Biology subjects

Shan, X.

Publications and source records attributed to Shan, X..

At least 19 recordsLinked to original sources

bioRxiv2026

Biosynthetic additive manufacturing through mycelium-bacteria consortia

Lignocellulosic biomass is the most abundant renewable raw material on Earth, yet its structural and carbon-storage potential remains unrealized: microbial decomposition returns stored carbon to the atmosphere before it can be harnessed as a durable material. Distinct microbial processes, such as biosynthesis and biomineralization, offer a natural counterpoint, converting organic carbon into mechanically robust, persistent materials such as polymers and minerals. Here, we establish a biosynthetic additive manufacturing strategy through mycelium-bacteria consortia, by coupling fungal self-assembly with bacterial biomineralization inside fabricated three-dimensional scaffolds derived from lignocellulosic biomass. Trametes versicolor forms a continuous living mycelial network that serves as both a structural template and a transport pathway, guiding the spatial colonization of Sporosarcina pasteurii and enabling volumetric calcium carbonate deposition throughout the scaffold interior, overcoming the surface-limited mineralization of conventional microbial systems. Integration with helicoidal Bouligand architectures translates microscale mineral reinforcement into macroscale performance, increasing compressive Young's modulus by 7-14-fold and ultimate strength by 5-fold relative to unmineralized conventional mycelium-based living composites. The living mycelial network also enables autonomous self-healing and modular self-assembly through hyphal bridging without external adhesives or energy input. This work establishes a scalable route for converting and upcycling transient biomass carbon into durable living structural materials for sustainable construction.

bioengineering↗

bioRxiv2026

Valine Engages a Prefrontal mGluR5 Allosteric Site to Preserve Social Behavior

Branched-chain amino acid metabolism is linked to neurodevelopmental disorders, but whether a defined amino acid directly modulates cortical receptor signaling to control behavior is unknown. Here, we show that valine is uniquely required for sociability through medial prefrontal cortex (mPFC) circuitry. Partial dietary valine restriction, but not comparable leucine or isoleucine restriction, or mPFC-restricted acceleration of BCAA catabolism through Bckdk loss, disrupts social interaction, and local valine supplementation rescues behavior. LiP-SMap, surface plasmon resonance, cryo-EM, and mutagenesis identify metabotropic glutamate receptor 5 (mGluR5) as a direct valine target and reveal a valine-selective allosteric pocket distinct from the glutamate site. Valine is signaling-biased: it drives {beta}-arrestin-linked output yet has little standalone Gq efficacy, instead potentiating glutamate-evoked mGluR5 signaling to recruit endocannabinoid/CB1 feedback, gate inhibitory transmission, and preserve mPFC-dependent social behavior. Together, these findings identify valine as a diet-derived allosteric ligand that links amino acid availability to cortical circuit control of social behavior.

neuroscience↗

bioRxiv2026

YGEP: An Integrated Web Platform for Genomic Evaluation and Intelligent Breeding in Yak

Background: The yak (Bos grunniens) is an essential livestock species in high-altitude alpine ecosystems, serving key roles in meat, milk, and wool production as well as ecological maintenance. However, traditional yak breeding systems face several limitations, including fragmented herd data management, inefficient phenotypic collection, missing pedigree records, and high technical barriers to applying genomic technologies. These factors constrain the widespread application of modern genetic evaluation methods in yak breeding programs. Description: We developed the Yak Genomic Evaluation Platform (YGEP, https://yakbreeding.swun.edu.cn/en/), an integrated digital system for yak genetic selection and herd management. YGEP integrates three core analytical modules: pedigree reconstruction, genotype imputation and genomic breeding value estimation. Benchmarking on 706 yaks showed that GBLUP achieved a prediction accuracy of r = 0.96 for cannon bone circumference (CCB), and KBeagle reached 84.0% imputation accuracy with the combined reference panel. Conclusion: YGEP bridges the gap between advanced genomic analytics and practical yak breeding. By integrating pedigree reconstruction, genotype imputation, and GEBV estimation into a user-friendly cloud platform, YGEP effectively eliminates technical and data bottlenecks. Overall, it provides an accessible, scalable, and standardized solution to advance digital herd management and precision genetic improvement in alpine livestock.

bioinformatics↗

bioRxiv2026

A scalable human neuron model of Alzheimer's disease relevant tauopathy reveals mechanisms linking Tau fibrillization to synaptic dysfunction

