bluuebunny/crossref_metadata_2025 huggingface dataset:
Subunit-specific analysis of cohesin-mutant myeloid malignancies reveals distinct ontogeny and outcomes
Authors: Jann Johann-Christoph , Hergott Christopher B. , Winkler Marisa , Liu Yiwen , Braun Benjamin , Charles Anne , Copson Kevin M. , Barua Shougat , Meggendorfer Manja , Nadarajah Niroshan , Shimony Shai , Winer Eric S. , Wadleigh Martha , Stone Richard M. , DeAngelo Daniel J. , Garcia Jacqueline S. , Haferlach Torsten , Lindsley R. Coleman , Luskin Marlise R. , Stahl Maximilian , Tothova Zuzana
Published: July 2024

Mutations in the cohesin complex components (STAG2, RAD21, SMC1A, SMC3, and PDS5B) are recurrent genetic drivers in myelodysplastic neoplasm (MDS) and acute myeloid leukemia (AML). Whether the different cohesin subunit mutations share clinical characteristics and prognostic significance is not known. We analyzed 790 cohesin-mutant patients from the Dana-Farber Cancer Institute (DFCI) and the Munich Leukemia Laboratory (MLL), 390 of which had available outcome data, and identified subunit-specific clinical, prognostic, and genetic characteristics suggestive of distinct ontogenies. We found that STAG2 mutations are acquired at MDS stage and are associated with secondary AML, adverse prognosis, and co-occurrence of secondary AML-type mutations. In contrast, mutations in RAD21, SMC1A and SMC3 share features with de novo AML with better prognosis, and co-occurrence with de novo AML-type lesions. The findings show the heterogeneous nature of cohesin complex mutations, and inform clinical and prognostic classification, as well as distinct biology of the cohesin complex.
Targeting cytokine and chemokine signaling pathways for cancer therapy
Authors: Yi Ming , Li Tianye , Niu Mengke , Zhang Haoxiang , Wu Yuze , Wu Kongming , Dai Zhijun
Published: July 2024

Cytokines are critical in regulating immune responses and cellular behavior, playing dual roles in both normal physiology and the pathology of diseases such as cancer. These molecules, including interleukins, interferons, tumor necrosis factors, chemokines, and growth factors like TGF-β, VEGF, and EGF, can promote or inhibit tumor growth, influence the tumor microenvironment, and impact the efficacy of cancer treatments. Recent advances in targeting these pathways have shown promising therapeutic potential, offering new strategies to modulate the immune system, inhibit tumor progression, and overcome resistance to conventional therapies. In this review, we summarized the current understanding and therapeutic implications of targeting cytokine and chemokine signaling pathways in cancer. By exploring the roles of these molecules in tumor biology and the immune response, we highlighted the development of novel therapeutic agents aimed at modulating these pathways to combat cancer. The review elaborated on the dual nature of cytokines as both promoters and suppressors of tumorigenesis, depending on the context, and discussed the challenges and opportunities this presents for therapeutic intervention. We also examined the latest advancements in targeted therapies, including monoclonal antibodies, bispecific antibodies, receptor inhibitors, fusion proteins, engineered cytokine variants, and their impact on tumor growth, metastasis, and the tumor microenvironment. Additionally, we evaluated the potential of combining these targeted therapies with other treatment modalities to overcome resistance and improve patient outcomes. Besides, we also focused on the ongoing research and clinical trials that are pivotal in advancing our understanding and application of cytokine- and chemokine-targeted therapies for cancer patients.
The association of early life factors with depression and anxiety in adults aged 40–69 years: a population-based cohort study
Authors: Wang Ruirui , Shi Mengyao , Zhang Qilu , Zhang Jing , Sun Lulu , Jia Yiming , Zhu Zhengbao , Xu Tan , Zhang Yonghong
Published: July 2024

This study was aimed to explore the longitudinal association of five early life factors (breastfeeding, maternal smoking around birth, birth weight, being born in a multiple birth, and adoption) during the in-utero, perinatal, and early childhood development stages with incidence of depression and anxiety in adults aged 40–69 years. We used data from the UK biobank, 5,02,394 participants aged 40–69 years were recruited between 2006 and 2010. Participants provided information on early life exposures through touchscreen questionnaires or verbal interviews at baseline. The primary outcomes, depression, and anxiety, were defined according to the International Classification of Diseases, 10th Revision. Hazard ratios (HR) and 95% confidence intervals (CI) for each factor were reported. During a median follow-up of 13.6 years, 16,502 (3.55%) participants developed depression, and 15,507 (3.33%) developed anxiety. After adjusting for potential confounders, increased risk of depression was found to be significantly associated with non-breastfeeding (HR, 1.08; 95% CI, 1.04–1.13), maternal smoking around birth (HR, 1.19; 95% CI, 1.14–1.23), being born in multiple births (HR, 1.16; 95% CI, 1.05–1.27), low birth weight (HR, 1.14; 95% CI, 1.07–1.22), and being an adoptee (HR, 1.42; 95% CI, 1.28–1.58). Increased risk of anxiety was associated with non-breastfeeding (HR, 1.09; 95% CI, 1.04–1.13), maternal smoking around birth (HR, 1.11; 95% CI, 1.07–1.16), being born in a multiple births (HR, 1.05; 95% CI, 0.95–1.17), low birth weight (HR, 1.12; 95% CI, 1.05–1.20), and being an adoptee (HR, 1.25; 95% CI, 1.10–1.41). Each of these five early life factors can be considered as early life risk factors for incident depression and anxiety in adulthood independently. The dose-response relationship was also observed, suggesting that with an increase in the number of early life risk factors, the likelihood of experiencing depression and anxiety also increased. These findings highlighted the imperative consideration of early life factors in comprehending the susceptibility to mental health disorders later in life, including non-breastfeeding, maternal smoking around birth, being born in multiple births, low birth weight, and being an adoptee.
Differential effects of purified low molecular weight Poly(I:C) in the maternal immune activation model depend on the laboratory environment
Authors: Tillmann Katharina E. , Schaer Ron , Mueller Flavia S. , Mueller Karin , Voelkl Bernhard , Weber-Stadlbauer Ulrike , Pollak Daniela D.
Published: July 2024

The Poly (I:C) (polyriboinosinic-polyribocytidilic acid) paradigm of maternal immune activation (MIA) is most widely used as experimental model for the evaluation of the effects of gestational infection on the brain and behavior of the progeny. We have previously reported significant batch-to-batch variability in the effects of Poly (I:C), purchased from the same supplier (Sigma–Aldrich), on maternal and fetal immune responses and found these differences to be dependent on the relative amount of synthetic double-stranded RNA fragments in the high versus low molecular weight (LMW) range contained in the compound. We here resorted to Poly (I:C) purified for LMW dsRNA fragments to establish a MIA paradigm with increased reproducibility and enhanced standardization in an effort to refine the MIA paradigm and characterize its effect on offspring behavior. We found that the parallel application of LMW Poly (I:C) in two different MIA-experienced laboratories (Vienna and Zurich) yielded differential outcomes in terms of maternal immune responses and behavioral phenotypes in the offspring generation. In both experimental sites, administration of LMW Poly (I:C) induced a significant sickness response and cytokine induction in the pregnant dam and fetal brains, while the expected deficit in sociability as one main behavioral outcome parameter in the MIA progeny, was only present in the Zurich, but not the Vienna cohort. We conclude that although using Poly (I:C) purified for a defined molecular weight range reduces batch-to-batch variability, it does not make the MIA model more reliable and robust. The differential response in behavioral phenotypes of the MIA offspring between the two laboratories illustrates the highly complex interaction between prenatal and postnatal milieus - including the laboratory environment - that determine offspring phenotypic outcomes after MIA. Consequently, establishing a new MIA protocol or implementing the MIA model firstly under new or changed environmental conditions must include the assessment of offspring behavior to ensure solid and reproducible experimental outcomes.
Unsupervised representation learning of chromatin images identifies changes in cell state and tissue organization in DCIS
Authors: Zhang Xinyi , Venkatachalapathy Saradha , Paysan Daniel , Schaerer Paulina , Tripodo Claudio , Uhler Caroline , Shivashankar G. V.
Published: July 2024

Ductal carcinoma in situ (DCIS) is a pre-invasive tumor that can progress to invasive breast cancer, a leading cause of cancer death. We generate a large-scale tissue microarray dataset of chromatin images, from 560 samples from 122 female patients in 3 disease stages and 11 phenotypic categories. Using representation learning on chromatin images alone, without multiplexed staining or high-throughput sequencing, we identify eight morphological cell states and tissue features marking DCIS. All cell states are observed in all disease stages with different proportions, indicating that cell states enriched in invasive cancer exist in small fractions in normal breast tissue. Tissue-level analysis reveals significant changes in the spatial organization of cell states across disease stages, which is predictive of disease stage and phenotypic category. Taken together, we show that chromatin imaging represents a powerful measure of cell state and disease stage of DCIS, providing a simple and effective tumor biomarker.
Discovery of a Ni2+-dependent heterohexameric metformin hydrolase
Authors: Li Tao , Xu Zhi-Jing , Zhang Shu-Ting , Xu Jia , Pan Piaopiao , Zhou Ning-Yi
Published: July 2024

The biguanide drug metformin is a first-line blood glucose-lowering medication for type 2 diabetes, leading to its presence in the global environment. However, little is known about the fate of metformin by microbial catabolism. Here, we characterize a Ni2+-dependent heterohexameric enzyme (MetCaCb) from the ureohydrolase superfamily, catalyzing the hydrolysis of metformin into guanylurea and dimethylamine. Either subunit alone is catalytically inactive, but together they work as an active enzyme highly specific for metformin. The crystal structure of the MetCaCb complex shows the coordination of the binuclear metal cluster only in MetCa, with MetCb as a protein binder of its active cognate. An in-silico search and functional assay discover a group of MetCaCb-like protein pairs exhibiting metformin hydrolase activity in the environment. Our findings not only establish the genetic and biochemical foundation for metformin catabolism but also provide additional insights into the adaption of the ancient enzymes toward newly occurred substrate.
Modelling chemical processes in explicit solvents with machine learning potentials
Authors: Zhang Hanwen , Juraskova Veronika , Duarte Fernanda
Published: July 2024

Solvent effects influence all stages of the chemical processes, modulating the stability of intermediates and transition states, as well as altering reaction rates and product ratios. However, accurately modelling these effects remains challenging. Here, we present a general strategy for generating reactive machine learning potentials to model chemical processes in solution. Our approach combines active learning with descriptor-based selectors and automation, enabling the construction of data-efficient training sets that span the relevant chemical and conformational space. We apply this strategy to investigate a Diels-Alder reaction in water and methanol. The generated machine learning potentials enable us to obtain reaction rates that are in agreement with experimental data and analyse the influence of these solvents on the reaction mechanism. Our strategy offers an efficient approach to the routine modelling of chemical reactions in solution, opening up avenues for studying complex chemical processes in an efficient manner.
Enhanced disulphide bond stability contributes to the once-weekly profile of insulin icodec
Authors: Hubálek František , Cramer Christian N. , Helleberg Hans , Johansson Eva , Nishimura Erica , Schluckebier Gerd , Steensgaard Dorte Bjerre , Sturis Jeppe , Kjeldsen Thomas B.
Published: July 2024

