Neuroprotective Effects of Functionalized Hydrophilic Carbon Clusters: Targeted Therapy of Traumatic Brain Injury in an Open Blast Rat Model.

Unlabelled: Traumatic brain injury (TBI) causes multiple cerebrovascular disruptions and oxidative stress. These pathological mechanisms are often accompanied by serious impairment of cerebral blood flow autoregulation and neuronal and glial degeneration.

Background/objectives: Multiple biochemical cascades are triggered by brain damage, resulting in reactive oxygen species production alongside blood loss and hypoxia.

Aqueous based ultra-small magnetic Cr-doped CdSe quantum dots as a potential dual imaging probe in biomedicine.

The substitution of semiconductor quantum dots (QDs) by a small number of transition-metal ions with magnetic properties gives rise to magnetic-doped semiconductors. With a balance of optical and magnetic properties, these magnetic semiconductors are widely used in spintronics, bioimaging and magnetic resonance imaging (MRI) applications. To facilitate their usage in bio-applications, it is critical to synthesize water-soluble magnetic QDs with a stabilized structure while maintaining their optical and magnetic properties.

The application of eXplainable artificial intelligence in studying cognition: A scoping review.

The rapid advancement of artificial intelligence (AI) has sparked renewed discussions on its trustworthiness and the concept of eXplainable AI (XAI). Recent research in neuroscience has emphasized the relevance of XAI in studying cognition. This scoping review aims to identify and analyze various XAI methods used to study the mechanisms and features of cognitive function and dysfunction.

Contrastive Graph Pooling for Explainable Classification of Brain Networks.

Functional magnetic resonance imaging (fMRI) is a commonly used technique to measure neural activation. Its application has been particularly important in identifying underlying neurodegenerative conditions such as Parkinson's, Alzheimer's, and Autism. Recent analysis of fMRI data models the brain as a graph and extracts features by graph neural networks (GNNs).