Traces of heavy metals in children toenails as a bio-indicator of environmental exposure in Forlì (Northern Italy): an observational study.
Bibliographic record
Abstract
OBJECTIVES: to assess the concentration of heavy metals in the nails of children aged 6-9 years residing in Forlì (Emilia-Romagna Region, Northern Italy). DESIGN: biomonitoring survey. SETTING AND PARTICIPANTS: in March 2017, a total of 236 toenail samples were collected, 221 of them were eligible; the concentration of 23 metals were measured in these eligible samples. MAIN OUTCOME MEASURES: a spatial analysis was conducted, considering home addresses as grouped in the four macroareas in which the local territory is administratively divided. RESULTS: In the two North-Center and East areas - which include various industrial operations, two waste incinerators and a motorway - the total concentration of all metals resulted 60% higher than in the West and South areas. Given the lack of Italian reference values, comparison tests between areas were performed for aluminum (Al), cadmium (Cd), iron (Fe), manganese (Mn), copper (Cu), and zinc (Zn), which concentrations were detectable in over 50% of the subjects. Higher concentrations were observed in the East area compared with the other areas, with statistical significance for Al (vs North-Center), Cu and Zn (vs West), and Al and Mn (vs South). Further comparisons showed significantly higher concentration of Cu in Nord-Center vs West, which in turn had higher concentrations of Zn compared to the Southern area. By applying a Tobit regression to evaluate possible confounding factors, a marginally significant correlation resulted for the nail concentration of Mn among children practicing outdoor sports and eating locally grown vegetables. The consumption of local vegetables was at the limits of significance also for Cd. CONCLUSIONS: the data obtained came from a voluntary and crowdfunded study and suggest a possible relationship between the exposure to air pollutants and subsequent accumulation of metals in the nails. Further and more detailed epidemiological studies are warranted to identify the exposure sources and to yield preventive intervention.
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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 | 0.001 |
| 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 | 0.000 | 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".