Biology subjects

Zhang, H.

Publications and source records attributed to Zhang, H..

At least 217 records · Page 12Linked to original sources

bioRxiv2026

Wetting-mediated extracellular phase separation drives long-range cell adhesion

Cells must efficiently locate and engage for tissue formation and immune coordination, yet classical receptor-ligand binding is limited to nanometre distances and is inherently slow [1-3]. Here, we uncover a previously unrecognised physical principle, liquid-like adhesion by phase separation (LAPS). This process creates dynamic wetting layers on cell surfaces [4, 5], functioning as "liquid bridges" that enable robust, long-range cell capture across tens of micrometres. Remarkably, this wetting-mediated attraction remains effective at nanomolar concentrations--conditions where bulk phase separation would not be expected--and facilitates high-fidelity cell sorting through competitive wetting. By integrating aqueous two-phase systems, endogenous proteins (Galectin-3, CCL5), and fluid-particle-dynamics simulations [6], we demonstrate that extracellular liquid-liquid phase separation not only mediates long-range cell capture but also acts as a physical catalyst for contact-dependent signaling. These findings establish extracellular phase separation as a key physical principle complementing molecular recognition in multicellular systems, offering new opportunities for understanding immune response, tissue morphogenesis, and therapeutic strategies targeting the extracellular environment [7, 8].

biophysics↗

bioRxiv2026

Small brown planthopper infestation enhances it reproduction and insecticide tolerance by manipulating glucose distribution and levels in rice

The evolutionary arms race between plants and insects involves not only direct defense and counter-defense but also sophisticated resource manipulation. However, how herbivorous insects respond to host nutritional signals to modulate their fitness traits remains unclear. This study investigates how the small brown planthopper (SBPH, Laodelphax striatellus) manipulates host plant carbohydrate allocation, and to elucidate the molecular mechanisms by which the acquired glucose enhances SBPH fecundity and insecticide tolerance. Using molecular, pharmacological, and biochemical approaches, we found that SBPH infestation induced systemic carbohydrate reallocation in rice, elevating whole-plant glucose levels by promoting aerial accumulation while depleting root reserves. Host-derived glucose enhanced SBPH fecundity by activating the target of rapamycin (TOR) pathway, upregulating juvenile hormone (JH) signaling, and increasing vitellogenin production. For imidacloprid tolerance, glucose boosted glutathione S-transferase (GST) activity via two synergistic mechanisms: by upregulating glutamate cysteine ligase (GCL) to increase glutathione synthesis, and transcriptionally via the glucose-TOR-JH axis to induce LsGSTe1 (SBPH epsilon class GST) and LsGSTo1 (SBPH omega class GST) expression. Our findings establish host-derived glucose as a central signaling molecule that SBPH utilizes to modulate conserved pathways for simultaneous optimization of reproduction and insecticide resistance. This reveals a multifaceted nutrient-responsive mechanism in insect pests and identifies the glucose-TOR-JH axis as critical molecular targets for developing nutrient-based pest control strategies, such as disrupting insect nutrient-sensing pathways or modulating host carbohydrate metabolism. HighlightsO_LISBPH infestation elevates whole-plant glucose levels by promoting aerial accumulation while suppressing root abundance. C_LIO_LISBPH-induced glucose in the rice aerial tissues boosts reproduction of SBPH via TOR-JH-Vg pathway. C_LIO_LISBPH-induced glucose in the rice aerial tissues enhances imidacloprid tolerance of SBPH through GCL-GSH-GST and TOR-JH-GST axis. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=152 SRC="FIGDIR/small/701313v2_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@39e084org.highwire.dtl.DTLVardef@1c310cborg.highwire.dtl.DTLVardef@1838575org.highwire.dtl.DTLVardef@1aedebe_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2026

A conserved and predictable pluripotency window in callus unlocks efficient transformation in grasses and beyond

