Biology subjects

Jiang, X.

Publications and source records attributed to Jiang, X..

At least 199 records · Page 11Linked to original sources

bioRxiv2024

MetaWorm: A Complete Model Bridging Brain, Body and Environment of C. elegans

The behavior of an organism is profoundly influenced by the complex interplay between its brain, body, and environment. Existing data-driven models focusing on either the brain or the body-environment separately. A model that integrates these two components is yet to be developed. Here, we present MetaWorm, an integrative data-driven model of a widely studied organism, C. elegans. This model consists of two sub-models: the brain model and the body & environment model. The brain model was built by multi-compartment models with realistic morphology, connectome, and neural population dynamics based on experimental data. Simultaneously, the body & environment model employed a lifelike body and a 3D physical environment, facilitating easy behavior quantification. Through the closed-loop interaction between two sub-models, MetaWorm faithfully reproduced the realistic zigzag movement towards attractors observed in C. elegans. Notably, MetaWorm is the first model to achieve seamless integration of detailed brain, body, and environment simulations, enabling unprecedented insights into the intricate relationships between neural structures, neural activities, and behaviors. Leveraging this model, we investigated the impact of neural system structure on both neural activities and behaviors. Consequently, MetaWorm can enhance our understanding of how the brain controls the body to interact with its surrounding environment.

neuroscience↗

bioRxiv2024

Genetic polymorphisms of Leukocyte Immunoglobulin-Like Receptor B3 (LILRB3) gene in African American kidney transplant recipients are associated with post-transplant graft failure

BackgroundAfrican American (AA) kidney transplant recipients exhibit a higher rate of graft loss compared to other racial and ethnic populations, highlighting the need to identify causative factors underlying this disparity. MethodWe analyzed RNA sequences of pretransplant whole blood from subjects followed in three kidney transplant cohorts to identify single nucleotide polymorphisms (SNPs) associated with death censored graft loss (DCGL). We employed a meta-analysis to uncover key transcriptional signatures and pathways associated with the identified SNPs and used single cell RNA to define cellular specificity. We characterized SNP functions using in vitro immunological and survival assays and tested for associations between the identified SNPs and other immune-related diseases using a [~]30,100 subject, electronic health record (EHR)-linked database. ResultsWe uncovered a cluster of four consecutive missense SNPs in the Leukocyte Immunoglobulin-Like Receptor B3 (LILRB3, a negative immune response regulator) gene that strongly associated with DCGL. This LILRB3-4SNPs cluster encodes missense mutations at amino acids 617-618 proximal to a SHP-1/2 phosphatase-binding ITIM motif. LILRB3-4SNPs is specifically enriched within subjects of AA ancestry (8.6% prevalence vs 2.3% in Hispanic and 0.1% in European populations), is not linked to APOL1 G1/G2 alleles, and exhibited a strong association with DCGL. Analysis of PBMC and transplant biopsies from recipients with LILRB3-4SNPs showed evidence of enhanced adaptive immune responsiveness and ferroptosis-associated death in monocytes. Overexpression of the variant allele in THP-1 cells (macrophage line) induced augmented inflammation and ferroptosis, which were attenuated by a ferroptosis inhibitor, verifying a causal link. The LILRB3-4SNPs also associated with multiple systemic and organ-specific immune-related diseases in AAs, consistent with conferring a broadly relevant immune function. Conclusionthe LILRB3-4SNPs represent a functionally important, distinct genetic risk factor for kidney transplant outcome and development/severity of other immune-related diseases in patients of AA ancestry. Pharmacological targeting of ferroptosis should be tested to prevent or treat these disease processes in AA recipients carrying LILRB3-4SNPs.

genetics↗

bioRxiv2024

Arginine Di-methylation of RIPK3 Safeguards Necroptosis for Intestinal Homeostasis

