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From noisy single cells to coupled tissues, circadian rhythms depend on interactions across multiple scales and on external time cues. Oscillator theory has played a central role in making sense of these dynamics, particularly in explaining synchronization and entrainment. Yet the same abstractions that make oscillator models powerful can also mask biologically relevant differences between systems. In this perspective, we outline where oscillator theory has been most informative, where it can mislead, and what this means for future experimental and theoretical work. While we focus here on circadian rhythms, related principles extend to other biological oscillators across timescales.

Cell and tissue functions arise from complex interactions among numerous genes, and a systematic understanding of these functions requires isoform-resolved transcriptomic analysis of single cells with high spatial resolution. Here, we introduce an in situ RNA amplification method and its integration with multiplexed error-robust fluorescence in situ hybridization (MERFISH) to detect short RNA sequences and enable whole-transcriptome-scale, isoform-resolved spatial transcriptomics of individual cells in intact tissues. Using this approach, we imaged ∼33,000 distinct RNAs-including ∼23,000 genes and ∼10,000 isoforms-in the mouse brain. Our data enabled systematic analyses of region- and cell-type-specific gene programs and ligand-receptor-based cell-cell communications. These data further revealed rich spatial diversity and cell-type specificity in isoform usage across numerous genes, as well as brain structures particularly rich in isoform specificity. We anticipate broad application of this method for characterizing the molecular and cellular basis of tissue functions, unlocking previously inaccessible discoveries in cell and organismal biology.

Pulmonary arterial hypertension (PAH) is a disease of abnormal pulmonary vascular remodeling and vascular obliteration that results in right heart failure and death. PAH pathogenesis is strongly associated with mutations of the Transforming Growth Factor Beta (TGF-β) superfamily signaling pathway, which has previously been challenging to target therapeutically. Sotatercept, a fusion protein of the extracellular portion of the activin type 2 receptor A (ACVR2A) and the human IgG1 Fc domain, is the first activin signaling inhibitor (ASI) FDA-approved for the treatment of PAH, demonstrating efficacy across the risk spectrum in PAH. This soluble protein binds to a range of circulating TGF-β superfamily ligands, including activins A and B, growth and differentiation factors (GDFs) 8 and 11, as well as some bone morphogenetic proteins (BMPs). Other ASIs have been developed primarily for hematologic indications, such as anemias and cytopenias associated with β-thalassemia, myelodysplastic syndromes, and myelodysplastic neoplasms. Fundamental questions remain regarding the basic biological mechanisms of ASIs, their short- and long-term side effect profiles, and their potential utility across the spectrum of different etiologies of pulmonary hypertension (PH). In this state-of-the-art review, we brought together basic and clinical researchers, and industry scientists under the umbrella of the Pulmonary Vascular Research Institute (PVRI) Innovative Drug Discovery Initiative (IDDI) to discuss the biology of ASIs, the importance of specific BMP ligands, efficacy and side effect profiles, and considerations in the development of next-generation ASIs.

Dynamic changes in mammary cells are essential for sustaining lactation and maintaining epithelial homeostasis. However, the phenotypic transition process of mammary cells during lactation remains unclear. Here, single-nucleus RNA sequencing (snRNA-seq) of 64 199 cells and single-nucleus chromatin accessibility sequencing (snATAC-seq) of 78 984 cells were generated from the goat mammary gland of dry and lactation stages. A total of 18 cell types were annotated, and spatial transcriptomic analysis confirmed the localization of lactation-related cell types within the mammary tissue. Enrichment analysis of SNP within cell type-specific chromatin accessibility regions revealed strong associations between mammary epithelial cells (MECs) with milk production traits. To further explore the MECs functional diversification during lactation and their differences from the dry stage, four differentiation trajectories from luminal progenitor to luminal mature cells were reconstructed. Lineage-specific gene regulatory networks (GRNs) were constructed by integrating snRNA-seq and snATAC-seq data, and stage-specific signals were identified through cell-cell communications. Finally, to explore the evolutionary conservation and divergence of MECs, cross-species comparative analyses were conducted and revealed MEC differential evolutionary rates, conserved milk-producing subtypes, and lineage-specific populations driving species-specific differences in milk composition. Overall, these findings uncover the coordinated transcriptional and chromatin dynamics that drive mammary epithelial differentiation and functional maintenance during lactation.