Insulin icodec is a once-weekly insulin analogue that has a long half-life of approximately 7 days, making it suitable for once weekly dosing. The Insulin icodec molecule was developed based on the hypothesis that lowering insulin receptor affinity and introducing a strong albumin-binding moiety would result in a long insulin half-life, provided that non-receptor-mediated clearance is diminished. Here, we report an insulin clearance mechanism, resulting in the splitting of insulin molecules into its A-chain and B-chain by a thiol–disulphide exchange reaction. Even though the substitutions in insulin icodec significantly stabilise insulin against such degradation, some free B-chain is observed in plasma samples from minipigs and people with type 2 diabetes. In summary, we identify thiol–disulphide exchange reactions to be an important insulin clearance mechanism and find that stabilising insulin icodec towards this reaction significantly contributes to its long pharmacokinetic/pharmacodynamic profile.
Iron photocatalysis via Brønsted acid-unlocked ligand-to-metal charge transfer
Authors: Jiang Xiaoyu , Lan Yu , Hao Yudong , Jiang Kui , He Jing , Zhu Jiali , Jia Shiqi , Song Jinshuai , Li Shi-Jun , Niu Linbin
Published: July 2024

Reforming sustainable 3d-metal-based visible light catalytic platforms for inert bulk chemical activation is highly desirable. Herein, we demonstrate the use of a Brønsted acid to unlock robust and practical iron ligand-to-metal charge transfer (LMCT) photocatalysis for the activation of multifarious inert haloalkylcarboxylates (CnXmCOO−, X = F or Cl) to produce CnXm radicals. This process enables the fluoro-polyhaloalkylation of non-activated alkenes by combining easily available Selectfluor as a fluorine source. Valuable alkyl fluorides including potential drug molecules can be easily obtained through this protocol. Mechanistic studies indicate that the real light-harvesting species may derive from the in situ-assembly of Fe3+, CnXmCOO−, H+, and acetonitrile solvent, in which the Brønsted acid indeed increases the efficiency of LMCT between the iron center and CnXmCOO− via hydrogen-bond interactions. We anticipate that this Brønsted acid-unlocked iron LMCT platform would be an intriguing sustainable option to execute the activation of inert compounds.
Utilizing cost-effective pyrocarbon for highly efficient gold retrieval from e-waste leachate
Authors: Fu Kaixing , Liu Xia , Zhang Xiaolin , Zhou Shiqing , Zhu Nanwen , Pei Yong , Luo Jinming
Published: July 2024

Addressing burdens of electronic waste (E-waste) leachate while achieving sustainable and selective recovery of noble metals, such as gold, is highly demanded due to its limited supply and escalating prices. Here we demonstrate an environmentally-benign and practical approach for gold recovery from E-waste leachate using alginate-derived pyrocarbon sorbent. The sorbent demonstrates potent gold recovery performance compared to most previously reported advanced sorbents, showcasing high recovery capacity of 2829.7 mg g−1, high efficiency (>99.5%), remarkable selectivity (Kd ~ 3.1 × 108 mL g−1), and robust anti-interference capabilities within environmentally relevant contexts. The aromatic structures of pyrocarbon serve as crucial electrons sources, enabling a hydroxylation process that simultaneously generates electrons and phenolic hydroxyls for the reduction of gold ions. Our investigations further uncover a “stepwise” nucleation mechanism, in which gold ions are reduced as intermediate gold-chlorine clusters, facilitating rapid reduction process by lowering energy barriers from 1.08 to −21.84 eV. Technoeconomic analysis demonstrates its economic viability with an input-output ratio as high as 1370%. Our protocol obviates the necessity for organic reagents whilst obtaining 23.96 karats gold product from real-world central processing units (CPUs) leachates. This work introduces a green sorption technique for gold recovery, emphasizing its role in promoting a circular economy and environmental sustainability.
Anomalous upper critical field in the quasicrystal superconductor Ta1.6Te
Authors: Terashima Taichi , Tokumoto Yuki , Hamano Kotaro , Konoike Takako , Kikugawa Naoki , Edagawa Keiichi
Published: July 2024

Superconductivity in quasicrystals poses a new challenge in condensed matter physics. We measured the resistance and ac magnetic susceptibility of a Ta1.6Te dodecagonal quasicrystal, which is superconducting belowTc ~ 1 K. We show that the upper critical field increases linearly with a large slope of − 4.4 T/K with decreasing temperature down to 0.04 K, with no tendency to level off. The extrapolated zero-temperature critical field exceeds the Pauli limit by a factor of 2.3. We also observed flux-flow resistance with thermally activated behavior and an irreversibility field that is distinct from the upper critical field. We discuss these peculiarities in terms of the nonuniform superconducting gap and spin-orbit interaction in quasicrystal structures.
A scoping review of global COVID-19 vaccine hesitancy among pregnant persons
Authors: Casubhoy Imaima , Kretz Alyssa , Tan Heang-Lee , St Clair Laura A. , Parish Maclaine , Golding Hana , Bersoff-Matcha Susan J. , Pilgrim-Grayson Catherine , Berhane Leah , Pekosz Andrew , Mostafa Heba H. , Cox Andrea L. , Burd Irina , Klein Sabra L. , Morgan Rosemary
Published: July 2024

