Reduced Body Weight, Adipose Tissue, and Leptin Levels Despite Increased Energy Intake in Female Mice Lacking Acylation-Stimulating Protein<sup>1</sup>
Bibliographic record
Abstract
Acylation-stimulating protein (ASP) is a potent lipogenic protein produced by adipocytes. In vitro studies have shown that ASP increases triglyceride synthesis and glucose transport in both murine and human adipocytes. Our initial study indicated that complement C3-deficient (-/-) mice (and, therefore, ASP deficient) demonstrated altered dietary postprandial triglyceride clearance. In the present study we examined the phenotype of female mice longitudinally on different diets. Female C3(-/-) mice on both low (10% of energy) and high (40% of energy) fat diets displayed an average reduction in total body weight of 10.1+/-0.5% (P < 0.0003, by ANOVA) compared with the C3(+/+) littermates. Reductions in white adipose tissue mass accounted for most of this weight difference (59% reduction; P < 0.01 on low fat diet). Plasma leptin levels were significantly reduced in C3(-/-) mice on both high (P < 0.001) and low fat diets (P < 0.01). This reduction was significant even after adjusting for the reduced body weight and body fat (P < 0.001). Leptin reductions in the C3(-/-) were greater on the high fat diet and were associated with increased food intake (18+/-2% increase; P < 0.001). Furthermore, there was a decrease in basal glucose levels and basal insulin levels [12.8% decrease in glucose at 14 weeks (HF; P < 0.05) and 41% decrease in insulin at 26 weeks (HF; P < 0.05)]. These in vivo experiments demonstrate that female mice lacking ASP have marked alterations of body weight, adiposity, plasma leptin, and plasma insulin levels. Decreased adiposity and leptin levels occurred in the ASP-deficient animals despite increased energy intake, suggesting that energy expenditure was elevated in these animals. Thus, ASP appears to have an important role in the regulation of energy balance in mice.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".