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Prospects for the use of graphene-based biological sensors in the early diagnosis of Alzheimer's disease (review of literature).

Authors :
Vorobev SV
Yanishevskij SN
Emelin AY
Lebedev AA
Lebedev SP
Makarov YN
Usikov AS
Klotchenko SA
Vasin AV
Source :
Klinicheskaia laboratornaia diagnostika [Klin Lab Diagn] 2022 Jan 21; Vol. 67 (1), pp. 5-12.
Publication Year :
2022

Abstract

Among the most significant challenges presented to modern medicine is the problem of cognitive disorders. The relevance of her research is determined by the wide spread of disorders of the higher cortical functions, their significant negative impact on the quality of life of patients, as well as high economic costs on the part of the state and the patient's relatives aimed at organizing medical, diagnostic and rehabilitation processes. The main cause of cognitive impairment in the elderly is Alzheimer's disease. Currently, the criteria for the diagnosis of this nosological form have been developed and are widely used in practice. However, it should be noted that their use is most effective if the patient has a detailed clinical picture, at the stage of dementia. In addition, they provide for the study of biomarkers in a number of cases in the cerebrospinal fluid or using positron emission tomography, which presents certain technical difficulties. Especially significant problems arise in the pre-dement stages. This situation dictates the need to search for new promising diagnostic methods that will have high sensitivity and specificity, as well as the possibility of application in the early stages of Alzheimer's disease, including in outpatient settings. The article provides information about modern methods of computer neuroimaging, discusses the research directions of individual biomarkers, and also shows the prospects for using diagnostic test panels developed on the basis of graphene biosensors, taking into account the latest achievements of nanotechnology and their integration into medical science.<br />Competing Interests: The authors declare no conflict of interest.

Details

Language :
English
ISSN :
0869-2084
Volume :
67
Issue :
1
Database :
MEDLINE
Journal :
Klinicheskaia laboratornaia diagnostika
Publication Type :
Academic Journal
Accession number :
35077063
Full Text :
https://doi.org/10.51620/0869-2084-2022-67-1-5-12