Biology subjects

Xia, Y.

Publications and source records attributed to Xia, Y..

At least 91 records · Page 5Linked to original sources

bioRxiv2024

Multimodal single-cell analyses reveal molecular markers of neuronal senescence in human drug-resistant epilepsy

The histopathological neurons in the brain tissue of drug-resistant epilepsy exhibit aberrant cytoarchitecture and imbalanced synaptic circuit function. However, the gene expression changes of these neurons remain unknown, making it difficult for the diagnosis or to dissect the mechanism of drug-resistant epilepsy. By integrating whole-cell patch clamp recording and single-cell RNA sequencing approaches, we identified a transcriptionally distinct subset of cortical pyramidal neurons. These neurons highly expressed genes CDKN1A (P21), CCL2 and NFKBIA that associated with mTOR pathway, inflammatory response and cellular senescence. We confirmed the expression of senescent marker genes in a subpopulation of cortical pyramidal neurons with enlarged soma size in the brain tissue of drug-resistant epilepsy. We further revealed the expression of senescent cell markers P21, P53, COX2, {gamma}-H2AX, {beta}-Gal and reduction of nuclear integrity marker Lamin B1 in histopathological neurons in the brain tissue of drug-resistant epilepsy patients with different pathologies, but not in control brain tissue with no history of epilepsy. Additionally, chronic, but not acute, epileptic seizures induced senescent markers expression in cortical neurons in mouse models of drug-resistant epilepsy. These results provide important molecular markers for histopathological neurons and new insights into the pathophysiological mechanisms of drug-resistant epilepsy.

neuroscience↗

bioRxiv2024

DeepAssembly2: A Web Server for Protein Complex Structure Assembly Based on Domain-Domain Interactions

Proteins often perform biological functions by forming complexes, thereby accurately predicting the structure of protein complexes is crucial to understanding and mastering their functions, as well as facilitating drug discovery. Protein monomeric structure prediction has made a breakthrough in recent years, but the accurate prediction of complex structure remains a challenge. In this work, we present DeepAssembly2, a web server for automatically assembling protein complex structure based on domain-domain interactions. First, the features are constructed according to the input complex sequence and monomeric structures, then these features are used to predict the inter-chain residue distance through a deep learning model, and finally, the complex structure is assembled under the guidance of inter-chain residue distances. Compared with the previously developed version, DeepAssembly2 is trained on a newly constructed inter-chain domain-domain interaction dataset. Meanwhile, several important features have been added, such as Interface Residue Propensity and Ultrafast Shape Recognition. In addition, we introduced the inter-chain residue distance from the AlphaFold-Multimer model to further improve the accuracy. Finally, we also integrate our recently developed model quality assessment method to select the output models. The performance of DeepAssembly2 is significantly improved compared with the previous version, providing a solution for large protein complex structure modeling through divide-and-conquer assembly strategy, and is expected to provide new insights and an effective tool for drug development, vaccine design, etc. The web server of DeepAssembly2 is freely available at http://zhanglab-bioinf.com/DeepAssembly/.

bioinformatics↗

bioRxiv2024

Language model generates cis-regulatory elements across prokaryotes

Deep learning had succeeded in designing Cis-regulatory elements (CREs) for certain species, but necessitated training data derived from experiments. Here, we present Promoter-Factory, a protocol that leverages language models (LM) to design CREs for prokaryotes without experimental prior. Millions of sequences were drawn from thousands of prokaryotic genomes to train a suite of language models, named PromoGen2, and achieved the highest zero-shot promoter strength prediction accuracy among tested LMs. Artificial CREs designed with Promoter-Factory achieved a 100% success rate to express gene in Escherichia coli, Bacillus subtilis, and Bacillus licheniformis. Furthermore, most of the promoters designed targeting Jejubacter sp. L23, a halophilic bacterium without available CREs, were active and successfully drove lycopene overproduction. The generation of 2 million putative promoters across 1,757 prokaryotic genera, along with the Promoter-Factory protocol, will significantly expand the sequence space and facilitate the development of an extensive repertoire of prokaryotic CREs.

bioinformatics↗

bioRxiv2024

Environmental polysulfides promote protein disulfide bond formation of microorganisms growing under anaerobic condition

