Proceedings of the National Academy of Sciences, Volume 123, Issue 5, February 2026. SignificanceMolecular dynamics simulation is an extremely powerful tool of ever-growing relevance in modern science. Here, we push the boundary of this approach by developing a method that allows investigating, in a blind way, the long-time behavior of ...

Publication date: March 2026 Source: Animal Behaviour, Volume 233 Author(s): Raziya Abliz, Wei Zhang, Shuang Liu, Rufeng Xiong, Chunhua Huang, Jun Li, Mian Zhao, Zhirong Gu, Man Su, Wei Liu, Hua Wu

Foraging bee decision-making research has focused on choice determinants, and the variability and underlying causes of pre-choice latency remain understudied. Here, individual bumblebees (Bombus impatiens) were trained to associate one colored stimulus with a medium-value reward and another with a novel, higher-value reward. The experimental design consists of seven blocks, each containing four consecutive single-stimulus presentations followed by a forced binary choice. The latency to choose a stimulus and the type of choice during dual-choice trials were analysed. In dual-choice trials, bees in the yellow-high reward group showed a slower increase in high-reward selection than those in the blue-high group, suggesting persistent innate color bias. Response latencies for the low-reward stimulus systematically increased across blocks, indicating progressive devaluation. Early learning phases showed a temporary increase in response latency, extending previous findings on experience-dependent adjustments in acceptance thresholds. Latency in single-stimulus trials correlated with binary choice results, though choice proved a stronger indicator of preference than latency. Certain options elicited faster responses when presented with an alternative than when presented alone. Together, these findings support a deliberative model of bumblebee decision-making, in which pre-choice latency is modulated by innate preferences, associative learning, and immediate context.

by Cassian Afting, Norin Bhatti, Christina Schlagheck, Encarnación Sánchez Salvador, Laura Herrera-Astorga, Rashi Agarwal, Risa Suzuki, Nicolaj Hackert, Hanns-Martin Lorenz, Lucie Zilova, Joachim Wittbrodt, Tarik Exner Retinal organoids have become important models for studying development and disease, yet stochastic heterogeneity in the formation of cell types, tissues, and phenotypes remains a major challenge. This limits our ability to precisely experimentally address the early developmental trajectories towards these outcomes. Here, we utilize deep learning to predict the differentiation path and resulting tissues in retinal organoids well before they become visually discernible. Our approach effectively bypasses the challenge of organoid-related heterogeneity in tissue formation. For this, we acquired a high-resolution time-lapse imaging dataset comprising about 1,000 organoids and over 100,000 images enabling precise temporal tracking of organoid development. By combining expert annotations with advanced image analysis of organoid morphology, we characterized the heterogeneity of the retinal pigmented epithelium (RPE) and lens tissues, as well as global organoid morphologies over time. Using this training set, our deep learning approach accurately predicts the emergence and size of RPE and lens tissue formation as well as similarities in overall organoid morphology on an organoid-by-organoid basis at early developmental stages, refining our understanding of when early lineage decisions are made. This approach advances knowledge of tissue and phenotype decision-making in organoid development and can inform the design of similar predictive platforms for other organoid systems, paving the way for more standardized and reproducible organoid research. Finally, it provides a direct focus on early developmental time points for in-depth molecular analyses, alleviated from confounding effects of heterogeneity.

Background Regular physical activity can improve the blood lipid profile, yet athletes may still experience dyslipidemia. This study examined lipid profiles in Turkish endurance and strength athletes in relation to the dietary intake. Methods Eighty-four participants, including strength athletes (n = 45), endurance athletes (n = 20), and non-athletes (n = 19) were assessed for dietary intake (quantitative food-frequency questionnaire), body composition, and blood lipid profile. Results Endurance athletes had a lower body mass index (BMI), body fat (%), fat mass, waist-to-hip ratio, and waist-to-height ratio than strength athletes and non-athletes (p < 0.05). Endurance athletes derived a lower percentage of daily energy intake from protein and fat, a higher from carbohydrate, and consumed more dietary fiber (p < 0.05). Compared with endurance athletes, strength athletes showed higher serum low-density lipoprotein cholesterol (LDL-C) and apolipoprotein B (ApoB) levels, total cholesterol/high-density lipoprotein cholesterol (TC/HDL-C), LDL-C/HDL-C, and ApoB/ApoA-1 ratios, a higher atherogenic index, and lower levels of HDL-C and ApoA-1 (p < 0.05). Overall, athletes had lower serum triacylglycerol (TG), very low-density lipoprotein cholesterol (VLDL-C), and higher LDL-C levels than non-athletes (p < 0.05). Logistic regression models showed that waist-to-height ratio and body fat (%) were consistent predictors of adverse lipid outcomes, independent of dietary energy intake; strength athletes had higher odds of elevated LDL-C and ApoB, highlighting distinct lipid risks by sport group. Conclusion Endurance athletes displayed a more favorable lipid profile than strength athletes and non-athletes. Group differences in lipids likely reflect a combination of adiposity, dietary patterns, and sport-specific behaviors.

