The following projects were awarded funds through a competitive, peer-reviewed program, with the goal of encouraging faculty to develop collaborative projects that stimulate the advancement of new ideas that can build 绿帽社's expertise toward a national reputation in the broad area of health sciences.
For the 2022-2023 academic year, the following seed grants were awarded:
Unraveling a New Mechanism for an Old Type II Diabetes Drug
Katie Edwards, pharmaceutical sciences; and Nannette Cowen, nursing
As of 2018, approximately 10.5% of the U.S. population (~34.2 million people) is estimated to have diabetes, with another 88 million U.S. adults with pre-diabetes, a condition that without changes in lifestyle and diet often leads to diabetes. Projections suggest that this number will nearly double by 2060, increasing to 60.6 million people in the U.S. alone. Metformin is a small molecule biguanide drug used as a first-line treatment for Type 2 diabetes and taken by more than 150 million people worldwide. Despite its widespread use, the mechanism of action of metformin is not fully elucidated. Our preliminary data suggests a correlation between the proven efficacy of metformin and vitamin-mediated processes. In this work, we aim to determine the impact of metformin on vitamin uptake, conversion to enzyme cofactor forms, and cellular retention in whole blood from patients who are and who are not taking metformin. Our findings are important for establishing a novel mechanism of action for this widely successful drug and finding potentially more effective preventative treatments for diabetes.
Mechanics of the normal and abnormal growth and folding of brain organoids
Tracy Hookway, biomedical engineering; and Mir Jalil Razavii, mechanical engineering
Brain organoids are self-organized 3D tissues derived from human pluripotent stem cells and have become an exciting tool to study neurodevelopmental and neurodegenerative diseases such as Alzheimer's and Parkinson's Disease. In this project we aim to utilize brain organoids to build a predictive mechanical model based on experimental data to determine the effects of cellular processes on the normal and abnormal folding of the brain. Understanding the mechanical underpinnings of this wrinkling process has direct implications in diseases such as Lissencephaly and Polymicrogyria where the brain does not go through proper folding. In this TAE proposal we specifically aim to understand the role cellular proliferation and nuclear density play in the context of developing brain organoids to determine its impact on normal folding. The experimental morphological and mechanical data obtained in these organoid studies will be fed directly into a mechanical model to predict additional parameters that will affect the folding process. This experimental test and data-driven mechanical modeling will be achieved by two complimentary PIs who together will achieve a feed-forward loop between organoid experiments and predictive modeling to determine to impact of cellular proliferation and nuclear density on brain folding patterns.
Assessment of Oxidative Stress in Biofilms by Visualization and Quantitation of Biomolecule Carbonylation
Susan Bane, chemistry; and Karin Sauer, biological sciences
Antibiotic resistance is a top threat to the public's health and a priority across the globe. In the U.S. alone, it causes more than 2 million infections and 23,000 deaths per year. Recent findings suggest that antibiotics kill by inducing oxidative stress (OS), by promoting the formation of reactive oxygen species (ROS), which play a role in cell death. The findings may lead to new, effective means to combat bacterial infections. However, the role of oxidative stress remains controversial as no direct, reliable method is available to quantify intracellular levels of ROS. Methods to detect oxidative stress (OS) generally employ probes for transient reactive species such as reactive oxygen species (ROS). A principal irreversible consequence of oxidative stress is carbonylation of biomolecules. The Bane lab develops fluorescent probes that form stable conjugates with biomolecule carbonyls and has employed them in eukaryotic cells and tissues to identify, quantitate and visualize OS-induced biomolecule carbonylation in these systems. In this project, the Sauer and Bane lab will evaluate the hypothesis that OS plays a role in killing bacterial cells by antibiotics using these novel probes.
