Biology subjects

Sato, S.

Publications and source records attributed to Sato, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Information coding strategies in biological reservoir computing for multiclass time-series classification

Physical reservoir computing (RC) using biological neural networks (BNNs) offers a framework for probing how high-dimensional dynamics arising from multicellular systems support complex information processing in the brain. However, how electrical inputs and extracellular readouts should be designed to suit different task demands remains unclear. Here, using primary rat cortical neurons cultured on a high-density microelectrode array, we investigated how input encoding and spike detection methods influence neural representations and the resulting RC performance in BNNs. Comparison of pulse amplitude modulation and latency coding revealed that the latter exhibited superior performance in demanding multiclass conditions, including a 10% improvement in a 10-class spoken digit classification task. Spike sorting further improved classification performance by enhancing class separability, while largely preserving the low-dimensional structure of population activity. These findings highlight the importance of designing information coding strategies according to task difficulty.

neuroscience↗

bioRxiv2026

Highly plastic macrophage niches orchestrate acquired quiescence and reactivation in breast-cancer bone metastasis

Recurrence and metastasis remain major causes of cancer mortality, sustained by therapy-resistant micrometastatic cells. Bone is a frequent site of breast-cancer relapse, yet the cues that reawaken disseminated cells remain poorly defined. We identify a previously unrecognized, highly plastic CXCL16 macrophage population that integrates tumor-associated macrophage programs found in distant metastatic sites such as lung and brain with non-tumor disease-associated traits in bone marrow. These CXCL16 macrophages establish a transient niche that restrains disseminated cancer-cell proliferation. Single-cell transcriptomics delineate functional remodeling of myeloid niches within the bone metastatic microenvironment: a CXCL16 macrophage niche that transiently constrains metastatic growth, and G-CSF macrophage and neutrophil niches that reignite tumor outgrowth. In primary tumors, cancer-associated fibroblasts (CAFs) aberrantly secrete G-CSF in response to cancer-cell signals, expanding G-CSF-receptor-positive subset of cancer cells with high metastatic potential. In advanced human bone metastases, CXCL16 macrophages localize to CAF-rich stroma but are excluded from cancer-cell clusters, indicating immune evasion. Together, these findings uncover CAF-bone-marrow cross-talk as a therapeutic target linking stromal inflammation, immune remodeling, and metastatic progression.

cancer biology↗

bioRxiv2026

Core genome MLST reveals genetic and BafA-associated phenotypic diversities in Bartonella henselae strains

Bartonella henselae is a zoonotic pathogen associated with cat-scratch disease. Although multilocus sequence typing (MLST) has been used for strain classification, its resolution for distinguishing between B. henselae isolates remains limited. We herein developed a B. henselae-specific core genome MLST (cgMLST) scheme based on whole-genome sequencing data and examined the genetic and phenotypic diversities of 80 strains derived from cats, humans, mongooses, and masked palm civets. Using the conventional MLST scheme, the 80 strains were classified into nine sequence types (STs), while cgMLST subdivided them into 72 cgSTs, demonstrating a marked improvement in discriminatory power. The cgMLST scheme comprised 1,183 core genes and showed high applicability across the 80 strains. A phylogenetic analysis revealed that ST1, which has been associated with cat-scratch disease, was further subdivided into three major clusters and two singletons, indicating high genetic heterogeneity within this ST. We also found that the bafA subtypes clustered in a manner that was largely consistent with the cgMLST-based phylogenetic structure, suggesting a close relationship between bafA variations and the genomic background of B. henselae strains. In a human umbilical vein endothelial cell proliferation assay, strains belonging to distinct cgSTs exhibited strain-dependent differences in proliferative capacity, which were associated with the bafA subtype classification. Some strains induced focal cell fragmentation and a reduced cell density at a high multiplicity of infection, indicating strain-dependent differences in endothelial cell injury. Collectively, the present results establish a high-resolution cgMLST framework for B. henselae and demonstrate that genetically distinct strains have diverse endothelial cell phenotypes.

microbiology↗

bioRxiv2026

Genome compartments guide protamine replacement and genome stability during spermiogenesis

