Oxidative Stress and DNA Damages Induced by Occupational Exposure to Asbestos: A Systematic Review
Bibliographic record
Abstract
Background: Asbestos is one of the most important environmental and occupational carcinogens. Nevertheless, the mechanisms by which asbestos fiber exposure causes chronic diseases are not fully understood. We performed the first systematic review on the epidemiological evidence to examine the association between occupational exposure to asbestos and oxidative stress and DNA damage. Methods: In this systematic review study, the PubMed and Scopus databases were searched for English-language publications. Eleven cross-sectional studies were included in the systematic review. A literature search was conducted by the main keywords including "Asbestos", "crocidolite", "chrysotile", "amphibole", "amosite", "Oxidative Stress", "DNA Damage", and "DNA injury". To evaluate the quality of studies, the "Newcastle-Ottawa Quality Assessment Scale" (NOS) was used. Results: Overall, 1235 articles were achieved by searching in databases. Finally, by considering the inclusion, and exclusion criteria, 11 articles were conducted for this study. These studies were published between 1986 and 2020. Oxidative stress and DNA damage can occur in exposure to asbestos. Among various biomarkers, 8-OHdG is the best. The analysis of 8-oxodG in asbestos workers can help identify subjects with a higher level of genotoxic damage. Conclusion: This systematic review suggests that oxidative stress and DNA damage are two main outputs of asbestos exposure. Therefore, oxidative stress and DNA damage biomarkers can be used for identifying subjects at higher risk of cancer. These findings support policy initiatives aimed at detecting and eliminating asbestos fiber exposure and preventing potential health hazards in occupational settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".