Matching Items (74)

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Mathematical Models of Androgen Resistance in Prostate Cancer Patients under Intermittent Androgen Suppression Therapy

Description

Predicting the timing of a castrate resistant prostate cancer is critical to lowering medical costs and improving the quality of life of advanced prostate cancer patients. We formulate, compare and

Predicting the timing of a castrate resistant prostate cancer is critical to lowering medical costs and improving the quality of life of advanced prostate cancer patients. We formulate, compare and analyze two mathematical models that aim to forecast future levels of prostate-specific antigen (PSA). We accomplish these tasks by employing clinical data of locally advanced prostate cancer patients undergoing androgen deprivation therapy (ADT). While these models are simplifications of a previously published model, they fit data with similar accuracy and improve forecasting results. Both models describe the progression of androgen resistance. Although Model 1 is simpler than the more realistic Model 2, it can fit clinical data to a greater precision. However, we found that Model 2 can forecast future PSA levels more accurately. These findings suggest that including more realistic mechanisms of androgen dynamics in a two population model may help androgen resistance timing prediction.

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Created

Date Created
  • 2016-11-16

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Temporal assessment of nanoparticle accumulation after experimental brain injury: Effect of particle size

Description

Nanoparticle (NP) based therapeutic and theranostic agents have been developed for various diseases, yet application to neural disease/injury is restricted by the blood-brain-barrier (BBB). Traumatic brain injury (TBI) results in

Nanoparticle (NP) based therapeutic and theranostic agents have been developed for various diseases, yet application to neural disease/injury is restricted by the blood-brain-barrier (BBB). Traumatic brain injury (TBI) results in a host of pathological alterations, including transient breakdown of the BBB, thus opening a window for NP delivery to the injured brain tissue. This study focused on investigating the spatiotemporal accumulation of different sized NPs after TBI. Specifically, animal cohorts sustaining a controlled cortical impact injury received an intravenous injection of PEGylated NP cocktail (20, 40, 100, and 500 nm, each with a unique fluorophore) immediately (0 h), 2 h, 5 h, 12 h, or 23 h after injury. NPs were allowed to circulate for 1 h before perfusion and brain harvest. Confocal microscopy demonstrated peak NP accumulation within the injury penumbra 1 h post-injury. An inverse relationship was found between NP size and their continued accumulation within the penumbra. NP accumulation preferentially occurred in the primary motor and somatosensory areas of the injury penumbra as compared to the parietal association and visual area. Thus, we characterized the accumulation of particles up to 500 nm at different times acutely after injury, indicating the potential of NP-based TBI theranostics in the acute period after injury.

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Created

Date Created
  • 2016-07-22

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Prevention and Control of Zika as a Mosquito-Borne and Sexually Transmitted Disease: A Mathematical Modeling Analysis

Description

The ongoing Zika virus (ZIKV) epidemic in the Americas poses a major global public health emergency. While ZIKV is transmitted from human to human by bites of Aedes mosquitoes, recent

The ongoing Zika virus (ZIKV) epidemic in the Americas poses a major global public health emergency. While ZIKV is transmitted from human to human by bites of Aedes mosquitoes, recent evidence indicates that ZIKV can also be transmitted via sexual contact with cases of sexually transmitted ZIKV reported in Argentina, Canada, Chile, France, Italy, New Zealand, Peru, Portugal, and the USA. Yet, the role of sexual transmission on the spread and control of ZIKV infection is not well-understood. We introduce a mathematical model to investigate the impact of mosquito-borne and sexual transmission on the spread and control of ZIKV and calibrate the model to ZIKV epidemic data from Brazil, Colombia, and El Salvador. Parameter estimates yielded a basic reproduction number R[subscript 0] = 2.055 (95% CI: 0.523–6.300), in which the percentage contribution of sexual transmission is 3.044% (95% CI: 0.123–45.73). Our sensitivity analyses indicate that R[subscript 0] is most sensitive to the biting rate and mortality rate of mosquitoes while sexual transmission increases the risk of infection and epidemic size and prolongs the outbreak. Prevention and control efforts against ZIKV should target both the mosquito-borne and sexual transmission routes.

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Created

Date Created
  • 2016-06-17

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Global Analysis for an HIV Infection Model with CTL Immune Response and Infected Cells in Eclipse Phase

Description

A modified mathematical model describing the human immunodeficiency virus (HIV) pathogenesis with cytotoxic T-lymphocytes (CTL) and infected cells in eclipse phase is presented and studied in this paper. The model

A modified mathematical model describing the human immunodeficiency virus (HIV) pathogenesis with cytotoxic T-lymphocytes (CTL) and infected cells in eclipse phase is presented and studied in this paper. The model under consideration also includes a saturated rate describing viral infection. First, the positivity and boundedness of solutions for nonnegative initial data are proved. Next, the global stability of the disease free steady state and the endemic steady states are established depending on the basic reproduction number R[subscript 0] and the CTL immune response reproduction number R[subscript CTL]. Moreover, numerical simulations are performed in order to show the numerical stability for each steady state and to support our theoretical findings. Our model based findings suggest that system immunity represented by CTL may control viral replication and reduce the infection.

