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                  <text>Coronavirus</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>Automated Assessment and Tracking of COVID-19 Pulmonary Disease Severity on Chest Radiographs using Convolutional Siamese Neural Networks.</text>
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                <text>Min Lang, Brent P Little, M D Li, F Deng, K Chang, J Kalpathy-Cramer, D P Mendoza, Nishanth Thumbavanam Arun, Mishka Gidwani, Susanna I Lee, Aileen O'Shea, Anushri Parakh, Praveer Singh</text>
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                <text>To develop an automated measure of COVID-19 pulmonary disease severity on chest radiographs (CXRs), for longitudinal disease tracking and outcome prediction. A convolutional Siamese neural network-based algorithm was trained to output a measure of pulmonary disease severity on CXRs (pulmonary x-ray severity (PXS) score), using weakly-supervised pretraining on ∼160,000 anterior-posterior images from CheXpert and transfer learning on 314 frontal CXRs from COVID-19 patients. The algorithm was evaluated on internal and external test sets from different hospitals (154 and 113 CXRs respectively). PXS scores were correlated with radiographic severity scores independently assigned by two thoracic radiologists and one in-training radiologist (Pearson r). For 92 internal test set patients with follow-up CXRs, PXS score change was compared to radiologist assessments of change (Spearman ρ). The association between PXS score and subsequent intubation or death was assessed. Bootstrap 95% confidence intervals (CI) were calculated. PXS scores correlated with radiographic pulmonary disease severity scores assigned to CXRs in the internal and external test sets (r=0.86 (95%CI 0.80-0.90) and r=0.86 (95%CI 0.79-0.90) respectively). The direction of change in PXS score in follow-up CXRs agreed with radiologist assessment (ρ=0.74 (95%CI 0.63-0.81)). In patients not intubated on the admission CXR, the PXS score predicted subsequent intubation or death within three days of hospital admission (area under the receiver operating characteristic curve=0.80 (95%CI 0.75-0.85)). A Siamese neural network-based severity score automatically measures radiographic COVID-19 pulmonary disease severity, which can be used to track disease change and predict subsequent intubation or death.</text>
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                <text>2020</text>
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                <text>10.1148/ryai.2020200079</text>
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                <text>Radiology. Artificial intelligence</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>COVID-19-associated autoimmunity as a feature of acute respiratory failure.</text>
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                <text>Marvin J Fritzler, Uriel Trahtemberg</text>
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                <text>2021</text>
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                <text>10.1007/s00134-021-06408-z</text>
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                <text>Intensive care medicine</text>
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                  <text>Coronavirus</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>Critical analysis of acute kidney injury in pediatric COVID-19 patients in the intensive care unit.</text>
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            <description>An entity primarily responsible for making the resource</description>
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                <text>Rupesh Raina, Ronith Chakraborty, Isabelle Mawby, Nirav Agarwal, Sidharth Sethi, Michael Forbes</text>
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                <text>COVID-19 is responsible for the 2019 novel coronavirus disease pandemic. Despite the vast research about the adult population, there has been little data collected on acute kidney injury (AKI) epidemiology, associated risk factors, treatments, and mortality in pediatric COVID-19 patients admitted to the ICU. AKI is a severe complication of COVID-19 among children and adolescents. A comprehensive literature search was conducted in PubMed/MEDLINE and Cochrane Center Trials to find all published literature related to AKI in COVID-19 patients, including incidence and outcomes. Twenty-four studies reporting the outcomes of interest were included. Across all studies, the overall sample size of COVID positive children was 1,247 and the median age of this population was 9.1 years old. Among COVID positive pediatric patients, there was an AKI incidence of 30.51%, with only 0.56% of these patients receiving KRT. The mortality was 2.55% among all COVID positive pediatric patients. The incidence of multisystem inflammatory syndrome in children (MIS-C) among COVID positive patients was 74.29%. AKI has shown to be a negative prognostic factor in adult patients with COVID-19 and now also in the pediatric cohort with high incidence and mortality rates. Additionally, our findings show a strong comparison in epidemiology between adult and pediatric COVID-19 patients; however, they need to be confirmed with additional data and studies.</text>
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                <text>2021</text>
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                <text>covid-19, acute kidney injury, Adult, kidney replacement therapy, pediatric, MIS-C</text>
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                <text>10.1007/s00467-021-05084-x</text>
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            <description>A related resource from which the described resource is derived</description>
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                <text>Pediatric nephrology (Berlin, Germany)</text>
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                  <text>Coronavirus</text>
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              <description>An account of the resource</description>
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                  <text>Dominio científico: Coronavirus</text>
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            <description>A name given to the resource</description>
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                <text>Selective and electronic detection of COVID-19 (Coronavirus) using carbon nanotube field effect transistor-based biosensor: A proof-of-concept study.</text>
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                <text>M Thanihaichelvan, S N Surendran, T Kumanan, U Sutharsini, P Ravirajan, R Valluvan, T Tharsika</text>
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                <text>In this work, we propose and demonstrate a carbon nanotube (CNT) field-effect transistor (FET) based biosensor for selective detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). CNT FETs were fabricated on a flexible Kapton substrate and the sensor was fabricated by immobilizing the reverse sequence of the 25-base portion of the RNA-dependent RNA polymerase gene of the SARS-CoV-2 onto the CNT channel. The biosensors were tested for the synthetic positive and control target sequences. The biosensor showed a selective sensing response to the positive target sequence with a limit of detection of 10 fM. The promising results from our study suggest that the CNT FET based biosensors can be used as a diagnostic tool for the detection of SARS-CoV-2.</text>
