Optogenetics: Background, Methodological Advances and Potential Applications for Cardiovascular Research and Medicine

Optogenetics is an elegant approach of precisely controlling and monitoring the biological functions of a cell, group of cells, tissues, or organs with high temporal and spatial resolution by using optical system and genetic engineering technologies. The field evolved with the need to precisely control neurons and decipher neural circuity and has made great accomplishments in neuroscience. It also evolved in cardiovascular research almost a decade ago and has made considerable progress in both in vitro and in vivo animal studies. Thus, this review is written with an objective to provide information on the evolution, background, methodical advances, and potential scope of the field for cardiovascular research and medicine. We begin with a review of literatures on optogenetic proteins related to their origin, structure, types, mechanism of action, methods to improve their performance, and the delivery vehicles and methods to express such proteins on target cells and tissues for cardiovascular research. Next, we reviewed historical and recent literatures to demonstrate the scope of optogenetics for cardiovascular research and regenerative medicine and examined that cardiac optogenetics is vital in mimicking heart diseases, understanding the mechanisms of disease progression and also in introducing novel therapies to treat cardiac abnormalities, such as arrhythmias. We also reviewed optogenetics as promising tools in providing high-throughput data for cardiotoxicity screening in drug development and also in deciphering dynamic roles of signaling moieties in cell signaling. Finally, we put forth considerations on the need of scaling up of the optogenetic system, clinically relevant in vivo and in silico models, light attenuation issues, and concerns over the level, immune reactions, toxicity, and ectopic expression with opsin expression. Detailed investigations on such considerations would accelerate the translation of cardiac optogenetics from present in vitro and in vivo animal studies to clinical therapies

Encapsulation of implantable microsensors

Heart function monitoring by attaching an accelerometer directly to the heart ventricle has been established as an effective way of diagnosing ischemia. The method holds a number of advantages over conventional monitoring techniques: high specificity and accuracy surpassing that of electrocardiography, and the ability to conduct non-stop monitoring unlike x-ray imaging. To this date, the drawback has been that the accelerometer-based devices have been too large to be used in the postoperative period, when the patient’s chest is closed. This period is of great interest.The PhD project has focused on developing a heart monitoring device intended to be used on patients recovering from a Coronary Artery Bypass Graft. The device is intended to be used during surgery and for the subsequent recovery period (3-5 days). The project has employed commercial 3-axis accelerometers.This PhD project has contributed to four different generations of devices, each one featuring incremental improvements. The first generation validated the concept, the second outlined the form factor of the device, and the third added extra functionality and revised the form of the implant. The fourth generation device also featured a newer, more compact sensor, which in turn, allowed to further miniaturize the device and evaluate different implant shapes. This evolutionary approach allowed us to formulate testing methodology for the devices. The latest generation devices underwent tests of: leakage current according to IEC60601 standard (current below 0.01 mA), including after cyclical loading of the capsule-cable joint, pull-out force measurements, implant stability evaluation that yielded tilt of no more than 4 degrees

Cyclic Nucleotide Signaling and the Cardiovascular System

The cyclic nucleotides 3',5'-adenosine monophosphate (cAMP) and 3',5'-cyclic guanosine monophosphate (cGMP) play important roles in the control of cardiovascular function under physiological and pathological conditions. In this book, which is a reprint of a Special Issue of the Journal of Cardiovascular Development and Disease entitled "Cyclic Nucleotide Signaling and the Cardiovascular System", internationally recognized experts give an overview of this vibrant scientific field. The first series of articles deal with the localization and function of membrane-bound and soluble adenylate cyclases, followed by articles on the roles of phosphodiesterase isoforms in the heart. Cyclic nucleotide signaling takes place in nanodomains and the A-kinase anchor proteins (AKAPS) are essential for the compartmentalized assembly of signaling proteins into functional complexes. Reviews on the role of AKAP proteins in the physiology and pathophysiology of the heart are also included in this book. Cyclic nucleotides act through effector proteins and articles on EPAC and POPDC proteins inform the reader of recent developments on these topics. A major advancement in our understanding of cyclic nucleotide signaling came through the use of genetically encoded cAMP sensor molecules, and a series of articles review the current insight that these reporter molecules have provided. The final set of articles in this book deals with the association of the cyclic nucleotide pathway and cardiovascular disease as well as the development of novel therapeutic approaches. Thomas Brand and Enno Klussmann Special Issue Editor

Learning Theory and Approximation

The main goal of this workshop – the third one of this type at the MFO – has been to blend mathematical results from statistical learning theory and approximation theory to strengthen both disciplines and use synergistic effects to work on current research questions. Learning theory aims at modeling unknown function relations and data structures from samples in an automatic manner. Approximation theory is naturally used for the advancement and closely connected to the further development of learning theory, in particular for the exploration of new useful algorithms, and for the theoretical understanding of existing methods. Conversely, the study of learning theory also gives rise to interesting theoretical problems for approximation theory such as the approximation and sparse representation of functions or the construction of rich kernel reproducing Hilbert spaces on general metric spaces. This workshop has concentrated on the following recent topics: Pitchfork bifurcation of dynamical systems arising from mathematical foundations of cell development; regularized kernel based learning in the Big Data situation; deep learning; convergence rates of learning and online learning algorithms; numerical refinement algorithms to learning; statistical robustness of regularized kernel based learning