A major bottleneck in plant biotechnology is the inefficient and genotype-dependent regeneration of callus, which severely limits genetic transformation and functional studies across many species. This barrier is acutely exemplified in the study of beneficial plant-microbe interactions, such as the Epichloe-grass symbiosis--a system conferring remarkable stress tolerance to its host but hindered by a lack of efficient genetic tools. To address this, we established a chromosome-scale genome for an Epichloe native host grass Achnatherum inebrians. We discovered that the expression dynamics of evolutionarily conserved cell pluripotency regulators (CPRs) including ARF5/7/19, BBM, WUS/WOX5 and CUC1/2 serve as a precise molecular predictor for callus regenerative capacity, revealing that pluripotency is dynamic and peaks within a narrow, definable time window. Harnessing this predictable window enabled the development of a highly efficient transformation system for A. inebrians (49.4% efficiency). Crucially, this CPR-based strategy proved generalizable: applied to wheat and the legume sainfoin, it pinpointed species-specific optimal regeneration windows, boosting shoot regeneration rates to 65.7% and 87.5%, respectively. Collectively, our work provides an integrated research system and a rational design principle that removes a key barrier to uncovering molecular mechanisms in plant systems, particularly the Epichloe-enhanced stress tolerance symbiosis.

plant biology↗

bioRxiv2026

Inhalable Polymeric Nanoparticle Vaccine for Lysosome-targeting Co-delivery of Antigen and Adjuvant with Enhanced Immunoprotection

Conventional subunit vaccines suffer from premature clearance and poor synchronization of antigen and adjuvant, limiting coordinated immune activation. Here, we develop an amphipathic polymer (YAXA) with acid-labile imine bonds for acid-sensitive degradation and terminal NHS-activated esters for antigen conjugation. YAXA is co-assembled with hydrophobic TLR7 agonist 3M-052 and conjugated to protein antigen, forming nanoparticle vaccine YM3.7. Following aerosolized intratracheal inoculation into the lung, YM3.7 is efficiently internalized by antigen-presenting cell and trafficked into lysosome, where acidic conditions trigger its dissociation and co-release of antigen and adjuvant. This spatiotemporally synchronized delivery promotes robust immune activation, including cell maturation, germinal center formation, systemic and lung-resident B/T cell response, and IgG/sIgA production. In lethal pneumonia models induced by either Pseudomonas aeruginosa or Staphylococcus aureus, YM3.7 markedly improves survival over conventional antigen and adjuvant mixture. This study presents an inhalable nanoparticle platform that coordinately activates innate, humoral, mucosal, and cellular immunity for enhanced protection.

immunology↗

bioRxiv2026

Super-resolved, three-dimensional spatial transcriptomics reveals cell-type and brain-region-specific modulation of key epitranscriptomic switches following adolescent alcohol exposure

Epitranscriptomic mechanisms dynamically regulate neuronal function through gene expression, but their precise roles in neuropsychiatric and neurological disorders remain to be fully elucidated. A major obstacle to advancing such studies is the absence of a methodology for precise, cell-type and brain-region-specific quantification of critical epitranscriptomic regulators under these complex brain conditions. To overcome this challenge, we developed a super-resolved, three-dimensional spatial transcriptomics method to quantify key epitranscriptomic switches in intact brains. Using this method, we quantified the expression of Mettl3, an N6-methyladenosine (m6A) methyltransferase enzyme recently shown to be upregulated in the amygdala after adolescent intermittent ethanol (AIE) exposure in rats. We observed a significant increase in cytoplasmic Mettl3 mRNA in neurons, but not in astrocytes or microglia, within the adult central amygdala and the CA1 and dentate gyrus of hippocampus following AIE. In contrast, no significant changes were observed across neurons, astrocytes, or microglia within the basolateral amygdala or the hippocampal CA3. Additionally, we found both the cytoplasmic density and subcellular localization of Mettl3 mRNA were dependent on the specific cell types and brain subregions examined. These results suggest that AIE increases Mettl3 expression in a highly cell-type-specific and spatially heterogeneous manner, underscoring the necessity of high-resolution spatial transcriptomics methods for studying transcriptomic and epitranscriptomic regulations under neurological conditions. Significance StatementEpitranscriptomics plays a crucial role in neuronal functions by influencing the splicing, stability, and translation of genes. However, the exact role of epitranscriptomic mechanisms, such as m6A RNA methylation, in brain disorders remains unclear, particularly in a cell-type and circuitry-specific manner. Here we developed a super-resolved, three-dimensional spatial transcriptomics method and applied it to a model of alcohol exposure. We found differential cell-type- and brain-region-specific modulation of Mettl3, a key m6A enzymatic switch, across major brain regions following adolescent intermittent ethanol exposure in adulthood. Our findings, coupled with our pipeline, are expected to address existing methodological limitations and knowledge gaps, thereby accelerating brain transcriptomic and epitranscriptomic studies under various psychiatric and neurological conditions.

