Biology subjects

Yang, Y.

Publications and source records attributed to Yang, Y..

At least 415 records · Page 23Linked to original sources

bioRxiv2025

Neural organoids protect engineered heart tissues from glucolipotoxicity by transferring versican in a co-culture system

Metabolic disorders could cause dysregulated glucose and lipid at the systemic level, but how inter-tissue/organ communications contribute to glucolipotoxicity is difficult to dissect in animal models. To solve this problem, myocardium and nerve tissues were modeled by 3D engineered heart tissues (EHTs) and neural organoids (NOs), which were co-cultured in a generalized medium with normal or elevated glucose/fatty acid contents. Morphology, gene expression, cell death and functional assessments detected no apparent alterations of EHTs and NOs in co-culture under normal conditions. By contrast, NOs significantly ameliorated glucolipotoxicity in EHTs. Transcriptomic and protein secretion assays identified the extracellular matrix protein versican as a key molecule that was transferred from NOs into EHTs in the high-glucose/fatty acid condition. Recombinant versican protein treatment was sufficient to reduce glucolipotoxicity in EHTs. Adeno-associated virus-delivered versican overexpression was sufficient to ameliorate cardiac dysfunction in a murine model of diabetic cardiomyopathy. These data provide the proof-of-concept evidence that inter-tissue/organ communications exist in the co-culture of engineered tissues and organoids, which could be systemically studied to explore potential pathological mechanisms and therapeutic strategies for multi-organ diseases in vitro.

cell biology↗

bioRxiv2025

Phosphorylation of the α subunit inhibits proteasome assembly and regulates cell division in archaea

Archaea of the order Sulfolobales possess a eukaryotic-like cell division machinery and display a eukaryotic-like cell cycle, however, the cell division and cell cycle control mechanisms remain enigmatic. Here, we demonstrate that phosphorylation of the subunit by a eukaryotic-like protein kinase ePK2 affects 26S proteasome assembly and controls cell division in Saccharolobus islandicus. ePK2 exhibits cell cycle-dependent expression at both transcriptional and translational levels. Deletion or overexpression of ePK2 results in impaired cytokinesis, with the deletion cells being unable to generate single chromosome cells after synchronization and the overexpression cells exhibiting growth retardation and cell enlargement. Interestingly, overexpression of ePK2 leads to a coherent reduction in cellular proteasome activity and degradation of cell division proteins. We identify S200 and T213 of the proteasome subunit as specific target sites for ePK2 phosphorylation. Functional and structural analyses of site-directed mutants at S200 and T213 suggest that S200 phosphorylation disrupts the assembly of 20S into 26S proteasome whereas T213 phosphorylation interferes the de novo ring assembly. Collectively, our study uncovers an ingenious and efficient mechanism of proteasome phosphorylation-mediated cell division regulation, a prototype of the eukaryotic cell cycle regulation system, in Sulfolobales archaea.

microbiology↗

bioRxiv2025

Longitudinal deep phenotyping in a mouse model of West syndrome reveals temporal dynamics of synapse remodeling, gliosis, and proteomic and lipidomic changes during seizure evolution

Neurodevelopmental disorders can have long-lasting effects, causing not only early pediatric symptoms but also a range of neurological issues throughout adulthood. West syndrome is a severe neurodevelopmental disorder marked by infantile spasms, an early symptom that typically subsides with age. However, many patients progress to other seizure forms, known as seizure evolution, which is closely linked to poor long-term outcomes. Despite its clinical significance, the neurobiological mechanisms behind seizure evolution in West syndrome remain poorly understood. Recent genetic studies have consistently identified the CYFIP2 p.Arg87Cys variant in West syndrome patients, and the Cyfip2+/R87C mouse model carrying this mutation has been shown to recapitulate key symptoms of the disorder, including infantile spasms. In this study, we aimed to gain deeper insight into seizure evolution by conducting longitudinal deep phenotyping of the Cyfip2+/R87C mouse model from the neonatal stage to seven months of age. We tracked seizure activity through behavioral and EEG recordings and employed multi-omic analyses, including tissue and single-cell level transcriptomics, ultrastructural analysis, proteomics, and lipidomics, to capture a comprehensive view of molecular and cellular changes. Our results showed that after an initial period of neonatal spasms, Cyfip2+/R87C mice entered a seizure-free phase, followed by spontaneous recurrent seizures in adulthood, ultimately leading to premature death. This progression was associated with synaptic remodeling, sequential activation of different glial cell types, lipid droplet accumulation in astrocytes, and significant proteomic and lipidomic changes in the brain. These findings suggest that seizure evolution in West syndrome involves complex, time-dependent interactions between neurons and glial cells, along with alterations in lipid metabolism. Our study highlights the potential of longitudinal multi-omic approaches to uncover underlying mechanisms of seizure evolution and suggests that targeting these changes could offer novel therapeutic strategies. Additionally, the dataset generated here may provide valuable insights for other epilepsy and neurodevelopmental disorder models.