For the 2019-2020 academic year, the following seed grants were awarded:
Understanding the combined effects of surface topography and material composition on the attachment of bacteria to implant surfaces
Ali Khoshkhoo ahd Jia Deng, both systems science and industrial engineering; and Laura Cook, biological sciences
As the older population grows dramatically globally, the need for implanted medical devices such as artificial hip and knee joints, coronary stents, and heart valves for elderly people increases rapidly. 3D printing, a highly customizable advanced manufacturing technique, is being gradually adopted to manufacture related surgery and implantation devices. However, infections and inflammation caused by bacteria that may be introduced immediately after surgery or develop later, remain a serious complication. There is an urgent need for antibacterial and biocompatible 3D printed implants that promote bone-tissue attachment. The goal of this research is to develop 3D printed implant surfaces that increase the lifetime of medical implants by reducing colonization of bacteria. The effects of three surface properties (material composition, coating, and surface texture) will be interpreted via surface wettability properties (i.e., contact angle) to elucidate the characteristics that correlate with decreased bacterial colonization. Two surface textures (i.e., groove, circular protrusion) and two material compositions (i.e., Stainless Steel (SS) 316 and pure Titanium (Ti)) will be 3D printed. The fabricated samples will then be coated with an array of materials (i.e., titanium dioxide (TiO2), nano-silver particles, and cobalt-chromium (Co-Cr) alloy films Diamond-Like Carbon (DLC) films,). Escherichia coli and Staphylococcus aureus will be cultivated on different samples to quantify both bacterial attachment to these surfaces as well as surface antibacterial effects.
Silencing the MYC oncogene to stop tumor growth
Tracy Brooks, pharmaceutical sciences; and Brian Callahan, chemistry
The c-myc protein is overproduced in the majority of human cancers where the protein overrides cellular safe guards and checkpoint mechanisms, thereby enabling tumors to proliferate uncontrollably. No effective clinical therapy yet exists to suppress the cancer causing activity of c-myc. Here the principal investigators propose leveraging two patent-pending technologies for a collaborative, high risk/high gain project to block malignant progression through genetic silencing of c-myc.
From Bench to Bedside: Translational Research in Complex Pain-Alcohol Interactions
Anushree Karkhanis, psychology; Nadine Mastroleo, CCPA; and Emily Zale, psychology
Pain and alcohol use are highly comorbid and engender a significant public health burden. Adolescence is a critical developmental period for neurological changes involved in the onset and progression of both pain and addiction, and alcohol use may be a risk factor for chronic pain due to changes in neural circuitry involved in reinforcement and pain processing. Translational addiction research utilizes both animal and human models to understand mechanisms, consequences, and treatment of substance use to ultimately improve public health. We propose a novel translational paradigm of pain and alcohol that, quite literally, spans bench to bedside. In Aim 1, pain-relevant neural mechanisms (e.g., mu and kappa opioid receptors) of adolescent ethanol exposure will be identified using animal models. In Aim 2, associations between adolescent drinking and human laboratory pain reactivity will be investigated. In Aim 3, we will explore acceptability of integrating pain-related components into an evidence-based alcohol intervention. The project is in line with the Health Sciences TAE Missions to address Disease Susceptibility, Pathogenesis, and Prevention as well as Healthcare Systems and Outcomes Research. Results will support an application to the Integrative Research on Polysubstance Abuse and Addiction R21/R33 sponsored by the NIH Collaborative Research on Addiction.
Brain Functional Organization Revealed by Resting-state Imaging
Weiying Dai, computer science; and Brandon Gibb, psychology
Functional magnetic resonance imaging (fMRI) has revealed activity covariation between brain regions during the resting state, frequently termed as brain resting-state networks. While the resting-state networks provide useful information about localization of the specialized networks, the overall organization of brain networks remains unclear. The proposed approach is based on our recent observations indicating that global signal fluctuations of perfusion fMRI may stem from globally synchronized neural activity. In this proposal, simultaneous electroencephalogram (EEG) and perfusion fMRI measurements will be employed to explore the neural basis of global perfusion signal fluctuations and global organization of brain networks, provide quantitative measurements of brain functional networks and improve the sensitivity of perfusion fMRI measurement. The methodology to be developed will fundamentally deepen our understanding of brain functional organization, provide necessary conditions to assess the feasibility of particular neural computational models, promote the design of digital devices and artificial intelligence systems more compatible with human brain.
