Wide-area measurement-based supervision of the cerebral venous hemodynamic in a novel rat model

Abstract(#br)Background(#br)Traumatic brain injury (TBI) includes primary and secondary injuries, while monitoring intracranial pressure (ICP) and cerebral blood flow (CBF) is conducive to improve the prognosis of patients. However, the function of cerebral venous in this process is still unclear.(#br)New Method(#br)An acute epidural hematoma (AEDH) model was developed by placing a controllable microballoon in the right epidural space of a rat. The laser speckle contrast imaging (LSCI) system was used to observe CBF in real time, while ICP was monitored simultaneously. And the stability of this model was examined by magnetic resonance imaging (MRI).(#br)Results(#br)The blood perfusion rate (BPR) of venous was significantly negatively correlated with ICP. In the 100 μL group, the ipsilateral cerebral venous and microcirculation blood flow significantly decreased. According to the gross observations and pathological results, ischemic brain injury was the most serious on this condition.(#br)Comparison with Existing Method(s)(#br)Modeling method is relatively simple, which effectively reduces the cost. The volume of the microballoon is adjusted to simulate the volume of different size of hematomas. In addition, LSCI, as an advanced blood flow monitoring technology, has high sensitivity to detect subtle changes in CBF.(#br)Conclusion(#br)This study successfully developed a stable and reproducible AEDH rat model. Based on this model, it is preliminarily demonstrated that local intracranial hypertension can cause cerebral venous return restriction, which is an indispensable factor leading to the aggravation of secondary brain injury

Wide-area measurement-based supervision of the cerebral venous hemodynamic in a novel rat model.

BACKGROUND(#br)Traumatic brain injury (TBI) includes primary and secondary injuries, while monitoring intracranial pressure (ICP) and cerebral blood flow (CBF) is conducive to improve the prognosis of patients. However, the function of cerebral venous in this process is still unclear.(#br)NEW METHOD(#br)An acute epidural hematoma (AEDH) model was developed by placing a controllable micro balloon in the right epidural space of a rat. The laser speckle contrast imaging (LSCI) system was used to observe CBF in real time, while ICP was monitored simultaneously. And the stability of this model was examined by magnetic resonance imaging (MRI).(#br)RESULTS(#br)The blood perfusion rate (BPR) of venous was significantly negatively correlated with ICP. In the 100 μ L group, the ipsilateral cerebral venous and microcirculation blood flow significantly decreased. According to the gross observations and pathological results, ischemic brain injury was the most serious on this condition.(#br)COMPARISON WITH EXISTING METHOD(S)(#br)Modeling method is relatively simple, which effectively reduces the cost. The volume of the micro balloon is adjusted to simulate the volume of different size of hematomas. In addition, LSCI, as an advanced blood flow monitoring technology, has high sensitivity to detect subtle changes in CBF.(#br)CONCLUSION(#br)This study successfully developed a stable and reproducible AEDH rat model. Based on this model, it is preliminarily demonstrated that local intracranial hypertension can cause cerebral venous return restriction, which is an indispensable factor leading to the aggravation of secondary brain injury

Identification of a diagnostic model and molecular subtypes of major depressive disorder based on endoplasmic reticulum stress-related genes

SubjectMajor depressive disorder (MDD) negatively affects patients’ behaviours and daily lives. Due to the high heterogeneity and complex pathological features of MDD, its diagnosis remains challenging. Evidence suggests that endoplasmic reticulum stress (ERS) is involved in the pathogenesis of MDD; however, relevant diagnostic markers have not been well studied. This study aimed to screen for ERS genes with potential diagnostic value in MDD.MethodsGene expression data on MDD samples were downloaded from the GEO database, and ERS-related genes were obtained from the GeneCards and MSigDB databases. Differentially expressed genes (DEGs) in MDD patients and healthy subjects were identified and then integrated with ERS genes. ERS diagnostic model and nomogram were developed based on biomarkers screened using the LASSO method. The diagnostic performance of this model was evaluated. ERS-associated subtypes were identified. CIBERSORT and GSEA were used to explore the differences between the different subtypes. Finally, WGCNA was performed to identify hub genes related to the subtypes.ResultsA diagnostic model was developed based on seven ERS genes: KCNE1, PDIA4, STAU1, TMED4, MGST1, RCN1, and SHC1. The validation analysis showed that this model had a good diagnostic performance. KCNE1 expression was positively correlated with M0 macrophages and negatively correlated with resting CD4+ memory T cells. Two subtypes (SubA and SubB) were identified, and these two subtypes showed different ER score. The SubB group showed higher immune infiltration than the SubA group. Finally, NCF4, NCF2, CSF3R, and FPR2 were identified as hub genes associated with ERS molecular subtypes.ConclusionOur current study provides novel diagnostic biomarkers for MDD from an ERS perspective, and these findings further facilitate the use of precision medicine in MDD

