Biology subjects

Li, T.

Publications and source records attributed to Li, T..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis

Cancer genomics and diagnostics is a rapidly evolving field in which identifying which topics attract early citation prominence can inform laboratory investment, clinical translation, and research strategy. We developed a bibliometric framework to identify and characterize the most influential recent publications in this domain across two consecutive annual cohorts. Using a mathematically exact threshold-expansion algorithm, we ranked over 10,000 OpenAlex-indexed research articles per cohort by 18-month post-publication citation count. Large language model (LLM)-based topical relevance filtering yielded 50 substantively on-topic papers per cohort (100 total). LLM-based concept extraction and a two-stage, embedding-guided normalization pipeline produced 1,090 canonical concepts organized into 77 parent themes, enabling structured cross-cohort comparison of paper-level concept prevalence. The most cited papers in both cohorts were large-scale genomic infrastructure resources rather than single-disease mechanistic studies. Between consecutive cohorts, normalized frequencies increased most for clonal evolution and intratumoral heterogeneity, single-cell and spatial omics technologies, spatial transcriptomics, immune cell infiltration, and copy number variation, while liquid biopsy and ctDNA-related themes showed the largest declines. These findings indicate that early citation impact in cancer genomics is shifting toward integrative, spatially resolved, and heterogeneity-aware research, and demonstrate that LLM-augmented citation ranking provides a replicable, semantically enriched lens for monitoring thematic evolution in precision oncology. A web interface for exploring the results is available at https://pri.pepkio.com/.

bioinformatics↗

bioRxiv2026

StructureSAFE: A structure-aware chemical language model for unified hit identification and lead optimization

Structure-based generative models (SBGMs) hold great promises for accelerating drug discovery by enabling target-aware molecular design. However, existing approaches face fundamental challenges: three-dimensional graph-based models can explicitly incorporate protein structural information but often generate chemically implausible molecules due to limited training data, while chemical language models (CLMs) produce chemically plausible molecules but struggle to effectively leverage three-dimensional structural information for structure-conditioned generation and hard to incorporate lead optimization functionality due to the nature of SMILES string. Here, we present StructureSAFE, a structure-aware chemical language model that resolves this trade-off by integrating protein structural and evolutionary encoders with the SAFE molecular representation via pretraining and finetuning training scheme, enabling both de novo hit identification and a comprehensive suite of lead optimization subtasks within a unified framework. Comprehensive benchmarking on the MolGenBench dataset demonstrates that StructureSAFE achieves state-of-the-art (SOTA) performance across multiple metrics, with particularly pronounced improvements in chemical plausibility relative to graph-based models lacking pretraining. Evaluation on a rigorously constructed held-out test set further confirms its ability to generate drug-like, synthetically accessible molecules with competitive predicted binding affinities for previously unseen targets on both hit identification and lead optimization setting. In silico case studies across four therapeutically relevant targets validate its capacity to generate chemically plausible molecules that recapitulate key binding interactions of known high-affinity ligands while proposing novel interactions for potential better affinity and exploring previously unknown regions of chemical space. Taking together, StructureSAFE represents a versatile and practical tool to provide high-quality candidate molecules for augmenting medicinal chemistry workflows in both hit identification and lead optimization campaigns.

bioinformatics↗

bioRxiv2026

Combinatorial regulation of cellular rotation by CUL-3-actomyosin-dependent oriented division, eggshell geometry, and Ras–MAPK signaling during dorsal–ventral axis establishment in Caenorhabditis elegans

