Biology subjects

Chen, A.

Publications and source records attributed to Chen, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Design of readers for pathological PTM proteoforms in Alzheimer's disease

Alzheimer's disease (AD) is characterized by heterogeneous Tau phosphorylation and aberrant amyloid-beta (Abeta) processing, yet molecular tools that distinguish closely related molecular states of tau and Abeta with predefined specificity remain difficult to develop. Here, we designed de novo protein readers targeting three disease-associated phospho-Tau regions and N-terminal pyroglutamate-modified Abeta (N3pG-Abeta). Screening 192 designs per target identified 51 modification-selective hits among 768 candidates (6.6%). Representative readers exhibited nanomolar to subnanomolar affinities for modified peptides, discriminated authentic modifications from unmodified or substitution-based controls, and preferentially recognized modified full-length targets. We further programmed local modification specificity by interface redesign, generating pT231 readers conditional on the phosphorylation state of neighboring S235 and S237. A 2.0-angstrom crystal structure of an N3pG-Abeta reader closely matched the computational design model (interface C-alpha RMSD = 0.52 angstrom), and redesign of pT231 readers tuned apparent binding affinities from greater than 1 uM to below 1 nM. In a human 3D neuronal culture with both pathological Abeta and tau, selective readers targeting N3pG-Abeta, Tau pT231, and Tau pT217 recognized disease-associated signals, exhibiting colocalization with related antibodies and much higher signal in the AD line than the control. Tau pT231 readers further quantitatively distinguish AD patients and control human brain lysates in dot-blot assays. Together, these results establish genetically encoded readers with programmable specificity for defined Tau and Abeta modification states, enabling molecular-state-resolved detection in human disease models and biological samples, and lay a foundation for controlled pathological molecular perturbation.

bioengineering↗

bioRxiv2026

Hidden grassland productivity from overlooked herbivore impacts

Grasslands cover approximately 40% of Earth's land surface and contribute substantially to terrestrial primary production. Despite widespread grazing, field estimates of grassland aboveground net primary productivity commonly overlook two grazing-related processes: biomass consumed by herbivores and post-grazing compensatory growth. The magnitude and direction of the resulting biases remain unclear. Here we quantified these biases using a 3-year yak grazing experiment on the Tibetan Plateau, a meta-analysis of 152 grazing experiments across China, and a global synthesis of 212 paired observations from 58 studies. Overlooking biomass consumed by herbivores consistently underestimated productivity by 34-51%. By contrast, overlooking grazing-induced compensation generated smaller but more variable biases, ranging from 29% underestimation to 19% overestimation, mainly reflecting contrasting compensatory responses under rotational versus continuous grazing. These findings show that overlooking grazing-mediated processes introduces substantial, process-dependent biases in grassland productivity estimates, underscoring the need to incorporate these processes into ecosystem and climate assessments.

ecology↗

bioRxiv2026

Imputation-Based Harmonization Mitigates Site Effects Without Data Leakage in Machine Learning Studies

Neuroimaging studies that pool data across clinical sites often suffer from site effects --- variability in imaging measures that arises from technical heterogeneity across sites as opposed to true biological signal. While numerous harmonization methods have been proposed to remove site effects from imaging features, less attention has been placed on how to incorporate harmonization models into common machine-learning pipelines. We demonstrate that current approaches for integration either suffer from data leakage, fail to fully remove site effects from the target data, or attenuate true biological associations during the harmonization process. To address these issues, we propose Multiple Imputation for Removing Technical Heterogeneity (MIRTH), which uses imputed outcomes to harmonize the test data. We benchmark MIRTH's performance using both simulated and real-world volumetric data from the Alzheimer's Disease Neuroimaging Initiative and the Baltimore Longitudinal Study of Aging, demonstrating that MIRTH can achieve high predictive accuracy while avoiding inflated performance when the outcome is imbalanced across clinical sites.