DCQA: Document-Level Chart Question Answering towards Complex Reasoning and Common-Sense Understanding

Visually-situated languages such as charts and plots are omnipresent in real-world documents. These graphical depictions are human-readable and are often analyzed in visually-rich documents to address a variety of questions that necessitate complex reasoning and common-sense responses. Despite the growing number of datasets that aim to answer questions over charts, most only address this task in isolation, without considering the broader context of document-level question answering. Moreover, such datasets lack adequate common-sense reasoning information in their questions. In this work, we introduce a novel task named document-level chart question answering (DCQA). The goal of this task is to conduct document-level question answering, extracting charts or plots in the document via document layout analysis (DLA) first and subsequently performing chart question answering (CQA). The newly developed benchmark dataset comprises 50,010 synthetic documents integrating charts in a wide range of styles (6 styles in contrast to 3 for PlotQA and ChartQA) and includes 699,051 questions that demand a high degree of reasoning ability and common-sense understanding. Besides, we present the development of a potent question-answer generation engine that employs table data, a rich color set, and basic question templates to produce a vast array of reasoning question-answer pairs automatically. Based on DCQA, we devise an OCR-free transformer for document-level chart-oriented understanding, capable of DLA and answering complex reasoning and common-sense questions over charts in an OCR-free manner. Our DCQA dataset is expected to foster research on understanding visualizations in documents, especially for scenarios that require complex reasoning for charts in the visually-rich document. We implement and evaluate a set of baselines, and our proposed method achieves comparable results

Identification of differentially expressed microRNAs and the potential of microRNA-455-3p as a novel prognostic biomarker in glioma.

Glioma is an aggressive central nervous system malignancy. MicroRNAs (miRNAs/miRs) have been reported to be involved in the tumorigenesis of numerous types of cancer, including glioma. The present study aimed to identify the differentially expressed miRNAs in glioma, and further explore the clinical value of miR-455-3p in patients with glioma. GEO2R was used for the identification of the differentially expressed miRNAs according to the miRNA expression profiles obtained from the Gene Expression Omnibus database. OncomiR was used to analyze the relationship of miRNAs with the survival outcomes of the patients with glioma. A total of 108 patients with glioma were recruited to examine the expression levels of miR-455-3p and further explore its clinical value. The bioinformatics analysis results suggested that a total of 64 and 48 differentially expressed miRNAs were identified in the GSE90603 and GSE103229 datasets, respectively. There were 12 miRNAs in the overlap of the two datasets, of which three were able to accurately predict overall cancer survival, namely hsa-miR-7-5p, hsa-miR-21-3p and hsa-miR-455-3p. In patients with glioma, miR-455-3p was determined to be significantly upregulated (P<0.001). Additionally, patients with high miR-455-3p expression had significantly lower 5-year overall survival than those with low miR-455-3p expression (log-rank test, P=0.001). Cox regression analysis further determined that miR-455-3p was an independent prognostic indicator for overall survival in patients with glioma (hazard ratio=2.136; 95% CI=1.177-3.877; P=0.013). In conclusion, the present study revealed a series of miRNAs with potential functional roles in the pathogenesis of glioma, and provides findings that indicate miR-455-3p as a promising biomarker for the prognosis of glioma

Construction of a High-Density Genetic Map and Identification of Leaf Trait-Related QTLs in Chinese Bayberry (Myrica rubra)

Chinese bayberry (Myrica rubra) is an economically important fruit tree that is grown in southern China. Owing to its over 10-year seedling period, the crossbreeding of bayberry is challenging. The characteristics of plant leaves are among the primary factors that control plant architecture and potential yields, making the analysis of leaf trait-related genetic factors crucial to the hybrid breeding of any plant. In the present study, molecular markers associated with leaf traits were identified via a whole-genome re-sequencing approach, and a genetic map was thereby constructed. In total, this effort yielded 902.11 Gb of raw data that led to the identification of 2,242,353 single nucleotide polymorphisms (SNPs) in 140 F1 individuals and parents (Myrica rubra cv. Biqizhong × Myrica rubra cv. 2012LXRM). The final genetic map ultimately incorporated 31,431 SNPs in eight linkage groups, spanning 1,351.85 cM. This map was then used to assemble and update previous scaffold genomic data at the chromosomal level. The genome size of M. rubra was thereby established to be 275.37 Mb, with 94.98% of sequences being assembled into eight pseudo-chromosomes. Additionally, 18 quantitative trait loci (QTLs) associated with nine leaf and growth-related traits were identified. Two QTL clusters were detected (the LG3 and LG5 clusters). Functional annotations further suggested two chlorophyll content-related candidate genes being identified in the LG5 cluster. Overall, this is the first study on the QTL mapping and identification of loci responsible for the regulation of leaf traits in M. rubra, offering an invaluable scientific for future marker-assisted selection breeding and candidate gene analyses

