Acetazolamide Alleviate Cerebral Edema Induced by Ischemic Stroke Through Inhibiting the Expression of AQP4 mRNA.

OBJECTIVE: We want to investigate the effect of aquaporin-4 (AQP4) on cerebral edema induced by ischemic stroke in rats and explore whether inhibiting the expression of AQP4 through acetazolamide (AZA) could attenuate brain edema and protect cerebral function. METHODS: The Sprague Dawley (SD) rats were randomly divided into four groups: sham + saline group, sham + AZA group, AZA intervention group, and nonintervention group. Each group was divided into five subgroups according to the time of cerebral ischemia (6 h, 1 day, 3 days, 5 days, and 7 days). The model of cerebral infarction in rats was adopted by means of the bilateral carotid arteries ligation (2-VO) method. The rats in intervention group were given intraperitoneal injection of AZA (35 mg/kg/day). Hematoxylin-eosin staining was performed for pathological analysis of the infarcted area. The brain water content was calculated to evaluate the degree of brain edema. The messenger RNA (mRNA) and protein expressions of AQP4 in the brain were measured by quantitative real-time polymerase chain reaction and immunohistochemistry, respectively. RESULTS: Significant cerebral pathological damages were found in ischemic stroke rats. The brain water content, protein, and mRNA expression of AQP4 of the intervention and nonintervention groups were markedly higher than those of the sham groups. By contrast, AZA administration reduced the brain water content, whereas improved cerebral dysfunction was induced by ischemic stroke. Moreover, AZA obviously reduced the protein and mRNA expression of AQP4 after ischemic stroke in rats' brains. CONCLUSIONS: The expression of AQP4 was closely related to cerebral edema induced by ischemic stroke. Decreasing the expression of AQP4 mRNA by AZA administration can effectively relieve cerebral edema and decrease cerebral pathological damage.

Effects of Different Farming Modes on Salmo trutta fario Growth and Intestinal Microbial Community.

The gut microbiota plays a pivotal role in upholding intestinal health, fostering intestinal development, fortifying organisms against pathogen intrusion, regulating nutrient absorption, and managing the body's lipid metabolism. However, the influence of different cultivation modes on the growth indices and intestinal microbes of Salmo trutta fario remains underexplored. In this study, we employed high-throughput sequencing and bioinformatics techniques to scrutinize the intestinal microbiota in three farming modes: traditional pond aquaculture (TPA), recirculating aquaculture (RA), and flow-through aquaculture (FTA). We aimed to assess the impact of different farming methods on the water environment and Salmo trutta fario's growth performance. Our findings revealed that the final weight and weight gain rate in the FTA model surpassed those in the other two. Substantial disparities were observed in the composition, relative abundance, and diversity of Salmo trutta fario gut microbiota under different aquaculture modes. Notably, the dominant genera of Salmo trutta fario gut microbiota varied across farming modes: for instance, in the FTA model, the most prevalent genera were SC-I-84 (7.34%), Subgroup_6 (9.93%), and UTCFX1 (6.71%), while, under RA farming, they were Bacteroidetes_vadinHA17 (10.61%), MBNT15 (7.09%), and Anaeromyxoactor (6.62%). In the TPA model, dominant genera in the gut microbiota included Anaeromyxobacter (8.72%), Bacteroidetes_vadinHA17 (8.30%), and Geobacter (12.54%). From a comparative standpoint, the genus-level composition of the gut microbiota in the RA and TPA models exhibited relative similarity. The gut microbiota in the FTA model showcased the most intricate functional diversity, while TPA farming displayed a more intricate interaction pattern with the gut microbiota. Transparency, pH, dissolved oxygen, conductivity, total dissolved solids, and temperature emerged as pivotal factors influencing Salmo trutta fario gut microbiota under diverse farming conditions. These research findings offer valuable scientific insights for fostering healthy aquaculture practices and disease prevention and control measures for Salmo trutta fario, holding substantial significance for the sustainable development of the cold-water fish industry in the Qinghai-Tibet Plateau.

