71 research outputs found

    Short Lag Times for Invasive Tropical Plants: Evidence from Experimental Plantings in Hawai'i

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    Background: The lag time of an invasion is the delay between arrival of an introduced species and its successful spread in a new area. To date, most estimates of lag times for plants have been indirect or anecdotal, and these estimates suggest that plant invasions are often characterized by lag times of 50 years or more. No general estimates are available of lag times for tropical plant invasions. Historical plantings and documentation were used to directly estimate lag times for tropical plant invasions in Hawai’i. Methodology/Principal Findings: Historical planting records for the Lyon Arboretum dating back to 1920 were examined to identify plants that have since become invasive pests in the Hawaiian Islands. Annual reports describing escape from plantings were then used to determine the lag times between initial plantings and earliest recorded spread of the successful invaders. Among 23 species that eventually became invasive pests, the average lag time between introduction and first evidence of spread was 14 years for woody plants and 5 years for herbaceous plants. Conclusions/Significance: These direct estimates of lag times are as much as an order of magnitude shorter than previous, indirect estimates, which were mainly based on temperate plants. Tropical invaders may have much shorter lag times than temperate species. A lack of direct and deliberate observations may have also inflated many previous lag time estimates. Although there have been documented cases of long lag times due to delayed arrival of a mutualist or environmenta

    Oxidative protein labeling in mass-spectrometry-based proteomics

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    Oxidation of proteins and peptides is a common phenomenon, and can be employed as a labeling technique for mass-spectrometry-based proteomics. Nonspecific oxidative labeling methods can modify almost any amino acid residue in a protein or only surface-exposed regions. Specific agents may label reactive functional groups in amino acids, primarily cysteine, methionine, tyrosine, and tryptophan. Nonspecific radical intermediates (reactive oxygen, nitrogen, or halogen species) can be produced by chemical, photochemical, electrochemical, or enzymatic methods. More targeted oxidation can be achieved by chemical reagents but also by direct electrochemical oxidation, which opens the way to instrumental labeling methods. Oxidative labeling of amino acids in the context of liquid chromatography(LC)–mass spectrometry (MS) based proteomics allows for differential LC separation, improved MS ionization, and label-specific fragmentation and detection. Oxidation of proteins can create new reactive groups which are useful for secondary, more conventional derivatization reactions with, e.g., fluorescent labels. This review summarizes reactions of oxidizing agents with peptides and proteins, the corresponding methodologies and instrumentation, and the major, innovative applications of oxidative protein labeling described in selected literature from the last decade

    Procalcitonin Is Not a Reliable Biomarker of Bacterial Coinfection in People With Coronavirus Disease 2019 Undergoing Microbiological Investigation at the Time of Hospital Admission

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    Admission procalcitonin measurements and microbiology results were available for 1040 hospitalized adults with coronavirus disease 2019 (from 48 902 included in the International Severe Acute Respiratory and Emerging Infections Consortium World Health Organization Clinical Characterisation Protocol UK study). Although procalcitonin was higher in bacterial coinfection, this was neither clinically significant (median [IQR], 0.33 [0.11–1.70] ng/mL vs 0.24 [0.10–0.90] ng/mL) nor diagnostically useful (area under the receiver operating characteristic curve, 0.56 [95% confidence interval, .51–.60])

    The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

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    We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC

    The effect of microbial challenge on the intestinal proteome of broiler chickens

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    Background: In poultry production intestinal health and function is paramount to achieving efficient feed utilisation and growth. Uncovering the localised molecular mechanisms that occur during the early and important periods of growth that allow birds to grow optimally is important for this species. The exposure of young chicks to used litter from older flocks, containing mixed microbial populations, is a widely utilised model in poultry research. It rarely causes mortality but effects an immunogenic stimulation sufficient enough to cause reduced and uneven growth that is reflective of a challenging growing environment. Methods: A mixed microbial challenge was delivered as used litter containing Campylobacter jejuni and coccidial oocysts to 120 male Ross 308 broiler chicks, randomly divided into two groups: control and challenged. On day 12, 15, 18 and 22 (pre- and 3, 6 and 10 days post-addition of the used litter) the proximal jejunum was recovered from 6 replicates per group and differentially abundant proteins identified between groups and over time using 2D DiGE. Results: The abundance of cytoskeletal proteins of the chicken small intestinal proteome, particularly actin and actin associated proteins, increased over time in both challenged and control birds. Villin-1, an actin associated anti-apoptotic protein, was reduced in abundance in the challenged birds indicating that many of the changes in cytoskeletal protein abundance in the challenged birds were as a result of an increased rate of apoptosis. A number of heat shock proteins decreased in abundance over time in the intestine and this was more pronounced in the challenged birds. Conclusions: The small intestinal proteome sampled from 12 to 22 days of age showed considerable developmental change, comparable to other species indicating that many of the changes in protein abundance in the small intestine are conserved among vertebrates. Identifying and distinguishing the changes in proteins abundance and molecular pathways that occur as a result of normal growth from those that occur as a result of a challenging microbial environment is important in this major food producing animal

