Exploring causal correlations of inflammatory biomarkers in idiopathic normal-pressure hydrocephalus: insights from bidirectional Mendelian randomization analysis.

Background and objective: Neuroinflammatory processes have been identified as playing a crucial role in the pathophysiology of various neurodegenerative diseases, including idiopathic normal-pressure hydrocephalus (iNPH). iNPH, defined as a common disease of cognitive impairment in older adults, poses major challenges for therapeutic interventions owing to the stringent methodological requirements of relevant studies, clinical heterogeneity, unclear etiology, and uncertain diagnostic criteria. This study aims to assess the relationship between circulating inflammatory biomarkers and iNPH risk using bidirectional two-sample Mendelian randomization (MR) combined with meta-analysis. Methods: In our bidirectional MR study, genetic data from a genome-wide association study (GWAS) involving 1,456 iNPH cases and 409,726 controls of European ancestry were employed. Single-nucleotide polymorphisms (SNPs) associated with exposures served as instrumental variables for estimating the causal relationships between iNPH and 132 types of circulating inflammatory biomarkers from corresponding GWAS data. Causal associations were primarily examined using the inverse variance-weighted method, supplemented by MR-Egger, weighted median, simple mode, and weighted mode analyses. In the results, heterogeneity was assessed using the Cochran Q test. Horizontal pleiotropy was evaluated through the MR-Egger intercept test and the MR pleiotropy residual sum and outliers test. Sensitivity analysis was conducted through leave-one-out analysis. Reverse MR analyses were performed to mitigate bias from reverse causality. Meta-analyses of identical inflammatory biomarkers from both data sources strengthened the findings. Results: Results indicated a genetically predicted association between Interleukin-16 (IL-16) [OR: 1.228, 95% CI: 1.049-1.439, p = 0.011], TNF-related apoptosis ligand (TRAIL) [OR: 1.111, 95% CI: 1.019-1.210, p = 0.017] and Urokinase-type plasminogen activator (uPA) [OR: 1.303, 95% CI: 1.025-1.658, p = 0.031] and the risk of iNPH. Additionally, changes in human Glial cell line-derived neurotrophic factor (hGDNF) [OR: 1.044, 95% CI: 1.006-1.084, p = 0.023], Matrix metalloproteinase-1 (MMP-1) [OR: 1.058, 95% CI: 1.020, 1.098, p = 0.003] and Interleukin-12p70 (IL-12p70) [OR: 0.897, 95% CI: 0.946-0.997, p = 0.037] levels were identified as possible consequences of iNPH. Conclusion: Our MR study of inflammatory biomarkers and iNPH, indicated that IL-16, TRAIL, and uPA contribute to iNPH pathogenesis. Furthermore, iNPH may influence the expression of hGDNF, MMP-1, and IL-12p70. Therefore, targeting specific inflammatory biomarkers could be promising strategy for future iNPH treatment and prevention.

Deubiquitinase OTUD5 promotes hepatitis B virus replication by removing K48-linked ubiquitination of HBV core/precore and upregulates HNF4ɑ expressions by inhibiting the ERK1/2/mitogen-activated protein kinase pathway.

Hepatitis B virus (HBV) infection is a major public health problem worldwide, causing nearly one million deaths annually. OTUD5 is a deubiquitinase associated with cancer development and innate immunity response. However, the regulatory mechanisms of OTUD5 underlying HBV replication need to be deeply elucidated. In the present investigation, we found that HBV induced significant up-regulation of OTUD5 protein in HBV-infected cells. Further study showed that OTUD5 interacted with HBV core/precore, removing their K48-linked ubiquitination chains and protecting their stability. Meanwhile, overexpression of OTUD5 could inhibit the MAPK pathway and then increase the expression of HNF4ɑ, and ERK1/2 signaling was required for OTUD5-mediated activation of HNF4α, promoting HBV replication. Together, these data indicate that OTUD5 could deubiquitinate HBV core protein degradation by its deubiquitinase function and promote HBV activity by up-regulating HNF4α expression via inhibition of the ERK1/2 pathway. These results might present a novel therapeutic strategy against HBV infection.

Mechanism of action of paclitaxel for treating glioblastoma based on single-cell RNA sequencing data and network pharmacology.

Paclitaxel is an herbal active ingredient used in clinical practice that shows anti-tumor effects. However, its biological activity, mechanism, and cancer cell-killing effects remain unknown. Information on the chemical gene interactions of paclitaxel was obtained from the Comparative Toxicogenomics Database, SwishTargetPrediction, Binding DB, and TargetNet databases. Gene expression data were obtained from the GSE4290 dataset. Differential gene analysis, Kyoto Encyclopedia of Genes and Genomes, and Gene Ontology analyses were performed. Gene set enrichment analysis was performed to evaluate disease pathway activation; weighted gene co-expression network analysis with diff analysis was used to identify disease-associated genes, analyze differential genes, and identify drug targets via protein-protein interactions. The Molecular Complex Detection (MCODE) analysis of critical subgroup networks was conducted to identify essential genes affected by paclitaxel, assess crucial cluster gene expression differences in glioma versus standard samples, and perform receiver operator characteristic mapping. To evaluate the pharmacological targets and signaling pathways of paclitaxel in glioblastoma, the single-cell GSE148196 dataset was acquired from the Gene Expression Omnibus database and preprocessed using Seurat software. Based on the single-cell RNA-sequencing dataset, 24 cell clusters were identified, along with marker genes for the two different cell types in each cluster. Correlation analysis revealed that the mechanism of paclitaxel treatment involves effects on neurons. Paclitaxel may affect glioblastoma by improving glucose metabolism and processes involved in modulating immune function in the body.

