Effects of Acute Hypoxia on Human Adipose Tissue Lipoprotein Lipase Activity and Lipolysis
Bibliographic record
Abstract
Context Adipose tissue regulates postprandial lipid metabolism by storing dietary fat through lipoprotein lipase (LPL)‐mediated hydrolysis of dietary triglycerides, and by inhibiting non‐esterified fatty acid (NEFA) delivery to nonadipose tissues. Studies conducted in animal showed that acute intermittent hypoxia, a model of obstructive sleep apnea, reduce adipose tissue LPL activity and increase NEFA release, adversely affecting postprandial lipemia. These observations remain to be tested in humans. Objective To investigate the effects of acute hypoxia on human adipose tissue LPL activity and lipolysis. Methods Differentiated human preadipocytes were exposed to hypoxia (3% O 2 ) for 24h and adipose tissue biopsies were obtained from 10 healthy men exposed for 6 hours to either normoxia or intermittent hypoxia following an isocaloric high‐fat meal. Results In differentiated human preadipocytes, acute hypoxia induced a 6‐fold reduction in LPL activity (p<0.001). In humans, the rise in postprandial triglyceride levels did not differ between normoxia and intermittent hypoxia. NEFA levels were significantly higher during intermittent hypoxia session (condition effect, p<0.05). Intermittent hypoxia did not affect subcutaneous abdominal adipose tissue LPL activity. No difference in lipolytic‐induced responses of isolated subcutaneous abdominal adipocytes were observed between normoxia and intermittent hypoxia sessions. Conclusions Acute hypoxia strongly inhibits LPL activity in differentiated subcutaneous abdominal preadipocytes. Acute intermittent hypoxia increases circulating plasma NEFA in young healthy men, but does not seem to affect postprandial triglyceride levels, nor subcutaneous abdominal adipose tissue LPL activity and adipocyte lipolysis. Support or Funding Information The study is dedicated to the memory of our colleague Michaël Babinsky. We are grateful to Mrs. Ann Beninato and Sabrina Ait‐Ouali for their technical assistance. Bimit Mahat is a recipient of a Ontario Graduate scholarship. Étienne Chassé is a recipient of a Institut de recherche de l'Hôpital Montfort scholarship. This study was supported by the Natural Sciences and Engineering Research Council of Canada as well as the University of Ottawa.
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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".