The 17-Beta-Estradiol Improves Insulin Sensitivity in a Rapid Estrogen Receptor Alpha-Dependent Manner in an Animal Model of Malnourishment
Bibliographic record
Abstract
Background: Protein restriction causes metabolic programming to maintain glucose homeostasis in rodents. They develop increased insulin sensitivity in peripheral tissues and reduced insulin secretion by pancreatic beta cells. Estradiol (E2) is a steroid hormone involved in the control of energy balance and glucose homeostasis. Here, we assessed the role of estrogen receptors (ERs) on glucose homeostasis in malnourished mice and the effect of E2 on insulin signaling. Methods: Post-weaned Swiss male mice were fed a low-protein (LP, 6%) or chow diet (control, 14%) for 8 weeks. The malnourished phenotype in LP mice was confirmed by different physiological parameters. Hypersensitivity to insulin was demonstrated by a higher glucose infusion in the LP group compared with the control by euglycemic-hyperinsulinemic clamp. Results: The administration of 10 µg/kg E2 during the clamp induced a significant increase in the glucose infusion rate in the LP group compared with the control, indicating enhanced insulin sensitivity in LP mice. In addition, E2 administration increased glucose uptake by peripheral tissues. These effects were blunted in mice treated with general ER antagonists (ICI 182,780 and MPP). However, PHTTP failed to interfere with the E2 effect on insulin sensitivity. In the estradiol LP-treated mice, the activity of the insulin pathway was augmented, as demonstrated by higher AKT phosphorylation and glucose uptake by the skeletal muscle. Conclusion: Thus, we show an acute effect of E2 on insulin signaling in the skeletal muscle of protein-restricted mice. It is mediated by ERalpha, which interacts directly with phosphatidylinositol 3-kinase (PI3K), increasing the phosphorylation of AKT and consequently, glucose uptake in muscle. J Endocrinol Metab. 2019;9(5):133-146 doi: https://doi.org/10.14740/jem612
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".