bluuebunny/crossref_metadata_2025_split huggingface dataset:
Key individuals catalyse intergroup violence
Authors: Glowacki Luke , McDermott Rose 
Published: April 2022

Intergroup violence is challenging to understand: why do individuals cooperate to harm members of other groups when they themselves may be killed or injured? Despite progress in understanding the evolutionary and proximate mechanisms that underlie violence, we still have little insight into the processes that lead to theemergenceof coalitionary aggression. We argue that an overlooked component is the presence of individuals who have a crucial role in initiating violence. In instigating intergroup violence, thesekey individualsmay expect to face lower costs, receive greater benefits, or garner benefits that have a greater value to them than others. Alternatively, key individuals may be motivated by individual traits such as increased boldness, propensity for aggression or exploratory behaviour. Key individuals catalyse the emergence of coalitionary violence through one of several processes including altering the costs and benefits that accrue to others, paying a greater share of the startup costs, signalling privileged knowledge, or providing coordination, among other factors. Here we integrate diverse lines of empirical research from humans and non-human animals demonstrating that inter-individual variation is an important factor in the emergence of intergroup violence. Focusing on the role of key individuals provides new insights into how and why violence emerges.This article is part of the theme issue ‘Intergroup conflict across taxa’.
Variation between species, populations, groups and individuals in the fitness consequences of out-group conflict
Authors: Morris-Drake Amy , Kennedy Patrick , Braga Goncalves Ines , Radford Andrew N. 
Published: April 2022

Out-group conflict is rife in the natural world, occurring from primates to ants. Traditionally, research on this aspect of sociality has focused on the interactions between groups and their conspecific rivals, investigating contest function and characteristics, which group members participate and what determines who wins. In recent years, however, there has been increasing interest in the consequences of out-group conflict. In this review, we first set the scene by outlining the fitness consequences that can arise immediately to contest participants, as well as a broader range of delayed, cumulative and third-party effects of out-group conflict on survival and reproductive success. For the majority of the review, we then focus on variation in these fitness consequences of out-group conflict, describing known examples both between species and between populations, groups and individuals of the same species. Throughout, we suggest possible reasons for the variation, provide examples from a diverse array of taxa, and suggest what is needed to advance this burgeoning area of social evolution.This article is part of the theme issue ‘Intergroup conflict across taxa’.
Male services during between-group conflict: the ‘hired gun’ hypothesis revisited
Authors: Bshary Redouan , Richter Xiang-Yi Li , van Schaik Carel 
Published: April 2022

In many group-living mammals, philopatric females form the stable core of the group and defend food or shelter against other groups of females. Where males are larger, their participation could give their female group the edge. How can females secure the contribution of males that are neither the father of current infants, nor the dominant male expecting to sire the next generation of infants? It has been proposed that females recruit these males as ‘hired guns’, receiving social support and copulations in exchange for fighting, against the interests of the dominant male. We first develop the logic of this hypothesis in unprecedented detail by considering the potential pay-off consequences for females and males. We then provide empirical evidence for the existence of hired guns in this context in several primate species. The game-theoretical aspects of the phenomenon remain to be studied, as is the distribution across contexts (e.g. predation avoidance) and species of the hired gun phenomenon.
This article is part of the theme issue ‘Intergroup conflict across taxa’.
Wins and losses in intergroup conflicts reflect energy balance in red-tailed monkeys
Authors: Brown Michelle , Steinitz Ronnie , Emery Thompson Melissa 
Published: April 2022

The energetic costs and benefits of intergroup conflicts over feeding sites are widely hypothesized to be significant, but rarely quantified. In this study, we use short-term measures of energy gain and expenditure to test whether winning an intergroup encounter is associated with greater benefits, and losing with greater costs. We also test an alternative perspective, where groups fight for access to large food sources that are neither depletable nor consistently monopolizable: in this case, a group that has already fed on the resource and is willing to leave first (the loser) is supplanted by a newly arrived group (the winner). We evaluate energy balance and travel distance during and after encounters for six groups of red-tailed monkeys in Kibale National Park, Uganda. We find that winning groups experience substantial energetic benefits, but do so to recoup from earlier deficits. Losing groups, contrary to predictions, experience minimal energetic costs. Winners and losers are predictable based upon their use of the contested resource immediately before the encounter. The short-term payoffs associated with these stressful conflicts compensate for any associated costs and support the perception that between-group contests are an important feature of social life for species that engage in non-lethal conflicts.
This article is part of the theme issue ‘Intergroup conflict across taxa’.
Are strangers just enemies you have not yet met? Group homogeneity, not intergroup relations, shapes ingroup bias in three natural groups
Authors: Doğan Gönül , Glowacki Luke , Rusch Hannes 
Published: April 2022