Cellular rotation is an understudied mechanism that regulates animal morphogenesis. In C. elegans, the dorsal-ventral axis is established when the two-cell-stage AB cell rotates within the eggshell as it divides, generating the diamond-shaped blastomere arrangement at the four-cell stage that enables distinct cell fate specification. Multiple mechanisms, including actomyosin-dependent oriented division, chiral cortical flow, and eggshell shape, have been proposed to regulate this arrangement, but whether these represent conflicting hypotheses or co-acting mechanisms remains unclear. Here, we show that CUL-3-actomyosin-dependent oriented division, eggshell geometry, and the Ras-MAPK signaling pathway regulate distinct steps of cellular rotation. AB cell rotation occurred in two distinct phases: Phase I during AB cytokinesis and Phase II during cytokinesis of the neighboring P1 cell. Quantitative analysis revealed that CUL-3-actomyosin-dependent oriented division is the only one of these three pathways that regulates the AB division axis before anaphase. Actomyosin-dependent oriented division and eggshell geometry were both required for Phase I rotation, whereas Phase II rotation was independent of eggshell geometry. We further identified the Ras-MAPK signaling pathway as a regulator of AB cell rotation that acts independently of eggshell geometry. Strikingly, the CUL-3-actomyosin-dependent pathway may have two distinct roles: first, specifying the AB division axis, and second, correcting the division axis in all cell types during cytokinesis. Together, these functions contribute significantly to cellular rotation and dorsal-ventral axis establishment.

Cell Biology↗

bioRxiv2026

Angiogenesis Guided by Bombyx mori Silk Proteins is Molecular Weight-Dependent

Silk proteins, including sericin and fibroin, are natural biopolymers with broad applications in tissue engineering where angiogenesis plays an essential role. However, the pro-angiogenic effects of silk proteins with varying molecular weights (MWs) remain poorly understood. Here, silk proteins with MW distributions at 40-180 kDa or less than 25 kDa were obtained through alkaline hydrolysis to evaluate their effects on angiogenesis. Structurally, reducing MW induced a conformational transition in silk proteins, accompanied by a striking morphological shift in sericin from nanofibers to nanoparticles. Functionally, high-MW sericin (SSH) suppressed, whereas low-MW sericin (SSL) and both high- and low-MW silk fibroin (SFH/SFL) directly promoted endothelial angiogenic activity. Transcriptomic analysis revealed that angiogenesis-related genes such as Id1 and Smad6/9 may underlie the angiostatic effects of SSH. Notably, both SSH and SSL enhanced angiogenesis indirectly via macrophages; however, SSH induced mixed M1/M2-like polarization, while SSL preferentially drove an M2-like phenotype. In a subcutaneous implantation model, SSH promoted angiogenesis but yielded vessels with weak integrity and increased fibrosis, whereas SSL enhanced angiogenesis with improved vascular maturity and reduced fibrotic response. These findings elucidate how the MWs of silk proteins shape angiogenic behavior and highlight the importance of MW tailoring for optimized tissue engineering applications.

Cell Biology↗

bioRxiv2026

CWF19L2 couples pre-mRNA alternative splicing with the maternal-to-zygotic transition to safeguard female fertility

The maternal-to-zygotic transition (MZT) requires precise spatiotemporal execution of pre-mRNA alternative splicing (AS), yet the core splicing machinery driving this developmental reprogramming remains incompletely understood. Here, we identify the CWF19-like protein 2 (CWF19L2) as an indispensable pre-mRNA AS regulator that safeguards against oocyte and early embryo competence defects (OECD). While murine germline-specific depletion of Cwf19l2 spares morphological folliculogenesis, oocyte maturation, or fertilization, it induces complete female sterility characterized by profound developmental arrest at the 2-cell stage. Mechanistically, maternal deficiency of CWF19L2 localized to nuclear speckles disrupts transcription-splicing-translation coupling, collapsing AS homeostasis during maternal reserves and zygotic genome activation. We further demonstrate that CWF19L2 orchestrates the pre-mRNA splicing network through directly binding to target transcripts and indirectly modulating via interacting with the core spliceosomal factor PRPF8. Importantly, exogenous Cwf19l2 mRNA partially rescues the embryonic arrest. Together, our findings establish CWF19L2 as an indispensable AS engine during the MZT, providing a mechanistic foundation for OECD and a novel molecular etiology for female infertility.

