Plasma levels of Hsp70 and anti-Hsp70 antibody predict risk of acute coronary syndrome
Bibliographic record
Abstract
Although immune reactions against heat shock proteins have been implicated in the pathogenesis of atherosclerosis, conflicting associations between Hsp70, anti-Hsp70 antibody and coronary heart disease (CHD) have been reported. This study assessed whether there is a significant association between extracellular human Hsp70, anti-Hsp70 antibody and acute coronary syndrome (ACS) and stable angina (SA), and examined dynamic changes in Hsp70 and anti-Hsp70 antibody levels induced by acute myocardial infarction (AMI). Plasma Hsp70 and anti-Hsp70 antibody levels in 291 patients with ACS (179 AMI, 112 unstable angina), 126 patients with SA and 417 age and sex-matched healthy subjects, and in 40 patients after admission for AMI, and on day 2, 3, and 7 after the onset of AMI were determined using enzyme-linked immunosorbent assays. Hsp70 levels were significantly higher in ACS and SA and anti-Hsp70 antibody levels were only markedly lower in ACS than controls. After adjustment for traditional CHD risk factors, increasing levels of Hsp70 were significantly associated with an increased risk and severity of ACS (P for trend < 0.001), whereas increasing levels of anti-Hsp70 antibody were associated with a decreased risk of ACS (P for trend = 0.0003). High levels of Hsp70 combined with low levels of anti-Hsp70 antibody had a joint effect on the risk of ACS (OR, 5.14, 95% CI, 3.00-8.79; P < 0.0001). In patients with AMI, Hsp70 levels decreased rapidly from days 1-7 after onset, whereas anti-Hsp70 antibody levels increased in patients with AMI. These findings suggest that higher Hsp70 levels or lower anti-Hsp70 antibody levels are independently associated with a higher risk of ACS. Higher Hsp70 levels and lower anti-Hsp70 antibody levels combine to further increase this risk.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".