Age-Trajectories of Higher-Order Diffusion Properties of Major Brain Metabolites in Cerebral and Cerebellar Gray Matter Using In Vivo Diffusion-Weighted MR Spectroscopy at 3T.

Healthy brain aging involves changes in both brain structure and function, including alterations in cellular composition and microstructure across brain regions. Unlike diffusion-weighted MRI (dMRI), diffusion-weighted MR spectroscopy (dMRS) can assess cell-type specific microstructural changes, providing indirect information on both cell composition and microstructure through the quantification and interpretation of metabolites' diffusion properties. This work investigates age-related changes in the higher-order diffusion properties of total N-Acetyl-aspartate (neuronal biomarker), total choline (glial biomarker), and total creatine (both neuronal and glial biomarker) beyond the classical apparent diffusion coefficient in cerebral and cerebellar gray matter of healthy human brain.

(CECT7484 and CECT7485) and (CECT7483) enhance actin cytoskeleton and CYP1A1 expression restoring epithelial permeability alterations induced by irritable bowel syndrome mediators.

Irritable bowel syndrome (IBS) is a multifactorial condition with heterogeneous pathophysiology, including intestinal permeability alterations. The aim of the present study was to assess the ability of a probiotic blend (PB) consisting of two strains (CECT7484 and CECT7485) and one strain of (CECT7483) to recover the permeability increase induced by mediators from IBS mucosal biopsies and to highlight the underlying molecular mechanisms. Twenty-one IBS patients diagnosed according to ROME IV criteria (11 IBS-D and 10 IBS-M) and 7 healthy controls were enrolled.

Soma and neurite density abnormalities of paramagnetic rim lesions and core-sign lesions in multiple sclerosis.

Background: In multiple sclerosis (MS), susceptibility-weighted imaging (SWI) may reveal white matter lesions (WML) with a paramagnetic rim ("paramagnetic rim lesions" [PRLs]) or diffuse hypointensity ("core-sign lesions"), reflecting different stages of WML evolution.

Objective: Using the soma and neurite density imaging (SANDI) model on diffusion-weighted magnetic resonance imaging (MRI), we characterized microstructural abnormalities of MS PRLs and core-sign lesions and their clinical relevance.

Methods: Forty MS patients and 20 healthy controls (HC) underwent a 3 T brain MRI.

Introducing µGUIDE for quantitative imaging via generalized uncertainty-driven inference using deep learning.

This work proposes µGUIDE: a general Bayesian framework to estimate posterior distributions of tissue microstructure parameters from any given biophysical model or signal representation, with exemplar demonstration in diffusion-weighted magnetic resonance imaging. Harnessing a new deep learning architecture for automatic signal feature selection combined with simulation-based inference and efficient sampling of the posterior distributions, µGUIDE bypasses the high computational and time cost of conventional Bayesian approaches and does not rely on acquisition constraints to define model-specific summary statistics. The obtained posterior distributions allow to highlight degeneracies present in the model definition and quantify the uncertainty and ambiguity of the estimated parameters.