Biology subjects

Jin, L.

Publications and source records attributed to Jin, L..

At least 19 recordsLinked to original sources

bioRxiv2026

Development of CYP8B1-specific inhibitors for metabolic diseases

Changes in bile acids (BAs) balance lead to various metabolic diseases, yet current treatment options targeting these changes remain severely limited. CYP8B1 (cytochrome P450, family 8, subfamily B, polypeptide 1) is a liver-exclusive enzyme that controls the synthesis of 12-hydroxylated (12-OH) BAs. Inhibiting CYP8B1 is an attractive therapeutic strategy for attenuating 12-OH BA levels, remodeling the gut microbiota and thereby ameliorating metabolic diseases. CYP8B1-specific inhibitors are currently lacking due to structural similarities between the active site of CYP8B1 and other CYPs, and the lack of suitable high-throughput screening (HTS) assays. Herein, we developed a highly sensitive, and specific enzyme-coupled fluorescence assay to detect CYP8B1 activity, making it ideal for HTS. Employing this assay, structure-based drug design by protein X-ray crystallography, structure-activity relationship (SAR) analyses, and in vitro and in vivo validation, we developed novel CYP8B1-specific small molecule inhibitors. The lead candidate alters BA composition, favorably remodels the gut microbiota, and corrects metabolic disease in a metabolic dysfunction-associated steatotic liver disease (MASLD) mouse model. These findings reveal that pharmacologically inhibiting CYP8B1 is able to reshape the BA and gut microbiota profiles and effectively ameliorates metabolic diseases. Overall, CYP8B1-specific inhibitors represent a first-in-class promising, safe and effective therapeutic strategy against metabolic disorders.

pharmacology and toxicology↗

bioRxiv2026

A spatial topology atlas of type I myofibers in porcine skeletal muscle reveals local slow-oxidative niches associated with meat quality traits

Skeletal muscle metabolism and meat quality are usually interpreted through myofiber type composition, fiber size, and histochemical state. Whether the spatial topology of myofibers constitutes an independent phenotype layer remains poorly quantified. Here, using succinate dehydrogenase (SDH)-stained cross-sectional images from multiple pig breeds and more than 40 skeletal muscle sites, we established a multiscale spatial phenotyping framework for type I myofibers. To enable scalable instance-level quantification, we developed an improved Mask R-CNN segmentation workflow, trained with SAM-assisted and manually corrected annotations, and optimized for dense, small, irregular, and variably stained muscle fibers. This framework captures single-fiber morphology and staining, local contact, connected-cluster architecture, diffusion-ring neighborhoods, and global tissue configuration. Type I myofiber abundance was separable from spatial organization capacity: some muscles formed stronger-than-expected local connectivity and clustering despite modest type I fiber abundance. Spatial transcriptomic integration further showed that slow-oxidative genes and functional modules were non-randomly organized and formed local high-expression domains in type I fiber-enriched, high-contact neighborhoods. Across muscle sites and breeds, skeletal muscles displayed distinguishable type I fiber spatial topology identities, which were remodeled by breed background in a muscle-specific manner. In samples with matched meat-quality measurements, spatial topology features improved the explanation of pH, meat color, conductivity, and intramuscular fat. These results suggest that skeletal muscle should be modeled as a spatially organized tissue system rather than a simple mixture of fiber types.

bioinformatics↗

bioRxiv2026

A Community-Driven Single-Cell PBMC Reference Integrating Landmark Datasets Spanning Health and Disease