Uptake of the COVID-19 vaccine among pregnant persons is lower than the general population. This scoping review explored pregnant people’s attitudes towards the COVID-19 vaccine, reasons for vaccine hesitancy, and whether attitudes about COVID-19 vaccines differ by country of origin. A scoping review was conducted across PubMed, Embase, CINHAL, and Scopus. Inclusion criteria were articles published in English from 2019–2022 focused on attitudes towards COVID-19 vaccination among pregnant persons. Data analysis was done via the 5Cs framework for vaccine hesitancy: Constraints, Complacency, Calculation, Confidence, and Collective Responsibility. 44 articles were extracted. A lack of confidence in vaccine safety was the most prevalent theme of hesitancy among pregnant persons. This was largely driven by a lack of access to information about the vaccine as well as mistrust of the vaccine and medical professionals. Meanwhile, vaccine acceptance was mostly driven by a desire to protect themselves and their loved ones. Overall, COVID-19 vaccine hesitancy among pregnant persons continues to be high. Vaccine hesitancy is primarily driven by fear of the unknown side effects of the vaccine on pregnant persons and their fetuses along with a lack of information and medical mistrust. Some differences can be seen between high income and low- and middle-income countries regarding vaccine hesitancy, showing that a single solution cannot be applied to all who are vaccine hesitant. General strategies, however, can be utilized to reduce vaccine hesitancy, including advocating for inclusion of pregnant persons in clinical trials and incorporating consistent COVID-19 vaccine counseling during prenatal appointments.
The 30 m vegetation maps from 1990 to 2020 in the Tibetan Plateau
Authors: Wu Fan , Ren Hongrui , Zhou Guangsheng
Published: July 2024

The Tibetan Plateau (TP) is crucial for global climate change and China’s ecological security. Given recent drastic changes in vegetation from climate change and human activities, long-term vegetation monitoring is urgently required. This study produced the vegetation maps of the TP from 1990 to 2020 every ten years using random forest classifier and Landsat imagery. We selected the same stable samples and features for mapping to reduce errors between years and proposed spatial filtering to further improve the accuracy. The overall accuracy surpassed 95.00%, with all Kappa coefficients exceeding 0.95. A further assessment based on sampling sites from literature and field survey was higher than 80%. The importance ranking results indicated that in the TP, climate factors and terrain factors are the most important factors in the vegetation mapping. This study provides a method for mapping vegetation in alpine areas and data support for researching the dynamic change of vegetation on the TP and evaluating its response to climate change.
Evaluation of antibacterial, antioxidant, and anti-inflammatory properties of GC/MS analysis of extracts of Ajuga. integrifolia Buch.-Ham. leaves
Authors: Singh Harsha , Kumar Suresh , Arya Atul
Published: July 2024

The purpose of the current study was to examine chemical composition, antioxidant, anti-inflammatory and antibacterial properties of leaves extract of Ajuga integrifolia Buch.-Ham. The antibacterial and antioxidant properties of three different solvents i.e. methanol (AIM), hexane (AIH), and water (AIW) were tested against two bacterial strains Staphylococcus aureus and Escherichia coli. The presence of antioxidant and antibacterial chemicals, such as hexanedioic acid, hexadecanoic acid, nonadecadiene, hexadecen-1-ol, octadecadienoic acid, nonane, phytol, henicosanal, stearyl aldehyde, and neophytadiene, were depicted in the GCMS chromatograms of three extracts. After the extracts' FTIR peaks were examined, it was discovered that phenols, amines, hydroxy groups, and components linked to amino acids were present. Compared to the Hexane and Water extracts, the Methanol extract showed a greater phenolic (196.16 ± 0.0083 mg gallic acid equivalent/gram), flavonoid (222.77 ± 0.002 mg rutin equivalents/g) and phosphomolybdate assay for total antioxidant activity (557.62 ± 0.0023 mg AAE/g). Methanol extract showed the highest scavenging activity with a minimum IC50 value was observed in DPPH assay. AIM showed its maximum anti-denaturation activity i.e. 3.75 ± 0.28%. For antibacterial activities, best zone of inhibition (ZOI) and minimum inhibitory concentration (MIC) was observed in case of the methanol extract as compared to other extracts against methicillin-resistant Staphylococcus aureus and β-lactam-resistant Escherichia coli.
Exploring the therapeutic potential of Aloin: unraveling neuroprotective and anticancer mechanisms, and strategies for enhanced stability and delivery
Authors: Zimbone Stefania , Romanucci Valeria , Zarrelli Armando , Giuffrida Maria Laura , Sciacca Michele F. M. , Lanza Valeria , Campagna Tiziana , Maugeri Ludovica , Petralia Salvatore , Consoli Grazia Maria Letizia , Di Fabio Giovanni , Milardi Danilo
Published: July 2024

We investigate the therapeutic potential of Aloin A and Aloin B, two natural compounds derived from Aloe vera leaves, focusing on their neuroprotective and anticancer properties. The structural differences between these two epimers suggest that they may exhibit distinct pharmacological properties. Our investigations revealed that both epimers are not stable in aqueous solution and tend to degrade rapidly, with their concentration decreasing by over 50% within approximately 12 h. These results underscore the importance of addressing issues such as the need for encapsulation into effective drug delivery systems to enhance stability. ThT fluorescence experiments showed that neither compound was able to inhibit Aβ amyloid aggregation, indicating that other mechanisms may be responsible for their neuroprotective effects. Next, an equimolar mixture of Aloin A and Aloin B demonstrated an ability to inhibit proteasome in tube tests, which is suggestive of potential anticancer properties, in accordance with antiproliferative effects observed in neuroblastoma SH-SY5Y and HeLa cell lines. Higher water stability and increased antiproliferative activity were observed by encapsulation in carbon dot nanoparticles, suggesting a promising potential for further in vivo studies.
Influence of environmental, geographic, socio-demographic, and epidemiological factors on presence of malaria at the community level in two continents
Authors: Villena Oswaldo C. , Arab Ali , Lippi Catherine A. , Ryan Sadie J. , Johnson Leah R.
Published: July 2024

