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Record W2500528560 · doi:10.1097/jom.0000000000000841

Air Pollution During Pregnancy and Cord Blood Immune System Biomarkers

2016· article· en· W2500528560 on OpenAlexfundaboutno aff
Jillian Ashley‐Martin, Éric Lavigne, Tye E. Arbuckle, Markey Johnson, Perry Hystad, Dan L. Crouse, Jean S. Marshall, Linda Dodds

Bibliographic record

VenueJournal of Occupational and Environmental Medicine · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicIL-33, ST2, and ILC Pathways
Canadian institutionsnot available
FundersHealth CanadaKillam Trusts
KeywordsCord bloodThymic stromal lymphopoietinMedicinePregnancyImmune systemImmunologyImmunoglobulin EPhysiologyUmbilical cordEnvironmental healthObstetricsAntibodyBiology

Abstract

fetched live from OpenAlex

OBJECTIVES: We aimed to determine whether average and trimester-specific exposures to ambient measures of nitrogen dioxide (NO2) and particular matter (PM2.5) were associated with elevated cord blood concentrations of immunoglobulin E (IgE) and two epithelial cell produced cytokines: interleukin-33 (IL-33) and thymic stromal lymphopoietin (TSLP). METHODS: This study utilized data and biospecimens from the Maternal-Infant Research on Environmental Chemicals (MIREC) Study. There were 2001 pregnant women recruited between 2008 and 2011 from 10 Canadian cities. Maternal exposure to NO2 and PM2.5 was estimated using land use regression and satellite-derived models. RESULTS: We observed statistically significant associations between maternal NO2 exposure and elevated cord blood concentrations of both IL-33 and TSLP among girls but not boys. CONCLUSIONS: Maternal NO2 exposure may impact the development of the newborn immune system as measured by cord blood concentrations of two cytokines.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.910
Threshold uncertainty score0.279

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.212
Teacher spread0.201 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations39
Published2016
Admission routes2
Has abstractyes

Explore more

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