Biology subjects

Chen, L.

Publications and source records attributed to Chen, L..

At least 19 recordsLinked to original sources

bioRxiv2026

C19 trityl and silyl andrographolide analogs exhibit in vitro anticancer activity in murine cancer models

Andrographolide, a labdane diterpenoid isolated from A. paniculata has been investigated for activity in a broad panel of biological contexts, including its anti-inflammatory, antiviral, and anticancer properties. Previously, A-ring analogs of andrographolide bearing silyl and trityl ethers at C19 have demonstrated improved in vitro anticancer activity in human cancer cell lines, with putative activity through the Wnt1/{beta}-catenin signaling axis. In order to investigate the activity of this series of C19 andrographolide analogs, alongside a cyclic A-ring acetonide analog, as anticancer agents in murine cancer cell models, we evaluated antiproliferative activity of these compounds in B16F10 melanoma, CT26 colorectal adenocarcinoma, Neuro2a neuroblastoma, and 4T1 mammary ductal carcinoma cell lines, and found that most compounds exhibited potent micromolar level anticancer activity. Among these, all trityl ethers exhibited nearly indistinguishable IC50 values of 4-20 M, and generally exhibited greater potency compared to C19 silyl ether analogs. This anticancer activity was further validated through apoptosis flow cytometry, wherein we concluded that our compounds induced apoptosis to a greater extent than the parent compound, andrographolide. Further, we examine the role of modulation of canonical Wnt1/{beta}-catenin signaling in a series of co-delivery assays with CHIR-99021, a selective GSK-3{beta} kinase inhibitor, and MSAB, a selective {beta}-catenin degrader. Finally, we demonstrate that a selection of silyl ether analogs of andrographolide elicit cell cycle arrest by flow cytometry in a manner that is decoupled to in vitro potency trends. Altogether, we report the first in vitro evaluation of trityl and silyl ether analogs of andrographolide within murine adherent cancer cells.

cancer biology↗

bioRxiv2026

Glioblastoma Hijacks Astrocyte Ribosomes to Feul Malignancy through Translatome Reprogramming

Cancer cells demand elevated protein synthesis, yet whether they directly requisition ribosomes from microenvironmental host cells remains unknown. Here, utilizing in vivo and in vitro ribosome tracing, we show that glioblastoma (GBM) cells hijack ribosomes from surrounding astrocytes via tunneling nanotube-like structures. This transfer supports GBM malignancy in both murine and patient derived models. Single cell RNA sequencing along with whole cell and cell source traceable ribosome profiling reveal that transferred ribosomes are translationally active and selectively reprogram the tumor translatome, prioritizing cell-cycle genes and driving interferon-response-mediated immune evasion. Through a genome wide CRISPR screen, we identify INTS12 as a critical mediator of ribosome transfer. Genetic inactivation or AAV-mediated knockdown of INTS12 impairs ribosome uptake, curbs translation and proliferation, remodels the immunosuppressive landscape, and extends survival in orthotopic models. Our study uncovers a parasitic translation-support mechanism in GBM, establishing INTS12 as a therapeutic vulnerability to disrupt ribosome transfer.

cancer biology↗

bioRxiv2026

Pulmonary colonization of Candida albicans drives breast cancer lung metastasis via candidalysin

The intratumoral mycobiome is emerging as a key modulator of cancer progression, with specific fungal taxa as potential biomarkers. However, whether and how mycobiomes colonizing distant organs contribute to tumor evolution remains largely unexplored. Here, we identify selective enrichment of Candida albicans in breast cancer lung metastases. Mechanistically, the fungal virulence factor candidalysin activates pulmonary mast cells, which release chemotactic mediators that expand immunosuppressive populations and suppress cytotoxic lymphocyte activity, remodeling the lung into a metastasis-permissive microenvironment. Analysis of clinical isolates and isogenic mutants further demonstrates that candidalysin secretion levels dictate metastasis-promoting potential. Informed by these findings, we developed a combination regimen that concurrently eliminates fungal colonization, stabilizes mast cells, and reverses the immunosuppressive microenvironment, thereby significantly curtailing metastatic progression. Collectively, our study establishes pulmonary C. albicans colonization as a driver of breast cancer lung metastasis and provides a mechanistic framework for targeting mycobiome-host interactions in metastatic disease.

