Air pollution biological effects in children living in Lecce (Italy) by Buccal micronucleus cytome assay (the MAPEC_LIFE study)
Bibliographic record
Abstract
The aim of the MAPEC_LIFE (Monitoring Air Pollution Effects on Children for Supporting Public Health Policy) study is to evaluate the associations between the concentrations of air pollutants and early biological effects in children living in five Italian towns (Brescia, Torino, Lecce, Perugia and Pisa) characterised by varying levels of air pollution.This paper presents the results of micronucleus cytome assays performed on the oral mucosa cells of subjects living in Lecce (Puglia, Italy) and their relationship to factors associated with indoor/outdoor exposure and lifestyles.The study was conducted on 6-8-year-old schoolchildren living in Lecce.The micronucleus cytome assay was performed on exfoliated buccal cells collected from the oral mucosa of children using a soft-bristled toothbrush.Micronuclei were evaluated only in normal differentiated cells.Overall, 43.0% of the samples tested were positive, with an average frequency of 0.28 MN/1000 differentiated cells.Data analysis shows positive associations between the frequency of MN in the children's buccal mucosa cells and obesity, heavy traffic and smoking mothers, while outdoor sports seem to have the opposite effect.These data will be integrated with data from the other cities involved in the MAPEC_LIFE study and could be used to build a model for estimating global genotoxic risk.
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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) | 0.001 | 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 | 0.001 |
| 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".