Spotted sea bass (Lateolabrax maculatus) is an economically important aquaculture species in China, but nocardiosis caused by Nocardia seriolae results in high mortality and economic losses. To investigate the genetic basis of disease resistance, two experimental populations are challenged and analyzed by genome-wide association studies (GWAS). We identify 112 SNPs, including 17 nonsynonymous variants in tgfbr2. Functional enrichment analysis highlights the TGF-β signaling and its related pathways. Structural analysis reveals that TGFBR2 is highly conserved, and mutations in the intracellular kinase domain may alter receptor conformation. Recombinant TGF-β1a modulated splenic lymphocytes transcription, upregulating foxp3b, il10 and smad7, while suppressing proinflammatory cytokines. The tgfbr2 mutation impaires downstream SMAD phosphorylation and reduces transcriptional activation of the foxp3b promoter. These results identify key genetic loci for resistance to N. seriolae and establish a mechanistic connection between TGF-β signaling and immune regulation, providing a foundation for molecular breeding of disease-resistant spotted sea bass.

Lung adenocarcinoma (LUAD), the most common non-small cell lung cancer, often resists ferroptosis and autophagy-two tumor-suppressive, therapy-sensitive regulated cell death pathways. MAPK12 (a stress-responsive p38 MAPK kinase) boosts LUAD cell survival under oxidative stress, while USP32 (a LUAD-upregulated deubiquitinase) correlates with poor prognosis. However, the USP32-MAPK12 axis's regulatory role in LUAD ferroptosis and autophagy remains uninvestigated. USP32/MAPK12 expression in LUAD tissues/cell lines was detected via Western blotting and immunohistochemistry. Functional assays (colony formation, Transwell migration, ferroptosis/mitophagy tests) were performed after gene overexpression/knockdown. Protein interactions and ubiquitination were analyzed by co-immunoprecipitation, with in vivo validation using xenograft models. USP32 overexpression in LUAD correlated with reduced overall survival; it stabilized MAPK12 by removing K48-linked ubiquitin chains to block proteasomal degradation. USP32/MAPK12 knockdown activated autophagy/ferroptosis (elevated LC3B/ACSL4/Fe²⁺/MDA, reduced GPX4/p62), inhibited LUAD cell proliferation/migration in vitro and tumor growth in vivo. Thus, targeting the USP32-MAPK12 axis may restore cell death sensitivity, representing a promising LUAD therapeutic strategy.

Interactions between peptide and MHC class II (pMHC-II) are crucial for T-cell recognition and immune responses, as MHC-II molecules present peptide fragments to T cells, enabling the distinction between self and non-self antigens. Accurately predicting the pMHC-II binding core is particularly important because it provides insights into pMHC-II interactions and T-cell receptor engagement. Given the high polymorphism and peptide-binding promiscuity of MHC-II molecules, computational prediction methods are essential for understanding pMHC-II interactions. While sequence-based methods are widely used, recent advances in AlphaFold-based structure prediction have opened new possibilities for improving pMHC-II binding core predictions. We constructed a non-redundant dataset of 72 pMHC-II complexes from the IMGT database, supplemented with shuffled negative peptides and curated non-binders. Two sequence-based methods (NetMHCIIpan-4.3 and DeepMHCII) and two structure-based methods (AlphaFold2 fine-tuned (AF-FT) and AlphaFold3 (AF3)) were benchmarked for binding and core prediction. Performance was evaluated using standard metrics (precision, recall, F1 score), and consensus strategies integrating sequence- and structure-based models were developed for scenarios with known and unknown binding status. The AlphaFold-based methods showed strong performance in predicting positive binders, with AF3 achieving the highest positive recall (0.86) and AF2-FT performing similarly (0.81). However, both methods frequently misclassified unbound peptides as binders. NetMHCIIpan excelled at identifying non-binders, achieving the highest negative recall (0.93), but had lower positive recall (0.44). In contrast, DeepMHCII demonstrated moderate performance without any notable strength. Consensus approaches combining AlphaFold-based methods for binder identification with filtering using NetMHCIIpan improved overall prediction precision (0.94 and 0.87 for known and unknown binding status, respectively). This study highlights the complementary strengths of AlphaFold-based and sequence-based methods for predicting pMHC-II binding core regions. AlphaFold-based methods excel in predicting positive binders, while NetMHCIIpan is highly effective at identifying non-binders. Future research should focus on improving the prediction of unbound peptides for AlphaFold-based models. Since NetMHCIIpan's binding core predictive ability is already high, future efforts should concentrate on enhancing its binding prediction to further improve overall accuracy.

