Design, synthesis, biological evaluation, and molecular modeling studies of some quinazolin-4(3)-one-benzenesulfonamide hybrids as potential α-glucosidase inhibitors.

Diabetes mellitus is a chronic metabolic disorder characterized by hyperglycemia, posing serious health risks and becoming increasingly prevalent. Prolonged hyperglycemia can lead to complications such as nephropathy, neuropathy, retinopathy, cardiovascular damage, and blindness. Controlling hyperglycemia through α-glucosidase inhibitors, which slow down carbohydrate breakdown, is an effective treatment strategy.

A novel deep learning-based perspective for tooth numbering and caries detection.

Objectives: The aim of this study was automatically detecting and numbering teeth in digital bitewing radiographs obtained from patients, and evaluating the diagnostic efficiency of decayed teeth in real time, using deep learning algorithms.

Methods: The dataset consisted of 1170 anonymized digital bitewing radiographs randomly obtained from faculty archives. After image evaluation and labeling process, the dataset was split into training and test datasets.

Assessment of Be-7, Pb-210 and Po-210 Activities in Airborne Particulate Matter Over Istanbul, Türkiye.

Airborne particulate matter is one of the air pollutants which can have detrimental health effects in the human body. Radionuclides adsorb onto air particles and make their way to humans primarily through inhalation. Naturally-occurring radionuclides, Pb and Po, are of notable health concern due to their relatively elevated ingestion and inhalation doses.

Dental student application of artificial intelligence technology in detecting proximal caries lesions.

Objectives: This study aimed to investigate the caries diagnosis performances of dental students after training with an artificial intelligence (AI) application utilizing deep learning techniques, a type of artificial neural network.

Methods: A total of 1200 bitewing radiographs were obtained from the institution's database and two specialist dentists labeled the caries lesions in the images. Randomly selected 1000 images were used for training purposes and the remaining 200 radiographs were used to evaluate the caries diagnostic performance of the AI.

Bridging the Gap between Gut Microbiota and Alzheimer's Disease: A Metaproteomic Approach for Biomarker Discovery in Transgenic Mice.

Alzheimer's Disease (AD) is a progressively debilitating form of dementia that affects millions of individuals worldwide. Although a vast amount of research has investigated the complex interplay between gut microbiota and neurodegeneration, the metaproteomic effects of microbiota on AD pathogenesis remain largely uncharted territory. This study aims to reveal the role of gut microbiota in AD pathogenesis, particularly regarding changes in the proteome and molecular pathways that are intricately linked to disease progression.