The interactions of environmental, geographic, socio-demographic, and epidemiological factors in shaping mosquito-borne disease transmission dynamics are complex and changeable, influencing the abundance and distribution of vectors and the pathogens they transmit. In this study, 27 years of cross-sectional malaria survey data (1990–2017) were used to examine the effects of these factors on Plasmodium falciparum and Plasmodium vivax malaria presence at the community level in Africa and Asia. Monthly long-term, open-source data for each factor were compiled and analyzed using generalized linear models and classification and regression trees. Both temperature and precipitation exhibited unimodal relationships with malaria, with a positive effect up to a point after which a negative effect was observed as temperature and precipitation increased. Overall decline in malaria from 2000 to 2012 was well captured by the models, as was the resurgence after that. The models also indicated higher malaria in regions with lower economic and development indicators. Malaria is driven by a combination of environmental, geographic, socioeconomic, and epidemiological factors, and in this study, we demonstrated two approaches to capturing this complexity of drivers within models. Identifying these key drivers, and describing their associations with malaria, provides key information to inform planning and prevention strategies and interventions to reduce malaria burden.
Development and external validation of a predictive model for type 2 diabetic retinopathy
Authors: Li Yongsheng , Hu Bin , Lu Lian , Li Yongnan , Caika Siqingaowa , Song Zhixin , Sen Gan
Published: July 2024

Diabetes retinopathy (DR) is a critical clinical disease with that causes irreversible visual damage in adults, and may even lead to permanent blindness in serious cases. Early identification and treatment of DR is critical. Our aim was to train and externally validate a prediction nomogram for early prediction of DR. 2381 patients with type 2 diabetes mellitus (T2DM) were retrospective study from the First Affiliated Hospital of Xinjiang Medical University in Xinjiang, China, hospitalised between Jan 1, 2019 and Jun 30, 2022. 962 patients with T2DM from the Suzhou BenQ Hospital in Jiangsu, China hospitalised between Jul 1, 2020 to Jun 30, 2022 were considered for external validation. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression was performed to identify independent predictors and establish a nomogram to predict the occurrence of DR. The performance of the nomogram was evaluated using a receiver operating characteristic curve (ROC), a calibration curve, and decision curve analysis (DCA). Neutrophil, 25-hydroxyvitamin D3 [25(OH)D3], Duration of T2DM, hemoglobin A1c (HbA1c), and Apolipoprotein A1 (ApoA1) were used to establish a nomogram model for predicting the risk of DR. In the development and external validation groups, the areas under the curve of the nomogram constructed from the above five factors were 0.834 (95%CI 0.820–0.849) and 0.851 (95%CI 0.829–0.874), respectively. The nomogram demonstrated excellent performance in the calibration curve and DCA. This research has developed and externally verified that the nomograph model shows a good predictive ability in assessing DR risk in people with type 2 diabetes. The application of this model will help clinicians to intervene early, thus effectively reducing the incidence rate and mortality of DR in the future, and has far-reaching significance in improving the long-term health prognosis of diabetes patients.
Interaction between ambient CO and temperature or relative humidity on the risk of stroke hospitalization
Authors: Liu Zhuo , Meng Hua , Wang Xingtian , Lu Wenwen , Ma Xiaojuan , Geng Yuhui , Su Xinya , Pan Dongfeng , Liang Peifeng
Published: July 2024

Although the independent effects of ambient CO, temperature or humidity on stroke have been confirmed, it is still unclear where there is an interaction between these factors and who is sensitive populations for these. The stroke hospitalization and ambient CO, temperature, humidity data were collected in 22 Counties and districts of Ningxia, China in 2014–2019. The lagged effect of ambient CO, temperature or humidity were analyze by the generalized additive model; the interaction were evaluated by the bivariate response surface model and stratified analysis with relative excessive risk (RERI). High temperature and CO levels had synergistic effects on hemorrhagic stroke (RERI = 0.05, 95% CI 0.033–0.086) and ischemic stroke (RERI = 0.035, 95% CI 0.006–0.08). Low relative humidity and CO were synergistic in hemorrhagic stroke (RERI = 0.192, 95% CI 0.184–0.205) and only in ischemic stroke in the elderly group (RERI = 0.056, 95% CI 0.025–0.085). High relative humidity and CO exhibited antagonistic effects on the risk of ischemic stroke hospitalization in both male and female groups (RERI = − 0.088, 95% CI − 0.151to − 0.031; RERI = − 0.144, 95% CI − 0.216 to − 0.197). Exposure to CO increases the risk of hospitalization related to hemorrhagic and ischemic strokes. CO and temperature or humidity interact with risk of stroke hospitalization with sex and age differences.
Machine learning analysis of PM1 impact on visibility with comprehensive sensitivity evaluation of concentration, composition, and meteorological factors
Authors: Majewski Grzegorz , Szeląg Bartosz , Rogula-Kozłowska Wioletta , Rogula-Kopiec Patrycja , Brandyk Andrzej , Rybak Justyna , Radziemska Maja , Liniauskiene Ernesta , Klik Barbara
Published: July 2024

