Biology subjects

Tang, R.

Publications and source records attributed to Tang, R..

At least 19 recordsLinked to original sources

bioRxiv2026

Consensus Formation History Shapes Collective Updating

Consensus is rarely a one-off achievement. In a changing world, groups must repeatedly update judgments they have already agreed upon, making consensus updating a common feature of real-world collective decisions. However, previous research on collective decision-making has focused mainly on how groups reach a single consensus, leaving the updating of established consensus largely unexamined. This raises two unanswered questions: does consensus updating involve biases analogous to sunk cost, and are such biases related to the cost of the previous consensus? Building a Fake Consensus paradigm, we manipulated consensus-formation cost and examined how dyads updated a subjectively established consensus after new information arrived. An independent individual experiment provided information-matched updating baselines, allowing us to determine whether dyads updated less or more than individuals responding to the same evidence. Contrary to sunk-cost predictions, low-cost consensus led dyads to update less than the individual baseline, whereas medium- and high-cost consensus led them to update more. The pathway through perceived consensus sharedness was significant, and the association between sharedness and updating was stronger at higher left temporoparietal junction inter-brain synchrony. These findings indicate that the history of consensus formation shapes subsequent updating by altering the psychological meaning of shared endorsement, while interpersonal alignment determines how this shared experience translates into coordinated behavior. To our knowledge, this is the first experimentally controlled study of consensus updating in teams to isolate formation history from actual disagreement, providing a new paradigm for studying how collective judgments change after agreement.

neuroscience↗

bioRxiv2026

When Deeper Analysis Weakens Aesthetic Experience: Behavioral and Brain Network Evidence

Analysis does not always enhance aesthetic experience. Philosophical accounts have long suggested that decomposing an aesthetic experience into determinate components may weaken it, yet this possibility has rarely been tested experimentally. To examine whether, when, and how analysis produces divergent effects on aesthetic experience, we conducted two experiments manipulating analysis depth. Experiment 1 showed that, during affective analysis of visual art, deep analysis produced a significantly weaker increase in aesthetic ratings than shallow analysis. In Experiment 2, we selected this condition to investigate the underlying mechanism. The behavioral effect was replicated: deep analysis removed the increase produced by shallow analysis without reducing ratings below the image baseline. Frequency-resolved brain network analysis further revealed a stronger task-related component and higher spatial entropy within the default mode network under deep analysis. Network-behavior correlations observed under shallow analysis were absent under deep analysis, suggesting reduced correspondence between the default-mode network (DMN) organization and aesthetic experience. Exploratory analyses further showed that spatial weights in the lateral temporal cortex and inferior parietal lobule were associated with smaller increases in aesthetic ratings. Together, these findings indicate that deeper analysis can selectively weaken improvements in aesthetic experience by altering how affective information is organized within the DMN.

neuroscience↗

bioRxiv2026

Use of photocaged molecular oxygen for time-resolved serial X-ray crystallography

Photocages offer an attractive means of synchronously triggering enzyme-substrate driven reactions in biological systems in crystallo expanding the reach of light-driven catalysis. We describe the application of photocaged molecular oxygen to trigger molecular oxygen binding in crystals of myoglobin under anaerobic conditions and follow structural changes using both serial synchrotron and serial femtosecond X-ray crystallography. This is enabled through use of fixed targets under anaerobic conditions, utilising thin polymeric films with low molecular oxygen permeability and validated by serially collecting deoxy myoglobin structures and complementary in crystallo UV-Vis spectroscopy. Release of molecular oxygen from the photocage and subsequent binding of the gaseous ligand is structurally visualised in oxygen-bound structures of myoglobin at 5 and 10 ms and various laser parameters. We present a robust workflow for enabling anaerobic room-temperature data collection of oxygen-sensitive samples on fixed targets and report the successful photo-release of caged molecular oxygen for time-resolved serial crystallography.

molecular biology↗

bioRxiv2026

Mechanisms of resilience to autosomal dominant Alzheimer's disease via oligogenic modulation of rare variants in the entorhinal cortex

