Medicine and Health Sciences Commons^™

Suspicion Encoded: Women Of Color And Biometric Technology In The United States, Lilith A. Saylor

sprinkle: an undergraduate journal of feminist and queer studies

This paper explores the commodification of privacy through biometric technology in the United States. It examines the impact of this technology on poor women of color (WOC), arguing that poor WOC face intersectional discrimination based on the convergence of sex, race, and class in their identities. I highlight the unique and powerful intrusion of biometric technology into the lives of poor WOC, and argue that the connection between data and the physical body created through biometric data has formed an environment in which the state wields unrestricted control in all spheres over the privacy of poor WOC.

Structural Characterization And In Vitro Antiproliferative Activity Of Non-Specific Lipid Transfer Protein 1 (Nsltp1) From Fennel (Foeniculum Vulgare) Seeds, Mekdes Megeressa

Pharmaceutical Sciences (PhD) Dissertations

Non-specific lipid transfer proteins (nsLTPs) are cationic proteins involved in intracellular lipid shuttling, in growth and reproduction, as well as in defense against pathogenic microbes. Even though the primary and spatial structures of some nsLTPs from different plants indicate their similar features, they exhibit distinct lipid-binding specificities signifying their various biological roles that dictate further structural study. The present study determined the complete amino acid sequence, in silico 3D structure modeling, and in vitro antiproliferative activity of nsLTP1 from fennel (Foeniculum vulgare) seeds.

Fennel is a member of the family Umbelliferae (Apiaceae) native to southern Europe and the …

Elucidating The Role Of The Tyrosine Phosphatase, Shp-2, In Regulation Of Pd-L1 Expression In Non-Small Lung Cancer Using Both Biochemical Analyses And Real-World Genomic Information, Keller Toral

Theses and Dissertations--Pharmacy

Immune checkpoint inhibitors (ICIs), especially those that target programmed cell death protein 1 (PD-1) and programmed cell death ligand-1 (PD-L1), have been shown to provide substantial clinical benefit in many patients with non-small cell lung cancer (NSCLC). While these therapeutic agents can be highly effective in the correct context, the biological systems that malignant cells draft from normal activities of the cell are poorly characterized. Tumor cell-specific expression of PD-L1 is likely important for clinical benefit from PD-1 and PD-L1 inhibitors. It is known that PD-L1 is inappropriately expressed in many cancers harboring mutations in the RAS family of genes. …

Towards Digestible Digital Health Solutions: Application Of A Health Literacy Inclusive Development Framework For Peripartum Depression Management, Alexandra Zingg, Tavleen Singh, Sahiti Myneni

Faculty, Staff and Student Publications

Women of low income and education have lower levels of peripartum depression (PPD) literacy, limiting their ability to recognize symptoms and make informed healthcare decisions. Existing digital solutions and underlying development frameworks for PPD lack an integrative approach addressing health literacy and related disparities. Therefore, we develop an integrative framework for digital content engineering in PPD self-management consisting of (a) user needs analysis, (b) inclusion of eHealth literacy principles (science and health literacy), and (c) mapping user needs to the Behavioral Intervention Technology model. Results revealed that perinatal women seeking mental health care prefer information in multisensory formats, and knowledge …

Cross-Vendor Ct Image Data Harmonization Using Cvh-Ct, Md Selim, Jie Zhang, Baowei Fei, Guo-Qiang Zhang, Gary Yeeming Ge, Jin Chen

Faculty, Staff and Student Publications

While remarkable advances have been made in Computed Tomography (CT), most of the existing efforts focus on imaging enhancement while reducing radiation dose. How to harmonize CT image data captured using different scanners is vital in cross-center large-scale radiomics studies but remains the boundary to explore. Furthermore, the lack of paired training image problem makes it computationally challenging to adopt existing deep learning models. We propose a novel deep learning approach called CVH-CT for harmonizing CT images captured using scanners from different vendors. The generator of CVH-CT uses a self-attention mechanism to learn the scanner-related information. We also propose a …

The Causes And Control Measures Of Extended Spectrum Beta-Lactamase Producing Enterobacteriaceae In Long-Term Care Facilities, Ismaila Olatunji Sule

