Low levels of soluble receptor for advanced glycation end products in non-ST elevation myocardial infarction patients
Bibliographic record
Abstract
BACKGROUND: Interaction of the receptors for advanced glycation end products (RAGEs) with advanced glycation end products (AGEs) results in expression of inflammatory mediators (tumor necrosis factor-alpha [TNF-α] and soluble vascular cell adhesion molecule-1 [sVCAM-1]), activation of nuclear factor-kappa B and induction of oxidative stress - all of which have been implicated in atherosclerosis. Soluble RAGE (sRAGE) acts as a decoy for the RAGE ligand and is protective against atherosclerosis. OBJECTIVES: To determine whether levels of serum sRAGE are lower, and whether levels of serum AGEs, TNF-α and sVCAM-1 are higher in non-ST elevation myocardial infarction (NSTEMI) patients than in healthy control subjects; and whether sRAGE or the ratio of AGEs to sRAGE (AGEs/sRAGE) is a predictor/biomarker of NSTEMI. METHODS: Serum levels of sRAGE, AGEs, TNF-α and sVCAM-1 were measured in 46 men with NSTEMI and 28 age- and sex-matched control subjects. Angiography was performed in the NSTEMI patients. RESULTS: sRAGE levels were lower, and levels of AGEs, TNF-α, sVCAM-1 and AGEs/sRAGE were higher in NSTEMI patients than in control subjects. sRAGE levels were negatively correlated with the number of diseased coronary vessels, serum AGEs, AGEs/sRAGE, TNF-α and sVCAM-1. The sensitivity of the AGEs/sRAGE test is greater than that of the sRAGE test, while the specificity and predictive values of the sRAGE test are greater than those of the AGEs/sRAGE test for identifying NSTEMI patients. CONCLUSIONS: Serum levels of sRAGE were low in NSTEMI patients, and were negatively correlated with extent of lesion, inflammatory mediators, AGEs and AGEs/sRAGE. Both sRAGE and AGEs/sRAGE may serve as biomarkers/predictors for identifying NSTEMI patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".