Uptake of inhaled polychlorinated biphenyls (PCBs) in a human longitudinal cohort study and animal inhalation studies
Bibliographic record
Abstract
PCBs are a group of 209 persistent organic pollutants whose carcinogenic and neurological toxicities are well established. PCB inhalation exposure assessments have been lacking for non-occupational conditions and for lower-Cl congeners. We assessed congener-specific inhalation and dietary exposure for 78 adolescent children and their mothers (n=68) in the Airborne Exposure to Semi-volatile Organic Pollutants (AESOP) Study. Congener-specific PCB inhalation exposure was modeled using 293 measurements of indoor and outdoor airborne PCB concentrations at homes and schools, analyzed via tandem quadrupole GS-MS/MS, combined with questionnaire data from the AESOP Study. Dietary exposure was modeled using Canadian Total Diet Survey PCBs and U.S. National Health and Nutrition Examination Survey food ingestion rates. For ∑PCB, including the higher-Cl congeners, dietary exposure dominated. For individual lower-Cl congeners, inhalation exposure was as high as one-third of the total dietary + inhalation exposure. Geometric mean ∑PCB inhalation was greater for urban mothers (7.1 µg yr-1) and children (12.0 µg yr-1) than for rural mothers (2.4 µg yr-1) and children (8.9 µg yr-1). AESOP Study schools had higher indoor PCB concentrations than did homes, and accounted for the majority of children9s inhalation exposure. Concurrent sub-chronic inhalation studies in rats using a complex PCB mixture that represents urban air demonstrated uptake from the lung resulting in alteration of thyroid hormones and increased oxidative stress. Although several PCB congeners were enriched in lung tissue, the lung was primarily a route of exposure rather than a target organ for inhaled PCBs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".