A Self-Fulfilling Prophecy
Bibliographic record
Abstract
BACKGROUND: Given the central importance of nitric oxide (NO) in the development and clinical course of cardiovascular diseases, we sought to determine whether the powerful predictive value of C-reactive protein (CRP) might be explained through an effect on NO production. METHODS AND RESULTS: Endothelial cells (ECs) were incubated with recombinant CRP (0 to 100 microg/mL, 24 hours), and NO and cyclic guanosine monophosphate (cGMP) production was assessed. The effects of CRP on endothelial NO synthase (eNOS) protein, mRNA expression, and mRNA stability were also examined. In a separate study, the effects of CRP (25 microg/mL) on EC cell survival, apoptosis, and in vitro angiogenesis were evaluated. Incubation of ECs with CRP resulted in a significant inhibition of basal and stimulated NO release, with concomitant reductions in cGMP production. CRP caused a marked downregulation of eNOS mRNA and protein expression. Actinomycin D studies suggested that eNOS downregulation was related to decreased mRNA stability. In conjunction with a decrease in NO production, CRP inhibited both basal and vascular endothelial growth factor-stimulated angiogenesis as assessed by EC migration and capillary-like tube formation. CRP did not induce EC survival but did, however, promote apoptosis in a NO-dependent fashion. CONCLUSIONS: CRP, at concentrations known to predict adverse vascular events, directly quenches the production of the NO, in part, through posttranscriptional effect on eNOS mRNA stability. Diminished NO bioactivity, in turn, inhibits angiogenesis, an important compensatory mechanism in chronic ischemia. Through decreasing NO synthesis, CRP may facilitate the development of diverse cardiovascular diseases. Risk reduction strategies designed to lower plasma CRP may be effective by improving NO bioavailability.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.007 |
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".