Association between body roundness index and overactive bladder: results from the NHANES 2005-2018.

BACKGROUND AND AIM: An increasing amount of research has indicated obesity greatly affects individuals with overactive bladder (OAB). However, traditional anthropometric methods present challenges in accurately assessing the likelihood of OAB. Hence, this study's objective was to identify the correlation between the body roundness index (BRI) and OAB. METHODS: The research included 12,401 individuals who participated in the National Health and Nutrition Examination Survey spanning 2005-2018. The correlation between BRI and OAB was explored by using weighted multiple logistic regression and weighted restricted cubic spline (RCS). Subgroup analyses showed the associations based on different population types. The study also analyzed the predictive capability of various anthropometric indices, including BRI, body mass index, waist circumference, and weight, in assessing the likelihood of OAB through Receiver-operating characteristic (ROC) curves. RESULTS: An independent positive correlation between OAB and BRI was identified after adjusting for potential confounders in weighted multivariate logistic models[odds ratio (OR) = 1.15, 95% confidence interval (CI), 1.12-1.17]. Weighted RCS analysis found a positive dose-response correlation between OAB and BRI. The effect size of BRI on OAB remained stable across all prespecified subgroups (all P for interactions > 0.05). In ROC analysis, BRI showed better discriminatory ability for OAB compared with other anthropometric measures for both genders (all P < 0.01). The best BRI cutoff for predicting OAB was lower for men (5.151) than for women (5.383), suggesting that men were more susceptible to changes in BRI than women. CONCLUSIONS: This study demonstrated that a raised BRI is correlated with a higher likelihood of OAB. Due to the effectiveness and non-invasiveness of BRI in predicting OAB, it is expected to become the preferred method for early detection and management strategies.

A nomogram based on 4-lncRNAs signature for improving prognostic prediction of hepatocellular carcinoma.

PURPOSE: Long noncoding RNAs (lncRNAs) with abnormal expression are frequently seen in hepatocellular cancer patients (HCC). Previous studies have reported the correlation between lncRNA and prognosis processes of HCC patients. In this research, a graphical nomogram with lncRNAs signatures, T, M phases was developed using the rms R package to estimate the survival rates of HCC patients in year 1, 3, and 5. METHODS: To find the prognostic lncRNA and create the lncRNA signatures, univariate Cox survival analysis and multivariate Cox regression analysis were chosen. The rms R software package was used to build a graphical nomogram based on lncRNAs signatures to predict the survival rates in of HCC patients in 1, 3, and 5 years. Using "edgeR", "DEseq" R packages to find the differentially expressed genes (DEGs). RESULTS: Firstly, a total of 5581 DEGs including 1526 lncRNAs and 3109 mRNAs were identified through bioinformatic analysis, of which 4 lncRNAs (LINC00578, RP11-298O21.2, RP11-383H13.1, RP11-440G9.1) were identified to be strongly related to the prognosis of liver cancer (P < 0.05). Moreover, we constructed a 4-lncRNAs signature by using the calculated regression coefficient. 4-lncRNAs signature is identified to significantly correlated with clinical and pathological characteristics (such as T stage, and death status of HCC patients). CONCLUSIONS: A prognostic nomogram on the base of 4-lncRNAs markers was built, which is capable to accurately predict the 1-year, 3-year, and 5-year survival of HCC patients after the construction of the 4-lncRNAs signature linked with prognosis of HCC.

Bisphenol AF induces apoptosis via estrogen receptor beta (ERß) and ROS-ASK1-JNK MAPK pathway in human granulosa cell line KGN.

Bisphenol AF (BPAF) is an emerging environmental pollutant. Although BPAF is widely spread in the environment and human surroundings, its interference with ovarian function has not been fully elucidated. The aim of this study was to identify the mechanism underlying the effect of BPAF on the apoptosis of KGN cells, which maintain the physiological characteristics of ovarian granulosa cells. Our results indicated that BPAF induces KGN cell apoptosis in a concentration- and time-dependent manner. Meanwhile, BPAF exposure significantly promoted the expression of pro-apoptotic proteins, including Bax, Bid and Bak, while the expression of anti-apoptotic proteins, such as Bcl-2, Bcl-xL and Mcl-1, decreased significantly. We further detected a significant increase in intracellular ROS levels in response to high concentrations of BPAF exposure. After blocking the corresponding pathway, it was found that ROS mediates ASK1 and JNK activation. Furthermore, the role of Ca2+ overload and estrogen receptor ß (ERß) in BPAF-induced KGN cell apoptosis was also confirmed by using inhibitors. These results suggest that BPAF has potential reproductive toxicity for females, and ROS-ASK1-JNK axis may play a key role in BPAF-induced ovarian dysfunction. In addition, Ca2+ overload and ERß pathway activation may also be an important mechanism of reproductive toxicity of BPAF.

A nomogram based on 4-lncRNAs signature for improving prognostic prediction of hepatocellular carcinoma

Purpose Long noncoding RNAs (lncRNAs) with abnormal expression are frequently seen in hepatocellular cancer patients (HCC). Previous studies have reported the correlation between lncRNA and prognosis processes of HCC patients. In this research, a graphical nomogram with lncRNAs signatures, T, M phases was developed using the rms R package to estimate the survival rates of HCC patients in year 1, 3, and 5. Methods To find the prognostic lncRNA and create the lncRNA signatures, univariate Cox survival analysis and multivariate Cox regression analysis were chosen. The rms R software package was used to build a graphical nomogram based on lncRNAs signatures to predict the survival rates in of HCC patients in 1, 3, and 5 years. Using “edgeR”, “DEseq” R packages to find the differentially expressed genes (DEGs). Results Firstly, a total of 5581 DEGs including 1526 lncRNAs and 3109 mRNAs were identified through bioinformatic analysis, of which 4 lncRNAs (LINC00578, RP11-298O21.2, RP11-383H13.1, RP11-440G9.1) were identified to be strongly related to the prognosis of liver cancer (P < 0.05). Moreover, we constructed a 4-lncRNAs signature by using the calculated regression coefficient. 4-lncRNAs signature is identified to significantly correlated with clinical and pathological characteristics (such as T stage, and death status of HCC patients). Conclusions A prognostic nomogram on the base of 4-lncRNAs markers was built, which is capable to accurately predict the 1-year, 3-year, and 5-year survival of HCC patients after the construction of the 4-lncRNAs signature linked with prognosis of HCC (AU)