Humans often favour ingroup members over others, a bias that drives discrimination and intergroup conflicts. Hostile relations between groups and homogeneity within groups may affect such ingroup bias. In an experiment with members of three natural groups in Ethiopia, we vary intergroup relations (neutral versus enmity) and exploit the natural variation in the homogeneity of groups (homogeneous versus heterogeneous) to identify their effect on in- and outgroup concerns. We find that ingroup bias largely manifests as positive concern for ingroup members combined with no concern for outgroup members. Enmity has no effect on ingroup bias, whereas ingroup concern is amplified in homogeneous groups. Group homogeneity, thus, is the primary driver of concerns for others in our study’s context. Our results are relevant to understanding the consequences of exclusionary group identities.
This article is part of the theme issue ‘Intergroup conflict across taxa’.
Predicting the future development of diabetic retinopathy using a deep learning algorithm for the analysis of non-invasive retinal imaging
Authors: Rom Yovel , Aviv Rachelle , Ianchulev Sean , Dvey-Aharon Zack 
Published: April 2022

AbstractAimsDiabetic retinopathy (DR) is the most common cause of vision loss in the working age. This research aimed to develop a machine learning model which can predict the development of referrable DR from fundus imagery of otherwise healthy eyes.MethodsOur researchers trained a machine learning algorithm on the EyePacs dataset, consisting of 156,363 fundus images. Referrable DR was defined as any level above mild on the International Clinical Diabetic Retinopathy scale.ResultsThe algorithm achieved 0.81 Area Under Receiver Operating Curve (AUC) when averaging scores from multiple images on the task of predicting development of referrable DR, and 0.76 AUC when using a single image.ConclusionOur results suggest that risk of DR may be predicted from fundus photography alone. Prediction of personalized risk of DR may become key in treatment and contribute to patient compliance across the board, particularly when supported by further prospective research.SynopsisThe deep learning algorithm our researchers developed was able to predict the development of referrable diabetic retinopathy in diabetic patients with otherwise healthy eyes with 0.81 AUC.
Blood flow restriction added to usual care exercise in patients with early weight bearing restrictions after cartilage or meniscus repair in the knee joint: A feasibility study
Authors: Jakobsen Thomas Linding , Thorborg Kristian , Fisker Jakob , Kallemose Thomas , Bandholm Thomas 
Published: April 2022

AbstractPurposeIn musculoskeletal rehabilitation, blood flow restriction – low load strength training (BFR-LLST) is theoretically indicated – as opposed to traditional heavy strength training – in patients who can or may not heavily load tissues healing from recent surgery. The main purpose was to examine the feasibility of BFR-LLST added to usual care exercise early after cartilage or meniscus repair in the knee joint.MethodsWe included 42 patients with cartilage (n=21) or meniscus repair (n=21) in the knee joint. They attended 9 weeks of BFR-LLST added to a usual care exercise at an outpatient rehabilitation center. Outcome measures were assessed at different time points from 4 (baseline) to 26 weeks postoperatively. They included: Adherence, harms, knee joint and thigh pain, perceived exertion, thigh circumference (muscle size proxy), isometric knee-extension strength, self-reported disability and quality of life.ResultsOn average, patients with cartilage and meniscus repair performed >84 % of the total BFR-LLST supervised sessions. Thirty-eight patients reported 146 adverse events (e.g., dizziness) - none considered serious. A decrease in thigh circumference of the operated leg was not found in both groups from baseline to the end of the intervention period with no exacerbation of knee joint or quadriceps muscle pain.ConclusionsBFR-LLST added to usual care exercise initiated early after cartilage or meniscus repair seems feasible and may prevent disuse thigh muscle atrophy during a period of weight bearing restrictions. Harms were reported, but no serious adverse events were found. Our findings are promising but need replication using RCT-design.
Predictors of all-cause mortality among patients hospitalized with influenza, respiratory syncytial virus, or SARS-CoV-2
Authors: Hamilton Mackenzie A. , Liu Ying , Calzavara Andrew , Sundaram Maria E. , Djebli Mohamed , Darvin Dariya , Baral Stefan , Kustra Rafal , Kwong Jeffrey C. , Mishra Sharmistha 
Published: April 2022

