Biology subjects

Gao, Z.

Publications and source records attributed to Gao, Z..

At least 19 recordsLinked to original sources

bioRxiv2026

Forward reactivation in human hippocampal CA1 supports repetition learning and is preserved in the aging brain

Repetition is a fundamental mechanism for strengthening episodic memory, yet the neural computations engaged during re-exposure remain disputed. Competing accounts attribute repetition-related gains either to retrospective reinstatement of prior events or to the prospective use of learned structure to anticipate what comes next. Using high-resolution functional MRI and representational similarity analysis in a lifespan cohort (N = 418, ages 36 -100), we tracked hippocampal representations as participants twice encoded two fixed sequences of face-name pairs, resolving reactivation by direction, distance and sequence. During repeated encoding, CA1 and CA2/3/DG representations spontaneously anticipated immediate next states, unprompted by explicit task demands. Forward, but not backward, reactivation predicted repetition-related gains, and showed no detectable age dependence. Only CA1 forward reactivation predicted memory gains after accounting for reactivation in other medial temporal lobe regions. Repetition learning is thus an active, temporally local prospective computation with a distinctive CA1 contribution that appears preserved well into old age.

neuroscience↗

bioRxiv2026

Reinforcement learning with evolutionary priors unlocks multi-site enzyme optimization from sparse experimental feedback

Industrial enzymes underpin sustainable manufacturing, yet natural proteins rarely combine the activity, robustness and application compatibility required for practical use. Engineering such properties requires identifying beneficial combinations of interacting mutations within vast sequence spaces that are too large to search exhaustively and too sparsely sampled to model reliably. Here we introduce AlphaVariant, a reinforcement-learning (RL) framework that couples a generative evolutionary prior with iteratively updated low-N fitness models to enable feedback-driven search of large combinatorial protein sequence spaces. Across six experimentally measured protein fitness landscapes, AlphaVariant ranked first on the three large, non-enumerable multi-site landscapes. In two successive rounds of savinase activity optimization, AlphaVariant-designed libraries yielded 75.4% and 83.8% activity-improved variants among experimentally characterized candidates even as the accessible mutation space expanded from 25 to 67 positions. The search identified beneficial mutation combinations involving up to 17 structurally dispersed sites and produced a variant with 7.1-fold higher activity than wild type after only two design-test cycles. We then extended AlphaVariant to jointly optimize activity, thermostability and a patent-informed constraint for intellectual-property freedom. This multi-objective search yielded variants that outperformed the commercial protease Uno 100 L in both biochemical assays and application-relevant detergent washing tests. These results demonstrate that generative RL can efficiently navigate vast protein fitness landscapes, progressively incorporate multiple engineering objectives and convert sparse experimental feedback into enzyme variants with industrially relevant performance, effectively resolving the limits of biocatalyst engineering.

bioinformatics↗

bioRxiv2026

Functional deficits of the inhibitory control system in children with ADHD: A task-based fMRI meta-analysis

Inhibitory control deficits have long been proposed as a central neurocognitive mechanism underlying childhood Attention Deficit/Hyperactivity Disorder (ADHD). However, neuroimaging findings remain heterogeneous, partly due to methodological variability across developmental samples and experimental paradigms. The present study aimed to characterize the neural architecture of motor response inhibition in typically developing (TD) children and identify reproducible functional abnormalities associated with pediatric ADHD using stringent, developmentally specific inclusion criteria. We conducted two coordinate-based meta-analyses using Activation Likelihood Estimation (ALE). Following a systematic literature search (up to August 2026), we identified 23 task-based fMRI studies reporting inhibitory-control-related activation in TD children (237 foci) and 17 studies comparing children with ADHD and TD peers (114 foci) during the Stop-Signal Task or Go/No-Go Task. All participants were younger than 18 years of age. Statistical significance was determined using cluster-level family-wise error (FWE) correction. In TD children, ALE revealed a robust inhibitory-control network encompassing the bilateral anterior insula (AI), inferior frontal gyrus (IFG), and the midline pre-supplementary motor area (preSMA) and anterior cingulate cortex (ACC). This spatial organization closely resembled the canonical inhibitory-control network consistently observed in adults, suggesting that the core neural architecture supporting motor inhibition is already detectably organized during development. In the between-group analysis, children with ADHD exhibited significant hypoactivation primarily within the preSMA. Notably, this region demonstrated striking spatial overlap with the preSMA cluster reliably recruited in TD children during motor inhibition. These findings provide convergent support for inhibitory-control models of ADHD and identify altered preSMA recruitment as one of the most consistent functional abnormalities associated with pediatric ADHD. While the neural infrastructure supporting inhibitory control is broadly established during childhood, children with ADHD exhibit reduced recruitment of a key cortical node within this network during motor inhibition demands.

