Currently, there is limited data on the risk factors associated with treatment delay in tuberculous meningitis (TBM). This study aimed to assess the duration of delay in the treatment TBM and to investigate its determinants. During the period from September 2009 to February 2016, a retrospective cohort study of consecutive TBM patients admitted to our hospital was conducted to determine the risk factors associated with treatment delay in TBM. Treatment delay duration was defined as the time interval from onset of symptoms (by patient recall) to initiation of treatment and was stratified into two categories: ≤ 20 days, >20 days (median delay day is 20 days). Data collected included demography, comorbidity, cerebrospinal fluid (CSF) examinations and others. Univariable and multivariable logistic regression analysis was used to evaluate the determinants of treatment delay. A total of 161 TBM patients were included in our study, all were confirmed by CSF mycobacterial culture. The median treatment delay for all patients included in the study was 20 days [interquartile range, 14–60 days]. Multivariate analysis revealed that age (≤21 years old, OR = 0.202, 95% CI: 0.079, 0.521), fever (OR = 0.414, 95% CI: 0.180, 0.952), and headache (OR = 0.204, 95% CI: 0.095, 0.442) had significantly lower risk for treatment delay, while multiple healthcare contact (>3 times) (OR = 3.938, 95% CI: 1.326, 11.691) as well as CSF chloride (>111 mmol/L) (OR = 2.479, 95% CI: 1.143, 5.377) had significantly higher risk of the delay. Our findings indicate that multiple healthcare contact and high CSF chloride predict the risk of long delay, while young age, fever and headache are associated with short delay. Maintained focus on awareness of TBM in the population and in healthcare systems, and continuous implementation of diagnostic methods for TBM to detect the disease early, may reduce the mortality and morbidity.

We investigated the influence of the long noncoding RNA VPS9D1 antisense RNA 1 (VPS9D1-AS1) on the malignant phenotype of non-small cell lung cancer (NSCLC) cells in vitro and in vivo. We also explored the mechanisms by which VPS9D1-AS1 exerts its oncogenic action during NSCLC progression. VPS9D1-AS1 expression was upregulated in NSCLC; the extent of its upregulation significantly correlated with patients' adverse clinicopathological characteristics and shorter overall survival. When VPS9D1-AS1 was knocked down in NSCLC cells, their proliferation, colony-forming capacity, migration, and invasiveness were lower, whereas their apoptosis rate was higher, compared to the control. VPS9D1-AS1 knockdown attenuated tumor growth of NSCLC cells in vivo. Mechanistically, VPS9D1-AS1 directly interacted with microRNA-532-3p (miR-532-3p) in NSCLC cells; the impact of VPS9D1-AS1 knockdown on NSCLC cells was attenuated by miR-532-3p inhibition. Furthermore, VPS9D1-AS1 knockdown decreased the expression of high mobility group AThook 2 (HMGA2) in NSCLC cells via miR-532-3p sponging. Recovery of HMGA2 expression partially reversed the inhibitory effects of VPS9D1-AS1 knockdown on NSCLC cells. Thus, VPS9D1-AS1 functions as a competing endogenous RNA that positively regulates HMGA2 expression by sponging miR-532-3p in NSCLC cells, suggesting that the VPS9D1-AS1-miR-532-3p-HMGA2 pathway can be a potential diagnostic and/or therapeutic target in NSCLC.

The aim of this study was to develop and internally validate an interpretable machine learning (ML) model for predicting the risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB) infection. We retrospectively collected clinical data from patients with HCC and CHB treated at the Fourth Affiliated Hospital of Guangxi Medical University from January 2022 to December 2022, including demographics, comorbidities, and laboratory parameters. The datasets were randomly divided into a training set (361 cases) and a validation set (155 cases) in a 7:3 ratio. Variables were screened using Least Absolute Shrinkage and Selection Operator (LASSO) and multifactor logistic regression. The prediction model of HCC risk in CHB patients was constructed based on five machine learning models, including logistic regression (LR), K-nearest neighbour (KNN), support vector machine (SVM), random forest (RF) and artificial neural network (ANN). Receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) were used to evaluate the predictive performance of the model in terms of identification, calibration and clinical application. The SHapley Additive exPlanation (SHAP) method was used to rank the importance of the features and explain the final model. Among the five ML models constructed, the RF model has the best performance, and the RF model predicts the risk of HCC in patients with CHB in the training set [AUC: 0.996, 95% confidence interval (CI) (0.991-0.999)] and internal validation set [AUC: 0.993, 95% CI (0.986-1.000)]. It has high AUC, specificity, sensitivity, F1 score and low Brier score. Calibration showed good agreement between observed and predicted risks. The model yielded higher positive net benefits in DCA than when all participants were considered to be at high or low risk, indicating good clinical utility. In addition, the SHAP plot of the RF showed that age, basophil/lymphocyte ratio (BLR), D-Dimer, aspartate aminotransferase/alanine aminotransferase (AST/ALT), γ-glutamyltransferase (GGT) and alpha-fetoprotein (AFP) can help identify patients with CHB who are at high or low risk of developing HCC. ML models can be used as a tool to predict the risk of HCC in patients with CHB. The RF model has the best predictive performance and helps clinicians to identify high-risk patients and intervene early to reduce or delay the occurrence of HCC. However, the model needs to be further improved through large sample studies.

