Biomonitoring Study of Persistent Organic Pollutants and Metals in Pregnant Women in Mexico
Bibliographic record
Abstract
ISEE-878 Introduction: Mexico is participating in the North American trilateral maternal blood contaminant monitoring study of persistent organic pollutants (POPs) and metals. The purpose is to obtain an integrated baseline that can be used to determine priorities for track progress in management of these substances domestically and on a broader cooperative basis within North America. Objective: To develop a profile of pregnant women exposures to persisted organic pollutants and metals to assist in the identification patterns of exposure in Mexico. Material and Methods: A total of 235 women from cities of Coatzacoalcos, Tultitlán Monterrey, Córdoba, Salamanca, Guadalajara, Hermosillo, Cd. Obregón, Mérida, and Querétaro were recruited for the study. The first 5 cities are urban populations and the others were selected on the basis of the identification of likely environmental hotspots. The doctor in charge of the pregnant women directed them to a nurse who applied a screening test, they were then included in the study, and obtained the blood samples. POPs and metals were analyzed at Institut National de Santé Publique du Québec, Canada laboratory and dioxins by CDC. Results: The highest concentration of metals were Cordoba (lead), Salamanca (cadmium), Monterrey (inorganic mercury), and Coatzacoalcos (total mercury). The results showed that the highest concentration of p′-DDE and P.p′-DDT were found in Coatzacoalcos, geometric mean = 8.80 μg/L (6.30, 12.31) and 0.32 (0.21, 0.05) PCB, Arochlor 1260 and PCB, IUPAC 180 were found in Merida 0.52 μg/L (0.41, 0.66); 0.035 μg/L (0.03, 0.05); Guadalajara had the highest level of Oxychlordane 0.21 (0.01, 0.03). For dioxins we found the highest levels in Coatzacoalcos TEQs 19.96 pg/g lipids. Conclusions: We found high levels of POP's in urban cities nonhotspots sites. We need to correlate the exposure questionnaires with the blood samples in order to obtain more information.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".