Air Pollution Particulate Matter Alters Antimycobacterial Respiratory Epithelium Innate Immunity
Bibliographic record
Abstract
Inhalation exposure to indoor air pollutants and cigarette smoke increases the risk of developing tuberculosis (TB). Whether exposure to ambient air pollution particulate matter (PM) alters protective human host immune responses against Mycobacterium tuberculosis has been little studied. Here, we examined the effect of PM from Iztapalapa, a municipality of Mexico City, with aerodynamic diameters below 2.5 μm (PM2.5) and 10 μm (PM10) on innate antimycobacterial immune responses in human alveolar type II epithelial cells of the A549 cell line. Exposure to PM2.5 or PM10 deregulated the ability of the A549 cells to express the antimicrobial peptides human β-defensin 2 (HBD-2) and HBD-3 upon infection with M. tuberculosis and increased intracellular M. tuberculosis growth (as measured by CFU count). The observed modulation of antibacterial responsiveness by PM exposure was associated with the induction of senescence in PM-exposed A549 cells and was unrelated to PM-mediated loss of cell viability. Thus, the induction of senescence and downregulation of HBD-2 and HBD-3 expression in respiratory PM-exposed epithelial cells leading to enhanced M. tuberculosis growth represent mechanisms by which exposure to air pollution PM may increase the risk of M. tuberculosis infection and the development of TB.
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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) | 0.001 | 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".