Biology subjects

Wan, Z.

Publications and source records attributed to Wan, Z..

At least 19 recordsLinked to original sources

bioRxiv2026

Counterions, Polarization and Pore Hydration Relay Drive Ion Permeation through Hydrophobic Pore Formed by the MERS Coronavirus E Protein

Hydrophobic pores are generally expected to exclude ions because the large desolvation penalty associated with ion transfer cannot be compensated within a nonpolar environment. The envelope (E) protein of Middle East Respiratory Syndrome coronavirus (MERS-CoV) presents a striking exception, conducting cations with high efficiency despite forming a predominantly hydrophobic pore. To resolve this apparent paradox, we combine finite-temperature string simulations with additive and polarizable force fields to determine the minimum free-energy pathways for ion permeation through the MERS E channel. The simulations reveal a cooperative permeation mechanism in which transient counterion association, localized pore hydration, and electronic polarization jointly reduce the desolvation penalty. Rather than acting as passive spectators, counterions transiently chaperone the permeating cation before dissociating within the channel, thereby lowering the energetic cost of charge desolvation while preserving net ionic conductance. Explicit electronic polarization further reshapes the pore hydration landscape and cation-{pi} interactions, leading to substantially reduced free-energy barriers and a permeation mechanism in substantially better agreement with experiment. These results suggest that efficient ion transport through hydrophobic pores arises from the cooperative interplay between electrostatics, polarization and hydration rather than complete pore wetting, providing both a mechanistic framework for MERS E protein function and a general physical principle for ion transport through biological and synthetic hydrophobic nanopores.

biophysics↗

bioRxiv2026

OmniSyn unifies target-aware molecular generation and optimization within a synthesis-native LLM framework across the human proteome

Designing target-specific bioactive molecules with actionable synthesis routes for the human proteome holds enormous potential for expanding therapeutic discovery, but remains a challenge. Existing target-aware generative models often depend on protein structures and generate molecules before assessing synthetic feasibility. Here we present OmniSyn, a protein-sequence-conditioned Mixture-of-Experts (MoE) language model that couples a task-conditioned interaction module with a synthesis-action decoder to generate molecules with explicit synthesis traces, thereby unifying de novo ligand generation, synthesizability projection and hit-to-lead (H2L) optimization within synthesis-traceable chemical space. OmniSyn is pre-trained with self-distillation and post-trained with task-specific reinforcement learning (RL) to adapt expert routing and optimize molecular properties across design modes. On unseen protein targets from MolGenBench, a real-world drug-discovery benchmark, OmniSyn achieves state-of-the-art performance across de novo design and H2L optimization, including target-awareness and hit-rediscovery metrics, despite relying only on protein sequences rather than three-dimensional (3D) pocket structures. By embedding synthesis planning into the design process, OmniSyn shifts molecular generation from a generate-then-filter paradigm toward design-with-synthesis paradigm, transforming virtual predictions into experimentally actionable candidates. Independent AiZynthFinder evaluation yielded retrosynthetic success rates of 68.47% for de novo generation and 71.92% for H2L optimization, improving over the strongest baselines by 61.3% and 184.2%, respectively, and supporting the synthetic feasibility of OmniSyn-generated molecules. In synthesizability projection, OmniSyn further converts outputs from external generative models into close analogues with improved retrosynthetic feasibility while preserving molecular similarity. Having established strong benchmark performance and external retrosynthetic feasibility, we next applied OmniSyn at human-proteome scale, spanning more than 21,000 targets. Rapid sequence-conditioned sampling enabled the construction of, to our knowledge, the largest human-proteome-scale generative virtual library, comprising 2.7 billion target-specific molecules, each accompanied by model-derived synthesis traces and target-specific prioritization scores. By enabling scalable target-specific molecular design with synthesis-aware generation across the human proteome, OmniSyn opens new opportunities for exploring previously inaccessible therapeutic targets, including those lacking experimentally resolved structures.

bioinformatics↗

bioRxiv2026

Neutrophil remodeling is associated with human meibomian gland dysfunction and enables IFN-γ- and PAD4-dependent gland obstruction in mice

