Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2003. / Includes bibliographical references (leaves 146-166). / Lymph node metastases have a negative impact on cancer survival, but the mechanisms for lymphatic metastasis are not well understood. The universal finding in solid tumors of an absence of functional lymphatic vessels seems paradoxical, as cancer cells do travel through lymphatics in order to disseminate. In order to address some of these issues, this thesis proposes two etiologies for the absence of functional lymphatic vessels in solid tumors. The first hypothesis addresses whether Vascular Endothelial Growth Factor-C (VEGF-C), a lymphangiogenic factor, was sufficient to induce lymphatic function in tumors. The overexpression of VEGF-C in tumors leads to an increase in lymph node metastasis as well as structures that positively stain for lymphatic markers, but does not induce functional lymphatics within the tumor. Thus VEGF-C is not sufficient to grow functional lymphatic vessels in tumors. The second hypothesis addresses whether mechanical forces generated by the proliferation of cancer cells in a confined space compress lymphatic vessels in tumors. The mechanical forces inside of the tumor were reduced by the selective killing of human cancer cells grown in mice by Diphtheria Toxin. Tumor cell death leads to an increase in the fraction of lymphatics with open lumen. In addition, lymphatic vessels with open lumen are surrounded by a lower cellular density than collapsed vessels. Thus, relieving solid stress allows lymphatic vessels to open. However, function was not restored in these vessels. This is presumably due to the inability of the lymphatic vessels to completely open along its entire length, leaving focal areas of lymphatic collapse. Compressive forces are common to all growing tumors, giving credence to the mechanical etiology of the absence of functional lymphatic vessels in tumors, regardless of tumor type or organ site. / (cont.) These findings lead to an interesting question: Does cancer treatment in humans relieve the mechanical compression allowing lymphatic and blood vessels to open? Furthermore, would the resumption of function of compressed blood and lymphatic vessels lead to a paradoxical increase in metastasis? These questions require further investigation. / by Timothy P. Padera. / Ph.D.

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2008. / Includes bibliographical references (p. 295-303). / Normal human listeners have a remarkable ability to focus on a single sound or speaker of interest and to block out competing sound sources. Individuals with hearing impairments, on the other hand, often experience great difficulty in noisy environments. The goal of our research is to develop novel signal processing methods inspired by neural auditory processing that can improve current speech separation systems. These could potentially be of use as assistive devices for the hearing impaired, and in many other communications applications. Our focus is the monaural case where spatial information is not available. Much perceptual evidence indicates that detecting common amplitude and frequency variation in acoustic signals plays an important role in the separation process. The physical mechanisms of sound generation in many sources cause common onsets/offsets and correlated increases/decreases in both amplitude and frequency among the spectral components of an individual source, which can potentially serve as a distinct signature. However, harnessing these common modulation patterns is difficult because when spectral components of competing sources overlap within the bandwidth of a single auditory filter, the modulation envelope of the resultant waveform resembles that of neither source. To overcome this, for the coherent, constant-frequency AM case, we derive a set of matrix equations which describes the mixture, and we prove that there exists a unique factorization under certain constraints. These constraints provide insight into the importance of onset cues in source separation. We develop algorithms for solving the system in those cases in which a unique solution exists. This work has direct bearing on the general theory of non-negative matrix factorization which has recently been applied to various problems in biology and learning. For the general, incoherent, AM and FM case, the situation is far more complex because constructive and destructive interference between sources causes amplitude fluctuations within channels that obscures the modulation patterns of individual sources. / (cont.) Motivated by the importance of temporal processing in the auditory system, and specifically, the use of extrema, we explore novel methods for estimating instantaneous amplitude, frequency, and phase of mixtures of sinusoids by comparing the location of local maxima of waveforms from various frequency channels. By using an overlapping exponential filter bank model with properties resembling the cochlea, and combining information from multiple frequency bands, we are able to achieve extremely high frequency and time resolution. This allows us to isolate and track the behavior of individual spectral components which can be compared and grouped with others of like type. Our work includes both computational and analytic approaches to the general problem. Two suites of tests were performed. The first were comparative evaluations of three filter-bank-based algorithms on sets of harmonic-like signals with constant frequencies. One of these algorithms was selected for further performance tests on more complex waveforms, including AM and FM signals of various types, harmonic sets in noise, and actual recordings of male and female speakers, both individual and mixed. For the frequency-varying case, initial results of signal analysis with our methods appear to resolve individual sidebands of single harmonics on short time scales, and raise interesting conceptual questions on how to define, use and interpret the concept of instantaneous frequency. Based on our results, we revisit a number of questions in current auditory research, including the need for both rate and place coding, the asymmetrical shapes of auditory filters, and a possible explanation for the deficit of the hearing impaired in noise. / by Barry David Jacobson. / Ph.D.

Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology, 2004. / Includes bibliographical references (p. 67-70). / Introduction. Models that represent mathematical relationships between clinical outcomes and their predictors are useful to the decision making process in patient care. Many models, such as the score of neonatal physiology (SNAP II) that predicts in-hospital mortality, have been well validated on several large populations. However, the performance profile of such models in the midst of changing predictor-outcome relationships or newly appearing outcome predictors have not been well studied. We address this problem using statistical process control (SPC) techniques in a novel way. Although widely used in the manufacturing industry to maintain high quality in critical processes, SPC's value to healthcare has begun only recently to gain attention from decision makers. It has been used to construct risk-adjusted charts to track outcomes in the intensive care unit and the surgical arena, and to monitor hospital acquired infections. However, there are no reports of using SPC techniques to scrutinize the performance quality of a clinical model over time. The series of experiments in this manuscript show that the deterioration of a model's performance can be a useful indicator of unexpected changes in the environment that it represents; therefore, defining when a model is statistically not performing according to expectations is the first step towards determining the causes of clinical variations that might impact patient healthcare. Methods. We obtained a database of 3437 newborns admitted to 7 Neonatal Intensive Care Units in the New England area from October 1994 to January 1996. We chronologically arranged the patients by birthday and grouped them into 14 sequential periods; thereby establishing a time-sequenced database to be used in our SPC experiments. / (cont.) Each of the first thirteen periods contained 250 cases, while the last period had the remaining 187 cases. Several versions of the database were constructed by altering patient data in order to simulate various clinical scenarios--we either introduced graded changes in predictor values and mortality outcomes, or added new predictors. We analyzed the prediction performance pattern of the SNAP II model as applied to periods 1 to 14 in the original and modified versions of our database. The quality parameter tracked by our SPC charts is the C-index, which has been shown to be equivalent to the area under the Receiver Operating Characteristic curve and a well accepted indicator of a model's predictive performance. We introduced the 'deterioration index' as a quantitative measure of performance degradation that permitted us to compare results among experiments. Results. Applying the SNAP II model to the unaltered database, we showed that the c-indices remained well within statistically acceptable boundaries over time. This supported the generalizability of the SNAPII model as well as allowed us to use the mean and standard deviation of the c-indices as control values for our later experiments. In chapter 5, we showed that the model's performance can be degraded beyond acceptable limits by variations in the database (high deterioration index). The index depends on how much the changes in the database affect the existing predictor-outcome relationships. We also showed how the deterioration index can be used to assess and rank contributions of predictors to the model over time. In chapter 6, we showed that model performance ... / by John Chuo. / S.M.

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2008. / Page 146 blank. / Includes bibliographical references. / The cellular microenvironment is remarkably complex. In the small space near each cell, growth factors are liberated from extracellular matrix, cytokines are secreted from neighboring cells, and hormones arrive from distant organs. These spatially and temporally diverse cues are integrated by signal transduction cascades to modulate the activity of transcription factors, the principle regulators of gene expression. To date, experimental investigation of spatial and temporal transcription factor activation patterns has been limited by the use of destructive measurement techniques that require averaging responses over large cell populations. Similarly, control of complex microenvironments has been limited by the use of static tissue culture platforms. This thesis describes development of a high-throughput experimental platform called the microfluidic living cell array (mLCA) that combines fluidically-addressable cell arrays with a library of GFP reporter cells to enable nondestructive spatiotemporal gene expression profiling in living cells. The first section describes construction of the GFP reporter library and the development of methodologies for performing routine seeding and culture of cells in microfluidic channels. Microfluidic circuits are then designed to achieve parallel control of soluble stimulus concentration and timing for delivery to downstream cells. A novel "Flow-encoded Switching" (FES) design strategy is introduced to control simultaneous delivery of temporally distinct stimulus patterns using a single input. These circuits are demonstrated by profiling dynamic transcriptional responses to cytokine stimulation, and in each case, cell responses are found to depend quantitatively and qualitatively on the timing of the stimulus. / (cont.) The second section describes development of a two-dimensional valve-controlled mLCA for simultaneously profiling the entire transcriptional reporter library in response to a panel of stimuli. Integrated microvalve arrays control row-seeding and column-stimulation of 256 nanoliter-scale bioreactors, creating a high density matrix of stimulus-response experiments. The platform is demonstrated in the context of the hepatocyte stress response by collecting -5000 single-time-point measurements in each automated and unattended experiment. Results from these studies revealed a novel relationship between TNF-alpha and heat shock response activation, and more generally, illustrated that a single cytokine can activate multiple transcription factors with distinct dynamics. The third section transitions from temporal to spatial profiling and describes discovery and exploration of a spatially heterogeneous gene expression pattern in the innate immune system. Using a stable monoclonal ISRE-GFP reporter, double-stranded DNA (dsDNA) stimulation is found to result in 'colonylike' patterns of reporter activity in an otherwise confluent monolayer. Cell sorting and expression profiling reveal that activated reporter colonies are functionally distinct from their non-activated neighbors, and that colonies are responsible for the majority of cytokine and chemokine expression, including the potent antiviral interferon-beta. Using a novel transplant co-culture experiment, colonies are shown to form by contact-dependent intercellular communication and furthermore, this communication is found to depend on gap junctions. In summary, this thesis introduces promising new tools for conducting high-throughput investigations of spatiotemporal gene expression patterns in living cells, and it provides evidence for a novel dsDNA-induced intercellular communication mechanism that amplifies innate immune responses. / by Kevin R. King. / Ph.D.

