Regulation of valve endothelial cell vasculogenic network architectures with ROCK and Rac inhibitors

Objective: The age- and disease-dependent presence of microvessels within heart valves is an understudied characteristic of these tissues. Neovascularization involves endothelial cell (EC) migration and cytoskeletal reorientation, which are heavily regulated by the Rho family of GTPases. Given that valve ECs demonstrate unique mesenchymal transdifferentiation and cytoskeletal mechanoresponsiveness, compared to vascular ECs, this study quantified the effect of inhibiting two members of the Rho family on vasculogenic network formation by valve ECs. Approach and results: A tubule-like structure vasculogenesis assay (assessing lacunarity, junction density, and vessel density) was performed with porcine aortic valve ECs treated with small molecule inhibitors of Rho-associated serine-threonine protein kinase (ROCK), Y-27632, or the Rac1 inhibitor, NSC-23766. Actin coordination, cell number, and cell migration were assessed through immunocytochemistry, MTT assay, and scratch wound healing assay. ROCK inhibition reduced network lacunarity and interrupted proper cell–cell adhesion and actin coordination. Rac1 inhibition increased lacunarity and delayed actin-mediated network formation. ROCK inhibition alone significantly inhibited migration, whereas both ROCK and Rac1 inhibition significantly reduced cell number over time compared to controls. Compared to a vascular EC line, the valve ECs generated a network with larger total vessel length, but a less smooth appearance. Conclusions: Both ROCK and Rac1 inhibition interfered with key processes in vascular network formation by valve ECs. This is the first report of manipulation of valve EC vasculogenic organization in response to small molecule inhibitors. Further study is warranted to comprehend this facet of valvular cell biology and pathology and how it differs from vascular biology

Computer-aided detection and diagnosis of breast cancer in 2D and 3D medical imaging through multifractal analysis

This Thesis describes the research work performed in the scope of a doctoral research program and presents its conclusions and contributions. The research activities were carried on in the industry with Siemens S.A. Healthcare Sector, in integration with a research team. Siemens S.A. Healthcare Sector is one of the world biggest suppliers of products, services and complete solutions in the medical sector. The company offers a wide selection of diagnostic and therapeutic equipment and information systems. Siemens products for medical imaging and in vivo diagnostics include: ultrasound, computer tomography, mammography, digital breast tomosynthesis, magnetic resonance, equipment to angiography and coronary angiography, nuclear imaging, and many others. Siemens has a vast experience in Healthcare and at the beginning of this project it was strategically interested in solutions to improve the detection of Breast Cancer, to increase its competitiveness in the sector. The company owns several patents related with self-similarity analysis, which formed the background of this Thesis. Furthermore, Siemens intended to explore commercially the computer- aided automatic detection and diagnosis eld for portfolio integration. Therefore, with the high knowledge acquired by University of Beira Interior in this area together with this Thesis, will allow Siemens to apply the most recent scienti c progress in the detection of the breast cancer, and it is foreseeable that together we can develop a new technology with high potential. The project resulted in the submission of two invention disclosures for evaluation in Siemens A.G., two articles published in peer-reviewed journals indexed in ISI Science Citation Index, two other articles submitted in peer-reviewed journals, and several international conference papers. This work on computer-aided-diagnosis in breast led to innovative software and novel processes of research and development, for which the project received the Siemens Innovation Award in 2012. It was very rewarding to carry on such technological and innovative project in a socially sensitive area as Breast Cancer.No cancro da mama a deteção precoce e o diagnóstico correto são de extrema importância na prescrição terapêutica e caz e e ciente, que potencie o aumento da taxa de sobrevivência à doença. A teoria multifractal foi inicialmente introduzida no contexto da análise de sinal e a sua utilidade foi demonstrada na descrição de comportamentos siológicos de bio-sinais e até na deteção e predição de patologias. Nesta Tese, três métodos multifractais foram estendidos para imagens bi-dimensionais (2D) e comparados na deteção de microcalci cações em mamogramas. Um destes métodos foi também adaptado para a classi cação de massas da mama, em cortes transversais 2D obtidos por ressonância magnética (RM) de mama, em grupos de massas provavelmente benignas e com suspeição de malignidade. Um novo método de análise multifractal usando a lacunaridade tri-dimensional (3D) foi proposto para classi cação de massas da mama em imagens volumétricas 3D de RM de mama. A análise multifractal revelou diferenças na complexidade subjacente às localizações das microcalci cações em relação aos tecidos normais, permitindo uma boa exatidão da sua deteção em mamogramas. Adicionalmente, foram extraídas por análise multifractal características dos tecidos que permitiram identi car os casos tipicamente recomendados para biópsia em imagens 2D de RM de mama. A análise multifractal 3D foi e caz na classi cação de lesões mamárias benignas e malignas em imagens 3D de RM de mama. Este método foi mais exato para esta classi cação do que o método 2D ou o método padrão de análise de contraste cinético tumoral. Em conclusão, a análise multifractal fornece informação útil para deteção auxiliada por computador em mamogra a e diagnóstico auxiliado por computador em imagens 2D e 3D de RM de mama, tendo o potencial de complementar a interpretação dos radiologistas

