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1,017 results for “antimicrobials”
Phytochemical Screening, Antioxidant and Antimicrobial Activity of Fabric Coated with Catharanthus Roseus Ethanolic Flowers Extract
<p>The aim of the present study was to evaluate the free radical scavenging and antimicrobial activity of fabric coated of the Catharanthus Roseus. Ethanol flowers extract. Free radical scavenging was determined by using 1, 1-diphenyl-2-picrylhydrazyl (DPPH), Reducing power, Hydroxyl radical scavenging assay and antimicrobial activity of Staphylococcus aureus, Escherichia coli and standard drug of Streptomycin using disc diffusion method. This inhibition was observed with the individual extracts and when they were used in lower concentrations with ineffective antibiotics. The present investigation clearly indicates that the Catharanthus Roseus possesses antioxidant properties and serve as free radical inhibitors or scavengers, acting possibly as primary antioxidants.</p><p>Keywords</p><p>Catharanthus Roseus, Fabric coated, DPPH, Staphylococcus aureus Escherichia coli, Streptomycin, Antioxidant,</p>
PanRes - Collection of antimicrobial resistance genes
<p><strong>PanRes database of antimicrobial resistance genes</strong></p><p>Many different collections of antimicrobial resistance genes (ARGs) have been collected and used for various purposes. In order to develop a workflow for mass screening of public metagenomes, we recently gathered up and filtered in a number of these gene collections to produce PanRes.</p><p>For details, please see the methods section in the following publication:</p><p><strong> "ARGfinder - a pipeline for large-scale analysis of antimicrobial resistance genes and their flanking regions in metagenomic datasets" (Unpublished, submitted)</strong></p><p>Briefly, the PanRes gene collection is gathered from a combination of other resistance gene collections into one, so each unique sequence has an "pan_" identifier (PanRes_genes). A separate table (PanRes_data) provides an overview of all the genes, their origin database and which genes cluster together in high-identity clusters.<br><br>A number of previously published collections of ARGs were used in the creation of PanRes (See references):</p><p><strong>ResFinder</strong> (downloaded 2023-01-20, (Bortolaia et al. 2020)),<br><strong>ResFinderFG</strong> (version 2.0, (Gschwind et al. 2023))<br><strong>CARD</strong> (version 3.2.5, (Alcock et al. 2023))<br><strong>MegaRes</strong> (version 3.0.0, (Bonin et al. 2023))<br><strong>AMRFinderPlus</strong> (version 3.11/2022-12-19.1, (Feldgarden et al. 2021))<br><strong>ARGANNOT</strong> (V6_July2019, (Gupta et al. 2014))<br><strong>The 'CsabaPal' collection</strong> (Provided by Csaba Pál and Zoltán Farkas in November 2022, Daruka et al. 2023))<br><strong>BacMet</strong> (version 1.1, (Pal et al. 2014))</p>
Machine learning designs non-hemolytic antimicrobial peptides
<p>The upload contains additional primary data associated with the publication, including raw data in the original file format whenever possible.</p> <p>Data content: HRMS, HPLC-MS, CD, MD, TEM</p>
Data set for publication: Determination of Virulence-Associated Genes and Antimicrobial Resistance Profiles in Brucella Isolates Recovered from Humans and Animals in Iran Using NGS Technology
<p>This dataset includes information on resistance profiling, as well as antimicrobial resistance (AMR) genes and virulence-related factors that were identified in <em>Brucella</em> isolates recovered from humans and animals in different regions of Iran using classical phenotyping and next-generation sequencing (NGS) technology.</p>
Dataset for "Biocompatible Rhamnolipid Self-Assemblies with pH-Responsive Antimicrobial Activity"
