Science Advances

Early life nutrition profoundly influences long-term metabolic health, and breast milk not only provides nutrients but also conveys maternal signals shaping infant metabolic development. While postpartum exercise by lactating women benefits maternal health, its impact on milk-borne signaling remains largely undefined. Small extracellular vesicles (sEVs) in breast milk are key mediators of maternal to infant communication because of their selectively packaged bioactive cargo and resistance to infant digestive enzymes and acids, enabling delivery of their cargo to peripheral tissues. Here, we show that a single session of moderate-intensity postpartum aerobic exercise robustly increases human breast milk sEV concentration, which persists for multiple post-exercise milk collections. Exercise enriches breast milk with sEVs containing regulatory metabolic cargo (proteins, miRNAs, and metabolites), which translates into enhanced mitochondrial capacity in neonatal stage cells. These findings implicate sEVs as an exercise-responsive signaling compartment in breast milk capable of connecting postpartum maternal physical activity to beneficial infant metabolic programming.

Nitazenes are driving a wave of overdose deaths in the United States and Europe and often require additional doses of naloxone to reverse. To understand the molecular basis, we conducted a joint experimental and simulation study of three common nitazenes, eto-, etodes-, and protonitazene. Radioligand experiments demonstrated that all three nitazenes display higher receptor affinity and longer dissociation half-lives than fentanyl. Notably, protonitazene dissociates slower than carfentanil and its displacement requires fourfold higher antagonist concentrations. The observed trend in nitazene half-lives is recapitulated by molecular dynamics simulations, which suggest that kinetics is controlled by specific interactions with two receptor subpockets. A newly published cryo-EM structure of fluetonitazene-OR complex confirms the predicted interactions, including a{pi} -hole bond between the nitro group and Tyr1.39, a residue recently shown to modulate OR signaling bias. Our findings suggest slow receptor dissociation as a key factor challenging overdose reversal. The mechanistic insights have implications for understanding opioid toxicity and designing more effective countermeasures.

The opioid crisis has emphasized the need for more effective treatments for opioid use disorder (OUD)1-3, which is characterized by habitual opioid use to avoid withdrawal symptoms4,5. Both physical and affective symptoms contribute to opioid withdrawal yet whether different neural mechanisms mediate these different symptom domains and contribute distinctly to opioid relapse is unknown. While neurons expressing mu opioid receptors (MORs) gate opioids reinforcing effects6-8 by increasing dopamine (DA) release in nucleus accumbens (NAc), sharp decreases in NAc DA release are associated with withdrawal9-11, the cellular and circuit mechanisms of which are unknown. Here we describe an unusual population of evolutionarily-conserved MOR+ neurons in the NAc expressing the transcription factor Tshz1. Increased activity in these neurons is required for withdrawal aversion learning. Deletion of MORs in Tshz1 neurons prevented withdrawal-induced decreases in DA release and affective aversion, but not physical symptoms associated with withdrawal. Pharmacological activation of mGluR8, which is preferentially expressed in Tshz1 neurons, reduced withdrawal aversion. Thus, by dissociating the circuit mechanisms contributing to the physical and affective components of opioid withdrawal focusing on the critical role of Tshz1 neurons, we have identified a novel druggable target with therapeutic potential for treating key OUD withdrawal symptoms.

-Synuclein (aSyn) is central to Parkinsons disease pathogenesis, yet its native physiological role at the presynapse remain poorly defined. Here, super-resolution imaging in dopaminergic neurons reveals that endogenous aSyn localises within nanometres of L-type voltage-gated calcium channels (LTCC), with closer proximity under both spontaneous neuronal activity and stimulated conditions compared to when extracellular calcium is chelated. Blocking Ca2+/calmodulin-dependent kinase II (CaMKII) reduces aSyn clustering at LTCC under spontaneous activity, suggesting that calcium entry and downstream calcium-dependent kinase activity contribute to aSyn localisation. Moreover, quantitative single-molecule analyses indicate that calcium increases the abundance of both total and serine129 phosphorylated (pS129) aSyn in synaptosomes under spontaneous conditions, and NMR analysis reveals that both calcium and S129 phosphorylation increase the binding affinity of aSyn to synaptic vesicles. Functional assays further demonstrate that LTCC blockade elevates intracellular DA levels exclusively in the presence of aSyn under spontaneous but not stimulated conditions. Finally, biochemical fractionation and multi-colour single-molecule imaging reveal that aSyn preferentially associates with small vesicles that are not obligately coupled to full-fusion associated recycling pools. These results suggest that aSyn acts as a calcium- and phosphorylation-regulated modulator of spontaneous DA release through pathways that are largely independent of full-fusion recycling mechanisms, and that pS129 aSyn is not solely a pathological marker but may also reflects physiological regulation. Together, these insights provide a framework for understanding how therapeutic strategies targeting aSyn may impact its normal synaptic functions.

