bluuebunny/crossref_metadata_2025 huggingface dataset:
Changes in Late Pleistocene Dust Activity in the Southern Tibetan Plateau in Response to Orbital Precession and Mountain Glaciers
Authors: Cheng Liangqing , Long Hao , Zhang Zhi , Zhang Jingran , Chen Zhong , Song Yougui , Wu Yubin , Luobu Pingcuo , Yang Linhai , Dong Zhibao
Published: June 2024

The Tibetan Plateau (TP) serves not only as the “water tower” of Asia but also as an important source in the global atmospheric dust cycle. While our knowledge of modern dust activity and its impacts and interactions with climate change in the TP has greatly advanced in the past decades, the emission, transport, and deposition of dust on the geological time scale remains unclear. This study analyzed a 7.6‐m thick sedimentary sequence consisting of loess and sand from the Yarlung Tsangpo River (YTR) valley in the southern TP. The sequence chronology was established using nineteen K‐feldspar post‐infrared infrared stimulated luminescence (pIRIR) ages, which ranged from 47.11 ± 1.95 to 116.65 ± 5.55 ka in a general stratigraphical order. The dust sedimentation rate and sorting coefficient of grain size were used to reflect dust activity and near‐surface wind, respectively. The results indicated that dust activity in the southern TP is mainly regulated by the near‐surface wind intensity and follows the variation pattern of precession, although the waxing and waning of mountain glaciers also affect the amplitude of dust activity. This pattern is not consistent with the Greenland dust record, which follows the variation pattern of obliquity. Therefore, dust accumulation in the southern TP is concluded to be primarily controlled by the South Asian winter monsoon (SAWM) forced by precession, whereas dust accumulation in Greenland is closely related to the intensity of the high‐level westerlies forced by obliquity.
The Representation of Convectively Coupled Kelvin Waves in Simulations With Modified Wave Amplitudes
Authors: Lawton Q. A. , Rios‐Berrios R. , Majumdar S. J. , Emerton R. , Magnusson L.
Published: June 2024

Convectively coupled Kelvin waves (CCKWs) are important drivers of tropical weather and may influence extreme rainfall and tropical cyclone formation. However, directly attributing these impacts to CCKWs remains a challenge. Numerical models also struggle to simulate the convective coupling of CCKWs. To address these gaps in understanding, this study examines a set of global simulations in which CCKW amplitudes are modified in the initial conditions. The Model for Prediction Across Scales –Atmosphere is used to simulate a time period in which several CCKWs coexisted around the globe, including an unusually strong CCKW located over the Atlantic. Prior to running the simulation, Kelvin‐filtered fields are identified in initial conditions and used to either amplify or dampen the initial wave amplitude. This method is effective at robustly changing the strength and structure of simulated CCKWs and can illuminate their convective coupling. Rainfall intensity within simulated CCKWs is shown to be partially controlled by column saturation fraction and deep convective inhibition. Despite the accurate depiction of most CCKWs during this time period, however, these experiments fail to simulate convective coupling in the strong Atlantic CCKW. This is true even after amplifying this wave at initialization. The cause of this failure is unclear and motivates additional work into the modeling and predictability of CCKW events. Overall, this study demonstrates that modifying CCKW amplitudes can serve as a useful tool for understanding CCKWs. This method may also be useful for future attributional work on the influence of CCKWs on other phenomena.
The Moana Project Braids Tradition and Science for a More Sustainable Ocean
Authors: de Souza Jo�o , Jakoboski Julie , Gardner Jonathan , Hudson Maui , Felsing Malene
Published: June 2024

Scientists and Māori communities in Aotearoa New Zealand are gathering knowledge on marine conditions and ecosystems to protect livelihoods and help ensure a sustainable future for the blue economy.
Influence of Farallon Slab Loading on Intraplate Stress and Seismicity in Eastern North America in the Presence of Pre‐Existing Weak Zones
Authors: Hightower Erin , Gurnis Michael , Mao Wei
Published: June 2024

Despite the stability of the continental interior, eastern North America has hosted many significant historical earthquakes. Seismicity concentrates within tectonically inherited structures, which can act as weak zones where stress accumulates. Within these zones, systematic stress rotations may be explained by long‐wavelength sources. We test the hypothesis that mantle‐flow driven by the Farallon slab contributes to intraplate seismicity via the reactivation of pre‐existing faults. We model the stress field using seismically constrained global high‐resolution finite‐element flow models with CitcomS. To isolate the slab's effect, we vary its buoyancy between a case of neutrality and a case with full negative thermal buoyancy derived from tomography. Low‐viscosity lithospheric weak zones located at failed rifts, loaded by a mass anomaly at depth, transmit elevated stresses to the overlying crust. The sinking of the Farallon slab drives localized mantle flow beneath the central‐eastern US, generating a large stress amplification of 100–150 MPa peaking over the New Madrid Seismic Zone (NMSZ). This stress amplification exerts a continent‐wide clockwise rotation on the stress field, which in the presence of weak zones reproduces some observed deviations of the seismically inferred SHmax from the regional borehole SHmax, bringing optimally oriented faults, closer to failure, some of which are associated with major historical earthquakes, including the Reelfoot Fault in the NMSZ and the Timiskaming Fault in Western Quebec. However, stronger lithospheric viscosity gradients, shallower weak zones, or weaker faults are still needed to fully reproduce the observed stress field in some areas.
Multi‐Year Potential Predictability of the Wintertime Heavy Precipitation Potentials in East Asia
Authors: Mochizuki Takashi
Published: June 2024

