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In many animal societies, groups of individuals form stable social units that are shaped by well-delineated dominance hierarchies and a range of affiliative relationships. How do socially complex groups maintain cohesion and achieve collective movement? Using high-resolution GPS tracking of members of a wild baboon troop, we test whether collective movement in stable social groups is governed by interactions among local neighbours (commonly found in groups with largely anonymous memberships), social affiliates, and/or by individuals paying attention to global group structure. We construct candidate movement prediction models and evaluate their ability to predict the future trajectory of focal individuals. We find that baboon movements are best predicted by 4 to 6 neighbours. While these are generally individuals' nearest neighbours, we find that baboons have distinct preferences for particular neighbours, and that these social affiliates best predict individual location at longer time scales (>10 minutes). Our results support existing theoretical and empirical studies highlighting the importance of local rules in driving collective outcomes, such as collective departures, in primates. We extend previous studies by elucidating the rules that maintain cohesion in baboons 'on the move', as well as the different temporal scales of social interactions that are at play.
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http://dx.doi.org/10.1038/srep27704 | DOI Listing |
Brief Bioinform
August 2025
College of Pharmacy, Chongqing Medical University, No. 1 Yixueyuan Road, Yuzhong District, Chongqing 400016, P. R. China.
Drug-induced hepatotoxicity (DIH), characterized by diverse phenotypes and complex mechanisms, remains a critical challenge in drug discovery. To systematically decode this diversity and complexity, we propose a multi-dimensional computational framework integrating molecular structure analysis with disease pathogenesis exploration, focusing on drug-induced intrahepatic cholestasis (DIIC) as a representative DIH subtype. First, a graph-based modularity maximization algorithm identified DIIC risk genes, forming a DIIC module and eight disease pathogenesis clusters.
View Article and Find Full Text PDFFront Public Health
September 2025
Department of Plastic and Reconstructive Surgery, The People's Hospital of Guangxi Zhuang Autonomous Region & Research Center of Medical Sciences, Guangxi Academy of Medical Sciences, Nanning, Guangxi, China.
Background: Obesity is a prevalent and clinically significant complication among individuals with diabetes mellitus (DM), contributing to increased cardiovascular risk, metabolic burden, and reduced quality of life. Despite its high prevalence, the risk factors for obesity within this population remain incompletely understood. With the growing availability of large-scale health datasets and advancements in machine learning, there is an opportunity to improve risk stratification.
View Article and Find Full Text PDFFront Biosci (Landmark Ed)
August 2025
Institute of Statistics, National University of Kaohsiung, 811 Kaohsiung, Taiwan.
Background: Obesity is a chronic condition linked to health issues such as diabetes, heart disease, and increased cancer risk. High body mass index (BMI) is associated with cancers such as breast and colorectal cancer due to hormone imbalances and inflammation from excess fat, whereas a low BMI can raise cancer risk by weakening the immune system. Maintaining a normal BMI improves cancer treatment outcomes, but in some cases, higher BMI might offer protective effects-a phenomenon known as the "obesity paradox".
View Article and Find Full Text PDFJ Eval Clin Pract
September 2025
St. Luke's Health System, Boise, Idaho, USA.
Introduction: Voucher-based food as medicine programs have become a common method to help reduce the burden of chronic disease. While recent studies find these programs reduce HbA1c, few of these studies included a comparison group.
Objective: This article evaluates the impact of a clinically based voucher program on HbA1c of diabetic patients.
J Affect Disord
September 2025
Tianjin University, Medical School, Tianjin, China; Tianjin University, Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin, China; Tianjin University, State Key Laboratory of Advanced Medical Materials and Medical Devices, Tianjin, China.
Background: Abnormal gamma-band auditory steady-state response (gamma-ASSR) power has been reported in major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ), but distinguishing between these disorders based solely on power remains challenging. Directed functional connectivity (DFC), which captures topological patterns of causal information flow, may provide more diagnostic-specific markers. However, conventional case-control framework often disregards the substantial individual heterogeneity, yielding unreliable biomarkers.
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