neuroscience↗

bioRxiv2025

FASN Inactivation-induced Progranulin (GRN) Expression Promotes Lysosome-dependent Cell Death to Suppress Leukemogenesis

Cancer cells rely on lipogenesis in addition to exogenous lipid uptake, and fatty acid synthase (FASN) is aberrantly overexpressed in myeloid leukemia. However, the precise role of FASN in leukemogenesis in vivo remains elusive. Here, we demonstrated that FASN is essential for leukemogenesis. Ablation of FASN impeded leukemic cell growth, survival, clonogenicity in vitro, and the leukemic burden in vivo. Conditional knockout of FASN barely affected hematopoiesis but significantly attenuated the leukemic progression of MLL-AF9 transplants. By screening a library of platensimycin derivatives, we identified compound MS-C19 as a potent FASN inhibitor. Pharmacological targeting of FASN by MS-C19 suppressed leukemic cell growth and clonogenicity in clinical AML blasts. Mechanistically, both MS-C19 treatment and FASN deficiency triggered the activation of lysosomal and inflammatory gene expression. Loss of FASN led to lysosomal membrane permeabilization and subsequent lysosome-associated cell death, but not lysosome biogenesis. We further identified that GRN, a lysosomal and neuroinflammatory gene, was potently transcribed by TFEB upon FASN loss. Depletion of GRN significantly reversed the inhibitory effects caused by FASN knockdown. Our work demonstrates that FASN is a therapeutic target for myeloid leukemia, and inactivation of FASN by the lead compound MS-C19 provides an alternative approach for leukemic intervention. Key PointsO_LIGenetic ablation of FASN induces apoptosis, impedes leukemia cell growth, and improves the survival of leukemic xenografts. C_LIO_LITargeting FASN by the compound MS-C19, a derivative of the natural microbe antibiotic platensimycin, reduces the cell survival of leukemic cell lines, the clinical leukemic blasts, and MLL-AF9 transformed murine leukemic cells. C_LIO_LIFASN inhibition induces lysosome-dependent cell death that relies on Progranulin (GRN) expression. C_LI

cancer biology↗

bioRxiv2025

Differential DNA damage response to WRN inhibition identifies a targetable vulnerability in ARID1A-mutated cancers

ARID1A, a key subunit of the SWI/SNF chromatin remodeling complex, is frequently mutated in cancers. However, effective clinical treatments for patients with this mutation are limited, highlighting a demand for new therapeutic strategies. Here, we establish Werner syndrome ATP-dependent helicase (WRN) as a critical vulnerability target in ARID1A-mutated cancers. Upon genetic and pharmacological inhibition of WRN, ARID1A-mutated cells had defective Chk1-mediated DNA damage signaling, resulting in compensatory Chk2 activation, leading to G1-phase arrest and apoptosis, whereas ARID1A-proficient cells underwent Chk1-dependent G2/M arrest. Additional p21 inhibition, combined with WRN suppression, drove G1-arrested cells to re-enter the cell cycle, triggering mitotic catastrophe. The anti-tumor efficacy of WRN inhibition was validated using in vivo cell lines and patient-derived xenograft mouse models. Our findings define WRN as a selective therapeutic target in ARID1A-mutated cancers and suggest a combinatorial strategy of WRN and p21 inhibition as a therapeutic approach.