Incorporating STEM (Science, Technology, Engineering, and Mathematics) into early childhood education has been associated with children&rsquo;s holistic development. STEM education not only enhances critical thinking, creativity, problem-solving, and other 21st-century skills but also contributes significantly to cognitive growth, emotional regulation, and social abilities. Within the early childhood context, the use of play and toys emerges as a natural and powerful medium for introducing STEM concepts in developmentally appropriate and engaging ways. Play and toys have a prominent role, and previous studies have provided strong evidence on their educational benefits. Toys enhanced with technological characteristics (Technology-Enhanced Toys&mdash;TETs), such as coding and interactive toys, are increasingly being viewed as cultural tools that mediate learning and nurture cognitive and collaborative skills among young learners. However, the impact TETs have on young children&rsquo;s STEM learning remains largely unexplored. This qualitative observational study, grounded in a socio-cultural perspective, explored how 37 children aged 3 to 4 years in four early childhood settings in Greece exhibited STEM-related behaviours during free play with technology-enhanced toys. Data were collected through systematic video recordings and written observations over a three-month period that involved interacting with various TETs, such as Bee-Bot, Coko Robot, a remote-controlled dog, and others. Results indicate that playing with TETs enhanced problem-solving, computational thinking, and collaboration, thus affirming the positive influence of digital technology and the potential of TETs to enrich early STEM education. Implications for equity, the importance of teachers&rsquo; professional development in effectively integrating TETs into early childhood curricula and the need for further research will also be discussed.

Scientific Reports, Published online: 10 February 2026; doi:10.1038/s41598-026-36109-wCorrection: A personalized federated learning-based glucose prediction algorithm for high-risk glycemic excursion regions in type 1 diabetes

Nature, Published online: 09 February 2026; doi:10.1038/d41586-026-00409-yStudy suggests moderate caffeine intake might reduce dementia risk and slow cognitive decline.

by Katie L. Flanagan, Sabra L. Klein Differences in immunity in males and females throughout the life span manifest as differences in susceptibility to chronic diseases, infections, cancer, and responses to therapeutic interventions such as immunomodulatory drugs and vaccines. Sex steroids and sex chromosome-linked immune response genes have major roles in driving these differences, but the cells and signaling pathways governing these are disease-specific and often not known. Such knowledge is required to better understand sex differences in disease incidence and clinical course, and to provide treatments tailored to sex-divergent pathways underlying specific diseases. This Essay explores the major areas where further research is required to determine sex-differential mechanisms.

Concern over insect declines has increased attention on the effects of pesticide residues on native insects. We collected strawberry (target) and common milkweed (non-target) foliage and flowers on two small Central New York farms, within crop fields as well as field margins, and analyzed the tissues for pesticide residues of 94 agrochemicals. We found quantifiable levels of 13 fungicides, herbicides, and insecticides, mostly at low concentrations (typically less than 200 ppb where detected), and more often on strawberry than milkweed. We generally found higher pesticide residue levels early in the season (June vs. July) and on leaves compared to flowers. Residue levels in fields did not differ strongly from margins but pesticide drift may have left low-level residues on milkweed leaves and flowers in margins. Given that non-target effects of fungicides are understudied, we selected two prevalent fungicides found in this study (cyprodinil and difenoconazole) and used them in laboratory assays to assess impacts on early instar monarch (Danaus plexippus) caterpillar feeding, growth, and growth efficiency on common milkweed, along with two other milkweed (Asclepias) species. We tested the hypothesis that exposure to pesticides may be most impactful on poor quality host plants. For both fungicides, exposure at the highest doses (>100,000 ppb) reduced feeding, with the strongest effect on Asclepias asperula, the lowest quality host plant. Effects on caterpillar growth were similarly negative and consistent across host plant species. Finally, effects of fungicides on gross growth efficiency of caterpillars were negative, but dependent on the fungicide. Effects of cyprodinil were stronger than difenoconazole, but at realistically low concentrations there was little effect of either fungicide. Nonetheless, higher concentrations of these chemicals, approximating those experienced directly after fungicide application, may impact non-target species. The observed interaction of fungicides with host plant species highlights the importance of considering resource quality in the assessment of non-target effects of pesticides.

