Biology subjects

Wang, J.

Publications and source records attributed to Wang, J..

At least 163 records · Page 9Linked to original sources

bioRxiv2026

Humanized Anti-PD-1 Antibodies Generated Using The Conditional Kernel-Elastic Autoencoder

The human immune system excels at generating highly effective antibodies through natural selection and somatic hypermutation, but adapting these antibodies for therapeutic use, referred to as "antibody medicine-likeness", requires careful consideration of biochemical and physiological properties. Traditional redesign methods are often slow and limited in scope. In this study, we introduce a machine learning-based approach to evolve new anti-PD-1 antibodies within a chemically informed latent space using a conditional kernel-elastic autoencoder (CKEA) between nivolumab and pembrolizumab, both of which bind the FG-loop "hotspot" of PD-1 in the most distantly related orientations, differing by 174{degrees}. This generative framework is designed to preserve favorable therapeutic features while exploring variants with different potency, ultimately for improved potency. To evaluate structural and functional viability, we performed molecular dynamics (MD) simulations of the generated antibody - PD-1 complexes and described their MD properties. These simulations reveal detailed free-energy landscapes and identify stable binding conformations, providing a strong basis for experimental validation. To validate our designs, we expressed and experimentally tested the antibodies for binding affinity to PD-1. Upon expression and purification, three out of six designed antibodies exhibited some binding to PD-1, whose properties could likely be improved using other computational saturation mutagenesis or laboratory evolution. Our results demonstrate the potential of artificial intelligence (AI)-guided interpolation methods to generate novel, high-affinity antibodies with therapeutic promise, offering a powerful strategy for next-generation antibody development. SYNOPSIS TOCCombination of MD simulations with machine learning algorithms could revolutionize the antibody-breeding sciences to lead to new antibody discovery that is compatible with or better than naturally occurring antibodies. Topics of Content (TOC)Fingerprints of R86 finger of PD-1 are recognized by our designed P2N_2 anti-PD-1 antibody according to our MD simulations O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=173 SRC="FIGDIR/small/742579v1_ufig1.gif" ALT="Figure 1000"> View larger version (49K): org.highwire.dtl.DTLVardef@130fd5aorg.highwire.dtl.DTLVardef@1495cd8org.highwire.dtl.DTLVardef@16e822forg.highwire.dtl.DTLVardef@25004c_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2026

MetaAMI: A Novel Meta-Learning Approach for Predicting In-Hospital Mortality in Acute Myocardial Infarction

Acute myocardial infarction (AMI) is one of the leading cardiovascular diseases worldwide and remains a major cause of mortality. Early risk prediction can help clinicians identify high risk patients shortly after admission and support timely monitoring and individualized treatment. Previous AMI risk assessment approaches predominantly rely on a single model structure or fixed feature representation, which may limit their ability to capture diverse risk related patterns and reduce predictive performance. To address these challenges, we propose MetaAMI, a random projection based meta-learning framework for AMI outcome prediction. Specifically, patients were selected based on ICD-9 and ICD-10 diagnostic codes for AMI from the Medical Information Mart for Intensive Care IV (MIMIC-IV) v3.1 database. Features were transformed through multiple random projections, with each random projection generating a distinct lower dimensional feature representation. Subsequently, baseline classifiers were trained on each lower dimension representation to predict in-hospital mortality among AMI patients. The predictions were aggregated to construct an integrated feature representation, which was used as input to a meta-learner architecture. By effectively integrating complementary information from diverse baseline models, the meta-learner refined the decision boundary and enhanced overall predictive performance. Survival analysis and SHapley Additive exPlanations (SHAP) analysis were further performed to evaluate clinical utility and interpret the model predictions. Benchmarking results based on MIMIC-IV dataset suggested that our MetaAMI consistently outperformed all the baseline classifiers across seven evaluation metrics including Accuracy, Area Under the Curve (AUC), F1 Score, G-Measure, Jaccard Index, Youden J, and Matthews Correlation Coefficient (MCC). In addition, feature importance analysis showed clinically relevant predictors of in-hospital mortality. In summary, MetaAMI provides an effective and robust solution for machine learning based AMI risk prediction. We anticipate that the application of MetaAMI will have a positive impact on clinical risk stratification and personalized treatment strategies for AMI.