Polysulfides are rich in anaerobic and microbial metabolism active environments. Anaerobic survival of microorganisms requires the formation of protein disulfide bond (DSB). The relation between environmental polysulfides and anaerobic DSB formation has not been studied so far. Herein, we discovered that environmental polysulfides can efficiently mediate protein DSB formation of microorganisms under anaerobic condition. We used polysulfides to treat proteins including roGFP2, Trx1, and DsbA under anaerobic condition and found that all three proteins formed intramolecular DSB in vitro. The growth of E. coli {Delta}dsbB was reduced and the amount of its intracellular protein DSB was decreased under anaerobic condition. However, treating the mutant strain with polysulfides recovered the growth and reversed DSB decrease. Treating E. coli {Delta}dsbA with polysulfides promoted DSB formation of its periplasmic roGFP2 and recovered its growth under anaerobic condition. In addition, treating Schizosaccharomyces pombe with polysulfides led to increase of the intracellular protein DSB content. Thus, our study reveals that environmental polysulfides can promote DSB formation independent of the enzymatic DSB mediating system and oxygen. In this aspect, environmental polysulfides are beneficial for the survival of microorganisms in anaerobic habitats. IMPORTANCEHow polysulfides benefit adaption of microorganisms to anaerobic environments are unclear. Our study reveals that environmental polysulfides efficiently facilitate protein DSB formation under anaerobic condition. Polysulfides contain zero valent sulfur atoms (S0), which can be transferred to the thiol group of cysteine residue. This S0 atom gets two electrons from two cysteine residues and becomes reduced H2S, leaving two cysteine residues in disulfide bond form. Anaerobic growth of microorganisms was benefited from the formation of DSB. This finding paves the way for a deeper understanding of the intricate relationship between polysulfides and microorganisms in environmental contexts.

molecular biology↗

bioRxiv2024

The mechanism and consequences of amyloid-β modulating thiamine pyrophosphokinase-1 expression in microglia

Ample studies attribute cognitive decline in Alzheimers disease to amyloid-{beta} deposition 1-6. However, brain amyloid-{beta} accumulation that saturates years before the manifestation of clinical symptoms is dissociated with cognitive decline of the disease 7. It is unknown how these two processes are mechanistically linked. In this and our accompanied study, we report that thiamine pyrophosphokinase-1 (TPK) deficiency plays essential roles in both processes via distinct mechanisms. Here we describe that diminished microglia Tpk controls the propagation of amyloid-{beta} plaques. In APP/PS1 transgenic mice, microglia showed elevated Tpk expression at 2-month-old, but reduction in a plaque-centric manner at 8-month-old. Interestingly, lipopolysaccharide, but not amyloid-{beta}, induceed Tpk reduction in cultured microglia. Tpk reduction led to microglia dysfunction, showing volatile motility but reduced phagocytosis and weak response to focal tissue injury, with accumulation of intracellular lipid droplets and abnormal mitochrondria. In Alzheimers disease mice, microglia-specific knockout of Tpk caused diminished plaque coverage, exacerbated plaque burden and synaptic loss. However, increased plaques were not accompanied by the development of neurofibrillary tangles or brain atrophy, in contrast to the phenotype described in our accompanied paper with neuronal Tpk deletion. In conclusion, plaque-induced inflammation reduces Tpk in microglia, selectively exacerbating the spread of amyloid pathology.

neuroscience↗

bioRxiv2024

Cholinergic basal forebrain neurons regulate vascular dynamics and cerebrospinal fluid flux

Waste from the brain is cleared via a cerebrospinal fluid (CSF) exchange pathway, the dysfunction of which is suggested to underlie the pathogenesis of many brain conditions. Coherent cerebrovascular oscillation that couples with pulsatile CSF inflow is suggested to drive the fluid flux. However, how this coupling is regulated, whether it mediates waste clearance, and why fluid flux is impaired in disease status remain unclear. Here we show that vascular-CSF coupling correlates with cortical cholinergic activity in non-demented aged humans. The causal role of basal forebrain cholinergic neurons that project to the cortex is then verified by specific lesioning in mice, revealing correlated changes in vascular-CSF coupling, arterial pulsation and glymphatic flux, which can be altered by an acetylcholinesterase inhibitor. These results suggest a neurovascular mechanism by which CSF/glymphatic flux is modulated by cholinergic neuronal activity, thereby providing a conceptual basis for the development of diagnostics and treatments for glymphatic dysfunction.

neuroscience↗

bioRxiv2024

Sapphire-Based Optrode for Low Noise Neural Recording and Optogenetic Manipulation