C-terminally truncated hepatitis B virus (HBV) X (ctHBx) infection and exposure to microcystins-LR (MC-LR) can lead to human hepatitis and liver cancer, but the mechanism associated with their synergistically effects not been fully elucidated. The ctHBx (HBxΔ4 and HBxΔ32) lentivirus were constructed and transfected into the HepG2 cells. Then we investigated the function of MC-LR and ctHBx using the molecular biology approaches, including enzyme-linked immunosorbent assay, clone formation assay, scratch wound testing, transwell assays, carried out flow cytometry respectively to examine cell cycle and apoptosis in each group, and detected the related proteins of HBx, MEK/ERK/JNK/p38 in mitogen-activated protein kinase (MAPK) pathway and the downstream proteins such as cdc2, cdc25C, and p53 by western blotting. We found that the protein phosphorylase 2A (PP2A) enzyme activity in MC-LR and HBxΔ32/HBxΔ4 groups decreased more than in MC-LR and HBx group at the same time point and MC-LR concentration (P < 0.05). Meanwhile the proliferation, migration, invasion and colony formation capability of HepG2 cells were significantly enhanced in MC-LR and ctHBx groups (P < 0.05). In addition the proportion of S stage cells in the MC-LR-treated HBxΔ32/HBxΔ4 groups was significantly greater than that in the untreated groups (P < 0.05). Furthermore, the protein expression of MAPK signaling pathway including phospho-MEK1/2, ERKl/2, p38, and JNK were up-regulated by MC-LR and HBxΔ32, and the expression of cyclin-related proteins, including p53, cdc25C, and cdc2 were also activated (P < 0.05). Taken together, our findings revealed the essential significance of the MC-LR and ctHBx on the PP2A/MAPK/p53, cdc25C and cdc2 axis in the formation and development of HCC and identified MC-LR and ctHBx as potential causal cofactors of hepatocarcinogenesis.

Mortality of Major Cancers in Guangxi, China: Sex, Age and Geographical Differences from 1971 and 2005 Cancer;mortality;Guangxi;China;1971-2005; The incidence and mortality rates of liver and nasopharyngeal cancer in Guangxi province of China have always been among the highest in the world, and cancer is one of the major diseases that pose a threat to the health of residents in Guangxi. However, no systematic study has been performed to evaluate the time trends in the structure of cancer-related deaths and cancer mortality. In this study, we reveal sex, age and geography differences of cancers mortality between three death surveys (1971 to 1973, 1990 to 1992, and 2004 to 2005). The results show that the standardized mortality rate of cancer in Guangxi residents has risen from 43.3/100,000 to 84.2/100,000, the share of cancer deaths in all-cause deaths has increased from 13.3% to 20.7%, and cancer has become the second most common cause of death. The five major cancers, liver cancer, lung cancer, gastric cancer, nasopharyngeal cancer and colorectal cancer, account for 60% of all the cancer deaths. Cancers with growing mortality rates over the past 30 years include lung cancer, colorectal cancer, liver cancer and female breast cancer, of which lung cancer is associated with the sharpest rise in mortality, with a more than 600% rise in both men and women. Cancer death in Guangxi residents occurs mainly in the elderly population above 45 years of age, especially in people over the age of 65. The areas with the highest mortality rates for liver cancer and nasopharyngeal cancer, which feature regional high incidences, include Chongzuo and Wuzhou. Therefore, for major cancers such as liver cancer, lung cancer, gastric cancer, nasopharyngeal cancer and female breast cancer in Guangxi, we can select high-risk age groups as the target population for cancer prevention and control efforts in high-prevalence areas in a bid to achieve the ultimate goal of lowering cancer mortality in Guangxi.

Background: Microcystin-LR (MC-LR) and hepatitis B virus (HBV) are associated with hepatocellular carcinoma (HCC). However, the concentrations of MC-LR in drinking water and the synergistic effect of MC-LR and HBV on hepatocellular carcinogenesis through their disturbance of redox balance have not been fully elucidated. Methods: We measured the MC-LR concentrations in 168 drinking water samples of areas with a high incidence of HCC. The relationships between MC-LR and both redox status and liver diseases in 177 local residents were analyzed. The hepatoma cell line HepG2 transfected with C-terminal truncated hepatitis B virus X gene (Ct-HBX) were treated with MC-LR. Reactive oxygen species (ROS), superoxide dismutase (SOD), glutathione (GSH) and malondialdehyde (MDA) were measured. Cell proliferation, migration, invasion, and apoptosis were assessed with cell activity assays, scratch and transwell assays, and flow cytometry, respectively. The mRNA and protein expression-related redox status genes were analyzed with qPCR and Western blotting. Results: The average concentration of MC-LR in well water, river water and reservoir water were 57.55 ng/L, 76.74 ng/L and 132.86 ng/L respectively, and the differences were statistically significant (P < 0.05). The MC-LR levels in drinking water were correlated with liver health status, including hepatitis, clonorchiasis, glutamic pyruvic transaminase abnormalities and hepatitis B surface antigen carriage (all P values < 0.05). The serum MDA increased in subjects who drank reservoir water and were infected with HBV (P < 0.05). In the cell experiment, ROS increased when Ct-HBX-transfected HepG2 cells were treated with MC-LR, followed by a decrease in SOD and GSH and an increase in MDA. MC-LR combined with Ct-HBX promoted the proliferation, migration and invasion of HepG2 cells, upregulated the mRNA and protein expression of MAOA gene, and downregulated UCP2 and GPX1 genes. Conclusion: MC-LR and HBV may synergistically affect redox status and play an important role in hepatocarcinoma genesis.