neuroscience↗

bioRxiv2026

Rank Normalization Enables Cross Pathway Comparison in Degradation Resolved Proteome Turnover Analysis

Protein homeostasis, or proteostasis, is essential for cellular health, and its disruption contributes to cancer, aging, and neurodegenerative disease. Proteostasis is maintained largely by two intracellular degradation systems: the ubiquitin proteasome system (UPS) and the autophagy lysosomal pathway (ALP). Here, we combine pulse stable isotope labeling by amino acids in cell culture (pSILAC) with selective inhibition of the UPS or ALP to quantify pathway-dependent protein turnover and identify substrates that are preferentially cleared through each route. Direct comparison of these perturbations is complicated by their markedly different response distributions. To address the mismatch in dynamic range, we developed a normalization strategy based on within-condition ranks. Protein stabilization values are converted to percentile scores before comparison across pathways, placing both perturbations on a common relative response scale. Across two independent pSILAC experiments, 5,518 proteins were quantified in at least one condition, and 3,814 yielded high confidence half-life measurements in control, proteasome-inhibited, and lysosome-inhibited conditions. Rank normalization resolved pathway sensitivities that were obscured by direct comparison of absolute half-life changes. Importantly, the method reports relative pathway preference rather than absolute pathway contribution, exchanging effect size magnitude for comparability across perturbations with unequal response distributions. Integration with a curated proteostasis network annotation revealed coherent pathway preferences, including coordinated stabilization of proteasome core and regulatory subunits following lysosomal inhibition. This finding provides proteome-wide quantitative evidence for proteaphagy that complements previous targeted observations. Together, these results establish rank normalization as a practical strategy for comparing degradation resolved proteome turnover across perturbations with different dynamic ranges.

molecular biology↗

bioRxiv2026

CycDelta: Multimodal Residue-Graph Learning of Permeability Changes in Cyclic Peptides

Membrane permeability remains a major challenge in cyclic-peptide drug discovery, where optimization often depends on estimating changes relative to measured reference compounds. Existing predictors mainly model absolute permeability, while heterogeneity across literature sources complicates pooled training and comparative evaluation. We present CycDelta, a multimodal residue-graph model trained directly on within-source permeability differences. CycDelta combines directed message passing with pretrained Uni-Mol monomer embeddings, physicochemical descriptors and assay information in a shared encoder for reference and query peptides. To evaluate this comparative formulation under controlled conditions, we establish CycDeltaBench, comprising in-distribution, scaffold-based out-of-distribution, external and zero-shot unseen-assay tests. On the out-of-distribution task, CycDelta achieved Pearson 0.69 versus 0.46 for the strongest baseline. It also led all evaluated methods on two external data sets and achieved zero-shot Spearman 0.70 versus 0.32 for the strongest baseline on an unseen assay. Residue-level attribution relates predictions to monomer contributions, while gradient-guided screening supports prioritization of permeability-enhancing analogue hypotheses. These results position CycDelta as a transferable and interpretable framework for comparative permeability prediction and cyclic-peptide optimization.

bioinformatics↗

bioRxiv2026

Unbiased and Epicardial-Specific Lineage Tracing Reveal Epicardial Contribution to Vascular Endothelial Cells in Heart Development