bioinformatics↗

bioRxiv2026

Enhancing Recombinant Vector Assembly Efficiency: A Novel Methodological Approach

With the rapid development of modern biotechnology, DNA vectors have become fundamental tools for inserting, transferring, and expressing specific gene sequences in various fields such as gene cloning, gene expression, gene editing, and gene therapy. However, when dealing with complex structured DNA sequences, traditional vector construction methods face challenges with low connection efficiency. This study proposes a new method for constructing recombinant vectors by employing a strategy of high-temperature treatment followed immediately by placement on ice, effectively reducing the complexity of DNA structures and enhancing the efficiency of PCR product-vector connection, thereby improving the construction efficiency of recombinant vectors. This paper describes the technical details of the method, experimental validation, and applications in gene cloning, gene recombination editing, and the preparation of gene therapy drugs, providing a new efficient tool for molecular biology experiments.

biochemistry↗

bioRxiv2026

Prompting Beyond Pairs: Decoupled Semantic Supervision for Knowledge-Guided Multiplex Virtual Staining

Virtual staining provides a non-invasive alternative to fluorescence microscopy, yet existing deep learning approaches fundamentally rely on pixel-aligned, multiplexed fluorescence targets for supervision. This dependence on rigidly paired data limits scalability, constrains flexibility in generating diverse subcellular structures, and becomes impractical in data-scarce biological settings. In this work, we introduce a semantic supervision paradigm for virtual staining, demonstrating that domain-knowledge prompts can effectively replace conventional pixel-level supervision. Unlike existing methods constrained by rigidly paired multiplex targets, our framework leverages biological prompts to decouple structural guidance from image translation. This decoupling enables high-fidelity, independent synthesis of multiple subcellular structures using only single-channel data. To ensure high-fidelity generation under weak supervision, we integrate self-supervised representation learning to mitigate data scarcity and incorporate direct preference optimization to suppress structural artifacts. Evaluations on the JUMP benchmark demonstrate that our approach effectively balances flexibility and fidelity, outperforming supervised baselines with a 43.3 % reduction in Average FID and an Average PCC of 0.912, while exhibiting high robustness in channel-deficient scenarios. Furthermore, the model generalizes across four in-house datasets to successfully multiplex six subcellular structures, overcoming the physical constraints of conventional fluorescent staining.

bioengineering↗

bioRxiv2026

Direct targeting of the WAVE-regulatory complex and the actin cytoskeleton by the Anaplasma phagocytophilum effector, AnkA

The obligate intracellular tick-borne pathogen Anaplasma phagocytophilum is unusual in its tropism for neutrophils, within which it survives and replicates. Central to the ability of this bacterium to colonize this hostile niche are secreted effector proteins. One such effector protein, AnkA, interacts with multiple host ligands in both the cytoplasm and the nucleus, yet how these interactions promote infection is largely unknown. We discovered that AnkA directly binds both the WAVE Regulatory Complex (WRC), a signal-integration hub that regulates the formation of branched actin networks underpinning diverse cell functions, and to monomeric and filamentous actin. We determined that AnkA uses two forms of molecular mimicry, first by binding to the Abi1 component of the WRC via a WRC-Recruiting Abi-binding Peptide (WRAP), and second by binding to actin via a WH2-like Actin Binding Motif (ABM). Via these interactions, AnkA can exert multi-factorial influence on the actin cytoskeleton and signaling pathways converging on this host structure. AnkA and the WRC co-localise during bacterial internalization and during the late stages of infection, suggesting a central role in both host-cell colonization and bacterial dissemination. Our work reveals AnkA as the first example of a bacterial effector that directly targets the WRC. The co-occurrence of WRAP- and ABM-like motifs in other bacterial effector proteins suggests that this mechanism of actin cytoskeleton subversion may represent a conserved strategy used by other obligate intracellular bacteria.