<p>This dataset provides the raw data supporting the paper: Biocompatible Rhamnolipid Self-Assemblies with pH-Responsive Antimicrobial Activity. It comprises SAXS data (Figure 2, Figure 3, Figure 4, Figure 5, Figure S2 and Figure S4), cryo-TEM images (Figure 2D, Figure 4D, Figure 5D, Figure 5E), Zeta-potential measurment (Figure 7), DLS data (Figure 8, Figure S5, Figure S6, Figure S7, Figure S8 and Table S2), Antimicrobial activity data (Figure 9, Table 1, Figure S9, Figure S10, Figure S12, Figure S13, Figure S14, Figure S15, Figure S16 and Table S3), Cytotoxicity data (Figure 10), Colloidal stability images (Figure S1 and Figure S3) and Biofilm inhibition and biofilm eradication assay (Figure S11).</p><p> </p>
BIONANO-MSCA4U. Biosynthesis of AgNP from Pseudomonas N5.12 and antimicrobial effect
<p>This dataset presents the collected data corresponding to characterization of the biosynthetized AgNP with <em>Pseudomonas</em> N5.12. Listing of all the different data collected, produced, and published are available open-access for the EU-funded <strong>MSCA4Ukraine project (ID:101101923)</strong> combined in different format (in .cvs, .xlsx, .txt and .pdf versions).</p> <p><em>Abbreviation of sample names: S1-S5 – different ratio of bacterial supernatant and 1 mM AgNO3 solution: <code>S1</code> (5:1), <code>S2</code> (4:2), <code>S3</code> (3:3), <code>S4</code> (2:4), <code>S5</code> (1:5). The next letter indicates the pH of the medium (<code>7</code> or <code>9</code>) at which the samples were synthesized.</em></p>
Genomic Typing, Antimicrobial Resistance Gene, Virulence Factor and Plasmid Replicon Dataset for the Important Pathogenic Bacteria Klebsiella pneumoniae
<p>The infections caused by various bacterial pathogens both in clinical and community settings represent a significant threat to public healthcare worldwide. The growing resistance to antimicrobial drugs acquired by bacterial species causing healthcare-associated infections has already become a life-threatening danger noticed by the World Health Organization. Several groups or lineages of bacterial isolates usually called 'the clones of high risk' often drive the spread of resistance within particular species. </p> <p>Thus, it is vitally important to reveal and track the spread of such clones and the mechanisms by which they acquire antibiotic resistance and enhance their survival skills. Currently, the analysis of whole genome sequences for bacterial isolates of interest is increasingly used for these purposes, including epidemiological surveillance and developing of spread prevention measures. However, the availability and uniformity of the data derived from the genomic sequences often represents a bottleneck for such investigations. </p> <p>In this dataset, we present the results of a genomic epidemiology analysis of 61,857 genomes of a dangerous bacterial pathogen <em>Klebsiella pneumoniae</em> obtained from NCBI Genbank database. Important typing information including multilocus sequence typing (MLST)-based sequence types (STs), capsular (KL) and oligosaccharide (OL) types, CRISPR-Cas systems, and cgMLST profiles are presented, as well as the assignment of particular isolates to clonal groups (CG). The presence of antimicrobial resistance and virulence genes, as well as plasmid replicons, within the genomes is also reported. </p> <p>These data will be useful for researchers in the field of <em>K. pneumoniae</em> genomic epidemiology, resistance analysis and prevention measure development.</p>
AMPSphere : the worldwide survey of prokaryotic antimicrobial peptides
