Purpose To determine the reproducibility of a comprehensive single-session measurement of glutathione (GSH), γ-aminobutyric acid (GABA), glutamate, and other biochemicals implicated in the pathophysiology of multiple sclerosis (MS) in the human brain with 1H MR spectroscopy. Materials and Methods Five healthy subjects were studied twice in separate 1-hour sessions at 7 Tesla. One MS patient was also scanned once. GSH and GABA were measured with J-difference editing using a semi-localized by adiabatic selective refocusing sequence (semi-LASER, TE=72 ms). A stimulated echo acquisition mode sequence (STEAM, TE=10 ms) was used to detect glutamate along with the overall biochemical profile. Spectra were quantified with LCModel. Quantification accuracy was assessed through Cramer-Rao lower bounds (CRLB). Reproducibility of the metabolite quantification was tested using coefficients of variation (CoV). Results CRLB were ≤7% for GSH, GABA, and glutamate and average CoV of 7.8±3.2%, 9.5±7.0%, and 3.2±1.7% were achieved, respectively. The average test/re-test concentration differences at this measurement reproducibility and quantification accuracy were smaller for GABA and glutamate than inter-subject variations in metabolite content with CoV ratios of 0.6 and 0.8, respectively. As proof of principle, GSH, GABA, and glutamate were also detected in an MS patient. Conclusion GSH, GABA, glutamate, and other metabolites relevant in MS can be quantified at 7 Tesla with high accuracy and reproducibility in a single 1-hour session. This methodology might serve as a clinical research tool to investigate biochemical markers associated with MS.

Cognitive behavior therapy effectively reduced postcancer fatigue and increased physical activity but did not change physical fitness. The effect of cognitive behavior therapy on postcancer fatigue is not mediated by a change in physical activity or physical fitness.

α-Hydroxybutyrate and BCAA concentrations during an OGTT characterize insulin-resistant youth and predict worsening of glycemic control. These findings provide potential biomarkers for risk assessment of type 2 diabetes and new insights into IR pathogenesis.

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The back movement during rising trot showed characteristics of both sitting trot and the unloaded condition. As the same maximal extension of the back is reached during rising and sitting trot, there is no reason to believe that rising trot was less challenging for the back.

The pathophysiology of progressive multiple sclerosis remains elusive, significantly limiting available disease-modifying therapies. Proton MRS ( 1 H-MRS) enables in vivo measurement of small molecules implicated in multiple sclerosis, but its application to key metabolites glutamate, γ-aminobutyric acid (GABA), and glutathione has been sparse. We employed, at 7 T, a previously validated 1 H-MRS protocol to measure glutamate, GABA, and glutathione, as well as glutamine, N-acetyl aspartate, choline, and myoinositol, in the frontal cortex of individuals with relapsing-remitting (N = 26) or progressive (N = 21) multiple sclerosis or healthy control adults (N = 25) in a cross-sectional analysis. Only individuals with progressive multiple sclerosis demonstrated reduced glutamate (F 2,65 = 3.424, p = 0.04; 12.40 ± 0.62 mM versus control 13.17 ± 0.95 mM, p = 0.03) but not glutamine (F 2,65 = 0.352, p = 0.7; 4.71 ± 0.35 mM versus control 4.84 ± 0.42 mM), reduced GABA (F 2,65 = 3.89, p = 0.03; 1.29 ± 0.23 mM versus control 1.47 ± 0.25 mM, p = 0.05), and possibly reduced glutathione (F 2,65 = 0.352, p = 0.056; 2.23 ± 0.46 mM versus control 2.51 ± 0.48 mM, p < 0.1). As a group, multiple sclerosis patients demonstrated significant negative correlations between disease duration and glutamate or GABA (ρ = À0.4, p = 0.02) but not glutamine or glutathione. Alone, only relapsing-remitting multiple sclerosis patients exhibited a significant negative correlation between disease duration and GABA (ρ = À0.5, p = 0.03). Taken together, these results indicate that frontal cortex metabolism is differentially disturbed in progressive and relapsingremitting multiple sclerosis.

It should be explored how to help patients with a relapse of severe fatigue following an initially successful CBT. They may profit from CBT again, or another evidence-based intervention for fatigue (like mindfulness or exercise therapy). Future research to gain insight into reasons for relapse is warranted.

Postcancer fatigue is neither characterized by abnormally high central muscle fatigue nor by low peripheral muscle fatigue. These findings suggest a difference in the underlying physiological mechanism of postcancer fatigue vs. other fatigue syndromes.