Detection of Rare Objects by Flow Cytometry: Imaging, Cell Sorting, and Deep Learning Approaches

Flow cytometry nowadays is among the main working instruments in modern biology paving the way for clinics to provide early, quick, and reliable diagnostics of many blood-related diseases. The major problem for clinical applications is the detection of rare pathogenic objects in patient blood. These objects can be circulating tumor cells, very rare during the early stages of cancer development, various microorganisms and parasites in the blood during acute blood infections. All of these rare diagnostic objects can be detected and identified very rapidly to save a patient's life. This review outlines the main techniques of visualization of rare objects in the blood flow, methods for extraction of such objects from the blood flow for further investigations and new approaches to identify the objects automatically with the modern deep learning methods.

Profile of MicroRNA Expression in Endometrial Cell during In Vitro Culture According to Progesterone Concentration

Artificial uterus using endometrium implant can be a novel treatment strategy for infertile women with refractory endometrial dysfunction. At early pregnancy, the function of uterine endometrial cells for the communication between the conceptus of pre-implantation period and maternal reproductive system is essential. MicroRNA (miR) expression profile of endometrial cells according to progesterone, a crucial pregnancy-maintaining hormone, provides important data for in vitro endometrial cell culture strategy that is useful for engineering artificial uteri using endometrial implants. The present study aimed to evaluate the miR expression profile of in vitro cultured endometrial cells under hormonal milieu mimicking early pregnancy period in terms of progesterone concentration. We cultured murine uterine endometrial cells, human uterine endometrial carcinoma cells, and immortalized human uterine endometrial cells using different progesterone concentrations, and analyzed the expression of miRs critical for early pregnancy. The expression of miR-20a, -21, -196a, -199a, and -200a was differently regulated according to progesterone concentration in different endometrial cell lines. The analysis of candidate target genes showed that the expression of phosphatase and tensin homolog, mucin 1 (MUC1), progesterone receptor, transforming growth factor β receptor II, matrix metallopeptidase-9 was up-regulated by progesterone treatment in mouse and human endometrial cell lines. These results indicate that physiological concentration range (10-7 and 10-9 M) of progesterone affect the survival and target gene expression via modulating miR expression. Taken together, progesterone can be a crucial factor in regulating miR expression on in vitro cultured endometrial cells.