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(1 - 3 of 3)
- Title
- PEGYLATION OF FIBRONECTIN AND ITS FUNCTIONAL DOMAINS: EFFECT ON STABILITY AND BIOLOGICAL ACTIVITY
- Creator
- Zhang, Chen
- Date
- 2013, 2013-07
- Description
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Delayed wound healing in many chronic wounds has been linked to the lack of extracellular matrix (ECM) support and the degradation of...
Show moreDelayed wound healing in many chronic wounds has been linked to the lack of extracellular matrix (ECM) support and the degradation of fibronectin (FN) by an abnormally high protease level. The ECM is important in wound healing because it provides physical and chemical cues that direct tissue growth and development. FN is a key ECM protein that attracts and binds different molecules and cells and thereby supports biological responses associated with wound healing. The goal of my study is two fold: (1) To create an ECM analogue based on a composite of polyethylene glycol (PEG) hydrogels and FN binding domains and (2) To stabilize FN against proteolytic degradation by conjugating it to PEG. To address the first goal, I used Michael addition chemistry to covalently link the cell-binding domain of FN, III9−10, to PEG diacrylate and cross-linked the conjugate to PEG hydrogels. The conjugation of PEG to III9−10 was through cysteines in the affinity tag Glutathione S Transferase (GST). The conjugate of GST-III9−10 and PEG was characterized by: (i) Circular dichroism studies to determine secondary structure, (ii) Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) to determine molecular weight, and (iii) Ellmans reagent to determine the efficiency of PEG conjugation to GST-III9−10. The conjugate of PEG and GST-III9−10 had comparable secondary structure to GST-III9−10. SDS-PAGE studies showed that up to three PEG molecules were attached to one GST-III9−10 molecule. The efficiency of PEG conjugation was greater than 90% and occurred within 30 minutes after PEG diacrylate addition. Adhesion assays were used as a metric of biological activity. These assays demonstrated that on a molar basis cell adhesion and spreading were significantly higher on PEG hydrogels with GST-III9−10 than those with the commonly used arginine-glycine-aspartic acid (RGD) peptide. Scaffold rigidity is an important biological cues that influence xi cell responses. However, a comparative study of rigidity on GST-III9−10 and RGD functionalized PEG hydrogels demonstrated that differences in rigidity could not account for differences in cell adhesion and spreading between RGD and GST-III9−10 functionalized PEG hydrogels. Thus as ECM analogues, GST-III9−10 functionalized hydrogels provide more robust biochemical cues than RGD functionalized hydrogels. Studies of PEG hydrogel composites with mixtures of III9−10 and a fibronectin binding domain demonstrated that biological responses of adhesion and spreading and extracellular matrix assembly could be controlled by varying the ratio of these two domains and the rigidity of the PEG hydrogels. FN was stabilized against proteolytic degradation by covalent attaching it to PEG or by PEGylating it. FN was first isolated from human plasma by gelatin affinity chromatography and then PEGylated using two methods. The first method is to PEGylate human plasma fibronectin (HPFN) at cysteine residues with 3.4 kDa PEG diacrylate. The second method is to PEGylate HPFN at lysine residues on the surface with 2-10 kDa PEG Succinimidyl carboxy methyl esters. Cysteine PEGylation of HPFN was first carried out because cysteines are concentrated in the amino- terminus of HPFN which leaves two-thirds of the molecule, including the cell-binding domain, unperturbed. PEGylation of HPFN on cysteines resulted in a molecule that supported cell adhesion, spreading, focal adhesion formation and cell migration in a comparable manner to native HPFN. Moreover, PEGylated HPFN was incorporated into the ECM in a similar manner to native HPFN when present in the culture media but not when coated on a surface indicating that PEGylation on cysteines modified some biological activity of HPFN. Additionally, HPFN PEGylated by this manner could not bind denatured collagen or gelatin. The gelatin-binding domain is at the site of cysteine PEGylation. The second approach for PEGylation of HPFN was through lysine residues xii on the surface of the protein. This approach was used because it targeted different amino acid residues in FN. The length of PEG and extent of PEGylation have been reported to influence biological activity of proteins. In the second approach, both PEG length and extent were varied. HPFN completely PEGylated on lysines residues was significantly more proteolytically stable than native HPFN but had reduced cell attachment and spreading. Furthermore, cell spreading and attachment on surfaces conjugated with this lysine PEGylated HPFN decreased with increasing PEG length. Partially PEGylated HPFN was synthesized by masking the cell and gelatin binding domains during PEGylation. The partially PEGylated HPFN supported cell adhesion and spreading in a similar manner to native HPFN and was more proteolytically stable. For the partially PEGylated HPFN, the size of PEG poly had no significant influence on the attachment and spreading of cells. These studies are the first attempt by any laboratory to stabilize FN against proteolytic degradation while retaining activity and show the feasibility of this approach as a potential therapeutic approach. The work presented here shows a two-prong approach by which the problem of ECM degradation and deficiency chronic wound healing can be addressed. The first approach for addressing ECM deficiency is through a scaffold design methodology. The novelty of the scaffold approach is that it uses the cell-binding domains of FN instead of the often-used RGD peptide. I demonstrate that a PEG hydrogel with the cell-binding domain produces a more robust biological response in cells than a PEG hydrogel with the RGD peptide. I also demonstrate that varying different functional domains of fibronectin can be used to controllably stimulate multiple biological responses. The second approach demonstrates a method by which FN, a key ECM protein, is stabilized against proteolytic degradation without perturbing its activity. These studies of creating PEG-FN conjugates are the first of their kind. Collectively, the data that I present in this thesis will lead to novel therapeutic methods for treating chronic wounds.
