Growth hormone-induced insulin resistance is associated with increased intramyocellular triglyceride content but unaltered VLDL-triglyceride kinetics
Bibliographic record
Abstract
The ability of growth hormone (GH) to stimulate lipolysis and cause insulin resistance in skeletal muscle may be causally linked, but the mechanisms remain obscure. We investigated the impact of GH on the turnover of FFA and VLDL-TG, intramuscular triglyceride content (IMTG), and insulin sensitivity (euglycemic clamp) in nine healthy men in a randomized double-blind placebo-controlled crossover study after 8 days treatment with (A) Placebo+Placebo, (B) GH (2 mg daily)+Placebo, and (C) GH (2 mg daily)+Acipimox (250 mgx3 daily). In the basal state, GH (B) increased FFA levels (P<0.05), palmitate turnover (P<0.05), and lipid oxidation (P=0.05), but VLDL-TG kinetics were unaffected. Administration of acipimox (C) suppressed basal lipolysis but did not influence VLDL-TG kinetics. In the basal state, IMTG content increased after GH (B; P=0.03). Insulin resistance was induced by GH irrespective of concomitant acipimox (P<0.001). The turnover of FFA and VLDL-TG was suppressed by hyperinsulinemia during placebo and GH, whereas coadministration of acipimox induced a rebound increase FFA turnover and VLDL-TG clearance. We conclude that these results show that GH-induced insulin resistance is associated with increased IMTG and unaltered VLDL-TG kinetics; we hypothesize that fat oxidation in muscle tissue is an important primary effect of GH and that circulating FFA rather than VLDL-TG constitute the major source for this process; and the role of IMTG in the development of GH-induced insulin resistance merits future research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".