Anti-inflammatory role of IDO and tryptophan metabolites
Bibliographic record
Abstract
Inflammation is essential to the establishment of homeostasis following injury and inflammatory cell and the cytokine network associate with tissue repair. However, sometimes inflammation can cause further inflammation; it can become self-perpetuating. One of the many possibilities of prolonged secretion of cytokines and growth factor is autoimmunity and delay in wound closure. The current anti-inflammatory treatment modalities vary however their adverse effects are common. Here we asked the question of whether Kynurenine (Kyn), one of the tryptophan (Trp) metabolite, could modulate the inflammation by altering the profile of the key pro-inflammatory cytokines as well as the proliferation of immune cells. We showed that Kyn treatment significantly reduced some pro-inflammatory cytokines and chemokines such as IL-17, IL-2, CXCL-9 and CXCL-10 in ConA⁺ Kyn-treated splenocytes. To validate our findings in a wound healing model, we also showed that topical application of Kyn cream resulted in fewer infiltration of CD3⁺ T cells at wound site. Further, in this study we used kynurenic acid (KynA) instead of Kyn as KynA is the end product and safer metabolites in the kynurenine pathway. The emphasis was given in evaluating the effect of KynA on expression of IL-17/IL-23 axis which has recently been identified to be very important in the immunopathogenesis of autoimmune diseases and inflammation such as psoriasis. Our findings have shown that KynA can modulate the frequency of IL-23 and IL-17 by DCs and CD4⁺ cells. Moreover, we showed that KynA suppresses the production of IL-23 in DCs through GPCR35 activation. We then evaluated the therapeutic use of intra-lesional injection of IDO-expressing fibroblasts, as a source of Kyn and KynA production in psoriasis, which is one of the most common recurrent chronic inflammatory diseases of the skin. The findings of this work demonstrated that IDO-expressing cells significantly improved thickness, erythema, and scaling scores in skin psoriatic like condition. Moreover, IDO-expressing fibroblasts reduce infiltration of IL-17⁺ CD4⁺, IL-17⁺ γδ⁺ T cells, IL-23⁺-activated dendritic cells and granulocytes in skin psoriatic like condition. The findings presented in this thesis collectively prove the potent local immunosuppressive activity of IDO-expressing dermal fibroblast and tryptophan metabolites in skin inflammatory conditions.
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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) | 0.002 | 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".