The necroptosis mediated by RIPK3 is stringently regulated for intestinal homeostasis. Here we found that mice lacking Prmt5 (Protein arginase methyltransferase 5) in intestinal epithelial cells (IECs) caused premature death with IECs necroptosis, villus atrophy and loss of Paneth cells. This pathology can be partially rescued by antibiotic treatment, germ-free breeding condition and pharmaceutical inhibition of RIPK1 and RIPK3, but aggravated for embryonic lethality by Caspase-8 deficiency, which demonstrating the importance of commensal bacteria and necroptosis for the Prmt5-IEC deficiency. Intriguingly, tumor-necrosis factor (TNF) receptor 1(Tnfr1) deficiency could not completely rescue the pathology, and mice deficit in Z- DNA binding protein 1(ZBP1) exhibited shorter lifespan compared with Prmt5 null mice, suggesting Prmt5 loss might trigger TNFR-RIPK1-depenfent and ZBP1- dependent necroptosis. Mechanically, we identified the 479-arginine residue of RIPK3 di-methylated by PRMT5 was an endogenous checkpoint for necroptosis. Furthermore, RIPK3-R479K mutation had higher affinity with both RIPK1 and ZBP1 by immunoprecipitation and STORM (Stochastic Optical Reconstruction Microscopy) analysis, which might explain the endogenous necroptosis triggered by mutated RIPK3 even without upstream stimuli. Moreover, the peptide of RIPK3-SDMA (Symmetric dimethylarginine of 479) could rescue lethality of Prmt5 lacking mice through necrosome formation inhibition, which demonstrating the great potential for necroptosis-related disease treatment through RIPK3 dimethylation targeting.

cell biology↗

bioRxiv2024

PI3K/HSCB axis facilitates FOG1 nuclear translocation to promote erythropoiesis and megakaryopoiesis

Erythropoiesis and megakaryopoiesis are stringently regulated by signaling pathways. However, the precise molecular mechanisms through which signaling pathways regulate key transcription factors controlling erythropoiesis and megakaryopoiesis remain partially understood. Herein, we identified heat shock cognate B (HSCB), which is well known for its iron-sulfur cluster delivery function, as an indispensable protein for friend of GATA 1 (FOG1) nuclear translocation during erythropoiesis of K562 human erythroleukemia cells and cord-blood-derived human CD34+CD90+ hematopoietic stem cells (HSCs), as well as during megakaryopoiesis of the CD34+CD90+ HSCs. Mechanistically, HSCB could be phosphorylated by phosphoinositol-3-kinase (PI3K) to bind with and mediate the proteasomal degradation of transforming acidic coiled-coil containing protein 3 (TACC3), which otherwise detained FOG1 in the cytoplasm, thereby facilitating FOG1 nuclear translocation. Given that PI3K is activated during both erythropoiesis and megakaryopoiesis, and that FOG1 is a key transcription factor for these processes, our findings elucidate an important, previously unrecognized iron-sulfur cluster delivery independent function of HSCB in erythropoiesis and megakaryopoiesis.

molecular biology↗

bioRxiv2024

PackDock: a Diffusion Based Side Chain Packing Model for Flexible Protein-Ligand Docking

Structure-based drug design (SBDD) relies on accurate knowledge of protein structure and ligand-binding conformations. However, most of the static conformations obtained by advanced methods such as structural biology and de novo protein folding algorithms often dont meet the needs for drug design. We introduce PackDock, a flexible docking method that combines "conformation selection" and "induced fit" mechanisms in a two-stage docking pipeline. The core module of this method is PackPocket, which uses a diffusion model to explore the side-chain conformation space in ligand binding pockets, both with or without a ligand. We evaluate our method using several tests that reflect real-world application scenarios. (1) Side-chain packing and Re-docking experiments validate the ability of PackDock to predict accurate side-chain conformations and ligand conformations. (2) Cross-docking experiments with apo and non-homologous ligand-induced holo structures align with real docking scenarios, demonstrating PackDocks practical value. (3) Docking experiments with hypothetical models show that PackPocket can potentially conduct SBDD starting from protein sequence information only. Additionally, we found that PackDock can identify key amino acid conformation changes, which may provide insights for lead compound optimization. We demonstrate PackDock can accurately predict the complex conformations in various application scenarios, by combining the conformation selection theory and the induced fit theory, and by using the ability of PackPocket to accurately predict the side chain conformations in the pocket region. We believe this method can improve the usability of existing structures, providing a new perspective for the SBDD community.