Brain and Behavior, Volume 16, Issue 2, February 2026.

Springtails execute millisecond-scale escape jumps with a single appendage, the furca, on soil, snow, leaf litter, and water. Across 15 taxonomic families (n=552 individuals), relative furca length is bimodal. High-speed video and confocal imaging show that in some long-furca springtails, the resilin-rich manubrium-dens joint behaves as a compliant hinge. It bends during push-off to prolong contact, suppress pitch, and bias takeoff forward, whereas rigid joints drive backward launches with rapid body rotation. We translate this mechanism to a 20-mm, 84-mg jumping robot with an elastic robo-furca hinge. This flexible hinge reduces body rotation by ~90% on flat ground compared to rigid-hinge designs, while maintaining takeoff speed on gravel, springboards, leaves, and pine needles, enabling passive, terrain-adaptable launches for power-limited insect-scale robots without onboard sensing or active control.

Michotte's launching displays are animations of collision-like interactions between two objects that elicit a stable and robust impression that one object, the launcher, caused another object, the target, to move. Although it is well-known that unexpected disruptions of movement continuation between launcher and target decrease causal impressions in centre-to-centre collisions, the role of observers' visual uncertainty around predicted moving trajectories remains relatively unexplored. In this work, we (1) assess observers' uncertainty around post-collision moving angles in a trajectory prediction task and (2) collect their causal impression in a causality rating task. In the latter task, observers viewed centre-to-centre collisions with different levels of movement continuity between the launcher and the target disc. By presenting different launch orientations, we exploited the well-known oblique effect to vary trajectory prediction uncertainty within individuals. If observers rely on their trajectory predictions to rate the causality of the collision, we expect their accuracy in (1) to have a systematic influence on their causality rating in (2). We replicate previous findings that observers report stronger causal impressions in trials where the target and the launcher move in the same direction and weaker causal impressions for collisions where the target and the launcher moving trajectory deviated. Furthermore, causality ratings were on average higher for oblique compared to cardinal launch directions, implying that increased sensory uncertainty induces a stronger causal impression. We hope this work will inspire deeper empirical assessments and computational models describing the role of sensory uncertainty and predictive processes in shaping subjective impressions of causality.

by Bin Liu, Jingwei Yang, Long Ye, Yang Xiao, Guohong Luo, Muyang He, Guy Smagghe, Yongyue Lu, Daifeng Cheng Oviposition holds crucial significance for insect reproduction. Nevertheless, the research on the neural conduction mechanism of oviposition is still rather limited in most agricultural pests. Here, we demonstrate that the conserved Kainate receptors (KARs) expressed in the glutamatergic neurons (GNs) and the ovipositor neuromuscular junctions (NMJs) regulate the oviposition behavior in Bactrocera dorsalis. We identified two KARs (Grik2b and Grik2c), which control the oviposition behavior by influencing both oviposition preference and egg-laying quantity. Protein-ligand interaction indicated that glutamate serves as the neurotransmitter of Grik2b and Grik2c. Knockdown glutamate-coding genes adversely impacted oviposition preference and egg-laying quantity. Specific knockdown Grik2b (or Grik2c) in the GNs and NMJs could respectively influence oviposition preference and egg-laying quantity. Finally, inhibitors of KARs were screened for their ability to inhibit oviposition. Our study provides strong supporting evidence that a novel neural conduction mechanism for oviposition by uncovering the diverse roles of KARs and provides potential molecular target controlling insect oviposition.

Background: Community readiness assessment is used to gauge a community&rsquo;s ability to address systemic issues and inform action. The Community Readiness Instrument (CRI) is the only published tool to have undergone rigorous development and testing. The purpose of this study is to further refine the CRI and establish its score reliability and validity evidence so that healthcare professionals, community advocates, and researchers have a strong assessment of community readiness. Methods: The present study details continued assessment of the CRI through full-scale testing. We conducted a second-order confirmatory factor analysis to analyze the CRI&rsquo;s six-factor structure. We also conducted Rasch analyses to determine the item-level fit statistics for each subscale. Results: Our results suggest that the CRI is a well-structured quantitative tool with items demonstrating sufficient fit under each first-order latent factor. The items each fell into one-factor solutions, and the six subscales collectively formed a higher-order construct of Community Readiness. The CRI continues to demonstrate strong psychometric properties, score reliability, and validity evidence. Conclusions: Mental health and addiction professionals can use the CRI to explore change readiness toward a specific issue in their communities. Implications for practitioners, community advocates, and future researchers are provided.

