Medicine and Health Sciences Commons^™

Enabling Precision Medicine In Cancer Care Through A Molecular Data Warehouse: The Moffitt Experience, Steven A Eschrich, Jamie K Teer, Phillip Reisman, Erin Siegel, Chandan Challa, Patricia Lewis, Katherine Fellows, Everin Malpica, Rodrigo Carvajal, Guillermo Gonzalez, Scott Cukras, Miguel Betin-Montes, Garrick Aden-Buie, Melissa Avedon, Daniel Manning, Aik Choon Tan, Brooke L Fridley, Travis Gerke, Mattias Van Looveren, Amilcar Blake, Jennifer Greenman, Dana E Rollison

Faculty, Staff and Students Publications

PURPOSE: The use of genomics within cancer research and clinical oncology practice has become commonplace. Efforts such as The Cancer Genome Atlas have characterized the cancer genome and suggested a wealth of targets for implementing precision medicine strategies for patients with cancer. The data produced from research studies and clinical care have many potential secondary uses beyond their originally intended purpose. Effective storage, query, retrieval, and visualization of these data are essential to create an infrastructure to enable new discoveries in cancer research.

METHODS: Moffitt Cancer Center implemented a molecular data warehouse to complement the extensive enterprise clinical data warehouse …

Proteogenomic And Metabolomic Characterization Of Human Glioblastoma, Liang-Bo Wang, Alla Karpova, Marina A Gritsenko, Jennifer E Kyle, Song Cao, Yize Li, Dmitry Rykunov, Antonio Colaprico, Joseph H Rothstein, Runyu Hong, Vasileios Stathias, Macintosh Cornwell, Francesca Petralia, Yige Wu, Boris Reva, Karsten Krug, Pietro Pugliese, Emily Kawaler, Lindsey K Olsen, Wen-Wei Liang, Xiaoyu Song, Yongchao Dou, Michael C Wendl, Wagma Caravan, Wenke Liu, Daniel Cui Zhou, Jiayi Ji, Chia-Feng Tsai, Vladislav A Petyuk, Jamie Moon, Weiping Ma, Rosalie K Chu, Karl K Weitz, Ronald J Moore, Matthew E Monroe, Rui Zhao, Xiaolu Yang, Seungyeul Yoo, Azra Krek, Alexis Demopoulos, Houxiang Zhu, Matthew A Wyczalkowski, Joshua F Mcmichael, Brittany L Henderson, Caleb M Lindgren, Hannah Boekweg, Shuangjia Lu, Jessika Baral, Lijun Yao, Kelly G Stratton, Lisa M Bramer, Erika Zink, Sneha P Couvillion, Kent J Bloodsworth, Shankha Satpathy, Weiva Sieh, Simina M Boca, Stephan Schürer, Feng Chen, Maciej Wiznerowicz, Karen A Ketchum, Emily S Boja, Christopher R Kinsinger, Ana I Robles, Tara Hiltke, Mathangi Thiagarajan, Alexey I Nesvizhskii, Bing Zhang, D R Mani, Michele Ceccarelli, Xi S Chen, Sandra L Cottingham, Qing Kay Li, Albert H Kim, David Fenyö, Kelly V Ruggles, Henry Rodriguez, Mehdi Mesri, Samuel H Payne, Adam C Resnick, Pei Wang, Richard D Smith, Antonio Iavarone, Milan G Chheda, Jill S Barnholtz-Sloan, Karin D Rodland, Tao Liu, Li Ding, Clinical Proteomic Tumor Analysis Consortium

Faculty, Staff and Students Publications

Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM …

Zno Nucleation Into Trititanate Nanotubes By Ald Equipment Techniques, A New Way To Functionalize Layered Metal Oxides, Mabel Moreno, Miryam Arredondo, Quentin M Ramasse, Matthew Mclaren, Philine Stötzner, Stefan Förster, Eglantina Benavente, Caterina Salgado, Sindy Devis, Paula Solar, Luis Velasquez, Guillermo González

Faculty, Staff and Students Publications

In this contribution, we explore the potential of atomic layer deposition (ALD) techniques for developing new semiconductor metal oxide composites. Specifically, we investigate the functionalization of multi-wall trititanate nanotubes, H2Ti3O7 NTs (sample T1) with zinc oxide employing two different ALD approaches: vapor phase metalation (VPM) using diethylzinc (Zn(C2H5)2, DEZ) as a unique ALD precursor, and multiple pulsed vapor phase infiltration (MPI) using DEZ and water as precursors. We obtained two different types of tubular H2Ti3O7 species containing ZnO in their structures. Multi-wall trititanate nanotubes with ZnO intercalated inside the tube wall sheets were the main products from the VPM infiltration …

