9 results match your criteria: "Nacional Institute of Health[Affiliation]"

Article Synopsis
  • - The study focuses on improving the detection of familial hypercholesterolemia (FH), a common genetic disorder that is often underdiagnosed, which could help prevent heart-related issues linked to it.
  • - Researchers used machine learning algorithms on data from the UK Biobank to identify individuals with FH-causing genetic variants, comparing the performance of these algorithms against existing clinical diagnostic criteria.
  • - The findings showed that their machine learning model outperformed traditional diagnostic methods in identifying FH, with better sensitivity and accuracy, and reduced the number of individuals needed to be screened to find a case of FH.
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Objectives: This paper evaluates 16 year results of the Allergy EQA program shared by EQA organisers in Belgium, Finland, Portugal, and The Netherlands.

Methods: The performance of Thermo Fisher and Siemens user groups (in terms of concordance between both groups, between laboratory CV, prevalence of clinically significant errors) and suitability of samples (stability and validity of dilution of patient samples) are evaluated using data of 192 samples in the EQA programs from 2007 to 2022. Measurands covered are total IgE, screens and mixes, specific IgE extracts and allergen components.

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Introduction: the risk of a worker becoming ill due to coronavirus disease 2019 (COVID-19) is related to occupational exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Due to the need to restore work activities in Mozambique, the study was conducted with the aim of identifying the occupational categories most affected by COVID-19 in the former in the period from March to July 2020.

Methods: this is a cross-sectional descriptive study, in which data from professions of confirmed cases of COVID-19 from 22 March to 29 July 2020 in Mozambique were analyzed.

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The Clinical Genome Resource (ClinGen) Familial Hypercholesterolemia Variant Curation Expert Panel consensus guidelines for LDLR variant classification.

Genet Med

February 2022

Department of Health Promotion and Prevention of Noncommunicable Diseases, Nacional Institute of Health Dr. Ricardo Jorge, Lisbon, Portugal; BioISI - BioSystems & Integrative Sciences Institute, Department of Chemistry and Biochemistry, Faculty of Sciences, University of Lisbon, Lisbon, Portugal. Electronic address:

Purpose: In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published consensus standardized guidelines for sequence-level variant classification in Mendelian disorders. To increase accuracy and consistency, the Clinical Genome Resource Familial Hypercholesterolemia (FH) Variant Curation Expert Panel was tasked with optimizing the existing ACMG/AMP framework for disease-specific classification in FH. In this study, we provide consensus recommendations for the most common FH-associated gene, LDLR, where >2300 unique FH-associated variants have been identified.

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ECMM CandiReg-A ready to use platform for outbreaks and epidemiological studies.

Mycoses

October 2019

Faculty of Medicine, Department I of Internal Medicine, Center for Integrated Oncology Aachen Bonn Cologne Dusseldorf (CIO ABCD), Excellence Center for Medical Mycology (ECMM), University of Cologne, Cologne, Germany.

Background: Recent outbreaks of Candida auris further exemplify that invasive Candida infections are a substantial threat to patients and healthcare systems. Even short treatment delays are associated with higher mortality rates. Epidemiological shifts towards more resistant Candida spp.

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The diversity of fungal species comprising the lung mycobiome is a reflection of exposure to environmental and endogenous filamentous fungi and yeasts. Most lung mycobiome studies have been culture-based. A few have utilized next generation sequencing (NGS).

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Aspergillus spp. have a high nutritional versatility and good growth on a large variety of construction materials. They also colonize soil or food, but decaying vegetation is their primary ecological niche.

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Molecular identification of clinical and environmental avian Aspergillus isolates.

Arch Microbiol

March 2019

Department of Medicine and Epidemiology, School of Veterinary Medicine, University of California, Davis, CA, USA.

Aspergillosis causes high morbidity and mortality in avian species. The main goal of this study was to use molecular techniques to identify Aspergillus species collected from different avian species with aspergillosis. A subsample of those isolates was also screened for resistance to itraconazole.

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Aspergillus is among a growing list of allergens that aggravate asthmatic responses. Significant pulmonary pathology is associated with Aspergillus-induced allergic and asthmatic lung disease. Environments with high levels of exposure to fungi are found in animal production facilities such as for swine and poultry, and farmers working with these are at increased risk for occupational respiratory diseases.

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