ABSTRACTBackgroundShared and divergent predictors of clinical severity across respiratory viruses may support clinical and community responses in the context of a novel respiratory pathogen.MethodsWe conducted a retrospective cohort study to identify predictors of 30-day all-cause mortality following hospitalization with influenza (N=45,749; 2011-09 to 2019-05), respiratory syncytial virus (RSV; N=24,345; 2011-09 to 2019-04), or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; N=8,988; 2020-03 to 2020-12; pre-vaccine) using population-based health administrative data from Ontario, Canada. Multivariable modified Poisson regression was used to assess associations between potential predictors and mortality. We compared the direction, magnitude, and confidence intervals of risk ratios to identify shared and divergent predictors of mortality.Results3,186 (7.0%), 697 (2.9%) and 1,880 (20.9%) patients died within 30 days of hospital admission with influenza, RSV, and SARS-CoV-2, respectively. Shared predictors of increased mortality included: older age, male sex, residence in a long-term care home, and chronic kidney disease. Positive associations between age and mortality were largest for patients with SARS-CoV-2. Few comorbidities were associated with mortality among patients with SARS-CoV-2 as compared to those with influenza or RSV.ConclusionsOur findings may help identify patients at greatest risk of illness secondary to a respiratory virus, anticipate hospital resource needs, and prioritize local prevention and therapeutic strategies to communities with higher prevalence of risk factors.
VMHdm/cSF-1Neuronal Circuits Regulate Skeletal Muscle PGC1-α via the Sympathoadrenal Drive
Authors: Yoshida Takuya , Fujitani Mina , Farmer Scotlynn , Harada Ami , Shi Zhen , Lee Jenny J. , Tinajero Arely , Singha Ashish K. , Fujikawa Teppei 
Published: April 2022

AbstractObjectiveTo adapt to metabolically challenging environments, the central nervous system (CNS) orchestrates metabolism of peripheral organs including skeletal muscle. The organ-communication between the CNS and skeletal muscle has been investigated, yet our understanding of the neuronal pathway from the CNS to skeletal muscle is still limited. Neurons in the dorsomedial and central parts of the ventromedial hypothalamic nucleus (VMHdm/c) expressing steroidogenic factor-1 (VMHdm/cSF-1neurons) are key for metabolic adaptations to exercise, including increased basal metabolic rate and skeletal muscle mass in mice. However, the mechanisms by which VMHdm/cSF-1neurons regulate skeletal muscle function remain unclear. Here, we show that VMHdm/cSF-1neurons increase the sympathoadrenal activity and regulate skeletal muscle peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PGC-1α) in mice via multiple downstream nodes.MethodsOptogenetics was used to specifically manipulate VMHdm/cSF-1neurons combined with genetically-engineered mice and surgical manipulation of the sympathoadrenal activity.ResultsOptogenetic activation of VMHdm/cSF-1neurons dramatically elevates mRNA levels of skeletal musclePgc-1α, which regulates a spectrum of skeletal muscle function including protein synthesis and metabolism. Mechanistically, the sympathoadrenal drive coupled with β2 adrenergic receptor (β2AdR) is essential for VMHdm/cSF-1neurons-mediated increases in skeletal muscle PGC1-α. Specifically, both adrenalectomy and β2AdR knockout block augmented skeletal muscle PGC1-α by VMHdm/cSF-1neuronal activation. Optogenetic functional mapping reveals that downstream nodes of VMHdm/cSF-1neurons are functionally redundant to increase circulating epinephrine and skeletal muscle PGC1-α.ConclusionsCollectively, we propose that VMHdm/cSF-1neurons-skeletal muscle pathway, VMHdm/cSF-1neurons→multiple downstream nodes→the adrenal gland→skeletal muscle β2AdR, underlies augmented skeletal muscle function for metabolic adaptations.
Asexual male production by ZW recombination in Artemia parthenogenetica
Authors: Boyer Loreleï , Jabbour-Zahab Roula , Joncour Pauline , Glémin Sylvain , Haag Christoph R. , Lenormand Thomas 
Published: April 2022

