Matching Items (20)

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Application of flat panel OLED display technology for the point-of-care detection of circulating cancer biomarkers

Description

Point-of-care molecular diagnostics can provide efficient and cost-effective medical care, and they have the potential to fundamentally change our approach to global health. However, most existing approaches are not scalable

Point-of-care molecular diagnostics can provide efficient and cost-effective medical care, and they have the potential to fundamentally change our approach to global health. However, most existing approaches are not scalable to include multiple biomarkers. As a solution, we have combined commercial flat panel OLED display technology with protein microarray technology to enable high-density fluorescent, programmable, multiplexed biorecognition in a compact and disposable configuration with clinical-level sensitivity. Our approach leverages advances in commercial display technology to reduce pre-functionalized biosensor substrate costs to pennies per cm[superscript 2]. Here, we demonstrate quantitative detection of IgG antibodies to multiple viral antigens in patient serum samples with detection limits for human IgG in the 10 pg/mL range. We also demonstrate multiplexed detection of antibodies to the HPV16 proteins E2, E6, and E7, which are circulating biomarkers for cervical as well as head and neck cancers.

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Created

Date Created
  • 2016-07-04

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Characterization and Optimization of Ion-Sensitive Field Effect Transistors for Rapid Personalized Diagnostics

Description

The growth of the medical diagnostic industry in the past several decades has largely been due to the creation and iterative optimization of bio sensors. Recent pushes towards value added

The growth of the medical diagnostic industry in the past several decades has largely been due to the creation and iterative optimization of bio sensors. Recent pushes towards value added as well as preventative health care has made point of care devices more attractive to health care providers. Rapid detection for diseases and cancers is done with a bio sensor, which a broad term used to describe an instrument which uses a bio chemical reaction to detect a chemical compound with the use of a bio recognition event in addition to a signal detection event. The bio sensors which are presented in this work are known as ion-sensitive field effects transistors (ISFETs) and are similar in function to a metal oxide field effect transistor (MOSFET). These ISFETs can be used to sense pH or the concentration of protons on the surface of the gate channel. These ISFETs can be used for certain bio recognition events and this work presents the application of these transistors for the quantification of tumor cell proliferation. This includes the development of a signal processing and acquisition system for the long term assessment of cellular metabolism and optimizing the system for use in an incubator. This thesis presents work done towards the optimization and implementation of complementary metal\u2014oxide\u2014semiconductor (CMOS) ISFETs as well as remote gate ISFETs for the continuous assessment of tumor cell extracellular pH. The work addresses the challenges faced with the fabrication and optimization of these sensors, which includes the mitigation of current drift with the use of pulse width modulation in addition to issues encountered with fabrication of electrodes on a quartz substrate. This work culminates in the testing of an autonomous system with mammary tumor cells as well as the assessment of cell viability in an incubator over extended periods. Future applications of this work include the creation of a remote gate ISFET array for multiplexed detection as well as the implementation of ISFETs for bio marker detection via an immunoassay.

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Created

Date Created
  • 2017-05

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Electromyograph Remote Control Jellyfish Toy: A Brief Exploration of Jellyfish Biomimetics

Description

The goal of this project was to explore biomimetics by creating a jellyfish flying device that uses propulsion of air to levitate while utilizing electromyography signals and infrared signals as

The goal of this project was to explore biomimetics by creating a jellyfish flying device that uses propulsion of air to levitate while utilizing electromyography signals and infrared signals as mechanisms to control the device. Completing this project would require knowledge of biological signals, electrical circuits, computer programming, and physics to accomplish. An EMG sensor was used to obtain processed electrical signals produced from the muscles in the forearm and was then utilized to control the actuation speed of the tentacles. An Arduino microprocessor was used to translate the EMG signals to infrared blinking sequences which would propagate commands through a constructed circuit shield to the infrared receiver on jellyfish. The receiver will then translate the received IR sequence into actions. Then the flying device must produce enough thrust to propel the body upwards. The application of biomimetics would best test my skills as an engineer as well as provide a method of applying what I have learned over the duration of my undergraduate career.

