Abstract 414: Local Artery Wall Inflammation Overrides Systemic Inflammation in Diabetes-Accelerated Atherosclerosis
Bibliographic record
Abstract
Human genomic studies have highlighted the importance of arterial wall-specific inflammatory processes in cardiovascular disease (CVD) risk. Diabetes increases systemic inflammation, local arterial inflammation, and CVD risk. To clarify the relative contributions of systemic inflammation versus artery wall inflammatory processes in atherosclerosis, we studied LDL receptor-deficient mice with streptozotocin-induced diabetes. The damage-associated molecular pattern protein S100A9 and toll-like receptor 4 (TLR4) have both been implicated in diabetes-induced inflammation. S100A9-deficient bone marrow chimeras were used to inhibit systemic inflammation, 5-aminosalicylic acid (5-ASA) was used to inhibit intestinal inflammation, and TLR4-deficient bone marrow chimeras were used to inhibit artery wall inflammation. No model affected the severity of diabetes, plasma cholesterol or blood leukocyte numbers. Hematopoietic S100A9-deficiency, but not TLR4-deficiency, reduced diabetes-associated systemic inflammation to levels observed in non-diabetic mice. 5-ASA differentially altered measures of systemic inflammation. Thus, diabetes induced a 2-fold increase in circulating leukocyte Il1b mRNA, which was normalized by S100A9-deficiency (p<0.01, n=7-10) and 5-ASA, but was not reduced by hematopoietic TLR4-deficiency (n=11-14). Similarly, diabetes increased plasma levels of the acute-phase protein serum amyloid-A (SAA), which were normalized by S100A9-deficiency (p<0.01, n=5-12), but not by TLR4-deficiency (n=5-10) or 5-ASA. Conversely, hematopoietic TLR4-deficiency (p<0.05), but not hematopoietic S100A9-deficiency or 5-ASA, reduced diabetes-accelerated myeloid cell accumulation in the artery wall determined by aortic en face Sudan IV staining (n=16-21). Finally, laser capture microdissection of CD68-positive lesional macrophages revealed that hematopoietic TLR4-deficiency prevents diabetes-induced inflammatory processes in the artery wall including expression of Il1b, Ccr2 , and S100a9 mRNA. Together, our data strongly suggest that although systemic inflammation is increased in diabetes, inhibition of inflammatory processes in the artery wall is required to prevent lesional macrophage accumulation.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".