Meibomian gland dysfunction (MGD), a disorder of the eyelid's modified sebaceous glands, is the leading cause of dry eye disease and ocular surface morbidity, yet the immune mechanisms driving gland obstruction remain poorly defined. In a cross-sectional study of 66 patients with ocular surface inflammation, we used meibography and spectral flow cytometry of tear washes to identify a disease-associated, remodeled neutrophil state whose abundance is associated with gland atrophy. Using single-cell transcriptomics in a murine model of immune-mediated MGD, we revealed a disease-associated neutrophil state that exhibited ocular surface-enrichment, CD14 and ICAM-1 expression, and elevated IFN-{gamma} response and inflammatory signatures. Spatial transcriptomics localized IFN-{gamma} signaling and neutrophil migration signatures to the periglandular compartment. The remodeled neutrophils exhibited PAD4-dependent histone citrullination, with Padi4 deletion reducing NET-associated obstructive plugging, thus identifying PAD4-dependent NETotic activity as their disease-producing output. Inhibition of IFN-{gamma} signaling phenocopied Padi4 deficiency, yet combined disruption of these pathways provided no additive protection, indicating that IFN-{gamma} and PAD4 function as separable required inputs. Remodeled neutrophils accumulated under both conditions, uncoupling disease severity from cell abundance alone. Our findings support immune-mediated obstructive MGD as a mechanistic endotype driven by the IFN-{gamma}- and PAD4-dependent effector output of a remodeled neutrophil state.

immunology↗

bioRxiv2026

Preserved Barrier Integrity and Altered Immune Profiles in Chronic Cannabis Users: Potential Roles of Δ9-Tetrahydrocannabinol

Although cannabinoids such as delta-9-tetrahydrocannabinol (THC) are generally immunosuppressive in preclinical models, chronic cannabis use in humans is paradoxically associated with increased infection risk and systemic inflammation. In this study, we demonstrate that THC directly strengthens intestinal epithelial barrier function in vitro by increasing trans-epithelial electrical resistance in a concentration-dependent manner in Caco-2 monolayers. In a cross-sectional study of chronic cannabis users via smoking or snorting compared with non-using controls, plasma lipopolysaccharide (LPS), and microbial translocation-driven inflammatory cytokines (IL-23, MCP-1, IL-8) were significantly reduced, while some cytokines (IL-6, IL-1{beta}, TNF-, IL-10) remained unchanged. Concurrently, users exhibited elevated macrophage-derived chemokine (MDC) and homeostatic cytokines IL-15 and IL-21, markedly suppressed IL-7 and IL-4. Plasma IL-15 and MDC levels correlated with consumption intensity, and IL-23, IL-7, and IP-10 correlated with age of first use or during heaviest use. These findings suggest that habitual cannabis use may protect gut barrier integrity and reduce microbial translocation and associated inflammation, while simultaneously disrupting systemic immune homeostasis through selective cytokine dysregulation. This dual, dose-dependent immunomodulatory profile highlights the complex balance between potential benefits and risks in both recreational and therapeutic cannabis use.

immunology↗

bioRxiv2026

Cocaine-Enriched Oral Streptococcus parasanguinis Promotes Neuroimmune Dysfunction and Memory Impairment

Chronic cocaine use is associated with neuroinflammation and cognitive dysfunction, but the underlying mechanisms remain unclear. We previously identified oral enrichment of Streptococcus parasanguinis (SP) and other species in individuals with cocaine use disorder (CUD), and here demonstrate that cocaine selectively enhanced SP growth in vitro. To investigate causality, antibiotic-pretreated wild-type C57BL/6 mice received chronic oral inoculation of SP, S. salivarius, Neisseria flavescens, or vehicle. SP-treated mice exhibited spatial memory impairment, increased brain IL-1{beta}, and non-region-specific microglial activation, without detectable bacterial translocation into the brain. While amyloid-associated signaling changes were observed across all bacterial treatment groups, only SP induced cognitive deficits and neuroinflammation. Untargeted metabolomics identified distinct SP-associated oral-to-brain metabolite signatures, including cysteine S-sulfate (CSS) and altered histamine-associated metabolites. CSS and histamine induced neuroinflammatory and amyloid-associated responses in vitro. Together, these findings identify a cocaine-associated oral pathobiont that promotes neuroinflammation and neurodegeneration, suggesting a novel oral microbiome-brain axis in CUD.

