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]. The performance of this model was assessed using the area under the receiver operating characteristic curve (AUC). Shapley additive explanation (SHAP) was further applied to interpret the findings of the best-performing model. RESULTS: The LightGBM model exhibited the highest AUC (0.849; 95% CI, 0.814-0.883). Additionally, the SHAP plot per the LightGBM depicted that age, heart failure, hypertension, glucose, serum creatinine, indirect bilirubin, serum uric acid, and amylase can help identify PLHIV who were at a high or low risk of developing CHD. CONCLUSION: This study developed a CHD risk prediction model for PLHIV utilizing ML techniques and EMR data. The LightGBM model exhibited improved comprehensive performance and thus had higher reliability in assessing the risk predictors of CHD. Hence, it can potentially facilitate the development of clinical management techniques for PLHIV care in the era of EMRs.

HERVK-mediated regulation of neighboring genes: implications for breast cancer prognosis.

Human endogenous retroviruses (HERVs) are the remnants of ancient retroviral infections integrated into the human genome. Although most HERVs are silenced or rendered inactive by various regulatory mechanisms, they retain the potential to influence the nearby genes. We analyzed the regulatory map of 91 HERV-Ks on neighboring genes in human breast cancer and investigated the impact of HERV-Ks on the tumor microenvironment (TME) and prognosis of breast cancer. Nine RNA-seq datasets were obtained from GEO and NCBI SRA. Differentially expressed genes and HERV-Ks were analyzed using DESeq2. Validation of high-risk prognostic candidate genes using TCGA data. These included Overall survival (multivariate Cox regression model), immune infiltration analysis (TIMER), tumor mutation burden (maftools), and drug sensitivity analysis (GSCA). A total of 88 candidate genes related to breast cancer prognosis were screened, of which CD48, SLAMF7, SLAMF1, IGLL1, IGHA1, and LRRC8A were key genes. Functionally, these six key genes were significantly enriched in some immune function-related pathways, which may be associated with poor prognosis for breast cancer (p = 0.00016), and the expression levels of these genes were significantly correlated with the sensitivity of breast cancer treatment-related drugs. Mechanistically, they may influence breast cancer development by modulating the infiltration of various immune cells into the TME. We further experimentally validated these genes to confirm the results obtained from bioinformatics analysis. This study represents the first report on the regulatory potential of HERV-K in the neighboring breast cancer genome. We identified three key HERV-Ks and five neighboring genes that hold promise as novel targets for future interventions and treatments for breast cancer.

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. Among 30,893 TB patients, 67.25% (20,774) had PTB and 32.75% (10,119) had EPTB. Among EPTB, pleural, skeletal, lymphatic, pericardial, meningeal, genitourinary, intestinal, and peritoneal TB accounted for 49.44%, 27.20%, 8.55%, 4.39%, 3.36%, 1.48%, 0.87%, and 0.79%, respectively. Patients who were younger (age < 25), from rural areas, Zhuang and other ethnic groups, and diagnosed with anemia and HIV infection were more likely to develop EPTB. However, patients with diabetes and COPD were less likely to have EPTB. From 2016 to 2021, the proportion of PTB cases decreased from 69.73 to 64.07%. The percentage of EPTB cases increased from 30.27 to 35.93%, with the largest increase in skeletal TB from 21.48 to 34.13%. The epidemiology and risk factors of EPTB in central Guangxi are different from those of PTB. The incidence of EPTB is increasing and further studies are needed to determine the reasons for it.

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. Detailed information on the sociodemographic and clinical features of the participants was collected. The X2 test was used to compare the prevalence between the anemic and non-anemic groups. The logistic regression analysis was applied to exclude confounding factors and identify factors related to anemia. RESULTS: Among 5645 patients with HIV, 1525 (27.02%) had anemia. The overall prevalence of mild, moderate, and severe anemia was 4.66%, 14.08%, and 8.27%, respectively. The factors significantly related to increased risk of anemia were CD4 count < 50 cells/µl (aOR = 2.221, 95% CI = [1.775, 2.779]), CD4 count 50-199 cells/µl (aOR = 1.659, 95% CI = [1.327, 2. 073]), female (aOR = 1.644, 95% CI = [1.436, 1.881]) co-infected with HCV (aOR = 1.465, 95% CI = [1.071, 2.002]), PM (aOR = 2.356, 95% CI = [1.950, 2.849]), or TB (aOR = 1.198, 95% CI = [1.053, 1.365]). CONCLUSIONS: Within Guangxi of China, 27.02% of hospitalized people living with HIV presented with anemia. Most patients with anemia were in the mild to moderate stage. The low CD4 count, female gender, and concomitant infection with Penicillium marneffei, Hepatitis C virus, or Tuberculosis were independent correlates of anemia. Thus, these findings would be helpful to clinicians in preventing and intervening in anemia in people living with HIV.

Effects of Aloe Vera in the Treatment of Oral Ulcers: A Systematic Review and Meta-Analysis of Randomised Controlled Trials.