bioinformatics↗

bioRxiv2024

Transcranial Photobiomodulation on the Left Prefrontal Cortex Enhances Mandarin Chinese L1 and L2 Complex Sentence Processing Performances

This study investigated the causal effect of transcranial photobiomodulation (tPBM) over the left prefrontal cortex (LPFC) on syntactically complex Mandarin Chinese first language (L1) and second language (L2) sentence processing performances. Two (L1 and L2) groups of participants (thirty per group) were recruited to receive the double-blind, sham-controlled tPBM intervention, followed by the sentence processing, the verbal working memory (WM), and the visual WM tasks. Results revealed a consistent pattern for both groups: (a) tPBM enhanced sentence processing performance but not verbal WM and visual WM performance; (b) Participants with lower sentence processing performances under sham tPBM benefited more from active tPBM. Taken together, the current study substantiated that tPBM enhanced L1 and L2 sentence processing ability directly without verbal WM interference, and would serve as a promising and cost-effective noninvasive brain stimulation (NIBS) tool for future applications on upregulating the human language faculty. HighlightsO_LIThe first study that applies tPBM to (complex) sentence processing. C_LIO_LItPBM enhances sentence processing performances in both Mandarin L1 & L2 speakers. C_LIO_LItPBM directly enhances sentence processing without the interference of verbal WM. C_LIO_LIA causal role of LPFC for sentence processing through active tPBM. C_LIO_LIOpening up the promising application prospect for tPBM on sentence processing. C_LI

neuroscience↗

bioRxiv2024

Age-Related Decline in BBB Function is More Pronounced in Males than Females

The blood-brain barrier (BBB) plays a pivotal role in protecting the central nervous system (CNS), shielding it from potential harmful entities. A natural decline of BBB function with aging has been reported in both animal and human studies, which may contribute to cognitive decline and neurodegenerative disorders. Limited data also suggest that being female may be associated with protective effects on BBB function. Here we investigated age and sex-dependent trajectories of perfusion and BBB water exchange rate (kw) across the lifespan in 186 cognitively normal participants spanning the ages of 8 to 92 years old, using a non-invasive diffusion prepared pseudo-continuous arterial spin labeling (DP-pCASL) MRI technique. We found that the pattern of BBB kw decline with aging varies across brain regions. Moreover, results from our DP-pCASL technique revealed a remarkable decline in BBB kw beginning in the early 60s, which was more pronounced in males. In addition, we observed sex differences in parietal and temporal regions. Our findings provide in vivo results demonstrating sex differences in the decline of BBB function with aging, which may serve as a foundation for future investigations into perfusion and BBB function in neurodegenerative and other brain disorders. Significance statementThe blood-brain barrier (BBB) serves as a critical protection mechanism for the CNS. A natural decline of BBB function with aging has been reported in both animal and human studies, with possible differences in BBB function by sex. Using our MRI technique, DP-pCASL that measures water exchange rate (kw) without contrast in 186 participants from diverse race and age groups, we identified age and sex-specific patterns in BBB kw especially in parietal and temporal regions. We observed of a decline in kw beginning in the early 60s, especially in males. Our study unveils the dynamic spatiotemporal pattern of kw differences with age and sex, which serve as a foundation for understanding aberrations of BBB function in neurodegenerative and other brain disorders.

neuroscience↗

bioRxiv2024

Genomic and transcriptomic characteristics of type VI secretion system in Klebsiella pneumoniae

