[Change in the volume of choroidal plexus at the onset of a demyelinating disease].

Choroidal plexuses (CPs) are particularly interesting due to their immunological activity and direct involvement in neuroinflammation in patients with multiple sclerosis (MS). Currently, MS pathogenesis has not been sufficiently studied, and the early stages of the disease, including radiologically isolated syndrome (RIS), are the most relevant ones for study. The CP volume is a new promising marker that can predict the transformation from preclinical forms of MS to the symptomatic form of the disease.

[Quantitative analysis of cerebrospinal fluid flow in multiple sclerosis patients].

Objective: To study changes in the quantitative indicators of intracranial cerebrospinal fluid (CSF) flow in patients with multiple sclerosis (MS) at different stages of the disease using phase contrast magnetic resonance imaging (PC MRI).

Material And Methods: The study included 80 patients diagnosed with MS (40 in the acute stage, 40 in remission) and 10 healthy volunteers. CSF flow parameters were assessed using a phase contrast MRI protocol.

Machine learning-based mapping of Acidobacteriota and Planctomycetota using 16 S rRNA gene metabarcoding data across soils in Russia.

The soil microbiome plays a crucial role in maintaining healthy ecosystems and supporting sustainable agriculture. Studying its biogeographical structure and distribution is essential for understanding the rates and mechanisms of microbially mediated soil ecosystem services. This study aimed to investigate the spatial distribution patterns of Acidobacteriota and Planctomycetota across soils in Russia, summarizing data from 16S rRNA gene metabarcoding of topsoils.

Unveiling the Fundamental Principles of Reconfigurable Resistance States in Silver/Poly(Ethylene Glycol) Nanofluids.

Developing novel memristive systems aims to implement key principles of biological neuron assemblies - plasticity, adaptivity, and self-organization - into artificial devices for parallel, energy-efficient computing. Solid-state memristive devices, such as crossbar arrays and percolated nanoparticle (NP) networks, already demonstrate these properties. However, closer similarity to neural networks is expected from liquid-state systems, including polymer melts, which remain largely unexplored.