellular processes 2 , densely connected clusters represent functional complexes 3 , and global patterns, such as the ring-like architecture of co-regulation networks, have been found to reflect principles of cellular organization 4 . However, the full potential of network visualizations for exploring complex systems is limited by several conceptual and practical challenges. (1) Networks do not have a natural two- or three-dimensional (2D or 3D) embedding. Any network layout thus involves a choice of which aspects of the high-dimensional pairwise relationships are visually represented, and which are not. (2) In widely used layout algorithms, such as force-directed methods, this choice is made in an implicit and thus intransparent fashion, often based on subjective, esthetic criteria. This lack of a clear relationship between structural network characteristics and node positioning makes the resulting layouts difficult to interpret. (3) Likewise, there are no layout algorithms available that allow for explicitly representing a given network characteristic. (4) Finally, the big size of many real-world networks is a key limiting factor for producing comprehensible layouts, leading to proverbial hair-ball visualizations. In this Brief Communication we introduce a framework for generating network layouts that address these challenges by using dimensionality reduction to directly encode network properties into node positions. Not only can structural network properties be visually encoded in this fashion, but also external information reflecting the functional characteristics of nodes or links. We propose the following procedure (Fig. 1a ). For a given network, we first compile a set of F features for each of N nodes, incorporating any structural or functional characteristic we wish to be visually reflected in the final layout. The resulting ( N × F ) feature matrix is then converted into an ( N × N ) similarity matrix, which serves as input to dimensionality reduction methods to compute 2D or 3D embeddings. These embeddings can either be used directly as node coordinates, resulting in network layouts we termed portraits. Alternately, embeddings on 2D surfaces can be further extended towards 3D topographic or geodesic maps by using the third dimension for an additional variable of choice. The topographic map extends a flat 2D embedding by an additional z coordinate, and geodesic maps introduce an additional radial coordinate in spherical embeddings. In total, our framework thus offers four different maps in two and three dimensions (Fig. 1b ). The key advantage of our framework, offering both versatility and interpretability, is its ability to incorporate and explicitly display various desired node characteristics or node pair relationships. We implemented five examples that demonstrate the diversity of potential layouts. (1) The global layout uses network propagation for an efficient, high-resolution representation of pairwise network distances. (2) The local layout emphasizes similar connection patterns between node pairs. (3) The importance layout combines several metrics for the overall importance of a node, such as degree, betweenness, closeness and eigenvector centrality. (4) Functional layouts depict node similarities according to external node features. (5) Combined layouts allow for tuning between layouts that are dominated by either structural or functional features. Fig. 1: Framework of interpretable network maps. a , Overview. A node similarity matrix reflecting any network features to be visually represented is embedded into 2D or 3D geometries using dimensionality reduction methods. b , Schematic depiction of the resulting four types of network map: 2D and 3D network portraits directly use the outputs of the dimensionality reduction; topographic and geodesic maps incorporate an additional z or radial variable, respectively. c , The network models used for benchmarking: Cayley tree, cubic grid and torus lattice. d – f , Model network portraits based on global ( d ), local ( e ) and importance ( f ) layouts. The global layouts recapitulate the expected global shape according to pairwise node distances. The local layouts reveal bi- and multipartite network structures. The importance layouts cluster nodes with similar structural importance. g , Comparison of network-based and Euclidean layout distance for all node pairs in a cubic grid ( N = 1,000) for the global layout, two force-directed algorithms and node2vec. All layouts achieve high correlation (Pearson’s ρ glob = 0.99, ρ node2vec = 0.97, ρ force,nx = 0.97, ρ force,igraph = 0.98). Boxes summarize values of all n node pairs at network distance d , with n ranging from n = 4 at distance d = 27 (for corner node pairs) to n = 46,852 for d = 9. Whiskers denote the values for the minimum, first, second and third quartiles and maximum. h , Comparison of the final correlations for cubic grids of increasing size when limiting the wall clock running time of the algorithms to the running time of the global layout. i , Computational wall times that the respective algorithms require to achieve the same correlation as the global layout for cube grids of increasing size. Source data Full size image To illustrate and benchmark our framework, we first applied it to easily interpretable model networks: (1) a Cayley tree, (2) a cubic grid and (3) a torus lattice (Fig. 1c ). The Cayley tree is organized in hierarchical levels. All nodes except for those in<|im_end|> <|im_start|>assistant Researchers at Cornell Tech have created a new approach to helping survivors of domestic abuse stop assailants from hacking into their devices and social media to surveil, harass and hurt them. The model focuses on "continuity of care," so clients experience a seamless relationship with one volunteer tech consultant over time, similar to a health care setting. It matches survivors with consultants who understand their needs and establish trust, offers survivors multiple ways to safely communicate with consultants, and securely stores their tech abuse history and concerns. "Personal data management in tech abuse is a complex thing that can't always be 'solved' in a single half-hour visit," said Emily Tseng, a doctoral student and lead author on a paper about the model. "Most of the approaches that exist in tech support are limited by a one-size-fits-all protocol more akin to an emergency room than a primary care provider." Tseng will present the paper "Care Infrastructure for Digital Security in Intimate Partner Violence" in April at the ACM CHI Conference on Human Factors in Computing Systems in New Orleans. Tseng and her colleagues at Cornell Tech's Clinic to End Tech Abuse developed the new approach in partnership with New York City's Mayor's Office to End Domestic and Gender-Based Violence. Their research draws on eight months of data, as well as interviews with volunteer technology consultants and experts on intimate partner violence (IPV). "This work provides an honest look at both the benefits and burdens of running a volunteer technology consultant service for IPV survivors, as well as the challenges that arise as we work to safely provide computer security advice as care," said co-author Nicola Dell, associate professor at Cornell Tech's Jacobs Technion-Cornell Institute. "Our hope is that our experiences will be valuable for others who are interested in helping at-risk communities experiencing computer insecurity." Survivors can experience many forms of gender-based violence, including technology facilitated abuse, said Cecile Noel, commissioner of the Mayor's Office to End Domestic and Gender-Based Violence. "Cornell Tech's groundbreaking program not only helps survivors experiencing technology abuse but is also working to better understand how people misuse technology so that we can create better protections for survivors," Noel said. "We are proud of the critical role our longstanding partner Cornell Tech plays in improving the lives of survivors." Tech abuse often exists within a larger web of harm, Tseng said. "In an ideal world, the people on the "Geek Squad' would be able to treat tech abuse with the sensitivity of a social worker." Assailants can abuse their victims through tech including spyware, also known as stalkerware, and through inappropriate use of location-tracking features in phones and other devices. They harass their former partners on social media, such as by posting private photos and posing as their victims to alienate family and friends. Abusers can also hack into email accounts and change recovery emails and phone numbers to their own, potentially devastating their victims' careers. In previous models, counselors remained anonymous, impacting their ability to build trust with survivors. Short, one-time appointments were not long enough to address clients' needs. And appointments took place at a specific time; survivors who could not leave their homes or find a safe, private place to take a call were unable to access services and couldn't reach counselors at other times. It can be frustrating and even re-traumatizing for survivors to share their stories with new consultants at each appointment, Tseng said. One of the team's larger goals is to offer survivors more peace of mind and feelings of empowerment—that they have the tools to handle future challenges. "With technology, there are so many ways to remain entangled with your abuser even after you've physically and romantically left the relationship," Tseng said. One tricky element is determining how much support is realistic. While a one-time "urgent care" visit is probably insufficient, prolonged engagement would be unsustainable for consultants and the clinic as a whole. "In several cases, consultants ended up working with clients over many appointments stretching on for weeks or months," Tseng said. As a next step, she wants to explore additional ways to evaluate ongoing security-care relations from the perspective of survivors, particularly people from marginalized communities. Dell co-created the Clinic to End Tech Abuse with Thomas Ristenpart, associate professor at Cornell Tech; both Dell and Ristenpart are also affiliated with the Cornell Ann S. Bowers College of Computing and Information Science. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 39810, 3085, 459, 42779, 9302, 13340, 315, 6485, 6067, 13, 44921, 4009, 17910, 649, 3629, 387, 15324, 555, 8071, 323, 11, 304, 2543, 11, 12912, 430, 2559, 704, 43395, 3629, 617, 264, 23222, 23692, 13, 763, 21349, 4009, 6932, 26249, 11, 4869, 11, 279, 24473, 6449, 1821, 315, 264, 2494, 753, 2361, 2949, 264, 6932, 527, 5107, 311, 75277, 323, 311, 2585, 13, 5810, 584, 30714, 459, 5603, 369, 6089, 11418, 25142, 24693, 477, 16003, 4009, 17910, 1139, 2494, 10093, 13, 1226, 19678, 264, 4101, 315, 1403, 12, 323, 2380, 33520, 50154, 11, 29531, 872, 15374, 369, 1646, 14488, 11, 323, 20461, 872, 2410, 369, 97298, 1113, 6070, 4791, 34849, 12135, 304, 3544, 13230, 24156, 14488, 13, 4802, 39810, 527, 1511, 311, 19874, 264, 7029, 2134, 315, 30116, 11, 3674, 323, 24156, 6067, 220, 16, 662, 5422, 9547, 369, 872, 2450, 527, 279, 18539, 315, 8147, 37072, 323, 55580, 6492, 7526, 11, 719, 1101, 872, 42779, 9302, 23692, 13, 1789, 3187, 11, 279, 8792, 2361, 315, 21389, 2949, 31206, 14488, 15151, 7718, 35693, 11618, 220, 17, 1174, 97617, 8599, 28066, 4097, 16003, 69125, 220, 18, 1174, 323, 3728, 12912, 11, 1778, 439, 279, 10264, 12970, 18112, 315, 1080, 33263, 2987, 14488, 11, 617, 1027, 1766, 311, 8881, 16565, 315, 35693, 7471, 220, 19, 662, 4452, 11, 279, 2539, 4754, 315, 4009, 9302, 8200, 369, 24919, 6485, 6067, 374, 7347, 555, 3892, 44901, 323, 15325, 11774, 13, 320, 16, 8, 39810, 656, 539, 617, 264, 5933, 1403, 12, 477, 2380, 33520, 320, 17, 35, 477, 220, 18, 35, 8, 40188, 13, 5884, 4009, 6932, 8617, 18065, 264, 5873, 315, 902, 13878, 315, 279, 1579, 33520, 93859, 12135, 527, 43395, 15609, 11, 323, 902, 527, 539, 13, 320, 17, 8, 763, 13882, 1511, 6932, 26249, 11, 1778, 439, 5457, 86855, 5528, 11, 420, 5873, 374, 1903, 304, 459, 18479, 323, 8617, 304, 29369, 11401, 11, 3629, 3196, 389, 44122, 11, 1826, 27961, 13186, 13, 1115, 6996, 315, 264, 2867, 5133, 1990, 24693, 4009, 17910, 323, 2494, 39825, 3727, 279, 13239, 50154, 5107, 311, 14532, 13, 320, 18, 8, 50487, 11, 1070, 527, 912, 6932, 26249, 2561, 430, 2187, 369, 21650, 14393, 264, 2728, 4009, 29683, 13, 320, 19, 8, 17830, 11, 279, 2466, 1404, 315, 1690, 1972, 31184, 14488, 374, 264, 1401, 33994, 8331, 369, 17843, 12963, 37864, 50154, 11, 6522, 311, 79538, 532, 7013, 68302, 9302, 8200, 13, 763, 420, 37618, 31966, 584, 19678, 264, 12914, 369, 24038, 4009, 50154, 430, 2686, 1521, 11774, 555, 1701, 13167, 2786, 14278, 311, 6089, 16559, 4009, 6012, 1139, 2494, 10093, 13, 2876, 1193, 649, 24693, 4009, 6012, 387, 43395, 21136, 304, 420, 11401, 11, 719, 1101, 9434, 2038, 42852, 279, 16003, 17910, 315, 7954, 477, 7902, 13, 1226, 30714, 279, 2768, 10537, 320, 30035, 13, 220, 16, 64, 7609, 1789, 264, 2728, 4009, 11, 584, 1176, 19742, 264, 743, 315, 435, 4519, 369, 1855, 315, 452, 7954, 11, 52913, 904, 24693, 477, 16003, 29683, 584, 6562, 311, 387, 43395, 27000, 304, 279, 1620, 6932, 13, 578, 13239, 320, 452, 25800, 435, 883, 4668, 6303, 374, 1243, 16489, 1139, 459, 320, 452, 25800, 452, 883, 38723, 6303, 11, 902, 17482, 439, 1988, 311, 13167, 2786, 14278, 5528, 311, 12849, 220, 17, 35, 477, 220, 18, 35, 71647, 13, 4314, 71647, 649, 3060, 387, 1511, 6089, 439, 2494, 14259, 11, 13239, 304, 4009, 50154, 584, 61937, 59234, 13, 20054, 2718, 11, 71647, 389, 220, 17, 35, 27529, 649, 387, 4726, 11838, 7119, 220, 18, 35, 1948, 12968, 477, 3980, 2601, 292, 14370, 555, 1701, 279, 4948, 13167, 369, 459, 5217, 3977, 315, 5873, 13, 578, 1948, 12968, 2472, 2289, 264, 10269, 220, 17, 35, 40188, 555, 459, 5217, 1167, 16580, 11, 323, 3980, 2601, 292, 14370, 19678, 459, 5217, 57936, 16580, 304, 65251, 71647, 13, 763, 2860, 11, 1057, 12914, 8617, 6209, 3116, 2204, 14370, 304, 1403, 323, 2380, 15696, 320, 30035, 13, 220, 16, 65, 7609, 578, 1401, 9610, 315, 1057, 12914, 11, 10209, 2225, 60112, 323, 14532, 2968, 11, 374, 1202, 5845, 311, 33435, 323, 21650, 3113, 5370, 12974, 2494, 17910, 477, 2494, 6857, 12135, 13, 1226, 11798, 4330, 10507, 430, 20461, 279, 20057, 315, 4754, 50154, 13, 320, 16, 8, 578, 3728, 6932, 5829, 4009, 54743, 369, 459, 11297, 11, 1579, 64036, 13340, 315, 93859, 4009, 27650, 13, 320, 17, 8, 578, 2254, 6932, 66159, 4528, 3717, 12912, 1990, 2494, 13840, 13, 320, 18, 8, 578, 12939, 6932, 33511, 3892, 17150, 369, 279, 8244, 12939, 315, 264, 2494, 11, 1778, 439, 8547, 11, 1990, 2136, 11, 4597, 24639, 323, 35834, 3239, 1279, 39239, 2786, 13, 320, 19, 8, 55550, 50154, 43504, 2494, 43874, 4184, 311, 9434, 2494, 4519, 13, 320, 20, 8, 58752, 50154, 2187, 369, 42438, 1990, 50154, 430, 527, 30801, 555, 3060, 24693, 477, 16003, 4519, 13, 23966, 13, 220, 16, 25, 24686, 315, 18412, 2048, 4009, 14370, 13, 264, 1174, 35907, 13, 362, 2494, 38723, 6303, 42852, 904, 4009, 4519, 311, 387, 43395, 15609, 374, 23711, 1139, 220, 17, 35, 477, 220, 18, 35, 69086, 4108, 1701, 13167, 2786, 14278, 5528, 13, 293, 1174, 328, 82149, 73764, 315, 279, 13239, 3116, 4595, 315, 4009, 2472, 25, 220, 17, 35, 323, 220, 18, 35, 4009, 59234, 6089, 1005, 279, 16674, 315, 279, 13167, 2786, 14278, 26, 1948, 12968, 323, 3980, 2601, 292, 14370, 33435, 459, 5217, 1167, 477, 57936, 3977, 11, 15947, 13, 272, 1174, 578, 4009, 4211, 1511, 369, 29531, 287, 25, 53883, 3258, 5021, 11, 41999, 5950, 323, 5801, 355, 55372, 13, 294, 1389, 282, 1174, 5008, 4009, 59234, 3196, 389, 3728, 320, 294, 7026, 2254, 320, 384, 883, 323, 12939, 320, 282, 883, 50154, 13, 578, 3728, 50154, 55099, 275, 6468, 279, 3685, 3728, 6211, 4184, 311, 93859, 2494, 27650, 13, 578, 2254, 50154, 16805, 6160, 12, 323, 69158, 635, 4009, 14726, 13, 578, 12939, 50154, 10879, 7954, 449, 4528, 24693, 12939, 13, 342, 1174, 43551, 315, 4009, 6108, 323, 22730, 51178, 6932, 6138, 369, 682, 2494, 13840, 304, 264, 41999, 5950, 320, 452, 284, 220, 16, 11, 931, 8, 369, 279, 3728, 6932, 11, 1403, 5457, 86855, 26249, 323, 2494, 17, 4175, 13, 2052, 50154, 11322, 1579, 26670, 320, 92140, 942, 753, 17839, 223, 13509, 284, 220, 15, 13, 1484, 11, 17839, 223, 2494, 17, 4175, 284, 220, 15, 13, 3534, 11, 17839, 223, 5457, 10337, 87, 284, 220, 15, 13, 3534, 11, 17839, 223, 5457, 11, 54967, 284, 220, 15, 13, 3264, 570, 72367, 63179, 2819, 315, 682, 308, 2494, 13840, 520, 4009, 6138, 294, 1174, 449, 308, 24950, 505, 308, 284, 220, 19, 520, 6138, 294, 284, 220, 1544, 320, 2000, 9309, 2494, 13840, 8, 311, 308, 284, 220, 2790, 11, 24571, 369, 294, 284, 220, 24, 13, 1254, 3267, 388, 79164, 279, 2819, 369, 279, 8187, 11, 1176, 11, 2132, 323, 4948, 41376, 3742, 323, 7340, 13, 305, 1174, 43551, 315, 279, 1620, 69916, 369, 41999, 57449, 315, 7859, 1404, 994, 33994, 279, 7147, 9042, 4401, 892, 315, 279, 26249, 311, 279, 4401, 892, 315, 279, 3728, 6932, 13, 602, 1174, 93028, 7147, 3115, 430, 279, 20081, 26249, 1397, 311, 11322, 279, 1890, 26670, 439, 279, 3728, 6932, 369, 24671, 57449, 315, 7859, 1404, 13, 8922, 828, 8797, 1404, 2217, 2057, 41468, 323, 29531, 1057, 12914, 11, 584, 1176, 9435, 433, 311, 6847, 18412, 2048, 1646, 14488, 25, 320, 16, 8, 264, 53883, 3258, 5021, 11, 320, 17, 8, 264, 41999, 5950, 323, 320, 18, 8, 264, 5801, 355, 55372, 320, 30035, 13, 220, 16, 66, 7609, 578, 53883, 3258, 5021, 374, 17057, 304, 70994, 5990, 13, 2052, 7954, 3734, 369, 1884, 304, 128257, 198, 128256, 78191, 198, 60210, 520, 56819, 17829, 617, 3549, 264, 502, 5603, 311, 10695, 32696, 315, 13018, 11737, 3009, 79788, 1821, 505, 39238, 1139, 872, 7766, 323, 3674, 3772, 311, 15765, 321, 11, 19259, 323, 13194, 1124, 13, 578, 1646, 24400, 389, 330, 22025, 35594, 315, 2512, 1359, 779, 8403, 3217, 264, 47970, 5133, 449, 832, 26202, 13312, 31760, 927, 892, 11, 4528, 311, 264, 2890, 2512, 6376, 13, 1102, 9248, 32696, 449, 50184, 889, 3619, 872, 3966, 323, 5813, 7095, 11, 6209, 32696, 5361, 5627, 311, 21676, 19570, 449, 50184, 11, 323, 52123, 10756, 872, 13312, 11737, 3925, 323, 10742, 13, 330, 35127, 828, 6373, 304, 13312, 11737, 374, 264, 6485, 3245, 430, 649, 956, 2744, 387, 364, 82, 8905, 6, 304, 264, 3254, 4376, 21925, 4034, 1359, 1071, 35266, 26132, 833, 11, 264, 74657, 5575, 323, 3063, 3229, 389, 264, 5684, 922, 279, 1646, 13, 330, 13622, 315, 279, 20414, 430, 3073, 304, 13312, 1862, 527, 7347, 555, 264, 832, 7321, 2269, 1220, 23148, 11766, 810, 53007, 311, 459, 13147, 3130, 1109, 264, 6156, 2512, 9287, 1210, 26132, 833, 690, 3118, 279, 5684, 330, 33099, 45587, 369, 14434, 8398, 304, 1357, 3509, 32413, 47732, 1, 304, 5936, 520, 279, 90315, 6969, 40, 15217, 389, 11344, 68318, 304, 46879, 15264, 304, 1561, 27008, 13, 26132, 833, 323, 1077, 18105, 520, 56819, 17829, 596, 40324, 311, 4060, 17829, 46784, 8040, 279, 502, 5603, 304, 15664, 449, 1561, 4356, 4409, 596, 22868, 596, 8410, 311, 4060, 52849, 323, 29317, 61439, 47732, 13, 11205, 3495, 27741, 389, 8223, 4038, 315, 828, 11, 439, 1664, 439, 19905, 449, 26202, 5557, 50184, 323, 11909, 389, 32487, 8427, 9349, 320, 3378, 53, 570, 330, 2028, 990, 5825, 459, 10978, 1427, 520, 2225, 279, 7720, 323, 64074, 315, 4401, 264, 26202, 5557, 31760, 2532, 369, 92598, 32696, 11, 439, 1664, 439, 279, 11774, 430, 31889, 439, 584, 990, 311, 21676, 3493, 6500, 4868, 9650, 439, 2512, 1359, 1071, 1080, 43802, 79541, 39424, 11, 22712, 14561, 520, 56819, 17829, 596, 52756, 7146, 290, 7813, 1540, 616, 10181, 13, 330, 8140, 3987, 374, 430, 1057, 11704, 690, 387, 15525, 369, 3885, 889, 527, 8173, 304, 10695, 520, 46570, 10977, 25051, 6500, 74935, 1210, 29878, 86493, 649, 3217, 1690, 7739, 315, 10026, 6108, 9349, 11, 2737, 5557, 72849, 11737, 11, 1071, 50245, 458, 70661, 11, 41443, 315, 279, 22868, 596, 8410, 311, 4060, 52849, 323, 29317, 61439, 47732, 13, 330, 91641, 616, 17829, 596, 64955, 2068, 539, 1193, 8779, 32696, 25051, 5557, 11737, 719, 374, 1101, 3318, 311, 2731, 3619, 1268, 1274, 62851, 5557, 779, 430, 584, 649, 1893, 2731, 37424, 369, 32696, 1359, 70661, 1071, 13, 330, 1687, 527, 12691, 315, 279, 9200, 3560, 1057, 74229, 8427, 56819, 17829, 11335, 304, 18899, 279, 6439, 315, 32696, 1210, 17829, 11737, 3629, 6866, 2949, 264, 8294, 3566, 315, 11682, 11, 26132, 833, 1071, 13, 330, 644, 459, 10728, 1917, 11, 279, 1274, 389, 279, 330, 9688, 1247, 35807, 6, 1053, 387, 3025, 311, 4322, 13312, 11737, 449, 279, 27541, 315, 264, 3674, 12128, 1210, 2755, 607, 1821, 649, 11737, 872, 12697, 1555, 13312, 2737, 21930, 1698, 11, 1101, 3967, 439, 357, 37908, 1698, 11, 323, 1555, 33781, 1005, 315, 3813, 94949, 4519, 304, 18084, 323, 1023, 7766, 13, 2435, 19259, 872, 4846, 8717, 389, 3674, 3772, 11, 1778, 439, 555, 17437, 879, 7397, 323, 53004, 439, 872, 12697, 311, 20167, 349, 3070, 323, 4885, 13, 3765, 4312, 649, 1101, 17524, 1139, 2613, 9815, 323, 2349, 13654, 14633, 323, 4641, 5219, 311, 872, 1866, 11, 13893, 33318, 872, 12697, 6, 31133, 13, 763, 3766, 4211, 11, 86347, 14958, 22939, 11, 74055, 872, 5845, 311, 1977, 7095, 449, 32696, 13, 10928, 11, 832, 7394, 37256, 1051, 539, 1317, 3403, 311, 2686, 8403, 6, 3966, 13, 1628, 37256, 3952, 2035, 520, 264, 3230, 892, 26, 32696, 889, 1436, 539, 5387, 872, 10632, 477, 1505, 264, 6220, 11, 879, 2035, 311, 1935, 264, 1650, 1051, 12153, 311, 2680, 3600, 323, 7846, 956, 5662, 86347, 520, 1023, 3115, 13, 1102, 649, 387, 35711, 323, 1524, 312, 80367, 46313, 4954, 369, 32696, 311, 4430, 872, 7493, 449, 502, 50184, 520, 1855, 18101, 11, 26132, 833, 1071, 13, 3861, 315, 279, 2128, 596, 8294, 9021, 374, 311, 3085, 32696, 810, 9096, 315, 4059, 323, 16024, 315, 74477, 41128, 814, 617, 279, 7526, 311, 3790, 3938, 11774, 13, 330, 2409, 5557, 11, 1070, 527, 779, 1690, 5627, 311, 7293, 1218, 40040, 449, 701, 671, 882, 1524, 1306, 499, 3077, 22655, 323, 68567, 2740, 2163, 279, 5133, 1359, 26132, 833, 1071, 13, 3861, 34553, 2449, 374, 26679, 1268, 1790, 1862, 374, 26569, 13, 6104, 264, 832, 7394, 330, 86153, 2512, 1, 4034, 374, 4762, 39413, 11, 44387, 20392, 1053, 387, 98609, 369, 50184, 323, 279, 28913, 439, 264, 4459, 13, 330, 644, 3892, 5157, 11, 50184, 9670, 709, 3318, 449, 8403, 927, 1690, 37256, 42949, 389, 369, 5672, 477, 4038, 1359, 26132, 833, 1071, 13, 1666, 264, 1828, 3094, 11, 1364, 6944, 311, 13488, 5217, 5627, 311, 15806, 14529, 4868, 41206, 4398, 505, 279, 13356, 315, 32696, 11, 8104, 1274, 505, 76820, 10977, 13, 39424, 1080, 72057, 279, 40324, 311, 4060, 17829, 46784, 449, 11355, 432, 38222, 4581, 11, 22712, 14561, 520, 56819, 17829, 26, 2225, 39424, 323, 432, 38222, 4581, 527, 1101, 37506, 449, 279, 56819, 9489, 328, 13, 426, 16345, 9304, 315, 46879, 323, 8245, 10170, 13, 220, 128257, 198 ]

2,188

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract DNA replication and repair enzyme Flap Endonuclease 1 (FEN1) is vital for genome integrity, and FEN1 mutations arise in multiple cancers. FEN1 precisely cleaves single-stranded (ss) 5′-flaps one nucleotide into duplex (ds) DNA. Yet, how FEN1 selects for but does not incise the ss 5′-flap was enigmatic. Here we combine crystallographic, biochemical and genetic analyses to show that two dsDNA binding sites set the 5′polarity and to reveal unexpected control of the DNA phosphodiester backbone by electrostatic interactions. Via ‘phosphate steering’, basic residues energetically steer an inverted ss 5′-flap through a gateway over FEN1’s active site and shift dsDNA for catalysis. Mutations of these residues cause an 18,000-fold reduction in catalytic rate in vitro and large-scale trinucleotide (GAA) n repeat expansions in vivo , implying failed phosphate-steering promotes an unanticipated lagging-strand template-switch mechanism during replication. Thus, phosphate steering is an unappreciated FEN1 function that enforces 5′-flap specificity and catalysis, preventing genomic instability. Introduction The structure-specific nuclease, flap endonuclease-1 (FEN1) plays a vital role in maintaining genome integrity by precisely processing intermediates of Okazaki fragment maturation, long-patch excision repair, telomere maintenance, and stalled replication forks. During DNA replication and repair, strand displacement synthesis produces single-stranded (ss) 5′-flaps, at junctions in double-stranded (ds) DNA. During replication in humans, FEN1 removes ∼ 50 million Okazaki fragment 5′-flaps with remarkable efficiency and selectivity to maintain genome integrity 1 , 2 , 3 . Consequently, FEN1 deletion is embryonically lethal in mammals 4 , and functional mutations can lead to cancer 5 . FEN1 also safeguards against DNA instability responsible for trinucleotide repeat expansion diseases 6 . As FEN1 is overexpressed in many cancer types 7 , 8 , it is an oncological therapy target 9 , 10 . Precise FEN1 incision site selection is central to DNA replication fidelity and repair. FEN1 preferentially binds to double flap substrates with a one nt 3′-flap and any length of 5′-flap, including zero. It catalyses a single hydrolytic incision one nucleotide (nt) into dsDNA ( Fig. 1a ) to yield nicked DNA ready for direct ligation 11 , 12 . Thus, FEN1 acts on dsDNA as both an endonuclease (with 5′-flap) and an exonuclease (without 5′-flap). Recent single molecule experiments show that FEN1 binds both ideal and non-ideal substrates but decisively incises only its true substrate 13 . In contrast to homologs in bacteriophage 14 , 15 , 16 and some eubacteria 17 , eukaryotic FEN1s do not hydrolyse within 5′-flap ssDNA. Figure 1: Specificity and inverted threading of ss5′-flap in hFEN1 D86N substrate structure. ( a ) Schematic FEN1 incision on an optimal double-flap substrate, incising 1 nt into dsDNA to ensure a ligatable product. ( b ) Proposed models for ssDNA selection. ( c ) Top view of hFEN1-D86N crystal structure showing extensive interaction to dsDNA arms of 5’ flap substrate. The 5’-flap substrate is composed of three strands; the 5′-flap strand (orange), the template strand (brown), and the 3′-flap strand (pink). Functionally critical regions in FEN1 include the gateway (blue) and the cap (violet) for selecting substrates with ss-5′-flaps, the hydrophobic wedge between the 3′-flap binding site and the gateway/cap (dark green), the K + ion and H2TH (purple) that interacts with the downstream DNA, the beta pin (grey) that locks in the DNA at the bend. Relative DNA orientation shown in schematic on lower right. ( d ) Front and side views of hFEN1-D86N crystal structure showing helical gateway and cap architecture position positively-charged residues to steer ss 5′-flaps through a protecting gateway in an inverted orientation across the active site. Relative DNA orientation is shown in schematic. The inverted 5′-flap ssDNA is threaded between gateway helices (blue) and under the helical cap (violet). The inverted threading reveals charged interactions to basic sidechains in the cap and van der Waals interactions to ssDNA. See also Supplementary Figs 1–3 ; Table 1 , and Supplementary Movies 1 and 2 . Full size image However, key features of FEN1 substrate selection remain unclear. FEN1 must efficiently remove 5′-flaps at discontinuous ss-dsDNA junctions yet avoid genome-threatening action on continuous ss–ds junctions, such as ss gaps or Holliday junctions. Paradoxically, other FEN1 5′-nuclease superfamily members 3 are specific for continuous DNA junctions: namely, ERCC5/XPG (nucleotide excision repair), which acts on continuous ss-ds bubble-like structures; and GEN1 (Holliday junction resolution), which processes four-way junctions. Structures determined with DNA of eukaryotic superfamily members lack ss-ds junction substrate with 5′-ssDNA or the attacking water molecule leaving cardinal questions unanswered 18 , 19 , 20 , 21 , 22 . For example, structures of FEN1 and Exo1 go from substrate duplex DNA with the scissile phosphodiester far from the catalytic metals to an unpaired terminal nt in the product; is the unpairing occurring before or after incision? Models of FEN1 specificity must address how ss–ds junctions are recognized and how 5′-flaps, as opposed to continuous ssDNA are recognized. There are threading and kinking models. To exclude continuous DNAs, 5′-flaps may thread through a ‘tunnel’ 21 , 23 , 24 , 25 formed by two superfamily-conserved helices flanking the active site, known as the ‘helical gateway,’ topped by a ‘helical cap’ ( Fig. 1b ). Due to cap and gateway disorder in DNA-free FEN1, they are thought disordered during threading and to undergo a disorder-to-order transition on 3′-flap binding 21 , 24 , 26 . In this threading model, however, ssDNA passes through a tunnel without an energy source and directly over the active site, risking non-specific incision. These issues prompted an alternative clamping model where the ss flap kinks away from the active site 11 , 20 ( Fig. 1b ). Whereas these models explain selection against continuous DNA junctions, FEN1 exonuclease activity does not require a 5′-flap. Furthermore, how FEN1 prevents off target incisions and moves the dsDNA junction onto the metal ions are not explained by these models. Here crystallographic analyses uncover an unprecedented electrostatic steering of an inverted 5′-flap through the human FEN1 (hFEN1) helical gateway. Gateway and cap positively-charged side chains are positioned to ‘steer’ the", "role": "user" }, { "content": "The actions of a protein used for DNA replication and repair are guided by electrostatic forces known as phosphate steering, a finding that not only reveals key details about a vital process in healthy cells, but provides new directions for cancer treatment research. The findings, published this week in the journal Nature Communications, focus on an enzyme called flap endonuclease 1, or FEN1. Using a combination of crystallographic, biochemical, and genetic analyses, researchers at the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) showed that phosphate steering kept FEN1 in line and working properly. \"FEN1, like many DNA replication and repair proteins, have paradoxical roles relevant to cancer,\" said study lead author Susan Tsutakawa, a biochemist at Berkeley Lab's Molecular Biophysics and Integrated Bioimaging Division. \"A mistake by FEN1 could damage the DNA, leading to the development of cancer. On the other side, many cancers need replication and repair proteins to survive and to repair DNA damaged from cancer treatments. New evidence shows that phosphate steering helps ensure that FEN1 behaves as it should to prevent genome instability.\" During the process of replication, double-stranded DNA unzips to expose the nucleotides along its two separate strands. In that process, flaps of single-stranded DNA are created. The job of FEN1 is to remove those flaps by positioning metal catalysts so that they can break down the phosphodiester bonds that make up the backbone of nucleic acid strands. This cleavage action occurs in the duplex DNA near the junction with the single-stranded flap. Flaps that remain uncleaved can lead to toxic DNA damage that either kill the cell or cause extensive mutations. For example, trinucleotide repeat expansions, a mutation associated with disorders such as Huntington's disease and fragile X syndrome, are characterized by the failure of FEN1 to cut off the excess strand. The schematic at top illustrates how inversion of the DNA flap keeps the phosphodiester bonds away from the metal catalysts that can inadvertently cut the strand. The bottom view shows a single-stranded DNA flap passing through a small opening in the FEN1 protein, guided by electrostatic forces in the basic region. Credit: Susan Tsutakawa/Berkeley Lab \"What had been unclear before our study was how FEN1 was able to identify its exact target while preventing the indiscriminate cutting of single-stranded flaps,\" said Tsutakawa. \"There must be a way for this protein to not shred similar targets, such as single-stranded RNA or DNA. Getting that right is critical.\" Tsutakawa worked with corresponding author John Tainer, Berkeley Lab research scientist and a professor at the University of Texas, at the Advanced Light Source, a DOE Office of Science User Facility that produces extremely bright X-ray beams suitable for solving the atomic structure of protein and DNA complexes. Using X-ray crystallography, they were able to get a molecular-level view of the FEN1 protein structure. They determined that the single-stranded flap threaded through a small hole formed by the FEN1 protein. The size of the hole serves as an extra check that FEN1 is binding the correct target. However, they surprisingly found that the single-stranded flap is inverted such that the more vulnerable part of the DNA, the phosphodiester backbone, faces away from the metal catalysts, thereby reducing the chance of inadvertent incision. The inversion is guided by a positively charged region in FEN1 that stabilizes the upside-down position and steers the negatively charged phosphodiester of the single-stranded DNA through the FEN1 tunnel. \"These metals are like scissors and will cut any DNA near them,\" said Tsutakawa. \"The positively charged region in FEN1 acts like a magnet, pulling the flap away from these metals and protecting the flap from being cut. This is how FEN1 avoids cutting single-stranded DNA or RNA.\" \"This phosphate steering is a previously unknown mechanism for controlling the specificity of FEN1,\" she added. \"Cancer cells need FEN proteins to replicate, so understanding how FEN1 works could help provide targets for research into treatments down the line.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract DNA replication and repair enzyme Flap Endonuclease 1 (FEN1) is vital for genome integrity, and FEN1 mutations arise in multiple cancers. FEN1 precisely cleaves single-stranded (ss) 5′-flaps one nucleotide into duplex (ds) DNA. Yet, how FEN1 selects for but does not incise the ss 5′-flap was enigmatic. Here we combine crystallographic, biochemical and genetic analyses to show that two dsDNA binding sites set the 5′polarity and to reveal unexpected control of the DNA phosphodiester backbone by electrostatic interactions. Via ‘phosphate steering’, basic residues energetically steer an inverted ss 5′-flap through a gateway over FEN1’s active site and shift dsDNA for catalysis. Mutations of these residues cause an 18,000-fold reduction in catalytic rate in vitro and large-scale trinucleotide (GAA) n repeat expansions in vivo , implying failed phosphate-steering promotes an unanticipated lagging-strand template-switch mechanism during replication. Thus, phosphate steering is an unappreciated FEN1 function that enforces 5′-flap specificity and catalysis, preventing genomic instability. Introduction The structure-specific nuclease, flap endonuclease-1 (FEN1) plays a vital role in maintaining genome integrity by precisely processing intermediates of Okazaki fragment maturation, long-patch excision repair, telomere maintenance, and stalled replication forks. During DNA replication and repair, strand displacement synthesis produces single-stranded (ss) 5′-flaps, at junctions in double-stranded (ds) DNA. During replication in humans, FEN1 removes ∼ 50 million Okazaki fragment 5′-flaps with remarkable efficiency and selectivity to maintain genome integrity 1 , 2 , 3 . Consequently, FEN1 deletion is embryonically lethal in mammals 4 , and functional mutations can lead to cancer 5 . FEN1 also safeguards against DNA instability responsible for trinucleotide repeat expansion diseases 6 . As FEN1 is overexpressed in many cancer types 7 , 8 , it is an oncological therapy target 9 , 10 . Precise FEN1 incision site selection is central to DNA replication fidelity and repair. FEN1 preferentially binds to double flap substrates with a one nt 3′-flap and any length of 5′-flap, including zero. It catalyses a single hydrolytic incision one nucleotide (nt) into dsDNA ( Fig. 1a ) to yield nicked DNA ready for direct ligation 11 , 12 . Thus, FEN1 acts on dsDNA as both an endonuclease (with 5′-flap) and an exonuclease (without 5′-flap). Recent single molecule experiments show that FEN1 binds both ideal and non-ideal substrates but decisively incises only its true substrate 13 . In contrast to homologs in bacteriophage 14 , 15 , 16 and some eubacteria 17 , eukaryotic FEN1s do not hydrolyse within 5′-flap ssDNA. Figure 1: Specificity and inverted threading of ss5′-flap in hFEN1 D86N substrate structure. ( a ) Schematic FEN1 incision on an optimal double-flap substrate, incising 1 nt into dsDNA to ensure a ligatable product. ( b ) Proposed models for ssDNA selection. ( c ) Top view of hFEN1-D86N crystal structure showing extensive interaction to dsDNA arms of 5’ flap substrate. The 5’-flap substrate is composed of three strands; the 5′-flap strand (orange), the template strand (brown), and the 3′-flap strand (pink). Functionally critical regions in FEN1 include the gateway (blue) and the cap (violet) for selecting substrates with ss-5′-flaps, the hydrophobic wedge between the 3′-flap binding site and the gateway/cap (dark green), the K + ion and H2TH (purple) that interacts with the downstream DNA, the beta pin (grey) that locks in the DNA at the bend. Relative DNA orientation shown in schematic on lower right. ( d ) Front and side views of hFEN1-D86N crystal structure showing helical gateway and cap architecture position positively-charged residues to steer ss 5′-flaps through a protecting gateway in an inverted orientation across the active site. Relative DNA orientation is shown in schematic. The inverted 5′-flap ssDNA is threaded between gateway helices (blue) and under the helical cap (violet). The inverted threading reveals charged interactions to basic sidechains in the cap and van der Waals interactions to ssDNA. See also Supplementary Figs 1–3 ; Table 1 , and Supplementary Movies 1 and 2 . Full size image However, key features of FEN1 substrate selection remain unclear. FEN1 must efficiently remove 5′-flaps at discontinuous ss-dsDNA junctions yet avoid genome-threatening action on continuous ss–ds junctions, such as ss gaps or Holliday junctions. Paradoxically, other FEN1 5′-nuclease superfamily members 3 are specific for continuous DNA junctions: namely, ERCC5/XPG (nucleotide excision repair), which acts on continuous ss-ds bubble-like structures; and GEN1 (Holliday junction resolution), which processes four-way junctions. Structures determined with DNA of eukaryotic superfamily members lack ss-ds junction substrate with 5′-ssDNA or the attacking water molecule leaving cardinal questions unanswered 18 , 19 , 20 , 21 , 22 . For example, structures of FEN1 and Exo1 go from substrate duplex DNA with the scissile phosphodiester far from the catalytic metals to an unpaired terminal nt in the product; is the unpairing occurring before or after incision? Models of FEN1 specificity must address how ss–ds junctions are recognized and how 5′-flaps, as opposed to continuous ssDNA are recognized. There are threading and kinking models. To exclude continuous DNAs, 5′-flaps may thread through a ‘tunnel’ 21 , 23 , 24 , 25 formed by two superfamily-conserved helices flanking the active site, known as the ‘helical gateway,’ topped by a ‘helical cap’ ( Fig. 1b ). Due to cap and gateway disorder in DNA-free FEN1, they are thought disordered during threading and to undergo a disorder-to-order transition on 3′-flap binding 21 , 24 , 26 . In this threading model, however, ssDNA passes through a tunnel without an energy source and directly over the active site, risking non-specific incision. These issues prompted an alternative clamping model where the ss flap kinks away from the active site 11 , 20 ( Fig. 1b ). Whereas these models explain selection against continuous DNA junctions, FEN1 exonuclease activity does not require a 5′-flap. Furthermore, how FEN1 prevents off target incisions and moves the dsDNA junction onto the metal ions are not explained by these models. Here crystallographic analyses uncover an unprecedented electrostatic steering of an inverted 5′-flap through the human FEN1 (hFEN1) helical gateway. Gateway and cap positively-charged side chains are positioned to ‘steer’ the<|im_end|> <|im_start|>assistant The actions of a protein used for DNA replication and repair are guided by electrostatic forces known as phosphate steering, a finding that not only reveals key details about a vital process in healthy cells, but provides new directions for cancer treatment research. The findings, published this week in the journal Nature Communications, focus on an enzyme called flap endonuclease 1, or FEN1. Using a combination of crystallographic, biochemical, and genetic analyses, researchers at the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) showed that phosphate steering kept FEN1 in line and working properly. "FEN1, like many DNA replication and repair proteins, have paradoxical roles relevant to cancer," said study lead author Susan Tsutakawa, a biochemist at Berkeley Lab's Molecular Biophysics and Integrated Bioimaging Division. "A mistake by FEN1 could damage the DNA, leading to the development of cancer. On the other side, many cancers need replication and repair proteins to survive and to repair DNA damaged from cancer treatments. New evidence shows that phosphate steering helps ensure that FEN1 behaves as it should to prevent genome instability." During the process of replication, double-stranded DNA unzips to expose the nucleotides along its two separate strands. In that process, flaps of single-stranded DNA are created. The job of FEN1 is to remove those flaps by positioning metal catalysts so that they can break down the phosphodiester bonds that make up the backbone of nucleic acid strands. This cleavage action occurs in the duplex DNA near the junction with the single-stranded flap. Flaps that remain uncleaved can lead to toxic DNA damage that either kill the cell or cause extensive mutations. For example, trinucleotide repeat expansions, a mutation associated with disorders such as Huntington's disease and fragile X syndrome, are characterized by the failure of FEN1 to cut off the excess strand. The schematic at top illustrates how inversion of the DNA flap keeps the phosphodiester bonds away from the metal catalysts that can inadvertently cut the strand. The bottom view shows a single-stranded DNA flap passing through a small opening in the FEN1 protein, guided by electrostatic forces in the basic region. Credit: Susan Tsutakawa/Berkeley Lab "What had been unclear before our study was how FEN1 was able to identify its exact target while preventing the indiscriminate cutting of single-stranded flaps," said Tsutakawa. "There must be a way for this protein to not shred similar targets, such as single-stranded RNA or DNA. Getting that right is critical." Tsutakawa worked with corresponding author John Tainer, Berkeley Lab research scientist and a professor at the University of Texas, at the Advanced Light Source, a DOE Office of Science User Facility that produces extremely bright X-ray beams suitable for solving the atomic structure of protein and DNA complexes. Using X-ray crystallography, they were able to get a molecular-level view of the FEN1 protein structure. They determined that the single-stranded flap threaded through a small hole formed by the FEN1 protein. The size of the hole serves as an extra check that FEN1 is binding the correct target. However, they surprisingly found that the single-stranded flap is inverted such that the more vulnerable part of the DNA, the phosphodiester backbone, faces away from the metal catalysts, thereby reducing the chance of inadvertent incision. The inversion is guided by a positively charged region in FEN1 that stabilizes the upside-down position and steers the negatively charged phosphodiester of the single-stranded DNA through the FEN1 tunnel. "These metals are like scissors and will cut any DNA near them," said Tsutakawa. "The positively charged region in FEN1 acts like a magnet, pulling the flap away from these metals and protecting the flap from being cut. This is how FEN1 avoids cutting single-stranded DNA or RNA." "This phosphate steering is a previously unknown mechanism for controlling the specificity of FEN1," she added. "Cancer cells need FEN proteins to replicate, so understanding how FEN1 works could help provide targets for research into treatments down the line." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 15922, 48891, 323, 13023, 49242, 3061, 391, 4060, 263, 1791, 1655, 220, 16, 320, 37, 965, 16, 8, 374, 16595, 369, 33869, 17025, 11, 323, 435, 965, 16, 34684, 31889, 304, 5361, 51423, 13, 435, 965, 16, 24559, 11551, 4798, 3254, 42728, 6601, 320, 784, 8, 220, 20, 39615, 12, 1517, 2690, 832, 31484, 69044, 1139, 81268, 320, 5469, 8, 15922, 13, 14968, 11, 1268, 435, 965, 16, 50243, 369, 719, 1587, 539, 3709, 1082, 279, 11107, 220, 20, 39615, 12, 1517, 391, 574, 665, 99830, 13, 5810, 584, 16343, 26110, 848, 79173, 11, 93532, 323, 19465, 29060, 311, 1501, 430, 1403, 11729, 56420, 11212, 6732, 743, 279, 220, 20, 39615, 79, 73627, 323, 311, 16805, 16907, 2585, 315, 279, 15922, 33088, 31559, 5302, 56527, 555, 25396, 2020, 22639, 13, 45899, 3451, 764, 93473, 33277, 20182, 6913, 71783, 38556, 456, 2740, 49715, 459, 47801, 11107, 220, 20, 39615, 12, 1517, 391, 1555, 264, 29895, 927, 435, 965, 16, 753, 4642, 2816, 323, 6541, 11729, 56420, 369, 34454, 4548, 13, 32328, 811, 315, 1521, 71783, 5353, 459, 220, 972, 11, 931, 24325, 14278, 304, 34454, 70504, 4478, 304, 55004, 323, 3544, 13230, 490, 258, 22935, 69044, 320, 38, 6157, 8, 308, 13454, 78588, 304, 41294, 1174, 73967, 4745, 79106, 97426, 4776, 39990, 459, 653, 93878, 22171, 3252, 42728, 438, 3896, 48296, 17383, 2391, 48891, 13, 14636, 11, 79106, 33277, 374, 459, 653, 680, 2827, 10234, 435, 965, 16, 734, 430, 665, 49896, 220, 20, 39615, 12, 1517, 391, 76041, 323, 34454, 4548, 11, 27252, 81064, 56399, 13, 29438, 578, 6070, 19440, 308, 1791, 1655, 11, 67533, 842, 263, 1791, 1655, 12, 16, 320, 37, 965, 16, 8, 11335, 264, 16595, 3560, 304, 20958, 33869, 17025, 555, 24559, 8863, 55275, 988, 315, 7777, 1394, 14966, 12569, 5634, 2060, 11, 1317, 2320, 759, 3521, 1854, 13023, 11, 19227, 316, 486, 13709, 11, 323, 68941, 48891, 74674, 13, 12220, 15922, 48891, 323, 13023, 11, 42589, 44153, 39975, 19159, 3254, 42728, 6601, 320, 784, 8, 220, 20, 39615, 12, 1517, 2690, 11, 520, 49341, 82, 304, 2033, 42728, 6601, 320, 5469, 8, 15922, 13, 12220, 48891, 304, 12966, 11, 435, 965, 16, 29260, 12264, 120, 220, 1135, 3610, 7777, 1394, 14966, 12569, 220, 20, 39615, 12, 1517, 2690, 449, 23649, 15374, 323, 3373, 1968, 311, 10519, 33869, 17025, 220, 16, 1174, 220, 17, 1174, 220, 18, 662, 53123, 11, 435, 965, 16, 37166, 374, 44481, 263, 2740, 45089, 304, 56669, 220, 19, 1174, 323, 16003, 34684, 649, 3063, 311, 9572, 220, 20, 662, 435, 965, 16, 1101, 78020, 2403, 15922, 56399, 8647, 369, 490, 258, 22935, 69044, 13454, 14800, 19338, 220, 21, 662, 1666, 435, 965, 16, 374, 927, 14107, 291, 304, 1690, 9572, 4595, 220, 22, 1174, 220, 23, 1174, 433, 374, 459, 78970, 5848, 15419, 2218, 220, 24, 1174, 220, 605, 662, 42770, 1082, 435, 965, 16, 3709, 1854, 2816, 6727, 374, 8792, 311, 15922, 48891, 83604, 323, 13023, 13, 435, 965, 16, 10932, 31668, 58585, 311, 2033, 67533, 16146, 988, 449, 264, 832, 32512, 220, 18, 39615, 12, 1517, 391, 323, 904, 3160, 315, 220, 20, 39615, 12, 1517, 391, 11, 2737, 7315, 13, 1102, 34454, 73279, 264, 3254, 17055, 398, 29150, 3709, 1854, 832, 31484, 69044, 320, 406, 8, 1139, 11729, 56420, 320, 23966, 13, 220, 16, 64, 883, 311, 7692, 16370, 291, 15922, 5644, 369, 2167, 326, 18413, 220, 806, 1174, 220, 717, 662, 14636, 11, 435, 965, 16, 14385, 389, 11729, 56420, 439, 2225, 459, 842, 263, 1791, 1655, 320, 4291, 220, 20, 39615, 12, 1517, 391, 8, 323, 459, 99844, 1791, 1655, 320, 30096, 220, 20, 39615, 12, 1517, 391, 570, 35390, 3254, 43030, 21896, 1501, 430, 435, 965, 16, 58585, 2225, 10728, 323, 2536, 12, 64053, 16146, 988, 719, 34122, 3210, 3709, 5014, 1193, 1202, 837, 54057, 220, 1032, 662, 763, 13168, 311, 5105, 1640, 82, 304, 17854, 72, 99054, 220, 975, 1174, 220, 868, 1174, 220, 845, 323, 1063, 384, 392, 78852, 220, 1114, 1174, 384, 3178, 661, 14546, 435, 965, 16, 82, 656, 539, 17055, 398, 325, 2949, 220, 20, 39615, 12, 1517, 391, 11107, 56420, 13, 19575, 220, 16, 25, 29362, 488, 323, 47801, 31259, 315, 11107, 20, 39615, 12, 1517, 391, 304, 305, 37, 965, 16, 423, 4218, 45, 54057, 6070, 13, 320, 264, 883, 328, 82149, 435, 965, 16, 3709, 1854, 389, 459, 23669, 2033, 12556, 391, 54057, 11, 3709, 3876, 220, 16, 32512, 1139, 11729, 56420, 311, 6106, 264, 29413, 15436, 2027, 13, 320, 293, 883, 99983, 4211, 369, 11107, 56420, 6727, 13, 320, 272, 883, 7054, 1684, 315, 305, 37, 965, 16, 9607, 4218, 45, 26110, 6070, 9204, 16781, 16628, 311, 11729, 56420, 11977, 315, 220, 20, 529, 67533, 54057, 13, 578, 220, 20, 529, 12, 1517, 391, 54057, 374, 24306, 315, 2380, 69864, 26, 279, 220, 20, 39615, 12, 1517, 391, 42589, 320, 35264, 705, 279, 3896, 42589, 320, 65561, 705, 323, 279, 220, 18, 39615, 12, 1517, 391, 42589, 320, 64349, 570, 5830, 750, 9200, 13918, 304, 435, 965, 16, 2997, 279, 29895, 320, 12481, 8, 323, 279, 2107, 320, 85, 32012, 8, 369, 27397, 16146, 988, 449, 11107, 12, 20, 39615, 12, 1517, 2690, 11, 279, 17055, 764, 31906, 64785, 1990, 279, 220, 18, 39615, 12, 1517, 391, 11212, 2816, 323, 279, 29895, 2971, 391, 320, 23449, 6307, 705, 279, 735, 489, 28772, 323, 473, 17, 3701, 320, 57607, 8, 430, 84261, 449, 279, 52452, 15922, 11, 279, 13746, 9160, 320, 35671, 8, 430, 32776, 304, 279, 15922, 520, 279, 37920, 13, 40502, 15922, 17140, 6982, 304, 68144, 389, 4827, 1314, 13, 320, 294, 883, 15248, 323, 3185, 6325, 315, 305, 37, 965, 16, 9607, 4218, 45, 26110, 6070, 9204, 11591, 950, 29895, 323, 2107, 18112, 2361, 40646, 11843, 93349, 71783, 311, 49715, 11107, 220, 20, 39615, 12, 1517, 2690, 1555, 264, 22973, 29895, 304, 459, 47801, 17140, 4028, 279, 4642, 2816, 13, 40502, 15922, 17140, 374, 6982, 304, 68144, 13, 578, 47801, 220, 20, 39615, 12, 1517, 391, 11107, 56420, 374, 67887, 1990, 29895, 11591, 1238, 320, 12481, 8, 323, 1234, 279, 11591, 950, 2107, 320, 85, 32012, 570, 578, 47801, 31259, 21667, 11684, 22639, 311, 6913, 3185, 59458, 304, 279, 2107, 323, 5355, 2761, 29614, 1147, 22639, 311, 11107, 56420, 13, 3580, 1101, 99371, 435, 14801, 220, 16, 4235, 18, 2652, 6771, 220, 16, 1174, 323, 99371, 27019, 220, 16, 323, 220, 17, 662, 8797, 1404, 2217, 4452, 11, 1401, 4519, 315, 435, 965, 16, 54057, 6727, 7293, 25420, 13, 435, 965, 16, 2011, 30820, 4148, 220, 20, 39615, 12, 1517, 2690, 520, 45980, 9373, 11107, 1773, 82, 56420, 49341, 82, 3686, 5766, 33869, 62999, 1957, 389, 19815, 11107, 4235, 5469, 49341, 82, 11, 1778, 439, 11107, 33251, 477, 25518, 49978, 49341, 82, 13, 4366, 40197, 2740, 11, 1023, 435, 965, 16, 220, 20, 39615, 12, 77, 1791, 1655, 2307, 19521, 3697, 220, 18, 527, 3230, 369, 19815, 15922, 49341, 82, 25, 32125, 11, 27590, 3791, 20, 34079, 11637, 320, 77, 22935, 69044, 3521, 1854, 13023, 705, 902, 14385, 389, 19815, 11107, 1773, 82, 24529, 12970, 14726, 26, 323, 43774, 16, 320, 39, 980, 49978, 49341, 11175, 705, 902, 11618, 3116, 27896, 49341, 82, 13, 71150, 11075, 449, 15922, 315, 384, 3178, 661, 14546, 2307, 19521, 3697, 6996, 11107, 1773, 82, 49341, 54057, 449, 220, 20, 39615, 12, 784, 56420, 477, 279, 23664, 3090, 43030, 9564, 56980, 4860, 76547, 220, 972, 1174, 220, 777, 1174, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 662, 1789, 3187, 11, 14726, 315, 435, 965, 16, 323, 1398, 78, 16, 733, 505, 54057, 81268, 15922, 449, 279, 1156, 1056, 458, 33088, 31559, 5302, 3117, 505, 279, 34454, 70504, 37182, 311, 459, 653, 77267, 15372, 32512, 304, 279, 2027, 26, 374, 279, 653, 12959, 287, 31965, 1603, 477, 1306, 3709, 1854, 30, 27972, 315, 435, 965, 16, 76041, 2011, 2686, 1268, 11107, 4235, 5469, 49341, 82, 527, 15324, 323, 1268, 220, 20, 39615, 12, 1517, 2690, 11, 439, 16475, 311, 19815, 11107, 56420, 527, 15324, 13, 2684, 527, 31259, 323, 597, 16113, 4211, 13, 2057, 22429, 19815, 61756, 2170, 11, 220, 20, 39615, 12, 1517, 2690, 1253, 4617, 1555, 264, 3451, 83, 41392, 529, 220, 1691, 1174, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 14454, 555, 1403, 2307, 19521, 69604, 2841, 11591, 1238, 1344, 33434, 279, 4642, 2816, 11, 3967, 439, 279, 3451, 50222, 950, 29895, 23189, 40901, 555, 264, 3451, 50222, 950, 2107, 529, 320, 23966, 13, 220, 16, 65, 7609, 24586, 311, 2107, 323, 29895, 19823, 304, 15922, 12862, 435, 965, 16, 11, 814, 527, 3463, 834, 10767, 2391, 31259, 323, 311, 37771, 264, 19823, 4791, 24747, 9320, 389, 220, 18, 39615, 12, 1517, 391, 11212, 220, 1691, 1174, 220, 1187, 1174, 220, 1627, 662, 763, 420, 31259, 1646, 11, 4869, 11, 11107, 56420, 16609, 1555, 264, 26711, 2085, 459, 4907, 2592, 323, 6089, 927, 279, 4642, 2816, 11, 86022, 2536, 19440, 3709, 1854, 13, 4314, 4819, 29746, 459, 10778, 1206, 31557, 1646, 1405, 279, 11107, 67533, 597, 15872, 3201, 505, 279, 4642, 2816, 220, 806, 1174, 220, 508, 320, 23966, 13, 220, 16, 65, 7609, 61695, 1521, 4211, 10552, 6727, 2403, 19815, 15922, 49341, 82, 11, 435, 965, 16, 99844, 1791, 1655, 5820, 1587, 539, 1397, 264, 220, 20, 39615, 12, 1517, 391, 13, 24296, 11, 1268, 435, 965, 16, 29034, 1022, 2218, 3709, 6948, 323, 11031, 279, 11729, 56420, 49341, 8800, 279, 9501, 65125, 527, 539, 11497, 555, 1521, 4211, 13, 5810, 26110, 848, 79173, 29060, 45063, 459, 31069, 25396, 2020, 33277, 315, 459, 47801, 220, 20, 39615, 12, 1517, 391, 1555, 279, 3823, 435, 965, 16, 320, 71, 37, 965, 16, 8, 11591, 950, 29895, 13, 40478, 323, 2107, 40646, 11843, 93349, 3185, 27271, 527, 35328, 311, 3451, 5455, 261, 529, 279, 128257, 198, 128256, 78191, 198, 791, 6299, 315, 264, 13128, 1511, 369, 15922, 48891, 323, 13023, 527, 33687, 555, 25396, 2020, 8603, 3967, 439, 79106, 33277, 11, 264, 9455, 430, 539, 1193, 21667, 1401, 3649, 922, 264, 16595, 1920, 304, 9498, 7917, 11, 719, 5825, 502, 18445, 369, 9572, 6514, 3495, 13, 578, 14955, 11, 4756, 420, 2046, 304, 279, 8486, 22037, 26545, 11, 5357, 389, 459, 49242, 2663, 67533, 842, 263, 1791, 1655, 220, 16, 11, 477, 435, 965, 16, 13, 12362, 264, 10824, 315, 26110, 848, 79173, 11, 93532, 11, 323, 19465, 29060, 11, 12074, 520, 279, 6011, 315, 12634, 596, 28574, 33108, 5165, 32184, 320, 39379, 28399, 11868, 8, 8710, 430, 79106, 33277, 8774, 435, 965, 16, 304, 1584, 323, 3318, 10489, 13, 330, 37, 965, 16, 11, 1093, 1690, 15922, 48891, 323, 13023, 28896, 11, 617, 52313, 950, 13073, 9959, 311, 9572, 1359, 1071, 4007, 3063, 3229, 31033, 26132, 332, 587, 14406, 11, 264, 17332, 75188, 520, 33108, 11868, 596, 60825, 12371, 5237, 17688, 323, 50521, 24432, 318, 4210, 14829, 13, 330, 32, 16930, 555, 435, 965, 16, 1436, 5674, 279, 15922, 11, 6522, 311, 279, 4500, 315, 9572, 13, 1952, 279, 1023, 3185, 11, 1690, 51423, 1205, 48891, 323, 13023, 28896, 311, 18167, 323, 311, 13023, 15922, 20727, 505, 9572, 22972, 13, 1561, 6029, 5039, 430, 79106, 33277, 8779, 6106, 430, 435, 965, 16, 74157, 439, 433, 1288, 311, 5471, 33869, 56399, 1210, 12220, 279, 1920, 315, 48891, 11, 2033, 42728, 6601, 15922, 653, 89, 3153, 311, 29241, 279, 31484, 354, 3422, 3235, 1202, 1403, 8821, 69864, 13, 763, 430, 1920, 11, 1344, 2690, 315, 3254, 42728, 6601, 15922, 527, 3549, 13, 578, 2683, 315, 435, 965, 16, 374, 311, 4148, 1884, 1344, 2690, 555, 39825, 9501, 51483, 82, 779, 430, 814, 649, 1464, 1523, 279, 33088, 31559, 5302, 27460, 430, 1304, 709, 279, 56527, 315, 31484, 292, 13935, 69864, 13, 1115, 11551, 68256, 1957, 13980, 304, 279, 81268, 15922, 3221, 279, 49341, 449, 279, 3254, 42728, 6601, 67533, 13, 3061, 2690, 430, 7293, 38594, 4234, 649, 3063, 311, 21503, 15922, 5674, 430, 3060, 5622, 279, 2849, 477, 5353, 16781, 34684, 13, 1789, 3187, 11, 490, 258, 22935, 69044, 13454, 78588, 11, 264, 27472, 5938, 449, 24673, 1778, 439, 75851, 596, 8624, 323, 45350, 1630, 28439, 11, 527, 32971, 555, 279, 8060, 315, 435, 965, 16, 311, 4018, 1022, 279, 13937, 42589, 13, 578, 68144, 520, 1948, 46480, 1268, 47588, 315, 279, 15922, 67533, 13912, 279, 33088, 31559, 5302, 27460, 3201, 505, 279, 9501, 51483, 82, 430, 649, 70185, 4018, 279, 42589, 13, 578, 5740, 1684, 5039, 264, 3254, 42728, 6601, 15922, 67533, 12579, 1555, 264, 2678, 8736, 304, 279, 435, 965, 16, 13128, 11, 33687, 555, 25396, 2020, 8603, 304, 279, 6913, 5654, 13, 16666, 25, 31033, 26132, 332, 587, 14406, 16675, 261, 28399, 11868, 330, 3923, 1047, 1027, 25420, 1603, 1057, 4007, 574, 1268, 435, 965, 16, 574, 3025, 311, 10765, 1202, 4839, 2218, 1418, 27252, 279, 94546, 3357, 14713, 315, 3254, 42728, 6601, 1344, 2690, 1359, 1071, 26132, 332, 587, 14406, 13, 330, 3947, 2011, 387, 264, 1648, 369, 420, 13128, 311, 539, 98862, 4528, 11811, 11, 1778, 439, 3254, 42728, 6601, 41214, 477, 15922, 13, 25531, 430, 1314, 374, 9200, 1210, 26132, 332, 587, 14406, 6575, 449, 12435, 3229, 3842, 350, 1780, 11, 33108, 11868, 3495, 28568, 323, 264, 14561, 520, 279, 3907, 315, 8421, 11, 520, 279, 21844, 8828, 8922, 11, 264, 93157, 8410, 315, 10170, 2724, 47750, 430, 19159, 9193, 10107, 1630, 30630, 51045, 14791, 369, 22581, 279, 25524, 6070, 315, 13128, 323, 15922, 69125, 13, 12362, 1630, 30630, 26110, 848, 1976, 88, 11, 814, 1051, 3025, 311, 636, 264, 31206, 11852, 1684, 315, 279, 435, 965, 16, 13128, 6070, 13, 2435, 11075, 430, 279, 3254, 42728, 6601, 67533, 67887, 1555, 264, 2678, 14512, 14454, 555, 279, 435, 965, 16, 13128, 13, 578, 1404, 315, 279, 14512, 17482, 439, 459, 5066, 1817, 430, 435, 965, 16, 374, 11212, 279, 4495, 2218, 13, 4452, 11, 814, 29392, 1766, 430, 279, 3254, 42728, 6601, 67533, 374, 47801, 1778, 430, 279, 810, 20134, 961, 315, 279, 15922, 11, 279, 33088, 31559, 5302, 56527, 11, 12580, 3201, 505, 279, 9501, 51483, 82, 11, 28592, 18189, 279, 6140, 315, 59928, 306, 3709, 1854, 13, 578, 47588, 374, 33687, 555, 264, 40646, 11684, 5654, 304, 435, 965, 16, 430, 27276, 4861, 279, 36941, 15220, 2361, 323, 4179, 388, 279, 48291, 11684, 33088, 31559, 5302, 315, 279, 3254, 42728, 6601, 15922, 1555, 279, 435, 965, 16, 26711, 13, 330, 9673, 37182, 527, 1093, 72724, 323, 690, 4018, 904, 15922, 3221, 1124, 1359, 1071, 26132, 332, 587, 14406, 13, 330, 791, 40646, 11684, 5654, 304, 435, 965, 16, 14385, 1093, 264, 33297, 11, 23062, 279, 67533, 3201, 505, 1521, 37182, 323, 22973, 279, 67533, 505, 1694, 4018, 13, 1115, 374, 1268, 435, 965, 16, 55952, 14713, 3254, 42728, 6601, 15922, 477, 41214, 1210, 330, 2028, 79106, 33277, 374, 264, 8767, 9987, 17383, 369, 26991, 279, 76041, 315, 435, 965, 16, 1359, 1364, 3779, 13, 330, 34, 11967, 7917, 1205, 435, 965, 28896, 311, 46113, 11, 779, 8830, 1268, 435, 965, 16, 4375, 1436, 1520, 3493, 11811, 369, 3495, 1139, 22972, 1523, 279, 1584, 1210, 220, 128257, 198 ]

2,522

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The latitudinal temperature gradient between the Equator and the poles influences atmospheric stability, the strength of the jet stream and extratropical cyclones 1 , 2 , 3 . Recent global warming is weakening the annual surface gradient in the Northern Hemisphere by preferentially warming the high latitudes 4 ; however, the implications of these changes for mid-latitude climate remain uncertain 5 , 6 . Here we show that a weaker latitudinal temperature gradient—that is, warming of the Arctic with respect to the Equator—during the early to middle part of the Holocene coincided with substantial decreases in mid-latitude net precipitation (precipitation minus evapotranspiration, at 30° N to 50° N). We quantify the evolution of the gradient and of mid-latitude moisture both in a new compilation of Holocene palaeoclimate records spanning from 10° S to 90° N and in an ensemble of mid-Holocene climate model simulations. The observed pattern is consistent with the hypothesis that a weaker temperature gradient led to weaker mid-latitude westerly flow, weaker cyclones and decreased net terrestrial mid-latitude precipitation. Currently, the northern high latitudes are warming at rates nearly double the global average 4 , decreasing the Equator-to-pole temperature gradient to values comparable with those in the early to middle Holocene. If the patterns observed during the Holocene hold for current anthropogenically forced warming, the weaker latitudinal temperature gradient will lead to considerable reductions in mid-latitude water resources. Main The response of mid-latitude climate to Arctic warming is poorly understood, in part because of a lack of long-term observational data 7 . There is evidence that the strength of the latitudinal temperature gradient (LTG) influences the position, strength and meridionality of mid-latitude jet streams and storm tracks (Fig. 1 ) 1 , 2 , 8 , 9 . Connections between the LTG and the mid-latitudes, however, may be nonlinear 6 , and attribution of recent changes in mid-latitude climate to Arctic warming remains a topic of active research 5 . A better understanding of links between Arctic amplification, the LTG and hemispheric circulation would have important implications for characterizing future variability in the mid-latitude hydroclimate. Fig. 1: Conceptual diagram. a , Cold high-latitude temperatures lead to a strong temperature gradient between the Equator and the pole, a stronger subtropical jet, and enhanced mid-latitude moisture transport and net precipitation. b , Warming the high latitudes reduces the LTG, and is coincident with weaker Hadley circulation, weaker westerly jets, and decreased mid-latitude moisture transport and net precipitation. Full size image Mid-latitude weather is largely shaped by extratropical cyclones, which form in regions of maximum baroclinic instability related to the LTG 1 , 10 . One hypothesis supported by theory, observations and climate models is that Arctic warming weakens the LTG and reduces zonal mid-latitude westerly winds through the thermal wind relationship 3 , 8 , 11 , 12 . The weakened LTG reduces the baroclinic potential energy that fuels storm systems, reducing mid-latitude cyclone frequency and intensity 3 , 10 , and thus reducing annual net precipitation at mid-latitudes. Palaeoclimate archives spanning the Holocene provide an opportunity to evaluate the impact of Arctic warming on the LTG and mid-latitude hydroclimates. Some model results suggest that annual LTG changes, driven annually by obliquity and seasonally by precession, would have favoured a Holocene trend towards increasing mid- to high-latitude storm activity 3 . Annual insolation peaked around 10,000 years ago (10 ka) in the Arctic, with maximum warming occurring about 7 ka (ref. 13 ). Insolation and temperatures have subsequently declined faster at high latitudes than at the Equator (Extended Data Fig. 1a ) 14 , providing a natural baseline for assessing the relationship between the evolution of the surface LTG and mid-latitude hydroclimates. In this study, we examine an extensive dataset of multi-proxy time series for the Holocene climate (Fig. 2 ). We explore the evolution of the LTG at three temporal scales from different but temporally overlapping datasets: the past 100 years (ref. 15 ), 2,000 years (ref. 16 ) and 10,000 years. We apply the new global compilation of 2,000-year palaeotemperature records from PAGES 2k 16 to bridge between instrumental data and Holocene-long temperature reconstructions. We compare the Holocene LTG evolution with that of mid-latitude hydroclimate between 30° N and 50° N, a region that is strongly influenced by extratropical cyclones and that encompasses extensive dry-land farming and large population centres vulnerable to hydroclimate change. We then use an ensemble of mid-Holocene (6 ka) PMIP3 simulations to explore the mechanistic framework and seasonality of the changes, and to compare with the proxy data. Fig. 2: Spatial and temporal distribution of Holocene proxy records. a , Proxy temperature records. b , Mid-latitude (30° N to 50° N) proxy hydroclimate records. Abbreviations for proxy types include: ratio of nitrogen-15 isotopes/argon-40 isotopes ( 15 N/ 40 Ar), glycerol dialkyle glycerol tetraethers (GDGT), long-chain diol index (LDI), tetraether index of 86 carbons (TEX 86 ), magnesium/calcium ratio (Mg/Ca), tree-ring width (TRW), carbon-13 isotopes (δ 13 C), oxygen-18 isotopes (δ 18 O), loss on ignition (LOI), ash content of peat (peat ash), ratio of strontium and calcium (Sr/Ca), deuterium isotopes of leaf wax (δD), and records composed of two or more proxy types (hybrid) 29 . The maps were generated using code and associated data from ref. 30 . A list of sites with metadata, including references for each record, is in Supplementary Tables 1 and 2 . Full size image Gridded instrumental TS4.01 data 15 from the Climatic Research Unit (CRU) show that historical LTGs have weakened over the past century by about 0.02 °C per degree of latitude (Extended Data Fig. 2a ). The LTGs derived from the PAGES 2k network show recent LTG reductions, consistent with the instrumental observations, and they place the historical trend within a millennial-scale context (Extended Data Fig. 2b ). The Holocene analysis is focused on the postglacial period starting at 10 ka when Northern Hemisphere ice-sheet area had diminished to 25% of its full-glacial extent, and global atmospheric CO 2 concentration (265 ppm) and mean", "role": "user" }, { "content": "When the Arctic warmed after the ice age 10,000 years ago, it created perfect conditions for drought. According to new research led by a University of Wyoming scientist, similar changes could be in store today because a warming Arctic weakens the temperature difference between the tropics and the poles. This, in turn, results in less precipitation, weaker cyclones and weaker mid-latitude westerly wind flow—a recipe for prolonged drought. The temperature difference between the tropics and the poles drives a lot of weather. When those opposite temperatures are wider, the result is more precipitation, stronger cyclones and more robust wind flow. However, due to the Arctic ice melting and warming up the poles, those disparate temperatures are becoming closer. \"Our analysis shows that, when the Arctic is warmer, the jet stream and other wind patterns tend to be weaker,\" says Bryan Shuman, a UW professor in the Department of Geology and Geophysics. \"The temperature difference in the Arctic and the tropics is less steep. The change brings less precipitation to the mid-latitudes.\" Shuman is a co-author of a new study that is highlighted in a paper, titled \"Mid-Latitude Net Precipitation Decreased With Arctic Warming During the Holocene,\" published today (March 27) online in Nature, an international weekly science journal. The print version of the article will be published April 4. Researchers from Northern Arizona University; Universite Catholique de Louvain in Louvain-In-Neuve, Belgium; the Florence Bascom Geoscience Center in Reston, Va.; and Cornell University also contributed to the paper. \"The Nature paper takes a global approach and relates the history of severe dry periods of temperature changes. Importantly, when temperatures have changed in similar ways to today (warming of the Arctic), the mid-latitudes—particularly places like Wyoming and other parts of central North America—dried out,\" Shuman explains. \"Climate models anticipate similar changes in the future.\" Currently, the northern high latitudes are warming at rates that are double the global average. This will decrease the equator-to-pole temperature gradient to values comparable with the early to middle Holocene Period, according to the paper. Shuman says his research contribution, using geological evidence, was helping to estimate how dry conditions have been in the past 10,000 years. His research included three water bodies in Wyoming: Lake of the Woods, located above Dubois; Little Windy Hill Pond in the Snowy Range; and Rainbow Lake in the Beartooth Mountains. \"Lakes are these natural recorders of wet and dry conditions,\" Shuman says. \"When lakes rise or lower, it leaves geological evidence behind.\" The researchers' Holocene temperature analysis included 236 records from 219 sites. During the past 10,000 years, many of the lakes studied were lower earlier in history than today, Shuman says. \"Wyoming had several thousand years where a number of lakes dried up, and sand dunes were active where they now have vegetation,\" Shuman says. \"Expanding to the East Coast, it is a wet landscape today. But 10,000 years ago, the East Coast was nearly as dry as the Great Plains.\" The research group looked at the evolution of the tropic-to-pole temperature difference from three time periods: 100 years ago, 2,000 years ago and 10,000 years ago. For the last 100 years, many atmospheric records facilitated the analysis but, for the past 2,000 years or 10,000 years, there were fewer records available. Tree rings can help to expand studies to measure temperatures over the past 2,000 years, but lake deposits, cave deposits and glacier ice were studied to record prior temperatures and precipitation. \"This information creates a test for climate models,\" Shuman says. \"If you want to use a computer to make a forecast of the future, then it's useful to test that computer's ability to make a forecast for some other time period. The geological evidence provides an excellent test.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The latitudinal temperature gradient between the Equator and the poles influences atmospheric stability, the strength of the jet stream and extratropical cyclones 1 , 2 , 3 . Recent global warming is weakening the annual surface gradient in the Northern Hemisphere by preferentially warming the high latitudes 4 ; however, the implications of these changes for mid-latitude climate remain uncertain 5 , 6 . Here we show that a weaker latitudinal temperature gradient—that is, warming of the Arctic with respect to the Equator—during the early to middle part of the Holocene coincided with substantial decreases in mid-latitude net precipitation (precipitation minus evapotranspiration, at 30° N to 50° N). We quantify the evolution of the gradient and of mid-latitude moisture both in a new compilation of Holocene palaeoclimate records spanning from 10° S to 90° N and in an ensemble of mid-Holocene climate model simulations. The observed pattern is consistent with the hypothesis that a weaker temperature gradient led to weaker mid-latitude westerly flow, weaker cyclones and decreased net terrestrial mid-latitude precipitation. Currently, the northern high latitudes are warming at rates nearly double the global average 4 , decreasing the Equator-to-pole temperature gradient to values comparable with those in the early to middle Holocene. If the patterns observed during the Holocene hold for current anthropogenically forced warming, the weaker latitudinal temperature gradient will lead to considerable reductions in mid-latitude water resources. Main The response of mid-latitude climate to Arctic warming is poorly understood, in part because of a lack of long-term observational data 7 . There is evidence that the strength of the latitudinal temperature gradient (LTG) influences the position, strength and meridionality of mid-latitude jet streams and storm tracks (Fig. 1 ) 1 , 2 , 8 , 9 . Connections between the LTG and the mid-latitudes, however, may be nonlinear 6 , and attribution of recent changes in mid-latitude climate to Arctic warming remains a topic of active research 5 . A better understanding of links between Arctic amplification, the LTG and hemispheric circulation would have important implications for characterizing future variability in the mid-latitude hydroclimate. Fig. 1: Conceptual diagram. a , Cold high-latitude temperatures lead to a strong temperature gradient between the Equator and the pole, a stronger subtropical jet, and enhanced mid-latitude moisture transport and net precipitation. b , Warming the high latitudes reduces the LTG, and is coincident with weaker Hadley circulation, weaker westerly jets, and decreased mid-latitude moisture transport and net precipitation. Full size image Mid-latitude weather is largely shaped by extratropical cyclones, which form in regions of maximum baroclinic instability related to the LTG 1 , 10 . One hypothesis supported by theory, observations and climate models is that Arctic warming weakens the LTG and reduces zonal mid-latitude westerly winds through the thermal wind relationship 3 , 8 , 11 , 12 . The weakened LTG reduces the baroclinic potential energy that fuels storm systems, reducing mid-latitude cyclone frequency and intensity 3 , 10 , and thus reducing annual net precipitation at mid-latitudes. Palaeoclimate archives spanning the Holocene provide an opportunity to evaluate the impact of Arctic warming on the LTG and mid-latitude hydroclimates. Some model results suggest that annual LTG changes, driven annually by obliquity and seasonally by precession, would have favoured a Holocene trend towards increasing mid- to high-latitude storm activity 3 . Annual insolation peaked around 10,000 years ago (10 ka) in the Arctic, with maximum warming occurring about 7 ka (ref. 13 ). Insolation and temperatures have subsequently declined faster at high latitudes than at the Equator (Extended Data Fig. 1a ) 14 , providing a natural baseline for assessing the relationship between the evolution of the surface LTG and mid-latitude hydroclimates. In this study, we examine an extensive dataset of multi-proxy time series for the Holocene climate (Fig. 2 ). We explore the evolution of the LTG at three temporal scales from different but temporally overlapping datasets: the past 100 years (ref. 15 ), 2,000 years (ref. 16 ) and 10,000 years. We apply the new global compilation of 2,000-year palaeotemperature records from PAGES 2k 16 to bridge between instrumental data and Holocene-long temperature reconstructions. We compare the Holocene LTG evolution with that of mid-latitude hydroclimate between 30° N and 50° N, a region that is strongly influenced by extratropical cyclones and that encompasses extensive dry-land farming and large population centres vulnerable to hydroclimate change. We then use an ensemble of mid-Holocene (6 ka) PMIP3 simulations to explore the mechanistic framework and seasonality of the changes, and to compare with the proxy data. Fig. 2: Spatial and temporal distribution of Holocene proxy records. a , Proxy temperature records. b , Mid-latitude (30° N to 50° N) proxy hydroclimate records. Abbreviations for proxy types include: ratio of nitrogen-15 isotopes/argon-40 isotopes ( 15 N/ 40 Ar), glycerol dialkyle glycerol tetraethers (GDGT), long-chain diol index (LDI), tetraether index of 86 carbons (TEX 86 ), magnesium/calcium ratio (Mg/Ca), tree-ring width (TRW), carbon-13 isotopes (δ 13 C), oxygen-18 isotopes (δ 18 O), loss on ignition (LOI), ash content of peat (peat ash), ratio of strontium and calcium (Sr/Ca), deuterium isotopes of leaf wax (δD), and records composed of two or more proxy types (hybrid) 29 . The maps were generated using code and associated data from ref. 30 . A list of sites with metadata, including references for each record, is in Supplementary Tables 1 and 2 . Full size image Gridded instrumental TS4.01 data 15 from the Climatic Research Unit (CRU) show that historical LTGs have weakened over the past century by about 0.02 °C per degree of latitude (Extended Data Fig. 2a ). The LTGs derived from the PAGES 2k network show recent LTG reductions, consistent with the instrumental observations, and they place the historical trend within a millennial-scale context (Extended Data Fig. 2b ). The Holocene analysis is focused on the postglacial period starting at 10 ka when Northern Hemisphere ice-sheet area had diminished to 25% of its full-glacial extent, and global atmospheric CO 2 concentration (265 ppm) and mean<|im_end|> <|im_start|>assistant When the Arctic warmed after the ice age 10,000 years ago, it created perfect conditions for drought. According to new research led by a University of Wyoming scientist, similar changes could be in store today because a warming Arctic weakens the temperature difference between the tropics and the poles. This, in turn, results in less precipitation, weaker cyclones and weaker mid-latitude westerly wind flow—a recipe for prolonged drought. The temperature difference between the tropics and the poles drives a lot of weather. When those opposite temperatures are wider, the result is more precipitation, stronger cyclones and more robust wind flow. However, due to the Arctic ice melting and warming up the poles, those disparate temperatures are becoming closer. "Our analysis shows that, when the Arctic is warmer, the jet stream and other wind patterns tend to be weaker," says Bryan Shuman, a UW professor in the Department of Geology and Geophysics. "The temperature difference in the Arctic and the tropics is less steep. The change brings less precipitation to the mid-latitudes." Shuman is a co-author of a new study that is highlighted in a paper, titled "Mid-Latitude Net Precipitation Decreased With Arctic Warming During the Holocene," published today (March 27) online in Nature, an international weekly science journal. The print version of the article will be published April 4. Researchers from Northern Arizona University; Universite Catholique de Louvain in Louvain-In-Neuve, Belgium; the Florence Bascom Geoscience Center in Reston, Va.; and Cornell University also contributed to the paper. "The Nature paper takes a global approach and relates the history of severe dry periods of temperature changes. Importantly, when temperatures have changed in similar ways to today (warming of the Arctic), the mid-latitudes—particularly places like Wyoming and other parts of central North America—dried out," Shuman explains. "Climate models anticipate similar changes in the future." Currently, the northern high latitudes are warming at rates that are double the global average. This will decrease the equator-to-pole temperature gradient to values comparable with the early to middle Holocene Period, according to the paper. Shuman says his research contribution, using geological evidence, was helping to estimate how dry conditions have been in the past 10,000 years. His research included three water bodies in Wyoming: Lake of the Woods, located above Dubois; Little Windy Hill Pond in the Snowy Range; and Rainbow Lake in the Beartooth Mountains. "Lakes are these natural recorders of wet and dry conditions," Shuman says. "When lakes rise or lower, it leaves geological evidence behind." The researchers' Holocene temperature analysis included 236 records from 219 sites. During the past 10,000 years, many of the lakes studied were lower earlier in history than today, Shuman says. "Wyoming had several thousand years where a number of lakes dried up, and sand dunes were active where they now have vegetation," Shuman says. "Expanding to the East Coast, it is a wet landscape today. But 10,000 years ago, the East Coast was nearly as dry as the Great Plains." The research group looked at the evolution of the tropic-to-pole temperature difference from three time periods: 100 years ago, 2,000 years ago and 10,000 years ago. For the last 100 years, many atmospheric records facilitated the analysis but, for the past 2,000 years or 10,000 years, there were fewer records available. Tree rings can help to expand studies to measure temperatures over the past 2,000 years, but lake deposits, cave deposits and glacier ice were studied to record prior temperatures and precipitation. "This information creates a test for climate models," Shuman says. "If you want to use a computer to make a forecast of the future, then it's useful to test that computer's ability to make a forecast for some other time period. The geological evidence provides an excellent test." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 6987, 13138, 992, 9499, 20779, 1990, 279, 11964, 859, 323, 279, 51879, 34453, 45475, 20334, 11, 279, 8333, 315, 279, 17004, 4365, 323, 11741, 266, 51172, 32343, 3233, 220, 16, 1174, 220, 17, 1174, 220, 18, 662, 35390, 3728, 24808, 374, 83526, 279, 9974, 7479, 20779, 304, 279, 17355, 96878, 555, 10932, 31668, 24808, 279, 1579, 6987, 21237, 220, 19, 2652, 4869, 11, 279, 25127, 315, 1521, 4442, 369, 5209, 2922, 17584, 10182, 7293, 36218, 220, 20, 1174, 220, 21, 662, 5810, 584, 1501, 430, 264, 43383, 6987, 13138, 992, 9499, 20779, 41128, 374, 11, 24808, 315, 279, 37518, 449, 5201, 311, 279, 11964, 859, 2345, 82977, 279, 4216, 311, 6278, 961, 315, 279, 16071, 78782, 23828, 4591, 449, 12190, 43154, 304, 5209, 2922, 17584, 4272, 61050, 320, 10872, 575, 7709, 28382, 3721, 91001, 34489, 29579, 11, 520, 220, 966, 11877, 452, 311, 220, 1135, 11877, 452, 570, 1226, 76498, 279, 15740, 315, 279, 20779, 323, 315, 5209, 2922, 17584, 32257, 2225, 304, 264, 502, 29772, 315, 16071, 78782, 11091, 6043, 62868, 3509, 7576, 56886, 505, 220, 605, 11877, 328, 311, 220, 1954, 11877, 452, 323, 304, 459, 40126, 315, 5209, 11529, 337, 78782, 10182, 1646, 47590, 13, 578, 13468, 5497, 374, 13263, 449, 279, 31178, 430, 264, 43383, 9499, 20779, 6197, 311, 43383, 5209, 2922, 17584, 289, 5302, 398, 6530, 11, 43383, 32343, 3233, 323, 25983, 4272, 80492, 5209, 2922, 17584, 61050, 13, 25122, 11, 279, 18671, 1579, 6987, 21237, 527, 24808, 520, 7969, 7154, 2033, 279, 3728, 5578, 220, 19, 1174, 44649, 279, 11964, 859, 4791, 2320, 1286, 9499, 20779, 311, 2819, 30139, 449, 1884, 304, 279, 4216, 311, 6278, 16071, 78782, 13, 1442, 279, 12912, 13468, 2391, 279, 16071, 78782, 3412, 369, 1510, 41416, 11968, 2740, 9770, 24808, 11, 279, 43383, 6987, 13138, 992, 9499, 20779, 690, 3063, 311, 24779, 47311, 304, 5209, 2922, 17584, 3090, 5070, 13, 4802, 578, 2077, 315, 5209, 2922, 17584, 10182, 311, 37518, 24808, 374, 31555, 16365, 11, 304, 961, 1606, 315, 264, 6996, 315, 1317, 9860, 90380, 828, 220, 22, 662, 2684, 374, 6029, 430, 279, 8333, 315, 279, 6987, 13138, 992, 9499, 20779, 320, 28504, 38, 8, 34453, 279, 2361, 11, 8333, 323, 4809, 307, 290, 2786, 315, 5209, 2922, 17584, 17004, 23914, 323, 13766, 14242, 320, 30035, 13, 220, 16, 883, 220, 16, 1174, 220, 17, 1174, 220, 23, 1174, 220, 24, 662, 67052, 1990, 279, 35569, 38, 323, 279, 5209, 99514, 21237, 11, 4869, 11, 1253, 387, 75098, 220, 21, 1174, 323, 63124, 315, 3293, 4442, 304, 5209, 2922, 17584, 10182, 311, 37518, 24808, 8625, 264, 8712, 315, 4642, 3495, 220, 20, 662, 362, 2731, 8830, 315, 7902, 1990, 37518, 23201, 2461, 11, 279, 35569, 38, 323, 17728, 285, 33349, 35855, 1053, 617, 3062, 25127, 369, 3752, 4954, 3938, 54709, 304, 279, 5209, 2922, 17584, 17055, 94874, 13, 23966, 13, 220, 16, 25, 35455, 940, 13861, 13, 264, 1174, 24062, 1579, 2922, 17584, 20472, 3063, 311, 264, 3831, 9499, 20779, 1990, 279, 11964, 859, 323, 279, 26078, 11, 264, 16643, 42129, 51172, 17004, 11, 323, 24872, 5209, 2922, 17584, 32257, 7710, 323, 4272, 61050, 13, 293, 1174, 468, 34002, 279, 1579, 6987, 21237, 26338, 279, 35569, 38, 11, 323, 374, 23828, 1748, 449, 43383, 24805, 3258, 35855, 11, 43383, 289, 5302, 398, 44305, 11, 323, 25983, 5209, 2922, 17584, 32257, 7710, 323, 4272, 61050, 13, 8797, 1404, 2217, 14013, 2922, 17584, 9282, 374, 14090, 27367, 555, 11741, 266, 51172, 32343, 3233, 11, 902, 1376, 304, 13918, 315, 7340, 3703, 511, 3817, 292, 56399, 5552, 311, 279, 35569, 38, 220, 16, 1174, 220, 605, 662, 3861, 31178, 7396, 555, 10334, 11, 24654, 323, 10182, 4211, 374, 430, 37518, 24808, 7621, 729, 279, 35569, 38, 323, 26338, 1167, 25180, 5209, 2922, 17584, 289, 5302, 398, 29592, 1555, 279, 29487, 10160, 5133, 220, 18, 1174, 220, 23, 1174, 220, 806, 1174, 220, 717, 662, 578, 58764, 35569, 38, 26338, 279, 3703, 511, 3817, 292, 4754, 4907, 430, 40373, 13766, 6067, 11, 18189, 5209, 2922, 17584, 32343, 606, 11900, 323, 21261, 220, 18, 1174, 220, 605, 1174, 323, 8617, 18189, 9974, 4272, 61050, 520, 5209, 99514, 21237, 13, 11165, 6043, 62868, 3509, 39104, 56886, 279, 16071, 78782, 3493, 459, 6776, 311, 15806, 279, 5536, 315, 37518, 24808, 389, 279, 35569, 38, 323, 5209, 2922, 17584, 17055, 566, 48571, 13, 4427, 1646, 3135, 4284, 430, 9974, 35569, 38, 4442, 11, 16625, 30171, 555, 1536, 41093, 488, 323, 3280, 750, 555, 864, 26540, 11, 1053, 617, 92867, 264, 16071, 78782, 9327, 7119, 7859, 5209, 12, 311, 1579, 2922, 17584, 13766, 5820, 220, 18, 662, 25992, 1672, 36062, 78292, 2212, 220, 605, 11, 931, 1667, 4227, 320, 605, 16909, 8, 304, 279, 37518, 11, 449, 7340, 24808, 31965, 922, 220, 22, 16909, 320, 1116, 13, 220, 1032, 7609, 9925, 36062, 323, 20472, 617, 28520, 19284, 10819, 520, 1579, 6987, 21237, 1109, 520, 279, 11964, 859, 320, 54290, 2956, 23966, 13, 220, 16, 64, 883, 220, 975, 1174, 8405, 264, 5933, 26954, 369, 47614, 279, 5133, 1990, 279, 15740, 315, 279, 7479, 35569, 38, 323, 5209, 2922, 17584, 17055, 566, 48571, 13, 763, 420, 4007, 11, 584, 21635, 459, 16781, 10550, 315, 7447, 84801, 892, 4101, 369, 279, 16071, 78782, 10182, 320, 30035, 13, 220, 17, 7609, 1226, 13488, 279, 15740, 315, 279, 35569, 38, 520, 2380, 37015, 29505, 505, 2204, 719, 19502, 750, 50917, 30525, 25, 279, 3347, 220, 1041, 1667, 320, 1116, 13, 220, 868, 7026, 220, 17, 11, 931, 1667, 320, 1116, 13, 220, 845, 883, 323, 220, 605, 11, 931, 1667, 13, 1226, 3881, 279, 502, 3728, 29772, 315, 220, 17, 11, 931, 4771, 11091, 6043, 354, 94825, 7576, 505, 393, 11488, 220, 17, 74, 220, 845, 311, 14497, 1990, 42045, 828, 323, 16071, 78782, 24725, 9499, 16456, 20232, 13, 1226, 9616, 279, 16071, 78782, 35569, 38, 15740, 449, 430, 315, 5209, 2922, 17584, 17055, 94874, 1990, 220, 966, 11877, 452, 323, 220, 1135, 11877, 452, 11, 264, 5654, 430, 374, 16917, 28160, 555, 11741, 266, 51172, 32343, 3233, 323, 430, 71010, 16781, 9235, 12, 1974, 33489, 323, 3544, 7187, 36282, 20134, 311, 17055, 94874, 2349, 13, 1226, 1243, 1005, 459, 40126, 315, 5209, 11529, 337, 78782, 320, 21, 16909, 8, 5975, 3378, 18, 47590, 311, 13488, 279, 7852, 4633, 12914, 323, 3280, 2786, 315, 279, 4442, 11, 323, 311, 9616, 449, 279, 13594, 828, 13, 23966, 13, 220, 17, 25, 75797, 323, 37015, 8141, 315, 16071, 78782, 13594, 7576, 13, 264, 1174, 33878, 9499, 7576, 13, 293, 1174, 14013, 2922, 17584, 320, 966, 11877, 452, 311, 220, 1135, 11877, 452, 8, 13594, 17055, 94874, 7576, 13, 27063, 7430, 17583, 369, 13594, 4595, 2997, 25, 11595, 315, 47503, 12, 868, 69551, 19031, 14, 71921, 12, 1272, 69551, 19031, 320, 220, 868, 452, 14, 220, 1272, 1676, 705, 37807, 3913, 337, 28960, 74, 982, 37807, 3913, 337, 28953, 969, 774, 388, 320, 41949, 26460, 705, 1317, 66286, 1891, 337, 1963, 320, 12615, 40, 705, 28953, 969, 2791, 1963, 315, 220, 4218, 35872, 2439, 320, 26256, 220, 4218, 7026, 61933, 2971, 17356, 2411, 11595, 320, 44, 70, 11547, 64, 705, 5021, 77029, 2430, 320, 2434, 54, 705, 12782, 12, 1032, 69551, 19031, 320, 86486, 220, 1032, 356, 705, 24463, 12, 972, 69551, 19031, 320, 86486, 220, 972, 507, 705, 4814, 389, 60692, 320, 1623, 40, 705, 24767, 2262, 315, 1069, 266, 320, 11221, 24767, 705, 11595, 315, 610, 546, 2411, 323, 35719, 320, 80026, 11547, 64, 705, 409, 29051, 2411, 69551, 19031, 315, 16312, 37123, 320, 86486, 35, 705, 323, 7576, 24306, 315, 1403, 477, 810, 13594, 4595, 320, 8671, 16621, 8, 220, 1682, 662, 578, 14370, 1051, 8066, 1701, 2082, 323, 5938, 828, 505, 2098, 13, 220, 966, 662, 362, 1160, 315, 6732, 449, 11408, 11, 2737, 15407, 369, 1855, 3335, 11, 374, 304, 99371, 43252, 220, 16, 323, 220, 17, 662, 8797, 1404, 2217, 2895, 1810, 291, 42045, 23822, 19, 13, 1721, 828, 220, 868, 505, 279, 62930, 780, 8483, 8113, 320, 9150, 52, 8, 1501, 430, 13970, 35569, 82252, 617, 58764, 927, 279, 3347, 9478, 555, 922, 220, 15, 13, 2437, 37386, 34, 824, 8547, 315, 21518, 320, 54290, 2956, 23966, 13, 220, 17, 64, 7609, 578, 35569, 82252, 14592, 505, 279, 393, 11488, 220, 17, 74, 4009, 1501, 3293, 35569, 38, 47311, 11, 13263, 449, 279, 42045, 24654, 11, 323, 814, 2035, 279, 13970, 9327, 2949, 264, 2606, 32331, 13230, 2317, 320, 54290, 2956, 23966, 13, 220, 17, 65, 7609, 578, 16071, 78782, 6492, 374, 10968, 389, 279, 1772, 6200, 33211, 4261, 6041, 520, 220, 605, 16909, 994, 17355, 96878, 10054, 90066, 3158, 1047, 54182, 311, 220, 914, 4, 315, 1202, 2539, 70750, 33211, 13112, 11, 323, 3728, 45475, 7432, 220, 17, 20545, 320, 14374, 64697, 8, 323, 3152, 128257, 198, 128256, 78191, 198, 4599, 279, 37518, 82830, 1306, 279, 10054, 4325, 220, 605, 11, 931, 1667, 4227, 11, 433, 3549, 4832, 4787, 369, 37846, 13, 10771, 311, 502, 3495, 6197, 555, 264, 3907, 315, 49832, 28568, 11, 4528, 4442, 1436, 387, 304, 3637, 3432, 1606, 264, 24808, 37518, 7621, 729, 279, 9499, 6811, 1990, 279, 21965, 1233, 323, 279, 51879, 13, 1115, 11, 304, 2543, 11, 3135, 304, 2753, 61050, 11, 43383, 32343, 3233, 323, 43383, 5209, 2922, 17584, 289, 5302, 398, 10160, 6530, 29096, 11363, 369, 44387, 37846, 13, 578, 9499, 6811, 1990, 279, 21965, 1233, 323, 279, 51879, 20722, 264, 2763, 315, 9282, 13, 3277, 1884, 14329, 20472, 527, 22622, 11, 279, 1121, 374, 810, 61050, 11, 16643, 32343, 3233, 323, 810, 22514, 10160, 6530, 13, 4452, 11, 4245, 311, 279, 37518, 10054, 50684, 323, 24808, 709, 279, 51879, 11, 1884, 85129, 20472, 527, 10671, 12401, 13, 330, 8140, 6492, 5039, 430, 11, 994, 279, 37518, 374, 46039, 11, 279, 17004, 4365, 323, 1023, 10160, 12912, 8541, 311, 387, 43383, 1359, 2795, 37453, 1443, 7282, 11, 264, 66716, 14561, 304, 279, 6011, 315, 4323, 2508, 323, 4323, 5237, 17688, 13, 330, 791, 9499, 6811, 304, 279, 37518, 323, 279, 21965, 1233, 374, 2753, 32366, 13, 578, 2349, 12716, 2753, 61050, 311, 279, 5209, 99514, 21237, 1210, 1443, 7282, 374, 264, 1080, 43802, 315, 264, 502, 4007, 430, 374, 27463, 304, 264, 5684, 11, 25891, 330, 34748, 8288, 17584, 9558, 42770, 575, 7709, 65201, 1503, 3161, 37518, 468, 34002, 12220, 279, 16071, 78782, 1359, 4756, 3432, 320, 28623, 220, 1544, 8, 2930, 304, 22037, 11, 459, 6625, 17496, 8198, 8486, 13, 578, 1194, 2373, 315, 279, 4652, 690, 387, 4756, 5936, 220, 19, 13, 59250, 505, 17355, 17368, 3907, 26, 15915, 635, 12513, 337, 2428, 409, 9928, 85, 467, 304, 9928, 85, 467, 32600, 12, 8989, 57123, 11, 34061, 26, 279, 48606, 15004, 884, 4323, 24366, 1873, 5955, 304, 9240, 263, 11, 27713, 16016, 323, 56819, 3907, 1101, 20162, 311, 279, 5684, 13, 330, 791, 22037, 5684, 5097, 264, 3728, 5603, 323, 36716, 279, 3925, 315, 15748, 9235, 18852, 315, 9499, 4442, 13, 13516, 18007, 11, 994, 20472, 617, 5614, 304, 4528, 5627, 311, 3432, 320, 86, 34002, 315, 279, 37518, 705, 279, 5209, 99514, 21237, 2345, 74039, 7634, 1093, 49832, 323, 1023, 5596, 315, 8792, 4892, 5270, 2345, 67, 4588, 704, 1359, 1443, 7282, 15100, 13, 330, 83146, 4211, 48248, 4528, 4442, 304, 279, 3938, 1210, 25122, 11, 279, 18671, 1579, 6987, 21237, 527, 24808, 520, 7969, 430, 527, 2033, 279, 3728, 5578, 13, 1115, 690, 18979, 279, 3312, 859, 4791, 2320, 1286, 9499, 20779, 311, 2819, 30139, 449, 279, 4216, 311, 6278, 16071, 78782, 26572, 11, 4184, 311, 279, 5684, 13, 1443, 7282, 2795, 813, 3495, 19035, 11, 1701, 86278, 6029, 11, 574, 10695, 311, 16430, 1268, 9235, 4787, 617, 1027, 304, 279, 3347, 220, 605, 11, 931, 1667, 13, 5414, 3495, 5343, 2380, 3090, 13162, 304, 49832, 25, 11940, 315, 279, 35848, 11, 7559, 3485, 17533, 30148, 26, 15013, 22862, 88, 8270, 71965, 304, 279, 19435, 88, 16842, 26, 323, 47745, 11940, 304, 279, 2893, 472, 6627, 41114, 13, 330, 43, 2094, 527, 1521, 5933, 3335, 388, 315, 14739, 323, 9235, 4787, 1359, 1443, 7282, 2795, 13, 330, 4599, 44236, 10205, 477, 4827, 11, 433, 11141, 86278, 6029, 4920, 1210, 578, 12074, 6, 16071, 78782, 9499, 6492, 5343, 220, 14087, 7576, 505, 220, 13762, 6732, 13, 12220, 279, 3347, 220, 605, 11, 931, 1667, 11, 1690, 315, 279, 44236, 20041, 1051, 4827, 6931, 304, 3925, 1109, 3432, 11, 1443, 7282, 2795, 13, 330, 68007, 18238, 1047, 3892, 16579, 1667, 1405, 264, 1396, 315, 44236, 32720, 709, 11, 323, 9462, 294, 8699, 1051, 4642, 1405, 814, 1457, 617, 54832, 1359, 1443, 7282, 2795, 13, 330, 8193, 26673, 311, 279, 6460, 16377, 11, 433, 374, 264, 14739, 18921, 3432, 13, 2030, 220, 605, 11, 931, 1667, 4227, 11, 279, 6460, 16377, 574, 7154, 439, 9235, 439, 279, 8681, 63911, 1210, 578, 3495, 1912, 7111, 520, 279, 15740, 315, 279, 21965, 292, 4791, 2320, 1286, 9499, 6811, 505, 2380, 892, 18852, 25, 220, 1041, 1667, 4227, 11, 220, 17, 11, 931, 1667, 4227, 323, 220, 605, 11, 931, 1667, 4227, 13, 1789, 279, 1566, 220, 1041, 1667, 11, 1690, 45475, 7576, 72849, 279, 6492, 719, 11, 369, 279, 3347, 220, 17, 11, 931, 1667, 477, 220, 605, 11, 931, 1667, 11, 1070, 1051, 17162, 7576, 2561, 13, 9119, 25562, 649, 1520, 311, 9407, 7978, 311, 6767, 20472, 927, 279, 3347, 220, 17, 11, 931, 1667, 11, 719, 22553, 34751, 11, 26457, 34751, 323, 94867, 10054, 1051, 20041, 311, 3335, 4972, 20472, 323, 61050, 13, 330, 2028, 2038, 11705, 264, 1296, 369, 10182, 4211, 1359, 1443, 7282, 2795, 13, 330, 2746, 499, 1390, 311, 1005, 264, 6500, 311, 1304, 264, 18057, 315, 279, 3938, 11, 1243, 433, 596, 5505, 311, 1296, 430, 6500, 596, 5845, 311, 1304, 264, 18057, 369, 1063, 1023, 892, 4261, 13, 578, 86278, 6029, 5825, 459, 9250, 1296, 1210, 220, 128257, 198 ]

2,322

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Genetically engineered mouse models only capture a small fraction of the genetic lesions that drive human cancer. Current CRISPR–Cas9 models can expand this fraction but are limited by their reliance on error-prone DNA repair. Here we develop a system for in vivo prime editing by encoding a Cre-inducible prime editor in the mouse germline. This model allows rapid, precise engineering of a wide range of mutations in cell lines and organoids derived from primary tissues, including a clinically relevant Kras mutation associated with drug resistance and Trp53 hotspot mutations commonly observed in pancreatic cancer. With this system, we demonstrate somatic prime editing in vivo using lipid nanoparticles, and we model lung and pancreatic cancer through viral delivery of prime editing guide RNAs or orthotopic transplantation of prime-edited organoids. We believe that this approach will accelerate functional studies of cancer-associated mutations and complex genetic combinations that are challenging to construct with traditional models. Main Cancer is driven by somatic mutations that accumulate throughout progression and often display extensive intertumoral heterogeneity, occurring in thousands of different combinations across human cancer 1 , 2 . The precise nature of driver mutations and their combinations can profoundly influence how cancers initiate, progress and respond to therapy, establishing tumor genotype as a critical determinant of disease outcome 3 , 4 . Emerging precision oncology treatment paradigms aim to match specific therapies with tumor genotypes, and this strategy has shown promise for several driver mutations 5 , 6 . To expand the promise of precision oncology to more patients, it is critical to develop tools to systematically interrogate the effects of distinct genetic lesions and combinations thereof on the overall tumor phenotype, particularly in vivo. Genetically engineered mouse models (GEMMs) have proven invaluable for elucidating the mechanisms by which cancer drivers promote tumor development and progression in vivo 7 , 8 . However, generating new GEMMs using traditional approaches is an expensive, laborious and time-consuming process. Established GEMMs can also take months for investigators to acquire and often require laborious breeding programs to combine multiple alleles of interest and to establish a colony of sufficient size for experimental cohorts. These factors impede studies aimed at developing precision oncology treatments for tumors driven by specific genetic variants, which continue to be identified on a regular basis 9 . Genome editing technologies like CRISPR–Cas9 can be used to rapidly engineer somatic mutations when delivered exogenously or when installed as germline alleles 10 , 11 , 12 , 13 , 14 . While these models have accelerated the study of putative cancer driver genes, they are most frequently used to induce DNA double-stranded breaks (DSBs), leading to inactivation of tumor suppressor genes via error-prone repair and frameshifting insertion/deletion (indel) formation. Although CRISPR-based homology-directed repair (HDR) has been used to model precise single nucleotide variants (SNVs) in Cas9-knockin mice, this method requires an exogenous DNA donor template and is limited by low efficiency and high rates of indel byproducts 15 . Furthermore, the requirement for DSBs to induce frameshifts or HDR-based precise edits can lead to confounding genotoxic effects, including on-target chromothripsis events and artificial fitness costs incurred through continued disruption of edited oncogenes 16 , 17 . Precision genome editing technologies like base editing 18 can be used to model cancer in mice by installing specific transition mutations with high efficiency and negligible indel byproducts 11 . Although precise and highly efficient, base editors also have limitations, including the requirement for different base editor enzymes depending on the mutation being studied (for example, cytosine base editor (CBE) or adenine base editor (ABE)), and their propensity for bystander editing, which can prohibit introducing desired amino acid substitutions. While the recent development of C:G and A:Y transversion base editors will expand the scope of cancer modeling 19 , 20 , 21 , 22 , current base editing technology is not amenable to modeling the full spectrum of small somatic mutations. In contrast to base editing and standard CRISPR–Cas9, prime editing enables engineering the full spectrum of single nucleotide substitutions and indels with high product purity 23 , 24 . Prime editors employ a Cas9 nickase coupled with a reverse transcriptase that complexes with prime editing guide RNAs (pegRNAs). pegRNAs encode mutations of interest within a reverse transcriptase template (RTT) 23 , 24 , enabling highly precise and programmable editing. Prime editing thus offers a versatile approach to study the full spectrum of cancer driver mutations, their combinations and the growing catalog of secondary mutations that confer resistance to targeted therapies 25 , 26 , 27 , 28 . Beyond editing versatility, prime editing also avoids the formation of indel byproducts associated with DSBs. This is particularly important for studying SNVs with putative neomorphic qualities in tumor suppressor genes, as HDR-directed mutations would be diluted by the higher rate of naturally selected indels. Prime editing also exhibits lower rates of unintended activity at off-target loci, reducing the risk of confounding off-target effects 24 , 29 . These advantages, combined with broad editing capacity, provide an unprecedented opportunity to generate faithful models of human cancer. With these considerations in mind, we developed both conditional and tissue-restricted prime editing GEMMs (PE GEMMs) that eliminate the need for exogenous delivery of prime editors, which can be challenging given their significant size 30 , 31 . Encoding the prime-editing machinery within the mouse germline also minimizes confounding acute or chronic anti-tumor immune responses that could be induced by exogenous delivery of a Cas9-based fusion protein 32 , 33 , 34 . In conjunction with the development of PE GEMMs, we also developed a range of DNA vectors and engineered pegRNAs (epegRNAs) that promote efficient prime editing in a variety of cell lines and organoids derived from these mice. With this toolset, we established organoid models harboring Trp53 mutations frequently found in patients with pancreatic cancer but not modeled by current GEMMs of the disease, as well as a clinically relevant Kras mutation associated with resistance to KRAS G12C inhibitors. We further showed that PE GEMMs", "role": "user" }, { "content": "Genomic studies of cancer patients have revealed thousands of mutations linked to tumor development. However, for the vast majority of those mutations, researchers are unsure of how they contribute to cancer because there's no easy way to study them in animal models. In an advance that could help scientists make a dent in that long list of unexplored mutations, MIT researchers have developed a way to easily engineer specific cancer-linked mutations into mouse models. Using this technique, which is based on CRISPR genome-editing technology, the researchers have created models of several different mutations of the cancer-causing gene Kras, in different organs. They believe this technique could also be used for nearly any other type of cancer mutation that has been identified. Such models could help researchers identify and test new drugs that target these mutations. \"This is a remarkably powerful tool for examining the effects of essentially any mutation of interest in an intact animal, and in a fraction of the time required for earlier methods,\" says Tyler Jacks, the David H. Koch Professor of Biology, a member of the Koch Institute for Integrative Cancer Research at MIT, and one of the senior authors of the new study. Francisco Sánchez-Rivera, an assistant professor of biology at MIT and member of the Koch Institute, and David Liu, a professor in the Harvard University Department of Chemistry and Chemical Biology and a core institute member of the Broad Institute, are also senior authors of the study, which appears today in Nature Biotechnology. Zack Ely Ph.D. '22, a former MIT graduate student who is now a visiting scientist at MIT, and MIT graduate student Nicolas Mathey-Andrews are the lead authors of the paper. Faster editing Testing cancer drugs in mouse models is an important step in determining whether they are safe and effective enough to go into human clinical trials. Over the past 20 years, researchers have used genetic engineering to create mouse models by deleting tumor suppressor genes or activating cancer-promoting genes. However, this approach is labor-intensive and requires several months or even years to produce and analyze mice with a single cancer-linked mutation. \"A graduate student can build a whole Ph.D. around building a model for one mutation,\" Ely says. \"With traditional models, it would take the field decades to catch up to all of the mutations we've discovered with the Cancer Genome Atlas.\" In the mid-2010s, researchers began exploring the possibility of using the CRISPR genome-editing system to make cancerous mutations more easily. Some of this work occurred in Jacks' lab, where Sánchez-Rivera (then an MIT graduate student) and his colleagues showed that they could use CRISPR to quickly and easily knock out genes that are often lost in tumors. However, while this approach makes it easy to knock out genes, it doesn't lend itself to inserting new mutations into a gene because it relies on the cell's DNA repair mechanisms, which tend to introduce errors. Inspired by research from Liu's lab at the Broad Institute, the MIT team wanted to come up with a way to perform more precise gene-editing that would allow them to make very targeted mutations to either oncogenes (genes that drive cancer) or tumor suppressors. In 2019, Liu and colleagues reported a new version of CRISPR genome-editing called prime editing. Unlike the original version of CRISPR, which uses an enzyme called Cas9 to create double-stranded breaks in DNA, prime editing uses a modified enzyme called Cas9 nickase, which is fused to another enzyme called reverse transcriptase. This fusion enzyme cuts only one strand of the DNA helix, which avoids introducing double-stranded DNA breaks that can lead to errors when the cell repairs the DNA. The MIT researchers designed their new mouse models by engineering the gene for the prime editor enzyme into the germline cells of the mice, which means that it will be present in every cell of the organism. The encoded prime editor enzyme allows cells to copy an RNA sequence into DNA that is incorporated into the genome. However, the prime editor gene remains silent until activated by the delivery of a specific protein called Cre recombinase. Since the prime editing system is installed in the mouse genome, researchers can initiate tumor growth by injecting Cre recombinase into the tissue where they want a cancer mutation to be expressed, along with a guide RNA that directs Cas9 nickase to make a specific edit in the cells' genome. The RNA guide can be designed to induce single DNA base substitutions, deletions, or additions in a specified gene, allowing the researchers to create any cancer mutation they wish. Modeling mutations To demonstrate the potential of this technique, the researchers engineered several different mutations into the Kras gene, which drives about 30% of all human cancers, including nearly all pancreatic adenocarcinomas. However, not all Kras mutations are identical. Many Kras mutations occur at a location known as G12, where the amino acid glycine is found, and depending on the mutation, this glycine can be converted into one of several different amino acids. The researchers developed models of four different types of Kras mutations found in lung cancer: G12C, G12D, G12R, and G12A. To their surprise, they found that the tumors generated in each of these models had very different traits. For example, G12R mutations produced large, aggressive lung tumors, while G12A tumors were smaller and progressed more slowly. Learning more about how these mutations affect tumor development differently could help researchers develop drugs that target each of the different mutations. Currently, there are only two FDA-approved drugs that target Kras mutations, and they are both specific to the G12C mutation, which accounts for about 30% of the Kras mutations seen in lung cancer. The researchers also used their technique to create pancreatic organoids with several different types of mutations in the tumor suppressor gene p53, and they are now developing mouse models of these mutations. They are also working on generating models of additional Kras mutations, along with other mutations that help to confer resistance to Kras inhibitors. \"One thing that we're excited about is looking at combinations of mutations including Kras mutations that drives tumorigenesis, along with resistance associated mutations,\" Mathey-Andrews says. \"We hope that will give us a handle on not just whether the mutation causes resistance, but what does a resistant tumor look like?\" The researchers have made mice with the prime editing system engineered into their genome available through a repository at the Jackson Laboratory, and they hope that other labs will begin to use this technique for their own studies of cancer mutations. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Genetically engineered mouse models only capture a small fraction of the genetic lesions that drive human cancer. Current CRISPR–Cas9 models can expand this fraction but are limited by their reliance on error-prone DNA repair. Here we develop a system for in vivo prime editing by encoding a Cre-inducible prime editor in the mouse germline. This model allows rapid, precise engineering of a wide range of mutations in cell lines and organoids derived from primary tissues, including a clinically relevant Kras mutation associated with drug resistance and Trp53 hotspot mutations commonly observed in pancreatic cancer. With this system, we demonstrate somatic prime editing in vivo using lipid nanoparticles, and we model lung and pancreatic cancer through viral delivery of prime editing guide RNAs or orthotopic transplantation of prime-edited organoids. We believe that this approach will accelerate functional studies of cancer-associated mutations and complex genetic combinations that are challenging to construct with traditional models. Main Cancer is driven by somatic mutations that accumulate throughout progression and often display extensive intertumoral heterogeneity, occurring in thousands of different combinations across human cancer 1 , 2 . The precise nature of driver mutations and their combinations can profoundly influence how cancers initiate, progress and respond to therapy, establishing tumor genotype as a critical determinant of disease outcome 3 , 4 . Emerging precision oncology treatment paradigms aim to match specific therapies with tumor genotypes, and this strategy has shown promise for several driver mutations 5 , 6 . To expand the promise of precision oncology to more patients, it is critical to develop tools to systematically interrogate the effects of distinct genetic lesions and combinations thereof on the overall tumor phenotype, particularly in vivo. Genetically engineered mouse models (GEMMs) have proven invaluable for elucidating the mechanisms by which cancer drivers promote tumor development and progression in vivo 7 , 8 . However, generating new GEMMs using traditional approaches is an expensive, laborious and time-consuming process. Established GEMMs can also take months for investigators to acquire and often require laborious breeding programs to combine multiple alleles of interest and to establish a colony of sufficient size for experimental cohorts. These factors impede studies aimed at developing precision oncology treatments for tumors driven by specific genetic variants, which continue to be identified on a regular basis 9 . Genome editing technologies like CRISPR–Cas9 can be used to rapidly engineer somatic mutations when delivered exogenously or when installed as germline alleles 10 , 11 , 12 , 13 , 14 . While these models have accelerated the study of putative cancer driver genes, they are most frequently used to induce DNA double-stranded breaks (DSBs), leading to inactivation of tumor suppressor genes via error-prone repair and frameshifting insertion/deletion (indel) formation. Although CRISPR-based homology-directed repair (HDR) has been used to model precise single nucleotide variants (SNVs) in Cas9-knockin mice, this method requires an exogenous DNA donor template and is limited by low efficiency and high rates of indel byproducts 15 . Furthermore, the requirement for DSBs to induce frameshifts or HDR-based precise edits can lead to confounding genotoxic effects, including on-target chromothripsis events and artificial fitness costs incurred through continued disruption of edited oncogenes 16 , 17 . Precision genome editing technologies like base editing 18 can be used to model cancer in mice by installing specific transition mutations with high efficiency and negligible indel byproducts 11 . Although precise and highly efficient, base editors also have limitations, including the requirement for different base editor enzymes depending on the mutation being studied (for example, cytosine base editor (CBE) or adenine base editor (ABE)), and their propensity for bystander editing, which can prohibit introducing desired amino acid substitutions. While the recent development of C:G and A:Y transversion base editors will expand the scope of cancer modeling 19 , 20 , 21 , 22 , current base editing technology is not amenable to modeling the full spectrum of small somatic mutations. In contrast to base editing and standard CRISPR–Cas9, prime editing enables engineering the full spectrum of single nucleotide substitutions and indels with high product purity 23 , 24 . Prime editors employ a Cas9 nickase coupled with a reverse transcriptase that complexes with prime editing guide RNAs (pegRNAs). pegRNAs encode mutations of interest within a reverse transcriptase template (RTT) 23 , 24 , enabling highly precise and programmable editing. Prime editing thus offers a versatile approach to study the full spectrum of cancer driver mutations, their combinations and the growing catalog of secondary mutations that confer resistance to targeted therapies 25 , 26 , 27 , 28 . Beyond editing versatility, prime editing also avoids the formation of indel byproducts associated with DSBs. This is particularly important for studying SNVs with putative neomorphic qualities in tumor suppressor genes, as HDR-directed mutations would be diluted by the higher rate of naturally selected indels. Prime editing also exhibits lower rates of unintended activity at off-target loci, reducing the risk of confounding off-target effects 24 , 29 . These advantages, combined with broad editing capacity, provide an unprecedented opportunity to generate faithful models of human cancer. With these considerations in mind, we developed both conditional and tissue-restricted prime editing GEMMs (PE GEMMs) that eliminate the need for exogenous delivery of prime editors, which can be challenging given their significant size 30 , 31 . Encoding the prime-editing machinery within the mouse germline also minimizes confounding acute or chronic anti-tumor immune responses that could be induced by exogenous delivery of a Cas9-based fusion protein 32 , 33 , 34 . In conjunction with the development of PE GEMMs, we also developed a range of DNA vectors and engineered pegRNAs (epegRNAs) that promote efficient prime editing in a variety of cell lines and organoids derived from these mice. With this toolset, we established organoid models harboring Trp53 mutations frequently found in patients with pancreatic cancer but not modeled by current GEMMs of the disease, as well as a clinically relevant Kras mutation associated with resistance to KRAS G12C inhibitors. We further showed that PE GEMMs<|im_end|> <|im_start|>assistant Genomic studies of cancer patients have revealed thousands of mutations linked to tumor development. However, for the vast majority of those mutations, researchers are unsure of how they contribute to cancer because there's no easy way to study them in animal models. In an advance that could help scientists make a dent in that long list of unexplored mutations, MIT researchers have developed a way to easily engineer specific cancer-linked mutations into mouse models. Using this technique, which is based on CRISPR genome-editing technology, the researchers have created models of several different mutations of the cancer-causing gene Kras, in different organs. They believe this technique could also be used for nearly any other type of cancer mutation that has been identified. Such models could help researchers identify and test new drugs that target these mutations. "This is a remarkably powerful tool for examining the effects of essentially any mutation of interest in an intact animal, and in a fraction of the time required for earlier methods," says Tyler Jacks, the David H. Koch Professor of Biology, a member of the Koch Institute for Integrative Cancer Research at MIT, and one of the senior authors of the new study. Francisco Sánchez-Rivera, an assistant professor of biology at MIT and member of the Koch Institute, and David Liu, a professor in the Harvard University Department of Chemistry and Chemical Biology and a core institute member of the Broad Institute, are also senior authors of the study, which appears today in Nature Biotechnology. Zack Ely Ph.D. '22, a former MIT graduate student who is now a visiting scientist at MIT, and MIT graduate student Nicolas Mathey-Andrews are the lead authors of the paper. Faster editing Testing cancer drugs in mouse models is an important step in determining whether they are safe and effective enough to go into human clinical trials. Over the past 20 years, researchers have used genetic engineering to create mouse models by deleting tumor suppressor genes or activating cancer-promoting genes. However, this approach is labor-intensive and requires several months or even years to produce and analyze mice with a single cancer-linked mutation. "A graduate student can build a whole Ph.D. around building a model for one mutation," Ely says. "With traditional models, it would take the field decades to catch up to all of the mutations we've discovered with the Cancer Genome Atlas." In the mid-2010s, researchers began exploring the possibility of using the CRISPR genome-editing system to make cancerous mutations more easily. Some of this work occurred in Jacks' lab, where Sánchez-Rivera (then an MIT graduate student) and his colleagues showed that they could use CRISPR to quickly and easily knock out genes that are often lost in tumors. However, while this approach makes it easy to knock out genes, it doesn't lend itself to inserting new mutations into a gene because it relies on the cell's DNA repair mechanisms, which tend to introduce errors. Inspired by research from Liu's lab at the Broad Institute, the MIT team wanted to come up with a way to perform more precise gene-editing that would allow them to make very targeted mutations to either oncogenes (genes that drive cancer) or tumor suppressors. In 2019, Liu and colleagues reported a new version of CRISPR genome-editing called prime editing. Unlike the original version of CRISPR, which uses an enzyme called Cas9 to create double-stranded breaks in DNA, prime editing uses a modified enzyme called Cas9 nickase, which is fused to another enzyme called reverse transcriptase. This fusion enzyme cuts only one strand of the DNA helix, which avoids introducing double-stranded DNA breaks that can lead to errors when the cell repairs the DNA. The MIT researchers designed their new mouse models by engineering the gene for the prime editor enzyme into the germline cells of the mice, which means that it will be present in every cell of the organism. The encoded prime editor enzyme allows cells to copy an RNA sequence into DNA that is incorporated into the genome. However, the prime editor gene remains silent until activated by the delivery of a specific protein called Cre recombinase. Since the prime editing system is installed in the mouse genome, researchers can initiate tumor growth by injecting Cre recombinase into the tissue where they want a cancer mutation to be expressed, along with a guide RNA that directs Cas9 nickase to make a specific edit in the cells' genome. The RNA guide can be designed to induce single DNA base substitutions, deletions, or additions in a specified gene, allowing the researchers to create any cancer mutation they wish. Modeling mutations To demonstrate the potential of this technique, the researchers engineered several different mutations into the Kras gene, which drives about 30% of all human cancers, including nearly all pancreatic adenocarcinomas. However, not all Kras mutations are identical. Many Kras mutations occur at a location known as G12, where the amino acid glycine is found, and depending on the mutation, this glycine can be converted into one of several different amino acids. The researchers developed models of four different types of Kras mutations found in lung cancer: G12C, G12D, G12R, and G12A. To their surprise, they found that the tumors generated in each of these models had very different traits. For example, G12R mutations produced large, aggressive lung tumors, while G12A tumors were smaller and progressed more slowly. Learning more about how these mutations affect tumor development differently could help researchers develop drugs that target each of the different mutations. Currently, there are only two FDA-approved drugs that target Kras mutations, and they are both specific to the G12C mutation, which accounts for about 30% of the Kras mutations seen in lung cancer. The researchers also used their technique to create pancreatic organoids with several different types of mutations in the tumor suppressor gene p53, and they are now developing mouse models of these mutations. They are also working on generating models of additional Kras mutations, along with other mutations that help to confer resistance to Kras inhibitors. "One thing that we're excited about is looking at combinations of mutations including Kras mutations that drives tumorigenesis, along with resistance associated mutations," Mathey-Andrews says. "We hope that will give us a handle on not just whether the mutation causes resistance, but what does a resistant tumor look like?" The researchers have made mice with the prime editing system engineered into their genome available through a repository at the Jackson Laboratory, and they hope that other labs will begin to use this technique for their own studies of cancer mutations. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 9500, 37774, 46036, 8814, 4211, 1193, 12602, 264, 2678, 19983, 315, 279, 19465, 63324, 430, 6678, 3823, 9572, 13, 9303, 12904, 1669, 6616, 4235, 50342, 24, 4211, 649, 9407, 420, 19983, 719, 527, 7347, 555, 872, 54180, 389, 1493, 27748, 606, 15922, 13023, 13, 5810, 584, 2274, 264, 1887, 369, 304, 41294, 10461, 16039, 555, 11418, 264, 7948, 18251, 1791, 1260, 10461, 6576, 304, 279, 8814, 17684, 1029, 483, 13, 1115, 1646, 6276, 11295, 11, 24473, 15009, 315, 264, 7029, 2134, 315, 34684, 304, 2849, 5238, 323, 2942, 17390, 14592, 505, 6156, 39881, 11, 2737, 264, 70432, 9959, 735, 13075, 27472, 5938, 449, 5623, 13957, 323, 1183, 79, 4331, 80310, 34684, 17037, 13468, 304, 98144, 9572, 13, 3161, 420, 1887, 11, 584, 20461, 1794, 780, 10461, 16039, 304, 41294, 1701, 68700, 94753, 11, 323, 584, 1646, 21271, 323, 98144, 9572, 1555, 29962, 9889, 315, 10461, 16039, 8641, 46916, 2170, 477, 30299, 354, 25847, 98702, 315, 10461, 35535, 1639, 2942, 17390, 13, 1226, 4510, 430, 420, 5603, 690, 43880, 16003, 7978, 315, 9572, 75968, 34684, 323, 6485, 19465, 28559, 430, 527, 17436, 311, 9429, 449, 8776, 4211, 13, 4802, 26211, 374, 16625, 555, 1794, 780, 34684, 430, 47376, 6957, 33824, 323, 3629, 3113, 16781, 958, 83, 372, 10020, 30548, 76730, 11, 31965, 304, 9214, 315, 2204, 28559, 4028, 3823, 9572, 220, 16, 1174, 220, 17, 662, 578, 24473, 7138, 315, 5696, 34684, 323, 872, 28559, 649, 66278, 10383, 1268, 51423, 39201, 11, 5208, 323, 6013, 311, 15419, 11, 31692, 36254, 80285, 439, 264, 9200, 88060, 315, 8624, 15632, 220, 18, 1174, 220, 19, 662, 86148, 16437, 78970, 2508, 6514, 28417, 343, 1026, 9395, 311, 2489, 3230, 52312, 449, 36254, 4173, 22583, 11, 323, 420, 8446, 706, 6982, 11471, 369, 3892, 5696, 34684, 220, 20, 1174, 220, 21, 662, 2057, 9407, 279, 11471, 315, 16437, 78970, 2508, 311, 810, 6978, 11, 433, 374, 9200, 311, 2274, 7526, 311, 60826, 37539, 349, 279, 6372, 315, 12742, 19465, 63324, 323, 28559, 34366, 389, 279, 8244, 36254, 82423, 11, 8104, 304, 41294, 13, 9500, 37774, 46036, 8814, 4211, 320, 38, 2783, 22365, 8, 617, 17033, 56193, 369, 97298, 1113, 279, 24717, 555, 902, 9572, 12050, 12192, 36254, 4500, 323, 33824, 304, 41294, 220, 22, 1174, 220, 23, 662, 4452, 11, 24038, 502, 480, 2783, 22365, 1701, 8776, 20414, 374, 459, 11646, 11, 9511, 1245, 323, 892, 70840, 1920, 13, 87350, 480, 2783, 22365, 649, 1101, 1935, 4038, 369, 26453, 311, 21953, 323, 3629, 1397, 9511, 1245, 40308, 7620, 311, 16343, 5361, 98260, 315, 2802, 323, 311, 5813, 264, 42036, 315, 14343, 1404, 369, 22772, 90388, 13, 4314, 9547, 3242, 15686, 7978, 20034, 520, 11469, 16437, 78970, 2508, 22972, 369, 56071, 16625, 555, 3230, 19465, 27103, 11, 902, 3136, 311, 387, 11054, 389, 264, 5912, 8197, 220, 24, 662, 82917, 16039, 14645, 1093, 12904, 1669, 6616, 4235, 50342, 24, 649, 387, 1511, 311, 19019, 24490, 1794, 780, 34684, 994, 12886, 506, 11968, 7162, 477, 994, 10487, 439, 17684, 1029, 483, 98260, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 662, 6104, 1521, 4211, 617, 49858, 279, 4007, 315, 2231, 1413, 9572, 5696, 21389, 11, 814, 527, 1455, 14134, 1511, 311, 49853, 15922, 2033, 42728, 6601, 18808, 320, 6061, 75307, 705, 6522, 311, 304, 23863, 315, 36254, 28321, 269, 21389, 4669, 1493, 27748, 606, 13023, 323, 14418, 71, 18148, 37027, 23365, 53725, 320, 485, 301, 8, 18488, 13, 10541, 12904, 1669, 6616, 6108, 5105, 2508, 86855, 13023, 320, 71388, 8, 706, 1027, 1511, 311, 1646, 24473, 3254, 31484, 69044, 27103, 320, 19503, 52837, 8, 304, 11301, 24, 12934, 88221, 258, 24548, 11, 420, 1749, 7612, 459, 506, 53595, 15922, 35558, 3896, 323, 374, 7347, 555, 3428, 15374, 323, 1579, 7969, 315, 1280, 301, 555, 10354, 220, 868, 662, 24296, 11, 279, 16686, 369, 423, 17094, 82, 311, 49853, 14418, 48933, 82, 477, 55491, 6108, 24473, 51944, 649, 3063, 311, 2389, 13900, 4173, 91676, 6372, 11, 2737, 389, 18996, 22083, 8942, 76816, 285, 4455, 323, 21075, 17479, 7194, 52872, 1555, 8738, 44219, 315, 19685, 78970, 11968, 288, 220, 845, 1174, 220, 1114, 662, 52459, 33869, 16039, 14645, 1093, 2385, 16039, 220, 972, 649, 387, 1511, 311, 1646, 9572, 304, 24548, 555, 27730, 3230, 9320, 34684, 449, 1579, 15374, 323, 82802, 1280, 301, 555, 10354, 220, 806, 662, 10541, 24473, 323, 7701, 11297, 11, 2385, 29846, 1101, 617, 9669, 11, 2737, 279, 16686, 369, 2204, 2385, 6576, 56067, 11911, 389, 279, 27472, 1694, 20041, 320, 2000, 3187, 11, 9693, 43681, 483, 2385, 6576, 320, 34, 11855, 8, 477, 100213, 483, 2385, 6576, 320, 1905, 36, 5850, 323, 872, 95323, 369, 83483, 261, 16039, 11, 902, 649, 48486, 33018, 12974, 42500, 13935, 94750, 13, 6104, 279, 3293, 4500, 315, 356, 25, 38, 323, 362, 25, 56, 1380, 4464, 2385, 29846, 690, 9407, 279, 7036, 315, 9572, 34579, 220, 777, 1174, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 1174, 1510, 2385, 16039, 5557, 374, 539, 1097, 12837, 311, 34579, 279, 2539, 20326, 315, 2678, 1794, 780, 34684, 13, 763, 13168, 311, 2385, 16039, 323, 5410, 12904, 1669, 6616, 4235, 50342, 24, 11, 10461, 16039, 20682, 15009, 279, 2539, 20326, 315, 3254, 31484, 69044, 94750, 323, 1280, 2053, 449, 1579, 2027, 53500, 220, 1419, 1174, 220, 1187, 662, 12801, 29846, 3539, 264, 11301, 24, 16370, 521, 34356, 449, 264, 10134, 36815, 521, 430, 69125, 449, 10461, 16039, 8641, 46916, 2170, 320, 10524, 51295, 2170, 570, 31787, 51295, 2170, 16559, 34684, 315, 2802, 2949, 264, 10134, 36815, 521, 3896, 320, 5463, 51, 8, 220, 1419, 1174, 220, 1187, 1174, 28462, 7701, 24473, 323, 56586, 481, 16039, 13, 12801, 16039, 8617, 6209, 264, 33045, 5603, 311, 4007, 279, 2539, 20326, 315, 9572, 5696, 34684, 11, 872, 28559, 323, 279, 7982, 16808, 315, 14580, 34684, 430, 49843, 13957, 311, 17550, 52312, 220, 914, 1174, 220, 1627, 1174, 220, 1544, 1174, 220, 1591, 662, 31886, 16039, 60112, 11, 10461, 16039, 1101, 55952, 279, 18488, 315, 1280, 301, 555, 10354, 5938, 449, 423, 17094, 82, 13, 1115, 374, 8104, 3062, 369, 21630, 18407, 52837, 449, 2231, 1413, 841, 71017, 29600, 304, 36254, 28321, 269, 21389, 11, 439, 55491, 86855, 34684, 1053, 387, 80703, 555, 279, 5190, 4478, 315, 18182, 4183, 1280, 2053, 13, 12801, 16039, 1101, 50829, 4827, 7969, 315, 73443, 5820, 520, 1022, 18996, 1353, 72, 11, 18189, 279, 5326, 315, 2389, 13900, 1022, 18996, 6372, 220, 1187, 1174, 220, 1682, 662, 4314, 22934, 11, 11093, 449, 7353, 16039, 8824, 11, 3493, 459, 31069, 6776, 311, 7068, 37513, 4211, 315, 3823, 9572, 13, 3161, 1521, 38864, 304, 4059, 11, 584, 8040, 2225, 35787, 323, 20438, 5621, 74172, 10461, 16039, 480, 2783, 22365, 320, 1777, 480, 2783, 22365, 8, 430, 22472, 279, 1205, 369, 506, 53595, 9889, 315, 10461, 29846, 11, 902, 649, 387, 17436, 2728, 872, 5199, 1404, 220, 966, 1174, 220, 2148, 662, 30430, 279, 10461, 22930, 287, 26953, 2949, 279, 8814, 17684, 1029, 483, 1101, 21877, 4861, 2389, 13900, 30883, 477, 21249, 7294, 2442, 69361, 22852, 14847, 430, 1436, 387, 36572, 555, 506, 53595, 9889, 315, 264, 11301, 24, 6108, 37608, 13128, 220, 843, 1174, 220, 1644, 1174, 220, 1958, 662, 763, 32546, 449, 279, 4500, 315, 22557, 480, 2783, 22365, 11, 584, 1101, 8040, 264, 2134, 315, 15922, 23728, 323, 46036, 31787, 51295, 2170, 320, 68, 10524, 51295, 2170, 8, 430, 12192, 11297, 10461, 16039, 304, 264, 8205, 315, 2849, 5238, 323, 2942, 17390, 14592, 505, 1521, 24548, 13, 3161, 420, 5507, 751, 11, 584, 9749, 2942, 590, 4211, 69566, 5620, 1183, 79, 4331, 34684, 14134, 1766, 304, 6978, 449, 98144, 9572, 719, 539, 62653, 555, 1510, 480, 2783, 22365, 315, 279, 8624, 11, 439, 1664, 439, 264, 70432, 9959, 735, 13075, 27472, 5938, 449, 13957, 311, 66269, 1950, 480, 717, 34, 68642, 13, 1226, 4726, 8710, 430, 22557, 480, 2783, 22365, 128257, 198, 128256, 78191, 198, 10172, 3151, 7978, 315, 9572, 6978, 617, 10675, 9214, 315, 34684, 10815, 311, 36254, 4500, 13, 4452, 11, 369, 279, 13057, 8857, 315, 1884, 34684, 11, 12074, 527, 44003, 315, 1268, 814, 17210, 311, 9572, 1606, 1070, 596, 912, 4228, 1648, 311, 4007, 1124, 304, 10065, 4211, 13, 763, 459, 12178, 430, 1436, 1520, 14248, 1304, 264, 18653, 304, 430, 1317, 1160, 315, 653, 69331, 1171, 34684, 11, 15210, 12074, 617, 8040, 264, 1648, 311, 6847, 24490, 3230, 9572, 55514, 34684, 1139, 8814, 4211, 13, 12362, 420, 15105, 11, 902, 374, 3196, 389, 12904, 1669, 6616, 33869, 22930, 287, 5557, 11, 279, 12074, 617, 3549, 4211, 315, 3892, 2204, 34684, 315, 279, 9572, 51877, 985, 15207, 735, 13075, 11, 304, 2204, 36853, 13, 2435, 4510, 420, 15105, 1436, 1101, 387, 1511, 369, 7154, 904, 1023, 955, 315, 9572, 27472, 430, 706, 1027, 11054, 13, 15483, 4211, 1436, 1520, 12074, 10765, 323, 1296, 502, 11217, 430, 2218, 1521, 34684, 13, 330, 2028, 374, 264, 49723, 8147, 5507, 369, 38936, 279, 6372, 315, 16168, 904, 27472, 315, 2802, 304, 459, 35539, 10065, 11, 323, 304, 264, 19983, 315, 279, 892, 2631, 369, 6931, 5528, 1359, 2795, 32320, 7762, 82, 11, 279, 6941, 473, 13, 40593, 17054, 315, 40023, 11, 264, 4562, 315, 279, 40593, 10181, 369, 30101, 1413, 26211, 8483, 520, 15210, 11, 323, 832, 315, 279, 10195, 12283, 315, 279, 502, 4007, 13, 13175, 328, 99634, 11151, 1553, 64, 11, 459, 18328, 14561, 315, 34458, 520, 15210, 323, 4562, 315, 279, 40593, 10181, 11, 323, 6941, 38805, 11, 264, 14561, 304, 279, 25996, 3907, 6011, 315, 42846, 323, 36424, 40023, 323, 264, 6332, 44798, 4562, 315, 279, 16273, 10181, 11, 527, 1101, 10195, 12283, 315, 279, 4007, 11, 902, 8111, 3432, 304, 22037, 12371, 52536, 13, 71566, 469, 398, 2405, 920, 13, 364, 1313, 11, 264, 4846, 15210, 19560, 5575, 889, 374, 1457, 264, 17136, 28568, 520, 15210, 11, 323, 15210, 19560, 5575, 52836, 7011, 36661, 12, 41598, 82, 527, 279, 3063, 12283, 315, 279, 5684, 13, 85586, 16039, 27866, 9572, 11217, 304, 8814, 4211, 374, 459, 3062, 3094, 304, 26679, 3508, 814, 527, 6220, 323, 7524, 3403, 311, 733, 1139, 3823, 14830, 19622, 13, 6193, 279, 3347, 220, 508, 1667, 11, 12074, 617, 1511, 19465, 15009, 311, 1893, 8814, 4211, 555, 34111, 36254, 28321, 269, 21389, 477, 72192, 9572, 66271, 11780, 21389, 13, 4452, 11, 420, 5603, 374, 9511, 88092, 323, 7612, 3892, 4038, 477, 1524, 1667, 311, 8356, 323, 24564, 24548, 449, 264, 3254, 9572, 55514, 27472, 13, 330, 32, 19560, 5575, 649, 1977, 264, 4459, 2405, 920, 13, 2212, 4857, 264, 1646, 369, 832, 27472, 1359, 469, 398, 2795, 13, 330, 2409, 8776, 4211, 11, 433, 1053, 1935, 279, 2115, 11026, 311, 2339, 709, 311, 682, 315, 279, 34684, 584, 3077, 11352, 449, 279, 26211, 82917, 43443, 1210, 763, 279, 5209, 12, 679, 15, 82, 11, 12074, 6137, 24919, 279, 13336, 315, 1701, 279, 12904, 1669, 6616, 33869, 22930, 287, 1887, 311, 1304, 9572, 788, 34684, 810, 6847, 13, 4427, 315, 420, 990, 10222, 304, 7762, 82, 6, 10278, 11, 1405, 328, 99634, 11151, 1553, 64, 320, 3473, 459, 15210, 19560, 5575, 8, 323, 813, 18105, 8710, 430, 814, 1436, 1005, 12904, 1669, 6616, 311, 6288, 323, 6847, 14459, 704, 21389, 430, 527, 3629, 5675, 304, 56071, 13, 4452, 11, 1418, 420, 5603, 3727, 433, 4228, 311, 14459, 704, 21389, 11, 433, 3250, 956, 39580, 5196, 311, 39398, 502, 34684, 1139, 264, 15207, 1606, 433, 34744, 389, 279, 2849, 596, 15922, 13023, 24717, 11, 902, 8541, 311, 19678, 6103, 13, 65925, 555, 3495, 505, 38805, 596, 10278, 520, 279, 16273, 10181, 11, 279, 15210, 2128, 4934, 311, 2586, 709, 449, 264, 1648, 311, 2804, 810, 24473, 15207, 22930, 287, 430, 1053, 2187, 1124, 311, 1304, 1633, 17550, 34684, 311, 3060, 78970, 11968, 288, 320, 59275, 430, 6678, 9572, 8, 477, 36254, 28321, 1105, 13, 763, 220, 679, 24, 11, 38805, 323, 18105, 5068, 264, 502, 2373, 315, 12904, 1669, 6616, 33869, 22930, 287, 2663, 10461, 16039, 13, 27140, 279, 4113, 2373, 315, 12904, 1669, 6616, 11, 902, 5829, 459, 49242, 2663, 11301, 24, 311, 1893, 2033, 42728, 6601, 18808, 304, 15922, 11, 10461, 16039, 5829, 264, 11041, 49242, 2663, 11301, 24, 16370, 521, 11, 902, 374, 75754, 311, 2500, 49242, 2663, 10134, 36815, 521, 13, 1115, 37608, 49242, 15455, 1193, 832, 42589, 315, 279, 15922, 11591, 953, 11, 902, 55952, 33018, 2033, 42728, 6601, 15922, 18808, 430, 649, 3063, 311, 6103, 994, 279, 2849, 31286, 279, 15922, 13, 578, 15210, 12074, 6319, 872, 502, 8814, 4211, 555, 15009, 279, 15207, 369, 279, 10461, 6576, 49242, 1139, 279, 17684, 1029, 483, 7917, 315, 279, 24548, 11, 902, 3445, 430, 433, 690, 387, 3118, 304, 1475, 2849, 315, 279, 47120, 13, 578, 21136, 10461, 6576, 49242, 6276, 7917, 311, 3048, 459, 41214, 8668, 1139, 15922, 430, 374, 32762, 1139, 279, 33869, 13, 4452, 11, 279, 10461, 6576, 15207, 8625, 21737, 3156, 22756, 555, 279, 9889, 315, 264, 3230, 13128, 2663, 7948, 38301, 7006, 521, 13, 8876, 279, 10461, 16039, 1887, 374, 10487, 304, 279, 8814, 33869, 11, 12074, 649, 39201, 36254, 6650, 555, 88385, 7948, 38301, 7006, 521, 1139, 279, 20438, 1405, 814, 1390, 264, 9572, 27472, 311, 387, 13605, 11, 3235, 449, 264, 8641, 41214, 430, 67146, 11301, 24, 16370, 521, 311, 1304, 264, 3230, 4600, 304, 279, 7917, 6, 33869, 13, 578, 41214, 8641, 649, 387, 6319, 311, 49853, 3254, 15922, 2385, 94750, 11, 19825, 919, 11, 477, 38314, 304, 264, 5300, 15207, 11, 10923, 279, 12074, 311, 1893, 904, 9572, 27472, 814, 6562, 13, 77349, 34684, 2057, 20461, 279, 4754, 315, 420, 15105, 11, 279, 12074, 46036, 3892, 2204, 34684, 1139, 279, 735, 13075, 15207, 11, 902, 20722, 922, 220, 966, 4, 315, 682, 3823, 51423, 11, 2737, 7154, 682, 98144, 100213, 511, 8362, 258, 23063, 13, 4452, 11, 539, 682, 735, 13075, 34684, 527, 20086, 13, 9176, 735, 13075, 34684, 12446, 520, 264, 3813, 3967, 439, 480, 717, 11, 1405, 279, 42500, 13935, 72157, 483, 374, 1766, 11, 323, 11911, 389, 279, 27472, 11, 420, 72157, 483, 649, 387, 16489, 1139, 832, 315, 3892, 2204, 42500, 33969, 13, 578, 12074, 8040, 4211, 315, 3116, 2204, 4595, 315, 735, 13075, 34684, 1766, 304, 21271, 9572, 25, 480, 717, 34, 11, 480, 717, 35, 11, 480, 717, 49, 11, 323, 480, 717, 32, 13, 2057, 872, 13051, 11, 814, 1766, 430, 279, 56071, 8066, 304, 1855, 315, 1521, 4211, 1047, 1633, 2204, 25022, 13, 1789, 3187, 11, 480, 717, 49, 34684, 9124, 3544, 11, 19738, 21271, 56071, 11, 1418, 480, 717, 32, 56071, 1051, 9333, 323, 62916, 810, 14297, 13, 21579, 810, 922, 1268, 1521, 34684, 7958, 36254, 4500, 22009, 1436, 1520, 12074, 2274, 11217, 430, 2218, 1855, 315, 279, 2204, 34684, 13, 25122, 11, 1070, 527, 1193, 1403, 30473, 67362, 11217, 430, 2218, 735, 13075, 34684, 11, 323, 814, 527, 2225, 3230, 311, 279, 480, 717, 34, 27472, 11, 902, 9815, 369, 922, 220, 966, 4, 315, 279, 735, 13075, 34684, 3970, 304, 21271, 9572, 13, 578, 12074, 1101, 1511, 872, 15105, 311, 1893, 98144, 2942, 17390, 449, 3892, 2204, 4595, 315, 34684, 304, 279, 36254, 28321, 269, 15207, 281, 4331, 11, 323, 814, 527, 1457, 11469, 8814, 4211, 315, 1521, 34684, 13, 2435, 527, 1101, 3318, 389, 24038, 4211, 315, 5217, 735, 13075, 34684, 11, 3235, 449, 1023, 34684, 430, 1520, 311, 49843, 13957, 311, 735, 13075, 68642, 13, 330, 4054, 3245, 430, 584, 2351, 12304, 922, 374, 3411, 520, 28559, 315, 34684, 2737, 735, 13075, 34684, 430, 20722, 15756, 4775, 268, 14093, 11, 3235, 449, 13957, 5938, 34684, 1359, 7011, 36661, 12, 41598, 82, 2795, 13, 330, 1687, 3987, 430, 690, 3041, 603, 264, 3790, 389, 539, 1120, 3508, 279, 27472, 11384, 13957, 11, 719, 1148, 1587, 264, 31785, 36254, 1427, 1093, 7673, 578, 12074, 617, 1903, 24548, 449, 279, 10461, 16039, 1887, 46036, 1139, 872, 33869, 2561, 1555, 264, 12827, 520, 279, 13972, 32184, 11, 323, 814, 3987, 430, 1023, 51048, 690, 3240, 311, 1005, 420, 15105, 369, 872, 1866, 7978, 315, 9572, 34684, 13, 220, 128257, 198 ]

2,679

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Large-scale estimations of the time of emergence of variants are essential to examine hypotheses concerning human evolution with precision. Using an open repository of genetic variant age estimations, we offer here a temporal evaluation of various evolutionarily relevant datasets, such as Homo sapiens -specific variants, high-frequency variants found in genetic windows under positive selection, introgressed variants from extinct human species, as well as putative regulatory variants specific to various brain regions. We find a recurrent bimodal distribution of high-frequency variants, but also evidence for specific enrichments of gene categories in distinct time windows, pointing to different periods of phenotypic changes, resulting in a mosaic. With a temporal classification of genetic mutations in hand, we then applied a machine learning tool to predict what genes have changed more in certain time windows, and which tissues these genes may have impacted more. Overall, we provide a fine-grained temporal mapping of derived variants in Homo sapiens that helps to illuminate the intricate evolutionary history of our species. Introduction The past decade has seen a significant shift in our understanding of the evolution of our lineage. We now recognize that anatomical features used as diagnostic for our species (globular neurocranium, small, retracted face, presence of a chin, narrow trunk, to cite only a few of the most salient traits associated with “anatomical modernity”) did not emerge as a package, from a single geographical location, but rather emerged gradually, in a mosaic-like fashion across the entire African continent and quite possibly beyond 1 , 2 , 3 . Likewise, behavioral characteristics once thought to be exclusive of Homo sapiens (funerary rituals, parietal art, ‘symbolic’ artefacts, etc.) have recently been attested in some form in closely related (extinct) clades, casting doubt on a simple definition of ‘cognitive/behavioral’ modernity 4 . We have also come to appreciate the extent of repeated (multidirectional) gene flow between Homo sapiens and Neanderthals and Denisovans, raising interesting questions about speciation 5 , 6 , 7 , 8 . Last, but not least, it is now well established that our species has a long history. Robust genetic analyses 9 indicate a divergence time between us and other hominins for whom genomes are available of roughly 700kya, leaving perhaps as many as 500ky between then and the earliest fossils displaying a near-complete suite of modern traits (Omo Kibish 1, Herto 1 and 2) 10 . Such a long period of time is likely to contain enough opportunities for multiple rounds of evolutionary modifications. Taken together, these findings render completely implausible simplistic narratives about the ‘modern human condition’ that seek to identify a specific geographical location or genetic mutation that would ‘define’ us 11 . Genomic analysis of ancient human remains in Africa reveal deep population splits and complex admixture patterns among populations 12 , 13 , 14 . At the same time, reanalysis of fossils in Africa 15 points to the extended presence of multiple hominins on this continent, together with real possibilities of admixture 16 , 17 . Lastly, our deeper understanding of other hominins points to derived characteristics in these lineages that make some of our species’ traits more ancestral (less ‘modern’) than previously believed 18 . In the context of this significant rewriting of our deep history, we decided to explore the temporal structure of an extended catalog of single nucleotide changes found at high frequency (HF \$\\ge\$ 90%) across major modern populations we previously generated on the basis of 3 high-coverage “archaic” genomes 19 , that is, Neanderthal/Denisovan individuals, used as outgroups. This catalog aims to offer a richer picture of molecular events setting us apart from our closest extinct relatives. In order to probe the temporal nature of this data, we took advantage of the Genealogical Estimation of Variant Age (GEVA) tool 20 . GEVA is a coalescence-based method that provides age estimates for over 45 million human variants. GEVA is non-parametric, making no assumptions about demographic history, tree shapes, or selection (for additional details on GEVA, see “ Methods ”). Our overall objective here is to use the temporal resolution afforded by GEVA to estimate the age of emergence of polymorphic sites, and gain further insights into the complex evolutionary trajectory of our species. Our analysis reveals a bimodal temporal distribution of modern human derived high-frequency variants and provides insights into milestones of Homo sapiens evolution through the investigation of the molecular correlates and the predicted impact of variants across evolutionary-relevant periods. Our chronological atlas allows us to provide a time window estimate of introgression events and evaluate the age of variants associated with signals of positive selection, tissue-specific changes, and specifically an estimate of the age of emergence of (enhancer) regulatory variants associated with different brain regions. Our enrichment analysis uncovers GO-terms unique to specific temporal windows, such as facial and behavioral-related terms for a period (between 300 and 500 k years) preceding the dating of human fossils like that of Jebel Irhoud. Our machine learning-based analyses predicting differential gene expression regulation of mapped variants (through 21 ) reveals a trend towards downregulation in brain-related tissues and allowed us to identify variant-associated genes whose differential regulation may specifically affect brain structures such as the cerebellum. Results Figure 1 ( a ) Density of distribution of derived Homo sapiens alleles over time in an aggregated control set (n = 1000) of random variants across the genome and two sets of derived ones: all derived variants, and those found at high-frequency. Horizontal lines mark distribution quantiles 0.25, 0.5 and 0.75. ( b ) Line plot showing the bimodal distribution of high-frequency variants using different generation times (in the text, we used 29 years, following 62 ). Full size image The distribution of derived alleles over time follows a bimodal distribution (Fig. 1 a,b; see also Fig. S2 for a more elaborated version), with a global maximum around 40 kya (for complete allele counts, see “ Methods ”). The two modes of the distribution of HF variants likely correspond to two periods of significance in the evolutionary history", "role": "user" }, { "content": "The study of the genomes of our closest relatives, the Neanderthals and Denisovans, has opened up new research paths that can broaden our understanding of the evolutionary history of Homo sapiens. A study led by the UB has made an estimation of the time when some of the genetic variants that characterize our species emerged. It does so by analyzing mutations that are very frequent in modern human populations, but not in these other species of archaic humans. The results, published in the journal Scientific Reports, show two moments in which mutations accumulated: one around 40,000 years ago, associated with the growth of the Homo sapiens population and its departure from Africa, and an older one, more than 100,000 years ago, related to the time of the greatest diversity of types of Homo sapiens in Africa. \"The understanding of the deep history of our species is expanding rapidly. However, it is difficult to determine when the genetic variants that distinguish us from other human species emerged. In this study, we have placed species-specific variants on a timeline. We have discovered how these variants accumulate over time, reflecting events such as the point of divergence between Homo sapiens and other human species around 100,000 years ago,\" says Alejandro Andirkó, first author of this article, which was part of his doctoral thesis at the UB. The study, led by Cedric Boeckx, ICREA research professor in the section of General Linguistics and member of the Institute of Complex Systems of the UB (UBICS), included the participation of Juan Moriano, UB researcher, Alessandro Vitriolo and Giuseppe Testa, experts from the University of Milan and the European Institute of Oncology, and Martin Kuhlwilm, researcher at the University of Vienna. Predominance of behavioral and facial-related variations The results of the research study also show differences between evolutionary periods. Specifically, they highlight the predominance of genetic variants related to behavior and facial structure—key characteristics in the differentiation of our species from other human species—more than 300,000 years ago, a date that coincides with the available fossil and archaeological evidence. \"We have discovered sets of genetic variants which affect the evolution of the face and which we have dated between 300,000 and 500,000 years ago, the period just prior to the dating of the earliest fossils of our species, such as the ones discovered at the Jebel Irhoud archaeological site in Morocco,\" notes Andirkó. The researchers also analyzed variants related to the brain, the organ that can best help explain key features of the rich repertoire of behaviors associated with Homo sapiens. Specifically, they dated variants which medical studies conducted in present-day humans have linked to the volume of the cerebellum, corpus callosum and other structures. \"We found that brain tissues have a particular genomic expression profile at different times in our history; that is, certain genes related to neural development were more highly expressed at certain times,\" says the researcher. Supporting the mosaic nature of the evolution of Homo sapiens These results complement an idea that is dominant in evolutionary anthropology: that there is no linear history of human species, but that different branches of our evolutionary tree coexisted and often intersected. \"The breadth of the range of human diversity in the past has surprised anthropologists. Even within Homo sapiens there are fossils, such as the ones I mentioned earlier from Jebel Irhoud, which, because of their features, were thought to belong to another species. That's why we say that human beings have lived a mosaic evolution,\" he notes. \"Our results,\" the researcher continues, \"offer a picture of how our genetics changed, which fits this idea, as we found no evidence of evolutionary changes that depended on one or a several key mutations,\" he says. Application of machine learning techniques The methodology used in the study was based on a Genealogical Estimation of Variant Age method, developed by researchers at the University of Oxford. Once they had this estimation, they applied a machine learning tool to predict which genes have changed the most in certain time windows and which tissues these genes may have impacted. Specifically, they used ExPecto, a deep learning tool that uses a convolutional network—a type of computational model—to predict gene expression levels and function from a DNA sequence. \"Since there are no data on the genomic expression of variants in the past, this tool is an approach to a problem that has not been addressed until now. Although the use of machine learning prediction is increasingly common in the clinical world, as far as we know, nobody has tried to predict the consequences of genomic changes over time,\" notes Andirkó. The importance of the perinatal phase in the brain development of our species In a previous study, the same UB team, together with the researcher Raül Gómez Buisán, used genomic information from archaic humans. In that study they analyzed genomic deserts, regions of the genome of our species where there are no genetic fragments of Neanderthals or Denisovans, and which, moreover, have been subjected to positive pressure in our species: that is, they have accumulated more mutations than would have been expected by neutral evolution. The researchers studied the expression of genes—i.e., which proteins code for different functions—found in desert regions throughout brain development, from prenatal to adult stages, covering sixteen brain structures. The results showed differences in gene expression in the cerebellum, striatum and thalamus. \"These results bring into focus the relevance of brain structures beyond the neocortex, which has traditionally dominated research on the evolution of the human brain,\" says Juan Moriano. Moreover, the most striking differences between brain structures were found at prenatal stages. \"These findings add new evidence to the hypothesis of a species-specific trajectory of brain development taking place at perinatal stages—the period from 22 weeks to the end of the first four weeks of neonatal life—that would result in a more globular head shape in modern humans, in contrast to the more elongated shape seen in Neanderthals,\" concludes Moriano. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Large-scale estimations of the time of emergence of variants are essential to examine hypotheses concerning human evolution with precision. Using an open repository of genetic variant age estimations, we offer here a temporal evaluation of various evolutionarily relevant datasets, such as Homo sapiens -specific variants, high-frequency variants found in genetic windows under positive selection, introgressed variants from extinct human species, as well as putative regulatory variants specific to various brain regions. We find a recurrent bimodal distribution of high-frequency variants, but also evidence for specific enrichments of gene categories in distinct time windows, pointing to different periods of phenotypic changes, resulting in a mosaic. With a temporal classification of genetic mutations in hand, we then applied a machine learning tool to predict what genes have changed more in certain time windows, and which tissues these genes may have impacted more. Overall, we provide a fine-grained temporal mapping of derived variants in Homo sapiens that helps to illuminate the intricate evolutionary history of our species. Introduction The past decade has seen a significant shift in our understanding of the evolution of our lineage. We now recognize that anatomical features used as diagnostic for our species (globular neurocranium, small, retracted face, presence of a chin, narrow trunk, to cite only a few of the most salient traits associated with “anatomical modernity”) did not emerge as a package, from a single geographical location, but rather emerged gradually, in a mosaic-like fashion across the entire African continent and quite possibly beyond 1 , 2 , 3 . Likewise, behavioral characteristics once thought to be exclusive of Homo sapiens (funerary rituals, parietal art, ‘symbolic’ artefacts, etc.) have recently been attested in some form in closely related (extinct) clades, casting doubt on a simple definition of ‘cognitive/behavioral’ modernity 4 . We have also come to appreciate the extent of repeated (multidirectional) gene flow between Homo sapiens and Neanderthals and Denisovans, raising interesting questions about speciation 5 , 6 , 7 , 8 . Last, but not least, it is now well established that our species has a long history. Robust genetic analyses 9 indicate a divergence time between us and other hominins for whom genomes are available of roughly 700kya, leaving perhaps as many as 500ky between then and the earliest fossils displaying a near-complete suite of modern traits (Omo Kibish 1, Herto 1 and 2) 10 . Such a long period of time is likely to contain enough opportunities for multiple rounds of evolutionary modifications. Taken together, these findings render completely implausible simplistic narratives about the ‘modern human condition’ that seek to identify a specific geographical location or genetic mutation that would ‘define’ us 11 . Genomic analysis of ancient human remains in Africa reveal deep population splits and complex admixture patterns among populations 12 , 13 , 14 . At the same time, reanalysis of fossils in Africa 15 points to the extended presence of multiple hominins on this continent, together with real possibilities of admixture 16 , 17 . Lastly, our deeper understanding of other hominins points to derived characteristics in these lineages that make some of our species’ traits more ancestral (less ‘modern’) than previously believed 18 . In the context of this significant rewriting of our deep history, we decided to explore the temporal structure of an extended catalog of single nucleotide changes found at high frequency (HF $\ge$ 90%) across major modern populations we previously generated on the basis of 3 high-coverage “archaic” genomes 19 , that is, Neanderthal/Denisovan individuals, used as outgroups. This catalog aims to offer a richer picture of molecular events setting us apart from our closest extinct relatives. In order to probe the temporal nature of this data, we took advantage of the Genealogical Estimation of Variant Age (GEVA) tool 20 . GEVA is a coalescence-based method that provides age estimates for over 45 million human variants. GEVA is non-parametric, making no assumptions about demographic history, tree shapes, or selection (for additional details on GEVA, see “ Methods ”). Our overall objective here is to use the temporal resolution afforded by GEVA to estimate the age of emergence of polymorphic sites, and gain further insights into the complex evolutionary trajectory of our species. Our analysis reveals a bimodal temporal distribution of modern human derived high-frequency variants and provides insights into milestones of Homo sapiens evolution through the investigation of the molecular correlates and the predicted impact of variants across evolutionary-relevant periods. Our chronological atlas allows us to provide a time window estimate of introgression events and evaluate the age of variants associated with signals of positive selection, tissue-specific changes, and specifically an estimate of the age of emergence of (enhancer) regulatory variants associated with different brain regions. Our enrichment analysis uncovers GO-terms unique to specific temporal windows, such as facial and behavioral-related terms for a period (between 300 and 500 k years) preceding the dating of human fossils like that of Jebel Irhoud. Our machine learning-based analyses predicting differential gene expression regulation of mapped variants (through 21 ) reveals a trend towards downregulation in brain-related tissues and allowed us to identify variant-associated genes whose differential regulation may specifically affect brain structures such as the cerebellum. Results Figure 1 ( a ) Density of distribution of derived Homo sapiens alleles over time in an aggregated control set (n = 1000) of random variants across the genome and two sets of derived ones: all derived variants, and those found at high-frequency. Horizontal lines mark distribution quantiles 0.25, 0.5 and 0.75. ( b ) Line plot showing the bimodal distribution of high-frequency variants using different generation times (in the text, we used 29 years, following 62 ). Full size image The distribution of derived alleles over time follows a bimodal distribution (Fig. 1 a,b; see also Fig. S2 for a more elaborated version), with a global maximum around 40 kya (for complete allele counts, see “ Methods ”). The two modes of the distribution of HF variants likely correspond to two periods of significance in the evolutionary history<|im_end|> <|im_start|>assistant The study of the genomes of our closest relatives, the Neanderthals and Denisovans, has opened up new research paths that can broaden our understanding of the evolutionary history of Homo sapiens. A study led by the UB has made an estimation of the time when some of the genetic variants that characterize our species emerged. It does so by analyzing mutations that are very frequent in modern human populations, but not in these other species of archaic humans. The results, published in the journal Scientific Reports, show two moments in which mutations accumulated: one around 40,000 years ago, associated with the growth of the Homo sapiens population and its departure from Africa, and an older one, more than 100,000 years ago, related to the time of the greatest diversity of types of Homo sapiens in Africa. "The understanding of the deep history of our species is expanding rapidly. However, it is difficult to determine when the genetic variants that distinguish us from other human species emerged. In this study, we have placed species-specific variants on a timeline. We have discovered how these variants accumulate over time, reflecting events such as the point of divergence between Homo sapiens and other human species around 100,000 years ago," says Alejandro Andirkó, first author of this article, which was part of his doctoral thesis at the UB. The study, led by Cedric Boeckx, ICREA research professor in the section of General Linguistics and member of the Institute of Complex Systems of the UB (UBICS), included the participation of Juan Moriano, UB researcher, Alessandro Vitriolo and Giuseppe Testa, experts from the University of Milan and the European Institute of Oncology, and Martin Kuhlwilm, researcher at the University of Vienna. Predominance of behavioral and facial-related variations The results of the research study also show differences between evolutionary periods. Specifically, they highlight the predominance of genetic variants related to behavior and facial structure—key characteristics in the differentiation of our species from other human species—more than 300,000 years ago, a date that coincides with the available fossil and archaeological evidence. "We have discovered sets of genetic variants which affect the evolution of the face and which we have dated between 300,000 and 500,000 years ago, the period just prior to the dating of the earliest fossils of our species, such as the ones discovered at the Jebel Irhoud archaeological site in Morocco," notes Andirkó. The researchers also analyzed variants related to the brain, the organ that can best help explain key features of the rich repertoire of behaviors associated with Homo sapiens. Specifically, they dated variants which medical studies conducted in present-day humans have linked to the volume of the cerebellum, corpus callosum and other structures. "We found that brain tissues have a particular genomic expression profile at different times in our history; that is, certain genes related to neural development were more highly expressed at certain times," says the researcher. Supporting the mosaic nature of the evolution of Homo sapiens These results complement an idea that is dominant in evolutionary anthropology: that there is no linear history of human species, but that different branches of our evolutionary tree coexisted and often intersected. "The breadth of the range of human diversity in the past has surprised anthropologists. Even within Homo sapiens there are fossils, such as the ones I mentioned earlier from Jebel Irhoud, which, because of their features, were thought to belong to another species. That's why we say that human beings have lived a mosaic evolution," he notes. "Our results," the researcher continues, "offer a picture of how our genetics changed, which fits this idea, as we found no evidence of evolutionary changes that depended on one or a several key mutations," he says. Application of machine learning techniques The methodology used in the study was based on a Genealogical Estimation of Variant Age method, developed by researchers at the University of Oxford. Once they had this estimation, they applied a machine learning tool to predict which genes have changed the most in certain time windows and which tissues these genes may have impacted. Specifically, they used ExPecto, a deep learning tool that uses a convolutional network—a type of computational model—to predict gene expression levels and function from a DNA sequence. "Since there are no data on the genomic expression of variants in the past, this tool is an approach to a problem that has not been addressed until now. Although the use of machine learning prediction is increasingly common in the clinical world, as far as we know, nobody has tried to predict the consequences of genomic changes over time," notes Andirkó. The importance of the perinatal phase in the brain development of our species In a previous study, the same UB team, together with the researcher Raül Gómez Buisán, used genomic information from archaic humans. In that study they analyzed genomic deserts, regions of the genome of our species where there are no genetic fragments of Neanderthals or Denisovans, and which, moreover, have been subjected to positive pressure in our species: that is, they have accumulated more mutations than would have been expected by neutral evolution. The researchers studied the expression of genes—i.e., which proteins code for different functions—found in desert regions throughout brain development, from prenatal to adult stages, covering sixteen brain structures. The results showed differences in gene expression in the cerebellum, striatum and thalamus. "These results bring into focus the relevance of brain structures beyond the neocortex, which has traditionally dominated research on the evolution of the human brain," says Juan Moriano. Moreover, the most striking differences between brain structures were found at prenatal stages. "These findings add new evidence to the hypothesis of a species-specific trajectory of brain development taking place at perinatal stages—the period from 22 weeks to the end of the first four weeks of neonatal life—that would result in a more globular head shape in modern humans, in contrast to the more elongated shape seen in Neanderthals," concludes Moriano. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 20902, 13230, 15279, 811, 315, 279, 892, 315, 49179, 315, 27103, 527, 7718, 311, 21635, 74513, 18815, 3823, 15740, 449, 16437, 13, 12362, 459, 1825, 12827, 315, 19465, 11678, 4325, 15279, 811, 11, 584, 3085, 1618, 264, 37015, 16865, 315, 5370, 15740, 6751, 9959, 30525, 11, 1778, 439, 84497, 82295, 729, 482, 52340, 27103, 11, 1579, 79412, 27103, 1766, 304, 19465, 11276, 1234, 6928, 6727, 11, 20285, 2542, 291, 27103, 505, 69918, 3823, 9606, 11, 439, 1664, 439, 2231, 1413, 23331, 27103, 3230, 311, 5370, 8271, 13918, 13, 1226, 1505, 264, 65174, 293, 318, 58697, 8141, 315, 1579, 79412, 27103, 11, 719, 1101, 6029, 369, 3230, 31518, 1392, 315, 15207, 11306, 304, 12742, 892, 11276, 11, 22364, 311, 2204, 18852, 315, 14345, 37941, 292, 4442, 11, 13239, 304, 264, 71624, 13, 3161, 264, 37015, 24790, 315, 19465, 34684, 304, 1450, 11, 584, 1243, 9435, 264, 5780, 6975, 5507, 311, 7168, 1148, 21389, 617, 5614, 810, 304, 3738, 892, 11276, 11, 323, 902, 39881, 1521, 21389, 1253, 617, 40028, 810, 13, 28993, 11, 584, 3493, 264, 7060, 25313, 2692, 37015, 13021, 315, 14592, 27103, 304, 84497, 82295, 729, 430, 8779, 311, 88682, 279, 57216, 41993, 3925, 315, 1057, 9606, 13, 29438, 578, 3347, 13515, 706, 3970, 264, 5199, 6541, 304, 1057, 8830, 315, 279, 15740, 315, 1057, 65009, 13, 1226, 1457, 15641, 430, 75893, 950, 4519, 1511, 439, 15439, 369, 1057, 9606, 320, 60026, 1299, 18247, 5192, 35822, 11, 2678, 11, 312, 55535, 3663, 11, 9546, 315, 264, 46175, 11, 15376, 38411, 11, 311, 39396, 1193, 264, 2478, 315, 279, 1455, 4371, 1188, 25022, 5938, 449, 1054, 276, 22612, 950, 6617, 488, 33611, 1550, 539, 34044, 439, 264, 6462, 11, 505, 264, 3254, 54001, 3813, 11, 719, 4856, 22763, 27115, 11, 304, 264, 71624, 12970, 11401, 4028, 279, 4553, 11904, 32843, 323, 5115, 11000, 7953, 220, 16, 1174, 220, 17, 1174, 220, 18, 662, 50487, 11, 36695, 17910, 3131, 3463, 311, 387, 14079, 315, 84497, 82295, 729, 320, 12158, 261, 661, 57679, 11, 1370, 3978, 278, 1989, 11, 3451, 19314, 292, 529, 52448, 69153, 11, 5099, 6266, 617, 6051, 1027, 1651, 10185, 304, 1063, 1376, 304, 15499, 5552, 320, 428, 7956, 8, 1206, 3536, 11, 25146, 10712, 389, 264, 4382, 7419, 315, 3451, 66, 51549, 14, 56966, 278, 529, 6617, 488, 220, 19, 662, 1226, 617, 1101, 2586, 311, 15763, 279, 13112, 315, 11763, 320, 26961, 307, 45770, 8, 15207, 6530, 1990, 84497, 82295, 729, 323, 4275, 8363, 339, 1147, 323, 61703, 869, 598, 11, 19054, 7185, 4860, 922, 1424, 7246, 220, 20, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 662, 8155, 11, 719, 539, 3325, 11, 433, 374, 1457, 1664, 9749, 430, 1057, 9606, 706, 264, 1317, 3925, 13, 4997, 592, 19465, 29060, 220, 24, 13519, 264, 82258, 892, 1990, 603, 323, 1023, 5105, 258, 1354, 369, 8884, 85381, 527, 2561, 315, 17715, 220, 7007, 74, 7911, 11, 9564, 8530, 439, 1690, 439, 220, 2636, 8050, 1990, 1243, 323, 279, 30758, 81473, 29040, 264, 3221, 75514, 16578, 315, 6617, 25022, 320, 46, 6489, 735, 581, 819, 220, 16, 11, 473, 14200, 220, 16, 323, 220, 17, 8, 220, 605, 662, 15483, 264, 1317, 4261, 315, 892, 374, 4461, 311, 6782, 3403, 10708, 369, 5361, 20101, 315, 41993, 29882, 13, 57074, 3871, 11, 1521, 14955, 3219, 6724, 11866, 43736, 78630, 58378, 922, 279, 3451, 50889, 3823, 3044, 529, 430, 6056, 311, 10765, 264, 3230, 54001, 3813, 477, 19465, 27472, 430, 1053, 3451, 1312, 529, 603, 220, 806, 662, 9500, 3151, 6492, 315, 14154, 3823, 8625, 304, 10384, 16805, 5655, 7187, 41567, 323, 6485, 14933, 13025, 12912, 4315, 22673, 220, 717, 1174, 220, 1032, 1174, 220, 975, 662, 2468, 279, 1890, 892, 11, 312, 35584, 315, 81473, 304, 10384, 220, 868, 3585, 311, 279, 11838, 9546, 315, 5361, 5105, 258, 1354, 389, 420, 32843, 11, 3871, 449, 1972, 24525, 315, 14933, 13025, 220, 845, 1174, 220, 1114, 662, 71809, 11, 1057, 19662, 8830, 315, 1023, 5105, 258, 1354, 3585, 311, 14592, 17910, 304, 1521, 1584, 1154, 430, 1304, 1063, 315, 1057, 9606, 529, 25022, 810, 78771, 320, 1752, 3451, 50889, 96206, 1109, 8767, 11846, 220, 972, 662, 763, 279, 2317, 315, 420, 5199, 95545, 315, 1057, 5655, 3925, 11, 584, 6773, 311, 13488, 279, 37015, 6070, 315, 459, 11838, 16808, 315, 3254, 31484, 69044, 4442, 1766, 520, 1579, 11900, 320, 50816, 1144, 11781, 713, 58858, 220, 1954, 11587, 4028, 3682, 6617, 22673, 584, 8767, 8066, 389, 279, 8197, 315, 220, 18, 1579, 12, 55350, 1054, 1132, 62488, 863, 85381, 220, 777, 1174, 430, 374, 11, 4275, 8363, 31392, 15302, 39685, 43757, 7931, 11, 1511, 439, 704, 17171, 13, 1115, 16808, 22262, 311, 3085, 264, 59774, 6945, 315, 31206, 4455, 6376, 603, 10980, 505, 1057, 18585, 69918, 29658, 13, 763, 2015, 311, 22477, 279, 37015, 7138, 315, 420, 828, 11, 584, 3952, 9610, 315, 279, 24983, 32051, 950, 9589, 5582, 315, 40392, 13381, 320, 11010, 13114, 8, 5507, 220, 508, 662, 30957, 13114, 374, 264, 1080, 3916, 36634, 6108, 1749, 430, 5825, 4325, 17989, 369, 927, 220, 1774, 3610, 3823, 27103, 13, 30957, 13114, 374, 2536, 74066, 16743, 11, 3339, 912, 32946, 922, 38462, 3925, 11, 5021, 21483, 11, 477, 6727, 320, 2000, 5217, 3649, 389, 30957, 13114, 11, 1518, 1054, 19331, 19524, 570, 5751, 8244, 16945, 1618, 374, 311, 1005, 279, 37015, 11175, 66699, 555, 30957, 13114, 311, 16430, 279, 4325, 315, 49179, 315, 46033, 41969, 6732, 11, 323, 8895, 4726, 26793, 1139, 279, 6485, 41993, 35782, 315, 1057, 9606, 13, 5751, 6492, 21667, 264, 293, 318, 58697, 37015, 8141, 315, 6617, 3823, 14592, 1579, 79412, 27103, 323, 5825, 26793, 1139, 69376, 315, 84497, 82295, 729, 15740, 1555, 279, 8990, 315, 279, 31206, 97303, 323, 279, 19698, 5536, 315, 27103, 4028, 41993, 5621, 8532, 18852, 13, 5751, 87634, 62032, 6276, 603, 311, 3493, 264, 892, 3321, 16430, 315, 20285, 30840, 4455, 323, 15806, 279, 4325, 315, 27103, 5938, 449, 17738, 315, 6928, 6727, 11, 20438, 19440, 4442, 11, 323, 11951, 459, 16430, 315, 279, 4325, 315, 49179, 315, 320, 40967, 11967, 8, 23331, 27103, 5938, 449, 2204, 8271, 13918, 13, 5751, 70272, 6492, 21482, 9146, 12890, 12, 18853, 5016, 311, 3230, 37015, 11276, 11, 1778, 439, 28900, 323, 36695, 14228, 3878, 369, 264, 4261, 320, 42967, 220, 3101, 323, 220, 2636, 597, 1667, 8, 38846, 279, 5029, 315, 3823, 81473, 1093, 430, 315, 71196, 301, 12227, 71, 3023, 13, 5751, 5780, 6975, 6108, 29060, 52997, 41264, 15207, 7645, 19812, 315, 24784, 27103, 320, 20322, 220, 1691, 883, 21667, 264, 9327, 7119, 1523, 1610, 2987, 304, 8271, 14228, 39881, 323, 5535, 603, 311, 10765, 11678, 75968, 21389, 6832, 41264, 19812, 1253, 11951, 7958, 8271, 14726, 1778, 439, 279, 28091, 17696, 372, 13, 18591, 19575, 220, 16, 320, 264, 883, 73710, 315, 8141, 315, 14592, 84497, 82295, 729, 98260, 927, 892, 304, 459, 71922, 2585, 743, 320, 77, 284, 220, 1041, 15, 8, 315, 4288, 27103, 4028, 279, 33869, 323, 1403, 7437, 315, 14592, 6305, 25, 682, 14592, 27103, 11, 323, 1884, 1766, 520, 1579, 79412, 13, 41009, 5238, 1906, 8141, 10484, 3742, 220, 15, 13, 914, 11, 220, 15, 13, 20, 323, 220, 15, 13, 2075, 13, 320, 293, 883, 7228, 7234, 9204, 279, 293, 318, 58697, 8141, 315, 1579, 79412, 27103, 1701, 2204, 9659, 3115, 320, 258, 279, 1495, 11, 584, 1511, 220, 1682, 1667, 11, 2768, 220, 5538, 7609, 8797, 1404, 2217, 578, 8141, 315, 14592, 98260, 927, 892, 11263, 264, 293, 318, 58697, 8141, 320, 30035, 13, 220, 16, 264, 8568, 26, 1518, 1101, 23966, 13, 328, 17, 369, 264, 810, 25985, 660, 2373, 705, 449, 264, 3728, 7340, 2212, 220, 1272, 597, 7911, 320, 2000, 4686, 70510, 14921, 11, 1518, 1054, 19331, 19524, 570, 578, 1403, 20362, 315, 279, 8141, 315, 51658, 27103, 4461, 8024, 311, 1403, 18852, 315, 26431, 304, 279, 41993, 3925, 128257, 198, 128256, 78191, 198, 791, 4007, 315, 279, 85381, 315, 1057, 18585, 29658, 11, 279, 4275, 8363, 339, 1147, 323, 61703, 869, 598, 11, 706, 9107, 709, 502, 3495, 13006, 430, 649, 84713, 1057, 8830, 315, 279, 41993, 3925, 315, 84497, 82295, 729, 13, 362, 4007, 6197, 555, 279, 74161, 706, 1903, 459, 42304, 315, 279, 892, 994, 1063, 315, 279, 19465, 27103, 430, 70755, 1057, 9606, 22763, 13, 1102, 1587, 779, 555, 42118, 34684, 430, 527, 1633, 21420, 304, 6617, 3823, 22673, 11, 719, 539, 304, 1521, 1023, 9606, 315, 5438, 62488, 12966, 13, 578, 3135, 11, 4756, 304, 279, 8486, 38130, 29140, 11, 1501, 1403, 14269, 304, 902, 34684, 41165, 25, 832, 2212, 220, 1272, 11, 931, 1667, 4227, 11, 5938, 449, 279, 6650, 315, 279, 84497, 82295, 729, 7187, 323, 1202, 25959, 505, 10384, 11, 323, 459, 9191, 832, 11, 810, 1109, 220, 1041, 11, 931, 1667, 4227, 11, 5552, 311, 279, 892, 315, 279, 12474, 20057, 315, 4595, 315, 84497, 82295, 729, 304, 10384, 13, 330, 791, 8830, 315, 279, 5655, 3925, 315, 1057, 9606, 374, 24050, 19019, 13, 4452, 11, 433, 374, 5107, 311, 8417, 994, 279, 19465, 27103, 430, 33137, 603, 505, 1023, 3823, 9606, 22763, 13, 763, 420, 4007, 11, 584, 617, 9277, 9606, 19440, 27103, 389, 264, 25845, 13, 1226, 617, 11352, 1268, 1521, 27103, 47376, 927, 892, 11, 42852, 4455, 1778, 439, 279, 1486, 315, 82258, 1990, 84497, 82295, 729, 323, 1023, 3823, 9606, 2212, 220, 1041, 11, 931, 1667, 4227, 1359, 2795, 86019, 1628, 14468, 1832, 11, 1176, 3229, 315, 420, 4652, 11, 902, 574, 961, 315, 813, 74657, 17850, 520, 279, 74161, 13, 578, 4007, 11, 6197, 555, 79613, 2265, 2577, 101458, 87, 11, 358, 9614, 32, 3495, 14561, 304, 279, 3857, 315, 3331, 89333, 5706, 323, 4562, 315, 279, 10181, 315, 22872, 15264, 315, 279, 74161, 320, 4594, 19645, 705, 5343, 279, 20852, 315, 29604, 8613, 13389, 11, 74161, 32185, 11, 70885, 42824, 29560, 462, 10216, 323, 15754, 93103, 3475, 64, 11, 11909, 505, 279, 3907, 315, 39855, 323, 279, 7665, 10181, 315, 77854, 2508, 11, 323, 11826, 735, 12825, 58153, 9672, 11, 32185, 520, 279, 3907, 315, 47387, 13, 30924, 8129, 685, 315, 36695, 323, 28900, 14228, 27339, 578, 3135, 315, 279, 3495, 4007, 1101, 1501, 12062, 1990, 41993, 18852, 13, 45863, 11, 814, 11415, 279, 35064, 685, 315, 19465, 27103, 5552, 311, 7865, 323, 28900, 6070, 2345, 798, 17910, 304, 279, 60038, 315, 1057, 9606, 505, 1023, 3823, 9606, 2345, 6518, 1109, 220, 3101, 11, 931, 1667, 4227, 11, 264, 2457, 430, 23828, 3422, 449, 279, 2561, 31376, 323, 69637, 6029, 13, 330, 1687, 617, 11352, 7437, 315, 19465, 27103, 902, 7958, 279, 15740, 315, 279, 3663, 323, 902, 584, 617, 30105, 1990, 220, 3101, 11, 931, 323, 220, 2636, 11, 931, 1667, 4227, 11, 279, 4261, 1120, 4972, 311, 279, 5029, 315, 279, 30758, 81473, 315, 1057, 9606, 11, 1778, 439, 279, 6305, 11352, 520, 279, 71196, 301, 12227, 71, 3023, 69637, 2816, 304, 59230, 1359, 8554, 1628, 14468, 1832, 13, 578, 12074, 1101, 30239, 27103, 5552, 311, 279, 8271, 11, 279, 2942, 430, 649, 1888, 1520, 10552, 1401, 4519, 315, 279, 9257, 77768, 315, 28198, 5938, 449, 84497, 82295, 729, 13, 45863, 11, 814, 30105, 27103, 902, 6593, 7978, 13375, 304, 3118, 11477, 12966, 617, 10815, 311, 279, 8286, 315, 279, 28091, 17696, 372, 11, 43194, 1652, 385, 1264, 323, 1023, 14726, 13, 330, 1687, 1766, 430, 8271, 39881, 617, 264, 4040, 81064, 7645, 5643, 520, 2204, 3115, 304, 1057, 3925, 26, 430, 374, 11, 3738, 21389, 5552, 311, 30828, 4500, 1051, 810, 7701, 13605, 520, 3738, 3115, 1359, 2795, 279, 32185, 13, 75096, 279, 71624, 7138, 315, 279, 15740, 315, 84497, 82295, 729, 4314, 3135, 23606, 459, 4623, 430, 374, 25462, 304, 41993, 95044, 25, 430, 1070, 374, 912, 13790, 3925, 315, 3823, 9606, 11, 719, 430, 2204, 23962, 315, 1057, 41993, 5021, 1080, 327, 13539, 323, 3629, 32896, 291, 13, 330, 791, 58321, 315, 279, 2134, 315, 3823, 20057, 304, 279, 3347, 706, 14792, 41416, 22012, 13, 7570, 2949, 84497, 82295, 729, 1070, 527, 81473, 11, 1778, 439, 279, 6305, 358, 9932, 6931, 505, 71196, 301, 12227, 71, 3023, 11, 902, 11, 1606, 315, 872, 4519, 11, 1051, 3463, 311, 9352, 311, 2500, 9606, 13, 3011, 596, 3249, 584, 2019, 430, 3823, 23837, 617, 12439, 264, 71624, 15740, 1359, 568, 8554, 13, 330, 8140, 3135, 1359, 279, 32185, 9731, 11, 330, 26133, 264, 6945, 315, 1268, 1057, 56104, 5614, 11, 902, 18809, 420, 4623, 11, 439, 584, 1766, 912, 6029, 315, 41993, 4442, 430, 79101, 389, 832, 477, 264, 3892, 1401, 34684, 1359, 568, 2795, 13, 7473, 315, 5780, 6975, 12823, 578, 38152, 1511, 304, 279, 4007, 574, 3196, 389, 264, 24983, 32051, 950, 9589, 5582, 315, 40392, 13381, 1749, 11, 8040, 555, 12074, 520, 279, 3907, 315, 26275, 13, 9843, 814, 1047, 420, 42304, 11, 814, 9435, 264, 5780, 6975, 5507, 311, 7168, 902, 21389, 617, 5614, 279, 1455, 304, 3738, 892, 11276, 323, 902, 39881, 1521, 21389, 1253, 617, 40028, 13, 45863, 11, 814, 1511, 1398, 47, 440, 78, 11, 264, 5655, 6975, 5507, 430, 5829, 264, 56812, 278, 4009, 29096, 955, 315, 55580, 1646, 50617, 7168, 15207, 7645, 5990, 323, 734, 505, 264, 15922, 8668, 13, 330, 12834, 1070, 527, 912, 828, 389, 279, 81064, 7645, 315, 27103, 304, 279, 3347, 11, 420, 5507, 374, 459, 5603, 311, 264, 3575, 430, 706, 539, 1027, 20669, 3156, 1457, 13, 10541, 279, 1005, 315, 5780, 6975, 20212, 374, 15098, 4279, 304, 279, 14830, 1917, 11, 439, 3117, 439, 584, 1440, 11, 19093, 706, 6818, 311, 7168, 279, 16296, 315, 81064, 4442, 927, 892, 1359, 8554, 1628, 14468, 1832, 13, 578, 12939, 315, 279, 824, 258, 4306, 10474, 304, 279, 8271, 4500, 315, 1057, 9606, 763, 264, 3766, 4007, 11, 279, 1890, 74161, 2128, 11, 3871, 449, 279, 32185, 18989, 36624, 480, 1832, 83256, 426, 9425, 11644, 11, 1511, 81064, 2038, 505, 5438, 62488, 12966, 13, 763, 430, 4007, 814, 30239, 81064, 951, 15916, 11, 13918, 315, 279, 33869, 315, 1057, 9606, 1405, 1070, 527, 912, 19465, 35603, 315, 4275, 8363, 339, 1147, 477, 61703, 869, 598, 11, 323, 902, 11, 44643, 11, 617, 1027, 38126, 311, 6928, 7410, 304, 1057, 9606, 25, 430, 374, 11, 814, 617, 41165, 810, 34684, 1109, 1053, 617, 1027, 3685, 555, 21277, 15740, 13, 578, 12074, 20041, 279, 7645, 315, 21389, 2345, 72, 1770, 2637, 902, 28896, 2082, 369, 2204, 5865, 2345, 15456, 304, 24521, 13918, 6957, 8271, 4500, 11, 505, 97128, 311, 6822, 18094, 11, 18702, 59139, 8271, 14726, 13, 578, 3135, 8710, 12062, 304, 15207, 7645, 304, 279, 28091, 17696, 372, 11, 6076, 27349, 323, 270, 17243, 355, 13, 330, 9673, 3135, 4546, 1139, 5357, 279, 41961, 315, 8271, 14726, 7953, 279, 841, 511, 45692, 11, 902, 706, 36342, 30801, 3495, 389, 279, 15740, 315, 279, 3823, 8271, 1359, 2795, 29604, 8613, 13389, 13, 23674, 11, 279, 1455, 21933, 12062, 1990, 8271, 14726, 1051, 1766, 520, 97128, 18094, 13, 330, 9673, 14955, 923, 502, 6029, 311, 279, 31178, 315, 264, 9606, 19440, 35782, 315, 8271, 4500, 4737, 2035, 520, 824, 258, 4306, 18094, 22416, 4261, 505, 220, 1313, 5672, 311, 279, 842, 315, 279, 1176, 3116, 5672, 315, 47752, 4306, 2324, 41128, 1053, 1121, 304, 264, 810, 13509, 1299, 2010, 6211, 304, 6617, 12966, 11, 304, 13168, 311, 279, 810, 74595, 660, 6211, 3970, 304, 4275, 8363, 339, 1147, 1359, 45537, 8613, 13389, 13, 220, 128257, 198 ]