We validate the multiyear potential predictability of wintertime heavy precipitation potential in East Asia by combining initialized decadal hindcasts of the global climate model and large ensemble simulations from a high‐resolution global atmospheric model. By analyzing a set of initialized hindcasts, the major predictive components of sea surface temperature (SST) variability beyond interannual timescales are identified as high‐latitudes multidecadal variability and the so‐called trans‐basin variability (TBV). A set of 100 ensemble simulations using a high‐resolution atmospheric model showed a significantly large signal‐to‐noise ratio for the wintertime heavy precipitation potential in East Asia, which is closely related to the TBV. When the SST around the maritime continent is higher, the anomalously low pressure in the northwestern Pacific enhances low‐level cold air transport due to the winter monsoon. Consequently, the resultant weaker baroclinicity in the lower atmosphere reduces storm activity and wintertime heavy precipitation potential in East Asia.
Modeling the Impacts of Volatile Chemical Product Emissions on Atmospheric Photochemistry and Ozone Formation in Los Angeles
Authors: Chen Tianshu , Gilman Jessica , Kim Si‐Wan , Lefer Barry , Washenfelder Rebecca , Young Cora J. , Rappenglueck Bernhard , Stevens Philip S. , Veres Patrick R. , Xue Likun , de Gouw Joost
Published: June 2024

The dominant fraction of anthropogenic volatile organic compound (VOC) emissions shifted from transportation fuels to volatile chemical products (VCP) in Los Angeles (LA) in 2010. This shift in VOC composition raises the question about the importance of VCP emissions for ozone (O3) formation. In this study, O3 chemistry during the CalNex 2010 was modeled using the Master Chemical Mechanism (MCM) version 3.3.1 and a detailed representation of VCP emissions based on measurements combined with inventory estimates. The model calculations indicate that VCP emissions contributed to 23% of the mean daily maximum 8‐hr average O3 (DMA8 O3) during the O3 episodes. The simulated OH reactivity, including the contribution from VCP emissions, aligns with observations. Additionally, this framework was employed using four lumped mechanisms with simplified representations of emissions and chemistry. RACM2‐VCP showed the closest agreement with MCM, with a slight 4% increase in average DMA8 O3 (65 ± 13 ppb), whereas RACM2 (58 ± 13 ppb) and SAPRC07B (59 ± 14 ppb) exhibited slightly lower levels. CB6r2, however, recorded reduced concentrations (37 ± 10 ppb). Although emissions of O3 precursors have declined in LA since 2010, O3 levels have not decreased significantly. Model results ascribed this trend to the rapid reduction in NOX emissions. Moreover, given the impact of COVID‐19, an analysis of 2020 reveals a shift to a NOX‐limited O3 formation regime in LA, thereby diminishing the influence of VCPs. This study provides new insights into the impact of VCP emissions on O3 pollution from an in‐depth photochemical perspective.
Synoptic Variability in the Tropical Oceanic Moist Margin
Authors: Robinson C. M. , Narsey S. , Jakob C.
Published: June 2024

Recent research has described a ‘moist margin’ in the tropics, defined through a total column water vapor (TCWV) value of 48 kg m−2, that encloses most of the rainfall over the tropical oceans. Diagnosing the moist margin in the ERA5 reanalysis reveals that it varies particularly on synoptic time scales, which this study aims to quantify. We define ‘wet and dry perturbation’ objects based on the margin's movement relative to its seasonal climatology. These perturbations are associated with a variety of synoptic weather systems. Wet (dry) perturbations produce substantially more (less) rainfall compared to the seasonal average, confirming the clear link between moisture and precipitation. On synoptic scales we suggest that mid‐tropospheric humidity plays a key role in creating these perturbations, while sea surface temperatures (SSTs) are relatively unimportant.
Obesity, psychological well-being related measures, and risk of seven non-communicable diseases: evidence from longitudinal studies of UK and US older adults
Authors: Putra I Gusti Ngurah Edi , Daly Michael , Sutin Angelina , Steptoe Andrew , Scholes Shaun , Robinson Eric
Published: June 2024

Background

We examined the role of psychological well-being related measures in explaining the associations between obesity and increased risk of non-communicable diseases (NCDs: hypertension, heart disease, stroke, diabetes, arthritis, cancer, and memory-related disease) in older adults.

Methods

Data were from the English Longitudinal Study of Ageing (ELSA), UK (baseline: Wave 4—2008/2009; n = 8127) and the Health and Retirement Study (HRS), US (baseline: Waves 9 and 10—2008/2010; n = 12,477). Objective body mass index was used to define obesity. A range of psychological well-being related measures (e.g., depressive symptoms, life satisfaction) was available in ELSA (n = 7) and HRS (n = 15), and an index of overall psychological well-being was developed separately in each study. NCDs were from a self-reported doctor diagnosis and/or other assessments (e.g., biomarker data) in both studies; and in ELSA, NCDs from linked hospital admissions data were examined. Longitudinal associations between obesity status, psychological well-being measures, and NCDs were examined using Cox proportional hazard models (individual NCDs) and Poisson regression (a cumulative number of NCDs). Mediation by psychological well-being related measures was assessed using causal mediation analysis.

