Acylcarnitine concentrations increase in response to an extended energy deficit, but return to baseline concentrations following a 2-week recovery in male US Army Rangers
Bibliographic record
Abstract
Energy deficit often occurs during military training and operations due to prolonged and strenuous physical exertion and limited access to food. During energy deficit, the body predominately relies on fat stores. This results in greater circulating acylcarnitine species as acyl groups are moved into the mitochondria for β-oxidation. Carnitine and acylcarnitine species have not been assessed during prolonged energy deficit and following a recovery period in healthy males undergoing strenuous military training. The objective of this study was to determine longitudinal changes in plasma carnitine and aclycarnitines following a prolonged and severe energy deficit and short-term recovery. This secondary analysis examined plasma carnitine and acylcarnitine concentrations before (PRE) and after (POST) 61-day U.S. Army Ranger training and following 2 weeks of recovery (REC). During training, participants ( n = 22; mean ± standard deviation: 23.2 ± 2.8 years; 81.7 ± 9.3 kg; 16.5 ± 6.8% body fat) consumed ∼2200 kcal/day and were in an ∼1000 kcal/day energy deficit. Carnitine and acylcarnitine (C2-C22) concentrations were measured by tandem mass spectrometry. At POST, participants had increased concentrations of total short-chain acylcarnitines and 10 of 58 acylcarnitine species (C2, C5, C8-dicarboxylic acid (DC), C16:1, C16:1-hydroxyl group (OH), C18:1-OH, C18:1-DC, C18:2-OH, C20:2-OH, C22:3; P ≤ 0.05) compared to PRE. These acylcarnitine species returned to PRE concentrations following REC ( P > 0.05). Greater bodyweight loss was associated with greater increases in short-chain acylcarnitine ( r = −0.68; P = 0.0006), medium-chain acylcarnitine ( r = −0.61; P = 0.0035), and long-chain acylcarnitine (ρ = −0.65; P = 0.0013) concentrations. Severe energy deficit incurred during strenuous military training increased 10 acylcarnitine species. However, 2 weeks of recovery was sufficient for acylcarnitine concentrations to return to baseline concentrations.
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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) | 0.002 | 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".