2,575

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Aims/hypothesis Loneliness is associated with all-cause mortality and coronary heart disease. However, the prospective relationship between loneliness and type 2 diabetes onset is unclear. Methods We conducted a longitudinal observational population study with data on 4112 diabetes-free participants (mean age 65.02 ± 9.05) from the English Longitudinal Study of Ageing. Loneliness was assessed in 2004–2005 using the revised University of California, Los Angeles (UCLA) Loneliness Scale. Incident type 2 diabetes cases were assessed from 2006 to 2017. Associations were modelled using Cox proportional hazards regression, adjusting for potential confounders, which included cardiometabolic comorbidities. Results A total of 264 (6.42%) participants developed type 2 diabetes over the follow-up period. Loneliness was a significant predictor of incident type 2 diabetes (HR 1.46; 95% CI 1.15, 1.84; p = 0.002) independent of age, sex, ethnicity, wealth, smoking status, physical activity, alcohol consumption, BMI, HbA 1c , hypertension and cardiovascular disease. Further analyses detected an association between loneliness and type 2 diabetes onset (HR 1.41; 95% CI 1.04, 1.90; p = 0.027), independent of depressive symptoms, living alone and social isolation. Living alone and social isolation were not significantly associated with type 2 diabetes onset. Conclusions/interpretation Loneliness is a risk factor for type 2 diabetes. The mechanisms underlying this relationship remain to be elucidated. Graphical abstract Working on a manuscript? Avoid the common mistakes Introduction Loneliness is a negative emotion that occurs when an individual perceives that their social needs are not being met. It reflects an imbalance between desired and actual social relationships [ 1 ]. Survey data suggest that loneliness is a common experience, with a fifth of adults in the UK [ 2 ] and a third of adults in the USA [ 3 ] reporting feeling lonely sometimes. There has been increasing research focused on loneliness as a determinant of health. Meta-analytic evidence suggests that loneliness is a predictor of all-cause mortality, indicating that lonely individuals have a 22% greater risk of death when compared with non-lonely individuals [ 4 ]. Loneliness has a negative effect on cardiovascular health and has been associated with incident CHD [ 5 ]. This is of relevance in type 2 diabetes, as CHD is a frequent complication of the condition and a leading cause of death in this population [ 6 ]. It is plausible that deleterious cardiometabolic factors associated with loneliness could contribute to type 2 diabetes [ 7 ]. Loneliness is associated with ageing [ 2 , 3 ] and obesity [ 8 ], both of which are major risk factors for type 2 diabetes [ 9 ]. Further, evidence from large observational cohort studies indicates that loneliness is associated both cross-sectionally [ 8 ] and prospectively [ 10 ] with the metabolic syndrome. However, studies associating loneliness with HbA 1c have been less consistent [ 11 , 12 ]. To date, no study has prospectively associated loneliness with incident type 2 diabetes, although there is evidence of a cross-sectional association [ 13 , 14 ]. Some studies have investigated social isolation [ 15 , 16 , 17 , 18 , 19 ] or living alone [ 17 , 20 , 21 , 22 ] as risk factors for type 2 diabetes. However, it is important to note that loneliness is not synonymous with social isolation as it relates to the perceived quality rather than quantity of social connections [ 1 ]. Further, there is evidence that loneliness and isolation are differentially associated with health outcomes [ 23 , 24 ]. The majority of studies assessing social isolation [ 15 , 16 , 18 , 19 ] and living alone [ 17 , 21 , 22 ] as risk factors for diabetes have failed to observe an association when taking potential confounding factors (such as health behaviours) into account. The German MONICA/KORA (MONitoring of Trends and Determinants in CArdiovascular Disease/Kooperative Gesundheitsforschung in der Region Augsburg (Cooperative Health Research in the Region of Augsburg) cohort of over 8000 participants found prospective associations between social isolation [ 18 ] and living alone [ 20 ] with incident diabetes, but only in male participants. A more recent analysis of this cohort found that poor social network satisfaction, a measure of relationship quality, increased the risk of type 2 diabetes in men only [ 25 ]. Interestingly, this association was independent of both social isolation and living alone. The current study set out to address whether loneliness was a predictor of incident type 2 diabetes in a representative cohort of adults aged over 50 years living in England. We also aimed to assess whether social isolation and living alone were risk factors for type 2 diabetes. As the relationship between loneliness and social isolation is suggested to be weak to moderate for older people [ 24 ], we hypothesised that loneliness, social isolation and living alone would exert independent effects on type 2 diabetes risk. Further, it is important to consider the impact of depression as a possible confounding variable in the relationship between loneliness and type 2 diabetes. Previous research indicates that loneliness has a reciprocal relationship with depression [ 26 ]. Depression is also a possible pathway through which loneliness impacts cardiometabolic health [ 10 ], with a large body of evidence suggesting that depressed individuals are more likely to develop type 2 diabetes than those without depression [ 27 ]. Given this, we considered depressive symptoms in our analyses. Methods Participants The study used data from the English Longitudinal Study of Ageing (ELSA), a representative panel study of adults aged 50 and older living in England. Data collection began in 2002–2003 (wave 1), with follow-up waves biennially [ 28 ]. Self-reported questionnaire and interview data are collected at each wave and biological and anthropometric data are collected at alternate waves. Ethical approval for ELSA was obtained from the National Research Ethics Service. All participants provided informed consent. In the current study, we investigated the association between loneliness measured at wave 2 (2004–2005; the first wave in which loneliness was assessed) and incident", "role": "user" }, { "content": "Published in the journal Diabetologia (the journal of the European Association for the Study of Diabetes [EASD]), the study shows that it is the absence of quality connections with people and not the lack of contact that predicts the onset of type 2 diabetes, suggesting that helping people form and experience positive relationships could be a useful tool in prevention strategies for type 2 diabetes. The results have implications in light of recent findings that people with diabetes are at greater risk of dying from COVID-19. The study indicates that prolonged loneliness may influence the development of diabetes, suggesting the experience of lockdown could potentially compound people's vulnerability in this pandemic if the loneliness continues for some time. Loneliness occurs when an individual perceives that their social needs are not being met and reflects an imbalance between desired and actual social relationships. A fifth of adults in the UK and a third of adults in the USA report feeling lonely sometimes. There is a growing interest in the role of loneliness in health and previous research has associated loneliness with increased risk of death and heart disease. This is the first study to investigate the experience of loneliness with later onset of type 2 diabetes. The study analyzed data from the English Longitudinal Study Ageing on 4112 adults aged 50 years and over which was collected at several times from 2002 to 2017. At the start of data collection all participants were free of diabetes and had normal levels of blood glucose. The study showed that over a period of 12 years 264 people developed type 2 diabetes. and the level of loneliness measured at the start of data collection was a significant predictor of the onset of type 2 diabetes later on in life. This relationship remained intact when accounting for smoking, alcohol, weight, level of blood glucose, high blood pressure and cardiovascular disease. The association was also independent of depression, living alone and social isolation. Lead author Dr. Ruth Hackett from the Institute of Psychiatry, Psychology & Neuroscience (IoPPN) King's College London said: \"The study shows a strong relationship between loneliness and the later onset of type 2 diabetes. What is particularly striking is that this relationship is robust even when factors that are important in diabetes development are taken into account such as smoking, alcohol intake and blood glucose as well as mental health factors such as depression. The study also demonstrates a clear distinction between loneliness and social isolation in that isolation or living alone does not predict type 2 diabetes whereas loneliness, which is defined by a person's quality of relationships, does. She continued: \"I came up with the idea for the research during UK lockdown for the COVID-19 pandemic as I became increasingly aware and interested in how loneliness may affect our health, especially as it is likely that many more people were experiencing this difficult emotion during this period.\" According to the study a possible biological reason behind the association between loneliness and type 2 diabetes could be the impact of constant loneliness on the biological system responsible for stress, which, over time affects the body and increases the risk for diabetes. \"If the feeling of loneliness becomes chronic,\" explained Dr. Hackett. \"Then everyday you're stimulating the stress system and over time that leads to wear and tear on your body and those negative changes in stress-related biology may be linked to type 2 diabetes development.\" Another explanation for the findings could be biases in our thinking that may perpetuate the association between loneliness and diabetes as when people feel lonely, they expect people will react to them negatively which makes it more difficult to form good relationships. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Aims/hypothesis Loneliness is associated with all-cause mortality and coronary heart disease. However, the prospective relationship between loneliness and type 2 diabetes onset is unclear. Methods We conducted a longitudinal observational population study with data on 4112 diabetes-free participants (mean age 65.02 ± 9.05) from the English Longitudinal Study of Ageing. Loneliness was assessed in 2004–2005 using the revised University of California, Los Angeles (UCLA) Loneliness Scale. Incident type 2 diabetes cases were assessed from 2006 to 2017. Associations were modelled using Cox proportional hazards regression, adjusting for potential confounders, which included cardiometabolic comorbidities. Results A total of 264 (6.42%) participants developed type 2 diabetes over the follow-up period. Loneliness was a significant predictor of incident type 2 diabetes (HR 1.46; 95% CI 1.15, 1.84; p = 0.002) independent of age, sex, ethnicity, wealth, smoking status, physical activity, alcohol consumption, BMI, HbA 1c , hypertension and cardiovascular disease. Further analyses detected an association between loneliness and type 2 diabetes onset (HR 1.41; 95% CI 1.04, 1.90; p = 0.027), independent of depressive symptoms, living alone and social isolation. Living alone and social isolation were not significantly associated with type 2 diabetes onset. Conclusions/interpretation Loneliness is a risk factor for type 2 diabetes. The mechanisms underlying this relationship remain to be elucidated. Graphical abstract Working on a manuscript? Avoid the common mistakes Introduction Loneliness is a negative emotion that occurs when an individual perceives that their social needs are not being met. It reflects an imbalance between desired and actual social relationships [ 1 ]. Survey data suggest that loneliness is a common experience, with a fifth of adults in the UK [ 2 ] and a third of adults in the USA [ 3 ] reporting feeling lonely sometimes. There has been increasing research focused on loneliness as a determinant of health. Meta-analytic evidence suggests that loneliness is a predictor of all-cause mortality, indicating that lonely individuals have a 22% greater risk of death when compared with non-lonely individuals [ 4 ]. Loneliness has a negative effect on cardiovascular health and has been associated with incident CHD [ 5 ]. This is of relevance in type 2 diabetes, as CHD is a frequent complication of the condition and a leading cause of death in this population [ 6 ]. It is plausible that deleterious cardiometabolic factors associated with loneliness could contribute to type 2 diabetes [ 7 ]. Loneliness is associated with ageing [ 2 , 3 ] and obesity [ 8 ], both of which are major risk factors for type 2 diabetes [ 9 ]. Further, evidence from large observational cohort studies indicates that loneliness is associated both cross-sectionally [ 8 ] and prospectively [ 10 ] with the metabolic syndrome. However, studies associating loneliness with HbA 1c have been less consistent [ 11 , 12 ]. To date, no study has prospectively associated loneliness with incident type 2 diabetes, although there is evidence of a cross-sectional association [ 13 , 14 ]. Some studies have investigated social isolation [ 15 , 16 , 17 , 18 , 19 ] or living alone [ 17 , 20 , 21 , 22 ] as risk factors for type 2 diabetes. However, it is important to note that loneliness is not synonymous with social isolation as it relates to the perceived quality rather than quantity of social connections [ 1 ]. Further, there is evidence that loneliness and isolation are differentially associated with health outcomes [ 23 , 24 ]. The majority of studies assessing social isolation [ 15 , 16 , 18 , 19 ] and living alone [ 17 , 21 , 22 ] as risk factors for diabetes have failed to observe an association when taking potential confounding factors (such as health behaviours) into account. The German MONICA/KORA (MONitoring of Trends and Determinants in CArdiovascular Disease/Kooperative Gesundheitsforschung in der Region Augsburg (Cooperative Health Research in the Region of Augsburg) cohort of over 8000 participants found prospective associations between social isolation [ 18 ] and living alone [ 20 ] with incident diabetes, but only in male participants. A more recent analysis of this cohort found that poor social network satisfaction, a measure of relationship quality, increased the risk of type 2 diabetes in men only [ 25 ]. Interestingly, this association was independent of both social isolation and living alone. The current study set out to address whether loneliness was a predictor of incident type 2 diabetes in a representative cohort of adults aged over 50 years living in England. We also aimed to assess whether social isolation and living alone were risk factors for type 2 diabetes. As the relationship between loneliness and social isolation is suggested to be weak to moderate for older people [ 24 ], we hypothesised that loneliness, social isolation and living alone would exert independent effects on type 2 diabetes risk. Further, it is important to consider the impact of depression as a possible confounding variable in the relationship between loneliness and type 2 diabetes. Previous research indicates that loneliness has a reciprocal relationship with depression [ 26 ]. Depression is also a possible pathway through which loneliness impacts cardiometabolic health [ 10 ], with a large body of evidence suggesting that depressed individuals are more likely to develop type 2 diabetes than those without depression [ 27 ]. Given this, we considered depressive symptoms in our analyses. Methods Participants The study used data from the English Longitudinal Study of Ageing (ELSA), a representative panel study of adults aged 50 and older living in England. Data collection began in 2002–2003 (wave 1), with follow-up waves biennially [ 28 ]. Self-reported questionnaire and interview data are collected at each wave and biological and anthropometric data are collected at alternate waves. Ethical approval for ELSA was obtained from the National Research Ethics Service. All participants provided informed consent. In the current study, we investigated the association between loneliness measured at wave 2 (2004–2005; the first wave in which loneliness was assessed) and incident<|im_end|> <|im_start|>assistant Published in the journal Diabetologia (the journal of the European Association for the Study of Diabetes [EASD]), the study shows that it is the absence of quality connections with people and not the lack of contact that predicts the onset of type 2 diabetes, suggesting that helping people form and experience positive relationships could be a useful tool in prevention strategies for type 2 diabetes. The results have implications in light of recent findings that people with diabetes are at greater risk of dying from COVID-19. The study indicates that prolonged loneliness may influence the development of diabetes, suggesting the experience of lockdown could potentially compound people's vulnerability in this pandemic if the loneliness continues for some time. Loneliness occurs when an individual perceives that their social needs are not being met and reflects an imbalance between desired and actual social relationships. A fifth of adults in the UK and a third of adults in the USA report feeling lonely sometimes. There is a growing interest in the role of loneliness in health and previous research has associated loneliness with increased risk of death and heart disease. This is the first study to investigate the experience of loneliness with later onset of type 2 diabetes. The study analyzed data from the English Longitudinal Study Ageing on 4112 adults aged 50 years and over which was collected at several times from 2002 to 2017. At the start of data collection all participants were free of diabetes and had normal levels of blood glucose. The study showed that over a period of 12 years 264 people developed type 2 diabetes. and the level of loneliness measured at the start of data collection was a significant predictor of the onset of type 2 diabetes later on in life. This relationship remained intact when accounting for smoking, alcohol, weight, level of blood glucose, high blood pressure and cardiovascular disease. The association was also independent of depression, living alone and social isolation. Lead author Dr. Ruth Hackett from the Institute of Psychiatry, Psychology & Neuroscience (IoPPN) King's College London said: "The study shows a strong relationship between loneliness and the later onset of type 2 diabetes. What is particularly striking is that this relationship is robust even when factors that are important in diabetes development are taken into account such as smoking, alcohol intake and blood glucose as well as mental health factors such as depression. The study also demonstrates a clear distinction between loneliness and social isolation in that isolation or living alone does not predict type 2 diabetes whereas loneliness, which is defined by a person's quality of relationships, does. She continued: "I came up with the idea for the research during UK lockdown for the COVID-19 pandemic as I became increasingly aware and interested in how loneliness may affect our health, especially as it is likely that many more people were experiencing this difficult emotion during this period." According to the study a possible biological reason behind the association between loneliness and type 2 diabetes could be the impact of constant loneliness on the biological system responsible for stress, which, over time affects the body and increases the risk for diabetes. "If the feeling of loneliness becomes chronic," explained Dr. Hackett. "Then everyday you're stimulating the stress system and over time that leads to wear and tear on your body and those negative changes in stress-related biology may be linked to type 2 diabetes development." Another explanation for the findings could be biases in our thinking that may perpetuate the association between loneliness and diabetes as when people feel lonely, they expect people will react to them negatively which makes it more difficult to form good relationships. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 362, 5861, 7682, 60400, 13491, 49281, 55798, 374, 5938, 449, 682, 12, 1593, 29528, 323, 66298, 4851, 8624, 13, 4452, 11, 279, 33547, 5133, 1990, 75040, 323, 955, 220, 17, 20335, 42080, 374, 25420, 13, 19331, 1226, 13375, 264, 68102, 90380, 7187, 4007, 449, 828, 389, 220, 17337, 17, 20335, 12862, 13324, 320, 14622, 4325, 220, 2397, 13, 2437, 20903, 220, 24, 13, 2304, 8, 505, 279, 6498, 5843, 13138, 992, 19723, 315, 13381, 287, 13, 49281, 55798, 574, 32448, 304, 220, 1049, 19, 4235, 1049, 20, 1701, 279, 32828, 3907, 315, 7188, 11, 9853, 12167, 320, 52, 42235, 8, 49281, 55798, 25635, 13, 69835, 955, 220, 17, 20335, 5157, 1051, 32448, 505, 220, 1049, 21, 311, 220, 679, 22, 13, 97189, 1051, 1646, 839, 1701, 39760, 55272, 52642, 31649, 11, 43468, 369, 4754, 2389, 801, 388, 11, 902, 5343, 73151, 4512, 57565, 470, 269, 21301, 1385, 13, 18591, 362, 2860, 315, 220, 12815, 320, 21, 13, 2983, 11587, 13324, 8040, 955, 220, 17, 20335, 927, 279, 1833, 5352, 4261, 13, 49281, 55798, 574, 264, 5199, 62254, 315, 10672, 955, 220, 17, 20335, 320, 17526, 220, 16, 13, 2790, 26, 220, 2721, 4, 21351, 220, 16, 13, 868, 11, 220, 16, 13, 5833, 26, 281, 284, 220, 15, 13, 6726, 8, 9678, 315, 4325, 11, 1877, 11, 57978, 11, 12205, 11, 20149, 2704, 11, 7106, 5820, 11, 13200, 15652, 11, 47224, 11, 473, 65, 32, 220, 16, 66, 1174, 63308, 323, 41713, 8624, 13, 15903, 29060, 16914, 459, 15360, 1990, 75040, 323, 955, 220, 17, 20335, 42080, 320, 17526, 220, 16, 13, 3174, 26, 220, 2721, 4, 21351, 220, 16, 13, 2371, 11, 220, 16, 13, 1954, 26, 281, 284, 220, 15, 13, 21360, 705, 9678, 315, 84564, 13803, 11, 5496, 7636, 323, 3674, 31398, 13, 19048, 7636, 323, 3674, 31398, 1051, 539, 12207, 5938, 449, 955, 220, 17, 20335, 42080, 13, 1221, 24436, 14, 17324, 367, 49281, 55798, 374, 264, 5326, 8331, 369, 955, 220, 17, 20335, 13, 578, 24717, 16940, 420, 5133, 7293, 311, 387, 97298, 660, 13, 12441, 950, 8278, 22938, 389, 264, 47913, 30, 35106, 279, 4279, 21294, 29438, 49281, 55798, 374, 264, 8389, 20356, 430, 13980, 994, 459, 3927, 62822, 1924, 430, 872, 3674, 3966, 527, 539, 1694, 2322, 13, 1102, 27053, 459, 68331, 1990, 12974, 323, 5150, 3674, 12135, 510, 220, 16, 21087, 24507, 828, 4284, 430, 75040, 374, 264, 4279, 3217, 11, 449, 264, 18172, 315, 12884, 304, 279, 6560, 510, 220, 17, 2331, 323, 264, 4948, 315, 12884, 304, 279, 7427, 510, 220, 18, 2331, 13122, 8430, 40666, 7170, 13, 2684, 706, 1027, 7859, 3495, 10968, 389, 75040, 439, 264, 88060, 315, 2890, 13, 16197, 19415, 5893, 29150, 6029, 13533, 430, 75040, 374, 264, 62254, 315, 682, 12, 1593, 29528, 11, 19392, 430, 40666, 7931, 617, 264, 220, 1313, 4, 7191, 5326, 315, 4648, 994, 7863, 449, 2536, 2922, 263, 989, 7931, 510, 220, 19, 21087, 49281, 55798, 706, 264, 8389, 2515, 389, 41713, 2890, 323, 706, 1027, 5938, 449, 10672, 6969, 35, 510, 220, 20, 21087, 1115, 374, 315, 41961, 304, 955, 220, 17, 20335, 11, 439, 6969, 35, 374, 264, 21420, 86919, 315, 279, 3044, 323, 264, 6522, 5353, 315, 4648, 304, 420, 7187, 510, 220, 21, 21087, 1102, 374, 50434, 430, 60393, 466, 1245, 73151, 4512, 57565, 9547, 5938, 449, 75040, 1436, 17210, 311, 955, 220, 17, 20335, 510, 220, 22, 21087, 49281, 55798, 374, 5938, 449, 80043, 510, 220, 17, 1174, 220, 18, 2331, 323, 33048, 510, 220, 23, 10881, 2225, 315, 902, 527, 3682, 5326, 9547, 369, 955, 220, 17, 20335, 510, 220, 24, 21087, 15903, 11, 6029, 505, 3544, 90380, 41944, 7978, 15151, 430, 75040, 374, 5938, 2225, 5425, 22327, 750, 510, 220, 23, 2331, 323, 22199, 3210, 510, 220, 605, 2331, 449, 279, 41861, 28439, 13, 4452, 11, 7978, 4189, 1113, 75040, 449, 473, 65, 32, 220, 16, 66, 617, 1027, 2753, 13263, 510, 220, 806, 1174, 220, 717, 21087, 2057, 2457, 11, 912, 4007, 706, 22199, 3210, 5938, 75040, 449, 10672, 955, 220, 17, 20335, 11, 8051, 1070, 374, 6029, 315, 264, 5425, 97319, 15360, 510, 220, 1032, 1174, 220, 975, 21087, 4427, 7978, 617, 27313, 3674, 31398, 510, 220, 868, 1174, 220, 845, 1174, 220, 1114, 1174, 220, 972, 1174, 220, 777, 2331, 477, 5496, 7636, 510, 220, 1114, 1174, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 2331, 439, 5326, 9547, 369, 955, 220, 17, 20335, 13, 4452, 11, 433, 374, 3062, 311, 5296, 430, 75040, 374, 539, 69593, 449, 3674, 31398, 439, 433, 36716, 311, 279, 26617, 4367, 4856, 1109, 12472, 315, 3674, 13537, 510, 220, 16, 21087, 15903, 11, 1070, 374, 6029, 430, 75040, 323, 31398, 527, 2204, 34575, 5938, 449, 2890, 20124, 510, 220, 1419, 1174, 220, 1187, 21087, 578, 8857, 315, 7978, 47614, 3674, 31398, 510, 220, 868, 1174, 220, 845, 1174, 220, 972, 1174, 220, 777, 2331, 323, 5496, 7636, 510, 220, 1114, 1174, 220, 1691, 1174, 220, 1313, 2331, 439, 5326, 9547, 369, 20335, 617, 4745, 311, 23846, 459, 15360, 994, 4737, 4754, 2389, 13900, 9547, 320, 21470, 439, 2890, 71177, 8, 1139, 2759, 13, 578, 6063, 29637, 32101, 33954, 52577, 320, 22053, 1960, 287, 315, 50730, 323, 36007, 1821, 304, 9362, 6634, 822, 33945, 31974, 33954, 78, 43719, 21031, 1263, 88918, 69, 81085, 2234, 304, 2761, 17593, 5033, 91201, 320, 7489, 43719, 6401, 8483, 304, 279, 17593, 315, 5033, 91201, 8, 41944, 315, 927, 220, 4728, 15, 13324, 1766, 33547, 30257, 1990, 3674, 31398, 510, 220, 972, 2331, 323, 5496, 7636, 510, 220, 508, 2331, 449, 10672, 20335, 11, 719, 1193, 304, 8762, 13324, 13, 362, 810, 3293, 6492, 315, 420, 41944, 1766, 430, 8009, 3674, 4009, 24617, 11, 264, 6767, 315, 5133, 4367, 11, 7319, 279, 5326, 315, 955, 220, 17, 20335, 304, 3026, 1193, 510, 220, 914, 21087, 58603, 11, 420, 15360, 574, 9678, 315, 2225, 3674, 31398, 323, 5496, 7636, 13, 578, 1510, 4007, 743, 704, 311, 2686, 3508, 75040, 574, 264, 62254, 315, 10672, 955, 220, 17, 20335, 304, 264, 18740, 41944, 315, 12884, 20330, 927, 220, 1135, 1667, 5496, 304, 9635, 13, 1226, 1101, 20034, 311, 8720, 3508, 3674, 31398, 323, 5496, 7636, 1051, 5326, 9547, 369, 955, 220, 17, 20335, 13, 1666, 279, 5133, 1990, 75040, 323, 3674, 31398, 374, 12090, 311, 387, 7621, 311, 24070, 369, 9191, 1274, 510, 220, 1187, 10881, 584, 22601, 6509, 4147, 430, 75040, 11, 3674, 31398, 323, 5496, 7636, 1053, 43844, 9678, 6372, 389, 955, 220, 17, 20335, 5326, 13, 15903, 11, 433, 374, 3062, 311, 2980, 279, 5536, 315, 18710, 439, 264, 3284, 2389, 13900, 3977, 304, 279, 5133, 1990, 75040, 323, 955, 220, 17, 20335, 13, 30013, 3495, 15151, 430, 75040, 706, 264, 87298, 5133, 449, 18710, 510, 220, 1627, 21087, 46904, 374, 1101, 264, 3284, 38970, 1555, 902, 75040, 25949, 73151, 4512, 57565, 2890, 510, 220, 605, 10881, 449, 264, 3544, 2547, 315, 6029, 23377, 430, 42642, 7931, 527, 810, 4461, 311, 2274, 955, 220, 17, 20335, 1109, 1884, 2085, 18710, 510, 220, 1544, 21087, 16644, 420, 11, 584, 6646, 84564, 13803, 304, 1057, 29060, 13, 19331, 52878, 578, 4007, 1511, 828, 505, 279, 6498, 5843, 13138, 992, 19723, 315, 13381, 287, 320, 2818, 7934, 705, 264, 18740, 7090, 4007, 315, 12884, 20330, 220, 1135, 323, 9191, 5496, 304, 9635, 13, 2956, 4526, 6137, 304, 220, 1049, 17, 4235, 1049, 18, 320, 31498, 220, 16, 705, 449, 1833, 5352, 17301, 6160, 32331, 398, 510, 220, 1591, 21087, 10323, 85296, 48964, 323, 7274, 828, 527, 14890, 520, 1855, 12330, 323, 24156, 323, 41416, 24264, 828, 527, 14890, 520, 25631, 17301, 13, 14693, 950, 14765, 369, 469, 7416, 32, 574, 12457, 505, 279, 5165, 8483, 50281, 5475, 13, 2052, 13324, 3984, 16369, 14771, 13, 763, 279, 1510, 4007, 11, 584, 27313, 279, 15360, 1990, 75040, 17303, 520, 12330, 220, 17, 320, 1049, 19, 4235, 1049, 20, 26, 279, 1176, 12330, 304, 902, 75040, 574, 32448, 8, 323, 10672, 128257, 198, 128256, 78191, 198, 29986, 304, 279, 8486, 7923, 10448, 39073, 320, 1820, 8486, 315, 279, 7665, 10229, 369, 279, 19723, 315, 53689, 510, 36, 1950, 35, 9918, 279, 4007, 5039, 430, 433, 374, 279, 19821, 315, 4367, 13537, 449, 1274, 323, 539, 279, 6996, 315, 3729, 430, 56978, 279, 42080, 315, 955, 220, 17, 20335, 11, 23377, 430, 10695, 1274, 1376, 323, 3217, 6928, 12135, 1436, 387, 264, 5505, 5507, 304, 27344, 15174, 369, 955, 220, 17, 20335, 13, 578, 3135, 617, 25127, 304, 3177, 315, 3293, 14955, 430, 1274, 449, 20335, 527, 520, 7191, 5326, 315, 23069, 505, 20562, 12, 777, 13, 578, 4007, 15151, 430, 44387, 75040, 1253, 10383, 279, 4500, 315, 20335, 11, 23377, 279, 3217, 315, 51235, 1436, 13893, 24549, 1274, 596, 34104, 304, 420, 28522, 422, 279, 75040, 9731, 369, 1063, 892, 13, 49281, 55798, 13980, 994, 459, 3927, 62822, 1924, 430, 872, 3674, 3966, 527, 539, 1694, 2322, 323, 27053, 459, 68331, 1990, 12974, 323, 5150, 3674, 12135, 13, 362, 18172, 315, 12884, 304, 279, 6560, 323, 264, 4948, 315, 12884, 304, 279, 7427, 1934, 8430, 40666, 7170, 13, 2684, 374, 264, 7982, 2802, 304, 279, 3560, 315, 75040, 304, 2890, 323, 3766, 3495, 706, 5938, 75040, 449, 7319, 5326, 315, 4648, 323, 4851, 8624, 13, 1115, 374, 279, 1176, 4007, 311, 19874, 279, 3217, 315, 75040, 449, 3010, 42080, 315, 955, 220, 17, 20335, 13, 578, 4007, 30239, 828, 505, 279, 6498, 5843, 13138, 992, 19723, 13381, 287, 389, 220, 17337, 17, 12884, 20330, 220, 1135, 1667, 323, 927, 902, 574, 14890, 520, 3892, 3115, 505, 220, 1049, 17, 311, 220, 679, 22, 13, 2468, 279, 1212, 315, 828, 4526, 682, 13324, 1051, 1949, 315, 20335, 323, 1047, 4725, 5990, 315, 6680, 34323, 13, 578, 4007, 8710, 430, 927, 264, 4261, 315, 220, 717, 1667, 220, 12815, 1274, 8040, 955, 220, 17, 20335, 13, 323, 279, 2237, 315, 75040, 17303, 520, 279, 1212, 315, 828, 4526, 574, 264, 5199, 62254, 315, 279, 42080, 315, 955, 220, 17, 20335, 3010, 389, 304, 2324, 13, 1115, 5133, 14958, 35539, 994, 24043, 369, 20149, 11, 13200, 11, 4785, 11, 2237, 315, 6680, 34323, 11, 1579, 6680, 7410, 323, 41713, 8624, 13, 578, 15360, 574, 1101, 9678, 315, 18710, 11, 5496, 7636, 323, 3674, 31398, 13, 30982, 3229, 2999, 13, 42893, 473, 5827, 83, 505, 279, 10181, 315, 69244, 11, 36673, 612, 85879, 320, 43899, 4505, 45, 8, 6342, 596, 9304, 7295, 1071, 25, 330, 791, 4007, 5039, 264, 3831, 5133, 1990, 75040, 323, 279, 3010, 42080, 315, 955, 220, 17, 20335, 13, 3639, 374, 8104, 21933, 374, 430, 420, 5133, 374, 22514, 1524, 994, 9547, 430, 527, 3062, 304, 20335, 4500, 527, 4529, 1139, 2759, 1778, 439, 20149, 11, 13200, 23730, 323, 6680, 34323, 439, 1664, 439, 10723, 2890, 9547, 1778, 439, 18710, 13, 578, 4007, 1101, 32216, 264, 2867, 30296, 1990, 75040, 323, 3674, 31398, 304, 430, 31398, 477, 5496, 7636, 1587, 539, 7168, 955, 220, 17, 20335, 20444, 75040, 11, 902, 374, 4613, 555, 264, 1732, 596, 4367, 315, 12135, 11, 1587, 13, 3005, 8738, 25, 330, 40, 3782, 709, 449, 279, 4623, 369, 279, 3495, 2391, 6560, 51235, 369, 279, 20562, 12, 777, 28522, 439, 358, 6244, 15098, 8010, 323, 8173, 304, 1268, 75040, 1253, 7958, 1057, 2890, 11, 5423, 439, 433, 374, 4461, 430, 1690, 810, 1274, 1051, 25051, 420, 5107, 20356, 2391, 420, 4261, 1210, 10771, 311, 279, 4007, 264, 3284, 24156, 2944, 4920, 279, 15360, 1990, 75040, 323, 955, 220, 17, 20335, 1436, 387, 279, 5536, 315, 6926, 75040, 389, 279, 24156, 1887, 8647, 369, 8631, 11, 902, 11, 927, 892, 22223, 279, 2547, 323, 12992, 279, 5326, 369, 20335, 13, 330, 2746, 279, 8430, 315, 75040, 9221, 21249, 1359, 11497, 2999, 13, 473, 5827, 83, 13, 330, 12487, 18254, 499, 2351, 65792, 279, 8631, 1887, 323, 927, 892, 430, 11767, 311, 10051, 323, 18036, 389, 701, 2547, 323, 1884, 8389, 4442, 304, 8631, 14228, 34458, 1253, 387, 10815, 311, 955, 220, 17, 20335, 4500, 1210, 13596, 16540, 369, 279, 14955, 1436, 387, 50183, 304, 1057, 7422, 430, 1253, 22313, 6426, 279, 15360, 1990, 75040, 323, 20335, 439, 994, 1274, 2733, 40666, 11, 814, 1755, 1274, 690, 14085, 311, 1124, 48291, 902, 3727, 433, 810, 5107, 311, 1376, 1695, 12135, 13, 220, 128257, 198 ]

2,066

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Defects in strongly correlated materials such as V 2 O 3 play influential roles on their electrical properties. Understanding the defects' structure is of paramount importance. In this project, we investigate defect structures in V 2 O 3 grown via a flux method. We use AFM to see surface features in several large flake-like particles that exhibit characteristics of spiral growth. We also use Bragg coherent diffractive imaging (BCDI) to probe in 3 dimensions a smaller particle without flake-like morphology and note an absence of the pure screw dislocation characteristic of spiral growth. We identified and measured several defects by comparing the observed local displacement of the crystal, measured via BCDI to well-known models of the displacement around defects in the crystal. We identified two partial dislocations in the crystal. We discuss how defects of different types influence the morphology of V 2 O 3 crystals grown via a flux method. This article is part of the themed collection: Nanomaterials Transition metal oxides such as vanadium oxides are interesting for a variety of technical applications, from electrochemical anodes 1,2 to unique optical applications 3,4 and supercapacitors. 5 Vanadium( iii ) oxide (V 2 O 3 ) particularly has been of interest due to its temperature driven first-order metal–insulator phase transition that changes a variety of electronic and optical properties. 6 The properties of vanadium oxide systems have also been shown to strongly depend on morphology and growth conditions, making it a versatile material for many applications. 7,8 Defects have been shown to heavily influence a variety of both mechanical and electronic properties of nanoscale materials, which in turn influences their performance in devices. 9–13 In particular, dislocations – while uncommon in nanoparticles – have been shown to affect: lithiation in nanoparticle anodes in Li-ion batteries, 14 optical performance of light emitting diodes, 9 and mechanical deformation of nanostructures. 11,15 The combination of potential nanoscale device application and the dependence of device performance on the type and density of defects results in a need to further understand the formation and control of defects in vanadium oxides, and how defects can influence particle characteristic such as morphology or physical properties. In this paper we demonstrate a flux method for growing V 2 O 3 crystallites. We use transmission electron microscopy (TEM) to analyze the crystal orientation of the crystallites. We use Bragg coherent diffractive imaging (BCDI) to retrieve high-resolution volumetric information about a crystallite showing a significantly different shape than the flake-like particles observed in TEM and optical microscopy. With the BCDI measurements we identified a few partial dislocations with mixed screw and edge character. BCDI is a technique that circumvents the phase problem of X-ray analytics by over-sampling the diffraction pattern to reconstruct the phase of the diffracted X-rays. 14,16,17 It is used to get high-resolution volumetric information about strain and lattice distortion. In BCDI one reconstructs the phase of the light scattered by a set of crystallographic planes satisfying the Bragg condition. This recovered phase contains information about distortions to the crystal lattice in the direction normal to the diffracting planes. BCDI has been used extensively to map Bragg electronic density, displacement, ferroelectric domains and strain within the volume of crystals with nanoscale resolution; 18–25 the best reported resolution to date is 4–9 nm. 26 It has been shown that BCDI can detect signatures of defects by measuring the disruptions to the long-range order of the crystal. 27–30 By examining these long-range effects it is possible to identify defects below the resolution limit of the technique, such as dislocation cores. We use BCDI in conjunction with AFM, TEM, and optical microscopy to analyze defects in V 2 O 3 crystallites grown via flux method. We report on the nature of defects in two different crystallites with different shapes: a flake-like crystallite with features typical of crystals grown via a screw dislocation driven growth mechanism, 31,32 and a smaller particle showing a more complex defect structure, featuring several mixed dislocations. We argue that differences in morphology of these particles are potentially a consequence of the different defect structures of the crystals. 1 Methods V 2 O 3 crystals were grown by flux method. A 5 ml graphite crucible containing 0.2 g of V 2 O 5 powder and 3.28 g of anhydrous KCl (the mole ratio of V 2 O 5 : KCl is 1 : 10) was placed in an alumina tube inside a furnace. The tube was evacuated to 0.1 Torr and then filled with H 2 (5%)/Ar gas. A steady flow of 50 sccm H 2 (5%)/Ar was maintained throughout the growth at ambient pressure. The crucible was heated at 20 °C/min to 900 °C and kept for 10 hours and then lowered at 0.5 °C/min to ambient. After growth, the contents of the crucible were washed in water (to dissolve the KCl) and black shiny crystals were obtained. The as-grown crystals were analyzed with optical microscopy, AFM, and BCDI. The optical microscopy was performed using a Nikon Eclipse Ti–S inverted optical microscope to determine the approximate size and shape of the crystals. The AFM measurements were conducted with a MultiModeTM AFM in order to study the topography of the particles. The BCDI was performed at the I13-1 beamline of the Diamond Light Source in order to more closely investigate defects indicated by the AFM measurements. The diffraction patterns used for BCDI were collected as illustrated in Fig. 1 . A monochromatic beam of energy 11.0 keV and bandwidth (Δ E / E ) = 1 × 10 −4 was focused onto our sample with randomly dispersed (00l)-oriented crystallites. A Fresnel zone plate with diameter of 400 μm and outer zone width of 150 nm was used to focus the beam. The sample was positioned slightly defocused and downstream of the focusing spot of the Fresnel zone plate, and the final spot size was approximately 2 μm full-width at half-maximum and carried a divergence of approximately 50 × 25 μrad. The detector was an Excalibur photon counting", "role": "user" }, { "content": "Researchers led by Edwin Fohtung, an associate professor of materials science and engineering at Rensselaer Polytechnic Institute, have developed a new technique for revealing defects in nanostructured vanadium oxide, a widely used transition metal with many potential applications including electrochemical anodes, optical applications, and supercapacitors. In the research—which was published in an article in the Royal Chemical Society journal CrystEngComm, and also featured on the cover of the edition—the team detailed a lensless microscopy technique to capture individual defects embedded in vanadium oxide nanoflakes. \"These observations could help explain the origin of defects in structure, crystallinity, or composition gradients observed near grain boundaries in other thin-film or flake technologies,\" said Fohtung, an expert in novel synchrotron scattering and imaging techniques. \"We believe that our work has the potential to change how we view the growth and non-destructive three-dimensional imaging of nanomaterials.\" Vanadium oxide is currently used in many technological fields such as energy storage, and can also be used in constructing field-effect transistors owing to metal insulating transition behavior that can be adjusted with an electric field. However, strain and defects in the material can alter its functionality, creating the need for non-destructive techniques to detect those potential flaws. The team developed a technique based on coherent X-ray diffraction imaging. This technique relies on a type of circular particle accelerator known as a synchrotron. Synchrotrons work by accelerating electrons through sequences of magnets until they reach almost the speed of light. These fast-moving electrons produce very bright intense light, predominantly in the X-ray region. This synchrotron light, as it is named, is millions of times brighter than light produced from conventional sources and 10 billion times brighter than the sun. Fohtung and his students have successfully used this light to develop techniques and capture minute matter such as atoms and molecules and now defects. When used to probe crystalline materials, this technique is known as Bragg coherent diffraction imaging (BCDI). In their research, the team used a BCDI approach to reveal nanoscale properties of electron densities in crystals, including strain and lattice defects. Fohtung worked closely with Jian Shi, a Rensselaer associate professor of materials science and engineering. They were joined in the research on \"Imaging defects in vanadium(III) oxide nanocrystals using Bragg coherent diffractive imaging\" by Zachary Barringer, Jie Jiang, Xiaowen Shi, and Elijah Schold at Rensselaer, as well as researchers at Carnegie Mellon University. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Defects in strongly correlated materials such as V 2 O 3 play influential roles on their electrical properties. Understanding the defects' structure is of paramount importance. In this project, we investigate defect structures in V 2 O 3 grown via a flux method. We use AFM to see surface features in several large flake-like particles that exhibit characteristics of spiral growth. We also use Bragg coherent diffractive imaging (BCDI) to probe in 3 dimensions a smaller particle without flake-like morphology and note an absence of the pure screw dislocation characteristic of spiral growth. We identified and measured several defects by comparing the observed local displacement of the crystal, measured via BCDI to well-known models of the displacement around defects in the crystal. We identified two partial dislocations in the crystal. We discuss how defects of different types influence the morphology of V 2 O 3 crystals grown via a flux method. This article is part of the themed collection: Nanomaterials Transition metal oxides such as vanadium oxides are interesting for a variety of technical applications, from electrochemical anodes 1,2 to unique optical applications 3,4 and supercapacitors. 5 Vanadium( iii ) oxide (V 2 O 3 ) particularly has been of interest due to its temperature driven first-order metal–insulator phase transition that changes a variety of electronic and optical properties. 6 The properties of vanadium oxide systems have also been shown to strongly depend on morphology and growth conditions, making it a versatile material for many applications. 7,8 Defects have been shown to heavily influence a variety of both mechanical and electronic properties of nanoscale materials, which in turn influences their performance in devices. 9–13 In particular, dislocations – while uncommon in nanoparticles – have been shown to affect: lithiation in nanoparticle anodes in Li-ion batteries, 14 optical performance of light emitting diodes, 9 and mechanical deformation of nanostructures. 11,15 The combination of potential nanoscale device application and the dependence of device performance on the type and density of defects results in a need to further understand the formation and control of defects in vanadium oxides, and how defects can influence particle characteristic such as morphology or physical properties. In this paper we demonstrate a flux method for growing V 2 O 3 crystallites. We use transmission electron microscopy (TEM) to analyze the crystal orientation of the crystallites. We use Bragg coherent diffractive imaging (BCDI) to retrieve high-resolution volumetric information about a crystallite showing a significantly different shape than the flake-like particles observed in TEM and optical microscopy. With the BCDI measurements we identified a few partial dislocations with mixed screw and edge character. BCDI is a technique that circumvents the phase problem of X-ray analytics by over-sampling the diffraction pattern to reconstruct the phase of the diffracted X-rays. 14,16,17 It is used to get high-resolution volumetric information about strain and lattice distortion. In BCDI one reconstructs the phase of the light scattered by a set of crystallographic planes satisfying the Bragg condition. This recovered phase contains information about distortions to the crystal lattice in the direction normal to the diffracting planes. BCDI has been used extensively to map Bragg electronic density, displacement, ferroelectric domains and strain within the volume of crystals with nanoscale resolution; 18–25 the best reported resolution to date is 4–9 nm. 26 It has been shown that BCDI can detect signatures of defects by measuring the disruptions to the long-range order of the crystal. 27–30 By examining these long-range effects it is possible to identify defects below the resolution limit of the technique, such as dislocation cores. We use BCDI in conjunction with AFM, TEM, and optical microscopy to analyze defects in V 2 O 3 crystallites grown via flux method. We report on the nature of defects in two different crystallites with different shapes: a flake-like crystallite with features typical of crystals grown via a screw dislocation driven growth mechanism, 31,32 and a smaller particle showing a more complex defect structure, featuring several mixed dislocations. We argue that differences in morphology of these particles are potentially a consequence of the different defect structures of the crystals. 1 Methods V 2 O 3 crystals were grown by flux method. A 5 ml graphite crucible containing 0.2 g of V 2 O 5 powder and 3.28 g of anhydrous KCl (the mole ratio of V 2 O 5 : KCl is 1 : 10) was placed in an alumina tube inside a furnace. The tube was evacuated to 0.1 Torr and then filled with H 2 (5%)/Ar gas. A steady flow of 50 sccm H 2 (5%)/Ar was maintained throughout the growth at ambient pressure. The crucible was heated at 20 °C/min to 900 °C and kept for 10 hours and then lowered at 0.5 °C/min to ambient. After growth, the contents of the crucible were washed in water (to dissolve the KCl) and black shiny crystals were obtained. The as-grown crystals were analyzed with optical microscopy, AFM, and BCDI. The optical microscopy was performed using a Nikon Eclipse Ti–S inverted optical microscope to determine the approximate size and shape of the crystals. The AFM measurements were conducted with a MultiModeTM AFM in order to study the topography of the particles. The BCDI was performed at the I13-1 beamline of the Diamond Light Source in order to more closely investigate defects indicated by the AFM measurements. The diffraction patterns used for BCDI were collected as illustrated in Fig. 1 . A monochromatic beam of energy 11.0 keV and bandwidth (Δ E / E ) = 1 × 10 −4 was focused onto our sample with randomly dispersed (00l)-oriented crystallites. A Fresnel zone plate with diameter of 400 μm and outer zone width of 150 nm was used to focus the beam. The sample was positioned slightly defocused and downstream of the focusing spot of the Fresnel zone plate, and the final spot size was approximately 2 μm full-width at half-maximum and carried a divergence of approximately 50 × 25 μrad. The detector was an Excalibur photon counting<|im_end|> <|im_start|>assistant Researchers led by Edwin Fohtung, an associate professor of materials science and engineering at Rensselaer Polytechnic Institute, have developed a new technique for revealing defects in nanostructured vanadium oxide, a widely used transition metal with many potential applications including electrochemical anodes, optical applications, and supercapacitors. In the research—which was published in an article in the Royal Chemical Society journal CrystEngComm, and also featured on the cover of the edition—the team detailed a lensless microscopy technique to capture individual defects embedded in vanadium oxide nanoflakes. "These observations could help explain the origin of defects in structure, crystallinity, or composition gradients observed near grain boundaries in other thin-film or flake technologies," said Fohtung, an expert in novel synchrotron scattering and imaging techniques. "We believe that our work has the potential to change how we view the growth and non-destructive three-dimensional imaging of nanomaterials." Vanadium oxide is currently used in many technological fields such as energy storage, and can also be used in constructing field-effect transistors owing to metal insulating transition behavior that can be adjusted with an electric field. However, strain and defects in the material can alter its functionality, creating the need for non-destructive techniques to detect those potential flaws. The team developed a technique based on coherent X-ray diffraction imaging. This technique relies on a type of circular particle accelerator known as a synchrotron. Synchrotrons work by accelerating electrons through sequences of magnets until they reach almost the speed of light. These fast-moving electrons produce very bright intense light, predominantly in the X-ray region. This synchrotron light, as it is named, is millions of times brighter than light produced from conventional sources and 10 billion times brighter than the sun. Fohtung and his students have successfully used this light to develop techniques and capture minute matter such as atoms and molecules and now defects. When used to probe crystalline materials, this technique is known as Bragg coherent diffraction imaging (BCDI). In their research, the team used a BCDI approach to reveal nanoscale properties of electron densities in crystals, including strain and lattice defects. Fohtung worked closely with Jian Shi, a Rensselaer associate professor of materials science and engineering. They were joined in the research on "Imaging defects in vanadium(III) oxide nanocrystals using Bragg coherent diffractive imaging" by Zachary Barringer, Jie Jiang, Xiaowen Shi, and Elijah Schold at Rensselaer, as well as researchers at Carnegie Mellon University. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 3979, 115192, 304, 16917, 49393, 7384, 1778, 439, 650, 220, 17, 507, 220, 18, 1514, 32549, 13073, 389, 872, 20314, 6012, 13, 46551, 279, 42655, 6, 6070, 374, 315, 74510, 12939, 13, 763, 420, 2447, 11, 584, 19874, 23011, 14726, 304, 650, 220, 17, 507, 220, 18, 15042, 4669, 264, 31405, 1749, 13, 1226, 1005, 20479, 44, 311, 1518, 7479, 4519, 304, 3892, 3544, 1344, 731, 12970, 19252, 430, 31324, 17910, 315, 42197, 6650, 13, 1226, 1101, 1005, 3320, 16094, 56887, 1422, 1658, 3104, 32758, 320, 5002, 18091, 8, 311, 22477, 304, 220, 18, 15696, 264, 9333, 19320, 2085, 1344, 731, 12970, 79612, 323, 5296, 459, 19821, 315, 279, 10748, 22733, 834, 2588, 29683, 315, 42197, 6650, 13, 1226, 11054, 323, 17303, 3892, 42655, 555, 27393, 279, 13468, 2254, 44153, 315, 279, 26110, 11, 17303, 4669, 426, 6620, 40, 311, 1664, 22015, 4211, 315, 279, 44153, 2212, 42655, 304, 279, 26110, 13, 1226, 11054, 1403, 7276, 834, 32409, 304, 279, 26110, 13, 1226, 4358, 1268, 42655, 315, 2204, 4595, 10383, 279, 79612, 315, 650, 220, 17, 507, 220, 18, 48473, 15042, 4669, 264, 31405, 1749, 13, 1115, 4652, 374, 961, 315, 279, 49644, 4526, 25, 33242, 316, 2229, 82, 38821, 9501, 19488, 3422, 1778, 439, 5355, 13786, 19488, 3422, 527, 7185, 369, 264, 8205, 315, 11156, 8522, 11, 505, 25396, 32056, 459, 2601, 220, 16, 11, 17, 311, 5016, 29393, 8522, 220, 18, 11, 19, 323, 2307, 11600, 582, 12170, 13, 220, 20, 13000, 13786, 7, 63193, 883, 51180, 320, 53, 220, 17, 507, 220, 18, 883, 8104, 706, 1027, 315, 2802, 4245, 311, 1202, 9499, 16625, 1176, 24747, 9501, 4235, 1354, 10733, 10474, 9320, 430, 4442, 264, 8205, 315, 14683, 323, 29393, 6012, 13, 220, 21, 578, 6012, 315, 5355, 13786, 51180, 6067, 617, 1101, 1027, 6982, 311, 16917, 6904, 389, 79612, 323, 6650, 4787, 11, 3339, 433, 264, 33045, 3769, 369, 1690, 8522, 13, 220, 22, 11, 23, 3979, 115192, 617, 1027, 6982, 311, 17345, 10383, 264, 8205, 315, 2225, 22936, 323, 14683, 6012, 315, 20622, 437, 2296, 7384, 11, 902, 304, 2543, 34453, 872, 5178, 304, 7766, 13, 220, 24, 4235, 1032, 763, 4040, 11, 834, 32409, 1389, 1418, 41296, 304, 94753, 1389, 617, 1027, 6982, 311, 7958, 25, 46282, 7246, 304, 76307, 7203, 459, 2601, 304, 14851, 80846, 27360, 11, 220, 975, 29393, 5178, 315, 3177, 90556, 1891, 2601, 11, 220, 24, 323, 22936, 91621, 315, 51593, 47194, 13, 220, 806, 11, 868, 578, 10824, 315, 4754, 20622, 437, 2296, 3756, 3851, 323, 279, 44393, 315, 3756, 5178, 389, 279, 955, 323, 17915, 315, 42655, 3135, 304, 264, 1205, 311, 4726, 3619, 279, 18488, 323, 2585, 315, 42655, 304, 5355, 13786, 19488, 3422, 11, 323, 1268, 42655, 649, 10383, 19320, 29683, 1778, 439, 79612, 477, 7106, 6012, 13, 763, 420, 5684, 584, 20461, 264, 31405, 1749, 369, 7982, 650, 220, 17, 507, 220, 18, 64568, 3695, 13, 1226, 1005, 18874, 17130, 92914, 320, 21695, 8, 311, 24564, 279, 26110, 17140, 315, 279, 64568, 3695, 13, 1226, 1005, 3320, 16094, 56887, 1422, 1658, 3104, 32758, 320, 5002, 18091, 8, 311, 17622, 1579, 64036, 63920, 16743, 2038, 922, 264, 64568, 635, 9204, 264, 12207, 2204, 6211, 1109, 279, 1344, 731, 12970, 19252, 13468, 304, 76770, 323, 29393, 92914, 13, 3161, 279, 426, 6620, 40, 22323, 584, 11054, 264, 2478, 7276, 834, 32409, 449, 9709, 22733, 323, 6964, 3752, 13, 426, 6620, 40, 374, 264, 15105, 430, 10408, 48764, 279, 10474, 3575, 315, 1630, 30630, 28975, 555, 927, 1355, 30809, 279, 3722, 16597, 5497, 311, 44928, 279, 10474, 315, 279, 1422, 1658, 22955, 1630, 82817, 13, 220, 975, 11, 845, 11, 1114, 1102, 374, 1511, 311, 636, 1579, 64036, 63920, 16743, 2038, 922, 26800, 323, 55372, 50971, 13, 763, 426, 6620, 40, 832, 44928, 82, 279, 10474, 315, 279, 3177, 38067, 555, 264, 743, 315, 26110, 848, 79173, 25761, 37154, 279, 3320, 16094, 3044, 13, 1115, 26403, 10474, 5727, 2038, 922, 70584, 919, 311, 279, 26110, 55372, 304, 279, 5216, 4725, 311, 279, 1422, 1658, 36022, 25761, 13, 426, 6620, 40, 706, 1027, 1511, 42817, 311, 2472, 3320, 16094, 14683, 17915, 11, 44153, 11, 18728, 299, 64465, 31576, 323, 26800, 2949, 279, 8286, 315, 48473, 449, 20622, 437, 2296, 11175, 26, 220, 972, 4235, 914, 279, 1888, 5068, 11175, 311, 2457, 374, 220, 19, 4235, 24, 26807, 13, 220, 1627, 1102, 706, 1027, 6982, 430, 426, 6620, 40, 649, 11388, 33728, 315, 42655, 555, 30090, 279, 98057, 311, 279, 1317, 31608, 2015, 315, 279, 26110, 13, 220, 1544, 4235, 966, 3296, 38936, 1521, 1317, 31608, 6372, 433, 374, 3284, 311, 10765, 42655, 3770, 279, 11175, 4017, 315, 279, 15105, 11, 1778, 439, 834, 2588, 36804, 13, 1226, 1005, 426, 6620, 40, 304, 32546, 449, 20479, 44, 11, 76770, 11, 323, 29393, 92914, 311, 24564, 42655, 304, 650, 220, 17, 507, 220, 18, 64568, 3695, 15042, 4669, 31405, 1749, 13, 1226, 1934, 389, 279, 7138, 315, 42655, 304, 1403, 2204, 64568, 3695, 449, 2204, 21483, 25, 264, 1344, 731, 12970, 64568, 635, 449, 4519, 14595, 315, 48473, 15042, 4669, 264, 22733, 834, 2588, 16625, 6650, 17383, 11, 220, 2148, 11, 843, 323, 264, 9333, 19320, 9204, 264, 810, 6485, 23011, 6070, 11, 16850, 3892, 9709, 834, 32409, 13, 1226, 18046, 430, 12062, 304, 79612, 315, 1521, 19252, 527, 13893, 264, 29774, 315, 279, 2204, 23011, 14726, 315, 279, 48473, 13, 220, 16, 19331, 650, 220, 17, 507, 220, 18, 48473, 1051, 15042, 555, 31405, 1749, 13, 362, 220, 20, 16116, 95273, 15131, 1260, 8649, 220, 15, 13, 17, 342, 315, 650, 220, 17, 507, 220, 20, 17138, 323, 220, 18, 13, 1591, 342, 315, 459, 8671, 67, 27620, 735, 5176, 320, 1820, 35751, 11595, 315, 650, 220, 17, 507, 220, 20, 551, 735, 5176, 374, 220, 16, 551, 220, 605, 8, 574, 9277, 304, 459, 34060, 2259, 14019, 4871, 264, 55564, 13, 578, 14019, 574, 63358, 311, 220, 15, 13, 16, 8611, 81, 323, 1243, 10409, 449, 473, 220, 17, 320, 20, 4, 5738, 7098, 6962, 13, 362, 24981, 6530, 315, 220, 1135, 274, 641, 76, 473, 220, 17, 320, 20, 4, 5738, 7098, 574, 18908, 6957, 279, 6650, 520, 35288, 7410, 13, 578, 15131, 1260, 574, 32813, 520, 220, 508, 37386, 34, 45273, 311, 220, 7467, 37386, 34, 323, 8774, 369, 220, 605, 4207, 323, 1243, 39920, 520, 220, 15, 13, 20, 37386, 34, 45273, 311, 35288, 13, 4740, 6650, 11, 279, 8970, 315, 279, 15131, 1260, 1051, 38593, 304, 3090, 320, 998, 73739, 279, 735, 5176, 8, 323, 3776, 42299, 48473, 1051, 12457, 13, 578, 439, 2427, 4935, 48473, 1051, 30239, 449, 29393, 92914, 11, 20479, 44, 11, 323, 426, 6620, 40, 13, 578, 29393, 92914, 574, 10887, 1701, 264, 63252, 37223, 23126, 4235, 50, 47801, 29393, 73757, 311, 8417, 279, 45968, 1404, 323, 6211, 315, 279, 48473, 13, 578, 20479, 44, 22323, 1051, 13375, 449, 264, 17896, 3720, 22809, 20479, 44, 304, 2015, 311, 4007, 279, 1948, 5814, 315, 279, 19252, 13, 578, 426, 6620, 40, 574, 10887, 520, 279, 358, 1032, 12, 16, 24310, 1074, 315, 279, 25328, 8828, 8922, 304, 2015, 311, 810, 15499, 19874, 42655, 16717, 555, 279, 20479, 44, 22323, 13, 578, 3722, 16597, 12912, 1511, 369, 426, 6620, 40, 1051, 14890, 439, 36762, 304, 23966, 13, 220, 16, 662, 362, 1647, 5059, 99866, 24310, 315, 4907, 220, 806, 13, 15, 2004, 53, 323, 34494, 320, 101561, 469, 611, 469, 883, 284, 220, 16, 25800, 220, 605, 25173, 19, 574, 10968, 8800, 1057, 6205, 449, 27716, 77810, 320, 410, 75, 7435, 33536, 64568, 3695, 13, 362, 60750, 8301, 10353, 12235, 449, 23899, 315, 220, 3443, 33983, 76, 323, 16335, 10353, 2430, 315, 220, 3965, 26807, 574, 1511, 311, 5357, 279, 24310, 13, 578, 6205, 574, 35328, 10284, 711, 21012, 323, 52452, 315, 279, 21760, 7858, 315, 279, 60750, 8301, 10353, 12235, 11, 323, 279, 1620, 7858, 1404, 574, 13489, 220, 17, 33983, 76, 2539, 9531, 520, 4376, 45173, 3375, 323, 11953, 264, 82258, 315, 13489, 220, 1135, 25800, 220, 914, 33983, 13584, 13, 578, 32314, 574, 459, 1398, 5531, 86298, 69010, 26060, 128257, 198, 128256, 78191, 198, 60210, 6197, 555, 76249, 32757, 427, 2234, 11, 459, 22712, 14561, 315, 7384, 8198, 323, 15009, 520, 432, 729, 82, 8458, 261, 19294, 26522, 292, 10181, 11, 617, 8040, 264, 502, 15105, 369, 31720, 42655, 304, 51593, 52243, 5355, 13786, 51180, 11, 264, 13882, 1511, 9320, 9501, 449, 1690, 4754, 8522, 2737, 25396, 32056, 459, 2601, 11, 29393, 8522, 11, 323, 2307, 11600, 582, 12170, 13, 763, 279, 3495, 50004, 574, 4756, 304, 459, 4652, 304, 279, 16591, 36424, 13581, 8486, 4656, 599, 4198, 18461, 11, 323, 1101, 15109, 389, 279, 3504, 315, 279, 14002, 22416, 2128, 11944, 264, 18848, 1752, 92914, 15105, 311, 12602, 3927, 42655, 23711, 304, 5355, 13786, 51180, 20622, 1073, 75, 2094, 13, 330, 9673, 24654, 1436, 1520, 10552, 279, 6371, 315, 42655, 304, 6070, 11, 64568, 13797, 11, 477, 18528, 53249, 13468, 3221, 24875, 23546, 304, 1023, 15792, 2269, 9672, 477, 1344, 731, 14645, 1359, 1071, 32757, 427, 2234, 11, 459, 6335, 304, 11775, 6925, 331, 299, 35785, 72916, 323, 32758, 12823, 13, 330, 1687, 4510, 430, 1057, 990, 706, 279, 4754, 311, 2349, 1268, 584, 1684, 279, 6650, 323, 2536, 97322, 535, 2380, 33520, 32758, 315, 20622, 316, 2229, 82, 1210, 13000, 13786, 51180, 374, 5131, 1511, 304, 1690, 30116, 5151, 1778, 439, 4907, 5942, 11, 323, 649, 1101, 387, 1511, 304, 50453, 2115, 23937, 1380, 380, 1105, 56612, 311, 9501, 1672, 15853, 9320, 7865, 430, 649, 387, 24257, 449, 459, 9249, 2115, 13, 4452, 11, 26800, 323, 42655, 304, 279, 3769, 649, 11857, 1202, 15293, 11, 6968, 279, 1205, 369, 2536, 97322, 535, 12823, 311, 11388, 1884, 4754, 41859, 13, 578, 2128, 8040, 264, 15105, 3196, 389, 56887, 1630, 30630, 3722, 16597, 32758, 13, 1115, 15105, 34744, 389, 264, 955, 315, 28029, 19320, 65456, 3967, 439, 264, 6925, 331, 299, 35785, 13, 24028, 331, 299, 376, 2439, 990, 555, 69741, 57678, 1555, 24630, 315, 73780, 3156, 814, 5662, 4661, 279, 4732, 315, 3177, 13, 4314, 5043, 86572, 57678, 8356, 1633, 10107, 19428, 3177, 11, 47904, 304, 279, 1630, 30630, 5654, 13, 1115, 6925, 331, 299, 35785, 3177, 11, 439, 433, 374, 7086, 11, 374, 11990, 315, 3115, 53657, 1109, 3177, 9124, 505, 21349, 8336, 323, 220, 605, 7239, 3115, 53657, 1109, 279, 7160, 13, 32757, 427, 2234, 323, 813, 4236, 617, 7946, 1511, 420, 3177, 311, 2274, 12823, 323, 12602, 9568, 5030, 1778, 439, 33299, 323, 35715, 323, 1457, 42655, 13, 3277, 1511, 311, 22477, 64568, 483, 7384, 11, 420, 15105, 374, 3967, 439, 3320, 16094, 56887, 3722, 16597, 32758, 320, 5002, 18091, 570, 763, 872, 3495, 11, 279, 2128, 1511, 264, 426, 6620, 40, 5603, 311, 16805, 20622, 437, 2296, 6012, 315, 17130, 90816, 304, 48473, 11, 2737, 26800, 323, 55372, 42655, 13, 32757, 427, 2234, 6575, 15499, 449, 88404, 41804, 11, 264, 432, 729, 82, 8458, 261, 22712, 14561, 315, 7384, 8198, 323, 15009, 13, 2435, 1051, 11096, 304, 279, 3495, 389, 330, 1453, 4210, 42655, 304, 5355, 13786, 7, 23440, 8, 51180, 20622, 4309, 92475, 1701, 3320, 16094, 56887, 1422, 1658, 3104, 32758, 1, 555, 39315, 661, 32817, 5248, 11, 622, 648, 61922, 11, 41235, 363, 268, 41804, 11, 323, 83692, 5124, 820, 520, 432, 729, 82, 8458, 261, 11, 439, 1664, 439, 12074, 520, 64373, 88487, 3907, 13, 220, 128257, 198 ]

1,920

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Post-traumatic stress disorder (PTSD) impacts many veterans and active duty soldiers, but diagnosis can be problematic due to biases in self-disclosure of symptoms, stigma within military populations, and limitations identifying those at risk. Prior studies suggest that PTSD may be a systemic illness, affecting not just the brain, but the entire body. Therefore, disease signals likely span multiple biological domains, including genes, proteins, cells, tissues, and organism-level physiological changes. Identification of these signals could aid in diagnostics, treatment decision-making, and risk evaluation. In the search for PTSD diagnostic biomarkers, we ascertained over one million molecular, cellular, physiological, and clinical features from three cohorts of male veterans. In a discovery cohort of 83 warzone-related PTSD cases and 82 warzone-exposed controls, we identified a set of 343 candidate biomarkers. These candidate biomarkers were selected from an integrated approach using (1) data-driven methods, including Support Vector Machine with Recursive Feature Elimination and other standard or published methodologies, and (2) hypothesis-driven approaches, using previous genetic studies for polygenic risk, or other PTSD-related literature. After reassessment of ~30% of these participants, we refined this set of markers from 343 to 28, based on their performance and ability to track changes in phenotype over time. The final diagnostic panel of 28 features was validated in an independent cohort (26 cases, 26 controls) with good performance (AUC = 0.80, 81% accuracy, 85% sensitivity, and 77% specificity). The identification and validation of this diverse diagnostic panel represents a powerful and novel approach to improve accuracy and reduce bias in diagnosing combat-related PTSD. Introduction Combat-related post-traumatic stress disorder (PTSD) has a lifetime prevalence of between 10.1%–30.9% in U.S. veterans of the Vietnam and subsequent conflicts, including the Iraq and Afghanistan wars [ 1 , 2 , 3 , 4 ]. PTSD is precipitated by experiencing or witnessing actual or threatened death, serious injury, or violence, and has symptoms that include re-experiencing, avoidance, negative thoughts, or moods associated with the traumatic event and hyperarousal (DSM-5 [ 5 ]). There is limited understanding of the biological processes underlying the core features of PTSD and associated psychiatric and somatic comorbidity [ 6 ]. Limited progress in the discovery of biological markers of PTSD has hampered accurate diagnosis, early identification of cases, staging and prognosis, stratification, personalized treatment, and new drug development. Additionally, individuals meeting diagnostic criteria for PTSD represent a heterogeneous group, as evidenced by differences in symptomatology, course, and treatment response [ 7 ]. Currently, case identification is limited by heavy reliance on self-reported symptoms for a disorder in which many trauma survivors under-report symptoms because of stigma, and some over-report symptoms for financial or other gains. Personalized treatment selection is limited by errors of omission (failing to identify individuals who would likely benefit from a specific behavioral or biological treatment) and errors of commission (treating individuals who are unlikely to benefit from a specific treatment), in part because of the lack of validated diagnostic and prognostic markers. Previous PTSD biomarker studies have primarily focused on using gene expression for predicting risk and diagnosis [ 8 , 9 , 10 , 11 ]. These studies have demonstrated moderate success in identifying predictive and diagnostic markers, but have been limited due to small sample sizes, as well as the focus on an individual molecular data type. In cancer, multi-site, integrated multi-omic studies have shown great promise in generating novel insights into disease mechanism, diagnostic and predictive markers, and signals of progression and stratification [ 12 , 13 , 14 ]. These studies have included high-throughput ‘omics data such as genomics, transcriptomics, proteomics, methylomics, lipidomics and metabolomics [ 15 ]. By employing a systems biology framework, multi-omic datasests provide the ability to understand the underlying disease network-associated biological processes [ 16 ]. The systems biology approach aims to characterize a large and diverse set of molecules within an illness or individual by examining entire biological systems, not just individual components, allowing the assessment of interactions among levels of cellular pathology, ranging from DNA to circulating metabolites [ 17 , 18 , 19 ]. This approach has the potential to provide a more comprehensive characterization of illnesses, to track underlying biological dysregulation before clinical symptoms develop or worsen, to lead to the identification of improved diagnostic markers, and to allow for the discovery of novel targets for treatment [ 20 ]. In 2012, the Department of Defense initiated a multi-site “PTSD Systems Biology Consortium”, which applied multiple ‘omics technologies to the same sample of combat-exposed PTSD and control participants. The goals of the PTSD Systems Biology Consortium included developing a reproducible panel of blood-based biomarkers with good sensitivity and specificity for PTSD diagnosis. Here, we present identification and validation of a set of multi-omic biomarkers for diagnosing warzone-related PTSD. Materials and methods Study inclusion criteria General inclusion criteria included being an Operation Enduring Freedom (OEF) and/or Operation Iraqi Freedom (OIF) male veteran between 20 and 60 years old, being able to understand the protocol and sign written informed consent, and meeting criteria for either PTSD-positive or PTSD-negative groups. PTSD-positive participants were defined as participants who met DSM-IV PTSD criteria for current warzone-related PTSD for at least 3 months duration, as indexed by the Clinician-Administered PTSD Scale (CAPS), with a minimum total score ≥ 40, which was calculated by summing each symptom on frequency and intensity ratings. Full criteria for DSM-IV diagnosis of PTSD was also met for all PTSD-positive participants. PTSD-negative controls were combat-exposed veterans that were negative for lifetime combat or civilian PTSD and had a current CAPS total score < 20. All study participants were exposed to DSM-IV PTSD Criterion A trauma during deployment. Detailed recruitment, enrollment, and exclusion criteria are listed in the Supplemental Material and Methods . Clinical assessment measures The Structured Clinical Interview for DSM (SCID) was used to determine whether participants met DSM-IV diagnostic criteria for mood, anxiety, psychotic, and substance use disorders [ 21 ]. The CAPS was used to determine combat-related PTSD status, as well as the severity of current PTSD symptoms (past month is", "role": "user" }, { "content": "An artificial intelligence tool—which analyzed 28 physical and molecular measures, all but one from blood samples—confirmed with 77 percent accuracy a diagnosis of posttraumatic stress disorder (PTSD) in male combat veterans, according to a new study. Led by NYU School of Medicine, Harvard John A. Paulson School of Engineering and Applied Sciences, and the U.S. Army Medical Research and Development Command, the study describes for the first time a blood-based biomarker panel for diagnosis of warzone-related PTSD. Published online September 9 in the journal Molecular Psychiatry, the measures included genomic, metabolic, and protein biomarkers. \"While work remains to further validate our panel, it holds tremendous promise as the first blood test that can screen for PTSD with a level of accuracy useful in the clinical setting,\" says senior study author Charles R. Marmar, MD, the Lucius N. Littauer Professor and chair of the Department of Psychiatry at NYU School of Medicine. \"If we are successful, this test would be one of the first of its kind—an objective blood test for a major psychiatric disorder.\" There are currently no FDA-approved blood tests, for instance, for depression or bipolar disorder, says Marmar. The new study embodies a longstanding goal in the field of psychiatry: to shift mental health toward standards like those used in cardiology or cancer, for instance, in which lab tests enable accurate diagnoses based on physical measures (biomarkers) instead of on self-reporting or interviews with inherent biases. Those with PTSD experience strong, persistent distress when reminded of a triggering, traumatic event. According to a World Health Organization survey, more than 70 percent of adults worldwide have experienced a traumatic event at some point in their lives, although not all develop the condition. Twenty Eight Out of a Million For the current study, 83 male, warzone-exposed veterans of the Iraq and Afghanistan conflicts with confirmed PTSD, and another 82 warzone-deployed veterans serving as healthy controls, were recruited from the Manhattan, Bronx and Brooklyn Veterans Affairs (VA) Medical Centers, as well as from other regional VA medical centers, veterans' service organizations, and the community. The researchers tested nearly one million features with current genomic and other molecular tests and narrowed them to 28 markers. By measuring a large number of unbiased quantities, the team sought to determine which of them were associated with an accurate PTSD symptom diagnosis. Using a combination of statistical techniques, the study authors narrowed the best measures from a million to 343 to 77, and then finally to 28, with the final group outperforming the larger groups in prediction accuracy. Some of this winnowing was accomplished using machine learning, mathematical models trained with data to find patterns. The team then applied their \"PTSD blood test\" to an independent group of veterans to see how well their new tool matched the diagnoses made previously using standard clinical questionnaires like the Clinician Administered PTSD Scale (CAPS). This comparison yielded the 77 percent accuracy figure. \"These molecular signatures will continue to be refined and adapted for commercialization,\" says co-senior study author Marti Jett, Ph.D., chief scientist in Systems Biology for the US Army Medical Research & Development Command (USAMRDC), within the US Army Center for Environmental Health Research (CIV USACEHR). \"The Department of Health Affairs within the Department of Defense is considering this approach as a potential screening tool that could identify service members, before and after deployment, with features of unresolved post-traumatic stress.\" Those identified would be referred for their specific issues (sleep disruption, anger management, etc.), which is available at most military bases, adds Jett. The current study did not seek to explain the disease mechanisms related to the final markers, but rather to blindly pick those that did the best job of diagnosing PTSD. That said, the group of best-performing markers included the activity levels of certain genes, amounts of key proteins in the blood, levels of metabolites involved in energy processing, as well as levels of circulating microRNAs (miRNAs), snippets of genetic material known to alter gene activity and tied to heart diseases and features of PTSD. The one indicator not measured by blood test was the heart rate variability. \"These results point toward many biochemical pathways that may guide the future design of new drugs, and support the theory that PTSD is a systemic disease that causes genetic and cellular changes well beyond the brain,\" says corresponding author Frank Doyle, Ph.D., dean of Harvard John A. Paulson School of Engineering and Applied Sciences, one of the research study's sites. Previous studies of genetic predictors of PTSD risk have shown strong performance in younger, active duty populations, says author Kelsey Dean, Ph.D., a member of Doyle's group at Harvard. This suggests that such biomarkers may be able to signal for PTSD at its earliest ages, and so be useful in prevention. For future research, studies of populations beyond male veterans will be needed to better understand the clinical utility of the proposed biomarker panel. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Post-traumatic stress disorder (PTSD) impacts many veterans and active duty soldiers, but diagnosis can be problematic due to biases in self-disclosure of symptoms, stigma within military populations, and limitations identifying those at risk. Prior studies suggest that PTSD may be a systemic illness, affecting not just the brain, but the entire body. Therefore, disease signals likely span multiple biological domains, including genes, proteins, cells, tissues, and organism-level physiological changes. Identification of these signals could aid in diagnostics, treatment decision-making, and risk evaluation. In the search for PTSD diagnostic biomarkers, we ascertained over one million molecular, cellular, physiological, and clinical features from three cohorts of male veterans. In a discovery cohort of 83 warzone-related PTSD cases and 82 warzone-exposed controls, we identified a set of 343 candidate biomarkers. These candidate biomarkers were selected from an integrated approach using (1) data-driven methods, including Support Vector Machine with Recursive Feature Elimination and other standard or published methodologies, and (2) hypothesis-driven approaches, using previous genetic studies for polygenic risk, or other PTSD-related literature. After reassessment of ~30% of these participants, we refined this set of markers from 343 to 28, based on their performance and ability to track changes in phenotype over time. The final diagnostic panel of 28 features was validated in an independent cohort (26 cases, 26 controls) with good performance (AUC = 0.80, 81% accuracy, 85% sensitivity, and 77% specificity). The identification and validation of this diverse diagnostic panel represents a powerful and novel approach to improve accuracy and reduce bias in diagnosing combat-related PTSD. Introduction Combat-related post-traumatic stress disorder (PTSD) has a lifetime prevalence of between 10.1%–30.9% in U.S. veterans of the Vietnam and subsequent conflicts, including the Iraq and Afghanistan wars [ 1 , 2 , 3 , 4 ]. PTSD is precipitated by experiencing or witnessing actual or threatened death, serious injury, or violence, and has symptoms that include re-experiencing, avoidance, negative thoughts, or moods associated with the traumatic event and hyperarousal (DSM-5 [ 5 ]). There is limited understanding of the biological processes underlying the core features of PTSD and associated psychiatric and somatic comorbidity [ 6 ]. Limited progress in the discovery of biological markers of PTSD has hampered accurate diagnosis, early identification of cases, staging and prognosis, stratification, personalized treatment, and new drug development. Additionally, individuals meeting diagnostic criteria for PTSD represent a heterogeneous group, as evidenced by differences in symptomatology, course, and treatment response [ 7 ]. Currently, case identification is limited by heavy reliance on self-reported symptoms for a disorder in which many trauma survivors under-report symptoms because of stigma, and some over-report symptoms for financial or other gains. Personalized treatment selection is limited by errors of omission (failing to identify individuals who would likely benefit from a specific behavioral or biological treatment) and errors of commission (treating individuals who are unlikely to benefit from a specific treatment), in part because of the lack of validated diagnostic and prognostic markers. Previous PTSD biomarker studies have primarily focused on using gene expression for predicting risk and diagnosis [ 8 , 9 , 10 , 11 ]. These studies have demonstrated moderate success in identifying predictive and diagnostic markers, but have been limited due to small sample sizes, as well as the focus on an individual molecular data type. In cancer, multi-site, integrated multi-omic studies have shown great promise in generating novel insights into disease mechanism, diagnostic and predictive markers, and signals of progression and stratification [ 12 , 13 , 14 ]. These studies have included high-throughput ‘omics data such as genomics, transcriptomics, proteomics, methylomics, lipidomics and metabolomics [ 15 ]. By employing a systems biology framework, multi-omic datasests provide the ability to understand the underlying disease network-associated biological processes [ 16 ]. The systems biology approach aims to characterize a large and diverse set of molecules within an illness or individual by examining entire biological systems, not just individual components, allowing the assessment of interactions among levels of cellular pathology, ranging from DNA to circulating metabolites [ 17 , 18 , 19 ]. This approach has the potential to provide a more comprehensive characterization of illnesses, to track underlying biological dysregulation before clinical symptoms develop or worsen, to lead to the identification of improved diagnostic markers, and to allow for the discovery of novel targets for treatment [ 20 ]. In 2012, the Department of Defense initiated a multi-site “PTSD Systems Biology Consortium”, which applied multiple ‘omics technologies to the same sample of combat-exposed PTSD and control participants. The goals of the PTSD Systems Biology Consortium included developing a reproducible panel of blood-based biomarkers with good sensitivity and specificity for PTSD diagnosis. Here, we present identification and validation of a set of multi-omic biomarkers for diagnosing warzone-related PTSD. Materials and methods Study inclusion criteria General inclusion criteria included being an Operation Enduring Freedom (OEF) and/or Operation Iraqi Freedom (OIF) male veteran between 20 and 60 years old, being able to understand the protocol and sign written informed consent, and meeting criteria for either PTSD-positive or PTSD-negative groups. PTSD-positive participants were defined as participants who met DSM-IV PTSD criteria for current warzone-related PTSD for at least 3 months duration, as indexed by the Clinician-Administered PTSD Scale (CAPS), with a minimum total score ≥ 40, which was calculated by summing each symptom on frequency and intensity ratings. Full criteria for DSM-IV diagnosis of PTSD was also met for all PTSD-positive participants. PTSD-negative controls were combat-exposed veterans that were negative for lifetime combat or civilian PTSD and had a current CAPS total score < 20. All study participants were exposed to DSM-IV PTSD Criterion A trauma during deployment. Detailed recruitment, enrollment, and exclusion criteria are listed in the Supplemental Material and Methods . Clinical assessment measures The Structured Clinical Interview for DSM (SCID) was used to determine whether participants met DSM-IV diagnostic criteria for mood, anxiety, psychotic, and substance use disorders [ 21 ]. The CAPS was used to determine combat-related PTSD status, as well as the severity of current PTSD symptoms (past month is<|im_end|> <|im_start|>assistant An artificial intelligence tool—which analyzed 28 physical and molecular measures, all but one from blood samples—confirmed with 77 percent accuracy a diagnosis of posttraumatic stress disorder (PTSD) in male combat veterans, according to a new study. Led by NYU School of Medicine, Harvard John A. Paulson School of Engineering and Applied Sciences, and the U.S. Army Medical Research and Development Command, the study describes for the first time a blood-based biomarker panel for diagnosis of warzone-related PTSD. Published online September 9 in the journal Molecular Psychiatry, the measures included genomic, metabolic, and protein biomarkers. "While work remains to further validate our panel, it holds tremendous promise as the first blood test that can screen for PTSD with a level of accuracy useful in the clinical setting," says senior study author Charles R. Marmar, MD, the Lucius N. Littauer Professor and chair of the Department of Psychiatry at NYU School of Medicine. "If we are successful, this test would be one of the first of its kind—an objective blood test for a major psychiatric disorder." There are currently no FDA-approved blood tests, for instance, for depression or bipolar disorder, says Marmar. The new study embodies a longstanding goal in the field of psychiatry: to shift mental health toward standards like those used in cardiology or cancer, for instance, in which lab tests enable accurate diagnoses based on physical measures (biomarkers) instead of on self-reporting or interviews with inherent biases. Those with PTSD experience strong, persistent distress when reminded of a triggering, traumatic event. According to a World Health Organization survey, more than 70 percent of adults worldwide have experienced a traumatic event at some point in their lives, although not all develop the condition. Twenty Eight Out of a Million For the current study, 83 male, warzone-exposed veterans of the Iraq and Afghanistan conflicts with confirmed PTSD, and another 82 warzone-deployed veterans serving as healthy controls, were recruited from the Manhattan, Bronx and Brooklyn Veterans Affairs (VA) Medical Centers, as well as from other regional VA medical centers, veterans' service organizations, and the community. The researchers tested nearly one million features with current genomic and other molecular tests and narrowed them to 28 markers. By measuring a large number of unbiased quantities, the team sought to determine which of them were associated with an accurate PTSD symptom diagnosis. Using a combination of statistical techniques, the study authors narrowed the best measures from a million to 343 to 77, and then finally to 28, with the final group outperforming the larger groups in prediction accuracy. Some of this winnowing was accomplished using machine learning, mathematical models trained with data to find patterns. The team then applied their "PTSD blood test" to an independent group of veterans to see how well their new tool matched the diagnoses made previously using standard clinical questionnaires like the Clinician Administered PTSD Scale (CAPS). This comparison yielded the 77 percent accuracy figure. "These molecular signatures will continue to be refined and adapted for commercialization," says co-senior study author Marti Jett, Ph.D., chief scientist in Systems Biology for the US Army Medical Research & Development Command (USAMRDC), within the US Army Center for Environmental Health Research (CIV USACEHR). "The Department of Health Affairs within the Department of Defense is considering this approach as a potential screening tool that could identify service members, before and after deployment, with features of unresolved post-traumatic stress." Those identified would be referred for their specific issues (sleep disruption, anger management, etc.), which is available at most military bases, adds Jett. The current study did not seek to explain the disease mechanisms related to the final markers, but rather to blindly pick those that did the best job of diagnosing PTSD. That said, the group of best-performing markers included the activity levels of certain genes, amounts of key proteins in the blood, levels of metabolites involved in energy processing, as well as levels of circulating microRNAs (miRNAs), snippets of genetic material known to alter gene activity and tied to heart diseases and features of PTSD. The one indicator not measured by blood test was the heart rate variability. "These results point toward many biochemical pathways that may guide the future design of new drugs, and support the theory that PTSD is a systemic disease that causes genetic and cellular changes well beyond the brain," says corresponding author Frank Doyle, Ph.D., dean of Harvard John A. Paulson School of Engineering and Applied Sciences, one of the research study's sites. Previous studies of genetic predictors of PTSD risk have shown strong performance in younger, active duty populations, says author Kelsey Dean, Ph.D., a member of Doyle's group at Harvard. This suggests that such biomarkers may be able to signal for PTSD at its earliest ages, and so be useful in prevention. For future research, studies of populations beyond male veterans will be needed to better understand the clinical utility of the proposed biomarker panel. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 3962, 80367, 33030, 8631, 19823, 320, 2898, 5608, 8, 25949, 1690, 26905, 323, 4642, 14523, 15201, 11, 719, 23842, 649, 387, 36033, 4245, 311, 50183, 304, 659, 52765, 11915, 315, 13803, 11, 60381, 2949, 6411, 22673, 11, 323, 9669, 25607, 1884, 520, 5326, 13, 32499, 7978, 4284, 430, 62419, 1253, 387, 264, 46417, 17563, 11, 28987, 539, 1120, 279, 8271, 11, 719, 279, 4553, 2547, 13, 15636, 11, 8624, 17738, 4461, 9575, 5361, 24156, 31576, 11, 2737, 21389, 11, 28896, 11, 7917, 11, 39881, 11, 323, 47120, 11852, 53194, 4442, 13, 59776, 315, 1521, 17738, 1436, 12576, 304, 50518, 11, 6514, 5597, 28846, 11, 323, 5326, 16865, 13, 763, 279, 2778, 369, 62419, 15439, 39538, 91141, 11, 584, 439, 12525, 2692, 927, 832, 3610, 31206, 11, 35693, 11, 53194, 11, 323, 14830, 4519, 505, 2380, 90388, 315, 8762, 26905, 13, 763, 264, 18841, 41944, 315, 220, 6069, 4208, 8855, 14228, 62419, 5157, 323, 220, 6086, 4208, 8855, 10397, 3950, 11835, 11, 584, 11054, 264, 743, 315, 220, 16522, 9322, 39538, 91141, 13, 4314, 9322, 39538, 91141, 1051, 4183, 505, 459, 18751, 5603, 1701, 320, 16, 8, 828, 32505, 5528, 11, 2737, 9365, 4290, 13257, 449, 86996, 20595, 43420, 2617, 323, 1023, 5410, 477, 4756, 81898, 11, 323, 320, 17, 8, 31178, 32505, 20414, 11, 1701, 3766, 19465, 7978, 369, 10062, 89305, 5326, 11, 477, 1023, 62419, 14228, 17649, 13, 4740, 32834, 24280, 315, 4056, 966, 4, 315, 1521, 13324, 11, 584, 38291, 420, 743, 315, 24915, 505, 220, 16522, 311, 220, 1591, 11, 3196, 389, 872, 5178, 323, 5845, 311, 3839, 4442, 304, 82423, 927, 892, 13, 578, 1620, 15439, 7090, 315, 220, 1591, 4519, 574, 33432, 304, 459, 9678, 41944, 320, 1627, 5157, 11, 220, 1627, 11835, 8, 449, 1695, 5178, 320, 32, 5576, 284, 220, 15, 13, 1490, 11, 220, 5932, 4, 13708, 11, 220, 5313, 4, 27541, 11, 323, 220, 2813, 4, 76041, 570, 578, 22654, 323, 10741, 315, 420, 17226, 15439, 7090, 11105, 264, 8147, 323, 11775, 5603, 311, 7417, 13708, 323, 8108, 15837, 304, 13493, 14759, 12896, 14228, 62419, 13, 29438, 37082, 14228, 1772, 80367, 33030, 8631, 19823, 320, 2898, 5608, 8, 706, 264, 19569, 38009, 315, 1990, 220, 605, 13, 16, 4, 4235, 966, 13, 24, 4, 304, 549, 815, 13, 26905, 315, 279, 23315, 323, 17876, 26885, 11, 2737, 279, 11340, 323, 21139, 25981, 510, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 21087, 62419, 374, 36841, 33337, 555, 25051, 477, 70042, 5150, 477, 21699, 4648, 11, 6129, 11134, 11, 477, 9349, 11, 323, 706, 13803, 430, 2997, 312, 10397, 32836, 11627, 11, 65411, 11, 8389, 11555, 11, 477, 296, 9242, 5938, 449, 279, 54286, 1567, 323, 17508, 277, 788, 278, 320, 6061, 44, 12, 20, 510, 220, 20, 97811, 2684, 374, 7347, 8830, 315, 279, 24156, 11618, 16940, 279, 6332, 4519, 315, 62419, 323, 5938, 47657, 323, 1794, 780, 470, 30986, 19025, 510, 220, 21, 21087, 19439, 5208, 304, 279, 18841, 315, 24156, 24915, 315, 62419, 706, 13824, 43868, 13687, 23842, 11, 4216, 22654, 315, 5157, 11, 48862, 323, 95350, 11, 44397, 2461, 11, 35649, 6514, 11, 323, 502, 5623, 4500, 13, 23212, 11, 7931, 6574, 15439, 13186, 369, 62419, 4097, 264, 98882, 1912, 11, 439, 69457, 555, 12062, 304, 49648, 75014, 11, 3388, 11, 323, 6514, 2077, 510, 220, 22, 21087, 25122, 11, 1162, 22654, 374, 7347, 555, 8987, 54180, 389, 659, 85296, 13803, 369, 264, 19823, 304, 902, 1690, 30988, 32696, 1234, 48511, 13803, 1606, 315, 60381, 11, 323, 1063, 927, 48511, 13803, 369, 6020, 477, 1023, 20192, 13, 19758, 1534, 6514, 6727, 374, 7347, 555, 6103, 315, 84218, 320, 69, 14612, 311, 10765, 7931, 889, 1053, 4461, 8935, 505, 264, 3230, 36695, 477, 24156, 6514, 8, 323, 6103, 315, 12396, 320, 10367, 1113, 7931, 889, 527, 17821, 311, 8935, 505, 264, 3230, 6514, 705, 304, 961, 1606, 315, 279, 6996, 315, 33432, 15439, 323, 63903, 537, 292, 24915, 13, 30013, 62419, 39538, 13152, 7978, 617, 15871, 10968, 389, 1701, 15207, 7645, 369, 52997, 5326, 323, 23842, 510, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 21087, 4314, 7978, 617, 21091, 24070, 2450, 304, 25607, 60336, 323, 15439, 24915, 11, 719, 617, 1027, 7347, 4245, 311, 2678, 6205, 12562, 11, 439, 1664, 439, 279, 5357, 389, 459, 3927, 31206, 828, 955, 13, 763, 9572, 11, 7447, 29654, 11, 18751, 7447, 12, 3151, 7978, 617, 6982, 2294, 11471, 304, 24038, 11775, 26793, 1139, 8624, 17383, 11, 15439, 323, 60336, 24915, 11, 323, 17738, 315, 33824, 323, 44397, 2461, 510, 220, 717, 1174, 220, 1032, 1174, 220, 975, 21087, 4314, 7978, 617, 5343, 1579, 43847, 631, 3451, 24203, 828, 1778, 439, 4173, 24203, 11, 36815, 24203, 11, 5541, 24203, 11, 79574, 24203, 11, 68700, 24203, 323, 28168, 24203, 510, 220, 868, 21087, 3296, 51297, 264, 6067, 34458, 12914, 11, 7447, 12, 3151, 17304, 18450, 3493, 279, 5845, 311, 3619, 279, 16940, 8624, 4009, 75968, 24156, 11618, 510, 220, 845, 21087, 578, 6067, 34458, 5603, 22262, 311, 70755, 264, 3544, 323, 17226, 743, 315, 35715, 2949, 459, 17563, 477, 3927, 555, 38936, 4553, 24156, 6067, 11, 539, 1120, 3927, 6956, 11, 10923, 279, 15813, 315, 22639, 4315, 5990, 315, 35693, 77041, 11, 24950, 505, 15922, 311, 54828, 28168, 3695, 510, 220, 1114, 1174, 220, 972, 1174, 220, 777, 21087, 1115, 5603, 706, 279, 4754, 311, 3493, 264, 810, 16195, 60993, 315, 49909, 11, 311, 3839, 16940, 24156, 22709, 1610, 2987, 1603, 14830, 13803, 2274, 477, 47293, 268, 11, 311, 3063, 311, 279, 22654, 315, 13241, 15439, 24915, 11, 323, 311, 2187, 369, 279, 18841, 315, 11775, 11811, 369, 6514, 510, 220, 508, 21087, 763, 220, 679, 17, 11, 279, 6011, 315, 16777, 33230, 264, 7447, 29654, 1054, 2898, 5608, 15264, 40023, 73547, 9520, 902, 9435, 5361, 3451, 24203, 14645, 311, 279, 1890, 6205, 315, 12896, 10397, 3950, 62419, 323, 2585, 13324, 13, 578, 9021, 315, 279, 62419, 15264, 40023, 73547, 5343, 11469, 264, 53823, 79385, 7090, 315, 6680, 6108, 39538, 91141, 449, 1695, 27541, 323, 76041, 369, 62419, 23842, 13, 5810, 11, 584, 3118, 22654, 323, 10741, 315, 264, 743, 315, 7447, 12, 3151, 39538, 91141, 369, 13493, 14759, 4208, 8855, 14228, 62419, 13, 32009, 323, 5528, 19723, 28286, 13186, 3331, 28286, 13186, 5343, 1694, 459, 17145, 4060, 1711, 25320, 320, 46, 15229, 8, 323, 5255, 17145, 31334, 25320, 320, 46, 2843, 8, 8762, 21487, 1990, 220, 508, 323, 220, 1399, 1667, 2362, 11, 1694, 3025, 311, 3619, 279, 11766, 323, 1879, 5439, 16369, 14771, 11, 323, 6574, 13186, 369, 3060, 62419, 69788, 477, 62419, 62035, 5315, 13, 62419, 69788, 13324, 1051, 4613, 439, 13324, 889, 2322, 80267, 12, 3166, 62419, 13186, 369, 1510, 4208, 8855, 14228, 62419, 369, 520, 3325, 220, 18, 4038, 8250, 11, 439, 31681, 555, 279, 18905, 12734, 12, 7358, 1601, 291, 62419, 25635, 320, 32500, 50, 705, 449, 264, 8187, 2860, 5573, 63247, 220, 1272, 11, 902, 574, 16997, 555, 2694, 5424, 1855, 49648, 389, 11900, 323, 21261, 18594, 13, 8797, 13186, 369, 80267, 12, 3166, 23842, 315, 62419, 574, 1101, 2322, 369, 682, 62419, 69788, 13324, 13, 62419, 62035, 11835, 1051, 12896, 10397, 3950, 26905, 430, 1051, 8389, 369, 19569, 12896, 477, 30028, 62419, 323, 1047, 264, 1510, 27193, 50, 2860, 5573, 366, 220, 508, 13, 2052, 4007, 13324, 1051, 15246, 311, 80267, 12, 3166, 62419, 69500, 362, 30988, 2391, 24047, 13, 63765, 34102, 11, 39148, 11, 323, 42308, 13186, 527, 10212, 304, 279, 43491, 278, 10441, 323, 19331, 662, 33135, 15813, 11193, 578, 16531, 3149, 33135, 32567, 369, 80267, 320, 3624, 926, 8, 574, 1511, 311, 8417, 3508, 13324, 2322, 80267, 12, 3166, 15439, 13186, 369, 20247, 11, 18547, 11, 94241, 11, 323, 20278, 1005, 24673, 510, 220, 1691, 21087, 578, 27193, 50, 574, 1511, 311, 8417, 12896, 14228, 62419, 2704, 11, 439, 1664, 439, 279, 31020, 315, 1510, 62419, 13803, 320, 53520, 2305, 374, 128257, 198, 128256, 78191, 198, 2127, 21075, 11478, 5507, 50004, 30239, 220, 1591, 7106, 323, 31206, 11193, 11, 682, 719, 832, 505, 6680, 10688, 2345, 42128, 449, 220, 2813, 3346, 13708, 264, 23842, 315, 1772, 2221, 33030, 8631, 19823, 320, 2898, 5608, 8, 304, 8762, 12896, 26905, 11, 4184, 311, 264, 502, 4007, 13, 32755, 555, 12551, 52, 6150, 315, 19152, 11, 25996, 3842, 362, 13, 7043, 942, 6150, 315, 17005, 323, 43608, 23199, 11, 323, 279, 549, 815, 13, 13309, 13235, 8483, 323, 11050, 7498, 11, 279, 4007, 16964, 369, 279, 1176, 892, 264, 6680, 6108, 39538, 13152, 7090, 369, 23842, 315, 4208, 8855, 14228, 62419, 13, 30114, 2930, 6250, 220, 24, 304, 279, 8486, 60825, 69244, 11, 279, 11193, 5343, 81064, 11, 41861, 11, 323, 13128, 39538, 91141, 13, 330, 8142, 990, 8625, 311, 4726, 9788, 1057, 7090, 11, 433, 10187, 28040, 11471, 439, 279, 1176, 6680, 1296, 430, 649, 4264, 369, 62419, 449, 264, 2237, 315, 13708, 5505, 304, 279, 14830, 6376, 1359, 2795, 10195, 4007, 3229, 15274, 432, 13, 386, 2227, 277, 11, 14306, 11, 279, 14103, 9334, 452, 13, 445, 1468, 28196, 17054, 323, 10716, 315, 279, 6011, 315, 69244, 520, 12551, 52, 6150, 315, 19152, 13, 330, 2746, 584, 527, 6992, 11, 420, 1296, 1053, 387, 832, 315, 279, 1176, 315, 1202, 3169, 85366, 16945, 6680, 1296, 369, 264, 3682, 47657, 19823, 1210, 2684, 527, 5131, 912, 30473, 67362, 6680, 7177, 11, 369, 2937, 11, 369, 18710, 477, 65919, 19823, 11, 2795, 386, 2227, 277, 13, 578, 502, 4007, 95122, 264, 74229, 5915, 304, 279, 2115, 315, 46876, 894, 25, 311, 6541, 10723, 2890, 9017, 10886, 1093, 1884, 1511, 304, 3786, 31226, 477, 9572, 11, 369, 2937, 11, 304, 902, 10278, 7177, 7431, 13687, 85488, 3196, 389, 7106, 11193, 320, 8385, 316, 91141, 8, 4619, 315, 389, 659, 48511, 287, 477, 19905, 449, 38088, 50183, 13, 13266, 449, 62419, 3217, 3831, 11, 26048, 35104, 994, 31256, 315, 264, 52605, 11, 54286, 1567, 13, 10771, 311, 264, 4435, 6401, 21021, 10795, 11, 810, 1109, 220, 2031, 3346, 315, 12884, 15603, 617, 10534, 264, 54286, 1567, 520, 1063, 1486, 304, 872, 6439, 11, 8051, 539, 682, 2274, 279, 3044, 13, 44956, 36944, 4470, 315, 264, 34629, 1789, 279, 1510, 4007, 11, 220, 6069, 8762, 11, 4208, 8855, 10397, 3950, 26905, 315, 279, 11340, 323, 21139, 26885, 449, 11007, 62419, 11, 323, 2500, 220, 6086, 4208, 8855, 6953, 2760, 291, 26905, 13788, 439, 9498, 11835, 11, 1051, 45425, 505, 279, 29890, 11, 66236, 323, 26832, 40432, 23298, 320, 13114, 8, 13235, 41991, 11, 439, 1664, 439, 505, 1023, 15481, 21571, 6593, 19169, 11, 26905, 6, 2532, 11351, 11, 323, 279, 4029, 13, 578, 12074, 12793, 7154, 832, 3610, 4519, 449, 1510, 81064, 323, 1023, 31206, 7177, 323, 74035, 1124, 311, 220, 1591, 24915, 13, 3296, 30090, 264, 3544, 1396, 315, 74315, 33776, 11, 279, 2128, 16495, 311, 8417, 902, 315, 1124, 1051, 5938, 449, 459, 13687, 62419, 49648, 23842, 13, 12362, 264, 10824, 315, 29564, 12823, 11, 279, 4007, 12283, 74035, 279, 1888, 11193, 505, 264, 3610, 311, 220, 16522, 311, 220, 2813, 11, 323, 1243, 5616, 311, 220, 1591, 11, 449, 279, 1620, 1912, 704, 29588, 287, 279, 8294, 5315, 304, 20212, 13708, 13, 4427, 315, 420, 3243, 3409, 287, 574, 27332, 1701, 5780, 6975, 11, 37072, 4211, 16572, 449, 828, 311, 1505, 12912, 13, 578, 2128, 1243, 9435, 872, 330, 2898, 5608, 6680, 1296, 1, 311, 459, 9678, 1912, 315, 26905, 311, 1518, 1268, 1664, 872, 502, 5507, 18545, 279, 85488, 1903, 8767, 1701, 5410, 14830, 3488, 69663, 1093, 279, 18905, 12734, 7735, 1601, 291, 62419, 25635, 320, 32500, 50, 570, 1115, 12593, 58487, 279, 220, 2813, 3346, 13708, 7216, 13, 330, 9673, 31206, 33728, 690, 3136, 311, 387, 38291, 323, 30464, 369, 8518, 2065, 1359, 2795, 1080, 1355, 268, 2521, 4007, 3229, 8290, 72, 622, 7211, 11, 2405, 920, 2637, 10388, 28568, 304, 15264, 40023, 369, 279, 2326, 13309, 13235, 8483, 612, 11050, 7498, 320, 2078, 1428, 49, 5744, 705, 2949, 279, 2326, 13309, 5955, 369, 25027, 6401, 8483, 320, 34, 3166, 2326, 5693, 17526, 570, 330, 791, 6011, 315, 6401, 23298, 2949, 279, 6011, 315, 16777, 374, 13126, 420, 5603, 439, 264, 4754, 23061, 5507, 430, 1436, 10765, 2532, 3697, 11, 1603, 323, 1306, 24047, 11, 449, 4519, 315, 81261, 1772, 80367, 33030, 8631, 1210, 13266, 11054, 1053, 387, 14183, 369, 872, 3230, 4819, 320, 26894, 44219, 11, 19788, 6373, 11, 5099, 25390, 902, 374, 2561, 520, 1455, 6411, 23963, 11, 11621, 622, 7211, 13, 578, 1510, 4007, 1550, 539, 6056, 311, 10552, 279, 8624, 24717, 5552, 311, 279, 1620, 24915, 11, 719, 4856, 311, 89447, 3820, 1884, 430, 1550, 279, 1888, 2683, 315, 13493, 14759, 62419, 13, 3011, 1071, 11, 279, 1912, 315, 1888, 17453, 55857, 24915, 5343, 279, 5820, 5990, 315, 3738, 21389, 11, 15055, 315, 1401, 28896, 304, 279, 6680, 11, 5990, 315, 28168, 3695, 6532, 304, 4907, 8863, 11, 439, 1664, 439, 5990, 315, 54828, 8162, 51295, 2170, 320, 8318, 51295, 2170, 705, 69742, 315, 19465, 3769, 3967, 311, 11857, 15207, 5820, 323, 17791, 311, 4851, 19338, 323, 4519, 315, 62419, 13, 578, 832, 21070, 539, 17303, 555, 6680, 1296, 574, 279, 4851, 4478, 54709, 13, 330, 9673, 3135, 1486, 9017, 1690, 93532, 44014, 430, 1253, 8641, 279, 3938, 2955, 315, 502, 11217, 11, 323, 1862, 279, 10334, 430, 62419, 374, 264, 46417, 8624, 430, 11384, 19465, 323, 35693, 4442, 1664, 7953, 279, 8271, 1359, 2795, 12435, 3229, 9454, 66309, 11, 2405, 920, 2637, 73962, 315, 25996, 3842, 362, 13, 7043, 942, 6150, 315, 17005, 323, 43608, 23199, 11, 832, 315, 279, 3495, 4007, 596, 6732, 13, 30013, 7978, 315, 19465, 95222, 315, 62419, 5326, 617, 6982, 3831, 5178, 304, 14992, 11, 4642, 14523, 22673, 11, 2795, 3229, 735, 93567, 25028, 11, 2405, 920, 2637, 264, 4562, 315, 66309, 596, 1912, 520, 25996, 13, 1115, 13533, 430, 1778, 39538, 91141, 1253, 387, 3025, 311, 8450, 369, 62419, 520, 1202, 30758, 17051, 11, 323, 779, 387, 5505, 304, 27344, 13, 1789, 3938, 3495, 11, 7978, 315, 22673, 7953, 8762, 26905, 690, 387, 4460, 311, 2731, 3619, 279, 14830, 15919, 315, 279, 11223, 39538, 13152, 7090, 13, 220, 128257, 198 ]

2,368

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The physical forces that drive morphogenesis are not well characterized in vivo , especially among vertebrates. In the early limb bud, dorsal and ventral ectoderm converge to form the apical ectodermal ridge (AER), although the underlying mechanisms are unclear. By live imaging mouse embryos, we show that prospective AER progenitors intercalate at the dorsoventral boundary and that ectoderm remodels by concomitant cell division and neighbour exchange. Mesodermal expansion and ectodermal tension together generate a dorsoventrally biased stress pattern that orients ectodermal remodelling. Polarized distribution of cortical actin reflects this stress pattern in a β-catenin- and Fgfr2-dependent manner. Intercalation of AER progenitors generates a tensile gradient that reorients resolution of multicellular rosettes on adjacent surfaces, a process facilitated by β-catenin-dependent attachment of cortex to membrane. Therefore, feedback between tissue stress pattern and cell intercalations remodels mammalian ectoderm. Main It has long been recognized that physical forces underlie embryonic shape changes 1 . New insights based on theory and experiment are progressively decorating this concept with exciting details 2 . However, many aspects of how forces relate to cell behaviours and how interplay between different tissues physically shapes embryonic structures remain unclear, especially among vertebrates. The limb bud derives from the lateral plate and is initially composed of a mesodermal core that is surrounded by a single cell layer of ectoderm. Mesodermal growth initiates limb development and is characterized by oriented cell behaviours that promote elongation of the proximodistal (PD) axis 3 , 4 , 5 , 6 . It has been postulated that early ectoderm and the AER, a stratified epithelial signalling centre that is essential for outgrowth and pattern formation 7 , might help to maintain a narrow dorsoventral (DV) bud axis 8 , 9 . AER formation requires, in part, a signal relay between mesodermal and ectodermal cells that activates canonical Wnt and Fgfr2 signalling in ectoderm 10 , 11 , 12 , 13 , 14 . The importance of these pathways is underscored by mutations that cause limb deficiencies in humans including tetra-amelia and Apert syndrome 15 , 16 . In the mouse embryo, AER precursors derive from a broad domain of primarily ventral ectoderm that transitions from cuboidal to columnar morphology 17 and converges just ventral to the DV boundary 18 , 19 , 20 , 21 . Although it is not clear what underlies this convergence, one possibility suggested previously is that coordinated cell rearrangements drive AER progenitors to move towards the DV compartment boundary 22 . Here we present evidence that supports this concept, and show that both mesodermal and ectodermal forces contribute to the ectodermal stress pattern that guides multicellular remodelling. Our findings suggest that β-catenin and Fgfr2 in part mediate cellular responses to tissue forces. RESULTS Cell topology and intercalation of prospective AER progenitors Cell intercalation is associated with non-hexagonal cell topology 23 . Using whole-mount immunostaining, we observed that ectodermal cells in the pre-AER limb field (20 som. (somite stage)) of the mouse embryo exhibited a wide range of topologies ( Fig. 1a ). The distribution of cell interfaces (number of cell neighbours) was centred on five and is shifted to the left compared with a common distribution centred on six interfaces that was previously described for invertebrate and earlier vertebrate embryos 24 ( Fig. 1b ). This finding suggests that some cell behaviours in the mouse embryo may be distinct to those observed in other metazoa. During early limb development (20 som.), ectodermal cells within the limb field became elongated along the DV axis ( Fig. 1a ), suggesting that they were under tension. By live imaging 18–20 som. CAG::H2B–EGFP reporter embryos that ubiquitously express nuclear EGFP (ref. 25 ), we found that cell division orientation was biased dorsoventrally in limb field and non-limb lateral plate ectoderm ( Fig. 1c ). By themselves, these cell behaviours would expand the DV axis of at least the ectodermal layer. Therefore, compensatory cell rearrangements may be important to accommodate new cells without distorting tissue shape. Figure 1: Cell topology and intercalation of AER progenitors. ( a ) Confocal section of rhodamine–phalloidin-stained pre-AER (20 som.) entire limb field (from somite 7 to 11, ∼ 250 ectodermal cells) demonstrating variable and non-hexagonal cell topologies as well as DV elongation of some ectodermal cells (quantified in Supplementary Figs 4 and 5 ). ( b ) Distribution of number of cell neighbours among 18–20 som. limb bud ectodermal cells. ( c ) Polar plot representing metaphase-to-telophase transition angles of limb bud ectoderm cells ( n = 3, 35–40 cell divisions (all cell divisions/2 h time-lapse video) per 18–20 som. embryo). ( d – f ) Confocal projection of the ectodermal Tcf/Lef::H2B–Venus reporter in pre-overt initiation limb field (16 som.; d ), early initiating limb field (18 som.; e ), and post-initiation limb field (22 som.; f ) (blue: DAPI). ( g ) Percentage of Tcf/Lef::H2B–Venus-positive cells in the limb field versus lateral plate in 18–20 som. embryos ( n = 3 embryos; P = 0.0022 (Student’s t -test)). ( h ) Percentage of pHH3-positive cells relative to total cells versus percentage of pHH3-positive cells relative to Tcf/Lef::H2B–Venus-positive cells in the limb field in 18–20 som. embryos ( n = 3 embryos; P = 0.26 (Student’s t -test)). ( i ) Confocal projection of the ectodermal Tcf/Lef::H2B–Venus reporter in an AER-forming limb bud (32 som.). ( j , k ) Meandering index ( j ) and DV displacement ( k ) among ubiquitously expressed H2B–GFP (representing total cells) versus Tcf/Lef::H2B–Venus (representing AER progenitors) cells in 18–20 som. embryos ( n = 20 cells in 3 embryos for each condition; ( j ) P = 0.86, ( k ) P = 0.74 (Student’s t -test)). ( l ) Time-lapse series of a 20 som. limb bud ectoderm expressing Tcf/Lef::H2B–Venus near the DV boundary. Dashed lines highlight regional tissue constriction. ( m ) Model of AER progenitor intercalation just ventral to the DV boundary (red line). Scale bars indicate 10 μm ( a , l ), 50 μm ( d", "role": "user" }, { "content": "University of Toronto engineers and a pediatric surgeon have joined forces to discover that physical forces like pressure and tension affect the development of limbs in embryos—research that could someday be used to help prevent birth defects. The team, including U of T mechanical engineer Yu Sun (MIE), U of T bioengineer Rodrigo Fernandez-Gonzalez (IBBME) and SickKids Hospital's Dr. Sevan Hopyan, used live imaging and computer models to study the links between mechanical forces, changes in cell shape and cell movement in the embryo. Their study—published this week in Nature Cell Biology—used cutting-edge techniques to gain valuable insight into the fundamental processes of arm and leg development. Mapping-out the growth of 'proto-limbs' An embryo starts out shaped like a ball, then grows to create complex shapes like limbs. In early embryonic development, cells divide into three layers: the ectoderm, which forms the nervous system, skin and sensory organs; the mesoderm, which produces the skeleton, muscles and most of the major organs, and; the endoderm, which turns into the body's respiratory tract and elimination systems. In the study, the team looked at cell behaviours in the ectoderm that promote limb development. They used unique tools, including micro-chiseling ablating lasers, atomic force microscopes and layer-by-layer computer models, to explore the early stages of limbs in unprecedented detail. They discovered that as cells divide and develop, the way they communicate with each other and the pressure resulting from movements of the three cell layers can impact how well limb buds—the early stages of what become arms or legs—are formed. \"We found amazing evidence on how mechanical forces regulate the remodeling of cells in the ectoderm layer and how the stress field changes when the ectoderm changes its shape as it develops,\" says Professor Sun. Prior to this work, scientists and engineers didn't have the tools and techniques to understand changes of shapes on a tissue scale and on small groups of cells. Thanks to their findings, the researchers know that two major cell layers, the ectoderm and mesoderm, speak to each other both mechanically and biochemically, that is, through molecules shuttling back and forth. This communication is linked to changes in the embryo. Engineering insights from the world of the cell \"The idea that two tissues are mechanically interacting and that such interaction affects cellular behaviour is really exciting to see,\" says Fernandez-Gonzalez. To measure mechanical forces, the authors used techniques borrowed from the world of manufacturing and engineering, including the use of a laser to cut interfaces between cells. \"If you hold a rubber band between your hands and I cut it while it's loose, nothing happens,\" says Fernandez-Gonzalez. \"But if you stretch the rubber band, your hands snap back when I cut it. That's essentially what happens with cell boundaries,\" he explains. \"We know some of the genes that are important in the structure of the embryo for development to proceed, but we didn't know how those pathways were linked with movement in the cells,\" says Hopyan. A path to preventing limb defects While their study was done on a highly fundamental level, the team says it will allow them and others to take important further steps like measuring forces in and between cells. The study also paves the way for the possibility of creating better simulations of cell remodeling and the early development of limbs. \"This research could someday be used in potential medical applications to prevent limb deformations,\" says Hopyan. The work is one of the first times a research team has applied biophysical methods to the study of cell and tissue mechanics in live mammals. Possible long-term outcomes in this research field could result in a drug that could alter mechanical stress on cells in embryos, repairing what would otherwise have become a deformed limb. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The physical forces that drive morphogenesis are not well characterized in vivo , especially among vertebrates. In the early limb bud, dorsal and ventral ectoderm converge to form the apical ectodermal ridge (AER), although the underlying mechanisms are unclear. By live imaging mouse embryos, we show that prospective AER progenitors intercalate at the dorsoventral boundary and that ectoderm remodels by concomitant cell division and neighbour exchange. Mesodermal expansion and ectodermal tension together generate a dorsoventrally biased stress pattern that orients ectodermal remodelling. Polarized distribution of cortical actin reflects this stress pattern in a β-catenin- and Fgfr2-dependent manner. Intercalation of AER progenitors generates a tensile gradient that reorients resolution of multicellular rosettes on adjacent surfaces, a process facilitated by β-catenin-dependent attachment of cortex to membrane. Therefore, feedback between tissue stress pattern and cell intercalations remodels mammalian ectoderm. Main It has long been recognized that physical forces underlie embryonic shape changes 1 . New insights based on theory and experiment are progressively decorating this concept with exciting details 2 . However, many aspects of how forces relate to cell behaviours and how interplay between different tissues physically shapes embryonic structures remain unclear, especially among vertebrates. The limb bud derives from the lateral plate and is initially composed of a mesodermal core that is surrounded by a single cell layer of ectoderm. Mesodermal growth initiates limb development and is characterized by oriented cell behaviours that promote elongation of the proximodistal (PD) axis 3 , 4 , 5 , 6 . It has been postulated that early ectoderm and the AER, a stratified epithelial signalling centre that is essential for outgrowth and pattern formation 7 , might help to maintain a narrow dorsoventral (DV) bud axis 8 , 9 . AER formation requires, in part, a signal relay between mesodermal and ectodermal cells that activates canonical Wnt and Fgfr2 signalling in ectoderm 10 , 11 , 12 , 13 , 14 . The importance of these pathways is underscored by mutations that cause limb deficiencies in humans including tetra-amelia and Apert syndrome 15 , 16 . In the mouse embryo, AER precursors derive from a broad domain of primarily ventral ectoderm that transitions from cuboidal to columnar morphology 17 and converges just ventral to the DV boundary 18 , 19 , 20 , 21 . Although it is not clear what underlies this convergence, one possibility suggested previously is that coordinated cell rearrangements drive AER progenitors to move towards the DV compartment boundary 22 . Here we present evidence that supports this concept, and show that both mesodermal and ectodermal forces contribute to the ectodermal stress pattern that guides multicellular remodelling. Our findings suggest that β-catenin and Fgfr2 in part mediate cellular responses to tissue forces. RESULTS Cell topology and intercalation of prospective AER progenitors Cell intercalation is associated with non-hexagonal cell topology 23 . Using whole-mount immunostaining, we observed that ectodermal cells in the pre-AER limb field (20 som. (somite stage)) of the mouse embryo exhibited a wide range of topologies ( Fig. 1a ). The distribution of cell interfaces (number of cell neighbours) was centred on five and is shifted to the left compared with a common distribution centred on six interfaces that was previously described for invertebrate and earlier vertebrate embryos 24 ( Fig. 1b ). This finding suggests that some cell behaviours in the mouse embryo may be distinct to those observed in other metazoa. During early limb development (20 som.), ectodermal cells within the limb field became elongated along the DV axis ( Fig. 1a ), suggesting that they were under tension. By live imaging 18–20 som. CAG::H2B–EGFP reporter embryos that ubiquitously express nuclear EGFP (ref. 25 ), we found that cell division orientation was biased dorsoventrally in limb field and non-limb lateral plate ectoderm ( Fig. 1c ). By themselves, these cell behaviours would expand the DV axis of at least the ectodermal layer. Therefore, compensatory cell rearrangements may be important to accommodate new cells without distorting tissue shape. Figure 1: Cell topology and intercalation of AER progenitors. ( a ) Confocal section of rhodamine–phalloidin-stained pre-AER (20 som.) entire limb field (from somite 7 to 11, ∼ 250 ectodermal cells) demonstrating variable and non-hexagonal cell topologies as well as DV elongation of some ectodermal cells (quantified in Supplementary Figs 4 and 5 ). ( b ) Distribution of number of cell neighbours among 18–20 som. limb bud ectodermal cells. ( c ) Polar plot representing metaphase-to-telophase transition angles of limb bud ectoderm cells ( n = 3, 35–40 cell divisions (all cell divisions/2 h time-lapse video) per 18–20 som. embryo). ( d – f ) Confocal projection of the ectodermal Tcf/Lef::H2B–Venus reporter in pre-overt initiation limb field (16 som.; d ), early initiating limb field (18 som.; e ), and post-initiation limb field (22 som.; f ) (blue: DAPI). ( g ) Percentage of Tcf/Lef::H2B–Venus-positive cells in the limb field versus lateral plate in 18–20 som. embryos ( n = 3 embryos; P = 0.0022 (Student’s t -test)). ( h ) Percentage of pHH3-positive cells relative to total cells versus percentage of pHH3-positive cells relative to Tcf/Lef::H2B–Venus-positive cells in the limb field in 18–20 som. embryos ( n = 3 embryos; P = 0.26 (Student’s t -test)). ( i ) Confocal projection of the ectodermal Tcf/Lef::H2B–Venus reporter in an AER-forming limb bud (32 som.). ( j , k ) Meandering index ( j ) and DV displacement ( k ) among ubiquitously expressed H2B–GFP (representing total cells) versus Tcf/Lef::H2B–Venus (representing AER progenitors) cells in 18–20 som. embryos ( n = 20 cells in 3 embryos for each condition; ( j ) P = 0.86, ( k ) P = 0.74 (Student’s t -test)). ( l ) Time-lapse series of a 20 som. limb bud ectoderm expressing Tcf/Lef::H2B–Venus near the DV boundary. Dashed lines highlight regional tissue constriction. ( m ) Model of AER progenitor intercalation just ventral to the DV boundary (red line). Scale bars indicate 10 μm ( a , l ), 50 μm ( d<|im_end|> <|im_start|>assistant University of Toronto engineers and a pediatric surgeon have joined forces to discover that physical forces like pressure and tension affect the development of limbs in embryos—research that could someday be used to help prevent birth defects. The team, including U of T mechanical engineer Yu Sun (MIE), U of T bioengineer Rodrigo Fernandez-Gonzalez (IBBME) and SickKids Hospital's Dr. Sevan Hopyan, used live imaging and computer models to study the links between mechanical forces, changes in cell shape and cell movement in the embryo. Their study—published this week in Nature Cell Biology—used cutting-edge techniques to gain valuable insight into the fundamental processes of arm and leg development. Mapping-out the growth of 'proto-limbs' An embryo starts out shaped like a ball, then grows to create complex shapes like limbs. In early embryonic development, cells divide into three layers: the ectoderm, which forms the nervous system, skin and sensory organs; the mesoderm, which produces the skeleton, muscles and most of the major organs, and; the endoderm, which turns into the body's respiratory tract and elimination systems. In the study, the team looked at cell behaviours in the ectoderm that promote limb development. They used unique tools, including micro-chiseling ablating lasers, atomic force microscopes and layer-by-layer computer models, to explore the early stages of limbs in unprecedented detail. They discovered that as cells divide and develop, the way they communicate with each other and the pressure resulting from movements of the three cell layers can impact how well limb buds—the early stages of what become arms or legs—are formed. "We found amazing evidence on how mechanical forces regulate the remodeling of cells in the ectoderm layer and how the stress field changes when the ectoderm changes its shape as it develops," says Professor Sun. Prior to this work, scientists and engineers didn't have the tools and techniques to understand changes of shapes on a tissue scale and on small groups of cells. Thanks to their findings, the researchers know that two major cell layers, the ectoderm and mesoderm, speak to each other both mechanically and biochemically, that is, through molecules shuttling back and forth. This communication is linked to changes in the embryo. Engineering insights from the world of the cell "The idea that two tissues are mechanically interacting and that such interaction affects cellular behaviour is really exciting to see," says Fernandez-Gonzalez. To measure mechanical forces, the authors used techniques borrowed from the world of manufacturing and engineering, including the use of a laser to cut interfaces between cells. "If you hold a rubber band between your hands and I cut it while it's loose, nothing happens," says Fernandez-Gonzalez. "But if you stretch the rubber band, your hands snap back when I cut it. That's essentially what happens with cell boundaries," he explains. "We know some of the genes that are important in the structure of the embryo for development to proceed, but we didn't know how those pathways were linked with movement in the cells," says Hopyan. A path to preventing limb defects While their study was done on a highly fundamental level, the team says it will allow them and others to take important further steps like measuring forces in and between cells. The study also paves the way for the possibility of creating better simulations of cell remodeling and the early development of limbs. "This research could someday be used in potential medical applications to prevent limb deformations," says Hopyan. The work is one of the first times a research team has applied biophysical methods to the study of cell and tissue mechanics in live mammals. Possible long-term outcomes in this research field could result in a drug that could alter mechanical stress on cells in embryos, repairing what would otherwise have become a deformed limb. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 7106, 8603, 430, 6678, 27448, 52379, 527, 539, 1664, 32971, 304, 41294, 1174, 5423, 4315, 67861, 99868, 13, 763, 279, 4216, 48694, 37808, 11, 96146, 323, 10594, 3545, 77594, 347, 4289, 80867, 311, 1376, 279, 1469, 950, 77594, 347, 18558, 58933, 320, 32, 643, 705, 8051, 279, 16940, 24717, 527, 25420, 13, 3296, 3974, 32758, 8814, 89873, 11, 584, 1501, 430, 33547, 362, 643, 84360, 12170, 958, 5531, 349, 520, 279, 53403, 708, 688, 3545, 19254, 323, 430, 77594, 347, 4289, 47086, 82, 555, 390, 884, 52044, 2849, 13096, 323, 22686, 9473, 13, 36684, 347, 18558, 14800, 323, 77594, 347, 18558, 24408, 3871, 7068, 264, 53403, 708, 688, 81, 750, 48761, 8631, 5497, 430, 477, 4167, 77594, 347, 18558, 1323, 347, 6427, 13, 56996, 1534, 8141, 315, 83619, 1180, 258, 27053, 420, 8631, 5497, 304, 264, 34318, 1824, 13827, 258, 12, 323, 435, 70, 1658, 17, 43918, 11827, 13, 1357, 3035, 278, 367, 315, 362, 643, 84360, 12170, 27983, 264, 22781, 458, 20779, 430, 312, 269, 4167, 11175, 315, 92520, 54230, 938, 751, 2392, 389, 24894, 27529, 11, 264, 1920, 72849, 555, 34318, 1824, 13827, 258, 43918, 20581, 315, 49370, 311, 39654, 13, 15636, 11, 11302, 1990, 20438, 8631, 5497, 323, 2849, 958, 5531, 811, 47086, 82, 36041, 10700, 77594, 347, 4289, 13, 4802, 1102, 706, 1317, 1027, 15324, 430, 7106, 8603, 1234, 11828, 44481, 14338, 6211, 4442, 220, 16, 662, 1561, 26793, 3196, 389, 10334, 323, 9526, 527, 72859, 49682, 420, 7434, 449, 13548, 3649, 220, 17, 662, 4452, 11, 1690, 13878, 315, 1268, 8603, 29243, 311, 2849, 71177, 323, 1268, 958, 1387, 1990, 2204, 39881, 22655, 21483, 44481, 14338, 14726, 7293, 25420, 11, 5423, 4315, 67861, 99868, 13, 578, 48694, 37808, 75549, 505, 279, 45569, 12235, 323, 374, 15453, 24306, 315, 264, 11083, 347, 18558, 6332, 430, 374, 23712, 555, 264, 3254, 2849, 6324, 315, 77594, 347, 4289, 13, 36684, 347, 18558, 6650, 12961, 988, 48694, 4500, 323, 374, 32971, 555, 42208, 2849, 71177, 430, 12192, 74595, 367, 315, 279, 22267, 318, 347, 380, 278, 320, 23891, 8, 8183, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 662, 1102, 706, 1027, 1772, 7913, 430, 4216, 77594, 347, 4289, 323, 279, 362, 643, 11, 264, 44397, 1908, 64779, 59544, 91977, 12541, 430, 374, 7718, 369, 704, 74189, 323, 5497, 18488, 220, 22, 1174, 2643, 1520, 311, 10519, 264, 15376, 53403, 708, 688, 3545, 320, 63071, 8, 37808, 8183, 220, 23, 1174, 220, 24, 662, 362, 643, 18488, 7612, 11, 304, 961, 11, 264, 8450, 32951, 1990, 11083, 347, 18558, 323, 77594, 347, 18558, 7917, 430, 75042, 43553, 468, 406, 323, 435, 70, 1658, 17, 91977, 304, 77594, 347, 4289, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 662, 578, 12939, 315, 1521, 44014, 374, 53209, 67, 555, 34684, 430, 5353, 48694, 72946, 304, 12966, 2737, 28953, 969, 33317, 37029, 323, 5345, 531, 28439, 220, 868, 1174, 220, 845, 662, 763, 279, 8814, 87701, 11, 362, 643, 5956, 34291, 43530, 505, 264, 7353, 8106, 315, 15871, 10594, 3545, 77594, 347, 4289, 430, 34692, 505, 19250, 71916, 311, 3330, 277, 79612, 220, 1114, 323, 19873, 4282, 1120, 10594, 3545, 311, 279, 52344, 19254, 220, 972, 1174, 220, 777, 1174, 220, 508, 1174, 220, 1691, 662, 10541, 433, 374, 539, 2867, 1148, 1234, 49201, 420, 56541, 11, 832, 13336, 12090, 8767, 374, 430, 47672, 2849, 56427, 526, 3808, 6678, 362, 643, 84360, 12170, 311, 3351, 7119, 279, 52344, 44598, 19254, 220, 1313, 662, 5810, 584, 3118, 6029, 430, 11815, 420, 7434, 11, 323, 1501, 430, 2225, 11083, 347, 18558, 323, 77594, 347, 18558, 8603, 17210, 311, 279, 77594, 347, 18558, 8631, 5497, 430, 28292, 92520, 54230, 1323, 347, 6427, 13, 5751, 14955, 4284, 430, 34318, 1824, 13827, 258, 323, 435, 70, 1658, 17, 304, 961, 1812, 6629, 35693, 14847, 311, 20438, 8603, 13, 54128, 14299, 45982, 323, 958, 5531, 367, 315, 33547, 362, 643, 84360, 12170, 14299, 958, 5531, 367, 374, 5938, 449, 2536, 2902, 327, 24346, 2849, 45982, 220, 1419, 662, 12362, 4459, 60688, 33119, 537, 2101, 11, 584, 13468, 430, 77594, 347, 18558, 7917, 304, 279, 864, 6830, 643, 48694, 2115, 320, 508, 1794, 13, 320, 57839, 635, 6566, 595, 315, 279, 8814, 87701, 51713, 264, 7029, 2134, 315, 1948, 9268, 320, 23966, 13, 220, 16, 64, 7609, 578, 8141, 315, 2849, 25066, 320, 4174, 315, 2849, 36956, 8, 574, 2960, 1171, 389, 4330, 323, 374, 30073, 311, 279, 2163, 7863, 449, 264, 4279, 8141, 2960, 1171, 389, 4848, 25066, 430, 574, 8767, 7633, 369, 304, 65932, 65216, 323, 6931, 67861, 65216, 89873, 220, 1187, 320, 23966, 13, 220, 16, 65, 7609, 1115, 9455, 13533, 430, 1063, 2849, 71177, 304, 279, 8814, 87701, 1253, 387, 12742, 311, 1884, 13468, 304, 1023, 2322, 1394, 20103, 13, 12220, 4216, 48694, 4500, 320, 508, 1794, 25390, 77594, 347, 18558, 7917, 2949, 279, 48694, 2115, 6244, 74595, 660, 3235, 279, 52344, 8183, 320, 23966, 13, 220, 16, 64, 7026, 23377, 430, 814, 1051, 1234, 24408, 13, 3296, 3974, 32758, 220, 972, 4235, 508, 1794, 13, 356, 1929, 487, 39, 17, 33, 4235, 9560, 11960, 19496, 89873, 430, 53336, 275, 7162, 3237, 11499, 57211, 11960, 320, 1116, 13, 220, 914, 7026, 584, 1766, 430, 2849, 13096, 17140, 574, 48761, 53403, 708, 688, 81, 750, 304, 48694, 2115, 323, 2536, 2922, 21495, 45569, 12235, 77594, 347, 4289, 320, 23966, 13, 220, 16, 66, 7609, 3296, 5694, 11, 1521, 2849, 71177, 1053, 9407, 279, 52344, 8183, 315, 520, 3325, 279, 77594, 347, 18558, 6324, 13, 15636, 11, 14573, 5382, 2849, 56427, 526, 3808, 1253, 387, 3062, 311, 29376, 502, 7917, 2085, 1612, 52572, 20438, 6211, 13, 19575, 220, 16, 25, 14299, 45982, 323, 958, 5531, 367, 315, 362, 643, 84360, 12170, 13, 320, 264, 883, 15323, 3768, 3857, 315, 22408, 347, 20588, 4235, 764, 37037, 307, 258, 5594, 2692, 864, 6830, 643, 320, 508, 1794, 6266, 4553, 48694, 2115, 320, 1527, 1794, 635, 220, 22, 311, 220, 806, 11, 12264, 120, 220, 5154, 77594, 347, 18558, 7917, 8, 45296, 3977, 323, 2536, 2902, 327, 24346, 2849, 1948, 9268, 439, 1664, 439, 52344, 74595, 367, 315, 1063, 77594, 347, 18558, 7917, 320, 31548, 1908, 304, 99371, 435, 14801, 220, 19, 323, 220, 20, 7609, 320, 293, 883, 35009, 315, 1396, 315, 2849, 36956, 4315, 220, 972, 4235, 508, 1794, 13, 48694, 37808, 77594, 347, 18558, 7917, 13, 320, 272, 883, 56996, 7234, 14393, 31768, 521, 4791, 2442, 301, 5237, 521, 9320, 27030, 315, 48694, 37808, 77594, 347, 4289, 7917, 320, 308, 284, 220, 18, 11, 220, 1758, 4235, 1272, 2849, 37601, 320, 543, 2849, 37601, 14, 17, 305, 892, 2922, 7629, 2835, 8, 824, 220, 972, 4235, 508, 1794, 13, 87701, 570, 320, 294, 1389, 282, 883, 15323, 3768, 22343, 315, 279, 77594, 347, 18558, 350, 9991, 7586, 830, 487, 39, 17, 33, 4235, 53, 38965, 19496, 304, 864, 16405, 1653, 61568, 48694, 2115, 320, 845, 1794, 16016, 294, 7026, 4216, 79516, 48694, 2115, 320, 972, 1794, 16016, 384, 7026, 323, 1772, 55873, 7246, 48694, 2115, 320, 1313, 1794, 16016, 282, 883, 320, 12481, 25, 423, 7227, 570, 320, 342, 883, 64341, 315, 350, 9991, 7586, 830, 487, 39, 17, 33, 4235, 53, 38965, 69788, 7917, 304, 279, 48694, 2115, 19579, 45569, 12235, 304, 220, 972, 4235, 508, 1794, 13, 89873, 320, 308, 284, 220, 18, 89873, 26, 393, 284, 220, 15, 13, 6726, 17, 320, 14428, 753, 259, 482, 1985, 4682, 320, 305, 883, 64341, 315, 281, 24056, 18, 69788, 7917, 8844, 311, 2860, 7917, 19579, 11668, 315, 281, 24056, 18, 69788, 7917, 8844, 311, 350, 9991, 7586, 830, 487, 39, 17, 33, 4235, 53, 38965, 69788, 7917, 304, 279, 48694, 2115, 304, 220, 972, 4235, 508, 1794, 13, 89873, 320, 308, 284, 220, 18, 89873, 26, 393, 284, 220, 15, 13, 1627, 320, 14428, 753, 259, 482, 1985, 4682, 320, 602, 883, 15323, 3768, 22343, 315, 279, 77594, 347, 18558, 350, 9991, 7586, 830, 487, 39, 17, 33, 4235, 53, 38965, 19496, 304, 459, 362, 643, 8627, 287, 48694, 37808, 320, 843, 1794, 36434, 320, 503, 1174, 597, 883, 2206, 61380, 1963, 320, 503, 883, 323, 52344, 44153, 320, 597, 883, 4315, 53336, 275, 7162, 13605, 473, 17, 33, 4235, 38, 11960, 320, 36369, 287, 2860, 7917, 8, 19579, 350, 9991, 7586, 830, 487, 39, 17, 33, 4235, 53, 38965, 320, 36369, 287, 362, 643, 84360, 12170, 8, 7917, 304, 220, 972, 4235, 508, 1794, 13, 89873, 320, 308, 284, 220, 508, 7917, 304, 220, 18, 89873, 369, 1855, 3044, 26, 320, 503, 883, 393, 284, 220, 15, 13, 4218, 11, 320, 597, 883, 393, 284, 220, 15, 13, 5728, 320, 14428, 753, 259, 482, 1985, 4682, 320, 326, 883, 4212, 2922, 7629, 4101, 315, 264, 220, 508, 1794, 13, 48694, 37808, 77594, 347, 4289, 37810, 350, 9991, 7586, 830, 487, 39, 17, 33, 4235, 53, 38965, 3221, 279, 52344, 19254, 13, 423, 13883, 5238, 11415, 15481, 20438, 19477, 2538, 13, 320, 296, 883, 5008, 315, 362, 643, 84360, 1960, 958, 5531, 367, 1120, 10594, 3545, 311, 279, 52344, 19254, 320, 1171, 1584, 570, 25635, 16283, 13519, 220, 605, 33983, 76, 320, 264, 1174, 326, 7026, 220, 1135, 33983, 76, 320, 294, 128257, 198, 128256, 78191, 198, 31272, 315, 14974, 25175, 323, 264, 53166, 46098, 617, 11096, 8603, 311, 7142, 430, 7106, 8603, 1093, 7410, 323, 24408, 7958, 279, 4500, 315, 49695, 304, 89873, 2345, 61564, 430, 1436, 54108, 387, 1511, 311, 1520, 5471, 7342, 42655, 13, 578, 2128, 11, 2737, 549, 315, 350, 22936, 24490, 28372, 8219, 320, 44, 5484, 705, 549, 315, 350, 17332, 8680, 261, 78868, 83726, 12279, 28143, 44045, 320, 3336, 33, 7614, 8, 323, 82411, 70533, 15429, 596, 2999, 13, 1369, 16023, 473, 1289, 276, 11, 1511, 3974, 32758, 323, 6500, 4211, 311, 4007, 279, 7902, 1990, 22936, 8603, 11, 4442, 304, 2849, 6211, 323, 2849, 7351, 304, 279, 87701, 13, 11205, 4007, 2345, 33966, 420, 2046, 304, 22037, 14299, 40023, 2345, 2656, 14713, 48448, 12823, 311, 8895, 15525, 20616, 1139, 279, 16188, 11618, 315, 6916, 323, 2531, 4500, 13, 39546, 9994, 279, 6650, 315, 364, 15461, 2922, 318, 1302, 6, 1556, 87701, 8638, 704, 27367, 1093, 264, 5041, 11, 1243, 28815, 311, 1893, 6485, 21483, 1093, 49695, 13, 763, 4216, 44481, 14338, 4500, 11, 7917, 22497, 1139, 2380, 13931, 25, 279, 77594, 347, 4289, 11, 902, 7739, 279, 23418, 1887, 11, 6930, 323, 49069, 36853, 26, 279, 11083, 347, 4289, 11, 902, 19159, 279, 30535, 11, 24569, 323, 1455, 315, 279, 3682, 36853, 11, 323, 26, 279, 842, 347, 4289, 11, 902, 10800, 1139, 279, 2547, 596, 42631, 42929, 323, 44032, 6067, 13, 763, 279, 4007, 11, 279, 2128, 7111, 520, 2849, 71177, 304, 279, 77594, 347, 4289, 430, 12192, 48694, 4500, 13, 2435, 1511, 5016, 7526, 11, 2737, 8162, 11843, 285, 20659, 98492, 1113, 72475, 11, 25524, 5457, 8162, 82025, 323, 6324, 14656, 48435, 6500, 4211, 11, 311, 13488, 279, 4216, 18094, 315, 49695, 304, 31069, 7872, 13, 2435, 11352, 430, 439, 7917, 22497, 323, 2274, 11, 279, 1648, 814, 19570, 449, 1855, 1023, 323, 279, 7410, 13239, 505, 19567, 315, 279, 2380, 2849, 13931, 649, 5536, 1268, 1664, 48694, 68543, 22416, 4216, 18094, 315, 1148, 3719, 11977, 477, 14535, 83872, 14454, 13, 330, 1687, 1766, 8056, 6029, 389, 1268, 22936, 8603, 37377, 279, 70430, 315, 7917, 304, 279, 77594, 347, 4289, 6324, 323, 1268, 279, 8631, 2115, 4442, 994, 279, 77594, 347, 4289, 4442, 1202, 6211, 439, 433, 39671, 1359, 2795, 17054, 8219, 13, 32499, 311, 420, 990, 11, 14248, 323, 25175, 3287, 956, 617, 279, 7526, 323, 12823, 311, 3619, 4442, 315, 21483, 389, 264, 20438, 5569, 323, 389, 2678, 5315, 315, 7917, 13, 11361, 311, 872, 14955, 11, 279, 12074, 1440, 430, 1403, 3682, 2849, 13931, 11, 279, 77594, 347, 4289, 323, 11083, 347, 4289, 11, 6604, 311, 1855, 1023, 2225, 99097, 323, 17332, 2464, 2740, 11, 430, 374, 11, 1555, 35715, 9495, 83, 2785, 1203, 323, 13544, 13, 1115, 10758, 374, 10815, 311, 4442, 304, 279, 87701, 13, 17005, 26793, 505, 279, 1917, 315, 279, 2849, 330, 791, 4623, 430, 1403, 39881, 527, 99097, 45830, 323, 430, 1778, 16628, 22223, 35693, 17432, 374, 2216, 13548, 311, 1518, 1359, 2795, 83726, 12279, 28143, 44045, 13, 2057, 6767, 22936, 8603, 11, 279, 12283, 1511, 12823, 46664, 505, 279, 1917, 315, 15266, 323, 15009, 11, 2737, 279, 1005, 315, 264, 21120, 311, 4018, 25066, 1990, 7917, 13, 330, 2746, 499, 3412, 264, 23506, 7200, 1990, 701, 6206, 323, 358, 4018, 433, 1418, 433, 596, 20784, 11, 4400, 8741, 1359, 2795, 83726, 12279, 28143, 44045, 13, 330, 4071, 422, 499, 14841, 279, 23506, 7200, 11, 701, 6206, 10885, 1203, 994, 358, 4018, 433, 13, 3011, 596, 16168, 1148, 8741, 449, 2849, 23546, 1359, 568, 15100, 13, 330, 1687, 1440, 1063, 315, 279, 21389, 430, 527, 3062, 304, 279, 6070, 315, 279, 87701, 369, 4500, 311, 10570, 11, 719, 584, 3287, 956, 1440, 1268, 1884, 44014, 1051, 10815, 449, 7351, 304, 279, 7917, 1359, 2795, 473, 1289, 276, 13, 362, 1853, 311, 27252, 48694, 42655, 6104, 872, 4007, 574, 2884, 389, 264, 7701, 16188, 2237, 11, 279, 2128, 2795, 433, 690, 2187, 1124, 323, 3885, 311, 1935, 3062, 4726, 7504, 1093, 30090, 8603, 304, 323, 1990, 7917, 13, 578, 4007, 1101, 281, 4798, 279, 1648, 369, 279, 13336, 315, 6968, 2731, 47590, 315, 2849, 70430, 323, 279, 4216, 4500, 315, 49695, 13, 330, 2028, 3495, 1436, 54108, 387, 1511, 304, 4754, 6593, 8522, 311, 5471, 48694, 79212, 811, 1359, 2795, 473, 1289, 276, 13, 578, 990, 374, 832, 315, 279, 1176, 3115, 264, 3495, 2128, 706, 9435, 6160, 91004, 5528, 311, 279, 4007, 315, 2849, 323, 20438, 30126, 304, 3974, 56669, 13, 37207, 1317, 9860, 20124, 304, 420, 3495, 2115, 1436, 1121, 304, 264, 5623, 430, 1436, 11857, 22936, 8631, 389, 7917, 304, 89873, 11, 68337, 1148, 1053, 6062, 617, 3719, 264, 409, 10365, 48694, 13, 220, 128257, 198 ]

2,343

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Inference of causality in time series has been principally based on the prediction paradigm. Nonetheless, the predictive causality approach may underestimate the simultaneous and reciprocal nature of causal interactions observed in real-world phenomena. Here, we present a causal-decomposition approach that is not based on prediction, but based on the covariation of cause and effect: cause is that which put, the effect follows; and removed, the effect is removed. Using empirical mode decomposition, we show that causal interaction is encoded in instantaneous phase dependency at a specific time scale, and this phase dependency is diminished when the causal-related intrinsic component is removed from the effect. Furthermore, we demonstrate the generic applicability of our method to both stochastic and deterministic systems, and show the consistency of causal-decomposition method compared to existing methods, and finally uncover the key mode of causal interactions in both modelled and actual predator–prey systems. Introduction Since the philosophical inception of causality by Galilei 1 and Hume 2 that cause must precede the effect in time, the scientific criteria for assessing causal relationships between two time series have been dominated by the notion of prediction, as proposed by Granger 3 . Namely, the causal relationship from variable A to variable B is inferred if the history of variable A is helpful in predicting the value of variable B , rather than using information from the history of variable B alone. Granger causality is based on the time dependency between cause and effect 4 . As discussed by Sugihara et al. 5 , Granger causality is critically dependent on the assumption that cause and effect are separable 3 . While the separability is often satisfied in linear stochastic systems where Granger causality works well, it might not be applicable in nonlinear deterministic systems where separability appears to be impossible because both cause and effect are embedded in a non-separable higher dimension trajectory 6 , 7 . Consequently, Sugihara et al. 5 proposed the convergent cross-mapping (CCM) method based on state-space reconstruction. In this context, cause and effect are state dependent, and variable A is said to causally influence variable B , although counterintuitive, if the state of variable B can be used to predict the state of variable A in the embedded space, and this predictability improves (i.e., converges) as the time series length increases. Existing methods of detecting causality in time series are predominantly based on the Bayesian 8 concept of prediction. However, cause and effect are likely simultaneous 9 . The succession in time of the cause and effect is produced because the cause cannot achieve the totality of its effect in one moment. At the moment when the effect first manifests, it is always simultaneous with its cause. Moreover, most real-world causal interactions are reciprocal; examples include predator–prey relationships and the physiologic regulation of body functions. In this sense, predictive causality may fail because the attempt to estimate the effect with the history of cause is compromised as the history of the cause is already simultaneously influenced by the effect itself, and vice versa. Another constraint of the generalised prediction framework is that it requires a priori knowledge of the extent of past history that may influence and predict the future, such as the time lag between cause and effect in Granger’s paradigm, or the embedding dimensions in state-space reconstructions such as CCM. Furthermore, a causality assessment is incomplete if it is based exclusively on time dependency or state dependency. Time series commonly observed in nature, including those from physiologic system or spontaneous brain activity, contain oscillatory components within specific frequency bands 10 , 11 . Identification of frequency-specific causal interaction is essential to understand the underlying mechanism 12 , 13 . Furthermore, the application of either linear Granger causality or the nonlinear CCM method alone is insufficient to accommodate the complex causal compositions typically observed in real-world data blending with oscillatory stochastic and deterministic mechanisms. Here, we present a causal-decomposition analysis that is not based on prediction, and more importantly, is neither based on time dependency nor state dependency, but based on the instantaneous phase dependency between cause and effect. The causal decomposition essentially involves two assumptions: (1) any cause–effect relationship can be quantified with instantaneous phase dependency between the source and target decomposed as intrinsic components at specific time scale, and (2) the phase dynamics in the target originating from the source are separable from the target itself. We define the cause–effect relationship between two time series according to the covariation principle of cause and effect 1 : cause is that which put, the effect follows; and removed, the effect is removed; thus, variable A causes variable B if the instantaneous phase dependency between A and B is diminished when the intrinsic component in B that is causally related to A is removed from B itself, but not vice versa. To achieve this, we use the ensemble empirical mode decomposition (ensemble EMD) 14 , 15 , 16 to decompose a time series into a finite number of intrinsic mode functions (IMFs) and identify the causal interaction that is encoded in instantaneous phase dependency between two time series at a specific time scale. We validate the causal-decomposition method with both stochastic and deterministic systems and illustrate its application to ecological time series data of prey and predators. Results Illustration of the causal-decomposition method Figure 1 depicts how the causal decomposition can be used to identify the predator–prey causal relationship of Didinium and Paramecium 17 . Briefly, we decomposed the time series of Didinium and Paramecium into two set of IMFs, and determined the instantaneous phase coherence 18 between comparable IMFs from the two time series (Fig. 1a ). Orthogonality and separability tests were performed to determine the ensemble EMD parameter (i.e., added noise level) that minimises the nonorthogonal leakage and root-mean-square of the correlation between the IMFs, thereby ensuring the orthogonality and separability of the IMFs (Fig. 1d, e ). Subsequently, we removed one of the IMFs (e.g., IMF 2) from Paramecium (Fig. 1b ;", "role": "user" }, { "content": "Natural little scientists, human babies love letting go of things and watching them fall. Baby's first experiment teaches them about more than the force of gravity. It establishes the concept of causality—the relationship between cause and effect that all human knowledge depends on. Let it go, it falls. The cause must precede its effect in time, as scientist from Galileo in the 16th Century to Clive Granger in 1969 defined causality. But in many cases, this one-way relationship between cause and effect fails to accurately describe reality. In a recent paper in Nature Communications, scientists led by Albert C. Yang, MD, Ph.D., of Beth Israel Deaconess Medical Center, introduce a new approach to causality that moves away from this temporally linear model of cause and effect. \"The reality in the real-world is that cause and effect are often reciprocal, as in the feedback loops seen in physiologic/endocrine pathways, neuronal regulation, ecosystems, and even the economy,\" said Albert C. Yang, MD, Ph.D., a scientist in the Division of Interdisciplinary Medicine and Biotechnology. \"Our new causal method allows for mutual or two-way causation, in which the effect of a cause can feed back to the cause itself simultaneously.\" Yang and colleagues' new approach defines causality independently from time. Their covariation principle of cause and effect defines cause as that which when present, the effect follows, and that which when removed, the effect is removed. The team demonstrates the new approach by applying it to predator and prey systems. Moreover, Yang and colleagues showed that their model can work well in systems where other causality methods cannot work. \"I would expect the method to represent a breakthrough of causal assessment of observational data,\" said Yang. \"It can be applied to a wide range of causal questions in the scientific field.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Inference of causality in time series has been principally based on the prediction paradigm. Nonetheless, the predictive causality approach may underestimate the simultaneous and reciprocal nature of causal interactions observed in real-world phenomena. Here, we present a causal-decomposition approach that is not based on prediction, but based on the covariation of cause and effect: cause is that which put, the effect follows; and removed, the effect is removed. Using empirical mode decomposition, we show that causal interaction is encoded in instantaneous phase dependency at a specific time scale, and this phase dependency is diminished when the causal-related intrinsic component is removed from the effect. Furthermore, we demonstrate the generic applicability of our method to both stochastic and deterministic systems, and show the consistency of causal-decomposition method compared to existing methods, and finally uncover the key mode of causal interactions in both modelled and actual predator–prey systems. Introduction Since the philosophical inception of causality by Galilei 1 and Hume 2 that cause must precede the effect in time, the scientific criteria for assessing causal relationships between two time series have been dominated by the notion of prediction, as proposed by Granger 3 . Namely, the causal relationship from variable A to variable B is inferred if the history of variable A is helpful in predicting the value of variable B , rather than using information from the history of variable B alone. Granger causality is based on the time dependency between cause and effect 4 . As discussed by Sugihara et al. 5 , Granger causality is critically dependent on the assumption that cause and effect are separable 3 . While the separability is often satisfied in linear stochastic systems where Granger causality works well, it might not be applicable in nonlinear deterministic systems where separability appears to be impossible because both cause and effect are embedded in a non-separable higher dimension trajectory 6 , 7 . Consequently, Sugihara et al. 5 proposed the convergent cross-mapping (CCM) method based on state-space reconstruction. In this context, cause and effect are state dependent, and variable A is said to causally influence variable B , although counterintuitive, if the state of variable B can be used to predict the state of variable A in the embedded space, and this predictability improves (i.e., converges) as the time series length increases. Existing methods of detecting causality in time series are predominantly based on the Bayesian 8 concept of prediction. However, cause and effect are likely simultaneous 9 . The succession in time of the cause and effect is produced because the cause cannot achieve the totality of its effect in one moment. At the moment when the effect first manifests, it is always simultaneous with its cause. Moreover, most real-world causal interactions are reciprocal; examples include predator–prey relationships and the physiologic regulation of body functions. In this sense, predictive causality may fail because the attempt to estimate the effect with the history of cause is compromised as the history of the cause is already simultaneously influenced by the effect itself, and vice versa. Another constraint of the generalised prediction framework is that it requires a priori knowledge of the extent of past history that may influence and predict the future, such as the time lag between cause and effect in Granger’s paradigm, or the embedding dimensions in state-space reconstructions such as CCM. Furthermore, a causality assessment is incomplete if it is based exclusively on time dependency or state dependency. Time series commonly observed in nature, including those from physiologic system or spontaneous brain activity, contain oscillatory components within specific frequency bands 10 , 11 . Identification of frequency-specific causal interaction is essential to understand the underlying mechanism 12 , 13 . Furthermore, the application of either linear Granger causality or the nonlinear CCM method alone is insufficient to accommodate the complex causal compositions typically observed in real-world data blending with oscillatory stochastic and deterministic mechanisms. Here, we present a causal-decomposition analysis that is not based on prediction, and more importantly, is neither based on time dependency nor state dependency, but based on the instantaneous phase dependency between cause and effect. The causal decomposition essentially involves two assumptions: (1) any cause–effect relationship can be quantified with instantaneous phase dependency between the source and target decomposed as intrinsic components at specific time scale, and (2) the phase dynamics in the target originating from the source are separable from the target itself. We define the cause–effect relationship between two time series according to the covariation principle of cause and effect 1 : cause is that which put, the effect follows; and removed, the effect is removed; thus, variable A causes variable B if the instantaneous phase dependency between A and B is diminished when the intrinsic component in B that is causally related to A is removed from B itself, but not vice versa. To achieve this, we use the ensemble empirical mode decomposition (ensemble EMD) 14 , 15 , 16 to decompose a time series into a finite number of intrinsic mode functions (IMFs) and identify the causal interaction that is encoded in instantaneous phase dependency between two time series at a specific time scale. We validate the causal-decomposition method with both stochastic and deterministic systems and illustrate its application to ecological time series data of prey and predators. Results Illustration of the causal-decomposition method Figure 1 depicts how the causal decomposition can be used to identify the predator–prey causal relationship of Didinium and Paramecium 17 . Briefly, we decomposed the time series of Didinium and Paramecium into two set of IMFs, and determined the instantaneous phase coherence 18 between comparable IMFs from the two time series (Fig. 1a ). Orthogonality and separability tests were performed to determine the ensemble EMD parameter (i.e., added noise level) that minimises the nonorthogonal leakage and root-mean-square of the correlation between the IMFs, thereby ensuring the orthogonality and separability of the IMFs (Fig. 1d, e ). Subsequently, we removed one of the IMFs (e.g., IMF 2) from Paramecium (Fig. 1b ;<|im_end|> <|im_start|>assistant Natural little scientists, human babies love letting go of things and watching them fall. Baby's first experiment teaches them about more than the force of gravity. It establishes the concept of causality—the relationship between cause and effect that all human knowledge depends on. Let it go, it falls. The cause must precede its effect in time, as scientist from Galileo in the 16th Century to Clive Granger in 1969 defined causality. But in many cases, this one-way relationship between cause and effect fails to accurately describe reality. In a recent paper in Nature Communications, scientists led by Albert C. Yang, MD, Ph.D., of Beth Israel Deaconess Medical Center, introduce a new approach to causality that moves away from this temporally linear model of cause and effect. "The reality in the real-world is that cause and effect are often reciprocal, as in the feedback loops seen in physiologic/endocrine pathways, neuronal regulation, ecosystems, and even the economy," said Albert C. Yang, MD, Ph.D., a scientist in the Division of Interdisciplinary Medicine and Biotechnology. "Our new causal method allows for mutual or two-way causation, in which the effect of a cause can feed back to the cause itself simultaneously." Yang and colleagues' new approach defines causality independently from time. Their covariation principle of cause and effect defines cause as that which when present, the effect follows, and that which when removed, the effect is removed. The team demonstrates the new approach by applying it to predator and prey systems. Moreover, Yang and colleagues showed that their model can work well in systems where other causality methods cannot work. "I would expect the method to represent a breakthrough of causal assessment of observational data," said Yang. "It can be applied to a wide range of causal questions in the scientific field." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 763, 2251, 315, 25540, 2786, 304, 892, 4101, 706, 1027, 92381, 3196, 389, 279, 20212, 49340, 13, 56733, 11, 279, 60336, 25540, 2786, 5603, 1253, 79583, 279, 58632, 323, 87298, 7138, 315, 59557, 22639, 13468, 304, 1972, 31184, 44247, 13, 5810, 11, 584, 3118, 264, 59557, 6953, 77907, 5603, 430, 374, 539, 3196, 389, 20212, 11, 719, 3196, 389, 279, 22590, 2850, 367, 315, 5353, 323, 2515, 25, 5353, 374, 430, 902, 2231, 11, 279, 2515, 11263, 26, 323, 7108, 11, 279, 2515, 374, 7108, 13, 12362, 46763, 3941, 66266, 11, 584, 1501, 430, 59557, 16628, 374, 21136, 304, 96219, 10474, 24999, 520, 264, 3230, 892, 5569, 11, 323, 420, 10474, 24999, 374, 54182, 994, 279, 59557, 14228, 47701, 3777, 374, 7108, 505, 279, 2515, 13, 24296, 11, 584, 20461, 279, 14281, 4666, 2968, 315, 1057, 1749, 311, 2225, 96340, 323, 73449, 6067, 11, 323, 1501, 279, 29237, 315, 59557, 6953, 77907, 1749, 7863, 311, 6484, 5528, 11, 323, 5616, 45063, 279, 1401, 3941, 315, 59557, 22639, 304, 2225, 1646, 839, 323, 5150, 68006, 4235, 1762, 88, 6067, 13, 29438, 8876, 279, 41903, 54529, 315, 25540, 2786, 555, 10845, 458, 72, 220, 16, 323, 473, 3972, 220, 17, 430, 5353, 2011, 16599, 68, 279, 2515, 304, 892, 11, 279, 12624, 13186, 369, 47614, 59557, 12135, 1990, 1403, 892, 4101, 617, 1027, 30801, 555, 279, 23035, 315, 20212, 11, 439, 11223, 555, 2895, 4091, 220, 18, 662, 31074, 989, 11, 279, 59557, 5133, 505, 3977, 362, 311, 3977, 426, 374, 68695, 422, 279, 3925, 315, 3977, 362, 374, 11190, 304, 52997, 279, 907, 315, 3977, 426, 1174, 4856, 1109, 1701, 2038, 505, 279, 3925, 315, 3977, 426, 7636, 13, 2895, 4091, 25540, 2786, 374, 3196, 389, 279, 892, 24999, 1990, 5353, 323, 2515, 220, 19, 662, 1666, 14407, 555, 84867, 7141, 5169, 1880, 453, 13, 220, 20, 1174, 2895, 4091, 25540, 2786, 374, 41440, 18222, 389, 279, 25329, 430, 5353, 323, 2515, 527, 4941, 481, 220, 18, 662, 6104, 279, 4941, 2968, 374, 3629, 20097, 304, 13790, 96340, 6067, 1405, 2895, 4091, 25540, 2786, 4375, 1664, 11, 433, 2643, 539, 387, 8581, 304, 75098, 73449, 6067, 1405, 4941, 2968, 8111, 311, 387, 12266, 1606, 2225, 5353, 323, 2515, 527, 23711, 304, 264, 2536, 7962, 50256, 5190, 13167, 35782, 220, 21, 1174, 220, 22, 662, 53123, 11, 84867, 7141, 5169, 1880, 453, 13, 220, 20, 11223, 279, 19873, 16149, 5425, 1474, 3713, 320, 3791, 44, 8, 1749, 3196, 389, 1614, 29047, 43738, 13, 763, 420, 2317, 11, 5353, 323, 2515, 527, 1614, 18222, 11, 323, 3977, 362, 374, 1071, 311, 25540, 750, 10383, 3977, 426, 1174, 8051, 5663, 396, 35251, 11, 422, 279, 1614, 315, 3977, 426, 649, 387, 1511, 311, 7168, 279, 1614, 315, 3977, 362, 304, 279, 23711, 3634, 11, 323, 420, 7168, 2968, 36050, 320, 72, 1770, 2637, 19873, 4282, 8, 439, 279, 892, 4101, 3160, 12992, 13, 69571, 5528, 315, 54626, 25540, 2786, 304, 892, 4101, 527, 47904, 3196, 389, 279, 99234, 220, 23, 7434, 315, 20212, 13, 4452, 11, 5353, 323, 2515, 527, 4461, 58632, 220, 24, 662, 578, 50787, 304, 892, 315, 279, 5353, 323, 2515, 374, 9124, 1606, 279, 5353, 4250, 11322, 279, 2458, 2786, 315, 1202, 2515, 304, 832, 4545, 13, 2468, 279, 4545, 994, 279, 2515, 1176, 84332, 11, 433, 374, 2744, 58632, 449, 1202, 5353, 13, 23674, 11, 1455, 1972, 31184, 59557, 22639, 527, 87298, 26, 10507, 2997, 68006, 4235, 1762, 88, 12135, 323, 279, 4571, 72, 39227, 19812, 315, 2547, 5865, 13, 763, 420, 5647, 11, 60336, 25540, 2786, 1253, 3775, 1606, 279, 4879, 311, 16430, 279, 2515, 449, 279, 3925, 315, 5353, 374, 44500, 439, 279, 3925, 315, 279, 5353, 374, 2736, 25291, 28160, 555, 279, 2515, 5196, 11, 323, 17192, 46391, 13, 13596, 22295, 315, 279, 4689, 4147, 20212, 12914, 374, 430, 433, 7612, 264, 4972, 72, 6677, 315, 279, 13112, 315, 3347, 3925, 430, 1253, 10383, 323, 7168, 279, 3938, 11, 1778, 439, 279, 892, 22171, 1990, 5353, 323, 2515, 304, 2895, 4091, 753, 49340, 11, 477, 279, 40188, 15696, 304, 1614, 29047, 16456, 20232, 1778, 439, 356, 10190, 13, 24296, 11, 264, 25540, 2786, 15813, 374, 33243, 422, 433, 374, 3196, 24121, 389, 892, 24999, 477, 1614, 24999, 13, 4212, 4101, 17037, 13468, 304, 7138, 11, 2737, 1884, 505, 4571, 72, 39227, 1887, 477, 54557, 8271, 5820, 11, 6782, 43524, 5382, 6956, 2949, 3230, 11900, 21562, 220, 605, 1174, 220, 806, 662, 59776, 315, 11900, 19440, 59557, 16628, 374, 7718, 311, 3619, 279, 16940, 17383, 220, 717, 1174, 220, 1032, 662, 24296, 11, 279, 3851, 315, 3060, 13790, 2895, 4091, 25540, 2786, 477, 279, 75098, 356, 10190, 1749, 7636, 374, 39413, 311, 29376, 279, 6485, 59557, 62644, 11383, 13468, 304, 1972, 31184, 828, 56941, 449, 43524, 5382, 96340, 323, 73449, 24717, 13, 5810, 11, 584, 3118, 264, 59557, 6953, 77907, 6492, 430, 374, 539, 3196, 389, 20212, 11, 323, 810, 23659, 11, 374, 14188, 3196, 389, 892, 24999, 6463, 1614, 24999, 11, 719, 3196, 389, 279, 96219, 10474, 24999, 1990, 5353, 323, 2515, 13, 578, 59557, 66266, 16168, 18065, 1403, 32946, 25, 320, 16, 8, 904, 5353, 4235, 27153, 5133, 649, 387, 10484, 1908, 449, 96219, 10474, 24999, 1990, 279, 2592, 323, 2218, 29602, 3950, 439, 47701, 6956, 520, 3230, 892, 5569, 11, 323, 320, 17, 8, 279, 10474, 30295, 304, 279, 2218, 71373, 505, 279, 2592, 527, 4941, 481, 505, 279, 2218, 5196, 13, 1226, 7124, 279, 5353, 4235, 27153, 5133, 1990, 1403, 892, 4101, 4184, 311, 279, 22590, 2850, 367, 17966, 315, 5353, 323, 2515, 220, 16, 551, 5353, 374, 430, 902, 2231, 11, 279, 2515, 11263, 26, 323, 7108, 11, 279, 2515, 374, 7108, 26, 8617, 11, 3977, 362, 11384, 3977, 426, 422, 279, 96219, 10474, 24999, 1990, 362, 323, 426, 374, 54182, 994, 279, 47701, 3777, 304, 426, 430, 374, 25540, 750, 5552, 311, 362, 374, 7108, 505, 426, 5196, 11, 719, 539, 17192, 46391, 13, 2057, 11322, 420, 11, 584, 1005, 279, 40126, 46763, 3941, 66266, 320, 49575, 469, 6204, 8, 220, 975, 1174, 220, 868, 1174, 220, 845, 311, 29602, 2972, 264, 892, 4101, 1139, 264, 35326, 1396, 315, 47701, 3941, 5865, 320, 1829, 49400, 8, 323, 10765, 279, 59557, 16628, 430, 374, 21136, 304, 96219, 10474, 24999, 1990, 1403, 892, 4101, 520, 264, 3230, 892, 5569, 13, 1226, 9788, 279, 59557, 6953, 77907, 1749, 449, 2225, 96340, 323, 73449, 6067, 323, 41468, 1202, 3851, 311, 50953, 892, 4101, 828, 315, 37693, 323, 56217, 13, 18591, 39154, 367, 315, 279, 59557, 6953, 77907, 1749, 19575, 220, 16, 62991, 1268, 279, 59557, 66266, 649, 387, 1511, 311, 10765, 279, 68006, 4235, 1762, 88, 59557, 5133, 315, 14910, 64990, 323, 4366, 373, 66, 2411, 220, 1114, 662, 37618, 398, 11, 584, 29602, 3950, 279, 892, 4101, 315, 14910, 64990, 323, 4366, 373, 66, 2411, 1139, 1403, 743, 315, 6654, 49400, 11, 323, 11075, 279, 96219, 10474, 78925, 220, 972, 1990, 30139, 6654, 49400, 505, 279, 1403, 892, 4101, 320, 30035, 13, 220, 16, 64, 7609, 32210, 540, 263, 2786, 323, 4941, 2968, 7177, 1051, 10887, 311, 8417, 279, 40126, 469, 6204, 5852, 320, 72, 1770, 2637, 3779, 12248, 2237, 8, 430, 21877, 5014, 279, 2536, 2419, 67071, 81373, 323, 3789, 84096, 34047, 315, 279, 26670, 1990, 279, 6654, 49400, 11, 28592, 23391, 279, 30299, 540, 263, 2786, 323, 4941, 2968, 315, 279, 6654, 49400, 320, 30035, 13, 220, 16, 67, 11, 384, 7609, 3804, 39742, 11, 584, 7108, 832, 315, 279, 6654, 49400, 320, 68, 1326, 2637, 60170, 220, 17, 8, 505, 4366, 373, 66, 2411, 320, 30035, 13, 220, 16, 65, 2652, 128257, 198, 128256, 78191, 198, 55381, 2697, 14248, 11, 3823, 24869, 3021, 20806, 733, 315, 2574, 323, 10307, 1124, 4498, 13, 21266, 596, 1176, 9526, 33992, 1124, 922, 810, 1109, 279, 5457, 315, 24128, 13, 1102, 64664, 279, 7434, 315, 25540, 2786, 22416, 5133, 1990, 5353, 323, 2515, 430, 682, 3823, 6677, 14117, 389, 13, 6914, 433, 733, 11, 433, 17503, 13, 578, 5353, 2011, 16599, 68, 1202, 2515, 304, 892, 11, 439, 28568, 505, 10845, 85234, 304, 279, 220, 845, 339, 28200, 311, 2493, 535, 2895, 4091, 304, 220, 5162, 24, 4613, 25540, 2786, 13, 2030, 304, 1690, 5157, 11, 420, 832, 27896, 5133, 1990, 5353, 323, 2515, 14865, 311, 30357, 7664, 8903, 13, 763, 264, 3293, 5684, 304, 22037, 26545, 11, 14248, 6197, 555, 17971, 356, 13, 25482, 11, 14306, 11, 2405, 920, 2637, 315, 29103, 6921, 1611, 23184, 434, 13235, 5955, 11, 19678, 264, 502, 5603, 311, 25540, 2786, 430, 11031, 3201, 505, 420, 19502, 750, 13790, 1646, 315, 5353, 323, 2515, 13, 330, 791, 8903, 304, 279, 1972, 31184, 374, 430, 5353, 323, 2515, 527, 3629, 87298, 11, 439, 304, 279, 11302, 30853, 3970, 304, 4571, 72, 39227, 83946, 78738, 44014, 11, 79402, 19812, 11, 61951, 11, 323, 1524, 279, 8752, 1359, 1071, 17971, 356, 13, 25482, 11, 14306, 11, 2405, 920, 2637, 264, 28568, 304, 279, 14829, 315, 5783, 71200, 19152, 323, 12371, 52536, 13, 330, 8140, 502, 59557, 1749, 6276, 369, 27848, 477, 1403, 27896, 25540, 367, 11, 304, 902, 279, 2515, 315, 264, 5353, 649, 5510, 1203, 311, 279, 5353, 5196, 25291, 1210, 25482, 323, 18105, 6, 502, 5603, 19170, 25540, 2786, 29235, 505, 892, 13, 11205, 22590, 2850, 367, 17966, 315, 5353, 323, 2515, 19170, 5353, 439, 430, 902, 994, 3118, 11, 279, 2515, 11263, 11, 323, 430, 902, 994, 7108, 11, 279, 2515, 374, 7108, 13, 578, 2128, 32216, 279, 502, 5603, 555, 19486, 433, 311, 68006, 323, 37693, 6067, 13, 23674, 11, 25482, 323, 18105, 8710, 430, 872, 1646, 649, 990, 1664, 304, 6067, 1405, 1023, 25540, 2786, 5528, 4250, 990, 13, 330, 40, 1053, 1755, 279, 1749, 311, 4097, 264, 42445, 315, 59557, 15813, 315, 90380, 828, 1359, 1071, 25482, 13, 330, 2181, 649, 387, 9435, 311, 264, 7029, 2134, 315, 59557, 4860, 304, 279, 12624, 2115, 1210, 220, 128257, 198 ]