Cell Biology↗

bioRxiv2026

Early Tracheal and Salivary miRNAs in Extremely Preterm Infants Predict BPD-related Pulmonary Hypertension

Pulmonary hypertension (BPD-PH) associated with bronchopulmonary dysplasia (BPD) in preterm infants associates with high morbidity and mortality within the first two years of life. In a previous unbiased study, we identified a panel miRNAs in tracheal aspirates (TA) that were differentially expressed in extremely low gestational age newborns (ELGANs) with BPD-PH compared to those with BPD but no PH. To explore the predictive potential of these miRNAs, we studied TA exosomes from 7 days old ELGANs and analysed a curated panel of 16 miRNAs through logistic regression and calculated the predictive AUROC to diagnose BPD-PH at 36 weeks PMA. AUROC of TA miRNAs was 0.76 with sensitivity and specificity of 53% and 93%, respectively. Adding sex and gestational age to the variables improved the AUROC to 0.78 with sensitivity and specificity of 61 and 87% respectively. Due to challenges of obtaining TA in non-invasively ventilated infants, we collected saliva samples from ELGANs at 7 days of age and compared the log expression of these 16 miRNAs in both biofluids and found significant correlation in their expression (pearson r=0.92, p<0.001). We calculated the predictive AUROC of the same miRNAs to diagnose BPD-PH at 36 weeks PMA. AUROC of these miRNAs in saliva was = 0.85 with sensitivity and specificity of 82% and 72%, respectively; addition of biological sex and gestational age improved AUROC to 0.86 with sensitivity and specificity of 79% and 76% respectively. Leave-one-sample-out sensitivity analysis demonstrated stable training performance with reduced performance in testing samples, supporting the need for validation in larger independent cohorts. In conclusion, early salivary miRNAs have great potential for risk stratification of ELGANs to develop BPD-PH, while also providing the opportunity to identify target molecules and mechanisms that modulate molecular function.

bioinformatics↗

bioRxiv2026

EMAlign: accurate alignment of cryo-EM maps through main-chain probability using deep learning

Accurate alignment of cryo-EM density maps is essential for comparing conformational states, searching map libraries, and guiding atomic model building, but remains challenging for noisy ex-perimental maps and partially overlapping structures. Existing alignment methods are often based on raw maps, which may result in reduced accuracy due to the density noise, or require manual intervention for local alignment, which suffers from limited general applicability. Addressing the limitations, we present EMAlign, an automatic global and local cryo-EM map alignment with predicted main-chain probability using deep learning. First, EMAlign predicts main-chain prob-ability maps from raw cryo-EM density maps using a BiMCUNet network. Then, a fast Fourier transform (FFT)-based search strategy is used to globally search the accurate alignment between cryo-EM maps based on predicted main-chain probability maps. As such, the main-chain prob-ability map overcomes the noisy raw map problem, and the FFT-based exhaustive global search ensures the general applicability of alignment. EMAlign is evaluated on 64 global map pairs, 195 local map pairs, and 60 structure-to-map pairs at 3-10 [A] resolution and compared with gm-fit, fitmap, VESPER, and CryoAlign. It is shown that EMAlign outperforms the other methods in both global and local alignment, achieving mean RMSDs of 1.03 [A] (global), 2.56 [A] (lo-cal), and 0.82 [A] (structure-to-map), with success rates of 100.0%, 100.0%, and 98.3% under the criterion of RMSD < 10 [A] . The EMAlign package is freely available at https://github.com/huang-laboratory/EMAlign/.

bioinformatics↗

bioRxiv2026

A missense mutation in FBXL3 links circadian regulation to out-of-season estrus in sheep

