bluuebunny/crossref_metadata_2025_split huggingface dataset:
TopEC: Improved classification of enzyme function by a localized 3D protein descriptor and 3D Graph Neural Networks
Authors: van der Weg Karel , Merdivan Erinc , Piraud Marie , Gohlke Holger 
Published: February 2024

AbstractAccurately annotating molecular function to enzymes remains challenging. Computational methods can aid in this and allow for high-throughput annotation. Tools available for inferring enzyme function from general sequence, fold, or evolutionary information are generally successful. However, they can lead to misclassification if for certain sequences a deviation in local structural features influences the function. Here, we present TopEC, a 3D graph neural network based on a localized 3D descriptor to learn chemical reactions of enzymes from (predicted) enzyme structures and predict Enzyme Commission (EC) classes. Using the message passing frameworks from SchNet and DimeNet++, we include distance and angle information to improve the predictive performance compared to regular 2D graph neural networks. We obtained significantly improved EC classification prediction (F-score: 0.72) without fold bias at residue and atomic resolutions and trained networks that can classify both experimental and computationally generated enzyme structures for a vast functional space (> 800 ECs). Our model is robust to uncertainties in binding site locations and similar functions in distinct binding sites. By investigating the importance of each graph node to the predictive performance, we see that TopEC networks learn from an interplay between biochemical features and local shape-dependent features.
Dynamic formation of a posterior-to-anterior peak-alpha-frequency gradient driven by two distinct processes
Authors: Smith Max Kailler , Grabowekcy Marcia , Suzuki Satoru 
Published: February 2024

AbstractPeak-alpha frequency varies across individuals and mental states, but it also forms a negative gradient from posterior to anterior regions in association with increases in cortical thickness and connectivity reflecting the cortical hierarchy in temporal integration. Tracking the spatial standard deviation of peak-alpha frequency in scalp EEG, we observed that the posterior-to-anterior gradient dynamically formed and dissolved. Periods of high spatial standard deviation yielded robustly negative posterior-to-anterior gradients—the gradient state—while periods of low spatial standard deviation yielded globally converged peak-alpha frequency—the uniform state. Our analyses suggest that the fluctuations between the gradient and uniform states are associated with two separate variables: (1) coordinated variations in peak-alpha frequency in anterior regions and (2) coordinated variations in peak-alpha power in central regions driven by posterior regions. These variables each accounted for ∼25% of the state fluctuations, were uncorrelated with each other, and together accounted for ∼50% of the state fluctuations. These results reflect general mechanisms as they replicated while participants engaged in a variety of behavioral tasks with their eyes closed (breath focus, vigilance, working memory, mental arithmetic, and generative thinking). Overall, our results suggest that the spatial pattern of peak-alpha frequency dynamically fluctuates between the gradient state, potentially facilitating information influx and temporal integration toward anterior regions, and the uniform state, potentially facilitating global communication, with the state fluctuations controlled by at least two distinct mechanisms, an anterior mechanism that directly adjusts peak-alpha frequencies and a posterior mechanism that indirectly adjusts them by influencing synchronization.
Notch controls early temporal factor expression to control timing of Mushroom body neuroblast apoptosis
Authors: Branham Kendall R. , Sood Chhavi , Doyle Susan E. , Pahl Matt C. , Siegrist Sarah E. 
Published: February 2024

