Biology subjects

Cao, S.

Publications and source records attributed to Cao, S..

At least 127 records · Page 7Linked to original sources

bioRxiv2021

Generation of potent cellular and humoral immunity against SARS-CoV-2 antigens via conjugation to a polymeric glyco-adjuvant

The SARS-CoV-2 virus has caused an unprecedented global crisis, and curtailing its spread requires an effective vaccine which elicits a diverse and robust immune response. We have previously shown that vaccines made of a polymeric glyco-adjuvant conjugated to an antigen were effective in triggering such a response in other disease models and hypothesized that the technology could be adapted to create an effective vaccine against SARS-CoV-2. The core of the vaccine platform is the copolymer p(Man-TLR7), composed of monomers with pendant mannose or a toll-like receptor 7 (TLR7) agonist. Thus, p(Man-TLR7) is designed to target relevant antigen-presenting cells (APCs) via mannose-binding receptors and then activate TLR7 upon endocytosis. The p(Man-TLR7) construct is amenable to conjugation to protein antigens such as the Spike protein of SARS-CoV-2, yielding Spike-p(Man-TLR7). Here, we demonstrate Spike-p(Man-TLR7) vaccination elicits robust antigen-specific cellular and humoral responses in mice. In adult and elderly wild-type mice, vaccination with Spike-p(Man-TLR7) generates high and long-lasting titers of anti-Spike IgGs, with neutralizing titers exceeding levels in convalescent human serum. Interestingly, adsorbing Spike-p(Man-TLR7) to the depot-forming adjuvant alum, amplified the broadly neutralizing humoral responses to levels matching those in mice vaccinated with formulations based off of clinically-approved adjuvants. Additionally, we observed an increase in germinal center B cells, antigen-specific antibody secreting cells, activated T follicular helper cells, and polyfunctional Th1-cytokine producing CD4+ and CD8+ T cells. We conclude that Spike-p(Man-TLR7) is an attractive, next-generation subunit vaccine candidate, capable of inducing durable and robust antibody and T cell responses.

bioengineering↗

bioRxiv2021

The Origin of Bladder Cancer from Mucosal Field Effects

We used whole-organ mapping to study loco-geographic molecular changes in evolution of human bladder cancer from mucosal field effects. The integrative multi-platform analyses based on genome-wide RNA sequencing, methylation, copy number variations, and whole exome sequencing identified over 100 dysregulated canonical pathways involving immunity, tissue differentiation and transformation as initiators of bladder carcinogenesis. Widespread dysregulation of interleukin signaling was the dominant change signifying the important role of inflammation and immunity in the incipient phases of urothelial carcinogenesis. The analyses of mutational patterns identified three types of mutations based on their geographic distribution and variant allele frequencies. The most common were low frequency subclonal mutations restricted to individual mucosal samples which were the progeny of their respective uroprogenitor cells. The two additional types of mutations were associated with clonal expansion and involved large areas of bladder mucosa. The first group referred to as mutations, showed a low mutational frequency across the mucosa. The second group referred to as {beta} mutations increased in their frequencies with disease progression and a large proportion of them represented mutated transcriptional regulators controlling proliferation. Time modeling revealed that bladder carcinogenesis is spanning 10-15 years and can be divided into dormant and progressive phases. The progressive phase lasted 1-2 years and was primarily driven by {beta} mutations with high proliferative advantage. This is the first detailed molecular characterization of mucosal field effects initiating bladder carcinogenesis on the whole-organ scale. It provides novel insights into incipient phases of bladder carcinogenesis and biomarkers for early detection of bladder cancer as well as targets for preventive therapies.

genomics↗

bioRxiv2021

Germline variants that influence the tumor immune microenvironment also drive response to immunotherapy