Blood provides an accessible window into human health, yet the absence of a peripheral blood mononuclear cells (PBMCs) reference with standardized immune cell annotations has constrained comparisons between single-cell RNA sequencing (scRNAseq) studies. Here, we present HARP (Human Cell Atlas Reference for PBMCs), an integrated atlas of ~9 million PBMCs from >2,600 donors across 15 studies spanning four continents, encompassing diverse populations, neonates to 97 years, across health and diverse immune-related diseases. We developed optimized integration workflows, including novel label-free metrics to assess integration quality, and generated community-driven consensus annotations for 192 immune cell subsets, identifying rare populations representing as few as 0.004% of PBMCs. HARP reveals coordinated cellular modules associated with age, sex, and disease, identifies female-biased interferon and inflammatory gene programs and their perturbation by COVID-19, and uncovers a novel sexual dimorphism in prostaglandin signaling. Finally, we introduce scTiger, a hierarchical label-transfer framework that accurately projects these 192 cell annotations onto ~18 million additional PBMCs, providing a robust and transferable reference for harmonizing future PBMC studies. HARP provides a high-resolution community-driven reference atlas for PBMC annotation and analysis, as a basis for emerging clinical applications of single-cell genomics.

immunology↗

bioRxiv2026

Extracellular Granzyme B Promotes Melanocytorrhagy, Melanocyte Senescence and Aberrant Epidermal Differentiation in Vitiligo and Is Therapeutically Targetable

Background Vitiligo is an acquired depigmenting disorder characterised by melanocyte loss. While immune responses against melanocytes are implicated in its pathogenesis, melanocyte detachment, melanocyte senescence and aberrant epidermal differentiation are increasingly characterised as additional pathological features. Granzyme B (GzmB), classically recognised as an intracellular effector of perforin-dependent cytotoxicity, is increased in vitiligo lesions; however, its extracellular contribution to vitiligo pathology remains unclear. Objectives To determine whether extracellular GzmB contributes to depigmentation and epidermal pathological features relevant to vitiligo, and to define its cellular source and underlying mechanisms. Methods Human vitiligo skin samples, murine depigmentation models and cultured human epidermal cells were analysed. The functional effects of extracellular GzmB were examined by subcutaneous administration of recombinant GzmB in mice. A rhododendrol (RD)-induced leukoderma model was used to evaluate the disease relevance of GzmB and the therapeutic effect of topical GzmB inhibition with VTI-1002. Results GzmB-positive cells were markedly increased in active vitiligo lesions and were predominantly associated with tryptase-positive cells, with limited co-distribution with CD8 or perforin. Vitiligo lesions also showed melanocyte detachment, increased p16INK4A-positive melanocytes and aberrant keratinocyte differentiation. These pathological features were recapitulated in vivo by extracellular GzmB administration, accompanied by focal depigmentation. In cultured melanocytes, GzmB exerted no cytotoxic effects but reduced attachment strength and induced a senescence-associated phenotype characterised by decreased extracellular matrix- and adhesion-related gene expression, increased p16INK4A level, elevated senescence-associated {beta}-galactosidase activity and activation of transforming growth factor-{beta}/SMAD signalling. In keratinocytes, extracellular GzmB promoted aberrant differentiation associated with activation of p53 signalling. Topical inhibition of GzmB in RD-induced leukoderma attenuated depigmentation progression, melanocyte detachment, melanocyte senescence and abnormal epidermal differentiation. Conclusions Extracellular GzmB promotes depigmentation associated with inducing melanocyte detachment, melanocyte senescence and aberrant keratinocyte differentiation. These findings identify extracellular GzmB as a previously underrecognised pathogenic mediator and potential therapeutic target in vitiligo-associated depigmentation.

immunology↗

bioRxiv2026

π-MNovo improves de novo peptide sequencing through microbial-domain adaptation and evidence-guided candidate selection

