Biology subjects

Xia, M.

Publications and source records attributed to Xia, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

PTTG1-Mediated Pericyte Dysfunction Drives Diabetes-Induced Microvascular Dysfunction

BackgroundPericytes are crucial for the development, stabilization, and functional regulation of microvasculature, especially in the retina. In diabetic retinopathy (DR), early loss of pericytes is a key event that drives microvascular dysfunction. Despite their critical role, the mechanisms underlying the functional heterogeneity of pericytes in DR remain poorly understood, impeding the development of effective therapeutic strategies. MethodsWe employed single-cell RNA sequencing to construct a comprehensive single- cell atlas of non-diabetic and diabetic retinas. Using bioinformatic clustering and subcluster analysis, we identified a specific pericyte subcluster associated with diabetic microvascular complications. Differential gene expression analysis and immunofluorescence validation highlighted PTTG1 as a potential key regulator of pericyte dysfunction. To investigate its functional role, we emplyed CRISPR/Cas9 and adenoviral vectors to modulate PTTG1 expression in vitro and in vivo. Combined transcriptomic and metabolomic approaches were used to explore the mechanistic pathways through which PTTG1 influences pericyte biology and vascular function. ResultsWe identified a novel pericyte subcluster characterized by elevated expression of PTTG1, which was strongly correlated with diabetic microvascular dysfunction. Silencing PTTG1 using CRISPR/Cas9 and siRNA in vitro mitigated pericyte dysfunction under high- glucose conditions. Targeted knockdown of PTTG1 using viral vectors improved retinal vascular integrity and reduced neovascularization in diabetic mice. Transcriptomic and untargeted metabolomic analyses revealed that PTTG1 knockdown reprogrammed pericyte energy metabolism by modulating glycolysis pathway genes, reducing oxidative stress, and restoring pericyte function, ultimately alleviating microvascular dysfunction in DR. ConclusionsPTTG1 plays a critical role in regulating pericyte dysfunction and maintaining vascular homeostasis in diabetic retinopathy. By modulating key metabolic pathways and pericyte phenotypes, PTTG1 represents a promising therapeutic target for treating diabetic microvascular complications. These insights offer a novel molecular framework for developing targeted therapies aimed at restoring retinal vascular health in diabetic patients.

molecular biology↗

bioRxiv2024

D-lactate derived from intestinal bacteria drives lysine D-lactylation to modulate transcription in liver cells

Emerging evidence indicates that the accumulated D-lactate (D-la) from intestinal bacteria induces diverse effects in human intestinal injury diseases. However, its regulatory mechanism and functional consequence remain unclear. Here, we show that the secreted D-la induces lysine D-lactylation (K-Dla) to modulate transcription in host cells. We uncover K-Dla in HepG2 cells stimulated by D-la from E. coli secretions. Then, we confirm the occurrence of D-la-driven K-Dla by four orthogonal approaches. We further validate that the existence of K-Dla in organisms by detecting the mouse liver and human intestinal tissue. Besides, we demonstrate a SCOT1-catalyzed biosynthetic pathway of D-lactyl-CoA, serving as a key donor for K-Dla. Next, we identify the K-Dla landscape with 2895 sites and further suggest the regulation of histone K-Dla in transcription by MNase ChIP-seq and RNA-seq assays. Finally, we show the potential effect of K-Dla on inhibiting the hepatocellular carcinoma cell proliferation. In summary, we report that the secreted D-la can induce K-Dla to regulate transcription, providing a new insight into the function of D-la secreted by gut microbiota and the effect of protein chemical modifications induced by bacterial secretions.

molecular biology↗

bioRxiv2024

Individual-specific strategies inform category learning

Categorization is an essential task for sensory perception. Individuals learn category labels using a variety of strategies to ensure that sensory signals, such as sounds or images, can be assigned to proper categories. Categories are often learned on the basis of extreme examples, and the boundary between categories can differ among individuals. The trajectories for learning also differ among individuals, as different individuals rely on different strategies, such as repeating or alternating choices. However, little is understood about the relationship between individual learning trajectories and learned categorization. To study this relationship, we trained mice to categorize auditory stimuli into two categories using a two-alternative forced choice task. Because the mice took several weeks to learn the task, we were able to quantify the time course of individual strategies and how they relate to how mice categorize stimuli around the categorization boundary. Different mice exhibited different trajectories while learning the task. Mice displayed preferences for a specific category, manifested by a choice bias in their responses, but this bias drifted with learning. We found that this drift in choice bias correlated with variability in the category boundary for sounds with ambiguous category membership. Next, we asked how stimulus-independent, individual-specific strategies informed learning. We found that the tendency to repeat choices, which is a form of perseveration, contributed to long-term learning. These results indicate that long-term trends in individual strategies during category learning affect learned category boundaries.

