Biology subjects

Yan, H.

Publications and source records attributed to Yan, H..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Sex-Specific Vulnerability to Radiofrequency Electromagnetic Radiation-Induced Reproductive and Neurological Impairment in Mice

Electromagnetic radiation (EMR) constitutes a pervasive environmental stressor, yet the sex-specific vulnerabilities to its biological effects remain inadequately characterized. This study investigated the differential impacts of 3.2 GHz pulsed EMR on reproductive and neurological functions in male and female mice following a four-week exposure regimen. We identified a pronounced sexual dimorphism in systemic and organ-specific responses. Male mice exhibited a primary vulnerability in the reproductive axis, manifesting as severe spermatogenic impairment, including depletion of the spermatogonial stem cell pool, disruption of sperm chromatin remodeling, and consequent declines in sperm quality and quantity. In contrast, exposed females showed preserved ovarian function but displayed marked neurobehavioral deficits, including increased anxiety- and depressive-like behaviors, and cognitive impairment, which were correlated with neurodegeneration in the hippocampus and prefrontal cortex. Proteomic analyses revealed distinct sex-specific biomarker profiles, with serum levels of Mdk, histone H1 variants (H1-1, H1-4, H1-5), Hp1bp3, Ncf2, and Rhoc strongly associated with male testicular dysfunction, while decreased levels of the synaptic motor protein KIF13A in serum and brain tissue were linked to female neurological impairment. Our findings delineate clear sex-divergent pathological pathways that target male spermatogenesis and female neurocognitive function and propose novel circulating protein biomarkers. This work provides a critical foundation for sex-aware risk assessment and the development of targeted preventive strategies against EMR-associated health risks.

pathology↗

bioRxiv2026

Toward Computationally Complete Spatial Omics

Multimodal spatial omics has transformed biology by mapping molecular complexity within intact tissues, yet current technologies remain limited in the number of modalities measured simultaneously and often produce lower-quality data than single-modality assays. We present COSIE, a computational framework that generates high-resolution, multilayered molecular landscapes across tissue sections, individuals, and platforms. COSIE integrates histology, epigenome, transcriptome, proteome, and metabolome into a unified representation. Applied to 12 datasets spanning 10 spatial technologies, eight modalities, and nine tissue types, ranging from thousands of spots to millions of cells, COSIE outperforms existing methods. It resolves tissue structures, enhances noisy measurements, predicts unmeasured modalities, and captures dynamic processes. In human tumors, COSIE identifies invasive subregions linked to clinical outcomes and predicts spatial gene expression in TCGA samples using only histology images. By transforming fragmented data into comprehensive spatial maps, COSIE advances computationally complete spatial omics and the creation of digital tissue twins for biomedicine.

genomics↗

bioRxiv2026

IntelliFold-2: Surpassing AlphaFold 3 via Architectural Refinement and Structural Consistency

IntelliFold-2 is an open-source biomolecular structure prediction model that improves accuracy and robustness through architectural refinement and multiscale structural consistency. We introduce latent space scaling in Pairformer blocks, a principled atom-attention formulation with stochastic atomization, policy-guided optimization for diffusion sampling and difficulty-aware loss reweighting. On Foldbench, IntelliFold-2 improves performance in therapeutically relevant settings, with particularly strong gains for antibody-antigen interactions and protein-ligand co-folding relative to AlphaFold 3. We release three variants (Flash, v2, and Pro) to cover efficient fine-tuning through high-precision server-side inference.

bioinformatics↗

bioRxiv2026

TREM2 agonist antibody rebuilds the resident synovial macrophage lining barrier in rheumatoid arthritis

Rheumatoid arthritis (RA) can be viewed as a disease of barrier failure, in which CX3CR1+/TREM2+ synovial tissue-resident macrophages that form the lining barrier over cartilage and bone become fragmented and disorganized. However, how to therapeutically rebuild this barrier--and how macrophage states transition during repair--remain unclear. We engineered TR-Ab19, a mouse-selective agonistic antibody against TREM2, as a precision tool to initiate and interrogate barrier repair in vivo. TR-Ab19 engages TREM2-linked downstream signaling and redirects synovial macrophages from Clec4d+ inflammatory/proliferative programs toward TREM2+CX3CR1+Aqp1+ barrier-like states, thereby rebuilding the lining barrier. Across collagen-induced arthritis (CIA) and serum-transfer arthritis (STA) models, TR-Ab19 reduces synovitis, preserves cartilage and bone microarchitecture, limits osteoclastogenesis, and attenuates systemic cytokines and B-cell abnormalities. Single-cell RNA-seq with trajectory and cell-cell communication analyses reveal a TREM2-dependent shift toward a barrier-dominant macrophage ecosystem. Together, these findings establish antibody-mediated reprogramming of resident synovial macrophages as a barrier-centered strategy for RA and provide a framework for instructing macrophage niches in chronic inflammation.