Vaccination programs worldwide have effectively reduced the burden of childhood diseases, yet immune responses remain highly heterogeneous among individuals 1,2. While host characteristics such as age and sex are established determinants of vaccine immunogenicity, the timing of vaccination, specifically the calendar season of vaccination, remains largely underexplored 3. Although circadian rhythms are known to regulate daily immune function 4, evidence for long-term circannual patterns has been limited by the difficulty of collecting year-round vaccination data across diverse populations. Here, we show that the season of vaccination systematically shapes the immune response across a broad range of pediatric vaccines. By leveraging data from 96 randomized control trials worldwide, including over 48,000 children vaccinated against 14 pathogens, we demonstrate that immunogenicity after vaccination follows a pronounced latitudinal gradient, typically peaking during colder months in temperate regions and exhibiting distinct variability in the tropics. These findings suggest that the circadian human immune response might extend to a circannual scale, potentially synchronized by environmental cues. Incorporating the season of vaccination into the design of clinical trials and public health campaigns may optimize vaccine performance and enhance seroprotection.

Ecological models using light limitation to explain coral depth distribution have largely disregarded the energetic cost of sustaining photosynthetic activity. Here, we quantified photosystem II (PSII) turnover across a depth-simulated light gradient in a zooxanthellate coral, measuring PSII half-life, D1 protein abundance, and PSII-complex gene expression. Maximum photosynthetic capacity remained stable across irradiance levels while respiration rose and PSII turnover accelerated as a power law, imposing increasing ATP demand at the shallowest depths. Declining D1 protein abundance alongside stable transcript levels demonstrated that this escalating maintenance cost operates through post-transcriptional regulation. Consequently, a decreasing fraction of photosynthetic usable energy is available for translocation to the coral host at high irradiance, as the energy required for PSII repair increases. Integrating these physiological constraints into a bio-optical model revealed that the balance between photosynthetic capacity and its maintenance cost defines an optimal depth, the Photosynthetic Usable Energy Supply (PUES) maximum, where host energetic returns are maximized. This framework provides a mechanistic basis for understanding depth distributions in symbiotic corals and extends as a predictive tool for any photosynthetic organism operating under variable irradiance, including forecasting how environmental degradation contracts viable depth ranges.

Dietary patterns worldwide have shifted toward increased consumption of ultraprocessed foods (UPFs), which has been linked to higher disease burden. One mechanism proposed to impact both their consumption and contribution to metabolic disease is altered post-ingestive metabolic response in comparison to nutritionally similar foods. Here, we recruited 57 healthy-weight 18-45-year-old adults to examine the effects of food processing on postprandial metabolism and brain response. Despite nutritional matching, UPF meals evoked a greater insulinemic and energetic response with attenuated carbohydrate oxidation relative to non-UPF meals. Next, between-condition differences in peak carbohydrate oxidation were associated with mesolimbic and superior temporal gyrus activation in response to food cues. Finally, although food value did not differ between conditions, brain responses correlated with food valuation were positive for non-UPF but negative for UPF in visual cortex and striatum. These findings demonstrate that food processing influences post-ingestive metabolism in a way that could help explain long term health effects and differences in food reward through mechanisms beyond calories and macronutrient composition alone.

Dexterous manipulation of objects relies on precise coordination between anatomical elements. In seed-eating birds, seeds are manipulated and dehusked using both the beak and tongue, but the functional roles and coordination of these structures remain unresolved. Here, we quantified the 3D movements of the upper beak, lower beak, tongue, and seed in a hard-biting and a weak-biting songbird species using X-ray Reconstruction of Moving Morphology (XROMM) and measured contractile properties of their primary jaw muscles. We show that the tongue serves as the main tool for seed rotation, transport, and stabilization. Multi-dimensional, high-frequency movements of the upper and lower beaks reveal that efficient seed processing depends on high mobility of the kinetic avian skull. Strong and weak biters differ in feeding kinematics and jaw muscle speeds, suggesting ecological specialization of cranial mechanics. The complexity, precision, and tight coordination of beak and tongue motions show that the avian cranium rivals the dexterity of the primate hand despite limited degrees of freedom.