neuroscience↗

bioRxiv2026

Angiopoietin-like protein 7 (ANGPTL7)-mediated effects on resident immune cells contribute to neurodegeneration in glaucomatous optic nerve head

Glaucoma is an optic neuropathy characterized by progressive retinal degeneration. Population genetic analyses describe an association of variants in angiopoietin-like protein 7 (ANGPTL7) with lower intraocular pressure (IOP) and decreased glaucoma susceptibility. In addition to its reported role in the trabecular meshwork (TM), we demonstrate that ANGPTL7 is also expressed within disease-relevant cell types of the human posterior eye, specifically prelaminar optic nerve head astrocytes (ONHA). Contrasting with previously published findings, we observe no difference in IOP between Angptl7-/- mice and wild-type littermates. Despite absence of an IOP phenotype, loss of ANGPTL7 protects from IOPinduced retinal ganglion cell (RGC) damage in a rodent glaucoma neurodegeneration model. ANGPTL7 may signal through LAIR1-positive immune cells, potentially contributing to pro-inflammatory signaling and phenotypic modulation of resident immune cells, with evidence suggesting that oligomerization of ANGPTL7 is necessary for its activity. Comprehensively, our data highlight an unappreciated role of ANGPTL7 in modulating neuroinflammation in the posterior eye, contributing to glaucoma progression.

neuroscience↗

bioRxiv2026

Ultra-fast and scalable high-resolution full-length single-cell RNA sequencing using CHART-seq

Plate-based full-length single-cell RNA sequencing resolves transcript structure details but remains difficult to scale because each cell usually requires a separate library. Here we developed CHART-seq (Combinatorial Heteroduplex Assay via Recombinant Tn5), which uses orthogonally indexed Tn5 complexes to tagment RNA/cDNA heteroduplexes and permits early sample pooling. The workflow processed up to 96 cells per library, was compatible with 384-well expansion, and completed library preparation within 3 h at a reagent cost below US$1 per cell. At matched sequencing depth, CHART-seq detected more genes and annotated isoforms than Smart-seq2, Smart-seq3, Flash-seq and SHERRY2, while retaining broad genebody coverage and reproducible expression estimates. In the CHART-seq results of vascular smooth muscle cells, TGF-{beta}1 pretreatment before PDGF-BB exposure partly restored contractile features, suppressed a PDGF-associated inflammatory programme, and induced a distinct metabolic-matrix response with coordinated transcript-usage changes. These biological findings remain exploratory because independent biological replicates were unavailable. CHART-seq provides a rapid, scalable route to full-length single-cell transcript profiling with gene-programme and candidate isoform resolution.

genomics↗

bioRxiv2026

Quantifying Uncertainty in Brain Age Predictions via Conformal Prediction

Youth can exhibit signs of delayed or accelerated neurodevelopment, measurable via brain magnetic resonance imaging (MRI). Brain age prediction seeks to estimate brain age at an individual level using machine learning models fitted on healthy individuals. The brain age gap (BAG): the difference between brain age and chronological age, has been studied as a potential biomarker. However, BAG suffers from known limitations, including dependence on chronological age, regression to the mean, and challenges in interpretability. As an alternative framework, we introduce brain age intervals (BAIs) as a normative interval on an individual's chronological age, based on MRI measures. BAIs can be derived using a recent statistical framework called conformal prediction that yields prediction intervals with guaranteed coverage. We train several brain age prediction models on structural and functional MRI scans from the Reproducible Brain Charts dataset (aged 6-22) and estimated BAIs. The BAIs demonstrated stable empirical coverage close to the nominal 90% level (median coverage=91%, width=7.36 years, root mean square error (RMSE)=2.20 years across 100 repeated train-test splits). Associations between interval coverage and clinical measures (p-factor, parental education) were weak, with only a modest directional signal for parental education. Together, these findings demonstrate the feasibility of uncertainty-aware brain age modeling in youth populations while highlighting the need for larger and more diverse samples to detect meaningful clinical and environmental associations.

