bluuebunny/crossref_metadata_2025_split huggingface dataset:
Direct therapeutic effect of sulfadoxine-pyrimethamine on nutritional deficiency-induced enteric dysfunction in a human intestine chip
Authors: Kim Seongmin , Naziripour Arash , Prabhala Pranav , Horváth Viktor , Junaid Abidemi , Breault David T. , Goyal Girija , Ingber Donald E. 
Published: July 2023

ABSTRACTSulfadoxine-pyrimethamine (SP) antimalarial therapy has been suggested to improve the birth weight of infants in pregnant women in sub-Saharan Africa independently of malarial infection. Here, we investigated whether SP could have a direct impact on improving intestinal function, thereby enhancing the absorption of essential fats and nutrients crucial for fetal growth.Using a human organ-on-a-chip model, we replicated the adult female intestine with patient organoid-derived duodenal epithelial cells interfaced with human intestinal endothelial cells. Nutrient-deficient (ND) medium was perfused to simulate malnutrition, resulting in the appearance of enteric dysfunction indicators such as villus blunting, reduced mucus production, impaired nutrient absorption, and increased inflammatory cytokine secretion. SP was administered to these chips in the presence or absence of human peripheral blood mononuclear cells (PBMCs).Treatment with SP successfully reversed many abnormalities observed in malnourished chips, as confirmed by transcriptomic and proteomic analysis. Notably, SP significantly enhanced intestinal absorptive functions. Furthermore, SP suppressed the recruitment of PBMCs in the nutrient deficient chips. SP may improve the birth weight of children born to malnourished mothers by countering the effects of enteric dysfunction and suppressing inflammation. These findings highlight the possibility of using SP as a direct intervention to improve maternal absorption and subsequently contribute to healthier fetal growth.
Domain mapping of disease mutations supports genetic testing of specificSORL1variants in familial Alzheimer’s Disease
Authors: Holstege Henne , de Waal Matthijs W. J. , Tesi Niccolo’ , van der Lee Sven J. , de Geus Christa , van Spaendonk Rosalina , Vogel Maartje , Ahmad Shahzad , Amin Najaf , Amouyel Philippe , Beecham Gary W. , Bellenguez Céline , Berr Claudine , Bis Joshua C. , Boland Anne , Bossù Paola , Bouwman Femke , Bras Jose , Charbonnier Camille , Clarimon Jordi , Cruchaga Carlos , Daniele Antonio , Dartigues Jean-François , Debette Stéphanie , Deleuze Jean-François , Denning Nicola , DeStefano Anita L. , Dols-Icardo Oriol , van Duijn Cornelia M. , Farrer Lindsay A. , Fernández Maria Victoria , van der Flier Wiesje M. , Fox Nick C. , Galimberti Daniela , Genin Emmanuelle , Gille Johan J.P. , Grenier-Boley Benjamin , Grozeva Detelina , Le Guen Yann , Guerreiro Rita , Haines Jonathan L. , Holmes Clive , Hummerich Holger , Ikram M. Arfan , Ikram M. Kamran , Kawalia Amit , Kraaij Robert , Lambert Jean-Charles , Lathrop Marc , Lemstra Afina W. , Lleó Alberto , Myers Richard M. , Mannens Marcel M. A. M. , Marshall Rachel , Martin Eden R. , Masullo Carlo , Mayeux Richard , Mead Simon , Mecocci Patrizia , Meggy Alun , Mol Merel O. , Nacmias Benedetta , Naj Adam C. , Napolioni Valerio , Cochran J. Nicholas , Nicolas Gaël , Pasquier Florence , Pastor Pau , Pericak-Vance Margaret A. , Pijnenburg Yolande A. L. , Piras Fabrizio , Quenez Olivier , Ramirez Alfredo , Raybould Rachel , Redon Richard , Reinders Marcel J.T. , Richard Anne-Claire , Riedel-Heller Steffi G , Rivadeneira Fernando , van Rooij Jeroen G. J. , Rousseau Stéphane , Ryan Natalie S. , Sanchez-Juan Pascual , Schellenberg Gerard D. , Scheltens Philip , Schott Jonathan M. , Seshadri Sudha , Sie Daoud , Sims Rebecca , Sistermans Erik A. , Sorbi Sandro , van Swieten John C. , Tijms Betty , Uitterlinden André G. , Visser Pieter Jelle , Wagner Michael , Wallon David , Wang Li-San , Williams Julie , Yokoyama Jennifer S. , Zarea Aline , Hulsman Marc , Andersen Olav M. 
Published: July 2023

