Biology subjects

Cai, H.

Publications and source records attributed to Cai, H..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Discovery of Selective Nrf2 Activators from Natural Products: AComputational Screening Approach to Minimize Off-Target Effects on PXR and CYP2D6

Nuclear factor erythroid 2-related factor 2 (Nrf2) is a central regulator of cellular antioxidant responses and a highly promising therapeutic target for a range of oxidative stress-related diseases. However, the clinical translation of Nrf2 activators has been hampered by significant off-target effects--notably unintended activation of the pregnane X receptor (PXR) and inhibition of cytochrome P450 2D6 (CYP2D6)--which can lead to dangerous drug-drug interactions and metabolic complications. To overcome this critical barrier, we conducted the first large-scale computational screening of 628,898 natural products from the COCONUT database, integrating molecular docking with a rigorous three-tier selectivity strategy designed to prioritize compounds that strongly bind KEAP1 (the primary Nrf2 repressor) while minimizing interactions with PXR and CYP2D6. Our innovative approach identified 10 ultraselective candidates that demonstrate potent KEAP1 affinity, negligible PXR engagement, and only moderate CYP2D6 binding--achieving up to 12.29-fold selectivity for Nrf2 pathway activation. These top hits are structurally novel, enriched in lipid-like and nucleoside-inspired scaffolds, and exhibit promising drug-like properties. By providing both a curated set of chemically diverse, selectivity-optimized leads and a publicly accessible screening dataset, this work establishes a new foundation for the rational development of safer, more precise Nrf2-targeted therapies, bridging a crucial gap between target potential and clinical viability. By prioritizing compounds with minimal off-target effects on PXR and CYP2D6, our approach offers a scalable template for reducing drug development failures and advancing safer therapeutics for oxidative stress-related diseases. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=124 SRC="FIGDIR/small/718057v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@13c6c79org.highwire.dtl.DTLVardef@1f5a078org.highwire.dtl.DTLVardef@fa4f4borg.highwire.dtl.DTLVardef@16bc881_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO C_FIG

bioinformatics↗

bioRxiv2026

TCMCard: A High-Confidence Digital Infrastructure for Traditional Chinese Medicine Quantified by Multi-Dimensional Evidence Integration

Network pharmacology has become a widely used approach for deciphering multi-component, multi-target mechanisms of traditional Chinese medicine (TCM). Here we introduce TCMCard, a high-confidence digital infrastructure built on a Multi-Dimensional Evidence Integration (MDEI) framework. The framework integrates experimental activity data from authoritative chemical databases, literature-derived evidence, and structure-based similarity inference. Preprocessing steps include chemical structure normalization, species-specific filtering, and target quality scoring. Applied to conventional interaction datasets, this pipeline leads to the removal of over 60% of low-confidence noise. TCMCard supports network pharmacology exploration through an interactive visualization platform, and module analysis identifies functionally relevant communities that offer insights into the synergistic actions of TCM formulas. Overall, TCMCard may help move the field beyond simple data aggregation toward evidence-informed curation and quality-driven analysis. As an interactive and publicly accessible platform, it reveals an organized backbone within complex interaction networks, offering a more reliable basis for understanding multi-component synergy in TCM.

bioinformatics↗

bioRxiv2026

A Targeting Parameter Space for Personalized 4x1 HD-tES: Montage Description, Optimization and Application

BackgroundPersonalized optimization of 4x1 high-definition transcranial electrical stimulation (HD-tES) faces inherent trade-offs between montage flexibility, computational efficiency, and implementation accessibility. Conventional 10-10 electrode systems constrain placement to discrete landmark positions, while unconstrained optimization relies on stochastic algorithms that risk converging to local optima and requires neuronavigation equipment often unavailable in rehabilitation settings. Here we introduce a scalp geometry-based parameter space (SGP) that parameterizes 4x1 HD-tES montages using three intuitive scalp-defined parameters--position, radius, and orientation--and characterize parameter-performance regularities through exhaustive electric field simulations across 30 subjects and 624 cortical targets (>3.6 million configurations). ResultsPosition primarily determined proximity to optimal performance, radius governed the intensity-focality trade-off, and orientation served as fine-tuning. Exploiting these regularities, a minimal search space (SGP-MSS) was constructed that reduced computational complexity by over 90% while guaranteeing global optima identification. Compared with standard 10-10 montages, SGP-MSS achieved up to 99% higher targeting intensity and 126% higher focality (all p < 0.0001). Compared with lead-field-free optimization, SGP-MSS achieved comparable performance with greater cross-subject stability. ConclusionsThe SGP framework enables efficient individualized HD-tES optimization without neuronavigation. Its scalp-based parameterization supports electrode positioning via standard cranial landmark measurements, facilitating translation to routine clinical and home-based rehabilitation settings.