METTL3-mediated m6A methylation of DNMT1 promotes the progression of non-small cell lung cancer by regulating the DNA methylation of FOXO3a.

Background: The aim of this study was to investigate the effect of DNA methylation of Fork Head Box O3 (FOXO3a) on the process of epithelial-mesenchymal transition (EMT) in non-small cell lung cancer (NSCLC). Methods: The expressions of FOXO3a, DNA methyltransferase 1 (DNMT1), METTL3, and EMT-related proteins (E-cadherin and N-cadherin) were measured. The influence of 5-Aza-dC and DNMT1 on the methylation level in the promoter region of FOXO3a was examined through the application of methylation-specific PCR (MSP). Chromatin immunoprecipitation (ChIP) was employed to detect binding between DNMT1 and the FOXO3a promoter. Methylated RNA immunoprecipitation (MeRIP) was utilized to evaluate the level of DNMT1 N6-methyladenosine (m6A) methylation. The assessment of cell viability and invasion abilities of A549 cells was performed using Cell Counting Kit-8 (CCK-8) and Transwell assays, respectively. NSCLC xenograft mouse models were established by subcutaneously injected treated A549 cells into nude mice. Results: The expression levels of DNMT1 and DNA methylation level FOXO3a were found to be significantly increased, whereas FOXO3a expression was considerably decreased in NSCLC cell lines and NSCLC tumor tissues. Both 5-Aza-dC treatment and DNMT1 knockdown resulted in the down-regulation of DNA methylation levels of FOXO3a while simultaneously up-regulating the expression of FOXO3a. A ChIP assay demonstrated that DNMT1 has the ability to bind to the promoter region of FOXO3a. Furthermore, the knockdown of DNMT1 promoted E-cadherin expression, but inhibited expression of N-cadherin, cell viability, and invasion ability. However, the knockdown of FOXO3a hindered the effect of DNMT1 knockdown on EMT, cell viability, and invasion ability of A549 cells. This was evidenced by decreased E-cadherin expression and increased N-cadherin expression, as well as increased cell viability and invasion ability. Increased expression of DNMT1 resulted from m6A methylation of DNMT1, which was mediated by METTL3. Overexpression of DNMT1 decreased of E-cadherin expression while increased N-cadherin expression, cell viability, and invasion ability in METTL3-shRNA treated A549 cells. In xenograft mouse models, DNMT1 knockdown significantly reduced tumor volumes and tumor weight. DNMT1 knockdown upregulated the expression of FOXO3a and E-cadherin, while downregulated N-cadherin expression in vivo. Conclusion: METTL3-mediated m6A methylation of DNMT1 up-regulates FOXO3a promoter methylation, thereby promoting the progression of NSCLC.

Applying OHSA to Detect Road Accident Blackspots.

With increasing numbers of crashes and injuries, understanding traffic accident spatial patterns and identifying blackspots is critical to improve overall road safety. This study aims at detecting blackspots using optimized hot spot analysis (OHSA). Traffic accidents were classified by their participants and severity to explore the relationship between blackspots and different types of accidents. Based on the outputs of incremental spatial autocorrelation, OHSA was then implemented on different types of accidents. Finally, the performance of OHSA in evaluating the road safety level of the proposed RBT index are examined using a binary correlation analysis (i.e., R2 = 0.89). The results show that: (1) The optimal scale distance varies from 0.6 km to 2.8 km and is influenced by the distance of the travel mode. (2) Central cities, with 54.6% of the total accidents, experiences more rigorous challenges regarding traffic safety than satellite cities. (3) There are many types of black spots in vulnerable communities, but in some specific areas, there are only black spots of non-motor vehicle accidents. Considering the practical significance of the above results, policy makers and traffic engineers are expected to give higher attention to central cities and vulnerable communities or prioritize the implementation of relevant optimization measures.

The signaling pathways involved in metabolic regulation and stress responses of the yeast-like fungi Aureobasidium spp.