neuroscience↗

bioRxiv2026

Medication and Developmental Stage Shape the Brain-Age Gap in ADHD

Identifying robust biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD) remains challenging. The brain-age gap (BAG), which is the difference between predicted biological brain age and chronological age, has been proposed as a marker of atypical neurodevelopment, yet findings have been inconsistent across studies, limiting its clinical translation. We hypothesized that two major sources of heterogeneity, medication status and developmental stage, contribute to these discrepancies. To test this, we analyzed structural MRI data from a large multi-site cohort (N = 947; ages 7-26 years). Individuals with ADHD were stratified by medication history (medicated vs. unmedicated) and developmental stage (childhood vs. adolescence) and compared with matched typically developing controls. We estimated global- and network-level BAG using publicly available pretrained models. Our results revealed that BAG differences were contingent on medication status, with abnormalities predominantly observed in unmedicated individuals. Developmental stage further moderated the presence of this effect: BAG abnormalities were present significantly in children with ADHD but not in adolescents. Network-level analyses demonstrated spatial specificity, with significant effects in visual, ventral attention, and dorsal attention networks. Together, these findings provide compelling evidence that BAG in ADHD is both medication- and development-dependent, highlighting the need to account for treatment exposure and developmental stage when evaluating BAG as a biomarker and further underscoring the importance of early intervention during childhood.

neuroscience↗

bioRxiv2026

Methanogenic archaea bolster mucosal homeostasis and protect from colitis

The intestinal microbiota profoundly shapes host homeostasis and disease, yet the role of Archaea, which comprise [~]10% of the anaerobic gut microbiota, is poorly understood. Here, we find that colonization of germ-free or conventional mice with the human methanogens Methanobrevibacter smithii (MSm) or Methanosphaera stadtmanae (MSt) enhances epithelial regeneration, mucus production, and regulatory T cell accumulation. These methanogens protect against chemically induced colitis, demonstrating a direct and beneficial role for Archaea in maintaining colonic health.

microbiology↗

bioRxiv2026

A reconfigurable DNA memory architecture for hierarchical data management via programmable phase transitions

DNA has emerged as a promising medium for the post-silicon era of information storage due to its ultrahigh density and longevity. However, current systems are bifurcated, with solid-state systems providing robust cold archival but lacking accessibility, while fluidic molecular computing systems offer dynamic processing but suffer from low density and instability. This mutual exclusivity has hindered the development of hierarchical memory, a standard in modern computing, within molecular storage systems. Here, we bridge this gap by engineering a reconfigurable DNA memory architecture driven by programmable liquid-liquid phase separation (LLPS). Our system leverages sequence-based encoding to achieve an ultrahigh storage density of 7x1010 GB/g, approaching the theoretical limits of DNA accessibility. In its fluidic hot state, DNA droplets enable rapid data loading ([~]83.8% in 5 min) and function as an in-memory editing platform supporting versatile, addressable bit-level operations including selective erasure ([~]65.1%) and high-efficiency rewriting and replacement (>99%) via programmable strand displacement. Importantly, to resolve the stability trade-off, we engineered a programmable phase transition whereby the triggered assembly of a rigid tetrahedral DNA framework (TDF) armor transforms liquid condensates into robust armored droplets. This cold state confers exceptional resistance to enzymatic and physical degradation, projecting multi-millennial data stability. By enabling reversible transitions between a editable, high-density computing mode and a stabilized archival mode, this work establishes the architectural foundation for scalable molecular information storage capable of hierarchical data management.

synthetic biology↗

bioRxiv2026

Ideal Free Distribution in a Multiple Predator-prey System

We study the mechanism and effects of ideal free distributions (IFDs) on an ecological community consisting of n prey and m predator species, for any positive integers n and m, by considering the corresponding diffusive Lotka-Volterra system with time-periodic coefficients. We define a notion of joint IFD in a timeperiodic environment, and give necessary and sufficient conditions for it to be achieved by a subcollection of prey and predator species with suitable dispersal strategies. Next, we show, via construction of a Lyapunov function, that such dispersal strategies are evolutionarily stable, in the sense that if a subcollection of prey and predator species adopts an ideal free dispersal strategy, then the total community must converge to an IFD for large time; if a unique combination of prey-predator species adopts an ideal free strategy, then it can drive all other species to extinction. Conversely, if a combination of prey-predator species adopts a non-ideal free dispersal strategy, then it can be invaded by some suitable mutant strategies. Our results provide insight into the evolution of spatial distribution of ecological communities with predator-prey interactions.