cancer biology↗

bioRxiv2026

Ratio-preserving super-resolution FLIM for quantitative live-cell lifetime imaging

Super-resolution (SR) fluorescence lifetime imaging promises nanoscale maps of molecular environment and function, but photon-limited acquisition and computational reconstruction can distort lifetime estimates, particularly for ratio-derived frequency-domain measurements under SR conditions. Here we introduce structured-illumination frequency-domain FLIM (SIM-fdFLIM), an SR lifetime imaging platform that combines commercial dual-tap fdFLIM detection with ratio-preserving reconstruction. SIM-fdFLIM uses direct-current (DC)-stabilized lifetime estimation to improve reconstruction robustness under low signal-to-noise conditions, followed by ratio-domain integrated variational estimation (RIVE) to correct channel misregistration and suppress noise amplification after SR reconstruction. The method achieves ~100 nm spatial resolution in lifetime maps and enables live-cell imaging at 2.8 Hz over a 56 x 56 {micro}m2 field of view. Across representative fluorophore standards, RIVE reduces lifetime standard deviation by approximately threefold relative to non-RIVE SIM-fdFLIM while preserving mean lifetime agreement with calibrated widefield fdFLIM. In living cells, SIM-fdFLIM resolves mitochondrial cristae-scale lifetime heterogeneity, mitochondrion-to-mitochondrion functional dynamics, nanoscale lipid-environment variations and perturbation-sensitive organelle-contact signatures. These results establish SIM-fdFLIM as a ratio-preserving platform for quantitative SR lifetime imaging, extending live-cell FLIM into a regime that combines nanoscale spatial resolution, Hz-rate acquisition, and preserved lifetime fidelity.

bioengineering↗

bioRxiv2026

A Cell-Autonomous Cold Sensor Promotes Lipolysis Through Phase Separation

Temperature is a fundamental determinant of mammalian metabolism. The canonical cold-adaptation pathway involves cold sensing by peripheral sensory neurons, which activate sympathetic outflow, {beta}-adrenergic signaling, and lipolysis in adipose tissue. In contrast, we report here a cell-intrinsic mechanism by which physiologically relevant cooling temperatures (27-31 oC) enhance lipolysis in subcutaneous adipose tissue. Mechanistically, cooling drives liquid-liquid phase separation (LLPS) of perilipin 1 (PLIN1), the dominant lipid droplet coat protein, promoting its condensation and the local recruitment of PKA to the droplet surface. This spatial reorganization selectively amplified PKA-mediated perilipin 1 phosphorylation, CGI-58 release, and ATGL-dependent lipolysis. The process depends on the intrinsically disordered region (IDR) of perilipin1, where four aromatic residues, conserved in endotherms but not in ectotherms, are required for cooling-induced LLPS and lipolysis in vivo. Notably, targeted delivery of an LLPS-competent perilipin 1 variant to the inguinal adipose tissue of mice enhanced local lipolysis and reduced depot mass. Together, these findings uncover a cell-intrinsic thermosensitive mechanism that can tune lipolytic responsiveness, offering a possible strategy for targeted depot-selective fat reduction.

cell biology↗

bioRxiv2026

Centered cross-context perturbation transfer on the public 2025 Virtual Cell Challenge benchmark

Predicting transcriptional responses across cellular contexts requires transferring both expression direction and differential-expression priority. We developed a compact numerical method that combines public perturbation summaries with a differential-expression kernel fitted to H1 CRISPRi training targets. The method centers an independent KOLF2.1J source on known training targets, transfers its response signs and magnitude ranks, and uses isotonic regression to render predicted expression means. We evaluated the frozen model retrospectively on the released public TEST100 of the 2025 Virtual Cell Challenge, using an external KOLF source released in 2026. The model achieved DES 0.371834, PDS 0.8614, and MAE 0.302206. With reconstructed historical anchors, its composite score was 0.341344, compared with the archived champion score of 0.340052, a difference of +0.001292. The comparison showed higher DES and lower PDS, with zero normalized MAE contributions for both methods. Source centering also improved development PDS across all three TRAIN folds and official VALIDATION. These results demonstrate a practical numerical approach to cross-context perturbation transfer and differential-expression ranking.

bioinformatics↗

bioRxiv2026

Large-genome phages encode diverse proteins associated with host cell envelope functions