neuroscience↗

bioRxiv2024

GABAergic neuron dysregulation in a human neurodevelopmental model for major psychiatric disorders

"GABA dysfunction" is a major hypothesis for the biological basis of schizophrenia with indirect supporting evidence from human post-mortem brain and genetic studies. Patient-derived induced pluripotent stem cells (iPSCs) have emerged as a valuable platform for modeling psychiatric disorders, and previous modeling has revealed glutamatergic synapse deficits. Whether GABAergic synapse properties are affected in patient-derived human neurons and how this impacts neuronal network activity remain poorly understood. Here we optimized a protocol to differentiate iPSCs into highly enriched ganglionic eminence-like neural progenitors and GABAergic neurons. Using a collection of iPSCs derived from patients of psychiatric disorders carrying a Disrupted-in-Schizophrenia 1 (DISC1) mutation and their unaffected family member, together with respective isogenic lines, we identified mutation-dependent deficits in GABAergic synapse formation and function, a phenotype similar to that of mutant glutamatergic neurons. However, mutant glutamatergic and GABAergic neurons contribute differentially to neuronal network excitability and synchrony deficits. Finally, we showed that GABAergic synaptic transmission is also defective in neurons derived from several idiopathic schizophrenia patient iPSCs. Transcriptome analysis further showed some shared gene expression dysregulation, which is more prominent in DISC1 mutant neurons. Together, our study supports a functional GABAergic synaptic deficit in major psychiatric disorders.

neuroscience↗

bioRxiv2024

Genetic diversity analysis of main agronomic traits and ISSR markers in 35 ornamental rape germplasm resources

Rape (Brassica napus L.) is a major oil crop in our country, valued for its oil and ornamental uses. This study analyzed 35 ornamental rape germplasm resources from different origins to examine differences in agronomic traits and molecular markers. Nine agronomic traits were assessed in the field for variability, correlation, principal component analysis, and cluster analysis. Genetic diversity was analyzed using microsatellite (ISSR) markers and the unweighted pair group method with arithmetic mean (UPGMA). Our findings revealed a notable average coefficient of variation of 22.59% across the nine agronomic traits, with flower color exhibiting the highest variability and corolla width the least. The observed range of variation spanned from 9.24% to 83.38%, the correlation among these traits was generally low, with a mere 13.9% demonstrating significant correlations. The four principal components accounted for an impressive 84.62% of the cumulative contribution rate, while the genetic similarity, as gauged by eight ISSR primers, varied from 0.675 to 0.980. Most strikingly, we observed that plants from the same geographical region displayed molecular-level differences, underscoring the rich genetic diversity inherent in the 35 ornamental rape resources under study. Employing UPGMA cluster analysis on the primary agronomic traits and ISSR molecular markers, the 35 ornamental rape resources were categorized into seven and four distinct groups, respectively. Although the clustering outcomes from these two methodologies did not align perfectly, they served to complement each other. Collectively, these insights offer a theoretical framework for the innovation of ornamental rape germplasm resources and the cultivation of novel varieties.

genetics↗

bioRxiv2024

Scalable Hypothalamic Arcuate Neuron Differentiation from Human Pluripotent Stem Cells Suitable for Modeling Metabolic and Reproductive Disorders