1,676

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The skeletal remains of a small bear ( Protarctos abstrusus ) were collected at the Beaver Pond fossil site in the High Arctic (Ellesmere I., Nunavut). This mid-Pliocene deposit has also yielded 12 other mammals and the remains of a boreal-forest community. Phylogenetic analysis reveals this bear to be basal to modern bears. It appears to represent an immigration event from Asia, leaving no living North American descendants. The dentition shows only modest specialization for herbivory, consistent with its basal position within Ursinae. However, the appearance of dental caries suggest a diet high in fermentable-carbohydrates. Fossil plants remains, including diverse berries, suggests that, like modern northern black bears, P . abstrusus may have exploited a high-sugar diet in the fall to promote fat accumulation and facilitate hibernation. A tendency toward a sugar-rich diet appears to have arisen early in Ursinae, and may have played a role in allowing ursine lineages to occupy cold habitats. Introduction In 1970, Philip Bjork described a small fossil bear from the Pliocene Glenn’s Ferry Formation of southwestern Idaho. Based on a single m1 as the holotype, he was understandably perplexed and named it Ursus abstrusus . Additional material has not been forthcoming since its initial description and this bear has remained an enigma. Hence the discovery in the 1990s of a similar bear from more complete fossils in the Pliocene of the Canadian High Arctic throws much needed light onto the mystery (Fig. 1 ). In addition to resolving the riddle of Ursus abstrusus , with a moderately complete skull and lower jaws with associated postcranials, the new materials present a rare opportunity to fill a large gap in our knowledge of North American High Arctic at a time in the early Pliocene when mean annual temperatures in the High Arctic were ~22 °C warmer than the present polar temperatures 1 . Such a warm climate supported an extensive boreal-type forest biome 2 , 3 , radically different from today’s arid polar tundra 4 . Thus the evidence of this primitive bear in an extinct polar forest offers valuable information about the diet and habitat of this basal ursine. Figure 1 Map of key basal ursine localities in Asia, Europe, and North America and routes of dispersal. The Beaver Pond site is indicated by red star 1 within Arctic Circle and the type locality of Protarctos abstrusus in Idaho is the red star 2, near the edge of the map. For much of the Neogene the Bering isthmus would have served as a land bridge, allowing for an Arctic biotic continuity between Eurasia and North America. By 3.5 Ma the Bering Strait was open, although mammalian dispersal could have been permitted by seasonal sea ice. Pliocene (5 Ma) paleogeography map modified from Wang et al . 86 Fig. 1 and Scotese 87 . Full size image The fossil records of basal ursines has improved with recent discoveries of three relatively complete specimens of basal ursines from China – a very advanced Ursavus 5 and a very primitive Protarctos 6 , 7 . We are now in a position to more tightly bracket the North American Pliocene bears as well as providing a wealth of information about cranial anatomy of basal ursines previously unavailable. The present description of P . abstrusus and a phylogenetic analysis combining molecular and morphological data of most fossil and living ursines for the first time allows a much more detailed view of the history of bears at the critical juncture of their initial diversification. In addition, the presence of dental caries provides insight into the evolutionary history of diet of ursines. Systematic Paleontology Order Carnivora Bowdich,1821 8 . Family Ursidae Fischer van Waldheim, 1817 9 . Subfamily Ursinae Fischer von Waldheim, 1817. Tribe Ursini Fischer von Waldheim, 1817. Protarctos Kretzoi, 1945 10 . Genotypic Species Protarctos boeckhi 11 . Included Species Protarctos boeckhi 11 ; P. abstrusus (Bjork, 1970); P. yinanensis (Li, 1993); and P. ruscinensis 12 . Distribution Pliocene of Europe, Pliocene and early Pleistocene of Asia, and Pliocene of North America. Emended diagnosis Protarctos abstrusus is a basal ursine the size of a small Asian black bear. It has a flat forehead covering an uninflated frontal sinus; very high sagittal crest that projects backward to overhang the occipital condyle (Figs 2 and 3 ); P4 with a small, distinct protocone situated at the level of carnassial notch; M2 talon modestly developed but not very elongated (Figs 4 and 5 ); no pre-metaconid on m1, smooth posterior surface of m1 trigonid without zigzag pattern, presence of a distinct pre-entoconid; m2 shorter than m1 (Fig. 6 and Supplementary Fig. S2 ). It is about the same size as P . boeckhi and differs from it in the relatively smaller p4, presence of a tiny cuspule on lingual side of posterior crest in p4, and presence of a pre-entoconid on m1. P . abstrusus is also similar in size to P . yinanensis and can be distinguished from the latter in a flattened forehead, posteriorly projected sagittal crest, p4 posterior accessory cuspule on lingual side of posterior crest, an m1 pre-entoconid, and less elongated M1 and M2. P . abstrusus differs from P . ruscinensis by its lack of unique features of the latter such as a deep angular process, reduction of P4 protocone, and a single entoconid on m1. Figure 2 Right ( A ) and left ( B ) lateral views of the skull of Protarctos abstrusus (CMN 54380), composite laser scans of five individual cranial fragments, assembled in Avizo Lite (version 9.0.0) and visualized in PointStream 3D Image Suite (Version 3.2.0.0). Full size image Figure 3 Dorsal ( A ) and ventral ( B ) views of the skull of Protarctos abstrusus (CMN 54380), composite laser scans of five individual cranial fragments, assembled in Avizo Lite (version 9.0.0) and visualized in PointStream 3D Image Suite (Version 3.2.0.0). Full size image Figure 4 Left upper posterior teeth (P4-M2) of Protarctos abstrusus , CMN 54380; ( A ) buccal, and", "role": "user" }, { "content": "Researchers from the Canadian Museum of Nature and the Natural History Museum of Los Angeles County have identified remains of a 3.5-million-year-old bear from a fossil-rich site in Canada's High Arctic. Their study shows not only that the animal is a close relative of the ancestor of modern bears—tracing its ancestry to extinct bears of similar age from East Asia—but that it also had a sweet tooth, as determined by cavities in the teeth. The scientists identify the bear as Protarctos abstrusus, which was previously only known from a tooth found in Idaho. Showing its transitional nature, the animal was slightly smaller than a modern black bear, with a flatter head and a combination of primitive and advanced dental characters. The results are published today in the journal Scientific Reports. \"This is evidence of the most northerly record for primitive bears, and provides an idea of what the ancestor of modern bears may have looked like,\" says Dr. Xiaoming Wang, lead author of the study and Head of Vertebrate Paleontology at the Natural History Museum of Los Angeles County (NHMLA). \"Just as interesting is the presence of dental caries, showing that oral infections have a long evolutionary history in the animals, which can tell us about their sugary diet, presumably from berries. This is the first and earliest documented occurrence of high-calorie diet in basal bears, likely related to fat storage in preparation for the harsh Arctic winters.\" The research team, which included co-author Dr. Natalia Rybczynski, a Research Associate and paleontologist with the Canadian Museum of Nature, were able to study recovered bones from the skull, jaws and teeth, as well as parts of the skeleton from two individuals. A view of the Beaver Pond fossil site, with a number of the animals and plants based on fossils recovered from the site. In the background, there is a bear family. When this art was contracted 15 years ago by the Canadian Museum of Nature, it wasn't known exactly what they were but can now be Protarctos. Credit: Art by George \"Rinaldinho\" Teichmann. The bones were discovered over a 20-year period by Canadian Museum of Nature scientists, including Dr. Rybczynski, at a fossil locality on Ellesmere Island known as the Beaver Pond site. The peat deposits include fossilized plants indicative of a boreal-type wetland forest, and have yielded other fossils, including fish, beaver, small carnivores, deerlets, and a three-toed horse. The findings show that the Ellesmere Protarctos lived in a northern boreal-type forest habitat, where there would have been 24-hour darkness in winter, as well as about six months of ice and snow. \"It is a significant find, in part because all other ancient fossil ursine bears, and even some modern bear species like the sloth bear and sun bear, are associated with lower-latitude, milder habitats,\" says co-author Dr. Rybczynski. \"So, the Ellesmere bear is important because it suggests that the capacity to exploit the harshest, most northern forests on the planet is not an innovation of modern grizzlies and black bears, but may have characterized the ursine lineage from its beginning.\" Dr. Wang analyzed characteristics of fossil bear remains from around the world to identify the Ellesmere remains as Protarctos and to establish its evolutionary lineage in relation to other bears. Modern bears are wide-ranging, found from equatorial to polar regions. Their ancestors, mainly found in Eurasia, date to about 5 million years ago. Digital reconstruction of the Canadian Arctic fossil bear, Protarctos abstrusus. Credit: Xiaoming Wang Fossil records of ursine bears (all living bears plus their ancestors, except the giant panda, which is an early offshoot) are poor and their early evolution controversial. The new fossil represents one of the early immigrations from Asia to North America but it is probably not a direct ancestor to the modern American black bear. Of further significance is that the teeth of both Protarctos individuals show signs of well-developed dental cavities, which were identified following CT scans by Stuart White, a retired professor with the UCLA School of Dentistry. The cavities underline that these ancient bears consumed large amounts of sugary foods such as berries. Indeed, berry plants are found preserved in the same Ellesmere deposits as the bear remains. \"We know that modern bears consume sugary fruits in the fall to promote fat accumulation that allows for winter survival via hibernation. The dental cavities in Protarctos suggest that consumption of sugar-rich foods like berries, in preparation for winter hibernation, developed early in the evolution of bears as a survival strategy,\" explains Rybczynski. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The skeletal remains of a small bear ( Protarctos abstrusus ) were collected at the Beaver Pond fossil site in the High Arctic (Ellesmere I., Nunavut). This mid-Pliocene deposit has also yielded 12 other mammals and the remains of a boreal-forest community. Phylogenetic analysis reveals this bear to be basal to modern bears. It appears to represent an immigration event from Asia, leaving no living North American descendants. The dentition shows only modest specialization for herbivory, consistent with its basal position within Ursinae. However, the appearance of dental caries suggest a diet high in fermentable-carbohydrates. Fossil plants remains, including diverse berries, suggests that, like modern northern black bears, P . abstrusus may have exploited a high-sugar diet in the fall to promote fat accumulation and facilitate hibernation. A tendency toward a sugar-rich diet appears to have arisen early in Ursinae, and may have played a role in allowing ursine lineages to occupy cold habitats. Introduction In 1970, Philip Bjork described a small fossil bear from the Pliocene Glenn’s Ferry Formation of southwestern Idaho. Based on a single m1 as the holotype, he was understandably perplexed and named it Ursus abstrusus . Additional material has not been forthcoming since its initial description and this bear has remained an enigma. Hence the discovery in the 1990s of a similar bear from more complete fossils in the Pliocene of the Canadian High Arctic throws much needed light onto the mystery (Fig. 1 ). In addition to resolving the riddle of Ursus abstrusus , with a moderately complete skull and lower jaws with associated postcranials, the new materials present a rare opportunity to fill a large gap in our knowledge of North American High Arctic at a time in the early Pliocene when mean annual temperatures in the High Arctic were ~22 °C warmer than the present polar temperatures 1 . Such a warm climate supported an extensive boreal-type forest biome 2 , 3 , radically different from today’s arid polar tundra 4 . Thus the evidence of this primitive bear in an extinct polar forest offers valuable information about the diet and habitat of this basal ursine. Figure 1 Map of key basal ursine localities in Asia, Europe, and North America and routes of dispersal. The Beaver Pond site is indicated by red star 1 within Arctic Circle and the type locality of Protarctos abstrusus in Idaho is the red star 2, near the edge of the map. For much of the Neogene the Bering isthmus would have served as a land bridge, allowing for an Arctic biotic continuity between Eurasia and North America. By 3.5 Ma the Bering Strait was open, although mammalian dispersal could have been permitted by seasonal sea ice. Pliocene (5 Ma) paleogeography map modified from Wang et al . 86 Fig. 1 and Scotese 87 . Full size image The fossil records of basal ursines has improved with recent discoveries of three relatively complete specimens of basal ursines from China – a very advanced Ursavus 5 and a very primitive Protarctos 6 , 7 . We are now in a position to more tightly bracket the North American Pliocene bears as well as providing a wealth of information about cranial anatomy of basal ursines previously unavailable. The present description of P . abstrusus and a phylogenetic analysis combining molecular and morphological data of most fossil and living ursines for the first time allows a much more detailed view of the history of bears at the critical juncture of their initial diversification. In addition, the presence of dental caries provides insight into the evolutionary history of diet of ursines. Systematic Paleontology Order Carnivora Bowdich,1821 8 . Family Ursidae Fischer van Waldheim, 1817 9 . Subfamily Ursinae Fischer von Waldheim, 1817. Tribe Ursini Fischer von Waldheim, 1817. Protarctos Kretzoi, 1945 10 . Genotypic Species Protarctos boeckhi 11 . Included Species Protarctos boeckhi 11 ; P. abstrusus (Bjork, 1970); P. yinanensis (Li, 1993); and P. ruscinensis 12 . Distribution Pliocene of Europe, Pliocene and early Pleistocene of Asia, and Pliocene of North America. Emended diagnosis Protarctos abstrusus is a basal ursine the size of a small Asian black bear. It has a flat forehead covering an uninflated frontal sinus; very high sagittal crest that projects backward to overhang the occipital condyle (Figs 2 and 3 ); P4 with a small, distinct protocone situated at the level of carnassial notch; M2 talon modestly developed but not very elongated (Figs 4 and 5 ); no pre-metaconid on m1, smooth posterior surface of m1 trigonid without zigzag pattern, presence of a distinct pre-entoconid; m2 shorter than m1 (Fig. 6 and Supplementary Fig. S2 ). It is about the same size as P . boeckhi and differs from it in the relatively smaller p4, presence of a tiny cuspule on lingual side of posterior crest in p4, and presence of a pre-entoconid on m1. P . abstrusus is also similar in size to P . yinanensis and can be distinguished from the latter in a flattened forehead, posteriorly projected sagittal crest, p4 posterior accessory cuspule on lingual side of posterior crest, an m1 pre-entoconid, and less elongated M1 and M2. P . abstrusus differs from P . ruscinensis by its lack of unique features of the latter such as a deep angular process, reduction of P4 protocone, and a single entoconid on m1. Figure 2 Right ( A ) and left ( B ) lateral views of the skull of Protarctos abstrusus (CMN 54380), composite laser scans of five individual cranial fragments, assembled in Avizo Lite (version 9.0.0) and visualized in PointStream 3D Image Suite (Version 3.2.0.0). Full size image Figure 3 Dorsal ( A ) and ventral ( B ) views of the skull of Protarctos abstrusus (CMN 54380), composite laser scans of five individual cranial fragments, assembled in Avizo Lite (version 9.0.0) and visualized in PointStream 3D Image Suite (Version 3.2.0.0). Full size image Figure 4 Left upper posterior teeth (P4-M2) of Protarctos abstrusus , CMN 54380; ( A ) buccal, and<|im_end|> <|im_start|>assistant Researchers from the Canadian Museum of Nature and the Natural History Museum of Los Angeles County have identified remains of a 3.5-million-year-old bear from a fossil-rich site in Canada's High Arctic. Their study shows not only that the animal is a close relative of the ancestor of modern bears—tracing its ancestry to extinct bears of similar age from East Asia—but that it also had a sweet tooth, as determined by cavities in the teeth. The scientists identify the bear as Protarctos abstrusus, which was previously only known from a tooth found in Idaho. Showing its transitional nature, the animal was slightly smaller than a modern black bear, with a flatter head and a combination of primitive and advanced dental characters. The results are published today in the journal Scientific Reports. "This is evidence of the most northerly record for primitive bears, and provides an idea of what the ancestor of modern bears may have looked like," says Dr. Xiaoming Wang, lead author of the study and Head of Vertebrate Paleontology at the Natural History Museum of Los Angeles County (NHMLA). "Just as interesting is the presence of dental caries, showing that oral infections have a long evolutionary history in the animals, which can tell us about their sugary diet, presumably from berries. This is the first and earliest documented occurrence of high-calorie diet in basal bears, likely related to fat storage in preparation for the harsh Arctic winters." The research team, which included co-author Dr. Natalia Rybczynski, a Research Associate and paleontologist with the Canadian Museum of Nature, were able to study recovered bones from the skull, jaws and teeth, as well as parts of the skeleton from two individuals. A view of the Beaver Pond fossil site, with a number of the animals and plants based on fossils recovered from the site. In the background, there is a bear family. When this art was contracted 15 years ago by the Canadian Museum of Nature, it wasn't known exactly what they were but can now be Protarctos. Credit: Art by George "Rinaldinho" Teichmann. The bones were discovered over a 20-year period by Canadian Museum of Nature scientists, including Dr. Rybczynski, at a fossil locality on Ellesmere Island known as the Beaver Pond site. The peat deposits include fossilized plants indicative of a boreal-type wetland forest, and have yielded other fossils, including fish, beaver, small carnivores, deerlets, and a three-toed horse. The findings show that the Ellesmere Protarctos lived in a northern boreal-type forest habitat, where there would have been 24-hour darkness in winter, as well as about six months of ice and snow. "It is a significant find, in part because all other ancient fossil ursine bears, and even some modern bear species like the sloth bear and sun bear, are associated with lower-latitude, milder habitats," says co-author Dr. Rybczynski. "So, the Ellesmere bear is important because it suggests that the capacity to exploit the harshest, most northern forests on the planet is not an innovation of modern grizzlies and black bears, but may have characterized the ursine lineage from its beginning." Dr. Wang analyzed characteristics of fossil bear remains from around the world to identify the Ellesmere remains as Protarctos and to establish its evolutionary lineage in relation to other bears. Modern bears are wide-ranging, found from equatorial to polar regions. Their ancestors, mainly found in Eurasia, date to about 5 million years ago. Digital reconstruction of the Canadian Arctic fossil bear, Protarctos abstrusus. Credit: Xiaoming Wang Fossil records of ursine bears (all living bears plus their ancestors, except the giant panda, which is an early offshoot) are poor and their early evolution controversial. The new fossil represents one of the early immigrations from Asia to North America but it is probably not a direct ancestor to the modern American black bear. Of further significance is that the teeth of both Protarctos individuals show signs of well-developed dental cavities, which were identified following CT scans by Stuart White, a retired professor with the UCLA School of Dentistry. The cavities underline that these ancient bears consumed large amounts of sugary foods such as berries. Indeed, berry plants are found preserved in the same Ellesmere deposits as the bear remains. "We know that modern bears consume sugary fruits in the fall to promote fat accumulation that allows for winter survival via hibernation. The dental cavities in Protarctos suggest that consumption of sugar-rich foods like berries, in preparation for winter hibernation, developed early in the evolution of bears as a survival strategy," explains Rybczynski. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 69397, 8625, 315, 264, 2678, 11984, 320, 11970, 277, 302, 437, 671, 496, 355, 355, 883, 1051, 14890, 520, 279, 92534, 71965, 31376, 2816, 304, 279, 5234, 37518, 320, 6719, 645, 61031, 358, 2637, 64778, 402, 332, 570, 1115, 5209, 9483, 747, 78782, 16946, 706, 1101, 58487, 220, 717, 1023, 56669, 323, 279, 8625, 315, 264, 39786, 278, 12, 51755, 4029, 13, 93682, 86945, 5411, 6492, 21667, 420, 11984, 311, 387, 80710, 311, 6617, 30824, 13, 1102, 8111, 311, 4097, 459, 15443, 1567, 505, 13936, 11, 9564, 912, 5496, 4892, 3778, 49446, 13, 578, 18653, 684, 5039, 1193, 27946, 66979, 369, 39999, 344, 683, 11, 13263, 449, 1202, 80710, 2361, 2949, 71138, 125887, 13, 4452, 11, 279, 11341, 315, 29106, 1841, 552, 4284, 264, 10173, 1579, 304, 68736, 481, 24948, 34658, 988, 13, 435, 85061, 11012, 8625, 11, 2737, 17226, 63494, 11, 13533, 430, 11, 1093, 6617, 18671, 3776, 30824, 11, 393, 662, 671, 496, 355, 355, 1253, 617, 51763, 264, 1579, 1355, 8734, 10173, 304, 279, 4498, 311, 12192, 8834, 46835, 323, 28696, 305, 18127, 367, 13, 362, 31954, 9017, 264, 13465, 41947, 10173, 8111, 311, 617, 90954, 4216, 304, 71138, 125887, 11, 323, 1253, 617, 6476, 264, 3560, 304, 10923, 220, 1759, 483, 1584, 1154, 311, 48678, 9439, 71699, 13, 29438, 763, 220, 4468, 15, 11, 26241, 69841, 672, 7633, 264, 2678, 31376, 11984, 505, 279, 393, 747, 78782, 40208, 753, 79549, 72466, 315, 99911, 40687, 13, 20817, 389, 264, 3254, 296, 16, 439, 279, 24429, 4249, 11, 568, 574, 88098, 74252, 291, 323, 7086, 433, 71138, 355, 671, 496, 355, 355, 662, 24086, 3769, 706, 539, 1027, 45764, 2533, 1202, 2926, 4096, 323, 420, 11984, 706, 14958, 459, 665, 11750, 13, 32140, 279, 18841, 304, 279, 220, 2550, 15, 82, 315, 264, 4528, 11984, 505, 810, 4686, 81473, 304, 279, 393, 747, 78782, 315, 279, 12152, 5234, 37518, 3872, 1790, 4460, 3177, 8800, 279, 23347, 320, 30035, 13, 220, 16, 7609, 763, 5369, 311, 53583, 279, 436, 3390, 315, 71138, 355, 671, 496, 355, 355, 1174, 449, 264, 70351, 4686, 35113, 323, 4827, 82356, 449, 5938, 1772, 73085, 10522, 11, 279, 502, 7384, 3118, 264, 9024, 6776, 311, 5266, 264, 3544, 13225, 304, 1057, 6677, 315, 4892, 3778, 5234, 37518, 520, 264, 892, 304, 279, 4216, 393, 747, 78782, 994, 3152, 9974, 20472, 304, 279, 5234, 37518, 1051, 4056, 1313, 37386, 34, 46039, 1109, 279, 3118, 25685, 20472, 220, 16, 662, 15483, 264, 8369, 10182, 7396, 459, 16781, 39786, 278, 10827, 13952, 84710, 220, 17, 1174, 220, 18, 1174, 61127, 2204, 505, 3432, 753, 802, 307, 25685, 259, 79830, 220, 19, 662, 14636, 279, 6029, 315, 420, 28694, 11984, 304, 459, 69918, 25685, 13952, 6209, 15525, 2038, 922, 279, 10173, 323, 39646, 315, 420, 80710, 220, 1759, 483, 13, 19575, 220, 16, 5135, 315, 1401, 80710, 220, 1759, 483, 2254, 1385, 304, 13936, 11, 4606, 11, 323, 4892, 5270, 323, 11543, 315, 79835, 278, 13, 578, 92534, 71965, 2816, 374, 16717, 555, 2579, 6917, 220, 16, 2949, 37518, 21918, 323, 279, 955, 69187, 315, 11970, 277, 302, 437, 671, 496, 355, 355, 304, 40687, 374, 279, 2579, 6917, 220, 17, 11, 3221, 279, 6964, 315, 279, 2472, 13, 1789, 1790, 315, 279, 4275, 34224, 279, 426, 4776, 6127, 35401, 355, 1053, 617, 10434, 439, 264, 4363, 14497, 11, 10923, 369, 459, 37518, 6160, 14546, 50106, 1990, 88177, 689, 323, 4892, 5270, 13, 3296, 220, 18, 13, 20, 11583, 279, 426, 4776, 83163, 574, 1825, 11, 8051, 36041, 10700, 79835, 278, 1436, 617, 1027, 15480, 555, 36899, 9581, 10054, 13, 393, 747, 78782, 320, 20, 11583, 8, 28639, 41632, 5814, 2472, 11041, 505, 29346, 1880, 453, 662, 220, 4218, 23966, 13, 220, 16, 323, 15835, 2423, 220, 4044, 662, 8797, 1404, 2217, 578, 31376, 7576, 315, 80710, 220, 1759, 1572, 706, 13241, 449, 3293, 54098, 315, 2380, 12309, 4686, 57749, 315, 80710, 220, 1759, 1572, 505, 5734, 1389, 264, 1633, 11084, 71138, 402, 355, 220, 20, 323, 264, 1633, 28694, 11970, 277, 302, 437, 220, 21, 1174, 220, 22, 662, 1226, 527, 1457, 304, 264, 2361, 311, 810, 40069, 32742, 279, 4892, 3778, 393, 747, 78782, 30824, 439, 1664, 439, 8405, 264, 12205, 315, 2038, 922, 70637, 532, 62690, 315, 80710, 220, 1759, 1572, 8767, 36087, 13, 578, 3118, 4096, 315, 393, 662, 671, 496, 355, 355, 323, 264, 37555, 86945, 5411, 6492, 35271, 31206, 323, 27448, 5848, 828, 315, 1455, 31376, 323, 5496, 220, 1759, 1572, 369, 279, 1176, 892, 6276, 264, 1790, 810, 11944, 1684, 315, 279, 3925, 315, 30824, 520, 279, 9200, 18169, 302, 554, 315, 872, 2926, 21797, 2461, 13, 763, 5369, 11, 279, 9546, 315, 29106, 1841, 552, 5825, 20616, 1139, 279, 41993, 3925, 315, 10173, 315, 220, 1759, 1572, 13, 744, 780, 12629, 63333, 7365, 32749, 344, 6347, 18943, 67, 718, 11, 10828, 16, 220, 23, 662, 12517, 71138, 114405, 63016, 5355, 51668, 21215, 11, 220, 10562, 22, 220, 24, 662, 3804, 19521, 71138, 125887, 63016, 6675, 51668, 21215, 11, 220, 10562, 22, 13, 63804, 71138, 6729, 63016, 6675, 51668, 21215, 11, 220, 10562, 22, 13, 11970, 277, 302, 437, 735, 2171, 89, 6870, 11, 220, 6393, 20, 220, 605, 662, 9500, 37941, 292, 51567, 11970, 277, 302, 437, 712, 101458, 6151, 220, 806, 662, 47064, 51567, 11970, 277, 302, 437, 712, 101458, 6151, 220, 806, 2652, 393, 13, 671, 496, 355, 355, 320, 33, 73, 672, 11, 220, 4468, 15, 1237, 393, 13, 379, 74276, 87778, 320, 46521, 11, 220, 2550, 18, 1237, 323, 393, 13, 53554, 18595, 87778, 220, 717, 662, 35009, 393, 747, 78782, 315, 4606, 11, 393, 747, 78782, 323, 4216, 33540, 380, 78782, 315, 13936, 11, 323, 393, 747, 78782, 315, 4892, 5270, 13, 5867, 2954, 23842, 11970, 277, 302, 437, 671, 496, 355, 355, 374, 264, 80710, 220, 1759, 483, 279, 1404, 315, 264, 2678, 14875, 3776, 11984, 13, 1102, 706, 264, 10269, 52354, 18702, 459, 71113, 1517, 660, 66746, 76914, 26, 1633, 1579, 30811, 83223, 73024, 430, 7224, 28655, 311, 927, 21313, 279, 3056, 575, 2223, 9955, 982, 320, 37, 14801, 220, 17, 323, 220, 18, 7048, 393, 19, 449, 264, 2678, 11, 12742, 18940, 59182, 31183, 520, 279, 2237, 315, 39438, 395, 532, 51554, 26, 386, 17, 8374, 263, 27946, 398, 8040, 719, 539, 1633, 74595, 660, 320, 37, 14801, 220, 19, 323, 220, 20, 7048, 912, 864, 55117, 444, 307, 389, 296, 16, 11, 11113, 46000, 7479, 315, 296, 16, 54033, 263, 307, 2085, 86912, 93774, 5497, 11, 9546, 315, 264, 12742, 864, 12, 17996, 444, 307, 26, 296, 17, 24210, 1109, 296, 16, 320, 30035, 13, 220, 21, 323, 99371, 23966, 13, 328, 17, 7609, 1102, 374, 922, 279, 1890, 1404, 439, 393, 662, 712, 101458, 6151, 323, 44642, 505, 433, 304, 279, 12309, 9333, 281, 19, 11, 9546, 315, 264, 13987, 272, 30863, 1130, 389, 38172, 940, 3185, 315, 46000, 73024, 304, 281, 19, 11, 323, 9546, 315, 264, 864, 12, 17996, 444, 307, 389, 296, 16, 13, 393, 662, 671, 496, 355, 355, 374, 1101, 4528, 304, 1404, 311, 393, 662, 379, 74276, 87778, 323, 649, 387, 39575, 505, 279, 15629, 304, 264, 68461, 52354, 11, 46000, 398, 28448, 30811, 83223, 73024, 11, 281, 19, 46000, 43081, 272, 30863, 1130, 389, 38172, 940, 3185, 315, 46000, 73024, 11, 459, 296, 16, 864, 12, 17996, 444, 307, 11, 323, 2753, 74595, 660, 386, 16, 323, 386, 17, 13, 393, 662, 671, 496, 355, 355, 44642, 505, 393, 662, 53554, 18595, 87778, 555, 1202, 6996, 315, 5016, 4519, 315, 279, 15629, 1778, 439, 264, 5655, 20932, 1920, 11, 14278, 315, 393, 19, 18940, 59182, 11, 323, 264, 3254, 1218, 78, 444, 307, 389, 296, 16, 13, 19575, 220, 17, 10291, 320, 362, 883, 323, 2163, 320, 426, 883, 45569, 6325, 315, 279, 35113, 315, 11970, 277, 302, 437, 671, 496, 355, 355, 320, 10190, 45, 220, 19642, 1490, 705, 28814, 21120, 43739, 315, 4330, 3927, 70637, 532, 35603, 11, 35105, 304, 7671, 43994, 41965, 320, 4464, 220, 24, 13, 15, 13, 15, 8, 323, 9302, 1534, 304, 5236, 3103, 220, 18, 35, 4758, 21652, 320, 5755, 220, 18, 13, 17, 13, 15, 13, 15, 570, 8797, 1404, 2217, 19575, 220, 18, 423, 1105, 278, 320, 362, 883, 323, 10594, 3545, 320, 426, 883, 6325, 315, 279, 35113, 315, 11970, 277, 302, 437, 671, 496, 355, 355, 320, 10190, 45, 220, 19642, 1490, 705, 28814, 21120, 43739, 315, 4330, 3927, 70637, 532, 35603, 11, 35105, 304, 7671, 43994, 41965, 320, 4464, 220, 24, 13, 15, 13, 15, 8, 323, 9302, 1534, 304, 5236, 3103, 220, 18, 35, 4758, 21652, 320, 5755, 220, 18, 13, 17, 13, 15, 13, 15, 570, 8797, 1404, 2217, 19575, 220, 19, 14043, 8582, 46000, 18311, 320, 47, 19, 5364, 17, 8, 315, 11970, 277, 302, 437, 671, 496, 355, 355, 1174, 18582, 45, 220, 19642, 1490, 26, 320, 362, 883, 1048, 641, 278, 11, 323, 128257, 198, 128256, 78191, 198, 60210, 505, 279, 12152, 16730, 315, 22037, 323, 279, 18955, 11346, 16730, 315, 9853, 12167, 6406, 617, 11054, 8625, 315, 264, 220, 18, 13, 20, 46149, 4771, 6418, 11984, 505, 264, 31376, 41947, 2816, 304, 7008, 596, 5234, 37518, 13, 11205, 4007, 5039, 539, 1193, 430, 279, 10065, 374, 264, 3345, 8844, 315, 279, 46831, 315, 6617, 30824, 2345, 376, 4628, 1202, 66004, 311, 69918, 30824, 315, 4528, 4325, 505, 6460, 13936, 38542, 430, 433, 1101, 1047, 264, 10437, 26588, 11, 439, 11075, 555, 57709, 1385, 304, 279, 18311, 13, 578, 14248, 10765, 279, 11984, 439, 11970, 277, 302, 437, 671, 496, 355, 355, 11, 902, 574, 8767, 1193, 3967, 505, 264, 26588, 1766, 304, 40687, 13, 72030, 1202, 66743, 7138, 11, 279, 10065, 574, 10284, 9333, 1109, 264, 6617, 3776, 11984, 11, 449, 264, 1344, 1683, 2010, 323, 264, 10824, 315, 28694, 323, 11084, 29106, 5885, 13, 578, 3135, 527, 4756, 3432, 304, 279, 8486, 38130, 29140, 13, 330, 2028, 374, 6029, 315, 279, 1455, 6463, 700, 398, 3335, 369, 28694, 30824, 11, 323, 5825, 459, 4623, 315, 1148, 279, 46831, 315, 6617, 30824, 1253, 617, 7111, 1093, 1359, 2795, 2999, 13, 41235, 18238, 29346, 11, 3063, 3229, 315, 279, 4007, 323, 11452, 315, 650, 14140, 65216, 12629, 63333, 520, 279, 18955, 11346, 16730, 315, 9853, 12167, 6406, 320, 52371, 2735, 32, 570, 330, 10156, 439, 7185, 374, 279, 9546, 315, 29106, 1841, 552, 11, 9204, 430, 21308, 30020, 617, 264, 1317, 41993, 3925, 304, 279, 10099, 11, 902, 649, 3371, 603, 922, 872, 31705, 661, 10173, 11, 36548, 505, 63494, 13, 1115, 374, 279, 1176, 323, 30758, 27470, 32659, 315, 1579, 49236, 30303, 10173, 304, 80710, 30824, 11, 4461, 5552, 311, 8834, 5942, 304, 18459, 369, 279, 25984, 37518, 86082, 1210, 578, 3495, 2128, 11, 902, 5343, 1080, 43802, 2999, 13, 42701, 689, 26775, 9081, 89, 1910, 33639, 11, 264, 8483, 33468, 323, 28639, 546, 16549, 449, 279, 12152, 16730, 315, 22037, 11, 1051, 3025, 311, 4007, 26403, 25896, 505, 279, 35113, 11, 82356, 323, 18311, 11, 439, 1664, 439, 5596, 315, 279, 30535, 505, 1403, 7931, 13, 362, 1684, 315, 279, 92534, 71965, 31376, 2816, 11, 449, 264, 1396, 315, 279, 10099, 323, 11012, 3196, 389, 81473, 26403, 505, 279, 2816, 13, 763, 279, 4092, 11, 1070, 374, 264, 11984, 3070, 13, 3277, 420, 1989, 574, 51068, 220, 868, 1667, 4227, 555, 279, 12152, 16730, 315, 22037, 11, 433, 5828, 956, 3967, 7041, 1148, 814, 1051, 719, 649, 1457, 387, 11970, 277, 302, 437, 13, 16666, 25, 5277, 555, 10058, 330, 49, 992, 67, 28676, 1, 2722, 718, 18022, 13, 578, 25896, 1051, 11352, 927, 264, 220, 508, 4771, 4261, 555, 12152, 16730, 315, 22037, 14248, 11, 2737, 2999, 13, 26775, 9081, 89, 1910, 33639, 11, 520, 264, 31376, 69187, 389, 4072, 645, 61031, 10951, 3967, 439, 279, 92534, 71965, 2816, 13, 578, 1069, 266, 34751, 2997, 31376, 1534, 11012, 64005, 315, 264, 39786, 278, 10827, 14739, 1974, 13952, 11, 323, 617, 58487, 1023, 81473, 11, 2737, 7795, 11, 387, 7403, 11, 2678, 97733, 4692, 11, 39149, 10145, 11, 323, 264, 2380, 4791, 291, 15580, 13, 578, 14955, 1501, 430, 279, 4072, 645, 61031, 11970, 277, 302, 437, 12439, 304, 264, 18671, 39786, 278, 10827, 13952, 39646, 11, 1405, 1070, 1053, 617, 1027, 220, 1187, 21925, 27394, 304, 12688, 11, 439, 1664, 439, 922, 4848, 4038, 315, 10054, 323, 12056, 13, 330, 2181, 374, 264, 5199, 1505, 11, 304, 961, 1606, 682, 1023, 14154, 31376, 220, 1759, 483, 30824, 11, 323, 1524, 1063, 6617, 11984, 9606, 1093, 279, 18067, 339, 11984, 323, 7160, 11984, 11, 527, 5938, 449, 4827, 2922, 17584, 11, 296, 21439, 71699, 1359, 2795, 1080, 43802, 2999, 13, 26775, 9081, 89, 1910, 33639, 13, 330, 4516, 11, 279, 4072, 645, 61031, 11984, 374, 3062, 1606, 433, 13533, 430, 279, 8824, 311, 33294, 279, 305, 1590, 6536, 11, 1455, 18671, 36658, 389, 279, 11841, 374, 539, 459, 19297, 315, 6617, 1099, 95795, 323, 3776, 30824, 11, 719, 1253, 617, 32971, 279, 220, 1759, 483, 65009, 505, 1202, 7314, 1210, 2999, 13, 29346, 30239, 17910, 315, 31376, 11984, 8625, 505, 2212, 279, 1917, 311, 10765, 279, 4072, 645, 61031, 8625, 439, 11970, 277, 302, 437, 323, 311, 5813, 1202, 41993, 65009, 304, 12976, 311, 1023, 30824, 13, 18766, 30824, 527, 7029, 82105, 11, 1766, 505, 3312, 39036, 311, 25685, 13918, 13, 11205, 38618, 11, 14918, 1766, 304, 88177, 689, 11, 2457, 311, 922, 220, 20, 3610, 1667, 4227, 13, 14434, 43738, 315, 279, 12152, 37518, 31376, 11984, 11, 11970, 277, 302, 437, 671, 496, 355, 355, 13, 16666, 25, 41235, 18238, 29346, 435, 85061, 7576, 315, 220, 1759, 483, 30824, 320, 543, 5496, 30824, 5636, 872, 38618, 11, 3734, 279, 14880, 89322, 11, 902, 374, 459, 4216, 1022, 68392, 8, 527, 8009, 323, 872, 4216, 15740, 20733, 13, 578, 502, 31376, 11105, 832, 315, 279, 4216, 15644, 811, 505, 13936, 311, 4892, 5270, 719, 433, 374, 4762, 539, 264, 2167, 46831, 311, 279, 6617, 3778, 3776, 11984, 13, 5046, 4726, 26431, 374, 430, 279, 18311, 315, 2225, 11970, 277, 302, 437, 7931, 1501, 12195, 315, 1664, 49061, 291, 29106, 57709, 1385, 11, 902, 1051, 11054, 2768, 19084, 43739, 555, 44632, 5929, 11, 264, 22311, 14561, 449, 279, 50751, 6150, 315, 43911, 5050, 13, 578, 57709, 1385, 52974, 430, 1521, 14154, 30824, 27073, 3544, 15055, 315, 31705, 661, 15657, 1778, 439, 63494, 13, 23150, 11, 86188, 11012, 527, 1766, 34683, 304, 279, 1890, 4072, 645, 61031, 34751, 439, 279, 11984, 8625, 13, 330, 1687, 1440, 430, 6617, 30824, 25024, 31705, 661, 26390, 304, 279, 4498, 311, 12192, 8834, 46835, 430, 6276, 369, 12688, 20237, 4669, 305, 18127, 367, 13, 578, 29106, 57709, 1385, 304, 11970, 277, 302, 437, 4284, 430, 15652, 315, 13465, 41947, 15657, 1093, 63494, 11, 304, 18459, 369, 12688, 305, 18127, 367, 11, 8040, 4216, 304, 279, 15740, 315, 30824, 439, 264, 20237, 8446, 1359, 15100, 26775, 9081, 89, 1910, 33639, 13, 220, 128257, 198 ]

2,508

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract A variety of hypotheses, involving sub-ice-shelf melting, stratospheric ozone depletion and tropical teleconnections, have been proposed to explain the observed Antarctic sea-ice expansion over the period of continuous satellite monitoring and corresponding model–observation discrepancy, but the issue remains unresolved. Here, by comparing multiple large ensembles of model simulations with available observations, we show that Antarctic sea ice has expanded due to ocean surface cooling associated with multidecadal variability in the Southern Ocean that temporarily outweighs the opposing forced response. In both observations and model simulations, Southern Ocean multidecadal variability is closely linked to internal variability in the tropics, especially in the Pacific, via atmospheric teleconnections. The linkages are, however, distinctly weaker in simulations than in observations, accompanied by a marked model–observation mismatch in global warming resulting from potential model bias in the forced response and observed tropical variability. Thus, the forced response dominates in simulations, resulting in apparent model–observation discrepancy. Main Continuous satellite observations since ~1979 indicate a pronounced interhemispheric asymmetry in sea-ice change, with a modest expansion in the Southern Ocean (SO) despite the global warming trend 1 , 2 . Unlike the marked sea-ice decline in the Arctic, Antarctic sea-ice expansion, which is accompanied by an overall cooling of sea surface temperature (SST) in the SO 3 , 4 , 5 , 6 , has generally not been reproduced by climate models over 1979−2014, under historical forcing 7 , 8 , 9 , 10 , 11 , 12 . Considering that Antarctic sea-ice changes affect ocean–atmosphere heat and momentum exchanges, ocean carbon uptake, ecosystems and the thermohaline circulation 13 , this marked discrepancy may have serious implications for the credibility of near-term model-projected climate change. It has been suggested that Antarctic sea-ice expansion has been due to increased freshwater fluxes 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 and changes in the Southern Annular Mode and associated SO circulation changes 5 , 22 , 23 , 24 , 25 , 26 , 27 , with this triggered by increased GHG concentrations and human-induced stratospheric ozone depletion. Although model deficiencies in representing these mechanisms cannot be ruled out 8 , 9 , 28 , 29 , several other studies have suggested that the Antarctic sea-ice expansion may have arisen from internal climate variability 3 , 4 , 7 , 9 , 11 , 30 , 31 , with this tied in part to climate variability in the Pacific and Atlantic Oceans 12 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 . The recent multiyear Antarctic sea-ice decline 2 , 8 , 36 , 41 , 42 , 43 seems to fit into this view. However, both the main cause of the satellite-observed sea-ice expansion, whether external forcing or internal variability, and the question of why models fail to reproduce observations under historical forcing, remains unresolved 13 , 16 , 17 , 44 , 45 , 46 , 47 . On the basis of the fact that regional patterns of sea-ice trends are governed mainly by wind fields 48 , ref. 26 demonstrated in a given model that applying realistic wind forcing along with realistic SSTs is essential for reproducing the observations over the period 1990−present, during which marked sea-ice expansion occurred. This implies that climate models may have deficiencies in representing teleconnection processes that affect SO wind and SST fields. One of the major obstacles to resolving these issues is the inherent difficulty in separating the observed changes over the relatively short period (1979−2014) into externally forced changes and internal variability. As the influence of internal variability on long-term trends diminishes with increasing time span 49 (Supplementary Text 1 ), we employ a long-term SST record in the SO (1950−2020) as a proxy for Antarctic sea ice. In this article, using the long-term proxy record and large-ensemble climate model simulations, we attempt to elucidate the main processes responsible for the satellite-observed sea-ice expansion and the causes of the model–observation discrepancy. Sea-ice and SST changes in the SO Before delving into the causes of the observed sea-ice expansion, we examine annual-mean total sea-ice extent (SIE) and SO (south of 50° S) SST trends over 1979–2014, for which continuous satellite observations are available, and each of the models analysed in this study is represented by more than 15 ensemble members ( Methods ). The satellite observations indicate a statistically significant sea-ice expansion at a rate of 0.223 ± 0.087 × 10 6 km 2 decade −1 over this period (Fig. 1a , solid line in red), which is not captured by the model simulations analysed in this study (dark blue boxes tagged as Hist in Fig. 1a ). A marked model–observation discrepancy is also apparent over periods other than 1979–2014, but this discrepancy does not appear to grow further with increases in time span (Fig. 2a ). Fig. 1: Observed and model-simulated changes in annual-mean SIE and SST over the SO (south of 50° S). a , Box plots of model-simulated SIE trends over 29-year (yellow green) and 36-year (dark blue) periods for three cases: Hist, trends over 1950−1978 and 1979−2014 under historical forcing; PI, trends for all possible overlapping 29-year and 36-year segments of pre-industrial control runs; and PI + forced, PI trends with the corresponding ensemble-mean values for 1950−1978 and 1979−2014 added. The box covers the inter-quartile range with the line inside the box representing the median value across multi-ensemble models and whiskers denoting the maximum and minimum values. The red solid line denotes the satellite-observed 1979−2014 SIE trend with the accompanying dashed lines representing the standard error of the trend. b , Same as in a , but for SST trends. The orange solid line denotes the observed 1950−1978 SST trend averaged over four SST datasets: Extended Reconstructed Sea Surface Temperature (ERSST), Hadley Centre Sea Ice and Sea Surface Temperature (HadISST), Centennial in situ Observation-Based Estimates (COBE) and European Centre for Medium-Range Weather Forecasts Reanalysis v.5 (ERA5). The accompanying dashed", "role": "user" }, { "content": "Antarctic sea-ice has expanded over the period of continuous satellite monitoring, which seemingly contradicts ongoing global warming resulting from increasing concentrations of greenhouse gasses. In a study, published in Nature Climate Change, an international team of scientists from the University of Hawaiʻi at Mānoa, National Oceanic and Atmospheric Administration (NOAA) and South Korea shows that a multi-decadal swing of the tropical sea surface temperatures and its ability to change the atmospheric circulation across large distances is in large part responsible for the observed sea-ice expansion since the late 1970s. Sea ice, which covers a substantial portion of the ocean surface in the polar regions, plays an important role in controlling global temperatures by reflecting incoming solar radiation. Decreases in sea-ice coverage, therefore, are expected to amplify greenhouse gas-induced global warming. Changes in sea ice also affect energy exchanges between the ocean and atmosphere, carbon uptake by the ocean, ecosystems and the thermohaline oceanic circulation. It is of great importance to monitor long-term changes in global sea ice and to ensure that physical processes that lead to those changes are accurately depicted in climate prediction models. Difference between computer model simulations and observations Continuous satellite observations, which started at the end of the 1970s, indicate marked decreases in Arctic sea ice over the satellite era, which is consistent with the global warming trend. In contrast, small but increasing trends have been observed, especially over the period 1979–2014, in the Southern Hemisphere. Furthermore, while climate models are able to broadly reproduce the observed Arctic sea-ice decreases, the majority of them are not able to capture the Antarctic sea-ice expansion over the period 1979–2014. \"The observed Antarctic sea-ice expansion and model-observation discrepancy have perplexed climate scientists over more than a decade,\" said lead author Eui-Seok Chung, from the Korea Polar Research Institute. \"Various hypotheses, such as increased freshwater fluxes due to sub-ice shelf melting, atmospheric and oceanic circulation changes associated with human-induced stratospheric ozone depletion and tropical teleconnections, have been proposed to explain the observed Antarctic sea-ice expansion, but the issue has remained as one of the biggest challenges in climate science,\" said professor Axel Timmermann, director of the IBS Center for Climate Physics at Pusan National University, and co-author of this study. The observed Antarctic sea-ice changes are caused not only by increasing concentrations of greenhouse gasses and/or stratospheric ozone depletion, but also linked to natural variability of the climate system, which occurs without direct connections with human activities. To determine the main causes of the observed Antarctic sea-ice expansion and model-observation discrepancy, the scientists turned their attention to a longer record of Southern Ocean sea surface temperatures as a proxy for Antarctic sea ice and conducted comprehensive analyses of multi-model large ensemble climate model simulations. Mismatch due to natural variability and regional model biases Over a certain period of time, Southern Ocean cooling and associated atmospheric and oceanic circulation changes linked to natural variability in the tropics may temporarily outweigh the opposing human-induced changes, thus resulting in temporary sea ice expansion. However, it does not explain the model-observation discrepancy. Malte Stuecker, co-author and assistant professor of oceanography from the UH Mānoa School of Ocean and Earth Science and Technology (SOEST) explained, \"Southern Ocean multi-decadal variability is also closely linked to tropical natural variability in climate model simulations, but the linkages are substantially weaker than in the observations. Thus, human-induced ocean surface warming dominates in the Southern Ocean in model simulations.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract A variety of hypotheses, involving sub-ice-shelf melting, stratospheric ozone depletion and tropical teleconnections, have been proposed to explain the observed Antarctic sea-ice expansion over the period of continuous satellite monitoring and corresponding model–observation discrepancy, but the issue remains unresolved. Here, by comparing multiple large ensembles of model simulations with available observations, we show that Antarctic sea ice has expanded due to ocean surface cooling associated with multidecadal variability in the Southern Ocean that temporarily outweighs the opposing forced response. In both observations and model simulations, Southern Ocean multidecadal variability is closely linked to internal variability in the tropics, especially in the Pacific, via atmospheric teleconnections. The linkages are, however, distinctly weaker in simulations than in observations, accompanied by a marked model–observation mismatch in global warming resulting from potential model bias in the forced response and observed tropical variability. Thus, the forced response dominates in simulations, resulting in apparent model–observation discrepancy. Main Continuous satellite observations since ~1979 indicate a pronounced interhemispheric asymmetry in sea-ice change, with a modest expansion in the Southern Ocean (SO) despite the global warming trend 1 , 2 . Unlike the marked sea-ice decline in the Arctic, Antarctic sea-ice expansion, which is accompanied by an overall cooling of sea surface temperature (SST) in the SO 3 , 4 , 5 , 6 , has generally not been reproduced by climate models over 1979−2014, under historical forcing 7 , 8 , 9 , 10 , 11 , 12 . Considering that Antarctic sea-ice changes affect ocean–atmosphere heat and momentum exchanges, ocean carbon uptake, ecosystems and the thermohaline circulation 13 , this marked discrepancy may have serious implications for the credibility of near-term model-projected climate change. It has been suggested that Antarctic sea-ice expansion has been due to increased freshwater fluxes 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 and changes in the Southern Annular Mode and associated SO circulation changes 5 , 22 , 23 , 24 , 25 , 26 , 27 , with this triggered by increased GHG concentrations and human-induced stratospheric ozone depletion. Although model deficiencies in representing these mechanisms cannot be ruled out 8 , 9 , 28 , 29 , several other studies have suggested that the Antarctic sea-ice expansion may have arisen from internal climate variability 3 , 4 , 7 , 9 , 11 , 30 , 31 , with this tied in part to climate variability in the Pacific and Atlantic Oceans 12 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 . The recent multiyear Antarctic sea-ice decline 2 , 8 , 36 , 41 , 42 , 43 seems to fit into this view. However, both the main cause of the satellite-observed sea-ice expansion, whether external forcing or internal variability, and the question of why models fail to reproduce observations under historical forcing, remains unresolved 13 , 16 , 17 , 44 , 45 , 46 , 47 . On the basis of the fact that regional patterns of sea-ice trends are governed mainly by wind fields 48 , ref. 26 demonstrated in a given model that applying realistic wind forcing along with realistic SSTs is essential for reproducing the observations over the period 1990−present, during which marked sea-ice expansion occurred. This implies that climate models may have deficiencies in representing teleconnection processes that affect SO wind and SST fields. One of the major obstacles to resolving these issues is the inherent difficulty in separating the observed changes over the relatively short period (1979−2014) into externally forced changes and internal variability. As the influence of internal variability on long-term trends diminishes with increasing time span 49 (Supplementary Text 1 ), we employ a long-term SST record in the SO (1950−2020) as a proxy for Antarctic sea ice. In this article, using the long-term proxy record and large-ensemble climate model simulations, we attempt to elucidate the main processes responsible for the satellite-observed sea-ice expansion and the causes of the model–observation discrepancy. Sea-ice and SST changes in the SO Before delving into the causes of the observed sea-ice expansion, we examine annual-mean total sea-ice extent (SIE) and SO (south of 50° S) SST trends over 1979–2014, for which continuous satellite observations are available, and each of the models analysed in this study is represented by more than 15 ensemble members ( Methods ). The satellite observations indicate a statistically significant sea-ice expansion at a rate of 0.223 ± 0.087 × 10 6 km 2 decade −1 over this period (Fig. 1a , solid line in red), which is not captured by the model simulations analysed in this study (dark blue boxes tagged as Hist in Fig. 1a ). A marked model–observation discrepancy is also apparent over periods other than 1979–2014, but this discrepancy does not appear to grow further with increases in time span (Fig. 2a ). Fig. 1: Observed and model-simulated changes in annual-mean SIE and SST over the SO (south of 50° S). a , Box plots of model-simulated SIE trends over 29-year (yellow green) and 36-year (dark blue) periods for three cases: Hist, trends over 1950−1978 and 1979−2014 under historical forcing; PI, trends for all possible overlapping 29-year and 36-year segments of pre-industrial control runs; and PI + forced, PI trends with the corresponding ensemble-mean values for 1950−1978 and 1979−2014 added. The box covers the inter-quartile range with the line inside the box representing the median value across multi-ensemble models and whiskers denoting the maximum and minimum values. The red solid line denotes the satellite-observed 1979−2014 SIE trend with the accompanying dashed lines representing the standard error of the trend. b , Same as in a , but for SST trends. The orange solid line denotes the observed 1950−1978 SST trend averaged over four SST datasets: Extended Reconstructed Sea Surface Temperature (ERSST), Hadley Centre Sea Ice and Sea Surface Temperature (HadISST), Centennial in situ Observation-Based Estimates (COBE) and European Centre for Medium-Range Weather Forecasts Reanalysis v.5 (ERA5). The accompanying dashed<|im_end|> <|im_start|>assistant Antarctic sea-ice has expanded over the period of continuous satellite monitoring, which seemingly contradicts ongoing global warming resulting from increasing concentrations of greenhouse gasses. In a study, published in Nature Climate Change, an international team of scientists from the University of Hawaiʻi at Mānoa, National Oceanic and Atmospheric Administration (NOAA) and South Korea shows that a multi-decadal swing of the tropical sea surface temperatures and its ability to change the atmospheric circulation across large distances is in large part responsible for the observed sea-ice expansion since the late 1970s. Sea ice, which covers a substantial portion of the ocean surface in the polar regions, plays an important role in controlling global temperatures by reflecting incoming solar radiation. Decreases in sea-ice coverage, therefore, are expected to amplify greenhouse gas-induced global warming. Changes in sea ice also affect energy exchanges between the ocean and atmosphere, carbon uptake by the ocean, ecosystems and the thermohaline oceanic circulation. It is of great importance to monitor long-term changes in global sea ice and to ensure that physical processes that lead to those changes are accurately depicted in climate prediction models. Difference between computer model simulations and observations Continuous satellite observations, which started at the end of the 1970s, indicate marked decreases in Arctic sea ice over the satellite era, which is consistent with the global warming trend. In contrast, small but increasing trends have been observed, especially over the period 1979–2014, in the Southern Hemisphere. Furthermore, while climate models are able to broadly reproduce the observed Arctic sea-ice decreases, the majority of them are not able to capture the Antarctic sea-ice expansion over the period 1979–2014. "The observed Antarctic sea-ice expansion and model-observation discrepancy have perplexed climate scientists over more than a decade," said lead author Eui-Seok Chung, from the Korea Polar Research Institute. "Various hypotheses, such as increased freshwater fluxes due to sub-ice shelf melting, atmospheric and oceanic circulation changes associated with human-induced stratospheric ozone depletion and tropical teleconnections, have been proposed to explain the observed Antarctic sea-ice expansion, but the issue has remained as one of the biggest challenges in climate science," said professor Axel Timmermann, director of the IBS Center for Climate Physics at Pusan National University, and co-author of this study. The observed Antarctic sea-ice changes are caused not only by increasing concentrations of greenhouse gasses and/or stratospheric ozone depletion, but also linked to natural variability of the climate system, which occurs without direct connections with human activities. To determine the main causes of the observed Antarctic sea-ice expansion and model-observation discrepancy, the scientists turned their attention to a longer record of Southern Ocean sea surface temperatures as a proxy for Antarctic sea ice and conducted comprehensive analyses of multi-model large ensemble climate model simulations. Mismatch due to natural variability and regional model biases Over a certain period of time, Southern Ocean cooling and associated atmospheric and oceanic circulation changes linked to natural variability in the tropics may temporarily outweigh the opposing human-induced changes, thus resulting in temporary sea ice expansion. However, it does not explain the model-observation discrepancy. Malte Stuecker, co-author and assistant professor of oceanography from the UH Mānoa School of Ocean and Earth Science and Technology (SOEST) explained, "Southern Ocean multi-decadal variability is also closely linked to tropical natural variability in climate model simulations, but the linkages are substantially weaker than in the observations. Thus, human-induced ocean surface warming dominates in the Southern Ocean in model simulations." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 362, 8205, 315, 74513, 11, 16239, 1207, 12, 560, 7666, 491, 50684, 11, 610, 14357, 33349, 77537, 92948, 323, 35148, 8122, 51086, 11, 617, 1027, 11223, 311, 10552, 279, 13468, 80841, 9581, 12, 560, 14800, 927, 279, 4261, 315, 19815, 24088, 16967, 323, 12435, 1646, 4235, 79060, 79105, 11, 719, 279, 4360, 8625, 81261, 13, 5810, 11, 555, 27393, 5361, 3544, 665, 41794, 315, 1646, 47590, 449, 2561, 24654, 11, 584, 1501, 430, 80841, 9581, 10054, 706, 17626, 4245, 311, 18435, 7479, 28015, 5938, 449, 2814, 579, 35555, 278, 54709, 304, 279, 16642, 22302, 430, 28191, 63074, 82, 279, 31322, 9770, 2077, 13, 763, 2225, 24654, 323, 1646, 47590, 11, 16642, 22302, 2814, 579, 35555, 278, 54709, 374, 15499, 10815, 311, 5419, 54709, 304, 279, 21965, 1233, 11, 5423, 304, 279, 16867, 11, 4669, 45475, 8122, 51086, 13, 578, 2723, 1154, 527, 11, 4869, 11, 71249, 43383, 304, 47590, 1109, 304, 24654, 11, 24895, 555, 264, 13160, 1646, 4235, 79060, 36401, 304, 3728, 24808, 13239, 505, 4754, 1646, 15837, 304, 279, 9770, 2077, 323, 13468, 35148, 54709, 13, 14636, 11, 279, 9770, 2077, 83978, 304, 47590, 11, 13239, 304, 10186, 1646, 4235, 79060, 79105, 13, 4802, 70067, 24088, 24654, 2533, 4056, 4468, 24, 13519, 264, 38617, 958, 30132, 285, 33349, 54395, 33342, 304, 9581, 12, 560, 2349, 11, 449, 264, 27946, 14800, 304, 279, 16642, 22302, 320, 14202, 8, 8994, 279, 3728, 24808, 9327, 220, 16, 1174, 220, 17, 662, 27140, 279, 13160, 9581, 12, 560, 18174, 304, 279, 37518, 11, 80841, 9581, 12, 560, 14800, 11, 902, 374, 24895, 555, 459, 8244, 28015, 315, 9581, 7479, 9499, 320, 50, 790, 8, 304, 279, 5745, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 1174, 706, 8965, 539, 1027, 55717, 555, 10182, 4211, 927, 220, 4468, 24, 34363, 679, 19, 11, 1234, 13970, 25957, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 662, 56877, 430, 80841, 9581, 12, 560, 4442, 7958, 18435, 4235, 266, 8801, 8182, 8798, 323, 24151, 30098, 11, 18435, 12782, 69575, 11, 61951, 323, 279, 30945, 2319, 278, 483, 35855, 220, 1032, 1174, 420, 13160, 79105, 1253, 617, 6129, 25127, 369, 279, 38769, 315, 3221, 9860, 1646, 34796, 291, 10182, 2349, 13, 1102, 706, 1027, 12090, 430, 80841, 9581, 12, 560, 14800, 706, 1027, 4245, 311, 7319, 80744, 31405, 288, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 1174, 220, 972, 1174, 220, 777, 1174, 220, 508, 1174, 220, 1691, 323, 4442, 304, 279, 16642, 9489, 1299, 14904, 323, 5938, 5745, 35855, 4442, 220, 20, 1174, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 1174, 220, 1627, 1174, 220, 1544, 1174, 449, 420, 22900, 555, 7319, 48584, 38, 32466, 323, 3823, 38973, 610, 14357, 33349, 77537, 92948, 13, 10541, 1646, 72946, 304, 14393, 1521, 24717, 4250, 387, 21989, 704, 220, 23, 1174, 220, 24, 1174, 220, 1591, 1174, 220, 1682, 1174, 3892, 1023, 7978, 617, 12090, 430, 279, 80841, 9581, 12, 560, 14800, 1253, 617, 90954, 505, 5419, 10182, 54709, 220, 18, 1174, 220, 19, 1174, 220, 22, 1174, 220, 24, 1174, 220, 806, 1174, 220, 966, 1174, 220, 2148, 1174, 449, 420, 17791, 304, 961, 311, 10182, 54709, 304, 279, 16867, 323, 23179, 507, 43320, 220, 717, 1174, 220, 843, 1174, 220, 1644, 1174, 220, 1958, 1174, 220, 1758, 1174, 220, 1927, 1174, 220, 1806, 1174, 220, 1987, 1174, 220, 2137, 1174, 220, 1272, 662, 578, 3293, 7447, 3236, 80841, 9581, 12, 560, 18174, 220, 17, 1174, 220, 23, 1174, 220, 1927, 1174, 220, 3174, 1174, 220, 2983, 1174, 220, 3391, 5084, 311, 5052, 1139, 420, 1684, 13, 4452, 11, 2225, 279, 1925, 5353, 315, 279, 24088, 12, 5598, 2841, 9581, 12, 560, 14800, 11, 3508, 9434, 25957, 477, 5419, 54709, 11, 323, 279, 3488, 315, 3249, 4211, 3775, 311, 23645, 24654, 1234, 13970, 25957, 11, 8625, 81261, 220, 1032, 1174, 220, 845, 1174, 220, 1114, 1174, 220, 2096, 1174, 220, 1774, 1174, 220, 2790, 1174, 220, 2618, 662, 1952, 279, 8197, 315, 279, 2144, 430, 15481, 12912, 315, 9581, 12, 560, 18845, 527, 27800, 14918, 555, 10160, 5151, 220, 2166, 1174, 2098, 13, 220, 1627, 21091, 304, 264, 2728, 1646, 430, 19486, 26569, 10160, 25957, 3235, 449, 26569, 92516, 82, 374, 7718, 369, 14843, 6253, 279, 24654, 927, 279, 4261, 220, 2550, 15, 34363, 29844, 11, 2391, 902, 13160, 9581, 12, 560, 14800, 10222, 13, 1115, 24897, 430, 10182, 4211, 1253, 617, 72946, 304, 14393, 8122, 7898, 11618, 430, 7958, 5745, 10160, 323, 92516, 5151, 13, 3861, 315, 279, 3682, 32116, 311, 53583, 1521, 4819, 374, 279, 38088, 17250, 304, 50545, 279, 13468, 4442, 927, 279, 12309, 2875, 4261, 320, 4468, 24, 34363, 679, 19, 8, 1139, 69442, 9770, 4442, 323, 5419, 54709, 13, 1666, 279, 10383, 315, 5419, 54709, 389, 1317, 9860, 18845, 57160, 288, 449, 7859, 892, 9575, 220, 2491, 320, 10254, 67082, 2991, 220, 16, 7026, 584, 3539, 264, 1317, 9860, 92516, 3335, 304, 279, 5745, 320, 6280, 15, 34363, 2366, 15, 8, 439, 264, 13594, 369, 80841, 9581, 10054, 13, 763, 420, 4652, 11, 1701, 279, 1317, 9860, 13594, 3335, 323, 3544, 12, 49575, 10182, 1646, 47590, 11, 584, 4879, 311, 97298, 349, 279, 1925, 11618, 8647, 369, 279, 24088, 12, 5598, 2841, 9581, 12, 560, 14800, 323, 279, 11384, 315, 279, 1646, 4235, 79060, 79105, 13, 15379, 12, 560, 323, 92516, 4442, 304, 279, 5745, 13538, 1624, 4504, 1139, 279, 11384, 315, 279, 13468, 9581, 12, 560, 14800, 11, 584, 21635, 9974, 84096, 2860, 9581, 12, 560, 13112, 320, 50, 5484, 8, 323, 5745, 320, 67584, 315, 220, 1135, 11877, 328, 8, 92516, 18845, 927, 220, 4468, 24, 4235, 679, 19, 11, 369, 902, 19815, 24088, 24654, 527, 2561, 11, 323, 1855, 315, 279, 4211, 67458, 304, 420, 4007, 374, 15609, 555, 810, 1109, 220, 868, 40126, 3697, 320, 19331, 7609, 578, 24088, 24654, 13519, 264, 47952, 5199, 9581, 12, 560, 14800, 520, 264, 4478, 315, 220, 15, 13, 12533, 20903, 220, 15, 13, 27311, 25800, 220, 605, 220, 21, 13437, 220, 17, 13515, 25173, 16, 927, 420, 4261, 320, 30035, 13, 220, 16, 64, 1174, 6573, 1584, 304, 2579, 705, 902, 374, 539, 17439, 555, 279, 1646, 47590, 67458, 304, 420, 4007, 320, 23449, 6437, 15039, 38213, 439, 67005, 304, 23966, 13, 220, 16, 64, 7609, 362, 13160, 1646, 4235, 79060, 79105, 374, 1101, 10186, 927, 18852, 1023, 1109, 220, 4468, 24, 4235, 679, 19, 11, 719, 420, 79105, 1587, 539, 5101, 311, 3139, 4726, 449, 12992, 304, 892, 9575, 320, 30035, 13, 220, 17, 64, 7609, 23966, 13, 220, 16, 25, 51541, 2841, 323, 1646, 1355, 318, 7913, 4442, 304, 9974, 84096, 328, 5484, 323, 92516, 927, 279, 5745, 320, 67584, 315, 220, 1135, 11877, 328, 570, 264, 1174, 8425, 31794, 315, 1646, 1355, 318, 7913, 328, 5484, 18845, 927, 220, 1682, 4771, 320, 28969, 6307, 8, 323, 220, 1927, 4771, 320, 23449, 6437, 8, 18852, 369, 2380, 5157, 25, 67005, 11, 18845, 927, 220, 6280, 15, 34363, 4468, 23, 323, 220, 4468, 24, 34363, 679, 19, 1234, 13970, 25957, 26, 23396, 11, 18845, 369, 682, 3284, 50917, 220, 1682, 4771, 323, 220, 1927, 4771, 21282, 315, 864, 18251, 47479, 2585, 8640, 26, 323, 23396, 489, 9770, 11, 23396, 18845, 449, 279, 12435, 40126, 84096, 2819, 369, 220, 6280, 15, 34363, 4468, 23, 323, 220, 4468, 24, 34363, 679, 19, 3779, 13, 578, 3830, 14861, 279, 958, 74801, 472, 458, 2134, 449, 279, 1584, 4871, 279, 3830, 14393, 279, 23369, 907, 4028, 7447, 12, 49575, 4211, 323, 41759, 388, 3453, 11780, 279, 7340, 323, 8187, 2819, 13, 578, 2579, 6573, 1584, 72214, 279, 24088, 12, 5598, 2841, 220, 4468, 24, 34363, 679, 19, 328, 5484, 9327, 449, 279, 24442, 67822, 5238, 14393, 279, 5410, 1493, 315, 279, 9327, 13, 293, 1174, 26823, 439, 304, 264, 1174, 719, 369, 92516, 18845, 13, 578, 19087, 6573, 1584, 72214, 279, 13468, 220, 6280, 15, 34363, 4468, 23, 92516, 9327, 37956, 927, 3116, 92516, 30525, 25, 41665, 1050, 82678, 15379, 28061, 38122, 320, 4419, 790, 705, 24805, 3258, 14821, 15379, 20534, 323, 15379, 28061, 38122, 320, 56568, 1669, 790, 705, 5838, 32331, 304, 10109, 87529, 61439, 95619, 320, 8445, 11855, 8, 323, 7665, 14821, 369, 25352, 12, 6174, 23454, 8371, 51134, 1050, 35584, 348, 13, 20, 320, 26763, 20, 570, 578, 24442, 67822, 128257, 198, 128256, 78191, 198, 17555, 277, 26636, 9581, 12, 560, 706, 17626, 927, 279, 4261, 315, 19815, 24088, 16967, 11, 902, 23490, 23093, 31095, 14529, 3728, 24808, 13239, 505, 7859, 32466, 315, 37647, 342, 52090, 13, 763, 264, 4007, 11, 4756, 304, 22037, 31636, 10604, 11, 459, 6625, 2128, 315, 14248, 505, 279, 3907, 315, 22153, 134, 119, 72, 520, 386, 31757, 2201, 64, 11, 5165, 22302, 292, 323, 87597, 17128, 320, 9173, 6157, 8, 323, 4987, 12126, 5039, 430, 264, 7447, 6953, 35555, 278, 19336, 315, 279, 35148, 9581, 7479, 20472, 323, 1202, 5845, 311, 2349, 279, 45475, 35855, 4028, 3544, 27650, 374, 304, 3544, 961, 8647, 369, 279, 13468, 9581, 12, 560, 14800, 2533, 279, 3389, 220, 4468, 15, 82, 13, 15379, 10054, 11, 902, 14861, 264, 12190, 13651, 315, 279, 18435, 7479, 304, 279, 25685, 13918, 11, 11335, 459, 3062, 3560, 304, 26991, 3728, 20472, 555, 42852, 19957, 13238, 25407, 13, 65201, 2315, 304, 9581, 12, 560, 10401, 11, 9093, 11, 527, 3685, 311, 97168, 37647, 6962, 38973, 3728, 24808, 13, 29240, 304, 9581, 10054, 1101, 7958, 4907, 30098, 1990, 279, 18435, 323, 16975, 11, 12782, 69575, 555, 279, 18435, 11, 61951, 323, 279, 30945, 2319, 278, 483, 18435, 292, 35855, 13, 1102, 374, 315, 2294, 12939, 311, 8891, 1317, 9860, 4442, 304, 3728, 9581, 10054, 323, 311, 6106, 430, 7106, 11618, 430, 3063, 311, 1884, 4442, 527, 30357, 44894, 304, 10182, 20212, 4211, 13, 56180, 1990, 6500, 1646, 47590, 323, 24654, 70067, 24088, 24654, 11, 902, 3940, 520, 279, 842, 315, 279, 220, 4468, 15, 82, 11, 13519, 13160, 43154, 304, 37518, 9581, 10054, 927, 279, 24088, 11639, 11, 902, 374, 13263, 449, 279, 3728, 24808, 9327, 13, 763, 13168, 11, 2678, 719, 7859, 18845, 617, 1027, 13468, 11, 5423, 927, 279, 4261, 220, 4468, 24, 4235, 679, 19, 11, 304, 279, 16642, 96878, 13, 24296, 11, 1418, 10182, 4211, 527, 3025, 311, 44029, 23645, 279, 13468, 37518, 9581, 12, 560, 43154, 11, 279, 8857, 315, 1124, 527, 539, 3025, 311, 12602, 279, 80841, 9581, 12, 560, 14800, 927, 279, 4261, 220, 4468, 24, 4235, 679, 19, 13, 330, 791, 13468, 80841, 9581, 12, 560, 14800, 323, 1646, 12, 79060, 79105, 617, 74252, 291, 10182, 14248, 927, 810, 1109, 264, 13515, 1359, 1071, 3063, 3229, 469, 2005, 98628, 564, 88425, 11, 505, 279, 12126, 56996, 8483, 10181, 13, 330, 73741, 74513, 11, 1778, 439, 7319, 80744, 31405, 288, 4245, 311, 1207, 12, 560, 28745, 50684, 11, 45475, 323, 18435, 292, 35855, 4442, 5938, 449, 3823, 38973, 610, 14357, 33349, 77537, 92948, 323, 35148, 8122, 51086, 11, 617, 1027, 11223, 311, 10552, 279, 13468, 80841, 9581, 12, 560, 14800, 11, 719, 279, 4360, 706, 14958, 439, 832, 315, 279, 8706, 11774, 304, 10182, 8198, 1359, 1071, 14561, 87779, 9538, 1195, 18022, 11, 7690, 315, 279, 358, 7497, 5955, 369, 31636, 28415, 520, 393, 41312, 5165, 3907, 11, 323, 1080, 43802, 315, 420, 4007, 13, 578, 13468, 80841, 9581, 12, 560, 4442, 527, 9057, 539, 1193, 555, 7859, 32466, 315, 37647, 342, 52090, 323, 5255, 610, 14357, 33349, 77537, 92948, 11, 719, 1101, 10815, 311, 5933, 54709, 315, 279, 10182, 1887, 11, 902, 13980, 2085, 2167, 13537, 449, 3823, 7640, 13, 2057, 8417, 279, 1925, 11384, 315, 279, 13468, 80841, 9581, 12, 560, 14800, 323, 1646, 12, 79060, 79105, 11, 279, 14248, 6656, 872, 6666, 311, 264, 5129, 3335, 315, 16642, 22302, 9581, 7479, 20472, 439, 264, 13594, 369, 80841, 9581, 10054, 323, 13375, 16195, 29060, 315, 7447, 29344, 3544, 40126, 10182, 1646, 47590, 13, 386, 26024, 4245, 311, 5933, 54709, 323, 15481, 1646, 50183, 6193, 264, 3738, 4261, 315, 892, 11, 16642, 22302, 28015, 323, 5938, 45475, 323, 18435, 292, 35855, 4442, 10815, 311, 5933, 54709, 304, 279, 21965, 1233, 1253, 28191, 63074, 279, 31322, 3823, 38973, 4442, 11, 8617, 13239, 304, 13643, 9581, 10054, 14800, 13, 4452, 11, 433, 1587, 539, 10552, 279, 1646, 12, 79060, 79105, 13, 8560, 668, 800, 361, 15512, 11, 1080, 43802, 323, 18328, 14561, 315, 18435, 5814, 505, 279, 549, 39, 386, 31757, 2201, 64, 6150, 315, 22302, 323, 9420, 10170, 323, 12053, 320, 14202, 5288, 8, 11497, 11, 330, 86838, 22302, 7447, 6953, 35555, 278, 54709, 374, 1101, 15499, 10815, 311, 35148, 5933, 54709, 304, 10182, 1646, 47590, 11, 719, 279, 2723, 1154, 527, 32302, 43383, 1109, 304, 279, 24654, 13, 14636, 11, 3823, 38973, 18435, 7479, 24808, 83978, 304, 279, 16642, 22302, 304, 1646, 47590, 1210, 220, 128257, 198 ]

2,163

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Although the amyloid β-protein (Aβ) is believed to play an initiating role in Alzheimer’s disease (AD), the molecular characteristics of the key pathogenic Aβ forms are not well understood. As a result, it has proved difficult to identify optimal agents that target disease-relevant forms of Aβ. Here, we combined the use of Aβ-rich aqueous extracts of brain samples from AD patients as a source of human Aβ and live-cell imaging of iPSC-derived human neurons to develop a bioassay capable of quantifying the relative protective effects of multiple anti-Aβ antibodies. We report the characterization of 1C22, an aggregate-preferring murine anti-Aβ antibody, which better protects against forms of Aβ oligomers that are toxic to neurites than do the murine precursors of the clinical immunotherapeutics, bapineuzumab and solanezumab. These results suggest further examination of 1C22 is warranted, and that this bioassay maybe useful as a primary screen to identify yet more potent anti-Aβ therapeutics. Introduction Approaches using monoclonal antibodies to target the amyloid β-protein (Aβ) constitute the largest and most advanced therapeutic effort to treat Alzheimer’s disease (AD) 1 , 2 , 3 . Despite generally good outcomes in preclinical mouse models, anti-Aβ immunotherapy has yielded limited success in humans 2 , 3 . Explanations offered to account for the poor translation of pre-clinical lead antibodies into human therapies include imperfect trial design, intervention at a disease stage when there is already significant neural loss, and inappropriate target selectivity of the antibodies used 2 , 4 , 5 . When assessing the efficacy of any therapeutic, there are several issues to consider besides target engagement, and yet the specific targeting of the most cytotoxic forms of Aβ is by far the most critical requirement. Synthetic Aβ can exist in vitro in a bewildering array of assemblies that differ in structure and size 6 , but it remains unclear whether the assemblies that can be formed in vitro ever exist in the human brain. In striking contrast to the hundreds of studies that have investigated the aggregation and toxicity of synthetic Aβ, only ~20 studies have focused on aqueously soluble Aβ species extracted directly from human brain. These studies can be divided into three categories: efforts to identify the primary sequence and/or assembly forms that constitute water-soluble Aβ, whether bioactive or not 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ; attempts to investigate the cytotoxic activity 22 , 23 , 24 , 25 , 26 , 27 or seeding activity 28 , 29 of crude Aβ–containing extracts; and efforts to study the assembly size of the neurotoxic components of Aβ-rich brain extracts 30 , 31 , 32 , 33 , 34 . Collectively, these studies suggest that Aβ in aqueous extracts of AD brain exists as a mixture of different sized assemblies 10 , 12 , 13 , 14 , 21 , 30 and that one or more of these are extremely potent toxins 22 , 23 , 24 , 25 , 26 , 30 , 31 , 32 , 33 . Indeed, in some experiments, human brain-derived Aβ assemblies were found to be many orders of magnitude more potent than synthetic Aβ peptides 24 , 32 . Recently, we have shown that only a fraction of AD brain-derived Aβ has disease-relevant bioactivity 34 . There are now at least 9 anti-Aβ monoclonal antibodies (mAbs) at various stages of clinical investigation 35 , five of which are believed to preferentially target Aβ oligomers 25 , 36 , 37 , 38 , 39 . Three of these advanced mAbs—crenezumab 25 , BAN2401 14 , 40 , and SAR228810 38 —were selected against synthetic Aβ, whereas aducanumab was selected based on immunohistochemical detection of AD amyloid plaques 37 , 41 . The rationale underlying the use of putatively oligomer-specific mAbs is based on the hypothesis that both Aβ monomers and insoluble fibrillar plaques are relatively innocuous; therefore, an ideal antibody would react weakly with monomers and mature fibrils, but strongly with diffusible oligomers. A key requirement for all CNS immunotherapies is delivering sufficient mAb to the brain. Normally, only ~0.1% of circulating antibody arrives in the brain at steady state 42 , so it is essential that the antibody that does enter the brain is not lost on superfluous targets. One explanation for the disappointing clinical efficacy of anti-Aβ antibodies in human trials is that they target a broad range of Aβ species, including many relatively inactive forms 34 and thus cannot attain the necessary therapeutic concentration against bioactive forms. Similarly, in certain studies sub-optimal antibody levels were used to avoid side-effects such amyloid-related imaging abnormalities (ARIA) 43 . Currently, there is no information in the public domain about the relative ability of candidate therapeutic antibodies to recognize toxic forms of Aβ in human brain, and the properties of optimal therapeutic Aβ antibodies remain ill-defined. To address this central problem, we generated an aggregate-preferring mAb, called 1C22, which shares many of the characteristics of the anti-oligomer mAbs in clinical development 25 , 36 , 40 , 44 , 45 , and we compared its binding properties to those of the murine precursors of solanezumab (mAb 266) and bapineuzumab (mAb 3D6). Solanezumab continues to be tested in two secondary prevention trials 46 , 47 , and an Fc-modified form of bapineuzumab, called AAB-003, is being assessed for treating mild AD 48 . We found that both 3D6 and 266 bound tightly to monomers, whereas 1C22 bound monomers only weakly, and that 1C22 preferentially bound protofibrils (PFs) of Aβ. PFs comprise a heterogeneous mixture of prefibrillar assemblies which by EM appear as short flexible rods with an average width of 5.8 ± 0.2 nm and length <300 nm 49 , 50 . Having established that 1C22, 3D6 and 266 possess distinct binding preferences, we examined the most important property of any potential anti-Aβ immunotherapeutic, its ability to neutralize neurotoxic Aβ. For this purpose, we developed", "role": "user" }, { "content": "Two new studies published by investigators from Brigham and Women's Hospital illustrate that not all forms of amyloid-beta (Aβ) protein—the protein thought to initiate Alzheimer's disease—play an equally menacing role in the progress of the disease. Using a new way of preparing and extracting the protein as well as a new technique to search for promising drug candidates, researchers have highlighted the importance of testing and targeting different forms of Aβ. Their work may help advance the search for more precise and effective drugs to prevent or halt the progress of Alzheimer's disease. \"Many different efforts are currently underway to find treatments for Alzheimer's disease, and anti-Aβ antibodies are currently the furthest advanced. But the question remains: what are the most important forms of Aβ to target? Our study points to some interesting answers,\" said Dominic Walsh, Ph.D., a principal investigator in the Ann Romney Center. Aβ protein can take forms ranging from monomers—single molecules—to twisted tangles of plaques that can pollute the brain and are large enough that they can be seen with a traditional microscope. Walsh compares monomers to single Lego bricks, which can start sticking together to form complex structures of varying sizes. The two recently published studies investigate how to find new potential therapeutics that can target the structures most likely to cause harm. Most Alzheimer's disease studies use synthetic Aβ to approximate what conditions in the brain of an Alzheimer's patient might be like. A small number of researchers have used Aβ extracted from human brain, but the extraction process is crude. In a study published in Acta Neuropathologica in April, Walsh and colleagues developed a much gentler extraction protocol to prepare samples from subjects with Alzheimer's disease. The team found that Aβ was far more abundant in traditional crude extracts, but that the bulk of the extracted Aβ was innocuous. In contrast, much less Aβ was obtained with the gentler protocol, but in this case most of the Aβ was toxic. In a second study published in Nature Communications in July, Walsh and colleagues developed a screening test to try to find potential drugs to target the toxic forms of Aβ. The new technique uses extracts of brain samples from Alzheimer's disease patients and live-cell imaging of stem-cell derived brain cells to find promising therapeutics. The team reports on 1C22, an Aβ antibody that they found could protect against toxic forms of amyloid-beta more effectively than the most clinically advanced Alzheimer's disease therapeutics currently in clinical trials. \"We anticipate that this primary screening technique will be useful in the search to identify more potent anti-Aβ therapeutics in the future,\" said Walsh. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Although the amyloid β-protein (Aβ) is believed to play an initiating role in Alzheimer’s disease (AD), the molecular characteristics of the key pathogenic Aβ forms are not well understood. As a result, it has proved difficult to identify optimal agents that target disease-relevant forms of Aβ. Here, we combined the use of Aβ-rich aqueous extracts of brain samples from AD patients as a source of human Aβ and live-cell imaging of iPSC-derived human neurons to develop a bioassay capable of quantifying the relative protective effects of multiple anti-Aβ antibodies. We report the characterization of 1C22, an aggregate-preferring murine anti-Aβ antibody, which better protects against forms of Aβ oligomers that are toxic to neurites than do the murine precursors of the clinical immunotherapeutics, bapineuzumab and solanezumab. These results suggest further examination of 1C22 is warranted, and that this bioassay maybe useful as a primary screen to identify yet more potent anti-Aβ therapeutics. Introduction Approaches using monoclonal antibodies to target the amyloid β-protein (Aβ) constitute the largest and most advanced therapeutic effort to treat Alzheimer’s disease (AD) 1 , 2 , 3 . Despite generally good outcomes in preclinical mouse models, anti-Aβ immunotherapy has yielded limited success in humans 2 , 3 . Explanations offered to account for the poor translation of pre-clinical lead antibodies into human therapies include imperfect trial design, intervention at a disease stage when there is already significant neural loss, and inappropriate target selectivity of the antibodies used 2 , 4 , 5 . When assessing the efficacy of any therapeutic, there are several issues to consider besides target engagement, and yet the specific targeting of the most cytotoxic forms of Aβ is by far the most critical requirement. Synthetic Aβ can exist in vitro in a bewildering array of assemblies that differ in structure and size 6 , but it remains unclear whether the assemblies that can be formed in vitro ever exist in the human brain. In striking contrast to the hundreds of studies that have investigated the aggregation and toxicity of synthetic Aβ, only ~20 studies have focused on aqueously soluble Aβ species extracted directly from human brain. These studies can be divided into three categories: efforts to identify the primary sequence and/or assembly forms that constitute water-soluble Aβ, whether bioactive or not 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ; attempts to investigate the cytotoxic activity 22 , 23 , 24 , 25 , 26 , 27 or seeding activity 28 , 29 of crude Aβ–containing extracts; and efforts to study the assembly size of the neurotoxic components of Aβ-rich brain extracts 30 , 31 , 32 , 33 , 34 . Collectively, these studies suggest that Aβ in aqueous extracts of AD brain exists as a mixture of different sized assemblies 10 , 12 , 13 , 14 , 21 , 30 and that one or more of these are extremely potent toxins 22 , 23 , 24 , 25 , 26 , 30 , 31 , 32 , 33 . Indeed, in some experiments, human brain-derived Aβ assemblies were found to be many orders of magnitude more potent than synthetic Aβ peptides 24 , 32 . Recently, we have shown that only a fraction of AD brain-derived Aβ has disease-relevant bioactivity 34 . There are now at least 9 anti-Aβ monoclonal antibodies (mAbs) at various stages of clinical investigation 35 , five of which are believed to preferentially target Aβ oligomers 25 , 36 , 37 , 38 , 39 . Three of these advanced mAbs—crenezumab 25 , BAN2401 14 , 40 , and SAR228810 38 —were selected against synthetic Aβ, whereas aducanumab was selected based on immunohistochemical detection of AD amyloid plaques 37 , 41 . The rationale underlying the use of putatively oligomer-specific mAbs is based on the hypothesis that both Aβ monomers and insoluble fibrillar plaques are relatively innocuous; therefore, an ideal antibody would react weakly with monomers and mature fibrils, but strongly with diffusible oligomers. A key requirement for all CNS immunotherapies is delivering sufficient mAb to the brain. Normally, only ~0.1% of circulating antibody arrives in the brain at steady state 42 , so it is essential that the antibody that does enter the brain is not lost on superfluous targets. One explanation for the disappointing clinical efficacy of anti-Aβ antibodies in human trials is that they target a broad range of Aβ species, including many relatively inactive forms 34 and thus cannot attain the necessary therapeutic concentration against bioactive forms. Similarly, in certain studies sub-optimal antibody levels were used to avoid side-effects such amyloid-related imaging abnormalities (ARIA) 43 . Currently, there is no information in the public domain about the relative ability of candidate therapeutic antibodies to recognize toxic forms of Aβ in human brain, and the properties of optimal therapeutic Aβ antibodies remain ill-defined. To address this central problem, we generated an aggregate-preferring mAb, called 1C22, which shares many of the characteristics of the anti-oligomer mAbs in clinical development 25 , 36 , 40 , 44 , 45 , and we compared its binding properties to those of the murine precursors of solanezumab (mAb 266) and bapineuzumab (mAb 3D6). Solanezumab continues to be tested in two secondary prevention trials 46 , 47 , and an Fc-modified form of bapineuzumab, called AAB-003, is being assessed for treating mild AD 48 . We found that both 3D6 and 266 bound tightly to monomers, whereas 1C22 bound monomers only weakly, and that 1C22 preferentially bound protofibrils (PFs) of Aβ. PFs comprise a heterogeneous mixture of prefibrillar assemblies which by EM appear as short flexible rods with an average width of 5.8 ± 0.2 nm and length <300 nm 49 , 50 . Having established that 1C22, 3D6 and 266 possess distinct binding preferences, we examined the most important property of any potential anti-Aβ immunotherapeutic, its ability to neutralize neurotoxic Aβ. For this purpose, we developed<|im_end|> <|im_start|>assistant Two new studies published by investigators from Brigham and Women's Hospital illustrate that not all forms of amyloid-beta (Aβ) protein—the protein thought to initiate Alzheimer's disease—play an equally menacing role in the progress of the disease. Using a new way of preparing and extracting the protein as well as a new technique to search for promising drug candidates, researchers have highlighted the importance of testing and targeting different forms of Aβ. Their work may help advance the search for more precise and effective drugs to prevent or halt the progress of Alzheimer's disease. "Many different efforts are currently underway to find treatments for Alzheimer's disease, and anti-Aβ antibodies are currently the furthest advanced. But the question remains: what are the most important forms of Aβ to target? Our study points to some interesting answers," said Dominic Walsh, Ph.D., a principal investigator in the Ann Romney Center. Aβ protein can take forms ranging from monomers—single molecules—to twisted tangles of plaques that can pollute the brain and are large enough that they can be seen with a traditional microscope. Walsh compares monomers to single Lego bricks, which can start sticking together to form complex structures of varying sizes. The two recently published studies investigate how to find new potential therapeutics that can target the structures most likely to cause harm. Most Alzheimer's disease studies use synthetic Aβ to approximate what conditions in the brain of an Alzheimer's patient might be like. A small number of researchers have used Aβ extracted from human brain, but the extraction process is crude. In a study published in Acta Neuropathologica in April, Walsh and colleagues developed a much gentler extraction protocol to prepare samples from subjects with Alzheimer's disease. The team found that Aβ was far more abundant in traditional crude extracts, but that the bulk of the extracted Aβ was innocuous. In contrast, much less Aβ was obtained with the gentler protocol, but in this case most of the Aβ was toxic. In a second study published in Nature Communications in July, Walsh and colleagues developed a screening test to try to find potential drugs to target the toxic forms of Aβ. The new technique uses extracts of brain samples from Alzheimer's disease patients and live-cell imaging of stem-cell derived brain cells to find promising therapeutics. The team reports on 1C22, an Aβ antibody that they found could protect against toxic forms of amyloid-beta more effectively than the most clinically advanced Alzheimer's disease therapeutics currently in clinical trials. "We anticipate that this primary screening technique will be useful in the search to identify more potent anti-Aβ therapeutics in the future," said Walsh. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 10541, 279, 64383, 52196, 34318, 10039, 39340, 320, 32, 52355, 8, 374, 11846, 311, 1514, 459, 79516, 3560, 304, 44531, 753, 8624, 320, 1846, 705, 279, 31206, 17910, 315, 279, 1401, 1853, 29569, 362, 52355, 7739, 527, 539, 1664, 16365, 13, 1666, 264, 1121, 11, 433, 706, 19168, 5107, 311, 10765, 23669, 13307, 430, 2218, 8624, 5621, 8532, 7739, 315, 362, 52355, 13, 5810, 11, 584, 11093, 279, 1005, 315, 362, 52355, 41947, 66300, 788, 49062, 315, 8271, 10688, 505, 9827, 6978, 439, 264, 2592, 315, 3823, 362, 52355, 323, 3974, 33001, 32758, 315, 77586, 3624, 72286, 3823, 34313, 311, 2274, 264, 17332, 395, 352, 13171, 315, 10484, 7922, 279, 8844, 29219, 6372, 315, 5361, 7294, 6830, 52355, 59854, 13, 1226, 1934, 279, 60993, 315, 220, 16, 34, 1313, 11, 459, 24069, 2320, 1116, 14782, 8309, 483, 7294, 6830, 52355, 63052, 11, 902, 2731, 36236, 2403, 7739, 315, 362, 52355, 55984, 69638, 430, 527, 21503, 311, 21850, 3695, 1109, 656, 279, 8309, 483, 5956, 34291, 315, 279, 14830, 33119, 1605, 88886, 11, 293, 391, 483, 5308, 372, 370, 323, 2092, 2194, 89, 372, 370, 13, 4314, 3135, 4284, 4726, 24481, 315, 220, 16, 34, 1313, 374, 74280, 11, 323, 430, 420, 17332, 395, 352, 7344, 5505, 439, 264, 6156, 4264, 311, 10765, 3686, 810, 36875, 7294, 6830, 52355, 9139, 88886, 13, 29438, 19157, 14576, 1701, 96157, 12490, 278, 59854, 311, 2218, 279, 64383, 52196, 34318, 10039, 39340, 320, 32, 52355, 8, 35256, 279, 7928, 323, 1455, 11084, 37471, 5149, 311, 4322, 44531, 753, 8624, 320, 1846, 8, 220, 16, 1174, 220, 17, 1174, 220, 18, 662, 18185, 8965, 1695, 20124, 304, 864, 91899, 8814, 4211, 11, 7294, 6830, 52355, 33119, 42811, 706, 58487, 7347, 2450, 304, 12966, 220, 17, 1174, 220, 18, 662, 1398, 10609, 811, 9076, 311, 2759, 369, 279, 8009, 14807, 315, 864, 31717, 258, 950, 3063, 59854, 1139, 3823, 52312, 2997, 69063, 9269, 2955, 11, 21623, 520, 264, 8624, 6566, 994, 1070, 374, 2736, 5199, 30828, 4814, 11, 323, 33781, 2218, 3373, 1968, 315, 279, 59854, 1511, 220, 17, 1174, 220, 19, 1174, 220, 20, 662, 3277, 47614, 279, 41265, 315, 904, 37471, 11, 1070, 527, 3892, 4819, 311, 2980, 28858, 2218, 20392, 11, 323, 3686, 279, 3230, 25103, 315, 279, 1455, 79909, 91676, 7739, 315, 362, 52355, 374, 555, 3117, 279, 1455, 9200, 16686, 13, 75928, 362, 52355, 649, 3073, 304, 55004, 304, 264, 99774, 4776, 1358, 315, 62407, 430, 1782, 304, 6070, 323, 1404, 220, 21, 1174, 719, 433, 8625, 25420, 3508, 279, 62407, 430, 649, 387, 14454, 304, 55004, 3596, 3073, 304, 279, 3823, 8271, 13, 763, 21933, 13168, 311, 279, 11758, 315, 7978, 430, 617, 27313, 279, 52729, 323, 58011, 315, 28367, 362, 52355, 11, 1193, 4056, 508, 7978, 617, 10968, 389, 66300, 7162, 88045, 362, 52355, 9606, 28532, 6089, 505, 3823, 8271, 13, 4314, 7978, 649, 387, 18255, 1139, 2380, 11306, 25, 9045, 311, 10765, 279, 6156, 8668, 323, 5255, 14956, 7739, 430, 35256, 3090, 1355, 337, 41572, 362, 52355, 11, 3508, 17332, 3104, 477, 539, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 1174, 220, 972, 1174, 220, 777, 1174, 220, 508, 1174, 220, 1691, 2652, 13865, 311, 19874, 279, 79909, 91676, 5820, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 1174, 220, 1627, 1174, 220, 1544, 477, 95515, 5820, 220, 1591, 1174, 220, 1682, 315, 35750, 362, 52355, 4235, 778, 2101, 49062, 26, 323, 9045, 311, 4007, 279, 14956, 1404, 315, 279, 18247, 998, 14668, 6956, 315, 362, 52355, 41947, 8271, 49062, 220, 966, 1174, 220, 2148, 1174, 220, 843, 1174, 220, 1644, 1174, 220, 1958, 662, 21153, 3210, 11, 1521, 7978, 4284, 430, 362, 52355, 304, 66300, 788, 49062, 315, 9827, 8271, 6866, 439, 264, 21655, 315, 2204, 30387, 62407, 220, 605, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 1691, 1174, 220, 966, 323, 430, 832, 477, 810, 315, 1521, 527, 9193, 36875, 62186, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 1174, 220, 1627, 1174, 220, 966, 1174, 220, 2148, 1174, 220, 843, 1174, 220, 1644, 662, 23150, 11, 304, 1063, 21896, 11, 3823, 8271, 72286, 362, 52355, 62407, 1051, 1766, 311, 387, 1690, 10373, 315, 26703, 810, 36875, 1109, 28367, 362, 52355, 96434, 220, 1187, 1174, 220, 843, 662, 42096, 11, 584, 617, 6982, 430, 1193, 264, 19983, 315, 9827, 8271, 72286, 362, 52355, 706, 8624, 5621, 8532, 17332, 7323, 220, 1958, 662, 2684, 527, 1457, 520, 3325, 220, 24, 7294, 6830, 52355, 96157, 12490, 278, 59854, 320, 76, 28878, 8, 520, 5370, 18094, 315, 14830, 8990, 220, 1758, 1174, 4330, 315, 902, 527, 11846, 311, 10932, 31668, 2218, 362, 52355, 55984, 69638, 220, 914, 1174, 220, 1927, 1174, 220, 1806, 1174, 220, 1987, 1174, 220, 2137, 662, 14853, 315, 1521, 11084, 296, 28878, 2345, 846, 55506, 372, 370, 220, 914, 1174, 426, 1111, 8273, 16, 220, 975, 1174, 220, 1272, 1174, 323, 69878, 14261, 19232, 220, 1987, 2001, 52898, 4183, 2403, 28367, 362, 52355, 11, 20444, 1008, 1791, 276, 372, 370, 574, 4183, 3196, 389, 33119, 2319, 26407, 32056, 18468, 315, 9827, 64383, 52196, 40852, 14295, 220, 1806, 1174, 220, 3174, 662, 578, 57916, 16940, 279, 1005, 315, 2231, 8046, 55984, 26429, 19440, 296, 28878, 374, 3196, 389, 279, 31178, 430, 2225, 362, 52355, 1647, 69638, 323, 85943, 41572, 95235, 484, 277, 40852, 14295, 527, 12309, 19132, 9373, 26, 9093, 11, 459, 10728, 63052, 1053, 14085, 7621, 398, 449, 1647, 69638, 323, 15196, 95235, 8839, 11, 719, 16917, 449, 3722, 355, 1260, 55984, 69638, 13, 362, 1401, 16686, 369, 682, 93643, 33119, 1605, 391, 552, 374, 24944, 14343, 296, 5953, 311, 279, 8271, 13, 52783, 11, 1193, 4056, 15, 13, 16, 4, 315, 54828, 63052, 30782, 304, 279, 8271, 520, 24981, 1614, 220, 2983, 1174, 779, 433, 374, 7718, 430, 279, 63052, 430, 1587, 3810, 279, 8271, 374, 539, 5675, 389, 2307, 1517, 9373, 11811, 13, 3861, 16540, 369, 279, 39223, 14830, 41265, 315, 7294, 6830, 52355, 59854, 304, 3823, 19622, 374, 430, 814, 2218, 264, 7353, 2134, 315, 362, 52355, 9606, 11, 2737, 1690, 12309, 32899, 7739, 220, 1958, 323, 8617, 4250, 36861, 279, 5995, 37471, 20545, 2403, 17332, 3104, 7739, 13, 35339, 11, 304, 3738, 7978, 1207, 57212, 2931, 63052, 5990, 1051, 1511, 311, 5766, 3185, 75888, 1778, 64383, 52196, 14228, 32758, 75815, 320, 946, 5987, 8, 220, 3391, 662, 25122, 11, 1070, 374, 912, 2038, 304, 279, 586, 8106, 922, 279, 8844, 5845, 315, 9322, 37471, 59854, 311, 15641, 21503, 7739, 315, 362, 52355, 304, 3823, 8271, 11, 323, 279, 6012, 315, 23669, 37471, 362, 52355, 59854, 7293, 5986, 39817, 13, 2057, 2686, 420, 8792, 3575, 11, 584, 8066, 459, 24069, 2320, 1116, 14782, 296, 5953, 11, 2663, 220, 16, 34, 1313, 11, 902, 13551, 1690, 315, 279, 17910, 315, 279, 7294, 12, 337, 343, 26429, 296, 28878, 304, 14830, 4500, 220, 914, 1174, 220, 1927, 1174, 220, 1272, 1174, 220, 2096, 1174, 220, 1774, 1174, 323, 584, 7863, 1202, 11212, 6012, 311, 1884, 315, 279, 8309, 483, 5956, 34291, 315, 2092, 2194, 89, 372, 370, 320, 76, 5953, 220, 15999, 8, 323, 293, 391, 483, 5308, 372, 370, 320, 76, 5953, 220, 18, 35, 21, 570, 11730, 2194, 89, 372, 370, 9731, 311, 387, 12793, 304, 1403, 14580, 27344, 19622, 220, 2790, 1174, 220, 2618, 1174, 323, 459, 435, 66, 17515, 1908, 1376, 315, 293, 391, 483, 5308, 372, 370, 11, 2663, 362, 1905, 12, 6268, 11, 374, 1694, 32448, 369, 27723, 23900, 9827, 220, 2166, 662, 1226, 1766, 430, 2225, 220, 18, 35, 21, 323, 220, 15999, 6965, 40069, 311, 1647, 69638, 11, 20444, 220, 16, 34, 1313, 6965, 1647, 69638, 1193, 7621, 398, 11, 323, 430, 220, 16, 34, 1313, 10932, 31668, 6965, 18940, 69, 10892, 8839, 320, 20280, 82, 8, 315, 362, 52355, 13, 29515, 82, 54350, 264, 98882, 21655, 315, 19257, 10892, 484, 277, 62407, 902, 555, 17329, 5101, 439, 2875, 19303, 58000, 449, 459, 5578, 2430, 315, 220, 20, 13, 23, 20903, 220, 15, 13, 17, 26807, 323, 3160, 366, 3101, 26807, 220, 2491, 1174, 220, 1135, 662, 20636, 9749, 430, 220, 16, 34, 1313, 11, 220, 18, 35, 21, 323, 220, 15999, 15575, 12742, 11212, 19882, 11, 584, 25078, 279, 1455, 3062, 3424, 315, 904, 4754, 7294, 6830, 52355, 33119, 1605, 32486, 11, 1202, 5845, 311, 21277, 553, 18247, 998, 14668, 362, 52355, 13, 1789, 420, 7580, 11, 584, 8040, 128257, 198, 128256, 78191, 198, 11874, 502, 7978, 4756, 555, 26453, 505, 96285, 323, 11215, 596, 15429, 41468, 430, 539, 682, 7739, 315, 64383, 52196, 68740, 320, 32, 52355, 8, 13128, 22416, 13128, 3463, 311, 39201, 44531, 596, 8624, 2345, 1387, 459, 18813, 95072, 3560, 304, 279, 5208, 315, 279, 8624, 13, 12362, 264, 502, 1648, 315, 20646, 323, 60508, 279, 13128, 439, 1664, 439, 264, 502, 15105, 311, 2778, 369, 26455, 5623, 11426, 11, 12074, 617, 27463, 279, 12939, 315, 7649, 323, 25103, 2204, 7739, 315, 362, 52355, 13, 11205, 990, 1253, 1520, 12178, 279, 2778, 369, 810, 24473, 323, 7524, 11217, 311, 5471, 477, 27365, 279, 5208, 315, 44531, 596, 8624, 13, 330, 8607, 2204, 9045, 527, 5131, 38199, 311, 1505, 22972, 369, 44531, 596, 8624, 11, 323, 7294, 6830, 52355, 59854, 527, 5131, 279, 18742, 61943, 11084, 13, 2030, 279, 3488, 8625, 25, 1148, 527, 279, 1455, 3062, 7739, 315, 362, 52355, 311, 2218, 30, 5751, 4007, 3585, 311, 1063, 7185, 11503, 1359, 1071, 68134, 52294, 11, 2405, 920, 2637, 264, 12717, 49581, 304, 279, 9489, 26386, 5955, 13, 362, 52355, 13128, 649, 1935, 7739, 24950, 505, 1647, 69638, 2345, 15698, 35715, 50617, 38817, 259, 17694, 315, 40852, 14295, 430, 649, 7230, 1088, 279, 8271, 323, 527, 3544, 3403, 430, 814, 649, 387, 3970, 449, 264, 8776, 73757, 13, 52294, 43565, 1647, 69638, 311, 3254, 65770, 50137, 11, 902, 649, 1212, 38072, 3871, 311, 1376, 6485, 14726, 315, 29865, 12562, 13, 578, 1403, 6051, 4756, 7978, 19874, 1268, 311, 1505, 502, 4754, 9139, 88886, 430, 649, 2218, 279, 14726, 1455, 4461, 311, 5353, 11682, 13, 7648, 44531, 596, 8624, 7978, 1005, 28367, 362, 52355, 311, 45968, 1148, 4787, 304, 279, 8271, 315, 459, 44531, 596, 8893, 2643, 387, 1093, 13, 362, 2678, 1396, 315, 12074, 617, 1511, 362, 52355, 28532, 505, 3823, 8271, 11, 719, 279, 33289, 1920, 374, 35750, 13, 763, 264, 4007, 4756, 304, 3298, 64, 45950, 897, 589, 1640, 3074, 304, 5936, 11, 52294, 323, 18105, 8040, 264, 1790, 16265, 1565, 33289, 11766, 311, 10772, 10688, 505, 15223, 449, 44531, 596, 8624, 13, 578, 2128, 1766, 430, 362, 52355, 574, 3117, 810, 44611, 304, 8776, 35750, 49062, 11, 719, 430, 279, 20155, 315, 279, 28532, 362, 52355, 574, 19132, 9373, 13, 763, 13168, 11, 1790, 2753, 362, 52355, 574, 12457, 449, 279, 16265, 1565, 11766, 11, 719, 304, 420, 1162, 1455, 315, 279, 362, 52355, 574, 21503, 13, 763, 264, 2132, 4007, 4756, 304, 22037, 26545, 304, 5887, 11, 52294, 323, 18105, 8040, 264, 23061, 1296, 311, 1456, 311, 1505, 4754, 11217, 311, 2218, 279, 21503, 7739, 315, 362, 52355, 13, 578, 502, 15105, 5829, 49062, 315, 8271, 10688, 505, 44531, 596, 8624, 6978, 323, 3974, 33001, 32758, 315, 19646, 33001, 14592, 8271, 7917, 311, 1505, 26455, 9139, 88886, 13, 578, 2128, 6821, 389, 220, 16, 34, 1313, 11, 459, 362, 52355, 63052, 430, 814, 1766, 1436, 6144, 2403, 21503, 7739, 315, 64383, 52196, 68740, 810, 13750, 1109, 279, 1455, 70432, 11084, 44531, 596, 8624, 9139, 88886, 5131, 304, 14830, 19622, 13, 330, 1687, 48248, 430, 420, 6156, 23061, 15105, 690, 387, 5505, 304, 279, 2778, 311, 10765, 810, 36875, 7294, 6830, 52355, 9139, 88886, 304, 279, 3938, 1359, 1071, 52294, 13, 220, 128257, 198 ]

1,993

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Early diagnosis of Alzheimer’s disease plays a pivotal role in patient care and clinical trials. In this study, we have developed a new approach based on 3D deep convolutional neural networks to accurately differentiate mild Alzheimer’s disease dementia from mild cognitive impairment and cognitively normal individuals using structural MRIs. For comparison, we have built a reference model based on the volumes and thickness of previously reported brain regions that are known to be implicated in disease progression. We validate both models on an internal held-out cohort from The Alzheimer's Disease Neuroimaging Initiative (ADNI) and on an external independent cohort from The National Alzheimer's Coordinating Center (NACC). The deep-learning model is accurate, achieved an area-under-the-curve (AUC) of 85.12 when distinguishing between cognitive normal subjects and subjects with either MCI or mild Alzheimer’s dementia. In the more challenging task of detecting MCI, it achieves an AUC of 62.45. It is also significantly faster than the volume/thickness model in which the volumes and thickness need to be extracted beforehand. The model can also be used to forecast progression: subjects with mild cognitive impairment misclassified as having mild Alzheimer’s disease dementia by the model were faster to progress to dementia over time. An analysis of the features learned by the proposed model shows that it relies on a wide range of regions associated with Alzheimer's disease. These findings suggest that deep neural networks can automatically learn to identify imaging biomarkers that are predictive of Alzheimer's disease, and leverage them to achieve accurate early detection of the disease. Introduction Alzheimer’s disease is the leading cause of dementia, and the sixth leading cause of death in the United States 1 . Improving early detection of Alzheimer’s disease is a critical need for optimal intervention success, as well as for counseling patients and families, clinical trial enrollment, and determining which patients would benefit from future disease-modifying therapy 2 . Alzheimer’s disease related brain degeneration begins years before the clinical onset of symptoms. In recent years, the development of PET imaging techniques using tracers for amyloid and tau have improved our ability to detect Alzheimer’s disease at preclinical and prodromal stages, but they have a significant disadvantage of being expensive and requiring specialized tracers and equipment. Many studies have shown that structural MRI-based volume measurements, particularly of the hippocampus and medial temporal lobe, are somewhat predictive of Alzheimer’s disease progression 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 . While the availability and cost of MRI is beneficial, these early attempts to discriminate healthy aging from Alzheimer’s disease based on volumetry had significant limitations, including small sample size and reliance on semi-automated segmentation methods. This motivated the emergence of more sophisticated methods to analyze MRI data based on machine learning. In the last decade, machine learning and fully automatic segmentation methods have achieved impressive results in multiple computer vision and image processing tasks. Early applications of machine learning to Alzheimer’s disease diagnosis from MRIs were based on discriminative features selected a priori 14 , 15 , 16 , 17 . These features include regional volumes and cortical thickness segmented from brain regions known to be involved/implicated with memory loss and accelerated neurodegeneration that accompany Alzheimer’s disease 17 , 18 , 19 . Newer machine learning methods based on deep convolutional neural networks (CNNs) make it possible to extract features directly from image data in a data-driven fashion 20 , 21 , 22 , 23 , 24 , 25 , 26 . These methods have been shown to outperform traditional techniques based on predefined features in most image processing and computer vision tasks 27 , 28 . In the biomedical field, CNN-based methods also have the potential to reveal new imaging biomarkers 29 , 30 . Multiple studies have addressed mild Alzheimer’s disease dementia detection from MRI via deep learning, with notable examples of 3D convolutional neural networks based on 3D AlexNet, 3D Resnet, patch based models, Siamese networks, auto-encoder based models, among others 31 , 32 , 33 . Based on systematic reviews and survey studies 34 , 35 , many of previous approaches had major limitations in their design or validation: Most of these studies focus on distinguishing Alzheimer’s disease dementia patients from normal controls. However, in order to develop effective and clinically relevant early detection methods, it is crucial to also differentiate prodromal Alzheimer’s disease, otherwise known as mild cognitive impairment (MCI), from both normal controls and patients with manifest Alzheimer’s disease dementia. Some recent studies have made inroads to this end 36 , 37 , 38 , but do not evaluate their results on large independent cohorts where there can be more variability in image acquisition and clinical diagnosis, more representative of real world scenarios. The goal of this work is to address these significant challenges. We propose a deep-learning model based on a novel CNN architecture that is capable of distinguishing between persons who have normal cognition, MCI, and mild Alzheimer’s disease dementia. The proposed model is trained using a publicly available dataset from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Although a multisite study, ADNI sites follow a rigorous standard protocol and stringent quality control to minimize site differences and improve our ability to reliably detect neuroanatomical changes. To assess the performance of the proposed methodology when applied in more realistic conditions, we evaluated our approach on an entirely independent cohort of 1522 subjects from the National Alzheimer’s Coordinating Center (NACC). Since (until very recently) each NIH/NIA funded center contributing to the NACC database is free to employ different acquisition parameters, this enables us to validate our approach on imaging data acquired with variable and non standardized protocols. Our approach achieves an area-under-the-curve (AUC) of 85.12 (95% CI: 84.98–85.26) when distinguishing between cognitive normal subjects and subjects with either MCI or mild Alzheimer’s dementia in the independent NACC cohort. For comparison, we have built a reference model based on the volumes and thickness of previously reported brain regions that are", "role": "user" }, { "content": "Griffith University researchers have demonstrated that a bacteria can travel through the olfactory nerve in the nose and into the brain in mice, where it creates markers that are a tell-tale sign of Alzheimer's disease. The study, published in the journal Scientific Reports, showed that Chlamydia pneumoniae used the nerve extending between the nasal cavity and the brain as an invasion path to invade the central nervous system. The cells in the brain then responded by depositing amyloid beta protein which is a hallmark of Alzheimer's disease. Professor James St John, Head of the Clem Jones Center for Neurobiology and Stem Cell Research, is a co-author of the world first research. \"We're the first to show that Chlamydia pneumoniae can go directly up the nose and into the brain where it can set off pathologies that look like Alzheimer's disease,\" Professor St John said. \"We saw this happen in a mouse model, and the evidence is potentially scary for humans as well.\" The olfactory nerve in the nose is directly exposed to air and offers a short pathway to the brain, one which bypasses the blood-brain barrier. It's a route that viruses and bacteria have sniffed out as an easy one into the brain. The team at the Center is already planning the next phase of research and aim to prove the same pathway exists in humans. \"We need to do this study in humans and confirm whether the same pathway operates in the same way. It's research that has been proposed by many people, but not yet completed. What we do know is that these same bacteria are present in humans, but we haven't worked out how they get there.\" There are some simple steps to look after the lining of your nose that Professor St John suggests people can take now if they want to lower their risk of potentially developing late-onset Alzheimer's disease. \"Picking your nose and plucking the hairs from your nose are not a good idea,\" he said. \"We don't want to damage the inside of our nose and picking and plucking can do that. If you damage the lining of the nose, you can increase how many bacteria can go up into your brain.\" Smell tests may also have potential as detectors for Alzheimer's and dementia says Professor St John, as loss of sense of smell is an early indicator of Alzheimer's disease. He suggests smell tests from when a person turns 60 years old could be beneficial as an early detector. \"Once you get over 65 years old, your risk factor goes right up, but we're looking at other causes as well, because it's not just age—it is environmental exposure as well. And we think that bacteria and viruses are critical.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Early diagnosis of Alzheimer’s disease plays a pivotal role in patient care and clinical trials. In this study, we have developed a new approach based on 3D deep convolutional neural networks to accurately differentiate mild Alzheimer’s disease dementia from mild cognitive impairment and cognitively normal individuals using structural MRIs. For comparison, we have built a reference model based on the volumes and thickness of previously reported brain regions that are known to be implicated in disease progression. We validate both models on an internal held-out cohort from The Alzheimer's Disease Neuroimaging Initiative (ADNI) and on an external independent cohort from The National Alzheimer's Coordinating Center (NACC). The deep-learning model is accurate, achieved an area-under-the-curve (AUC) of 85.12 when distinguishing between cognitive normal subjects and subjects with either MCI or mild Alzheimer’s dementia. In the more challenging task of detecting MCI, it achieves an AUC of 62.45. It is also significantly faster than the volume/thickness model in which the volumes and thickness need to be extracted beforehand. The model can also be used to forecast progression: subjects with mild cognitive impairment misclassified as having mild Alzheimer’s disease dementia by the model were faster to progress to dementia over time. An analysis of the features learned by the proposed model shows that it relies on a wide range of regions associated with Alzheimer's disease. These findings suggest that deep neural networks can automatically learn to identify imaging biomarkers that are predictive of Alzheimer's disease, and leverage them to achieve accurate early detection of the disease. Introduction Alzheimer’s disease is the leading cause of dementia, and the sixth leading cause of death in the United States 1 . Improving early detection of Alzheimer’s disease is a critical need for optimal intervention success, as well as for counseling patients and families, clinical trial enrollment, and determining which patients would benefit from future disease-modifying therapy 2 . Alzheimer’s disease related brain degeneration begins years before the clinical onset of symptoms. In recent years, the development of PET imaging techniques using tracers for amyloid and tau have improved our ability to detect Alzheimer’s disease at preclinical and prodromal stages, but they have a significant disadvantage of being expensive and requiring specialized tracers and equipment. Many studies have shown that structural MRI-based volume measurements, particularly of the hippocampus and medial temporal lobe, are somewhat predictive of Alzheimer’s disease progression 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 . While the availability and cost of MRI is beneficial, these early attempts to discriminate healthy aging from Alzheimer’s disease based on volumetry had significant limitations, including small sample size and reliance on semi-automated segmentation methods. This motivated the emergence of more sophisticated methods to analyze MRI data based on machine learning. In the last decade, machine learning and fully automatic segmentation methods have achieved impressive results in multiple computer vision and image processing tasks. Early applications of machine learning to Alzheimer’s disease diagnosis from MRIs were based on discriminative features selected a priori 14 , 15 , 16 , 17 . These features include regional volumes and cortical thickness segmented from brain regions known to be involved/implicated with memory loss and accelerated neurodegeneration that accompany Alzheimer’s disease 17 , 18 , 19 . Newer machine learning methods based on deep convolutional neural networks (CNNs) make it possible to extract features directly from image data in a data-driven fashion 20 , 21 , 22 , 23 , 24 , 25 , 26 . These methods have been shown to outperform traditional techniques based on predefined features in most image processing and computer vision tasks 27 , 28 . In the biomedical field, CNN-based methods also have the potential to reveal new imaging biomarkers 29 , 30 . Multiple studies have addressed mild Alzheimer’s disease dementia detection from MRI via deep learning, with notable examples of 3D convolutional neural networks based on 3D AlexNet, 3D Resnet, patch based models, Siamese networks, auto-encoder based models, among others 31 , 32 , 33 . Based on systematic reviews and survey studies 34 , 35 , many of previous approaches had major limitations in their design or validation: Most of these studies focus on distinguishing Alzheimer’s disease dementia patients from normal controls. However, in order to develop effective and clinically relevant early detection methods, it is crucial to also differentiate prodromal Alzheimer’s disease, otherwise known as mild cognitive impairment (MCI), from both normal controls and patients with manifest Alzheimer’s disease dementia. Some recent studies have made inroads to this end 36 , 37 , 38 , but do not evaluate their results on large independent cohorts where there can be more variability in image acquisition and clinical diagnosis, more representative of real world scenarios. The goal of this work is to address these significant challenges. We propose a deep-learning model based on a novel CNN architecture that is capable of distinguishing between persons who have normal cognition, MCI, and mild Alzheimer’s disease dementia. The proposed model is trained using a publicly available dataset from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Although a multisite study, ADNI sites follow a rigorous standard protocol and stringent quality control to minimize site differences and improve our ability to reliably detect neuroanatomical changes. To assess the performance of the proposed methodology when applied in more realistic conditions, we evaluated our approach on an entirely independent cohort of 1522 subjects from the National Alzheimer’s Coordinating Center (NACC). Since (until very recently) each NIH/NIA funded center contributing to the NACC database is free to employ different acquisition parameters, this enables us to validate our approach on imaging data acquired with variable and non standardized protocols. Our approach achieves an area-under-the-curve (AUC) of 85.12 (95% CI: 84.98–85.26) when distinguishing between cognitive normal subjects and subjects with either MCI or mild Alzheimer’s dementia in the independent NACC cohort. For comparison, we have built a reference model based on the volumes and thickness of previously reported brain regions that are<|im_end|> <|im_start|>assistant Griffith University researchers have demonstrated that a bacteria can travel through the olfactory nerve in the nose and into the brain in mice, where it creates markers that are a tell-tale sign of Alzheimer's disease. The study, published in the journal Scientific Reports, showed that Chlamydia pneumoniae used the nerve extending between the nasal cavity and the brain as an invasion path to invade the central nervous system. The cells in the brain then responded by depositing amyloid beta protein which is a hallmark of Alzheimer's disease. Professor James St John, Head of the Clem Jones Center for Neurobiology and Stem Cell Research, is a co-author of the world first research. "We're the first to show that Chlamydia pneumoniae can go directly up the nose and into the brain where it can set off pathologies that look like Alzheimer's disease," Professor St John said. "We saw this happen in a mouse model, and the evidence is potentially scary for humans as well." The olfactory nerve in the nose is directly exposed to air and offers a short pathway to the brain, one which bypasses the blood-brain barrier. It's a route that viruses and bacteria have sniffed out as an easy one into the brain. The team at the Center is already planning the next phase of research and aim to prove the same pathway exists in humans. "We need to do this study in humans and confirm whether the same pathway operates in the same way. It's research that has been proposed by many people, but not yet completed. What we do know is that these same bacteria are present in humans, but we haven't worked out how they get there." There are some simple steps to look after the lining of your nose that Professor St John suggests people can take now if they want to lower their risk of potentially developing late-onset Alzheimer's disease. "Picking your nose and plucking the hairs from your nose are not a good idea," he said. "We don't want to damage the inside of our nose and picking and plucking can do that. If you damage the lining of the nose, you can increase how many bacteria can go up into your brain." Smell tests may also have potential as detectors for Alzheimer's and dementia says Professor St John, as loss of sense of smell is an early indicator of Alzheimer's disease. He suggests smell tests from when a person turns 60 years old could be beneficial as an early detector. "Once you get over 65 years old, your risk factor goes right up, but we're looking at other causes as well, because it's not just age—it is environmental exposure as well. And we think that bacteria and viruses are critical." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 23591, 23842, 315, 44531, 753, 8624, 11335, 264, 60850, 3560, 304, 8893, 2512, 323, 14830, 19622, 13, 763, 420, 4007, 11, 584, 617, 8040, 264, 502, 5603, 3196, 389, 220, 18, 35, 5655, 56812, 278, 30828, 14488, 311, 30357, 54263, 23900, 44531, 753, 8624, 52857, 505, 23900, 25702, 53317, 323, 19329, 275, 3210, 4725, 7931, 1701, 24693, 29433, 3957, 13, 1789, 12593, 11, 584, 617, 5918, 264, 5905, 1646, 3196, 389, 279, 27378, 323, 26839, 315, 8767, 5068, 8271, 13918, 430, 527, 3967, 311, 387, 69702, 304, 8624, 33824, 13, 1226, 9788, 2225, 4211, 389, 459, 5419, 5762, 9994, 41944, 505, 578, 44531, 596, 31974, 32359, 318, 4210, 38756, 320, 1846, 15259, 8, 323, 389, 459, 9434, 9678, 41944, 505, 578, 5165, 44531, 596, 3623, 6114, 1113, 5955, 320, 45, 30542, 570, 578, 5655, 71856, 1646, 374, 13687, 11, 17427, 459, 3158, 72207, 10826, 1824, 74147, 320, 32, 5576, 8, 315, 220, 5313, 13, 717, 994, 86055, 1990, 25702, 4725, 15223, 323, 15223, 449, 3060, 386, 11487, 477, 23900, 44531, 753, 52857, 13, 763, 279, 810, 17436, 3465, 315, 54626, 386, 11487, 11, 433, 83691, 459, 362, 5576, 315, 220, 5538, 13, 1774, 13, 1102, 374, 1101, 12207, 10819, 1109, 279, 8286, 21071, 26989, 1646, 304, 902, 279, 27378, 323, 26839, 1205, 311, 387, 28532, 52159, 13, 578, 1646, 649, 1101, 387, 1511, 311, 18057, 33824, 25, 15223, 449, 23900, 25702, 53317, 5906, 65974, 439, 3515, 23900, 44531, 753, 8624, 52857, 555, 279, 1646, 1051, 10819, 311, 5208, 311, 52857, 927, 892, 13, 1556, 6492, 315, 279, 4519, 9687, 555, 279, 11223, 1646, 5039, 430, 433, 34744, 389, 264, 7029, 2134, 315, 13918, 5938, 449, 44531, 596, 8624, 13, 4314, 14955, 4284, 430, 5655, 30828, 14488, 649, 9651, 4048, 311, 10765, 32758, 39538, 91141, 430, 527, 60336, 315, 44531, 596, 8624, 11, 323, 33164, 1124, 311, 11322, 13687, 4216, 18468, 315, 279, 8624, 13, 29438, 44531, 753, 8624, 374, 279, 6522, 5353, 315, 52857, 11, 323, 279, 26084, 6522, 5353, 315, 4648, 304, 279, 3723, 4273, 220, 16, 662, 22728, 4504, 4216, 18468, 315, 44531, 753, 8624, 374, 264, 9200, 1205, 369, 23669, 21623, 2450, 11, 439, 1664, 439, 369, 42316, 6978, 323, 8689, 11, 14830, 9269, 39148, 11, 323, 26679, 902, 6978, 1053, 8935, 505, 3938, 8624, 17515, 7922, 15419, 220, 17, 662, 44531, 753, 8624, 5552, 8271, 5367, 17699, 12302, 1667, 1603, 279, 14830, 42080, 315, 13803, 13, 763, 3293, 1667, 11, 279, 4500, 315, 50359, 32758, 12823, 1701, 490, 73797, 369, 64383, 52196, 323, 32923, 617, 13241, 1057, 5845, 311, 11388, 44531, 753, 8624, 520, 864, 91899, 323, 14814, 442, 278, 18094, 11, 719, 814, 617, 264, 5199, 49836, 315, 1694, 11646, 323, 23537, 28175, 490, 73797, 323, 7241, 13, 9176, 7978, 617, 6982, 430, 24693, 52460, 6108, 8286, 22323, 11, 8104, 315, 279, 71206, 44651, 323, 97348, 37015, 326, 15784, 11, 527, 14738, 60336, 315, 44531, 753, 8624, 33824, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 662, 6104, 279, 18539, 323, 2853, 315, 52460, 374, 24629, 11, 1521, 4216, 13865, 311, 60541, 9498, 30084, 505, 44531, 753, 8624, 3196, 389, 63920, 15501, 1047, 5199, 9669, 11, 2737, 2678, 6205, 1404, 323, 54180, 389, 18768, 12, 28172, 660, 60852, 5528, 13, 1115, 27762, 279, 49179, 315, 810, 27877, 5528, 311, 24564, 52460, 828, 3196, 389, 5780, 6975, 13, 763, 279, 1566, 13515, 11, 5780, 6975, 323, 7373, 17392, 60852, 5528, 617, 17427, 16358, 3135, 304, 5361, 6500, 11376, 323, 2217, 8863, 9256, 13, 23591, 8522, 315, 5780, 6975, 311, 44531, 753, 8624, 23842, 505, 29433, 3957, 1051, 3196, 389, 50419, 1413, 4519, 4183, 264, 4972, 72, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 662, 4314, 4519, 2997, 15481, 27378, 323, 83619, 26839, 86045, 505, 8271, 13918, 3967, 311, 387, 6532, 14, 6802, 14040, 449, 5044, 4814, 323, 49858, 18247, 451, 81157, 430, 19780, 44531, 753, 8624, 220, 1114, 1174, 220, 972, 1174, 220, 777, 662, 1561, 261, 5780, 6975, 5528, 3196, 389, 5655, 56812, 278, 30828, 14488, 320, 56555, 82, 8, 1304, 433, 3284, 311, 8819, 4519, 6089, 505, 2217, 828, 304, 264, 828, 32505, 11401, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 1174, 220, 1627, 662, 4314, 5528, 617, 1027, 6982, 311, 704, 29588, 8776, 12823, 3196, 389, 64162, 4519, 304, 1455, 2217, 8863, 323, 6500, 11376, 9256, 220, 1544, 1174, 220, 1591, 662, 763, 279, 94612, 2115, 11, 20352, 6108, 5528, 1101, 617, 279, 4754, 311, 16805, 502, 32758, 39538, 91141, 220, 1682, 1174, 220, 966, 662, 29911, 7978, 617, 20669, 23900, 44531, 753, 8624, 52857, 18468, 505, 52460, 4669, 5655, 6975, 11, 449, 28289, 10507, 315, 220, 18, 35, 56812, 278, 30828, 14488, 3196, 389, 220, 18, 35, 8683, 7099, 11, 220, 18, 35, 1838, 4816, 11, 11140, 3196, 4211, 11, 12095, 986, 68, 14488, 11, 3313, 12, 28106, 3196, 4211, 11, 4315, 3885, 220, 2148, 1174, 220, 843, 1174, 220, 1644, 662, 20817, 389, 37538, 8544, 323, 10795, 7978, 220, 1958, 1174, 220, 1758, 1174, 1690, 315, 3766, 20414, 1047, 3682, 9669, 304, 872, 2955, 477, 10741, 25, 7648, 315, 1521, 7978, 5357, 389, 86055, 44531, 753, 8624, 52857, 6978, 505, 4725, 11835, 13, 4452, 11, 304, 2015, 311, 2274, 7524, 323, 70432, 9959, 4216, 18468, 5528, 11, 433, 374, 16996, 311, 1101, 54263, 14814, 442, 278, 44531, 753, 8624, 11, 6062, 3967, 439, 23900, 25702, 53317, 320, 44, 11487, 705, 505, 2225, 4725, 11835, 323, 6978, 449, 14794, 44531, 753, 8624, 52857, 13, 4427, 3293, 7978, 617, 1903, 304, 43791, 311, 420, 842, 220, 1927, 1174, 220, 1806, 1174, 220, 1987, 1174, 719, 656, 539, 15806, 872, 3135, 389, 3544, 9678, 90388, 1405, 1070, 649, 387, 810, 54709, 304, 2217, 24279, 323, 14830, 23842, 11, 810, 18740, 315, 1972, 1917, 26350, 13, 578, 5915, 315, 420, 990, 374, 311, 2686, 1521, 5199, 11774, 13, 1226, 30714, 264, 5655, 71856, 1646, 3196, 389, 264, 11775, 20352, 18112, 430, 374, 13171, 315, 86055, 1990, 11434, 889, 617, 4725, 75310, 11, 386, 11487, 11, 323, 23900, 44531, 753, 8624, 52857, 13, 578, 11223, 1646, 374, 16572, 1701, 264, 17880, 2561, 10550, 505, 279, 44531, 753, 31974, 32359, 318, 4210, 38756, 320, 1846, 15259, 570, 10541, 264, 75837, 635, 4007, 11, 9827, 15259, 6732, 1833, 264, 47999, 5410, 11766, 323, 70099, 4367, 2585, 311, 30437, 2816, 12062, 323, 7417, 1057, 5845, 311, 57482, 11388, 18247, 276, 22612, 950, 4442, 13, 2057, 8720, 279, 5178, 315, 279, 11223, 38152, 994, 9435, 304, 810, 26569, 4787, 11, 584, 26126, 1057, 5603, 389, 459, 11622, 9678, 41944, 315, 220, 9756, 17, 15223, 505, 279, 5165, 44531, 753, 3623, 6114, 1113, 5955, 320, 45, 30542, 570, 8876, 320, 39830, 1633, 6051, 8, 1855, 84370, 20906, 5987, 24853, 4219, 29820, 311, 279, 452, 30542, 4729, 374, 1949, 311, 3539, 2204, 24279, 5137, 11, 420, 20682, 603, 311, 9788, 1057, 5603, 389, 32758, 828, 19426, 449, 3977, 323, 2536, 51114, 32885, 13, 5751, 5603, 83691, 459, 3158, 72207, 10826, 1824, 74147, 320, 32, 5576, 8, 315, 220, 5313, 13, 717, 320, 2721, 4, 21351, 25, 220, 5833, 13, 3264, 4235, 5313, 13, 1627, 8, 994, 86055, 1990, 25702, 4725, 15223, 323, 15223, 449, 3060, 386, 11487, 477, 23900, 44531, 753, 52857, 304, 279, 9678, 452, 30542, 41944, 13, 1789, 12593, 11, 584, 617, 5918, 264, 5905, 1646, 3196, 389, 279, 27378, 323, 26839, 315, 8767, 5068, 8271, 13918, 430, 527, 128257, 198, 128256, 78191, 198, 6600, 3168, 411, 3907, 12074, 617, 21091, 430, 264, 24032, 649, 5944, 1555, 279, 8492, 22348, 32015, 304, 279, 19689, 323, 1139, 279, 8271, 304, 24548, 11, 1405, 433, 11705, 24915, 430, 527, 264, 3371, 2442, 1604, 1879, 315, 44531, 596, 8624, 13, 578, 4007, 11, 4756, 304, 279, 8486, 38130, 29140, 11, 8710, 430, 921, 24705, 88, 32106, 69329, 68, 1511, 279, 32015, 33459, 1990, 279, 72188, 56429, 323, 279, 8271, 439, 459, 30215, 1853, 311, 75272, 279, 8792, 23418, 1887, 13, 578, 7917, 304, 279, 8271, 1243, 16846, 555, 16946, 287, 64383, 52196, 13746, 13128, 902, 374, 264, 98799, 315, 44531, 596, 8624, 13, 17054, 7957, 800, 3842, 11, 11452, 315, 279, 46268, 12201, 5955, 369, 32359, 81162, 323, 81948, 14299, 8483, 11, 374, 264, 1080, 43802, 315, 279, 1917, 1176, 3495, 13, 330, 1687, 2351, 279, 1176, 311, 1501, 430, 921, 24705, 88, 32106, 69329, 68, 649, 733, 6089, 709, 279, 19689, 323, 1139, 279, 8271, 1405, 433, 649, 743, 1022, 1853, 9268, 430, 1427, 1093, 44531, 596, 8624, 1359, 17054, 800, 3842, 1071, 13, 330, 1687, 5602, 420, 3621, 304, 264, 8814, 1646, 11, 323, 279, 6029, 374, 13893, 29565, 369, 12966, 439, 1664, 1210, 578, 8492, 22348, 32015, 304, 279, 19689, 374, 6089, 15246, 311, 3805, 323, 6209, 264, 2875, 38970, 311, 279, 8271, 11, 832, 902, 31818, 288, 279, 6680, 31217, 467, 22881, 13, 1102, 596, 264, 6149, 430, 42068, 323, 24032, 617, 58387, 291, 704, 439, 459, 4228, 832, 1139, 279, 8271, 13, 578, 2128, 520, 279, 5955, 374, 2736, 9293, 279, 1828, 10474, 315, 3495, 323, 9395, 311, 12391, 279, 1890, 38970, 6866, 304, 12966, 13, 330, 1687, 1205, 311, 656, 420, 4007, 304, 12966, 323, 7838, 3508, 279, 1890, 38970, 27149, 304, 279, 1890, 1648, 13, 1102, 596, 3495, 430, 706, 1027, 11223, 555, 1690, 1274, 11, 719, 539, 3686, 8308, 13, 3639, 584, 656, 1440, 374, 430, 1521, 1890, 24032, 527, 3118, 304, 12966, 11, 719, 584, 9167, 956, 6575, 704, 1268, 814, 636, 1070, 1210, 2684, 527, 1063, 4382, 7504, 311, 1427, 1306, 279, 36471, 315, 701, 19689, 430, 17054, 800, 3842, 13533, 1274, 649, 1935, 1457, 422, 814, 1390, 311, 4827, 872, 5326, 315, 13893, 11469, 3389, 10539, 751, 44531, 596, 8624, 13, 330, 47, 16671, 701, 19689, 323, 628, 47270, 279, 66060, 505, 701, 19689, 527, 539, 264, 1695, 4623, 1359, 568, 1071, 13, 330, 1687, 1541, 956, 1390, 311, 5674, 279, 4871, 315, 1057, 19689, 323, 21816, 323, 628, 47270, 649, 656, 430, 13, 1442, 499, 5674, 279, 36471, 315, 279, 19689, 11, 499, 649, 5376, 1268, 1690, 24032, 649, 733, 709, 1139, 701, 8271, 1210, 4487, 616, 7177, 1253, 1101, 617, 4754, 439, 69087, 369, 44531, 596, 323, 52857, 2795, 17054, 800, 3842, 11, 439, 4814, 315, 5647, 315, 22843, 374, 459, 4216, 21070, 315, 44531, 596, 8624, 13, 1283, 13533, 22843, 7177, 505, 994, 264, 1732, 10800, 220, 1399, 1667, 2362, 1436, 387, 24629, 439, 459, 4216, 32314, 13, 330, 12805, 499, 636, 927, 220, 2397, 1667, 2362, 11, 701, 5326, 8331, 5900, 1314, 709, 11, 719, 584, 2351, 3411, 520, 1023, 11384, 439, 1664, 11, 1606, 433, 596, 539, 1120, 4325, 44603, 374, 12434, 14675, 439, 1664, 13, 1628, 584, 1781, 430, 24032, 323, 42068, 527, 9200, 1210, 220, 128257, 198 ]

1,844

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The transformation of coral reefs has profound implications for millions of people. However, the interactive effects of changing reefs and fishing remain poorly resolved. We combine underwater surveys (271 000 fishes), catch data (18 000 fishes), and household surveys (351 households) to evaluate how reef fishes and fishers in Moorea, French Polynesia responded to a landscape-scale loss of coral caused by sequential disturbances (a crown-of-thorns sea star outbreak followed by a category 4 cyclone). Although local communities were aware of the disturbances, less than 20% of households reported altering what fishes they caught or ate. This contrasts with substantial changes in the taxonomic composition in the catch data that mirrored changes in fish communities observed on the reef. Our findings highlight that resource users and scientists may have very different interpretations of what constitutes ‘change’ in these highly dynamic social–ecological systems, with broad implications for successful co-management of coral reef fisheries. Access provided by MPDL Services gGmbH c/o Max Planck Digital Library Working on a manuscript? Avoid the common mistakes Introduction Coral reef ecosystems are under significant anthropogenic pressures from overfishing, pollution, sedimentation, ocean acidification, and rising seawater temperatures (Bellwood et al. 2004 ; Hughes et al. 2018 ), resulting in unprecedented levels of coral mortality (Hughes et al. 2017 ) and shifts from coral-dominated to macroalgae-dominated community states (Rogers and Miller 2006 ). Beyond biodiversity loss, degraded reefs present challenges for millions of coastal dwellers who rely on healthy reef ecosystems for food, income, and their personal and cultural identities. This has prompted research examining how local communities and resource users perceive, adapt to, and manage coral reefs in the Anthropocene (McClanahan and Cinner 2012 ; McMillen et al. 2014 ), including a focus on adaptive co-management, whereby management is implemented and adapted based on knowledge about feedbacks between resource users and shifting local ecosystems (Hughes et al. 2005 ). The Pacific Islands region represents an ideal context to investigate how local communities and changing coral reefs interact. Island peoples have shown the capacity to adapt, cope, and innovate in the face of social–ecological change, with positive and negative outcomes for coral reef health (Johannes 2002 ). In some Pacific Islands, such as Fiji, Vanuatu, and the Solomon Islands, marine resources have been effectively managed over long periods through periodic fishing ground closures, gear restrictions, and other socially enforced constraints on harvesting (Cinner et al. 2006 ). Elsewhere, local responses to changing conditions have had negative ecological outcomes, as with poison and dynamite fishing (McManus et al. 1997 ). The effectiveness of adaptive responses is shaped by local cultural values and power relations that inform decision-making and the range of possibilities available (Cinner et al. 2018 ). Effective adaptive management requires that resource users detect or anticipate shifts in the local environment and alter their activities accordingly. Some empirical studies have demonstrated that Pacific islanders can detect rapid shifts in benthic communities disrupted by tsunamis (Lauer and Matera 2016 ), in addition to more gradual changes such as expanding seagrass beds (Lauer and Aswani 2010 ). Numerous questions remain, however, about the sensitivity of local resource users to change, and in particular whether ecosystem disturbances identified by ecologists are similarly perceived by Pacific islanders. We addressed these issues for a small-scale reef fishery on the island of Moorea, French Polynesia. Social and ecological surveys explored how communities perceived and responded to changes in fishery resources associated with a crown-of-thorns sea star (COTS) outbreak followed by a destructive cyclone. In 2004, coral cover around Moorea was near the highest levels observed in the past half century (Trapon et al. 2011 ; Lamy et al. 2016 ), but an outbreak of corallivorous COTS that peaked in 2009, followed by Cyclone Oli in early 2010, reduced live coral cover by > 95% (Adam et al. 2011 ; Trapon et al. 2011 ; Adam et al. 2014 ; Lamy et al. 2015 ). Dead coral skeletons and cleared reef substrates provided substantial free space for growth of macroalgae, raising the possibility that a macroalgal phase shift could occur. However, benthic community changes were rapidly followed by changes in the fish assemblage, with roving herbivorous fishes such as parrotfishes doubling in density and tripling in total biomass (Han et al. 2016 ), thus preventing macroalgae from establishing. Moreover, in the years since the disturbances, coral cover has increased and even exceeds predisturbance levels in some areas (Holbrook et al. 2018 ). Despite intensive ecological study, it is not known if these changes in the fish assemblages have altered fishable resources, the activities of reef fishers, or how local people perceived the changes. Because spearfishing—a highly selective method—is common in Moorea, a shift in the abundances of fishable resources provides an opportunity to assess whether fishers alter what they catch as their resource environment changes. This study addressed four questions: (1) How did residents of Moorea perceive the shifts documented in ecological studies? (2) Do they report changing their fishing behavior or seafood consumption in response to the shift? (3) How did the changes in the fish assemblage affect the availability and taxonomic composition of fishable biomass? and (4) Is there evidence for changes in fishing behavior (such as taxonomic selectivity) over time? To answer these questions, we conducted 351 household surveys documenting fishers’ perceptions of the changes and their potential responses via alteration in fishing practices or fish consumption. We analyzed a time series of catch data (~ 18 000 identified and measured fishes) collected before and after the disturbances, spanning a 9-year time period, to determine changes in targeted fish species and sizes, including key groups of herbivores crucial to recovery and resilience of the coral state. Finally, we compared the catch data with extensive surveys that estimated abundances and biomass of fishes on the reef throughout the same time frame. Materials and Methods Ecological and social contexts Moorea (17°32′S, 149°50′W) is a volcanic ‘high’ island 60 km in perimeter with an offshore barrier reef that encloses a shallow lagoon (Fig. 1", "role": "user" }, { "content": "Results of a new study looking at coral reef disturbances, fish abundance and coastal fishers' catches suggest that ecologists and community anglers may perceive environmental disruptions in very different ways. The apparent disconnect between data-driven scientists and experience-driven fishing communities has implications for the management and resilience of coral reefs and other sensitive marine ecosystems. Lead study author Andrew Rassweiler of Florida State University (FSU), who worked with collaborators at the University of California, Santa Barbara (UCSB) and San Diego State University to conduct fishing surveys and fish population assessments on the French Polynesian island of Moorea, said the research \"shows that different groups have different perceptions of change and ecosystem health.\" The findings are published this week in the journal Ambio. Ecological Distress Coral reefs around the world experience pressure from human activities. As ecosystems react to declines in biodiversity, tropical coastal fishers—whose livelihoods often depend on coral reefs—become less economically and culturally secure. In Moorea, some parts of the island's lagoons support thriving coral communities, while other areas are giving way to overgrowth by seaweed. Scientists looked at fish abundance on the reef in comparison to fish species sold on the island. Credit: Sarah Lester An outbreak of coral-devouring crown-of-thorns sea stars in 2009 and a destructive cyclone in 2010 reduced live coral cover by some 95 percent in many locations. These events threw the ecosystem into disarray, scientists say. In addition to widespread coral losses, effects included abrupt changes in fish populations, with algae-eating, herbivorous fish swarming the area to graze on seaweed growing on the skeletons of dead coral. This influx of seaweed-eating fish wasn't necessarily a surprise, the researchers maintain. Studies at the National Science Foundation's (NSF) Moorea Coral Reef Long-Term Ecological Research (LTER) site on the island had identified the role of herbivorous fish in keeping seaweed forests in check. But Moorea's local fishing communities, where more than three quarters of households have a member who actively fishes the reef, knew less about how this rapid shift in fish abundance occurred. The marine biologists used sizing cards to determine the sizes of fish that were caught and sold. Credit: Terava Atger \"Everyone around the island is fishing, but we know very little about how fishers decide where to fish and what fish to target,\" Rassweiler said. \"This research was a first step in looking at how fishing behavior changed following a big change in the fish community itself.\" Russ Schmitt, a marine ecologist at UCSB and principal investigator of the NSF Moorea Coral Reef LTER site, added \"It turned out that the fishers in Moorea barely noticed the massive ecological shift and reported they didn't change their fishing practices, yet the composition of fish in their catches changed dramatically.\" Local Perceptions By comparing fish caught and sold to fish observed on the reef, the team determined that the shifting catches did in fact reflect shifting abundances of reef-dwelling fish. Notably, Naso, or unicornfish, which islanders ate multiple times per week, decreased, and algae-eating parrotfish increased, appearing in higher concentrations after the mass coral die-off. Understanding which fish were offered at markets was important to the study. Credit: Mark Strother Fishers prized both unicornfish and parrotfish before the ecological disturbances. But the local fishers didn't perceive the changes in their concentrations as significant. Surveys conducted by the team indicated that while residents of the island were aware of shifts, the disturbances did not prompt a change in fishing behavior and, puzzlingly for researchers, did not result in reported changes in the composition of fish caught, sold and eaten. \"Fish consumers can have very different perceptions than scientists and resource managers, even in a place like Moorea where locals are closely connected to reefs,\" said Dan Thornhill, a program director in the National Science Foundation's (NSF) Division of Ocean Sciences, which funded the study along with NSF's Dynamics of Coupled Natural and Human Systems program. The latter is part of NSF's Environmental Research and Education (ERE) portfolio. Noting the different perceptions \"is an important consideration going forward in the sustainable management of reefs and the fisheries they support,\" Thornhill said. Added study co-author and UCSB marine ecologist Sally Holbrook, \"Moorea's fishers view the environment as naturally variable, and changes in abundances of fish on the reef are normal occurrences for them.\" The researchers charted courses around the island to survey which fish were at roadside stands. Credit: Andrew Rassweiler Scientific Perspective The changes concerned the scientists. Seemingly small changes in population abundances could be portents of deeper ecological dysfunction, they said. \"We demonstrated that these shifts are ecologically important,\" Rassweiler said. \"This is part of a bigger project in which we're working with fishers to think about reef health and management. It's been enlightening because they have unique insights into the status of different species.\" San Diego State University anthropologist Matthew Lauer added, \"It's fascinating that marine scientists and Polynesian fishers, both of whom spend a huge amount of time on these reefs, have such radically different views about ecosystem change. \"Getting a handle on their views about marine health will help us learn more about these reefs, and contribute to more effective and collaborative resource management.\" The team worked to understand how fishing behavior changed in response to changes on the reef. Credit: Mark Strother ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The transformation of coral reefs has profound implications for millions of people. However, the interactive effects of changing reefs and fishing remain poorly resolved. We combine underwater surveys (271 000 fishes), catch data (18 000 fishes), and household surveys (351 households) to evaluate how reef fishes and fishers in Moorea, French Polynesia responded to a landscape-scale loss of coral caused by sequential disturbances (a crown-of-thorns sea star outbreak followed by a category 4 cyclone). Although local communities were aware of the disturbances, less than 20% of households reported altering what fishes they caught or ate. This contrasts with substantial changes in the taxonomic composition in the catch data that mirrored changes in fish communities observed on the reef. Our findings highlight that resource users and scientists may have very different interpretations of what constitutes ‘change’ in these highly dynamic social–ecological systems, with broad implications for successful co-management of coral reef fisheries. Access provided by MPDL Services gGmbH c/o Max Planck Digital Library Working on a manuscript? Avoid the common mistakes Introduction Coral reef ecosystems are under significant anthropogenic pressures from overfishing, pollution, sedimentation, ocean acidification, and rising seawater temperatures (Bellwood et al. 2004 ; Hughes et al. 2018 ), resulting in unprecedented levels of coral mortality (Hughes et al. 2017 ) and shifts from coral-dominated to macroalgae-dominated community states (Rogers and Miller 2006 ). Beyond biodiversity loss, degraded reefs present challenges for millions of coastal dwellers who rely on healthy reef ecosystems for food, income, and their personal and cultural identities. This has prompted research examining how local communities and resource users perceive, adapt to, and manage coral reefs in the Anthropocene (McClanahan and Cinner 2012 ; McMillen et al. 2014 ), including a focus on adaptive co-management, whereby management is implemented and adapted based on knowledge about feedbacks between resource users and shifting local ecosystems (Hughes et al. 2005 ). The Pacific Islands region represents an ideal context to investigate how local communities and changing coral reefs interact. Island peoples have shown the capacity to adapt, cope, and innovate in the face of social–ecological change, with positive and negative outcomes for coral reef health (Johannes 2002 ). In some Pacific Islands, such as Fiji, Vanuatu, and the Solomon Islands, marine resources have been effectively managed over long periods through periodic fishing ground closures, gear restrictions, and other socially enforced constraints on harvesting (Cinner et al. 2006 ). Elsewhere, local responses to changing conditions have had negative ecological outcomes, as with poison and dynamite fishing (McManus et al. 1997 ). The effectiveness of adaptive responses is shaped by local cultural values and power relations that inform decision-making and the range of possibilities available (Cinner et al. 2018 ). Effective adaptive management requires that resource users detect or anticipate shifts in the local environment and alter their activities accordingly. Some empirical studies have demonstrated that Pacific islanders can detect rapid shifts in benthic communities disrupted by tsunamis (Lauer and Matera 2016 ), in addition to more gradual changes such as expanding seagrass beds (Lauer and Aswani 2010 ). Numerous questions remain, however, about the sensitivity of local resource users to change, and in particular whether ecosystem disturbances identified by ecologists are similarly perceived by Pacific islanders. We addressed these issues for a small-scale reef fishery on the island of Moorea, French Polynesia. Social and ecological surveys explored how communities perceived and responded to changes in fishery resources associated with a crown-of-thorns sea star (COTS) outbreak followed by a destructive cyclone. In 2004, coral cover around Moorea was near the highest levels observed in the past half century (Trapon et al. 2011 ; Lamy et al. 2016 ), but an outbreak of corallivorous COTS that peaked in 2009, followed by Cyclone Oli in early 2010, reduced live coral cover by > 95% (Adam et al. 2011 ; Trapon et al. 2011 ; Adam et al. 2014 ; Lamy et al. 2015 ). Dead coral skeletons and cleared reef substrates provided substantial free space for growth of macroalgae, raising the possibility that a macroalgal phase shift could occur. However, benthic community changes were rapidly followed by changes in the fish assemblage, with roving herbivorous fishes such as parrotfishes doubling in density and tripling in total biomass (Han et al. 2016 ), thus preventing macroalgae from establishing. Moreover, in the years since the disturbances, coral cover has increased and even exceeds predisturbance levels in some areas (Holbrook et al. 2018 ). Despite intensive ecological study, it is not known if these changes in the fish assemblages have altered fishable resources, the activities of reef fishers, or how local people perceived the changes. Because spearfishing—a highly selective method—is common in Moorea, a shift in the abundances of fishable resources provides an opportunity to assess whether fishers alter what they catch as their resource environment changes. This study addressed four questions: (1) How did residents of Moorea perceive the shifts documented in ecological studies? (2) Do they report changing their fishing behavior or seafood consumption in response to the shift? (3) How did the changes in the fish assemblage affect the availability and taxonomic composition of fishable biomass? and (4) Is there evidence for changes in fishing behavior (such as taxonomic selectivity) over time? To answer these questions, we conducted 351 household surveys documenting fishers’ perceptions of the changes and their potential responses via alteration in fishing practices or fish consumption. We analyzed a time series of catch data (~ 18 000 identified and measured fishes) collected before and after the disturbances, spanning a 9-year time period, to determine changes in targeted fish species and sizes, including key groups of herbivores crucial to recovery and resilience of the coral state. Finally, we compared the catch data with extensive surveys that estimated abundances and biomass of fishes on the reef throughout the same time frame. Materials and Methods Ecological and social contexts Moorea (17°32′S, 149°50′W) is a volcanic ‘high’ island 60 km in perimeter with an offshore barrier reef that encloses a shallow lagoon (Fig. 1<|im_end|> <|im_start|>assistant Results of a new study looking at coral reef disturbances, fish abundance and coastal fishers' catches suggest that ecologists and community anglers may perceive environmental disruptions in very different ways. The apparent disconnect between data-driven scientists and experience-driven fishing communities has implications for the management and resilience of coral reefs and other sensitive marine ecosystems. Lead study author Andrew Rassweiler of Florida State University (FSU), who worked with collaborators at the University of California, Santa Barbara (UCSB) and San Diego State University to conduct fishing surveys and fish population assessments on the French Polynesian island of Moorea, said the research "shows that different groups have different perceptions of change and ecosystem health." The findings are published this week in the journal Ambio. Ecological Distress Coral reefs around the world experience pressure from human activities. As ecosystems react to declines in biodiversity, tropical coastal fishers—whose livelihoods often depend on coral reefs—become less economically and culturally secure. In Moorea, some parts of the island's lagoons support thriving coral communities, while other areas are giving way to overgrowth by seaweed. Scientists looked at fish abundance on the reef in comparison to fish species sold on the island. Credit: Sarah Lester An outbreak of coral-devouring crown-of-thorns sea stars in 2009 and a destructive cyclone in 2010 reduced live coral cover by some 95 percent in many locations. These events threw the ecosystem into disarray, scientists say. In addition to widespread coral losses, effects included abrupt changes in fish populations, with algae-eating, herbivorous fish swarming the area to graze on seaweed growing on the skeletons of dead coral. This influx of seaweed-eating fish wasn't necessarily a surprise, the researchers maintain. Studies at the National Science Foundation's (NSF) Moorea Coral Reef Long-Term Ecological Research (LTER) site on the island had identified the role of herbivorous fish in keeping seaweed forests in check. But Moorea's local fishing communities, where more than three quarters of households have a member who actively fishes the reef, knew less about how this rapid shift in fish abundance occurred. The marine biologists used sizing cards to determine the sizes of fish that were caught and sold. Credit: Terava Atger "Everyone around the island is fishing, but we know very little about how fishers decide where to fish and what fish to target," Rassweiler said. "This research was a first step in looking at how fishing behavior changed following a big change in the fish community itself." Russ Schmitt, a marine ecologist at UCSB and principal investigator of the NSF Moorea Coral Reef LTER site, added "It turned out that the fishers in Moorea barely noticed the massive ecological shift and reported they didn't change their fishing practices, yet the composition of fish in their catches changed dramatically." Local Perceptions By comparing fish caught and sold to fish observed on the reef, the team determined that the shifting catches did in fact reflect shifting abundances of reef-dwelling fish. Notably, Naso, or unicornfish, which islanders ate multiple times per week, decreased, and algae-eating parrotfish increased, appearing in higher concentrations after the mass coral die-off. Understanding which fish were offered at markets was important to the study. Credit: Mark Strother Fishers prized both unicornfish and parrotfish before the ecological disturbances. But the local fishers didn't perceive the changes in their concentrations as significant. Surveys conducted by the team indicated that while residents of the island were aware of shifts, the disturbances did not prompt a change in fishing behavior and, puzzlingly for researchers, did not result in reported changes in the composition of fish caught, sold and eaten. "Fish consumers can have very different perceptions than scientists and resource managers, even in a place like Moorea where locals are closely connected to reefs," said Dan Thornhill, a program director in the National Science Foundation's (NSF) Division of Ocean Sciences, which funded the study along with NSF's Dynamics of Coupled Natural and Human Systems program. The latter is part of NSF's Environmental Research and Education (ERE) portfolio. Noting the different perceptions "is an important consideration going forward in the sustainable management of reefs and the fisheries they support," Thornhill said. Added study co-author and UCSB marine ecologist Sally Holbrook, "Moorea's fishers view the environment as naturally variable, and changes in abundances of fish on the reef are normal occurrences for them." The researchers charted courses around the island to survey which fish were at roadside stands. Credit: Andrew Rassweiler Scientific Perspective The changes concerned the scientists. Seemingly small changes in population abundances could be portents of deeper ecological dysfunction, they said. "We demonstrated that these shifts are ecologically important," Rassweiler said. "This is part of a bigger project in which we're working with fishers to think about reef health and management. It's been enlightening because they have unique insights into the status of different species." San Diego State University anthropologist Matthew Lauer added, "It's fascinating that marine scientists and Polynesian fishers, both of whom spend a huge amount of time on these reefs, have such radically different views about ecosystem change. "Getting a handle on their views about marine health will help us learn more about these reefs, and contribute to more effective and collaborative resource management." The team worked to understand how fishing behavior changed in response to changes on the reef. Credit: Mark Strother <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 18475, 315, 53103, 92822, 706, 28254, 25127, 369, 11990, 315, 1274, 13, 4452, 11, 279, 21416, 6372, 315, 10223, 92822, 323, 20543, 7293, 31555, 20250, 13, 1226, 16343, 46474, 32313, 320, 15828, 220, 931, 95461, 705, 2339, 828, 320, 972, 220, 931, 95461, 705, 323, 14048, 32313, 320, 18113, 29939, 8, 311, 15806, 1268, 71145, 95461, 323, 7795, 388, 304, 20832, 64, 11, 8753, 3735, 84267, 689, 16846, 311, 264, 18921, 13230, 4814, 315, 53103, 9057, 555, 52100, 85160, 320, 64, 27631, 8838, 7716, 44129, 9581, 6917, 31188, 8272, 555, 264, 5699, 220, 19, 32343, 606, 570, 10541, 2254, 10977, 1051, 8010, 315, 279, 85160, 11, 2753, 1109, 220, 508, 4, 315, 29939, 5068, 60923, 1148, 95461, 814, 10791, 477, 30912, 13, 1115, 83379, 449, 12190, 4442, 304, 279, 3827, 48228, 18528, 304, 279, 2339, 828, 430, 70137, 4442, 304, 7795, 10977, 13468, 389, 279, 71145, 13, 5751, 14955, 11415, 430, 5211, 3932, 323, 14248, 1253, 617, 1633, 2204, 58689, 315, 1148, 42675, 3451, 3455, 529, 304, 1521, 7701, 8915, 3674, 4235, 762, 5848, 6067, 11, 449, 7353, 25127, 369, 6992, 1080, 55885, 315, 53103, 71145, 82596, 13, 9742, 3984, 555, 9599, 16931, 8471, 342, 38, 32198, 272, 20886, 7639, 9878, 377, 14434, 11896, 22938, 389, 264, 47913, 30, 35106, 279, 4279, 21294, 29438, 64916, 71145, 61951, 527, 1234, 5199, 41416, 29569, 40850, 505, 927, 69, 11218, 11, 25793, 11, 59132, 367, 11, 18435, 13935, 2461, 11, 323, 16448, 67329, 977, 20472, 320, 85238, 6798, 1880, 453, 13, 220, 1049, 19, 2652, 41411, 1880, 453, 13, 220, 679, 23, 7026, 13239, 304, 31069, 5990, 315, 53103, 29528, 320, 95871, 288, 1880, 453, 13, 220, 679, 22, 883, 323, 29735, 505, 53103, 90723, 311, 18563, 24823, 6043, 90723, 4029, 5415, 320, 49, 540, 388, 323, 17472, 220, 1049, 21, 7609, 31886, 73119, 4814, 11, 91978, 92822, 3118, 11774, 369, 11990, 315, 35335, 44935, 388, 889, 17631, 389, 9498, 71145, 61951, 369, 3691, 11, 8070, 11, 323, 872, 4443, 323, 13042, 40521, 13, 1115, 706, 29746, 3495, 38936, 1268, 2254, 10977, 323, 5211, 3932, 45493, 11, 10737, 311, 11, 323, 10299, 53103, 92822, 304, 279, 70384, 78782, 320, 26353, 5176, 276, 22826, 323, 356, 4481, 220, 679, 17, 2652, 4584, 12608, 268, 1880, 453, 13, 220, 679, 19, 7026, 2737, 264, 5357, 389, 48232, 1080, 55885, 11, 49001, 6373, 374, 11798, 323, 30464, 3196, 389, 6677, 922, 11302, 82, 1990, 5211, 3932, 323, 32931, 2254, 61951, 320, 95871, 288, 1880, 453, 13, 220, 1049, 20, 7609, 578, 16867, 23028, 5654, 11105, 459, 10728, 2317, 311, 19874, 1268, 2254, 10977, 323, 10223, 53103, 92822, 16681, 13, 10951, 32538, 617, 6982, 279, 8824, 311, 10737, 11, 37586, 11, 323, 92064, 304, 279, 3663, 315, 3674, 4235, 762, 5848, 2349, 11, 449, 6928, 323, 8389, 20124, 369, 53103, 71145, 2890, 320, 41, 2319, 42256, 220, 1049, 17, 7609, 763, 1063, 16867, 23028, 11, 1778, 439, 86196, 11, 13000, 84, 36409, 11, 323, 279, 50899, 23028, 11, 29691, 5070, 617, 1027, 13750, 9152, 927, 1317, 18852, 1555, 39445, 20543, 5015, 61000, 11, 14787, 17294, 11, 323, 1023, 40418, 45421, 17413, 389, 66747, 320, 34, 4481, 1880, 453, 13, 220, 1049, 21, 7609, 19334, 2940, 11, 2254, 14847, 311, 10223, 4787, 617, 1047, 8389, 50953, 20124, 11, 439, 449, 21109, 323, 18003, 635, 20543, 320, 26353, 1692, 355, 1880, 453, 13, 220, 2550, 22, 7609, 578, 27375, 315, 48232, 14847, 374, 27367, 555, 2254, 13042, 2819, 323, 2410, 4398, 430, 6179, 5597, 28846, 323, 279, 2134, 315, 24525, 2561, 320, 34, 4481, 1880, 453, 13, 220, 679, 23, 7609, 48023, 48232, 6373, 7612, 430, 5211, 3932, 11388, 477, 48248, 29735, 304, 279, 2254, 4676, 323, 11857, 872, 7640, 28178, 13, 4427, 46763, 7978, 617, 21091, 430, 16867, 13218, 388, 649, 11388, 11295, 29735, 304, 293, 21341, 292, 10977, 69627, 555, 10814, 359, 309, 285, 320, 43, 28196, 323, 99408, 64, 220, 679, 21, 7026, 304, 5369, 311, 810, 53722, 4442, 1778, 439, 24050, 513, 69405, 395, 28036, 320, 43, 28196, 323, 1666, 86, 5676, 220, 679, 15, 7609, 86915, 4860, 7293, 11, 4869, 11, 922, 279, 27541, 315, 2254, 5211, 3932, 311, 2349, 11, 323, 304, 4040, 3508, 26031, 85160, 11054, 555, 12208, 22012, 527, 30293, 26617, 555, 16867, 13218, 388, 13, 1226, 20669, 1521, 4819, 369, 264, 2678, 13230, 71145, 7795, 727, 389, 279, 13218, 315, 20832, 64, 11, 8753, 3735, 84267, 689, 13, 9983, 323, 50953, 32313, 36131, 1268, 10977, 26617, 323, 16846, 311, 4442, 304, 7795, 727, 5070, 5938, 449, 264, 27631, 8838, 7716, 44129, 9581, 6917, 320, 34, 47313, 8, 31188, 8272, 555, 264, 40652, 32343, 606, 13, 763, 220, 1049, 19, 11, 53103, 3504, 2212, 20832, 64, 574, 3221, 279, 8592, 5990, 13468, 304, 279, 3347, 4376, 9478, 320, 1305, 10969, 1880, 453, 13, 220, 679, 16, 2652, 445, 27322, 1880, 453, 13, 220, 679, 21, 7026, 719, 459, 31188, 315, 1867, 543, 344, 20857, 356, 47313, 430, 78292, 304, 220, 1049, 24, 11, 8272, 555, 72545, 606, 507, 747, 304, 4216, 220, 679, 15, 11, 11293, 3974, 53103, 3504, 555, 871, 220, 2721, 4, 320, 38675, 1880, 453, 13, 220, 679, 16, 2652, 1183, 10969, 1880, 453, 13, 220, 679, 16, 2652, 15387, 1880, 453, 13, 220, 679, 19, 2652, 445, 27322, 1880, 453, 13, 220, 679, 20, 7609, 15371, 53103, 75407, 323, 23803, 71145, 16146, 988, 3984, 12190, 1949, 3634, 369, 6650, 315, 18563, 24823, 6043, 11, 19054, 279, 13336, 430, 264, 18563, 278, 16876, 10474, 6541, 1436, 12446, 13, 4452, 11, 293, 21341, 292, 4029, 4442, 1051, 19019, 8272, 555, 4442, 304, 279, 7795, 439, 28111, 425, 11, 449, 938, 4504, 39999, 344, 20857, 95461, 1778, 439, 1370, 4744, 18668, 288, 60115, 304, 17915, 323, 2463, 12127, 304, 2860, 58758, 320, 74225, 1880, 453, 13, 220, 679, 21, 7026, 8617, 27252, 18563, 24823, 6043, 505, 31692, 13, 23674, 11, 304, 279, 1667, 2533, 279, 85160, 11, 53103, 3504, 706, 7319, 323, 1524, 36375, 4255, 380, 9225, 685, 5990, 304, 1063, 5789, 320, 79762, 43366, 1880, 453, 13, 220, 679, 23, 7609, 18185, 37295, 50953, 4007, 11, 433, 374, 539, 3967, 422, 1521, 4442, 304, 279, 7795, 439, 28111, 1154, 617, 29852, 7795, 481, 5070, 11, 279, 7640, 315, 71145, 7795, 388, 11, 477, 1268, 2254, 1274, 26617, 279, 4442, 13, 9393, 41963, 69, 11218, 29096, 7701, 44010, 1749, 55434, 4279, 304, 20832, 64, 11, 264, 6541, 304, 279, 23325, 3095, 315, 7795, 481, 5070, 5825, 459, 6776, 311, 8720, 3508, 7795, 388, 11857, 1148, 814, 2339, 439, 872, 5211, 4676, 4442, 13, 1115, 4007, 20669, 3116, 4860, 25, 320, 16, 8, 2650, 1550, 11062, 315, 20832, 64, 45493, 279, 29735, 27470, 304, 50953, 7978, 30, 320, 17, 8, 3234, 814, 1934, 10223, 872, 20543, 7865, 477, 53405, 15652, 304, 2077, 311, 279, 6541, 30, 320, 18, 8, 2650, 1550, 279, 4442, 304, 279, 7795, 439, 28111, 425, 7958, 279, 18539, 323, 3827, 48228, 18528, 315, 7795, 481, 58758, 30, 323, 320, 19, 8, 2209, 1070, 6029, 369, 4442, 304, 20543, 7865, 320, 21470, 439, 3827, 48228, 3373, 1968, 8, 927, 892, 30, 2057, 4320, 1521, 4860, 11, 584, 13375, 220, 18113, 14048, 32313, 68071, 7795, 388, 529, 51866, 315, 279, 4442, 323, 872, 4754, 14847, 4669, 73681, 304, 20543, 12659, 477, 7795, 15652, 13, 1226, 30239, 264, 892, 4101, 315, 2339, 828, 31857, 220, 972, 220, 931, 11054, 323, 17303, 95461, 8, 14890, 1603, 323, 1306, 279, 85160, 11, 56886, 264, 220, 24, 4771, 892, 4261, 11, 311, 8417, 4442, 304, 17550, 7795, 9606, 323, 12562, 11, 2737, 1401, 5315, 315, 39999, 344, 4692, 16996, 311, 13654, 323, 56062, 315, 279, 53103, 1614, 13, 17830, 11, 584, 7863, 279, 2339, 828, 449, 16781, 32313, 430, 13240, 23325, 3095, 323, 58758, 315, 95461, 389, 279, 71145, 6957, 279, 1890, 892, 4124, 13, 32009, 323, 19331, 37211, 5848, 323, 3674, 38697, 20832, 64, 320, 1114, 11877, 843, 39615, 50, 11, 220, 10161, 11877, 1135, 39615, 54, 8, 374, 264, 67164, 3451, 12156, 529, 13218, 220, 1399, 13437, 304, 47442, 449, 459, 39500, 22881, 71145, 430, 3289, 50441, 264, 26682, 326, 68513, 320, 30035, 13, 220, 16, 128257, 198, 128256, 78191, 198, 10001, 315, 264, 502, 4007, 3411, 520, 53103, 71145, 85160, 11, 7795, 37492, 323, 35335, 7795, 388, 6, 38934, 4284, 430, 12208, 22012, 323, 4029, 56404, 388, 1253, 45493, 12434, 98057, 304, 1633, 2204, 5627, 13, 578, 10186, 30069, 1990, 828, 32505, 14248, 323, 3217, 32505, 20543, 10977, 706, 25127, 369, 279, 6373, 323, 56062, 315, 53103, 92822, 323, 1023, 16614, 29691, 61951, 13, 30982, 4007, 3229, 13929, 432, 395, 906, 5888, 315, 9784, 3314, 3907, 320, 8653, 52, 705, 889, 6575, 449, 79119, 520, 279, 3907, 315, 7188, 11, 16376, 32207, 320, 5576, 17094, 8, 323, 5960, 18842, 3314, 3907, 311, 6929, 20543, 32313, 323, 7795, 7187, 41300, 389, 279, 8753, 3735, 1910, 30321, 13218, 315, 20832, 64, 11, 1071, 279, 3495, 330, 60556, 430, 2204, 5315, 617, 2204, 51866, 315, 2349, 323, 26031, 2890, 1210, 578, 14955, 527, 4756, 420, 2046, 304, 279, 8486, 20423, 822, 13, 37211, 5848, 28704, 676, 64916, 92822, 2212, 279, 1917, 3217, 7410, 505, 3823, 7640, 13, 1666, 61951, 14085, 311, 58054, 304, 73119, 11, 35148, 35335, 7795, 388, 2345, 86243, 64751, 82, 3629, 6904, 389, 53103, 92822, 2345, 17106, 638, 2753, 47379, 323, 66963, 9966, 13, 763, 20832, 64, 11, 1063, 5596, 315, 279, 13218, 596, 326, 6438, 2439, 1862, 53414, 53103, 10977, 11, 1418, 1023, 5789, 527, 7231, 1648, 311, 927, 74189, 555, 67329, 12320, 13, 57116, 7111, 520, 7795, 37492, 389, 279, 71145, 304, 12593, 311, 7795, 9606, 6216, 389, 279, 13218, 13, 16666, 25, 21077, 83758, 1556, 31188, 315, 53103, 26842, 414, 287, 27631, 8838, 7716, 44129, 9581, 9958, 304, 220, 1049, 24, 323, 264, 40652, 32343, 606, 304, 220, 679, 15, 11293, 3974, 53103, 3504, 555, 1063, 220, 2721, 3346, 304, 1690, 10687, 13, 4314, 4455, 22982, 279, 26031, 1139, 834, 1686, 11, 14248, 2019, 13, 763, 5369, 311, 24716, 53103, 18151, 11, 6372, 5343, 44077, 4442, 304, 7795, 22673, 11, 449, 68951, 5773, 1113, 11, 39999, 344, 20857, 7795, 2064, 34002, 279, 3158, 311, 28699, 3059, 389, 67329, 12320, 7982, 389, 279, 75407, 315, 5710, 53103, 13, 1115, 53952, 315, 67329, 12320, 5773, 1113, 7795, 5828, 956, 14647, 264, 13051, 11, 279, 12074, 10519, 13, 19241, 520, 279, 5165, 10170, 5114, 596, 320, 2507, 37, 8, 20832, 64, 64916, 77036, 5843, 9469, 4289, 37211, 5848, 8483, 320, 43, 4292, 8, 2816, 389, 279, 13218, 1047, 11054, 279, 3560, 315, 39999, 344, 20857, 7795, 304, 10494, 67329, 12320, 36658, 304, 1817, 13, 2030, 20832, 64, 596, 2254, 20543, 10977, 11, 1405, 810, 1109, 2380, 32573, 315, 29939, 617, 264, 4562, 889, 22815, 95461, 279, 71145, 11, 7020, 2753, 922, 1268, 420, 11295, 6541, 304, 7795, 37492, 10222, 13, 578, 29691, 6160, 22012, 1511, 64101, 7563, 311, 8417, 279, 12562, 315, 7795, 430, 1051, 10791, 323, 6216, 13, 16666, 25, 10335, 2979, 2468, 1414, 330, 34124, 2212, 279, 13218, 374, 20543, 11, 719, 584, 1440, 1633, 2697, 922, 1268, 7795, 388, 10491, 1405, 311, 7795, 323, 1148, 7795, 311, 2218, 1359, 432, 395, 906, 5888, 1071, 13, 330, 2028, 3495, 574, 264, 1176, 3094, 304, 3411, 520, 1268, 20543, 7865, 5614, 2768, 264, 2466, 2349, 304, 279, 7795, 4029, 5196, 1210, 4608, 5124, 24621, 11, 264, 29691, 12208, 16549, 520, 80346, 33, 323, 12717, 49581, 315, 279, 80628, 20832, 64, 64916, 77036, 445, 4292, 2816, 11, 3779, 330, 2181, 6656, 704, 430, 279, 7795, 388, 304, 20832, 64, 20025, 14000, 279, 11191, 50953, 6541, 323, 5068, 814, 3287, 956, 2349, 872, 20543, 12659, 11, 3686, 279, 18528, 315, 7795, 304, 872, 38934, 5614, 29057, 1210, 8949, 3700, 36028, 3296, 27393, 7795, 10791, 323, 6216, 311, 7795, 13468, 389, 279, 71145, 11, 279, 2128, 11075, 430, 279, 32931, 38934, 1550, 304, 2144, 8881, 32931, 23325, 3095, 315, 71145, 1773, 86, 6427, 7795, 13, 2876, 2915, 11, 39322, 78, 11, 477, 82930, 18668, 11, 902, 13218, 388, 30912, 5361, 3115, 824, 2046, 11, 25983, 11, 323, 68951, 5773, 1113, 1370, 4744, 18668, 7319, 11, 26449, 304, 5190, 32466, 1306, 279, 3148, 53103, 2815, 12744, 13, 46551, 902, 7795, 1051, 9076, 520, 11987, 574, 3062, 311, 279, 4007, 13, 16666, 25, 4488, 800, 299, 700, 17019, 388, 87630, 2225, 82930, 18668, 323, 1370, 4744, 18668, 1603, 279, 50953, 85160, 13, 2030, 279, 2254, 7795, 388, 3287, 956, 45493, 279, 4442, 304, 872, 32466, 439, 5199, 13, 8242, 50369, 13375, 555, 279, 2128, 16717, 430, 1418, 11062, 315, 279, 13218, 1051, 8010, 315, 29735, 11, 279, 85160, 1550, 539, 10137, 264, 2349, 304, 20543, 7865, 323, 11, 32854, 2785, 398, 369, 12074, 11, 1550, 539, 1121, 304, 5068, 4442, 304, 279, 18528, 315, 7795, 10791, 11, 6216, 323, 35661, 13, 330, 65641, 13723, 649, 617, 1633, 2204, 51866, 1109, 14248, 323, 5211, 20258, 11, 1524, 304, 264, 2035, 1093, 20832, 64, 1405, 25958, 527, 15499, 8599, 311, 92822, 1359, 1071, 11824, 78024, 28607, 11, 264, 2068, 7690, 304, 279, 5165, 10170, 5114, 596, 320, 2507, 37, 8, 14829, 315, 22302, 23199, 11, 902, 24853, 279, 4007, 3235, 449, 80628, 596, 53711, 315, 18733, 50185, 18955, 323, 11344, 15264, 2068, 13, 578, 15629, 374, 961, 315, 80628, 596, 25027, 8483, 323, 11930, 320, 43272, 8, 20136, 13, 2876, 287, 279, 2204, 51866, 330, 285, 459, 3062, 18361, 2133, 4741, 304, 279, 22556, 6373, 315, 92822, 323, 279, 82596, 814, 1862, 1359, 78024, 28607, 1071, 13, 18152, 4007, 1080, 43802, 323, 80346, 33, 29691, 12208, 16549, 53391, 16071, 43366, 11, 330, 26694, 61148, 596, 7795, 388, 1684, 279, 4676, 439, 18182, 3977, 11, 323, 4442, 304, 23325, 3095, 315, 7795, 389, 279, 71145, 527, 4725, 57115, 369, 1124, 1210, 578, 12074, 9676, 291, 14307, 2212, 279, 13218, 311, 10795, 902, 7795, 1051, 520, 80743, 13656, 13, 16666, 25, 13929, 432, 395, 906, 5888, 38130, 70288, 578, 4442, 11920, 279, 14248, 13, 1369, 336, 11559, 2678, 4442, 304, 7187, 23325, 3095, 1436, 387, 2700, 812, 315, 19662, 50953, 32403, 11, 814, 1071, 13, 330, 1687, 21091, 430, 1521, 29735, 527, 12208, 30450, 3062, 1359, 432, 395, 906, 5888, 1071, 13, 330, 2028, 374, 961, 315, 264, 11493, 2447, 304, 902, 584, 2351, 3318, 449, 7795, 388, 311, 1781, 922, 71145, 2890, 323, 6373, 13, 1102, 596, 1027, 41316, 6147, 1606, 814, 617, 5016, 26793, 1139, 279, 2704, 315, 2204, 9606, 1210, 5960, 18842, 3314, 3907, 41416, 16549, 19475, 445, 28196, 3779, 11, 330, 2181, 596, 27387, 430, 29691, 14248, 323, 3735, 1910, 30321, 7795, 388, 11, 2225, 315, 8884, 8493, 264, 6908, 3392, 315, 892, 389, 1521, 92822, 11, 617, 1778, 61127, 2204, 6325, 922, 26031, 2349, 13, 330, 29755, 264, 3790, 389, 872, 6325, 922, 29691, 2890, 690, 1520, 603, 4048, 810, 922, 1521, 92822, 11, 323, 17210, 311, 810, 7524, 323, 40806, 5211, 6373, 1210, 578, 2128, 6575, 311, 3619, 1268, 20543, 7865, 5614, 304, 2077, 311, 4442, 389, 279, 71145, 13, 16666, 25, 4488, 800, 299, 700, 220, 128257, 198 ]