Compartment-scale genome organisation persists in mammalian sperm, yet how histone-protamine replacement is orchestrated in space and time during spermiogenesis remains unclear. Here we combine stage-resolved purification of mouse spermatids with spike-in-normalised ATAC-seq and PRM1 CUT&Tag to map chromatin accessibility and protamine incorporation across spermiogenesis. We uncover a transient, genome-wide hyper-accessible phase coincident with replacement that is uncoupled from transcription and suppressed in catalytic PHF7-mutant spermatids. PRM1 loading initiates within accessible A-compartment chromatin and later spreads across both A- and B-compartments, whereas protamine-null mice demonstrated that PRM1/ PRM2 deficiency selectively destabilises A-compartment closure. Sequencing of short DNA fragments from Prm1/Prm2 dosage-reduced epididymal sperm reveals early enrichment of breakage at protamine-targeted A-compartment regions, which dissipates as fragmentation becomes genome-wide during epididymal transit. Together, our data place histone-protamine replacement within a compartment-centred framework that links 3D genome domains to the timing, targeting and integrity of the sperm genome.

genomics↗

bioRxiv2026

Oribatid Mites Supply Tetrodotoxin to Poisonous Newts

Tetrodotoxin (TTX) is a potent neurotoxin widely distributed among marine and terrestrial animals, yet how terrestrial vertebrates acquire this toxin has been debated for decades. Here, we identify oribatid mites as the primary dietary sources of TTX for the Japanese fire-bellied newt, Cynops pyrrhogaster. We detect TTX and its analogs in the mites Scheloribates processus and Galumna sp. KM1, which are preferentially consumed by terrestrial newts. In a controlled toxification experiment, juvenile newts accumulated TTX after consuming TTX-bearing mites, directly demonstrating dietary sequestration. Our results demonstrate that the early terrestrial stage is critical for lifelong TTX acquisition in newts. Notably, we also detect pumiliotoxin, a poison-frog alkaloid, in S. processus, suggesting that newts and poison frogs have convergently evolved to exploit toxin-bearing microarthropods for chemical defense. We propose a "terrestrial toxic web" hypothesis in which oribatid mites act as a shared environmental reservoir linking putative microbial toxin production to vertebrate chemical defense, highlighting microarthropods as key mediators in terrestrial toxin flow.

ecology↗

bioRxiv2026

Predictive E-prop: A biologically inspired approach to train predictive coding-based recurrent spiking neural networks

The predictive coding framework offers a compelling model for temporal signal processing in the cortex. Recent studies explored its implementation in spiking architectures using Hebbian plasticity rules or offline learning; however, a biologically inspired model that enables gradient-based minimization of prediction errors remains an open challenge. In this work, we demonstrate that the predictive coding objective can be optimized using the online and local nature of the e-prop learning algorithm in recurrent spiking neural networks, creating the Predictive E-prop model. We demonstrate that the model is capable of learning complex time-series signals purely from self-supervised learning, using only its own prediction error as input, maintaining self-sustaining activity and reproducing the targets underlying dynamics even in the absence of external stimuli. Furthermore, Predictive E-prop shows robust signal reconstruction abilities, effectively filtering noise and successfully interpolating sparse data. A comparative study against a backpropagation-based approach reveals that the two achieve comparable performance after training, confirming the viability of our model for timeseries generation tasks. These findings are particularly relevant for future developments in neuromorphic hardware, offering a purely self-supervised, gradient-based model that could provide significant advantages in power efficiency and computational ability.

neuroscience↗

bioRxiv2026

The REFLEX system enables in vivo identification of perivascular angiogenic macrophages in the heart

Direct identification of physically interacting cells in vivo remains challenging because conventional interactome analyses infer signaling partners from transcriptomes and cannot reveal which cells are in direct contact. In pressure-overload induced cardiac remodeling, VEGF-A plays a central role in the maintenance of vascular integrity and cardiac function. However, the cell type which produces VEGF-A and how the VEGF-A peptide is delivered to vascular endothelial cells remains unclear. Here, we developed a genetically encoded platform that combines REFLEX mice with HUNTERuni-seq, enabling unbiased detection and transcriptional profiling of the cells that physically interact with vascular endothelial cells. The REFLEX and HUNTERuni-seq approach identified subpopulations of Vegfa positive macrophages which we named perivascular angiogenic macrophages (PVAMs). Although the amount of VEGF-A in PVAMs is small, loss of VEGF-A in PVAMs impaired angiogenesis and systolic function during pressure overload. We additionally show that direct contact between PVAMs and endothelial cells is critical for the delivery of VEGF-A to endothelial cells. Conventional interactome analysis predicted that cardiomyocytes as dominant sources of VEGF-A in the heart. However, cardiomyocyte Vegfa deletion had no effect on capillary density nor systolic function in a model of heart failure. These results suggest that VEGF-A signaling does not rely on free diffusion through the interstitium and that cellular proximity and physical contact between PVAMs and endothelial cells are the key determinants of effective signal delivery. Together, these findings establish REFLEX and HUNTERuni-seq as a versatile platform for uncovering biologically critical cell-to-cell interactions and provide new insight into intercellular communication in pathological tissue contexts.