cancer biology↗

bioRxiv2025

Metabolic reprogramming of protists within the microbiome of sinking particles

Protists play a crucial role in the biological carbon pump, yet their metabolic activity and function in sinking particles, which drive the aggregation and degradation of organic carbon, remains poorly characterized. Here, we examined transcriptional dynamics of protists in sinking and suspended particles collected by marine snow catcher in the Oyashio region to explore active lineages and their function during the sinking export. We found taxon-specific metabolic variations, with suspended particles showing up-regulated transcripts from diatoms, haptophytes, and chlorophytes, while sinking particles exhibited those from diatoms, ciliates, and dinoflagellates. Our data further revealed niche-dependent cellular metabolic reprogramming. The small diatoms Minidiscus variabilis and Thalassiosira oceanica upregulated more genes in suspended particles, while the chain-forming Thalassiosira rotula overexpressed more genes in sinking particles. The activity of both phototrophic and heterotrophic protists in sinking particles suggests the export of fresh organic carbon, with heterotrophic protists driving its degradation. Notably, the dinoflagellates Karlodinium veneficum and Karenia brevis exhibited significantly upregulated genes related to feeding and carbon metabolism in sinking particles. Additionally, the activity of RNA viruses was positively correlated with carbon flux. Overall, our study highlights the critical role of large-celled diatoms, heterotrophic dinoflagellate, ciliates and RNA viruses in organic carbon aggregation and degradation.

microbiology↗

bioRxiv2025

Locus Coeruleus to Medial Prefrontal Cortex Noradrenergic Neural Circuit Modulates States of Consciousness during Sevoflurane Anesthesia in Mice

How exactly does general anesthesia achieve its effects? It is so widely used in surgeries and medical treatments to enhance comfort for nearly one hundred years, yet its precise mechanisms underlying the loss and recovery of consciousness still remain unclear. Utilizing a variety of research methods-pharmacological, optogenetic, chemogenetic, fiber photometry, and gene knockdown approaches-our study has shed light on the significant modulatory function of locus coeruleus noradrenergic neurons during the transition from sevoflurane anesthesia to awakening. Furthermore, the activation of the LC-mPFC circuit has been found to have a substantial arousal effect, with 1-AR playing a crucial role in this process. Additionally, GABAA-R has been identified as the key binding site for sevoflurane within the locus coeruleus. These findings collectively offer novel insights into the neural network mechanisms underlying general anesthesia, advancing our understanding of this complex medical phenomenon.

neuroscience↗

bioRxiv2025

A high-throughput platform for biophysical antibody developability assessment to enable AI/ML model training

Antibodies must bind their targets with high affinity and specificity to achieve useful therapeutic activity. They must also possess suitable developability properties (e.g., thermostability, solubility, viscosity, polyreactivity) to ensure favorable manufacturing, formulation, and in vivo performance. Both binding and developability properties are inherent to a given antibody amino acid sequence. Identification or selection of antibodies possessing suitable binding characteristics is now routine, and de novo computational design models, trained on extensive complementarity-determining region sequence and structural data, are rapidly improving. Developability properties, however, remain difficult to predict largely due to insufficient training data, with empirical testing being heavily used to avoid challenges in late-stage antibody development. To fill this gap, we built a high-throughput antibody developability assay platform designed to generate the large datasets needed to train improved machine learning (ML) models. We optimized and automated known developability assays [Jain et al., 2017], and developed a robust integrated data analytics pipeline. Here we report data on 246 antibodies--representing 106 approved, 135 clinical-stage, and 5 preregistration/withdrawn molecules--across a panel of 10 developability assays, in a "tidy data" format suitable for AI/ML modeling. We used these data to develop an XGBoost [Chen et al., 2016] ML model that better predicts similarity to approved antibodies compared to conventional use of developability warning thresholds. Additionally, we confirm that preliminary predictive models do improve with more training data. Our high-throughput PROPHET-Ab platform enables data generation at the scale needed to develop improved ML models to predict antibody developability. SignificanceSuccessful antibody drugs exhibit important "developability" properties, beyond tight and specific binding to their target, including high expressibility, high stability and solubility, low aggregation propensity, low viscosity, low polyreactivity, and long in vivo half-life. Collectively, developability properties predict favorable manufacturing, storage, administration, and safety, and deficiencies in these properties increase risk for clinical failure. Despite progress in developing machine learning models to predict structure and binding, antibody developability models lag, largely due to a lack of sufficiently large training datasets. We have built a high-throughput platform, PROPHET-Ab, that enables data generation at the scale needed to train improved AI/ML models to predict antibody developability.