The high taxonomic and strain-level diversity of microbial communities makes it difficult for reference databases to fully represent the protein sequences present in metaproteomic samples, limiting database-dependent peptide identification. De novo peptide sequencing can recover peptide sequences directly from tandem mass spectra without relying on reference databases, providing complementary peptide evidence for metaproteomics. However, most existing de novo sequencing models were developed largely from non-microbial proteomic data and lack specific adaptation to microbial spectra. Here, we established a dedicated microbial spectral resource comprising more than 10 million annotated high-quality tandem mass spectra from 72 cultured microbial isolates, with peptide digests from each isolate separated into five high-pH reversed-phase fractions to increase the opportunity for deeper and more diverse peptide sampling. Using this resource, we developed {pi}-MNovo, which combines adaptation to microbial spectra with evidence-guided candidate selection to improve full-length peptide sequencing precision. On a seven-species external benchmark, {pi}-MNovo achieved 66.30% complete-peptide recall under the same residue-mass-based complete-peptide matching criterion applied to all models, exceeding four published models by 6.9-21.7% in relative recall, with consistent gains across species and peptide-length groups. In two independent metaproteomic datasets, {pi}-MNovo increased reference-supported taxonomic coverage, while synthetic-community analysis recapitulated the designed abundance ranking. From pFind-unidentified spectra, {pi}-MNovo recovered 1,587 pFind-unreported, reference-matched peptides that passed spectrum-evidence filtering. These results show that {pi}-MNovo expands recoverable peptide evidence and enhances the utility of de novo sequencing for metaproteomic analysis.

bioinformatics↗

bioRxiv2026

Human skin fibrosis with iPSC-derived organoids reveals RUNX2-mediated fibroblast reprogramming

Fibrotic skin diseases are characterized by persistent fibroblast activation and extracellular matrix remodeling, yet the mechanisms governing fibroblast state transitions remain incompletely understood. Here, we established a human iPSC-derived skin organoid model of fibrosis through chronic TGF-{beta} stimulation. Single-cell RNA sequencing combined with immunofluorescence-based spatial analysis revealed dynamic fibroblast state transitions, spatial reorganization, and expansion of activated fibroblast populations during fibrotic remodeling. Integration with human scleroderma single-cell datasets demonstrated conserved fibroblast states and transcriptional programs between organoids and patient tissues. We further identified broad induction of RUNX2 in the dermal compartment during fibrosis, and RUNX2 depletion attenuated fibrotic marker expression. CUT&RUN profiling revealed RUNX2 occupancy at fibrosis-associated loci, including RUNX1 and LOXL2. Using a machine learning-guided screening approach, we identified F0565-0303, a small molecule that suppressed RUNX2-dependent fibrotic programs in vitro and reduced fibrosis in a bleomycin-induced mouse model. Together, these findings establish human skin organoids as a platform for modeling fibrosis and nominate RUNX2 as a potential therapeutic target.

bioengineering↗

bioRxiv2026

Impact of Trastuzumab and Pertuzumab on HER2 Localization and the Estrogen Receptor Cistrome in ER+/HER2+ Breast Cancer

Background: Although anti-HER2 monoclonal antibody therapy with trastuzumab and pertuzumab is highly effective for HER2-positive breast cancer, co-expression of estrogen receptor (ER) significantly reduces pathologic complete response rates. Objective: We investigated how HER2-targeted inhibition affects HER2 cellular localization and ER genomic binding in ER-positive, HER2-positive breast cancer. Methods: We evaluated HER2 localization in a tissue microarray of treatment-naive patients. Using cellular fractionation, immunofluorescence, chromatin immunoprecipitation, and genome-wide profiling (CUT&RUN), we evaluated HER2 localization and ER genomic binding following acute anti-HER2 treatment and in models of treatment resistance. The treatment-induced ER-bound gene signature was assessed for associations with pathologic complete response and survival in breast cancer clinical cohorts. Results: In treatment-naive primary breast tumors, nuclear HER2 inversely correlated with ER levels. In cell models, treatment with trastuzumab and pertuzumab induced nuclear and chromatin accumulation of HER2. Concurrently, acute anti-HER2 treatment displaced ER from canonical estrogen response elements at classical target genes, yet genome-wide profiling revealed redistribution of ER binding toward non-canonical zinc finger motifs adjacent to pro-survival Wnt and RAGE pathway genes (FZD8, RELA). Expression of a drug-induced ER-bound gene signature was significantly higher in tumors of individuals who did not achieve pathologic complete response following neoadjuvant anti-HER2 therapy and significantly correlated with reduced distant metastasis-free survival in clinical cohorts. Conclusions: Anti-HER2 targeted therapy causes dynamic cistromic reprogramming of ER from classical estrogen pathways toward alternative pro-survival networks. These findings implicate ER redistribution as a possible mediator of resistance and highlight novel therapeutic targets in ER-positive, HER2-positive breast cancer.