Controversy surrounds the lineage potential of cardiac cells, particularly epicardial cells, during heart development, largely due to the non-specific expression of epicardial marker genes and the resulting non-specific labeling in Cre-loxP mouse models. Using DARLIN mice, a CRISPR/Cas9-based lineage-tracing system independent of the Cre-loxP system, we analyzed the lineage development of embryonic cardiac cells in an unbiased manner and identified lineages shared among different cell types, such as epicardial cells and vascular endothelial cells (Vas_ECs). To further confirm the lineage potential of epicardial cells, we identified an epicardial cell-specific marker gene, Lrrn4, through analysis of a multi-staged single-cell mRNA-sequencing (scRNA-seq) dataset, and generated a corresponding Lrrn4-CreER mouse line. We then bred this line with a reporter mouse to confirm its specificity for labeling epicardial cells, and subsequently performed prolonged lineage tracing, which revealed specification of the labeled epicardial cells into Vas_ECs. Finally, Using this mouse line, we investigated epicardial cell function by selectively ablating these cells and by expressing TGF{beta} in epicardial cells to convert their lineage from Vas_ECs to fibroblasts. Both approaches resulted in significant developmental defects in embryonic hearts. Together, these results indicate that epicardial cells can give rise to Vas_ECs, and that the Lrrn4-CreER mouse model is a valuable tool for elucidating the role of the epicardium in heart development.

developmental biology↗

bioRxiv2026

TRAPPC8 Is an Endogenous Brake on UFMylation That Suppresses Tauopathy

UFMylation, a ubiquitin-like protein modification, drives tau spread through the brain, but what keeps this process in check has remained unclear. We show that TRAPPC8 acts as a natural brake on UFMylation, binding directly to the E1 enzyme UBA5 to dampen pathway activity. In Alzheimer's disease brain tissue, TRAPPC8 is reduced while UFMylation is elevated, suggesting this brake fails as disease progresses. Sustaining UFMylation in human iPSC-derived neurons increased tau aggregation and spread while disrupting lysosomal function and lipid balance. Restoring TRAPPC8-UBA5 binding reversed these defects through the lysosomal protein CLN8, which restored lysosomal function and reduced tau pathology. Notably, expressing just the UBA5-binding region of TRAPPC8 was enough to suppress tau pathology in vivo, marking it as a promising therapeutic target.

neuroscience↗

bioRxiv2026

RegFM: an interpretable context-aware foundation model for human transcriptional regulation

Transcriptional regulation is governed by interactions between cis-regulatory elements (CREs) and trans-acting regulators in a context-specific manner. Although DNA and single-cell foundation models have enabled modeling regulatory biology at scale, most represent either sequence or cellular state alone, limiting their ability to capture context-dependent gene regulation. Here we present RegFM, a context-aware foundation model for human transcriptional regulation. RegFM treats transcriptional regulation as a dialogue between cis-regulatory sequences (e.g., CREs) and trans-acting regulators (e.g., transcription factors (TFs) and chromatin regulators (CRs)) by coupling long-range CRE representations with TFs and CRs activity. Trained on large-scale ENCODE and CELLxGENE transcriptomic profiles, RegFM learns gene-centered regulatory representations that generalize across unseen cellular contexts. In a wide range of tasks, including gene expression prediction, cis-regulatory element annotation, bivalent promoter and dosage-sensitivity classification, and perturbation-response prediction, RegFM consistently improves over existing methods. RegFM emerges as a scalable and interpretable framework for modeling human transcriptional regulation and provides insights into context-dependent gene regulatory programs.

genomics↗

bioRxiv2026

In situ Discovery of Immune Repertoire Reveals Antitumor Immunity and Therapeutic Antibodies

Spatial transcriptomics offers a glimpse into the immunology of tissues. However, limitations in spatial transcriptomics preclude the detection of highly diverse, low-abundance, and previously unknown sequences, including immune repertoires and microbiota. Here, we introduce Archimap, a spatial transcriptomic platform that simultaneously profiles spatial transcriptomes, immune repertoires, and microbiota from formalin-fixed paraffin-embedded (FFPE) tissues. Using Archimap, we profile the spatial localization of TCRs, BCRs, and the microbiota landscape in archived clinical tissues at single-cell resolution. Through comprehensive benchmarking, we validate Archimaps performance and fidelity. Archimap in situ assembles the immune complex and reconstructs the clonal evolution of antibodies. Together, Archimap shows the power of in situ discovery of functional immune repertoires for their antitumor immunity.

bioinformatics↗

bioRxiv2026

Knee Joint Biomechanics During Lunges at Different Tibial Angles and External Loads: A Musculoskeletal Analysis with Finite Element Insights

