Proceedings of the National Academy of Sciences, Volume 122, Issue 51, December 2025. SignificanceThe hormone oxytocin is linked to reproduction, social bonding, and health. To date, no single study has investigated oxytocin in both sexes across the life course. Working with the Tsimane of lowland Bolivia—a subsistence population with high ...

by Salsabil Arabi, Chaoqun Ni, B. Ian Hutchins During career advancement and funding allocation decisions in biomedicine, reviewers have traditionally depended on journal-level measures of scientific influence like the impact factor. Prestigious journals reject large quantities of papers, many of which may be meritorious. It is possible that this process could create a system whereby some influential articles are prospectively identified and recognized by journal brands, but most influential articles are overlooked. Here, we measure the degree to which journal prestige hierarchies capture or overlook influential science. We quantify the fraction of scientists’ articles that would receive recognition because (a) they are published in journals above a chosen impact factor threshold, or (b) they are at least as well-cited as articles appearing in such journals. We find that the number of papers cited at least as well as those appearing in high-impact factor journals vastly exceeds the number of papers published in such venues. At the investigator level, this phenomenon extends across gender, racial, and career stage groupings of scientists. We also find that approximately half of researchers never publish in a venue with an impact factor above 15, which, under journal-level evaluation regimes, may exclude them from consideration for opportunities. Many of these researchers publish equally influential work; however, raising the possibility that the traditionally chosen journal-level measures that are routinely considered under decision-making norms, policy, or law, may recognize as little as 10%–20% of this influential work.

Publication date: February 2026 Source: Current Opinion in Behavioral Sciences, Volume 67 Author(s): Emily J Davidson, R. Nathan Spreng

Finding resources for the colony is one of the most difficult and risky tasks for a social insect worker. A worker on a foraging trip can face a number of challenges, including interference from other individuals, her own errors, and environmental disturbances. Collectively, colonies may use a variety of strategies to minimize the impact of such perturbations of the foraging process. Here, we investigated how individual Solenopsis xyloni ant workers react to perturbation of an established pheromone trail. We trained foragers from colonies in the field to either a low or high concentration sucrose solution in a feeder on a T-maze setup, then replaced a section of floor covering, removing a section of the pheromone trail previously laid. We found that while ants made correct choices on the T-maze when the trail was intact, their choices did not differ from chance when the trail was absent, indicating strong reliance on a pheromone trail (and not, for example, memory) to return to the resource. Moreover, when the trail was absent, we found that a majority of ants abandoned the resource, and that even the ants that were able to reach the resource did not repair the perturbed trail. However, with a high-quality resource, more ants persisted in attempting to reach it (instead of abandoning). We interpret these responses in the framework of robustness mechanisms discussed in systems biology. Our study thus links individual and collective responses to perturbations, and provides an empirical example of how information use interacts with system robustness.

Scientific Reports, Published online: 27 December 2025; doi:10.1038/s41598-025-33478-6Identifying key genes for European canker resistance in apple: machine learning and gene expression profiling of quantitative disease resistance

Nature Communications, Published online: 27 December 2025; doi:10.1038/s41467-025-67884-1Current superresolution imaging can beat the Rayleigh limit but struggles with complex imaging tasks. Here, the authors use a quantum-learning framework to address these challenges and introduce an improved method that enhances superresolution of nearby compact sources.

by Yanying Yu, Nicole E. Wheeler, Lars Barquist Antimicrobial resistance (AMR) poses a growing threat to human health. Increasingly, genome sequencing is being applied for the surveillance of bacterial pathogens, producing a wealth of data to train machine learning (ML) applications to predict AMR and identify resistance determinants. However, bacterial populations are highly structured, and sampling is biased towards human disease isolates, violating ML assumptions of independence between samples. This is rarely considered in applications of ML to AMR. Here, we demonstrate the confounding effects of sample structure by analyzing over 24,000 whole genome sequences and AMR phenotypes from five diverse pathogens, using pathological training data where resistance is confounded with phylogeny. We show the resulting ML models perform poorly and that increasing the training sample size fails to rescue performance. A comprehensive analysis of 6,740 models identifies species- and drug-specific effects on model accuracy. These findings highlight the limitations of current ML approaches in the face of realistic sampling biases and underscore the need for population structure-aware methods and more diverse datasets to improve AMR prediction and surveillance.

