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Dataset results
13 results for “Particle Identification”
LHCb Particle Identification Compression Challenge
<p>A dataset containing Particle Identification information for a challenge to compress the contained features. </p> <p>An example of how to use this dataset and a compression benchmark is given here: https://github.com/weissercn/LHCb_PID_Compression</p> <p>-999 is the missing value identifier.</p> <p>The goal is to compress features with the name of the form S[n]x[m], where [n] and [m] are integers. Features of the form S[n]aux[m], where [n] and [m] are integers, contain information present at any time during compression and decompression. These features do not have to be compressed. The feature labelled 'pid' is the truth information of which type of particle an example is. This information is not present in real running conditions, is not present during either compression or decompression and can only be used to evaluate how well the autoencoder did. An example of this is in the example code.<br> </p>
All black: a microplastic extraction combined with colour-based analysis allows identification and characterisation of tire wear particles (TWP) in soils
<p>The present file contains the information collected on particles analyzed in the study:</p> <p><em><strong><span><span><span><span><span><span>All black: a microplastic extraction combined with colour-based analysis allows identification and characterisation of tire wear particles (TWP) in soil</span></span></span></span></span></span><span>s</span></strong></em></p> <p><span>published in the Microplastics and Nanoplastics journal in 2024. </span></p> <p><span>The first sheet of the excel file contains the data, the second sheet contains the description of the data and the parameters recorded. </span></p>
Data from: Particle backtracking improves breeding subpopulation discrimination and natal-source identification in mixed populations
We provide a novel method to improve the use of natural tagging approaches for subpopulation discrimination and source-origin identification in aquatic and terrestrial animals with a passive dispersive phase. Our method integrates observed site-referenced biological information on individuals in mixed populations with a particle-tracking model to retrace likely dispersal histories prior to capture (i.e., particle backtracking). To illustrate and test our approach, we focus on western Lake Erie's yellow perch (Perca flavescens) population during 2006–2007, using microsatellite DNA and otolith microchemistry from larvae and juveniles as natural tags. Particle backtracking showed that not all larvae collected near a presumed hatching location may have originated there, owing to passive drift during the larval stage that was influenced by strong river- and wind-driven water circulation. Re-assigning larvae to their most probable hatching site (based on probabilistic dispersal trajectories from the particle backtracking model) improved the use of genetics and otolith microchemistry to discriminate among local breeding subpopulations. This enhancement, in turn, altered (and likely improved) the estimated contributions of each breeding subpopulation to the mixed population of juvenile recruits. Our findings indicate that particle backtracking can complement existing tools used to identify the origin of individuals in mixed populations, especially in flow-dominated systems.
Data from: Particle backtracking improves breeding subpopulation discrimination and natal-source identification in mixed populations
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Genome-wide identification and analysis of A-to-I RNA editing events in the malignantly transformed cell lines from BEP2D induced by α-particles radiation
GEO Series GSE126723. Homo sapiens. 9 samples. Type: Other.
Delayed Cardiomyocyte Response to Total Body Particle Radiation Exposure – Identification of Regulatory Gene Network [proton]
GEO Series GSE68875. Mus musculus. 15 samples. Type: Expression profiling by array.
Delayed Cardiomyocyte Response to Total Body Particle Radiation Exposure - Identification of Regulatory Gene Network
GEO Series GSE68876. Mus musculus. 30 samples. Type: Expression profiling by array.
Identification of a dose of diesel exhaust particles that is sufficient to induce significant DNA methylation changes in A549 cells after four weeks of exposure.
GEO Series GSE267214. Homo sapiens. 10 samples. Type: Methylation profiling by array.
Identification of distinct cytotoxic granules as the origin of supramolecular attack particles in T lymphocytes
<p>Cytotoxic T lymphocytes (CTLs) kill malignant and infected cells through the directed release of cytotoxic proteins into the immunological synapse. The cytotoxic protein granzyme B (GzmB) is released in its soluble form or in supramolecular attack particles (SMAPs). We utilized synaptobrevin2-mRFP knock-in mice to isolate fusogenic cytotoxic granules in an unbiased manner and visualize them alone or in degranulating CTLs. We identified two classes of fusion-competent granules, single core granules (SCGs) and multi core granules (MCGs), with different diameter, morphology and protein composition. Functional analyses demonstrate that both classes of granules fuse with the plasma membrane at the IS. SCG fusion released soluble GzmB. MCGs can be labelled with the SMAP marker thrombospondin-1 and their fusion released intact SMAPs. We envision that CTLs use SCG fusion to fill the synaptic cleft with active cytotoxic proteins instantly and parallel MCG fusion to deliver latent SMAPs for delayed killing of refractory targets.</p>
Delayed Cardiomyocyte Response to Total Body Particle Radiation Exposure – Identification of Regulatory Gene Network [iron]
GEO Series GSE68874. Mus musculus. 15 samples. Type: Expression profiling by array.