neuroscience↗

bioRxiv2026

What is common to memory retrieval and relational reasoning? Testing neural overlap in anterior lateral prefrontal cortex

Anterior lateral prefrontal cortex (aLPFC) has been consistently implicated in retrieval monitoring and relational reasoning. However, it is unknown whether aLPFC supports a cognitive process that is common to memory retrieval and reasoning tasks. To inform this question, a first step is to ascertain whether there is, within individuals, spatial overlap in aLPFC between tasks. A prior study found overlap in activation of left aLPFC between verbal analogy and source memory retrieval tasks, using tightly matched word stimuli (Westphal et al., 2016). To assess whether this overlap in activation extends to other stimulus types and task designs, and another sensory modality, we collected fMRI data from 35 healthy young adults as they completed an associative memory retrieval task along with four variants of a relational reasoning paradigm that reliably engages left aLPFC. The reasoning tasks followed a 2 (visual/auditory modality) x 2 (spatial/featural relations) x 2 (low/high relational complexity) design. In the associative memory task, participants studied word pairs and decided whether the two words were related. At retrieval, they viewed pairs of previously seen words and judged whether the pair was Intact (words paired together at encoding) or Recombined (previously seen words recombined into new pairs). Response times were slower for Recombined vs. Intact pairs, consistent with heightened retrieval monitoring. As predicted, aLPFC was more active for Recombined than Intact pairs, as well as for the manipulation of relational complexity across the four reasoning tasks. A group-level conjunction analysis demonstrated substantial overlap between memory and reasoning manipulations in left aLPFC (Glasser parcels a47r, p47r, a10p, and p10p). Within individuals, clusters defined from the reasoning task were also sensitive to retrieval monitoring demands. Further, there was within-participant overlap in the pattern of active vertices, as measured via Dice coefficients. Bayes factor testing within each parcel of interest demonstrated greater vertex-level overlap than expected by chance, particularly in p47r. Importantly, degree of overlap varied widely among individuals, and exploratory results showed that both cluster-level activation and vertex overlap in p47r correlated with memory discriminability (d-prime). Thus, we hypothesize that neural overlap in this area reflects engagement in relational thinking during memory retrieval monitoring. Together, these results move beyond general characterizations of aLPFC function by testing whether it meets a precondition -- individual-level neural overlap across varied tasks -- of a unified neurocognitive function in support of reasoning and memory retrieval.

neuroscience↗

bioRxiv2026

Tumor-tropic E. coli engineered as living T and NK cell engagers

Despite advances in immunotherapy, most solid tumors remain resistant to treatment. Immune cell engagers redirect cytotoxic lymphocytes against cancer, but limited tumor access, immunosuppressive microenvironments and systemic immune activation limit efficacy. Here we develop live immune modulating engagers (LIME), a modular platform where non-pathogenic, tumor-tropic Escherichia coli display tandem single-chain variable fragments targeting a tumor-associated antigen and an activating receptor on T or natural killer cells. LIME bridged effector and tumor cells, induced transcriptional programs of T cell activation, metabolism and proliferation, and enhanced cytotoxicity across cancer cell lines and patient-derived organoids. In mouse models, LIME safely accumulated in tumors, outperformed tarlatamab in small cell lung cancer, and induced durable immunity in lymphoma. RAS inhibition and PD-L1 blockade enhanced LIME activity in pancreatic cancer and induced humoral responses. Multi-lineage immune modulation remained tumor-confined, without organ toxicity. These findings establish LIME as a versatile living therapeutic platform for programmable, tumor-restricted immune orchestration.

bioengineering↗

bioRxiv2026

A traveling network model predicts emergent dynamics and search behavior from local remodeling in Physarum polycephalum

