205 research outputs found

    3-D lung deformation and function from respiratory-gated 4-D x-ray CT images : application to radiation treatment planning.

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    Many lung diseases or injuries can cause biomechanical or material property changes that can alter lung function. While the mechanical changes associated with the change of the material properties originate at a regional level, they remain largely asymptomatic and are invisible to global measures of lung function until they have advanced significantly and have aggregated. In the realm of external beam radiation therapy of patients suffering from lung cancer, determination of patterns of pre- and post-treatment motion, and measures of regional and global lung elasticity and function are clinically relevant. In this dissertation, we demonstrate that 4-D CT derived ventilation images, including mechanical strain, provide an accurate and physiologically relevant assessment of regional pulmonary function which may be incorporated into the treatment planning process. Our contributions are as follows: (i) A new volumetric deformable image registration technique based on 3-D optical flow (MOFID) has been designed and implemented which permits the possibility of enforcing physical constraints on the numerical solutions for computing motion field from respiratory-gated 4-D CT thoracic images. The proposed optical flow framework is an accurate motion model for the thoracic CT registration problem. (ii) A large displacement landmark-base elastic registration method has been devised for thoracic CT volumetric image sets containing large deformations or changes, as encountered for example in registration of pre-treatment and post-treatment images or multi-modality registration. (iii) Based on deformation maps from MOFIO, a novel framework for regional quantification of mechanical strain as an index of lung functionality has been formulated for measurement of regional pulmonary function. (iv) In a cohort consisting of seven patients with non-small cell lung cancer, validation of physiologic accuracy of the 4-0 CT derived quantitative images including Jacobian metric of ventilation, Vjac, and principal strains, (V?1, V?2, V?3, has been performed through correlation of the derived measures with SPECT ventilation and perfusion scans. The statistical correlations with SPECT have shown that the maximum principal strain pulmonary function map derived from MOFIO, outperforms all previously established ventilation metrics from 40-CT. It is hypothesized that use of CT -derived ventilation images in the treatment planning process will help predict and prevent pulmonary toxicity due to radiation treatment. It is also hypothesized that measures of regional and global lung elasticity and function obtained during the course of treatment may be used to adapt radiation treatment. Having objective methods with which to assess pre-treatment global and regional lung function and biomechanical properties, the radiation treatment dose can potentially be escalated to improve tumor response and local control

    Biologically-informed neural networks guide mechanistic modeling from sparse experimental data

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    Biologically-informed neural networks (BINNs), an extension of physics-informed neural networks [1], are introduced and used to discover the underlying dynamics of biological systems from sparse experimental data. In the present work, BINNs are trained in a supervised learning framework to approximate in vitro cell biology assay experiments while respecting a generalized form of the governing reaction-diffusion partial differential equation (PDE). By allowing the diffusion and reaction terms to be multilayer perceptrons (MLPs), the nonlinear forms of these terms can be learned while simultaneously converging to the solution of the governing PDE. Further, the trained MLPs are used to guide the selection of biologically interpretable mechanistic forms of the PDE terms which provides new insights into the biological and physical mechanisms that govern the dynamics of the observed system. The method is evaluated on sparse real-world data from wound healing assays with varying initial cell densities [2]

    2016 IMSAloquium, Student Investigation Showcase

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    Welcome to the twenty-eighth year of the Student Inquiry and Research Program (SIR)! This is a program that is as old as IMSA. The SIR program represents our unending dedication to enabling our students to learn what it is to be an innovator and to make contributions to what is known on Earth.https://digitalcommons.imsa.edu/archives_sir/1026/thumbnail.jp