<p><strong>AMPSphere v.2022-03: the worldwide survey of prokaryotic antimicrobial peptides</strong></p> <p> </p> <p><strong>INTRODUCTION</strong></p> <p>AMPSphere is a comprehensive catalog of antimicrobial peptides predicted using Macrel (DOI: <a href="https://peerj.com/articles/10555/">10.7717/peerj.10555</a>) from 63,410 public metagenomes, <a href="http://progenomes.embl.de/">ProGenomes v2.2 database</a> (82,400 high-quality microbial genomes), and c.a. 4k non-whitelisted microbial genomes from NCBI. Currently, AMPSphere is available as a web resource at <a href="https://ampsphere.big-data-biology.org/">https://ampsphere.big-data-biology.org/</a>.</p> <p> </p> <p><strong>GENERATION</strong></p> <p>Peptides were predicted using <a href="https://www.big-data-biology.org/software/macrel/">Macrel</a>. Singleton peptides were removed, except those with a direct hit to <a href="http://dramp.cpu-bioinfor.org/">DRAMP<br> database</a>. Redundant peptides were coded using a reduced alphabet and hierarchically clustered using CD-HIT (version 4.6) at 100%, 85%, and 75% of amino acid identity (and 90% of overlap of the shorter peptide). The obtained clusters were numbered by decreasing size (number of peptides). Each level of clustering was called a SPHERE. Redundant nucleotide sequences for the gene variants of different AMPs also were included in this version of AMPSphere.</p> <p> </p> <p><strong>STATISTICS</strong></p> <p>AMPSphere v.2022-03 contains 863,498 sequences (avg length: 36 amino acids, range 8-98). DRAMP database was used to find confirmed sequences with strict homology to reference. This approach showed that 2,488 peptides were previously confirmed in our dataset.</p> <p> </p> <p><strong>IDENTIFIERS</strong></p> <p>Peptides are named in the form <strong>>AMP10.XXX_XXX</strong> where <strong>XXX_XXX</strong> is a unique numerical identifier (starting at zero). Numbers were assigned in order of increasing number of copies. So that the lower the number, the greater number of copies of that peptide were present in the input data. Annotations were also provided as separated fields in the fasta file, containing their:</p> <p>- SPHERE families at level III (corresponding to hierarchically obtained clusters using 100-85-75% of identity with a minimum overlap of 90% of the shorter gene).</p> <p>Example of header:</p> <pre><code class="language-bash">>AMP10.000_000 | SPHERE-III.001_493 </code></pre> <p><br> <strong>VERSION DETAILS</strong></p> <p><strong>Version 2022-03</strong> includes:</p> <p>- quality assessment of documented AMPs,</p> <p>- metadata associated with the genes,</p> <p>- a better taxonomic identification of AMP sources using GTDB.</p> <p><em>WARNING: Due to a different procedure of AMP sorting, now some entries and families may have changed their accessions.</em></p> <p> </p> <p><strong>FILES WITHIN THIS VERSION</strong></p> <p><em>README.md</em><br> This file.</p> <p> </p> <p><em>AMPsphere_v.2022-03.fna.xz</em><br> Multi-fasta with AMPSphere gene sequences (nucleotide).</p> <p> </p> <p><em>AMPsphere_v.2022-03.faa.gz</em></p> <p>Multi-fasta with AMPSphere peptide sequences (amino acid).</p> <p> </p> <p><em>SPHERE_v.2022-03.levels_assessment.tsv.gz</em></p> <p>TSV table relating AMP name and the hierarchically obtained clusters per level. Columns:</p> <p>- AMP accession<br> - evaluation vs. representative<br> - SPHERE_fam level I<br> - SPHERE_fam level II<br> - SPHERE_fam level III</p> <p>Levels of each SPHERE family:</p> <p>I: contains clusters obtained with 100% of identity cut-off and 90% of overlap of the shorter sequence;</p> <p>II: contains clusters obtained with the unclustered sequences and the representatives from level I at 85% of identity and 90% of overlap of the sorter sequence;</p> <p>III: contains clusters obtained with the unclustered sequences and the representatives from level II at 75% of identity and 90% of overlap of the sorter sequence;</p> <p>`evaluation vs. representatives` shows the percent of identity the sequence has in an alignment against the cluster representative, and also the overlap in percent.</p> <p>Example:</p> <p> * -- This means: this sequence is a cluster representative.