With the continued promise of immunotherapy as an avenue for treating cancer, understanding how host genetics contributes to the tumor immune microenvironment (TIME) is essential to tailoring cancer screening and treatment strategies. Approaches that intersect SNP modifiers of molecular phenotype, such as gene expression, with disease phenotypes have shown promise for implicating causal genetic factors. Here we evaluated 194 literature-curated TIME associations and 890 associations detected with 157 immune phenotype (IP) components found using genotypes from over 8,000 individuals in The Cancer Genome Atlas. Of these 1084, 233 associations comprising 219 unique TIME-SNPs were also cancer relevant, associating with cancer risk, survival, and/or immunotherapy treatment response. Many cancer relevant TIME-SNPS overlapped regions of active transcription, and were associated with gene expression in specific immune cell subsets, such as macrophages and dendritic cells. TIME-SNPs associated with cancer risk and response to immunotherapy implicated genes involved in antigen presentation, especially by antigen presenting cells. The strongest associations with survival were with PD-L1 and CTLA-4, suggesting that SNPs modifying the potential for immune evasion could contribute to disease progression. To assess whether our approach could reveal novel cancer immunotherapy targets, we inhibited CTSS, a gene implicated by cancer risk and immunotherapy response-associated TIME-SNPs; CTSS inhibition resulted in slowed tumor growth and extended survival in vivo. These results validate the potential of cancer relevant TIME-SNPs to implicate target genes for countering immune suppressive characteristics of the TIME and set the stage for future host genetics analysis integrating germline variation and TIME characteristics. SignificanceA systematic screen for common germline variants associated with the tumor immune microenvironment across > 8000 tumors reveals novel cancer risk factors and targets for immunotherapy.

cancer biology↗

bioRxiv2021

Intermittent Fasting Enhances Hippocampal Npy Expression to Promote Neurogenesis Following Traumatic Brain Injury

Interventions for preventing cognitive dysfunction post traumatic brain injury (TBI) is limited. Given that adult hippocampal neurogenesis (AHN) after brain injury contributes to cognitive recovery, and that the AHN is potentially affected by nutritional factors, we asked whether fasting could promote AHN and thus ameliorates cognitive defects after TBI. Here we show that a one-month intermittent fasting (IF) regimen enhanced proliferation of neural stem cells (NSCs) in the subgranular zone (SGZ) of hippocampus 3 days post TBI, as well as improved cognitive performance in Morris water maze (MWM) test. Furthermore, an increase in hippocampal Npy expression was detected in IF group after injury, compared to the mice fed ad libitum (AL), and locally knock-down of Npy in vivo attenuated the aforementioned effects of IF in TBI. These findings suggest that IF promotes AHN following TBI by a mechanism involving enhancement of Npy expression, which may offer novel interventions that might prevent cognitive dysfunction caused by injury.

neuroscience↗

bioRxiv2021

Polymersomes decorated with SARS-CoV-2 spike protein receptor binding domain elicit robust humoral and cellular immunity

A diverse portfolio of SARS-CoV-2 vaccine candidates is needed to combat the evolving COVID-19 pandemic. Here, we developed a subunit nanovaccine by conjugating SARS-CoV-2 Spike protein receptor binding domain (RBD) to the surface of oxidation-sensitive polymersomes. We evaluated the humoral and cellular responses of mice immunized with these surface-decorated polymersomes (RBDsurf) compared to RBD-encapsulated polymersomes (RBDencap) and unformulated RBD (RBDfree), using monophosphoryl lipid A-encapsulated polymersomes (MPLA PS) as an adjuvant. While all three groups produced high titers of RBD-specific IgG, only RBDsurf elicited a neutralizing antibody response to SARS-CoV-2 comparable to that of human convalescent plasma. Moreover, RBDsurf was the only group to significantly increase the proportion of RBD-specific germinal center B cells in the vaccination-site draining lymph nodes. Both RBDsurf and RBDencap drove similarly robust CD4+ and CD8+ T cell responses that produced multiple Th1-type cytokines. We conclude that multivalent surface display of Spike RBD on polymersomes promotes a potent neutralizing antibody response to SARS-CoV-2, while both antigen formulations promote robust T cell immunity.

bioengineering↗

bioRxiv2021

CliP: subclonal architecture reconstruction of cancer cells in DNA sequencing data using a penalized likelihood model

Tumor subclonal architecture shapes cancer evolution, yet subclonal reconstruction from bulk sequencing remains difficult to scale due to computational cost and model complexity. We present CliPP, a penalized-likelihood framework that jointly estimates cellular prevalence with pairwise fusion penalties, automatically identifying subclones without requiring extensive priors. Across simulations and 2,778 whole-genome tumors with external consensus reconstructions, CliPP achieves consistently good performances when compared to state-of-the-art approaches while providing substantial runtime reductions. Applied to 7,000+ tumors across >30 cancer types, CliPP quantifies pervasive subclonality and delineates cohort-level subclone landscapes. CliPP enables fast, reproducible large-scale subclonal analysis and is freely available to the community through GitHub and a shiny app.

