Nezamoddin N. Kachouie

Fabrication of three-dimensional porous cell-laden hydrogel for tissue engineering

For tissue engineering applications, scaffolds should be porous to enable rapid nutrient and oxygen transfer while providing a three-dimensional (3D) microenvironment for the encapsulated cells. This dual characteristic can be achieved by fabrication of porous hydrogels that contain encapsulated cells. In this work, we developed a simple method that allows cell encapsulation and pore generation inside alginate hydrogels simultaneously. Gelatin beads of 150-300 microm diameter were used as a sacrificial porogen for generating pores within cell-laden hydrogels. Gelation of gelatin at low temperature (4 degrees C) was used to form beads without chemical crosslinking and their subsequent dissolution after cell encapsulation led to generation of pores within cell-laden hydrogels. The pore size and porosity of the scaffolds were controlled by the gelatin bead size and their volume ratio, respectively. Fabricated hydrogels were characterized for their internal microarchitecture, mechanical properties and permeability. Hydrogels exhibited a high degree of porosity with increasing gelatin bead content in contrast to nonporous alginate hydrogel. Furthermore, permeability increased by two to three orders while compressive modulus decreased with increasing porosity of the scaffolds. Application of these scaffolds for tissue engineering was tested by encapsulation of hepatocarcinoma cell line (HepG2). All the scaffolds showed similar cell viability; however, cell proliferation was enhanced under porous conditions. Furthermore, porous alginate hydrogels resulted in formation of larger spheroids and higher albumin secretion compared to nonporous conditions. These data suggest that porous alginate hydrogels may have provided a better environment for cell proliferation and albumin production. This may be due to the enhanced mass transfer of nutrients, oxygen and waste removal, which is potentially beneficial for tissue engineering and regenerative medicine applications.

Directed assembly of cell-laden hydrogels for engineering functional tissues

Tissue engineering aims to develop functionalized tissues for organ replacement or restoration. Biodegradable scaffolds have been used in tissue engineering to support cell growth and maintain mechanical and biological properties of tissue constructs. Ideally cells on these scaffolds adhere, proliferate, and deposit matrix at a rate that is consistent with scaffold degradation. However, the cellular rearrangement within these scaffolds often does not recapitulate the architecture of the native tissues. Directed assembly of tissue-like structures is an attractive alternative to scaffold-based approach for tissue engineering which potentially can build tissue constructs with biomimetic architecture and function. In directed assembly, shape-controlled microstructures are fabricated in which organized structures of different cell types can be used as tissue building blocks. To fabricate tissue building blocks, hydrogels are commonly used as biomaterials for cell encapsulation to mimic the matrix in vivo. The hydrogel-based tissue building blocks can be arranged in pre-defined architectures by various directed tissue assembly techniques. In this paper, recent advances in directed assembly-based tissue engineering are summarized as an emerging alternative to meet challenges associated with scaffold-based tissue engineering and future directions are addressed.

Drug-eluting microarrays for cell-based screening of chemical-induced apoptosis

Traditional high-throughput screening (HTS) is carried out in centralized facilities that require extensive robotic liquid and plate handling equipment. This model of HTS is restrictive as such facilities are not accessible to many researchers. We have designed a simple microarray platform for cell-based screening that can be carried out at the benchtop. The device creates a microarray of 2100 individual cell-based assays in a standard microscope slide format. A microarray of chemical-laden hydrogels addresses a matching array of cell-laden microwells thus creating a microarray of sealed microscale cell cultures each with unique conditions. We demonstrate the utility of the device by screening the extent of apoptosis and necrosis in MCF-7 breast cancer cells in response to exposure to a small library of chemical compounds. From a set of screens we produced a rank order of chemicals that preferentially induce apoptosis over necrosis in MCF-7 cells. Treatment with doxorubicin induced high levels of apoptosis in comparison with staurosporine, ethanol, and hydrogen peroxide, whereas treatment with 100 μM ethanol induced minimal apoptosis with high levels of necrosis. We anticipate broad application of the device for various research and discovery applications as it is easy to use, scalable, and can be fabricated and operated with minimal peripheral equipment.

Probabilistic Model-Based Cell Tracking

The study of cell behavior is of crucial importance in drug and disease research. The fields of bioinformatics and biotechnology rely on the collection, processing, and analysis of huge numbers of biocellular images, including cell features such as cell size, shape, and motility. However manual methods of inferring these values are so onerous that automated methods of cell tracking and segmentation are in high demand. In this paper, a novel model-based cell tracker is designed to locate and track individual cells. The proposed cell tracker has been successfully applied to track hematopoietic stem cells (HSCs) based on identified cell locations and probabilistic data association.