AbstractThe neurogenic period, where neural stem cells (NSCs) proliferate to produce molecularly distinct progeny in the developing brain, is a critical time of growth in many organisms. Proper brain development is crucial for survival and requires strict regulation of NSC divisions along a set developmental timeline. InDrosophilaNSCs known as neuroblasts (NBs), cell intrinsic programs integrate with extrinsic cues to control periods of rapid growth through temporal patterning genes. Without regulation, NSCs can under proliferate leading to diseases like microcephaly and autism spectrum disorders, or over proliferate leading to macrocephaly and tumors. We know programs to control timing of proliferation and elimination of NSCs exist, but many elements of temporal cassettes are still unclear. What genes may be upstream to regulate known temporal programs to control when certain progeny are produced have not been fully identified, leaving a gap in our understanding. To address these questions, we carried out a large-scale RNAi screen aimed at identifying genes required for NSC elimination. We identified Notch and its ligand, Delta. When Notch pathway activity is reduced in NSCs, we found premature elimination of an important subset of neuroblasts called the mushroom body neuroblasts (MBNBs). These MBNBs produce the neurons responsible for formation of the evolutionarily conserved structure called the mushroom body (MB), which is involved in olfactory based learning and memory. MBNBs with reduced Notch pathway activity also experienced defects in MB structure. Furthermore, we determined that temporal patterning is disrupted primarily through loss of early temporal factor expression. In this work, we find that cell signaling pathways that involve the receptor Notch and its ligand. Delta function to regulate NB proliferation inDrosophila melanogasterby regulating early temporal factor expression.
Neurotrophic factor Neuritin modulates T cell electrical and metabolic state for the balance of tolerance and immunity
Authors: Yu Hong , Nishio Hiroshi , Barbi Joseph , Mitchell-Flack Marisa , Vignali Paolo D. A. , Zheng Ying , Lebid Andriana , Chang Kwang-Yu , Fu Juan , Higgins Makenzie , Huang Ching-Tai , Zhang Xuehong , Li Zhiguang , Blosser Lee , Tam Ada , Drake Charles G. , Pardoll Drew M. 
Published: February 2024

AbstractThe adaptive T cell response is accompanied by continuous rewiring of the T cell’s electric and metabolic state. Ion channels and nutrient transporters integrate bioelectric and biochemical signals from the environment, setting cellular electric and metabolic states. Divergent electric and metabolic states contribute to T cell immunity or tolerance. Here, we report that neuritin (Nrn1) contributes to tolerance development by modulating regulatory and effector T cell function. Nrn1 expression in regulatory T cells promotes its expansion and suppression function, while expression in the T effector cell dampens its inflammatory response. Nrn1 deficiency causes dysregulation of ion channel and nutrient transporter expression in Treg and effector T cells, resulting in divergent metabolic outcomes and impacting autoimmune disease progression and recovery. These findings identify a novel immune function of the neurotrophic factor Nrn1 in regulating the T cell metabolic state in a cell context-dependent manner and modulating the outcome of an immune response.
Comparative transcriptomic analyses reveal differences in the responses of diploid and triploid eastern oysters to environmental stress during a summer mortality event
Authors: Vaidya Rujuta V. , Bodenstein Sarah , Rasulova Dildorakhon , La Peyre Jerome F. , Kelly Morgan W. 
Published: February 2024

AbstractTriploid oysters are commonly used as the basis for production in the aquaculture of eastern oysters along the U.S East and Gulf of Mexico coasts. While they are valued for their rapid growth, incidents of triploid mortality during summer months have been well documented in eastern oysters, especially at low salinity sites. We compared global transcriptomic responses of diploid and triploid oysters bred from the same three maternal lines and outplanted to a high (annual mean salinity = 19.4 ± 6.7) and low (annual mean salinity = 9.3 ± 5.0) salinity site at the onset of mortality event in summer of 2021 to test for effect of parental contribution on triploid performance. We compared transcriptomic responses of same diploid and triploid oysters to test for ploidy specific differences in gene expression in response to high and low salinity sites and tested for instances of aneuploidy in experimental triploid oyster lines. Maternal parentage did not affect triploid mortality, but a strong effect of hatchery conditions (cohort) was observed. We detected a higher number of DEGs in response to outplant sites (salinity) and cohorts, indicating stronger influence of these two factors on triploid mortality. At the low salinity site where triploid oysters experienced high mortality, we observed downregulation of transcripts related to calcium signaling (Calmodulin-a, Histidine-rich calcium binding protein (HRC), and cadherin EGF LAG seven-pass G-type receptor 1(CELSR1)), ciliary activity (axonemal and cytoplasmic dyneins), and cell cycle check points (CDK1, HAUS augmin-like complex subunit 3, and MAPKKK, MCM7, SMCs, RTEL1). These transcripts suggest dampening of the salinity stress response and problems during cell division as key contributors to elevated summer mortality in triploid oysters. No instances of aneuploidy were detected in our triploid oyster lines.
Assessing quadriceps strength in patellofemoral pain patients: A study on the reliability and validity of a low-cost load-cell for clinical practice
Authors: Deysel Germari , van Aswegen Mariaan , Kramer Mark 
Published: February 2024

