An apta-aggregation based machine learning assay for rapid quantification of lysozyme through texture parameters.

ABSTRACT: A novel assay technique that involves quantification of lysozyme (Lys) through machine learning is put forward here. This article reports the tendency of the well- documented Ellington group anti-Lys aptamer, to produce aggregates when exposed to Lys. This property of apta-aggregation has been exploited here to develop an assay that quantifies the Lys using texture and area parameters from a photograph of the elliptical aggregate mass through machine learning. Two assay sets were made for the experimental procedure: one with high Lys concentration between 25-100 mM and another with low concentration between 1-20 mM. The high concentration set had a sample volume of 10 μl while the low concentration set had a higher sample volume of 100 μl, in order to obtain the statistical texture values

SUBMITTER: Sanjay M 

PROVIDER: S-EPMC7939288 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature