posted on 2020-08-27, 16:36authored byJulian Schütt, Diana Isabel Sandoval Bojorquez, Elisabetta Avitabile, Eduardo Sergio Oliveros Mata, Gleb Milyukov, Juliane Colditz, Lucia Gemma Delogu, Martina Rauner, Anja Feldmann, Stefanie Koristka, Jan Moritz Middeke, Katja Sockel, Jürgen Fassbender, Michael Bachmann, Martin Bornhäuser, Gianaurelio Cuniberti, Larysa Baraban
We
realize an ultracompact nanocytometer for real-time impedimetric
detection and classification of subpopulations of living cells. Nanoscopic
nanowires in a microfluidic channel act as nanocapacitors and measure
in real time the change of the amplitude and phase of the output voltage
and, thus, the electrical properties of living cells. We perform the
cell classification in the human peripheral blood (PBMC) and demonstrate
for the first time the possibility to discriminate monocytes and subpopulations of lymphocytes in a label-free format. Further,
we demonstrate that the PBMC of acute myeloid leukemia and healthy
samples grant the label free identification of the disease. Using
the algorithm based on machine learning, we generated specific
data patterns to discriminate healthy donors and leukemia
patients. Such a solution has the potential to improve the traditional
diagnostics approaches with respect to the overall cost and time effort,
in a label-free format, and restrictions of the complex data analysis.