biophysics↗

bioRxiv2026

Transient immune landscape remodelling shapes CD8 T-cell priming during infection

Immune responses to intracellular pathogens require the generation of a CD8 T-cell response comprised of clones with a broad range of T Cell Receptor (TCR) affinities for their cognate peptide. While high-affinity clones clear pathogens during initial infection, low-affinity T-cells are critical to protect against subsequent encounters with mutated pathogens. Low-affinity T-cells are recruited to an immune response despite known mechanisms that limit their expansion and priming. As such, the mechanism safeguarding the recruitment of low-affinity T-cell clones during infection remains unclear. Here, we show that at the start of an infection, the spatial immune architecture is transiently reorganised to initiate broad T-cell priming. In particular, Tregs become segregated from the initial priming site, resulting in a spatio-temporal window during which pathogen-specific T-cell priming is protected from Treg inhibition. Priming induces the expression of CXCR3 in a TCR affinity-dependent manner, which conditions the retention of activated T-cells in the priming region. Inability to express CXCR3 leads to T-cell relocation towards Treg-rich areas, where their expansion is limited by the lack of the costimulatory molecule CD70. Our study redefines the role of Treg during infection and provides a mechanism to explain how the priming and breadth of the CD8 T-cell response is protected during infection.

immunology↗

bioRxiv2026

Modeling Multi-Modal Brain Connectomes for Brain Disorder Diagnosis via Graph Diffusion Optimal Transport Network

Network analysis of human brain connectivity provides a fundamental framework for identifying the neurobiological mechanisms that cause cognitive variations and neurological disorders. However, existing diagnostic models often treat structural connectivity (SC) as a fixed or optimal topological scaffold for functional connectivity (FC). This consequently overlooks the higher-order dependencies between brain regions that are critical for characterizing pathological alterations. Moreover, the distinct spatial organizations of SC and FC complicate their direct integration, as naive alignment methods may distort the inherent nonlinear patterns of brain connectivity. To address these limitations, we propose the Graph Diffusion Optimal Transport Network (GDOT-Net), which models disease-related topological evolution and achieves precise alignment between SC and FC. Unlike existing diffusion studies, the proposed model introduces an evolvable brain connectome modeling approach to infer the complex topological structure of brain networks, unveiling higher-order connectivity patterns linked to specific neuropsychiatric disorders. Furthermore, GDOT-Net incorporates a Pattern-Specific Alignment mechanism, leveraging optimal transport to align structural and functional topological representations in a geometry-aware manner. To capture nonlinear topological relationships between brain regions, a Neural Graph Aggregator Module was developed, which adaptively learns complex node interaction patterns in brain networks. By leveraging this module, GDOT-Net generates highly discriminative representations that form a robust basis for the precision diagnosis of brain disorders. Experiments on REST-meta-MDD and ADNI demonstrate that GDOT-Net surpasses SOTA methods in uncovering structural-functional misalignments and disorder-specific subnetworks. The source code is publicly available at this Link.

neuroscience↗

bioRxiv2026

A pleiotropic hitchhiking model recapitulates alignments between fly wing divergence and variation

The alignment among mutational variance (M), standing genetic variance (G), and macroevolutionary divergence (R) in Drosophila wing shape poses a rate paradox under a simple constraint hypothesis: evolution follows mutational lines of least resistance, yet proceeds orders of magnitude slower than the abundant genetic variation would permit. This is difficult to reconcile with a simple constraint view in which long-term evolution merely tracks the amount of available variation in each direction. Previous explanations invoke deleterious pleiotropy on unmeasured traits or correlational selection on trait combinations, but recent empirical work finds little evidence of fitness costs beyond flight performance. Here, by reanalyzing published data, I show that wing size shows the hallmark of the primary selection target: among all wing traits, size exhibits the lowest ratio of standing genetic to mutational variance, indicating the strongest selective depletion. Based on this empirical observation, I develop a single-axis selection model in which natural selection targets only a single trait while all other traits evolve as correlated byproducts via within-module pleiotropy. This minimal model reproduces both the observed M -G-R alignment and slower-than-neutral divergence rates, explaining micro- and macroevolutionary patterns in fly wings without invoking complex adaptive landscapes. Significance StatementA fundamental question in biology is whether large-scale evolutionary patterns arise from the same processes that drive change within populations. Fly wing shape offers a striking test case: the directions of genetic variation and species divergence are closely aligned, yet wing shape evolves far more slowly than expected -- a rate paradox under a simple constraint hypothesis. I show that this paradox can be explained by a simple mechanism: natural selection on one trait indirectly constrains the evolution of other non-selected traits through within-module pleiotropy. This single-axis selection model reproduces observed evolutionary patterns without requiring complex multivariate selection, and its prediction that wing size is the primary target of selection is supported by reanalysis of published data. The framework applies broadly to any trait that shares mutations with correlated characters.

evolutionary biology↗

bioRxiv2026

Between- and Within-subject Variability in Actigraphy Data: A Case Study on Sleep Patterns in Schizophrenia

Variability in longitudinal health outcomes provides critical insight into disease dynamics, yet most statistical analyses continue to prioritize mean trajectories. This limitation is particularly consequential in psychiatric and mobile health (mHealth) research, where intensive repeated measurements increasingly reveal pronounced heterogeneity and temporal instability that cannot be captured by average responses alone. Standard mixed-effects models typically impose homoscedastic variance assumptions and relegate variability to a nuisance component, despite mounting evidence that both variability information, at both between- and within-subject level, carry independent clinical significance. Here, we describe an improved mixed-effects location-scale model for longitudinal outcomes that simultaneously characterizes mean structure, between-subject heterogeneity, and within-subject fluctuations. The proposed framework explicitly links variance components to both time-invariant and time-varying covariates, extending classical mixed-effects models to accommodate heteroscedastic and dynamically evolving variability. By jointly modeling location and scale parameters, the method enables direct inference on variability (or stability) of the data alongside mean trends. We evaluated the approach using an actigraphy-based mHealth case study of sleep patterns in schizophrenia. Our results demonstrate that explicitly modeling variability uncovers clinically relevant structure obscured by mean-based analyses, underscoring the importance of variability-aware modeling for modern longitudinal and mHealth research.

neuroscience↗

bioRxiv2026

PRISM: Niche-informed Deciphering of Incomplete Spatial Multi-Omics Data

Spatial multi-omics data, characterizing the knowledge of diverse molecular layers, have become indispensable for the in situ analysis of tissue architecture and complex biological processes. Nevertheless, current spatial multi-omics sequencing protocols are often hindered by incompatible protocols, resulting in incomplete spatial multi-omics pairing due to inconsistent field-of-view or spatial resolution. To address this, we present PRISM, a novel computational method tailored for this scenario. PRISM leverages a niche-informed graph to propagate information from paired to unpaired regions, jointly achieving the spatial domain identification and spatial omics imputation. Extensive benchmarking on five diverse simulated and real experimental datasets demonstrated that PRISM outperformed existing methods in spatial multi-omics analysis tasks. Application to the human Parkinsons disease data revealed that PRISM accurately recovered dopamine-associated spatial domains and metabolite distributions masked by incomplete data gaps. PRISM offers a robust solution for bridging the integration gap inherent in incompatible sequencing protocols, thereby facilitating more accurate downstream biological interpretation.