AbstractBackgroundProtein truncating variants (PTVs) inSORL1are observed almost exclusively in Alzheimer’s Disease (AD) cases, but the effect of rareSORL1missense variants is unclear.MethodsTo identify high-priority missense variants (HPVs), we applied ‘domain mapping of disease mutations’ on the 637 unique codingSORL1variants detected in 18,959 AD-cases and 21,893 non-demented controls.ResultsIn this sample, PTVs and HPVs associated with respectively a 35- and 10-fold increased risk of early onset AD and 17- and 6-fold increased risk of overall AD. The median age at onset (AAO) of PTV- and HPV-carriers was 62 and 64 years, andAPOE-genotype contributed to AAO-variability. The median AAO of PTV- and HPV-carriers is ∼8-10 years earlier than wild-typeSORL1carriers, matched forAPOE-genotype. Specific HPVs are highly penetrant and lead to earlier AAOs than PTVs, suggesting possible dominant negative effects.ConclusionOur results justify a debate on whether HPV carriers should be considered for clinical counseling.
Exploring Perceptions and Experiences of ChatGPT in Medical Education: A Qualitative Study Among Medical College Faculty and Students in Saudi Arabia
Authors: Abouammoh Noura , Alhasan Khalid , Raina Rupesh , Malki Khalid A. , Aljamaan Fadi , Tamimi Ibraheem , Muaygil Ruaim , Wahabi Hayfaa , Jamal Amr , Al-Tawfiq Jaffar A. , Al-Eyadhy Ayman , Soliman Mona , Temsah Mohamad-Hani 
Published: July 2023

AbstractBackgroundWith the rapid development of artificial intelligence (AI) technologies, there is a growing interest in the potential use of AI-based tools like ChatGPT in medical education. However, there is limited research on the perceptions and experiences of faculty and students with ChatGPT, particularly in Saudi Arabia.ObjectiveThis study aimed to explore the knowledge, perceived benefits, concerns, and limitations of using ChatGPT in medical education, among faculty and students at a leading Saudi Arabian university.MethodsA qualitative study was conducted, involving focused meetings with medical faculty and students with varying levels of ChatGPT experience. A thematic analysis was used to identify key themes and subthemes emerging from the discussions.ResultsParticipants demonstrated good knowledge of ChatGPT and its functions. The main themes were: (1) knowledge and perception of ChatGPT, and (2) roles of ChatGPT in research and medical education. The perceived benefits included collecting and summarizing information and saving time and effort. However, concerns and limitations centered around the potential lack of critical thinking in the information provided, the ambiguity of references, limitations of access, trust in the output of ChatGPT, and ethical concerns.ConclusionsThis study provides valuable insights into the perceptions and experiences of medical faculty and students regarding the use of ChatGPT in medical education. While the benefits of ChatGPT were recognized, participants also expressed concerns and limitations requiring further studies for effective integration into medical education, exploring the impact of ChatGPT on learning outcomes, student and faculty satisfaction, and the development of critical thinking skills.
Decrease in multiple complement protein levels is associated with the development of islet autoimmunity and type 1 diabetes
Authors: Webb-Robertson Bobbie-Jo M , Nakayasu Ernesto S , Dong Fran , Waugh Kathy C , Flores Javier , Bramer Lisa M , Schepmoes Athena , Gao Yuqian , Fillmore Thomas , Onengut-Gumuscu Suna , Frazer-Abel Ashley , Rich Stephen S , Holers V. Michael , Metz Thomas O , Rewers Marian J 
Published: July 2023

SummaryType 1 diabetes (T1D) is a chronic condition caused by autoimmune destruction of the insulin-producing pancreatic β-cells. While it is known that gene-environment interactions play a key role in triggering the autoimmune process leading to T1D, the pathogenic mechanism leading to the appearance of islet autoantibodies - biomarkers of autoimmunity – is poorly understood. Here we show that disruption of the complement system precedes the detection of islet autoantibodies and persists through disease onset. Our results suggest that children who exhibit islet autoimmunity and progress to clinical T1D have lower complement protein levels relative to those who do not progress within a similar timeframe. Thus, the complement pathway, an understudied mechanistic and therapeutic target in T1D, merits increased attention for use as protein biomarkers of prediction and potentially prevention of T1D.
High-Dimensional Single-Cell Multimodal Landscape of Human Carotid Atherosclerosis
Authors: Bashore Alexander C. , Yan Hanying , Xue Chenyi , Zhu Lucie Y. , Kim Eunyoung , Mawson Thomas , Coronel Johana , Chung Allen , Ho Sebastian , Ross Leila S. , Kissner Michael , Passegué Emmanuelle , Bauer Robert C. , Maegdefessel Lars , Li Mingyao , Reilly Muredach P. 
Published: July 2023

