An Integrated Machine Learning Framework Identifies Prognostic Gene Pair Biomarkers Associated with Programmed Cell Death Modalities in Clear Cell Renal Cell Carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is a common and lethal urological malignancy for which there are no effective personalized therapeutic strategies. Programmed cell death (PCD) patterns have emerged as critical determinants of clinical prognosis and immunotherapy responses. However, the actual clinical relevance of PCD processes in ccRCC is still poorly understood. METHODS: We screened for PCD-related gene pairs through single-sample gene set enrichment analysis (ssGSEA), consensus cluster analysis, and univariate Cox regression analysis. A novel machine learning framework incorporating 12 algorithms and 113 unique combinations were used to develop the cell death-related gene pair score (CDRGPS). Additionally, a radiomic score (Rad_Score) derived from computed tomography (CT) image features was used to classify the CDRGPS status as high or low. Finally, we conclusively verified the function of PRSS23 in ccRCC. RESULTS: The CDRGPS was developed through an integrated machine learning approach that leveraged 113 algorithm combinations. CDRGPS represents an independent prognostic biomarker for overall survival and demonstrated consistent performance between training and external validation cohorts. Moreover, CDRGPS showed better prognostic accuracy compared to seven previously published cell death-related signatures. In addition, patients classified as high-risk by CDRGPS exhibited increased responsiveness to tyrosine kinase inhibitors (TKIs), mammalian Target of Rapamycin (mTOR) inhibitors, and immunotherapy. The Rad_Score demonstrated excellent discrimination for predicting high versus low CDRGPS status, with an area under the curve (AUC) value of 0.813 in the Cancer Imaging Archive (TCIA) database. PRSS23 was identified as a significant factor in the metastasis and immune response of ccRCC, thereby validating experimental in vitro results. CONCLUSIONS: CDRGPS is a robust and non-invasive tool that has the potential to improve clinical outcomes and enable personalized medicine in ccRCC patients.

Association between triglyceride glucose-body mass and one-year all-cause mortality of patients with heart failure: a retrospective study utilizing the MIMIC-IV database.

BACKGROUND: The triglyceride glucose-body mass (TyG-BMI) index is acknowledged as both a reliable indicator of the risk of cardiovascular disease and an accurate surrogate biomarker for evaluating insulin resistance (IR). The importance of the TyG-BMI index among people with heart failure (HF), however, requires more investigation. The objective of this study was to inquire about the relationship between HF patients' TyG-BMI index and their risk of 360-day mortality. METHODS: The Medical Information Mart for Intensive Care (MIMIC-IV) database provided the study's patient data, which were divided into quartiles according to their TyG-BMI index. The endpoint was mortality from all causes within 360 days. Kaplan-Meier analysis was used to compare this primary endpoint amongst the four groups indicated above. The association between the TyG-BMI index and the endpoint was investigated using restricted cubic splines and Cox proportional hazards analysis. RESULTS: The study enrolled a total of 423 patients with HF (59.2% male), of whom 70 patients (16.9%) died within 360 days. Patients with higher TyG-BMI indexes had significantly lower mortality risks, according to the Kaplan-Meier analysis (log-rank P = 0.003). Furthermore, the restricted cubic spline analysis illustrated a decrease in the risk of all-cause mortality with an increasing TyG-BMI index. Additionally, multivariable Cox proportional hazards analyses showed that the risk of 360-day death from all causes was considerably higher in the lowest quartile of TyG-BMI. In comparison to the lowest TyG-BMI group, the fully adjusted Cox model yielded a hazard ratio (HR) of 0.24 (95% CI: 0.10, 0.59; p = 0.002) for 360-day mortality. CONCLUSIONS: In patients diagnosed with HF, a lower TyG-BMI index is strongly related to a higher risk of 360-day mortality. This index can be employed to categorize the risk levels of patients with HF and predict their one-year all-cause mortality .

Development of machine learning prognostic models for overall survival of prostate cancer patients with lymph node-positive.