This study introduces a novel approach to visibility modelling, focusing on PM1 concentration, its chemical composition, and meteorological conditions in two distinct Polish cities, Zabrze and Warsaw. The analysis incorporates PM1 concentration measurements as well as its chemical composition and meteorological parameters, including visibility data collected during summer and winter measurement campaigns (120 samples in each city). The developed calculation procedure encompasses several key steps: formulating a visibility prediction model through machine learning, identifying data in clusters using unsupervised learning methods, and conducting global sensitivity analysis for each cluster. The multi-layer perceptron methods developed demonstrate high accuracy in predicting visibility, with R values of 0.90 for Warsaw and an RMSE of 1.52 km for Zabrze. Key findings reveal that air temperature and relative humidity significantly impact visibility, alongside PM1 concentration and specific heavy metals such as Rb, Vi, and Cd in Warsaw and Cr, Vi, and Mo in Zabrze. Cluster analysis underscores the localized and complex nature of visibility determinants, highlighting the substantial but previously underappreciated role of heavy metals. Integrating the k-means clustering and GSA methods emerges as a powerful tool for unravelling complex mechanisms of chemical compound changes in particulate matter and air, significantly influencing visibility development.
Cost-utility and budget impact analysis of neoadjuvant dual HER2 targeted therapy for HER2-positive breast cancer in Sri Lanka
Authors: Gunasekara Agampodi Danushi Mendis , Youngkong Sitaporn , Anothaisintawee Thunyarat , Dejthevaporn Thitiya , Fernandopulle Rohini , Chaikledkaew Usa
Published: July 2024

This study aimed to assess the cost-utility and budget impact of dual to single HER2 targeted neoadjuvant therapy for HER2-positive breast cancer in Sri Lanka. A five-health state Markov model with lifetime horizon was used to assess the cost-utility of neoadjuvant trastuzumab (T) plus pertuzumab (P) or lapatinib (L) compared to single therapy of T with chemotherapy (C), in public healthcare system and societal perspectives. Input parameters were estimated using local data, network meta-analysis, published reports and literature. Costs were adjusted to year 2021 (1USD = LKR194.78). Five-year budget impact for public healthcare system was assessed. Incremental cost-effectiveness ratios in societal perspective for neoadjuvantLTC plus adjuvantT (strategy 3), neoadjuvantPTC plus adjuvantT (strategy 2), neoadjuvantLTC plus adjuvantLT (strategy 5), and neoadjuvantPTC plus adjuvantPT (strategy 4) compared to neoadjuvantTC plus adjuvantT (strategy 1) were USD2716, USD5600, USD6878, and USD12127 per QALY gained, respectively. One GDP per-capita (USD3815) was considered as the cost-effectiveness threshold for the analysis. Even though only the ICER for strategy 3 was cost-effective, uncertainty of efficacy parameter was revealed. For strategy 2 neoadjuvant PTC plus adjuvant T, a 25% reduction of neoadjuvant regimen cost was required to be cost effective for use in early HER2 positive breast cancer.
Risk of chronic kidney disease in patients with a hyperglycemic crisis as the initial presentation of type 2 diabetes
Authors: Huang Chun-Ta , Muo Chih-Hsin , Sung Fung-Chang , Chen Pei-Chun
Published: July 2024

Limited data exist on long-term renal outcomes in patients with hyperglycemic crisis (HC) as initial type 2 diabetes presentation. We evaluated the risk of chronic kidney disease (CKD) development in those with concurrent HC at diagnosis. Utilizing Taiwan’s insurance claims from adults newly diagnosed with type 2 diabetes during 2006–2015, we created HC and matched non-HC cohorts. We assessed incident CKD/diabetic kidney disease (DKD) by 2018’s end, calculating the hazard ratio (HR) with the Cox model. Each cohort comprised 13,242 patients. The combined CKD and DKD incidence was two-fold higher in the HC cohort than in the non-HC cohort (56.47 versus 28.49 per 1000 person-years) with an adjusted HR (aHR) of 2.00 (95% confidence interval [CI] 1.91–2.10]). Risk increased from diabetic ketoacidosis (DKA) (aHR:1.69 [95% CI 1.59–1.79]) to hyperglycemic hyperosmolar state (HHS) (aHR:2.47 [95% CI 2.33–2.63]) and further to combined DKA-HHS (aHR:2.60 [95% CI 2.29–2.95]). Subgroup analysis in individuals aged ≥ 40 years revealed a similar trend with slightly reduced incidences and HRs. Patients with HC as their initial type 2 diabetes presentation face a higher CKD risk than do those without HC. Enhanced medical attention and customized interventions are crucial to reduce this risk.
The N400 effect captures nuances in implicit political preferences
Authors: Mahieux Emmanuel , de-Wit Lee , Otten Leun J. , Devlin Joseph T. , Wicha Nicole Y. Y.
Published: July 2024

We conducted a study in San Antonio, Texas, in the weeks preceding the 2022 state Governor election to determine if implicit or explicit measures of political preference could predict voter behavior. We adapted an established event-related potential (ERP) paradigm showing political statements to participants one word at the time where the last word made the statement pro-Republican or pro-Democratic. Our sample of college students included decided and undecided voters, and was reflective of the demographic make-up of south-central Texas. Our implicit measures were an established authoritarianism scale and the N400 effect to the sentence-final word. The N400 is an ERP to any stimulus that engages semantic memory and has been shown to measure implicit disagreement with political statements. Explicit measures of political preference and authoritarianism were predictive of vote choice. The expected N400 effect was found for Democratic voters, with larger amplitude to pro-Republican than pro-Democratic statements. Surprisingly, decided Republican voters showed no difference in N400 responses to pro-Republican and pro-Democratic statements and there was no group difference in the N400 effect. In turn, the N400 was not predictive of voter behavior. We argue that the N400 effect reflected individual political preferences, but that ultimately voter behavior aligned with partisan identity.
Retrospective analysis of interpretable machine learning in predicting ICU thrombocytopenia in geriatric ICU patients
Authors: Xu Yingting , Zhang Weimin , Ma Xuchao , Wu Muying , Jiang Xuandong
Published: July 2024

