72 research outputs found
Detection of circulating breast cancer cells using photoacoustic flow cytometry
Title from PDF of title page (University of Missouri--Columbia, viewed on September 5, 2013).The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.Thesis advisor: Dr. John ViatorIncludes bibliographical references.Vita.M.S. University of Missouri--Columbia 2013.Dissertations, Academic -- University of Missouri--Columbia -- Biological engineering."May 2013"According to the American Cancer Society, more than 200,000 new cases of breast cancer are expected to be diagnosed this year. Moreover, about 40,000 women died from breast cancer last year alone. As breast cancer progresses in an individual, it can transform from a localized state to a metastatic one with multiple tumors distributed through the body, not necessarily contained within the breast. Metastasis is the spread of cancer through the body by circulating tumor cells (CTCs) which can be found in the blood and lymph of the diagnosed patient. Diagnosis of a metastatic state by the discovery of a secondary tumor can often come too late and hence, significantly reduce the patient's chance of survival. There is a current need for a CTC detection method which would diagnose metastasis before the secondary tumor occurs or reaches a size resolvable by current imaging systems. Since earlier detection would improve prognosis, this study proposes a method of labeling of breast cancer cells for detection with a photoacoustic flow cytometry system as a model for CTC detection in human blood. Gold nanoparticles and fluorescent polystyrene nanoparticles are proposed as contrast agents for T47D, the breast cancer cell line of choice. The labeling, photoacoustic detection limit, and sensitivity are first characterized and then applied to a study to show detection from human blood
Distributed Resilient Estimation over Directed Graphs
This paper addresses the problem of estimating an unknown static parameter by
a network of sensor nodes in a distributed manner over a directed communication
network in the presence of adversaries. We introduce an algorithm, Resilient
Estimation through Weight Balancing (REWB), which ensures that all the nodes,
both normal and malicious, asymptotically converge to the value to be estimated
provided less than half of them are affected by adversaries. We discuss how our
REWB algorithm is developed using the concepts of weight balancing of directed
graphs, and the consensus+innovations approach for linear estimation. Numerical
simulations are presented to show the performance of our algorithm over
directed graphs and its resilience to sensor attacks.Comment: 12 pages, 9 figure
Visual Performance under Varying Illumination Conditions while using an Indigenously Developed Wrist Wearable Computer
Ambient illumination conditions have significant impact on users’ visual performance while carrying out onscreen reading tasks on visual display units, especially smaller screen sizes. Present study assessed the visual performance responses of different ambient illumination levels during onscreen reading on Wrist Wearable Computer (WWC) developed for the command-control-communication between the control room and the soldiers operating in remote locations. Ten (10) Indian Infantry soldiers performed two different types of loud reading tasks on the display of WWC under three different ambient illumination (mean ±SEM) conditions namely, Indoor controlled (450.00±10.00 lx), Outdoor daylight (11818.7±582.91 lx) and Indoor dark (0.12±0.03 lx) environments. While reading, participants wore an eye tracking glass which recorded the eye movement responses. Visualisation techniques were used to predict the association of illumination levelof surrounding with visual performance of the user. Subjective legibility rating was also applied to understand participants’ preferences towards physical attributes of the onscreen information and illumination level. Results indicated that illumination had a significant effect on eye movement parameters like fixation frequency, fixation duration and scanpath length while completing the tasks. Overall, participants performed better under indoor controlled illumination conditions in terms of fixation profile and scanpath length, apart from improved subjective legibility ratings as compared to other two illumination conditions. Future research attempts need to be directed towards the optimum performance of the display across wide range of ambient illumination conditions and to establish how the display of indigenously developed wearable computer performs in comparison to other such displays available across the globe
An Effective Strategy for the Synthesis of Biocompatible Gold Nanoparticles Using Cinnamon Phytochemicals for Phantom CT Imaging and Photoacoustic Detection of Cancerous Cells
This is a post-print version of the Pharmaceutical Research Article. The original publication is available at www.springerlink.com. DOI 10.1007/s11095-010-0276-6Purpose: The purpose of the present study was to explore the utilization of cinnamon coated gold nanoparticles (Cin-AuNPs) as CT/optical contrast enhancement agent for detection of cancer cells.