A variety of connected systems, ranging from the cytoskeleton to human organizations, dynamically rearrange themselves in order to move through physical or abstract space. However, our understanding of how systems-level behaviors arise from local restructuring actions remains limited, necessitating comparison of real-world data to models that predict network structure and dynamics. To understand these systems, we study an accessible example, the branching slime mold Physarum polycephalum, by imaging the organism as it travels and extracting key fundamental quantities from its continuously remodeling tubular network. By using these quantities as input parameters to a traveling network model, we find that with no further fitting, the model quantitatively matches key emergent properties from P. polycephalum dynamics including path length, relocation time, and search efficiency at different spatial resolutions. These findings demonstrate how a traveling network model can capture P. polycephalum behaviors, highlighting the potential to use traveling networks more broadly for understanding and predicting connected dynamic systems by linking local measurements to emergent, system-wide behaviors.

biophysics↗

bioRxiv2026

Oxygen-sensing regulatory architecture structures mammalian diversification

The HIF oxygen-sensing pathway traces to the last metazoan common ancestor [~]800 million years ago and is conventionally viewed as a conserved cellular stress-response module. Whether this ancestral system has contributed to mammalian diversification at macroevolutionary timescales remains unexplored. We analyzed sequence-encoded TF-gene regulatory architecture for 34 transcription factors and 705 genes in 10 oxygen-sensing pathways across 239 mammalian species. Oxygen-sensing regulatory architecture carries strong clade-structured evolutionary signal. The primary axis of variation tracks a fast-slow life history gradient, marked by rewiring of growth-control and tumor suppressor hub genes. A second axis recovers the monotreme-marsupial-placental transition and aligns with the decline in atmospheric O2 from the Permo-Carboniferous maximum toward present-day levels1. Orthogonal axes encode distinct ecological regulatory strategies; two later axes separately resolve HIF-compatible binding-site architecture and dominant TF-family assignment, identifying regulatory strategies associated with powered flight and hibernation. This multidimensional space also informs Petos paradox, suggesting that relative cancer resistance tracks the combination of tumor-suppressor enrichment and coordinated HIF-complex assignment. Together, these results indicate that regulatory configurations arise at major evolutionary transitions and persist coherently across descendant lineages through a punctuated mode of regulatory evolution, providing genomic-level evidence for Simpsons adaptive zones and a mechanism for evolutionary stasis. These findings reframe oxygen sensing as a regulatory hub in mammalian diversification, with stable patterns of TF-family assignment configurations emerging as a structuring force in macroevolution. BriefAncient molecular processes such as oxygen-sensing, whose HIF-pathway dates to the origin of animals [~]800 million years ago, are typically regarded as conserved across lineages. How such deeply ancestral systems have contributed to mammalian diversification remains largely unexplored. By analyzing the oxygen-sensing regulatory architecture (which transcription factors regulate which genes) across 239 mammalian species, we find that oxygen-sensing regulatory rewiring tracks placental evolution, atmospheric O2, life history evolution, ecological specializations, and cancer resistance. Major radiations occupy discrete, heritable configurations established at key phylogenetic transitions and subsequently retained across descendant lineages through near-neutral within-regime drift, revealing regulatory architecture lock-in as a structuring force in macroevolution.

