The role of comprehensive stress cardiac MRI in autoimmune rheumatic disease: A review.

Cardiovascular disease is the leading cause of morbidity and mortality in patients with autoimmune rheumatic diseases. Much of this may be attributed to systemic inflammation resulting in coronary atherosclerosis and myocarditis. Cardiac magnetic resonance imaging is the gold standard for the evaluation of cardiac structure and function, including tissue characterization, which allows for detection of myocardial edema, inflammation, and fibrosis. Advances in parametric mapping and coronary flow reserve measurement techniques have the potential to change the diagnosis, risk stratification, and management of patients with autoimmune rheumatic diseases. We provide an overview of the current evidence and suggest potential future roles for the use of comprehensive cardiac magnetic resonance in patients with autoimmune rheumatic diseases in the field of cardio-rheumatology.

Potential measurement error from vessel reflex and multiple light paths in dual-wavelength retinal oximetry.

PURPOSE: This study aims to characterize the dependence of measured retinal arterial and venous saturation on vessel diameter and central reflex in retinal oximetry, with an ultimate goal of identifying potential causes and suggesting approaches to improve measurement accuracy. METHODS: In 10 subjects, oxygen saturation, vessel diameter and optical density are obtained using Oxymap Analyzer software without diameter correction. Diameter dependence of saturation is characterized using linear regression between measured values of saturation and diameter. Occurrences of negative values of vessel optical densities (ODs) associated with central vessel reflex are acquired from Oxymap Analyzer. A conceptual model is used to calculate the ratio of optical densities (ODRs) according to retinal reflectance properties and single and double-pass light transmission across fixed path lengths. Model-predicted values are compared with measured oximetry values at different vessel diameters. RESULTS: Venous saturation shows an inverse relationship with vessel diameter (D) across subjects, with a mean slope of -0.180 (SE = 0.022) %/µm (20 < D < 180 µm) and a more rapid saturation increase at small vessel diameters reaching to over 80%. Arterial saturation yields smaller positive and negative slopes in individual subjects, with an average of -0.007 (SE = 0.021) %/µm (20 < D < 200 µm) across all subjects. Measurements where vessel brightness exceeds that of the retinal background result in negative values of optical density, causing an artifactual increase in saturation. Optimization of model reflectance values produces a good fit of the conceptual model to measured ODRs. CONCLUSION: Measurement artefacts in retinal oximetry are caused by strong central vessel reflections, and apparent diameter sensitivity may result from single and double-pass transmission in vessels. Improvement in correction for vessel diameter is indicated for arteries however further study is necessary for venous corrections.

Clinical Management of Brugada Syndrome: Commentary From the Experts.

Although there is consensus on the management of patients with Brugada Syndrome with high risk for sudden cardiac arrest, asymptomatic or intermediate-risk patients present clinical management challenges. This document explores the management opinions of experts throughout the world for patients with Brugada Syndrome who do not fit guideline recommendations. Four real-world clinical scenarios were presented with commentary from small expert groups for each case. All authors voted on case-specific questions to evaluate the level of consensus among the entire group in nuanced diagnostic and management decisions relevant to each case. Points of agreement, points of controversy, and gaps in knowledge are highlighted.

Adding open spectral data to MassBank and PubChem using open source tools to support non-targeted exposomics of mixtures.

The term "exposome" is defined as a comprehensive study of life-course environmental exposures and the associated biological responses. Humans are exposed to many different chemicals, which can pose a major threat to the well-being of humanity. Targeted or non-targeted mass spectrometry techniques are widely used to identify and characterize various environmental stressors when linking exposures to human health. However, identification remains challenging due to the huge chemical space applicable to exposomics, combined with the lack of sufficient relevant entries in spectral libraries. Addressing these challenges requires cheminformatics tools and database resources to share curated open spectral data on chemicals to improve the identification of chemicals in exposomics studies. This article describes efforts to contribute spectra relevant for exposomics to the open mass spectral library MassBank (https://www.massbank.eu) using various open source software efforts, including the R packages RMassBank and Shinyscreen. The experimental spectra were obtained from ten mixtures containing toxicologically relevant chemicals from the US Environmental Protection Agency (EPA) Non-Targeted Analysis Collaborative Trial (ENTACT). Following processing and curation, 5582 spectra from 783 of the 1268 ENTACT compounds were added to MassBank, and through this to other open spectral libraries (e.g., MoNA, GNPS) for community benefit. Additionally, an automated deposition and annotation workflow was developed with PubChem to enable the display of all MassBank mass spectra in PubChem, which is rerun with each MassBank release. The new spectral records have already been used in several studies to increase the confidence in identification in non-target small molecule identification workflows applied to environmental and exposomics research.

