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2,394 results for “ms”
In vitro shoot regeneration and root induction of Hylocereus polyrhizus 'Da Hong' from Murashige and Skoog (MS) medium supplemented with 0.05–0.20 mg/L α-naphthaleneacetic acid (NAA).
<p>Figure S1. <em>In vitro </em>shoot regeneration and root induction of <em>Hylocereus polyrhizus</em> ‘Da Hong’ from Murashige and Skoog (MS) medium supplemented with 0.05–0.20 mg/L α-naphthaleneacetic acid (NAA). Treatments: CS, control; TS01, 0.05 mg/L NAA; TS02, 0.10 mg/L NAA; TS03, 0.20 mg/L NAA. Bar = 5 cm.</p>
Exposome Chemicals without MS data in the public domain
<p>List of high priority exposome chemicals that lack mass spectral data in public mass spectral repositories and the NIST MS 2020 database. Some of them are not amenable to mass spectrometry instruments. These compounds should be candidates for MS library expansion projects in exposome. </p>
LC-MS raw data for proteomic elucidation of the targets and primary functions of picornavirus 2A protease
<p>This dataset contains LC-MS raw data for pulldowns from the project "Proteomic elucidation of the targets and primary functions of picornavirus 2A protease." The descriptions of the raw data files are in Summary_Table_MS_RawData.pdf.</p>
MALDI-TOF MS data: Species delimitation of Hexacorallia and Octocorallia around Iceland using nuclear and mitochondrial DNA and proteome fingerprinting
<p>Cold-water corals build up reef structures or coral gardens and play an important role for many organisms in the deep sea. Climate change, deep-sea mining, and bottom trawling are severely compromising these ecosystems, making it all the more important to document the diversity, distribution, and impacts on corals. This goes hand in hand with species identification, which is morphologically and genetically challenging for Hexa- and Octocorallia. Morphological variation and slowly evolving molecular markers both contribute to the difficulty of species identification. In this study, a fast and cheap species delimitation tool for Octocorallia and Scleractinia of the Northeast Atlantic was tested based on 49 specimens. Two nuclear markers (ITS2 and 28S rDNA) and two mitochondrial markers (COI and mtMutS) were sequenced. The sequences formed the basis of a reference library for comparison to the results of species delimitation based on proteomic analysis using the MALDI-TOF MS method. The genetic methods were able to distinguish 17 of 18 presumed species. The MALDI-TOF MS method was able to distinguish 7 species. Species that could not be distinguished from one another still achieved good signals but were not represented by enough specimens for comparison. Therefore, it is predicted that with an extensive reference library of proteome spectra for Scleractinia and Octocorallia, MALDI-TOF MS may provide a rapid and cost-effective alternative for species discrimination in corals.</p>
Data Transformation for Clustering Utilization for Feature Detection in MS
<p>Dataset and roof-of-concept method used for proceeding titled "Data Transformation for Clustering Utilization<br> for Feature Detection in MS" of IWBBIO 22 conference.</p>
RECETOX Exposome HR-[ESI]-MS library
<p>The RECETOX Mass Spectrum Reference Libraries is a collection of MS spectra collected from authentic compounds. Each Library comprises the spectra in MSP format. The collection is shared under terms & conditions of CC-BY-NC.</p> <p>The RECETOX Exposome Pesticide HR-[ESI]-MS library is a collection of pesticides obtained from Restek Corporation. The RECETOX Exposome Pharmaceutical HR-[ESI]-MS library is a collection of pharmaceuticals selected from Prestwick Chemical Libraries.</p> <p>Compounds were analyzed by liquid chromatography coupled to a Thermo Scientific™ Orbitrap Fusion™ Tribrid™ Mass Spectrometer. Reversed-phase chromatography was performed using a pentabromobenzyl column. Tandem mass spectra were acquired via data-dependent acquisition with higher energy C-trap dissociation and real-time collision energy optimization for positive and negative mode electrospray ionization. The scan range was 85-1275 m/z with MS1 collected at 120K and MS2 at 60K resolving power. </p>