Generalized And Transferable Patient Language Representation For Phenotyping With Limited Data, Yuqi Si, Elmer V Bernstam, Kirk Roberts

Faculty, Staff and Student Publications

The paradigm of representation learning through transfer learning has the potential to greatly enhance clinical natural language processing. In this work, we propose a multi-task pre-training and fine-tuning approach for learning generalized and transferable patient representations from medical language. The model is first pre-trained with different but related high-prevalence phenotypes and further fine-tuned on downstream target tasks. Our main contribution focuses on the impact this technique can have on low-prevalence phenotypes, a challenging task due to the dearth of data. We validate the representation from pre-training, and fine-tune the multi-task pre-trained models on low-prevalence phenotypes including 38 circulatory diseases, 23 …

A Principal Components Analysis Of Factors Associated With Successful Implementation Of An Lvad Decision Support Tool, Kristin M Kostick, Meredith Trejo, Arvind Bhimaraj, Andrew Civitello, Jonathan Grinstein, Douglas Horstmanshof, Ulrich P Jorde, Matthias Loebe, Mandeep R Mehra, Nasir Z Sulemanjee, Vinay Thohan, Barry H Trachtenberg, Nir Uriel, Robert J Volk, Jerry D Estep, J S Blumenthal-Barby

Faculty, Staff and Students Publications

BACKGROUND: A central goal among researchers and policy makers seeking to implement clinical interventions is to identify key facilitators and barriers that contribute to implementation success. Despite calls from a number of scholars, empirical insights into the complex structural and cultural predictors of why decision aids (DAs) become routinely embedded in health care settings remains limited and highly variable across implementation contexts.

METHODS: We examined associations between "reach", a widely used indicator (from the RE-AIM model) of implementation success, and multi-level site characteristics of nine LVAD clinics engaged over 18 months in implementation and dissemination of a decision aid for …

A Deep Learning Approach To Diagnostic Classification Of Prostate Cancer Using Pathology–Radiology Fusion, Pegah Khosravi, Maria Lysandrou, Mahmoud Eljalby, Qianzi Li, Ehsan Kazemi, Pantelis Zisimopoulos, Alexandros Sigaras, Matthew Brendel, Josue Barnes, Camir Ricketts, Dmitry Meleshko, Andy Yat, Timothy D. Mcclure, Brian D. Robinson, Andrea Sboner, Olivier Elemento, Bilal Chughtai, Iman Hajirasouliha

Publications and Research

Background

A definitive diagnosis of prostate cancer requires a biopsy to obtain tissue for pathologic analysis, but this is an invasive procedure and is associated with complications.

Purpose

To develop an artificial intelligence (AI)-based model (named AI-biopsy) for the early diagnosis of prostate cancer using magnetic resonance (MR) images labeled with histopathology information.

Study Type

Retrospective.

Population

Magnetic resonance imaging (MRI) data sets from 400 patients with suspected prostate cancer and with histological data (228 acquired in-house and 172 from external publicly available databases).

Field Strength/Sequence

1.5 to 3.0 Tesla, T2-weighted image pulse sequences.

Assessment

MR images reviewed and selected …

Discovery And Characterization Of Bromodomain 2-Specific Inhibitors Of Brdt, Zhifeng Yu, Angela F Ku, Justin L Anglin, Rajesh Sharma, Melek Nihan Ucisik, John C Faver, Feng Li, Pranavanand Nyshadham, Nicholas Simmons, Kiran L Sharma, Sureshbabu Nagarajan, Kevin Riehle, Gundeep Kaur, Banumathi Sankaran, Marta Storl-Desmond, Stephen S Palmer, Damian W Young, Choel Kim, Martin M Matzuk

Faculty, Staff and Students Publications

Bromodomain testis (BRDT), a member of the bromodomain and extraterminal (BET) subfamily that includes the cancer targets BRD2, BRD3, and BRD4, is a validated contraceptive target. All BET subfamily members have two tandem bromodomains (BD1 and BD2). Knockout mice lacking BRDT-BD1 or both bromodomains are infertile. Treatment of mice with JQ1, a BET BD1/BD2 nonselective inhibitor with the highest affinity for BRD4, disrupts spermatogenesis and reduces sperm number and motility. To assess the contribution of each BRDT bromodomain, we screened our collection of DNA-encoded chemical libraries for BRDT-BD1 and BRDT-BD2 binders. High-enrichment hits were identified and resynthesized off-DNA and examined …

