Comparative Analysis of Vision Transformers and Conventional Convolutional Neural Networks in Detecting Referable Diabetic Retinopathy.

Objective: Vision transformers (ViTs) have shown promising performance in various classification tasks previously dominated by convolutional neural networks (CNNs). However, the performance of ViTs in referable diabetic retinopathy (DR) detection is relatively underexplored. In this study, using retinal photographs, we evaluated the comparative performances of ViTs and CNNs on detection of referable DR.

Inflammasome signaling is dispensable for ß-amyloid-induced neuropathology in preclinical models of Alzheimer's disease.

Background: Alzheimer's disease (AD) is the most common neurodegenerative disorder affecting memory and cognition. The disease is accompanied by an abnormal deposition of ß-amyloid plaques in the brain that contributes to neurodegeneration and is known to induce glial inflammation. Studies in the mouse model of ß-amyloid-induced neuropathology have suggested a role for inflammasome activation in ß-amyloid-induced neuroinflammation and neuropathology.

Inflammasomes in neuroinflammatory and neurodegenerative diseases.

Neuroinflammation and neurodegeneration often result from the aberrant deposition of aggregated host proteins, including amyloid-β, α-synuclein, and prions, that can activate inflammasomes. Inflammasomes function as intracellular sensors of both microbial pathogens and foreign as well as host-derived danger signals. Upon activation, they induce an innate immune response by secreting the inflammatory cytokines interleukin (IL)-1β and IL-18, and additionally by inducing pyroptosis, a lytic cell death mode that releases additional inflammatory mediators.