Thesis: Ph. D. in Bioinformatics and Integrative Genomics, Harvard-MIT Program in Health Sciences and Technology, 2018. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged student-submitted from PDF version of thesis. / Includes bibliographical references (pages 141-156). / Comparative genomics is a powerful method for identifying functional genetic elements by their evolutionary patterns across species. However, current studies largely focus on analysis of genome sequences. The recent development of RNA-sequencing reveals dimensions of regulatory information previously inaccessible to us by sequence alone. The comparison of RNA-sequencing data across mammals has great potential for addressing two open problems in biology: identifying the regulatory mechanisms crucial to mammalian physiology, and deciphering how gene regulation contributes to the diversity of mammalian phenotypes. For my thesis, I developed two methodologies for interrogating comparative transcriptomic data for biological inference. First, I developed a framework for quantifying the evolutionary forces acting on gene expression and inferring evolutionarily optimal expression levels. I demonstrate how to use this framework to identify expression pathways underlying conserved, adaptive, and disease states of mammalian biology. Second, I developed novel metrics of transcriptional evolution to evaluate the conservation of long noncoding RNAs. These metrics further reveal that long noncoding RNAs harbor distinct evolutionary signatures, suggesting that they are not a homogenous class of molecules but rather a mixture of multiple functional classes with distinct biological roles. My thesis work provides fundamental quantitative tools for asking biological questions about transcriptome evolution. These tools provide a pivotal framework for interpreting transcriptional data across species and pave the way for deciphering the regulatory changes that lead to mammalian phenotypic variation. / by Jenny Chen. / Ph. D. in Bioinformatics and Integrative Genomics

Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology, 2009. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 68-72). / 'Smart' targeted drug carriers have long been sought after in the treatment of epidermal growth factor (EGF)-overexpressing cancers due to the potential advantages, relative to current clinical therapies (generally limited to surgery, radiation therapy, traditional chemotherapy, and EGF receptor inhibitors (EGFRIs)), of using such 'smart' targeted drug delivery systems. However, progress toward this goal has been challenged by the difficulty of creating a drug carrier that can autonomously detect and respond to tumor cells in the body. 'Smart' micron-size drug-encapsulating epidermal growth factor (EGF)-sensitive liposomes for EGF-overexpressing cancer therapies have been developed and studied. These drug-encapsulating liposomes remain inert until they are exposed to an abnormal concentration of EGF. As a drug delivery system, these drug-encapsulating liposomes could release pharmaceutical agents specifically in the immediate neighborhood of tumors overexpressing EGF, thereby maximizing the effective amount of drug received by the tumor while minimizing the effective systemic toxicity of the drug. Additionally, quantitative mathematical models were developed to characterize multiple critical rate processes (including drug leakage from drug-encapsulating liposomes and distribution of (drug-encapsulating) liposomes in blood vessels) associated i with (drug-encapsulating) liposomes in general. / (cont.) These quantitative mathematical models provide a low-cost and rapid method for screening novel drug-encapsulating liposome compositions, configurations, and synthetic methods to identify liposome compositions, configurations, and synthetic methods that would deliver optimal performance. The results provide a stepping stone toward the development of EGF-sensitive liposomes for clinical use. More generally, they also present implications for future development of other targeted drug delivery vehicles. / by Albert Wong. / S.M.

