Elevating the rice blast disease immunity through CPKA protein targeting in () with natural compounds.

Rice blast disease, instigated by (), significantly impedes global rice production. Targeting the signaling protein, cAMP-Protein Kinase A (CPKA), which facilitates appressorium development and host penetration, this study explores the potential inhibitory effects of natural compounds. Virtual screening, molecular docking and text mining approaches were used to find the nimonol and curcumin that inhibit the CPKA protein.

Extensive Deep Vein Thrombosis in a Young Man Taking Tirzepatide for Weight Loss.

Background/objective: Obesity and rapid weight loss are risk factors for developing deep vein thromboses (DVTs). Our aims were to present a patient who developed extensive DVT after relatively rapid and severe weight loss that followed taking tirzepatide and to raise the awareness among health care professionals regarding the risk of DVT that can be associated with significant weight loss due to these agents.

Case Report: We present the case of a 20-year-old young man, with raised body mass index of >35 kg/m, who was initiated on tirzepatide treatment for weight loss, with 12-kg weight lost over 6 weeks.

Risk of Microvascular Complications in Newly Diagnosed Type 2 Diabetes Patients Using Automated Machine Learning Prediction Models.

In type 2 diabetes (T2D), collective damage to the eyes, kidneys, and peripheral nerves constitutes microvascular complications, which significantly affect patients' quality of life. This study aimed to prospectively evaluate the risk of microvascular complications in newly diagnosed T2D patients in Dubai, UAE. Supervised automated machine learning in the Auto-Classifier model of the IBM SPSS Modeler package was used to predict microvascular complications in a training data set of 348 long-term T2D patients with complications using 24 independent variables as predictors and complications as targets.

Artificial intelligence-enhanced electrocardiogram for the diagnosis of cardiac amyloidosis: A systemic review and meta-analysis.

Background: Diagnosis of cardiac amyloidosis (CA) is often delayed due to variability in clinical presentation. The electrocardiogram (ECG) is one of the most common and widely available tools for assessing cardiovascular diseases. Artificial intelligence (AI) models analyzing ECG have recently been developed to detect CA, but their pooled accuracy is yet to be evaluated.