cancer biology↗

bioRxiv2026

Nuclear Cathepsin L Remodels the Replication Machinery to Create a Therapeutic Vulnerability in Ovarian Cancer

Abstract Therapeutic resistance in ovarian cancer is frequently driven by persistent replication stress, yet the molecular mechanisms that convert replication stress into a therapeutically exploitable vulnerability remain incompletely understood. Here, we identify drug-induced nuclear cathepsin L (nCTSL) as a previously unrecognized regulator of replication stress and DNA repair. Clofarabine (CLF) combined with the ATR inhibitor AZD6738, or the CHK1 inhibitor prexasertib promoted nuclear accumulation of CTSL, where it remodeled the replication machinery through degradation of CCNE1, MCM3, MCM6, and geminin, accompanied by loss of RAD51 and 53BP1 and increased {gamma}H2AX and phospho-RPA2. DNA fiber analysis demonstrated marked inhibition of replication fork progression following CLF-based combinations, whereas CTSL depletion accelerated fork progression and abolished therapy-induced replication stress. Reconstitution with the nuclear M1F CTSL isoform restored replication restraint, confirming a direct role for nuclear CTSL in regulating replication dynamics. GFP-based DNA repair reporter assays further revealed that CLF-based combinations suppress DNA repair competence in a CTSL-dependent manner, indicating that nuclear CTSL couples replication stress amplification with functional inhibition of repair pathways. Functionally, CLF-based combinations selectively targeted transformed fallopian tube secretory epithelial cells while sparing non-transformed counterparts, demonstrated broad activity in patient-derived ovarian cancer ascites spheroids, and significantly inhibited tumor growth and prolonged survival in vivo. Collectively, our findings identify nuclear CTSL as a mechanistic driver of replication stress that remodels the replication machinery, impairs DNA repair, and creates a therapeutically exploitable vulnerability in ovarian cancer. We propose that nuclear CTSL promotes a transition from replication competence to replication catastrophe, thereby establishing a conceptual framework for biomarker-guided therapeutic strategies targeting CTSL-dependent replication stress.

cancer biology↗

bioRxiv2026

Cell-state-dependent responses to PLK1 inhibition reveal a non-canonical microtubule-endolysosomal vulnerability in quiescent leukemia stem cells

Relapse in cancer is frequently driven by therapy-resistant quiescent cancer stem cells. Conventional chemotherapy has been designed to target proliferating tumor cells and is generally presumed to be ineffective against non-cycling cancer stem cells. Using acute myeloid leukemia (AML) as a model, we challenge this prevailing view by showing that inhibition of the mitotic master regulator Polo-like kinase 1 (PLK1), a kinase extensively pursued for antiproliferative cancer therapy, unexpectedly eradicates quiescent leukemia stem cells (LSC) through a mechanism distinct from its canonical mitotic function. In proliferating AML cells, PLK1 inhibition (PLK1i) induced G2/M arrest and mitotic catastrophe. In contrast, quiescent LSC underwent apoptosis independent of mitotic arrest, revealing a cell-state-dependent mode of drug action. Mechanistically, PLK1i initiated a multi-step process through disruption of a previously unrecognized, stem cell-specific interaction between PLK1 and MAP1A, resulting in perturbed vesicle trafficking and endolysosomal homeostasis characterized by altered receptor internalization, vesicle accumulation and lysosomal dysfunction, ultimately culminating in apoptotic cell death. Combinatorial pharmacologic perturbation studies established microtubule regulation as a critical determinant of quiescent LSC survival, while ex vivo and in vivo assays demonstrated depletion of functionally-defined LSC following PLK1i. These findings identify a previously unrecognized role for PLK1 in intracellular trafficking and establish MAP1A-dependent control of vesicle homeostasis as a mechanistic determinant of cancer stem cell survival. More broadly, this study demonstrates that classical antimitotic compounds, including microtubule-targeting agents and PLK1 inhibitors, can eradicate both cycling leukemic blasts and quiescent LSC through distinct, cell state-dependent mechanisms, challenging proliferation-centric models of chemotherapy action.