evolutionary biology↗

bioRxiv2026

A Microgel-Based Platform for Tunable Expansion and Function of γδ T-cells

Current {gamma}{delta} T-cell expansion protocols often sacrifice functionality for yield and largely ignore the context of activation. Here we utilize a tunable alginate microgel system functionalized with anti-CD3 and co-stimulatory antibodies (CD28 or CD2) to investigate the impact of biochemical signaling and substrate mechanics on {gamma}{delta} T-cell activation. Microgel-mediated expansion was compared to conventional soluble antibodies and TransAct beads. The microgels enhanced {gamma}{delta} T-cell expansion compared to soluble antibodies, allowed for controlled tuning of differentiation state, and promoted higher NKG2D, IFN-{gamma} and TNF- expression levels. Functionally, microgel-expanded {gamma}{delta} T-cells exhibited superior cytotoxicity against both solid and liquid tumor targets. This system also allowed elucidation of the differences in stimulation requirements for various donors, based on the starting phenotype. These findings establish a tunable platform for engineering {gamma}{delta} T-cells with improved therapeutic potential. Significance Statement{gamma}{delta} T-cells have shown promising therapeutic effects when used for T cell-based immunotherapy to treat solid tumor. However, achieving rapid expansion of {gamma}{delta} T-cells while maintaining their functionality remains a major challenge, especially given the heterogeneous responses from donors. We demonstrate that a tunable microgel system with flexible presentation of stimulatory cues improves {gamma}{delta} T-cell expansion while preserving cytotoxic function and reveal how starting phenotypes influence responses to activation. These understandings will provide design rationale to enable patient-specific treatment for optimal therapeutic outcomes.

bioengineering↗

bioRxiv2026

HARMONY: A large-scale harmonized neuroimaging dataset for research on anxious misery disorders

Patterns of brain circuit dysfunction underlying depression and anxiety have been increasingly characterized, including dimensional and subtype variation. A key challenge is determining how such patterns generalize across populations and measurement frameworks. Here, we introduce HARMONY, a harmonized multimodal neuroimaging dataset supporting large-scale investigation of brain-behavior associations across symptom-defined dimensions. HARMONY integrates four Human Connectome Project-style Connectomes Related to Human Disease cohorts spanning adolescence to later adulthood and capturing anxious misery symptoms. The resource combines standardized HCP-style preprocessing, quality control, imaging-derived phenotypes, and harmonized symptom measures into a clinically enriched public dataset. Proof-of-concept analyses using HARMONY showed that pooling heterogeneous cohorts increased statistical power for detecting associations between imaging-derived phenotypes and anhedonia and depression severity. Effect sizes remained modest, consistent with symptom-based measures across heterogeneous samples. Functional imaging-derived phenotypes showed the strongest multivariate predictive performance. In summary, HARMONY provides a large multi-cohort resource for reproducible mental health neuroimaging research.

neuroscience↗

bioRxiv2026

MOTS-c Coordinates Inter-Organellar Proteostasis for Adaptation to Chronic Metabolic Stress

Mitochondrial communication coordinates adaptive responses across organelles to sustain cellular homeostasis, a network that declines with age and contributes to loss of proteostasis. Here, we identify MOTS-c, an exercise-induced mitochondrial-derived peptide (MDP) encoded within the 12S rRNA locus, as an inter-organellar arm of the mitochondrial stress response (MSR) that links mitochondrial signaling to endoplasmic reticulum (ER) proteostasis and enables adaptation to chronic stress. Using progressive stress media (PSM), a model of gradual and multifactorial metabolic stress, we show that MOTS-c enables adaptation through a biphasic program: acutely, a reversible, ATF4-independent suppression of protein synthesis; and chronically, an ATF6-biased ER unfolded protein response (UPRER) with tempered ATF4 engagement and coordinated metabolic remodeling. Whereas mitochondrial unfolded protein response (UPRmt) pathways have been extensively characterized in acute, genetic, and sustained models of mitochondrial perturbation, this work reveals how mitochondrial communication actively engages ER proteostasis during progressive and persistent metabolic stress. By expanding proteostatic capacity while tempering terminal stress signaling, MOTS-c enables cells to withstand chronic stress. Together, these findings define a MOTS-c-dependent arm of the MSR that integrates mitochondrial communication with ER proteostasis to promote chronic metabolic stress adaptation.

