The Toxin of the Year: Airborne PM <sub>2.5</sub>
Bibliographic record
Abstract
Abstract: Particulate matter (PM) with a diameter of 2.5 µm or smaller (PM 2.5 ) has emerged as a critical environmental toxin affecting skin health. In light of its widespread and often underestimated impact, we designated PM 2.5 as the “toxin of the year.” Although PM 2.5 primarily affects the respiratory system, growing evidence indicates that it also plays a significant role in cutaneous health. Exposure to PM 2.5 can lead to oxidative stress, inflammation, and impairment of the skin barrier, particularly in individuals with preexisting skin conditions. An increasing number of studies highlight an association between PM 2.5 exposure and the prevalence and exacerbation of inflammatory skin diseases such as atopic dermatitis and psoriasis. This review therefore focuses on the fundamental mechanisms, including key molecular pathways, by which PM 2.5 contributes to skin damage, with an emphasis on its role in the onset and progression of inflammatory skin diseases, as evidenced by population-based studies. A deeper understanding of these processes is crucial for guiding the development of targeted prevention and therapeutic strategies in response to raising environmental pollution. Giving the growing body of evidence, this review aims to consolidate current knowledge and highlight critical gaps in our understanding of PM 2.5 impact on inflammatory 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".