Background The current diagnosis of Alzheimer’s disease(AD)is based on a series of analyses which involve clinical,instrumental and laboratory findings.However,signs,symptoms and biomarker alterations observed in AD ...Background The current diagnosis of Alzheimer’s disease(AD)is based on a series of analyses which involve clinical,instrumental and laboratory findings.However,signs,symptoms and biomarker alterations observed in AD might overlap with other dementias,resulting in misdiagnosis.Methods Here we describe a new diagnostic approach for AD which takes advantage of the boosted sensitivity in biomolecular detection,as allowed by seed amplification assay(SAA),combined with the unique specificity in biomolecular recognition,as provided by surface-enhanced Raman spectroscopy(SERS).Results The SAA-SERS approach supported by machine learning data analysis allowed efficient identification of pathological Aβoligomers in the cerebrospinal fluid of patients with a clinical diagnosis of AD or mild cognitive impairment due to AD.Conclusions Such analytical approach can be used to recognize disease features,thus allowing early stratification and selection of patients,which is fundamental in clinical treatments and pharmacological trials.展开更多
基金supported in part by the Italian Ministry of Health(RRC,5M-2018-23680266,and GR-2021-12372019)to FMthe European Community,Italian Ministry of Education,University and Research and the Italian Ministry of Health within the EuroNanoMed3 ERANET cofund SPEEDY project and by Tuscany Region(FAS-Salute 2018)project PRAMA to PM and to FM.
文摘Background The current diagnosis of Alzheimer’s disease(AD)is based on a series of analyses which involve clinical,instrumental and laboratory findings.However,signs,symptoms and biomarker alterations observed in AD might overlap with other dementias,resulting in misdiagnosis.Methods Here we describe a new diagnostic approach for AD which takes advantage of the boosted sensitivity in biomolecular detection,as allowed by seed amplification assay(SAA),combined with the unique specificity in biomolecular recognition,as provided by surface-enhanced Raman spectroscopy(SERS).Results The SAA-SERS approach supported by machine learning data analysis allowed efficient identification of pathological Aβoligomers in the cerebrospinal fluid of patients with a clinical diagnosis of AD or mild cognitive impairment due to AD.Conclusions Such analytical approach can be used to recognize disease features,thus allowing early stratification and selection of patients,which is fundamental in clinical treatments and pharmacological trials.
