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1,017 results for “Antimicrobial”

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zenodo32/100

Antimicrobial Compounds in the Volatilome of Social Spider Communities

<p>This data set contains the raw GC-MS data in cdf-format of the corresponding publication.</p>

opencc-by-4.0Jun 2021View details →
zenodo32/100

Decorating Nanostructured Surfaces with Antimicrobial Peptides to Efficiently Fight Bacteria

<p>Data underlying the figures in the publication &ldquo;Decorating Nanostructured Surfaces with Antimicrobial Peptides to Efficiently Fight Bacteria&rdquo;, published in <em>ACS Appl. Bio Mater</em>., <strong>2020</strong>, 3, 3, 1533&ndash;1543.</p> <p><a href="https://pubs.acs.org/doi/10.1021/acsabm.9b01154">https://pubs.acs.org/doi/10.1021/acsabm.9b01154</a></p> <p>Table of contents:</p> <p><strong>1. Figure 1</strong>; Zip file containing the numerical data for the FCS studies of <em>Figure 1</em>.</p> <p><strong>2. Figure 2</strong>; Zip file containing the data underlying <em>Figure 2</em>.</p> <p><strong>3. Figure 3</strong>; Zip file containing the numerical data for the XPS studies of <em>Figure 3</em>.</p> <p><strong>4. Figure 4</strong>; Zip file containing the numerical data for the QCM-D studies of <em>Figure 4</em>.</p> <p><strong>5. Figure 5</strong>; Zip file containing the data underlying <em>Figure 5</em>.</p> <p><strong>6. Table 1</strong>; Zip file containing the numerical data for the FCS Fitting Parameters in <em>Table 1</em>.</p> <p><strong>5. Table 2</strong>; Zip file containing the numerical data for the Atomic concentrations calculated in <em>Table 1</em>.</p> <p>&nbsp;</p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Jul 2021View details →
zenodo32/100

Mixed chirality α-helix in a stapled bicyclic and a linear antimicrobial peptide revealed by X-ray crystallography

<p>The upload contains additional primary data associated with the publication <a href="https://doi.org/10.1039/D1CB00124H">https://doi.org/10.1039/D1CB00124H</a>, including raw data in the original file format whenever possible.</p> <p>Data content: HPLC-MS,&nbsp;CD,&nbsp;Vesicle leakage, Molecular Dynamics,&nbsp;Crystallography (primary electron density maps) and Supporting Information.</p>

opencc-by-4.0Jun 2021View details →
zenodo32/100

antimicrobial susceptibility profiles of MDR indicator bacteria

<table> <tbody> <tr> <td> <p>Sixteen antimicrobial agents were tested in the Sensititre&trade; panel to evaluate the antimicrobial susceptibility of <em>Salmonella</em> Gallinarum CNHJ001, <em>Salmonella</em> Enteritidis 190610_1, <em>Escherichia coli</em> ROH_0034,<em> Staphylococcus aureus</em> ROH_0029. <em>Escherichia coli</em> ATCC25922 was also tested as a susceptible control. The antimicrobial agents used in these experiments were; ciprofloxacin (<strong>CIP</strong>), nalidixic acid (<strong>NAL</strong>), imipenem (<strong>IMI</strong>), colistin (<strong>COL</strong>), ampicillin (<strong>AMP</strong>), tetracycline (<strong>TET</strong>), chloramphenicol (<strong>CHL</strong>), azithromycin (<strong>AZI</strong>), gentamicin (<strong>GEN</strong>), streptomycin (<strong>STR</strong>), amikacin (<strong>AMI</strong>), trimethoprim/sulfamethoxazole (<strong>SXT</strong>), cefotaxime (<strong>FOT</strong>), ceftriaxone (<strong>AXO</strong>), cefoxitin (<strong>FOX</strong>), ceftazidime (<strong>TAZ</strong>).<br> <em>a. </em>R=resistant<em>&nbsp; b. </em>S=susceptible<em>&nbsp; c. </em>I=intermediate.</p> </td> </tr> </tbody> </table> <p>&nbsp;</p>

opencc-by-4.0Dec 2022View details →
zenodo32/100

Raw data for: Cell-free biosynthesis combined with deep learning accelerates de novo-development of antimicrobial peptides