bioengineering↗

bioRxiv2026

DNA-templated Chiral Metamaterial Array as Information Bits

The growth of digital information demands physically secure information bits that combine intrinsic randomness with multi-layered optical readout. Digital metamaterials with physical unclonable function characteristics are promising, but nearly all examples operate at microwave or terahertz frequencies. Extending digital metamaterials to the visible range requires a physical property that allows binary (0/1) encoding via nanoscale geometry and is orthogonal to intensity-or color-based imaging. Chiral plasmonic metamaterials satisfy these criteria perfectly: their broken mirror symmetry yields chirality polarity in the visible spectrum whose sign and magnitude directly encode bit values ("0", spin-up; "1", spin-down), while remaining invisible under linear polarization. Here, we realize visible-range digital metamaterials by programming self-assembled DNA origami templates with asymmetrically placed gold nanorods to create discrete 3D chiral metamolecules. Using on-surface DNA origami assembly and the Silica Microsphere-Assisted Patterning by Liquid Elimination (SiMPLE) method, we fabricate large-scale bit arrays on optical active glass substrate in solution with [~]1.33 m lattice spacing, [~]86% site occupancy, and [~]12-month stability after silicification. These bottom-up fabricated digital metamaterial array exhibits two independent security layers: (1) a macroscopic spatial pattern only visible by dark-field microscopy, and (2) hidden binary information stored in the single-particle chiroptical response, read out by position-resolved circular dichroism spectroscopy. Quantitative analysis confirms reliable bit encoding and high optical randomness arising from slight structural variations. By leveraging the polarity of plasmonic chirality to translate molecular-scale handedness into robust visible-range digital signals, this work establishes a scalable nanophotonic platform for secure optical information storage, authentication, and encryption.

bioengineering↗

bioRxiv2026

Selective Immune Silencing by Targeted TGF-β Agonists

Depletion of pathogenic T and B cells is a pillar of therapies for autoimmune, inflammatory, and transplantation-related immunological diseases. However, adverse events, safety concerns in immunocompromised patients, and disease relapse limit clinical utility. Here, we exploit the immunosuppressive properties of a transforming growth factor beta (TGF-{beta}) mimic repurposed from helminths for cell type-specific therapeutic silencing, as a new approach to complement existing therapies. Mouse CD4 and CD8 T cell-targeted TGF-{beta} agonists selectively and potently silence antigen-specific T cell responses in OVA-immunized mice by suppressing pro-inflammatory effector, cytotoxic, and T follicular helper programs, while skewing cells toward a quiescent state biased toward regulatory and type 17 T cell phenotypes. Similarly, human CD4 and CD8 T cell-targeted TGF-{beta} agonists precisely and effectively suppress live-attenuated influenza vaccine (LAIV)-induced T cell activation and expansion in human spleen organoids. Correspondingly, CD4 T cell-targeted TGF-{beta} agonist effectively ameliorated disease activity and promoted disease remission in CD4 T cell-driven models of autoimmune neuroinflammation and allergic airway inflammation, demonstrating efficacy in both prophylactic and established inflammatory settings. Moreover, both CD4 and CD8 T cell-targeted TGF-{beta} agonists ameliorated disease activity in graft-versus-host disease. Additionally, a human CD19 B cell-targeted TGF-{beta} agonist robustly inhibits germinal center B cell-to-plasmablast maturation and antibody responses in LAIV-stimulated human spleen organoids. These early-stage results suggest that cell-selective TGF-{beta} agonism merits further investigation as a versatile therapeutic approach for the precise silencing of pathogenic adaptive immune responses.