Many studies have shown that flow, psychological capital (PsyCap), anxiety, and academic efficacy play significant roles in EFL learning, yet little attention has been paid to how these positive and negative states jointly shape learners’ PsyCap. Grounded in the broaden-and-build theory, this study investigated how flow, a state of deep engagement and enjoyment in learning, affected EFL learners’ PsyCap. A total of 1611 EFL learners at the CEFR B1–B2 levels from six universities in China participated in the study. Data were collected using validated questionnaires developed for this study that measured flow, foreign language classroom anxiety (FLCA), academic efficacy, and PsyCap, and analyzed using structural equation modeling (SEM) in AMOS. The results revealed that flow had a significant direct positive effect on PsyCap (β = 0.648, p < 0.001). Academic efficacy significantly mediated this relationship (β = 0.059, p < 0.001), and a significant chain-mediated path was observed through FLCA and academic efficacy (β = 0.023, p < 0.001). The total effect of flow on PsyCap was 0.729 (p < 0.001). These findings provide new insights into educational practices that can effectively enhance EFL learners’ PsyCap and academic achievement by facilitating flow and reducing anxiety.

Ecology and Evolution, Volume 15, Issue 12, December 2025.

Scientific Reports, Published online: 27 December 2025; doi:10.1038/s41598-025-33308-9Field assessment of economy fan coil unit performance in cooling capacity and acoustic compliance analysis

Brain and Behavior, Volume 15, Issue 12, December 2025.

Time-series data have become ubiquitous in psychological research, allowing us to study detailed within-person dynamics and their heterogeneity across persons. Vector autoregressive (VAR) models have become a popular choice as a first approximation of these dynamics. The VAR model for each person and heterogeneity across persons can be jointly modeled using a hierarchical model that treats heterogeneity as a latent distribution. Currently, the most popular choice for this is the multilevel VAR model, which models heterogeneity across persons as quantitative variation through a multivariate Gaussian distribution. Here, we discuss an alternative, the latent class VAR model, which models heterogeneity as qualitative variation using a number of discrete clusters. While this model has been introduced before, it has not been readily accessible to researchers. Here we address this issue by providing an accessible introduction to latent class VAR models; a simulation evaluating how well this model can be estimated in situations resembling applied research; introducing a new R package ClusterVAR, which provides easy-to-use functions to estimate the model; and providing a fully reproducible tutorial on modeling emotion dynamics, which walks the reader through all steps of estimating, analyzing, and interpreting latent class VAR models.

Proceedings of the National Academy of Sciences, Volume 122, Issue 51, December 2025. SignificanceEvolutionary games on graphs are a famous framework describing dynamics over networks for many applications, from biology to physics. Individuals reside on nodes of the network, collect payoffs from pairwise interactions with neighbors, and, ...

Publication date: January 2026 Source: Hormones and Behavior, Volume 177 Author(s): Jason S. Moser, Grace E. Anderson, E. Reid Davis, Ashley Hayden, Kenan G. Sayers, Lilianne Gloe, Courtney C. Louis

Perinatal mental health is a major public health concern, and postpartum women are particularly vulnerable to conditions such as postpartum obsessive-compulsive disorder and postpartum depression. Many postpartum symptoms involve heightened concern for infant safety, suggesting the presence of offspring-centered defensive processes that are distinct from general anxiety focused on self-safety. One offspring-centered defensive behavior described in wild rats is entrance sealing, in which lactating females plug the entrance of their burrow to limit access by potential intruders. Although laboratory mice rarely exhibit sealing spontaneously, sealing-like behavior can be experimentally induced by chemogenetic activation of hypothalamic perifornical urocortin-3 neurons, indicating that mice retain a latent motor pattern for this response. However, no method has existed for reliably quantifying sealing behavior under controlled laboratory conditions. To address this gap, we developed the Tube-Sealing Test (TST), an assay that measures bedding packed into tube-like openings attached to the home cage and enables repeated, non-invasive quantification of sealing behavior. Using this approach, we found that tube sealing occurred rarely in males, intermittently in virgin females, and with markedly greater intensity in postpartum females. Although virgin and postpartum females showed a similar likelihood of performing sealing, postpartum females inserted substantially more bedding than either group. In postpartum females, exposure to a male intruder increased sealing specifically at the tube through which the intruder was introduced, indicating that sealing intensity is modulated by direct threat experience. Together, these findings establish the TST as a simple and reproducible method for quantifying sealing behavior and identify tube sealing as a measurable component of offspring-centered defensive behavior.

