1,720,958 research outputs found
Longitudinal plasma proteomic analysis of 1,117 hospitalized COVID-19 patients identifies features associated with severity and outcomes
No full text<h1><span>Data availability:</span></h1>
<p><strong>Data files are available at ImmPort (immport.org) under accession number SDY1760.</strong></p>
<p>Abstract:</p>
<p>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is characterized by highly heterogenous manifestations ranging from asymptomatic cases to death for still incompletely understood reasons. As part of the <em>IMmunoPhenotyping Assessment in a COVID-19 Cohort</em> (IMPACC) study, we mapped the plasma proteomes of 1,117 hospitalized coronavirus disease 2019 (COVID-19) patients from 15 hospitals across the USA. Up to 6 samples were collected within ~28 days of hospitalization resulting in one of the largest COVID-19 plasma proteomics cohorts with 2,934 samples. Using perchloric acid to deplete the most abundant plasma proteins allowed for detecting 2,910 proteins. Our findings show that increased levels of neutrophil extracellular trap and heart damage markers are associated with fatal outcomes. Our analysis also identified prognostic biomarkers for worsening severity and death. Our comprehensive longitudinal plasma proteomics study, involving 1,117 participants and 2,934 samples, allowed for testing the generalizability of the findings of many previous COVID-19 plasma proteomics studies using much smaller cohorts.</p>
<p> </p>
<p>Data:</p>
<p>MATERIALS & METHODS</p>
<p>Ethics Statement</p>
<p>Ethics NIAID staff conferred with the Department of Health and Human Services Office for Human Research Protections (OHRP) regarding potential applicability of the public health surveillance exception [45CFR46.102(39, 93) to the IMPACC study protocol. OHRP concurred that the study satisfied criteria for the public health surveillance exception, and the IMPACC study team sent the study protocol, and participant information sheet for review, and assessment to institutional review boards (IRBs) at participating institutions. Twelve institutions elected to conduct the study as public health surveillance, while 3 sites with prior IRB-approved biobanking protocols elected to integrate and conduct IMPACC under their institutional protocols (University of Texas at Austin, IRB 2020-04-0117; University of California San Francisco, IRB 20-30497; Case Western Reserve University, IRB STUDY20200573) with informed consent requirements. Participants enrolled under the public health surveillance exclusion were provided information sheets describing the study, samples to be collected, and plans for data de-identification, and use. Those that requested not to participate after reviewing the information sheet were not enrolled. In addition, participants did not receive compensation for study participation while inpatient, and subsequently were offered compensation during outpatient follow-ups(40).</p>
<p> </p>
<p>Cohort and Study Design</p>
<p>The cohort and study design of the IMPACC study has been previously published(39, 40). In brief, hospital in-patients 18 years and older admitted to one of the 20 USA hospitals (affiliated with 15 academic institutions) were enrolled in the study within 72 hours of hospital admission. Symptomatic patients with a confirmed positive SARS-CoV-2 PCR test were followed longitudinally for up to 28 days of their hospital stay. Patient outcome was followed for up to 12 months after discharge. The November 2021 data freeze of the clinical data was used for the subsequent analysis.</p>
<p> </p>
<p>Cohort Demographics, Timepoints and Data Collected</p>
<p>All study participant data, containing all relevant deidentified variables, was collected using a secure electronic data collection form(40). Plasma samples were collected upon admission at the hospital and up to 5 additional samples were collected during the acute phase in the hospital.<span> </span>contains demographic information, including sex, median age, median BMI, and median symptom onset.</p>
<p> </p>
<p>Outcome Categorization</p>
<p>As reported(40), the clinical severity of illness was assessed using a 7-point ordinal scale (OS), adapted from the World Health Organization COVID-19 and NIAID disease ordinal severity scales. The 7-point OS includes, OS1 = Not hospitalized, no limitations; OS2= Not hospitalized, activity limitations or requires home O2; OS3 = Hospitalized, not requiring supplemental O2; OS4 = Hospitalized, requiring O2; OS5 = Hospitalized on non-invasive ventilation or high-flow O2; OS6 = Hospitalized on invasive mechanical ventilation and/or Extracorporeal membrane oxygenation (ECMO); OS7 = Death. The 7-point OS for respiratory status was calculated at each hospitalization time point. Patients were then classified into 5 clinical trajectory groups (TG) based on longitudinal modeling of OS over time. A subset of the full IMPACC cohort was analyzed using plasma proteomics after depletion of the most abundant classical plasma proteins. We used the definition of ‘classical plasma proteins’ from Anderson and Anderson(45) and applied the biochemical depletion method as described in Viode et al(44)).The detailed description of the clinical characteristics of the full IMPACC cohort has been reported(40). These include TG1 (n=230) characterized by a mild respiratory disease and brief hospital stay with a largely uncomplicated hospital course, TG2 (n=272) generally required more respiratory support than TG1 and had a longer hospital stay but were discharged without limitations, TG3 (n=260 patients) was characterized by roughly similar respiratory support requirements and similar length of<span> </span>hospital stay as TG2 but generally had limitations at discharge, TG4 (n=199) generally received more aggressive respiratory support and generally experienced a prolonged hospital stay, and TG5 (n=98) characterized by high respiratory support requirements that progressed to mortality by day 28. For some analyses, TG4 was split into 2 sub-groups: TG4 survivors (TG4-S) and TG4 fatalities (TG4-F). TG4-F includes participants who eventually died within the study but only after the 28-day sampling period.</p>
<p> </p>
