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270 results for “antimicrobial resistance”
Data for: Heavy metal pollution impacts soil bacterial community structure and antimicrobial resistance at the Birmingham 35th Avenue Superfund Site
<p>The data in this archive are the results of a study on the impact of heavy metals (HMs) on the soil microbiota of an urban Superfund site in Alabama. HMs are known to modify bacterial communities both in the laboratory and in situ. Consequently, soils in HM-contaminated sites such as the U.S. Environmental Protection Agency (EPA) Superfund sites are predicted to have altered ecosystem functioning, with potential ramifications for the health of organisms, including humans, that live nearby. Further, several studies have shown that heavy metal-resistant (HMR) bacteria often also display antimicrobial resistance (AMR), and therefore HM-contaminated soils could potentially act as reservoirs that could disseminate AMR genes into human-associated pathogenic bacteria. To explore this possibility, topsoil samples were collected from six public locations in the zip code 35207 (the home of the North Birmingham 35th Avenue Superfund Site) and in six public areas in the neighboring zip code, 35214. 35027 soils had significantly elevated levels of the HMs As, Mn, Pb, and Zn, and sequencing of the V4 region of the bacterial 16S rRNA gene revealed that elevated HM concentrations correlated with reduced microbial diversity and altered community structure. While there was no difference between zip codes in the proportion of total culturable HMR bacteria, bacterial isolates with HMR almost always also exhibited AMR. Metagenomes inferred using PICRUSt2 also predicted significantly higher mean relative frequencies in 35207 for several AMR genes related to both specific and broad-spectrum AMR phenotypes. Together, these results support the hypothesis that chronic HM pollution alters the soil bacterial community structure in ecologically meaningful ways and may also select for bacteria with increased potential to contribute to AMR in human disease.</p>
Antimicrobial Resistance Microbiological Dataset (ARMD-UTSW): A deidentified collection of electronic health records, from a quaternary, academic medical center, for antimicrobial resistance research
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Antimicrobial Resistance Microbiological Dataset (ARMD-ECUH): A deidentified collection of electronic health records from a rural academic health system for antimicrobial resistance research
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Chemokines kill bacteria without triggering antimicrobial resistance by binding anionic phospholipids
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Data for: Heavy metal pollution impacts soil bacterial community structure and antimicrobial resistance at the Birmingham 35th Avenue Superfund Site
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Chemokines kill bacteria by binding anionic phospholipids without triggering antimicrobial resistance
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Predicting antimicrobial resistance in Pseudomonas aeruginosa with machine learning-enabled molecular diagnostics
<p>Datasets for manuscript "Predicting antimicrobial resistance in Pseudomonas aeruginosa with machine learning-enabled molecular diagnostics"</p> <p><strong>Metadata.zip</strong></p> <ol> <li><strong>phenotypes.txt: </strong>tabular file containing binary resistance phenotypes based on CLSI guidelines, where the rows are the isolates and the columns correspond to different drugs. Resistance : 1, susceptibility: 0, missing: intermediate resistant</li> </ol> <p><strong>Features_gpa_exp_snps.zip </strong></p> <p>We provide the processed molecular data as Numpy compressed files (npz.). You can use the Numpy load method to read in these tables https://docs.scipy.org/doc/numpy/reference/generated/numpy.load.htm. The row (strains_list) and column labels (feature_lists) are stored separately.</p> <ol> <li><strong>genexp</strong>: gene expression table directory <ul> <li>genexp_feature_vect.npz: The feature matrix in the numpy format</li> <li>genexp_feature_list.txt: The columns of the feature matrix (features)</li> <li>genexp_strains_list.txt: The rows of the feature matrix (isolates)</li> </ul> </li> <li><strong>gpa: </strong>gene presence/absence table directory <ul> <li>gpa_feature_vect.npz: The feature matrix in the numpy format</li> <li>gpa_feature_list.txt: The columns of the feature matrix (features)</li> <li>gpa_strains_list.txt: The rows of the feature matrix (isolates)</li> </ul> </li> <li><strong>snps: </strong>SNPs table directory <ul> <li>snps_feature_vect.npz: The feature matrix in the numpy format</li> <li>snps_feature_list.txt: The columns of the feature matrix (features)</li> <li>snps_strains_list.txt: The rows of the feature matrix (isolates)</li> </ul> </li> </ol>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - 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. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_IE_20200204: >> The Food Safety Authority of Ireland</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - Sweden
