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Kasper, S.

Publications and source records attributed to Kasper, S..

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JNK activation in TA and EDL muscle is load-dependent in rats receiving identical excitation patterns

ABSTACTO_ST_ABSAimC_ST_ABSAs the excitation-contraction coupling is inseparable during voluntary exercise, the relative contribution of the mechanical and neural input is poorly understood. Herein, we use a rat in-vivo strength training setup with an electrically induced standardized excitation pattern previously shown to lead to a load-dependent increase in myonuclear number and hypertrophy, to study acute effects of load per se on molecular signalling. MethodsAnaesthetized rats were subjected to unliteral identical electrically-paced contractions of the TA and EDL muscles under a high or low load for a duration of 2, 10 or 28-minutes. Muscle soluble proteins were extracted, and abundance and specific phosphorylations of FAK, mTOR, p70S6K and JNK were measured. Effects of exercise, load, muscle and exercise duration were assessed. ResultsSpecific phosphorylation of S2448-mTOR, T421/S424-p70S6K and T183/Y185-JNK was increased after 28-minutes of exercise under the high- and low-load protocol. Elevated phosphorylation of mTOR and JNK was detectable already after 2 and 10 minutes of exercise, respectively, but greatest after 28-minutes of exercise. T183/Y185-JNK and S2448-mTOR demonstrated a load-dependent increase in phosphorylation in the exercised muscles that for mTOR depended on muscle type. The abundance of all four kinases was higher in TA compared to EDL muscle. FAK and JNK abundance was reduced after 28 minutes of exercise in both the exercised and control muscle. ConclusionThe current study shows that JNK and mTOR activation is load-driven, and together with muscle-type specific mTOR and p70S6K effects it may drive muscle-type specific exercise and load-responses.

physiology

Regional expression profiles of risk genes for depression are associated with brain activation patterns in emotion and reward tasks

The spatial relationship between gene expression profiles and neural response patterns known to be altered in neuropsychiatric disorders, e.g. depression, can guide the development of more targeted therapies. Here, we estimated the correlation between human transcriptome data and two different brain activation maps measured with functional magnetic resonance imaging (fMRI) in healthy subjects. Whole-brain activation patterns evoked during an emotional face recognition task were associated with topological mRNA expression of genes involved in cellular transport. In contrast, fMRI activation patterns related to the acceptance of monetary rewards were associated with genes implicated in neuronal development, synapse regulation, and gene transcription. An overlap of these genes with risk genes from major depressive disorder genome-wide associations studies revealed the involvement of the master regulators TCF4 and MEF2C. These results were further validated by means of meta-analytic fMRI data. Overall, the identification of stable relationships between spatial gene expression profiles and fMRI data may reshape the prospects for imaging transcriptomics studies.

neuroscience