Results

Obesity was consistently associated with an increased prospective risk of hypertension, heart disease, diabetes, arthritis, and a cumulative number of NCDs in both ELSA and HRS. Worse overall psychological well-being (index measure) and some individual psychological well-being related measures were associated with an increased prospective risk of heart disease, stroke, arthritis, memory-related disease, and a cumulative number of NCDs across studies. Findings from mediation analyses showed that neither the index of overall psychological well-being nor any individual psychological well-being related measures explained (mediated) why obesity increased the risk of developing NCDs in both studies.

Conclusion

Obesity and psychological well-being may independently and additively increase the risk of developing NCDs.
Relationships between minerals’ intake and blood homocysteine levels based on three machine learning methods: a large cross-sectional study
Authors: Fan Jing , Liu Shaojie , Wei Lanxin , Zhao Qi , Zhao Genming , Dong Ruihua , Chen Bo
Published: June 2024

Background

Blood homocysteine (Hcy) level has become a sensitive indicator in predicting the development of cardiovascular disease. Studies have shown an association between individual mineral intake and blood Hcy levels. The effect of mixed minerals’ intake on blood Hcy levels is unknown.

Methods

Data were obtained from the baseline survey data of the Shanghai Suburban Adult Cohort and Biobank(SSACB) in 2016. A total of 38273 participants aged 20–74 years met our inclusion and exclusion criteria. Food frequency questionnaire (FFQ) was used to calculate the intake of 10 minerals (calcium, potassium, magnesium, sodium, iron, zinc, selenium, phosphorus, copper and manganese). Measuring the concentration of Hcy in the morning fasting blood sample. Traditional regression models were used to assess the relationship between individual minerals’ intake and blood Hcy levels. Three machine learning models (WQS, Qg-comp, and BKMR) were used to the relationship between mixed minerals’ intake and blood Hcy levels, distinguishing the individual effects of each mineral and determining their respective weights in the joint effect.

Results

Traditional regression model showed that higher intake of calcium, phosphorus, potassium, magnesium, iron, zinc, copper, and manganese was associated with lower blood Hcy levels. Both Qg-comp and BKMR results consistently indicate that higher intake of mixed minerals is associated with lower blood Hcy levels. Calcium exhibits the highest weight in the joint effect in the WQS model. In Qg-comp, iron has the highest positive weight, while manganese has the highest negative weight. The BKMR results of the subsample after 10,000 iterations showed that except for sodium, all nine minerals had the high weights in the joint effect on the effect of blood Hcy levels.

Conclusion

Overall, higher mixed mineral’s intake was associated with lower blood Hcy levels, and each mineral contributed differently to the joint effect. Future studies are available to further explore the mechanisms underlying this association, and the potential impact of mixed minerals’ intake on other health indicators needs to be further investigated. These efforts will help provide additional insights to deepen our understanding of mixed minerals and their potential role in health maintenance.
Serum albumin and white matter hyperintensities
Authors: Zahr Natalie M. , Pfefferbaum Adolf
Published: June 2024

People living with HIV and those diagnosed with alcohol use disorders (AUD) relative to healthy individuals commonly have low levels of serum albumin, substantiated as an independent predictor of cardiovascular events. White matter hyperintensities (WMH)—a neuroimaging feature of cerebral small vessel disease—are also related to cardiovascular disease. Despite consensus regarding associations between high levels of urine albumin and WMH prevalence, and low serum albumin levels and impaired cognitive functioning, relations between serum albumin and WMH burdens have rarely been evaluated. Here, a sample including 160 individuals with AUD, 142 living with HIV, and 102 healthy controls was used to test the hypothesis that serum albumin would be inversely related to WMH volumes and directly related to cognitive performance in the two diagnostic groups. Although serum albumin and periventricular WMH volumes showed an inverse relationship in both AUD and HIV groups, this relationship persisted only in the HIV group after consideration of traditional cardiovascular (i.e., age, sex, body mass index (BMI), nicotine use, hypertension, diabetes), study-relevant (i.e., race, socioeconomic status, hepatitis C virus status), and disease-specific (i.e., CD4 nadir, HIV viral load, HIV duration) factors. Further, serum albumin contributed more significantly than periventricular WMH volume to variance in performance on a verbal learning and memory composite score in the HIV group only. Relations in both HIV and AUD groups between albumin and hematological red blood cell markers (e.g., hemoglobin, hematocrit) suggest that in this sample, serum albumin reflects hematological abnormalities. Albumin, a simple serum biomarker available in most clinical settings, may therefore help identify periventricular WMH burden and performance levels in specific cognitive domains in people living with HIV. Whether serum albumin contributes mechanistically to periventricular WMH in HIV will require additional investigation.
Inflammation and immune system pathways as biological signatures of adolescent depression—the IDEA-RiSCo study
Authors: Zonca Valentina , Marizzoni Moira , Saleri Samantha , Zajkowska Zuzanna , Manfro Pedro H. , Souza Laila , Viduani Anna , Sforzini Luca , Swartz Johnna R. , Fisher Helen L. , Kohrt Brandon A. , Kieling Christian , Riva Marco Andrea , Cattaneo Annamaria , Mondelli Valeria
Published: June 2024