immunology↗

bioRxiv2025

The CCCH Zinc Finger Gene PgCCCH50 from Pearl Millet Confers Drought and Salt Tolerance through an ABA-Dependent PgAREB1-PgCCCH50 Module

Abiotic stresses like drought and salinity severely constrain crop productivity. Pearl millet (Pennisetum glaucum L.), a stress-resilient cereal of global importance, is ideal for deciphering genetic adaptation. Although CCCH zinc finger proteins play key roles in plant stress responses, members with multiple regulatory functions remain unknown in this crop. This study analyzed 53 CCCH genes in pearl millet, examining their phylogeny, structure, chromosomal localization, and promoter cis-elements. Expression profiling revealed seven CCCH genes responsive to multiple stresses. Functional characterization of PgC3H50 showed that its overexpression in Arabidopsis conferred enhanced tolerance to drought and salt, evidenced by improved physiological parameters and upregulation of stress-responsive genes. We discovered that the ABA-responsive transcription factor PgAREB1(ABSCISIC ACID RESPONSIVE ELEMENT BINDING PROTEIN 1) directly binds to ABRE cis-elements in the PgC3H50 promoter and activates its transcription, validated by yeast one-hybrid, dual-luciferase, and EMSA assays. This defines a novel PgAREB1-PgC3H50 regulatory module within the ABA-mediated stress signaling pathway. Our findings provide a valuable genetic resource for the pearl millet CCCH family and unveil a promising candidate gene and transcriptional regulatory module for engineering crops with improved tolerance to drought and salinity. HighlightThis study reports the first genome-wide analysis of the CCCH family in pearl millet and identifies the novel PgAREB1-PgCCCH50 module as essential for salt and drought tolerance.

plant biology↗

bioRxiv2025

Spacing effect improves generalization in biological and artificial systems

Generalization is a fundamental criterion for evaluating learning effectiveness, a domain where biological intelligence excels yet artificial intelligence continues to face challenges. In biological learning and memory, the well-documented spacing effect shows that appropriately spaced intervals between learning trials can significantly improve behavioral performance. While multiple theories have been proposed to explain its underlying mechanisms, one compelling hypothesis is that spaced training promotes integration of input and innate variations, thereby enhancing generalization to novel but related scenarios. Here we examine this hypothesis by introducing a bio-inspired spacing effect into artificial neural networks, integrating input and innate variations across spaced intervals at the neuronal, synaptic, and network levels. These spaced ensemble strategies yield significant performance gains across various benchmark datasets and network architectures. Biological experiments on Drosophila further validate the complementary effect of appropriate variations and spaced intervals in improving generalization, which together reveal a convergent computational principle shared by biological learning and machine learning.

neuroscience↗

bioRxiv2025

RAFTER: a releasing factor tethered RNA editing system for quantifying mRNA translation

Measurement of mRNA translational efficiency has heavily relied on quantifying the amount of polysome-associated RNAs which would not always reflect the efficient translation. To address this, we developed RAFTER, which combined RNA editing enzyme with translation releasing factor to selectively label successfully translated RNAs. The translational efficiency estimated based on RAFTER correlated well with that by Ribo-seq and Polysome-seq, but with greatly simplified workflow, which enables it for single-cell analysis.

genomics↗

bioRxiv2025

Scalable integration and prediction of unpaired single-cell and spatial multi-omics via regularized disentanglement

Deciphering cellular states requires methods capable of integrating large-scale heterogeneous single-cell and spatial omics data. However, these data are typically unpaired due to destructive assays and further confounded by modality heterogeneity, technical noise, and immense scale. Here we present scMRDR, a scalable computational framework based on regularized disentangled representation learning for integrating fully unpaired single-cell and spatial multi-omics datasets. Built on a unified and structure-preserving architecture, scMRDR removes the need for pairing supervision while maintaining computational efficiency, enabling scaling to large datasets spanning multiple disparate omics modalities. Across diverse real-world benchmarks, scMRDR demonstrates strong performance in batch correction, modality alignment, and biological signal preservation. The framework further supports cross-modal translation across omics modalities and enables spatial coordinate imputation for non-spatial single-cell datasets using a reference atlas. The resulting spatial mapping allows spatially resolved analyses, including identification of spatially variable genes and characterization of epigenetic regulatory programs in their native tissue context. These capabilities position scMRDR as a scalable and versatile framework for large-scale multi-omics integration.