biophysics↗

bioRxiv2025

Dimethyl fumarate reprograms cervical cancer cells to enhance antitumor immunity by activating mtDNA-cGAS-STING pathway

BackgroundCervical cancer (CC) remains a significant global health challenge for women, especially in advanced stages where effective treatments are limited. Current immunotherapies, including PD-1/PD-L1 blockades and adoptive T cell therapies, show limited response rates and durability. Dimethyl fumarate (DMF), an FDA-approved drug for autoimmune diseases, has demonstrated that it might exhibit direct antitumor activity in several cancers. However, its influence on anti-tumor immunity and its function in CC remain poorly understood. This study aims to investigate the therapeutic potential of DMF in CC models and elucidate its underlying mechanisms of action. MethodsCC cell lines and mouse models were treated with DMF. Transcriptional level changes in cervical cancer cells following DMF treatment were analyzed by RNA-seq. Mitochondrial DNA (mtDNA) release, and cGAS-STING activation were assessed via qPCR, immunofluorescence, immunoblotting and ELISA. CD8+ T cell recruitment was analyzed by flow cytometry. Combinatorial therapies (DMF + anti-PD-1/TILs) were tested in syngeneic or patient-derived xenografts (PDX) models. ResultsDMF treatment induces mitochondrial dysfunction in tumor cells, resulting in the release of mtDNA into the cytosol. The cytosolic mtDNA activates the cGAS-STING-TBK1 pathway and type I interferon response, leading to the secretion of CCL5 and CXCL10, thereby enhancing CD8 T cell infiltration. Additionally, DMF exhibits synergistic effect with PD-1 blockade in murine CC model, and can enhance the therapeutic efficacy of adoptively transferred T cells toward CC patient-derived xenografts model. ConclusionThis work elucidated that DMF reprograms CC cells to activate the mtDNA-cGAS-STING pathway, fostering a chemokine-rich microenvironment that recruits CD8+ T cells. Its synergy with PD-1 blockade or TIL therapy underscores its potential as an immunomodulatory adjuvant. These findings suggest that DMF holds promise as a novel immunotherapeutic strategy for improving clinical outcomes in CC.

immunology↗

bioRxiv2025

Hypoxia Exacerbates Kir2.1 Channel Dysfunction in an Andersen-Tawil Syndrome Variant Through a SUMO-Dependent Mechanism

BackgroundAndersen-Tawil Syndrome type 1 (ATS1) is a multisystem channelopathy that predisposes patients to ventricular dysrhythmias and increases the risk of sudden cardiac death. ATS1 arises from loss-of-function mutations in Kir2.1, the inward rectifying potassium channel responsible for most of IK1 in ventricular cardiomyocytes. IK1 is suppressed by SUMOylation, a post- translational modification upregulated in hypoxia, a known proarrhythmic stimulus. We investigated whether current from the ATS1-linked variant Kir2.1-R67Q is inhibited by hypoxia and whether this suppression can be reversed by pharmacological inhibition of the SUMO pathway. MethodsWe used patch-clamp recording to measure IK1 and Kir2.1 currents under acute hypoxia, with and without the SUMO pathway inhibitor TAK-981. To quantify SUMOylation stoichiometry, we applied single molecule photobleaching. A multidisciplinary approach combining electrophysiology, molecular modeling, and optogenetic phosphoinositide was used to measure the impact of Kir2.1- R67Q and SUMOylation on channel interactions with phosphatidylinositol 4,5-bisphosphate (PIP2), a required gating cofactor. ResultsKir2.1 can be modified by up to two SUMO proteins attached to diagonally opposite subunits, with each SUMOylation event reducing current by [~]20%. Heterozygouse channels containing two R67Q subunits were more susceptible to hypoxic suppression than wild type. TAK-981 blocked hypoxic inhibition of IK1 in ventricular cardiomyocytes and abolished Kir2.1 SUMOylation. In cells expressing Kir2.1-R67Q, TAK-981 significantly increased currents and mitigated hypoxic suppression. Computational modeling and optogenetic dephosphorylation revealed that both the R67Q mutation and converge to disrupt Kir2.1- PIP2 interactions, producing synergistic inhibition of channel function. ConclusionsHypoxia-induced SUMOylation and the R67Q mutation synergistically suppress Kir2.1 activity by impairing channel-PIP2 interactions. TAK-981 restores IK1 by preventing SUMOylation under hypoxic conditions and enhancing current through Kir2.1-R67Q channels. These findings support a two-hit model of arrhythmogenesis in ATS1 and identify SUMO pathway inhibition as a potential therapeutic strategy to reduce arrhythmic risk in affected patients.

physiology↗

bioRxiv2025

Identification of Raptor and GLI1 as USP37 substrates highlight its context-specific function in medulloblastoma cells.