Tools For Visualizing And Analyzing Fourier Space Sampling In Cryo-Em, Philip R Baldwin, Dmitry Lyumkis

Faculty, Staff and Students Publications

A complete understanding of how an orientation distribution contributes to a cryo-EM reconstruction remains lacking. It is necessary to begin critically assessing the set of views to gain an understanding of its effect on experimental reconstructions. Toward that end, we recently suggested that the type of orientation distribution may alter resolution measures in a systematic manner. We introduced the sampling compensation factor (SCF), which incorporates how the collection geometry might change the spectral signal-to-noise ratio (SSNR), irrespective of the other experimental aspects. We show here that knowledge of the sampling restricted to spherical surfaces of sufficiently large radii in Fourier …

Evaluating The Revised American Society For Gastrointestinal Endoscopy Guidelines For Common Bile Duct Stone Diagnosis, Jake S Jacob, Michelle E Lee, Erin Y Chew, Aaron P Thrift, Robert J Sealock

Faculty, Staff and Students Publications

BACKGROUND/AIMS: The American Society for Gastrointestinal Endoscopy (ASGE) revised its guidelines for risk stratification of patients with suspected choledocholithiasis. This study aimed to assess the diagnostic performance of the revision and to compare it to the previous guidelines.

METHODS: We conducted a retrospective cohort study of 267 patients with suspected choledocholithiasis. We identified high-risk patients according to the original and revised guidelines and examined the diagnostic accuracy of both guidelines. We measured the association between individual criteria and choledocholithiasis.

RESULTS: Under the original guidelines, 165 (62%) patients met the criteria for high risk, of whom 79% had confirmed choledocholithiasis. The …

Continuous-Flow Left Ventricular Assist Device Therapy In Adults With Transposition Of The Great Vessels, Tadahisa Sugiura, Chitaru Kurihara, Masashi Kawabori, Andre C Critsinelis, Andrew B Civitello, Jeffrey A Morgan, O H Frazier

Faculty, Staff and Students Publications

An increasing number of children with congenital heart disease are surviving into adulthood and subsequently developing end-stage heart failure. Two example populations are adults who have been previously operated on for congenitally corrected transposition of the great arteries (CCTGA) and transposition of the great arteries (TGA). Implantation of a continuous flow left ventricular assist device (CF-LVAD) in these patients can present unusual anatomical and physiologic challenges. In this report, we describe outcomes of CF-LVAD implantation in three such patients. These cases demonstrate the feasibility of implanting a CF-LVAD in patients who have undergone surgery for CCTGA and/or TGA.

The Mitochondrial Protease Lonp1 Promotes Proteasome Inhibitor Resistance In Multiple Myeloma, Laure Maneix, Melanie A Sweeney, Sukyeong Lee, Polina Iakova, Shannon E Moree, Ergun Sahin, Premal Lulla, Sarvari V Yellapragada, Francis T F Tsai, Andre Catic

Faculty, Staff and Students Publications

Multiple myeloma and its precursor plasma cell dyscrasias affect 3% of the elderly population in the US. Proteasome inhibitors are an essential part of several standard drug combinations used to treat this incurable cancer. These drugs interfere with the main pathway of protein degradation and lead to the accumulation of damaged proteins inside cells. Despite promising initial responses, multiple myeloma cells eventually become drug resistant in most patients. The biology behind relapsed/refractory multiple myeloma is complex and poorly understood. Several studies provide evidence that in addition to the proteasome, mitochondrial proteases can also contribute to protein quality control outside of …

Exchanges In A Virtual Environment For Diabetes Self-Management Education And Support: Social Network Analysis, Carlos A Pérez-Aldana, Allison A Lewinski, Constance M Johnson, Allison A Vorderstrasse, Sahiti Myneni

Faculty, Staff and Student Publications

BACKGROUND: Diabetes remains a major health problem in the United States, affecting an estimated 10.5% of the population. Diabetes self-management interventions improve diabetes knowledge, self-management behaviors, and clinical outcomes. Widespread internet connectivity facilitates the use of eHealth interventions, which positively impacts knowledge, social support, and clinical and behavioral outcomes. In particular, diabetes interventions based on virtual environments have the potential to improve diabetes self-efficacy and support, while being highly feasible and usable. However, little is known about the patterns of social interactions and support taking place within type 2 diabetes-specific virtual communities.