Two PSEN1 E280A carriers have presented extreme protection against autosomal dominant Alzheimers disease (ADAD), with over two decades of delay for dementia onset. One of them, a male heterozygous for the RELN-COLBOS protective variant showed increased neuronal density in the entorhinal cortex 1. We conducted a deep phenotyping and genotyping study of the entorhinal cortex in protected and unprotected PSEN1 E280A cases, sporadic AD, and non-demented controls. We used single nuclei and spatial transcriptomics, whole genome sequencing, and candidate genotype-associated expression changes (GAEC) analysis. Our results showed unique neuronal and oligodendrocytic populations in the male RELN-COLBOS patient. Unique RELN positive inhibitory interneurons were enriched in cortical Layer I, while unique abundant ADAMTSL1 positive excitatory neurons were distributed in Layers II/III and Layer Va. These neurons and mature myelinated oligodendrocytes benefitted from increased expression of LRP6 receptor, functioning as a non-canonical receptor for the mutated Reelin protein encoded by RELN-COLBOS. Finally, GAEC and pathway enrichment analyses suggested that other mutations enhanced RELN-COLBOS effects in oligodendrocytes in the male RELN-COLBOS patient, explaining the phenotypic differences with his sister, a RELN-COLBOS carrier with no evident protection from ADAD. Our findings suggest that extreme deviations of the PSEN1 E280A phenotype are more likely attributed to oligogenic effects, including simultaneous mutations occurring in genes including ITGA2, involved in single molecular pathways, such as the Integrins / Focal Adhesion pathway, as potential disease modifiers for Alzheimers disease (AD).

neuroscience↗

bioRxiv2026

Characterizing Functional Clusters of V4 Neurons in Digital Twins

Neurons in primate visual cortical area V4 display tuning for multiple visual features, including color, shape, texture, and depth. Whether and how these neurons are organized into functional architectures remains largely unknown. Using two-photon calcium imaging in anesthetized macaques, we recorded responses of hundreds of V4 neurons to natural images and used these data to train deep convolutional neural network models (digital twins), obtaining synthetic images (SI) that maximized neuronal responses. Based on their SIs, these neurons clustered into classes that spatially matched the orientation, color, and curvature maps from intrinsic signal imaging. Furthermore, lesion study in digital twins revealed different integration rules for different neuron classes. Thus, digital twins of V4 neurons can be applied as a promising tool to characterize neurons fundamental features, which underlie the functional clustering in this area. HighlightsO_LINeurons in V4 are examined with two-photon calcium imaging and DCNN modeling (digital twins) C_LIO_LISynthetic images derived from neurons digital twins reveal distinct neuron groups C_LIO_LIThese groups match functional types defined by intrinsic signal optical imaging C_LIO_LILesion study in digital twins demonstrates neural mechanisms underlying feature tuning C_LI

neuroscience↗

bioRxiv2026

Autophagy protects pancreatic β-cells during hypoxia and islet transplantation but is compromised by TFEB-lysosomal dysfunction

Hypoxia is a potent stressor and a major cause of {beta}-cell failure and loss after islet transplantation. Autophagy is a critical homeostatic mechanism that preserves organelle integrity and metabolic balance in cells under stress, but whether it supports {beta}-cell adaptation to sustained oxygen deprivation is unclear. Here, we used {beta}-cell-specific Atg5 knockout together with hypoxia and transplantation models, to demonstrate that autophagy is a major determinant of {beta}-cell survival during oxygen limitation and supports islet graft function. However, prolonged hypoxia suppressed autophagic flux, reduced lysosomal activity, and led to autophagosome accumulation, indicating failure of the lysosomal clearance pathway. This was accompanied by a marked reduction in transcription factor EB (TFEB) and its lysosomal target genes. Genetic and pharmacological activation of TFEB restored lysosomal gene expression and cathepsin B activity and improved {beta}-cell viability under hypoxia, implicating TFEB decline as a contributor to autophagy-lysosome dysfunction. Together, these findings outline a sequence in which autophagy initially safeguards {beta}-cells but becomes ineffective under sustained hypoxia as TFEB levels fall, identifying TFEB as a potential target to strengthen {beta}-cell resilience and survival in islet transplantation.

cell biology↗

bioRxiv2026

Gaming Addiction Transmission: Interpersonal Neural Pathways Revealed by HYPER-NESS

