Differential regulation of fatty acid trapping in mouse adipose tissue and muscle by ASP
Bibliographic record
Abstract
Acylation-stimulating protein (ASP) is a lipogenic hormone secreted by white adipose tissue (WAT). Male C3 knockout (KO; C3(-/-)) ASP-deficient mice have delayed postprandial triglyceride (TG) clearance and reduced WAT mass. The objective of this study was to examine the mechanism(s) by which ASP deficiency induces differences in postprandial TG clearance and body composition in male KO mice. Except for increased (3)H-labeled nonesterified fatty acid (NEFA) trapping in brown adipose tissue (BAT) of KO mice (P = 0.02), there were no intrinsic tissue differences between wild-type (WT) and KO mice in (3)H-NEFA or [(14)C]glucose oxidation, TG synthesis or lipolysis in WAT, muscle, or liver. There were no differences in WAT or skeletal muscle hydrolysis, uptake, and storage of [(3)H]triolein substrate [in situ lipoprotein lipase (LPL) activity]. ASP, however, increased in situ LPL activity in WAT (+64.8%, P = 0.02) but decreased it in muscle (-35.0%, P = 0.0002). In addition, after prelabeling WAT with [(3)H]oleate and [(14)C]glucose, ASP increased (3)H-lipid retention, [(3)H]TG synthesis, and [(3)H]TG-to-[(14)C]TG ratio, whereas it decreased (3)H-NEFA release, indicating increased NEFA trapping in WAT. Conversely, in muscle, ASP induced effects opposite to those in WAT and increased lipolysis, indicating reduced NEFA trapping within muscle by ASP (P < 0.05 for all parameters). In conclusion, novel data in this study suggest that 1) there is little intrinsic difference between KO and WT tissue in the parameters examined and 2) ASP differentially regulates in situ LPL activity and NEFA trapping in WAT and skeletal muscle, which may promote optimal insulin sensitivity in vivo.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".