ObjectiveThis study investigates knee joint biomechanics during lunges under varying tibial angles and external loads using musculoskeletal modeling and finite element analysis. The goal is to provide a biomechanical basis for understanding knee loading patterns and optimizing sports training and rehabilitation. MethodsTwenty-six healthy young men performed lunges under tibial inclination angles relative to the ground (60{degrees} and 90{degrees}) and two external load conditions (bodyweight and an additional 98 N external load). Kinematic and kinetic data were captured using motion capture and force plates. Musculoskeletal models were used to estimate joint moments, range of motion, and stiffness, with data analyzed using two-way repeated-measures ANOVA. Finite element analysis was performed at 90{degrees} tibial angle to evaluate tissue stress and displacement. ResultsThe joint moment at a 60{degrees} tibial angle was much higher than at a 90{degrees}. External load showed significant effects on knee stiffness, with lower rotational stiffness in the horizontal plane (P < 0.001) and lower coronal plane stiffness at 90{degrees} (P = 0.012) under the 98 N external-load condition, indicating reduced resistance to angular displacement in these planes. Under the 90{degrees} tibial-angle condition with external load, peak stress and displacement were concentrated in the posterior horn of the meniscus, with a maximum displacement of 3.12 mm. ConclusionThe anterior tilt of the tibia increased sagittal-plane knee loading, while external load mainly reduced joint stiffness in the coronal and horizontal planes. Under the 90{degrees} loaded condition, the concentration of stress and displacement in the posterior horn of the meniscus suggests a mechanically unfavorable loading pattern rather than direct evidence of injury risk. These findings may provide useful biomechanical information for load management during lunge-based training and rehabilitation.

bioengineering↗

bioRxiv2026

Decoding the oxytocinergic and behavioral signatures of milk ejection

Oxytocin-mediated milk ejection (ME) is pivotal to effective breastfeeding and productive health, yet behaviorally decoding and revealing neural mechanisms of ME remains challenging. Here, we combined in vivo calcium imaging and intramammary pressure recording to uncover the temporal connections between episodic activity of oxytocin neurons and ME in conscious lactating rats. Leveraging the association and behavioral responses in dam and pup, we developed a supervised machine learning framework (ME Decoder) to enable automated analyses of ME. Inspired by its interpretable features, we defined the activity-coupled dam-pup interactions (ADPI), manifested by high kyphosis of the dam followed by pup treading and stretch, as the behavioral signatures of ME. By ME Decoder and ADPI analyses, we detected reduced ME but unaffected activity of oxytocinergic neurons after systemic blockade of oxytocin receptor. Our study uncovers the oxytocinergic and behavioral signatures of ME and provides a generalizable approach for further investigation.

neuroscience↗

bioRxiv2026

Protracted Maturation of Proactive and Reactive Systems Predicts Cognitive Stability and Psychopathology : A longitudinal multi-cohort study

Inhibitory control matures progressively from childhood to early adulthood, yet the neural mechanisms driving this development and their relevance to psychiatric risk remain poorly understood. Guided by the Dual Cognitive Control model, we leveraged longitudinal fMRI from two independent cohorts in the US (ABCD, ages 9-12) and Europe (IMAGEN, ages 14-22) to map the spatiotemporal dynamics of reactive and proactive control using novel single-trial modeling and representational similarity analysis. We found both reactive and proactive stopping networks stabilize after mid-adolescence, tracking the developmental patterns of inhibitory control and behavioral stability. By decoding trial-by-trial fluctuations along a speed-caution continuum, we demonstrate that brain-behavior coupling to a proactive "Safe state" tightens progressively with age. Furthermore, network-level representational coherence of this Safe state emerged as a scanner-invariant, trait-like biomarker that robustly predicted inhibitory control, behavioral stability, and transdiagnostic psychopathology across multiple developmental windows, providing a validated neural phenotype for precision psychiatry.

neuroscience↗

bioRxiv2026

Design of a Low-Latency sEMG Real-Time Correction System Based on High CMRR and EMRMS Mathematical Modeling