    Mathematical models for glioma growh and migration inside the brain

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    284 p.Los gliomas forman el subtipo más prevalente, agresivo e invasivo de tumores cerebrales primarios,caracterizados por una rápida proliferación celular y una elevada capacidad de infiltración. A pesar de los avances de la investigación clínica, estos tumores suelen ser resistentes al tratamiento; la supervivencia media oscila entre 9 y 12 meses, siendo la recurrencia la principal causa de mortalidad.La migración y la invasión de los gliomas en el cerebro son fenómenos complejos y aún se desconocen varios de los mecanismos subyacentes que guían la progresión de estos tumores.En esta tesis, proponemos varios modelos matemáticos para estudiar diversos aspectos de la progresión del glioma en relación con las escalas microscópicas y macroscópicas que caracterizan este proceso. Considerar el carácter intrínsico multiescala de la evolución del glioma permite definir modelos basados en sistemas dinámicos, ecuaciones cinéticas y EDP macroscópicas con diferentes roles dependiendo de los fenómenos a estudiar. Uno de los objetivos principales de esta tesis es integrar datos biológicos y clínicos con los modelos matemáticos. Los datos experimentales utilizados se han obtenido de imágenes por resonancia magnética, de imágenes con tensor de difusión del cerebro humano y de análisis de inmunofluorescencia in vivo de distribuciones de varias proteínas en Drosophila, un modelo fiable para el estudio de la dinámica del glioblastoma.Analizamos las características de anisotropía del tejido nervioso, utilizando los datos del tensor de difusión, y la influencia de la estructura de las fibras en la dinámica de las células tumorales.Mostramos cómo la red de fibras guía la migración celular a lo largo de rutas preferenciales,reproduciendo los patrones ramificados y heterogéneos típicos de la evolución del glioma; asimismo,demostramos cómo los tratamientos multimodales pueden reducir este comportamiento.Estudiamos la interdependencia entre la acidez del microambiente y la vascularización en el proceso de angiogénesis tumoral. Para ello, construimos un modelo capaz de reproducir la influencia de estos mecanismos en el desarrollo de la heterogeneidad intratumoral y de características típicas de la progresión del glioma relacionadas con la hipoxia (e.g. la necrosis). Este estudio permite formular una clasificación de los tumores basada en el nivel de necrosis, así como la investigación de terapias multimodales que incluyan efectos antiangiogénicos.Investigamos la influencia de las protrusiones celulares desde una perspectiva no local.Analizamos su rol en el fenómeno de la guía por contacto y en la manifestación de efectos colaborativos o competitivos entre dos estímulos que determinan cambios de dirección de la velocidad celular.Utilizando el análisis experimental de las distribuciones de varias proteínas, evaluamos la relación de las protrusiones celulares con las integrinas y las proteasas como principales mecanismos de progresión del glioblastoma. Mostramos cómo las interacciones bioquímicas y biomecánicas de estos agentes dan como resultado el desarrollo de frentes de propagación tumoral, que pueden presentar una evolución dinámica y heterogénea en relación a los cambios ambientales.bcam:basque center for applied mathematics; La Caixa Foundatio

    Optimizing T Cell Manufacturing and Quality Using Functionalized Degradable Microscaffolds

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    Adoptive cell therapy using chimeric antigen receptor (CAR) T cells have shown promise in treating cancer, but manufacturing large numbers of high quality cells remains challenging. Currently approved T cell expansion technologies involve anti-CD3 and anti-CD28 antibodies, usually mounted on magnetic beads. This method fails to recapitulate many key signals found in vivo and is also heavily licensed by a few companies, limiting its long-term usefulness to manufactures and clinicians. Furthermore, highly potent, anti-tumor T cells are generally less-differentiated subtypes such as central memory and stem memory T cells. Despite this understanding, little has been done to optimize T cell expansion for generating these subtypes, including measurement and feedback control strategies that are necessary for any modern manufacturing process. The goal of this dissertation was to develop a microcarrier-based degradable microscaffold (DMS) T cell expansion system and determine biologically-meaningful critical quality attitudes and critical process parameters that could be used to optimize for highly-potent T cells. We developed and characterized the DMS system, including quality control steps. We also demonstrated the feasibility of expanding high-quality T cells. We used Design of Experiments methodology to optimize the DMS platform, and we developed a computational pipeline to identify and model the effects of measurable critical quality attributes and critical process parameters on the final product. Finally, we demonstrated the effectiveness of the DMS platform in vivo. This thesis lays the groundwork for a novel T cell expansion method which can be utilized at scale for clinical trials and beyond.Ph.D