neuroscience↗

bioRxiv2026

CodeCytos: AI-assisted spatial molecular imaging analysis via code-augmented agent action space

Conventional tissue image analysis software provides foundational capabilities for cellular analysis, including segmentation, basic morphological feature extraction, and spatial organization analysis. However, these tools often require manual intervention and are not well integrated with code-driven automation, limiting efficiency and scalability for complex spatial tissue studies. In addition, they offer limited flexibility for custom analyses, as they typically support only a fixed set of pre-implemented spatial cellular features. To address these limitations, we propose CodeCytos, a coding-based reasoning agent framework that enables dynamic, programmable interaction with spatial molecular imaging data, to improve automation and customization. CodeCytos is designed to streamline the exploration of custom spatial cellular features and adapt to diverse research needs. We demonstrate its utility through case studies on four expert-curated datasets from distinct tissue types: frontal cortex, non-small-cell lung cancer, pancreas, and tonsil. We evaluate CodeCytos under a realistic minimal prompt setting, where bioscientists pose simple questions without task-specific instructions or contextual information about spatial cellular analysis, and benchmark multiple LLM backbones with strong coding capabilities. We further show that incorporating tailored, domain-agnostic few-shot in-context coding-reasoning examples (randomly sampled demonstrations outside the spatial analysis domain) can substantially improve performance without requiring costly, expert-crafted in-domain demonstrations. Overall, CodeCytos outperforms baseline approaches, highlighting the potential of code-action agents to assist with custom feature exploration in spatial molecular imaging and to accelerate biomarker discovery.

bioinformatics↗

bioRxiv2026

Attention-Guided Multimodal Neuroimaging Fusion Network for Modeling Brain Aging Pattern

Brain age prediction from neuroimaging data provides critical insights into neurodevelopmental trajectories and neurodegenerative processes. However, effectively leveraging complementary structural and functional brain information for accurate prediction remains a major challenge. In this study, we propose an Attention-guided Multimodal brain Age prediction Network (AMAge-Net), a novel framework that integrates resting-state functional MRI (fMRI) and structural MRI (sMRI) to enhance brain age estimation. In AMAge-Net, functional features are captured from fMRI through a hierarchical Graph Attention Network, while structural features are learned from sMRI via a 3D DenseNet architecture. To enable effective cross-modal integration, AMAge-Net incorporates a Multi-Head Cross-Attention mechanism followed by a Gated Fusion Module, allowing the model to dynamically prioritize the most informative features from each modality, thereby improving interpretability and predictive accuracy. Evaluation on the Cam-CAN dataset (652 participants, aged 18-89) demonstrates that AMAge-Net outperforms state-of-the-art unimodal and multimodal baselines, achieving a mean absolute error (MAE) of 5.09, root mean square error (RMSE) of 6.52, R2 of 0.87, and Pearson correlation (PCC) of 0.94. The proposed model further demonstrates robust generalization, achieving an MAE of 4.29, RMSE of 5.59, R2 of 0.58, and PCC of 0.77 on the independent OASIS-3 dataset. Comparative and ablation studies further confirm the effectiveness of the proposed fusion strategy and modality-specific encoders. Beyond predictive performance, AMAge-Net highlights interpretable brain regions that provide insights into the mechanisms of functional and structural brain aging, while gender-specific analyses reveal distinct aging trajectories between males and females. These findings establish AMAge-Net as a powerful and interpretable approach to brain age estimation, advancing efforts to characterize healthy aging and detect early deviations associated with neurological and psychiatric disorders. Author summaryEstimating the biological age of the brain from imaging data offers a window into normal development, healthy aging, and the early stages of disease. A major challenge is how to combine information from structural scans, which show brain anatomy, and functional scans, which capture brain activity. Here, we present a new computational framework that integrates both types of data to improve the accuracy and interpretability of brain age prediction. Applied to two independent, large-scale lifespan magnetic resonance imaging datasets of individuals spanning early adulthood to late life, our framework produced highly accurate predictions and consistently outperformed existing methods. Beyond predictive performance, the model highlighted brain regions that appear especially important for age-related changes, and it revealed distinct aging patterns between men and women. These findings provide a powerful and interpretable tool for studying how the brain changes across the lifespan, with potential applications in detecting early deviations linked to neurological and psychiatric disorders.