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Created

Date Created
  • 2014-05

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Using Machine Learning to Objectively Determine Colorimetric Assay Results from Cell Phone Photos Taken Under Ambient Lighting

Description

Colorimetric assays are an important tool in point-of-care testing that offers several advantages to traditional testing methods such as rapid response times and inexpensive costs. A factor that currently limits

Colorimetric assays are an important tool in point-of-care testing that offers several advantages to traditional testing methods such as rapid response times and inexpensive costs. A factor that currently limits the portability and accessibility of these assays are methods that can objectively determine the results of these assays. Current solutions consist of creating a test reader that standardizes the conditions the strip is under before being measured in some way. However, this increases the cost and decreases the portability of these assays. The focus of this study is to create a machine learning algorithm that can objectively determine results of colorimetric assays under varying conditions. To ensure the flexibility of a model to several types of colorimetric assays, three models were trained on the same convolutional neural network with different datasets. The images these models are trained on consist of positive and negative images of ETG, fentanyl, and HPV Antibodies test strips taken under different lighting and background conditions. A fourth model is trained on an image set composed of all three strip types. The results from these models show it is able to predict positive and negative results to a high level of accuracy.

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Created

Date Created
  • 2021-05

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Energy-Efficient Electoral System for Underwater Sea Turtle Image Recognition

Description

This paper presents work that was done to develop an energy-efficient electoral and frame count system for underwater sea turtle image and video recognition using convolutional neural networks, deep learning

This paper presents work that was done to develop an energy-efficient electoral and frame count system for underwater sea turtle image and video recognition using convolutional neural networks, deep learning framework, and the Python programming language. An underwater sea turtle image recognition program is essential to protect turtles from the threat of bycatch - sea turtles are accidentally caught when fishermen aim for a different type of underwater species. This underwater image recognition system is used to detect the presence of sea turtles, then different kinds of acoustic and light stimuli are used to warn the turtles of approaching danger to reduce bycatch. This image detection system will be placed on a fishing boat to run on a machine at all times (24 hours and 7 days a week). A live video capture from a low-power underwater camera that is attached to the boat will be sent to the image detection system on the machine to analyze the presence of sea turtles in each frame of the video. To lower the computational time and energy of the machine, an energy-efficient electoral and frame count system is implemented on this image detection system.

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Created

Date Created
  • 2019-05

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INVESTIGATING ECCRINE SWEAT AS A NONINVASIVE BIOMARKER RESOURCE

Description

Background: Recent interests in continuous biomonitoring and the surge of wearable biotechnology demand a better understanding of sweat as a noninvasive biomarker resource. The ability to use sweat as a

Background: Recent interests in continuous biomonitoring and the surge of wearable biotechnology demand a better understanding of sweat as a noninvasive biomarker resource. The ability to use sweat as a biofluid provides the opportunity for noninvasive early and continuous diagnostics. This thesis serves to help fill the existing knowledge gap in sweat biomarker discovery and applications.

Experimental Design: In part one of this study, exercise-induced eccrine sweat was collected from 50 healthy individuals and analyzed using mass spectrometry, protein microarrays, and quantitative ELISAs to identify a broad range of proteins, antibody isotypes, and cytokines in sweat. In part two of this study, cortisol and melatonin levels were analyzed in exercise-induced sweat and plasma samples collected from 22 individuals.

Results: 220 unique proteins were identified by shotgun analysis in pooled sweat samples. Detectable antibody isotypes include IgA (100% positive; median 1230 ± 28 700 pg/mL), IgD (18%; 22.0 ± 119 pg/mL), IgG1 (96%;1640 ± 6750 pg/mL), IgG2 (37%; 292 ± 6810 pg/mL), IgG3 (71%;74.0 ± 119 pg/mL), IgG4 (69%; 43.0 ± 42.0 pg/mL), and IgM (41%;69.0 ± 1630 pg/mL). Of 42 cytokines, three were readily detected in all sweat samples (p<0.01). The median concentration for interleukin-1α was 352 ± 521 pg/mL, epidermal growth factor was 86.5 ± 147 pg/mL, and angiogenin was 38.3 ± 96.3 pg/mL. Multiple other cytokines were detected at lower levels. The median and standard deviation of cortisol was determined to be 4.17 ± 11.1 ng/mL in sweat and 76.4 ± 28.8 ng/mL in plasma. The correlation between sweat and plasma cortisol levels had an R-squared value of 0.0802 (excluding the 2 highest sweat cortisol levels). The median and standard deviation of melatonin was determined to be 73.1 ± 198 pg/mL in sweat and 194 ± 93.4 pg/mL in plasma. Similar to cortisol, the correlation between sweat and plasma melatonin had an R-squared value of 0.117.