<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. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_SE_20200204: >> National Veterinary Institute, Swedish Zoonosis Centre</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - 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. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_LV_20200204: >> Assessment and Registration Agency of Food and Veterinary Service of Latvia</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - 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. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_ES_20200204: >> Agencia Espaola de Consumo, Seguridad Alimentaria y Nutricin >> Ministerio de Agricultura, Pesca y Alimentacin</p>
Specific monitoring results of ESBL-/AmpC-/carbapenemase-producing bacteria and specific monitoring of carbapenemase-producing bacteria, in the absence of isolates detected complementing the European Union Overview Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2017/2018
<p>This dataset derives from the specific monitoring of E. coli producers of ESBLs/AmpC/carbapenemases, as well as the specific monitoring of carbapenemase-producers (voluntary reporting), in the absence of any isolates detected. This dataset contains only data when Total units positive equals zero '0'.</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - 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. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_CY_20200204: >> Ministry of Agriculture, Natural Resources and Evironment - Veterinary Services</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - Iceland
<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. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_IS_20200204: >> Icelandic Food and Veterinary Authority</p>
Dataset for Antimicrobial resistance of Neisseria gonorrhoeae in Germany: low levels of cephalosporin resistance but rising azithromycin resistance
<p>This is Dataset used for Publication "Antimicrobial resistance of <em>Neisseria gonorrhoeae</em> in Germany: low levels of cephalosporin resistance but rising azithromycin resistance" and contains data on Information on performed Neisseria gonorrhoeae AMR tests in sentinel Laboratories as well as AMR testing in consiliary Laboratory.</p>
Genomic epidemiology of Escherichia coli: antimicrobial resistance through a One Health lens in sympatric humans, livestock and peri-domestic wildlife in Nairobi, Kenya
<p><strong><span>Background</span></strong></p> <p><span>Livestock systems have been proposed as a reservoir for antimicrobial-resistant (AMR) bacteria and AMR genetic determinants that may infect or colonise humans, yet quantitative evidence regarding their epidemiological role remains lacking. Here we used a combination of genomics, epidemiology and ecology to investigate patterns of AMR gene carriage in <em>Escherichia</em> <em>coli</em>, regarded as a sentinel organism.</span></p> <p><strong><span>Methods</span></strong></p> <p><span>We conducted a structured epidemiological survey of 99 households across Nairobi, Kenya, and whole genome sequenced <em>E</em>. <em>coli</em> isolates from 311 human, 606 livestock, and 399 wildlife faecal samples. We used statistical models to investigate the prevalence of AMR carriage and characterise AMR gene diversity and structure of AMR genes in different host populations across the city. We also investigated house-hold level risk factors for exchange of AMR genes between sympatric humans and livestock.</span></p> <p><strong><span>Findings</span></strong></p> <p><span>We detected 56 unique acquired genes along with 13 point mutations present in variable proportions in human and animal isolates, known to confer resistance to nine antibiotic classes. We find that AMR gene community composition is not associated with host species, but AMR genes were frequently co-located, potentially enabling the acquisition and dispersal of multi-drug resistance in a single step. We find that whilst keeping livestock had no influence on human AMR gene carriage, the potential for AMR transmission across human-livestock interfaces is greatest when manure is poorly disposed of and in larger households.</span></p> <p><strong><span>Conclusions</span></strong></p> <p><span>Findings of widespread carriage of AMR bacteria in human and animal populations, including in long-distance wildlife species, in community settings, highlight the value of evidence-based surveillance to address antimicrobial resistance on a global scale. Our genomic analysis provided in-depth understanding of AMR determinants at the interfaces of One-Health sectors that will inform AMR prevention and control.</span></p>
Data from: Antimicrobial resistance of Staphylococcus and Enterococcus bacteria in rural dogs in Hungary - a preliminary report
