COVID-19 pneumonia chest radiographic severity score: variability assessment among experienced and in-training radiologists and creation of a multireader composite score database for artificial intelligence algorithm development.

OBJECTIVE: The purpose was to evaluate reader variability between experienced and in-training radiologists of COVID-19 pneumonia severity on chest radiograph (CXR), and to create a multireader database suitable for AI development. METHODS: In this study, CXRs from polymerase chain reaction positive COVID-19 patients were reviewed. Six experienced cardiothoracic radiologists and two residents classified each CXR according to severity. One radiologist performed the classification twice to assess intraobserver variability. Severity classification was assessed using a 4-class system: normal (0), mild (1), moderate (2), and severe (3). A median severity score (Rad Med) for each CXR was determined for the six radiologists for development of a multireader database (XCOMS). Kendal Tau correlation and percentage of disagreement were calculated to assess variability. RESULTS: A total of 397 patients (1208 CXRs) were included (mean age, 60 years SD ± 1), 189 men). Interobserver variability between the radiologists ranges between 0.67 and 0.78. Compared to the Rad Med score, the radiologists show good correlation between 0.79-0.88. Residents show slightly lower interobserver agreement of 0.66 with each other and between 0.69 and 0.71 with experienced radiologists. Intraobserver agreement was high with a correlation coefficient of 0.77. In 220 (18%), 707 (59%), 259 (21%) and 22 (2%) CXRs there was a 0, 1, 2 or 3 class-difference. In 594 (50%) CXRs the median scores of the residents and the radiologists were similar, in 578 (48%) and 36 (3%) CXRs there was a 1 and 2 class-difference. CONCLUSION: Experienced and in-training radiologists demonstrate good inter- and intraobserver agreement in COVID-19 pneumonia severity classification. A higher percentage of disagreement was observed in moderate cases, which may affect training of AI algorithms. ADVANCES IN KNOWLEDGE: Most AI algorithms are trained on data labeled by a single expert. This study shows that for COVID-19 X-ray severity classification there is significant variability and disagreement between radiologist and between residents.

Toward understanding COVID-19 pneumonia: a deep-learning-based approach for severity analysis and monitoring the disease.

We report a new approach using artificial intelligence (AI) to study and classify the severity of COVID-19 using 1208 chest X-rays (CXRs) of 396 COVID-19 patients obtained through the course of the disease at Emory Healthcare affiliated hospitals (Atlanta, GA, USA). Using a two-stage transfer learning technique to train a convolutional neural network (CNN), we show that the algorithm is able to classify four classes of disease severity (normal, mild, moderate, and severe) with the average Area Under the Curve (AUC) of 0.93. In addition, we show that the outputs of different layers of the CNN under dominant filters provide valuable insight about the subtle patterns in the CXRs, which can improve the accuracy in the reading of CXRs by a radiologist. Finally, we show that our approach can be used for studying the disease progression in a single patient and its influencing factors. The results suggest that our technique can form the foundation of a more concrete clinical model to predict the evolution of COVID-19 severity and the efficacy of different treatments for each patient through using CXRs and clinical data in the early stages of the disease. This use of AI to assess the severity and possibly predicting the future stages of the disease early on, will be essential in dealing with the upcoming waves of COVID-19 and optimizing resource allocation and treatment.

Association of NAD (P) H Quinine Oxidoreductase 1 rs1800566 Polymorphism with Bladder and Prostate Cancers - a Systematic Review and Meta-Analysis.

BACKGROUND: Number of studies has been performed to investigate the association of NAD (P) H quinine oxidoreductase 1 (NQO1) rs1800566 polymorphism with risk of bladder and prostate cancers, but presented inconsistent results. Therefore, we performed a meta-analysis to provide a comprehensive data on the association of NQO1 rs1800566 polymorphism with bladder and prostate cancers. METHODS: All eligible studies were identified in PubMed, Google Scholar, EMBASE, and China National Knowledge Infrastructure databases before June 01, 2019. RESULTS: A total of 22 case-control studies including 15 studies with 4,413 cases and 4,275 controls on bladder cancer and 7 studies with 762 cases and 1,813 controls on prostate cancer were selected. Overall, pooled data showed that the NQO1 rs1800566 polymorphism was significantly associated with an increased risk of bladder cancer (T vs. C: OR 1.300; 95% CI 1.112-1.518; P = 0.001; TT vs. CC: OR 1.415; 95% CI 1.084-1.847; P = 0.011; TC vs. CC: OR 1.389; 95% CI 1.111-1.738; P = 0.004; TT + TC vs. CC: OR 1.428; 95% CI 1.145-1.782; P = 0.002) and prostate cancer (TC vs. CC: OR 1.276; 95% CI 1.047-1.555; P = 0.016; TT + TC vs. CC: OR 1.268; 95% CI 1.050-1.532; P = 0.014). The stratified analysis by ethnicity revealed an increased risk of bladder cancer among Caucasians and prostate cancer among Asians. CONCLUSION: This meta-analysis suggested that the NQO1 rs1800566 polymorphism was significantly associated with increased risk of bladder and prostate cancers.