bioinformatics↗

bioRxiv2021

Towards the NMR solution Structure and the Dynamics of the C-terminal Region of APOL1 and its G1, G2 Variants with a Membrane Mimetic

Secreted apolipoprotein L1 (APOL1) is well known as an innate immune factor, protecting against African trypanosomiasis. The intracellular form has multiple functions, including regulating autophagy, intracellular vesicle trafficking, and ion channel activity. The APOL1 protein (G0) has two common variants (denoted G1 and G2) in the C-terminal region and are associated with a high risk of chronic kidney disease (CKD) and progression to end-stage kidney disease. Our previous studies using molecular modeling suggested that APOL1 G1 and G2 stabilize an autoinhibited state of the C-terminus, leading to impaired intracellular interactions with SNARE proteins. To characterize the structural consequence of kidney disease-associated APOL1 variants further, we assigned the C-terminal region proteins using 1H, 13C, 15N multidimensional nuclear magnetic resonance (NMR) spectra in solution in the presence of membrane mimetic dodecylphosphocholine micelles. We then derived models for the three-dimensional structure of APOL1-G0, and -G1 and -G2 variant C-terminal regions using the chemical shifts of the main chain nuclei followed by NMR relaxation measurements. The data suggest that changes in the three-dimensional structure of APOL1 C-terminal region induced by kidney disease-associated variants, not least the alteration of key sidechains and their interactions, could disrupt membrane association and the yet to be characterized protein-protein interactions including its binding partners, such as SNARE proteins. Such interactions could underlie the intracellular mechanisms that mediate the pathogenesis of CKD. In the future, one may try to reverse such structural and dynamics changes in the protein by designing agents that may bind and then mitigate APOL1 variant-associated CKD.

biophysics↗

bioRxiv2021

Permeant Fluorescent Probes Visualize the Activation of SARM1 and Uncover an Anti-neurodegenerative Drug Candidate

SARM1 regulates axonal degeneration through its NAD-metabolizing activity and is a drug target for neurodegenerative disorders. We designed and synthesized fluorescent conjugates of styryl derivative with pyridine to serve as substrates of SARM1, which exhibited large red-shifts after conversion. With the conjugates, SARM1 activation was visualized in live cells following elevation of endogenous NMN or treatment with a cell-permeant NMN-analog. In neurons, imaging documented SARM1 activation preceded vincristine-induced axonal degeneration by hours. Library screening identified a derivative of nisoldipine as a covalent inhibitor of SARM1 that reacted with Cys311 in its Armadillo-domain and blocked its NMN-activation, protecting axons from degeneration. CryoEM showed that SARM1 was locked into an inactive conformation by the inhibitor, uncovering an unsuspected neuroprotective mechanism of dihydropyridines.

biochemistry↗

bioRxiv2021

Single-cell ATAC and RNA sequencing reveal pre-existing and persistent subpopulations of cells associated with relapse of prostate cancer

Prostate cancer is profoundly heterogeneous and patients would benefit from methods that stratify clinically indolent from more aggressive forms of the disease. We employed single-cell assay for transposase-accessible chromatin (ATAC) and RNA sequencing in models of early treatment response and resistance to enzalutamide. In doing so, we identified pre-existing and treatment-persistent cell subpopulations that possess transcriptional stem-like features and regenerative potential when subjected to treatment. We found distinct chromatin landscapes associated with enzalutamide treatment and resistance that are linked to alternative transcriptional programs. Transcriptional profiles characteristic of persistent stem-like cells were able to stratify the treatment response of patients. Ultimately, we show that defining changes in chromatin and gene expression in single-cell populations from pre-clinical models can reveal hitherto unrecognized molecular predictors of treatment response. This suggests that high analytical resolution of pre-clinical models may powerfully inform clinical decision-making.

cancer biology↗

bioRxiv2020

3D Genome Contributes to Protein-Protein Interactome

Numerous computational methods have been proposed to predict protein-protein interactions, none of which however, considers the original DNA loci of the interacting proteins in the perspective of 3D genome. Here we retrospect the DNA origins of the interacting proteins in the context of 3D genome and discovered that 1) if a gene pair is more proximate in 3D genome, their corresponding proteins are more likely to interact. 2) signal peptide involvement of PPI affects the corresponding gene-gene proximity in 3D genome space. 3) by incorporating 3D genome information, existing PPI prediction methods can be further improved in terms of accuracy. Combining our previous discoveries, we conjecture the existence of 3D genome driven cellular compartmentalization, meaning the co-localization of DNA elements lead to increased probability of the co-localization of RNA elements and protein elements.

