1,721,024 research outputs found
Effect of paclitaxel treatment on cellular mechanics and morphology of human oesophageal squamous cell carcinoma in 2D and 3D environments
No full textDuring chemotherapy, structural and mechanical changes in malignant cells have been observed in several cancers, including leukaemia and pancreatic and prostate cancer. Such cellular changes may act as physical biomarkers for chemoresistance and cancer recurrence. This study aimed to determine how exposure to paclitaxel affects the intracellular stiffness of human oesophageal cancer of South African origin in vitro. A human oesophageal squamous cell carcinoma cell line WHCO1 was cultured on glass substrates (2D) and in collagen gels (3D) and exposed to paclitaxel for up to 48 h. Cellular morphology and stiffness were assessed with confocal microscopy, visually aided morpho-phenotyping image recognition and mitochondrial particle tracking microrheology at 24 and 48 h. In the 2D environment, the intracellular stiffness was higher for the paclitaxel-treated than for untreated cells at 24 and 48 h. In the 3D environment, the paclitaxel-treated cells were stiffer than the untreated cells at 24 h, but no statistically significant differences in stiffness were observed at 48 h. In 2D, paclitaxel-treated cells were significantly larger at 24 and 48 h and more circular at 24 but not at 48 h than the untreated controls. In 3D, there were no significant morphological differences between treated and untreated cells. The distribution of cell shapes was not significantly different across the different treatment conditions in 2D and 3D environments. Future studies with patient-derived primary cancer cells and prolonged drug exposure will help identify physical cellular biomarkers to detect chemoresistance onset and assess therapy effectiveness in oesophageal cancer patients
Integrated electrochemical device to screen for liver function at the point-of-care
Get PDFHuman Immunodeficiency Virus (HIV) and Tuberculosis (TB) continue to be a significant global burden, disproportionately affecting low- and middle-income countries (LMICs). While much progress has been made in treating these epidemics, this has led to a rise in liver complications, as patients on anti-retroviral therapies (to treat HIV) and anti-TBs (to treat TB) are at an increased risk of drug-induced liver injury (DILI). Therefore, patients on these medicines require consistent screening of liver function. But, due to logistical barriers, gold standard DILI screening fails to be executed at the point-of-care (POC) in LMICs. This thesis aims to fill a current and critical void in diagnosis and management of liver diseases in patients with HIV/AIDS and TB in these settings where conventional diagnostic approaches are prohibitively expensive.
To address this gap in technology and patient care, we have developed and optimized a robust, novel assay for on-site POC monitoring of liver health. We take an electrochemical approach to quantify the levels of alanine aminotransferase, a key biomarker of liver function, from whole blood samples. Additionally, we build a patient- and provider-centric platform for detection, aiming to minimize sample preparation steps and simplify the user experience. Furthermore, we use a computational approach to explore the impact of our technology at the POC in LMICs, quantifying both the efficacy and cost-effectiveness.
Using this technology, health care providers can assess patient liver health at the POC and make clinical decisions in real time. In the field this technology has the potential to impact HIV and TB patient treatment and improve patient quality of life
Small volume drug release testing using ultrasonic agitation: development, characterization, and applications
Get PDFThe first standardized methods for in vitro drug release testing of solid dosage forms were first introduced in the 1960s. Drug release testing has since become an important analytical measure along all stages of the drug development process. Despite the expanded role of dissolution testing and innovations in the types of dosage forms reaching the market, the fundamental methods and approaches to dissolution testing have not changed from their original introduction. This lack of innovation and one-size-fits-all approach to drug release testing has led to inefficiencies in testing and limited the scope of applications where this type of information could have an impact. In order to meet this need, we have designed, characterized, and implemented a small volume drug release