genomics↗

bioRxiv2025

Deconvolution of Sparse-count RNA Sequencing Data for Tumor Cells Using Embedded Negative Binomial Distributions

Estimating tumor-specific transcript proportions from mixed bulk samples has potential to inform novel biology. However, estimation accuracy using existing methods in sparse-count data such as microRNA-seq and spatial transcriptomics has yet to be established. We generated a mixed small RNA benchmark dataset to demonstrate analytical challenges. To resolve them, we developed DeMixNB, a semi-reference-based deconvolution model assuming a sum of negative binomial distributions. Applications to miRNA-seq from 856 patients with breast cancer and 3,755 spatial spots from lung cancer generated either clinical or mechanistic insights into tumor cell plasticity. This supports the important utility of DeMixNB to investigate cancer RNomes.

bioinformatics↗

bioRxiv2025

Activation of IRF7/ISG15 axis in microglia inhibits NLRP3 Expression and Improves the Prognosis of Ischemia/Reperfusion in Mice

Ischemic stroke is a leading cause of disability and mortality, with neuroinflammation playing a key role in post-stroke injury. The molecular mechanisms remain incompletely defined. This study explored the functions of IRF7 and its downstream target ISG15 in stroke-associated neuroinflammation and prognosis of ischemic stroke. Bioinformatic analysis of transcriptomic datasets from microglia and ischemic brain tissues identified both molecules as hub genes. Their expression was validated in a mouse transient middle cerebral artery occlusion (tMCAO) model and in microglial cultures exposed to oxygen-glucose deprivation/reoxygenation (OGD/R). The effects of these molecules were assessed using siRNA knockdown, conditioned media assays with SY5Y neuronal cells, in vivo overexpression of ISG15, histological and functional assessments. Both IRF7 and ISG15 were significantly upregulated after stroke. IRF7 knockdown reduced ISG15 expression, whereas ISG15 knockdown did not affect IRF7, suggesting a unidirectional regulatory relationship. Conditioned media from microglia treated with siIRF7 or siISG15 increased SY5Y cell mortality, with a stronger effect in the siISG15 group, highlighting neuroprotective role of ISG15. ISG15 knockdown also enhanced microglial migration. Conversely, microglial ISG15 overexpression in vivo promoted a shift toward reduced neuroinflammation, improved neuronal survival, and enhanced functional recovery. Mechanistically, ISG15 stabilized NLRP3 protein but more strongly decreased its mRNA stability through accelerated degradation. These findings demonstrate that the activation of IRF7/ISG15 axis in microglia inhibits NLRP3 Expression and improve the prognosis of ischemia/reperfusion in mice, with ISG15 exerting stronger neuroprotective effects. Targeting microglial ISG15 may offer a promising therapeutic strategy for ischemic stroke. MAIN POINTSO_LIISG15 shows a stronger neuroprotective effect than IRF7 in ischemic stroke. C_LIO_LIISG15 stabilizes NLRP3 protein but more strongly decreases its mRNA stability. C_LIO_LIMicroglial ISG15 overexpression in vivo improves the prognosis of ischemic stroke in mice. C_LI

neuroscience↗

bioRxiv2025

Small amphiphilic DNA for programmable transmembrane signaling and amplification

Interrogating the sequence-specific DNA/RNA content of a living cell without destroying it, is an elusive goal in biology and diagnostics with transformative potential. A DNA/RNA-based approach, however, must relay the recognition event across the intact lipid bilayer, a step that has long been considered impossible because hydrophilic, massively charged DNA/RNA is incompatible with the hydrophobic membrane interior. Here, we show that DNA branch migration can be driven across a lipid bilayer, converting an intracellular nucleic-acid sequence into an amplified, extracellular optical signal while preserving cell viability and compartmentalization, a synthetic transmembrane signal transduction analogous to natural receptors, such as G-protein-coupled receptors (GPCRs), but operating in reverse. We demonstrate this principle with Hybridization Across Lipid for Oligonucleotide Sensing (HALOS), an amphiphilic DNA hairpin comprising a toehold for recognition, a stem for stability, a loop, and cholesterols for transmembrane anchoring. Upon binding to a sequence-specific nucleic acid target, toehold-mediated strand invasion drives DNA branch migration across the bilayer, switching HALOS from a closed to an open conformation that relays the signal to the opposite face. Molecular dynamics simulations revealed that a cholesterol belt stabilizes the DNA stem within the membrane, preserving the hairpin structure necessary for transmembrane signaling. Notably, this branch migration proceeds despite the kinetic barrier of hybridization through the hydrophobic bilayer interior. By combining HALOS with an isothermal hybridization chain reaction (HCR), we established a platform that enables intracellular nucleic acid target detection and amplified fluorescent reporting from outside synthetic vesicles and live mammalian cells, achieving nanomolar-range sensitivity. These results establish DNA branch migration across lipid membranes as a design principle for programmable lysis-free molecular sensing in intact cells.