AbstractBackgroundAtherosclerotic plaques are complex tissues composed of a heterogeneous mixture of cells. However, we have limited understanding of the comprehensive transcriptional and phenotypical landscape of the cells within these lesions.MethodsTo characterize the landscape of human carotid atherosclerosis in greater detail, we combined cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and single-cell RNA sequencing (scRNA-seq) to classify all cell types within lesions (n=21; 13 symptomatic) to achieve a comprehensive multimodal understanding of the cellular identities of atherosclerosis and their association with clinical pathophysiology.ResultsWe identified 25 distinct cell populations each having a unique multi-omic signature, including macrophages, T cells, NK cells, mast cells, B cells, plasma cells, neutrophils, dendritic cells, endothelial cells, fibroblasts, and smooth muscle cells (SMCs). Within the macrophage populations, we identified 2 proinflammatory subsets that were enriched in IL1B or C1Q expression, 2 distinct TREM2 positive foam cell subsets, one of which also expressed inflammatory genes, as well as subpopulations displaying a proliferative gene expression signature and one expressing SMC-specific genes and upregulation of fibrotic pathways. An in-depth characterization uncovered several subsets of SMCs and fibroblasts, including a SMC-derived foam cell. We localized this foamy SMC to the deep intima of coronary atherosclerotic lesions. Using CITE-seq data, we also developed the first flow cytometry panel, using cell surface proteins CD29, CD142, and CD90, to isolate SMC-derived cells from lesions. Last, we found that the proportion of efferocytotic macrophages, classically activated endothelial cells, contractile and modulated SMC-derived cell types were reduced, and inflammatory SMCs were enriched in plaques of clinically symptomatic vs. asymptomatic patients.ConclusionsOur multimodal atlas of cell populations within atherosclerosis provides novel insights into the diversity, phenotype, location, isolation, and clinical relevance of the unique cellular composition of human carotid atherosclerosis. This facilitates both the mapping of cardiovascular disease susceptibility loci to specific cell types as well as the identification of novel molecular and cellular therapeutic targets for treatment of the disease.
CORRELATION OF BODY COMPOSITION (BODY MASS INDEX, WAIST-TO-HIP RATIO, WAIST-TO-HEIGHT RATIO, NECK CIRCUMFERENCE) WITH FITNESS INDEX USING HARVARD STEP TEST
Authors: Baruah Hazra Chinmoyee 
Published: July 2023

ABSTRACTBACKGROUNDDespite many clear benefits of active lifestyle lack of physical activity are common mostly among students, which further lead to alteration in body compositions. This alteration in body composition is the leading cause of various diseases as well as decrease in Fitness Index level.OBJECTIVETo correlate the body compositions i.e. Body Mass Index, Waist-to-Hip Ratio, Waist-to-Height Ratio, Neck Circumference with Fitness Index using Harvard Step Test among students of PEWS Group of Institutions and also to find which body composition is the strongest predictor of Fitness Index.METHODOLOGY100 subjects were selected randomly in the study and were divided into two groups i.e Group A (Male) and Group B (Female), each having 50 subjects. For each subject BMI, WHR, WHtR, NC was measured. Harvard Step Test was performed and FI was calculated using it.RESULTBased on the statistical analysis i.e Karl Pearson’s Coefficient of Correlation, BMI, WHR, WHtR, NC all are negatively correlated with FI for both males and females. BMI, WHtR, NC of females and WHR of males have greater negative correlation with FI.CONCLUSIONThere is correlation between body compositions i.e. BMI, WHR, WHtR, NC and FI. BMI is the best predictor of FI in both males and females; also it has been observed that the males are fitter than the females.
The Impact of Post-Acute Care on Depression and Anxiety in Stroke Patients: A Prospective Study to Explore the Mediating Effect of Cognitive Function
Authors: Lou Shi-Jer , Lin Hsiu-Fen , Shiu Yu-Tsz , Shi Hon-Yi 
Published: July 2023