2,522

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The persistence of leukemic stem cells (LSCs) represents a problem in the therapy of chronic myeloid leukemia (CML). Hence, it is of utmost importance to explore the underlying mechanisms to develop new therapeutic approaches to cure CML. Using the genetically engineered ScltTA/TRE-BCR::ABL1 mouse model for chronic phase CML, we previously demonstrated that the loss of the docking protein GAB2 counteracts the infiltration of mast cells (MCs) in the bone marrow (BM) of BCR::ABL1 positive mice. Here, we show for the first time that BCR::ABL1 drives the cytokine independent expansion of BM derived MCs and sensitizes them for FcεRI triggered degranulation. Importantly, we demonstrate that genetic mast cell deficiency conferred by the Cpa3 Cre allele prevents BCR::ABL1 induced splenomegaly and impairs the production of pro-inflammatory cytokines. Furthermore, we show in CML patients that splenomegaly is associated with high BM MC counts and that upregulation of pro-inflammatory cytokines in patient serum samples correlates with tryptase levels. Finally, MC-associated transcripts were elevated in human CML BM samples. Thus, our study identifies MCs as essential contributors to disease progression and suggests considering them as an additional target in CML therapy. Mast cells play a key role in the pro-inflammatory tumor microenvironment of the bone marrow. Shown is a cartoon summarizing our results from the mouse model. BCR::ABL1 transformed MCs, as part of the malignant clone, are essential for the elevation of pro-inflammatory cytokines, known to be important in disease initiation and progression. Introduction Chronic myeloid leukemia (CML) represents about 20% of all adult leukemia cases and is caused by a chromosomal translocation between chromosomes 9 and 22, leading to the expression of the fusion kinase BCR::ABL1 [ 1 ]. BCR::ABL1 organizes a multimeric signaling network with various components such as the docking protein GAB2 (GRB-associated-binding protein 2). GAB2 serves as an assembly platform downstream of cytokine and growth factor receptors [ 2 ]. By binding via the adaptor protein, GRB2, GAB2 amplifies the signaling into SHP2/RAS/ERK, PI3K/AKT, and STAT5 pathways, leading to survival, proliferation, and migration [ 2 , 3 , 4 ]. Due to its role in these oncogenic pathways, GAB2 is implicated in both solid tumors and leukemia [ 5 ]. Using GAB2 deficient mice [ 6 ], we previously showed that GAB2 serves as an important effector of the oncogenic FLT3-ITD receptor tyrosine kinase in acute myeloid leukemia (AML) [ 7 , 8 ] and of BCR::ABL1 in CML [ 9 , 10 , 11 , 12 ]. We demonstrated that GAB2 confers resistance to clinically approved BCR::ABL1 inhibitors, including the third-generation inhibitor ponatinib [ 9 , 12 ]. We also showed that GAB2 is increasingly expressed in myeloid cells from CML patients with TKI-refractory disease [ 12 ] or blast crisis [ 13 ]. Using GAB2 knock-out mice [ 6 ], we analyzed the in vivo role of GAB2 in a chronic-phase CML mouse model in which a tetracycline (tet) regulated BCR::ABL1 transgene is expressed in hematopoietic stem cells in their native microenvironment [ 10 , 14 ]. We demonstrated that GAB2 deficiency impairs disease development in a steady-state in vivo setting [ 10 ]. Surprisingly, we also detected increased numbers of mast cells (MCs) in the bone marrow (BM) and kidneys from BCR::ABL1 expressing mice. As reported previously for this mouse model [ 14 ], we observed uni- or bilateral hydronephrosis in BCR::ABL1 positive mice driven by urinary obstruction due to myeloid infiltration within the renal pelvis and ureters. Interestingly, we identified MCs as the predominant infiltrating cell type in the kidney, suggesting their contribution to hydronephrosis. Strikingly, Gab2 −/− mice showed neither MC infiltration in the BM or kidney nor hydronephrosis at all. This might be explained by a synergistic effect of GAB2 as a common downstream signaling effector of BCR::ABL1 and cytokine receptor signaling pathways [ 2 ]. In line with this, GAB2 has been shown to be critical for MC development and KIT signaling [ 15 ]. MCs play a role in different diseases such as allergy, as contributors to a pro-inflammatory tumor microenvironment, and as carriers of oncogenic mutations they cause mastocytosis or MC leukemia [ 16 , 17 ]. Very little, however, is known about MCs in the context of CML. It was shown that MCs are increased in the BM of CML patients compared to healthy individuals and that the TKI imatinib depletes normal and neoplastic MCs in these patients [ 18 ]. However, as imatinib targets both BCR::ABL1 and KIT, it remains unclear whether BCR::ABL1 positive MCs still rely on KIT and whether the effect of this TKI reflects the inhibition of one or both targets. In addition, Askmyr et al. observed an aberrant CD25 + phenotype reminiscient of systemic mastocytosis in xenografts of BCR::ABL1 transduced human cord blood cells [ 19 ]. Interesting to note, basophils, which share many features and a bipotent progenitor with MCs [ 20 ], are often elevated in CML patients and used as a prognostic marker [ 21 ]. These mostly descriptive studies on MCs in BCR::ABL1 mediated transformation and our recent data from Gab2 −/− mice provided the rationale for further analysis of MCs in CML. Therefore, we aimed to analyze the role of MCs in CML in more detail. In particular, we were interested whether this MC accumulation could be driven by BCR::ABL1 itself or whether these cells reacted as bystanders to an inflammatory reaction induced by leukemic infiltrates. Using the ScltTA/TRE-BCR::ABL1 CML mouse model, we now show for the first time that BCR::ABL1 drives the cytokine independent expansion of BM derived mast cells (BMMCs) and sensitizes them for degranulation, IL-6 and TNF release. Importantly, by crossing in the MC-deficient Cpa3Cre mouse line, we discover a crucial role of MCs in CML development. We demonstrate that MC deficiency prevents BCR::ABL1 induced splenomegaly and elevation of pro-inflammatory cytokines. Furthermore, we provide supportive data from CML patients showing that splenomegaly is associated with high BM MC counts and that upregulation of pro-inflammatory cytokines in patient serum samples correlates with tryptase levels. In addition, we detected", "role": "user" }, { "content": "Chronic myeloid leukemia (CML) is a type of blood cancer that arises from malignant changes in blood-forming cells of the bone marrow. It mainly occurs in older individuals and represents about 20% of all adult leukemia cases. A research team led by Dr. Sebastian Halbach, Melanie Langhammer and Dr. Julia Schöpf from the Institute of Molecular Medicine and Cell Research at the University of Freiburg has now demonstrated for the first time that mast cells play a crucial role in the development of CML. Mast cells could therefore serve as an additional therapeutic target in the clinic. \"It was really impressive to see that mice lacking mast cells no longer developed severe CML,\" says study leader Halbach. The results were recently published in the journal Leukemia. Significantly elevated cytokine levels Mast cells are cells of the immune system that play a decisive role in the defense against pathogens, but also in allergies. In this context, mast cells release inflammation inducing messenger molecules, so-called proinflammatory cytokines, which are crucial for the immune response. However, proinflammatory cytokines are also frequently found in the microenvironment of tumors and are suspected of decisively promoting cancer development. Using a mouse model for CML, the scientists were able to demonstrate for the first time that cytokines in CML could indeed originate from mast cells. First, the researchers found an unusually high number of mast cells in the bone marrow of mice showing leukemia symptoms. In subsequent experiments, they were able to demonstrate that the oncogene Bcr-Abl, as the cancer-causing protein in CML, had taken control of these mast cells. This resulted in a significantly increased release of proinflammatory cytokines. Consequently, mice lacking mast cells due to their genetic predisposition did not show an increase in proinflammatory cytokines. Moreover, these animals did not develop splenomegaly, a pathological enlargement of the spleen frequently observed in leukemias. Clinical data support findings For the study, the team collaborated with Prof. Dr. Tilman Brummer, Professor for Signal Transduction and Medical Cell Research at the University of Freiburg, Dr. Khalid Shoumariyeh and Prof. Dr. Heiko Becker from the University Medical Center Freiburg, and Dr. Mirle Schemionek-Reinders and Prof. Dr. Michael Huber from the University Medical Center Aachen. With the help of the partners, the findings from the animal model could finally be supported by clinical data from CML patients: On the one hand, it was shown that patients with severe splenomegaly often have an increased number of mast cells in their bone marrow. On the other hand, patients with increased concentrations of tryptase, a lead enzyme of mast cells, also had increased levels of proinflammatory cytokines in their blood. \"These results could be the basis for new therapeutic approaches,\" Halbach explains. The discovery of the Bcr-Abl oncogene as the trigger for CML has made it possible to develop so-called tyrosine kinase inhibitors (TKIs), which revolutionized the therapy. However, it is often not possible to eliminate all malignant cells with these drugs, especially the leukemia stem cells in the bone marrow, which is why lifelong treatment is necessary. In addition, resistances to the TKIs can develop during therapy, leading to relapse. Moreover, a lifelong use of TKIs is associated with a high burden of side effects for patients. \"It is therefore of great importance to develop new and more effective therapies,\" says Halbach. And the study also offers suggestions for further research into many types of cancer beyond CML. \"I am convinced that mast cells also play an important role in other cancers, since proinflammatory cytokines are often found upregulated here as well.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The persistence of leukemic stem cells (LSCs) represents a problem in the therapy of chronic myeloid leukemia (CML). Hence, it is of utmost importance to explore the underlying mechanisms to develop new therapeutic approaches to cure CML. Using the genetically engineered ScltTA/TRE-BCR::ABL1 mouse model for chronic phase CML, we previously demonstrated that the loss of the docking protein GAB2 counteracts the infiltration of mast cells (MCs) in the bone marrow (BM) of BCR::ABL1 positive mice. Here, we show for the first time that BCR::ABL1 drives the cytokine independent expansion of BM derived MCs and sensitizes them for FcεRI triggered degranulation. Importantly, we demonstrate that genetic mast cell deficiency conferred by the Cpa3 Cre allele prevents BCR::ABL1 induced splenomegaly and impairs the production of pro-inflammatory cytokines. Furthermore, we show in CML patients that splenomegaly is associated with high BM MC counts and that upregulation of pro-inflammatory cytokines in patient serum samples correlates with tryptase levels. Finally, MC-associated transcripts were elevated in human CML BM samples. Thus, our study identifies MCs as essential contributors to disease progression and suggests considering them as an additional target in CML therapy. Mast cells play a key role in the pro-inflammatory tumor microenvironment of the bone marrow. Shown is a cartoon summarizing our results from the mouse model. BCR::ABL1 transformed MCs, as part of the malignant clone, are essential for the elevation of pro-inflammatory cytokines, known to be important in disease initiation and progression. Introduction Chronic myeloid leukemia (CML) represents about 20% of all adult leukemia cases and is caused by a chromosomal translocation between chromosomes 9 and 22, leading to the expression of the fusion kinase BCR::ABL1 [ 1 ]. BCR::ABL1 organizes a multimeric signaling network with various components such as the docking protein GAB2 (GRB-associated-binding protein 2). GAB2 serves as an assembly platform downstream of cytokine and growth factor receptors [ 2 ]. By binding via the adaptor protein, GRB2, GAB2 amplifies the signaling into SHP2/RAS/ERK, PI3K/AKT, and STAT5 pathways, leading to survival, proliferation, and migration [ 2 , 3 , 4 ]. Due to its role in these oncogenic pathways, GAB2 is implicated in both solid tumors and leukemia [ 5 ]. Using GAB2 deficient mice [ 6 ], we previously showed that GAB2 serves as an important effector of the oncogenic FLT3-ITD receptor tyrosine kinase in acute myeloid leukemia (AML) [ 7 , 8 ] and of BCR::ABL1 in CML [ 9 , 10 , 11 , 12 ]. We demonstrated that GAB2 confers resistance to clinically approved BCR::ABL1 inhibitors, including the third-generation inhibitor ponatinib [ 9 , 12 ]. We also showed that GAB2 is increasingly expressed in myeloid cells from CML patients with TKI-refractory disease [ 12 ] or blast crisis [ 13 ]. Using GAB2 knock-out mice [ 6 ], we analyzed the in vivo role of GAB2 in a chronic-phase CML mouse model in which a tetracycline (tet) regulated BCR::ABL1 transgene is expressed in hematopoietic stem cells in their native microenvironment [ 10 , 14 ]. We demonstrated that GAB2 deficiency impairs disease development in a steady-state in vivo setting [ 10 ]. Surprisingly, we also detected increased numbers of mast cells (MCs) in the bone marrow (BM) and kidneys from BCR::ABL1 expressing mice. As reported previously for this mouse model [ 14 ], we observed uni- or bilateral hydronephrosis in BCR::ABL1 positive mice driven by urinary obstruction due to myeloid infiltration within the renal pelvis and ureters. Interestingly, we identified MCs as the predominant infiltrating cell type in the kidney, suggesting their contribution to hydronephrosis. Strikingly, Gab2 −/− mice showed neither MC infiltration in the BM or kidney nor hydronephrosis at all. This might be explained by a synergistic effect of GAB2 as a common downstream signaling effector of BCR::ABL1 and cytokine receptor signaling pathways [ 2 ]. In line with this, GAB2 has been shown to be critical for MC development and KIT signaling [ 15 ]. MCs play a role in different diseases such as allergy, as contributors to a pro-inflammatory tumor microenvironment, and as carriers of oncogenic mutations they cause mastocytosis or MC leukemia [ 16 , 17 ]. Very little, however, is known about MCs in the context of CML. It was shown that MCs are increased in the BM of CML patients compared to healthy individuals and that the TKI imatinib depletes normal and neoplastic MCs in these patients [ 18 ]. However, as imatinib targets both BCR::ABL1 and KIT, it remains unclear whether BCR::ABL1 positive MCs still rely on KIT and whether the effect of this TKI reflects the inhibition of one or both targets. In addition, Askmyr et al. observed an aberrant CD25 + phenotype reminiscient of systemic mastocytosis in xenografts of BCR::ABL1 transduced human cord blood cells [ 19 ]. Interesting to note, basophils, which share many features and a bipotent progenitor with MCs [ 20 ], are often elevated in CML patients and used as a prognostic marker [ 21 ]. These mostly descriptive studies on MCs in BCR::ABL1 mediated transformation and our recent data from Gab2 −/− mice provided the rationale for further analysis of MCs in CML. Therefore, we aimed to analyze the role of MCs in CML in more detail. In particular, we were interested whether this MC accumulation could be driven by BCR::ABL1 itself or whether these cells reacted as bystanders to an inflammatory reaction induced by leukemic infiltrates. Using the ScltTA/TRE-BCR::ABL1 CML mouse model, we now show for the first time that BCR::ABL1 drives the cytokine independent expansion of BM derived mast cells (BMMCs) and sensitizes them for degranulation, IL-6 and TNF release. Importantly, by crossing in the MC-deficient Cpa3Cre mouse line, we discover a crucial role of MCs in CML development. We demonstrate that MC deficiency prevents BCR::ABL1 induced splenomegaly and elevation of pro-inflammatory cytokines. Furthermore, we provide supportive data from CML patients showing that splenomegaly is associated with high BM MC counts and that upregulation of pro-inflammatory cytokines in patient serum samples correlates with tryptase levels. In addition, we detected<|im_end|> <|im_start|>assistant Chronic myeloid leukemia (CML) is a type of blood cancer that arises from malignant changes in blood-forming cells of the bone marrow. It mainly occurs in older individuals and represents about 20% of all adult leukemia cases. A research team led by Dr. Sebastian Halbach, Melanie Langhammer and Dr. Julia Schöpf from the Institute of Molecular Medicine and Cell Research at the University of Freiburg has now demonstrated for the first time that mast cells play a crucial role in the development of CML. Mast cells could therefore serve as an additional therapeutic target in the clinic. "It was really impressive to see that mice lacking mast cells no longer developed severe CML," says study leader Halbach. The results were recently published in the journal Leukemia. Significantly elevated cytokine levels Mast cells are cells of the immune system that play a decisive role in the defense against pathogens, but also in allergies. In this context, mast cells release inflammation inducing messenger molecules, so-called proinflammatory cytokines, which are crucial for the immune response. However, proinflammatory cytokines are also frequently found in the microenvironment of tumors and are suspected of decisively promoting cancer development. Using a mouse model for CML, the scientists were able to demonstrate for the first time that cytokines in CML could indeed originate from mast cells. First, the researchers found an unusually high number of mast cells in the bone marrow of mice showing leukemia symptoms. In subsequent experiments, they were able to demonstrate that the oncogene Bcr-Abl, as the cancer-causing protein in CML, had taken control of these mast cells. This resulted in a significantly increased release of proinflammatory cytokines. Consequently, mice lacking mast cells due to their genetic predisposition did not show an increase in proinflammatory cytokines. Moreover, these animals did not develop splenomegaly, a pathological enlargement of the spleen frequently observed in leukemias. Clinical data support findings For the study, the team collaborated with Prof. Dr. Tilman Brummer, Professor for Signal Transduction and Medical Cell Research at the University of Freiburg, Dr. Khalid Shoumariyeh and Prof. Dr. Heiko Becker from the University Medical Center Freiburg, and Dr. Mirle Schemionek-Reinders and Prof. Dr. Michael Huber from the University Medical Center Aachen. With the help of the partners, the findings from the animal model could finally be supported by clinical data from CML patients: On the one hand, it was shown that patients with severe splenomegaly often have an increased number of mast cells in their bone marrow. On the other hand, patients with increased concentrations of tryptase, a lead enzyme of mast cells, also had increased levels of proinflammatory cytokines in their blood. "These results could be the basis for new therapeutic approaches," Halbach explains. The discovery of the Bcr-Abl oncogene as the trigger for CML has made it possible to develop so-called tyrosine kinase inhibitors (TKIs), which revolutionized the therapy. However, it is often not possible to eliminate all malignant cells with these drugs, especially the leukemia stem cells in the bone marrow, which is why lifelong treatment is necessary. In addition, resistances to the TKIs can develop during therapy, leading to relapse. Moreover, a lifelong use of TKIs is associated with a high burden of side effects for patients. "It is therefore of great importance to develop new and more effective therapies," says Halbach. And the study also offers suggestions for further research into many types of cancer beyond CML. "I am convinced that mast cells also play an important role in other cancers, since proinflammatory cytokines are often found upregulated here as well." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 42056, 315, 57381, 8274, 19646, 7917, 320, 43, 3624, 82, 8, 11105, 264, 3575, 304, 279, 15419, 315, 21249, 856, 301, 590, 96306, 320, 34, 2735, 570, 32140, 11, 433, 374, 315, 54711, 12939, 311, 13488, 279, 16940, 24717, 311, 2274, 502, 37471, 20414, 311, 27208, 356, 2735, 13, 12362, 279, 52033, 46036, 328, 566, 83, 15559, 17146, 793, 12, 5002, 49, 487, 95035, 16, 8814, 1646, 369, 21249, 10474, 356, 2735, 11, 584, 8767, 21091, 430, 279, 4814, 315, 279, 89310, 13128, 480, 1905, 17, 5663, 11613, 279, 98835, 315, 19218, 7917, 320, 11865, 82, 8, 304, 279, 17685, 83748, 320, 30042, 8, 315, 426, 9150, 487, 95035, 16, 6928, 24548, 13, 5810, 11, 584, 1501, 369, 279, 1176, 892, 430, 426, 9150, 487, 95035, 16, 20722, 279, 83185, 483, 9678, 14800, 315, 20387, 14592, 21539, 82, 323, 74633, 4861, 1124, 369, 435, 66, 31243, 4403, 22900, 409, 68163, 2987, 13, 13516, 18007, 11, 584, 20461, 430, 19465, 19218, 2849, 48294, 91670, 555, 279, 356, 6733, 18, 7948, 70510, 29034, 426, 9150, 487, 95035, 16, 36572, 12786, 268, 638, 70, 5893, 323, 3242, 4825, 279, 5788, 315, 463, 67595, 83185, 1572, 13, 24296, 11, 584, 1501, 304, 356, 2735, 6978, 430, 12786, 268, 638, 70, 5893, 374, 5938, 449, 1579, 20387, 21539, 14921, 323, 430, 709, 1610, 2987, 315, 463, 67595, 83185, 1572, 304, 8893, 41529, 10688, 97303, 449, 1456, 418, 521, 5990, 13, 17830, 11, 21539, 75968, 61412, 1051, 32389, 304, 3823, 356, 2735, 20387, 10688, 13, 14636, 11, 1057, 4007, 36611, 21539, 82, 439, 7718, 20965, 311, 8624, 33824, 323, 13533, 13126, 1124, 439, 459, 5217, 2218, 304, 356, 2735, 15419, 13, 37582, 7917, 1514, 264, 1401, 3560, 304, 279, 463, 67595, 36254, 8162, 24175, 315, 279, 17685, 83748, 13, 1443, 785, 374, 264, 31449, 29385, 4954, 1057, 3135, 505, 279, 8814, 1646, 13, 426, 9150, 487, 95035, 16, 24411, 21539, 82, 11, 439, 961, 315, 279, 94329, 15057, 11, 527, 7718, 369, 279, 27255, 315, 463, 67595, 83185, 1572, 11, 3967, 311, 387, 3062, 304, 8624, 61568, 323, 33824, 13, 29438, 73782, 856, 301, 590, 96306, 320, 34, 2735, 8, 11105, 922, 220, 508, 4, 315, 682, 6822, 96306, 5157, 323, 374, 9057, 555, 264, 22083, 96108, 1380, 2588, 1990, 83181, 220, 24, 323, 220, 1313, 11, 6522, 311, 279, 7645, 315, 279, 37608, 82160, 426, 9150, 487, 95035, 16, 510, 220, 16, 21087, 426, 9150, 487, 95035, 16, 2942, 4861, 264, 2814, 3212, 292, 43080, 4009, 449, 5370, 6956, 1778, 439, 279, 89310, 13128, 480, 1905, 17, 320, 8796, 33, 75968, 65500, 13128, 220, 17, 570, 480, 1905, 17, 17482, 439, 459, 14956, 5452, 52452, 315, 83185, 483, 323, 6650, 8331, 44540, 510, 220, 17, 21087, 3296, 11212, 4669, 279, 93041, 13128, 11, 15116, 33, 17, 11, 480, 1905, 17, 23201, 9803, 279, 43080, 1139, 6570, 47, 17, 19945, 1950, 14, 643, 42, 11, 23396, 18, 42, 10576, 34639, 11, 323, 26030, 20, 44014, 11, 6522, 311, 20237, 11, 53840, 11, 323, 12172, 510, 220, 17, 1174, 220, 18, 1174, 220, 19, 21087, 24586, 311, 1202, 3560, 304, 1521, 78970, 29569, 44014, 11, 480, 1905, 17, 374, 69702, 304, 2225, 6573, 56071, 323, 96306, 510, 220, 20, 21087, 12362, 480, 1905, 17, 87544, 24548, 510, 220, 21, 10881, 584, 8767, 8710, 430, 480, 1905, 17, 17482, 439, 459, 3062, 3369, 1279, 315, 279, 78970, 29569, 97161, 18, 12, 964, 35, 35268, 13892, 3714, 483, 82160, 304, 30883, 856, 301, 590, 96306, 320, 32202, 8, 510, 220, 22, 1174, 220, 23, 2331, 323, 315, 426, 9150, 487, 95035, 16, 304, 356, 2735, 510, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 21087, 1226, 21091, 430, 480, 1905, 17, 2389, 388, 13957, 311, 70432, 12054, 426, 9150, 487, 95035, 16, 68642, 11, 2737, 279, 4948, 43927, 70785, 35023, 15111, 581, 510, 220, 24, 1174, 220, 717, 21087, 1226, 1101, 8710, 430, 480, 1905, 17, 374, 15098, 13605, 304, 856, 301, 590, 7917, 505, 356, 2735, 6978, 449, 45399, 40, 44107, 81, 2992, 8624, 510, 220, 717, 2331, 477, 21327, 11501, 510, 220, 1032, 21087, 12362, 480, 1905, 17, 14459, 9994, 24548, 510, 220, 21, 10881, 584, 30239, 279, 304, 41294, 3560, 315, 480, 1905, 17, 304, 264, 21249, 82710, 356, 2735, 8814, 1646, 304, 902, 264, 259, 17820, 2826, 89034, 320, 73542, 8, 35319, 426, 9150, 487, 95035, 16, 1380, 43471, 374, 13605, 304, 96849, 56809, 3978, 292, 19646, 7917, 304, 872, 10068, 8162, 24175, 510, 220, 605, 1174, 220, 975, 21087, 1226, 21091, 430, 480, 1905, 17, 48294, 3242, 4825, 8624, 4500, 304, 264, 24981, 21395, 304, 41294, 6376, 510, 220, 605, 21087, 8242, 49264, 11, 584, 1101, 16914, 7319, 5219, 315, 19218, 7917, 320, 11865, 82, 8, 304, 279, 17685, 83748, 320, 30042, 8, 323, 81960, 505, 426, 9150, 487, 95035, 16, 37810, 24548, 13, 1666, 5068, 8767, 369, 420, 8814, 1646, 510, 220, 975, 10881, 584, 13468, 48986, 12, 477, 52303, 45705, 606, 764, 63412, 304, 426, 9150, 487, 95035, 16, 6928, 24548, 16625, 555, 72735, 61051, 4245, 311, 856, 301, 590, 98835, 2949, 279, 63915, 12077, 2749, 323, 53560, 5153, 13, 58603, 11, 584, 11054, 21539, 82, 439, 279, 96531, 43364, 1113, 2849, 955, 304, 279, 39042, 11, 23377, 872, 19035, 311, 45705, 606, 764, 63412, 13, 4610, 1609, 11559, 11, 24664, 17, 25173, 14, 34363, 24548, 8710, 14188, 21539, 98835, 304, 279, 20387, 477, 39042, 6463, 45705, 606, 764, 63412, 520, 682, 13, 1115, 2643, 387, 11497, 555, 264, 80526, 4633, 2515, 315, 480, 1905, 17, 439, 264, 4279, 52452, 43080, 3369, 1279, 315, 426, 9150, 487, 95035, 16, 323, 83185, 483, 35268, 43080, 44014, 510, 220, 17, 21087, 763, 1584, 449, 420, 11, 480, 1905, 17, 706, 1027, 6982, 311, 387, 9200, 369, 21539, 4500, 323, 735, 964, 43080, 510, 220, 868, 21087, 21539, 82, 1514, 264, 3560, 304, 2204, 19338, 1778, 439, 60754, 11, 439, 20965, 311, 264, 463, 67595, 36254, 8162, 24175, 11, 323, 439, 35991, 315, 78970, 29569, 34684, 814, 5353, 19218, 511, 16820, 10934, 477, 21539, 96306, 510, 220, 845, 1174, 220, 1114, 21087, 15668, 2697, 11, 4869, 11, 374, 3967, 922, 21539, 82, 304, 279, 2317, 315, 356, 2735, 13, 1102, 574, 6982, 430, 21539, 82, 527, 7319, 304, 279, 20387, 315, 356, 2735, 6978, 7863, 311, 9498, 7931, 323, 430, 279, 45399, 40, 737, 15111, 581, 409, 698, 2392, 4725, 323, 841, 454, 52279, 21539, 82, 304, 1521, 6978, 510, 220, 972, 21087, 4452, 11, 439, 737, 15111, 581, 11811, 2225, 426, 9150, 487, 95035, 16, 323, 735, 964, 11, 433, 8625, 25420, 3508, 426, 9150, 487, 95035, 16, 6928, 21539, 82, 2103, 17631, 389, 735, 964, 323, 3508, 279, 2515, 315, 420, 45399, 40, 27053, 279, 61478, 315, 832, 477, 2225, 11811, 13, 763, 5369, 11, 21069, 2465, 81, 1880, 453, 13, 13468, 459, 82102, 519, 11325, 914, 489, 82423, 43650, 3510, 1188, 315, 46417, 19218, 511, 16820, 10934, 304, 53265, 540, 3017, 82, 315, 426, 9150, 487, 95035, 16, 1380, 54478, 3823, 23125, 6680, 7917, 510, 220, 777, 21087, 71770, 311, 5296, 11, 3122, 5237, 8839, 11, 902, 4430, 1690, 4519, 323, 264, 29978, 64632, 84360, 1960, 449, 21539, 82, 510, 220, 508, 10881, 527, 3629, 32389, 304, 356, 2735, 6978, 323, 1511, 439, 264, 63903, 537, 292, 11381, 510, 220, 1691, 21087, 4314, 10213, 53944, 7978, 389, 21539, 82, 304, 426, 9150, 487, 95035, 16, 78926, 18475, 323, 1057, 3293, 828, 505, 24664, 17, 25173, 14, 34363, 24548, 3984, 279, 57916, 369, 4726, 6492, 315, 21539, 82, 304, 356, 2735, 13, 15636, 11, 584, 20034, 311, 24564, 279, 3560, 315, 21539, 82, 304, 356, 2735, 304, 810, 7872, 13, 763, 4040, 11, 584, 1051, 8173, 3508, 420, 21539, 46835, 1436, 387, 16625, 555, 426, 9150, 487, 95035, 16, 5196, 477, 3508, 1521, 7917, 55841, 439, 83483, 388, 311, 459, 47288, 13010, 36572, 555, 57381, 8274, 43364, 988, 13, 12362, 279, 328, 566, 83, 15559, 17146, 793, 12, 5002, 49, 487, 95035, 16, 356, 2735, 8814, 1646, 11, 584, 1457, 1501, 369, 279, 1176, 892, 430, 426, 9150, 487, 95035, 16, 20722, 279, 83185, 483, 9678, 14800, 315, 20387, 14592, 19218, 7917, 320, 33, 8195, 34645, 8, 323, 74633, 4861, 1124, 369, 409, 68163, 2987, 11, 11598, 12, 21, 323, 32023, 37, 4984, 13, 13516, 18007, 11, 555, 27736, 304, 279, 21539, 29899, 5499, 356, 6733, 18, 10987, 8814, 1584, 11, 584, 7142, 264, 16996, 3560, 315, 21539, 82, 304, 356, 2735, 4500, 13, 1226, 20461, 430, 21539, 48294, 29034, 426, 9150, 487, 95035, 16, 36572, 12786, 268, 638, 70, 5893, 323, 27255, 315, 463, 67595, 83185, 1572, 13, 24296, 11, 584, 3493, 33445, 828, 505, 356, 2735, 6978, 9204, 430, 12786, 268, 638, 70, 5893, 374, 5938, 449, 1579, 20387, 21539, 14921, 323, 430, 709, 1610, 2987, 315, 463, 67595, 83185, 1572, 304, 8893, 41529, 10688, 97303, 449, 1456, 418, 521, 5990, 13, 763, 5369, 11, 584, 16914, 128257, 198, 128256, 78191, 198, 1163, 8535, 856, 301, 590, 96306, 320, 34, 2735, 8, 374, 264, 955, 315, 6680, 9572, 430, 48282, 505, 94329, 4442, 304, 6680, 8627, 287, 7917, 315, 279, 17685, 83748, 13, 1102, 14918, 13980, 304, 9191, 7931, 323, 11105, 922, 220, 508, 4, 315, 682, 6822, 96306, 5157, 13, 362, 3495, 2128, 6197, 555, 2999, 13, 44609, 20442, 35638, 11, 85350, 23272, 46434, 323, 2999, 13, 40394, 5124, 3029, 16276, 505, 279, 10181, 315, 60825, 19152, 323, 14299, 8483, 520, 279, 3907, 315, 7730, 581, 5673, 706, 1457, 21091, 369, 279, 1176, 892, 430, 19218, 7917, 1514, 264, 16996, 3560, 304, 279, 4500, 315, 356, 2735, 13, 37582, 7917, 1436, 9093, 8854, 439, 459, 5217, 37471, 2218, 304, 279, 28913, 13, 330, 2181, 574, 2216, 16358, 311, 1518, 430, 24548, 32161, 19218, 7917, 912, 5129, 8040, 15748, 356, 2735, 1359, 2795, 4007, 7808, 20442, 35638, 13, 578, 3135, 1051, 6051, 4756, 304, 279, 8486, 2009, 3178, 22689, 13, 7220, 98864, 32389, 83185, 483, 5990, 37582, 7917, 527, 7917, 315, 279, 22852, 1887, 430, 1514, 264, 51391, 3560, 304, 279, 9232, 2403, 78284, 11, 719, 1101, 304, 58742, 13, 763, 420, 2317, 11, 19218, 7917, 4984, 37140, 96811, 50596, 35715, 11, 779, 19434, 463, 258, 55097, 83185, 1572, 11, 902, 527, 16996, 369, 279, 22852, 2077, 13, 4452, 11, 463, 258, 55097, 83185, 1572, 527, 1101, 14134, 1766, 304, 279, 8162, 24175, 315, 56071, 323, 527, 24740, 315, 34122, 3210, 22923, 9572, 4500, 13, 12362, 264, 8814, 1646, 369, 356, 2735, 11, 279, 14248, 1051, 3025, 311, 20461, 369, 279, 1176, 892, 430, 83185, 1572, 304, 356, 2735, 1436, 13118, 82316, 505, 19218, 7917, 13, 5629, 11, 279, 12074, 1766, 459, 57899, 1579, 1396, 315, 19218, 7917, 304, 279, 17685, 83748, 315, 24548, 9204, 96306, 13803, 13, 763, 17876, 21896, 11, 814, 1051, 3025, 311, 20461, 430, 279, 78970, 34224, 426, 5192, 6830, 2067, 11, 439, 279, 9572, 51877, 985, 13128, 304, 356, 2735, 11, 1047, 4529, 2585, 315, 1521, 19218, 7917, 13, 1115, 19543, 304, 264, 12207, 7319, 4984, 315, 463, 258, 55097, 83185, 1572, 13, 53123, 11, 24548, 32161, 19218, 7917, 4245, 311, 872, 19465, 80632, 3571, 1550, 539, 1501, 459, 5376, 304, 463, 258, 55097, 83185, 1572, 13, 23674, 11, 1521, 10099, 1550, 539, 2274, 12786, 268, 638, 70, 5893, 11, 264, 89961, 66507, 315, 279, 87450, 268, 14134, 13468, 304, 57381, 336, 3557, 13, 33135, 828, 1862, 14955, 1789, 279, 4007, 11, 279, 2128, 78174, 449, 8626, 13, 2999, 13, 58769, 1543, 3320, 63373, 11, 17054, 369, 28329, 4149, 23985, 323, 13235, 14299, 8483, 520, 279, 3907, 315, 7730, 581, 5673, 11, 2999, 13, 52709, 307, 1443, 283, 76, 2850, 88, 2701, 323, 8626, 13, 2999, 13, 1283, 24551, 78484, 505, 279, 3907, 13235, 5955, 7730, 581, 5673, 11, 323, 2999, 13, 14603, 273, 328, 2464, 290, 1247, 69060, 32551, 323, 8626, 13, 2999, 13, 8096, 27636, 261, 505, 279, 3907, 13235, 5955, 362, 46799, 13, 3161, 279, 1520, 315, 279, 8717, 11, 279, 14955, 505, 279, 10065, 1646, 1436, 5616, 387, 7396, 555, 14830, 828, 505, 356, 2735, 6978, 25, 1952, 279, 832, 1450, 11, 433, 574, 6982, 430, 6978, 449, 15748, 12786, 268, 638, 70, 5893, 3629, 617, 459, 7319, 1396, 315, 19218, 7917, 304, 872, 17685, 83748, 13, 1952, 279, 1023, 1450, 11, 6978, 449, 7319, 32466, 315, 1456, 418, 521, 11, 264, 3063, 49242, 315, 19218, 7917, 11, 1101, 1047, 7319, 5990, 315, 463, 258, 55097, 83185, 1572, 304, 872, 6680, 13, 330, 9673, 3135, 1436, 387, 279, 8197, 369, 502, 37471, 20414, 1359, 20442, 35638, 15100, 13, 578, 18841, 315, 279, 426, 5192, 6830, 2067, 78970, 34224, 439, 279, 8346, 369, 356, 2735, 706, 1903, 433, 3284, 311, 2274, 779, 19434, 13892, 3714, 483, 82160, 68642, 320, 16155, 3957, 705, 902, 14110, 1534, 279, 15419, 13, 4452, 11, 433, 374, 3629, 539, 3284, 311, 22472, 682, 94329, 7917, 449, 1521, 11217, 11, 5423, 279, 96306, 19646, 7917, 304, 279, 17685, 83748, 11, 902, 374, 3249, 51263, 6514, 374, 5995, 13, 763, 5369, 11, 22884, 3095, 311, 279, 45399, 3957, 649, 2274, 2391, 15419, 11, 6522, 311, 1375, 7629, 13, 23674, 11, 264, 51263, 1005, 315, 45399, 3957, 374, 5938, 449, 264, 1579, 23104, 315, 3185, 6372, 369, 6978, 13, 330, 2181, 374, 9093, 315, 2294, 12939, 311, 2274, 502, 323, 810, 7524, 52312, 1359, 2795, 20442, 35638, 13, 1628, 279, 4007, 1101, 6209, 18726, 369, 4726, 3495, 1139, 1690, 4595, 315, 9572, 7953, 356, 2735, 13, 330, 40, 1097, 22954, 430, 19218, 7917, 1101, 1514, 459, 3062, 3560, 304, 1023, 51423, 11, 2533, 463, 258, 55097, 83185, 1572, 527, 3629, 1766, 709, 81722, 1618, 439, 1664, 1210, 220, 128257, 198 ]

2,297

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Manipulation of solid-state spin coherence is an important paradigm for quantum information processing. Current systems either operate at very low temperatures or are difficult to scale up. Developing low-cost, scalable materials whose spins can be coherently manipulated at room temperature is thus highly attractive for a sustainable future of quantum information science. Here we report ambient-condition all-optical initialization, manipulation and readout of hole spins in an ensemble of solution-grown CsPbBr 3 perovskite quantum dots with a single hole in each dot. The hole spins are initialized by sub-picosecond electron scavenging following circularly polarized femtosecond-pulse excitation. A transverse magnetic field induces spin precession, and a second off-resonance femtosecond-pulse coherently rotates hole spins via strong light–matter interaction. These operations accomplish near-complete quantum-state control, with a coherent rotation angle close to the π radian, of hole spins at room temperature. Main Coherent control of spins in solid-state systems holds great promise for quantum information science 1 . Compared with bulk semiconductor materials, localized systems (such as epitaxial-grown quantum dots (QDs)) were considered to be more adaptable to quantum information science because of the possibility of addressing and manipulating single spins 2 , 3 , 4 . Other examples of localized systems include defect centres or dopants in solids 5 . Traditionally, radiofrequency electrical or magnetic stimuli are implemented for spin quantum-state control 6 , 7 , but the time limits of such operations are on the order of nanoseconds at best. Femtosecond or picosecond optical pulses have recently enabled ultrafast spin manipulation at exceptionally high speeds 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 . In spite of the success of various manipulation methods, there are still many shortcomings associated with current spin-host materials from the viewpoint of practical applications. Epitaxial QDs are fabricated using expensive, high-temperature and high-vacuum apparatus. Another fundamental issue is that interlevel scattering and coupling to phonon baths can strongly damp the spin coherence. Consequently, spin manipulation of these QDs is typically accomplished at cryogenic temperatures of a few kelvin 9 , 15 . By contrast, the defect or dopant spins in solids are highly isolated and can be manipulated at room temperature 16 . However, scaled-up production of these point defects might eventually become a challenge. For the scalable and sustainable implementation of spin-based quantum information science, it is desirable to develop low-cost materials whose spins can be coherently manipulated under ambient conditions. The colloidal counterparts of QDs (also called nanocrystals) can be synthesized in large quantities in solution at low cost, yet with high precision in terms of size and shape control, and are particularly suitable for self-assembly or device integration 17 . However, spin manipulation for prototypical CdSe-based colloidal QDs has not been realized at room temperature 10 . We turn our focus to recently developed lead halide perovskite colloidal QDs 18 . Their spin–orbit coupling and electronic structure 19 have proved to be ideal for efficient spin injection by optical means 20 , 21 , 22 , 23 , 24 , 25 , and their strong light–matter interaction should also facilitate spin manipulation based on an optical Stark effect (OSE) 26 , 27 , 28 , 29 . The challenge of spin manipulation in lead halide perovskite QDs, however, is their rapid spin relaxation at room temperature (a few picoseconds) 24 , 25 , probably limited by enhanced electron–hole exchange in these confined systems 30 . In this Article, we combine interfacial charge-transfer chemistry of lead halide perovskite QDs and femtosecond laser pulses to initialize, manipulate and read out hole spins at room temperature. We functionalize the surfaces of CsPbBr 3 QDs with anthraquinone (AQ) molecules. Following the preparation of a spin-polarized exciton in a QD using a circularly polarized photon, the AQ can extract the electron on a sub-picosecond timescale, thus quenching the spin relaxation induced by electron–hole exchange. This results in long-lived hole spin precession about an applied transverse magnetic field up to hundreds of picoseconds, during which a second off-resonance laser pulse coherently rotates the hole spin around a longitudinal axis through the OSE. Taken together, the precession and rotation accomplish successful quantum-state control of hole spins at room temperature. Sample characterization and experimental set-up Figure 1 illustrates the sample characteristics, optical set-up and principle of our experiment. All measurements were performed at room temperature. CsPbBr 3 QDs of controllable sizes were synthesized using a hot-injection method 24 ; details can be found in the Methods. Figure 1a shows the absorption spectra of two QD samples (QD1 and QD2) dispersed in hexane. Their transmission electron microscope (TEM) images in Supplementary Fig. 1 reveal monodisperse cube-shaped dots with average edge lengths of ~4.2 and 4.6 nm for QD1 and QD2, respectively. The uniform quantum confinement results in a series of exciton peaks identifiable at room temperature, with the lowest peaks at 470 and 481 nm for QD1 and QD2, respectively (Fig. 1a ). Confinement-induced energy quantization in these QDs should help to suppress phonon-induced interlevel scattering and sustain spin coherence compared with bulk samples, although their large single-dot linewidth (~50–100 meV; refs. 31 , 32 ) compared with phonon energies suggests that intralevel scattering still poses an issue at room temperature. A carboxylated derivative of AQ, which is a well-known electron acceptor 33 , 34 , was anchored onto the QD surface through the carboxyl group ( Methods ). The enhanced absorption of QD1–AQ and QD2–AQ compared with bare QD1 and QD2 in the ultraviolet can be attributed to the AQ molecules (Supplementary Fig. 2 ). On the basis of absorption spectra and extinction coefficients, we estimate that there are more than 200 AQ molecules on each QD. Fig. 1: System design and experimental set-up. a , Absorption spectra of CsPbBr 3 QD1 and QD2. The spectra of the pump and the tipping pulses (shaded pulses) are included for comparison. The arrows indicate the centre wavelengths of the two lowest exciton peaks for QD1 and QD2. b , Band-edge optical selection rules in CsPbBr 3", "role": "user" }, { "content": "A research group led by Prof. Wu Kaifeng from the Dalian Institute of Chemical Physics (DICP), Chinese Academy of Sciences recently reported the successful initialization, coherent quantum-state control, and readout of spins at room temperature using solution-grown quantum dots, which represents an important advance in quantum information science. The study was published in Nature Nanotechnology on Dec 19th. Quantum information science is concerned with the manipulation of the quantum version of information bits (called qubits). When people talk about materials for quantum information processing, they usually think of those manufactured using the most cutting-edge technologies and operating at very cold temperatures (below a few Kelvin), not the \"warm and messy\" materials synthesized in solution by chemists. Recent years have witnessed the discovery of isolated defects in solid-state materials (such as NV centers) that have made possible room-temperature spin-qubit manipulation, but scaled-up production of these \"point defects\" will eventually become a challenge. Colloidal quantum dots (QDs), which are tiny semiconductor nanoparticles made in solution, could be a game changer. They can be synthesized in large quantities in solution at low cost, yet with high finesse in size and shape control. Further, they are usually strongly quantum-confined, thus their carriers well isolated from the phonon bath, which could enable long-lived spin coherence at room temperature. But room-temperature coherent manipulation of spins in colloidal QDs has never been reported, in that a QD system whose spins can be simultaneously initialized, rotated, and readout at room-temperature remains to be invented. Here the authors show that solution-grown CsPbBr3 perovskite QDs can actually accomplish this intimidating goal. Polarized hole spins are obtained by sub-picosecond electron scavenging, to surface-anchored molecular acceptors, following a circularly-polarized femtosecond pulse excitation. A transverse magnetic field induces coherent Larmor precession of the hole spins. A second off-resonance femtosecond pulse coherently rotates the spins through the optical Stark effect, which is enabled by the exceptionally strong light-matter interaction of the perovskite QDs. These results represent full quantum-state control of single-hole spins at room temperature, holding great promise for a scalable and sustainable future of spin-based quantum information processing \"Our success here is enabled by a very rare combination of knowledge in materials, chemistry and physics,\" said Prof. Wu. \"We fabricated strongly- and uniformly-confined CsPbBr3 QDs as the unique system for the study, and identified appropriate surface-ligand molecules to rapidly extract the electrons via charge-transfer chemistry for hole-spin initialization at room temperature. Meanwhile, we were able to utilize strong light-matter interaction of these QDs to perform coherent spin manipulation.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Manipulation of solid-state spin coherence is an important paradigm for quantum information processing. Current systems either operate at very low temperatures or are difficult to scale up. Developing low-cost, scalable materials whose spins can be coherently manipulated at room temperature is thus highly attractive for a sustainable future of quantum information science. Here we report ambient-condition all-optical initialization, manipulation and readout of hole spins in an ensemble of solution-grown CsPbBr 3 perovskite quantum dots with a single hole in each dot. The hole spins are initialized by sub-picosecond electron scavenging following circularly polarized femtosecond-pulse excitation. A transverse magnetic field induces spin precession, and a second off-resonance femtosecond-pulse coherently rotates hole spins via strong light–matter interaction. These operations accomplish near-complete quantum-state control, with a coherent rotation angle close to the π radian, of hole spins at room temperature. Main Coherent control of spins in solid-state systems holds great promise for quantum information science 1 . Compared with bulk semiconductor materials, localized systems (such as epitaxial-grown quantum dots (QDs)) were considered to be more adaptable to quantum information science because of the possibility of addressing and manipulating single spins 2 , 3 , 4 . Other examples of localized systems include defect centres or dopants in solids 5 . Traditionally, radiofrequency electrical or magnetic stimuli are implemented for spin quantum-state control 6 , 7 , but the time limits of such operations are on the order of nanoseconds at best. Femtosecond or picosecond optical pulses have recently enabled ultrafast spin manipulation at exceptionally high speeds 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 . In spite of the success of various manipulation methods, there are still many shortcomings associated with current spin-host materials from the viewpoint of practical applications. Epitaxial QDs are fabricated using expensive, high-temperature and high-vacuum apparatus. Another fundamental issue is that interlevel scattering and coupling to phonon baths can strongly damp the spin coherence. Consequently, spin manipulation of these QDs is typically accomplished at cryogenic temperatures of a few kelvin 9 , 15 . By contrast, the defect or dopant spins in solids are highly isolated and can be manipulated at room temperature 16 . However, scaled-up production of these point defects might eventually become a challenge. For the scalable and sustainable implementation of spin-based quantum information science, it is desirable to develop low-cost materials whose spins can be coherently manipulated under ambient conditions. The colloidal counterparts of QDs (also called nanocrystals) can be synthesized in large quantities in solution at low cost, yet with high precision in terms of size and shape control, and are particularly suitable for self-assembly or device integration 17 . However, spin manipulation for prototypical CdSe-based colloidal QDs has not been realized at room temperature 10 . We turn our focus to recently developed lead halide perovskite colloidal QDs 18 . Their spin–orbit coupling and electronic structure 19 have proved to be ideal for efficient spin injection by optical means 20 , 21 , 22 , 23 , 24 , 25 , and their strong light–matter interaction should also facilitate spin manipulation based on an optical Stark effect (OSE) 26 , 27 , 28 , 29 . The challenge of spin manipulation in lead halide perovskite QDs, however, is their rapid spin relaxation at room temperature (a few picoseconds) 24 , 25 , probably limited by enhanced electron–hole exchange in these confined systems 30 . In this Article, we combine interfacial charge-transfer chemistry of lead halide perovskite QDs and femtosecond laser pulses to initialize, manipulate and read out hole spins at room temperature. We functionalize the surfaces of CsPbBr 3 QDs with anthraquinone (AQ) molecules. Following the preparation of a spin-polarized exciton in a QD using a circularly polarized photon, the AQ can extract the electron on a sub-picosecond timescale, thus quenching the spin relaxation induced by electron–hole exchange. This results in long-lived hole spin precession about an applied transverse magnetic field up to hundreds of picoseconds, during which a second off-resonance laser pulse coherently rotates the hole spin around a longitudinal axis through the OSE. Taken together, the precession and rotation accomplish successful quantum-state control of hole spins at room temperature. Sample characterization and experimental set-up Figure 1 illustrates the sample characteristics, optical set-up and principle of our experiment. All measurements were performed at room temperature. CsPbBr 3 QDs of controllable sizes were synthesized using a hot-injection method 24 ; details can be found in the Methods. Figure 1a shows the absorption spectra of two QD samples (QD1 and QD2) dispersed in hexane. Their transmission electron microscope (TEM) images in Supplementary Fig. 1 reveal monodisperse cube-shaped dots with average edge lengths of ~4.2 and 4.6 nm for QD1 and QD2, respectively. The uniform quantum confinement results in a series of exciton peaks identifiable at room temperature, with the lowest peaks at 470 and 481 nm for QD1 and QD2, respectively (Fig. 1a ). Confinement-induced energy quantization in these QDs should help to suppress phonon-induced interlevel scattering and sustain spin coherence compared with bulk samples, although their large single-dot linewidth (~50–100 meV; refs. 31 , 32 ) compared with phonon energies suggests that intralevel scattering still poses an issue at room temperature. A carboxylated derivative of AQ, which is a well-known electron acceptor 33 , 34 , was anchored onto the QD surface through the carboxyl group ( Methods ). The enhanced absorption of QD1–AQ and QD2–AQ compared with bare QD1 and QD2 in the ultraviolet can be attributed to the AQ molecules (Supplementary Fig. 2 ). On the basis of absorption spectra and extinction coefficients, we estimate that there are more than 200 AQ molecules on each QD. Fig. 1: System design and experimental set-up. a , Absorption spectra of CsPbBr 3 QD1 and QD2. The spectra of the pump and the tipping pulses (shaded pulses) are included for comparison. The arrows indicate the centre wavelengths of the two lowest exciton peaks for QD1 and QD2. b , Band-edge optical selection rules in CsPbBr 3<|im_end|> <|im_start|>assistant A research group led by Prof. Wu Kaifeng from the Dalian Institute of Chemical Physics (DICP), Chinese Academy of Sciences recently reported the successful initialization, coherent quantum-state control, and readout of spins at room temperature using solution-grown quantum dots, which represents an important advance in quantum information science. The study was published in Nature Nanotechnology on Dec 19th. Quantum information science is concerned with the manipulation of the quantum version of information bits (called qubits). When people talk about materials for quantum information processing, they usually think of those manufactured using the most cutting-edge technologies and operating at very cold temperatures (below a few Kelvin), not the "warm and messy" materials synthesized in solution by chemists. Recent years have witnessed the discovery of isolated defects in solid-state materials (such as NV centers) that have made possible room-temperature spin-qubit manipulation, but scaled-up production of these "point defects" will eventually become a challenge. Colloidal quantum dots (QDs), which are tiny semiconductor nanoparticles made in solution, could be a game changer. They can be synthesized in large quantities in solution at low cost, yet with high finesse in size and shape control. Further, they are usually strongly quantum-confined, thus their carriers well isolated from the phonon bath, which could enable long-lived spin coherence at room temperature. But room-temperature coherent manipulation of spins in colloidal QDs has never been reported, in that a QD system whose spins can be simultaneously initialized, rotated, and readout at room-temperature remains to be invented. Here the authors show that solution-grown CsPbBr3 perovskite QDs can actually accomplish this intimidating goal. Polarized hole spins are obtained by sub-picosecond electron scavenging, to surface-anchored molecular acceptors, following a circularly-polarized femtosecond pulse excitation. A transverse magnetic field induces coherent Larmor precession of the hole spins. A second off-resonance femtosecond pulse coherently rotates the spins through the optical Stark effect, which is enabled by the exceptionally strong light-matter interaction of the perovskite QDs. These results represent full quantum-state control of single-hole spins at room temperature, holding great promise for a scalable and sustainable future of spin-based quantum information processing "Our success here is enabled by a very rare combination of knowledge in materials, chemistry and physics," said Prof. Wu. "We fabricated strongly- and uniformly-confined CsPbBr3 QDs as the unique system for the study, and identified appropriate surface-ligand molecules to rapidly extract the electrons via charge-transfer chemistry for hole-spin initialization at room temperature. Meanwhile, we were able to utilize strong light-matter interaction of these QDs to perform coherent spin manipulation." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 62011, 2987, 315, 6573, 21395, 12903, 78925, 374, 459, 3062, 49340, 369, 31228, 2038, 8863, 13, 9303, 6067, 3060, 14816, 520, 1633, 3428, 20472, 477, 527, 5107, 311, 5569, 709, 13, 81745, 3428, 41238, 11, 69311, 7384, 6832, 45858, 649, 387, 1080, 1964, 4501, 55315, 520, 3130, 9499, 374, 8617, 7701, 19411, 369, 264, 22556, 3938, 315, 31228, 2038, 8198, 13, 5810, 584, 1934, 35288, 59105, 682, 57212, 950, 17923, 11, 34786, 323, 1373, 412, 315, 14512, 45858, 304, 459, 40126, 315, 6425, 2427, 4935, 68432, 47, 65, 6971, 220, 18, 824, 869, 4991, 635, 31228, 32094, 449, 264, 3254, 14512, 304, 1855, 13046, 13, 578, 14512, 45858, 527, 17719, 555, 1207, 83873, 974, 1321, 17130, 83750, 833, 287, 2768, 28029, 398, 25685, 1534, 5103, 83, 974, 1321, 2320, 17660, 3521, 7709, 13, 362, 1380, 4550, 24924, 2115, 90974, 12903, 864, 26540, 11, 323, 264, 2132, 1022, 11849, 263, 685, 5103, 83, 974, 1321, 2320, 17660, 1080, 1964, 4501, 90159, 14512, 45858, 4669, 3831, 3177, 4235, 60065, 16628, 13, 4314, 7677, 22829, 3221, 75514, 31228, 21395, 2585, 11, 449, 264, 56887, 12984, 9392, 3345, 311, 279, 52845, 9038, 1122, 11, 315, 14512, 45858, 520, 3130, 9499, 13, 4802, 3623, 38638, 2585, 315, 45858, 304, 6573, 21395, 6067, 10187, 2294, 11471, 369, 31228, 2038, 8198, 220, 16, 662, 59813, 449, 20155, 87836, 7384, 11, 44589, 6067, 320, 21470, 439, 67422, 710, 532, 2427, 4935, 31228, 32094, 320, 48, 68050, 595, 1051, 6646, 311, 387, 810, 94848, 311, 31228, 2038, 8198, 1606, 315, 279, 13336, 315, 28118, 323, 63614, 3254, 45858, 220, 17, 1174, 220, 18, 1174, 220, 19, 662, 7089, 10507, 315, 44589, 6067, 2997, 23011, 36282, 477, 27420, 1821, 304, 82486, 220, 20, 662, 15415, 17868, 11, 9063, 47621, 20314, 477, 24924, 56688, 527, 11798, 369, 12903, 31228, 21395, 2585, 220, 21, 1174, 220, 22, 1174, 719, 279, 892, 13693, 315, 1778, 7677, 527, 389, 279, 2015, 315, 20622, 76989, 520, 1888, 13, 35295, 83, 974, 1321, 477, 10532, 974, 1321, 29393, 66557, 617, 6051, 9147, 24955, 9533, 12903, 34786, 520, 48298, 1579, 25753, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 662, 763, 34781, 315, 279, 2450, 315, 5370, 34786, 5528, 11, 1070, 527, 2103, 1690, 73021, 5938, 449, 1510, 12903, 39689, 7384, 505, 279, 59485, 315, 15325, 8522, 13, 11266, 275, 710, 532, 1229, 68050, 527, 70554, 1701, 11646, 11, 1579, 12, 35658, 323, 1579, 8437, 582, 21066, 41705, 13, 13596, 16188, 4360, 374, 430, 958, 3374, 72916, 323, 59086, 311, 51923, 263, 59300, 649, 16917, 41369, 279, 12903, 78925, 13, 53123, 11, 12903, 34786, 315, 1521, 1229, 68050, 374, 11383, 27332, 520, 16106, 29569, 20472, 315, 264, 2478, 49328, 9799, 220, 24, 1174, 220, 868, 662, 3296, 13168, 11, 279, 23011, 477, 27420, 519, 45858, 304, 82486, 527, 7701, 25181, 323, 649, 387, 55315, 520, 3130, 9499, 220, 845, 662, 4452, 11, 31790, 5352, 5788, 315, 1521, 1486, 42655, 2643, 9778, 3719, 264, 8815, 13, 1789, 279, 69311, 323, 22556, 8292, 315, 12903, 6108, 31228, 2038, 8198, 11, 433, 374, 35946, 311, 2274, 3428, 41238, 7384, 6832, 45858, 649, 387, 1080, 1964, 4501, 55315, 1234, 35288, 4787, 13, 578, 82048, 26966, 38495, 315, 1229, 68050, 320, 19171, 2663, 20622, 4309, 92475, 8, 649, 387, 92106, 304, 3544, 33776, 304, 6425, 520, 3428, 2853, 11, 3686, 449, 1579, 16437, 304, 3878, 315, 1404, 323, 6211, 2585, 11, 323, 527, 8104, 14791, 369, 659, 12, 15343, 477, 3756, 18052, 220, 1114, 662, 4452, 11, 12903, 34786, 369, 1760, 88167, 85090, 1542, 6108, 82048, 26966, 1229, 68050, 706, 539, 1027, 15393, 520, 3130, 9499, 220, 605, 662, 1226, 2543, 1057, 5357, 311, 6051, 8040, 3063, 15104, 579, 824, 869, 4991, 635, 82048, 26966, 1229, 68050, 220, 972, 662, 11205, 12903, 4235, 75441, 59086, 323, 14683, 6070, 220, 777, 617, 19168, 311, 387, 10728, 369, 11297, 12903, 26127, 555, 29393, 3445, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 1174, 323, 872, 3831, 3177, 4235, 60065, 16628, 1288, 1101, 28696, 12903, 34786, 3196, 389, 459, 29393, 47849, 2515, 320, 76734, 8, 220, 1627, 1174, 220, 1544, 1174, 220, 1591, 1174, 220, 1682, 662, 578, 8815, 315, 12903, 34786, 304, 3063, 15104, 579, 824, 869, 4991, 635, 1229, 68050, 11, 4869, 11, 374, 872, 11295, 12903, 43685, 520, 3130, 9499, 320, 64, 2478, 10532, 76989, 8, 220, 1187, 1174, 220, 914, 1174, 4762, 7347, 555, 24872, 17130, 4235, 31520, 9473, 304, 1521, 45408, 6067, 220, 966, 662, 763, 420, 13659, 11, 584, 16343, 958, 22974, 532, 6900, 93791, 30903, 315, 3063, 15104, 579, 824, 869, 4991, 635, 1229, 68050, 323, 5103, 83, 974, 1321, 21120, 66557, 311, 9656, 11, 37735, 323, 1373, 704, 14512, 45858, 520, 3130, 9499, 13, 1226, 16003, 553, 279, 27529, 315, 68432, 47, 65, 6971, 220, 18, 1229, 68050, 449, 23064, 969, 36444, 606, 320, 93173, 8, 35715, 13, 23548, 279, 18459, 315, 264, 12903, 2320, 7569, 1534, 25435, 263, 304, 264, 1229, 35, 1701, 264, 28029, 398, 25685, 1534, 69010, 11, 279, 83555, 649, 8819, 279, 17130, 389, 264, 1207, 83873, 974, 1321, 3115, 2296, 11, 8617, 934, 20345, 287, 279, 12903, 43685, 36572, 555, 17130, 4235, 31520, 9473, 13, 1115, 3135, 304, 1317, 62954, 14512, 12903, 864, 26540, 922, 459, 9435, 1380, 4550, 24924, 2115, 709, 311, 11758, 315, 10532, 76989, 11, 2391, 902, 264, 2132, 1022, 11849, 263, 685, 21120, 28334, 1080, 1964, 4501, 90159, 279, 14512, 12903, 2212, 264, 68102, 8183, 1555, 279, 507, 937, 13, 57074, 3871, 11, 279, 864, 26540, 323, 12984, 22829, 6992, 31228, 21395, 2585, 315, 14512, 45858, 520, 3130, 9499, 13, 19690, 60993, 323, 22772, 743, 5352, 19575, 220, 16, 46480, 279, 6205, 17910, 11, 29393, 743, 5352, 323, 17966, 315, 1057, 9526, 13, 2052, 22323, 1051, 10887, 520, 3130, 9499, 13, 68432, 47, 65, 6971, 220, 18, 1229, 68050, 315, 687, 69855, 12562, 1051, 92106, 1701, 264, 4106, 3502, 7761, 1749, 220, 1187, 2652, 3649, 649, 387, 1766, 304, 279, 19331, 13, 19575, 220, 16, 64, 5039, 279, 44225, 63697, 315, 1403, 1229, 35, 10688, 320, 48, 35, 16, 323, 1229, 35, 17, 8, 77810, 304, 12651, 2194, 13, 11205, 18874, 17130, 73757, 320, 21695, 8, 5448, 304, 99371, 23966, 13, 220, 16, 16805, 1647, 347, 28470, 325, 24671, 35831, 32094, 449, 5578, 6964, 29416, 315, 4056, 19, 13, 17, 323, 220, 19, 13, 21, 26807, 369, 1229, 35, 16, 323, 1229, 35, 17, 11, 15947, 13, 578, 14113, 31228, 66678, 3135, 304, 264, 4101, 315, 25435, 263, 40035, 72450, 520, 3130, 9499, 11, 449, 279, 15821, 40035, 520, 220, 17711, 323, 220, 21235, 26807, 369, 1229, 35, 16, 323, 1229, 35, 17, 11, 15947, 320, 30035, 13, 220, 16, 64, 7609, 1221, 5589, 1133, 38973, 4907, 10484, 2065, 304, 1521, 1229, 68050, 1288, 1520, 311, 28321, 51923, 263, 38973, 958, 3374, 72916, 323, 14201, 12903, 78925, 7863, 449, 20155, 10688, 11, 8051, 872, 3544, 3254, 82002, 48947, 31857, 1135, 4235, 1041, 757, 53, 26, 44243, 13, 220, 2148, 1174, 220, 843, 883, 7863, 449, 51923, 263, 49969, 13533, 430, 10805, 1604, 899, 72916, 2103, 34103, 459, 4360, 520, 3130, 9499, 13, 362, 1841, 2054, 4010, 660, 32905, 315, 83555, 11, 902, 374, 264, 1664, 22015, 17130, 4287, 269, 220, 1644, 1174, 220, 1958, 1174, 574, 78219, 8800, 279, 1229, 35, 7479, 1555, 279, 1841, 2054, 4010, 1912, 320, 19331, 7609, 578, 24872, 44225, 315, 1229, 35, 16, 4235, 93173, 323, 1229, 35, 17, 4235, 93173, 7863, 449, 12743, 1229, 35, 16, 323, 1229, 35, 17, 304, 279, 37232, 85311, 649, 387, 30706, 311, 279, 83555, 35715, 320, 10254, 67082, 23966, 13, 220, 17, 7609, 1952, 279, 8197, 315, 44225, 63697, 323, 52609, 37929, 11, 584, 16430, 430, 1070, 527, 810, 1109, 220, 1049, 83555, 35715, 389, 1855, 1229, 35, 13, 23966, 13, 220, 16, 25, 744, 2955, 323, 22772, 743, 5352, 13, 264, 1174, 22855, 66181, 63697, 315, 68432, 47, 65, 6971, 220, 18, 1229, 35, 16, 323, 1229, 35, 17, 13, 578, 63697, 315, 279, 14155, 323, 279, 72293, 66557, 320, 939, 14589, 66557, 8, 527, 5343, 369, 12593, 13, 578, 38057, 13519, 279, 12541, 93959, 315, 279, 1403, 15821, 25435, 263, 40035, 369, 1229, 35, 16, 323, 1229, 35, 17, 13, 293, 1174, 17366, 48448, 29393, 6727, 5718, 304, 68432, 47, 65, 6971, 220, 18, 128257, 198, 128256, 78191, 198, 32, 3495, 1912, 6197, 555, 8626, 13, 37230, 23109, 333, 833, 505, 279, 423, 10700, 10181, 315, 36424, 28415, 320, 94261, 47, 705, 8620, 16192, 315, 23199, 6051, 5068, 279, 6992, 17923, 11, 56887, 31228, 21395, 2585, 11, 323, 1373, 412, 315, 45858, 520, 3130, 9499, 1701, 6425, 2427, 4935, 31228, 32094, 11, 902, 11105, 459, 3062, 12178, 304, 31228, 2038, 8198, 13, 578, 4007, 574, 4756, 304, 22037, 33242, 52536, 389, 3799, 220, 777, 339, 13, 56413, 2038, 8198, 374, 11920, 449, 279, 34786, 315, 279, 31228, 2373, 315, 2038, 9660, 320, 44982, 2874, 82502, 570, 3277, 1274, 3137, 922, 7384, 369, 31228, 2038, 8863, 11, 814, 6118, 1781, 315, 1884, 28648, 1701, 279, 1455, 14713, 48448, 14645, 323, 10565, 520, 1633, 9439, 20472, 320, 54277, 264, 2478, 92073, 705, 539, 279, 330, 83697, 323, 46946, 1, 7384, 92106, 304, 6425, 555, 8590, 1705, 13, 35390, 1667, 617, 32126, 279, 18841, 315, 25181, 42655, 304, 6573, 21395, 7384, 320, 21470, 439, 25464, 19169, 8, 430, 617, 1903, 3284, 3130, 12, 35658, 12903, 52708, 60320, 34786, 11, 719, 31790, 5352, 5788, 315, 1521, 330, 2837, 42655, 1, 690, 9778, 3719, 264, 8815, 13, 4349, 385, 26966, 31228, 32094, 320, 48, 68050, 705, 902, 527, 13987, 87836, 94753, 1903, 304, 6425, 11, 1436, 387, 264, 1847, 62439, 13, 2435, 649, 387, 92106, 304, 3544, 33776, 304, 6425, 520, 3428, 2853, 11, 3686, 449, 1579, 35018, 325, 304, 1404, 323, 6211, 2585, 13, 15903, 11, 814, 527, 6118, 16917, 31228, 51817, 1619, 11, 8617, 872, 35991, 1664, 25181, 505, 279, 51923, 263, 9061, 11, 902, 1436, 7431, 1317, 62954, 12903, 78925, 520, 3130, 9499, 13, 2030, 3130, 12, 35658, 56887, 34786, 315, 45858, 304, 82048, 26966, 1229, 68050, 706, 2646, 1027, 5068, 11, 304, 430, 264, 1229, 35, 1887, 6832, 45858, 649, 387, 25291, 17719, 11, 46720, 11, 323, 1373, 412, 520, 3130, 12, 35658, 8625, 311, 387, 36592, 13, 5810, 279, 12283, 1501, 430, 6425, 2427, 4935, 68432, 47, 65, 6971, 18, 824, 869, 4991, 635, 1229, 68050, 649, 3604, 22829, 420, 64130, 5915, 13, 56996, 1534, 14512, 45858, 527, 12457, 555, 1207, 83873, 974, 1321, 17130, 83750, 833, 287, 11, 311, 7479, 12, 3581, 3093, 31206, 4287, 1105, 11, 2768, 264, 28029, 398, 2320, 7569, 1534, 5103, 83, 974, 1321, 28334, 3521, 7709, 13, 362, 1380, 4550, 24924, 2115, 90974, 56887, 445, 43648, 864, 26540, 315, 279, 14512, 45858, 13, 362, 2132, 1022, 11849, 263, 685, 5103, 83, 974, 1321, 28334, 1080, 1964, 4501, 90159, 279, 45858, 1555, 279, 29393, 47849, 2515, 11, 902, 374, 9147, 555, 279, 48298, 3831, 3177, 1474, 1683, 16628, 315, 279, 824, 869, 4991, 635, 1229, 68050, 13, 4314, 3135, 4097, 2539, 31228, 21395, 2585, 315, 3254, 87693, 45858, 520, 3130, 9499, 11, 10168, 2294, 11471, 369, 264, 69311, 323, 22556, 3938, 315, 12903, 6108, 31228, 2038, 8863, 330, 8140, 2450, 1618, 374, 9147, 555, 264, 1633, 9024, 10824, 315, 6677, 304, 7384, 11, 30903, 323, 22027, 1359, 1071, 8626, 13, 37230, 13, 330, 1687, 70554, 16917, 12, 323, 78909, 51817, 1619, 68432, 47, 65, 6971, 18, 1229, 68050, 439, 279, 5016, 1887, 369, 279, 4007, 11, 323, 11054, 8475, 7479, 2922, 343, 438, 35715, 311, 19019, 8819, 279, 57678, 4669, 6900, 93791, 30903, 369, 14512, 82006, 17923, 520, 3130, 9499, 13, 26982, 11, 584, 1051, 3025, 311, 29166, 3831, 3177, 1474, 1683, 16628, 315, 1521, 1229, 68050, 311, 2804, 56887, 12903, 34786, 1210, 220, 128257, 198 ]

2,005

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The capacity and reach of long-haul fiber optical communication systems is limited by in-line amplifier noise and fiber nonlinearities. Phase-sensitive amplifiers add 6 dB less noise than conventional phase-insensitive amplifiers, such as erbium-doped fiber amplifiers, and they can provide nonlinearity mitigation after each span. Realizing a long-haul transmission link with in-line phase-sensitive amplifiers providing simultaneous low-noise amplification and nonlinearity mitigation is challenging and to date no such transmission link has been demonstrated. Here, we demonstrate a multi-channel-compatible and modulation-format-independent long-haul transmission link with in-line phase-sensitive amplifiers. Compared to a link amplified by conventional erbium-doped fiber amplifiers, we demonstrate a reach improvement of 5.6 times at optimal launch powers with the phase-sensitively amplified link operating at a total accumulated nonlinear phase shift of 6.2 rad. The phase-sensitively amplified link transmits two data-carrying waves, thus occupying twice the bandwidth and propagating twice the total power compared to the phase-insensitively amplified link. Introduction The achievable transmission performance of fiber optical transmission systems is limited by amplifier noise and fiber nonlinearities degrading the signal 1 , 2 , 3 . Phase-sensitive amplifiers (PSAs) can provide low-noise amplification, because at high gains their noise figure (NF) is 3 dB lower than that of even ideal phase-insensitive amplifiers (PIAs) 4 , 5 . Using an alternative NF definition where only the signal power is accounted for (idler power is neglected), the NF difference between PSAs and PIAs increases to 6 dB 5 . PSAs are also capable of all-optical mitigation of nonlinear transmission distortions 6 , 7 , 8 . Using PSAs low-noise amplification and nonlinearity mitigation capabilities, PSAs can potentially improve the transmission performance of fiber optical transmission systems 9 , 10 . PSAs can be realized, for example using, parametric gain in χ (2) nonlinear materials through three-wave mixing (TWM) 11 , or χ (3) nonlinear materials through four-wave mixing (FWM) 12 . Typically, two weak waves, called signal and idler, are amplified by one or two high-power waves, called pumps. Depending on how the frequencies of the interacting waves are chosen, different amplification schemes are possible. Two common schemes are the one-mode PSAs in which signal and idler are frequency degenerate and the two-mode PSAs in which signal and idler are frequency non-degenerate. In one-mode PSAs, one quadrature is amplified while the other quadrature is deamplified, squeezing the signal phase along the direction of the amplified quadrature 4 . If the PSA is operated in unsaturated regime, phase noise in the squeezed quadrature will be converted into amplitude noise in the amplified quadrature. If, however, the PSA is operated in saturation both phase and amplitude noise can be suppressed thus making this scheme suitable for simultaneous phase and amplitude regeneration of binary phase-shift keying (BPSK) signals 13 , 14 , 15 . Using this scheme, a two times reach extension, originating from phase and amplitude regeneration, not low-noise amplification, has been demonstrated 16 , 17 . Two severe drawbacks of the one-mode PSA scheme is that it is inherently single-channel and that it is only suitable for BPSK signals. Using other PSA-based schemes, regeneration of more advanced modulation formats such as quadrature phase-shift keying (QPSK) 18 , 19 , and star 8-quadrature amplitude modulation (QAM) 20 , have been demonstrated as well as simultaneous regeneration of more than one channel 21 , 22 . Another way to benefit from PSAs is to utilize their capabilities of low-noise amplification and nonlinearity mitigation. This can be done using two-mode PSAs implemented with the so-called copier-PSA scheme 23 . Using the copier-PSA scheme, all signal phase states will experience low-noise amplification thus providing modulation-format transparency 24 . Moreover, two-mode PSAs are multi-channel compatible and can be used for amplification of wavelength division multiplexing (WDM) signals 25 . In ref. 26 , it was shown that two-mode PSAs potentially can be combined with multi-channel amplitude regenerators for multi-channel regeneration of advanced modulation formats. For details on the requirements regarding the tracking and alignment of polarization in PSA links see ref. 27 Mitigation of fiber nonlinearities to extend transmission reach is a vivid research area currently 28 , and many different schemes have been proposed, e.g., phase conjugated twin waves 29 or conjugate data repetition 30 , which are based on the idea that the signal and the conjugate signal are co-propagated through the same medium and coherently superposed to suppress the nonlinear-induced phase distortion. Cancellation of nonlinear distortion by digital signal processing 31 in the receiver 32 or transmitter 33 has also been demonstrated, as has optical phase conjugation (OPC) 34 . Typically, a doubling or at most a tripling of the system reach have been reported by these schemes, at the expense of spectral efficiency and/or complexity. A way to further enhance performance could be to distribute the compensation, which is attractive for all-optical schemes such as PSAs or OPC, and for OPCs that was recently demonstrated 35 , 36 , although relatively moderate Q-factor improvements over single OPCs were reported. Here we present experimental evidence that in-line PSAs, can provide an unprecedented nonlinear tolerance and transmission reach extension 9 , 10 . In this demonstration of a recirculating loop (i.e., long-haul) transmission experiment with in-line PSAs, we benefit from the inherent simultaneous low-noise amplification and nonlinearity mitigation. This scheme, which is both modulation format-independent and multi-channel compatible 5 , is shown experimentally to have a 5.6 times reach improvement compared to a transmission link using conventional in-line erbium-doped fiber amplifiers (EDFAs) when transmitting a 10 GBd QPSK signal. The accumulated nonlinear phase shift in the PSA link is 6.2 rad, which we believe is the highest nonlinear tolerance ever reported in a lumped-amplifier system. These results demonstrate not only the feasibility of realizing long-haul transmission links using low-noise PSAs but also significant improvement over conventional approaches. The concept of amplification using cascaded PSAs might also find applications in the field of quantum information science, where generation and processing of quantum states are of interest. Results Basic principle The amplifier implementation we consider in this", "role": "user" }, { "content": "Researchers from Chalmers University of Technology, Sweden, and Tallinn University of Technology, Estonia, have demonstrated a 4000 kilometre fibre-optical transmission link using ultra low-noise, phase-sensitive optical amplifiers. This is a reach improvement of almost six times what is possible when using conventional optical amplifiers. The results are published in Nature Communications. Video streaming, cloud storage and other online services have created an insatiable demand for higher transmission capacity. To meet this demand, new technologies capable of significant improvements over existing solutions are being explored worldwide. The reach and capacity in today's fibre optical transmission links are both limited by the accumulation of noise, originating from optical amplifiers in the link, and by the signal distortion from nonlinear effects in the transmission fibre. In this ground-breaking demonstration, the researchers showed that the use of phase-sensitive amplifiers can significantly, and simultaneously, reduce the impact of both of these effects. \"While there remain several engineering challenges before these results can be implemented commercially, the results show, for the first time, in a very clear way, the great benefits of using these amplifiers in optical communication,\" says Professor Peter Andrekson, who leads the research on optical communication at Chalmers University of Technology. The amplifiers can provide a very significant reach improvement over conventional approaches, and could potentially improve the performance of future fibre-optical communication systems. \"Such amplifiers may also find applications in quantum informatics and related fields, where generation and processing of quantum states are of interest, as well as in spectroscopy or any other application which could benefit from ultra-low-noise amplification,\" says Professor Peter Andrekson. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The capacity and reach of long-haul fiber optical communication systems is limited by in-line amplifier noise and fiber nonlinearities. Phase-sensitive amplifiers add 6 dB less noise than conventional phase-insensitive amplifiers, such as erbium-doped fiber amplifiers, and they can provide nonlinearity mitigation after each span. Realizing a long-haul transmission link with in-line phase-sensitive amplifiers providing simultaneous low-noise amplification and nonlinearity mitigation is challenging and to date no such transmission link has been demonstrated. Here, we demonstrate a multi-channel-compatible and modulation-format-independent long-haul transmission link with in-line phase-sensitive amplifiers. Compared to a link amplified by conventional erbium-doped fiber amplifiers, we demonstrate a reach improvement of 5.6 times at optimal launch powers with the phase-sensitively amplified link operating at a total accumulated nonlinear phase shift of 6.2 rad. The phase-sensitively amplified link transmits two data-carrying waves, thus occupying twice the bandwidth and propagating twice the total power compared to the phase-insensitively amplified link. Introduction The achievable transmission performance of fiber optical transmission systems is limited by amplifier noise and fiber nonlinearities degrading the signal 1 , 2 , 3 . Phase-sensitive amplifiers (PSAs) can provide low-noise amplification, because at high gains their noise figure (NF) is 3 dB lower than that of even ideal phase-insensitive amplifiers (PIAs) 4 , 5 . Using an alternative NF definition where only the signal power is accounted for (idler power is neglected), the NF difference between PSAs and PIAs increases to 6 dB 5 . PSAs are also capable of all-optical mitigation of nonlinear transmission distortions 6 , 7 , 8 . Using PSAs low-noise amplification and nonlinearity mitigation capabilities, PSAs can potentially improve the transmission performance of fiber optical transmission systems 9 , 10 . PSAs can be realized, for example using, parametric gain in χ (2) nonlinear materials through three-wave mixing (TWM) 11 , or χ (3) nonlinear materials through four-wave mixing (FWM) 12 . Typically, two weak waves, called signal and idler, are amplified by one or two high-power waves, called pumps. Depending on how the frequencies of the interacting waves are chosen, different amplification schemes are possible. Two common schemes are the one-mode PSAs in which signal and idler are frequency degenerate and the two-mode PSAs in which signal and idler are frequency non-degenerate. In one-mode PSAs, one quadrature is amplified while the other quadrature is deamplified, squeezing the signal phase along the direction of the amplified quadrature 4 . If the PSA is operated in unsaturated regime, phase noise in the squeezed quadrature will be converted into amplitude noise in the amplified quadrature. If, however, the PSA is operated in saturation both phase and amplitude noise can be suppressed thus making this scheme suitable for simultaneous phase and amplitude regeneration of binary phase-shift keying (BPSK) signals 13 , 14 , 15 . Using this scheme, a two times reach extension, originating from phase and amplitude regeneration, not low-noise amplification, has been demonstrated 16 , 17 . Two severe drawbacks of the one-mode PSA scheme is that it is inherently single-channel and that it is only suitable for BPSK signals. Using other PSA-based schemes, regeneration of more advanced modulation formats such as quadrature phase-shift keying (QPSK) 18 , 19 , and star 8-quadrature amplitude modulation (QAM) 20 , have been demonstrated as well as simultaneous regeneration of more than one channel 21 , 22 . Another way to benefit from PSAs is to utilize their capabilities of low-noise amplification and nonlinearity mitigation. This can be done using two-mode PSAs implemented with the so-called copier-PSA scheme 23 . Using the copier-PSA scheme, all signal phase states will experience low-noise amplification thus providing modulation-format transparency 24 . Moreover, two-mode PSAs are multi-channel compatible and can be used for amplification of wavelength division multiplexing (WDM) signals 25 . In ref. 26 , it was shown that two-mode PSAs potentially can be combined with multi-channel amplitude regenerators for multi-channel regeneration of advanced modulation formats. For details on the requirements regarding the tracking and alignment of polarization in PSA links see ref. 27 Mitigation of fiber nonlinearities to extend transmission reach is a vivid research area currently 28 , and many different schemes have been proposed, e.g., phase conjugated twin waves 29 or conjugate data repetition 30 , which are based on the idea that the signal and the conjugate signal are co-propagated through the same medium and coherently superposed to suppress the nonlinear-induced phase distortion. Cancellation of nonlinear distortion by digital signal processing 31 in the receiver 32 or transmitter 33 has also been demonstrated, as has optical phase conjugation (OPC) 34 . Typically, a doubling or at most a tripling of the system reach have been reported by these schemes, at the expense of spectral efficiency and/or complexity. A way to further enhance performance could be to distribute the compensation, which is attractive for all-optical schemes such as PSAs or OPC, and for OPCs that was recently demonstrated 35 , 36 , although relatively moderate Q-factor improvements over single OPCs were reported. Here we present experimental evidence that in-line PSAs, can provide an unprecedented nonlinear tolerance and transmission reach extension 9 , 10 . In this demonstration of a recirculating loop (i.e., long-haul) transmission experiment with in-line PSAs, we benefit from the inherent simultaneous low-noise amplification and nonlinearity mitigation. This scheme, which is both modulation format-independent and multi-channel compatible 5 , is shown experimentally to have a 5.6 times reach improvement compared to a transmission link using conventional in-line erbium-doped fiber amplifiers (EDFAs) when transmitting a 10 GBd QPSK signal. The accumulated nonlinear phase shift in the PSA link is 6.2 rad, which we believe is the highest nonlinear tolerance ever reported in a lumped-amplifier system. These results demonstrate not only the feasibility of realizing long-haul transmission links using low-noise PSAs but also significant improvement over conventional approaches. The concept of amplification using cascaded PSAs might also find applications in the field of quantum information science, where generation and processing of quantum states are of interest. Results Basic principle The amplifier implementation we consider in this<|im_end|> <|im_start|>assistant Researchers from Chalmers University of Technology, Sweden, and Tallinn University of Technology, Estonia, have demonstrated a 4000 kilometre fibre-optical transmission link using ultra low-noise, phase-sensitive optical amplifiers. This is a reach improvement of almost six times what is possible when using conventional optical amplifiers. The results are published in Nature Communications. Video streaming, cloud storage and other online services have created an insatiable demand for higher transmission capacity. To meet this demand, new technologies capable of significant improvements over existing solutions are being explored worldwide. The reach and capacity in today's fibre optical transmission links are both limited by the accumulation of noise, originating from optical amplifiers in the link, and by the signal distortion from nonlinear effects in the transmission fibre. In this ground-breaking demonstration, the researchers showed that the use of phase-sensitive amplifiers can significantly, and simultaneously, reduce the impact of both of these effects. "While there remain several engineering challenges before these results can be implemented commercially, the results show, for the first time, in a very clear way, the great benefits of using these amplifiers in optical communication," says Professor Peter Andrekson, who leads the research on optical communication at Chalmers University of Technology. The amplifiers can provide a very significant reach improvement over conventional approaches, and could potentially improve the performance of future fibre-optical communication systems. "Such amplifiers may also find applications in quantum informatics and related fields, where generation and processing of quantum states are of interest, as well as in spectroscopy or any other application which could benefit from ultra-low-noise amplification," says Professor Peter Andrekson. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 8824, 323, 5662, 315, 1317, 2902, 5049, 24722, 29393, 10758, 6067, 374, 7347, 555, 304, 8614, 61166, 12248, 323, 24722, 75098, 1385, 13, 28673, 57767, 23201, 12099, 923, 220, 21, 44868, 2753, 12248, 1109, 21349, 10474, 22610, 19245, 23201, 12099, 11, 1778, 439, 68748, 2411, 1773, 16771, 24722, 23201, 12099, 11, 323, 814, 649, 3493, 2536, 1074, 10981, 66860, 1306, 1855, 9575, 13, 8976, 4954, 264, 1317, 2902, 5049, 18874, 2723, 449, 304, 8614, 10474, 57767, 23201, 12099, 8405, 58632, 3428, 29466, 1082, 23201, 2461, 323, 2536, 1074, 10981, 66860, 374, 17436, 323, 311, 2457, 912, 1778, 18874, 2723, 706, 1027, 21091, 13, 5810, 11, 584, 20461, 264, 7447, 54968, 81315, 323, 67547, 39480, 98885, 1317, 2902, 5049, 18874, 2723, 449, 304, 8614, 10474, 57767, 23201, 12099, 13, 59813, 311, 264, 2723, 83598, 555, 21349, 68748, 2411, 1773, 16771, 24722, 23201, 12099, 11, 584, 20461, 264, 5662, 16048, 315, 220, 20, 13, 21, 3115, 520, 23669, 7195, 13736, 449, 279, 10474, 1355, 729, 275, 3210, 83598, 2723, 10565, 520, 264, 2860, 41165, 75098, 10474, 6541, 315, 220, 21, 13, 17, 9038, 13, 578, 10474, 1355, 729, 275, 3210, 83598, 2723, 1380, 45803, 1403, 828, 1824, 11687, 287, 17301, 11, 8617, 72280, 11157, 279, 34494, 323, 17425, 1113, 11157, 279, 2860, 2410, 7863, 311, 279, 10474, 22610, 729, 275, 3210, 83598, 2723, 13, 29438, 578, 89253, 18874, 5178, 315, 24722, 29393, 18874, 6067, 374, 7347, 555, 61166, 12248, 323, 24722, 75098, 1385, 409, 33359, 279, 8450, 220, 16, 1174, 220, 17, 1174, 220, 18, 662, 28673, 57767, 23201, 12099, 320, 5119, 2170, 8, 649, 3493, 3428, 29466, 1082, 23201, 2461, 11, 1606, 520, 1579, 20192, 872, 12248, 7216, 320, 39167, 8, 374, 220, 18, 44868, 4827, 1109, 430, 315, 1524, 10728, 10474, 22610, 19245, 23201, 12099, 320, 1932, 2170, 8, 220, 19, 1174, 220, 20, 662, 12362, 459, 10778, 45827, 7419, 1405, 1193, 279, 8450, 2410, 374, 41853, 369, 320, 307, 1565, 2410, 374, 51533, 705, 279, 45827, 6811, 1990, 11659, 2170, 323, 23396, 2170, 12992, 311, 220, 21, 44868, 220, 20, 662, 11659, 2170, 527, 1101, 13171, 315, 682, 57212, 950, 66860, 315, 75098, 18874, 70584, 919, 220, 21, 1174, 220, 22, 1174, 220, 23, 662, 12362, 11659, 2170, 3428, 29466, 1082, 23201, 2461, 323, 2536, 1074, 10981, 66860, 17357, 11, 11659, 2170, 649, 13893, 7417, 279, 18874, 5178, 315, 24722, 29393, 18874, 6067, 220, 24, 1174, 220, 605, 662, 11659, 2170, 649, 387, 15393, 11, 369, 3187, 1701, 11, 1719, 16743, 8895, 304, 100897, 320, 17, 8, 75098, 7384, 1555, 2380, 89354, 27890, 320, 51, 15565, 8, 220, 806, 1174, 477, 100897, 320, 18, 8, 75098, 7384, 1555, 3116, 89354, 27890, 320, 37, 15565, 8, 220, 717, 662, 46402, 11, 1403, 7621, 17301, 11, 2663, 8450, 323, 887, 1565, 11, 527, 83598, 555, 832, 477, 1403, 1579, 27624, 17301, 11, 2663, 43875, 13, 40730, 389, 1268, 279, 34873, 315, 279, 45830, 17301, 527, 12146, 11, 2204, 23201, 2461, 31956, 527, 3284, 13, 9220, 4279, 31956, 527, 279, 832, 15331, 11659, 2170, 304, 902, 8450, 323, 887, 1565, 527, 11900, 5367, 13523, 323, 279, 1403, 15331, 11659, 2170, 304, 902, 8450, 323, 887, 1565, 527, 11900, 2536, 6953, 19927, 13, 763, 832, 15331, 11659, 2170, 11, 832, 30236, 1598, 374, 83598, 1418, 279, 1023, 30236, 1598, 374, 409, 309, 501, 1908, 11, 88807, 279, 8450, 10474, 3235, 279, 5216, 315, 279, 83598, 30236, 1598, 220, 19, 662, 1442, 279, 70586, 374, 24026, 304, 7120, 35467, 17942, 11, 10474, 12248, 304, 279, 65262, 30236, 1598, 690, 387, 16489, 1139, 45209, 12248, 304, 279, 83598, 30236, 1598, 13, 1442, 11, 4869, 11, 279, 70586, 374, 24026, 304, 50843, 2225, 10474, 323, 45209, 12248, 649, 387, 56089, 8617, 3339, 420, 13155, 14791, 369, 58632, 10474, 323, 45209, 60517, 315, 8026, 10474, 91043, 1401, 287, 320, 33, 5119, 42, 8, 17738, 220, 1032, 1174, 220, 975, 1174, 220, 868, 662, 12362, 420, 13155, 11, 264, 1403, 3115, 5662, 9070, 11, 71373, 505, 10474, 323, 45209, 60517, 11, 539, 3428, 29466, 1082, 23201, 2461, 11, 706, 1027, 21091, 220, 845, 1174, 220, 1114, 662, 9220, 15748, 89173, 315, 279, 832, 15331, 70586, 13155, 374, 430, 433, 374, 49188, 3254, 54968, 323, 430, 433, 374, 1193, 14791, 369, 426, 5119, 42, 17738, 13, 12362, 1023, 70586, 6108, 31956, 11, 60517, 315, 810, 11084, 67547, 20447, 1778, 439, 30236, 1598, 10474, 91043, 1401, 287, 320, 48, 5119, 42, 8, 220, 972, 1174, 220, 777, 1174, 323, 6917, 220, 23, 74801, 15008, 1598, 45209, 67547, 320, 48, 1428, 8, 220, 508, 1174, 617, 1027, 21091, 439, 1664, 439, 58632, 60517, 315, 810, 1109, 832, 5613, 220, 1691, 1174, 220, 1313, 662, 13596, 1648, 311, 8935, 505, 11659, 2170, 374, 311, 29166, 872, 17357, 315, 3428, 29466, 1082, 23201, 2461, 323, 2536, 1074, 10981, 66860, 13, 1115, 649, 387, 2884, 1701, 1403, 15331, 11659, 2170, 11798, 449, 279, 779, 19434, 6293, 1291, 12, 5119, 32, 13155, 220, 1419, 662, 12362, 279, 6293, 1291, 12, 5119, 32, 13155, 11, 682, 8450, 10474, 5415, 690, 3217, 3428, 29466, 1082, 23201, 2461, 8617, 8405, 67547, 39480, 28330, 220, 1187, 662, 23674, 11, 1403, 15331, 11659, 2170, 527, 7447, 54968, 18641, 323, 649, 387, 1511, 369, 23201, 2461, 315, 46406, 13096, 12842, 2635, 287, 320, 54, 8561, 8, 17738, 220, 914, 662, 763, 2098, 13, 220, 1627, 1174, 433, 574, 6982, 430, 1403, 15331, 11659, 2170, 13893, 649, 387, 11093, 449, 7447, 54968, 45209, 1239, 804, 3046, 369, 7447, 54968, 60517, 315, 11084, 67547, 20447, 13, 1789, 3649, 389, 279, 8670, 9002, 279, 15194, 323, 17632, 315, 83245, 304, 70586, 7902, 1518, 2098, 13, 220, 1544, 22515, 18413, 315, 24722, 75098, 1385, 311, 13334, 18874, 5662, 374, 264, 43120, 3495, 3158, 5131, 220, 1591, 1174, 323, 1690, 2204, 31956, 617, 1027, 11223, 11, 384, 1326, 2637, 10474, 64380, 660, 28497, 17301, 220, 1682, 477, 64380, 349, 828, 54515, 220, 966, 1174, 902, 527, 3196, 389, 279, 4623, 430, 279, 8450, 323, 279, 64380, 349, 8450, 527, 1080, 77671, 351, 660, 1555, 279, 1890, 11298, 323, 1080, 1964, 4501, 2307, 3950, 311, 28321, 279, 75098, 38973, 10474, 50971, 13, 356, 50322, 315, 75098, 50971, 555, 7528, 8450, 8863, 220, 2148, 304, 279, 14291, 220, 843, 477, 62210, 220, 1644, 706, 1101, 1027, 21091, 11, 439, 706, 29393, 10474, 64380, 367, 320, 3143, 34, 8, 220, 1958, 662, 46402, 11, 264, 60115, 477, 520, 1455, 264, 2463, 12127, 315, 279, 1887, 5662, 617, 1027, 5068, 555, 1521, 31956, 11, 520, 279, 20900, 315, 57077, 15374, 323, 5255, 23965, 13, 362, 1648, 311, 4726, 18885, 5178, 1436, 387, 311, 16822, 279, 20448, 11, 902, 374, 19411, 369, 682, 57212, 950, 31956, 1778, 439, 11659, 2170, 477, 87471, 11, 323, 369, 87471, 82, 430, 574, 6051, 21091, 220, 1758, 1174, 220, 1927, 1174, 8051, 12309, 24070, 1229, 75197, 18637, 927, 3254, 87471, 82, 1051, 5068, 13, 5810, 584, 3118, 22772, 6029, 430, 304, 8614, 11659, 2170, 11, 649, 3493, 459, 31069, 75098, 25065, 323, 18874, 5662, 9070, 220, 24, 1174, 220, 605, 662, 763, 420, 30816, 315, 264, 1421, 2496, 15853, 6471, 320, 72, 1770, 2637, 1317, 2902, 5049, 8, 18874, 9526, 449, 304, 8614, 11659, 2170, 11, 584, 8935, 505, 279, 38088, 58632, 3428, 29466, 1082, 23201, 2461, 323, 2536, 1074, 10981, 66860, 13, 1115, 13155, 11, 902, 374, 2225, 67547, 3645, 98885, 323, 7447, 54968, 18641, 220, 20, 1174, 374, 6982, 9526, 750, 311, 617, 264, 220, 20, 13, 21, 3115, 5662, 16048, 7863, 311, 264, 18874, 2723, 1701, 21349, 304, 8614, 68748, 2411, 1773, 16771, 24722, 23201, 12099, 320, 1507, 37, 2170, 8, 994, 78768, 264, 220, 605, 19397, 67, 1229, 5119, 42, 8450, 13, 578, 41165, 75098, 10474, 6541, 304, 279, 70586, 2723, 374, 220, 21, 13, 17, 9038, 11, 902, 584, 4510, 374, 279, 8592, 75098, 25065, 3596, 5068, 304, 264, 49629, 291, 33317, 501, 3125, 1887, 13, 4314, 3135, 20461, 539, 1193, 279, 69543, 315, 44114, 1317, 2902, 5049, 18874, 7902, 1701, 3428, 29466, 1082, 11659, 2170, 719, 1101, 5199, 16048, 927, 21349, 20414, 13, 578, 7434, 315, 23201, 2461, 1701, 76057, 14589, 11659, 2170, 2643, 1101, 1505, 8522, 304, 279, 2115, 315, 31228, 2038, 8198, 11, 1405, 9659, 323, 8863, 315, 31228, 5415, 527, 315, 2802, 13, 18591, 14967, 17966, 578, 61166, 8292, 584, 2980, 304, 420, 128257, 198, 128256, 78191, 198, 60210, 505, 921, 7828, 388, 3907, 315, 12053, 11, 24067, 11, 323, 42202, 6258, 3907, 315, 12053, 11, 69462, 11, 617, 21091, 264, 220, 3443, 15, 44987, 265, 57525, 57212, 950, 18874, 2723, 1701, 24955, 3428, 29466, 1082, 11, 10474, 57767, 29393, 23201, 12099, 13, 1115, 374, 264, 5662, 16048, 315, 4661, 4848, 3115, 1148, 374, 3284, 994, 1701, 21349, 29393, 23201, 12099, 13, 578, 3135, 527, 4756, 304, 22037, 26545, 13, 8519, 17265, 11, 9624, 5942, 323, 1023, 2930, 3600, 617, 3549, 459, 1672, 266, 2205, 7631, 369, 5190, 18874, 8824, 13, 2057, 3449, 420, 7631, 11, 502, 14645, 13171, 315, 5199, 18637, 927, 6484, 10105, 527, 1694, 36131, 15603, 13, 578, 5662, 323, 8824, 304, 3432, 596, 57525, 29393, 18874, 7902, 527, 2225, 7347, 555, 279, 46835, 315, 12248, 11, 71373, 505, 29393, 23201, 12099, 304, 279, 2723, 11, 323, 555, 279, 8450, 50971, 505, 75098, 6372, 304, 279, 18874, 57525, 13, 763, 420, 5015, 55407, 30816, 11, 279, 12074, 8710, 430, 279, 1005, 315, 10474, 57767, 23201, 12099, 649, 12207, 11, 323, 25291, 11, 8108, 279, 5536, 315, 2225, 315, 1521, 6372, 13, 330, 8142, 1070, 7293, 3892, 15009, 11774, 1603, 1521, 3135, 649, 387, 11798, 54453, 11, 279, 3135, 1501, 11, 369, 279, 1176, 892, 11, 304, 264, 1633, 2867, 1648, 11, 279, 2294, 7720, 315, 1701, 1521, 23201, 12099, 304, 29393, 10758, 1359, 2795, 17054, 11291, 27525, 74, 942, 11, 889, 11767, 279, 3495, 389, 29393, 10758, 520, 921, 7828, 388, 3907, 315, 12053, 13, 578, 23201, 12099, 649, 3493, 264, 1633, 5199, 5662, 16048, 927, 21349, 20414, 11, 323, 1436, 13893, 7417, 279, 5178, 315, 3938, 57525, 57212, 950, 10758, 6067, 13, 330, 21365, 23201, 12099, 1253, 1101, 1505, 8522, 304, 31228, 6179, 29470, 323, 5552, 5151, 11, 1405, 9659, 323, 8863, 315, 31228, 5415, 527, 315, 2802, 11, 439, 1664, 439, 304, 66425, 51856, 477, 904, 1023, 3851, 902, 1436, 8935, 505, 24955, 60369, 29466, 1082, 23201, 2461, 1359, 2795, 17054, 11291, 27525, 74, 942, 13, 220, 128257, 198 ]

1,753

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Water radiolysis continuously produces H 2 and oxidized chemicals in wet sediment and rock. Radiolytic H 2 has been identified as the primary electron donor (food) for microorganisms in continental aquifers kilometers below Earth’s surface. Radiolytic products may also be significant for sustaining life in subseafloor sediment and subsurface environments of other planets. However, the extent to which most subsurface ecosystems rely on radiolytic products has been poorly constrained, due to incomplete understanding of radiolytic chemical yields in natural environments. Here we show that all common marine sediment types catalyse radiolytic H 2 production, amplifying yields by up to 27X relative to pure water. In electron equivalents, the global rate of radiolytic H 2 production in marine sediment appears to be 1-2% of the global organic flux to the seafloor. However, most organic matter is consumed at or near the seafloor, whereas radiolytic H 2 is produced at all sediment depths. Comparison of radiolytic H 2 consumption rates to organic oxidation rates suggests that water radiolysis is the principal source of biologically accessible energy for microbial communities in marine sediment older than a few million years. Where water permeates similarly catalytic material on other worlds, life may also be sustained by water radiolysis. Introduction Radionuclides are ubiquitous in sediment and rock, where their decay leads to hydrogen (H 2 ) and oxidant production via radiolysis of water 1 , 2 , 3 , 4 . Radiolytic yields in pure water are well constrained 5 , 6 and some monominerals (pyrite, various oxides, mordenite, calcite) are known to amplify water-radiolytic H 2 yields when irradiated by γ rays 7 , 8 , 9 . Similarly, other oxides and calcite enhance water-radiolytic H 2 production following exposure to α particles 9 , 10 , 11 . The effect of mineralogically complex natural materials on H 2 yields is previously unexplored. Hydrogen (H 2 ) and oxidants generated by natural radiolysis of water provide a continuous source of chemical energy for subsurface ecosystems 2 , 3 , 4 , 12 , 13 . Microbial life persists deep beneath Earth’s surface 14 , 15 and constitutes a significant fraction of Earth’s total biomass 16 , 17 . Radiolytic H 2 is now recognized as the primary electron donor for microbial communities kilometers below the surface in Precambrian regions of continental lithosphere 14 . However, the extent to which most subsurface ecosystems rely on radiolytic products has been unclear because (i) radiolytic chemical yields in natural environments have been poorly constrained and (ii) organic matter and oxidants from the surface photosynthetic world are pervasive in many subsurface environments. Results and discussion We experimentally quantified H 2 yields for α- and γ-irradiation of pure water, seawater, and seawater-saturated marine sediment with a typical abyssal clay porosity (80–85%) for all abundant marine sediment types (abyssal clay, nannofossil-bearing clay (calcareous marl), clay-bearing siliceous ooze, calcareous ooze, and lithogenous sediment), which collectively cover ~70% of Earth’s surface. Our results show that for pure water, seawater, and marine sediment slurries, H 2 production increases linearly with absorbed α- and γ-ray dose. Energy-normalized radiolytic H 2 yields, denoted by G(H 2 ) (molecules H 2 per 100 eV absorbed) 1 , in seawater are indistinguishable from those in pure water, within the 90% confidence limit of our experiments. In contrast, G(H 2 ) values of marine sediment slurries are consistently higher than values for pure water (Fig. 1 ). The catalytic effect of marine sediment on radiolytic yield is significant for both α- and γ-irradiation, but much larger for α-irradiation. Alpha-irradiation G(H 2 ) values for abyssal clay slurries are more than an order of magnitude higher than for pure water. On average, clay-bearing siliceous ooze and calcareous marl increase G(H 2 ) for α-irradiation by factors of 15 and 12, respectively. Calcareous ooze increases yields by a factor of 5 for α-irradiation. For γ-irradiation, clay-bearing siliceous ooze and abyssal clay amplify G(H 2 ) by factors of 8 and 4, respectively. Calcareous ooze and marl slurries doubled G(H 2 ) for γ-irradiation. These results demonstrate that (i) all common marine sediment types catalyze radiolytic H 2 production, and (ii) the magnitude of this catalysis depends on sediment composition and radiation type. Fig. 1: Radiolytic H 2 catalysis by marine sediment. Experimental H 2 yields for α irradiation ( A ) and γ irradiation ( B ). Reported yields are averages of a minimum of four replicate experiments. Vertical dashed lines represent multiples of production in pure water. Site locations ( C ) color-coded to indicate origins of samples in A and B . Full size image Previous experiments with oxides suggest that the primary cause of increased yield in all of our sediment types is energy transfer from sediment particles to the water via excitons 18 , 19 , 20 . H 2 yield exceeds the pure-water yield for γ-irradiated oxides characterized by a band gap equal to the 5.1 eV energy of the H–OH bond in water 18 . This result is consistent with irradiation of the oxide generating excitons that propagate to the oxide–water interface, where they lyse the water 18 , 19 , 20 . With excitons as the primary mechanism for transferring irradiation energy from sediment particles to particle–water interfaces 18 , 19 , factors that may cause variation in radiolytic H 2 catalysis from one sediment type to another include mineral composition of the sediment (which affects band gap), particle size (which affects exciton migration distance), water adsorption form (physisorbed vs. chemisorbed), and surface density of hydroxyl groups 20 . In addition to H 2 , water radiolysis generates diverse oxidized products in wet sediment. In pure water, production of H 2 from radiolysis is stoichiometrically balanced by production of H 2 O 2 [2H 2 O → H 2 + H 2 O 2 ] 12 , 21 . In the presence of reduced chemicals, such as reduced sulfur and/or reduced iron, H 2 production is balanced by production of H 2 O", "role": "user" }, { "content": "A team of researchers from the University of Rhode Island's Graduate School of Oceanography and their collaborators have revealed that the abundant microbes living in ancient sediment below the seafloor are sustained primarily by chemicals created by the natural irradiation of water molecules. The team discovered that the creation of these chemicals is amplified significantly by minerals in marine sediment. In contrast to the conventional view that life in sediment is fueled by products of photosynthesis, an ecosystem fueled by irradiation of water begins just meters below the seafloor in much of the open ocean. This radiation-fueled world is one of Earth's volumetrically largest ecosystems. The research was published today in the journal Nature Communications. \"This work provides an important new perspective on the availability of resources that subsurface microbial communities can use to sustain themselves. This is fundamental to understand life on Earth and to constrain the habitability of other planetary bodies, such as Mars,\" said Justine Sauvage, the study's lead author and a postdoctoral fellow at the University of Gothenburg who conducted the research as a doctoral student at URI. The process driving the research team's findings is radiolysis of water—the splitting of water molecules into hydrogen and oxidants as a result of being exposed to naturally occurring radiation. Steven D'Hondt, URI professor of oceanography and a co-author of the study, said the resulting molecules become the primary source of food and energy for the microbes living in the sediment. \"The marine sediment actually amplifies the production of these usable chemicals,\" he said. \"If you have the same amount of irradiation in pure water and in wet sediment, you get a lot more hydrogen from wet sediment. The sediment makes the production of hydrogen much more effective.\" Justine Sauvage, lead author of the study, measures dissolved oxygen content in sediment cores collected in the North Atlantic. Photo courtesy of Justine Sauvage Why the process is amplified in wet sediment is unclear, but D'Hondt speculates that minerals in the sediment may \"behave like a semiconductor, making the process more efficient.\" The discoveries resulted from a series of laboratory experiments conducted in the Rhode Island Nuclear Science Center. Sauvage irradiated vials of wet sediment from various locations in the Pacific and Atlantic Oceans, collected by the Integrated Ocean Drilling Program and by U.S. research vessels. She compared the production of hydrogen to similarly irradiated vials of seawater and distilled water. The sediment amplified the results by as much as a factor of 30. \"This study is a unique combination of sophisticated laboratory experiments integrated into a global biological context,\" said co-author Arthur Spivack, URI professor of oceanography. The implications of the findings are significant. \"If you can support life in subsurface marine sediment and other subsurface environments from natural radioactive splitting of water, then maybe you can support life the same way in other worlds,\" said D'Hondt. \"Some of the same minerals are present on Mars, and as long as you have those wet catalytic minerals, you're going to have this process. If you can catalyze production of radiolytic chemicals at high rates in the wet Martian subsurface, you could potentially sustain life at the same levels that it's sustained in marine sediment.\" Sauvage added, \"This is especially relevant given that the Perseverance Rover has just landed on Mars, with its mission to collect Martian rocks and to characterize its habitable environments.\" D'Hondt said the research team's findings also have implications for the nuclear industry, including for how nuclear waste is stored and how nuclear accidents are managed. \"If you store nuclear waste in sediment or rock, it may generate hydrogen and oxidants faster than in pure water. That natural catalysis may make those storage systems more corrosive than is generally realized,\" he said. The next steps for the research team will be to explore the effect of hydrogen production through radiolysis in other environments on Earth and beyond, including oceanic crust, continental crust and subsurface Mars. They also will seek to advance the understanding of how subsurface microbial communities live, interact and evolve when their primary energy source is derived from the natural radiolytic splitting of water. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Water radiolysis continuously produces H 2 and oxidized chemicals in wet sediment and rock. Radiolytic H 2 has been identified as the primary electron donor (food) for microorganisms in continental aquifers kilometers below Earth’s surface. Radiolytic products may also be significant for sustaining life in subseafloor sediment and subsurface environments of other planets. However, the extent to which most subsurface ecosystems rely on radiolytic products has been poorly constrained, due to incomplete understanding of radiolytic chemical yields in natural environments. Here we show that all common marine sediment types catalyse radiolytic H 2 production, amplifying yields by up to 27X relative to pure water. In electron equivalents, the global rate of radiolytic H 2 production in marine sediment appears to be 1-2% of the global organic flux to the seafloor. However, most organic matter is consumed at or near the seafloor, whereas radiolytic H 2 is produced at all sediment depths. Comparison of radiolytic H 2 consumption rates to organic oxidation rates suggests that water radiolysis is the principal source of biologically accessible energy for microbial communities in marine sediment older than a few million years. Where water permeates similarly catalytic material on other worlds, life may also be sustained by water radiolysis. Introduction Radionuclides are ubiquitous in sediment and rock, where their decay leads to hydrogen (H 2 ) and oxidant production via radiolysis of water 1 , 2 , 3 , 4 . Radiolytic yields in pure water are well constrained 5 , 6 and some monominerals (pyrite, various oxides, mordenite, calcite) are known to amplify water-radiolytic H 2 yields when irradiated by γ rays 7 , 8 , 9 . Similarly, other oxides and calcite enhance water-radiolytic H 2 production following exposure to α particles 9 , 10 , 11 . The effect of mineralogically complex natural materials on H 2 yields is previously unexplored. Hydrogen (H 2 ) and oxidants generated by natural radiolysis of water provide a continuous source of chemical energy for subsurface ecosystems 2 , 3 , 4 , 12 , 13 . Microbial life persists deep beneath Earth’s surface 14 , 15 and constitutes a significant fraction of Earth’s total biomass 16 , 17 . Radiolytic H 2 is now recognized as the primary electron donor for microbial communities kilometers below the surface in Precambrian regions of continental lithosphere 14 . However, the extent to which most subsurface ecosystems rely on radiolytic products has been unclear because (i) radiolytic chemical yields in natural environments have been poorly constrained and (ii) organic matter and oxidants from the surface photosynthetic world are pervasive in many subsurface environments. Results and discussion We experimentally quantified H 2 yields for α- and γ-irradiation of pure water, seawater, and seawater-saturated marine sediment with a typical abyssal clay porosity (80–85%) for all abundant marine sediment types (abyssal clay, nannofossil-bearing clay (calcareous marl), clay-bearing siliceous ooze, calcareous ooze, and lithogenous sediment), which collectively cover ~70% of Earth’s surface. Our results show that for pure water, seawater, and marine sediment slurries, H 2 production increases linearly with absorbed α- and γ-ray dose. Energy-normalized radiolytic H 2 yields, denoted by G(H 2 ) (molecules H 2 per 100 eV absorbed) 1 , in seawater are indistinguishable from those in pure water, within the 90% confidence limit of our experiments. In contrast, G(H 2 ) values of marine sediment slurries are consistently higher than values for pure water (Fig. 1 ). The catalytic effect of marine sediment on radiolytic yield is significant for both α- and γ-irradiation, but much larger for α-irradiation. Alpha-irradiation G(H 2 ) values for abyssal clay slurries are more than an order of magnitude higher than for pure water. On average, clay-bearing siliceous ooze and calcareous marl increase G(H 2 ) for α-irradiation by factors of 15 and 12, respectively. Calcareous ooze increases yields by a factor of 5 for α-irradiation. For γ-irradiation, clay-bearing siliceous ooze and abyssal clay amplify G(H 2 ) by factors of 8 and 4, respectively. Calcareous ooze and marl slurries doubled G(H 2 ) for γ-irradiation. These results demonstrate that (i) all common marine sediment types catalyze radiolytic H 2 production, and (ii) the magnitude of this catalysis depends on sediment composition and radiation type. Fig. 1: Radiolytic H 2 catalysis by marine sediment. Experimental H 2 yields for α irradiation ( A ) and γ irradiation ( B ). Reported yields are averages of a minimum of four replicate experiments. Vertical dashed lines represent multiples of production in pure water. Site locations ( C ) color-coded to indicate origins of samples in A and B . Full size image Previous experiments with oxides suggest that the primary cause of increased yield in all of our sediment types is energy transfer from sediment particles to the water via excitons 18 , 19 , 20 . H 2 yield exceeds the pure-water yield for γ-irradiated oxides characterized by a band gap equal to the 5.1 eV energy of the H–OH bond in water 18 . This result is consistent with irradiation of the oxide generating excitons that propagate to the oxide–water interface, where they lyse the water 18 , 19 , 20 . With excitons as the primary mechanism for transferring irradiation energy from sediment particles to particle–water interfaces 18 , 19 , factors that may cause variation in radiolytic H 2 catalysis from one sediment type to another include mineral composition of the sediment (which affects band gap), particle size (which affects exciton migration distance), water adsorption form (physisorbed vs. chemisorbed), and surface density of hydroxyl groups 20 . In addition to H 2 , water radiolysis generates diverse oxidized products in wet sediment. In pure water, production of H 2 from radiolysis is stoichiometrically balanced by production of H 2 O 2 [2H 2 O → H 2 + H 2 O 2 ] 12 , 21 . In the presence of reduced chemicals, such as reduced sulfur and/or reduced iron, H 2 production is balanced by production of H 2 O<|im_end|> <|im_start|>assistant A team of researchers from the University of Rhode Island's Graduate School of Oceanography and their collaborators have revealed that the abundant microbes living in ancient sediment below the seafloor are sustained primarily by chemicals created by the natural irradiation of water molecules. The team discovered that the creation of these chemicals is amplified significantly by minerals in marine sediment. In contrast to the conventional view that life in sediment is fueled by products of photosynthesis, an ecosystem fueled by irradiation of water begins just meters below the seafloor in much of the open ocean. This radiation-fueled world is one of Earth's volumetrically largest ecosystems. The research was published today in the journal Nature Communications. "This work provides an important new perspective on the availability of resources that subsurface microbial communities can use to sustain themselves. This is fundamental to understand life on Earth and to constrain the habitability of other planetary bodies, such as Mars," said Justine Sauvage, the study's lead author and a postdoctoral fellow at the University of Gothenburg who conducted the research as a doctoral student at URI. The process driving the research team's findings is radiolysis of water—the splitting of water molecules into hydrogen and oxidants as a result of being exposed to naturally occurring radiation. Steven D'Hondt, URI professor of oceanography and a co-author of the study, said the resulting molecules become the primary source of food and energy for the microbes living in the sediment. "The marine sediment actually amplifies the production of these usable chemicals," he said. "If you have the same amount of irradiation in pure water and in wet sediment, you get a lot more hydrogen from wet sediment. The sediment makes the production of hydrogen much more effective." Justine Sauvage, lead author of the study, measures dissolved oxygen content in sediment cores collected in the North Atlantic. Photo courtesy of Justine Sauvage Why the process is amplified in wet sediment is unclear, but D'Hondt speculates that minerals in the sediment may "behave like a semiconductor, making the process more efficient." The discoveries resulted from a series of laboratory experiments conducted in the Rhode Island Nuclear Science Center. Sauvage irradiated vials of wet sediment from various locations in the Pacific and Atlantic Oceans, collected by the Integrated Ocean Drilling Program and by U.S. research vessels. She compared the production of hydrogen to similarly irradiated vials of seawater and distilled water. The sediment amplified the results by as much as a factor of 30. "This study is a unique combination of sophisticated laboratory experiments integrated into a global biological context," said co-author Arthur Spivack, URI professor of oceanography. The implications of the findings are significant. "If you can support life in subsurface marine sediment and other subsurface environments from natural radioactive splitting of water, then maybe you can support life the same way in other worlds," said D'Hondt. "Some of the same minerals are present on Mars, and as long as you have those wet catalytic minerals, you're going to have this process. If you can catalyze production of radiolytic chemicals at high rates in the wet Martian subsurface, you could potentially sustain life at the same levels that it's sustained in marine sediment." Sauvage added, "This is especially relevant given that the Perseverance Rover has just landed on Mars, with its mission to collect Martian rocks and to characterize its habitable environments." D'Hondt said the research team's findings also have implications for the nuclear industry, including for how nuclear waste is stored and how nuclear accidents are managed. "If you store nuclear waste in sediment or rock, it may generate hydrogen and oxidants faster than in pure water. That natural catalysis may make those storage systems more corrosive than is generally realized," he said. The next steps for the research team will be to explore the effect of hydrogen production through radiolysis in other environments on Earth and beyond, including oceanic crust, continental crust and subsurface Mars. They also will seek to advance the understanding of how subsurface microbial communities live, interact and evolve when their primary energy source is derived from the natural radiolytic splitting of water. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 10164, 12164, 337, 4548, 31978, 19159, 473, 220, 17, 323, 36172, 1534, 26333, 304, 14739, 59132, 323, 7091, 13, 35969, 5849, 29150, 473, 220, 17, 706, 1027, 11054, 439, 279, 6156, 17130, 35558, 320, 14239, 8, 369, 8162, 76991, 304, 58636, 15715, 99913, 41668, 3770, 9420, 753, 7479, 13, 35969, 5849, 29150, 3956, 1253, 1101, 387, 5199, 369, 80184, 2324, 304, 1207, 325, 2642, 4081, 59132, 323, 5258, 10730, 22484, 315, 1023, 33975, 13, 4452, 11, 279, 13112, 311, 902, 1455, 5258, 10730, 61951, 17631, 389, 12164, 5849, 29150, 3956, 706, 1027, 31555, 54852, 11, 4245, 311, 33243, 8830, 315, 12164, 5849, 29150, 11742, 36508, 304, 5933, 22484, 13, 5810, 584, 1501, 430, 682, 4279, 29691, 59132, 4595, 34454, 88, 325, 12164, 5849, 29150, 473, 220, 17, 5788, 11, 23201, 7922, 36508, 555, 709, 311, 220, 1544, 55, 8844, 311, 10748, 3090, 13, 763, 17130, 86106, 11, 279, 3728, 4478, 315, 12164, 5849, 29150, 473, 220, 17, 5788, 304, 29691, 59132, 8111, 311, 387, 220, 16, 12, 17, 4, 315, 279, 3728, 17808, 31405, 311, 279, 513, 2642, 4081, 13, 4452, 11, 1455, 17808, 5030, 374, 27073, 520, 477, 3221, 279, 513, 2642, 4081, 11, 20444, 12164, 5849, 29150, 473, 220, 17, 374, 9124, 520, 682, 59132, 43957, 13, 43551, 315, 12164, 5849, 29150, 473, 220, 17, 15652, 7969, 311, 17808, 71162, 7969, 13533, 430, 3090, 12164, 337, 4548, 374, 279, 12717, 2592, 315, 6160, 30450, 15987, 4907, 369, 75418, 10977, 304, 29691, 59132, 9191, 1109, 264, 2478, 3610, 1667, 13, 11208, 3090, 55424, 988, 30293, 34454, 70504, 3769, 389, 1023, 24800, 11, 2324, 1253, 1101, 387, 29759, 555, 3090, 12164, 337, 4548, 13, 29438, 21254, 290, 84, 566, 3422, 527, 64564, 304, 59132, 323, 7091, 11, 1405, 872, 31815, 11767, 311, 35784, 320, 39, 220, 17, 883, 323, 36172, 519, 5788, 4669, 12164, 337, 4548, 315, 3090, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 662, 35969, 5849, 29150, 36508, 304, 10748, 3090, 527, 1664, 54852, 220, 20, 1174, 220, 21, 323, 1063, 1647, 8129, 17822, 320, 3368, 1269, 11, 5370, 19488, 3422, 11, 296, 28884, 635, 11, 10241, 635, 8, 527, 3967, 311, 97168, 3090, 3880, 2836, 5849, 29150, 473, 220, 17, 36508, 994, 76327, 660, 555, 63127, 45220, 220, 22, 1174, 220, 23, 1174, 220, 24, 662, 35339, 11, 1023, 19488, 3422, 323, 10241, 635, 18885, 3090, 3880, 2836, 5849, 29150, 473, 220, 17, 5788, 2768, 14675, 311, 19581, 19252, 220, 24, 1174, 220, 605, 1174, 220, 806, 662, 578, 2515, 315, 25107, 540, 2740, 6485, 5933, 7384, 389, 473, 220, 17, 36508, 374, 8767, 653, 69331, 1171, 13, 40602, 4469, 320, 39, 220, 17, 883, 323, 36172, 1821, 8066, 555, 5933, 12164, 337, 4548, 315, 3090, 3493, 264, 19815, 2592, 315, 11742, 4907, 369, 5258, 10730, 61951, 220, 17, 1174, 220, 18, 1174, 220, 19, 1174, 220, 717, 1174, 220, 1032, 662, 18654, 48059, 2324, 67145, 5655, 24923, 9420, 753, 7479, 220, 975, 1174, 220, 868, 323, 42675, 264, 5199, 19983, 315, 9420, 753, 2860, 58758, 220, 845, 1174, 220, 1114, 662, 35969, 5849, 29150, 473, 220, 17, 374, 1457, 15324, 439, 279, 6156, 17130, 35558, 369, 75418, 10977, 41668, 3770, 279, 7479, 304, 42770, 3042, 7414, 13918, 315, 58636, 46282, 66222, 220, 975, 662, 4452, 11, 279, 13112, 311, 902, 1455, 5258, 10730, 61951, 17631, 389, 12164, 5849, 29150, 3956, 706, 1027, 25420, 1606, 320, 72, 8, 12164, 5849, 29150, 11742, 36508, 304, 5933, 22484, 617, 1027, 31555, 54852, 323, 320, 3893, 8, 17808, 5030, 323, 36172, 1821, 505, 279, 7479, 7397, 1910, 18015, 1917, 527, 71867, 304, 1690, 5258, 10730, 22484, 13, 18591, 323, 10430, 1226, 9526, 750, 10484, 1908, 473, 220, 17, 36508, 369, 19581, 12, 323, 63127, 12, 404, 70312, 367, 315, 10748, 3090, 11, 67329, 977, 11, 323, 67329, 977, 1355, 35467, 29691, 59132, 449, 264, 14595, 88314, 278, 37148, 4247, 22828, 320, 1490, 4235, 5313, 11587, 369, 682, 44611, 29691, 59132, 4595, 320, 6243, 784, 278, 37148, 11, 308, 1036, 1073, 85061, 92253, 37148, 320, 5531, 10727, 788, 3678, 75, 705, 37148, 92253, 5554, 560, 788, 57009, 3059, 11, 10241, 548, 788, 57009, 3059, 11, 323, 46282, 53595, 59132, 705, 902, 45925, 3504, 4056, 2031, 4, 315, 9420, 753, 7479, 13, 5751, 3135, 1501, 430, 369, 10748, 3090, 11, 67329, 977, 11, 323, 29691, 59132, 84671, 4108, 11, 473, 220, 17, 5788, 12992, 13790, 398, 449, 42101, 19581, 12, 323, 63127, 30630, 19660, 13, 12634, 53183, 1534, 12164, 5849, 29150, 473, 220, 17, 36508, 11, 3453, 9437, 555, 480, 11135, 220, 17, 883, 320, 76, 82206, 473, 220, 17, 824, 220, 1041, 384, 53, 42101, 8, 220, 16, 1174, 304, 67329, 977, 527, 1280, 89747, 481, 505, 1884, 304, 10748, 3090, 11, 2949, 279, 220, 1954, 4, 12410, 4017, 315, 1057, 21896, 13, 763, 13168, 11, 480, 11135, 220, 17, 883, 2819, 315, 29691, 59132, 84671, 4108, 527, 21356, 5190, 1109, 2819, 369, 10748, 3090, 320, 30035, 13, 220, 16, 7609, 578, 34454, 70504, 2515, 315, 29691, 59132, 389, 12164, 5849, 29150, 7692, 374, 5199, 369, 2225, 19581, 12, 323, 63127, 12, 404, 70312, 367, 11, 719, 1790, 8294, 369, 19581, 12, 404, 70312, 367, 13, 25737, 12, 404, 70312, 367, 480, 11135, 220, 17, 883, 2819, 369, 88314, 278, 37148, 84671, 4108, 527, 810, 1109, 459, 2015, 315, 26703, 5190, 1109, 369, 10748, 3090, 13, 1952, 5578, 11, 37148, 92253, 5554, 560, 788, 57009, 3059, 323, 10241, 548, 788, 3678, 75, 5376, 480, 11135, 220, 17, 883, 369, 19581, 12, 404, 70312, 367, 555, 9547, 315, 220, 868, 323, 220, 717, 11, 15947, 13, 3400, 10727, 788, 57009, 3059, 12992, 36508, 555, 264, 8331, 315, 220, 20, 369, 19581, 12, 404, 70312, 367, 13, 1789, 63127, 12, 404, 70312, 367, 11, 37148, 92253, 5554, 560, 788, 57009, 3059, 323, 88314, 278, 37148, 97168, 480, 11135, 220, 17, 883, 555, 9547, 315, 220, 23, 323, 220, 19, 11, 15947, 13, 3400, 10727, 788, 57009, 3059, 323, 3678, 75, 84671, 4108, 35717, 480, 11135, 220, 17, 883, 369, 63127, 12, 404, 70312, 367, 13, 4314, 3135, 20461, 430, 320, 72, 8, 682, 4279, 29691, 59132, 4595, 34454, 88, 3059, 12164, 5849, 29150, 473, 220, 17, 5788, 11, 323, 320, 3893, 8, 279, 26703, 315, 420, 34454, 4548, 14117, 389, 59132, 18528, 323, 25407, 955, 13, 23966, 13, 220, 16, 25, 35969, 5849, 29150, 473, 220, 17, 34454, 4548, 555, 29691, 59132, 13, 57708, 473, 220, 17, 36508, 369, 19581, 76327, 367, 320, 362, 883, 323, 63127, 76327, 367, 320, 426, 7609, 79711, 36508, 527, 49920, 315, 264, 8187, 315, 3116, 46113, 21896, 13, 36563, 67822, 5238, 4097, 66160, 315, 5788, 304, 10748, 3090, 13, 13207, 10687, 320, 356, 883, 1933, 87411, 311, 13519, 33472, 315, 10688, 304, 362, 323, 426, 662, 8797, 1404, 2217, 30013, 21896, 449, 19488, 3422, 4284, 430, 279, 6156, 5353, 315, 7319, 7692, 304, 682, 315, 1057, 59132, 4595, 374, 4907, 8481, 505, 59132, 19252, 311, 279, 3090, 4669, 25435, 2439, 220, 972, 1174, 220, 777, 1174, 220, 508, 662, 473, 220, 17, 7692, 36375, 279, 10748, 55051, 7692, 369, 63127, 12, 404, 70312, 660, 19488, 3422, 32971, 555, 264, 7200, 13225, 6273, 311, 279, 220, 20, 13, 16, 384, 53, 4907, 315, 279, 473, 4235, 47861, 11049, 304, 3090, 220, 972, 662, 1115, 1121, 374, 13263, 449, 76327, 367, 315, 279, 51180, 24038, 25435, 2439, 430, 58514, 311, 279, 51180, 4235, 13284, 3834, 11, 1405, 814, 14869, 325, 279, 3090, 220, 972, 1174, 220, 777, 1174, 220, 508, 662, 3161, 25435, 2439, 439, 279, 6156, 17383, 369, 51051, 76327, 367, 4907, 505, 59132, 19252, 311, 19320, 4235, 13284, 25066, 220, 972, 1174, 220, 777, 1174, 9547, 430, 1253, 5353, 23851, 304, 12164, 5849, 29150, 473, 220, 17, 34454, 4548, 505, 832, 59132, 955, 311, 2500, 2997, 25107, 18528, 315, 279, 59132, 320, 8370, 22223, 7200, 13225, 705, 19320, 1404, 320, 8370, 22223, 25435, 263, 12172, 6138, 705, 3090, 14058, 66181, 1376, 320, 764, 4548, 269, 2788, 6296, 13, 8590, 16220, 2788, 705, 323, 7479, 17915, 315, 17055, 87, 4010, 5315, 220, 508, 662, 763, 5369, 311, 473, 220, 17, 1174, 3090, 12164, 337, 4548, 27983, 17226, 36172, 1534, 3956, 304, 14739, 59132, 13, 763, 10748, 3090, 11, 5788, 315, 473, 220, 17, 505, 12164, 337, 4548, 374, 43132, 41652, 24264, 750, 24770, 555, 5788, 315, 473, 220, 17, 507, 220, 17, 510, 17, 39, 220, 17, 507, 11651, 473, 220, 17, 489, 473, 220, 17, 507, 220, 17, 2331, 220, 717, 1174, 220, 1691, 662, 763, 279, 9546, 315, 11293, 26333, 11, 1778, 439, 11293, 72591, 323, 5255, 11293, 11245, 11, 473, 220, 17, 5788, 374, 24770, 555, 5788, 315, 473, 220, 17, 507, 128257, 198, 128256, 78191, 198, 32, 2128, 315, 12074, 505, 279, 3907, 315, 50981, 10951, 596, 44825, 6150, 315, 22302, 5814, 323, 872, 79119, 617, 10675, 430, 279, 44611, 80727, 5496, 304, 14154, 59132, 3770, 279, 513, 2642, 4081, 527, 29759, 15871, 555, 26333, 3549, 555, 279, 5933, 76327, 367, 315, 3090, 35715, 13, 578, 2128, 11352, 430, 279, 9886, 315, 1521, 26333, 374, 83598, 12207, 555, 34072, 304, 29691, 59132, 13, 763, 13168, 311, 279, 21349, 1684, 430, 2324, 304, 59132, 374, 59461, 555, 3956, 315, 7397, 74767, 11, 459, 26031, 59461, 555, 76327, 367, 315, 3090, 12302, 1120, 20645, 3770, 279, 513, 2642, 4081, 304, 1790, 315, 279, 1825, 18435, 13, 1115, 25407, 2269, 361, 839, 1917, 374, 832, 315, 9420, 596, 63920, 16743, 750, 7928, 61951, 13, 578, 3495, 574, 4756, 3432, 304, 279, 8486, 22037, 26545, 13, 330, 2028, 990, 5825, 459, 3062, 502, 13356, 389, 279, 18539, 315, 5070, 430, 5258, 10730, 75418, 10977, 649, 1005, 311, 14201, 5694, 13, 1115, 374, 16188, 311, 3619, 2324, 389, 9420, 323, 311, 80799, 279, 14464, 2968, 315, 1023, 62938, 13162, 11, 1778, 439, 21725, 1359, 1071, 4702, 483, 42116, 85, 425, 11, 279, 4007, 596, 3063, 3229, 323, 264, 1772, 38083, 278, 12637, 520, 279, 3907, 315, 6122, 3473, 10481, 889, 13375, 279, 3495, 439, 264, 74657, 5575, 520, 16403, 13, 578, 1920, 10043, 279, 3495, 2128, 596, 14955, 374, 12164, 337, 4548, 315, 3090, 22416, 45473, 315, 3090, 35715, 1139, 35784, 323, 36172, 1821, 439, 264, 1121, 315, 1694, 15246, 311, 18182, 31965, 25407, 13, 24565, 423, 68070, 2159, 83, 11, 16403, 14561, 315, 18435, 5814, 323, 264, 1080, 43802, 315, 279, 4007, 11, 1071, 279, 13239, 35715, 3719, 279, 6156, 2592, 315, 3691, 323, 4907, 369, 279, 80727, 5496, 304, 279, 59132, 13, 330, 791, 29691, 59132, 3604, 23201, 9803, 279, 5788, 315, 1521, 41030, 26333, 1359, 568, 1071, 13, 330, 2746, 499, 617, 279, 1890, 3392, 315, 76327, 367, 304, 10748, 3090, 323, 304, 14739, 59132, 11, 499, 636, 264, 2763, 810, 35784, 505, 14739, 59132, 13, 578, 59132, 3727, 279, 5788, 315, 35784, 1790, 810, 7524, 1210, 4702, 483, 42116, 85, 425, 11, 3063, 3229, 315, 279, 4007, 11, 11193, 56767, 24463, 2262, 304, 59132, 36804, 14890, 304, 279, 4892, 23179, 13, 11064, 27104, 315, 4702, 483, 42116, 85, 425, 8595, 279, 1920, 374, 83598, 304, 14739, 59132, 374, 25420, 11, 719, 423, 68070, 2159, 83, 1424, 24031, 430, 34072, 304, 279, 59132, 1253, 330, 1395, 19553, 1093, 264, 87836, 11, 3339, 279, 1920, 810, 11297, 1210, 578, 54098, 19543, 505, 264, 4101, 315, 27692, 21896, 13375, 304, 279, 50981, 10951, 38544, 10170, 5955, 13, 42116, 85, 425, 76327, 660, 348, 10522, 315, 14739, 59132, 505, 5370, 10687, 304, 279, 16867, 323, 23179, 507, 43320, 11, 14890, 555, 279, 50521, 22302, 2999, 9585, 6826, 323, 555, 549, 815, 13, 3495, 31080, 13, 3005, 7863, 279, 5788, 315, 35784, 311, 30293, 76327, 660, 348, 10522, 315, 67329, 977, 323, 89867, 3090, 13, 578, 59132, 83598, 279, 3135, 555, 439, 1790, 439, 264, 8331, 315, 220, 966, 13, 330, 2028, 4007, 374, 264, 5016, 10824, 315, 27877, 27692, 21896, 18751, 1139, 264, 3728, 24156, 2317, 1359, 1071, 1080, 43802, 28686, 3165, 344, 474, 11, 16403, 14561, 315, 18435, 5814, 13, 578, 25127, 315, 279, 14955, 527, 5199, 13, 330, 2746, 499, 649, 1862, 2324, 304, 5258, 10730, 29691, 59132, 323, 1023, 5258, 10730, 22484, 505, 5933, 59862, 45473, 315, 3090, 11, 1243, 7344, 499, 649, 1862, 2324, 279, 1890, 1648, 304, 1023, 24800, 1359, 1071, 423, 68070, 2159, 83, 13, 330, 8538, 315, 279, 1890, 34072, 527, 3118, 389, 21725, 11, 323, 439, 1317, 439, 499, 617, 1884, 14739, 34454, 70504, 34072, 11, 499, 2351, 2133, 311, 617, 420, 1920, 13, 1442, 499, 649, 34454, 88, 3059, 5788, 315, 12164, 5849, 29150, 26333, 520, 1579, 7969, 304, 279, 14739, 82128, 5258, 10730, 11, 499, 1436, 13893, 14201, 2324, 520, 279, 1890, 5990, 430, 433, 596, 29759, 304, 29691, 59132, 1210, 42116, 85, 425, 3779, 11, 330, 2028, 374, 5423, 9959, 2728, 430, 279, 3700, 325, 424, 685, 53276, 706, 1120, 27212, 389, 21725, 11, 449, 1202, 9131, 311, 6667, 82128, 23902, 323, 311, 70755, 1202, 14464, 481, 22484, 1210, 423, 68070, 2159, 83, 1071, 279, 3495, 2128, 596, 14955, 1101, 617, 25127, 369, 279, 11499, 5064, 11, 2737, 369, 1268, 11499, 12571, 374, 9967, 323, 1268, 11499, 33788, 527, 9152, 13, 330, 2746, 499, 3637, 11499, 12571, 304, 59132, 477, 7091, 11, 433, 1253, 7068, 35784, 323, 36172, 1821, 10819, 1109, 304, 10748, 3090, 13, 3011, 5933, 34454, 4548, 1253, 1304, 1884, 5942, 6067, 810, 46657, 535, 1109, 374, 8965, 15393, 1359, 568, 1071, 13, 578, 1828, 7504, 369, 279, 3495, 2128, 690, 387, 311, 13488, 279, 2515, 315, 35784, 5788, 1555, 12164, 337, 4548, 304, 1023, 22484, 389, 9420, 323, 7953, 11, 2737, 18435, 292, 40712, 11, 58636, 40712, 323, 5258, 10730, 21725, 13, 2435, 1101, 690, 6056, 311, 12178, 279, 8830, 315, 1268, 5258, 10730, 75418, 10977, 3974, 11, 16681, 323, 38680, 994, 872, 6156, 4907, 2592, 374, 14592, 505, 279, 5933, 12164, 5849, 29150, 45473, 315, 3090, 13, 220, 128257, 198 ]

2,334

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Functional interfaces between electronics and biological matter are essential to diverse fields including health sciences and bio-engineering. Here, we report the discovery of spontaneous (no external energy input) hydrogen transfer from biological glucose reactions into SmNiO 3 , an archetypal perovskite quantum material. The enzymatic oxidation of glucose is monitored down to ~5 × 10 −16 M concentration via hydrogen transfer to the nickelate lattice. The hydrogen atoms donate electrons to the Ni d orbital and induce electron localization through strong electron correlations. By enzyme specific modification, spontaneous transfer of hydrogen from the neurotransmitter dopamine can be monitored in physiological media. We then directly interface an acute mouse brain slice onto the nickelate devices and demonstrate measurement of neurotransmitter release upon electrical stimulation of the striatum region. These results open up avenues for use of emergent physics present in quantum materials in trace detection and conveyance of bio-matter, bio-chemical sciences, and brain-machine interfaces. Introduction Functional interfaces between biological and synthetic matter can greatly benefit from hydrogen transfer, which is of broad relevance to bio-sensing and bio-chemical sciences. Sensing media that responds to low concentrations of bio-markers therefore can be relevant in this context, however, must be functional near room (or body) temperature while constantly exposed to complex biological media. As a promising candidate, the perovskite nickelate SmNiO 3 (SNO, space group Pbnm) 1 , is water-stable, and belongs to a class of strongly correlated quantum materials, whose properties are highly sensitive to the occupancy of electrons in their partially filled orbitals 2 , 3 , 4 . When doped with charge carriers, SNO shows massive electronic structure changes: For one electron/unit cell doping from hydrogen, the electrical resistance changes by ~10 orders of magnitude 5 . In previous work, perovskite nickelates have shown potential for electric field detection in salt water media 6 . Glucose is a sugar that is essential for energy production in organisms and widely serves as a model system for bio-chemical studies. In nature, glucose can be oxidized into gluconolactone by losing hydrogen in the presence of glucose oxidase (GOx) enzyme 7 , and this reaction is seen across various organisms 8 , 9 . Utilizing an external electric field, perovskite oxide nano-particles have been used for glucose detection 10 , 11 . An important strategy to understand such biological and bio-chemical reactions involves measurement of the hydrogen transfer processes. Here, we present enzyme-mediated spontaneous hydrogen transfer between glucose reaction and SNO devices, as well as interfacing perovskite devices with acute mouse brain slices. Results Reaction mechanism Figure 1a shows the schematic pathway for spontaneous atomic hydrogen transfer between glucose–GOx reaction and a perovskite, where the nickelate participates in the reaction by accepting the hydrogen in the glucose–enzyme–oxide transfer chain. The reaction mechanism is described in Fig. 1b . During the glucose–enzyme–SNO reaction, the hydrogen atoms from the glucose are first transferred to the GOx enzyme as it occurs in nature, and then into the SNO lattice. This process occurs spontaneously without the need for any external energy input. The hydrogen then bonds with oxygen anions and occupies interstitial sites among the oxygen octahedra in SmNiO 3 , contributing an electron to the d orbitals of nickel 5 . The hydrogen acts as a donor dopant in the lattice. As a result, the singly occupied Ni e g orbitals in glucose-reacted SNO (GSNO) become doubly occupied and the additional electron in the e g orbital imposes large on-site Mott–Hubbard electron–electron repulsion, leading to localization of the charge carriers and resistivity increase 1 , 12 , as shown in Fig. 1c . Such a hydrogen-induced conduction suppression serves as a sensitive platform for chemical transduction at the interface between the nickelate films and biological glucose reaction. Fig. 1 Spontaneous hydrogen transfer between perovskite and glucose–enzyme reaction. a Schematic figure of the atomic hydrogen transfer from the glucose to perovskite. The glucose oxidase (GOx) enzymes are anchored on the gold electrode via cystamine bonding (details are described in Supplementary Fig. 1 ). Figure not drawn to scale for clarity. b Reaction mechanism of glucose+SmNiO 3 transformation to gluconolactone+G-SmNiO 3 . The GOx enzyme serves as a catalyst and transfers hydrogen from glucose to SmNiO 3 , referred to as G-SmNiO 3 . The hydrogens bonded with carbons are omitted for figure clarity. c The electron filling configuration of the Ni 3 d orbitals in SmNiO 3 and G-SmNiO 3 . For the pristine SmNiO 3 , the e g orbitals are singly occupied. In the case of G-SmNiO 3 , the donors doped from the hydrogen occupy an e g orbital, resulting in large on-site columbic repulsion energy U , and localizing the charge carriers resulting in reduction of electronic conductivity Full size image Electrical characterization To demonstrate the hydrogen transfer from the glucose–GOx reaction to SNO, SNO devices with GOx-modified Au electrodes were first fabricated, as schematically shown in Fig. 2a (for details, see Supplementary Methods and Supplementary Fig. 1 ). Next, atomic force microscopy (AFM) and cyclic voltammetry (CV) measurements were performed to verify the successful decoration of GOx on Au surface. As shown in Fig. 2b , bright GOx dots were observed on the Au surface. A line scan along AB indicates the height of GOx is around 5 nm, which is consistent with the actual size of GOx 13 . The pristine Au surface is smooth with a roughness of ~0.7 nm (Supplementary Fig. 2 ). In the CV scan, a pair of reversible electron transfer peaks were observed at the position characteristic of the GOx enzyme (Fig. 2c ) 14 . No CV peak was found at this voltage region when the measurement is performed on a bare Au electrode surface (Supplementary Fig. 3 ). With these measurements, we can confirm the existence of GOx on the Au surface. The reaction between the enzyme–SNO device and glucose solution was initiated by applying a droplet (20 μL) of 0.5 M glucose solution (in deionized water (DI) water) on top of the device, as", "role": "user" }, { "content": "What if the brain could detect its own disease? Researchers have been trying to create a material that \"thinks\" like the brain does, which would be more sensitive to early signs of neurological diseases such as Parkinson's. Thinking is a long way off, but Purdue University and Argonne National Laboratory researchers have engineered a new material that can at least \"listen.\" The lingua franca is ionic currents, which help the brain perform a particular reaction, needed for something as basic as sending a signal to breathe. Detecting ions means also detecting the concentration of a molecule, which serves as an indicator of the brain's health. In a study published in Nature Communications, researchers demonstrate the ability of a quantum material to automatically receive hydrogen when placed beneath an animal model's brain slice. Quantum means that the material has electronic properties that both can't be explained by classical physics, and that give it a unique edge over other materials used in electronics, such as silicon. The edge, in this case, is strong, \"correlated\" electrons that make the material extra sensitive and extra tunable. \"The goal is to bridge the gap between how electronics think, which is via electrons, and how the brain thinks, which is via ions. This material helped us find a potential bridge,\" said Hai-Tian Zhang, a Gilbreth postdoctoral fellow in Purdue's College of Engineering and first author on the paper. In the long run, this material might even bring the ability to \"download\" your brain, the researchers say. \"Imagine putting an electronic device in the brain, so that when natural brain functions start deteriorating, a person could still retrieve memories from that device,\" said Shriram Ramanathan, a Purdue professor of materials engineering whose lab specializes in developing brain-inspired technology. \"We can confidently say that this material is a potential pathway to building a computing device that would store and transfer memories,\" he said. The researchers tested this material on two molecules: Glucose, a sugar essential for energy production, and dopamine, a chemical messenger that regulates movement, emotional responses and memory. Because dopamine amounts are typically low in the brain, and even lower for people with Parkinson's disease, detecting this chemical has been notoriously difficult. But detecting dopamine levels early would mean sooner treatment of the disease. \"This quantum material is about nine times more sensitive to dopamine than methods that we use currently in animal models,\" said Alexander Chubykin, an assistant professor of biological sciences in the Purdue Institute for Integrative Neuroscience, based in Discovery Park. The quantum material owes its sensitivity to strong interactions between so-called \"correlated electrons.\" The researchers first found that when they placed the material in contact with glucose molecules, the oxides would spontaneously grab hydrogen from the glucose via an enzyme. The same happened with dopamine released from a mouse brain slice. The strong affinity to hydrogen, as shown when researchers at Argonne National Laboratory created simulations of the experiments, allowed the material to extract atoms on its own—without a power source. \"The fact that we didn't provide power to the material for it to take in hydrogen means that it could bring very low-power electronics with high sensitivity,\" Ramanathan said. \"This could be helpful for probing unexplored environments, as well.\" The researchers also say that this material could sense the atoms of a range of molecules, beyond just glucose and dopamine. The next step is creating a way for the material to \"talk back\" to the brain. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Functional interfaces between electronics and biological matter are essential to diverse fields including health sciences and bio-engineering. Here, we report the discovery of spontaneous (no external energy input) hydrogen transfer from biological glucose reactions into SmNiO 3 , an archetypal perovskite quantum material. The enzymatic oxidation of glucose is monitored down to ~5 × 10 −16 M concentration via hydrogen transfer to the nickelate lattice. The hydrogen atoms donate electrons to the Ni d orbital and induce electron localization through strong electron correlations. By enzyme specific modification, spontaneous transfer of hydrogen from the neurotransmitter dopamine can be monitored in physiological media. We then directly interface an acute mouse brain slice onto the nickelate devices and demonstrate measurement of neurotransmitter release upon electrical stimulation of the striatum region. These results open up avenues for use of emergent physics present in quantum materials in trace detection and conveyance of bio-matter, bio-chemical sciences, and brain-machine interfaces. Introduction Functional interfaces between biological and synthetic matter can greatly benefit from hydrogen transfer, which is of broad relevance to bio-sensing and bio-chemical sciences. Sensing media that responds to low concentrations of bio-markers therefore can be relevant in this context, however, must be functional near room (or body) temperature while constantly exposed to complex biological media. As a promising candidate, the perovskite nickelate SmNiO 3 (SNO, space group Pbnm) 1 , is water-stable, and belongs to a class of strongly correlated quantum materials, whose properties are highly sensitive to the occupancy of electrons in their partially filled orbitals 2 , 3 , 4 . When doped with charge carriers, SNO shows massive electronic structure changes: For one electron/unit cell doping from hydrogen, the electrical resistance changes by ~10 orders of magnitude 5 . In previous work, perovskite nickelates have shown potential for electric field detection in salt water media 6 . Glucose is a sugar that is essential for energy production in organisms and widely serves as a model system for bio-chemical studies. In nature, glucose can be oxidized into gluconolactone by losing hydrogen in the presence of glucose oxidase (GOx) enzyme 7 , and this reaction is seen across various organisms 8 , 9 . Utilizing an external electric field, perovskite oxide nano-particles have been used for glucose detection 10 , 11 . An important strategy to understand such biological and bio-chemical reactions involves measurement of the hydrogen transfer processes. Here, we present enzyme-mediated spontaneous hydrogen transfer between glucose reaction and SNO devices, as well as interfacing perovskite devices with acute mouse brain slices. Results Reaction mechanism Figure 1a shows the schematic pathway for spontaneous atomic hydrogen transfer between glucose–GOx reaction and a perovskite, where the nickelate participates in the reaction by accepting the hydrogen in the glucose–enzyme–oxide transfer chain. The reaction mechanism is described in Fig. 1b . During the glucose–enzyme–SNO reaction, the hydrogen atoms from the glucose are first transferred to the GOx enzyme as it occurs in nature, and then into the SNO lattice. This process occurs spontaneously without the need for any external energy input. The hydrogen then bonds with oxygen anions and occupies interstitial sites among the oxygen octahedra in SmNiO 3 , contributing an electron to the d orbitals of nickel 5 . The hydrogen acts as a donor dopant in the lattice. As a result, the singly occupied Ni e g orbitals in glucose-reacted SNO (GSNO) become doubly occupied and the additional electron in the e g orbital imposes large on-site Mott–Hubbard electron–electron repulsion, leading to localization of the charge carriers and resistivity increase 1 , 12 , as shown in Fig. 1c . Such a hydrogen-induced conduction suppression serves as a sensitive platform for chemical transduction at the interface between the nickelate films and biological glucose reaction. Fig. 1 Spontaneous hydrogen transfer between perovskite and glucose–enzyme reaction. a Schematic figure of the atomic hydrogen transfer from the glucose to perovskite. The glucose oxidase (GOx) enzymes are anchored on the gold electrode via cystamine bonding (details are described in Supplementary Fig. 1 ). Figure not drawn to scale for clarity. b Reaction mechanism of glucose+SmNiO 3 transformation to gluconolactone+G-SmNiO 3 . The GOx enzyme serves as a catalyst and transfers hydrogen from glucose to SmNiO 3 , referred to as G-SmNiO 3 . The hydrogens bonded with carbons are omitted for figure clarity. c The electron filling configuration of the Ni 3 d orbitals in SmNiO 3 and G-SmNiO 3 . For the pristine SmNiO 3 , the e g orbitals are singly occupied. In the case of G-SmNiO 3 , the donors doped from the hydrogen occupy an e g orbital, resulting in large on-site columbic repulsion energy U , and localizing the charge carriers resulting in reduction of electronic conductivity Full size image Electrical characterization To demonstrate the hydrogen transfer from the glucose–GOx reaction to SNO, SNO devices with GOx-modified Au electrodes were first fabricated, as schematically shown in Fig. 2a (for details, see Supplementary Methods and Supplementary Fig. 1 ). Next, atomic force microscopy (AFM) and cyclic voltammetry (CV) measurements were performed to verify the successful decoration of GOx on Au surface. As shown in Fig. 2b , bright GOx dots were observed on the Au surface. A line scan along AB indicates the height of GOx is around 5 nm, which is consistent with the actual size of GOx 13 . The pristine Au surface is smooth with a roughness of ~0.7 nm (Supplementary Fig. 2 ). In the CV scan, a pair of reversible electron transfer peaks were observed at the position characteristic of the GOx enzyme (Fig. 2c ) 14 . No CV peak was found at this voltage region when the measurement is performed on a bare Au electrode surface (Supplementary Fig. 3 ). With these measurements, we can confirm the existence of GOx on the Au surface. The reaction between the enzyme–SNO device and glucose solution was initiated by applying a droplet (20 μL) of 0.5 M glucose solution (in deionized water (DI) water) on top of the device, as<|im_end|> <|im_start|>assistant What if the brain could detect its own disease? Researchers have been trying to create a material that "thinks" like the brain does, which would be more sensitive to early signs of neurological diseases such as Parkinson's. Thinking is a long way off, but Purdue University and Argonne National Laboratory researchers have engineered a new material that can at least "listen." The lingua franca is ionic currents, which help the brain perform a particular reaction, needed for something as basic as sending a signal to breathe. Detecting ions means also detecting the concentration of a molecule, which serves as an indicator of the brain's health. In a study published in Nature Communications, researchers demonstrate the ability of a quantum material to automatically receive hydrogen when placed beneath an animal model's brain slice. Quantum means that the material has electronic properties that both can't be explained by classical physics, and that give it a unique edge over other materials used in electronics, such as silicon. The edge, in this case, is strong, "correlated" electrons that make the material extra sensitive and extra tunable. "The goal is to bridge the gap between how electronics think, which is via electrons, and how the brain thinks, which is via ions. This material helped us find a potential bridge," said Hai-Tian Zhang, a Gilbreth postdoctoral fellow in Purdue's College of Engineering and first author on the paper. In the long run, this material might even bring the ability to "download" your brain, the researchers say. "Imagine putting an electronic device in the brain, so that when natural brain functions start deteriorating, a person could still retrieve memories from that device," said Shriram Ramanathan, a Purdue professor of materials engineering whose lab specializes in developing brain-inspired technology. "We can confidently say that this material is a potential pathway to building a computing device that would store and transfer memories," he said. The researchers tested this material on two molecules: Glucose, a sugar essential for energy production, and dopamine, a chemical messenger that regulates movement, emotional responses and memory. Because dopamine amounts are typically low in the brain, and even lower for people with Parkinson's disease, detecting this chemical has been notoriously difficult. But detecting dopamine levels early would mean sooner treatment of the disease. "This quantum material is about nine times more sensitive to dopamine than methods that we use currently in animal models," said Alexander Chubykin, an assistant professor of biological sciences in the Purdue Institute for Integrative Neuroscience, based in Discovery Park. The quantum material owes its sensitivity to strong interactions between so-called "correlated electrons." The researchers first found that when they placed the material in contact with glucose molecules, the oxides would spontaneously grab hydrogen from the glucose via an enzyme. The same happened with dopamine released from a mouse brain slice. The strong affinity to hydrogen, as shown when researchers at Argonne National Laboratory created simulations of the experiments, allowed the material to extract atoms on its own—without a power source. "The fact that we didn't provide power to the material for it to take in hydrogen means that it could bring very low-power electronics with high sensitivity," Ramanathan said. "This could be helpful for probing unexplored environments, as well." The researchers also say that this material could sense the atoms of a range of molecules, beyond just glucose and dopamine. The next step is creating a way for the material to "talk back" to the brain. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 55550, 25066, 1990, 31591, 323, 24156, 5030, 527, 7718, 311, 17226, 5151, 2737, 2890, 36788, 323, 17332, 50725, 4776, 13, 5810, 11, 584, 1934, 279, 18841, 315, 54557, 320, 2201, 9434, 4907, 1988, 8, 35784, 8481, 505, 24156, 34323, 25481, 1139, 4487, 57594, 46, 220, 18, 1174, 459, 5438, 295, 1100, 278, 824, 869, 4991, 635, 31228, 3769, 13, 578, 32011, 780, 71162, 315, 34323, 374, 41223, 1523, 311, 4056, 20, 25800, 220, 605, 25173, 845, 386, 20545, 4669, 35784, 8481, 311, 279, 52349, 349, 55372, 13, 578, 35784, 33299, 33009, 57678, 311, 279, 22652, 294, 65691, 323, 49853, 17130, 53404, 1555, 3831, 17130, 69916, 13, 3296, 49242, 3230, 17466, 11, 54557, 8481, 315, 35784, 505, 279, 90351, 16517, 66128, 649, 387, 41223, 304, 53194, 3772, 13, 1226, 1243, 6089, 3834, 459, 30883, 8814, 8271, 16363, 8800, 279, 52349, 349, 7766, 323, 20461, 19179, 315, 90351, 16517, 4984, 5304, 20314, 41959, 315, 279, 6076, 27349, 5654, 13, 4314, 3135, 1825, 709, 73234, 369, 1005, 315, 7425, 306, 22027, 3118, 304, 31228, 7384, 304, 11917, 18468, 323, 20599, 685, 315, 17332, 1474, 1683, 11, 17332, 12, 32056, 36788, 11, 323, 8271, 84315, 25066, 13, 29438, 55550, 25066, 1990, 24156, 323, 28367, 5030, 649, 19407, 8935, 505, 35784, 8481, 11, 902, 374, 315, 7353, 41961, 311, 17332, 1355, 49205, 323, 17332, 12, 32056, 36788, 13, 32252, 287, 3772, 430, 31680, 311, 3428, 32466, 315, 17332, 30004, 388, 9093, 649, 387, 9959, 304, 420, 2317, 11, 4869, 11, 2011, 387, 16003, 3221, 3130, 320, 269, 2547, 8, 9499, 1418, 15320, 15246, 311, 6485, 24156, 3772, 13, 1666, 264, 26455, 9322, 11, 279, 824, 869, 4991, 635, 52349, 349, 4487, 57594, 46, 220, 18, 320, 50, 9173, 11, 3634, 1912, 393, 11328, 76, 8, 220, 16, 1174, 374, 3090, 5594, 481, 11, 323, 17623, 311, 264, 538, 315, 16917, 49393, 31228, 7384, 11, 6832, 6012, 527, 7701, 16614, 311, 279, 66419, 315, 57678, 304, 872, 26310, 10409, 27605, 1147, 220, 17, 1174, 220, 18, 1174, 220, 19, 662, 3277, 294, 16771, 449, 6900, 35991, 11, 328, 9173, 5039, 11191, 14683, 6070, 4442, 25, 1789, 832, 17130, 79411, 2849, 97928, 505, 35784, 11, 279, 20314, 13957, 4442, 555, 4056, 605, 10373, 315, 26703, 220, 20, 662, 763, 3766, 990, 11, 824, 869, 4991, 635, 52349, 988, 617, 6982, 4754, 369, 9249, 2115, 18468, 304, 12290, 3090, 3772, 220, 21, 662, 8444, 94697, 374, 264, 13465, 430, 374, 7718, 369, 4907, 5788, 304, 44304, 323, 13882, 17482, 439, 264, 1646, 1887, 369, 17332, 12, 32056, 7978, 13, 763, 7138, 11, 34323, 649, 387, 36172, 1534, 1139, 78376, 444, 337, 533, 606, 555, 13490, 35784, 304, 279, 9546, 315, 34323, 36172, 521, 320, 15881, 87, 8, 49242, 220, 22, 1174, 323, 420, 13010, 374, 3970, 4028, 5370, 44304, 220, 23, 1174, 220, 24, 662, 10377, 4954, 459, 9434, 9249, 2115, 11, 824, 869, 4991, 635, 51180, 51593, 2320, 16641, 617, 1027, 1511, 369, 34323, 18468, 220, 605, 1174, 220, 806, 662, 1556, 3062, 8446, 311, 3619, 1778, 24156, 323, 17332, 12, 32056, 25481, 18065, 19179, 315, 279, 35784, 8481, 11618, 13, 5810, 11, 584, 3118, 49242, 82076, 54557, 35784, 8481, 1990, 34323, 13010, 323, 328, 9173, 7766, 11, 439, 1664, 439, 34284, 4628, 824, 869, 4991, 635, 7766, 449, 30883, 8814, 8271, 35354, 13, 18591, 67941, 17383, 19575, 220, 16, 64, 5039, 279, 68144, 38970, 369, 54557, 25524, 35784, 8481, 1990, 34323, 4235, 15881, 87, 13010, 323, 264, 824, 869, 4991, 635, 11, 1405, 279, 52349, 349, 91287, 304, 279, 13010, 555, 25694, 279, 35784, 304, 279, 34323, 4235, 65728, 4235, 55189, 8481, 8957, 13, 578, 13010, 17383, 374, 7633, 304, 23966, 13, 220, 16, 65, 662, 12220, 279, 34323, 4235, 65728, 4235, 50, 9173, 13010, 11, 279, 35784, 33299, 505, 279, 34323, 527, 1176, 23217, 311, 279, 12890, 87, 49242, 439, 433, 13980, 304, 7138, 11, 323, 1243, 1139, 279, 328, 9173, 55372, 13, 1115, 1920, 13980, 88558, 2085, 279, 1205, 369, 904, 9434, 4907, 1988, 13, 578, 35784, 1243, 27460, 449, 24463, 459, 919, 323, 76854, 958, 49270, 6732, 4315, 279, 24463, 18998, 1494, 291, 969, 304, 4487, 57594, 46, 220, 18, 1174, 29820, 459, 17130, 311, 279, 294, 27605, 1147, 315, 52349, 220, 20, 662, 578, 35784, 14385, 439, 264, 35558, 27420, 519, 304, 279, 55372, 13, 1666, 264, 1121, 11, 279, 86599, 25366, 22652, 384, 342, 27605, 1147, 304, 34323, 31696, 291, 328, 9173, 320, 16929, 9173, 8, 3719, 94989, 25366, 323, 279, 5217, 17130, 304, 279, 384, 342, 65691, 88381, 3544, 389, 29654, 386, 1751, 4235, 19876, 67019, 17130, 4235, 75603, 2109, 34003, 11, 6522, 311, 53404, 315, 279, 6900, 35991, 323, 22884, 1968, 5376, 220, 16, 1174, 220, 717, 1174, 439, 6982, 304, 23966, 13, 220, 16, 66, 662, 15483, 264, 35784, 38973, 390, 23985, 46735, 17482, 439, 264, 16614, 5452, 369, 11742, 1380, 23985, 520, 279, 3834, 1990, 279, 52349, 349, 12631, 323, 24156, 34323, 13010, 13, 23966, 13, 220, 16, 3165, 546, 18133, 35784, 8481, 1990, 824, 869, 4991, 635, 323, 34323, 4235, 65728, 13010, 13, 264, 328, 82149, 7216, 315, 279, 25524, 35784, 8481, 505, 279, 34323, 311, 824, 869, 4991, 635, 13, 578, 34323, 36172, 521, 320, 15881, 87, 8, 56067, 527, 78219, 389, 279, 6761, 72048, 4669, 63581, 20588, 64186, 320, 15216, 527, 7633, 304, 99371, 23966, 13, 220, 16, 7609, 19575, 539, 15107, 311, 5569, 369, 32373, 13, 293, 67941, 17383, 315, 34323, 10, 10902, 57594, 46, 220, 18, 18475, 311, 78376, 444, 337, 533, 606, 10, 38, 6354, 76, 57594, 46, 220, 18, 662, 578, 12890, 87, 49242, 17482, 439, 264, 51483, 323, 31711, 35784, 505, 34323, 311, 4487, 57594, 46, 220, 18, 1174, 14183, 311, 439, 480, 6354, 76, 57594, 46, 220, 18, 662, 578, 17055, 59405, 70241, 449, 35872, 2439, 527, 40542, 369, 7216, 32373, 13, 272, 578, 17130, 21973, 6683, 315, 279, 22652, 220, 18, 294, 27605, 1147, 304, 4487, 57594, 46, 220, 18, 323, 480, 6354, 76, 57594, 46, 220, 18, 662, 1789, 279, 66085, 4487, 57594, 46, 220, 18, 1174, 279, 384, 342, 27605, 1147, 527, 86599, 25366, 13, 763, 279, 1162, 315, 480, 6354, 76, 57594, 46, 220, 18, 1174, 279, 33149, 294, 16771, 505, 279, 35784, 48678, 459, 384, 342, 65691, 11, 13239, 304, 3544, 389, 29654, 94325, 94598, 2109, 34003, 4907, 549, 1174, 323, 2254, 4954, 279, 6900, 35991, 13239, 304, 14278, 315, 14683, 98971, 8797, 1404, 2217, 45034, 60993, 2057, 20461, 279, 35784, 8481, 505, 279, 34323, 4235, 15881, 87, 13010, 311, 328, 9173, 11, 328, 9173, 7766, 449, 12890, 87, 17515, 1908, 33150, 80390, 1051, 1176, 70554, 11, 439, 20225, 7167, 6982, 304, 23966, 13, 220, 17, 64, 320, 2000, 3649, 11, 1518, 99371, 19331, 323, 99371, 23966, 13, 220, 16, 7609, 9479, 11, 25524, 5457, 92914, 320, 8440, 44, 8, 323, 77102, 16798, 309, 33342, 320, 20161, 8, 22323, 1051, 10887, 311, 10356, 279, 6992, 20841, 315, 12890, 87, 389, 33150, 7479, 13, 1666, 6982, 304, 23966, 13, 220, 17, 65, 1174, 10107, 12890, 87, 32094, 1051, 13468, 389, 279, 33150, 7479, 13, 362, 1584, 8737, 3235, 14469, 15151, 279, 2673, 315, 12890, 87, 374, 2212, 220, 20, 26807, 11, 902, 374, 13263, 449, 279, 5150, 1404, 315, 12890, 87, 220, 1032, 662, 578, 66085, 33150, 7479, 374, 11113, 449, 264, 11413, 2136, 315, 4056, 15, 13, 22, 26807, 320, 10254, 67082, 23966, 13, 220, 17, 7609, 763, 279, 14499, 8737, 11, 264, 6857, 315, 81193, 17130, 8481, 40035, 1051, 13468, 520, 279, 2361, 29683, 315, 279, 12890, 87, 49242, 320, 30035, 13, 220, 17, 66, 883, 220, 975, 662, 2360, 14499, 16557, 574, 1766, 520, 420, 22465, 5654, 994, 279, 19179, 374, 10887, 389, 264, 12743, 33150, 72048, 7479, 320, 10254, 67082, 23966, 13, 220, 18, 7609, 3161, 1521, 22323, 11, 584, 649, 7838, 279, 14209, 315, 12890, 87, 389, 279, 33150, 7479, 13, 578, 13010, 1990, 279, 49242, 4235, 50, 9173, 3756, 323, 34323, 6425, 574, 33230, 555, 19486, 264, 7118, 11053, 320, 508, 33983, 43, 8, 315, 220, 15, 13, 20, 386, 34323, 6425, 320, 258, 409, 290, 1534, 3090, 320, 18091, 8, 3090, 8, 389, 1948, 315, 279, 3756, 11, 439, 128257, 198, 128256, 78191, 198, 3923, 422, 279, 8271, 1436, 11388, 1202, 1866, 8624, 30, 59250, 617, 1027, 4560, 311, 1893, 264, 3769, 430, 330, 339, 15872, 1, 1093, 279, 8271, 1587, 11, 902, 1053, 387, 810, 16614, 311, 4216, 12195, 315, 64908, 19338, 1778, 439, 62145, 596, 13, 53389, 374, 264, 1317, 1648, 1022, 11, 719, 73334, 3907, 323, 7793, 30052, 5165, 32184, 12074, 617, 46036, 264, 502, 3769, 430, 649, 520, 3325, 330, 37437, 1210, 578, 38172, 4381, 35847, 374, 220, 21427, 60701, 11, 902, 1520, 279, 8271, 2804, 264, 4040, 13010, 11, 4460, 369, 2555, 439, 6913, 439, 11889, 264, 8450, 311, 37397, 13, 34387, 287, 65125, 3445, 1101, 54626, 279, 20545, 315, 264, 43030, 11, 902, 17482, 439, 459, 21070, 315, 279, 8271, 596, 2890, 13, 763, 264, 4007, 4756, 304, 22037, 26545, 11, 12074, 20461, 279, 5845, 315, 264, 31228, 3769, 311, 9651, 5371, 35784, 994, 9277, 24923, 459, 10065, 1646, 596, 8271, 16363, 13, 56413, 3445, 430, 279, 3769, 706, 14683, 6012, 430, 2225, 649, 956, 387, 11497, 555, 29924, 22027, 11, 323, 430, 3041, 433, 264, 5016, 6964, 927, 1023, 7384, 1511, 304, 31591, 11, 1778, 439, 51692, 13, 578, 6964, 11, 304, 420, 1162, 11, 374, 3831, 11, 330, 6133, 9920, 1, 57678, 430, 1304, 279, 3769, 5066, 16614, 323, 5066, 11716, 481, 13, 330, 791, 5915, 374, 311, 14497, 279, 13225, 1990, 1268, 31591, 1781, 11, 902, 374, 4669, 57678, 11, 323, 1268, 279, 8271, 15849, 11, 902, 374, 4669, 65125, 13, 1115, 3769, 9087, 603, 1505, 264, 4754, 14497, 1359, 1071, 63782, 9469, 1122, 37120, 11, 264, 21456, 21152, 339, 1772, 38083, 278, 12637, 304, 73334, 596, 9304, 315, 17005, 323, 1176, 3229, 389, 279, 5684, 13, 763, 279, 1317, 1629, 11, 420, 3769, 2643, 1524, 4546, 279, 5845, 311, 330, 13181, 1, 701, 8271, 11, 279, 12074, 2019, 13, 330, 52157, 10917, 459, 14683, 3756, 304, 279, 8271, 11, 779, 430, 994, 5933, 8271, 5865, 1212, 39436, 1113, 11, 264, 1732, 1436, 2103, 17622, 19459, 505, 430, 3756, 1359, 1071, 1443, 38315, 309, 432, 13005, 14308, 11, 264, 73334, 14561, 315, 7384, 15009, 6832, 10278, 46672, 304, 11469, 8271, 53161, 5557, 13, 330, 1687, 649, 78076, 2019, 430, 420, 3769, 374, 264, 4754, 38970, 311, 4857, 264, 25213, 3756, 430, 1053, 3637, 323, 8481, 19459, 1359, 568, 1071, 13, 578, 12074, 12793, 420, 3769, 389, 1403, 35715, 25, 8444, 94697, 11, 264, 13465, 7718, 369, 4907, 5788, 11, 323, 66128, 11, 264, 11742, 50596, 430, 80412, 7351, 11, 14604, 14847, 323, 5044, 13, 9393, 66128, 15055, 527, 11383, 3428, 304, 279, 8271, 11, 323, 1524, 4827, 369, 1274, 449, 62145, 596, 8624, 11, 54626, 420, 11742, 706, 1027, 73835, 5107, 13, 2030, 54626, 66128, 5990, 4216, 1053, 3152, 31373, 6514, 315, 279, 8624, 13, 330, 2028, 31228, 3769, 374, 922, 11888, 3115, 810, 16614, 311, 66128, 1109, 5528, 430, 584, 1005, 5131, 304, 10065, 4211, 1359, 1071, 20643, 921, 20629, 8148, 11, 459, 18328, 14561, 315, 24156, 36788, 304, 279, 73334, 10181, 369, 30101, 1413, 85879, 11, 3196, 304, 39193, 5657, 13, 578, 31228, 3769, 69944, 1202, 27541, 311, 3831, 22639, 1990, 779, 19434, 330, 6133, 9920, 57678, 1210, 578, 12074, 1176, 1766, 430, 994, 814, 9277, 279, 3769, 304, 3729, 449, 34323, 35715, 11, 279, 19488, 3422, 1053, 88558, 11894, 35784, 505, 279, 34323, 4669, 459, 49242, 13, 578, 1890, 7077, 449, 66128, 6004, 505, 264, 8814, 8271, 16363, 13, 578, 3831, 51552, 311, 35784, 11, 439, 6982, 994, 12074, 520, 7793, 30052, 5165, 32184, 3549, 47590, 315, 279, 21896, 11, 5535, 279, 3769, 311, 8819, 33299, 389, 1202, 1866, 2345, 30096, 264, 2410, 2592, 13, 330, 791, 2144, 430, 584, 3287, 956, 3493, 2410, 311, 279, 3769, 369, 433, 311, 1935, 304, 35784, 3445, 430, 433, 1436, 4546, 1633, 3428, 27624, 31591, 449, 1579, 27541, 1359, 432, 13005, 14308, 1071, 13, 330, 2028, 1436, 387, 11190, 369, 84072, 653, 69331, 1171, 22484, 11, 439, 1664, 1210, 578, 12074, 1101, 2019, 430, 420, 3769, 1436, 5647, 279, 33299, 315, 264, 2134, 315, 35715, 11, 7953, 1120, 34323, 323, 66128, 13, 578, 1828, 3094, 374, 6968, 264, 1648, 369, 279, 3769, 311, 330, 36341, 1203, 1, 311, 279, 8271, 13, 220, 128257, 198 ]