evolutionary biology↗

bioRxiv2026

A Bear-Specific Coding Exon in TMEM41B Is Associated with Cold Adaptation

AbstractBears exhibit an unusual form of hibernation in which core body temperature remains relatively high despite profound suppression of whole-body metabolism. How such a warm yet hypometabolic state is achieved remains poorly understood. Here, through integrative analysis of 238 RNA-seq datasets spanning seven species, we identify transmembrane protein 41B (TMEM41B) as an evolutionarily conserved factor associated with thermogenic capacity. Loss of Tmem41b in mice and Drosophila results in severe cold intolerance, whereas its overexpression enhances thermogenic performance, supporting a conserved role in heat production. Comparative genomic analyses reveal a bear-specific 51-amino acid N-terminal extension in TMEM41B, arising from a 5' untranslated region mutation that converts a premature stop codon into coding sequence. Interactome profiling indicates that this bear-specific isoform differs from the canonical TMEM41B in its protein interaction landscape, including reduced association with components of mitochondria-associated endoplasmic reticulum membranes such as voltage-dependent anion-selective channel protein 1 (VDAC1). Consistent with this altered interaction profile, the extended isoform is associated with reduced mitochondrial oxidative activity. Functional analyses further suggest that the 51- amino acid extension modulates multiple cellular programs, including suppression of oxidative phosphorylation and myogenic differentiation alongside activation of osteogenic pathways, collectively biasing cells toward a hypometabolic state. Notably, expression of the polar bear TMEM41B isoform in mice induces a torpor-like phenotype under fasting conditions. Together, these findings identify TMEM41B as a conserved regulator of thermogenic capacity and suggest that evolutionary modification of its N terminus may contribute to metabolic suppression and energy conservation during bear hibernation.

evolutionary biology↗

bioRxiv2026

UniWave: A Waveform-Based Encoding Framework for Nucleic Acid Feature Extraction

Nucleic acid sequence analysis constitutes a core research area in biomedical and health informatics, playing a critical role in infectious disease surveillance, epigenetic regulation, and genomic biomarker discovery. However, most existing sequence encoding methods rely on discrete representations, which are inadequate for capturing the intrinsic continuous structural properties of biological sequences. Inspired by waveform representations in modern physics, we propose UniWave, a novel encoding framework that converts discrete nucleotide sequences into biologically informative one-dimensional continuous waveforms through base mapping, windowed sinc interpolation, and wavelet-based downsampling. To enable more efficient spatiotemporal modeling, we design a learnable positional encoding module, WavePosition, which incorporates positional information to project the one-dimensional waveform into a two-dimensional continuous representation. In addition, we develop a lightweight dual-attention network, InceptionTime-ATT, to facilitate efficient multi-scale extraction of biological features. Experiments conducted on multiple representative genomic benchmark tasks demonstrate that UniWave consistently and significantly outperforms conventional encoding methods in viral genotype classification, cross-species enhancer identification, epigenetic modification site detection, and bacterial genome classification. Moreover, UniWave maintains excellent robustness under perturbation and noise stress tests, while its low-dimensional continuous representation further contributes to reduced model complexity. In summary, UniWave establishes a novel paradigm for biomedical nucleic acid sequenceencoding that is interpretable, noise-resilient, and computationally efficient, offering new avenues for uncovering disease-associated genomic patterns and advancing data-driven biomedical research.

bioinformatics↗

bioRxiv2026

Microglia Piezo1 aggravates cerebral ischemia and reperfusion injury by chemotactic recruitment of T lymphocytes

