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Articles 1 - 21 of 21
Full-Text Articles in Entire DC Network
Genetic Contributors Of Incident Stroke In 10,700 African Americans With Hypertension: A Meta-Analysis From The Genetics Of Hypertension Associated Treatments And Reasons For Geographic And Racial Differences In Stroke Studies, Nicole D. Armstrong, Vinodh Srinivasasainagendra, Amit Patki, Rikki M. Tanner, Bertha A. Hidalgo, Hemant K. Tiwari, Nita A. Limdi, Ethan M. Lange, Leslie A. Lange, Donna K. Arnett, Marguerite R. Irvin
Genetic Contributors Of Incident Stroke In 10,700 African Americans With Hypertension: A Meta-Analysis From The Genetics Of Hypertension Associated Treatments And Reasons For Geographic And Racial Differences In Stroke Studies, Nicole D. Armstrong, Vinodh Srinivasasainagendra, Amit Patki, Rikki M. Tanner, Bertha A. Hidalgo, Hemant K. Tiwari, Nita A. Limdi, Ethan M. Lange, Leslie A. Lange, Donna K. Arnett, Marguerite R. Irvin
Epidemiology and Environmental Health Faculty Publications
Background: African Americans (AAs) suffer a higher stroke burden due to hypertension. Identifying genetic contributors to stroke among AAs with hypertension is critical to understanding the genetic basis of the disease, as well as detecting at-risk individuals.
Methods: In a population comprising over 10,700 AAs treated for hypertension from the Genetics of Hypertension Associated Treatments (GenHAT) and Reasons for Geographic and Racial Differences in Stroke (REGARDS) studies, we performed an inverse variance-weighted meta-analysis of incident stroke. Additionally, we tested the predictive accuracy of a polygenic risk score (PRS) derived from a European ancestral population in both GenHAT and REGARDS AAs …
Characterizing Long Covid: Deep Phenotype Of A Complex Condition, Rachel R. Deer, Madeline A. Rock, Nicole Vasilevsky, Leigh Carmody, Halie Rando, Alfred J. Anzalone, Marc D. Basson, Tellen D. Bennett, Timothy Bergquist, Eilis A. Boudreau, Carolyn T. Bramante, James Brian Byrd, Tiffany J. Callahan, Lauren E. Chan, Haitao Chu, Christopher G. Chute, Ben D. Coleman, Hannah E. Davis, Joel Gagnier, Casey S. Greene, Ramakanth Kavuluru
Characterizing Long Covid: Deep Phenotype Of A Complex Condition, Rachel R. Deer, Madeline A. Rock, Nicole Vasilevsky, Leigh Carmody, Halie Rando, Alfred J. Anzalone, Marc D. Basson, Tellen D. Bennett, Timothy Bergquist, Eilis A. Boudreau, Carolyn T. Bramante, James Brian Byrd, Tiffany J. Callahan, Lauren E. Chan, Haitao Chu, Christopher G. Chute, Ben D. Coleman, Hannah E. Davis, Joel Gagnier, Casey S. Greene, Ramakanth Kavuluru
Institute for Biomedical Informatics Faculty Publications
BACKGROUND: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or "long COVID"), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies.