Synthetic Small Molecule Characterization and Isomer Discrimination Using Gas-Phase Hydrogen-Deuterium Exchange IMS-MS.

Ion mobility spectrometry-mass spectrometry (IMS-MS) combined with gas-phase hydrogen-deuterium exchange has been used to characterize novel psychoactive substances (NPSs) which are small synthetic compounds designed to mimic the effects of other illicit substances. Here, NPSs containing labile heteroatom hydrogens were evaluated for HDX reactivity in the presence of either deuterated water (D2O) or ammonia (ND3) within the drift tube. An initial evaluation of exchange propensity was performed for six NPSs. Five compounds exchanged in the presence of ND3 while only one NPS (benzyl piperazine) exchanged with D2O. The exchange mechanism of D2O requires stabilization with a nearby charged site; the diamine ring of benzyl piperazine provided this charge site at a fixed length. Three disubstituted benzene isomers ( o-, m-, and p-fluorophenyl piperazine) containing the diamine ring structure and a fluorine atom were subsequently analyzed. Having identical isotopic composition and nearly identical drift time distributions, these isomers could not be distinguished by IMS-MS alone. However, upon undergoing HDX in the drift tube, a t test of means (α = 0.05) showed that discrimination was possible if the exchange data from both reagent gases were included. Molecular dynamics simulations show that the proximity of the fluorine to the diamine ring hinders the dihedral angle rotation between the benzene and the diamine ring; this may partially account for the observed exchange differences.

Ion Mobility Spectrometry-Mass Spectrometry Coupled with Gas-Phase Hydrogen/Deuterium Exchange for Metabolomics Analyses.

Ion mobility spectrometry-mass spectrometry (IMS-MS) in combination with gas-phase hydrogen/deuterium exchange (HDX) and collision-induced dissociation (CID) is evaluated as an analytical method for small-molecule standard and mixture characterization. Experiments show that compound ions exhibit unique HDX reactivities that can be used to distinguish different species. Additionally, it is shown that gas-phase HDX kinetics can be exploited to provide even further distinguishing capabilities by using different partial pressures of reagent gas. The relative HDX reactivity of a wide variety of molecules is discussed in light of the various molecular structures. Additionally, hydrogen accessibility scoring (HAS) and HDX kinetics modeling of candidate (in silico) ion structures is utilized to estimate the relative ion conformer populations giving rise to specific HDX behavior. These data interpretation methods are discussed with a focus on developing predictive tools for HDX behavior. Finally, an example is provided in which ion mobility information is supplemented with HDX reactivity data to aid identification efforts of compounds in a metabolite extract. Graphical Abstract ᅟ.

Magnifying ion mobility spectrometry-mass spectrometry measurements for biomolecular structure studies.

Ion mobility spectrometry-mass spectrometry (IMS-MS) provides information about the structures of gas-phase ions in the form of a collision cross section (CCS) with a neutral buffer gas. Indicating relative ion size, a CCS value alone is of limited utility. Although such information can be used to propose different conformer types, finer details of structure are not captured. The increased accessibility of IMS-MS measurements with commercial instrumentation in recent years has ballooned its usage in combination with separate measurements to provide enhanced data from which greater structural inferences can be drawn. This short review presents recent outstanding developments in scientific research that employs complementary measurements that when combined with IMS-MS data are used to characterize the structures of a wide range of compounds.

Ion Mobility, Hydrogen/Deuterium Exchange, and Isotope Scrambling: Tools to Aid Compound Identification in 'Omics Mixtures.