Understanding the interactions between various aging processes and the resulting heterogeneity in aging is crucial for promoting healthy aging. Here, we provide evidence that heterogeneity in microbiome and host interactions contributes to diversifying aging phenotypes in sleep, gut integrity, and longevity in Drosophila. Aged flies exhibiting sleep fragmentation preserve gut integrity, accompanied by a shift in microbiota composition, particularly an increase in Acinetobacter junii. A. junii induces sleep fragmentation via its metabolite, urocanic acid, through serotonin receptor-dependent dopamine upregulation. In parallel, A. junii exploits the host response to promote its growth, leading to lifespan extension, which is recapitulated by genetically modified Escherichia coli, suggesting a trade-off between sleep quality and lifespan. Our study demonstrates a systematic mechanism underlying aging heterogeneity, suggesting interventions through bacterial supplements.

With the widespread application of artificial intelligence (AI) technology in the sports industry, the spectator’s experience is increasingly shaped by AI-driven features. To explore the mechanism through which the perceived AI-enabled spectating experience affects viewing behavior, and to validate the mediating role of viewing motivation (SDT Needs Satisfaction) in the relationship between AI and viewing behavior as well as the moderating role of player identification in this mediating pathway, we adopted literature review, survey, and empirical analysis methods. A sample of 272 Chinese tennis enthusiasts was surveyed, and both the measurement model and the structural model were evaluated. The results indicate that the measurement model has good internal consistency, reliability, convergent validity, and discriminant validity. The perceived AI-enabled spectating experience has a significant positive effect on viewing motivation, viewing intention, and recommendation intention. The data show that the indirect effect of the perceived AI-enabled spectating experience on the viewing intention through the viewing motivation is 0.0479, and the indirect effect of the perceived AI-enabled spectating experience on the recommendation intention through the viewing motivation is 0.0548. Both reached a significant level, and the direct effect of the perceived AI-enabled spectating experience has also reached statistical significance. Therefore, viewing motivation plays a partial mediating role between AI and viewing intention and between AI and recommendation intention. Player identification plays a significant positive moderating role (β = 0.2809 on viewing intention, β = 0.1621 on recommendation intention) in the relationship between viewing motivation and viewing behavior; however, it does not moderate the relationship between AI and viewing motivation. In other words, for spectators with higher player identification, viewing motivation drives more strongly both their viewing intention and recommendation intention. We suggest that sports event organizers and media use AI technologies to design differentiated marketing to enhance user engagement and optimize spectators’ experience. For spectators with lower player identification, improving service quality can enhance their satisfaction; for those with higher player identification, efforts should focus on strengthening their connection with the players.

Nature Communications, Published online: 25 December 2025; doi:10.1038/s41467-025-67450-9The authors of this study map the human E3 ubiquitin ligome using a metric learning approach, revealing a unified classification framework that explains preserved patterns and functional segregation of E3 families, linking enzymes to substrates and drug interactions, and guiding strategies for targeted therapies.

Ecology and Evolution, Volume 15, Issue 12, December 2025.

Brain and Behavior, Volume 15, Issue 12, December 2025.

Proceedings of the National Academy of Sciences, Volume 122, Issue 51, December 2025. The COVID-19 pandemic provided a natural experiment to test the impacts of human activity on urban-dwelling wildlife. Urban dark-eyed juncos differ in bill shape and size in Los Angeles in comparison to local wildlands. We measured juncos that hatched ...