Computer-aided Image Processing of Angiogenic Histological

This article reviews the questions regarding the image evaluation of angiogeneic histological samples, particularly the ovarian epithelial cancer. Review is focused on the principles of image analysis in the field of histology and pathology. The definition, classification, pathogenesis and angiogenesis regulation in the ovaries are also briefly discussed. It is hoped that the complex image analysis together with the patient’s clinical parameters will allow an acquiring of a clear pathogenic picture of the disease, extension of the differential diagnosis and become a useful tool for the evaluation of drug effects. The challenge of the assessment of angiogenesis activity is the heterogeneity of several objects: parameters derived from patient’s anamnesis as well as of pathology samples. The other unresolved problems are the subjectivity of the region of interest selection and performance of the whole slide scanning

Immobilization of Cell-Adhesive Laminin Peptides in Degradable PEGDA Hydrogels Influences Endothelial Cell Tubulogenesis

Attachment, spreading, and organization of endothelial cells into tubule networks are mediated by interactions between cells in the extracellular microenvironment. Laminins are key extracellular matrix components and regulators of cell adhesion, migration, and proliferation. In this study, laminin-derived peptides were conjugated to poly(ethylene glycol) (PEG) monoacrylate and covalently incorporated into degradable PEG diacrylate (PEGDA) hydrogels to investigate the influence of these peptides on endothelial cellular adhesion and function in organizing into tubule networks. Degradable PEGDA hydrogels were synthesized by incorporating a matrix metalloproteinase (MMP)-sensitive peptide, GGGPQGIWGQGK (abbreviated PQ), into the polymer backbone. The secretion ofMMP-2 and MMP-9 by endothelial cells promotes polymer degradation and consequently cell migration. We demonstrate the formation of extensive networks of tubule-like structures by encapsulated human umbilical vein endothelial cells in hydrogels with immobilized synthetic peptides. The resulting structures were stabilized by pericyte precursor cells (10T1/2s) in vitro. During tubule formation and stabilization, extracellular matrix proteins such as collagen IV and laminin were deposited. Tubules formed in the matrix of metalloproteinase sensitive hydrogels were visualized from 7 days to 4 weeks in response to different combination of peptides. Moreover, hydrogels functionalized with laminin peptides and transplanted in a mouse cornea supported the ingrowth and attachment of endothelial cells to the hydrogel during angiogenesis. Results of this study illustrate the use of laminin-derived peptides as potential candidates for modification of biomaterials to support angiogenesis

FRACTAL DIMENSION AND LACUNARITY COMBINATION FOR PLANT LEAF CLASSIFICATION

Plants play important roles for the existence of all beings in the world. High diversity of plant’s species make a manual observation of plants classifying becomes very difficult. Fractal dimension is widely known feature descriptor for shape or texture. It is utilized to determine the complexity of an object in a form of fractional dimension. On the other hand, lacunarity is a feature descriptor that able to determine the heterogeneity of a texture image. Lacunarity was not really exploited in many fields. Moreover, there are no significant research on fractal dimension and lacunarity combination in the study of automatic plant’s leaf classification. In this paper, we focused on combination of fractal dimension and lacunarity features extraction to yield better classification result. A box counting method is implemented to get the fractal dimension feature of leaf boundary and vein. Meanwhile, a gliding box algorithm is implemented to get the lacunarity feature of leaf texture. Using 626 leaves from flavia, experiment was conducted by analyzing the performance of both feature vectors, while considering the optimal box size r. Using support vector machine classifier, result shows that combined features able to reach 93.92 % of classification accuracy