ABSTRACTBACKGROUNDCognitive function was significantly associated with post-stroke depression and anxiety in stroke patients. However, no studies have examined whether there is an interaction. this study purposed to investigate whether cognitive function mediates the effect of enrollment in post-acute care (PAC) programs on depression or anxiety in stroke patients and whether the indicators are moderated in the pathway.METHODSThis is a prospective observational cohort study. A group of patients who had received PAC for stroke at one of two medical centers (PAC group, n = 2,087) was compared with a group who had received standard care for stroke at one of four hospitals (three regional hospitals and one district hospital; non-PAC group, n = 1,591) in Taiwan from March, 2015, to March, 2022. The effects of PAC on cognitive function and depression and anxiety at baseline, 12thweek, and 1styear after rehabilitation were investigated using structural equation modeling (SEM). The effect of each variable on the moderation of different pathways in the model was analyzed using AMOS 23.0, and The SPSS PROCESS macro also was used to perform mediation analysis.RESULTSThe PAC program had a mediating effect on cognition and depression at week 12 (a*b= -0.098, P<0.05) on cognition and anxiety at week 12 (a*b= -0.107, P<0.05), and the PAC program had a direct effect on depression and anxiety in the first year. It was found that acute lengths of stay had a significant moderation effect in the model (X*W→M=0.204, P=0.002), but the model lost its mediating effect when the moderation variable was added.CONCLUSIONSPatients with stroke should receive post-acute care as soon as possible to improve their cognitive function after rehabilitation, to maximize the effectiveness of treatment for mental disorders, and to reduce the burden of the disease.WHAT IS KNOWNResearch suggests that cognitive function, including depression and anxiety, significantly improved for patients using post-acute care (PAC).Cognitive function was significantly associated with post-stroke depression and anxiety in patients with stroke.WHAT THE STUDY ADDSPAC had a mediating effect on cognition and depression at week 12 on cognition and anxiety at week 12, and it also had a direct effect on depression and anxiety in the first year.Acute lengths of stay had a significant moderation effect in the model, but the model lost its mediating effect when the moderation variable was added.Patients with stroke should receive post-acute care as soon as possible to improve their cognitive function after rehabilitation, to maximize the effectiveness of treatment for mental disorders, and to reduce the burden of the disease.
A Novel Easy-To-Access Model That Predicts Stroke-Associated Pneumonia
Authors: Chung Cheng-Yu , Wang Wen-Hwa , Yin Chun-Hao , Chen Jin-Shuen , Chen Yao-Shen , Yen Cheng-Chang , Lin Ching-Huang 
Published: July 2023

ABSTRACTBACKGROUNDStroke-associated pneumonia (SAP) is a common poststroke complication but the influence of early neurological deterioration (END) on SAP risk remains unclear. We aimed to develop an easy-to-access model to predict SAP and evaluate the SAP–END relationship using the Glasgow Coma Scale (GCS).METHODSThis retrospective study enrolled consecutive patients aged ≥20 years with first-ever acute ischemic stroke at Kaohsiung Veterans General Hospital between January 1, 2010, and November 30, 2020. SAP was defined according to modified Centers for Disease Control and Prevention criteria. Patients’ baseline characteristics, laboratory data within 24 h, neurological findings, and serial GCS scores within 48 h were collected. Regression analysis was used to identify independent risk factors for SAP.RESULTSAmong 1009 enrolled patients, SAP occurred in 85 (8.4%) patients. Using multivariate analysis, END after admission (adjusted odds ratio [aOR] 2.94, 95% confidence interval [CI] 1.74–4.95, P<0.001) remained significant after adjusting for confounders. Initial GCS score <10 (aOR 2.30, 95% CI 1.30–4.06, P=0.004), National Institutes of Health Stroke Scale (NIHSS) score 5–15 (aOR 2.02, 95% CI 1.09–3.73, P=0.026) or ≥16 (aOR 3.45, 95% CI 1.72–6.89, P<0.001), cardioembolism (aOR 4.76, 95% CI 1.90–11.91, P=0.014), undetermined etiology (aOR 3.41, 95% CI 1.29–9.03, P=0.001), and neutrophil-to- lymphocyte ratio (NLR) >2.5 (aOR 2.10, 95% CI 1.28–3.46, P=0.004) were also significant. The area under the curve (AUC) of combined GCS score, END, NIHSS score, cardioembolism, stroke with undetermined type, and NLR was 0.83 (95% CI 0.78–0.87, P<0.001), which was superior to that of PANTHERIS scores (0.62, 95% CI 0.55–0.68, P<0.001).CONCLUSIONSThis study developed a simple predictive model for SAP using easily accessible and generally available parameters. GCS-based END was an independent risk factor for SAP. Early identification of SAP risk factors and reversible END causes may lower SAP incidence.
Wobbly hedgehog syndrome- a progressive neurodegenerative disease
Authors: Doss Grayson A. , Radecki Daniel Z. , Kethireddy Arya , Reilly Madelyn J. , Pohly Andrea E. , August Benjamin K. , Duncan Ian D. , Samanta Jayshree 
Published: July 2023

