AhR signaling in skin-resident CD207 <sup>+</sup> cells is involved in UV-B-induced amelioration of neuroinflammation
Bibliographic record
Abstract
Environmental stimuli, including the exposure to ultraviolet (UV)-B light, are known to play a role in the modulation of immune-mediated mechanisms in multiple sclerosis (MS). In experimental autoimmune encephalomyelitis (EAE), we have shown that UV-B irradiation ameliorates disease outcome by regulatory T cells (Treg) expansion. Moreover, the UV-B-mediated induction of Treg numbers was also observed in MS. The aryl hydrocarbon receptor (AhR) can be activated by environmental factors including UV-B-induced photoproducts of tryptophan. Thus, we investigated the role of AhR during the transmission of UV-B irradiation. Therefore, wild-type (WT) and AhR-deficient mice (AhR –/– ) were irradiated with UV-B light and immunized with myelin oligodendrocyte glycoprotein (MOG)-peptide. In WT mice it was shown that UV-B irradiation reduces EAE symptoms by Treg expansion. This effect was abrogated in animals with AhR deficiency. To better understand the underlying mechanisms of AhR regulation, we used mice with a deletion of AhR specifically in different subsets of antigen-presenting cells (APC) that have been shown to mediate the expansion of Treg. Interestingly, we could show that the AhR activation in murine cutaneous APC was sufficient to switch APC from a stimulatory into a regulatory phenotype, and moreover, responsible for APC cell maturation and migration into regional lymph nodes. Thus, our data indicate that AhR activation in APC might be required for UV-B-mediated immunosuppression during MOG-induced EAE. Hence, activation of AHR in tissue-resident APC, potentially by low-dose UV-B irradiation, might be beneficial as an adjuvant treatment in inflammatory or degenerative diseases of the central nervous system.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".