Aureobasidium spp. can use a wide range of substrates and are widely distributed in different environments, suggesting that they can sense and response to various extracellular signals and be adapted to different environments. It is true that their pullulan, lipid and liamocin biosynthesis and cell growth are regulated by the cAMP-PKA signaling pathway; Polymalate (PMA) and pullulan biosynthesis is controlled by the Ca2+ and TORC1 signaling pathways; the HOG1 signaling pathway determines high osmotic tolerance and high pullulan and liamocin biosynthesis; the Snf1/Mig1 pathway controls glucose repression on pullulan and liamocin biosynthesis; DHN-melanin biosynthesis and stress resistance are regulated by the CWI signaling pathway and TORC1 signaling pathway. In addition, the HSF1 pathway may control cell growth of some novel strains of A. melanogenum at 37 °C. However, the detailed molecular mechanisms of high temperature growth and thermotolerance of some novel strains of A. melanogenum and glucose derepression in A. melanogenum TN3-1 are still unclear.

Systematic review of efficacy, safety and pharmacokinetics of intravenous and intraventricular vancomycin for central nervous system infections.

Objective: The decision of vancomycin dosage for central nervous system (CNS) infections is still a challenge because its bactericidal nature in cerebrospinal fluid (CSF) has not been confirmed by human studies. This study systematically reviewed the literatures on vancomycin in patients with meningitis, ventriculitis, and CNS device-associated infections, to assess efficacy, safety, and pharmacokinetics to better serve as a practical reference. Methods: Medline, Embase, and Cochrane Library were searched using terms vancomycin, Glycopeptides, meningitis, and central nervous system infections. Data were extracted including characteristics of participants, causative organism(s), administration, dosage, etc., The clinical response, microbiological response, adverse events and pharmacokinetic parameters were analyzed. Results: Nineteen articles were included. Indications for vancomycin included meningitis, ventriculitis, and intracranial device infections. No serious adverse effects of intravenous (IV) and intraventricular (IVT) vancomycin have been reported. Dosages of IV and IVT vancomycin ranged from 1000-3000 mg/day and 2-20 mg/day. Duration of IV and IVT vancomycin therapy most commonly ranged from 3-27 days and 2-21 days. Therapeutic drug monitoring was conducted in 14 studies. Vancomycin levels in CSF in patients using IV and IVT vancomycin were varied widely from 0.06 to 22.3 mg/L and 2.5-292.9 mg/L. No clear relationships were found between vancomycin CSF levels and efficacy or toxicity. Conclusion: Using vancomycin to treat CNS infections appears effective and safe based on current evidence. However, the optimal regimens are still unclear. Higher quality clinical trials are required to explore the vancomycin disposition within CNS.

S100A gene family: immune-related prognostic biomarkers and therapeutic targets for low-grade glioma.

BACKGROUND: Despite the better prognosis given by surgical resection and chemotherapy in low-grade glioma (LGG), progressive transformation is still a huge concern. In this case, the S100A gene family, being capable of regulating inflammatory responses, can promote tumor development. METHODS: The analysis was carried out via ONCOMINE, GEPIA, cBioPortal, String, GeneMANIA, WebGestalt, LinkedOmics, TIMER, CGGA, R 4.0.2 and immunohistochemistry. RESULTS: S100A2, S100A6, S100A10, S100A11, and S100A16 were up-regulated and S100A1 and S100A13 were down-regulated in LGG compared to normal tissues. S100A3, S100A4, S100A8, and S100A9 expression was up-regulated during the progression of glioma grade. In addition, genetic variation of the S100A family was high in LGG, and the S100A family genes mostly function through IL-17 signaling pathway, S100 binding protein, and inflammatory responses. The TIMER database also revealed a relationship between gene expression and immune cell infiltration. High expression of S100A2, S100A3, S100A4, S100A6, S100A8, S100A9, S100A10, S100A11, S100A13, and S100A16 was significantly associated with poor prognosis in LGG patients. S100A family genes S100A2, S100A3, S100A6, S100A10, and S100A11 may be prognosis-related genes in LGG, and were significantly associated with IDH mutation and 1p19q codeletion. The immunohistochemical staining results also confirmed that S100A2, S100A3, S100A6, S100A10, and S100A11 expression was upregulated in LGG. CONCLUSION: The S100A family plays a vital role in LGG pathogenesis, presumably facilitating LGG progression via modulating inflammatory state and immune cell infiltration.