2,090

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Streptococcus mutans employs a key virulence factor, three glucosyltransferase (GtfBCD) enzymes to establish cariogenic biofilms. Therefore, the inhibition of GtfBCD would provide anti-virulence therapeutics. Here a small molecule library of 500,000 small molecule compounds was screened in silico against the available crystal structure of the GtfC catalytic domain. Based on the predicted binding affinities and drug-like properties, small molecules were selected and evaluated for their ability to reduce S. mutans biofilms, as well as inhibit the activity of Gtfs. The most potent inhibitor was further characterized for Gtf binding using OctetRed instrument, which yielded low micromolar K D against GtfB and nanomolar K D against GtfC, demonstrating selectivity towards GtfC. Additionally, the lead compound did not affect the overall growth of S. mutans and commensal oral bacteria, and selectively inhibit the biofilm formation by S. mutans , indicative of its selectivity and non-bactericidal nature. The lead compound also effectively reduced cariogenicity i n vivo in a rat model of dental caries. An analog that docked poorly in the GtfC catalytic domain failed to inhibit the activity of Gtfs and S. mutans biofilms, signifying the specificity of the lead compound. This report illustrates the validity and potential of structure-based design of anti- S. mutans virulence inhibitors. Introduction Dental caries is a multifactorial disease of bacterial origin, which is characterized by the localized destruction of dental hard tissues 1 , 2 . Though the oral cavity harbors over 700 different bacterial species, Streptococcus mutans initiates the cariogenic process and remains as the key etiological agent 3 . Using key matrix producing enzymes, glucosyltransferases (Gtfs), S. mutans produces sticky glucosyl glucan polymers, which facilitate the attachment of the bacteria to the tooth surface. The glucans is a major component of the biofilm matrix that shields the microbial community from host defenses, mechanical and oxidative stresses, and orchestrates the formation of cariogenic biofilms 4 . Furthermore, copious amounts of lactic acid are produced as a byproduct of bacterial consumption of dietary sugars within the mature biofilm community, which ultimately leads to demineralization of the tooth surface, ensuing cariogenesis. Current practices to prevent dental caries remove oral bacteria non-discriminatively through chemical and physical means such as mouthwash and tooth brushing 5 . Since the biofilm assembly renders bacteria to become more resistant to antibiotics and other manipulations, these traditional approaches have had only limited success. Additionally, existing mouthwashes are often associated with adverse side effects because the use of broad-spectrum antimicrobials are often detrimental to beneficial commensal species. Selectively targeting cariogenic pathogens such as S. mutans has been explored previously, however it was found that the antimicrobial peptide also alters the overall microbiota 6 . Our increasing understanding of bacterial virulence mechanisms provides new opportunities to target and interfere with crucial virulence factors such as Gtfs. This approach has the added advantages of not only being selective, but may also help to preserve the natural microbial flora of the mouth 7 , which may avoid to exert the strong pressure to promote the development of antibiotic resistance, overcoming a major public health issue in the antibiotic era. It is well established that glucans produced by S. mutans Gtfs contribute significantly to the cariogenicity of dental biofilms. Therefore, the inhibition of the Gtf activity and the consequential glucan synthesis would impair the S. mutans virulence, which could offer an alternative strategy to prevent and treat biofilm-related diseases 8 , 9 . S . mutans harbors three Gtfs: GtfB, GtfC, and GtfD. While GtfB synthesizes pre-dominantly insoluble glucans, GtfD only produces water-soluble glucans, and GtfC can synthesize both soluble and insoluble glucans 10 , 11 , 12 . Previous studies have demonstrated that glucans produced by GtfB and GtfC are essential for the assembly of the S. mutans biofilms 4 , while glucans produced by GtfD serve not only as a primer for GtfB, but also as a source of nutrient for S. mutans and other bacteria 13 , 14 . All Gtfs are composed of three functional regions: the N-terminal variable junction region, the C-terminal glucan-binding region, and the highly conserved catalytic region in the middle, which is essential for the glucan synthesis. The crystal structural of GtfC from S. mutans has been determined 15 , which provides key molecular insights for the design and development of novel Gtf inhibitors. Polyphenolic compounds 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 that include catechins, flavonoids, proanthocyanidin oligomers, and other plant-derived analogs 24 , 25 and synthetic small molecules 26 have been studied extensively for years and were found to display modest anti-biofilm activities through modulating the expression of Gtfs of S. mutans . However, the selectivity of these bioactive compounds remains to be determined and the potency is not satisfactory for the biofilm inhibition. In the present study, novel inhibitors of S. mutans Gtfs were developed through in silico screening of commercial compound libraries against the active site of the catalytic domain from the S. mutans GtfC. A lead compound targeting Gtfs was identified, synthesized, and shown to have the ability to bind to Gtfs and inhibit S. mutans biofilm formation selectively in vitro . Furthermore, the lead compound possesses anti-virulence properties in vivo . Results Structure-based virtual screening to identify small-molecule compounds that target Gtfs and inhibit biofilm formation Taking advantage of the available crystal structure of the GtfC catalytic domain complexed with acarbose, we conducted a structure-based in silico screening of 500,000 drug-like compounds using the FlexX/LeadIT software. The top ranked small molecules, as calculated using the binding energy scores in the FlexX software, were considered based on their binding pose, potential interactions with key residues, and ease of synthesis. Due to the abundance of polar residues in the GtfC active site, several of the top scored docking scaffolds contain aromatic rings, nitro groups, and polar functional groups such as amides and heteroatoms such as sulfur, etc. A total of 90 compounds with diverse scaffolds which vary in their functional groups, hydrophobicity, and H-bond accepting/donating capacity were", "role": "user" }, { "content": "University of Alabama at Birmingham researchers have created a small molecule that prevents or impedes tooth cavities in a preclinical model. The inhibitor blocks the function of a key virulence enzyme in an oral bacterium, a molecular sabotage that is akin to throwing a monkey wrench into machinery to jam the gears. In the presence of the molecule, Streptococcus mutans—the prime bacterial cause of the tooth decay called dental caries—is unable to make the protective and sticky biofilm that allows it to glue to the tooth surface, where it eats away tooth enamel by producing lactic acid. This selective inhibition of the sticky biofilm appears to act specifically against S. mutans, and the inhibitor drastically reduced dental caries in rats fed a caries-promoting diet. \"Our compound is drug-like, non-bactericidal and easy to synthesize, and it exhibits very potent efficacy in vivo,\" the researchers explained in an article in Scientific Reports. It is \"an excellent candidate that can be developed into therapeutic drugs that prevent and treat dental caries.\" About 2.3 billion people worldwide have dental caries in their permanent teeth, according to a 2015 Global Burden of Disease study. Current practices to prevent cavities, such as mouthwash and tooth brushing, indiscriminately remove oral bacteria through chemical and physical means, and have limited success. Caries is the Latin word for rottenness. \"If we have something that can selectively take away the bacteria's ability to form biofilms, that would be a tremendous advance,\" said Sadanandan Velu, Ph.D., associate professor of chemistry in the UAB College of Arts and Sciences, and a lead researcher in the study. \"This is particularly exciting in the broad sense of targeting microbiota using chemical probes tailored to the specific pathogen within a complex microbial community,\" said Hui Wu, Ph.D., professor of pediatric dentistry, UAB School of Dentistry, director of UAB Microbiome Center, and a lead investigator in the study. \"Successful development of this selective lead inhibitor in the dental setting offers a proof of concept that selective targeting of keystone bacteria is promising for the design of new treatments,\" Wu said. \"This is relevant for many elusive human diseases as the microbiome is being linked to overall health and disease.\" Wu's expertise is bacteriology and biochemistry, and Velu's is structure-based drug design. Their interdisciplinary study also included researchers from the Department of Microbiology in the UAB School of Medicine. Research details The glucan biofilm is made by three S. mutans glucosyltransferase, or Gtf, enzymes. The crystal structure of the GtfC glucosyltransferase is known, and the UAB researchers used that structure to screen—via computer simulations—500,000 drug-like compounds for binding at the enzyme's active site. Ninety compounds with diverse scaffolds showing promise in the computer screening were purchased and tested for their ability to block biofilm formation by S. mutans in culture. Seven showed potent, low-micromolar inhibition, and one, #G43, was tested more extensively. #G43 inhibited the activity of enzymes GtfB and GtfC, with micromolar affinity for GtfB and nanomolar affinity for GtfC. #G43 did not inhibit the expression of the gtfC gene, and it did not affect growth or viability of S. mutans and several other oral bacteria tested. Also, #G43 did not inhibit biofilm production by several other oral streptococcal species. In the rat-model of dental caries, animals on a low-sucrose diet were infected with S. mutans and their teeth were treated topically with #G43 twice a day for four weeks. The #G43 treatment caused very significant reductions in enamel and dentinal caries. \"In conclusion,\" Wu and Velu wrote in their paper, \"using structure-based design, we have developed a unique low-micromolar biofilm inhibitor that targets S. mutans Gtfs through binding to key virulence factors, Gtfs.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Streptococcus mutans employs a key virulence factor, three glucosyltransferase (GtfBCD) enzymes to establish cariogenic biofilms. Therefore, the inhibition of GtfBCD would provide anti-virulence therapeutics. Here a small molecule library of 500,000 small molecule compounds was screened in silico against the available crystal structure of the GtfC catalytic domain. Based on the predicted binding affinities and drug-like properties, small molecules were selected and evaluated for their ability to reduce S. mutans biofilms, as well as inhibit the activity of Gtfs. The most potent inhibitor was further characterized for Gtf binding using OctetRed instrument, which yielded low micromolar K D against GtfB and nanomolar K D against GtfC, demonstrating selectivity towards GtfC. Additionally, the lead compound did not affect the overall growth of S. mutans and commensal oral bacteria, and selectively inhibit the biofilm formation by S. mutans , indicative of its selectivity and non-bactericidal nature. The lead compound also effectively reduced cariogenicity i n vivo in a rat model of dental caries. An analog that docked poorly in the GtfC catalytic domain failed to inhibit the activity of Gtfs and S. mutans biofilms, signifying the specificity of the lead compound. This report illustrates the validity and potential of structure-based design of anti- S. mutans virulence inhibitors. Introduction Dental caries is a multifactorial disease of bacterial origin, which is characterized by the localized destruction of dental hard tissues 1 , 2 . Though the oral cavity harbors over 700 different bacterial species, Streptococcus mutans initiates the cariogenic process and remains as the key etiological agent 3 . Using key matrix producing enzymes, glucosyltransferases (Gtfs), S. mutans produces sticky glucosyl glucan polymers, which facilitate the attachment of the bacteria to the tooth surface. The glucans is a major component of the biofilm matrix that shields the microbial community from host defenses, mechanical and oxidative stresses, and orchestrates the formation of cariogenic biofilms 4 . Furthermore, copious amounts of lactic acid are produced as a byproduct of bacterial consumption of dietary sugars within the mature biofilm community, which ultimately leads to demineralization of the tooth surface, ensuing cariogenesis. Current practices to prevent dental caries remove oral bacteria non-discriminatively through chemical and physical means such as mouthwash and tooth brushing 5 . Since the biofilm assembly renders bacteria to become more resistant to antibiotics and other manipulations, these traditional approaches have had only limited success. Additionally, existing mouthwashes are often associated with adverse side effects because the use of broad-spectrum antimicrobials are often detrimental to beneficial commensal species. Selectively targeting cariogenic pathogens such as S. mutans has been explored previously, however it was found that the antimicrobial peptide also alters the overall microbiota 6 . Our increasing understanding of bacterial virulence mechanisms provides new opportunities to target and interfere with crucial virulence factors such as Gtfs. This approach has the added advantages of not only being selective, but may also help to preserve the natural microbial flora of the mouth 7 , which may avoid to exert the strong pressure to promote the development of antibiotic resistance, overcoming a major public health issue in the antibiotic era. It is well established that glucans produced by S. mutans Gtfs contribute significantly to the cariogenicity of dental biofilms. Therefore, the inhibition of the Gtf activity and the consequential glucan synthesis would impair the S. mutans virulence, which could offer an alternative strategy to prevent and treat biofilm-related diseases 8 , 9 . S . mutans harbors three Gtfs: GtfB, GtfC, and GtfD. While GtfB synthesizes pre-dominantly insoluble glucans, GtfD only produces water-soluble glucans, and GtfC can synthesize both soluble and insoluble glucans 10 , 11 , 12 . Previous studies have demonstrated that glucans produced by GtfB and GtfC are essential for the assembly of the S. mutans biofilms 4 , while glucans produced by GtfD serve not only as a primer for GtfB, but also as a source of nutrient for S. mutans and other bacteria 13 , 14 . All Gtfs are composed of three functional regions: the N-terminal variable junction region, the C-terminal glucan-binding region, and the highly conserved catalytic region in the middle, which is essential for the glucan synthesis. The crystal structural of GtfC from S. mutans has been determined 15 , which provides key molecular insights for the design and development of novel Gtf inhibitors. Polyphenolic compounds 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 that include catechins, flavonoids, proanthocyanidin oligomers, and other plant-derived analogs 24 , 25 and synthetic small molecules 26 have been studied extensively for years and were found to display modest anti-biofilm activities through modulating the expression of Gtfs of S. mutans . However, the selectivity of these bioactive compounds remains to be determined and the potency is not satisfactory for the biofilm inhibition. In the present study, novel inhibitors of S. mutans Gtfs were developed through in silico screening of commercial compound libraries against the active site of the catalytic domain from the S. mutans GtfC. A lead compound targeting Gtfs was identified, synthesized, and shown to have the ability to bind to Gtfs and inhibit S. mutans biofilm formation selectively in vitro . Furthermore, the lead compound possesses anti-virulence properties in vivo . Results Structure-based virtual screening to identify small-molecule compounds that target Gtfs and inhibit biofilm formation Taking advantage of the available crystal structure of the GtfC catalytic domain complexed with acarbose, we conducted a structure-based in silico screening of 500,000 drug-like compounds using the FlexX/LeadIT software. The top ranked small molecules, as calculated using the binding energy scores in the FlexX software, were considered based on their binding pose, potential interactions with key residues, and ease of synthesis. Due to the abundance of polar residues in the GtfC active site, several of the top scored docking scaffolds contain aromatic rings, nitro groups, and polar functional groups such as amides and heteroatoms such as sulfur, etc. A total of 90 compounds with diverse scaffolds which vary in their functional groups, hydrophobicity, and H-bond accepting/donating capacity were<|im_end|> <|im_start|>assistant University of Alabama at Birmingham researchers have created a small molecule that prevents or impedes tooth cavities in a preclinical model. The inhibitor blocks the function of a key virulence enzyme in an oral bacterium, a molecular sabotage that is akin to throwing a monkey wrench into machinery to jam the gears. In the presence of the molecule, Streptococcus mutans—the prime bacterial cause of the tooth decay called dental caries—is unable to make the protective and sticky biofilm that allows it to glue to the tooth surface, where it eats away tooth enamel by producing lactic acid. This selective inhibition of the sticky biofilm appears to act specifically against S. mutans, and the inhibitor drastically reduced dental caries in rats fed a caries-promoting diet. "Our compound is drug-like, non-bactericidal and easy to synthesize, and it exhibits very potent efficacy in vivo," the researchers explained in an article in Scientific Reports. It is "an excellent candidate that can be developed into therapeutic drugs that prevent and treat dental caries." About 2.3 billion people worldwide have dental caries in their permanent teeth, according to a 2015 Global Burden of Disease study. Current practices to prevent cavities, such as mouthwash and tooth brushing, indiscriminately remove oral bacteria through chemical and physical means, and have limited success. Caries is the Latin word for rottenness. "If we have something that can selectively take away the bacteria's ability to form biofilms, that would be a tremendous advance," said Sadanandan Velu, Ph.D., associate professor of chemistry in the UAB College of Arts and Sciences, and a lead researcher in the study. "This is particularly exciting in the broad sense of targeting microbiota using chemical probes tailored to the specific pathogen within a complex microbial community," said Hui Wu, Ph.D., professor of pediatric dentistry, UAB School of Dentistry, director of UAB Microbiome Center, and a lead investigator in the study. "Successful development of this selective lead inhibitor in the dental setting offers a proof of concept that selective targeting of keystone bacteria is promising for the design of new treatments," Wu said. "This is relevant for many elusive human diseases as the microbiome is being linked to overall health and disease." Wu's expertise is bacteriology and biochemistry, and Velu's is structure-based drug design. Their interdisciplinary study also included researchers from the Department of Microbiology in the UAB School of Medicine. Research details The glucan biofilm is made by three S. mutans glucosyltransferase, or Gtf, enzymes. The crystal structure of the GtfC glucosyltransferase is known, and the UAB researchers used that structure to screen—via computer simulations—500,000 drug-like compounds for binding at the enzyme's active site. Ninety compounds with diverse scaffolds showing promise in the computer screening were purchased and tested for their ability to block biofilm formation by S. mutans in culture. Seven showed potent, low-micromolar inhibition, and one, #G43, was tested more extensively. #G43 inhibited the activity of enzymes GtfB and GtfC, with micromolar affinity for GtfB and nanomolar affinity for GtfC. #G43 did not inhibit the expression of the gtfC gene, and it did not affect growth or viability of S. mutans and several other oral bacteria tested. Also, #G43 did not inhibit biofilm production by several other oral streptococcal species. In the rat-model of dental caries, animals on a low-sucrose diet were infected with S. mutans and their teeth were treated topically with #G43 twice a day for four weeks. The #G43 treatment caused very significant reductions in enamel and dentinal caries. "In conclusion," Wu and Velu wrote in their paper, "using structure-based design, we have developed a unique low-micromolar biofilm inhibitor that targets S. mutans Gtfs through binding to key virulence factors, Gtfs." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 36772, 418, 511, 92411, 5318, 598, 51242, 264, 1401, 9043, 59566, 8331, 11, 2380, 30217, 437, 4010, 25163, 521, 320, 38, 9112, 5002, 35, 8, 56067, 311, 5813, 1841, 72, 29569, 17332, 66502, 13, 15636, 11, 279, 61478, 315, 480, 9112, 5002, 35, 1053, 3493, 7294, 8437, 404, 59566, 9139, 88886, 13, 5810, 264, 2678, 43030, 6875, 315, 220, 2636, 11, 931, 2678, 43030, 32246, 574, 58677, 304, 5554, 4042, 2403, 279, 2561, 26110, 6070, 315, 279, 480, 9112, 34, 34454, 70504, 8106, 13, 20817, 389, 279, 19698, 11212, 3611, 258, 1385, 323, 5623, 12970, 6012, 11, 2678, 35715, 1051, 4183, 323, 26126, 369, 872, 5845, 311, 8108, 328, 13, 5318, 598, 17332, 66502, 11, 439, 1664, 439, 69033, 279, 5820, 315, 480, 83, 3933, 13, 578, 1455, 36875, 70785, 574, 4726, 32971, 369, 480, 9112, 11212, 1701, 5020, 295, 6161, 14473, 11, 902, 58487, 3428, 19748, 442, 7569, 735, 423, 2403, 480, 9112, 33, 323, 20622, 316, 7569, 735, 423, 2403, 480, 9112, 34, 11, 45296, 3373, 1968, 7119, 480, 9112, 34, 13, 23212, 11, 279, 3063, 24549, 1550, 539, 7958, 279, 8244, 6650, 315, 328, 13, 5318, 598, 323, 1081, 729, 278, 21308, 24032, 11, 323, 82775, 69033, 279, 17332, 31255, 18488, 555, 328, 13, 5318, 598, 1174, 64005, 315, 1202, 3373, 1968, 323, 2536, 1481, 2540, 292, 26966, 7138, 13, 578, 3063, 24549, 1101, 13750, 11293, 1841, 72, 29569, 488, 602, 308, 41294, 304, 264, 11494, 1646, 315, 29106, 1841, 552, 13, 1556, 24291, 430, 28649, 291, 31555, 304, 279, 480, 9112, 34, 34454, 70504, 8106, 4745, 311, 69033, 279, 5820, 315, 480, 83, 3933, 323, 328, 13, 5318, 598, 17332, 66502, 11, 1879, 7922, 279, 76041, 315, 279, 3063, 24549, 13, 1115, 1934, 46480, 279, 32939, 323, 4754, 315, 6070, 6108, 2955, 315, 7294, 12, 328, 13, 5318, 598, 9043, 59566, 68642, 13, 29438, 48804, 1841, 552, 374, 264, 62387, 5739, 532, 8624, 315, 45964, 6371, 11, 902, 374, 32971, 555, 279, 44589, 19814, 315, 29106, 2653, 39881, 220, 16, 1174, 220, 17, 662, 18056, 279, 21308, 56429, 69566, 1105, 927, 220, 7007, 2204, 45964, 9606, 11, 36772, 418, 511, 92411, 5318, 598, 12961, 988, 279, 1841, 72, 29569, 1920, 323, 8625, 439, 279, 1401, 1880, 41314, 8479, 220, 18, 662, 12362, 1401, 6303, 17843, 56067, 11, 30217, 437, 4010, 25163, 2315, 320, 38, 83, 3933, 705, 328, 13, 5318, 598, 19159, 28502, 30217, 437, 4010, 30217, 276, 46033, 388, 11, 902, 28696, 279, 20581, 315, 279, 24032, 311, 279, 26588, 7479, 13, 578, 30217, 598, 374, 264, 3682, 3777, 315, 279, 17332, 31255, 6303, 430, 53765, 279, 75418, 4029, 505, 3552, 46616, 11, 22936, 323, 79401, 59623, 11, 323, 66228, 988, 279, 18488, 315, 1841, 72, 29569, 17332, 66502, 220, 19, 662, 24296, 11, 6293, 1245, 15055, 315, 326, 24045, 13935, 527, 9124, 439, 264, 555, 3107, 315, 45964, 15652, 315, 34625, 70913, 2949, 279, 15196, 17332, 31255, 4029, 11, 902, 13967, 11767, 311, 2486, 258, 3333, 2065, 315, 279, 26588, 7479, 11, 72758, 1841, 72, 52379, 13, 9303, 12659, 311, 5471, 29106, 1841, 552, 4148, 21308, 24032, 2536, 1773, 42710, 258, 8046, 1555, 11742, 323, 7106, 3445, 1778, 439, 11013, 70545, 323, 26588, 77826, 220, 20, 662, 8876, 279, 17332, 31255, 14956, 45382, 24032, 311, 3719, 810, 31785, 311, 46850, 323, 1023, 14951, 7607, 11, 1521, 8776, 20414, 617, 1047, 1193, 7347, 2450, 13, 23212, 11, 6484, 11013, 86, 14380, 527, 3629, 5938, 449, 31959, 3185, 6372, 1606, 279, 1005, 315, 7353, 1355, 39806, 79312, 2823, 65, 10522, 527, 3629, 65069, 311, 24629, 1081, 729, 278, 9606, 13, 8593, 3210, 25103, 1841, 72, 29569, 78284, 1778, 439, 328, 13, 5318, 598, 706, 1027, 36131, 8767, 11, 4869, 433, 574, 1766, 430, 279, 79312, 83059, 72249, 1101, 88687, 279, 8244, 53499, 6217, 220, 21, 662, 5751, 7859, 8830, 315, 45964, 9043, 59566, 24717, 5825, 502, 10708, 311, 2218, 323, 40978, 449, 16996, 9043, 59566, 9547, 1778, 439, 480, 83, 3933, 13, 1115, 5603, 706, 279, 3779, 22934, 315, 539, 1193, 1694, 44010, 11, 719, 1253, 1101, 1520, 311, 21813, 279, 5933, 75418, 82088, 315, 279, 11013, 220, 22, 1174, 902, 1253, 5766, 311, 43844, 279, 3831, 7410, 311, 12192, 279, 4500, 315, 60595, 13957, 11, 74017, 264, 3682, 586, 2890, 4360, 304, 279, 60595, 11639, 13, 1102, 374, 1664, 9749, 430, 30217, 598, 9124, 555, 328, 13, 5318, 598, 480, 83, 3933, 17210, 12207, 311, 279, 1841, 72, 29569, 488, 315, 29106, 17332, 66502, 13, 15636, 11, 279, 61478, 315, 279, 480, 9112, 5820, 323, 279, 91183, 30217, 276, 39975, 1053, 38974, 279, 328, 13, 5318, 598, 9043, 59566, 11, 902, 1436, 3085, 459, 10778, 8446, 311, 5471, 323, 4322, 17332, 31255, 14228, 19338, 220, 23, 1174, 220, 24, 662, 328, 662, 5318, 598, 69566, 1105, 2380, 480, 83, 3933, 25, 480, 9112, 33, 11, 480, 9112, 34, 11, 323, 480, 9112, 35, 13, 6104, 480, 9112, 33, 52389, 4861, 864, 1773, 8129, 18007, 85943, 41572, 30217, 598, 11, 480, 9112, 35, 1193, 19159, 3090, 1355, 337, 41572, 30217, 598, 11, 323, 480, 9112, 34, 649, 6925, 27985, 2225, 88045, 323, 85943, 41572, 30217, 598, 220, 605, 1174, 220, 806, 1174, 220, 717, 662, 30013, 7978, 617, 21091, 430, 30217, 598, 9124, 555, 480, 9112, 33, 323, 480, 9112, 34, 527, 7718, 369, 279, 14956, 315, 279, 328, 13, 5318, 598, 17332, 66502, 220, 19, 1174, 1418, 30217, 598, 9124, 555, 480, 9112, 35, 8854, 539, 1193, 439, 264, 27909, 369, 480, 9112, 33, 11, 719, 1101, 439, 264, 2592, 315, 50123, 369, 328, 13, 5318, 598, 323, 1023, 24032, 220, 1032, 1174, 220, 975, 662, 2052, 480, 83, 3933, 527, 24306, 315, 2380, 16003, 13918, 25, 279, 452, 91723, 3977, 49341, 5654, 11, 279, 356, 91723, 30217, 276, 65500, 5654, 11, 323, 279, 7701, 1615, 2841, 34454, 70504, 5654, 304, 279, 6278, 11, 902, 374, 7718, 369, 279, 30217, 276, 39975, 13, 578, 26110, 24693, 315, 480, 9112, 34, 505, 328, 13, 5318, 598, 706, 1027, 11075, 220, 868, 1174, 902, 5825, 1401, 31206, 26793, 369, 279, 2955, 323, 4500, 315, 11775, 480, 9112, 68642, 13, 19294, 15112, 7918, 32246, 220, 845, 1174, 220, 1114, 1174, 220, 972, 1174, 220, 777, 1174, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 1174, 220, 1419, 430, 2997, 59239, 331, 1354, 11, 18779, 263, 17390, 11, 463, 32329, 511, 8503, 307, 258, 55984, 69638, 11, 323, 1023, 6136, 72286, 24291, 82, 220, 1187, 1174, 220, 914, 323, 28367, 2678, 35715, 220, 1627, 617, 1027, 20041, 42817, 369, 1667, 323, 1051, 1766, 311, 3113, 27946, 7294, 1481, 822, 31255, 7640, 1555, 1491, 15853, 279, 7645, 315, 480, 83, 3933, 315, 328, 13, 5318, 598, 662, 4452, 11, 279, 3373, 1968, 315, 1521, 17332, 3104, 32246, 8625, 311, 387, 11075, 323, 279, 77229, 374, 539, 58831, 369, 279, 17332, 31255, 61478, 13, 763, 279, 3118, 4007, 11, 11775, 68642, 315, 328, 13, 5318, 598, 480, 83, 3933, 1051, 8040, 1555, 304, 5554, 4042, 23061, 315, 8518, 24549, 20797, 2403, 279, 4642, 2816, 315, 279, 34454, 70504, 8106, 505, 279, 328, 13, 5318, 598, 480, 9112, 34, 13, 362, 3063, 24549, 25103, 480, 83, 3933, 574, 11054, 11, 92106, 11, 323, 6982, 311, 617, 279, 5845, 311, 10950, 311, 480, 83, 3933, 323, 69033, 328, 13, 5318, 598, 17332, 31255, 18488, 82775, 304, 55004, 662, 24296, 11, 279, 3063, 24549, 50326, 7294, 8437, 404, 59566, 6012, 304, 41294, 662, 18591, 29696, 6108, 4200, 23061, 311, 10765, 2678, 1474, 55269, 32246, 430, 2218, 480, 83, 3933, 323, 69033, 17332, 31255, 18488, 36925, 9610, 315, 279, 2561, 26110, 6070, 315, 279, 480, 9112, 34, 34454, 70504, 8106, 6485, 291, 449, 1645, 277, 8461, 11, 584, 13375, 264, 6070, 6108, 304, 5554, 4042, 23061, 315, 220, 2636, 11, 931, 5623, 12970, 32246, 1701, 279, 27233, 55, 14, 54963, 964, 3241, 13, 578, 1948, 21682, 2678, 35715, 11, 439, 16997, 1701, 279, 11212, 4907, 12483, 304, 279, 27233, 55, 3241, 11, 1051, 6646, 3196, 389, 872, 11212, 17477, 11, 4754, 22639, 449, 1401, 71783, 11, 323, 14553, 315, 39975, 13, 24586, 311, 279, 37492, 315, 25685, 71783, 304, 279, 480, 9112, 34, 4642, 2816, 11, 3892, 315, 279, 1948, 16957, 89310, 57250, 18938, 6782, 82688, 25562, 11, 25719, 299, 5315, 11, 323, 25685, 16003, 5315, 1778, 439, 1097, 3422, 323, 30548, 78, 66650, 1778, 439, 72591, 11, 5099, 13, 362, 2860, 315, 220, 1954, 32246, 449, 17226, 57250, 18938, 902, 13592, 304, 872, 16003, 5315, 11, 17055, 764, 31906, 488, 11, 323, 473, 1481, 2159, 25694, 3529, 263, 1113, 8824, 1051, 128257, 198, 128256, 78191, 198, 31272, 315, 21272, 520, 36937, 12074, 617, 3549, 264, 2678, 43030, 430, 29034, 477, 50502, 288, 26588, 57709, 1385, 304, 264, 864, 91899, 1646, 13, 578, 70785, 10215, 279, 734, 315, 264, 1401, 9043, 59566, 49242, 304, 459, 21308, 17854, 2411, 11, 264, 31206, 80753, 430, 374, 53007, 311, 21939, 264, 39803, 60588, 1139, 26953, 311, 20673, 279, 54260, 13, 763, 279, 9546, 315, 279, 43030, 11, 36772, 418, 511, 92411, 5318, 598, 22416, 10461, 45964, 5353, 315, 279, 26588, 31815, 2663, 29106, 1841, 552, 55434, 12153, 311, 1304, 279, 29219, 323, 28502, 17332, 31255, 430, 6276, 433, 311, 38561, 311, 279, 26588, 7479, 11, 1405, 433, 50777, 3201, 26588, 92848, 555, 17843, 326, 24045, 13935, 13, 1115, 44010, 61478, 315, 279, 28502, 17332, 31255, 8111, 311, 1180, 11951, 2403, 328, 13, 5318, 598, 11, 323, 279, 70785, 48863, 11293, 29106, 1841, 552, 304, 32510, 23114, 264, 1841, 552, 66271, 11780, 10173, 13, 330, 8140, 24549, 374, 5623, 12970, 11, 2536, 1481, 2540, 292, 26966, 323, 4228, 311, 6925, 27985, 11, 323, 433, 50829, 1633, 36875, 41265, 304, 41294, 1359, 279, 12074, 11497, 304, 459, 4652, 304, 38130, 29140, 13, 1102, 374, 330, 276, 9250, 9322, 430, 649, 387, 8040, 1139, 37471, 11217, 430, 5471, 323, 4322, 29106, 1841, 552, 1210, 10180, 220, 17, 13, 18, 7239, 1274, 15603, 617, 29106, 1841, 552, 304, 872, 15690, 18311, 11, 4184, 311, 264, 220, 679, 20, 8121, 12649, 5294, 315, 31974, 4007, 13, 9303, 12659, 311, 5471, 57709, 1385, 11, 1778, 439, 11013, 70545, 323, 26588, 77826, 11, 94546, 258, 2718, 4148, 21308, 24032, 1555, 11742, 323, 7106, 3445, 11, 323, 617, 7347, 2450, 13, 3341, 552, 374, 279, 20023, 3492, 369, 78792, 2136, 13, 330, 2746, 584, 617, 2555, 430, 649, 82775, 1935, 3201, 279, 24032, 596, 5845, 311, 1376, 17332, 66502, 11, 430, 1053, 387, 264, 28040, 12178, 1359, 1071, 31781, 276, 83908, 31298, 84, 11, 2405, 920, 2637, 22712, 14561, 315, 30903, 304, 279, 549, 1905, 9304, 315, 17979, 323, 23199, 11, 323, 264, 3063, 32185, 304, 279, 4007, 13, 330, 2028, 374, 8104, 13548, 304, 279, 7353, 5647, 315, 25103, 53499, 6217, 1701, 11742, 63610, 41891, 311, 279, 3230, 1853, 11968, 2949, 264, 6485, 75418, 4029, 1359, 1071, 473, 2005, 37230, 11, 2405, 920, 2637, 14561, 315, 53166, 18653, 5050, 11, 549, 1905, 6150, 315, 43911, 5050, 11, 7690, 315, 549, 1905, 18654, 8385, 638, 5955, 11, 323, 264, 3063, 49581, 304, 279, 4007, 13, 330, 37474, 4500, 315, 420, 44010, 3063, 70785, 304, 279, 29106, 6376, 6209, 264, 11311, 315, 7434, 430, 44010, 25103, 315, 2004, 42366, 24032, 374, 26455, 369, 279, 2955, 315, 502, 22972, 1359, 37230, 1071, 13, 330, 2028, 374, 9959, 369, 1690, 66684, 3823, 19338, 439, 279, 53499, 638, 374, 1694, 10815, 311, 8244, 2890, 323, 8624, 1210, 37230, 596, 19248, 374, 17854, 31226, 323, 17332, 52755, 11, 323, 31298, 84, 596, 374, 6070, 6108, 5623, 2955, 13, 11205, 88419, 4007, 1101, 5343, 12074, 505, 279, 6011, 315, 18654, 81162, 304, 279, 549, 1905, 6150, 315, 19152, 13, 8483, 3649, 578, 30217, 276, 17332, 31255, 374, 1903, 555, 2380, 328, 13, 5318, 598, 30217, 437, 4010, 25163, 521, 11, 477, 480, 9112, 11, 56067, 13, 578, 26110, 6070, 315, 279, 480, 9112, 34, 30217, 437, 4010, 25163, 521, 374, 3967, 11, 323, 279, 549, 1905, 12074, 1511, 430, 6070, 311, 4264, 2345, 20708, 6500, 47590, 2345, 2636, 11, 931, 5623, 12970, 32246, 369, 11212, 520, 279, 49242, 596, 4642, 2816, 13, 27825, 2676, 32246, 449, 17226, 57250, 18938, 9204, 11471, 304, 279, 6500, 23061, 1051, 15075, 323, 12793, 369, 872, 5845, 311, 2565, 17332, 31255, 18488, 555, 328, 13, 5318, 598, 304, 7829, 13, 31048, 8710, 36875, 11, 3428, 1474, 292, 442, 7569, 61478, 11, 323, 832, 11, 674, 38, 3391, 11, 574, 12793, 810, 42817, 13, 674, 38, 3391, 99669, 279, 5820, 315, 56067, 480, 9112, 33, 323, 480, 9112, 34, 11, 449, 19748, 442, 7569, 51552, 369, 480, 9112, 33, 323, 20622, 316, 7569, 51552, 369, 480, 9112, 34, 13, 674, 38, 3391, 1550, 539, 69033, 279, 7645, 315, 279, 342, 9112, 34, 15207, 11, 323, 433, 1550, 539, 7958, 6650, 477, 68507, 315, 328, 13, 5318, 598, 323, 3892, 1023, 21308, 24032, 12793, 13, 7429, 11, 674, 38, 3391, 1550, 539, 69033, 17332, 31255, 5788, 555, 3892, 1023, 21308, 5527, 418, 511, 511, 5531, 9606, 13, 763, 279, 11494, 29344, 315, 29106, 1841, 552, 11, 10099, 389, 264, 3428, 1355, 1791, 25888, 10173, 1051, 29374, 449, 328, 13, 5318, 598, 323, 872, 18311, 1051, 12020, 1948, 2740, 449, 674, 38, 3391, 11157, 264, 1938, 369, 3116, 5672, 13, 578, 674, 38, 3391, 6514, 9057, 1633, 5199, 47311, 304, 92848, 323, 18653, 992, 1841, 552, 13, 330, 644, 17102, 1359, 37230, 323, 31298, 84, 6267, 304, 872, 5684, 11, 330, 985, 6070, 6108, 2955, 11, 584, 617, 8040, 264, 5016, 3428, 1474, 292, 442, 7569, 17332, 31255, 70785, 430, 11811, 328, 13, 5318, 598, 480, 83, 3933, 1555, 11212, 311, 1401, 9043, 59566, 9547, 11, 480, 83, 3933, 1210, 220, 128257, 198 ]

2,297

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Many energy storage materials undergo large volume changes during charging and discharging. The resulting stresses often lead to defect formation in the bulk, but less so in nanosized systems. Here, we capture in real time the mechanism of one such transformation—the hydrogenation of single-crystalline palladium nanocubes from 15 to 80 nm—to better understand the reason for this durability. First, using environmental scanning transmission electron microscopy, we monitor the hydrogen absorption process in real time with 3 nm resolution. Then, using dark-field imaging, we structurally examine the reaction intermediates with 1 nm resolution. The reaction proceeds through nucleation and growth of the new phase in corners of the nanocubes. As the hydrogenated phase propagates across the particles, portions of the lattice misorient by 1.5%, diminishing crystal quality. Once transformed, all the particles explored return to a pristine state. The nanoparticles’ ability to remove crystallographic imperfections renders them more durable than their bulk counterparts. Introduction The development of improved energy storage technologies is crucial for the advancement of a number of industries including large-scale alternative energy, clean transport and portable electronics 1 . Two promising strategies—electrical energy storage in batteries and chemical storage of hydrogen in metals—often rely on solute-induced phase transformations 2 , 3 , 4 . These transformations are generally accompanied by large structural changes from incorporation of the solute atom 5 , 6 . In bulk samples, the large stresses resulting from volume changes cause the formation of several misfit dislocations and eventual fracture, which reduce the cyclability of the system 7 , 8 , 9 , 10 , 11 , 12 . To address these problems, there has been a push towards nanoscale systems, as they have proven to have faster transformation kinetics and are more robust upon repeated charge/discharge cycles 13 , 14 . Recent work suggests that conducting solute introduction and removal at high rates suppresses phase separation and thus causes the reaction to proceed through a continuous solid solution 15 . The resulting lack of phase coexistence and, accordingly, the lack of interfacial strains or defects, helps to explain the increased durability. At lower rates, however, many systems undergo phase separation and thus sustain large stresses 10 , 16 , 17 , 18 , 19 , 20 , 21 . How nanoparticles exhibiting solute-induced phase transformations suffer such high stresses but remain durable remains unclear; notably, in typical systems, solute uptake induces significant volume changes on the order of 7–10% (refs 5 , 6 , 22 ). Palladium hydride serves as an excellent model to understand solute-induced phase transitions. This system is characterized by one of the oldest and most well-studied solute-driven phase transitions, with physics that closely parallel those of Li intercalation and deintercalation compounds, such as LiNiMnO 4 (refs 23 , 24 , 25 ). Moreover, the palladium hydrogen system shows fairly fast kinetics at readily attainable temperatures and pressures, allowing more accessible probing of the phase transformation thermodynamics 26 . PdH x generally exists in two face-centered cubic phases: a hydrogen-poor α phase existing at lower H 2 pressures and a hydrogen-rich β phase existing at higher H 2 pressures. The phase transformation behaviour of PdH x is well known in the bulk, but the changes at the level of individual nanoparticles are only now starting to be addressed, thanks to the development of several single-particle techniques, including in situ transmission electron microscopy (TEM) 23 , 27 , 28 , plasmonic nanospectroscopy 29 , 30 and coherent X-ray diffractive imaging 21 . These studies have demonstrated that single crystalline particles do not exhibit phase coexistence at equilibrium 23 , 29 , in contrast to multiply twinned particles 27 . Recent X-ray diffraction experiments have captured intermediates during the hydrogenation reaction, revealing the arrangement of the α and β phases and their corresponding strain profiles at one step during the hydrogenation reaction 21 . However, none of these studies reveals the nature by which the α phase transforms to the β phase in real time. Here we conduct high-resolution dynamic studies of the α to β transformation on the subparticle level. Our results not only give structural insights into the reaction intermediates but help explain the high durability of such nanoparticles in energy storage devices. An environmental TEM serves as an effective tool to study the hydrogenation of palladium in situ 31 , 32 . The ability to flow in hydrogen gas at pressures up to 600 Pa with a variable temperature stage allows us to study both structural and spectroscopic properties as a reaction occurs. For example, in palladium, the lattice constant increases by 3.7% and the bulk plasmon resonance shifts by 2 eV upon transformation from the α to the β phase 6 , 23 , 27 , 33 , 34 . Techniques such as selected area electron diffraction (SAED), dark field (DF) imaging, and scanning TEM (STEM) allow insight into the particle structure and crystallography. Electron energy loss spectroscopy (EELS) quantifies the energy lost by the electron beam as it excites a variety of processes, characterizing electronic changes in Pd 35 . Combined, these techniques allow us to image particles with sub-nanometre resolution and allow for thorough structure–function correlation. Here, we first use a combination of STEM and EELS to image the hydrogen absorption process in single crystalline Pd cubes in real time. We find that the reaction proceeds through a nucleation-and-growth pathway where the β-phase nucleates in one or more corners of the cube before establishing a (100) phase front. We then examine nanocubes using DF imaging and SAED after freezing the reaction while it is in progress to examine the various reaction intermediates in greater depth (see Supplementary Methods and Supplementary Discussion for details). This analysis suggests the development of a lattice misorientation, which disappears upon completion of the transformation. SAED patterns of representative particles that have been loaded and unloaded twice show that the diffraction spots sharpen upon loading, further underscoring that the completion of the solute absorption process can reverse the crystal quality degradation induced", "role": "user" }, { "content": "In a lab 18 feet below the Engineering Quad of Stanford University, researchers in the Dionne lab camped out with one of the most advanced microscopes in the world to capture an unimaginably small reaction. The lab members conducted arduous experiments - sometimes requiring a continuous 30 hours of work—to capture real-time, dynamic visualizations of atoms that could someday help our phone batteries last longer and our electric vehicles go farther on a single charge. Toiling underground in the tunneled labs, they recorded atoms moving in and out of nanoparticles less than 100 nanometers in size, with a resolution approaching 1 nanometer. \"The ability to directly visualize reactions in real time with such high resolution will allow us to explore many unanswered questions in the chemical and physical sciences,\" said Jen Dionne, associate professor of materials science and engineering at Stanford and senior author of the paper detailing this work, published Jan. 16 in Nature Communications. \"While the experiments are not easy, they would not be possible without the remarkable advances in electron microscopy from the past decade.\" Their experiments focused on hydrogen moving into palladium, a class of reactions known as an intercalation-driven phase transition. This reaction is physically analogous to how ions flow through a battery or fuel cell during charging and discharging. Observing this process in real time provides insight into why nanoparticles make better electrodes than bulk materials and fits into Dionne's larger interest in energy storage devices that can charge faster, hold more energy and stave off permanent failure. Technical complexity and ghosts For these experiments, the Dionne lab created palladium nanocubes, a form of nanoparticle, that ranged in size from about 15 to 80 nanometers, and then placed them in a hydrogen gas environment within an electron microscope. The researchers knew that hydrogen would change both the dimensions of the lattice and the electronic properties of the nanoparticle. They thought that, with the appropriate microscope lens and aperture configuration, techniques called scanning transmission electron microscopy and electron energy loss spectroscopy might show hydrogen uptake in real time. After months of trial and error, the results were extremely detailed, real-time videos of the changes in the particle as hydrogen was introduced. The entire process was so complicated and novel that the first time it worked, the lab didn't even have the video software running, leading them to capture their first movie success on a smartphone. Following these videos, they examined the nanocubes during intermediate stages of hydrogenation using a second technique in the microscope, called dark-field imaging, which relies on scattered electrons. In order to pause the hydrogenation process, the researchers plunged the nanocubes into an ice bath of liquid nitrogen mid-reaction, dropping their temperature to 100 degrees Kelvin (-280 F). These dark-field images served as a way to check that the application of the electron beam hadn't influenced the previous observations and allowed the researchers to see detailed structural changes during the reaction. \"With the average experiment spanning about 24 hours at this low temperature, we faced many instrument problems and called Ai Leen Koh [co-author and research scientist at Stanford's Nano Shared Facilities] at the weirdest hours of the night,\" recalled Fariah Hayee, lead co-author of the study and graduate student in the Dionne lab. \"We even encountered a 'ghost-of-the-joystick problem,' where the joystick seemed to move the sample uncontrollably for some time.\" While most electron microscopes operate with the specimen held in a vacuum, the microscope used for this research has the advanced ability to allow the researchers to introduce liquids or gases to their specimen. \"We benefit tremendously from having access to one of the best microscope facilities in the world,\" said Tarun Narayan, lead co-author of this study and recent doctoral graduate from the Dionne lab. \"Without these specific tools, we wouldn't be able to introduce hydrogen gas or cool down our samples enough to see these processes take place.\" Pushing out imperfections Aside from being a widely applicable proof of concept for this suite of visualization techniques, watching the atoms move provides greater validation for the high hopes many scientists have for nanoparticle energy storage technologies. The researchers saw the atoms move in through the corners of the nanocube and observed the formation of various imperfections within the particle as hydrogen moved within it. This sounds like an argument against the promise of nanoparticles but that's because it's not the whole story. \"The nanoparticle has the ability to self-heal,\" said Dionne. \"When you first introduce hydrogen, the particle deforms and loses its perfect crystallinity. But once the particle has absorbed as much hydrogen as it can, it transforms itself back to a perfect crystal again.\" The researchers describe this as imperfections being \"pushed out\" of the nanoparticle. This ability of the nanocube to self-heal makes it more durable, a key property needed for energy storage materials that can sustain many charge and discharge cycles. Looking toward the future As the efficiency of renewable energy generation increases, the need for higher quality energy storage is more pressing than ever. It's likely that the future of storage will rely on new chemistries and the findings of this research, including the microscopy techniques the researchers refined along the way, will apply to nearly any solution in those categories. For its part, the Dionne lab has many directions it can go from here. The team could look at a variety of material compositions, or compare how the sizes and shapes of nanoparticles affect the way they work, and, soon, take advantage of new upgrades to their microscope to study light-driven reactions. At present, Hayee has moved on to experimenting with nanorods, which have more surface area for the ions to move through, promising potentially even faster kinetics. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Many energy storage materials undergo large volume changes during charging and discharging. The resulting stresses often lead to defect formation in the bulk, but less so in nanosized systems. Here, we capture in real time the mechanism of one such transformation—the hydrogenation of single-crystalline palladium nanocubes from 15 to 80 nm—to better understand the reason for this durability. First, using environmental scanning transmission electron microscopy, we monitor the hydrogen absorption process in real time with 3 nm resolution. Then, using dark-field imaging, we structurally examine the reaction intermediates with 1 nm resolution. The reaction proceeds through nucleation and growth of the new phase in corners of the nanocubes. As the hydrogenated phase propagates across the particles, portions of the lattice misorient by 1.5%, diminishing crystal quality. Once transformed, all the particles explored return to a pristine state. The nanoparticles’ ability to remove crystallographic imperfections renders them more durable than their bulk counterparts. Introduction The development of improved energy storage technologies is crucial for the advancement of a number of industries including large-scale alternative energy, clean transport and portable electronics 1 . Two promising strategies—electrical energy storage in batteries and chemical storage of hydrogen in metals—often rely on solute-induced phase transformations 2 , 3 , 4 . These transformations are generally accompanied by large structural changes from incorporation of the solute atom 5 , 6 . In bulk samples, the large stresses resulting from volume changes cause the formation of several misfit dislocations and eventual fracture, which reduce the cyclability of the system 7 , 8 , 9 , 10 , 11 , 12 . To address these problems, there has been a push towards nanoscale systems, as they have proven to have faster transformation kinetics and are more robust upon repeated charge/discharge cycles 13 , 14 . Recent work suggests that conducting solute introduction and removal at high rates suppresses phase separation and thus causes the reaction to proceed through a continuous solid solution 15 . The resulting lack of phase coexistence and, accordingly, the lack of interfacial strains or defects, helps to explain the increased durability. At lower rates, however, many systems undergo phase separation and thus sustain large stresses 10 , 16 , 17 , 18 , 19 , 20 , 21 . How nanoparticles exhibiting solute-induced phase transformations suffer such high stresses but remain durable remains unclear; notably, in typical systems, solute uptake induces significant volume changes on the order of 7–10% (refs 5 , 6 , 22 ). Palladium hydride serves as an excellent model to understand solute-induced phase transitions. This system is characterized by one of the oldest and most well-studied solute-driven phase transitions, with physics that closely parallel those of Li intercalation and deintercalation compounds, such as LiNiMnO 4 (refs 23 , 24 , 25 ). Moreover, the palladium hydrogen system shows fairly fast kinetics at readily attainable temperatures and pressures, allowing more accessible probing of the phase transformation thermodynamics 26 . PdH x generally exists in two face-centered cubic phases: a hydrogen-poor α phase existing at lower H 2 pressures and a hydrogen-rich β phase existing at higher H 2 pressures. The phase transformation behaviour of PdH x is well known in the bulk, but the changes at the level of individual nanoparticles are only now starting to be addressed, thanks to the development of several single-particle techniques, including in situ transmission electron microscopy (TEM) 23 , 27 , 28 , plasmonic nanospectroscopy 29 , 30 and coherent X-ray diffractive imaging 21 . These studies have demonstrated that single crystalline particles do not exhibit phase coexistence at equilibrium 23 , 29 , in contrast to multiply twinned particles 27 . Recent X-ray diffraction experiments have captured intermediates during the hydrogenation reaction, revealing the arrangement of the α and β phases and their corresponding strain profiles at one step during the hydrogenation reaction 21 . However, none of these studies reveals the nature by which the α phase transforms to the β phase in real time. Here we conduct high-resolution dynamic studies of the α to β transformation on the subparticle level. Our results not only give structural insights into the reaction intermediates but help explain the high durability of such nanoparticles in energy storage devices. An environmental TEM serves as an effective tool to study the hydrogenation of palladium in situ 31 , 32 . The ability to flow in hydrogen gas at pressures up to 600 Pa with a variable temperature stage allows us to study both structural and spectroscopic properties as a reaction occurs. For example, in palladium, the lattice constant increases by 3.7% and the bulk plasmon resonance shifts by 2 eV upon transformation from the α to the β phase 6 , 23 , 27 , 33 , 34 . Techniques such as selected area electron diffraction (SAED), dark field (DF) imaging, and scanning TEM (STEM) allow insight into the particle structure and crystallography. Electron energy loss spectroscopy (EELS) quantifies the energy lost by the electron beam as it excites a variety of processes, characterizing electronic changes in Pd 35 . Combined, these techniques allow us to image particles with sub-nanometre resolution and allow for thorough structure–function correlation. Here, we first use a combination of STEM and EELS to image the hydrogen absorption process in single crystalline Pd cubes in real time. We find that the reaction proceeds through a nucleation-and-growth pathway where the β-phase nucleates in one or more corners of the cube before establishing a (100) phase front. We then examine nanocubes using DF imaging and SAED after freezing the reaction while it is in progress to examine the various reaction intermediates in greater depth (see Supplementary Methods and Supplementary Discussion for details). This analysis suggests the development of a lattice misorientation, which disappears upon completion of the transformation. SAED patterns of representative particles that have been loaded and unloaded twice show that the diffraction spots sharpen upon loading, further underscoring that the completion of the solute absorption process can reverse the crystal quality degradation induced<|im_end|> <|im_start|>assistant In a lab 18 feet below the Engineering Quad of Stanford University, researchers in the Dionne lab camped out with one of the most advanced microscopes in the world to capture an unimaginably small reaction. The lab members conducted arduous experiments - sometimes requiring a continuous 30 hours of work—to capture real-time, dynamic visualizations of atoms that could someday help our phone batteries last longer and our electric vehicles go farther on a single charge. Toiling underground in the tunneled labs, they recorded atoms moving in and out of nanoparticles less than 100 nanometers in size, with a resolution approaching 1 nanometer. "The ability to directly visualize reactions in real time with such high resolution will allow us to explore many unanswered questions in the chemical and physical sciences," said Jen Dionne, associate professor of materials science and engineering at Stanford and senior author of the paper detailing this work, published Jan. 16 in Nature Communications. "While the experiments are not easy, they would not be possible without the remarkable advances in electron microscopy from the past decade." Their experiments focused on hydrogen moving into palladium, a class of reactions known as an intercalation-driven phase transition. This reaction is physically analogous to how ions flow through a battery or fuel cell during charging and discharging. Observing this process in real time provides insight into why nanoparticles make better electrodes than bulk materials and fits into Dionne's larger interest in energy storage devices that can charge faster, hold more energy and stave off permanent failure. Technical complexity and ghosts For these experiments, the Dionne lab created palladium nanocubes, a form of nanoparticle, that ranged in size from about 15 to 80 nanometers, and then placed them in a hydrogen gas environment within an electron microscope. The researchers knew that hydrogen would change both the dimensions of the lattice and the electronic properties of the nanoparticle. They thought that, with the appropriate microscope lens and aperture configuration, techniques called scanning transmission electron microscopy and electron energy loss spectroscopy might show hydrogen uptake in real time. After months of trial and error, the results were extremely detailed, real-time videos of the changes in the particle as hydrogen was introduced. The entire process was so complicated and novel that the first time it worked, the lab didn't even have the video software running, leading them to capture their first movie success on a smartphone. Following these videos, they examined the nanocubes during intermediate stages of hydrogenation using a second technique in the microscope, called dark-field imaging, which relies on scattered electrons. In order to pause the hydrogenation process, the researchers plunged the nanocubes into an ice bath of liquid nitrogen mid-reaction, dropping their temperature to 100 degrees Kelvin (-280 F). These dark-field images served as a way to check that the application of the electron beam hadn't influenced the previous observations and allowed the researchers to see detailed structural changes during the reaction. "With the average experiment spanning about 24 hours at this low temperature, we faced many instrument problems and called Ai Leen Koh [co-author and research scientist at Stanford's Nano Shared Facilities] at the weirdest hours of the night," recalled Fariah Hayee, lead co-author of the study and graduate student in the Dionne lab. "We even encountered a 'ghost-of-the-joystick problem,' where the joystick seemed to move the sample uncontrollably for some time." While most electron microscopes operate with the specimen held in a vacuum, the microscope used for this research has the advanced ability to allow the researchers to introduce liquids or gases to their specimen. "We benefit tremendously from having access to one of the best microscope facilities in the world," said Tarun Narayan, lead co-author of this study and recent doctoral graduate from the Dionne lab. "Without these specific tools, we wouldn't be able to introduce hydrogen gas or cool down our samples enough to see these processes take place." Pushing out imperfections Aside from being a widely applicable proof of concept for this suite of visualization techniques, watching the atoms move provides greater validation for the high hopes many scientists have for nanoparticle energy storage technologies. The researchers saw the atoms move in through the corners of the nanocube and observed the formation of various imperfections within the particle as hydrogen moved within it. This sounds like an argument against the promise of nanoparticles but that's because it's not the whole story. "The nanoparticle has the ability to self-heal," said Dionne. "When you first introduce hydrogen, the particle deforms and loses its perfect crystallinity. But once the particle has absorbed as much hydrogen as it can, it transforms itself back to a perfect crystal again." The researchers describe this as imperfections being "pushed out" of the nanoparticle. This ability of the nanocube to self-heal makes it more durable, a key property needed for energy storage materials that can sustain many charge and discharge cycles. Looking toward the future As the efficiency of renewable energy generation increases, the need for higher quality energy storage is more pressing than ever. It's likely that the future of storage will rely on new chemistries and the findings of this research, including the microscopy techniques the researchers refined along the way, will apply to nearly any solution in those categories. For its part, the Dionne lab has many directions it can go from here. The team could look at a variety of material compositions, or compare how the sizes and shapes of nanoparticles affect the way they work, and, soon, take advantage of new upgrades to their microscope to study light-driven reactions. At present, Hayee has moved on to experimenting with nanorods, which have more surface area for the ions to move through, promising potentially even faster kinetics. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 9176, 4907, 5942, 7384, 37771, 3544, 8286, 4442, 2391, 23468, 323, 834, 63459, 13, 578, 13239, 59623, 3629, 3063, 311, 23011, 18488, 304, 279, 20155, 11, 719, 2753, 779, 304, 20622, 437, 1534, 6067, 13, 5810, 11, 584, 12602, 304, 1972, 892, 279, 17383, 315, 832, 1778, 18475, 22416, 35784, 367, 315, 3254, 48689, 599, 543, 483, 67597, 13786, 20622, 511, 51725, 505, 220, 868, 311, 220, 1490, 26807, 50617, 2731, 3619, 279, 2944, 369, 420, 39665, 13, 5629, 11, 1701, 12434, 36201, 18874, 17130, 92914, 11, 584, 8891, 279, 35784, 44225, 1920, 304, 1972, 892, 449, 220, 18, 26807, 11175, 13, 5112, 11, 1701, 6453, 19677, 32758, 11, 584, 2080, 43024, 21635, 279, 13010, 55275, 988, 449, 220, 16, 26807, 11175, 13, 578, 13010, 34555, 1555, 31484, 367, 323, 6650, 315, 279, 502, 10474, 304, 24359, 315, 279, 20622, 511, 51725, 13, 1666, 279, 35784, 660, 10474, 17425, 988, 4028, 279, 19252, 11, 19885, 315, 279, 55372, 5906, 15226, 555, 220, 16, 13, 20, 13689, 84153, 26110, 4367, 13, 9843, 24411, 11, 682, 279, 19252, 36131, 471, 311, 264, 66085, 1614, 13, 578, 94753, 529, 5845, 311, 4148, 26110, 848, 79173, 17190, 25384, 45382, 1124, 810, 27220, 1109, 872, 20155, 38495, 13, 29438, 578, 4500, 315, 13241, 4907, 5942, 14645, 374, 16996, 369, 279, 50925, 315, 264, 1396, 315, 19647, 2737, 3544, 13230, 10778, 4907, 11, 4335, 7710, 323, 23665, 31591, 220, 16, 662, 9220, 26455, 15174, 2345, 19493, 12381, 4907, 5942, 304, 27360, 323, 11742, 5942, 315, 35784, 304, 37182, 2345, 61917, 17631, 389, 2092, 1088, 38973, 10474, 54070, 220, 17, 1174, 220, 18, 1174, 220, 19, 662, 4314, 54070, 527, 8965, 24895, 555, 3544, 24693, 4442, 505, 88465, 315, 279, 2092, 1088, 19670, 220, 20, 1174, 220, 21, 662, 763, 20155, 10688, 11, 279, 3544, 59623, 13239, 505, 8286, 4442, 5353, 279, 18488, 315, 3892, 5906, 6410, 834, 32409, 323, 42835, 59904, 11, 902, 8108, 279, 32343, 2968, 315, 279, 1887, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 662, 2057, 2686, 1521, 5435, 11, 1070, 706, 1027, 264, 4585, 7119, 20622, 437, 2296, 6067, 11, 439, 814, 617, 17033, 311, 617, 10819, 18475, 91468, 323, 527, 810, 22514, 5304, 11763, 6900, 42610, 14215, 25492, 220, 1032, 1174, 220, 975, 662, 35390, 990, 13533, 430, 31474, 2092, 1088, 17219, 323, 17065, 520, 1579, 7969, 28321, 288, 10474, 25768, 323, 8617, 11384, 279, 13010, 311, 10570, 1555, 264, 19815, 6573, 6425, 220, 868, 662, 578, 13239, 6996, 315, 10474, 1080, 93772, 323, 11, 28178, 11, 279, 6996, 315, 958, 22974, 532, 42400, 477, 42655, 11, 8779, 311, 10552, 279, 7319, 39665, 13, 2468, 4827, 7969, 11, 4869, 11, 1690, 6067, 37771, 10474, 25768, 323, 8617, 14201, 3544, 59623, 220, 605, 1174, 220, 845, 1174, 220, 1114, 1174, 220, 972, 1174, 220, 777, 1174, 220, 508, 1174, 220, 1691, 662, 2650, 94753, 87719, 2092, 1088, 38973, 10474, 54070, 7831, 1778, 1579, 59623, 719, 7293, 27220, 8625, 25420, 26, 35146, 11, 304, 14595, 6067, 11, 2092, 1088, 69575, 90974, 5199, 8286, 4442, 389, 279, 2015, 315, 220, 22, 4235, 605, 4, 320, 16541, 220, 20, 1174, 220, 21, 1174, 220, 1313, 7609, 72460, 13786, 6409, 67, 1425, 17482, 439, 459, 9250, 1646, 311, 3619, 2092, 1088, 38973, 10474, 34692, 13, 1115, 1887, 374, 32971, 555, 832, 315, 279, 24417, 323, 1455, 1664, 5594, 664, 1142, 2092, 1088, 32505, 10474, 34692, 11, 449, 22027, 430, 15499, 15638, 1884, 315, 14851, 958, 5531, 367, 323, 409, 2295, 5531, 367, 32246, 11, 1778, 439, 14851, 57594, 44, 77, 46, 220, 19, 320, 16541, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 7609, 23674, 11, 279, 67597, 13786, 35784, 1887, 5039, 14470, 5043, 91468, 520, 31368, 36861, 481, 20472, 323, 40850, 11, 10923, 810, 15987, 84072, 315, 279, 10474, 18475, 30945, 80011, 220, 1627, 662, 393, 67, 39, 865, 8965, 6866, 304, 1403, 3663, 50482, 41999, 35530, 25, 264, 35784, 2320, 10922, 19581, 10474, 6484, 520, 4827, 473, 220, 17, 40850, 323, 264, 35784, 41947, 34318, 10474, 6484, 520, 5190, 473, 220, 17, 40850, 13, 578, 10474, 18475, 17432, 315, 393, 67, 39, 865, 374, 1664, 3967, 304, 279, 20155, 11, 719, 279, 4442, 520, 279, 2237, 315, 3927, 94753, 527, 1193, 1457, 6041, 311, 387, 20669, 11, 9523, 311, 279, 4500, 315, 3892, 3254, 2320, 7203, 12823, 11, 2737, 304, 10109, 18874, 17130, 92914, 320, 21695, 8, 220, 1419, 1174, 220, 1544, 1174, 220, 1591, 1174, 628, 300, 74689, 20622, 437, 1002, 299, 51856, 220, 1682, 1174, 220, 966, 323, 56887, 1630, 30630, 1422, 1658, 3104, 32758, 220, 1691, 662, 4314, 7978, 617, 21091, 430, 3254, 64568, 483, 19252, 656, 539, 31324, 10474, 1080, 93772, 520, 56411, 220, 1419, 1174, 220, 1682, 1174, 304, 13168, 311, 31370, 4483, 21203, 19252, 220, 1544, 662, 35390, 1630, 30630, 3722, 16597, 21896, 617, 17439, 55275, 988, 2391, 279, 35784, 367, 13010, 11, 31720, 279, 27204, 315, 279, 19581, 323, 34318, 35530, 323, 872, 12435, 26800, 21542, 520, 832, 3094, 2391, 279, 35784, 367, 13010, 220, 1691, 662, 4452, 11, 7000, 315, 1521, 7978, 21667, 279, 7138, 555, 902, 279, 19581, 10474, 29575, 311, 279, 34318, 10474, 304, 1972, 892, 13, 5810, 584, 6929, 1579, 64036, 8915, 7978, 315, 279, 19581, 311, 34318, 18475, 389, 279, 1207, 43079, 2237, 13, 5751, 3135, 539, 1193, 3041, 24693, 26793, 1139, 279, 13010, 55275, 988, 719, 1520, 10552, 279, 1579, 39665, 315, 1778, 94753, 304, 4907, 5942, 7766, 13, 1556, 12434, 76770, 17482, 439, 459, 7524, 5507, 311, 4007, 279, 35784, 367, 315, 67597, 13786, 304, 10109, 220, 2148, 1174, 220, 843, 662, 578, 5845, 311, 6530, 304, 35784, 6962, 520, 40850, 709, 311, 220, 5067, 16056, 449, 264, 3977, 9499, 6566, 6276, 603, 311, 4007, 2225, 24693, 323, 66425, 58510, 6012, 439, 264, 13010, 13980, 13, 1789, 3187, 11, 304, 67597, 13786, 11, 279, 55372, 6926, 12992, 555, 220, 18, 13, 22, 4, 323, 279, 20155, 628, 300, 1677, 58081, 29735, 555, 220, 17, 384, 53, 5304, 18475, 505, 279, 19581, 311, 279, 34318, 10474, 220, 21, 1174, 220, 1419, 1174, 220, 1544, 1174, 220, 1644, 1174, 220, 1958, 662, 66044, 1778, 439, 4183, 3158, 17130, 3722, 16597, 320, 7934, 1507, 705, 6453, 2115, 320, 5375, 8, 32758, 11, 323, 36201, 76770, 320, 15642, 8, 2187, 20616, 1139, 279, 19320, 6070, 323, 26110, 848, 1976, 88, 13, 77976, 4907, 4814, 66425, 51856, 320, 36, 98952, 8, 10484, 9803, 279, 4907, 5675, 555, 279, 17130, 24310, 439, 433, 3521, 3695, 264, 8205, 315, 11618, 11, 3752, 4954, 14683, 4442, 304, 393, 67, 220, 1758, 662, 58752, 11, 1521, 12823, 2187, 603, 311, 2217, 19252, 449, 1207, 5392, 276, 4512, 265, 11175, 323, 2187, 369, 17879, 6070, 4235, 1723, 26670, 13, 5810, 11, 584, 1176, 1005, 264, 10824, 315, 64182, 323, 469, 98952, 311, 2217, 279, 35784, 44225, 1920, 304, 3254, 64568, 483, 393, 67, 55204, 304, 1972, 892, 13, 1226, 1505, 430, 279, 13010, 34555, 1555, 264, 31484, 367, 9976, 2427, 19632, 38970, 1405, 279, 34318, 82710, 31484, 988, 304, 832, 477, 810, 24359, 315, 279, 24671, 1603, 31692, 264, 320, 1041, 8, 10474, 4156, 13, 1226, 1243, 21635, 20622, 511, 51725, 1701, 44476, 32758, 323, 16998, 1507, 1306, 43318, 279, 13010, 1418, 433, 374, 304, 5208, 311, 21635, 279, 5370, 13010, 55275, 988, 304, 7191, 8149, 320, 4151, 99371, 19331, 323, 99371, 36613, 369, 3649, 570, 1115, 6492, 13533, 279, 4500, 315, 264, 55372, 5906, 25280, 11, 902, 61370, 5304, 9954, 315, 279, 18475, 13, 16998, 1507, 12912, 315, 18740, 19252, 430, 617, 1027, 6799, 323, 88806, 11157, 1501, 430, 279, 3722, 16597, 19300, 57463, 5304, 8441, 11, 4726, 26445, 66, 5620, 430, 279, 9954, 315, 279, 2092, 1088, 44225, 1920, 649, 10134, 279, 26110, 4367, 53568, 36572, 128257, 198, 128256, 78191, 198, 644, 264, 10278, 220, 972, 7693, 3770, 279, 17005, 39118, 315, 31788, 3907, 11, 12074, 304, 279, 65157, 818, 10278, 3190, 291, 704, 449, 832, 315, 279, 1455, 11084, 8162, 82025, 304, 279, 1917, 311, 12602, 459, 87212, 2915, 2678, 13010, 13, 578, 10278, 3697, 13375, 802, 1072, 788, 21896, 482, 7170, 23537, 264, 19815, 220, 966, 4207, 315, 990, 50617, 12602, 1972, 7394, 11, 8915, 9302, 8200, 315, 33299, 430, 1436, 54108, 1520, 1057, 4641, 27360, 1566, 5129, 323, 1057, 9249, 11731, 733, 43726, 389, 264, 3254, 6900, 13, 2057, 8138, 26326, 304, 279, 11716, 818, 839, 51048, 11, 814, 12715, 33299, 7366, 304, 323, 704, 315, 94753, 2753, 1109, 220, 1041, 20622, 33504, 304, 1404, 11, 449, 264, 11175, 31047, 220, 16, 20622, 21037, 13, 330, 791, 5845, 311, 6089, 51187, 25481, 304, 1972, 892, 449, 1778, 1579, 11175, 690, 2187, 603, 311, 13488, 1690, 76547, 4860, 304, 279, 11742, 323, 7106, 36788, 1359, 1071, 25937, 65157, 818, 11, 22712, 14561, 315, 7384, 8198, 323, 15009, 520, 31788, 323, 10195, 3229, 315, 279, 5684, 45293, 420, 990, 11, 4756, 4448, 13, 220, 845, 304, 22037, 26545, 13, 330, 8142, 279, 21896, 527, 539, 4228, 11, 814, 1053, 539, 387, 3284, 2085, 279, 23649, 31003, 304, 17130, 92914, 505, 279, 3347, 13515, 1210, 11205, 21896, 10968, 389, 35784, 7366, 1139, 67597, 13786, 11, 264, 538, 315, 25481, 3967, 439, 459, 958, 5531, 367, 32505, 10474, 9320, 13, 1115, 13010, 374, 22655, 79283, 311, 1268, 65125, 6530, 1555, 264, 11863, 477, 10633, 2849, 2391, 23468, 323, 834, 63459, 13, 31943, 287, 420, 1920, 304, 1972, 892, 5825, 20616, 1139, 3249, 94753, 1304, 2731, 80390, 1109, 20155, 7384, 323, 18809, 1139, 65157, 818, 596, 8294, 2802, 304, 4907, 5942, 7766, 430, 649, 6900, 10819, 11, 3412, 810, 4907, 323, 357, 525, 1022, 15690, 8060, 13, 27766, 23965, 323, 54940, 1789, 1521, 21896, 11, 279, 65157, 818, 10278, 3549, 67597, 13786, 20622, 511, 51725, 11, 264, 1376, 315, 76307, 7203, 11, 430, 41829, 304, 1404, 505, 922, 220, 868, 311, 220, 1490, 20622, 33504, 11, 323, 1243, 9277, 1124, 304, 264, 35784, 6962, 4676, 2949, 459, 17130, 73757, 13, 578, 12074, 7020, 430, 35784, 1053, 2349, 2225, 279, 15696, 315, 279, 55372, 323, 279, 14683, 6012, 315, 279, 76307, 7203, 13, 2435, 3463, 430, 11, 449, 279, 8475, 73757, 18848, 323, 58101, 6683, 11, 12823, 2663, 36201, 18874, 17130, 92914, 323, 17130, 4907, 4814, 66425, 51856, 2643, 1501, 35784, 69575, 304, 1972, 892, 13, 4740, 4038, 315, 9269, 323, 1493, 11, 279, 3135, 1051, 9193, 11944, 11, 1972, 7394, 6946, 315, 279, 4442, 304, 279, 19320, 439, 35784, 574, 11784, 13, 578, 4553, 1920, 574, 779, 17395, 323, 11775, 430, 279, 1176, 892, 433, 6575, 11, 279, 10278, 3287, 956, 1524, 617, 279, 2835, 3241, 4401, 11, 6522, 1124, 311, 12602, 872, 1176, 5818, 2450, 389, 264, 22234, 13, 23548, 1521, 6946, 11, 814, 25078, 279, 20622, 511, 51725, 2391, 29539, 18094, 315, 35784, 367, 1701, 264, 2132, 15105, 304, 279, 73757, 11, 2663, 6453, 19677, 32758, 11, 902, 34744, 389, 38067, 57678, 13, 763, 2015, 311, 18579, 279, 35784, 367, 1920, 11, 279, 12074, 75803, 279, 20622, 511, 51725, 1139, 459, 10054, 9061, 315, 14812, 47503, 5209, 5621, 1335, 11, 26156, 872, 9499, 311, 220, 1041, 12628, 92073, 10505, 11209, 435, 570, 4314, 6453, 19677, 5448, 10434, 439, 264, 1648, 311, 1817, 430, 279, 3851, 315, 279, 17130, 24310, 19117, 956, 28160, 279, 3766, 24654, 323, 5535, 279, 12074, 311, 1518, 11944, 24693, 4442, 2391, 279, 13010, 13, 330, 2409, 279, 5578, 9526, 56886, 922, 220, 1187, 4207, 520, 420, 3428, 9499, 11, 584, 17011, 1690, 14473, 5435, 323, 2663, 57086, 2009, 268, 34975, 510, 1030, 43802, 323, 3495, 28568, 520, 31788, 596, 64051, 17423, 66389, 60, 520, 279, 98086, 5086, 4207, 315, 279, 3814, 1359, 32230, 435, 10649, 71, 18276, 2176, 11, 3063, 1080, 43802, 315, 279, 4007, 323, 19560, 5575, 304, 279, 65157, 818, 10278, 13, 330, 1687, 1524, 23926, 264, 364, 39754, 8838, 10826, 12, 7453, 31513, 3575, 2965, 1405, 279, 62689, 9508, 311, 3351, 279, 6205, 71093, 1119, 2915, 369, 1063, 892, 1210, 6104, 1455, 17130, 8162, 82025, 14816, 449, 279, 58184, 5762, 304, 264, 29302, 11, 279, 73757, 1511, 369, 420, 3495, 706, 279, 11084, 5845, 311, 2187, 279, 12074, 311, 19678, 67849, 477, 45612, 311, 872, 58184, 13, 330, 1687, 8935, 72423, 505, 3515, 2680, 311, 832, 315, 279, 1888, 73757, 13077, 304, 279, 1917, 1359, 1071, 24912, 359, 29853, 44957, 11, 3063, 1080, 43802, 315, 420, 4007, 323, 3293, 74657, 19560, 505, 279, 65157, 818, 10278, 13, 330, 27131, 1521, 3230, 7526, 11, 584, 8434, 956, 387, 3025, 311, 19678, 35784, 6962, 477, 7155, 1523, 1057, 10688, 3403, 311, 1518, 1521, 11618, 1935, 2035, 1210, 23804, 287, 704, 17190, 25384, 57194, 505, 1694, 264, 13882, 8581, 11311, 315, 7434, 369, 420, 16578, 315, 42148, 12823, 11, 10307, 279, 33299, 3351, 5825, 7191, 10741, 369, 279, 1579, 16388, 1690, 14248, 617, 369, 76307, 7203, 4907, 5942, 14645, 13, 578, 12074, 5602, 279, 33299, 3351, 304, 1555, 279, 24359, 315, 279, 20622, 511, 3845, 323, 13468, 279, 18488, 315, 5370, 17190, 25384, 2949, 279, 19320, 439, 35784, 7882, 2949, 433, 13, 1115, 10578, 1093, 459, 5811, 2403, 279, 11471, 315, 94753, 719, 430, 596, 1606, 433, 596, 539, 279, 4459, 3446, 13, 330, 791, 76307, 7203, 706, 279, 5845, 311, 659, 38435, 278, 1359, 1071, 65157, 818, 13, 330, 4599, 499, 1176, 19678, 35784, 11, 279, 19320, 409, 10008, 323, 33291, 1202, 4832, 64568, 13797, 13, 2030, 3131, 279, 19320, 706, 42101, 439, 1790, 35784, 439, 433, 649, 11, 433, 29575, 5196, 1203, 311, 264, 4832, 26110, 1578, 1210, 578, 12074, 7664, 420, 439, 17190, 25384, 1694, 330, 9254, 291, 704, 1, 315, 279, 76307, 7203, 13, 1115, 5845, 315, 279, 20622, 511, 3845, 311, 659, 38435, 278, 3727, 433, 810, 27220, 11, 264, 1401, 3424, 4460, 369, 4907, 5942, 7384, 430, 649, 14201, 1690, 6900, 323, 32643, 25492, 13, 21815, 9017, 279, 3938, 1666, 279, 15374, 315, 33268, 4907, 9659, 12992, 11, 279, 1205, 369, 5190, 4367, 4907, 5942, 374, 810, 26422, 1109, 3596, 13, 1102, 596, 4461, 430, 279, 3938, 315, 5942, 690, 17631, 389, 502, 8590, 380, 4108, 323, 279, 14955, 315, 420, 3495, 11, 2737, 279, 92914, 12823, 279, 12074, 38291, 3235, 279, 1648, 11, 690, 3881, 311, 7154, 904, 6425, 304, 1884, 11306, 13, 1789, 1202, 961, 11, 279, 65157, 818, 10278, 706, 1690, 18445, 433, 649, 733, 505, 1618, 13, 578, 2128, 1436, 1427, 520, 264, 8205, 315, 3769, 62644, 11, 477, 9616, 1268, 279, 12562, 323, 21483, 315, 94753, 7958, 279, 1648, 814, 990, 11, 323, 11, 5246, 11, 1935, 9610, 315, 502, 32714, 311, 872, 73757, 311, 4007, 3177, 32505, 25481, 13, 2468, 3118, 11, 18276, 2176, 706, 7882, 389, 311, 60257, 449, 20622, 269, 30797, 11, 902, 617, 810, 7479, 3158, 369, 279, 65125, 311, 3351, 1555, 11, 26455, 13893, 1524, 10819, 91468, 13, 220, 128257, 198 ]

2,487

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The rising demand for radiation detection materials in many applications has led to extensive research on scintillators 1 , 2 , 3 . The ability of a scintillator to absorb high-energy (kiloelectronvolt-scale) X-ray photons and convert the absorbed energy into low-energy visible photons is critical for applications in radiation exposure monitoring, security inspection, X-ray astronomy and medical radiography 4 , 5 . However, conventional scintillators are generally synthesized by crystallization at a high temperature and their radioluminescence is difficult to tune across the visible spectrum. Here we describe experimental investigations of a series of all-inorganic perovskite nanocrystals comprising caesium and lead atoms and their response to X-ray irradiation. These nanocrystal scintillators exhibit strong X-ray absorption and intense radioluminescence at visible wavelengths. Unlike bulk inorganic scintillators, these perovskite nanomaterials are solution-processable at a relatively low temperature and can generate X-ray-induced emissions that are easily tunable across the visible spectrum by tailoring the anionic component of colloidal precursors during their synthesis. These features allow the fabrication of flexible and highly sensitive X-ray detectors with a detection limit of 13 nanograys per second, which is about 400 times lower than typical medical imaging doses. We show that these colour-tunable perovskite nanocrystal scintillators can provide a convenient visualization tool for X-ray radiography, as the associated image can be directly recorded by standard digital cameras. We also demonstrate their direct integration with commercial flat-panel imagers and their utility in examining electronic circuit boards under low-dose X-ray illumination. Main The nature of the atomic constituents of a scintillator plays an important role in the radioluminescence process of the material because X-ray absorption increases exponentially with atomic number 6 . Although a wide range of scintillation materials containing heavy atoms have been characterized in detail for efficient X-ray scintillation, almost all of these materials are bulk crystals and grown by the Czochralski method 7 at temperatures above 1,700 °C. For bulk-form scintillators, such as PbWO 4 and Bi 4 Ge 3 O 12 , a certain distance of exciton migration is typically needed to transport charge carriers for subsequent trapping by luminescence centres 8 . However, excessive exciton migration is detrimental because it can cause either radioluminescence afterglow or low-efficiency X-ray scintillation. In addition, conventional activator-doped scintillators, such as thallium-activated CsI (CsI:Tl) and cerium-activated YAlO 3 (YAlO 3 :Ce), cannot produce tunable scintillation because of their fixed transition energies 9 , 10 . Despite enormous efforts, the development of scintillating materials that are low-temperature- and solution-processable, highly sensitive to X-rays and integrable to flexible substrates remains a daunting challenge. Recently, bulk crystals of organic–inorganic hybrid perovskites have been found to exhibit large X-ray stopping power 11 , 12 , 13 , 14 and the ability of efficiently converting X-ray photons into charge carriers 15 , 16 , 17 , 18 . The direct photon-to-current conversion can be attributed to the heavy Pb atom 19 and large electron–hole diffusion lengths available in organic–inorganic hybrid perovskites 20 , 21 , 22 , 23 , 24 , 25 . We reason that caesium lead halide perovskite nanocrystals 26 , which feature heavy constituent elements and tunable electronic bandgaps in the visible range, could be a promising candidate for high-efficiency X-ray scintillation. An appealing aspect of these perovskite nanocrystals is that their unique electronic structures render highly emissive triplet excited states 27 and anomalous fast emission rates 28 . By virtue of the effect of quantum confinement and increased overlap of electron and hole wavefunctions, the spatial distribution of luminescence centres and X-ray-generated excitons can be confined within the Bohr radius of the nanocrystals. Here we report experimental investigations of multicolour X-ray scintillation from a series of all-inorganic perovskite nanocrystals and demonstrate their use for ultrasensitive X-ray sensing and low-dose digital X-ray technology. In a typical bulk scintillator material, incident X-ray photons can interact with heavy atoms (for example, Pb, Tl or Ce) to produce a large number of hot electrons through the photoelectric effect 8 . These charge carriers are quickly thermalized to form low-energy excitons, which can subsequently be transported to defect centres or activators for radiative luminescence (Extended Data Fig. 1a ). We thus predict that high-energy (kiloelectronvolt-scale) X-ray photons can be converted to numerous low-energy visible photons via direct bandgap emissions in lead halide perovskite nanocrystals (Fig. 1a ). To validate this hypothesis, we prepared a series of perovskite nanocrystals (CsPbX 3 , with X = Cl, Br or I) by controlling the reaction of Cs-oleate with different PbX 2 precursors via a hot-injection solution method 29 (Extended Data Fig. 2 ). Transmission electron micrograph imaging reveals a cubic shape of the as-synthesized nanocrystals, with an average size of 9.6 nm (Fig. 1b ). Remarkably, under X-ray beam excitation the perovskite quantum dots (QDs) yield narrow and colour-tunable emissions (Fig. 1c , Extended Data Fig. 3 ). This unique property allows multicolour, high-efficiency X-ray scintillation to be realized (Fig. 1d, e , Extended Data Table 1 ). By contrast, the radioluminescence spectrum of conventional bulk scintillators (CsI:Tl, PbWO 4 , YAlO 3 :Ce and Bi 4 Ge 3 O 12 ) is almost invariable and exhibits a wide emission peak with a large full-width at half-maximum (Extended Data Fig. 1b ). This inherent limitation of conventional scintillators makes it difficult to achieve multicolour visualization of X-ray irradiation. Fig. 1: Full-colour radioluminescence from perovskite nanocrystal scintillators. a , Schematic representation of X-ray-induced luminescence of energy hν (where h is the Planck constant and ν is the frequency), generated in an all-inorganic perovskite lattice with a cubic crystal structure (see main text for details). b , Low-resolution transmission electron microscopy (TEM) image of the as-synthesized CsPbBr 3 nanocrystals. The inset shows a high-resolution TEM image of a single CsPbBr 3 nanocrystal and the corresponding electron diffraction pattern along the [100] zoom axis. c , Tunable luminescence spectra of the perovskite QDs under X-ray illumination with a dose rate of 278 μGy s −1 at a voltage of 50 kV. The material compositions of samples 1–12 are CsPbCl 3", "role": "user" }, { "content": "Medical imaging, such as X-ray or computerised tomography (CT), may soon be cheaper and safer, thanks to a recent discovery made by chemists from the National University of Singapore (NUS). Professor Liu Xiaogang and his team from the Department of Chemistry under the NUS Faculty of Science had developed novel lead halide perovskite nanocrystals that are highly sensitive to X-ray irradiation. By incorporating these nanocrystals into flat-panel X-ray imagers, the team developed a new type of detector that could sense X-rays at a radiation dose about 400 times lower than the standard dose used in current medical diagnostics. These nanocrystals are also cheaper than the inorganic crystals used in conventional X-ray imaging machines. \"Our technology uses a much lower radiation dose to deliver higher resolution images, and it can also be used for rapid, real-time X-ray imaging. It shows great promise in revolutionising imaging technology for the medical and electronics industries. For patients, this means lower cost of X-ray imaging and less radiation risk,\" said Prof Liu. The team's research breakthrough was the result of a collaborative effort with researchers from Australia, China, Hong Kong, Italy, Saudi Arabia, Singapore and the United States. It was first published in the online edition of Nature on 27 August 2018, and a patent for this novel technology has been filed. Nanocrystals light the way for better imaging X-ray imaging technology has been widely used for many applications since the 1890s. Among its many uses are medical diagnostics, homeland security, national defence, advanced manufacturing, nuclear technology, and environmental monitoring. A crucial part of X-ray imaging technology is scintillation, which is the conversion of high-energy X-ray photons to visible luminescence. Most scintillator materials used in conventional imaging devices comprise expensive and large inorganic crystals that have low light emission conversion efficiency. Hence, they will need a high dose of X-rays for effective imaging. Conventional scintillators are also usually produced using a solid-growth method at a high temperature, making it difficult to fabricate thin, large and uniform scintillator films. To overcome the limitations of current scintillator materials, Prof Liu and his team developed novel lead halide perovskite nanocrystals as an alternative scintillator material. From their experiments, the team found that their nanocrystals can detect small doses of X-ray photons and convert them into visible light. They can also be tuned to light up, or scintillate, in different colours in response to the X-rays they absorb. With these properties, these nanocrystals could achieve higher resolution X-ray imaging with lower radiation exposure. To test the application of the lead halide perovskite nanocrystals in X-ray imaging technology, the team replaced the scintillators of commercial flat-panel X-ray imagers with their nanocrystals. \"Our experiments showed that using this approach, X-ray images can be directly recorded using low-cost, widely available digital cameras, or even using cameras of mobile phones. This was not achievable using conventional bulky scintillators. In addition, we have also demonstrated that the nanocrystal scintillators can be used to examine the internal structures of electronic circuit boards. This offers a cheaper and highly sensitive alternative to current technology,\" explained Dr. Chen Qiushui, a Research Fellow with the NUS Department of Chemistry and the first author of the study. Using nanocrystals as scintillator materials could also lower the cost of X-ray imaging as these nanocrystals can be produced using simpler, less expensive processes and at a relatively low temperature. Prof Liu elaborated, \"Our creation of perovskite nanocrystal scintillators has significant implications for many fields of research and opens the door to new applications. We hope that this new class of high performance X-ray scintillator can better meet tomorrow's increasingly diversified needs.\" Next steps and commercialisation opportunities To validate the performance of their invention, the NUS scientists will be testing their abilities of the nanocrystals for longer times, and at different temperatures and humidity levels. The team is also looking to collaborate with industry partners to commercialise their novel imaging technique. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The rising demand for radiation detection materials in many applications has led to extensive research on scintillators 1 , 2 , 3 . The ability of a scintillator to absorb high-energy (kiloelectronvolt-scale) X-ray photons and convert the absorbed energy into low-energy visible photons is critical for applications in radiation exposure monitoring, security inspection, X-ray astronomy and medical radiography 4 , 5 . However, conventional scintillators are generally synthesized by crystallization at a high temperature and their radioluminescence is difficult to tune across the visible spectrum. Here we describe experimental investigations of a series of all-inorganic perovskite nanocrystals comprising caesium and lead atoms and their response to X-ray irradiation. These nanocrystal scintillators exhibit strong X-ray absorption and intense radioluminescence at visible wavelengths. Unlike bulk inorganic scintillators, these perovskite nanomaterials are solution-processable at a relatively low temperature and can generate X-ray-induced emissions that are easily tunable across the visible spectrum by tailoring the anionic component of colloidal precursors during their synthesis. These features allow the fabrication of flexible and highly sensitive X-ray detectors with a detection limit of 13 nanograys per second, which is about 400 times lower than typical medical imaging doses. We show that these colour-tunable perovskite nanocrystal scintillators can provide a convenient visualization tool for X-ray radiography, as the associated image can be directly recorded by standard digital cameras. We also demonstrate their direct integration with commercial flat-panel imagers and their utility in examining electronic circuit boards under low-dose X-ray illumination. Main The nature of the atomic constituents of a scintillator plays an important role in the radioluminescence process of the material because X-ray absorption increases exponentially with atomic number 6 . Although a wide range of scintillation materials containing heavy atoms have been characterized in detail for efficient X-ray scintillation, almost all of these materials are bulk crystals and grown by the Czochralski method 7 at temperatures above 1,700 °C. For bulk-form scintillators, such as PbWO 4 and Bi 4 Ge 3 O 12 , a certain distance of exciton migration is typically needed to transport charge carriers for subsequent trapping by luminescence centres 8 . However, excessive exciton migration is detrimental because it can cause either radioluminescence afterglow or low-efficiency X-ray scintillation. In addition, conventional activator-doped scintillators, such as thallium-activated CsI (CsI:Tl) and cerium-activated YAlO 3 (YAlO 3 :Ce), cannot produce tunable scintillation because of their fixed transition energies 9 , 10 . Despite enormous efforts, the development of scintillating materials that are low-temperature- and solution-processable, highly sensitive to X-rays and integrable to flexible substrates remains a daunting challenge. Recently, bulk crystals of organic–inorganic hybrid perovskites have been found to exhibit large X-ray stopping power 11 , 12 , 13 , 14 and the ability of efficiently converting X-ray photons into charge carriers 15 , 16 , 17 , 18 . The direct photon-to-current conversion can be attributed to the heavy Pb atom 19 and large electron–hole diffusion lengths available in organic–inorganic hybrid perovskites 20 , 21 , 22 , 23 , 24 , 25 . We reason that caesium lead halide perovskite nanocrystals 26 , which feature heavy constituent elements and tunable electronic bandgaps in the visible range, could be a promising candidate for high-efficiency X-ray scintillation. An appealing aspect of these perovskite nanocrystals is that their unique electronic structures render highly emissive triplet excited states 27 and anomalous fast emission rates 28 . By virtue of the effect of quantum confinement and increased overlap of electron and hole wavefunctions, the spatial distribution of luminescence centres and X-ray-generated excitons can be confined within the Bohr radius of the nanocrystals. Here we report experimental investigations of multicolour X-ray scintillation from a series of all-inorganic perovskite nanocrystals and demonstrate their use for ultrasensitive X-ray sensing and low-dose digital X-ray technology. In a typical bulk scintillator material, incident X-ray photons can interact with heavy atoms (for example, Pb, Tl or Ce) to produce a large number of hot electrons through the photoelectric effect 8 . These charge carriers are quickly thermalized to form low-energy excitons, which can subsequently be transported to defect centres or activators for radiative luminescence (Extended Data Fig. 1a ). We thus predict that high-energy (kiloelectronvolt-scale) X-ray photons can be converted to numerous low-energy visible photons via direct bandgap emissions in lead halide perovskite nanocrystals (Fig. 1a ). To validate this hypothesis, we prepared a series of perovskite nanocrystals (CsPbX 3 , with X = Cl, Br or I) by controlling the reaction of Cs-oleate with different PbX 2 precursors via a hot-injection solution method 29 (Extended Data Fig. 2 ). Transmission electron micrograph imaging reveals a cubic shape of the as-synthesized nanocrystals, with an average size of 9.6 nm (Fig. 1b ). Remarkably, under X-ray beam excitation the perovskite quantum dots (QDs) yield narrow and colour-tunable emissions (Fig. 1c , Extended Data Fig. 3 ). This unique property allows multicolour, high-efficiency X-ray scintillation to be realized (Fig. 1d, e , Extended Data Table 1 ). By contrast, the radioluminescence spectrum of conventional bulk scintillators (CsI:Tl, PbWO 4 , YAlO 3 :Ce and Bi 4 Ge 3 O 12 ) is almost invariable and exhibits a wide emission peak with a large full-width at half-maximum (Extended Data Fig. 1b ). This inherent limitation of conventional scintillators makes it difficult to achieve multicolour visualization of X-ray irradiation. Fig. 1: Full-colour radioluminescence from perovskite nanocrystal scintillators. a , Schematic representation of X-ray-induced luminescence of energy hν (where h is the Planck constant and ν is the frequency), generated in an all-inorganic perovskite lattice with a cubic crystal structure (see main text for details). b , Low-resolution transmission electron microscopy (TEM) image of the as-synthesized CsPbBr 3 nanocrystals. The inset shows a high-resolution TEM image of a single CsPbBr 3 nanocrystal and the corresponding electron diffraction pattern along the [100] zoom axis. c , Tunable luminescence spectra of the perovskite QDs under X-ray illumination with a dose rate of 278 μGy s −1 at a voltage of 50 kV. The material compositions of samples 1–12 are CsPbCl 3<|im_end|> <|im_start|>assistant Medical imaging, such as X-ray or computerised tomography (CT), may soon be cheaper and safer, thanks to a recent discovery made by chemists from the National University of Singapore (NUS). Professor Liu Xiaogang and his team from the Department of Chemistry under the NUS Faculty of Science had developed novel lead halide perovskite nanocrystals that are highly sensitive to X-ray irradiation. By incorporating these nanocrystals into flat-panel X-ray imagers, the team developed a new type of detector that could sense X-rays at a radiation dose about 400 times lower than the standard dose used in current medical diagnostics. These nanocrystals are also cheaper than the inorganic crystals used in conventional X-ray imaging machines. "Our technology uses a much lower radiation dose to deliver higher resolution images, and it can also be used for rapid, real-time X-ray imaging. It shows great promise in revolutionising imaging technology for the medical and electronics industries. For patients, this means lower cost of X-ray imaging and less radiation risk," said Prof Liu. The team's research breakthrough was the result of a collaborative effort with researchers from Australia, China, Hong Kong, Italy, Saudi Arabia, Singapore and the United States. It was first published in the online edition of Nature on 27 August 2018, and a patent for this novel technology has been filed. Nanocrystals light the way for better imaging X-ray imaging technology has been widely used for many applications since the 1890s. Among its many uses are medical diagnostics, homeland security, national defence, advanced manufacturing, nuclear technology, and environmental monitoring. A crucial part of X-ray imaging technology is scintillation, which is the conversion of high-energy X-ray photons to visible luminescence. Most scintillator materials used in conventional imaging devices comprise expensive and large inorganic crystals that have low light emission conversion efficiency. Hence, they will need a high dose of X-rays for effective imaging. Conventional scintillators are also usually produced using a solid-growth method at a high temperature, making it difficult to fabricate thin, large and uniform scintillator films. To overcome the limitations of current scintillator materials, Prof Liu and his team developed novel lead halide perovskite nanocrystals as an alternative scintillator material. From their experiments, the team found that their nanocrystals can detect small doses of X-ray photons and convert them into visible light. They can also be tuned to light up, or scintillate, in different colours in response to the X-rays they absorb. With these properties, these nanocrystals could achieve higher resolution X-ray imaging with lower radiation exposure. To test the application of the lead halide perovskite nanocrystals in X-ray imaging technology, the team replaced the scintillators of commercial flat-panel X-ray imagers with their nanocrystals. "Our experiments showed that using this approach, X-ray images can be directly recorded using low-cost, widely available digital cameras, or even using cameras of mobile phones. This was not achievable using conventional bulky scintillators. In addition, we have also demonstrated that the nanocrystal scintillators can be used to examine the internal structures of electronic circuit boards. This offers a cheaper and highly sensitive alternative to current technology," explained Dr. Chen Qiushui, a Research Fellow with the NUS Department of Chemistry and the first author of the study. Using nanocrystals as scintillator materials could also lower the cost of X-ray imaging as these nanocrystals can be produced using simpler, less expensive processes and at a relatively low temperature. Prof Liu elaborated, "Our creation of perovskite nanocrystal scintillators has significant implications for many fields of research and opens the door to new applications. We hope that this new class of high performance X-ray scintillator can better meet tomorrow's increasingly diversified needs." Next steps and commercialisation opportunities To validate the performance of their invention, the NUS scientists will be testing their abilities of the nanocrystals for longer times, and at different temperatures and humidity levels. The team is also looking to collaborate with industry partners to commercialise their novel imaging technique. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 16448, 7631, 369, 25407, 18468, 7384, 304, 1690, 8522, 706, 6197, 311, 16781, 3495, 389, 1156, 396, 484, 3046, 220, 16, 1174, 220, 17, 1174, 220, 18, 662, 578, 5845, 315, 264, 1156, 396, 71184, 311, 35406, 1579, 65487, 320, 86626, 4748, 70329, 97371, 13230, 8, 1630, 30630, 89235, 323, 5625, 279, 42101, 4907, 1139, 3428, 65487, 9621, 89235, 374, 9200, 369, 8522, 304, 25407, 14675, 16967, 11, 4868, 26767, 11, 1630, 30630, 82213, 323, 6593, 12164, 5814, 220, 19, 1174, 220, 20, 662, 4452, 11, 21349, 1156, 396, 484, 3046, 527, 8965, 92106, 555, 64568, 2065, 520, 264, 1579, 9499, 323, 872, 12164, 1152, 1572, 36634, 374, 5107, 311, 26306, 4028, 279, 9621, 20326, 13, 5810, 584, 7664, 22772, 26969, 315, 264, 4101, 315, 682, 3502, 61694, 824, 869, 4991, 635, 20622, 4309, 92475, 46338, 2211, 41930, 323, 3063, 33299, 323, 872, 2077, 311, 1630, 30630, 76327, 367, 13, 4314, 20622, 4309, 14272, 1156, 396, 484, 3046, 31324, 3831, 1630, 30630, 44225, 323, 19428, 12164, 1152, 1572, 36634, 520, 9621, 93959, 13, 27140, 20155, 304, 61694, 1156, 396, 484, 3046, 11, 1521, 824, 869, 4991, 635, 20622, 316, 2229, 82, 527, 6425, 51194, 481, 520, 264, 12309, 3428, 9499, 323, 649, 7068, 1630, 30630, 38973, 20748, 430, 527, 6847, 11716, 481, 4028, 279, 9621, 20326, 555, 9986, 5620, 279, 459, 21427, 3777, 315, 82048, 26966, 5956, 34291, 2391, 872, 39975, 13, 4314, 4519, 2187, 279, 59251, 315, 19303, 323, 7701, 16614, 1630, 30630, 69087, 449, 264, 18468, 4017, 315, 220, 1032, 20622, 540, 66243, 824, 2132, 11, 902, 374, 922, 220, 3443, 3115, 4827, 1109, 14595, 6593, 32758, 35130, 13, 1226, 1501, 430, 1521, 12745, 2442, 47028, 824, 869, 4991, 635, 20622, 4309, 14272, 1156, 396, 484, 3046, 649, 3493, 264, 17125, 42148, 5507, 369, 1630, 30630, 12164, 5814, 11, 439, 279, 5938, 2217, 649, 387, 6089, 12715, 555, 5410, 7528, 18632, 13, 1226, 1101, 20461, 872, 2167, 18052, 449, 8518, 10269, 32476, 6669, 388, 323, 872, 15919, 304, 38936, 14683, 16622, 21126, 1234, 3428, 1773, 974, 1630, 30630, 77052, 13, 4802, 578, 7138, 315, 279, 25524, 51720, 315, 264, 1156, 396, 71184, 11335, 459, 3062, 3560, 304, 279, 12164, 1152, 1572, 36634, 1920, 315, 279, 3769, 1606, 1630, 30630, 44225, 12992, 75251, 449, 25524, 1396, 220, 21, 662, 10541, 264, 7029, 2134, 315, 1156, 396, 67184, 7384, 8649, 8987, 33299, 617, 1027, 32971, 304, 7872, 369, 11297, 1630, 30630, 1156, 396, 67184, 11, 4661, 682, 315, 1521, 7384, 527, 20155, 48473, 323, 15042, 555, 279, 123203, 5059, 81, 1147, 6780, 1749, 220, 22, 520, 20472, 3485, 220, 16, 11, 7007, 37386, 34, 13, 1789, 20155, 8627, 1156, 396, 484, 3046, 11, 1778, 439, 98454, 23513, 220, 19, 323, 12371, 220, 19, 4323, 220, 18, 507, 220, 717, 1174, 264, 3738, 6138, 315, 25435, 263, 12172, 374, 11383, 4460, 311, 7710, 6900, 35991, 369, 17876, 93669, 555, 41263, 1572, 36634, 36282, 220, 23, 662, 4452, 11, 27639, 25435, 263, 12172, 374, 65069, 1606, 433, 649, 5353, 3060, 12164, 1152, 1572, 36634, 1306, 6200, 363, 477, 3428, 53465, 10603, 1630, 30630, 1156, 396, 67184, 13, 763, 5369, 11, 21349, 4197, 859, 1773, 16771, 1156, 396, 484, 3046, 11, 1778, 439, 270, 543, 2411, 12, 31262, 68432, 40, 320, 34645, 40, 69761, 75, 8, 323, 10362, 2411, 12, 31262, 816, 2149, 46, 220, 18, 320, 56, 2149, 46, 220, 18, 551, 43270, 705, 4250, 8356, 11716, 481, 1156, 396, 67184, 1606, 315, 872, 8521, 9320, 49969, 220, 24, 1174, 220, 605, 662, 18185, 23205, 9045, 11, 279, 4500, 315, 1156, 396, 484, 1113, 7384, 430, 527, 3428, 12, 35658, 12, 323, 6425, 51194, 481, 11, 7701, 16614, 311, 1630, 82817, 323, 8936, 481, 311, 19303, 16146, 988, 8625, 264, 57697, 8815, 13, 42096, 11, 20155, 48473, 315, 17808, 4235, 258, 61694, 26038, 824, 869, 4991, 3695, 617, 1027, 1766, 311, 31324, 3544, 1630, 30630, 23351, 2410, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 323, 279, 5845, 315, 30820, 34537, 1630, 30630, 89235, 1139, 6900, 35991, 220, 868, 1174, 220, 845, 1174, 220, 1114, 1174, 220, 972, 662, 578, 2167, 69010, 4791, 45275, 14747, 649, 387, 30706, 311, 279, 8987, 98454, 19670, 220, 777, 323, 3544, 17130, 4235, 31520, 58430, 29416, 2561, 304, 17808, 4235, 258, 61694, 26038, 824, 869, 4991, 3695, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 662, 1226, 2944, 430, 2211, 41930, 3063, 15104, 579, 824, 869, 4991, 635, 20622, 4309, 92475, 220, 1627, 1174, 902, 4668, 8987, 75164, 5540, 323, 11716, 481, 14683, 7200, 70, 2690, 304, 279, 9621, 2134, 11, 1436, 387, 264, 26455, 9322, 369, 1579, 53465, 10603, 1630, 30630, 1156, 396, 67184, 13, 1556, 33352, 13189, 315, 1521, 824, 869, 4991, 635, 20622, 4309, 92475, 374, 430, 872, 5016, 14683, 14726, 3219, 7701, 99763, 535, 99809, 12304, 5415, 220, 1544, 323, 37782, 30543, 5043, 41353, 7969, 220, 1591, 662, 3296, 35460, 315, 279, 2515, 315, 31228, 66678, 323, 7319, 28347, 315, 17130, 323, 14512, 12330, 22124, 11, 279, 29079, 8141, 315, 41263, 1572, 36634, 36282, 323, 1630, 30630, 16581, 25435, 2439, 649, 387, 45408, 2949, 279, 52450, 81, 10801, 315, 279, 20622, 4309, 92475, 13, 5810, 584, 1934, 22772, 26969, 315, 2814, 27561, 414, 1630, 30630, 1156, 396, 67184, 505, 264, 4101, 315, 682, 3502, 61694, 824, 869, 4991, 635, 20622, 4309, 92475, 323, 20461, 872, 1005, 369, 8725, 13811, 19245, 1630, 30630, 60199, 323, 3428, 1773, 974, 7528, 1630, 30630, 5557, 13, 763, 264, 14595, 20155, 1156, 396, 71184, 3769, 11, 10672, 1630, 30630, 89235, 649, 16681, 449, 8987, 33299, 320, 2000, 3187, 11, 98454, 11, 350, 75, 477, 24703, 8, 311, 8356, 264, 3544, 1396, 315, 4106, 57678, 1555, 279, 6685, 64465, 2515, 220, 23, 662, 4314, 6900, 35991, 527, 6288, 29487, 1534, 311, 1376, 3428, 65487, 25435, 2439, 11, 902, 649, 28520, 387, 40460, 311, 23011, 36282, 477, 4197, 3046, 369, 12164, 1413, 41263, 1572, 36634, 320, 54290, 2956, 23966, 13, 220, 16, 64, 7609, 1226, 8617, 7168, 430, 1579, 65487, 320, 86626, 4748, 70329, 97371, 13230, 8, 1630, 30630, 89235, 649, 387, 16489, 311, 12387, 3428, 65487, 9621, 89235, 4669, 2167, 7200, 42510, 20748, 304, 3063, 15104, 579, 824, 869, 4991, 635, 20622, 4309, 92475, 320, 30035, 13, 220, 16, 64, 7609, 2057, 9788, 420, 31178, 11, 584, 10235, 264, 4101, 315, 824, 869, 4991, 635, 20622, 4309, 92475, 320, 34645, 47, 65, 55, 220, 18, 1174, 449, 1630, 284, 2493, 11, 3320, 477, 358, 8, 555, 26991, 279, 13010, 315, 68432, 12, 1286, 349, 449, 2204, 98454, 55, 220, 17, 5956, 34291, 4669, 264, 4106, 3502, 7761, 6425, 1749, 220, 1682, 320, 54290, 2956, 23966, 13, 220, 17, 7609, 48125, 17130, 8162, 4539, 32758, 21667, 264, 41999, 6211, 315, 279, 439, 1355, 1910, 83979, 20622, 4309, 92475, 11, 449, 459, 5578, 1404, 315, 220, 24, 13, 21, 26807, 320, 30035, 13, 220, 16, 65, 7609, 83833, 2915, 11, 1234, 1630, 30630, 24310, 3521, 7709, 279, 824, 869, 4991, 635, 31228, 32094, 320, 48, 68050, 8, 7692, 15376, 323, 12745, 2442, 47028, 20748, 320, 30035, 13, 220, 16, 66, 1174, 41665, 2956, 23966, 13, 220, 18, 7609, 1115, 5016, 3424, 6276, 2814, 27561, 414, 11, 1579, 53465, 10603, 1630, 30630, 1156, 396, 67184, 311, 387, 15393, 320, 30035, 13, 220, 16, 67, 11, 384, 1174, 41665, 2956, 6771, 220, 16, 7609, 3296, 13168, 11, 279, 12164, 1152, 1572, 36634, 20326, 315, 21349, 20155, 1156, 396, 484, 3046, 320, 34645, 40, 69761, 75, 11, 98454, 23513, 220, 19, 1174, 816, 2149, 46, 220, 18, 551, 43270, 323, 12371, 220, 19, 4323, 220, 18, 507, 220, 717, 883, 374, 4661, 304, 10014, 323, 50829, 264, 7029, 41353, 16557, 449, 264, 3544, 2539, 9531, 520, 4376, 45173, 3375, 320, 54290, 2956, 23966, 13, 220, 16, 65, 7609, 1115, 38088, 20893, 315, 21349, 1156, 396, 484, 3046, 3727, 433, 5107, 311, 11322, 2814, 27561, 414, 42148, 315, 1630, 30630, 76327, 367, 13, 23966, 13, 220, 16, 25, 8797, 20024, 414, 12164, 1152, 1572, 36634, 505, 824, 869, 4991, 635, 20622, 4309, 14272, 1156, 396, 484, 3046, 13, 264, 1174, 328, 82149, 13340, 315, 1630, 30630, 38973, 41263, 1572, 36634, 315, 4907, 305, 34369, 320, 2940, 305, 374, 279, 9878, 377, 6926, 323, 99786, 374, 279, 11900, 705, 8066, 304, 459, 682, 3502, 61694, 824, 869, 4991, 635, 55372, 449, 264, 41999, 26110, 6070, 320, 4151, 1925, 1495, 369, 3649, 570, 293, 1174, 12310, 64036, 18874, 17130, 92914, 320, 21695, 8, 2217, 315, 279, 439, 1355, 1910, 83979, 68432, 47, 65, 6971, 220, 18, 20622, 4309, 92475, 13, 578, 55959, 5039, 264, 1579, 64036, 76770, 2217, 315, 264, 3254, 68432, 47, 65, 6971, 220, 18, 20622, 4309, 14272, 323, 279, 12435, 17130, 3722, 16597, 5497, 3235, 279, 510, 1041, 60, 15932, 8183, 13, 272, 1174, 28556, 481, 41263, 1572, 36634, 63697, 315, 279, 824, 869, 4991, 635, 1229, 68050, 1234, 1630, 30630, 77052, 449, 264, 19660, 4478, 315, 220, 16949, 33983, 38, 88, 274, 25173, 16, 520, 264, 22465, 315, 220, 1135, 597, 53, 13, 578, 3769, 62644, 315, 10688, 220, 16, 4235, 717, 527, 68432, 47, 65, 5176, 220, 18, 128257, 198, 128256, 78191, 198, 53654, 32758, 11, 1778, 439, 1630, 30630, 477, 6500, 4147, 10390, 5814, 320, 1182, 705, 1253, 5246, 387, 23917, 323, 30549, 11, 9523, 311, 264, 3293, 18841, 1903, 555, 8590, 1705, 505, 279, 5165, 3907, 315, 21181, 320, 45, 2078, 570, 17054, 38805, 41235, 540, 526, 323, 813, 2128, 505, 279, 6011, 315, 42846, 1234, 279, 452, 2078, 42904, 315, 10170, 1047, 8040, 11775, 3063, 15104, 579, 824, 869, 4991, 635, 20622, 4309, 92475, 430, 527, 7701, 16614, 311, 1630, 30630, 76327, 367, 13, 3296, 52913, 1521, 20622, 4309, 92475, 1139, 10269, 32476, 1630, 30630, 6669, 388, 11, 279, 2128, 8040, 264, 502, 955, 315, 32314, 430, 1436, 5647, 1630, 82817, 520, 264, 25407, 19660, 922, 220, 3443, 3115, 4827, 1109, 279, 5410, 19660, 1511, 304, 1510, 6593, 50518, 13, 4314, 20622, 4309, 92475, 527, 1101, 23917, 1109, 279, 304, 61694, 48473, 1511, 304, 21349, 1630, 30630, 32758, 12933, 13, 330, 8140, 5557, 5829, 264, 1790, 4827, 25407, 19660, 311, 6493, 5190, 11175, 5448, 11, 323, 433, 649, 1101, 387, 1511, 369, 11295, 11, 1972, 7394, 1630, 30630, 32758, 13, 1102, 5039, 2294, 11471, 304, 14110, 3876, 32758, 5557, 369, 279, 6593, 323, 31591, 19647, 13, 1789, 6978, 11, 420, 3445, 4827, 2853, 315, 1630, 30630, 32758, 323, 2753, 25407, 5326, 1359, 1071, 8626, 38805, 13, 578, 2128, 596, 3495, 42445, 574, 279, 1121, 315, 264, 40806, 5149, 449, 12074, 505, 8494, 11, 5734, 11, 19730, 18711, 11, 15704, 11, 18387, 23931, 11, 21181, 323, 279, 3723, 4273, 13, 1102, 574, 1176, 4756, 304, 279, 2930, 14002, 315, 22037, 389, 220, 1544, 6287, 220, 679, 23, 11, 323, 264, 25589, 369, 420, 11775, 5557, 706, 1027, 13019, 13, 33242, 4309, 92475, 3177, 279, 1648, 369, 2731, 32758, 1630, 30630, 32758, 5557, 706, 1027, 13882, 1511, 369, 1690, 8522, 2533, 279, 220, 9378, 15, 82, 13, 22395, 1202, 1690, 5829, 527, 6593, 50518, 11, 56336, 4868, 11, 5426, 23682, 11, 11084, 15266, 11, 11499, 5557, 11, 323, 12434, 16967, 13, 362, 16996, 961, 315, 1630, 30630, 32758, 5557, 374, 1156, 396, 67184, 11, 902, 374, 279, 14747, 315, 1579, 65487, 1630, 30630, 89235, 311, 9621, 41263, 1572, 36634, 13, 7648, 1156, 396, 71184, 7384, 1511, 304, 21349, 32758, 7766, 54350, 11646, 323, 3544, 304, 61694, 48473, 430, 617, 3428, 3177, 41353, 14747, 15374, 13, 32140, 11, 814, 690, 1205, 264, 1579, 19660, 315, 1630, 82817, 369, 7524, 32758, 13, 1221, 44322, 1156, 396, 484, 3046, 527, 1101, 6118, 9124, 1701, 264, 6573, 2427, 19632, 1749, 520, 264, 1579, 9499, 11, 3339, 433, 5107, 311, 13354, 349, 15792, 11, 3544, 323, 14113, 1156, 396, 71184, 12631, 13, 2057, 23075, 279, 9669, 315, 1510, 1156, 396, 71184, 7384, 11, 8626, 38805, 323, 813, 2128, 8040, 11775, 3063, 15104, 579, 824, 869, 4991, 635, 20622, 4309, 92475, 439, 459, 10778, 1156, 396, 71184, 3769, 13, 5659, 872, 21896, 11, 279, 2128, 1766, 430, 872, 20622, 4309, 92475, 649, 11388, 2678, 35130, 315, 1630, 30630, 89235, 323, 5625, 1124, 1139, 9621, 3177, 13, 2435, 649, 1101, 387, 33519, 311, 3177, 709, 11, 477, 1156, 396, 484, 349, 11, 304, 2204, 27230, 304, 2077, 311, 279, 1630, 82817, 814, 35406, 13, 3161, 1521, 6012, 11, 1521, 20622, 4309, 92475, 1436, 11322, 5190, 11175, 1630, 30630, 32758, 449, 4827, 25407, 14675, 13, 2057, 1296, 279, 3851, 315, 279, 3063, 15104, 579, 824, 869, 4991, 635, 20622, 4309, 92475, 304, 1630, 30630, 32758, 5557, 11, 279, 2128, 12860, 279, 1156, 396, 484, 3046, 315, 8518, 10269, 32476, 1630, 30630, 6669, 388, 449, 872, 20622, 4309, 92475, 13, 330, 8140, 21896, 8710, 430, 1701, 420, 5603, 11, 1630, 30630, 5448, 649, 387, 6089, 12715, 1701, 3428, 41238, 11, 13882, 2561, 7528, 18632, 11, 477, 1524, 1701, 18632, 315, 6505, 18084, 13, 1115, 574, 539, 89253, 1701, 21349, 78921, 1156, 396, 484, 3046, 13, 763, 5369, 11, 584, 617, 1101, 21091, 430, 279, 20622, 4309, 14272, 1156, 396, 484, 3046, 649, 387, 1511, 311, 21635, 279, 5419, 14726, 315, 14683, 16622, 21126, 13, 1115, 6209, 264, 23917, 323, 7701, 16614, 10778, 311, 1510, 5557, 1359, 11497, 2999, 13, 25507, 58094, 1136, 2005, 11, 264, 8483, 37946, 449, 279, 452, 2078, 6011, 315, 42846, 323, 279, 1176, 3229, 315, 279, 4007, 13, 12362, 20622, 4309, 92475, 439, 1156, 396, 71184, 7384, 1436, 1101, 4827, 279, 2853, 315, 1630, 30630, 32758, 439, 1521, 20622, 4309, 92475, 649, 387, 9124, 1701, 35388, 11, 2753, 11646, 11618, 323, 520, 264, 12309, 3428, 9499, 13, 8626, 38805, 25985, 660, 11, 330, 8140, 9886, 315, 824, 869, 4991, 635, 20622, 4309, 14272, 1156, 396, 484, 3046, 706, 5199, 25127, 369, 1690, 5151, 315, 3495, 323, 16264, 279, 6134, 311, 502, 8522, 13, 1226, 3987, 430, 420, 502, 538, 315, 1579, 5178, 1630, 30630, 1156, 396, 71184, 649, 2731, 3449, 16986, 596, 15098, 85957, 3966, 1210, 9479, 7504, 323, 8518, 8082, 10708, 2057, 9788, 279, 5178, 315, 872, 28229, 11, 279, 452, 2078, 14248, 690, 387, 7649, 872, 18000, 315, 279, 20622, 4309, 92475, 369, 5129, 3115, 11, 323, 520, 2204, 20472, 323, 38193, 5990, 13, 578, 2128, 374, 1101, 3411, 311, 51696, 449, 5064, 8717, 311, 8518, 1082, 872, 11775, 32758, 15105, 13, 220, 128257, 198 ]

2,419

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract An assumption of sleep and self-regulation theories is that sleep quality impacts mood which, in turn, prompts individuals to revise their work-related goals. We propose that gender differences in emotion, emotional regulation, and career aspirations layer complexity onto these basic assumptions. In the current work, we investigate the effect of daily sleep quality – via positive affect – on intentions to pursue more status and responsibility at work (i.e., aspirations), as a function of participant gender. We test our model using experience sampling methodology, surveying 135 full-time employees residing in the United States twice daily across two consecutive work weeks (10 workdays), for a total of 2,272 observations. We find that among women, but not men, sleep quality is positively related to positive affect which, in turn, relates to greater daily intentions to pursue more status and responsibility at work. We discuss the implications of our work for research and practice. Access provided by MPDL Services gGmbH c/o Max Planck Digital Library Working on a manuscript? Avoid the common mistakes “Years ago, Sheryl [Sandberg] famously told us to ‘lean in’ but as comedian Ali Wong quips, many of us are tired, and just want to “lie down’” (Ly, 2017 ). This tongue-in-cheek quote taken from a professional woman’s LinkedIn blog suggests that intentions to pursue more status and responsibility at work fluctuate as a function of physical or affective states, one of which is the state of exhaustion. Though this is an intuitive notion – that the energy one has on any given day to devote to achieving their goals will shape their daily persistence and engagement at work (Ilies & Judge, 2005 ) – scholars have generally not conceived of aspirations as impacted by daily states, such as the sense of exhaustion and crankiness following a night of poor sleep. Instead, most of the literature treats aspirations as something akin to a personality trait (e.g., Huang et al., 2014 ), or at least a ‘mid-level’ characteristic – not quite as stable as personality but certainly not as situational as behavioral intentions (e.g., Judge & Kammeyer-Mueller, 2012 ). Despite this general tendency in the literature, some research has shown that even temporary situational factors can impact career aspirations. Indeed, Steffens et al. ( 2018 ) found that participants’ aspirations fluctuated as a function of being randomly assigned to receive either positive or negative feedback about their leadership potential, thereby lending support to the notion that aspirations might also fluctuate daily in response to various events or emotional states. The opening quote, in referencing Sheryl Sandberg’s work on women and leadership, implies that women’s career aspirations might be differentially impacted by situational factors relative to men’s, a suggestion that receives support from a recent collection of research. For example, Fritz & van Knippenberg ( 2017 ) found that both women’s and men’s leadership aspirations were positively impacted by the presence of a cooperative organizational climate, but for women it was the element of perceived collaboration among employees that mattered most, whereas for men it was perceived support from the organization. Meanwhile, Joo et al. ( 2018 ) found that participating in formal leadership mentoring improved the leadership self-efficacy of men mentees more than women mentees. In the current work, we build upon this research using time-lagged experience sampling methodology (ESM) that focuses on the situational characteristic of sleep quality – a naturally varying, daily condition. Specifically, we investigate whether sleep quality influences self-reported, daily intentions to pursue more status and responsibility at work, through its influence on next-day positive affect, and the extent to which this pathway is moderated by participant gender. Figure 1 depicts our model. Fig. 1 Theoretical Model Full size image The Impact of Sleep on Work Outcomes The impact of sleep – defined as an immobile state comprised of reduced physical responsiveness (Siegel, 2005 ) – on work-related outcomes went largely overlooked for a long time (Mullins et al., 2014 ), despite that well over half of Americans report sleep problems at least a few times a week (Swanson et al., 2011 ). Fortunately, interest in sleep among management scholars has increased significantly in the past decade, and sleep is now known to impact a variety of work outcomes, such as leader behavior (Barnes et al., 2016 ), ethical conduct (Barnes et al., 2011 ), and work engagement (Kuhnel et al., 2017 ; Lanaj et al., 2014 ). Most relevant to the current work, Schilpzand et al. ( 2018 ) found that sleep quality positively predicted employees’ tendency to engage in proactive goal setting the following day at work. The mechanism underlying this effect is explained by the sleep and self-regulation model (Barnes, 2012 ), which proposes that sleep influences self-regulation (i.e., the ability to effectively manage one’s goal-directed actions; Karoly, 1993 ), a component of which is emotion regulation, or an individual’s capacity to “monitor, evaluate, and modify the nature and course of an emotional response, in order to pursue his or her goals and appropriately respond to environmental demands” (Nolen-Hoeksema, 2012 , p. 163). The effectiveness of self-regulation, in turn, impacts daily work engagement and progress toward short- and long-term work goals (Rothbard & Wilk, 2011 ). Depending on observed short-term goal progress, individuals revise their goals in an upward or downward direction (Donovan & Williams, 2003 ). Drawing from this rationale, we expect higher sleep quality would predict enhanced mood (Franzen et al., 2008 ), operationalized as daily positive affect in the current research. Positive affect, in turn, should predict greater daily intent to pursue more status and responsibility at work. Accordingly, we offer the following within-person hypotheses: Hypothesis 1 Higher sleep quality will have a positive effect on next day’s affect. Hypothesis 2 Higher affect will lead to higher daily career aspirations. Hypothesis 3 Positive daily affect will mediate the association between nightly sleep quality and career aspirations. The Moderating Role of Participant Gender Relative to men, women tend to confront more numerous and substantial obstacles in their paths to high-ranking positions", "role": "user" }, { "content": "If women want to lean in to work, they may first want to lay down for a good night's rest. A Washington State University-led study indicated that sleep quality impacted women's mood and changed how they felt about advancing in their careers. Meanwhile, men's aspirations were not impacted by sleep quality. The researchers discovered this finding in a two-week-long survey study of 135 workers in the U.S. Each day the participants first noted how well they had slept and the quality of their current mood, and then later in the day how they felt about striving for more status and responsibility at work. \"When women are getting a good night's sleep and their mood is boosted, they are more likely to be oriented in their daily intentions toward achieving status and responsibility at work,\" said lead author Leah Sheppard, an associate professor in WSU's Carson College of Business. \"If their sleep is poor and reduces their positive mood, then we saw that they were less oriented toward those goals.\" For the study published in the journal Sex Roles, Sheppard and co-authors Julie Kmec of WSU and Teng Iat Loi of University of Minnesota-Duluth surveyed full-time employees twice a day for two consecutive work weeks for a total of more than 2,200 observations. The participants answered questions about their previous night's sleep and current mood around noon every day and in the evenings answered questions about their intentions to pursue more responsibility, status, and influence at work. Both men and women reported good and bad sleep quality over the course of the study, notably with no gender difference in reported sleep quality. However, women more often reported lowered intentions to pursue more status at work on days following a night of poor sleep. The researchers can only speculate about exactly why sleep's impact on mood effects women's aspirations and not men's, but they suspect it may have to do with gender differences in emotion regulation as well as societal expectations—or some combination of these forces. Neuroscience research has shown that women tend to experience greater emotional re-activity and less emotion regulation than men, and this can be reinforced by cultural stereotypes of women as more emotional. At the same time, stereotypes of men as being more ambitious than women likely add more pressure for them to scale the corporate ladder, so perhaps poor sleep quality would be less likely to deter men from their work aspirations. These findings hold some good news for women who want to advance their careers, though, Sheppard said. For instance, they might take some practical steps to improve work aspirations, ranging from practicing meditation to help with both sleep and emotion regulation to putting better boundaries on work hours—and of course, simply striving to get better sleep. \"It's important to be able to connect aspirations to something happening outside the work environment that is controllable,\" she said. \"There are lots of things that anyone can do to have a better night's sleep and regulate mood in general.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract An assumption of sleep and self-regulation theories is that sleep quality impacts mood which, in turn, prompts individuals to revise their work-related goals. We propose that gender differences in emotion, emotional regulation, and career aspirations layer complexity onto these basic assumptions. In the current work, we investigate the effect of daily sleep quality – via positive affect – on intentions to pursue more status and responsibility at work (i.e., aspirations), as a function of participant gender. We test our model using experience sampling methodology, surveying 135 full-time employees residing in the United States twice daily across two consecutive work weeks (10 workdays), for a total of 2,272 observations. We find that among women, but not men, sleep quality is positively related to positive affect which, in turn, relates to greater daily intentions to pursue more status and responsibility at work. We discuss the implications of our work for research and practice. Access provided by MPDL Services gGmbH c/o Max Planck Digital Library Working on a manuscript? Avoid the common mistakes “Years ago, Sheryl [Sandberg] famously told us to ‘lean in’ but as comedian Ali Wong quips, many of us are tired, and just want to “lie down’” (Ly, 2017 ). This tongue-in-cheek quote taken from a professional woman’s LinkedIn blog suggests that intentions to pursue more status and responsibility at work fluctuate as a function of physical or affective states, one of which is the state of exhaustion. Though this is an intuitive notion – that the energy one has on any given day to devote to achieving their goals will shape their daily persistence and engagement at work (Ilies & Judge, 2005 ) – scholars have generally not conceived of aspirations as impacted by daily states, such as the sense of exhaustion and crankiness following a night of poor sleep. Instead, most of the literature treats aspirations as something akin to a personality trait (e.g., Huang et al., 2014 ), or at least a ‘mid-level’ characteristic – not quite as stable as personality but certainly not as situational as behavioral intentions (e.g., Judge & Kammeyer-Mueller, 2012 ). Despite this general tendency in the literature, some research has shown that even temporary situational factors can impact career aspirations. Indeed, Steffens et al. ( 2018 ) found that participants’ aspirations fluctuated as a function of being randomly assigned to receive either positive or negative feedback about their leadership potential, thereby lending support to the notion that aspirations might also fluctuate daily in response to various events or emotional states. The opening quote, in referencing Sheryl Sandberg’s work on women and leadership, implies that women’s career aspirations might be differentially impacted by situational factors relative to men’s, a suggestion that receives support from a recent collection of research. For example, Fritz & van Knippenberg ( 2017 ) found that both women’s and men’s leadership aspirations were positively impacted by the presence of a cooperative organizational climate, but for women it was the element of perceived collaboration among employees that mattered most, whereas for men it was perceived support from the organization. Meanwhile, Joo et al. ( 2018 ) found that participating in formal leadership mentoring improved the leadership self-efficacy of men mentees more than women mentees. In the current work, we build upon this research using time-lagged experience sampling methodology (ESM) that focuses on the situational characteristic of sleep quality – a naturally varying, daily condition. Specifically, we investigate whether sleep quality influences self-reported, daily intentions to pursue more status and responsibility at work, through its influence on next-day positive affect, and the extent to which this pathway is moderated by participant gender. Figure 1 depicts our model. Fig. 1 Theoretical Model Full size image The Impact of Sleep on Work Outcomes The impact of sleep – defined as an immobile state comprised of reduced physical responsiveness (Siegel, 2005 ) – on work-related outcomes went largely overlooked for a long time (Mullins et al., 2014 ), despite that well over half of Americans report sleep problems at least a few times a week (Swanson et al., 2011 ). Fortunately, interest in sleep among management scholars has increased significantly in the past decade, and sleep is now known to impact a variety of work outcomes, such as leader behavior (Barnes et al., 2016 ), ethical conduct (Barnes et al., 2011 ), and work engagement (Kuhnel et al., 2017 ; Lanaj et al., 2014 ). Most relevant to the current work, Schilpzand et al. ( 2018 ) found that sleep quality positively predicted employees’ tendency to engage in proactive goal setting the following day at work. The mechanism underlying this effect is explained by the sleep and self-regulation model (Barnes, 2012 ), which proposes that sleep influences self-regulation (i.e., the ability to effectively manage one’s goal-directed actions; Karoly, 1993 ), a component of which is emotion regulation, or an individual’s capacity to “monitor, evaluate, and modify the nature and course of an emotional response, in order to pursue his or her goals and appropriately respond to environmental demands” (Nolen-Hoeksema, 2012 , p. 163). The effectiveness of self-regulation, in turn, impacts daily work engagement and progress toward short- and long-term work goals (Rothbard & Wilk, 2011 ). Depending on observed short-term goal progress, individuals revise their goals in an upward or downward direction (Donovan & Williams, 2003 ). Drawing from this rationale, we expect higher sleep quality would predict enhanced mood (Franzen et al., 2008 ), operationalized as daily positive affect in the current research. Positive affect, in turn, should predict greater daily intent to pursue more status and responsibility at work. Accordingly, we offer the following within-person hypotheses: Hypothesis 1 Higher sleep quality will have a positive effect on next day’s affect. Hypothesis 2 Higher affect will lead to higher daily career aspirations. Hypothesis 3 Positive daily affect will mediate the association between nightly sleep quality and career aspirations. The Moderating Role of Participant Gender Relative to men, women tend to confront more numerous and substantial obstacles in their paths to high-ranking positions<|im_end|> <|im_start|>assistant If women want to lean in to work, they may first want to lay down for a good night's rest. A Washington State University-led study indicated that sleep quality impacted women's mood and changed how they felt about advancing in their careers. Meanwhile, men's aspirations were not impacted by sleep quality. The researchers discovered this finding in a two-week-long survey study of 135 workers in the U.S. Each day the participants first noted how well they had slept and the quality of their current mood, and then later in the day how they felt about striving for more status and responsibility at work. "When women are getting a good night's sleep and their mood is boosted, they are more likely to be oriented in their daily intentions toward achieving status and responsibility at work," said lead author Leah Sheppard, an associate professor in WSU's Carson College of Business. "If their sleep is poor and reduces their positive mood, then we saw that they were less oriented toward those goals." For the study published in the journal Sex Roles, Sheppard and co-authors Julie Kmec of WSU and Teng Iat Loi of University of Minnesota-Duluth surveyed full-time employees twice a day for two consecutive work weeks for a total of more than 2,200 observations. The participants answered questions about their previous night's sleep and current mood around noon every day and in the evenings answered questions about their intentions to pursue more responsibility, status, and influence at work. Both men and women reported good and bad sleep quality over the course of the study, notably with no gender difference in reported sleep quality. However, women more often reported lowered intentions to pursue more status at work on days following a night of poor sleep. The researchers can only speculate about exactly why sleep's impact on mood effects women's aspirations and not men's, but they suspect it may have to do with gender differences in emotion regulation as well as societal expectations—or some combination of these forces. Neuroscience research has shown that women tend to experience greater emotional re-activity and less emotion regulation than men, and this can be reinforced by cultural stereotypes of women as more emotional. At the same time, stereotypes of men as being more ambitious than women likely add more pressure for them to scale the corporate ladder, so perhaps poor sleep quality would be less likely to deter men from their work aspirations. These findings hold some good news for women who want to advance their careers, though, Sheppard said. For instance, they might take some practical steps to improve work aspirations, ranging from practicing meditation to help with both sleep and emotion regulation to putting better boundaries on work hours—and of course, simply striving to get better sleep. "It's important to be able to connect aspirations to something happening outside the work environment that is controllable," she said. "There are lots of things that anyone can do to have a better night's sleep and regulate mood in general." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 1556, 25329, 315, 6212, 323, 659, 33263, 2987, 26018, 374, 430, 6212, 4367, 25949, 20247, 902, 11, 304, 2543, 11, 52032, 7931, 311, 65836, 872, 990, 14228, 9021, 13, 1226, 30714, 430, 10026, 12062, 304, 20356, 11, 14604, 19812, 11, 323, 7076, 58522, 6324, 23965, 8800, 1521, 6913, 32946, 13, 763, 279, 1510, 990, 11, 584, 19874, 279, 2515, 315, 7446, 6212, 4367, 1389, 4669, 6928, 7958, 1389, 389, 34334, 311, 23564, 810, 2704, 323, 12014, 520, 990, 320, 72, 1770, 2637, 58522, 705, 439, 264, 734, 315, 25923, 10026, 13, 1226, 1296, 1057, 1646, 1701, 3217, 25936, 38152, 11, 10795, 287, 220, 8878, 2539, 7394, 8420, 67512, 304, 279, 3723, 4273, 11157, 7446, 4028, 1403, 24871, 990, 5672, 320, 605, 990, 14097, 705, 369, 264, 2860, 315, 220, 17, 11, 15741, 24654, 13, 1226, 1505, 430, 4315, 3278, 11, 719, 539, 3026, 11, 6212, 4367, 374, 40646, 5552, 311, 6928, 7958, 902, 11, 304, 2543, 11, 36716, 311, 7191, 7446, 34334, 311, 23564, 810, 2704, 323, 12014, 520, 990, 13, 1226, 4358, 279, 25127, 315, 1057, 990, 369, 3495, 323, 6725, 13, 9742, 3984, 555, 9599, 16931, 8471, 342, 38, 32198, 272, 20886, 7639, 9878, 377, 14434, 11896, 22938, 389, 264, 47913, 30, 35106, 279, 4279, 21294, 1054, 55519, 4227, 11, 1443, 46125, 510, 48144, 7881, 60, 51287, 3309, 603, 311, 3451, 2742, 304, 529, 719, 439, 51912, 14925, 56728, 934, 3153, 11, 1690, 315, 603, 527, 19781, 11, 323, 1120, 1390, 311, 1054, 11828, 1523, 529, 863, 320, 48412, 11, 220, 679, 22, 7609, 1115, 25466, 3502, 37840, 1247, 12929, 4529, 505, 264, 6721, 5333, 753, 33867, 5117, 13533, 430, 34334, 311, 23564, 810, 2704, 323, 12014, 520, 990, 39388, 6426, 439, 264, 734, 315, 7106, 477, 7958, 535, 5415, 11, 832, 315, 902, 374, 279, 1614, 315, 70663, 13, 18056, 420, 374, 459, 42779, 23035, 1389, 430, 279, 4907, 832, 706, 389, 904, 2728, 1938, 311, 48772, 311, 32145, 872, 9021, 690, 6211, 872, 7446, 42056, 323, 20392, 520, 990, 320, 12319, 552, 612, 20819, 11, 220, 1049, 20, 883, 1389, 31839, 617, 8965, 539, 50178, 315, 58522, 439, 40028, 555, 7446, 5415, 11, 1778, 439, 279, 5647, 315, 70663, 323, 51358, 1918, 2768, 264, 3814, 315, 8009, 6212, 13, 12361, 11, 1455, 315, 279, 17649, 32839, 58522, 439, 2555, 53007, 311, 264, 17743, 18027, 320, 68, 1326, 2637, 59509, 1880, 453, 2637, 220, 679, 19, 7026, 477, 520, 3325, 264, 3451, 16497, 11852, 529, 29683, 1389, 539, 5115, 439, 15528, 439, 17743, 719, 7995, 539, 439, 10109, 1697, 439, 36695, 34334, 320, 68, 1326, 2637, 20819, 612, 735, 8836, 35472, 5364, 84, 7218, 11, 220, 679, 17, 7609, 18185, 420, 4689, 31954, 304, 279, 17649, 11, 1063, 3495, 706, 6982, 430, 1524, 13643, 10109, 1697, 9547, 649, 5536, 7076, 58522, 13, 23150, 11, 3441, 544, 729, 1880, 453, 13, 320, 220, 679, 23, 883, 1766, 430, 13324, 529, 58522, 39388, 13148, 439, 264, 734, 315, 1694, 27716, 12893, 311, 5371, 3060, 6928, 477, 8389, 11302, 922, 872, 11692, 4754, 11, 28592, 40651, 1862, 311, 279, 23035, 430, 58522, 2643, 1101, 39388, 6426, 7446, 304, 2077, 311, 5370, 4455, 477, 14604, 5415, 13, 578, 8736, 12929, 11, 304, 57616, 1443, 46125, 8847, 7881, 753, 990, 389, 3278, 323, 11692, 11, 24897, 430, 3278, 753, 7076, 58522, 2643, 387, 2204, 34575, 40028, 555, 10109, 1697, 9547, 8844, 311, 3026, 753, 11, 264, 24710, 430, 21879, 1862, 505, 264, 3293, 4526, 315, 3495, 13, 1789, 3187, 11, 91083, 612, 5355, 13934, 575, 2821, 7881, 320, 220, 679, 22, 883, 1766, 430, 2225, 3278, 753, 323, 3026, 753, 11692, 58522, 1051, 40646, 40028, 555, 279, 9546, 315, 264, 48566, 41295, 10182, 11, 719, 369, 3278, 433, 574, 279, 2449, 315, 26617, 20632, 4315, 8420, 430, 81720, 1455, 11, 20444, 369, 3026, 433, 574, 26617, 1862, 505, 279, 7471, 13, 26982, 11, 622, 2689, 1880, 453, 13, 320, 220, 679, 23, 883, 1766, 430, 24435, 304, 16287, 11692, 76579, 13241, 279, 11692, 659, 5773, 21264, 2826, 315, 3026, 11540, 5633, 810, 1109, 3278, 11540, 5633, 13, 763, 279, 1510, 990, 11, 584, 1977, 5304, 420, 3495, 1701, 892, 2922, 97576, 3217, 25936, 38152, 320, 1600, 44, 8, 430, 24400, 389, 279, 10109, 1697, 29683, 315, 6212, 4367, 1389, 264, 18182, 29865, 11, 7446, 3044, 13, 45863, 11, 584, 19874, 3508, 6212, 4367, 34453, 659, 85296, 11, 7446, 34334, 311, 23564, 810, 2704, 323, 12014, 520, 990, 11, 1555, 1202, 10383, 389, 1828, 11477, 6928, 7958, 11, 323, 279, 13112, 311, 902, 420, 38970, 374, 87316, 555, 25923, 10026, 13, 19575, 220, 16, 62991, 1057, 1646, 13, 23966, 13, 220, 16, 578, 91867, 5008, 8797, 1404, 2217, 578, 29680, 315, 24708, 389, 5664, 4470, 6716, 578, 5536, 315, 6212, 1389, 4613, 439, 459, 4998, 3454, 1614, 40056, 315, 11293, 7106, 100039, 320, 51955, 29952, 11, 220, 1049, 20, 883, 1389, 389, 990, 14228, 20124, 4024, 14090, 45536, 369, 264, 1317, 892, 320, 44, 620, 1354, 1880, 453, 2637, 220, 679, 19, 7026, 8994, 430, 1664, 927, 4376, 315, 9053, 1934, 6212, 5435, 520, 3325, 264, 2478, 3115, 264, 2046, 320, 13521, 37645, 1880, 453, 2637, 220, 679, 16, 7609, 42536, 11, 2802, 304, 6212, 4315, 6373, 31839, 706, 7319, 12207, 304, 279, 3347, 13515, 11, 323, 6212, 374, 1457, 3967, 311, 5536, 264, 8205, 315, 990, 20124, 11, 1778, 439, 7808, 7865, 320, 33, 1923, 288, 1880, 453, 2637, 220, 679, 21, 7026, 31308, 6929, 320, 33, 1923, 288, 1880, 453, 2637, 220, 679, 16, 7026, 323, 990, 20392, 320, 42, 12825, 8301, 1880, 453, 2637, 220, 679, 22, 2652, 35882, 1662, 1880, 453, 2637, 220, 679, 19, 7609, 7648, 9959, 311, 279, 1510, 990, 11, 5124, 321, 67665, 438, 1880, 453, 13, 320, 220, 679, 23, 883, 1766, 430, 6212, 4367, 40646, 19698, 8420, 529, 31954, 311, 16988, 304, 59314, 5915, 6376, 279, 2768, 1938, 520, 990, 13, 578, 17383, 16940, 420, 2515, 374, 11497, 555, 279, 6212, 323, 659, 33263, 2987, 1646, 320, 33, 1923, 288, 11, 220, 679, 17, 7026, 902, 55725, 430, 6212, 34453, 659, 33263, 2987, 320, 72, 1770, 2637, 279, 5845, 311, 13750, 10299, 832, 753, 5915, 86855, 6299, 26, 13528, 5849, 11, 220, 2550, 18, 7026, 264, 3777, 315, 902, 374, 20356, 19812, 11, 477, 459, 3927, 753, 8824, 311, 1054, 33325, 11, 15806, 11, 323, 5719, 279, 7138, 323, 3388, 315, 459, 14604, 2077, 11, 304, 2015, 311, 23564, 813, 477, 1077, 9021, 323, 36001, 6013, 311, 12434, 18651, 863, 320, 45, 17648, 11529, 78, 1247, 325, 1764, 11, 220, 679, 17, 1174, 281, 13, 220, 9892, 570, 578, 27375, 315, 659, 33263, 2987, 11, 304, 2543, 11, 25949, 7446, 990, 20392, 323, 5208, 9017, 2875, 12, 323, 1317, 9860, 990, 9021, 320, 49, 8942, 67019, 612, 10785, 74, 11, 220, 679, 16, 7609, 40730, 389, 13468, 2875, 9860, 5915, 5208, 11, 7931, 65836, 872, 9021, 304, 459, 40872, 477, 45578, 5216, 320, 8161, 43757, 612, 13926, 11, 220, 1049, 18, 7609, 38859, 505, 420, 57916, 11, 584, 1755, 5190, 6212, 4367, 1053, 7168, 24872, 20247, 320, 76431, 5797, 1880, 453, 2637, 220, 1049, 23, 7026, 25605, 1534, 439, 7446, 6928, 7958, 304, 279, 1510, 3495, 13, 45003, 7958, 11, 304, 2543, 11, 1288, 7168, 7191, 7446, 7537, 311, 23564, 810, 2704, 323, 12014, 520, 990, 13, 63909, 11, 584, 3085, 279, 2768, 2949, 29145, 74513, 25, 39515, 78, 13491, 220, 16, 35321, 6212, 4367, 690, 617, 264, 6928, 2515, 389, 1828, 1938, 753, 7958, 13, 39515, 78, 13491, 220, 17, 35321, 7958, 690, 3063, 311, 5190, 7446, 7076, 58522, 13, 39515, 78, 13491, 220, 18, 45003, 7446, 7958, 690, 1812, 6629, 279, 15360, 1990, 75860, 6212, 4367, 323, 7076, 58522, 13, 578, 44527, 1113, 15766, 315, 47476, 29317, 40502, 311, 3026, 11, 3278, 8541, 311, 17302, 810, 12387, 323, 12190, 32116, 304, 872, 13006, 311, 1579, 72539, 10093, 128257, 198, 128256, 78191, 198, 2746, 3278, 1390, 311, 16025, 304, 311, 990, 11, 814, 1253, 1176, 1390, 311, 11203, 1523, 369, 264, 1695, 3814, 596, 2800, 13, 362, 6652, 3314, 3907, 35054, 4007, 16717, 430, 6212, 4367, 40028, 3278, 596, 20247, 323, 5614, 1268, 814, 6612, 922, 44169, 304, 872, 31133, 13, 26982, 11, 3026, 596, 58522, 1051, 539, 40028, 555, 6212, 4367, 13, 578, 12074, 11352, 420, 9455, 304, 264, 1403, 30609, 24725, 10795, 4007, 315, 220, 8878, 7487, 304, 279, 549, 815, 13, 9062, 1938, 279, 13324, 1176, 10555, 1268, 1664, 814, 1047, 46498, 323, 279, 4367, 315, 872, 1510, 20247, 11, 323, 1243, 3010, 304, 279, 1938, 1268, 814, 6612, 922, 68727, 369, 810, 2704, 323, 12014, 520, 990, 13, 330, 4599, 3278, 527, 3794, 264, 1695, 3814, 596, 6212, 323, 872, 20247, 374, 65208, 11, 814, 527, 810, 4461, 311, 387, 42208, 304, 872, 7446, 34334, 9017, 32145, 2704, 323, 12014, 520, 990, 1359, 1071, 3063, 3229, 67961, 3005, 99104, 11, 459, 22712, 14561, 304, 25950, 52, 596, 41276, 9304, 315, 8184, 13, 330, 2746, 872, 6212, 374, 8009, 323, 26338, 872, 6928, 20247, 11, 1243, 584, 5602, 430, 814, 1051, 2753, 42208, 9017, 1884, 9021, 1210, 1789, 279, 4007, 4756, 304, 279, 8486, 6834, 52007, 11, 3005, 99104, 323, 1080, 34603, 1105, 42287, 93582, 762, 315, 25950, 52, 323, 350, 833, 358, 266, 6621, 72, 315, 3907, 315, 19461, 9607, 360, 952, 49098, 2539, 7394, 8420, 11157, 264, 1938, 369, 1403, 24871, 990, 5672, 369, 264, 2860, 315, 810, 1109, 220, 17, 11, 1049, 24654, 13, 578, 13324, 19089, 4860, 922, 872, 3766, 3814, 596, 6212, 323, 1510, 20247, 2212, 38245, 1475, 1938, 323, 304, 279, 59938, 19089, 4860, 922, 872, 34334, 311, 23564, 810, 12014, 11, 2704, 11, 323, 10383, 520, 990, 13, 11995, 3026, 323, 3278, 5068, 1695, 323, 3958, 6212, 4367, 927, 279, 3388, 315, 279, 4007, 11, 35146, 449, 912, 10026, 6811, 304, 5068, 6212, 4367, 13, 4452, 11, 3278, 810, 3629, 5068, 39920, 34334, 311, 23564, 810, 2704, 520, 990, 389, 2919, 2768, 264, 3814, 315, 8009, 6212, 13, 578, 12074, 649, 1193, 64601, 922, 7041, 3249, 6212, 596, 5536, 389, 20247, 6372, 3278, 596, 58522, 323, 539, 3026, 596, 11, 719, 814, 15562, 433, 1253, 617, 311, 656, 449, 10026, 12062, 304, 20356, 19812, 439, 1664, 439, 59529, 17078, 51749, 1063, 10824, 315, 1521, 8603, 13, 85879, 3495, 706, 6982, 430, 3278, 8541, 311, 3217, 7191, 14604, 312, 12, 7323, 323, 2753, 20356, 19812, 1109, 3026, 11, 323, 420, 649, 387, 49680, 555, 13042, 54168, 315, 3278, 439, 810, 14604, 13, 2468, 279, 1890, 892, 11, 54168, 315, 3026, 439, 1694, 810, 32855, 1109, 3278, 4461, 923, 810, 7410, 369, 1124, 311, 5569, 279, 13166, 36865, 11, 779, 8530, 8009, 6212, 4367, 1053, 387, 2753, 4461, 311, 4130, 3026, 505, 872, 990, 58522, 13, 4314, 14955, 3412, 1063, 1695, 3754, 369, 3278, 889, 1390, 311, 12178, 872, 31133, 11, 3582, 11, 3005, 99104, 1071, 13, 1789, 2937, 11, 814, 2643, 1935, 1063, 15325, 7504, 311, 7417, 990, 58522, 11, 24950, 505, 36666, 33862, 311, 1520, 449, 2225, 6212, 323, 20356, 19812, 311, 10917, 2731, 23546, 389, 990, 4207, 17223, 315, 3388, 11, 5042, 68727, 311, 636, 2731, 6212, 13, 330, 2181, 596, 3062, 311, 387, 3025, 311, 4667, 58522, 311, 2555, 12765, 4994, 279, 990, 4676, 430, 374, 687, 69855, 1359, 1364, 1071, 13, 330, 3947, 527, 10283, 315, 2574, 430, 5606, 649, 656, 311, 617, 264, 2731, 3814, 596, 6212, 323, 37377, 20247, 304, 4689, 1210, 220, 128257, 198 ]

1,931

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Widespread evidence points to the existence of an ancient Martian ocean 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 . Most compelling are the putative ancient shorelines in the northern plains 2 , 7 . However, these shorelines fail to follow an equipotential surface, and this has been used to challenge the notion that they formed via an early ocean 9 and hence to question the existence of such an ocean. The shorelines’ deviation from a constant elevation can be explained by true polar wander occurring after the formation of Tharsis 10 , a volcanic province that dominates the gravity and topography of Mars. However, surface loading from the oceans can drive polar wander only if Tharsis formed far from the equator 10 , and most evidence indicates that Tharsis formed near the equator 11 , 12 , 13 , 14 , 15 , meaning that there is no current explanation for the shorelines’ deviation from an equipotential that is consistent with our geophysical understanding of Mars. Here we show that variations in shoreline topography can be explained by deformation caused by the emplacement of Tharsis. We find that the shorelines must have formed before and during the emplacement of Tharsis, instead of afterwards, as previously assumed. Our results imply that oceans on Mars formed early, concurrent with the valley networks 15 , and point to a close relationship between the evolution of oceans on Mars and the initiation and decline of Tharsis volcanism, with broad implications for the geology, hydrological cycle and climate of early Mars. Main Distinct geological boundaries (contacts) lining the northern plains of Mars for thousands of kilometres have been interpreted as palaeo-shorelines and evidence of an early ocean 2 , 3 , 4 , 6 , 7 . However, observed long-wavelength deviations (by up to several kilometres) in shoreline elevation from an equipotential have been used as an argument against the emplacement of the contacts by a body of liquid water, the interpretation of the features as shorelines, and the existence of a Martian ocean 9 . Perron et al . 10 showed that the elevation changes of two extensive contacts, Arabia (contact 1) and Deuteronilus (contact 2), can be explained by deformation due to 30°–60° and 5°–25° of post-Tharsis true polar wander (TPW), respectively, because a varying rotation pole also changes the orientation of a planet’s equatorial bulge, or polar flattening, altering equipotential surfaces (such as sea levels) globally. Such large magnitudes of TPW can be driven by ocean loading/unloading, but only if Tharsis formed far from the equator 10 . If Tharsis formed near the equator, then the remnant fossil bulge would have prevented ocean loading from causing large amounts of post-Tharsis TPW (see Extended Data Fig. 1 ). Most evidence points to the formation of Tharsis near the equator 11 , 12 , 13 , 14 , 15 . Mars’ remnant rotational figure (fossil bulge) is close to the equator, indicating a palaeopole of (259.5 ± 49.5° E, ° N), the likely pre-Tharsis orientation of Mars 14 . The pre-Tharsis palaeopole also matches the likely orientation of Mars during valley network formation 15 . Formation of Tharsis probably drove only limited (approximately 20°) TPW to reach Mars’ current configuration, which precludes the possibility that surface loads drove sufficient TPW to deform the shorelines 10 , 16 . We propose that the Arabia shoreline instead formed before or during the early stages of Tharsis emplacement, which initiated > 3.7 billion years (Gyr) ago 17 when the rotation pole of Mars was at the palaeopole (259.5° E, 71.1° N) corresponding to the fossil bulge 14 . The Arabia shoreline, potentially emplaced at least 4 Gyr ago 6 , would have been modified by both topographic changes from Tharsis (which dominates Mars’ topography and gravity on a global scale; see Extended Data Fig. 2 ), and the approximately 20° of Tharsis-induced TPW. The Deuteronilus shoreline, which differs less from a present-day equipotential than the older Arabia shoreline, is dated to about 3.6 Gyr ago 18 , after most of Tharsis was emplaced. However, Tharsis had complex and multi-stage growth that extended into the Hesperian and Amazonian 17 , 19 , meaning that the Deuteronilus shoreline would have been deformed by the late stages of Tharsis’ emplacement. We examine a chronology in which shoreline deformation is due mainly to Tharsis ( Table 1 ), and compare expected deformation due to Tharsis with the elevation profiles of the Arabia and Deuteronilus contacts. Table 1 Possible evolution of Martian shorelines Full size table Assuming the Arabia shoreline formed before Tharsis, and the Deuteronilus shoreline formed after most of Tharsis was emplaced, we compare the best fits for the deformation expected from Tharsis to the current topography of the shorelines, including an offset factor Z to represent sea level at the time of shoreline formation. We also examine the Isidis shoreline, which formed 100 million years (Myr) after Deuteronilus 18 . For the Arabia shoreline emplaced before Tharsis, deformation is expressed as the contribution of Tharsis to Mars’ topography along the shoreline, and the change in topography from limited Tharsis-induced TPW. For the Deuteronilus and Isidis shorelines emplaced during the late stages of Tharsis growth, deformation is taken as the percentage of Tharsis’ contribution to topography occurring after the shorelines formed, and no contribution from TPW (because reorientation should occur within tens of thousands of years to a few million years after the Tharsis plume reaches the surface 20 , much less than the 100 Myr or more that lies between Tharsis initiation and Deuteronilus formation). See Methods for more details. We show that the Arabia shoreline’s deviations from an equipotential can be explained almost entirely by deformation due to Tharsis emplacement ( Fig. 1 ). Our best fit (equation (3) with Z = −2.3 km) yields a root-mean square misfit σ rms of 0.615 km, comparable to the error values from Perron et al . 10 , and follows the", "role": "user" }, { "content": "A new scenario seeking to explain how Mars' putative oceans came and went over the last 4 billion years implies that the oceans formed several hundred million years earlier and were not as deep as once thought. The proposal by geophysicists at the University of California, Berkeley, links the existence of oceans early in Mars history to the rise of the solar system's largest volcanic system, Tharsis, and highlights the key role played by global warming in allowing liquid water to exist on Mars. \"Volcanoes may be important in creating the conditions for Mars to be wet,\" said Michael Manga, a UC Berkeley professor of earth and planetary science and senior author of a paper appearing in Nature this week and posted online March 19. Those claiming that Mars never had oceans of liquid water often point to the fact that estimates of the size of the oceans don't jibe with estimates of how much water could be hidden today as permafrost underground and how much could have escaped into space. These are the main options, given that the polar ice caps don't contain enough water to fill an ocean. The new model proposes that the oceans formed before or at the same time as Mars' largest volcanic feature, Tharsis, instead of after Tharsis formed 3.7 billion years ago. Because Tharsis was smaller at that time, it did not distort the planet as much as it did later, in particular the plains that cover most of the northern hemisphere and are the presumed ancient seabed. The absence of crustal deformation from Tharsis means the seas would have been shallower, holding about half the water of earlier estimates. \"The assumption was that Tharsis formed quickly and early, rather than gradually, and that the oceans came later,\" Manga said. \"We're saying that the oceans predate and accompany the lava outpourings that made Tharsis.\" It's likely, he added, that Tharsis spewed gases into the atmosphere that created a global warming or greenhouse effect that allowed liquid water to exist on the planet, and also that volcanic eruptions created channels that allowed underground water to reach the surface and fill the northern plains. Following the shorelines The model also counters another argument against oceans: that the proposed shorelines are very irregular, varying in height by as much as a kilometer, when they should be level, like shorelines on Earth. This irregularity could be explained if the first ocean, called Arabia, started forming about 4 billion years ago and existed, if intermittently, during as much as the first 20 percent of Tharsis's growth. The growing volcano would have depressed the land and deformed the shoreline over time, which could explain the irregular heights of the Arabia shoreline. Similarly, the irregular shoreline of a subsequent ocean, called Deuteronilus, could be explained if it formed during the last 17 percent of Tharsis's growth, about 3.6 billion years ago. \"These shorelines could have been emplaced by a large body of liquid water that existed before and during the emplacement of Tharsis, instead of afterwards,\" said first author Robert Citron, a UC Berkeley graduate student. Citron will present a paper about the new analysis on March 20 at the annual Lunar and Planetary Science conference in Texas. Tharsis, now a 5,000-kilometer-wide eruptive complex, contains some of the biggest volcanoes in the solar system and dominates the topography of Mars. Earth, twice the diameter and 10 times more massive than Mars, has no equivalent dominating feature. Tharsis's bulk creates a bulge on the opposite side of the planet and a depression halfway between. This explains why estimates of the volume of water the northern plains could hold based on today's topography are twice what the new study estimates based on the topography 4 billion years ago. New hypothesis supplants old Manga, who models the internal heat flow of Mars, such as the rising plumes of molten rock that erupt into volcanoes at the surface, tried to explain the irregular shorelines of the plains of Mars 11 years ago with another theory. He and former graduate student Taylor Perron suggested that Tharsis, which was then thought to have originated at far northern latitudes, was so massive that it caused the spin axis of Mars to move several thousand miles south, throwing off the shorelines. Since then, however, others have shown that Tharsis originated only about 20 degrees above the equator, nixing that theory. But Manga and Citron came up with another idea, that the shorelines could have been etched as Tharsis was growing, not afterward. The new theory also can account for the cutting of valley networks by flowing water at around the same time. \"This is a hypothesis,\" Manga emphasized. \"But scientists can do more precise dating of Tharsis and the shorelines to see if it holds up.\" NASA's next Mars lander, the InSight mission (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport), could help answer the question. Scheduled for launch in May, it will place a seismometer on the surface to probe the interior and perhaps find frozen remnants of that ancient ocean, or even liquid water. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Widespread evidence points to the existence of an ancient Martian ocean 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 . Most compelling are the putative ancient shorelines in the northern plains 2 , 7 . However, these shorelines fail to follow an equipotential surface, and this has been used to challenge the notion that they formed via an early ocean 9 and hence to question the existence of such an ocean. The shorelines’ deviation from a constant elevation can be explained by true polar wander occurring after the formation of Tharsis 10 , a volcanic province that dominates the gravity and topography of Mars. However, surface loading from the oceans can drive polar wander only if Tharsis formed far from the equator 10 , and most evidence indicates that Tharsis formed near the equator 11 , 12 , 13 , 14 , 15 , meaning that there is no current explanation for the shorelines’ deviation from an equipotential that is consistent with our geophysical understanding of Mars. Here we show that variations in shoreline topography can be explained by deformation caused by the emplacement of Tharsis. We find that the shorelines must have formed before and during the emplacement of Tharsis, instead of afterwards, as previously assumed. Our results imply that oceans on Mars formed early, concurrent with the valley networks 15 , and point to a close relationship between the evolution of oceans on Mars and the initiation and decline of Tharsis volcanism, with broad implications for the geology, hydrological cycle and climate of early Mars. Main Distinct geological boundaries (contacts) lining the northern plains of Mars for thousands of kilometres have been interpreted as palaeo-shorelines and evidence of an early ocean 2 , 3 , 4 , 6 , 7 . However, observed long-wavelength deviations (by up to several kilometres) in shoreline elevation from an equipotential have been used as an argument against the emplacement of the contacts by a body of liquid water, the interpretation of the features as shorelines, and the existence of a Martian ocean 9 . Perron et al . 10 showed that the elevation changes of two extensive contacts, Arabia (contact 1) and Deuteronilus (contact 2), can be explained by deformation due to 30°–60° and 5°–25° of post-Tharsis true polar wander (TPW), respectively, because a varying rotation pole also changes the orientation of a planet’s equatorial bulge, or polar flattening, altering equipotential surfaces (such as sea levels) globally. Such large magnitudes of TPW can be driven by ocean loading/unloading, but only if Tharsis formed far from the equator 10 . If Tharsis formed near the equator, then the remnant fossil bulge would have prevented ocean loading from causing large amounts of post-Tharsis TPW (see Extended Data Fig. 1 ). Most evidence points to the formation of Tharsis near the equator 11 , 12 , 13 , 14 , 15 . Mars’ remnant rotational figure (fossil bulge) is close to the equator, indicating a palaeopole of (259.5 ± 49.5° E, ° N), the likely pre-Tharsis orientation of Mars 14 . The pre-Tharsis palaeopole also matches the likely orientation of Mars during valley network formation 15 . Formation of Tharsis probably drove only limited (approximately 20°) TPW to reach Mars’ current configuration, which precludes the possibility that surface loads drove sufficient TPW to deform the shorelines 10 , 16 . We propose that the Arabia shoreline instead formed before or during the early stages of Tharsis emplacement, which initiated > 3.7 billion years (Gyr) ago 17 when the rotation pole of Mars was at the palaeopole (259.5° E, 71.1° N) corresponding to the fossil bulge 14 . The Arabia shoreline, potentially emplaced at least 4 Gyr ago 6 , would have been modified by both topographic changes from Tharsis (which dominates Mars’ topography and gravity on a global scale; see Extended Data Fig. 2 ), and the approximately 20° of Tharsis-induced TPW. The Deuteronilus shoreline, which differs less from a present-day equipotential than the older Arabia shoreline, is dated to about 3.6 Gyr ago 18 , after most of Tharsis was emplaced. However, Tharsis had complex and multi-stage growth that extended into the Hesperian and Amazonian 17 , 19 , meaning that the Deuteronilus shoreline would have been deformed by the late stages of Tharsis’ emplacement. We examine a chronology in which shoreline deformation is due mainly to Tharsis ( Table 1 ), and compare expected deformation due to Tharsis with the elevation profiles of the Arabia and Deuteronilus contacts. Table 1 Possible evolution of Martian shorelines Full size table Assuming the Arabia shoreline formed before Tharsis, and the Deuteronilus shoreline formed after most of Tharsis was emplaced, we compare the best fits for the deformation expected from Tharsis to the current topography of the shorelines, including an offset factor Z to represent sea level at the time of shoreline formation. We also examine the Isidis shoreline, which formed 100 million years (Myr) after Deuteronilus 18 . For the Arabia shoreline emplaced before Tharsis, deformation is expressed as the contribution of Tharsis to Mars’ topography along the shoreline, and the change in topography from limited Tharsis-induced TPW. For the Deuteronilus and Isidis shorelines emplaced during the late stages of Tharsis growth, deformation is taken as the percentage of Tharsis’ contribution to topography occurring after the shorelines formed, and no contribution from TPW (because reorientation should occur within tens of thousands of years to a few million years after the Tharsis plume reaches the surface 20 , much less than the 100 Myr or more that lies between Tharsis initiation and Deuteronilus formation). See Methods for more details. We show that the Arabia shoreline’s deviations from an equipotential can be explained almost entirely by deformation due to Tharsis emplacement ( Fig. 1 ). Our best fit (equation (3) with Z = −2.3 km) yields a root-mean square misfit σ rms of 0.615 km, comparable to the error values from Perron et al . 10 , and follows the<|im_end|> <|im_start|>assistant A new scenario seeking to explain how Mars' putative oceans came and went over the last 4 billion years implies that the oceans formed several hundred million years earlier and were not as deep as once thought. The proposal by geophysicists at the University of California, Berkeley, links the existence of oceans early in Mars history to the rise of the solar system's largest volcanic system, Tharsis, and highlights the key role played by global warming in allowing liquid water to exist on Mars. "Volcanoes may be important in creating the conditions for Mars to be wet," said Michael Manga, a UC Berkeley professor of earth and planetary science and senior author of a paper appearing in Nature this week and posted online March 19. Those claiming that Mars never had oceans of liquid water often point to the fact that estimates of the size of the oceans don't jibe with estimates of how much water could be hidden today as permafrost underground and how much could have escaped into space. These are the main options, given that the polar ice caps don't contain enough water to fill an ocean. The new model proposes that the oceans formed before or at the same time as Mars' largest volcanic feature, Tharsis, instead of after Tharsis formed 3.7 billion years ago. Because Tharsis was smaller at that time, it did not distort the planet as much as it did later, in particular the plains that cover most of the northern hemisphere and are the presumed ancient seabed. The absence of crustal deformation from Tharsis means the seas would have been shallower, holding about half the water of earlier estimates. "The assumption was that Tharsis formed quickly and early, rather than gradually, and that the oceans came later," Manga said. "We're saying that the oceans predate and accompany the lava outpourings that made Tharsis." It's likely, he added, that Tharsis spewed gases into the atmosphere that created a global warming or greenhouse effect that allowed liquid water to exist on the planet, and also that volcanic eruptions created channels that allowed underground water to reach the surface and fill the northern plains. Following the shorelines The model also counters another argument against oceans: that the proposed shorelines are very irregular, varying in height by as much as a kilometer, when they should be level, like shorelines on Earth. This irregularity could be explained if the first ocean, called Arabia, started forming about 4 billion years ago and existed, if intermittently, during as much as the first 20 percent of Tharsis's growth. The growing volcano would have depressed the land and deformed the shoreline over time, which could explain the irregular heights of the Arabia shoreline. Similarly, the irregular shoreline of a subsequent ocean, called Deuteronilus, could be explained if it formed during the last 17 percent of Tharsis's growth, about 3.6 billion years ago. "These shorelines could have been emplaced by a large body of liquid water that existed before and during the emplacement of Tharsis, instead of afterwards," said first author Robert Citron, a UC Berkeley graduate student. Citron will present a paper about the new analysis on March 20 at the annual Lunar and Planetary Science conference in Texas. Tharsis, now a 5,000-kilometer-wide eruptive complex, contains some of the biggest volcanoes in the solar system and dominates the topography of Mars. Earth, twice the diameter and 10 times more massive than Mars, has no equivalent dominating feature. Tharsis's bulk creates a bulge on the opposite side of the planet and a depression halfway between. This explains why estimates of the volume of water the northern plains could hold based on today's topography are twice what the new study estimates based on the topography 4 billion years ago. New hypothesis supplants old Manga, who models the internal heat flow of Mars, such as the rising plumes of molten rock that erupt into volcanoes at the surface, tried to explain the irregular shorelines of the plains of Mars 11 years ago with another theory. He and former graduate student Taylor Perron suggested that Tharsis, which was then thought to have originated at far northern latitudes, was so massive that it caused the spin axis of Mars to move several thousand miles south, throwing off the shorelines. Since then, however, others have shown that Tharsis originated only about 20 degrees above the equator, nixing that theory. But Manga and Citron came up with another idea, that the shorelines could have been etched as Tharsis was growing, not afterward. The new theory also can account for the cutting of valley networks by flowing water at around the same time. "This is a hypothesis," Manga emphasized. "But scientists can do more precise dating of Tharsis and the shorelines to see if it holds up." NASA's next Mars lander, the InSight mission (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport), could help answer the question. Scheduled for launch in May, it will place a seismometer on the surface to probe the interior and perhaps find frozen remnants of that ancient ocean, or even liquid water. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 468, 3422, 21376, 6029, 3585, 311, 279, 14209, 315, 459, 14154, 82128, 18435, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 662, 7648, 29722, 527, 279, 2231, 1413, 14154, 31284, 8128, 304, 279, 18671, 78466, 220, 17, 1174, 220, 22, 662, 4452, 11, 1521, 31284, 8128, 3775, 311, 1833, 459, 26458, 354, 2335, 7479, 11, 323, 420, 706, 1027, 1511, 311, 8815, 279, 23035, 430, 814, 14454, 4669, 459, 4216, 18435, 220, 24, 323, 16472, 311, 3488, 279, 14209, 315, 1778, 459, 18435, 13, 578, 31284, 8128, 529, 38664, 505, 264, 6926, 27255, 649, 387, 11497, 555, 837, 25685, 40320, 31965, 1306, 279, 18488, 315, 666, 1590, 285, 220, 605, 1174, 264, 67164, 17271, 430, 83978, 279, 24128, 323, 1948, 5814, 315, 21725, 13, 4452, 11, 7479, 8441, 505, 279, 54280, 649, 6678, 25685, 40320, 1193, 422, 666, 1590, 285, 14454, 3117, 505, 279, 3312, 859, 220, 605, 1174, 323, 1455, 6029, 15151, 430, 666, 1590, 285, 14454, 3221, 279, 3312, 859, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 1174, 7438, 430, 1070, 374, 912, 1510, 16540, 369, 279, 31284, 8128, 529, 38664, 505, 459, 26458, 354, 2335, 430, 374, 13263, 449, 1057, 3980, 91004, 8830, 315, 21725, 13, 5810, 584, 1501, 430, 27339, 304, 99164, 1948, 5814, 649, 387, 11497, 555, 91621, 9057, 555, 279, 991, 16491, 315, 666, 1590, 285, 13, 1226, 1505, 430, 279, 31284, 8128, 2011, 617, 14454, 1603, 323, 2391, 279, 991, 16491, 315, 666, 1590, 285, 11, 4619, 315, 27905, 11, 439, 8767, 19655, 13, 5751, 3135, 34608, 430, 54280, 389, 21725, 14454, 4216, 11, 35135, 449, 279, 34681, 14488, 220, 868, 1174, 323, 1486, 311, 264, 3345, 5133, 1990, 279, 15740, 315, 54280, 389, 21725, 323, 279, 61568, 323, 18174, 315, 666, 1590, 285, 36373, 2191, 11, 449, 7353, 25127, 369, 279, 3980, 2508, 11, 17055, 31356, 11008, 323, 10182, 315, 4216, 21725, 13, 4802, 28704, 7956, 86278, 23546, 320, 30163, 8, 36471, 279, 18671, 78466, 315, 21725, 369, 9214, 315, 52957, 617, 1027, 33398, 439, 11091, 6043, 78, 7666, 461, 8128, 323, 6029, 315, 459, 4216, 18435, 220, 17, 1174, 220, 18, 1174, 220, 19, 1174, 220, 21, 1174, 220, 22, 662, 4452, 11, 13468, 1317, 2695, 35961, 86365, 320, 1729, 709, 311, 3892, 52957, 8, 304, 99164, 27255, 505, 459, 26458, 354, 2335, 617, 1027, 1511, 439, 459, 5811, 2403, 279, 991, 16491, 315, 279, 19015, 555, 264, 2547, 315, 14812, 3090, 11, 279, 23692, 315, 279, 4519, 439, 31284, 8128, 11, 323, 279, 14209, 315, 264, 82128, 18435, 220, 24, 662, 86848, 263, 1880, 453, 662, 220, 605, 8710, 430, 279, 27255, 4442, 315, 1403, 16781, 19015, 11, 23931, 320, 6421, 220, 16, 8, 323, 1611, 332, 20110, 321, 355, 320, 6421, 220, 17, 705, 649, 387, 11497, 555, 91621, 4245, 311, 220, 966, 11877, 4235, 1399, 11877, 323, 220, 20, 11877, 4235, 914, 11877, 315, 1772, 71626, 1590, 285, 837, 25685, 40320, 320, 4334, 54, 705, 15947, 11, 1606, 264, 29865, 12984, 26078, 1101, 4442, 279, 17140, 315, 264, 11841, 753, 3312, 39036, 7173, 713, 11, 477, 25685, 52139, 6147, 11, 60923, 26458, 354, 2335, 27529, 320, 21470, 439, 9581, 5990, 8, 31550, 13, 15483, 3544, 8622, 21237, 315, 30170, 54, 649, 387, 16625, 555, 18435, 8441, 36317, 10853, 11, 719, 1193, 422, 666, 1590, 285, 14454, 3117, 505, 279, 3312, 859, 220, 605, 662, 1442, 666, 1590, 285, 14454, 3221, 279, 3312, 859, 11, 1243, 279, 1323, 52985, 31376, 7173, 713, 1053, 617, 32098, 18435, 8441, 505, 14718, 3544, 15055, 315, 1772, 71626, 1590, 285, 30170, 54, 320, 4151, 41665, 2956, 23966, 13, 220, 16, 7609, 7648, 6029, 3585, 311, 279, 18488, 315, 666, 1590, 285, 3221, 279, 3312, 859, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 662, 21725, 529, 1323, 52985, 92371, 7216, 320, 69, 85061, 7173, 713, 8, 374, 3345, 311, 279, 3312, 859, 11, 19392, 264, 11091, 6043, 454, 1286, 315, 320, 15537, 13, 20, 20903, 220, 2491, 13, 20, 11877, 469, 11, 37386, 452, 705, 279, 4461, 864, 71626, 1590, 285, 17140, 315, 21725, 220, 975, 662, 578, 864, 71626, 1590, 285, 11091, 6043, 454, 1286, 1101, 9248, 279, 4461, 17140, 315, 21725, 2391, 34681, 4009, 18488, 220, 868, 662, 72466, 315, 666, 1590, 285, 4762, 23980, 1193, 7347, 320, 97836, 220, 508, 11877, 8, 30170, 54, 311, 5662, 21725, 529, 1510, 6683, 11, 902, 864, 7548, 279, 13336, 430, 7479, 21577, 23980, 14343, 30170, 54, 311, 79212, 279, 31284, 8128, 220, 605, 1174, 220, 845, 662, 1226, 30714, 430, 279, 23931, 99164, 4619, 14454, 1603, 477, 2391, 279, 4216, 18094, 315, 666, 1590, 285, 991, 16491, 11, 902, 33230, 871, 220, 18, 13, 22, 7239, 1667, 320, 38, 11160, 8, 4227, 220, 1114, 994, 279, 12984, 26078, 315, 21725, 574, 520, 279, 11091, 6043, 454, 1286, 320, 15537, 13, 20, 11877, 469, 11, 220, 6028, 13, 16, 11877, 452, 8, 12435, 311, 279, 31376, 7173, 713, 220, 975, 662, 578, 23931, 99164, 11, 13893, 991, 37469, 520, 3325, 220, 19, 480, 11160, 4227, 220, 21, 1174, 1053, 617, 1027, 11041, 555, 2225, 1948, 12968, 4442, 505, 666, 1590, 285, 320, 8370, 83978, 21725, 529, 1948, 5814, 323, 24128, 389, 264, 3728, 5569, 26, 1518, 41665, 2956, 23966, 13, 220, 17, 7026, 323, 279, 13489, 220, 508, 11877, 315, 666, 1590, 285, 38973, 30170, 54, 13, 578, 1611, 332, 20110, 321, 355, 99164, 11, 902, 44642, 2753, 505, 264, 3118, 11477, 26458, 354, 2335, 1109, 279, 9191, 23931, 99164, 11, 374, 30105, 311, 922, 220, 18, 13, 21, 480, 11160, 4227, 220, 972, 1174, 1306, 1455, 315, 666, 1590, 285, 574, 991, 37469, 13, 4452, 11, 666, 1590, 285, 1047, 6485, 323, 7447, 51256, 6650, 430, 11838, 1139, 279, 473, 70138, 1122, 323, 8339, 1122, 220, 1114, 1174, 220, 777, 1174, 7438, 430, 279, 1611, 332, 20110, 321, 355, 99164, 1053, 617, 1027, 409, 10365, 555, 279, 3389, 18094, 315, 666, 1590, 285, 529, 991, 16491, 13, 1226, 21635, 264, 27076, 2508, 304, 902, 99164, 91621, 374, 4245, 14918, 311, 666, 1590, 285, 320, 6771, 220, 16, 7026, 323, 9616, 3685, 91621, 4245, 311, 666, 1590, 285, 449, 279, 27255, 21542, 315, 279, 23931, 323, 1611, 332, 20110, 321, 355, 19015, 13, 6771, 220, 16, 37207, 15740, 315, 82128, 31284, 8128, 8797, 1404, 2007, 65064, 279, 23931, 99164, 14454, 1603, 666, 1590, 285, 11, 323, 279, 1611, 332, 20110, 321, 355, 99164, 14454, 1306, 1455, 315, 666, 1590, 285, 574, 991, 37469, 11, 584, 9616, 279, 1888, 18809, 369, 279, 91621, 3685, 505, 666, 1590, 285, 311, 279, 1510, 1948, 5814, 315, 279, 31284, 8128, 11, 2737, 459, 4445, 8331, 1901, 311, 4097, 9581, 2237, 520, 279, 892, 315, 99164, 18488, 13, 1226, 1101, 21635, 279, 2209, 85342, 99164, 11, 902, 14454, 220, 1041, 3610, 1667, 320, 5159, 81, 8, 1306, 1611, 332, 20110, 321, 355, 220, 972, 662, 1789, 279, 23931, 99164, 991, 37469, 1603, 666, 1590, 285, 11, 91621, 374, 13605, 439, 279, 19035, 315, 666, 1590, 285, 311, 21725, 529, 1948, 5814, 3235, 279, 99164, 11, 323, 279, 2349, 304, 1948, 5814, 505, 7347, 666, 1590, 285, 38973, 30170, 54, 13, 1789, 279, 1611, 332, 20110, 321, 355, 323, 2209, 85342, 31284, 8128, 991, 37469, 2391, 279, 3389, 18094, 315, 666, 1590, 285, 6650, 11, 91621, 374, 4529, 439, 279, 11668, 315, 666, 1590, 285, 529, 19035, 311, 1948, 5814, 31965, 1306, 279, 31284, 8128, 14454, 11, 323, 912, 19035, 505, 30170, 54, 320, 28753, 312, 25280, 1288, 12446, 2949, 22781, 315, 9214, 315, 1667, 311, 264, 2478, 3610, 1667, 1306, 279, 666, 1590, 285, 628, 3972, 25501, 279, 7479, 220, 508, 1174, 1790, 2753, 1109, 279, 220, 1041, 3092, 81, 477, 810, 430, 15812, 1990, 666, 1590, 285, 61568, 323, 1611, 332, 20110, 321, 355, 18488, 570, 3580, 19331, 369, 810, 3649, 13, 1226, 1501, 430, 279, 23931, 99164, 753, 86365, 505, 459, 26458, 354, 2335, 649, 387, 11497, 4661, 11622, 555, 91621, 4245, 311, 666, 1590, 285, 991, 16491, 320, 23966, 13, 220, 16, 7609, 5751, 1888, 5052, 320, 26378, 367, 320, 18, 8, 449, 1901, 284, 25173, 17, 13, 18, 13437, 8, 36508, 264, 3789, 84096, 9518, 5906, 6410, 48823, 81094, 315, 220, 15, 13, 21385, 13437, 11, 30139, 311, 279, 1493, 2819, 505, 86848, 263, 1880, 453, 662, 220, 605, 1174, 323, 11263, 279, 128257, 198, 128256, 78191, 198, 32, 502, 15398, 11125, 311, 10552, 1268, 21725, 6, 2231, 1413, 54280, 3782, 323, 4024, 927, 279, 1566, 220, 19, 7239, 1667, 24897, 430, 279, 54280, 14454, 3892, 7895, 3610, 1667, 6931, 323, 1051, 539, 439, 5655, 439, 3131, 3463, 13, 578, 14050, 555, 3980, 85404, 292, 1705, 520, 279, 3907, 315, 7188, 11, 33108, 11, 7902, 279, 14209, 315, 54280, 4216, 304, 21725, 3925, 311, 279, 10205, 315, 279, 13238, 1887, 596, 7928, 67164, 1887, 11, 666, 1590, 285, 11, 323, 22020, 279, 1401, 3560, 6476, 555, 3728, 24808, 304, 10923, 14812, 3090, 311, 3073, 389, 21725, 13, 330, 37461, 4919, 7217, 1253, 387, 3062, 304, 6968, 279, 4787, 369, 21725, 311, 387, 14739, 1359, 1071, 8096, 71035, 11, 264, 31613, 33108, 14561, 315, 9578, 323, 62938, 8198, 323, 10195, 3229, 315, 264, 5684, 26449, 304, 22037, 420, 2046, 323, 8621, 2930, 5587, 220, 777, 13, 13266, 21039, 430, 21725, 2646, 1047, 54280, 315, 14812, 3090, 3629, 1486, 311, 279, 2144, 430, 17989, 315, 279, 1404, 315, 279, 54280, 1541, 956, 503, 24459, 449, 17989, 315, 1268, 1790, 3090, 1436, 387, 8340, 3432, 439, 824, 99161, 42602, 26326, 323, 1268, 1790, 1436, 617, 28883, 1139, 3634, 13, 4314, 527, 279, 1925, 2671, 11, 2728, 430, 279, 25685, 10054, 19079, 1541, 956, 6782, 3403, 3090, 311, 5266, 459, 18435, 13, 578, 502, 1646, 55725, 430, 279, 54280, 14454, 1603, 477, 520, 279, 1890, 892, 439, 21725, 6, 7928, 67164, 4668, 11, 666, 1590, 285, 11, 4619, 315, 1306, 666, 1590, 285, 14454, 220, 18, 13, 22, 7239, 1667, 4227, 13, 9393, 666, 1590, 285, 574, 9333, 520, 430, 892, 11, 433, 1550, 539, 70584, 279, 11841, 439, 1790, 439, 433, 1550, 3010, 11, 304, 4040, 279, 78466, 430, 3504, 1455, 315, 279, 18671, 69766, 323, 527, 279, 62357, 14154, 66591, 291, 13, 578, 19821, 315, 40712, 278, 91621, 505, 666, 1590, 285, 3445, 279, 52840, 1053, 617, 1027, 4985, 1223, 11, 10168, 922, 4376, 279, 3090, 315, 6931, 17989, 13, 330, 791, 25329, 574, 430, 666, 1590, 285, 14454, 6288, 323, 4216, 11, 4856, 1109, 27115, 11, 323, 430, 279, 54280, 3782, 3010, 1359, 71035, 1071, 13, 330, 1687, 2351, 5605, 430, 279, 54280, 864, 1045, 323, 19780, 279, 58668, 704, 55619, 826, 430, 1903, 666, 1590, 285, 1210, 1102, 596, 4461, 11, 568, 3779, 11, 430, 666, 1590, 285, 993, 93176, 45612, 1139, 279, 16975, 430, 3549, 264, 3728, 24808, 477, 37647, 2515, 430, 5535, 14812, 3090, 311, 3073, 389, 279, 11841, 11, 323, 1101, 430, 67164, 61354, 1324, 3549, 12006, 430, 5535, 26326, 3090, 311, 5662, 279, 7479, 323, 5266, 279, 18671, 78466, 13, 23548, 279, 31284, 8128, 578, 1646, 1101, 32632, 2500, 5811, 2403, 54280, 25, 430, 279, 11223, 31284, 8128, 527, 1633, 42408, 11, 29865, 304, 2673, 555, 439, 1790, 439, 264, 15395, 21037, 11, 994, 814, 1288, 387, 2237, 11, 1093, 31284, 8128, 389, 9420, 13, 1115, 42408, 488, 1436, 387, 11497, 422, 279, 1176, 18435, 11, 2663, 23931, 11, 3940, 30164, 922, 220, 19, 7239, 1667, 4227, 323, 25281, 11, 422, 60769, 4501, 11, 2391, 439, 1790, 439, 279, 1176, 220, 508, 3346, 315, 666, 1590, 285, 596, 6650, 13, 578, 7982, 66306, 1053, 617, 42642, 279, 4363, 323, 409, 10365, 279, 99164, 927, 892, 11, 902, 1436, 10552, 279, 42408, 36394, 315, 279, 23931, 99164, 13, 35339, 11, 279, 42408, 99164, 315, 264, 17876, 18435, 11, 2663, 1611, 332, 20110, 321, 355, 11, 1436, 387, 11497, 422, 433, 14454, 2391, 279, 1566, 220, 1114, 3346, 315, 666, 1590, 285, 596, 6650, 11, 922, 220, 18, 13, 21, 7239, 1667, 4227, 13, 330, 9673, 31284, 8128, 1436, 617, 1027, 991, 37469, 555, 264, 3544, 2547, 315, 14812, 3090, 430, 25281, 1603, 323, 2391, 279, 991, 16491, 315, 666, 1590, 285, 11, 4619, 315, 27905, 1359, 1071, 1176, 3229, 8563, 18002, 2298, 11, 264, 31613, 33108, 19560, 5575, 13, 18002, 2298, 690, 3118, 264, 5684, 922, 279, 502, 6492, 389, 5587, 220, 508, 520, 279, 9974, 79195, 323, 9878, 16238, 10170, 10017, 304, 8421, 13, 666, 1590, 285, 11, 1457, 264, 220, 20, 11, 931, 12934, 321, 21037, 25480, 44779, 535, 6485, 11, 5727, 1063, 315, 279, 8706, 36373, 7217, 304, 279, 13238, 1887, 323, 83978, 279, 1948, 5814, 315, 21725, 13, 9420, 11, 11157, 279, 23899, 323, 220, 605, 3115, 810, 11191, 1109, 21725, 11, 706, 912, 13890, 68366, 4668, 13, 666, 1590, 285, 596, 20155, 11705, 264, 7173, 713, 389, 279, 14329, 3185, 315, 279, 11841, 323, 264, 18710, 42436, 1990, 13, 1115, 15100, 3249, 17989, 315, 279, 8286, 315, 3090, 279, 18671, 78466, 1436, 3412, 3196, 389, 3432, 596, 1948, 5814, 527, 11157, 1148, 279, 502, 4007, 17989, 3196, 389, 279, 1948, 5814, 220, 19, 7239, 1667, 4227, 13, 1561, 31178, 1043, 64805, 2362, 71035, 11, 889, 4211, 279, 5419, 8798, 6530, 315, 21725, 11, 1778, 439, 279, 16448, 628, 19131, 315, 22337, 2002, 7091, 430, 44779, 1139, 36373, 7217, 520, 279, 7479, 11, 6818, 311, 10552, 279, 42408, 31284, 8128, 315, 279, 78466, 315, 21725, 220, 806, 1667, 4227, 449, 2500, 10334, 13, 1283, 323, 4846, 19560, 5575, 16844, 86848, 263, 12090, 430, 666, 1590, 285, 11, 902, 574, 1243, 3463, 311, 617, 44853, 520, 3117, 18671, 6987, 21237, 11, 574, 779, 11191, 430, 433, 9057, 279, 12903, 8183, 315, 21725, 311, 3351, 3892, 16579, 8931, 10007, 11, 21939, 1022, 279, 31284, 8128, 13, 8876, 1243, 11, 4869, 11, 3885, 617, 6982, 430, 666, 1590, 285, 44853, 1193, 922, 220, 508, 12628, 3485, 279, 3312, 859, 11, 308, 953, 287, 430, 10334, 13, 2030, 71035, 323, 18002, 2298, 3782, 709, 449, 2500, 4623, 11, 430, 279, 31284, 8128, 1436, 617, 1027, 1880, 2454, 439, 666, 1590, 285, 574, 7982, 11, 539, 49043, 13, 578, 502, 10334, 1101, 649, 2759, 369, 279, 14713, 315, 34681, 14488, 555, 36612, 3090, 520, 2212, 279, 1890, 892, 13, 330, 2028, 374, 264, 31178, 1359, 71035, 46728, 13, 330, 4071, 14248, 649, 656, 810, 24473, 5029, 315, 666, 1590, 285, 323, 279, 31284, 8128, 311, 1518, 422, 433, 10187, 709, 1210, 22146, 596, 1828, 21725, 4363, 261, 11, 279, 763, 50, 492, 9131, 320, 86225, 76022, 1701, 1369, 55194, 89205, 11, 4323, 2601, 88, 323, 27162, 17159, 705, 1436, 1520, 4320, 279, 3488, 13, 78196, 369, 7195, 304, 3297, 11, 433, 690, 2035, 264, 513, 2191, 21037, 389, 279, 7479, 311, 22477, 279, 15135, 323, 8530, 1505, 20268, 73440, 315, 430, 14154, 18435, 11, 477, 1524, 14812, 3090, 13, 220, 128257, 198 ]

