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Title: Development of Human Brain Atlas Resources
Creator: Qi, Xiaoxiao
Date: 2020
Description: Digital human brain atlases play an increasingly critical role and are widely used in neuroimaging studies such as developing biomarkers,...
Show moreDigital human brain atlases play an increasingly critical role and are widely used in neuroimaging studies such as developing biomarkers, training data for machine learning algorithms, functional connectivity analysis and so on. A brain atlas typically consists of brain templates of different imaging modalities that are representative of individual brains under study in a standard atlas space and semantic labels that delineate brain regions according to the characteristics of the underlying tissue.The IIT Human Brain Atlas project has developed the state-of-the-art diffusion tensor imaging (DTI) template, high angular resolution diffusion imaging (HARDI) template, and anatomical templates for the young adult brain in a standardized space. The probabilistic maps of gray matter (GM) labels and tissue segmentations were also constructed based on the anatomical information of the atlas. This thesis introduced an enhanced T1-weighted template that were developed by combining information from both diffusion and anatomical data. The GM labels and tissue segmentation maps in the standardized space were also improved. Existing white matter (WM) atlases typically lack specificity in terms of brain connectivity. A new approach named regionconnect was developed in this work based on precalculated average healthy adult brain connectivity information stored in standard space in a fashion that allows fast retrieval and integration. This thesis first generated and evaluated the white matter connectome of the IIT Human Brain Atlas v.5.0. Next, the new white matter connectome was used to develop multi-layer, connectivity-based labels for each white matter voxel of the atlas, consistent with the fact that each voxel may contain axons from multiple connections. The regionconnect algorithm was then developed to rapidly integrate information contained in the multi-layer labels across voxels of a white matter region and to generate a list of the most probable connections traversing that region. The regionconnect algorithm as well as the white matter tractogram and connectome, multi-layer, connectivity-based labels, and associated resources developed for the IIT Human Brain Atlas v.5.0 in this work are available at www.nitrc.org/projects/iit. Furthermore, it was well established that use of a young adult atlas in studies of older adults is inappropriate due to the age-related characteristic changes of the brain, resulting in an increasing demand of digital brain atlases for the older adults. To fulfill this demand, a function of fiber orientation distribution (fODF) template that is representative of older adults was developed in a standardized atlas space for studies of white matter of older adult human brains, which built a solid foundation for the development of the white matter resources for the older adults human brain atlas.
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Title: Development of Microfluidic Platform to Study Insulin Resistance
Creator: Tanataweethum, Nida
Date: 2020
Description: Insulin resistance, a precursor for the development of type 2 diabetes (T2D), propagates among heterologous tissues through dysregulated lipid...
Show moreInsulin resistance, a precursor for the development of type 2 diabetes (T2D), propagates among heterologous tissues through dysregulated lipid flux, as well as dysregulated glucose production, and secretion of cytokines, adipokines and hepatokines. Although T2D is characterized by systemic insulin resistance, disruption of insulin signaling in the liver and adipose tissue recapitulates many aspects of T2D, including enhance endogenous glucose production as well as defects of insulin action. Mechanistic studies often aim to provide fundamental understanding of the observations from human and animal studies. Due to the complexity of animal models and the multifactorial character of T2D, there is a strong need to develop advanced experimental systems such as in vitro models that can enable the recapitulation of the complex physiology of the in vivo system and enable investigation of the pathological pathways as well as identify novel treatment options. The overall goal of this study was to develop insulin resistant models of adipose tissue and liver to study the metabolic function of each organ as well as to the organ-organ crosstalk. To accomplish this goal, four specific aims were pursued: (1) Establish adipose tissue on-a-chip to study the metabolic function of the adipocytes in flow culture; (2) Develop towards an insulin resistant adipose on-a-chip to study the metabolic function of adipocytes in setting of insulin resistance; (3) Develop insulin resistant liver on-a-chip to investigate the metabolic function of hepatocytes in setting of insulin resistance; (4) Develop adipose-liver on-a-chip in setting of insulin resistance to identify the metabolic interaction between organs.
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Title: ENLARGED PERIVASCULAR SPACES IN COMMUNITY-BASED OLDER ADULTS
Creator: Javierre Petit, Carles
Date: 2020
Description: Enlarged perivascular spaces (EPVS) have been associated with aging, increased stroke risk, decreased cognitive function and vascular dementia...
