Microfluidics allows the miniaturization of conventional operations that occur in a conventional biological or chemical laboratory. Many components of the culture medium can affect the rate of cell proliferation, but serum represents one of the best documented modulators of cell division and growth. These components include hormones, vitamins, nucleosides, amino acids, lipids, carrier proteins (albumin, globin and transferrin), extracellular matrix components (fibronectin and laminin), stabilizing factors, detoxifying agents, proliferation factors and growth factors. Only about 200 of the thousand of components that are present in the FBS composition have been defined. Normally, FBS is used to supplement the culture medium at a concentration of 5% to 20%. FBS was constituted as a standard supplement of the cell culture medium, which is easily obtained and contains a high concentration of growth factors and a low concentration of gammaglobulins, compared to other sera originated from animals. To maintain cell function and allow cell division and proliferation, the culture medium is universally complemented with fetal bovine serum (FBS), a mixture containing growth factors among its components. In cell cultures, special combinations of nutrients are required in the culture media to provide optimum conditions for the survival and in vitro growth of the different cell lines under study. Since the beginning of cell biology, scientists have sought methods to isolate and cultivate different cell lines for the investigation of cell and dynamics biology and their subsequent clinical application. In this contribution, it has been presented an image processing software, Python based image analysis for cell growth (PIACG), that is able to calculate the total area of the well occupied by cells with fusiform and rounded morphology in response to different concentrations of fetal bovine serum in microfluidic chips, from microscopy images in transmission light, in a highly efficient way. The software available so far are suitable for the processing of fluorescence and phase contrast images, but often do not provide good results from transmission light microscopy images, due to the intrinsic variation of the acquisition of images technique itself (adjustment of brightness / contrast, for instance) and the variability between image acquisition introduced by operators / equipment. The amount of data that is generated requires automated methods for the processing and analysis of all the resulting information. Over the past few years, image analysis has emerged as a powerful tool for analyzing various cell biology parameters in an unprecedented and highly specific manner.
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