Result files (ALLDATA): "Joint structural annotation of small molecules using liquid chromatography retention order and tandem mass spectrometry data with LC-MS²Struct"
<p>Result files associated with the publication: "<strong>Joint structural annotation of small molecules using liquid chromatography retention order and tandem mass spectrometry data</strong>" by Bach et al.</p> <p>The following files are included in the archive:</p> <ul> <li>Raw max-marginal predictions using LC-MS²Struct for all LC-MS² experiments of the ALLDATA setup</li> <li>Averaged max-marginals for the LC-MS²Struct over all SSVM models</li> <li>Top-k accuracies for the comparison methods (MS²+RT, ...)</li> <li>Ranks for the ground-truth structures predicted by Only MS² and LC-MS²Struct (molecule class analysis)</li> </ul> <p>Instructions:</p> <ul> <li>clone the repository containing the experimental scripts and analysis notebooks: <a href="https://github.com/aalto-ics-kepaco/lcms2struct_exp">https://github.com/aalto-ics-kepaco/lcms2struct_exp</a></li> <li>download the archive in this repository</li> <li>unpack the archive in the git-repository root directory</li> <li>follow the instructions given in the <a href="https://github.com/aalto-ics-kepaco/lcms2struct_exp/blob/main/README.md">README.md</a> of the git-repository to reproduce the figures, etc.</li> </ul> <p>Version history:</p> <ul> <li><strong>Version 1</strong>: Experimental results for "Method comparison" and "Molecule classification analysis" where performed with <strong>2D fingerprints</strong> (<a href="https://www.biorxiv.org/content/10.1101/2022.02.11.480137v1">preprint v1</a>)</li> <li><strong>Version 2</strong> <em>(this version)</em>: Experimental results for "Method comparison" and "Molecule classification analysis" where performed with <strong>3D fingerprints</strong></li> </ul>
MALDI-MS raw files of primary human lung cancer samples, lung cancer patient derived xenografts and lung cancer mouse models
<p>Human primary lung cancer samples, patient derived lung cancer xenografts and lung tumors from the TetO-KRASG12D mouse model were analyzed using MALDI-MS. We determined the spatial distribution and relative abundance of lipids of interest. </p>
Datatset associated to Journal of Marine Systems submission : Ms. No. MARSYS-D-21-00246R1
<p>Individual growth increment measurements (µm) of the 21 live collected <em>A. islandica</em> used in the publication entitled : "The 18.6-year lunar nodal cycle may affect ecosystems on the Northwest Atlantic continental shelves". All information regarding data acquisition are presented in the section "2. Construction of <em>Arctica islandica </em>master chronology" of the article submitted to Journal of Marine Systems.</p> <p>Data are presented as a "Tucson File" which is a standard format for tree-ring dataset (see : <a href="http://www.cybis.se/wiki/index.php?title=Tucson_format">http://www.cybis.se/wiki/index.php?title=Tucson_format</a> for a precise description).</p> <p> </p>
LC-MS raw dataset of Dendrobium extracts
<p class="MsoNormal"><span>Orbitrap mass spectrometry is one kind of high-</span><span>resolution mass analyzer containing </span><span>multistage </span><span>fragment monitoring, a selective fragmentation mode, and a personalized data acquisition method</span><span><span>, </span></span><span><span>which </span></span><span><span>i</span></span><span><span>s </span></span><span>widely applied in </span><span>p</span><span>harmacokinetic analysis, </span><span><span>t</span></span><span><span>he </span></span><span>food </span><span>industry</span><span>, environmental monitoring</span><span><span>,</span></span><span> and proteomi</span><span>cs. </span><span><span>Alkaloids are an important active ingredient in Dendrobium officinale, but there are few studies on their isolation and identification. Here, </span></span><span>a </span><span><span>c</span></span><span><span>om</span></span><span><span>bin</span></span><span><span>atio</span></span><span><span>n </span></span><span><span>meth</span></span><span><span>od </span></span><span>for </span><span><span>s</span></span><span><span>ep</span></span><span><span>a</span></span><span><span>ra</span></span><span><span>tin</span></span><span><span>g</span></span><span> and </span><span><span>de</span></span><span><span>tect</span></span><span><span>ing </span></span><span>alkaloids and </span><span><span>the</span></span><span><span>ir </span></span><span>precursors</span><span> </span><span>was </span><span>established. </span><span>T</span><span>he accurate mass </span><span>of the </span><span>components</span><span> separated by HPLC were determined using an </span><span>high resolution</span><span><span> </span></span><span>mass analyzer. </span><span>T</span><span>he multistage fragmentation </span><span><span>p</span></span><span><span>at</span></span><span><span>hway</span></span><span> of </span><span>alkaloids</span><span> w</span><span><span>as</span></span><span> </span><span>speculated</span><span><span> </span></span><span>based on a database-dependent retrieval method.</span></p> <p class="MsoNormal"><span><span>By using a SPE-HP</span></span><span><span>LC</span></span><span><span>-</span></span><span><span>M</span></span><span><span>S</span></span><span><span>/MS </span></span><span><span>method, the potential compounds were tentatively identified by aligning the accurate molecular weight with the METLIN and Dictionary of Natural Products databases. The chemical structures and main characteristic fragments of the potential compounds were further confirmed by retrieving the multistage mass spectra from the MassBank and METLIN databases.The Mass Frontier software was used to speculate the fragmentation pathway of the identified compounds. Seven alkaloids were separated and identified from </span></span><em><span><span>D. officinale</span></span></em><span><span>, which were mainly classified into five types (tropane alkaloids, tetrahydroisoquinoline alkaloids, quinolizidine alkaloids, piperidine alkaloids and spermidine alkaloids). Besides the alkaloids, forty-nine chemical substances, including guanidines, nucleotides, dipeptides, sphingolipids and nitrogen-containing glucosides, were concurrently identified. </span></span></p>
Dataset of the 1976 Ms 7.3 Chaldiran earthquake
<p>The dataset, used in the study of the 1976 Ms 7.3 Chaldiran earthquake by Lu and Zhou (2023), includes KeyHole (KH-4B and KH-9) ortho-images, post-earthquake Pleiades data (1-m DEM and ortho-image) and a 30-m ALOS DEM.</p>
GC-MS chromatogram of the hexane fraction of the ciceraritnum
<p>GC-MS chromatogram of the hexane fraction of the ciceraritnum<br> </p>
Rapid pathogen identification in aqueous humor samples by combining Fc-MBL@Fe3O4 enrichment and MALDI-TOF MS profiling
<p>Prompt clinical diagnosis and antimicrobial therapy are key to managing infective endophthalmitis. The small volume of aqueous humor, low bacterial counts, and empirical medication by physicians make existing diagnostic methods time-consuming and imprecise. Here, we investigated the feasibility of combining Fc-MBL@Fe3O4 enrichment with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling to identify pathogens in aqueous humor. Aqueous humor aspirated from freshly enucleated porcine eyes was inoculated with different inocula of <em>Staphylococcus aureus</em> (<em>S. aureus</em>), <em>Staphylococcus </em><em>epidermidis</em> (<em>S. epidermidis</em>), and <em>Klebsiella pneumoniae</em> (<em>K. pneumoniae</em>). We performed identification directly in aqueous humor samples and after short-term culture of micro-LB broth. Aqueous humor endophthalmitis samples were enriched with Fc-MBL@Fe3O4 and analyzed with MALDI-TOF MS. The identification time and minimum bacterial concentration required for identification were determined. The enrichment efficiency of Fc-MBL@Fe3O4 for different bacteria was > (87.5±5.0)%. The objects of direct identification include live bacteria and bacteria treated with antibiotics, which can be completed within 1.5 hours. The minimum number of bacteria needed for positive identification was 2.20×10<sup>6 </sup>CFU. For micro-LB broth culture, the identification of bacteria can be completed within 6.5-9.5 h for aqueous humor samples with an initial bacterial count of tens to hundreds.</p>
Proteomic Profiling for Identification of Animal Skin Species in Ancient Egyptian Archaeological Leather using Liquid Chromatography Coupled with Tandem Mass Spectrometry (Nano LC-MS/MS)