The Type VI secretion system (T6SS) serves as a crucial molecular weapon in interbacterial competition and significantly influences cell-cell interactions. Various bacterial species utilize their T6SSs to execute a multitude of functions, dictated by their ecological niche. However, the characteristics of T6SS in clinical Klebsiella pneumoniae, a common opportunistic nosocomial pathogen, have not been fully elucidated. Here, we conducted a genomic analysis of 65 clinical K. pneumoniae isolates obtained from patients with varying infections. Genes encoding a T6SS cluster were present in all analyzed strains of K. pneumoniae. Strains of identical sequence type (ST) carried structurally and numerically identical T6SS. Our study also highlights the importance of selecting conserved regions in key T6SS genes for effective primer design in PCR identification. We then utilized the predominant ST11 K. pneumoniae HS11286 to investigate the effect of knocking out T6SS marker genes hcp or vgrG. Transcriptome analysis identified a total of 1,298 co-upregulated and 1,752 co-downregulated differentially expressed genes. Additionally, the absence of hcp or vgrG gene suppressed the expression of other T6SS-related genes within the locus I cluster. Pathway analysis showed that the {Delta}hcp mutant exhibited alterations in transport, establishment of localization, localization and cell processes. Furthermore, interbacterial competition experiments showed that hcp and vgrG are essential for competitive ability of ST11 K. pneumoniae HS11286. This study furthers our understanding of the genomic characteristics of T6SS in K. pneumoniae and suggested that the involvement of multiple genes in T6SS of strain HS11286. ImportanceGram-negative bacteria use T6SS to deliver effectors that interact with neighboring cells for niche advantage. K. pneumoniae is an opportunistic nosocomial pathogen that often carriers multiple T6SS loci, the function of which has not yet been elucidated. We performed a genomic analysis of 65 clinical K. pneumoniae strains isolated from various sources, confirming that all strains contained T6SS. We then used transcriptomics to further study changes in gene expression and effect upon interbacterial competition following knockout of key T6SS genes in ST11 K. pneumoniae HS11286. Our findings revealed the distribution and genomic characteristics of T6SS in clinical K. pneumoniae. This study also described the overall transcriptional changes in the predominant Chinese ST11 strain HS11286 upon deletion of crucial T6SS genes. Additionally, this work provides a reference for future research on the identification of T6SS in bacteria.

microbiology↗

bioRxiv2023

Emergence of synchronised growth oscillations in filamentous fungi

Soil fungi are important decomposers of organic matter and play crucial roles in the biogeochemical cycles in the soil. Many species of fungi grow in the form of branched networks. While there have been investigations on the growth and architecture of the fungal networks, their growth dynamics in space and time is still not fully understood. In this study, we monitor the growth dynamics of the plant-promoting filamentous fungus Serendipita indica for several days in a controlled environment within a microfluidic channel. We find that this species displays synchronized growth oscillations with the onset of sporulation and at a period of 3 hours. Quantifying this experimental synchronisation of oscillatory dynamics, we show that the synchronisation can be captured by the nearest neighbour Kuramoto model. Our analysis suggested the existence of millimetre-scale cell-cell communication across the fungi network. The microfluidic setup presented in this work may aid the future characterization of the molecular mechanisms of the cell-cell communication, which could in turn be exploited in order to control fungi growth and reproductive sporulation in soil and plant health management.

biophysics↗

bioRxiv2023

Bayesian Hidden Mark Interaction Model forDetecting Spatially Variable Genes inImaging-Based Spatially ResolvedTranscriptomics Data

Recent technology breakthroughs in spatially resolved transcriptomics (SRT) have enabled the comprehensive molecular characterization of cells whilst preserving their spatial and gene expression contexts. One of the fundamental questions in analyzing SRT data is the identification of spatially variable genes whose expressions display spatially correlated patterns. Existing approaches are built upon either the Gaussian process-based model, which relies on ad hoc kernels, or the energy-based Ising model, which requires gene expression to be measured on a lattice grid. To overcome these potential limitations, we developed a generalized energybased framework to model gene expression measured from imaging-based SRT platforms, accommodating the irregular spatial distribution of measured cells. Our Bayesian model applies a zero-inflated negative binomial mixture model to dichotomize the raw count data, reducing noise. Additionally, we incorporate a geostatistical mark interaction model with a generalized energy function, where the interaction parameter is used to identify the spatial pattern. Auxiliary variable MCMC algorithms were employed to sample from the posterior distribution with an intractable normalizing constant. We demonstrated the strength of our method on both simulated and real data. Our simulation study showed that our method captured various spatial patterns with high accuracy; moreover, analysis of a seqFISH dataset and a STARmap dataset established that our proposed method is able to identify genes with novel and strong spatial patterns.

