Decreased levels of PTCSC3 promote the deterioration of prostate cancer and affect the prognostic outcome of patients through sponge miR-182-5p.

BACKGROUND: Prostate cancer, characterized by its insidious onset and short overall survival, and has seen a rise in incidence over recent decades. This study aims to investigate the expression and molecular mechanism of lncRNA PTCSC3 (PTCSC3) in prostate cancer in order to develop new prognostic and therapeutic biomarkers. METHODS: The level of PTCSC3 in serum and cell samples of prostate cancer was quantitatively measured using RT-qPCR assays. The correlation between the variation in PTCSC3 levels and clinical indicators of patients was evaluated. The survival status of the prostate cancer patients included in the study was evaluated using Kaplan-Meier curve and multivariable Cox analysis. The impact of PTCSC3 overexpression on cell growth and activity was revealed by CCK-8 and Transwell assays. The targeting relationship between PTCSC3 and miR-182-5p was determined by bioinformatics prediction and luciferase activity. RESULTS: PTCSC3 was found to be downregulated in prostate cancer, and its low levels were associated with short overall survival in patients. It influenced the progression of prostate cancer by targeting miR-182-5p. Increasing PTCSC3 levels suppressed the proliferation, migration and invasion levels of cells, and miR-182-5p mimic counteracted PTCSC3's effects on cells. CONCLUSIONS: As a potential prognostic biological factor for prostate cancer, PTCSC3 may regulate the progression of prostate cancer by sponging miR-182-5p and affect the prognosis of patients.

Dietary choline intake and health outcomes in U.S. adults: exploring the impact on cardiovascular disease, cancer prevalence, and all-cause mortality.

BACKGROUND: Choline, an indispensable nutrient, plays a pivotal role in various physiological processes. The available evidence regarding the nexus between dietary choline intake and health outcomes, encompassing cardiovascular disease (CVD), cancer, and all-cause mortality, is limited and inconclusive. This study aimed to comprehensively explore the relationship between dietary choline intake and the aforementioned health outcomes in adults aged > 20 years in the U.S. METHODS: This study utilized data from the National Health and Nutrition Examination Survey between 2011 and 2018. Dietary choline intake was evaluated using two 24-h dietary recall interviews. CVD and cancer status were determined through a combination of standardized medical status questionnaires and self-reported physician diagnoses. Mortality data were gathered from publicly available longitudinal Medicare and mortality records. The study utilized survey-weighted logistic and Cox regression analyses to explore the associations between choline consumption and health outcomes. Restricted cubic spline (RCS) analysis was used for dose‒response estimation and for testing for nonlinear associations. RESULTS: In our study of 14,289 participants (mean age 48.08 years, 47.71% male), compared with those in the lowest quintile (Q1), the adjusted odds ratios (ORs) of CVD risk in the fourth (Q4) and fifth (Q5) quintiles of choline intake were 0.70 (95% CI 0.52, 0.95) and 0.65 (95% CI 0.47, 0.90), respectively (p for trend = 0.017). Each 100 mg increase in choline intake was associated with a 9% reduced risk of CVD. RCS analysis revealed a linear correlation between choline intake and CVD risk. Moderate choline intake (Q3) was associated with a reduced risk of mortality, with an HR of 0.75 (95% CI 0.60-0.94) compared with Q1. RCS analysis demonstrated a significant nonlinear association between choline intake and all-cause mortality (P for nonlinearity = 0.025). The overall cancer prevalence association was nonsignificant, except for colon cancer, where each 100 mg increase in choline intake indicated a 23% reduced risk. CONCLUSION: Elevated choline intake demonstrates an inverse association with CVD and colon cancer, while moderate consumption exhibits a correlated reduction in mortality. Additional comprehensive investigations are warranted to elucidate the broader health implications of choline.

Artificial intelligence annotated clinical-pathologic risk model to predict outcomes of advanced gastric cancer.

Background: Gastric cancer with synchronous distant metastases indicates a dismal prognosis. The success in survival improvement mainly relies on our ability to predict the potential benefit of a therapy. Our objective is to develop an artificial intelligence annotated clinical-pathologic risk model to predict its outcomes. Methods: In participants (n=47553) with gastric cancer of the surveillance, epidemiology, and end results program, we selected patients with distant metastases at first diagnosis, complete clinical-pathologic data and follow-up information. Patients were randomly divided into the training and test cohort at 7:3 ratio. 93 patients with advanced gastric cancer from six other cancer centers were collected as the external validation cohort. Multivariable analysis was used to identify the prognosis-related clinical-pathologic features. Then a survival prediction model was established and validated. Importantly, we provided explanations to the prediction with artificial intelligence SHAP (Shapley additive explanations) method. We also provide novel insights into treatment options. Results: Data from a total 2549 patients were included in model development and internal test (median age, 61 years [range, 53-69 years]; 1725 [67.7%] male). Data from an additional 93 patients were collected as the external validation cohort (median age, 59 years [range, 48-66 years]; 51 [54.8%] male). The clinical-pathologic model achieved a consistently high accuracy for predicting prognosis in the training (C-index: 0.705 [range, 0.690-0.720]), test (C-index: 0.737 [range, 0.717-0.757]), and external validation (C-index: 0.694 [range, 0.562-0.826]) cohorts. Shapley values indicated that undergoing surgery, chemotherapy, young, absence of lung metastases and well differentiated were the top 5 contributors to the high likelihood of survival. A combination of surgery and chemotherapy had the greatest benefit. However, aggressive treatment did not equate to a survival benefit. SHAP dependence plots demonstrated insightful nonlinear interactive associations among predictors in survival benefit prediction. For example, patients who were elderly, or poor differentiated, or presence of lung or bone metastases had a worse prognosis if they undergo surgery or chemotherapy, while patients with metastases to liver alone seemed to gain benefit from surgery and chemotherapy. Conclusion: In this large multicenter cohort study, we developed an artificial intelligence annotated clinical-pathologic risk model to predict outcomes of advanced gastric cancer. It could be used to discuss treatment options.

Oscillation and variation inequalities for the multilinear singular integrals related to Lipschitz functions.

The main purpose of this paper is to establish the weighted [Formula: see text] inequalities of the oscillation and variation operators for the multilinear Calderón-Zygmund singular integral with a Lipschitz function.