Photomorphogenesis allows plants to adjust growth to ambient light conditions and relies on protein quality control to ensure the timely turnover of signaling components. The conserved AAA+ ATPase CDC48, along with its cofactors NPL4 and UFD1, is a crucial regulator of proteasomal degradation. While well characterized in other organisms, its role in plant development remains largely unexplored. Here, we show that CDC48 is required for blue light-mediated photomorphogenesis in Arabidopsis. Under blue light, CDC48A accumulates at the plasma membrane and in the nucleus, and cdc48a mutants fail to repress hypocotyl elongation properly. Similar phenotypes are observed upon inhibition of CDC48 or in npl4 and ufd1 mutants. Genetic and biochemical analyses further reveal that CDC48A negatively regulates gibberellin (GA) signaling. Consistently, UFD1 directly interacts with the GA receptor GID1 to promote its degradation. Together, these findings demonstrate that CDC48A integrates light and hormonal cues through protein homeostasis to regulate photomorphogenic development.

The adolescent brain is attuned to social and environmental exploration, allowing behavioral adaptation as experiences shape lasting patterns of morphological organization. Using a convolutional neural network on longitudinal structural MRI data, we assess the early part of this developmental window and derive latent brain representations reflecting patterns of structural variability linked to personal, social, and neighborhood conditions in adolescence. These representations offer a flexible framework for mapping brain-trait associations in adolescence and beyond.

Menopause affects over one billion women worldwide, yet remains poorly characterized at scale. We apply an ICD-10-based phenotyping algorithm to electronic health records (EHR) from an academic medical center (n=33,444 women aged 35-64) and a safety-net hospital system (n=7,041), yielding one of the most racially and socioeconomically diverse menopause cohorts in the literature. Structured EHR fields underrepresent symptom burden: only 38.8% of patients had any documented symptom via natural language processing, despite an estimated prevalence of 90%. Adverse pregnancy outcomes were associated with earlier menopause onset after adjustment ({beta}=-1.21 years, p=8.7x10-45). Menopausal women showed elevated risk for osteoporosis (hazard ratio of 12.40), rheumatoid arthritis (HR of 2.43), and mental and behavioral disorders (HR 2.38) relative to age-matched men, with divergence at menopause onset. We show that large-scale EHR can characterize menopause at a scale and diversity that prospective enrollment has not achieved.

Homeostatic mechanisms protect synapses from destabilizing challenges throughout an organisms lifespan, ensuring stable yet flexible neural network activity. To delineate the molecular basis of presynaptic homeostatic potentiation (PHP), we conducted a comprehensive, in vivo CRISPR/Cas9-based screen of all 16 glutamate receptor (GluR) genes encoded in the Drosophila genome. We first generated a complete expression atlas across larval and adult stages, identifying nine GluRs expressed in presynaptic motor neurons. We then generated null mutants for all 16 GluRs and screened them at the larval neuromuscular junction. While the loss of any single presynaptic GluR did not affect baseline synaptic growth or neurotransmission, our screen revealed a selective and critical requirement for the kainate receptor subunit ekar in the expression of chronic PHP. Further genetic analysis indicates that Ekar functions coordinately with the kainate receptor subunits KaiRID and Ukar within a shared pathway to promote this plasticity. Mechanistically, Ekar acts downstream of active zone remodeling to drive the homeostatic enhancement of presynaptic Ca2+ influx, which is the defining feature of chronic PHP. Together, this genome-wide analysis establishes a definitive functional atlas for the Drosophila glutamate receptome and highlights a specialized, essential role for Ekar in stabilizing long-term synaptic homeostasis.