The hypothalamus, composed of several nuclei, is essential for maintaining our bodys homeostasis. The arcuate nucleus (ARC), located in the mediobasal hypothalamus, contains neuronal populations with eminent roles in energy and glucose homeostasis as well as reproduction. These neuronal populations are of great interest for translational research. To fulfill this promise, we used a robotic cell culture platform to provide a scalable and chemically defined approach for differentiating human pluripotent stem cells (hPSCs) into pro-opiomelanocortin (POMC), somatostatin (SST), tyrosine hydroxylase (TH) and gonadotropin-releasing hormone (GnRH) neuronal subpopulations with an ARC-like signature. This robust approach is reproducible across several distinct hPSC lines and exhibits a stepwise induction of key ventral diencephalon and ARC markers in transcriptomic profiling experiments. This is further corroborated by direct comparison to human fetal hypothalamus, and the enriched expression of genes implicated in obesity and type 2 diabetes (T2D). Genome-wide chromatin accessibility profiling by ATAC-seq identified accessible regulatory regions that can be utilized to predict candidate enhancers related to metabolic disorders and hypothalamic development. In depth molecular, cellular, and functional experiments unveiled the responsiveness of the hPSC-derived hypothalamic neurons to hormonal stimuli, such as insulin, neuropeptides including kisspeptin, and incretin mimetic drugs such as Exendin-4, highlighting their potential utility as physiologically relevant cellular models for disease studies. In addition, differential glucose and insulin treatments uncovered adaptability within the generated ARC neurons in the dynamic regulation of POMC and insulin receptors. In summary, the establishment of this model represents a novel, chemically defined, and scalable platform for manufacturing large numbers of hypothalamic arcuate neurons and serves as a valuable resource for modeling metabolic and reproductive disorders.

developmental biology↗

bioRxiv2024

Methyltransferase DNMT3B promotes colorectal cancer cell proliferation by inhibiting PLCG2

BackgroundAberrant DNA methylation patterns in the promoter region of PLCG2 have been associated with dysregulated signaling pathways and cellular functions. Its role in colorectal cancer cells is still unknown. MethodsqRT-PCR was used to examine DNMT3B expression in colorectal cancer. Western blot and immunohistochemistry were used to analyze DNMT3B and PLCG2 protein levels in colorectal tissues and cell lines. The cell counting kit-8 and colony experiments were used to identify the proliferation of colorectal cancer cells. Methylation-specific PCR (MSP) and bisulfite-sequencing PCR (BSP) was used to measure DNA methylation levels. ResultsDNMT3B is overexpressed in colorectal cell in TCGA datasets and Kaplan-Meier plots. DNMT3B is significantly overexpressed in tumor tissues compared to adjacent non-tumor tissues. Western blotting results demonstrated high expression of DNMT3B in tumor tissues. Compared to normal colonic epithelial cells, colorectal cancer cell lines exhibited elevated levels of PLCG2 methylation. oePLCG2 effectively prevented the in vivo xenograft tumor growth of colorectal cancer. ConclusionsPLCG2 is identified as a key downstream regulatory protein of DNMT3B in colorectal cancer. DNMT3B Inhibits PLCG2 transcription through methylation of the PLCG2 promoter region. DNMT3B controls colorectal cancer cell proliferation through the PLCG2, which is useful for creating therapeutic approaches that target PLCG2 expression for the treatment of colorectal cancer.

cancer biology↗

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

Comparison of Wild-Type and High-risk PNPLA3 variants in a Human Biomimetic Liver Microphysiology System for Metabolic Dysfunction-associated Steatotic Liver Disease Precision Therapy

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a worldwide health epidemic with a global occurrence of approximately 30%. The pathogenesis of MASLD is a complex, multisystem disorder driven by multiple factors including genetics, lifestyle, and the environment. Patient heterogeneity presents challenges for developing MASLD therapeutics, creation of patient cohorts for clinical trials and optimization of therapeutic strategies for specific patient cohorts. Implementing pre-clinical experimental models for drug development creates a significant challenge as simple in vitro systems and animal models do not fully recapitulate critical steps in the pathogenesis and the complexity of MASLD progression. To address this, we implemented a precision medicine strategy that couples the use of our liver acinus microphysiology system (LAMPS) constructed with patient-derived primary cells. We investigated the MASLD-associated genetic variant PNPLA3 rs738409 (I148M variant) in primary hepatocytes, as it is associated with MASLD progression. We constructed LAMPS with genotyped wild type and variant PNPLA3 hepatocytes together with key non-parenchymal cells and quantified the reproducibility of the model. We altered media components to mimic blood chemistries, including insulin, glucose, free fatty acids, and immune activating molecules to reflect normal fasting (NF), early metabolic syndrome (EMS) and late metabolic syndrome (LMS) conditions. Finally, we investigated the response to treatment with resmetirom, an approved drug for metabolic syndrome-associated steatohepatitis (MASH), the progressive form of MASLD. This study using primary cells serves as a benchmark for studies using "patient biomimetic twins" constructed with patient iPSC-derived liver cells using a panel of reproducible metrics. We observed increased steatosis, immune activation, stellate cell activation and secretion of pro-fibrotic markers in the PNPLA3 GG variant compared to wild type CC LAMPS, consistent with the clinical characterization of this variant. We also observed greater resmetirom efficacy in PNPLA3 wild type CC LAMPS compared to the GG variant in multiple MASLD metrics including steatosis, stellate cell activation and the secretion of pro-fibrotic markers. In conclusion, our study demonstrates the capability of the LAMPS platform for the development of MASLD precision therapeutics, enrichment of patient cohorts for clinical trials, and optimization of therapeutic strategies for patient subgroups with different clinical traits and disease stages.

