Bibliographic record
Abstract
The acquired depigmenting disorder of vitiligo affects an estimated 1% of the world population and constitutes one of the commonest dermatoses. Although essentially asymptomatic, the psychosocial impact of vitiligo can be severe. The cause of vitiligo remains enigmatic, hampering efforts at successful therapy. The underlying pathogenesis of the pigment loss has, however, been clarified to some extent in recent years, offering the prospect of effective treatment, accurate prognosis and rational preventative strategies. Vitiligo occurs when functioning melanocytes disappear from the epidermis. A single dominant pathway is unlikely to account for all cases of melanocyte loss in vitiligo; rather, it is the result of complex interactions of biochemical, environmental and immunological events, in a permissive genetic milieu. ROS (reactive oxygen species) and H2O2 in excess can damage biological processes, and this situation has been documented in active vitiligo skin. Tyrosinase activity is impaired by excess H2O2 through oxidation of methionine residues in this key melanogenic enzyme. Mechanisms for repairing this oxidant damage are also damaged by H2O2, compounding the effect. Numerous proteins and peptides, in addition to tyrosinase, are similarly affected. It is possible that oxidant stress is the principal cause of vitiligo. However, there is also ample evidence of immunological phenomena in vitiligo, particularly in established chronic and progressive disease. Both innate and adaptive arms of the immune system are involved, with a dominant role for T-cells. Sensitized CD8+ T-cells are targeted to melanocyte differentiation antigens and destroy melanocytes either as the primary event in vitiligo or as a secondary promotive consequence. There is speculation on the interplay, if any, between ROS and the immune system in the pathogenesis of vitiligo. The present review focuses on the scientific evidence linking alterations in ROS and/or T-cells to vitiligo.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".