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Shen, Xing-Rong,Feng, Rui,Chai, Jing,Cheng, Jing,Wang, De-Bin Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.22
Large scale secular registry or surveillance systems have been accumulating vast data that allow mathematical modeling of cancer incidence and mortality rates. Most contemporary models in this regard use time series and APC (age-period-cohort) methods and focus primarily on predicting or analyzing cancer epidemiology with little attention being paid to implications for designing cancer registry, surveillance or evaluation initiatives. This research models age-specific cancer incidence rates using logistic growth equations and explores their performance under different scenarios of data completeness in the hope of deriving clues for reshaping relevant data collection. The study used China Cancer Registry Report 2012 as the data source. It employed 3-parameter logistic growth equations and modeled the age-specific incidence rates of all and the top 10 cancers presented in the registry report. The study performed 3 types of modeling, namely full age-span by fitting, multiple 5-year-segment fitting and single-segment fitting. Measurement of model performance adopted adjusted goodness of fit that combines sum of squred residuals and relative errors. Both model simulation and performance evalation utilized self-developed algorithms programed using C# languade and MS Visual Studio 2008. For models built upon full age-span data, predicted age-specific cancer incidence rates fitted very well with observed values for most (except cervical and breast) cancers with estimated goodness of fit (Rs) being over 0.96. When a given cancer is concerned, the R valuae of the logistic growth model derived using observed data from urban residents was greater than or at least equal to that of the same model built on data from rural people. For models based on multiple-5-year-segment data, the Rs remained fairly high (over 0.89) until 3-fourths of the data segments were excluded. For models using a fixed length single-segment of observed data, the older the age covered by the corresponding data segment, the higher the resulting Rs. Logistic growth models describe age-specific incidence rates perfectly for most cancers and may be used to inform data collection for purposes of monitoring and analyzing cancer epidemic. Helped by appropriate logistic growth equations, the work vomume of contemporary data collection, e.g., cancer registry and surveilance systems, may be reduced substantially.
Thermal-balanced integral model for pyrolysis and ignition of wood
Rui Xiao,Dekui Shen,Mengxiang Fang,Wanki Chow 한국화학공학회 2013 Korean Journal of Chemical Engineering Vol.30 No.1
The pyrolysis and ignition of wood is of great importance to understand the initial stage of combustion,helping control the occurrence and spread of unwanted building and forestry fires. The development of a thermal-balanced model is introduced for examining the analytical relationship between the ignition time and external heat flux. The critical heat flux, one of the important fire-retardant characteristics of combustible solid, is determined from a correlation study between the ignition time and external heat flux. One of the thermal-balanced integral models, considering the effect of surface heat losses, average absorptivity and moisture content, is employed to give the prediction of surface temperature rise, ignition time and ignition temperature of the Aspen. The results show that the model readily and satisfactorily predicts ignition temperature and ignition time of wood with different moisture contents.
Rui Li,Jiping Sheng,Lin Shen 한국식물병리학회 2020 Plant Pathology Journal Vol.36 No.2
β-Aminobutyric acid (BABA) has consistently been reported to enhance plant immunity. However, the specific mechanisms and downstream components that mediate this resistance are not yet agreed upon. Nitric oxide (NO) is an important signal molecule involved in a diverse range of physiological processes, and whether NO is involved in BABA-induced resistance is interest- ing. In this study, treatment with BABA significantly increased NO accumulation and reduced the sensitivity to Botrytis cinerea in tomato plants. BABA treatment reduced physical signs of infection and increased both the transcription of key defense marker genes and the activity of defensive enzymes. Interestingly, compared to treatment with BABA alone, treatment with BABA plus cPTIO (NO specific scavenger) not only signifi- cantly reduced NO accumulation, but also increased disease incidence and lesion area. These results sug- gest that NO accumulation plays an important role in BABA-induced resistance against B. cinerea in tomato plants.