PubChem 2023 update.

PubChem (https://pubchem.ncbi.nlm.nih.gov) is a popular chemical information resource that serves a wide range of use cases. In the past two years, a number of changes were made to PubChem. Data from more than 120 data sources was added to PubChem. Some major highlights include: the integration of Google Patents data into PubChem, which greatly expanded the coverage of the PubChem Patent data collection; the creation of the Cell Line and Taxonomy data collections, which provide quick and easy access to chemical information for a given cell line and taxon, respectively; and the update of the bioassay data model. In addition, new functionalities were added to the PubChem programmatic access protocols, PUG-REST and PUG-View, including support for target-centric data download for a given protein, gene, pathway, cell line, and taxon and the addition of the 'standardize' option to PUG-REST, which returns the standardized form of an input chemical structure. A significant update was also made to PubChemRDF. The present paper provides an overview of these changes.

Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data.

Analyses of data from genome-wide association studies on unrelated individuals have shown that, for human traits and diseases, approximately one-third to two-thirds of heritability is captured by common SNPs. However, it is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular whether the causal variants are rare, or whether it is overestimated due to bias in inference from pedigree data. Here we estimated heritability for height and body mass index (BMI) from whole-genome sequence data on 25,465 unrelated individuals of European ancestry. The estimated heritability was 0.68 (standard error 0.10) for height and 0.30 (standard error 0.10) for body mass index. Low minor allele frequency variants in low linkage disequilibrium (LD) with neighboring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection. Our results imply that rare variants, in particular those in regions of low linkage disequilibrium, are a major source of the still missing heritability of complex traits and disease.

PubChem in 2021: new data content and improved web interfaces.

PubChem (https://pubchem.ncbi.nlm.nih.gov) is a popular chemical information resource that serves the scientific community as well as the general public, with millions of unique users per month. In the past two years, PubChem made substantial improvements. Data from more than 100 new data sources were added to PubChem, including chemical-literature links from Thieme Chemistry, chemical and physical property links from SpringerMaterials, and patent links from the World Intellectual Properties Organization (WIPO). PubChem's homepage and individual record pages were updated to help users find desired information faster. This update involved a data model change for the data objects used by these pages as well as by programmatic users. Several new services were introduced, including the PubChem Periodic Table and Element pages, Pathway pages, and Knowledge panels. Additionally, in response to the coronavirus disease 2019 (COVID-19) outbreak, PubChem created a special data collection that contains PubChem data related to COVID-19 and the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

PubChem 2019 update: improved access to chemical data.

PubChem (https://pubchem.ncbi.nlm.nih.gov) is a key chemical information resource for the biomedical research community. Substantial improvements were made in the past few years. New data content was added, including spectral information, scientific articles mentioning chemicals, and information for food and agricultural chemicals. PubChem released new web interfaces, such as PubChem Target View page, Sources page, Bioactivity dyad pages and Patent View page. PubChem also released a major update to PubChem Widgets and introduced a new programmatic access interface, called PUG-View. This paper describes these new developments in PubChem.

Finding Potential Multitarget Ligands Using PubChem.

PubChem ( https://pubchem.ncbi.nlm.nih.gov ) is a key chemical information resource, developed and maintained by the US National Institutes of Health. The present chapter describes how to find potential multitarget ligands from PubChem that would be tested in further experiments. While the protocol presented here uses PubChem's Web-based interfaces to allow users to follow it interactively, it can also be implemented in computer software by using programmatic access interfaces to PubChem (such as PUG-REST or E-Utilities).

Relation of Body Mass Index to Symptom Burden in Patients withAtrial Fibrillation.