Show moreEnlarged perivascular spaces (EPVS) have been associated with aging, increased stroke risk, decreased cognitive function and vascular dementia. Furthermore, recent studies have investigated the links of EPVS with the glymphatic system (GS), since perivascular spaces are thought to play a major role as the main channels for clearance of interstitial solutes from the brain. However, the relationship of EPVS with age-related neuropathologies is not well understood. Therefore, more conclusive studies are needed to elucidate specific relationships between EPVS and neuropathologies. After demonstration of their neuropathologic correlates, detailed assessment of EPVS severity could provide as a potential biomarker for specific neuropathologies.In this dissertation, our focus was twofold: to develop a fully automatic EPVS segmentation model via deep learning with a set of guidelines for model optimization, and to evaluate both manual and automatic assessment of EPVS severity to investigate the neuropathologic correlates of EPVS, and their contribution to cognitive decline, by combining ex-vivo brain magnetic resonance imaging (MRI) and pathology (from autopsy) in a large community-based cohort of older adults. This project was structured as follows. First, a manual approach was used to assess neuropathologic and cognitive correlates of EPVS burden in a large dataset of community-dwelling older adults. MR images from each participant were rated using a semiquantitative 4-level rating scale, and a group of identified EPVS was histologically evaluated. Two groups of participants in descending order of average cognitive impairment were defined based and studied. Elasticnet regularized ordinal logistic regression was used to assess the neuropathologic correlates of EPVS burden in each group, and linear mixed effects models were used to investigate the associations of EPVS burden with cognitive decline. Second, a fully automatic EPVS segmentation model was implemented via deep learning (DL) using a small dataset of 10 manually segmented brain MR images. Multiple techniques were evaluated to optimize performance, mainly by implementing strategies to reduce model overfitting. The final segmentation model was evaluated in an independent test set and the performance was validated with an expert radiologist. Third, the DL segmentation model was used to segment and quantify EPVS. Quantified EPVS (qEPVS) were evaluated by combining ex-vivo MRI, pathology, and longitudinal cognitive evaluation. EPVS quantification allowed to study qEPVS both in the whole brain and regionally. Two different qEPVS metrics were studied. Elastic-net regularized linear regression was used to assess the neuropathologic correlates of qEPVS within each region of interest (ROI) under study, and linear mixed effects models were used to investigate the associations of qEPVS with cognitive decline. Finally, a preliminary study investigated the longitudinal associations of qEPVS with time. The DL segmentation model was re-trained using 4 in-vivo MR images. EPVS were segmented and quantified in a large longitudinal cohort where each participant was imaged at multiple timepoints. Factors that influenced segmentation performance across timepoints were evaluated, and linear mixed effects models controlling for these factors were used to investigate the associations of qEPVS with time.
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Title: Three-Dimensional Co-Culture Systems for Vascularization of Cardiac Tissue
Creator: Rodriguez Arias, Jessica A.
Date: 2023
Description: Myocardial Infarction (MI) is the partial or complete blockage of blood flow to the myocardial tissue resulting in damage and therefore loss...
Show moreMyocardial Infarction (MI) is the partial or complete blockage of blood flow to the myocardial tissue resulting in damage and therefore loss of heart function. In the U.S. every 40 seconds, someone will suffer from MI and the only available treatment is medication to treat the symptoms of heart function loss, but do not treat the underlying cause. Some attempts to treat the underlying cause have arisen in the last decades including cell-based therapies or tissue engineering therapies such as spheroid-based cardiac patches that have shown to be promising. Improvement in the mechanical properties to create suturable engineered tissues remain to be improved for ease of implantation purposes. Cell-laden hydrogel scaffolds can provide improved mechanical properties compared to biomaterial free cell-based therapies but need to allow for vascularization of the engineered tissue. Thus, the goal of this thesis is to provide preliminary studies for the use of a cell adhesive, proteolytically degradable PEG hydrogel scaffold that eventually would be used as an invitro model to evaluate engineered tissue vascularization for cardiac tissue engineering. To construct this model, important cell spheroid parameters on vascular invasion in 3D culture were investigated including the total number of cells/spheroid, the supporting cell for endothelial cells. In order to scale-up scaffolds to size of clinically relevant dimensions, a multilayered hydrogel construct visible light free-radical polymerization approach encapsulating vascular spheroids in multiple layers was also investigated. Results indicate that a total cell number of 5000 cells/spheroid aggregate were feasible due to cell sourcing. In addition, co-cultures of endothelial and mesenchymal stem cells led to maximized vascular invasion of the spheroids compared to fibroblast/endothelial co-culture and endothelial monoculture of spheroids in the hydrogel. Finally, the extent of vascularization of spheroids in each layer of the multilayered hydrogel constructs varied due to the observed differences in mechanical properties and swelling ratio of each layer due to incomplete polymerization of layers. This study demonstrated the importance of support cells and hydrogel mechanical properties in promoting vascularization of spheroid which serves as basis for building cell-laden hydrogel scaffolds for vascularization for cardiac tissues.
