Engineering Commons^™

Transport Barriers Influence The Activation Of Anti-Tumor Immunity: A Systems Biology Analysis, Mohammad R. Nikmaneshi, James W. Baish, Hengbo Zhou, Lance L. Munn

Faculty Journal Articles

Effective anti-cancer immune responses require activation of one or more naïve T cells. If the correct naïve T cell encounters its cognate antigen presented by an antigen presenting cell, then the T cell can activate and proliferate. Here, mathematical modeling is used to explore the possibility that immune activation in lymph nodes is a rate-limiting step in anti-cancer immunity and can affect response rates to immune checkpoint therapy. The model provides a mechanistic framework for optimizing cancer immunotherapy and developing testable solutions to unleash anti-tumor immune responses for more patients with cancer. The results show that antigen production rate and …

Marineepi: A Gui-Based Matlab Toolbox To Simulate Marine Pathogen Transmission, Gorka Bidegain, Tal Ben-Horin, Eric N. Powell, John M. Klinck, Eileen E. Hofmann

CCPO Publications

The Graphical User Interface (GUI) MarineEpi is presented as a Matlab toolbox for easily (i) constructing disease transmission models for different marine host-pathogen systems, (ii) running simulations by specifying initial conditions and model parameters, and (iii) interpreting the resulting time series of the host and pathogen population dynamics. MarineEpi users can generate models for systems in which pathogen transmission occurs through contact with infected individuals (SI), contact with dead infected individuals (SID), contact with environmental pathogens released by infected individuals (SIP), and contact with environmental pathogens released by dead infected individuals (SIPD). MarineEpi is a freely available GUI that provides …

Heart Disease Prediction Using Stacking Model With Balancing Techniques And Dimensionality Reduction, Ayesha Noor, Nadeem Javaid, Nabil Alrajeh, Babar Mansoor, Ali Khaqan, Safdar Hussain Bouk

School of Cybersecurity Faculty Publications

Heart disease is a serious worldwide health issue with wide-reaching effects. Since heart disease is one of the leading causes of mortality worldwide, early detection is crucial. Emerging technologies like Machine Learning (ML) are currently being actively used by the biomedical, healthcare, and health prediction industries. PaRSEL, a new stacking model is proposed in this research, that combines four classifiers, Passive Aggressive Classifier (PAC), Ridge Classifier (RC), Stochastic Gradient Descent Classifier (SGDC), and eXtreme Gradient Boosting (XGBoost), at the base layer, and LogitBoost is deployed for the final predictions at the meta layer. The imbalanced and irrelevant features in the …

A Unified Health Information System Framework For Connecting Data, People, Devices, And Systems, Wu He, Justin Zuopeng Zhang, Huanmei Wu, Wenzhuo Li, Sachin Shetty

Information Technology & Decision Sciences Faculty Publications

The COVID-19 pandemic has heightened the necessity for pervasive data and system interoperability to manage healthcare information and knowledge. There is an urgent need to better understand the role of interoperability in improving the societal responses to the pandemic. This paper explores data and system interoperability, a very specific area that could contribute to fighting COVID-19. Specifically, the authors propose a unified health information system framework to connect data, systems, and devices to increase interoperability and manage healthcare information and knowledge. A blockchain-based solution is also provided as a recommendation for improving the data and system interoperability in healthcare.

Novel Approaches For Enhancing Cell Survival And Function In Vivo, Ou Wang

Department of Chemical and Biomolecular Engineering: Theses and Student Research

FDA has approved several cell-based therapeutics and hundreds of cell therapy clinical trials are ongoing. Cells will be a significant type of medicine after small molecule and protein drugs. However, several obstacles need to be addressed to achieve the widespread use of cellular therapeutics. The first challenge is the low efficacy of cell transplantation due to low retention, survival, integration, and function of cells in vivo. The second challenge is producing a massive number of cells for clinical treatment with cost-effectively and reproducibly technologies.

In this thesis, we proposed and investigated two approaches to address these challenges. To begin …

Personalized Digital Phenotype Score, Healthcare Management And Intervention Strategies Using Knowledge Enabled Digital Health Framework For Pediatric Asthma, Utkarshani Jaimini, Amit Sheth

Publications

Asthma is a personalized, and multi-trigger respiratory condition which requires continuous monitoring and management of symptoms and medication adherence. We developed kHealth: Knowledge-enabled Digital Healthcare Framework to monitor and manage the asthma symptoms, medication adherence, lung function, daily activity, sleep quality, indoor, and outdoor environmental triggers of pediatric asthma patients. The kHealth framework collects up to 1852 data points per patient per day. It is practically impossible for the clinicians, parents, and the patient to analyze this vast amount of multimodal data collected from the kHealth framework. In this chapter, we describe the personalized scores, clinically relevant asthma categorization using …

Bibliometric Review On Applications Of Disease Detection Using Digital Image Processing Techniques, Jayant Jagtap, Rahil Sharma, Aryan Sinha, Nikhil Panda, Amulya Reddy

Library Philosophy and Practice (e-journal)

Advances around the field of deep learning and cognitive computing have allowed mankind to look and solve the problems of the world in a completely new way. Deep learning has been making huge advancements in the field of healthcare, which most importantly focuses upon disease detection and disease prediction. Techniques such as these have been conceptualized the idea of early detection and economical ways of treating the predicted disease in particular. Still, it has been observed that there seems to be no change in the way diagnosis of a particular disease takes place even in the 21^st generation of …