cell biology↗

bioRxiv2024

Decoding Missense Variants by Incorporating Phase Separation via Machine Learning

Computational models have made significant progress in predicting the effect of protein variants. However, deciphering numerous variants of unknown significance (VUS) located within intrinsically disordered regions (IDRs) remains challenging. To address this issue, we introduced phase separation (PS), which is tightly linked to IDRs, into the investigation of missense variants. Phase separation is vital for multiple physiological processes. By leveraging missense variants that alter phase separation propensity, we developed a machine learning approach named PSMutPred to predict the impact of missense mutations on phase separation. PSMutPred demonstrated robust performance in predicting missense variants that affect natural phase separation. In vitro experimental findings further underscore its validity. By applying PSMutPred on over 522,000 ClinVar missense variants, it significantly contributes to decoding the pathogenesis of disease variants, especially those in IDRs. Our work provides unique insights into the understanding of a vast number of VUSs in IDRs, thereby expediting clinical interpretation and diagnosis of disease variants.

bioinformatics↗

bioRxiv2024

Normative growth modeling of brain morphology reveals neuroanatomical heterogeneity and biological subtypes in children with ADHD

BackgroundNeuroimaging studies suggest substantial individual heterogeneity in brain phenotypes in attention-deficit/hyperactivity disorder (ADHD). However, how these individual-level brain phenotypes contribute to the identification of ADHD biotypes and whether these biotypes have different treatment outcomes and neurobiological underpinnings remain largely unknown. MethodsWe collected multisite, high-quality structural magnetic resonance imaging data from 1,006 children aged 6-14 years, including 351 children with ADHD and 655 typically developing children. Normative growth models of cortical thickness were established for 219 regions in the typically developing children. Individual-level deviations from these normal references were quantified and clustered to identify ADHD biotypes. We validated the replicability and generalizability of the ADHD biotypes using two independent datasets and evaluated the associations of the biotypes with symptomatic, cognitive, and gene expression profiles, as well as follow-up treatment outcomes. FindingsNo more than 10% of children with ADHD had extreme deviations in cortical thickness in a single region, suggesting high heterogeneity among individuals with ADHD. On the basis of the brain deviation maps, we discovered two robust ADHD biotypes, an infra-normal subtype with cortical thinning associated with ADHD symptoms and a supranormal subtype with cortical thickening associated with cognition. Patients with the infra-normal subtype responded better to methylphenidate than to atomoxetine, although both subtypes showed treatment efficacy. Brain deviations in the infra-normal subtype were explained by the expression levels of genes enriched in presynaptic and axonal development and polygenic risk of ADHD. InterpretationWe identified anatomically distinct, clinically valuable, and biologically informed ADHD subtypes, providing insight into the neurobiological basis of clinical heterogeneity and facilitating a personalized medication strategy for ADHD patients. Panel: Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSubstantial individual heterogeneity in brain phenotypes in attention-deficit/hyperactivity disorder (ADHD) motivates the need to discover homogeneous biotypes. We searched PubMed for research articles on ADHD biotypes using brain MRI published before December 1, 2023, using the search terms ((attention deficit hyperactivity disorder [Title/Abstract]) OR (ADHD [Title/Abstract])) AND ((subtypes [Title/Abstract]) OR (subgroups [Title/Abstract]) OR (subtyping [Title/Abstract])) AND ((MRI [Title/Abstract]) OR (neuroimaging [Title/Abstract]) OR (brain [Title/Abstract])) without language restrictions. Of the eight included studies, two identified ADHD biotypes using structural morphology, four used functional activity, and two used multimodal features. However, none of these studies considered the developmental effect of the brain phenotypes, examined treatment response, or investigated the genetic correlates of the biotypes. Added value of this studyThis study is the first to use individualized brain measures extracted from normative models to investigate ADHD biotypes in a large sample of more than 1,000 children. We identified two reproducible ADHD biotypes, characterized by distinct symptomatic, cognitive, and gene expression profiles, as well as differential treatment responses. This study advances our understanding of the neurobiological basis underlying the clinical heterogeneity of ADHD and highlights the critical need to discover ADHD biotypes using an unbiased and individualized approach. Implications of all the available evidenceThis study revealed remarkable neuroanatomical heterogeneity in ADHD patients and identified anatomically distinct, clinically valuable, and biologically informed ADHD biotypes. Our findings have potential value for the investigation of data-driven biotypes to evaluate treatment efficacy and facilitate personalized treatment. We also highlight the need for future studies to move beyond the understanding of ADHD solely based on the "average patient" perspective.