The biological mechanisms underlying the onset of major depressive disorder (MDD) have predominantly been studied in adult populations from high-income countries, despite the onset of depression typically occurring in adolescence and the majority of the world’s adolescents living in low- and middle-income countries (LMIC). Taking advantage of a unique adolescent sample in an LMIC (Brazil), this study aimed to identify biological pathways characterizing the presence and increased risk of depression in adolescence, and sex-specific differences in such biological signatures. We collected blood samples from a risk-stratified cohort of 150 Brazilian adolescents (aged 14–16 years old) comprising 50 adolescents with MDD, 50 adolescents at high risk of developing MDD but without current MDD, and 50 adolescents at low risk of developing MDD and without MDD (25 females and 25 males in each group). We conducted RNA-Seq and pathway analysis on whole blood. Inflammatory-related biological pathways, such as role of hypercytokinemia/hyperchemokinemia in the pathogenesis of influenza (z-score = 3.464, p < 0.001), interferon signaling (z-score = 2.464, p < 0.001), interferon alpha/beta signaling (z-score = 3.873, p < 0.001), and complement signaling (z-score = 2, p = 0.002) were upregulated in adolescents with MDD compared with adolescents without MDD independently from their level of risk. The up-regulation of such inflammation-related pathways was observed in females but not in males. Inflammatory-related pathways involved in the production of cytokines and in interferon and complement signaling were identified as key indicators of adolescent depression, and this effect was present only in females.
Mechanism and role of nuclear laminin B1 in cell senescence and malignant tumors
Authors: Lv Tingcong , Wang Cong , Zhou Jialin , Feng Xiao , Zhang Lijun , Fan Zhe
Published: June 2024

Nuclear lamin B1 (LMNB1) is a member of the nuclear lamin protein family. LMNB1 can maintain and ensure the stability of nuclear structure and influence the process of cell senescence by regulating chromatin distribution, DNA replication and transcription, gene expression, cell cycle, etc. In recent years, several studies have shown that the abnormal expression of LMNB1, a classical biomarker of cell senescence, is highly correlated with the progression of various malignant tumors; LMNB1 is therefore considered a new potential tumor marker and therapeutic target. However, the mechanism of action of LMNB1 is influenced by many factors, which are difficult to clarify at present. This article focuses on the recent progress in understanding the role of LMNB1 in cell senescence and malignant tumors and offers insights that could contribute to elucidating the mechanism of action of LMNB1 to provide a new direction for further research.
Benign splenic lesions in BAP1-tumor predisposition syndrome: a case series
Authors: Miranda Joao , Dave Priya , Kemel Yelena , Sheikh Rania , Zong Grace , Calderon Lina Posada , Will Marie , Liu Ying L. , Walsh Michael , Stadler Zsofia K. , Offit Kenneth , Latham Alicia , Mandelker Diana , Chen Ying-Bei , Andrieu Pamela Causa , Carlo Maria Isabel
Published: June 2024

BAP1-Tumor Predisposition Syndrome (TPDS) is caused by germline variants in BAP1 and predisposes to solid tumors. After observation of a radiologically malignant-appearing splenic mass with benign pathology in a patient with BAP1-TPDS, we sought to retrospectively characterize splenic lesions in individuals with BAP1-TPDS seen at a comprehensive cancer center. A dedicated radiology review for splenic abnormalities was performed. We identified 37 individuals with BAP1-TPDS, 81% with a history of cancer. Of 33 individuals with abdominal imaging, 10 (30%) had splenic lesions, and none were shown to be malignant on follow-up. Splenectomy in an individual with suspected splenic angiosarcoma showed a benign vascular neoplasm with loss of nuclear staining for BAP1 in a subset of cells. Benign splenic lesions appear to be common and potentially BAP1-driven in individuals with BAP1-TPDS; confirmation of these findings could lead to more conservative management and avoidance of splenectomy.
A 3D ray traced biological neural network learning model
Authors: Yuen Brosnan , Dong Xiaodai , Lu Tao
Published: June 2024

Training large neural networks on big datasets requires significant computational resources and time. Transfer learning reduces training time by pre-training a base model on one dataset and transferring the knowledge to a new model for another dataset. However, current choices of transfer learning algorithms are limited because the transferred models always have to adhere to the dimensions of the base model and can not easily modify the neural architecture to solve other datasets. On the other hand, biological neural networks (BNNs) are adept at rearranging themselves to tackle completely different problems using transfer learning. Taking advantage of BNNs, we design a dynamic neural network that is transferable to any other network architecture and can accommodate many datasets. Our approach uses raytracing to connect neurons in a three-dimensional space, allowing the network to grow into any shape or size. In the Alcala dataset, our transfer learning algorithm trains the fastest across changing environments and input sizes. In addition, we show that our algorithm also outperformance the state of the art in EEG dataset. In the future, this network may be considered for implementation on real biological neural networks to decrease power consumption.
Concentrated solar CO2 reduction in H2O vapour with >1% energy conversion efficiency
Authors: Ren Yuqi , Fu Yiwei , Li Naixu , You Changjun , Huang Jie , Huang Kai , Sun Zhenkun , Zhou Jiancheng , Si Yitao , Zhu Yuanhao , Chen Wenshuai , Duan Lunbo , Liu Maochang
Published: June 2024