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Title: A MICROFLUIDIC INTESTINAL-MICROBIOTA PLATFORM TO STUDY DRUG METABOLISM
Creator: Wang, Chengyao
Date: 2020
Description: The intestine is the main site that orally administered drugs are primarily metabolized, absorbed, and distributed. The trillions of bacteria...
Show moreThe intestine is the main site that orally administered drugs are primarily metabolized, absorbed, and distributed. The trillions of bacteria that inhabit the intestine influence health and regulate important biochemical factors, such as the activity of enzymes pertinent to drug metabolism. However, this has not been systematically studied partly due to the challenges of recapitulating the unique and complex intestinal microenvironment that includes (1) the presence of mammalian and microbial cells and (2) a unique partitioned oxygenation proﬁle across the lumen to the subepithelial mucosa from anaerobic to the richly vascularized oxygenated. This thesis reports the development of a microfluidic device in which is integrated a membrane synthesized from a key element of mucosal basal lamina, collagen, and precisely controlled partitioned oxygen environment. The device enabled excellent cell viability and long-term function. More importantly, it enabled the coculture of intestinal epithelial cells and aerobic and anaerobic bacteria in the partitioned oxygen environment. These experiments on one hand allowed the measurement of cellular oxygen consumption rate under perfusion, which could be used to study microbial regulation of oxidative metabolism in epithelial cells. On the other hand, the device allowed a systematic examination of the role of different gut bacteria strains on the regulation of factors that are important in drug metabolism, namely, transporters and phase I enzymes. Our studies highlighted the importance of direct communication between the intestinal cells and the gut bacteria with major findings being that species-specific differences exist in the regulation of drug metabolism. This work will be useful for (1) the discovery of novel regulators of drug metabolizing enzymes, (2) developing new pharmacokinetic models, and (3) advancing precision medicine models for patients.
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Title: Intraoperative Assessment of Surgical Margins in Head And Neck Cancer Resection Using Time-Domain Fluorescence Imaging
Creator: Cleary, Brandon M.
Date: 2023
Description: Rapid and accurate determination of surgical margin depth in fluorescence guided surgery has been a difficult issue to overcome, leading to...
Show moreRapid and accurate determination of surgical margin depth in fluorescence guided surgery has been a difficult issue to overcome, leading to over- or under-resection of cancerous tissues and follow-up treatments such as ‘call-back’ surgery and chemotherapy. Current techniques utilizing direct measurement of tumor margins in frozen section pathology are slow, which can prevent surgeons from acting on information before a patient is sent home. Other fluorescence techniques require the measurement of margins via captured images that are overlayed with fluorescent data. This method is flawed, as measuring depth from captured images loses spatial information. Intensity-based fluorescence techniques utilizing tumor-to-background ratios do not decouple the effects of concentration from the depth information acquired. Thus, it is necessary to perform an objective measurement to determine depths of surgical margins. This thesis focuses on the theory, device design, simulation development, and overall viability of time-domain fluorescence imaging as an alternative method of determining surgical margin depths. Characteristic regressions were generated using a thresholding method on acquired time-domain fluorescence signals, which were used to convert time-domain data to a depth value. These were applied to an image space to generate a depth map of a modelled tissue sample. All modeling was performed on homogeneous media using Monte Carlo simulations, providing high accuracy at the cost of increased computational time. In practice, the imaging process should be completed within a span of under 20 minutes for a full tissue sample, rather than 20 minutes for a single slice of the sample. This thesis also explores the effects of different thresholding levels on the accuracy of depth determination, as well as the precautions to be taken regarding hardware limitations and signal noise.
