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1,017 results for “Antimicrobial”
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 – Slovenia
<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, Forestry 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 – Denmark
<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 Institute - The Technical University of Denmark</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 – Latvia
<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: Assessment and Registration Agency of Food and Veterinary Service of Latvia</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 – Switzerland
<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 Food Safety and Veterinary Office</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 – Croatia
<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: Croatian Veterinary 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 – Portugal
<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: Instituto Nacional de Investigação Agrária e Veterinária</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 – Hungary
<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 Chain Safety Office</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 – Norway
<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: Norwegian Veterinary 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 – Slovakia
<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 and Food 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 – Ireland
<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: The Food Safety Authority of Ireland</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 – The United Kingdom
<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: Animal and Plant Health Agency</p>
Land use influences the composition and antimicrobial effects of propolis
<p>Honey bee propolis is a complex, resinous mixture created by bees using plant sources such as leaves, flowers, and bud exudates. This study characterized how cropland surrounding apiaries affects the chemical composition and antimicrobial effects of propolis. The chemical composition and compound abundance of the propolis samples were analyzed using Gas Chromatography-Mass Spectrometry (GC-MS) and the antimicrobial effects were analyzed using the 50% minimum inhibitory concentration (MIC<sub>50</sub>) assay against four relevant bee pathogens, <span class="html-italic">Serratia marcescens, Paenibacillus larvae, Lysinibacillus sphaericus,</span> and <span class="html-italic">Klebsiella pneumoniae</span>. Propolis composition varied significantly with apiary, and cropland coverage predicted mean sum abundance of compounds. The apiary with the highest cropland coverage exhibited significantly higher MIC<sub>50</sub> values for <span class="html-italic">S. marcescens</span> and <span class="html-italic">K. pneumoniae</span> compared to other apiaries. These results demonstrate that agricultural land use surrounding honey bee apiaries decreases the chemical quality and antimicrobial effects of propolis, which may have implications for the impacts of land use on hive immunity to potential pathogens.</p>
Genetic and transcriptomic datasets characterizing gene drive mosquitoes expressing antimicrobial peptides that retard Plasmodium sporogonic development
<p><span>Gene drives hold promise for the genetic control of malaria vectors. The development of vector population modification strategies hinges on the availability of effector mechanisms impeding parasite development in transgenic mosquitoes. We augmented a midgut gene of the malaria mosquito <em>Anopheles gambiae</em> to secrete two exogenous antimicrobial peptides, Magainin 2 and Melittin. This small genetic modification, capable of efficient non-autonomous gene</span> drive, hampers oocyst development in both <em>Plasmodium falciparum</em> and <em>Plasmodium berghei</em>. It delays the release of infectious sporozoites while it simultaneously reduces the lifespan <span>of homozygous female transgenic mosquitoes. Modeling the spread of this modification using a large-scale agent-based model of malaria epidemiology reveals that it can break the cycle of disease transmission across a range of transmission intensities.</span></p>
Co-occurrence of antimicrobials and metals in swine manure as potential drivers of antimicrobial resistance in the environment
