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1,111 results for “nanoparticles”
Silica Nanoparticles Enhance Disease Resistance in Arabidopsis Plants - RAW DATA
<p>These datasets are used to produce the figures/graphs published in our article</p> <p><strong>Silica Nanoparticles Enhance Disease Resistance in <em>Arabidopsis</em> Plants</strong></p> <p>in <em>Nat. Nanotechnol.</em> (2020). <a href="https://doi.org/10.1038/s41565-020-00812-0">https://doi.org/10.1038/s41565-020-00812-0</a></p> <p> </p><p><strong>Correspondence: </strong></p> <p></p> <p>fabienne.schwab@alumni.ethz.ch, Tel: +41 78 736 00 19;</p> <p>m.shetehy@uky.edu, Tel. +41 76 455 56 02</p> <p>Further raw data related to qPCR and microbiology are available upon reasonable request from M.H. El‑Shetehy.</p> <p>Further raw data related to the nanoparticles and plant microscopy are available upon reasonable request by F. Schwab.</p> <p> </p> <p><strong>Abstract</strong></p> <p>In plants, pathogen attack can induce an immune response known as systemic acquired resistance (SAR) that protects against a broad spectrum of pathogens. In the search for safer agrochemicals, silica nanoparticles (SiO<sub>2</sub>‑NPs, food additive E551) have recently been proposed as a new tool. However, initial results are controversial, and the molecular mechanisms of SiO<sub>2</sub>‑NP-induced disease resistance are unknown. Here, we show that SiO<sub>2</sub>‑NPs, as well as soluble orthosilicic acid (Si(OH)<sub>4</sub>), can induce SAR in a dose-dependent manner, that involves the defence hormone salicylic acid. Nanoparticle uptake and action occurred exclusively through stomata (leaf pores facilitating gas exchange) and involved extracellular adsorption in leaf air spaces of the spongy mesophyll. In contrast to treatment with SiO<sub>2</sub>‑NPs, induction of SAR by Si(OH)<sub>4 </sub>was problematic, since high concentrations caused stress. We conclude that SiO<sub>2</sub>‑NPs have the potential to serve as an inexpensive, highly efficient, safe, and sustainable alternative for plant disease protection.</p>
Dataset of "MoO3-xNiMoO4 nanorods synthetized using NiO nanoparticles for hydrogen evolution in anion exchange membrane water electrolysis"
<p>Novel method of Mo-Ni catalyst for hydrogen evolution reaction in anion exchange membrane water electrolysis was used. Complete physico-chemical and electrochemical characterization was done. Prepared material showed enhanced performance when compared to the similar Ni based materials. Physico-chemical characterization showed, that final material is formed by NiMoO4 nanorods coverd on the surface by the layer of the MoO3-x.</p>
Experimental data for "Deep Learning Methods for Colloidal Silver Nanoparticle Concentration and Size Distribution Determination from UV-Vis Extinction Spectra"
<p>Testing data (experimental data) for neural networks published in preprint https://doi.org/10.48550/arXiv.2404.10891</p> <p>The UV-VIS-NIR spectral data was also used in the dissertation of Nadzeya Khinevch, titled "Two-dimensional structures of nanoparticles for elements of surface-enhanced Raman scattering substrates".</p> <p>Emails of the corresponding authors:</p> <p>Tomas Klinavičius tomas.klinavicius@ktu.lt</p> <p>Tomas Tamulevičius tomas.tamulevicius@ktu.lt</p>
Concentration of nanoparticles per mL for water samples collected from Venice Lagoon
<p>The concentration of nanoparticles from surface seawater collected from the three sites of Venice Lagoon, Venice-Lido Port Inlet, Grand Canal under Rialto Bridge, and Saint Marc basin was analyzed via the Nanoparticle Tracking Analysis technique. Five replications were tested for each sample. Sampling locations: Venice-Lido Port Inlet, GPS coordinates: latitude: 45.431508, longi-tude: 12.406952; Grand Canal under Rialto Bridge, GPS coordinates: latitude: 45.438350, longitude: 12.336311; and Saint Marc basin, GPS coordinates: latitude: 45.431962, longitude: 12.340953.</p>
