Serum Levels of TGF-β1 and MCP-1 as Biomarkers for Progressive Coal Workers’ Pneumoconiosis in Retired Coal Workers: A Three-year Follow-up Study
Bibliographic record
Abstract
Various cytokines activated by the inhalation of coal dust may mediate inflammation and lead to tissue damage. Objective of this study was to examine the relationships between coal workers' pneumoconiosis (CWP) progression over a 3 yr period and the serum levels of cytokines in 85 retired coal workers. To investigate the relevance of serum cytokines in CWP, serum levels of interleukin-8 (IL-8), tumor necrosis factor-alpha (TNF-α), transforming growth factor-beta1 (TGF-β1), and monocyte chemotactic protein-1 (MCP-1) as progressive CWP biomarkers were studied in relation to the progression of pneumoconiosis over a 3 yr period in 85 patients with CWP. CWP progression was evaluated through paired comparisons of chest radiographs. Median levels of TGF-β1 and MCP-1 were significantly higher in subjects with progressive CWP than in those without CWP progression. The area under the ROC curve for TGF-β1 (0.693) and MCP-1 (0.653) indicated that these cytokines could serve as biomarkers for the progression of CWP. Serum TGF-β1 levels were related to the progression of CWP (β=0.247, p=0.016). The results suggest that high serum levels of TGF-β1 and MCP-1 are associated with the progression of CWP.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".