Ghrelin rescues palmitate‐induced decrements in insulin signaling in oxidative skeletal muscle from rats
Bibliographic record
Abstract
Introduction Ghrelin is an orexigenic gastric hormone that also has metabolic effects on insulin‐responsive tissues (eg. skeletal muscle). Existing work from our lab using rat skeletal muscle (unpublished), and others using myoblasts (Han L et al . 2015) demonstrate that ghrelin can stimulate fatty acid oxidation. Our current experimental model is aimed at extending these findings, and determining whether ghrelin can protect against acute, palmitate‐induced impairments in insulin signaling and glucose uptake in skeletal muscle, a major site for insulin‐stimulated glucose disposal. Methods To date, oxidative soleus muscle strips have been isolated from healthy, male Sprague‐Dawley rats and incubated in vials containing pre‐gassed (95% O 2 , 5% CO 2 ) and warmed (30ºC) media. All muscles were equilibrated for 30min, then underwent either low palmitate (0.2mM, LP) or high palmitate (2mM, HP) treatment, with or without acylated (AG) or unacylated (UnAG) ghrelin, for 4h. Muscles were then subjected to either saline or maximal insulin (10mU/ml, 10min) and then snap frozen in liquid nitrogen. Western blots were used to quantify the activation of insulin signaling protein AKT (Ser 473 , Thr 308 ). Results We first confirmed that HP impairs muscle insulin signaling within 4h. Insulin significantly stimulated AKT activation (Ser 473 ) in both palmitate conditions at 1mU/ml (LP: 2.4±0.6; HP: 1.9±0.3) and 10mU/ml (LP: 12.5±1.6; HP: 5.4±0.6) doses. The HP‐induced blunting of AKT phosphorylation was more readily apparent at the maximal insulin concentration; therefore, this was utilized for subsequent incubations to examine the potential effects of ghrelin. For signaling experiments with ghrelin, when compared to control (1.2±0.6), 10mU/ml insulin increased the activation of AKT at both its Ser 473 (LP: 15.3±3.23; HP: 6.86±1.01) and Thr 308 (LP: 12.1±3.17; HP: 7.7±2.05) residues at both palmitate concentrations (p<0.01). Therefore, consistent with our pilot work, 4h of HP exposure significantly reduced insulin's activation of AKT at Ser 473 compared to LP (p<0.01); this trend was present with Thr 308 , but was not significant (p=0.1). Interestingly, AG (14.8±7.6, p<0.05), but not UnAG,(11.2±7.3, p>0.05) was able to preserve Ser 473 AKT activation in the HP condition. Neither AG (8.19±2.32) nor UnAG (5.86±1.20) altered insulin's ability to activate AKT (Thr 308 ) in the context of HP (p>0.05). Conclusions AG preserved insulin's ability to fully activate AKT at its Ser 473 site under HP conditions. Further incubations will be performed to increase statistical power as UnAG trended towards a similar effect, and has been reported to increase insulin sensitivity in the literature. Future measurements will determine whether this alteration to AKT signaling can manifest as a functional change in glucose transport (i.e. whether AG can protect against palmitate‐induced reductions in glucose transport). Also, we will assess ghrelin's effects on (2mM) palmitate oxidation and whether AMPK is involved. These experiments will contribute to the interpretation of both AG and UnAG's effects in skeletal muscle glucose/fatty acid metabolism and insulin signaling. Support or Funding Information DJD is supported by a grant from the Natural Sciences and Engineering Research Council (NSERC) of Canada. DTC holds an NSERC PGS‐D Scholarship. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".