Designer Hydrophilic Regions Regulate Droplet Shape for Controlled Surface Patterning and 3D Microgel Synthesis

A simple technique is presented for controlling the shapes of micro- and nanodrops by patterning surfaces with special hydrophilic regions surrounded by hydrophobic boundaries. Finite element method simulations link the shape of the hydrophilic regions to that of the droplets. Shaped droplets are used to controllably pattern planar surfaces and microwell arrays with microparticles and cells at the micro- and macroscales. Droplets containing suspended sedimenting particles, initially at uniform concentration, deposit more particles under deeper regions than under shallow regions. The resulting surface concentration is thus proportional to the local fluid depth and agrees well with the measured and simulated droplet profiles. A second application is also highlighted in which shaped droplets of prepolymer solution are crosslinked to synthesize microgels with tailored 3D geometry.

Watershed deconvolution for cell segmentation

Cell segmentation and/or localization is the first stage of a (semi)automatic tracking system. We addressed the cell localization problem in our previous work where we characterized a typical blood stem cell in a microscopic image as an approximately circular object with dark interior and bright boundary. We also addressed the modelling of adjacent and dividing cells in our previous work as a deconvolution method to model individual blood stem cell as well as adjacent and dividing blood stem cells where an optimization algorithm was combined with a template matching method to segment cell regions and locate the cell centers. Our previous cell deconvolution method is capable of modelling different cell types with changes in the model parameters. However in cases where either a complex parameterized shape is needed to model a specific cell type, or in place of cell center localization, an exact cell segmentation is needed, this method will not be effective. In this paper we propose a method to achieve cell boundary segmentation. Considering cell segmentation as an inverse problem, we assume that cell centers are located in advance. Then, the cell segmentation will be solved by finding cell regions for optimal representation of cell centers while a template matching method is effectively employed to localize cell

A Medical Texture Local Binary Pattern For TRUS Prostate Segmentation

Prostate cancer diagnosis and treatment rely on segmentation of Transrectal Ultrasound (TRUS) prostate images. This is a challenging and difficult task dut to weak prostate boundaries, speckle noise and the short range of gray levels. Advances in digital imaging techniques have made it possible the acquisition of large volumes of TRUS prostate images so that there is considerable demand for automated segmentation systems. Local binary pattern (LBP) has been used for texture segmentation and analysis. Despite its promising performance for texture classification it has not yet been considered for TRUS prostate segmentation. In this paper we introduce a medical texture local binary pattern operator designed for applications of medical imaging where different tissues or micro organisms might maintain extremely weak underlying textures that make it impossible or very difficult for ordinary texture analysis approaches to classify them. In the proposed method the deformations of a level set contour are controlled based on the medical texture local binary pattern operator.

Arraycount, an algorithm for automatic cell counting in microwell arrays

Microscale technologies have emerged as a powerful tool for studying and manipulating biological systems and miniaturizing experiments. However, the lack of software complementing these techniques has made it difficult to apply them for many high-throughput experiments. This work establishes Arraycount, an approach to automatically count cells in microwell arrays. The procedure consists of fluorescent microscope imaging of cells that are seeded in microwells of a microarray system and then analyzing images via computer to recognize the array and count cells inside each microwell. To start counting, green and red fluorescent images (representing live and dead cells, respectively) are extracted from the original image and processed separately. A template-matching algorithm is proposed in which pre-defined well and cell templates are matched against the red and green images to locate microwells and cells. Subsequently, local maxima in the correlation maps are determined and local maxima maps are thresholded. At the end, the software records the cell counts for each detected microwell on the original image in high-throughput. The automated counting was shown to be accurate compared with manual counting, with a difference of approximately 1-2 cells per microwell: based on cell concentration, the absolute difference between manual and automatic counting measurements was 2.5-13%.

An Elliptical Level Set Method for Automatic TRUS Prostate Image Segmentation

One of the most important tasks in prostate cancer diagnosis and treatment is segmentation of transrectal ultrasound (TRUS) prostate images. Due to the large volumes of TRUS prostate images, automatic segmentation systems are mandatory. Weak prostate boundaries, speckle noise and the short range of gray levels make the task more challenging and difficult. Deformable models have been considered as an effective approach for semi-automatic prostate segmentation. However the main problem toward a fully automatic segmentation system using deformable models is initialization of seed or control points. In this paper an automatic level set prostate segmentation is presented. A classification method is employed to locate the approximate location of the prostate which is used to initiate the proposed elliptical level set contour. The deformations of the level set are guided by a velocity function which is derived using the TRUS prostate image histogram

A Statistical Thresholding Method for Cell Tracking

Tracking the motion of cells in culture is a task, which often still Is undertaken manually, and for which automated methods are strongly desirable. Researchers visually perform cell motion analysis, observe cell movements and cell shape changes for hours to discover when, where and how fast It moves, splits or dies. Hematopoletlc stem cells (HSCs) proliferate and differentiate to different blood cell types continuously during their lifetime, and are of substantial interest in gene therapy, cancer, and stem-cell research. In this paper a statistical method is introduced to track HSCs over time. A statistical thresholding method is combined with joint probabilistic data association in the proposed HSC tracker