Occupational exposure to formaldehyde and alterations in lymphocyte subsets
Bibliographic record
Abstract
BACKGROUND: Formaldehyde is used in many occupational settings, most notably in manufacturing, health care, and embalming. Formaldehyde has been classified as a human carcinogen, but its mechanism of action remains uncertain. METHODS: We carried out a cross-sectional study of 43 formaldehyde-exposed workers and 51 unexposed age and sex-matched controls in Guangdong, China to study formaldehyde's early biologic effects. To follow up our previous report that the total lymphocyte count was decreased in formaldehyde-exposed workers compared with controls, we evaluated each major lymphocyte subset (i.e., CD4(+) T cells, CD8(+) T cells, natural killer [NK] cells, and B cells) and T cell lymphocyte subset (CD4(+) naïve and memory T cells, CD8(+) naïve and memory T cells, and regulatory T cells). Linear regression of each subset was used to test for differences between exposed workers and controls, adjusting for potential confounders. RESULTS: Total NK cell and T cell counts were about 24% (P = 0.037) and 16% (P = 0.0042) lower, respectively, among exposed workers. Among certain T cell subsets, decreased counts among exposed workers were observed for CD8(+) T cells (P = 0.026), CD8(+) effector memory T cells (P = 0.018), and regulatory T cells (CD4(+) FoxP3(+) : P = 0.04; CD25(+) FoxP3(+) : P = 0.008). CONCLUSIONS: Formaldehyde-exposed workers experienced decreased counts of NK cells, regulatory T cells, and CD8(+) effector memory T cells; however, due to the small sample size; these findings need to be confirmed in larger studies.
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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 | 0.001 | 0.000 |
| 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".