ABSTRACTIn some asexual species, parthenogenetic females occasionally produce males, which may strongly affect the evolution and maintenance of asexuality if they cross with related sexuals and transmit genes causing asexuality to their offspring (“contagious parthenogenesis”). How these males arise in the first place has remained enigmatic, especially in species with sex chromosomes. Here, we test the hypothesis that rare, asexually produced males of the crustacean Artemia parthenogenetica are produced by recombination between the Z and W sex chromosomes during non-clonal parthenogenesis, resulting in ZZ males through loss of heterozygosity at the sex determination locus. We used RAD-sequencing to compare asexual mothers with their male and female offspring. Markers on several sex-chromosome scaffolds indeed lost heterozygosity in all male but no female offspring, suggesting that they correspond to the sex-determining region. Other sex-chromosome scaffolds lost heterozygosity in only a part of the male offspring, consistent with recombination occurring at a variable location. Alternative hypotheses for the production of these males (such as partial or total hemizygosity of the Z) could be excluded. Rare males are thus produced because recombination is not entirely suppressed during parthenogenesis in A. parthenogenetica. This finding may contribute to explaining the maintenance of recombination in these asexuals.
A comparison of feature selection methodologies and learning algorithms in the development of a DNA methylation-based telomere length estimator
Authors: Doherty Trevor , Dempster Emma , Hannon Eilis , Mill Jonathan , Poulton Richie , Corcoran David , Sugden Karen , Williams Ben , Caspi Avshalom , Moffitt Terrie E , Delany Sarah Jane , Murphy Therese M. 
Published: April 2022

AbstractThe field of epigenomics holds great promise in understanding and treating disease with advances in machine learning (ML) and artificial intelligence being vitally important in this pursuit. Increasingly, research now utilises DNA methylation measures at cytosine-guanine dinucleotides (CpG) to detect disease and estimate biological traits such as aging. Given the high dimensionality of DNA methylation data, feature-selection techniques are commonly employed to reduce dimensionality and identify the most important subset of features. In this study, we test and compare a range of feature-selection methods and ML algorithms in the development of a novel DNA methylation-based telomere length (TL) estimator. We found that principal component analysis in advance of elastic net regression led to the overall best performing estimator when evaluated using a nested cross-validation analysis and two independent test cohorts. In contrast, the baseline model of elastic net regression with no prior feature reduction stage performed worst - suggesting a prior feature-selection stage may have important utility. The variance in performance across tested approaches shows that estimators are sensitive to data set heterogeneity and the development of an optimal DNA methylation-based estimator should benefit from the robust methodological approach used in this study. Additionally, we observed that different DNA methylation-based TL estimators, which have few common CpGs, are associated with many of the same biological entities. Moreover, our methodology which utilises a range of feature-selection approaches and ML algorithms could be applied to other biological markers and disease phenotypes, to examine their relationship with DNA methylation and predictive value.
SEACells: Inference of transcriptional and epigenomic cellular states from single-cell genomics data
Authors: Persad Sitara , Choo Zi-Ning , Dien Christine , Masilionis Ignas , Chaligné Ronan , Nawy Tal , Brown Chrysothemis C , Pe’er Itsik , Setty Manu , Pe’er Dana 
Published: April 2022