Rui Deng,Shi-min Wang,Tao Yin,Ting-hong Ye,Guo-bo Shen, Ling Li,Jing-yi Zhao,Ya-xiong Sang,Xiao-gang Duan,Yu-Quan Wei 한국유방암학회 2014 Journal of breast cancer Vol.17 No.1
Purpose: The universal organic solvent dimethyl sulfoxide (DMSO)can be used as a differentiation inducer of many cancer cells andhas been widely used as a solvent in laboratories. However, itseffects on breast cancer cells are not well understood. The aimof this study is to investigate the effect and associated mechanismsof DMSO on mouse breast cancer. Methods: We appliedDMSO to observe the effect on tumors in a mouse breast cancermodel. Tumor-associated macrophages (TAMs) were tested byflow cytometry. Ex vivo tumor microenvironment was imitated by4T1 cultured cell conditioned medium. Enzyme-linked immunosorbentassays were performed to detect interleukin (IL)-10 andIL-12 expression in medium. To investigate the cytotoxicity ofDMSO on TAMs, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazoliumbromide (MTT) assays were performed. Results: We foundthat DMSO produced tumor retardation when injected into mouseperitoneal cavities in a certain concentration range (0.5–1.0 mg/g). Furthermore, as detected by flow cytometry, TAM subtypeswere found to be transformed. We further imitated a tumor microenvironmentin vitro by using 4T1 cultured cell conditionedmedium. Similarly, by using low concentration DMSO (1.0%–2.0% v/v), TAMs were induced to polarize to the classically activatedmacrophage (M1-type) and inhibited from polarizing intothe alternatively activated macrophage (M2-type) in the conditionedmedium. IL-10 expression in tumors was reduced, whileIL-12 was increased compared with the control. Furthermore, wereported that 2.0% (v/v) DMSO could lead to cytotoxicity in peritonealmacrophages after 48 hours in MTT assays. Conclusion:Our findings suggest that DMSO could exert antitumor effects in4T1 cancer-bearing mice by reversing TAM orientation and polarizationfrom M2- to M1-type TAMs. These data may providenovel insight into studying breast cancer immunotherapy.
Shen, Xing-Rong,Chai, Jing,Feng, Rui,Liu, Tong-Zhu,Tong, Gui-Xian,Cheng, Jing,Li, Kai-Chun,Xie, Shao-Yu,Shi, Yong,Wang, De-Bin Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.24
The big gap between efficacy of population level prevention and expectations due to heterogeneity and complexity of cancer etiologic factors calls for selective yet personalized interventions based on effective risk assessment. This paper documents our research protocol aimed at refining and validating a two-stage and web-based cancer risk assessment tool, from a tentative one in use by an ongoing project, capable of identifying individuals at elevated risk for one or more types of the 80% leading cancers in rural China with adequate sensitivity and specificity and featuring low cost, easy application and cultural and technical sensitivity for farmers and village doctors. The protocol adopted a modified population-based case control design using 72, 000 non-patients as controls, 2, 200 cancer patients as cases, and another 600 patients as cases for external validation. Factors taken into account comprised 8 domains including diet and nutrition, risk behaviors, family history, precancerous diseases, related medical procedures, exposure to environment hazards, mood and feelings, physical activities and anthropologic and biologic factors. Modeling stresses explored various methodologies like empirical analysis, logistic regression, neuro-network analysis, decision theory and both internal and external validation using concordance statistics, predictive values, etc..
Xiaobin Shen,Kun Zhou,Rui Yu,Binrui Wang 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.7
In this paper, we aim to improve the tracking performance of the manipulator joint system by establishing accurate friction model based on the Stribeck model and the cubic polynomial method. Meanwhile, in view of the established system model, an adaptive Radial Basis Function Neural Network (RBFNN) compensation computedtorque controller is designed for the manipulator joint system. Firstly, we consider the friction modeling process at low- and high- velocity regions to advance the model accuracy, and identify the parameters in the friction model equation offline via the particle swarm optimization (PSO) algorithm. Secondly, an adaptive RBFNN algorithm is developed to analyze the unmodeled dynamics online and introduce it to the computed-torque controller design. After that, we further conduct the stability analysis for the proposed controller based on the Lyapunov stability criterion. Finally, the self-developed manipulator joint platform introduction, the simulation experiment and the contradistinctive experiments are given to illustrate the effectiveness of designed controller.