Blood-brain barrier in vitro model: A tissue engineering approach and validation

This dissertation evaluated the feasibility of using commercially available immortalized cell lines in building a tissue engineered in vitro blood-brain barrier (BBB) co-culture model for preliminary drug development studies. Mouse endothelial cell line and rat astrocyte cell lines purchased from American Type Culture Collections (ATCC) were the building blocks of the co-culture model. An astrocyte derived acellular extracellular matrix (aECM) was introduced in the co-culture model to provide a novel in vitro biomimetic basement membrane for the endothelial cells to form endothelial tight junctions. Trans-endothelial electrical resistance (TEER) and solute mass transport studies were engaged to quantitatively evaluate the tight junction formation on the in-vitro BBB models. Immuno-fluorescence microscopy and Western Blot analysis were used to qualitatively verify the in vitro expression of occludin, one of the earliest discovered tight junction proteins. Experimental data from a total of 12 experiments conclusively showed that the novel BBB in vitro co-culture model with the astrocyte derived aECM (CO+aECM) was promising in terms of establishing tight junction formation represented by TEER values, transport profiles and tight junction protein expression when compared with traditional co-culture (CO) model setups and endothelial cells cultured alone. Experimental data were also found to be comparable with several existing in vitro BBB models built from various methods. In vitro colorimetric sulforhodamine B (SRB) assay revealed that the co-cultured samples with aECM resulted in less cell loss on the basal sides of the insert membranes than that from traditional co-culture samples. The novel tissue engineering approach using immortalized cell lines with the addition of aECM was proven to be a relevant alternative to the traditional BBB in vitro modeling.

Regulation of Bone Marrow Stem Cells through Oscillatory Shear Stresses - A Heart Valve Tissue Engineering Perspective

Heart valve disease occurs in adults as well as in pediatric population due to age-related changes, rheumatic fever, infection or congenital condition. Current treatment options are limited to mechanical heart valve (MHV) or bio-prosthetic heart valve (BHV) replacements. Lifelong anti-coagulant medication in case of MHV and calcification, durability in case of BHV are major setbacks for both treatments. Lack of somatic growth of these implants require multiple surgical interventions in case of pediatric patients. Advent of stem cell research and regenerative therapy propose an alternative and potential tissue engineered heart valves (TEHV) treatment approach to treat this life threatening condition. TEHV has the potential to promote tissue growth by replacing and regenerating a functional native valve. Hemodynamics play a crucial role in heart valve tissue formation and sustained performance. The focus of this study was to understand the role of physiological shear stress and flexure effects on de novo HV tissue formation as well as resulting gene and protein expression. A bioreactor system was used to generate physiological shear stress and cyclic flexure. Human bone marrow mesenchymal stem cell derived tissue constructs were exposed to native valve-like physiological condition. Responses of these tissue constructs to the valve-relevant stress states along with gene and protein expression were investigated after 22 days of tissue culture. We conclude that the combination of steady flow and cyclic flexure helps support engineered tissue formation by the co-existence of both OSS and appreciable shear stress magnitudes, and potentially augment valvular gene and protein expression when both parameters are in the physiological range.

Regulation of bone marrow stem cells through oscillatory shear stresses - A heart valve tissue engineering perspective

Heart valve disease occurs in adults as well as in pediatric population due to age-related changes, rheumatic fever, infection or congenital condition. Current treatment options are limited to mechanical heart valve (MHV) or bio-prosthetic heart valve (BHV) replacements. Lifelong anti-coagulant medication in case of MHV and calcification, durability in case of BHV are major setbacks for both treatments. Lack of somatic growth of these implants require multiple surgical interventions in case of pediatric patients. Advent of stem cell research and regenerative therapy propose an alternative and potential tissue engineered heart valves (TEHV) treatment approach to treat this life threatening condition. TEHV has the potential to promote tissue growth by replacing and regenerating a functional native valve. Hemodynamics play a crucial role in heart valve tissue formation and sustained performance. The focus of this study was to understand the role of physiological shear stress and flexure effects on de novo HV tissue formation as well as resulting gene and protein expression. A bioreactor system was used to generate physiological shear stress and cyclic flexure. Human bone marrow mesenchymal stem cell derived tissue constructs were exposed to native valve-like physiological condition. Responses of these tissue constructs to the valve-relevant stress states along with gene and protein expression were investigated after 22 days of tissue culture. We conclude that the combination of steady flow and cyclic flexure helps support engineered tissue formation by the co-existence of both OSS and appreciable shear stress magnitudes, and potentially augment valvular gene and protein expression when both parameters are in the physiological range. ^

