Abstract:
Suggested is a method for measuring etiologic substances within a cell using a microlens, capable of enabling the early detection of Alzheimer`s disease by collecting light generated from beta-amyloid within a cell underwent fluorescent staining in a phototransistor channel using the microlens. The suggested method comprises the steps of: preparing the microlens; cultivating a cell including a protein biomarker causing Alzheimer`s disease on the microlens; performing fluorescent staining the cultivated cell; and collecting light generated from the cell through the microlens in an optical sensor opposed to the microlens.
Abstract:
PURPOSE: A method for early diagnosing Alzheimer's disease using a phototransistor is provided to enable early diagnosis of the disease and to quantitate cells or beta-amyloid proteins. CONSTITUTION: A method for early diagnosing Alzheimer's disease using a phototransistor comprises: a step of placing the phototransistor for sensing photocurrent difference according to the amount of incident light and a step of sensing photocurrent different according to cells fixed on the surface of a channel layer. The phototransistor comprises the channel layer. The cells have a protein biomarker causing Alzheimer's disease. The protein biomarker is labeled with magnetic particles(200) which are conjugated with multi-proteins. The protein biomarker is beta-amyloid protein(240).
Abstract:
본 발명은 거대자기저항 센서를 이용한 알츠하이머병의 진단방법 및 알츠하이머병 진단용 자기비드-다중단백질 복합체에 관한 것이다. 본 발명에 따른 거대자기저항 센서를 이용하여 알츠하이머병의 진단방법은 기존의 형광물질이나 유전자 분석 대신 거대자기저항 센서를 이용하여 간단한 방법으로 알츠하이머병을 쉽게 진단할 수 있고, 알츠하이머병 진단용 바이오 센서로 대량생산이 가능하므로, 알츠하이머병의 모니터링과 치료에 유용하게 사용할 수 있다.
Abstract:
본 발명은 거대자기저항 센서를 이용한 알츠하이머병의 진단방법 및 알츠하이머병 진단용 자기비드-다중단백질 복합체에 관한 것이다. 본 발명에 따른 거대자기저항 센서를 이용하여 알츠하이머병의 진단방법은 기존의 형광물질이나 유전자 분석 대신 거대자기저항 센서를 이용하여 간단한 방법으로 알츠하이머병을 쉽게 진단할 수 있고, 알츠하이머병 진단용 바이오 센서로 대량생산이 가능하므로, 알츠하이머병의 모니터링과 치료에 유용하게 사용할 수 있다.
Abstract:
Disclosed are a device and a method for predicting the incidence rate of the Alzheimer′s disease by utilizing a beta-amyloid concentration, a p-FET measurement value, and a PMT measurement value as input data, extracting the feature values of the input data, and applying the feature values to a pattern recognizing algorithm. The device comprises: a feature extracting part for extracting the feature values through the recognition of a pattern by comparing a beta-amyloid concentration value contained in a sample to be measured, a photosensitive field-effect transistor measurement value, and a photo multiplier tube measurement value, which are inputted from the outside, with pre-stored initial values; and an incidence rate predicting part for predicting the incidence rate of the Alzheimer′s disease based on the extracted feature values. The photosensitive field-effect transistor measurement value is obtained by measuring the photoelectric current of light emitted by exciting light while the sample in which the beta-amyloid and fluorescent substances are combined is fixed in the sensing section of a photosensitive field-effect transistor, and the photo multiplier tube measurement value is obtained by measuring the number of photons in the light emitted by exciting the light to the same sample used in the measurement of the photoelectric current.