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1,017 results for “Antimicrobial”
Figure 2 in Antimicrobial activity of noni fruit essential oil on Escherichia coli O157:H7 and Salmonella Enteritidis
Figure 2. The effect of noni EO on E. coli O157:H7 and S. Enteritidis using the broth dilution method in TBS to determine the MBC value of noni EO against both pathogens.
Selected Simple Natural Antimicrobial Terpenoids as Additives to Control Biodegradation of Polyhydroxy Butyrate
<p><strong>Abstract</strong></p> <div>In this experimental research, different types of essential oils (EOs) were blended with polyhydroxybutyrate (PHB) to study the influence of these additives on PHB degradation. The blends were developed by incorporating three terpenoids at two concentrations (1 and 3%). The mineralization rate obtained from CO<sub>2</sub> released from each sample was the factor that defined biodegradation. Furthermore, scanning electron microscope (SEM), differential scanning calorimetry (DSC), and dynamic mechanical analysis (DMA) were used in this research. The biodegradation percentages of PHB blended with 3% of eucalyptol, limonene, and thymol after 226 days were reached 66.4%, 73.3%, and 76.9%, respectively, while the rate for pure PHB was 100% after 198 days, and SEM images proved these results. Mechanical analysis of the samples showed that eucalyptol had the highest resistance level, even before the burial test. The other additives showed excellent mechanical properties although they had less mechanical strength than pure PHB after extrusion. The samples’ mechanical properties improved due to their crystallinity and decreased glass transition temperature (Tg). DSC results showed that blending terpenoids caused a reduction in Tg, which is evident in the DMA results, and a negligible reduction in melting point (Tm).</div> <p> </p> <p><strong>Open access data</strong></p> <p>The datasets for this publication can be accessed using the DOI: 10.5281/zenodo.13829790 or via the zip folder below.</p>
MS-UMG: MALDI-TOF Mass Spectra and Resistance Information on Antimicrobials from University Medical Center Göttingen
<p>During routine diagnostic procedures, we aggregated MALDI-TOF MS data of organisms isolated from clinical specimens from the University Medical Center Göttingen (UMG) in 2020 / 2021. We integrated these with corresponding antimicrobial susceptibility profiles. This amounted to 26,961 mass spectra and 26,961 corresponding metadata entries for the year 2020, and 50,381 mass spectra and 50,381 corresponding metadata entries for 2021, respectively. The dataset reflects 348 different species of bacterial and fungal organisms and 72 different antimicrobial susceptibility testing (AST) results.</p> <p> </p> <p>Please cite: </p> <div> <div>Effect of Data Heterogeneity in Clinical MALDI-TOF Mass Spectra Profiles on Direct Antimicrobial Resistance Prediction through Machine Learning</div> </div> <div><span><span><span>Youngjun</span> <span>Park</span></span>, <span><span>Michael</span> <span>Weig</span></span>, <span><span>Christine</span> <span>Noll</span></span>, <span><span>Oliver</span> <span>Bader</span></span>, <span><span>Anne-Christin</span> <span>Hauschild</span></span></span></div> <div><span>bioRxiv </span><span>2024.10.18.617592; </span><span><span>doi:</span> https://doi.org/10.1101/2024.10.18.617592</span></div>
pH-responsive aminolipid nanocarriers for antimicrobial peptide delivery