Electrophysiological recordings of neurons in deep brain regions using optogenetic stimulation are essential to understanding and regulating the role of complex neural activity in biological behavior and cognitive function. Optogenetic techniques have significantly advanced neuroscience research by enabling the optical manipulation of neural activities. Because of the significance of the technique, constant advancements in implantable optrodes that integrate optical stimulation with low-noise, large-scale electrophysiological recording are in demand to improve the spatiotemporal resolution for various experimental designs and future clinical applications. However, robust and easy-to-use neural optrodes that integrate neural recording arrays with high-intensity light emitting diodes (LEDs) are still lacking. Here, we propose a neural optrode based on Gallium Nitride (GaN) on sapphire technology, which integrates a high-intensity blue LED with a 5x2 recording array monolithically for simultaneous neural recording and optogenetic manipulation. To reduce the noise interference between the recording electrodes and the LED, which is in close physical proximity, three metal grounding interlayers were incorporated within the optrode, and their ability to reduce LED-induced artifacts during neural recording was confirmed through both electromagnetic simulations and experimental demonstrations. The capability of the sapphire optrode to record action potentials has been demonstrated by recording the firing of mitral/tuft cells in the olfactory bulbs of mice in vivo. Additionally, the elevation of action potential firing due to optogenetic stimulation observed using the sapphire probe in medial superior olive (MSO) neurons of the gerbil auditory brainstem confirms the capability of this sapphire optrode to precisely access neural activities in deep brain regions under complex experimental designs.

neuroscience↗

bioRxiv2024

Single-Molecule Barcoding Technology for Single-Cell Genomics

Recent advances in barcoding technologies have significantly enhanced the scalability of single-cell genomic experiments. However, large-scale experiments are still rare due to high costs, complex logistics, and laborintensive procedures. To facilitate the routine application of the largest scalability, it is critical to simplify the production and use of barcoding reagents. Here, we introduce AmpliDrop, a technology that initiates the barcoding process using a pool of inexpensive single-copy barcodes and integrates barcode multiplicity generation with tagging of cellular content into a single reaction driven by DNA polymerase during library preparation. The barcoding reactions are compartmentalized using an electronic pipette or a robotic or standalone liquid handling system. These innovations eliminate the need for barcoded beads and complex combinatorial indexing workflows and provide flexibility for a wide range of scales and tube formats, as well as compatibility with automation. We show that AmpliDrop is capable of capturing transcriptomes and chromatin accessibility, and it can also be adapted for user-customized applications, including antibody-based protein detection, bacterial or viral DNA detection, and CRISPR perturbations without dual guide RNA-expression vectors. We validated AmpliDrop by investigating the influence of short-term static culturing on cell composition in human forebrain organoids, revealing metabolic reprogramming in lineage progenitors.

molecular biology↗

bioRxiv2024

Ultra-resolution Deconvolution of Spatial Transcriptomics Unveils Spatiotemporal Cellular Dynamics in Complex Microenvironments

Immune cells infiltrate tissues in response to exogenous pathogens or spontaneous tumors, generating protective immunity to safeguard tissues. Despite advancements in spatial transcriptomics (ST), the precise spatial distribution and functional specialization of immune cells within tissue microenvironments remain elusive. Here, we introduce an ultra-precision ST deconvolution algorithm (UCASpatial) that enhances the mapping of cell subpopulations to spatial locations by leveraging the contribution of genes indicative of cell identity through entropy-based weighting. Using both in silico and real ST datasets, we demonstrate that UCASpatial improves the robustness and accuracy in identifying low-abundant cell subpopulations and distinguishing transcriptionally heterogeneous cell subpopulations. Applying UCASpatial to human colorectal cancer (CRC), we link genomic alterations in individual cancer clones to multi-cellular characteristics of the tumor immune microenvironment (TIME) and reveal the co-evolution of tumor cells and TIME at a clonal resolution. We show that the copy number gain on chromosome 20q (chr20q-gain) in tumor cells orchestrates a T cell-excluded TIME, indicative of resistance to immunotherapy in CRC, and is associated with tumor-intrinsic human endogenous retrovirus subfamily H (HERV-H) silencing and impaired type I interferon response. In murine wound healing models, we illuminate the spatiotemporal dynamics of individual cell subsets across various stages of the healing process. We discovered that the scarring-healing mice (C57BL/6) exhibited a replacement of Prg4+ chondrogenic progenitors to Igfbp5+ chondrocytes in the wound bed at the regeneration stage, a change not observed in the regenerative strain (MRL/MpJ). The Igfbp5+ chondrocyte, spatially coordinating with Cd36+ Gpnmb+ Il1b- macrophage and Fmod+ fibroblast, forms a pro-fibrotic community associated with regeneration failure. The cell-cell interactions within this three-cell cluster, mediated by the IL11-IL11RA axis, drive the pro-fibrotic community formation and limit regeneration in C57BL/6 mice. Our findings present UCASpatial as a versatile tool for deciphering fine-grained cellular landscapes in ST and exploring intercellular mechanisms in complex and dynamic microenvironments.