METHODS: The Human Phenotype Ontology …
Untargeted Lipidomics Of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes In Cancer Vs. Non-Cancer Tissue, Joshua M. Mitchell, Robert M. Flight, Hunter N. B. Moseley
Untargeted Lipidomics Of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes In Cancer Vs. Non-Cancer Tissue, Joshua M. Mitchell, Robert M. Flight, Hunter N. B. Moseley
Molecular and Cellular Biochemistry Faculty Publications
Lung cancer remains the leading cause of cancer death worldwide and non-small cell lung carcinoma (NSCLC) represents 85% of newly diagnosed lung cancers. In this study, we utilized our untargeted assignment tool Small Molecule Isotope Resolved Formula Enumerator (SMIRFE) and ultra-high-resolution Fourier transform mass spectrometry to examine lipid profile differences between paired cancerous and non-cancerous lung tissue samples from 86 patients with suspected stage I or IIA primary NSCLC. Correlation and co-occurrence analysis revealed significant lipid profile differences between cancer and non-cancer samples. Further analysis of machine-learned lipid categories for the differentially abundant molecular formulas identified a high abundance sterol, …
Real-World Evaluation Of Universal Germline Screening For Cancer Treatment-Relevant Pharmacogenes, Megan L. Hutchcraft, Nan Lin, Shulin Zhang, Catherine Sears, Kyle Zacholski, Elizabeth A. Belcher, Eric B. Durbin, John L. Villano, Michael J. Cavnar, Susanne M. Arnold, Frederick R. Ueland, Jill M. Kolesar
Real-World Evaluation Of Universal Germline Screening For Cancer Treatment-Relevant Pharmacogenes, Megan L. Hutchcraft, Nan Lin, Shulin Zhang, Catherine Sears, Kyle Zacholski, Elizabeth A. Belcher, Eric B. Durbin, John L. Villano, Michael J. Cavnar, Susanne M. Arnold, Frederick R. Ueland, Jill M. Kolesar
Pathology and Laboratory Medicine Faculty Publications
The purpose of this study was to determine the frequency of clinically actionable treatment-relevant germline pharmacogenomic variants in patients with cancer and assess the real-world clinical utility of universal screening using whole-exome sequencing in this population. Cancer patients underwent research-grade germline whole-exome sequencing as a component of sequencing for somatic variants. Analysis in a clinical bioinformatics pipeline identified clinically actionable pharmacogenomic variants. Clinical Pharmacogenetics Implementation Consortium guidelines defined clinical actionability. We assessed clinical utility by reviewing electronic health records to determine the frequency of patients receiving pharmacogenomically actionable anti-cancer agents and associated outcomes. This observational study evaluated 291 patients with …
Random Forest-Integrated Analysis In Ad And Late Brain Transcriptome-Wide Data To Identify Disease-Specific Gene Expression, Xinxing Wu, Chong Peng, Peter T. Nelson, Qiang Cheng
Random Forest-Integrated Analysis In Ad And Late Brain Transcriptome-Wide Data To Identify Disease-Specific Gene Expression, Xinxing Wu, Chong Peng, Peter T. Nelson, Qiang Cheng
Sanders-Brown Center on Aging Faculty Publications
Alzheimer's disease (AD) is a complex neurodegenerative disorder that affects thinking, memory, and behavior. Limbic-predominant age-related TDP-43 encephalopathy (LATE) is a recently identified common neurodegenerative disease that mimics the clinical symptoms of AD. The development of drugs to prevent or treat these neurodegenerative diseases has been slow, partly because the genes associated with these diseases are incompletely understood. A notable hindrance from data analysis perspective is that, usually, the clinical samples for patients and controls are highly imbalanced, thus rendering it challenging to apply most existing machine learning algorithms to directly analyze such datasets. Meeting this data analysis challenge is …
Bone Quality And Fractures In Women With Osteoporosis Treated With Bisphosphonates For 1 To 14 Years, Hartmut H. Malluche, Jin Chen, Florence Lima, Lucas J. Liu, Marie-Claude Monier-Faugere, David A. Pienkowski
Bone Quality And Fractures In Women With Osteoporosis Treated With Bisphosphonates For 1 To 14 Years, Hartmut H. Malluche, Jin Chen, Florence Lima, Lucas J. Liu, Marie-Claude Monier-Faugere, David A. Pienkowski