<p>This repository contains data related to &quot;Cell-free biosynthesis combined with deep learning accelerates de novo-development of antimicrobial peptides&quot; by Pandi et al.</p> <p>Included are molecular dynamics parameter files, initial structures after system equilibration and production trajectories. For simulations of AMPs with membranes, trajectories are subsampled with 1 frame every 5 ns and final structures after 1 &mu;s of production simulation are included.</p> <p>Contact information:<br> Name: Stefan L. Schaefer<br> Institution: Department of Theoretical Biophysics, Max Planck Institute of Biophysics<br> Address: Max-von-Laue-Str. 3, 60438 Frankfurt am Main, Germany<br> Email: stefan.schaefer@biophys.mpg.de</p>

opencc-by-4.0Nov 2022View details →
zenodo32/100

supplementary data for Synthesis, Characterization, and Preliminary Antimicrobial Study of Some New Phthalimide Phenyl Hydrazide Derivatives

<p>supplementary data for Synthesis, Characterization, and Preliminary Antimicrobial Study of Some New Phthalimide Phenyl Hydrazide Derivatives</p>

opencc-by-4.0Jan 2023View details →
zenodo32/100

ArMoR Cluster: 7 research projects fight Antimicrobial Resistance in livestock farming (updated version)

<p>Supported by the European Commission, Horizon Dissemination Booster (HRB) contributes to an effective transfer of research and innovation project results to policy makers, industry and society by offering various services as dissemination, exploitation strategy and business plan development to projects. Within Horizon Results Booster programme (HRB), 7 research projects AMRILS, AVANT, BM-FARM, FARMCARE, DISARM, HealthyLivestock and ROADMAP have formed the &quot;ArMoR Cluster&quot; to develop a conceptual framework to improve understanding of AMR in livestock systems.</p> <p>The video is available on YouTube:&nbsp;<a href="https://www.youtube.com/watch?v=ACbnyu3PhOY">https://www.youtube.com/watch?v=ACbnyu3PhOY</a></p> <p>For any further questions please contact us at:</p> <ul> <li><strong><a href="https://zenodo.org/record/avant@rtds-group.com">avant@rtds-group.com</a></strong>&nbsp;(project AVANT)</li> </ul>

opencc-by-4.0Jan 2023View details →
zenodo32/100

CalcAMP: A new machine learning model for the accurate pre-diction of antimicrobial activity of peptides

<p>Datasets used for the publication:&nbsp;</p> <p>CalcAMP: A new machine learning model for the accurate prediction of antimicrobial activity of peptides</p>

opencc-by-4.0Jan 2023View details →
zenodo32/100

Assessing the antimicrobial Capacity of metal oxide nanomaterials using ZOI and MIC measurements by employing  Machine learning tools.

<p>Assessing the antimicrobial Capacity of metal and metal oxide&nbsp;nanomaterials (IONPs, AgNPs, ZnONPs) using ZOI and MIC measurements by employing Machine learning tools.</p>

opencc-by-4.0Jul 2021View details →
zenodo32/100

Table S1 Metadata and antimicrobial data

<p>High prevalence of <em>bla</em><sub>CTX-M-15</sub> type extended spectrum beta-lactamases in Gambian Hooded Vultures (<em>Necrosyrtes monachus</em>) &ndash; a threatened species with substantial human interaction</p> <p>Table S1&nbsp;Metadata and antimicrobial data for all <em>E.coli</em> and <em>K. pneumoniae</em> in this study.</p>

opencc-by-4.0Feb 2023View details →
zenodo32/100

Antibiotic-induced accumulation of lipid II synergizes with antimicrobial fatty acids to eradicate bacterial populations - confocal dataset

<p>Dataset of confocal images that accompanies:</p> <p>Ashelyn E Sidders, Katarzyna M Kedziora, Melina Arts, Jan-Martin Daniel, Stefania de Benedetti, Jenna E Beam, Duyen T Bui, Joshua B Parsons, Tanja Schneider, Sarah E Rowe, Brian P Conlon (2023) Antibiotic-induced accumulation of lipid II synergizes with antimicrobial fatty acids to eradicate bacterial populations eLife 12:e80246.</p> <p>https://doi.org/10.7554/eLife.80246&nbsp;</p> <p>Pre-print:</p> <p>Ashelyn E. Sidders, Katarzyna M. Kedziora, Jenna E. Beam, Duyen T. Bui, Joshua Parsons, Sarah E. Rowe, Brian P. Conlon: Antibiotic-induced accumulation of lipid II sensitizes bacteria to antimicrobial fatty acids.</p> <p>https://www.biorxiv.org/content/10.1101/2022.05.03.490474v1.full.pdf</p> <p>Analysis code:</p> <p>https://github.com/fjorka/bacteria_pa_van_analysis</p>

opencc-by-4.0Mar 2023View details →
zenodo32/100

To fold or not to fold: diastereomeric optimization of an α-helical antimicrobial peptide