microbiology↗

bioRxiv2026

Catch-bond engineering surpasses high-affinity maturation for T cell receptor therapies against solid tumors

The sensitivity of T cell receptors (TCRs) has traditionally been attributed to their affinity, a principle that has long underpinned both T cell biology and TCR engineering. Currently, high-affinity maturation remains the predominant strategy employed to enhance TCR sensitivity; however, this approach has been associated with severe off-target toxicities in clinical settings. In this study, using the only FDA-approved TCR-T therapy as a clinical reference, we demonstrate that force-induced catch bonds, rather than static affinity, primarily determine TCR sensitivity and facilitate the development of more effective TCR engineering strategies. Among polar and charged amino acids, histidine was determined to be the most effective residue for pinpointing engineering hotspots. TCRs engineered to form catch bonds exhibited superior performance compared to the FDA-approved TCR subjected to high-affinity maturation, improving the efficacy of TCR-T cell therapies against solid tumors without eliciting off-target toxicity or alloreactivity. Mechanistically, a correlation was observed between TCR sensitivity and the strength of catch bonds, whereas no such relationship was found with affinity. The duration of T cell-tumor cell interactions, immunological synapse formation, and the intensity of subsequent signaling are governed by catch bonds rather than by affinity. Structural and computational investigations have demonstrated that force-induced reconfiguration of the ligand-receptor interface, along with the formation of a novel hydrogen bond network, augments the specificity of interactions between the TCR and antigenic peptides. Furthermore, bispecific T cell engagers utilizing the TCR scaffold also formed catch bonds with tumor antigens, indicating intrinsic mechanosensory properties of the extracellular domains of TCRs and suggesting a novel therapeutic modality based on catch-bond-engineered TCRs.

immunology↗

bioRxiv2026

A hierarchical activation threshold shapes RSV F antibody repertoires from toddler vulnerability to adult protection

Respiratory syncytial virus (RSV) causes severe infant morbidity, yet the mechanisms underlying their suboptimal immunity and the failure of prefusion F-stabilized adult vaccines in infants remain unclear. Here we integrate deep mutational scanning of 761 preF-binding antibodies, repertoire profiling of 102 repeatedly exposed pediatricians and 61 RSV-experienced toddlers, structural analysis, and >40,000 viral genomes to decode RSV F immunity. We resolved 12 immunologically distinct functional antibody subclasses and uncovered a hierarchical activation threshold: apical epitope-targeting antibodies with superior neutralizing potency demand extensive somatic hypermutation and cooperative CDR networks, whereas central-to-basal epitope-directed, marginal or non-neutralizing antibodies engage germline-encoded antibodies through minimal mutations (e.g., S31G). Toddler repertoires are confined to low-threshold, non-productive sites; adult repertoires enrich for apical elite neutralizers whose immune pressure drives contemporary RSV-B evolution. These reframe pediatric RSV vulnerability as a threshold-gated repertoire deficit and prescribe vaccine strategies that actively redirect immunodominance from permissive epitopes toward high-barrier apical targets.

immunology↗

bioRxiv2026

Uncovering key genes related to potato tuber starch concentration from the tuber bulking, maturation stage to storage