AGING, A PATHOLOGICAL FACTOR IN NEUROLOGICAL INJURY

One of the main reasons for CNS drugs to fail in clinical development is not considering age as a risk factor while studying chronic age-related neurological/neurodegenerative diseases in preclinical studies. We first set out to gain a comprehensive understanding of the impact of age on various aspects (anatomical, immunological, and biochemical) in rodents that play a key role in determining the onset, progression, and evolution of disease severity. With advancing age, the vascular structure and function are compromised which is hypothesized to accelerate cognitive decline. The initial step toward developing novel therapeutics is to characterize the age-related vascular modifications. Utilizing a vessel painting technique, we labelled the surface cortical vessels of young and aged Sprague-Dawley rats and analyzed for classical angiographic features (junctions, lengths, end points, density, etc). We found significant decrease in vascular components while vascular complexity and lacunarity were significantly increased in the aged brain compared to young brain. These age-dependent changes were prominent at the level of right and left middle cerebral artery (MCA) as well as on a global scale. Next, we investigated the changes on the peripheral immune response following lipopolysaccharide (LPS) induced acute systemic inflammation in young and aged Sprague Dawley rats. We observed age-related immunosuppression in the splenic leukocytes indicative of reduced ability of the spleen to retain the immune cells. We also found dysregulated cytokine/chemokine expression in the plasma following LPS stimulation in aged and young animals. Interestingly, we noticed significant increase in circulatory neutrophil population in the aged animals compared to young animals in response to LPS at 24h. Taken together, these studies confirm the presence of age-related modifications in the vasculature as well as immune system suggesting altered response to injury/infection and thus emphasizing the need to utilize age-appropriate models when studying diseases of the elderly. Lastly, we wanted to test the therapeutic effect of a novel agent in case of brain injury model in aged rodents. Previous studies by our lab and others have showed that targeting mitoNEET using NL-1 was neuroprotective following brain injury models. We wanted to investigate if administration of NL-1 could improve functional outcomes following stroke in an aged rodent model of cerebral ischemia reperfusion injury. We found significant decrease in infarct volume and edema index at 24h post stroke. We also saw enhanced survival and reduced behavior deficits. Moreover, we showed improved BBB integrity, reduced oxidative stress and apoptosis at 72h post stroke. Interestingly, PLGA encapsulated NL-1 at 0.25mg/kg (which is 40-fold lesser dose than NL-1 at 10mg/kg) produced better therapeutic effects. Future studies should focus on understanding the mechanism underlying the biology of aging thus enabling the development of novel therapeutic targets for neurological disorders/diseases

Tailoring vessel morphology in vivo

Tissue engineering is a rapidly growing field which seeks to provide alternatives to organ transplantation in order to address the increasing need for transplantable tissues. One huge hurdle in this effort is the provision of thick tissues; this hurdle exists because currently there is no way to provide prevascularized or rapidly vascularizable scaffolds. To design thick, vascularized tissues, scaffolds are needed that can induce vessels which are similar to the microvasculature found in normal tissues. Angiogenic biomaterials are being developed to provide useful scaffolds to address this problem. In this thesis angiogenic and cell signaling and adhesion factors were incorporated into a biomimetic poly(ethylene glycol) (PEG) hydrogel system. The composition of these hydrogels was precisely tuned to induce the formation of differing vessel morphology. To sensitively measure induced microvascular morphology and to compare it to native microvessels in several tissues, this thesis developed an image-based tool for quantification of scale invariant and classical measures of vessel morphology. The tool displayed great utility in the comparison of native vessels and remodeling vessels in normal tissues. To utilize this tool to tune the vessel response in vivo , Flk1::myr-mCherry fluorescently labeled mice were implanted with Platelet Derived Growth Factor-BB (PDGF-BB) and basic Fibroblast Growth Factor (FGF-2) containing PEG-based hydrogels in a modified mouse corneal angiogenesis assay. Resulting vessels were imaged with confocal microscopy, analyzed with the image based tool created in this thesis to compare morphological differences between treatment groups, and used to create a linear relationship between space filling parameters and dose of growth factor release. Morphological parameters of native mouse tissue vessels were then compared to the linear fit to calculate the dose of growth factors needed to induce vessels similar in morphology to native vessels. Resulting induced vessels did match in morphology to the target vessels. Several other covalently bound signals were then analyzed in the assay and resulting morphology of vessels was compared in several studies which further highlighted the utility of the micropocket assay in conjunction with the image based tool for vessel morphological quantification. Finally, an alternative method to provide rapid vasculature to the constructs, which relied on pre-seeded hydrogels encapsulated endothelial cells was also developed and shown to allow anastamosis between induced host vessels and the implanted construct within 48 hours. These results indicate great promise in the rational design of synthetic, bioactive hydrogels, which can be used as a platform to study microvascular induction for regenerative medicine and angiogenesis research. Future applications of this research may help to develop therapeutic strategies to ameliorate human disease by replacing organs or correcting vessel morphology in the case of ischemic diseases and cancer

Lacunarity as a quantitative measure of mixing—a micro-CT analysis-based case study on granular materials

In practically every industry, mixing is a fundamental process, yet its 3D analysis is scarce in the literature. High-resolution computed tomography (micro-CT) is the perfect X-ray imaging tool to investigate the mixing of granular materials. Other than qualitative analysis, 3D micro-CT images provide an opportunity for quantitative analysis, which is of utmost importance, in terms of efficiency (time and budget), and environmental impact of the mixing process. In this work, lacunarity is proposed as a measure of mixing. By the lacunarity calculation on the repeated micro-CT measurements, a temporal description of the mixing can be given in three dimensions. As opposed to traditional mixing indices, the lacunarity curve provides additional information regarding the spatial distribution of the grains. Discrete element method simulations were also performed and showed similar results to the experiments