Walden Dissertations and Doctoral Studies

Due to extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-PE), infections among residents are increasing in long-term care facilities (LTCFs), resulting in high rate of morbidity and healthcare costs. ESBL-PE resists empirical antibiotics and reduces treatment options, and a designated infection control team is unavailable to prevent the prevalence of the disease. Ecological theory guided this study. A systematic review and meta-analysis were conducted to characterize the causes of ESBL-PE and evaluate the infection control strategies within LTCFs. Multiple regression analysis (MRA) was included as supplementary statistical analysis to identify relationships between LTCFs, geographical locations, infection control measures (ICMs), and ESBL-PE. A systematic search …

A Comparison Of Exhaustive And Non-Lattice-Based Methods For Auditing Hierarchical Relations In Gene Ontology, Rashmie Abeysinghe, Fengbo Zheng, Licong Cui

Faculty, Staff and Student Publications

Uncovering and fixing errors in biomedical terminologies is essential so that they provide accurate knowledge to downstream applications that rely on them. Non-lattice-based methods have been applied to identify various kinds of inconsistencies in different biomedical terminologies. In previous work, we have introduced two inference-based approaches that were applied in an exhaustive manner to audit hierarchical relations in the Gene Ontology: (1) Lexical-based inference framework, and (2) Subsumption-based sub-term inference framework. However, it is unclear how effective these exhaustive approaches perform compared with their corresponding non-lattice-based approaches. Therefore, in this paper, we implement the non-lattice versions of these two exhaustive …

Identifying Sleep-Related Factors Associated With Cognitive Function In A Hispanics/Latinos Cohort: A Dual Random Forest Approach, Li Xiaojin, Cui Licong, Wang Fei, Paul E Schulz, Guo-Qiang Zhang

Faculty, Staff and Student Publications

Disordered sleep is associated with poor cognitive function and cognitive decline. However, little is known regarding the association of sleep-related factors with cognitive function in underrepresented cohorts such as the Hispanic/Latino population. Leveraging the National Sleep Research Resource, one of the most comprehensive collections of sleep studies, we identified a Hispanic/Latino cohort of 1,031 lower cognitive function cases and 2,062 normal controls. We developed a novel dual random forest (DRF) approach to discriminate cases against controls for estimating the potential impact of sleep-related variables related to the decline of cognitive function. Several important sleep-related factors were identified which may be …

Impact Of Case Management On Childhood Lead Exposure In Marion County, Indiana, Maliki Yacouba

Walden Dissertations and Doctoral Studies

The Centers for Disease Control and Prevention recently declared that no amount of childhood blood lead level (BLL) is safe. The purpose of this quantitative study with a retrospective cohort design was to evaluate the effectiveness of case management intervention on children diagnosed with elevated BLL (EBLL; ≥ 5 μg/dL) in Marion, County, Indiana. The health belief model was used as the theoretical foundation for the study. A data set of 160 lead exposure case management records was analyzed to find whether: (a) BLL at post-case-management time significantly differ from BLL at baseline (b) BLL at post-case-management time is affected …

Deep Learning For Automated Analysis Of Cellular And Extracellular Components Of The Foreign Body Response In Multiphoton Microscopy Images, Mattia Sarti, Maria Parlani, Luis Diaz-Gomez, Antonios G Mikos, Pietro Cerveri, Stefano Casarin, Eleonora Dondossola

Faculty, Staff and Student Publications

The Foreign body response (FBR) is a major unresolved challenge that compromises medical implant integration and function by inflammation and fibrotic encapsulation. Mice implanted with polymeric scaffolds coupled to intravital non-linear multiphoton microscopy acquisition enable multiparametric, longitudinal investigation of the FBR evolution and interference strategies. However, follow-up analyses based on visual localization and manual segmentation are extremely time-consuming, subject to human error, and do not allow for automated parameter extraction. We developed an integrated computational pipeline based on an innovative and versatile variant of the U-Net neural network to segment and quantify cellular and extracellular structures of interest, which is …

Carving The Path To Allogeneic Car T Cell Therapy In Acute Myeloid Leukemia, Oren Pasvolsky, May Daher, Gheath Alatrash, David Marin, Naval Daver, Farhad Ravandi, Katy Rezvani, Elizabeth Shpall, Partow Kebriaei