OBJECTIVE: The objective of this study was to …

Spliceosome-Targeted Therapies Trigger An Antiviral Immune Response In Triple-Negative Breast Cancer, Elizabeth A Bowling, Jarey H Wang, Fade Gong, William Wu, Nicholas J Neill, Ik Sun Kim, Siddhartha Tyagi, Mayra Orellana, Sarah J Kurley, Rocio Dominguez-Vidaña, Hsiang-Ching Chung, Tiffany Y-T Hsu, Julien Dubrulle, Alexander B Saltzman, Heyuan Li, Jitendra K Meena, Gino M Canlas, Srinivas Chamakuri, Swarnima Singh, Lukas M Simon, Calla M Olson, Lacey E Dobrolecki, Michael T Lewis, Bing Zhang, Ido Golding, Jeffrey M Rosen, Damian W Young, Anna Malovannaya, Fabio Stossi, George Miles, Matthew J Ellis, Lihua Yu, Silvia Buonamici, Charles Y Lin, Kristen L Karlin, Xiang H-F Zhang, Thomas F Westbrook

Faculty, Staff and Students Publications

Many oncogenic insults deregulate RNA splicing, often leading to hypersensitivity of tumors to spliceosome-targeted therapies (STTs). However, the mechanisms by which STTs selectively kill cancers remain largely unknown. Herein, we discover that mis-spliced RNA itself is a molecular trigger for tumor killing through viral mimicry. In MYC-driven triple-negative breast cancer, STTs cause widespread cytoplasmic accumulation of mis-spliced mRNAs, many of which form double-stranded structures. Double-stranded RNA (dsRNA)-binding proteins recognize these endogenous dsRNAs, triggering antiviral signaling and extrinsic apoptosis. In immune-competent models of breast cancer, STTs cause tumor cell-intrinsic antiviral signaling, downstream adaptive immune signaling, and tumor cell death. Furthermore, RNA …

Knowledge Network Embedding Of Transcriptomic Data From Spaceflown Mice Uncovers Signs And Symptoms Associated With Terrestrial Diseases, Amber M. Paul, Charlotte A. Nelson, Ana Uriarte Acuna, Ryan T. Scott, Atul J. Butte, Egle Cekanaviciute, Sergio E. Baranzini

Publications

There has long been an interest in understanding how the hazards from spaceflight may trigger or exacerbate human diseases. With the goal of advancing our knowledge on physiological changes during space travel, NASA GeneLab provides an open-source repository of multi-omics data from real and simulated spaceflight studies. Alone, this data enables identification of biological changes during spaceflight, but cannot infer how that may impact an astronaut at the phenotypic level. To bridge this gap, Scalable Precision Medicine Oriented Knowledge Engine (SPOKE), a heterogeneous knowledge graph connecting biological and clinical data from over 30 databases, was used in combination with GeneLab …

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 …

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 …

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 …

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.

Determining The Utility Of Hl7® Fast Healthcare Interoperability Resources (Fhir®) Standards In Supporting Ehr And Edc-Agnostic Esource Implementations For Clinical Research, Maryam Garza

Dissertations and Theses (Open Access)

Advances in efficiency while maintaining or improving quality are immediately needed in clinical research, specifically for multicenter clinical studies. Though recent evidence points toward electronic health record (EHR) to electronic data capture (EDC) system (EHR to EDC) data collection as a viable contribution, there are many unanswered process and outcome-level questions regarding quality, site burden, and cost within the context of multicenter clinical trials. Direct extraction and use of EHR data in multicenter clinical studies is a long-term and multifaceted endeavor that includes design, development, implementation and evaluation of methods and tools for semi-automating tasks in the research data collection …

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, …

Improvement Of Cryo-Em Maps By Density Modification, Thomas C Terwilliger, Steven J Ludtke, Randy J Read, Paul D Adams, Pavel V Afonine

Faculty, Staff and Students Publications

A density-modification procedure for improving maps from single-particle electron cryogenic microscopy (cryo-EM) is presented. The theoretical basis of the method is identical to that of maximum-likelihood density modification, previously used to improve maps from macromolecular X-ray crystallography. Key differences from applications in crystallography are that the errors in Fourier coefficients are largely in the phases in crystallography but in both phases and amplitudes in cryo-EM, and that half-maps with independent errors are available in cryo-EM. These differences lead to a distinct approach for combination of information from starting maps with information obtained in the density-modification process. The density-modification procedure was …

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 …

Critical Micrornas And Regulatory Motifs In Cleft Palate Identified By A Conserved Mirna-Tf-Gene Network Approach In Humans And Mice, Aimin Li, Peilin Jia, Saurav Mallik, Rong Fei, Hiroki Yoshioka, Akiko Suzuki, Junichi Iwata, Zhongming Zhao