cancer biology↗

bioRxiv2026

Quantifying Crop Disease Trait Dynamics through Longitudinal Imaging and Temporal Analytics

Reliable and objective phenotyping is essential for plant breeding programs to characterize genetic variation and accelerate crop improvement. Conventional disease assessment relies on expert visual scoring, which is labor-intensive, subjective, and prone to inter- and intra-rater variability. Although image-based phenotyping methods have been proposed, many require manual intervention, specialized imaging setups, or single time-point measurements, limiting their ability to capture disease progression over time. Here, we present a pipeline for longitudinal plant disease phenotyping that quantifies wheat stripe rust and leaf rust progression from time-series images. The pipeline performs semi-automated leaf and automated pustule segmentation from images acquired in situ, enabling objective disease severity estimation with minimal user intervention and without requiring solid backgrounds or manual leaf manipulation or detachment. By extracting temporal traits, including disease severity trajectories and standardized area under the disease progress curve, the method provides a comprehensive characterization of disease development throughout infection. Association between automated and expert assessments was moderate for stripe rust (R2 = 0.58) and strong for leaf rust (R2 = 0.85), while expert inter-rater reliability was moderate for both diseases (ICC = 0.675 and 0.800, respectively). The proposed approach establishes a scalable and reproducible framework for longitudinal disease phenotyping in controlled environments, with broad applications in disease resistance screening and crop breeding.

bioinformatics↗

bioRxiv2026

SVPopEx: Population-Wide Visualization and Exploration of Structural Variants

Structural variants (SVs) are large-scale genomic variants, which can disrupt important functional and regulatory elements, leading to genomic disorders in humans and playing important roles in domestication, disease resistance, and traits in plants. SVs are generated across populations of individuals and used for association studies, consisting of large datasets with thousands of genomic loci. Visualization of these SVs aids in understanding their genomic distribution, identifying patterns across affected or phenotypic groups, and assessing their proximity to other genomic regions of interest. A variety of tools exist for visualizing SVs, including linear genome browsers and graph-based methods; however, many do not offer intuitive or scalable representations of SVs across large populations. To address this, we present SVPopEx, an interactive tool for population-wide visualization and exploration of SVs. SVPopEx provides a unique and intuitive representation for insertions, deletions, inversions, duplications, and translocations in a linear genome-style browser. Novel features were developed to support comparisons across genomes within user-defined regions, including rendering SVs based on one or more samples and visualizing haplotypes. Use of the tool is demonstrated with SV datasets from Schistosoma mansoni and Lens culinaris. A task-based evaluation was conducted using SVPopEx and two other linear genome browsers, which demonstrated that SVPopEx excelled in (1) providing a clear representation of the SVs present and (2) supporting comparisons across genomes.

bioinformatics↗

bioRxiv2026

Plasma titration provides a physical ruler for cross-platform proteomics

Plasma proteomics is expanding across platforms and cohorts, and integrating these data for AI demands comparability at the protein level, not merely concordant associations1,2. Affinity and MS platforms use distinct probes (antibodies, aptamers, or peptides) and signal readouts, yielding contradictory cross-platform results3,4. Without a known quantitative truth, we cannot distinguish biology from measurement distortion, leaving no gold standard for integration. Here we introduce Plasmix--a plasma reference suite with predefined male:female ratios (M, 1:0; Y, 3:1; P, 1:1; X, 1:3; F, 0:1)--and show that preserving this quantitative titration gradient, not just technical repeatability, predicts cross-platform concordance and identifies protein measurements suitable for integration. Profiling Plasmix across five platforms (Olink, SomaScan, NULISA, AAgAtlas, and MS-DIA) and 12 protocols across 17 batches, we found discordance is dominated by signal generation, not sample identity, and platforms distort signals in a protein-specific manner. Crucially, proteins retaining the titration response showed stronger agreement in an independent cohort; anchoring to the Plasmix midpoint (P) via sample-to-reference ratios reduced distortions, extending harmonizable coverage by 10-20%. Plasmix thus provides a physical ruler to benchmark accuracy, identifying genuinely integrable measurements before pooling datasets or training AI models--a critical bottleneck for plasma proteomics.