bioinformatics↗

bioRxiv2026

Identification of Lupus Immune Complex-Driven Pathogenic Pro-inflammatory Monocytes and Macrophages in Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE or lupus) is an autoimmune disease characterized by anti-nuclear antibody (ANA) production and inflammation, though the mechanisms by which ANAs induce inflammation and tissue injury are incompletely understood. Here, we identified distinct subsets of mononuclear phagocytes (MPs), including monocytes (Mo) and macrophages (M{Phi}), driven by lupus immune complex (IC), comprised of ANAs and their target antigens. scRNA-seq of human Mo incubated with U1-snRNP (snRNP) lupus IC revealed expansion of distinct pro-inflammatory Mo subsets with upregulation of inflammatory genes including those encoding cytokines, NLRP3, and transcription factors. These transcriptomic changes strongly correlated with protein expression, as determined by proteomic analysis. Mo developed similar pro-inflammatory transcriptomic changes in response to other lupus ICs containing anti-dsDNA and Ro60 antibodies. Interrogation of scRNA-seq datasets from the skin, kidney, and peripheral blood of lupus patients revealed the presence and expansion of pro-inflammatory Mo and M{Phi} populations exhibiting transcriptomic signatures similar to those observed in lupus IC-stimulated Mo. Some of these cells expressing the snRNP IC gene signature exhibited low expression of the type I IFN signature, suggesting that lupus IC and type I IFN signaling may independently affect Mo subsets. In lupus nephritis, infiltration of CD68+ M{Phi} expressing NLRP3 was associated with treatment outcomes. Inhibiting activation of the transcription factor ETS2, a master regulator of Mo/M{Phi}-driven inflammation, attenuated lupus IC-induced activation of pro-inflammatory Mo. Collectively, these findings provide novel insights into the role of lupus IC-driven pro-inflammatory MPs in the pathogenesis of SLE and highlight their relevance as therapeutic targets. Significance StatementSystemic lupus erythematosus (SLE or lupus) is a multi-systemic autoimmune inflammatory disease characterized by anti-nuclear antibody (ANA) production. Lupus immune complex (IC), consisting of ANAs and their target antigens, likely play a critical role in the pathogenesis of lupus through activation of mononuclear phagocytes (MPs), including monocytes (Mo) and macrophages (M{Phi}), which can produce an array of inflammatory molecules. Using transcriptomic and proteomic analyses, our study identified distinct pro-inflammatory Mo populations driven by lupus IC, along with expansion of similar pro-inflammatory Mo and M{Phi} subsets in the skin, kidneys, and peripheral blood of lupus patients. These findings provide novel insights into the pathogenic role of lupus IC-driven pro-inflammatory MPs and support a scientific rationale for therapeutically targeting these cells. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=155 HEIGHT=200 SRC="FIGDIR/small/700902v2_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@1839430org.highwire.dtl.DTLVardef@175dd1dorg.highwire.dtl.DTLVardef@107b54forg.highwire.dtl.DTLVardef@11096b0_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2026

Mast cell-driven adipocyte lipolysis promotes post-expansive VAT atrophy and ectopic hepatic steatosis

Excessive visceral fat is an essential risk factor of metabolic dysfunction-associated steatotic liver disease (MASLD). Yet, the cellular and molecular mechanisms implicated in the correlation between visceral fat metabolism and hepatic steatosis remain poorly understood. Here we report post-expansive epididymal adipose tissue (EAT) atrophy and hepatic steatosis in mice fed a high-fat diet (HFD) primarily due to elevated adipocyte lipolysis in EAT. Mast cell (MC) accumulation in EAT represents a lipolysis-associated feature. Pharmacological stabilization of MCs suppresses EAT adipocyte lipolysis, and improves EAT atrophy and hepatic steatosis. MC-derived serotonin (5-HT) correlates with visceral adipose tissue (VAT) lipolysis in HFD-fed mice as well as in MASLD patients. Conditional deletion of 5-HT from MCs or its receptor HTR2b on adipocytes demonstrates that MC-derived 5-HT promotes adipocyte lipolysis, EAT atrophy, and hepatic steatosis by binding on adipocyte HTR2b. These results suggest that MCs and MC-derived 5-HT are potential therapeutic targets for obesity-associated MASLD.

cell biology↗

bioRxiv2025

A gastric microbial chromatin remodeler drives gastric cancer progression and immune evasion by reprogramming the host epigenome