neuroscience↗

bioRxiv2026

Integrin Activation Enhances Lesion-Specific Targeting of Monocyte-Mimetic Nanoparticles in Atherosclerosis

PurposeEndothelial cell (EC) activation, characterized by upregulation of adhesion molecules that drive monocyte recruitment, contributes to plaque progression while also providing an opportunity for targeted therapeutic delivery. Leveraging the cell membrane cloaking strategy, we recently developed a monocyte-mimetic nanoparticle (MoNP) platform that exploits the natural inflammatory tropism of monocytes for site-specific delivery to atherosclerotic vessels. Recognizing that integrin activation is a key determinant of monocyte adhesion to ECs, this study investigates whether pre-activating integrins on MoNP enhances their binding affinity and accumulation at atherosclerotic lesions. MethodsMouse bone marrow-derived monocytes were pretreated with CCL2 or Mn2{square} to activate membrane integrins. Isolated monocyte plasma membranes were cloaked onto fluorescently labeled polymeric cores to generate integrin-activated MoNPs (IA@MoNPs). The targeting capability of IA@MoNPs toward endothelial ligands, inflamed ECs, and atherosclerotic lesions was evaluated using in vitro and in vivo models. ResultsIA@MoNPs exhibited markedly enhanced binding to VCAM1, the primary endothelial ligand mediating integrin-dependent monocyte adhesion, and significantly increased uptake by ECs under atheroprone conditions compared to standard MoNPs. In vivo, IA@MoNPs demonstrated enhanced accumulation in atherosclerotic arteries without increasing nonspecific binding, and blocking {beta}1-integrins on IA@MoNPs abolished this targeting effect. Importantly, integrin activation on IA@MoNPs did not compromise circulatory stability or induce immune or organ toxicity. ConclusionIntegrin activation represents a simple yet effective strategy to enhance MoNP targeting to inflamed ECs and atherosclerotic lesions. This mechanism-driven approach improves targeting performance while maintaining specificity and safety, advancing the translational potential of the biomimetic nanomedicine platform for atherosclerosis.

bioengineering↗

bioRxiv2026

bMAE: Masked Autoencoder Latent Representations for Bulk RNA-seq Tissues

Bulk tissue RNA-sequencing data from large-scale consortia such as GTEx provide comprehensive gene expression profiles across diverse human tissues. However, the high-dimensional nature of bulk RNA-seq data, combined with technical noise and batch effects, poses challenges for downstream analyses. While dimensionality reduction methods are routinely applied, standard approaches such as PCA often fail to optimally preserve tissue-discriminative information and exhibit poor generalization to unseen tissue types. We developed a masked autoencoder for bulk tissue RNA-seq that learns compressed latent representations through self-supervised learning with variable masking schedules. Evaluated on GTEx data (31 tissue types, 19,788 samples, 19,308 genes), our method substantially outperformed all baselines in leave-one-tissue-out (LOTO) cross-validation. We achieved mean silhouette 0.20, ARI 0.58, and NMI 0.84 versus best baseline UMAP (0.007, 0.25, 0.47), representing 28.6-fold, 2.3-fold, and 1.8-fold improvements. Remarkably, within held-out tissue categories containing subtissues, our latent space revealed hierarchical structure with enhanced subtissue separation (silhouette 0.16, ARI 0.35, NMI 0.36) versus baselines (silhouette 0.15, ARI 0.20, NMI 0.20), despite never observing these distinctions during training. The method compressed 19,308 genes to 128 dimensions while preserving multi-scale structure.

bioinformatics↗

bioRxiv2026

Deep behavioral phenotyping of pathogen infected mosquitoes reveals species-specific behavior changes enhancing transmission