H2O dissociation plays a crucial role in solar-driven catalytic CO2 methanation, demanding high temperature even for solar-to-chemical conversion efficiencies <1% with modest product selectivity. Herein, we report an oxygen-vacancy (Vo) rich CeO2 catalyst with single-atom Ni anchored around its surface Vo sites by replacing Ce atoms to promote H2O dissociation and achieve effective photothermal CO2 reduction under concentrated light irradiation. The high photon flux reduces the apparent activation energy for CH4 production and prevents Vo from depletion. The defects coordinated with single-atom Ni, significantly promote the capture of charges and local phonons at the Ni d-impurity orbitals, thereby inducing more effective H2O activation. The catalyst presents a CH4 yield of 192.75 µmol/cm2/h, with a solar-to-chemical efficiency of 1.14% and a selectivity ~100%. The mechanistic insights uncovered in this study should help further the development of H2O-activating catalysts for CO2 reduction and thereby expedite the practical utilization of solar-to-chemical technologies.
NIR-II emissive anionic copper nanoclusters with intrinsic photoredox activity in single-electron transfer
Authors: Liu Li-Juan , Zhang Mao-Mao , Deng Ziqi , Yan Liang-Liang , Lin Yang , Phillips David Lee , Yam Vivian Wing-Wah , He Jian
Published: June 2024

Ultrasmall copper nanoclusters have recently emerged as promising photocatalysts for organic synthesis, owing to their exceptional light absorption ability and large surface areas for efficient interactions with substrates. Despite significant advances in cluster-based visible-light photocatalysis, the types of organic transformations that copper nanoclusters can catalyze remain limited to date. Herein, we report a structurally well-defined anionic Cu40 nanocluster that emits in the second near-infrared region (NIR-II, 1000−1700 nm) after photoexcitation and can conduct single-electron transfer with fluoroalkyl iodides without the need for external ligand activation. This photoredox-active copper nanocluster efficiently catalyzes the three-component radical couplings of alkenes, fluoroalkyl iodides, and trimethylsilyl cyanide under blue-LED irradiation at room temperature. A variety of fluorine-containing electrophiles and a cyanide nucleophile can be added onto an array of alkenes, including styrenes and aliphatic olefins. Our current work demonstrates the viability of using readily accessible metal nanoclusters to establish photocatalytic systems with a high degree of practicality and reaction complexity.
Photochemically responsive polymer films enable tunable gliding flights
Authors: Yang Jianfeng , Shankar M. Ravi , Zeng Hao
Published: June 2024

Miniaturized passive fliers based on smart materials face challenges in precise control of shape-morphing for aerodynamics and contactless modulation of diverse gliding modes. Here, we present the optical control of gliding performances in azobenzene-crosslinked liquid crystal networks films through photochemical actuation, enabling reversible and bistable shape-morphing. First, an actuator film is integrated with additive constructs to form a rotating glider, inspired by the natural maple samara, surpassing natural counterparts in reversibly optical tuning of terminal velocity, rotational rate, and circling position. We demonstrate optical modulation dispersion of landing points for the photo-responsive microfliers indoors and outdoors. Secondly, we show the scalability of polymer film geometry for miniature gliders with similar light tunability. Thirdly, we extend the material platform to other three gliding modes: Javan cucumber seed-like glider, parachute and artificial dandelion seed. The findings pave the way for distributed microflier with contactless flight dynamics control.
Development and deployment of a histopathology-based deep learning algorithm for patient prescreening in a clinical trial
Authors: Juan Ramon Albert , Parmar Chaitanya , Carrasco-Zevallos Oscar M. , Csiszer Carlos , Yip Stephen S. F. , Raciti Patricia , Stone Nicole L. , Triantos Spyros , Quiroz Michelle M. , Crowley Patrick , Batavia Ashita S. , Greshock Joel , Mansi Tommaso , Standish Kristopher A.
Published: June 2024

Accurate identification of genetic alterations in tumors, such as Fibroblast Growth Factor Receptor, is crucial for treating with targeted therapies; however, molecular testing can delay patient care due to the time and tissue required. Successful development, validation, and deployment of an AI-based, biomarker-detection algorithm could reduce screening cost and accelerate patient recruitment. Here, we develop a deep-learning algorithm using >3000 H&E-stained whole slide images from patients with advanced urothelial cancers, optimized for high sensitivity to avoid ruling out trial-eligible patients. The algorithm is validated on a dataset of 350 patients, achieving an area under the curve of 0.75, specificity of 31.8% at 88.7% sensitivity, and projected 28.7% reduction in molecular testing. We successfully deploy the system in a non-interventional study comprising 89 global study clinical sites and demonstrate its potential to prioritize/deprioritize molecular testing resources and provide substantial cost savings in the drug development and clinical settings.
Socio-demographic and cross-country differences in attention to sustainable certifications and changes in food consumption
Authors: Mota-Gutierrez Jatziri , Sparacino Antonina , Merlino Valentina Maria , Blanc Simone , Brun Filippo , Massimelli Fabrizio , Vassallo Emanuela , Borra Danielle , Massaglia Stefano
Published: June 2024