Fluid dynamics and platelet deposition in a model arterial stenosis

The objective of this study was to gain further understanding and elucidation of the fluid dynamic factors and flow-induced mechanisms of the thrombogenic process of platelet deposition onto, and possible subsequent embolization from, the walls of an arterial stenosis. This has been accomplished by measurement of the axial dependence of platelet deposition within a modeled arterial stenosis for a transitional flow and a completely laminar flow field. The stenotic region of the model was collagen-coated to simulate a damaged endothelial lining of an artery. Fluid dynamics within a stenosis was studied using qualitative flow visualization, and was further compared to the in vitro platelet deposition studies. Normalized platelet density (NPD) measurements indicate decreased levels of NPD in the high shear throat region of the stenosis for a Reynolds number of 300 and a drastic increase in NPD at the throat for a Reynolds number of 175. This study provides further understanding of the flow dynamic effects on thrombus development within a stenosis. ^

Multipurpose portable system for environmental, industrial, and medical applications

This dissertation is about the research carried on developing an MPS (Multipurpose Portable System) which consists of an instrument and many accessories. The instrument is portable, hand-held, and rechargeable battery operated, and it measures temperature, absorbance, and concentration of samples by using optical principles. The system also performs auxiliary functions like incubation and mixing. This system can be used in environmental, industrial, and medical applications. ^ Research emphasis is on system modularity, easy configuration, accuracy of measurements, power management schemes, reliability, low cost, computer interface, and networking. The instrument can send the data to a computer for data analysis and presentation, or to a printer. ^ This dissertation includes the presentation of a full working system. This involved integration of hardware and firmware for the micro-controller in assembly language, software in C and other application modules. ^ The instrument contains the Optics, Transimpedance Amplifiers, Voltage-to-Frequency Converters, LCD display, Lamp Driver, Battery Charger, Battery Manager, Timer, Interface Port, and Micro-controller. ^ The accessories are a Printer, Data Acquisition Adapter (to transfer the measurements to a computer via the Printer Port and expand the Analog/Digital conversion capability), Car Plug Adapter, and AC Transformer. This system has been fully evaluated for fault tolerance and the schemes will also be presented. ^

A mathematical resolution to log transformations and the binning effect in applied processing of data in flow cytometry

This dissertation develops a new mathematical approach that overcomes the effect of a data processing phenomenon known as “histogram binning” inherent to flow cytometry data. A real-time procedure is introduced to prove the effectiveness and fast implementation of such an approach on real-world data. The histogram binning effect is a dilemma posed by two seemingly antagonistic developments: (1) flow cytometry data in its histogram form is extended in its dynamic range to improve its analysis and interpretation, and (2) the inevitable dynamic range extension introduces an unwelcome side effect, the binning effect, which skews the statistics of the data, undermining as a consequence the accuracy of the analysis and the eventual interpretation of the data. ^ Researchers in the field contended with such a dilemma for many years, resorting either to hardware approaches that are rather costly with inherent calibration and noise effects; or have developed software techniques based on filtering the binning effect but without successfully preserving the statistical content of the original data. ^ The mathematical approach introduced in this dissertation is so appealing that a patent application has been filed. The contribution of this dissertation is an incremental scientific innovation based on a mathematical framework that will allow researchers in the field of flow cytometry to improve the interpretation of data knowing that its statistical meaning has been faithfully preserved for its optimized analysis. Furthermore, with the same mathematical foundation, proof of the origin of such an inherent artifact is provided. ^ These results are unique in that new mathematical derivations are established to define and solve the critical problem of the binning effect faced at the experimental assessment level, providing a data platform that preserves its statistical content. ^ In addition, a novel method for accumulating the log-transformed data was developed. This new method uses the properties of the transformation of statistical distributions to accumulate the output histogram in a non-integer and multi-channel fashion. Although the mathematics of this new mapping technique seem intricate, the concise nature of the derivations allow for an implementation procedure that lends itself to a real-time implementation using lookup tables, a task that is also introduced in this dissertation. ^