bioinformatics↗

bioRxiv2020

Timing variability and midfrontal ~4 Hz rhythms correlate with cognition in Parkinson's disease

Patients with Parkinsons disease (PD) can have significant cognitive dysfunction; however, the mechanisms for these cognitive symptoms are unknown. Here, we used scalp electroencephalography (EEG) to investigate the cortical basis for PD-related cognitive impairments during interval timing, which requires participants to estimate temporal intervals of several seconds. Time estimation is an ideal task demand for investigating cognition in PD because it is simple, requires medial frontal cortical areas, and recruits basic executive processes such as working memory and attention. However, interval timing has never been systematically studied in PD patients with cognitive impairments. We report three main findings. First, 71 PD patients had increased temporal variability compared to 37 demographically-matched controls, and this variability correlated with cognitive dysfunction as measured by the Montreal Cognitive Assessment (MOCA). Second, PD patients had attenuated ~4 Hz EEG oscillatory activity at midfrontal electrodes in response to the interval-onset cue, which was also predictive of MOCA. Finally, trial-by-trial linear mixed-effects modeling demonstrated that cue-triggered ~4 Hz power predicted subsequent temporal estimates as a function of PD and MOCA. Our data suggest that impaired cue-evoked midfrontal ~4 Hz activity predicts increased timing variability that is indicative of cognitive dysfunction in PD. These findings link PD-related cognitive dysfunction with cortical mechanisms of cognitive control, which could advance novel biomarkers and neuromodulation for PD.

neuroscience↗

bioRxiv2020

Differing total mRNA expression shapes the molecular and clinical phenotype of cancer

Cancers can vary greatly in their transcriptomes. In contrast to alterations in specific genes or pathways, differences in tumor cell total mRNA content have not been comprehensively assessed. Technical and analytical challenges have impeded examination of total mRNA expression at scale across cancers. To address this, we developed a model for quantifying tumor-specific total mRNA expression (TmS) from bulk sequencing data, which performs transcriptomic deconvolution while adjusting for mixed genomes. We used single-cell RNA sequencing data to demonstrate total mRNA expression as a feature of tumor phenotype. We estimated and validated TmS in 5,015 patients across 15 cancer types identifying significant inter-individual variability. At a pan-cancer level, high TmS is associated with increased risk of disease progression and death. Cancer type-specific patterns of genetic alterations, intra-tumor genetic heterogeneity, as well as pan-cancer trends in metabolic dysregulation and hypoxia contribute to TmS. Taken together, our results suggest that measuring cell-type specific total mRNA expression offers a broader perspective of tracking cancer transcriptomes, which has important biological and clinical implications.

genomics↗

bioRxiv2020

scFEA: A graph neural network model to estimate cell-wise metabolic flux using single cell RNA-seq data

The metabolic heterogeneity, and metabolic interplay between cells and their microenvironment have been known as significant contributors to disease treatment resistance. However, with the lack of a mature high-throughput single cell metabolomics technology, we are yet to establish systematic understanding of intra-tissue metabolic heterogeneity and cooperation phenomena among cell populations. To mitigate this knowledge gap, we developed a novel computational method, namely scFEA (single cell Flux Estimation Analysis), to infer single cell fluxome from single cell RNA-sequencing (scRNA-seq) data. scFEA is empowered by a comprehensively reconstructed human metabolic map into a factor graph, a novel probabilistic model to leverage the flux balance constraints on scRNA-seq data, and a novel graph neural network based optimization solver. The intricate information cascade from transcriptome to metabolome was captured using multi-layer neural networks to fully capitulate the non-linear dependency between enzymatic gene expressions and reaction rates. We experimentally validated scFEA by generating an scRNA-seq dataset with matched metabolomics data on cells of perturbed oxygen and genetic conditions. Application of scFEA on this dataset demonstrated the consistency between predicted flux and metabolic imbalance with the observed variation of metabolite abundance in the matched metabolomics data. We also applied scFEA on five publicly available scRNA-seq and spatial transcriptomics datasets and identified context and cell group specific metabolic variations. The cell-wise fluxome predicted by scFEA empowers a series of downstream analysis including identification of metabolic modules or cell groups that share common metabolic variations, sensitivity evaluation of enzymes with regards to their impact on the whole metabolic flux, and inference of cell-tissue and cell-cell metabolic communications.

