Predictive model and risk analysis for coronary heart disease in people living with HIV using machine learning.

Objective: This study aimed to construct a coronary heart disease (CHD) risk-prediction model in people living with human immunodeficiency virus (PLHIV) with the help of machine learning (ML) per electronic medical records (EMRs).

Methods: Sixty-one medical characteristics (including demography information, laboratory measurements, and complicating disease) readily available from EMRs were retained for clinical analysis. These characteristics further aided the development of prediction models by using seven ML algorithms [light gradient-boosting machine (LightGBM), support vector machine (SVM), eXtreme gradient boosting (XGBoost), adaptive boosting (AdaBoost), decision tree, multilayer perceptron (MLP), and logistic regression].

Prediction of the risk of cytopenia in hospitalized HIV/AIDS patients using machine learning methods based on electronic medical records.

Background: Cytopenia is a frequent complication among HIV-infected patients who require hospitalization. It can have a negative impact on the treatment outcomes for these patients. However, by leveraging machine learning techniques and electronic medical records, a predictive model can be developed to evaluate the risk of cytopenia during hospitalization in HIV patients.

Anemia and opportunistic infections in hospitalized people living with HIV: a retrospective study.

Background: There is a high prevalence of anemia among people living with HIV in Guangxi, China. Therefore, we investigated anemia and opportunistic infections in hospitalized people living with HIV and explored the risk factors related to anemia in people living with HIV to actively prevent anemia in people living with HIV.

Methods: We retrospectively studied people living with HIV admitted to Guangxi Chest Hospital from June 2016 to October 2021.

Epidemiology of extrapulmonary tuberculosis in central Guangxi from 2016 to 2021.

The burden of extrapulmonary tuberculosis (EPTB) has gradually increased in recent years, but not enough epidemiological data is available from central Guangxi. To better understand the epidemiology of EPTB in central Guangxi and identify risk factors associated with them, we retrospectively investigated the epidemiology of tuberculosis (TB), especially EPTB, among patients admitted to the Chest Hospital of Guangxi Zhuang Autonomous Region between 2016 and 2021. We excluded those infected with both pulmonary tuberculosis (PTB) and EPTB, reported the proportion and incidence of PTB or EPTB, and compared the demographic characteristics and risk factors of EPTB and PTB cases using univariate and multivariate logistic regression models.

Lncap-AI prostate cancer cell line establishment by Flutamide and androgen-free environment to promote cell adherent.

Background: To establish castration-resistant prostate cancer (CRPC) - Lncap androgen-independent (AI) cell line from Lncap androgen-dependent (AD) cell line, and explore the different molecular biological between these two cell lines.

Methods: The Lncap-AD cell line was cultured and passaged 60 times over 16 months. The morphology of the Lncap-AI cell line was observed.

Influence of sleep disruption on inflammatory bowel disease and changes in circadian rhythm genes.

According to clinical investigations, sleep disruption (SD) can influence the immune system and cause inflammatory bowel disease (IBD). However, the detailed effects of sleep on IBD development and progression have not been clarified. Here, we used dextran sulfate sodium (DSS) to induce colitis in mice, and then interfered with SD (day-time 8:00 a.

Screening and Identification of Human Endogenous Retrovirus-K mRNAs for Breast Cancer Through Integrative Analysis of Multiple Datasets.

Objective: Human endogenous retroviruses (HERVs) make up 8% of the human genome. HERVs are biologically active elements related to multiple diseases. HERV-K, a subfamily of HERVs, has been associated with certain types of cancer and suggested as an immunologic target in some tumors.

Long noncoding RNA HCP5 suppresses skin cutaneous melanoma development by regulating gene expression via sponging miR-12.

Objective: This research aimed to investigate the role and mechanism of long noncoding RNA (lncRNA) HCP5 in skin cutaneous melanoma (SKCM).

Materials And Methods: Survival analysis was performed using The Cancer Genome Atlas (TCGA)-SKCM data and SKCM patients' clinical data. Primary SKCM cells were derived from patients' pathologic tissue specimens.