USP37 gene encodes a deubiquitylase (DUB), which catalyzes the proteolytic removal of ubiquitin moieties from proteins to modulate their stability, cellular localization or activity. Its expression is downregulated in a subgroup of medulloblastomas driven by constitutive activation of sonic hedgehog (SHH) signaling. Patients with SHH-driven medulloblastomas with elevated expression of the RE1 silencing transcription factor (REST) and reduced expression of USP37 have poor outcomes. In previous studies, we showed sustained proliferation of SHH-medulloblastoma cells due to blockade of terminal cell cycle exit and neuronal differentiation stemming from a failure in USP37-dependent stabilization of its target, the cyclin-dependent kinase inhibitor (CDKI)-p27. This finding suggested a tumor suppressive function for USP37. Interestingly, the current study also uncovered Raptor, a component of the mTORC1 complex, as a novel target of USP37. Under conditions of low-USP37 expression, reduced Raptor stability and mTORC1 activity caused a decline in phosphorylation of 4E-binding protein 1 (4EBP1) and increased its interaction with eukaryotic elongation factor 4E (eIF4E), which is known to inhibit CAP-dependent translation initiation. Surprisingly, a subset of patients with SHH-driven medulloblastomas with elevated expression of USP37 and the Glioma associated Oncogene 1 (GLI1), also exhibited poor outcomes. Using genetic and biochemical analyses, we showed that USP37-mediated stabilization of GLI1, a terminal effector of SHH signaling, increases pathway activity and upregulates expression of its target oncogene products, NMYC and CCND1, to drive cell proliferation. These data indicate that USP37 elevation in SHH-driven medulloblastomas has the potential to promote non-canonical activation of SHH signaling. Overall, our findings suggest that USP37 may have context-specific oncogenic and tumor suppressive roles in medulloblastoma cells.

cancer biology↗

bioRxiv2025

Collagen Nanofiber Reinforced Alginate Hydrogel Tube Microbioreactors for Cell Culture

The large-scale production of mammalian cells is pivotal for various applications; however, current bioreactor technologies encounter significant technical and economic challenges. Scaling up cell cultures remains problematic due to excessive cell aggregation, shear stress-induced cell death, batch-to-batch inconsistencies, and limited scalability. We propose that engineering a cell-friendly microenvironment can enhance culture efficiency. Previously, we developed alginate hydrogel microtubes (AlgTubes) that significantly improved cell density and growth rates. Nevertheless, AlgTubes lack adhesion sites essential for anchorage-dependent cells and frequently break, causing cell leakage and production inconsistencies. To address these limitations, this study reinforced AlgTubes with collagen nanofibers, creating collagen-alginate hybrid hydrogel microtubes (ColAlgTubes). Utilizing a novel micro-extruder, we efficiently produced cell-loaded ColAlgTubes. Collagen formed a dense nanofiber network interwoven with the alginate mesh, enhancing the hydrogels mechanical properties while providing cell adhesion sites. ColAlgTubes protected cells from hydrodynamic stress and maintained cell mass within a 400 m diameter, ensuring efficient nutrient exchange and waste removal. This optimized microenvironment resulted in high cell viability, rapid proliferation, and exceptional yields of 5x108 cells/mL - 200 times higher than conventional culture methods. With their scalability, cost-effectiveness, and efficiency, ColAlgTubes offers a transformative solution for large-scale cell production with broad applications in biotechnology, regenerative medicine, and therapeutic manufacturing.

bioengineering↗

bioRxiv2025

MiT4SL: multi-omics triplet representation learning for cancer cell line-adapted prediction of synthetic lethality