Internal Medicine Faculty Publications
Oral bisphosphonates are the primary medication for osteoporosis, but concerns exist regarding potential bone-quality changes or low-energy fractures. This cross-sectional study used artificial intelligence methods to analyze relationships among bisphosphonate treatment duration, a wide variety of bone-quality parameters, and low-energy fractures. Fourier transform infrared spectroscopy and histomorphometry quantified bone-quality parameters in 67 osteoporotic women treated with oral bisphosphonates for 1 to 14 years. Artificial intelligence methods established two models relating bisphosphonate treatment duration to bone-quality changes and to low-energy clinical fractures. The model relating bisphosphonate treatment duration to bone quality demonstrated optimal performance when treatment durations of 1 to 8 …
Human Apobec3 Variations And Viral Infection, Shiva Sadeghpour, Saeideh Khodaee, Mostafa Rahnama, Hamzeh Rahimi, Diako Ebrahimi
Human Apobec3 Variations And Viral Infection, Shiva Sadeghpour, Saeideh Khodaee, Mostafa Rahnama, Hamzeh Rahimi, Diako Ebrahimi
Plant Pathology Faculty Publications
Human APOBEC3 (apolipoprotein B mRNA-editing catalytic polypeptide-like 3) enzymes are capable of inhibiting a wide range of endogenous and exogenous viruses using deaminase and deaminase-independent mechanisms. These enzymes are essential components of our innate immune system, as evidenced by (a) their strong positive selection and expansion in primates, (b) the evolution of viral counter-defense mechanisms, such as proteasomal degradation mediated by HIV Vif, and (c) hypermutation and inactivation of a large number of integrated HIV-1 proviruses. Numerous APOBEC3 single nucleotide polymorphisms, haplotypes, and splice variants have been identified in humans. Several of these variants have been reported to be associated …
Hierarchical Harmonization Of Atom-Resolved Metabolic Reactions Across Metabolic Databases, Huan Jin, Hunter N. B. Moseley
Hierarchical Harmonization Of Atom-Resolved Metabolic Reactions Across Metabolic Databases, Huan Jin, Hunter N. B. Moseley
Molecular and Cellular Biochemistry Faculty Publications
Metabolic models have been proven to be useful tools in system biology and have been successfully applied to various research fields in a wide range of organisms. A relatively complete metabolic network is a prerequisite for deriving reliable metabolic models. The first step in constructing metabolic network is to harmonize compounds and reactions across different metabolic databases. However, effectively integrating data from various sources still remains a big challenge. Incomplete and inconsistent atomistic details in compound representations across databases is a very important limiting factor. Here, we optimized a subgraph isomorphism detection algorithm to validate generic compound pairs. Moreover, we …
Analysis Of High-Risk Pedigrees Identifies 12 Candidate Variants For Alzheimer's Disease, Craig C. Teerlink, Justin B. Miller, Elizabeth L. Vance, Lyndsay A. Staley, Jeffrey Stevens, Justina P. Tavana, Matthew E. Cloward, Madeline L. Page, Louisa Dayton, Alzheimer's Disease Genetics Consortium, Lisa A. Cannon-Albright, John S. K. Kauwe
Analysis Of High-Risk Pedigrees Identifies 12 Candidate Variants For Alzheimer's Disease, Craig C. Teerlink, Justin B. Miller, Elizabeth L. Vance, Lyndsay A. Staley, Jeffrey Stevens, Justina P. Tavana, Matthew E. Cloward, Madeline L. Page, Louisa Dayton, Alzheimer's Disease Genetics Consortium, Lisa A. Cannon-Albright, John S. K. Kauwe
Institute for Biomedical Informatics Faculty Publications
INTRODUCTION: Analysis of sequence data in high-risk pedigrees is a powerful approach to detect rare predisposition variants.
METHODS: Rare, shared candidate predisposition variants were identified from exome sequencing 19 Alzheimer's disease (AD)-affected cousin pairs selected from high-risk pedigrees. Variants were further prioritized by risk association in various external datasets. Candidate variants emerging from these analyses were tested for co-segregation to additional affected relatives of the original sequenced pedigree members.
