TNF <b>α</b> and IL-6 Responses to Particulate Matter <i>in Vitro</i> : Variation According to PM Size, Season, and Polycyclic Aromatic Hydrocarbon and Soil Content
Bibliographic record
Abstract
BACKGROUND: Observed seasonal differences in particulate matter (PM) associations with human health may be due to their composition and to toxicity-related seasonal interactions. OBJECTIVES: We assessed seasonality in PM composition and in vitro PM pro-inflammatory potential using multiple PM samples. METHODS: We collected 90 weekly PM10 and PM2.5 samples during the rainy-warm and dry-cold seasons in five urban areas with different pollution sources. The elements, polycyclic aromatic hydrocarbons (PAHs), and endotoxins identified in the samples were subjected to principal component analysis (PCA). We tested the potential of the PM to induce tumor necrosis factor alpha (TNFα) and interleukin 6 (IL-6) secretion in cultured human monocytes (THP-1), and we modeled pro-inflammatory responses using the component scores. RESULTS: PM composition varied by size and by season. PCA identified two main components that varied by season. Combustion-related constituents (e.g., vanadium, benzo[a]pyrene, benzo[a]anthracene) mainly comprised component 1 (C1). Soil-related constituents (e.g., endotoxins, silicon, aluminum) mainly comprised component 2 (C2). PM from the rainy-warm season was high in C2. PM (particularly PM2.5) from the dry-cold season was rich in C1. Elevated levels of cytokine production were associated with PM10 and C2 (rainy-warm season), whereas reduced levels of cytokine production were associated with PM2.5 and C1 (dry-cold season). TNFα secretion was increased following exposure to PM with high (vs. low) C2 content, but TNFα secretion in response to PM was decreased following exposure to samples containing ≥ 0.1% of C1-related PAHs, regardless of C2 content. The results of the IL-6 assays suggested more complex interactions between PM components and particle size. CONCLUSIONS: Variations in PM soil and PAH content underlie seasonal and PM size-related patterns in TNFα secretion. These results suggest that the mixture of components in PM explains some seasonal differences in associations between health outcomes and PM in epidemiologic studies. CITATION: Manzano-León N, Serrano-Lomelin J, Sánchez BN, Quintana-Belmares R, Vega E, Vázquez-López I, Rojas-Bracho L, López-Villegas MT, Vadillo-Ortega F, De Vizcaya-Ruiz A, Rosas Perez I, O'Neill MS, Osornio-Vargas AR. 2016. TNFα and IL-6 responses to particulate matter in vitro: variation according to PM size, season, and polycyclic aromatic hydrocarbon and soil content. Environ Health Perspect 124:406-412; http://dx.doi.org/10.1289/ehp.1409287.
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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".