Medical Image Segmentation by Deep Convolutional Neural Networks

Medical image segmentation is a fundamental and critical step for medical image analysis. Due to the complexity and diversity of medical images, the segmentation of medical images continues to be a challenging problem. Recently, deep learning techniques, especially Convolution Neural Networks (CNNs) have received extensive research and achieve great success in many vision tasks. Specifically, with the advent of Fully Convolutional Networks (FCNs), automatic medical image segmentation based on FCNs is a promising research field. This thesis focuses on two medical image segmentation tasks: lung segmentation in chest X-ray images and nuclei segmentation in histopathological images. For the lung segmentation task, we investigate several FCNs that have been successful in semantic and medical image segmentation. We evaluate the performance of these different FCNs on three publicly available chest X-ray image datasets. For the nuclei segmentation task, since the challenges of this task are difficulty in segmenting the small, overlapping and touching nuclei, and limited ability of generalization to nuclei in different organs and tissue types, we propose a novel nuclei segmentation approach based on a two-stage learning framework and Deep Layer Aggregation (DLA). We convert the original binary segmentation task into a two-step task by adding nuclei-boundary prediction (3-classes) as an intermediate step. To solve our two-step task, we design a two-stage learning framework by stacking two U-Nets. The first stage estimates nuclei and their coarse boundaries while the second stage outputs the final fine-grained segmentation map. Furthermore, we also extend the U-Nets with DLA by iteratively merging features across different levels. We evaluate our proposed method on two public diverse nuclei datasets. The experimental results show that our proposed approach outperforms many standard segmentation architectures and recently proposed nuclei segmentation methods, and can be easily generalized across different cell types in various organs

Analysis of bacterial biofilms using NMR-based metabolomics

Infectious diseases can be difficult to cure, especially if the pathogen forms a biofilm. After decades of extensive research into the morphology, physiology and genomics of biofilm formation, attention has recently been directed toward the analysis of the cellular metabolome in order to understand the transformation of a planktonic cell to a biofilm. Metabolomics can play an invaluable role in enhancing our understanding of the underlying biological processes related to the structure, formation and antibiotic resistance of biofilms. A systematic view of metabolic pathways or processes responsible for regulating this ‘social structure’ of microorganisms may provide critical insights into biofilm-related drug resistance and lead to novel treatments. This review will discuss the development of NMR-based metabolomics as a technology to study medically relevant biofilms. Recent advancements from case studies reviewed in this manuscript have shown the potential of metabolomics to shed light on numerous biological problems related to biofilms

Analysis of bacterial biofilms using NMR-based metabolomics

Infectious diseases can be difficult to cure, especially if the pathogen forms a biofilm. After decades of extensive research into the morphology, physiology and genomics of biofilm formation, attention has recently been directed toward the analysis of the cellular metabolome in order to understand the transformation of a planktonic cell to a biofilm. Metabolomics can play an invaluable role in enhancing our understanding of the underlying biological processes related to the structure, formation and antibiotic resistance of biofilms. A systematic view of metabolic pathways or processes responsible for regulating this ‘social structure’ of microorganisms may provide critical insights into biofilm-related drug resistance and lead to novel treatments. This review will discuss the development of NMR-based metabolomics as a technology to study medically relevant biofilms. Recent advancements from case studies reviewed in this manuscript have shown the potential of metabolomics to shed light on numerous biological problems related to biofilms