Gaming addiction may be contagious through social interaction. In team competitive video games, individuals of varying addiction levels are often paired. This raises the question of whether, and through what mechanisms, one individuals addiction level is affected by other players. Methodologically, addressing this question requires understanding both what happens between brains and within individual brains during a gaming session. To this end, we used HYPER-NESS (Hyper Brain Network Estimation via Source Separation), a novel analytical framework to decompose and weight the distinct contributions of inter-brain and intra-brain processes to social brain networks. We applied this framework to a hyperscanning fNIRS dataset where dyads were scanned while playing a video game together against experimenters. We found that inter-brain and intra-brain contributions to the social brain networks were differentially associated with changes in game reward and social reward sensitivity, depending on the addiction level of ones partner. Granger causality analysis of both social and individual brain networks revealed influences from the high-addiction partner to low-addiction partner. Furthermore, significant cross-frequency coupling was found selectively between low-addiction players, supporting the idea that this form of inter-brain interactions underpins the joint processing of task-relevant rewards. To our knowledge, these findings provide the first neural-level account for the hypothesis that gaming addiction propagates though dyadic social interaction.

neuroscience↗

bioRxiv2026

Single-cell gene regulatory network reconstruction and key regulator identification using a dual-channel fusion graph convolutional network

Background and objectiveGene regulatory networks are formed by complex regulatory relationships between transcription factors and their target genes. A systematic understanding of these regulatory relationships is crucial for deciphering the molecular mechanisms that underlie cell state transitions under physiological and pathological conditions. Single-cell expression data can reveal cell-type-specific transcriptional regulation, and computational methods have recently been developed to infer gene regulatory networks from single-cell transcriptomics and prior regulatory knowledge. However, existing methods could not explore the common and specific information in expression correlations and prior regulatory knowledge, which can adversely affect prediction performance. MethodsWe propose a novel method for inferring gene regulatory networks from single-cell RNA sequencing data. The proposed method consists of dual-channel graph neural networks and a weight-shared common graph neural network, enabling effective fusion of prior regulatory knowledge with gene co-expression patterns. Furthermore, we formulate a new computational framework built upon the proposed algorithm, which integrates differential gene expression profiles and regulatory changes to identify key regulators that distinguish different cell states. ResultsExperimental results demonstrate that our method significantly improves the accuracy of regulatory inference across multiple datasets, outperforming other state-of-the-art approaches. Our method also exhibits robustness to noise and missing data. Analysis of two single-cell expression datasets suggests that the proposed framework could help identify key regulators involved in tumor metastasis and drug resistance. ConclusionThese results indicate that the proposed method could advance the understanding of the biological mechanisms underlying diseases by reconstructing single-cell gene regulatory networks and identifying key regulators across different cell states.

bioinformatics↗

bioRxiv2026

Visual gamma stimulation causes prolonged enhancement of low-frequency blood flow oscillations across cortical regions in mice

IntroductionGamma entrainment using sensory stimuli (GENUS) uses 40Hz-pulsed sensory stimuli to entrain neural activity in the gamma band (30-150Hz). However, the effect of GENUS on low-frequency vascular oscillations has not been fully explored. ObjectivesThe objective of this study is to elucidate the effect of GENUS on vasomotion in healthy mice and potential confounds for future application in disease studies. MethodsHead-fixed, awake C57Bl/6 mice (n=18; 9M 9F) aged between 18 to 60 weeks were subjected to white light of either 40Hz visual flicker (GENUS), or constant stimulus (control). Blood flow was imaged using laser speckle contrast imaging (LSCI) before, during, immediately after 1 hour of stimulus, and 30min after the stimulus termination. ResultsA linear mixed-effects model showed that GENUS enhanced the magnitude of 0.2-0.4Hz blood flow oscillations by 38% during stimulation and by 30% at 30 minutes after stimulation compared to control when controlled for age, sex, and other factors. The effect on vasomotion was distributed across many cortical regions not limited to visual areas and lasted beyond 24 hours post-stimulus. ConclusionThese results support the exploration of GENUS for increasing vasomotion in therapeutic contexts. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=186 SRC="FIGDIR/small/729102v1_ufig1.gif" ALT="Figure 1"> View larger version (67K): org.highwire.dtl.DTLVardef@1deee2eorg.highwire.dtl.DTLVardef@e71833org.highwire.dtl.DTLVardef@1e5c4f0org.highwire.dtl.DTLVardef@1e4832e_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2026

CXCL-CXCR2 signaling drives cancer-endothelium interactions in SCLC metastatic seeding

Small cell lung cancer (SCLC) is a highly metastatic malignancy with tropism to the liver, yet the signals that enable organ-specific metastatic colonization remain largely undefined. During metastasis, disseminated cancer cells first encounter endothelial cells (ECs) at the vascular-tissue interface, positioning cancer-endothelium crosstalk as a key determinant of metastatic success. Defining the signaling pathways underlying this reciprocal communication may uncover actionable vulnerabilities for preventing and treating this lethal disease. Here, we uncover an EC-derived CXCL chemokine program that activates cancer-intrinsic CXCR2-RAC1 signaling as a critical mediator of SCLC liver metastasis. By integrating in vitro and in vivo models, we show that SCLC cells induce robust CXCL chemokine expression from liver ECs, which in turn enhances SCLC migration and reinforces cancer cell-EC interactions. We applied highly quantitative metastatic colony barcode sequencing coupled with individual gene inactivation to demonstrate that CXCR2 is essential for SCLC migration and liver metastatic seeding. Mechanistically, CXCL-CXCR2 signaling activates RAC1-dependent F-actin assembling to drive SCLC motility during CXCL-induced metastatic seeding. Pharmacologic inhibition of CXCR2 or RAC1 suppresses SCLC migration and prevents SCLC liver metastasis. Together, our research defined a chemokine-driven signaling circuit that governs cancer-endothelium communication during the metastatic cascade and nominate the CXCL-CXCR2-RAC1 axis as a promising therapeutic vulnerability for preventing and treating metastatic SCLC.

cancer biology↗

bioRxiv2026

Betrayal is worse than loss during cooperation

Cooperative behavior is a cornerstone of human interaction. Although both "betrayal aversion" (the affective cost of being betrayed) and "loss aversion" (the financial detriment incurred from betrayal) are established determinants of cooperative behavior, their relative potency remains undetermined. Here, we investigated these effects by integrating computational modeling and event-related potential (ERP) techniques. In two tasks involving risk and cooperation, participants decided whether to take financial risks or to cooperate under possible betrayal. Our results showed that betrayal aversion had a stronger effect on reducing cooperation compared to loss aversion. Furthermore, ERP data demonstrated sequential processing: betrayal was encoded early in decision-making, reflected by increased P3 with weaker betrayal aversion, whereas loss aversion manifested later, marked by increased LPP. By dissociating the contributions of betrayal and loss, our finding provides novel insights into the cognitive and neural mechanisms underlying cooperative behavior.

neuroscience↗

bioRxiv2026

Quantitative dissection of the metastatic cascade at single colony resolution

Metastasis is the leading cause of cancer-related deaths. However, the core determinants and mechanistic principles underlying the metastatic cascade remain elusive. Small cell lung cancer (SCLC) is a highly aggressive malignancy with exceptional metastatic potential and limited therapeutic options. Here, we present Metastasis Originated Barcode Sequencing (MOBA-seq), a high-throughput in vivo platform that systematically maps genetic regulators across the metastatic cascade at single-colony resolution. MOBA-seq integrates scalable barcode-based lineage tracing with a computational pipeline that quantitatively deconvolutes genotype-specific effects on metastatic seeding, dormancy, and clonal expansion across hundreds of thousands of metastatic events. Applying this approach to more than 400 candidate regulators of SCLC, we uncovered tissue-specific metastatic suppressors and universal metastatic essential genes. We identified metastatic seeding as the predominant determinant of metastasis. Comparative analysis across recipient mice of distinct genetic backgrounds further revealed that innate immune surveillance constrains metastatic progression by reducing metastatic seeding and enforcing dormancy, with additional modulation by sex and tissue context. We validated the frequently mutated gene CREBBP as a key metastasis suppressor whose loss enhances SCLC metastasis through both tumor-intrinsic and immune-modulatory mechanisms. This work establishes a scalable and quantitative platform for mapping the metastatic fitness landscape at single-colony resolution across hundreds of thousands of in vivo data points. Our approach offers a broadly applicable framework for dissecting the interactions between cancer-intrinsic and microenvironmental factors governing tumor initiation, progression, and therapeutic response.

cancer biology↗

bioRxiv2026

MtDNA heteroplasmy controls tumor immune reprogramming through mitochondrial translation

