Biomedical Informatics Commons^™

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

Deep Learning In Clinical Natural Language Processing: A Methodical Review, Stephen Wu, Kirk Roberts, Surabhi Datta, Jingcheng Du, Zongcheng Ji, Yuqi Si, Sarvesh Soni, Qiong Wang, Qiang Wei, Yang Xiang, Bo Zhao, Hua Xu

Faculty, Staff and Student Publications

OBJECTIVE: This article methodically reviews the literature on deep learning (DL) for natural language processing (NLP) in the clinical domain, providing quantitative analysis to answer 3 research questions concerning methods, scope, and context of current research.

MATERIALS AND METHODS: We searched MEDLINE, EMBASE, Scopus, the Association for Computing Machinery Digital Library, and the Association for Computational Linguistics Anthology for articles using DL-based approaches to NLP problems in electronic health records. After screening 1,737 articles, we collected data on 25 variables across 212 papers.

RESULTS: DL in clinical NLP publications more than doubled each year, through 2018. Recurrent neural networks (60.8%) …

A Broad-Spectrum Antiviral Molecule, Ql47, Selectively Inhibits Eukaryotic Translation, Mélissanne De Wispelaere, Margot Carocci, Dominique J Burri, William J Neidermyer, Calla M Olson, Imme Roggenbach, Yanke Liang, Jinhua Wang, Sean P J Whelan, Nathanael S Gray, Priscilla L Yang

Faculty, Staff and Students Publications

Small-molecule inhibitors of translation are critical tools to study the molecular mechanisms of protein synthesis. In this study, we sought to characterize how QL47, a host-targeted, small-molecule antiviral agent, inhibits steady-state viral protein expression. We demonstrate that this small molecule broadly inhibits both viral and host protein synthesis and targets a translation step specific to eukaryotic cells. We show that QL47 inhibits protein neosynthesis initiated by both canonical cap-driven and noncanonical initiation strategies, most likely by targeting an early step in translation elongation. Our findings thus establish QL47 as a new small-molecule inhibitor that can be utilized to probe the …

Digilego For Peripartum Depression: A Novel Patient-Facing Digital Health Instantiation, J Rodin, C Timko, S Harris

Faculty, Staff and Student Publications

Digital health technologies offer unique opportunities to improve health outcomes for mental health conditions such as peripartum depression (PPD), a disorder that affects approximately 10-15% of women in the U.S. every year. In this paper, we present the adaption of a digital technology development framework, Digilego, in the context of PPD. Methods include mapping of the Behavior Intervention Technology (BIT) model and the Patient Engagement Framework (PEF) to translate patient needs captured through focus groups. This informs formative development and implementation of digital health features for optimal patient engagement in PPD screening and management. Results show an array ofPPD-specific Digilego …

Causal Discovery In Radiographic Markers Of Knee Osteoarthritis And Prediction For Knee Osteoarthritis Severity With Attention-Long Short-Term Memory, Yanfei Wang, Lei You, Jacqueline Chyr, Lan Lan, Weiling Zhao, Yujia Zhou, Hua Xu, Philip Noble, Xiaobo Zhou

Faculty, Staff and Student Publications

The goal of this study is to build a prognostic model to predict the severity of radiographic knee osteoarthritis (KOA) and to identify long-term disease progression risk factors for early intervention and treatment. We designed a long short-term memory (LSTM) model with an attention mechanism to predict Kellgren/Lawrence (KL) grade for knee osteoarthritis patients. The attention scores reveal a time-associated impact of different variables on KL grades. We also employed a fast causal inference (FCI) algorithm to estimate the causal relation of key variables, which will aid in clinical interpretability. Based on the clinical information of current visits, we accurately …

Non-Uniformity Of Projection Distributions Attenuates Resolution In Cryo-Em, Philip R Baldwin, Dmitry Lyumkis

Faculty, Staff and Students Publications

Virtually all single-particle cryo-EM experiments currently suffer from specimen adherence to the air-water interface, leading to a non-uniform distribution in the set of projection views. Whereas it is well accepted that uniform projection distributions can lead to high-resolution reconstructions, non-uniform (anisotropic) distributions can negatively affect map quality, elongate structural features, and in some cases, prohibit interpretation altogether. Although some consequences of non-uniform sampling have been described qualitatively, we know little about how sampling quantitatively affects resolution in cryo-EM. Here, we show how inhomogeneity in any projection distribution scheme attenuates the global Fourier Shell Correlation (FSC) in relation to the number …

Metaproteomic Analysis Of Human Gut Microbiome In Digestive And Metabolic Diseases, Sheng Pan, Ru Chen

Faculty, Staff and Students Publications

Metaproteomics, as a subfield of proteomics, has quickly emerged as a pivotal tool for global characterization of a microbiome system at a functional level. It has been increasingly applied in studying human digestive and metabolic diseases, and provides information-rich data to identify the dysbiosis of human gut microbiome related to healthy or disease states to elucidate the molecular events underlying host-microbiota interplays. While significant technical challenges still exist, this emerging technology has been demonstrated to provide essential information in interrogating functional changes in the human gut microbiome, complementary to metagenomics and metatranscriptomics. This chapter overviews the overall metaproteomic work flow …