Atrial fibrillation (AF) is the most common sustained arrhythmia and is associated with significant morbidity and increased mortality. As body mass index (BMI) is increasingly recognized as an important risk factor for the development of AF, we tested the hypothesis that BMI modulates symptomatic AF burden. Cross-sectional data collected from 1,382 patients in the Vanderbilt AF Registry were analyzed. AF severity was assessed using the Toronto atrial fibrillation severity scale (AFSS). BMI was categorized according to World Health Organization guidelines and patients were grouped according to their present AF treatment regimen: no treatment (n = 185), rate control therapy with atrioventricular nodal blocking agents (n = 351), rhythm control with antiarrhythmic drugs (n = 636), and previous AF ablation (n = 210). Patients with BMI >35 kg/m2 had higher AFSS scores than those with BMI <30 kg/m2 in the rate control (43.57 vs 38.21: p = 0.0057), rhythm control (46.61 vs 41.08: p = 1.6 × 10-4), and ablation (44.01 vs 39.02: p = 0.047) groups. Inunivariate linear models, BMI was associated with an increase in the AFSS score in the rate control (0.27, 95% confidence interval [CI] 0.05 to 0.5, p = 0.02), rhythm control (0.38, 95% CI 0.21 to 0.56, p = 2.49 × 10-5), and ablation (0.38, 95% CI 0.03 to 0.73, p = 0.03) groups. The association remained significant in the rhythm control groups after adjusting for age, gender, race, and comorbidities (0.29, 95% CI 0.11 to 0.49, p = 0.002). In conclusion, increasing BMI was directly associated with patient reported measures of AF symptom severity, burden, and quality of life. This was most significant in patients treated with rhythm-control strategies.

Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with In Silico Workflows.

We describe a computational protocol to aid the design of small molecule and peptide drugs that target protein-protein interactions, particularly for anti-cancer therapy. To achieve this goal, we explore multiple strategies, including finding binding hot spots, incorporating chemical similarity and bioactivity data, and sampling similar binding sites from homologous protein complexes. We demonstrate how to combine existing interdisciplinary resources with examples of semi-automated workflows. Finally, we discuss several major problems, including the occurrence of drug-resistant mutations, drug promiscuity, and the design of dual-effect inhibitors.

PubChem BioAssay: 2017 update.

PubChem's BioAssay database (https://pubchem.ncbi.nlm.nih.gov) has served as a public repository for small-molecule and RNAi screening data since 2004 providing open access of its data content to the community. PubChem accepts data submission from worldwide researchers at academia, industry and government agencies. PubChem also collaborates with other chemical biology database stakeholders with data exchange. With over a decade's development effort, it becomes an important information resource supporting drug discovery and chemical biology research. To facilitate data discovery, PubChem is integrated with all other databases at NCBI. In this work, we provide an update for the PubChem BioAssay database describing several recent development including added sources of research data, redesigned BioAssay record page, new BioAssay classification browser and new features in the Upload system facilitating data sharing.

Literature information in PubChem: associations between PubChem records and scientific articles.

BACKGROUND: PubChem is an open archive consisting of a set of three primary public databases (BioAssay, Compound, and Substance). It contains information on a broad range of chemical entities, including small molecules, lipids, carbohydrates, and (chemically modified) amino acid and nucleic acid sequences (including siRNA and miRNA). Currently (as of Nov. 2015), PubChem contains more than 150 million depositor-provided chemical substance descriptions, 60 million unique chemical structures, and 225 million biological activity test results provided from over 1 million biological assay records. DESCRIPTION: Many PubChem records (substances, compounds, and assays) include depositor-provided cross-references to scientific articles in PubMed. Some PubChem contributors provide bioactivity data extracted from scientific articles. Literature-derived bioactivity data complement high-throughput screening (HTS) data from the concluded NIH Molecular Libraries Program and other HTS projects. Some journals provide PubChem with information on chemicals that appear in their newly published articles, enabling concurrent publication of scientific articles in journals and associated data in public databases. In addition, PubChem links records to PubMed articles indexed with the Medical Subject Heading (MeSH) controlled vocabulary thesaurus. CONCLUSION: Literature information, both provided by depositors and derived from MeSH annotations, can be accessed using PubChem's web interfaces, enabling users to explore information available in literature related to PubChem records beyond typical web search results. GRAPHICAL ABSTRACT: Graphical abstractLiterature information for PubChem records is derived from various sources.

PubChem Substance and Compound databases.