Baseline Quantitative Hepatitis B Core Antibody Titer Is a Predictor for Hepatitis B Virus Infection Recurrence After Orthotopic Liver Transplantation.

Objective: Hepatitis B virus (HBV) reinfection is a serious complication that arise in patients who undergo hepatitis B virus related liver transplantation. We aimed to use biomarkers to evaluate the HBV reinfection in patients after orthotopic liver transplantation. Methods: Seventy-nine patients who underwent liver transplantation between 2009 and 2015 were enrolled, and levels of biomarkers were analyzed at different time points. Cox regression and receiver operating characteristic (ROC) curves of different markers at baseline were used to analyze sustained hepatitis B surface antigen (HBsAg) loss. The Kaplan-Meier method was used to compare the levels of the biomarkers. Results: Among the 79 patients, 42 sustained HBsAg loss with a median time of 65.2 months (12.0-114.5, IQR 19.5) after liver transplantation and 37 patients exhibited HBsAg recurrence with a median time of 8.8 (0.47-59.53, IQR 19.47) months. In the ROC curve analysis, at baseline, 4.25 log10 IU/mL qHBcAb and 2.82 log10 IU/mL qHBsAg showed the maximum Youden's index values with area under the curves (AUCs) of 0.685and 0.651, respectively. The Kaplan-Meier method indicated that qHBsAg and quantitative antibody against hepatitis B core antigen (qHBcAb) levels in the two groups were significantly different (p = 0.031 and 0.006, respectively). Furthermore, the Cox regression model confirmed the predictive ability of qHBcAb at baseline (AUC = 0.685). Conclusion: Lower pretransplantation qHBcAb is associated with HBV infection. The baseline concentration of qHBcAb is a promising predictor for the recurrence of HBV in patients undergoing liver transplantation and can be used to guide antiviral treatment for HBV infection.

Comparative Analysis of Transcriptomes to Identify Genes Associated with Fruit Size in the Early Stage of Fruit Development in Pyrus pyrifolia.

Pear (Pyrus L.) is an important commercial fruit in the world. The fruit size is one of the important characters in fruit quality. The previous research reported that the fruit size of pear was mainly caused by the number of cell in about 40 days after blossom (DAB) in nature. However, studies about the mechanisms underlying cell division in young fruit development are very limited in pear. Two pear accessions codenamed 'GH59B' with big fruit and 'GH81S' with small fruit in three stages were sampled and the RNA-seq high-throughput sequencing was used to evaluate changes of gene transcription levels in the early stage of fruit development. The difference of cell size among two samples was little in 40 DAB, implying that the difference of the fruit size was caused by the number of the cell. More than 274,517,982 high quality reads from six libraries of fruit development were sequenced. A total of 797 differentially expressed genes (DEGs) were identified. Three cytokinin dehydrogenase genes and two gibberellin 2-beta-dioxygenase gene were identified in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to zeatin and gibberellin. Their expression was upregulated at 20 DAB in 'GH81S' and at 30 DAB in 'GH59B', suggesting that the small fruit size might be related to the early degradation of cytokinin and gibberellin inducing a short period of cell division. A total of 38 DEGs of transcription factors were found and 23 DEGs including NAC, ERF and bHLH transcription factors were highly related with cytokinin dehydrogenase and gibberellin dioxygenase genes. Altogether, the results of the present study provide information from a comprehensive gene expression analysis and insight into the molecular mechanism underlying the difference of fruit size in Pyrus pyrifolia.

Transcriptome Analysis Reveals Candidate Genes Involved in Gibberellin-Induced Fruit Setting in Triploid Loquat (Eriobotrya japonica).

The triploid loquat (Eriobotrya japonica) is a new germplasm with a high edible fruit rate. Under natural conditions, the triploid loquat has a low fruit setting ratio (not more than 10 fruits in a tree), reflecting fertilization failure. To unravel the molecular mechanism of gibberellin (GA) treatment to induce parthenocarpy in triploid loquats, a transcriptome analysis of fruit setting induced by GA3 was analyzed using RNA-seq at four different stages during the development of young fruit. Approximately 344 million high quality reads in seven libraries were de novo assembled, yielding 153,900 unique transcripts with more than 79.9% functionally annotated transcripts. A total of 2,220, 2,974, and 1,614 differentially expressed genes (DEGs) were observed at 3, 7, and 14 days after GA treatment, respectively. The weighted gene co-expression network and Venn diagram analysis of DEGs revealed that sixteen candidate genes may play critical roles in the fruit setting after GA treatment. Five genes were related to auxin, in which one auxin synthesis gene of yucca was upregulated, suggesting that auxin may act as a signal for fruit setting. Furthermore, ABA 8'-hydroxylase was upregulated, while ethylene-forming enzyme was downregulated, suggesting that multiple hormones may be involved in GA signaling. Four transcription factors, NAC7, NAC23, bHLH35, and HD16, were potentially negatively regulated in fruit setting, and two cell division-related genes, arr9 and CYCA3, were upregulated. In addition, the expression of the GA receptor gid1 was downregulated by GA treatment, suggesting that the negative feedback mechanism in GA signaling may be regulated by gid1. Altogether, the results of the present study provide information from a comprehensive gene expression analysis and insight into the molecular mechanism underlying fruit setting under GA treatment in E. japonica.