SOLUBLE AND INSOLUBLE AIR PARTICLE FRACTIONS INDUCE DIFFERENTIAL PRODUCTION OF TUMOR NECROSIS FACTOR α IN RAT LUNG
Bibliographic record
Abstract
Altered cytokine production in the lung follows the deposition of urban air particles. The present study was designed to measure changes in tumor necrosis factoralpha (TNFalpha) and endothelin-1 (ET-1) levels in rat lung after instilling various fractions of the dust EHC-93, while in vitro, alveolar macrophages (AMs) and type 2 epithelial cells were studied to determine relative production of these molecules in response to the same particles. Whole dust and its soluble and leached components were instilled into rat lung and the animals were killed at intervals to 2 weeks; they received tritiated thymidine by intraperitoneal injection 1 hour before death. All samples induced some inflammation, with the highest cellular efflux being found by bronchoalveolar lavage 1 day after leached particles. Lung injury, illustrated by protein levels in lavage fluid, was maximal after instilling the soluble fraction and subsequently epithelial regeneration was also maximal in this group. TNFalpha levels were highest after instilling whole dust or its leached fraction at 4 hours and 1 day, and cell culture studies indicated a predominant AM source for this cytokine. ET-1 levels were also increased in BAL from 4 hours to 3 days and were mostly associated with the instillation of leached particles. The results demonstrate that the rapid production/release of TNFalpha and ET-1 after particle deposition is largely due to the insoluble particulate fraction. There appears to be a differential response to whole dust where the soluble components cause some inflammation and epithelial cell necrosis, whereas the leached particles are more likely to react with macrophages to induce the production of proinflammatory cytokines such as TNFalpha.
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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) | 0.001 | 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 | 0.001 |
| 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".