Mosquito-borne pathogens are often proposed to alter mosquito behavior to enhance transmission, yet the prevalence, magnitude, and consequences of such effects remain unclear. Using custom high- throughput behavioral assays and deep-learning analysis, we quantified the blood-feeding behavior of more than 5,000 mosquitoes, and long-term activity patterns of more than 1,000 mosquitoes across six clinically relevant mosquito-pathogen combinations. Infection effects were highly species-specific. Anopheles stephensi infected with an African Plasmodium falciparum strain showed elevated flight activity throughout infection, an increased tendency to blood-feed upon host contact, and prolonged feeding times. In contrast, infection with an Asian P. falciparum strain or P. vivax had little impact on An. stephensi behavior. We detected no behavioral changes associated with P. falciparum infection in Anopheles gambiae s.s. or Anopheles coluzzii. Interestingly, dengue virus infection in Aedes aegypti increased landing, probing, and engorgement rates. Together, these results demonstrate that infection-induced behavioral change is not a general phenomenon among mosquito-borne pathogens, yet differs markedly per mosquito and pathogen species. A transmission model parameterized with our data showed that even modest behavioral shifts can substantially increase transmission, underscoring the potential epidemiological importance of subtle phenotypic shifts.

animal behavior and cognition↗

bioRxiv2026

Characterizing cellular subpopulations critical to treatment response in autoimmune diseases

Single-cell RNA sequencing provides a powerful approach for characterizing cell types, states, and lineages within heterogeneous tissues. However, identifying cell subpopulations that drive phenotypes, particularly treatment responses, remains a challenge. In this study, we performed comprehensive analyses to identify treatment response-associated cell subpopulations in autoimmune diseases by mapping bulk response information onto single-cell data. We integrated single-cell and bulk biopsy data from 314 responders and 619 non-responders treated with six therapeutics targeting tumor necrosis factor (TNF), integrin, or interleukin pathways in inflammatory bowel diseases (IBD) and psoriasis (PsO). Our analyses captured 128,428 interactions among 3,617 differentially expressed genes (DEGs), 852 pathways, and nine cell types spanning immune, stromal, and epithelial compartments. The importance of epithelial barrier integrity and enterocyte-mediated permeability in responses and inflammatory signaling in macrophages in non-responses in all tested therapies were highlighted by the presence of shared DEGs and pathways in both Crohns disease (CD) and ulcerative colitis (UC). In PsO, keratinocytes drove non-response to integrin-targeting therapies via disrupted adhesion, migration, and sustained epidermal inflammation. Additionally we introduce SCTRAD (https://immbioinfoabbv.shinyapps.io/SCTRAD/), an online web-based platform that allows exploration of mechanisms that influence the heterogeneity of cellular responses through DEGs and pathways at the single-cell level, as well as analysis of the cell-type-specific drug-related gene network. Our findings provide a comprehensive analysis of the role of cellular heterogeneity in treatment outcomes and for advancing precision medicine strategies in autoimmune diseases.

immunology↗

bioRxiv2025

Female-predominant anti-CD4 IgG autoantibody production and its correlations with plasma levels of progesterone, microbial translocation, and blunted immune reconstitution in HIV-infected patients on suppressive ART

