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Record W4417040413 · doi:10.1038/s41598-025-30900-x

Cross-sectional evaluation of exposure to ozone, nitrogen dioxide, and particulate mass levels on circulating immune markers in women in the California Teachers Study

2025· article· en· W4417040413 on OpenAlexaff
Emily Cauble, Michael J. Kleeman, Yusheng Zhao, Meredith Franklin, Mandy Yao, Emma S. Spielfogel, Tarik Benmarhnia, James V. Lacey, Mitchell S.V. Elkind, Juan Zhao, Larry Magpantay, Otoniel Martı́nez-Maza, Sophia Wang, Marta Epeldegui

Bibliographic record

VenueScientific Reports · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsUniversity of Toronto
FundersNational Institute of Environmental Health SciencesNational Cancer InstituteNational Institutes of Health
KeywordsImmune systemInterquartile rangeInhalation exposureParticulatesAir pollutantsLogistic regression

Abstract

fetched live from OpenAlex

Abstract Exposure to ambient air pollutants, specifically ozone (O 3 ), nitrogen dioxide (NO 2 ), ultrafine, fine or coarse particulate matter (PM 0.1 , PM 2.5 , and PM 10 ), has been linked to a number of adverse health outcomes, including cardiovascular disease. Changes in immune response may be a key mechanism underlying these effects. Within the California Teachers Study cohort, we conducted a cross-sectional analysis of 1,898 women to assess the associations between exposure to O 3 , NO 2 , PM 0.1 , PM 2.5 , and PM 10 and 15 immune markers measured from serum samples collected in 2015. Daily residential exposures to O 3 , NO 2 , PM 0.1 , PM 2.5 , and PM 10 were estimated by a validated chemical transport model and averaged over 12-, 3-, and 1-month periods prior to blood draw. Fifteen immune markers (categorized as quartiles) were estimated per interquartile range (IQR) of air pollutant exposures using multivariable ordinal logistic regressions adjusted for age, body mass index, and respective pollutants. Immune markers were also grouped into immune pathways (pro-inflammatory/macrophage activation, B-cell activation, and T-cell activation). After applying Bonferroni correction, elevated exposure to O 3 levels at all three exposure windows were associated with elevated circulating levels of IL-1β (interleukin-1 beta), IL-8 (interleukin 8), sTNFR2 (soluble tumor necrosis factor receptor 2), and sgp130 (soluble glycoprotein 130). Elevated O 3 at 3- and 1-month periods were associated with increased levels of sCD27 (soluble cluster of differentiation 27) and BAFF (B-cell activating factor). In pathway analyses, O 3 was consistently and significantly associated with the pro-inflammatory/macrophage activation pathway (12-month OR = 1.49, 3-month OR = 1.57, 1-month OR = 1.54) and with B-cell activation at all three exposure windows (12-month OR = 1.24, 3-month OR = 1.53, 1-month OR = 1.41). NO 2 was positively associated with TNFα at the 3- and 1-month exposure windows. For the PM size fractions, sporadic, mainly inverse, associations with immune markers were observed. Elevated O 3 exposure up to one year prior to blood draw was associated with elevated immune markers related to pro-inflammatory response, macrophage activation, and B cell activation. These findings suggest potential immunologic pathways linking air pollution to adverse health outcomes in women.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.056
GPT teacher head0.352
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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