Image-based remote evaluation of PASI scores with psoriasis by the YOLO-v4 algorithm.

As a chronic relapsing disease, psoriasis is characterized by widespread skin lesions. The Psoriasis Area and Severity Index (PASI) is the most frequently utilized tool for evaluating the severity of psoriasis in clinical practice. Nevertheless, long-term monitoring and precise evaluation pose difficulties for dermatologists and patients, which is time-consuming, subjective and prone to evaluation bias. To develop a deep learning system with high accuracy and speed to assist PASI evaluation, we collected 2657 high-quality images from 1486 psoriasis patients, and images were segmented and annotated. Then, we utilized the YOLO-v4 algorithm to establish the model via four modules, we also conducted a human-computer comparison through quadratic weighted Kappa (QWK) coefficients and intra-class correlation coefficients (ICC). The YOLO-v4 algorithm was selected for model training and optimization compared with the YOLOv3, RetinaNet, EfficientDet and Faster_rcnn. The model evaluation results of mean average precision (mAP) for various lesion features were as follows: erythema, mAP = 0.903; scale, mAP = 0.908; and induration, mAP = 0.882. In addition, the results of human-computer comparison also showed a median consistency for the skin lesion severity and an excellent consistency for the area and PASI score. Finally, an intelligent PASI app was established for remote disease assessment and course management, with a pleasurable agreement with dermatologists. Taken together, we proposed an intelligent PASI app based on the image YOLO-v4 algorithm that can assist dermatologists in long-term and objective PASI scoring, shedding light on similar clinical assessments that can be assisted by computers in a time-saving and objective manner.

Efficacy and Safety of Topical Traditional Chinese Medicine Monotherapy in Persistent HPV Infection Among Males.

Objective: We studied the efficacy and safety of traditional Chinese medicine paiteling treatment of persistent human papillomavirus (HPV) infection in males. Methods: The study included 159 male patients with persistent HPV infection between January 2018 and July 2022, and categorized into the treatment group (n = 96) and control group (n = 63) based on the treatment. The treatment group was externally treated with paiteling diluent for 4 consecutive days and then stopped for 3 days. The total course of treatment was one month. The treatment group underwent a second test six months after treatment. The control group did not receive any therapy and underwent a second test in the seventh month. Results: 19 of the 159 patients were lost during the 6-month follow-up period, leaving 140 patients. The male HPV infection peaks between the ages of 26-35 years 73(52.14%), and its prevalence decrease with age. 84 (60.0%) were single type infections, and 22 (15.71%) had at least 3 types infections. There were 76 (54.29%) patients with the high-risk types, 34 (24.29%) with the low-risk types, and 30 (21.43%) with the mixed types. After 6 months, complete negative conversion rates and negative conversion rates were 74.7% and 90.8% in the treatment group respectively, compared to the control group (P < .01). A comparison of negative conversion rates among different types reveals that 16 type (89.5%) and 6 type (92.3%) had statistical differences, (P < .01) and (P < .05) respectively. Multivariate analysis revealed that the vaccine status of sexual partners was a protective factor (OR = 0.050-0.848) and multi-type infection was a risk factor (OR = 1.807-22.527) for the curative effect. Conclusion: Paiteling is convenient, safe, and effective for the treatment of persistent HPV infection in males.

Augmentation of danusertib's anticancer activity against melanoma by blockage of autophagy.

Previous evidence has shown that the increased expression of aurora kinase is closely related to melanoma progression and is an important therapeutic target in melanoma. Danusertib is an inhibitor of aurora kinase, and recent studies have shown that danusertib treatment induces autophagy in several types of cancer. Interestingly, autophagy plays a dual function in cancer as a pro-survival and anti-survival factor. In this study, we investigated the role of danusertib on the induction of autophagy in melanoma and determined the impact of autophagy induction on its anticancer activity against melanoma. Our results showed that danusertib can significantly inhibit melanoma growth by inducing cell cycle arrest and apoptosis. In addition, we demonstrated that danusertib treatment significantly inhibits the oncogenic Akt/mTOR signaling pathway and induces autophagy in melanoma cells. Furthermore, we identified that the inhibition of autophagy can enhance the inhibitory effects of danusertib on melanoma growth. Thus, the induction of autophagy by danusertib appears to be a survival mechanism in melanoma cells that may counteract its anticancer effects. These findings suggest a novel strategy to enhance the anticancer efficacy of danusertib in melanoma by blocking autophagy.

Alisertib promotes apoptosis and autophagy in melanoma through p38 MAPK-mediated aurora a signaling.

We investigated the efficacy of Alisertib (ALS), a selective Aurora kinase A (AURKA) inhibitor, in melanoma. We found that ALS exerts anti-proliferative, pro-apoptotic, and pro-autophagic effects on A375 and skmel-5 melanoma cells by inhibiting p38 MAPK signaling. SB202190, a p38 MAPK-selective inhibitor, enhanced ALS-induced apoptosis and autophagy in both cell lines. ALS induced cell cycle arrest in melanoma cells through activation of the p53/p21/cyclin B1 pathway. Knockdown of p38 MAPK enhanced ALS-induced apoptosis and reduced ALS-induced autophagy. Inhibition of autophagy sensitized melanoma cells to ALS-induced apoptosis. These data indicate ALS is a potential therapeutic agent for melanoma.