GLAC-Unet: Global-Local Active Contour Loss with an Efficient U-Shaped Architecture for Multiclass Medical Image Segmentation.

The field of medical image segmentation powered by deep learning has recently received substantial attention, with a significant focus on developing novel architectures and designing effective loss functions. Traditional loss functions, such as Dice loss and Cross-Entropy loss, predominantly rely on global metrics to compare predictions with labels. However, these global measures often struggle to address challenges such as occlusion and nonuni-form intensity.

Intracerebroventricular administration of a modified hexosaminidase ameliorates late-stage neurodegeneration in a GM2 mouse model.

The GM2 gangliosidoses, Tay-Sachs disease and Sandhoff disease, are devastating neurodegenerative disorders caused by β-hexosaminidase A (HexA) deficiency. In the Sandhoff disease mouse model, rescue potential was severely reduced when HexA was introduced after disease onset. Here, we assess the effect of recombinant HexA and HexD3, a newly engineered mimetic of HexA optimized for the treatment of Tay-Sachs disease and Sandhoff disease.

Highly Diastereoselective Access to Densely Functionalized Piperidine Cores of Influenza Endonuclease Inhibitors via a Metal-Free S1 Approach.

A novel, highly diastereoselective, and metal-free synthesis of multisubstituted piperidines via an S1 approach is reported in this study. The method allows for the preparation of highly functionalized compounds with exceptional diastereomeric selectivities and consistently reproducible yields. These compounds are of significant interest due to their remarkable biological activities toward influenza endonuclease.

A deep learning-based ADRPPA algorithm for the prediction of diabetic retinopathy progression.

As an alternative to assessments performed by human experts, artificial intelligence (AI) is currently being used for screening fundus images and monitoring diabetic retinopathy (DR). Although AI models can provide quasi-clinician diagnoses, they rarely offer new insights to assist clinicians in predicting disease prognosis and treatment response. Using longitudinal retinal imaging data, we developed and validated a predictive model for DR progression: AI-driven Diabetic Retinopathy Progression Prediction Algorithm (ADRPPA).

Epidemiology of viral gastroenteritis in children and genetic diversity of rotavirus strains in Kolkata, West Bengal after introduction of rotavirus vaccine.

Background: Despite global rotavirus vaccination efforts, rotavirus remains a leading cause of childhood deaths from acute gastroenteritis. Post-vaccination studies in India, particularly in eastern India, have been limited, despite high prevalence of rotavirus in this region prior to vaccine introduction. This study was conducted to assess the impact of rotavirus vaccine on the epidemiology of rotavirus and other enteric viruses, as well as the changes in the diversity of rotavirus strains among children (≤5 years) with acute gastroenteritis.