Delayed Cardiomyocyte Response to Total Body Particle Radiation Exposure - Identification of Regulatory Gene Network [iron]
We examined molecular responses using transcriptome profiling in isolated left ventricular murine cardiomyocytes to 90 cGy, 1 GeV proton (1H) and 15 cGy, 1 GeV/nucleon (n) iron (56Fe) particles 1, 3, 7, 14 and 28 days after exposure. Unsupervised clustering analysis of gene expression segregated samples according to the radiation (IR) response, and time after exposure with 56Fe-IR showing the greatest level of gene modulation. 1H-IR exposures showed little differential transcript modulation. Network analysis categorized the major differentially expressed genes into cell cycle, oxidative responses and transcriptional regulation functional groups. Transcriptional networks identified key nodes regulating expression. Individual transcription factors were inferred to be active at 1, 3, 7, 14 and 28 days after exposure. Validation of the signal transduction network by protein analysis showed that particle IR clearly regulates a long lived signaling mechanism for p38 MAPK signaling and NFATc4 activation. Electrophoresis mobility shift assays supported the role of additional key transcription factors GATA-4, STAT-3 and NF-kB as regulators of the response at specific time points. These data suggest that the molecular response to 56Fe-IR is unique and shows long-lasting gene expression in cardiomyocytes, up to 28 days after exposure. Additionally, proteins involved in signal transduction and transcriptional activation via DNA binding play a role in the response to high charge (Z) and energy (E) particles (HZE). Our study may have implications for NASA's efforts to develop heart disease risk estimates for astronauts safety via identification of specific HZE-IR molecular markers and for patients receiving conventional and particle radiotherapy. Transcriptome profiling in isolated left ventricular murine cardiomyocytes to 90 cGy, 1 GeV proton (1H) and 15 cGy, 1 GeV/nucleon (n) iron (56Fe) particles 1, 3, 7, 14 and 28 days after exposure.
Delayed Cardiomyocyte Response to Total Body Particle Radiation Exposure - Identification of Regulatory Gene Network [proton]
We examined molecular responses using transcriptome profiling in isolated left ventricular murine cardiomyocytes to 90 cGy, 1 GeV proton (1H) and 15 cGy, 1 GeV/nucleon (n) proton (56Fe) particles 1, 3, 7, 14 and 28 days after exposure. Unsupervised clustering analysis of gene expression segregated samples according to the radiation (IR) response, and time after exposure with 56Fe-IR showing the greatest level of gene modulation. 1H-IR exposures showed little differential transcript modulation. Network analysis categorized the major differentially expressed genes into cell cycle, oxidative responses and transcriptional regulation functional groups. Transcriptional networks identified key nodes regulating expression. Individual transcription factors were inferred to be active at 1, 3, 7, 14 and 28 days after exposure. Validation of the signal transduction network by protein analysis showed that particle IR clearly regulates a long lived signaling mechanism for p38 MAPK signaling and NFATc4 activation. Electrophoresis mobility shift assays supported the role of additional key transcription factors GATA-4, STAT-3 and NF-kB as regulators of the response at specific time points. These data suggest that the molecular response to 56Fe-IR is unique and shows long-lasting gene expression in cardiomyocytes, up to 28 days after exposure. Additionally, proteins involved in signal transduction and transcriptional activation via DNA binding play a role in the response to high charge (Z) and energy (E) particles (HZE). Our study may have implications for NASA's efforts to develop heart disease risk estimates for astronauts safety via identification of specific HZE-IR molecular markers and for patients receiving conventional and particle radiotherapy. Transcriptome profiling in isolated left ventricular murine cardiomyocytes to 90 cGy, 1 GeV proton (1H) and 15 cGy, 1 GeV/nucleon (n) proton (56Fe) particles 1, 3, 7, 14 and 28 days after exposure.
Identification of novel potential biomarkers and signaling pathways related to otitis media induced by diesel exhaust particle in in vivo system via transcriptomic analysis
GEO Series GSE86844. Mus musculus. 4 samples. Type: Expression profiling by array.
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