2,521

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The R2TP/Prefoldin-like co-chaperone, in concert with HSP90, facilitates assembly and cellular stability of RNA polymerase II, and complexes of PI3-kinase-like kinases such as mTOR. However, the mechanism by which this occurs is poorly understood. Here we use cryo-EM and biochemical studies on the human R2TP core (RUVBL1–RUVBL2–RPAP3–PIH1D1) which reveal the distinctive role of RPAP3, distinguishing metazoan R2TP from the smaller yeast equivalent. RPAP3 spans both faces of a single RUVBL ring, providing an extended scaffold that recruits clients and provides a flexible tether for HSP90. A 3.6 Å cryo-EM structure reveals direct interaction of a C-terminal domain of RPAP3 and the ATPase domain of RUVBL2, necessary for human R2TP assembly but absent from yeast. The mobile TPR domains of RPAP3 map to the opposite face of the ring, associating with PIH1D1, which mediates client protein recruitment. Thus, RPAP3 provides a flexible platform for bringing HSP90 into proximity with diverse client proteins. Introduction The R2TP/Prefoldin-like (R2TP/PFDL) complex collaborates with the HSP90 molecular chaperone to facilitate assembly, activation, and cellular stability of a range of multiprotein complexes, including RNA polymerase II (Pol II), complexes of PI3 kinase-like kinases (PIKKs) such as TOR and SMG1, and small nuclear ribonuclear protein (snRNPs) complexes, amongst others 1 , 2 , 3 , 4 , 5 , 6 , 7 . Yeast R2TP complexes comprise four subunits, RuvB-like AAA+ ATPases Rvb1p and Rvb2p, a TPR domain-containing protein Tah1p, and a PIH domain protein Pih1p. Metazoan R2TP complexes contain the orthologous proteins RUVBL1, RUVBL2, RPAP3, and PIH1D1, respectively. However, whereas the TPR domain-containing component of the yeast R2TP complex is a small (12 kDa) protein, Tah1p, in human R2TP this is a large (75 kDa) multi-domain protein, RPAP3 (RNA polymerase II associated protein 3) (or hSPAGH), containing two TPR domains. The C-terminal region in RPAP3 has been annotated as a protein domain (pfam13877), which is also present in other proteins, such as CCDC103 8 , a dynein arm assembly factor that interacts with RUVBL2 9 . In mammals, the R2TP core components associate with additional subunits of the prefoldin (PFDL) module, forming the R2TP/PFDL complex. This PFDL module includes prefoldin and prefoldin-like proteins PFDN2, PFDN6, URI1, UXT, PDRG1, and it associates with two additional components, the RNA polymerase subunit POLR2E/RPB5 and WDR92/Monad 5 , 10 . In addition, R2TP/PFDL interacts with additional proteins that serve as adaptors between R2TP/PFDL and the clients (see later) 5 , 11 , 12 . RPAP3 was first identified and named after a systematic analysis of complexes containing components of the transcription and RNA processing machineries using protein affinity purification coupled to mass spectrometry 13 . RPAP3 was then found to be a component of the multi-subunit R2TP/PFDL complex 14 . Subsequently it was found to associate with Pol II subunits and HSP90 when Pol II assembly is blocked by α-amanitin, implicating both RPAP3 and HSP90 in Pol II assembly in the cytoplasm 10 . Pol II subunits RPB1, RPB2, and RPB5 all co-precipitate with RPAP3, but RPAP3 seems to associate independently with RPB1 and RPB5-containing complexes, suggesting the existence of different RPAP3 complexes as intermediates in Pol II assembly. RPAP3 also binds some subunits of RNA Pol I and it may therefore play a more general role in the assembly of all RNA polymerases 10 . The mechanistic details of how RNA Pol II subunits are recruited to R2TP and how R2TP and HSP90 contribute to Pol II assembly are poorly understood. Unconventional prefoldin RPB5 Interactor 1 (URI1) interacts with the RPB5/POLR2E subunit of Pol II, and this suggests that the PFDL module contributes to recruit Pol II assembly intermediates to the R2TP/PFLD complex 10 , 15 . Recruitment of PIKK proteins to R2TP is mediated by the phosphopeptide-binding PIH domain at the N-terminus of Pih1p/PIH1D1, which recognizes a specific phosphorylated acidic motif, generated by casein kinase 2 (CK2) 2 , 3 , 4 . This motif is conserved in Tel2p/TELO2, a component of the TTT (Tel2p/TELO2–Tti1p/TTI1–Tti2p/TTI2) complex that also interacts directly with PIKKs, thereby bridging their interaction to R2TP. A similar PIH-binding motif is also found in Mre11p/MRE11A suggesting that R2TP may also play a role in the assembly of MRN complexes involved in DNA double-strand break repair 2 . Neither Pol II nor snRNPs subunits contain this motif, and must therefore be recruited to R2TP through alternative mechanisms. Biogenesis of box C/D snoRNP requires R2TP and additional factors such as NUFIP1 and the Zinc-finger HIT domain proteins ZNHIT3 and ZNHIT6, which have been proposed to function as adaptors between R2TP and C/D core proteins 12 . Interestingly, ZNHIT2, another protein of the same family, was recently shown to bind RUVBL2 and regulate assembly of U5 small ribonucleoprotein 5 . ZNHIT2 may function as a bridging factor between the U5 snRNP and the R2TP/PFDL, a function where the Ecdysoneless (ECD) protein could also contribute 5 , 16 . Human ECD homolog interacts with the pre-mRNA-processing-splicing factor 8 (PRPF8) 17 , and the R2TP 18 . Phosphorylated ECD interacts with the PIH1D1 subunit, as well as with RUVBL1 in a phosphorylation-independent manner 18 . Therefore, it seems that sets of different adaptors collaborate to bring specific clients to R2TP/PFLD. Previous structural and biochemical studies have defined most of the pairwise interactions of R2TP core components. The TPR domain of yeast Tah1p mediates interaction with the conserved MEEVD C-terminal tail peptide of HSP90 2 , 19 , 20 , 21 , 22 , while its C-terminal extension couples Tah1p to the CS-domain of Pih1p 2 , 21 . The central region of Pih1p mediates recruitment of Pih1p–Tah1p to the Rvb1p–Rvb2p heterohexameric ring 23 , 24 . The N-terminal PIH domain of Pih1p/PIH1D1 binds a CK2-phosphorylation motif on Tel2p/TELO2, mediating recruitment of the TTT complex to R2TP 2 , 3 . Most recently, we have determined the cryo-EM structure of the intact yeast R2TP complex, in which a single Tah1p–Pih1p sub-complex binds a heterohexameric Rvb1–Rvb2 ring 24 , a finding subsequently confirmed by others 25 . In metazoan R2TP, the small (12", "role": "user" }, { "content": "A team from the Spanish National Cancer Research Centre (CNIO) has determined for the first time the high-resolution structure of a complex (R2TP) involved in key processes for cell survival and in diseases such as cancer. This achievement was made with high-resolution cryo-electron microscopy, a technique brought to the CNIO by Óscar Llorca, director of the Structural Biology Programme and lead author on the paper published in Nature Communications. In 2017, the Nobel Prize for Chemistry was awarded to three scientists (Jacques Dubochet, Joachim Frank, and Richard Henderson) for their work on the development of cryo-electron microscopy. This technique can capture images of individual molecules, which are used to determine their structure and to ascertain biological processes in atomic detail. Óscar Llorca and his team have used this technique to learn about the structure and functioning of a complex system called R2TP, which is involved in key processes for cell survival such as the activation of the kinases mTOR, ATR and ATM, proteins that are the target of various cancer drugs currently being developed. mTOR, ATR and other related kinases do not work in isolation but rather by interacting and forming complexes with other proteins, which are essential for their normal functioning. The assembly of these structures with multiple components does not take place in cells spontaneously. The R2TP system and the HSP90 chaperone are crucial for the assembly and activation of mTOR and other related kinases, but how this happens in cells is still somewhat of a mystery. \"If we understand this assembly pathway, :explains the researcher, \"we will be able to identify new ways of targeting the activity of these kinases.\" Thanks to cryo-electron microscopy, \"we have been able to visualise, for the first time, the high-resolution structure of the human R2TP system,\" says Llorca. The researchers were surprised by the unexpected complexity of the human R2TP system compared to its yeast homologues. The microscope images show that R2TP is a large platform capable of putting HSP90 in contact with the kinases on which HSP90 must act. When viewed under the microscope, R2TP looks like a jellyfish with three very flexible tentacles made up of RPAP3 protein. The kinases of the mTOR family are recruited to the base of its head, while HSP90 is hooked by the tentacles and taken to the kinases, thanks to their flexibility. \"This first observation of the human R2TP system has allowed us to understand its structure and functioning mechanisms, which were previously unknown. Our next steps will be to study the details of how R2TP and HSP90 are able to assemble the complexes made up of kinases of the mTOR family, in order to find ways of interfering with these processes,\" concludes Llorca. \"The R2TP system is also involved in the activation of other essential molecules for the cell and in the development of cancer, such as the RNA polymerase, telomerase, or the 'splicing' system, areas that we intend to explore in the future.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The R2TP/Prefoldin-like co-chaperone, in concert with HSP90, facilitates assembly and cellular stability of RNA polymerase II, and complexes of PI3-kinase-like kinases such as mTOR. However, the mechanism by which this occurs is poorly understood. Here we use cryo-EM and biochemical studies on the human R2TP core (RUVBL1–RUVBL2–RPAP3–PIH1D1) which reveal the distinctive role of RPAP3, distinguishing metazoan R2TP from the smaller yeast equivalent. RPAP3 spans both faces of a single RUVBL ring, providing an extended scaffold that recruits clients and provides a flexible tether for HSP90. A 3.6 Å cryo-EM structure reveals direct interaction of a C-terminal domain of RPAP3 and the ATPase domain of RUVBL2, necessary for human R2TP assembly but absent from yeast. The mobile TPR domains of RPAP3 map to the opposite face of the ring, associating with PIH1D1, which mediates client protein recruitment. Thus, RPAP3 provides a flexible platform for bringing HSP90 into proximity with diverse client proteins. Introduction The R2TP/Prefoldin-like (R2TP/PFDL) complex collaborates with the HSP90 molecular chaperone to facilitate assembly, activation, and cellular stability of a range of multiprotein complexes, including RNA polymerase II (Pol II), complexes of PI3 kinase-like kinases (PIKKs) such as TOR and SMG1, and small nuclear ribonuclear protein (snRNPs) complexes, amongst others 1 , 2 , 3 , 4 , 5 , 6 , 7 . Yeast R2TP complexes comprise four subunits, RuvB-like AAA+ ATPases Rvb1p and Rvb2p, a TPR domain-containing protein Tah1p, and a PIH domain protein Pih1p. Metazoan R2TP complexes contain the orthologous proteins RUVBL1, RUVBL2, RPAP3, and PIH1D1, respectively. However, whereas the TPR domain-containing component of the yeast R2TP complex is a small (12 kDa) protein, Tah1p, in human R2TP this is a large (75 kDa) multi-domain protein, RPAP3 (RNA polymerase II associated protein 3) (or hSPAGH), containing two TPR domains. The C-terminal region in RPAP3 has been annotated as a protein domain (pfam13877), which is also present in other proteins, such as CCDC103 8 , a dynein arm assembly factor that interacts with RUVBL2 9 . In mammals, the R2TP core components associate with additional subunits of the prefoldin (PFDL) module, forming the R2TP/PFDL complex. This PFDL module includes prefoldin and prefoldin-like proteins PFDN2, PFDN6, URI1, UXT, PDRG1, and it associates with two additional components, the RNA polymerase subunit POLR2E/RPB5 and WDR92/Monad 5 , 10 . In addition, R2TP/PFDL interacts with additional proteins that serve as adaptors between R2TP/PFDL and the clients (see later) 5 , 11 , 12 . RPAP3 was first identified and named after a systematic analysis of complexes containing components of the transcription and RNA processing machineries using protein affinity purification coupled to mass spectrometry 13 . RPAP3 was then found to be a component of the multi-subunit R2TP/PFDL complex 14 . Subsequently it was found to associate with Pol II subunits and HSP90 when Pol II assembly is blocked by α-amanitin, implicating both RPAP3 and HSP90 in Pol II assembly in the cytoplasm 10 . Pol II subunits RPB1, RPB2, and RPB5 all co-precipitate with RPAP3, but RPAP3 seems to associate independently with RPB1 and RPB5-containing complexes, suggesting the existence of different RPAP3 complexes as intermediates in Pol II assembly. RPAP3 also binds some subunits of RNA Pol I and it may therefore play a more general role in the assembly of all RNA polymerases 10 . The mechanistic details of how RNA Pol II subunits are recruited to R2TP and how R2TP and HSP90 contribute to Pol II assembly are poorly understood. Unconventional prefoldin RPB5 Interactor 1 (URI1) interacts with the RPB5/POLR2E subunit of Pol II, and this suggests that the PFDL module contributes to recruit Pol II assembly intermediates to the R2TP/PFLD complex 10 , 15 . Recruitment of PIKK proteins to R2TP is mediated by the phosphopeptide-binding PIH domain at the N-terminus of Pih1p/PIH1D1, which recognizes a specific phosphorylated acidic motif, generated by casein kinase 2 (CK2) 2 , 3 , 4 . This motif is conserved in Tel2p/TELO2, a component of the TTT (Tel2p/TELO2–Tti1p/TTI1–Tti2p/TTI2) complex that also interacts directly with PIKKs, thereby bridging their interaction to R2TP. A similar PIH-binding motif is also found in Mre11p/MRE11A suggesting that R2TP may also play a role in the assembly of MRN complexes involved in DNA double-strand break repair 2 . Neither Pol II nor snRNPs subunits contain this motif, and must therefore be recruited to R2TP through alternative mechanisms. Biogenesis of box C/D snoRNP requires R2TP and additional factors such as NUFIP1 and the Zinc-finger HIT domain proteins ZNHIT3 and ZNHIT6, which have been proposed to function as adaptors between R2TP and C/D core proteins 12 . Interestingly, ZNHIT2, another protein of the same family, was recently shown to bind RUVBL2 and regulate assembly of U5 small ribonucleoprotein 5 . ZNHIT2 may function as a bridging factor between the U5 snRNP and the R2TP/PFDL, a function where the Ecdysoneless (ECD) protein could also contribute 5 , 16 . Human ECD homolog interacts with the pre-mRNA-processing-splicing factor 8 (PRPF8) 17 , and the R2TP 18 . Phosphorylated ECD interacts with the PIH1D1 subunit, as well as with RUVBL1 in a phosphorylation-independent manner 18 . Therefore, it seems that sets of different adaptors collaborate to bring specific clients to R2TP/PFLD. Previous structural and biochemical studies have defined most of the pairwise interactions of R2TP core components. The TPR domain of yeast Tah1p mediates interaction with the conserved MEEVD C-terminal tail peptide of HSP90 2 , 19 , 20 , 21 , 22 , while its C-terminal extension couples Tah1p to the CS-domain of Pih1p 2 , 21 . The central region of Pih1p mediates recruitment of Pih1p–Tah1p to the Rvb1p–Rvb2p heterohexameric ring 23 , 24 . The N-terminal PIH domain of Pih1p/PIH1D1 binds a CK2-phosphorylation motif on Tel2p/TELO2, mediating recruitment of the TTT complex to R2TP 2 , 3 . Most recently, we have determined the cryo-EM structure of the intact yeast R2TP complex, in which a single Tah1p–Pih1p sub-complex binds a heterohexameric Rvb1–Rvb2 ring 24 , a finding subsequently confirmed by others 25 . In metazoan R2TP, the small (12<|im_end|> <|im_start|>assistant A team from the Spanish National Cancer Research Centre (CNIO) has determined for the first time the high-resolution structure of a complex (R2TP) involved in key processes for cell survival and in diseases such as cancer. This achievement was made with high-resolution cryo-electron microscopy, a technique brought to the CNIO by Óscar Llorca, director of the Structural Biology Programme and lead author on the paper published in Nature Communications. In 2017, the Nobel Prize for Chemistry was awarded to three scientists (Jacques Dubochet, Joachim Frank, and Richard Henderson) for their work on the development of cryo-electron microscopy. This technique can capture images of individual molecules, which are used to determine their structure and to ascertain biological processes in atomic detail. Óscar Llorca and his team have used this technique to learn about the structure and functioning of a complex system called R2TP, which is involved in key processes for cell survival such as the activation of the kinases mTOR, ATR and ATM, proteins that are the target of various cancer drugs currently being developed. mTOR, ATR and other related kinases do not work in isolation but rather by interacting and forming complexes with other proteins, which are essential for their normal functioning. The assembly of these structures with multiple components does not take place in cells spontaneously. The R2TP system and the HSP90 chaperone are crucial for the assembly and activation of mTOR and other related kinases, but how this happens in cells is still somewhat of a mystery. "If we understand this assembly pathway, :explains the researcher, "we will be able to identify new ways of targeting the activity of these kinases." Thanks to cryo-electron microscopy, "we have been able to visualise, for the first time, the high-resolution structure of the human R2TP system," says Llorca. The researchers were surprised by the unexpected complexity of the human R2TP system compared to its yeast homologues. The microscope images show that R2TP is a large platform capable of putting HSP90 in contact with the kinases on which HSP90 must act. When viewed under the microscope, R2TP looks like a jellyfish with three very flexible tentacles made up of RPAP3 protein. The kinases of the mTOR family are recruited to the base of its head, while HSP90 is hooked by the tentacles and taken to the kinases, thanks to their flexibility. "This first observation of the human R2TP system has allowed us to understand its structure and functioning mechanisms, which were previously unknown. Our next steps will be to study the details of how R2TP and HSP90 are able to assemble the complexes made up of kinases of the mTOR family, in order to find ways of interfering with these processes," concludes Llorca. "The R2TP system is also involved in the activation of other essential molecules for the cell and in the development of cancer, such as the RNA polymerase, telomerase, or the 'splicing' system, areas that we intend to explore in the future." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 432, 17, 4334, 16744, 1116, 820, 258, 12970, 1080, 11843, 3271, 606, 11, 304, 21497, 449, 473, 4695, 1954, 11, 73633, 14956, 323, 35693, 20334, 315, 41214, 47393, 521, 8105, 11, 323, 69125, 315, 23396, 18, 12, 8148, 521, 12970, 24890, 2315, 1778, 439, 296, 50758, 13, 4452, 11, 279, 17383, 555, 902, 420, 13980, 374, 31555, 16365, 13, 5810, 584, 1005, 16106, 78, 12, 2783, 323, 93532, 7978, 389, 279, 3823, 432, 17, 4334, 6332, 320, 49, 23042, 9574, 16, 4235, 49, 23042, 9574, 17, 4235, 22394, 2599, 18, 4235, 1932, 39, 16, 35, 16, 8, 902, 16805, 279, 35947, 3560, 315, 42561, 2599, 18, 11, 86055, 2322, 41284, 276, 432, 17, 4334, 505, 279, 9333, 41580, 13890, 13, 42561, 2599, 18, 45395, 2225, 12580, 315, 264, 3254, 432, 23042, 9574, 10264, 11, 8405, 459, 11838, 85552, 430, 56197, 8403, 323, 5825, 264, 19303, 80665, 369, 473, 4695, 1954, 13, 362, 220, 18, 13, 21, 80352, 16106, 78, 12, 2783, 6070, 21667, 2167, 16628, 315, 264, 356, 91723, 8106, 315, 42561, 2599, 18, 323, 279, 67656, 521, 8106, 315, 432, 23042, 9574, 17, 11, 5995, 369, 3823, 432, 17, 4334, 14956, 719, 28310, 505, 41580, 13, 578, 6505, 350, 6616, 31576, 315, 42561, 2599, 18, 2472, 311, 279, 14329, 3663, 315, 279, 10264, 11, 4189, 1113, 449, 23396, 39, 16, 35, 16, 11, 902, 25098, 988, 3016, 13128, 34102, 13, 14636, 11, 42561, 2599, 18, 5825, 264, 19303, 5452, 369, 12967, 473, 4695, 1954, 1139, 37843, 449, 17226, 3016, 28896, 13, 29438, 578, 432, 17, 4334, 16744, 1116, 820, 258, 12970, 320, 49, 17, 4334, 16744, 14938, 43, 8, 6485, 11430, 988, 449, 279, 473, 4695, 1954, 31206, 523, 3271, 606, 311, 28696, 14956, 11, 15449, 11, 323, 35693, 20334, 315, 264, 2134, 315, 12842, 91748, 69125, 11, 2737, 41214, 47393, 521, 8105, 320, 15000, 8105, 705, 69125, 315, 23396, 18, 82160, 12970, 24890, 2315, 320, 1932, 51557, 82, 8, 1778, 439, 71061, 323, 14031, 38, 16, 11, 323, 2678, 11499, 20735, 263, 9834, 13128, 320, 9810, 51295, 21051, 8, 69125, 11, 24059, 3885, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 1174, 220, 22, 662, 32269, 561, 432, 17, 4334, 69125, 54350, 3116, 1207, 26726, 11, 432, 12328, 33, 12970, 48197, 10, 67656, 2315, 432, 43505, 16, 79, 323, 432, 43505, 17, 79, 11, 264, 350, 6616, 8106, 93871, 13128, 58087, 16, 79, 11, 323, 264, 23396, 39, 8106, 13128, 393, 7141, 16, 79, 13, 6344, 41284, 276, 432, 17, 4334, 69125, 6782, 279, 30299, 1640, 788, 28896, 432, 23042, 9574, 16, 11, 432, 23042, 9574, 17, 11, 42561, 2599, 18, 11, 323, 23396, 39, 16, 35, 16, 11, 15947, 13, 4452, 11, 20444, 279, 350, 6616, 8106, 93871, 3777, 315, 279, 41580, 432, 17, 4334, 6485, 374, 264, 2678, 320, 717, 597, 31516, 8, 13128, 11, 58087, 16, 79, 11, 304, 3823, 432, 17, 4334, 420, 374, 264, 3544, 320, 2075, 597, 31516, 8, 7447, 73894, 13128, 11, 42561, 2599, 18, 320, 31820, 47393, 521, 8105, 5938, 13128, 220, 18, 8, 320, 269, 305, 4695, 1929, 39, 705, 8649, 1403, 350, 6616, 31576, 13, 578, 356, 91723, 5654, 304, 42561, 2599, 18, 706, 1027, 63951, 439, 264, 13128, 8106, 320, 16276, 309, 10350, 2813, 705, 902, 374, 1101, 3118, 304, 1023, 28896, 11, 1778, 439, 13844, 5744, 6889, 220, 23, 1174, 264, 14282, 818, 258, 6916, 14956, 8331, 430, 84261, 449, 432, 23042, 9574, 17, 220, 24, 662, 763, 56669, 11, 279, 432, 17, 4334, 6332, 6956, 22712, 449, 5217, 1207, 26726, 315, 279, 19257, 820, 258, 320, 47, 14938, 43, 8, 4793, 11, 30164, 279, 432, 17, 4334, 16744, 14938, 43, 6485, 13, 1115, 393, 14938, 43, 4793, 5764, 19257, 820, 258, 323, 19257, 820, 258, 12970, 28896, 393, 14938, 45, 17, 11, 393, 14938, 45, 21, 11, 16403, 16, 11, 549, 9213, 11, 393, 7842, 38, 16, 11, 323, 433, 40531, 449, 1403, 5217, 6956, 11, 279, 41214, 47393, 521, 1207, 3928, 32740, 49, 17, 36, 19945, 41737, 20, 323, 468, 7842, 6083, 10482, 263, 329, 220, 20, 1174, 220, 605, 662, 763, 5369, 11, 432, 17, 4334, 16744, 14938, 43, 84261, 449, 5217, 28896, 430, 8854, 439, 10737, 1105, 1990, 432, 17, 4334, 16744, 14938, 43, 323, 279, 8403, 320, 4151, 3010, 8, 220, 20, 1174, 220, 806, 1174, 220, 717, 662, 42561, 2599, 18, 574, 1176, 11054, 323, 7086, 1306, 264, 37538, 6492, 315, 69125, 8649, 6956, 315, 279, 46940, 323, 41214, 8863, 8002, 258, 4804, 1701, 13128, 51552, 94536, 34356, 311, 3148, 9618, 442, 15501, 220, 1032, 662, 42561, 2599, 18, 574, 1243, 1766, 311, 387, 264, 3777, 315, 279, 7447, 18451, 3928, 432, 17, 4334, 16744, 14938, 43, 6485, 220, 975, 662, 3804, 39742, 433, 574, 1766, 311, 22712, 449, 3735, 8105, 1207, 26726, 323, 473, 4695, 1954, 994, 3735, 8105, 14956, 374, 19857, 555, 19581, 12, 13005, 85986, 11, 92195, 1113, 2225, 42561, 2599, 18, 323, 473, 4695, 1954, 304, 3735, 8105, 14956, 304, 279, 9693, 99705, 10753, 220, 605, 662, 3735, 8105, 1207, 26726, 432, 41737, 16, 11, 432, 41737, 17, 11, 323, 432, 41737, 20, 682, 1080, 12, 10872, 575, 20227, 449, 42561, 2599, 18, 11, 719, 42561, 2599, 18, 5084, 311, 22712, 29235, 449, 432, 41737, 16, 323, 432, 41737, 20, 93871, 69125, 11, 23377, 279, 14209, 315, 2204, 42561, 2599, 18, 69125, 439, 55275, 988, 304, 3735, 8105, 14956, 13, 42561, 2599, 18, 1101, 58585, 1063, 1207, 26726, 315, 41214, 3735, 358, 323, 433, 1253, 9093, 1514, 264, 810, 4689, 3560, 304, 279, 14956, 315, 682, 41214, 47393, 2315, 220, 605, 662, 578, 7852, 4633, 3649, 315, 1268, 41214, 3735, 8105, 1207, 26726, 527, 45425, 311, 432, 17, 4334, 323, 1268, 432, 17, 4334, 323, 473, 4695, 1954, 17210, 311, 3735, 8105, 14956, 527, 31555, 16365, 13, 1252, 444, 44322, 19257, 820, 258, 432, 41737, 20, 5783, 5739, 220, 16, 320, 10514, 16, 8, 84261, 449, 279, 432, 41737, 20, 16744, 1971, 49, 17, 36, 1207, 3928, 315, 3735, 8105, 11, 323, 420, 13533, 430, 279, 393, 14938, 43, 4793, 44072, 311, 20927, 3735, 8105, 14956, 55275, 988, 311, 279, 432, 17, 4334, 16744, 6254, 35, 6485, 220, 605, 1174, 220, 868, 662, 57544, 315, 23396, 51557, 28896, 311, 432, 17, 4334, 374, 78926, 555, 279, 33088, 2862, 47309, 65500, 23396, 39, 8106, 520, 279, 452, 12, 23827, 355, 315, 393, 7141, 16, 79, 14, 1932, 39, 16, 35, 16, 11, 902, 45799, 264, 3230, 95089, 22851, 84903, 60612, 11, 8066, 555, 1162, 258, 82160, 220, 17, 320, 3096, 17, 8, 220, 17, 1174, 220, 18, 1174, 220, 19, 662, 1115, 60612, 374, 1615, 2841, 304, 23683, 17, 79, 14, 2505, 1623, 17, 11, 264, 3777, 315, 279, 350, 15249, 320, 38342, 17, 79, 14, 2505, 1623, 17, 4235, 51, 10462, 16, 79, 126970, 40, 16, 4235, 51, 10462, 17, 79, 126970, 40, 17, 8, 6485, 430, 1101, 84261, 6089, 449, 23396, 51557, 82, 11, 28592, 77847, 3252, 872, 16628, 311, 432, 17, 4334, 13, 362, 4528, 23396, 39, 65500, 60612, 374, 1101, 1766, 304, 386, 265, 806, 79, 10482, 793, 806, 32, 23377, 430, 432, 17, 4334, 1253, 1101, 1514, 264, 3560, 304, 279, 14956, 315, 29433, 45, 69125, 6532, 304, 15922, 2033, 42728, 438, 1464, 13023, 220, 17, 662, 25215, 3735, 8105, 6463, 4224, 51295, 21051, 1207, 26726, 6782, 420, 60612, 11, 323, 2011, 9093, 387, 45425, 311, 432, 17, 4334, 1555, 10778, 24717, 13, 12371, 52379, 315, 3830, 356, 15302, 66184, 49, 27321, 7612, 432, 17, 4334, 323, 5217, 9547, 1778, 439, 452, 21180, 3378, 16, 323, 279, 96499, 2269, 5248, 79503, 8106, 28896, 1901, 52371, 964, 18, 323, 1901, 52371, 964, 21, 11, 902, 617, 1027, 11223, 311, 734, 439, 10737, 1105, 1990, 432, 17, 4334, 323, 356, 15302, 6332, 28896, 220, 717, 662, 58603, 11, 1901, 52371, 964, 17, 11, 2500, 13128, 315, 279, 1890, 3070, 11, 574, 6051, 6982, 311, 10950, 432, 23042, 9574, 17, 323, 37377, 14956, 315, 549, 20, 2678, 20735, 263, 22935, 454, 91748, 220, 20, 662, 1901, 52371, 964, 17, 1253, 734, 439, 264, 77847, 3252, 8331, 1990, 279, 549, 20, 4224, 49, 27321, 323, 279, 432, 17, 4334, 16744, 14938, 43, 11, 264, 734, 1405, 279, 469, 4484, 1065, 606, 1752, 320, 36, 6620, 8, 13128, 1436, 1101, 17210, 220, 20, 1174, 220, 845, 662, 11344, 469, 6620, 5105, 1640, 84261, 449, 279, 864, 1474, 31820, 70293, 23032, 90214, 8331, 220, 23, 320, 6616, 20280, 23, 8, 220, 1114, 1174, 323, 279, 432, 17, 4334, 220, 972, 662, 2405, 24527, 683, 22851, 469, 6620, 84261, 449, 279, 23396, 39, 16, 35, 16, 1207, 3928, 11, 439, 1664, 439, 449, 432, 23042, 9574, 16, 304, 264, 95089, 2354, 98885, 11827, 220, 972, 662, 15636, 11, 433, 5084, 430, 7437, 315, 2204, 10737, 1105, 51696, 311, 4546, 3230, 8403, 311, 432, 17, 4334, 16744, 6254, 35, 13, 30013, 24693, 323, 93532, 7978, 617, 4613, 1455, 315, 279, 93859, 22639, 315, 432, 17, 4334, 6332, 6956, 13, 578, 350, 6616, 8106, 315, 41580, 58087, 16, 79, 25098, 988, 16628, 449, 279, 1615, 2841, 386, 7244, 12757, 356, 91723, 9986, 72249, 315, 473, 4695, 1954, 220, 17, 1174, 220, 777, 1174, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 1174, 1418, 1202, 356, 91723, 9070, 21961, 58087, 16, 79, 311, 279, 10211, 73894, 315, 393, 7141, 16, 79, 220, 17, 1174, 220, 1691, 662, 578, 8792, 5654, 315, 393, 7141, 16, 79, 25098, 988, 34102, 315, 393, 7141, 16, 79, 4235, 51, 1494, 16, 79, 311, 279, 432, 43505, 16, 79, 4235, 49, 43505, 17, 79, 30548, 2319, 42716, 11893, 10264, 220, 1419, 1174, 220, 1187, 662, 578, 452, 91723, 23396, 39, 8106, 315, 393, 7141, 16, 79, 14, 1932, 39, 16, 35, 16, 58585, 264, 31166, 17, 63837, 24527, 683, 2354, 60612, 389, 23683, 17, 79, 14, 2505, 1623, 17, 11, 1812, 23747, 34102, 315, 279, 350, 15249, 6485, 311, 432, 17, 4334, 220, 17, 1174, 220, 18, 662, 7648, 6051, 11, 584, 617, 11075, 279, 16106, 78, 12, 2783, 6070, 315, 279, 35539, 41580, 432, 17, 4334, 6485, 11, 304, 902, 264, 3254, 58087, 16, 79, 4235, 47, 7141, 16, 79, 1207, 11733, 9289, 58585, 264, 30548, 2319, 42716, 11893, 432, 43505, 16, 4235, 49, 43505, 17, 10264, 220, 1187, 1174, 264, 9455, 28520, 11007, 555, 3885, 220, 914, 662, 763, 2322, 41284, 276, 432, 17, 4334, 11, 279, 2678, 320, 717, 128257, 198, 128256, 78191, 198, 32, 2128, 505, 279, 15506, 5165, 26211, 8483, 14821, 320, 29768, 3895, 8, 706, 11075, 369, 279, 1176, 892, 279, 1579, 64036, 6070, 315, 264, 6485, 320, 49, 17, 4334, 8, 6532, 304, 1401, 11618, 369, 2849, 20237, 323, 304, 19338, 1778, 439, 9572, 13, 1115, 26501, 574, 1903, 449, 1579, 64036, 16106, 78, 37081, 2298, 92914, 11, 264, 15105, 7263, 311, 279, 25914, 3895, 555, 1717, 241, 25529, 445, 9761, 936, 11, 7690, 315, 279, 73800, 40023, 47516, 323, 3063, 3229, 389, 279, 5684, 4756, 304, 22037, 26545, 13, 763, 220, 679, 22, 11, 279, 48078, 32293, 369, 42846, 574, 22034, 311, 2380, 14248, 320, 83929, 14295, 17533, 5059, 295, 11, 11186, 613, 318, 9454, 11, 323, 12131, 45677, 8, 369, 872, 990, 389, 279, 4500, 315, 16106, 78, 37081, 2298, 92914, 13, 1115, 15105, 649, 12602, 5448, 315, 3927, 35715, 11, 902, 527, 1511, 311, 8417, 872, 6070, 323, 311, 77277, 24156, 11618, 304, 25524, 7872, 13, 1717, 241, 25529, 445, 9761, 936, 323, 813, 2128, 617, 1511, 420, 15105, 311, 4048, 922, 279, 6070, 323, 31301, 315, 264, 6485, 1887, 2663, 432, 17, 4334, 11, 902, 374, 6532, 304, 1401, 11618, 369, 2849, 20237, 1778, 439, 279, 15449, 315, 279, 24890, 2315, 296, 50758, 11, 362, 2434, 323, 47135, 11, 28896, 430, 527, 279, 2218, 315, 5370, 9572, 11217, 5131, 1694, 8040, 13, 296, 50758, 11, 362, 2434, 323, 1023, 5552, 24890, 2315, 656, 539, 990, 304, 31398, 719, 4856, 555, 45830, 323, 30164, 69125, 449, 1023, 28896, 11, 902, 527, 7718, 369, 872, 4725, 31301, 13, 578, 14956, 315, 1521, 14726, 449, 5361, 6956, 1587, 539, 1935, 2035, 304, 7917, 88558, 13, 578, 432, 17, 4334, 1887, 323, 279, 473, 4695, 1954, 523, 3271, 606, 527, 16996, 369, 279, 14956, 323, 15449, 315, 296, 50758, 323, 1023, 5552, 24890, 2315, 11, 719, 1268, 420, 8741, 304, 7917, 374, 2103, 14738, 315, 264, 23347, 13, 330, 2746, 584, 3619, 420, 14956, 38970, 11, 551, 30992, 1771, 279, 32185, 11, 330, 906, 690, 387, 3025, 311, 10765, 502, 5627, 315, 25103, 279, 5820, 315, 1521, 24890, 2315, 1210, 11361, 311, 16106, 78, 37081, 2298, 92914, 11, 330, 906, 617, 1027, 3025, 311, 9302, 1082, 11, 369, 279, 1176, 892, 11, 279, 1579, 64036, 6070, 315, 279, 3823, 432, 17, 4334, 1887, 1359, 2795, 445, 9761, 936, 13, 578, 12074, 1051, 14792, 555, 279, 16907, 23965, 315, 279, 3823, 432, 17, 4334, 1887, 7863, 311, 1202, 41580, 5105, 1640, 1157, 13, 578, 73757, 5448, 1501, 430, 432, 17, 4334, 374, 264, 3544, 5452, 13171, 315, 10917, 473, 4695, 1954, 304, 3729, 449, 279, 24890, 2315, 389, 902, 473, 4695, 1954, 2011, 1180, 13, 3277, 19894, 1234, 279, 73757, 11, 432, 17, 4334, 5992, 1093, 264, 52441, 18668, 449, 2380, 1633, 19303, 16006, 18709, 1903, 709, 315, 42561, 2599, 18, 13128, 13, 578, 24890, 2315, 315, 279, 296, 50758, 3070, 527, 45425, 311, 279, 2385, 315, 1202, 2010, 11, 1418, 473, 4695, 1954, 374, 43770, 555, 279, 16006, 18709, 323, 4529, 311, 279, 24890, 2315, 11, 9523, 311, 872, 25152, 13, 330, 2028, 1176, 22695, 315, 279, 3823, 432, 17, 4334, 1887, 706, 5535, 603, 311, 3619, 1202, 6070, 323, 31301, 24717, 11, 902, 1051, 8767, 9987, 13, 5751, 1828, 7504, 690, 387, 311, 4007, 279, 3649, 315, 1268, 432, 17, 4334, 323, 473, 4695, 1954, 527, 3025, 311, 42840, 279, 69125, 1903, 709, 315, 24890, 2315, 315, 279, 296, 50758, 3070, 11, 304, 2015, 311, 1505, 5627, 315, 75387, 449, 1521, 11618, 1359, 45537, 445, 9761, 936, 13, 330, 791, 432, 17, 4334, 1887, 374, 1101, 6532, 304, 279, 15449, 315, 1023, 7718, 35715, 369, 279, 2849, 323, 304, 279, 4500, 315, 9572, 11, 1778, 439, 279, 41214, 47393, 521, 11, 19227, 316, 19206, 11, 477, 279, 364, 2203, 90214, 6, 1887, 11, 5789, 430, 584, 30730, 311, 13488, 304, 279, 3938, 1210, 220, 128257, 198 ]

2,421

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The ambition and effectiveness of climate policies will be essential in determining greenhouse gas emissions and, as a consequence, the scale of climate change impacts 1 , 2 . However, the socio-politico-technical processes that will determine climate policy and emissions trajectories are treated as exogenous in almost all climate change modelling 3 , 4 . Here we identify relevant feedback processes documented across a range of disciplines and connect them in a stylized model of the climate–social system. An analysis of model behaviour reveals the potential for nonlinearities and tipping points that are particularly associated with connections across the individual, community, national and global scales represented. These connections can be decisive for determining policy and emissions outcomes. After partly constraining the model parameter space using observations, we simulate 100,000 possible future policy and emissions trajectories. These fall into 5 clusters with warming in 2100 ranging between 1.8 °C and 3.6 °C above the 1880–1910 average. Public perceptions of climate change, the future cost and effectiveness of mitigation technologies, and the responsiveness of political institutions emerge as important in explaining variation in emissions pathways and therefore the constraints on warming over the twenty-first century. Main The global trajectory of anthropogenic greenhouse gas emissions is the most important determinant of projected global temperature increases in this century and beyond, swamping the magnitude of internal climate variability or model differences 1 . However, this key driver of Earth’s future climate is treated as exogenous in almost all climate science 3 . Moreover, although emissions pathways arise from complex interactions among social, political, economic and technical systems, these elements are often analysed separately within disciplinary silos, neglecting interactions and feedback that can give rise to or stymie rapid change 5 . Understanding the potential for nonlinear dynamics in the socio-technical systems producing both greenhouse gases and climate policy is essential for identifying high-impact intervention points and better informing policy 4 , 6 , 7 . However, the coupling and interaction among social, political, economic, technical and climate systems—and their implications for emissions and temperature trajectories over the twenty-first century—have not been widely examined (although refs. 2 , 8 , 9 provide some exceptions). Evidence regarding the likely emissions path over the twenty-first century is mixed. On the one hand, although emissions growth may have decelerated in recent years, with some evidence of declining emissions in a few advanced economies, global emissions continue to grow 10 . National commitments under the Paris Agreement remain inadequate to meet either the 1.5-°C or 2-°C temperature target 11 and it is unclear whether government policies are yet sufficient to deliver on these emissions pledges 12 . Carbon dioxide emissions from energy infrastructure currently in place or under development will exceed the 1.5-°C carbon budget, and standard energy-system models struggle to simulate pathways that meet either temperature target without the widespread deployment of negative emissions technologies that are highly speculative 13 , 14 , 15 . The pace of decarbonization that is required to meet the Paris temperature targets vastly exceeds anything in the historical record at the global scale 16 . On the other hand, specific cases of very rapid change in energy systems do exist, with accelerating deployment as market or policy conditions shift and technology costs fall. Path dependencies, increasing returns to scale and learning-by-doing cost reductions can produce sudden, tipping-point-like transitions that cannot be extrapolated from past system behaviour 17 , 18 . Recent examples include the rapid fall in coal generation in the UK electricity mix and the dominance of electric vehicles sales in Norway 19 , 20 . Standard energy models, which mostly rely on linear extrapolations of past behaviour, repeatedly underpredict the rate of renewable energy growth 21 . Historically, technological innovation and government policies often motivated by energy security concerns 22 have also, in notable cases, spurred rapid shifts in energy systems, one of the fastest examples of which being the transition to kerosene lighting in the nineteenth century 23 . Social norms that shape individual behaviour and preferences can exhibit similar tipping-point style dynamics 24 . These changes, via collective action operating though political institutions, could in turn affect the regulatory and market conditions in which energy technologies compete. The presence of both positive and negative feedback processes within the political system has also been documented, as policy changes can both create new interest groups and activate incumbents against further change 25 , 26 , 27 . These coupled feedback processes could give rise to complex behaviour and a wide range of plausible emissions pathways but, although the space of possibility is wide, that does not mean it is unknowable. Our goal is to model the drivers of potential emissions scenarios over the twenty-first century and, in doing so, shed light on how both climate policy and emissions arise from more fundamental socio-politico-technical forces and the key parameters governing these dynamics. The main contributions are threefold. First, we present a stylized model of the coupled climate–social system, focusing on coupling across individual to global scales and on feedback processes documented across a wide range of relevant disciplinary literatures. This model is distinct from previous work that represents feedback processes within energy systems 28 or between the climate, the economy and emissions pathways 29 in that climate policy is still specified exogenously in these applications. By contrast, in this model, climate policy and greenhouse gas emissions arise endogenously from the coupled interaction of the climate, social, political and energy systems. Second, we used this model to systematically examine potential dynamics of the system, highlighting feedback, connections and thresholds across different components. Finally, after partially constraining the set of parameter values using historical data, we examined the space of possible emissions and policy trajectories over the twenty-first century arising from the model. These fall into five clusters associated with particular parameter combinations, enabling these future trajectories to be classified on the basis of their underlying social, political and technical characteristics. Overall, we find that the socio-politico-technical feedback processes can be decisive", "role": "user" }, { "content": "Politics and society largely dictate climate policy ambitions and therefore the trajectory of greenhouse gas emissions, yet climate change models and projections rarely include political and social drivers. A study from the University of California, Davis, simulated 100,000 possible future policy and emissions trajectories to identify relevant variables within the climate-social system that could impact climate change in this century. The study, published today in the journal Nature, indicates that public perceptions of climate change, the future cost and effectiveness of climate mitigation and technologies, and how political institutions respond to public pressure are all important determinants of the degree to which the climate will change over the 21st century. \"Small changes in some variables, like the responsiveness of the political system or the level of public support for climate policy, can sometimes trigger a cascade of feedbacks that result in a tipping point and drastically change the emissions trajectory over the century,\" said lead author Frances C. Moore, an assistant professor with the UC Davis Department of Environmental Science and Policy. \"We're trying to understand what it is about these fundamental socio-political-technical systems that determine emissions.\" Coupling climate and policy The authors note that the biggest uncertainty in understanding climate impacts over the long term is what emissions will be in the future. Most climate and energy modeling treats policy as something external to the models. But to prepare for climate impacts, adaptation planners need to understand the probability of different temperature outcomes for future decades. For this study, the authors modeled 100,000 possible future pathways of climate policy and greenhouse gas emissions. They used an integrated, multidisciplinary model that connected data across a wide range of social, political and technical fields. Such scenarios included public and political support, social perceptions of climate change, how quickly collective action or carbon pricing responds to changes in public opinion and other inputs. The pathways fell into five clusters, with warming in 2100 varying between 1.8 to 3.6 degrees Celsius above the 1880-1910 average, but with a strong probability of warming between 2 and 3 degrees Celsius at the end of the century. Key drivers The results indicate that people's perceptions and social groups, the improvements in mitigation technology over time, and the responsiveness of political institutions are key drivers of future emissions, even more so than individual actions. The study is not prescriptive. Rather, it examines what it is about the social-political-technical system that determines future emissions, integrates that information into existing climate models, and connects them across individual, community, national and global scales. \"Understanding how societies respond to environmental change, and how policy arises from social and political systems, is a key question in sustainability science,\" Moore said. \"I see this as pushing that research, and also being useful for climate adaptation and impacts planning.\" The study's co-authors are Katherine Lacasse of Rhode Island College, Katharine Mach of the University of Miami, Yoon Ah Shin of Arizona State University, Louis Gross of University of Tennessee, and Brian Beckage of University of Vermont. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The ambition and effectiveness of climate policies will be essential in determining greenhouse gas emissions and, as a consequence, the scale of climate change impacts 1 , 2 . However, the socio-politico-technical processes that will determine climate policy and emissions trajectories are treated as exogenous in almost all climate change modelling 3 , 4 . Here we identify relevant feedback processes documented across a range of disciplines and connect them in a stylized model of the climate–social system. An analysis of model behaviour reveals the potential for nonlinearities and tipping points that are particularly associated with connections across the individual, community, national and global scales represented. These connections can be decisive for determining policy and emissions outcomes. After partly constraining the model parameter space using observations, we simulate 100,000 possible future policy and emissions trajectories. These fall into 5 clusters with warming in 2100 ranging between 1.8 °C and 3.6 °C above the 1880–1910 average. Public perceptions of climate change, the future cost and effectiveness of mitigation technologies, and the responsiveness of political institutions emerge as important in explaining variation in emissions pathways and therefore the constraints on warming over the twenty-first century. Main The global trajectory of anthropogenic greenhouse gas emissions is the most important determinant of projected global temperature increases in this century and beyond, swamping the magnitude of internal climate variability or model differences 1 . However, this key driver of Earth’s future climate is treated as exogenous in almost all climate science 3 . Moreover, although emissions pathways arise from complex interactions among social, political, economic and technical systems, these elements are often analysed separately within disciplinary silos, neglecting interactions and feedback that can give rise to or stymie rapid change 5 . Understanding the potential for nonlinear dynamics in the socio-technical systems producing both greenhouse gases and climate policy is essential for identifying high-impact intervention points and better informing policy 4 , 6 , 7 . However, the coupling and interaction among social, political, economic, technical and climate systems—and their implications for emissions and temperature trajectories over the twenty-first century—have not been widely examined (although refs. 2 , 8 , 9 provide some exceptions). Evidence regarding the likely emissions path over the twenty-first century is mixed. On the one hand, although emissions growth may have decelerated in recent years, with some evidence of declining emissions in a few advanced economies, global emissions continue to grow 10 . National commitments under the Paris Agreement remain inadequate to meet either the 1.5-°C or 2-°C temperature target 11 and it is unclear whether government policies are yet sufficient to deliver on these emissions pledges 12 . Carbon dioxide emissions from energy infrastructure currently in place or under development will exceed the 1.5-°C carbon budget, and standard energy-system models struggle to simulate pathways that meet either temperature target without the widespread deployment of negative emissions technologies that are highly speculative 13 , 14 , 15 . The pace of decarbonization that is required to meet the Paris temperature targets vastly exceeds anything in the historical record at the global scale 16 . On the other hand, specific cases of very rapid change in energy systems do exist, with accelerating deployment as market or policy conditions shift and technology costs fall. Path dependencies, increasing returns to scale and learning-by-doing cost reductions can produce sudden, tipping-point-like transitions that cannot be extrapolated from past system behaviour 17 , 18 . Recent examples include the rapid fall in coal generation in the UK electricity mix and the dominance of electric vehicles sales in Norway 19 , 20 . Standard energy models, which mostly rely on linear extrapolations of past behaviour, repeatedly underpredict the rate of renewable energy growth 21 . Historically, technological innovation and government policies often motivated by energy security concerns 22 have also, in notable cases, spurred rapid shifts in energy systems, one of the fastest examples of which being the transition to kerosene lighting in the nineteenth century 23 . Social norms that shape individual behaviour and preferences can exhibit similar tipping-point style dynamics 24 . These changes, via collective action operating though political institutions, could in turn affect the regulatory and market conditions in which energy technologies compete. The presence of both positive and negative feedback processes within the political system has also been documented, as policy changes can both create new interest groups and activate incumbents against further change 25 , 26 , 27 . These coupled feedback processes could give rise to complex behaviour and a wide range of plausible emissions pathways but, although the space of possibility is wide, that does not mean it is unknowable. Our goal is to model the drivers of potential emissions scenarios over the twenty-first century and, in doing so, shed light on how both climate policy and emissions arise from more fundamental socio-politico-technical forces and the key parameters governing these dynamics. The main contributions are threefold. First, we present a stylized model of the coupled climate–social system, focusing on coupling across individual to global scales and on feedback processes documented across a wide range of relevant disciplinary literatures. This model is distinct from previous work that represents feedback processes within energy systems 28 or between the climate, the economy and emissions pathways 29 in that climate policy is still specified exogenously in these applications. By contrast, in this model, climate policy and greenhouse gas emissions arise endogenously from the coupled interaction of the climate, social, political and energy systems. Second, we used this model to systematically examine potential dynamics of the system, highlighting feedback, connections and thresholds across different components. Finally, after partially constraining the set of parameter values using historical data, we examined the space of possible emissions and policy trajectories over the twenty-first century arising from the model. These fall into five clusters associated with particular parameter combinations, enabling these future trajectories to be classified on the basis of their underlying social, political and technical characteristics. Overall, we find that the socio-politico-technical feedback processes can be decisive<|im_end|> <|im_start|>assistant Politics and society largely dictate climate policy ambitions and therefore the trajectory of greenhouse gas emissions, yet climate change models and projections rarely include political and social drivers. A study from the University of California, Davis, simulated 100,000 possible future policy and emissions trajectories to identify relevant variables within the climate-social system that could impact climate change in this century. The study, published today in the journal Nature, indicates that public perceptions of climate change, the future cost and effectiveness of climate mitigation and technologies, and how political institutions respond to public pressure are all important determinants of the degree to which the climate will change over the 21st century. "Small changes in some variables, like the responsiveness of the political system or the level of public support for climate policy, can sometimes trigger a cascade of feedbacks that result in a tipping point and drastically change the emissions trajectory over the century," said lead author Frances C. Moore, an assistant professor with the UC Davis Department of Environmental Science and Policy. "We're trying to understand what it is about these fundamental socio-political-technical systems that determine emissions." Coupling climate and policy The authors note that the biggest uncertainty in understanding climate impacts over the long term is what emissions will be in the future. Most climate and energy modeling treats policy as something external to the models. But to prepare for climate impacts, adaptation planners need to understand the probability of different temperature outcomes for future decades. For this study, the authors modeled 100,000 possible future pathways of climate policy and greenhouse gas emissions. They used an integrated, multidisciplinary model that connected data across a wide range of social, political and technical fields. Such scenarios included public and political support, social perceptions of climate change, how quickly collective action or carbon pricing responds to changes in public opinion and other inputs. The pathways fell into five clusters, with warming in 2100 varying between 1.8 to 3.6 degrees Celsius above the 1880-1910 average, but with a strong probability of warming between 2 and 3 degrees Celsius at the end of the century. Key drivers The results indicate that people's perceptions and social groups, the improvements in mitigation technology over time, and the responsiveness of political institutions are key drivers of future emissions, even more so than individual actions. The study is not prescriptive. Rather, it examines what it is about the social-political-technical system that determines future emissions, integrates that information into existing climate models, and connects them across individual, community, national and global scales. "Understanding how societies respond to environmental change, and how policy arises from social and political systems, is a key question in sustainability science," Moore said. "I see this as pushing that research, and also being useful for climate adaptation and impacts planning." The study's co-authors are Katherine Lacasse of Rhode Island College, Katharine Mach of the University of Miami, Yoon Ah Shin of Arizona State University, Louis Gross of University of Tennessee, and Brian Beckage of University of Vermont. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 45715, 323, 27375, 315, 10182, 10396, 690, 387, 7718, 304, 26679, 37647, 6962, 20748, 323, 11, 439, 264, 29774, 11, 279, 5569, 315, 10182, 2349, 25949, 220, 16, 1174, 220, 17, 662, 4452, 11, 279, 41589, 55096, 275, 4042, 12, 73237, 11618, 430, 690, 8417, 10182, 4947, 323, 20748, 86648, 527, 12020, 439, 506, 53595, 304, 4661, 682, 10182, 2349, 61966, 220, 18, 1174, 220, 19, 662, 5810, 584, 10765, 9959, 11302, 11618, 27470, 4028, 264, 2134, 315, 49255, 323, 4667, 1124, 304, 264, 49304, 1534, 1646, 315, 279, 10182, 4235, 23191, 1887, 13, 1556, 6492, 315, 1646, 17432, 21667, 279, 4754, 369, 75098, 1385, 323, 72293, 3585, 430, 527, 8104, 5938, 449, 13537, 4028, 279, 3927, 11, 4029, 11, 5426, 323, 3728, 29505, 15609, 13, 4314, 13537, 649, 387, 51391, 369, 26679, 4947, 323, 20748, 20124, 13, 4740, 28135, 19477, 2101, 279, 1646, 5852, 3634, 1701, 24654, 11, 584, 38553, 220, 1041, 11, 931, 3284, 3938, 4947, 323, 20748, 86648, 13, 4314, 4498, 1139, 220, 20, 28066, 449, 24808, 304, 220, 8848, 15, 24950, 1990, 220, 16, 13, 23, 37386, 34, 323, 220, 18, 13, 21, 37386, 34, 3485, 279, 220, 9367, 15, 4235, 7529, 15, 5578, 13, 3142, 51866, 315, 10182, 2349, 11, 279, 3938, 2853, 323, 27375, 315, 66860, 14645, 11, 323, 279, 100039, 315, 5054, 14673, 34044, 439, 3062, 304, 26073, 23851, 304, 20748, 44014, 323, 9093, 279, 17413, 389, 24808, 927, 279, 17510, 38043, 9478, 13, 4802, 578, 3728, 35782, 315, 41416, 29569, 37647, 6962, 20748, 374, 279, 1455, 3062, 88060, 315, 28448, 3728, 9499, 12992, 304, 420, 9478, 323, 7953, 11, 2064, 31557, 279, 26703, 315, 5419, 10182, 54709, 477, 1646, 12062, 220, 16, 662, 4452, 11, 420, 1401, 5696, 315, 9420, 753, 3938, 10182, 374, 12020, 439, 506, 53595, 304, 4661, 682, 10182, 8198, 220, 18, 662, 23674, 11, 8051, 20748, 44014, 31889, 505, 6485, 22639, 4315, 3674, 11, 5054, 11, 7100, 323, 11156, 6067, 11, 1521, 5540, 527, 3629, 67458, 26214, 2949, 57315, 5554, 437, 11, 39332, 287, 22639, 323, 11302, 430, 649, 3041, 10205, 311, 477, 357, 1631, 648, 11295, 2349, 220, 20, 662, 46551, 279, 4754, 369, 75098, 30295, 304, 279, 41589, 12, 73237, 6067, 17843, 2225, 37647, 45612, 323, 10182, 4947, 374, 7718, 369, 25607, 1579, 12, 58400, 21623, 3585, 323, 2731, 63025, 4947, 220, 19, 1174, 220, 21, 1174, 220, 22, 662, 4452, 11, 279, 59086, 323, 16628, 4315, 3674, 11, 5054, 11, 7100, 11, 11156, 323, 10182, 6067, 17223, 872, 25127, 369, 20748, 323, 9499, 86648, 927, 279, 17510, 38043, 9478, 2345, 19553, 539, 1027, 13882, 25078, 320, 37241, 44243, 13, 220, 17, 1174, 220, 23, 1174, 220, 24, 3493, 1063, 20157, 570, 44796, 9002, 279, 4461, 20748, 1853, 927, 279, 17510, 38043, 9478, 374, 9709, 13, 1952, 279, 832, 1450, 11, 8051, 20748, 6650, 1253, 617, 1654, 8023, 660, 304, 3293, 1667, 11, 449, 1063, 6029, 315, 43848, 20748, 304, 264, 2478, 11084, 37671, 11, 3728, 20748, 3136, 311, 3139, 220, 605, 662, 5165, 42356, 1234, 279, 12366, 23314, 7293, 46579, 311, 3449, 3060, 279, 220, 16, 13, 20, 12, 11877, 34, 477, 220, 17, 12, 11877, 34, 9499, 2218, 220, 806, 323, 433, 374, 25420, 3508, 3109, 10396, 527, 3686, 14343, 311, 6493, 389, 1521, 20748, 79118, 220, 717, 662, 22208, 40589, 20748, 505, 4907, 14054, 5131, 304, 2035, 477, 1234, 4500, 690, 12771, 279, 220, 16, 13, 20, 12, 11877, 34, 12782, 8199, 11, 323, 5410, 4907, 37748, 4211, 14993, 311, 38553, 44014, 430, 3449, 3060, 9499, 2218, 2085, 279, 24716, 24047, 315, 8389, 20748, 14645, 430, 527, 7701, 66836, 220, 1032, 1174, 220, 975, 1174, 220, 868, 662, 578, 18338, 315, 1654, 52745, 2065, 430, 374, 2631, 311, 3449, 279, 12366, 9499, 11811, 53108, 36375, 4205, 304, 279, 13970, 3335, 520, 279, 3728, 5569, 220, 845, 662, 1952, 279, 1023, 1450, 11, 3230, 5157, 315, 1633, 11295, 2349, 304, 4907, 6067, 656, 3073, 11, 449, 69741, 24047, 439, 3157, 477, 4947, 4787, 6541, 323, 5557, 7194, 4498, 13, 8092, 20113, 11, 7859, 4780, 311, 5569, 323, 6975, 14656, 30659, 287, 2853, 47311, 649, 8356, 11210, 11, 72293, 16983, 12970, 34692, 430, 4250, 387, 71462, 660, 505, 3347, 1887, 17432, 220, 1114, 1174, 220, 972, 662, 35390, 10507, 2997, 279, 11295, 4498, 304, 11756, 9659, 304, 279, 6560, 18200, 6651, 323, 279, 44592, 315, 9249, 11731, 6763, 304, 32603, 220, 777, 1174, 220, 508, 662, 12028, 4907, 4211, 11, 902, 10213, 17631, 389, 13790, 71462, 811, 315, 3347, 17432, 11, 19352, 1234, 35798, 279, 4478, 315, 33268, 4907, 6650, 220, 1691, 662, 22425, 2740, 11, 30116, 19297, 323, 3109, 10396, 3629, 27762, 555, 4907, 4868, 10742, 220, 1313, 617, 1101, 11, 304, 28289, 5157, 11, 85747, 11295, 29735, 304, 4907, 6067, 11, 832, 315, 279, 26731, 10507, 315, 902, 1694, 279, 9320, 311, 597, 6398, 1994, 18186, 304, 279, 66089, 9478, 220, 1419, 662, 9983, 40851, 430, 6211, 3927, 17432, 323, 19882, 649, 31324, 4528, 72293, 16983, 1742, 30295, 220, 1187, 662, 4314, 4442, 11, 4669, 22498, 1957, 10565, 3582, 5054, 14673, 11, 1436, 304, 2543, 7958, 279, 23331, 323, 3157, 4787, 304, 902, 4907, 14645, 20874, 13, 578, 9546, 315, 2225, 6928, 323, 8389, 11302, 11618, 2949, 279, 5054, 1887, 706, 1101, 1027, 27470, 11, 439, 4947, 4442, 649, 2225, 1893, 502, 2802, 5315, 323, 20891, 43850, 812, 2403, 4726, 2349, 220, 914, 1174, 220, 1627, 1174, 220, 1544, 662, 4314, 34356, 11302, 11618, 1436, 3041, 10205, 311, 6485, 17432, 323, 264, 7029, 2134, 315, 50434, 20748, 44014, 719, 11, 8051, 279, 3634, 315, 13336, 374, 7029, 11, 430, 1587, 539, 3152, 433, 374, 84644, 481, 13, 5751, 5915, 374, 311, 1646, 279, 12050, 315, 4754, 20748, 26350, 927, 279, 17510, 38043, 9478, 323, 11, 304, 3815, 779, 11, 25351, 3177, 389, 1268, 2225, 10182, 4947, 323, 20748, 31889, 505, 810, 16188, 41589, 55096, 275, 4042, 12, 73237, 8603, 323, 279, 1401, 5137, 10217, 1521, 30295, 13, 578, 1925, 19564, 527, 2380, 20557, 13, 5629, 11, 584, 3118, 264, 49304, 1534, 1646, 315, 279, 34356, 10182, 4235, 23191, 1887, 11, 21760, 389, 59086, 4028, 3927, 311, 3728, 29505, 323, 389, 11302, 11618, 27470, 4028, 264, 7029, 2134, 315, 9959, 57315, 7080, 2859, 13, 1115, 1646, 374, 12742, 505, 3766, 990, 430, 11105, 11302, 11618, 2949, 4907, 6067, 220, 1591, 477, 1990, 279, 10182, 11, 279, 8752, 323, 20748, 44014, 220, 1682, 304, 430, 10182, 4947, 374, 2103, 5300, 506, 11968, 7162, 304, 1521, 8522, 13, 3296, 13168, 11, 304, 420, 1646, 11, 10182, 4947, 323, 37647, 6962, 20748, 31889, 842, 11968, 7162, 505, 279, 34356, 16628, 315, 279, 10182, 11, 3674, 11, 5054, 323, 4907, 6067, 13, 10657, 11, 584, 1511, 420, 1646, 311, 60826, 21635, 4754, 30295, 315, 279, 1887, 11, 39686, 11302, 11, 13537, 323, 57240, 4028, 2204, 6956, 13, 17830, 11, 1306, 26310, 19477, 2101, 279, 743, 315, 5852, 2819, 1701, 13970, 828, 11, 584, 25078, 279, 3634, 315, 3284, 20748, 323, 4947, 86648, 927, 279, 17510, 38043, 9478, 40986, 505, 279, 1646, 13, 4314, 4498, 1139, 4330, 28066, 5938, 449, 4040, 5852, 28559, 11, 28462, 1521, 3938, 86648, 311, 387, 21771, 389, 279, 8197, 315, 872, 16940, 3674, 11, 5054, 323, 11156, 17910, 13, 28993, 11, 584, 1505, 430, 279, 41589, 55096, 275, 4042, 12, 73237, 11302, 11618, 649, 387, 51391, 128257, 198, 128256, 78191, 198, 97036, 323, 8396, 14090, 62974, 10182, 4947, 51566, 323, 9093, 279, 35782, 315, 37647, 6962, 20748, 11, 3686, 10182, 2349, 4211, 323, 41579, 19029, 2997, 5054, 323, 3674, 12050, 13, 362, 4007, 505, 279, 3907, 315, 7188, 11, 17200, 11, 46836, 220, 1041, 11, 931, 3284, 3938, 4947, 323, 20748, 86648, 311, 10765, 9959, 7482, 2949, 279, 10182, 43129, 1887, 430, 1436, 5536, 10182, 2349, 304, 420, 9478, 13, 578, 4007, 11, 4756, 3432, 304, 279, 8486, 22037, 11, 15151, 430, 586, 51866, 315, 10182, 2349, 11, 279, 3938, 2853, 323, 27375, 315, 10182, 66860, 323, 14645, 11, 323, 1268, 5054, 14673, 6013, 311, 586, 7410, 527, 682, 3062, 6449, 1821, 315, 279, 8547, 311, 902, 279, 10182, 690, 2349, 927, 279, 220, 1691, 267, 9478, 13, 330, 26375, 4442, 304, 1063, 7482, 11, 1093, 279, 100039, 315, 279, 5054, 1887, 477, 279, 2237, 315, 586, 1862, 369, 10182, 4947, 11, 649, 7170, 8346, 264, 43118, 315, 11302, 82, 430, 1121, 304, 264, 72293, 1486, 323, 48863, 2349, 279, 20748, 35782, 927, 279, 9478, 1359, 1071, 3063, 3229, 43833, 356, 13, 20832, 11, 459, 18328, 14561, 449, 279, 31613, 17200, 6011, 315, 25027, 10170, 323, 11216, 13, 330, 1687, 2351, 4560, 311, 3619, 1148, 433, 374, 922, 1521, 16188, 41589, 55096, 32360, 12, 73237, 6067, 430, 8417, 20748, 1210, 18733, 12127, 10182, 323, 4947, 578, 12283, 5296, 430, 279, 8706, 27924, 304, 8830, 10182, 25949, 927, 279, 1317, 4751, 374, 1148, 20748, 690, 387, 304, 279, 3938, 13, 7648, 10182, 323, 4907, 34579, 32839, 4947, 439, 2555, 9434, 311, 279, 4211, 13, 2030, 311, 10772, 369, 10182, 25949, 11, 34185, 68552, 1205, 311, 3619, 279, 19463, 315, 2204, 9499, 20124, 369, 3938, 11026, 13, 1789, 420, 4007, 11, 279, 12283, 62653, 220, 1041, 11, 931, 3284, 3938, 44014, 315, 10182, 4947, 323, 37647, 6962, 20748, 13, 2435, 1511, 459, 18751, 11, 64486, 3510, 44550, 1646, 430, 8599, 828, 4028, 264, 7029, 2134, 315, 3674, 11, 5054, 323, 11156, 5151, 13, 15483, 26350, 5343, 586, 323, 5054, 1862, 11, 3674, 51866, 315, 10182, 2349, 11, 1268, 6288, 22498, 1957, 477, 12782, 21913, 31680, 311, 4442, 304, 586, 9647, 323, 1023, 11374, 13, 578, 44014, 11299, 1139, 4330, 28066, 11, 449, 24808, 304, 220, 8848, 15, 29865, 1990, 220, 16, 13, 23, 311, 220, 18, 13, 21, 12628, 62447, 3485, 279, 220, 9367, 15, 12, 7529, 15, 5578, 11, 719, 449, 264, 3831, 19463, 315, 24808, 1990, 220, 17, 323, 220, 18, 12628, 62447, 520, 279, 842, 315, 279, 9478, 13, 5422, 12050, 578, 3135, 13519, 430, 1274, 596, 51866, 323, 3674, 5315, 11, 279, 18637, 304, 66860, 5557, 927, 892, 11, 323, 279, 100039, 315, 5054, 14673, 527, 1401, 12050, 315, 3938, 20748, 11, 1524, 810, 779, 1109, 3927, 6299, 13, 578, 4007, 374, 539, 1685, 41419, 13, 26848, 11, 433, 49095, 1148, 433, 374, 922, 279, 3674, 55096, 32360, 12, 73237, 1887, 430, 27667, 3938, 20748, 11, 75762, 430, 2038, 1139, 6484, 10182, 4211, 11, 323, 34161, 1124, 4028, 3927, 11, 4029, 11, 5426, 323, 3728, 29505, 13, 330, 71251, 1268, 34775, 6013, 311, 12434, 2349, 11, 323, 1268, 4947, 48282, 505, 3674, 323, 5054, 6067, 11, 374, 264, 1401, 3488, 304, 41329, 8198, 1359, 20832, 1071, 13, 330, 40, 1518, 420, 439, 17919, 430, 3495, 11, 323, 1101, 1694, 5505, 369, 10182, 34185, 323, 25949, 9293, 1210, 578, 4007, 596, 1080, 34603, 1105, 527, 62426, 55141, 13559, 315, 50981, 10951, 9304, 11, 33995, 75314, 18798, 315, 279, 3907, 315, 18045, 11, 816, 9186, 16770, 35549, 315, 17368, 3314, 3907, 11, 12140, 43907, 315, 3907, 315, 24097, 11, 323, 17520, 29818, 425, 315, 3907, 315, 35739, 13, 220, 128257, 198 ]

1,862

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Guidelines Hypothesis Interesting Images Letter New Book Received Obituary Opinion Perspective Proceeding Paper Project Report Protocol Registered Report Reply Retraction Short Note Study Protocol Systematic Review Technical Note Tutorial Viewpoint All Article Types Advanced Search Section All Sections AI Remote Sensing Atmospheric Remote Sensing Biogeosciences Remote Sensing Coral Reefs Remote Sensing Discoveries in Remote Sensing Earth Observation Data Earth Observation for Emergency Management Ecological Remote Sensing Engineering Remote Sensing Environmental Remote Sensing Forest Remote Sensing Ocean Remote Sensing Remote Sensing and Geo-Spatial Science Remote Sensing Communications Remote Sensing Image Processing Remote Sensing in Agriculture and Vegetation Remote Sensing in Geology, Geomorphology and Hydrology Remote Sensing of the Water Cycle Satellite Missions for Earth and Planetary Exploration Urban Remote Sensing All Sections Special Issue All Special Issues Remote Sensing: 15th Anniversary 100 Years ISPRS - Advancing Remote Sensing Science 2nd Edition Advances in Remote Sensing for Archaeological Heritage 3D Point Clouds in Rock Mechanics Applications Accuracy Assessment of UAS Lidar Active-Passive Microwave Sensing for Earth System Parameters Advanced Communication and Networking Techniques for Remote Sensing Advanced Machine Learning and Big Data Analytics in Remote Sensing for Natural Hazards Management Advanced Machine Learning Approaches for Hyperspectral Data Analysis Advanced Radar Signal Processing and Applications Advanced Remote Sensing Methods for 3D Vegetation Mapping and Characterization Advanced Satellite-Terrestrial Networks Advanced Topics in Remote Sensing Advancement of Remote Sensing and UAS in Cartography and Visualisation Advancements in Remote Sensing and GIS in Mobile Computing and Location-Based Services Advances and Innovative Applications of Unmanned Aerial Vehicles Advances in Applications of Volunteered Geographic Information Advances in Climate and Geophysics Advances in Geographic Object-Based Image Analysis (GEOBIA) Advances in Mobile Laser Scanning and Mobile Mapping Advances in Object and Activity Detection in Remote Sensing Imagery Advances in Object and Activity Detection in Remote Sensing Imagery II Advances in Object-Based Image Analysis—Linking with Computer Vision and Machine Learning Advances in Quantitative Remote Sensing in China – In Memory of Prof. Xiaowen Li Advances in Real Aperture and Synthetic Aperture Ground-Based Interferometry Advances in Remote Sensing and Geographic Information Science and Their Uses in Geointelligence Advances in Remote Sensing Applications for the Detection of Biological Invasions Advances in Remote Sensing for Archaeological Heritage Advances in Remote Sensing in Coastal Geomorphology Advances in Remote Sensing of Agriculture Advances in Remote Sensing of Crop Water Use Estimation Advances in Remote Sensing of Forestry Advances in Remote Sensing of Wildland Fires Advances in Remote Sensing-based Disaster Monitoring and Assessment Advances in SAR: Sensors, Methodologies, and Applications Advances in Satellite Altimetry Advances in Satellite Altimetry and Its Application Advances in Synthetic Aperture Radar Remote Sensing Advances in the Remote Sensing of Terrestrial Evaporation Advances in VIIRS Data Advances of Remote Sensing in Environmental Geoscience Aerosol and Cloud Remote Sensing Airborne Laser Scanning Analysis of Remote Sensing Image Data Application of Machine Learning in Volcano Monitoring Application of Multi-Sensor Fusion Technology in Target Detection and Recognition Application of Remote Sensing in Hydrological Modeling and Watershed Management Applications and New Trends in Metrology for Radar/LiDAR-Based Systems Applications of Deep Learning in Smart Agriculture Applications of Full Waveform Lidar Applications of GNSS Reflectometry for Earth Observation Applications of Micro- and Nano-Satellites for Earth Observation Applications of Remote Sensing in Landscape Ecology in Latin America Applications of Remote Sensing in Rangelands Research Applications of Synthetic Aperture Radar (SAR) for Land Cover Analysis Approaches for Monitoring Land Degradation with Remote Sensing Archaeological Prospecting and Remote Sensing Artifacts in Remote Sensing Data Analysis: An Ecological Perspective Artificial Intelligence and Automation in Sustainable Smart Farming Artificial Neural Networks and Evolutionary Computation in Remote Sensing Assessment of Renewable Energy Resources with Remote Sensing Assimilation of Remote Sensing Data into Earth System Models Atmospheric Remote Sensing Baltic Sea Remote Sensing Big Data Analytics for Secure and Smart Environmental Services Big Earth Observation Data: From Cloud Technologies to Insights and Foresight Bistatic HF Radar Calibration and Validation of Synthetic Aperture Radar Calibration and Verification of Remote Sensing Instruments and Observations Carbon Cycle, Global Change, and Multi-Sensor Remote Sensing Cartography of the Solar System: Remote Sensing beyond Earth Celebrating the 50th Anniversary of the Moon Landing with Views of Earth from Satellite and Apollo Missions Citizen Science and Earth Observation Climate Modelling and Monitoring Using GNSS Close Range Remote Sensing Close-Range Remote Sensing by Ground Penetrating Radar Compact Polarimetric SAR Concurrent Positioning, Mapping and Perception of Multi-source Data Fusion for Smart Applications Contemporary Microwave and Radar Techniques in Remote Sensing—MIKON 2022, IRS 2022 CORINE Land Cover System: Limits and Challenges for Territorial Studies and Planning Cross-Calibration and Interoperability of Remote Sensing Instruments Cryospheric Remote Sensing Data Mining in Multi-Platform Remote Sensing Data Science in Remote Sensing Data Science, Artificial Intelligence and Remote Sensing Deep Learning for Intelligent Synthetic Aperture Radar Systems Deep Learning for Target Object Detection and Identification in Remote Sensing Data Deep Learning in Remote Sensing: Sample Datasets, Algorithms and Applications Dense Image Time Series Analysis for Ecosystem Monitoring Design and Calibration of Microwave Radiometers and Scatterometers for Remote Sensing of the Earth Designing and Managing the Next Generation of Transportation Infrastructure Digital Forest Resource Monitoring and Uncertainty Analysis Discovering A More Diverse Remote Sensing Discipline Drone-Based Ecological Conservation Earth Environment Monitoring with Advanced Spaceborne Synthetic Aperture Radar: New Architectures, Operational Modes, and Processing Techniques Earth Monitoring from A New Generation of Geostationary Satellites Earth Observation and Sustainable Development in Marine and Freshwater Systems Earth Observation for Ecosystems Monitoring in Space and Time Earth Observation for Water Resource Management in Africa Earth Observation in Planning for Sustainable Urban Development Earth Observation Technology Cluster: Innovative Sensor Systems for Advanced Land Surface Studies Earth Observation to Support Disaster Preparedness and Disaster Risk Management Earth Observation with AVHRR Data and Interconsistency Earth Observations for a Better Future Earth Earth Observations for Addressing Global Challenges Earth Observations for Geohazards Earth Observations for the Sustainable Development Ecogeomorphological Research Using Satellite Images Ecological Status and Change by Remote Sensing Environmental Research with Global Navigation Satellite System (GNSS) EO Solutions to Support Countries Implementing the SDGs ESA - NRSCC", "role": "user" }, { "content": "People in big cities breathe bad air. Bad air that consists of particulate matter and other pollutants, which pose health risks to urban citizens. Researchers led by Dr. Martin Ramacher of the Hereon Institute of Coastal Environmental Chemistry, in collaboration with the National Observatory of Athens, are now helping to make the determination of particulate matter smaller than 2.5 micrometers (PM2.5) more accurate. To do this, they used openly available EU-wide Copernicus satellite data in combination with the EPISODE-CityChem chemical transport model. The system developed at Hereon was able to model hotspots for bad air at a resolution of 100x100 square meters using Hamburg as an example. The calculated particulate matter concentrations are combined with population data and can thus simultaneously indicate areas with poor air quality and high population density. These areas are of particular interest for achieving air quality improvements. The pioneering aspect of the developed method is the combination of different satellite data, which are freely available for all of Europe, with city-scale model calculations. Compared with the mean value of 14 micrograms per cubic meter for the entire city previously collected by the World Health Organization (WHO) for the example year 2016 used, Hamburg was actually subject to lower fine particulate matter concentrations of 11 to 12 micrograms per cubic meter as an urban average. However, the new detailed calculations show that pollution levels are distributed differently across the city and can rise to 17 micrograms per cubic meter in some neighborhoods. \"In particular, we were able to determine elevated annual mean values for particulate matter concentrations for the sample year 2016 on busy roads and in the industrial area near the port in the south of the Elbe River. While relatively few people live near the industrial areas, we were able to demonstrate that many people live near heavily traveled roads and are affected by elevated concentrations. Such considerations of air pollution hotspots, have so far been unrepresented in the UN indicator. But our approach, in line with the UN indicator, allows to better record pollution levels and can help local decision-makers to initiate countermeasures,\" says Ramacher. Overall, Hamburg is below the European average for particulate matter pollution compared to other major European cities and does not exceed the annual EU limit of 20 micrograms per cubic meter for particulate matter smaller than 2.5 micrometers (PM2.5). The SDG 11.6.2 indicator was developed by the United Nations to address the threat to public health from urban air pollution globally. The World Health Organization (WHO) published updated guidelines for air quality benchmarks in late September 2021 to respond to the threat of pollution. The effects of those include seven million premature deaths worldwide each year and many millions of people becoming ill. Air pollution is still a major health problem in Europe as well. The local definition of SDG 11.6.2 indicator brings challenges—mainly because of the diversity of causes of air pollution, for example, from a wide range of emission sources and other influencing factors. The often too few monitoring sites cannot accurately capture the spatial complexity. The study, conducted jointly by Hereon and the National Observatory of Athens, aims to advance the discussion on the potential of the SDG 11.6.2 indicator for local decision-making. This is because detailed inner-city information on pollution and population is needed to fill the research gap that has existed to date and eventually to improve air quality in cities. The study is published in the journal Remote Sensing. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Guidelines Hypothesis Interesting Images Letter New Book Received Obituary Opinion Perspective Proceeding Paper Project Report Protocol Registered Report Reply Retraction Short Note Study Protocol Systematic Review Technical Note Tutorial Viewpoint All Article Types Advanced Search Section All Sections AI Remote Sensing Atmospheric Remote Sensing Biogeosciences Remote Sensing Coral Reefs Remote Sensing Discoveries in Remote Sensing Earth Observation Data Earth Observation for Emergency Management Ecological Remote Sensing Engineering Remote Sensing Environmental Remote Sensing Forest Remote Sensing Ocean Remote Sensing Remote Sensing and Geo-Spatial Science Remote Sensing Communications Remote Sensing Image Processing Remote Sensing in Agriculture and Vegetation Remote Sensing in Geology, Geomorphology and Hydrology Remote Sensing of the Water Cycle Satellite Missions for Earth and Planetary Exploration Urban Remote Sensing All Sections Special Issue All Special Issues Remote Sensing: 15th Anniversary 100 Years ISPRS - Advancing Remote Sensing Science 2nd Edition Advances in Remote Sensing for Archaeological Heritage 3D Point Clouds in Rock Mechanics Applications Accuracy Assessment of UAS Lidar Active-Passive Microwave Sensing for Earth System Parameters Advanced Communication and Networking Techniques for Remote Sensing Advanced Machine Learning and Big Data Analytics in Remote Sensing for Natural Hazards Management Advanced Machine Learning Approaches for Hyperspectral Data Analysis Advanced Radar Signal Processing and Applications Advanced Remote Sensing Methods for 3D Vegetation Mapping and Characterization Advanced Satellite-Terrestrial Networks Advanced Topics in Remote Sensing Advancement of Remote Sensing and UAS in Cartography and Visualisation Advancements in Remote Sensing and GIS in Mobile Computing and Location-Based Services Advances and Innovative Applications of Unmanned Aerial Vehicles Advances in Applications of Volunteered Geographic Information Advances in Climate and Geophysics Advances in Geographic Object-Based Image Analysis (GEOBIA) Advances in Mobile Laser Scanning and Mobile Mapping Advances in Object and Activity Detection in Remote Sensing Imagery Advances in Object and Activity Detection in Remote Sensing Imagery II Advances in Object-Based Image Analysis—Linking with Computer Vision and Machine Learning Advances in Quantitative Remote Sensing in China – In Memory of Prof. Xiaowen Li Advances in Real Aperture and Synthetic Aperture Ground-Based Interferometry Advances in Remote Sensing and Geographic Information Science and Their Uses in Geointelligence Advances in Remote Sensing Applications for the Detection of Biological Invasions Advances in Remote Sensing for Archaeological Heritage Advances in Remote Sensing in Coastal Geomorphology Advances in Remote Sensing of Agriculture Advances in Remote Sensing of Crop Water Use Estimation Advances in Remote Sensing of Forestry Advances in Remote Sensing of Wildland Fires Advances in Remote Sensing-based Disaster Monitoring and Assessment Advances in SAR: Sensors, Methodologies, and Applications Advances in Satellite Altimetry Advances in Satellite Altimetry and Its Application Advances in Synthetic Aperture Radar Remote Sensing Advances in the Remote Sensing of Terrestrial Evaporation Advances in VIIRS Data Advances of Remote Sensing in Environmental Geoscience Aerosol and Cloud Remote Sensing Airborne Laser Scanning Analysis of Remote Sensing Image Data Application of Machine Learning in Volcano Monitoring Application of Multi-Sensor Fusion Technology in Target Detection and Recognition Application of Remote Sensing in Hydrological Modeling and Watershed Management Applications and New Trends in Metrology for Radar/LiDAR-Based Systems Applications of Deep Learning in Smart Agriculture Applications of Full Waveform Lidar Applications of GNSS Reflectometry for Earth Observation Applications of Micro- and Nano-Satellites for Earth Observation Applications of Remote Sensing in Landscape Ecology in Latin America Applications of Remote Sensing in Rangelands Research Applications of Synthetic Aperture Radar (SAR) for Land Cover Analysis Approaches for Monitoring Land Degradation with Remote Sensing Archaeological Prospecting and Remote Sensing Artifacts in Remote Sensing Data Analysis: An Ecological Perspective Artificial Intelligence and Automation in Sustainable Smart Farming Artificial Neural Networks and Evolutionary Computation in Remote Sensing Assessment of Renewable Energy Resources with Remote Sensing Assimilation of Remote Sensing Data into Earth System Models Atmospheric Remote Sensing Baltic Sea Remote Sensing Big Data Analytics for Secure and Smart Environmental Services Big Earth Observation Data: From Cloud Technologies to Insights and Foresight Bistatic HF Radar Calibration and Validation of Synthetic Aperture Radar Calibration and Verification of Remote Sensing Instruments and Observations Carbon Cycle, Global Change, and Multi-Sensor Remote Sensing Cartography of the Solar System: Remote Sensing beyond Earth Celebrating the 50th Anniversary of the Moon Landing with Views of Earth from Satellite and Apollo Missions Citizen Science and Earth Observation Climate Modelling and Monitoring Using GNSS Close Range Remote Sensing Close-Range Remote Sensing by Ground Penetrating Radar Compact Polarimetric SAR Concurrent Positioning, Mapping and Perception of Multi-source Data Fusion for Smart Applications Contemporary Microwave and Radar Techniques in Remote Sensing—MIKON 2022, IRS 2022 CORINE Land Cover System: Limits and Challenges for Territorial Studies and Planning Cross-Calibration and Interoperability of Remote Sensing Instruments Cryospheric Remote Sensing Data Mining in Multi-Platform Remote Sensing Data Science in Remote Sensing Data Science, Artificial Intelligence and Remote Sensing Deep Learning for Intelligent Synthetic Aperture Radar Systems Deep Learning for Target Object Detection and Identification in Remote Sensing Data Deep Learning in Remote Sensing: Sample Datasets, Algorithms and Applications Dense Image Time Series Analysis for Ecosystem Monitoring Design and Calibration of Microwave Radiometers and Scatterometers for Remote Sensing of the Earth Designing and Managing the Next Generation of Transportation Infrastructure Digital Forest Resource Monitoring and Uncertainty Analysis Discovering A More Diverse Remote Sensing Discipline Drone-Based Ecological Conservation Earth Environment Monitoring with Advanced Spaceborne Synthetic Aperture Radar: New Architectures, Operational Modes, and Processing Techniques Earth Monitoring from A New Generation of Geostationary Satellites Earth Observation and Sustainable Development in Marine and Freshwater Systems Earth Observation for Ecosystems Monitoring in Space and Time Earth Observation for Water Resource Management in Africa Earth Observation in Planning for Sustainable Urban Development Earth Observation Technology Cluster: Innovative Sensor Systems for Advanced Land Surface Studies Earth Observation to Support Disaster Preparedness and Disaster Risk Management Earth Observation with AVHRR Data and Interconsistency Earth Observations for a Better Future Earth Earth Observations for Addressing Global Challenges Earth Observations for Geohazards Earth Observations for the Sustainable Development Ecogeomorphological Research Using Satellite Images Ecological Status and Change by Remote Sensing Environmental Research with Global Navigation Satellite System (GNSS) EO Solutions to Support Countries Implementing the SDGs ESA - NRSCC<|im_end|> <|im_start|>assistant People in big cities breathe bad air. Bad air that consists of particulate matter and other pollutants, which pose health risks to urban citizens. Researchers led by Dr. Martin Ramacher of the Hereon Institute of Coastal Environmental Chemistry, in collaboration with the National Observatory of Athens, are now helping to make the determination of particulate matter smaller than 2.5 micrometers (PM2.5) more accurate. To do this, they used openly available EU-wide Copernicus satellite data in combination with the EPISODE-CityChem chemical transport model. The system developed at Hereon was able to model hotspots for bad air at a resolution of 100x100 square meters using Hamburg as an example. The calculated particulate matter concentrations are combined with population data and can thus simultaneously indicate areas with poor air quality and high population density. These areas are of particular interest for achieving air quality improvements. The pioneering aspect of the developed method is the combination of different satellite data, which are freely available for all of Europe, with city-scale model calculations. Compared with the mean value of 14 micrograms per cubic meter for the entire city previously collected by the World Health Organization (WHO) for the example year 2016 used, Hamburg was actually subject to lower fine particulate matter concentrations of 11 to 12 micrograms per cubic meter as an urban average. However, the new detailed calculations show that pollution levels are distributed differently across the city and can rise to 17 micrograms per cubic meter in some neighborhoods. "In particular, we were able to determine elevated annual mean values for particulate matter concentrations for the sample year 2016 on busy roads and in the industrial area near the port in the south of the Elbe River. While relatively few people live near the industrial areas, we were able to demonstrate that many people live near heavily traveled roads and are affected by elevated concentrations. Such considerations of air pollution hotspots, have so far been unrepresented in the UN indicator. But our approach, in line with the UN indicator, allows to better record pollution levels and can help local decision-makers to initiate countermeasures," says Ramacher. Overall, Hamburg is below the European average for particulate matter pollution compared to other major European cities and does not exceed the annual EU limit of 20 micrograms per cubic meter for particulate matter smaller than 2.5 micrometers (PM2.5). The SDG 11.6.2 indicator was developed by the United Nations to address the threat to public health from urban air pollution globally. The World Health Organization (WHO) published updated guidelines for air quality benchmarks in late September 2021 to respond to the threat of pollution. The effects of those include seven million premature deaths worldwide each year and many millions of people becoming ill. Air pollution is still a major health problem in Europe as well. The local definition of SDG 11.6.2 indicator brings challenges—mainly because of the diversity of causes of air pollution, for example, from a wide range of emission sources and other influencing factors. The often too few monitoring sites cannot accurately capture the spatial complexity. The study, conducted jointly by Hereon and the National Observatory of Athens, aims to advance the discussion on the potential of the SDG 11.6.2 indicator for local decision-making. This is because detailed inner-city information on pollution and population is needed to fill the research gap that has existed to date and eventually to improve air quality in cities. The study is published in the journal Remote Sensing. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 48528, 39515, 78, 13491, 71770, 12041, 27757, 1561, 6017, 39517, 507, 4590, 3620, 60767, 70288, 41870, 287, 18343, 5907, 8423, 25590, 36639, 8423, 18321, 10608, 16597, 10928, 7181, 19723, 25590, 744, 780, 10506, 27766, 7181, 49107, 2806, 2837, 2052, 13659, 21431, 21844, 7694, 11360, 2052, 60137, 15592, 21400, 32252, 287, 87597, 21400, 32252, 287, 12371, 41632, 85728, 2436, 21400, 32252, 287, 64916, 1050, 45062, 21400, 32252, 287, 34039, 552, 304, 21400, 32252, 287, 9420, 87529, 2956, 9420, 87529, 369, 32708, 9744, 37211, 5848, 21400, 32252, 287, 17005, 21400, 32252, 287, 25027, 21400, 32252, 287, 20585, 21400, 32252, 287, 22302, 21400, 32252, 287, 21400, 32252, 287, 323, 33010, 6354, 33514, 10170, 21400, 32252, 287, 26545, 21400, 32252, 287, 4758, 29225, 21400, 32252, 287, 304, 37963, 323, 43800, 367, 21400, 32252, 287, 304, 4323, 2508, 11, 4323, 316, 16751, 2508, 323, 40602, 36781, 21400, 32252, 287, 315, 279, 10164, 42392, 61657, 9083, 919, 369, 9420, 323, 9878, 16238, 76022, 29422, 21400, 32252, 287, 2052, 60137, 9984, 26292, 2052, 9984, 37543, 21400, 32252, 287, 25, 220, 868, 339, 47898, 220, 1041, 23116, 3507, 91206, 482, 12605, 9151, 21400, 32252, 287, 10170, 220, 17, 303, 14398, 91958, 304, 21400, 32252, 287, 369, 66102, 5848, 34243, 220, 18, 35, 5236, 15161, 82, 304, 9305, 77923, 32625, 51275, 37357, 315, 549, 1950, 81709, 277, 10106, 9483, 395, 535, 98641, 32252, 287, 369, 9420, 744, 13831, 21844, 31966, 323, 60563, 66044, 369, 21400, 32252, 287, 21844, 13257, 21579, 323, 6295, 2956, 33527, 304, 21400, 32252, 287, 369, 18955, 32595, 2402, 9744, 21844, 13257, 21579, 19157, 14576, 369, 39515, 388, 87675, 2956, 18825, 21844, 68886, 28329, 29225, 323, 32625, 21844, 21400, 32252, 287, 19331, 369, 220, 18, 35, 43800, 367, 39546, 323, 16007, 2065, 21844, 61657, 9469, 261, 53686, 39810, 21844, 41994, 304, 21400, 32252, 287, 12605, 16887, 315, 21400, 32252, 287, 323, 549, 1950, 304, 13416, 5814, 323, 20796, 8082, 12605, 39681, 304, 21400, 32252, 287, 323, 83471, 304, 13716, 46879, 323, 10067, 61439, 8471, 91958, 323, 98669, 32625, 315, 1252, 76, 7443, 362, 2918, 56120, 91958, 304, 32625, 315, 11119, 11066, 12616, 66542, 8245, 91958, 304, 31636, 323, 4323, 5237, 17688, 91958, 304, 66542, 3075, 61439, 4758, 18825, 320, 38, 6903, 33, 5987, 8, 91958, 304, 13716, 40708, 2522, 6073, 323, 13716, 39546, 91958, 304, 3075, 323, 15330, 58453, 304, 21400, 32252, 287, 77533, 727, 91958, 304, 3075, 323, 15330, 58453, 304, 21400, 32252, 287, 77533, 727, 8105, 91958, 304, 3075, 61439, 4758, 18825, 2345, 4026, 287, 449, 17863, 31541, 323, 13257, 21579, 91958, 304, 32541, 22018, 21400, 32252, 287, 304, 5734, 1389, 763, 14171, 315, 8626, 13, 41235, 363, 268, 14851, 91958, 304, 8976, 5345, 42947, 323, 75928, 5345, 42947, 26486, 61439, 5783, 809, 7133, 91958, 304, 21400, 32252, 287, 323, 66542, 8245, 10170, 323, 11205, 39923, 304, 4323, 787, 8677, 91958, 304, 21400, 32252, 287, 32625, 369, 279, 58453, 315, 63711, 763, 4378, 919, 91958, 304, 21400, 32252, 287, 369, 66102, 5848, 34243, 91958, 304, 21400, 32252, 287, 304, 72658, 4323, 316, 16751, 2508, 91958, 304, 21400, 32252, 287, 315, 37963, 91958, 304, 21400, 32252, 287, 315, 68420, 10164, 5560, 9589, 5582, 91958, 304, 21400, 32252, 287, 315, 8371, 4720, 91958, 304, 21400, 32252, 287, 315, 13944, 1974, 83930, 91958, 304, 21400, 32252, 287, 6108, 73378, 51803, 323, 37357, 91958, 304, 69878, 25, 95520, 11, 6872, 9268, 11, 323, 32625, 91958, 304, 61657, 1708, 20693, 15501, 91958, 304, 61657, 1708, 20693, 15501, 323, 11699, 7473, 91958, 304, 75928, 5345, 42947, 68886, 21400, 32252, 287, 91958, 304, 279, 21400, 32252, 287, 315, 10335, 53686, 10641, 96649, 91958, 304, 30768, 91064, 2956, 91958, 315, 21400, 32252, 287, 304, 25027, 4323, 24366, 1873, 64250, 337, 323, 15161, 21400, 32252, 287, 6690, 32096, 40708, 2522, 6073, 18825, 315, 21400, 32252, 287, 4758, 2956, 7473, 315, 13257, 21579, 304, 11119, 69377, 51803, 7473, 315, 17896, 6354, 3890, 43337, 12053, 304, 13791, 58453, 323, 48698, 7473, 315, 21400, 32252, 287, 304, 40602, 31356, 77349, 323, 47978, 42109, 9744, 32625, 323, 1561, 50730, 304, 21631, 36781, 369, 68886, 7586, 72, 35, 946, 61439, 15264, 32625, 315, 18682, 21579, 304, 16147, 37963, 32625, 315, 8797, 32418, 630, 81709, 277, 32625, 315, 42102, 1242, 35698, 7133, 369, 9420, 87529, 32625, 315, 18654, 12, 323, 64051, 6354, 266, 42760, 369, 9420, 87529, 32625, 315, 21400, 32252, 287, 304, 63641, 78375, 304, 20023, 5270, 32625, 315, 21400, 32252, 287, 304, 432, 17729, 2914, 8483, 32625, 315, 75928, 5345, 42947, 68886, 320, 50, 946, 8, 369, 11680, 18230, 18825, 19157, 14576, 369, 51803, 11680, 58337, 13584, 367, 449, 21400, 32252, 287, 66102, 5848, 32134, 66448, 323, 21400, 32252, 287, 5277, 27499, 304, 21400, 32252, 287, 2956, 18825, 25, 1556, 37211, 5848, 70288, 59294, 22107, 323, 54878, 304, 61593, 16147, 18945, 287, 59294, 61577, 39810, 323, 38321, 661, 1219, 13623, 304, 21400, 32252, 287, 37357, 315, 93438, 12634, 16607, 449, 21400, 32252, 287, 2755, 318, 13763, 315, 21400, 32252, 287, 2956, 1139, 9420, 744, 27972, 87597, 21400, 32252, 287, 73089, 15379, 21400, 32252, 287, 6295, 2956, 33527, 369, 35602, 323, 16147, 25027, 8471, 6295, 9420, 87529, 2956, 25, 5659, 15161, 25579, 311, 73137, 323, 435, 4692, 492, 426, 380, 780, 51658, 68886, 97395, 323, 19490, 315, 75928, 5345, 42947, 68886, 97395, 323, 56573, 315, 21400, 32252, 287, 58513, 323, 31943, 811, 22208, 42392, 11, 8121, 10604, 11, 323, 17896, 6354, 3890, 21400, 32252, 287, 13416, 5814, 315, 279, 25450, 744, 25, 21400, 32252, 287, 7953, 9420, 33292, 1113, 279, 220, 1135, 339, 47898, 315, 279, 17781, 47524, 449, 25987, 315, 9420, 505, 61657, 323, 36250, 9083, 919, 47317, 10170, 323, 9420, 87529, 31636, 5768, 6427, 323, 51803, 12362, 42102, 1242, 13330, 16842, 21400, 32252, 287, 13330, 12, 6174, 21400, 32252, 287, 555, 26486, 13597, 17820, 1113, 68886, 55882, 56996, 318, 16743, 69878, 43804, 12661, 287, 11, 39546, 323, 86950, 315, 17896, 31874, 2956, 43337, 369, 16147, 32625, 48302, 98641, 323, 68886, 66044, 304, 21400, 32252, 287, 2345, 9972, 42, 715, 220, 2366, 17, 11, 34483, 220, 2366, 17, 27563, 4069, 11680, 18230, 744, 25, 72955, 323, 69778, 369, 18122, 1960, 532, 19241, 323, 28780, 11511, 76450, 18856, 323, 5783, 3376, 2968, 315, 21400, 32252, 287, 58513, 43805, 24527, 11893, 21400, 32252, 287, 2956, 26917, 304, 17896, 12, 17745, 21400, 32252, 287, 2956, 10170, 304, 21400, 32252, 287, 2956, 10170, 11, 59294, 22107, 323, 21400, 32252, 287, 18682, 21579, 369, 78188, 75928, 5345, 42947, 68886, 15264, 18682, 21579, 369, 13791, 3075, 58453, 323, 59776, 304, 21400, 32252, 287, 2956, 18682, 21579, 304, 21400, 32252, 287, 25, 19690, 423, 77749, 11, 86859, 323, 32625, 43622, 4758, 4212, 11378, 18825, 369, 469, 24168, 51803, 7127, 323, 97395, 315, 98641, 35969, 33504, 323, 95459, 33504, 369, 21400, 32252, 287, 315, 279, 9420, 7127, 287, 323, 49407, 279, 9479, 24367, 315, 30978, 45587, 14434, 20585, 12027, 51803, 323, 29879, 81246, 18825, 34039, 287, 362, 4497, 423, 8194, 21400, 32252, 287, 98646, 74581, 61439, 37211, 5848, 45435, 9420, 11847, 51803, 449, 21844, 11746, 32096, 75928, 5345, 42947, 68886, 25, 1561, 24979, 1439, 11, 90396, 82789, 11, 323, 29225, 66044, 9420, 51803, 505, 362, 1561, 24367, 315, 4323, 537, 367, 661, 13479, 42760, 9420, 87529, 323, 61593, 11050, 304, 23820, 323, 30260, 13284, 15264, 9420, 87529, 369, 469, 24168, 82, 51803, 304, 11746, 323, 4212, 9420, 87529, 369, 10164, 12027, 9744, 304, 10384, 9420, 87529, 304, 28780, 369, 61593, 29422, 11050, 9420, 87529, 12053, 36480, 25, 98669, 31145, 15264, 369, 21844, 11680, 28061, 19241, 9420, 87529, 311, 9365, 73378, 88267, 2136, 323, 73378, 32388, 9744, 9420, 87529, 449, 12431, 39, 8268, 2956, 323, 5783, 6387, 48194, 9420, 31943, 811, 369, 264, 24327, 12781, 9420, 9420, 31943, 811, 369, 9356, 287, 8121, 69778, 9420, 31943, 811, 369, 4323, 2319, 1394, 2402, 9420, 31943, 811, 369, 279, 61593, 11050, 37211, 41632, 316, 16751, 5848, 8483, 12362, 61657, 12041, 37211, 5848, 8266, 323, 10604, 555, 21400, 32252, 287, 25027, 8483, 449, 8121, 18464, 61657, 744, 320, 26228, 1242, 8, 93626, 23508, 311, 9365, 54837, 32175, 287, 279, 8189, 82252, 92743, 482, 40395, 3624, 34, 128257, 198, 128256, 78191, 198, 16298, 304, 2466, 9919, 37397, 3958, 3805, 13, 11717, 3805, 430, 17610, 315, 2598, 6468, 5030, 323, 1023, 83661, 11, 902, 17477, 2890, 15635, 311, 16036, 10495, 13, 59250, 6197, 555, 2999, 13, 11826, 15504, 11252, 315, 279, 5810, 263, 10181, 315, 72658, 25027, 42846, 11, 304, 20632, 449, 279, 5165, 58974, 315, 46926, 11, 527, 1457, 10695, 311, 1304, 279, 26314, 315, 2598, 6468, 5030, 9333, 1109, 220, 17, 13, 20, 19748, 442, 2481, 320, 8971, 17, 13, 20, 8, 810, 13687, 13, 2057, 656, 420, 11, 814, 1511, 30447, 2561, 10013, 25480, 25991, 944, 59344, 24088, 828, 304, 10824, 449, 279, 19613, 100001, 7813, 488, 64938, 11742, 7710, 1646, 13, 578, 1887, 8040, 520, 5810, 263, 574, 3025, 311, 1646, 4106, 68110, 369, 3958, 3805, 520, 264, 11175, 315, 220, 1041, 87, 1041, 9518, 20645, 1701, 51562, 439, 459, 3187, 13, 578, 16997, 2598, 6468, 5030, 32466, 527, 11093, 449, 7187, 828, 323, 649, 8617, 25291, 13519, 5789, 449, 8009, 3805, 4367, 323, 1579, 7187, 17915, 13, 4314, 5789, 527, 315, 4040, 2802, 369, 32145, 3805, 4367, 18637, 13, 578, 71674, 13189, 315, 279, 8040, 1749, 374, 279, 10824, 315, 2204, 24088, 828, 11, 902, 527, 26662, 2561, 369, 682, 315, 4606, 11, 449, 3363, 13230, 1646, 29217, 13, 59813, 449, 279, 3152, 907, 315, 220, 975, 8162, 51870, 824, 41999, 23819, 369, 279, 4553, 3363, 8767, 14890, 555, 279, 4435, 6401, 21021, 320, 78847, 8, 369, 279, 3187, 1060, 220, 679, 21, 1511, 11, 51562, 574, 3604, 3917, 311, 4827, 7060, 2598, 6468, 5030, 32466, 315, 220, 806, 311, 220, 717, 8162, 51870, 824, 41999, 23819, 439, 459, 16036, 5578, 13, 4452, 11, 279, 502, 11944, 29217, 1501, 430, 25793, 5990, 527, 4332, 22009, 4028, 279, 3363, 323, 649, 10205, 311, 220, 1114, 8162, 51870, 824, 41999, 23819, 304, 1063, 33100, 13, 330, 644, 4040, 11, 584, 1051, 3025, 311, 8417, 32389, 9974, 3152, 2819, 369, 2598, 6468, 5030, 32466, 369, 279, 6205, 1060, 220, 679, 21, 389, 13326, 19795, 323, 304, 279, 13076, 3158, 3221, 279, 2700, 304, 279, 10007, 315, 279, 4072, 1395, 11188, 13, 6104, 12309, 2478, 1274, 3974, 3221, 279, 13076, 5789, 11, 584, 1051, 3025, 311, 20461, 430, 1690, 1274, 3974, 3221, 17345, 31796, 19795, 323, 527, 11754, 555, 32389, 32466, 13, 15483, 38864, 315, 3805, 25793, 4106, 68110, 11, 617, 779, 3117, 1027, 653, 53859, 304, 279, 6781, 21070, 13, 2030, 1057, 5603, 11, 304, 1584, 449, 279, 6781, 21070, 11, 6276, 311, 2731, 3335, 25793, 5990, 323, 649, 1520, 2254, 5597, 76170, 311, 39201, 5663, 2727, 24368, 1359, 2795, 15504, 11252, 13, 28993, 11, 51562, 374, 3770, 279, 7665, 5578, 369, 2598, 6468, 5030, 25793, 7863, 311, 1023, 3682, 7665, 9919, 323, 1587, 539, 12771, 279, 9974, 10013, 4017, 315, 220, 508, 8162, 51870, 824, 41999, 23819, 369, 2598, 6468, 5030, 9333, 1109, 220, 17, 13, 20, 19748, 442, 2481, 320, 8971, 17, 13, 20, 570, 578, 8189, 38, 220, 806, 13, 21, 13, 17, 21070, 574, 8040, 555, 279, 3723, 19687, 311, 2686, 279, 6023, 311, 586, 2890, 505, 16036, 3805, 25793, 31550, 13, 578, 4435, 6401, 21021, 320, 78847, 8, 4756, 6177, 17959, 369, 3805, 4367, 63119, 304, 3389, 6250, 220, 2366, 16, 311, 6013, 311, 279, 6023, 315, 25793, 13, 578, 6372, 315, 1884, 2997, 8254, 3610, 42227, 16779, 15603, 1855, 1060, 323, 1690, 11990, 315, 1274, 10671, 5986, 13, 6690, 25793, 374, 2103, 264, 3682, 2890, 3575, 304, 4606, 439, 1664, 13, 578, 2254, 7419, 315, 8189, 38, 220, 806, 13, 21, 13, 17, 21070, 12716, 11774, 2345, 3902, 398, 1606, 315, 279, 20057, 315, 11384, 315, 3805, 25793, 11, 369, 3187, 11, 505, 264, 7029, 2134, 315, 41353, 8336, 323, 1023, 66700, 9547, 13, 578, 3629, 2288, 2478, 16967, 6732, 4250, 30357, 12602, 279, 29079, 23965, 13, 578, 4007, 11, 13375, 53258, 555, 5810, 263, 323, 279, 5165, 58974, 315, 46926, 11, 22262, 311, 12178, 279, 10430, 389, 279, 4754, 315, 279, 8189, 38, 220, 806, 13, 21, 13, 17, 21070, 369, 2254, 5597, 28846, 13, 1115, 374, 1606, 11944, 9358, 54429, 2038, 389, 25793, 323, 7187, 374, 4460, 311, 5266, 279, 3495, 13225, 430, 706, 25281, 311, 2457, 323, 9778, 311, 7417, 3805, 4367, 304, 9919, 13, 578, 4007, 374, 4756, 304, 279, 8486, 21400, 32252, 287, 13, 220, 128257, 198 ]

2,083

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Mycobacteriophages are a diverse group of viruses infecting Mycobacterium with substantial therapeutic potential. However, as this potential becomes realized, the molecular details of phage infection and mechanisms of resistance remain ill-defined. Here we use live-cell fluorescence microscopy to visualize the spatiotemporal dynamics of mycobacteriophage infection in single cells and populations, showing that infection is dependent on the host nucleoid-associated Lsr2 protein. Mycobacteriophages preferentially adsorb at Mycobacterium smegmatis sites of new cell wall synthesis and following DNA injection, Lsr2 reorganizes away from host replication foci to establish zones of phage DNA replication (ZOPR). Cells lacking Lsr2 proceed through to cell lysis when infected but fail to generate consecutive phage bursts that trigger epidemic spread of phage particles to neighbouring cells. Many mycobacteriophages code for their own Lsr2-related proteins, and although their roles are unknown, they do not rescue the loss of host Lsr2. Main Bacteriophages are the most numerous biological entities in the biosphere 1 , 2 and possess unparalleled genetic diversity 3 . Host factors needed for phage replication are poorly understood, but mutations both in receptors and intracellular functions can confer phage resistance, and phages must co-evolve in response. This bacterial–phage arms race spans billions of years and dominantly shaped the coevolutionary picture of phages and their hosts 1 , 2 , 4 . Together, these factors contribute to viral host range, a key factor influencing phage therapeutic potential 5 , 6 , 7 , 8 , 9 , 10 . Adsorption to the cell surface is the first step in the phage life cycle. Prevention of adsorption through modification of surface receptors serving as phage entry points is the first line of defence for bacteria, and it is a prevalent target for phage resistance mechanisms 11 . Bacteria thwart phages by acquiring mutations in genes responsible for synthesizing receptors and pathways that secrete extracellular matrix 11 . Resistance can also result from acquiring mutations in host genes that are critical for other stages of the phage life cycle, including those required for phage DNA replication and assembly into mature phage particles 11 . Mycobacteriophages—phages infecting Mycobacterium hosts—are well-studied genomically and are highly diverse. Many are temperate 12 and enter lysogeny where they replicate passively with the host chromosome 13 , 14 , 15 , 16 . Mycobacteriophages have considerable therapeutic potential for Mycobacterium tuberculosis and Mycobacterium abscessus infections, which are challenging to control due to intrinsic or acquired antibiotic resistance as well as prolonged treatment with harsh antibiotic regimens 8 , 12 , 17 , 18 . The more than 2,000 sequenced mycobacteriophage genomes have been grouped into sequence-related clusters (Clusters A, B and so on), many of which have been divided into subclusters (Subclusters A1, A2 and so on) 19 . Currently, there are 31 clusters (Clusters A–AE) and 7 ‘singletons’, each of which has no close relatives 12 , 19 , 20 . All are double-stranded DNA tailed phages, with either siphoviral or myoviral virion morphotypes 12 , 21 . Their narrow host range among nontuberculous mycobacteria strains limits broad therapeutic potential 22 , but little is known about receptors or other determinants of specificity 23 . Lsr2 is a nucleoid-associated protein conserved in mycobacteria and actinomycetes encoded by the lsr2 gene 24 . M. tuberculosis Lsr2 is composed of two domains: an N-terminal DNA-binding domain that binds preferentially to AT-rich DNA and a C-terminal oligomerization domain that promotes nucleoprotein filament formation 25 , 26 . Similar to other bacterial nucleoid-associated proteins, Lsr2 polymerizes around DNA to organize and compact bacterial chromatin 27 and mediates DNA bridging 28 . Lsr2 is essential for M. tuberculosis growth but not for planktonic growth of M. smegmatis , although it is required for biofilm formation 29 and conjugal transfer 30 . Lsr2 is a global gene regulator of cell wall synthesis 26 , 31 , 32 , 33 and virulence genes of M. tuberculosis and M. abscessus 32 , 34 , and contributes to antibiotic resistance 35 . Here we show that Mycobacterium Lsr2 is required for productive infection by many mycobacteriophages. We observed that phages adsorb specifically to sites of new cell wall synthesis and Lsr2 reorganizes away from chromosomal DNA foci to zones of phage DNA replication (ZOPR). We demonstrate that loss of Lsr2 leads to poor ZOPR establishment, phage resistance and interruption of population-level viral epidemics. Results Disruption of M. smegmatis lsr2 confers phage resistance Resistance to phage infection can be mediated by bacterial surface changes resulting in defective binding and DNA injection, or post DNA injection processes that result in either cell death or inhibition of phage replication 36 (Fig. 1a ). Mechanisms of resistance to Cluster K mycobacteriophages and phage Fionnbharth (Subcluster K4) are specifically of interest as these have been proposed for tuberculosis therapy 18 and the related Cluster K2 phage TM4 is widely used for specialized transduction 37 , diagnostic reporter phages 38 and transposon delivery 39 , 40 . We used lytic derivatives of Fionnbharth (FionnbharthΔ 47 or FionnbharthΔ 45 Δ 47 , deleted for repressor or both integrase and repressor, respectively 22 ) to isolate resistant mutants of M. smegmatis mc 2 155. Five resistant strains were recovered and purified, and designated LM11, LM12, LM13, LM14 and LM15. We confirmed them to be Fionnbharth-resistant (Fig. 1b ) but sensitive to unrelated phages such as Bxb1 (Subcluster A1) 41 (Fig. 1b ) and BPs (Subcluster G1) 42 . The five genomes were completely sequenced and compared with the parent strain. LM11 has non-synonymous mutations in several genes including those encoding NAD(P)-dependent alcohol dehydrogenase (MSMEG_4039) and glycogen debranching enzyme GlgX (MSMEG_3186). LM12 and LM13 share the same mutation in a methylmalonyl CoA mutase gene (MSMEG_4881) but have additional mutations elsewhere. Strain LM15 has three mutations resulting in amino acid substitutions: D113G (A3649339G) in MSMEG_3578, E392A (C6970708A) in ABC transporter permease subunit MSMEG_6909 and G93V (C6169539A) in lsr2 (MSMEG_6092). Strains LM11–LM13 and LM15 were not characterized further. Strain LM14 contains only a single difference from the parent strain: insertion of a resident", "role": "user" }, { "content": "As antibacterial resistance continues to render obsolete the use of some antibiotics, some have turned to bacteria-killing viruses to treat acute infections as well as some chronic illnesses. Graham Hatfull, the Eberly Family Professor of Biotechnology in the Kenneth P. Dietrich School of Arts and Sciences at Pitt, has pioneered the use of these viruses—bacteriophages, phages for short—to treat infections in chronic diseases such as cystic fibrosis. Although the importance of resistance may have eluded the early discovers of antibiotics, Hatfull is intent on understanding how bacteria become resistant to phages. His lab has just discovered how a specific mutation in a bacterium results in phage resistance. The results were published Feb. 23, in the journal Nature Microbiology. The new methodology and tools his team developed also gave them the opportunity to watch in unprecedented detail as a phage attacks a bacterium. As the use of phage therapy expands, these tools can help others better understand how different mutations protect bacteria against invasion by their phages. For this study, the team started with Mycobacterium smegmatis, a harmless relative of the bacteria responsible for tuberculosis, leprosy and other hard-to-treat, chronic diseases. They then isolated a mutant form of the bacterium that is resistant to infection by a phage called Fionnbharth. Infection of Mycobacterium smegmatis by a genetically engineered mutant of phage Fionnbharth. Three steps in the infection process can be seen:1) A single phage particle binds to the bacterial cell, and is seen as a red dot 0.42 seconds into the video.2) Two seconds into the movie, green fluorescence is observed where the phage has injected its DNA into the cell. The green fluorescence comes directly from the phage DNA (ignore the bright green dots at the very ends of the cell). Over the next few seconds, the green-labeled DNA forms a zone of phage replication (ZOPR) and spreads throughout the cell. 3) At 6:25 seconds, lysis occurs and the cell explodes. Total time elapsed is about three hours. Credit: Charles Dulberger To understand how the specific mutation in the lsr2 gene helps these resistant bacteria fight off a phage, the team first needed to understand how phages killed a bacteria without the relevant mutation. Carlos Guerrero-Bustamante, a fourth-year graduate student in Hatfull's lab, genetically engineered two special kinds of phages for this study. Some produced red fluorescence when they entered a bacterial cell. Others had segments of DNA that would stick to fluorescent molecules so phage DNA would light up in an infected cell. Following the fluorescent beacons, \"We could see where the phage DNA entered the cell,\" Guerrero-Bustamante said. The imaging methods they used were designed by Charles Dulberger, a collaborator and co-first author of the paper who was then at Harvard T.H. Chan School of Public Health. \"We saw for the first time how the phages take that first step of binding to cells and injecting their DNA into the bacteria,\" said Hatfull, who is also a Howard Hughes Medical Institute Professor. \"Then we applied those insights to ask, 'So, how's it different if we get rid of the Lsr2 protein?'\" The link between Lsr2 and phage resistance has not been previously known, but with their new methods and tools, the team clearly saw the critical role it played. Typically, Lsr2 helps bacteria replicate its own DNA. When a phage attacks, however, the virus co-opts the protein, using it to replicate phage DNA and overwhelm the bacteria. When the lsr2 gene is missing or defective—as in the phage-resistant Mycobacterium smegmatis—the bacteria doesn't make the protein and phages don't replicate enough to take over the bacterial cell. This was a surprise. \"We didn't know Lsr2 had anything to do with bacteriophages,\" Hatfull said. These new tools can be used to uncover all manner of surprises written in the genes of phage-resistant bacteria. It may also help today's researchers and tomorrow's clinicians to better understand and take advantage of phages' abilities while avoiding the missteps that led to antibiotic resistance. \"This paper focuses on just one bacterial protein,\" and its resistance to just one phage, Hatfull said, but its implications are wide. \"There are lots of different phages and lots of other proteins.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Mycobacteriophages are a diverse group of viruses infecting Mycobacterium with substantial therapeutic potential. However, as this potential becomes realized, the molecular details of phage infection and mechanisms of resistance remain ill-defined. Here we use live-cell fluorescence microscopy to visualize the spatiotemporal dynamics of mycobacteriophage infection in single cells and populations, showing that infection is dependent on the host nucleoid-associated Lsr2 protein. Mycobacteriophages preferentially adsorb at Mycobacterium smegmatis sites of new cell wall synthesis and following DNA injection, Lsr2 reorganizes away from host replication foci to establish zones of phage DNA replication (ZOPR). Cells lacking Lsr2 proceed through to cell lysis when infected but fail to generate consecutive phage bursts that trigger epidemic spread of phage particles to neighbouring cells. Many mycobacteriophages code for their own Lsr2-related proteins, and although their roles are unknown, they do not rescue the loss of host Lsr2. Main Bacteriophages are the most numerous biological entities in the biosphere 1 , 2 and possess unparalleled genetic diversity 3 . Host factors needed for phage replication are poorly understood, but mutations both in receptors and intracellular functions can confer phage resistance, and phages must co-evolve in response. This bacterial–phage arms race spans billions of years and dominantly shaped the coevolutionary picture of phages and their hosts 1 , 2 , 4 . Together, these factors contribute to viral host range, a key factor influencing phage therapeutic potential 5 , 6 , 7 , 8 , 9 , 10 . Adsorption to the cell surface is the first step in the phage life cycle. Prevention of adsorption through modification of surface receptors serving as phage entry points is the first line of defence for bacteria, and it is a prevalent target for phage resistance mechanisms 11 . Bacteria thwart phages by acquiring mutations in genes responsible for synthesizing receptors and pathways that secrete extracellular matrix 11 . Resistance can also result from acquiring mutations in host genes that are critical for other stages of the phage life cycle, including those required for phage DNA replication and assembly into mature phage particles 11 . Mycobacteriophages—phages infecting Mycobacterium hosts—are well-studied genomically and are highly diverse. Many are temperate 12 and enter lysogeny where they replicate passively with the host chromosome 13 , 14 , 15 , 16 . Mycobacteriophages have considerable therapeutic potential for Mycobacterium tuberculosis and Mycobacterium abscessus infections, which are challenging to control due to intrinsic or acquired antibiotic resistance as well as prolonged treatment with harsh antibiotic regimens 8 , 12 , 17 , 18 . The more than 2,000 sequenced mycobacteriophage genomes have been grouped into sequence-related clusters (Clusters A, B and so on), many of which have been divided into subclusters (Subclusters A1, A2 and so on) 19 . Currently, there are 31 clusters (Clusters A–AE) and 7 ‘singletons’, each of which has no close relatives 12 , 19 , 20 . All are double-stranded DNA tailed phages, with either siphoviral or myoviral virion morphotypes 12 , 21 . Their narrow host range among nontuberculous mycobacteria strains limits broad therapeutic potential 22 , but little is known about receptors or other determinants of specificity 23 . Lsr2 is a nucleoid-associated protein conserved in mycobacteria and actinomycetes encoded by the lsr2 gene 24 . M. tuberculosis Lsr2 is composed of two domains: an N-terminal DNA-binding domain that binds preferentially to AT-rich DNA and a C-terminal oligomerization domain that promotes nucleoprotein filament formation 25 , 26 . Similar to other bacterial nucleoid-associated proteins, Lsr2 polymerizes around DNA to organize and compact bacterial chromatin 27 and mediates DNA bridging 28 . Lsr2 is essential for M. tuberculosis growth but not for planktonic growth of M. smegmatis , although it is required for biofilm formation 29 and conjugal transfer 30 . Lsr2 is a global gene regulator of cell wall synthesis 26 , 31 , 32 , 33 and virulence genes of M. tuberculosis and M. abscessus 32 , 34 , and contributes to antibiotic resistance 35 . Here we show that Mycobacterium Lsr2 is required for productive infection by many mycobacteriophages. We observed that phages adsorb specifically to sites of new cell wall synthesis and Lsr2 reorganizes away from chromosomal DNA foci to zones of phage DNA replication (ZOPR). We demonstrate that loss of Lsr2 leads to poor ZOPR establishment, phage resistance and interruption of population-level viral epidemics. Results Disruption of M. smegmatis lsr2 confers phage resistance Resistance to phage infection can be mediated by bacterial surface changes resulting in defective binding and DNA injection, or post DNA injection processes that result in either cell death or inhibition of phage replication 36 (Fig. 1a ). Mechanisms of resistance to Cluster K mycobacteriophages and phage Fionnbharth (Subcluster K4) are specifically of interest as these have been proposed for tuberculosis therapy 18 and the related Cluster K2 phage TM4 is widely used for specialized transduction 37 , diagnostic reporter phages 38 and transposon delivery 39 , 40 . We used lytic derivatives of Fionnbharth (FionnbharthΔ 47 or FionnbharthΔ 45 Δ 47 , deleted for repressor or both integrase and repressor, respectively 22 ) to isolate resistant mutants of M. smegmatis mc 2 155. Five resistant strains were recovered and purified, and designated LM11, LM12, LM13, LM14 and LM15. We confirmed them to be Fionnbharth-resistant (Fig. 1b ) but sensitive to unrelated phages such as Bxb1 (Subcluster A1) 41 (Fig. 1b ) and BPs (Subcluster G1) 42 . The five genomes were completely sequenced and compared with the parent strain. LM11 has non-synonymous mutations in several genes including those encoding NAD(P)-dependent alcohol dehydrogenase (MSMEG_4039) and glycogen debranching enzyme GlgX (MSMEG_3186). LM12 and LM13 share the same mutation in a methylmalonyl CoA mutase gene (MSMEG_4881) but have additional mutations elsewhere. Strain LM15 has three mutations resulting in amino acid substitutions: D113G (A3649339G) in MSMEG_3578, E392A (C6970708A) in ABC transporter permease subunit MSMEG_6909 and G93V (C6169539A) in lsr2 (MSMEG_6092). Strains LM11–LM13 and LM15 were not characterized further. Strain LM14 contains only a single difference from the parent strain: insertion of a resident<|im_end|> <|im_start|>assistant As antibacterial resistance continues to render obsolete the use of some antibiotics, some have turned to bacteria-killing viruses to treat acute infections as well as some chronic illnesses. Graham Hatfull, the Eberly Family Professor of Biotechnology in the Kenneth P. Dietrich School of Arts and Sciences at Pitt, has pioneered the use of these viruses—bacteriophages, phages for short—to treat infections in chronic diseases such as cystic fibrosis. Although the importance of resistance may have eluded the early discovers of antibiotics, Hatfull is intent on understanding how bacteria become resistant to phages. His lab has just discovered how a specific mutation in a bacterium results in phage resistance. The results were published Feb. 23, in the journal Nature Microbiology. The new methodology and tools his team developed also gave them the opportunity to watch in unprecedented detail as a phage attacks a bacterium. As the use of phage therapy expands, these tools can help others better understand how different mutations protect bacteria against invasion by their phages. For this study, the team started with Mycobacterium smegmatis, a harmless relative of the bacteria responsible for tuberculosis, leprosy and other hard-to-treat, chronic diseases. They then isolated a mutant form of the bacterium that is resistant to infection by a phage called Fionnbharth. Infection of Mycobacterium smegmatis by a genetically engineered mutant of phage Fionnbharth. Three steps in the infection process can be seen:1) A single phage particle binds to the bacterial cell, and is seen as a red dot 0.42 seconds into the video.2) Two seconds into the movie, green fluorescence is observed where the phage has injected its DNA into the cell. The green fluorescence comes directly from the phage DNA (ignore the bright green dots at the very ends of the cell). Over the next few seconds, the green-labeled DNA forms a zone of phage replication (ZOPR) and spreads throughout the cell. 3) At 6:25 seconds, lysis occurs and the cell explodes. Total time elapsed is about three hours. Credit: Charles Dulberger To understand how the specific mutation in the lsr2 gene helps these resistant bacteria fight off a phage, the team first needed to understand how phages killed a bacteria without the relevant mutation. Carlos Guerrero-Bustamante, a fourth-year graduate student in Hatfull's lab, genetically engineered two special kinds of phages for this study. Some produced red fluorescence when they entered a bacterial cell. Others had segments of DNA that would stick to fluorescent molecules so phage DNA would light up in an infected cell. Following the fluorescent beacons, "We could see where the phage DNA entered the cell," Guerrero-Bustamante said. The imaging methods they used were designed by Charles Dulberger, a collaborator and co-first author of the paper who was then at Harvard T.H. Chan School of Public Health. "We saw for the first time how the phages take that first step of binding to cells and injecting their DNA into the bacteria," said Hatfull, who is also a Howard Hughes Medical Institute Professor. "Then we applied those insights to ask, 'So, how's it different if we get rid of the Lsr2 protein?'" The link between Lsr2 and phage resistance has not been previously known, but with their new methods and tools, the team clearly saw the critical role it played. Typically, Lsr2 helps bacteria replicate its own DNA. When a phage attacks, however, the virus co-opts the protein, using it to replicate phage DNA and overwhelm the bacteria. When the lsr2 gene is missing or defective—as in the phage-resistant Mycobacterium smegmatis—the bacteria doesn't make the protein and phages don't replicate enough to take over the bacterial cell. This was a surprise. "We didn't know Lsr2 had anything to do with bacteriophages," Hatfull said. These new tools can be used to uncover all manner of surprises written in the genes of phage-resistant bacteria. It may also help today's researchers and tomorrow's clinicians to better understand and take advantage of phages' abilities while avoiding the missteps that led to antibiotic resistance. "This paper focuses on just one bacterial protein," and its resistance to just one phage, Hatfull said, but its implications are wide. "There are lots of different phages and lots of other proteins." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 3092, 86656, 2540, 72, 5237, 1154, 527, 264, 17226, 1912, 315, 42068, 34527, 287, 3092, 86656, 2540, 2411, 449, 12190, 37471, 4754, 13, 4452, 11, 439, 420, 4754, 9221, 15393, 11, 279, 31206, 3649, 315, 1343, 425, 19405, 323, 24717, 315, 13957, 7293, 5986, 39817, 13, 5810, 584, 1005, 3974, 33001, 97332, 92914, 311, 51187, 279, 993, 9491, 354, 3342, 10020, 30295, 315, 856, 86656, 2540, 72, 99054, 19405, 304, 3254, 7917, 323, 22673, 11, 9204, 430, 19405, 374, 18222, 389, 279, 3552, 31484, 590, 75968, 445, 15444, 17, 13128, 13, 3092, 86656, 2540, 72, 5237, 1154, 10932, 31668, 14058, 30986, 520, 3092, 86656, 2540, 2411, 1554, 797, 76, 3689, 6732, 315, 502, 2849, 7147, 39975, 323, 2768, 15922, 26127, 11, 445, 15444, 17, 312, 8629, 4861, 3201, 505, 3552, 48891, 282, 2168, 311, 5813, 26467, 315, 1343, 425, 15922, 48891, 320, 57, 3143, 49, 570, 59190, 32161, 445, 15444, 17, 10570, 1555, 311, 2849, 326, 4548, 994, 29374, 719, 3775, 311, 7068, 24871, 1343, 425, 66801, 430, 8346, 42620, 9041, 315, 1343, 425, 19252, 311, 62027, 7917, 13, 9176, 856, 86656, 2540, 72, 5237, 1154, 2082, 369, 872, 1866, 445, 15444, 17, 14228, 28896, 11, 323, 8051, 872, 13073, 527, 9987, 11, 814, 656, 539, 17629, 279, 4814, 315, 3552, 445, 15444, 17, 13, 4802, 426, 2540, 72, 5237, 1154, 527, 279, 1455, 12387, 24156, 15086, 304, 279, 49554, 8182, 220, 16, 1174, 220, 17, 323, 15575, 71257, 19465, 20057, 220, 18, 662, 16492, 9547, 4460, 369, 1343, 425, 48891, 527, 31555, 16365, 11, 719, 34684, 2225, 304, 44540, 323, 10805, 65441, 5865, 649, 49843, 1343, 425, 13957, 11, 323, 1343, 1154, 2011, 1080, 91345, 4035, 304, 2077, 13, 1115, 45964, 4235, 764, 425, 11977, 7102, 45395, 33151, 315, 1667, 323, 11358, 18007, 27367, 279, 1080, 5230, 3294, 661, 6945, 315, 1343, 1154, 323, 872, 18939, 220, 16, 1174, 220, 17, 1174, 220, 19, 662, 32255, 11, 1521, 9547, 17210, 311, 29962, 3552, 2134, 11, 264, 1401, 8331, 66700, 1343, 425, 37471, 4754, 220, 20, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 662, 43283, 66181, 311, 279, 2849, 7479, 374, 279, 1176, 3094, 304, 279, 1343, 425, 2324, 11008, 13, 36947, 315, 14058, 66181, 1555, 17466, 315, 7479, 44540, 13788, 439, 1343, 425, 4441, 3585, 374, 279, 1176, 1584, 315, 23682, 369, 24032, 11, 323, 433, 374, 264, 46941, 2218, 369, 1343, 425, 13957, 24717, 220, 806, 662, 426, 78852, 64788, 1343, 1154, 555, 42990, 34684, 304, 21389, 8647, 369, 52389, 4954, 44540, 323, 44014, 430, 513, 9537, 11741, 65441, 6303, 220, 806, 662, 40980, 649, 1101, 1121, 505, 42990, 34684, 304, 3552, 21389, 430, 527, 9200, 369, 1023, 18094, 315, 279, 1343, 425, 2324, 11008, 11, 2737, 1884, 2631, 369, 1343, 425, 15922, 48891, 323, 14956, 1139, 15196, 1343, 425, 19252, 220, 806, 662, 3092, 86656, 2540, 72, 5237, 1154, 2345, 764, 1154, 34527, 287, 3092, 86656, 2540, 2411, 18939, 83872, 1664, 5594, 664, 1142, 99298, 2740, 323, 527, 7701, 17226, 13, 9176, 527, 6940, 349, 220, 717, 323, 3810, 84495, 11968, 88, 1405, 814, 46113, 1522, 3210, 449, 279, 3552, 51815, 220, 1032, 1174, 220, 975, 1174, 220, 868, 1174, 220, 845, 662, 3092, 86656, 2540, 72, 5237, 1154, 617, 24779, 37471, 4754, 369, 3092, 86656, 2540, 2411, 88234, 323, 3092, 86656, 2540, 2411, 3731, 1140, 355, 30020, 11, 902, 527, 17436, 311, 2585, 4245, 311, 47701, 477, 19426, 60595, 13957, 439, 1664, 439, 44387, 6514, 449, 25984, 60595, 1239, 46697, 220, 23, 1174, 220, 717, 1174, 220, 1114, 1174, 220, 972, 662, 578, 810, 1109, 220, 17, 11, 931, 11506, 5886, 856, 86656, 2540, 72, 99054, 85381, 617, 1027, 41141, 1139, 8668, 14228, 28066, 320, 96092, 362, 11, 426, 323, 779, 389, 705, 1690, 315, 902, 617, 1027, 18255, 1139, 1207, 79621, 320, 3214, 79621, 362, 16, 11, 362, 17, 323, 779, 389, 8, 220, 777, 662, 25122, 11, 1070, 527, 220, 2148, 28066, 320, 96092, 362, 4235, 13983, 8, 323, 220, 22, 3451, 15698, 35511, 20182, 1855, 315, 902, 706, 912, 3345, 29658, 220, 717, 1174, 220, 777, 1174, 220, 508, 662, 2052, 527, 2033, 42728, 6601, 15922, 259, 5805, 1343, 1154, 11, 449, 3060, 274, 15619, 869, 37478, 477, 856, 869, 37478, 9043, 290, 27448, 22583, 220, 717, 1174, 220, 1691, 662, 11205, 15376, 3552, 2134, 4315, 308, 546, 392, 3035, 13850, 856, 86656, 78852, 42400, 13693, 7353, 37471, 4754, 220, 1313, 1174, 719, 2697, 374, 3967, 922, 44540, 477, 1023, 6449, 1821, 315, 76041, 220, 1419, 662, 445, 15444, 17, 374, 264, 31484, 590, 75968, 13128, 1615, 2841, 304, 856, 86656, 78852, 323, 1180, 258, 316, 3418, 96281, 21136, 555, 279, 326, 15444, 17, 15207, 220, 1187, 662, 386, 13, 88234, 445, 15444, 17, 374, 24306, 315, 1403, 31576, 25, 459, 452, 91723, 15922, 65500, 8106, 430, 58585, 10932, 31668, 311, 7520, 41947, 15922, 323, 264, 356, 91723, 55984, 26429, 2065, 8106, 430, 39990, 31484, 454, 91748, 91880, 18488, 220, 914, 1174, 220, 1627, 662, 22196, 311, 1023, 45964, 31484, 590, 75968, 28896, 11, 445, 15444, 17, 47393, 4861, 2212, 15922, 311, 31335, 323, 17251, 45964, 22083, 15111, 220, 1544, 323, 25098, 988, 15922, 77847, 3252, 220, 1591, 662, 445, 15444, 17, 374, 7718, 369, 386, 13, 88234, 6650, 719, 539, 369, 73187, 783, 292, 6650, 315, 386, 13, 1554, 797, 76, 3689, 1174, 8051, 433, 374, 2631, 369, 17332, 31255, 18488, 220, 1682, 323, 16898, 45284, 8481, 220, 966, 662, 445, 15444, 17, 374, 264, 3728, 15207, 40704, 315, 2849, 7147, 39975, 220, 1627, 1174, 220, 2148, 1174, 220, 843, 1174, 220, 1644, 323, 9043, 59566, 21389, 315, 386, 13, 88234, 323, 386, 13, 3731, 1140, 355, 220, 843, 1174, 220, 1958, 1174, 323, 44072, 311, 60595, 13957, 220, 1758, 662, 5810, 584, 1501, 430, 3092, 86656, 2540, 2411, 445, 15444, 17, 374, 2631, 369, 27331, 19405, 555, 1690, 856, 86656, 2540, 72, 5237, 1154, 13, 1226, 13468, 430, 1343, 1154, 14058, 30986, 11951, 311, 6732, 315, 502, 2849, 7147, 39975, 323, 445, 15444, 17, 312, 8629, 4861, 3201, 505, 22083, 96108, 15922, 282, 2168, 311, 26467, 315, 1343, 425, 15922, 48891, 320, 57, 3143, 49, 570, 1226, 20461, 430, 4814, 315, 445, 15444, 17, 11767, 311, 8009, 1901, 3143, 49, 21967, 11, 1343, 425, 13957, 323, 75103, 315, 7187, 11852, 29962, 28817, 38305, 13, 18591, 4185, 14455, 315, 386, 13, 1554, 797, 76, 3689, 326, 15444, 17, 2389, 388, 1343, 425, 13957, 40980, 311, 1343, 425, 19405, 649, 387, 78926, 555, 45964, 7479, 4442, 13239, 304, 64903, 11212, 323, 15922, 26127, 11, 477, 1772, 15922, 26127, 11618, 430, 1121, 304, 3060, 2849, 4648, 477, 61478, 315, 1343, 425, 48891, 220, 1927, 320, 30035, 13, 220, 16, 64, 7609, 28901, 13978, 315, 13957, 311, 36480, 735, 856, 86656, 2540, 72, 5237, 1154, 323, 1343, 425, 435, 290, 18571, 13279, 339, 320, 3214, 19386, 735, 19, 8, 527, 11951, 315, 2802, 439, 1521, 617, 1027, 11223, 369, 88234, 15419, 220, 972, 323, 279, 5552, 36480, 735, 17, 1343, 425, 24929, 19, 374, 13882, 1511, 369, 28175, 1380, 23985, 220, 1806, 1174, 15439, 19496, 1343, 1154, 220, 1987, 323, 1380, 981, 263, 9889, 220, 2137, 1174, 220, 1272, 662, 1226, 1511, 14869, 29150, 43645, 315, 435, 290, 18571, 13279, 339, 320, 37, 290, 18571, 13279, 339, 101561, 220, 2618, 477, 435, 290, 18571, 13279, 339, 101561, 220, 1774, 82263, 220, 2618, 1174, 11309, 369, 312, 57320, 477, 2225, 8936, 521, 323, 312, 57320, 11, 15947, 220, 1313, 883, 311, 43223, 31785, 88754, 315, 386, 13, 1554, 797, 76, 3689, 19777, 220, 17, 220, 9992, 13, 21594, 31785, 42400, 1051, 26403, 323, 92600, 11, 323, 24073, 47514, 806, 11, 47514, 717, 11, 47514, 1032, 11, 47514, 975, 323, 47514, 868, 13, 1226, 11007, 1124, 311, 387, 435, 290, 18571, 13279, 339, 47056, 320, 30035, 13, 220, 16, 65, 883, 719, 16614, 311, 46305, 1343, 1154, 1778, 439, 426, 8088, 16, 320, 3214, 19386, 362, 16, 8, 220, 3174, 320, 30035, 13, 220, 16, 65, 883, 323, 426, 21051, 320, 3214, 19386, 480, 16, 8, 220, 2983, 662, 578, 4330, 85381, 1051, 6724, 11506, 5886, 323, 7863, 449, 279, 2748, 26800, 13, 47514, 806, 706, 2536, 1355, 1910, 9956, 34684, 304, 3892, 21389, 2737, 1884, 11418, 452, 1846, 5417, 7435, 38655, 13200, 409, 67229, 4469, 521, 320, 4931, 7614, 38, 62, 13074, 24, 8, 323, 72157, 11968, 409, 18424, 287, 49242, 8444, 70, 55, 320, 4931, 7614, 38, 62, 17592, 21, 570, 47514, 717, 323, 47514, 1032, 4430, 279, 1890, 27472, 304, 264, 79574, 14991, 3633, 75, 3623, 32, 5318, 521, 15207, 320, 4931, 7614, 38, 62, 21310, 16, 8, 719, 617, 5217, 34684, 18403, 13, 4610, 467, 47514, 868, 706, 2380, 34684, 13239, 304, 42500, 13935, 94750, 25, 423, 8190, 38, 320, 32, 15951, 25806, 24, 38, 8, 304, 10504, 7614, 38, 62, 18520, 23, 11, 469, 19695, 32, 320, 34, 25388, 17819, 23, 32, 8, 304, 19921, 73565, 55424, 521, 1207, 3928, 10504, 7614, 38, 62, 21741, 24, 323, 480, 6365, 53, 320, 34, 21379, 25326, 24, 32, 8, 304, 326, 15444, 17, 320, 4931, 7614, 38, 62, 21138, 17, 570, 4610, 1771, 47514, 806, 4235, 11237, 1032, 323, 47514, 868, 1051, 539, 32971, 4726, 13, 4610, 467, 47514, 975, 5727, 1193, 264, 3254, 6811, 505, 279, 2748, 26800, 25, 37027, 315, 264, 19504, 128257, 198, 128256, 78191, 198, 2170, 21196, 71034, 13957, 9731, 311, 3219, 47166, 279, 1005, 315, 1063, 46850, 11, 1063, 617, 6656, 311, 24032, 12934, 9585, 42068, 311, 4322, 30883, 30020, 439, 1664, 439, 1063, 21249, 49909, 13, 26181, 22050, 9054, 11, 279, 469, 655, 398, 12517, 17054, 315, 12371, 52536, 304, 279, 49498, 393, 13, 27304, 14172, 6150, 315, 17979, 323, 23199, 520, 21823, 11, 706, 96734, 279, 1005, 315, 1521, 42068, 2345, 65, 2540, 72, 5237, 1154, 11, 1343, 1154, 369, 2875, 50617, 4322, 30020, 304, 21249, 19338, 1778, 439, 63581, 292, 16178, 63412, 13, 10541, 279, 12939, 315, 13957, 1253, 617, 658, 38477, 279, 4216, 52114, 315, 46850, 11, 22050, 9054, 374, 7537, 389, 8830, 1268, 24032, 3719, 31785, 311, 1343, 1154, 13, 5414, 10278, 706, 1120, 11352, 1268, 264, 3230, 27472, 304, 264, 17854, 2411, 3135, 304, 1343, 425, 13957, 13, 578, 3135, 1051, 4756, 13806, 13, 220, 1419, 11, 304, 279, 8486, 22037, 18654, 81162, 13, 578, 502, 38152, 323, 7526, 813, 2128, 8040, 1101, 6688, 1124, 279, 6776, 311, 3821, 304, 31069, 7872, 439, 264, 1343, 425, 8951, 264, 17854, 2411, 13, 1666, 279, 1005, 315, 1343, 425, 15419, 52956, 11, 1521, 7526, 649, 1520, 3885, 2731, 3619, 1268, 2204, 34684, 6144, 24032, 2403, 30215, 555, 872, 1343, 1154, 13, 1789, 420, 4007, 11, 279, 2128, 3940, 449, 3092, 86656, 2540, 2411, 1554, 797, 76, 3689, 11, 264, 53997, 8844, 315, 279, 24032, 8647, 369, 88234, 11, 514, 782, 23707, 323, 1023, 2653, 4791, 2442, 1244, 11, 21249, 19338, 13, 2435, 1243, 25181, 264, 61618, 1376, 315, 279, 17854, 2411, 430, 374, 31785, 311, 19405, 555, 264, 1343, 425, 2663, 435, 290, 18571, 13279, 339, 13, 763, 13421, 315, 3092, 86656, 2540, 2411, 1554, 797, 76, 3689, 555, 264, 52033, 46036, 61618, 315, 1343, 425, 435, 290, 18571, 13279, 339, 13, 14853, 7504, 304, 279, 19405, 1920, 649, 387, 3970, 25, 16, 8, 362, 3254, 1343, 425, 19320, 58585, 311, 279, 45964, 2849, 11, 323, 374, 3970, 439, 264, 2579, 13046, 220, 15, 13, 2983, 6622, 1139, 279, 2835, 13, 17, 8, 9220, 6622, 1139, 279, 5818, 11, 6307, 97332, 374, 13468, 1405, 279, 1343, 425, 706, 41772, 1202, 15922, 1139, 279, 2849, 13, 578, 6307, 97332, 4131, 6089, 505, 279, 1343, 425, 15922, 320, 13431, 279, 10107, 6307, 32094, 520, 279, 1633, 10548, 315, 279, 2849, 570, 6193, 279, 1828, 2478, 6622, 11, 279, 6307, 2922, 23121, 15922, 7739, 264, 10353, 315, 1343, 425, 48891, 320, 57, 3143, 49, 8, 323, 43653, 6957, 279, 2849, 13, 220, 18, 8, 2468, 220, 21, 25, 914, 6622, 11, 326, 4548, 13980, 323, 279, 2849, 95013, 13, 10884, 892, 26401, 374, 922, 2380, 4207, 13, 16666, 25, 15274, 63715, 49120, 2057, 3619, 1268, 279, 3230, 27472, 304, 279, 326, 15444, 17, 15207, 8779, 1521, 31785, 24032, 4465, 1022, 264, 1343, 425, 11, 279, 2128, 1176, 4460, 311, 3619, 1268, 1343, 1154, 7577, 264, 24032, 2085, 279, 9959, 27472, 13, 30397, 98836, 7826, 592, 309, 5048, 11, 264, 11999, 4771, 19560, 5575, 304, 22050, 9054, 596, 10278, 11, 52033, 46036, 1403, 3361, 13124, 315, 1343, 1154, 369, 420, 4007, 13, 4427, 9124, 2579, 97332, 994, 814, 10862, 264, 45964, 2849, 13, 26080, 1047, 21282, 315, 15922, 430, 1053, 9396, 311, 74864, 35715, 779, 1343, 425, 15922, 1053, 3177, 709, 304, 459, 29374, 2849, 13, 23548, 279, 74864, 387, 76544, 11, 330, 1687, 1436, 1518, 1405, 279, 1343, 425, 15922, 10862, 279, 2849, 1359, 98836, 7826, 592, 309, 5048, 1071, 13, 578, 32758, 5528, 814, 1511, 1051, 6319, 555, 15274, 63715, 49120, 11, 264, 11430, 859, 323, 1080, 38043, 3229, 315, 279, 5684, 889, 574, 1243, 520, 25996, 350, 3924, 13, 42402, 6150, 315, 3142, 6401, 13, 330, 1687, 5602, 369, 279, 1176, 892, 1268, 279, 1343, 1154, 1935, 430, 1176, 3094, 315, 11212, 311, 7917, 323, 88385, 872, 15922, 1139, 279, 24032, 1359, 1071, 22050, 9054, 11, 889, 374, 1101, 264, 20462, 41411, 13235, 10181, 17054, 13, 330, 12487, 584, 9435, 1884, 26793, 311, 2610, 11, 364, 4516, 11, 1268, 596, 433, 2204, 422, 584, 636, 9463, 315, 279, 445, 15444, 17, 13128, 30, 15260, 578, 2723, 1990, 445, 15444, 17, 323, 1343, 425, 13957, 706, 539, 1027, 8767, 3967, 11, 719, 449, 872, 502, 5528, 323, 7526, 11, 279, 2128, 9539, 5602, 279, 9200, 3560, 433, 6476, 13, 46402, 11, 445, 15444, 17, 8779, 24032, 46113, 1202, 1866, 15922, 13, 3277, 264, 1343, 425, 8951, 11, 4869, 11, 279, 17188, 1080, 12, 10740, 279, 13128, 11, 1701, 433, 311, 46113, 1343, 425, 15922, 323, 96848, 279, 24032, 13, 3277, 279, 326, 15444, 17, 15207, 374, 7554, 477, 64903, 60654, 304, 279, 1343, 425, 47056, 3092, 86656, 2540, 2411, 1554, 797, 76, 3689, 22416, 24032, 3250, 956, 1304, 279, 13128, 323, 1343, 1154, 1541, 956, 46113, 3403, 311, 1935, 927, 279, 45964, 2849, 13, 1115, 574, 264, 13051, 13, 330, 1687, 3287, 956, 1440, 445, 15444, 17, 1047, 4205, 311, 656, 449, 17854, 72, 5237, 1154, 1359, 22050, 9054, 1071, 13, 4314, 502, 7526, 649, 387, 1511, 311, 45063, 682, 11827, 315, 46540, 5439, 304, 279, 21389, 315, 1343, 425, 47056, 24032, 13, 1102, 1253, 1101, 1520, 3432, 596, 12074, 323, 16986, 596, 78545, 311, 2731, 3619, 323, 1935, 9610, 315, 1343, 1154, 6, 18000, 1418, 31526, 279, 5906, 25047, 430, 6197, 311, 60595, 13957, 13, 330, 2028, 5684, 24400, 389, 1120, 832, 45964, 13128, 1359, 323, 1202, 13957, 311, 1120, 832, 1343, 425, 11, 22050, 9054, 1071, 11, 719, 1202, 25127, 527, 7029, 13, 330, 3947, 527, 10283, 315, 2204, 1343, 1154, 323, 10283, 315, 1023, 28896, 1210, 220, 128257, 198 ]

2,517

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Exploration for shale gas occurs in onshore basins, with two approaches used to predict the maximum gas in place (GIP) in the absence of production data. The first estimates adsorbed plus free gas held within pore space, and the second measures gas yields from laboratory pyrolysis experiments on core samples. Here we show the use of sequential high-pressure water pyrolysis (HPWP) to replicate petroleum generation and expulsion in uplifted onshore basins. Compared to anhydrous pyrolysis where oil expulsion is limited, gas yields are much lower, and the gas at high maturity is dry, consistent with actual shales. Gas yields from HPWP of UK Bowland Shales are comparable with those from degassed cores, with the ca. 1% porosity sufficient to accommodate the gas generated. Extrapolating our findings to the whole Bowland Shale, the maximum GIP equate to potentially economically recoverable reserves of less than 10 years of current UK gas consumption. Introduction Shale gas arises from the cracking of insoluble organic matter in source rocks (kerogen) and any oil retained in the pores 1 , 2 , 3 . Shale gas produced in the USA is generally quite dry with methane contents being typically over 75% 3 , 4 , 5 with shales needing a vitrinite reflectance (VR) maturity of >1.4% Ro to produce dry gas 6 . To guide exploration and development where production has not commenced, it is essential that rigorous methodologies are established to estimate the maximum recoverable reserves. The UK is such a case, with the Carboniferous Bowland-Hodder Shale being the major gas source 7 , 8 , 9 , 10 , 11 . It has been estimated that the gas in place (GIP) for the entire Bowland Shale is large, the Upper and Lower units containing 164–447 and 658–1834 trillion standard cubic feet (TCF), respectively 7 . However, this was based on adsorbed and free gas estimates for US shales, and assumed that all Bowland Shale source rock with a maturity above 1.1% Ro, had already generated gas, contrary to US producing shales (Barnett, Marcellus and Fayetteville) having VR >1.4% Ro 6 . The large UK estimate may also be due to the assumption that all Carboniferous Shales of the Bowland basin are potential shale gas source rocks 7 . Rock-Eval pyrolysis is the standard approach for assessing source rock potential and quality in which volatile hydrocarbons are measured as they evolve 12 , 13 . Although hydrocarbon gases are not measured, an empirical relationship based on the S1 and S2 parameters (free and potential for generated hydrocarbons, respectively) to estimate shale gas yields has been developed 6 . Closed system pyrolysis uses micro-scale sealed-vessels (MSSV) where all volatiles are retained within the system 14 , 15 . The drawback with both techniques is that they do not replicate oil expulsion during maturation. In hydrous pyrolysis, albeit in a closed system, oil generated is expelled into the water phase and is thus not in as close contact with the source rock, so better replicating actual expulsion 16 . However, water and vapour are in equilibrium, with the pressure set by the temperature of the experiment. To better replicate petroleum systems, high pressure water pyrolysis (HPWP), where there is no free vapour space in the reactor can be used to understand source rock maturation, hydrocarbon generation and associated pressure effects 17 , 18 , 19 , 20 . We use sequential HPWP here to predict the maximum GIP using oil window and gas window mature UK Bowland Shales with expelled oil being removed at each stage. Comparisons are drawn firstly with recent reports for degassed core samples 21 , 22 and then the adsorbed plus pore (free) gas estimated for the gas window shale. It must be remembered that some differences between the different studies arise from the samples coming from different locations within the basin with consequent differences in sediment provenance, stratigraphical, structural and tectonic histories of the different parts of the same basin 12 . Moisture equilibration is essential since it affects both the free and adsorbed gas, and vast reductions in the amount of adsorbed methane with increasing humidity have been reported 23 . Further, much of the variation in the reported porosities of shales (1–8%) arises from the extent to which shales are moisture-equilibrated 6 , 24 , 25 . The implications of our findings for the entire Bowland Shale gas resource are considered on the basin and we show that these are actually ~10 times lower than previously thought. Results Gas and oil yields The methane and total hydrocarbon (C 1 –C 5 ) gas yields from the five stages in sequential HPWP for the oil window mature Rempstone shale (0.71% Ro, containing a mixture of types II, III and IV kerogen, Supplementary Table 1 , Supplementary Fig. 1 ) investigated at 800 bar and under anhydrous conditions are presented in Figs. 1a, b , respectively, together with the yields of oil expelled and the heavier oil/bitumen retained in the shale. The full gas compositions, vitrinite reflectance and Rock-Eval pyrolysis results for the matured shale samples from these experiments are listed in Supplementary Table 2 , together with those for experiments at 300 bar. Maturities >2.3% Ro were attained to represent the high maturities of the gas window. Slightly higher Ro values were achieved at 300 bar due to the previously described pressure retardation effect on maturation at higher pressure 20 . Fig. 1 Total hydrocarbon gas (C 1 –C 5 ), methane, expelled oil and retained oil/bitumen yields (mg/g TOC of the rock at the end of each stage) for the Rempstone shale. a Sequential HPWP (800 bar). b Anhydrous experiments. For stages 3–5 in the HPWP experiment, the results are also presented for the sample that was solvent extracted at the end of stage 2. The VR % (Ro) values below each histogram are for the start and end of each stage. The differences in the measured values from duplicate tests are generally within 6% for gas (C 1", "role": "user" }, { "content": "A team of researchers from the University of Nottingham, the British Geological Survey (BGS) and Advanced Geochemical Systems, Ltd, has found evidence that suggests the amount of shale gas available for fracking in the U.K. is much less than previously thought. In their paper published in the journal Nature Communications, the group describes their new technique and what it showed. Just six years ago, the BGS announced that they had found that gas fields beneath the ground in parts of England and Scotland held approximately 1,300tn cubic feet of obtainable shale gas. Since that time, energy firms have instigated fracking projects that have extracted some of that gas. But others have complained that doing so has caused small earthquakes in the areas near the extraction sites. Also, some environmentalists in the country have suggested that relying on fracked gas reduces efforts made to convert the country to more sustainable resources. In this new effort, the researchers have used what they describe as a new technique to estimate the amount of gas under the ground in the U.K. and found it to be much less than what BGS found in 2013. They suggest there is enough there for just seven to 10 years of extraction—not the 50 claimed by researchers with the earlier study. The researchers describe their new technique as based on a study of actual shale deposits using gas absorption data along with field data. They studied shale samples from two locations in the Bowland Shale, and used that to calculate the amount of gas at the entire site. They note that the 2013 study included no field studies—the researchers on the project used data from energy companies. The researchers with the new effort further note that great strides have been made in learning how to measure gas below the surface over the past several years. The lead scientist at BGS, Mike Stephenson, who was not involved in the new effort, suggested to the press that much more study of U.K. gas fields is required to determine the true amount of shale gas. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Exploration for shale gas occurs in onshore basins, with two approaches used to predict the maximum gas in place (GIP) in the absence of production data. The first estimates adsorbed plus free gas held within pore space, and the second measures gas yields from laboratory pyrolysis experiments on core samples. Here we show the use of sequential high-pressure water pyrolysis (HPWP) to replicate petroleum generation and expulsion in uplifted onshore basins. Compared to anhydrous pyrolysis where oil expulsion is limited, gas yields are much lower, and the gas at high maturity is dry, consistent with actual shales. Gas yields from HPWP of UK Bowland Shales are comparable with those from degassed cores, with the ca. 1% porosity sufficient to accommodate the gas generated. Extrapolating our findings to the whole Bowland Shale, the maximum GIP equate to potentially economically recoverable reserves of less than 10 years of current UK gas consumption. Introduction Shale gas arises from the cracking of insoluble organic matter in source rocks (kerogen) and any oil retained in the pores 1 , 2 , 3 . Shale gas produced in the USA is generally quite dry with methane contents being typically over 75% 3 , 4 , 5 with shales needing a vitrinite reflectance (VR) maturity of >1.4% Ro to produce dry gas 6 . To guide exploration and development where production has not commenced, it is essential that rigorous methodologies are established to estimate the maximum recoverable reserves. The UK is such a case, with the Carboniferous Bowland-Hodder Shale being the major gas source 7 , 8 , 9 , 10 , 11 . It has been estimated that the gas in place (GIP) for the entire Bowland Shale is large, the Upper and Lower units containing 164–447 and 658–1834 trillion standard cubic feet (TCF), respectively 7 . However, this was based on adsorbed and free gas estimates for US shales, and assumed that all Bowland Shale source rock with a maturity above 1.1% Ro, had already generated gas, contrary to US producing shales (Barnett, Marcellus and Fayetteville) having VR >1.4% Ro 6 . The large UK estimate may also be due to the assumption that all Carboniferous Shales of the Bowland basin are potential shale gas source rocks 7 . Rock-Eval pyrolysis is the standard approach for assessing source rock potential and quality in which volatile hydrocarbons are measured as they evolve 12 , 13 . Although hydrocarbon gases are not measured, an empirical relationship based on the S1 and S2 parameters (free and potential for generated hydrocarbons, respectively) to estimate shale gas yields has been developed 6 . Closed system pyrolysis uses micro-scale sealed-vessels (MSSV) where all volatiles are retained within the system 14 , 15 . The drawback with both techniques is that they do not replicate oil expulsion during maturation. In hydrous pyrolysis, albeit in a closed system, oil generated is expelled into the water phase and is thus not in as close contact with the source rock, so better replicating actual expulsion 16 . However, water and vapour are in equilibrium, with the pressure set by the temperature of the experiment. To better replicate petroleum systems, high pressure water pyrolysis (HPWP), where there is no free vapour space in the reactor can be used to understand source rock maturation, hydrocarbon generation and associated pressure effects 17 , 18 , 19 , 20 . We use sequential HPWP here to predict the maximum GIP using oil window and gas window mature UK Bowland Shales with expelled oil being removed at each stage. Comparisons are drawn firstly with recent reports for degassed core samples 21 , 22 and then the adsorbed plus pore (free) gas estimated for the gas window shale. It must be remembered that some differences between the different studies arise from the samples coming from different locations within the basin with consequent differences in sediment provenance, stratigraphical, structural and tectonic histories of the different parts of the same basin 12 . Moisture equilibration is essential since it affects both the free and adsorbed gas, and vast reductions in the amount of adsorbed methane with increasing humidity have been reported 23 . Further, much of the variation in the reported porosities of shales (1–8%) arises from the extent to which shales are moisture-equilibrated 6 , 24 , 25 . The implications of our findings for the entire Bowland Shale gas resource are considered on the basin and we show that these are actually ~10 times lower than previously thought. Results Gas and oil yields The methane and total hydrocarbon (C 1 –C 5 ) gas yields from the five stages in sequential HPWP for the oil window mature Rempstone shale (0.71% Ro, containing a mixture of types II, III and IV kerogen, Supplementary Table 1 , Supplementary Fig. 1 ) investigated at 800 bar and under anhydrous conditions are presented in Figs. 1a, b , respectively, together with the yields of oil expelled and the heavier oil/bitumen retained in the shale. The full gas compositions, vitrinite reflectance and Rock-Eval pyrolysis results for the matured shale samples from these experiments are listed in Supplementary Table 2 , together with those for experiments at 300 bar. Maturities >2.3% Ro were attained to represent the high maturities of the gas window. Slightly higher Ro values were achieved at 300 bar due to the previously described pressure retardation effect on maturation at higher pressure 20 . Fig. 1 Total hydrocarbon gas (C 1 –C 5 ), methane, expelled oil and retained oil/bitumen yields (mg/g TOC of the rock at the end of each stage) for the Rempstone shale. a Sequential HPWP (800 bar). b Anhydrous experiments. For stages 3–5 in the HPWP experiment, the results are also presented for the sample that was solvent extracted at the end of stage 2. The VR % (Ro) values below each histogram are for the start and end of each stage. The differences in the measured values from duplicate tests are generally within 6% for gas (C 1<|im_end|> <|im_start|>assistant A team of researchers from the University of Nottingham, the British Geological Survey (BGS) and Advanced Geochemical Systems, Ltd, has found evidence that suggests the amount of shale gas available for fracking in the U.K. is much less than previously thought. In their paper published in the journal Nature Communications, the group describes their new technique and what it showed. Just six years ago, the BGS announced that they had found that gas fields beneath the ground in parts of England and Scotland held approximately 1,300tn cubic feet of obtainable shale gas. Since that time, energy firms have instigated fracking projects that have extracted some of that gas. But others have complained that doing so has caused small earthquakes in the areas near the extraction sites. Also, some environmentalists in the country have suggested that relying on fracked gas reduces efforts made to convert the country to more sustainable resources. In this new effort, the researchers have used what they describe as a new technique to estimate the amount of gas under the ground in the U.K. and found it to be much less than what BGS found in 2013. They suggest there is enough there for just seven to 10 years of extraction—not the 50 claimed by researchers with the earlier study. The researchers describe their new technique as based on a study of actual shale deposits using gas absorption data along with field data. They studied shale samples from two locations in the Bowland Shale, and used that to calculate the amount of gas at the entire site. They note that the 2013 study included no field studies—the researchers on the project used data from energy companies. The researchers with the new effort further note that great strides have been made in learning how to measure gas below the surface over the past several years. The lead scientist at BGS, Mike Stephenson, who was not involved in the new effort, suggested to the press that much more study of U.K. gas fields is required to determine the true amount of shale gas. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 76022, 369, 75105, 6962, 13980, 304, 389, 29526, 3122, 1354, 11, 449, 1403, 20414, 1511, 311, 7168, 279, 7340, 6962, 304, 2035, 320, 38, 3378, 8, 304, 279, 19821, 315, 5788, 828, 13, 578, 1176, 17989, 14058, 269, 2788, 5636, 1949, 6962, 5762, 2949, 97551, 3634, 11, 323, 279, 2132, 11193, 6962, 36508, 505, 27692, 4611, 299, 398, 14744, 21896, 389, 6332, 10688, 13, 5810, 584, 1501, 279, 1005, 315, 52100, 1579, 89561, 3090, 4611, 299, 398, 14744, 320, 6748, 26758, 8, 311, 46113, 60063, 9659, 323, 95989, 304, 97547, 291, 389, 29526, 3122, 1354, 13, 59813, 311, 459, 8671, 67, 27620, 4611, 299, 398, 14744, 1405, 5707, 95989, 374, 7347, 11, 6962, 36508, 527, 1790, 4827, 11, 323, 279, 6962, 520, 1579, 48261, 374, 9235, 11, 13263, 449, 5150, 559, 3916, 13, 21523, 36508, 505, 12478, 26758, 315, 6560, 18943, 1974, 1443, 3916, 527, 30139, 449, 1884, 505, 5367, 60104, 36804, 11, 449, 279, 2211, 13, 220, 16, 4, 4247, 22828, 14343, 311, 29376, 279, 6962, 8066, 13, 72334, 17070, 1113, 1057, 14955, 311, 279, 4459, 18943, 1974, 1443, 1604, 11, 279, 7340, 480, 3378, 3312, 349, 311, 13893, 47379, 11993, 481, 30600, 315, 2753, 1109, 220, 605, 1667, 315, 1510, 6560, 6962, 15652, 13, 29438, 1443, 1604, 6962, 48282, 505, 279, 52829, 315, 85943, 41572, 17808, 5030, 304, 2592, 23902, 320, 7197, 11968, 8, 323, 904, 5707, 35363, 304, 279, 72028, 220, 16, 1174, 220, 17, 1174, 220, 18, 662, 1443, 1604, 6962, 9124, 304, 279, 7427, 374, 8965, 5115, 9235, 449, 61083, 8970, 1694, 11383, 927, 220, 2075, 4, 220, 18, 1174, 220, 19, 1174, 220, 20, 449, 559, 3916, 33921, 264, 13458, 81, 16235, 8881, 685, 320, 19330, 8, 48261, 315, 871, 16, 13, 19, 4, 12093, 311, 8356, 9235, 6962, 220, 21, 662, 2057, 8641, 27501, 323, 4500, 1405, 5788, 706, 539, 65362, 11, 433, 374, 7718, 430, 47999, 81898, 527, 9749, 311, 16430, 279, 7340, 11993, 481, 30600, 13, 578, 6560, 374, 1778, 264, 1162, 11, 449, 279, 22208, 11691, 788, 18943, 1974, 11529, 347, 1126, 1443, 1604, 1694, 279, 3682, 6962, 2592, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 662, 1102, 706, 1027, 13240, 430, 279, 6962, 304, 2035, 320, 38, 3378, 8, 369, 279, 4553, 18943, 1974, 1443, 1604, 374, 3544, 11, 279, 31714, 323, 28636, 8316, 8649, 220, 10513, 4235, 20800, 323, 220, 23654, 4235, 10750, 19, 32610, 5410, 41999, 7693, 320, 7905, 37, 705, 15947, 220, 22, 662, 4452, 11, 420, 574, 3196, 389, 14058, 269, 2788, 323, 1949, 6962, 17989, 369, 2326, 559, 3916, 11, 323, 19655, 430, 682, 18943, 1974, 1443, 1604, 2592, 7091, 449, 264, 48261, 3485, 220, 16, 13, 16, 4, 12093, 11, 1047, 2736, 8066, 6962, 11, 26102, 311, 2326, 17843, 559, 3916, 320, 33, 1923, 7211, 11, 2947, 5997, 355, 323, 99915, 8078, 8, 3515, 19718, 871, 16, 13, 19, 4, 12093, 220, 21, 662, 578, 3544, 6560, 16430, 1253, 1101, 387, 4245, 311, 279, 25329, 430, 682, 22208, 11691, 788, 1443, 3916, 315, 279, 18943, 1974, 58309, 527, 4754, 75105, 6962, 2592, 23902, 220, 22, 662, 9305, 13737, 838, 4611, 299, 398, 14744, 374, 279, 5410, 5603, 369, 47614, 2592, 7091, 4754, 323, 4367, 304, 902, 17509, 17055, 7063, 47620, 527, 17303, 439, 814, 38680, 220, 717, 1174, 220, 1032, 662, 10541, 17055, 74441, 45612, 527, 539, 17303, 11, 459, 46763, 5133, 3196, 389, 279, 328, 16, 323, 328, 17, 5137, 320, 10816, 323, 4754, 369, 8066, 17055, 7063, 47620, 11, 15947, 8, 311, 16430, 75105, 6962, 36508, 706, 1027, 8040, 220, 21, 662, 45779, 1887, 4611, 299, 398, 14744, 5829, 8162, 13230, 19584, 8437, 434, 2053, 320, 44, 1242, 53, 8, 1405, 682, 4499, 266, 3742, 527, 35363, 2949, 279, 1887, 220, 975, 1174, 220, 868, 662, 578, 88620, 449, 2225, 12823, 374, 430, 814, 656, 539, 46113, 5707, 95989, 2391, 5634, 2060, 13, 763, 6409, 67, 27620, 4611, 299, 398, 14744, 11, 43169, 304, 264, 8036, 1887, 11, 5707, 8066, 374, 67331, 1139, 279, 3090, 10474, 323, 374, 8617, 539, 304, 439, 3345, 3729, 449, 279, 2592, 7091, 11, 779, 2731, 29641, 1113, 5150, 95989, 220, 845, 662, 4452, 11, 3090, 323, 68857, 414, 527, 304, 56411, 11, 449, 279, 7410, 743, 555, 279, 9499, 315, 279, 9526, 13, 2057, 2731, 46113, 60063, 6067, 11, 1579, 7410, 3090, 4611, 299, 398, 14744, 320, 6748, 26758, 705, 1405, 1070, 374, 912, 1949, 68857, 414, 3634, 304, 279, 38729, 649, 387, 1511, 311, 3619, 2592, 7091, 5634, 2060, 11, 17055, 74441, 9659, 323, 5938, 7410, 6372, 220, 1114, 1174, 220, 972, 1174, 220, 777, 1174, 220, 508, 662, 1226, 1005, 52100, 12478, 26758, 1618, 311, 7168, 279, 7340, 480, 3378, 1701, 5707, 3321, 323, 6962, 3321, 15196, 6560, 18943, 1974, 1443, 3916, 449, 67331, 5707, 1694, 7108, 520, 1855, 6566, 13, 23611, 19941, 527, 15107, 95052, 449, 3293, 6821, 369, 5367, 60104, 6332, 10688, 220, 1691, 1174, 220, 1313, 323, 1243, 279, 14058, 269, 2788, 5636, 97551, 320, 10816, 8, 6962, 13240, 369, 279, 6962, 3321, 75105, 13, 1102, 2011, 387, 27569, 430, 1063, 12062, 1990, 279, 2204, 7978, 31889, 505, 279, 10688, 5108, 505, 2204, 10687, 2949, 279, 58309, 449, 12777, 306, 12062, 304, 59132, 17033, 685, 11, 44397, 54967, 950, 11, 24693, 323, 259, 440, 14338, 53210, 315, 279, 2204, 5596, 315, 279, 1890, 58309, 220, 717, 662, 82804, 554, 3312, 321, 18856, 374, 7718, 2533, 433, 22223, 2225, 279, 1949, 323, 14058, 269, 2788, 6962, 11, 323, 13057, 47311, 304, 279, 3392, 315, 14058, 269, 2788, 61083, 449, 7859, 38193, 617, 1027, 5068, 220, 1419, 662, 15903, 11, 1790, 315, 279, 23851, 304, 279, 5068, 4247, 437, 1385, 315, 559, 3916, 320, 16, 4235, 23, 11587, 48282, 505, 279, 13112, 311, 902, 559, 3916, 527, 32257, 63359, 321, 61666, 220, 21, 1174, 220, 1187, 1174, 220, 914, 662, 578, 25127, 315, 1057, 14955, 369, 279, 4553, 18943, 1974, 1443, 1604, 6962, 5211, 527, 6646, 389, 279, 58309, 323, 584, 1501, 430, 1521, 527, 3604, 4056, 605, 3115, 4827, 1109, 8767, 3463, 13, 18591, 21523, 323, 5707, 36508, 578, 61083, 323, 2860, 17055, 74441, 320, 34, 220, 16, 1389, 34, 220, 20, 883, 6962, 36508, 505, 279, 4330, 18094, 304, 52100, 12478, 26758, 369, 279, 5707, 3321, 15196, 432, 3342, 11046, 75105, 320, 15, 13, 6028, 4, 12093, 11, 8649, 264, 21655, 315, 4595, 8105, 11, 14767, 323, 17244, 34801, 11968, 11, 99371, 6771, 220, 16, 1174, 99371, 23966, 13, 220, 16, 883, 27313, 520, 220, 4728, 3703, 323, 1234, 459, 8671, 67, 27620, 4787, 527, 10666, 304, 435, 14801, 13, 220, 16, 64, 11, 293, 1174, 15947, 11, 3871, 449, 279, 36508, 315, 5707, 67331, 323, 279, 44922, 5707, 87744, 28999, 35363, 304, 279, 75105, 13, 578, 2539, 6962, 62644, 11, 13458, 81, 16235, 8881, 685, 323, 9305, 13737, 838, 4611, 299, 398, 14744, 3135, 369, 279, 15196, 67, 75105, 10688, 505, 1521, 21896, 527, 10212, 304, 99371, 6771, 220, 17, 1174, 3871, 449, 1884, 369, 21896, 520, 220, 3101, 3703, 13, 386, 2693, 1385, 871, 17, 13, 18, 4, 12093, 1051, 63260, 311, 4097, 279, 1579, 296, 2693, 1385, 315, 279, 6962, 3321, 13, 328, 80598, 5190, 12093, 2819, 1051, 17427, 520, 220, 3101, 3703, 4245, 311, 279, 8767, 7633, 7410, 77072, 367, 2515, 389, 5634, 2060, 520, 5190, 7410, 220, 508, 662, 23966, 13, 220, 16, 10884, 17055, 74441, 6962, 320, 34, 220, 16, 1389, 34, 220, 20, 7026, 61083, 11, 67331, 5707, 323, 35363, 5707, 87744, 28999, 36508, 320, 12591, 4951, 5257, 34, 315, 279, 7091, 520, 279, 842, 315, 1855, 6566, 8, 369, 279, 432, 3342, 11046, 75105, 13, 264, 60109, 12478, 26758, 320, 4728, 3703, 570, 293, 1556, 8671, 67, 27620, 21896, 13, 1789, 18094, 220, 18, 4235, 20, 304, 279, 12478, 26758, 9526, 11, 279, 3135, 527, 1101, 10666, 369, 279, 6205, 430, 574, 69996, 28532, 520, 279, 842, 315, 6566, 220, 17, 13, 578, 19718, 1034, 320, 39972, 8, 2819, 3770, 1855, 31381, 527, 369, 279, 1212, 323, 842, 315, 1855, 6566, 13, 578, 12062, 304, 279, 17303, 2819, 505, 23329, 7177, 527, 8965, 2949, 220, 21, 4, 369, 6962, 320, 34, 220, 16, 128257, 198, 128256, 78191, 198, 32, 2128, 315, 12074, 505, 279, 3907, 315, 67659, 11, 279, 8013, 80850, 24507, 320, 33, 16929, 8, 323, 21844, 33010, 32056, 15264, 11, 12604, 11, 706, 1766, 6029, 430, 13533, 279, 3392, 315, 75105, 6962, 2561, 369, 71154, 304, 279, 549, 11606, 13, 374, 1790, 2753, 1109, 8767, 3463, 13, 763, 872, 5684, 4756, 304, 279, 8486, 22037, 26545, 11, 279, 1912, 16964, 872, 502, 15105, 323, 1148, 433, 8710, 13, 4702, 4848, 1667, 4227, 11, 279, 426, 16929, 7376, 430, 814, 1047, 1766, 430, 6962, 5151, 24923, 279, 5015, 304, 5596, 315, 9635, 323, 19627, 5762, 13489, 220, 16, 11, 3101, 1546, 41999, 7693, 315, 6994, 481, 75105, 6962, 13, 8876, 430, 892, 11, 4907, 19339, 617, 1798, 83341, 71154, 7224, 430, 617, 28532, 1063, 315, 430, 6962, 13, 2030, 3885, 617, 35070, 430, 3815, 779, 706, 9057, 2678, 66579, 304, 279, 5789, 3221, 279, 33289, 6732, 13, 7429, 11, 1063, 12434, 1705, 304, 279, 3224, 617, 12090, 430, 39661, 389, 1448, 11440, 6962, 26338, 9045, 1903, 311, 5625, 279, 3224, 311, 810, 22556, 5070, 13, 763, 420, 502, 5149, 11, 279, 12074, 617, 1511, 1148, 814, 7664, 439, 264, 502, 15105, 311, 16430, 279, 3392, 315, 6962, 1234, 279, 5015, 304, 279, 549, 11606, 13, 323, 1766, 433, 311, 387, 1790, 2753, 1109, 1148, 426, 16929, 1766, 304, 220, 679, 18, 13, 2435, 4284, 1070, 374, 3403, 1070, 369, 1120, 8254, 311, 220, 605, 1667, 315, 33289, 63938, 279, 220, 1135, 11922, 555, 12074, 449, 279, 6931, 4007, 13, 578, 12074, 7664, 872, 502, 15105, 439, 3196, 389, 264, 4007, 315, 5150, 75105, 34751, 1701, 6962, 44225, 828, 3235, 449, 2115, 828, 13, 2435, 20041, 75105, 10688, 505, 1403, 10687, 304, 279, 18943, 1974, 1443, 1604, 11, 323, 1511, 430, 311, 11294, 279, 3392, 315, 6962, 520, 279, 4553, 2816, 13, 2435, 5296, 430, 279, 220, 679, 18, 4007, 5343, 912, 2115, 7978, 22416, 12074, 389, 279, 2447, 1511, 828, 505, 4907, 5220, 13, 578, 12074, 449, 279, 502, 5149, 4726, 5296, 430, 2294, 37387, 617, 1027, 1903, 304, 6975, 1268, 311, 6767, 6962, 3770, 279, 7479, 927, 279, 3347, 3892, 1667, 13, 578, 3063, 28568, 520, 426, 16929, 11, 11519, 41659, 34237, 11, 889, 574, 539, 6532, 304, 279, 502, 5149, 11, 12090, 311, 279, 3577, 430, 1790, 810, 4007, 315, 549, 11606, 13, 6962, 5151, 374, 2631, 311, 8417, 279, 837, 3392, 315, 75105, 6962, 13, 220, 128257, 198 ]

