Twelve weeks of endurance training increases mitochondrial density and percent IMCL touching mitochondria and alters IMCL storage distribution
Bibliographic record
Abstract
Intramyocellular lipids (IMCL) are elevated in obesity and are correlated with insulin resistance (IR); however, elite athletes have elevated IMCL but are highly insulin sensitive. We postulate that the IMCL‐mitochondria physical relationship delineates whether IMCL are metabolically active. Methods: Muscle biopsies from 24 women (12 lean; 12 obese) were analyzed for IMCL and mitochondria ultrastructure using electron microscopy prior to and following a 12‐week progressive endurance training protocol. Results: In obese women, there was a strong trend for higher IMCL area density in the intermyofibrillar (IMF) region (P = 0.053) vs. lean. Training increased IMF IMCL size (P = 0.008), total fiber mitochondrial size (P = 0.006 and number (P = 0.009), subsarcolemmal (SS) (P = 0.01) and total fiber (P < 0.0001) mitochondrial area density, and the % IMCL touching mitochondria in the SS (P = 0.04), IMF (P < 0.0001) and total fiber (P < 0.0001), whereas it decreased SS #IMCL/area (P = 0.001). Following training, IMCL area density decreased in SS (P = 0.009), increased in IMF (P = 0.07), and did not change in the total fiber. HOMA‐IR was higher in obese women (P = 0.002), with no training effect. Discussion: The increase in IMCL‐mitochondrial proximity and mitochondrial density suggests an increased capacity to utilize IMCL following endurance training. Training‐induced IMCL mobilization from SS into IMF may be more favorable, as SS IMCL could prevent signal transduction and GLUT‐4 mediated glucose uptake. (Supported by CIHR).
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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".