<p><span>Antimicrobial resistance (AMR) is one of the most relevant health challenges globally. Since resistant bacteria and their resistance genes circulate through the ecosystem, AMR is among the main focuses of One Health. Dogs are the best friends of humans, therefore their relationships with the owners are mostly very close. This connection can make the dogs vehicles of AMR between the environment and humans. Based on this hypothesis, we investigated faecal samples from 37 dogs in Inner Somogy, Hungary. We isolated and investigated for antibiotic susceptibility 21 and 6 strains of <em>Staphylococcus</em> and <em>Enterococcus</em> genera, respectively. Among staphylococci and enterococci, 12 and 3 strains proved to be resistant to at least one antibiotic. Multidrug resistant strains were detected only among coagulase negative staphylococci, mainly in <em>S. sciuri</em> species. The antibiotics that proved to be inefficient against the most strains were benzylpenicillin (8 strains), moxifloxacin (6 strains), clindamycin (5 <em>S. sciuri</em> strains), and fusidic acid (12 strains). In the case of moxifloxacin and fusidic acid, the MIC excessed the EUCAST clinical breakpoint. Analysing the epidemiological background of the animals, outdoors keeping and higher income level of the owners seemed risk factors of AMR carrying, though the sample size of this study could not confirm statistically the apparent interdependence.</span></p>
Data from: Chicken gut microbiome members limit the spread of an antimicrobial resistance plasmid in Escherichia coli
<p>Plasmid-mediated antimicrobial resistance is a major contributor to the spread of resistance genes within bacterial communities. Successful plasmid spread depends upon a balance between plasmid fitness effects on the host and rates of horizontal transmission. While these key parameters are readily quantified in vitro, the influence of interactions with other microbiome members is largely unknown. Here, we investigated the influence of three genera of lactic acid bacteria (LAB) derived from the chicken gastrointestinal microbiome on the spread of an epidemic narrow-range ESBL resistance plasmid, IncI1 carrying <em>bla<sub>CTX-M-1</sub></em>, in mixed cultures of isogenic <em>Escherichia coli </em>strains. Secreted products of LAB decreased <em>E. coli</em> growth rates in a genus-specific manner but did not affect plasmid transfer rates. Importantly, we quantified plasmid transfer rates by controlling for density-dependent mating opportunities. Parametrization of a mathematical model with our in vitro estimates illustrated that small fitness costs of plasmid carriage may tip the balance towards plasmid loss under growth conditions in the gastrointestinal tract. This work shows that microbial interactions can influence plasmid success and provides an experimental-theoretical framework for further study of plasmid transfer in a microbiome context.</p>
Assessment of animal diseases caused by bacteria resistant to antimicrobials: Cattle- Appendix B: Excel file with all data extracted
<p>Information on all the full-text studies that were assessed, including the reason for exclusion for those that were excluded at the full-text screening and the data extracted from the included studies, can be consulted here. </p> <p>The extensive literature review was carried out by the University of Copenhagen under the contract OC/EFSA/ALPHA/2020/02 – LOT 1 (https://ted.europa.eu/udl?uri=TED:NOTICE:457654-2020:TEXT:EN:HTML)</p>
DRIAMS: Database of Resistance Information on Antimicrobials and MALDI-TOF Mass Spectra
<p>Early administration of effective antimicrobial treatments is critical for the outcome of infections and the prevention of treatment resistance. Antimicrobial resistance testing enables the selection of optimal antibiotic treatments, but current culture-based techniques can take up to 72 hours to generate results. We have developed a novel machine learning approach to predict antimicrobial resistance directly from MALDI-TOF mass spectra profiles of clinical samples. We trained calibrated classifiers on a newly-created publicly available database of mass spectra profiles from clinically most relevant isolates with linked antimicrobial susceptibility phenotypes. The dataset combines more than 300,000 mass spectra with more than 750,000 antimicrobial resistance phenotypes from four medical institutions. Validation against a panel of clinically important pathogens, including Staphylococcus aureus, Escherichia coli, and Klebsiella pneumoniae, resulting in AUROC values of 0.80, 0.74, and 0.74 respectively, demonstrated the potential of using machine learning to substantially accelerate antimicrobial resistance determination and change of clinical management. Furthermore, a retrospective clinical case study found that implementation of this approach would have resulted in a beneficial change in the clinical treatment in 88% (8/9) of cases. MALDI-TOF mass spectra based machine learning may thus be an important new tool for treatment optimization and antibiotic stewardship.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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.