Prostate cancer (PCa) patients with lymph node involvement (LNI) constitute a single-risk group with varied prognoses. Existing studies on this group have focused solely on those who underwent prostatectomy (RP), using statistical models to predict prognosis. This study aimed to develop an easily accessible individual survival prediction tool based on multiple machine learning (ML) algorithms to predict survival probability for PCa patients with LNI. A total of 3280 PCa patients with LNI were identified from the Surveillance, Epidemiology, and End Results (SEER) database, covering the years 2000-2019. The primary endpoint was overall survival (OS). Gradient Boosting Survival Analysis (GBSA), Random Survival Forest (RSF), and Extra Survival Trees (EST) were used to develop prognosis models, which were compared to Cox regression. Discrimination was evaluated using the time-dependent areas under the receiver operating characteristic curve (time-dependent AUC) and the concordance index (c-index). Calibration was assessed using the time-dependent Brier score (time-dependent BS) and the integrated Brier score (IBS). Moreover, the beeswarm summary plot in SHAP (SHapley Additive exPlanations) was used to display the contribution of variables to the results. The 3280 patients were randomly split into a training cohort (n = 2624) and a validation cohort (n = 656). Nine variables including age at diagnosis, race, marital status, clinical T stage, prostate-specific antigen (PSA) level at diagnosis, Gleason Score (GS), number of positive lymph nodes, radical prostatectomy (RP), and radiotherapy (RT) were used to develop models. The mean time-dependent AUC for GBSA, RSF, and EST was 0.782 (95% confidence interval [CI] 0.779-0.783), 0.779 (95% CI 0.776-0.780), and 0.781 (95% CI 0.778-0.782), respectively, which were higher than the Cox regression model of 0.770 (95% CI 0.769-0.773). Additionally, all models demonstrated almost similar calibration, with low IBS. A web-based prediction tool was developed using the best-performing GBSA, which is accessible at https://pengzihexjtu-pca-n1.streamlit.app/ . ML algorithms showed better performance compared with Cox regression and we developed a web-based tool, which may help to guide patient treatment and follow-up.

The active phthalate metabolite, DHEP, induces proliferation and metastasis of prostate cancer cells via upregulation of ß-catenin and downregulation of KLF7.

Phthalates such as DHEP are among the widely used compounds in industry. It has been shown that DHEP can convey various biological consequences in mammalian cells, among them, the carcinogenic effects of DHEP are emphasized. The present study aimed to assess the impact of DHEP exposure on the proliferation and invasiveness of DU145 prostate cancer cells through in vitro and in vivo models. The DU145 cells were treated with increasing concentrations of DHEP and the tumorigenic parameters were analyzed. KLF7 as a probable mediator of the effect of DHEP was either overexpressed or knocked down in DU145 to evaluate the probable impact of KLF7 on the biological effects of DHEP. The effect of DHEP was also studied in a DU145 xenograft tumor model. The moderate doses of DHEP increased the proliferation and migration of DU145 cells. In the case of gene expression patterns, DHEP reduced the levels of p53 and KLF7 while elevated the expression of ß-catenin. The knock-down of KLF7 conveyed comparable effects to that of DHEP to some degree and increased the proliferation of DU145 cells, while the transduction of KLF7 increased the expressions of p53 and p21 along with controlling the tumor size. The present study demonstrated the potential of DHEP in increasing the tumorigenic properties of DU145 cells along with a focus on the underlying mechanisms. Sustained exposure to DHEP can cause a dysregulation in balance between oncogenes and tumor suppressor genes which is the hallmark of malignant transformation. Thus, special considerations seem necessary for the safe exploitation of phthalates.

The information-motivation-behavioral skills (IMB) model of antiretroviral therapy (ART) adherence among people living with HIV in Shanghai.

The Information-Motivation-Behavioral skills (IMB) model of antiretroviral therapy (ART) adherence was applied in people living with HIV/AIDS in Shanghai, China to understand how adherence-related information, motivation and behavioral skills would affect ART adherence. The LifeWindows Information-Motivation-Behavioral Skills ART Adherence Questionnaire (LW-IMB-AAQ) was translated into Chinese and used. The IMB model was then implemented by testing standardized path estimates with standard model fitness indices in the participants. 426 participants from 11 community centres in Putuo district of Shanghai were recruited, of which 95.3% reported a high level of adherence (>95% adherence). The fitness indices of the final adjusted model were χ2 = 6.110, df = 7, p = 0.527(>0.05), CFI = 1.000(>0.9) and RMSEA = 0.000 (<0.08). In the model, information, which was separated into two sections (the perceived effect of ART on health and knowledge about ART medication), had an indirect effect on the ART adherence through behavioral skills, while motivation did not have such an effect. Neither information nor motivation had a direct effect on ART adherence. In addition, motivation was related to the two sections of information. The feasibility of the IMB model of ART adherence is verified by its application to predictive of adherence-related behaviors among HIV+ patients in this study.

Reliability and Validity of the LifeWindows Information-Motivation-Behavioral Skills Antiretroviral Therapy Adherence Questionnaire Among HIV+ Patients in Shanghai.