Food labeling can influence, sometimes facilitate, changes in consumer diets to support environmental sustainability and in response to climate change. However, a significant impediment to this dietary shift may arise from the consumers’ tendency to underestimate the environmental impact of their food choices and from their limited knowledge about sustainable certifications. These aspects are influenced by the characteristics and geographical affiliations of individuals. In such a context, the aim of this research has been to identify the main factors that drive the food purchasing frequency and the changes in food consumption associated with consumers’ concerns about climate change and interest in sustainable food certifications by comparing different food products and countries (Italy, France, Germany, Denmark, the USA, and China). A cross-country survey was conducted on 6500 consumers of various food products. The obtained mean scores were then compared, using generalized linear mixed-effect models, to evaluate the associations between the consumers’ food purchasing frequency, the importance of sustainable certifications, and changes in food consumption due to climate change concerns. Much of the variation in food consumption, purchasing behaviors, and interest in sustainable certifications was found to depend on such factors as age, gender, and country of origin. Indeed, Chinese consumers exhibited a heightened interest in sustainable food certifications, yet their consumption scores for all food products overall were higher. Conversely, adult and elderly Danish consumers demonstrated a decrease in the consumption of cheeses, meat, fruits, and vegetables, and their interest scores in all sustainable food certifications were lower. Despite the challenges posed by various consumers’ interests and minimal changes in food consumption patterns, our findings suggest that sustainable certifications present a promising avenue for straightforward interventions to promote the adoption of sustainable diets and to address climate change.
Exploring the genetic prediction of academic underachievement and overachievement
Authors: Kawakami Kaito , Procopio Francesca , Rimfeld Kaili , Malanchini Margherita , von Stumm Sophie , Asbury Kathryn , Plomin Robert
Published: June 2024

Academic underachievement refers to school performance which falls below expectations. Focusing on the pivotal first stage of education, we explored a quantitative measure of underachievement using genomically predicted achievement delta (GPAΔ), which reflects the difference between observed and expected achievement predicted by genome-wide polygenic scores. We analyzed the relationship between GPAΔ at age 7 and achievement trajectories from ages 7 to 16, using longitudinal data from 4175 participants in the Twins Early Development Study to assess empirically the extent to which students regress to their genomically predicted levels by age 16. We found that the achievement of underachievers and overachievers who deviated from their genomic predictions at age 7 regressed on average by one-third towards their genomically predicted levels. We also found that GPAΔ at age 7 was as predictive of achievement trajectories as a traditional ability-based index of underachievement. Targeting GPAΔ underachievers might prove cost-effective because such interventions seem more likely to succeed by going with the genetic flow rather than swimming upstream, helping GPAΔ underachievers reach their genetic potential as predicted by their GPS. However, this is a hypothesis that needs to be tested in intervention research investigating whether GPAΔ underachievers respond better to the intervention than other underachievers. We discuss the practicality of genomic indices in assessing underachievement.
Inhibition of lysine acetyltransferase KAT6 in ER+HER2− metastatic breast cancer: a phase 1 trial
Authors: Mukohara Toru , Park Yeon Hee , Sommerhalder David , Yonemori Kan , Hamilton Erika , Kim Sung-Bae , Kim Jee Hyun , Iwata Hiroji , Yamashita Toshinari , Layman Rachel M. , Mita Monica , Clay Timothy , Chae Yee Soo , Oakman Catherine , Yan Fengting , Kim Gun Min , Im Seock-Ah , Lindeman Geoffrey J. , Rugo Hope S. , Liyanage Marlon , Saul Michelle , Le Corre Christophe , Skoura Athanasia , Liu Li , Li Meng , LoRusso Patricia M.
Published: June 2024

Inhibition of histone lysine acetyltransferases (KATs) KAT6A and KAT6B has shown antitumor activity in estrogen receptor-positive (ER+) breast cancer preclinical models. PF-07248144 is a selective catalytic inhibitor of KAT6A and KAT6B. In the present study, we report the safety, pharmacokinetics (PK), pharmacodynamics, efficacy and biomarker results from the first-in-human, phase 1 dose escalation and dose expansion study (n = 107) of PF-07248144 monotherapy and fulvestrant combination in heavily pretreated ER+ human epidermal growth factor receptor-negative (HER2−) metastatic breast cancer (mBC). The primary objectives of assessing the safety and tolerability and determining the recommended dose for expansion of PF-07248144, as monotherapy and in combination with fulvestrant, were met. Secondary endpoints included characterization of PK and evaluation of antitumor activity, including objective response rate (ORR) and progression-free survival (PFS). Common treatment-related adverse events (any grade; grades 3–4) included dysgeusia (83.2%, 0%), neutropenia (59.8%, 35.5%) and anemia (48.6%, 13.1%). Exposure was approximately dose proportional. Antitumor activity was observed as monotherapy. For the PF-07248144–fulvestrant combination (n = 43), the ORR (95% confidence interval (CI)) was 30.2% (95% CI = 17.2–46.1%) and the median PFS was 10.7 (5.3–not evaluable) months. PF-07248144 demonstrated a tolerable safety profile and durable antitumor activity in heavily pretreated ER+HER2− mBC. These findings establish KAT6A and KAT6B as druggable cancer targets, provide clinical proof of concept and reveal a potential avenue to treat mBC. clinicaltrial.gov registration: NCT04606446.
Pembrolizumab for advanced urothelial carcinoma: exploratory ctDNA biomarker analyses of the KEYNOTE-361 phase 3 trial
Authors: Powles Thomas , Chang Yen-Hwa , Yamamoto Yoshiaki , Munoz Jose , Reyes-Cosmelli Felipe , Peer Avivit , Cohen Graham , Yu Evan Y. , Lorch Anja , Bavle Abhishek , Homet Moreno Blanca , Markensohn Julia , Edmondson Mackenzie , Chen Cai , Cristescu Razvan , Peña Carol , Lunceford Jared , Gunduz Seyda
Published: June 2024

