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Wishart, C.

Publications and source records attributed to Wishart, C..

2 recordsLinked to original sources

High fat low carbohydrate diet is linked to protection against CNS autoimmunity

Multiple sclerosis (MS) is a common central nervous system (CNS) autoimmune disease, and diets and nutrients are emerging as critical contributing factors. However, a comprehensive understanding of their impacts and the underlying mechanisms involved is lacking. Harnessing state-of-the-art nutritional geometry analytical methods, we first revealed that globally, increased carbohydrate supply was associated with increased MS disease burden, while fat supply had an opposite effect. Furthermore, in a preclinical MS mouse model, experimental autoimmune encephalomyelitis (EAE), we found that an isocaloric diet high in carbohydrate aggravated EAE, while a diet enriched in fat was fully protective. This was reflected by reduced neuroinflammation and skewing towards anti-inflammatory phenotypes, which involved transcriptomic, epigenetic and immunometabolic changes. We showcased that manipulating diets is a potentially efficient and cost-effective approach to prevent and/or ameliorate EAE. This exhibits translational potentials for intervention/prevention of MS and possibly other autoimmune diseases.

immunology↗

A unique human cord blood CD8+CD45RA+CD27+CD161+ T cell subset identified by flow cytometric data analysis using Seurat

Advances in single cell analysis, especially cytometric approaches, have profoundly innovated immunological research. This has resulted in an expansion of high dimensional data, posing great challenges for comprehensive and unbiased analysis. Conventional manual analysis thus becomes untenable, while most computational methods lack flexibility and interoperability, hampering usability. Here, for the first time, we adapted Seurat, a single cell RNA sequencing (scRNA-seq) analysis package, for end-to-end flow cytometric data analysis. We showcased its robust analytical capacity by analyzing the adult blood and cord blood T cell profiles, which was validated by Spectre, another cytometric data analysis package, and manual analysis. Importantly, a unique CD8+CD45RA+CD27+CD161+ T cell subset, was identified in cord blood and characterized using flow cytometry and scRNA-seq analysis from a published dataset. Collectively, Seurat possesses great potential for cytometric data analysis. It facilitates thorough interpretations of high dimensional data using a single pipeline, implementing data-driven investigation in clinical immunology.

immunology↗