bioinformatics↗

bioRxiv2020

SSMD: A semi-supervised approach for a robust cell type identification and deconvolution of mouse transcriptomics data

Deconvolution of mouse transcriptomic data is challenged by the fact that mouse models carry various genetic and physiological perturbations, making it questionable to assume fixed cell types and cell type marker genes for different dataset scenarios. We developed a Semi-Supervised Mouse data Deconvolution (SSMD) method to study the mouse tissue microenvironment (TME). SSMD is featured by (i) a novel non-parametric method to discover data set specific cell type signature genes; (ii) a community detection approach for fixing cell types and their marker genes; (iii) a constrained matrix decomposition method to solve cell type relative proportions that is robust to diverse experimental platforms. In summary, SSMD addressed several key challenges in the deconvolution of mouse tissue data, including: (1) varied cell types and marker genes caused by highly divergent genotypic and phenotypic conditions of mouse experiment, (2) diverse experimental platforms of mouse transcriptomics data, (3) small sample size and limited training data source, and (4) capable to estimate the proportion of 35 cell types in blood, inflammatory, central nervous or hematopoietic systems. In silico and experimental validation of SSMD demonstrated its high sensitivity and accuracy in identifying (sub) cell types and predicting cell proportions comparing to state-of-the-arts methods. A user-friendly R package and a web server of SSMD are released via https://github.com/xiaoyulu95/SSMD. Key pointsO_LIWe provide a novel tissue deconvolution method, namely SSMD, which is specifically designed for mouse data to handle the variations caused by different mouse strain, genetic and phenotypic background, and experimental platforms. C_LIO_LISSMD is capable to detect data set and tissue microenvironment specific cell markers for more than 30 cell types in mouse blood, inflammatory tissue, cancer, and central nervous system. C_LIO_LISSMD achieve much improved performance in estimating relative proportion of the cell types compared with state-of-the-art methods. C_LIO_LIThe semi-supervised setting enables the application of SSMD on transcriptomics, DNA methylation and ATAC-seq data. C_LIO_LIA user friendly R package and a R shiny of SSMD based webserver are also developed. C_LI

bioinformatics↗

bioRxiv2020

RobMixReg: an R package for robust, flexible and high dimensional mixture regression

MotivationMixture regression has been widely used as a statistical model to untangle the latent subgroups of the sample population. Traditional mixture regression faces challenges when dealing with: 1) outliers and versatile regression forms; and 2) the high dimensionality of the predictors. Here, we develop an R package called RobMixReg, which provides comprehensive solutions for robust, flexible as well as high dimensional mixture modeling. Availability and ImplementationRobMixReg R package and associated documentation is available at CRAN: https://CRAN.R-project.org/package=RobMixReg.

bioinformatics↗

bioRxiv2020

Intrinsic neural timescales related to sensory processing: Evidence from abnormal behavioural states

The brain exhibits a complex temporal structure which translates into a hierarchy of distinct neural timescales. An open question is how these intrinsic timescales are related to sensory or motor information processing and whether these dynamics have common patterns in different behavioural states. We address these questions by investigating the brains intrinsic timescales in healthy controls, motor (amyotrophic lateral sclerosis, locked-in syndrome), sensory (anaesthesia, unresponsive wakefulness syndrome), and progressive reduction of sensory processing (from awake states over N1, N2, N3). We employed a combination of measures from EEG resting-state data: auto-correlation window (ACW), power spectral density (PSD), and power-law exponent (PLE). Prolonged neural timescales accompanied by a shift towards slower frequencies were observed in the conditions with sensory deficits, but not in conditions with motor deficits. Our results establish that the spontaneous activitys intrinsic neural timescale is related to specifically sensory rather than motor information processing in the healthy brain. HighlightsO_LIEEG resting-state shows a hierarchy of intrinsic neural timescales. C_LIO_LISensory deficits as in disorders of consciousness lead to prolonged intrinsic neuraltimescales. C_LIO_LIClinical conditions with motor deficits do not show changes in intrinsic neural timescales.20 C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/229161v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1893c45org.highwire.dtl.DTLVardef@d4176dorg.highwire.dtl.DTLVardef@4dfaa8org.highwire.dtl.DTLVardef@183621e_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2020

LINE-1 expression in cancer correlates with DNA damage response, copy number variation, and cell cycle progression