bioinformatics↗

bioRxiv2023

SurfDock is a Surface-Informed Diffusion Generative Model for Reliable and Accurate Protein-ligand Complex Prediction

In the field of structure-based drug design, accurately predicting the binding conformation of ligands to proteins is a long-standing objective. Despite recent advances in deep learning yielding various methods for predicting protein-ligand complex structures, these AI-driven approaches frequently fall short of traditional docking methods in practice and often yield structures that lack physical and chemical plausibility. To overcome these limitations, we present SurfDock, an advanced geometric diffusion network, distinguished by its ability to integrate multiple protein representations including protein sequence, three-dimensional structural graphs, and surface-level details into its equivariant architecture. SurfDock employs a generative diffusion model on a non-Euclidean manifold, enabling precise optimization of molecular translations, rotations, and torsions for reliable binding poses generation. Complemented by a mixture density network for scoring using the same comprehensive representation, SurfDock achieves significantly improved docking success rates over all existing methods, excelling in both accuracy and adherence to physical constraints. Equipped with post-docking energy minimization as an optional feature, the plausibility of generated poses is further enhanced. Importantly, SurfDock demonstrates excellent generalizability to unseen proteins and extensibility to virtual screening tasks with state-of-the-art performance. We consider it a transformative contribution that could serve as an invaluable asset in structure-based drug design.

bioinformatics↗

bioRxiv2023

Comparison of chronic aerosol inhalation with combustible cigarette and e-cigarette on the psychiatric behaviors and neuroimmune profile in mice

With the worldwide use of electronic cigarettes (e-cigarettes) as a substitution for tobacco, the effects of e-cigarette vapor exposure on human health have been investigated. However, the comparison of long-term effects of aerosol inhalation with combustible cigarette and e-cigarette on the psychiatric behaviors has not been fully revealed. The present study examines the distinct effects of combustible cigarette and e-cigarette on anxiety, depression, cognition, and social behaviors. Here we found that the combustible cigarette induced the higher level of anxiety after long-term inhalation compared to the e-cigarettes with or without the tobacco flavor. Since the mechanism of action on the psychiatric behaviors entails the alterations on the neuroimmune-sensors and principal regulators such as glial cells, we further profiled the alterations of microglia and astrocytes by chronic inhalation of combustible tobacco cigarette, specifically the negative correlations between the IBA-1 level in the locus coeruleus (LC) and the latency to nest in VLT; as well as the GFAP level in LC and the open arm time in EPM were observed. Our current data provided an insight into the less impact of e-cigarettes on the anxiety-like behaviors and neuroimmune activation compared to combustible tobacco cigarettes which is not related to the flavor in e-cigarette, and the modulation on the neuroimmune signals in LC could be a therapeutic target for smoking-related anxiety.

animal behavior and cognition↗

bioRxiv2023

Reconstructing Spatial Transcriptomics at the Single-cell Resolution with BayesDeep

Spatially resolved transcriptomics (SRT) techniques have revolutionized the characterization of molecular profiles while preserving spatial and morphological context. However, most next-generation sequencing-based SRT techniques are limited to measuring gene expression in a confined array of spots, capturing only a fraction of the spatial domain. Typically, these spots encompass gene expression from a few to hundreds of cells, underscoring a critical need for more detailed, single-cell resolution SRT data to enhance our understanding of biological functions within the tissue context. Addressing this challenge, we introduce BayesDeep, a novel Bayesian hierarchical model that leverages cellular morphological data from histology images, commonly paired with SRT data, to reconstruct SRT data at the single-cell resolution. BayesDeep effectively model count data from SRT studies via a negative binomial regression model. This model incorporates explanatory variables such as cell types and nuclei-shape information for each cell extracted from the paired histology image. A feature selection scheme is integrated to examine the association between the morphological and molecular profiles, thereby improving the model robustness. We applied BayesDeep to two real SRT datasets, successfully demonstrating its capability to reconstruct SRT data at the single-cell resolution. This advancement not only yields new biological insights but also significantly enhances various downstream analyses, such as pseudotime and cell-cell communication.

