Literature-Based Discovery to Elucidate the Biological Links between Resistant Hypertension and COVID-19.

Multiple studies have reported new or exacerbated persistent or resistant hypertension in patients previously infected with COVID-19. We used literature-based discovery to identify and prioritize multi-scalar explanatory biology that relates resistant hypertension to COVID-19. Cross-domain text mining of 33+ million PubMed articles within a comprehensive knowledge graph was performed using SemNet 2.0. Unsupervised rank aggregation determined which concepts were most relevant utilizing the normalized HeteSim score. A series of simulations identified concepts directly related to COVID-19 and resistant hypertension or connected via one of three renin-angiotensin-aldosterone system hub nodes (mineralocorticoid receptor, epithelial sodium channel, angiotensin I receptor). The top-ranking concepts relating COVID-19 to resistant hypertension included: cGMP-dependent protein kinase II, MAP3K1, haspin, ral guanine nucleotide exchange factor, N-(3-Oxododecanoyl)-L-homoserine lactone, aspartic endopeptidases, metabotropic glutamate receptors, choline-phosphate cytidylyltransferase, protein tyrosine phosphatase, tat genes, MAP3K10, uridine kinase, dicer enzyme, CMD1B, USP17L2, FLNA, exportin 5, somatotropin releasing hormone, beta-melanocyte stimulating hormone, pegylated leptin, beta-lipoprotein, corticotropin, growth hormone-releasing peptide 2, pro-opiomelanocortin, alpha-melanocyte stimulating hormone, prolactin, thyroid hormone, poly-beta-hydroxybutyrate depolymerase, CR 1392, BCR-ABL fusion gene, high density lipoprotein sphingomyelin, pregnancy-associated murine protein 1, recQ4 helicase, immunoglobulin heavy chain variable domain, aglycotransferrin, host cell factor C1, ATP6V0D1, imipramine demethylase, TRIM40, H3C2 gene, COL1A1+COL1A2 gene, QARS gene, VPS54, TPM2, MPST, EXOSC2, ribosomal protein S10, TAP-144, gonadotropins, human gonadotropin releasing hormone 1, beta-lipotropin, octreotide, salmon calcitonin, des-n-octanoyl ghrelin, liraglutide, gastrins. Concepts were mapped to six physiological themes: altered endocrine function, 23.1%; inflammation or cytokine storm, 21.3%; lipid metabolism and atherosclerosis, 17.6%; sympathetic input to blood pressure regulation, 16.7%; altered entry of COVID-19 virus, 14.8%; and unknown, 6.5%.

Optimizations for Computing Relatedness in Biomedical Heterogeneous Information Networks: SemNet 2.0.

Literature-based discovery (LBD) summarizes information and generates insight from large text corpuses. The SemNet framework utilizes a large heterogeneous information network or "knowledge graph" of nodes and edges to compute relatedness and rank concepts pertinent to a user-specified target. SemNet provides a way to perform multi-factorial and multi-scalar analysis of complex disease etiology and therapeutic identification using the 33+ million articles in PubMed. The present work improves the efficacy and efficiency of LBD for end users by augmenting SemNet to create SemNet 2.0. A custom Python data structure replaced reliance on Neo4j to improve knowledge graph query times by several orders of magnitude. Additionally, two randomized algorithms were built to optimize the HeteSim metric calculation for computing metapath similarity. The unsupervised learning algorithm for rank aggregation (ULARA), which ranks concepts with respect to the user-specified target, was reconstructed using derived mathematical proofs of correctness and probabilistic performance guarantees for optimization. The upgraded ULARA is generalizable to other rank aggregation problems outside of SemNet. In summary, SemNet 2.0 is a comprehensive open-source software for significantly faster, more effective, and user-friendly means of automated biomedical LBD. An example case is performed to rank relationships between Alzheimer's disease and metabolic co-morbidities.

CompositeView: A Network-Based Visualization Tool.

Large networks are quintessential to bioinformatics, knowledge graphs, social network analysis, and graph-based learning. CompositeView is a Python-based open-source application that improves interactive complex network visualization and extraction of actionable insight. CompositeView utilizes specifically formatted input data to calculate composite scores and display them using the Cytoscape component of Dash. Composite scores are defined representations of smaller sets of conceptually similar data that, when combined, generate a single score to reduce information overload. Visualized interactive results are user-refined via filtering elements such as node value and edge weight sliders and graph manipulation options (e.g., node color and layout spread). The primary difference between CompositeView and other network visualization tools is its ability to auto-calculate and auto-update composite scores as the user interactively filters or aggregates data. CompositeView was developed to visualize network relevance rankings, but it performs well with non-network data. Three disparate CompositeView use cases are shown: relevance rankings from SemNet 2.0, an open-source knowledge graph relationship ranking software for biomedical literature-based discovery; Human Development Index (HDI) data; and the Framingham cardiovascular study. CompositeView was stress tested to construct reference benchmarks that define breadth and size of data effectively visualized. Finally, CompositeView is compared to Excel, Tableau, Cytoscape, neo4j, NodeXL, and Gephi.

