Abstract: This study compares the relative utility of deep learning models as automated phenotypic classifiers, built with features of peripheral blood cell populations assayed with flow cytometry. We ...

Over the past decade, flow cytometry has undergone transformative advancements, notably with the adoption of spectral flow cytometry and the emergence of next-generation imaging cytometers. These ...

Amid a season of regulatory and scientific advances, experts reveal a culture of data hoarding among cell and gene therapy developers that is reinforcing fragmentation, stalling innovation and ...

1 Salivary Disorders Unit, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, United States 2 NIDCR Sjögren’s Disease Clinic, National Institute of ...

Not all patients respond well to chimeric antigen receptor (CAR) T cell therapies, which reprogram a patient’s own immune cells to recognize and attack cancer. A way to optimize these treatments is to ...

As for many antibody-based experiments, labeling challenges related to brightness, signal stability, target detection, and background noise are common roadblocks in flow cytometry. Scientists can ...

Flow cytometry is a versatile technique often used in biomedical research, pharmaceutical development, and scientific diagnostics. This sophisticated technology enables researchers to examine the ...

Abstract: Microfluidic impedance flow cytometry (IFC) is a widely used technique for high-throughput analysis and single-cell identification, analyzing cells based on their electrical properties ...

The capability to sort single cells of interest and to deeply characterize them has greatly added to our understanding of biology and disease states. Indeed, cell sorting has become an indispensable ...