cell biology↗

bioRxiv2026

A Dual-Pathway Prediction Error Model of Schizophrenia Spectrum Disorders:Bridging NMDA Hypofunction and Dopaminergic Hyperfunction

1.Schizophrenia spectrum disorders (SSDs) present a profound clinical enigma, manifesting as a heterogeneous continuum ranging from the chaotic volatility of acute psychosis to the impenetrable rigidity of systematized delusions. While neurobiological research has independently implicated NMDA receptor hypofunction or dopaminergic hyperfunction as cardinal pathophysiological distinct mechanisms, a computational framework capable of bridging these distinct cellular deficits to the spectrums vast phenomenological diversity remains elusive. Here, we propose a biologically plausible neural model using a dynamic Bayesian inference with separable positive and negative prediction-error pathways. We demonstrate that NMDA hypofunction selectively blunts negative prediction errors, fostering rigid, bias-dominated beliefs, while dopaminergic hyperfunction uniformly amplifies error signals, driving volatile, observation-dominated states. Their interaction reconstructs SSDs as a continuous bias-volatility spectrum, accounting for key neurophysiological markers and offering a theoretical foundation for mechanism-based patient stratification.

neuroscience↗

bioRxiv2026

Molecular Crowding-Driven Nucleosome Interactions Revealed Through Single-Molecule Optical Tweezers

Molecular crowding causes the compaction of chromatin fibers, contributing to the formation of the nuclear architecture. However, the molecular mechanism of compaction under crowded conditions is not yet fully understood. In this study, we employed the single-molecule optical tweezer method to investigate the effect of molecular crowding on chromatin structure. Force-extension experiments on a 12-mer polynucleosome in the presence of different sizes and concentrations of polyethylene glycol (PEG) as a crowding agent showed that at low concentrations of low-molecular-weight (MW) PEG, the compaction of the polynucleosome was not significant. In this respect, nucleosomes predominantly remained separated, while DNA-histone interactions within individual nucleosomes were slightly stabilized. In contrast, high concentrations of high-MW PEG significantly promote internucleosomal interactions, leading to highly compact polynucleosome conformations. Under these conditions, approximately 30 pN of force was required to disrupt the internucleosomal interactions and release DNA; this force was 36% higher than that required for DNA unwrapping in the absence of PEG. These findings suggest that molecular crowding impacts cellular processes by mechanically regulating chromatin accessibility for regulatory proteins and the passage of motor molecules such as RNA polymerase. Significance StatementChromatin condensation is closely related to biological processes such as transcription and replication. Molecular crowding has recently attracted attention as a factor regulating chromatin condensation. In this study, we used the optical tweezer method to analyze the molecular mechanisms underlying chromatin condensation. We found that high-molecular weight and high-concentration crowders (polyethylene glycol) induced significant compaction, which involved internucleosomal interactions that markedly reduced DNA accessibility. Our results suggest that molecular crowding not only alters the condensation state, but also mechanically regulates chromatin accessibility.

biophysics↗

bioRxiv2026

Small Extracellular Vesicle Cargoes Associated with Lymph Node Metastasis in Head and Neck Cancer

Head and neck squamous cell carcinoma (HNSCC) is a highly aggressive malignancy in which cervical lymph node metastasis critically determines patient prognosis. Despite advances in clinical staging based on tumor size, depth of invasion, and nodal status, these parameters fail to capture the biological heterogeneity of HNSCC, leading to overtreatment or undertreatment, and significant morbidity. Emerging evidence implicates small extracellular vesicles (SEVs) as key mediators of tumor progression and promising biomarkers for metastatic potential. In this study, we performed iTRAQ-based proteomic profiling of SEVs from metastatic (MOC2) and nonmetastatic (MOC1) HNSCC mouse cell lines and identified multiple cargoes associated with metastatic processes, including angiogenesis, extracellular matrix remodeling, immune modulation, and perineural invasion. Further, we employed an immune-competent orthotopic mouse oral carcinoma (MOC) model to investigate how exosome biogenesis affects HNSCC metastasis. Loss of the exosome/SEV biogenesis protein HRS in MOC2 HNSCC cells impaired SEV formation in vitro and tumor growth and metastasis in vivo. Consistent with the SEV cargoes enriched in MOC2 EVs, immunohistochemical analyses of MOC2 tumors revealed reduced blood vessel and nerve density in HRS-deficient tumors. Analysis of candidate biomarker SEV cargoes in the circulating EVs from HPV-negative HNSCC patients revealed significant correlations of these proteins with metastatic status. Collectively, these findings identify SEV cargoes as potential functional mediators of metastasis and liquid biopsy biomarkers in HNSCC.