A 3D Bioprinted In Vitro Model of Pulmonary Artery Atresia to Evaluate Endothelial Cell Response to Microenvironment.

Vascular atresia are often treated via transcatheter recanalization or surgical vascular anastomosis due to congenital malformations or coronary occlusions. The cellular response to vascular anastomosis or recanalization is, however, largely unknown and current techniques rely on restoration rather than optimization of flow into the atretic arteries. An improved understanding of cellular response post anastomosis may result in reduced restenosis. Here, an in vitro platform is used to model anastomosis in pulmonary arteries (PAs) and for procedural planning to reduce vascular restenosis. Bifurcated PAs are bioprinted within 3D hydrogel constructs to simulate a reestablished intervascular connection. The PA models are seeded with human endothelial cells and perfused at physiological flow rate to form endothelium. Particle image velocimetry and computational fluid dynamics modeling show close agreement in quantifying flow velocity and wall shear stress within the bioprinted arteries. These data are used to identify regions with greatest levels of shear stress alterations, prone to stenosis. Vascular geometry and flow hemodynamics significantly affect endothelial cell viability, proliferation, alignment, microcapillary formation, and metabolic bioprofiles. These integrated in vitro-in silico methods establish a unique platform to study complex cardiovascular diseases and can lead to direct clinical improvements in surgical planning for diseases of disturbed flow.

Biomedical Text Link Prediction for Drug Discovery: A Case Study with COVID-19.

Link prediction in artificial intelligence is used to identify missing links or derive future relationships that can occur in complex networks. A link prediction model was developed using the complex heterogeneous biomedical knowledge graph, SemNet, to predict missing links in biomedical literature for drug discovery. A web application visualized knowledge graph embeddings and link prediction results using TransE, CompleX, and RotatE based methods. The link prediction model achieved up to 0.44 hits@10 on the entity prediction tasks. The recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as COVID-19, served as a case study to demonstrate the efficacy of link prediction modeling for drug discovery. The link prediction algorithm guided identification and ranking of repurposed drug candidates for SARS-CoV-2 primarily by text mining biomedical literature from previous coronaviruses, including SARS and middle east respiratory syndrome (MERS). Repurposed drugs included potential primary SARS-CoV-2 treatment, adjunctive therapies, or therapeutics to treat side effects. The link prediction accuracy for nodes ranked highly for SARS coronavirus was 0.875 as calculated by human in the loop validation on existing COVID-19 specific data sets. Drug classes predicted as highly ranked include anti-inflammatory, nucleoside analogs, protease inhibitors, antimalarials, envelope proteins, and glycoproteins. Examples of highly ranked predicted links to SARS-CoV-2: human leukocyte interferon, recombinant interferon-gamma, cyclosporine, antiviral therapy, zidovudine, chloroquine, vaccination, methotrexate, artemisinin, alkaloids, glycyrrhizic acid, quinine, flavonoids, amprenavir, suramin, complement system proteins, fluoroquinolones, bone marrow transplantation, albuterol, ciprofloxacin, quinolone antibacterial agents, and hydroxymethylglutaryl-CoA reductase inhibitors. Approximately 40% of identified drugs were not previously connected to SARS, such as edetic acid or biotin. In summary, link prediction can effectively suggest repurposed drugs for emergent diseases.

Diabetes and Total Joint Arthroplasty: Infection Risk May Not Be Predictable by Markers of Glycemic Control.

With an increasing prevalence of diabetes, there is a need to risk stratify arthroplasty patients preoperatively and characterize postoperative infections. This study sought to determine if perioperative markers of diabetic control were associated with infection and to further characterize diabetic periprosthetic joint infections (PJI). A retrospective analysis of 506 diabetic patients and 900 nondiabetic patients who underwent primary total hip and knee arthroplasty was performed. In this cohort, an infection rate of 4.7% and 2.0% for diabetic and nondiabetic patients, respectively, was observed. There was no association between infection at 1 year and preoperative hemoglobin A1C or postoperative blood glucose; however, diabetic infections were significantly more likely to be deep (HR = 4.6; p < .001) and present >6 weeks postoperatively (HR = 8.0; p = .001). This study concluded that common markers of glycemic control are not predictive of the increased risk of diabetic PJI and alternative markers should be investigated. (Journal of Surgical Orthopaedic Advances 28(2):127-131, 2019).