In prior years, the following seed grants were awarded:
Engineering a Gut Microbiome
Gretchen Mahler, Department of Biomedical Engineering
Claudia Marques, Department of Biological Sciences
Microorganisms colonize the human gastrointestinal (GI) tract and comprise the resident human microbiota. A healthy gut microbiome is critical to regulating metabolism, promoting immune function, and eliminating xenobiotics, and changes in the number or composition of microbes may lead to pathophysiologic conditions. In this work we will engineer a mock community of upper GI bacteria, incorporate this community into a human GI tract model, and determine the effects of food additive exposure on microbial community dynamics and epithelial cell function. This system, which will be the first to model upper GI conditions using a physiologically realistic, reproducible method with human-derived cells, will allow quantitative assessment of the contributions of bacteria toward GI function and the ability to determine how what we eat governs microbial dynamics.
Smart Computer-Aided Diagnosis: Machine Learning Framework for Bio-Medical Image Segmentation
Dae Han Won, School of Systems Science and Industrial Engineering
Fake (Frank) Lu, Department of Biomedical Engineering
Advances in imaging technology have led to a proliferation of various bio-medical image. Simultaneously, computer-aided diagnosis (CAD) is beginning to be applied widely in the detection and differential diagnosis of abnormalities in medical images. Image segmentation, which delineates the specified regions (e.g., tumors), is one of the important component of CAD. In this study, we propose to develop fully automated two-dimensional (2D) and three-dimensional (3D) medical image segmentation pipeline using deep convolutional neural networks (CNNs). We will employee the data from two-cutting edge medical optical technologies: optical coherence tomography (OCT) and stimulated Raman scattering (SRS) microscopy to develop and validate our models. Research aims of this project are: (1) designing baseline architectures of CNNs for both 2D and 3D medical image segmentation, (2) modifying and optimizing the 2D/3D CNN models for medical imaging applications, and (3) applying the models to actual imaginary data and segmenting cancerous regions for Head and Neck cancer in OCT and glioma brain tumor in SRS. Eventually, our computational framework will provide a valuable guideline for pathological investigation as well as for surgical interventions with a great potential for future clinical use.
Understanding Antibody-Drug-Conjugate (ADC) Internalization via Stimulated Raman Scattering (SRS) Imaging of Alkyne Tags in Live Cancer Cells
Fake (Frank) Lu, Department of Biomedical Engineering
L. Nathan Tumey, Department of Pharmaceutical sciences
Antibody-drug-conjugate (ADC) technology is a rapidly growing area of pharmaceutical research that has resulted in more than 60 clinical trials and four approved drugs. This "targeted delivery" technology is deceptively simple: the antibody serves as a drug-carrier that directs the agent to antigen-expressing tissues of interest whereby the ADC is internalized, trafficked to the lysosome, and degraded thus resulting in drug-release. In spite of the conceptual elegance of this approach, the process of ADC internalization and processing remains poorly understood. Most of what we know about the internalization process relies on microscopic imaging using large fluorescent tags. The heavy fluorescent tags with high molecular weight may affect pharmacodynamics and pharmacokinetics of the drugs, thus impacting our understanding of the internalization and trafficking process. New imaging techniques are needed to allow for spatial and temporal resolution of the internalization process. Stimulated Raman scattering (SRS) microscopy is an emerging technology for rapid chemical bond imaging based on Raman contrasts, without the use of fluorescent tags. Imaging speed of SRS microscopy is several orders of magnitude faster than Raman confocal mapping, making it a powerful tool for fast imaging of fresh and dynamic samples, up to video rate. The goal of this project is to develop and optimize SRS imaging methodology for the study of ADCs that contain small Raman tags, such as an alkyne or cyano group. The ADCs will be administered to human breast cancer cells and we will perform time-lapse imaging of the live cells to investigate the processes and dynamics of ADCs cell surface binding, internalization, trafficking and payload release in the lysosomes. We believe that SRS microscopy will enable studies of ADC internalization and trafficking that are either not possible or not practical using existing fluorescence and mass-spectroscopy techniques.