    Anisotropy Across Fields and Scales

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    This open access book focuses on processing, modeling, and visualization of anisotropy information, which are often addressed by employing sophisticated mathematical constructs such as tensors and other higher-order descriptors. It also discusses adaptations of such constructs to problems encountered in seemingly dissimilar areas of medical imaging, physical sciences, and engineering. Featuring original research contributions as well as insightful reviews for scientists interested in handling anisotropy information, it covers topics such as pertinent geometric and algebraic properties of tensors and tensor fields, challenges faced in processing and visualizing different types of data, statistical techniques for data processing, and specific applications like mapping white-matter fiber tracts in the brain. The book helps readers grasp the current challenges in the field and provides information on the techniques devised to address them. Further, it facilitates the transfer of knowledge between different disciplines in order to advance the research frontiers in these areas. This multidisciplinary book presents, in part, the outcomes of the seventh in a series of Dagstuhl seminars devoted to visualization and processing of tensor fields and higher-order descriptors, which was held in Dagstuhl, Germany, on October 28–November 2, 2018

    Mathematical models for glioma growth and migration inside the brain

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    Gliomas are the most prevalent, aggressive, and invasive subtype of primary brain tumors, characterized by rapid cell proliferation and great infiltration capacity. De- spite the advances of clinical research, these tumors are often resistant to treatment, the median survival ranges between 9 and 12 months, and recurrence is the main cause of mortality. Glioma migration and invasion into the brain tissue is a complex phenomenon and little is still known about the underlying mechanisms that lead to tumor progression. In this thesis, we propose several mathematical models studying various aspects of glioma progression in relation to the microscopic and macroscopic scales charac- terizing this process. Exploiting the inherently multiscale nature of glioma evolution allows to define models based on dynamical systems, kinetic equations, and macro- scopic PDEs with different roles depending on the considered phenomena. The in- tegration of biological and clinical data with the mathematical models is one of the key objectives of this thesis. The experimental data at hand are obtained from mag- netic resonance and diffusion tensor images of the human brain and from in-vivo im- munofluorescence analysis of protein distributions in Drosophila, a reliable model for the study of glioblastoma dynamics. We analyze the anisotropic characteristics of the brain tissue, using the diffusion tensor data, and the influence of the fiber structures on tumor cell dynamics. We show how the fiber network directs cell migration along preferential paths, reproducing the branched and heterogeneous patterns typical of glioma evolution, and how multi- modal treatments can reduce this behavior. We study the interdependency of microenvironmental acidity and vasculature in tumor angiogenesis, defining a model capable of reproducing their influence on the emergence of phenotypic heterogeneity and hypoxia-related features (like necrosis) typical of glioma progression. This study enables the testing of a necrosis-based tumor grading and the investigation of multi-modal therapies with anti-angiogenic effects. We investigated the role of cell protrusions from a non-local perspective. We ex- plore their influence on the contact guidance phenomenon and on the emergence of collaborative or competitive effects between two cues driving cell velocity changes. Using the experimental analysis of protein distributions, we evaluate cell protru- sion relationship with integrins and proteases as leading mechanisms of glioblastoma progression. We show how the biochemical and biomechanical interactions of these agents result in the emergence of tumor propagation fronts, which can feature a dy- namical and heterogenous evolution in relation to environmental changes.European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 713673. ”la Caixa” Foundation (ID 100010434), with fellowship code LCF/BQ/IN17/11620056