Faculty, Staff and Student Publications

Despite advances in the understanding of the genetic landscape of acute myeloid leukemia (AML) and the addition of targeted biological and epigenetic therapies to the available armamentarium, achieving long-term disease-free survival remains an unmet need. Building on growing knowledge of the interactions between leukemic cells and their bone marrow microenvironment, strategies to battle AML by immunotherapy are under investigation. In the current review we describe the advances in immunotherapy for AML, with a focus on chimeric antigen receptor (CAR) T cell therapy. CARs constitute powerful immunologic modalities, with proven clinical success in B-Cell malignancies. We discuss the challenges and possible …

Loss-Of-Function Genomic Variants Highlight Potential Therapeutic Targets For Cardiovascular Disease, Jonas B. Nielsen, Oren Rom, Ida Surakka, Sarah E. Graham, Wei Zhou, Tanmoy Roychowdhury, Lars G. Fritsche, Sarah A. Gagliano Taliun, Carlo Sidore, Yuhao Liu, Maiken E. Gabrielsen, Anne Heidi Skogholt, Brooke Wolford, William Overton, Ying Zhao, Jin Chen, He Zhang, Whitney E. Hornsby, Akua Acheampong, Austen Grooms, Amanda Schaefer, Gregory J. M. Zajac, Luis Villacorta, Jifeng Zhang, Ben Brumpton, Mari Løset, Vivek Rai, Pia R. Lundegaard, Morten S. Olesen, Kent D. Taylor, Donna K. Arnett

Epidemiology and Environmental Health Faculty Publications

Pharmaceutical drugs targeting dyslipidemia and cardiovascular disease (CVD) may increase the risk of fatty liver disease and other metabolic disorders. To identify potential novel CVD drug targets without these adverse effects, we perform genome-wide analyses of participants in the HUNT Study in Norway (n = 69,479) to search for protein-altering variants with beneficial impact on quantitative blood traits related to cardiovascular disease, but without detrimental impact on liver function. We identify 76 (11 previously unreported) presumed causal protein-altering variants associated with one or more CVD- or liver-related blood traits. Nine of the variants are predicted to result in loss-of-function of …

Outlier Concepts Auditing Methodology For A Large Family Of Biomedical Ontologies, Ling Zheng, Hua Min, Yan Chen, Vipina Keloth, James Geller, Yehoshua Perl, George Hripcsak

Publications and Research

Background: Summarization networks are compact summaries of ontologies. The “Big Picture” view offered by summarization networks enables to identify sets of concepts that are more likely to have errors than control concepts. For ontologies that have outgoing lateral relationships, we have developed the "partial-area taxonomy" summarization network. Prior research has identified one kind of outlier concepts, concepts of small partials-areas within partial-area taxonomies. Previously we have shown that the small partial-area technique works successfully for four ontologies (or their hierarchies).

Methods: To improve the Quality Assurance (QA) scalability, a family-based QA framework, where one QA technique is potentially applicable to …

Missing Lateral Relationships In Top‑Level Concepts Of An Ontology, Ling Zheng, Yan Chen, Hua Min, P. Lloyd Hildebrand, Hao Liu, Michael Halper, James Geller, Sherri De Coronado, Yehoshua Perl

Publications and Research

Background: Ontologies house various kinds of domain knowledge in formal structures, primarily in the form of concepts and the associative relationships between them. Ontologies have become integral components of many health information processing environments. Hence, quality assurance of the conceptual content of any ontology is critical. Relationships are foundational to the definition of concepts. Missing relationship errors (i.e., unintended omissions of important definitional relationships) can have a deleterious effect on the quality of an ontology. An abstraction network is a structure that overlays an ontology and provides an alternate, summarization view of its contents. One kind of abstraction network is …

Pathway‐Extended Gene Expression Signatures Integrate Novel Biomarkers That Improve Predictions Of Patient Responses To Kinase Inhibitors, Ashis Bagchee‐Clark, Eliseos J. Mucaki, Tyson Whitehead, Peter Rogan