Synthetic lethality (SL) offers a promising approach for targeted cancer therapies. Current SL prediction models heavily rely on extensive labeled data for specific cell lines to accurately identify SL pairs. However, a major limitation is the scarcity of SL labels across most cell lines, which makes it challenging to predict SL pairs for target cell lines with limited or even no available labels in real-world scenarios. Furthermore, gene interactions could be opposite between training and test cell lines, i.e. SL vs. non-SL, which further aggravates the challenge of generalization among cell lines. A promising strategy is to transfer knowledge learned from cell lines with relatively abundant SL labels to those with limited SL labels for the discovery of novel SL pairs, i.e., cell line-adapted SL prediction. Here, we propose MiT4SL, a multi-omics triplet representation learning model for cell line-adapted SL prediction. The core idea of MiT4SL is to model cell lineage information as embeddings, which are generated by combining a protein-protein interaction network representation tailored to each cell line with the corresponding protein sequence embeddings. We then combine these cell line embeddings with gene pair representations derived from a biomedical knowledge graph and protein sequences. This triplet representation learning strategy enables MiT4SL to capture both shared biological mechanisms across cell lines and those unique to each cell line, effectively mitigating distribution shift and improving generalization to target cell lines. Additionally, explicit cell line embeddings provide the necessary signals for MiT4SL to effectively differentiate between cell line contexts, enabling it to adjust predictions and mitigate possible label conflicts for the same gene pair across different cell lines. Experimental results across various cell line-adapted scenarios show that MiT4SL outperforms six state-of-the-art models. To the best of our knowledge, MiT4SL is the first deep learning model designed specifically for cancer cell line-adapted SL prediction. AvailabilityThe code of our work is available at https://github.com/JieZheng-ShanghaiTech/MiT4SL.

bioinformatics↗

bioRxiv2025

BioMiner: A Multi-modal System for Automated Mining of Protein-Ligand Bioactivity Data from Literature

Protein-ligand bioactivity data published in the literature are essential for drug discovery, yet manual curation struggles to keep pace with rapidly growing literature. Automated bioactivity extraction remains challenging because it requires not only interpreting biochemical semantics distributed across text, tables, and figures, but also reconstructing chemically exact ligand structures (e.g., Markush structures). To address this bottleneck, we introduce BO_SCPLOWIOC_SCPLOWMO_SCPLOWINERC_SCPLOW, a multi-modal extraction framework that explicitly separates bioactivity semantic interpretation from ligand structure construction. Within BO_SCPLOWIOC_SCPLOWMO_SCPLOWINERC_SCPLOW, bioactivity semantics are inferred through direct reasoning, while chemical structures are resolved via a chemical-structure-grounded visual semantic reasoning paradigm, in which multi-modal large language models operate on chemically grounded visual representations to infer inter-structure relationships, and exact molecular construction is delegated to domain chemistry tools. For rigorous evaluation and method development, we further establish BO_SCPLOWIOC_SCPLOWVO_SCPLOWISTAC_SCPLOW, a comprehensive benchmark comprising 16,457 bioactivity entries curated from 500 publications. BO_SCPLOWIOC_SCPLOWMO_SCPLOWINERC_SCPLOW validates its extraction ability and provides a quantitative baseline, achieving an F1 score of 0.32 for bioactivity triplets. BO_SCPLOWIOC_SCPLOWMO_SCPLOWINERC_SCPLOWs practical utility is demonstrated via three applications: (1) extracting 82,262 data from 11,683 papers to build a pre-training database that improves downstream models performance by 3.9%; (2) enabling a human-in-the-loop workflow that doubles the number of high-quality NLRP3 bioactivity data, helping 38.6% improvement over 28 QSAR models and identification of 16 hit candidates with novel scaffolds; and (3) accelerating protein-ligand complex bioactivity annotation, achieving a 5.59-fold speed increase and 5.75% accuracy improvement over manual workflows in PoseBusters dataset. BO_SCPLOWIOC_SCPLOWMO_SCPLOWINERC_SCPLOW and BO_SCPLOWIOC_SCPLOWVO_SCPLOWISTAC_SCPLOW provide a scalable extraction methodology and a rigorous benchmark, paving the way to unlock bioactivity data that previously required extensive human effort. All data and code are available at GitHub.