Seasonal breeding is a remarkable adaptive trait, but it constrains efficient production in the sheep industry. Recent studies have shown that seasonal breeding is associated with endogenous circannual rhythms, which are regulated in part by the circadian clock system. FBXL3, a pivotal component of the SCF (SKP1 - CUL1 - F-box) E3 ubiquitin ligase complex, is a known determinant of the mammalian circadian period. In this study, we identified a missense mutation, T183M, in FBXL3 through selective sweep analysis. The allele frequency of this mutation differed significantly between sheep breeds exhibiting year-round estrus and those showing seasonal breeding patterns. The association between the T183M mutation and seasonal breeding was further validated using an ovariectomized, estradiol-implanted sheep model. We then generated mice carrying the homologous T183M mutation and found that they exhibited significantly lengthened circadian periods, accompanied by reduced CRY1 expression and increased CLOCK expression. Co-immunoprecipitation assays confirmed that the mutation reduced the interaction between FBXL3 and CRY1. These findings demonstrate an evolutionarily conserved role of FBXL3 in the circadian clock system. We propose that the T183M mutation disrupts day-length recognition, thereby influencing seasonal estrus in sheep. Author summarySeasonal breeding limits sheep productivity and is regulated by circadian rhythms, yet the key genetic determinants remain poorly understood. Here, we identified an FBXL3 T183M missense mutation whose allele frequency differed markedly between year-round-estrous and seasonally breeding sheep, and validated its association with seasonal reproduction in a sheep population. Functional analyses in mutant mice showed that this variant lengthened the circadian period, disrupted the expression of core clock genes, and weakened the interaction between FBXL3 and CRY1. These findings suggest that the FBXL3 T183M variant impairs day-length perception, thereby modulating seasonal estrus in sheep. Our study reveals a conserved circadian mechanism underlying seasonal breeding and highlights FBXL3 T183M as a promising genetic target for improving reproductive performance in sheep.

genetics↗

bioRxiv2026

Unlocking Your Programmable and Creative RNA Sequence Designer with RDiffusion

RNA, a pillar of the central dogma, has shaped three billion years of evolution. Despite cataloging tens of millions of non-coding RNAs and annotating millions, we have barely scratched the surface of the vast, unexplored RNA sequence space. Here, we introduce RDiffusion, a discrete-diffusion-based generative transformer model for RNA sequence design. Conditioned on diverse biological features, such as desired function, family type, secondary and tertiary structure, or binding protein partners, it can guide the generation of novel RNA sequences tailored to specific design specifications. We evaluate RDiffusion across a broad spectrum of RNA design tasks and find that it not only surpasses all baseline methods in design success rate and sequence diversity but also achieves advanced performance on downstream tasks. To demonstrate its translational potential, we applied RDiffusion with a customized seed-screening pipeline to de novo design therapeutic MicroRNA(miRNA) mimics in osteoarthritis (OA). This strategy identified mimic 0-4 as a lead candidate targeting SDC4 to preserve ECM homeostasis and cartilage integrity, with robust efficacy validated in clinical OA samples. Altogether, RDiffusion holds strong potential to serve as a cornerstone for RNA generation and representation learning, establishing a generalizable AI-driven paradigm for RNA therapeutic discovery.

bioengineering↗

bioRxiv2026

Spatial atlas of the ovary identifies molecular events in primordial follicle activation in humans

The human ovarian reserve is established prenatally, when granulosa cells encapsulate germ cells to form a pool of quiescent primordial follicles, that ultimately determines the female reproductive and endocrine lifespan. From birth to menopause, subsets of these quiescent follicles, located in the thin outer ovarian cortex, are activated and undergo a growth programme with progressive inward migration to the inner cortex, before either undergoing atresia or, during reproductive age, ovulation. Disruption of this process may lead to infertility, metabolic disorders and early menopause, yet early follicle development remains largely poorly understood. Here, we generate the most comprehensive single-cell and spatial multiomics atlas of the human pre- and postnatal ovarian cortex, integrating transcriptomic and chromatin profiles from over four million cells obtained from fetal and newly profiled pediatric and adult donors. We resolve the early granulosa cell trajectory at unprecedented resolution and identify a retinoic acid-associated regulatory switch accompanying follicle activation. We further show that stromal fibroblasts are not homogeneous, but instead form a dynamic scaffold establishing previously unrecognised morphogen and paracrine gradients that organise the cortex into functional niches supporting quiescent, growing, and atretic follicles. Finally, we identify ovarian lipid associated macrophages (oLAMs) that localise around follicles and are likely to support tissue remodelling during folliculogenesis. Together, this atlas provides a foundational blueprint for human ovarian development and homeostasis, and provides a framework for improving strategies in fertility preservation and in vitro follicle maturation.