Liquid chromatography tandem mass spectrometry (LC-MS/MS), a widely used method for comparative 'omics analysis, experiences challenges with compound identification due to matrix effects, difficulty in separating isomer and isobaric ions, and long analysis times. Ion mobility spectrometry (IMS) has proven to be useful in separating isomer and isobar ions; however, IMS-MS suffers from decreased peak capacity due to the correlation in ion size and mass. In proof-of-principle experiments, the use of gas-phase hydrogen/deuterium exchange (HDX) combined with IMS-MS/MS techniques is demonstrated to offer advantages for compound identification. Measurements providing unique information for ions include m/z value, drift time in He buffer gas, drift time in He and D2O buffer gases, deuterium incorporation pattern (isotopic distribution), deuterium incorporation pattern after collisional activation, and fragment ion deuterium incorporation pattern upon collision-induced dissociation (CID). These techniques are here shown to be highly reproducible (drift time coefficients of variation < 1.0% and isotopic pattern root-mean-square deviations of 0.5-1.5%) while demonstrating an increased ability to distinguish individual molecules from diverse classes of compounds (peptides, catecholamines, nucleosides, amino acids, etc.). The concept of using such (and similar) information for rapid, high-throughput molecular identification via database searching of standard libraries is briefly discussed, and an example of such usage is presented for a bonafide metabolite extract sample.

Comparative plasma proteomic studies of pulmonary TiO2 nanoparticle exposure in rats using liquid chromatography tandem mass spectrometry.

Mounting evidence suggests that pulmonary exposure to nanoparticles (NPs) has a toxic effect on biological systems. A number of studies have shown that exposure to NPs result in systemic inflammatory response, oxidative stress, and leukocyte adhesion. However, significant knowledge gaps exist for understanding the key molecular mechanisms responsible for altered microvasculature function. Utilizing comprehensive LC-MS/MS and comparative proteomic analysis strategies, important proteins related to TiO2 NP exposure in rat plasma have been identified. Molecular pathway analysis of these proteins revealed 13 canonical pathways as being significant (p ≤ 0.05), but none were found to be significantly up or down-regulated (z>|2|). This work lays the foundation for future research that will monitor relative changes in protein abundance in plasma and tissue as a function of post-exposure time and TiO2 NP dosage to further elucidate mechanisms of pathway activation as well as to decipher other affected pathways.

Combining ion mobility spectrometry with hydrogen-deuterium exchange and top-down MS for peptide ion structure analysis.

The gas-phase conformations of electrosprayed ions of the model peptide KKDDDDIIKIIK have been examined by ion mobility spectrometry (IMS) and hydrogen deuterium exchange (HDX)-tandem mass spectrometry (MS/MS) techniques. [M+4H](4+) ions exhibit two conformers with collision cross sections of 418 Å(2) and 471 Å(2). [M+3H](3+) ions exhibit a predominant conformer with a collision cross section of 340 Å(2) as well as an unresolved conformer (shoulder) with a collision cross section of ~367 Å(2). Maximum HDX levels for the more compact [M+4H](4+) ions and the compact and partially-folded [M+3H](3+) ions are ~12.9, ~15.5, and ~14.9, respectively. Ion structures obtained from molecular dynamics simulations (MDS) suggest that this ordering of HDX level results from increased charge-site/exchange-site density for the more compact ions of lower charge. Additionally, a new model that includes two distance calculations (charge site to carbonyl group and carbonyl group to exchange site) for the computer-generated structures is shown to better correlate to the experimentally determined per-residue deuterium uptake. Future comparisons of IMS-HDX-MS data with structures obtained from MDS are discussed with respect to novel experiments that will reveal the HDX rates of individual residues.

A new ion mobility-linear ion trap instrument for complex mixture analysis.

A new instrument that couples a low-pressure drift tube with a linear ion trap mass spectrometer is demonstrated for complex mixture analysis. The combination of the low-pressure separation with the ion trapping capabilities provides several benefits for complex mixture analysis. These include high sensitivity, unique ion fragmentation capabilities, and high reproducibility. Even though the gas-phase separation and the mass measurement steps are each conducted in an ion filtering mode, detection limits for mobility-selected peptide ions are in the tens of attomole range. In addition to ion separation, the low-pressure drift tube can be used as an ion fragmentation cell yielding mobility-resolved fragment ions that can be subsequently analyzed by multistage tandem mass spectrometry (MS(n)) methods in the ion trap. Because of the ion trap configuration, these methods can be comprised of any number (limited by ion signal) of collision-induced dissociation (CID) and electron transfer dissociation (ETD) processes. The high reproducibility of the gas-phase separation allows for comparison of two-dimensional ion mobility spectrometry (IMS)-MS data sets in a pixel-by-pixel fashion without the need for data set alignment. These advantages are presented in model analyses representing mixtures encountered in proteomics and metabolomics experiments.