Cell Biology↗

bioRxiv2026

EditorForge: An Active-Site-Aware Framework for Inverse-Folding-Based Protein Redesign

Inverse-folding models can rapidly generate protein sequences compatible with a supplied backbone, but unconstrained redesign is poorly suited to enzyme and genome-editor-associated domains, where catalytic, substrate-proximal, and conserved structural regions must remain protected. In this paper, we present EditorForge, a modular constraint-and-audit suite for editor-domain protein redesign that wraps fixed-backbone inverse folding with explicit design masks, fixed-position enforcement, active-site-proximity auditing, active-site-shielded regeneration, and downstream structural quality control. Using full-length Moloney murine leukemia virus reverse transcriptase structure 4MH8 (MMLV RT 4MH8) as a demonstration target, EditorForge first restricted redesign to a bounded 25-position envelope while fixing 428 residues. An initial audit detected active-site-proximal failure modes despite fixed-position integrity. Later, the Active Site Shield module then removed five unsafe design positions, replaced them with lower-contact alternatives, and regenerated candidates under stricter constraints. Post Shield Audit evaluated 24 regenerated candidates, all of which satisfied the hard sequence/mask and active-site-shield constraints. For the eight candidates that were selected or returned for structure-prediction/refolding quality control, Enhanced RefoldQC found that all 8 evaluated predicted structures passed the computational structure-QC screen. That said, the selected 8 candidates passed the computational structure-QC screen, with global C RMSD values of 1.2061-1.5555 {degrees}A, active-site C RMSD values of 0.4098-1.8397 {degrees}A, mutation-neighborhood C RMSD values of 1.3155-1.6848 {degrees}A, and average pLDDT-like confidence values of 94.87-95.11. In short, EditorForge provides a reproducible triage layer that converts general inverse-folding output into constrained and editor-specific candidate sets for downstream structural and biological review on top of existing structural prediction tools.

bioinformatics↗

bioRxiv2026

Integrating Histology with Spatial Molecular Programs Using a Multimodal Foundation Model

Histopathological assessment remains central to cancer diagnosis and stratification, yet its mechanistic interpretation remains limited without molecular context. To address this, we developed SQUALL, a multimodal foundation model integrating histology with spatial molecular programs. For pretraining, we assembled histMol, a large-scale corpus of 1.76 billion paired histology-spatial transcriptomics spots/bins across 33 tissues and 12 platforms from 3,446 tissue sections. Following pretraining, SQUALL enables transcriptome-wide virtual biomarker profiling, prognostically relevant spatial niches discovery, and integrative disease progression modeling. Leveraging its multimodal embeddings, SQUALL identifies niches associated with tertiary lymphoid structure (TLS) maturation and ovarian cancer relapse, reconstructs molecular trajectories of breast cancer invasion across 325,112 spots, and uncovers underlying transcriptional programs. Applied to whole-slide images from 898 patients, SQUALL outperforms existing pathology foundation models in outcome prediction while enabling interpretable risk stratification. Together, these results establish spatially aligned multimodal pretraining as a new paradigm for extending molecular insights into pathology images.

bioinformatics↗

bioRxiv2026

Immune variation and host ontogeny constrain pathogen virulence and transmission in a helminth parasite

Host immune strategies vary widely, yet how this variation shapes parasite virulence and transmission in natural systems remains unresolved. We tested whether host immune strategy governs macroparasite transmission timing and magnitude in Schistocephalus solidus, a cestode with a three-host life cycle. Over 13 months, we surveyed infection and immune activation (fibrosis) in second-intermediate host populations (threespine stickleback) from eight lakes. Host immune strategy (ranging from resistance to tolerance) strongly influenced whether and when parasites reached transmissible sizes, and shifted the synchrony between transmissible-stage peaks and definitive host availability. Across populations, transmission potential peaked at intermediate parasite burdens, consistent with virulence-transmission trade-off theory. These findings demonstrate that host immune phenotype alters epidemiological outcomes in complex life cycle parasites, by shifting both the magnitude and phenology of parasite growth to structure the effective transmission window.

ecology↗

bioRxiv2026

Combined Checkpoint Inhibition Amplifies Post-Infarction Injury via T Cell-Mediated Macrophage Activation