cell biology↗

bioRxiv2026

Macrocycle screening against the C-terminal region of CHD4 uncovers its role as an interaction hub in the formation of the nucleosome remodeling and deacetylase complex

The Nucleosome Remodeling and Deacetylase complex (NuRD) plays a key role in regulating hemoglobin expression in adult erythroid cells. Selectively disrupting this complex potently induces the expression of fetal hemoglobin, a proven therapeutic strategy for treating beta-hemoglobinopathies such as sickle cell anemia. In these studies, we have used mRNA display to identify small macrocyclic peptides that inhibit the interaction between two core components of NuRD, the SANT-SLIDE domain of CHD4 and the CR2 domain of GATAD2A. In addition, the screen suggested a second binding site on the CHD4 domain. Based on this observation, we hypothesized and confirmed that CDK2AP1 bound to this region of CHD4, leading us to purify and determine the structure of the ternary complex between CHD4, GATAD2A, and CDK2AP1. The results of our studies show that the SANT-SLIDE domain of CHD4 functions as a critical interaction hub in the formation of NuRD and suggest a strategy to block NuRD function for therapy.

biophysics↗

bioRxiv2026

STITCH: Spatial Transcriptomics Imputation via Flow Matching with Internal Learning

AO_SCPLOWBSTRACTC_SCPLOWSpatial transcriptomics datasets frequently suffer from spatial gaps and missing regions due to sectioning artifacts, tissue damage, and the high cost of sequencing that limits tissue coverage. We present STITCH, a scalable and robust generative framework for multidimensional virtual spatial transcriptomics reconstruction. STITCH models intrinsic spatial-transcriptomic patterns directly from individual tissue samples, enabling reconstruction without requiring external reference atlases or matched histological image priors. The framework adopts a decoupled architecture that separates spatial morphology restoration from transcriptomic generation. STITCH first compresses high dimensional transcriptomic profiles into a low-dimensional latent representation through a spatial-aware graph autoencoder. For 3D cross-slice gaps, STITCH employs optimal transport-conditioned flow matching for spatial reconstruction, whereas 2D in-slice damage is repaired through an internal learning strategy. To generate the corresponding transcriptomic profiles, STITCH further establishes a point-wise conditional flow matching model in the latent space. This module achieves linear computational complexity, enabling continuous 3D atlas reconstruction of over 11 million cells within 5 hours on a single commodity GPU. Extensive evaluations across diverse spatial transcriptomics platforms, spanning both single-cell and spot-level technologies, demonstrate that STITCH consistently preserves transcriptomic identities, spatial topologies, and anatomical continuity. Overall, STITCH provides a scalable and platform-compatible computational framework for reconstructing high-resolution continuous spatial transcriptomic atlases.