Mitochondrial DNA (mtDNA) mutations are among the most frequent genetic alterations in human cancers, yet their molecular mechanisms in shaping tumor progression and metastasis under physiological conditions remain poorly understood. Here, we show that mtDNA heteroplasmy acts as a tumor cell-intrinsic rheostat that orchestrates fate decisions between progression and suppression. Moderate heteroplasmy induces a ribosomal storm of mitochondrial translation and ribosome biogenesis, driven by leucyl-tRNA synthetase 2 (LARS2). This response enhances metabolic fitness and licenses the secretion of S100A8/A9, enabling tumor cells to actively remodel the immune microenvironment through recruitment of myeloid-derived suppressor cells and exclusion of CD8 T cells, thereby promoting immune evasion and metastatic progression. In contrast, high heteroplasmy impairs tumorigenesis due to oxidative phosphorylation collapse. Disruption of LARS2, mitochondrial translation, or S100A9 signalling abrogates tumor progression. Our findings establish mtDNA heteroplasmy as a key regulator of cancer evolution, linking mitochondrial genetic variation to immune modulation, and reveal the LARS2-mitochondrial translation-S100A8/A9 axis as a therapeutically targetable programme within the pro-tumorigenic window of mtDNA heteroplasmy.

cancer biology↗

bioRxiv2026

Physics-Informed Neural Network for Mapping Vascular and Tissue Dynamics Using Laser Speckle Contrast Imaging

SignificanceQuantitatively mapping both cerebral blood flow and tissue dynamics from laser speckle contrast imaging (LSCI) is powerful for studying cerebral blood flow and neurovascular coupling, particularly in the context of stroke. Conventional multi-exposure fitting is slow and difficult to scale. Efficient, physically grounded methods are needed to extract both vascular and tissue dynamic biomarkers from LSCI data. AimTo develop and validate a physics-informed neural network (PINN) that quantitatively estimates fast (vascular) and slow (tissue-related) speckle decorrelation parameters directly from LSCI measurements without requiring ground-truth labels. ApproachWe developed a physics-informed neural network (PINN) to estimate fast (vascular) and slow (tissue-related) speckle decorrelation parameters directly from multi-exposure LSCI data without requiring ground-truth labels. The analytical LSCI model is embedded in the network loss function, enforcing consistency with speckle physics during training. The model operates in a self-supervised manner and performs pixel-wise inference across full-field images. The framework was evaluated using in vivo mouse stroke LSCI datasets. ResultsThe PINN accurately recovered fast decorrelation rates associated with cerebral blood flow and slower dynamics linked to tissue and cellular motion. The parameter maps closely match those from traditional nonlinear fitting, but at orders-of-magnitude higher speed, reducing analysis to under one second per image. It also generalizes to unseen subjects and remains robust under noise. ConclusionsOur approach establishes physics-informed learning as a practical framework for near real-time extraction of vascular and cellular biomarkers from LSCI, enabling longitudinal monitoring of stroke progression and potentially facilitating clinical translation.

bioengineering↗

bioRxiv2026

Oxaloacetate damages mitochondria by perturbing MIC60-dependent membrane remodeling

Mitochondria catabolize nutrients by generating sequentially-ordered organic acid intermediates that are oxidized through the tricarboxylic acid cycle. Pathogenic accumulation of metabolic organic acids manifests as devastating organic acidemias/acidurias and other severe diseases, but the underlying mechanisms are largely unknown. Using unbiased C. elegans genetic screening, we here reveal that mutations in the phosphoenolpyruvate carboxykinases PCK-1 and PCK-2 cause buildup of oxaloacetate, a key tricarboxylic acid cycle intermediate, leading to severe mitochondrial damage. Depletion of mitochondrial GOT-2.1 or GOT-2.2, which catalyze oxaloacetate conversion to aspartate, also causes oxaloacetate accumulation and defective mitochondria with disrupted cristae. We demonstrate that oxaloacetate binds the MICOS complex subunit CHCH-3/MIC19 and inhibits its function of promoting IMMT-1/MIC60-dependent membrane shaping and remodeling. In mammalian cells, aberrant OAA buildup similarly causes mitochondrial impairment through MIC19 and MIC60. These findings not only provide important mechanistic insights into mitochondrial damage in the context of defective oxaloacetate metabolism, but also suggest therapeutic strategies for oxaloacetate-related mitochondriopathies.