<p><strong>Proteomic Profiling Dataset for Identification of Animal Skin Species in Ancient Egyptian Archaeological Leather using Liquid Chromatography Coupled with Tandem Mass Spectrometry (Nano LC-MS/MS)</strong></p>
Latin MS 182
Bede's Historia ecclesiastica gentis Anglorum, with the Continuo Bedae and two miracle stories, formerly owned by - and possibly produced at - the Benedictine Abbey of (Mönchen-)Gladbach, Germany in the twelfth century. Ancient binding, parchment over wooden boards, carefully restored. The 12th century script is in double columns of 31 lines, a very fine upright minuscule. Some coloured initials. Creator: Bede, the Venerable, Saint, 673-735 https://www.digitalcollections.manchester.ac.uk/view/MS-LATIN-00182/1 Source: Objaverse 1.0 / Sketchfab
Proteomics LC-MS/MS test dataset for protein quantitation via stable isotope labelling
<p>The provided mzML file can be used as a test dataset for protein identification and quantitation software. It was generated from human embryonic kidney (HEK) cells that were either unlabelled or labelled with heavy SILAC (K6R6, unimod accession 188, PSI-MS Name: "Label:13C(6)"). Apart from different labelling, the HEK cells were kept in exactly the same conditions and harvested simultaneously. Light and heavy labelled proteins from HEK cell lysate were mixed in a certain ratio, digested with Trypsin and measured on a ThermoFisher QExactive mass spectrometer. A more detailed description on the generation of the dataset will soon be accessible at PRIDE.</p> <p>The provided mzML file has been converted from Thermo RAW and slightly modified via msConvert (ProteoWizard). To reduce the filesize and to speed up analysis, it has further been filtered to contain only the data measured between 2,000 sec and 3,000 sec of the original LC-MS/MS run.</p>
Data set for spectral and FT-ICR-MS analysis of dissolved organic matter in sediments of the New Britain Trench axis station
<p> </p> <p>数据集包括原始数据和简单处理所需的数据、图表和文章。</p> <p> </p> <p>表格包含样品数量、收集深度、样品名称以及相应光谱和 FT-ICR-MS 数据的名称。</p> <p> </p> <p>例如,光谱数据包括荧光相对强度、荧光指数,而 FT-ICR-MS 光谱数据包括化合物类型相对强度以及化学式、元素比、等效双键数 (DBE) 和每个样品的芳香指数 (AImod)。</p> <p> </p>
LC-MS/MS data for WT human PANX1 with or without co-expressing Src-Y529F mutant
<p>Protein phosphorylation is one of the major molecular mechanisms regulating protein activity and function throughout the cell. Pannexin 1 (PANX1) is a large-pore channel permeable to ATP and other cellular metabolites. Its tyrosine phosphorylation and subsequent activation have been found to play critical roles in diverse cellular conditions, including neuronal cell death, acute inflammation, and smooth muscle contraction. Specifically, the non-receptor kinase Src has been reported to phosphorylate Tyr198 and Tyr308 of mouse PANX1 (equivalent to Tyr199 and Tyr309 of human PANX1), resulting in channel opening and ATP release. Although the Src-dependent PANX1 activation mechanism has been widely discussed in the literature, independent validation of the tyrosine phosphorylation of PANX1 has been lacking. Here, we show that commercially available antibodies against the two phosphorylation sites mentioned above—which were used to identify endogenous PANX1 phosphorylation at these two sites—are nonspecific and should not be used to interpret results related to PANX1 phosphorylation. We further provide evidence that neither tyrosine residue is a major phosphorylation site for Src kinase in heterologous expression systems. We call on the field to re-examine the existing paradigm of tyrosine phosphorylation-dependent activation of the PANX1 channel.</p>
Biblioteca Civica di Udine, Fondo Joppi, ms. 122 (inventario beni e censi della società Gubertino-Valentino di Udine, prima metà XIV secolo)
