The level of Hsp27 in lymphocytes is negatively associated with a higher risk of lung cancer
Bibliographic record
Abstract
Heat shock proteins (Hsps) can protect cells, organs, and whole organisms against damage caused by abnormal environmental hazards. Some studies have reported that lymphocyte Hsps may serve as biomarkers for evaluating disease status and exposure to environmental stresses; however, few epidemiologic studies have examined the associations between lymphocyte Hsps levels and lung cancer risk. We examined lymphocyte levels of Hsp27 and Hsp70 in 263 lung cancer cases and age- and gender-matched cancer-free controls by flow cytometry. Multivariate logistic regression models were used to estimate the association between lymphocyte Hsps levels and lung cancer risk. Our results showed that Hsp27 levels were significantly lower in lung cancer cases than in controls (16.5 vs 17.8 mean fluorescence intensity, P < 0.001). This was not observed for Hsp70 levels. Further stratification analysis revealed that lymphocyte Hsp27 levels were negatively associated with lung cancer risk especially in males and heavy smokers. There was a statistical trend of low odd ratios (95% confidence intervals) and upper tertile levels of Hsp27 [1.000, 0.904 (0.566-1.444) and 0.382 (0.221-0.658, P (trend) = 0.001) in males and 1.000, 0.9207 (0.465-1.822) and 0.419 (0.195-0.897, P (trend) = 0.036) in heavy smokers] after adjustment for confounding factors. These results suggest that lower lymphocyte Hsp27 levels might be associated with an increased risk of lung cancer. Our findings need to be validated in a large prospective study.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 0.001 |
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".