Surface electromyography (sEMG) interfaces require interference-resistant acquisition, faithful preprocessing, and a responsive envelope for downstream control. This work presents a reproducible, analog-aware digital conditioning pipeline comprising an eighth-order Butterworth band-pass, a narrow static notch, a recursive-oscillator two-harmonic normalised least-mean-squares (NLMS) canceller, a rolling mains-frequency tracker, and an exponentially weighted RMS (EMRMS) envelope. The analog common-mode analysis is separated into a complex frequency-domain decomposition and a scalar CMRR sensitivity screen; the latter is explicitly treated as a pre-prototype approximation rather than a substitute for circuit simulation or bench measurement. A running-sum rectangular RMS requires O(1) arithmetic and O(L) memory, whereas EMRMS requires O(1) arithmetic and one dynamic power state. At fs = 2 kHz and{tau} = 25 ms, the EMRMS power smoother has a weight-centroid delay of 24.75 ms and a noise-equivalent rectangular length of 100.0 samples. In a controlled drifting-line experiment, the tracker achieved an RMSE of 0.118 Hz; tracked two-harmonic cancellation improved whole-record reconstruction SNR by approximately 19.3 dB relative to the static-notch baseline. In a separate 12-channel synthetic ablation, median reconstruction SNR was 11.5 dB for tracked harmonic cancellation, compared with 8.8 dB for fixed-frequency harmonic cancellation and -11.2 dB for the static-notch baseline. Delay-aligned EMRMS and length-200 running-RMS envelopes had correlation{rho} = 0.994. The host-Python fast path required a median of 13.0 {micro}s per sample and a 99th percentile of 24.9 {micro}s; accepted frequency updates required a median of 161 {micro}s and should be scheduled as a supervisory task on embedded hardware. All numerical performance results reported here are controlled synthetic experiments. The accompanying real-data workflow never substitutes generated data when recordings are absent; multi-subject and embedded-hardware validation remain future work.

bioengineering↗

bioRxiv2026

Light-dependent and predator inducible aldehyde synthesis in Prochlorococcus for specific defense against Uronema

Cyanobacteria as a primary producer provide energy and carbon sources for the marine food web, of which predation-interactions play central roles in regulating global element cycles and marine ecosystem stability. Here, we report the anti-predation activity of a typical marine cyanobacterium Prochlorococcus MED4 to defend the predation by Uronema marinum. MED4 synthesize formaldehyde as the anti-predation chemical, of which the synthesis was light-dependent and predator-inducible. Compared to other protists, both the higher concentration of accumulated formaldehyde in U. marinum and the lower formaldehyde tolerance of U. marinum resulted in the specific anti-predation of MED4 against U. marinum. This specific anti-predation could regulate the cyanobacterial growth and the U. marinum infection of marine fishes. Metadata analyses showed the mutually exclusion of Prochlorococcus and Uronema in global marine environments. These findings significantly advance our understanding of the marine food web and biogeochemical cycles. Significance StatementPredation-driven interactions in the ocean are critical regulators of global biogeochemical cycles, yet active defense mechanisms in marine picophytoplankton remain largely unknown. This study reveals that Prochlorococcus MED4 as the most abundant primary producer in the ocean synthesize light-driven and predator-inducible aldehydes to actively and specifically defend predation against the ciliate Uronema marinum. The anti-predation of Prochlorococcus against Uronema could have broad implications in biocontrol of Uronema infection in marine fishes and regulation of the marine food web.

microbiology↗

bioRxiv2026

scMTG reconstructs single-cell temporal dynamics with Markov transition generators

Single-cell time-series data offer a unique opportunity to study how cell states emerge, evolve, and diversify over time. However, cells are destructively measured across time points and individual cells cannot be directly tracked, making it challenging to reconstruct cell-state transitions and uncover the dynamic regulatory programs. Existing methods are predominantly based on optimal transport and typically require predefined low-dimensional representations, which can limit scalability, flexibility, and mechanistic interpretability. Here we present scMTG, a single-cell Markov transition generative framework that jointly learns cell representations and temporal cell-state transitions from unpaired single-cell time-series data. In a series of experiments, scMTG demonstrates superior performance in interpolating held-out missing-time-point data and inferring cross-time-point transition matrices, compared with state-of-the-art methods. More importantly, the learned Markov transition generator provides an interpretable framework for identifying the molecular programs that drive cell-state changes, enabling characterization of cell fate decisions and construction of time-resolved regulatory networks. Together, scMTG provides a unified generative framework for reconstructing cellular dynamics and uncovering regulatory programs that shape development, differentiation, and disease progression. scMTG is available as open-source software at https://github.com/liuq-lab/scMTG.