test using ultrasonic agitation to screen for differences in dosage form composition. Our approach aims to supplement official methods for use during multiple stages of the drug development process. The hydro-acoustic environment in the system was characterized as a function of input power and position of the acoustic source. Drug release behavior from tablets was also studied over these system parameters, and a preliminary mechanistic explanation is made linking the two. The interplay between fragmentation and diffusion on solid dissolution processes was then explored through a deterministic partial differential equation model. This model provides the first instance of time-evolving particle size distributions in a dissolution model. In the final sections of this dissertation, uses of the ultrasonic agitation mediated drug screening method are demonstrated at two different parts of the drug development process – during early formulation development for the study of composite microparticle matrix structure on drug release behavior and post market surveillance for the screening of substandard tablets.2020-02-28T00:00:00
Substandard antimicrobial drugs: detection methods and their contributions to antibiotic resistance
Get PDFSubstandard and counterfeit medicines are major obstacles to the treatment of infectious diseases. Substandard medicines vary from standard drugs in terms of dose, bioavailability, or the presence of impurities. Current methods to identify substandard and counterfeit antimicrobial drugs are either resource intensive or have poor specificity. This dissertation examined two issues related to poor quality antimicrobial medicines: 1) Methods to detect and prevent the consumption of substandard drugs. 2) The relationship between substandard medicines and the evolution of rifampicin resistance. This dissertation advanced two technologies that may aid in the detection of substandard medicines: aptamers and biosensors. Oligonucleotide aptamers may be adapted for drug detection by coupling binding events to changes in fluorescence, luminescence or colorimetric signals. A computational model was developed to discover experimental factors that increase the probability of selecting a high affinity aptamer. Among them are: micromolar drug target concentration, high affinity substrate to partition aptamers, and high aptamer library affinity distribution. Random losses of aptamers due to experimental noise greatly decreased the probability of selecting an aptamer. Experimental parameters to optimize the process of aptamer discovery for small molecules are discussed. Bacterial biosensors are an alternative strategy for the detection of active pharmaceutical ingredients. Here, luciferase-expressing Escherichia coli were used to create profiles of drug interactions for anti-mycobacterial drugs. Drug interactions were tested by the Loewe additivity model. A novel method to differentiate rifamycin drugs from the drug degradation product rifampicin quinone was developed by analyzing each drug’s unique interactions.
While subinhibitory drug doses are known to select for antimicrobial resistance in vitro, the role of substandard anti-mycobacterial medicines in the development of rifampicin resistance remains poorly understood. The role of the drug degradation product rifampicin quinone on rifamycin resistance was assessed through in vitro studies of bacteria. Wild type Escherichia coli and Mycobacterium smegmatis cultured in the presence of rifampicin quinone acquired high levels of resistance to rifamycin drugs. Resistance was associated with genetic mutations in the rifampicin resistance cluster of the rpoB gene. The studies presented here demonstrate that substandard medicines can contribute towards rifamycin resistance, and offer methodologies to identify substandard medicines.2020-10-24T00:00:00
Quantitative analysis and predictions of multiplexed microenvironmental stimuli on tumor progression
Get PDFMicroenvironmental stimuli are important in maintenance of homeostasis, development, and tumor progression. For example, in tumor tissues the collagen becomes abnormal when tumor advances, and this remodeling may potentially in turn impact cell fates and even malignancy. However, little has been investigated into how this matrix reorganization occurs and regulates cellular behaviors through intracellular signaling transduction. This also poses a challenging but important question regarding how cells dynamically integrate cell-cell and cell-matrix interactions to respond to this mechanical remodeling.