    Co-infections, secondary infections, and antimicrobial use in patients hospitalised with COVID-19 during the first pandemic wave from the ISARIC WHO CCP-UK study: a multicentre, prospective cohort study

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    Background: Microbiological characterisation of co-infections and secondary infections in patients with COVID-19 is lacking, and antimicrobial use is high. We aimed to describe microbiologically confirmed co-infections and secondary infections, and antimicrobial use, in patients admitted to hospital with COVID-19. Methods: The International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study is an ongoing, prospective cohort study recruiting inpatients from 260 hospitals in England, Scotland, and Wales, conducted by the ISARIC Coronavirus Clinical Characterisation Consortium. Patients with a confirmed or clinician-defined high likelihood of SARS-CoV-2 infection were eligible for inclusion in the ISARIC WHO CCP-UK study. For this specific study, we excluded patients with a recorded negative SARS-CoV-2 test result and those without a recorded outcome at 28 days after admission. Demographic, clinical, laboratory, therapeutic, and outcome data were collected using a prespecified case report form. Organisms considered clinically insignificant were excluded. Findings: We analysed data from 48 902 patients admitted to hospital between Feb 6 and June 8, 2020. The median patient age was 74 years (IQR 59–84) and 20 786 (42·6%) of 48 765 patients were female. Microbiological investigations were recorded for 8649 (17·7%) of 48 902 patients, with clinically significant COVID-19-related respiratory or bloodstream culture results recorded for 1107 patients. 762 (70·6%) of 1080 infections were secondary, occurring more than 2 days after hospital admission. Staphylococcus aureus and Haemophilus influenzae were the most common pathogens causing respiratory co-infections (diagnosed ≤2 days after admission), with Enterobacteriaceae and S aureus most common in secondary respiratory infections. Bloodstream infections were most frequently caused by Escherichia coli and S aureus. Among patients with available data, 13 390 (37·0%) of 36 145 had received antimicrobials in the community for this illness episode before hospital admission and 39 258 (85·2%) of 46 061 patients with inpatient antimicrobial data received one or more antimicrobials at some point during their admission (highest for patients in critical care). We identified frequent use of broad-spectrum agents and use of carbapenems rather than carbapenem-sparing alternatives. Interpretation: In patients admitted to hospital with COVID-19, microbiologically confirmed bacterial infections are rare, and more likely to be secondary infections. Gram-negative organisms and S aureus are the predominant pathogens. The frequency and nature of antimicrobial use are concerning, but tractable targets for stewardship interventions exist. Funding: National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, UK Department for International Development, Bill & Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, and NIHR HPRU in Respiratory Infections at Imperial College London

    Co-infections, secondary infections, and antimicrobial use in patients hospitalised with COVID-19 during the first pandemic wave from the ISARIC WHO CCP-UK study: a multicentre, prospective cohort study

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    Background: Microbiological characterisation of co-infections and secondary infections in patients with COVID-19 is lacking, and antimicrobial use is high. We aimed to describe microbiologically confirmed co-infections and secondary infections, and antimicrobial use, in patients admitted to hospital with COVID-19. Methods: The International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study is an ongoing, prospective cohort study recruiting inpatients from 260 hospitals in England, Scotland, and Wales, conducted by the ISARIC Coronavirus Clinical Characterisation Consortium. Patients with a confirmed or clinician-defined high likelihood of SARS-CoV-2 infection were eligible for inclusion in the ISARIC WHO CCP-UK study. For this specific study, we excluded patients with a recorded negative SARS-CoV-2 test result and those without a recorded outcome at 28 days after admission. Demographic, clinical, laboratory, therapeutic, and outcome data were collected using a prespecified case report form. Organisms considered clinically insignificant were excluded. Findings: We analysed data from 48 902 patients admitted to hospital between Feb 6 and June 8, 2020. The median patient age was 74 years (IQR 59–84) and 20 786 (42·6%) of 48 765 patients were female. Microbiological investigations were recorded for 8649 (17·7%) of 48 902 patients, with clinically significant COVID-19-related respiratory or bloodstream culture results recorded for 1107 patients. 762 (70·6%) of 1080 infections were secondary, occurring more than 2 days after hospital admission. Staphylococcus aureus and Haemophilus influenzae were the most common pathogens causing respiratory co-infections (diagnosed ≤2 days after admission), with Enterobacteriaceae and S aureus most common in secondary respiratory infections. Bloodstream infections were most frequently caused by Escherichia coli and S aureus. Among patients with available data, 13 390 (37·0%) of 36 145 had received antimicrobials in the community for this illness episode before hospital admission and 39 258 (85·2%) of 46 061 patients with inpatient antimicrobial data received one or more antimicrobials at some point during their admission (highest for patients in critical care). We identified frequent use of broad-spectrum agents and use of carbapenems rather than carbapenem-sparing alternatives. Interpretation: In patients admitted to hospital with COVID-19, microbiologically confirmed bacterial infections are rare, and more likely to be secondary infections. Gram-negative organisms and S aureus are the predominant pathogens. The frequency and nature of antimicrobial use are concerning, but tractable targets for stewardship interventions exist. Funding: National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, UK Department for International Development, Bill & Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, and NIHR HPRU in Respiratory Infections at Imperial College London

    Non-steroidal anti-inflammatory drug use and outcomes of COVID-19 in the ISARIC Clinical Characterisation Protocol UK cohort: a matched, prospective cohort study.

