CD55 Deficiency Protects against Atherosclerosis in ApoE-Deficient Mice via C3a Modulation of Lipid Metabolism
Bibliographic record
Abstract
Atherosclerosis, the leading cause of death in the Western world, is driven by chronic inflammation within the artery wall. Elements of the complement cascade are implicated in the pathogenesis, because complement proteins and their activation products are found in the atherosclerotic plaque. We examined the role of CD55, a membrane inhibitor of the complement component 3 (C3) convertase, which converts C3 into C3a and C3b, in atherosclerosis. CD55-deficient (CD55(-/-)) mice were crossed onto the atherosclerosis-prone apolipoprotein E (apoE)-deficient (apoE(-/-)) background. High fat-fed male apoE(-/-)/CD55(-/-) mice were strongly protected from developing atherosclerosis compared with apoE(-/-) controls. Lipid profiling showed significantly lower levels of triglycerides, nonesterified fatty acids, and cholesterol in apoE(-/-)/CD55(-/-) mice than that in controls after high-fat feeding, whereas body fat in apoE(-/-)/CD55(-/-) mice content was increased. Plasma levels of C3 fell, whereas concentrations of C3adesArg (alias acylation stimulating protein; ASP), produced by serum carboxypeptidase N-mediated desargination of C3a, increased in nonfasted high fat-fed apoE(-/-)/CD55(-/-) mice, indicating complement activation. Thus, complement dysregulation in the absence of CD55 provoked increased C3adesArg production that, in turn, caused altered lipid handling, resulting in atheroprotection and increased adiposity. Interventions that target complement activation in adipose tissue should be explored as lipid-decreasing strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".