Biochemistry Publications

Cancer chemotherapy responses have been related to multiple pharmacogenetic biomarkers, often for the same drug. This study utilizes machine learning to derive multi‐gene expression signatures that predict individual patient responses to specific tyrosine kinase inhibitors, including erlotinib, gefitinib, sorafenib, sunitinib, lapatinib and imatinib. Support vector machine (SVM) learning was used to train mathematical models that distinguished sensitivity from resistance to these drugs using a novel systems biology‐based approach. This began with expression of genes previously implicated in specific drug responses, then expanded to evaluate genes whose products were related through biochemical pathways and interactions. Optimal pathway‐extended SVMs predicted responses in …

A Context-Forward In Vivo Functional Genomics Platform For Target Discovery And Establishing Vulnerability Context In Pancreatic Cancer, Johnathon Rose, Johnathon Lynn Rose

Dissertations and Theses (Open Access)

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a very poor patient prognosis (5-year survival of ≤ 7%). While transcriptional profiling has aided in the classification of this disease into at least two broader subtypes, this alone has so far been insufficient to inform on more nuanced patterns of oncogenic dependency. We hypothesized that a more comprehensive and granular characterization of PDAC disease diversity is required to establish relevant context for targeted therapy. To this end, we sought to establish an integrated platform to: i) more comprehensively characterize differential oncogenic signaling across our tumor models, and ii) establish …

Development Of Computational To Ols To Target Microrna, Luo Song

Dissertations and Theses (Open Access)

MicroRNAs (a.k.a, miRNAs) play an important role in disease development. However, few of their structures have been determined and structure-based computational methods remain challenging in accurately predicting their interactions with small molecules. To address this issue, my thesis is to develop integrated approaches to screening for novel inhibitors by targeting specific structure motifs in miRNAs. The project starts with implementing a tool to find potential miRNA targets with desired motifs. I combined both sequence information of miRNAs and known RNA structure data from Protein Data Bank (PDB) to predict the miRNA structure and identify the motif to target, then I …

Investigation Of Proliferation Suppressors In Genetic Fitness Screens, Walter Frank Lenoir Iv

Dissertations and Theses (Open Access)

Innovation of CRISPR gene-editing technology has provided scientists genome manipulation tools that allowed rapid advancement of scientific capabilities and thus improved our ability to systematically study mammalian genetic functional profiles. Genome-wide CRISPR knockout screens conducted in collections of human cell lines can knock out genes at multiple loci, and have provided new insights into functional roles for independent genes. This method has launched massive efforts in looking across genetic backgrounds for context specific genetic vulnerabilities within cancer. Much of the research effort thus far has been spent on optimizing phenotype distinctions between essential, genes required for cell fitness, and non-essential, …

Security And Privacy When Applying Fair Principles To Genomic Information, Jaime Delgado, Silvia Llorente

Faculty, Staff and Student Publications

Making data Findable, Accessible, Interoperable and Reusable (FAIR) is a good approach when data needs to be shared. However, security and privacy are still critical aspects. In the FAIRification process, there is a need both for de-identification of data and for license attribution. The paper analyses some of the issues related to this process when the objective is sharing genomic information. The main results are the identification of the already existing standards that could be used for this purpose and how to combine them. Nevertheless, the area is quickly evolving and more specific standards could be specified.

Pathway-Extended Gene Expression Signatures Integrate Novel Biomarkers That Improve Predictions Of Patient Responses To Kinase Inhibitors, Ashis Jem Bagchee-Clark, Eliseos J. Mucaki, Tyson Whitehead, Peter Rogan

Biochemistry Publications

No abstract provided.

Genome-Wide Dna Methylation Profiling In Human Breast Tissue By Illumina Truseq Methyl Capture Epic Sequencing And Infinium Methylationepic Beadchip Microarray, Nan Lin, Jinpeng Liu, James Castle, Jun Wan, Aditi Shendre, Yunlong Liu, Chi Wang, Chunyan He

Markey Cancer Center Faculty Publications

A newly-developed platform, the Illumina TruSeq Methyl Capture EPIC library prep (TruSeq EPIC), builds on the content of the Infinium MethylationEPIC Beadchip Microarray (EPIC-array) and leverages the power of next-generation sequencing for targeted bisulphite sequencing. We empirically examined the performance of TruSeq EPIC and EPIC-array in assessing genome-wide DNA methylation in breast tissue samples. TruSeq EPIC provided data with a much higher density in the regions when compared to EPIC-array (~2.74 million CpGs with at least 10X coverage vs ~752 K CpGs, respectively). Approximately 398 K CpGs were common and measured across the two platforms in every sample. Overall, there …

