Occupational exposure to trichloroethylene is associated with a decline in lymphocyte subsets and soluble CD27 and CD30 markers
Bibliographic record
Abstract
Occupational cohort and case-control studies suggest that trichloroethylene (TCE) exposure may be associated with non-Hodgkin lymphoma (NHL) but findings are not consistent. There is a need for mechanistic studies to evaluate the biologic plausibility of this association. We carried out a cross-sectional molecular epidemiology study of 80 healthy workers that used TCE and 96 comparable unexposed controls in Guangdong, China. Personal exposure measurements were taken over a three-week period before blood collection. Ninety-six percent of workers were exposed to TCE below the current US Occupational Safety and Health Administration Permissible Exposure Limit (100 p.p.m. 8 h time-weighted average), with a mean (SD) of 22.2 (36.0) p.p.m. The total lymphocyte count and each of the major lymphocyte subsets including CD4+ T cells, CD8+ T cells, natural killer (NK) cells and B cells were significantly decreased among the TCE-exposed workers compared with controls (P < 0.05), with evidence of a dose-dependent decline. Further, there was a striking 61% decline in sCD27 plasma level and a 34% decline in sCD30 plasma level among TCE-exposed workers compared with controls. This is the first report that TCE exposure under the current Occupational Safety and Health Administration workplace standard is associated with a decline in all major lymphocyte subsets and sCD27 and sCD30, which play an important role in regulating cellular activity in subsets of T, B and NK cells and are associated with lymphocyte activation. Given that altered immunity is an established risk factor for NHL, these results add to the biologic plausibility that TCE is a possible lymphomagen.
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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 | 0.000 |
| 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) | 0.001 | 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".