Circulating tumor DNA (ctDNA) is emerging as a potential biomarker in early-stage urothelial cancer, but its utility in metastatic disease remains unknown. In the phase 3 KEYNOTE-361 study, pembrolizumab with and without chemotherapy was compared with chemotherapy alone in patients with metastatic urothelial cancer. The study did not meet prespecified efficacy thresholds for statistical significance. To identify potential biomarkers of response, we retrospectively evaluated the association of pre- and posttreatment ctDNA with clinical outcomes in a subset of patients who received pembrolizumab (n = 130) or chemotherapy (n = 130) in KEYNOTE-361. Baseline ctDNA was associated with best overall response (BOR; P = 0.009), progression-free survival (P < 0.001) and overall survival (OS; P < 0.001) for pembrolizumab but not for chemotherapy (all; P > 0.05). Chemotherapy induced larger ctDNA decreases from baseline to treatment cycle 2 than pembrolizumab; however, change with pembrolizumab (n = 87) was more associated with BOR (P = 4.39 × 10−5) and OS (P = 7.07 × 10−5) than chemotherapy (n = 102; BOR: P = 1.01 × 10−4; OS: P = 0.018). Tumor tissue-informed versions of ctDNA change metrics were most associated with clinical outcomes but did not show a statistically significant independent value for explaining OS beyond radiographic change by RECIST v.1.1 when jointly modeled (pembrolizumab P = 0.364; chemotherapy P = 0.823). These results suggest distinct patterns in early ctDNA changes with immunotherapy and chemotherapy and differences in their association with long-term outcomes, which provide preliminary insights into the utility of liquid biopsies for treatment monitoring in metastatic urothelial cancer. Clinical trial registration: NCT02853305.
Neonatal mortality rate and determinants among births of mothers at extreme ages of reproductive life in low and middle income countries
Authors: Tamir Tadesse Tarik
Published: June 2024

Neonatal mortality, which refers to the death of neonates during the first 28 completed days of life, is a critical global public health concern. The neonatal period is widely recognized as one of the most precarious phases in human life. Research has indicated that maternal extreme ages during reproductive years significantly impact neonatal survival, particularly in low- and middle-income countries. Consequently, this study aims to evaluate the neonatal mortality rate and determinants among neonates born to mothers at extreme reproductive ages within these countries. A secondary analysis of demographic and health surveys conducted between 2015 and 2022 in 43 low- and middle-income countries was performed. The study included a total sample of 151,685 live births. Researchers utilized a multilevel mixed-effects model to identify determinants of neonatal mortality. The measures of association were evaluated using the adjusted odds ratio within a 95% confidence interval. The neonatal mortality rate among neonates born to mothers at extreme ages of reproductive life in low- and middle-income countries was 28.96 neonatal deaths per 1000 live births (95% CI 28.13–29.82). Factors associated with higher rates of neonatal mortality include male gender, low and high birth weight, maternal education (no or low), home deliveries, multiple births, short preceding birth intervals, lack of postnatal checkups, and countries with high fertility and low literacy rates. This study sheds light on the neonatal mortality rates among neonates born to mothers at extreme ages of reproductive life in low- and middle-income countries. Notably, we found that neonatal mortality was significantly higher in this group compared to neonatal mortality rates reported regardless of maternal ages. Male babies, low and high birth-weighted babies, those born to mothers with no or low education, delivered at home, singletons, babies born with a small preceding birth interval, and those without postnatal checkups faced elevated risks of neonatal mortality. Additionally, neonates born in countries with high fertility and low literacy rates were also vulnerable. These findings underscore the urgent need for targeted interventions tailored to mothers at extreme ages. Policymakers and healthcare providers should prioritize strategies that address specific risk factors prevalent in these vulnerable populations. By doing so, we can improve neonatal outcomes and ensure the survival of these newborns during the critical neonatal period.
Robust memory of face moral values is encoded in the human caudate tail: a simultaneous EEG-fMRI study
Authors: Ataei Ali , Amini Arash , Ghazizadeh Ali
Published: June 2024

Moral judgements about people based on their actions is a key component that guides social decision making. It is currently unknown how positive or negative moral judgments associated with a person’s face are processed and stored in the brain for a long time. Here, we investigate the long-term memory of moral values associated with human faces using simultaneous EEG-fMRI data acquisition. Results show that only a few exposures to morally charged stories of people are enough to form long-term memories a day later for a relatively large number of new faces. Event related potentials (ERPs) showed a significant differentiation of remembered good vs bad faces over centerofrontal electrode sites (value ERP). EEG-informed fMRI analysis revealed a subcortical cluster centered on the left caudate tail (CDt) as a correlate of the face value ERP. Importantly neither this analysis nor a conventional whole-brain analysis revealed any significant coding of face values in cortical areas, in particular the fusiform face area (FFA). Conversely an fMRI-informed EEG source localization using accurate subject-specific EEG head models also revealed activation in the left caudate tail. Nevertheless, the detected caudate tail region was found to be functionally connected to the FFA, suggesting FFA to be the source of face-specific information to CDt. A further psycho-physiological interaction analysis also revealed task-dependent coupling between CDt and dorsomedial prefrontal cortex (dmPFC), a region previously identified as retaining emotional working memories. These results identify CDt as a main site for encoding the long-term value memories of faces in humans suggesting that moral value of faces activates the same subcortical basal ganglia circuitry involved in processing reward value memory for objects in primates.
Enhancing ecological uncertainty predictions in pollution control games through dynamic Bayesian updating
Authors: Zhou Jiangjing , Petrosian Ovanes , Gao Hongwei
Published: June 2024