RESULTS: AD-affected high-risk cousin pairs contained 564 shared rare variants. Eleven variants spanning 10 genes were prioritized in external datasets: rs201665195 (ABCA7), and rs28933981 (TTR) were previously …
Keap1 Is Required For Artesunate Anticancer Activity In Non-Small-Cell Lung Cancer, Kristen S. Hill, Anthony Mcdowell Jr., J. Robert Mccorkle, Erin Schuler, Sally R. Ellingson, Rina Plattner, Jill M. Kolesar
Keap1 Is Required For Artesunate Anticancer Activity In Non-Small-Cell Lung Cancer, Kristen S. Hill, Anthony Mcdowell Jr., J. Robert Mccorkle, Erin Schuler, Sally R. Ellingson, Rina Plattner, Jill M. Kolesar
Pathology and Laboratory Medicine Faculty Publications
Artesunate is the most common treatment for malaria throughout the world. Artesunate has anticancer activity likely through the induction of reactive oxygen species, the same mechanism of action utilized in Plasmodium falciparum infections. Components of the kelch-like ECH-associated protein 1 (KEAP1)/nuclear factor erythroid 2-related factor 2 (NRF2) pathway, which regulates cellular response to oxidative stress, are mutated in approximately 30% of non-small-cell lung cancers (NSCLC); therefore, we tested the hypothesis that KEAP1 is required for artesunate sensitivity in NSCLC. Dose response assays identified A549 cells, which have a G333C-inactivating mutation in KEAP1, as resistant to artesunate, with an IC50 of …
Toward The Discovery Of Biological Functions Associated With The Mechanosensor Mtl1p Of Saccharomyces Cerevisiae Via Integrative Multi-Omics Analysis, Nelson Martínez-Matías, Nataliya Chorna, Sahily González-Crespo, Lilliam Villanueva, Ingrid Montes-Rodríguez, Loyda M. Melendez-Aponte, Abiel Roche-Lima, Kelvin Carrasquillo-Carrión, Ednalise Santiago-Cartagena, Brian C. Rymond, Mohan Babu, Igor Stagljar, José R. Rodríguez-Medina
Toward The Discovery Of Biological Functions Associated With The Mechanosensor Mtl1p Of Saccharomyces Cerevisiae Via Integrative Multi-Omics Analysis, Nelson Martínez-Matías, Nataliya Chorna, Sahily González-Crespo, Lilliam Villanueva, Ingrid Montes-Rodríguez, Loyda M. Melendez-Aponte, Abiel Roche-Lima, Kelvin Carrasquillo-Carrión, Ednalise Santiago-Cartagena, Brian C. Rymond, Mohan Babu, Igor Stagljar, José R. Rodríguez-Medina
Biology Faculty Publications
Functional analysis of the Mtl1 protein in Saccharomyces cerevisiae has revealed that this transmembrane sensor endows yeast cells with resistance to oxidative stress through a signaling mechanism called the cell wall integrity pathway (CWI). We observed upregulation of multiple heat shock proteins (HSPs), proteins associated with the formation of stress granules, and the phosphatase subunit of trehalose 6-phosphate synthase which suggests that mtl1Δ strains undergo intrinsic activation of a non-lethal heat stress response. Furthermore, quantitative global proteomic analysis conducted on TMT-labeled proteins combined with metabolome analysis revealed that mtl1Δ strains exhibit decreased levels of metabolites of carboxylic acid metabolism, decreased …
The Mwtab Python Library For Restful Access And Enhanced Quality Control, Deposition, And Curation Of The Metabolomics Workbench Data Repository, Christian D. Powell, Hunter N. B. Moseley
The Mwtab Python Library For Restful Access And Enhanced Quality Control, Deposition, And Curation Of The Metabolomics Workbench Data Repository, Christian D. Powell, Hunter N. B. Moseley
Markey Cancer Center Faculty Publications
The Metabolomics Workbench (MW) is a public scientific data repository consisting of experimental data and metadata from metabolomics studies collected with mass spectroscopy (MS) and nuclear magnetic resonance (NMR) analyses. MW has been constantly evolving; updating its ‘mwTab’ text file format, adding a JavaScript Object Notation (JSON) file format, implementing a REpresentational State Transfer (REST) interface, and nearly quadrupling the number of datasets hosted on the repository within the last three years. In order to keep up with the quickly evolving state of the MW repository, the ‘mwtab’ Python library and package have been continuously updated to mirror the changes …
Deep Active Learning For Classifying Cancer Pathology Reports, Kevin De Angeli, Shang Gao, Mohammed Alawad, Hong‑Jun Yoon, Noah Schaeferkoetter, Xiao‑Cheng Wu, Eric B. Durbin, Jennifer Doherty, Antoinette Stroup, Linda Coyle, Lynne Penberthy, Georgia Tourassi
Deep Active Learning For Classifying Cancer Pathology Reports, Kevin De Angeli, Shang Gao, Mohammed Alawad, Hong‑Jun Yoon, Noah Schaeferkoetter, Xiao‑Cheng Wu, Eric B. Durbin, Jennifer Doherty, Antoinette Stroup, Linda Coyle, Lynne Penberthy, Georgia Tourassi
Kentucky Cancer Registry Faculty Publications
Background: Automated text classification has many important applications in the clinical setting; however, obtaining labelled data for training machine learning and deep learning models is often difficult and expensive. Active learning techniques may mitigate this challenge by reducing the amount of labelled data required to effectively train a model. In this study, we analyze the effectiveness of 11 active learning algorithms on classifying subsite and histology from cancer pathology reports using a Convolutional Neural Network as the text classification model.
