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3,788 results for “indices”
Gigantic genomes of salamanders indicate body temperature, not genome size, is the driver of global methylation and 5-methylcytosine deamination in vertebrates
<p>Transposable elements (TEs) are sequences that replicate and move throughout genomes, and they can be silenced through methylation of cytosines at CpG dinucelotides. TE abundance contributes to genome size, but TE silencing variation across genomes of different sizes remains underexplored. Salamanders include most of the largest C-values -- 9 to 120 Gb. We measured CpG methylation levels in salamanders with genomes ranging from 2N = ~58 Gb to 4N = ~116 Gb. We compared these levels to results from endo- and ectothermic vertebrates with more typical genomes. Salamander methylation levels are ~90%, higher than all endotherms. However, salamander methylation does not differ from other ectotherms, despite a ~100-fold difference in nuclear DNA content. Because methylation affects the nucleotide compositional landscape through 5-methylcytosine deamination to thymine, we quantified salamander CpG dinucleotide levels and compared them to other vertebrates. Salamanders and other ectotherms have comparable CpG levels, and ectotherm levels are higher than endotherms. These data show no shift in global methylation at the base of salamanders, despite a dramatic increase in TE load and genome size. This result is reconcilable with previous studies by considering endothermy and ectothermy, which may be more important drivers of methylation in vertebrates than genome size.</p>
Dataset_Scoping review_Changes in quality of cancer care assessed through performance indicators
<p>Data on which the conclusions of the study "<em>Changes in the quality of cancer care as assessed through performance indicators during the first wave of the COVID-19 pandemic in 2020: a Scoping Review</em>" rely, namely: articles included in the Scoping Review and performance indicators extracted and collated.</p>
Daily indices of heat at select U.S. military installations (1990 - 2019)
<p>R data files for annual indices of heat of 30 Continental U.S. (CONUS) U.S. military installations from 1990-2019.</p> <p>Daily indices were derived from hourly meteorological estimates from the North American Land Data Assimilation System 2 (NLDAS-2) forcing dataset served as the primary source of weather and atmospheric data. We extracted parameters from NLDAS grid cells containing the centroid of each installation based on shapefiles from the Department of Defense (DoD) Military Installations, Ranges, and Training Areas (MIRTA) Dataset. We calculated relative humidity from specific humidity, temperature, and atmospheric pressure; heat index (HI) from temperature and relative humidity based on a US National Weather Service algorithm; and outdoor WBGT from air temperature, relative humidity, solar irradiance, barometric pressure, and wind speed using the method of Liljegren <em>et al.</em></p> <p>`daily_indices.Rmd` (328402 observations of 18 variables) contains indices for daily maximum, mean, minimum, and 95th percentile values of temperature (deg F), heat index (deg F), and WBGT (deg C) with urban and non-urban inputs to the Liljegren model.</p> <p>`morning_indices.Rmd` (328364 observations of 5 variables) contains indices for daily 0600 hour (local time) values of temperature (deg F), heat index (deg F), and WBGT (deg C, urban model). </p>
The lower airways microbiota and antimicrobial peptides indicate dysbiosis in sarcoidosis
<p><span><strong>Rationale</strong>: </span><span>The role of the pulmonary microbiome in sarcoidosis is unknown.</span><br><br><span><strong>Objectives</strong>: </span><span>The objectives of the current study was to: 1) </span><span>Examine whether the pulmonary fungal and bacterial microbiota differed in patients with sarcoidosis compared with controls. 2) Examine whether there was an association between the microbiota and levels of the antimicrobial peptides (AMPs) in protected bronchoalveolar lavage (PBAL), indicating an interaction with the innate immune response.</span><br><br><span><strong>Methods</strong>: </span><span>35 sarcoidosis patients and 35 healthy controls underwent bronchoscopy and were sampled with oral wash (OW), protected BAL (PBAL) and left protected sterile brushes (LPSB). The fungal ITS1 region and the V3V4 region of the bacterial 16SrDNA gene were sequenced. Bioinformatic analyses were performed with QIIME 2. The AMPs secretory leucocyte protease inhibitor (SLPI) and human beta defensins 1 and 2 (hBD-1 & hBD-2), were measured in PBAL by enzyme linked immunosorbent assay (ELISA).</span><br><br><span><strong>Measurements and Main Results</strong>: </span><em><span>Aspergillus</span></em><span> dominated the PBAL samples in sarcoidosis. Differences in bacterial taxonomy were minor. There was no significant difference in fungal alpha diversity between sarcoidosis and controls, but the bacterial alpha diversity in sarcoidosis was significantly lower in OW (p=0.047) and PBAL (p=0.03) compared with controls. The beta diversity for sarcoidosis compared with controls differed for both fungi and bacteria. AMP levels were significantly lower in sarcoidosis compared to controls (SLPI & hBD-1: p<0.01). No significant correlations were found between </span><span>a</span><span>-diversity and AMPs.</span><br><br><span><strong>Conclusions</strong>: </span><span>The pulmonary fungal and bacterial microbiota in sarcoidosis differed from controls, with lower antimicrobial peptides levels in sarcoidosis.</span></p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Albania
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Institute of Food Safety and Veterinary</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Estonia
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Veterinary and Food Board</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Finland
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Finnish Food Authority</p>
European Union Summary Report on Antimicrobial Resistance in Zoonotic and Indicator Bacteria from Humans, Animals and Food in 2019/2020
<p>All tables produced for the European Union Summary Report on Antimicrobial Resistance in Zoonotic and Indicator Bacteria from Humans, Animals and Food in 2020:</p> <p>- Campylobacter</p> <p>- E. coli</p> <p>- MRSA</p> <p>- Salmonella</p> <p>- ESBL</p> <p>Annexes A to E are also included:</p> <p>Annexes A to E are also included.</p> <p>Annex A – Data reported on antimicrobial resistance in Salmonella <em>spp</em>.</p> <p>Annex B – Data reported on antimicrobial resistance in Campylobacter <em>spp</em>.</p> <p>Annex C – Data reported on AMR in indicator Escherichia coli from food-producing animals and derived meat</p> <p>Annex D – Data on presumptive ESBL-, AmpC- and/or carbapenemase-producing microorganisms and their resistance occurrence (routine and specific monitorings)</p> <p>Annex E – Data reported on antimicrobial resistance in MRSA from food-producing animals and derived meat</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Bulgaria
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Risk Assessment Center on Food Chain</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Greece
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Ministry of Rural Development and Food</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Germany
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Federal Institute for Risk Assessment</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Cyprus
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Ministry of Agriculture, Rural Development and Environment</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Spain
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Agencia Española de Consumo, Seguridad Alimentaria y Nutrición; Ministerio de Agricultura, Pesca y Alimentación</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Czechia
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: State Veterinary Administration</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Austria
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Austrian Agency for Health and Food Safety</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Luxembourg
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Administration des services vétérinaires</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Romania
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Institute of Hygiene and Veterinary Public Heath and Institute for Diagnosis and Animal Health</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Malta
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: Ministry for Agriculture, Fisheries and Animal Rights</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Lithuania
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: National Food and Veterinary Risk Assessment Institute</p>
Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2019/2020 – Belgium
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included.</p> <p>Reporting authorities contributing to 2020 AMR data collection: SCIENSANO</p>
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