ABSTRACTRetrotransposons are genomic DNA sequences that are capable of copying themselves to new genomic locations via RNA intermediates; LINE-1 is the only retrotransposon that remains autonomous and active in the human genome. The mobility of LINE-1 is largely repressed in somatic tissues, but LINE-1 is active in many cancers. Recent studies using LINE-1 constructs indicate that host cells activate a DNA damage response (DDR) to repair retrotransposition intermediates and resolve conflicts between LINE-1 and DNA replication. Using multi-omic data from the CPTAC project, we found correlations between LINE-1 expression and ATM-MRN-SMC DDR signalling in endometrial cancer and between LINE-1 and the ATR-CHEK1 pathway in p53 wild type breast cancer. This provides evidence that conflicts between LINE-1 and DNA replication occur in at least some human cancers. Furthermore, LINE-1 expression in these cancers is correlated with the total amount of copy number variation genome wide, indicating that, when active in cancer, pointing to a direct impact of LINE-1 associated DNA damage on genome structure. We also find that, in endometrial and ovarian cancer, LINE-1 expression is correlated with the expression of genes that drive cycle progression including E2F3, PLK1 and Aurora kinase B. This study provides evidence, supporting recent work in model cell lines, of a LINE-1/DDR connection in human tumors and raises the possibility of additional interactions between LINE-1 and the cell cycle.Competing Interest StatementThe authors have declared no competing interest.View Full Text

cancer biology↗

bioRxiv2020

Precise Localization and Dynamic Distribution of Japanese Encephalitis Virus in theBrain Nuclei of Infected Mice

Japanese encephalitis virus (JEV) is a pathogen that causes severe vector-borne zoonotic diseases, thereby posing a serious threat to human health. Although JEV is potentially neurotropic, its pathogenesis and distribution in the host have not been fully elucidated. In this study, an infected mouse model was established using a highly virulent P3 strain of JEV. Immunohistochemistry and in situ hybridization, combined with anatomical imaging of the mouse brain, were used to dynamically localize the virus and construct three-dimensional (3D) images. Consequently, onset of mild clinical symptoms occurred in some mice at 84h post JEV infection, while most mice displayed typical neurological symptoms at 144h post infection. Moreover, brain pathology revealed typical changes associated with non-suppurative encephalitis, which lasted up to 192h. The earliest detection of viral antigen was achieved at 72h post infection, in the thalamus and medulla oblongata. At 144h post infection, the positive viral antigen signals were mainly distributed in the cerebral cortex, olfactory area, basal ganglia, thalamus, and brainstem regions in mice. At 192h post infection, the antigen signals gradually decreased, and the localization of JEV tended to concentrate in the cerebrum and thalamus, while no viral antigen was detected in the brain at 504h post infection. In this model, the viral antigen was first expressed in the reticular thalamic nucleus (Rt), at a consistent concentration. The expression of the viral antigen in the hippocampal CA2 region, the anterior olfactory nucleus, and the deep mesencephalic nucleus was high and persistent. The 3D images showed that viral signals were mostly concentrated in the parietal cortex, occipital lobe, and hippocampus, near the mid-sagittal plane. In the early stages of infection in mice, a large number of viral antigens were detected in denatured and necrotic neurons, suggesting that JEV directly causes neuronal damage. From the time of its entry, JEV is widely distributed in the central nervous system thereby causing extensive damage.Author summary There are many theories regarding the mechanism of entry of the Japanese encephalitis virus (JEV) into the nervous system. The inflammation cascade effect, resulting from the virus entering the central nervous system (CNS), is a major cause of brain injury in JEV patients. In this study, we found that the earliest point at which viral antigen was detected in the brain tissues following peripheral infection of JEV was at 72h. The virus was located in the nerve nuclei of the thalamus and medulla oblongata and, subsequently, viral antigens were found in the anterior olfactory nucleus. At 96h post infection, the virus was extensively distributed in the brain tissue, and at 144h-192h the viral antigen was widely distributed and highly concentrated. The viral concentration detected in the ventromedial thalamic nucleus (VM), deep mesencephalic nucleus (DpMe), and motor trigeminal nucleus (Mo5) remained high throughout the experiment. The hypertrophic nerve nuclei of JEV include the early anterior olfactory (AO) nucleus and the late hippocampal CA2 region. In the early stages of viral infection (72-144h post infection), the changes in viral antigen concentration and mortality rate were consistent. It was hypothesized that this stage represents the activation of viral proliferation and brain inflammation.View Full Text

pathology↗