Raw Particle Number Size-Distribution Data of twin-DMPS equipped with two CPCs for nanoparticle detection for SMEAR II station, Hyytiälä, Finland, Spring 2017
<p>Raw size-Distribution data from twin-DMPS system (Aalto et al., 2001), where the nano-DMA (measuring up to 40 nm, short Hauke type DMA) is quipped with two detectors:<br> a TSI 3776 and a modified Airmodus A20 (Kangasluoma et al., 2015)</p> <p>Data acquired during in March-May 2017 at the SMEAR II station in Hyytiälä, Finland.<br> Data associated with the publication Stolzenburg, Laurila et al. (2023), Atmos. Meas. Techn., "Improved counting statistics of an ultrafine differential mobility particle size spectrometer system"</p> <p>Files DMYYDDMM_A20.Dat contain the raw DMPS data, with YYMMDD indicating the day of the measurement.<br> Data are provided alternating between data acquired with the nano-DMA and with the long-DMA, on a scan by scan basis.<br> First line of each scan cycle (for both DMAs) always indicates the start and end times of the voltage scan.<br> Second line gives the parameters related to the DMPS as given below:<br> (sheath flow in [l per min], aerosol flow in [l per min], DMA inner electrode diameter in [m], DMA outer electrode diameter in [m], DMA classification length in [m], other parameters)<br> Following lines give<br> (for long-DMA): set voltage at DMA [in V], concentration measured by TSI3772 in [per cm3]<br> (for nano_DMA): et voltage at DMA [in V], concentration measured by TSI 3776 in [per cm3], concentration measured by mod. Airmodus A20 in [per cm3]</p> <p>File dmps_data_format_specifier.text gives a conversion from voltage to diameter and indicates the measurement time at each voltage during the stepping of the DMPS.<br> Needs to be used to convert measured concentrations in counts per set-interval.</p> <p>Files GR_J_overview.xlsx gives size-distribution derived quantities during that campaign.<br> Header defines Date, Growth Rate and Formation Rate measured at different sizes [in nm] and by the two different CPCs connected to the nano-DMA.<br> Growth rates in [nm per h], formation rate in [per cm3 per s].</p> <p>Other data related to the campaign can be obtained from the corresponding author upon reasonable request.<br> juha.kangasluoma@helsinki.fi</p> <p>References:</p> <p>Stolzenburg, Laurila et al. "Improved counting statistics of an ultrafine differential mobility particle size spectrometer system",<br> Atmos. Meas. Techn., in press, 2023</p> <p>Aalto et al., "Physical characterization of aerosol particles during nucleation events",<br> Tellus B, vol. 53, pp. 344-358, 2001</p> <p>Kangasluoma et al., "Sub-3 nm Particle Detection with Commercial TSI 3772 and Airmodus A20 Fine Condensation Particle Counters",<br> Aerosol Sci. Techn., vol. 49, pp. 674-681, 2015</p>
Magnetic hyperthermia with e-Fe2O3 nanoparticles
<p>These data correspond to the figures in the paper: Gu Y. et al. RSC Adv., 2020, 10, 28786–28797. doi:10.1039/d0ra04361c.</p>
BAM reference data: XPS raw data of Al-coated titania nanoparticles (JRCNM62001a and JRCNM62002a)
<p>The raw data are given as VAMAS-File. The measurement condtions are given in the file. The C1s-fits are provided as ascii-files.</p> <p>For further information please look at Radnik, J. Kersting, R., Hagenhoff, B., Bennet, F., Ciornii, D.; Nymark, P., Grafström R. and Hodoroaba, V.-D. <em>Nanomaterials </em><strong>2021</strong>, <em>11</em>, 639. https://doi.org/10.3390/nano11030639.</p> <p>The transmission function is obtained as ascii-file trm.dat. The energy scale is kinetic energy.</p> <p> </p> <p>Measurement conditions:</p> <p>XPS measurements were performed at an Axis Ultra DLD (KRATOS, Manchester, UK) with monochromatic Al K radiation (E = 1486.6 eV). The electron emission angle was 0° and the source-to-analyzer angle was 60°. The binding energy scale of the instrument was calibrated following a Kratos analytical procedure, which uses ISO 15472 binding energy data. The setting of the instrument was the hybrid lens mode and the slot mode with an analysis area of approximately 300x700 m². Furthermore, charge neutralization with a flood gun was used. All spectra were recorded in the fixed analyzer transmission (FAT) mode. The samples were measured as powders prepared on a special stainless-steel sample holder.</p> <p> </p> <p> </p> <p> </p>
