Adsorption kinetics and isotherm characteristics of phosphorus in the riverbed sediment of Ganga and Yamuna at Prayagraj, India.

Understanding the mechanism and storage of phosphorus (P) in riverbed sediment is a prerequisite for better management and protection of water resources, ensuring a sustainable ecosystem and safe water for human use. This study describes the adsorption behaviour of P in sediment collected from the Ganga and Yamuna rivers at Prayagraj, India, employing both kinetics and isotherm models. The sediment showed significant physicochemical characteristics, with Ganga characterized by high sand (91.

A Rare Presentation of Erosive Gastritis Caused by Helicobacter heilmannii Infection.

 () is an uncommon gastric pathogen increasingly recognized for its role in gastrointestinal diseases. Unlike  (),  is rarely detected and often overlooked. It is typically associated with milder pathological features, including less neutrophilic activity, reduced mononuclear infiltration, and endoscopic signs of chronic gastritis without erosions or ulcers.

Ethical framework for responsible foundational models in medical imaging.

The emergence of foundational models represents a paradigm shift in medical imaging, offering extraordinary capabilities in disease detection, diagnosis, and treatment planning. These large-scale artificial intelligence systems, trained on extensive multimodal and multi-center datasets, demonstrate remarkable versatility across diverse medical applications. However, their integration into clinical practice presents complex ethical challenges that extend beyond technical performance metrics.

Large Scale MRI Collection and Segmentation of Cirrhotic Liver.

Liver cirrhosis represents the end stage of chronic liver disease, characterized by extensive fibrosis and nodular regeneration that significantly increases mortality risk. While magnetic resonance imaging (MRI) offers a non-invasive assessment, accurately segmenting cirrhotic livers presents substantial challenges due to morphological alterations and heterogeneous signal characteristics. Deep learning approaches show promise for automating these tasks, but progress has been limited by the absence of large-scale, annotated datasets.