Predicting Conversion to Psychosis in At-Risk Youth: The Role of Stress-Inflammation Interactions
Gregory Strauss, Department of Psychology
Terrence Deak, Department of Psychology
Hiroki Sayama, Departments of Systems Science and Industrial Engineering and Biomedical Engineering
Gary D. James, Department of Anthropology and Decker School of Nursing
Schizophrenia and other psychotic disorders are severe and functionally debilitating forms of mental illness that result in suffering and major challenges to the public healthcare system. For example, in the United States, schizophrenia ranks as the number one cause of medical disability and results in an estimated $62.7 billion of annually incurred costs. Given the severity of psychotic symptoms and limited ability to improve functional outcome once illness has ensued, the field has moved toward a model of early identification and prevention of psychosis. These efforts target the "prodromal" phase of illness, which occurs prior to the onset of a psychotic disorder when functioning declines and clinical symptoms gradually emerge over late adolescence. Unfortunately, prediction algorithms have yielded poor sensitivity and specificity in determining which individuals will go on to develop a psychotic disorder. The current study aims to improve prediction models. We will evaluate the novel hypothesis that acute and prolonged activation of inflammatory mechanisms renders the hypothalamic-pituitary-adrenal (HPA) axis and stress response to a sensitized state, resulting in increased risk for psychosis. Results will serve as preliminary data for a larger multi-site grant examining biomarkers of psychosis risk.
Treatment of Parkinson's Disease Using Intranasal Delivery via Electrospray Atomization
Christopher Bishop, Department of Psychology,
Paul Chiarot, Department of Mechanical Engineering
Increasingly, alternative routes of drug administration for brain disease have been sought. This is particularly true of Parkinson's disease (PD), where pathophysiolology includes reduced gastrointestinal motility, reduced nutrient absorption, and constipation. Indeed, oral drug administration to advanced PD patients is hindered by a fluctuating clinical response that relates to variable and poor drug bioavailability. To obviate this issue, one strategy that has gained attention is the intranasal route, which appears to gain direct and rapid access to the brain. Intranasal devices may have unique utility as rescue inhalers to rapidly restore movement in common and debilitating "freezing" in late-stage PD patients. Dr. Chris Bishop (Psychology) and Dr. Paul Chiarot (Mechanical Engineering) are currently collaborating to develop an innovative intranasal delivery apparatus that is now ready for preclinical testing. This specialized equipment employs 5V batteries to drive a fine aerosolized spray into the nasal cavity that is optimized for drug delivery by tightly regulating aqueous drug drop size and velocity. Preliminary in vivo work has established that the electrospray is feasible and can be accomplished with minimal discomfort for the animal. The proposed work will validate the electrospray approach in a disease model with key translational health implications for CNS disorders.
Real-Time Monitoring of Global Neurophysiological Function Using Customized 3D Printed BioSensors and Sensor Data Fusion Algorithms
Prahalada Rao, School of Systems Science and Industrial Engineering
Chun-An Chou, School of Systems Science and Industrial Engineering
Vladimir Miskovic, Department of Psychology
This work proposes novel signal processing methods for detecting the onset of acute physiological anomalies, e.g., epileptic seizures, cognitive exhaustion, etc. We apply change point detection algorithms to complex spatio-temporal data acquired from biosensors, such as electroencephalography (EEG), electrocardiography (ECG), etc., so that abrupt transitions demarcating normative from atypical physiological states can be rapidly identified in real-time (e.g., in patients prone to epileptic seizures), and the deleterious downstream consequences averted via pre-emptive alerts. This is an open research problem with current efforts driven by pattern recognition and nonlinear system identification techniques. Instead, we propose an innovative strategy using algebraic graph theoretic signal processing approaches. Furthermore, we propose to integrate the algorithm with patient-specific smart wearable sensors made using additive manufacturing (3D printing) processes. Such a customized, noninvasive platform for the acquisition of physiological signals will entail continuous monitoring of patient health, and thus facilitate preventive diagnostics, i.e., timely intervention before the patient's condition worsens. The outcomes of this research will include real-time monitoring of acute changes in neurophysiological state, including the detection of lapses in cognitive and motor functions to prevent accidents in high risk occupations e.g., hazardous cargo trucking, heavy machinery operation, airline pilots, etc.