Comparison of the QuantiFERON-TB Gold Plus and QuantiFERON-TB Gold In-Tube Interferon Gamma Release Assays in Patients at Risk for Tuberculosis and in Health Care Workers.

The QuantiFERON-TB Gold Plus (QFT-Plus; Qiagen, Germantown, MD) interferon gamma release assay (IGRA) received FDA clearance in 2017 and will replace the prior version of the assay, the QFT-Gold In-Tube (QFT-GIT). Here, we compared performances of the QFT-Plus assay and the QFT-GIT version in a diverse patient population, including patients undergoing evaluation for or follow-up of latent tuberculosis infection (LTBI; n = 39) or active TB infection (n = 3), and in health care workers (HCWs; n = 119) at Mayo Clinic (Rochester, MN). Compared to the QFT-GIT, the QFT-Plus assay showed 91.2% (31/34) positive, 98.4% (124/126) negative, and 96.6% (156/161) overall qualitative agreement among the 161 enrolled subjects, with a Cohen's kappa value of 0.91 (excellent interrater agreement). Among the 28 patients diagnosed with LTBI at the time of enrollment, the QFT-GIT and QFT-Plus assays agreed in 24 (85.7%) patients; in all four discordant patients, the positivity of the QFT-GIT or QFT-Plus IGRA was associated with low-level interferon gamma (IFN-γ) reactivity, ranging from 0.36 IU/ml to 0.66 IU/ml. Additionally, we document a high degree of correlation between IFN-γ levels in the QFT-GIT TB antigen tube and each of the two QFT-Plus TB antigen tubes, as well as between the QFT-Plus TB1 and TB2 tubes (Pearson's correlation coefficients [R] > 0.95). Overall, we show comparable results between the QFT-GIT and QFT-Plus assays in our study population composed of subjects presenting with a diverse spectrum of TB infections. Our findings suggest that the necessary transition to the QFT-Plus assay will be associated with a minimal difference in assay performance characteristics.

Combinatorial Immunoprofiling in Latent Tuberculosis Infection. Toward Better Risk Stratification.

RATIONALE: Most immunocompetent patients diagnosed with latent tuberculosis infection (LTBI) will not progress to tuberculosis (TB) reactivation. However, current diagnostic tools cannot reliably distinguish nonprogressing from progressing patients a priori, and thus LTBI therapy must be prescribed with suboptimal patient specificity. We hypothesized that LTBI diagnostics could be improved by generating immunomarker profiles capable of categorizing distinct patient subsets by a combinatorial immunoassay approach. OBJECTIVES: A combinatorial immunoassay analysis was applied to identify potential immunomarker combinations that distinguish among unexposed subjects, untreated patients with LTBI, and treated patients with LTBI and to differentiate risk of reactivation. METHODS: IFN-γ release assay (IGRA) was combined with a flow cytometric assay that detects induction of CD25(+)CD134(+) coexpression on TB antigen-stimulated T cells from peripheral blood. The combinatorial immunoassay analysis was based on receiver operating characteristic curves, technical cut-offs, 95% bivariate normal density ellipse prediction, and statistical analysis. Risk of reactivation was estimated with a prediction formula. MEASUREMENTS AND MAIN RESULTS: Sixty-five out of 150 subjects were included. The combinatorial immunoassay approach identified at least four different T-cell subsets. The representation of these immune phenotypes was more heterogeneous in untreated patients with LTBI than in treated patients with LTBI or unexposed groups. Patients with IGRA(+) CD4(+)CD25(+)CD134(+) T-cell phenotypes had the highest estimated reactivation risk (4.11 ± 2.11%). CONCLUSIONS: These findings suggest that immune phenotypes defined by combinatorial assays may potentially have a role in identifying those at risk of developing TB; this potential role is supported by risk of reactivation modeling. Prospective studies will be needed to test this novel approach.

Measurement of Natural Losses of LNAPL Using CO2 Traps.

Efflux of CO2 above releases of petroleum light nonaqueous phase liquids (LNAPLs) has emerged as a critical parameter for resolving natural losses of LNAPLs and managing LNAPL sites. Current approaches for resolving CO2 efflux include gradient, flux chamber, and mass balance methods. Herein a new method for measuring CO2 efflux above LNAPL bodies, referred to as CO2 traps, is introduced. CO2 traps involve an upper and a lower solid phase sorbent elements that convert CO2 gas into solid phase carbonates. The sorbent is placed in an open vertical section of 10 cm ID polyvinyl chloride (PVC) pipe located at grade. The lower sorbent element captures CO2 released from the subsurface via diffusion and advection. The upper sorbent element prevents atmospheric CO2 from reaching the lower sorbent element. CO2 traps provide integral measurement of CO2 efflux based over the period of deployment, typically 2 to 4 weeks. Favorable attributes of CO2 traps include simplicity, generation of integral (time averaged) measurement, and a simple means of capturing CO2 for carbon isotope analysis. Results from open and closed laboratory experiments indicate that CO2 traps quantitatively capture CO2 . Results from the deployment of 23 CO2 traps at a former refinery indicate natural loss rates of LNAPL (measured in the fall, likely concurrent with high soil temperatures and consequently high degradation rates) ranging from 13,400 to 130,000 liters per hectare per year (L/Ha/year). A set of field triplicates indicates a coefficient of variation of 18% (resulting from local spatial variations and issues with measurement accuracy).