AbstractBackgroundPatellofemoral pain (PFP) is a common knee complaint affecting diverse populations both acutely and chronically. Quadriceps muscle weakness is one possible aetiology, but current devices for measuring muscle strength (isokinetic dynamometer and hand-held dynamometers) are frequently too expensive for practitioners, especially in under-resourced settings. There is a need to evaluate a low-cost device to manage rehabilitation of people with PFP.MethodsIsometric quadriceps strength of participants aged 18-35 years (total [n = 33], control group [n = 17] and PFP group [n = 16]) were evaluated on an isokinetic dynamometer and a low-cost load cell at baseline and after an 8-week non-standardised intervention for validity scores.ResultsThe load cell showed high absolute and relative reliability (intraclass correlation coefficient = 0.89-0.99; typical error of measurement = 3.9-10.4%). Clinically meaningful difference scores (12.2-45 Nm) were greater than the typical error of measurement, implying sufficient sensitivity of the load cell to measure true changes in isometric quadricep strength. Strong to very strong correlations were evident between the load cell and isokinetic dynamometer torque measurements (r = 0.88-0.90, SEE = 0.05-0.07 Nm), but slope values (β = 0.65-0.77) indicated that torque from the load cell was typically lower than that obtained from the isokinetic dynamometer. An average systematic bias of 16.3-28.8 Nm was evident in favour of the isokinetic dynamometer, with no statistically significant between-group differences being noted between the baseline and follow-up testing.ConclusionThe load cell is a reliable instrument, sensitive enough to detect clinically meaningful differences in quadriceps strength in healthy individuals and those with PFP. The load cell lacks validity and cannot replace isokinetic dynamometry. Given the low cost and excellent reliability, the load cell can be a valuable tool to assess quadriceps muscle deficits and track rehabilitation progress in people with PFP.
White Matter Microstructure Alterations in Early Psychosis and Schizophrenia
Authors: Pavan Tommaso , Alemán-Gómez Yasser , Jenni Raoul , Steullet Pascal , Schilliger Zoé , Dwir Daniella , Cleusix Martine , Alameda Luis , Do Kim Q. , Conus Philippe , Klauser Paul , Hagmann Patric , Jelescu Ileana 
Published: February 2024

AbstractStudies on schizophrenia feature diffusion magnetic resonance imaging (dMRI) to investigate white matter (WM) anomalies. The heterogeneity in the possible interpretations of typical Diffusion Tensor Imaging (DTI) metrics highlights the importance of increasing their specificity. Here, we characterize WM pathology in early psychosis (EP) and schizophrenia (SZ) with increased specificity using advanced dMRI: Diffusion Kurtosis Imaging and the biophysical model White Matter Tract Integrity – Watson (WMTI-W). This enables us to better characterize WM abnormalities, while preserving good sensitivity to group differences, and relate them to the current literature (ENIGMA-schizophrenia), patient’s clinical characteristics and symptomatology. dMRI-derived microstructure features were extracted from all of WM and from individual regions of interest in 275 individuals. 93 subjects diagnosed with EP and 47 with SZ were compared respectively to 135 age-range matched healthy controls (HC). WM DTI diffusivities were higher, while kurtosis was lower in EP vs HC and in SZ vs HC. Differences were more widespread in EP than SZ. The regional alterations found in our cohort matched the DTI patterns found in ENIGMA-schizophrenia. WMTI-W model parameters indicate that the WM alterations in patients come primarily from the extra-axonal compartment, consistent with abnormal myelin integrity in the disease pathology. The direct link between WM alterations and symptomatology is, however, limited.
An Empirical Study on KDIGO-Defined Acute Kidney Injury Prediction in the Intensive Care Unit
Authors: Lyu Xinrui , Fan Bowen , Hüser Matthias , Hartout Philip , Gumbsch Thomas , Faltys Martin , Merz Tobias M. , Rätsch Gunnar , Borgwardt Karsten 
Published: February 2024