Tauopathies, including Alzheimer's disease, are driven by pathological aggregation of hyperphosphorylated Tau, which disrupts synaptic integrity, impairs neuronal communication, and contributes to cognitive decline. To dissect tauopathy pathogenesis and enable therapeutic discovery, reliable and scalable human iPSC-neuron models are essential. Here, we developed two complementary iPSC-derived neuron models: an endogenous Tau seeding model, in which neurons are challenged with pre-formed Tau fragments that form paired helical filament (PHF)-consistent structures, and a Tau-0N3R overexpression seeding model to accelerate pathology. Both models recapitulate hallmark features of tauopathy, including the progressive formation of intracellular, hyperphosphorylated, sarkosyl-insoluble, and conformationally altered Tau aggregates (AT8, MC1 positive), along with synaptic and neuronal dysfunction. Cryogenic electron tomography (cryo-ET) further revealed the morphology of Tau fibrils within cells, as well as the ultrastructure of Tau fibrils trapping synaptic vesicles in situ. Using this platform, we performed integrated phosphoproteomics, high-content screening, and functional validation to identify key pathways driving Tau aggregation. MARK2-mediated phosphorylation within Tau's microtubule-binding domain emerged as an early trigger of aggregation, confirmed by site-specific mutagenesis. In parallel, small molecules targeting the PI3K/mTOR/GSK3 pathway reduced aggregation and restored synaptic function, with GSK3 inhibition lowering phosphorylation at critical aggregation-driving sites on Tau. Together, these findings establish a physiologically relevant, scalable platform for therapeutic screening that connects Tau seed uptake, site-specific phosphorylation, fibril formation, and synaptic disruption, ultimately identifying mechanistically separable intervention points along the aggregation cascade.

cell biology↗

bioRxiv2026

Integrated morphological, multi-omics, and functional profiling reveals microglial plasticity driven by AD risk genes

Microglia, the resident macrophages of the central nervous system, are highly dynamic cells essential for brain homeostasis. While genome-wide association studies (GWAS) strongly implicate microglial dysfunction in Alzheimer's disease (AD), the mechanistic links coordinating their diverse transcriptional, morphological, and functional states remain poorly understood. Using human induced pluripotent stem cell-derived microglia (iMicroglia) and single-cell RNA sequencing, we identified six distinct transcriptional profiles and mapped them to specific morphological phenotypes via targeted immunofluorescence, establishing a link between microglial morphology and molecular identity. Transcriptomic and morphological profiling further demonstrated profound microglial plasticity, revealing distinct, stimulus-specific responses to AD-relevant pathologies, including Tau PFF, amyloid-beta, and apoptotic neurons. To assess how AD risk variants perturb these states, we performed high-efficiency CRISPR-Cas9 ribonucleoprotein (RNP) knockouts of specific AD GWAS genes. Bulk RNA-seq profiling revealed extensive transcriptional remodeling following genetic perturbation. Crucially, we show that depletion of these AD risk genes disrupts baseline morpho-transcriptomic coupling and fundamentally alters microglial phagocytic capacity. Together, this study reveals how AD GWAS genes may drive microglia into dysfunctional states characterized by altered morphology, distinct multi-omic signatures, and impaired functions.

neuroscience↗

bioRxiv2026

Rational antigen engineering and mucosal delivery design for next-generation RSV vaccines

Respiratory syncytial virus (RSV) prefusion F (preF) vaccines have transformed adult prophylaxis, yet unmet needs in antigen stability, pediatric safety, and mucosal protection persist. Here, we develop an integrated structure-guided RSV vaccine design platform that couples allosteric stabilization, epitope-focused immunogen engineering, and route-specific mRNA delivery for systemic and mucosal immune activations. By mapping prefusion F "breathing" motions and applying a ThermoNet-and Rosetta-guided screening funnel, we identified R296, a stabilized prefusion F immunogen that reinforces the 1-5 hinge and interprotomer interfaces while preserving key neutralizing epitopes. Cryo-EM confirmed that R296 retains a native-like prefusion architecture. And mRNA-LNP vaccination elicited potent, durable, and broadly protective neutralizing responses in mice, rats, and cotton rats, with clearance of detectable infectious virus and no evidence of Th2-skewed enhanced respiratory disease. To address pediatric safety, we designed a stalkless nanoparticle immunogen, Head38-50AB-3, which enriches high-potency apical epitopes while excluding stalk regions associated with low-potency or non-protective responses, conferring protection without VAERD-like pathology. Finally, we engineered an intranasal-delivered LNP that enables intranasal R296 mRNA delivery, inducing systemic neutralization together with robust nasal and bronchoalveolar secretory IgA (sIgA). R296 has now advanced to Phase 1 clinical trials. These results establish a modular framework for next-generation RSV vaccines.