cell biology↗

bioRxiv2025

Mid-Infrared Photothermal Mesoscopy with Millimeter Field of View and Sub-micron Spatial Resolution

By optically sensing mid-infrared absorption through a visible probe beam, mid-infrared photothermal (MIP) microscopy has emerged as a powerful tool for chemical imaging with micromolar sensitivity and submicron spatial resolution. The adoption of spatially multiplexed camera-based widefield detection further enhanced the imaging speed. However, current widefield MIP systems suffer from a small field of view (FOV)--typically tens of square micrometers, which constrains their utility in large-area tissue imaging applications. Here, we report a laser-scan MIP mesoscope that achieves millimeter-scale FOV while preserving submicron resolution. By leveraging an all-reflective laser scanning architecture, low-magnification and medium numerical-aperture objectives, and a defocused signal collection scheme, our MIP mesoscope achieves a 1.2 x 1.2 mm2 FOV, 650 nm lateral resolution, and microsecond-scale pixel dwell time. In vivo chemical imaging of whole Caenorhabditis elegans and high-throughput detection of beta-amyloids in both mouse and human brain tissues associated with Alzheimers disease are demonstrated.

bioengineering↗

bioRxiv2025

Helicobacter pylori genome aggregation database reveals complex evolutionary forces shaping its genomic landscape and clinical impact in East Asia

We assembled HPgnomAD, a comprehensive global genome aggregation database of Helicobacter pylori (H. pylori) featuring 7,544 high-quality genomes from 278 populations, along with the first species-wide haplotype reference panel for genotype imputation. The panel provides high accuracy across diverse H. pylori populations, including those from low-coverage data, and is openly accessible with integrated analysis tools (https://www.hpgnomad.top/). Variant discovery revealed 1.82 million SNPs and 0.65 million InDels, with African strains exhibiting the most tremendous diversity and East Asian strains showing unexpectedly high novel variation. Fine-scale analysis of the hpEAsia lineage revealed six new sublineages shaped by altitude-, latitude-related divergence and region-specific admixture. Phylogenomic dating revealed two divergence waves in East Asia, paralleling Upper Paleolithic settlement and Neolithic human expansions, with highland-lowland separation at [~]18.8 kya, followed by the formation of complex geography-related population substructures. Genome-wide scans revealed adaptive loci related to metal acquisition, nitrogen metabolism, surface adhesion, and membrane transport, including altitude-associated highly differentiated variants linked to antibiotic resistance and gastric disease. By integrating genomic, evolutionary, environmental, and clinical data, HPgnomAD offers a framework for understanding H. pylori evolution, host-pathogen adaptation, and precision medicine worldwide.

evolutionary biology↗

bioRxiv2025

A 3D Human Neuron-on-Chip Platform to Monitor Neuronal Injury Responses

Traumatic brain injury (TBI) is a major cause of neurological dysfunction and long-term neurodegeneration, yet the intrinsic neuronal contributions to TBI pathophysiology remain incompletely defined. Here, we present a novel Neuron-on-Chip microfluidic platform that can be used to mechanically injure mature human prefrontal cortex neurons (hPFCs) embedded in three-dimensional (3D) hydrogels, enabling the study of injury responses in pure neuronal cultures. We assessed real-time calcium dynamics across 13 metrics of single-cell and network activity, revealing a biphasic injury response: an early phase (0.5-24 hr) characterized by excitotoxicity, hyper-synchronized bursting, and network collapse; and a late phase (8 d) marked by sustained depolarization and structural remodeling. Secretome profiling uncovered progressive elevations in extracellular pT181 and total Tau from days 1 to 5 post-injury. Cytokine analyses identified early (24 hr) elevations in IP-10, IL-10, IFN2, and NCAM, and late increases (8 d) in CXCL9 and MPO, linking neuronal activity changes to stage-specific inflammatory signaling. Immunocytochemistry and immunoblotting confirmed temporally ordered upregulation of calpain-1 and active caspase-3 (days 1-3), phosphorylated Tau (AT8+, days 5-8), and neurofibrillary tangle-like Tau aggregates (NFT+, day 8). These findings establish our platform as a scalable microphysiological model for probing the dynamic cellular and molecular sequelae of neuronal response to injury, offering insights into neurodegeneration and opportunities for therapeutic discovery.

neuroscience↗