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Created

Date Created
  • 2017-08-21

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Mathematical Analysis of Glioma Growth in a Murine Model

Description

Five immunocompetent C57BL/6-cBrd/cBrd/Cr (albino C57BL/6) mice were injected with GL261-luc2 cells, a cell line sharing characteristics of human glioblastoma multiforme (GBM). The mice were imaged using magnetic resonance (MR) at

Five immunocompetent C57BL/6-cBrd/cBrd/Cr (albino C57BL/6) mice were injected with GL261-luc2 cells, a cell line sharing characteristics of human glioblastoma multiforme (GBM). The mice were imaged using magnetic resonance (MR) at five separate time points to characterize growth and development of the tumor. After 25 days, the final tumor volumes of the mice varied from 12 mm[superscript 3] to 62 mm[superscript 3], even though mice were inoculated from the same tumor cell line under carefully controlled conditions. We generated hypotheses to explore large variances in final tumor size and tested them with our simple reaction-diffusion model in both a 3-dimensional (3D) finite difference method and a 2-dimensional (2D) level set method. The parameters obtained from a best-fit procedure, designed to yield simulated tumors as close as possible to the observed ones, vary by an order of magnitude between the three mice analyzed in detail. These differences may reflect morphological and biological variability in tumor growth, as well as errors in the mathematical model, perhaps from an oversimplification of the tumor dynamics or nonidentifiability of parameters. Our results generate parameters that match other experimental in vitro and in vivo measurements. Additionally, we calculate wave speed, which matches with other rat and human measurements.

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Date Created
  • 2017-05-31

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Improving the Realism and Magnetic Resonance Imaging of Multicellular Tumor Spheroids

Description

Magnetic resonance imaging (MRI) of changes in metabolic activity in tumors and metabolic abnormalities can provide a window to understanding the complex behavior of malignant tumors. Both diagnostics and treatment

Magnetic resonance imaging (MRI) of changes in metabolic activity in tumors and metabolic abnormalities can provide a window to understanding the complex behavior of malignant tumors. Both diagnostics and treatment options can be improved through the further comprehension of the processes that contribute to tumor malignancy and growth. By detecting and disturbing this activity through personalized treatments, it is the hope to provide better diagnostics and care to patients. Experimenting with multicellular tumor spheroids (MCTS) allows for a rapid, inexpensive and convenient solution to studying multiple in vitro tumors. High quality magnetic resonance images of small samples, such as spheroid, however, are difficult to achieve with current radio frequency coils. In addition, in order for the information provided by these scans to accurately represent the interactions and metabolic activity in vivo, there is a need for a perfused vascular network. A perfused vascular network has the potential to improve metabolic realism and particle transport within a tumor spheroid. By creating a more life-like cancer model and allowing the progressive imaging of metabolic functions of such small samples, a better, more efficient mode of studying metabolic activity in cancer can be created and research efforts can expand. The progress described in this paper attempts to address both of these current shortcomings of metabolic cancer research and offers potential solutions, while acknowledging the potential of future work to improve cancer research with MCTS.

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Created

Date Created
  • 2016-12

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Optimization of Human Neural Tissue Clearing for Immunohistochemical Imaging

Description

The combination of immunohistochemical (IHC) stainings and optical microscopy has allowed for the visualization of specific microscopic structures within tissue; however, limitations in light and antibody penetration mitigate the scale

The combination of immunohistochemical (IHC) stainings and optical microscopy has allowed for the visualization of specific microscopic structures within tissue; however, limitations in light and antibody penetration mitigate the scale on which these images can be taken (Alshammari et al, 2016; Marx, 2014). Tissue clearing, specifically the removal of lipids to improve sample transparency, solves the former weakness well, but does not improve antibody penetration significantly (Chung et al, 2013; Treweek et al, 2015). Therefore, there is a need to equalize the maximum depth that light can pass through a section with the depth at which there is recognizable fluorescence. This is particularly important when staining blood vessels as traditional size limitations exclusively allows for cross sectional visualization. Passive CLARITY Technique (PACT) has been at the forefront of tissue clearing protocols, utilizing an acrylamide hydrogel solution to maintain structure and sodium dodecyl sulfate to wash out lipids (Tomer et al, 2014). PACT is limited in its ability to clear larger sections and is not conducive to IHC antibody diffusion (Treweek et al, 2015). In order to circumvent these drawbacks, CUBIC was developed as an alternative passive protocol, aimed at being scalable to any tissue size (Richardson, 2015; Susaki et al, 2015). This study compared the effectiveness of both protocols in high and low lipid tissues in the context of blood vessel staining efficacy. Upon initial comparison, it became apparent that there was a statistically significant difference in mean DAPI intensity at all depths, up to 200 micrometers, between CUBIC and PACT \u2014 the former showcasing brighter stainings. Moreover, it was found that PACT does not remove erythrocytes from the tissue meaning that their auto-fluorescence is seen during imaging. Therefore, for blood vessel stainings, only CUBIC was optimized and quantitatively analyzed. In both tissue conditions as well as for two stainings, DAPI and fibronectin (FNCT), optimized CUBIC demonstrated a statistically significant difference from standard CUBIC with regards to mean fluorescent intensity.

