Evidence-Based Utility of Adjunct Antioxidant Supplementation for the Prevention and Treatment of Dermatologic Diseases: A Comprehensive Systematic Review
Bibliographic record
Abstract
Skin conditions are a significant cause of fatal and nonfatal disease burdens globally, ranging from mild irritations to debilitating diseases. Oxidative stress, which is an imbalance between reactive oxygen species and the cells' ability to repair damage, is implicated in various skin diseases. Antioxidants have been studied for their potential benefits in dermatologic health, but the evidence is limited and conflicting. Herein, we conducted a systematic review of controlled trials, meta-analyses, and Cochrane review articles to evaluate the current evidence on the utility of antioxidant supplementation for adjunct prevention and treatment of skin disease and to provide a comprehensive assessment of their role in promoting dermatologic health. The Cochrane Library, PubMed, EMBASE, and Epistemonikos databases were queried. Eligibility criteria included (1) primary focus on nanoparticle utility for skin cancer; (2) includes measurable outcomes data with robust comparators; (3) includes a number of human subjects or cell-line types, where applicable; (4) English language; and (5) archived as full-text journal articles. A total of 55 articles met the eligibility criteria for the present review. Qualitative analysis revealed that topical and oral antioxidant supplementation has demonstrated preliminary efficacy in reducing sunburns, depigmentation, and photoaging. Dietary exogenous antioxidants (namely vitamins A, C, and E) have shown chemopreventive effects against skin cancer. Antioxidant supplementation has also shown efficacy in treating non-cancer dermatoses, including rosacea, psoriasis, atopic dermatitis, and acne vulgaris. While further studies are needed to validate these findings on a larger scale, antioxidant supplementation holds promise for improving skin health and preventing skin diseases.
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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 | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".