neuroscience↗

bioRxiv2024

The first discovery of SFTSV in the Centre of Metropolitan Beijing, China

Severe fever with thrombocytopenia virus (SFTSV), an emerging tick-borne bandavirus, poses a significant public health threat in rural China. Since 2021, an increase in local cases has been noted in the rural-urban fringe surrounding Beijing. This study aimed to assess the formation of natural foci in urban areas by conducting a field survey of ticks and hedgehogs from Beijings second to fifth ring roads. Our survey revealed a diverse tick population in city parks, including the major SFTSV vector, H. longicornis. Parthenogenetic H. longicornis, known for its role in rapid SFTSV spread, was identified in key locations like Beihai Park and Taoranting Park, near the Forbidden City. Notably, high SFTSV seroprevalence and RNA prevalence were found in hedgehogs and parasitic ticks in the center of Beijing. These findings highlight the circulation of SFTSV in central Beijing, underscoring the need for urgent attention and enhanced surveillance measures.

microbiology↗

bioRxiv2024

Topographic, cognitive, and neurobiological profiling of the interdependent structural and functional connectome in the human brain

The structural connectome (SC) is tightly coupled to the functional connectome (FC) in the human brain. Most previous related studies have modeled and analyzed SC or FC as isolated brain networks. However, challenges remain in modeling the interdependent structural-functional connectome and elucidating its cognitive implications and molecular underpinnings. Here, we present a multilayer connectome model composed of SC and FC components and further characterize their interacting topological properties. We found that the interdependent connectome is topographically heterogeneous, with the transmodal cortex exhibiting greater modular variability across layers. This spatial topography reflects cortical hierarchy and evolution and shows high test-retest reliability, reproducibility, and heritability. The interdependent connectome contributes to high-order cognitive processes and is associated with multiple neurotransmitter systems and transcriptional signatures of synaptic transmission. Our results provide insights into the nontrivial interdependencies of SC and FC, highlighting their cognitive significance and the molecular mechanisms underlying the connectome of connectomes.

neuroscience↗

bioRxiv2023

Ependymocytes control cerebrospinal fluid flow to the peripheral organs through periaxonal pathway

Mechanisms controlling movement of the CSF through the central canal towards the peripheral nerves are poorly characterized. We found that fluorescent dyes injected into cisterna magna are carried with cerebrospinal fluid (CSF) through the central canal and peripheral nerves to the peripheral organs such as liver, and pancreas. We also found close connection between spinal axons and ependymocytes, suggesting synaptic interactions. Serotonin, acting through the 5-HT2B receptors abundantly expressed in ependymal cells, trigger Ca2+ signal that induces polymerization of cytoskeleton protein F-actin, consequently reducing the volume of ependymocytes. Shrinkage of the latter opens one-way route to facilitate CSF outflow from the central canal into the spinal cord parenchyma and peripheral nerves. In liver, CSF is received by stellate cells. Ependymal control over transfer of the CSF from central canal to peripheral organs by the periaxonal space (PAS) represents a novel mechanism dynamically connecting the CNS with the periphery. In briefEpendymocytes control CSF flow from CNS to peripheral organs by periaxonal pathway, and serotonin evokes the ependymal shrinkage by the aggregation of F-actin. HighlightsEpendymocytes control CSF flow from central canal to peripheral organs; CSF flows through the peripheral periaxonal space to reach the peripheral organs; Serotonin makes ependymocytes shrunk by 5-HT2B receptor-mediated Ca2+ signaling and F-actin polymerization; The hepatic stellate cells are potential collectors of CSF in the liver.

neuroscience↗

bioRxiv2023

Functional connectome through the human life span

The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimers disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.

