CRIECNN: Ensemble convolutional neural network and advanced feature extraction methods for the precise forecasting of circRNA-RBP binding sites.

Circular RNAs (circRNAs) have surfaced as important non-coding RNA molecules in biology. Understanding interactions between circRNAs and RNA-binding proteins (RBPs) is crucial in circRNA research. Existing prediction models suffer from limited availability and accuracy, necessitating advanced approaches. In this study, we propose CRIECNN (Circular RNA-RBP Interaction predictor using an Ensemble Convolutional Neural Network), a novel ensemble deep learning model that enhances circRNA-RBP binding site prediction accuracy. CRIECNN employs advanced feature extraction methods and evaluates four distinct sequence datasets and encoding techniques (BERT, Doc2Vec, KNF, EIIP). The model consists of an ensemble convolutional neural network, a BiLSTM, and a self-attention mechanism for feature refinement. Our results demonstrate that CRIECNN outperforms state-of-the-art methods in accuracy and performance, effectively predicting circRNA-RBP interactions from both full-length sequences and fragments. This novel strategy makes an enormous advancement in the prediction of circRNA-RBP interactions, improving our understanding of circRNAs and their regulatory roles.

A review of molecular mechanisms linked to potential renal injury agents in tropical rural farming communities.

The chronic kidney disease of unknown etiology (CKDu) is a global health concern primarily impacting tropical farming communities. Although the precise etiology is debated, CKDu is associated with environmental exposures including heat stress and chemical contaminants such as fluoride, heavy metals, and herbicide glyphosate. However, a comprehensive synthesis is lacking on molecular networks underpinning renal damage induced by these factors. Addressing this gap, here we present key molecular events associated with heat and chemical exposures. We identified that caspase activation and lipid peroxidation are common endpoints of glyphosate exposure, while vasopressin and polyol pathways are associated with heat stress and dehydration. Heavy metal exposure is shown to induce lipid peroxidation and endoplasmic reticulum stress from ROS activated MAPK, NFĸB, and caspase. Collectively, we identify that environmental exposure induced increased cellular oxidative stress as a common mechanism mediating renal cell inflammation, apoptosis, and necrosis, likely contributing to CKDu initiation and progression.