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Objective To establish the menstrual blood identification model based on Na?ve Bayes and multivariate logistic regression methods by using specific mRNA markers in menstrual blood detection technology combined with statistical methods, and to quantitatively distinguish menstrual blood from other body fluids. Methods Body fluids including 86 menstrual blood, 48 peripheral blood, 48 vaginal secretions, 24 semen and 24 saliva samples were collected. RNA of the samples was extracted and cDNA was obtained by reverse transcription. Five menstrual blood-specific markers including members of the matrix metalloproteinase （MMP） family MMP3, MMP7, MMP11, progestogens associated endometrial protein （PAEP） and stanniocalcin-1 （STC1） were amplified and analyzed by electrophoresis. The results were analyzed by Na?ve Bayes and multivariate logistic regression. Results The accuracy of the classification model constructed was 88.37% by Na?ve Bayes and 91.86% by multivariate logistic regression. In non-menstrual blood samples, the distinguishing accuracy of peripheral blood, saliva and semen was generally higher than 90%, while the distinguishing accuracy of vaginal secretions was lower, which were 16.67% and 33.33%, respectively. Conclusion The mRNA detection technology combined with statistical methods can be used to establish a classification and discrimination model for menstrual blood, which can distignuish the menstrual blood and other body fluids, and quantitative description of analysis results, which has a certain application value in body fluid stain identification.

According to the "White Paper on China's Intelligent Internet of Things (AIoT) 2020",with the prompt development of China's 5G network,the rapid popularization of large-capacity with low-price IoT sensor devices and the explosive growth of data,image processing is widely used in various fields of Internet of Things,such as smart city,smart transportation,smart healthcare,and other industry,etc.In these research areas,researchers usually ignore the actual problems in the data collection process,for instance,data degradation caused by time changes:seasonal shifting,diurnal variation,weather changes,and noise problems caused by spatial changes:object superposition,blur,and partial occlusion.Among those problems,the weather pro-blems represented by rainy days are the most challenging and common.Therefore,this paper systematically investigates the actual problems in the data collection process above,classifies and summarizes the image rain-removal algorithms under complex weather conditions.At the same time,regarding the compute-intensive execution of such algorithms,we utilize the Amazon EC2 cloud instance G4 and P3 series to quantitatively evaluate the processing time and effect of various reviewed rain removal algorithms.Finally,we illustrate the characteristics of various rain removal algorithms and the latest trends in Cloud-IoT applications.

Objective To explore the antioxidant effect and mechanism of kaempferol(KP), a component of Vernonia anthelmintica (L.) Willd., in human immortalized keratinocytes (HaCaT). Methods Using selective reaction/multiple response monitoring technique for quantitative analysis of the flavonoids in the seeds of Vernonia anthelmintica (L.) Willd.. HaCaT cells were divided into control group, model group(HaCaT cells were treated with AAPH to establish the oxidative stress model), low-, middle- and high-dose KP intervention groups.CCK-8 assay for proliferation, RT-qPCR was used for checking the expression of Nrf2, HO-1, NQO1, GCLC and GCLM mRNA, Western blot was used for checking the expression of Nrf2 protein. Results 1)The content of total flavonoids of Vernonia anthelmintica (L.) Willd.. was 0.97 g/100 g, and a total of 36 flavonoid compounds were quantified, the content of KP was 62.96 ng/100 g. 2)The optimum concentration of AAPH for constructing oxidative stress model was 25 mmol/L, and when the concentration of KP was 0-40 μmol/L, no obvious cytotoxicity was found. 3)Low-dose KP increased the expression of Nrf2, HO-1 and GCLC mRNA. Among them, the expression of HO-1 changed most significantly. 4)KP increased the expression of Nrf2 protein in a concentration-dependent manner. Conclusions A component of Vernonia anthelmintica (L.) Willd., reduces the oxidative stress injury of human keratinocytes, the mechanism might be related to the up-regulation of Nrf2 expression.

Abstract Background This study aimed to explore the effects of (body mass index) BMI on health related quality of life (HRQoL) among the elderly in Jiangsu, China. Methods A total of 10,257 community dwelling elderly (≥60 years old) were enrolled in a cross-sectional study. HRQoL was measured via the Eq-5d-3 L. Chi-square tests and one-way ANOVA analyses were used to compare the frequencies and scores of Eq-5d responses among different BMI groups (defined as “underweight”, “normal weight”, “overweight” and “obese”). Logistic regression analyses were conducted to examine the associations between BMI and HRQoL. Results Among the subjects, the proportion of “normal weight”, “underweight”, “overweight” and “obese” were 66.0, 8.3, 23.1, and 2.6%, respectively. The score of the Eq-5d index among total participants was 0.8036 and the Visual Analog Scale (VAS) score was 75.47. For both the responses frequency and scores of Eq-5d-3 L, there were significant differences among BMI groups (P