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. 2018 Nov 26;9:1639. doi: 10.3389/fphys.2018.01639

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Copyright © 2018 Mariné-Casadó, Domenech-Coca, del Bas, Bladé, Arola and Caimari.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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The 112 analyzed parameters were used to set up a PLS-DA predictive model (A). The 28 variables with a coefficient mean higher than 30 ((B) were analyzed by PCA (C). 3Hxb, 3-hydroxybutyrate; Bmal1, brain and muscle Arnt-like protein-1; Cry1, cryptochrome circadian clock 1; EE, energy expenditure; Fat_ox, fat oxidation; Fatp1, fatty acid transport protein 1; Ga, gastrocnemius muscle; Ghsr, ghrelin receptor; Glut4, glucose transporter 4; Hp, hypothalamus; Irs1, insulin receptor substrate 1; Leu, leucine; Li, liver; Npy, neuropeptide Y; Nr1d1, nuclear receptor subfamily 1, group D, member 1; pAkt2, phosphorylated Akt serine/threonine kinase 2; Per2, period circadian clock 2; Pro, proline; Rorα, RAR-related orphan receptor alpha; RQ, respiratory quotient; Se, serum; So, soleus muscle.