Predicting Risk Factors for Hospital Readmissions Post Discharge from Skilled Nursing Care
Nina M. Flanagan, Decker School of Nursing
Victoria M. Rizzo, Department of Social Work
Gary D. James, Department of Anthropology and Decker School of Nursing
Adele Mattinat Spegman, Geisinger Health System
The Affordable Care Act provides new opportunities to develop and implement community-based transitions in care models to address individual determinants of health behaviors of older adults transitioning from skilled nursing facilities (SNF) to the community to decrease their risk of 30-day hospital readmissions. Using Andersen's Behavioral Model for Health Services Use, the specific aims of this exploratory study are to: (1) examine the relationships between individual determinants of health behaviors currently used as assessments of residents admitted to a skilled nursing center with those residents readmitted to the hospital within 30 days from discharge from the center. The determinants include Confusion Assessment Method for delirium, Barthel Index for functional status, Brief Interview for Mental Status, Geriatric Depression Scale, Braden Scale for skin integrity, risk for falls, initial renal panel and complete blood count.; (2) identify and describe the determinants that are risk factors for readmission to the hospital within thirty days post discharge form SNF; and, (3) use the findings to develop a transdisciplinary transitions in care model to target the mutable risk factors for 30-day hospital readmission. The findings will be used to develop an external funding proposal to design and test a new transitions in care model.
Is Atopic Dermatitis a Result of S. Aureus Infection due to Stratum Corneum Lipid Loss?
Guy German, Department of Bioengineering
Claudia Marques, Department of Biological Sciences
Atopic dermatitis (AD) is an important chronic inflammatory skin disease that often precedes the onset of allergic disorders. In recent years it has been demonstrated that patients with AD have reduced levels of ceramides in their outermost layer of skin, or stratum corneum, and a predisposition to infection and colonization by microbial organisms, particularly Staphylococcus aureus. Currently the mechanisms that lead to the onset of AD remain poorly understood. The goal of this research is to establish the effects of lipid depletion in human stratum corneum on the ability of S. aureus bacteria to cause atopic dermatitis. This work will bring together Dr. Cl谩udia Marques and Dr. Guy German on a trans-disciplinary project that focuses on skin susceptibility to disease due to the pathogenesis of the bacteria S. aureus. An improved understanding of the relevance of bacterial colonization to the onset of AD has the potential to reevaluate existing treatments and act as a building block for establishing new methods of prevention. Establishing methods to prevent or reduce AD will improve population health and is likely provide new insight into the onset of other dry skin disorders and diseases where cracking and lesions form.
A Machine Learning-Based Approach for Optimizing the Discovery of Brain-Based Risk Markers for Psychiatric Illness
Vladimir Miskovic, Department of Psychology
Brandon Gibb, Department of Psychology
Chun-An Chou, School of Systems Science and Industrial Engineering
Hiroki Sayama, Department of Bioengineering
The goal of identifying brain-based markers of risk for future psychiatric illness continues to elude investigators despite its high clinical importance. To address this challenge, we will develop a set of methodological tools for the automated discovery of brain-based risk markers that predict psychiatric status with high accuracy. In this interdisciplinary proposal we apply technical resources derived from clinical neuroscience, complex network analysis and bioinformatics to the analysis of spontaneous brain electrical rhythms collected from hundreds of children and adolescents falling within an age range that is critical for the emergence of psychiatric problems. Regional and network measures of neural function will be extracted from continuous brain signals to serve as potential predictors of clinical status on standardized psychiatric assessments. An automated, data driven approach based on machine learning algorithms will then sort through the brain signal patterns and select specifically those multivariate neurophysiological features with the greatest accuracy in predicting psychiatric outcomes. The combination of neuroscience technology with tools derived from bioinformatics and systems engineering holds great promise for novel breakthroughs in improving the accuracy of prognosis, diagnosis, and timely intervention to alleviate the immense health care costs of psychiatric disorders such as anxiety, depression and substance abuse.
