Segmentation and Quantitative Analysis of Apoptosis of Chinese Hamster Ovary Cells from Fluorescence Microscopy Images.

Accurate and fast quantitative analysis of living cells from fluorescence microscopy images is useful for evaluating experimental outcomes and cell culture protocols. An algorithm is developed in this work to automatically segment and distinguish apoptotic cells from normal cells. The algorithm involves three steps consisting of two segmentation steps and a classification step. The segmentation steps are: (i) a coarse segmentation, combining a range filter with a marching square method, is used as a prefiltering step to provide the approximate positions of cells within a two-dimensional matrix used to store cells' images and the count of the number of cells for a given image; and (ii) a fine segmentation step using the Active Contours Without Edges method is applied to the boundaries of cells identified in the coarse segmentation step. Although this basic two-step approach provides accurate edges when the cells in a given image are sparsely distributed, the occurrence of clusters of cells in high cell density samples requires further processing. Hence, a novel algorithm for clusters is developed to identify the edges of cells within clusters and to approximate their morphological features. Based on the segmentation results, a support vector machine classifier that uses three morphological features: the mean value of pixel intensities in the cellular regions, the variance of pixel intensities in the vicinity of cell boundaries, and the lengths of the boundaries, is developed for distinguishing apoptotic cells from normal cells. The algorithm is shown to be efficient in terms of computational time, quantitative analysis, and differentiation accuracy, as compared with the use of the active contours method without the proposed preliminary coarse segmentation step.

Classification of Normal and Apoptotic Cells from Fluorescence Microscopy Images Using Generalized Polynomial Chaos and Level Set Function.

Accurate automated quantitative analysis of living cells based on fluorescence microscopy images can be very useful for fast evaluation of experimental outcomes and cell culture protocols. In this work, an algorithm is developed for fast differentiation of normal and apoptotic viable Chinese hamster ovary (CHO) cells. For effective segmentation of cell images, a stochastic segmentation algorithm is developed by combining a generalized polynomial chaos expansion with a level set function-based segmentation algorithm. This approach provides a probabilistic description of the segmented cellular regions along the boundary, from which it is possible to calculate morphological changes related to apoptosis, i.e., the curvature and length of a cell's boundary. These features are then used as inputs to a support vector machine (SVM) classifier that is trained to distinguish between normal and apoptotic viable states of CHO cell images. The use of morphological features obtained from the stochastic level set segmentation of cell images in combination with the trained SVM classifier is more efficient in terms of differentiation accuracy as compared with the original deterministic level set method.

Experimental Investigation of Methyl Methacrylate in Stirred Batch Emulsion Reactor: AGET ATRP Approach.

This study examines the ab initio emulsion atom transfer radical polymerization (ATRP) initiated by an eco-friendly reducing agent to produce poly(methyl methacrylate) (PMMA) polymer with controlled characteristics in a 2 L stirred batch reactor. The effect of the reaction temperature, surfactant concentration, monomer to water ratio, and stirring speed was thoroughly investigated. The results showed that PMMA coagulation becomes quite severe at a certain temperature threshold. However, the coagulation could be avoided at mild reaction temperature, since the outcomes showed that loading more surfactant to the system under high mixing speed has balanced the polymer mixture and yielded high monomer conversion. The PMMA product was analyzed by gravimetry and GPC measurements and after 5 h of polymerization at a reaction temperature of 50 °C, monomer conversion of 64.1% was obtained, and PMMA polymer samples produced had an average molar mass of 4.5 kg/mol and a polydispersity index of 1.17. The structure of the PMMA polymer was successfully proved by FTIR and nuclear magnetic resonance (NMR) spectroscopy. The results confirm the living feature of MMA AGET ATRP in emulsion medium and recommend further investigation for other types of surfactant.

Optimization of culture media to enhance the growth of tissue engineered cartilage.

Tissue engineering is a promising option for cartilage repair. However, several hurdles still need to be overcome to develop functional tissue constructs suitable for implantation. One of the most common challenges is the general low capacity of chondrocytes to synthesize cartilage-specific extracellular matrix (ECM). While different approaches have been explored to improve the biosynthetic response of chondrocytes, several studies have demonstrated that the nutritional environment (e.g., glucose concentration and media volume) can have a profound effect on ECM synthesis. Thus, the purpose of this study was to optimize the formulation of cell culture media to upregulate the accumulation of cartilaginous ECM constituents (i.e., proteoglycans and collagen) by chondrocytes in 3D culture. Using response surface methodology, four different media factors (basal media, media volume, glucose, and glutamine) were first screened to determine optimal media formulations. Constructs were then cultured under candidate optimal media formulations for 4 weeks and analyzed for their biochemical and structural properties. Interestingly, the maximal accumulation of proteoglycans and collagen appeared to be elicited by different media formulations. Most notably, proteoglycan accumulation was favored by high volume, low glucose-containing DMEM/F12 (1:1) media whereas collagen accumulation was favored by high volume, high glucose-containing F12 media. While high glutamine-containing media elicited increased DNA content, glutamine concentration had no apparent effect on ECM accumulation. Therefore, optimizing the nutritional environment during chondrocyte culture appears to be a promising, straight-forward approach to improve cartilaginous tissue formation. Future work will investigate the combined effects of the nutritional environment and external stimuli.