Three-dimensional brain fiber tracking modeling in diffusion tensor imaging

This dissertation establishes the foundation for a new 3-D visual interface integrating Magnetic Resonance Imaging (MRI) to Diffusion Tensor Imaging (DTI). The need for such an interface is critical for understanding brain dynamics, and for providing more accurate diagnosis of key brain dysfunctions in terms of neuronal connectivity. ^ This work involved two research fronts: (1) the development of new image processing and visualization techniques in order to accurately establish relational positioning of neuronal fiber tracts and key landmarks in 3-D brain atlases, and (2) the obligation to address the computational requirements such that the processing time is within the practical bounds of clinical settings. The system was evaluated using data from thirty patients and volunteers with the Brain Institute at Miami Children's Hospital. ^ Innovative visualization mechanisms allow for the first time white matter fiber tracts to be displayed alongside key anatomical structures within accurately registered 3-D semi-transparent images of the brain. ^ The segmentation algorithm is based on the calculation of mathematically-tuned thresholds and region-detection modules. The uniqueness of the algorithm is in its ability to perform fast and accurate segmentation of the ventricles. In contrast to the manual selection of the ventricles, which averaged over 12 minutes, the segmentation algorithm averaged less than 10 seconds in its execution. ^ The registration algorithm established searches and compares MR with DT images of the same subject, where derived correlation measures quantify the resulting accuracy. Overall, the images were 27% more correlated after registration, while an average of 1.5 seconds is all it took to execute the processes of registration, interpolation, and re-slicing of the images all at the same time and in all the given dimensions. ^ This interface was fully embedded into a fiber-tracking software system in order to establish an optimal research environment. This highly integrated 3-D visualization system reached a practical level that makes it ready for clinical deployment. ^

Subdural electroencephalogram analysis for extracting discriminating measures in epileptogenic data

This dissertation introduces an integrated algorithm for a new application dedicated at discriminating between electrodes leading to a seizure onset and those that do not, using interictal subdural EEG data. The significance of this study is in determining among all of these channels, all containing interictal spikes, why some electrodes eventually lead to seizure while others do not. A first finding in the development process of the algorithm is that these interictal spikes had to be asynchronous and should be located in different regions of the brain, before any consequential interpretations of EEG behavioral patterns are possible. A singular merit of the proposed approach is that even when the EEG data is randomly selected (independent of the onset of seizure), we are able to classify those channels that lead to seizure from those that do not. It is also revealed that the region of ictal activity does not necessarily evolve from the tissue located at the channels that present interictal activity, as commonly believed.^ The study is also significant in terms of correlating clinical features of EEG with the patient's source of ictal activity, which is coming from a specific subset of channels that present interictal activity. The contributions of this dissertation emanate from (a) the choice made on the discriminating parameters used in the implementation, (b) the unique feature space that was used to optimize the delineation process of these two type of electrodes, (c) the development of back-propagation neural network that automated the decision making process, and (d) the establishment of mathematical functions that elicited the reasons for this delineation process. ^

A nanoliter volume nuclear magnetic resonance (NMR) system using tunneling magneto-resistive (TMR) sensors to recognize biomolecules

The need to incorporate advanced engineering tools in biology, biochemistry and medicine is in great demand. Many of the existing instruments and tools are usually expensive and require special facilities.^ With the advent of nanotechnology in the past decade, new approaches to develop devices and tools have been generated by academia and industry. ^ One such technology, NMR spectroscopy, has been used by biochemists for more than 2 decades to study the molecular structure of chemical compounds. However, NMR spectrometers are very expensive and require special laboratory rooms for their proper operation. High magnetic fields with strengths in the order of several Tesla make these instruments unaffordable to most research groups.^ This doctoral research proposes a new technology to develop NMR spectrometers that can operate at field strengths of less than 0.5 Tesla using an inexpensive permanent magnet and spin dependent nanoscale magnetic devices. This portable NMR system is intended to analyze samples as small as a few nanoliters.^ The main problem to resolve when downscaling the variables is to obtain an NMR signal with high Signal-To-Noise-Ratio (SNR). A special Tunneling Magneto-Resistive (TMR) sensor design was developed to achieve this goal. The minimum specifications for each component of the proposed NMR system were established. A complete NMR system was designed based on these minimum requirements. The goat was always to find cost effective realistic components. The novel design of the NMR system uses technologies such as Direct Digital Synthesis (DDS), Digital Signal Processing (DSP) and a special Backpropagation Neural Network that finds the best match of the NMR spectrum. The system was designed, calculated and simulated with excellent results.^ In addition, a general method to design TMR Sensors was developed. The technique was automated and a computer program was written to help the designer perform this task interactively.^