Intraocular pressure (IOP), a major risk factor for glaucoma, follows a circadian rhythm with nocturnal increases driven by norepinephrine (NE) from the superior cervical ganglion. This rhythm depends on aqueous humor (AH) dynamics, particularly the outflow through the trabecular meshwork (TM). Herein, we investigated its underlying regulatory mechanisms in the TM because disruption of IOP rhythm increases the risk of glaucoma. Comprehensive gene expression analysis of human TM cells and mouse eyes uncovered NE-upregulated 18 genes, including the small GTPase RHOB. Promoter assays revealed that RHOB is regulated via a cAMP-responsive element. RHOB deficiency enhanced TM phagocytosis and reversed NE-induced suppression of permeability, whereas RHOB overexpression had the opposite effect. In mice, RHO and ROCK inhibitors reduced both nocturnal and NE-induced IOP elevations. These findings suggest that NE elevates IOP by inhibiting TM phagocytosis via RHOB, identifying RHOB as a key regulator of IOP rhythm and a potential target for glaucoma treatment.

The population of Vietnam remains underrepresented in global genomic databases. Here, we present VN1K, a resource of multi-omics and phenotypic information for 1011 unrelated Vietnamese individuals. We present high-depth short-read whole-genome sequencing data for all samples along with various -omics datasets. Using a high-sensitivity variant detection pipeline, which includes a pangenome graph reference and a deep-learning framework, we identify approximately 42 million variants with 7 million short insertions/deletions and 90 thousand structural variants. VN1K also features a whole-genome methylation profile based on long read sequencing. We create a genotype imputation panel with high accuracy on the Vietnamese population, allowing us to identify variants with significantly different allele frequencies in the Vietnamese population compared to other populations. We establish the functional relevance of some of these variants, particularly those in genes associated with genetic disorders, immune diseases, and drug responses, by integrating the allele frequency differences with known genotype-phenotype associations and clinical annotations. Further, we map various loci related to hepatitis B virus infection, triglyceride levels, LDL-C levels, serum glucose levels, HbA1c levels, and levels of two liver enzymes (ALT and AST). The VN1K dataset is accessible via genome.vinbigdata.org, an integrated platform with both linear and graph-based genome browsers.

Prohibitin 2 (PHB2) is a highly conserved protein with essential roles in cell homeostasis and survival across different cell types. Previous studies have shown that the deletion of PHB2 results in an arrest in proliferation due to impaired mitochondrial function regulated by the dynamin-like GTPase OPA1. The function of PHB2 in immune cells remains unclear; however, some studies suggest that PHB2 plays a role in the cell membranes of B and T cells. In order to elucidate the role of PHB2 in immune cells, we generated PHB2-deficient T cells. Our findings reveal a pivotal role for PHB2 in the proliferation and differentiation of T cells. PHB2 deficiency inhibits T cell proliferation by inducing a cell cycle arrest at the G1 to S phase, thereby preventing the differentiation into effector T cells. Furthermore, in contrast to previous reports, T cells lacking PHB2 are more resistant to apoptosis. Metabolic analysis reveals that PHB2-deficient T cells fail to boost their energy production through glycolysis and oxidative phosphorylation upon activation, hindering their ability to sustain biosynthetic processes and to proliferate in response to activation.