biophysics↗

bioRxiv2025

Secondary lymphoid organ endothelial cells prime alloreactive CD4+ T cells to trigger acute graft-versus-host disease

Donor CD4 T cell priming is a pivotal determinant of acute graft-versus-host disease (aGvHD) after allogeneic hematopoietic cell transplantation (allo-HCT). While professional hematopoietic antigen-presenting cells (APCs) have long been implicated in the pathogenesis of aGvHD, the contribution of non-hematopoietic APCs has remained unclear. Here, we show that naive alloreactive CD4 T cells initially localize and activate specifically within secondary lymphoid organs (SLOs) before infiltrating target tissues. Using genetic models to selectively ablate MHC class II on endothelial cells (ECs) or hematopoietic cells, we demonstrate that blood endothelial cells (BECs) in SLOs function as APCs, efficiently processing and presenting antigen to prime donor CD4 T cells. Deletion of MHC class II (MHCII) specifically in ECs substantially attenuates T cell activation and protects mice from lethal aGvHD, whereas selective deletion of MHCII in lymphatic ECs has no effect. Likewise, selective deletion of MHCII in hematopoietic cells also protects mice against aGvHD, suggesting that both cell types contribute to pathogenic allogeneic T cells activation after allo-HCT. Mechanistically, IL-12/IFN{gamma} signaling upregulates MHC class II expression on BECs. These findings identify BECs in SLOs as initiators of alloreactive CD4 T cell responses and highlight a potential target for preventing aGvHD. HighlightsO_LIBlood endothelial cells in secondary lymphoid organs prime naive CD4 T cells to trigger acute GvHD. C_LIO_LIT cell activation occurs exclusively in secondary lymphoid organs before tissue infiltration. C_LIO_LIExpression of MHC class II only on endothelial cells is sufficient to drive lethal GvHD, independent of other antigen presenting cells. C_LIO_LIRegulation of MHC class II expression in blood endothelial cells by IL-12/IFN{gamma} offers the potential for new therapeutic targets and corroborates findings for existing therapeutics. C_LI

immunology↗

bioRxiv2025

Transfer Learning for Survival-based Clustering of Predictors with an Application to TP53 Mutation Annotation

TP53 is the most frequently mutated gene in human cancers, and germline mutations in TP53 cause Li-Fraumeni syndrome (LFS), a hereditary predisposition to diverse cancers. Accurate annotation of TP53 mutations based on their survival effects is critical for informed LFS patient management. Motivated by this need, we develop a new approach for Survival-based Clustering of Predictors (SCP) by identifying homogeneous coefficients in Cox regression. We formulate this task as a fusionpenalized Cox regression problem and provide an efficient computational algorithm. A nonconvex distance-to-set penalty is adopted to facilitate parameter tuning and improve estimation accuracy. To overcome data limitations, we further develop TLSCP, a transfer learning extension that borrows coefficient ranking information from a source dataset under the assumption of similar ranking patterns between source and target. TL-SCP integrates ranking information through weighted rank averaging, allowing flexibility in accommodating cohort heterogeneity while maintaining model simplicity. Simulation studies demonstrate TL-SCPs superior performance over SCP in clustering recovery and coefficient estimation. In the application of TP53 mutation annotation where we utilize non-LFS germline TP53 mutation carriers as a source cohort for the target LFS cohort, TL-SCP identifies biologically meaningful TP53 mutation clusters and offers improved clinical interpretability compared to experiment-based annotations.

