Psoriasis is a common, chronic immune-mediated systemic disease that had no effective and durable treatment. Mesenchymal stem cells (MSCs) have immunomodulatory properties. Therefore, we performed a phase 1/2a, single-arm clinical trial to evaluate the safety and efficacy of human umbilical cord-derived MSCs (UMSCs) in the treatment of psoriasis and to preliminarily explore the possible mechanisms. Seventeen patients with psoriasis were enrolled and received UMSC infusions. Adverse events, laboratory parameters, PASI, and PGA were analyzed. We did not observe obvious side effects during the treatment and 6-month follow-up. A total of 47.1% (8/17) of the psoriasis patients had at least 40% improvement in the PASI score, and 17.6% (3/17) had no sign of disease or minimal disease based on the PGA score. And the efficiency was 25% (2/8) for males and 66.7% (6/9) for females. After UMSC transplantation (UMSCT), the frequencies of Tregs and CD4⁺ memory T cells were significantly increased, and the frequencies of T helper (Th) 17 and CD4⁺ naive T cells were significantly decreased in peripheral blood (PB) of psoriasis patients. And all responders showed significant increases in Tregs and CD4⁺ memory T cells, and significant decreases in Th17 cells and serum IL-17 level after UMSCT. And baseline level of Tregs in responders were significantly lower than those in nonresponders. In conclusion, allogeneic UMSCT is safe and partially effective in psoriasis patients, and level of Tregs may be used as a potent biomarker to predict the clinical efficacy of UMSCT. Trial registration Clinical Trials NCT03765957

Background: Psoriasis is one of the most frequent inflammatory skin conditions and could be treated via tele-dermatology, provided that the current lack of reliable tools for objective severity assessments is overcome. Psoriasis Area and Severity Index (PASI) has a prominent level of subjectivity and is rarely used in real practice, although it is the most widely accepted metric for measuring psoriasis severity currently. Objective: This study aimed to develop an image–artificial intelligence (AI)–based validated system for severity assessment with the explicit intention of facilitating long-term management of patients with psoriasis. Methods: A deep learning system was trained to estimate the PASI score by using 14,096 images from 2367 patients with psoriasis. We used 1962 patients from January 2015 to April 2021 to train the model and the other 405 patients from May 2021 to July 2021 to validate it. A multiview feature enhancement block was designed to combine vision features from different perspectives to better simulate the visual diagnostic method in clinical practice. A classification header along with a regression header was simultaneously applied to generate PASI scores, and an extra cross-teacher header after these 2 headers was designed to revise their output. The mean average error (MAE) was used as the metric to evaluate the accuracy of the predicted PASI score. By making the model minimize the MAE value, the model becomes closer to the target value. Then, the proposed model was compared with 43 experienced dermatologists. Finally, the proposed model was deployed into an app named SkinTeller on the WeChat platform. Results: The proposed image-AI–based PASI-estimating model outperformed the average performance of 43 experienced dermatologists with a 33.2% performance gain in the overall PASI score. The model achieved the smallest MAE of 2.05 at 3 input images by the ablation experiment. In other words, for the task of psoriasis severity assessment, the severity score predicted by our model was close to the PASI score diagnosed by experienced dermatologists. The SkinTeller app has been used 3369 times for PASI scoring in 1497 patients from 18 hospitals, and its excellent performance was confirmed by a feedback survey of 43 dermatologist users. Conclusions: An image-AI–based psoriasis severity assessment model has been proposed to automatically calculate PASI scores in an efficient, objective, and accurate manner. The SkinTeller app may be a promising alternative for dermatologists’ accurate assessment in the real world and chronic disease self-management in patients with psoriasis.

The skin is the main barrier between the human body and the outside world, which not only plays the role of a physical barrier but also functions as the first line of defence of immunology. Langerhans cells (LCs), as dendritic cells (DC) that play an important role in the immune system, are mainly distributed in the epidermis. This review focuses on the role of these epidermal LCs in regulating skin threats (such as microorganisms, ultraviolet radiation and allergens), especially psoriasis. Since human and mouse skin DC subsets share common ontogenetic characteristics, we can further explore the role of LCs in psoriatic inflammation.

Previous studies have proven that ultraviolet (UV)-based phototherapy, including UVB or psoralen UVA (PUVA), and their combination therapies, is effective for psoriasis treatment.To compare the cli...