Representation Of Ehr Data For Predictive Modeling: A Comparison Between Umls And Other Terminologies, Laila Rasmy, Firat Tiryaki, Yujia Zhou, Yang Xiang, Cui Tao, Hua Xu, Degui Zhi

Faculty, Staff and Student Publications

OBJECTIVE: Predictive disease modeling using electronic health record data is a growing field. Although clinical data in their raw form can be used directly for predictive modeling, it is a common practice to map data to standard terminologies to facilitate data aggregation and reuse. There is, however, a lack of systematic investigation of how different representations could affect the performance of predictive models, especially in the context of machine learning and deep learning.

MATERIALS AND METHODS: We projected the input diagnoses data in the Cerner HealthFacts database to Unified Medical Language System (UMLS) and 5 other terminologies, including CCS, CCSR, …

Integrated Multiparametric Radiomics And Informatics System For Characterizing Breast Tumor Characteristics With The Oncotypedx Gene Assay, Michael A. Jacobs, Christopher B. Umbricht, Vishwa S. Parekh, Riham H. El Khouli, Leslie Cope, Katarzyna J. Macura, Susan Harvey, Antonio C. Wolff

Radiology Faculty Publications

Optimal use of multiparametric magnetic resonance imaging (mpMRI) can identify key MRI parameters and provide unique tissue signatures defining phenotypes of breast cancer. We have developed and implemented a new machine-learning informatic system, termed Informatics Radiomics Integration System (IRIS) that integrates clinical variables, derived from imaging and electronic medical health records (EHR) with multiparametric radiomics (mpRad) for identifying potential risk of local or systemic recurrence in breast cancer patients. We tested the model in patients (n = 80) who had Estrogen Receptor positive disease and underwent OncotypeDX gene testing, radiomic analysis, and breast mpMRI. The IRIS method was trained …

Atom Identifiers Generated By A Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization Across Metabolic Databases, Huan Jin, Joshua M. Mitchell, Hunter N. B. Moseley

Molecular and Cellular Biochemistry Faculty Publications

Metabolic flux analysis requires both a reliable metabolic model and reliable metabolic profiles in characterizing metabolic reprogramming. Advances in analytic methodologies enable production of high-quality metabolomics datasets capturing isotopic flux. However, useful metabolic models can be difficult to derive due to the lack of relatively complete atom-resolved metabolic networks for a variety of organisms, including human. Here, we developed a neighborhood-specific graph coloring method that creates unique identifiers for each atom in a compound facilitating construction of an atom-resolved metabolic network. What is more, this method is guaranteed to generate the same identifier for symmetric atoms, enabling automatic identification of …

Current Scenario Of Covid-19 With Epidemiological And Phylogenetic Analysis Of Pakistani Coronavirus: A Review, Asma Altaf, Wafa Iqbal, Sidra Younis, Farah Deeba

Journal of Bioresource Management

A novel corona virus named as 2019 n-CoV was identified to be the actual cause of an outbreak of respiratory illness in Wuhan, China beginning in late December 2019. This respiratory disease was named as COVID-19 by WHO. There are many countries affected by COVID-19 including Pakistan. In this review we have provided a brief introduction of COVID-19 and discussed epidemiological and phylogenetic analysis of Pakistani novel corona virus strain. Our epidemiological analysis of data till 16^th May 2020 showed rapidly increasing number of new cases, while at the same time a higher recovery rate than number of deaths …

Mechanism Of Translation Inhibition By Type Ii Gnat Toxin Atat2, Stepan V Ovchinnikov, Dmitry Bikmetov, Alexei Livenskyi, Marina Serebryakova, Brendan Wilcox, Kyle Mangano, Dmitrii I Shiriaev, Ilya A Osterman, Petr V Sergiev, Sergei Borukhov, Nora Vazquez-Laslop, Alexander S Mankin, Konstantin Severinov, Svetlana Dubiley