molecular biology↗

bioRxiv2026

Comparative Transcriptome Analysis Unveils Mechanisms of Salt Tolerance in Bluebunch Wheatgrass

Bluebunch wheatgrass (Pseudoroegneria spicata) exhibits substantial variation in its response to salt stress, making it a valuable model for studying salinity-tolerance mechanisms for use in crop improvement. In this study, we identified two P. spicata genotypes with contrasting responses to salt stress: the tolerant W6 56551, which maintained growth with green foliage under saline conditions, and the susceptible PI693916, which exhibited severe leaf chlorosis and stunted growth. To better understand the molecular basis of salt tolerance in blue-bunch wheatgrass, we conducted RNA-sequencing at 0, 1, and 4 days (D0, D1, and D4) after salt treatment at 160 mM level to examine changes in gene expression of salt-tolerant and salt-susceptible genotypes. Comparative analysis across time points identified 6,154 and 1,086 differentially expressed genes (DEGs) at D4 and D1 in PI693916, and 4,638 and 3,302 DEGs at D4 and D1 in W6 56551, respectively, relative to control (D0). Functional analysis of these DEGs showed that the salt-tolerant geno-type displayed an early and broad transcriptional reprogramming, including induction of photosynthesis, carbon metabolism, and flavonoid biosynthesis pathways, whereas the salt-susceptible genotype exhibited delayed and less coordinated responses, with enrichment of cyanoamino acid metabolism and repression of antioxidant-associated pathways. Notably, calcium signaling, ion transporter regulation, and osmolyte biosynthesis genes showed contrasting expression between genotypes, highlighting distinct strategies for ionic and osmotic homeostasis. Collectively, these results demonstrate that salt tolerance in P. spicata is associated with rapid metabolic adjustment, enhanced photosynthetic stability, and differential regulation of ion transport and osmoprotectant pathways.

genomics↗

bioRxiv2026

Locus-specific transposable element expression drives human hematopoietic stem cell disease pathophysiology

VEXAS syndrome (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) is a severe, inflammatory syndrome resulting from mutated UBA1 leading to hematopoietic stem cells (HSC) expansion. Although UBA1-mutant HSC show complex phenotypes including proteostasis defects, sustained inflammation and clonal expansion of myeloid biased progeny, the pathogenic mechanisms at the HSC level are unknown from these gene-centric studies alone. By focussing on the non-coding genome and using advanced functional genetic methods, we found that VEXAS HSC, compared to controls, had altered expression of individual transposable elements (TE) and are key regulators of VEXAS pathogenesis. Locus-specific TE quantification identified two L1 elements, L1-10 and L1-15, active in both normal and VEXAS HSC that drive myeloid commitment by co-opting SPI1 and IRF1 transcription factors (TF) via networks common to other myeloid-biased conditions. Lipid nanoparticle (LNP)-mediated CRISPRi of L1-10 and L1-15 in UBA1-mutant HSC also caused reversion of VEXAS-associated functional phenotypes in vitro and in vivo. Functionally, pharmacologic inhibition of UBA1 with TAK-243 led to L1-10 and L1-15 RNA accumulation, while enhancement of UBA1 activity with Auranofin reversed this effect. Our study provides direct evidence that VEXAS-specific TE govern HSC clonal dominance, thereby uncovering a regulatory axis underlying HSC biology and disease mechanisms, opening a therapeutic strategy directed towards the repetitive genome.