bioinformatics↗

bioRxiv2025

Saccades orchestrate intraocular glucose to shape visual responses in birds

Birds exhibit remarkable vision despite lacking the typical network of blood vessels in their eyes. The characteristic poses a long-standing question about how avian retinas fulfill high energy demands necessary for sight. Here we show that natural, rhythmic eye movements, known as oscillatory saccades, orchestrate intraocular metabolic dynamics and attention-guided visual processing in pigeons. In a series of integrated experiments, we monitored eye movements along with glucose levels in the eye and neuronal activity in key brain regions receiving direct input from the retina. We found that these saccades generate fluctuations in intraocular glucose concentrations, closely linked to changes in neuronal visual responses over timescales of seconds to minutes. Moreover, pharmacological manipulations that altered glucose availability and eliminated these oscillatory saccades resulted in corresponding shifts in neuronal responses, demonstrating a causal linkage between oscillatory saccades, metabolic regulation, and visual processing. These findings reveal a mechanism by which birds actively evoked saccades during attention-driven information gathering, propelling retinal metabolism and facilitating their vision in the absence of retinal vasculature. This study underscores the interplay among eye movements, metabolic regulation, and high-level visual performance, suggesting broader implications for how eye movements contribute to retinal health, attention, and visual function across species.

neuroscience↗

bioRxiv2025

A surprising link between cognitive maps, successor-relation based reinforcement learning, and BTSP

Recent recordings from the hippocampus of the human brain suggest that after a few presentations of sequences of unrelated natural images, correlations between emergent neural codes encode the sequential structure of these sequences. We show that this learning process, which is consistent with experimental data on BTSP (Behavioral Time Scale Synaptic Plasticity), creates a cognitive map that enables online-generation of plans for moving to any given goal, both in spatial environments and in abstract graphs. Furthermore, the resulting neural circuits and plasticity rules provide a biologically plausible implementation of Successor Relation based Reinforcement Learning. In addition, this brain-derived approach for learning cognitive maps provides a blueprint for implementing autonomous learning through on-chip plasticity in energy-efficient neuromorphic hardware.

neuroscience↗

bioRxiv2025

Senescence-induced reparative fibroblasts enable scarless wound healing in aged murine skin.

It has been reported that elderly individuals exhibit reduced scarring during the wound healing process compared to younger adults. However, the underlying mechanisms responsible for this phenomenon remain poorly understood. Here, we revealed that aged mice exhibited more pronounced regenerative outcomes compared to young mice, characterized by increased hair follicle numbers and collagen fiber features closer to normal skin. Single-cell sequencing identified a reparative fibroblast subpopulation (Prss35+Fib) enriched in the aged group, which promotes regeneration through communication with epithelial cells, macrophages, and T cell subpopulations via PTN and EREG signaling. Spatial transcriptomics validated this communication pattern by elucidating cell proximity and locating the regenerative niche in the upper dermis. Finally, EREG treatment significantly enhanced regenerative outcomes in young mice, while the small wound model of aged mice, lacking the reparative fibroblast and EREG signaling, failed to achieve regeneration. Collectively, our findings advance the understanding of regenerative plasticity in aging and provide new insights for designing scarless therapeutic strategies.

cell biology↗

bioRxiv2025

Heritability of human lifespan is about 50% when confounding factors are addressed

The heritability of human lifespan is a fundamental question in biology. Current estimates of heritability are low - twin studies show that about 20-25% of the variation in lifespan is explained by genetics, and some large family pedigree studies suggest it is as low as 7%. However, these studies do not distinguish between deaths driven by intrinsic biological processes and deaths caused by extrinsic factors such as accidents or infections. Here we use mathematical modeling and analyses of twin cohorts raised together and apart to show that extrinsic mortality skews heritability estimates by driving down measured lifespan correlations among twin pairs. We also identify a nonlinear effect of the cutoff age--the minimum age of death included in each study -- on estimates of heritability. Correcting for these factors more than doubles previous estimates, revealing that intrinsic heritability of human lifespan is above 50%. Such high heritability is similar to most other complex human traits. We thus challenge the consensus that genetics has only a minor effect on lifespan and show that genes explain the majority of lifespan variation. Since genes are important, understanding the genetics of longevity can reveal aging mechanisms and inform medicine and public health.

genetics↗