</p> <p>OR something like this:</p> <p> 77.50%,1:40:1:40 -- This means: alignment identity against the<br> representative of the cluster equals 77.5% and the<br> alignment start and end position for the query (1 and<br> 40, respectively), and target (1 and 40, respectively).</p> <p> </p> <p><em>AMPSphere_v.2022-03.quality_assessment.tsv.gz</em><br> TSV table containing the results of each quality test (by sequence). Columns:</p> <p>- AMP ID<br> - Antifam<br> - RNAcode<br> - Metaproteomes<br> - Metatranscriptomes<br> - Coordinates</p> <p>Results are one of 'Passed', 'Failed', or 'Not tested'.</p> <p><a href="https://www.ebi.ac.uk/research/bateman/software/antifam-tool-identify-spurious-proteins">Antifam </a>results show if the sequence matches ('Fail') or does not match ('Pass') to Antifams, a set of well-known spurious ORFs.</p> <p><a href="https://github.com/ViennaRNA/RNAcode">RNAcode</a> relies on gene diversity, therefore, families with less than 3 different gene sequences could not be tested and were marked as such.</p> <p>The direct match of 50% of our peptide to transcripts (in at least 2 different samples) or peptides from meta-omics studies sampled from different environments assigned the peptide as passing the metatranscriptomes and metaproteomes tests, respectively.</p> <p>Finally, the coordinates test check if the start of the small ORF happens with at least one stop codon upstream, this ensures that the gene is not a fragment from a larger protein.</p> <p> </p> <p><em>AMPSphere_v.2022-03.general_geneinfo.tsv.gz</em><br> TSV table relating AMP, gene name, the microbial source, sample, environment, and geographical location. Columns:</p> <p>- gmsc (gene code access) <br> - amp <br> - sample (biosample)<br> - source (microbial origin, GTDB taxonomy)<br> - specI (species cluster according to ProGenomes v.2 classification)<br> - is_metagenomic (False if comming from a high-quality microbial genome)<br> - geographic_location<br> - latitude<br> - longitude<br> - general_envo_name<br> - environment_material</p> <p> </p> <p><strong>CONTACT</strong></p> <p>You can contact us via our discussion group: <a href="https://groups.google.com/g/ampsphere-users">https://groups.google.com/g/ampsphere-users</a></p> <p>AMPsphere main developers:</p> <p>- <a href="mailto:celio@big-data-biology.com?subject=AMPSphere%20v.2022-03&body=Dear%20Celio%2C%20%0A%0ARegarding%20AMPSphere%20v.2022-03.">Célio Dias Santos Júnior</a><br> - <a href="mailto:yiqian@big-data-biology.org?subject=AMPSphere%20v2022-03&body=Dear%20Yiqian%2C%20%0A%0ARegarding%20AMPSphere%20v2022-03.%0A">Yiqian Duan</a><br> - <a href="mailto:hui@big-data-biology.org?subject=AMPSphere%20v2022-03&body=Dear%20Hui%2C%20%0A%0ARegarding%20AMPSphere%20v.2022-03.">Hui Chong</a><br> - <a href="mailto:luispedro@big-data-biology.com?subject=AMPSphere%20v.2022-03&body=Dear%20Luis%2C%20%0A%0ARegarding%20AMPSphere%20v.2022-03.">Luis Pedro Coelho</a></p> <p><br> <strong>COPYRIGHT NOTICE</strong></p> <p><em>AMPSphere v.2022-03 - the worldwide survey of prokaryotic antimicrobial peptides.</em></p> <p>This work is a joint effort of Big Data Biology group from the Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI) - Fudan University, Shanghai, China, and the Structural and Computational Biology Unit<br> (Heidelberg) - European Molecular Biology Laboratory (EMBL).</p> <p>Copyright (C) 2019-2022 The Authors</p> <p> AMPSphere IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,<br> EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES<br> OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.<br> IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,<br> DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR<br> OTHERWISE,ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE<br> USE OR OTHER DEALINGS IN THE SOFTWARE.