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Background Diabetic nephropathy (DN) is one of the most common microvascular complications of diabetes, which is highly prevalent and harmful. Early detection of DN is an important task in preventing related diseases. Currently, most of the researches are based on traditional statistical prediction methods, and data need to meet the prerequisites it requires. It is necessary to try to apply new methods such as machine learning in the area of DN prediction for its failing to meet the needs in the field of DN prediction in recent years. Objective To construct DN prediction model using the LASSO regression and BP neural network optimized by sparrow search algorithm (SSA-BP) . Methods This study was conducted from April 2023 to August 2023, and the data was obtained from publicly available data on complications of 133 patients with diabetes mellitus in Iran. Univariate analysis was conducted using SPSS 26.0 software, and variables were screened using LASSO regression. Using the presence of DN as the dependent variable, the training and testing sets were divided into 8∶2 and 7∶3 ratios, respectively. The SSA-BP neural network was used for modeling and analysis, and the prediction performance was compared with classical machine learning models to analyze the better DN model. Model evaluation was performed based on accuracy, precision, sensitivity, specificity, F1-score and AUC indicators. Results Excluding 9 patients with type 1 diabetes, the effective sample size included in this study was 124 patients with type 2 diabetes mellitus (T2DM) , of which 73 (58.9%) were diagnosed with DN. Univariate analysis of risk factors for type 2 DN showed statistically significant for age, BMI, duration of diabetes, fasting blood glucose (FBG) , glycosylated hemoglobin (HbA1c) , low-density lipoprotein (LDL) , high-density lipoprotein (HDL) , triacylglycerol (TG) , systolic blood pressure (SBP) and diastolic blood pressure (DBP) (P

As a high metastatic tumor, patients having hepatocellular carcinoma (HCC) show poor prognosis. The carcinogenic roles of circMMP11 are generally described in the development of other cancers. However, there is a lack of studies on its involvement in HCC. Therefore, we investigated the potential role and molecular mechanisms of CircMMP11 in the development of HCC in vitro, providing preliminary evidence for the clinical treatment of HCC. First, we examined the expression of CircMMP11 in HCC tissues and cell lines in both clinical and in vitro experiments. We then used a loss-of-function assay to determine CircMMP11’s regulatory role on the malignant characteristics of HCC cells. The results showed that high expression of CircMMP11 in HCC was associated with patient overall survival. Serum CircMMP11 had good diagnostic efficacy in distinguishing HCC patients from the control group. In vitro, inhibiting CircMMP11 suppressed the malignant characteristics of human HCC cell lines by directly sequestering miR-361-3p, which further affected the downstream gene HMGB1 expression. In addition, we knocked down CircMMP11 and found that its deletion inhibited the malignant characteristics of HCC cells through the miR-361-3p/HMGB1 axis.

Ovarian cancer is characterized by aberrant activation of the mitogen-activated protein kinase (MAPK), highlighting the importance of targeting the MAPK pathway as an attractive therapeutic strategy. However, the clinical efficacy of MEK inhibitors is limited by intrinsic or acquired drug resistance. Here, we established patient-derived ovarian cancer models resistant to MEK inhibitors and demonstrated that resistance to the clinically approved MEK inhibitor trametinib was associated with enhancer reprogramming. We also showed that enhancer decommissioning induced the downregulation of negative regulators of the MAPK pathway, leading to constitutive ERK activation and acquired resistance to trametinib. Epigenetic compound screening uncovered that HDAC inhibitors could alter the enhancer reprogramming and upregulate the expression of MAPK negative regulators, resulting in sustained MAPK inhibition and reversal of trametinib resistance. Consequently, a combination of HDAC inhibitor and trametinib demonstrated a synergistic antitumor effect in vitro and in vivo, including patient-derived xenograft mouse models. These findings demonstrated that enhancer reprogramming of the MAPK regulatory pathway might serve as a potential mechanism underlying MAPK inhibitor resistance and concurrent targeting of epigenetic pathways and MAPK signaling might provide an effective treatment strategy for advanced ovarian cancer., Introduction Epithelial ovarian cancer (OV) is the leading cause of mortality from gynecological malignancies (1); the overall survival rate has remained poor at 30% to 50% for decades, mainly owing [...]

We measured expression of miRNA-145 in gallbladder carcinoma and its influence on propagation, invasion, and apoptosis of gallbladder carcinoma cells in vitro.