Rowan-Virtua School of Osteopathic Medicine Departmental Research

Type II toxin-antitoxins systems are widespread in prokaryotic genomes. Typically, they comprise two proteins, a toxin, and an antitoxin, encoded by adjacent genes and forming a complex in which the enzymatic activity of the toxin is inhibited. Under stress conditions, the antitoxin is degraded liberating the active toxin. Though thousands of various toxin-antitoxins pairs have been predicted bioinformatically, only a handful has been thoroughly characterized. Here, we describe the AtaT2 toxin from a toxin-antitoxin system from Escherichia coli O157:H7. We show that AtaT2 is the first GNAT (Gcn5-related N-acetyltransferase) toxin that specifically targets charged glycyl tRNA. In vivo, the AtaT2 …

A Lung Cancer Screening Personalized Decision-Aid Improves Knowledge And Reduces Decisional Conflict Among A Diverse Population Of Smokers At An Urban Academic Medical Center, Madeline Kaufman, Nilan Schnure, Andrea Nicholson, Frank Leone, Carmen Guerra

Journal of Health Disparities Research and Practice

Introduction: Few lung cancer screening decision aids have been tested in diverse populations. The study objective was to determine whether the online decision aid www.shouldiscreen.com impacts knowledge of and decisional conflict around lung cancer screening in a diverse population.

Methods: Eligible patients had significant smoking histories, were at increased risk for lung cancer (ages 45-80, >20 pack-years, smoking within last 15 years) and had no history of prior lung cancer or screening. Data was collected and analyzed in 2017.

Results: 40 patients were enrolled: 80% were female, 62.5% black, 33% white, and 48% had a high school …

A Neutrosophic Clinical Decision-Making System For Cardiovascular Diseases Risk Analysis, Florentin Smarandache, Shaista Habib, Wardat-Us- Salam, M. Arif Butt, Muhammad Akram

Branch Mathematics and Statistics Faculty and Staff Publications

Cardiovascular diseases are the leading cause of death worldwide. Early diagnosis of heart disease can reduce this large number of deaths so that treatment can be carried out. Many decision-making systems have been developed, but they are too complex for medical professionals. To target these objectives, we develop an explainable neutrosophic clinical decision-making system for the timely diagnose of cardiovascular disease risk. We make our system transparent and easy to understand with the help of explainable artificial intelligence techniques so that medical professionals can easily adopt this system. Our system is taking thirtyfive symptoms as input parameters, which are, gender, …

Understanding Spatial Language In Radiology: Representation Framework, Annotation, And Spatial Relation Extraction From Chest X-Ray Reports Using Deep Learning, Surabhi Datta, Yuqi Si, Laritza Rodriguez, Sonya E Shooshan, Dina Demner-Fushman, Kirk Roberts

Faculty, Staff and Student Publications

Radiology reports contain a radiologist's interpretations of images, and these images frequently describe spatial relations. Important radiographic findings are mostly described in reference to an anatomical location through spatial prepositions. Such spatial relationships are also linked to various differential diagnoses and often described through uncertainty phrases. Structured representation of this clinically significant spatial information has the potential to be used in a variety of downstream clinical informatics applications. Our focus is to extract these spatial representations from the reports. For this, we first define a representation framework based on the Spatial Role Labeling (SpRL) scheme, which we refer to as …

Β-Amyloid And Tau Drive Early Alzheimer's Disease Decline While Glucose Hypometabolism Drives Late Decline, Tyler C. Hammond, Xin Xing, Chris Wang, David Ma, Kwangsik Nho, Paul K. Crane, Fanny Elahi, David A. Ziegler, Gongbo Liang, Qiang Cheng, Lucille M. Yanckello, Nathan Jacobs, Ai-Ling Lin

Sanders-Brown Center on Aging Faculty Publications

Clinical trials focusing on therapeutic candidates that modify β-amyloid (Aβ) have repeatedly failed to treat Alzheimer’s disease (AD), suggesting that Aβ may not be the optimal target for treating AD. The evaluation of Aβ, tau, and neurodegenerative (A/T/N) biomarkers has been proposed for classifying AD. However, it remains unclear whether disturbances in each arm of the A/T/N framework contribute equally throughout the progression of AD. Here, using the random forest machine learning method to analyze participants in the Alzheimer’s Disease Neuroimaging Initiative dataset, we show that A/T/N biomarkers show varying importance in predicting AD development, with elevated biomarkers of Aβ …