Tumor microenvironment is multi-faceted and dynamic, and quantitative understanding of the feedback between the tumor and the microenvironment requires a high-dimensional quantitative analysis. To pursue these goals, we first developed a toolkit to precisely and reliably quantify matrix-based microenvironmental features during tumor progression. A collagen network dynamic model was also built to further study and predict the mechanical property changes during collagen remodeling in tumor expansion. The transcriptional regulators Yes-associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ) have been found as the most robust mechanosensors that tightly regulate malignant phenotypes and chemo-resistance in many cancers, however we have little knowledge of how they are regulated by multiplexed microenvironmental stimuli simultaneously. Here, we combined computational modeling with experimental evidence to examine how changes in matrix mechanical property regulate YAP/TAZ and related phenotypes integrating varying local cell densities and the integration signaling mechanism. The kinetic parameter estimation of our model suggests that the key mechanism in driving YAP/TAZ activation in the triple negative breast cancer MDA-MB-231 cell lines is the endogenous high contractility. Therefore, the matrix feature quantification, the collagen network mechanical predictions and integration mechanism of YAP/TAZ upstream signaling present a comprehensive knowledge of the role of collagen remodeling in cancer at different scales and time points. This study of platform enables potential treatment strategy exploration based on mechanical inhibition in cancer cells, and more importantly, the role of multiplexed microenvironment in tumor progression with the big data analysis.2020-07-02T00:00:00
Toward a quantitative understanding of cancer cell signaling: mathematical models, computational tools, applications, and beyond
Get PDFTumor development and progression are dictated by more than the activities of cancer cells alone and are in large part determined by interactions with the immune system and the surrounding stroma. Therefore, a robust understanding of cancer in the context of this dynamic interplay is required to truly understand the progression toward and past malignancy. The work included herein attempts to develop such an understanding of three particular facets of cancer biology at a quantitative level. The first facet of this work modeled the effects of the mechanical properties and cytokine composition of the tumor microenvironment on tumor-associated macrophage migration. Using an integrated in silico and three-dimensional in vitro approach, we studied how interstitial flow, in concert with other environmental factors, affects macrophage migration and its potential contribution to cancer invasion. The model suggested interleukin-8 (IL-8), chemokine (C-C motif) ligand 2 (CCL2), and β-integrin as key pathways that commonly regulate various Rho GTPases, and, in agreement with the model, in vitro macrophage migration remained elevated when exposed to a saturating concentration of recombinant IL-8 or CCL2, or to the co-addition of a sub-optimal concentration of both cytokines. Next, we sought to quantitatively analyze the effect of tumor-localized macrophage cytokine signaling on the migration behaviors of cancer cells. Using an integrated experimental and computational approach, we analyzed the signaling networks associated with two cytokines secreted by tumor-associated macrophages (TAMs), transforming growth factor beta 1 (TGF-β1) and tumor necrosis factor alpha (TNFα), with the results suggesting that migratory behavior is driven by a nonlinear signaling network characterized by extensive crosstalk between the downstream intracellular signaling pathways activated by these cytokines, where migration persistence is controlled by the synergistic integration of TGF-β1 and TNFα signals and migration speed is more directly regulated by TGF-β1 signals alone. Furthermore, computational analysis of this network suggested that signaling kinase TAK1 and inhibitor Smad7 are key nodes in the signaling network structure underlying this synergistic signal integration. Finally, we developed a quantitative model of TGF-β signaling and associated gene expression in cancer to analyze the effects of the mechanical properties and cytokine composition of the tumor microenvironment on TGF-β signaling, which can switch between acting as a tumor promoter and tumor suppressor through unclear mechanisms. Sensitivity analyses of the model suggested that signals originating in the mechanical tumor microenvironment, in particular extracellular matrix-induced signaling, move TGF-β signaling toward a tumor-promoting expression profile, and furthermore that the most influential reactions on this expression regulation occur at or near the transcriptional level. We then used the model to conduct a simulated drug screen to demonstrate potential applications for models of this type in the development of therapeutic tools targeting mechanically induced TGF-β signaling in cancer. Taken together, the results of these efforts all support the hypothesis that environmental cues not only bear influence on the outcomes of the processes regulated by these dynamic systems, but can, depending on the nature of the integration of these environmental signals at the intracellular level, be responsible for the biological decision-making between fundamentally different behaviors and outcomes.2021-12-24T00:00:00
Using one health approaches to study effects of antibiotic stewardship on AMR development