Cerebral ischemia reperfusion injury (CIRI) is a complex pathophysiological process involving multiple mechanisms. Piezo1, a stretch-activated ion channel, has recently emerged as a potential regulator of cellular responses to ischemic conditions. However, its role in specific cells during ischemic events is not well elucidated. Here, we showed that after experimentally induced CIRI, Piezo1 channel was highly expressed in peri-infarct area, where is upregulated and activated mainly in microglia. Behavioral tests, and infarct volume measurements demonstrated that conditional Piezo1 deficient in microglia markedly ameliorated the neurological deficits and reduced the infarct volumes. Flow cytometry and immunofluorescence staining showed decreased peripheral immune cells, especially T lymphocytes infiltration into the brain in microglia Piezo1 deficient mice after stroke. Multiplex chemokine immunoassay and T cell migration assays screened that Piezo1 deficient microglia blocked the CXC chemokine ligand 10 (CXCL10) release from astrocyte, which lead to the inhibited T cell recruitment in transwell co-cultured system. Furthermore, RNA-Sequencing analysis showed that defective Piezo1 in microglia lead to its polarization towards an anti-inflammatory phenotype in response to cerebral ischemia and reduced the secretion of tumor necrosis factor- (TNF-) and interferon-{gamma} (IFN-{gamma}). Collectively, Piezo1 deficiency inhibited the secretion of TNF- and IFN-{gamma} in microglia. The reduction of these inflammatory cytokines further blocked the CXCL10 release from astrocyte, and ultimately ameliorated the infiltration of peripheral T lymphocytes after stroke. Our results therefore highlight the critical role of Piezo1 in microglia-orchestrated neuroinflammation and suggest a potential means for reducing stroke-induced neurological injury.

neuroscience↗

bioRxiv2026

GraphESMStable: A Deep Learning Framework for Protein Stability Prediction Fusing Pre-trained Sequence Models and Graph Neural Networks

Predicting protein stability is fundamental, yet existing computational methods often face limitations in generalization, reliance on single data modalities, and challenges with complex multi-point mutations. To address these, we propose GraphESMStable, a novel deep learning framework for predicting protein mutation-induced thermal stability changes. GraphESMStable integrates rich evolutionary context from a frozen pre-trained protein sequence language model with fine-grained three-dimensional structural geometry captured by a trainable Graph Neural Network. A sophisticated residue-level cross-attention mechanism facilitates the deep fusion of these distinct modal representations. The framework features a dedicated prediction head capable of predicting an entire single-point mutation landscape in a single forward pass, and an Epistasis Decoder explicitly modeling non-additive effects for multi-point mutations. Trained exclusively on a large-scale dataset, GraphESMStable achieves state-of-the-art performance, outperforming baselines across a diverse suite of independent evaluation benchmarks. This includes superior generalization on multiple stability datasets, cross-metric generalization to thermal melting prediction, and a significant lead in predicting double mutation epistatic effects. Furthermore, it demonstrates robust performance in predicting human pathogenic mutation stability and achieves substantial improvements in low-sample fitness prediction tasks. Our ablation studies confirm the synergistic benefits of this cross-modal fusion. GraphESMStable represents a significant advancement towards building highly generalizable and efficient foundational models for protein stability prediction, offering broad applicability in protein design and biomedical research.

bioengineering↗

bioRxiv2026

mAbClust with AlphaFold 3 avoids hallucinations to define a quaternary broadly neutralizing HCV epitope

The hepatitis C virus (HCV) envelope glycoprotein E1E2 heterodimer is the target of broadly neutralizing antibodies (bNAbs). Although prior studies have indicated that E1-dependent bNAbs are associated with spontaneous clearance of HCV, all E1-dependent human monoclonal antibodies (mAbs) have been isolated from individuals with chronic HCV infection. Here, we isolated E1-dependent bNAbs from an individual with high neutralizing antibody breadth who spontaneously cleared HCV, showing that these bNAbs bind to four distinct sites on E1E2. We also developed mAbClust, an algorithm that improves identification of accurate AlphaFold 3 (AF3) structure predictions of antigen-antibody complexes. We used AF3 and mAbClust to generate a high-confidence predicted structure of an E1-dependent bNAb in complex with E1E2, showing that this bNAb binds to a quaternary epitope spanning E1 and E2. This study identifies four neutralizing sites and a quaternary bNAb epitope associated with HCV control, which can guide HCV vaccine design. AF3 with mAbClust could have broad applications for accurate epitope mapping of antibodies.

immunology↗

bioRxiv2026

EssTFNet: Integration of Adaptive Time - Frequency and DNA Language Models for Interpretable Human Essential Gene Prediction