<p>In many regions of the United States (US) and other countries, animal manures are often agronomically applied to cropland to recycle nutrients. However, aggregated manure wastes commonly contain contaminants including veterinary antimicrobials, heavy metals, and antimicrobial resistance genes (ARGs) that can stimulate the development and proliferation of antimicrobial resistance (AMR). While the presence of antimicrobials in manure is well-documented, very little has been reported on the co-occurrence of other chemical stressors in swine manure that may stimulate AMR spread in exposed bacteria. This study quantifies and analyzes correlations between antimicrobials, metals, and certain ARGs present in manure samples from swine farms in Iowa, US. Relationships between contaminants and different stages of swine production or feed composition are also investigated. Results revealed notable levels of tetracyclines (up to 1,260 µg g-1 dry weight (d.w.) of manure for oxytetracycline) detected in all samples. Tiamulin, two ionophores (monensin and lasalocid), and one macrolide (tilmicosin) were detected at maximum class concentrations of 9.4, 0.547, and 0.472 µg g-1 d.w., respectively. The median relative abundances of ErmB and TetM were 0.13 and 0.17 copies g-1 wet weight (w.w.) manure (normalized to 16S gene), respectively. Additionally, high levels of copper (Cu), iron (Fe), and zinc (Zn) were detected in all samples, with maximum concentrations of 887, 1,900, and 2,100 µg g-1 d.w., respectively. Notably, uranium was detected in 11 samples, at concentrations up to 0.77 µg g-1. A global analysis of AMR-stressor relationships using Spearman's rank correlation indicates Cu, and Ba are the most positively and significantly correlated with anhydrotetracycline (ATC) and/or anhydrochlortetracycline (ACTC) concentrations in all tested facilities (Cu-ATC: ρ = 0.67, p = 0.0093; Cu-ACTC: ρ = 0.75, p = 0.0022; Ba-ATC: ρ = 0.84, p = 0.0002). Interestingly, ermB and tetM genes were strongly, positively correlated to each other (ρ=0.92, p= 0.000), suggesting possible co-selection, despite the absence of correlation between ARGs and tetracycline concentrations. This study demonstrates the complexity of interactions between antimicrobials, metals, and ARGs in multiple manure storage pits prior to cropland application.</p>
Statistical and power calculations animal trial persistant antimicrobials and resistance levels
<p>This repository is containing the datasets with statistical analysis of the paper: "Extended period of selection pressure due to persistancy of antimicrobials in broilers."</p> <p><em>Power calculation</em></p> <ul> <li>Two CSV-files: Power calculation resistant isolates and Power calculation antibiotics</li> <li>One R-file: Power calculation antimicrobial persistent residues</li> </ul> <p><em>The phenotypic resistance</em></p> <ul> <li>R-file: Phenotypic resistance analysis trial, CSV-file: E. coli resistance per treatment</li> </ul> <p><em>The resistome analysis </em></p> <ul> <li>one CSV-files: Resistome workfile </li> <li>one R-file: Resistome statistical analysis</li> </ul> <p><em>Microbiome analysis</em><strong><em><br></em></strong></p> <ul> <li>Phyloseq object <ul> <li>R-file: Rarfied phyloseq object from biom file, CSV-file: metedata, biom-file: reads_trail </li> </ul> </li> <li>Alpha- and beta-diversity analysis<br> <ul> <li>R-file: Beta en alpha diversity animal trail, Rdata-file: rarefy.animaltrial</li> </ul> </li> <li>Microbial abundance analysis <ul> <li>R-file: relative abundance animal trial, Rdata-file: rarefy.animaltrial</li> </ul> </li> </ul>
Data on the Blackthorn fruit peel: phenolic compounds and antimicrobial synergy with blue light against Listeria monocytogenes
<p>The dataset contains results obtained during a project funded by the National Science Centre, Poland [Grant number 2022/45/B/NZ9/00299 (OPUS-23)].</p>
The metabolomics raw data and a supporting statistical analyses data set for publication: Metabolomic analysis revealed the absence of the principal antimicrobial compound of Pseudomonas donghuensis P482, 7-hydroxytropolone, under restricted nutrient conditions.
<p><a href="../api/records/11220997/draft/files/Metabolomic%20analyses%20raw%20files.zip/content" target="_blank" rel="noopener noreferrer">Metabolomic analyses raw files</a>, Compounds analyses, Hierarchical Condition tress and PCA Scores are uploaded.</p>
Fig. 1 in Antimicrobial activity of the crude peptide extracts from Blackfin sea catfish Arius jella Day, 1877
Fig. 1 — Photograph of experimental species Arius jella
Fig 1 in Antimicrobial activity of pandanus leaves extract to against Aeromonas hydrophila which attacked catfish
Fig 1: Inhibition test of Aeromonas hydrophila bacteria
Antimicrobial molecules derived from kefir, effective against P aeruginosa and MRSA strains
<p>These files contain the NGS data of the partial 16.S rRNA gene (V3-V4 region) amplicon from Kefir grains used within the manuscript "Antimicrobial molecules derived from kefir, effective against P aeruginosa and MRSA strains"</p>
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.