Combined continuous nanoparticle synthesis with chromatographic size classification
<p>In this paper, we report a combination of the continuous flow synthesis of gold nanoparticles (AuNPs) with subsequent purification and narrowing of the particle size distribution (PSD) by size-exclusion chromatography (SEC) by adapting the flow rates of synthesis and classification. First, we show scalability of chromatographic classification with respect to column dimension and the absence of irreversible nanoparticle adhesion on the column material. Two different syntheses lead to a large and widely distributed and a small and narrowly distributed AuNP dispersion, which are classified by a semipreparative column. The PSDs of individual fractions are characterized by analytical SEC. The broadly distributed AuNP dispersion was classified into three fractions with distinct PSDs. For the narrowly distributed AuNPs, the separation is almost independent of the mobile phase flow rate: coarse and fine fractions with almost identical PSDs and separation efficiency curves are observed irrespective of the flow rate. Even NP samples with narrow PSDs can be classified into multiple fractions with tailored PSDs while simultaneously removing dissolved impurities from the dispersion. With our study, we demonstrate the potential of a direct combination of continuous NP synthesis with chromatographic classification for the optimization of final PSDs and the simultaneous purification of nanoparticulate dispersions.</p><p>Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)– Project-ID 416229255 – SFB 1411</p>
Problems with nanoparticle tracking analysis (NTA) of urine extracellular vesicles (uEVs)
<p>Urinary extracellular vesicle (uEV) proteins may be used as specific markers of kidney damage in various pathophysiological conditions. The nanoparticle-tracking analysis (NTA) appears to be the most useful method for the analysis of uEVs due to its ability to analyze particles below 300 nm. The NTA method has been used to measure the size and concentration of uEVs and also allows for a deeper analysis of uEVs based on their protein composition using fluorescence measurements. However, despite much interest in the clinical application of uEVs, their analysis using the NTA method is poorly described and requires meticulous sample preparation, experimental adjustment of instrument settings, and above all, an understanding of the limitations of the method. We present the problems encountered during analysis with possible solutions: the choice of sample dilution, the method of the presentation and comparison of results, photobleaching, and the adjustment of instrument settings for a specific analysis.</p> <p> </p> <p>Figure 1. Expressions of specific markers CD63 in protein-standardized samples detected with Western blot analysis; anti-CD 63 (HPA010088, Sigma-Aldrich, Saint Louis, MO, USA, 1:1000); secondary antibodies conjugated to horseradish peroxidase (554021, BD Pharmingen (BD Biosciences, San Jose, CA, USA) 1:10000).</p> <p> </p> <p>Nanoparticle-Tracking Analysis of uEVs. A NanoSight NS300 instrument (Malvern Panalytical, Malvern, UK) was used to determine the concentrations and sizes of the uEVs in the samples. The total number of extracellular vesicles was measured during the continuous flow of samples delivered from a syringe pump.</p> <p>Figure 2. Determination of the size and concentration of uEVs: dilution factor—1:100; laser—405 nm.</p> <p>Figure 3. Effect of dilution on total number of particles per milliliter and size of uEVs in nanoparticle tracking analysis: sample dilutions—1:100, 1:500, and 1:1000; laser—488 nm.