The etiology of chronic urticaria (CU) remains elusive. Histamine-releasing factor (HRF) is reported to have a proinflammatory role in asthma and immediate hypersensitivity of the skin. The aim of this study was to examine the role of HRF in the pathogenesis of CU. Forty patients with CU were enrolled and their serum HRF concentrations were determined by ELISA. The results demonstrated that the concentrations of HRF and HRF-reactive IgE in the CU group were significantly higher than those in the control group, and there was a significant linear correlation between HRF and HRF-reactive IgE concentrations (r = 0.859, p < 0.001) in CU patients. Additionally, the HRF-reactive IgE concentration was significantly correlated with the disease activity (r = 0.693, p < 0.0001). HRF and HRF-reactive IgE alone failed to activate LAD2 cells. After being primed by the patient sera with the highest IgE concentrations and stimulated by HRF, β-hexosaminidase can be released from LAD2 cells. Our findings suggest that the synergistic actions of HRF and HRF-reactive IgE may play important roles in the pathogenesis of CU.
Objective The second messenger inositol triphosphate (IP3) is involved in signal transduction in multiple cell types. We evaluated the effects of high-dose levocetirizine on chronic spontaneous urticaria (CSU) and examined the significance of serum IP3 level in the pathogenesis of CSU. Methods Fifteen patients with refractory CSU were given oral levocetirizine at a dose of 15 mg once daily for 7 days, and treatment efficacy was determined using the Urticaria Activity Score and by evaluating wheal-and-erythema reactions and itching. The serum concentration of IP3 at specific time points was determined by enzyme-linked immunosorbent assay. Results The mean serum concentration of IP3 was 43.54 ± 41.97 pg/mL prior to treatment, 18.40 ± 17.53 pg/mL after treatment, and 1.31 ± 0.92 pg/mL in a healthy control group. The mean concentration of IP3 was significantly higher before treatment than after treatment, and the level of IP3 in the patient group before and after treatment was significantly higher than that in the control group. Conclusion High-dose levocetirizine was shown to be effective in the treatment of CSU. The level of serum IP3 was positively correlated with CSU activity, indicating that IP3 may play an important role in the pathogenesis of this condition.
The estimated number of outpatients with skin diseases in China is ~200 million per year, while the dermatologists are insufficient and the doctor-patient ratio remains low, which causes fewer patients receive effective diagnosis. Compared with others, the diagnosis of skin diseases, which is less reliant on laboratory tests, imaging and pathology, needs the assistance of large hardware devices. By contrast, dermatologic diagnosis requires a combination of visual inspection and interrogation frequently which is exactly what Artificial Intelligence (AI) specialises in — Computer Vision (CV), Natural Language Processing (NLP) and Speech Recognition (SR). This allows a simple image capturing tool embedded with an AI model to perform dermatological diagnosis at the primary level. Hence, based on the dataset, which from Asian, with more than 200,000 images and 220,000 medical records, we explored an AI skin diseases diagnosis model---DIET-AI to diagnose 31 skin diseases, covering the majority of common skin diseases. Ranging from 1st September to 1st December 2021, we prospectively collected case information from 15 hospitals in 7 provinces in China, using mobile devices to collect images and medical records of 6043 cases. Then, we compared the performance of the DIET-AI with 6 doctors of different seniority in the prospective clinical dataset, concluding the average performance of the DIET-AI in 31 diseases is no less than that of all different seniority doctors. By comparing the area under curve (AUC), sensitivity and specificity, we demonstrate that DIET-AI model is effective under the clinical scenario. It is further validated under more complex clinical scenarios, providing references for exploring the feasibility and performance evaluation of DIET-AI in clinical use afterwards
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