1,801

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract A wide range of molecular devices with nanoscale dimensions have been recently designed to perform a variety of functions in response to specific molecular inputs. Only limited examples, however, utilize antibodies as regulatory inputs. In response to this, here we report the rational design of a modular DNA-based nanomachine that can reversibly load and release a molecular cargo on binding to a specific antibody. We show here that, by using three different antigens (including one relevant to HIV), it is possible to design different DNA nanomachines regulated by their targeting antibody in a rapid, versatile and highly specific manner. The antibody-powered DNA nanomachines we have developed here may thus be useful in applications like controlled drug-release, point-of-care diagnostics and in vivo imaging. Introduction One of the most exciting research paths in the field of nanotechnology and supramolecular chemistry is aimed at rationally designing and developing responsive molecular machines that, like naturally occurring proteins, can perform a specific function in response to a certain molecular input 1 , 2 , 3 , 4 , 5 . Several supramolecular nanodevices of increasing chemical complexity have been described in the recent years for applications ranging from controlled release of a therapeutic cargo 6 , signal transduction 7 , 8 and sensing 9 . With its highly predictable base-pairings, its low cost, ease of synthesis and biocompatibility, DNA has become the material of choice to design and engineer nanomechanical devices and machines that display specific structures and functions 10 , 11 , 12 , 13 , 14 . A wide range of DNA-based nanodevices have been reported that, in response to a specific molecular cue, can give a signal, release a cargo or perform a directional motion 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 . Despite their impressive performances, a limitation affects these DNA-based nanodevices: their activity, in fact, is usually triggered by a quite restricted class of molecular cues and inputs. These inputs range from environmental stimuli (like pH or temperature) 23 , 24 to chemical inputs that, in the majority of cases, are limited to DNA strands or, more seldom, to small molecules and proteins 25 , 26 , 27 . Several DNA-based sensors, able to signal the presence of a specific antibody, have been reported to date 28 , 29 , 30 . However, the demonstration of DNA nanomachines performing more complex functions (such as, for example, drug-release) and employing antibodies as regulatory inputs has witnessed only limited efforts 31 , 32 . Thus motivated, here we report an antibody-powered DNA-based nanomachine that can reversibly load and release a molecular cargo on binding to a specific antibody. Our strategy takes inspiration from transport proteins, highly evolved machines that are essential to the crucial mechanism of cell transport 33 , 34 . These proteins can load and release a specific molecular cargo through a conformational change mechanism that can be regulated by different inputs 35 . By mimicking this mechanism we designed a DNA-based nanomachine that is able to load a DNA strand in a highly specific and stable fashion and release it only in the presence of a specific antibody. Results Design of an antibody-powered DNA nanomachine Our strategy to rationally design an antibody-driven DNA-based nanomachine takes advantage of triplex forming DNA sequences that are designed to recognize a specific DNA strand (blue in Fig. 1 ) through the formation of a clamp-like structure that involves both Watson–Crick (–) and Hoogsteen (·) interactions ( Fig. 1 ) 36 . This clamp-like structure is conjugated at the two ends with a pair of antigens. Antibody binding to the two antigens on the nanomachine causes a conformational change that induces the triplex-complex opening (see for analogy antibody triggered stem-loop opening) 28 and energetically disrupts the less stable triplex-forming Hoogsteen interactions (·) thus destabilizing the nanomachine/cargo complex. As the Watson–Crick interactions in such complex are not strong enough to retain the cargo, this latter is released from the nanomachine ( Fig. 1 ). Figure 1: Working principle of antibody-powered DNA-based nanomachine. A DNA strand (black) labelled with two antigens (green hexagons) can load a nucleic acid strand (blue) through a clamp-like triplex-forming mechanism. The binding of a bivalent macromolecule (here an antibody) to the two antigens causes a conformational change that reduces the stability of the triplex complex with the consequent release of the loaded strand. Full size image Selection of DNA cargo strand Instrumental for our strategy, to observe the antibody-induced DNA cargo release, is the need to find an optimal thermodynamic trade-off that requires to meet the following main conditions. First, a strong difference in stability between the triplex conformation (containing both Watson–Crick and Hoogsteen interactions) and a simple duplex conformation (only Watson–Crick base-pairings). Second, the duplex conformation, under the chosen experimental conditions (for example, temperature and concentration range), should be unstable enough to allow release of the cargo. Finally, the triplex conformation should not be too stable so that bidentate binding to the nanomachine by the antibody would be allowed. To achieve this, we have studied DNA cargos of different length (thus leading to complexes of different stabilities) and tested them with a triplex-forming DNA nanomachine (involving both Watson–Crick and Hoogsteen interactions) and a control DNA nanomachine lacking the triplex forming portion ( Fig. 2a ). As expected 36 , because of the additional Hoogsteen interactions, for all cargos tested the triplex-forming DNA nanomachine shows a higher affinity (and thus stability) compared to the control nanomachine able to only form a duplex complex ( Fig. 2b–e ). We find that a 12-nt DNA cargo leads to the strongest difference in affinity between triplex and duplex formation under our experimental conditions ( Fig. 2f,g ). Using this DNA cargo we show that, while the complex formed with the triplex-forming nanomachine is stable at temperatures below 50 °C ( T m =52.1±0.5 °C), the complex obtained with the control nanomachine (only duplex) is partially unstable at room temperature and leads to an almost complete", "role": "user" }, { "content": "An international team of researchers from the University of Rome Tor Vergata and the University of Montreal has reported, in a paper published this week in Nature Communications, the design and synthesis of a nanoscale molecular slingshot made of DNA that is 20,000 times smaller than a human hair. This molecular slingshot could \"shoot\" and deliver drugs at precise locations in the human body once triggered by specific disease markers. The molecular slingshot is only a few nanometres long and is composed of a synthetic DNA strand that can load a drug and then effectively act as the rubber band of the slingshot. The two ends of this DNA \"rubber band\" contain two anchoring moieties that can specifically stick to a target antibody, a Y-shaped protein expressed by the body in response to different pathogens such as bacteria and viruses. When the anchoring moieties of the slingshot recognize and bind to the arms of the target antibody the DNA \"rubber band\" is stretched and the loaded drug is released. \"One impressive feature about this molecular slingshot,\" says Francesco Ricci, Associate Professor of Chemistry at the University of Rome Tor Vergata, \"is that it can only be triggered by the specific antibody recognizing the anchoring tags of the DNA 'rubber band'. By simply changing these tags, one can thus program the slingshot to release a drug in response to a variety of specific antibodies. Since different antibodies are markers of different diseases, this could become a very specific weapon in the clinician's hands.\" \"Another great property of our slingshot,\" adds Alexis Vallée-Bélisle, Assistant Professor in the Department of Chemistry at the University of Montreal, \"is its high versatility. For example, until now we have demonstrated the working principle of the slingshot using three different trigger antibodies, including an HIV antibody, and employing nucleic acids as model drugs. But thanks to the high programmability of DNA chemistry, one can now design the DNA slingshot to 'shoot' a wide range of threrapeutic molecules.\" \"Designing this molecular slingshot was a great challenge,\" says Simona Ranallo, a postdoctoral researcher in Ricci's team and principal author of the new study. \"It required a long series of experiments to find the optimal design, which keeps the drug loaded in 'rubber band' in the absence of the antibody, without affecting too much its shooting efficiency once the antibody triggers the slingshot.\" The group of researchers is now eager to adapt the slingshot for the delivery of clinically relevant drugs, and to demonstrate its clinical efficiency. \"We envision that similar molecular slingshots may be used in the near future to deliver drugs to specific locations in the body. This would drastically improve the efficiency of drugs as well as decrease their toxic secondary effects,\" concludes Ricci. The next step in the project is to target a specific disease and drug for which the therapeutic slingshot can be adapted for testing on cells in vitro, prior to testing in mice. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract A wide range of molecular devices with nanoscale dimensions have been recently designed to perform a variety of functions in response to specific molecular inputs. Only limited examples, however, utilize antibodies as regulatory inputs. In response to this, here we report the rational design of a modular DNA-based nanomachine that can reversibly load and release a molecular cargo on binding to a specific antibody. We show here that, by using three different antigens (including one relevant to HIV), it is possible to design different DNA nanomachines regulated by their targeting antibody in a rapid, versatile and highly specific manner. The antibody-powered DNA nanomachines we have developed here may thus be useful in applications like controlled drug-release, point-of-care diagnostics and in vivo imaging. Introduction One of the most exciting research paths in the field of nanotechnology and supramolecular chemistry is aimed at rationally designing and developing responsive molecular machines that, like naturally occurring proteins, can perform a specific function in response to a certain molecular input 1 , 2 , 3 , 4 , 5 . Several supramolecular nanodevices of increasing chemical complexity have been described in the recent years for applications ranging from controlled release of a therapeutic cargo 6 , signal transduction 7 , 8 and sensing 9 . With its highly predictable base-pairings, its low cost, ease of synthesis and biocompatibility, DNA has become the material of choice to design and engineer nanomechanical devices and machines that display specific structures and functions 10 , 11 , 12 , 13 , 14 . A wide range of DNA-based nanodevices have been reported that, in response to a specific molecular cue, can give a signal, release a cargo or perform a directional motion 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 . Despite their impressive performances, a limitation affects these DNA-based nanodevices: their activity, in fact, is usually triggered by a quite restricted class of molecular cues and inputs. These inputs range from environmental stimuli (like pH or temperature) 23 , 24 to chemical inputs that, in the majority of cases, are limited to DNA strands or, more seldom, to small molecules and proteins 25 , 26 , 27 . Several DNA-based sensors, able to signal the presence of a specific antibody, have been reported to date 28 , 29 , 30 . However, the demonstration of DNA nanomachines performing more complex functions (such as, for example, drug-release) and employing antibodies as regulatory inputs has witnessed only limited efforts 31 , 32 . Thus motivated, here we report an antibody-powered DNA-based nanomachine that can reversibly load and release a molecular cargo on binding to a specific antibody. Our strategy takes inspiration from transport proteins, highly evolved machines that are essential to the crucial mechanism of cell transport 33 , 34 . These proteins can load and release a specific molecular cargo through a conformational change mechanism that can be regulated by different inputs 35 . By mimicking this mechanism we designed a DNA-based nanomachine that is able to load a DNA strand in a highly specific and stable fashion and release it only in the presence of a specific antibody. Results Design of an antibody-powered DNA nanomachine Our strategy to rationally design an antibody-driven DNA-based nanomachine takes advantage of triplex forming DNA sequences that are designed to recognize a specific DNA strand (blue in Fig. 1 ) through the formation of a clamp-like structure that involves both Watson–Crick (–) and Hoogsteen (·) interactions ( Fig. 1 ) 36 . This clamp-like structure is conjugated at the two ends with a pair of antigens. Antibody binding to the two antigens on the nanomachine causes a conformational change that induces the triplex-complex opening (see for analogy antibody triggered stem-loop opening) 28 and energetically disrupts the less stable triplex-forming Hoogsteen interactions (·) thus destabilizing the nanomachine/cargo complex. As the Watson–Crick interactions in such complex are not strong enough to retain the cargo, this latter is released from the nanomachine ( Fig. 1 ). Figure 1: Working principle of antibody-powered DNA-based nanomachine. A DNA strand (black) labelled with two antigens (green hexagons) can load a nucleic acid strand (blue) through a clamp-like triplex-forming mechanism. The binding of a bivalent macromolecule (here an antibody) to the two antigens causes a conformational change that reduces the stability of the triplex complex with the consequent release of the loaded strand. Full size image Selection of DNA cargo strand Instrumental for our strategy, to observe the antibody-induced DNA cargo release, is the need to find an optimal thermodynamic trade-off that requires to meet the following main conditions. First, a strong difference in stability between the triplex conformation (containing both Watson–Crick and Hoogsteen interactions) and a simple duplex conformation (only Watson–Crick base-pairings). Second, the duplex conformation, under the chosen experimental conditions (for example, temperature and concentration range), should be unstable enough to allow release of the cargo. Finally, the triplex conformation should not be too stable so that bidentate binding to the nanomachine by the antibody would be allowed. To achieve this, we have studied DNA cargos of different length (thus leading to complexes of different stabilities) and tested them with a triplex-forming DNA nanomachine (involving both Watson–Crick and Hoogsteen interactions) and a control DNA nanomachine lacking the triplex forming portion ( Fig. 2a ). As expected 36 , because of the additional Hoogsteen interactions, for all cargos tested the triplex-forming DNA nanomachine shows a higher affinity (and thus stability) compared to the control nanomachine able to only form a duplex complex ( Fig. 2b–e ). We find that a 12-nt DNA cargo leads to the strongest difference in affinity between triplex and duplex formation under our experimental conditions ( Fig. 2f,g ). Using this DNA cargo we show that, while the complex formed with the triplex-forming nanomachine is stable at temperatures below 50 °C ( T m =52.1±0.5 °C), the complex obtained with the control nanomachine (only duplex) is partially unstable at room temperature and leads to an almost complete<|im_end|> <|im_start|>assistant An international team of researchers from the University of Rome Tor Vergata and the University of Montreal has reported, in a paper published this week in Nature Communications, the design and synthesis of a nanoscale molecular slingshot made of DNA that is 20,000 times smaller than a human hair. This molecular slingshot could "shoot" and deliver drugs at precise locations in the human body once triggered by specific disease markers. The molecular slingshot is only a few nanometres long and is composed of a synthetic DNA strand that can load a drug and then effectively act as the rubber band of the slingshot. The two ends of this DNA "rubber band" contain two anchoring moieties that can specifically stick to a target antibody, a Y-shaped protein expressed by the body in response to different pathogens such as bacteria and viruses. When the anchoring moieties of the slingshot recognize and bind to the arms of the target antibody the DNA "rubber band" is stretched and the loaded drug is released. "One impressive feature about this molecular slingshot," says Francesco Ricci, Associate Professor of Chemistry at the University of Rome Tor Vergata, "is that it can only be triggered by the specific antibody recognizing the anchoring tags of the DNA 'rubber band'. By simply changing these tags, one can thus program the slingshot to release a drug in response to a variety of specific antibodies. Since different antibodies are markers of different diseases, this could become a very specific weapon in the clinician's hands." "Another great property of our slingshot," adds Alexis Vallée-Bélisle, Assistant Professor in the Department of Chemistry at the University of Montreal, "is its high versatility. For example, until now we have demonstrated the working principle of the slingshot using three different trigger antibodies, including an HIV antibody, and employing nucleic acids as model drugs. But thanks to the high programmability of DNA chemistry, one can now design the DNA slingshot to 'shoot' a wide range of threrapeutic molecules." "Designing this molecular slingshot was a great challenge," says Simona Ranallo, a postdoctoral researcher in Ricci's team and principal author of the new study. "It required a long series of experiments to find the optimal design, which keeps the drug loaded in 'rubber band' in the absence of the antibody, without affecting too much its shooting efficiency once the antibody triggers the slingshot." The group of researchers is now eager to adapt the slingshot for the delivery of clinically relevant drugs, and to demonstrate its clinical efficiency. "We envision that similar molecular slingshots may be used in the near future to deliver drugs to specific locations in the body. This would drastically improve the efficiency of drugs as well as decrease their toxic secondary effects," concludes Ricci. The next step in the project is to target a specific disease and drug for which the therapeutic slingshot can be adapted for testing on cells in vitro, prior to testing in mice. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 362, 7029, 2134, 315, 31206, 7766, 449, 20622, 437, 2296, 15696, 617, 1027, 6051, 6319, 311, 2804, 264, 8205, 315, 5865, 304, 2077, 311, 3230, 31206, 11374, 13, 8442, 7347, 10507, 11, 4869, 11, 29166, 59854, 439, 23331, 11374, 13, 763, 2077, 311, 420, 11, 1618, 584, 1934, 279, 25442, 2955, 315, 264, 44993, 15922, 6108, 20622, 316, 3899, 430, 649, 17888, 6623, 2865, 323, 4984, 264, 31206, 26735, 389, 11212, 311, 264, 3230, 63052, 13, 1226, 1501, 1618, 430, 11, 555, 1701, 2380, 2204, 68937, 729, 320, 16564, 832, 9959, 311, 23495, 705, 433, 374, 3284, 311, 2955, 2204, 15922, 20622, 316, 71242, 35319, 555, 872, 25103, 63052, 304, 264, 11295, 11, 33045, 323, 7701, 3230, 11827, 13, 578, 63052, 41503, 15922, 20622, 316, 71242, 584, 617, 8040, 1618, 1253, 8617, 387, 5505, 304, 8522, 1093, 14400, 5623, 45824, 11, 1486, 8838, 41206, 50518, 323, 304, 41294, 32758, 13, 29438, 3861, 315, 279, 1455, 13548, 3495, 13006, 304, 279, 2115, 315, 20622, 52536, 323, 1043, 2453, 43943, 30903, 374, 20034, 520, 436, 30154, 30829, 323, 11469, 27078, 31206, 12933, 430, 11, 1093, 18182, 31965, 28896, 11, 649, 2804, 264, 3230, 734, 304, 2077, 311, 264, 3738, 31206, 1988, 220, 16, 1174, 220, 17, 1174, 220, 18, 1174, 220, 19, 1174, 220, 20, 662, 26778, 1043, 2453, 43943, 20622, 536, 85, 1238, 315, 7859, 11742, 23965, 617, 1027, 7633, 304, 279, 3293, 1667, 369, 8522, 24950, 505, 14400, 4984, 315, 264, 37471, 26735, 220, 21, 1174, 8450, 1380, 23985, 220, 22, 1174, 220, 23, 323, 60199, 220, 24, 662, 3161, 1202, 7701, 45207, 2385, 2320, 1334, 826, 11, 1202, 3428, 2853, 11, 14553, 315, 39975, 323, 6160, 12255, 54153, 11, 15922, 706, 3719, 279, 3769, 315, 5873, 311, 2955, 323, 24490, 20622, 638, 5776, 950, 7766, 323, 12933, 430, 3113, 3230, 14726, 323, 5865, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 662, 362, 7029, 2134, 315, 15922, 6108, 20622, 536, 85, 1238, 617, 1027, 5068, 430, 11, 304, 2077, 311, 264, 3230, 31206, 50498, 11, 649, 3041, 264, 8450, 11, 4984, 264, 26735, 477, 2804, 264, 73945, 11633, 220, 868, 1174, 220, 845, 1174, 220, 1114, 1174, 220, 972, 1174, 220, 777, 1174, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 662, 18185, 872, 16358, 24601, 11, 264, 20893, 22223, 1521, 15922, 6108, 20622, 536, 85, 1238, 25, 872, 5820, 11, 304, 2144, 11, 374, 6118, 22900, 555, 264, 5115, 22486, 538, 315, 31206, 57016, 323, 11374, 13, 4314, 11374, 2134, 505, 12434, 56688, 320, 4908, 37143, 477, 9499, 8, 220, 1419, 1174, 220, 1187, 311, 11742, 11374, 430, 11, 304, 279, 8857, 315, 5157, 11, 527, 7347, 311, 15922, 69864, 477, 11, 810, 56452, 11, 311, 2678, 35715, 323, 28896, 220, 914, 1174, 220, 1627, 1174, 220, 1544, 662, 26778, 15922, 6108, 26148, 11, 3025, 311, 8450, 279, 9546, 315, 264, 3230, 63052, 11, 617, 1027, 5068, 311, 2457, 220, 1591, 1174, 220, 1682, 1174, 220, 966, 662, 4452, 11, 279, 30816, 315, 15922, 20622, 316, 71242, 16785, 810, 6485, 5865, 320, 21470, 439, 11, 369, 3187, 11, 5623, 45824, 8, 323, 51297, 59854, 439, 23331, 11374, 706, 32126, 1193, 7347, 9045, 220, 2148, 1174, 220, 843, 662, 14636, 27762, 11, 1618, 584, 1934, 459, 63052, 41503, 15922, 6108, 20622, 316, 3899, 430, 649, 17888, 6623, 2865, 323, 4984, 264, 31206, 26735, 389, 11212, 311, 264, 3230, 63052, 13, 5751, 8446, 5097, 20343, 505, 7710, 28896, 11, 7701, 28995, 12933, 430, 527, 7718, 311, 279, 16996, 17383, 315, 2849, 7710, 220, 1644, 1174, 220, 1958, 662, 4314, 28896, 649, 2865, 323, 4984, 264, 3230, 31206, 26735, 1555, 264, 390, 1659, 278, 2349, 17383, 430, 649, 387, 35319, 555, 2204, 11374, 220, 1758, 662, 3296, 28003, 16671, 420, 17383, 584, 6319, 264, 15922, 6108, 20622, 316, 3899, 430, 374, 3025, 311, 2865, 264, 15922, 42589, 304, 264, 7701, 3230, 323, 15528, 11401, 323, 4984, 433, 1193, 304, 279, 9546, 315, 264, 3230, 63052, 13, 18591, 7127, 315, 459, 63052, 41503, 15922, 20622, 316, 3899, 5751, 8446, 311, 436, 30154, 2955, 459, 63052, 32505, 15922, 6108, 20622, 316, 3899, 5097, 9610, 315, 2463, 9289, 30164, 15922, 24630, 430, 527, 6319, 311, 15641, 264, 3230, 15922, 42589, 320, 12481, 304, 23966, 13, 220, 16, 883, 1555, 279, 18488, 315, 264, 43004, 12970, 6070, 430, 18065, 2225, 32580, 4235, 34, 12938, 320, 4235, 8, 323, 17723, 540, 95057, 320, 14260, 8, 22639, 320, 23966, 13, 220, 16, 883, 220, 1927, 662, 1115, 43004, 12970, 6070, 374, 64380, 660, 520, 279, 1403, 10548, 449, 264, 6857, 315, 68937, 729, 13, 95951, 1094, 11212, 311, 279, 1403, 68937, 729, 389, 279, 20622, 316, 3899, 11384, 264, 390, 1659, 278, 2349, 430, 90974, 279, 2463, 9289, 11733, 9289, 8736, 320, 4151, 369, 56203, 63052, 22900, 19646, 61766, 8736, 8, 220, 1591, 323, 38556, 456, 2740, 24927, 82, 279, 2753, 15528, 2463, 9289, 8627, 287, 17723, 540, 95057, 22639, 320, 14260, 8, 8617, 72257, 4954, 279, 20622, 316, 3899, 2971, 12359, 6485, 13, 1666, 279, 32580, 4235, 34, 12938, 22639, 304, 1778, 6485, 527, 539, 3831, 3403, 311, 14389, 279, 26735, 11, 420, 15629, 374, 6004, 505, 279, 20622, 316, 3899, 320, 23966, 13, 220, 16, 7609, 19575, 220, 16, 25, 22938, 17966, 315, 63052, 41503, 15922, 6108, 20622, 316, 3899, 13, 362, 15922, 42589, 320, 11708, 8, 61336, 449, 1403, 68937, 729, 320, 13553, 12651, 351, 2439, 8, 649, 2865, 264, 31484, 292, 13935, 42589, 320, 12481, 8, 1555, 264, 43004, 12970, 2463, 9289, 8627, 287, 17383, 13, 578, 11212, 315, 264, 293, 12031, 9155, 442, 55269, 320, 6881, 459, 63052, 8, 311, 279, 1403, 68937, 729, 11384, 264, 390, 1659, 278, 2349, 430, 26338, 279, 20334, 315, 279, 2463, 9289, 6485, 449, 279, 12777, 306, 4984, 315, 279, 6799, 42589, 13, 8797, 1404, 2217, 25117, 315, 15922, 26735, 42589, 43405, 278, 369, 1057, 8446, 11, 311, 23846, 279, 63052, 38973, 15922, 26735, 4984, 11, 374, 279, 1205, 311, 1505, 459, 23669, 30945, 61002, 6696, 12744, 430, 7612, 311, 3449, 279, 2768, 1925, 4787, 13, 5629, 11, 264, 3831, 6811, 304, 20334, 1990, 279, 2463, 9289, 390, 1659, 320, 778, 2101, 2225, 32580, 4235, 34, 12938, 323, 17723, 540, 95057, 22639, 8, 323, 264, 4382, 81268, 390, 1659, 320, 3323, 32580, 4235, 34, 12938, 2385, 2320, 1334, 826, 570, 10657, 11, 279, 81268, 390, 1659, 11, 1234, 279, 12146, 22772, 4787, 320, 2000, 3187, 11, 9499, 323, 20545, 2134, 705, 1288, 387, 45311, 3403, 311, 2187, 4984, 315, 279, 26735, 13, 17830, 11, 279, 2463, 9289, 390, 1659, 1288, 539, 387, 2288, 15528, 779, 430, 293, 1748, 349, 11212, 311, 279, 20622, 316, 3899, 555, 279, 63052, 1053, 387, 5535, 13, 2057, 11322, 420, 11, 584, 617, 20041, 15922, 62762, 437, 315, 2204, 3160, 320, 34232, 6522, 311, 69125, 315, 2204, 357, 8623, 8, 323, 12793, 1124, 449, 264, 2463, 9289, 8627, 287, 15922, 20622, 316, 3899, 320, 258, 12821, 4504, 2225, 32580, 4235, 34, 12938, 323, 17723, 540, 95057, 22639, 8, 323, 264, 2585, 15922, 20622, 316, 3899, 32161, 279, 2463, 9289, 30164, 13651, 320, 23966, 13, 220, 17, 64, 7609, 1666, 3685, 220, 1927, 1174, 1606, 315, 279, 5217, 17723, 540, 95057, 22639, 11, 369, 682, 62762, 437, 12793, 279, 2463, 9289, 8627, 287, 15922, 20622, 316, 3899, 5039, 264, 5190, 51552, 320, 438, 8617, 20334, 8, 7863, 311, 279, 2585, 20622, 316, 3899, 3025, 311, 1193, 1376, 264, 81268, 6485, 320, 23966, 13, 220, 17, 65, 4235, 68, 7609, 1226, 1505, 430, 264, 220, 717, 12, 406, 15922, 26735, 11767, 311, 279, 31005, 6811, 304, 51552, 1990, 2463, 9289, 323, 81268, 18488, 1234, 1057, 22772, 4787, 320, 23966, 13, 220, 17, 69, 22377, 7609, 12362, 420, 15922, 26735, 584, 1501, 430, 11, 1418, 279, 6485, 14454, 449, 279, 2463, 9289, 8627, 287, 20622, 316, 3899, 374, 15528, 520, 20472, 3770, 220, 1135, 37386, 34, 320, 350, 296, 284, 4103, 13, 16, 38121, 15, 13, 20, 37386, 34, 705, 279, 6485, 12457, 449, 279, 2585, 20622, 316, 3899, 320, 3323, 81268, 8, 374, 26310, 45311, 520, 3130, 9499, 323, 11767, 311, 459, 4661, 4686, 128257, 198, 128256, 78191, 198, 2127, 6625, 2128, 315, 12074, 505, 279, 3907, 315, 22463, 8611, 52409, 460, 323, 279, 3907, 315, 30613, 706, 5068, 11, 304, 264, 5684, 4756, 420, 2046, 304, 22037, 26545, 11, 279, 2955, 323, 39975, 315, 264, 20622, 437, 2296, 31206, 1776, 826, 10847, 1903, 315, 15922, 430, 374, 220, 508, 11, 931, 3115, 9333, 1109, 264, 3823, 7013, 13, 1115, 31206, 1776, 826, 10847, 1436, 330, 68392, 1, 323, 6493, 11217, 520, 24473, 10687, 304, 279, 3823, 2547, 3131, 22900, 555, 3230, 8624, 24915, 13, 578, 31206, 1776, 826, 10847, 374, 1193, 264, 2478, 20622, 4512, 417, 1317, 323, 374, 24306, 315, 264, 28367, 15922, 42589, 430, 649, 2865, 264, 5623, 323, 1243, 13750, 1180, 439, 279, 23506, 7200, 315, 279, 1776, 826, 10847, 13, 578, 1403, 10548, 315, 420, 15922, 330, 60530, 655, 7200, 1, 6782, 1403, 34330, 5620, 4647, 32606, 430, 649, 11951, 9396, 311, 264, 2218, 63052, 11, 264, 816, 35831, 13128, 13605, 555, 279, 2547, 304, 2077, 311, 2204, 78284, 1778, 439, 24032, 323, 42068, 13, 3277, 279, 34330, 5620, 4647, 32606, 315, 279, 1776, 826, 10847, 15641, 323, 10950, 311, 279, 11977, 315, 279, 2218, 63052, 279, 15922, 330, 60530, 655, 7200, 1, 374, 41398, 323, 279, 6799, 5623, 374, 6004, 13, 330, 4054, 16358, 4668, 922, 420, 31206, 1776, 826, 10847, 1359, 2795, 89699, 33652, 5979, 11, 33468, 17054, 315, 42846, 520, 279, 3907, 315, 22463, 8611, 52409, 460, 11, 330, 285, 430, 433, 649, 1193, 387, 22900, 555, 279, 3230, 63052, 49183, 279, 34330, 5620, 9681, 315, 279, 15922, 364, 60530, 655, 7200, 4527, 3296, 5042, 10223, 1521, 9681, 11, 832, 649, 8617, 2068, 279, 1776, 826, 10847, 311, 4984, 264, 5623, 304, 2077, 311, 264, 8205, 315, 3230, 59854, 13, 8876, 2204, 59854, 527, 24915, 315, 2204, 19338, 11, 420, 1436, 3719, 264, 1633, 3230, 10500, 304, 279, 9400, 12734, 596, 6206, 1210, 330, 14364, 2294, 3424, 315, 1057, 1776, 826, 10847, 1359, 11621, 60061, 79763, 8047, 7826, 19010, 41205, 11, 22103, 17054, 304, 279, 6011, 315, 42846, 520, 279, 3907, 315, 30613, 11, 330, 285, 1202, 1579, 60112, 13, 1789, 3187, 11, 3156, 1457, 584, 617, 21091, 279, 3318, 17966, 315, 279, 1776, 826, 10847, 1701, 2380, 2204, 8346, 59854, 11, 2737, 459, 23495, 63052, 11, 323, 51297, 31484, 292, 33969, 439, 1646, 11217, 13, 2030, 9523, 311, 279, 1579, 56586, 2968, 315, 15922, 30903, 11, 832, 649, 1457, 2955, 279, 15922, 1776, 826, 10847, 311, 364, 68392, 6, 264, 7029, 2134, 315, 8983, 261, 32486, 35715, 1210, 330, 21103, 287, 420, 31206, 1776, 826, 10847, 574, 264, 2294, 8815, 1359, 2795, 4567, 6863, 39431, 37037, 11, 264, 1772, 38083, 278, 32185, 304, 33652, 5979, 596, 2128, 323, 12717, 3229, 315, 279, 502, 4007, 13, 330, 2181, 2631, 264, 1317, 4101, 315, 21896, 311, 1505, 279, 23669, 2955, 11, 902, 13912, 279, 5623, 6799, 304, 364, 60530, 655, 7200, 6, 304, 279, 19821, 315, 279, 63052, 11, 2085, 28987, 2288, 1790, 1202, 10658, 15374, 3131, 279, 63052, 31854, 279, 1776, 826, 10847, 1210, 578, 1912, 315, 12074, 374, 1457, 24450, 311, 10737, 279, 1776, 826, 10847, 369, 279, 9889, 315, 70432, 9959, 11217, 11, 323, 311, 20461, 1202, 14830, 15374, 13, 330, 1687, 48146, 430, 4528, 31206, 1776, 826, 35513, 1253, 387, 1511, 304, 279, 3221, 3938, 311, 6493, 11217, 311, 3230, 10687, 304, 279, 2547, 13, 1115, 1053, 48863, 7417, 279, 15374, 315, 11217, 439, 1664, 439, 18979, 872, 21503, 14580, 6372, 1359, 45537, 33652, 5979, 13, 578, 1828, 3094, 304, 279, 2447, 374, 311, 2218, 264, 3230, 8624, 323, 5623, 369, 902, 279, 37471, 1776, 826, 10847, 649, 387, 30464, 369, 7649, 389, 7917, 304, 55004, 11, 4972, 311, 7649, 304, 24548, 13, 220, 128257, 198 ]

2,004

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Oestradiol establishes neural sex differences in many vertebrates 1 , 2 , 3 and modulates mood, behaviour and energy balance in adulthood 4 , 5 , 6 , 7 , 8 . In the canonical pathway, oestradiol exerts its effects through the transcription factor oestrogen receptor-α (ERα) 9 . Although ERα has been extensively characterized in breast cancer, the neuronal targets of ERα, and their involvement in brain sex differences, remain largely unknown. Here we generate a comprehensive map of genomic ERα-binding sites in a sexually dimorphic neural circuit that mediates social behaviours. We conclude that ERα orchestrates sexual differentiation of the mouse brain through two mechanisms: establishing two male-biased neuron types and activating a sustained male-biased gene expression program. Collectively, our findings reveal that sex differences in gene expression are defined by hormonal activation of neuronal steroid receptors. The molecular targets we identify may underlie the effects of oestradiol on brain development, behaviour and disease. Main In mammals, gonadal steroid hormones regulate sex differences in neural activity and behaviour. These hormones establish sex-typical neural circuitry during critical periods of development and activate the display of innate social behaviours in adulthood. Among these hormones, oestradiol is the principal regulator of brain sexual differentiation in mice. In males, the testes briefly activate at birth, generating a sharp rise in testosterone that subsides within hours 10 . Neural aromatase converts circulating testosterone to 17β-oestradiol, which acts through ERα in discrete neuronal populations to specify sex differences in cell number and connectivity 1 , 3 , 11 . Despite extensive characterization of the neural circuits controlling sex-typical behaviours 12 , 13 , the underlying genomic mechanisms by which steroid hormone receptors act in these circuits remain unknown. Recent advancements in low-input and single-cell chromatin profiling methods have provided transformative insights into how transcription factors (TFs) regulate gene expression in small numbers of cells 14 . We set out to use these methods to discover the neuronal genomic targets of ERα and how they coordinate brain sexual differentiation. Genomic targets of ERα in the brain To determine the genomic targets of ERα in the brain, we used an established hormone starvation and replacement paradigm that reproducibly elicits sex-typical behaviours 2 and replicates the medium conditions required to detect ERα genomic binding in cell lines 15 . At 4 h after treatment with oestradiol benzoate (E2) or vehicle control, we profiled ERα binding in three interconnected limbic brain regions in which ERα regulates sex-typical behaviours: the posterior bed nucleus of the stria terminalis (BNSTp), medial pre-optic area and posterior medial amygdala 11 , 12 , 16 (Fig. 1a ). We used the low-input TF profiling method CUT&RUN, which we first validated in MCF-7 breast cancer cells by comparing to a previous dataset for chromatin immunoprecipitation with sequencing (ChIP–seq) of ERα (Extended Data Fig. 1 ). We detected 1,930 E2-induced ERα-bound loci in the brain (Fig. 1b , Extended Data Fig. 2 and Supplementary Table 1 ). The most enriched TF-binding motif in these peaks was the oestrogen response element (ERE), the canonical binding site of oestrogen receptors (Extended Data Fig. 2c, d ). Comparison of these ERα-binding sites to those previously detected in peripheral mouse tissues revealed that most are specific to the brain (Fig. 1c and Extended Data Fig. 2f ). Brain-specific ERα binding events were uniquely enriched for synaptic and neurodevelopmental disease Gene Ontology terms, including neurotransmitter receptors, ion channels, neurotrophin receptors and extracellular matrix genes (Fig. 1d , Extended Data Fig. 2h–k and Supplementary Table 1 ). We also found evidence supporting direct crosstalk between oestradiol and neuroprotection, as ERα directly binds loci for the neurotrophin receptors Ntrk2 (also known as Trkb ) and Ntrk3 (Extended Data Fig. 2k and Supplementary Table 1 ). Moreover, ERα targets the genes encoding androgen and progesterone receptors ( Ar and Pgr ; Supplementary Table 1 ). Fig. 1: Genomic targets of ERα in sexually dimorphic neuronal populations. a , Coronal sections containing sexually dimorphic brain areas used for ERα CUT&RUN. MPOA, medial pre-optic area; BNSTp, posterior bed nucleus of the stria terminalis; MeAp, posterior medial amygdala. b , Line plots (top) and heatmaps (bottom) of mean IgG and ERα CUT&RUN (C&R) CPM ±1 kb around E2-induced ERα CUT&RUN peaks (DiffBind edgeR, P adj < 0.1). The heatmaps are sorted by E2 ERα CUT&RUN signal. Colour scale is counts per million (CPM). Veh, vehicle. c , Cross-tissue ERα comparison, showing the proportion of ERα peaks detected specifically in brain. d , Top Gene Ontology biological process terms associated with genes nearest to brain-specific or shared (≥4 other tissues) ERα CUT&RUN peaks (clusterProfiler, P adj < 0.1). e , Combined sex E2 versus vehicle RNA-seq in BNSTp Esr1 + cells; light grey and red dots (DESeq2, P adj < 0.1), dark grey and red dots (DESeq2, P < 0.01), purple dots (validated by in situ hybridization (ISH)). FC, fold change. Positive FC is E2-upregulated, negative FC is E2-downregulated. f , Images (left panels) and quantitative analysis (right panels) of ISH for select genes induced by E2 in both sexes. Boxplot centre, median; box boundaries, first and third quartiles; whiskers, 1.5 × IQR from boundaries. Two-way analysis of variance: Brinp2 P = 0.0373, Rcn1 P = 0.0307, Enah P = 0.0003, Tle3 P = 0.0001; n = 4 per condition; scale bar, 200 µm. g , MA plot of E2-regulated ATAC–seq peaks in BNSTp Esr1 + cells; red dots are E2-open peaks (DiffBind edgeR, log 2 [FC] > 1, P adj < 0.05), grey dots are E2-close peaks (DiffBind edgeR, log 2 [FC] < −1, P adj < 0.05). h , Example ERα peaks at E2-induced genes. Top left number is the y-axis range in CPM. Shaded band indicates peak region. Source Data Full size image To determine the effects of ERα binding on gene expression and chromatin state, we focused on a single brain region, the BNSTp, given its central role in the regulation of sex-typical behaviours. The BNSTp receives olfactory input through the accessory olfactory", "role": "user" }, { "content": "Sex hormones play an important role in shaping an animal's behavior, and their influence starts early. Early-life hormonal surges help shape the developing brain, establishing circuitry that will influence behavior for a lifetime. Hundreds of genes in the brain fall under the control of estrogen. Fluctuating levels of the hormone cause shifts in mood, energy balance, and behavior throughout life, in addition to sculpting developing neural circuits early on. These effects occur when activated estrogen receptors sit directly on a cell's DNA to turn genes on or off. Cold Spring Harbor Laboratory Assistant Professor Jessica Tollkuhn, graduate student Bruno Gegenhuber, and their colleagues, have been mapping exactly where estrogen receptors latch onto DNA inside mouse brain cells. They've looked at both males and females and compared the brains of adults to the still-developing brains of young pups. In the journal Nature, they report on the hormone receptor's targets in the brain and show that estrogen sets up physical differences in the brains of males and females during development. Tollkuhn explains that estrogen is present in the brains of both males and females: some neurons make it themselves out of testosterone. In male mice, estrogen generated through a surge of testosterone that is released soon after birth shapes developing circuitry. As a result, certain brain regions are larger and contain more cells in males than they do in females—a difference that affects a range of behaviors in adulthood, including mating, parenting, and aggression. \"There's this critical period when the brain is developing and wiring up that it has to get this input in order to make these permanent changes in the brain wiring. This is a transient surge, but it seems to have extremely long-lasting effects on brain development.\" Tollkuhn's team examined where estrogen receptors landed after this hormonal surge, focusing on a brain region called the BNST, which is larger in males than females in both mice and humans. They found a host of genes that were under estrogen's control, including many involved in neurodevelopment and neuronal signaling. And although estrogen itself remains in the brain for only a few hours, it seems that the hormone-controlled genes remain active for weeks. Now that they know what genes estrogen is targeting in the brain, Tollkuhn's team plans to explore exactly how those genes mediate the hormone's diverse effects on brain development, behavior, and disease. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Oestradiol establishes neural sex differences in many vertebrates 1 , 2 , 3 and modulates mood, behaviour and energy balance in adulthood 4 , 5 , 6 , 7 , 8 . In the canonical pathway, oestradiol exerts its effects through the transcription factor oestrogen receptor-α (ERα) 9 . Although ERα has been extensively characterized in breast cancer, the neuronal targets of ERα, and their involvement in brain sex differences, remain largely unknown. Here we generate a comprehensive map of genomic ERα-binding sites in a sexually dimorphic neural circuit that mediates social behaviours. We conclude that ERα orchestrates sexual differentiation of the mouse brain through two mechanisms: establishing two male-biased neuron types and activating a sustained male-biased gene expression program. Collectively, our findings reveal that sex differences in gene expression are defined by hormonal activation of neuronal steroid receptors. The molecular targets we identify may underlie the effects of oestradiol on brain development, behaviour and disease. Main In mammals, gonadal steroid hormones regulate sex differences in neural activity and behaviour. These hormones establish sex-typical neural circuitry during critical periods of development and activate the display of innate social behaviours in adulthood. Among these hormones, oestradiol is the principal regulator of brain sexual differentiation in mice. In males, the testes briefly activate at birth, generating a sharp rise in testosterone that subsides within hours 10 . Neural aromatase converts circulating testosterone to 17β-oestradiol, which acts through ERα in discrete neuronal populations to specify sex differences in cell number and connectivity 1 , 3 , 11 . Despite extensive characterization of the neural circuits controlling sex-typical behaviours 12 , 13 , the underlying genomic mechanisms by which steroid hormone receptors act in these circuits remain unknown. Recent advancements in low-input and single-cell chromatin profiling methods have provided transformative insights into how transcription factors (TFs) regulate gene expression in small numbers of cells 14 . We set out to use these methods to discover the neuronal genomic targets of ERα and how they coordinate brain sexual differentiation. Genomic targets of ERα in the brain To determine the genomic targets of ERα in the brain, we used an established hormone starvation and replacement paradigm that reproducibly elicits sex-typical behaviours 2 and replicates the medium conditions required to detect ERα genomic binding in cell lines 15 . At 4 h after treatment with oestradiol benzoate (E2) or vehicle control, we profiled ERα binding in three interconnected limbic brain regions in which ERα regulates sex-typical behaviours: the posterior bed nucleus of the stria terminalis (BNSTp), medial pre-optic area and posterior medial amygdala 11 , 12 , 16 (Fig. 1a ). We used the low-input TF profiling method CUT&RUN, which we first validated in MCF-7 breast cancer cells by comparing to a previous dataset for chromatin immunoprecipitation with sequencing (ChIP–seq) of ERα (Extended Data Fig. 1 ). We detected 1,930 E2-induced ERα-bound loci in the brain (Fig. 1b , Extended Data Fig. 2 and Supplementary Table 1 ). The most enriched TF-binding motif in these peaks was the oestrogen response element (ERE), the canonical binding site of oestrogen receptors (Extended Data Fig. 2c, d ). Comparison of these ERα-binding sites to those previously detected in peripheral mouse tissues revealed that most are specific to the brain (Fig. 1c and Extended Data Fig. 2f ). Brain-specific ERα binding events were uniquely enriched for synaptic and neurodevelopmental disease Gene Ontology terms, including neurotransmitter receptors, ion channels, neurotrophin receptors and extracellular matrix genes (Fig. 1d , Extended Data Fig. 2h–k and Supplementary Table 1 ). We also found evidence supporting direct crosstalk between oestradiol and neuroprotection, as ERα directly binds loci for the neurotrophin receptors Ntrk2 (also known as Trkb ) and Ntrk3 (Extended Data Fig. 2k and Supplementary Table 1 ). Moreover, ERα targets the genes encoding androgen and progesterone receptors ( Ar and Pgr ; Supplementary Table 1 ). Fig. 1: Genomic targets of ERα in sexually dimorphic neuronal populations. a , Coronal sections containing sexually dimorphic brain areas used for ERα CUT&RUN. MPOA, medial pre-optic area; BNSTp, posterior bed nucleus of the stria terminalis; MeAp, posterior medial amygdala. b , Line plots (top) and heatmaps (bottom) of mean IgG and ERα CUT&RUN (C&R) CPM ±1 kb around E2-induced ERα CUT&RUN peaks (DiffBind edgeR, P adj < 0.1). The heatmaps are sorted by E2 ERα CUT&RUN signal. Colour scale is counts per million (CPM). Veh, vehicle. c , Cross-tissue ERα comparison, showing the proportion of ERα peaks detected specifically in brain. d , Top Gene Ontology biological process terms associated with genes nearest to brain-specific or shared (≥4 other tissues) ERα CUT&RUN peaks (clusterProfiler, P adj < 0.1). e , Combined sex E2 versus vehicle RNA-seq in BNSTp Esr1 + cells; light grey and red dots (DESeq2, P adj < 0.1), dark grey and red dots (DESeq2, P < 0.01), purple dots (validated by in situ hybridization (ISH)). FC, fold change. Positive FC is E2-upregulated, negative FC is E2-downregulated. f , Images (left panels) and quantitative analysis (right panels) of ISH for select genes induced by E2 in both sexes. Boxplot centre, median; box boundaries, first and third quartiles; whiskers, 1.5 × IQR from boundaries. Two-way analysis of variance: Brinp2 P = 0.0373, Rcn1 P = 0.0307, Enah P = 0.0003, Tle3 P = 0.0001; n = 4 per condition; scale bar, 200 µm. g , MA plot of E2-regulated ATAC–seq peaks in BNSTp Esr1 + cells; red dots are E2-open peaks (DiffBind edgeR, log 2 [FC] > 1, P adj < 0.05), grey dots are E2-close peaks (DiffBind edgeR, log 2 [FC] < −1, P adj < 0.05). h , Example ERα peaks at E2-induced genes. Top left number is the y-axis range in CPM. Shaded band indicates peak region. Source Data Full size image To determine the effects of ERα binding on gene expression and chromatin state, we focused on a single brain region, the BNSTp, given its central role in the regulation of sex-typical behaviours. The BNSTp receives olfactory input through the accessory olfactory<|im_end|> <|im_start|>assistant Sex hormones play an important role in shaping an animal's behavior, and their influence starts early. Early-life hormonal surges help shape the developing brain, establishing circuitry that will influence behavior for a lifetime. Hundreds of genes in the brain fall under the control of estrogen. Fluctuating levels of the hormone cause shifts in mood, energy balance, and behavior throughout life, in addition to sculpting developing neural circuits early on. These effects occur when activated estrogen receptors sit directly on a cell's DNA to turn genes on or off. Cold Spring Harbor Laboratory Assistant Professor Jessica Tollkuhn, graduate student Bruno Gegenhuber, and their colleagues, have been mapping exactly where estrogen receptors latch onto DNA inside mouse brain cells. They've looked at both males and females and compared the brains of adults to the still-developing brains of young pups. In the journal Nature, they report on the hormone receptor's targets in the brain and show that estrogen sets up physical differences in the brains of males and females during development. Tollkuhn explains that estrogen is present in the brains of both males and females: some neurons make it themselves out of testosterone. In male mice, estrogen generated through a surge of testosterone that is released soon after birth shapes developing circuitry. As a result, certain brain regions are larger and contain more cells in males than they do in females—a difference that affects a range of behaviors in adulthood, including mating, parenting, and aggression. "There's this critical period when the brain is developing and wiring up that it has to get this input in order to make these permanent changes in the brain wiring. This is a transient surge, but it seems to have extremely long-lasting effects on brain development." Tollkuhn's team examined where estrogen receptors landed after this hormonal surge, focusing on a brain region called the BNST, which is larger in males than females in both mice and humans. They found a host of genes that were under estrogen's control, including many involved in neurodevelopment and neuronal signaling. And although estrogen itself remains in the brain for only a few hours, it seems that the hormone-controlled genes remain active for weeks. Now that they know what genes estrogen is targeting in the brain, Tollkuhn's team plans to explore exactly how those genes mediate the hormone's diverse effects on brain development, behavior, and disease. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 507, 15462, 2836, 337, 64664, 30828, 1877, 12062, 304, 1690, 67861, 99868, 220, 16, 1174, 220, 17, 1174, 220, 18, 323, 1491, 24031, 20247, 11, 17432, 323, 4907, 8335, 304, 64033, 220, 19, 1174, 220, 20, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 662, 763, 279, 43553, 38970, 11, 297, 15462, 2836, 337, 506, 15916, 1202, 6372, 1555, 279, 46940, 8331, 297, 478, 26252, 35268, 12, 19481, 320, 643, 19481, 8, 220, 24, 662, 10541, 27590, 19481, 706, 1027, 42817, 32971, 304, 17659, 9572, 11, 279, 79402, 11811, 315, 27590, 19481, 11, 323, 872, 22315, 304, 8271, 1877, 12062, 11, 7293, 14090, 9987, 13, 5810, 584, 7068, 264, 16195, 2472, 315, 81064, 27590, 19481, 65500, 6732, 304, 264, 27681, 5213, 41969, 30828, 16622, 430, 25098, 988, 3674, 71177, 13, 1226, 32194, 430, 27590, 19481, 66228, 988, 7392, 60038, 315, 279, 8814, 8271, 1555, 1403, 24717, 25, 31692, 1403, 8762, 1481, 72, 1503, 49384, 4595, 323, 72192, 264, 29759, 8762, 1481, 72, 1503, 15207, 7645, 2068, 13, 21153, 3210, 11, 1057, 14955, 16805, 430, 1877, 12062, 304, 15207, 7645, 527, 4613, 555, 74218, 15449, 315, 79402, 77848, 44540, 13, 578, 31206, 11811, 584, 10765, 1253, 1234, 11828, 279, 6372, 315, 297, 15462, 2836, 337, 389, 8271, 4500, 11, 17432, 323, 8624, 13, 4802, 763, 56669, 11, 64592, 51588, 77848, 44315, 37377, 1877, 12062, 304, 30828, 5820, 323, 17432, 13, 4314, 44315, 5813, 1877, 2442, 89215, 30828, 16622, 894, 2391, 9200, 18852, 315, 4500, 323, 20891, 279, 3113, 315, 65070, 3674, 71177, 304, 64033, 13, 22395, 1521, 44315, 11, 297, 15462, 2836, 337, 374, 279, 12717, 40704, 315, 8271, 7392, 60038, 304, 24548, 13, 763, 25000, 11, 279, 1296, 288, 27851, 20891, 520, 7342, 11, 24038, 264, 17676, 10205, 304, 40032, 430, 5258, 3422, 2949, 4207, 220, 605, 662, 61577, 32369, 266, 521, 33822, 54828, 40032, 311, 220, 1114, 52355, 16405, 15462, 2836, 337, 11, 902, 14385, 1555, 27590, 19481, 304, 44279, 79402, 22673, 311, 14158, 1877, 12062, 304, 2849, 1396, 323, 31357, 220, 16, 1174, 220, 18, 1174, 220, 806, 662, 18185, 16781, 60993, 315, 279, 30828, 46121, 26991, 1877, 2442, 89215, 71177, 220, 717, 1174, 220, 1032, 1174, 279, 16940, 81064, 24717, 555, 902, 77848, 36908, 44540, 1180, 304, 1521, 46121, 7293, 9987, 13, 35390, 83787, 304, 3428, 14258, 323, 3254, 33001, 22083, 15111, 56186, 5528, 617, 3984, 87435, 26793, 1139, 1268, 46940, 9547, 320, 11042, 82, 8, 37377, 15207, 7645, 304, 2678, 5219, 315, 7917, 220, 975, 662, 1226, 743, 704, 311, 1005, 1521, 5528, 311, 7142, 279, 79402, 81064, 11811, 315, 27590, 19481, 323, 1268, 814, 16580, 8271, 7392, 60038, 13, 9500, 3151, 11811, 315, 27590, 19481, 304, 279, 8271, 2057, 8417, 279, 81064, 11811, 315, 27590, 19481, 304, 279, 8271, 11, 584, 1511, 459, 9749, 36908, 78245, 323, 14039, 49340, 430, 53823, 7697, 6623, 658, 51650, 1877, 2442, 89215, 71177, 220, 17, 323, 29641, 988, 279, 11298, 4787, 2631, 311, 11388, 27590, 19481, 81064, 11212, 304, 2849, 5238, 220, 868, 662, 2468, 220, 19, 305, 1306, 6514, 449, 297, 15462, 2836, 337, 3399, 13028, 349, 320, 36, 17, 8, 477, 7458, 2585, 11, 584, 5643, 67, 27590, 19481, 11212, 304, 2380, 83416, 48694, 292, 8271, 13918, 304, 902, 27590, 19481, 80412, 1877, 2442, 89215, 71177, 25, 279, 46000, 4950, 62607, 315, 279, 357, 4298, 15372, 285, 320, 15967, 790, 79, 705, 97348, 864, 57212, 292, 3158, 323, 46000, 97348, 64383, 29684, 6181, 220, 806, 1174, 220, 717, 1174, 220, 845, 320, 30035, 13, 220, 16, 64, 7609, 1226, 1511, 279, 3428, 14258, 30245, 56186, 1749, 73957, 5, 48490, 11, 902, 584, 1176, 33432, 304, 386, 9847, 12, 22, 17659, 9572, 7917, 555, 27393, 311, 264, 3766, 10550, 369, 22083, 15111, 33119, 454, 2827, 575, 7709, 449, 62119, 320, 1163, 3378, 4235, 13565, 8, 315, 27590, 19481, 320, 54290, 2956, 23966, 13, 220, 16, 7609, 1226, 16914, 220, 16, 11, 19306, 469, 17, 38973, 27590, 19481, 50962, 1353, 72, 304, 279, 8271, 320, 30035, 13, 220, 16, 65, 1174, 41665, 2956, 23966, 13, 220, 17, 323, 99371, 6771, 220, 16, 7609, 578, 1455, 69671, 30245, 65500, 60612, 304, 1521, 40035, 574, 279, 297, 478, 26252, 2077, 2449, 320, 43272, 705, 279, 43553, 11212, 2816, 315, 297, 478, 26252, 44540, 320, 54290, 2956, 23966, 13, 220, 17, 66, 11, 294, 7609, 43551, 315, 1521, 27590, 19481, 65500, 6732, 311, 1884, 8767, 16914, 304, 35688, 8814, 39881, 10675, 430, 1455, 527, 3230, 311, 279, 8271, 320, 30035, 13, 220, 16, 66, 323, 41665, 2956, 23966, 13, 220, 17, 69, 7609, 31417, 19440, 27590, 19481, 11212, 4455, 1051, 42329, 69671, 369, 99827, 323, 18247, 30671, 278, 8624, 24983, 18298, 2508, 3878, 11, 2737, 90351, 16517, 44540, 11, 28772, 12006, 11, 18247, 83, 22761, 258, 44540, 323, 11741, 65441, 6303, 21389, 320, 30035, 13, 220, 16, 67, 1174, 41665, 2956, 23966, 13, 220, 17, 71, 4235, 74, 323, 99371, 6771, 220, 16, 7609, 1226, 1101, 1766, 6029, 12899, 2167, 272, 3714, 90849, 1990, 297, 15462, 2836, 337, 323, 18247, 782, 40241, 11, 439, 27590, 19481, 6089, 58585, 1353, 72, 369, 279, 18247, 83, 22761, 258, 44540, 452, 376, 74, 17, 320, 19171, 3967, 439, 1183, 22016, 883, 323, 452, 376, 74, 18, 320, 54290, 2956, 23966, 13, 220, 17, 74, 323, 99371, 6771, 220, 16, 7609, 23674, 11, 27590, 19481, 11811, 279, 21389, 11418, 323, 26252, 323, 30371, 5302, 606, 44540, 320, 1676, 323, 393, 911, 2652, 99371, 6771, 220, 16, 7609, 23966, 13, 220, 16, 25, 9500, 3151, 11811, 315, 27590, 19481, 304, 27681, 5213, 41969, 79402, 22673, 13, 264, 1174, 4563, 25180, 14491, 8649, 27681, 5213, 41969, 8271, 5789, 1511, 369, 27590, 19481, 73957, 5, 48490, 13, 386, 2089, 32, 11, 97348, 864, 57212, 292, 3158, 26, 46416, 790, 79, 11, 46000, 4950, 62607, 315, 279, 357, 4298, 15372, 285, 26, 2206, 10835, 11, 46000, 97348, 64383, 29684, 6181, 13, 293, 1174, 7228, 31794, 320, 3565, 8, 323, 8798, 18106, 320, 15205, 8, 315, 3152, 39551, 38, 323, 27590, 19481, 73957, 5, 48490, 320, 34, 85120, 8, 356, 8971, 20903, 16, 39753, 2212, 469, 17, 38973, 27590, 19481, 73957, 5, 48490, 40035, 320, 22499, 10154, 6964, 49, 11, 393, 12751, 366, 220, 15, 13, 16, 570, 578, 8798, 18106, 527, 10839, 555, 469, 17, 27590, 19481, 73957, 5, 48490, 8450, 13, 41962, 5569, 374, 14921, 824, 3610, 320, 7269, 44, 570, 650, 2701, 11, 7458, 13, 272, 1174, 11511, 2442, 11407, 27590, 19481, 12593, 11, 9204, 279, 21801, 315, 27590, 19481, 40035, 16914, 11951, 304, 8271, 13, 294, 1174, 7054, 24983, 18298, 2508, 24156, 1920, 3878, 5938, 449, 21389, 24379, 311, 8271, 19440, 477, 6222, 320, 120156, 19, 1023, 39881, 8, 27590, 19481, 73957, 5, 48490, 40035, 320, 19386, 51689, 11, 393, 12751, 366, 220, 15, 13, 16, 570, 384, 1174, 58752, 1877, 469, 17, 19579, 7458, 41214, 7962, 80, 304, 46416, 790, 79, 9419, 81, 16, 489, 7917, 26, 3177, 20366, 323, 2579, 32094, 320, 1170, 20794, 17, 11, 393, 12751, 366, 220, 15, 13, 16, 705, 6453, 20366, 323, 2579, 32094, 320, 1170, 20794, 17, 11, 393, 366, 220, 15, 13, 1721, 705, 25977, 32094, 320, 60690, 555, 304, 10109, 26038, 2065, 320, 16849, 4682, 16396, 11, 11816, 2349, 13, 45003, 16396, 374, 469, 17, 5352, 81722, 11, 8389, 16396, 374, 469, 17, 15220, 81722, 13, 282, 1174, 12041, 320, 2414, 21988, 8, 323, 47616, 6492, 320, 1315, 21988, 8, 315, 3507, 39, 369, 3373, 21389, 36572, 555, 469, 17, 304, 2225, 76032, 13, 8425, 4569, 12541, 11, 23369, 26, 3830, 23546, 11, 1176, 323, 4948, 41376, 3742, 26, 41759, 388, 11, 220, 16, 13, 20, 25800, 358, 31565, 505, 23546, 13, 9220, 27896, 6492, 315, 33373, 25, 3320, 43192, 17, 393, 284, 220, 15, 13, 23587, 18, 11, 432, 14606, 16, 393, 284, 220, 15, 13, 14649, 22, 11, 2998, 1494, 393, 284, 220, 15, 13, 931, 18, 11, 350, 273, 18, 393, 284, 220, 15, 13, 931, 16, 26, 308, 284, 220, 19, 824, 3044, 26, 5569, 3703, 11, 220, 1049, 64012, 76, 13, 342, 1174, 9917, 7234, 315, 469, 17, 33263, 7913, 7520, 1741, 4235, 13565, 40035, 304, 46416, 790, 79, 9419, 81, 16, 489, 7917, 26, 2579, 32094, 527, 469, 17, 26770, 40035, 320, 22499, 10154, 6964, 49, 11, 1515, 220, 17, 510, 6897, 60, 871, 220, 16, 11, 393, 12751, 366, 220, 15, 13, 2304, 705, 20366, 32094, 527, 469, 17, 35562, 40035, 320, 22499, 10154, 6964, 49, 11, 1515, 220, 17, 510, 6897, 60, 366, 25173, 16, 11, 393, 12751, 366, 220, 15, 13, 2304, 570, 305, 1174, 13688, 27590, 19481, 40035, 520, 469, 17, 38973, 21389, 13, 7054, 2163, 1396, 374, 279, 379, 36421, 2134, 304, 356, 8971, 13, 1443, 14589, 7200, 15151, 16557, 5654, 13, 8922, 2956, 8797, 1404, 2217, 2057, 8417, 279, 6372, 315, 27590, 19481, 11212, 389, 15207, 7645, 323, 22083, 15111, 1614, 11, 584, 10968, 389, 264, 3254, 8271, 5654, 11, 279, 46416, 790, 79, 11, 2728, 1202, 8792, 3560, 304, 279, 19812, 315, 1877, 2442, 89215, 71177, 13, 578, 46416, 790, 79, 21879, 8492, 22348, 1988, 1555, 279, 43081, 8492, 22348, 128257, 198, 128256, 78191, 198, 20004, 44315, 1514, 459, 3062, 3560, 304, 46620, 459, 10065, 596, 7865, 11, 323, 872, 10383, 8638, 4216, 13, 23591, 26928, 74218, 1765, 4282, 1520, 6211, 279, 11469, 8271, 11, 31692, 16622, 894, 430, 690, 10383, 7865, 369, 264, 19569, 13, 73436, 315, 21389, 304, 279, 8271, 4498, 1234, 279, 2585, 315, 70180, 13, 3061, 670, 54643, 5990, 315, 279, 36908, 5353, 29735, 304, 20247, 11, 4907, 8335, 11, 323, 7865, 6957, 2324, 11, 304, 5369, 311, 27863, 287, 11469, 30828, 46121, 4216, 389, 13, 4314, 6372, 12446, 994, 22756, 70180, 44540, 2503, 6089, 389, 264, 2849, 596, 15922, 311, 2543, 21389, 389, 477, 1022, 13, 24062, 12531, 40282, 32184, 22103, 17054, 33467, 86394, 12407, 25105, 11, 19560, 5575, 52210, 480, 20578, 27780, 261, 11, 323, 872, 18105, 11, 617, 1027, 13021, 7041, 1405, 70180, 44540, 58026, 8800, 15922, 4871, 8814, 8271, 7917, 13, 2435, 3077, 7111, 520, 2225, 25000, 323, 28585, 323, 7863, 279, 35202, 315, 12884, 311, 279, 2103, 49061, 287, 35202, 315, 3995, 90821, 13, 763, 279, 8486, 22037, 11, 814, 1934, 389, 279, 36908, 35268, 596, 11811, 304, 279, 8271, 323, 1501, 430, 70180, 7437, 709, 7106, 12062, 304, 279, 35202, 315, 25000, 323, 28585, 2391, 4500, 13, 86394, 12407, 25105, 15100, 430, 70180, 374, 3118, 304, 279, 35202, 315, 2225, 25000, 323, 28585, 25, 1063, 34313, 1304, 433, 5694, 704, 315, 40032, 13, 763, 8762, 24548, 11, 70180, 8066, 1555, 264, 22531, 315, 40032, 430, 374, 6004, 5246, 1306, 7342, 21483, 11469, 16622, 894, 13, 1666, 264, 1121, 11, 3738, 8271, 13918, 527, 8294, 323, 6782, 810, 7917, 304, 25000, 1109, 814, 656, 304, 28585, 29096, 6811, 430, 22223, 264, 2134, 315, 28198, 304, 64033, 11, 2737, 73219, 11, 49058, 11, 323, 40307, 13, 330, 3947, 596, 420, 9200, 4261, 994, 279, 8271, 374, 11469, 323, 19358, 709, 430, 433, 706, 311, 636, 420, 1988, 304, 2015, 311, 1304, 1521, 15690, 4442, 304, 279, 8271, 19358, 13, 1115, 374, 264, 41658, 22531, 11, 719, 433, 5084, 311, 617, 9193, 1317, 65265, 6372, 389, 8271, 4500, 1210, 86394, 12407, 25105, 596, 2128, 25078, 1405, 70180, 44540, 27212, 1306, 420, 74218, 22531, 11, 21760, 389, 264, 8271, 5654, 2663, 279, 46416, 790, 11, 902, 374, 8294, 304, 25000, 1109, 28585, 304, 2225, 24548, 323, 12966, 13, 2435, 1766, 264, 3552, 315, 21389, 430, 1051, 1234, 70180, 596, 2585, 11, 2737, 1690, 6532, 304, 18247, 30671, 323, 79402, 43080, 13, 1628, 8051, 70180, 5196, 8625, 304, 279, 8271, 369, 1193, 264, 2478, 4207, 11, 433, 5084, 430, 279, 36908, 41370, 21389, 7293, 4642, 369, 5672, 13, 4800, 430, 814, 1440, 1148, 21389, 70180, 374, 25103, 304, 279, 8271, 11, 86394, 12407, 25105, 596, 2128, 6787, 311, 13488, 7041, 1268, 1884, 21389, 1812, 6629, 279, 36908, 596, 17226, 6372, 389, 8271, 4500, 11, 7865, 11, 323, 8624, 13, 220, 128257, 198 ]

2,018

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract We demonstrate that chirality of the electron scattering in Weyl semimetals leads to the formation of magnetic chemical bonds for molecular states of a pair of impurities. The effect is associated with the presence of time-reversal symmetry breaking terms in the Hamiltonian which drive a crossover from s - to p -wave scattering. The profiles of the corresponding molecular orbitals and their spin polarizations are defined by the relative orientation of the lines connecting two Weyl nodes and two impurities. The magnetic character of the molecular orbitals and their tunability open the way for using doped Weyl semimetals for spintronics and realization of qubits . Introduction Recent years witnessed unprecedented penetration of the ideas of high energy physics into the domain of condensed matter. In particular, lot of attention is now attracted to the condensed matter realizations of three dimensional (3D) massless quasi-relativistic particles known as Dirac or Weyl fermions 1 . The experimental observation of Dirac fermions in such materials as Na 3 Bi 2 , 3 and Cd 3 As 2 4 , 5 made possible the study of the 3D analogs of graphene physics in a robust topologically protected material possessing both inversion ( \$ {\\mathcal I} \$ ) and time reversal ( \${\\mathscr{T}}\$ ) symmetries 6 . In Weyl semimetals, where one of these symmetries is broken, a Dirac node, which is the point where conduction and valence bands touch each other, splits into a pair of Weyl nodes with opposite chiralities. Such nodes are predicted to give rise to a plethora of interesting phenomena, including formation of Fermi arcs, unusual Hall effects, and chiral anomaly, among others 6 , 7 , 8 , 9 , 10 , 11 , 12 . The material platform for realization of Weyl fermions is presented by such compounds as tantalum arsenide (TaAs) 13 , 14 , 15 , 16 , 17 , niobium arsenide (NbAs) 18 , and tantalum phosphide (TaP) 19 . One of the aspects of Weyl semimetals which recently received particular attention is the peculiar impurity physics 20 , 21 , 22 , 23 , 24 , 25 . For instance, in the case of a single Kondo impurity, Zheng, S.-H. et al . 24 have observed beating patterns in the local density of states strongly dependent upon the \$ {\\mathcal I} \$ and \${\\mathscr{T}}\$ symmetries. Additionally, some of us have found an unusual ground state of antibonding-type for a diatomic molecule immersed into a Dirac host, which corresponds to Weyl semimetal with the symmetries above preserved 25 . Thus by working off these regimes, we consider the \${\\mathscr{T}}\$ – breaking Weyl semimetal and propose the formation of molecules due to an unprecedented chemical bond mechanism, which we reveal being of chiral-magnetic nature. In the present work, we clarify the role played by chirality of Weyl quasiparticles in the processes of impurity scattering by investigation of the local density of states. The latter can be experimentally addressed by means of the scanning tunneling microscopy (STM). We show that long-range Friedel-like oscillations 26 contribute to the formation of molecular states in a pair of distant impurities embedded in a 3D relativistic semimetal. We demonstrate that, the scenario of the impurity scattering is radically different in Dirac and Weyl semimetals and show that in the latter case magnetic molecular states can be formed. Their particular type is defined by the relative orientation of the lines connecting two Weyl nodes and two impurities. We report a crossover from s- to p- type atomic orbitals for individual impurities and related formation of spin-polarized σ – and π –type molecular orbitals for an impurity pair. Model We set \$\\hslash =1\$ throughout the calculations and represent the total Hamiltonian as the sum of the three terms: $$ {\\mathcal H} ={ {\\mathcal H} }_{0}+{ {\\mathcal H} }_{{\\rm{d}}}+{ {\\mathcal H} }_{{\\mathscr{V}}}.$$ (1) The low-energy Hamiltonian of the host may be represented as $${ {\\mathcal H} }_{0}=\\sum _{{\\bf{k}}}{\\psi }^{\\dagger }({\\bf{k}})({H}_{+}\\oplus {H}_{-}){\\psi }({\\bf{k}}),$$ (2) where \$\\psi ({\\bf{k}})={({c}_{{\\bf{k}}+\\uparrow },{c}_{{\\bf{k}}+\\downarrow },{c}_{{\\bf{k}}-\\uparrow },{c}_{{\\bf{k}}-\\downarrow })}^{T}\$ is four-spinor operator whose components \${c}_{{\\bf{k}}\\chi \\sigma }^{\\dagger }\$ ( \${c}_{{\\bf{k}}\\chi \\sigma }\$ ) stand for the creation (annihilation) operators of an electron with wave number k and spin σ , $${H}_{\\chi }({\\bf{k}})=\\chi {v}_{F}{\\sigma }\\cdot ({\\bf{k}}-\\chi Q),$$ (3) where k = ( k x , k y , k z ) is the three-dimensional wave vector, σ stands for the vector of Pauli matrices, the index \$\\chi =\\pm \\,1\$ corresponds to the chirality of the Weyl nodes and \${v}_{F}\$ is the Fermi velocity. For Q = 0, \${\\mathscr{T}}\$ symmetry is conserved and a pair of Weyl nodes is degenerated, which corresponds to the case of a standard Dirac semimetal. If \${\\mathscr{T}}\$ symmetry is broken ( Q ≠ 0), two Weyl nodes are displaced with respect to each other towards two different points in the Brillouin zone located at ± Q , but maintain energetic degeneracy as it is depicted in the Fig. 1 . Figure 1 Panel (a) Sketch of the proposed setup. Two impurities are embedded in a 3D semimetal of Dirac or Weyl type. The density of electrons forming molecular orbitals can be probed by an STM-tip. Panels (b,c) show low energy band structure for Dirac and \${\\mathscr{T}}\$ -breaking Weyl semimetals with two Weyl nodes located at ± Q i , i = x , y , z . The blue color of the lower cones indicates the filling of the valence bands, black dotted line is the Fermi energy set at ε F = 0 and red dotted line corresponds to the single-particle energy of the impurities. Full size image The impurities are modeled by the Hamiltonian $${ {\\mathcal H} }_{{\\rm{d}}}=\\sum _{j\\sigma }{\\varepsilon }_{j\\sigma }{d}_{j\\sigma }^{\\dagger }{d}_{j\\sigma }+\\sum _{j}{U}_{j}{n}_{j\\uparrow }{n}_{j\\downarrow },$$ (4) with ε jσ being single-particle energy and U j the on-site Coulomb repulsion, whereas \${n}_{j\\sigma }={d}_{j\\sigma }^{\\dagger }{d}_{j\\sigma }\$ corresponds to the number of electrons with spin projection σ at the site j with \${d}_{j\\sigma }^{\\dagger }\$ and d jσ being respectively creation and annihilation operators. The hybridization between", "role": "user" }, { "content": "In a study published in Scientific Reports, a group of researchers affiliated with São Paulo State University (UNESP) in Brazil describes an important theoretical finding that may contribute to the development of quantum computing and spintronics (spin electronics), an emerging technology that uses electron spin or angular momentum rather than electron charge to build faster, more efficient devices. The study was supported by São Paulo Research Foundation—FAPESP. Its principal investigator was Antonio Carlos Seridonio, a professor in UNESP's Department of Physics and Chemistry at Ilha Solteira, São Paulo State. His graduate students Yuri Marques, Willian Mizobata and Renan Oliveira also participated. The researchers observed that molecules with the capacity to encode information are produced in systems called Weyl semimetals when time-reversal symmetry is broken. These systems can be considered three-dimensional versions of graphene and are associated with very peculiar kinds of objects called Weyl fermions. These are massless, quasi-relativistic, chiral particles—quasi-relativistic because they move similarly to photons (the fundamental \"particles\" of light) and behave as if they were relativistic, contracting space and dilating time. The term \"chiral\" applies to an object that cannot be superimposed onto its mirror image. A sphere is achiral, but our left and right hands are chiral. In the case of Weyl fermions, chirality makes them behave as magnetic monopoles, unlike all magnetic objects in the trivial world, which behave as dipoles. Weyl fermions were proposed in 1929 by German mathematician, physicist and philosopher Hermann Weyl (1885-1955) as a possible solution to Dirac's equation. Formulated by British theoretical physicist Paul Dirac (1902-1984), this equation combines principles of quantum mechanics and special relativity to describe the behavior of electrons, quarks and other objects. Weyl fermions are hypothetical entities and have never been observed freely in nature, but studies performed in 2015 showed that they can be the basis for explaining certain phenomena. Similar to Majorana fermions, which also solve Dirac's equation, Weyl fermions manifest themselves as quasi-particles in condensed matter molecular systems. This field, in which high-energy physics and condensed matter physics converge, has mobilized major research efforts, not only because of the opportunities it offers for the development of basic science but also because the peculiarities of these quasi-particles may one day be used in quantum computing to encode information. The new study conducted at UNESP Ilha Solteira advanced in that direction. \"Our theoretical study focused on molecules made up of widely separated atoms. These molecules wouldn't be viable outside the Weyl context because the distance between atoms prevents them from forming covalent bonds and hence from sharing electrons. We demonstrated that the chirality of electron scattering in Weyl semimetals leads to the formation of magnetic chemical bonds,\" Seridonio told. Examples of Weyl semimetals include tantalum arsenide (TaAs), niobium arsenide (NbAs) and tantalum phosphide (TaP). \"In these materials, Weyl fermions play an analogous role to that of electrons in graphene. However, graphene is a quasi-2-D system, whereas these materials are fully 3-D,\" Seridonio said. The theoretical study showed that Weyl fermions in these systems appear as splits in Dirac fermions, a category comprising all material particles of the so-called Standard Model, with the possible exception of neutrinos. These splits occur at points where the conduction band (the space in which free electrons circulate) touches the valence band (the outermost layer of electrons in atoms). \"A break in symmetry makes this point, the Dirac node, split into a pair of Weyl nodes with opposite chiralities. In our study, we broke the time-reversal symmetry,\" Seridonio said. Time reversal symmetry essentially means that a system remains the same if the flow of time is reversed. \"When this symmetry is broken, the resulting molecule has spin-polarized orbitals.\" In usual molecular systems, spin-up electrons and spin-down electrons are evenly distributed in the electron cloud. This is not the case in Weyl systems. \"The result is a molecule in which the spin-up and spin-down electron clouds are spatially different. This peculiarity can be used to encode information because the molecule can be associated with the binary system, which is the bit or basic unit of information,\" Seridonio said. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract We demonstrate that chirality of the electron scattering in Weyl semimetals leads to the formation of magnetic chemical bonds for molecular states of a pair of impurities. The effect is associated with the presence of time-reversal symmetry breaking terms in the Hamiltonian which drive a crossover from s - to p -wave scattering. The profiles of the corresponding molecular orbitals and their spin polarizations are defined by the relative orientation of the lines connecting two Weyl nodes and two impurities. The magnetic character of the molecular orbitals and their tunability open the way for using doped Weyl semimetals for spintronics and realization of qubits . Introduction Recent years witnessed unprecedented penetration of the ideas of high energy physics into the domain of condensed matter. In particular, lot of attention is now attracted to the condensed matter realizations of three dimensional (3D) massless quasi-relativistic particles known as Dirac or Weyl fermions 1 . The experimental observation of Dirac fermions in such materials as Na 3 Bi 2 , 3 and Cd 3 As 2 4 , 5 made possible the study of the 3D analogs of graphene physics in a robust topologically protected material possessing both inversion ( $ {\mathcal I} $ ) and time reversal ( ${\mathscr{T}}$ ) symmetries 6 . In Weyl semimetals, where one of these symmetries is broken, a Dirac node, which is the point where conduction and valence bands touch each other, splits into a pair of Weyl nodes with opposite chiralities. Such nodes are predicted to give rise to a plethora of interesting phenomena, including formation of Fermi arcs, unusual Hall effects, and chiral anomaly, among others 6 , 7 , 8 , 9 , 10 , 11 , 12 . The material platform for realization of Weyl fermions is presented by such compounds as tantalum arsenide (TaAs) 13 , 14 , 15 , 16 , 17 , niobium arsenide (NbAs) 18 , and tantalum phosphide (TaP) 19 . One of the aspects of Weyl semimetals which recently received particular attention is the peculiar impurity physics 20 , 21 , 22 , 23 , 24 , 25 . For instance, in the case of a single Kondo impurity, Zheng, S.-H. et al . 24 have observed beating patterns in the local density of states strongly dependent upon the $ {\mathcal I} $ and ${\mathscr{T}}$ symmetries. Additionally, some of us have found an unusual ground state of antibonding-type for a diatomic molecule immersed into a Dirac host, which corresponds to Weyl semimetal with the symmetries above preserved 25 . Thus by working off these regimes, we consider the ${\mathscr{T}}$ – breaking Weyl semimetal and propose the formation of molecules due to an unprecedented chemical bond mechanism, which we reveal being of chiral-magnetic nature. In the present work, we clarify the role played by chirality of Weyl quasiparticles in the processes of impurity scattering by investigation of the local density of states. The latter can be experimentally addressed by means of the scanning tunneling microscopy (STM). We show that long-range Friedel-like oscillations 26 contribute to the formation of molecular states in a pair of distant impurities embedded in a 3D relativistic semimetal. We demonstrate that, the scenario of the impurity scattering is radically different in Dirac and Weyl semimetals and show that in the latter case magnetic molecular states can be formed. Their particular type is defined by the relative orientation of the lines connecting two Weyl nodes and two impurities. We report a crossover from s- to p- type atomic orbitals for individual impurities and related formation of spin-polarized σ – and π –type molecular orbitals for an impurity pair. Model We set $\hslash =1$ throughout the calculations and represent the total Hamiltonian as the sum of the three terms: $$ {\mathcal H} ={ {\mathcal H} }_{0}+{ {\mathcal H} }_{{\rm{d}}}+{ {\mathcal H} }_{{\mathscr{V}}}.$$ (1) The low-energy Hamiltonian of the host may be represented as $${ {\mathcal H} }_{0}=\sum _{{\bf{k}}}{\psi }^{\dagger }({\bf{k}})({H}_{+}\oplus {H}_{-}){\psi }({\bf{k}}),$$ (2) where $\psi ({\bf{k}})={({c}_{{\bf{k}}+\uparrow },{c}_{{\bf{k}}+\downarrow },{c}_{{\bf{k}}-\uparrow },{c}_{{\bf{k}}-\downarrow })}^{T}$ is four-spinor operator whose components ${c}_{{\bf{k}}\chi \sigma }^{\dagger }$ ( ${c}_{{\bf{k}}\chi \sigma }$ ) stand for the creation (annihilation) operators of an electron with wave number k and spin σ , $${H}_{\chi }({\bf{k}})=\chi {v}_{F}{\sigma }\cdot ({\bf{k}}-\chi Q),$$ (3) where k = ( k x , k y , k z ) is the three-dimensional wave vector, σ stands for the vector of Pauli matrices, the index $\chi =\pm \,1$ corresponds to the chirality of the Weyl nodes and ${v}_{F}$ is the Fermi velocity. For Q = 0, ${\mathscr{T}}$ symmetry is conserved and a pair of Weyl nodes is degenerated, which corresponds to the case of a standard Dirac semimetal. If ${\mathscr{T}}$ symmetry is broken ( Q ≠ 0), two Weyl nodes are displaced with respect to each other towards two different points in the Brillouin zone located at ± Q , but maintain energetic degeneracy as it is depicted in the Fig. 1 . Figure 1 Panel (a) Sketch of the proposed setup. Two impurities are embedded in a 3D semimetal of Dirac or Weyl type. The density of electrons forming molecular orbitals can be probed by an STM-tip. Panels (b,c) show low energy band structure for Dirac and ${\mathscr{T}}$ -breaking Weyl semimetals with two Weyl nodes located at ± Q i , i = x , y , z . The blue color of the lower cones indicates the filling of the valence bands, black dotted line is the Fermi energy set at ε F = 0 and red dotted line corresponds to the single-particle energy of the impurities. Full size image The impurities are modeled by the Hamiltonian $${ {\mathcal H} }_{{\rm{d}}}=\sum _{j\sigma }{\varepsilon }_{j\sigma }{d}_{j\sigma }^{\dagger }{d}_{j\sigma }+\sum _{j}{U}_{j}{n}_{j\uparrow }{n}_{j\downarrow },$$ (4) with ε jσ being single-particle energy and U j the on-site Coulomb repulsion, whereas ${n}_{j\sigma }={d}_{j\sigma }^{\dagger }{d}_{j\sigma }$ corresponds to the number of electrons with spin projection σ at the site j with ${d}_{j\sigma }^{\dagger }$ and d jσ being respectively creation and annihilation operators. The hybridization between<|im_end|> <|im_start|>assistant In a study published in Scientific Reports, a group of researchers affiliated with São Paulo State University (UNESP) in Brazil describes an important theoretical finding that may contribute to the development of quantum computing and spintronics (spin electronics), an emerging technology that uses electron spin or angular momentum rather than electron charge to build faster, more efficient devices. The study was supported by São Paulo Research Foundation—FAPESP. Its principal investigator was Antonio Carlos Seridonio, a professor in UNESP's Department of Physics and Chemistry at Ilha Solteira, São Paulo State. His graduate students Yuri Marques, Willian Mizobata and Renan Oliveira also participated. The researchers observed that molecules with the capacity to encode information are produced in systems called Weyl semimetals when time-reversal symmetry is broken. These systems can be considered three-dimensional versions of graphene and are associated with very peculiar kinds of objects called Weyl fermions. These are massless, quasi-relativistic, chiral particles—quasi-relativistic because they move similarly to photons (the fundamental "particles" of light) and behave as if they were relativistic, contracting space and dilating time. The term "chiral" applies to an object that cannot be superimposed onto its mirror image. A sphere is achiral, but our left and right hands are chiral. In the case of Weyl fermions, chirality makes them behave as magnetic monopoles, unlike all magnetic objects in the trivial world, which behave as dipoles. Weyl fermions were proposed in 1929 by German mathematician, physicist and philosopher Hermann Weyl (1885-1955) as a possible solution to Dirac's equation. Formulated by British theoretical physicist Paul Dirac (1902-1984), this equation combines principles of quantum mechanics and special relativity to describe the behavior of electrons, quarks and other objects. Weyl fermions are hypothetical entities and have never been observed freely in nature, but studies performed in 2015 showed that they can be the basis for explaining certain phenomena. Similar to Majorana fermions, which also solve Dirac's equation, Weyl fermions manifest themselves as quasi-particles in condensed matter molecular systems. This field, in which high-energy physics and condensed matter physics converge, has mobilized major research efforts, not only because of the opportunities it offers for the development of basic science but also because the peculiarities of these quasi-particles may one day be used in quantum computing to encode information. The new study conducted at UNESP Ilha Solteira advanced in that direction. "Our theoretical study focused on molecules made up of widely separated atoms. These molecules wouldn't be viable outside the Weyl context because the distance between atoms prevents them from forming covalent bonds and hence from sharing electrons. We demonstrated that the chirality of electron scattering in Weyl semimetals leads to the formation of magnetic chemical bonds," Seridonio told. Examples of Weyl semimetals include tantalum arsenide (TaAs), niobium arsenide (NbAs) and tantalum phosphide (TaP). "In these materials, Weyl fermions play an analogous role to that of electrons in graphene. However, graphene is a quasi-2-D system, whereas these materials are fully 3-D," Seridonio said. The theoretical study showed that Weyl fermions in these systems appear as splits in Dirac fermions, a category comprising all material particles of the so-called Standard Model, with the possible exception of neutrinos. These splits occur at points where the conduction band (the space in which free electrons circulate) touches the valence band (the outermost layer of electrons in atoms). "A break in symmetry makes this point, the Dirac node, split into a pair of Weyl nodes with opposite chiralities. In our study, we broke the time-reversal symmetry," Seridonio said. Time reversal symmetry essentially means that a system remains the same if the flow of time is reversed. "When this symmetry is broken, the resulting molecule has spin-polarized orbitals." In usual molecular systems, spin-up electrons and spin-down electrons are evenly distributed in the electron cloud. This is not the case in Weyl systems. "The result is a molecule in which the spin-up and spin-down electron clouds are spatially different. This peculiarity can be used to encode information because the molecule can be associated with the binary system, which is the bit or basic unit of information," Seridonio said. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 1226, 20461, 430, 71546, 2786, 315, 279, 17130, 72916, 304, 468, 1216, 75, 5347, 86366, 1147, 11767, 311, 279, 18488, 315, 24924, 11742, 27460, 369, 31206, 5415, 315, 264, 6857, 315, 3242, 38333, 13, 578, 2515, 374, 5938, 449, 279, 9546, 315, 892, 5621, 3078, 278, 46220, 15061, 3878, 304, 279, 24051, 1122, 902, 6678, 264, 49480, 505, 274, 482, 311, 281, 482, 31498, 72916, 13, 578, 21542, 315, 279, 12435, 31206, 27605, 1147, 323, 872, 12903, 25685, 8200, 527, 4613, 555, 279, 8844, 17140, 315, 279, 5238, 21583, 1403, 468, 1216, 75, 7954, 323, 1403, 3242, 38333, 13, 578, 24924, 3752, 315, 279, 31206, 27605, 1147, 323, 872, 11716, 2968, 1825, 279, 1648, 369, 1701, 294, 16771, 468, 1216, 75, 5347, 86366, 1147, 369, 12903, 35785, 1233, 323, 49803, 315, 2874, 82502, 662, 29438, 35390, 1667, 32126, 31069, 44596, 315, 279, 6848, 315, 1579, 4907, 22027, 1139, 279, 8106, 315, 75826, 5030, 13, 763, 4040, 11, 2763, 315, 6666, 374, 1457, 29123, 311, 279, 75826, 5030, 1972, 8200, 315, 2380, 56987, 320, 18, 35, 8, 3148, 1752, 48844, 48712, 20053, 4633, 19252, 3967, 439, 31194, 582, 477, 468, 1216, 75, 81682, 919, 220, 16, 662, 578, 22772, 22695, 315, 31194, 582, 81682, 919, 304, 1778, 7384, 439, 13106, 220, 18, 12371, 220, 17, 1174, 220, 18, 323, 85090, 220, 18, 1666, 220, 17, 220, 19, 1174, 220, 20, 1903, 3284, 279, 4007, 315, 279, 220, 18, 35, 24291, 82, 315, 66192, 22027, 304, 264, 22514, 1948, 30450, 2682, 3769, 60662, 2225, 47588, 320, 18240, 29252, 10590, 5531, 358, 92, 1144, 8, 883, 323, 892, 59214, 320, 1144, 2358, 59, 10590, 26121, 77125, 3500, 58858, 883, 8045, 4150, 4108, 220, 21, 662, 763, 468, 1216, 75, 5347, 86366, 1147, 11, 1405, 832, 315, 1521, 8045, 4150, 4108, 374, 11102, 11, 264, 31194, 582, 2494, 11, 902, 374, 279, 1486, 1405, 390, 23985, 323, 1062, 768, 21562, 5916, 1855, 1023, 11, 41567, 1139, 264, 6857, 315, 468, 1216, 75, 7954, 449, 14329, 523, 37478, 1385, 13, 15483, 7954, 527, 19698, 311, 3041, 10205, 311, 264, 68706, 315, 7185, 44247, 11, 2737, 18488, 315, 99362, 72, 67850, 11, 19018, 11166, 6372, 11, 323, 523, 37478, 64048, 11, 4315, 3885, 220, 21, 1174, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 1174, 220, 806, 1174, 220, 717, 662, 578, 3769, 5452, 369, 49803, 315, 468, 1216, 75, 81682, 919, 374, 10666, 555, 1778, 32246, 439, 95685, 372, 87364, 579, 320, 57099, 2170, 8, 220, 1032, 1174, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 1174, 13080, 677, 2411, 87364, 579, 320, 86107, 2170, 8, 220, 972, 1174, 323, 95685, 372, 33088, 579, 320, 57099, 47, 8, 220, 777, 662, 3861, 315, 279, 13878, 315, 468, 1216, 75, 5347, 86366, 1147, 902, 6051, 4036, 4040, 6666, 374, 279, 44797, 3242, 5631, 22027, 220, 508, 1174, 220, 1691, 1174, 220, 1313, 1174, 220, 1419, 1174, 220, 1187, 1174, 220, 914, 662, 1789, 2937, 11, 304, 279, 1162, 315, 264, 3254, 735, 36071, 3242, 5631, 11, 77547, 11, 328, 12898, 39, 13, 1880, 453, 662, 220, 1187, 617, 13468, 27242, 12912, 304, 279, 2254, 17915, 315, 5415, 16917, 18222, 5304, 279, 18240, 29252, 10590, 5531, 358, 92, 1144, 8, 323, 1144, 2358, 59, 10590, 26121, 77125, 3500, 58858, 8045, 4150, 4108, 13, 23212, 11, 1063, 315, 603, 617, 1766, 459, 19018, 5015, 1614, 315, 21196, 2159, 287, 10827, 369, 264, 1891, 6756, 43030, 78308, 1139, 264, 31194, 582, 3552, 11, 902, 34310, 311, 468, 1216, 75, 5347, 318, 22029, 449, 279, 8045, 4150, 4108, 3485, 34683, 220, 914, 662, 14636, 555, 3318, 1022, 1521, 61911, 11, 584, 2980, 279, 1144, 2358, 59, 10590, 26121, 77125, 3500, 58858, 1389, 15061, 468, 1216, 75, 5347, 318, 22029, 323, 30714, 279, 18488, 315, 35715, 4245, 311, 459, 31069, 11742, 11049, 17383, 11, 902, 584, 16805, 1694, 315, 523, 37478, 1474, 39100, 7138, 13, 763, 279, 3118, 990, 11, 584, 38263, 279, 3560, 6476, 555, 71546, 2786, 315, 468, 1216, 75, 934, 300, 575, 16641, 304, 279, 11618, 315, 3242, 5631, 72916, 555, 8990, 315, 279, 2254, 17915, 315, 5415, 13, 578, 15629, 649, 387, 9526, 750, 20669, 555, 3445, 315, 279, 36201, 26711, 287, 92914, 320, 36949, 570, 1226, 1501, 430, 1317, 31608, 31351, 301, 12970, 43524, 811, 220, 1627, 17210, 311, 279, 18488, 315, 31206, 5415, 304, 264, 6857, 315, 29827, 3242, 38333, 23711, 304, 264, 220, 18, 35, 59425, 4633, 5347, 318, 22029, 13, 1226, 20461, 430, 11, 279, 15398, 315, 279, 3242, 5631, 72916, 374, 61127, 2204, 304, 31194, 582, 323, 468, 1216, 75, 5347, 86366, 1147, 323, 1501, 430, 304, 279, 15629, 1162, 24924, 31206, 5415, 649, 387, 14454, 13, 11205, 4040, 955, 374, 4613, 555, 279, 8844, 17140, 315, 279, 5238, 21583, 1403, 468, 1216, 75, 7954, 323, 1403, 3242, 38333, 13, 1226, 1934, 264, 49480, 505, 274, 12, 311, 281, 12, 955, 25524, 27605, 1147, 369, 3927, 3242, 38333, 323, 5552, 18488, 315, 12903, 2320, 7569, 1534, 48823, 1389, 323, 52845, 1389, 1337, 31206, 27605, 1147, 369, 459, 3242, 5631, 6857, 13, 5008, 1226, 743, 1144, 11781, 71, 51356, 284, 16, 58858, 6957, 279, 29217, 323, 4097, 279, 2860, 24051, 1122, 439, 279, 2694, 315, 279, 2380, 3878, 25, 27199, 29252, 10590, 5531, 473, 92, 73242, 29252, 10590, 5531, 473, 92, 335, 15511, 15, 92, 10, 90, 29252, 10590, 5531, 473, 92, 335, 62, 3052, 59, 8892, 90, 67, 76642, 10, 90, 29252, 10590, 5531, 473, 92, 335, 62, 3052, 59, 10590, 26121, 90, 53, 76642, 77566, 320, 16, 8, 578, 3428, 65487, 24051, 1122, 315, 279, 3552, 1253, 387, 15609, 439, 400, 2420, 29252, 10590, 5531, 473, 92, 335, 15511, 15, 92, 35533, 1264, 721, 3052, 59, 13536, 70194, 3500, 15523, 59, 31865, 335, 61, 36802, 67, 10322, 335, 2358, 59, 13536, 70194, 3500, 8, 2358, 39, 52635, 10, 11281, 56178, 355, 314, 39, 52635, 12, 5525, 36802, 31865, 335, 2358, 59, 13536, 70194, 3500, 705, 14415, 320, 17, 8, 1405, 1144, 11781, 31865, 9657, 59, 13536, 70194, 3500, 8, 83966, 66, 20009, 3052, 59, 13536, 70194, 3500, 42815, 455, 6172, 90172, 66, 20009, 3052, 59, 13536, 70194, 3500, 42815, 2996, 6172, 90172, 66, 20009, 3052, 59, 13536, 70194, 3500, 31629, 455, 6172, 90172, 66, 20009, 3052, 59, 13536, 70194, 3500, 31629, 2996, 6172, 6547, 92, 48922, 51, 11281, 8, 374, 3116, 82006, 269, 5793, 6832, 6956, 1144, 2358, 66, 20009, 3052, 59, 13536, 70194, 3500, 59, 14946, 1144, 25956, 335, 61, 36802, 67, 10322, 52400, 8, 320, 1144, 2358, 66, 20009, 3052, 59, 13536, 70194, 3500, 59, 14946, 1144, 25956, 52400, 8, 883, 2559, 369, 279, 9886, 320, 1036, 92341, 8, 20197, 315, 459, 17130, 449, 12330, 1396, 597, 323, 12903, 48823, 1174, 400, 2420, 39, 52635, 59, 14946, 335, 2358, 59, 13536, 70194, 3500, 11992, 59, 14946, 314, 85, 52635, 37, 15523, 59, 25956, 52400, 51953, 9657, 59, 13536, 70194, 3500, 31629, 14946, 1229, 705, 14415, 320, 18, 8, 1405, 597, 284, 320, 597, 865, 1174, 597, 379, 1174, 597, 1167, 883, 374, 279, 2380, 33520, 12330, 4724, 11, 48823, 13656, 369, 279, 4724, 315, 7043, 72, 36295, 11, 279, 1963, 1144, 11781, 14946, 284, 59, 5298, 1144, 11, 16, 58858, 34310, 311, 279, 71546, 2786, 315, 279, 468, 1216, 75, 7954, 323, 1144, 2358, 85, 52635, 37, 11281, 8, 374, 279, 99362, 72, 15798, 13, 1789, 1229, 284, 220, 15, 11, 1144, 2358, 59, 10590, 26121, 77125, 3500, 58858, 46220, 374, 1615, 2841, 323, 264, 6857, 315, 468, 1216, 75, 7954, 374, 5367, 10766, 11, 902, 34310, 311, 279, 1162, 315, 264, 5410, 31194, 582, 5347, 318, 22029, 13, 1442, 1144, 2358, 59, 10590, 26121, 77125, 3500, 58858, 46220, 374, 11102, 320, 1229, 95404, 220, 15, 705, 1403, 468, 1216, 75, 7954, 527, 49246, 449, 5201, 311, 1855, 1023, 7119, 1403, 2204, 3585, 304, 279, 67744, 283, 258, 10353, 7559, 520, 20903, 1229, 1174, 719, 10519, 45955, 5367, 804, 2826, 439, 433, 374, 44894, 304, 279, 23966, 13, 220, 16, 662, 19575, 220, 16, 19482, 320, 64, 8, 39501, 315, 279, 11223, 6642, 13, 9220, 3242, 38333, 527, 23711, 304, 264, 220, 18, 35, 5347, 318, 22029, 315, 31194, 582, 477, 468, 1216, 75, 955, 13, 578, 17915, 315, 57678, 30164, 31206, 27605, 1147, 649, 387, 463, 2788, 555, 459, 48273, 84329, 13, 81592, 320, 65, 10317, 8, 1501, 3428, 4907, 7200, 6070, 369, 31194, 582, 323, 1144, 2358, 59, 10590, 26121, 77125, 3500, 58858, 482, 37757, 468, 1216, 75, 5347, 86366, 1147, 449, 1403, 468, 1216, 75, 7954, 7559, 520, 20903, 1229, 602, 1174, 602, 284, 865, 1174, 379, 1174, 1167, 662, 578, 6437, 1933, 315, 279, 4827, 87992, 15151, 279, 21973, 315, 279, 1062, 768, 21562, 11, 3776, 59201, 1584, 374, 279, 99362, 72, 4907, 743, 520, 60247, 435, 284, 220, 15, 323, 2579, 59201, 1584, 34310, 311, 279, 3254, 2320, 7203, 4907, 315, 279, 3242, 38333, 13, 8797, 1404, 2217, 578, 3242, 38333, 527, 62653, 555, 279, 24051, 1122, 400, 2420, 29252, 10590, 5531, 473, 92, 335, 62, 3052, 59, 8892, 90, 67, 76642, 35533, 1264, 102499, 73, 59, 25956, 335, 36802, 85, 548, 60992, 335, 15511, 73, 59, 25956, 335, 90, 67, 52635, 73, 59, 25956, 335, 61, 36802, 67, 10322, 335, 90, 67, 52635, 73, 59, 25956, 335, 42815, 1264, 102499, 73, 15523, 52, 52635, 73, 15523, 77, 52635, 73, 59, 455, 6172, 335, 90, 77, 52635, 73, 59, 2996, 6172, 2529, 14415, 320, 19, 8, 449, 60247, 503, 45028, 1694, 3254, 2320, 7203, 4907, 323, 549, 503, 279, 389, 29654, 67948, 2925, 2109, 34003, 11, 20444, 1144, 2358, 77, 52635, 73, 59, 25956, 335, 1185, 67, 52635, 73, 59, 25956, 335, 61, 36802, 67, 10322, 335, 90, 67, 52635, 73, 59, 25956, 52400, 8, 34310, 311, 279, 1396, 315, 57678, 449, 12903, 22343, 48823, 520, 279, 2816, 503, 449, 1144, 2358, 67, 52635, 73, 59, 25956, 335, 61, 36802, 67, 10322, 52400, 8, 323, 294, 503, 45028, 1694, 15947, 9886, 323, 3008, 92341, 20197, 13, 578, 26038, 2065, 1990, 128257, 198, 128256, 78191, 198, 644, 264, 4007, 4756, 304, 38130, 29140, 11, 264, 1912, 315, 12074, 37506, 449, 48790, 38026, 3314, 3907, 320, 1899, 57329, 8, 304, 16327, 16964, 459, 3062, 32887, 9455, 430, 1253, 17210, 311, 279, 4500, 315, 31228, 25213, 323, 12903, 35785, 1233, 320, 42682, 31591, 705, 459, 24084, 5557, 430, 5829, 17130, 12903, 477, 20932, 24151, 4856, 1109, 17130, 6900, 311, 1977, 10819, 11, 810, 11297, 7766, 13, 578, 4007, 574, 7396, 555, 48790, 38026, 8483, 5114, 2345, 37, 2599, 57329, 13, 11699, 12717, 49581, 574, 23245, 30397, 8409, 307, 82513, 11, 264, 14561, 304, 6781, 57329, 596, 6011, 315, 28415, 323, 42846, 520, 7695, 4317, 11730, 668, 9008, 11, 48790, 38026, 3314, 13, 5414, 19560, 4236, 86873, 2947, 14295, 11, 4946, 1122, 72695, 677, 460, 323, 14094, 276, 96414, 1101, 31408, 13, 578, 12074, 13468, 430, 35715, 449, 279, 8824, 311, 16559, 2038, 527, 9124, 304, 6067, 2663, 468, 1216, 75, 5347, 86366, 1147, 994, 892, 5621, 3078, 278, 46220, 374, 11102, 13, 4314, 6067, 649, 387, 6646, 2380, 33520, 11028, 315, 66192, 323, 527, 5938, 449, 1633, 44797, 13124, 315, 6302, 2663, 468, 1216, 75, 81682, 919, 13, 4314, 527, 3148, 1752, 11, 48844, 48712, 20053, 4633, 11, 523, 37478, 19252, 2345, 447, 10426, 48712, 20053, 4633, 1606, 814, 3351, 30293, 311, 89235, 320, 1820, 16188, 330, 69598, 1, 315, 3177, 8, 323, 36792, 439, 422, 814, 1051, 59425, 4633, 11, 60506, 3634, 323, 19371, 1113, 892, 13, 578, 4751, 330, 331, 37478, 1, 17208, 311, 459, 1665, 430, 4250, 387, 2307, 318, 3950, 8800, 1202, 18327, 2217, 13, 362, 26436, 374, 34361, 37478, 11, 719, 1057, 2163, 323, 1314, 6206, 527, 523, 37478, 13, 763, 279, 1162, 315, 468, 1216, 75, 81682, 919, 11, 71546, 2786, 3727, 1124, 36792, 439, 24924, 1647, 454, 7298, 11, 20426, 682, 24924, 6302, 304, 279, 36747, 1917, 11, 902, 36792, 439, 294, 7088, 645, 13, 468, 1216, 75, 81682, 919, 1051, 11223, 304, 220, 5926, 24, 555, 6063, 21651, 1122, 11, 83323, 323, 55475, 32565, 1036, 468, 1216, 75, 320, 9367, 20, 12, 6280, 20, 8, 439, 264, 3284, 6425, 311, 31194, 582, 596, 24524, 13, 3459, 7913, 555, 8013, 32887, 83323, 7043, 31194, 582, 320, 7028, 17, 12, 3753, 19, 705, 420, 24524, 33511, 16565, 315, 31228, 30126, 323, 3361, 1375, 44515, 311, 7664, 279, 7865, 315, 57678, 11, 934, 7341, 323, 1023, 6302, 13, 468, 1216, 75, 81682, 919, 527, 59159, 15086, 323, 617, 2646, 1027, 13468, 26662, 304, 7138, 11, 719, 7978, 10887, 304, 220, 679, 20, 8710, 430, 814, 649, 387, 279, 8197, 369, 26073, 3738, 44247, 13, 22196, 311, 17559, 3444, 81682, 919, 11, 902, 1101, 11886, 31194, 582, 596, 24524, 11, 468, 1216, 75, 81682, 919, 14794, 5694, 439, 48844, 2320, 16641, 304, 75826, 5030, 31206, 6067, 13, 1115, 2115, 11, 304, 902, 1579, 65487, 22027, 323, 75826, 5030, 22027, 80867, 11, 706, 29905, 1534, 3682, 3495, 9045, 11, 539, 1193, 1606, 315, 279, 10708, 433, 6209, 369, 279, 4500, 315, 6913, 8198, 719, 1101, 1606, 279, 44797, 1385, 315, 1521, 48844, 2320, 16641, 1253, 832, 1938, 387, 1511, 304, 31228, 25213, 311, 16559, 2038, 13, 578, 502, 4007, 13375, 520, 6781, 57329, 7695, 4317, 11730, 668, 9008, 11084, 304, 430, 5216, 13, 330, 8140, 32887, 4007, 10968, 389, 35715, 1903, 709, 315, 13882, 19180, 33299, 13, 4314, 35715, 8434, 956, 387, 31528, 4994, 279, 468, 1216, 75, 2317, 1606, 279, 6138, 1990, 33299, 29034, 1124, 505, 30164, 1080, 838, 306, 27460, 323, 16472, 505, 11821, 57678, 13, 1226, 21091, 430, 279, 71546, 2786, 315, 17130, 72916, 304, 468, 1216, 75, 5347, 86366, 1147, 11767, 311, 279, 18488, 315, 24924, 11742, 27460, 1359, 8409, 307, 82513, 3309, 13, 26379, 315, 468, 1216, 75, 5347, 86366, 1147, 2997, 95685, 372, 87364, 579, 320, 57099, 2170, 705, 13080, 677, 2411, 87364, 579, 320, 86107, 2170, 8, 323, 95685, 372, 33088, 579, 320, 57099, 47, 570, 330, 644, 1521, 7384, 11, 468, 1216, 75, 81682, 919, 1514, 459, 79283, 3560, 311, 430, 315, 57678, 304, 66192, 13, 4452, 11, 66192, 374, 264, 48844, 12, 17, 9607, 1887, 11, 20444, 1521, 7384, 527, 7373, 220, 18, 9607, 1359, 8409, 307, 82513, 1071, 13, 578, 32887, 4007, 8710, 430, 468, 1216, 75, 81682, 919, 304, 1521, 6067, 5101, 439, 41567, 304, 31194, 582, 81682, 919, 11, 264, 5699, 46338, 682, 3769, 19252, 315, 279, 779, 19434, 12028, 5008, 11, 449, 279, 3284, 4788, 315, 42699, 15570, 13, 4314, 41567, 12446, 520, 3585, 1405, 279, 390, 23985, 7200, 320, 1820, 3634, 304, 902, 1949, 57678, 4319, 6468, 8, 29727, 279, 1062, 768, 7200, 320, 1820, 16335, 3646, 6324, 315, 57678, 304, 33299, 570, 330, 32, 1464, 304, 46220, 3727, 420, 1486, 11, 279, 31194, 582, 2494, 11, 6859, 1139, 264, 6857, 315, 468, 1216, 75, 7954, 449, 14329, 523, 37478, 1385, 13, 763, 1057, 4007, 11, 584, 14760, 279, 892, 5621, 3078, 278, 46220, 1359, 8409, 307, 82513, 1071, 13, 4212, 59214, 46220, 16168, 3445, 430, 264, 1887, 8625, 279, 1890, 422, 279, 6530, 315, 892, 374, 28537, 13, 330, 4599, 420, 46220, 374, 11102, 11, 279, 13239, 43030, 706, 12903, 2320, 7569, 1534, 27605, 1147, 1210, 763, 13783, 31206, 6067, 11, 12903, 5352, 57678, 323, 12903, 15220, 57678, 527, 42147, 4332, 304, 279, 17130, 9624, 13, 1115, 374, 539, 279, 1162, 304, 468, 1216, 75, 6067, 13, 330, 791, 1121, 374, 264, 43030, 304, 902, 279, 12903, 5352, 323, 12903, 15220, 17130, 30614, 527, 29079, 398, 2204, 13, 1115, 31100, 24520, 10981, 649, 387, 1511, 311, 16559, 2038, 1606, 279, 43030, 649, 387, 5938, 449, 279, 8026, 1887, 11, 902, 374, 279, 2766, 477, 6913, 5089, 315, 2038, 1359, 8409, 307, 82513, 1071, 13, 220, 128257, 198 ]

2,648

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Organic electrochemical transistors (OECTs) are receiving significant attention due to their ability to efficiently transduce biological signals. A major limitation of this technology is that only p-type materials have been reported, which precludes the development of complementary circuits, and limits sensor technologies. Here, we report the first ever n-type OECT, with relatively balanced ambipolar charge transport characteristics based on a polymer that supports both hole and electron transport along its backbone when doped through an aqueous electrolyte and in the presence of oxygen. This new semiconducting polymer is designed specifically to facilitate ion transport and promote electrochemical doping. Stability measurements in water show no degradation when tested for 2 h under continuous cycling. This demonstration opens the possibility to develop complementary circuits based on OECTs and to improve the sophistication of bioelectronic devices. Introduction Interest in mixed conduction, as in recent bioelectronic and energy applications, has led to a surge in novel organic electronic materials and devices. One characteristic example is an organic electrochemical transistor (OECT), in which ions from an electrolyte penetrate a polymer film and modulate its conductivity. As a result, OECTs can efficiently transduce ionic signals into electronic ones, making them ideal biological sensing elements. OECTs can be fabricated from biocompatible materials 1 , 2 and operate in aqueous environments, which enables recordings in vivo and in vitro 1 , 3 , 4 , 5 . The advantage of OECT-based sensors compared to organic field-effect transistor (OFET)-based sensors is that ions in the former interact with the whole volume of the active material, giving rise to lower impedance and higher transconductance 6 . As a result, the performance of an OECT, defined by the efficiency with which it transduces a voltage modulation at the gate ( V G ) into a current modulation in the channel ( I D ), depends on the thickness of the active layer. This is contrary to OFETs, which rely on the interfacial accumulation of charges and are thus limited by the double layer capacitance 5 , 6 . In particular, the transconductance ( g m =∂ I D /∂ V G ) of OECTs operated in an aqueous environment can reach more than 3.0 mS (refs 3 , 7 , 8 ) at low biases, enabling their use in clinical neuroscience applications, including electrocardiography 3 , 9 , electroencephalography 6 , 9 or neural stimulation 4 . The current state-of-the-art active material for OECTs is the conducting polymer blend poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) PEDOT:PSS, where the material is doped in its native state, requiring the OECT to be operated in depletion mode 3 , 8 . The operation of an OECT in accumulation mode allows for low power consumption devices with high ON/OFF ratios. The ability of a polythiophene-based polyelectrolyte to operate as an accumulation mode OECT has previously been demonstrated with transconductances of up to 2.0 mS (ref. 10 ). Intermediate materials, where conducting and semiconducting polymers were blended together, have also been reported 11 . To date, however, all reported OECTs have relied on hole transport (p-type), while development of electron transporting (n-type) or ambipolar OECTs has been ignored. Such OECTs would allow the development of complementary circuits and will dramatically improve the sophistication of bioelectronics devices. However, the development of appropriate semiconductor materials is a major challenge: It requires that a material be both stable in an aqueous electrolyte, and that it be reversibly reduced and oxidized within the electrochemical window imparted by that electrolyte. This requires the design of materials that concurrently have a high electron affinity (EA), a low ionization potential and the capacity for facile ion penetration. In addition to their ability to be oxidized and reduced efficiently, these materials should also show high electron and hole mobilities in order to sustain large electronic currents and yield efficient current modulation in an OECT format. Recently, the electron mobility of n-type polymers has increased rapidly, reaching values of more than 1.0 cm −2 V −1 s −1 in OFETs, 12 , 13 , 14 , 15 , 16 , 17 thus enabling n-type OECTs operating in accumulation mode. While air stable n-type materials for OFETs have been reported 18 , 19 , these materials usually degrade when operated in water. In this work, we report the first n-type and ambipolar OECT which operates in water and shows a high stability during pulse measurements over 2 h. This work paves the way for the fabrication of OECT complementary circuits. Results Materials synthesis The synthetic design for developing n-type OECT materials required a narrow band gap donor acceptor copolymer with polar side chains. To this end, we focus on the highly electron-deficient 2,6-dibromonaphthalene-1,4,5,8-tetracarboxylic diimide (NDI) monomer which can easily be copolymerized with electron-rich thiophene based co-monomers. The synthesis of linear glycol chains with several ethylene glycol repeating units and an amine end-group which is needed for the imide formation is usually time consuming and involves several reaction steps 20 . Here, we present a simple reaction where the NDI monomer gNDI-Br 2 ( 2 , Fig. 1 ) with long linear ethylene glycol-based side chains is synthesized in a one-pot reaction from commercial reagents. The amino alcohol forms an ester with 2-[2-(2-methoxyethoxy)ethoxy]acetic acid while the dianhydride 1 is converted to the diimide monomer 2 . Stille polymerization of 2 in chlorobenzene with 5,5′-bis(trimethylstannyl)-2,2′-bithiophene 3b and the (2-(2-(2-methoxyethoxy)ethoxy)ethoxy) analogue 3a with 2 mol% Pd 2 (dba) 3 and P( o -tol) 3 was carried out to synthesize polymers p(gNDI-T2) and p(gNDI-gT2), respectively, following a procedure for semiconducting polymers with polar side chains 21 . The solubility of the polymer in polar solvents increases with the amount of glycol side chains. Polymer p(gNDI-gT2) is soluble in chloroform, 1,1,2,2-tetrachloroethane and dimethylformamide while p(gNDI-T2), with lower glycol side chain density, can only be dissolved in hot 1,1,2,2-tetrachloroethane. End-capping of p(gNDI-gT2) with mono-functionalized thiophenes was performed to remove bromo or organo-tin polymer endgroups. Due to a low solubility of p(gNDI-T2) in chlorobenzene it was not possible to carry out the end-capping procedure. The molecular weight", "role": "user" }, { "content": "Scientists have created a material that could make reading biological signals, from heartbeats to brainwaves, much more sensitive. Organic electrochemical transistors (OECTs) are designed to measure signals created by electrical impulses in the body, such as heartbeats or brainwaves. However, they are currently only able to measure certain signals. Now researchers led by a team from Imperial College London have created a material that measures signals in a different way to traditional OECTs that they believe could be used in complementary circuits, paving the way for new biological sensor technologies. Semiconducting materials can conduct electronic signals, carried by either electrons or their positively charged counterparts, called holes. Holes in this sense are the absence of electrons - the spaces within atoms that can be filled by them. Electrons can be passed between atoms but so can holes. Materials that use primarily hole-driven transport are called 'p-type' materials, and those that use primarily electron-driven transport are called, and 'n-type' materials. An 'ambipolar' material is the combination of both types, allowing the transport of holes and electrons within the same material, leading to potentially more sensitive devices. However, it has not previously been possible to create ambipolar materials that work in the body. Credit: Imperial College London The current most sensitive OECTs use a material where only holes are transported. Electron transport in these devices however has not been possible, since n-type materials readily break down in water-based environments like the human body. But in research published today in Nature Communications, the team have demonstrated the first ambipolar OECT that can conduct electrons as well as holes with high stability in water-based solutions. The team overcame the seemingly inherent instability of n-type materials in water by designing new structures that prevent electrons from engaging in side-reactions, which would otherwise degrade the device. These new devices can detect positively charged sodium and potassium ions, important for neuron activities in the body, particularly in the brain. In the future, the team hope to be able to create materials tuned to detect particular ions, allowing ion-specific signals to be detected. Lead author Alexander Giovannitti, a PhD student under the supervision of Professor Iain McCulloch, from the Department of Chemistry and Centre for Plastic Electronics at Imperial said: \"Proving that an n-type organic electrochemical transistor can operate in water paves the way for new sensor electronics with improved sensitivity. \"It will also allow new applications, particularly in the sensing of biologically important positive ions, which are not feasible with current devices. For example, these materials might be able to detect abnormalities in sodium and potassium ion concentrations in the brain, responsible for neuron diseases such as epilepsy.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Organic electrochemical transistors (OECTs) are receiving significant attention due to their ability to efficiently transduce biological signals. A major limitation of this technology is that only p-type materials have been reported, which precludes the development of complementary circuits, and limits sensor technologies. Here, we report the first ever n-type OECT, with relatively balanced ambipolar charge transport characteristics based on a polymer that supports both hole and electron transport along its backbone when doped through an aqueous electrolyte and in the presence of oxygen. This new semiconducting polymer is designed specifically to facilitate ion transport and promote electrochemical doping. Stability measurements in water show no degradation when tested for 2 h under continuous cycling. This demonstration opens the possibility to develop complementary circuits based on OECTs and to improve the sophistication of bioelectronic devices. Introduction Interest in mixed conduction, as in recent bioelectronic and energy applications, has led to a surge in novel organic electronic materials and devices. One characteristic example is an organic electrochemical transistor (OECT), in which ions from an electrolyte penetrate a polymer film and modulate its conductivity. As a result, OECTs can efficiently transduce ionic signals into electronic ones, making them ideal biological sensing elements. OECTs can be fabricated from biocompatible materials 1 , 2 and operate in aqueous environments, which enables recordings in vivo and in vitro 1 , 3 , 4 , 5 . The advantage of OECT-based sensors compared to organic field-effect transistor (OFET)-based sensors is that ions in the former interact with the whole volume of the active material, giving rise to lower impedance and higher transconductance 6 . As a result, the performance of an OECT, defined by the efficiency with which it transduces a voltage modulation at the gate ( V G ) into a current modulation in the channel ( I D ), depends on the thickness of the active layer. This is contrary to OFETs, which rely on the interfacial accumulation of charges and are thus limited by the double layer capacitance 5 , 6 . In particular, the transconductance ( g m =∂ I D /∂ V G ) of OECTs operated in an aqueous environment can reach more than 3.0 mS (refs 3 , 7 , 8 ) at low biases, enabling their use in clinical neuroscience applications, including electrocardiography 3 , 9 , electroencephalography 6 , 9 or neural stimulation 4 . The current state-of-the-art active material for OECTs is the conducting polymer blend poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) PEDOT:PSS, where the material is doped in its native state, requiring the OECT to be operated in depletion mode 3 , 8 . The operation of an OECT in accumulation mode allows for low power consumption devices with high ON/OFF ratios. The ability of a polythiophene-based polyelectrolyte to operate as an accumulation mode OECT has previously been demonstrated with transconductances of up to 2.0 mS (ref. 10 ). Intermediate materials, where conducting and semiconducting polymers were blended together, have also been reported 11 . To date, however, all reported OECTs have relied on hole transport (p-type), while development of electron transporting (n-type) or ambipolar OECTs has been ignored. Such OECTs would allow the development of complementary circuits and will dramatically improve the sophistication of bioelectronics devices. However, the development of appropriate semiconductor materials is a major challenge: It requires that a material be both stable in an aqueous electrolyte, and that it be reversibly reduced and oxidized within the electrochemical window imparted by that electrolyte. This requires the design of materials that concurrently have a high electron affinity (EA), a low ionization potential and the capacity for facile ion penetration. In addition to their ability to be oxidized and reduced efficiently, these materials should also show high electron and hole mobilities in order to sustain large electronic currents and yield efficient current modulation in an OECT format. Recently, the electron mobility of n-type polymers has increased rapidly, reaching values of more than 1.0 cm −2 V −1 s −1 in OFETs, 12 , 13 , 14 , 15 , 16 , 17 thus enabling n-type OECTs operating in accumulation mode. While air stable n-type materials for OFETs have been reported 18 , 19 , these materials usually degrade when operated in water. In this work, we report the first n-type and ambipolar OECT which operates in water and shows a high stability during pulse measurements over 2 h. This work paves the way for the fabrication of OECT complementary circuits. Results Materials synthesis The synthetic design for developing n-type OECT materials required a narrow band gap donor acceptor copolymer with polar side chains. To this end, we focus on the highly electron-deficient 2,6-dibromonaphthalene-1,4,5,8-tetracarboxylic diimide (NDI) monomer which can easily be copolymerized with electron-rich thiophene based co-monomers. The synthesis of linear glycol chains with several ethylene glycol repeating units and an amine end-group which is needed for the imide formation is usually time consuming and involves several reaction steps 20 . Here, we present a simple reaction where the NDI monomer gNDI-Br 2 ( 2 , Fig. 1 ) with long linear ethylene glycol-based side chains is synthesized in a one-pot reaction from commercial reagents. The amino alcohol forms an ester with 2-[2-(2-methoxyethoxy)ethoxy]acetic acid while the dianhydride 1 is converted to the diimide monomer 2 . Stille polymerization of 2 in chlorobenzene with 5,5′-bis(trimethylstannyl)-2,2′-bithiophene 3b and the (2-(2-(2-methoxyethoxy)ethoxy)ethoxy) analogue 3a with 2 mol% Pd 2 (dba) 3 and P( o -tol) 3 was carried out to synthesize polymers p(gNDI-T2) and p(gNDI-gT2), respectively, following a procedure for semiconducting polymers with polar side chains 21 . The solubility of the polymer in polar solvents increases with the amount of glycol side chains. Polymer p(gNDI-gT2) is soluble in chloroform, 1,1,2,2-tetrachloroethane and dimethylformamide while p(gNDI-T2), with lower glycol side chain density, can only be dissolved in hot 1,1,2,2-tetrachloroethane. End-capping of p(gNDI-gT2) with mono-functionalized thiophenes was performed to remove bromo or organo-tin polymer endgroups. Due to a low solubility of p(gNDI-T2) in chlorobenzene it was not possible to carry out the end-capping procedure. The molecular weight<|im_end|> <|im_start|>assistant Scientists have created a material that could make reading biological signals, from heartbeats to brainwaves, much more sensitive. Organic electrochemical transistors (OECTs) are designed to measure signals created by electrical impulses in the body, such as heartbeats or brainwaves. However, they are currently only able to measure certain signals. Now researchers led by a team from Imperial College London have created a material that measures signals in a different way to traditional OECTs that they believe could be used in complementary circuits, paving the way for new biological sensor technologies. Semiconducting materials can conduct electronic signals, carried by either electrons or their positively charged counterparts, called holes. Holes in this sense are the absence of electrons - the spaces within atoms that can be filled by them. Electrons can be passed between atoms but so can holes. Materials that use primarily hole-driven transport are called 'p-type' materials, and those that use primarily electron-driven transport are called, and 'n-type' materials. An 'ambipolar' material is the combination of both types, allowing the transport of holes and electrons within the same material, leading to potentially more sensitive devices. However, it has not previously been possible to create ambipolar materials that work in the body. Credit: Imperial College London The current most sensitive OECTs use a material where only holes are transported. Electron transport in these devices however has not been possible, since n-type materials readily break down in water-based environments like the human body. But in research published today in Nature Communications, the team have demonstrated the first ambipolar OECT that can conduct electrons as well as holes with high stability in water-based solutions. The team overcame the seemingly inherent instability of n-type materials in water by designing new structures that prevent electrons from engaging in side-reactions, which would otherwise degrade the device. These new devices can detect positively charged sodium and potassium ions, important for neuron activities in the body, particularly in the brain. In the future, the team hope to be able to create materials tuned to detect particular ions, allowing ion-specific signals to be detected. Lead author Alexander Giovannitti, a PhD student under the supervision of Professor Iain McCulloch, from the Department of Chemistry and Centre for Plastic Electronics at Imperial said: "Proving that an n-type organic electrochemical transistor can operate in water paves the way for new sensor electronics with improved sensitivity. "It will also allow new applications, particularly in the sensing of biologically important positive ions, which are not feasible with current devices. For example, these materials might be able to detect abnormalities in sodium and potassium ion concentrations in the brain, responsible for neuron diseases such as epilepsy." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 44037, 25396, 32056, 1380, 380, 1105, 320, 46, 6060, 82, 8, 527, 12588, 5199, 6666, 4245, 311, 872, 5845, 311, 30820, 1380, 13677, 24156, 17738, 13, 362, 3682, 20893, 315, 420, 5557, 374, 430, 1193, 281, 10827, 7384, 617, 1027, 5068, 11, 902, 864, 7548, 279, 4500, 315, 58535, 46121, 11, 323, 13693, 12271, 14645, 13, 5810, 11, 584, 1934, 279, 1176, 3596, 308, 10827, 507, 6060, 11, 449, 12309, 24770, 9049, 575, 7569, 6900, 7710, 17910, 3196, 389, 264, 47393, 430, 11815, 2225, 14512, 323, 17130, 7710, 3235, 1202, 56527, 994, 294, 16771, 1555, 459, 66300, 788, 73396, 668, 323, 304, 279, 9546, 315, 24463, 13, 1115, 502, 5347, 1965, 1076, 287, 47393, 374, 6319, 11951, 311, 28696, 28772, 7710, 323, 12192, 25396, 32056, 97928, 13, 81238, 22323, 304, 3090, 1501, 912, 53568, 994, 12793, 369, 220, 17, 305, 1234, 19815, 33162, 13, 1115, 30816, 16264, 279, 13336, 311, 2274, 58535, 46121, 3196, 389, 507, 6060, 82, 323, 311, 7417, 279, 85536, 315, 17332, 19493, 8535, 7766, 13, 29438, 25074, 304, 9709, 390, 23985, 11, 439, 304, 3293, 17332, 19493, 8535, 323, 4907, 8522, 11, 706, 6197, 311, 264, 22531, 304, 11775, 17808, 14683, 7384, 323, 7766, 13, 3861, 29683, 3187, 374, 459, 17808, 25396, 32056, 99041, 320, 46, 6060, 705, 304, 902, 65125, 505, 459, 73396, 668, 64855, 264, 47393, 4632, 323, 1491, 6468, 1202, 98971, 13, 1666, 264, 1121, 11, 507, 6060, 82, 649, 30820, 1380, 13677, 220, 21427, 17738, 1139, 14683, 6305, 11, 3339, 1124, 10728, 24156, 60199, 5540, 13, 507, 6060, 82, 649, 387, 70554, 505, 6160, 12255, 38179, 7384, 220, 16, 1174, 220, 17, 323, 14816, 304, 66300, 788, 22484, 11, 902, 20682, 38140, 304, 41294, 323, 304, 55004, 220, 16, 1174, 220, 18, 1174, 220, 19, 1174, 220, 20, 662, 578, 9610, 315, 507, 6060, 6108, 26148, 7863, 311, 17808, 2115, 23937, 99041, 320, 12766, 1372, 7435, 31039, 26148, 374, 430, 65125, 304, 279, 4846, 16681, 449, 279, 4459, 8286, 315, 279, 4642, 3769, 11, 7231, 10205, 311, 4827, 91048, 323, 5190, 1380, 77752, 685, 220, 21, 662, 1666, 264, 1121, 11, 279, 5178, 315, 459, 507, 6060, 11, 4613, 555, 279, 15374, 449, 902, 433, 1380, 1072, 1634, 264, 22465, 67547, 520, 279, 18618, 320, 650, 480, 883, 1139, 264, 1510, 67547, 304, 279, 5613, 320, 358, 423, 7026, 14117, 389, 279, 26839, 315, 279, 4642, 6324, 13, 1115, 374, 26102, 311, 3083, 1372, 82, 11, 902, 17631, 389, 279, 958, 22974, 532, 46835, 315, 10405, 323, 527, 8617, 7347, 555, 279, 2033, 6324, 99758, 685, 220, 20, 1174, 220, 21, 662, 763, 4040, 11, 279, 1380, 77752, 685, 320, 342, 296, 284, 22447, 224, 358, 423, 611, 22447, 224, 650, 480, 883, 315, 507, 6060, 82, 24026, 304, 459, 66300, 788, 4676, 649, 5662, 810, 1109, 220, 18, 13, 15, 296, 50, 320, 16541, 220, 18, 1174, 220, 22, 1174, 220, 23, 883, 520, 3428, 50183, 11, 28462, 872, 1005, 304, 14830, 93048, 8522, 11, 2737, 25396, 5057, 72, 5814, 220, 18, 1174, 220, 24, 1174, 25396, 768, 764, 278, 5814, 220, 21, 1174, 220, 24, 477, 30828, 41959, 220, 19, 662, 578, 1510, 1614, 8838, 10826, 38921, 4642, 3769, 369, 507, 6060, 82, 374, 279, 31474, 47393, 20955, 10062, 7, 18, 11, 19, 12, 774, 88, 2963, 63059, 4223, 339, 72, 5237, 1994, 1680, 34535, 6019, 88, 1466, 288, 14643, 263, 349, 8, 94853, 1831, 93511, 1242, 11, 1405, 279, 3769, 374, 294, 16771, 304, 1202, 10068, 1614, 11, 23537, 279, 507, 6060, 311, 387, 24026, 304, 92948, 3941, 220, 18, 1174, 220, 23, 662, 578, 5784, 315, 459, 507, 6060, 304, 46835, 3941, 6276, 369, 3428, 2410, 15652, 7766, 449, 1579, 6328, 17991, 1785, 42338, 13, 578, 5845, 315, 264, 10062, 339, 72, 5237, 1994, 6108, 1499, 9188, 772, 299, 398, 668, 311, 14816, 439, 459, 46835, 3941, 507, 6060, 706, 8767, 1027, 21091, 449, 1380, 77752, 3095, 315, 709, 311, 220, 17, 13, 15, 296, 50, 320, 1116, 13, 220, 605, 7609, 61748, 7384, 11, 1405, 31474, 323, 5347, 1965, 1076, 287, 46033, 388, 1051, 55645, 3871, 11, 617, 1101, 1027, 5068, 220, 806, 662, 2057, 2457, 11, 4869, 11, 682, 5068, 507, 6060, 82, 617, 41013, 389, 14512, 7710, 320, 79, 10827, 705, 1418, 4500, 315, 17130, 67757, 320, 77, 10827, 8, 477, 9049, 575, 7569, 507, 6060, 82, 706, 1027, 12305, 13, 15483, 507, 6060, 82, 1053, 2187, 279, 4500, 315, 58535, 46121, 323, 690, 29057, 7417, 279, 85536, 315, 17332, 79666, 7766, 13, 4452, 11, 279, 4500, 315, 8475, 87836, 7384, 374, 264, 3682, 8815, 25, 1102, 7612, 430, 264, 3769, 387, 2225, 15528, 304, 459, 66300, 788, 73396, 668, 11, 323, 430, 433, 387, 17888, 6623, 11293, 323, 36172, 1534, 2949, 279, 25396, 32056, 3321, 70772, 291, 555, 430, 73396, 668, 13, 1115, 7612, 279, 2955, 315, 7384, 430, 79126, 617, 264, 1579, 17130, 51552, 320, 19657, 705, 264, 3428, 28772, 2065, 4754, 323, 279, 8824, 369, 51794, 28772, 44596, 13, 763, 5369, 311, 872, 5845, 311, 387, 36172, 1534, 323, 11293, 30820, 11, 1521, 7384, 1288, 1101, 1501, 1579, 17130, 323, 14512, 12881, 4396, 304, 2015, 311, 14201, 3544, 14683, 60701, 323, 7692, 11297, 1510, 67547, 304, 459, 507, 6060, 3645, 13, 42096, 11, 279, 17130, 31139, 315, 308, 10827, 46033, 388, 706, 7319, 19019, 11, 19261, 2819, 315, 810, 1109, 220, 16, 13, 15, 10166, 25173, 17, 650, 25173, 16, 274, 25173, 16, 304, 3083, 1372, 82, 11, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 8617, 28462, 308, 10827, 507, 6060, 82, 10565, 304, 46835, 3941, 13, 6104, 3805, 15528, 308, 10827, 7384, 369, 3083, 1372, 82, 617, 1027, 5068, 220, 972, 1174, 220, 777, 1174, 1521, 7384, 6118, 96630, 994, 24026, 304, 3090, 13, 763, 420, 990, 11, 584, 1934, 279, 1176, 308, 10827, 323, 9049, 575, 7569, 507, 6060, 902, 27149, 304, 3090, 323, 5039, 264, 1579, 20334, 2391, 28334, 22323, 927, 220, 17, 305, 13, 1115, 990, 281, 4798, 279, 1648, 369, 279, 59251, 315, 507, 6060, 58535, 46121, 13, 18591, 32009, 39975, 578, 28367, 2955, 369, 11469, 308, 10827, 507, 6060, 7384, 2631, 264, 15376, 7200, 13225, 35558, 4287, 269, 6293, 5849, 1195, 449, 25685, 3185, 27271, 13, 2057, 420, 842, 11, 584, 5357, 389, 279, 7701, 17130, 29899, 5499, 220, 17, 11, 21, 1773, 581, 442, 263, 1366, 31392, 1994, 12, 16, 11, 19, 11, 20, 11, 23, 2442, 17820, 582, 277, 2054, 88, 416, 1891, 318, 579, 320, 8225, 40, 8, 1647, 26429, 902, 649, 6847, 387, 6293, 5849, 1195, 1534, 449, 17130, 41947, 62428, 5237, 1994, 3196, 1080, 1474, 14609, 388, 13, 578, 39975, 315, 13790, 37807, 2119, 27271, 449, 3892, 8537, 64651, 37807, 2119, 40916, 8316, 323, 459, 1097, 483, 842, 4449, 902, 374, 4460, 369, 279, 737, 579, 18488, 374, 6118, 892, 35208, 323, 18065, 3892, 13010, 7504, 220, 508, 662, 5810, 11, 584, 3118, 264, 4382, 13010, 1405, 279, 452, 18091, 1647, 26429, 342, 8225, 40, 12, 6971, 220, 17, 320, 220, 17, 1174, 23966, 13, 220, 16, 883, 449, 1317, 13790, 8537, 64651, 37807, 2119, 6108, 3185, 27271, 374, 92106, 304, 264, 832, 2320, 354, 13010, 505, 8518, 312, 55975, 13, 578, 42500, 13200, 7739, 459, 1826, 261, 449, 220, 17, 42095, 17, 8172, 17, 1474, 774, 61263, 774, 61263, 8, 774, 61263, 60, 582, 5411, 13935, 1418, 279, 294, 1122, 8671, 67, 1425, 220, 16, 374, 16489, 311, 279, 1891, 318, 579, 1647, 26429, 220, 17, 662, 800, 4618, 47393, 2065, 315, 220, 17, 304, 37833, 677, 17007, 1994, 449, 220, 20, 11, 20, 39615, 12, 54681, 41689, 42972, 267, 1036, 4010, 7435, 17, 11, 17, 39615, 12, 65, 411, 72, 5237, 1994, 220, 18, 65, 323, 279, 320, 17, 8172, 17, 8172, 17, 1474, 774, 61263, 774, 61263, 8, 774, 61263, 8, 774, 61263, 8, 91343, 220, 18, 64, 449, 220, 17, 22337, 4, 393, 67, 220, 17, 320, 90555, 8, 220, 18, 323, 393, 7, 297, 482, 21220, 8, 220, 18, 574, 11953, 704, 311, 6925, 27985, 46033, 388, 281, 3348, 8225, 40, 9469, 17, 8, 323, 281, 3348, 8225, 40, 2427, 51, 17, 705, 15947, 11, 2768, 264, 10537, 369, 5347, 1965, 1076, 287, 46033, 388, 449, 25685, 3185, 27271, 220, 1691, 662, 578, 2092, 392, 1429, 315, 279, 47393, 304, 25685, 2092, 48764, 12992, 449, 279, 3392, 315, 37807, 2119, 3185, 27271, 13, 97770, 281, 3348, 8225, 40, 2427, 51, 17, 8, 374, 88045, 304, 37833, 78, 630, 11, 220, 16, 11, 16, 11, 17, 11, 17, 2442, 17820, 613, 9761, 78, 774, 2194, 323, 5213, 42972, 630, 66796, 1418, 281, 3348, 8225, 40, 9469, 17, 705, 449, 4827, 37807, 2119, 3185, 8957, 17915, 11, 649, 1193, 387, 56767, 304, 4106, 220, 16, 11, 16, 11, 17, 11, 17, 2442, 17820, 613, 9761, 78, 774, 2194, 13, 4060, 1824, 3713, 315, 281, 3348, 8225, 40, 2427, 51, 17, 8, 449, 40774, 99616, 1534, 62428, 5237, 22383, 574, 10887, 311, 4148, 94571, 78, 477, 2942, 78, 2442, 258, 47393, 842, 17171, 13, 24586, 311, 264, 3428, 2092, 392, 1429, 315, 281, 3348, 8225, 40, 9469, 17, 8, 304, 37833, 677, 17007, 1994, 433, 574, 539, 3284, 311, 6920, 704, 279, 842, 1824, 3713, 10537, 13, 578, 31206, 4785, 128257, 198, 128256, 78191, 198, 72326, 617, 3549, 264, 3769, 430, 1436, 1304, 5403, 24156, 17738, 11, 505, 4851, 1395, 1900, 311, 8271, 58365, 11, 1790, 810, 16614, 13, 44037, 25396, 32056, 1380, 380, 1105, 320, 46, 6060, 82, 8, 527, 6319, 311, 6767, 17738, 3549, 555, 20314, 87633, 304, 279, 2547, 11, 1778, 439, 4851, 1395, 1900, 477, 8271, 58365, 13, 4452, 11, 814, 527, 5131, 1193, 3025, 311, 6767, 3738, 17738, 13, 4800, 12074, 6197, 555, 264, 2128, 505, 31013, 9304, 7295, 617, 3549, 264, 3769, 430, 11193, 17738, 304, 264, 2204, 1648, 311, 8776, 507, 6060, 82, 430, 814, 4510, 1436, 387, 1511, 304, 58535, 46121, 11, 82568, 279, 1648, 369, 502, 24156, 12271, 14645, 13, 14582, 1965, 1076, 287, 7384, 649, 6929, 14683, 17738, 11, 11953, 555, 3060, 57678, 477, 872, 40646, 11684, 38495, 11, 2663, 20349, 13, 473, 7298, 304, 420, 5647, 527, 279, 19821, 315, 57678, 482, 279, 12908, 2949, 33299, 430, 649, 387, 10409, 555, 1124, 13, 10085, 26692, 649, 387, 5946, 1990, 33299, 719, 779, 649, 20349, 13, 32009, 430, 1005, 15871, 14512, 32505, 7710, 527, 2663, 364, 79, 10827, 6, 7384, 11, 323, 1884, 430, 1005, 15871, 17130, 32505, 7710, 527, 2663, 11, 323, 364, 77, 10827, 6, 7384, 13, 1556, 364, 3042, 575, 7569, 6, 3769, 374, 279, 10824, 315, 2225, 4595, 11, 10923, 279, 7710, 315, 20349, 323, 57678, 2949, 279, 1890, 3769, 11, 6522, 311, 13893, 810, 16614, 7766, 13, 4452, 11, 433, 706, 539, 8767, 1027, 3284, 311, 1893, 9049, 575, 7569, 7384, 430, 990, 304, 279, 2547, 13, 16666, 25, 31013, 9304, 7295, 578, 1510, 1455, 16614, 507, 6060, 82, 1005, 264, 3769, 1405, 1193, 20349, 527, 40460, 13, 77976, 7710, 304, 1521, 7766, 4869, 706, 539, 1027, 3284, 11, 2533, 308, 10827, 7384, 31368, 1464, 1523, 304, 3090, 6108, 22484, 1093, 279, 3823, 2547, 13, 2030, 304, 3495, 4756, 3432, 304, 22037, 26545, 11, 279, 2128, 617, 21091, 279, 1176, 9049, 575, 7569, 507, 6060, 430, 649, 6929, 57678, 439, 1664, 439, 20349, 449, 1579, 20334, 304, 3090, 6108, 10105, 13, 578, 2128, 927, 6142, 279, 23490, 38088, 56399, 315, 308, 10827, 7384, 304, 3090, 555, 30829, 502, 14726, 430, 5471, 57678, 505, 23387, 304, 3185, 5621, 4109, 11, 902, 1053, 6062, 96630, 279, 3756, 13, 4314, 502, 7766, 649, 11388, 40646, 11684, 39695, 323, 62275, 65125, 11, 3062, 369, 49384, 7640, 304, 279, 2547, 11, 8104, 304, 279, 8271, 13, 763, 279, 3938, 11, 279, 2128, 3987, 311, 387, 3025, 311, 1893, 7384, 33519, 311, 11388, 4040, 65125, 11, 10923, 28772, 19440, 17738, 311, 387, 16914, 13, 30982, 3229, 20643, 61678, 1036, 72866, 11, 264, 30661, 5575, 1234, 279, 38217, 315, 17054, 358, 467, 14583, 65688, 331, 11, 505, 279, 6011, 315, 42846, 323, 14821, 369, 37108, 38784, 520, 31013, 1071, 25, 330, 1360, 4504, 430, 459, 308, 10827, 17808, 25396, 32056, 99041, 649, 14816, 304, 3090, 281, 4798, 279, 1648, 369, 502, 12271, 31591, 449, 13241, 27541, 13, 330, 2181, 690, 1101, 2187, 502, 8522, 11, 8104, 304, 279, 60199, 315, 6160, 30450, 3062, 6928, 65125, 11, 902, 527, 539, 43303, 449, 1510, 7766, 13, 1789, 3187, 11, 1521, 7384, 2643, 387, 3025, 311, 11388, 75815, 304, 39695, 323, 62275, 28772, 32466, 304, 279, 8271, 11, 8647, 369, 49384, 19338, 1778, 439, 70655, 1210, 220, 128257, 198 ]

2,129

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Lignin causes lignocellulosic biomass recalcitrance to enzymatic hydrolysis. Engineered low-lignin plants have reduced recalcitrance but often exhibit yield penalties, offsetting their gains in fermentable sugar yield. Here, CRISPR/Cas9-generated CCR2 (−/*) line 12 poplars have one knockout CCR2 allele while the other contains a 3-bp deletion, resulting in a 114I115A-to-114T conversion in the corresponding protein. Despite having 10% less lignin, CCR2 (−/*) line 12 grows normally. On a plant basis, the saccharification efficiency of CCR2 (−/*) line 12 is increased by 25–41%, depending on the pretreatment. Analysis of monoallelic CCR2 knockout lines shows that the reduced lignin amount in CCR2 (−/*) line 12 is due to the combination of a null and the specific haploinsufficient CCR2 allele. Analysis of another CCR2 (−/*) line shows that depending on the specific CCR2 amino-acid change, lignin amount and growth can be affected to different extents. Our findings open up new possibilities for stably fine-tuning residual gene function in planta . Introduction The lignin polymer provides strength and hydrophobicity to the plant cell wall and is generally derived from the monolignols coniferyl and sinapyl alcohol and low levels of p -coumaryl alcohol. Depending on the plant species, other monomers or derivatives may also contribute to the lignin polymer 1 . After polymerization in the cell wall, the monolignols produce guaiacyl (G), syringyl (S), and p -hydroxyphenyl (H) units, respectively 1 . Engineering plants to deposit less lignin is a promising strategy to enable improved biomass processability. However, hurdles need to be overcome for the development of low-lignin elite clones for forestry applications. One hurdle is to reduce lignin amount in a stable way. For example, RNA interference (RNAi) was frequently used to downregulate the expression of lignin biosynthesis genes in poplar 2 , 3 , 4 , 5 . However, this method often results in unstable downregulation of the targeted genes 3 , 4 , 5 . As an illustration, the red xylem phenotype caused by reductions in CINNAMOYL-CoA REDUCTASE (CCR) activity, appeared in patches on debarked CCR2 -downregulated poplar stems, as a consequence of the unequal levels of gene silencing in red versus white regions 3 . Unequal gene silencing levels even appeared between individual clones of the same CCR2 -downregulated line 3 . A second hurdle is to reduce lignin amount without affecting plant development and biomass yield. For example, the CCR2 -downregulated poplars with the highest levels of CCR2 downregulation had up to 24% less lignin and an up to 104% increased enzymatic cellulose-to-glucose conversion without pretreatment 3 . Unfortunately, similar to many other plants yielding higher cellulose-to-glucose conversion levels 2 , 6 , 7 , 8 , these CCR2 -downregulated poplars suffered from a reduction of up to 51% in biomass, (entirely) offsetting their gains in fermentable sugar yield 3 . Hence, for applications, a method is desired to make plants with a stable and fine-tuned lignin amount to still achieve higher sugar yields in all replicates, but without affecting growth. To evaluate the specific role of CCR2 in poplar, CCR2 (−/−) null mutants are generated using CRISPR/Cas9. In addition to severely dwarfed CCR2 (−/−) plants, a biallelically modified line has normal growth. Here, we show that this line, named CCR2 (−/*) line 12, contains a knockout and a specific haploinsufficient CCR2 allele (114I115A-to-114T amino-acid change in the corresponding CCR2 protein sequence) that results in a uniformly distributed red xylem phenotype, a 10% reduction in lignin amount and a 25 to 41% increase in saccharification efficiency on a plant basis, depending on the applied pretreatment. Analysis of another CCR2 (−/*) line shows that, whereas multiple amino-acid changes in CCR2 can result in lower lignin content (to different extents), they will not all allow normal growth. We propose that in planta screening for combinations of a knockout and a haploinsufficient allele is a promising strategy to fine-tune the desired level of residual gene function. Results CCR2 (−/*) line 12 grows normally while having red xylem To evaluate the effect of fully knocking out CCR2 on the phenotype of poplar, we generated 21 biallelically edited CCR2 mutants in Populus tremula × P. alba by CRISPR/Cas9 using a gRNA (gRNA1) targeting the third exon of the CCR2 gene (Supplementary Fig. 1a ). The twenty lines that contained biallelic frameshift mutations in CCR2 , CCR2 (−/−) lines, were all severely dwarfed (Fig. 1 ; Supplementary Fig. 1b ). Interestingly, one biallelic mutant line did not display observable growth perturbations (Fig. 1 ). CCR2 (−/*) line 12 had a frameshift mutation (1-bp insertion) in the P. tremula CCR2 allele, and a deletion of 3 bp in the P. alba CCR2 allele, which resulted into a substitution of Ile114 and Ala115 for a Thr114 in the corresponding P. alba CCR2 protein sequence (Supplementary Figs. 1b and 2 ). The amino-acid change occurred in α4 of the CCR2 protein, but not in the active site, NAPD-binding domain, or substrate-binding pocket residues 9 , 10 , 11 . Fig. 1: Phenotype of poplar containing biallelic CCR2 mutations. Plants were grown for 11 weeks in the greenhouse. CCR2 (−/−) and CCR2 (−/*) line 12 poplars ( P. tremula × P. alba) were generated via CRISPR/Cas9 using gRNA1 (targeting the third exon of both CCR2 alleles). The status of the CCR2 alleles present in P. tremula × P. alba is denoted between the parentheses; the first one represents that of the P. tremula allele, the second one that of the P. alba allele; −, knockout; *, protein-modified. The plants shown are representative of twenty biologically independent samples for wild type and CCR2 (−/−). One plant was available for CCR2 (−/*) line 12. Scale bar = 10 cm. Full size image To evaluate the growth and xylem phenotypes of CCR2 (−/*) line 12, wild type, and CCR2 (−/*) line 12 were clonally propagated to generate multiple biological replicates. The replicates were grown in the greenhouse for a period of 20 weeks. Plant height was followed weekly, and by the end of the growth period, the trees were harvested, and biomass parameters", "role": "user" }, { "content": "Researchers led by prof. Wout Boerjan (VIB-UGent Center for Plant Systems Biology) have discovered a way to stably finetune the amount of lignin in poplar by applying CRISPR/Cas9 technology. Lignin is one of the main structural substances in plants and it makes processing wood into, for example, paper difficult. This study is an important breakthrough in the development of wood resources for the production of paper with a lower carbon footprint, biofuels, and other bio-based materials. Their work, in collaboration with VIVES University College (Roeselare, Belgium) and University of Wisconsin (U.S.) appears in Nature Communications. Today's fossil-based economy results in a net increase of CO2 in the Earth's atmosphere and is a major cause of global climate change. To counter this, a shift toward a circular and bio-based economy is essential. Woody biomass can play a crucial role in such a bio-based economy by serving as a renewable and carbon-neutral resource for the production of many chemicals. Unfortunately, the presence of lignin hinders the processing of wood into bio-based products. Prof. Wout Boerjan (VIB-UGent) said, \"A few years ago, we performed a field trial with poplars that were engineered to make wood containing less lignin. Most plants showed large improvements in processing efficiency for many possible applications. The downside, however, was that the reduction in lignin accomplished with the technology we used then—RNA interference—was unstable and the trees grew less tall.\" New tools Undeterred, the researchers went looking for a solution. They employed the recent CRISPR/Cas9 technology in poplar to lower the lignin amount in a stable way, without causing a biomass yield penalty. In other words, the trees grew just as well and as tall as those without genetic changes. Dr. Barbara De Meester (VIB-UGent) commented, \"Poplar is a diploid species, meaning every gene is present in two copies. Using CRISPR/Cas9, we introduced specific changes in both copies of a gene that is crucial for the biosynthesis of lignin. We inactivated one copy of the gene, and only partially inactivated the other. The resulting poplar line had a stable 10% reduction in lignin amount while it grew normally in the greenhouse. Wood from the engineered trees had an up to 41% increase in processing efficiency\". Dr. Ruben Vanholme (VIB-UGent) noted, \"The mutations that we have introduced through CRISPR/Cas9 are similar to those that spontaneously arise in nature. The advantage of the CRISPR/Cas9 method is that the beneficial mutations can be directly introduced into the DNA of highly productive tree varieties in only a fraction of the time it would take by a classical breeding strategy.\" The applications of this method are not only restricted to lignin but might also be useful to engineer other traits in crops, providing a versatile new breeding tool to improve agricultural productivity. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Lignin causes lignocellulosic biomass recalcitrance to enzymatic hydrolysis. Engineered low-lignin plants have reduced recalcitrance but often exhibit yield penalties, offsetting their gains in fermentable sugar yield. Here, CRISPR/Cas9-generated CCR2 (−/*) line 12 poplars have one knockout CCR2 allele while the other contains a 3-bp deletion, resulting in a 114I115A-to-114T conversion in the corresponding protein. Despite having 10% less lignin, CCR2 (−/*) line 12 grows normally. On a plant basis, the saccharification efficiency of CCR2 (−/*) line 12 is increased by 25–41%, depending on the pretreatment. Analysis of monoallelic CCR2 knockout lines shows that the reduced lignin amount in CCR2 (−/*) line 12 is due to the combination of a null and the specific haploinsufficient CCR2 allele. Analysis of another CCR2 (−/*) line shows that depending on the specific CCR2 amino-acid change, lignin amount and growth can be affected to different extents. Our findings open up new possibilities for stably fine-tuning residual gene function in planta . Introduction The lignin polymer provides strength and hydrophobicity to the plant cell wall and is generally derived from the monolignols coniferyl and sinapyl alcohol and low levels of p -coumaryl alcohol. Depending on the plant species, other monomers or derivatives may also contribute to the lignin polymer 1 . After polymerization in the cell wall, the monolignols produce guaiacyl (G), syringyl (S), and p -hydroxyphenyl (H) units, respectively 1 . Engineering plants to deposit less lignin is a promising strategy to enable improved biomass processability. However, hurdles need to be overcome for the development of low-lignin elite clones for forestry applications. One hurdle is to reduce lignin amount in a stable way. For example, RNA interference (RNAi) was frequently used to downregulate the expression of lignin biosynthesis genes in poplar 2 , 3 , 4 , 5 . However, this method often results in unstable downregulation of the targeted genes 3 , 4 , 5 . As an illustration, the red xylem phenotype caused by reductions in CINNAMOYL-CoA REDUCTASE (CCR) activity, appeared in patches on debarked CCR2 -downregulated poplar stems, as a consequence of the unequal levels of gene silencing in red versus white regions 3 . Unequal gene silencing levels even appeared between individual clones of the same CCR2 -downregulated line 3 . A second hurdle is to reduce lignin amount without affecting plant development and biomass yield. For example, the CCR2 -downregulated poplars with the highest levels of CCR2 downregulation had up to 24% less lignin and an up to 104% increased enzymatic cellulose-to-glucose conversion without pretreatment 3 . Unfortunately, similar to many other plants yielding higher cellulose-to-glucose conversion levels 2 , 6 , 7 , 8 , these CCR2 -downregulated poplars suffered from a reduction of up to 51% in biomass, (entirely) offsetting their gains in fermentable sugar yield 3 . Hence, for applications, a method is desired to make plants with a stable and fine-tuned lignin amount to still achieve higher sugar yields in all replicates, but without affecting growth. To evaluate the specific role of CCR2 in poplar, CCR2 (−/−) null mutants are generated using CRISPR/Cas9. In addition to severely dwarfed CCR2 (−/−) plants, a biallelically modified line has normal growth. Here, we show that this line, named CCR2 (−/*) line 12, contains a knockout and a specific haploinsufficient CCR2 allele (114I115A-to-114T amino-acid change in the corresponding CCR2 protein sequence) that results in a uniformly distributed red xylem phenotype, a 10% reduction in lignin amount and a 25 to 41% increase in saccharification efficiency on a plant basis, depending on the applied pretreatment. Analysis of another CCR2 (−/*) line shows that, whereas multiple amino-acid changes in CCR2 can result in lower lignin content (to different extents), they will not all allow normal growth. We propose that in planta screening for combinations of a knockout and a haploinsufficient allele is a promising strategy to fine-tune the desired level of residual gene function. Results CCR2 (−/*) line 12 grows normally while having red xylem To evaluate the effect of fully knocking out CCR2 on the phenotype of poplar, we generated 21 biallelically edited CCR2 mutants in Populus tremula × P. alba by CRISPR/Cas9 using a gRNA (gRNA1) targeting the third exon of the CCR2 gene (Supplementary Fig. 1a ). The twenty lines that contained biallelic frameshift mutations in CCR2 , CCR2 (−/−) lines, were all severely dwarfed (Fig. 1 ; Supplementary Fig. 1b ). Interestingly, one biallelic mutant line did not display observable growth perturbations (Fig. 1 ). CCR2 (−/*) line 12 had a frameshift mutation (1-bp insertion) in the P. tremula CCR2 allele, and a deletion of 3 bp in the P. alba CCR2 allele, which resulted into a substitution of Ile114 and Ala115 for a Thr114 in the corresponding P. alba CCR2 protein sequence (Supplementary Figs. 1b and 2 ). The amino-acid change occurred in α4 of the CCR2 protein, but not in the active site, NAPD-binding domain, or substrate-binding pocket residues 9 , 10 , 11 . Fig. 1: Phenotype of poplar containing biallelic CCR2 mutations. Plants were grown for 11 weeks in the greenhouse. CCR2 (−/−) and CCR2 (−/*) line 12 poplars ( P. tremula × P. alba) were generated via CRISPR/Cas9 using gRNA1 (targeting the third exon of both CCR2 alleles). The status of the CCR2 alleles present in P. tremula × P. alba is denoted between the parentheses; the first one represents that of the P. tremula allele, the second one that of the P. alba allele; −, knockout; *, protein-modified. The plants shown are representative of twenty biologically independent samples for wild type and CCR2 (−/−). One plant was available for CCR2 (−/*) line 12. Scale bar = 10 cm. Full size image To evaluate the growth and xylem phenotypes of CCR2 (−/*) line 12, wild type, and CCR2 (−/*) line 12 were clonally propagated to generate multiple biological replicates. The replicates were grown in the greenhouse for a period of 20 weeks. Plant height was followed weekly, and by the end of the growth period, the trees were harvested, and biomass parameters<|im_end|> <|im_start|>assistant Researchers led by prof. Wout Boerjan (VIB-UGent Center for Plant Systems Biology) have discovered a way to stably finetune the amount of lignin in poplar by applying CRISPR/Cas9 technology. Lignin is one of the main structural substances in plants and it makes processing wood into, for example, paper difficult. This study is an important breakthrough in the development of wood resources for the production of paper with a lower carbon footprint, biofuels, and other bio-based materials. Their work, in collaboration with VIVES University College (Roeselare, Belgium) and University of Wisconsin (U.S.) appears in Nature Communications. Today's fossil-based economy results in a net increase of CO2 in the Earth's atmosphere and is a major cause of global climate change. To counter this, a shift toward a circular and bio-based economy is essential. Woody biomass can play a crucial role in such a bio-based economy by serving as a renewable and carbon-neutral resource for the production of many chemicals. Unfortunately, the presence of lignin hinders the processing of wood into bio-based products. Prof. Wout Boerjan (VIB-UGent) said, "A few years ago, we performed a field trial with poplars that were engineered to make wood containing less lignin. Most plants showed large improvements in processing efficiency for many possible applications. The downside, however, was that the reduction in lignin accomplished with the technology we used then—RNA interference—was unstable and the trees grew less tall." New tools Undeterred, the researchers went looking for a solution. They employed the recent CRISPR/Cas9 technology in poplar to lower the lignin amount in a stable way, without causing a biomass yield penalty. In other words, the trees grew just as well and as tall as those without genetic changes. Dr. Barbara De Meester (VIB-UGent) commented, "Poplar is a diploid species, meaning every gene is present in two copies. Using CRISPR/Cas9, we introduced specific changes in both copies of a gene that is crucial for the biosynthesis of lignin. We inactivated one copy of the gene, and only partially inactivated the other. The resulting poplar line had a stable 10% reduction in lignin amount while it grew normally in the greenhouse. Wood from the engineered trees had an up to 41% increase in processing efficiency". Dr. Ruben Vanholme (VIB-UGent) noted, "The mutations that we have introduced through CRISPR/Cas9 are similar to those that spontaneously arise in nature. The advantage of the CRISPR/Cas9 method is that the beneficial mutations can be directly introduced into the DNA of highly productive tree varieties in only a fraction of the time it would take by a classical breeding strategy." The applications of this method are not only restricted to lignin but might also be useful to engineer other traits in crops, providing a versatile new breeding tool to improve agricultural productivity. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 445, 625, 258, 11384, 72700, 511, 616, 29752, 292, 58758, 1421, 17356, 22288, 685, 311, 32011, 780, 17055, 398, 14744, 13, 8364, 12616, 3428, 2922, 625, 258, 11012, 617, 11293, 1421, 17356, 22288, 685, 719, 3629, 31324, 7692, 31086, 11, 4445, 1303, 872, 20192, 304, 68736, 481, 13465, 7692, 13, 5810, 11, 12904, 1669, 6616, 11547, 300, 24, 16581, 356, 9150, 17, 320, 34363, 1075, 8, 1584, 220, 717, 2477, 75, 1590, 617, 832, 77173, 356, 9150, 17, 70510, 1418, 279, 1023, 5727, 264, 220, 18, 1481, 79, 37166, 11, 13239, 304, 264, 220, 8011, 40, 7322, 32, 4791, 12, 8011, 51, 14747, 304, 279, 12435, 13128, 13, 18185, 3515, 220, 605, 4, 2753, 72700, 258, 11, 356, 9150, 17, 320, 34363, 1075, 8, 1584, 220, 717, 28815, 14614, 13, 1952, 264, 6136, 8197, 11, 279, 11347, 1799, 2461, 15374, 315, 356, 9150, 17, 320, 34363, 1075, 8, 1584, 220, 717, 374, 7319, 555, 220, 914, 4235, 3174, 13689, 11911, 389, 279, 4509, 35320, 13, 18825, 315, 40774, 5164, 416, 356, 9150, 17, 77173, 5238, 5039, 430, 279, 11293, 72700, 258, 3392, 304, 356, 9150, 17, 320, 34363, 1075, 8, 1584, 220, 717, 374, 4245, 311, 279, 10824, 315, 264, 854, 323, 279, 3230, 46900, 385, 1354, 27781, 356, 9150, 17, 70510, 13, 18825, 315, 2500, 356, 9150, 17, 320, 34363, 1075, 8, 1584, 5039, 430, 11911, 389, 279, 3230, 356, 9150, 17, 42500, 38698, 307, 2349, 11, 72700, 258, 3392, 323, 6650, 649, 387, 11754, 311, 2204, 92589, 13, 5751, 14955, 1825, 709, 502, 24525, 369, 357, 2915, 7060, 2442, 38302, 33247, 15207, 734, 304, 82765, 662, 29438, 578, 72700, 258, 47393, 5825, 8333, 323, 17055, 764, 31906, 488, 311, 279, 6136, 2849, 7147, 323, 374, 8965, 14592, 505, 279, 1647, 337, 625, 3145, 390, 333, 46125, 323, 7589, 391, 4010, 13200, 323, 3428, 5990, 315, 281, 482, 23045, 1563, 75, 13200, 13, 40730, 389, 279, 6136, 9606, 11, 1023, 1647, 69638, 477, 43645, 1253, 1101, 17210, 311, 279, 72700, 258, 47393, 220, 16, 662, 4740, 47393, 2065, 304, 279, 2849, 7147, 11, 279, 1647, 337, 625, 3145, 8356, 1709, 2192, 2826, 75, 320, 38, 705, 6705, 12928, 4010, 320, 50, 705, 323, 281, 482, 67229, 4223, 15112, 4010, 320, 39, 8, 8316, 11, 15947, 220, 16, 662, 17005, 11012, 311, 16946, 2753, 72700, 258, 374, 264, 26455, 8446, 311, 7431, 13241, 58758, 1920, 2968, 13, 4452, 11, 73635, 1205, 311, 387, 23075, 369, 279, 4500, 315, 3428, 2922, 625, 258, 21342, 67007, 369, 88134, 8522, 13, 3861, 81783, 374, 311, 8108, 72700, 258, 3392, 304, 264, 15528, 1648, 13, 1789, 3187, 11, 41214, 32317, 320, 31820, 72, 8, 574, 14134, 1511, 311, 1523, 1610, 6468, 279, 7645, 315, 72700, 258, 49554, 74767, 21389, 304, 2477, 14115, 220, 17, 1174, 220, 18, 1174, 220, 19, 1174, 220, 20, 662, 4452, 11, 420, 1749, 3629, 3135, 304, 45311, 1523, 1610, 2987, 315, 279, 17550, 21389, 220, 18, 1174, 220, 19, 1174, 220, 20, 662, 1666, 459, 40134, 11, 279, 2579, 865, 982, 76, 82423, 9057, 555, 47311, 304, 356, 691, 45, 1428, 46, 57070, 87271, 32, 26895, 10834, 4157, 320, 70246, 8, 5820, 11, 9922, 304, 29760, 389, 4316, 43161, 356, 9150, 17, 482, 2996, 81722, 2477, 14115, 44814, 11, 439, 264, 29774, 315, 279, 78295, 5990, 315, 15207, 5554, 11627, 304, 2579, 19579, 4251, 13918, 220, 18, 662, 39783, 1788, 15207, 5554, 11627, 5990, 1524, 9922, 1990, 3927, 67007, 315, 279, 1890, 356, 9150, 17, 482, 2996, 81722, 1584, 220, 18, 662, 362, 2132, 81783, 374, 311, 8108, 72700, 258, 3392, 2085, 28987, 6136, 4500, 323, 58758, 7692, 13, 1789, 3187, 11, 279, 356, 9150, 17, 482, 2996, 81722, 2477, 75, 1590, 449, 279, 8592, 5990, 315, 356, 9150, 17, 1523, 1610, 2987, 1047, 709, 311, 220, 1187, 4, 2753, 72700, 258, 323, 459, 709, 311, 220, 6849, 4, 7319, 32011, 780, 70002, 974, 4791, 70750, 94697, 14747, 2085, 4509, 35320, 220, 18, 662, 19173, 11, 4528, 311, 1690, 1023, 11012, 78504, 5190, 70002, 974, 4791, 70750, 94697, 14747, 5990, 220, 17, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 1174, 1521, 356, 9150, 17, 482, 2996, 81722, 2477, 75, 1590, 16654, 505, 264, 14278, 315, 709, 311, 220, 3971, 4, 304, 58758, 11, 320, 306, 556, 398, 8, 4445, 1303, 872, 20192, 304, 68736, 481, 13465, 7692, 220, 18, 662, 32140, 11, 369, 8522, 11, 264, 1749, 374, 12974, 311, 1304, 11012, 449, 264, 15528, 323, 7060, 2442, 49983, 72700, 258, 3392, 311, 2103, 11322, 5190, 13465, 36508, 304, 682, 29641, 988, 11, 719, 2085, 28987, 6650, 13, 2057, 15806, 279, 3230, 3560, 315, 356, 9150, 17, 304, 2477, 14115, 11, 356, 9150, 17, 320, 34363, 14, 34363, 8, 854, 88754, 527, 8066, 1701, 12904, 1669, 6616, 11547, 300, 24, 13, 763, 5369, 311, 35906, 50561, 291, 356, 9150, 17, 320, 34363, 14, 34363, 8, 11012, 11, 264, 293, 532, 273, 416, 750, 11041, 1584, 706, 4725, 6650, 13, 5810, 11, 584, 1501, 430, 420, 1584, 11, 7086, 356, 9150, 17, 320, 34363, 1075, 8, 1584, 220, 717, 11, 5727, 264, 77173, 323, 264, 3230, 46900, 385, 1354, 27781, 356, 9150, 17, 70510, 320, 8011, 40, 7322, 32, 4791, 12, 8011, 51, 42500, 38698, 307, 2349, 304, 279, 12435, 356, 9150, 17, 13128, 8668, 8, 430, 3135, 304, 264, 78909, 4332, 2579, 865, 982, 76, 82423, 11, 264, 220, 605, 4, 14278, 304, 72700, 258, 3392, 323, 264, 220, 914, 311, 220, 3174, 4, 5376, 304, 11347, 1799, 2461, 15374, 389, 264, 6136, 8197, 11, 11911, 389, 279, 9435, 4509, 35320, 13, 18825, 315, 2500, 356, 9150, 17, 320, 34363, 1075, 8, 1584, 5039, 430, 11, 20444, 5361, 42500, 38698, 307, 4442, 304, 356, 9150, 17, 649, 1121, 304, 4827, 72700, 258, 2262, 320, 998, 2204, 92589, 705, 814, 690, 539, 682, 2187, 4725, 6650, 13, 1226, 30714, 430, 304, 82765, 23061, 369, 28559, 315, 264, 77173, 323, 264, 46900, 385, 1354, 27781, 70510, 374, 264, 26455, 8446, 311, 7060, 2442, 2957, 279, 12974, 2237, 315, 33247, 15207, 734, 13, 18591, 356, 9150, 17, 320, 34363, 1075, 8, 1584, 220, 717, 28815, 14614, 1418, 3515, 2579, 865, 982, 76, 2057, 15806, 279, 2515, 315, 7373, 50244, 704, 356, 9150, 17, 389, 279, 82423, 315, 2477, 14115, 11, 584, 8066, 220, 1691, 293, 532, 273, 416, 750, 19685, 356, 9150, 17, 88754, 304, 10466, 19990, 18659, 5724, 25800, 393, 13, 453, 4749, 555, 12904, 1669, 6616, 11547, 300, 24, 1701, 264, 342, 31820, 320, 70, 31820, 16, 8, 25103, 279, 4948, 99844, 315, 279, 356, 9150, 17, 15207, 320, 10254, 67082, 23966, 13, 220, 16, 64, 7609, 578, 17510, 5238, 430, 13282, 293, 532, 273, 416, 14418, 48933, 34684, 304, 356, 9150, 17, 1174, 356, 9150, 17, 320, 34363, 14, 34363, 8, 5238, 11, 1051, 682, 35906, 50561, 291, 320, 30035, 13, 220, 16, 2652, 99371, 23966, 13, 220, 16, 65, 7609, 58603, 11, 832, 293, 532, 273, 416, 61618, 1584, 1550, 539, 3113, 40635, 6650, 18713, 9225, 811, 320, 30035, 13, 220, 16, 7609, 356, 9150, 17, 320, 34363, 1075, 8, 1584, 220, 717, 1047, 264, 14418, 48933, 27472, 320, 16, 1481, 79, 37027, 8, 304, 279, 393, 13, 18659, 5724, 356, 9150, 17, 70510, 11, 323, 264, 37166, 315, 220, 18, 27783, 304, 279, 393, 13, 453, 4749, 356, 9150, 17, 70510, 11, 902, 19543, 1139, 264, 50068, 315, 358, 273, 8011, 323, 89762, 7322, 369, 264, 30665, 8011, 304, 279, 12435, 393, 13, 453, 4749, 356, 9150, 17, 13128, 8668, 320, 10254, 67082, 435, 14801, 13, 220, 16, 65, 323, 220, 17, 7609, 578, 42500, 38698, 307, 2349, 10222, 304, 19581, 19, 315, 279, 356, 9150, 17, 13128, 11, 719, 539, 304, 279, 4642, 2816, 11, 452, 2599, 35, 65500, 8106, 11, 477, 54057, 65500, 18301, 71783, 220, 24, 1174, 220, 605, 1174, 220, 806, 662, 23966, 13, 220, 16, 25, 69883, 4249, 315, 2477, 14115, 8649, 293, 532, 273, 416, 356, 9150, 17, 34684, 13, 50298, 1051, 15042, 369, 220, 806, 5672, 304, 279, 37647, 13, 356, 9150, 17, 320, 34363, 14, 34363, 8, 323, 356, 9150, 17, 320, 34363, 1075, 8, 1584, 220, 717, 2477, 75, 1590, 320, 393, 13, 18659, 5724, 25800, 393, 13, 453, 4749, 8, 1051, 8066, 4669, 12904, 1669, 6616, 11547, 300, 24, 1701, 342, 31820, 16, 320, 5775, 287, 279, 4948, 99844, 315, 2225, 356, 9150, 17, 98260, 570, 578, 2704, 315, 279, 356, 9150, 17, 98260, 3118, 304, 393, 13, 18659, 5724, 25800, 393, 13, 453, 4749, 374, 3453, 9437, 1990, 279, 75075, 26, 279, 1176, 832, 11105, 430, 315, 279, 393, 13, 18659, 5724, 70510, 11, 279, 2132, 832, 430, 315, 279, 393, 13, 453, 4749, 70510, 26, 25173, 11, 77173, 26, 12039, 13128, 17515, 1908, 13, 578, 11012, 6982, 527, 18740, 315, 17510, 6160, 30450, 9678, 10688, 369, 8545, 955, 323, 356, 9150, 17, 320, 34363, 14, 34363, 570, 3861, 6136, 574, 2561, 369, 356, 9150, 17, 320, 34363, 1075, 8, 1584, 220, 717, 13, 25635, 3703, 284, 220, 605, 10166, 13, 8797, 1404, 2217, 2057, 15806, 279, 6650, 323, 865, 982, 76, 14345, 22583, 315, 356, 9150, 17, 320, 34363, 1075, 8, 1584, 220, 717, 11, 8545, 955, 11, 323, 356, 9150, 17, 320, 34363, 1075, 8, 1584, 220, 717, 1051, 1206, 263, 750, 86150, 311, 7068, 5361, 24156, 29641, 988, 13, 578, 29641, 988, 1051, 15042, 304, 279, 37647, 369, 264, 4261, 315, 220, 508, 5672, 13, 18317, 2673, 574, 8272, 17496, 11, 323, 555, 279, 842, 315, 279, 6650, 4261, 11, 279, 12690, 1051, 67572, 11, 323, 58758, 5137, 128257, 198, 128256, 78191, 198, 60210, 6197, 555, 2848, 13, 468, 412, 2577, 261, 23685, 320, 53, 3336, 12, 3014, 306, 5955, 369, 18317, 15264, 40023, 8, 617, 11352, 264, 1648, 311, 357, 2915, 1913, 295, 2957, 279, 3392, 315, 72700, 258, 304, 2477, 14115, 555, 19486, 12904, 1669, 6616, 11547, 300, 24, 5557, 13, 445, 625, 258, 374, 832, 315, 279, 1925, 24693, 33155, 304, 11012, 323, 433, 3727, 8863, 7732, 1139, 11, 369, 3187, 11, 5684, 5107, 13, 1115, 4007, 374, 459, 3062, 42445, 304, 279, 4500, 315, 7732, 5070, 369, 279, 5788, 315, 5684, 449, 264, 4827, 12782, 43972, 11, 17332, 33721, 2053, 11, 323, 1023, 17332, 6108, 7384, 13, 11205, 990, 11, 304, 20632, 449, 650, 49860, 3907, 9304, 320, 49, 7217, 301, 548, 11, 34061, 8, 323, 3907, 315, 21073, 320, 52, 815, 6266, 8111, 304, 22037, 26545, 13, 11450, 596, 31376, 6108, 8752, 3135, 304, 264, 4272, 5376, 315, 7432, 17, 304, 279, 9420, 596, 16975, 323, 374, 264, 3682, 5353, 315, 3728, 10182, 2349, 13, 2057, 5663, 420, 11, 264, 6541, 9017, 264, 28029, 323, 17332, 6108, 8752, 374, 7718, 13, 76059, 58758, 649, 1514, 264, 16996, 3560, 304, 1778, 264, 17332, 6108, 8752, 555, 13788, 439, 264, 33268, 323, 12782, 92322, 5211, 369, 279, 5788, 315, 1690, 26333, 13, 19173, 11, 279, 9546, 315, 72700, 258, 305, 32551, 279, 8863, 315, 7732, 1139, 17332, 6108, 3956, 13, 8626, 13, 468, 412, 2577, 261, 23685, 320, 53, 3336, 12, 3014, 306, 8, 1071, 11, 330, 32, 2478, 1667, 4227, 11, 584, 10887, 264, 2115, 9269, 449, 2477, 75, 1590, 430, 1051, 46036, 311, 1304, 7732, 8649, 2753, 72700, 258, 13, 7648, 11012, 8710, 3544, 18637, 304, 8863, 15374, 369, 1690, 3284, 8522, 13, 578, 52497, 11, 4869, 11, 574, 430, 279, 14278, 304, 72700, 258, 27332, 449, 279, 5557, 584, 1511, 1243, 2345, 31820, 32317, 2345, 16514, 45311, 323, 279, 12690, 14264, 2753, 16615, 1210, 1561, 7526, 17314, 1430, 1171, 11, 279, 12074, 4024, 3411, 369, 264, 6425, 13, 2435, 20011, 279, 3293, 12904, 1669, 6616, 11547, 300, 24, 5557, 304, 2477, 14115, 311, 4827, 279, 72700, 258, 3392, 304, 264, 15528, 1648, 11, 2085, 14718, 264, 58758, 7692, 16750, 13, 763, 1023, 4339, 11, 279, 12690, 14264, 1120, 439, 1664, 323, 439, 16615, 439, 1884, 2085, 19465, 4442, 13, 2999, 13, 32207, 1611, 2206, 5302, 320, 53, 3336, 12, 3014, 306, 8, 29786, 11, 330, 11859, 14115, 374, 264, 24522, 52196, 9606, 11, 7438, 1475, 15207, 374, 3118, 304, 1403, 11236, 13, 12362, 12904, 1669, 6616, 11547, 300, 24, 11, 584, 11784, 3230, 4442, 304, 2225, 11236, 315, 264, 15207, 430, 374, 16996, 369, 279, 49554, 74767, 315, 72700, 258, 13, 1226, 304, 31262, 832, 3048, 315, 279, 15207, 11, 323, 1193, 26310, 304, 31262, 279, 1023, 13, 578, 13239, 2477, 14115, 1584, 1047, 264, 15528, 220, 605, 4, 14278, 304, 72700, 258, 3392, 1418, 433, 14264, 14614, 304, 279, 37647, 13, 12404, 505, 279, 46036, 12690, 1047, 459, 709, 311, 220, 3174, 4, 5376, 304, 8863, 15374, 3343, 2999, 13, 13134, 268, 13000, 8619, 2727, 320, 53, 3336, 12, 3014, 306, 8, 10555, 11, 330, 791, 34684, 430, 584, 617, 11784, 1555, 12904, 1669, 6616, 11547, 300, 24, 527, 4528, 311, 1884, 430, 88558, 31889, 304, 7138, 13, 578, 9610, 315, 279, 12904, 1669, 6616, 11547, 300, 24, 1749, 374, 430, 279, 24629, 34684, 649, 387, 6089, 11784, 1139, 279, 15922, 315, 7701, 27331, 5021, 36680, 304, 1193, 264, 19983, 315, 279, 892, 433, 1053, 1935, 555, 264, 29924, 40308, 8446, 1210, 578, 8522, 315, 420, 1749, 527, 539, 1193, 22486, 311, 72700, 258, 719, 2643, 1101, 387, 5505, 311, 24490, 1023, 25022, 304, 31665, 11, 8405, 264, 33045, 502, 40308, 5507, 311, 7417, 29149, 26206, 13, 220, 128257, 198 ]