Feasibility Of Continuous Fever Monitoring Using Wearable Devices, Benjamin L. Smarr, Kirstin Aschbacher, Sarah M. Fisher, Anoushka Chowdhary, Stephan Dilchert, Karena Puldon, Adam Rao, Frederick M. Hecht, Ashley E. Mason

Publications and Research

Elevated core temperature constitutes an important biomarker for COVID-19 infection; however, no standards currently exist to monitor fever using wearable peripheral temperature sensors. Evidence that sensors could be used to develop fever monitoring capabilities would enable large-scale health-monitoring research and provide high-temporal resolution data on fever responses across heterogeneous populations. We launched the TemPredict study in March of 2020 to capture continuous physiological data, including peripheral temperature, from a commercially available wearable device during the novel coronavirus pandemic. We coupled these data with symptom reports and COVID-19 diagnosis data. Here we report findings from the first 50 subjects who reported …

Scalable Profiling And Visualization For Characterizing Microbiomes, Camilo Valdes

FIU Electronic Theses and Dissertations

Metagenomics is the study of the combined genetic material found in microbiome samples, and it serves as an instrument for studying microbial communities, their biodiversities, and the relationships to their host environments. Creating, interpreting, and understanding microbial community profiles produced from microbiome samples is a challenging task as it requires large computational resources along with innovative techniques to process and analyze datasets that can contain terabytes of information.

The community profiles are critical because they provide information about what microorganisms are present in the sample, and in what proportions. This is particularly important as many human diseases and environmental disasters …

Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre

Honors Scholar Theses

Abnormal ocular motility is a common manifestation of many underlying pathologies particularly those that are neurological. Dynamics of saccades, when the eye rapidly changes its point of fixation, have been characterized for many neurological disorders including concussions, traumatic brain injuries (TBI), and Parkinson’s disease. However, widespread saccade analysis for diagnostic and research purposes requires the recognition of certain eye movement parameters. Key information such as velocity and duration must be determined from data based on a wide set of patients’ characteristics that may range in eye shapes and iris, hair and skin pigmentation [36]. Previous work on saccade analysis has …

Modeling In The Physiology Classroom, Sowmya Anjur

Faculty Publications & Research

Physiology and Disease is a Biology elective at IMSA that has been developed to be mostly student-centered. Some examples of student projects include modeling heart structure to reflect function and creating LED arduino monitors to measure heart rate. Students also measure their lung capacity and blood pressure to demonstrate correlation of these values with heart rate, and trace the correlation back to neuronal controls. Projects such as these integrate other disciplines such as engineering and conform to NGSS Science and Engineering standards and NGSS Cross cutting Concepts standards. Students take responsibility for their own learning and articulate better on tests.

Pattern Discovery In Brain Imaging Genetics Via Scca Modeling With A Generic Non-Convex Penalty, Lei Du, Kefei Liu, Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen, Michael W. Weiner, Paul Aisen, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, John Morris, Leslie M. Shaw, Zaven Khachaturian, Greg Sorensen, Maria Carrillo, Lew Kuller, Marc Raichle, Steven Paul, Peter Davies, Howard Fillit, Franz Hefti, David Holtzman, Charles D. Smith, Gregory Jicha, Peter A. Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad

Neurology Faculty Publications

Brain imaging genetics intends to uncover associations between genetic markers and neuroimaging quantitative traits. Sparse canonical correlation analysis (SCCA) can discover bi-multivariate associations and select relevant features, and is becoming popular in imaging genetic studies. The L1-norm function is not only convex, but also singular at the origin, which is a necessary condition for sparsity. Thus most SCCA methods impose ℓ₁-norm onto the individual feature or the structure level of features to pursuit corresponding sparsity. However, the ℓ₁-norm penalty over-penalizes large coefficients and may incurs estimation bias. A number of non-convex penalties are proposed to reduce …

Modeling The Adaptive Immune Response To Mutation-Generated Antigens, Rory J. Geyer

University Scholar Projects

Somatic mutations may drive tumorigenesis or lead to new, immunogenic epitopes (neoantigens). The immune system is thought to represses neoplastic growths through the recognition of neoantigens presented only by tumor cells. To study mutations as well as the immune response to mutation-generated antigens, we have created a conditional knockin mouse line with a gene encoding, 5’ to 3’, yellow fluorescent protein (YFP), ovalbumin (which is processed to the immunologically recognizable peptide, SIINFEKL), and cyan fluorescent protein (CFP), or, YFP-ovalbumin-CFP. A frame shift mutation has been created at the 5’ end of the ovalbumin gene, hence YFP should always be expressed, …

Modeling The Adaptive Immune Response To Mutation-Generated Antigens, Rory J. Geyer

Honors Scholar Theses

Somatic mutations may drive tumorigenesis or lead to new, immunogenic epitopes (neoantigens). The immune system is thought to represses neoplastic growths through the recognition of neoantigens presented only by tumor cells. To study mutations as well as the immune response to mutation-generated antigens, we have created a conditional knockin mouse line with a gene encoding, 5’ to 3’, yellow fluorescent protein (YFP), ovalbumin (which is processed to the immunologically recognizable peptide, SIINFEKL), and cyan fluorescent protein (CFP), or, YFP-ovalbumin-CFP. A frame shift mutation has been created at the 5’ end of the ovalbumin gene, hence YFP should always be expressed, …