Deciphering how the human brain matures and reorganizes across the lifespan remains a central challenge in developmental neuroscience. Understanding the complex developmental processes is essential for elucidating the biological bases of cognition and behavior, as well as the mechanisms underlying aging and neurodegenerative diseases. Neuroimaging has enabled the mapping of nonlinear, age-related changes in brain morphology, microstructure, and connectivity from gestation to senescence. However, we lack a unified understanding of interplay across multimodal neuroimaging measures, structure-function coupling, and the cellular and molecular drivers of network reorganization. In this review, we synthesize current evidence to provide a multiscale MRI-derived account of structural and functional brain development across the human lifespan, highlight key conceptual and methodological gaps, and outline priorities for future research.

Pretrained models, originally developed for vision and textual data, are not a panacea and may fail to fully represent the complexity of sequences in immunological tasks. In studying pretrained immunological sequence modules of a renowned immunogenicity prediction model, pMTnet, we observe that our carefully designed model removing (ablating) the pretrained T cell receptor (TCR) autoencoder in pMTnet can even improve the prediction accuracy. Furthermore, we note the TCR pretraining data, used by pretrained modules within pMTnet, dramatically deviates from a broader and more representative TCR repertoire. Such findings underscore the impacts of the blend of heterogeneous representations and distribution discrepancy in immunological sequences, which necessitate appropriate coordination of different pretrained models and representative databases.

To investigate the integrated response of plankton to climate warming, we measured simultaneous shifts in abundance, geographic range and phenology of eight copepod taxa across the North Sea and NE Atlantic over 6 decades. Here we show that the North Sea warmed about twice as rapidly as the NE Atlantic, yet its species showed greater resilience, maintaining more stable abundance and ranges. In contrast, the NE Atlantic experienced declining copepod populations and greater range shifts (up to 139 km northwards per decade). Regionally specific conditions (high food abundance and/or advection) in the North Sea, may have contributed to this resilience. Most taxa exhibited consistent seasonal shifts with warming (up to ~39 days earlier °C-1) in both areas. In the North Sea, species with greater range shifts also had more pronounced phenological shifts, suggesting a link between the two responses. Climate - smart marine management needs to incorporate this variable ecosystem resilience under warming, moving beyond temperature-centric models of the stability of ecosystems.

Class-level recognition, whereby receivers learn signaller cues and associate them with class-specific information such as familiarity, guides partner choice in mutualisms and supports community stability. Yet its molecular basis is poorly understood. In Labroides dimidiatus, class-level recognition shapes its behavioural ecology: a single individual can engage in 2,300 daily interspecific interactions, favouring rapid partner assessment and categorisation based on learned cues. To probe the molecular basis of this capacity, we coupled a familiar-unfamiliar two-choice social preference test with forebrain RNA-sequencing and H3K27ac profiling at 0, 30, and 120 min, linking behaviour, transcription, and chromatin state. Behaviourally, familiarisation reduced time spent near the familiar client. At the molecular level, transcriptomic profiles varied across time points, with early differences in genes related to synaptic release and chemosensory processes, followed by changes at 30 min in genes associated with GABAergic/homeostatic functions and, at 120 min, in genes linked to neuronal remodelling, consistent with a temporally structured molecular response. Chromatin profiling revealed broad baseline accessibility with modest between-condition differences and stronger within-condition temporal shifts, suggesting that chromatin supports, rather than drives, transcriptional change. Overall, this work provides a molecular framework for class-level recognition and suggests temporally structured molecular dynamics associated with social information processing.