Potato is the worlds fourth major staple crop, and tuber starch is a critical dietary energy source and a food processing raw material. In this study, hybrid progenies of the high-starch cultivar Huasheng No.7 and China main commercial varieties were used as materials, high-throughput sequencing was performed on tuber samples at tuber bulking, maturation and storage stages. Combined with bioinformatics analysis, parent-progeny resequencing, SNP screening, the regulatory mechanism of tuber starch metabolism was explored. The results showed significant stage-specific transcriptional reprogramming in potato tubers: few differentially expressed genes (DEGs) were identified at tuber bulking and maturation stages, but massive transcriptional changes occurred during storage. XET family genes regulated cell wall remodeling and carbon translocation across all stages, and WRKY transcription factors specifically controlled starch homeostasis in stored tubers. The DEGs at different stage were induced by the SNPs from their parent, and the allele from the high-starch parent, Huasheng 7 may contribute the high-starch allele to the offsprings. One key gene, Soltu.DM.02G019910, which encoded {beta}-glucosidase, have a negatively relationship with tuber starch concentration. The low-starch potato breeding tubers shown higher significantly {beta}-glucosidase activity than high-starch breeding population at maturation stage. This study clarifies the molecular regulatory network of potato tuber starch metabolism and screens core regulatory genes from the tuber bulking stage to tuber storage, thereby providing theoretical support and genetic resources for molecular breeding of high-starch and storage-resistant potato varieties.

plant biology↗

bioRxiv2026

Characterizing Functional Clusters of V4 Neurons in Digital Twins

Neurons in primate visual cortical area V4 display tuning for multiple visual features, including color, shape, texture, and depth. Whether and how these neurons are organized into functional architectures remains largely unknown. Using two-photon calcium imaging in anesthetized macaques, we recorded responses of hundreds of V4 neurons to natural images and used these data to train deep convolutional neural network models (digital twins), obtaining synthetic images (SI) that maximized neuronal responses. Based on their SIs, these neurons clustered into classes that spatially matched the orientation, color, and curvature maps from intrinsic signal imaging. Furthermore, lesion study in digital twins revealed different integration rules for different neuron classes. Thus, digital twins of V4 neurons can be applied as a promising tool to characterize neurons fundamental features, which underlie the functional clustering in this area. HighlightsO_LINeurons in V4 are examined with two-photon calcium imaging and DCNN modeling (digital twins) C_LIO_LISynthetic images derived from neurons digital twins reveal distinct neuron groups C_LIO_LIThese groups match functional types defined by intrinsic signal optical imaging C_LIO_LILesion study in digital twins demonstrates neural mechanisms underlying feature tuning C_LI

neuroscience↗

bioRxiv2026

Cross-Species Efficacy of Combinatorial Gene Therapy for Osteoarthritis and Correction of Neuro-Inflammatory Pain Mechanisms

Osteoarthritis is a leading cause of chronic pain and disability, which lacks disease-modifying treatment. Given the complex multi-tissue and multifactorial drivers behind disease progression, effective treatments will require simultaneously targeting several mechanisms underlying joint degeneration and pain. Here, we developed and evaluated a combinatorial gene therapy, consisting of a high-capacity adenoviral vector carrying two therapeutic genes to target distinct pathological mechanisms: inflammation (IL-1Ra) and chondrocyte health (PRG4). Intra-articular delivery of this treatment improved functional, structural, and pain outcomes in murine and equine osteoarthritis models. In addition, treatment normalized inflammatory environments in joint tissues, as well as in the dorsal root ganglia (DRG) known to harbor joint-innervating sensory neurons. Moreover, gene therapy reversed OA-induced molecular signatures of neural hyperexcitability, suggesting amelioration of peripheral sensitization. Collectively, these findings support combinatorial gene therapy as a promising treatment for osteoarthritis, while identifying neuroinflammatory signatures for correction of disease progression and pain. One Sentence SummaryA single intra-articular injection of a combinatorial gene therapy slows OA progression and reduces pain in small and large animal models.

systems biology↗

bioRxiv2026

A thalamostriatal brake counteracts cortical recruitment of striatal ensembles in levodopa-induced dyskinesia