This study presents a dynamic Bayesian game model designed to improve predictions of ecological uncertainties leading to natural disasters. It incorporates historical signal data on ecological indicators. Participants, acting as decision-makers, receive signals about an unknown parameter-observations of a random variable’s realization values before a specific time, offering insights into ecological uncertainties. The essence of the model lies in its dynamic Bayesian updating, where beliefs about unknown parameters are refined with each new signal, enhancing predictive accuracy. The main focus of our paper is to theoretically validate this approach, by presenting a number of theorems that prove its precision and efficiency in improving uncertainty estimations. Simulation results validate the model’s effectiveness in various scenarios, highlighting its role in refining natural disaster forecasts.
Establishing a 4D-CT lung function related volumetric dose model to reduce radiation pneumonia
Authors: Liu Chunmei , Liu Huizhi , Li Yange , Xiao Zhiqing , Wang Yanqiang , Guo Han , Luo Jianmin
Published: June 2024

In order to study how to use pulmonary functional imaging obtained through 4D-CT fusion for radiotherapy planning, and transform traditional dose volume parameters into functional dose volume parameters, a functional dose volume parameter model that may reduce level 2 and above radiation pneumonia was obtained. 41 pulmonary tumor patients who underwent 4D-CT in our department from 2020 to 2023 were included. MIM Software (MIM 7.0.7; MIM Software Inc., Cleveland, OH, USA) was used to register adjacent phase CT images in the 4D-CT series. The three-dimensional displacement vector of CT pixels was obtained when changing from one respiratory state to another respiratory state, and this three-dimensional vector was quantitatively analyzed. Thus, a color schematic diagram reflecting the degree of changes in lung CT pixels during the breathing process, namely the distribution of ventilation function strength, is obtained. Finally, this diagram is fused with the localization CT image. Select areas with Jacobi > 1.2 as high lung function areas and outline them as fLung. Import the patient's DVH image again, fuse the lung ventilation image with the localization CT image, and obtain the volume of fLung different doses (V60, V55, V50, V45, V40, V35, V30, V25, V20, V15, V10, V5). Analyze the functional dose volume parameters related to the risk of level 2 and above radiation pneumonia using R language and create a predictive model. By using stepwise regression and optimal subset method to screen for independent variables V35, V30, V25, V20, V15, and V10, the prediction formula was obtained as follows: Risk = 0.23656–0.13784 * V35 + 0.37445 * V30-0.38317 * V25 + 0.21341 * V20-0.10209 * V15 + 0.03815 * V10. These six independent variables were analyzed using a column chart, and a calibration curve was drawn using the calibrate function. It was found that the Bias corrected line and the Apparent line were very close to the Ideal line, The consistency between the predicted value and the actual value is very good. By using the ROC function to plot the ROC curve and calculating the area under the curve: 0.8475, 95% CI 0.7237–0.9713, it can also be determined that the accuracy of the model is very high. In addition, we also used Lasso method and random forest method to filter out independent variables with different results, but the calibration curve drawn by the calibration function confirmed poor prediction performance. The function dose volume parameters V35, V30, V25, V20, V15, and V10 obtained through 4D-CT are key factors affecting radiation pneumonia. Establishing a predictive model can provide more accurate lung restriction basis for clinical radiotherapy planning.
A comparative study of brine solutions as completion fluids for oil and gas fields
Authors: Kazemihokmabad Parsa , Khamehchi Ehsan , Mahdavi Kalatehno Javad , Ebadi Reza
Published: June 2024

Completion fluids play a vital role in well-related processes within the oil extraction industry. This article presents a comprehensive study of the properties and performance of various brine solutions as completion fluids for different well and reservoir conditions. Attributes examined include density, corrosion resistance, temperature stability, compatibility with formation fluids, clay swelling potential and influence on wettability. The research highlights the significance of selecting appropriate completion fluids to optimize well and reservoir operations. Zinc chloride emerges as an excellent option for high density applications, while sodium chloride and potassium formate solutions are ideal for extreme cold conditions. Potassium acetate outperforms calcium chloride and potassium chloride and has excellent pH stability. The compatibility of completion fluids with formation water has been observed to be excellent, with no sedimentation or emulsion formation. Potassium acetate also experiences minimal clay swelling, making it suitable for clay-rich formations. On the other hand, calcium chloride has a higher clay swelling than most of the brines tested, making it less suitable for sandstone formations with a higher clay content than these brines. The research evaluates the water-wetting abilities of completion fluids in carbonate and sandstone formations. Potassium chloride and zinc chloride have the most significant impact in carbonate formations, while potassium acetate and potassium formate excel in sandstone formations. This study provides a comprehensive understanding of completion fluids, facilitating informed decisions that maximize operational efficiency, protect reservoir integrity, and enhance hydrocarbon recovery. The appropriate selection of completion fluids should align with specific well and reservoir conditions, considering the priorities of the application.