    Mathematical models for glioma growh and migration inside the brain

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    284 p.Los gliomas forman el subtipo más prevalente, agresivo e invasivo de tumores cerebrales primarios,caracterizados por una rápida proliferación celular y una elevada capacidad de infiltración. A pesar de los avances de la investigación clínica, estos tumores suelen ser resistentes al tratamiento; la supervivencia media oscila entre 9 y 12 meses, siendo la recurrencia la principal causa de mortalidad.La migración y la invasión de los gliomas en el cerebro son fenómenos complejos y aún se desconocen varios de los mecanismos subyacentes que guían la progresión de estos tumores.En esta tesis, proponemos varios modelos matemáticos para estudiar diversos aspectos de la progresión del glioma en relación con las escalas microscópicas y macroscópicas que caracterizan este proceso. Considerar el carácter intrínsico multiescala de la evolución del glioma permite definir modelos basados en sistemas dinámicos, ecuaciones cinéticas y EDP macroscópicas con diferentes roles dependiendo de los fenómenos a estudiar. Uno de los objetivos principales de esta tesis es integrar datos biológicos y clínicos con los modelos matemáticos. Los datos experimentales utilizados se han obtenido de imágenes por resonancia magnética, de imágenes con tensor de difusión del cerebro humano y de análisis de inmunofluorescencia in vivo de distribuciones de varias proteínas en Drosophila, un modelo fiable para el estudio de la dinámica del glioblastoma.Analizamos las características de anisotropía del tejido nervioso, utilizando los datos del tensor de difusión, y la influencia de la estructura de las fibras en la dinámica de las células tumorales.Mostramos cómo la red de fibras guía la migración celular a lo largo de rutas preferenciales,reproduciendo los patrones ramificados y heterogéneos típicos de la evolución del glioma; asimismo,demostramos cómo los tratamientos multimodales pueden reducir este comportamiento.Estudiamos la interdependencia entre la acidez del microambiente y la vascularización en el proceso de angiogénesis tumoral. Para ello, construimos un modelo capaz de reproducir la influencia de estos mecanismos en el desarrollo de la heterogeneidad intratumoral y de características típicas de la progresión del glioma relacionadas con la hipoxia (e.g. la necrosis). Este estudio permite formular una clasificación de los tumores basada en el nivel de necrosis, así como la investigación de terapias multimodales que incluyan efectos antiangiogénicos.Investigamos la influencia de las protrusiones celulares desde una perspectiva no local.Analizamos su rol en el fenómeno de la guía por contacto y en la manifestación de efectos colaborativos o competitivos entre dos estímulos que determinan cambios de dirección de la velocidad celular.Utilizando el análisis experimental de las distribuciones de varias proteínas, evaluamos la relación de las protrusiones celulares con las integrinas y las proteasas como principales mecanismos de progresión del glioblastoma. Mostramos cómo las interacciones bioquímicas y biomecánicas de estos agentes dan como resultado el desarrollo de frentes de propagación tumoral, que pueden presentar una evolución dinámica y heterogénea en relación a los cambios ambientales.bcam:basque center for applied mathematics; La Caixa Foundatio

    Anisotropy Across Fields and Scales

    Get PDF
    This open access book focuses on processing, modeling, and visualization of anisotropy information, which are often addressed by employing sophisticated mathematical constructs such as tensors and other higher-order descriptors. It also discusses adaptations of such constructs to problems encountered in seemingly dissimilar areas of medical imaging, physical sciences, and engineering. Featuring original research contributions as well as insightful reviews for scientists interested in handling anisotropy information, it covers topics such as pertinent geometric and algebraic properties of tensors and tensor fields, challenges faced in processing and visualizing different types of data, statistical techniques for data processing, and specific applications like mapping white-matter fiber tracts in the brain. The book helps readers grasp the current challenges in the field and provides information on the techniques devised to address them. Further, it facilitates the transfer of knowledge between different disciplines in order to advance the research frontiers in these areas. This multidisciplinary book presents, in part, the outcomes of the seventh in a series of Dagstuhl seminars devoted to visualization and processing of tensor fields and higher-order descriptors, which was held in Dagstuhl, Germany, on October 28–November 2, 2018

    Design, synthesis and pharmacological evaluation of novel fused pyrimidine analogues as anticancer agents.

