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首页> 外文会议>Annual and International Meeting of the Japanese Association for Animal Cell Technology >Development of a High-Throughput Evaluation System for Antiviral Activities of Food Factors By Using Bioinformatics
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Development of a High-Throughput Evaluation System for Antiviral Activities of Food Factors By Using Bioinformatics

机译：利用生物信息学，开发用于食物因素抗病毒活动的高通量评估系统

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To elucidate food functionality maintaining health is one of the most expected things in science activity for the human. Various physiological functions of food factors are being evaluated and the most are for the purpose of prevention of life-style related diseases or to raise biophylaxis ability. An estimated 170 million individuals in the world are infected with hepatitis C virus (HCV), a serious cause of chronic liver disease . Although the acute phase of infection is usually associated with mildsymptoms, approximate 80% of HCV infection results in chronic infection that frequently leads to severe chronic liver disease; 20-30% of infected individuals may develop cirrhosis and 1-3% may develop liver cancer. Therefore, screening a new food factorfor chronic HCV is a major public health objective. A point of view of phylaxis for viruses such as influenza is important as well as a HCV, too. There are many functions which should be measured, for example, as well as above, antioxidation activity, anti-metastatic activity, anti-angiogenic activity, anti-inflammatory activity and so on. However, to measure all necessary bioactivity makes serious demands upon investigator's time. Therefore we want to suggest a new method to evaluate plural functionsat the same time by applying artificial neural network. Neural networks, with their remarkable ability to derive meaning from complicated or imprecise data, can be used to extract patterns and detect trends that are too complex to be noticed by either humans or other computer techniques. In this study, we chose anti-HCV activity and natural killer (NK) cell activation activity as the plural bioactivities for simultaneous evaluation, and demonstrated that those bioactivities was able to be predicted withhigh precision at the same time.
机译：为了阐明食物功能，维持健康是人类科学活动中最预期的事情之一。正在评估食物因素的各种生理功能，最重要的是预防生命风格的相关疾病或提高生物面病症能力。据估计，世界上有1.7亿人感染丙型肝炎病毒（HCV），这是一种严重的慢性肝病的原因。虽然感染的急性阶段通常与脂联蛋白有关，但近似80％的HCV感染导致慢性感染，经常导致严重的慢性肝病; 20-30％的受感染的个体可能发展肝硬化，1-3％可能会发展肝癌。因此，筛选新的食物因素慢性HCV是一个主要的公共卫生目标。诸如流感等病毒的植物的观点也很重要，也是HCV。例如，还应测量许多功能，例如，如上所述，抗氧化活性，抗转移活性，抗血管生成活性，抗炎活性等。然而，为了衡量所有必要的生物活动，对调查员的时间产生严重要求。因此，我们希望通过应用人工神经网络来表示一种新方法来评估多个功能。神经网络，具有从复杂或不精确的数据中得出意义的显着能力，可以用于提取模式并检测太复杂的趋势，以通过人类或其他计算机技术被注意到。在本研究中，我们选择抗HCV活性和天然杀伤（NK）细胞活化活性作为同时评估的多种生物活化，并证明这些生物活像能够同时预测精度。

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