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                <text>2021</text>
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                <text>covid-19, SARS-CoV-2, biosensor, rapid detection, Coronavirus, Carbon nanotube Field-effect transistor</text>
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                <text>10.1016/j.matpr.2021.05.011</text>
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                <text>Materials today. Proceedings</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>Impact of COVID-19 on the outcomes of gastrointestinal surgery.</text>
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                <text>Rahul Gupta, Jyoti Gupta, Houssem Ammar</text>
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                <text>COVID-19 pandemic has brought a paradigm shift in the treatment of various surgical gastrointestinal disorders. Given the increasing number of patients requiring hospitalization and intensive care for SARS-CoV-2 infections, various surgical departments worldwide were forced to stop or postpone elective surgeries to save the health resources for COVID-19 patients. Since the declaration of the COVID-19 pandemic by the World Health Organization on 12th March 2020, the recommendations from the surgical societies kept evolving to help the surgeons in making informed decisions regarding patient care. Moreover, various socio-economic and epidemiological factors have come into play while deciding the optimal approach towards patients requiring gastrointestinal surgery. Surgeries for many abdominal diseases such as acute appendicitis and acute calculous cholecystitis were postponed. Elective surgeries were triaged based on the urgency of performing the surgical procedure, the hospital burden of COVID-19 patients, and the availability of healthcare resources. Various measures were adopted such as preoperative screening for SARS-CoV-2 infection, use of personal protective equipment, and the COVID-19-free surgical pathway to prevent perioperative SARS-CoV-2 transmission. In this article, we have reviewed the recent studies reporting the outcomes of various gastrointestinal surgeries in the COVID-19 pandemic era and the recommendations from various surgical societies on the safety precautions to be followed during gastrointestinal surgery.</text>
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                <text>2021</text>
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                <text>covid-19, SARS-CoV-2, bariatric surgery, liver transplant, colorectal cancer</text>
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                <text>10.1007/s12328-021-01424-4</text>
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                <text>Clinical journal of gastroenterology</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>Regional differences in the impact of the COVID-19 pandemic on food sufficiency in California, April-July 2020: implications for food programmes and policies.</text>
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                <text>To evaluate regional differences in factors associated with food insufficiency during the initial months of the COVID-19 pandemic among three major metropolitan regions in California, a state with historically low participation rates in the Supplementation Nutrition Assistance Program, the nation's largest food assistance programme. Analysis of cross-sectional data from phase 1 (23 April-21 July 2020) of the US Census Household Pulse Survey, a weekly national online survey. California, and three Californian metropolitan statistical areas (MSA), including San Francisco-Oakland-Berkeley, Los Angeles-Long Beach-Anaheim and Riverside-San Bernardino-Ontario MSA. Adults aged 18 years and older living in households. Among the three metropolitan areas, food insufficiency rates were lowest in the San Francisco-Oakland-Berkeley MSA. Measures of disadvantage (e.g., having low-income, being unemployed, recent loss of employment income and pre-pandemic food insufficiency) were widely associated with household food insufficiency. However, disadvantaged households in the San Francisco Bay Area, the area with the lowest poverty and unemployment rates, were more likely to be food insufficient compared with those in the Los Angeles-Long Beach-Anaheim and Riverside-San Bernardino-Ontario MSA. Food insufficiency risk among disadvantaged households differed by region. To be effective, governmental response to food insufficiency must address the varied local circumstances that contribute to these disparities.</text>
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                <text>2021</text>
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                <text>covid-19, health disparities, food policy, Food Insufficiency</text>
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                <text>10.1017/S1368980021001889</text>
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                <text>Public health nutrition</text>
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              <name>Title</name>
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              <description>An account of the resource</description>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>No country or continent is on its own in the ongoing COVID-19 pandemic.</text>
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                <text>Kari Johansen, Hanna Nohynek</text>
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                <text>2021</text>
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                <text>Vaccination, COVID-19 vaccines, equity, evidence-based decision-making</text>
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                <text>10.2807/1560-7917.ES.2021.26.17.2100430</text>
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            <description>A related resource from which the described resource is derived</description>
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                <text>Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin</text>
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                  <text>Dominio científico: Coronavirus</text>
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            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>Socioeconomic Factors Associated With an Intention to Work While Sick From COVID-19.</text>
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            <name>Creator</name>
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                <text>Carla Tilchin, Lauren Dayton, Carl A Latkin</text>
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            <name>Description</name>
            <description>An account of the resource</description>