Get PDFAntimicrobial resistance (AMR) is a growing global threat to public health expected to impact 10 million people by 2050, with a disproportionate effect on low- and middle- income countries, that is further exacerbated in communities living in urban informal settlements and refugee camps. As a result, there is a heightened urgency to understand how current antibiotic use is driving the spread of drug resistance in communities with high population density and those that are in proximity to wastewater settings and environmentally contaminated surroundings. Currently, there is a limited quantitative and mechanistic understanding of the evolution and spread of multidrug resistant (MDR) pathogens in these complex settings where there are a multitude of antibiotic residues and bacterial species present. Computational and experimental work in this area can lead to predictive outcomes and more effective strategies to prevent outbreaks of resistant pathogens. The goal of this thesis was to develop and test an integrated mathematical modeling and high-throughput experimental approach to quantitatively analyze AMR evolution in complex environments. The mathematical model captures predicted behavior for systems with multiple antibiotic residues and metal ions, incorporating the effects of both antibiotic-antibiotic interactions and metal-antibiotic interactions. This model is rooted in fundamental principles of biological systems modeling and was continuously integrated with a novel experimental workflow utilizing the eVOLVER for rapid iterative model development and validation. This work has resulted in the development of a robust method of understanding and predicting the development and spread of MDR bacteria in complex environments and has the potential to provide robust strategies to protect the health of vulnerable populations in these environments
Pediatric diarrhea: risks associated with treatment and access to care analysis in humanitarian crisis settings
Get PDFA global rise in humanitarian emergencies, driven by conflict, poses significant health challenges, especially for children under five years old. While the source of such crises and the challenges affected healthcare systems face may be confined to man-made borders, the resulting spread of health problems such as antimicrobial resistant (AMR) infections and diarrheal diseases are not bound geographically. To address concerns in such dynamic environments, healthcare workers utilize simple, fast acting solutions to save as many children as possible. For diarrheal diseases, this entails initially treating with zinc supplements and oral rehydration solutions (ORS), saving antibiotics for the cases that do not respond to this treatment. Determining who needs this care is often assessed through proxy data tracked via routine vaccination records, such as “zero dose communities”. However, both protocols are not without their shortcomings. The goal of this thesis is to examine their risks. We first examine how zinc might impact resistance development in Escherichia coli in vitro. We further demonstrate by computational modeling that slight changes in fitness have disproportionate changes on the rate of resistance onset. After discovering that the use of zinc for diarrhea treatment may be contributing to the AMR crisis, we next focus on ensuring that children suffering from diarrheal diseases can access treatment. We find that using zero dose communities as a means of determining which children could access care, while suitable for other services, is ultimately insufficient for diarrheal diseases in crisis settings such as Democratic Republic of Congo, Afghanistan and Bangladesh. Finally, we look at developing a tool that could be used to better understand access to care patterns for diarrheal disease and show the impacts that conflict, weather and travel infrastructure have on altering access to care in Yemen, which has been in the midst of the world’s worst humanitarian crisis. Overall, this body of work demonstrates how both current treatment practices and access to care assessments for diarrheal diseases have previously overlooked risks which can contribute to poor health outcomes especially for children under five years old living in areas affected by humanitarian crises
Impact of tumor microenvironment on intracellular properties within a 3D system
Get PDFBreast cancer remains one of the leading causes of cancer death in women with one in eight women expected to develop breast cancer. Breast cancer progression causes several adverse changes in the extracellular matrix (ECM) composition and organization including an increase in stromal collagen and stiffening of the ECM. Clinical studies have recently discovered that stiff and dense breast tissue, a result of the abnormal architecture of the tumor microenvironment, correlates with breast tumor growth and increases the likelihood of tumor metastasis. However, the tumor microenvironment influence on cancer progression and intracellular behavior is not well understood due to the lack of physiologically relevant three dimensional (3D) in vitro models that are able to capture the mechanical and structural in vivo complexity and are also able to provide rigorous and quantitative understanding. The goal of this dissertation is to investigate how the mechanical components of the microenvironment influence intracellular and molecular activity to drive cancer progression in a robust and scalable 3D system.
In order to address these gaps, our work studied the the impact of collagen concentration, cell type, and drug incubation time on drug response in 2D and 3D environments. To understand the role of local cellular mechanics in mediating drug response, we optimized and utilized particle-tracking microrheology to quantify the intracellular activity of single cells and spheroids embedded in 3D collagen gels. Finally, our study connected both structure and mechanics with cell signaling by investigating the relationship between the mechanical components of the ECM and the YAP/TAZ pathway. Furthermore, we integrated our 3D embedded spheroid model with tissue clearing methods to allow for complete visualization of YAP/YAZ activity throughout the dense spheroid structure.
Collectively, the results showed that matrix properties interact with matrix dimensionality to influence drug response. This interaction also was found to affect intracellular activity, even in the presence of chemotherapeutic and anti-MMP drugs. We then showed how this interaction in mechanics and ECM properties affects the spatial and temporal heterogeneity of YAP/YAZ activity within a 3D spheroid. Overall, the work in this dissertation provides new insights into how the physical properties of the tumor microenvironment influence cellular form and function, as well as response to therapy of cancer cells, which may have implications on development of novel treatment strategies and patient outcome
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