Gene-environment interactions in Paget's disease of bone
Bibliographic record
Abstract
OBJECTIVES: This study explored the role of outdoor and indoor air pollutants in Paget's disease of bone (PDB). METHODS: We performed a survey in 140 French-Canadian patients with PDB, including 39 carriers of p.Pro392Leu mutation (SQSTM1 gene) and 113 healthy not mutated controls. The survey covered outdoor air pollution near the residence and indoor air pollutants by focusing on heating fuels and exposure to tobacco smoke. In a subgroup of patients, urinary concentrations of 17 heavy metals and 11 polycyclic aromatic hydrocarbons were measured by mass spectrometry. In light of what we learned from the survey and urinary assays, we explored the in vitro effects of certain toxics on osteoclasts in PDB. We conducted in vitro monocytes differentiation from peripheral blood of more than 40 participants, whose osteoclasts were treated with or without the toxic. The morphology of osteoclasts, their bone resorption abilities, gene and protein expression levels, and cellular oxidative stress levels were assayed. RESULTS: An inhibitory effect of cigarette smoke condensate and heavy metals was observed on morphology and bone resorption activity of patients' osteoclasts. SQSTM1 gene expression was upregulated in osteoclasts from patients with PDB versus healthy controls in presence of cadmium, and SQSTM1 protein expression was upregulated in presence of bismuth and tobacco smoke condensates, in particular in osteoclasts from carriers of the SQSTM1 mutation. Furthermore, high levels of oxidative stress in patients' osteoclasts were observed. CONCLUSIONS: Our in vitro experiments suggest an interaction between SQSTM1 gene and exposure to cadmium and tobacco smoke condensates.
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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 | 0.001 | 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 | 0.000 |
| 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".