Autoimmunity contributes to HIV immunopathogenesis even in the absence of overt autoimmune disease. We previously showed that anti-CD4 autoantibodies from people with HIV (PWH) on suppressive antiretroviral therapy (ART) can mediate cytotoxicity against CD4+ T cells, implicating a role in impaired immune reconstitution. Despite viral suppression, many PWH with poor CD4 recovery exhibit chronic immune activation, microbial translocation, and dysregulated humoral immunity. Here, we identify a female-predominant elevation of plasma anti-CD4 IgG autoantibodies in aviremic PWH receiving ART. Across two independent cohorts, HIV-positive females, but not males, displayed significantly higher anti-CD4 IgG, predominantly IgG1, compared with HIV-negative controls, without parallel increases in anti-CD4 IgA or IgM. This sex-specific pattern was unique to anti-CD4 IgG and was not observed for anti-CD8 IgG, anti-double-stranded DNA IgG, or anti-nuclear antigen IgG; these control autoantibodies correlated with one another but not with anti-CD4 IgG. Elevated anti-CD4 IgG levels were associated with lower plasma progesterone levels and reduced absolute CD4+ T-cell counts. Markers of microbial translocation, soluble CD14 (sCD14), lipopolysaccharide-binding protein (LBP), and lipopolysaccharide (LPS), were also selectively increased in HIV-positive females, with sCD14 and LBP showing significant or borderline associations with anti-CD4 IgG. Together, these findings identify anti-CD4 IgG as a sex-dimorphic autoimmune signature in treated HIV infection, linked to progesterone levels, persistent microbial translocation, and incomplete immune recovery. This work highlights an under-recognized intersection of sex, mucosal barrier dysfunction, and autoimmunity in HIV pathogenesis and suggests potential therapeutic targets to improve immune reconstitution in women.

pathology↗

bioRxiv2025

Cannabis-enriched oral Actinomyces induces anxiety-like behavior via impairing mitochondria and GABA signaling

The human oral microbiome is increasingly recognized as a contributor to brain health, yet its mechanisms remain unclear. Our previous work revealed that oral Actinomyces species was enriched in chronic cannabis smokers. Here, we show oral inoculation of cannabis use-associated Actinomyces species, especially A. meyeri, to wild-type C57BL/6 mice leads to anxiety-like behaviors, non-region-specific microglia activation, mitochondrial dysfunction, and reduced GABAergic neurotransmission, without evidence of bacterial translocation to the brain, neuroinflammation, and memory decline. Notably, Actinomyces species-producing metabolites, i.e., arginine and argininosuccinate, were increased in both oral swabs and brain following inoculation in vivo. These Actinomyces species-producing metabolites induced mitochondrial dysfunction and oxidative stress in neurons in vitro, indicating a neuropathogenic role and aligning with reduced GABAergic neurotransmission in vivo. Together, these results suggest that oral cannabis-associated dysbiosis impacts behavior through mitochondrial stress and impaired inhibitory signaling, indicating the oral-brain metabolic axis is potentially consequential in neuropsychiatric disorders. TeaserChronic heavy cannabis use-enriched oral bacteria can drive anxiety and neuropathogenesis in mice. Highlights{whitebullet} Cannabis-associated oral Actinomyces enrichment induces anxiety-like behavior in mice {whitebullet}Microglial activation occurs without neuroinflammation (IL-1{beta}, TNF-, and IL-6) {whitebullet}Mitochondrial hyperactivation and reduced inhibitory GABAergic signaling Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=160 SRC="FIGDIR/small/689724v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@120b0b1org.highwire.dtl.DTLVardef@1304782org.highwire.dtl.DTLVardef@a6aa77org.highwire.dtl.DTLVardef@17d6d_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2025

Characterize Oral-to-Blood Microbial DNA Translocation in Individuals with Cocaine Use Disorder

BackgroundCocaine disrupts gut barriers in animal models, potentially enabling microbial translocation and inflammation in the periphery and central nervous system (CNS), but its direct role in inducing inflammation remains controversial. This study aimed to determine if the oral cavity is a source of circulating microbial DNA translocation in individuals with current cocaine use disorder (CUD). ResultsA cross-sectional case-control study was conducted, comparing CUD and demographically matched non-drug controls. Ten CUD (via smoking or vaping) and 24 controls provided paired saliva and blood samples. Microbial 16S rRNA V4 region was sequenced in isolated microbial DNA from saliva and plasma. Single-cell RNA sequencing (scRNAseq) was analyzed in human peripheral blood mononuclear cells. Saliva from CUD, but not plasma, exhibited reduced alpha diversity and altered beta diversity, characterized by enriched Streptococcus and depleted Fusobacterium, Neisseria, and other taxa relative to controls. Controls exhibited low to undetectable microbial translocation in plasma. By contrast, plasma displayed CUD-specific oral enrichment of several Streptococcal species and evidence of translocation into the bloodstream. S. parasanguinis, but not cocaine alone, induced IL-1{beta} and TNF- production in human primary monocytes in vitro. scRNAseq further revealed innate immune activation, impaired T cell function, and heightened susceptibility to infection in CUD. ConclusionsThis pilot study demonstrating that CUD via smoking or snorting exhibited oral microbial dysbiosis and selective oral-to-blood microbial translocation in vivo. These findings suggest that a compromised oral-to-blood barrier, rather than cocaine itself, promotes immune perturbations in CUD.