bioinformatics↗

bioRxiv2024

In silico generation and augmentation of regulatory variants from massively parallel reporter assay using conditional variational autoencoder

Predicting the functional consequences of genetic variants in non-coding regions is a challenging problem. Massively parallel reporter assays (MPRAs), which are an in vitro high-throughput method, can simultaneously test thousands of variants by evaluating the existence of allele specific regulatory activity. Nevertheless, the identified labelled variants by MPRAs, which shows differential allelic regulatory effects on the gene expression are usually limited to the scale of hundreds, limiting their potential to be used as the training set for achieving a robust genome-wide prediction. To address the limitation, we propose a deep generative model, MpraVAE, to in silico generate and augment the training sample size of labelled variants. By benchmarking on several MPRA datasets, we demonstrate that MpraVAE significantly improves the prediction performance for MPRA regulatory variants compared to the baseline method, conventional data augmentation approaches as well as existing variant scoring methods. Taking autoimmune diseases as one example, we apply MpraVAE to perform a genome-wide prediction of regulatory variants and find that predicted regulatory variants are more enriched than background variants in enhancers, active histone marks, open chromatin regions in immune-related cell types, and chromatin states associated with promoter, enhancer activity and binding sites of cMyC and Pol II that regulate gene expression. Importantly, predicted regulatory variants are found to link immune-related genes by leveraging chromatin loop and accessible chromatin, demonstrating the importance of MpraVAE in genetic and gene discovery for complex traits.

bioinformatics↗

bioRxiv2024

Marseilleviruses biological properties and viral translation-associated proteins based on in silico tertiary structure

Marseilleviruses are a group of double-strand DNA viruses that infect amoeba within the Nucleocytoviricota phylum and are ubiquitous in water and soil globally. Here, we report four novel strains isolated from mangroves in Guangdong province, China, namely, futianmevirus, futianmfvirus, dashavirus str. E, and xiwanvirus. Viral particles presented about 220[~]240 nm icosahedrally shaped capsids and were wrapped by membranes to form giant vesicles. Based on stability assays, viral particles were halotolerant and acid-tolerant, but sensitive to chloroform and high temperature, while giant vesicles conferred thermal and acid/alkaline resistance to particles. Genomics and phylogenetic analyses showed that the four strains formed divergent branches within different lineages of marseillevirus. Notably, to our knowledge, futianmevirus was the first reported marseillevirus lacking translation elongation factor EF-1alpha (EF1A). Our in silico analysis of marseillevirus coded translation-associated homolgs suggested their conserved functions. Additionally, we predicted at least four novel proteins that were structurally similar to components of the protozoan ribosome. Overall, not only our data comprehensively described the diversity of marseillevirus biological properties, but also proposed a new perspective on the giant virus translation system. ImportanceThe family Marseilleviridae was the second reported family of giant viruses and distributed globally. In this work, we reported the four novel marseilleviruses isolated from saltwater samples of mangrove. Difference of biological properties between giant vesicles and viral particles revealed the environment fitness of marseillevirus. On the other hand, sensitivity to chloroform indicated the importance of lipid components for viral infection. Additionally, our comparative genomics, phylogenetic analysis, and protein structure comparison revealed the diverse translation-associated gene sets of marseilleviruses. The prediction of ribosome components expands the knowledge about the giant viral translation-associated proteins, and will be helpful in future to reveal how giant viruses hijack the amoeba translation system.

microbiology↗

bioRxiv2024

Modeling neural coding in the auditory brain with high resolution and accuracy

Computational models of auditory processing can be valuable tools for research and technology development. Models of the cochlea are highly accurate and widely used, but models of the auditory brain lag far behind in both performance and penetration. Here, we present ICNet, a model that provides accurate simulation of neural dynamics in the inferior colliculus across a wide range of sounds, including near-perfect simulation of responses to speech. We developed ICNet using deep learning and large-scale intracranial recordings from gerbils, addressing three key modeling challenges that are common across all sensory systems: capturing the full statistical complexity of neuronal response patterns; accounting for physiological and experimental non-stationarity; and extracting features of sensory processing that are shared across different brains. ICNet can be used to simulate activity from thousands of neural units or to provide a compact representation of central auditory processing through its latent dynamics, facilitating a wide range of hearing and audio applications.

