Synergistic Toxicity of Pollutant and Ultraviolet Exposure from a Mitochondrial Perspective
Bibliographic record
Abstract
Ultraviolet (UV) exposure and atmospheric pollution are both independently implicated in skin diseases such as cancer and premature aging. UVA wavelengths, which penetrate in the deep layers of the skin dermis, exert their toxicity mainly through chromophore photosensitization reactions. Benzo[a]pyrene (BaP), the most abundant polycyclic aromatic hydrocarbon originating from the incomplete combustion of organic matter, could act as a chromophore and absorb UVA. We and other groups have previously shown that BaP and UVA synergize their toxicity in skin cells, which leads to important oxidation. Even if mitochondria alterations have been related to premature skin aging and other skin disorders, no studies have focused on the synergy between UV exposure and pollution on mitochondria. Our study aims to investigate the combined effect of UVA and BaP specifically on mitochondria in order to assess the effect on mitochondrial membranes and the consequences on mitochondrial activity. We show that BaP has a strong affinity for mitochondria and that this affinity leads to an important induction of lipid peroxidation and membrane disruption when exposed to UVA. Co-exposure to UVA and BaP synergizes their toxicity to negatively impact mitochondrial membrane potential, mitochondrial metabolism and the mitochondrial network. Altogether, our results highlight the implication of mitochondria in the synergistic toxicity of pollution and UV exposure and the potential of this toxicity on skin integrity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".