Emerging evidence highlights the crucial role of microbial communities in modulating cancer development and progression. In gastric cancer (GC), we identify Streptococcus anginosus (SA) as a tumor-resident oncobacterium that drives both tumor progression and immune evasion. We define a novel mechanism in which SA secretes extracellular vesicles (saEVs) that translocate the bacterial chromatin remodeler saSNF2 into host cell. There, saSNF2 partners with host transcription factor TEAD1--through its ATPase activity and participation in BAF complex assembly--to coordinately activate oncogenic transcription. This transkingdom interaction upregulates the palmitoyltransferase ZDHHC11, which in turn stabilizes PD-L1 via palmitoylation to establish an immunosuppressive niche, while also amplifying other TEAD1 target genes to fuel tumor progression. Functionally, saEVs promote tumor growth and limit CD8+ T-cell infiltration in vivo. Strikingly, pharmacological inhibition of ZDHHC11 reverses immune evasion and synergizes with anti-PD-1 checkpoint blockade. Our results establish SA as a multifaceted driver of GC and reveal the saSNF2-ZDHHC11 axis as a promising target to potentiate immunotherapy.

cancer biology↗

bioRxiv2025

Steric Gating Dictates Selective Activation of BIRC6 by UBA6 Over UBA1

The giant E2-E3 chimera BIRC6 is specifically activated by the ubiquitin-activating enzyme UBA6, but not by UBA1. This specificity allows BIRC6 to ubiquitinate downstream substrates (e.g., caspases) and thereby regulate apoptosis. However, the molecular mechanism that underlies UBA6mediated specific activation of BIRC6 remains elusive. Here, we used a UbDha (Ub residue 76 dehydroalanine) probe to achieve one-step, activity-based trapping of the transient transthioesterification intermediate, and resolved the cryo-EM structures of two key complexes: 1) the doubly loaded UBA6-BIRC6UBC-UbT-UbA complex (3.4 [A] resolution) and 2) the singly loaded UBA6-BIRC6UBC-UbT complex (3.3 [A] resolution). Structural analysis reveals that the specific BIRC6-UBA6 pairing is dictated by steric compatibility between an insertion loop (residues 4649- 4653) in BIRC6s UBC domain and UBA6s gate helix. Unlike UBA1, UBA6 avoids steric clash with this insertion loop via two key conformational changes: a ~30{degrees} clockwise rotation and a 19 [A] displacement of its gate helix. These conformational changes collectively create a compatible cavity to accommodate the insertion loop. Biochemical validation confirms two key findings: 1) truncating BIRC6s insertion loop rescues UBA1-mediated ubiquitin charging of BIRC6UBC; 2) swapping UBA6s gate helix with that of UBA1 abolishes UBA6s transthioesterification activity towards BIRC6UBC. Our study provides key structural insights into the molecular basis of E1-E2 pairing specificity and advances our mechanistic understanding of apoptotic signalling.

biochemistry↗

bioRxiv2025

Oxygen-adaptive plasticity of Asgard archaea dependent on terminal oxidase and globin

The oxygenation of ancient Earth is thought to have driven eukaryogenesis, beginning with the endosymbiosis of an aerobic alphaproteobacterium (proto-mitochondria) with an archaeal host. Given that the archaeal host likely evolved from within Asgard archaea (phylum Promethearchaeota), the metabolic traits of Asgard archaea could provide key insights into eukaryotic origins. Although Asgard archaea cultured to date are obligate anaerobes, their genomes encode oxygen-adaptive proteins, suggesting they might be oxygen-tolerant. Here, we demonstrate that some Asgard archaea, in particular, Hodarchaeales, the closest known relatives of eukaryotes, and Kariarchaeaceae, exhibit oxygen adaptation mediated by terminal oxidase and globin. Phylogenetic analysis reveals long-term vertical evolution of terminal oxidases in Asgard archaea, suggesting ancient adaptation to molecular oxygen. By contrast, globin was likely acquired by Asgard archaea via horizontal gene transfer from facultative aerobic Chloroflexales bacteria. Heterologous expression of the Asgard globin enhances aerobic growth of Haloarchaea and Escherichia coli in the presence of terminal oxidase-dependent electron transfer chain, suggesting that Asgard growth benefits from ambient oxygen. The Asgard globin gene is embedded in an oxygen-sensitive bidirectional promoter region, with one promoter driving oxygen-induced globin expression, and the other anaerobically activating expression of two enzymes, PdxS and PdxT, involved in a pyridoxal 5-phosphate biosynthesis. The Asgard globin and promoter region exhibit high functional robustness across archaea and bacteria, and could contribute to the symbiosis between the Asgard and aerobic bacterial partners. These findings highlight the oxygen-adaptive plasticity of Asgard archaea and its potential contribution to eukaryogenesis.