genetics↗

bioRxiv2025

CDCA7 facilitates MET1-mediated CG DNA methylation maintenance in centromeric heterochromatin via histone H1

DNA methylation is a conserved epigenetic modification essential for maintaining genome stability. However, how methyltransferases maintain CG methylation within compact chromatin, including centromeres, remains unclear. In humans, CDCA7 is necessary for the inheritance of DNA methylation at juxta-centromeres. Mutations that impair its ability to bind chromatin result in Immunodeficiency, Centromeric Instability, and Facial Anomalies (ICF) syndrome, characterized by centromeric instability. To investigate whether CDCA7 function is conserved, we identified two Arabidopsis thaliana orthologs, CDCA7A and CDCA7B. The loss of both copies results in CG hypomethylation at pericentromeric regions and centromeric satellite repeat arrays. Machine learning analysis suggested that heterochromatic nucleosomes, with enrichment of H1, H2A.W, and H3K9me2 levels, depend heavily on CDCA7 proteins for CG methylation maintenance of the associated DNA. Loss of H1 restores heterochromatic DNA methylation in cdca7a cdca7b mutants, indicating that CDCA7A and CDCA7B mainly remodel H1-containing nucleosomes for methyltransferases to access DNA. Notably, in h1.1 h1.2 mutants, CG methylation shows a significant increase in centromeres, which reveals a new inhibitory role of H1 in DNA methylation maintenance within satellite repeat arrays. Centromeric DNA hypermethylation is lost in h1.1 h1.2 cdca7a cdca7b quadruple mutants, demonstrating that CDCA7A and CDCA7B can act independently of H1 to enhance MET1 activity. Overall, these findings establish CDCA7A and CDCA7B as conserved regulators of DNA methylation within heterochromatin and centromeric satellite repeat arrays.

molecular biology↗

bioRxiv2025

Designing smart spatial omics experiments with S2Omics

Spatial omics technologies have transformed biomedical research by enabling high-resolution molecular profiling while preserving the native tissue architecture. These advances provide unprecedented insights into tissue structure and function. However, the high cost and time-intensive nature of spatial omics experiments necessitate careful experimental design, particularly in selecting regions of interest (ROIs) from large tissue sections. Currently, ROI selection is performed manually, which introduces subjectivity, inconsistency, and a lack of reproducibility. Previous studies have shown strong correlations between spatial molecular patterns and histological features, suggesting that readily available and cost-effective histology images can be leveraged to guide spatial omics experiments. Here, we present S2Omics, an end-to-end workflow that automatically selects ROIs from histology images with the goal of maximizing molecular information content in the ROIs. Through comprehensive evaluations across multiple spatial omics platforms and tissue types, we demonstrate that S2Omics enables systematic and reproducible ROI selection and enhances the robustness and impact of downstream biological discovery.

genomics↗

bioRxiv2025

Convergent utilization of APN receptor by hedgehog merbecoviruses

Dipeptidyl peptidase-4 (DPP4) and angiotensin-converting enzyme 2 (ACE2) are well-established receptors for merbecoviruses, yet the receptor usage of merbecoviruses of European and Asian hedgehogs (EriCoVs) remains unknown. Here, by testing hedgehog orthologs of known coronavirus receptors, we identify hedgehog aminopeptidase N (APN) as a functional receptor for EriCoVs. Analysis of 94 APN orthologs indicates that EriCoVs have a limited host range, primarily utilizing hedgehog APN and, to a lesser extent, APN from certain felids, shaped by specific determinants at the virus-receptor interface. Cryo-EM reveals an APN-binding mode distinct from those used by alpha- and deltacoronaviruses. Functional assays indicate that hedgehog transmembrane serine protease 2 (TMPRSS2) enhances spike activation and promotes pseudovirus entry. Neutralizing antibodies targeting RBD and APN were developed and could effectively block EriCoV pseudovirus entry and propagation. These findings reveal an unexpected convergent evolution of APN utilization among merbecovirus, establishing a foundation for risk assessment and countermeasure development. Graphic abstractConvergent utilization of hedgehog APN by EriCoVs O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/676546v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@1ea334aorg.highwire.dtl.DTLVardef@cd53bforg.highwire.dtl.DTLVardef@352102org.highwire.dtl.DTLVardef@a1eed_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