Investigating Bacterial Biofilm Formation and Toxin Trafficking Using Microfluidic Technology
Jeffrey Schertzer, Department of Biological Sciences
Paul Chiarot, Department of Mechanical Engineering
Bacterial Outer Membrane Vesicles (OMVs) play important roles in acute and chronic human infections. They are ubiquitous, representing an important yet understudied contributor to the virulence of many pathogens. As we begin to unravel the mechanisms bacteria use to package and launch these microscopic weapons, we face significant limitations in our ability to study them on a molecular level. This is because, although all biological membranes have asymmetric lipid distribution, existing technologies are incapable of creating synthetic membranes with complex structure. Available membrane models are poor physiological mimics; particularly when studying the bacterial outer membrane, which is strongly asymmetric. This motivates the proposed interdisciplinary collaboration between biology and mechanical engineering. High-throughput microfluidics and interfacial self-assembly will be used to build asymmetric synthetic vesicles with controlled lipid composition in each leaflet of the bilayer membrane. Along with rapid production and asymmetric membranes, this technology allows for the size, uniformity, luminal content, and unilamellarity of the vesicles to be tightly controlled. Access to physiologically-relevant OMV-mimics will enable us to study the importance of OMVs to the biofilm lifestyle (given their abundance in the biofilm extracellular matrix). Going forward, mass-produced OMV-like biological nanoparticles will be useful in advancing vaccine development and drug delivery.
Design Optimization of Porous Scaffolds for Bone Regeneration
Ryan Willing, Department of Mechanical Engineering
Kaiming Ye, Department of Bioengineering
Bioresorbable scaffolds are an attractive alternative to bone grafts for replacing missing bone resulting from complex fractures or bone tumors. These scaffolds dissolve over time, and are designed to allow in-growth of new bone tissue which eventually replaces the scaffold. As of yet, the design of these scaffolds, in terms of microstructure and overall shape, has not been optimized such that healing time is minimized, the new bone has adequate mechanical strength, and the final bone structure has the correct (anatomical) shape. We hypothesize that a rigorous and systematic design technique called multiobjective design optimization (MDO) will allow us to examine the relationship between these performance measures and create patient-optimized bone scaffold designs. This research will use a computational model for predicting bone growth and scaffold resorption, which will be validated against companion experimental results where bone will be grown in 3D scaffold prototypes. The model will then be used to design patient-optimized scaffolds using MDO. The resulting design optimization technique will be an important tool for patient-specific bone scaffold design.
A New Strategy to Prevent Neoronal Glutamate Excitotoxicity
Christof Grewer, professor of chemistry
David Werner, assistant professor of psychology
Glutamate transporters play essential roles in controlling the levels of the neuro-transmitter glutamate in the normally-functioning mammalian brain. When energy supply to neurons is interrupted, as encountered under ischemic conditions, glutamate transporters reverse their transport direction, releasing glutamate into the extracellular space instead of taking it up. This uncontrolled glutamate release can result in the widespread death of neurons. The long-term goal of the present collaborative project between the Werner and Grewer laboratories is to explore new strategies to prevent glutamate-induced excitotoxicity under conditions of energy deprivation, potentially leading to new avenues to combat stroke. Specifically, our aim is to develop cell- permeable, competitive inhibitors that selectively block glutamate release by reverse transport, without minimally affecting glutamate uptake under physiological conditions. Preliminary results based on a compound we have already synthesized show that glutamate release can be blocked in a model system. Conceptually and methodologically, the proposed research is innovative because we expect to identify novel methods and strategies for modulation of the glutamate release rate. The expected results could be ultimately used to extend existing, or devise new strategies, to reduce the destructive role of glutamate release through glutamate reverse transport in neurodegenerative disease and stroke.