OBJECTIVE: The purpose of this article was to examine the validity and reliability of the LifeWindows Information-Motivation-Behavioral Skills Antiretroviral Therapy (ART) Adherence Questionnaire (LW-IMB-AAQ) among HIV+ patients in Shanghai. METHODS: We surveyed 426 HIV+ patients in Shanghai's Putuo District to examine the validity and reliability of the questionnaire. The questionnaire includes self-reported demographic characteristics, the modified version of the Community Programs for Clinical Research on AIDS Antiretroviral Medication Self-Report (CPCRA) and LW-IMB-AAQ. CPCRA was used to calculate ART adherence. LW-IMB-AAQ, including the information section, the motivation section and the behavioral skills section, was used to analyze patients' ART adherence. We analyzed data by means, standard deviation, critical ratio, and item-total correlation. Reliability was assessed by internal consistency, split-half reliability, and test-retest reliability. Validity was assessed by exploratory factor analysis (EFA), confirmatory factor analysis (CFA), convergent validity and discriminant validity. RESULTS: Item analysis showed that except for motivation item 1, all items were acceptable. For reliability, Cronbach's alpha coefficients for the three sections and the total scale were all higher than 0.7, with interclass correlation coefficients (ICC) all higher than 0.6 (p<0.001). The Spearman-Brown coefficient for the total scale was 0.825. For validity, results showed that the information section could be divided into two subscales, motivation section and behavioral skills section could be divided into three and two subscales, respectively. The final model demonstrated good validity (p=0.471, χ 2/df=0.960, CFI=1.000, GFI=0.994 and RMSEA<0.001) without motivation item 4. CONCLUSION: Excluding motivation items 1 and 4, the LifeWindows Information-Motivation-Behavioral Skills ART Adherence Questionnaire (LW-IMB-AAQ) demonstrated good validity and reliability among HIV+ patients in Shanghai.

How involuntary subordination and social support influence the association between self-esteem and depression: a moderated mediation model.

BACKGROUND: In China, young migrants are at elevated risk of mental health problems, such as depression. The influence of self-esteem on depression is well acknowledged. We examined correlates of depression and their mediating and moderating role in the association between self-esteem and depression to promote a better understanding of depression prevention among young migrants. METHODS: We conducted a cross-sectional study among young Chinese migrants. A moderated mediation model was used to test the combined effect of involuntary subordination and social support on the association between self-esteem and depression. The Johnson-Neyman method was used to identify the range of scores for which social support acted as a moderator. RESULTS: A total of 572 participants completed questionnaires. The median depression score was 19 (interquartile range: 14). Self-esteem had a negative effect on involuntary subordination (ß = - 2.1440, p < 0.001). Involuntary subordination (ß = 0.2406, p < 0.001), self-esteem (ß = - 0.3870, p < 0.01), and social support (ß = - 0.1221, p < 0.01) all had significant effects on depression. The effect of involuntary subordination on depression was moderated by social support (ß = - 0.0041, p < 0.05), and the effect decreased as social support scores increased. CONCLUSIONS: Our results indicated a mediating role of involuntary subordination and a moderating role of social support in the association between self-esteem and depression among young Chinese migrants. Future intervention strategies should focus on these factors to reduce depressive symptoms.

Enhanced expression levels of aquaporin-1 and aquaporin-4 in A549 cells exposed to silicon dioxide.

Aquaporins (AQPs), water channel proteins in the cell membranes of mammals, have been reported to be important in maintaining the water balance of the respiratory system. However, little is known regarding the role of AQP in occupational pulmonary diseases such as silicosis. The present study investigated the expression of AQP1 and AQP4 in the human A549 alveolar epithelial cell line stimulated by silica (SiO2). A549 cells were cultured and divided into four groups: Control, SiO2­stimulated, AQP1 inhibitor and AQP4 inhibitor. The cells of the SiO2­stimulated group were stimulated with SiO2 dispersed suspension (50 mg/ml). The cells of the inhibitor group were pretreated with mercury (II) chloride (HgCl2; a specific channel inhibitor of AQP1) and 2­(nicotinamide)­1,3,4­thiadiazole (TGN­020; a specific channel inhibitor of AQP4) and stimulated with SiO2. The mRNA expression levels of AQP1 and AQP4 were detected by reverse transcription­quantitative polymerase chain reaction, and the protein expression levels of AQP1 and AQP4 were detected by western blotting and immunocytochemistry. Compared with the control group, the expression levels of AQP1 and AQP4 mRNA and protein in SiO2­stimulated groups increased and subsequently decreased (AQP1 peaked at 2 h and AQP4 at 1h; both P<0.001 compared with control group). In the inhibitor group, expression levels were increased compared with controls; however, they were significantly decreased compared with the SiO2­stimulated group at 2 h (AQP1; P<0.001) and 1 h (AQP4; P<0.001). The expression of AQP1 and AQP4 increased when exposed to SiO2, and this was inhibited by HgCl2 and TGN­020, suggesting that AQP1 and AQP4 may contribute to A549 cell damage induced by SiO2. AQP1 and AQP4 may thus be involved in the initiation and development of silicosis.