</p> <p>Figure 5. Fluorescence-based nanoparticle-tracking analysis of CD 63 expression in uEVs: without 500 nm long-pass filter; with 500 nm long-pass filter; comparison of sizes and concentrations of uEVs without and with 500 nm long-pass filter; dilution factor—1:100; laser—488 nm; anti-CD 63 (HPA010088, Sigma-Aldrich); secondary antibodies conjugated to Alexa Fluor 488 fluorescent dye (ab150073-500, Abcam, Cambridge, MA, USA).</p> <p>Figure 6. Fluorescence-based nanoparticle-tracking analysis of podocin expression in uEVs: without 500 nm long-pass filter; with 500 nm long-pass filter; comparison of sizes and concentrations of uEVs without and with 500 nm long-pass filter; dilution factor—1:100; laser—488 nm; anti-podocin (P0372, Sigma-Aldrich); secondary antibodies conjugated to Alexa Fluor 488 fluorescent dye (ab150073-500, Abcam, Cambridge, MA, USA).</p>
Data for: Temperature-controlled Molecular Bonding Hysteresis: Interphase Dynamics of a Nanoparticle-modified Polymer Network
<p>The data is supplementary to the publication "Temperature-controlled Molecular Bonding Hysteresis: Interphase Dynamics of a Nanoparticle-modified Polymer Network", DOI: <a title="DOI URL" href="https://doi.org/10.1021/acs.jpclett.4c00406">10.1021/acs.jpclett.4c00406</a></p> <p>Key words: Thermal volume expansion, Interphase dynamics, Temperature-modulated optical refractometry, Nanoparticles, Optical Remanence, Hysteresis, Refractive index</p> <p>The data sets contain measured and processed data on the interphase dynamics of a nanoparticle modified epoxy resin collected via Temperature-modulated optical refractometry (TMOR).</p> <p>Material details:</p> <ul> <li>Cycloaliphatic epoxy resin + Anhydride curing agent + 1-methylimidazole</li> <li>Core-shell rubber nanoparticles, 100 nm, dispersed in a cycloaliphatic epoxy carrier resin</li> </ul> <p>Funding received from:</p> <ul> <li>German Research Foundation (DFG), project number: 521902629.</li> </ul>
Bolaform Surfactant-Induced Au Nanoparticle Assemblies for Reliable Solution-Based Surface-Enhanced Raman Scattering Detection
<p>Related publication: García-Lojo, D; Méndez-Merino, D; Pérez-Juste, I; Acuña, A; García-Río, L; Rodríguez-Patón, A; Pastoriza-Santos, I; Pérez-Juste, J. Bolaform surfactant-induced Au nanoparticle assemblies for reliable solution-based SERS detection. Adv.Mater. Technol. 2022, 2101726. <a href="https://doi.org/10.1002/admt.202101726">https://doi.org/10.1002/admt.202101726</a></p> <p> </p> <p> </p> <p>Abstract:</p> <p>Solution-based surface-enhanced Raman scattering (SERS) detection typically involves the aggregation of citrate-stabilized Au nanoparticles into colloidal assemblies. Although this sensing methodology offers excellent prospects for sensitivity, portability, and speed, it is still challenging to control the assembly process by a salting-out effect, which affects the reproducibility of the assemblies and, therefore, the reliability of the analysis. This work presents an alternative approach that uses a bolaform surfactant, B<sub>20</sub>, to induce the plasmonic assembly. The decrease of the surface charge and the bridging effect, both promoted by the adsorption of B<sub>20</sub>, are hypothesized as the key points governing the assembly. Furthermore, molecular dynamic simulations supported the bridging effect of the B<sub>20</sub> by showing the preferential bridging of surfactant monomers between two adjacent Au(111) slabs. The colloidal assemblies showed excellent SERS capabilities towards the rapid, on-site detection and quantification of beta-blockers and analgesic drugs in the nanomolar regime, with a portable Raman device. Interestingly, the application of state-of-the-art convolutional neural networks, such as ResNet, allows a 100% accuracy in classifying the concentration of different binary mixtures. Finally, the colloidal approach was successfully implemented in a millifluidic chip allowing the automation of the whole process, as well as improving the performance of the sensor in terms of speed, reliability, and reusability without affecting its sensitivity.</p>
