Sensitivity to Ozone, Diesel Exhaust Particles, and Standardized Ambient Particulate Matter in Rats with a<i>Listeria Monocytogenes</i>-Induced Respiratory Infection
Bibliographic record
Abstract
Ambient particulate matter may increase respiratory allergic skewing of the T-cell-mediated immune response toward a T-helper-2 (Th2) response, with the consequence that the Th1 response develops less well. Successful clearing of a respiratory bacterial infection depends on an adequate Th1 immune response; therefore, the subject would not control the infection as well if exposed to particulate matter. To substantiate this hypothesis, we examined the effect of exposure to diesel exhaust particles (DEP) and urban particulate matter (EHC-93, Ottawa dust) on rats with a Listeria monocytogenes respiratory infection. Since this hypothesis has been confirmed for ozone, we used it as a positive control. Wistar rats were exposed to ozone (2 mg/m3 for 24 h/day for 7 days) and to DEP or to EHC-93 (50 microg/rat intranasally daily for 7 consecutive days). Twenty-four hours after the last exposure, the rats were infected intratracheally with 1 x 10(6) L. monocytogenes bacteria. The number of L. monocytogenes was determined after 3, 4 and 5 days. Statistically significant increases of the number of L. monocytogenes in rats exposed to ozone were observed in the lungs and spleen at all three times. However, we found no significant differences in the numbers of bacteria that were found in rats exposed to DEP or EHC-93 compared to the saline-treated group at any of the three times. In conclusion, the results of this study do not support the hypothesis that exposure to DEP or EHC-93 reduces subsequent resistance to a respiratory infection in rats.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 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".