Excessive vascular smooth muscle and macrophage proliferation underlies impaired coronary collateral growth in the metabolic syndrome
Bibliographic record
Abstract
Rationale Coronary collateral growth (CCG) is impaired in the metabolic syndrome. It is thought that inadequate cell proliferation is a causative factor. Pro‐angiogenic growth factors (GFs) stimulate cell proliferation. Metabolic syndrome patients and animal models exhibit elevated GF levels, but administration of GFs does not promote CCG in the metabolic syndrome. Objective To determine whether temporally inappropriate excessive cell proliferation underlies impaired CCG in the metabolic syndrome. Methods and Results Normal (SD) and metabolic syndrome (JCR) rats underwent transient, repetitive coronary artery occlusion (RI). We have previously shown that CCG was maximal at day 9 of RI in SD rats but did not occur in JCR rats. Cell proliferation was evaluated by immunohistochemistry (PCNA, Ki‐67) and Western blotting (PCNA). The increase in cell proliferation was transient in SD but greater and sustained in JCR rats. Assessment of cell cycle progression confirmed early and transient cell proliferation in SD vs. sustained proliferation in JCR rats. This was associated with accumulation of proliferating cells in the lumen of small arterioles in JCR rats, which failed to undergo outward expansion. Conclusions Excessive cell proliferation in the later stages of collateral remodeling underlies impaired CCG in the metabolic syndrome. R01 HL093052
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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) | 0.000 | 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) | 0.001 | 0.000 |
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".