Bridging the gap between single nanoparticle imaging and global electrochemical response by correlative microscopy assisted by machine vision
<p>The data in this repository corresponds to experimental data: linear sweep voltammetry, optical movie and the database of the SEM images. They support the findings of a study discussed in the article by Godeffroy et al. published in Small Methods with the doi: http:/doi.org/10.1002/smtd.202200659. The data analysis to reproduce the results presented in the article has been carried out by homemade Python program routines also provided in this repository. The descirption of each routine is also provided in a text file.</p>
Atomistic trajectories from ab-initio molecular dynamics simulations of wetted TiO2 nanoparticle
<p>This repository contains atomistic trajectories from ab-initio molecular dynamics simulations of water and TiO2 nanoparticle described in the paper:</p> <p>E. G. Brandt, L. Agosta and A.P.Lyubartsev, " Reactive wetting properties of TiO2 nanoparticles predicted by ab initio molecular dynamics simulations", Nanoscale, 8, 13385-13398 (2016) DOI: 10.1039/c6nr02791a</p> <p>The trajectories are saved in the .xtc format, and initial structures with specification of atom types are given in the .pdb format.</p> <p>The name of each file contains brief information about the simulated system:</p> <p>TiO2 : composition of the nanoparticle<br> n24 : number of TiO2 units in the nanoparticle<br> anatase/brookite/rutile : type of crystall structure<br> - a number 0 - 30 : number of water molecules in the simulation<br> 2fs - the time step</p> <p>For more details, see the referred paper</p>
The Immunomodulatory Effect of Silver Nanoparticles in a Retinal Inflammatory Environment
<p>Activation of immune response plays an important role in the development of retinal diseases. One of the main populations of immune cells contributing to the retinal homeostasis are microglia, which represent a population of residential macrophages. However, under pathological conditions, microglia become activated and rather support a harmful inflammatory reaction and retinal angiogenesis. Therefore, targeting these cells could provide protection against retinal neuroinflammation and neovascularization. In the recent study, we analyzed effects of silver nanoparticles (AgNPs) on microglia in vitro and in vivo. We showed that the AgNPs interact in vitro with stimulated mouse CD45/CD11b positive cells (microglia/macrophages), decrease their secretion of nitric oxide and vascular endothelial growth factor, and regulate the expression of genes for Iba-1 and interleukin-1β (IL-1β). In our in vivo experimental mouse model, the intravitreal application of a mixture of proinflammatory cytokines tumor necrosis factor-α, IL-1β and interferon-γ induced local inflammation and increased local expression of genes for inducible nitric oxide synthase, IL-α, IL-1β and galectin-3 in the retina. This stimulation of local inflammatory reaction was significantly inhibited by intravitreal administration of AgNPs. The application of AgNPs also decreased the presence of CD11b/Galectin-3 positive cells in neuroinflammatory retina, but did not influence viability of cells and expression of gene for rhodopsin in the retinal tissue. These data indicate that AgNPs regulate reactivity of activated microglia in the diseased retina and thus could provide a beneficial effect for the treatment of several retinal diseases.</p>
Geometric Frustration Directs the Self-assembly of Nanoparticles with Crystallized Ligand Bundles
<p>This is the supporting dataset of the publication "Geometric Frustration Directs the Self-assembly of Nanoparticles with Crystallized Ligand Bundles".</p> <p><a href="https://doi.org/10.1021/acs.jpcb.4c04562">https://doi.org/10.1021/acs.jpcb.4c04562</a></p> <p>The description of the dataset can be found in the file README.txt</p>
Adsorption free energies and potentials of mean-force for interactions between amino acids, lipid fragments, and nanoparticles