Faculty, Staff and Student Publications

Cleft palate (CP) is the second most common congenital birth defect. The etiology of CP is complicated, with involvement of various genetic and environmental factors. To investigate the gene regulatory mechanisms, we designed a powerful regulatory analytical approach to identify the conserved regulatory networks in humans and mice, from which we identified critical microRNAs (miRNAs), target genes and regulatory motifs (miRNA-TF-gene) related to CP. Using our manually curated genes and miRNAs with evidence in CP in humans and mice, we constructed miRNA and transcription factor (TF) co-regulation networks for both humans and mice. A consensus regulatory loop (miR17/miR20a-FOXE1-PDGFRA) and eight …

Covid-19 Testnorm: A Tool To Normalize Covid-19 Testing Names To Loinc Codes, Xiao Dong, Jianfu Li, Ekin Soysal, Jiang Bian, Scott L Duvall, Elizabeth Hanchrow, Hongfang Liu, Kristine E Lynch, Michael Matheny, Karthik Natarajan, Lucila Ohno-Machado, Serguei Pakhomov, Ruth Madeleine Reeves, Amy M Sitapati, Swapna Abhyankar, Theresa Cullen, Jami Deckard, Xiaoqian Jiang, Robert Murphy, Hua Xu

Faculty, Staff and Student Publications

Large observational data networks that leverage routine clinical practice data in electronic health records (EHRs) are critical resources for research on coronavirus disease 2019 (COVID-19). Data normalization is a key challenge for the secondary use of EHRs for COVID-19 research across institutions. In this study, we addressed the challenge of automating the normalization of COVID-19 diagnostic tests, which are critical data elements, but for which controlled terminology terms were published after clinical implementation. We developed a simple but effective rule-based tool called COVID-19 TestNorm to automatically normalize local COVID-19 testing names to standard LOINC (Logical Observation Identifiers Names and Codes) …

Rna-Gps Predicts High-Resolution Rna Subcellular Localization And Highlights The Role Of Splicing, Kevin E Wu, Kevin R Parker, Furqan M Fazal, Howard Y Chang, James Zou

Faculty, Staff and Students Publications

Subcellular localization is essential to RNA biogenesis, processing, and function across the gene expression life cycle. However, the specific nucleotide sequence motifs that direct RNA localization are incompletely understood. Fortunately, new sequencing technologies have provided transcriptome-wide atlases of RNA localization, creating an opportunity to leverage computational modeling. Here we present RNA-GPS, a new machine learning model that uses nucleotide-level features to predict RNA localization across eight different subcellular locations-the first to provide such a wide range of predictions. RNA-GPS's design enables high-throughput sequence ablation and feature importance analyses to probe the sequence motifs that drive localization prediction. We find localization …

Proteolysis-Targeting Chimera (Protac) For Targeted Protein Degradation And Cancer Therapy, Xin Li, Yongcheng Song

Faculty, Staff and Students Publications

Proteolysis-targeting chimera (PROTAC) has been developed to be a useful technology for targeted protein degradation. A bifunctional PROTAC molecule consists of a ligand (mostly small-molecule inhibitor) of the protein of interest (POI) and a covalently linked ligand of an E3 ubiquitin ligase (E3). Upon binding to the POI, the PROTAC can recruit E3 for POI ubiquitination, which is subjected to proteasome-mediated degradation. PROTAC complements nucleic acid-based gene knockdown/out technologies for targeted protein reduction and could mimic pharmacological protein inhibition. To date, PROTACs targeting ~ 50 proteins, many of which are clinically validated drug targets, have been successfully developed with several …

Tortuosity-Powered Microfluidic Device For Assessment Of Thrombosis And Antithrombotic Therapy In Whole Blood, David J Luna, Navaneeth K R Pandian, Tanmay Mathur, Justin Bui, Pranav Gadangi, Vadim V Kostousov, Shiu-Ki Rocky Hui, Jun Teruya, Abhishek Jain

Faculty, Staff and Students Publications

Accurate assessment of blood thrombosis and antithrombotic therapy is essential for the management of patients in a variety of clinical conditions, including surgery and on extracorporeal life support. However, current monitoring devices do not measure the effects of hemodynamic forces that contribute significantly to coagulation, platelet function and fibrin formation. This limits the extent to which current assays can predict clotting status in patients. Here, we demonstrate that a biomimetic microfluidic device consisting stenosed and tortuous arteriolar vessels would analyze blood clotting under flow, while requiring a small blood volume. When the device is connected to an inline pressure sensor …