bioengineering↗

bioRxiv2024

Bridging the Gap: biofilm-mediated establishment of Bacillus velezensis on Trichoderma guizhouense mycelia

Bacterial-fungal interactions (BFIs) are important in ecosystem dynamics, especially within the soil rhizosphere. The bacterium Bacillus velezensis SQR9 and the fungus Trichoderma guizhouense NJAU 4742 have garnered considerable attention due to their roles in promoting plant growth and protecting their host against pathogens. In this study, we utilized these two model microorganisms to investigate BFI. We firstly demonstrate that while co-inoculation of B. velezensis and T. guizhouense could promote tomato growth, these two microorganisms display mutual antagonism on agar solidified medium. To resolve this contradiction, we developed an inoculation method, that allows B. velezensis colonization of T. guizhouense hyphae and performed a transcriptome analysis. During colonization of the fungal hyphae, B. velezensis SQR9 upregulates expression of biofilm related genes (e.g. eps, tasA, and bslA) that is distinct from free-living cells. This result suggested an intricate association between extracellular matrix expression and hyphae colonization. In accordance, deletion epsD, tasA, or both epsD and tasA genes of B. velezensis diminished colonization of the T. guizhouense hyphae. The insights from our study demonstrate that soil BFIs are more complex than we understood, potentially involving both competition and cooperation. These intricate biofilm-mediated BFI dynamics might contribute to the remarkable diversity observed within soil microbiota, providing a fresh perspective for further exploration of BFIs in the plant rhizosphere.

microbiology↗

bioRxiv2024

Design nonrepetitive and diverse activity single-guide RNA by deep learning

Multiplex and precise control of the gene expression based on CRISPR/Cas9 is important to metabolic regulation in synthetic biology. However, employing single guide RNAs (sgRNAs) that possess repetitive DNA sequences and exhibit uniform activity could detrimentally affect the editing process, undermining both its stability and regulatory potential. In this study, we developed a deep generative model based on a decoder-only Transformer architecture (sgRNAGen) for the de novo generation of a series of nonrepetitive and diverse sgRNAs with activity. To assess the quality of sgRNAs generated by sgRNAGen, we evaluated their activity by targeting essential genes, with the results indicating that 98% of the generated sgRNAs were active in Bacillus subtilis. The generated sgRNAs were further validated for applications in single-gene editing, large fragment knockouts, and multiplex editing. Notably, the efficiency of knocking out long fragments up to 169.5 kb reached 100%, and targeting multiple sites allowed for the creation of strains with various combinations of mutations in a single editing. Furthermore, we developed a CRISPRi system utilizing the designed sgRNAs to regulate gene expression with desired strength and high precision. SgRNAGen offers a method for devising nonrepetitive and diverse activity sgRNAs, enhancing metabolic control and advancing applications within synthetic biology. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/596019v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@f68faaorg.highwire.dtl.DTLVardef@151f5e2org.highwire.dtl.DTLVardef@1e5cb28org.highwire.dtl.DTLVardef@17cd3f8_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2024

A foundation model for generalizable cancer diagnosis and survival prediction from histopathological images

Computational pathology, utilizing whole slide image (WSI) for pathological diagnosis, has advanced the development of intelligent healthcare. However, the scarcity of annotated data and histological differences hinder the general application of existing methods. Extensive histopathological data and the robustness of self-supervised models in small-scale data demonstrate promising prospects for developing foundation pathology models. Due to the need for deployment, lightweight foundation models also need to be developed. In this work, we propose the BEPH (BEiT-based model Pre-training on Histopathological images), a general lightweight foundation model that leverages self-supervised learning to learn meaningful representations from 11 million unlabeled histopathological images. These representations are then efficiently adapted to various tasks, including 2 cancer patch-level recognition tasks, 3 cancer WSI-level classification tasks, and 6 cancer subtypes survival prediction tasks. Experimental results demonstrate that our model consistently outperforms several comparative models with similar parameters, even with limited training data reduced to 50%. Especially when the downstream structure is the same, the model can improve ResNet and DINO by up to a maximum increase of 8.8% and 7.2% (WSI level classification), and 6.44% and 3.28% on average (survival prediction), respectively. Therefore, BEPH offers a universal solution to enhance model performance, reduce the burden of expert annotations, and enable widespread clinical applications of artificial intelligence. The code and models can be obtained at https://github.com/Zhcyoung/BEPH. And currently, online fine-tuning of WSI classification tasks is available for use on http://yulab-sjtu.natapp1.cc/BEPH.