microbiology↗

bioRxiv2025

ETV2 mediated differentiation of human pluripotent stem cells results in functional endothelial cells for engineering advanced vascularized microphysiological models

Patient-specific microphysiological models, exemplified by organs-on-a-chip and organoids, have become a valuable tool for broad applications, revolutionizing biomedical research. However, limitations persist, with functional vasculature being a significant challenge. Generating functional human induced pluripotent stem cell (h-iPSC) derived endothelial cells (h-iECs) represent an urgent need. With the discovery of ETV2s determinant role in specifying EC lineages during differentiation, researchers have adopted techniques involving ETV2 overexpression to produce h-iECs more efficiently and consistently. However, the capacity of these cells to form functional vasculatures has not yet been thoroughly investigated. Here, we generated multiple h-iPSC lines with inducible ETV2 expression, and subsequently differentiated them into h-iECs, which were validated functionally and by key endothelial markers and RNA-seq analysis. These cells are capable of self-organizing into stable microvascular networks (MVNs) in a microfluidic chip reproducibly, forming lumenized and functional vessels that mimic the in vivo capillary bed in both morphology and function - a result not achieved using h-iECs differentiated with conventional two-step methods using the same h-iPSC lines. Furthermore, complex microphysiological models featuring perfusable vasculature were also successfully developed using ETV2 activated h-iECs, demonstrated with vascularized tumor and blood-brain barrier (BBB) models. Additionally, by pooling genetically engineered h-iPSCs with inducible ETV2, we effectively employed an orthogonally induced differentiation approach to enhance vascularization of an organoid model. Our methodology opens avenues in precision medicine, leading to personalized microphysiological models with perfusable vasculature for various applications.

bioengineering↗

bioRxiv2025

Blood, sweat, and beers: investigating mosquito biting preferences amidst noise and intoxication in a cross-sectional cohort study at a large music festival

IntroductionWe live in a world split between mosquito magnets and those lucky enough to remain (nearly) untouched. The reasons why some people attract more mosquito bites than others remain largely mysterious. In the Mosquito Magnet Trial, we investigated differences in mosquito attraction amongst festivalgoers with varying levels of hygiene and intoxication. MethodsOur study was conducted in a slightly steamy pop-up laboratory inside four connected shipping containers at Lowlands Festival in The Netherlands (August 18-20, 2023). Participants completed an anonymous questionnaire on hygiene, diet, and festival-related behaviour (including alcohol uptake and shared sleeping arrangements). Mosquito attraction was measured using a custom designed setup: a transparent cage with perforations where female Anopheles mosquitoes were offered a choice between a sugar-feeder and the participants arm. Mosquitoes could only smell, not bite, the participants arm. Attraction was quantified through video imaging, measuring arm landings relative to total landings. Mosquito attraction was correlated with questionnaire responses and skin microbiota profiles collected from forearm skin swabs. ResultsAmongst the 465 included participants, mosquitoes showed a clear fondness for those who drank beer over those who abstained from the liquid gold (Fold Change 1.35, 95% CI 1.12-1.63, PFDR<0.001). Attraction was also contagious: participants that successfully lured a fellow human into their tent the previous night also proved more enticing to mosquitoes (FC 1.34, 95% CI 1.14-1.58, PFDR=0.002). Meanwhile, skipping the morning showering routine and using sunscreen reduced mosquito attraction (FC 0.52, 95% 0.38-0.70, PFDR<0.001). Streptococci were more abundant on the skin of highly attractive individuals (Puncorrected=0.017), and the overall abundance of malodour associated bacteria was high - possibly reflecting the containers smell. ConclusionThe Mosquito Magnet Trial, to our knowledge the largest study of its kind, was conducted in a loosely controlled setting with a selection bias towards science loving festivalgoers. That said, using our custom designed experimental set-up, we found that mosquitoes are drawn to those who avoid sunscreen, drink beer, and share their bed. They simply have a taste for the hedonists among us.

