A secondary metabolite of Limosilactobacillusreuteri R2lc drives strain-specific pathology in a spontaneous mouse model of multiple sclerosis.

Limosilactobacillus reuteri is an immunomodulatory bacterium enriched in non-industrialized microbiomes, making it a therapeutic candidate for chronic diseases. However, effects of L. reuteri strains in mouse models of multiple sclerosis have been contradictory.

Characterising equine abdominal lipomata: Can histological features improve the understanding of pathogenesis and risk?

Background: Strangulating lipomata are the most common cause of small intestinal strangulating obstruction. Evaluation of histological features of pathological and non-pathological lipomata, and the histological properties of omental and retroperitoneal fat have not been described.

Objectives: To characterise histological features of equine abdominal lipomata, omental and retroperitoneal adipose tissue, and associations between them.

Evaluation of a stent dressing and abdominal bandage on surgical site infection following emergency equine laparotomy: A randomised controlled trial.

Background: Surgical site infection (SSI) is a frequent complication following emergency equine laparotomy, negatively impacting equine welfare, increasing treatment costs and presenting a hospital biosecurity risk.

Objectives: To determine if a sutured-on stent dressing for incisional protection during anaesthetic recovery reduced SSI following emergency laparotomy.

Study Design: Randomised controlled trial.

Learning disentangled representations to harmonize connectome network measures.

Purpose: Connectome network metrics are commonly regarded as fundamental properties of the brain, and their alterations have been implicated in the development of Alzheimer's disease, multiple sclerosis, and traumatic brain injury. However, these metrics are actually estimated properties through a multistage propagation from local voxel diffusion estimations, regional tractography, and region of interest mapping. These estimation processes are significantly influenced by choices specific to imaging protocols and software, producing site-wise effects.

Head Motion in Diffusion Magnetic Resonance Imaging: Quantification, Mitigation, and Structural Associations in Large, Cross-Sectional Datasets Across the Lifespan.

Head motion during diffusion magnetic resonance imaging (MRI) scans can cause numerous artifacts and biases subsequent quantification. However, a thorough characterization of motion across multiple scans, cohorts, and consortiums has not been performed. To address this, we designed a study with three aims.