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Title: Retrospective Quantitative T1 Imaging to Examine Characteristics of Multiple Sclerosis Lesions
Creator: Young, Griffin James
Date: 2024
Description: Quantitative MRI plays an essential role in assessing tissue abnormality and diseaseprogression in multiple sclerosis (MS). Specifically, T1...
Show moreQuantitative MRI plays an essential role in assessing tissue abnormality and diseaseprogression in multiple sclerosis (MS). Specifically, T1 relaxometry is gaining popularity as elevated T1 values have been shown to correlate with increased inflammation, demyelination, and gliosis. The predominant issue is that relaxometry requires parametric mapping through advanced imaging techniques not commonly included in standard clinical protocols. This leaves an information gap in large clinical datasets from which quantitative mapping could have been performed. We introduce T1-REQUIRE, a retrospective T1 mapping method that approximates T1 values from a single T1-weighted MR image. This method has already been shown to be accurate within 10% of a clinically available reference standard in healthy controls but will be further validated in MS cohorts. We also further aim to determine T1-REQUIRE’s statistical significance as a unique biomarker for the assessment of MS lesions as they relate to clinical disability and disease burden. A 14-subject comparison between T1-REQUIRE maps derived from 3D T1 weighted turbo field echoes (3D T1w TFE) and an inversion-recovery fast field echo (IRFFE) revealed a whole-brain voxel-wise Pearson’s correlation of r = 0.89 (p < 0.001) and mean bias of 3.99%. In MS white matter lesions, r = 0.81, R2 = 0.65 (p < 0.001, N = 159), bias = 10.07%, and in normal appearing white matter (NAWM), r = 0.82, R 2 = 0.67 (p < 0.001), bias = 9.48%. Mean lesional T1-REQUIRE and MTR correlated significantly (r = -0.68, p < 0.001, N = 587) similar to previously published literature. Median lesional MTR correlated significantly with EDSS (rho = -0.34, p = 0.037), and lesional T1-REQUIRE exhibited xiii significant correlations with global brain tissue atrophy as measured by brain parenchymal fraction (BPF) (r = -0.41, p = 0.010, N = 38). Multivariate linear regressions between T1- REQUIRE NAWM provided meaningful statistical relationships with EDSS (β = 0.03, p = 0.027, N = 38), as well as did mean MTR values in the Thalamus (β = -0.27, p = 0.037, N = 38). A new spoiled gradient echo variation of T1-REQUIRE was assessed as a proof of concept in a small 5-subject MS cohort compared with IR-FFE T1 maps, with a whole brain voxel-wise correlation of r = 0.88, R2 = 0.77 (p < 0.001), and Bias = 0.19%. Lesional T1 comparisons reached a correlation of r = 0.75, R2 = 0.56 (p < 0.001, N = 42), and Bias = 10.81%. The significance of these findings means that there is the potential to provide supplementary quantitative information in clinical datasets where quantitative protocols were not implemented. Large MS data repositories previously only containing structural T1 weighted images now may be used in big data relaxometric studies with the potential to lead to new findings in newly uncovered datasets. Furthermore, T1-REQUIRE has the potential for immediate use in clinics where standard T1 mapping sequences aren’t able to be readily implemented.
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Title: LOCAL VISCOELASTIC PROPERTIES OF SOFT ANISOTROPIC FIBROUS TISSUE
Creator: Gallo, Nicolas Remy
Date: 2020
Description: The current aging population, with more than 80 million "baby boomers", will present a steep medical challenge for our society in a...