Electronic health record (EHR) data are critical for clinical research but are challenging to share due to privacy and re-identification risks, particularly in sensitive domains such as opioid use disorder (OUD). Synthetic data generation offers a promising alternative; however, existing methods often struggle to preserve complex multivariate dependencies while maintaining a strong balance between data utility and privacy. The recently proposed MIIC-SDG framework leverages multivariate information theory and Bayesian network modeling to capture dependency structures and introduces Quality-Privacy Scores (QPS) to evaluate this tradeoff, yet its capacity to model nonlinear relationships and support multi-task predictive settings remains limited. In this work, we propose a multi-task extension of TabGraphSyn, a graph-based generative framework for privacy-preserving EHR synthesis. The method constructs patient similarity graphs from high-dimensional tabular data and learns topology-aware embeddings via a graph convolutional network, which are then incorporated into a conditional variational autoencoder for synthetic data generation. Unlike prior approaches, our framework jointly models multiple clinically relevant OUD targets, including 180-day opioid abuse outcome, opioid concept group, and opioid source concept group, enabling preservation of label-dependent relationships across tasks. We evaluate TabGraphSyn against MIIC-SDG under a unified framework including multi-task predictive utility, distributional similarity, identifiability risk, membership inference risk, and QPS-based metrics. Results on the NIH All of Us dataset show that TabGraphSyn achieves a stronger overall utility-privacy balance, outperforming MIIC in most headline metrics, including higher synthetic multi-task ROC-AUC (0.5278 vs 0.4932), MetaQPS (AM: 0.0215 vs 0.0115; HM: 0.0391 vs 0.0223), while slightly underperforming in macro F1 (0.2321 vs 0.2840). These findings demonstrate improved modeling of nonlinear dependencies and more favorable quality-privacy trade-offs in multi-task settings, supporting its use for realistic and privacy-aware synthetic EHR data generation.

People do not always feel as they appear. Someone who seems stable may struggle internally, whereas someone who appears distressed may experience it differently. This gap matters in psychiatry, where assessment relies on symptom scales and external evaluation. Here we developed mindGAP (Measuring INDividual-population GAPs in psychiatric energy landscapes), a hierarchical variational Bayesian framework that uses longitudinal questionnaire data to estimate both population-level symptom dynamics and each participants individual symptom dynamics. We applied mindGAP to time-series PHQ-9 data from 248 participants during the COVID-19 pandemic. The population landscape contained three major states, whereas individualized landscapes often diverged from this shared structure. We quantified this gap as individual-population landscape divergence, which was associated not only with depressive severity but also with modern-type depression-related traits (TACS-22) and interpersonal sensitivity-self traits (IPS-22). Thus, mindGAP opens a route to quantifying a previously unquantified gap between population-level and individual-level symptom organization.

Animals rely on olfaction to locate food, mates, and suitable habitats, yet natural odour environments contain thousands of volatile molecules, creating a high-dimensional sensory problem for both nervous systems and the researchers who study them 1-5. For example, a banana emits around 100 individual volatiles4,6. It remains unclear which components of complex odour blends animals have evolved to use as behavioural cues. Here, combining fieldwork, chemical and behavioural analyses, we show across multiple Drosophila species that behaviourally relevant cues can be predicted directly from the statistical structure of natural odour environments. Animals preferentially respond to components that are most distinctive within their natural host odour blends, and therefore most ecologically informative. These cues can be either major or minor blend components. Our results indicate that host-guided olfactory behaviours have evolved to exploit the statistical structure of natural odour environments by selectively targeting the most informative features of odour blends.

Head and neck cancer (HNC) is the 6th most common malignancy worldwide. 60% of patients present with advanced disease and approximately 50% of patients recur following primary treatment. Chemoradiation remains a standard of care for most patients. However, clinicians lack functional tools to predict which patients will respond to chemoradiation prior to treatment and current models, including organoids and animal model systems, fail to capture either full complexity or patient-to-patient heterogeneity of the individual HNC tumor and microenvironment (TME). Here, we have developed, characterized, and tested a patient-specific microphysiological system (MPS) that reconstructs the HNC TME in a vascularized 3D environment. This MPS was constructed from malignant cells, fibroblasts, and immune cells from a patients surgically resected tumor, seeded within a 3D hydrogel with molded endothelial lumens. Single-cell RNA sequencing confirmed that the MPS preserved 12 transcriptionally distinct cell populations found in matched native tissue. The platform recapitulated tumor hypoxia, with a 12-fold increase in hypoxic marker expression that altered radiation response, consistent with clinical HNC biology. Compartment-resolved imaging revealed distinct treatment dynamics in tumor, stromal, and vascular regions, and individual patients exhibited divergent responses to chemoradiation in spheroid morphology, cell viability, and migration. We found the slope of spheroid area change with treatment tracked with tumor recurrence, suggesting this metric could serve as a functional predictor of therapeutic response.