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Created

Date Created
  • 2018-05

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Large Scale Biomanufacturing of Human Induced Pluripotent Stem Cell-Derived Neurons

Description

Current culturing methods allow for human neural progenitor cells to be differentiated into neurons for use in diagnostic tools and disease modeling. An issue arises in the relatively low number

Current culturing methods allow for human neural progenitor cells to be differentiated into neurons for use in diagnostic tools and disease modeling. An issue arises in the relatively low number of cells that can be successfully expanded and differentiated using these current methods, making the progress of research dependent on these cultures as a large number of cells are needed to conduct relevant assays. This project focuses on the expansion and differentiation of human neural progenitor cells cultured on microcarriers and within a rotating bioreactor system as a way to increase the total number of cells generated. Additionally, cryopreservation and the characteristics of these neurons post thaw is being investigated to create a way for long term storage, as well as, a method for standardizing cell lines between multiple experiments at different time points. The experiments covered in this study are aimed to compare the characteristics of differentiated human neurons, both demented and non-demented cell lines between pre-cryopreservation, freshly differentiated neurons and post-cryopreservation neurons. The assays conducted include immunofluorescence, calcium imaging, quantitative polymerase chain reaction, flow cytometry and ELISA data looking at Alzheimer’s disease traits. With the data collected within this study, the use of bioreactors, in addition to, cryopreservation of human neurons for long term storage can be better implemented into human neural progenitor cell research. Both of these aspects will increase the output of these cultures and potentially remove the bottleneck currently found within human neural disease modeling.

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Date Created
  • 2020-05

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Stochastic parameterization of the proliferation-diffusion model of brain cancer in a Murine model

Description

Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made

Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and includes chemotherapy, radiation therapy, and surgical removal if the tumor is surgically accessible. Treatment seldom results in a significant increase in longevity, partly due to the lack of precise information regarding tumor size and location. This lack of information arises from the physical limitations of MR and CT imaging coupled with the diffusive nature of glioblastoma tumors. GBM tumor cells can migrate far beyond the visible boundaries of the tumor and will result in a recurring tumor if not killed or removed. Since medical images are the only readily available information about the tumor, we aim to improve mathematical models of tumor growth to better estimate the missing information. Particularly, we investigate the effect of random variation in tumor cell behavior (anisotropy) using stochastic parameterizations of an established proliferation-diffusion model of tumor growth. To evaluate the performance of our mathematical model, we use MR images from an animal model consisting of Murine GL261 tumors implanted in immunocompetent mice, which provides consistency in tumor initiation and location, immune response, genetic variation, and treatment. Compared to non-stochastic simulations, stochastic simulations showed improved volume accuracy when proliferation variability was high, but diffusion variability was found to only marginally affect tumor volume estimates. Neither proliferation nor diffusion variability significantly affected the spatial distribution accuracy of the simulations. While certain cases of stochastic parameterizations improved volume accuracy, they failed to significantly improve simulation accuracy overall. Both the non-stochastic and stochastic simulations failed to achieve over 75% spatial distribution accuracy, suggesting that the underlying structure of the model fails to capture one or more biological processes that affect tumor growth. Two biological features that are candidates for further investigation are angiogenesis and anisotropy resulting from differences between white and gray matter. Time-dependent proliferation and diffusion terms could be introduced to model angiogenesis, and diffusion weighed imaging (DTI) could be used to differentiate between white and gray matter, which might allow for improved estimates brain anisotropy.

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Date Created
  • 2016-05

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Volume Distributions of Metastatic Brain Tumors

Description

Magnetic resonance imaging (MRI) data of metastatic brain cancer patients at the Barrow Neurological Institute sparked interest in the radiology department due to the possibility that tumor size distributions might

Magnetic resonance imaging (MRI) data of metastatic brain cancer patients at the Barrow Neurological Institute sparked interest in the radiology department due to the possibility that tumor size distributions might mimic a power law or an exponential distribution. In order to consider the question regarding the growth trends of metastatic brain tumors, this thesis analyzes the volume measurements of the tumor sizes from the BNI data and attempts to explain such size distributions through mathematical models. More specifically, a basic stochastic cellular automaton model is used and has three-dimensional results that show similar size distributions of those of the BNI data. Results of the models are investigated using the likelihood ratio test suggesting that, when the tumor volumes are measured based on assuming tumor sphericity, the tumor size distributions significantly mimic the power law over an exponential distribution.

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Created

Date Created
  • 2018-12