Tanshinone I Ameliorates Psoriasis-Like Dermatitis by Suppressing Inflammation and Regulating Keratinocyte Differentiation
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Bibliographic record
Abstract
Background: Psoriasis is an immune-related inflammatory systemic condition characterized by dysregulated keratinocyte proliferation and chronic inflammation. Tanshinone I (Tan-I) has recently been discovered to have immunomodulatory properties, but its role and mechanisms in treating psoriasis remain unclear. Objective: To evaluate the efficacy of Tan-I in the treatment of psoriasis and to determine the mechanisms involved. Methods: An imiquimod (IMQ)-induced psoriasis-like mouse model was treated topically with Tan-I (7.5 mg/kg/d) or a vehicle. Disease severity was evaluated using the Psoriasis Area and Severity Index (PASI), and histological changes were assessed via H&E staining and Ki67 immunofluorescence. TNF-α-stimulated HaCaT keratinocytes were used for in vitro analyses, including apoptosis, cell cycle progression, and inflammatory gene expression via RT-qPCR. RNA sequencing (RNA-seq) was performed to investigate Tan-I's mechanisms in vivo and in vitro, while keratin expression was analyzed by immunofluorescence and Western blot. Results: Tan-I treatment significantly alleviated psoriasis-like lesions in the IMQ mouse model, improving skin pathology and reducing Ki67-positive cells. RNA-seq revealed that Tan-I modulated immune pathways, keratinocyte differentiation, and barrier function. In TNF-α-stimulated HaCaT cells, Tan-I induced G1-phase cell cycle arrest, reduced apoptosis, and suppressed inflammatory gene expression. RNA-seq further showed that Tan-I normalized cell cycle signaling and apoptosis pathways disrupted by TNF-α. Additionally, Tan-I restored keratin expression patterns, increasing K1 and decreasing K6 and K17 levels in both mouse skin and HaCaT cells. Conclusion: Tan-I is a promising therapeutic candidate for psoriasis, effectively mitigating inflammation, normalizing keratinocyte differentiation, and inhibiting abnormal keratinocyte apoptosis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it