evolutionary biology↗

bioRxiv2025

AniMarkerDB: a comprehensive database for exploring cell types and marker genes in livestock and poultry at single-cell resolution

Single-cell RNA sequencing (scRNA-seq) has dramatically advanced the understanding of cellular heterogeneity. While numerous marker gene databases are available for humans and mice, a lack of systematic resources for livestock and poultry species remains, limiting progress in functional genomics, immunology, and breeding.. To address this challenge, we developed AniMarkerDB (https://animarkerdb.bio), a comprehensive and curated database dedicated to marker genes and immune-related epitopes in economically animals, including chicken, pig, and duck. AniMarkerDB integrates 7,010 marker gene across 37 tissues and 846 cell types, together with 71,442 immune epitope records from IEDB. All entries undergo rigorous literature curation, manual validation, and multi-level quality control, with standardized nomenclature and annotation to ensure data consistency and reusability. The platform supports flexible queries by species, tissue, cell type, or gene. It offers analytical tools for cross-species comparison model organisms such as human and mouse, interactive single-cell atlas visualization, and user-defined cell type annotation. Additionally, AniMarkerDB provides dynamic visualizations and export options, enabling researchers to efficiently obtain large-scale marker and epitope data for downstream applications such as infectious disease research, vaccine target design, and comparative immunology. Looking ahead, AniMarkerDB will expand species coverage and incorporate additional modalities, including single-cell atlases from healthy and disease models, establishing itself as a comprehensive and authoritative platform for animal cell biology, disease modeling, and translational research. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/682327v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@af7e7borg.highwire.dtl.DTLVardef@198d114org.highwire.dtl.DTLVardef@1c69ed2org.highwire.dtl.DTLVardef@e4fc43_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Stage-resolved Spatial Multi-omics Reveals Myeloid Niches in Human Atherosclerotic Plaques

BackgroundAtherosclerosis, a leading cause of heart attack and stroke, involves intricate immune cell dynamics within arterial plaques, yet their spatial organization and functional roles remain elusive. MethodsWe combined Visium HD spatial transcriptomics, imaging mass cytometry, and single-cell RNA-seq across fatty-streak, advanced, and restenotic plaques to map myeloid architectures and relate them to lesion geography and extracellular matrix features. Slingshot trajectory analysis resolved macrophages differentiation path. In vitro, we tested microenvironmental and lipid cues separately: fibronectin (FN) exposure during PMA-driven THP-1 differentiation and oxidized LDL (oxLDL)-induced foam cell formation in murine bone-marrow derived macrophages (BMDMs). ResultsOur analysis identified seven macrophage subsets and two neutrophil populations with distinct spatial distribution and functional roles. In early lesions, neutrophils expressing MMP9, MPO, p47phox, TGF-{beta}1 and arachidonate 5-lipoxygenase (ALOX5), aligned with proteolysis, inflammatory processes, and endothelial-mesenchymal transition features. In advanced plaques, macrophage subsets exhibit specialized functions: Ki67+ proliferative macrophages localized near necrotic cores, sustaining local population; SPP1+ macrophages, enriched in lipid handling and tissue remodeling, are prone to apoptosis/ferroptosis, potentially promoting necrotic core expansion; and C3aR+ macrophages form antigen-presenting niches with elevated HLA-DR and CD74, engaging T cells possibly through CXCL12-CXCR4 signaling. Slingshot trajectories indicated progression from C3aR toward SPP1 remodeling states concentrated at fibronectin-rich rims. In vitro, FN increased MMP9 and TIMP1 in THP-1-derived macrophages, consistent with FN imprinting remodeling features characteristic of SPP1 macrophages in situ. Concurrently, oxLDL-treated BMDMs showed enhanced lipid-handling and remodeling modules consistent with the SPP1 program. ConclusionsThese findings define conserved myeloid niches and support a microenvironment-imprinting model that links ECM composition and lipid loading to macrophage state transitions, providing a framework for microenvironment-targeted therapies to stabilize plaques and mitigate cardiovascular risk.