genetics↗

bioRxiv2026

Manifold Agentic Reasoning: Extending Agentic POMDPs and Post-Training Reasoning to Riemannian State and Reasoning Spaces

Agentic reasoning systems increasingly interact with environments whose states are only partially observed, dynamically evolving, and constrained by physical, biological, or logical structure. Existing agentic reasoning frameworks often model internal reasoning, tool use, and post-training adaptation using flat latent representations and struggle in curved manifold space environments. However, many scientific and embodied domains naturally lie on curved state spaces, including tissue geometry, developmental trajectories, protein conformations, robotic configuration spaces, and constrained physical systems. We introduce Manifold Agentic Reasoning, a geometric framework that extends agentic reasoning from Euclidean latent spaces to Riemannian manifolds. In the proposed framework, observations are encoded as manifold-valued states, memory is retrieved by geodesic similarity, candidate hypotheses are generated in tangent spaces, predicted transitions are projected by exponential maps, and decisions are admitted through verification-gated commitment or repaired by manifold self-correction. We further extend the framework to graph-agentic manifold reasoning, where node states live on manifolds and neighbor information is transported by logarithmic maps before attention-based aggregation. Manifold agent reasoning moves AI past brittle, prompt-chained templates to solve four critical production flaws: silent hallucinations and reasoning drift, brittle tool and context misuse, the black-box evaluation problem and stiff behavior profiles. To evaluate the framework, we introduce a Curved Tissue Manipulation and Recovery benchmark in which an agent must repair damaged tissue on a curved manifold. Simulated results show that the full manifold-agent substantially outperforms both a baseline reasoning agent and a full flat-agent reasoning system, achieving higher recovery success, lower geodesic shape error, lower pattern error, and fewer invalid transitions. Curvature and ablation studies indicate that the performance gain is driven by geometry-aware reasoning, verification, memory, and self-repair. These results suggest that manifold-aware agentic reasoning provides a principled foundation for reliable scientific and embodied AI systems operating in curved, constrained, or mechanistic domains.

bioinformatics↗

bioRxiv2026

Quantum-Classical Reservoir Computing to Predict Influenza H3N2 Antigenic Distance

Accurate prediction of antigenic distance between influenza A/H3N2 strains is essential for timely vaccine strain selection, yet traditional hemagglutination inhibition (HI) assays are labour-intensive and limited in throughput. We present FluQRC, a hybrid Quantum-Classical Reservoir Computing framework for sequence-based antigenic distance prediction. FluQRC integrates three novel components: (1) a differentiable gated property ranking network for data-driven property selection, (2) a dimensionality reduction network that compresses the feature representation into a form suitable for quantum processing, and (3) a hybrid quantum-classical reservoir computing architecture for antigenic distance prediction. Experiments on two datasets covering 1963-2002 (271 strains, 73,441 pairs) and 2003-2025 (888 strains, 788,544 pairs) show that FluQRC outperforms four established baselines across all three evaluation metrics (MAE, RMSE, R2). On the larger and more challenging 2003-2025 dataset, FluQRC achieves MAE = 0.369, RMSE = 0.635, and R2 = 0.900, corresponding to a 20.3% reduction in MAE and a 14.3% reduction in RMSE relative to the strongest baseline, while raising R2 from 0.862 to 0.900. These results demonstrate the scalability and effectiveness of FluQRC for large-scale antigenic distance prediction.

bioinformatics↗

bioRxiv2026

Circulating APOH promotes aortic dissection by activating the vascular smooth muscle cell NR5A1-PPARγ pathway.