</p> <p> This database is free; you can redistribute it and/or modify it<br> as you wish, under the terms of the CC BY 4.0 license.</p> <p> You are allowed to:</p> <p> Share — copy and redistribute the material in any medium or format</p> <p> Adapt — remix, transform, and build upon the material for any purpose,<br> even commercially.</p> <p> You may also obtain a copy of the CC BY 4.0 license here:<br> <br> https://creativecommons.org/licenses/by/4.0/</p> <p><br> <strong>REFERENCES CITED</strong></p> <p>- Macrel: Santos-Júnior CD, Pan S, Zhao X, Coelho LP. 2020. Macrel: antimicrobial peptide screening in genomes and metagenomes. PeerJ 8:e10555. https://doi.org/10.7717/peerj.10555</p> <p>- ProGenomes: Mende DR, Letunic I, Maistrenko OM et al. 2020. proGenomes2: an improved database for accurate and consistent habitat, taxonomic and functional annotations of prokaryotic genomes. Nucleic Acids Research 48(D1): D621–D625. https://doi.org/10.1093/nar/gkz1002</p> <p>- DRAMP: Kang X, Dong F, Shi C et al. 2019. DRAMP 2.0, an updated data repository of antimicrobial peptides. Sci Data 6, 148. https://doi.org/10.1038/s41597-019-0154-y</p> <p>- ANTIFAM: Eberhardt RY, Haft DH, Punta M, Martin M, O’Donovan C, BatemanA. 2012. AntiFam: a tool to help identify spurious ORFs in protein annotation. Database, Bas003.</p> <p>- RNAcode: Washietl S, Findeiss S, Müller SA, Kalkhof S, von Bergen M, Hofacker IL, Stadler PF, Goldman N. 2011. RNAcode: robust discrimination of coding and noncoding regions in comparative sequence data. RNA 17(4):578-94.<br> </p>
Not the silver bullet: assessing the effects of silver-containing antimicrobial showerheads on the drinking water microbiome
<p>Demultiplexed fastq files used for sequencing analysis, processed taxonomy read data for all samples and controls, and relevant environmental metadata as described in "Not the silver bullet: assessing the effects of silver-containing antimicrobial showerheads on the drinking water microbiome".</p>
A new in vitro blood flow model for the realistic evaluation of antimicrobial surfaces
<p>Dataset to the publication</p> <p>A new <em>in vitro</em> blood flow model for the realistic evaluation of antimicrobial surfaces</p> <p>Juliane Valtin, Stephan Behrens, André Ruland, Florian Schmieder, Frank Sonntag, Lars D. Renner, Manfred F. Maitz, Carsten Werner</p> <p><em>Adv. Healthcare Mater.</em> 2023, 2301300. <a href="https://doi.org/10.1002/adhm.202301300">https://doi.org/10.1002/adhm.202301300</a></p>
Stimuli Responsive and Antimicrobial Cellulose-Chitosan Hydrogels Containing Polydiacetylene Nanosheets
<p>Hydrogels were prepared by esterification of chitosan (Cs) with monochloroacetic acid to produce CMCs which was then crosslinked to HEC using citric acid as the crosslinking agent. To impart a stimuli responsiveness property to the hydrogels, polydiacetylene-zinc oxide (PDA-ZnO) nanosheets were synthesized in-situ during the crosslinking reaction followed by photopolymerization of the resultant composite. First, 10,12-pentacosadiynoic acid (PCDA) head groups were stabilized with ZnO nanoparticles in the presence of CMCs-HEC hydrogels in petroleum ether. This was followed by irradiating the composite with Uv radiation to photopolymerize the PCDA to PDA within the hydrogel matrix so as to impart thermal and pH responsiveness to the hydrogel</p>
Population pharmacokinetic studies of critically ill adults receiving beta-lactam antimicrobials: covariate dataset
<p>A dataset of reported covariates from a systematic review of population pharmacokinetic studies of critically ill adults receiving beta-lactam antimicrobials, including R script of statistical and graphical analyses</p>
In vitro Evaluation of Biofield Treatment on Enterobacter cloacae: Impact on Antimicrobial Susceptibility and Biotype