Show moreThe current aging population, with more than 80 million "baby boomers", will present a steep medical challenge for our society in a foreseeable future. Half of the adults over 85 years old are predicted to be diagnosed with Alzheimer's disease by 2050. With healthcare cost reaching over 700 billion dollars in the United States, early detection of Alzheimer's disease (AD) and other co-existing neurodegenerative diseases is crucial to improve the recovery odds in patients and to decrease individual care cost. This work seeks to tackle this problem by proposing a novel computational framework toward improving the measurement of shear visco-elastic properties of brain white matter (WM), which vary with age. These measurements practically represent the effective (average) response of many cells and are typically obtained by using rheology or elastography. Although the former is direct, the latter requires the solution of an inverse problem based on a priori mechanical tissue model. The mechanical anisotropy of WM has previously not been fully explored although many inconsistencies have been reported in brain MRE experiments. To account for these inconsistencies a transversely isotropic constitutive model for the brain WM is proposed to interpret prior experiments involving 7 young and 4 older healthy men. By employing a novel inversion scheme, we report the local variation of the effective transverse and axial shear moduli in two well aligned WM structures (corpus callosum: CC; and cortical spinal tract: CST) for both the young and old cohort of healthy subjects part of the study. This work reports statistically significant changes in local regional variation of the transverse modulus across the CC for the young cohort. In the older cohort, the trend was similar yet not statistically significant. A novel candidate biomarker, the shear anisotropy metric, defined as the ratio of the transverse and axial shear moduli, found statistically significant local regional variation across the CC but not in the CST. Healthy aging was observed to decrease both transverse and axial in both CC and CST, although the variation was significant only for the CC. Finally, in an effort to understand the cause of effective transverse mechanical properties variation in WM with aging, the connection between effective and intrinsic contribution of WM cellular constituents is established. The intrinsic mechanical contributions of axons and glial matrix are separated by fitting the estimates of the effective shear moduli to a microscopic composite fiber model of myelinated axons embedded in the glial matrix. This work provides a method to establish a baseline for healthy brain mechanical properties thus promising to increase the specificity of MRE toward early diagnosis of neurodegenerative diseases. Additional oscillating disc rheology experiments with decellularized porcine myocardium, and the fabrication of a stable heterogeneous phantom matching the mechanical, diffusional and electrical properties of the WM provide foundational knowledge for due development and validation of MRE methodologies employed in other tissues.
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Title: Quantification of Imaging Markers at Different MRI Contrast Weightings, Vasculature, and Across Field Strengths
Creator: Nguyen, Vivian S.
Date: 2024
Description: Quantitative MRI measures physical characteristics of tissue, which creates a set scale with units that allows longitudinal monitoring and...
Show moreQuantitative MRI measures physical characteristics of tissue, which creates a set scale with units that allows longitudinal monitoring and cross-patient and cross-center studies. It enables earlier detection of disease, complements biopsy, and provides a clear numeric scale for differentiation of disease states. However, quantitative MRI acquisitions and post-processing are not trivial, which makes it hard to implement the clinical setting. This along with the variability in clinically used acquisitions and post-processing techniques leads to difficulty in establishing reliable, consistent, and accurate quantitative information. There is a critical need for rigorous validation of quantitative imaging biomarkers, both for current and novel quantitative imaging techniques. This dissertation seeks to both validate current quantitative MR imaging techniques and develop new ones in the heart and brain by: 1) examining the data variability and the loss in tag fidelity that occurs when quantitative cardiac tagging is incorrectly run post-Gadolinium injection; 2) quantifying the negative impact of unexpected relaxometric behavior observed in low field MR imaging for low inversion times during T1 mapping; 3) validating retrospectively calculated T1 as a biomarker for Multiple Sclerosis progression; 4) and prototyping an oxygen extraction fraction (OEF) mapping technique for the purpose of stroke prediction and establishment of a numeric scale for tissue health for stroke patients.Assessment of pre-Gadolinium and post-Gadolinium cardiac tag quality showed that post-Gadolinium tags are less saturated (p = 0.012) and have a wider range of saturation, contrast, and sharpness. This results in a loss of information in the late cardiac cycle and impeding quantification of myocardial function.Investigation of 64mT T1 mapping revealed unique relaxometric behavior in that at low inversion times (<250 ms), the signal response curve displayed an increase in signal intensity or a plateau in signal intensity dependent on T1 relaxation time. Inclusion of this increase or plateau in signal intensity negatively impacted T1 fitting algorithms, leading to their failure or incorrectly calculated T1 values. The maximum peak signal intensity before the null point was found to be 210 ms, which impacts current low field T1 mapping protocols which use an initial inversion time of 80-110 ms.Validation of retrospectively calculated T1 as a biomarker in Multiple Sclerosis revealed that T1 of normal appearing brain tissue correlates with measures of Multiple Sclerosis progression (EDSS, BPF, and disease duration) with normal appearing white matter T1 correlating with BPF (r = -0.49, p = 0.0018); putamen T1 correlating with EDSS (r = 0.48, p = 2.40e-03), with BPF (r = 0.69, p = 2.04e-06), and disease duration (r = -0.37; p = 0.02); and globus pallidus T1 correlating with disease duration (r = -0.42; p = 0.0093). Lesion T1 is reflective of MS severity whereas MTR is not.Finally, development of an oxygen extraction fraction (OEF) mapping technique showed that application of independent component analysis (ICA) to cardiac gated spiral-trajectory phase images yielded components that feature stenosis features observed in magnitude images. These ICA components form the basis of OEF mapping from phase images. This dissertation presents four studies that seek to improve either current quantitative MR imaging protocols in the heart, or to develop and validate new quantitative MR imaging techniques in the brain for the purpose of monitoring disease progression or predicting disease.