MotivationAcute kidney injury (AKI) is a syndrome that affects a large fraction of all critically ill patients, and early diagnosis to receive adequate treatment is as imperative as it is challenging to make early. Consequently, machine learning approaches have been developed to predict AKI ahead of time. However, the prevalence of AKI is often underestimated in state-of-the-art approaches, as they rely on an AKI event annotation solely based on creatinine, ignoring urine output.MethodsWe construct and evaluate early warning systems for AKI in a multi-disciplinary ICU setting, using the complete KDIGO definition of AKI. We propose several variants of gradient-boosted decision trees (GBDT)-based models, including a novel time-stacking based approach. A state-of-the-art LSTM-based model previously proposed for AKI prediction is used as a comparison, which was not specifically evaluated in ICU settings yet.ResultsWe find that optimal performance is achieved by using GBDT with the time-based stacking technique (AUPRC=65.7%, compared with the LSTM-based model’s AUPRC=62.6%), which is motivated by the high relevance of time since ICU admission for this task. Both models show mildly reduced performance in the limited training data setting, perform fairly across different subco-horts, and exhibit no issues in gender transfer.ConclusionFollowing the official KDIGO definition substantially increases the number of annotated AKI events. In our study GBDTs outperform LSTM models for AKI prediction. Generally, we find that both model types are robust in a variety of challenging settings arising for ICU data.
A data driven approach to address missing data in the 1970 British birth cohort
Authors: Katsoulis Michail , Narayanan Martina , Dodgeon Brian , Ploubidis George , Silverwood Richard 
Published: February 2024

ABSTRACTBackgroundMissing data may induce bias when analysing longitudinal population surveys. We aimed to tackle this problem in the 1970 British Cohort Study (BCS70)MethodsWe utilised a data-driven approach to address missing data issues in BCS70. Our method consisted of a 3-step process to identify important predictors of non-response from a pool of ∼20,000 variables from 9 sweeps in 18037 individuals. We used parametric regression models to identify a moderate set of variables (predictors of non-response) that can be used as auxiliary variables in principled methods of missing data handling to restore baseline sample representativeness.ResultsIndividuals from disadvantaged socio-economic backgrounds, increased number of older siblings, non-response at previous sweeps and ethnic minority background were consistently associated with non-response in BCS70 at both early (ages 5-16) and later sweeps (ages 26-46). Country of birth, parents not being married and higher father’s age at completion of education were additional consistent predictors of non-response only at early sweeps. Moreover, being male, greater number of household moves, low cognitive ability, and non-participation in the UK 1997 elections were additional consistent predictors of non-response only at later sweeps. Using this information, we were able to restore sample representativeness, as we could replicate the original sample distribution of father’s social class and cognitive ability and reduce the bias due to missing data in the relationship between father’s socioeconomic status and mortality.ConclusionsWe provide a set of variables that researchers can utilise as auxiliary variables to address missing data issues in BCS70 and restore sample representativeness.Key MessagesWe aimed to address the problem of missing data in the 1970 British Cohort Study (BCS70) caused by non-response at different sweepsWe identified a set of predictors of non-response that can successfully restore baseline sample representativeness across sweepsThe information from this study can be used from researchers in the future to utilise appropriate auxiliary variables to tackle problems due to missing data in BCS70
Epidemiological model can forecast COVID-19 outbreaks from wastewater-based surveillance in rural communities
Authors: Meadows Tyler , Coats Erik R. , Narum Solana , Top Eva , Ridenhour Benjamin J. , Stalder Thibault 
Published: February 2024

AbstractWastewater can play a vital role in infectious disease surveillance, especially in underserved communities where it can reduce the equity gap to larger municipalities. However, using wastewater surveillance in a predictive manner remains a challenge. We tested if detecting SARS-CoV-2 in wastewater can predict outbreaks in rural communities. Under the CDC National Wastewater Surveillance program, we monitored several rural communities in Idaho (USA). While high daily variations in wastewater viral load made real-time interpretation difficult, a SEIR model could factor out the data noise and forecast the start of the Omicron outbreak in five of the six cities that were sampled soon after SARS-CoV-2 quantities increased in wastewater. For one city, the model could predict an outbreak 11 days before reported clinical cases began to increase. An epidemiological modeling approach can transform how epidemiologists use wastewater data to provide public health guidance on infectious diseases in rural communities.
The Association Between Dietary Changes to Lose Weight and Mental Health Status in the National Health and Nutrition Examination Survey, 2005-2006
Authors: Min Jihyun Jane , Noh Keeyoon , Nam Sojeong , Ellison-Barnes Alejandra 
Published: February 2024

