Prevention of Chromium-Induced Radiation-Chemical Oncogenesis, Including in Offspring, in an Experimental Model: A Systematic Review
Bibliographic record
Abstract
Radiation and chemical-induced cancer are of increasing concern as the various activities of humans continuously elevate the levels of radiation and toxic chemicals in the environment. The prevention of this incidence using alternative medicines-phytopreparations, therefore, becomes pertinent as conventional approaches tend to produce various unwanted side effects. To achieve this, there is a need to understand the various mechanisms of action through which phytopreparations exhibit their protective effects. This systematic review, therefore, aims to explore the mechanism of action of various phytopreparations in the prevention of induced radiation and chemical (chromium) cancer. A systematic review approach following the stipulated guidelines by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was used to identify research papers published between 2015 and 2025. Four databases, namely Europe PubMed Central (PMC), PubMed, Springer Open, and Wiley Online Library were used to search for related open access papers. A total of 621 research papers were reviewed for suitability to the review objective; however, only five papers met the inclusion criteria, and an additional two papers were sourced from ResearchGate. Thus, a total of seven papers were finally included in the analysis. This review highlights the mechanisms of action of various phytopreparations in the prevention of radiation and chromium-induced cancer. The major mechanisms of phytopreparations' action in the prevention of induced radiation and chromium oncogenesis majorly involve regulating pro and anti-inflammatory cytokines, improving cell-to-cell communication, and preventing damage to DNA structure.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".