Bronchoscopy in suspected pulmonary TB with negative induced-sputum smear and MTD(®) Gen-probe testing.

INTRODUCTION: In our institution, patients with suspected pulmonary TB undergo multiple induced-sputum sampling for microscopy, culture and nucleic acid amplification (NAA) with the MTD(®) Gen-probe assay. Those with negative induced-sputum results still suspected with TB are then referred for bronchoscopy. We sought to determine the diagnostic yield of bronchoscopy in these patients with negative initial induced-sputum results both via smear and NAA testing. METHODS: We identified 30 consecutive cases of suspected pulmonary TB between 2001 and 2007, who had undergone a diagnostic bronchoscopy after negative results on induced-sputum smears and the MTD(®) Gen-probe on at least 2 samples. RESULTS: The cohort (M = 20 & F = 10) had a median age of 37 (range 16-85 yrs); were predominantly foreign born (27/30); HIV-negative (29/30) individuals with strongly positive TST's (mean 18 + 5 mm). Induced-sputum cultures were negative for M-TB in all patients after a full 60-day incubation period. BAL was culture positive for M-TB in 3/30 cases (10%) with 2 strains being pan-sensitive and the third being INH resistant. BAL microscopy with acid-fast smear (n = 30) and BAL Gen-probe (n = 23) were negative in all cases. A third of the patients (9/27, 33%) with negative bronchoscopy results were treated for culture negative TB. Treatment for latent TB was initiated in 5/27 (18%) individuals whereas 13/27 (48%) received no further treatment. CONCLUSION: Bronchoscopy provided diagnostic confirmation of pulmonary TB in 10% of subjects at least 2 negative induced-sputum samples by smear microscopy and NAA testing.

An innovative model for tuberculosis control: an academic medical center-public health department partnership.

Between 1996 and 1999, the incidence rate of active tuberculosis (TB) in Olmsted County, Minnesota, increased by 365%--from 3.4 cases per 100,000 population to 15.8 per 100,000 people. The need for early detection and treatment of TB, efficient care delivery, and cost containment led to the establishment in 2001 of an innovative centralized TB clinic. The clinic was established through a collaboration between Mayo Clinic and the Olmsted County Public Health Department. Following its inception, conversion rates for sputum-positive culture increased from 69.2% to 92%, and the percentage of patients taking part in directly observed therapy increased from 20.8% to 94.6%. Because of successful medical outcomes and acceptance by patients, providers, and the community, the clinic model lends itself to replication elsewhere in the United States.

Incidence of tuberculosis in Olmsted County, Minnesota, 1990-2001.

OBJECTIVE: To describe and compare the incidence and clinical characteristics of tuberculosis in Olmsted County, Minnesota, among US-born and foreign-born persons. PATIENTS AND METHODS: We performed a retrospective cohort study at the Mayo Clinic in Rochester, Minn, of all residents of Olmsted County (2000 population: 124,277) diagnosed as having tuberculosis between January 1, 1990, and December 31, 2001. Potential cases were identified with use of a computerized diagnostic coding database and microbiological laboratory data; all identified medical records were abstracted. Definite cases were those in which Mycobacterium tuberculosis was recovered in culture. Probable cases were those that met predefined clinical or radiographic evidence of tuberculosis and other criteria. Age-specific, sex-specific, and country of origin-specific incidence rates were calculated with use of Olmsted County census data. Variables were compared among risk groups using the Fisher exact test. RESULTS: During a 12-year period, 71 cases of tuberculosis (53 definite, 18 probable) were identified, for an incidence of 5.3 per 100,000 person-years. Of these cases, 54 (76%) occurred during the second half of the study (incidence: 7.7 per 100,000 person-years). The incidence among US-born persons was similar throughout the study period; however, the Incidence among foreign-born persons increased more than 3-fold during the second half of the study period. Twenty-five patients (35%) were former refugees. All isoniazid-resistant infections (12% of isolates) and multidrug-resistant infections (6% of isolates) occurred among foreign-born persons. CONCLUSION: The incidence of tuberculosis increased substantially in Olmsted County between 1990 and 2001, primarily because of an increase in the number of cases among foreign-born persons.