AbstractWobbly hedgehog syndrome (WHS) has been long considered to be a myelin disease primarily affecting the four-toed hedgehog. In this study, we have shown for the first time that demyelination is accompanied by extensive remyelination in WHS. However, remyelination is not enough to compensate for the axonal degeneration and neuronal loss, resulting in a progressive neurodegenerative disease reminiscent of progressive forms of multiple sclerosis (MS) in humans. Thus, understanding the pathological features of WHS may shed light on the disease progression in progressive MS and ultimately help to develop therapeutic strategies for both diseases.HighlightsWobbly hedgehog syndrome (WHS) is a progressive neurodegenerative disease.Spongy degeneration of the brain and spinal cord is the diagnostic feature of WHS.WHS affected brain and spinal cord show extensive demyelination and remyelination.Axonal degeneration is accompanied by loss of neurons in WHS.Graphical Abstract
Snowmobile noise alters bird vocalization patterns during winter and pre-breeding season
Authors: Cretois Benjamin , Avery Bick Ian , Balantic Cathleen , Gelderblom Femke B. , Pávon-Jordán Diego , Wiel Julia , Sethi Sarab S. , Betchkal Davyd H. , Banet Ben , Arne Reinen Tor 
Published: July 2023

AbstractNoise pollution poses a significant threat to ecosystems worldwide, disrupting animal communication and causing cascading effects on biodiversity. In this study, we focus on the impact of snowmobile noise on avian vocalizations during the non-breeding winter season, a less-studied area in soundscape ecology. We developed a pipeline relying on deep learning methods to detect snowmobile noise and applied it to a large acoustic monitoring dataset collected in Yellowstone National Park. Our results demonstrate the effectiveness of the snowmobile detection model in identifying snowmobile noise and reveal an association between snowmobile passage and changes in avian vocalization patterns. Snowmobile noise led to a decrease in the frequency of bird vocalizations during mornings and evenings, potentially affecting winter and pre-breeding behaviors such as foraging, predator avoidance and successfully finding a mate. However, we observed a recovery in avian vocalizations after detection of snowmobiles during mornings and afternoons, indicating some resilience to sporadic noise events. These findings emphasize the need to consider noise impacts in the non-breeding season and provide valuable insights for natural resource managers to minimize disturbance and protect critical avian habitats. The deep learning approach presented in this study offers an efficient and accurate means of analyzing large-scale acoustic monitoring data and contributes to a comprehensive understanding of the cumulative impacts of multiple stressors on avian communities.Graphical Abstract
ChatGPT-Enhanced ROC Analysis (CERA): A Shiny Web Tool for Finding Optimal Cutoff in Biomarker Analysis
Authors: Agraz Melih , Karniadakis George Em 
Published: July 2023

AbstractDiagnostic tests play a crucial role in establishing the presence of a specific disease in an individual. Receiver Operating Characteristic (ROC) curve analyses are essential tools that provide performance metrics for diagnostic tests. Accurate determination of the cutoff point in ROC curve analyses is the most critical aspect of the process. A variety of methods have been developed to find the optimal cutoffs. Although the R programming language provides a variety of package programs for conducting ROC curve analysis and determining the appropriate cutoffs, it typically needs coding skills and a substantial investment of time. Specifically, the necessity for data preprocessing and analysis can present a significant challenge, especially for individuals without coding experience. We have developed the CERA (ChatGPT-Enhanced ROC Analysis) tool, a user-friendly ROC curve analysis web tool using the shiny interface for faster and more effective analyses to solve this problem. CERA is not only user-friendly, but it also interacts with ChatGPT, which interprets the outputs. This allows for an interpreted report generated by R-Markdown to be presented to the user, enhancing the accessibility and understanding of the analysis results.Authors summaryMelih Agraz, after graduating from Dokuz Eylül University in Izmir, Turkiye, with a major in Mathematics from the Department of Education, he pursued his Master’s degree at the same university in the field of Statistics. He furthered his education by obtaining a Ph.D. in Statistics from the Middle East Technical University, Ankara in Turkiye. As part of his academic journey, he also served as a Fulbright postdoctoral researcher at UC Berkeley in the United States. Following this, he worked as a postdoctoral researcher at Brown University and Beth Israel Hospital of Harvard Medical School. Currently, he holds the position of Assistant Professor in the Department of Statistics at Giresun University in Turkey.George Em Karniadakisis Professor of Applied Mathematics and Engineering at Brown University. He is a member of the National Academy of Engineering of USA. His interests include stochastic multiscale modeling of physical and biological systems, physics-informed machine learning, and deep neural operators. He has co-authored over 500 papers and five books, and he has the highest h-index in Applied Mathematics according to Google Scholar.