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                <text>We sought to understand barriers to staying home from work when sick from COVID-19 (COVID-19 presenteeism) to understand COVID-19 health disparities and transmission and guide workplace and social policy. We used logistic regression models to assess which socioeconomic factors were associated with intended COVID-19 presenteeism among an online study population working outside their home in March 2020 (N = 220). Overall, 34.5% of participants reported intended COVID-19 presenteeism. Younger individuals and individuals making over $90,000 per year were less likely to report COVID-19 presenteeism. Individuals who were worried about having enough food had 3-fold higher odds of intended COVID-19 presenteeism. Current policies around food access, paid sick leave, and other workplace protections need to be expanded and made more accessible to reduce health disparities as well as the transmission of COVID-19 and other infections.</text>
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                <text>2021</text>
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            <name>Identifier</name>
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                <text>10.1097/JOM.0000000000002147</text>
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            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="79990">
                <text>Journal of occupational and environmental medicine</text>
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  <item itemId="9598" public="1" featured="0">
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              <name>Title</name>
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                  <text>Coronavirus</text>
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              <name>Description</name>
              <description>An account of the resource</description>
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                <elementText elementTextId="2">
                  <text>Dominio científico: Coronavirus</text>
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      <name>Text</name>
      <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
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        <name>Dublin Core</name>
        <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
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          <element elementId="50">
            <name>Title</name>
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                <text>Pharmaceutical Aspects and Clinical Evaluation of COVID-19 Vaccines.</text>
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            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
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              <elementText elementTextId="79992">
                <text>Kirk Hofman, Gautam N Shenoy, Vincent Chak, Sathy V Balu-Iyer</text>
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          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
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              <elementText elementTextId="79993">
                <text>COVID-19, the disease caused by the novel severe acute respiratory syndrome-associated coronavirus 2 (SARS-CoV-2), was first detected in December 2019 and has since morphed into a global pandemic claiming over 2.4 million human lives and severely impacting global economy. The race for a safe and efficacious vaccine was thus initiated with government agencies as well as major pharmaceutical companies as frontrunners. An ideal vaccine would activate multiple arms of the adaptive immune system to generate cytotoxic T cell responses as well as neutralizing antibody responses, while avoiding pathological or deleterious immune responses that result in tissue damage or exacerbation of the disease. Developing an effective vaccine requires an inter-disciplinary effort involving virology, protein biology, biotechnology, immunology and pharmaceutical sciences. In this review, we provide a brief overview of the pathology and immune responses to SARS-CoV-2, which are fundamental to vaccine development. We then summarize the rationale for developing COVID-19 vaccines and provide novel insights into vaccine development from a pharmaceutical science perspective, such as selection of different antigens, adjuvants, delivery platforms and formulations. Finally, we review multiple clinical trial outcomes of novel vaccines in terms of safety and efficacy.</text>
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              <elementText elementTextId="79994">
                <text>2021</text>
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            <name>Subject</name>
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                <text>vaccine, covid-19, Clinical trial, SARS-CoV-2, Formulation</text>
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                <text>10.1080/08820139.2021.1904977</text>
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                <text>Immunological investigations</text>
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              <name>Title</name>
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              <description>An account of the resource</description>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>Neurological update: COVID-19.</text>
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                <text>Edward Needham, A L Ren, R J Digby</text>
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            <description>An account of the resource</description>
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                <text>Coronavirus Disease 2019 is predominantly a disorder of the respiratory system, but neurological complications have been recognised since early in the pandemic. The major pathophysiological processes leading to neurological damage in COVID-19 are cerebrovascular disease, immunologically mediated neurological disorders and the detrimental effects of critical illness on the nervous system. It is still unclear whether direct invasion of the nervous system by the Severe Acute Respiratory Syndrome Coronavirus 2 occurs; given the vast numbers of people infected at this point, this uncertainty suggests that nervous system infection is unlikely to represent a significant issue if it occurs at all. In this review, we explore what has been learnt about the neurological complications of COVID-19 over the course of the pandemic, and by which mechanisms these complications most commonly occur.</text>
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                <text>2021</text>
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                <text>covid-19, Critical illness, neuroimmunology, Cerebrovascular disease</text>
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            <name>Identifier</name>
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                <text>10.1007/s00415-021-10581-y</text>
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              <elementText elementTextId="80004">
                <text>Journal of neurology</text>
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