Results: We compare the performance of each active learning strategy using two differently sized datasets and two different classification tasks. …
Real World Clinicopathologic Observations Of Patients With Metastatic Solid Tumors Receiving Immune Checkpoint Inhibitor Therapy: Analysis From Kentucky Cancer Registry, Aasems Jacob, Jianrong Wu, Jill M. Kolesar, Eric B. Durbin, Aju Mathew, Susanne Arnold, Aman Chauhan
Real World Clinicopathologic Observations Of Patients With Metastatic Solid Tumors Receiving Immune Checkpoint Inhibitor Therapy: Analysis From Kentucky Cancer Registry, Aasems Jacob, Jianrong Wu, Jill M. Kolesar, Eric B. Durbin, Aju Mathew, Susanne Arnold, Aman Chauhan
Biostatistics Faculty Publications
The state of Kentucky has the highest cancer incidence and mortality in the United States. High‐risk populations such as this are often underrepresented in clinical trials. The study aims to do a comprehensive analysis of molecular landscape of metastatic cancers among these patients with detailed evaluation of factors affecting response and outcomes to immune checkpoint inhibitor (ICI) therapy. We performed a retrospective analysis of metastatic solid tumor patients who received ICI and underwent molecular profiling at our institution.
Sixty nine patients with metastatic solid tumors who received ICI were included in the study. Prevalence of smoking and secondhand tobacco exposure …
Machine Intelligence Identifies Soluble Tnfa As A Therapeutic Target For Spinal Cord Injury, J. R. Huie, A. R. Ferguson, N. Kyritsis, J. Z. Pan, K.-A. Irvine, J. L. Nielson, P. G. Schupp, M. C. Oldham, John C. Gensel, A. Lin, M. R. Segal, R. R. Ratan, J. C. Bresnahan, M. S. Beattie
Machine Intelligence Identifies Soluble Tnfa As A Therapeutic Target For Spinal Cord Injury, J. R. Huie, A. R. Ferguson, N. Kyritsis, J. Z. Pan, K.-A. Irvine, J. L. Nielson, P. G. Schupp, M. C. Oldham, John C. Gensel, A. Lin, M. R. Segal, R. R. Ratan, J. C. Bresnahan, M. S. Beattie
Spinal Cord and Brain Injury Research Center Faculty Publications
Traumatic spinal cord injury (SCI) produces a complex syndrome that is expressed across multiple endpoints ranging from molecular and cellular changes to functional behavioral deficits. Effective therapeutic strategies for CNS injury are therefore likely to manifest multi-factorial effects across a broad range of biological and functional outcome measures. Thus, multivariate analytic approaches are needed to capture the linkage between biological and neurobehavioral outcomes. Injury-induced neuroinflammation (NI) presents a particularly challenging therapeutic target, since NI is involved in both degeneration and repair. Here, we used big-data integration and large-scale analytics to examine a large dataset of preclinical efficacy tests combining five …
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. …
Development Of Tools For Atom-Level Interpretation Of Stable Isotope-Resolved Metabolomics Datasets, Huan Jin
Development Of Tools For Atom-Level Interpretation Of Stable Isotope-Resolved Metabolomics Datasets, Huan Jin
Theses and Dissertations--Toxicology and Cancer Biology
Metabolomics is the global study of small molecules in living systems under a given state, merging as a new ‘omics’ study in systems biology. It has shown great promise in elucidating biological mechanism in various areas. Many diseases, especially cancers, are closely linked to reprogrammed metabolism. As the end point of biological processes, metabolic profiles are more representative of the biological phenotype compared to genomic or proteomic profiles. Therefore, characterizing metabolic phenotype of various diseases will help clarify the metabolic mechanisms and promote the development of novel and effective treatment strategies.