Mammalian diet and feeding ecology are often reflected by craniofacial skeleton specializations, but feeding requires skeletal actuation by a complex suite of muscles with varying sizes, lines of action, and mechanical function. While muscles play a critical role in feeding mechanics, and hence diet, it remains unclear how well variation in jaw muscle morphology predicts diet in mammals. We quantified the evolutionary interplay between mammalian muscle morphology and diet using a large and taxonomically broad sample. We measured the relative proportions and putative force production capacity, quantified as muscle physiological cross-sectional area (PCSA), for the major adductor complexes, along with a key jaw depressor, in 91 mammalian species (30 chiropterans, 33 primates, and 28 ungulates, carnivorans, rodents, and marsupials). We recovered clear dietary signals for several muscle complexes, with the medial pterygoid (larger in herbivores) and temporalis (larger in carnivores) performing best as dietary predictors. The medial pterygoid is particularly relevant for the mechanical innovation in mammals of moving the mandible along non-orthal, medio-lateral trajectories during mastication. Our findings underscore the intuitive, yet previously unquantified, importance of muscles in the evolution of mandibular roll, yaw, and lateral translation, all mammalian hallmarks of processing diverse types of food.

In their recent study entitled "Ancient DNA reveals the co-existence of domestic horses, donkeys and their hybrids in the prehistorical northwestern China", Li and colleagues (2026) report the genetic identification of three horses, three donkeys and four first-generation hinny hybrids dating to 400-160 BCE from the Mazongshan jade mining site in northwestern China. While a re-analysis of their ancient DNA sequence data confirms the horse and donkey identifications, it indicates that the four putative hinny specimens were, in fact, donkeys. This revision removes the primary evidence originally shown for the presence of hinnies at this site. Therefore, new data from the Mazongshan bone assemblage are required to support the proposed role of hinny hybrids as integral components of trans-regional trade networks during the Late Warring States and Early Han periods.

The RNA helicase MOV10 is highly expressed in developing brain, is present in synapses and is required for embryonic viability. A murine brain-specific knockout of MOV10 (Mov10 Deletion) has a thickened cortex, abnormal dendritic arborization and enhanced fear memory. In human studies, MOV10 is among the loci that is correlated with enhanced cortical brain volumes and is also significantly associated with substance dependence by epigenetic profiling. Here we demonstrate that Mov10 Deletion mice show enhanced fear learning that is aligned with impaired structural connectivity of canonical fear circuits revealed by Diffusion Tensor Imaging. We propose a model where MOV10 loss leads to increased GABRA2 expression in the hippocampus and reduced anatomical connectivity that drives augmented fear learning. Memory reactivation is observable during fear memory retrieval as an overall increase in fMRI functional activity in cortical regions. Taken together, this framework identifies that enhanced fear in the MOV10 model is driven via a "corticalized" fear response during re-exposure to the training context that is not driven by the canonical fear circuit. These findings support a molecular basis for non-traditional enhanced learning mechanisms activated by fearful events that shed light on the intractability of fear memories with the potential to inform PTSD and substance dependence disorders.

Animal venoms represent a major source of chemical novelty, yet how venom compounds originate, diversify, and are maintained across deep evolutionary timescales remains poorly understood. This gap is especially pronounced in cephalopods, which evolved venom systems used in predation, defense, and sexual competition, but whose venom genetic architectures, secretory cell types, and venom-producing glands remain largely unexplored. To date, only a single cephalopod venom compound with confirmed paralytic activity and a known primary sequence, SE-CTX from the golden cuttlefish Acanthosepion esculentum, has been described. Here, we reconstruct the evolutionary history, molecular diversity, and glandular localization of SE-CTX-like proteins using a multimodal approach. We identify 29 homologs across 20 squid and cuttlefish species and define a previously unrecognized venom gene family, which we name deca-ctx, specific to decapodiform cephalopods (squids and cuttlefish). Phylogenetic analyses reveal a single origin of deca-ctx followed by gene duplication and lineage-specific diversification, indicating long-term retention of this venom gene. Predicted DECA-CTX protein structures were separated into two clusters and 20 singletons highlighting potentially extensive structural diversity within a single cephalopod venom gene family. Proteomic analysis confirms expression of five DECA-CTX proteins across three species. Our imaging and histological analyses localize deca-ctx expression to specialized secretory cells within squid and cuttlefish venom glands. Together, these findings reposition SE-CTX as part of an evolutionarily and chemically diverse venom system, rather than an isolated venom protein, and establish cephalopods as a key lineage for investigating how new venom genes arise, diversify, and are integrated into functional venom arsenals.