Associations of prenatal exposure to lead and mercury with auditory function in infants
Bibliographic record
Abstract
PURPOSE: This study examined the association between lead (Pb) and mercury (Hg) exposure during early brain development with auditory function in infants. METHODS: Auditory function of six-month-old infants from the Maternal-Infant Research on Environmental Chemicals-Infant Development (MIREC-ID) cohort was assessed with minimal auditory response levels (MRLs) to warble tones and speech in soundfield, tympanometry, and otoacoustic emissions (OAEs; transient - TEOAEs; and distortion product - DPOAEs). Pb and total Hg concentrations in blood samples were obtained at three time points: maternal blood samples at the first and third trimesters of pregnancy, and umbilical cord blood samples at birth. RESULTS: Higher maternal blood Pb concentrations during pregnancy were significantly related with low OAEs. The associations were stronger for TEOAEs, in particular TEOAE reproducibility, than DPOAEs, and were stronger in the left ear compared with the right ear for TEOAEs. Pb was barely associated with MRLs. No clear evidence of association between Hg exposure and auditory function (OAEs and MRL) was found. CONCLUSIONS: Developmental exposure to low Pb concentrations are associated with a reduction of outer hair cells responses to sounds, suggestive of a decrease in inner ear function. Further studies are needed to verify these results in a larger sample of infants.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".