bioinformatics↗

bioRxiv2023

Molecular and neuronal mechanisms governing sexually dimorphic prioritization of innate behaviors

Males and females display dimorphic innate behaviors and further prioritize them differently. How the sexually dimorphic behavioral prioritization is mediated is poorly understood. In Drosophila, around 60 pairs of pC1 neurons in males and 6 pairs in females control sexually dimorphic behaviors. We show that an increase of pC1 activity determines the sequential execution of behaviors such as sex, aggression, sleep, and feeding in a sex-specific way. We identify distinct subsets of pC1 neurons in both males and females that regulate different behaviors. We further discover diuretic hormone 44 (DH44) and acetylcholine (ACh) as co-transmitters in pC1 neurons. ACh promotes the execution of each behavior in both sexes, whereas DH44 functions in a sex-specific and activity-dependent manner to establish the sexually dimorphic behavioral outputs. These findings provide a framework for understanding the molecular and cellular mechanisms underlying sexually dimorphic prioritization of innate behaviors.

neuroscience↗

bioRxiv2023

Exploring the Brain Characteristics of Structure-informed Functional Connectivity through Graph Attention Network

Independent brain regions in neuroanatomy achieve a specific function through connections. As one of the significant morphological features of the cerebral cortex, previous studies have found significant differences in the structure and function of the cerebral gyri and sulci, which provides a basis for us to study the functional connectivity differences between these two anatomic parts. Previous studies using fully connected functional connectivity (FC) and structural connectivity (SC) matrices found significant differences in the perspective of region or connection in gyri and sulci. However, a clear issue is that previous studies have only analyzed the differences through either FC or SC, without effectively integrating both. Meanwhile, another nonnegligible issue is that the subcortical areas, involved in various tasks, have not been systematically explored with cortical regions. Due to the strong coupling between FC and SC, we use SC-informed FC to systematically explore the functional characteristics of gyri/sulci and subcortical regions by combining deep learning method with magnetic resonance imaging (MRI) technology. Specifically, we use graph attention network (GAT) to explore the important connections in the SC-informed FC through the Human Connectome Project (HCP) dataset. With high classification results of above 99%, we have successfully discovered important connections under different tasks. We have successfully explored the importance of different types of connections. In low threshold, gyri-gyri are the most important connections. With the threshold increasing, sub-sub become the most important. Gyri have a higher importance in functional connectivity than sulci. In the seven task states, these connections are mainly distributed among the front, subcortical, and occipital. This study provides a novel way to explore the characteristics of functional connectivity at the whole brain scale.

bioinformatics↗

bioRxiv2023

Multi-task machine learning reveals the neuroanatomy fingerprint of mental processing

Mental processing delineates the functions of human mind encompassing a wide range of motor, sensory, emotional, and cognitive processes, each of which is underlain by the neuroanatomical substrates. Identifying accurate representation of functional neuroanatomy substrates of mental processing could inform understanding of its neural mechanism. The challenge is that it is unclear whether a specific mental process possesses a functional neuroanatomy fingerprint, i.e., a unique and reliable pattern of functional neuroanatomy that underlies the mental process. To address this question, we utilized a multi-task deep learning model to disentangle the functional neuroanatomy fingerprint of seven different and representative mental processes including Emotion, Gambling, Language, Motor, Relational, Social, and Working Memory. Results based on the functional magnetic resonance imaging data of two independent cohorts of 1235 subjects from the US and China consistently show that each of the seven mental processes possessed a functional neuroanatomy fingerprint, which is represented by a unique set of functional activity weights of whole-brain regions characterizing the degree of each region involved in the mental process. The functional neuroanatomy fingerprint of a specific mental process exhibits high discrimination ability (93% classification accuracy and AUC of 0.99) with those of the other mental processes, and is robust across different datasets and using different brain atlases. This study provides a solid functional neuroanatomy foundation for investigating the neural mechanism of mental processing. One-Sentence SummaryThere exists a functional neuroanatomy fingerprint to underlie the mental process.