Eating for 100 Trillion: The Gut Microbiome, Food Additives and Metabolic Disorders
Gretchen Mahler, assistant professor of bioengineering
Anthony Fiumera, associate professor of biological sciences
Metabolic disorders are some of the most pressing health-related challenges. Approximately 35 percent of American adults and 17 percent of children are clinically obese, and obese individuals have an increased risk for Type 2 diabetes, hypertension and coronary heart disease. Obesity was estimated to have increased overall healthcare costs in the United States by $147 billion in 2008 alone. Recent studies have observed associations between the gut microbiome and metabolic disorders, and nanoparticles may be an environmental factor contributing to metabolic disorders through gut microbiome changes. The long-term goal of this work is to develop and utilize in vivo and in vitro systems to study ingested compound toxicity, genetic susceptibility, the role of the gut microbiome and the molecular mechanisms underlying genotype-by-environment interactions affecting metabolic disorders. This project will allow us to investigate how environmental nanoparticle exposure affects the gut microbiome and interacts with genetic variation in populations to influence disease susceptibility. Understanding these relationships, and the mechanisms that drive them, is critical for the development of prevention and intervention strategies at the policy, behavioral and biological levels; and this transdisciplinary work is relevant to the Health Sciences Steering Committee's Themes 1 and 4: Disease Susceptibility, Pathogenesis and Prevention and Individualized Therapeutics.
A Novel Mobile Human-Computer Interaction Approach Based on Wearable Eye-Controlled Glasses for Assisted Living and Health Care
Zhanpeng Jin, assistant professor of electrical and computer engineering
Sarah Laszlo, assistant professor of psychology
Human computer interaction (HCI) has gained widespread attention because of the increasing demands to interact with computers in a human cognitive sense. Nonconventional HCIs show great potential for controlling computers and smart appliances, which is of particular significance to people with disabilities requiring hands-free alternatives. The movement of the eyes contains a rich source of information and has been widely used as a tool to investigate visual cognition. In this study, we propose a new HCI paradigm, taking advantage of the recent glass-style wearable computing technology. Specifically, we will embed miniaturized dry sensors placed inside the glass arms, which will record eye movements through the measurement of electrooculograph (EOG) signals, and enable users to control the glass or wirelessly tethered devices via intentional eye movements. The aim of the proposed work is to explore a synergistic solution of a truly wearable, eye-controlled mobile HCI device, which can be seamlessly extended to a hands-free assistive control system for people with disabilities or special needs. Proposed research activities include developing a user-friendly, glass-style EOG acquisition system, recognizing and distinguishing various types and levels of eye movements, and investigating a comprehensive eye-movement encoding language for eye-controlled HCI applications.
Development of a Nanodelivery System for Enhanced Treatment of Biofilm-Related Infections
Amber Doiron, assistant professor of bioengineering
Karin Sauer, professor of biological sciences
A new collaborative project between Dr. Amber Doiron (Bioengineering Department) and Dr. Karin Sauer (Biological Sciences Department) was funded by the 2013 Health Sciences Transdisciplinary Area of Excellence. The project brings together Dr. Sauer's expertise in biofilms and Dr. Doiron's expertise in nanoparticle drug delivery formulations. Surface-associated bacterial communities known as biofilms pose significant problems in medicine due to their resistance to killing by antibiotics. Recent evidence suggests that microcolony formation, which is the first step of biofilms formed by Pseudomonas aeruginosa, requires a specific metabolite. Our primary objective is to develop a nanoparticle for co-delivery of agents targeting this metabolite and other aspects of the biolfilm and that may have clinical applications related to health concerns caused by biofilms. Findings from this research are anticipated to be translational with respect to treatment of biofilm infections in wounds and to enable a collaborative proposal to be submitted to the NIH or the DOD in the near future.
Principal investigators/deartments: Amber Doiron, assistant professor of bioengineering, and Karin Sauer, professor of biological sciences