Essential oil supplementation improves insulin sensitivity and modulates the plasma metabolome of hyperinsulinemic horses
Bibliographic record
Abstract
The objective of this study was to investigate the effect of essential oil (EO) supplementation on insulin sensitivity (IS) and the plasma metabolome in insulin dysregulated (ID) horses. Horses were blocked by degree of IS and assigned randomly to treatment: oral daily bolus (50 mL) of either a plant derived EO supplement or carrier (CON). Mares were housed in dry lots with ad libitum access to grass hay and supplemented individually twice daily with a concentrate to meet nutrient requirements for mature horses. Before and after 6 wks of treatment, mares underwent a combined glucose-insulin tolerance test (CGIT) and an oral sugar test (OST) on separate days. Global metabolome analysis was conducted on plasma samples before and after treatment. Although treatment did not affect (p > 0.4) AUC or glucose clearance during CGIT, there was a treatment*covariate interaction (p ≤ 0.08) for insulin concentrations at 75 min (INS75) and positive phase time (PT) with EO decreasing both INS75 (p ≤ 0.002) and PT (p = 0.05) in horses with more severe initial degree of ID. Similarly, EO treatment reduced (p ≤ 0.006) insulinemic response to the OST in horses exhibiting higher pre-treatment responses (treatment*covariate, p = 0.004). There were 702 metabolites identified that were uniquely changed with EO treatment. Pathway analysis and biomarkers showed EO-mediated changes in amino acid, linoleic acid, mesaconic acid, TCA-cyle intermediates and bile acid metabolism. The directional changes in these pathways or biomarkers are consistent with changes in inulin sensitivity in other models. These data show that EO shifted the plasma metabolome and improved insulin sensitivity in horses.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".