Ferroptosis in kidney disease: a bibliometric analysis from 2012 to 2024.

Background And Aims: Ferroptosis, a novel concept of programmed cell death proposed in 2012, in kidney disease, has garnered significant attention based on evidence of abnormal iron deposition and lipid peroxidation damage in the kidney. Our study aim to examine the trends and future research directions in the field of ferroptosis in kidney disease, so as to further explore the target or treatment strategy for clinical treatment of kidney disease.

Material And Methods: A thorough survey using the Web of Science Core Collection, focusing on literature published between 2012 and 2024 examining the interaction between kidney disease and ferroptosis was conducted.

Revealing Molecular Connections between Dissolved Organic Matter in Surface Water Sources and Their Cytotoxicity Influenced by Chlorination Disinfection.

Dissolved organic matter (DOM) is the primary precursor of disinfection products (DBPs) during chlorination. However, the compositional characteristics of DOM transformation during the chlorination process in different source waters and its relationship to cytotoxicity remain understudied. Here, we used high-resolution mass spectrometry to evaluate chlorination-induced molecular-level changes in DOM derived from different surface water sources.

Class-Wise Combination of Mixture-Based Data Augmentation for Class Imbalance Learning of Focal Liver Lesions in Abdominal CT Images.

In this paper, we propose a method to address the class imbalance learning in the classification of focal liver lesions (FLLs) from abdominal CT images. Class imbalance is a significant challenge in medical image analysis, making it difficult for machine learning models to learn to classify them accurately. To overcome this, we propose a class-wise combination of mixture-based data augmentation (CCDA) method that uses two mixture-based data augmentation techniques, MixUp and AugMix.