<p>This research work investigated the influence of biofield treatment on <em>Enterobacter cloacae</em> (ATCC 13047) against antimicrobial susceptibility. Two sets of ATCC samples were taken in this experiment and denoted as A and B. ATCC A sample was revived and divided into two parts Gr. I (control) and Gr. II (revived); likewise, ATCC B was labeled as Gr. III (lyophilized). Group II and III were given with biofield treatment. The control and treatment groups of E. cloacae cells were tested with respect to antimicrobial susceptibility, biochemical reactions pattern and biotype number. The result showed significant decrease in the minimum inhibitory concentration (MIC) value of aztreonam and ceftazidime (≤ 8 μg/mL), as compared to control group (≥ 16 μg/mL). It was observed that 9% reaction was altered in the treated groups with respect to control out of the 33 biochemical reactions. Moreover, biotype number of this organism was substantially changed in group II (7731 7376) and group III (7710 3176) on day 10 as compared to control (7710 3376). The result suggested that biofield treatment had an impact on <em>E. cloacae</em> with respect to antimicrobial susceptibility, alteration of biochemical reactions pattern and biotype.</p> <p><strong>Source:</strong></p> <ul> <li><a href="https://www.trivedieffect.com/science/in-vitro-evaluation-of-biofield-treatment-on-enterobacter-cloacae-impact-on-antimicrobial-susceptibility-and-biotype">https://www.trivedieffect.com/science/in-vitro-evaluation-of-biofield-treatment-on-enterobacter-cloacae-impact-on-antimicrobial-susceptibility-and-biotype</a></li> <li><a href="https://www.omicsonline.org/open-access/in-vitro-evaluation-of-biofield-treatment-on-enterobacter-cloacae-impact-onantimicrobial-susceptibility-and-biotype-2155-9597-1000241.php?aid=60445">https://www.omicsonline.org/open-access/in-vitro-evaluation-of-biofield-treatment-on-enterobacter-cloacae-impact-onantimicrobial-susceptibility-and-biotype-2155-9597-1000241.php?aid=60445</a></li> </ul>
Antimicrobial resistance - Salmonella, E. Coli, prevalence ESBL data
<p>The database contains the evidence presented by the Data Visualization tool (available on EFSA website) accompanying the publication of the 2015 European Union Summary Report on antimicrobial resistance (AMR). Data correspond to occurrence of resistance in Salmonella from animals and humans, occurrence of resistance in E. Coli in animals and prevalence of ESBL-producing E.coli in animals and meat, in EU Member States.</p> <p>Format XLSX; Contact zoonoses_support@efsa.europa.eu (EFSA); FWD@ecdc.europa.eu (ECDC)</p> <p> </p>
Antimicrobial resistance - Salmonella, E. Coli, prevalence ESBL data
<p>The database contains the evidence presented by the Data Visualization tool (available on EFSA website) accompanying the publication of the 2015 European Union Summary Report on antimicrobial resistance (AMR). Data correspond to occurrence of resistance in Salmonella from animals and humans, occurrence of resistance in E.Coli in animals and prevalence of ESBL-producing E.coli in animals and meat, in EU Member States.</p> <p> </p> <p><strong>Format XLSX; Contact zoonoses_support@efsa.europa.eu (EFSA); FWD@ecdc.europa.eu (ECDC)</strong></p>
Comparison of Leaves and Stem Aqueous Extract of Tridax Procumbens for Antimicrobial Activity
<p>In present study, aq. extracts of leaves and stem part of Tridax Procumbens were compared for antimicrobial activity. Firstly, all organoleptic and physicochemical properties of leaves and stem powder were evaluated and it shows that drug is pure and having required constituents sufficiently. Aq. extract of leaves powder and stem powder was prepared separately using Soxhlet extraction technique. Both the extracts were evaluated for physiochemical screening using standard procedures. Aq. extract of leaves shows presence of tannis, saponins, anthocyanin, coumarins, alkaloids, proteins, amino acids, diterpenes, phytosterol, cardial