Scientific Reports, Published online: 10 February 2026; doi:10.1038/s41598-026-39031-3Accurate forecasting of photovoltaic optimal points and efficiency using advanced hybrid machine learning models

Communication research traditionally prioritizes receiver variance, often overlooking how a single message induces commonality across distinct systems. Drawing on classical theory, we propose that effective messages entrain the biological rhythms of the audience. In a large-scale experiment (N=198) monitoring eye-tracking, heart rate, and electrodermal activity during a film, we mapped this alignment. Results reveal a processing hierarchy: alignment was strongest for information acquisition (gaze) but also extended to downstream autonomic regulation. Crucially, a temporal manipulation confirmed this state is content-locked: alignment vanished when the narrative sequence was altered but was restored upon computational unscrambling of the physiological time series. This confirms that responses carry a temporal fingerprint of the content. We conclude that messages function as alignment devices, reducing individual noise to create a network of receivers exhibiting shared processing states, thus providing a materially grounded, signal-based definition of the audience.

Nature Communications, Published online: 09 February 2026; doi:10.1038/s41467-026-69272-9Relaxor ferroelectricity is achieved in two-dimensional CuInP2(S1−xSex)6 crystal via controlling the monoclinic and trigonal coexist phase, enabling memristors with more analog states and lower operating voltages.

Brain and Behavior, Volume 16, Issue 2, February 2026.

Proceedings of the National Academy of Sciences, Volume 123, Issue 5, February 2026. SignificanceMyosins are motor proteins that move along actin filaments and underpin various intracellular functions. Recently, some myosins have been found to drive actin filaments along chiral curved paths, but the mechanisms and significance of this ...

Nature, Published online: 09 February 2026; doi:10.1038/d41586-026-00389-zInventor Josh Miele says that accelerating change requires uprooting social attitudes about blindness and other disabilities.

Movement paths reflect temporal shifts in behavioural states, typically driven by internal and external drivers. However, the inherently multiphasic nature of these trajectories is frequently overlooked in empirical studies, an oversight that can hinder progress in our understanding of movement ecology. While Hidden Markov Models (HMMs) can successfully identify latent states, such as foraging or travelling, they face significant challenges, particularly in determining the appropriate number of states and in interpreting their ecological relevance in the context of both movement patterns and environmental covariates. We present a framework based on Hidden Markov Models with Step Selection Functions (HMM-SSFs) that identifies behavioural states, represented by ecologically meaningful labels linked to explicit hypotheses about animal movement, that best explain observed movement patterns. The framework imposes interpretable conditions and diagnostic criteria on the post-identified behavioural states to ensure ecological coherence. It is grounded in the evaluation of biologically motivated scenarios rather than purely data-driven partitioning. The framework proceeds in two main steps: first, movement-based states are identified using movement-derived covariates only; second, these states are refined by incorporating environmental predictors, such as habitat structure or species interactions (e.g., predator-prey dynamics). This sequential integration enables the detection of ecological responses that are conditional on behavioural context. Simulations show that the framework effectively recovers behavioural states across most conditions. State decoding accuracy was notably higher when control locations were drawn from an exponential-family distribution, compared to a uniform one. The exponential-family approach improved state separation and reduced mislabelling, especially when few control locations are generated. However, low state persistence, particularly in Encamped behaviours, resulted in an overestimation of the number of states. These findings underscore the influence of transition probabilities on behavioural labelling. Finally, we applied our framework to zebra (Equus quagga) movement data by combining movement predictors with changes in direction toward the nearest preferred habitat. This enabled us to distinguish between habitat-dependent and habitat-independent travelling behaviours, as well as to identify spatially finer-scale such as encamped state. The proposed framework balances complexity and biological interpretability by using basic movement metrics to identify the behavioural states and their sequence that best explain multiphasic movement paths, together with environmental factors directing movement in each state. Unlike traditional methods that predefine the number of states, the framework estimates both state number and labels, offering a flexible and ecologically meaningful approach for behavioural inference.