PH.D in Chemical Engineering, December 2012
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- Title
- TWO-LAYERED DEPTH ESTIMATION USING SEMI-GLOBAL MATCHING WITH MUTUAL INFORMATION
- Creator
- Zhang, Chen
- Date
- 2014, 2014-07
- Description
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Depth estimation plays an important role in three-dimensional computer vision area. Its recent development focuses on real-time application....
Show moreDepth estimation plays an important role in three-dimensional computer vision area. Its recent development focuses on real-time application. To be able to provide depth map for real-time applications like pedestrian detection and intelligent vehicles, three challenges must be overcome: 1. Real-time processing speed; 2. Insensitive to brightness change; 3. Clear boundaries and smooth surface. The thesis first describes the major steps of depth estimation, then many commonly used methods are reviewed. From them and other related real-time method, we found that the iteration based semi-global matching with mutual information has much potential to be improved. Based on that, the thesis proposed a method with two layers to provide depth map for pedestrian detection. The low resolution layer’s task is to produce a coarse depth map as quick as possible, then it helps to produce accurate mutual information distribution without iterations. The Full-resolution layer applies semi-global matching with two optional simplification schemes to speed up. The proposed method is implemented on both CPU and GPU. Experimental results and evaluation shows that it has great insensitivity to brightness changes and achieves real-time processing speed while maintaining a comparable performance with state-of-the-art real-time depth estimation methods.
M.S. in Electrical Engineering, May 2014
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- Title
- Exploiting contextual information for deep learning based object detection
- Creator
- Zhang, Chen
- Date
- 2020
- Description
-
Object detection has long been an important research topic in computer vision area. It forms the basis of many applications. Despite the great...
Show moreObject detection has long been an important research topic in computer vision area. It forms the basis of many applications. Despite the great progress made in recent years, object detection is still a challenging task. One of the keys to improving the performance of object detection is to utilize the contextual information from the image itself or from a video sequence. Contextual information is defined as the interrelated condition in which something exists or occurs. In object detection, such interrelated condition can be related background/surroundings, support from image segmentation task, and the existence of the object in the temporal domain for video-based object detection. In this thesis, we propose multiple methods to exploit contextual information to improve the performance of object detection from images and videos.First, we focus on exploiting spatial contextual information in still-image based object detection, where each image is treated independently. Our research focuses on extracting contextual information using different approaches, which includes recurrent convolutional layer with feature concatenation (RCL-FC), 3-D recurrent neural networks (3-D RNN), and location-aware deformable convolution. Second, we focus on exploiting pixel-level contextual information from a related computer vision task, namely image segmentation. Our research focuses on applying a weakly-supervised auxiliary multi-label segmentation network to improve the performance of object detection without increasing the inference time. Finally, we focus on video object detection, where the temporal contextual information between video frames are exploited. Our first research involves modeling short-term temporal contextual information using optical flow and modeling long-term temporal contextual information using convLSTM. Another research focuses on creating a two-path convLSTM pyramid to handle multi-scale temporal contextual information for dealing with the change in object's scale. Our last work is the event-aware convLSTM that forces convLSTM to learn about the event that causes the performance to drop in a video sequence.
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