IntroductionsAortic dissection (AD) is a life-threatening vascular disease with limited therapeutic targets. Apolipoprotein H (APOH), a circulating glycoprotein implicated in lipid metabolism, has not been studied in AD. MethodsPlasma APOH levels and aortic deposition were examined in AD patients. A {beta}-aminopropionitrile (BAPN) and angiotensin II (Ang-II)-induced mouse AD model with AAV-mediated Apoh knockdown was used to evaluate survival, aortic dilation, and extracellular matrix remodeling. Transcriptomic profiling, chromatin immunoprecipitation, and gene silencing in human aortic vascular smooth muscle cells (HAVSMC) were performed to dissect the mechanism. PPAR{gamma} agonist rescue was conducted in vivo. ResultsAPOH was elevated in plasma and deposited in AD aortas. Apoh knockdown improved survival, reduced AD incidence and ascending aortic dilation, and attenuated elastic fiber disruption and collagen deposition. Transcriptomics revealed enrichment of the PPAR pathway. APOH promoted HAVSMC phenotypic switching from a contractile to a synthetic state, decreasing ACTA2/TAGLN and increasing OPN/MMP9. Mechanistically, APOH upregulated NR5A1, which directly bound the PPAR{gamma} promoter to enhance PPAR{gamma} and FABP4 expression. Silencing NR5A1 or PPAR{gamma} reversed APOH-induced phenotypic switching and inflammation. In vivo, PPAR{gamma} agonist diminished the protective effects of Apoh silencing. ConclusionAPOH promotes AD progression through the NR5A1-PPAR{gamma} axis, driving vascular smooth muscle cell phenotypic switching and inflammation, and represents a potential therapeutic target. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=142 SRC="FIGDIR/small/739043v1_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@6c4196org.highwire.dtl.DTLVardef@145f5a2org.highwire.dtl.DTLVardef@19bdborg.highwire.dtl.DTLVardef@19f5019_HPS_FORMAT_FIGEXP M_FIG C_FIG Circulating APOH promotes aortic dissection through the NR5A1-PPAR{gamma} axis in human aortic vascular smooth muscle cells. Clinical observations showed that plasma APOH levels were elevated in patients with aortic dissection. Circulating APOH acts on human aortic vascular smooth muscle cells (HAVSMC) and upregulates NR5A1, which binds to the PPARG promoter and enhances PPAR{gamma} transcription. Activation of the NR5A1-PPAR{gamma} signaling axis promotes the phenotypic transition of HAVSMCs from a contractile phenotype to a synthetic phenotype, as indicated by decreased ACTA2 and TAGLN expression and increased OPN and MMP9 expression, accompanied by enhanced production of the inflammatory mediators IL-6, MCP-1, and TNF-. Silencing NR5A1 or PPAR{gamma} reverses APOH-induced phenotypic switching and inflammatory responses, supporting the critical role of the NR5A1-PPAR{gamma} axis in APOH-mediated vascular injury.

genomics↗

bioRxiv2026

scSAID: A Comprehensive Cross-Species Single-Cell Skin Atlas Reveals Species-Specific Responses to Psoriasis

Single-cell RNA sequencing has rapidly expanded the scale of skin transcriptomic data, yet these datasets remain fragmented across studies spanning different species, diseases and experimental manipulations. An up-to-date, comprehensive, and queryable single-cell cross-species repository for skin is still lacking. Here, we present scSAID (skin-scsaid.com), a single-cell database with an interactive web portal offering a broad suite of in-depth analyses for human and mouse skin. It integrates more than 1.2 million high-quality cells collected from 252 samples, establishing a unified reference for cell-type annotation, cross-species comparison and pathological studies. Using psoriasis as a case study, we demonstrate how scSAID can be used to evaluate how faithfully mouse models reproduce human pathology. Systematic comparison with the imiquimod-induced mouse model revealed numerous species-specific molecular signatures of psoriasis, including human-specific NFKB1 activation and STAT1 involvement, indicating that the current mouse model captures only limited aspects of the disease. We further introduce psoSpotter, a disease-biomarker-selection algorithm that, coupled with in silico perturbation using scSAID data, uncovers PPIA as a novel psoriasis drug target, illustrating the potential of scSAID for identifying therapeutic approaches. Overall, scSAID delivers a large-scale, cross-species skin single-cell resource and analysis platform, opening new opportunities for the discovery of disease-relevant targets in skin diseases.

bioinformatics↗