bioinformatics↗

bioRxiv2023

Paternal genomic resources from the YanHuang cohort suggested a Weakly-Differentiated Multi-source Admixture model for the formation of Hans founding ancestral lineages

The large-scale human genome revolution and rapidly advanced statistical innovation have updated our understanding of the fine-scale and complex genetic structure, the entire landscape of genetic diversity and the evolutionary trajectories of spatiotemporally different ancients and ethnolinguistically diverse modern populations. Recent ancient DNA research provided a detailed and complex admixture picture of ancient Europeans but limited insights into East Asians as the few available genomes. Y-chromosome variations in the male-specific regions, served as molecular archaeological tool, have unique evolutionary features that can be utilized to reconstruct the origin and subsequent interaction of ancient East Asian paternal lineages. We launched the YanHuang cohort using our designed highest-resolution capture sequencing panel to explore the detailed evolutionary trajectory of the Han Chinese, one of the largest ethnic groups in the world. We reported one of the largest uniparental genomic resources and observed multiple founding paternal lineages dominant in ancient western Eurasian, Siberian and East Asian participating in the formation of the gene pool of the Han Chinese. We identified fine-scale paternal genetic structure correlated with different patterns of ancient population interaction and geographical mountain barriers (Qinling-Huaihe line and Nanling Mountains), suggesting isolation-enhanced and admixture-introduced genetic differentiation enhanced the complexity of the Han Chinese genomic diversity. We observed a strong direct correlation between the frequency of multiple founding lineages of the Han Chinese and the proportion of subsistence-related ancestry sources related to western pastoralists, Holocene Mongolian Plateau people and ancient East Asians, reflecting the ancient migration events contributed to our identified patterns of Chinese paternal genomic diversity. We finally provided one novel and the most plausible admixture-by-admixture model, the Weakly-Differentiated Multi-Source Admixture model, as the major genetic mechanism to illuminate our observed pattern of complex interactions of multiple ancestral sources and landscape of the Han Chinese paternal genetic diversity. Generally, we presented one large-scale uniparental genomic resource from the YanHuang cohort, portrayed one novel admixture formation model and presented the entire genomic landscape with multiple ancestral sources related to ancient herders, hunter-gatherers and farmers who participated in the ancestral formation of the Han Chinese.

evolutionary biology↗

bioRxiv2023

A high-performance brain-sentence communication designed for logosyllabic language

Many severe neurological diseases, such as stroke and amyotrophic lateral sclerosis, can impair or destroy the ability of verbal communication. Recent advances in brain-computer interfaces (BCIs) have shown promise in restoring communication by decoding neural signals related to speech or motor activities into text. Existing research on speech neuroprosthesis has predominantly focused on alphabetic languages, leaving a significant gap of logosyllabic languages such as Mandarin Chinese which are spoken by more than 15% of the world population. Logosyllabic languages pose unique challenges to brain-to-text decoding due to extended character sets (e.g., 50,000+ for Mandarin Chinese) and complex mapping between characters and pronunciation. To address these challenges, we established a speech BCI designed for Mandarin, decoding speech-related stereoelectroencephalography (sEEG) signals into coherent sentences. We leverage the unique acoustic features of Mandarin Chinese syllables, constructing prediction models for syllable components (initials, tones, and finals), and employ a language model to resolve pronunciation to character ambiguities according to the semantic context. This method leads to a high-performance decoder with a median character accuracy of 71.00% over the full character set, demonstrating huge potentials for clinical application. To our knowledge, we are the first to report brain-to-sentence decoding for logosyllabic languages over full character set with a large intracranial electroencephalography dataset.

neuroscience↗