Segmental body composition determination through a bioelectrical very large scale integration (VLSI) system

The purpose of this investigation was to develop new techniques to generate segmental assessments of body composition based on Segmental Bioelectrical Impedance Analysis (SBIA). An equally important consideration was the design, simulation, development, and the software and hardware integration of the SBIA system. This integration was carried out with a Very Large Scale Integration (VLSI) Field Programmable Gate Array (FPGA) microcontroller that analyzed the measurements obtained from segments of the body, and provided full body and segmental Fat Free Mass (FFM) and Fat Mass (FM) percentages. Also, the issues related to the estimate of the body's composition in persons with spinal cord injury (SCI) were addressed and investigated. This investigation demonstrated that the SBIA methodology provided accurate segmental body composition measurements. Disabled individuals are expected to benefit from these SBIA evaluations, as they are non-invasive methods, suitable for paralyzed individuals. The SBIA VLSI system may replace bulky, non flexible electronic modules attached to human bodies. ^

Electrocardiogram breathing: A study of electrocardiogram derived respiration plus multiresolution wavelet analysis of heartbeat interval variability in sleep study patients

This dissertation presents a unique research opportunity by using recordings which provide electrocardiogram (ECG) plus a reference breathing signal (RBS). ECG derived breathing (EDR) is measured and correlated against RBS. Standard deviations of multiresolution wavelet analysis coefficients (SDMW) are obtained from heart rate and classified using RBS. Prior works by others used select patients for sleep apnea scoring with EDR but no RBS. Another prior work classified select heart disease patients with SDMW but no RBS. This study used randomly chosen sleep disorder patient recordings; central and obstructive apneas, with and without heart disease.^ Implementation required creating an application because existing systems were limited in power and scope. A review survey was created to choose a development environment. The survey is presented as a learning tool and teaching resource. Development objectives were rapid development using limited resources (manpower and money). Open Source resources were used exclusively for implementation. ^ Results show: (1) Three groups of patients exist in the study. Grouping RBS correlations shows a response with either ECG interval or amplitude variation. A third group exists where neither ECG intervals nor amplitude variation correlate with breathing. (2) Previous work done by other groups analyzed SDMW. Similar results were found in this study but some subjects had higher SDMW, attributed to a large number of apneas, arousals and/or disconnects. SDMW does not need RBS to show apneic conditions exist within ECG recordings. (3) Results in this study support the assertion that autonomic nervous system variation was measured with SDMW. Measurements using RBS are not corrupted due to breathing even though respiration overlaps the same frequency band.^ Overall, this work becomes an Open Source resource which can be reused, modified and/or expanded. It might fast track additional research. In the future the system could also be used for public domain data. Prerecorded data exist in similar formats in public databases which could provide additional research opportunities. ^

Durability assessment of polymer trileaflet heart valves

The durability of a polymer trileaflet valve is dependent on leaflet stress concentrations, so valve designs that reduce stress can, hypothetically, increase durability. Design aspects that are believed to contribute to reduced leaflet stress include stent flexibility, parabolic coaptation curvature, and leaflet anisotropy. With this in mind, the purpose of this investigation was to elucidate what specific combinations of these parameters promote optimal acute and long-term valve function. A combination of four stent designs, seven leaflet reinforcement materials, and three coaptation geometries were evaluated through a combination of experimentation and modeling. Static tensile and Poisson’s ratio tests and dynamic tensile fatigue testing were used to evaluate the individual leaflet components; and hydrodynamic testing and accelerated valve fatigue was used to assess complete valve prototypes. The two most successful designs included a 0.40 mm thick knit-reinforced valve with a fatigue life of 10.35 years, and a 0.20 mm thick knit-reinforced valve with a 28.9 mmHg decrease in pressure drop over the former. A finite element model was incorporated to verify the impact of the above-mentioned parameters on leaflet stress concentrations. Leaflet anisotropy had a large impact on stress concentrations, and matching the circumferential modulus to that of the natural valve showed the greatest benefit. Varying the radial modulus had minimal impact. Varying coaptation geometry had no impact, but stent flexibility did have a marked effect on the stress at the top of the commissure, where a completely rigid stent resulted in a higher peak stress than a flexible stent (E = 385 MPa). In conclusion, stent flexibility and leaflet anisotropy do effect stress concentrations in the SIBS trileaflet valve, but coaptation geometry does not. Regions of high stress concentrations were linked to failure locations in vitro, so a fatigue prediction model was developed from the S/N curves generated during dynamic tensile testing of the 0.20 mm knit-reinforced leaflets. Failure was predicted at approximately 400 million cycles (10 years) at the top of the commissure. In vitro fatigue of this valve showed failure initiation after approximately 167 million cycles (4.18 years), but it was related to a design defect that is subsequently being changed.