2,250

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract The dispersal of animals from their birth place has profound effects on the immediate survival and longer-term persistence of populations. Molecular studies have estimated that bumblebee colonies can be established many kilometers from their queens’ natal nest site. However, little is known about when and how queens disperse during their lifespan. One possible life stage when dispersal may occur, is directly after emerging from hibernation. Here, harmonic radar tracking of artificially over-wintered Bombus terrestris queens shows that they spend most of their time resting on the ground with intermittent very short flights (duration and distance). We corroborate these behaviors with observations of wild queen bees, which show similar prolonged resting periods between short flights, indicating that the behavior of our radar-monitored bees was not due to the attachment of transponders nor an artifact of the bees being commercially reared. Radar-monitored flights were not continuously directed away from the origin, suggesting that bees were not intentionally trying to disperse from their artificial emergence site. Flights did not loop back to the origin suggesting bees were not trying to remember or get back to the original release site. Most individuals dispersed from the range of the harmonic radar within less than two days and did not return. Flight directions were not different from a uniform distribution and flight lengths followed an exponential distribution, both suggesting random dispersal. A random walk model based on our observed data estimates a positive net dispersal from the origin over many flights, indicating a biased random dispersal, and estimates the net displacement of queens to be within the range of those estimated in genetic studies. We suggest that a distinct post-hibernation life history stage consisting mostly of rest with intermittent short flights and infrequent foraging fulfils the dual purpose of ovary development and dispersal prior to nest searching. Introduction Wild pollinators are under threat by anthropogenic changes in landscape, including agricultural development and urban sprawl 1 . Knowledge of a species’ dispersal patterns can be crucial in predicting how animals respond to environmental change 2 . Bumblebees are important for the pollination of many native and wild plants throughout temperate ecosystems 3 , 4 , 5 , 6 , but the dispersal behaviors of bumblebee queens after hibernation is relatively unknown. Bumblebee colonies are comprised of a queen and up to a few hundred daughter workers. At the end of the colony’s annual life cycle, new queens and males are produced which then leave the hive to mate. The males die before the winter, whereas the new queens hibernate and go on to set up colonies in the spring. Dispersal of new queen bumblebees from their natal nest sites could occur at various stages of life, including before mating, between mating and hibernation, after emergence from hibernation but before nest searching, or while nest searching. To our knowledge, only two studies have explicitly examined the dispersal of queen bumblebees. By looking at genetic relatedness of bees from nearby colonies, Lepais and colleagues 7 estimated that new colonies were founded between three and five kilometers from their queen’s natal nest. Another study using genetic analyses and geographical sampling investigated the invasion of imported bumblebee species into Chile and suggested that Bombus terrestris queens spread up to about 200 km each year 8 . However, this surprisingly long distance was likely, as the authors point out, aided by the prevailing strong winds across the Andes, and perhaps due to anthropogenic causes, e.g. unintentional automotive transportation of queens within plants or soil. In temperate regions, bumblebees take an estimated two to three weeks to locate a new nest site and begin to forage for pollen 9 , but there is very limited information on the behavior of queen bumblebees immediately after emergence from hibernation. Several accounts from almost 60 years ago claim that when queen bumblebees first appear in the early days of spring they spend most of their time actively flying and foraging for nectar and pollen, which helps replenish their fat reserves and develop their ovaries, and within a short time they begin searching for nest sites 10 , 11 , 12 , 13 . However, there are no empirical data specifically on this life stage. The behavior of newly emerged queens and the contribution of this time period to colony dispersal is unknown. Using harmonic radar tracking of artificially over-wintered queen bees, we describe their behavior upon emergence and use a random walk model to estimate their dispersal pattern and displacement. Results Radar tracking of artificially over-wintered bumblebee queens We monitored 20 artificially over-wintered queen bumblebees with harmonic radar (Fig. 1a ). Queen bumblebees were kept at 4 °C until the morning of the start of experiments (Methods), at which point a transponder was superglued to the thorax of each bee (Fig. 1a inset). Subsequently, each bee was placed in a small depression in the center of a mound of earth (approx. 5 cm high and 15 cm in diameter), where they were allowed to warm up naturally. The activity of all bees was monitored with the harmonic radar for between 4 and 15 hours each day (depending on weather and therefore likelihood of any flights occurring) and until all the bees had permanently dispersed outside the range of the radar (Fig. 1a ). Three bees were monitored individually for up to three days each. The other 17 bees were monitored simultaneously for a period of five days. Figure 1 Queen bumblebees ( Bombus terrestris ) that have recently emerged from artificial or natural hibernation spend more time resting than flying. ( a ) Aerial view of field site where harmonic radar tracking took place (an orthomosaic created from drone photography; flight tracks overlaid using MATLAB 2015b). Yellow triangle designates position where queen bumblebees were placed prior to the start of experiment (release site). Orange square and blue circle indicate positions of the harmonic radar for the 17 group- and three individually-monitored bees, respectively. Pink lines indicate flight paths of radar tracked bees. Inset photo: queen", "role": "user" }, { "content": "Scientists at Queen Mary University of London have discovered a never before reported behaviour of queen bumblebees. It was long thought that queen bumblebees, after hibernating in the ground over winter, emerged, began feeding and dispersed quite quickly to found their new colony. But new research shows that directly after hibernation, queen bumblebees spend the majority of their time hiding and resting amongst dead leaves and grass. The study, published in the journal Scientific Reports, suggests that this behaviour of long rests with short intermittent flights explains how queen bumblebees find themselves far away from their natal nest. Dr. James Makinson, who co-led the study at Queen Mary University of London but is now based at Hawkesbury Institute for the Environment at Western Sydney University, said: \"We wanted to see what queens actually do right after they emerge. By combining state-of-the-art tracking technology with wild bee observations, we were able to uncover a never before seen behavior of queen bumblebees.\" The researchers placed small antenna on the backs of queens that had just emerged from artificially induced hibernation. At an outdoor field site, radar was used to track the bees via the antennae as they woke up and left the area. Queen bumblebee with antenna Credit: James Makinson The data showed that the queens were spending most of their time on the ground (between 10-20 minutes on average) and making short flights (10-20 seconds on average) in nearly random directions. Observations of wild queen bumblebees verified this was not due to the antennas but rather natural behaviour of recently emerged queens. Computer modelling also showed that this behaviour can explain how bees end up many kilometres from the hibernation spots. Dr. Joe Woodgate, a co-lead author of the study from Queen Mary University of London, said: \"Our study suggests that a few weeks of this type of behaviour would carry queen bees several kilometers away from their hibernation site and might explain how queens disperse from the nest in which they were born to the place they choose to found a new colony.\" Dr. Makinson added: \"Better understanding the behavior of queens during this crucial period of their lives can suggest practices to improve their chances of successfully founding new colonies and help their survival. Queen bumblebee resting among leaves Credit: Clint Perry \"Our findings suggest that creating pollinator friendly corridors between conserved landscape patches would be helpful. It would also be beneficial to plant pollinator friendly flowers and trees all year round, giving bumblebee queens ample access to food during their early spring emergence. And leaving vegetation, such as leaf litter and long grass, undisturbed until late in the spring would give queen bumblebees safe places to rest.\" If you see an exhausted bumblebee queen around this time of the year, researchers suggest you can rescue her by giving her sugar solution (half water, half sugar, thoroughly stirred). Put the solution on a teaspoon and move the spoon gently to near her antennae or mouthparts. Drinking the solution will allow the bee to warm up its flight motor and have sufficient energy to find flowers on its own. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract The dispersal of animals from their birth place has profound effects on the immediate survival and longer-term persistence of populations. Molecular studies have estimated that bumblebee colonies can be established many kilometers from their queens’ natal nest site. However, little is known about when and how queens disperse during their lifespan. One possible life stage when dispersal may occur, is directly after emerging from hibernation. Here, harmonic radar tracking of artificially over-wintered Bombus terrestris queens shows that they spend most of their time resting on the ground with intermittent very short flights (duration and distance). We corroborate these behaviors with observations of wild queen bees, which show similar prolonged resting periods between short flights, indicating that the behavior of our radar-monitored bees was not due to the attachment of transponders nor an artifact of the bees being commercially reared. Radar-monitored flights were not continuously directed away from the origin, suggesting that bees were not intentionally trying to disperse from their artificial emergence site. Flights did not loop back to the origin suggesting bees were not trying to remember or get back to the original release site. Most individuals dispersed from the range of the harmonic radar within less than two days and did not return. Flight directions were not different from a uniform distribution and flight lengths followed an exponential distribution, both suggesting random dispersal. A random walk model based on our observed data estimates a positive net dispersal from the origin over many flights, indicating a biased random dispersal, and estimates the net displacement of queens to be within the range of those estimated in genetic studies. We suggest that a distinct post-hibernation life history stage consisting mostly of rest with intermittent short flights and infrequent foraging fulfils the dual purpose of ovary development and dispersal prior to nest searching. Introduction Wild pollinators are under threat by anthropogenic changes in landscape, including agricultural development and urban sprawl 1 . Knowledge of a species’ dispersal patterns can be crucial in predicting how animals respond to environmental change 2 . Bumblebees are important for the pollination of many native and wild plants throughout temperate ecosystems 3 , 4 , 5 , 6 , but the dispersal behaviors of bumblebee queens after hibernation is relatively unknown. Bumblebee colonies are comprised of a queen and up to a few hundred daughter workers. At the end of the colony’s annual life cycle, new queens and males are produced which then leave the hive to mate. The males die before the winter, whereas the new queens hibernate and go on to set up colonies in the spring. Dispersal of new queen bumblebees from their natal nest sites could occur at various stages of life, including before mating, between mating and hibernation, after emergence from hibernation but before nest searching, or while nest searching. To our knowledge, only two studies have explicitly examined the dispersal of queen bumblebees. By looking at genetic relatedness of bees from nearby colonies, Lepais and colleagues 7 estimated that new colonies were founded between three and five kilometers from their queen’s natal nest. Another study using genetic analyses and geographical sampling investigated the invasion of imported bumblebee species into Chile and suggested that Bombus terrestris queens spread up to about 200 km each year 8 . However, this surprisingly long distance was likely, as the authors point out, aided by the prevailing strong winds across the Andes, and perhaps due to anthropogenic causes, e.g. unintentional automotive transportation of queens within plants or soil. In temperate regions, bumblebees take an estimated two to three weeks to locate a new nest site and begin to forage for pollen 9 , but there is very limited information on the behavior of queen bumblebees immediately after emergence from hibernation. Several accounts from almost 60 years ago claim that when queen bumblebees first appear in the early days of spring they spend most of their time actively flying and foraging for nectar and pollen, which helps replenish their fat reserves and develop their ovaries, and within a short time they begin searching for nest sites 10 , 11 , 12 , 13 . However, there are no empirical data specifically on this life stage. The behavior of newly emerged queens and the contribution of this time period to colony dispersal is unknown. Using harmonic radar tracking of artificially over-wintered queen bees, we describe their behavior upon emergence and use a random walk model to estimate their dispersal pattern and displacement. Results Radar tracking of artificially over-wintered bumblebee queens We monitored 20 artificially over-wintered queen bumblebees with harmonic radar (Fig. 1a ). Queen bumblebees were kept at 4 °C until the morning of the start of experiments (Methods), at which point a transponder was superglued to the thorax of each bee (Fig. 1a inset). Subsequently, each bee was placed in a small depression in the center of a mound of earth (approx. 5 cm high and 15 cm in diameter), where they were allowed to warm up naturally. The activity of all bees was monitored with the harmonic radar for between 4 and 15 hours each day (depending on weather and therefore likelihood of any flights occurring) and until all the bees had permanently dispersed outside the range of the radar (Fig. 1a ). Three bees were monitored individually for up to three days each. The other 17 bees were monitored simultaneously for a period of five days. Figure 1 Queen bumblebees ( Bombus terrestris ) that have recently emerged from artificial or natural hibernation spend more time resting than flying. ( a ) Aerial view of field site where harmonic radar tracking took place (an orthomosaic created from drone photography; flight tracks overlaid using MATLAB 2015b). Yellow triangle designates position where queen bumblebees were placed prior to the start of experiment (release site). Orange square and blue circle indicate positions of the harmonic radar for the 17 group- and three individually-monitored bees, respectively. Pink lines indicate flight paths of radar tracked bees. Inset photo: queen<|im_end|> <|im_start|>assistant Scientists at Queen Mary University of London have discovered a never before reported behaviour of queen bumblebees. It was long thought that queen bumblebees, after hibernating in the ground over winter, emerged, began feeding and dispersed quite quickly to found their new colony. But new research shows that directly after hibernation, queen bumblebees spend the majority of their time hiding and resting amongst dead leaves and grass. The study, published in the journal Scientific Reports, suggests that this behaviour of long rests with short intermittent flights explains how queen bumblebees find themselves far away from their natal nest. Dr. James Makinson, who co-led the study at Queen Mary University of London but is now based at Hawkesbury Institute for the Environment at Western Sydney University, said: "We wanted to see what queens actually do right after they emerge. By combining state-of-the-art tracking technology with wild bee observations, we were able to uncover a never before seen behavior of queen bumblebees." The researchers placed small antenna on the backs of queens that had just emerged from artificially induced hibernation. At an outdoor field site, radar was used to track the bees via the antennae as they woke up and left the area. Queen bumblebee with antenna Credit: James Makinson The data showed that the queens were spending most of their time on the ground (between 10-20 minutes on average) and making short flights (10-20 seconds on average) in nearly random directions. Observations of wild queen bumblebees verified this was not due to the antennas but rather natural behaviour of recently emerged queens. Computer modelling also showed that this behaviour can explain how bees end up many kilometres from the hibernation spots. Dr. Joe Woodgate, a co-lead author of the study from Queen Mary University of London, said: "Our study suggests that a few weeks of this type of behaviour would carry queen bees several kilometers away from their hibernation site and might explain how queens disperse from the nest in which they were born to the place they choose to found a new colony." Dr. Makinson added: "Better understanding the behavior of queens during this crucial period of their lives can suggest practices to improve their chances of successfully founding new colonies and help their survival. Queen bumblebee resting among leaves Credit: Clint Perry "Our findings suggest that creating pollinator friendly corridors between conserved landscape patches would be helpful. It would also be beneficial to plant pollinator friendly flowers and trees all year round, giving bumblebee queens ample access to food during their early spring emergence. And leaving vegetation, such as leaf litter and long grass, undisturbed until late in the spring would give queen bumblebees safe places to rest." If you see an exhausted bumblebee queen around this time of the year, researchers suggest you can rescue her by giving her sugar solution (half water, half sugar, thoroughly stirred). Put the solution on a teaspoon and move the spoon gently to near her antennae or mouthparts. Drinking the solution will allow the bee to warm up its flight motor and have sufficient energy to find flowers on its own. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 578, 79835, 278, 315, 10099, 505, 872, 7342, 2035, 706, 28254, 6372, 389, 279, 14247, 20237, 323, 5129, 9860, 42056, 315, 22673, 13, 60825, 7978, 617, 13240, 430, 293, 23568, 33131, 49028, 649, 387, 9749, 1690, 41668, 505, 872, 70097, 529, 308, 4306, 23634, 2816, 13, 4452, 11, 2697, 374, 3967, 922, 994, 323, 1268, 70097, 834, 82344, 2391, 872, 61961, 13, 3861, 3284, 2324, 6566, 994, 79835, 278, 1253, 12446, 11, 374, 6089, 1306, 24084, 505, 305, 18127, 367, 13, 5810, 11, 82341, 28608, 15194, 315, 78220, 927, 2695, 2295, 291, 33909, 355, 88026, 496, 285, 70097, 5039, 430, 814, 8493, 1455, 315, 872, 892, 41219, 389, 279, 5015, 449, 75568, 1633, 2875, 25952, 320, 17456, 323, 6138, 570, 1226, 79819, 349, 1521, 28198, 449, 24654, 315, 8545, 29006, 40558, 11, 902, 1501, 4528, 44387, 41219, 18852, 1990, 2875, 25952, 11, 19392, 430, 279, 7865, 315, 1057, 28608, 78396, 37301, 40558, 574, 539, 4245, 311, 279, 20581, 315, 1380, 3595, 388, 6463, 459, 37739, 315, 279, 40558, 1694, 54453, 312, 1636, 13, 68886, 78396, 37301, 25952, 1051, 539, 31978, 15910, 3201, 505, 279, 6371, 11, 23377, 430, 40558, 1051, 539, 37304, 4560, 311, 834, 82344, 505, 872, 21075, 49179, 2816, 13, 3061, 2866, 1550, 539, 6471, 1203, 311, 279, 6371, 23377, 40558, 1051, 539, 4560, 311, 6227, 477, 636, 1203, 311, 279, 4113, 4984, 2816, 13, 7648, 7931, 77810, 505, 279, 2134, 315, 279, 82341, 28608, 2949, 2753, 1109, 1403, 2919, 323, 1550, 539, 471, 13, 27675, 18445, 1051, 539, 2204, 505, 264, 14113, 8141, 323, 11213, 29416, 8272, 459, 59855, 8141, 11, 2225, 23377, 4288, 79835, 278, 13, 362, 4288, 4321, 1646, 3196, 389, 1057, 13468, 828, 17989, 264, 6928, 4272, 79835, 278, 505, 279, 6371, 927, 1690, 25952, 11, 19392, 264, 48761, 4288, 79835, 278, 11, 323, 17989, 279, 4272, 44153, 315, 70097, 311, 387, 2949, 279, 2134, 315, 1884, 13240, 304, 19465, 7978, 13, 1226, 4284, 430, 264, 12742, 1772, 2902, 18127, 367, 2324, 3925, 6566, 31706, 10213, 315, 2800, 449, 75568, 2875, 25952, 323, 4225, 70791, 369, 4210, 5716, 69, 8839, 279, 19091, 7580, 315, 25568, 661, 4500, 323, 79835, 278, 4972, 311, 23634, 15389, 13, 29438, 13944, 7230, 258, 3046, 527, 1234, 6023, 555, 41416, 29569, 4442, 304, 18921, 11, 2737, 29149, 4500, 323, 16036, 35908, 75, 220, 16, 662, 33025, 315, 264, 9606, 529, 79835, 278, 12912, 649, 387, 16996, 304, 52997, 1268, 10099, 6013, 311, 12434, 2349, 220, 17, 662, 426, 23568, 1395, 288, 527, 3062, 369, 279, 7230, 2617, 315, 1690, 10068, 323, 8545, 11012, 6957, 6940, 349, 61951, 220, 18, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 1174, 719, 279, 79835, 278, 28198, 315, 293, 23568, 33131, 70097, 1306, 305, 18127, 367, 374, 12309, 9987, 13, 426, 23568, 33131, 49028, 527, 40056, 315, 264, 29006, 323, 709, 311, 264, 2478, 7895, 10003, 7487, 13, 2468, 279, 842, 315, 279, 42036, 753, 9974, 2324, 11008, 11, 502, 70097, 323, 25000, 527, 9124, 902, 1243, 5387, 279, 66607, 311, 30276, 13, 578, 25000, 2815, 1603, 279, 12688, 11, 20444, 279, 502, 70097, 305, 19348, 323, 733, 389, 311, 743, 709, 49028, 304, 279, 10683, 13, 4185, 32390, 278, 315, 502, 29006, 293, 23568, 1395, 288, 505, 872, 308, 4306, 23634, 6732, 1436, 12446, 520, 5370, 18094, 315, 2324, 11, 2737, 1603, 73219, 11, 1990, 73219, 323, 305, 18127, 367, 11, 1306, 49179, 505, 305, 18127, 367, 719, 1603, 23634, 15389, 11, 477, 1418, 23634, 15389, 13, 2057, 1057, 6677, 11, 1193, 1403, 7978, 617, 21650, 25078, 279, 79835, 278, 315, 29006, 293, 23568, 1395, 288, 13, 3296, 3411, 520, 19465, 5552, 2136, 315, 40558, 505, 14373, 49028, 11, 121688, 2852, 323, 18105, 220, 22, 13240, 430, 502, 49028, 1051, 18538, 1990, 2380, 323, 4330, 41668, 505, 872, 29006, 753, 308, 4306, 23634, 13, 13596, 4007, 1701, 19465, 29060, 323, 54001, 25936, 27313, 279, 30215, 315, 25973, 293, 23568, 33131, 9606, 1139, 34100, 323, 12090, 430, 33909, 355, 88026, 496, 285, 70097, 9041, 709, 311, 922, 220, 1049, 13437, 1855, 1060, 220, 23, 662, 4452, 11, 420, 29392, 1317, 6138, 574, 4461, 11, 439, 279, 12283, 1486, 704, 11, 63957, 555, 279, 61129, 3831, 29592, 4028, 279, 1628, 288, 11, 323, 8530, 4245, 311, 41416, 29569, 11384, 11, 384, 1326, 13, 70576, 278, 40508, 18386, 315, 70097, 2949, 11012, 477, 17614, 13, 763, 6940, 349, 13918, 11, 293, 23568, 1395, 288, 1935, 459, 13240, 1403, 311, 2380, 5672, 311, 25539, 264, 502, 23634, 2816, 323, 3240, 311, 369, 425, 369, 79784, 220, 24, 1174, 719, 1070, 374, 1633, 7347, 2038, 389, 279, 7865, 315, 29006, 293, 23568, 1395, 288, 7214, 1306, 49179, 505, 305, 18127, 367, 13, 26778, 9815, 505, 4661, 220, 1399, 1667, 4227, 3802, 430, 994, 29006, 293, 23568, 1395, 288, 1176, 5101, 304, 279, 4216, 2919, 315, 10683, 814, 8493, 1455, 315, 872, 892, 22815, 16706, 323, 369, 4210, 369, 308, 39916, 323, 79784, 11, 902, 8779, 70543, 819, 872, 8834, 30600, 323, 2274, 872, 66168, 552, 11, 323, 2949, 264, 2875, 892, 814, 3240, 15389, 369, 23634, 6732, 220, 605, 1174, 220, 806, 1174, 220, 717, 1174, 220, 1032, 662, 4452, 11, 1070, 527, 912, 46763, 828, 11951, 389, 420, 2324, 6566, 13, 578, 7865, 315, 13945, 22763, 70097, 323, 279, 19035, 315, 420, 892, 4261, 311, 42036, 79835, 278, 374, 9987, 13, 12362, 82341, 28608, 15194, 315, 78220, 927, 2695, 2295, 291, 29006, 40558, 11, 584, 7664, 872, 7865, 5304, 49179, 323, 1005, 264, 4288, 4321, 1646, 311, 16430, 872, 79835, 278, 5497, 323, 44153, 13, 18591, 68886, 15194, 315, 78220, 927, 2695, 2295, 291, 293, 23568, 33131, 70097, 1226, 41223, 220, 508, 78220, 927, 2695, 2295, 291, 29006, 293, 23568, 1395, 288, 449, 82341, 28608, 320, 30035, 13, 220, 16, 64, 7609, 16657, 293, 23568, 1395, 288, 1051, 8774, 520, 220, 19, 37386, 34, 3156, 279, 6693, 315, 279, 1212, 315, 21896, 320, 18337, 705, 520, 902, 1486, 264, 1380, 20949, 574, 2307, 6200, 3340, 311, 279, 73833, 710, 315, 1855, 38328, 320, 30035, 13, 220, 16, 64, 55959, 570, 3804, 39742, 11, 1855, 38328, 574, 9277, 304, 264, 2678, 18710, 304, 279, 4219, 315, 264, 73266, 315, 9578, 320, 49153, 13, 220, 20, 10166, 1579, 323, 220, 868, 10166, 304, 23899, 705, 1405, 814, 1051, 5535, 311, 8369, 709, 18182, 13, 578, 5820, 315, 682, 40558, 574, 41223, 449, 279, 82341, 28608, 369, 1990, 220, 19, 323, 220, 868, 4207, 1855, 1938, 320, 81580, 389, 9282, 323, 9093, 29736, 315, 904, 25952, 31965, 8, 323, 3156, 682, 279, 40558, 1047, 31859, 77810, 4994, 279, 2134, 315, 279, 28608, 320, 30035, 13, 220, 16, 64, 7609, 14853, 40558, 1051, 41223, 32399, 369, 709, 311, 2380, 2919, 1855, 13, 578, 1023, 220, 1114, 40558, 1051, 41223, 25291, 369, 264, 4261, 315, 4330, 2919, 13, 19575, 220, 16, 16657, 293, 23568, 1395, 288, 320, 33909, 355, 88026, 496, 285, 883, 430, 617, 6051, 22763, 505, 21075, 477, 5933, 305, 18127, 367, 8493, 810, 892, 41219, 1109, 16706, 13, 320, 264, 883, 362, 2918, 1684, 315, 2115, 2816, 1405, 82341, 28608, 15194, 3952, 2035, 320, 276, 30299, 316, 45883, 3549, 505, 27811, 24685, 26, 11213, 14242, 29204, 3864, 1701, 50447, 220, 679, 20, 65, 570, 26541, 22217, 2955, 988, 2361, 1405, 29006, 293, 23568, 1395, 288, 1051, 9277, 4972, 311, 279, 1212, 315, 9526, 320, 23859, 2816, 570, 22725, 9518, 323, 6437, 12960, 13519, 10093, 315, 279, 82341, 28608, 369, 279, 220, 1114, 1912, 12, 323, 2380, 32399, 78396, 37301, 40558, 11, 15947, 13, 27211, 5238, 13519, 11213, 13006, 315, 28608, 34156, 40558, 13, 763, 751, 6685, 25, 29006, 128257, 198, 128256, 78191, 198, 72326, 520, 16657, 10455, 3907, 315, 7295, 617, 11352, 264, 2646, 1603, 5068, 17432, 315, 29006, 293, 23568, 1395, 288, 13, 1102, 574, 1317, 3463, 430, 29006, 293, 23568, 1395, 288, 11, 1306, 305, 18127, 1113, 304, 279, 5015, 927, 12688, 11, 22763, 11, 6137, 26040, 323, 77810, 5115, 6288, 311, 1766, 872, 502, 42036, 13, 2030, 502, 3495, 5039, 430, 6089, 1306, 305, 18127, 367, 11, 29006, 293, 23568, 1395, 288, 8493, 279, 8857, 315, 872, 892, 26092, 323, 41219, 24059, 5710, 11141, 323, 16763, 13, 578, 4007, 11, 4756, 304, 279, 8486, 38130, 29140, 11, 13533, 430, 420, 17432, 315, 1317, 54331, 449, 2875, 75568, 25952, 15100, 1268, 29006, 293, 23568, 1395, 288, 1505, 5694, 3117, 3201, 505, 872, 308, 4306, 23634, 13, 2999, 13, 7957, 40424, 29973, 11, 889, 1080, 35054, 279, 4007, 520, 16657, 10455, 3907, 315, 7295, 719, 374, 1457, 3196, 520, 12897, 12841, 20176, 10181, 369, 279, 11847, 520, 11104, 21972, 3907, 11, 1071, 25, 330, 1687, 4934, 311, 1518, 1148, 70097, 3604, 656, 1314, 1306, 814, 34044, 13, 3296, 35271, 1614, 8838, 10826, 38921, 15194, 5557, 449, 8545, 38328, 24654, 11, 584, 1051, 3025, 311, 45063, 264, 2646, 1603, 3970, 7865, 315, 29006, 293, 23568, 1395, 288, 1210, 578, 12074, 9277, 2678, 41032, 389, 279, 28678, 315, 70097, 430, 1047, 1120, 22763, 505, 78220, 36572, 305, 18127, 367, 13, 2468, 459, 16166, 2115, 2816, 11, 28608, 574, 1511, 311, 3839, 279, 40558, 4669, 279, 72577, 6043, 439, 814, 39826, 709, 323, 2163, 279, 3158, 13, 16657, 293, 23568, 33131, 449, 41032, 16666, 25, 7957, 40424, 29973, 578, 828, 8710, 430, 279, 70097, 1051, 10374, 1455, 315, 872, 892, 389, 279, 5015, 320, 42967, 220, 605, 12, 508, 4520, 389, 5578, 8, 323, 3339, 2875, 25952, 320, 605, 12, 508, 6622, 389, 5578, 8, 304, 7154, 4288, 18445, 13, 31943, 811, 315, 8545, 29006, 293, 23568, 1395, 288, 24884, 420, 574, 539, 4245, 311, 279, 87851, 719, 4856, 5933, 17432, 315, 6051, 22763, 70097, 13, 17863, 61966, 1101, 8710, 430, 420, 17432, 649, 10552, 1268, 40558, 842, 709, 1690, 52957, 505, 279, 305, 18127, 367, 19300, 13, 2999, 13, 13142, 12404, 25623, 11, 264, 1080, 12, 27152, 3229, 315, 279, 4007, 505, 16657, 10455, 3907, 315, 7295, 11, 1071, 25, 330, 8140, 4007, 13533, 430, 264, 2478, 5672, 315, 420, 955, 315, 17432, 1053, 6920, 29006, 40558, 3892, 41668, 3201, 505, 872, 305, 18127, 367, 2816, 323, 2643, 10552, 1268, 70097, 834, 82344, 505, 279, 23634, 304, 902, 814, 1051, 9405, 311, 279, 2035, 814, 5268, 311, 1766, 264, 502, 42036, 1210, 2999, 13, 40424, 29973, 3779, 25, 330, 56351, 8830, 279, 7865, 315, 70097, 2391, 420, 16996, 4261, 315, 872, 6439, 649, 4284, 12659, 311, 7417, 872, 17393, 315, 7946, 36330, 502, 49028, 323, 1520, 872, 20237, 13, 16657, 293, 23568, 33131, 41219, 4315, 11141, 16666, 25, 56129, 31421, 330, 8140, 14955, 4284, 430, 6968, 7230, 17720, 11919, 75752, 1990, 1615, 2841, 18921, 29760, 1053, 387, 11190, 13, 1102, 1053, 1101, 387, 24629, 311, 6136, 7230, 17720, 11919, 19837, 323, 12690, 682, 1060, 4883, 11, 7231, 293, 23568, 33131, 70097, 42853, 2680, 311, 3691, 2391, 872, 4216, 10683, 49179, 13, 1628, 9564, 54832, 11, 1778, 439, 16312, 39682, 323, 1317, 16763, 11, 2073, 380, 75325, 3156, 3389, 304, 279, 10683, 1053, 3041, 29006, 293, 23568, 1395, 288, 6220, 7634, 311, 2800, 1210, 1442, 499, 1518, 459, 39019, 293, 23568, 33131, 29006, 2212, 420, 892, 315, 279, 1060, 11, 12074, 4284, 499, 649, 17629, 1077, 555, 7231, 1077, 13465, 6425, 320, 38106, 3090, 11, 4376, 13465, 11, 27461, 75940, 570, 10435, 279, 6425, 389, 264, 42384, 323, 3351, 279, 46605, 30373, 311, 3221, 1077, 72577, 6043, 477, 11013, 18753, 13, 83681, 279, 6425, 690, 2187, 279, 38328, 311, 8369, 709, 1202, 11213, 9048, 323, 617, 14343, 4907, 311, 1505, 19837, 389, 1202, 1866, 13, 220, 128257, 198 ]

1,943

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Control of the structure and function of three-dimensional multicellular tissues depends critically on the spatial and temporal coordination of cellular physical properties, yet the organizational principles that govern these events and their disruption in disease remain poorly understood. Using a multicellular mammary cancer organoid model, we map here the spatial and temporal evolution of positions, motions and physical characteristics of individual cells in three dimensions. Compared with cells in the organoid core, cells at the organoid periphery and the invasive front are found to be systematically softer, larger and more dynamic. These mechanical changes are shown to arise from supracellular fluid flow through gap junctions, the suppression of which delays the transition to an invasive phenotype. These findings highlight the role of spatiotemporal coordination of cellular physical properties in tissue organization and disease progression. Main Living cells are dynamic systems undergoing processes ranging from gene expression, intracellular dynamics and forces at the molecular level 1 , 2 , 3 to cell contraction, deformation and migration at the cellular level 4 , 5 , 6 , 7 , 8 , 9 , 10 . Within a multicellular tissue, the precise control of these physical characteristics in space and time is critical for the maintenance of mechanical integrity and biological function. Deviation from mechanical haemostasis is associated with diseases, including aberrant wound repair, developmental abnormalities and cancer 11 , 12 , 13 , 14 , 15 , 16 , 17 . In isolated cells in vitro, for example, increased deformability 18 , 19 , 20 , 21 , intracellular dynamics 22 , contractility 23 and mobility have each been identified as a physical hallmark of different types of cancer 24 and have been proposed as potential targets for cancer treatment 25 . Despite the promise of in vitro approaches, extensive studies have shown that the mechanical properties of cells are regulated by their microenvironment, including but not limited to stiffness of the surrounding matrix, cell densities and dimensions 26 , 27 . Hence, in the context of a multicellular system in the three-dimensional (3D) microenvironment, it remains unknown how the physical characteristics of individual cells regulate and coordinate tumour development and invasion. By integrating confocal microscopy with optical tweezers, we have developed a platform to measure morphological characteristics, physical properties and migratory dynamics of individual cells throughout a growing multicellular 3D breast cancer model 11 , 12 . By tracking the spatiotemporal evolution of individual cells during the growing process, we find heterogeneous patterns of cellular physical characteristics that facilitate tumour cell invasion. Compared with cells in the organoid core, those at the invasive leading edge are faster, softer and larger. The volumes of both the cell body and the nucleus are larger at the invasive leading edge, and the temporal fluctuations characterizing cytoplasmic dynamics become stronger. Blocking gap junctions (GJs) significantly suppresses these changes, suggesting that supracellular fluid flow may drive the evolution of the observed patterns of cellular properties. Furthermore, the elimination of the softer subpopulation in the cancer organoid strongly delays the transition to an invasive phenotype. These findings highlight a causal role of spatiotemporal coordination of cellular physical properties—especially cell swelling and softening—in tumour development and invasive dynamics. Epithelial cancer organoids have been widely used to model glandular epithelial cancers in 3D culture systems 28 ; these models recapitulate distinguishing physiological features of epithelial tissues and capture the pathological features of epithelial tumours. For example, the well-ordered epithelial architecture becomes disrupted, the lumen fills with cells and invasive branches then form 28 . To reveal the mechanical underpinnings of this process, we transfected MCF 10A human breast epithelial cells with a green fluorescent protein (GFP) tagged with a nuclear-localization signal (NLS). We then seeded these cells into a 3D interpenetrating network hydrogel composed of 5 mg ml −1 alginate and 4 mg ml −1 Matrigel 12 , with a shear modulus close to 300 Pa to mimic the mechanical microenvironment of a breast carcinoma in vivo 12 , 29 . Starting from a single cell, a multicellular cluster grows, and invasive branches develop over approximately 10 days (Fig. 1a–c ); in accordance with recent definitions, we call this cluster a cancer organoid 30 . During the early stage, an individual MCF 10A cell proliferates to form a spherical cluster (early stage; Fig. 1a , day 3). This cell cluster grows into a larger spheroid with cells both in the core and on the periphery (middle stage; Fig. 1b , day 5). As this spheroid develops further, invasive branches extend from the main body and invade the surrounding extracellular matrix (ECM) (later stage; Fig. 1c , day 10). The phenotype observed in this 3D breast cancer model shows uncontrolled cellular proliferation, lack of cellular polarization and the initiation of matrix invasion, much like those observed in vivo in invasive ductal carcinomas (Fig. 1d ). This contrasts with a normal acinar structure that develops when cells are seeded in a soft matrix (Supplementary Fig. 1 ). Fig. 1: Evolution of heterogeneity and subpopulations of cell stiffness in the growing cancer organoid. a – c , Cross-section images of epithelial cancer organoid developed from GFP-NLS-labelled MCF 10A cells at different stages: early stage (day 3; a ), middle stage (day 5; b ) and later stage (day 10; c ). d , Haematoxylin and eosin stains from grade-2 ER+ invasive ductal carcinoma human breast cancer tissue samples. Tumour glands are indicated using red arrows. e , Schematic of the cytoplasmic mechanics and dynamics measurements in a growing cancer organoid using optical tweezers. f , E A of individual cells in the core, periphery and branch regions of the cancer organoid, quantified from slopes of the normalized force–displacement curves (inset). F and x are the resistant force and displacement of the trapped particle. S and a are the cross-section area and diameter of the particle. The boxes represent the interquartile range between the first and third quartiles, whereas the whiskers represent the 95% and 5% values, and the squares represent the", "role": "user" }, { "content": "Engineers at MIT and elsewhere have tracked the evolution of individual cells within an initially benign tumor, showing how the physical properties of those cells drive the tumor to become invasive, or metastatic. The team carried out experiments with a human breast cancer tumor that developed in the lab. As the tumor grew and amassed more cells over a period of about two weeks, the researchers observed that cells in the interior of the tumor were small and stiff, while the cells on the periphery were soft and more swollen. These softer, peripheral cells were more apt to stretch beyond the tumor body, forming \"invasive tips\" that eventually broke away to spread elsewhere. The researchers found that the cells at the tumor's edges were softer because they contained more water than those in the center. The cells in the center of a tumor are surrounded by other cells that press inward, squeezing water out of the interior cells and into those cells at the periphery, through nanometer-sized channels between them called gap junctions. \"You can think of the tumor like a sponge,\" says Ming Guo, assistant professor of mechanical engineering at MIT. \"When they grow, they build up compressive stresses inside the tumor, and that will squeeze the water from the core out to the cells on the outside, which will slowly swell over time and become softer as well—therefore they are more able to invade.\" When the team treated the tumor to draw water out of peripheral cells, the cells became stiffer and less likely to form invasive tips. Conversely, when they flooded the tumor with a diluted solution, the same peripheral cells swelled and quickly formed long, branchlike tips that invaded the surrounding environment. The results, which the team reports in the journal Nature Physics, point to a new route for cancer therapy, focused on changing the physical properties of cancer cells to delay or even prevent a tumor from spreading. Guo's co-authors include lead author and MIT postdoc Yu Long Han, along with Guoqiang Xu, Zichen Gu, Jiawei Sun, Yukun Hao, Staish Kumar Gupta, Yiwei Li, and Wenhui Tang, from MIT; Adrian Pegoraro and Yuan Yuan of the Harvard John A. Paulson School of Engineering and Applied Sciences; Hui Li of the Chinese Academy of Sciences; Kaifu Li, Hua Kang, and Lianghong Teng of Capital Medical University in Beijing; and Jeffrey Fredberg of the Harvard T. H. Chan School of Public Health in Boston. Cell tweezing Scientists suspect that cancer cells that migrate from a main tumor are able to do so in part because of their softer, more pliable nature, enabling the cells to squeeze through the body's labrynthine vasculature and proliferate far from the initial tumor. Past experiments have shown this soft, migratory nature in individual cancer cells, but Guo's team is the first to explore the role of cell stiffness in a whole, developing tumor. \"People have looked at single cells for a long time, but organisms are multicellular, three-dimensional systems,\" Guo says. \"Each cell is a physical building block, and we're interested in how each single cell is regulating its own physical properties, as the cells develop into a tissue like a tumor or an organ.\" The researchers used recently developed techniques to grow healthy human epithelial cells in 3-D and transform them into a human breast cancer tumor in the lab. Over the next week, the researchers watched as the cells multiplied and coalesced into a benign primary tumor that comprised several hundred individual cells. Several times throughout the week, the researchers infused the growing number of cells with plastic particles. They then probed each individual cell's stiffness with optical tweezers, a technique in which researchers direct a highly focused laser beam at a cell. In this case, the team trained a laser on a plastic particle within each cell, pinning the particle in place, then applying a slight pulse in a attempt to move the particle within the cell, much like using tweezers to pick an egg shell out from the surrounding yolk. Guo says the degree to which researchers can move a particle gives them an idea for the stiffness of the surrounding cell: The more resistant the particle is to being moved, the stiffer a cell must be. In this way, the researchers found that the hundreds of cells within a single benign tumor exhibit a gradient of stiffness as well as size. The interior cells were smaller and stiffer, and the further the cells were from the core, the softer and larger they became. They also became more likely to stretch out from the spherical primary tumor and form branches, or invasive tips. To see whether altering cells' water content affects their invasive behavior, the team added low-molecular-weight polymers to the tumor solution to draw water out from cells, and found that the cells shrank, became more stiff, and were less likely to migrate away from the tumor—a measure that delayed metastasis. When they added water to dilute the tumor solution, the cells, particularly at the edges, swelled, became softer, and formed invasive tips more quickly. As a last test, the researchers obtained a sample of a patient's breast cancer tumor and measured the size of every cell within the tumor sample. They observed a gradient similar to what they found in their lab-derived tumor: Cells in the tumor's core were smaller than those closer to the periphery. \"We found this doesn't just happen in a model system—it's real,\" Guo says. \"This means we may be able to develop some treatment based on the physical picture, to target cell stiffness or size to see if that helps. If you make the cells stiffer, they are less likely to migrate, and that could potentially delay invasion.\" Perhaps one day, he says, clinicians may be able to look at a tumor and, based on the size and stiffness of cells, from the inside out, be able to say with some confidence whether a tumor will metastasize or not. \"If there is an established size or stiffness gradient, you can know this will cause trouble,\" Guo says. \"If there's no gradient, you can maybe safely say it's fine.\" ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Control of the structure and function of three-dimensional multicellular tissues depends critically on the spatial and temporal coordination of cellular physical properties, yet the organizational principles that govern these events and their disruption in disease remain poorly understood. Using a multicellular mammary cancer organoid model, we map here the spatial and temporal evolution of positions, motions and physical characteristics of individual cells in three dimensions. Compared with cells in the organoid core, cells at the organoid periphery and the invasive front are found to be systematically softer, larger and more dynamic. These mechanical changes are shown to arise from supracellular fluid flow through gap junctions, the suppression of which delays the transition to an invasive phenotype. These findings highlight the role of spatiotemporal coordination of cellular physical properties in tissue organization and disease progression. Main Living cells are dynamic systems undergoing processes ranging from gene expression, intracellular dynamics and forces at the molecular level 1 , 2 , 3 to cell contraction, deformation and migration at the cellular level 4 , 5 , 6 , 7 , 8 , 9 , 10 . Within a multicellular tissue, the precise control of these physical characteristics in space and time is critical for the maintenance of mechanical integrity and biological function. Deviation from mechanical haemostasis is associated with diseases, including aberrant wound repair, developmental abnormalities and cancer 11 , 12 , 13 , 14 , 15 , 16 , 17 . In isolated cells in vitro, for example, increased deformability 18 , 19 , 20 , 21 , intracellular dynamics 22 , contractility 23 and mobility have each been identified as a physical hallmark of different types of cancer 24 and have been proposed as potential targets for cancer treatment 25 . Despite the promise of in vitro approaches, extensive studies have shown that the mechanical properties of cells are regulated by their microenvironment, including but not limited to stiffness of the surrounding matrix, cell densities and dimensions 26 , 27 . Hence, in the context of a multicellular system in the three-dimensional (3D) microenvironment, it remains unknown how the physical characteristics of individual cells regulate and coordinate tumour development and invasion. By integrating confocal microscopy with optical tweezers, we have developed a platform to measure morphological characteristics, physical properties and migratory dynamics of individual cells throughout a growing multicellular 3D breast cancer model 11 , 12 . By tracking the spatiotemporal evolution of individual cells during the growing process, we find heterogeneous patterns of cellular physical characteristics that facilitate tumour cell invasion. Compared with cells in the organoid core, those at the invasive leading edge are faster, softer and larger. The volumes of both the cell body and the nucleus are larger at the invasive leading edge, and the temporal fluctuations characterizing cytoplasmic dynamics become stronger. Blocking gap junctions (GJs) significantly suppresses these changes, suggesting that supracellular fluid flow may drive the evolution of the observed patterns of cellular properties. Furthermore, the elimination of the softer subpopulation in the cancer organoid strongly delays the transition to an invasive phenotype. These findings highlight a causal role of spatiotemporal coordination of cellular physical properties—especially cell swelling and softening—in tumour development and invasive dynamics. Epithelial cancer organoids have been widely used to model glandular epithelial cancers in 3D culture systems 28 ; these models recapitulate distinguishing physiological features of epithelial tissues and capture the pathological features of epithelial tumours. For example, the well-ordered epithelial architecture becomes disrupted, the lumen fills with cells and invasive branches then form 28 . To reveal the mechanical underpinnings of this process, we transfected MCF 10A human breast epithelial cells with a green fluorescent protein (GFP) tagged with a nuclear-localization signal (NLS). We then seeded these cells into a 3D interpenetrating network hydrogel composed of 5 mg ml −1 alginate and 4 mg ml −1 Matrigel 12 , with a shear modulus close to 300 Pa to mimic the mechanical microenvironment of a breast carcinoma in vivo 12 , 29 . Starting from a single cell, a multicellular cluster grows, and invasive branches develop over approximately 10 days (Fig. 1a–c ); in accordance with recent definitions, we call this cluster a cancer organoid 30 . During the early stage, an individual MCF 10A cell proliferates to form a spherical cluster (early stage; Fig. 1a , day 3). This cell cluster grows into a larger spheroid with cells both in the core and on the periphery (middle stage; Fig. 1b , day 5). As this spheroid develops further, invasive branches extend from the main body and invade the surrounding extracellular matrix (ECM) (later stage; Fig. 1c , day 10). The phenotype observed in this 3D breast cancer model shows uncontrolled cellular proliferation, lack of cellular polarization and the initiation of matrix invasion, much like those observed in vivo in invasive ductal carcinomas (Fig. 1d ). This contrasts with a normal acinar structure that develops when cells are seeded in a soft matrix (Supplementary Fig. 1 ). Fig. 1: Evolution of heterogeneity and subpopulations of cell stiffness in the growing cancer organoid. a – c , Cross-section images of epithelial cancer organoid developed from GFP-NLS-labelled MCF 10A cells at different stages: early stage (day 3; a ), middle stage (day 5; b ) and later stage (day 10; c ). d , Haematoxylin and eosin stains from grade-2 ER+ invasive ductal carcinoma human breast cancer tissue samples. Tumour glands are indicated using red arrows. e , Schematic of the cytoplasmic mechanics and dynamics measurements in a growing cancer organoid using optical tweezers. f , E A of individual cells in the core, periphery and branch regions of the cancer organoid, quantified from slopes of the normalized force–displacement curves (inset). F and x are the resistant force and displacement of the trapped particle. S and a are the cross-section area and diameter of the particle. The boxes represent the interquartile range between the first and third quartiles, whereas the whiskers represent the 95% and 5% values, and the squares represent the<|im_end|> <|im_start|>assistant Engineers at MIT and elsewhere have tracked the evolution of individual cells within an initially benign tumor, showing how the physical properties of those cells drive the tumor to become invasive, or metastatic. The team carried out experiments with a human breast cancer tumor that developed in the lab. As the tumor grew and amassed more cells over a period of about two weeks, the researchers observed that cells in the interior of the tumor were small and stiff, while the cells on the periphery were soft and more swollen. These softer, peripheral cells were more apt to stretch beyond the tumor body, forming "invasive tips" that eventually broke away to spread elsewhere. The researchers found that the cells at the tumor's edges were softer because they contained more water than those in the center. The cells in the center of a tumor are surrounded by other cells that press inward, squeezing water out of the interior cells and into those cells at the periphery, through nanometer-sized channels between them called gap junctions. "You can think of the tumor like a sponge," says Ming Guo, assistant professor of mechanical engineering at MIT. "When they grow, they build up compressive stresses inside the tumor, and that will squeeze the water from the core out to the cells on the outside, which will slowly swell over time and become softer as well—therefore they are more able to invade." When the team treated the tumor to draw water out of peripheral cells, the cells became stiffer and less likely to form invasive tips. Conversely, when they flooded the tumor with a diluted solution, the same peripheral cells swelled and quickly formed long, branchlike tips that invaded the surrounding environment. The results, which the team reports in the journal Nature Physics, point to a new route for cancer therapy, focused on changing the physical properties of cancer cells to delay or even prevent a tumor from spreading. Guo's co-authors include lead author and MIT postdoc Yu Long Han, along with Guoqiang Xu, Zichen Gu, Jiawei Sun, Yukun Hao, Staish Kumar Gupta, Yiwei Li, and Wenhui Tang, from MIT; Adrian Pegoraro and Yuan Yuan of the Harvard John A. Paulson School of Engineering and Applied Sciences; Hui Li of the Chinese Academy of Sciences; Kaifu Li, Hua Kang, and Lianghong Teng of Capital Medical University in Beijing; and Jeffrey Fredberg of the Harvard T. H. Chan School of Public Health in Boston. Cell tweezing Scientists suspect that cancer cells that migrate from a main tumor are able to do so in part because of their softer, more pliable nature, enabling the cells to squeeze through the body's labrynthine vasculature and proliferate far from the initial tumor. Past experiments have shown this soft, migratory nature in individual cancer cells, but Guo's team is the first to explore the role of cell stiffness in a whole, developing tumor. "People have looked at single cells for a long time, but organisms are multicellular, three-dimensional systems," Guo says. "Each cell is a physical building block, and we're interested in how each single cell is regulating its own physical properties, as the cells develop into a tissue like a tumor or an organ." The researchers used recently developed techniques to grow healthy human epithelial cells in 3-D and transform them into a human breast cancer tumor in the lab. Over the next week, the researchers watched as the cells multiplied and coalesced into a benign primary tumor that comprised several hundred individual cells. Several times throughout the week, the researchers infused the growing number of cells with plastic particles. They then probed each individual cell's stiffness with optical tweezers, a technique in which researchers direct a highly focused laser beam at a cell. In this case, the team trained a laser on a plastic particle within each cell, pinning the particle in place, then applying a slight pulse in a attempt to move the particle within the cell, much like using tweezers to pick an egg shell out from the surrounding yolk. Guo says the degree to which researchers can move a particle gives them an idea for the stiffness of the surrounding cell: The more resistant the particle is to being moved, the stiffer a cell must be. In this way, the researchers found that the hundreds of cells within a single benign tumor exhibit a gradient of stiffness as well as size. The interior cells were smaller and stiffer, and the further the cells were from the core, the softer and larger they became. They also became more likely to stretch out from the spherical primary tumor and form branches, or invasive tips. To see whether altering cells' water content affects their invasive behavior, the team added low-molecular-weight polymers to the tumor solution to draw water out from cells, and found that the cells shrank, became more stiff, and were less likely to migrate away from the tumor—a measure that delayed metastasis. When they added water to dilute the tumor solution, the cells, particularly at the edges, swelled, became softer, and formed invasive tips more quickly. As a last test, the researchers obtained a sample of a patient's breast cancer tumor and measured the size of every cell within the tumor sample. They observed a gradient similar to what they found in their lab-derived tumor: Cells in the tumor's core were smaller than those closer to the periphery. "We found this doesn't just happen in a model system—it's real," Guo says. "This means we may be able to develop some treatment based on the physical picture, to target cell stiffness or size to see if that helps. If you make the cells stiffer, they are less likely to migrate, and that could potentially delay invasion." Perhaps one day, he says, clinicians may be able to look at a tumor and, based on the size and stiffness of cells, from the inside out, be able to say with some confidence whether a tumor will metastasize or not. "If there is an established size or stiffness gradient, you can know this will cause trouble," Guo says. "If there's no gradient, you can maybe safely say it's fine." <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 7935, 315, 279, 6070, 323, 734, 315, 2380, 33520, 92520, 54230, 39881, 14117, 41440, 389, 279, 29079, 323, 37015, 38793, 315, 35693, 7106, 6012, 11, 3686, 279, 41295, 16565, 430, 2633, 1521, 4455, 323, 872, 44219, 304, 8624, 7293, 31555, 16365, 13, 12362, 264, 92520, 54230, 33820, 1563, 9572, 2942, 590, 1646, 11, 584, 2472, 1618, 279, 29079, 323, 37015, 15740, 315, 10093, 11, 54245, 323, 7106, 17910, 315, 3927, 7917, 304, 2380, 15696, 13, 59813, 449, 7917, 304, 279, 2942, 590, 6332, 11, 7917, 520, 279, 2942, 590, 824, 94648, 323, 279, 53354, 4156, 527, 1766, 311, 387, 60826, 64230, 11, 8294, 323, 810, 8915, 13, 4314, 22936, 4442, 527, 6982, 311, 31889, 505, 1043, 20554, 54230, 15962, 6530, 1555, 13225, 49341, 82, 11, 279, 46735, 315, 902, 32174, 279, 9320, 311, 459, 53354, 82423, 13, 4314, 14955, 11415, 279, 3560, 315, 993, 9491, 354, 3342, 10020, 38793, 315, 35693, 7106, 6012, 304, 20438, 7471, 323, 8624, 33824, 13, 4802, 19048, 7917, 527, 8915, 6067, 47397, 11618, 24950, 505, 15207, 7645, 11, 10805, 65441, 30295, 323, 8603, 520, 279, 31206, 2237, 220, 16, 1174, 220, 17, 1174, 220, 18, 311, 2849, 71895, 11, 91621, 323, 12172, 520, 279, 35693, 2237, 220, 19, 1174, 220, 20, 1174, 220, 21, 1174, 220, 22, 1174, 220, 23, 1174, 220, 24, 1174, 220, 605, 662, 25218, 264, 92520, 54230, 20438, 11, 279, 24473, 2585, 315, 1521, 7106, 17910, 304, 3634, 323, 892, 374, 9200, 369, 279, 13709, 315, 22936, 17025, 323, 24156, 734, 13, 6168, 7246, 505, 22936, 6520, 336, 537, 10949, 374, 5938, 449, 19338, 11, 2737, 82102, 519, 27653, 13023, 11, 48006, 75815, 323, 9572, 220, 806, 1174, 220, 717, 1174, 220, 1032, 1174, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 220, 1114, 662, 763, 25181, 7917, 304, 55004, 11, 369, 3187, 11, 7319, 79212, 2968, 220, 972, 1174, 220, 777, 1174, 220, 508, 1174, 220, 1691, 1174, 10805, 65441, 30295, 220, 1313, 1174, 5226, 1429, 220, 1419, 323, 31139, 617, 1855, 1027, 11054, 439, 264, 7106, 98799, 315, 2204, 4595, 315, 9572, 220, 1187, 323, 617, 1027, 11223, 439, 4754, 11811, 369, 9572, 6514, 220, 914, 662, 18185, 279, 11471, 315, 304, 55004, 20414, 11, 16781, 7978, 617, 6982, 430, 279, 22936, 6012, 315, 7917, 527, 35319, 555, 872, 8162, 24175, 11, 2737, 719, 539, 7347, 311, 70334, 315, 279, 14932, 6303, 11, 2849, 90816, 323, 15696, 220, 1627, 1174, 220, 1544, 662, 32140, 11, 304, 279, 2317, 315, 264, 92520, 54230, 1887, 304, 279, 2380, 33520, 320, 18, 35, 8, 8162, 24175, 11, 433, 8625, 9987, 1268, 279, 7106, 17910, 315, 3927, 7917, 37377, 323, 16580, 15756, 414, 4500, 323, 30215, 13, 3296, 54952, 2389, 3768, 92914, 449, 29393, 14887, 10333, 388, 11, 584, 617, 8040, 264, 5452, 311, 6767, 27448, 5848, 17910, 11, 7106, 6012, 323, 9971, 5382, 30295, 315, 3927, 7917, 6957, 264, 7982, 92520, 54230, 220, 18, 35, 17659, 9572, 1646, 220, 806, 1174, 220, 717, 662, 3296, 15194, 279, 993, 9491, 354, 3342, 10020, 15740, 315, 3927, 7917, 2391, 279, 7982, 1920, 11, 584, 1505, 98882, 12912, 315, 35693, 7106, 17910, 430, 28696, 15756, 414, 2849, 30215, 13, 59813, 449, 7917, 304, 279, 2942, 590, 6332, 11, 1884, 520, 279, 53354, 6522, 6964, 527, 10819, 11, 64230, 323, 8294, 13, 578, 27378, 315, 2225, 279, 2849, 2547, 323, 279, 62607, 527, 8294, 520, 279, 53354, 6522, 6964, 11, 323, 279, 37015, 65649, 3752, 4954, 9693, 99705, 10753, 292, 30295, 3719, 16643, 13, 83045, 13225, 49341, 82, 320, 38, 31580, 8, 12207, 28321, 288, 1521, 4442, 11, 23377, 430, 1043, 20554, 54230, 15962, 6530, 1253, 6678, 279, 15740, 315, 279, 13468, 12912, 315, 35693, 6012, 13, 24296, 11, 279, 44032, 315, 279, 64230, 1207, 45541, 304, 279, 9572, 2942, 590, 16917, 32174, 279, 9320, 311, 459, 53354, 82423, 13, 4314, 14955, 11415, 264, 59557, 3560, 315, 993, 9491, 354, 3342, 10020, 38793, 315, 35693, 7106, 6012, 2345, 36046, 2849, 55307, 323, 8579, 6147, 49525, 15756, 414, 4500, 323, 53354, 30295, 13, 11266, 411, 59544, 9572, 2942, 17390, 617, 1027, 13882, 1511, 311, 1646, 67169, 1299, 64779, 59544, 51423, 304, 220, 18, 35, 7829, 6067, 220, 1591, 2652, 1521, 4211, 55099, 275, 6468, 86055, 53194, 4519, 315, 64779, 59544, 39881, 323, 12602, 279, 89961, 4519, 315, 64779, 59544, 15756, 2530, 13, 1789, 3187, 11, 279, 1664, 12, 10767, 64779, 59544, 18112, 9221, 69627, 11, 279, 326, 28999, 41687, 449, 7917, 323, 53354, 23962, 1243, 1376, 220, 1591, 662, 2057, 16805, 279, 22936, 1234, 79, 6258, 826, 315, 420, 1920, 11, 584, 20429, 1599, 386, 9847, 220, 605, 32, 3823, 17659, 64779, 59544, 7917, 449, 264, 6307, 74864, 13128, 320, 38, 11960, 8, 38213, 449, 264, 11499, 41160, 2065, 8450, 320, 45, 7416, 570, 1226, 1243, 90916, 1521, 7917, 1139, 264, 220, 18, 35, 958, 2821, 17820, 1113, 4009, 17055, 29952, 24306, 315, 220, 20, 14060, 16116, 25173, 16, 17797, 3357, 323, 220, 19, 14060, 16116, 25173, 16, 7011, 14746, 301, 220, 717, 1174, 449, 264, 65344, 75124, 3345, 311, 220, 3101, 16056, 311, 56459, 279, 22936, 8162, 24175, 315, 264, 17659, 89468, 304, 41294, 220, 717, 1174, 220, 1682, 662, 28757, 505, 264, 3254, 2849, 11, 264, 92520, 54230, 10879, 28815, 11, 323, 53354, 23962, 2274, 927, 13489, 220, 605, 2919, 320, 30035, 13, 220, 16, 64, 4235, 66, 7048, 304, 18859, 449, 3293, 17931, 11, 584, 1650, 420, 10879, 264, 9572, 2942, 590, 220, 966, 662, 12220, 279, 4216, 6566, 11, 459, 3927, 386, 9847, 220, 605, 32, 2849, 43036, 988, 311, 1376, 264, 65251, 10879, 320, 22928, 6566, 26, 23966, 13, 220, 16, 64, 1174, 1938, 220, 18, 570, 1115, 2849, 10879, 28815, 1139, 264, 8294, 274, 29182, 590, 449, 7917, 2225, 304, 279, 6332, 323, 389, 279, 824, 94648, 320, 20231, 6566, 26, 23966, 13, 220, 16, 65, 1174, 1938, 220, 20, 570, 1666, 420, 274, 29182, 590, 39671, 4726, 11, 53354, 23962, 13334, 505, 279, 1925, 2547, 323, 75272, 279, 14932, 11741, 65441, 6303, 320, 7650, 44, 8, 320, 68676, 6566, 26, 23966, 13, 220, 16, 66, 1174, 1938, 220, 605, 570, 578, 82423, 13468, 304, 420, 220, 18, 35, 17659, 9572, 1646, 5039, 653, 59707, 35693, 53840, 11, 6996, 315, 35693, 83245, 323, 279, 61568, 315, 6303, 30215, 11, 1790, 1093, 1884, 13468, 304, 41294, 304, 53354, 45339, 278, 52788, 23063, 320, 30035, 13, 220, 16, 67, 7609, 1115, 83379, 449, 264, 4725, 1645, 14080, 6070, 430, 39671, 994, 7917, 527, 90916, 304, 264, 8579, 6303, 320, 10254, 67082, 23966, 13, 220, 16, 7609, 23966, 13, 220, 16, 25, 38321, 315, 30548, 76730, 323, 1207, 8539, 7607, 315, 2849, 70334, 304, 279, 7982, 9572, 2942, 590, 13, 264, 1389, 272, 1174, 11511, 22327, 5448, 315, 64779, 59544, 9572, 2942, 590, 8040, 505, 61170, 38584, 32901, 386, 9847, 220, 605, 32, 7917, 520, 2204, 18094, 25, 4216, 6566, 320, 1316, 220, 18, 26, 264, 7026, 6278, 6566, 320, 1316, 220, 20, 26, 293, 883, 323, 3010, 6566, 320, 1316, 220, 605, 26, 272, 7609, 294, 1174, 14433, 336, 4428, 4223, 3817, 323, 62894, 258, 63563, 505, 12239, 12, 17, 27590, 10, 53354, 45339, 278, 89468, 3823, 17659, 9572, 20438, 10688, 13, 350, 372, 414, 82375, 527, 16717, 1701, 2579, 38057, 13, 384, 1174, 328, 82149, 315, 279, 9693, 99705, 10753, 292, 30126, 323, 30295, 22323, 304, 264, 7982, 9572, 2942, 590, 1701, 29393, 14887, 10333, 388, 13, 282, 1174, 469, 362, 315, 3927, 7917, 304, 279, 6332, 11, 824, 94648, 323, 9046, 13918, 315, 279, 9572, 2942, 590, 11, 10484, 1908, 505, 60108, 315, 279, 30510, 5457, 4235, 4338, 16491, 37033, 320, 258, 751, 570, 435, 323, 865, 527, 279, 31785, 5457, 323, 44153, 315, 279, 31691, 19320, 13, 328, 323, 264, 527, 279, 5425, 22327, 3158, 323, 23899, 315, 279, 19320, 13, 578, 15039, 4097, 279, 958, 447, 472, 458, 2134, 1990, 279, 1176, 323, 4948, 41376, 3742, 11, 20444, 279, 41759, 388, 4097, 279, 220, 2721, 4, 323, 220, 20, 4, 2819, 11, 323, 279, 32440, 4097, 279, 128257, 198, 128256, 78191, 198, 4674, 388, 520, 15210, 323, 18403, 617, 34156, 279, 15740, 315, 3927, 7917, 2949, 459, 15453, 65309, 36254, 11, 9204, 1268, 279, 7106, 6012, 315, 1884, 7917, 6678, 279, 36254, 311, 3719, 53354, 11, 477, 68370, 780, 13, 578, 2128, 11953, 704, 21896, 449, 264, 3823, 17659, 9572, 36254, 430, 8040, 304, 279, 10278, 13, 1666, 279, 36254, 14264, 323, 93250, 810, 7917, 927, 264, 4261, 315, 922, 1403, 5672, 11, 279, 12074, 13468, 430, 7917, 304, 279, 15135, 315, 279, 36254, 1051, 2678, 323, 31161, 11, 1418, 279, 7917, 389, 279, 824, 94648, 1051, 8579, 323, 810, 76193, 13, 4314, 64230, 11, 35688, 7917, 1051, 810, 20697, 311, 14841, 7953, 279, 36254, 2547, 11, 30164, 330, 258, 78134, 10631, 1, 430, 9778, 14760, 3201, 311, 9041, 18403, 13, 578, 12074, 1766, 430, 279, 7917, 520, 279, 36254, 596, 13116, 1051, 64230, 1606, 814, 13282, 810, 3090, 1109, 1884, 304, 279, 4219, 13, 578, 7917, 304, 279, 4219, 315, 264, 36254, 527, 23712, 555, 1023, 7917, 430, 3577, 63018, 11, 88807, 3090, 704, 315, 279, 15135, 7917, 323, 1139, 1884, 7917, 520, 279, 824, 94648, 11, 1555, 20622, 21037, 28935, 12006, 1990, 1124, 2663, 13225, 49341, 82, 13, 330, 2675, 649, 1781, 315, 279, 36254, 1093, 264, 69448, 1359, 2795, 56983, 4673, 78, 11, 18328, 14561, 315, 22936, 15009, 520, 15210, 13, 330, 4599, 814, 3139, 11, 814, 1977, 709, 25633, 535, 59623, 4871, 279, 36254, 11, 323, 430, 690, 37663, 279, 3090, 505, 279, 6332, 704, 311, 279, 7917, 389, 279, 4994, 11, 902, 690, 14297, 78353, 927, 892, 323, 3719, 64230, 439, 1664, 2345, 19041, 1348, 814, 527, 810, 3025, 311, 75272, 1210, 3277, 279, 2128, 12020, 279, 36254, 311, 4128, 3090, 704, 315, 35688, 7917, 11, 279, 7917, 6244, 357, 14657, 323, 2753, 4461, 311, 1376, 53354, 10631, 13, 82671, 11, 994, 814, 49886, 279, 36254, 449, 264, 80703, 6425, 11, 279, 1890, 35688, 7917, 2064, 15556, 323, 6288, 14454, 1317, 11, 9046, 4908, 10631, 430, 64765, 279, 14932, 4676, 13, 578, 3135, 11, 902, 279, 2128, 6821, 304, 279, 8486, 22037, 28415, 11, 1486, 311, 264, 502, 6149, 369, 9572, 15419, 11, 10968, 389, 10223, 279, 7106, 6012, 315, 9572, 7917, 311, 7781, 477, 1524, 5471, 264, 36254, 505, 31135, 13, 4673, 78, 596, 1080, 34603, 1105, 2997, 3063, 3229, 323, 15210, 1772, 5349, 28372, 5843, 21296, 11, 3235, 449, 4673, 108268, 28323, 57514, 11, 1901, 29424, 4673, 11, 55551, 38685, 8219, 11, 58763, 359, 94809, 11, 60920, 819, 41240, 74798, 11, 48934, 28204, 14851, 11, 323, 468, 40967, 2005, 41462, 11, 505, 15210, 26, 44692, 50766, 269, 17606, 323, 69984, 69984, 315, 279, 25996, 3842, 362, 13, 7043, 942, 6150, 315, 17005, 323, 43608, 23199, 26, 473, 2005, 14851, 315, 279, 8620, 16192, 315, 23199, 26, 23109, 21519, 14851, 11, 473, 4381, 55376, 11, 323, 14851, 526, 111882, 350, 833, 315, 18880, 13235, 3907, 304, 27647, 26, 323, 42107, 28588, 7881, 315, 279, 25996, 350, 13, 473, 13, 42402, 6150, 315, 3142, 6401, 304, 10406, 13, 14299, 14887, 10333, 287, 57116, 15562, 430, 9572, 7917, 430, 45666, 505, 264, 1925, 36254, 527, 3025, 311, 656, 779, 304, 961, 1606, 315, 872, 64230, 11, 810, 628, 2205, 7138, 11, 28462, 279, 7917, 311, 37663, 1555, 279, 2547, 596, 10278, 894, 52838, 483, 44496, 3395, 1598, 323, 43036, 349, 3117, 505, 279, 2926, 36254, 13, 24561, 21896, 617, 6982, 420, 8579, 11, 9971, 5382, 7138, 304, 3927, 9572, 7917, 11, 719, 4673, 78, 596, 2128, 374, 279, 1176, 311, 13488, 279, 3560, 315, 2849, 70334, 304, 264, 4459, 11, 11469, 36254, 13, 330, 16298, 617, 7111, 520, 3254, 7917, 369, 264, 1317, 892, 11, 719, 44304, 527, 92520, 54230, 11, 2380, 33520, 6067, 1359, 4673, 78, 2795, 13, 330, 4959, 2849, 374, 264, 7106, 4857, 2565, 11, 323, 584, 2351, 8173, 304, 1268, 1855, 3254, 2849, 374, 58499, 1202, 1866, 7106, 6012, 11, 439, 279, 7917, 2274, 1139, 264, 20438, 1093, 264, 36254, 477, 459, 2942, 1210, 578, 12074, 1511, 6051, 8040, 12823, 311, 3139, 9498, 3823, 64779, 59544, 7917, 304, 220, 18, 9607, 323, 5276, 1124, 1139, 264, 3823, 17659, 9572, 36254, 304, 279, 10278, 13, 6193, 279, 1828, 2046, 11, 279, 12074, 15746, 439, 279, 7917, 56016, 323, 1080, 3916, 2041, 1139, 264, 65309, 6156, 36254, 430, 40056, 3892, 7895, 3927, 7917, 13, 26778, 3115, 6957, 279, 2046, 11, 279, 12074, 72903, 279, 7982, 1396, 315, 7917, 449, 12466, 19252, 13, 2435, 1243, 463, 2788, 1855, 3927, 2849, 596, 70334, 449, 29393, 14887, 10333, 388, 11, 264, 15105, 304, 902, 12074, 2167, 264, 7701, 10968, 21120, 24310, 520, 264, 2849, 13, 763, 420, 1162, 11, 279, 2128, 16572, 264, 21120, 389, 264, 12466, 19320, 2949, 1855, 2849, 11, 9160, 1251, 279, 19320, 304, 2035, 11, 1243, 19486, 264, 8275, 28334, 304, 264, 4879, 311, 3351, 279, 19320, 2949, 279, 2849, 11, 1790, 1093, 1701, 14887, 10333, 388, 311, 3820, 459, 19151, 12811, 704, 505, 279, 14932, 379, 23427, 13, 4673, 78, 2795, 279, 8547, 311, 902, 12074, 649, 3351, 264, 19320, 6835, 1124, 459, 4623, 369, 279, 70334, 315, 279, 14932, 2849, 25, 578, 810, 31785, 279, 19320, 374, 311, 1694, 7882, 11, 279, 357, 14657, 264, 2849, 2011, 387, 13, 763, 420, 1648, 11, 279, 12074, 1766, 430, 279, 11758, 315, 7917, 2949, 264, 3254, 65309, 36254, 31324, 264, 20779, 315, 70334, 439, 1664, 439, 1404, 13, 578, 15135, 7917, 1051, 9333, 323, 357, 14657, 11, 323, 279, 4726, 279, 7917, 1051, 505, 279, 6332, 11, 279, 64230, 323, 8294, 814, 6244, 13, 2435, 1101, 6244, 810, 4461, 311, 14841, 704, 505, 279, 65251, 6156, 36254, 323, 1376, 23962, 11, 477, 53354, 10631, 13, 2057, 1518, 3508, 60923, 7917, 6, 3090, 2262, 22223, 872, 53354, 7865, 11, 279, 2128, 3779, 3428, 1474, 43943, 12923, 46033, 388, 311, 279, 36254, 6425, 311, 4128, 3090, 704, 505, 7917, 11, 323, 1766, 430, 279, 7917, 559, 13430, 11, 6244, 810, 31161, 11, 323, 1051, 2753, 4461, 311, 45666, 3201, 505, 279, 36254, 29096, 6767, 430, 23540, 68370, 10949, 13, 3277, 814, 3779, 3090, 311, 19371, 1088, 279, 36254, 6425, 11, 279, 7917, 11, 8104, 520, 279, 13116, 11, 2064, 15556, 11, 6244, 64230, 11, 323, 14454, 53354, 10631, 810, 6288, 13, 1666, 264, 1566, 1296, 11, 279, 12074, 12457, 264, 6205, 315, 264, 8893, 596, 17659, 9572, 36254, 323, 17303, 279, 1404, 315, 1475, 2849, 2949, 279, 36254, 6205, 13, 2435, 13468, 264, 20779, 4528, 311, 1148, 814, 1766, 304, 872, 10278, 72286, 36254, 25, 59190, 304, 279, 36254, 596, 6332, 1051, 9333, 1109, 1884, 12401, 311, 279, 824, 94648, 13, 330, 1687, 1766, 420, 3250, 956, 1120, 3621, 304, 264, 1646, 1887, 44603, 596, 1972, 1359, 4673, 78, 2795, 13, 330, 2028, 3445, 584, 1253, 387, 3025, 311, 2274, 1063, 6514, 3196, 389, 279, 7106, 6945, 11, 311, 2218, 2849, 70334, 477, 1404, 311, 1518, 422, 430, 8779, 13, 1442, 499, 1304, 279, 7917, 357, 14657, 11, 814, 527, 2753, 4461, 311, 45666, 11, 323, 430, 1436, 13893, 7781, 30215, 1210, 19292, 832, 1938, 11, 568, 2795, 11, 78545, 1253, 387, 3025, 311, 1427, 520, 264, 36254, 323, 11, 3196, 389, 279, 1404, 323, 70334, 315, 7917, 11, 505, 279, 4871, 704, 11, 387, 3025, 311, 2019, 449, 1063, 12410, 3508, 264, 36254, 690, 68370, 300, 553, 477, 539, 13, 330, 2746, 1070, 374, 459, 9749, 1404, 477, 70334, 20779, 11, 499, 649, 1440, 420, 690, 5353, 12544, 1359, 4673, 78, 2795, 13, 330, 2746, 1070, 596, 912, 20779, 11, 499, 649, 7344, 21676, 2019, 433, 596, 7060, 1210, 220, 128257, 198 ]

2,624

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Induced pluripotent stem cells (iPSCs) undergo unlimited self-renewal while maintaining their potential to differentiate into post-mitotic cells with an intact proteome. As such, iPSCs suppress the aggregation of polyQ-expanded huntingtin (HTT), the mutant protein underlying Huntington’s disease (HD). Here we show that proteasome activity determines HTT levels, preventing polyQ-expanded aggregation in iPSCs from HD patients (HD-iPSCs). iPSCs exhibit high levels of UBR5, a ubiquitin ligase required for proteasomal degradation of both normal and mutant HTT. Conversely, loss of UBR5 increases HTT levels and triggers polyQ-expanded aggregation in HD-iPSCs. Moreover, UBR5 knockdown hastens polyQ-expanded aggregation and neurotoxicity in invertebrate models. Notably, UBR5 overexpression induces polyubiquitination and degradation of mutant HTT, reducing polyQ-expanded aggregates in HD-cell models. Besides HTT levels, intrinsic enhanced UBR5 expression determines global proteostasis of iPSCs preventing the aggregation of misfolded proteins ensued from normal metabolism. Thus, our findings indicate UBR5 as a modulator of super-vigilant proteostasis of iPSCs. Introduction As the origin of multicellular organisms, a series of cellular quality control mechanisms must operate at high fidelity in pluripotent stem cells 1 . In culture, embryonic stem cells (ESCs) derived from blastocysts do not undergo senescence and can replicate indefinitely while maintaining their capacity to differentiate into all cell lineages 2 . Alternatively, somatic cells can be reprogrammed to generate induced pluripotent stem cells (iPSCs), which are similar to ESCs in many respects, such as their gene expression, potential for differentiation and ability to replicate continuously 3 . This unlimited self-renewal capacity requires stringent quality control mechanisms, including increased DNA damage responses and antioxidant defense systems 1 , 4 , 5 , 6 , 7 . Growing evidence indicates that pluripotent stem cells also have intrinsic mechanisms to maintain the integrity of the proteome, a critical process for organismal development and cell function 7 , 8 , 9 . Hence, defining the mechanisms of super-vigilant proteostasis in these cells is of central importance. The proteostasis network is formed by multiple integrated processes that control the concentration, folding, location and interactions of proteins from their synthesis through their degradation 10 . Defects in proteostasis lead to the accumulation of damaged, misfolded and aggregated proteins that may alter the immortality of pluripotent stem cells. During the asymmetric divisions invoked by these cells, the passage of damaged proteins to progenitor cells could compromise organismal development and aging. Thus, pluripotent stem cells have a tightly regulated proteostasis network linked with their intrinsic characteristics and biological function 1 , 7 . While ESC identity requires enhanced global translational rates 11 , these cells also exhibit high levels of distinct chaperones to assure proper protein folding 5 , 9 . For instance, ESCs have increased assembly of the TRiC/CCT (T-complex protein-1 (TCP-1) ring complex)/(chaperonin containing TCP-1) complex 12 , a chaperonin that facilitates the folding of approximately 15% of the proteome and reduces the aggregation of disease-related mutant proteins 13 . To terminate damaged proteins, ESCs possess a powerful proteolytic machinery induced by high levels of PSMD11/RPN6 14 , 15 , 16 , a scaffolding subunit that promotes the assembly of active proteasomes 16 , 17 . Remarkably, pluripotent stem cells are able to maintain enhanced proteostasis while proliferating indefinitely in their undifferentiated state 1 , 7 , 8 . However, the differentiation process triggers a rewiring of the proteostasis network that reduces their ability to sustain proteome integrity 7 , 8 , 9 . In addition, post-mitotic and progenitor cells as well as somatic stem cells undergo a progressive decline in their protein folding and clearance activities with age 8 , 18 , 19 . This demise of proteostasis is linked with the onset of age-related disorders such as Alzheimer’s, Parkinson’s and Huntington’s disease (HD) 10 , 18 . On the other hand, the proteostasis network of somatic cells is rewired during cell reprogramming to generate iPSCs with high assembly of active TRiC/CCT and proteasome complexes, resembling ESCs 9 , 12 , 16 , 20 . HD is a fatal neurodegenerative disorder characterized by cognitive deficits, psychosis and motor dysfunction. The disease is inherited in a dominant manner and caused by mutations in the huntingtin ( HTT ) gene, which translates into an expanded polyglutamine stretch (polyQ) 21 . The wild-type HTT gene encodes a large protein of approximately 350 kDa that contains 6–35 polyQ repeats. In individuals affected by HD, HTT contains greater than 35 polyQ repeats 21 . Although loss of normal HTT function could also be a determinant of HD 22 , the dominant inheritance pattern of the disease and numerous experiments in model organisms indicate that gain of function of mutant HTT is toxic and induces neurodegeneration 21 , 23 , 24 . PolyQ-expanded HTT is prone to aggregation, and the accumulation of mutant HTT fibrils as well as intermediate oligomers formed during the aggregation/disaggregation process contributes to neurodegeneration 21 , 23 , 24 . The longer the polyQ-expanded repeat, the earlier HD symptoms (e.g., neurodegeneration) typically appear 21 . However, the length of the pathological polyQ does not affect survival, self-renewal and pluripotency of iPSCs derived from HD patients (HD-iPSCs), which can proliferate indefinitely as control iPSCs 25 , 26 . Moreover, HD-iPSCs do not accumulate polyQ-expanded inclusions 12 , 25 , 27 . These findings indicate that iPSCs have increased mechanisms to maintain proteostasis of mutant HTT. Once differentiated into neural progenitors and neurons, these cells exhibit HD-associated phenotypes such as altered gene expression, increased vulnerability to excitotoxic stressors and cumulative risk of death over time 25 , 28 . However, HD neurons lack polyQ aggregates and robust neurodegeneration phenotype 12 , 25 , 27 , supporting a proteostasis-rejuvenating process during cell reprogramming that allows for HD-iPSC differentiation into neurons with an intact proteome. Although cumulative evidence indicates a strong link between HD-related changes and proteasomal dysfunction 29 , the mechanisms by which the proteasome recognizes polyQ-expanded HTT are poorly understood. With the high levels of proteasome activity exhibited by iPSCs 16 , we ask whether these cells have an intrinsic E3 ubiquitin ligase network to", "role": "user" }, { "content": "Neuroscientist Dr. David Vilchez and his team at CECAD, the University of Cologne's Cluster of Excellence for Aging Research, have made an important step toward understanding the mechanisms that cause the neurodegenerative disorder Huntington's disease. Specifically, they identified a system blocking the accumulation of toxin protein aggregates, which are responsible for neurodegeneration. The results have now been published in the journal Nature Communications. Huntington's disease is a neurodegenerative disorder that results in the death of brain cells, leading to uncontrolled body movement, loss of speech, and psychosis. Mutations in the huntingtin gene cause the disease, resulting in the toxic aggregation of the huntingtin protein. The accumulation of these aggregates causes neurodegeneration and usually leads to the patient's death within 20 years after the onset of the disease. To examine the mechanisms underlying Huntington's disease, Vilchez and his team used so-called induced pluripotent stem cells (iPSC) from Huntington's disease patients, which are able to differentiate into any cell type, such as neurons. Induced pluripotent stem cells derived from patients with Huntington's disease exhibit a striking ability to avoid the accumulation of toxic protein aggregates, a hallmark of the disease. Even though iPSCs express the mutant gene responsible for Huntington's disease, no aggregates were found. The researchers identified a protein called UBR5 as a protective mechanism for the cells, promoting the degradation of mutant huntingtin. These findings can contribute to a better understanding of Huntington's disease and could be a stepping stone to developing further treatment in patients. The researchers screened immortal iPSCs from patients and derived neurons for differences in their ability to avoid mutant huntingtin aggregation. They found that huntingtin can be degraded by the cellular disposal system known as the proteasome. However, this system is defective in the neurons, which leads to the aberrant aggregation of the mutant huntingtin protein. Vilchez and his team found that UBR5 is increased in pluripotent stem cells to accelerate the degradation of huntingtin in the cells. To examine the role of UBR5 in the regulation of the mutant huntingtin gene (HTT), they reduced the levels of UBR5 and could immediately see an accumulation of aggregated proteins in iPSCs. \"This was striking to see,\" says Vilchez. \"From nothing, the cells went to huge amounts of aggregates.\" The authors went a step further and examined whether UBR5 also controls mutant huntingtin aggregation in Huntington's disease organismal models. They found that dysregulation of UBR5 results in a massive increase in the aggregation and neurotoxic effects in neurons. On the other hand, promoting UBR5 activity blocks mutant huntingtin aggregation in the Huntington's disease models. To test the specificity of the results, the researchers also kept an eye on other illnesses. \"We also checked the mechanism in other neurodegenerative diseases like amyotrophic lateral sclerosis,\" says Seda Koyuncu, a doctoral student working in Vilchez's lab and a main author of the publication. \"Our result is very specific to Huntington's disease,\" adds Dr. Isabel Saez, another main author working with Vilchez at CECAD. Even though the results could be important for treatment and drug development, there is no therapy yet. \"It's not like you discover something new and then there is a cure, it's more difficult—but in some years, there might be a therapy,\" Saez says. Until then, more research needs to be done. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Induced pluripotent stem cells (iPSCs) undergo unlimited self-renewal while maintaining their potential to differentiate into post-mitotic cells with an intact proteome. As such, iPSCs suppress the aggregation of polyQ-expanded huntingtin (HTT), the mutant protein underlying Huntington’s disease (HD). Here we show that proteasome activity determines HTT levels, preventing polyQ-expanded aggregation in iPSCs from HD patients (HD-iPSCs). iPSCs exhibit high levels of UBR5, a ubiquitin ligase required for proteasomal degradation of both normal and mutant HTT. Conversely, loss of UBR5 increases HTT levels and triggers polyQ-expanded aggregation in HD-iPSCs. Moreover, UBR5 knockdown hastens polyQ-expanded aggregation and neurotoxicity in invertebrate models. Notably, UBR5 overexpression induces polyubiquitination and degradation of mutant HTT, reducing polyQ-expanded aggregates in HD-cell models. Besides HTT levels, intrinsic enhanced UBR5 expression determines global proteostasis of iPSCs preventing the aggregation of misfolded proteins ensued from normal metabolism. Thus, our findings indicate UBR5 as a modulator of super-vigilant proteostasis of iPSCs. Introduction As the origin of multicellular organisms, a series of cellular quality control mechanisms must operate at high fidelity in pluripotent stem cells 1 . In culture, embryonic stem cells (ESCs) derived from blastocysts do not undergo senescence and can replicate indefinitely while maintaining their capacity to differentiate into all cell lineages 2 . Alternatively, somatic cells can be reprogrammed to generate induced pluripotent stem cells (iPSCs), which are similar to ESCs in many respects, such as their gene expression, potential for differentiation and ability to replicate continuously 3 . This unlimited self-renewal capacity requires stringent quality control mechanisms, including increased DNA damage responses and antioxidant defense systems 1 , 4 , 5 , 6 , 7 . Growing evidence indicates that pluripotent stem cells also have intrinsic mechanisms to maintain the integrity of the proteome, a critical process for organismal development and cell function 7 , 8 , 9 . Hence, defining the mechanisms of super-vigilant proteostasis in these cells is of central importance. The proteostasis network is formed by multiple integrated processes that control the concentration, folding, location and interactions of proteins from their synthesis through their degradation 10 . Defects in proteostasis lead to the accumulation of damaged, misfolded and aggregated proteins that may alter the immortality of pluripotent stem cells. During the asymmetric divisions invoked by these cells, the passage of damaged proteins to progenitor cells could compromise organismal development and aging. Thus, pluripotent stem cells have a tightly regulated proteostasis network linked with their intrinsic characteristics and biological function 1 , 7 . While ESC identity requires enhanced global translational rates 11 , these cells also exhibit high levels of distinct chaperones to assure proper protein folding 5 , 9 . For instance, ESCs have increased assembly of the TRiC/CCT (T-complex protein-1 (TCP-1) ring complex)/(chaperonin containing TCP-1) complex 12 , a chaperonin that facilitates the folding of approximately 15% of the proteome and reduces the aggregation of disease-related mutant proteins 13 . To terminate damaged proteins, ESCs possess a powerful proteolytic machinery induced by high levels of PSMD11/RPN6 14 , 15 , 16 , a scaffolding subunit that promotes the assembly of active proteasomes 16 , 17 . Remarkably, pluripotent stem cells are able to maintain enhanced proteostasis while proliferating indefinitely in their undifferentiated state 1 , 7 , 8 . However, the differentiation process triggers a rewiring of the proteostasis network that reduces their ability to sustain proteome integrity 7 , 8 , 9 . In addition, post-mitotic and progenitor cells as well as somatic stem cells undergo a progressive decline in their protein folding and clearance activities with age 8 , 18 , 19 . This demise of proteostasis is linked with the onset of age-related disorders such as Alzheimer’s, Parkinson’s and Huntington’s disease (HD) 10 , 18 . On the other hand, the proteostasis network of somatic cells is rewired during cell reprogramming to generate iPSCs with high assembly of active TRiC/CCT and proteasome complexes, resembling ESCs 9 , 12 , 16 , 20 . HD is a fatal neurodegenerative disorder characterized by cognitive deficits, psychosis and motor dysfunction. The disease is inherited in a dominant manner and caused by mutations in the huntingtin ( HTT ) gene, which translates into an expanded polyglutamine stretch (polyQ) 21 . The wild-type HTT gene encodes a large protein of approximately 350 kDa that contains 6–35 polyQ repeats. In individuals affected by HD, HTT contains greater than 35 polyQ repeats 21 . Although loss of normal HTT function could also be a determinant of HD 22 , the dominant inheritance pattern of the disease and numerous experiments in model organisms indicate that gain of function of mutant HTT is toxic and induces neurodegeneration 21 , 23 , 24 . PolyQ-expanded HTT is prone to aggregation, and the accumulation of mutant HTT fibrils as well as intermediate oligomers formed during the aggregation/disaggregation process contributes to neurodegeneration 21 , 23 , 24 . The longer the polyQ-expanded repeat, the earlier HD symptoms (e.g., neurodegeneration) typically appear 21 . However, the length of the pathological polyQ does not affect survival, self-renewal and pluripotency of iPSCs derived from HD patients (HD-iPSCs), which can proliferate indefinitely as control iPSCs 25 , 26 . Moreover, HD-iPSCs do not accumulate polyQ-expanded inclusions 12 , 25 , 27 . These findings indicate that iPSCs have increased mechanisms to maintain proteostasis of mutant HTT. Once differentiated into neural progenitors and neurons, these cells exhibit HD-associated phenotypes such as altered gene expression, increased vulnerability to excitotoxic stressors and cumulative risk of death over time 25 , 28 . However, HD neurons lack polyQ aggregates and robust neurodegeneration phenotype 12 , 25 , 27 , supporting a proteostasis-rejuvenating process during cell reprogramming that allows for HD-iPSC differentiation into neurons with an intact proteome. Although cumulative evidence indicates a strong link between HD-related changes and proteasomal dysfunction 29 , the mechanisms by which the proteasome recognizes polyQ-expanded HTT are poorly understood. With the high levels of proteasome activity exhibited by iPSCs 16 , we ask whether these cells have an intrinsic E3 ubiquitin ligase network to<|im_end|> <|im_start|>assistant Neuroscientist Dr. David Vilchez and his team at CECAD, the University of Cologne's Cluster of Excellence for Aging Research, have made an important step toward understanding the mechanisms that cause the neurodegenerative disorder Huntington's disease. Specifically, they identified a system blocking the accumulation of toxin protein aggregates, which are responsible for neurodegeneration. The results have now been published in the journal Nature Communications. Huntington's disease is a neurodegenerative disorder that results in the death of brain cells, leading to uncontrolled body movement, loss of speech, and psychosis. Mutations in the huntingtin gene cause the disease, resulting in the toxic aggregation of the huntingtin protein. The accumulation of these aggregates causes neurodegeneration and usually leads to the patient's death within 20 years after the onset of the disease. To examine the mechanisms underlying Huntington's disease, Vilchez and his team used so-called induced pluripotent stem cells (iPSC) from Huntington's disease patients, which are able to differentiate into any cell type, such as neurons. Induced pluripotent stem cells derived from patients with Huntington's disease exhibit a striking ability to avoid the accumulation of toxic protein aggregates, a hallmark of the disease. Even though iPSCs express the mutant gene responsible for Huntington's disease, no aggregates were found. The researchers identified a protein called UBR5 as a protective mechanism for the cells, promoting the degradation of mutant huntingtin. These findings can contribute to a better understanding of Huntington's disease and could be a stepping stone to developing further treatment in patients. The researchers screened immortal iPSCs from patients and derived neurons for differences in their ability to avoid mutant huntingtin aggregation. They found that huntingtin can be degraded by the cellular disposal system known as the proteasome. However, this system is defective in the neurons, which leads to the aberrant aggregation of the mutant huntingtin protein. Vilchez and his team found that UBR5 is increased in pluripotent stem cells to accelerate the degradation of huntingtin in the cells. To examine the role of UBR5 in the regulation of the mutant huntingtin gene (HTT), they reduced the levels of UBR5 and could immediately see an accumulation of aggregated proteins in iPSCs. "This was striking to see," says Vilchez. "From nothing, the cells went to huge amounts of aggregates." The authors went a step further and examined whether UBR5 also controls mutant huntingtin aggregation in Huntington's disease organismal models. They found that dysregulation of UBR5 results in a massive increase in the aggregation and neurotoxic effects in neurons. On the other hand, promoting UBR5 activity blocks mutant huntingtin aggregation in the Huntington's disease models. To test the specificity of the results, the researchers also kept an eye on other illnesses. "We also checked the mechanism in other neurodegenerative diseases like amyotrophic lateral sclerosis," says Seda Koyuncu, a doctoral student working in Vilchez's lab and a main author of the publication. "Our result is very specific to Huntington's disease," adds Dr. Isabel Saez, another main author working with Vilchez at CECAD. Even though the results could be important for treatment and drug development, there is no therapy yet. "It's not like you discover something new and then there is a cure, it's more difficult—but in some years, there might be a therapy," Saez says. Until then, more research needs to be done. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 2314, 24921, 60217, 575, 64632, 19646, 7917, 320, 72, 47, 3624, 82, 8, 37771, 27862, 659, 5621, 943, 278, 1418, 20958, 872, 4754, 311, 54263, 1139, 1772, 1474, 275, 14546, 7917, 449, 459, 35539, 5541, 638, 13, 1666, 1778, 11, 77586, 3624, 82, 28321, 279, 52729, 315, 10062, 48, 31136, 23330, 57071, 320, 2607, 51, 705, 279, 61618, 13128, 16940, 75851, 753, 8624, 320, 19694, 570, 5810, 584, 1501, 430, 5541, 300, 638, 5820, 27667, 5373, 51, 5990, 11, 27252, 10062, 48, 31136, 52729, 304, 77586, 3624, 82, 505, 12445, 6978, 320, 19694, 18064, 47, 3624, 82, 570, 77586, 3624, 82, 31324, 1579, 5990, 315, 549, 13396, 20, 11, 264, 53336, 85986, 29413, 521, 2631, 369, 5541, 300, 53911, 53568, 315, 2225, 4725, 323, 61618, 5373, 51, 13, 82671, 11, 4814, 315, 549, 13396, 20, 12992, 5373, 51, 5990, 323, 31854, 10062, 48, 31136, 52729, 304, 12445, 18064, 47, 3624, 82, 13, 23674, 11, 549, 13396, 20, 14459, 2996, 34143, 729, 10062, 48, 31136, 52729, 323, 18247, 998, 14668, 488, 304, 304, 65932, 65216, 4211, 13, 2876, 2915, 11, 549, 13396, 20, 927, 29199, 90974, 10062, 392, 5118, 275, 2617, 323, 53568, 315, 61618, 5373, 51, 11, 18189, 10062, 48, 31136, 71643, 304, 12445, 33001, 4211, 13, 31909, 5373, 51, 5990, 11, 47701, 24872, 549, 13396, 20, 7645, 27667, 3728, 5541, 537, 10949, 315, 77586, 3624, 82, 27252, 279, 52729, 315, 5906, 20557, 291, 28896, 96763, 505, 4725, 39097, 13, 14636, 11, 1057, 14955, 13519, 549, 13396, 20, 439, 264, 1491, 10733, 315, 2307, 8437, 343, 321, 519, 5541, 537, 10949, 315, 77586, 3624, 82, 13, 29438, 1666, 279, 6371, 315, 92520, 54230, 44304, 11, 264, 4101, 315, 35693, 4367, 2585, 24717, 2011, 14816, 520, 1579, 83604, 304, 60217, 575, 64632, 19646, 7917, 220, 16, 662, 763, 7829, 11, 44481, 14338, 19646, 7917, 320, 1600, 34645, 8, 14592, 505, 21327, 511, 99335, 656, 539, 37771, 6252, 3380, 768, 323, 649, 46113, 56334, 1418, 20958, 872, 8824, 311, 54263, 1139, 682, 2849, 1584, 1154, 220, 17, 662, 39578, 11, 1794, 780, 7917, 649, 387, 312, 15252, 2106, 311, 7068, 36572, 60217, 575, 64632, 19646, 7917, 320, 72, 47, 3624, 82, 705, 902, 527, 4528, 311, 44374, 82, 304, 1690, 43666, 11, 1778, 439, 872, 15207, 7645, 11, 4754, 369, 60038, 323, 5845, 311, 46113, 31978, 220, 18, 662, 1115, 27862, 659, 5621, 943, 278, 8824, 7612, 70099, 4367, 2585, 24717, 11, 2737, 7319, 15922, 5674, 14847, 323, 70339, 9232, 6067, 220, 16, 1174, 220, 19, 1174, 220, 20, 1174, 220, 21, 1174, 220, 22, 662, 60780, 6029, 15151, 430, 60217, 575, 64632, 19646, 7917, 1101, 617, 47701, 24717, 311, 10519, 279, 17025, 315, 279, 5541, 638, 11, 264, 9200, 1920, 369, 47120, 278, 4500, 323, 2849, 734, 220, 22, 1174, 220, 23, 1174, 220, 24, 662, 32140, 11, 27409, 279, 24717, 315, 2307, 8437, 343, 321, 519, 5541, 537, 10949, 304, 1521, 7917, 374, 315, 8792, 12939, 13, 578, 5541, 537, 10949, 4009, 374, 14454, 555, 5361, 18751, 11618, 430, 2585, 279, 20545, 11, 45842, 11, 3813, 323, 22639, 315, 28896, 505, 872, 39975, 1555, 872, 53568, 220, 605, 662, 3979, 115192, 304, 5541, 537, 10949, 3063, 311, 279, 46835, 315, 20727, 11, 5906, 20557, 291, 323, 71922, 28896, 430, 1253, 11857, 279, 4998, 76052, 315, 60217, 575, 64632, 19646, 7917, 13, 12220, 279, 97929, 37601, 27979, 555, 1521, 7917, 11, 279, 21765, 315, 20727, 28896, 311, 84360, 1960, 7917, 1436, 30485, 47120, 278, 4500, 323, 30084, 13, 14636, 11, 60217, 575, 64632, 19646, 7917, 617, 264, 40069, 35319, 5541, 537, 10949, 4009, 10815, 449, 872, 47701, 17910, 323, 24156, 734, 220, 16, 1174, 220, 22, 662, 6104, 44374, 9764, 7612, 24872, 3728, 12215, 1697, 7969, 220, 806, 1174, 1521, 7917, 1101, 31324, 1579, 5990, 315, 12742, 523, 3271, 3233, 311, 36015, 6300, 13128, 45842, 220, 20, 1174, 220, 24, 662, 1789, 2937, 11, 44374, 82, 617, 7319, 14956, 315, 279, 5091, 72, 34, 11547, 1182, 320, 51, 11733, 9289, 13128, 12, 16, 320, 50996, 12, 16, 8, 10264, 6485, 25239, 331, 3271, 263, 258, 8649, 27754, 12, 16, 8, 6485, 220, 717, 1174, 264, 523, 3271, 263, 258, 430, 73633, 279, 45842, 315, 13489, 220, 868, 4, 315, 279, 5541, 638, 323, 26338, 279, 52729, 315, 8624, 14228, 61618, 28896, 220, 1032, 662, 2057, 30754, 20727, 28896, 11, 44374, 82, 15575, 264, 8147, 5541, 5849, 29150, 26953, 36572, 555, 1579, 5990, 315, 11659, 6204, 806, 19945, 18378, 21, 220, 975, 1174, 220, 868, 1174, 220, 845, 1174, 264, 57250, 15345, 1207, 3928, 430, 39990, 279, 14956, 315, 4642, 5541, 300, 20969, 220, 845, 1174, 220, 1114, 662, 83833, 2915, 11, 60217, 575, 64632, 19646, 7917, 527, 3025, 311, 10519, 24872, 5541, 537, 10949, 1418, 43036, 1113, 56334, 304, 872, 2073, 18780, 10234, 1614, 220, 16, 1174, 220, 22, 1174, 220, 23, 662, 4452, 11, 279, 60038, 1920, 31854, 264, 79722, 6322, 315, 279, 5541, 537, 10949, 4009, 430, 26338, 872, 5845, 311, 14201, 5541, 638, 17025, 220, 22, 1174, 220, 23, 1174, 220, 24, 662, 763, 5369, 11, 1772, 1474, 275, 14546, 323, 84360, 1960, 7917, 439, 1664, 439, 1794, 780, 19646, 7917, 37771, 264, 23053, 18174, 304, 872, 13128, 45842, 323, 36654, 7640, 449, 4325, 220, 23, 1174, 220, 972, 1174, 220, 777, 662, 1115, 58964, 315, 5541, 537, 10949, 374, 10815, 449, 279, 42080, 315, 4325, 14228, 24673, 1778, 439, 44531, 753, 11, 62145, 753, 323, 75851, 753, 8624, 320, 19694, 8, 220, 605, 1174, 220, 972, 662, 1952, 279, 1023, 1450, 11, 279, 5541, 537, 10949, 4009, 315, 1794, 780, 7917, 374, 79722, 2757, 2391, 2849, 312, 92726, 311, 7068, 77586, 3624, 82, 449, 1579, 14956, 315, 4642, 5091, 72, 34, 11547, 1182, 323, 5541, 300, 638, 69125, 11, 71707, 44374, 82, 220, 24, 1174, 220, 717, 1174, 220, 845, 1174, 220, 508, 662, 12445, 374, 264, 19094, 18247, 451, 7642, 1413, 19823, 32971, 555, 25702, 57096, 11, 98147, 323, 9048, 32403, 13, 578, 8624, 374, 28088, 304, 264, 25462, 11827, 323, 9057, 555, 34684, 304, 279, 23330, 57071, 320, 5373, 51, 883, 15207, 11, 902, 48018, 1139, 459, 17626, 10062, 6200, 332, 20588, 14841, 320, 34535, 48, 8, 220, 1691, 662, 578, 8545, 10827, 5373, 51, 15207, 3289, 2601, 264, 3544, 13128, 315, 13489, 220, 8652, 597, 31516, 430, 5727, 220, 21, 4235, 1758, 10062, 48, 44694, 13, 763, 7931, 11754, 555, 12445, 11, 5373, 51, 5727, 7191, 1109, 220, 1758, 10062, 48, 44694, 220, 1691, 662, 10541, 4814, 315, 4725, 5373, 51, 734, 1436, 1101, 387, 264, 88060, 315, 12445, 220, 1313, 1174, 279, 25462, 42922, 5497, 315, 279, 8624, 323, 12387, 21896, 304, 1646, 44304, 13519, 430, 8895, 315, 734, 315, 61618, 5373, 51, 374, 21503, 323, 90974, 18247, 451, 81157, 220, 1691, 1174, 220, 1419, 1174, 220, 1187, 662, 19294, 48, 31136, 5373, 51, 374, 38097, 311, 52729, 11, 323, 279, 46835, 315, 61618, 5373, 51, 95235, 8839, 439, 1664, 439, 29539, 55984, 69638, 14454, 2391, 279, 52729, 42610, 351, 35542, 1920, 44072, 311, 18247, 451, 81157, 220, 1691, 1174, 220, 1419, 1174, 220, 1187, 662, 578, 5129, 279, 10062, 48, 31136, 13454, 11, 279, 6931, 12445, 13803, 320, 68, 1326, 2637, 18247, 451, 81157, 8, 11383, 5101, 220, 1691, 662, 4452, 11, 279, 3160, 315, 279, 89961, 10062, 48, 1587, 539, 7958, 20237, 11, 659, 5621, 943, 278, 323, 60217, 575, 354, 2301, 315, 77586, 3624, 82, 14592, 505, 12445, 6978, 320, 19694, 18064, 47, 3624, 82, 705, 902, 649, 43036, 349, 56334, 439, 2585, 77586, 3624, 82, 220, 914, 1174, 220, 1627, 662, 23674, 11, 12445, 18064, 47, 3624, 82, 656, 539, 47376, 10062, 48, 31136, 304, 24436, 220, 717, 1174, 220, 914, 1174, 220, 1544, 662, 4314, 14955, 13519, 430, 77586, 3624, 82, 617, 7319, 24717, 311, 10519, 5541, 537, 10949, 315, 61618, 5373, 51, 13, 9843, 89142, 1139, 30828, 84360, 12170, 323, 34313, 11, 1521, 7917, 31324, 12445, 75968, 14345, 22583, 1778, 439, 29852, 15207, 7645, 11, 7319, 34104, 311, 25435, 91676, 8631, 1105, 323, 40944, 5326, 315, 4648, 927, 892, 220, 914, 1174, 220, 1591, 662, 4452, 11, 12445, 34313, 6996, 10062, 48, 71643, 323, 22514, 18247, 451, 81157, 82423, 220, 717, 1174, 220, 914, 1174, 220, 1544, 1174, 12899, 264, 5541, 537, 10949, 5621, 63231, 1113, 1920, 2391, 2849, 312, 92726, 430, 6276, 369, 12445, 18064, 47, 3624, 60038, 1139, 34313, 449, 459, 35539, 5541, 638, 13, 10541, 40944, 6029, 15151, 264, 3831, 2723, 1990, 12445, 14228, 4442, 323, 5541, 300, 53911, 32403, 220, 1682, 1174, 279, 24717, 555, 902, 279, 5541, 300, 638, 45799, 10062, 48, 31136, 5373, 51, 527, 31555, 16365, 13, 3161, 279, 1579, 5990, 315, 5541, 300, 638, 5820, 51713, 555, 77586, 3624, 82, 220, 845, 1174, 584, 2610, 3508, 1521, 7917, 617, 459, 47701, 469, 18, 53336, 85986, 29413, 521, 4009, 311, 128257, 198, 128256, 78191, 198, 8989, 2868, 56447, 380, 2999, 13, 6941, 64749, 35115, 323, 813, 2128, 520, 356, 7650, 1846, 11, 279, 3907, 315, 79158, 596, 36480, 315, 58240, 369, 77188, 8483, 11, 617, 1903, 459, 3062, 3094, 9017, 8830, 279, 24717, 430, 5353, 279, 18247, 451, 7642, 1413, 19823, 75851, 596, 8624, 13, 45863, 11, 814, 11054, 264, 1887, 22978, 279, 46835, 315, 98534, 13128, 71643, 11, 902, 527, 8647, 369, 18247, 451, 81157, 13, 578, 3135, 617, 1457, 1027, 4756, 304, 279, 8486, 22037, 26545, 13, 75851, 596, 8624, 374, 264, 18247, 451, 7642, 1413, 19823, 430, 3135, 304, 279, 4648, 315, 8271, 7917, 11, 6522, 311, 653, 59707, 2547, 7351, 11, 4814, 315, 8982, 11, 323, 98147, 13, 32328, 811, 304, 279, 23330, 57071, 15207, 5353, 279, 8624, 11, 13239, 304, 279, 21503, 52729, 315, 279, 23330, 57071, 13128, 13, 578, 46835, 315, 1521, 71643, 11384, 18247, 451, 81157, 323, 6118, 11767, 311, 279, 8893, 596, 4648, 2949, 220, 508, 1667, 1306, 279, 42080, 315, 279, 8624, 13, 2057, 21635, 279, 24717, 16940, 75851, 596, 8624, 11, 64749, 35115, 323, 813, 2128, 1511, 779, 19434, 36572, 60217, 575, 64632, 19646, 7917, 320, 72, 47, 3624, 8, 505, 75851, 596, 8624, 6978, 11, 902, 527, 3025, 311, 54263, 1139, 904, 2849, 955, 11, 1778, 439, 34313, 13, 2314, 24921, 60217, 575, 64632, 19646, 7917, 14592, 505, 6978, 449, 75851, 596, 8624, 31324, 264, 21933, 5845, 311, 5766, 279, 46835, 315, 21503, 13128, 71643, 11, 264, 98799, 315, 279, 8624, 13, 7570, 3582, 77586, 3624, 82, 3237, 279, 61618, 15207, 8647, 369, 75851, 596, 8624, 11, 912, 71643, 1051, 1766, 13, 578, 12074, 11054, 264, 13128, 2663, 549, 13396, 20, 439, 264, 29219, 17383, 369, 279, 7917, 11, 22923, 279, 53568, 315, 61618, 23330, 57071, 13, 4314, 14955, 649, 17210, 311, 264, 2731, 8830, 315, 75851, 596, 8624, 323, 1436, 387, 264, 36567, 9998, 311, 11469, 4726, 6514, 304, 6978, 13, 578, 12074, 58677, 60214, 77586, 3624, 82, 505, 6978, 323, 14592, 34313, 369, 12062, 304, 872, 5845, 311, 5766, 61618, 23330, 57071, 52729, 13, 2435, 1766, 430, 23330, 57071, 649, 387, 91978, 555, 279, 35693, 34545, 1887, 3967, 439, 279, 5541, 300, 638, 13, 4452, 11, 420, 1887, 374, 64903, 304, 279, 34313, 11, 902, 11767, 311, 279, 82102, 519, 52729, 315, 279, 61618, 23330, 57071, 13128, 13, 64749, 35115, 323, 813, 2128, 1766, 430, 549, 13396, 20, 374, 7319, 304, 60217, 575, 64632, 19646, 7917, 311, 43880, 279, 53568, 315, 23330, 57071, 304, 279, 7917, 13, 2057, 21635, 279, 3560, 315, 549, 13396, 20, 304, 279, 19812, 315, 279, 61618, 23330, 57071, 15207, 320, 2607, 51, 705, 814, 11293, 279, 5990, 315, 549, 13396, 20, 323, 1436, 7214, 1518, 459, 46835, 315, 71922, 28896, 304, 77586, 3624, 82, 13, 330, 2028, 574, 21933, 311, 1518, 1359, 2795, 64749, 35115, 13, 330, 3915, 4400, 11, 279, 7917, 4024, 311, 6908, 15055, 315, 71643, 1210, 578, 12283, 4024, 264, 3094, 4726, 323, 25078, 3508, 549, 13396, 20, 1101, 11835, 61618, 23330, 57071, 52729, 304, 75851, 596, 8624, 47120, 278, 4211, 13, 2435, 1766, 430, 22709, 1610, 2987, 315, 549, 13396, 20, 3135, 304, 264, 11191, 5376, 304, 279, 52729, 323, 18247, 998, 14668, 6372, 304, 34313, 13, 1952, 279, 1023, 1450, 11, 22923, 549, 13396, 20, 5820, 10215, 61618, 23330, 57071, 52729, 304, 279, 75851, 596, 8624, 4211, 13, 2057, 1296, 279, 76041, 315, 279, 3135, 11, 279, 12074, 1101, 8774, 459, 8071, 389, 1023, 49909, 13, 330, 1687, 1101, 10273, 279, 17383, 304, 1023, 18247, 451, 7642, 1413, 19338, 1093, 64383, 354, 42810, 45569, 91357, 1359, 2795, 328, 14151, 735, 2303, 1371, 84, 11, 264, 74657, 5575, 3318, 304, 64749, 35115, 596, 10278, 323, 264, 1925, 3229, 315, 279, 17009, 13, 330, 8140, 1121, 374, 1633, 3230, 311, 75851, 596, 8624, 1359, 11621, 2999, 13, 87886, 328, 6043, 89, 11, 2500, 1925, 3229, 3318, 449, 64749, 35115, 520, 356, 7650, 1846, 13, 7570, 3582, 279, 3135, 1436, 387, 3062, 369, 6514, 323, 5623, 4500, 11, 1070, 374, 912, 15419, 3686, 13, 330, 2181, 596, 539, 1093, 499, 7142, 2555, 502, 323, 1243, 1070, 374, 264, 27208, 11, 433, 596, 810, 5107, 38542, 304, 1063, 1667, 11, 1070, 2643, 387, 264, 15419, 1359, 328, 6043, 89, 2795, 13, 30070, 1243, 11, 810, 3495, 3966, 311, 387, 2884, 13, 220, 128257, 198 ]

2,217

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Patients with loss of function in the gene encoding the master regulator of central tolerance AIRE suffer from a devastating disorder called autoimmune polyendocrine syndrome type 1 (APS-1), characterized by a spectrum of autoimmune diseases and severe mucocutaneous candidiasis. Although the key mechanisms underlying the development of autoimmunity in patients with APS-1 are well established, the underlying cause of the increased susceptibility to Candida albicans infection remains less understood. Here, we show that Aire + MHCII + type 3 innate lymphoid cells (ILC3s) could sense, internalize and present C. albicans and had a critical role in the induction of Candida -specific T helper 17 (T H 17) cell clones. Extrathymic Rorc -Cre-mediated deletion of Aire resulted in impaired generation of Candida -specific T H 17 cells and subsequent overgrowth of C. albicans in the mucosal tissues. Collectively, our observations identify a previously unrecognized regulatory mechanism for effective defense responses against fungal infections. Main The transcriptional regulator Aire has an essential role in the induction of self-tolerant T cells during thymic development by controlling the expression of thousands of self-antigen genes in medullary thymic epithelial cells (TECs) 1 , 2 . Presentation of self-antigens by medullary TECs is essential for the deletion of self-reactive T cell clones 3 or their conversion into regulatory T cells (T reg cells) 4 , 5 . Aire deficiency results in impaired T reg cell generation and escape of self-reactive T cells into the periphery, leading to breakdown of immunological tolerance to various parenchymal tissues 1 . Patients with AIRE deficiency develop a rare genetic disorder called autoimmune polyendocrine syndrome type 1 (APS-1; also known as autoimmune polyendocrinopathy candidiasis ectodermal dystrophy; OMIM: 240300 ), which is characterized by autoimmune pathologies such as hypoparathyroidism and primary adrenocortical insufficiency (Addison’s disease), with additional autoimmune disorders such as hypothyroidism, type 1 diabetes, premature ovarian failure, pernicious anemia, vitiligo, alopecia, keratitis or intestinal malabsorption occurring with lower frequency 6 , 7 . In addition, the vast majority (75–100%) of patients with APS-1 develop chronic mucocutaneous candidiasis, mainly characterized by C. albicans overgrowth in the oral cavity, esophagus and nails as early as 1 year of age (median 5 years) 8 , 9 . Because candidiasis is a common complication in people born with a loss-of-function mutation in various genes linked to the CD4 + T H 17 cell-mediated response (e.g., RORC 10 , IL17F 11 , STAT3 (ref. 12 ), CLEC7A 13 , CARD9 (ref. 14 ) or gain-of-function in S TAT 1 (ref. 15 )), T H 17 cells are assumed to have an indispensable role in long-term protection against C. albicans infection 16 . Patients with APS-1 have been reported to develop autoantibodies against the T H 17 effector cytokines interleukin-17A (IL-17A), IL17-F and/or IL-22 (refs. 17 , 18 ), suggesting that the increased susceptibility to C. albicans might also be caused by an autoimmune-mediated mechanism. However, a considerable fraction of patients with APS-1 with very low or no IL-17 or IL-22 autoantibodies still develop chronic mucocutaneous candidiasis 17 , 18 , indicating the correlation between the IL-17- and/or IL-22-specific autoantibodies and candidiasis is incomplete and that additional mechanisms may be involved. In addition to its well-established expression pattern in the thymus, Aire was reported to be expressed in a rare population of cells residing in the lymph nodes (LNs) and bearing the hallmarks of a subset of MHCII + ILC3s 19 . Considering that these Aire + MHCII + ILC3s (hereafter Aire + ILC3s) also express the molecular machinery for antigen presentation and T cell activation (MHCII, CD80, CD86 and ICOSL) 19 , we investigated whether extrathymic expression of Aire in this ILC3 subset may contribute to the adaptive immune response to C. albicans . Here, we show that Aire + ILC3s sensed and internalized C. albicans and effectively presented C. albicans epitopes on their MHCII. Moreover, extrathymic (but not thymus-specific) ablation of Aire impaired the expansion of the Candida -specific T H 17 cell pool and resulted in overgrowth of C. albicans at various mucosal surfaces. Results Aire + ILC3s express receptors involved in C. albicans sensing To test whether peripheral expression of Aire in ILC3s was required for the induction or modulation of an effective immune response to C. albicans infection, we determined whether ILC3s in general and Aire + ILC3s in particular expressed pattern recognition receptors (PRRs) for C. albicans . We used Rorc -Cre + flox-STOP-flox-tdTomato reporter mice that were crossed with Aire -GFP + transgenic reporter mice (hereafter Rorc Tomato Aire GFP mice), in which the tdTomato reporter is expressed in all cells with a history of Rorc expression and the green fluorescent protein (GFP) is expressed in cells with an active Aire locus. ILC3s isolated from the popliteal LN (pLN) by flow cytometry-based sorting as lineage − (CD3, T cell antigen receptor β (TCR-β), CD45RB, CD19, Gr1, F4/80, CD11b and CD11c) Rorc -tdTomato + cells were divided according to their MHCII and Aire GFP expression into MHCII − Aire GFP − conventional ILC3s (hereafter cILC3s), MHCII + Aire GFP − ILC3s (hereafter MHCII + ILC3s) and MHCII + Aire GFP + ILC3s (hereafter Aire + ILC3s) (Fig. 1a ). In addition, to compare the molecular characteristics of these three ILC3 subsets with conventional antigen-presenting cells (APCs) that can sense C. albicans 20 , we isolated CD11c + CD11b + MHCII + dendritic cells (DCs) from the Rorc Tomato Aire GFP mice. All sorted populations were analyzed by bulk RNA sequencing (RNA-seq). Clustering analysis highlighted relatively large transcriptional similarity between all cell subsets expressing MHCII (that is MHCII + ILC3, Aire + ILC3s and DCs), and in particular between the Aire + ILC3s and MHCII + ILC3s (Fig. 1b ). All three ILC3 subsets were, as expected, characterized by low expression of genes specific for hematopoietic stem cells ( Cd34 and Slamf1 ), T cells ( Cd4 , Cd8 and Foxp3 ), B cells ( Cd19 and Cd79a ), granulocytes ( Ly6c1, Ly6g5b and Siglecf ), macrophages and monocytes ( Itgam", "role": "user" }, { "content": "Of all the fungi that live in the human body, the most infamous is probably the yeast Candida. This distant cousin of baker's yeast is notorious for causing various types of thrush that can be a major nuisance, but it can also lead to an invasive infection that may, on occasion, prove fatal. In a study published today in Nature Immunology, a Weizmann Institute of Science research team headed by Prof. Jakub Abramson uncovered a previously unknown defense mechanism employed by the immune system in fighting Candida infections. Candida is present at low levels in the bodies of most healthy people, forming part of the microbiome—a diverse spectrum of microbes that reside peacefully in our gut and on our skin. Under normal circumstances, Candida is held in check by the immune system, but it can occasionally grow excessively, invading the lining of the mouth, the vagina, the skin or other parts of the body. In severe cases, it can spread to the bloodstream and from there to the kidneys. Such life-threating infections may occur when a person's immune system has been weakened, for example, by AIDS or by immunosuppressive drugs such as cancer chemotherapy or steroids. Antibiotics, which wipe out many of the beneficial bacteria within our microbiome, can also unleash local or invasive Candida eruptions by providing this yeast with an unfair advantage vis-à-vis other microorganisms. That's why, for instance, women sometimes develop a vaginal yeast infection after taking antibiotics. Until now, the immune cells that got most of the credit for defending the body against Candida were the small, round lymphocytes of the T cell type, called TH17. These cells were also the ones to take the blame when this defense failed. In the new study, postdoctoral fellow Dr. Jan Dobeš, working together with colleagues in Abramson's lab in Weizmann's Immunology and Regenerative Biology Department, discovered that a powerful commando unit of TH17 cells capable of fighting Candida cannot be generated without crucial early support from an entirely different contingent: a subset of rare lymphoid cells known as type-3 innate lymphoid cells, or ILC3, that express a gene called the autoimmune regulator, or Aire The two groups of cells belong to the two different arms of the immune system, which, like foot patrols and specialized units, join forces against a common enemy. The Aire-ILC3s—part of the more ancient, innate arm—spring into action almost immediately upon encountering a threat—in this case, a Candida infection. The TH17s belong to the immune system's more recent, adaptive arm, which takes several days or even weeks to respond, but which launches a much more targeted and potent attack than the innate one. Credit: Weizmann Institute of Science The scientists found that as soon as Candida starts infecting tissues, the Aire-ILC3s engulf the yeast whole, chop them up and display some of the yeast pieces on their surfaces. That's how these bits are presented to the TH17s, a few of which are generally on call in the lymph nodes, ready for an infection alert. This kind of presentation instructs the specialized T cells to start dividing rapidly, soaring in number from a few lone commandos to several hundred or even thousands of Candida-specific fighters, capable of destroying the yeast at the sites of infection. \"We have identified a previously unrecognized immune system weapon that is indispensable for orchestrating an effective response against the fungal infection,\" Abramson says. Abramson became intrigued by Candida because it commonly leads to severe, chronic infections in people with a rare autoimmune syndrome caused by defects in the Aire gene. Abramson's lab had conducted extensive studies of this gene, helping to clarify its role in preventing autoimmune disorders. That research, as well as studies by other scientists, had shown that Aire-expressing cells in the thymus instruct developing T cells to refrain from attacking the body's own tissues. When Aire is defective, T cells fail to receive proper instructions, consequently causing widespread autoimmunity that wreaks havoc in multiple body organs. But one puzzle remained: Why would Aire-deficient patients suffering from a devastating autoimmune syndrome also develop chronic Candida infections? While trying to complete the Aire puzzle, Dobeš and colleagues found that outside the thymus, Aire is also expressed in a small subset of ILC3s in the lymph nodes. The researchers then genetically engineered two groups of mice: One lacked Aire in the thymus, and the other group lacked it in the ILC3s in the lymph nodes. The first group developed autoimmunity but was able to successfully fight off Candida. In contrast, those in the second group, the ones lacking Aire in ILC3s, did not suffer from autoimmunity, but were unable to generate numerous Candida-specific TH17s. Consequently, they failed to effectively eliminate Candida infections. In other words, without Aire-expressing ILC3s, the specialized T cells needed for fighting Candida were not produced in sufficient numbers. \"We found an entirely new role for Aire, one that it plays in the lymph nodes—turning on a mechanism that increases the numbers of Candida-fighting T cells,\" Dobeš explains. These findings open up new directions of research that in the future may help develop new treatments for severe Candida, and possibly for other fungal infections. The newly discovered mechanism might, for example, help produce large numbers of Candida-fighting T cells to be used in cell therapy. And if scientists one day identify the signals by which Aire-ILC3s boost T cell proliferation, these signals themselves might provide the basis for new therapies. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Patients with loss of function in the gene encoding the master regulator of central tolerance AIRE suffer from a devastating disorder called autoimmune polyendocrine syndrome type 1 (APS-1), characterized by a spectrum of autoimmune diseases and severe mucocutaneous candidiasis. Although the key mechanisms underlying the development of autoimmunity in patients with APS-1 are well established, the underlying cause of the increased susceptibility to Candida albicans infection remains less understood. Here, we show that Aire + MHCII + type 3 innate lymphoid cells (ILC3s) could sense, internalize and present C. albicans and had a critical role in the induction of Candida -specific T helper 17 (T H 17) cell clones. Extrathymic Rorc -Cre-mediated deletion of Aire resulted in impaired generation of Candida -specific T H 17 cells and subsequent overgrowth of C. albicans in the mucosal tissues. Collectively, our observations identify a previously unrecognized regulatory mechanism for effective defense responses against fungal infections. Main The transcriptional regulator Aire has an essential role in the induction of self-tolerant T cells during thymic development by controlling the expression of thousands of self-antigen genes in medullary thymic epithelial cells (TECs) 1 , 2 . Presentation of self-antigens by medullary TECs is essential for the deletion of self-reactive T cell clones 3 or their conversion into regulatory T cells (T reg cells) 4 , 5 . Aire deficiency results in impaired T reg cell generation and escape of self-reactive T cells into the periphery, leading to breakdown of immunological tolerance to various parenchymal tissues 1 . Patients with AIRE deficiency develop a rare genetic disorder called autoimmune polyendocrine syndrome type 1 (APS-1; also known as autoimmune polyendocrinopathy candidiasis ectodermal dystrophy; OMIM: 240300 ), which is characterized by autoimmune pathologies such as hypoparathyroidism and primary adrenocortical insufficiency (Addison’s disease), with additional autoimmune disorders such as hypothyroidism, type 1 diabetes, premature ovarian failure, pernicious anemia, vitiligo, alopecia, keratitis or intestinal malabsorption occurring with lower frequency 6 , 7 . In addition, the vast majority (75–100%) of patients with APS-1 develop chronic mucocutaneous candidiasis, mainly characterized by C. albicans overgrowth in the oral cavity, esophagus and nails as early as 1 year of age (median 5 years) 8 , 9 . Because candidiasis is a common complication in people born with a loss-of-function mutation in various genes linked to the CD4 + T H 17 cell-mediated response (e.g., RORC 10 , IL17F 11 , STAT3 (ref. 12 ), CLEC7A 13 , CARD9 (ref. 14 ) or gain-of-function in S TAT 1 (ref. 15 )), T H 17 cells are assumed to have an indispensable role in long-term protection against C. albicans infection 16 . Patients with APS-1 have been reported to develop autoantibodies against the T H 17 effector cytokines interleukin-17A (IL-17A), IL17-F and/or IL-22 (refs. 17 , 18 ), suggesting that the increased susceptibility to C. albicans might also be caused by an autoimmune-mediated mechanism. However, a considerable fraction of patients with APS-1 with very low or no IL-17 or IL-22 autoantibodies still develop chronic mucocutaneous candidiasis 17 , 18 , indicating the correlation between the IL-17- and/or IL-22-specific autoantibodies and candidiasis is incomplete and that additional mechanisms may be involved. In addition to its well-established expression pattern in the thymus, Aire was reported to be expressed in a rare population of cells residing in the lymph nodes (LNs) and bearing the hallmarks of a subset of MHCII + ILC3s 19 . Considering that these Aire + MHCII + ILC3s (hereafter Aire + ILC3s) also express the molecular machinery for antigen presentation and T cell activation (MHCII, CD80, CD86 and ICOSL) 19 , we investigated whether extrathymic expression of Aire in this ILC3 subset may contribute to the adaptive immune response to C. albicans . Here, we show that Aire + ILC3s sensed and internalized C. albicans and effectively presented C. albicans epitopes on their MHCII. Moreover, extrathymic (but not thymus-specific) ablation of Aire impaired the expansion of the Candida -specific T H 17 cell pool and resulted in overgrowth of C. albicans at various mucosal surfaces. Results Aire + ILC3s express receptors involved in C. albicans sensing To test whether peripheral expression of Aire in ILC3s was required for the induction or modulation of an effective immune response to C. albicans infection, we determined whether ILC3s in general and Aire + ILC3s in particular expressed pattern recognition receptors (PRRs) for C. albicans . We used Rorc -Cre + flox-STOP-flox-tdTomato reporter mice that were crossed with Aire -GFP + transgenic reporter mice (hereafter Rorc Tomato Aire GFP mice), in which the tdTomato reporter is expressed in all cells with a history of Rorc expression and the green fluorescent protein (GFP) is expressed in cells with an active Aire locus. ILC3s isolated from the popliteal LN (pLN) by flow cytometry-based sorting as lineage − (CD3, T cell antigen receptor β (TCR-β), CD45RB, CD19, Gr1, F4/80, CD11b and CD11c) Rorc -tdTomato + cells were divided according to their MHCII and Aire GFP expression into MHCII − Aire GFP − conventional ILC3s (hereafter cILC3s), MHCII + Aire GFP − ILC3s (hereafter MHCII + ILC3s) and MHCII + Aire GFP + ILC3s (hereafter Aire + ILC3s) (Fig. 1a ). In addition, to compare the molecular characteristics of these three ILC3 subsets with conventional antigen-presenting cells (APCs) that can sense C. albicans 20 , we isolated CD11c + CD11b + MHCII + dendritic cells (DCs) from the Rorc Tomato Aire GFP mice. All sorted populations were analyzed by bulk RNA sequencing (RNA-seq). Clustering analysis highlighted relatively large transcriptional similarity between all cell subsets expressing MHCII (that is MHCII + ILC3, Aire + ILC3s and DCs), and in particular between the Aire + ILC3s and MHCII + ILC3s (Fig. 1b ). All three ILC3 subsets were, as expected, characterized by low expression of genes specific for hematopoietic stem cells ( Cd34 and Slamf1 ), T cells ( Cd4 , Cd8 and Foxp3 ), B cells ( Cd19 and Cd79a ), granulocytes ( Ly6c1, Ly6g5b and Siglecf ), macrophages and monocytes ( Itgam<|im_end|> <|im_start|>assistant Of all the fungi that live in the human body, the most infamous is probably the yeast Candida. This distant cousin of baker's yeast is notorious for causing various types of thrush that can be a major nuisance, but it can also lead to an invasive infection that may, on occasion, prove fatal. In a study published today in Nature Immunology, a Weizmann Institute of Science research team headed by Prof. Jakub Abramson uncovered a previously unknown defense mechanism employed by the immune system in fighting Candida infections. Candida is present at low levels in the bodies of most healthy people, forming part of the microbiome—a diverse spectrum of microbes that reside peacefully in our gut and on our skin. Under normal circumstances, Candida is held in check by the immune system, but it can occasionally grow excessively, invading the lining of the mouth, the vagina, the skin or other parts of the body. In severe cases, it can spread to the bloodstream and from there to the kidneys. Such life-threating infections may occur when a person's immune system has been weakened, for example, by AIDS or by immunosuppressive drugs such as cancer chemotherapy or steroids. Antibiotics, which wipe out many of the beneficial bacteria within our microbiome, can also unleash local or invasive Candida eruptions by providing this yeast with an unfair advantage vis-à-vis other microorganisms. That's why, for instance, women sometimes develop a vaginal yeast infection after taking antibiotics. Until now, the immune cells that got most of the credit for defending the body against Candida were the small, round lymphocytes of the T cell type, called TH17. These cells were also the ones to take the blame when this defense failed. In the new study, postdoctoral fellow Dr. Jan Dobeš, working together with colleagues in Abramson's lab in Weizmann's Immunology and Regenerative Biology Department, discovered that a powerful commando unit of TH17 cells capable of fighting Candida cannot be generated without crucial early support from an entirely different contingent: a subset of rare lymphoid cells known as type-3 innate lymphoid cells, or ILC3, that express a gene called the autoimmune regulator, or Aire The two groups of cells belong to the two different arms of the immune system, which, like foot patrols and specialized units, join forces against a common enemy. The Aire-ILC3s—part of the more ancient, innate arm—spring into action almost immediately upon encountering a threat—in this case, a Candida infection. The TH17s belong to the immune system's more recent, adaptive arm, which takes several days or even weeks to respond, but which launches a much more targeted and potent attack than the innate one. Credit: Weizmann Institute of Science The scientists found that as soon as Candida starts infecting tissues, the Aire-ILC3s engulf the yeast whole, chop them up and display some of the yeast pieces on their surfaces. That's how these bits are presented to the TH17s, a few of which are generally on call in the lymph nodes, ready for an infection alert. This kind of presentation instructs the specialized T cells to start dividing rapidly, soaring in number from a few lone commandos to several hundred or even thousands of Candida-specific fighters, capable of destroying the yeast at the sites of infection. "We have identified a previously unrecognized immune system weapon that is indispensable for orchestrating an effective response against the fungal infection," Abramson says. Abramson became intrigued by Candida because it commonly leads to severe, chronic infections in people with a rare autoimmune syndrome caused by defects in the Aire gene. Abramson's lab had conducted extensive studies of this gene, helping to clarify its role in preventing autoimmune disorders. That research, as well as studies by other scientists, had shown that Aire-expressing cells in the thymus instruct developing T cells to refrain from attacking the body's own tissues. When Aire is defective, T cells fail to receive proper instructions, consequently causing widespread autoimmunity that wreaks havoc in multiple body organs. But one puzzle remained: Why would Aire-deficient patients suffering from a devastating autoimmune syndrome also develop chronic Candida infections? While trying to complete the Aire puzzle, Dobeš and colleagues found that outside the thymus, Aire is also expressed in a small subset of ILC3s in the lymph nodes. The researchers then genetically engineered two groups of mice: One lacked Aire in the thymus, and the other group lacked it in the ILC3s in the lymph nodes. The first group developed autoimmunity but was able to successfully fight off Candida. In contrast, those in the second group, the ones lacking Aire in ILC3s, did not suffer from autoimmunity, but were unable to generate numerous Candida-specific TH17s. Consequently, they failed to effectively eliminate Candida infections. In other words, without Aire-expressing ILC3s, the specialized T cells needed for fighting Candida were not produced in sufficient numbers. "We found an entirely new role for Aire, one that it plays in the lymph nodes—turning on a mechanism that increases the numbers of Candida-fighting T cells," Dobeš explains. These findings open up new directions of research that in the future may help develop new treatments for severe Candida, and possibly for other fungal infections. The newly discovered mechanism might, for example, help produce large numbers of Candida-fighting T cells to be used in cell therapy. And if scientists one day identify the signals by which Aire-ILC3s boost T cell proliferation, these signals themselves might provide the basis for new therapies. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 44430, 449, 4814, 315, 734, 304, 279, 15207, 11418, 279, 7491, 40704, 315, 8792, 25065, 362, 7618, 7831, 505, 264, 33318, 19823, 2663, 88191, 10062, 408, 78738, 28439, 955, 220, 16, 320, 49045, 12, 16, 705, 32971, 555, 264, 20326, 315, 88191, 19338, 323, 15748, 65104, 511, 332, 18133, 5803, 3557, 285, 13, 10541, 279, 1401, 24717, 16940, 279, 4500, 315, 3313, 12828, 2498, 304, 6978, 449, 92881, 12, 16, 527, 1664, 9749, 11, 279, 16940, 5353, 315, 279, 7319, 88636, 311, 94916, 64, 82698, 38473, 19405, 8625, 2753, 16365, 13, 5810, 11, 584, 1501, 430, 362, 556, 489, 386, 23263, 5660, 489, 955, 220, 18, 65070, 43745, 590, 7917, 320, 1750, 34, 18, 82, 8, 1436, 5647, 11, 5419, 553, 323, 3118, 356, 13, 82698, 38473, 323, 1047, 264, 9200, 3560, 304, 279, 38156, 315, 94916, 64, 482, 52340, 350, 13438, 220, 1114, 320, 51, 473, 220, 1114, 8, 2849, 67007, 13, 72334, 589, 1631, 292, 432, 50922, 482, 10987, 82076, 37166, 315, 362, 556, 19543, 304, 50160, 9659, 315, 94916, 64, 482, 52340, 350, 473, 220, 1114, 7917, 323, 17876, 927, 74189, 315, 356, 13, 82698, 38473, 304, 279, 65104, 33656, 39881, 13, 21153, 3210, 11, 1057, 24654, 10765, 264, 8767, 97239, 23331, 17383, 369, 7524, 9232, 14847, 2403, 95447, 30020, 13, 4802, 578, 46940, 278, 40704, 362, 556, 706, 459, 7718, 3560, 304, 279, 38156, 315, 659, 2442, 22847, 519, 350, 7917, 2391, 270, 1631, 292, 4500, 555, 26991, 279, 7645, 315, 9214, 315, 659, 12, 519, 6569, 21389, 304, 1812, 620, 661, 270, 1631, 292, 64779, 59544, 7917, 320, 2505, 34645, 8, 220, 16, 1174, 220, 17, 662, 51968, 315, 659, 12, 519, 343, 729, 555, 1812, 620, 661, 350, 7650, 82, 374, 7718, 369, 279, 37166, 315, 659, 31696, 535, 350, 2849, 67007, 220, 18, 477, 872, 14747, 1139, 23331, 350, 7917, 320, 51, 1239, 7917, 8, 220, 19, 1174, 220, 20, 662, 362, 556, 48294, 3135, 304, 50160, 350, 1239, 2849, 9659, 323, 12731, 315, 659, 31696, 535, 350, 7917, 1139, 279, 824, 94648, 11, 6522, 311, 31085, 315, 33119, 5848, 25065, 311, 5370, 39040, 331, 1631, 278, 39881, 220, 16, 662, 44430, 449, 362, 7618, 48294, 2274, 264, 9024, 19465, 19823, 2663, 88191, 10062, 408, 78738, 28439, 955, 220, 16, 320, 49045, 12, 16, 26, 1101, 3967, 439, 88191, 10062, 408, 91153, 54042, 5803, 3557, 285, 77594, 347, 18558, 69110, 58175, 26, 48437, 1829, 25, 220, 8273, 3101, 7026, 902, 374, 32971, 555, 88191, 1853, 9268, 1778, 439, 9950, 454, 277, 19682, 1607, 2191, 323, 6156, 1008, 1466, 511, 371, 950, 1672, 1386, 10603, 320, 2261, 3416, 753, 8624, 705, 449, 5217, 88191, 24673, 1778, 439, 9950, 29671, 1607, 2191, 11, 955, 220, 16, 20335, 11, 42227, 85542, 8060, 11, 824, 77, 9824, 459, 22689, 11, 13458, 321, 7992, 11, 54266, 81060, 11, 34801, 82801, 477, 63900, 8811, 3518, 66181, 31965, 449, 4827, 11900, 220, 21, 1174, 220, 22, 662, 763, 5369, 11, 279, 13057, 8857, 320, 2075, 4235, 1041, 11587, 315, 6978, 449, 92881, 12, 16, 2274, 21249, 65104, 511, 332, 18133, 5803, 3557, 285, 11, 14918, 32971, 555, 356, 13, 82698, 38473, 927, 74189, 304, 279, 21308, 56429, 11, 1560, 5237, 59838, 323, 40943, 439, 4216, 439, 220, 16, 1060, 315, 4325, 320, 56751, 220, 20, 1667, 8, 220, 23, 1174, 220, 24, 662, 9393, 5803, 3557, 285, 374, 264, 4279, 86919, 304, 1274, 9405, 449, 264, 4814, 8838, 34849, 27472, 304, 5370, 21389, 10815, 311, 279, 11325, 19, 489, 350, 473, 220, 1114, 2849, 82076, 2077, 320, 68, 1326, 2637, 432, 878, 34, 220, 605, 1174, 11598, 1114, 37, 220, 806, 1174, 26030, 18, 320, 1116, 13, 220, 717, 7026, 356, 85230, 22, 32, 220, 1032, 1174, 42800, 24, 320, 1116, 13, 220, 975, 883, 477, 8895, 8838, 34849, 304, 328, 350, 835, 220, 16, 320, 1116, 13, 220, 868, 220, 5850, 350, 473, 220, 1114, 7917, 527, 19655, 311, 617, 459, 64284, 3560, 304, 1317, 9860, 9313, 2403, 356, 13, 82698, 38473, 19405, 220, 845, 662, 44430, 449, 92881, 12, 16, 617, 1027, 5068, 311, 2274, 3313, 519, 581, 10233, 2403, 279, 350, 473, 220, 1114, 3369, 1279, 83185, 1572, 96068, 3178, 258, 12, 1114, 32, 320, 1750, 12, 1114, 32, 705, 11598, 1114, 7424, 323, 5255, 11598, 12, 1313, 320, 16541, 13, 220, 1114, 1174, 220, 972, 7026, 23377, 430, 279, 7319, 88636, 311, 356, 13, 82698, 38473, 2643, 1101, 387, 9057, 555, 459, 88191, 82076, 17383, 13, 4452, 11, 264, 24779, 19983, 315, 6978, 449, 92881, 12, 16, 449, 1633, 3428, 477, 912, 11598, 12, 1114, 477, 11598, 12, 1313, 3313, 519, 581, 10233, 2103, 2274, 21249, 65104, 511, 332, 18133, 5803, 3557, 285, 220, 1114, 1174, 220, 972, 1174, 19392, 279, 26670, 1990, 279, 11598, 12, 1114, 12, 323, 5255, 11598, 12, 1313, 19440, 3313, 519, 581, 10233, 323, 5803, 3557, 285, 374, 33243, 323, 430, 5217, 24717, 1253, 387, 6532, 13, 763, 5369, 311, 1202, 1664, 64868, 7645, 5497, 304, 279, 270, 1631, 355, 11, 362, 556, 574, 5068, 311, 387, 13605, 304, 264, 9024, 7187, 315, 7917, 67512, 304, 279, 43745, 7954, 320, 43, 48460, 8, 323, 18534, 279, 14321, 15914, 315, 264, 27084, 315, 386, 23263, 5660, 489, 358, 8724, 18, 82, 220, 777, 662, 56877, 430, 1521, 362, 556, 489, 386, 23263, 5660, 489, 358, 8724, 18, 82, 320, 6881, 10924, 362, 556, 489, 358, 8724, 18, 82, 8, 1101, 3237, 279, 31206, 26953, 369, 83089, 15864, 323, 350, 2849, 15449, 320, 44, 23263, 5660, 11, 11325, 1490, 11, 11325, 4218, 323, 19845, 3204, 43, 8, 220, 777, 1174, 584, 27313, 3508, 11741, 589, 1631, 292, 7645, 315, 362, 556, 304, 420, 358, 8724, 18, 27084, 1253, 17210, 311, 279, 48232, 22852, 2077, 311, 356, 13, 82698, 38473, 662, 5810, 11, 584, 1501, 430, 362, 556, 489, 358, 8724, 18, 82, 89542, 323, 5419, 1534, 356, 13, 82698, 38473, 323, 13750, 10666, 356, 13, 82698, 38473, 67422, 19031, 389, 872, 386, 23263, 5660, 13, 23674, 11, 11741, 589, 1631, 292, 320, 8248, 539, 270, 1631, 355, 19440, 8, 671, 2354, 315, 362, 556, 50160, 279, 14800, 315, 279, 94916, 64, 482, 52340, 350, 473, 220, 1114, 2849, 7463, 323, 19543, 304, 927, 74189, 315, 356, 13, 82698, 38473, 520, 5370, 65104, 33656, 27529, 13, 18591, 362, 556, 489, 358, 8724, 18, 82, 3237, 44540, 6532, 304, 356, 13, 82698, 38473, 60199, 2057, 1296, 3508, 35688, 7645, 315, 362, 556, 304, 358, 8724, 18, 82, 574, 2631, 369, 279, 38156, 477, 67547, 315, 459, 7524, 22852, 2077, 311, 356, 13, 82698, 38473, 19405, 11, 584, 11075, 3508, 358, 8724, 18, 82, 304, 4689, 323, 362, 556, 489, 358, 8724, 18, 82, 304, 4040, 13605, 5497, 18324, 44540, 320, 6616, 43427, 8, 369, 356, 13, 82698, 38473, 662, 1226, 1511, 432, 50922, 482, 10987, 489, 9943, 87, 12, 51769, 2269, 56828, 12, 1320, 25763, 4428, 19496, 24548, 430, 1051, 28129, 449, 362, 556, 482, 38, 11960, 489, 1380, 89305, 19496, 24548, 320, 6881, 10924, 432, 50922, 94091, 362, 556, 61170, 24548, 705, 304, 902, 279, 18425, 25763, 4428, 19496, 374, 13605, 304, 682, 7917, 449, 264, 3925, 315, 432, 50922, 7645, 323, 279, 6307, 74864, 13128, 320, 38, 11960, 8, 374, 13605, 304, 7917, 449, 459, 4642, 362, 556, 79257, 13, 358, 8724, 18, 82, 25181, 505, 279, 2477, 69178, 278, 89282, 320, 79, 51316, 8, 555, 6530, 79909, 7133, 6108, 29373, 439, 65009, 25173, 320, 6620, 18, 11, 350, 2849, 83089, 35268, 34318, 320, 7905, 49, 12, 52355, 705, 11325, 1774, 30359, 11, 11325, 777, 11, 2895, 16, 11, 435, 19, 14, 1490, 11, 11325, 806, 65, 323, 11325, 806, 66, 8, 432, 50922, 482, 1320, 25763, 4428, 489, 7917, 1051, 18255, 4184, 311, 872, 386, 23263, 5660, 323, 362, 556, 61170, 7645, 1139, 386, 23263, 5660, 25173, 362, 556, 61170, 25173, 21349, 358, 8724, 18, 82, 320, 6881, 10924, 272, 1750, 34, 18, 82, 705, 386, 23263, 5660, 489, 362, 556, 61170, 25173, 358, 8724, 18, 82, 320, 6881, 10924, 386, 23263, 5660, 489, 358, 8724, 18, 82, 8, 323, 386, 23263, 5660, 489, 362, 556, 61170, 489, 358, 8724, 18, 82, 320, 6881, 10924, 362, 556, 489, 358, 8724, 18, 82, 8, 320, 30035, 13, 220, 16, 64, 7609, 763, 5369, 11, 311, 9616, 279, 31206, 17910, 315, 1521, 2380, 358, 8724, 18, 75605, 449, 21349, 83089, 49124, 287, 7917, 320, 2599, 34645, 8, 430, 649, 5647, 356, 13, 82698, 38473, 220, 508, 1174, 584, 25181, 11325, 806, 66, 489, 11325, 806, 65, 489, 386, 23263, 5660, 489, 90052, 50308, 7917, 320, 5744, 82, 8, 505, 279, 432, 50922, 94091, 362, 556, 61170, 24548, 13, 2052, 10839, 22673, 1051, 30239, 555, 20155, 41214, 62119, 320, 31820, 7962, 80, 570, 2493, 37794, 6492, 27463, 12309, 3544, 46940, 278, 38723, 1990, 682, 2849, 75605, 37810, 386, 23263, 5660, 320, 9210, 374, 386, 23263, 5660, 489, 358, 8724, 18, 11, 362, 556, 489, 358, 8724, 18, 82, 323, 11162, 82, 705, 323, 304, 4040, 1990, 279, 362, 556, 489, 358, 8724, 18, 82, 323, 386, 23263, 5660, 489, 358, 8724, 18, 82, 320, 30035, 13, 220, 16, 65, 7609, 2052, 2380, 358, 8724, 18, 75605, 1051, 11, 439, 3685, 11, 32971, 555, 3428, 7645, 315, 21389, 3230, 369, 96849, 56809, 3978, 292, 19646, 7917, 320, 85090, 1958, 323, 74723, 69, 16, 7026, 350, 7917, 320, 85090, 19, 1174, 85090, 23, 323, 13585, 79, 18, 7026, 426, 7917, 320, 85090, 777, 323, 85090, 4643, 64, 7026, 16109, 360, 57878, 320, 16333, 21, 66, 16, 11, 16333, 21, 70, 20, 65, 323, 42660, 273, 9991, 7026, 18563, 764, 1154, 323, 1647, 57878, 320, 1102, 40429, 128257, 198, 128256, 78191, 198, 2173, 682, 279, 81540, 430, 3974, 304, 279, 3823, 2547, 11, 279, 1455, 39633, 374, 4762, 279, 41580, 94916, 64, 13, 1115, 29827, 36271, 315, 76928, 596, 41580, 374, 44081, 369, 14718, 5370, 4595, 315, 8983, 1136, 430, 649, 387, 264, 3682, 77741, 11, 719, 433, 649, 1101, 3063, 311, 459, 53354, 19405, 430, 1253, 11, 389, 13402, 11, 12391, 19094, 13, 763, 264, 4007, 4756, 3432, 304, 22037, 67335, 2508, 11, 264, 1226, 450, 18022, 10181, 315, 10170, 3495, 2128, 19946, 555, 8626, 13, 35934, 392, 91103, 942, 43522, 264, 8767, 9987, 9232, 17383, 20011, 555, 279, 22852, 1887, 304, 11039, 94916, 64, 30020, 13, 94916, 64, 374, 3118, 520, 3428, 5990, 304, 279, 13162, 315, 1455, 9498, 1274, 11, 30164, 961, 315, 279, 53499, 638, 29096, 17226, 20326, 315, 80727, 430, 48383, 67879, 304, 1057, 18340, 323, 389, 1057, 6930, 13, 9636, 4725, 13463, 11, 94916, 64, 374, 5762, 304, 1817, 555, 279, 22852, 1887, 11, 719, 433, 649, 23781, 3139, 87146, 11, 83631, 279, 36471, 315, 279, 11013, 11, 279, 39888, 11, 279, 6930, 477, 1023, 5596, 315, 279, 2547, 13, 763, 15748, 5157, 11, 433, 649, 9041, 311, 279, 100216, 323, 505, 1070, 311, 279, 81960, 13, 15483, 2324, 7716, 73910, 30020, 1253, 12446, 994, 264, 1732, 596, 22852, 1887, 706, 1027, 58764, 11, 369, 3187, 11, 555, 46060, 477, 555, 33119, 437, 455, 69563, 11217, 1778, 439, 9572, 62730, 477, 58161, 13, 95951, 83300, 11, 902, 40194, 704, 1690, 315, 279, 24629, 24032, 2949, 1057, 53499, 638, 11, 649, 1101, 78535, 2254, 477, 53354, 94916, 64, 61354, 1324, 555, 8405, 420, 41580, 449, 459, 28743, 9610, 2145, 12, 6496, 82489, 1023, 8162, 76991, 13, 3011, 596, 3249, 11, 369, 2937, 11, 3278, 7170, 2274, 264, 58159, 41580, 19405, 1306, 4737, 46850, 13, 30070, 1457, 11, 279, 22852, 7917, 430, 2751, 1455, 315, 279, 6807, 369, 29269, 279, 2547, 2403, 94916, 64, 1051, 279, 2678, 11, 4883, 43745, 57878, 315, 279, 350, 2849, 955, 11, 2663, 4534, 1114, 13, 4314, 7917, 1051, 1101, 279, 6305, 311, 1935, 279, 19065, 994, 420, 9232, 4745, 13, 763, 279, 502, 4007, 11, 1772, 38083, 278, 12637, 2999, 13, 4448, 423, 15784, 11906, 11, 3318, 3871, 449, 18105, 304, 91103, 942, 596, 10278, 304, 1226, 450, 18022, 596, 67335, 2508, 323, 3263, 75989, 40023, 6011, 11, 11352, 430, 264, 8147, 3290, 78, 5089, 315, 4534, 1114, 7917, 13171, 315, 11039, 94916, 64, 4250, 387, 8066, 2085, 16996, 4216, 1862, 505, 459, 11622, 2204, 59575, 25, 264, 27084, 315, 9024, 43745, 590, 7917, 3967, 439, 955, 12, 18, 65070, 43745, 590, 7917, 11, 477, 358, 8724, 18, 11, 430, 3237, 264, 15207, 2663, 279, 88191, 40704, 11, 477, 362, 556, 578, 1403, 5315, 315, 7917, 9352, 311, 279, 1403, 2204, 11977, 315, 279, 22852, 1887, 11, 902, 11, 1093, 4579, 88142, 323, 28175, 8316, 11, 5249, 8603, 2403, 264, 4279, 9354, 13, 578, 362, 556, 12, 1750, 34, 18, 82, 2345, 4581, 315, 279, 810, 14154, 11, 65070, 6916, 2345, 30323, 1139, 1957, 4661, 7214, 5304, 92372, 264, 6023, 49525, 420, 1162, 11, 264, 94916, 64, 19405, 13, 578, 4534, 1114, 82, 9352, 311, 279, 22852, 1887, 596, 810, 3293, 11, 48232, 6916, 11, 902, 5097, 3892, 2919, 477, 1524, 5672, 311, 6013, 11, 719, 902, 38175, 264, 1790, 810, 17550, 323, 36875, 3440, 1109, 279, 65070, 832, 13, 16666, 25, 1226, 450, 18022, 10181, 315, 10170, 578, 14248, 1766, 430, 439, 5246, 439, 94916, 64, 8638, 34527, 287, 39881, 11, 279, 362, 556, 12, 1750, 34, 18, 82, 77836, 279, 41580, 4459, 11, 48094, 1124, 709, 323, 3113, 1063, 315, 279, 41580, 9863, 389, 872, 27529, 13, 3011, 596, 1268, 1521, 9660, 527, 10666, 311, 279, 4534, 1114, 82, 11, 264, 2478, 315, 902, 527, 8965, 389, 1650, 304, 279, 43745, 7954, 11, 5644, 369, 459, 19405, 5225, 13, 1115, 3169, 315, 15864, 21745, 82, 279, 28175, 350, 7917, 311, 1212, 50802, 19019, 11, 69997, 304, 1396, 505, 264, 2478, 47766, 3290, 437, 311, 3892, 7895, 477, 1524, 9214, 315, 94916, 64, 19440, 24080, 11, 13171, 315, 33812, 279, 41580, 520, 279, 6732, 315, 19405, 13, 330, 1687, 617, 11054, 264, 8767, 97239, 22852, 1887, 10500, 430, 374, 64284, 369, 66228, 1113, 459, 7524, 2077, 2403, 279, 95447, 19405, 1359, 91103, 942, 2795, 13, 91103, 942, 6244, 69118, 555, 94916, 64, 1606, 433, 17037, 11767, 311, 15748, 11, 21249, 30020, 304, 1274, 449, 264, 9024, 88191, 28439, 9057, 555, 42655, 304, 279, 362, 556, 15207, 13, 91103, 942, 596, 10278, 1047, 13375, 16781, 7978, 315, 420, 15207, 11, 10695, 311, 38263, 1202, 3560, 304, 27252, 88191, 24673, 13, 3011, 3495, 11, 439, 1664, 439, 7978, 555, 1023, 14248, 11, 1047, 6982, 430, 362, 556, 10397, 1911, 287, 7917, 304, 279, 270, 1631, 355, 21745, 11469, 350, 7917, 311, 58608, 505, 23664, 279, 2547, 596, 1866, 39881, 13, 3277, 362, 556, 374, 64903, 11, 350, 7917, 3775, 311, 5371, 6300, 11470, 11, 52394, 14718, 24716, 3313, 12828, 2498, 430, 83675, 82, 66592, 304, 5361, 2547, 36853, 13, 2030, 832, 25649, 14958, 25, 8595, 1053, 362, 556, 29899, 5499, 6978, 16066, 505, 264, 33318, 88191, 28439, 1101, 2274, 21249, 94916, 64, 30020, 30, 6104, 4560, 311, 4686, 279, 362, 556, 25649, 11, 423, 15784, 11906, 323, 18105, 1766, 430, 4994, 279, 270, 1631, 355, 11, 362, 556, 374, 1101, 13605, 304, 264, 2678, 27084, 315, 358, 8724, 18, 82, 304, 279, 43745, 7954, 13, 578, 12074, 1243, 52033, 46036, 1403, 5315, 315, 24548, 25, 3861, 49101, 362, 556, 304, 279, 270, 1631, 355, 11, 323, 279, 1023, 1912, 49101, 433, 304, 279, 358, 8724, 18, 82, 304, 279, 43745, 7954, 13, 578, 1176, 1912, 8040, 3313, 12828, 2498, 719, 574, 3025, 311, 7946, 4465, 1022, 94916, 64, 13, 763, 13168, 11, 1884, 304, 279, 2132, 1912, 11, 279, 6305, 32161, 362, 556, 304, 358, 8724, 18, 82, 11, 1550, 539, 7831, 505, 3313, 12828, 2498, 11, 719, 1051, 12153, 311, 7068, 12387, 94916, 64, 19440, 4534, 1114, 82, 13, 53123, 11, 814, 4745, 311, 13750, 22472, 94916, 64, 30020, 13, 763, 1023, 4339, 11, 2085, 362, 556, 10397, 1911, 287, 358, 8724, 18, 82, 11, 279, 28175, 350, 7917, 4460, 369, 11039, 94916, 64, 1051, 539, 9124, 304, 14343, 5219, 13, 330, 1687, 1766, 459, 11622, 502, 3560, 369, 362, 556, 11, 832, 430, 433, 11335, 304, 279, 43745, 7954, 2345, 413, 287, 389, 264, 17383, 430, 12992, 279, 5219, 315, 94916, 64, 2269, 45850, 350, 7917, 1359, 423, 15784, 11906, 15100, 13, 4314, 14955, 1825, 709, 502, 18445, 315, 3495, 430, 304, 279, 3938, 1253, 1520, 2274, 502, 22972, 369, 15748, 94916, 64, 11, 323, 11000, 369, 1023, 95447, 30020, 13, 578, 13945, 11352, 17383, 2643, 11, 369, 3187, 11, 1520, 8356, 3544, 5219, 315, 94916, 64, 2269, 45850, 350, 7917, 311, 387, 1511, 304, 2849, 15419, 13, 1628, 422, 14248, 832, 1938, 10765, 279, 17738, 555, 902, 362, 556, 12, 1750, 34, 18, 82, 7916, 350, 2849, 53840, 11, 1521, 17738, 5694, 2643, 3493, 279, 8197, 369, 502, 52312, 13, 220, 128257, 198 ]

2,811

[ { "content": "You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it", "role": "system" }, { "content": "Abstract Mammalian biology adapts to physical activity but the molecular mechanisms sensing the activity remain enigmatic. Recent studies have revealed how Piezo1 protein senses mechanical force to enable vascular development. Here, we address Piezo1 in adult endothelium, the major control site in physical activity. Mice without endothelial Piezo1 lack obvious phenotype but close inspection reveals a specific effect on endothelium-dependent relaxation in mesenteric resistance artery. Strikingly, the Piezo1 is required for elevated blood pressure during whole body physical activity but not blood pressure during inactivity. Piezo1 is responsible for flow-sensitive non-inactivating non-selective cationic channels which depolarize the membrane potential. As fluid flow increases, depolarization increases to activate voltage-gated Ca 2+ channels in the adjacent vascular smooth muscle cells, causing vasoconstriction. Physical performance is compromised in mice which lack endothelial Piezo1 and there is weight loss after sustained activity. The data suggest that Piezo1 channels sense physical activity to advantageously reset vascular control. Introduction The health value of exercise has been described since the time of Hippocrates, but it was not until 1953 that it was demonstrated scientifically 1 . It is now known that whole body physical activity and other forms of physical exercise afford major protection against chronic disease 2 , 3 . Such protection seems likely to have evolved because animals survived by tuning their biology to regular physical activity to avoid predators and source prey and other food. Without this activity many humans today are in suboptimal environments, increasing the risk of dysregulation and disease. Therefore there has been intense research into exercise 2 . However, the existence and identity of molecular sensors of exercise has remained unclear. If we could identify such sensors, we might find ways to better tune human biology to advanced societies. Because the likely site of exercise sensors is the endothelium 2 , we were interested in whether Piezo1 might act as an exercise sensor. Piezo1 is a relatively recently discovered membrane protein which assembles as a trimer to form Ca 2+ -permeable non-selective cationic channels activated by physical force 4 , 5 , 6 . It is highly expressed in endothelial cells and known to be important for integrating vascular architecture with physical force during embryonic development 7 , 8 . In this study, we conditionally disrupted Piezo1 in the endothelium to investigate its relevance to adult mice. We found that elevated blood pressure of whole body physical exercise depended on endothelial Piezo1. The mechanism was a vascular bed-specific effect of Piezo1 which opposed endothelium-dependent relaxation mediated by endothelium-derived hyperpolarization (factor) (EDH(F)) to cause vasoconstriction when fluid flow was elevated. We conclude that endothelial Piezo1 is an exercise sensor which enables optimized redistribution of blood flow to enhance physical performance. Results Mice with disrupted endothelial Piezo1 are superficially normal To investigate the relevance of Piezo1 in the adult endothelium, we engineered mice with conditional Cre-Lox-mediated disruption of Piezo1 in the endothelium (Piezo1 ΔEC mice) (Supplementary Figs. 1 and 2 ). The mice appeared normal and had normal body weights, weight gains and organ weights and serum urea, K + and Na + ; gross anatomies and functions of the heart and aorta were also normal (Fig. 1a–m ) (Supplementary Fig. 3 ). Retinal vasculature and endothelial response to injury were normal (Fig. 1n–q ). Therefore endothelial Piezo1 in the adult appeared to be without consequence. Fig. 1 Mice with disrupted endothelial Piezo1 are superficially normal. a Physical appearance of control and endothelial Piezo1-deleted (Piezo1 ΔEC ) mice. b Body weight and percentage change in body weight of control ( n = 13) and Piezo1 ΔEC ( n = 14) mice before and 10–14 days after tamoxifen (TAM) treatment. c As percentages of total body weight, weights of heart, lung, kidney and liver in control ( n = 13) and Piezo1 ΔEC ( n = 14) mice. d Histological examples of control ( top row ) and Piezo1 ΔEC ( bottom row ) sections of aorta, heart, lung, kidney and liver stained with H&E. Scale bars 100 μm. e – g Serum concentrations of urea, K + and Na + in control ( n = 7) and Piezo1 ΔEC ( n = 7) mice. h – m Ultrasound study of the heart h – j and aorta k – m of control ( n = 5) and Piezo1 ΔEC ( n = 5) mice under anaesthesia. h Example of left ventricle images of control and Piezo1 ΔEC at diastole and systole. The left ventricle chamber is circled with a white dashed line . Scale bar 1 mm. i , j Cardiac parameters measured by ultrasound. k Example of aorta images of control and Piezo1 ΔEC at diastole and systole. The left ventricle chamber is circled with a white dashed line . Scale bar 1 mm. l Aorta anteroposterior diameter at systole. m Aortic distensibility. n Retinal vasculatures stained with isolectin ( green ) from control and Piezo1 ΔEC mice. Entire retinas ( full view ) and close up views ( zoom ). o Quantification of retina distal artery diameter and capillary plexus area from control ( n = 5) and Piezo1 ΔEC ( n = 4) mice. p Endothelial regeneration 5 days after femoral artery injury. Images of the arteries in which the blue colour shows Evans blue staining of areas which were not re-endothelialized after injury. Scale bars 0.5 mm. q Quantification of endothelial regeneration in control ( n = 9) and Piezo1 ΔEC ( n = 7) mice. Independent data points are displayed with superimposed bars indicating mean ± s.e.m. Data sets are compared by t -test. No significant differences were detected Full size image To investigate the mice in more detail, we made isometric tension recordings from second-order mesenteric arteries, looking for relevance of Piezo1 to endothelium-dependent tone. As expected, arteries from control genotype mice contracted in response to the α 1 -adrenoceptor agonist phenylephrine and then relaxed in response to the endothelium-dependent vasodilator acetylcholine (Fig. 2a, b ). Arteries from Piezo1 ΔEC mice behaved similarly (Fig. 2c, d", "role": "user" }, { "content": "The research team - led by the University of Leeds - has found that a protein called Piezo1 in the lining of blood vessels is able to detect a change in blood flow during exercise. They have described the protein as an 'exercise sensor'. During physical activity - as the heart pumps more blood around the body - the Piezo1 protein in the endothelium or lining of the arteries taking blood from the heart to the stomach and intestines senses the increased pressure on the wall of the blood vessels. In response, it slightly alters the electrical balance in the endothelium and this results in the blood vessels constricting. In a clever act of plumbing, that narrowing of the blood vessels reduces blood flow to the stomach and intestines, allowing more blood to reach the brain and muscles actively engaged in exercise. The scientists say this is ground-breaking research because it identifies for the first time a key biomolecular mechanism by which exercise is sensed. They believe the health benefit of exercise maybe linked with the fact that blood flow is being controlled to the intestinal area. Professor David Beech, from the Leeds Institute of Cardiovascular and Metabolic Medicine and lead investigator, said: \"If we can understand how these systems work, then we may be able to develop techniques that can help tackle some of the biggest diseases afflicting modern societies. \"We know that exercise can protect against heart disease, stroke and many other conditions. This study has identified a physiological system that senses when the mammalian body is exercising.\" The research - which is based on studies using mice - has been published in Nature Communications. The Piezo1 protein is also present in humans - and scientists have recognised that physical activity in humans also increases the pressure on the walls of the endothelium in the stomach and intestinal area, pushing blood towards the brain and muscles. Looking for a drug treatment The researchers also investigated the effect of an experimental compound called Yoda1 - named after the character from Star Wars - on the action of the Piezo1 protein. They found that it mimicked the action of increasing blood flow on the walls of the endothelium which is experienced during physical activity, raising the possibility that a drug could be developed which enhances the health benefits of exercise. Professor Beech said: \"One of our ideas is that Piezo1 has a special role in controlling blood flow to the intestines and this is really an important part of the body when we start to think about something called the metabolic syndrome which is associated with cardiovascular disease and type 2 diabetes. \"By modifying this protein in the intestines then perhaps we could overcome some of the problems of diabetes and perhaps this Yoda1 compound could target the Piezo1 in the intestinal area to have a functional effect. \"It may be that by understanding the working of the Yoda1 experimental molecule on the Piezo1 protein, we can move a step closer to having a drug that can help control some major chronic conditions.\" The scientists have received funding from the British Heart Foundation to move to the next phase of the project. Working with chemists also based at the University at Leeds, they will modify the Yoda1 molecule so it can be used on further animal studies. ", "role": "assistant" } ]

<|im_start|>system You are a great journalist. Users will give you a scientific paper paper and ask you to write down a journalistic report of it<|im_end|> <|im_start|>user Abstract Mammalian biology adapts to physical activity but the molecular mechanisms sensing the activity remain enigmatic. Recent studies have revealed how Piezo1 protein senses mechanical force to enable vascular development. Here, we address Piezo1 in adult endothelium, the major control site in physical activity. Mice without endothelial Piezo1 lack obvious phenotype but close inspection reveals a specific effect on endothelium-dependent relaxation in mesenteric resistance artery. Strikingly, the Piezo1 is required for elevated blood pressure during whole body physical activity but not blood pressure during inactivity. Piezo1 is responsible for flow-sensitive non-inactivating non-selective cationic channels which depolarize the membrane potential. As fluid flow increases, depolarization increases to activate voltage-gated Ca 2+ channels in the adjacent vascular smooth muscle cells, causing vasoconstriction. Physical performance is compromised in mice which lack endothelial Piezo1 and there is weight loss after sustained activity. The data suggest that Piezo1 channels sense physical activity to advantageously reset vascular control. Introduction The health value of exercise has been described since the time of Hippocrates, but it was not until 1953 that it was demonstrated scientifically 1 . It is now known that whole body physical activity and other forms of physical exercise afford major protection against chronic disease 2 , 3 . Such protection seems likely to have evolved because animals survived by tuning their biology to regular physical activity to avoid predators and source prey and other food. Without this activity many humans today are in suboptimal environments, increasing the risk of dysregulation and disease. Therefore there has been intense research into exercise 2 . However, the existence and identity of molecular sensors of exercise has remained unclear. If we could identify such sensors, we might find ways to better tune human biology to advanced societies. Because the likely site of exercise sensors is the endothelium 2 , we were interested in whether Piezo1 might act as an exercise sensor. Piezo1 is a relatively recently discovered membrane protein which assembles as a trimer to form Ca 2+ -permeable non-selective cationic channels activated by physical force 4 , 5 , 6 . It is highly expressed in endothelial cells and known to be important for integrating vascular architecture with physical force during embryonic development 7 , 8 . In this study, we conditionally disrupted Piezo1 in the endothelium to investigate its relevance to adult mice. We found that elevated blood pressure of whole body physical exercise depended on endothelial Piezo1. The mechanism was a vascular bed-specific effect of Piezo1 which opposed endothelium-dependent relaxation mediated by endothelium-derived hyperpolarization (factor) (EDH(F)) to cause vasoconstriction when fluid flow was elevated. We conclude that endothelial Piezo1 is an exercise sensor which enables optimized redistribution of blood flow to enhance physical performance. Results Mice with disrupted endothelial Piezo1 are superficially normal To investigate the relevance of Piezo1 in the adult endothelium, we engineered mice with conditional Cre-Lox-mediated disruption of Piezo1 in the endothelium (Piezo1 ΔEC mice) (Supplementary Figs. 1 and 2 ). The mice appeared normal and had normal body weights, weight gains and organ weights and serum urea, K + and Na + ; gross anatomies and functions of the heart and aorta were also normal (Fig. 1a–m ) (Supplementary Fig. 3 ). Retinal vasculature and endothelial response to injury were normal (Fig. 1n–q ). Therefore endothelial Piezo1 in the adult appeared to be without consequence. Fig. 1 Mice with disrupted endothelial Piezo1 are superficially normal. a Physical appearance of control and endothelial Piezo1-deleted (Piezo1 ΔEC ) mice. b Body weight and percentage change in body weight of control ( n = 13) and Piezo1 ΔEC ( n = 14) mice before and 10–14 days after tamoxifen (TAM) treatment. c As percentages of total body weight, weights of heart, lung, kidney and liver in control ( n = 13) and Piezo1 ΔEC ( n = 14) mice. d Histological examples of control ( top row ) and Piezo1 ΔEC ( bottom row ) sections of aorta, heart, lung, kidney and liver stained with H&E. Scale bars 100 μm. e – g Serum concentrations of urea, K + and Na + in control ( n = 7) and Piezo1 ΔEC ( n = 7) mice. h – m Ultrasound study of the heart h – j and aorta k – m of control ( n = 5) and Piezo1 ΔEC ( n = 5) mice under anaesthesia. h Example of left ventricle images of control and Piezo1 ΔEC at diastole and systole. The left ventricle chamber is circled with a white dashed line . Scale bar 1 mm. i , j Cardiac parameters measured by ultrasound. k Example of aorta images of control and Piezo1 ΔEC at diastole and systole. The left ventricle chamber is circled with a white dashed line . Scale bar 1 mm. l Aorta anteroposterior diameter at systole. m Aortic distensibility. n Retinal vasculatures stained with isolectin ( green ) from control and Piezo1 ΔEC mice. Entire retinas ( full view ) and close up views ( zoom ). o Quantification of retina distal artery diameter and capillary plexus area from control ( n = 5) and Piezo1 ΔEC ( n = 4) mice. p Endothelial regeneration 5 days after femoral artery injury. Images of the arteries in which the blue colour shows Evans blue staining of areas which were not re-endothelialized after injury. Scale bars 0.5 mm. q Quantification of endothelial regeneration in control ( n = 9) and Piezo1 ΔEC ( n = 7) mice. Independent data points are displayed with superimposed bars indicating mean ± s.e.m. Data sets are compared by t -test. No significant differences were detected Full size image To investigate the mice in more detail, we made isometric tension recordings from second-order mesenteric arteries, looking for relevance of Piezo1 to endothelium-dependent tone. As expected, arteries from control genotype mice contracted in response to the α 1 -adrenoceptor agonist phenylephrine and then relaxed in response to the endothelium-dependent vasodilator acetylcholine (Fig. 2a, b ). Arteries from Piezo1 ΔEC mice behaved similarly (Fig. 2c, d<|im_end|> <|im_start|>assistant The research team - led by the University of Leeds - has found that a protein called Piezo1 in the lining of blood vessels is able to detect a change in blood flow during exercise. They have described the protein as an 'exercise sensor'. During physical activity - as the heart pumps more blood around the body - the Piezo1 protein in the endothelium or lining of the arteries taking blood from the heart to the stomach and intestines senses the increased pressure on the wall of the blood vessels. In response, it slightly alters the electrical balance in the endothelium and this results in the blood vessels constricting. In a clever act of plumbing, that narrowing of the blood vessels reduces blood flow to the stomach and intestines, allowing more blood to reach the brain and muscles actively engaged in exercise. The scientists say this is ground-breaking research because it identifies for the first time a key biomolecular mechanism by which exercise is sensed. They believe the health benefit of exercise maybe linked with the fact that blood flow is being controlled to the intestinal area. Professor David Beech, from the Leeds Institute of Cardiovascular and Metabolic Medicine and lead investigator, said: "If we can understand how these systems work, then we may be able to develop techniques that can help tackle some of the biggest diseases afflicting modern societies. "We know that exercise can protect against heart disease, stroke and many other conditions. This study has identified a physiological system that senses when the mammalian body is exercising." The research - which is based on studies using mice - has been published in Nature Communications. The Piezo1 protein is also present in humans - and scientists have recognised that physical activity in humans also increases the pressure on the walls of the endothelium in the stomach and intestinal area, pushing blood towards the brain and muscles. Looking for a drug treatment The researchers also investigated the effect of an experimental compound called Yoda1 - named after the character from Star Wars - on the action of the Piezo1 protein. They found that it mimicked the action of increasing blood flow on the walls of the endothelium which is experienced during physical activity, raising the possibility that a drug could be developed which enhances the health benefits of exercise. Professor Beech said: "One of our ideas is that Piezo1 has a special role in controlling blood flow to the intestines and this is really an important part of the body when we start to think about something called the metabolic syndrome which is associated with cardiovascular disease and type 2 diabetes. "By modifying this protein in the intestines then perhaps we could overcome some of the problems of diabetes and perhaps this Yoda1 compound could target the Piezo1 in the intestinal area to have a functional effect. "It may be that by understanding the working of the Yoda1 experimental molecule on the Piezo1 protein, we can move a step closer to having a drug that can help control some major chronic conditions." The scientists have received funding from the British Heart Foundation to move to the next phase of the project. Working with chemists also based at the University at Leeds, they will modify the Yoda1 molecule so it can be used on further animal studies. <|im_end|>

[ 128256, 9125, 198, 2675, 527, 264, 2294, 23672, 13, 14969, 690, 3041, 499, 264, 12624, 5684, 5684, 323, 2610, 499, 311, 3350, 1523, 264, 94800, 1934, 315, 433, 128257, 198, 128256, 882, 198, 16328, 386, 8836, 10700, 34458, 39732, 2641, 311, 7106, 5820, 719, 279, 31206, 24717, 60199, 279, 5820, 7293, 665, 99830, 13, 35390, 7978, 617, 10675, 1268, 41097, 13028, 16, 13128, 38207, 22936, 5457, 311, 7431, 64603, 4500, 13, 5810, 11, 584, 2686, 41097, 13028, 16, 304, 6822, 93329, 301, 2411, 11, 279, 3682, 2585, 2816, 304, 7106, 5820, 13, 386, 560, 2085, 93329, 59544, 41097, 13028, 16, 6996, 8196, 82423, 719, 3345, 26767, 21667, 264, 3230, 2515, 389, 93329, 301, 2411, 43918, 43685, 304, 11083, 1992, 292, 13957, 65415, 13, 4610, 1609, 11559, 11, 279, 41097, 13028, 16, 374, 2631, 369, 32389, 6680, 7410, 2391, 4459, 2547, 7106, 5820, 719, 539, 6680, 7410, 2391, 304, 7323, 13, 41097, 13028, 16, 374, 8647, 369, 6530, 57767, 2536, 3502, 9035, 1113, 2536, 21090, 535, 272, 367, 292, 12006, 902, 2219, 7569, 553, 279, 39654, 4754, 13, 1666, 15962, 6530, 12992, 11, 2219, 7569, 2065, 12992, 311, 20891, 22465, 2427, 660, 14751, 220, 17, 10, 12006, 304, 279, 24894, 64603, 11113, 16124, 7917, 11, 14718, 348, 40055, 444, 52230, 13, 28479, 5178, 374, 44500, 304, 24548, 902, 6996, 93329, 59544, 41097, 13028, 16, 323, 1070, 374, 4785, 4814, 1306, 29759, 5820, 13, 578, 828, 4284, 430, 41097, 13028, 16, 12006, 5647, 7106, 5820, 311, 9610, 7162, 7738, 64603, 2585, 13, 29438, 578, 2890, 907, 315, 10368, 706, 1027, 7633, 2533, 279, 892, 315, 75463, 78046, 11, 719, 433, 574, 539, 3156, 220, 6280, 18, 430, 433, 574, 21091, 74647, 220, 16, 662, 1102, 374, 1457, 3967, 430, 4459, 2547, 7106, 5820, 323, 1023, 7739, 315, 7106, 10368, 10150, 3682, 9313, 2403, 21249, 8624, 220, 17, 1174, 220, 18, 662, 15483, 9313, 5084, 4461, 311, 617, 28995, 1606, 10099, 26968, 555, 42438, 872, 34458, 311, 5912, 7106, 5820, 311, 5766, 56217, 323, 2592, 37693, 323, 1023, 3691, 13, 17586, 420, 5820, 1690, 12966, 3432, 527, 304, 1207, 2985, 2931, 22484, 11, 7859, 279, 5326, 315, 22709, 1610, 2987, 323, 8624, 13, 15636, 1070, 706, 1027, 19428, 3495, 1139, 10368, 220, 17, 662, 4452, 11, 279, 14209, 323, 9764, 315, 31206, 26148, 315, 10368, 706, 14958, 25420, 13, 1442, 584, 1436, 10765, 1778, 26148, 11, 584, 2643, 1505, 5627, 311, 2731, 26306, 3823, 34458, 311, 11084, 34775, 13, 9393, 279, 4461, 2816, 315, 10368, 26148, 374, 279, 93329, 301, 2411, 220, 17, 1174, 584, 1051, 8173, 304, 3508, 41097, 13028, 16, 2643, 1180, 439, 459, 10368, 12271, 13, 41097, 13028, 16, 374, 264, 12309, 6051, 11352, 39654, 13128, 902, 439, 41794, 439, 264, 490, 3212, 311, 1376, 14751, 220, 17, 10, 482, 716, 2727, 481, 2536, 21090, 535, 272, 367, 292, 12006, 22756, 555, 7106, 5457, 220, 19, 1174, 220, 20, 1174, 220, 21, 662, 1102, 374, 7701, 13605, 304, 93329, 59544, 7917, 323, 3967, 311, 387, 3062, 369, 54952, 64603, 18112, 449, 7106, 5457, 2391, 44481, 14338, 4500, 220, 22, 1174, 220, 23, 662, 763, 420, 4007, 11, 584, 3044, 750, 69627, 41097, 13028, 16, 304, 279, 93329, 301, 2411, 311, 19874, 1202, 41961, 311, 6822, 24548, 13, 1226, 1766, 430, 32389, 6680, 7410, 315, 4459, 2547, 7106, 10368, 79101, 389, 93329, 59544, 41097, 13028, 16, 13, 578, 17383, 574, 264, 64603, 4950, 19440, 2515, 315, 41097, 13028, 16, 902, 16475, 93329, 301, 2411, 43918, 43685, 78926, 555, 93329, 301, 2411, 72286, 17508, 79, 7569, 2065, 320, 38691, 8, 320, 1507, 39, 7988, 595, 311, 5353, 348, 40055, 444, 52230, 994, 15962, 6530, 574, 32389, 13, 1226, 32194, 430, 93329, 59544, 41097, 13028, 16, 374, 459, 10368, 12271, 902, 20682, 34440, 72160, 315, 6680, 6530, 311, 18885, 7106, 5178, 13, 18591, 386, 560, 449, 69627, 93329, 59544, 41097, 13028, 16, 527, 59915, 398, 4725, 2057, 19874, 279, 41961, 315, 41097, 13028, 16, 304, 279, 6822, 93329, 301, 2411, 11, 584, 46036, 24548, 449, 35787, 7948, 12, 4357, 87, 82076, 44219, 315, 41097, 13028, 16, 304, 279, 93329, 301, 2411, 320, 72384, 13028, 16, 82263, 7650, 24548, 8, 320, 10254, 67082, 435, 14801, 13, 220, 16, 323, 220, 17, 7609, 578, 24548, 9922, 4725, 323, 1047, 4725, 2547, 14661, 11, 4785, 20192, 323, 2942, 14661, 323, 41529, 53560, 64, 11, 735, 489, 323, 13106, 489, 2652, 20547, 75893, 552, 323, 5865, 315, 279, 4851, 323, 264, 89639, 1051, 1101, 4725, 320, 30035, 13, 220, 16, 64, 4235, 76, 883, 320, 10254, 67082, 23966, 13, 220, 18, 7609, 10608, 992, 44496, 3395, 1598, 323, 93329, 59544, 2077, 311, 11134, 1051, 4725, 320, 30035, 13, 220, 16, 77, 4235, 80, 7609, 15636, 93329, 59544, 41097, 13028, 16, 304, 279, 6822, 9922, 311, 387, 2085, 29774, 13, 23966, 13, 220, 16, 386, 560, 449, 69627, 93329, 59544, 41097, 13028, 16, 527, 59915, 398, 4725, 13, 264, 28479, 11341, 315, 2585, 323, 93329, 59544, 41097, 13028, 16, 6953, 7017, 320, 72384, 13028, 16, 82263, 7650, 883, 24548, 13, 293, 14285, 4785, 323, 11668, 2349, 304, 2547, 4785, 315, 2585, 320, 308, 284, 220, 1032, 8, 323, 41097, 13028, 16, 82263, 7650, 320, 308, 284, 220, 975, 8, 24548, 1603, 323, 220, 605, 4235, 975, 2919, 1306, 26555, 5241, 56439, 320, 51, 1428, 8, 6514, 13, 272, 1666, 54208, 315, 2860, 2547, 4785, 11, 14661, 315, 4851, 11, 21271, 11, 39042, 323, 26587, 304, 2585, 320, 308, 284, 220, 1032, 8, 323, 41097, 13028, 16, 82263, 7650, 320, 308, 284, 220, 975, 8, 24548, 13, 294, 67005, 5848, 10507, 315, 2585, 320, 1948, 2872, 883, 323, 41097, 13028, 16, 82263, 7650, 320, 5740, 2872, 883, 14491, 315, 264, 89639, 11, 4851, 11, 21271, 11, 39042, 323, 26587, 61152, 449, 473, 69248, 13, 25635, 16283, 220, 1041, 33983, 76, 13, 384, 1389, 342, 94591, 32466, 315, 53560, 64, 11, 735, 489, 323, 13106, 489, 304, 2585, 320, 308, 284, 220, 22, 8, 323, 41097, 13028, 16, 82263, 7650, 320, 308, 284, 220, 22, 8, 24548, 13, 305, 1389, 296, 16991, 54865, 4007, 315, 279, 4851, 305, 1389, 503, 323, 264, 89639, 597, 1389, 296, 315, 2585, 320, 308, 284, 220, 20, 8, 323, 41097, 13028, 16, 82263, 7650, 320, 308, 284, 220, 20, 8, 24548, 1234, 41390, 63623, 13, 305, 13688, 315, 2163, 10594, 81, 2045, 5448, 315, 2585, 323, 41097, 13028, 16, 82263, 7650, 520, 1891, 561, 1286, 323, 42345, 1286, 13, 578, 2163, 10594, 81, 2045, 25199, 374, 4319, 839, 449, 264, 4251, 67822, 1584, 662, 25635, 3703, 220, 16, 9653, 13, 602, 1174, 503, 6938, 18029, 5137, 17303, 555, 63859, 13, 597, 13688, 315, 264, 89639, 5448, 315, 2585, 323, 41097, 13028, 16, 82263, 7650, 520, 1891, 561, 1286, 323, 42345, 1286, 13, 578, 2163, 10594, 81, 2045, 25199, 374, 4319, 839, 449, 264, 4251, 67822, 1584, 662, 25635, 3703, 220, 16, 9653, 13, 326, 362, 89639, 3276, 261, 454, 11975, 2521, 23899, 520, 42345, 1286, 13, 296, 362, 90438, 1612, 729, 3225, 13, 308, 10608, 992, 44496, 3395, 2859, 61152, 449, 34556, 772, 258, 320, 6307, 883, 505, 2585, 323, 41097, 13028, 16, 82263, 7650, 24548, 13, 80340, 2160, 20718, 320, 2539, 1684, 883, 323, 3345, 709, 6325, 320, 15932, 7609, 297, 32541, 2461, 315, 84827, 1612, 278, 65415, 23899, 323, 2107, 35605, 281, 2635, 355, 3158, 505, 2585, 320, 308, 284, 220, 20, 8, 323, 41097, 13028, 16, 82263, 7650, 320, 308, 284, 220, 19, 8, 24548, 13, 281, 4060, 8942, 59544, 60517, 220, 20, 2919, 1306, 5103, 10020, 65415, 11134, 13, 12041, 315, 279, 85648, 304, 902, 279, 6437, 12745, 5039, 30563, 6437, 88896, 315, 5789, 902, 1051, 539, 312, 12, 8862, 339, 59544, 1534, 1306, 11134, 13, 25635, 16283, 220, 15, 13, 20, 9653, 13, 2874, 32541, 2461, 315, 93329, 59544, 60517, 304, 2585, 320, 308, 284, 220, 24, 8, 323, 41097, 13028, 16, 82263, 7650, 320, 308, 284, 220, 22, 8, 24548, 13, 22765, 828, 3585, 527, 12882, 449, 2307, 318, 3950, 16283, 19392, 3152, 20903, 274, 1770, 749, 13, 2956, 7437, 527, 7863, 555, 259, 482, 1985, 13, 2360, 5199, 12062, 1051, 16914, 8797, 1404, 2217, 2057, 19874, 279, 24548, 304, 810, 7872, 11, 584, 1903, 374, 24264, 24408, 38140, 505, 2132, 24747, 11083, 1992, 292, 85648, 11, 3411, 369, 41961, 315, 41097, 13028, 16, 311, 93329, 301, 2411, 43918, 16630, 13, 1666, 3685, 11, 85648, 505, 2585, 80285, 24548, 51068, 304, 2077, 311, 279, 19581, 220, 16, 482, 329, 55983, 15709, 57770, 380, 14345, 982, 764, 40101, 323, 1243, 31467, 304, 2077, 311, 279, 93329, 301, 2411, 43918, 44496, 347, 321, 859, 1645, 87348, 331, 22671, 320, 30035, 13, 220, 17, 64, 11, 293, 7609, 1676, 466, 552, 505, 41097, 13028, 16, 82263, 7650, 24548, 89831, 30293, 320, 30035, 13, 220, 17, 66, 11, 294, 128257, 198, 128256, 78191, 198, 791, 3495, 2128, 482, 6197, 555, 279, 3907, 315, 52629, 482, 706, 1766, 430, 264, 13128, 2663, 41097, 13028, 16, 304, 279, 36471, 315, 6680, 31080, 374, 3025, 311, 11388, 264, 2349, 304, 6680, 6530, 2391, 10368, 13, 2435, 617, 7633, 279, 13128, 439, 459, 364, 64562, 12271, 4527, 12220, 7106, 5820, 482, 439, 279, 4851, 43875, 810, 6680, 2212, 279, 2547, 482, 279, 41097, 13028, 16, 13128, 304, 279, 93329, 301, 2411, 477, 36471, 315, 279, 85648, 4737, 6680, 505, 279, 4851, 311, 279, 23152, 323, 39408, 1572, 38207, 279, 7319, 7410, 389, 279, 7147, 315, 279, 6680, 31080, 13, 763, 2077, 11, 433, 10284, 88687, 279, 20314, 8335, 304, 279, 93329, 301, 2411, 323, 420, 3135, 304, 279, 6680, 31080, 390, 6765, 287, 13, 763, 264, 28799, 1180, 315, 44288, 11, 430, 98867, 315, 279, 6680, 31080, 26338, 6680, 6530, 311, 279, 23152, 323, 39408, 1572, 11, 10923, 810, 6680, 311, 5662, 279, 8271, 323, 24569, 22815, 17045, 304, 10368, 13, 578, 14248, 2019, 420, 374, 5015, 55407, 3495, 1606, 433, 36611, 369, 279, 1176, 892, 264, 1401, 39538, 43943, 17383, 555, 902, 10368, 374, 89542, 13, 2435, 4510, 279, 2890, 8935, 315, 10368, 7344, 10815, 449, 279, 2144, 430, 6680, 6530, 374, 1694, 14400, 311, 279, 63900, 3158, 13, 17054, 6941, 38530, 331, 11, 505, 279, 52629, 10181, 315, 92976, 33945, 323, 6344, 57565, 19152, 323, 3063, 49581, 11, 1071, 25, 330, 2746, 584, 649, 3619, 1268, 1521, 6067, 990, 11, 1243, 584, 1253, 387, 3025, 311, 2274, 12823, 430, 649, 1520, 22118, 1063, 315, 279, 8706, 19338, 3611, 79308, 6617, 34775, 13, 330, 1687, 1440, 430, 10368, 649, 6144, 2403, 4851, 8624, 11, 12943, 323, 1690, 1023, 4787, 13, 1115, 4007, 706, 11054, 264, 53194, 1887, 430, 38207, 994, 279, 36041, 10700, 2547, 374, 51582, 1210, 578, 3495, 482, 902, 374, 3196, 389, 7978, 1701, 24548, 482, 706, 1027, 4756, 304, 22037, 26545, 13, 578, 41097, 13028, 16, 13128, 374, 1101, 3118, 304, 12966, 482, 323, 14248, 617, 39764, 430, 7106, 5820, 304, 12966, 1101, 12992, 279, 7410, 389, 279, 14620, 315, 279, 93329, 301, 2411, 304, 279, 23152, 323, 63900, 3158, 11, 17919, 6680, 7119, 279, 8271, 323, 24569, 13, 21815, 369, 264, 5623, 6514, 578, 12074, 1101, 27313, 279, 2515, 315, 459, 22772, 24549, 2663, 816, 14320, 16, 482, 7086, 1306, 279, 3752, 505, 7834, 15317, 482, 389, 279, 1957, 315, 279, 41097, 13028, 16, 13128, 13, 2435, 1766, 430, 433, 28003, 19011, 279, 1957, 315, 7859, 6680, 6530, 389, 279, 14620, 315, 279, 93329, 301, 2411, 902, 374, 10534, 2391, 7106, 5820, 11, 19054, 279, 13336, 430, 264, 5623, 1436, 387, 8040, 902, 57924, 279, 2890, 7720, 315, 10368, 13, 17054, 38530, 331, 1071, 25, 330, 4054, 315, 1057, 6848, 374, 430, 41097, 13028, 16, 706, 264, 3361, 3560, 304, 26991, 6680, 6530, 311, 279, 39408, 1572, 323, 420, 374, 2216, 459, 3062, 961, 315, 279, 2547, 994, 584, 1212, 311, 1781, 922, 2555, 2663, 279, 41861, 28439, 902, 374, 5938, 449, 41713, 8624, 323, 955, 220, 17, 20335, 13, 330, 1383, 47141, 420, 13128, 304, 279, 39408, 1572, 1243, 8530, 584, 1436, 23075, 1063, 315, 279, 5435, 315, 20335, 323, 8530, 420, 816, 14320, 16, 24549, 1436, 2218, 279, 41097, 13028, 16, 304, 279, 63900, 3158, 311, 617, 264, 16003, 2515, 13, 330, 2181, 1253, 387, 430, 555, 8830, 279, 3318, 315, 279, 816, 14320, 16, 22772, 43030, 389, 279, 41097, 13028, 16, 13128, 11, 584, 649, 3351, 264, 3094, 12401, 311, 3515, 264, 5623, 430, 649, 1520, 2585, 1063, 3682, 21249, 4787, 1210, 578, 14248, 617, 4036, 11006, 505, 279, 8013, 18449, 5114, 311, 3351, 311, 279, 1828, 10474, 315, 279, 2447, 13, 22938, 449, 8590, 1705, 1101, 3196, 520, 279, 3907, 520, 52629, 11, 814, 690, 5719, 279, 816, 14320, 16, 43030, 779, 433, 649, 387, 1511, 389, 4726, 10065, 7978, 13, 220, 128257, 198 ]

2,107