bioinformatics↗

bioRxiv2026

Balancing of immune activation and suppression during phage infection

Signaling-based anti-bacteriophage systems such as CBASS and Thoeris synthesize infection-triggered nucleotide signals that activate anti-phage effectors1,2. However, the phage features sensed by these systems and the mechanisms phages use to evade signaling immunity remain poorly understood. Here, studying clinically relevant Pseudomonas aeruginosa phages from the Migulavirinae family3, we show that closely related phages encode subtle allelic variation in side tail fiber proteins that determine sensitivity to type II Thoeris. In parallel, these same phages encode an "anti-defense hotspot" that contains three adjacent genes that are each sufficient to facilitate phage evasion of both CBASS and Thoeris defenses, counter-balancing the activating proteins. Comparative analysis of this anti-signaling hotspot across the broader family of related N4-like phages uncovered a new Thoeris anti-defense (Tad) protein that sponges NAD-derived molecules (e.g. gcADPR) and exhibits sequence and structural similarity to a poorly characterized nucleotide-binding region of the human ryanodine receptor. Together, these findings reveal how the balance between immune activation and antagonism shifts phage outcomes and reveals a surprising similarity between a phage molecular sponge and an important human protein.

microbiology↗

bioRxiv2026

Interpreting GC content differences across populations at polymorphic sites

Recent studies have reported consistent inter-population differences in GC content at polymorphic sites in multiple species, including humans. Specifically, populations that experienced recent bottlenecks exhibit lower average GC content (GC%) at common polymorphic sites compared to non-bottlenecked groups--an observation previously interpreted as indication of rapid evolution of base composition. In this study, we investigate the evolutionary and technical factors driving these patterns across humans, mice, maize, and silkworm. We find that GC% at polymorphic sites is highly sensitive to the allele frequency threshold applied. Relaxing this threshold reduces inter-population differences to negligible levels in humans and significantly attenuates similar signals in other species. We further observe substantial GC% variation across allele frequency bins, a pattern driven by the differential abundance of different mutation types. We demonstrate that these observations are collectively driven by an interaction between demographic history and a universal excess of strong-to-weak mutations relative to weak-to-strong mutations, which is counteracted by GC-biased gene conversion (gBGC) over long evolutionary timescales. Forward-in-time simulations with realistic parameters recapitulate observed patterns of GC% variation across both populations and allele frequency bins. Overall, our findings reveal that the base composition at polymorphic sites is strongly shaped by the interaction between demographic history, mutation bias, and gBGC, and does not represent stable, genome-wide trends. Consequently, inter-population differences in GC content--especially at common variants--should not be interpreted as evidence of ongoing divergence in base composition or shifts in mutation patterns.

evolutionary biology↗

bioRxiv2026

SpaCir-VDJ: a broadly compatible circularization strategy for spatial immune repertoire profiling

Deciphering the spatial organization of immune clonal lineages is critical for understanding the evolution of adaptive immune responses. However, mainstream spatial transcriptomics platforms struggle to reconcile cost-effective short-read sequencing with the simultaneous and efficient capture of V(D)J sequences. To address this gap, we developed SpaCir-VDJ, an approach that utilizes a "multiplex PCR enrichment plus library circularization" strategy to integrate spatial barcodes and V(D)J CDR3 regions into a compact circular template optimized for standard short-read sequencing. This workflow is accompanied by an automated computational pipeline designed for circular-library data parsing, sequence reconstruction, spatial barcode deconvolution, and high-fidelity clonotype calling. In human lymphoid tissues, SpaCir-VDJ delineated germinal center (GC)-associated clonal organization and isotype-linked somatic hypermutation (SHM) patterns. Notably, lineage-based spatial analyses inferred inter-GC clonal redistribution events, suggesting that GCs in the analyzed samples may not be fully isolated reaction units. Functional perturbation provided orthogonal support for candidate SHM regulators identified by spatial analysis, with knockdown of MDM4, LYN, EAF2, and H2AFY each leading to reduced SHM. Finally, in gastric cancer, SpaCir-VDJ localized dominant BCR lineages within tertiary lymphoid structures and tumor-margin plasma cell-rich regions, with lineage patterns consistent with extension toward the tumor interior. We further observed a significant positive correlation between cumulative tumor mutations and spatial TCR diversity, consistent with a spatial association between local mutational burden and T-cell remodeling within the tumor microenvironment. Collectively, SpaCir-VDJ provides a scalable and cost-effective framework for interrogating the spatiotemporal dynamics of immune microenvironments.

immunology↗