ABSTRACTMetacells are cell groupings derived from single-cell sequencing data that represent highly granular, distinct cell states. Here, we present single-cell aggregation of cell-states (SEACells), an algorithm for identifying metacells; overcoming the sparsity of single-cell data, while retaining heterogeneity obscured by traditional cell clustering. SEACells outperforms existing algorithms in identifying accurate, compact, and well-separated metacells in both RNA and ATAC modalities across datasets with discrete cell types and continuous trajectories. We demonstrate the use of SEACells to improve gene-peak associations, compute ATAC gene scores and measure gene accessibility in each metacell. Metacell-level analysis scales to large datasets and are particularly well suited for patient cohorts, including facilitation of data integration. We use our metacells to reveal expression dynamics and gradual reconfiguration of the chromatin landscape during hematopoietic differentiation, and to uniquely identify CD4 T cell differentiation and activation states associated with disease onset and severity in a COVID-19 patient cohort.
Integrative analysis of metabolite GWAS illuminates the molecular basis of pleiotropy and genetic correlation
Authors: Smith Courtney J. , Sinnott-Armstrong Nasa , Cichońska Anna , Julkunen Heli , Fauman Eric , Würtz Peter , Pritchard Jonathan K. 
Published: April 2022

SummaryPleiotropy and genetic correlation are widespread features in GWAS, but they are often difficult to interpret at the molecular level. Here, we perform GWAS of 16 metabolites clustered at the intersection of amino acid catabolism, glycolysis, and ketone body metabolism in a subset of UK Biobank. We utilize the well-documented biochemistry jointly impacting these metabolites to analyze pleiotropic effects in the context of their pathways. Among the 213 lead GWAS hits, we find a strong enrichment for genes encoding pathway-relevant enzymes and transporters. We demonstrate that the effect directions of variants acting on biology between metabolite pairs often contrast with those of upstream or downstream variants as well as the polygenic background. Thus, we find that these outlier variants often reflect biology local to the traits. Finally, we explore the implications for interpreting disease GWAS, underscoring the potential of unifying biochemistry with dense metabolomics data to understand the molecular basis of pleiotropy in complex traits and diseases.
Cardiac impairment in Long Covid 1-year post-SARS-CoV-2 infection
Authors: Roca-Fernández Adriana , Wamil Malgorzata , Telford Alison , Carapella Valentina , Borlotti Alessandra , Monteiro David , Thomaides-Brears Helena , Kelly Matthew D , Dennis Andrea , Banerjee Rajarshi , Robson Matthew D. , Brady Michael , Lip Gregory Y. H. , Bull Sacha , Heightman Melissa , Ntusi Ntobeko , Banerjee Amitava 
Published: April 2022

AbstractBackgroundLong Covid is associated with multiple symptoms and impairment in multiple organs. Cardiac impairment has been reported to varying degrees by varying methodologies in cross-sectional studies. Using cardiac magnetic resonance (CMR), we investigated the 12-month trajectory of cardiac impairment in individuals with Long Covid.Methods534 individuals with Long Covid underwent baseline CMR (T1 and T2 mapping, cardiac mass, volumes, function, and strain) and multi-organ MRI at 6 months (IQR 4.3,7.3) since first post-COVID-19 symptoms and 330 were rescanned at 12.6 (IQR 11.4, 14.2) months if abnormal findings were reported at baseline. Symptoms, standardised questionnaires, and blood samples were collected at both timepoints. Cardiac impairment was defined as one or more of: low left or right ventricular ejection fraction (LVEF and RVEF), high left or right ventricular end diastolic volume (LVEDV and RVEDV), low 3D left ventricular global longitudinal strain (GLS), or elevated native T1 in ≥3 cardiac segments. A significant change over time was reported by comparison with 92 healthy controls.ResultsThe technical success of this multiorgan assessment in non-acute settings was 99.1% at baseline, and 98.3% at follow up, with 99.6% and 98.8% for CMR respectively. Of individuals with Long Covid, 102/534 [19%] had cardiac impairment at baseline; 71/102 had complete paired data at 12 months. Of those, 58% presented with ongoing cardiac impairment at 12 months. High sensitivity cardiac troponin I and B-type natriuretic peptide were not predictive of CMR findings, symptoms, or clinical outcomes. At baseline, low LVEF, high RVEDV and low GLS were associated with cardiac impairment. Low LVEF at baseline was associated with persistent cardiac impairment at 12 months.ConclusionCardiac impairment, other than myocarditis, is present in 1 in 5 individuals with Long Covid at 6 months, persisting in over half of those at 12 months. Cardiac-related blood biomarkers are unable to identify cardiac impairment in Long COVID. Subtypes of disease (based on symptoms, examination, and investigations) and predictive biomarkers are yet to be established. Interventional trials with pre-specified subgroup analyses are required to inform therapeutic options.