Brain gray matter volume of reward-related structures in Inuit adolescents pre- and postnatally exposed to lead, mercury and polychlorinated biphenyls
Bibliographic record
Abstract
This study aimed to assess associations between prenatal and postnatal exposure to lead (Pb), mercury (Hg) and polychlorinated biphenyls (PCBs) and gray matter volume of key regions of the brain reward circuit, namely the caudate nucleus, putamen, nucleus accumbens (nAcc), the amygdala, the orbitofrontal cortex (OFC) and the anterior cingulate cortex (ACC). Structural magnetic resonance imaging (MRI) was conducted in 77 Inuit adolescents (mean age = 18.39) from Nunavik, Canada, who also completed the Brief Sensation Seeking Scale (BSSS-4) and Sensation Seeking - 2 (SS-2), two self-report questionnaires evaluating the tendency toward sensation seeking, which is a proxy of reward-related behaviors. Exposures to Pb, Hg and PCBs were measured in cord blood at birth, in blood samples at 11 years old and at time of testing (18 years old). Multivariate linear regressions were corrected for multiple comparisons and adjusted for potential confounders, such as participants' sociodemographic characteristics and nutrient fish intake. Results showed that higher cord blood Pb levels predicted smaller gray matter volume in the bilateral nAcc, caudate nucleus, amygdala and OFC as well as in left ACC. A moderating effect of sex was identified, indicating that the Pb-related reduction in volume in the nAcc and caudate nucleus was more pronounced in female. Higher blood Hg levels at age 11 predicted smaller right amygdala independently of sex. No significant associations were found between blood PCBs levels at all three times of exposure. This study provides scientific support for the detrimental effects of prenatal Pb and childhood Hg blood concentrations on gray matter volume in key reward-related brain structures.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".