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Title: NON-DESTRUCTIVE CANCER DETECTION IN LYMPH NODE USING PAIRED-AGENT MOLECULAR IMAGING
Creator: Li, Chengyue
Date: 2020
Description: Identification of cancer spread to tumor-draining lymph nodes through lymph node dissection and histology offers critical information for...
Show moreIdentification of cancer spread to tumor-draining lymph nodes through lymph node dissection and histology offers critical information for guiding treatment in many cancer types, including breast, melanoma, head and neck, lung and gynecologic cancers, as the lymphatic system serves as the primary route for metastasis. Lymph node biopsy involves localization of tumor-draining lymph nodes, followed by their surgical removal and histological assessment. However, the procedure is associated with overtreatment concerns and some considerable morbidity, including lymphedema, seroma formation, and restricted arm movement. Moreover, conventional histological analyses are time-consuming and laborious, yet pathologists generally examine less than 1% of the volume of each lymph node, leading to undetected micrometastasis (tumor clusters 0.2-2mm in diameter) in 30-60% of cases. In response to these limitations in standard lymph node dissection protocol, there is a significant need for the development of lymph node imaging strategies that are capable of identifying metastatic cancer as a means of staging a patient’s cancer without the need for invasive and time-intensive conventional pathology. Paired-agent imaging molecular imaging protocols have been spearheaded by our group and entail co-administration of a control imaging agent with a molecular targeted agent as a way to account for nonspecific uptake and retention. The overall goal of my thesis was to methodically design, optimize and evaluate the clinical utility of a paired-agent lymph node imaging protocol to achieve levels of sensitivity and specificity in nodal staging not possible with current conventional methods, less invasively and at a fraction of the time and cost.
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Title: IMPACT OF DATA SHAPE, FIDELITY, AND INTER-OBSERVER REPRODUCIBILITY ON CARDIAC MAGNETIC RESONANCE IMAGE PIPELINES
Creator: Obioma, Blessing Ngozi
Date: 2020
Description: Artificial Intelligence (AI) holds a great promise in the healthcare. It provides a variety of advantages with its application in clinical...
Show moreArtificial Intelligence (AI) holds a great promise in the healthcare. It provides a variety of advantages with its application in clinical diagnosis, disease prediction, and treatment, with such interests intensifying in the medical image field. AI can automate various cumbersome data processing techniques in medical imaging such as segmentation of left ventricular chambers and image-based classification of diseases. However, full clinical implementation and adaptation of emerging AI-based tools face challenges due to the inherently opaque nature of such AI algorithms based on Deep Neural Networks (DNN), for which computer-trained bias is not only difficult to detect by physician users but is also difficult to safely design in software development. In this work, we examine AI application in Cardiac Magnetic Resonance (CMR) using an automated image classification task, and thereby propose an AI quality control framework design that differentially evaluates the black-box DNN via carefully prepared input data with shape and fidelity variations to probe system responses to these variations. Two variants of the Visual Geometric Graphics with 19 neural layers (VGG19) was used for classification, with a total of 60,000 CMR images. Findings from this work provides insights on the importance of quality training data preparation and demonstrates the importance of data shape variability. It also provides gateway for computation performance optimization in training and validation time.
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Title: Cardiolipin Modulates the Insertion of Adsorbed Helical Amyloid Beta Peptide Into Model Mitochondrial Membranes
Creator: Kaczmarek, Julia A.
Date: 2023
Description: The loss of mitochondrial phospholipid cardiolipin (CL) may play a role in both the pathogenesis of Alzheimer's Disease (AD) and its treatment...