<p>Sample Preparation</p>
<p>Fifty microliters of neat plasma samples were diluted with 450 µL water and 25 µL of perchloric acid (70%) was added(44). After vigorous agitation, the suspension is kept at -20°C for 15 min. The suspension was centrifuged for 60 min (4°C, 3200 ×g) and the supernatant is kept. The supernatant was mixed with 40 µL of 1% trifluoroacetic acid and loaded onto a µSPE HLB plate (Waters, catalog #186001828BA), pre-conditioned with 300 µL methanol and twice with 500 µL of 0.1% trifluoroacetic acid. Proteins were eluted from the µSPE HLB plate with 100µL 90% acetonitrile 0.1% trifluoroacetic acid. After elution, the samples were dried using a Speedvac. The samples were resuspended with 35µL of 50 mM ammonium bicarbonate and digested with 10µL trypsin (Promega, catalog #V5280, 500 ng) overnight at 37°C. Digestion was stopped by the addition of 5µL 10% formic acid. The samples were stored at -80°C before LC/MS analysis.</p>
<p> </p>
<p>Sample MS Data Acquisition</p>
<p>Two microliters of tryptic peptides were loaded onto Evotip and analyzed using an EVOSEP one Liquid Chromatography (EVOSEP) connected to a TIMSTOF Pro (Bruker). The EVOSEP one method was the 60 sample per day (21 min gradient) and the mass spectrometer was operated in DDA-PASEF mode. 4 PASEF MS/MS scans were triggered per cycle. DDA-PASEF parameters were set as follows: m/z range 100-1700, mobility (1/K0) range was set to 0.70-1.45 V.s/cm2, the accumulation and ramp time were 100ms. Target intensity per individual PASEF precursor was set to 5000. The values for mobility-dependent collision energy ramping were set to 51eV at an inversed reduced mobility (1/K0) of 1.45 V.s/cm2 and 21eV at 0.7 V.s/cm2. Collision energies were linearly interpolated between these two 1/K0 values.</p>
<p> </p>
<p>Sample Search</p>
<p>The method used for protein identification and quantification is described in van Zalm et al(41). In brief, data were copied to a high-performance computing (HPC) system (https://www.mghpcc.org) for which we wrote a parallelization strategy to facilitate the identification and quantification of proteins in such large LC/MS dataset(41) using MSFragger(94). This parallelization strategy allowed for data analysis, including match between runs, in less than 2 weeks of computing time.<span> </span>The Uniprot human protein sequences without isoforms were combined with the protein sequences of the SARS-CoV-2 virus into a single FASTA file downloaded on March 27th, 2021. Methionine oxidation and protein N-term acetylation were set as variable modifications; no fixed modifications were specified. A maximum of three modifications was allowed during the peptide spectrum matching. A 1% false discovery rate was applied using the Philosopher toolkit(95). IonQuant(96) was used for quantification, which uses MS1 spectra to determine the relative quantification between samples. At least one ion was required for protein quantification.</p>
<p> </p>
<p>Statistical Analysis</p>
<p>Statistical analysis was performed using R studio. Protein intensities were normalized using VSN(97) and log2 transformed for further analysis. ClusterProfiler(49) was used for the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and ReactomePA(98) for Reactome. The heatmap in Figure 3 was done using ComplexHeatmap(99).</p>
<p>To identify longitudinal associations, presented in Figure 4, we tested if proteins kinetics during hospitalization were different across the TGs via a generalized additive model with mixed effects (gamm4 v0.2.6) while controlling for sex and age. Proteins for which the average (intercept in the gamm4 documentation) or shape (smoothing term in the gamm4 documentation) differed between the TGs at FDR<5% were considered significant dysregulated (detailed description in (100)).</p>
<p>Results from Figure 5 were visualized using ClusterProfiler(49): after a paired t-test and Benjamini Hochberg correction, the significant proteins for each trajectory group were submitted to the CompareCluster function of the ClusterProfiler tool.<span> </span></p>
<p>For the discovery of the prognostic biomarker panels analysis, missing values were imputed protein-wise with half the minimum value for each protein. Data were split between a training and a test cohort. This splitting met the FDA-definition of independence the two cohorts featured samples from two independent sets of hospitals. The samples from the training cohort were collected: University of Arizona (UA)-Tucson, Baylor, Brigham and Women's Hospital (BWH) Boston, Case Western, University of Oklahoma Health Sciences Center (OUHSC), University of California, Los Angeles (UCLA), and Yale. The samples from the test cohort were collected at: Drexel/Tower Health, Emory, University of Florida (UF), Icahn School of Medicine at Mount Sinai (ISMMS), Oregon Health & Science University (OHSU), Stanford, University of California, San Francisco (UCSF), and The University of Texas (UT) Austin.</p>
<p>A Mann-Whitney test was performed, only on the training cohort, between the 2 conditions, i.e., Death vs. Survival or ECMO/invasive mechanical ventilation Yes vs. No. The 20 most significant proteins were further evaluated by performing a stepwise selection applying the Akaike Information Criteria (AIC)(101) to find the best prognostic biomarker panel. Only significant proteins were selected (Supplementary Figure 2). For ROC analysis and AUROC calculation, pROC(102) was used.</p>
<p> </p>
<p> </p>
<p> </p>
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Author Under Sail The Imagination of Jack London, 1893-1902
No full textIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Intro -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- 1. Spirit Truth -- 2. From Absorption to Theatricality and Back Again -- 3. "I Will Build a New Present" -- 4. Sons as Authors -- 5. Fathers as Publishers -- 6. The Daughter as Author -- 7. Lovers as Authors -- 8. At Sea with the Family -- 9. Yellow News, Yellow Stories -- 10. The Return Home -- Notes -- Bibliography -- Index -- About Jay WilliamsIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Description based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
- …