Huge phages (or jumbo phages, >200 kilobases) encode extensive protein repertoires, yet their functional diversity and potential roles in host physiology remain poorly understood. Using protein structure-based analyses of dominant protein families across 7,187 non-redundant genomes of huge phages, we uncovered pronounced phylogenetic and habitat-associated diversification. Notably, we identified diverse proteins associated with bacterial cell envelope functions, particularly in human gut-associated huge phages. These included previously unreported phage-encoded sortase B, whose putative substrates contain signal peptides and cell-wall sorting signals, suggesting a potential route for displaying phage proteins on bacterial surfaces. Phage-encoded phage shock protein A (PspA) was distributed across diverse lineages and frequently neighbored genes associated with membrane organization and transport, implicating potential roles in membrane physiology. We also identified 1,603 {beta}-barrel outer membrane proteins (OMPs) across 1,303 huge phages from diverse ecosystems. These OMPs exhibited structural diversity and associations with predicted host taxonomy, habitat, and neighboring envelope-related genes. Metatranscriptomic analysis supported expression of representative phage-encoded PspA and OMP genes in natural communities including the human gut. Together, these findings reveal bacterial cell envelope processes as a previously underappreciated potential interface for huge phage-host interactions.

microbiology↗

bioRxiv2026

Hypothalamic plasticity for alloparenting in male mice

Repeated exposure to young can induce caregiving in virgin female mice, a phenomenon known as pup sensitization, but whether virgin males can similarly acquire parental behavior and the neural mechanisms underlying this transition remain unclear. We show that 7 days of continuous pup exposure reliably converts virgin adult male mice to a parental state. This transition requires calcitonin receptor (CalcR)-expressing neurons in the medial preoptic area (MPOA): silencing MPOACalcR neurons disrupts both the acquisition and expression of paternal behavior, whereas optogenetic activation of GABAergic MPOACalcR neurons promotes caregiving in virgin males. Longitudinal two-photon calcium imaging reveals that MPOACalcR neurons develop enhanced pup-selective responses as males transition to a parental state. Moreover, CalcR signaling in the MPOA promotes synaptic potentiation and facilitates the emergence of parental behavior. These results identify an experience-dependent hypothalamic plasticity mechanism that enables parental behavior in non-father males.

neuroscience↗

bioRxiv2026

An immune world model with multi-agent orchestration for peptide vaccines

Peptide-vaccine design requires a connection between vaccine-induced priming and recognition of the antigen naturally displayed by a tumor. We present an immune world model that preserves this connection through separate vaccine and tumor branches, endpoint-specific evidence and multi-agent orchestration. Native-recognition constraints held an altered peptide despite its higher presentation score, and targeted perturbations removed antigen-dependent benefit when required tumor-recognition conditions were absent. Public dendritic-cell data distinguished donor from antigen-source transfer: a context ranker achieved Recall@20 of 0.483 and 0.333 under the respective holdouts. Structure-informed receptor prediction added candidate-ranking evidence while preserving functional constraints and matched scenario trajectories. An assay observation model further concentrated a cross-presentation coefficient around its known value in a synthetic conditioning experiment. Together, these results establish a computational framework for linking molecular predictions, native-target requirements and conditional immune dynamics. The framework provides a reproducible basis for choosing peptide-vaccine candidates and the experiments needed to resolve their biological dependencies.

bioinformatics↗

bioRxiv2026

Metabolite-centric Knowledge Graph Unveils Predictive and Mechanistic Insights through Self-supervised Multimodal Learning

Metabolomics research is advancing toward a comprehensive view of metabolites and their biological functions, yet conventional, dictionary-like databases fall short of presenting these complexities. To overcome this limitation, we developed MetaKG, a metabolite-centric knowledge graph that integrates diverse chemical, biological, and semantic data, coupled with a global self-supervised multimodal learning framework that generates advanced embeddings (MetaKGE) for both predictive and mechanistic analyses. MetaKG outperforms existing models in standard representation learning metrics and across 12 external datasets. Furthermore, MetaKG refines existing database information by detecting misannotated labels and uncovering previously overlooked biochemical relationships. Its predictive capability naturally yields testable biochemical hypotheses, as demonstrated in studies of G6PD deficiency and colorectal cancer. By transforming passive, database-scale information into extractable knowledge and actionable insights, MetaKG paves the way for hypothesis-driven discovery in metabolomics and holds promise for informing future research in clinical biomarker identification and therapeutic development.

