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DETECTION DEVICE, DETECTION METHOD AND DETECTION PROGRAM WHICH SUPPORT DETECTION OF SIGN OF STATE TRANSITION IN LIVING ORGANISM ON BASIS OF NETWORK ENTROPY

外国特許コード F200010139
整理番号 EF001P04WO
掲載日 2020年6月1日
出願国 世界知的所有権機関(WIPO)
国際出願番号 2013JP077929
国際公開番号 WO 2014065155
国際出願日 平成25年10月15日(2013.10.15)
国際公開日 平成26年5月1日(2014.5.1)
優先権データ
  • 特願2012-233886 (2012.10.23) JP
発明の名称 (英語) DETECTION DEVICE, DETECTION METHOD AND DETECTION PROGRAM WHICH SUPPORT DETECTION OF SIGN OF STATE TRANSITION IN LIVING ORGANISM ON BASIS OF NETWORK ENTROPY
発明の概要(英語) Provided are a detection device, a detection method and a detection program which enable highly precise detection of a pre-disease state that indicates a sign of a state transition from a healthy state to a disease state. Acquisition processing (s1), by which measurement data such as genes and proteins relating to a living organism is acquired as high throughput data, election processing (s2) of a differential biomolecule, calculation (s3) of the SNE of a local network, selection (s4) of a biomarker candidate, calculation (s5) of the average SNE of an entire network, and detection processing (s6), by which it is determined whether a pre-disease state applies and by which detection occurs, are implemented.
従来技術、競合技術の概要(英語) BACKGROUND ART
According to the result of various studies, many disease, progression of disease progression is particularly complicated processes, climate system, the biological system, economic system or the like similar to the system, critical threshold value at a time, so-called branch point is reached, a sudden occurrence of a state transition and, a stable state rapidly from the health change in disease state (for example, see Non-Patent Document 1-5). Such a complex disease in the study of dynamic mechanism, the deterioration of the disease (for example, an asthma attack, the onset of cancer) progression of processes, time-dependent non-linear dynamics and modeled as a system, a model by analyzing the dynamics of the system, the state transition of the branch point of the disease is rapidly degraded may be already known (Non-Patent Document 1, reference 6).
Fig. 1 is, the progress of the disease is an explanatory diagram conceptually showing the processes. Fig. 1 a is of, the progress of the disease are schematically illustrated in the processes. B of Fig. 1, c and d is, progress in the course of the processes, described above as a function of potential stability of the system, the horizontal axis of the system to take the state variables, take the value of the potential function on the vertical axis conceptually shown on the schematic. As shown in Fig. 1 a of, the progress of the deterioration of the disease processes, the normal state (health), before a disease state, disease state can be expressed as. In the normal state, the system is stable, as shown in b of Fig. 1, a minimum value of the potential function. In the state prior the disease, the system, as shown in c of Fig. 1, the value of the potential function is increased. Therefore, is prone to the influence of disturbance, only small disturbances in the vicinity of the branch point and the state transition, that is, the position of the limit of the normal state. However, the previous state is a disease, an appropriate treatment, often can be recovered to a normal state. On the other hand, in the disease state, the system is again stabilized, as shown in d of Fig. 1, the value of the global potential function becomes minimum. Therefore, the state transition of the branch from the normal condition occurs in the disease state, it is difficult to recover to the normal state.
Therefore, to be detected before the disease state, disease state before the transition, while a transition to a disease state is as long as it is possible to notify the patient, can take an appropriate action, from the patient before the disease state can be restored to the normal state is a high possibility.
That is, the branch point (critical threshold) can be detected, and allow the prediction of the state transition, early diagnosis of a disease can be realized. However, in the case of complex diseases, the state transition prediction is very difficult. The reason for this is as follows.
, First, before a disease state, is limited to a normal state, before reaching the branch point, is difficult to detect a significant change. Therefore, a conventional biomarker, the snapshot measurement and the like by the method of diagnosis, a disease state before the normal state and it is difficult to distinguish., Second, various studies have been made in, for early diagnosis for the prediction of the branch point a warning signal can be detected with high accuracy and high reliability not yet been developed the disease model. In particular, in the same disease, by an individual, the disease progression of the deterioration for different processes, a model-based diagnostic methods, lower probability of success., Thirdly, before a disease detection of the state of the subject is a patient, generally, one obtained from the patient due to the limited number of samples, over a long period of time, a necessary and sufficient to predict that it is difficult to sample may be taken.
On the other hand, the inventors of the present invention, the disease state from the normal state before the transition to the state of the disease and pre-warning signal to detect a candidate biomarker of the proposed method (Non-Patent Document 7). According to this method, a disease state (DNB) appearing immediately before the transition can be detected by the dynamic network biomarker, early diagnosis of a disease can be realized.
  • 出願人(英語)
  • ※2012年7月以前掲載分については米国以外のすべての指定国
  • JAPAN SCIENCE AND TECHNOLOGY AGENCY
  • 発明者(英語)
  • AIHARA, Kazuyuki
  • CHEN, Luonan
  • LIU, Rui
国際特許分類(IPC)
指定国 National States: AE AG AL AM AO AT AU AZ BA BB BG BH BN BR BW BY BZ CA CH CL CN CO CR CU CZ DE DK DM DO DZ EC EE EG ES FI GB GD GE GH GM GT HN HR HU ID IL IN IR IS KE KG KN KP KR KZ LA LC LK LR LS LT LU LY MA MD ME MG MK MN MW MX MY MZ NA NG NI NO NZ OM PA PE PG PH PL PT QA RO RS RU RW SA SC SD SE SG SK SL SM ST SV SY TH TJ TM TN TR TT TZ UA UG US UZ VC VN ZA ZM ZW
ARIPO: BW GH GM KE LR LS MW MZ NA RW SD SL SZ TZ UG ZM ZW
EAPO: AM AZ BY KG KZ RU TJ TM
EPO: AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR
OAPI: BF BJ CF CG CI CM GA GN GQ GW KM ML MR NE SN TD TG
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