Seizure detection in subdural recordings using nonlinear decision functions

This dissertation proposed a new approach to seizure detection in intracranial EEG recordings using nonlinear decision functions. It implemented well-established features that were designed to deal with complex signals such as brain recordings, and proposed a 2-D domain of analysis. Since the features considered assume both the time and frequency domains, the analysis was carried out both temporally and as a function of different frequency ranges in order to ascertain those measures that were most suitable for seizure detection. In retrospect, this study established a generalized approach to seizure detection that works across several features and across patients. ^ Clinical experiments involved 8 patients with intractable seizures that were evaluated for potential surgical interventions. A total of 35 iEEG data files collected were used in a training phase to ascertain the reliability of the formulated features. The remaining 69 iEEG data files were then used in the testing phase. ^ The testing phase revealed that the correlation sum is the feature that performed best across all patients with a sensitivity of 92% and an accuracy of 99%. The second best feature was the gamma power with a sensitivity of 92% and an accuracy of 96%. In the frequency domain, all of the 5 other spectral bands considered, revealed mixed results in terms of low sensitivity in some frequency bands and low accuracy in other frequency bands, which is expected given that the dominant frequencies in iEEG are those of the gamma band. In the time domain, other features which included mobility, complexity, and activity, all performed very well with an average a sensitivity of 80.3% and an accuracy of 95%. ^ The computational requirement needed for these nonlinear decision functions to be generated in the training phase was extremely long. It was determined that when the duration dimension was rescaled, the results improved and the convergence rates of the nonlinear decision functions were reduced dramatically by more than a 100 fold. Through this rescaling, the sensitivity of the correlation sum improved to 100% and the sensitivity of the gamma power to 97%, which meant that there were even less false negatives and false positives detected. ^

Fluorescence-enhanced optical imaging on three-dimensional phantoms using a hand-held probe based frequency-domain intensified charge coupled device (ICCD) optical imager

Fluorescence-enhanced optical imaging is an emerging non-invasive and non-ionizing modality towards breast cancer diagnosis. Various optical imaging systems are currently available, although most of them are limited by bulky instrumentation, or their inability to flexibly image different tissue volumes and shapes. Hand-held based optical imaging systems are a recent development for its improved portability, but are currently limited only to surface mapping. Herein, a novel optical imager, consisting primarily of a hand-held probe and a gain-modulated intensified charge coupled device (ICCD) detector, is developed towards both surface and tomographic breast imaging. The unique features of this hand-held probe based optical imager are its ability to; (i) image large tissue areas (5×10 sq. cm) in a single scan, (ii) reduce overall imaging time using a unique measurement geometry, and (iii) perform tomographic imaging for tumor three-dimensional (3-D) localization. Frequency-domain based experimental phantom studies have been performed on slab geometries (650 ml) under different target depths (1-2.5 cm), target volumes (0.45, 0.23 and 0.10 cc), fluorescence absorption contrast ratios (1:0, 1000:1 to 5:1), and number of targets (up to 3), using Indocyanine Green (ICG) as fluorescence contrast agents. An approximate extended Kalman filter based inverse algorithm has been adapted towards 3-D tomographic reconstructions. Single fluorescence target(s) was reconstructed when located: (i) up to 2.5 cm deep (at 1:0 contrast ratio) and 1.5 cm deep (up to 10:1 contrast ratio) for 0.45 cc-target; and (ii) 1.5 cm deep for target as small as 0.10 cc at 1:0 contrast ratio. In the case of multiple targets, two targets as close as 0.7 cm were tomographically resolved when located 1.5 cm deep. It was observed that performing multi-projection (here dual) based tomographic imaging using a priori target information from surface images, improved the target depth recovery over using single projection based imaging. From a total of 98 experimental phantom studies, the sensitivity and specificity of the imager was estimated as 81-86% and 43-50%, respectively. With 3-D tomographic imaging successfully demonstrated for the first time using a hand-held based optical imager, the clinical translation of this technology is promising upon further experimental validation from in-vitro and in-vivo studies.