by Ben Vezina, Helena B. Cooper, Christopher K. Barlow, Martin Rethoret-Pasty, Sylvain Brisse, Jonathan M. Monk, Kathryn E. Holt, Kelly L. Wyres The Klebsiella pneumoniae species complex inhabits a wide variety of hosts and environments, and is a major cause of antimicrobial resistant infections. Genomics has revealed the population comprises multiple species/sub-species and hundreds of distinct co-circulating sub-lineage (SLs) that are associated with distinct gene complements. A substantial fraction of the pan-genome is predicted to be involved in metabolic functions and hence these data are consistent with metabolic differentiation at the SL level. However, this has so far remained unsubstantiated because in the past it was not possible to explore metabolic variation at scale. Here, we used a combination of comparative genomics and high-throughput genome-scale metabolic modeling to systematically explore metabolic diversity across the K. pneumoniae species complex (n = 7,835 genomes). We simulated growth outcomes for each isolate using carbon, nitrogen, phosphorus, and sulfur sources under aerobic and anaerobic conditions (n = 1,278 conditions per isolate). We showed that the distributions of metabolic genes and growth capabilities are structured in the population, and confirmed that SLs exhibit unique metabolic profiles. In vitro co-culture experiments demonstrated reciprocal commensalistic cross-feeding between SLs, effectively extending the range of conditions supporting individual growth. We propose that these substrate specializations may promote the existence and persistence of co-circulating SLs by reducing nutrient competition and facilitating commensal interactions. Our findings have implications for understanding the eco-evolutionary dynamics of K. pneumoniae and for the design of novel strategies to prevent opportunistic infections caused by this World Health Organization priority antimicrobial resistant pathogen.

Navigating social relationships is a primary determinant of fitness in group-living animals and thus the transition of individuals from infancy to fully fledged group members is marked by concomitant changes in interactions. This developmental trajectory is particularly relevant in primates, where individuals must navigate a social landscape composed of different types of relationships and interactions while gaining independence from their mothers. Yet, little is currently known about how different layers of sociality, like proximity and grooming interactions, co-develop during the sensitive juvenile phase. Here, we harness multilayer network analysis on observations from 18 wild vervet juveniles (4-36 months of age) from two social groups to dissect the maturation of the juvenile social network. We quantify developmental trajectories across three complementary scales: maternal dyadic interactions, individual network centrality, and global network topology. We find that social maturation is defined not by simple network expansion, but by structural reorganisation. Specifically, juveniles shed their early bias toward mothers and kin, replacing these primary bonds by social interactions aligning with spatial proximity. This restructuring is further modulated by socio-demographic traits. Higher maternal rank confers access to influential partners, while females are more central than males in grooming networks, foreshadowing adult social roles. By charting the reorganisation of multiple social layers, this study unravels the processes underpinning the juvenile transition to independence in primates.

Nature Communications, Published online: 25 December 2025; doi:10.1038/s41467-025-67996-8Aqueous zinc-ion batteries are safe and affordable but limited by incompatible electrode kinetics. Here, authors present a machine learning framework that resolves this mismatch, enabling the rational design of durable and stretchable zinc-ion batteries.

The garden dormouse (Eliomys quercinus) inhabits a wide range of habitats, from urban areas in warm temperate lowlands to cool mountain ranges. Despite its adaptability, it has largely disappeared from its former range. While most forest populations in Germany are declining, some populations in cities remain stable. To better understand the ecology of this endangered species, VHF telemetry studies were conducted. Between May and September in 2021, 2022, and 2023, 19 adult individuals (7 males, 12 females) were tracked between 15 to 79 days. The animals were assigned to one of three habitat types: ‘Urban’ (entirely human-modified areas, n = 7), ‘Forest’ (forest habitat with minimal human presence, n = 6), and ‘Mixed’ (a combination of forest and human-modified areas, n = 6). Garden dormice had the largest home ranges (MCP100) in ‘Forest’ habitats (4.06 ha) followed by ‘Mixed’ (1.2 ha) and ‘Urban’ habitats (0.56 ha). They preferred structures with high coverage and proximity to food resources, such as structurally rich plant communities (‘Urban’), rock crevices and ruderal shrub vegetation, including berry bushes (‘Forest’). Nest sites offered protection from predators and a stable microclimate, and were predominantly located in buildings (‘Mixed’, ‘Urban’) and rock crevices (‘Forest’). They were changed frequently. Garden dormice occupied smaller home ranges in areas where human-provided resources were concentrated in a small space. Although garden dormice habitats and the resources they use differ in appearance, they fulfill the same ecological needs: sufficient food, safe movement through the habitat and secure nest sites.