Levodopa-induced dyskinesia (LID) is a disabling complication of Parkinsons disease therapy, yet how upstream circuits recruit and restrain dyskinesia-linked striatal ensembles remains unclear. Using FosTRAP-based ensemble access in a unilateral 6-hydroxydopamine mouse model, we identified secondary motor cortex (M2) and parafascicular thalamus (PF) as dominant afferents with opposing functions. Projection-wide M2 activation promoted dyskinesia, whereas PF activation suppressed ongoing dyskinesia and shifted behavior toward non-dyskinetic states. Chronic levodopa reduced overall presynaptic terminal abundance while preserving putative contacts onto ensemble neurons, thereby increasing effective pathway-to-ensemble coupling. This remodeling followed distinct pathway rules: M2 contacts became spatially dispersed and biased toward NMDAR-mediated excitation, whereas PF inputs recruited stronger polysynaptic inhibition. Dyskinesia preferentially re-engaged ensemble-projecting M2 neurons, but reactivated PF neurons were topographically segregated from PF neurons directly innervating the ensemble. Accordingly, selective M2-to-ensemble stimulation promoted dyskinesia, whereas selective PF-to-ensemble stimulation was ineffective. Finally, ensemble-restricted Grin1 knockdown reduced peak dyskinesia and weakened M2-driven dyskinesia. These findings define LID as a targetable imbalance between cortical ensemble recruitment and thalamostriatal restraint.

neuroscience↗

bioRxiv2026

An Integrated Multi-omics Single Cell Atlas of the Human RPE and Choroid

The retinal pigment epithelium and choroid are critical for supporting the function and maintaining the homeostasis of the outer retina, and their dysfunction underlies a range of inherited and complex ocular diseases. To comprehensively characterize the cellular, transcriptomic, and epigenomic heterogeneity and dynamics within these tissues, we assembled an integrated multi-omics reference atlas comprising 719,813 single-cell/single-nucleus transcriptomes and 234,007 snATAC-seq profiles from 102 ancestrally diverse donors spanning 0 to 99 years of age, including cells from both the macula and periphery. This atlas resolves 48 distinct cell types or states and catalogs 448,567 open chromatin regions. Specifically, we resolved five distinct RPE subpopulations organized along a central-to-peripheral spatial axis, alongside two distinct stress/senescence states. We reconstructed the transcriptomic and epigenetic zonation of endothelial cells and expanded choroidal stromal heterogeneity by characterizing 11 fibroblast and two pericyte types. Age-associated compositional analysis revealed a significant fractional depletion of melanocytes, PI16+ fibroblasts, and venule endothelial cells with age, alongside a modest relative loss of central RPE and a corresponding increase in far-peripheral RPE. Cell-type-specific aging transcriptomics uncovered shared pathways related to inflammatory responses alongside distinct cell-type-specific signatures. Notably, significant age-associated epigenetic changes concentrated in the macula during the transition from early-to-middle adulthood and remained stable into old age, with transcription factors from the AP-1/bZIP family emerging as the dominant enriched motifs. Finally, integrating this atlas with AMD GWAS data provides novel variant-to-gene evidence implicating LIPG and COL4A3 in AMD pathogenesis. Together, this multi-omics atlas serves as both an invaluable community reference and a powerful discovery engine that translates genetic risk signals into localized target cells and candidate mechanisms, laying a foundation for understanding RPE/choroid biology in health and disease.

genomics↗

bioRxiv2026

Widely used GWAS methods can be poorly suited to SNP-level localization under diffuse polygenic architecture in livestock

In livestock populations, genome-wide association studies (GWAS) can produce strong, apparently localized associations even when no truly discrete nearby causal effect exists. This occurs because small effective population sizes, strong family structure, long-range linkage disequilibrium (LD), and diffuse polygenic architecture can cause the effects of many variants to accumulate and be captured jointly across broad genomic intervals, making variant-level associations difficult to interpret biologically. Using real pig genotypes, we constructed a benchmark in which phenotypes were simulated under diffuse polygenic architecture across a genome partitioned into alternating effect and null windows, with central-null regions (at least 1 Mb away from effect-containing regions) positioned to detect long-range LD-driven signal propagation. We evaluated nine configurations of six GWAS methods (BOLT-LMM, REGENIE, fastGWA, FarmCPU, BLINK, and SLEMM) under this architecture. The central finding is that strong associations, of the kind normally read as evidence of nearby moderate- or large-effect variants, are produced by many of these methods even though the simulated signal is distributed across many tiny effects and cannot be localized to any single variant. The methods differed sharply in the extent of locus-level spillover: several produced large numbers of genome-wide significant loci within central-null regions, whereas the full-GRM mixed-model benchmark (SLEMM) produced no genome-wide significant loci in central-null regions. These results show that, under a highly polygenic architecture with livestock-like LD, GWAS tool choice has major consequences for biological interpretation. When the goal is to localize biologically meaningful signals rather than to flag association peaks that may merely reflect tiny effects accumulated through LD across a broad block, methods that control long-range LD spillover should be prioritized.