PubChem (https://pubchem.ncbi.nlm.nih.gov) is a public repository for information on chemical substances and their biological activities, launched in 2004 as a component of the Molecular Libraries Roadmap Initiatives of the US National Institutes of Health (NIH). For the past 11 years, PubChem has grown to a sizable system, serving as a chemical information resource for the scientific research community. PubChem consists of three inter-linked databases, Substance, Compound and BioAssay. The Substance database contains chemical information deposited by individual data contributors to PubChem, and the Compound database stores unique chemical structures extracted from the Substance database. Biological activity data of chemical substances tested in assay experiments are contained in the BioAssay database. This paper provides an overview of the PubChem Substance and Compound databases, including data sources and contents, data organization, data submission using PubChem Upload, chemical structure standardization, web-based interfaces for textual and non-textual searches, and programmatic access. It also gives a brief description of PubChem3D, a resource derived from theoretical three-dimensional structures of compounds in PubChem, as well as PubChemRDF, Resource Description Framework (RDF)-formatted PubChem data for data sharing, analysis and integration with information contained in other databases.

Balancing Protein Stability and Activity in Cancer: A New Approach for Identifying Driver Mutations Affecting CBL Ubiquitin Ligase Activation.

Oncogenic mutations in the monomeric Casitas B-lineage lymphoma (Cbl) gene have been found in many tumors, but their significance remains largely unknown. Several human c-Cbl (CBL) structures have recently been solved, depicting the protein at different stages of its activation cycle and thus providing mechanistic insight underlying how stability-activity tradeoffs in cancer-related proteins-may influence disease onset and progression. In this study, we computationally modeled the effects of missense cancer mutations on structures representing four stages of the CBL activation cycle to identify driver mutations that affect CBL stability, binding, and activity. We found that recurrent, homozygous, and leukemia-specific mutations had greater destabilizing effects on CBL states than random noncancer mutations. We further tested the ability of these computational models, assessing the changes in CBL stability and its binding to ubiquitin-conjugating enzyme E2, by performing blind CBL-mediated EGFR ubiquitination assays in cells. Experimental CBL ubiquitin ligase activity was in agreement with the predicted changes in CBL stability and, to a lesser extent, with CBL-E2 binding affinity. Two thirds of all experimentally tested mutations affected the ubiquitin ligase activity by either destabilizing CBL or disrupting CBL-E2 binding, whereas about one-third of tested mutations were found to be neutral. Collectively, our findings demonstrate that computational methods incorporating multiple protein conformations and stability and binding affinity evaluations can successfully predict the functional consequences of cancer mutations on protein activity, and provide a proof of concept for mutations in CBL.

National health accounts data from 1996 to 2010: a systematic review.

OBJECTIVE: To collect, compile and evaluate publicly available national health accounts (NHA) reports produced worldwide between 1996 and 2010. METHODS: We downloaded country-generated NHA reports from the World Health Organization global health expenditure database and the Organisation for Economic Co-operation and Development (OECD) StatExtract website. We also obtained reports from Abt Associates, through contacts in individual countries and through an online search. We compiled data in the four main types used in these reports: (i) financing source; (ii) financing agent; (iii) health function; and (iv) health provider. We combined and adjusted data to conform with OECD's first edition of A system of health accounts manual, (2000). FINDINGS: We identified 872 NHA reports from 117 countries containing a total of 2936 matrices for the four data types. Most countries did not provide complete health expenditure data: only 252 of the 872 reports contained data in all four types. Thirty-eight countries reported an average not-specified-by-kind value greater than 20% for all data types and years. Some countries reported substantial year-on-year changes in both the level and composition of health expenditure that were probably produced by data-generation processes. All study data are publicly available at http://vizhub.healthdata.org/nha/. CONCLUSION: Data from NHA reports on health expenditure are often incomplete and, in some cases, of questionable quality. Better data would help finance ministries allocate resources to health systems, assist health ministries in allocating capital within the health sector and enable researchers to make accurate comparisons between health systems.

Structural Perspectives on the Evolutionary Expansion of Unique Protein-Protein Binding Sites.

