Transcutaneous delivery of protein tyrosine phosphatase ameliorates inflammatory skin diseases
Bibliographic record
Abstract
Abstract Transcutaneous delivery of therapeutic drugs has many advantages of topical treatment over the systemic administration for inflammatory skin diseases such as atopic dermatitis or psoriasis. However, the greatest challenge for transcutaneous drug delivery limits clinical applications due to the skin tissue barrier. Here, we identified a novel transcutaneous delivery peptide, AP, from human neuronal adhesion protein (Astrotactin 1) which could deliver a macromolecule such as a protein into skin tissue. AP-conjugated EGFP protein exhibited significantly higher intracellular transduction efficacy in HaCaT (keratinocyte), NIH3T3 (fibroblast) and Jurkat (T cell) cells compared with control proteins. In addition, AP-EGFP and –dTomato protein was efficiently localized into the dermis as well as epidermis in mouse skin tissue following transcutaneous administration. Next, we generated AP-rPTP protein, which is chimeric protein of AP and phosphatase domain of TC-PTP. AP-rPTP inhibited phosphorylation of STAT1, 3, 5 in mouse splenocytes and T cells and reduced cytokines production by activated splenocyets. To confirm its in vivo relevance, we transcutaneously applied it to dermatitis mouse models. Multiple skin patch administrations of AP-rPTP protein significantly ameliorated tissue inflammation in oxazolone-induced contact dermatitis and imiquimod-induced psoriasis mouse model. Our results collectively demonstrate that AP is a novel human derived transcutaneous delivery peptide and AP-rPTP protein could be a therapeutic biomolecule in inflammatory skin diseases such as allergic dermatitis and psoriasis.
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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) | 0.001 | 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".