Prevalence and Characterization of Staphylococcus aureus Isolated From Women and Children in Guangzhou, China

The prevalent Staphylococcus aureus clones and antibiotic susceptibility profiles are known to change dynamically and geographically; however, recent S. aureus strains causing infections in women and children in China have not been characterized. In this study, we analyzed the molecular epidemiology and antimicrobial resistance of S. aureus isolated from patients in four centers for women and children in Guangzhou, China. In total, 131 S. aureus isolates (100 from children and 31 from women) were analyzed by spa typing, multi-locus sequence typing, virulence gene and antimicrobial resistance profiling, staphylococcal chromosomal cassette mec typing, and mutation analyses of rpoB. A total of 58 spa types, 27 sequence types (STs), and 10 clonal complexes (CCs) were identified. While CC59 (ST59-IV, 48.8%; ST338-III, 35.7%) and CC45 (ST45-IV, 100%) were the major clones (84.4%) among MRSA isolates, CC5 (ST188, 24.3%; ST1, 21.6%) and CC398 (ST398, 70%) were the major ones (70.1%) among MSSA isolates. ST338-MRSA-III mostly found in pus but hardly in respiratory tract samples while ST45-MRSA-IV was on the opposite, even though they both found in blood and cerebrospinal fluid sample frequently. Staphylococcal enterotoxin genes seb-seq-sek were strongly associated with ST59 and ST338, while sec was associated with ST45, ST121, ST22, and ST30. All ST338, ST1232, and SCCmec III isolates carried lukF/S-PV genes. A total of 80% of ST338 isolates were resistant to erythromycin, clindamycin, and tetracycline. All ST45 isolates exhibited intermediate or complete resistance to rifampicin. In total, 481 HIS/ASN mutations in rpoB were found in rifampicin-resistant or intermediate-resistant isolates. ST338-III and ST45-IV emerged as two of three major clones in MRSA isolates from women and children in Guangzhou, China, though ST59-MRSA-IV remained the most prevalent MRSA clone. Clonal distribution of S. aureus varied, depending on the specimen source. Virulence genes and antibiograms were closely associated with the clonal lineage. These results clarified the molecular epidemiology of S. aureus from women and children in Guangzhou, China, and provide critical information for the control and treatment of S. aureus infections

Interleukin-17 Contributes to the Pathogenesis of Autoimmune Hepatitis through Inducing Hepatic Interleukin-6 Expression

T helper cells that produce IL-17 (Th17 cells) have recently been identified as the third distinct subset of effector T cells. Emerging data suggests that Th17 cells play an important role in the pathogenesis of many liver diseases by regulating innate immunity, adaptive immunity, and autoimmunity. In this study, we examine the role and mechanism of Th17 cells in the pathogenesis of autoimmune hepatitis (AIH). The serum levels of IL-17 and IL-23, as well as the frequency of IL-17+ cells in the liver, were significantly elevated in patients with AIH, compared to other chronic hepatitis and healthy controls. The hepatic expressions of IL-17, IL-23, ROR-γt, IL-6 and IL-1β in patients with AIH were also significantly increased and were associated with increased inflammation and fibrosis. IL-17 induces IL-6 expression via the MAPK signaling pathway in hepatocytes, which, in turn, may further stimulate Th17 cells and forms a positive feedback loop. In conclusion, Th17 cells are key effector T cells that regulate the pathogenesis of AIH, via induction of MAPK dependent hepatic IL-6 expression. Blocking the signaling pathway and interrupting the positive feedback loop are potential therapeutic targets for autoimmune hepatitis

The Interaction between Regulatory T Cells and NKT Cells in the Liver: A CD1d Bridge Links Innate and Adaptive Immunity

Regulatory T cells (Tregs) and natural killer T (NKT) cells are two distinct lymphocyte subsets that independently regulate hepatic adaptive and innate immunity, respectively. In the current study, we examine the interaction between Tregs and NKT cells to understand the mechanisms of cross immune regulation by these cells.The frequency and function of Tregs were evaluated in wild type and NKT cell deficient (CD1dko) mice. In vitro lymphocyte proliferation and apoptosis assays were performed with NKT cells co-cultured with Tregs. The ability of Tregs to inhibit NKT cells in vivo was examined by adoptive transfer of Tregs in a model of NKT cell mediated hepatitis.CD1dko mice have a significant reduction in hepatic Tregs. Although, the Tregs from CD1dko mice remain functional and can suppress conventional T cells, their ability to suppress activation induced NKT cell proliferation and to promote NKT cell apoptosis is greatly diminished. These effects are CD1d dependent and require cell to cell contact. Adoptive transfer of Tregs inhibits NKT cell-mediated liver injury.NKT cells promote Tregs, and Tregs inhibit NKT cells in a CD1d dependent manner requiring cell to cell contact. These cross-talk immune regulations provide a linkage between innate and adaptive immunity