We developed an interpretable machine learning algorithm that prospectively predicts the risk of thrombocytopenia in older critically ill patients during their stay in the intensive care unit (ICU), ultimately aiding clinical decision-making and improving patient care. Data from 2286 geriatric patients who underwent surgery and were admitted to the ICU of Dongyang People’s Hospital between 2012 and 2021 were retrospectively analyzed. Integrated algorithms were developed, and four machine-learning algorithms were used. Selected characteristics included common demographic data, biochemical indicators, and vital signs. Eight key variables were selected using the Least Absolute Shrinkage and Selection Operator and Random Forest Algorithm. Thrombocytopenia occurred in 18.2% of postoperative geriatric patients, with a higher mortality rate. The C5.0 model showed the best performance, with an area under the receiver operating characteristic curve close to 0.85, along with unparalleled accuracy, precision, specificity, recall, and balanced accuracy scores of 0.88, 0.98, 0.89, 0.98, and 0.85, respectively. The support vector machine model excelled at predictively assessing thrombocytopenia severity, demonstrating an accuracy rate of 0.80 in the MIMIC database. Thus, our machine learning-based models have considerable potential in effectively predicting the risk and severity of postoperative thrombocytopenia in geriatric ICU patients for better clinical decision-making and patient care.
Dynamics of ionized poly(4-hydroxystyrene)-type resist polymers with tert-butoxycarbonyl-protecting group
Authors: Okamoto Kazumasa , Muroya Yusa , Kozawa Takahiro
Published: July 2024

The imaging reactions of resist materials used for nano-patterning have become radiation-chemical reactions, with the shortening of wavelengths of the exposure light sources in lithography systems. The most widely used patterning materials in industrial lithography are chemically amplified resists (CAR). Understanding the deprotonation mechanism of ionized polymers (radical cations) is important for acid generation in CARs. In this study, the dynamics of radical cations in poly(4-hydroxystyrene) (PHS)–type resist polymers, partially and totally protected by tert-butoxycarbonyl (t-BOC) groups, are investigated using a combination of electron pulse radiolysis experiments, acid yield measurements, and quantum chemical calculations. The t-BOC(oxy) group exhibits π-electron-donating behavior in the monomer cation but changes to electron-accepting behavior in the polymer cation, owing to the interaction between substituents. The destabilization of radical cations due to decreased intramolecular charge resonance may contribute to the high deprotonation efficiency of t-BOC-capped PHS polymers.
Estimating the household secondary attack rate and serial interval of COVID-19 using social media
Authors: Dhiman Aarzoo , Yom-Tov Elad , Pellis Lorenzo , Edelstein Michael , Pebody Richard , Hayward Andrew , House Thomas , Finnie Thomas , Guzman David , Lampos Vasileios ,   Virus Watch Consortium, Aldridge Rob , Beale Sarah , Byrne Thomas , Kovar Jana , Braithwaite Isobel , Fragaszy Ellen , Fong Wing Lam Erica , Geismar Cyril , Hoskins Susan , Navaratnam Annalan , Nguyen Vincent , Patel Parth , Shrotri Maddie , Yavlinsky Alexei , Hardelid Pia , Wijlaars Linda , Nastouli Eleni , Spyer Moira , Aryee Anna , McKendry Rachel , Cheng Tao , Johnson Anne , Michie Susan , Gibbs Jo , Gilson Richard , Rodger Alison , Cox Ingemar J.
Published: July 2024

We propose a method to estimate the household secondary attack rate (hSAR) of COVID-19 in the United Kingdom based on activity on the social media platform X, formerly known as Twitter. Conventional methods of hSAR estimation are resource intensive, requiring regular contact tracing of COVID-19 cases. Our proposed framework provides a complementary method that does not rely on conventional contact tracing or laboratory involvement, including the collection, processing, and analysis of biological samples. We use a text classifier to identify reports of people tweeting about themselves and/or members of their household having COVID-19 infections. A probabilistic analysis is then performed to estimate the hSAR based on the number of self or household, and self and household tweets of COVID-19 infection. The analysis includes adjustments for a reluctance of Twitter users to tweet about household members, and the possibility that the secondary infection was not acquired within the household. Experimental results for the UK, both monthly and weekly, are reported for the period from January 2020 to February 2022. Our results agree with previously reported hSAR estimates, varying with the primary variants of concern, e.g. delta and omicron. The serial interval (SI) is based on the time between the two tweets that indicate a primary and secondary infection. Experimental results, though larger than the consensus, are qualitatively similar. The estimation of hSAR and SI using social media data constitutes a new tool that may help in characterizing, forecasting and managing outbreaks and pandemics in a faster, affordable, and more efficient manner.
Dissecting task-based fMRI activity using normative modelling: an application to the Emotional Face Matching Task
Authors: Savage Hannah S. , Mulders Peter C. R. , van Eijndhoven Philip F. P. , van Oort Jasper , Tendolkar Indira , Vrijsen Janna N. , Beckmann Christian F. , Marquand Andre F.
Published: July 2024