cancer biology↗

bioRxiv2025

Genetic diversity in horseshoe bat ACE2 and sarbecovirus spike proteins mutually shape one another

Angiotensin-converting enzyme 2 (ACE2) serves as the entry receptor for a wide diversity of sarbecoviruses naturally harboured by horseshoe bats (genus Rhinolophus). Despite the extensive circulation of these viruses in many horseshoe bat species, the potential interactions between virus and receptor evolution remain poorly understood. We sampled individuals of the intermediate horseshoe bat (Rhinolophus affinis) across Vietnam and identified 15 genotypes of ACE2 proteins, 10 of which are previously unreported. Phylogenetic analysis and infectivity assays with a panel of 36 sarbecovirus spike proteins indicated that the R. affinis ACE2 phylogeny has geographic structuring and genotypes originating from different geographic regions exhibit distinct infectivity phenotypes. We detected site-specific positive selection on ACE2 site 24 with the associated substitutions largely affecting the receptors sarbecovirus infectivity profile. Together, our findings suggest that the R. affinis within-species ACE2 diversity has likely been shaped through selection by past sarbecovirus infection. Similarly on the virus end, we use mutagenesis assays and structural analysis through cryo-EM, to delineate the proximal evolution of the Ra22QT77 spike defined by specialization to the ACE2 genotypes of horseshoe bats found in and near southern Vietnam, where the virus was sampled. Our findings contribute to a better understanding of host-sarbecovirus co-evolution dynamics and provide valuable insights into the receptor usage determinants of these viruses. HighlightsO_LIWe identify a total of 15 ACE2 genotypes in R. affinis bats from Vietnam. C_LIO_LIACE2 intraspecific polymorphism is geographically separated and associated with distinct sarbecovirus infectivity. C_LIO_LISite 24 of R. affinis ACE2 experiences positive selection and controls susceptibility to sarbecoviruses. C_LIO_LIBat ACE2s and sarbecovirus spikes are bidirectionally shaped by each others evolution. C_LI

microbiology↗

bioRxiv2025

Reliable Detection of SGLT2 Protein through Knockout-based Antibody Characterization and Optimized Procedures

IntroductionSodium-glucose cotransporter 2 (SGLT2) is a key mediator of renal glucose reabsorption. Its pharmacological inhibition exerts cardio- and reno-protective benefits. Despite widespread clinical interest, reliable detection of SGLT2 protein remains challenging due to concerns regarding the specificity of available antibodies. MethodsThis study assessed the specificity of eight commercially available anti-SGLT2 antibodies by immunohistochemistry and Western blotting. Genetically engineered Sglt2-deficient mice and rats, generated via clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) technology, were employed as definitive negative controls. Additionally, human kidney tissues, including renal cell carcinoma samples, were analyzed. ResultsAmong the antibodies tested, few exhibited robust specificity, characterized by substantial immunostaining with minimal background in wild-type kidney tissues and complete absence of staining in Sglt2-deficient samples. In renal cell carcinoma samples, a validated antibody detected SGLT2 immunostaining in proximal tubules of non-tumor regions but not in tumor areas. Subcellular localization studies revealed that SGLT2 was enriched within proximal tubular microvilli, partially overlapping with its co-factor PDZK1IP1 (MAP17). LRP2 (megalin) and NHE3 were placed at the microvillar base and did not colocalize with SGLT2. Western blotting identified a specific SGLT2 band at approximately 55 kDa in kidney lysates using several antibodies under optimized procedures. This band was shifted to approximately 45 kDa after enzymatic removal of N-linked glycans. One antibody detected a weak band at the same molecular mass even in kidney lysates from Sglt2-deficient rodents. ConclusionsConsiderable variability exists in the specificity of commercially available anti-SGLT2 antibodies. Only a limited number of antibodies are suitable for reliable detection of SGLT2 in rodent and human samples. Rigorous antibody characterization, including the use of knockout controls and optimized experimental conditions, is essential to ensure reproducibility and prevent misinterpretation in studies investigating the biological and pathophysiological roles of SGLT2.