Essential genes are defined as those that are indispensable for an organisms survival. The loss of function of these genes results in cell death or an inability to complete the normal life cycle. Research on essential genes is pivotal in elucidating the origin and evolution of life, as well as in identifying potential therapeutic targets. Therefore, accurately predicting essential genes is of great scientific importance and has many applications in basic research and the biomedical field. In this study, we propose EssTFNet, a novel and interpretable deep learning framework that combines adaptive time-frequency analysis with a DNA language model to achieve accurate prediction of human essential genes while enabling mechanistic biological interpretation. Specifically, EssTFNet leverages the architecture of ATFNet, which innovatively maps DNA and protein sequences into equivalent time-series signals to extract periodic and non-stationary features, thereby enhancing the models capacity to capture complex sequence patterns. Through effective feature selection and architectural optimization, EssTFNet strikes a favorable balance among prediction accuracy, model interpretability, and cross-tissues generalization capability, significantly outperforming current mainstream sequence-based deep learning methods with an AUC of 0.8336 and an AUPR of 0.8212. Additionally, the DeepLIFT attribution method was employed to identify functional motifs closely associated with gene essentiality, offering valuable insights for experimental validation. For the convenience of researchers, we have developed an easy-to-use web server and made it along with the source code in a GitHub repository: https://github.com/QIANJINYDX/EssTFNet. Overall, this study presents a potentially useful methodological framework for human essential genes prediction, which could provide valuable insights for future research and applications in this field.

bioinformatics↗

bioRxiv2026

Accurate, scalable, and unified single-cell atlas integration with scBIOT

Single-cell omics technologies have revolutionized the study of cellular diversity, yet integrating datasets across experiments remains challenging due to technical artifacts that obscure biology and confound clustering. We introduce scBIOT (Single-cell Biological Insights via Optimal Transport and Omics Transformers), a self-supervised framework that combines optimal transport alignment with Transformer-based variational autoencoders (VAEs) to learn a shared latent space across batches and modalities. This approach mitigates technical variation while preserving lineage boundaries and continuous trajectories, producing unsupervised clusters consistent with expert annotations. A semi-supervised variant, supBIOT, leverages partial labels to enhance cell-type resolution and cross-dataset consistency. Across multi-batch single-cell RNA sequencing benchmarks, scBIOT matches or outperforms leading integration methods without collapsing related subtypes, and the architecture generalizes to single-nucleus ATAC-seq and multimodal data with minimal adaptation. By integrating geometry-aware alignment with long-range feature modeling, scBIOT provides a scalable, modality-agnostic framework for high-resolution single-cell integration and analysis.

bioinformatics↗

bioRxiv2025

Structural, biophysical, and virological mechanistic characterization of HIV-1 capsid-targeting antivirals

Due to its significant role in virus replication, the HIV capsid is an attractive antiviral target. This is validated by the recent clinical approval of lenacapavir for both treatment and pre-exposure prophylaxis (PrEP). PF74 is a well-characterized capsid-targeting antiviral that was discontinued in further study due to potency and metabolic issues. We hypothesized that making chemical modifications at certain sites of PF74 could result in capsid-targeting antivirals with improved potency and bioavailability. Our cumulative studies show that making changes at the R1 and R3 positions of PF74 results in compounds with increased antiviral potency, increased stability of wild-type HIV capsid hexamers and virions, tighter binding to wild-type HIV capsid hexamer compared to PF74, and different interactions at the "FG" binding site of capsid compared to PF74. These data provide insights into the design of future capsid-targeting antivirals relevant for clinical use.

biochemistry↗

bioRxiv2025

The Hippo Pathway Regulates Corneal Endothelial Regeneration

Corneal endothelial cells (CECs) have limited regeneration capacity in primates while display a potent restorative capability in some species such as rodents after wounding. The mechanism which determines the regenerative capability of CECs remains poorly understood. Here, we identify that the Hippo signaling pathway is inhibited and the downstream effector YAP is activated during CEC wound healing in rabbit and mouse. Knockdown of Yap1 and pharmacological inhibition of YAP suppresses CECs wound healing in rodents in both in vitro and in vivo models. XMU-MP-1, a specific small molecular inhibitor for Hippo signaling pathway, can promote the corneal endothelial regeneration in rodents and corneal endothelial proliferation in cultured primate CECs, as well as in vivo non-human primate CEC wounding model. These findings suggest that Hippo pathway serves as a conserved signal to regulate corneal endothelial regeneration among various species, providing a novel target for non-invasive treatment of corneal endothelium decompensation.

cell biology↗