ASP-C5L2 neutralizing antibodies alter triglyceride metabolism in vitro and in vivo (53.10)
Bibliographic record
Abstract
Abstract There are growing data that show the linkage between immune and metabolic systems. C3a is an anaphylatoxin. Its inactive product, C3a desArg, known as Acylation Stimulating Protein (ASP), is well documented as a lipogenic factor stimulating triglyceride synthesis (TGS) and glucose transport (GT). Recently, C5L2 was identified as a functional receptor of ASP. Interestingly, C5a also binds C5L2, but binding has no inflammatory response, suggesting C5L2 is a C5a decoy receptor. The aim of this study is to determine in vitro and in vivo effects of blocking ASP-C5L2 interaction using antiASP and antiC5L2 IgG. In C5L2 transfected HEK cells, antiASP or antiC5L2 competes for ASP binding (IC50: ASP 93±27 nM; antiC5L2, 199±19 nM;) and inhibit TGS and GT. In mice, antibody injection had no effect on body and tissue weight, food intake, and plasma levels of insulin, leptin, or adiponectin, but caused delayed TG (AUC: control 2.0±0.3 mM*5 h; antiASP 11.8±1.5 mM*5h p<0.001; antiC5L2 10.4±0.9 mM*5h, p<0.001) and non-esterified fatty acid (AUC: control 1.3±0.3 mM*5h; antiASP 7.2±0.5 mM*5h p<0.001; antiC5L2 6.9±0.3 mM*5h p<0.001) clearance. TG content decreased in liver (antiASP -28.0% p<0.05; anti-C5L2 −40.9% p<0.01), but increased in muscle (62.0%, antiASP, p<0.01; 81.4%, antiC5L2, p<0.001). AntiASP and antiC5L2 block ASP-C5L2 interaction, demonstrating ASP functions through C5L2 receptor. Funding: 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) | 0.001 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".