<p>This dataset contains tabulated potentials of mean force (PMFs) and associated adsorption (binding) free energies for interactions of amino acids side chain analogues and lipid fragments (LF) with a range of materials: titanium dioxide, iron oxide, amorphous silica, quartz, and a range of carbon-based materials including amorphous carbon, graphene and carbon nanotubes both in a pristine form and functionalized by certain chemical groups. All data were computed from atomistic molecular dynamics simulations as a part of the SmartNanoTox project 2016-2020. Version 2 of the dataset includes additional materials: zink oxide, zink sulfate in pristine and PMMA-coated forms computed within NanoSolveIt project (2019-2023). The data are intended to be used in coarse-grained models describing interactions of nanomaterials with nanoparticles, for the prediction of the binding affinity of proteins and lipids to nanoparticles, and as biological "fingerprints" of nanomaterials characterizing behavior of the nanomaterials in biological environments. </p>
EXAFS and DRIFTS data collected during palladium hydride phase formation in supported palladium nanoparticles
<p>The dataset contains DRIFTS and EXAFS spectra measured under identical conditions at different hydrogen partial pressures with the presence of 0.5% CO in the gas flow. The first line in DRIFTS.dat file is the wavenumber in inverse cm, the following lines are the averaged spectra measured at different conditions. The first line in EXAFS.dat file is the energy in eV, the following lines are the averaged spectra measured at different conditions. File params.dat contain information about the sample temperature (Temperature column), hydrogen partial pressure (H pressure), number of cycle (each experiment was repeated 3 times), and the descriptors of DRIFTS spectra: FWHM, Area (Square) and positions of 8 gaussians, 3 positions of the maxima assigned to On top, Bridged and Hollow geometries of adsorbed CO molecules, and structural descriptors obtained from EXAFS: Pd-Pd interatomic distances (R), coordination numbers (N) and Debye-Waller parameters (ss) with corresponding errors.</p>
Synthetic magnetic nanoparticles for remote-controlled stemcell therapies of neurodegenerative disorders
<p>In the context of the MAGNEURON european project, we developed different types of magnetic nanoparticles that can act as nanoactuators to manipulate intracellular proteins involved in signaling pathways.</p> <p>Four types of particles are presented here. First, size-sorted maghemite cores of different diameter (8 to 20 nm) were synthesized. Then these cores were used to make Fe2O3@SiO2 core-shell nanoparticles that are colloidally stable and easy to functionalize, and poly(acrylic acid) coated nanoparticles. Both types of particles can be rendered fluorescent by the addition of a fluorophore. Finally, we also developed a way to synthesize micro-needles made of aligned maghemite cores encapsulated in a silica layer.</p> <p>In this dataset are presented some electron microscopy images of the optimized particles and their characterizations in terms of sizes and magnetic properties. These particles have then been used by the other members of the Magneuron consortium in order to manipulate different intracellular signalling pathways.</p>
RECODE_DS19.Toxicological profile of calcium carbonate nanoparticles for industrial applications
<p>The documentation will include: for the <em>in vitro</em> and <em>in vivo </em>studies all the data acquired after the exposure of cells or zebrafish to the nano-sized CaCO3 particles.</p>
Effect of superparamagnetic iron oxide nanoparticles on glucose homeostasis on type 2 diabetes experimental model
<p>The data correspond to figures in the paper by Ali, L.M.A. et al. Life Sciences 245 (2020) 117361. doi:10.1016/j.lfs.2020.117361.</p>
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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.
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.