pathology↗

bioRxiv2025

De Novo Design of Anti-Aging Peptides

Aging, a universal biological process in complex organisms, is increasingly recognized to be driven by progressive loss of epigenetic information, as proposed in the Information Theory of Aging (ITOA). However, research on anti-aging peptides remains scarce, with most existing efforts confined to derivatives of natural proteins, while systematic design attempts are virtually absent. This limitation not only restricts discovery within the evolutionary sequence space but also hampers the identification of candidates with novel mechanisms and improved efficacy. Here, we present ElixirSeeker2, the first computational framework for de novo design of anti-aging peptides. By integrating modeling of known anti-aging peptides, activity scoring from the IC50 database, and penalty constraints from toxic peptides, ElixirSeeker2 enables large-scale virtual screening and identification of novel peptide candidates. Several lead peptides demonstrated significant effects in delaying cellular senescence, restoring cellular functions in vitro and in enhancing locomotor activity of aged Caenorhabditis elegans. This study not only validates the feasibility of de novo design in anti-aging interventions but also establishes a strategy for the development of next-generation biologics.

bioinformatics↗

bioRxiv2025

Scaling Personalized TMS: A Scalp-Based MRI-guided Alternative to Neuronavigation

BackgroundPersonalized transcranial magnetic stimulation (TMS) has shown promise in treating psychiatric and neurological disorders, but its accessibility is limited by reliance on costly and complex neuronavigation systems, particularly in resource-constrained clinical settings. ObjectiveTo develop and validate a scalp-based alternative to neuronavigation for personalized TMS targeting. MethodsWe developed a Continuous Proportional Coordinate (CPC) system-based approach for personalized TMS targeting and validated its performance through three operators across ten participants, using individualized DLPFC-SGC targets as an example. The validation framework included targeting consistency assessment, reproducibility evaluation, and cross-cortical generalizability analysis. ResultsThe CPC-based approach demonstrated comparable performance to neuronavigation, achieving 99.4% of its electric field strength (74.80 vs. 75.14 V/m; r = 0.962) and 93.9% of DLPFC-SGC functional connectivity (-0.216 vs. -0.230; r = 0.949), with high inter-operator reliability (ICC [≥] 0.903). Reproducibility analysis showed strong correlation between sessions (r = 0.948-0.957) with high reliability. Further simulations across 1,125 uniformly distributed cortical targets supported generalizability of this approach, with stable electric field preservation (99.07 {+/-} 1.54%) across different brain regions. ConclusionsThe CPC-based approach offers a practical alternative to neuronavigation, maintaining targeting accuracy and providing a more accessible option for personalized TMS implementation.

neuroscience↗

bioRxiv2025

Subtype-Specific Roles of Nigrostriatal Dopaminergic Neurons in Motor and Associative Learning

Nigrostriatal dopaminergic neurons (DANs) in the substantia nigra pars compacta (SNc) comprise distinct subtypes defined by unique gene expression profiles and anatomical characteristics. However, their specific contributions to motor and non-motor functions remain elusive. Using Calbindin 1 (Calb1) and Aldehyde dehydrogenase 1a1 (Aldh1a1) as molecular markers, we investigated the functions of these nigrostriatal DAN subtypes in mice. Through intersectional genetics and chemogenetic manipulation, we selectively inhibited Calb1+ or Aldh1a1+ DANs by stereotactically delivering an adeno-associated viral vector (AAV-CreOn-FlpOn-hM4Di-P2A-mCherry) into the SNc of ThFlp; Calb1IRESCre or ThFlp; Aldh1a1CreERT2 double knock-in (KI) mice. This approach enabled subtype-specific neuronal inhibition via designer receptors exclusively activated by designer drugs (DREADD). Following DREADD ligand administration, both Calb1+ and Aldh1a1+ DAN-inhibited mice exhibited significant reduction in voluntary movement and impaired motor skill learning, demonstrating their essential roles in motor function. However, only Calb1+ DAN inhibition affected early associative-learning behavior, suggesting a unique role in reinforcement learning. These findings establish Calb1+ and Aldh1a1+ nigrostriatal DANs as key regulators of movement and motor learning, with Calb1+ neurons additionally modulating reward-based associative learning. This study advances our understanding of the functional heterogeneity of nigrostriatal DAN subtypes and identifies potential therapeutic targets for addressing motor and non-motor deficits in Parkinsons disease.

neuroscience↗