11 results about "Amyloid beta" patented technology

The present invention provides a novel anti-Aβ antibody capable of detecting an Aβ related peptide, a method for measuring an Aβ related peptide in a biological sample by immunochemically using the above-mentioned novel anti-Aβ antibody, and a kit. A monoclonal antibody that recognizes an Aβ related peptide, and is produced by a hybridoma deposited under the accession number NITE BP-02998 at the NITE Patent Microorganisms Depositary of the National Institute of Technology and Evaluation. An antibody-immobilized carrier that includes a carrier and the monoclonal antibody defined in claim 1 bound to the carrier. A kit for measuring an Aβ related peptide, comprising the antibody-immobilized carrier.

A method for early diagnosis or stage classification of Alzheimer's disease includes obtaining a tau protein-derived phosphorylated peptide from an isolated biological sample and quantifying the tau protein-derived phosphorylated peptide. Through the quantification of tau protein-derived phosphorylated peptides, it is possible to effectively diagnose Alzheimer's disease at an early stage or classify its stages, and determine the accumulation of amyloid beta in the brain.

The present disclosure provides anti-amyloid beta (Aβ) antibodies and antibody fragments that preferentially bind to soluble amyloid Aβ fibrils / oligomers and trigger ADPCs in microglia; anti-amyloid beta (Aβ) antibodies and antibody fragments that reduce soluble amyloid Aβ fibril / oligomer levels and insoluble amyloid Aβ plaques in brain tissue; and uses of anti-Aβ fibril / oligomer antibodies and antibody fragments in the treatment, prevention, diagnosis, screening and monitoring of conditions associated with Aβ protein aggregation, in particular Alzheimer's disease (AD).

The present invention relates to a composition for preventing, ameliorating or treating cognitive dysfunction or Alzheimer's disease comprising, as an active ingredient, Lactobacillus fermentum SRK414 strain which has accession number KCTC13687BP. The strain of the present invention is excellent in reducing barrier permeability and reducing amyloid beta and tau proteins and has an excellent effect in improving cognitive function, and accordingly, the strain can be useful for a food and therapeutic agent for same purposes.

The present application provides: a spectroscopic analysis substrate for diagnosing dementia, comprising a hydrophilized graphene layer; and a spectroscopic device comprising same. More specifically, the present application provides: a spectroscopic analysis substrate for diagnosing dementia, having improved accuracy due to increased binding force and selectivity for amyloid beta, the substrate comprising a hydrophilized graphene layer; and a spectroscopic device comprising the spectroscopic analysis substrate.

The present invention relates to a method for preparing a plasma sample comprising amyloid beta peptides for analysis by mass spectrometry, comprising the steps of:a) contacting said plasma sample with a denaturing agent, b) performing a first solid phase extraction step on the solution obtained in step a) to recover a first eluate, c) performing a second solid phase extraction step on said first eluate obtained in step b) to recover a second eluate, and d) drying said second eluate obtained in step c) and processing it for analysis by mass spectrometry, wherein the solution obtained in step d) comprises intact amyloid beta peptides Aβ40 and Aβ42.

The present invention relates to amyloid beta pathology, which is the cause of Alzheimer's disease, and, more specifically, to an amyloid beta pathology risk stratification method using an artificial intelligence model. To this end, provided is the amyloid beta pathology risk stratification method using an artificial intelligence model, comprising steps in which: a dataset related to brain atrophy is extracted from multimodal data (T1, T2 or CT); an artificial intelligence model (140) learns a dataset (100) related to brain atrophy; (S100) the trained artificial intelligence model (140) outputs a predicted probability distribution of amyloid beta-PET positivity and a predicted probability distribution of amyloid beta-PET negativity; (S100) the artificial intelligence model (140) determines an upper threshold and a lower threshold on the basis of the predicted probability distribution of amyloid beta-PET positivity and the predicted probability distribution of amyloid beta-PET negativity; (S120) a control unit stratifies the risk of amyloid beta-PET positivity into a high risk group (151), an intermediate risk group (153) and a low risk group (155) on the basis of the upper threshold and the lower threshold; (S140) a blood biomarker test is performed on the intermediate risk group (153); and (S160) a patient with a positive blood biomarker test result is determined as a patient of amyloid beta-PET positivity, and a patient with a negative blood biomarker test result is determined as a patient of amyloid beta-PET negativity.

The application belongs to the technical field of small-molecule fluorescent materials, and particularly relates to an imine small molecule and application of the imine small molecule as a fluorescent probe in detection of heavy metal ions and A beta peptide. 2+ In order to mine a multifunctional fluorescent material with a simple synthesis method, high sensitivity and a low detection limit, the application provides an imine small-molecule compound. 2+ The small molecule has high sensitivity and selectivity to Zn 2+ , Cu 2+ and Fe 2+ , wherein the small molecule shows a fluorescence 'off' effect to Cu 2+ and Fe 2+ , and shows a fluorescence 'on' effect to Zn 2+ . In addition, the small molecule can selectively combine with A beta peptide to produce a fluorescence 'on' effect, and the fluorescence is continuously enhanced with protein aggregation, so that different aggregation states of amyloid A beta can be distinguished. Therefore, the small molecule as the fluorescent probe can be used for simultaneously detecting Zn 2+ , Cu 2+ 0> , Fe 2+ 1> and amyloid beta aggregates, and has a wide application prospect.