Conclusion: These studies suggest that sweat holds more proteomic and hormonal biomarkers than previously thought and may eventually serve as a noninvasive biomarker resource. These studies also highlight many of the challenges associated with monitoring sweat content including differences between collection devices and hydration, evaporation losses, and sweat rate.

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Created

Date Created
  • 2019-05

Engineering Novel Microbead Encapsulated Three-Dimensional Tumor and Stem Cell Models

Description

Cellular assays are the backbone of biological studies - be it for tissue modeling, drug discovery, therapeutics, or diagnostics. Two-dimensional (2D) cell culture has been deployed for several decades to

Cellular assays are the backbone of biological studies - be it for tissue modeling, drug discovery, therapeutics, or diagnostics. Two-dimensional (2D) cell culture has been deployed for several decades to garner physiologically relevant information and predict data before the cost-intensive animal testing. Although 2D techniques have been valuable for cellular assays, they have a colossal limitation - they do not adequately consider the natural three-dimensional (3D) microenvironment of the cells. As a result, they sometimes provide misleading statistics. Therefore, it is important to develop a 3D model that predicts cellular behaviors and their interaction with neighboring cells and extracellular matrix (ECM) in a more realistic manner. In recent biomedical research, various platforms have been modeled to generate 3D prototypes of tissues, spheroids, in vitro that could allow the study of cellular responses resembling in vivo environments, such as matrices, scaffolds, and devices. But most of these platforms have drawbacks such as lack of spheroid size control, low yield, or high cost associated with them. On the other hand, Amikagel is a low cost, high-fidelity platform that can facilitate the convenient generation of tumor and stem cell spheroids. Furthermore, Amikabeads are aminoglycoside-derived hydrogel microbeads derived from the same monomers as Amikagel. They are a versatile platform with several chemical groups that can be exploited for encapsulating the spheroids and investigating the delivery of bioactive compounds to the cells. This thesis is focused on engineering novel 3D tumor and stem cell models generated on Amikagel and encapsulated in Amikabeads for proximal delivery of bioactive compounds and applications in regenerative medicine.

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Agent

Created

Date Created
  • 2020

Bluetooth low energy for use with MEM sensors

Description

ABSTRACT

Designers creating the next generation remote sensing enabled smart devices need to overcome the challenges of prevailing ventures including time to market and expense.

To reduce the time and effort involved

ABSTRACT

Designers creating the next generation remote sensing enabled smart devices need to overcome the challenges of prevailing ventures including time to market and expense.

To reduce the time and effort involved in initial prototyping, a good reference design is often desired and warranted. This paper provides the necessary reference materials for Designers to implement a wireless solution efficiently and effectively.

This document is intended for users with limited Bluetooth technology experience.

Many sensing-enabled devices require a ‘hard-wire’ or cable link to a host monitoring system. This can limit the potential for product advancements by anchoring the system to a single location preventing portability and the convenience of a remote system. By removing the “wired” or cabled portion from a design, a broader scope of devices becomes feasible.

One common problematic area for these types of sensors is within the internal medicine field. Proximity sensing is far more practical and less invasive to implement than surgical implantation. Bluetooth Low Energy (BLE) systems solve the hard wired problem by decoupling the physical sensor from the host system through a BLE transceiver that can send information to an external monitoring system. This wireless link enables new sensor technology to be leveraged into previously unobtainable markets; such as, internal medicine, wearable devices, and Infotainment to name a few. Wireless technology for sensor systems are a potentially disruptive technology changing the way environmental monitoring is implemented and considered.

With this BLE design reference, products can be created with new capabilities to advance current technologies for military, commercial, industrial and medical sectors in rapid succession.