bioinformatics↗

bioRxiv2026

Single-Cell Multi-Omics Dissection of Malignant Evolutionary Mechanisms and Construction of a Prognostic Model for Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) exhibits pronounced heterogeneity across WHO histological grades, yet systematic single-cell multi-omics studies characterizing these transitions remain limited. We integrated scRNA-seq and scATAC-seq data across ccRCC WHO grades to establish a multi-omics framework encompassing tumor cells and immune populations. Using pseudotime trajectory analysis and machine learning ensembles, we developed a prognostic signature (CBG) from core nodes of transcriptional regulatory networks. We found that in tumor cells, epigenetic alterations consistently precede metabolic reprogramming and invasive adaptation. CD8+ T cell exhaustion followed a trajectory shifting from IRF7- to ZNF683-regulated states, while monocytes differentiated toward M1 and M2 macrophages orchestrated by NFIC/IL1B and CEBPD/GLI2. Intercellular communication networks showed a temporal progression from inflammation, through vascular remodeling, to immunosuppression dominance. The CBG signature demonstrated robust performance in independent cohorts, identifying SLC11A1 and SH3YL1 as antagonistic survival determinants. This study elucidates the dynamic molecular and immunological mechanisms underlying ccRCC grade progression, providing a robust framework for subtype-specific prognostication and precision therapeutic targeting.

bioinformatics↗

bioRxiv2026

Ploidy shapes gemcitabine response through altered potency and delayed cell death

Aberrant tumor ploidy is a near-universal hallmark of cancer and increasingly recognized as a determinant of therapeutic response, but the mechanisms by which ploidy shapes sensitivity to specific cytotoxic agents remain unclear. Here, we investigated the relationship between ploidy and therapeutic response using pharmacogenomic reanalysis, isogenic cancer cell systems, live-cell imaging, intracellular pharmacokinetic/ pharmacodynamic (PK/PD) measurements, and mathematical modeling. Across public pharmacogenomic datasets, gemcitabine emerged as a low-ploidy-selective cytotoxic agent. In matched isogenic low- and high-ploidy cell systems, higher-ploidy cells were consistently less sensitive to gemcitabine across multiple lineages. Live-cell imaging and PK/PD measurements in near-diploid and near-tetraploid SUM-159 cells showed that both states formed intracellular dFdCTP, active form of gemcitabine; but, high-ploidy cells exhibited weaker and slower treatment responses, with delayed accumulation of cell death. To quantify these differences, we developed a delay-aware live/dead model driven by intracellular dFdCTP exposure. The model identified both reduced effective gemcitabine potency and a substantially longer delay from intracellular drug action to observed death in high-ploidy cells (17.5 hours in near-diploid cells versus 42.5 hours in near-tetraploid cells). Interpreting these fitted quantities alongside checkpoint signaling and metabolomic profiling suggests that high-ploidy cells convert intracellular gemcitabine exposure less efficiently into replication-stress signaling, nucleotide-metabolic disruption, and cytotoxic commitment. Together, these results establish ploidy as a determinant of both the magnitude and timing of gemcitabine response and provide a quantitative framework for linking intracellular drug exposure to delayed cytotoxic outcomes across ploidy states.

cancer biology↗

bioRxiv2026

Astrocytic μ-δ opioid receptor heterodimers mediate the antidepressant effects of ketamine's metabolite

A deeper understanding of the targets and mechanisms of fast-acting antidepressants, exemplified by ketamine, remains indispensable for better therapeutic strategies and understanding depression. Beyond the canonical neuron-centric NMDAR inhibition hypothesis, brain opioid system and glia-mediated processes are increasingly implicated in ketamines antidepressant efficacy, yet their precise contributions remain poorly understood. Here, we demonstrate that one major metabolite of ketamine, (2R,6R)-hydroxynorketamine (HNK), selectively targets -{delta} opioid receptor heterodimers (-{delta}-ORs) on astrocytes. By promoting the formation and/or stabilization of -{delta}-ORs, HNK engages Gs-coupled signaling, elevates intracellular cAMP, phosphorylates CREB (p-CREB) levels and Ca{superscript 2} dynamics in astrocytes, and consequently restores key astrocytic proteins and functions in depression models. Disrupting -{delta}-OR assembly or Gs signaling abolishes HNK-mediated antidepressant responses both in vitro and in vivo. Collectively, astrocytic opioid receptor heterodimers are critical to antidepressant responses and HNK may serve as a prototype compound for targeting astrocyte dysfunction across a wide range of brain disorders.