pathology↗

bioRxiv2024

The Influence of Crosslinker Architecture on Dynamic Covalent Hydrogel Viscoelasticity

Dynamic covalent crosslinked (DCC) hydrogels represent a significant advance in biomaterials for regenerative medicine and mechanobiology. These gels typically offer viscoelasticity and self-healing properties that more closely mimic in vivo tissue mechanics than traditional, predominantly elastic, covalent crosslinked hydrogels. Despite their promise, the effects of varying crosslinker architecture - side chain versus telechelic crosslinks - on the viscoelastic properties of DCC hydrogels have not been thoroughly investigated. This study introduces hydrazone-based alginate hydrogels and examines how side-chain and telechelic crosslinker architectures impact hydrogel viscoelasticity and stiffness. In hydrogels with side-chain crosslinking (SCX), higher polymer concentrations enhance stiffness and decelerates stress relaxation, while an off-stoichiometric hydrazine-to-aldehyde ratio leads to reduced stiffness and shorter relaxation time. In hydrogels with telechelic crosslinking, maximal stiffness and slowest stress relaxation occurs at intermediate crosslinker concentrations for both linear and star crosslinkers, with higher crosslinker valency further increasing stiffness and relaxation time. Our result suggested different ranges of stiffness and stress relaxation are accessible with the different crosslinker architectures, with SCX hydrogels leading to slower stress relaxation relative to the other architectures, and hydrogels with star crosslinking (SX) providing increased stiffness and slower stress relaxation relative to hydrogels with linear crosslinking (LX). The mechanical properties of SX hydrogels are more robust to changes induced by competing chemical reactions compared to LX hydrogels. Our research underscores the pivotal role of crosslinker architecture in defining hydrogel stiffness and viscoelasticity, providing crucial insights for the design of DCC hydrogels with tailored mechanical properties for specific biomedical applications.

bioengineering↗

bioRxiv2024

Development of the overlapping network modules in the human brain

Developmental connectomic studies have shown that the modular organization of functional networks in the human brain undergoes substantial reorganization with age to support cognitive growth. However, these studies implicitly assume that each brain region belongs to one and only one specific network module, ignoring the potential spatial overlap between functional modules. How the overlapping functional modular architecture develops and whether this development is related to structural signatures remain unknown. Using longitudinal multimodal structural, functional, and diffusion MRI data from 305 children (aged 6-14 years), we investigated the development of the overlapping modular architecture of functional networks, and further explored their structural associations. Specifically, an edge-centric network model was used to identify the overlapping functional modules, and the nodal overlap in module affiliations was quantified using the entropy measure. We showed a remarkable regional inhomogeneity in module overlap in children, with higher entropy in the ventral attention, somatomotor, and subcortical networks and lower entropy in the visual and default-mode networks. Furthermore, the overlapping modules developed in a linear, spatially dissociable manner from childhood to adolescence, with significantly reduced entropy in the prefrontal cortex and putamen and increased entropy in the parietal lobules. Personalized overlapping modular patterns capture individual brain maturity as characterized by brain age. Finally, the overlapping functional modules can be significantly predicted by integrating gray matter morphology and white matter network properties. Our findings highlight the maturation of overlapping network modules and their structural substrates, thereby advancing our understanding of the principles of connectome development.

neuroscience↗

bioRxiv2024

The muscarinic acetylcholine receptor in dermal papilla cells regulates hair growth

The role of cholinergic system in hair biology is poorly understood. In M4 muscarinic receptor (mAChR) knockout mice, the hair follicles have a prolonged telogen phase and fail to produce hair shafts. Here, we reported that hair growth was regulated by cholinergic system via mAChRs. Dermal papilla cells expressed different cholinergic biomarkers. Inhibiting AChE or activating mAChR in dermal papilla cells, culture vibrissae and skin epidermis promoted the hair growth. In cultured papilla cells treated with bethanechol, an agonist of mAChR, an activation of Wnt/{beta}-catenin signalling was illustrated by various indicative biomarkers, including phosphorylation of GSK-3{beta} and mRNA expression of various molecules for Wnt/{beta}- catenin signalling. Activation of Wnt/{beta}-catenin signalling was mediated by PI3K/AKT and ERK signalling upon the stimulation of bethanechol. In addition, an increase in hair shaft elongation was observed in mouse vibrissae upon the treatment of bethanechol, suggesting the cholinergic role in hair growth.

neuroscience↗