In many group-living animals, affiliating with larger conspecific aggregations can reduce predation risk through dilution. A central question is what simple mechanisms can support such affiliation: are responses driven by generic visual magnitude cues (e.g., "more visual mass" results in stronger attraction), or is affiliation conditioned on perceptual cues about what is being viewed, such that numerical group-size information is used for conspecific-like stimuli but suppressed for predator-like stimuli. Here we test this in zebrafish (Danio rerio) by orthogonally manipulating number and stimulus regime (conspecific zebrafish line drawings versus predator-like large-fish line drawings, differing in both apparent body size and body morphology/identity). In a spontaneous-choice assay with high-resolution tracking, zebrafish preferentially affiliated with the larger of two groups when stimuli were conspecific-like, and preference strength scaled with the logarithmic ratio between groups, consistent with ratio-sensitive numerical processing of group size. Trial-level model comparison favoured an Approximate Number System (ANS) predictor over an object-tracking (OTS) "small-number" account, with no additional small-number advantage under these conditions. When stimuli were predator-like, numerosity- based affiliation was abolished and sometimes weakly reversed, and neither ANS nor OTS predictors explained systematic variance, consistent with threat-like appearance suppressing affiliation even when a larger group is available. These findings show that zebrafish display ANS-like sensitivity to conspecific group size, but that its behavioural influence is selectively deployed: a predator-like stimulus regime (larger body size with correlated changes in morphology/identity) gates whether numerical information guides social affiliation.

by Krupakar V. Subramaniam, Hui Jing Lim, Bao Wang, Valia T. Mihaylova, Evrett N. Thompson, Diane S. Krause, Ellen F. Foxman Interferons (IFNs) are potent antiviral cytokines that are rapidly activated when infected cells sense a virus, but continued IFN production following acute infection is linked to impaired recovery. IFNs protect against infection by inducing a suite of antiviral effectors in IFN receptor-expressing cells via JAK/STAT signaling. However, how IFNs curtail tissue repair is not fully understood. Here, we studied the effects of Type III IFNs (IFNλ1 and IFNλ2) and Type I IFN (IFNβ) on tissue repair functions of human bronchial epithelial cells (HBEC). We show that both Type III IFNs and IFNβ reduce bronchial epithelial cell migration and proliferation through a common upstream mechanism: activation of LATS1, a kinase best known for limiting organ growth as part of the Hippo signaling pathway. Mechanistically, Type III IFN or IFNβ curtailed wound healing by triggering phosphorylation of LATS1 via JAK activity, bypassing activation of MST1/2, the canonical activator of LATS1 in the Hippo pathway. Further experiments showed that distinct signaling pathways lead to LATS1 and STAT1 phosphorylation downstream of IFN receptor signaling. STAT1 was dispensable for IFN-mediated LATS1 phosphorylation and suppression of tissue repair, although as expected STAT1 was required for IFN-mediated protection from rhinovirus or influenza infection. Dose–response curve experiments revealed that higher concentrations of IFN were required to trigger LATS1 phosphorylation compared to STAT1 phosphorylation. Consistently, during rhinovirus or influenza virus infection of organotypic HBEC cultures, we observed phosphorylation of both LATS1 and STAT1, but with different kinetics, with LATS1 activation showing earlier resolution compared to STAT1 activation. These results provide a conceptual framework for understanding how IFN receptor signaling differentially controls epithelial functions required for tissue repair and antiviral defense, and inform efforts to target pathological effects of IFNs following viral infection and in other high IFN states.

Background Falls among older adults represent a major public health concern and are strongly associated with pain, fear of falling, and fear of movement. Pain may increase fall risk in a dose-response manner, while fear of falling can limit mobility, further enhancing vulnerability. This study aimed to investigate the interrelationship between pain, kinesiophobia, and fear of falling in geriatric patients. Methods A descriptive cross-sectional study was conducted in the Physical Therapy Unit of Burdur State Hospital, Turkey, between March 2022 and March 2023. A total of 100 participants aged ≥65 years were recruited by random sampling. Data collection included sociodemographic characteristics, fall history, chronic diseases, and regular medication use. Pain was assessed using the Visual Analog Scale (VAS) and Verbal Category Scale, kinesiophobia using the Tampa Kinesiophobia Scale, and fear of falling using the Tinetti Falls Efficacy Scale. Data were analyzed using Statistical Package for the Social Sciences (SPSS version 23). Descriptive statistics, Student’s t-test, analysis of variance (ANOVA) with Tukey post-hoc, and Pearson correlation analyses were performed. Results The mean age of participants was 70.6 ± 4.5 years. The difference in VAS scores between genders was statistically significant (p < 0.05), with higher pain levels in women. A strong positive correlation was found between the Tampa and Tinetti scores (r = 0.704, p < 0.01), and a moderate positive correlation was observed between VAS and Verbal Category Scale scores (r = 0.535, p < 0.01). Other subgroup comparisons by education, marital status, and chronic disease were not statistically significant. Conclusions Pain, kinesiophobia, and fear of falling are interrelated in older adults and negatively affect daily functioning. Routine assessment of these factors is essential for personalized fall-prevention strategies. Interventions that encourage safe mobility and reduce fear of movement may improve quality of life in the geriatric population.