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    Background: Early in the pandemic it was suggested that pre-existing use of non-steroidal anti-inflammatory drugs (NSAIDs) could lead to increased disease severity in patients with COVID-19. NSAIDs are an important analgesic, particularly in those with rheumatological disease, and are widely available to the general public without prescription. Evidence from community studies, administrative data, and small studies of hospitalised patients suggest NSAIDs are not associated with poorer COVID-19 outcomes. We aimed to characterise the safety of NSAIDs and identify whether pre-existing NSAID use was associated with increased severity of COVID-19 disease. Methods: This prospective, multicentre cohort study included patients of any age admitted to hospital with a confirmed or highly suspected SARS-CoV-2 infection leading to COVID-19 between Jan 17 and Aug 10, 2020. The primary outcome was in-hospital mortality, and secondary outcomes were disease severity at presentation, admission to critical care, receipt of invasive ventilation, receipt of non-invasive ventilation, use of supplementary oxygen, and acute kidney injury. NSAID use was required to be within the 2 weeks before hospital admission. We used logistic regression to estimate the effects of NSAIDs and adjust for confounding variables. We used propensity score matching to further estimate effects of NSAIDS while accounting for covariate differences in populations. Results: Between Jan 17 and Aug 10, 2020, we enrolled 78 674 patients across 255 health-care facilities in England, Scotland, and Wales. 72 179 patients had death outcomes available for matching; 40 406 (56·2%) of 71 915 were men, 31 509 (43·8%) were women. In this cohort, 4211 (5·8%) patients were recorded as taking systemic NSAIDs before admission to hospital. Following propensity score matching, balanced groups of NSAIDs users and NSAIDs non-users were obtained (4205 patients in each group). At hospital admission, we observed no significant differences in severity between exposure groups. After adjusting for explanatory variables, NSAID use was not associated with worse in-hospital mortality (matched OR 0·95, 95% CI 0·84–1·07; p=0·35), critical care admission (1·01, 0·87–1·17; p=0·89), requirement for invasive ventilation (0·96, 0·80–1·17; p=0·69), requirement for non-invasive ventilation (1·12, 0·96–1·32; p=0·14), requirement for oxygen (1·00, 0·89–1·12; p=0·97), or occurrence of acute kidney injury (1·08, 0·92–1·26; p=0·33). Interpretation: NSAID use is not associated with higher mortality or increased severity of COVID-19. Policy makers should consider reviewing issued advice around NSAID prescribing and COVID-19 severity. Funding: National Institute for Health Research and Medical Research Council

    Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study

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    Background Prognostic models to predict the risk of clinical deterioration in acute COVID-19 cases are urgently required to inform clinical management decisions. Methods We developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) among consecutively hospitalised adults with highly suspected or confirmed COVID-19 who were prospectively recruited to the International Severe Acute Respiratory and Emerging Infections Consortium Coronavirus Clinical Characterisation Consortium (ISARIC4C) study across 260 hospitals in England, Scotland, and Wales. Candidate predictors that were specified a priori were considered for inclusion in the model on the basis of previous prognostic scores and emerging literature describing routinely measured biomarkers associated with COVID-19 prognosis. We used internal–external cross-validation to evaluate discrimination, calibration, and clinical utility across eight National Health Service (NHS) regions in the development cohort. We further validated the final model in held-out data from an additional NHS region (London). Findings 74 944 participants (recruited between Feb 6 and Aug 26, 2020) were included, of whom 31 924 (43·2%) of 73 948 with available outcomes met the composite clinical deterioration outcome. In internal–external cross-validation in the development cohort of 66 705 participants, the selected model (comprising 11 predictors routinely measured at the point of hospital admission) showed consistent discrimination, calibration, and clinical utility across all eight NHS regions. In held-out data from London (n=8239), the model showed a similarly consistent performance (C-statistic 0·77 [95% CI 0·76 to 0·78]; calibration-in-the-large 0·00 [–0·05 to 0·05]); calibration slope 0·96 [0·91 to 1·01]), and greater net benefit than any other reproducible prognostic model. Interpretation The 4C Deterioration model has strong potential for clinical utility and generalisability to predict clinical deterioration and inform decision making among adults hospitalised with COVID-19
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