Show moreThe loss of mitochondrial phospholipid cardiolipin (CL) may play a role in both the pathogenesis of Alzheimer's Disease (AD) and its treatment. An effector molecule of the disease, amyloid-beta (Aβ), has been observed to interact with lipid membranes, but its relevance to mitochondrial membranes containing CL remained elusive. The present study investigated if the presence of CL modulated the insertion of adsorbed helical amyloid beta (Aβ14-40) into model mitochondrial membranes, and if this effect was more pronounced for its N-terminus or C-terminus. I conducted a coarse-grained computer simulation using well-tempered metadynamics to traverse the free energy landscape that maps the translocation of Aβ14-40. Insertion into CL-containing bilayers created larger local membrane deformations and modulated the location of the transition path but had an inconclusive impact on the free energy cost of translocation. Since the generation of toxic calcium-permeable pores depends on the insertion of Aβ into the bilayer, the loss of CL seen in AD may prime the inner mitochondrial membrane for pore formation, but more research is needed to pursue this hypothesis.
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Title: Correlating Microstructural Properties to Macroscopic Shear Mechanics to Improve the Understanding of Tissue Biomechanics
Creator: Cahoon, Stacey Marie
Date: 2023
Description: Understanding tissue biomechanics is of interest for modeling organ injury from external loads, development of tissue surrogate materials, and...
Show moreUnderstanding tissue biomechanics is of interest for modeling organ injury from external loads, development of tissue surrogate materials, and creating new biomarkers for disease. Probing the response of soft tissue in shear can provide information on histopathology, provided a methodology exists that connects the macroscopic mechanical properties with cell-level properties. Two of the available methods to measure the macroscopic shear viscoelastic properties of soft tissue are oscillatory shear rheometry and ultrasound shear wave elastography (SWE). Due to its accuracy, rheometry is the gold standard, but it is destructive, requires excised homogeneous samples, and can only be applied ex-vivo. SWE is an emerging non-invasive imaging technique which requires validation, ostensibly by comparing with rheometry. Histology is the gold standard for providing morphological information on the cell level, which can determine tissue pathology. The challenge is to connect the macroscopic mechanical metrics derived from SWE and rheometry to the tissue microstructure. To address this challenge, mathematical models can be used that employ multiple, judiciously chosen measurements of macroscopic shear properties and histology to estimate intrinsic mechanical properties at the cell level.A class of homogeneous and composite lipid phantoms mimicking the mechanical properties of brain white matter were fabricated to test a novel stereotactic system and an optimized SWE imaging protocol. The shear stiffness measurements obtained with SWE on the whole phantom were validated with rheometry performed on a series of samples made with the same material as the phantoms. The same procedure was applied to porcine brain white matter excised from fresh whole brains (n=3). Cylindrical cores were extracted from the corpus callosum area, sliced into discs and microscopic sections were subsequently removed for histology. Good agreement was found between the SWE and rheometry measurements of shear stiffness, which generally increases with the level of compressive prestress. Immunofluorescence was used to stain separately the axon neurofilaments and myelin sheaths, and digital image analysis of the confocal microscopy images allowed the estimation of axon volume fraction and axon-to-myelin ratio in the corpus callosum. Using these metrics and a composite mechanical model, a connection between the macroscopic shear measurements and the viscoelastic properties of axon and glia matrix was made for porcine brain tissue. Similarly, rheometry was used to measure the macroscopic properties of decellularized porcine myocardium extracellular matrix (ECM) in two different fiber locations, and for three different fiber orientations. The mechanical properties were found to be dependent upon fiber location, but not on fiber orientation. Since collagen is a primary supportive structure for the ECM, several microscopic slices were probed with immunofluorescence to compute the collagen I and collagen IV volume fractions. Another mechanical model was employed to establish a connection between the macroscopic properties and the mechanical properties of the collagen matrix in decellularized porcine myocardial ECM.This dissertation highlights the use and integration of three different experimental techniques (rheometry, ultrasound SWE, and histology) to correlate key microstructural properties of soft, fibrous tissues (ex-vivo healthy porcine brain white matter and myocardium ECM) with macroscopic shear mechanics. The consideration of the effect of compressive prestress is noteworthy. The reported baseline data for the tissues under shear loading and prestress are pertinent to the physiological function of these tissues, and therefore constitute preliminary data and a necessary first step before a systematic study of the biomechanics of the same tissues in vivo is performed.
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