AbstractBackgroundWeight loss is a common endeavor taken by millions of residents annually in the U.S.—a country with a 31% overweight and 42% obesity rate. Weight loss is associated with numerous physical health benefits, such as better cardiovascular health. However, unhealthy weight loss strategies can cause adverse mental health effects. Past research has focused on how weight loss strategies affect the mental health of a general population—rather than those who are trying to lose weight—or has investigated a diverse array of weight loss strategies. This paper explores how dietary changes for weight loss are associated with mental health, specifically through several variables used in the Patient Health Questionnaire-9 (PHQ9), which measures depression severity. We hypothesize that eating less and skipping meals will be associated with poorer mental health status, while eating fewer carbohydrates, eating less fat, and drinking more water will be associated with better mental health status.Methods and FindingsThis study uses the U.S. 2005-2006 National Health and Nutrition Examination Survey (NHANES) 2005. Univariate (descriptive statistics), bivariate (correlation coefficient), and multivariate (ordinal logistic regression) analyses were performed. The main results show that ‘skipped meals’ was positively associated with ‘feeling bad about yourself,’ ‘feeling down, depressed, or hopeless,’ and ‘little interest in doing things.’ ‘Ate fewer carbohydrates’ was negatively associated with the ‘little interest in doing things.’ConclusionDiffering dietary changes used for weight loss, particularly skipping meals and eating fewer carbohydrates, are associated with differences in mental health status. Health care professionals providing weight loss guidance should be cognizant of patients’ baseline mental health and the potential for changes in mental health with different dietary strategies. Future research employing a longitudinal approach to determine whether there is evidence of a causal relationship between these and other dietary strategies and subsequent mental health outcomes.
Consent in Canadian-Led Critical Care Research During the COVID-19 Pandemic: A Scoping Review
Authors: Krewulak Karla , Albrecht Lisa , Cameron Saoirse , Gibson Jessica , Martin Dori-Ann , Porteous Rebecca , Sampson Margaret , O’Hearn Katie 
Published: February 2024

ABSTRACTIntroductionDespite the importance of critical care research during the SARS-CoV-2 pandemic, several pandemic-related factors made the process of obtaining prior written informed consent for research infeasible. To overcome these challenges, research studies utilized alternate informed consent models suggested by available guidance.ObjectiveTo describe the consent models used in Canadian intensive care unit (ICU) and pediatric ICU (PICU) studies during the COVID-19 pandemic.Data SourcesWe searched MEDLINE, EMBASE, CENTRAL,clinicaltrials.gov, and medRxiv from 01-Jan-2020 to 28-Apr-2023 using Medical Subject Headings and keywords related to the setting (ICU, PICU), study design (e.g., RCT) and study region (i.e., Canada). We included Canadian-led studies that were enrolling during the SARS-CoV-2 and reported on consent. Two independent reviewers reviewed titles/abstracts and full text articles for inclusion.ResultsWe included 13 studies from adult (n=12, 92.3%) and pediatric (n=1, 7.7%) populations. Some study authors reported that informed (n=3/13, 23.1%) or a priori (n=2/13, 15.4%) consent was obtained, without further details. Study authors also reported using written informed (n=4/13, 30.8%), deferred (n=3/13, 23.1%), verbal/waived/assent (each n=2/13, 15.4%), or that ethics approval was not necessary which means consent was not required (n=1/13, 7.7%). Five studies (n=5/13, 38.5%) used multiple consent models: a priori/deferred (n=2/5, 40%), written/verbal (n=2/5, 40%), or waived/assent (n=1/5, 20%).ConclusionThis scoping review underscores the importance of transparent reporting of or modifications to trial procedures during crises, such as the COVID-19 pandemic. Improved reporting practices and exploration of alternate consent models, including electronic consent, are crucial for advancing critical care trials beyond the pandemic and preparing for future health emergencies.