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10 results for “gas chromatography mass spectrometry”
Liquid Chromatography - Tandem Mass Spectrometry (LC-MS/MS) and Gas Chromatography - Mass Spectrometry (GC-MS) Reference Libraries from Global Natural Products Social Molecular Networking (GNPS) and National Institute of Standards and Technology (NIST) WebBook Processed for Spectral Library Matching
<div>In order to obtain a high-quality LC-MS/MS reference database for spectral library matching, we selected 22 high-quality GNPS tandem mass spectrometry databases generated under the positive ion mode. Further preprocessing similar to Huber et al involving mass-to-charge (m/z) and intensity filtering yields the database found in the file LCMS_GNPS_reference_library.csv which contains 14,705 electrospray ionization (ESI) mass spectra, each of which corresponds to a unique compound. The NIST WebBook database was used to construct GC-MS database contained in the file GCMS_NIST_WebBook.csv. This database contains 23,721 electron ionization (EI) mass spectra, each of which corresponds to a unique non-hyphenated Chemical Abstract Service (CAS) Registry Number.</div> <div> </div> <div>Both LC-MS/MS and GC-MS databases are organized into three columns: one for the identifier, one for the m/z values, and one for the intensity values. For example, if spectrum A has 20 ion fragments, then there will be 20 rows corresponding to spectrum A in the corresponding database with the identifier A repeated 20 times with the corresponding m/z and intensity values.</div>
Data from: Normalizing gas-chromatography–mass spectrometry data: method choice can alter biological inference
<p>Gas-Chromatography Mass Spectrometry data from European badger (<em>Meles meles</em>) sub-caudal gland secretion used in:</p> <p>Noonan, M.J., Tinnesand, H.V.,<sup> </sup>and Buesching, C.D. (2018). Normalizing gas-chromatography–mass spectrometry data: method choice can alter biological inference. BioEssays, 40(6): 0-0. DOI: 10.1002/bies.201700210.</p>
Dataset for the optimization and validation of a gas chromatography-mass spectrometry method to analyze acetate, propionate and butyrate in the systemic circulation.
<p>This dataset contains data about the optimization and validation of a gas chromatography method to analyze acetate, propionate and butyrate in blood. Validation parameters include linearity, precision, accuracy and recovery. The method's applicability was demonstrated with the analysis of the short-chain fatty acids in human blood samples that were collected in a dietary intervention study.</p>
Novel Insights into the Bioactive Metabolites of Macrocybe gigantea (Massee) Pegler & Lodge, a Wild Edible Macrofungi Using Gas Chromatography Mass Spectrometry (GC-MS) Combined with Chemoinformatics Approaches
<p><em>Macrocybe gigantea </em>(MG) is an edible mushroom and has multiple pharmacological activities such as antibacterial, antioxidant, and antitumor activities. However, only a few reports were available on the bioactive compounds and bioactivity of this mushroom. In this concern, the present study was aimed to explore the unique chemical diversity from the fruiting body of MG<em>. </em>The species identification was done accurately with morphological and molecular methods followed by mycochemical extraction in different solvent systems. The ethanolic extract of the fruiting body gave maximum yield and its Gas Chromatography-Mass Spectrometry (GC-MS) analysis was performed along with antibacterial activity and cell viability by MTT assay. The GC-MS analysis revealed 50 metabolites and further chemoinformatics analysis of these metabolites revealed their possible biological activities. In addition, the mushrooms' physico-chemical and mineral element analysis revealed the quality and authenticity of the species. Altogether, the current investigation gives a comprehensive overview of the bioactive metabolites of MG.</p>
Data and code for "Large volume injection and assessment of reference standards for n-alkane δD and δ13C analysis via gas chromatography isotope ratio mass spectrometry"
<p>This file includes data and code related ot the publication, "<span>Large volume injection and assessment of reference standards for <em>n</em>-alkane δD and δ<sup>13</sup>C analysis via gas chromatography isotope ratio mass spectrometry" in Rapid Communications in Mass Spectrometry (in review). Included are datasets of <em>n</em>-alkane δD and δ<sup>13</sup>C measurements with a recently developed large-volume injeciton method. Measuremtns of reference standards and lake sediment samples from Eifel maar lakes of Germany are included. Additionally, code to implement the correction schemes and reporduce the figures and analysis described in the paper are included. </span></p>
Fig. 2 in Global metabolome analysis of Dunaliella tertiolecta, Phaeobacter italicus R11 Co-cultures using thermal desorption - Comprehensive two-dimensional gas chromatography - Time-of-flight mass spectrometry (TD-GC×GC-TOFMS)
Fig. 2. Workflow for sample preparation and injection. Culture samples were filtered and dried (A–B). Dried filter papers were placed in clean vials (C) and then resuspended in methanol (D) before being extracted with Chloroform (E). Water was added (F) and subsequently, the chloroform layer was aliquotted into GC vials (G) for further sample preparation. Extracts were dried (H) and then derivatized using a two-step methoximation/silylation process to yield derivatized extracts (I). 9-μL aliquots of derivatized extracts were automatically transferred to microvial inserts in thermal desorption tubes for injection (J) using an initial solvent vent step to remove excess solvent and derivatisation reagents (K), followed by thermal desorption to a cooled PTV inlet and subsequent splitless injection to the GC × GC-TOFMS system. Non-volatile residues from the extracts remained in the microvial insert for subsequent disposal (L). See text for details.
Fig. 4 in Global metabolome analysis of Dunaliella tertiolecta, Phaeobacter italicus R11 Co-cultures using thermal desorption - Comprehensive two-dimensional gas chromatography - Time-of-flight mass spectrometry (TD-GC×GC-TOFMS)
Fig. 4. From left to right: results of principal component analysis of the raw data (autoscaled), similarly scaled data normalised to class-specific TUPA, and the normalised, scaled data using the selected features from the FS-CR routine. Quality control samples were not included in the feature selection routine, and are displayed as filled icons connected to their corresponding replicate with a straight line, following projection into the optimised principal component space. Confidence ellipses were drawn about each sample class for a confidence interval of 0.95. Note the convention: DUN refers to D. tertiolecta samples, CO refers to co-culture samples, and BAC refers to P. italicus R11 samples.
Fig. 3 in Global metabolome analysis of Dunaliella tertiolecta, Phaeobacter italicus R11 Co-cultures using thermal desorption - Comprehensive two-dimensional gas chromatography - Time-of-flight mass spectrometry (TD-GC×GC-TOFMS)
Fig. 3. Example Total Ion Current (TIC) chromatograms from each sample class.
Figure 4 in Analysis of amino acids, fatty acids and neurotoxins using gas chromatography-mass spectrometry in four scorpions species inhabiting New Valley Governorate, Egypt
Figure 4. GC-MS chromatogram of Buthacus leptochelys.
Fig. 1 in Global metabolome analysis of Dunaliella tertiolecta, Phaeobacter italicus R11 Co-cultures using thermal desorption - Comprehensive two-dimensional gas chromatography - Time-of-flight mass spectrometry (TD-GC×GC-TOFMS)
Fig. 1. Cross validated receiver operator characteristics suggest that the calculated model is robust, and improves with more iterations. Light blue lines show the results of further iterations, and red lines show the results of fewer iterations. Each line is semi-transparent, but the AUC is close to 1 in all cases. Calculation of the classification scores was based off the named class (Class 1), versus everything else (Class 0). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
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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.
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DANDI Archive for NWB datasets
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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.