microbiology↗

bioRxiv2026

Spatial co-expression and cell-cell communication inference from spatially resolved transcriptomics with CONCISE

Cell-cell communication is fundamental to tissue organization, homeostasis, and disease progression. Recent advances in spatial transcriptomics provide unprecedented opportunities to systematically characterize ligand-receptor interactions directly within intact tissues. However, robust inference of spatial ligand-receptor interactions remains challenging because intrinsic features of spatial transcriptomics data, including spatial autocorrelation, variation in total molecular counts, and measurement errors, can induce spurious spatial co-expression and lead to inflated false-positive results. Most existing methods do not adequately account for these confounding factors, limiting the reliability of inferred cellular communication. Here, we present CONCISE, a statistical method for spatially constrained co-expression and ligand-receptor interaction inference that jointly models spatial autocorrelation, variation in total molecular counts, measurement errors, and spatial proximity constraints. CONCISE combines efficient moment-based parameter estimation with analytical hypothesis testing, enabling fast and statistically rigorous inference without restrictive distributional assumptions. Through extensive simulations, real-data permutation experiments, and biologically motivated negative-control analyses across different spatial transcriptomics platforms, we show that most existing methods presented inflated false-positive rates, whereas CONCISE achieved well-calibrated inference, robust false-positive control, and improved detection power. Application of CONCISE to high-resolution MERFISH and CosMx datasets from intestinal inflammation and non-small cell lung cancer further highlights its biological utility in disease contexts. CONCISE uncovered inflammation-associated fibroblast-specific interactions during intestinal inflammation and delineated complex tumor-immune and tumor-stromal signaling networks within the tumor microenvironment.

bioinformatics↗

bioRxiv2026

Direct RNA Sequencing reveals epitranscriptomic regulation of brain cells and Alzheimer's Disease pathology

Alternative mRNA splicing and post-transcriptional RNA modification are key mechanisms that regulate transcript function; however, their role in neuronal activity and neurodegenerative disease remains poorly defined. In this study, we evaluated two nanopore-based long-read sequencing (LR-seq) formats: cDNA-PCR sequencing (CPS) and direct RNA sequencing (DRS). We then applied DRS to profile both full-length isoforms and RNA modifications in major brain cell types derived from induced pluripotent stem cells (iPSCs) and post-mortem Alzheimers disease (AD) brains. Relative to CPS, DRS achieved higher accuracy and sensitivity for transcript quantification, de novo transcript model construction, and open reading frame (ORF) annotation across neuropathological gene sets. Focusing on iPSC-derived neurons, we built a multi-omic atlas to connect transcriptional output with translational engagement and protein abundance, by integrating DRS-based mRNA abundance, N6-methyladenosine (m6A) status and poly(A) tail length with ribosome profiling (Ribo-seq) and mass spectrometry (MS). The combination of DRS and Ribo-seq data demonstrated synergism in predicting protein abundance. This analysis also uncovered a significant inverse relationship between m6A modification and mRNA abundance, which was dependent on the engagement of the ribosomal A-site. Lastly, we applied DRS to the epitranscriptomic analysis of AD brain samples, demonstrating that m6A profiles can be used to distinguish early-versus late-stage disease.

neuroscience↗

bioRxiv2026

SETD5 dysfunction in human astrocytes drives IL-6-mediated neuronal impairments via the JAK/STAT signaling pathway

Intellectual disability (ID) and autism spectrum disorder (ASD) are neurodevelopmental conditions marked by lifelong impairments in cognitive, motor, and social functions. Hundreds of genetic variants have been linked to these disorders, including mutations in chromatin regulators such as the SET-domain-containing protein 5 (SETD5) gene. Most studies linking SETD5 loss-of-function to ASD/ID have focused primarily on neurons. However, while SETD5 is highly expressed in astrocytes, its role in glia cells remains poorly understood. Here, we examine how dysfunction of SETD5 in human-induced pluripotent stem cell (hiPSC)-derived astrocytes affects neuronal physiology. We show that SETD5-deficient astrocytes have increased levels of extracellular reactive oxygen species (ROS), glutamate, and interleukins-6 and 8 (IL-6 and IL-8). Elevated astrocytic IL-6 exerts a non-cell autonomous harmful effect on healthy neurons. Using SETD5-deficient astrocytes as a screening platform, we identify the JAK/STAT pathway as an upstream regulator of abnormal IL-6 accumulation associated with SETD5 dysfunction. Accordingly, pharmacological inhibition of JAK-STAT signaling restores extracellular IL-6 to basal levels and partially rescues astrocyte morphology and neuronal deficits. Collectively, these findings highlight the JAK/STAT pathway as a key regulator of SETD5-mediated astrocytic function and suggest its potential as a therapeutic target for astrocytic-driven neuronal impairments in ASD and ID.