An approach to develop sustainable medical devices

Tese de doutoramento BioengenhariaThe development and commercialization of contemporary Medical Devices is inherently of a multidisciplinary nature. Consequently, they have to undergo a stringent regulatory compliance procedure in conformity with an ever increasingly fierce and competitive business environment. Throughout the product life cycle, medical devices would significantly consume renewable as well as non-renewable resources and as a result exert a substantial social, economic and environmental impact(s). Accordingly, it is imperative to consider the criteria of the aforementioned domains of sustainability in the initial phases of product development. The proposed conceptual multifaceted framework comprehensively explores a broader scope of sustainable product development, mainly from the pragmatic standpoint of systems engineering in comparison to the contemporary evaluation and development approaches. The underpinnings of the proposed framework encompasses the critical role of a decision model titled ‘Multi Criteria Hierarchical Model (MCHM)’ which is in fact an extensive revision of the Analytical Hierarchy Process decision modelling approach. The MCHM contains three tiers of pertinent criteria to attain overall sustainability. The structure of MCHM illustrates the tolerable level of sustainability in Tier 1, which is non-negotiable and compulsory, and the additional degrees of sustainability that increases from Tier 2 to Tier 3. Furthermore, the proposed framework elucidates the active participation of the MCHM in product design and development by conjoining with a wide spectrum of technical and conceptual tools. The research methodologies in the thesis are comprised of interviews, questionnaires and case studies that mainly involved active participatory observation. The objective of incorporating case studies in the thesis is to evaluate the effectiveness of the MCHM in an Industrial environment. In this doctoral research the contemporary medical devices explored during the case studies included a wide spectrum of materials and technologies that range from metal and non-metal prosthesis (external and sometimes internal), instruments, advanced implantable devices and biodegradable scaffolds used in regenerative medicine. The research activities commenced with a thorough literature review that directed the researcher to the need for an exploratory study, accomplished by interviews with experts from academia and industry. These experts provided their feedback on the Sustainability related criteria outlined in the MCHM based on their expertise and knowledge of product development in diverse economic circumstances. The feedback was obtained in the form of assigning numerical scores during pair-wise comparison between two criteria at a time. The scores and recommendations were documented for being incorporated within the case studies. In the case studies, the MCHM was incorporated in the early stage of product development to prioritize bare minimum environmental sustainability and profitability in accordance with regulatory compliance. During the decision making process, the product design was investigated in order to simultaneously accomplish the aforementioned facets by way of incorporating the expert recommendations. Furthermore, these expert recommendations obtained in conjunction with business strategies and technical problem solving techniques, such as Case based Reasoning (CBR), Design by Analogy (DA) and Theory of Inventive Problem Solving (TRIZ) were considered for resolving conflicts between the criteria of Tier 1 and other Tiers. The thesis provides decision makers and the product development teams with a framework to gain a more holistic perspective on sustainable product development with respect to policies, technical/non-technical tools and business strategies. The goal is to enable these product development teams to implement pragmatic solutions for ensuring long-term competitiveness and the welfare of the Stakeholders.O desenvolvimento e comercialização de dispositivos médicos contemporâneos é por inerência de natureza multidisciplinar. Consequentemente, estes dispositivos têm que passar por um procedimento de regulamentação rigoroso, num ambiente de negócios cada vez cada vez mais acirrado e competitivo. Durante o ciclo de vida do produto, os dispositivos médicos consomem recursos renováveis, bem como recursos não-renováveis, o que origina impactos sociais, económicos e ambientais significativos. Assim, é imperativo considerar as diferentes dimensões da sustentabilidade nas fases iniciais de desenvolvimento do produto. O modelo conceptual proposto explora exaustivamente um propósito mais amplo de desenvolvimento de produtos sustentáveis, principalmente do ponto de vista pragmático da engenharia de sistemas, em comparação com a avaliação e abordagem contemporânea de desenvolvimento de novos produtos. A abordagem proposta suporta-se no modelo de apoio à decisão intitulado Multi Criteria Hierarchy Model (MCHM), que é uma extensão do modelo Analytical Hierarchy Process (AHP). O MCHM contém três níveis de critérios relevantes para alcançar a sustentabilidade global. A estrutura do MCHM reflete o que é obrigatório e não negociável no nível 1, e ainda a importância crescente dos critérios de sustentabilidade do nível 2 para o nível 3. Além disso, o modelo proposto demonstra a relevância da inclusão do MCHM no design e desenvolvimento do produto em conjunção com um amplo espectro de ferramentas técnicas e conceptuais. As metodologias de investigação incluem entrevistas, questionários e estudo de casos que envolveram, principalmente, a observação ativa. A realização de estudos de caso teve como objetivo avaliar a adequação do MCHM em ambiente industrial. Os dispositivos médicos considerados durante o estudo de casos incluíram uma diversidade de materiais e tecnologias que vão desde próteses metálicas e não-metálicas (externas e internas), instrumentos, implantes e suportes poliméricos biodegradáveis usados em medicina regenerativa. A revisão bibliográfica identificou a necessidade de desenvolver um estudo exploratório, suportado em entrevistas a peritos académicos e industriais. Estes peritos apresentaram a sua opinião relativa aos critérios considerados no MCHM, de acordo com a sua experiência e conhecimento sobre o desenvolvimento de produtos em circunstâncias económicas diversas. A comparação par a par dos critérios permitiu avaliar a sua importância relativa. Os resultados das entrevistas foram documentados para serem incorporados nos estudos de caso. Nos estudos de caso, o MCHM foi incorporado na fase inicial do desenvolvimento de novos produtos para garantir sustentabilidade ambiental e rentabilidade, em concordância com da regulamentação em vigor. Durante o processo de tomada de decisão, o design do produto foi analisado de modo a cumprir simultaneamente os aspetos acima mencionados e incorporar as recomendações dos peritos. Além disso, estas recomendações foram consideradas em conjunto com as estratégias de negócio e técnicas de resolução de problemas técnicos, tais como o Case Based Reasoning (CBR), Design by Analogy (DA) e Theory of Inventive Problem Solving (TRIZ) para a resolução de conflitos entre os critérios do nível 1 e dos outros níveis. A tese proporciona aos decisores e às equipas de desenvolvimento de novos produtos um modelo para obter uma perspectiva mais holística sobre o desenvolvimento de produtos sustentáveis, relativamente às políticas, ferramentas técnicas/não-técnicas e estratégias de negócio. O objetivo é capacitar essas equipas de desenvolvimento de novos produtos para implementar soluções pragmáticas que assegurem a competitividade a longo prazo e o bem-estar dos stakeholders