Advances in analytical technologies such as nuclear magnetic resonance …
Machine Learning And Bioinformatic Insights Into Key Enzymes For A Bio-Based Circular Economy, Japheth E. Gado
Machine Learning And Bioinformatic Insights Into Key Enzymes For A Bio-Based Circular Economy, Japheth E. Gado
Theses and Dissertations--Chemical and Materials Engineering
The world is presently faced with a sustainability crisis; it is becoming increasingly difficult to meet the energy and material needs of a growing global population without depleting and polluting our planet. Greenhouse gases released from the continuous combustion of fossil fuels engender accelerated climate change, and plastic waste accumulates in the environment. There is need for a circular economy, where energy and materials are renewably derived from waste items, rather than by consuming limited resources. Deconstruction of the recalcitrant linkages in natural and synthetic polymers is crucial for a circular economy, as deconstructed monomers can be used to manufacture …
Leveraging Transcriptomic Approaches To Identify Differences In Genetic Programming Driving Two Distinct Wound Healing Mechanisms, Regeneration And Fibrosis, In Acomys And Mus, Shishir K. Biswas
Theses and Dissertations--Biology
Why can some animals and others cannot? This fundamental question has fueled scientists studying regeneration for hundreds of years since early observations in crayfish, salamanders and many other organisms. While most contemporary work in regeneration is done in a handful of species including salamanders, zebrafish and flatforms, these organisms lack a closely-related, non-regenerating sister species from which unique genetic differences can be identified. Additionally, while much has been learned from these organisms, they do not share fundamental biological traits with mammals (endothermy, metabolism and immune system) which limits the ability to translate this research for clinical medicine. To this end, …
Novel Computational Methods For Cancer Genomics Data Analysis, Jinpeng Liu
Novel Computational Methods For Cancer Genomics Data Analysis, Jinpeng Liu
Theses and Dissertations--Computer Science
Cancer is a genetic disease responsible for one in eight deaths worldwide. The advancement of next-generation sequencing (NGS) technology has revolutionized the cancer research, allowing comprehensively profiling the cancer genome at great resolution. Large-scale cancer genomics research has sparked the needs for efficient and accurate Bioinformatics methods to analyze the data. The research presented in this dissertation focuses on three areas in cancer genomics: cancer somatic mutation detection; cancer driver genes identification and transcriptome profiling on single-cell level.
NGS data analysis involves a series of complicated data transformation that convert raw sequencing data to the information that is interpretable by …
Distribution And Diversity Of Heliothine And Other Lepidopteran Nudiviruses, Emrah Ozel
Distribution And Diversity Of Heliothine And Other Lepidopteran Nudiviruses, Emrah Ozel
Theses and Dissertations--Entomology
Helicoverpa zea nudivirus 2 (HzNV-2) is the only known sterilizing and sexually-transmitted insect virus and causes pathological symptoms in H. zea reproductive tissues. HzNV-2 has features that make it a candidate as a H. zea (corn earworm) control agent, such as the ability to cause asymptomatic (latent) and symptomatic (lytic) infections and the ability to influence mating behavior of its host to favor virus spread. HzNV pathology has been studied and its genome sequenced, however, its prevalence in natural populations is largely unknown. In this study, we developed and used a low-cost PCR-based molecular survey to investigate HzNV-2 prevalence and …