Therapeutic Properties of Superoxide Dismutase 3 and Mesenchymal Stromal Cells in Peripheral Ischemia

The aim of this study was to characterize the cellular mechanisms leading to the beneficial effect of anti-oxidative gene therapy and pro-angiogenic stem cell therapy in acute peripheral ischemia. Post-ischemic events aim to re-establish tissue blood perfusion, to clear cellular debris, and to regenerate lost tissue by differentiation of satellite cells into myoblasts. Although leukocytes have an essential role in clearing cellular debris and promoting angiogenesis, they also contribute to tissue injury through excessive ROS production. First, we investigated the therapeutic properties of extracellular superoxide dismutase (SOD3) gene transfer. SOD3 was shown to reduce oxidative stress, to normalize glucose metabolism, and to enhance cell proliferation in the ischemic muscle. Analysis of the mitogenic Ras-Erk1/2 pathway showed SOD3 mediated induction offering a plausible explanation for enhanced cell proliferation. In addition, SOD3 reduced NF-κB activity by enhancing IκBα expression thus leading to reduced expression of inflammatory cytokines and adhesion molecules with consequent reduction in macrophage infiltration. Secondly, we sought to determine the fate and the effect of locally transplanted mesenchymal stem/stromal cells (MSCs) in acute ischemia. We showed that a vast majority of the transplanted cells are cleared from the injury site within 24 hours after local transplantation. Despite rapid clearance, transplantation was able to temporarily promote angiogenesis and cell proliferation in the muscle. Lack of graft-derived growth factor expression suggests other than secretory function to mediate this observed effect. In conclusion, both SOD3 and MSCs could be utilized to alleviate peripheral ischemia induced tissue injury. We have described a previously unidentified growth regulatory role for SOD3, and suggest a novel mechanism whereby transplanted MSCs enhance the reparative potential of the recipient tissue through physical contacts.

Local Binary Patterns in Focal-Plane Processing. Analysis and Applications

Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented

The effect of focal point parameters in fiber laser welding of structural steel

In this thesis the effect of focal point parameters in fiber laser welding of structural steel is studied. The goal is to establish relations between laser power, focal point diameter and focal point position with the resulting quality, weld-bead geometry and hardness of the welds. In the laboratory experiments, AB AH36 shipbuilding steel was welded in an I-butt joint configuration using IPG YLS-10000 continuous wave fiber laser. The quality of the welds produced were evaluated based on standard SFS-EN ISO 13919-1. The weld-bead geometry was defined from the weld cross-sections and Vickers hardness test was used to measure hardness's from the middle of the cross-sections. It was shown that all the studied focal point parameters have an effect on the quality, weld-bead geometry and hardness of the welds produced.