PSVIII-40 Late-Breaking Abstract: Variability in body composition is associated with insulin sensitivity in growing-finishing pigs
Bibliographic record
Abstract
Abstract Growing pigs’ body composition variation can be associated with differences in insulin sensitivity given the insulin anabolic effect on protein and lipid synthesis. The objective of this study was to elucidate this association by relating the individual insulin response to the oral glucose tolerance test (OGTT) with the body composition of growing pigs. Thirty 95 kg jugular vein catheterized pigs received an oral dose of 1.75 g of glucose/kg of BW after 18 hours of fasting. Blood samples were collected at -20, -10, 5, 10, 15, 20, 25, 30, 45, 60, 90, 120, 150, 180, 210, 240, 300 and 360 min following glucose ingestion. Insulin sensitivity indexes were calculated and analyzed. Body lipids (LB, %) and protein (PB, %) composition were estimated by dual X-ray densitometry. Association between body composition and insulin sensitivity were studied by using partial least squares and correlations. Average LB and PB were 19.7% (CV = 7.6 %) and 16.2% (CV = 2.2%), respectively. Basal insulin blood concentration and area-under-the-curve (AUC) CV (51.9 % and 26.9 %, respectively) were larger than those for basal glucose and AUC (5.52 and 5.48 %, respectively). Additionally, insulin sensitivity (%S), steady-state beta cell function (%B), and insulin resistance (HOMA-IR) estimated with the Homeostasis Model Assessment (HOMA 2) and whole-body insulin sensitivity index (ISI) were highly variable between pigs which CV ranged from 30.1 % to 54.5 %. These results can indicate an early stage of insulin resistance in an important part of the studied pig population. LB and PB were affected by insulin sensitivity indexes (P < 0.05) which accounted, respectively, for 48% and 44% of the observed variation. In conclusion, lower insulin sensitivity was associated with higher body fat in growing pigs raised under similar conditions.
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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) | 0.003 | 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".