The fractions of respiratory tract cells at risk in formaldehyde carcinogenesis
Bibliographic record
Abstract
Clonal growth modeling of carcinogenesis requires data on the number of cells at risk of becoming cancerous. We synthesized literature data to estimate the fraction of respiratory tract epithelial cells that are progenitor cells, and therefore at risk, in formaldehyde carcinogenesis for specific respiratory tract regions. We concluded that the progenitor cells for the transitional and respiratory epithelia of the nose are basal and nonciliated cells and Type II cells in the alveolar region. In the conducting airways, our evaluation indicated that ciliated and basal cells are not in the progenitor pool. Respiratory tract epithelial cell fractions of 0.819 in rats and 0.668 in humans were estimated from the data. The total numbers of epithelial cells in the lower respiratory tract of humans and rats were allocated to individual generations. Cell cycle times were also estimated from literature data, since the reciprocal of cell cycle time is an important variable in clonal growth modeling. Sensitivity analyses of a previously published risk model for formaldehyde carcinogenesis showed that specification of the fraction of cells at risk markedly affects estimates of some parameters of the clonal growth model. When all epithelial cells are considered part of the progenitor pool, additional risks for the non-smoking population was typically over predicted by about 35% for high exposure levels. These results demonstrate the importance of accurately identifying cell populations at risk when applying quantitative models in risk assessments.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".