Mast Cell Response to Formaldehyde
Bibliographic record
Abstract
To examine the effects of the atmospheric pollutant formaldehyde on functionally distinct mast cells, peritoneal mast cells (PMC), intestinal mucosal mast cells (IMMC) and mouse bone-marrow-derived mast cells (BMMC) were incubated with various concentrations of formaldehyde. Pretreatment for 30 min with up to 100 micrograms/ml formaldehyde was not cytotoxic to mast cells. Formaldehyde (1-10 micrograms/ml) alone induced low levels of histamine release (< 10%) from IMMC and BMMC. Antigen-induced histamine release was significantly increased in both PMC pretreated with low concentrations of formaldehyde (5-20 micrograms/ml) and BMMC pretreated with 10 micrograms/ml formaldehyde but decreased in PMC pretreated with a higher concentration (100 micrograms/ml) of formaldehyde. By contrast, antigen-induced histamine release was decreased in IMMC pretreated with formaldehyde in a dose-dependent manner. Histamine release stimulated with A23187 was also increased in PMC pretreated with a low concentration (10 micrograms/ml) of formaldehyde but decreased in those pretreated with a higher concentration (100 micrograms/ml) of formaldehyde. Pretreatment with 10 micrograms/ml formaldehyde significantly enhanced beta-hexosaminidase release from PMC stimulated with antigen or A23187. Compared to sham-treated PMC, PMC pretreated with formaldehyde expressed a markedly depressed natural cytotoxicity for the tumor target WEHI-164 (an assay of tumor necrosis factor alpha activity). These results suggest that formaldehyde modifies various mast cell functions through alterations in cellular metabolism. Such effects may be important in respiratory and other diseases associated with formaldehyde exposure.
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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 | 0.000 | 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) | 0.002 | 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".