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Created

Date Created
  • 2015

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Nano-bilayer lipid membranes hosted on biogenic nanoporous substrates

Description

Engineered nanoporous substrates made using materials such as silicon nitride or silica have been demonstrated to work as particle counters or as hosts for nano-lipid bilayer membrane formation. These mechanically

Engineered nanoporous substrates made using materials such as silicon nitride or silica have been demonstrated to work as particle counters or as hosts for nano-lipid bilayer membrane formation. These mechanically fabricated porous structures have thicknesses of several hundred nanometers up to several micrometers to ensure mechanical stability of the membrane. However, it is desirable to have a three-dimensional structure to ensure increased mechanical stability. In this study, circular silica shells used from Coscinodiscus wailesii, a species of diatoms (unicellular marine algae) were immobilized on a silicon chip with a micrometer-sized aperture using a UV curable polyurethane adhesive. The current conducted by a single nanopore of 40 nm diameter and 50 nm length, during the translocation of a 27 nm polystyrene sphere was simulated using COMSOL multiphysics and tested experimentally. The current conducted by a single 40 nm diameter nanopore of the diatom shell during the translocation of a 27 nm polystyrene sphere was simulated using COMSOL Multiphysics (28.36 pA) and was compared to the experimental measurement (28.69 pA) and Coulter Counting theory (29.95 pA).In addition, a mobility of 1.11 x 10-8 m2s-1V-1 for the 27 nm polystyrene spheres was used to convert the simulated current from spatial dependence to time dependence.

To achieve a sensing diameter of 1-2 nanometers, the diatom shells were used as substrates to perform ion-channel reconstitution experiments. The immobilized diatom shell was functionalized using silane chemistry and lipid bilayer membranes were formed. Functionalization of the diatom shell surface improves bilayer formation probability from 1 out of 10 to 10 out of 10 as monitored by impedance spectroscopy. Self-insertion of outer membrane protein OmpF of E.Coli into the lipid membranes could be confirmed using single channel recordings, indicating that nano-BLMs had formed which allow for fully functional porin activity. The results indicate that biogenic silica nanoporous substrates can be simulated using a simplified two dimensional geometry to predict the current when a nanoparticle translocates through a single aperture. With their tiered three-dimensional structure, diatom shells can be used in to form nano-lipid bilayer membranes and can be used in ion-channel reconstitution experiments similar to synthetic nanoporous membranes.

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Created

Date Created
  • 2015

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Wearable Devices for Non-Invasive Cardiorespiratory Monitoring

Description

Wearable technology has brought in a rapid shift in the areas of healthcare and lifestyle management. The recent development and usage of wearable devices like smart watches has created significant

Wearable technology has brought in a rapid shift in the areas of healthcare and lifestyle management. The recent development and usage of wearable devices like smart watches has created significant impact in areas like fitness management, exercise tracking, sleep quality assessment and early diagnosis of diseases like asthma, sleep apnea etc. This thesis is dedicated to the development of wearable systems and algorithms to fulfill unmet needs in the area of cardiorespiratory monitoring.

First, a pneumotach based flow sensing technique has been developed and integrated into a face mask for respiratory profile tracking. Algorithms have been developed to convert the pressure profile into respiratory flow rate profile. Gyroscope-based correction is used to remove motion artifacts that arise from daily activities. By using Principal Component Analysis, the follow-up work established a unique respiratory signature for each subject based on the flow profile and lung parameters computed using the wearable mask system.

Next, wristwatch devices to track transcutaneous gases like oxygen (TcO2) and carbon dioxide (TcCO2), and oximetry (SpO2) have been developed. Two chemical sensing approaches have been explored. In the first approach, miniaturized low-cost commercial sensors have been integrated into the wristwatch for transcutaneous gas sensing. In the second approach, CMOS camera-based colorimetric sensors are integrated into the wristwatch, where a part of camera frame is used for photoplethysmography while the remaining part tracks the optical signal from colorimetric sensors.

Finally, the wireless connectivity using Bluetooth Low Energy (BLE) in wearable systems has been explored and a data transmission protocol between wearables and host for reliable transfer has been developed. To improve the transmission reliability, the host is designed to use queue-based re-request routine to notify the wearable device of the missing packets that should be re-transmitted. This approach avoids the issue of host dependent packet losses and ensures that all the necessary information is received.

The works in this thesis have provided technical solutions to address challenges in wearable technologies, ranging from chemical sensing, flow sensing, data analysis, to wireless data transmission. These works have demonstrated transformation of traditional bench-top medical equipment into non-invasive, unobtrusive, ergonomic & stand-alone healthcare devices.

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Created

Date Created
  • 2020