Acylation-stimulating protein deficiency and altered adipose tissue in alternative complement pathway knockout mice
Bibliographic record
Abstract
Acylation-stimulating protein (C3adesArg/ASP) is an adipokine that acts on its receptor C5L2 to stimulate triglyceride (TG) synthesis in adipose tissue. The present study investigated ASP levels in mouse models of obesity and leanness and the effect of ASP deficiency in C3 knockout (C3KO) mice on adipose tissue morphology. Plasma ASP levels in wild-type (WT) mice correlated positively with plasma nonesterified fatty acids (NEFA) (R = 0.664, P < 0.001) and total cholesterol (R = 0.515, P < 0.001). Plasma ASP was increased by 85% in obese ob/ob leptin-deficient mice and decreased in lean diacylglycerol acyltransferase 1 (DGAT1) KO mice (-54%) and C/EBPalpha(beta/beta) transgenic mice (-70%) compared with WT. Mice lacking alternative complement factor B or adipsin (FBKO or ADKO), required for ASP production, were also ASP deficient. Both FBKO and C3KO mice had delayed postprandial TG and NEFA clearance on low-fat (LF) and high-fat (HF) diets, suggesting that lack of ASP, not C3, drives the metabolic phenotype. Adipocyte size distribution in C3KO mice was polarized (increased number of both small and large cells), with decreased adipsin expression (-33% gonadal HF), DGAT1 expression (-31% to -50%) and DGAT activity (-41%). Overall, a reduction/deficiency in ASP is associated with an antiadipogenic state and ASP may provide a target for controlling fat storage.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".