glycosides, phlobatannins and flavonoids. Aq. extract of stem shows presence of tannins, coumarins, phenol, cardial glycosides and flavonoids. Both extracts were primarily evaluated for antimicrobial activity against E.coli and S. aureus by selecting dose of 500 mg. Finally, antimicrobial assay was performed for both extracts (500mg) against E.coli and S. aureus by well diffusion method using Amoxicillin and Amikacin as standards respectively. Antimicrobial assay shows that aq. extract of stem part is more effective against S. aureus than E.coli; leaves aq. extract also shows antimicrobial activity against S .aureus and E.coli. From present studies we can conclude that aq. extract of stem and leaves of Tridax Procumbens having antimicrobial activity and stem extract is more effective against S. aureus as compared to leaf extract. </p>
Antimicrobial Stewardship & Patient Safety Improvements: Introducing the NIVAS Line Flushing Guidance
<p>Recent published literature highlights that as much as 35% [1] of medication may remain in the infusion line as residual volume. The line is not commonly flushed outside of paediatric and oncology settings and therefore the total prescribed dose is not administered to patients, and this residual medication is discarded, raising the issue of underdosing. [2]</p><p> </p><p>At Salisbury NHS Foundation Trust, the Medical Device Management Services team is actively working towards improving patient safety and recovery through antimicrobial stewardship and compliance with new NIVAS guidelines [3]. We were keen to understand the implications of current intravenous administration practice at our Trust. We were particularly interested in assessing the prevalence and extent to which patients are underdosed, and the cost implications of discarded medication.</p>
Human antimicrobial peptide inactivation mechanism of enveloped viruses
<p>This dataset provides the raw data supporting the paper: Human antimicrobial peptide inactivation mechanism of enveloped viruses. <a href="https://doi.org/10.1016/j.jcis.2023.11.055">https://doi.org/10.1016/j.jcis.2023.11.055</a></p><p>It comprises the infectivity data (Figure 1), DLS data (Figure 2 and Figures S1-5), cryo-TEM images (Figure 2), SAXS data (Figure 3), SANS data (Figure 3), and the Zeta-potential measurement (in text).</p><p>Setup and conditions for the experiments are described in the experimental section of the published (open access) manuscript.</p>
Supplementary material Comparative Genomic Analysis of Antimicrobial-Resistant Escherichia coli from South American Camelids in Central Germany
<p>Supplementary material for publication González-Santamarina, B.; Weber, M.; Menge, C.; Berens, C. Comparative Genomic Analysis of Antimicrobial-Resistant <i>Escherichia coli</i> from South American Camelids in Central Germany. <i>Microorganisms</i> <strong>2022</strong>, <i>10</i>, 1697. https://doi.org/10.3390/microorganisms10091697 </p>
Dataset for article: Antimicrobial peptide induced colloidal transformations in bacteria-mimetic vesicles: Combining in silico tools and experimental methods
<p><strong>Dataset for publication:</strong></p><p>Antimicrobial peptide induced colloidal transformations in bacteria-mimetic vesicles: Combining in silico tools and experimental methods<br><i>Rafael V.M. Freire, Yeny Pillco-Valencia, Gabriel C.A. da Hora, Madeleine Ramstedt, Linda Sandblad, Thereza A. Soares, Stefan Salentinig</i><br>Journal of Colloid and Interface Science Volume 596, 15 August 2021, Pages 352-363 https://doi.org/10.1016/j.jcis.2021.03.060</p><p>Setup and conditions for the experiments are described in the experimental section of the published (open access) manuscript.</p><p>Data description in README.txt file.</p>
ScienceDex guides
Understand access before you commit
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.