Induction of Anti-Anti-Idiotype Antibodies Against Sulfated Glycosaminoglycans Reduces Atherosclerosis in Apolipoprotein E–Deficient Mice
Bibliographic record
Abstract
OBJECTIVE: The pathogenesis of atherosclerosis is associated with the early retention of low-density lipoproteins that are trapped in the extracellular matrix of the arterial intima by interaction with glycosaminoglycan side chains of proteoglycans. Mutant mouse/human chimeric antibodies of the murine monoclonal antibody P3, which react with N-glycolyl-containing gangliosides and sulfated glycosaminoglycans, were tested for their potentially antiatherogenic properties through the induction of an idiotypic antibody network that may specifically interfere with the binding of low-density lipoproteins to proteoglycan side chains, low-density lipoprotein modification, and foam cell formation. METHODS AND RESULTS: Apolipoprotein E-deficient mice fed a high-fat, high-cholesterol diet received 5 to 6 doses of chP3R99 or chP3S98 mutant antibodies, showing high and low reactivity, respectively, against their respective antigens. Both chimeric antibodies elicited an immunodominant anti-idiotypic response in the absence of adjuvant. A striking (40%-43%) reduction (P<0.01) in total lesion areas was observed in 18-week-old mice immunized with chP3R99, but not chP3S98, compared with PBS-treated mice. The antiatherosclerotic effect was associated with increased mice sera reactivity against heparin and sulfated glycosaminoglycans, including chondroitin and dermatan sulfate. In addition, purified IgG from chP3R99-immunized mice blocked the retention of apolipoprotein B-containing lipoproteins within the arterial wall of apolipoprotein E(-/-) mice. CONCLUSIONS: The present study supports use of active immunization and the mounting of an idiotypic antibody network response against glycosaminoglycans as a novel approach to target atherosclerosis.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".