bioinformatics↗

bioRxiv2026

Cortex-wide single-cell activity mapping in freely moving mice

How the cortex supports complex, naturalistic behavior can be revealed only in freely moving animals. Although head-mounted microscopes promise access to the neural dynamics underlying such behavior, fundamental trade-offs among field of view, spatial resolution, device weight, and background contamination have prevented cortex-wide single-neuron recording, leaving distributed cortical coordination largely inaccessible. To meet these challenges, we introduce COMET (Cortex-wide Observational Miniature Epifluorescence Technique), a 3.75-g head-mounted mesoscope that integrates an aberration-controlled wide-field optical design, uniform high-efficiency excitation and single-coaxial power-and-data transmission with an end-to-end denoising and signal-extraction pipeline. This enables cortex-wide calcium imaging at single-cell resolution in freely moving mice. COMET captures activity from >15,000 layer 2/3 neurons per 5-min recording over fields of view up to 10 mm in diameter while preserving natural behavior. Benchmarking against benchtop two-photon microscopy demonstrates high spatial concordance of detected neurons and matched event-level calcium dynamics. We apply COMET to social interaction to quantify region-specific engagement and to an auditory trace fear-conditioning task that requires natural movement and behavioral expression, revealing time-ordered changes in regional firing-rate structure and functional connectivity preceding a global conditioned response. COMET provides an open, lightweight hardware-software framework for linking single-neuron activity to cortex-scale network dynamics during freely expressed behaviors under changing internal or external conditions.

neuroscience↗

bioRxiv2026

Structural Basis of γδ T-Cell Receptor Crosslinking and Activation by a Spontaneously Dimerized Fab

The gamma delta T-cell receptor ({gamma}{delta} TCR) mediates {gamma}{delta} T-cell responses that are crucial for immune defense, tissue surveillance, and homeostasis. While recent studies suggest that {gamma}{delta} TCRs engage ligands multivalently, how multivalent engagement activates the {gamma}{delta} TCR remains elusive. Here, we present the structures of the V{gamma}9V{delta}2 (clone G115) TCR in both the inactive and the agonist-crosslinked active states. In the {gamma}{delta} TCR lipoprotein complex, cholesterol and phospholipids form a "barrier" that isolates CD3{zeta}{zeta} from the other subunits and likely prevents autoactivation. As an agonist, the Fab fragment of the UCHT1 antibody dimerizes upon binding the V{gamma}9V{delta}2 TCR, thereby crosslinking and activating the receptor. Cryo-EM analysis of Fab-crosslinked V{gamma}9V{delta}2 TCR identifies three Fab dimer interfaces, one between the two light chains and the other two between light and heavy chains. These Fab-Fab interfaces, together with the Fab-CD3{epsilon} interface, mediate the assembly of the V{gamma}9V{delta}2 TCR and UCHT1 Fab into 2:2 tetramers. Upon activation, the V{gamma}9V{delta}2 TCR becomes conformationally plastic and loses enriched lipids, including cholesterol and phosphatidylethanolamine. Our findings reveal a dimerization-driven activation mechanism, inform the design of rigid TCR-crosslinking agonists, and suggest multivalency-induced clustering as a general paradigm for {gamma}{delta} TCR activation.

immunology↗

bioRxiv2026

Simultaneous multi-area recordings in macaque frontoparietal cortex during a manual object-interaction task

Dexterous hand control is essential for daily activities and a top restoration priority for people with tetraplegia, yet neurophysiological datasets suitable for studying and decoding naturalistic hand behavior remain scarce. Most available recordings constrain movements to a small number of degrees of freedom or cover only a single stereotypical grasp-and-hold structure. Moreover, previous brain-computer interface (BCI) studies have largely relied on signals from a single cortical area, even though dexterous hand control is distributed across an interconnected frontoparietal network. To address these limitations, we designed a paradigm that elicits rich hand movements across 40 distinct hand-object interaction conditions. We recorded simultaneous frontoparietal activity with hand kinematics from a rhesus macaque performing them. Neural activity was recorded from the primary motor cortex, anterior intraparietal area, and ventral premotor cortex using microelectrode arrays spanning 1,920 channels, while a multi-camera markerless motion-capture system acquired video from which kinematics were extracted offline. The dataset comprises data from 20 sessions, including processed neural features, synchronized 3D coordinates of hand and elbow keypoints, and trial-level metadata including task conditions and event timing. We further provide technical validation, including a neural decoding benchmark with multiple algorithms for continuous keypoint coordination reconstruction. We found that cross-day and cross-task decoding performance varied among algorithms. Variation in channel availability leads to different performance degradation curves in different algorithms. This task-rich dataset offers a valuable resource for investigating the neural mechanisms of dexterous hand control and for advancing the performance of motor BCIs.

