Objective To make a survey on common cosmetic allergens, and to provide epidemiological data and clinical evidence for cosmetic allergy. Methods Patch test was performed by using 49cosmetic allergens from a European cosmetic series and 5 Chinese standard screening allergens on 89patients with suspected cosmetic allergic contact dermatitis. Test results were determined according to the International Contact Dermatitis Research Group (ICDRG) recommendation. Results Of the 89 patients, 61(68.5%) showed positive reactions to one or more cosmetic allergens. The most common allergens were fragrances (33.7%), followed by preservatives (30.3%), para-phenylenediamine (25.8%) and amerchol L 101(10.1%). Conclusion Fragrances, preservatives, para-phenylenediamine and amerchol L 101 are dominant causative allergens in patients with cosmetic allergic contact dermatitis.

Objective:To explore a blood cell recognition algorithm that combined threshold image segmentation with deep learning in conventional image processing,so as to be used in automatic recognition and classification of blood cell smears.Method:Global threshold segmentation was used to extract blood cells from blood cell smears and to store them separately.The segmented cell images were manually labeled and classified so as to reduce the requirements for hardware in subsequent processing.The deep learning training of labeled images was on the basis of the GoogLeNet pre training model,which could generate deep learning model of automatic recognition that could be used in the images of blood cell smear.The trained model could be used to evaluate the test set,and generate confusion matrix and area under curve(AUC)value of receiver operating characteristic(ROC)curve.Result:This preprocessing has been proven that it can improve the training of deep learning model,and the subsequent recognition speed of using model can exceed over 10 times.Using the online image dataset Raabin WBC Data of blood cell smear,the accuracy of model training reached to 93.06%.Both of them obtained favorable results.Conclusion:The blood cell recognition algorithm based on the combination of threshold image segmentation and deep learning can greatly improve the efficiency of recognition and classification of blood cells,and ensure accuracy of the diagnosis of blood related diseases.

Objective To establish the drug use evaluation(DUE)criteria of recombinant human prourokinase(rhPro-UK),and to provide reference for the rational clinical application of rhPro-UK.Methods Based on the drug instructions of rhPro-UK,DUE standard rules were established by referring to relevant guidelines,expert consensus,authoritative literature and expert consultation.The medical records of hospitalized patients treated with rhPro-UK from January 2019 to May 2022 in Xilin Gol League Central Hospital were evaluated by retrospective investigation.The effectiveness of rhPro-UK was evaluated based on clinical outcome,and its safety was evaluated based on the incidence and severity of adverse reactions.Results A total of 230 cases were included,and 4 cases fully met the evaluation criteria(medication indication,medication process,medication results),accounting for 1.74％.There were 226 patients(98.26％)with irrational drug use,mainly manifested in two aspects of drug indication and drug process(administration mode and dosage).Treatment was effective in 221 patients,with an overall effective rate of 96.09％;139 patients experienced adverse reactions,with an incidence rate of 60.43％.Conclusion The clinical use of rhPro-UK in our hospital is irrational in the indication of medication and the process of medication,and the establishment of the DUE standard rules of rhPro-UK can provide a reference to standardize the clinical application of rhPro-UK and promote its rational use.

Objective: To investigate the efficacy and safety of the recombinant human tumor necrosis factor receptor Ⅱ-IgG Fc fusion protein (rhTNFR: Fc, etanercept) for the treatment of occupational medicamentosa-like dermatitis induced by trichloroethylene (OMLDT) . Methods: In September 2011 to February 2016, 12 patients with OMLDT were treated with etanercept 25 mg, subcutaneous injection, twice per week, doubling of first dose. The course of treatment was 6 weeks. The drug eruption area and severity index (DASI) score, the proportion of patients achieving a 50%, 75% and 90% reduction in DASI (DASI50, DASI75, DASI90) and the serum level of TNF-α were used to assess the efficacy at different times. Adverse reactions were also recorded and evaluated. The results were statistically analyzed by nonparametric Friedman test and repetitive measurement ANOVA using the software SPSS19.0. Results: After 4 weeks treatment, the DASI score decreased form 56.33±7.02 to 0.50±0.91 (P<0.01) . The DASI50, DASI75 and DASI90 were all increased to 12 (100%) . The serum level of TNF-α decreased form (43.74±41.62) pg/ml to (3.03±0.47) pg/ml (P<0.01) . Statistically significant difference was observed from the above indexes. There were no adverse reactions in clinical application. Conclusion Recombinant human tumor necrosis factor receptor Ⅱ-IgG Fc fusion protein may be a safe and effective drug in the treatment of OMLDT.