neuroscience↗

bioRxiv2026

Discovery of a phenazine thiol conjugase from sparse data using genome-informed machine learning

Machine learning has enabled powerful biological discoveries using models trained on large datasets. However, for many important biological questions, such as identifying enzymes that transform understudied substrates, sparsity of training data is often a major bottleneck. Here, using phenazine natural products as a case study, we show that integrating genome-informed data augmentation with contrastive learning in protein language space enables identification of phenazine-interacting proteins starting from only 14 known phenazine modifying sequences. Applying this framework led to the discovery of PTC (Phenazine-Thiol Conjugase), the first enzyme known to catalyze phenazine thioconjugation, a phenazine modification reaction long observed but previously presumed to occur only through non-enzymatic chemistry. In silico simulation and experimental measurements demonstrate that PTC binds to both phenazine and glutathione as substrates. Recombinant expression and biochemical characterization reveal that PTC promotes glutathione-dependent modification of phenazines, yielding distinct reaction outcomes that depend on substrate identity. Although thiol-conjugated phenazine products exhibit reduced toxicity to bacterial cells, deletion of the gene encoding PTC does not confer a strong fitness disadvantage, illustrating how direct learning of sequences can uncover relevant enzymes that might evade phenotype-based genetic screens. Together, these results demonstrate that coupling comparative genomics with protein machine learning can convert "small data" typically outside the scope of machine learning into actionable predictive power, thereby facilitating enzyme discovery. SignificanceMachine learning excels when large, well-labeled datasets are available, yet many biologically important problems lack sufficient experimental data to support such approaches to discovery. This limitation is particularly acute for identifying enzymes acting on rare or understudied substrates. Here, we show that genomic organization can be leveraged as an additional source of biological information to address data sparsity. Starting with only 14 enzymes experimentally shown to modify phenazines, we developed a model identifying phenazine-interacting enzymes by integrating genome-informed data augmentation with protein machine learning. Guided by the model, we discovered the first enzyme known to catalyze thioconjugation modifications of phenazines, demonstrating a simple yet powerful strategy for extracting predictive insight from sparse biological knowledge.

microbiology↗

bioRxiv2025

Spatial 5mC-seq profiling of embryos and decidua after implantation in mammal

DNA methylation plays key roles in development and diseases. However, no spatial DNA methylation profiling technology has been reported until now. Here, we developed a spatial 5mC-seq method (SmC-seq) based on a microfluidic system. The SmC-seq can provide a non-biased genome-wide methylome at about single-cell scale (10 m in width per channel). We further applied this SmC-seq to explore the spatiotemporal dynamics of DNA methylation during post-implantation development in mouse. A clear spatial heterogeneous pattern of DNA methylation among inner cell mass-derived tissues can be observed. Additionally, we identified a two-layer organization in the ectoplacental cone at the E8.5 stage, characterized by distinct DNA methylation patterning and proliferation states. Unexpectedly, a portion of maternal tissue with low DNA methylation level, enriched for nutrient-supplier progenitor cell, is observed in the middle region of maternal decidua after implantation. The hypomethylated regions in the nutrient-supplier progenitor cell cluster are associated with cell proliferation. Interestingly, the genes associated with hypomethylated regions in the mature nutrient-supplier cell cluster are enriched in exocytosis and nutrient synthesis, which is associated with nutrient provision before functional placenta is formed to support mammalian embryogenesis. In summary, SmC-seq enables spatial mapping of DNA methylation and facilitates our understanding of various biological events.