Elucidating the molecular mechanisms governing mammalian hibernation is crucial for understanding energy homeostasis and physiological adaptation to extreme environments. In this study, we present the first high-quality telomere-to-telomere (T2T) reference genome (2.69 Gb) of the Daurian ground squirrel (Spermophilus dauricus), a typical hibernating mammal. The assembled genome comprises 19 chromosomes, nine of which are completely gapless chromosomes, and exhibits a scaffold N50 of 160 Mb. Comparative genomic analysis with 17 hibernating and non-hibernating mammals revealed lineage-specific expansions, the arachidonic acid metabolic pathway was one of the pathways enriched in 222 expanded gene families. To explore the temporal regulation of metabolic pathways during hibernation, we performed multi-omics analysis using liver tissue samples collected at four distinct periods: pre-hibernation (PH), hibernation (H), emergence from hibernation (EH), and summer active (SA). Transcriptomic and metabolomic analysis identified a cluster of lipid metabolism-related genes dynamically regulated during hibernation, highlighting the arachidonic acid (20:4 n-6) as a key regulatory molecule for lipid energy remodeling. Molecular docking and in vitro assays using primary hepatocytes from the Daurian ground squirrel demonstrated that arachidonic acid interacts with PPARα (Peroxisome proliferator-activated receptor alpha) and TRPV channel (Transient receptor potential vanilloid subfamily member), triggering intracellular Ca2+ signaling and increasing the expression of lipid metabolic enzymes, thereby modulating hepatic lipid metabolism during hibernation. Collectively, our study not only provides the first T2T genome of a hibernating mammal but also uncovers an arachidonic acid-mediated lipid metabolic regulatory mechanism, offering evolutionary and biomedical insights into metabolic plasticity during hibernation.

Persistent neural activity often outlasts sensory stimulation, forming a bridge between perception and action. Such activity has been associated commonly with working memory, decision making, and action preparation under active task conditions. However, its existence and characteristics during passive states and sleep remain understudied. Using chronic high-density electrophysiology in freely behaving mice, we show that persistent population spiking activity in the mouse auditory cortical hierarchy enables decoding of past stimuli after their physical offset, during both wakefulness and natural sleep. Using time-resolved decoding, we demonstrate that in wakefulness, persistent representation decays uniformly across early sensory and association cortices. In contrast, sleep is associated with longer persistent stimulus representation in association cortex, while early auditory regions maintain shorter wake-like dynamics. These results reveal how the brain maintains sensory information across behavioral states and establish that persistent representation is a passive and state-dependent feature of sensory processing.

Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C-related burden is critical for guiding prevention and treatment strategies. To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Population-level LDL-C concentrations. Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C-attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C-attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.

The interrogation of data across biological and environmental systems has become increasingly complex. Fortunately, communities are adopting the FAIR (Findable, Accessible, Interoperable, Reusable) data principles for individual datasets, and continue to develop domain-specific, machine-actionable standards. However, integrating FAIR data for meta-analysis across data resources is still challenging. Understanding how disparate datasets are organized remains a manual, time-consuming process. Updating FAIR databases to reflect changes in knowledge is slow, allowing stale annotations and incorrect relationships to propagate, amplified by Artificial Intelligence (AI) systems that harvest data. Building on FAIR, we argue that data should be iteratively updated and improved. FAIR + COPE (Comparable, Organized, Predictive, Engaged) takes FAIR data and makes it Comparable, rapidly Organized (applying / updating standards) for Predictive models, which can be validated and improved by an Engaged community. We provide examples of FAIR + COPE resources and science use cases that highlight the importance of FAIR + COPE in scientific research.

Although previous studies have examined numerous ancient Mycobacterium leprae genomes, the available strains remain concentrated in western Eurasia. Ancient genomes from eastern Eurasia have remained virtually unexplored, limiting our ability to reconstruct the evolutionary history of M. leprae. In this study, we report the first two ancient M. leprae genomes recovered from this region. Phylogenetic analyses place both genomes within the ancestral Branch 0, and the observed phylogeographical patterns are consistent with the hypothesis that this lineage originated in southern East Asia. Together, these findings expand the known ancient genomic diversity of M. leprae and suggest that population movements across the Tianshan region may have contributed to its wider dissemination.