Chronic Hepatitis B in Women of Childbearing Age and Pregnant Women in China: A Cross-Sectional Study.

Pregnant women and women of childbearing age were enrolled in our study and their knowledge about the Hepatitis B virus (HBV) and chronic hepatitis B (CHB) was evaluated. A questionnaire was distributed to every woman in the cross-sectional study. The questionnaire was answered by all participants before they received health education and advice about HBV and CHB from the doctors visited. Data collected from all answers were analyzed using the χ2 test and logistic regression models. A total of 206 pregnant women and women of childbearing age with CHB infection were enrolled in the study during their first visit to the Infectious Diseases Clinic of the Third Affiliated Hospital of Guangzhou Medical University. Some women of childbearing age (40.8%) and pregnant women with CHB infection (30.6%) still believed HBV could be transmitted through diet and/or mosquito bites. Some women of childbearing age and pregnant women with CHB infection had limited knowledge of the prevention of HBV transmission (111 of 206, 53.9%). Women with higher levels of education had more knowledge about HBV (senior middle school, P = 0.02; university, P <0.01). The majority of participants were willing to take antiviral medicine to decrease the mother-to-child transmission (MTCT) rate of HBV. Some women of childbearing age and/or pregnant women with CHB infection have relatively limited knowledge about HBV or CHB. This situation contributes to the timeliness, or lack thereof, of these women with CHB to see a doctor and receive antiviral therapy. As a result, the morbidity and mortality of HBV-related complications could increase along with the rate of MTCT of HBV.

Accurate integration of multiple heterogeneous single-cell RNA-seq data sets by learning contrastive biological variation.

For most biological and medical applications of single-cell transcriptomics, an integrative study of multiple heterogeneous single-cell RNA sequencing (scRNA-seq) data sets is crucial. However, present approaches are unable to integrate diverse data sets from various biological conditions effectively because of the confounding effects of biological and technical differences. We introduce single-cell integration (scInt), an integration method based on accurate, robust cell-cell similarity construction and unified contrastive biological variation learning from multiple scRNA-seq data sets. scInt provides a flexible and effective approach to transfer knowledge from the already integrated reference to the query. We show that scInt outperforms 10 other cutting-edge approaches using both simulated and real data sets, particularly in the case of complex experimental designs. Application of scInt to mouse developing tracheal epithelial data shows its ability to integrate development trajectories from different developmental stages. Furthermore, scInt successfully identifies functionally distinct condition-specific cell subpopulations in single-cell heterogeneous samples from a variety of biological conditions.

scMTD: a statistical multidimensional imputation method for single-cell RNA-seq data leveraging transcriptome dynamic information.

BACKGROUND: Single-cell RNA sequencing (scRNA-seq) provides a powerful tool to capture transcriptomes at single-cell resolution. However, dropout events distort the gene expression levels and underlying biological signals, misleading the downstream analysis of scRNA-seq data. RESULTS: We develop a statistical model-based multidimensional imputation algorithm, scMTD, that identifies local cell neighbors and specific gene co-expression networks based on the pseudo-time of cells, leveraging information on cell-level, gene-level, and transcriptome dynamic to recover scRNA-seq data. Compared with the state-of-the-art imputation methods through several real-data-based analytical experiments, scMTD effectively recovers biological signals of transcriptomes and consistently outperforms the other algorithms in improving FISH validation, trajectory inference, differential expression analysis, clustering analysis, and identification of cell types. CONCLUSIONS: scMTD maintains the gene expression characteristics, enhances the clustering of cell subpopulations, assists the study of gene expression dynamics, contributes to the discovery of rare cell types, and applies to both UMI-based and non-UMI-based data. Overall, scMTD's reliability, applicability, and scalability make it a promising imputation approach for scRNA-seq data.

Huperzine A protects against traumatic brain injury through anti-oxidative effects via the Nrf2-ARE pathway.

OBJECTIVES: Traumatic brain injury (TBI) is a prominent health problem worldwide and it may lead to cognitive dysfunction, disability, and even death. To date, there is no effective treatment for TBI. Our previous study showed that Huperzine A (HupA) improved cognitive function in a mouse model of TBI. However, the detailed mechanism of HupA remains unaddressed. In this study, we investigated the possible mechanism of the neuroprotective effect of HupA. MATERIALS AND METHODS: C57BL/6 mice were randomly divided into 3 groups as sham, injured with vehicle treatment, and injured with HupA treatment groups. The Morris water maze task was used to evaluate the impairment of special learning and memory. Brain edema was as-sessed by measuring the wet weight to dry weight ratio. Malondialdehyde (MDA) and glutathione peroxidase (GPx) levels were measured for oxidative stress. Protein expressions of nuclear factor erythroid 2-related factor 2 (Nrf2), heme oxygen-ase-1(HO-1), and synaptophysin were detected by Western blot. The brain sections were stained with hematoxylin-eosin (H&E) for histology study. RESULTS: We found that HupA therapy improved histology and cognitive functional outcomes after TBI. HupA reduced brain edema in TBI mice. furthermore, HupA inhibited ox-idative stress. HupA promoted nuclear factor erythroid 2-related factor 2 (Nrf2) nu-clear translocation and activated Nrf2 after TBI. CONCLUSION: HupA protects against TBI through antioxidative effects via the Nrf2-ARE pathway.