neuroscience↗

bioRxiv2026

MeCP2 is Necessary in Cerebellar Purkinje Cells for Precise Network Dynamics During Associative Motor Learning

Loss-of-function variants of MECP2 cause Rett syndrome; however, their impact on cerebellar computations for learning remains poorly understood. Here, we show that Mecp2 deletion specifically in Purkinje cells does not broadly disrupt cerebellar-dependent behaviors but selectively compromises those that require precise timing, coordination, and associative updating in the cerebellar cortex. Mecp2 loss altered the emergence of learning-related Purkinje cell activity in vivo and disrupted their intrinsic and synaptic properties that support adaptive cerebellar output. These findings identify MeCP2 as a critical player in Purkinje cell function to regulate cerebellar learning signals and suggest that Rett syndrome-related motor dysfunction reflects impaired adaptive computation rather than a generalized loss of motor capacity.

neuroscience↗

bioRxiv2026

An arthropod-specific TMEM16 protein accelerates olfactory response termination in Drosophila

Rapid termination of odor responses is essential for accurate olfactory coding in insects, where odorant receptors function as ligand-gated ion channels rather than G protein-coupled receptors. However, the mechanisms that restore olfactory receptor neuron (ORN) excitability after stimulation remain poorly understood. Here, we identify DmTMEM16O (CG6938), an arthropod-specific member of the TMEM16 (Anoctamin) family, as a key regulator of ORN response termination in Drosophila melanogaster. DmTMEM16O is highly enriched in Orco-positive ORNs in both larval and adult olfactory organs. Loss of DmTMEM16O prolongs odor-evoked neuronal activity, increasing decay time constants and causing persistent depolarization. DmTMEM16O mutant ORNs fail to resolve repeated odor stimulation and show impaired temporal coding, accompanied by reduced behavioral responses to both attractive and aversive odorants. Cell-specific rescue demonstrates that DmTMEM16O acts within ORNs to accelerate response termination. Although DmTMEM16O does not exhibit detectable Ca2+-activated chloride channel activity in heterologous cells, our results support a model in which it increases membrane conductance during the decay phase of the response, thereby shortening the membrane time constant and promoting rapid repolarization. This function is consistent with a role for chloride influx in insect ORNs, in contrast to mammalian systems where TMEM16B-mediated chloride efflux amplifies depolarization. Together, our findings identify DmTMEM16O as a lineage-specific regulator of ORN dynamics that enables precise temporal coding in insect olfaction.

physiology↗

bioRxiv2026

DOC Release and Physiological Response of Zostera marina Under Light and Nutrient Gradients

The seagrass bed, known as an important blue carbon ecosystem, not only has robust carbon sequestration capacity, but also releases the fixed organic carbon into the water column in the form of dissolved organic carbon (DOC). Zostera marina is the main constructive species of the seagrass meadows of northern China, but the regulatory mechanism of its DOC release in response to environmental changes still remains unclear. Adult Z. marina was used as the experimental material in this research to investigate the effects of light intensity and nutrient concentration on its DOC release, and to observe its physiological responses. By using a total organic carbon (TOC) analyzer, dissolved oxygen monitoring, transmission electron microscopy (TEM), and transcriptome analysis, we explored how light and nutrients affect DOC release and the underlying physiological mechanisms in Z. marina. The results showed that both elevated light intensity and short-term nutrient enrichment promoted organic carbon release from Z. marina to the environment. Increased light enhanced the net primary productivity (NPP) of Z. marina, while the magnitude of DOC release increased more than NPP itself. Nutrient enrichment reduced NPP while raising the proportion of DOC released by Z. marina. Transcriptome analysis showed that nutrient enrichment significantly affected pathways, including flavonoid biosynthesis and fatty acid degradation. This study demonstrated that changes in light and nutrients can significantly influence DOC release and carbon allocation patterns in Z. marina, providing a theoretical basis for blue carbon accounting and ecological restoration evaluation in seagrass beds.

plant biology↗