molecular biology↗

bioRxiv2025

Locations of consecutive G·C base-pairs direct genomic nucleosome positioning

The nucleosome is a structural and functional subunit of chromatin, and its positioning and dynamics in the eukaryotic genomes serves as a key platform for gene regulation. Here, we determine the positions of fully wrapped nucleosomes across the yeast genome by chemical mapping through the histone H2A-A122C residue, which cleaves near the DNA entry/exit sites. This approach reveals the most refined sequence-dependent profile of nucleosomes reported to date. Comparison of H2A-A122C with the H3-Q85C and H4-S47C methods clearly shows a sequence preference for the chemical cleavage site, and mapping results suggest that the nucleosome locations are dynamic in vivo. More importantly, we find that the depletion of CC and GG dinucleotides at nucleotide positions -11 to -9 and +9 to +11 bp, respectively, from the nucleosome dyad position (0) is inextricably associated with the enrichment of AA/AT/TA/TT dinucleotides in both yeast and mouse genomes. Introducing consecutive C*G base pairs to the corresponding sites in the 601 sequence shifts the nucleosomes to less frequent positions without altering thermal stability, implying a structural constraint imposed by DNA sequence. Thus, CC and GG dinucleotides in the major groove blocks at superhelix locations (SHL) -1.0 and +1.0, respectively, destabilize histone-DNA interactions, serving as intrinsic determinants of nucleosome positioning in eukaryotic genomes.

molecular biology↗

bioRxiv2025

Online supervised learning of temporal patterns in biological neural networks under feedback control

In vitro biological neural networks (BNNs) provide a well-defined model system to constructively investigate how living cells interact with their environment to shape high-dimensional dynamics that could be used to generate a coherent temporal output, such as those required for motor control. Here, we developed a real-time closed-loop BNN system capable of generating periodic and chaotic temporal signals by integrating cultured cortical neurons with microfluidic devices and high-density microelectrode arrays. We show that training a simple linear decoder with fixed feedback weights enables the system to learn and autonomously generate diverse temporal patterns. When feedback was switched on, irregular activity in BNNs is transformed into low-dimensional, structured dynamics, producing coherent trajectories characterized by stable transitions between neural states. BNNs trained on different target frequencies--ranging from 4 to 30 s--could be trained to sustain oscillations at distinct frequencies, demonstrating their adaptability. Importantly, a top-down control of self-organized network formation with microfluidic devices is the key to suppress excessive synchronization and increase dynamical complexity in BNNs, facilitating the training and robust output generation. This work offers a biologically inspired platform for understanding the physical basis of cortical computation and for advancing energy-efficient neuromorphic computation. Significance StatementReservoir computing is a machine learning paradigm that exploits the transient dynamics of high-dimensional nonlinear systems. Although it was originally inspired by the mammalian brain and widely explored in physical systems, its implementations in biological neural networks (BNNs) have been limited due to their excessive connectivity and global synchrony in vitro. Here, we use microfluidic devices to construct modular, nonrandomly connected BNNs and integrate them with microelectrode arrays in a closed-loop reservoir computing environment. We show that the system can be trained to autonomously output various temporal signals, with the modular connectivity that is essential for learning. In vitro BNNs provide unique alternatives for physical reservoirs with dynamic adaptability.

neuroscience↗

bioRxiv2025

Cyclophilin A-mediated cis/trans isomerization modulates RIN4 to control intracellular rhizobial infection in legumes

In most legume-rhizobium symbioses, rhizobial colonization occurs through host-derived intracellular infection threads, which enable recruitment of compatible rhizobia while presumably modulating the host immune system to prevent rejection. To investigate how legumes regulate immune responses through post-translational mechanisms during the infection, we focused on Cyclophilin A (CyPA), a peptidyl-prolyl cis/trans isomerase. The model legume Lotus japonicus encodes three canonical CyPA genes. Among them, LjCyPA1 was characterized through CRISPR/Cas9-mediated knockout analysis and shown to be important for normal intracellular infection of compatible rhizobia. A gain-of-function LjCyPA1 variant in a soybean cultivar was able to promote symbiosis with not only compatible but also incompatible rhizobia. Structural modeling followed by genetic analysis demonstrated a functional interaction between LjCyPA1 and the immune hub protein LjRIN4. The cis conformation of LjRIN4 promoted intracellular rhizobial infection, while the trans conformation suppressed it. LjCyPA1 acted with the rhizobial type III secretion system (T3SS) which exhibited a cooperative role between host and symbiont in facilitating infection. Phylogenomic analysis showed that conservation of the CyPA1 orthologue is correlated with the trait of intracellular infection in legumes. Our results contribute to the understanding of how legumes accept symbiotic partners while balancing immune responses.