neuroscience↗

bioRxiv2026

Biologically grounded cell profiling across microscopy modalities

Microscopy-based cell profiling has broad applications in biological discovery, disease characterization, and phenotypic drug screening. Modern microscopy continues to push the limits of resolution, speed, depth and throughput, but better imaging does not automatically lead to better biomedical discovery and translation. A key bottleneck is feature representation: existing features are either handcrafted or learned as black-box embeddings and often lack explicit biological meaning. Here we propose biological grounding as a first principle for cell profiling and implement it through MorphAgent, an AI agent framework in which each quantitative feature originates from a biological hypothesis and is anchored to a cellular structure or process. By integrating biological knowledge, multimodal reasoning and automated validation, MorphAgent makes biologically grounded feature design systematic and scalable. We show biological grounding fundamentally changes the properties of cell profiling features. Across three microscopy modalities, MorphAgent produces compact, expressive and transferable features for drug screening, cell state characterization and disease morphology analysis. In wide-field Cell Painting, a common assay for phenotypic drug screening, it improves perturbation-retrieval mean average precision by 48% over CellProfiler and 20% over DeepProfiler while using substantially fewer dimensions. In confocal mitochondrial imaging, biologically grounded features transfer across independently acquired datasets and imaging resolutions, supporting accurate aging-state classification. In structured illumination microscopy (SIM) imaging of Tau-labeled samples, biologically grounded super resolution features reveal nanoscale morphologies inaccessible at conventional resolution, enhancing the discrimination of disease-associated mutations. Moreover, biologically grounded features provide a hierarchical organization of cellular morphology, enabling multilevel alignment with transcriptomics data and facilitating mechanistic understanding. Biologically grounded cell profiling thus brings AI reasoning closer to biological mechanisms, advancing biomedical discovery and translation.

bioinformatics↗

bioRxiv2026

TREM2 Orchestrates Myeloid Cell Programming and Immune Dysregulation in Pulmonary Hypertension

Pulmonary hypertension (PH) is a progressive and fatal disease characterized by pulmonary vascular remodeling, inflammation, and immune dysregulation. Myeloid-derived suppressor cells (MDSCs) and macrophages contribute to PAH pathobiology; however, the molecular regulators of their pathological activation remain poorly defined. The triggering receptor expressed on myeloid cells 2 (TREM2) is an immunomodulatory receptor that shapes myeloid cell metabolism, survival, and immunosuppressive function, yet its role in PH has not been investigated. Methods: Single-cell RNA sequencing (scRNA-seq) data from human pulmonary artery tissue (GSE210248; n=3 PAH, n=3 donors) were analyzed to characterize TREM2 expression across cell populations. Wild-type (WT) and global TREM2 knockout (TREM2 KO) mice were exposed to chronic hypoxia (10% FiO2, 28 days). Hemodynamic, histological, flow cytometric, and ex vivo functional assessments were performed. TREM2 expression was measured by flow cytometry in circulating MDSCs from PAH patients (n=22) and healthy controls (n=13). Results: TREM2 was markedly enriched in monocyte/macrophage populations in PH pulmonary arteries and TREM2-high immune cells exhibited transcriptional downregulation of chemotaxis programs and upregulation of antigen processing and MHC II presentation pathways. TREM2 deficiency significantly attenuated hypoxia-induced RVSP increase, right ventricular dysfunction, pulmonary inflammation, and vascular remodeling. MDSCs from TREM2 KO mice exerted significantly less suppression of CD4+ and CD8+ T cell proliferation. TREM2 was significantly elevated in circulating MDSCs from PAH patients and showed a directional association with hemodynamic severity. Conclusions: TREM2 is a novel regulator of myeloid-driven immunosuppression and vascular remodeling in PAH and warrants investigation as a therapeutic target and biomarker.

immunology↗

bioRxiv2026

Postnatal sensorimotor experience causally shapes hemispheric specialization across motor and language networks