Thesis: Ph. D., Harvard-MIT Program in Health Sciences and Technology, 2016. / This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 121-132). / The tectorial membrane (TM) is an extracellular matrix that overlies the mechanically sensitive hair bundles of sensory receptor cells in the inner ear. Based on this strategic position, it has long been accepted that the TM plays a critical role in the stimulation of sensory hair cells. Early measurements demonstrated elastic properties of the TM and suggested that the TM is resonant. More recent measurements have shown that longitudinal coupling of the TM generates traveling waves that contribute to cochlear tuning. Here we show the importance of (1) viscosity in controlling the spread of excitation in TM traveling waves, as well as the importance of matrix porosity in determining (2) the viscosity of genetically modified TMs, and (3) local interactions with hair bundles. To understand the longitudinal spread of mechanical excitation via TM traveling waves, we develop chemical manipulations that systematically and reversibly alter TM stiffness and viscosity. Increasing TM viscosity or decreasing stiffness reduces longitudinal spread of mechanical excitation, thereby coupling a smaller range of best frequencies, which would sharpen tuning. In contrast, increasing viscous loss or decreasing stiffness would tend to broaden tuning in resonance based TM models. Thus, TM wave and resonance mechanisms are fundamentally different in the way they control frequency selectivity. To understand the molecular origin of TM viscosity, we investigate traveling waves in genetically modified TMs. We show that nanoscale pores of TectaY1870C/+ TMs are significantly larger than those of Tectb -/- TMs. The larger pore size reduces shear viscosity, thereby reducing traveling wave speed and increasing spread of excitation. These results demonstrate the previously unrecognized importance of TM porosity in cochlear tuning. To understand how TM porosity affects the local interaction between the TM and hair cells, we apply oscillatory forces to the TM with spherical probe tips. The effective stiffness of the TM is small at low frequencies where the porous matrix and surrounding fluid can move independently. By contrast, the effective stiffness of the TM is large at high frequencies, where these two phases are entrained by viscosity to move together. Interestingly, the transition frequency is in the audio frequency range only for hair bundle sized tips. Furthermore, the transition region is characterized by increased phase lead between the stimulus force and applied displacement that may play an essential role in the stability of micromechanical feedback paths and ultimately the sensitivity of hearing. In conclusion, these results show that traveling wave properties and local interactions with the hair bundles depend critically on TM porosity, thus fundamentally changing the way we think about molecular mechanisms underlying cochlear frequency selectivity and sensitivity. / by Jonathan Blake Sellon. / Ph. D.

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2007. / Includes bibliographical references (leaves 93-101). / Embryonic stem cells serve as powerful models for the study of development and disease and hold enormous potential for future therapeutics. Yet, over two decades after mouse embryonic stem cells (mESCs) were first isolated, there is still little known about the role of cell-cell signaling in self-renewal. Since traditional cell-culture techniques do not provide significant control of the stem cell microenvironment, the goal of this thesis was to develop a cell patterning technology that allows us to precisely control stem cell signaling and monitor cell proliferation over time. In the first aim of this thesis, we describe the development of our first cell patterning technology using dielectrophoresis (DEP). DEP uses nonuniform electric fields to trap cells on or between electrodes. We first used beads as model particles to validate the strength of our DEP square trap, and then demonstrated efficient cell patterning with multiple cell types. In the second aim of this thesis, we describe the development of a novel cell patterning technology that we created, called the Bio Flip Chip (BFC). / (cont.) The BFC is a microfabricated polymer chip, containing thousands of microwells, that enables cell patterning with single-cell resolution anywhere on a substrate and onto any substrate. In the last aim of this thesis, we used our BFC technology to control the stem cell microenvironment, allowing us to incrementally and independently modulate cell-cell contact. We present the first quantitative evidence that cell-cell contact depresses mESC colony formation and show that E-cadherin signaling is responsible for this negative regulatory pathway. / by Adam Rosenthal. / Ph.D.

Thesis: Ph. D. in Biomedical Engineering, Harvard-MIT Program in Health Sciences and Technology, 2018. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 125-136). / The conventional pathologic analysis of malignancies involves a qualitative characterization and integration of several factors including tumor size, general degree of differentiation, tumor heterogeneity, mitotic rate, and lymphovascular invasion. For some cancers, biomarkers such as hormone receptor expression or receptor kinase over-expression can provide additional prognostic and therapeutic guidance. Unfortunately, all of these qualitative histologic approaches, while generally accepted for directing patient care, often exhibit significant inter-observer variability resulting in inconsistent inter- and intra-institutional predictions of tumor behavior (including metastases and/or recurrence), resulting in incorrect diagnoses or treatment. Because cellular morphology is an integrated reflection of genetic and epigenetic expression, we hypothesize that a more accurate quantitative accounting and measurement of histologic features can provide a more robust and reliable prediction of tumor behavior. Computational imaging utilizes software to augment or replace the role of traditional optical elements in imaging systems and has an ability to significantly increase the accuracy, robustness and cost-efficiency of digital pathology. In this thesis, we develop and test three novel computational imaging algorithms including, to the best of our knowledge, the first system for lensless computational imaging through deep learning. We then test our hypothesis by applying augmented image retrieval, analysis algorithms, and machine learning on a validated dataset of breast cancer images where the clinical outcomes of the primary tumor are known. In particular, we analyze algorithms related to identifying mitoses as a central proof of concept. / by Justin Lee. / Ph. D. in Biomedical Engineering

Thesis (Ph.D.)--Harvard--Massachusetts Institute of Technology Division of Health Sciences and Technology, February 1999. / Includes bibliographical references (leaves 229-239). / by Douglas R. Daum. / Ph.D.