Influence of Adiposity in the Blunted Whole-Body Protein Anabolic Response to Insulin With Aging
Bibliographic record
Abstract
BACKGROUND: Although insulin resistance of glucose is often reported with aging, that of protein metabolism is still debated. We tested if the insulin sensitivity of protein metabolism parallels that of glucose and is altered with aging. METHODS: Whole-body (13)C-leucine and (3)H-glucose kinetics were measured in the postabsorptive state and during an hyperinsulinemic, euglycemic, isoaminoacidemic clamp in 12 young men (age: 27 +/- 1 years; body mass index [BMI]: 23 +/- 1 kg/m(2)), 11 young women (age: 25 +/- 1 years; BMI: 21 +/- 1 kg/m(2)), 9 elderly men (age: 70 +/- 1 years; BMI: 26 +/- 1 kg/m(2)), and 10 elderly women (age: 69 +/- 2 years; BMI: 23 +/- 1 kg/m(2)). RESULTS: Postabsorptive leucine flux rates adjusted for fat-free mass (FFM) were not different between elderly and young participants. During the clamp, leucine flux and protein synthesis rates increased less in the elderly participants, and protein breakdown decreased equally. Thus, the net anabolic (protein balance) response to hyperinsulinemia was lower in elderly versus young participants (p =.007) and was highly correlated with the clamp glucose rate of disposal (r = 0.671, p <.001), indicating insulin resistance of protein concurrent with that of glucose. From regression analysis, FFM explained 73% of the variance in the anabolic response. Age explained an additional 3%, but was accounted for by markers of adiposity. FFM and percent body fat collectively explained 79% of the variance. CONCLUSION: Both reduction in absolute FFM and increased adiposity, intrinsic to the aging process, are associated with an altered anabolic action of insulin in stimulating protein synthesis. This alteration may contribute to the progressive muscle loss with aging.
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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 | 0.001 | 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) | 0.000 | 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".