genomics↗

bioRxiv2025

Dynamic changes in mRNA isoform usage during human retinal development

BackgroundAlternative mRNA splicing is a key mechanism for generating isoform diversity in eukaryotic cells. However, the extent of the splicing changes that occur during complex regulatory processes like neurodevelopment are still incompletely characterized. ResultsWe performed nanopore-based long-read RNA sequencing on differentiating human stem cell-derived retinal organoids to identify temporal patterns of isoform usage across developmental stages. We found that retinal organoids undergo dynamic shifts in isoform usage throughout differentiation, which were not necessarily accompanied with changes in overall gene expression, as was observed for many genes involved in the regulation of mRNA splicing itself. Further analysis of human stem cell-derived retinal ganglion cells uncovered neuron-specific splicing signatures. Additionally, allele-specific gene expression analysis revealed extensive allelic imbalance in induced pluripotent stem cell-derived organoid cultures. ConclusionsBy combining direct long-read RNA sequencing with human stem cell retinal models we were able to develop a comprehensive database of isoform-level changes in differentiating human retinal cells during development. These results uncovered dynamic shifts in transcript usage during retinal differentiation, adding to our knowledge base of post-transcriptional RNA processing in the developing central nervous system and human in vitro culture systems.

molecular biology↗

bioRxiv2025

Iterative delivery of mRNA by MEFI

Conventional therapeutic mRNA delivery systems are inherently single-use, limiting expression potency, duration, and penetration across biological barriers. To address this, we engineered the mRNA Exporting and Ferrying Implement (MEFI), a platform that enables iterative cell-to-cell transfer of cargo mRNA, allowing a single mRNA molecule to be utilized multiple times across various cells. MEFI encodes a fusion protein that assembles virus-like particles (VLPs) and encapsulates both itself and cargo mRNA into these VLPs, orchestrating reproduction of VLPs from targeted cells and continuous intercellular spreading. MEFI significantly amplified cargo protein expression in the transfected cell populations ([~]20-fold) and in organs ([~]500-fold in lung) from mice administered systemically. Notably, through intramuscular injection of naked plasmids, MEFI promoted robust ([~]20-fold) and durable ([~]2-month) cargo expression, interorgan mRNA transfer, and successful crossing of the blood-brain barrier. Moreover, modified MEFI demonstrated cell-type-specific targeting, mediating the elimination of antigen-expressing cells. Collectively, MEFI establishes a modular platform for enhancing mRNA delivery, leveraging the concept of iterative delivery of mRNA. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/667827v2_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@14522c2org.highwire.dtl.DTLVardef@1ecfa7dorg.highwire.dtl.DTLVardef@1314347org.highwire.dtl.DTLVardef@1380cc7_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2025

Arousal-Driven Serial Dependence: Internal States Modulate Perceived Duration

Emotional experiences shape not only how we perceive the present but also how recent experiences inform our current judgments. This study examined whether emotional arousal and valence modulate serial dependence in time perception--the tendency for prior stimuli to bias ongoing estimates. Participants viewed affective images that induced high-arousal (positive or negative) or low-arousal (neutral) states and then reproduced each images duration. High arousal reliably lengthened perceived durations. More critically, it strengthened serial dependence, with the strongest biases emerging when high-arousal trials followed other high-arousal trials, showing a state-dependent amplification of temporal integration. Emotional valence, by contrast, exerted no measurable influence on either temporal distortion or sequential bias. These findings show that emotional arousal tunes how the brain weighs past against present, highlighting internal emotional states as a key driver of temporal continuity in perception.

neuroscience↗

bioRxiv2025

China Autism Brain Imaging Consortium: Charting Brain Growth in Chinese Children with Autism

Autism Spectrum Disorder (ASD) is a lifelong neurodevelopmental condition characterized by atypical brain growth. While advances in neuroimaging and openly sharing large-sample datasets such as the Autism Brain Imaging Data Exchange (ABIDE) have improved understanding of ASD, most studies focus on adolescents and adults, with early brain development-critical for diagnosis and intervention-remaining underexplored. Existing research predominantly involves Western samples, offering limited insight and generalizability into non-Caucasian populations. We introduce the China Autism Brain Imaging Consortium (CABIC) (https://php.bdnilab.com/resources/), a grassroots effort by researchers across the country to aggregate previously collected multi-site structural MRI datasets and phenotypic information from 1,451 autistic children and 1,119 typically developing children, covering an age range from early childhood to school age (1.0 - 12.92 years). Here, we present this resource and depict brain growth charts to push forward a more comprehensive understanding of the brain development in Chinese autism children. We constructed brain growth charts that reveal a developmental shift in autistic children, transitioning from early overgrowth to delayed maturation. Regional analyses identified distinct atypical trajectories across specific brain regions. Individual deviation scores quantified inter-subject variability, characterizing the heterogeneity of brain development in ASD. Comparative analyses between CABIC and ABIDE highlighted differences potentially attributable to ethnicity and culture, advancing our understanding of cross-population neurodevelopmental diversity. CABIC MRI datasets will be shared publicly to foster investigation of the potential neural mechanisms underlying ASD in non-Western populations and support efforts toward precision medicine for autistic individuals across diverse backgrounds.

