Mechanisms of Neurosyphilis-Induced Dementia: Insights into Pathophysiology.

Neurosyphilis-induced dementia represents a severe manifestation of tertiary syphilis, characterized by cognitive and neuropsychiatric impairments. This condition arises from the progression of syphilis to the central nervous system, where the spirochete causes damage through invasion, chronic inflammation, and neurodegeneration. The pathophysiology involves chronic inflammatory responses, direct bacterial damage, and proteinopathies.

Pneumothorax detection and segmentation from chest X-ray radiographs using a patch-based fully convolutional encoder-decoder network.

Pneumothorax, a life-threatening condition characterized by air accumulation in the pleural cavity, requires early and accurate detection for optimal patient outcomes. Chest X-ray radiographs are a common diagnostic tool due to their speed and affordability. However, detecting pneumothorax can be challenging for radiologists because the sole visual indicator is often a thin displaced pleural line.

Neuromorphic Computing Primitives Using Polymer-Networked Nanoparticles.

Nanoparticle networks have potential applications in brain-like computing yet their ability to adopt different states remains unexplored. In this work, we reveal the dynamics of the attachment of polyelectrolytes onto gold nanoparticles (AuNPs), using a bottom-up two-bead-monomer dissipative particle dynamics (TBM-DPD) model to show the heterogeneity of polymer coverage. We found that the use of one polyelectrolyte homopolymer limits the complexity of the possible engineered nanoparticle networks (ENPNs) that can be built.

ReLMM: Reinforcement Learning Optimizes Feature Selection in Modeling Materials.

A challenge to materials discovery is the identification of the physical features that are most correlated to a given target material property without redundancy. Such variables necessarily comprise the optimal search domain in subsequent material design. Here, we introduce a reinforcement learning-based material model (ReLMM) as a tool for analyzing a given database in identifying a minimal or near minimal subset of physical features for the design of a material with a given target property.