<p>The upload contains additional primary data associated with the publication <a href="https://doi.org/10.1021/acs.jmedchem.3c00460">https://doi.org/10.1021/acs.jmedchem.3c00460</a>, including raw data in the original file format whenever possible.</p> <p>Data content: HPLC-MS for characterization and serum stability, HRMS, CD,&nbsp;Vesicle leakage, Cytotoxicity, Molecular Dynamics,&nbsp;Crystallography (primary electron density maps), pictures for microbiological and hemolysis assays&nbsp;and Supporting Information.</p>

opencc-by-4.0May 2023View details →
zenodo32/100

A Survey of Antimicrobial Biocides in Direct-to-Consumer Products in Australia

<p>Antimicrobial biocides such as disinfectants and preservatives are extremely widely used to control microbial growth, but are not regulated like antibiotics. Unfortunately, there is increasing evidence that many biocides can compromise antibiotic efficacy. The aim of this survey was to determine which biocides are most commonly found in products available to the public in Australia. Over 350 non-redundant products were surveyed and the results collated and presented by product category and biocide class. This data is a startpoint to understand overall biocide usage in Australia. Results and survey background are provided in the pdf report, and the full data on products surveyed and biocides present is available as a spreadsheet.</p>

opencc-by-4.0Jun 2023View details →
zenodo32/100

Technological and antimicrobial properties of indigenous LAB from Portuguese artisanal goat cheeses

<p>Recording of the talk &ldquo;Technological and antimicrobial properties of indigenous LAB from Portuguese artisanal goat cheeses&rdquo; presented by Beatriz Nunes Silva&nbsp;at the Artisanal Foods and Bioactive Molecules Seminar,&nbsp;M&eacute;denine, Tunisia (19-21 December 2021).</p>

opencc-by-4.0Dec 2021View details →
zenodo32/100

Fig. 6 in Chemical constituents of Rumex dentatus L. and their antimicrobial and anti-inflammatory activities

Fig. 6. Anti-inflammatory properties of the isolated compounds. (A): Effects of compounds 1–17 and 19 on LPS-induced NO production in RAW264.7 cells at a concentration of 50μM; (B): Effect of compound 9 on the viability of RAW264.7 cells; (C): Effects of compound9 on LPS-induced NO production in RAW264.7 cells at different concentrations.

opennotspecifiedJan 2023View details →
zenodo32/100

Fig. 5 in Chemical constituents of Rumex dentatus L. and their antimicrobial and anti-inflammatory activities

Fig. 5. LC‒MS/MS identification. (A): Total ion chromatogram of crude ethanol extract in negative ion mode with numbers of identified compounds; (B): Total ion chromatogram of crude ethanol extract in positive ion mode; (C): HPLC chromatography of crude ethanol extract monitored at 254 nm and names of the two most abundant compounds.

opennotspecifiedJan 2023View details →
zenodo32/100

Fig. 2 in Polyketides with antimicrobial activities from Penicillium canescens DJJ-1

Fig. 2. Two possible planar structures of 1 deduced on the basis of 1H–1H COSY and HMBC correlations.

opennotspecifiedFeb 2023View details →
zenodo32/100

Fig. 4 in Nardosinane-related antimicrobial terpenoids from Lemnalia sp. soft coral

Fig. 4. Comparison of the experimental ECD spectrum of 7 and the calculated ECD specta of the model molecules 7a (4S,5S,6R,7S,11S,12S,4′S,5′R,11′S), 7b (4S,5S,6R,7S,11S,12S,4′S,5′S,11′S), 7c (4R,5R,6S,7R,11R,12R,4′R,5′R,11′R) and 7d (4R,5R,6S,7R,11R,12R,4′R,5′S,11′R).

opennotspecifiedApr 2022View details →
zenodo32/100

Fig. 3 in Nardosinane-related antimicrobial terpenoids from Lemnalia sp. soft coral

Fig. 3. Comparison of the experimental ECD curve of 6 and the calculated ECD spectra of the model molecules 6a (4S,5S,6R,7S,11S,12S,4′S,5′S,6′R,11′R), 6b (4S,5S,6R,7S,11S,12S,4′R,5′R,6′S,11′S), 6c (4R,5R,6S,7R,11R,12R,4′S,5′S,6′R, 11′R) and 6d (4R,5R,6S,7R,11R,12R,4′R,5′R,6′S,11′S).

opennotspecifiedApr 2022View details →
zenodo32/100

Fig. 2 in Nardosinane-related antimicrobial terpenoids from Lemnalia sp. soft coral

Fig. 2. Key COSY (bold), HMBC (blue), and NOE (red) correlations of 6 and 7. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

opennotspecifiedApr 2022View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record