genetics↗

bioRxiv2026

Hydrostatic pressure shapes and canalizes semicircular canal morphology to ensure vestibular function

How tissues acquire reproducible shapes to support their function is a fundamental question in developmental biology. Zebrafish semicircular canals form when epithelial pillars partition the lumen of the otic vesicle, the embryonic precursor of the inner ear, into the tubes that sense head rotation for balance. We show that hydrostatic pressure generated by the inflating otic vesicle shapes pillar geometry. Acute vesicle deflation shortens and broadens pillars, whereas pharmacologically induced inflation elongates and narrows them, effects captured by a physical model that treats the vesicle as a pressurized viscoelastic shell. Pillars initially form with variable curvature, but continued vesicle expansion drives them toward a common, straight geometry, a process accelerated by inflation and blocked by deflation. We identify Wnt signaling as crucial for sustaining this pressure by maintaining epithelial barrier integrity. Its disruption impairs pillar geometry and vestibular-dependent swimming behavior. Together, these findings identify hydrostatic pressure as a critical physical mechanism that canalizes tissue geometry to ensure robust organ formation and function.

developmental biology↗

bioRxiv2026

Human antibody heavy chain variable region exon interacts with 3' regulatory region to form a stable somatic hypermutation center

Activation-induced cytidine deaminase (AID) initiates somatic hypermutation (SHM) of immunoglobulin heavy chain (HC) variable region exons in germinal center (GC) B cells, allowing selection of affinity-matured B cell receptors. The V(D)J exon location is privileged for SHM targeting of diverse sequences within it. In analogy to the related HC class switch recombination center, we proposed that cohesin-mediated loop extrusion juxtaposes widely separated enhancers, including 3 Igh regulatory region ("3RR"), with the V(D)J exon in GC B cells to establish a SHM-center (SHM-C) "privileged" for AID access. To test this hypothesis, we employed a human RAMOS GC B lymphoma cell SHM model with inducible AID expression in which we targeted an unmutated mouse HC V(D)J exon in place of its human counterpart. Activation of AID expression in this cycling RAMOS line for 10 days led to robust SHM accumulation in the mouse V(D)J exon with a pattern similar to that in mouse GC B cells. In this model, the mouse V(D)J exon was indeed juxtaposed to the two human 3RRs and other elements consistent with SHM-C formation. While deletion of individual 3RRs had little effect, deletion of both greatly reduced SHM, but left V(D)J exon transcription unabated. Moreover, the SHM-C and SHM accumulation remained intact over a 10-day period in viably G1-arrested and viably G1-arrested RAD21 (cohesin)-depleted versions of the model. We discuss implications for SHM-C structure and function, its long-term functional stability in the absence of the loop extrusion process proposed to assemble it, and for 3RR SHM functions beyond transcriptional activation. Significance StatementUpon encountering pathogens, B cells enter specialized lymphoid structures known as germinal centers (GCs). GC B cells express activation-induced cytidine deaminase (AID) that initiates somatic hypermutation (SHM) of the portion of antibody genes that encodes antigen recognition. B cells in which mutations increase antibody affinity for activating pathogen are selected to enhance antibody responses. We proposed SHM occurs in a chromosomal structure in the antibody gene locus termed a SHM-center (SHM-C). By studying SHM in a human B cell lymphoma model, we provide direct evidence for existence of a SHM-C assembled from different functional components normally separated by considerable distances. We also find that the SHM-C is surprisingly stable and continues to function for many days in non-dividing cells.