neuroscience↗

bioRxiv2023

Development of Sensorimotor-Visual Connectome Gradient at Birth Predicts Cognitive Outcomes at 2 Years of Age

Functional connectome gradients represent fundamental brain organizing principles. Here, we investigate the maturation of the macroscopic connectome gradients in a task-free functional MRI dataset consisting of 39 preterm and term babies aged 31-42 postmenstrual weeks and its connection with postnatal cognitive growth. We show that the principal sensorimotor-to-visual gradient is present in baby connectomes around 35.6 postmenstrual weeks and continuously develops towards a more term-like pattern. The gradients global topographical structure undergoes progressive maturation with age, characterized by increases in explanation ratio, gradient range and gradient variation. The development of focal gradients is mostly localized in primary regions serving sensory, motor and visual functions. Machine learning approaches revealed that the connectome gradient at birth significantly predicts individual cognitive outcomes at 2-y follow-up. These findings highlight the early emerging rules of functional connectome gradients and have implications for understanding how the connectome gradients at birth underlies cognitive growth in later life. HighlightsO_LISensorimotor-to-visual gradient is present around 35.6 postmenstrual weeks C_LIO_LIGlobal gradient structure undergoes substantial changes during the third trimester C_LIO_LIRegional gradient develops mostly in primary sensory, motor, and visual regions C_LIO_LISensorimotor-to-visual gradient at birth predicts cognitive outcomes at age 2 C_LI

neuroscience↗

bioRxiv2023

No evidence for enhanced disease with polyclonal SARS-CoV-2 antibody in the ferret model.

Since SARS-CoV-2 emerged in late 2019, it spread from China to the rest of the world. An initial concern was the potential for vaccine- or antibody-enhanced disease (AED) as had been reported with other coronaviruses. To evaluate this, we first developed a ferret model by exposing ferrets to SARS-CoV-2 by either mucosal inoculation (intranasal/oral) or inhalation using a small particle aerosol. Mucosal inoculation caused a mild fever and weight loss that resolved quickly; inoculation via either route resulted in virus shedding detected in the nares, throat, and rectum for 7-10 days post-infection. To evaluate the potential for AED, we then inoculated groups of ferrets intravenously with 0.1, 0.5, or 1 mg/kg doses of a human polyclonal anti-SARS-CoV-2 IgG from hyper-immunized transchromosomic bovines (SAB-185). Twelve hours later, ferrets were challenged by mucosal inoculation with SARS-CoV-2. We found no significant differences in fever, weight loss, or viral shedding after infection between the three antibody groups or the controls. Signs of pathology in the lungs were noted in infected ferrets but no differences were found between control and antibody groups. The results of this study indicate that healthy, young adult ferrets of both sexes are a suitable model of mild COVID-19 and that low doses of specific IgG in SAB-185 are unlikely to enhance the disease caused by SARS-CoV-2.

microbiology↗

bioRxiv2023

Longitudinal associations between language network characteristics in the infant brain and school-age reading abilities are mediated by early-developing phonological skills

Reading acquisition is a prolonged learning process relying on language development starting in utero. Behavioral longitudinal studies reveal prospective associations between infant language abilities and preschool/kindergarten phonological development that relates to subsequent reading performance. While recent pediatric neuroimaging work has begun to characterize the neural network underlying language development in infants, how this neural network scaffolds long-term language and reading acquisition remains unknown. We addressed this question in a 7-year longitudinal study from infancy to school-age. Seventy-six infants completed resting-state fMRI scanning, and underwent standardized language assessments in kindergarten. Of this larger cohort, forty-one were further assessed on their emergent word reading abilities after receiving formal reading instructions. Hierarchical clustering analyses identified a modular infant language network in which functional connectivity (FC) of the inferior frontal module prospectively correlated with kindergarten-age phonological skills and emergent word reading abilities. These correlations were obtained when controlling for infant age at scan, nonverbal IQ and parental education. Furthermore, kindergarten-age phonological skills mediated the relationship between infant FC and school-age reading abilities, implying a critical mid-way milestone for long-term reading development from infancy. Overall, our findings illuminate the neurobiological mechanisms by which infant language capacities could scaffold long-term reading acquisition. HighlightsO_LIClustering analyses revealed a modular language network in the infant brain C_LIO_LIInfant language network characteristics associate with school-age reading outcomes C_LIO_LIThese longitudinal associations are mediated by kindergarten-age phonological skills C_LI

neuroscience↗