Infrared Sensor Uses AI, Plasmonics To Detect Neural Diseases

It is difficult to diagnose neurodegenerative diseases (NDDs), such as Parkinson’s disease and Alzheimer’s disease, because no methods are available to identify preclinical biomarkers. The importance of protein misfolding into oligomeric and fibrillar aggregates in the onset and evolution of NDDs highlights the demand for structural biomarker-based diagnostics. Researchers created an immunoassay-coupled nanoplasmonic infrared metasurface sensor that distinguishes between the various structural types and specifically identifies proteins connected to NDDs, such as alpha-synuclein. Researchers added an artificial neural network to the infrared sensor to make the first-ever quantitative predictions of oligomeric and fibrillar protein clumps in their mixture. The microfluidic integrated sensor can multiplex for the simultaneous monitoring of several pathology-related biomarkers and may obtain time-resolved absorbance fingerprints in the presence of a complex biomatrix. As a result, the infrared sensor is an excellent option for the clinical diagnosis of NDDs, illness monitoring, and the assessment of innovative therapeutics.

Researchers present ImmunoSEIRA, an optofluidic immunoassay linked SEIRA sensor that can extract distinctive structural fingerprints of several conformational species of one of the NDD biomarkers – aSyn, including its oligomeric and fibrillary aggregates. The infrared sensor device detects a particular protein using an antibody-functionalized array of manufactured gold nanorods as a nanoplasmonic metasurface. To ease in situ capture and structural analysis of the target protein in tiny sample volumes, the chip is constructed in a two-dimensional (2D) microarray format and connected with microfluidics.

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