animal behavior and cognition↗

bioRxiv2025

CD40 agonistic-monovalent streptavidin fusion antibody for targeted neoantigen peptide delivery and potent cancer vaccination

Cancer vaccines targeting patient-derived neoantigens offer great promise for personalized cancer therapy but face challenges in achieving targeted delivery to antigen-presenting cells (APCs) to elicit robust and durable cancer-specific immune responses. We synthesized an anti-mouse CD40 agonistic-monovalent streptavidin fusion antibody (CD40-mSAs), which enables targeted delivery of biotinylated neoantigen peptides to APCs in draining lymph nodes (dLNs). We confirmed mSA expression on the engineered antibody and its strong binding affinities to mouse CD40 and biotin. Advanced microscopy demonstrated that CD40-mSAs enhances homing to dLNs and intracellular delivery of neoantigen peptides to critical APC subsets, such as cDC1. The potent agonistic effects of CD40-mSAs on dendritic cell maturation, activation, and antigen presentation were verified through in vitro assays. Vaccination with CD40-mSAs elicited robust cancer-specific CD8 T cell responses, leading to significant tumor regression and prevention in a mouse tumor model. These results support CD40-mSAs as an all-in-one vaccine delivery platform with multifunctional immunopharmacological advantages and strong translational potential for personalized cancer vaccination. TeaserCD40-mSAs is an engineered anti-CD40 agonistic antibody designed to enhance cancer vaccine delivery.

immunology↗

bioRxiv2025

MSF-CPMP: A Novel Multi-Source Feature Fusion Model for Prediction of Cyclic Peptide Membrane Permeability

Cyclic peptides are becoming attractive molecules for drug discovery because of their properties with inherent stability and structural diversity. However, the high potential of cyclic peptide drugs is challenged by the limited membrane permeability cross cell membrane. To predict cyclic peptide membrane permeability (CPMP), an increased number of computational models or tools are designed and used. But these existing algorithms or models do not appropriately capture feature diversity of cyclic peptides. In this study, we introduce a novel multi-source feature fusion model called MSF-CPMP, which aims to increase the accuracy of predicted CPMP. The MSF-CPMP model incorporates three features extracted from SMILES sequences, graph-based molecular structures, and physicochemical properties of cyclic peptides. By benchmarking with other machine learning and deep learning-based methods, MSF-CPMP achieved the highest levels of the evaluation metrics such as accuracy of 0.9062 and AUROC of 0.9546, and further validated MSF-CPMP robustness in learning capabilities and efficacy of its multi-source fusion. Our result demonstrates that MSF-CPMP outperforms other methods in predicting CPMP, that provides also exemplifies the power of advanced deep learning methods in tackling complex biological challenges, offering contributions to computational biology and clinical treatment. Code is available at https://github.com/wanglabhku/MSF-CPMP Author summaryWe have recognized that cyclic peptides are one type of main macro-molecular drugs useful for treatment of human diseases. However, the structural diversity of cyclic peptides results in limited permeability across cell membranes which is challenging drug research or industrial development. Previously some computational models or tools including machine learning or deep learning ones tried to solve this problem, but they still are not efficient. There are urgent requirement for more effective methodologies. Thus, we introduce a novel multi-source feature fusion model called MSF-CPMP. Our aim is to enhance accuracy and efficiency of predicted CPMP. We carried out evaluation of performance metrics by comparative analysis between MSF-CPMP and other machine learning or deep learning methods. Our result demonstrates that MSF-CPMP outperforms other models in predicting CPMP. We further validated MSF-CPMP robustness in learning capabilities and efficacy of its multi-source feature fusion. In the future we would further improve our methods that can integrate broader biomedicine and biomedical information and provide guide for drug diversity in clinically treating complex human diseases.

bioinformatics↗