plant biology↗

bioRxiv2025

Functional redundancy between UTY and UTX in regulating the localization of transcription factors involved in pluripotency

The Y chromosome harbors few protein-coding genes, and their roles in early human development remain largely unclear. Here, we demonstrate that UTY, a Y-linked homolog of the histone demethylase UTX, plays a critical, demethylase-independent role in maintaining pluripotency in human embryonic stem cells (hESCs). Despite its low expression and weak enzymatic activity, UTY co-occupies active cis-regulatory elements with UTX and promotes the transcription of key pluripotency genes, including NODAL and LEFTY. Integrated genomic analyses of single and double knockout hESCs reveal that UTY and UTX function redundantly to maintain chromatin accessibility and ensure proper recruitment of core transcription factors such as OCT4 and SOX2. The combined loss of UTY and UTX disrupts transcription factor localization, induces widespread gene expression changes, and leads to a collapse of the pluripotent state, without detectable changes in H3K27 methylation. Instead, these defects are associated with impaired recruitment of ATP-dependent chromatin remodelers and reduced histone acetylation, suggesting a demethylase-independent mechanism. Our findings uncover an essential role for the evolutionarily conserved UTY in safeguarding enhancer function and transcription factor occupancy, highlighting Y-linked regulatory mechanisms that are critical for maintaining human pluripotency. Summary statementThis study reveals how UTX and UTY cooperate to maintain stable gene regulation in human stem cells and guide proper developmental programs.

developmental biology↗

bioRxiv2025

Efficient learning and intrinsic noise filtering in recurrent spiking neural networks trained with e-prop

ObjectiveBiologically plausible learning rules for neural networks, such as e-prop (eligibility propagation), are essential both for advancing neuromorphic computing and for understanding fundamental mechanisms of learning in animal brains. However, their behavior under different network conditions remains unclear. ApproachHere, we investigate the performance of the e-prop learning algorithm in recurrent spiking neural networks (RSNNs) across different levels of recurrent connectivity and input noise using a complex temporal credit assignment task, a supervised classification problem known to be solvable by rodents. Main resultsWe show that increased sparsity in the recurrent layer significantly enhances learning performance by promoting the generation of more diverse activation patterns. Analysis of the networks evolution further reveals that the e-prop-trained input layer evolves to route distinct inputs to different regions of the recurrent layer while suppressing the contribution of noise. This partially resembles signal routing functions attributed to the thalamus in mammalian sensory systems, providing additional support for the biological plausibility of e-prop. SignificanceThese findings offer promising insights for efficiency and advantages of biologically inspired training in RSNNs.

neuroscience↗

bioRxiv2025

Microfluidic platforms for probing spontaneous functional recovery in hierarchically modular neuronal networks

Inherent capacity to flexibly reorganize after injury is a hallmark of brain networks, and recent studies suggest that functional consequences of focal damage are strongly influenced by the networks non-random connectivity. Although many of these insights have been derived from animal models and computational simulations, experimental platforms that enable bottom-up investigations of the structure-function relationships underlying damage and recovery processes remain limited. In this study, we used polydimethylsiloxane microfluidic devices to construct hierarchically modular neuronal networks that mimic the architectural features of the mammalian cortex. Laser microdissection was employed to selectively sever intermodular connections, enabling controlled damage to either hub or peripheral connections. Damage to hub connections led to delayed recovery, requiring more than three days for correlations to re-emerge. In contrast, peripheral damage resulted in faster recovery. Experiments that induced repeated injury to neuronal networks further demonstrated that recovery primarily occurred through the formation of alternative pathways rather than restoration of the original connections. These findings highlight how topological features of neuronal networks shape their response to injury and subsequent reorganization, providing mechanistic insights into the intrinsic self-repair capacity of biological systems.

neuroscience↗