<p>Raw data for the paper entitled, "pH-responsive aminolipid nanocarriers for antimicrobial peptide delivery" published in the Journal of Colloid and Interface Science on 11 June 2021.</p> <p> </p> <p>Abstract:</p> <p>pH-responsive aminolipid self-assemblies are promising platforms for the targeted delivery of antimicrobial peptides (AMPs), with the potential to improve their therapeutic efficiency and physicochemical stability. pH-sensitive nanocarriers based on dispersed self-assemblies of 1,2-dioleoyl-3-dimethylammonium-propane (DODAP) with the human cathelicidin LL-37 in excess water were characterized at different pH values using small-angle X-ray scattering, cryogenic transmission electron microscopy, and dynamic light scattering. Fluorescence and electrophoretic mobility measurements were used to probe the encapsulation efficiency of LL-37 and the nanocarriers’ surface potential. Upon decreasing pH in the DODAP/water systems, normal oil-in-water emulsions at pH ≥ 5.0 transitioned to emulsions encapsulating inverse hexagonal and cubic structures at pH between 4.5 and 4.0, and mostly positively-charged vesicles at pH < 4.0. These colloidal transformations are driven by the protonation of DODAP upon pH decrease. The larger lipid-water interfacial area provided by the DODAP self-assemblies at pH ≤ 4.5 allowed for an adequate encapsulation efficiency of LL-37, favouring the formation of vesicles in a concentration-dependent manner. Contrary, LL-37 was found to dissociate from the emulsion droplets at pH 6.0. The knowledge on the pH-triggered self-assembly of LL-37 and DODAP, combined with the results on peptide release from the structures contribute to the fundamental understanding of lipid/peptide self-assembly. The results can guide the rational design of future pH-responsive AMP delivery systems.</p>
Modified poly(L-lysine)-based structures as novel antimicrobials for diabetic foot infections, an in-vitro study.
<p><strong>Data used to generate Figures 2 to 7 </strong></p> <p>Figure 2. Bactericidal activity of poly-L-lysine polymers against <em>S. aureus</em> and <em>P. aeruginosa</em> laboratory strains compared to antibiotics.</p> <p>Figure 3. Bactericidal activity of poly-L-lysine polymers against <em>S. aureus</em> and <em>P. aeruginosa</em> laboratory strains.</p> <p>Figure 4. Comparative bactericidal activity of poly-L-lysine G3(16) copolymers series with hydrophobic amino acid isoleucine, tyrosine and phenylalanine.</p> <p>Figure 5. Comparison of Bactericidal activity of poly-L-lysine polymers, PLL<sub>160 </sub>and G2(8)PLL<sub>20</sub> against <em>S. aureus</em> clinical isolates from wound infections. </p> <p>Figure 6. Bactericidal activity of linear PLL<sub>160 </sub>against <em>S. aureus</em> and <em>P. aeruginosa </em>isolates from suspected diabetic foot infections.</p> <p>Figure 7. Investigation of PLL polymer-induced loss of biofilm viability by resazurin staining of 24 h biofilms.</p>
A Supervised Machine-Learning Prediction of Textile's Antimicrobial Capacity Coated with Nanomaterials
<p>The dataset contains P-Chem properties of NMs and experimental conditions for assessing the antimicrobial properties of inorganic and organic NMs using machine learning tools.</p>
European Union Summary Report on Antimicrobial Resistance in Zoonotic and Indicator Bacteria from Humans, Animals and Food in 2020/2021
<p>All tables produced for the European Union Summary Report on Antimicrobial Resistance in Zoonotic and Indicator Bacteria from Humans, Animals and Food in 2021:</p> <p>- <em>Campylobacter</em></p> <p><em>- E. coli</em></p> <p>- MRSA</p> <p>- <em>Salmonella</em></p> <p>- ESBL</p> <p>Annexes A to F are also included.</p>
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>
Microbiota or Placebo After Antimicrobial Therapy for Recurrent C. Difficile at Home (MATCH)
ClinicalTrials.gov study NCT03005379. IPD Sharing: YES. Countries: 1. Publications: 2.
Dissemination and Implementation of a Videoconference Antimicrobial Stewardship Team
ClinicalTrials.gov study NCT05319561. IPD Sharing: NO. Countries: 1. Publications: 1.
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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Data and code for: Dihydrothiazolo ring-fused 2-pyridone antimicrobial compounds effectively treat Streptococcus pyogenes skin and soft tissue infection
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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>
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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.