PURPOSE: To analyse the effects of aloe vera on the treatment of oral ulcers. MATERIALS AND METHODS: Relevant studies were identified from PubMed, Embase, ClinicalTrials.gov, SinoMed, Web of Science and Cochrane Library. Randomised controlled trials (RCTs) involving aloe vera (AV) in the treatment of oral ulcers were included. The data were extracted and pooled for meta-analysis to compare the clinical outcomes of patients with oral ulcers in terms of treatment effect, the size of ulcers, Visual Analogue Scale (VAS) for pain, and therapy duration. The standardised mean differences (SMD) with 95% confidence intervals (CI) were determined for the main outcomes, heterogeneity was analysed using the I2 test, and the studies' risk of bias was evaluating using the Cochrane risk of bias assessment tool. RESULTS: The study included 9 trials with a total of 847 participants. Seven trials were included in the meta-analysis. The results indicated no statistically significant differences in pain scores as assessed by the VAS (I2 = 95%, p = 0.89; SMD: -0.12, 95% CI: -1.84, 1.60) and size of ulcers (I2 = 88%, p = 0.60; SMD: -0.29, 95% CI: -1.39, 0.81). Clinical efficacy of the aloe vera group was better compared to control group (I2 = 89%, p = 0.007; RR: 2.25, 95% CI: 1.25, 4.06). Therapy duration was statistically significantly lower following AV gel application in two of the studies (I2 = 0%, p < 0.001; SMD: -1.32, 95% CI: -1.84, -0.79). Considering the results in a systematic manner, AV accelerated tissue epithelialisation and the wound-healing process. CONCLUSION: Compared with other interventions, aloe vera has a better therapeutic effect and shorter healing time. It is comparable with other interventions in relieving pain and reducing ulcer size, but it has higher safety and almost no side effects.

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. The expression levels of HERV-K in breast cancer (BCa) have been studied as biomarkers and immunologic therapeutic targets. However, HERV-K has multiple copies in the human genome, and few studies determined the transcriptional profile of HERV-K copies across the human genome for BCa. Methods: Ninety-one HERV-K indexes with entire proviral sequences were used as the reference database. Nine raw sequencing datasets with 243 BCa and 137 control samples were mapped to this database by Salmon software. The differential proviral expression across several groups was analyzed by DESeq2 software. Results: First, the clustering of each dataset demonstrated that these 91 HERV-K proviruses could well cluster the BCa and control samples when the normal controls were normal cells or healthy donor tissues. Second, several common HERV-K proviruses that are closely related with BCa risk were significantly differentially expressed (p adj < 0.05 and absolute log2FC > 1.5) in the tissues and cell lines. Additionally, almost all the HERV-K proviruses had higher expression in BCa tissue than in healthy donor tissue. Notably, we first found the expression of 17p13.1 provirus that located with TP53 should regulate TP53 expression in ER+ and HER2+ BCa. Conclusion: The expression profiling of these 91 HERV-K proviruses can be used as biomarkers to distinguish individuals with BCa and healthy controls. Some proviruses, especially 17p13.1, were strongly associated with BCa risk. The results suggest that HERV-K expression profiles may be appropriate biomarkers and targets for BCa.

Associations of perinatal exposure to PM2.5 with gestational weight gain and offspring birth weight.

BACKGROUND: PM2.5 have been associated with weight change in animal models and non-pregnant populations. Evidence of associations between PM2.5 and gestational weight gain (GWG), an important determinant of course and outcomes of pregnancy, and subsequent birth outcomes is limited. METHODS: The study was conducted among a subset of participants from the Omega Study, a prospective pregnancy cohort. Exposure to PM2.5 (µg/m3) was ascertained for participants (N = 855) based on their residential address using a validated national spatiotemporal model. Adjusted multivariable linear regression models were used to estimate associations of trimester-specific and pregnancy-month PM2.5 exposures with early (<20 weeks gestation), late (≥20 weeks gestation), and total GWG and infant birth weight. Stratified models and product terms were used to examine whether pre-pregnancy BMI (ppBMI) and infant sex modified the associations. RESULTS: Average monthly PM2.5 exposure during the first, second, and third trimesters were 7.3 µg/m3, 7.9 µg/m3, and 7.7 µg/m3, respectively. Higher third trimester PM2.5 exposure was associated with higher late (0.40 kg per 5 µg/m (McDowell et al., 2018); 95%CI: 0.12, 0.67) and total (0.35 kg; 95%CI: 0.01, 0.70) GWG among participants with normal ppBMI. Higher second month PM2.5 exposure was associated with lower early (-0.70 kg; 95%CI: 1.22, -0.18), late (-0.84 kg; 95% CI: 1.54, -0.14), and total (-1.70 kg; 95%CI: 2.57, -0.82) GWG among participants with overweight/obese ppBMI. Product terms between PM2.5 and ppBMI were significant for second month PM2.5 exposure and early (p-value = 0.01) and total GWG (p-value<0.01). Higher third trimester PM2.5 exposure was associated with higher birth weight, though higher fourth month PM2.5 exposure was associated with lower birth weight, particularly among those with normal ppBMI and male infants. CONCLUSIONS: Associations of PM2.5 with GWG vary by exposure window and ppBMI, while associations of PM2.5 with birth weight potentially vary by exposure window, ppBMI and infant sex. Further exploration of associations between PM2.5 and maternal/child health outcomes are needed.