Functional neuroimaging has contributed substantially to understanding brain function but is dominated by group analyses that index only a fraction of the variation in these data. It is increasingly clear that parsing the underlying heterogeneity is crucial to understand individual differences and the impact of different task manipulations. We estimate large-scale (N = 7728) normative models of task-evoked activation during the Emotional Face Matching Task, which enables us to bind heterogeneous datasets to a common reference and dissect heterogeneity underlying group-level analyses. We apply this model to a heterogenous patient cohort, to map individual differences between patients with one or more mental health diagnoses relative to the reference cohort and determine multivariate associations with transdiagnostic symptom domains. For the face>shapes contrast, patients have a higher frequency of extreme deviations which are spatially heterogeneous. In contrast, normative models for faces>baseline have greater predictive value for individuals’ transdiagnostic functioning. Taken together, we demonstrate that normative modelling of fMRI task-activation can be used to illustrate the influence of different task choices and map replicable individual differences, and we encourage its application to other neuroimaging tasks in future studies.
Enhancing shift current response via virtual multiband transitions
Authors: Chen Sihan , Chaudhary Swati , Refael Gil , Lewandowski Cyprian
Published: July 2024

Materials exhibiting a significant shift current response could potentially outperform conventional solar cell materials. The myriad of factors governing shift-current response, however, poses significant challenges in finding such strong shift-current materials. Here we propose a general design principle that exploits inter-orbital mixing to excite virtual multiband transitions in materials with multiple flat bands to achieve an enhanced shift current response. We further relate this design principle to maximizing Wannier function spread as expressed through the formalism of quantum geometry. We demonstrate the viability of our design using a 1D stacked Rice-Mele model. Furthermore, we consider a concrete material realization - alternating angle twisted multilayer graphene (TMG) - a natural platform to experimentally realize such an effect. We identify a set of twist angles at which the shift current response is maximized via virtual transitions for each multilayer graphene and highlight the importance of TMG as a promising material to achieve an enhanced shift current response at terahertz frequencies. Our proposed mechanism also applies to other 2D systems and can serve as a guiding principle for designing multiband systems that exhibit an enhanced shift current response.
Copper oxide coupled with photon upconversion for solar water splitting
Authors: Magazov Yerbolat , Kudryashov Vladislav , Moldabekov Kuanysh , Amze Magzhan , Nurmanova Aiisha , Aliyev Asset , Nuraje Nurxat
Published: July 2024

Photoelectrochemical water splitting is a promising solution for harnessing solar radiation for hydrogen production. Copper oxide semiconductors, particularly materials based on cuprous oxide, have attracted attention due to their abundant elemental availability and scalable synthesis methods. To improve the generated photocurrent of the photoelectrode system, photon upconversion materials can be implemented into water-splitting devices. Here, we demonstrate the potential application of triplet-triplet annihilation-based upconversion in solar-assisted water splitting and highlight the significance of photonic designs to improve the light-harnessing properties of photoactive materials. The triplet-triplet annihilation mechanism is particularly suitable due to its efficient conversion at low photon intensity, namely under 1-sun illumination. Our results show that Cu2O coupled with an upconverter outperforms bare Cu2O by 56% in terms of produced photocurrent density. We construct a hybrid water-splitting device with an extended absorption range by utilizing a semi-transparent 600 nm Cu2O film with a 5 nm Au underlayer.
Efficient separation of large particles and giant cancer cells using an isosceles trapezoidal spiral microchannel
Authors: Park Chanyong , Lim Wanyoung , Song Ryungeun , Han Jeonghun , You Daeun , Kim Sangmin , Lee Jeong Eon , van Noort Danny , Mandenius Carl-Fredrik , Lee Jinkee , Hyun Kyung-A. , Jung Hyo-Il , Park Sungsu
Published: July 2024

Polyploid giant cancer cells (PGCCs) contribute to the genetic heterogeneity and evolutionary dynamics of tumors.
Molecular islands at the liquid–solid interface
Authors: Hu Yi , Tahara Kazukuni , De Feyter Steven
Published: July 2024

Scanning tunneling microscopy reveals molecular islands at the liquid–solid interface.
A visible-light regulated luminescent switch based on a spiropyran-derived Pt(ii) complex for advanced anti-counterfeiting materials
Authors: Lei Xin , Jiang Ying , Zeng Qingguo , Dou Yuncan , Zhang Haokun , Ni Jiatao , Zhuo Yinuo , Wang Wei , Ai Yeye , Li Yongguang
Published: July 2024

A photo-controlled optical molecular switch has been achieved. Apparent and emissive color changes under visible light irradiation and temperature stimulation have been achieved and used to develop anti-counterfeiting materials.
Growth and anisotropic optoelectronic properties of a two-inch CsPbBr3 crystal by the vertical Bridgman method
Authors: Wu Shufan , Gong Zheng , Qian Lu , Yan Xinlong , Pan Jianguo , Yang Fan , Pan Shangke , Zheng Yanqing
Published: July 2024

A high-quality CsPbBr3 crystal of Φ 50 mm × 80 mm with uniform and crack-free appearance was successfully grown by the vertical Bridgman method, and the anisotropic optoelectronic properties of the crystals were studied.
The smallest triple-ring tubular gold clusters M2@Au15 with M = Mo, W: stability, electronic properties and nonlinear optical response
Authors: Trang Nguyen Thi Bao , Dang Minh Triet , Si Nguyen Thanh , Thao Tran Thi Ngoc , Thao Pham Thi Bich , Nguyen Minh Tho , Nhat Pham Vu
Published: July 2024

Formation of (M2@Au15)2 dimers from M2@Au15 monomers.
Spurious proton transfer in hydrogen bonded dimers
Authors: Bautista-Renedo Joanatan , Ireta Joel
Published: July 2024

A proton transfer is eased if the monomer covalent bonds are predicted to be too long in hydrogen bonded systems.