neuroscience↗

bioRxiv2024

Inferring Cell-Type-Specific Co-Expressed Genes from Single Cell Data

Cell-type-specific gene co-expression networks are widely used to characterize gene relationships. Although many methods have been developed to infer such co-expression networks from single-cell data, the lack of consideration of false positive control in many evaluations and downstream analyses may lead to incorrect conclusions because higher reproducibility, higher functional coherence, and a larger overlap with known biological networks may not imply better performance if the false positives are not well controlled. In this study, we systematically compared two distinct criteria for selecting correlated gene pairs from single-cell data, p-value versus correlation strength. We found that the use of p-values instead of correlation strength is more robust for both selecting meaningful gene pairs and for the fair benchmarking of co-expression estimation methods. To make this approach universally applicable, we extended and validated a simulation method that can efficiently and reliably generate empirical p-values for co-expression estimation methods that do not have corresponding or well-controlled p-values. Furthermore, we demonstrated that a fair comparison of the estimation methods requires adjusting for the varying number of gene pairs they identified and accounting for the inherent expression-level biases within ground truth biological networks. Our study provides a practical guide for researchers to select reliable correlated gene pairs for downstream study and establishes a more rigorous standard for the evaluation and comparison of gene co-expression network estimation methods.

bioinformatics↗

bioRxiv2024

S1PR1 Regulates Lymphatic Valve Development And Prevents Ileitis-Independent Tertiary Lymphoid Organ Formation

Lymphatic vessels function throughout the body to drain interstitial fluids. Efficient lymph flow is ensured by lymphatic valves (LVs). However, the mechanisms that regulate LV development are incompletely understood. Here, we show that the deletion of the GPCR sphingosine 1-phosphate receptor-1 (S1PR1) from lymphatic endothelial cells (LECs) results in fewer LVs. Interestingly, LVs that remained in the terminal-ileum draining lymphatic vessels were specifically dysfunctional, and tertiary lymphoid organs (TLOs) formed in this location. TLOs in the terminal ileum are associated with ileitis in humans and mice. However, mice lacking S1PR1 did not develop obvious characteristics of ileitis. Sphingosine kinases 1 and 2 (SPHK1/2) are required for the synthesis of S1P, the ligand of S1PR1. Mice that lack Sphk1/2 in LECs recapitulate the LV and TLO phenotypes of mice that lack S1PR1. Mechanistically, S1PR1 regulates shear stress signaling and the expression of the valve-regulatory molecules FOXC2 and connexin-37. Importantly, Foxc2+/- mice, a model for lymphedema-distichiasis syndrome, also develop TLOs in the terminal ileum. Thus, we have discovered S1PR1 as a previously unknown regulator of LV and TLO development. We also suggest that TLOs are a sign of subclinical inflammation that can form due to lymphatic disorders in the absence of ileitis.

developmental biology↗

bioRxiv2024

Mother-child dyadic interactions shape children's social brain and theory of mind

Social cognition develops through a complex interplay between neural maturation and environmental factors, yet the neurobehavioral mechanisms underlying this process remain unclear. Using a naturalistic fMRI paradigm, we investigated the effects of age and parental caregiving on social brain development and Theory of Mind (ToM) in 34 mother-child dyads. The functional maturity of social brain networks was positively associated with age, while mother-child neural synchronization during movie viewing was related to dyadic relationship quality. Crucially, parenting and child factors interactively shaped social cognition outcomes, mediated by ToM abilities. Our findings demonstrate the dynamic interplay of neurocognitive development and interpersonal synchrony in early childhood social cognition, and provide novel evidence for neurodevelopmental plasticity and reciprocal determinism. This integrative approach, bridging brain, behavior, and parenting environment, advances our understanding of the complex mechanisms shaping social cognition. The insights gained can inform personalized interventions promoting social competence, emphasizing the critical importance of nurturing parental relationships in facilitating healthy social development.

neuroscience↗