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In particular a recent study by Shyti et al., [191] identified metabolic changes by mass spectrometry in a transgenic mouse model of hemiplegic migraine after experimentally induced CSD [207].
We identified metabolic changes in the microbial community associated with the initial stages of dysbiosis.
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We used the LAESI technique to identify metabolic changes in HTLV1 and Tax1 transformed T lymphocytes and in HTLV3 and Tax3 transfected kidney epithelial cells.
In this contribution we aim to identify metabolic changes in HTLV1 transformed T lymphocytes by the direct application of the LAESI method that is rapid and eliminates the need for sample preparation.
The aim of this study was therefore to identify metabolic changes in our GHR mutant mice by analysis of urinary and hepatic metabolites and to correlate these changes with transcriptome-based pathway analysis to establish metabolic pathways affected by the extents of differential STAT5 signalling.
Nevertheless we could identify metabolic changes specific to the two cultivars.
However, we recently showed that saliva can also be used to identify metabolic changes in diabetes [ 13].
To identify metabolic changes associated with seed development and storage product accumulation, metabolomic analysis was conducted on developing seeds harvested at 25, 30, 35, 45 and 50 DAF.
In the present work we used GC-MS based metabonomic analysis to identify metabolic changes in urine extracts from H2S-poisoned and control rats.
To assess the metabolic changes or differences between samples and to identify metabolic changes involved in group discrimination, multivariate analyses (PCA, PLS-DA) were performed by using the SIMCA-P + (12.0.0.0.0) program (Umetrics AB, Tvistevdgen 48 Umea 907 19, Sweden).
With FDA approvals for pediatric antipsychotic treatment down to age 5 6 years old for some SGA medications, there is a growing need to identify metabolic changes that can be detected in young children (e.g. insulin sensitivity changes that proceed over diabetes).
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