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 Binghamton University's expertise toward a national reputation in the broad area of health sciences.

Predicting Conversion to Psychosis in At-Risk Youth: The Role of Stress-Inflammation Interactions

Principle investigators/department:

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

Principle investigators/departments:

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

Principle investigators/departments:

Prahalada Rao, Department of Systems Science and Industrial Engineering
Chun-An Chou, Department 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

Principle investigators/department:

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?

Principal investigators/departments:

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. Cláudia 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

Principal investigators/departments:

Vladimir Miskovic, Department of Psychology
Brandon Gibb, Department of Psychology
Chun-An Chou, Department 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

Principal investigators/departments:

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

Principal investigators/departments:

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

Principal investigators/departments:

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

Principal investigators/departments:

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

Principal investigators/departments:

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

Principal investigators/deartments:

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