immunology↗

bioRxiv2026

Assembly of the ATP-driven cobalt chelatase

Nature has evolved two distinct chelatase families to catalyze the insertion of metal ions into tetrapyrrole macrocycles. Whereas the single-subunit ATP-independent chelatases have been widely investigated, little is known about the three-subunit ATP-driven chelatases. Here we show step-wise assembly of the ATP-driven cobalt chelatase CobSTN that is essential for aerobic vitamin B12 biosynthesis. The motor subunit CobS fits into a hexameric or dodecameric spiral, and forms complex with the adaptor subunit CobT. Upon binding to adenine nucleotide, the spiral transforms to an asymmetrical ring and CobT synergistically rotates and inserts a distinctive shaft into the ring hole. The largest subunit CobN interacts with the opposite side of CobT from the CobS ring, and hence the holoenzyme is assembled.

biochemistry↗

bioRxiv2026

CSOA: A Novel Single-Cell Gene Set Enrichment Analysis Method with Comprehensive Benchmarking

Single-cell gene set enrichment analysis is widely used to evaluate the activity of gene sets in individual cells, as measured by single-cell sequencing technologies. However, existing methods often generate ambiguous scores that cannot reliably distinguish cells enriched for a biological signal from background cells. To address this limitation, we developed Cell Set Overlap Analysis (CSOA), a novel method for gene set enrichment analysis that leverages gene pair relationships by quantifying pairwise overlaps between high-expression cell sets constructed for each signature gene. We benchmarked CSOA against sixteen established methods representing five methodological classes: direct scoring, rank-based scoring, model-based scoring, matrix decomposition, and overrepresentation analysis. Our evaluation framework introduces novel metrics tailored for the gene set scoring problem, such as score coverage and silhouette rank alignment. They are used alongside traditional metrics for binary classification, such as the Matthews correlation coefficient and area under the receiver operating characteristic (AUROC). CSOA showed superior accurate annotation of cell types and specific biological processes compared with competing approaches. This advantage was particularly pronounced in the class boundary determination benchmark, where it ranked the first in all evaluated datasets. CSOA also outperformed most of the compared methods in computational efficiency. Notably, CSOAs combination of outstanding performance in the score coverage metric and solid overall performance positions it as a uniquely well-suited method for distinguishing cells enriched for specific biological signals.

bioinformatics↗

bioRxiv2026

Tracing the 'Panda of the Sea': Species-Specific qPCR Assays for eDNA Monitoring of Critically Endangered Bahaba taipingensis in the Pearl River Estuary

Chinese Bahaba (Bahaba taipingensis, Sciaenidae) is a Critically Endangered, Grade I state-protected marine fish in China. Reliable, non-invasive monitoring tools are urgently needed to inform conservation and restocking efforts. We developed and validated three TaqMan probe-based qPCR assays targeting mitochondrial 12S rRNA, ND5, and control region (D-loop) loci for species-specific detection of B. taipingensis. Primer-probe sets were designed from complete mitochondrial genomes and evaluated in silico against GenBank and in vitro against tissue DNA from B. taipingensis and closely related sciaenids, plus positive eDNA samples; sensitivity was quantified using serial dilutions of synthetic target DNA. All three assays showed high specificity and consistent amplification; 12S rRNA assay (Bhb_12S) was selected for field screening based on superior low-copy sensitivity and minimal by-products. We applied the Bhb_12S assay to 414 seawater samples collected from 23 sites in western Hong Kong during 2025 surveys, detecting B. taipingensis eDNA in the September samples (0.71-2.85 copies per L; mean 2.05), with positive detections confirmed by Sanger sequencing. Overall, these validated qPCR assays provide a robust molecular toolkit for non-invasive monitoring of B. taipingensis and will aid conservation planning, restocking evaluation, and long-term biodiversity assessments in the Pearl River Estuary and adjacent coastal waters.

ecology↗