Structures of protein complexes provide atomistic insights into protein interactions. Human proteins represent a quarter of all structures in the Protein Data Bank; however, available protein complexes cover less than 10% of the human proteome. Although it is theoretically possible to infer interactions in human proteins based on structures of homologous protein complexes, it is still unclear to what extent protein interactions and binding sites are conserved, and whether protein complexes from remotely related species can be used to infer interactions and binding sites. We considered biological units of protein complexes and clustered protein-protein binding sites into similarity groups based on their structure and sequence, which allowed us to identify unique binding sites. We showed that the growth rate of the number of unique binding sites in the Protein Data Bank was much slower than the growth rate of the number of structural complexes. Next, we investigated the evolutionary roots of unique binding sites and identified the major phyletic branches with the largest expansion in the number of novel binding sites. We found that many binding sites could be traced to the universal common ancestor of all cellular organisms, whereas relatively few binding sites emerged at the major evolutionary branching points. We analyzed the physicochemical properties of unique binding sites and found that the most ancient sites were the largest in size, involved many salt bridges, and were the most compact and least planar. In contrast, binding sites that appeared more recently in the evolution of eukaryotes were characterized by a larger fraction of polar and aromatic residues, and were less compact and more planar, possibly due to their more transient nature and roles in signaling processes.

Coverage of protein domain families with structural protein-protein interactions: current progress and future trends.

Protein interactions have evolved into highly precise and regulated networks adding an immense layer of complexity to cellular systems. The most accurate atomistic description of protein binding sites can be obtained directly from structures of protein complexes. The availability of structurally characterized protein interfaces significantly improves our understanding of interactomes, and the progress in structural characterization of protein-protein interactions (PPIs) can be measured by calculating the structural coverage of protein domain families. We analyze the coverage of protein domain families (defined according to CDD and Pfam databases) by structures, structural protein-protein complexes and unique protein binding sites. Structural PPI coverage of currently available protein families is about 30% without any signs of saturation in coverage growth dynamics. Given the current growth rates of domain databases and structural PPI deposition, complete domain coverage with PPIs is not expected in the near future. As a result of this study we identify families without any protein-protein interaction evidence (listed on a supporting website http://www.ncbi.nlm.nih.gov/Structure/ibis/coverage/) and propose them as potential targets for structural studies with a focus on protein interactions.

PubChem BioAssay: 2014 update.

PubChem's BioAssay database (http://pubchem.ncbi.nlm.nih.gov) is a public repository for archiving biological tests of small molecules generated through high-throughput screening experiments, medicinal chemistry studies, chemical biology research and drug discovery programs. In addition, the BioAssay database contains data from high-throughput RNA interference screening aimed at identifying critical genes responsible for a biological process or disease condition. The mission of PubChem is to serve the community by providing free and easy access to all deposited data. To this end, PubChem BioAssay is integrated into the National Center for Biotechnology Information retrieval system, making them searchable by Entrez queries and cross-linked to other biomedical information archived at National Center for Biotechnology Information. Moreover, PubChem BioAssay provides web-based and programmatic tools allowing users to search, access and analyze bioassay test results and metadata. In this work, we provide an update for the PubChem BioAssay resource, such as information content growth, new developments supporting data integration and search, and the recently deployed PubChem Upload to streamline chemical structure and bioassay submissions.

Cancer missense mutations alter binding properties of proteins and their interaction networks.

Many studies have shown that missense mutations might play an important role in carcinogenesis. However, the extent to which cancer mutations might affect biomolecular interactions remains unclear. Here, we map glioblastoma missense mutations on the human protein interactome, model the structures of affected protein complexes and decipher the effect of mutations on protein-protein, protein-nucleic acid and protein-ion binding interfaces. Although some missense mutations over-stabilize protein complexes, we found that the overall effect of mutations is destabilizing, mostly affecting the electrostatic component of binding energy. We also showed that mutations on interfaces resulted in more drastic changes of amino acid physico-chemical properties than mutations occurring outside the interfaces. Analysis of glioblastoma mutations on interfaces allowed us to stratify cancer-related interactions, identify potential driver genes, and propose two dozen additional cancer biomarkers, including those specific to functions of the nervous system. Such an analysis also offered insight into the molecular mechanism of the phenotypic outcomes of mutations, including effects on complex stability, activity, binding and turnover rate. As a result of mutated protein and gene network analysis, we observed that interactions of proteins with mutations mapped on interfaces had higher bottleneck properties compared to interactions with mutations elsewhere on the protein or unaffected interactions. Such observations suggest that genes with mutations directly affecting protein binding properties are preferably located in central network positions and may influence critical nodes and edges in signal transduction networks.