<p>Il presente dataset costituisce la sistematizzazione dei dati contenuti nel manoscritto 122 del Fondo Joppi della Biblitoeca civica di Udine e va inteso come materiale di corredo a T. Vidal, <em>Centri senza contado? La costruzione della territorialità urbana in Friuli (sec. XIII-XV)</em>, "Studi di storia medioevale e di diplomatica", n.s. VIII (2024) a cui si rimanda per gli aspetti di contestualizzazione e descrizione storica del manoscritto. </p> <p> </p> <p>Nel dataset sono usate le seguenti abbreviazioni:</p> <p>Md = marca di denari</p> <p>frx = frisacensi </p> <p>den = denari.</p> <p> </p> <p>Il database presenta 25 campi:</p> <p>1) ID: numerazione progressiva dei singoli beni</p> <p>2) tipologia: definisce il tipo di bene acquistato distinguendo tra diritti di riscossione (censi, livelli perpetui) o diritti di piena proprietà sui beni </p> <p>3) luogo: identifica la località in cui il censo o il bene erano situati</p> <p>4) bene: tipologia di bene su cui la rendita era assisa o di cui era stata acquisita la proprietà reso nella forma originale latina al nominativo</p> <p>5) tipologia bene: raccoglie i beni per tipologia distinguendo tra immobili (a loro volta distinti nel caso di strutture produttive come i forni), campi, terreni cintati, mansi (aziende agricole)</p> <p>6-10) censi o affitti imputati relativamente ai principali cereali, espresso in pesinali (vedi <em>infra </em>per metrologia)</p> <p>11) censo o affitto di vino in congi (vedi <em>infra </em>per metrologia)</p> <p>12) censo o affitto di vino in orne (vedi <em>infra </em>per metrologia)</p> <p>13) fitto altro: campo testuale che raccoglie le componenti monetarie e non cerealicole e vinicole degli affitti e dei censi</p> <p>14) fitto valore <em>usum curie</em>: riporta, quando espresso dal manoscritto, il valore di conto degli affitti espresso in piccoli della marca <em>ad usum curie </em>(vedi <em>infra </em>per la monetazione)</p> <p>15) affittuario: nome/i delle persone a cui il bene risulta affittato o, nel caso di censi, intestato</p> <p>16) anno acquisto: anno di acquisizione espresso nel registro; in caso di valore vuoto il dato è mancante o non desumibile</p> <p>17) prezzo di acquisto: espresso in piccoli (vedi <em>infra </em>per monetazione); in caso di valore vuoto il dato può essere mancante o indicato come somma complessiva per acquisti multipli (in quest'ultimo caso la somme è riportata nel campo note)</p> <p>18) venditore: nome/i delle persone che hanno venduto il bene</p> <p>19) note vendita/fitto: eventuali note relative specificamente alla vendita o all'affitto</p> <p>20) notaio: notaio rogante la carta di acquisto</p> <p>21) informazioni successive: annotazioni e modifiche intercorse dopo la stesura della prima registrazione relativa al singolo bene</p> <p>22) note: campo testuale generico che raccoglie le informazioni non altirmenti catalogabili</p> <p>23) depennata: campo binario (vuoto/x) indicante la presenza di un depennamento intenzionale con freghi trasversali dell'intera nota relativa a un bene/censo</p> <p>24) foglio: numero di foglio.</p> <p> </p> <p>Al fine di permettere un maggiore livello di analisi si è scelto di scorporare acquisti multipli nelle singole voci di beni/censi così come vengono registrati nel manoscritto. In questi casi il prezzo di acquisto (qualora espresso) non è stato riportato sotto la voce dedicata ma nel campo note con riferimento al numero di progressivo dei beni acquistati.</p> <p> </p> <p>Metrologia (se non altrimenti espresso il valore è in riferimento alle misure in uso a Udine; dati da Perusini, <em>Vita di Popolo</em>, pp. 250-259) </p> <p>1 staio = 6 pesinali = 73,15 litri</p> <p>1 conzo = 79,60 litri</p> <p>1 orna = 91,61 litri (in uso a Latisana)</p> <p> </p> <p>Monetazione</p> <p>1 marca di denari = 160 denari = 2240 piccoli (da Bernardi, <em>Monetazione</em>, p. 28)</p> <p> </p> <p>1 marca <em>usum curie</em> = 160 denari <em>usum curie </em>= 2240 piccoli <em>usum curie</em></p> <p>1 lira <em>usum curie </em>= 8 denari <em>usum curie </em>= 112 piccoli <em>usum curie</em></p> <p> </p> <p>All'altezza cronologica del registro (prima metà XIV secolo) frisacensi e denari erano considerati sinonimi e valevano entrambi 14 denari piccoli di moneta di conto.</p> <p> </p>
MS analysis of ([Hmim][OTf])3Zn - NCN project OPUS, grant no. 2020/37/B/ST8/00693.
<p>Dataset contains results obtained during the NCN project OPUS, grant no. 2020/37/B/ST8/00693. The file presents MS analysis of ([Hmim][OTf])3Zn.</p>
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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.