The functional organization of the human brain is shaped by the interplay between innate constraints and postnatal experience. Hemispheric specialization, as a fundamental organizing principle of brain function, raises unresolved questions about how postnatal experience shapes lateralization and importantly, whether different lateralized cognitive systems develop through shared or independent mechanisms. We leveraged a natural experiment in individuals with obstetric brachial plexus injury (OBPI) in the right upper limb, resulting in lifelong left-hand dominance dissociated from the typical predisposition, to address these questions. Using functional MRI experiments during manual motor tasks, we found that altered hand-use experience selectively reshaped hemispheric organization in higher-order frontoparietal motor regions. Specifically, individuals with right OBPI showed reduced left-hemisphere dominance and rightward reorganization of abstract, hand-independent action representations relative to controls and individuals with left-side OBPI, whereas primary sensorimotor and subcortical regions preserved their canonical lateralizedl organization. Strikingly, experience-dependent motor reorganization extended beyond the motor system:individuals with right OBPI exhibited reduced left lateralization of the language network in Broca's area (BA44) during sentence listening. Crucially, language lateralization in BA44 covaried with the left lateralization of frontal motor areas, particularly for the compensatory, functional left hand. These findings demonstrate that postnatal bodily experience shapes the developmental emergence of hemispheric specialization, specifically in higher-order motor and language networks, and revealed coordinated organization between action and language systems.

neuroscience↗

bioRxiv2026

A Chemigenetic Fluorescence Lifetime Biosensor for Dopamine Sensing

Measuring the precise dynamics of specific neuromodulators in neurons is key to understanding how information is transmitted and processed in the brain. Despite the growing use of intensity-based neural activity sensors such as dLight in recent years, it remains challenging to monitor the dynamics of multiple neurochemicals simultaneously in live neurons. Unlike intensiometric sensors that are susceptible to artifacts caused by fluctuations in excitation power and rapid photobleaching, fluorescence lifetime-based sensors are less affected by these factors and can provide more stable measurements. Here we introduce dHaloLife635, a novel genetically encoded fluorescence-lifetime-based dopamine (DA) sensor that exhibits a fluorescence lifetime change up to -0.20 ns upon dopamine binding. dHaloLife635 consists of a G protein-coupled dopamine receptor (DRD1), a circularly permuted HaloTag (cpHaloTag), and a cell-permeable dye JF635 functionalized with a HaloTag ligand, a reactive chloroalkane linker (JF635-HTL). When dopamine binds to the dHaloLife635 sensor, it induces a conformational change in the cpHaloTag that alters the local environment of the conjugated dye, thereby changing its fluorescence lifetime. In live HEK293T cells and primary neurons, dHaloLife635 responds selectively to dopamine but not to serotonin, L-DOPA, or GABA, demonstrating excellent specificity. This dHaloLife635 sensor represents an initial step toward the establishment of a broader family of chemigenetic lifetime sensors that exhibit distinct fluorescence lifetime signatures upon binding their respective targets, thereby enabling highly specific and sensitive, real-time monitoring of multiple neurochemical dynamics in vivo.

bioengineering↗

bioRxiv2026

MINT infers the latent single-cell spatial transcriptome from paired histology

Sequencing-based spatial transcriptomics captures transcriptome-wide molecular information, yet the corresponding cell-resolved tissue map remains incomplete. Histology records dense cellular morphology, tissue architecture and local context. Here, we present MINT (Morphological Integrative Network for Transcriptomics), which combines this latent cellular organisation with sample-specific spatial measurements to infer tissue-wide, cell-resolved transcriptomes without an external single-cell reference. MINT reconstructs expression from sparse Slide-tags profiles across unmatched adjacent sections; its shared nucleus-centred representation also resolves pooled Visium measurements into cell-level profiles. MINT improved Slide-tags alignment and expression recovery under controlled nuclear loss and cross-section perturbation. It also outperformed reference-free Visium disaggregation methods against Xenium ground truth and was validated with Visium HD sequencing. In human lung adenocarcinoma, MINT reconstructed the tumour immune microenvironment cell by cell and resolved tertiary lymphoid structures and their maturity. These results establish paired histology as a quantitative, sample-intrinsic complement to molecularly rich but cellularly incomplete spatial-transcriptomic assays.

bioinformatics↗