BackgroundThis study aimed to investigate whether combined PD-1/CTLA-4 immune checkpoint inhibition predisposes the heart to a hyperinflammatory state, thereby exacerbating cardiac injury following acute myocardial infarction (MI), a critical unresolved question in cardio-oncology. MethodsMyocardial infarction was induced in Pd1-/-Ctla4+/- mice, a genetic model mimicking combined checkpoint inhibition. Key mechanistic insights were gained through in vivodepletion of CD8+ T cells (using anti-CD8a antibody) and pharmacological inhibition of the JAK-STAT1 pathway (using Tofacitinib). Cardiac function, structural injury, and immune responses were comprehensively assessed via echocardiography, flow cytometry, immunofluorescence, and molecular analyses. ResultsCompared to wild-type controls, Pd1-/-Ctla4+/- mice exhibited significantly increased post-MI mortality, worse cardiac function, and larger infarct size. Mechanistically, the aggravated injury was driven by an amplified infiltration of activated, IFN-{gamma}-producing CD8+ T cells, which activated the JAK-STAT1 pathway in macrophages, polarizing them towards a pro-inflammatory state. Depleting CD8+ T cells or inhibiting the JAK-STAT1 pathway effectively attenuated macrophage-driven inflammation and improved all aspects of post-MI injury. ConclusionsCombined PD-1/CTLA-4 blockade exacerbates post-infarction cardiac injury by promoting CD8+ T cell-mediated activation of macrophages via the JAK-STAT1 axis. This work elucidates MI as a context-dependent immune-related adverse event in ICI therapy and identifies CD8+ T cells and the JAK-STAT1 pathway as promising therapeutic targets for cardioprotection in these patients. RESEARCH PERSPECTIVEO_ST_ABSWhat Is New?C_ST_ABSO_LIThis study identifies acute myocardial infarction (MI) as a potential, context-dependent immune-related adverse event in the setting of combined PD-1/CTLA-4 checkpoint inhibition, shifting the paradigm beyond the classic focus on myocarditis. C_LIO_LIIt elucidates a novel pathogenic axis where combined checkpoint deficiency exacerbates post-MI injury specifically through CD8+ T cell-derived IFN-{gamma}, which activates macrophages via the JAK-STAT1 pathway. C_LI What Question Should Be Addressed Next?O_LIFuture studies should employ anti-PD-1/CTLA-4 monoclonal antibodies in wild-type or humanized mouse models to validate findings and better recapitulate the pharmacokinetics of clinical ICI therapy, strengthening translational relevance. C_LIO_LIThe long-term consequences of this primed inflammatory state on chronic cardiac remodeling, heart failure development, and the potential interplay with atherosclerosis warrant further investigation. C_LI

immunology↗

bioRxiv2026

HESTIA: Scalable Multimodal Integration of Histology and High-Resolution Spatial Transcriptomics for Robust Spatial Domain Identification

Spatial omics has revolutionized molecular biology by providing invaluable insights into how native tissue microenvironments regulate cellular functions and disease mechanisms. Accurately capturing this structural complexity and decoding the underlying biological processes requires effectively integrating data from multiple modalities. However, transitioning to subcellular resolutions introduces massive data scales and severe transcriptomic sparsity, which challenge current analytical frameworks. To address this, we present HESTIA (Histology-Enhanced Scalable cross-Resolution inTegration for spatial trAnscriptomics), a highly efficient multimodal algorithm designed for identifying spatial domains in large-scale, high-resolution spatial omics data. By circumventing memory-intensive computations, HESTIA efficiently processes massive datasets on which existing algorithms fail due to memory constraints. HESTIA outperforms current multimodal methods in clustering accuracy and spatial continuity, accurately delineating fine structural boundaries. Furthermore, applying HESTIA to large-scale pathological samples successfully dissects clinically relevant intratumoral heterogeneity and maps distinct immune microenvironments in lung and colorectal cancers.

bioinformatics↗