A Novel Immune-Related Prognostic Biomarker and Target Associated With Malignant Progression of Glioma.

BACKGROUND: Glioma is one of the most common malignancies in the central nervous system and has limited effective therapeutic options. Therefore, we sought to identify a suitable target for immunotherapy. MATERIALS AND METHODS: We screened prognostic genes for glioma in the CGGA database and GSE43378 dataset using survival analysis, receiver operating characteristic (ROC) curves, independent prognostic analysis, and clinical correlation analysis. The results were intersected with immune genes from the ImmPort database through Venn diagrams to obtain likely target genes. The target genes were validated as prognostically relevant immune genes for glioma using survival, ROC curve, independent prognostic, and clinical correlation analyses in samples from the CGGA database and GSE43378 dataset, respectively. We also constructed a nomogram using statistically significant glioma prognostic factors in the CGGA samples and verified their sensitivity and specificity with ROC curves. The functions, pathways, and co-expression-related genes for the glioma target genes were assessed using PPI networks, enrichment analysis, and correlation analysis. The correlation between target gene expression and immune cell infiltration in glioma and the relationship with the survival of glioma patients were investigated using the TIMER database. Finally, target gene expression in normal brain, low-grade glioma, and high-grade glioma tissues was detected using immunohistochemical staining. RESULTS: We identified TNFRSF12A as the target gene. Satisfactory results from survival, ROC curve, independent prognosis, and clinical correlation analyses in the CGGA and GSE43378 samples verified that TNFRSF12A was significantly associated with the prognosis of glioma patients. A nomogram was constructed using glioma prognostic correlates, including TNFRSF12A expression, primary-recurrent-secondary (PRS) type, grade, age, chemotherapy, IDH mutation, and 1p19q co-deletion in CGGA samples with an AUC value of 0.860, which illustrated the accuracy of the prognosis prediction. The results of the TIMER analysis validated the significant correlation of TNFRSF12A with immune cell infiltration and glioma survival. The immunohistochemical staining results verified the progressive up-regulation of TNFRSF12A expression in normal brain, low-grade glioma, and high-grade glioma tissues. CONCLUSION: We concluded that TNFRSF12A was a viable prognostic biomarker and a potential immunotherapeutic target for glioma.

Bioinformatics analysis of potential core genes for glioblastoma.

BACKGROUND: Glioblastoma (GBM) has a high degree of malignancy, aggressiveness and recurrence rate. However, there are limited options available for the treatment of GBM, and they often result in poor prognosis and unsatisfactory outcomes. MATERIALS AND METHODS: In order to identify potential core genes in GBM that may provide new therapeutic insights, we analyzed three gene chips (GSE2223, GSE4290 and GSE50161) screened from the GEO database. Differentially expressed genes (DEG) from the tissues of GBM and normal brain were screened using GEO2R. To determine the functional annotation and pathway of DEG, Gene Ontology (GO) and KEGG pathway enrichment analysis were conducted using DAVID database. Protein interactions of DEG were visualized using PPI network on Cytoscape software. Next, 10 Hub nodes were screened from the differentially expressed network using MCC algorithm on CytoHubba software and subsequently identified as Hub genes. Finally, the relationship between Hub genes and the prognosis of GBM patients was described using GEPIA2 survival analysis web tool. RESULTS: A total of 37 up-regulated and 187 down-regulated genes were identified through microarray analysis. Amongst the 10 Hub genes selected, SV2B appeared to be the only gene associated with poor prognosis in glioblastoma based on the survival analysis. CONCLUSION: Our study suggests that high expression of SV2B is associated with poor prognosis in GBM patients. Whether SV2B can be used as a new therapeutic target for GBM requires further validation.