Methods: Cin-AuNPs were synthesized by a “Green” procedure and the detailed characterization has been performed by physic-chemical analysis. Cytotoxicity and cellualar uptake studies were carried out in normal human fibroblast and cancerous (PC-3 and MCF-7) cells respectively. The efficacy of detecting cancerous cells was monitored using photoacoustic technique. In vivo biodistribution was studied after IV injection of Cin-AuNPs in mice and a CT phantom model was generated.
Results: Biocompatible Cin-AuNPs were synthesized with high purity. Significant uptake of these gold nanoparticles was observed in PC-3 and MCF-7 cells. Cin-AuNPs internalized in cancerous cells facilitate detectable photoacoustic signals. In vivo biodistribution in normal mouse shows steady accumulation of gold nanoparticles in lungs and rapid clearance from blood. Quantitative analysis of CT values in phantom model reveals that the cinnamon phytochemicals coated AuNPs has reasonable attenuation efficiency.
Conclusions: The results indicate that these non-toxic Cin-AuNPs can serve as excellent CT/ photoacoustic contrast enhancement agents and may provide a novel approach toward the tumor detection through nanopharmaceuticals.This work has been supported by grants from the National Institutes of Health/National Cancer Institute under the Cancer Nanotechnology Platform program (grant number: 5R01CA119412-01), NIH - 1R21CA128460-01; NIH-SBIR-Contract no. 241, and University of Missouri-Research Board - Program C8761 RB 06-030
Activating the knowledge-to-action cycle for geriatric care in India
Despite a rapidly aging population, geriatrics - the branch of medicine that focuses on healthcare of the elderly - is relatively new in India, with many practicing physicians having little knowledge of the clinical and functional implications of aging. Negative attitudes and limited awareness, knowledge or acceptance of geriatrics as a legitimate discipline contribute to inaccessible and poor quality care for India's old. The aim of this paper is to argue that knowledge translation is a potentially effective tool for engaging Indian healthcare providers in the delivery of high quality geriatric care. The paper describes India's context, including demographics, challenges and current policies, summarizes evidence on provider behaviour change, and integrates the two in order to propose an action plan for promoting improvements in geriatric care
Understanding the United States Congress through Data Visualization, Network Analysis, and Topic Modeling
MAC Protocol Based IoT Network Intrusion Detection Using Improved Efficient Shuffle Bidirectional COOT Channel Attention Network
The IoT networks are customized to work under various smart environments, utilizing diverse sensors. However, they are vulnerable to several cyberattacks because of their finite resources and limited computing capabilities. Intruders can easily hack the data transmitted across the end nodes. Therefore, it is crucial to protect the privacy of the IoT network against adversarial attacks. For real-time insights from IoT networks, an appropriate networking protocol is essential. In previous studies, several routing protocols have been formulated for intrusion detection with limited performance. Even the application of advanced machine learning (ML) has shown relatively lower accuracy with an increased error rate. To address these issues, an innovative intrusion detection system (IDS) for IoT networks based on medium access control (MAC) protocols with an improved efficient shuffle bidirectional COOT channel attention network (IEsBCCA-Net) method has been proposed. The suggested system uses the MAC protocol to securely transmit the data with low energy consumption and delay, which provides increased throughput. The collected data is stored in the BoT-IoT dataset, which is imbalanced and balanced using the synthetic minority over-sampling technique (SMOTE) and random under-sampling (RUS) techniques. The data is pre-processed using the reformed histogram equalization method, and the optimal features are selected using the modified honey badger algorithm (MHBA). Finally, the intrusions are classified using the IEsBCCA-Net approach, which provides outstanding accuracy compared to state-of-the-art (SOTA) methods
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