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    Doctoral Degree. University of KwaZulu-Natal, Durban.Cancer is a multifaceted disease considered as the most serious health burden all over the world. Due to existing of limited anticancer drugs and detrimental side effects, the anticancer research has been challenging. An investigation on identifying novel potential drugs is highly required to treat this serious abnormal cell growth. Advanced potential anticancer drug entrants are crucially required to combat the drawbacks linked with current drugs or line of therapies. Extensive investigations are being carried out on synthetic manipulations of heterocyclic aromatic compounds (purines) for developing efficient and potent anticancer drugs. Besides, these manipulations also offer effective leads for further optimization. Therefore, this project is an effort in detecting a novel and potent anticancer leads based on bioisostere of purines called pyrazolopyrimidines. In this research project we have performed an comprehensive literature survey of structural isomers of pyrazolopyrimidines (pyrazolo[1,5-a]pyrimidine and pyrazolo[4,3-d]pyrimidine) for their synthetic approaches and biological activities with special emphasis on structure-activity relationship (SAR) studies. These SAR studies prompted us to implement the observed studies on one of the structural isomer of pyrazolopyrimidine called pyrazolo[3,4-d]pyrimidine. And further, we have synthesized some novel series of pyrazolo[3,4-d]pyrimidine derivatives with various substituents at C-4 and C-6 positions of the scaffold. A total 71 compounds comprising of phenethyl and pentane hybrids (7-43, Chapter 4), benzoyl hybrids (5a-5h, 6a-6d and 7a-7c, Chapter 5) and lastly phenylcarbamoyl acetamide hybrids (9a-9s, Chapter 6) have been synthesized by molecular hybridization approach as outlined in schemes of respective chapters. The completion of reaction and the purity of novel synthesized compounds were confirmed by chromatographic analysis. All the newly synthesized compounds displayed acceptable analysis for their anticipated structures, which were established based on physicochemical and spectral data (IR, 1 H NMR, 13C NMR and HRMS). All synthesized compounds were primarily evaluated for their in vitro anticancer activities at Laboratory of Growth Regulators, Centre of the Region Hana for Biotechnological and Agricultural Research, Palacky University & Institute of Experimental Botany ASCR, Slechtitelu 27, 78371 Olomouc, Czech Republic. From the systematic analysis of anticancer activity, results obtained following key observations were made. i. Structural isomers of fused pyrimidines have been looked upon for molecular changes in emerging drug like candidates. Pyrazolopyrimidine is a bioisostere of purines has acquired considerable importance due to its diverse, facile and general synthetic methodologies with great medicinal importance. Several analogs of this scaffold have emerged as a promising leads in the design of some novel pharmacologically active compounds with enhanced iii metabolic, pharmacokinetic and pharmacological profiles, representing that there is plenty scope for considering pyrazolopyrimidine as a structural framework for evolving effective leads. ii. Chapter 4: From the 37 novel phenethyl and alkyl pentane pyrazolo[3,4-d]pyrimidine derivatives synthesized and evaluated for CDK2/Cyclin E, Abl kinase inhibitory activity and anti-proliferative activity against K-562 (chronic myelogeneous leukemia) and MCF7 (breast adenocarcinoma) cell lines. From the tested results, compounds 11 (CDK: IC50 = 5.1 µM; Abl: ˃12.5 µM), 8 (CDK: IC50 = 7.8 µM; Abl: ˃25 µM) and 36 (CDK: IC50 = 8.8 µM; Abl: >25 µM) exhibited significant inhibitory activity. Further from this series, most of the synthesized compounds indicated prominent anti-proliferative effects with IC50 value ranging from 19.2 µM to 27.4 µM. Incorporation of monosubstituted phenyl groups at C-4 of the pyrazolo[3,4-d]pyrimidine nucleus had favored for most prominent anticancer activity. iii. Chapter 5: Among the 15 novel benzoyl hybrids synthesized and evaluated, compounds 5a and 6c displayed (CDK2: IC50 = 8.8 µM, 6.8 µM) commendable inhibitory activity and notable anti-proliferative activity ranging from 18.9 µM to 89.3 µM). Presence of heteroatom containing bicyclic moieties at C-4 of the nucleus enhanced both inhibitory and anti-proliferative activity. iv. Chapter 6: Of the 19 novel phenylcarbamoyl acetamide hybrids synthesized and tested, compounds 9a, 9c, 9g, 9m and 9p showed moderate enzymatic inhibitory activity with an IC50 value ˃12.5 µM against both CDK2 and Abl kinases while, remaining compounds of this series could not generate IC50 values due to solubility limit (IC50 = ˃25 µM to ˃100 µM).Professor Neil Koorbanally was acknowledged by the author as his previous supervisor
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