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75 results for “lc-ms”

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dryad36/100

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>

opencc-zeroApr 2024View details →
zenodo36/100

LC-MS/MS data of pharmaceutical compounds for lIbrary building

<p>Dataset used for MergeION package testing are&nbsp;provided by Janssen Pharmaceutica. It consists of known standard pharmaceutical compounds for which high quality Q-Exactive MS/MS data is provided. Details&nbsp;about these compounds can be found in Metadata_Library.txt. All datasets were acquired in positive ion mode through either DDA (data-dependent acquisition) or targeted MS/MS.&nbsp;Raw data in profile mode were converted into centroid-mode mzML or mzXML files using MSConvertGUI</p> <p>&nbsp;</p>

opencc-by-4.0Aug 2018View details →
zenodo36/100

LC-MS/MS plasma protein measurements from children with bacterial and viral infections - "MS-A"

<p>LC-MS/MS data generated from plasma samples from children with bacterial and viral infections.&nbsp;</p>

openApr 2023View details →
zenodo36/100

LC-MS/MS plasma protein measurements from children with bacterial and viral infections - "MS-B"

<p>LC-MS/MS data generated from plasma samples from children with bacterial and viral infections.&nbsp;</p>

openApr 2023View details →
dryad36/100

LC-MS/MS data for WT human PANX1 with or without co-expressing Src-Y529F mutant

Open the record for dataset details and reuse information.

publicApr 2024View details →
dryad36/100

LC-MS raw dataset of Dendrobium extracts

Open the record for dataset details and reuse information.

publicJul 2022View details →
dryad32/100

Data from: Liquid chromatography-mass spectrometry (LC-MS) data of a multi-epitope peptibody with bFGF/VEGFA

<p><span><span><span><span><span><span><span><span><span><span><span>The <span><span><span>protein </span></span></span><span><span><span>primary </span></span></span><span><span><span>structure of the recombinant </span></span></span>Peptibody were investigated systematically by Liquid Chromatography-Mass Spectrometry (LC-MS)<span><span><span>. T</span></span></span><span><span>he 15 amino acids of N-terminal were </span></span>Met-Gln-Lys-Arg-Lys-Arg-Lys-Lys-Ser-Arg-Tyr-Lys-Ser-Gly-Gly and <span><span>the C-terminal was Lys (K</span></span><span><span>), the same as</span></span> the theoretical sequence. <span><span>With more </span></span><a><span class="15"><span>protease</span></span></a><span><span>s, the whole sequence was detected at the coverage of </span></span>trypsin 87.5%, <span><span>c</span></span><span><span>hymotrypsin</span></span> 75.3% and <span><span>Glu-C</span></span> 76.7%<span><span>. The </span></span>peptide-mapping could be used as an valuable standard to certify the complete expression and primary structure of Peptibody. The pI and MW were 8.93 and 37.415 kDa, within the errors allowed . The binding specificity after production were analyzed using anti-VEGFA and anti-His antibodies.</span></span></span></span></span></span></span></span></span></span></span></p>

opencc-zeroJul 2020View details →
dryad32/100

Data from: Novel insights into relationships between egg corticosterone and timing of breeding revealed by LC-MS/MS

Inter- and intra-clutch variation in egg corticosterone (CORT), the major glucocorticoid in birds, may provide insights into how maternal stress levels vary with the timing of breeding and with laying order. Common analytical methods (e.g. immunoassays), however, suffer from cross-reaction with other steroids, leading to potential overestimation of CORT concentrations which can obscure true hormone–environment relationships and complicate among-study comparisons. We here apply a new LC-MS/MS technique, which has recently been shown to avoid the problem of cross-reactivity due to its high specificity, to quantify CORT concentrations in yolk and albumen in clutches of lesser black-backed gulls Larus fuscus. We found that CORT concentration exhibited a previously unreported U-shaped relationship with time of breeding, which we explain as a potential interplay of two forces exerting extra strain on the early and late breeders. Furthermore, results showed an increase in CORT with laying order indicating the energetic expense of egg production. The levels of CORT assessed in this study were significantly lower than those previously reported in studies using immunoassays for CORT analysis. This supports the fact that incorporating chromatography effectively reduces overestimation of CORT due to cross-reactivity with other steroid hormones, particularly in egg yolk.

opencc-zeroDec 2014View details →
zenodo32/100

Lipidomics and metabolomics datasets for "Adverse effects of arsenic uptake in rice metabolome and lipidome revealed by untargeted liquid chromatography coupled to mass spectrometry (LC-MS) and regions of interest multivariate curve resolution"

<p><strong>Files description</strong></p> <p>Raw files for lipidomics and metabolics studies on the impact of arsenic exposure on rice growth.</p> <p>File details on the worksheets lipids_files.xlsx and metabolomics_files.xlsx</p> <p>Files have been organized as follows:</p> <p><strong>Lipidomics</strong></p> <blockquote> <p>1) Control samples: lip_controls.rar<br> 2) Watering low As exposure: lip_water_1.rar<br> 3) Watering high As exposure: lip_water_1000.rar<br> 4) Soil low As exposure: lip_soil_5.rar<br> 5) Soil high As exposure: lip_soil_50.rar<br> 6) QC samples: lip_qcs.rar</p> </blockquote> <p><strong>Metabolomics (positive ionization mode)</strong></p> <blockquote> <p>1) Control samples: met_pos_controls.rar<br> 2) Watering low As exposure: met_pos_water_1.rar<br> 3) Watering high As exposure: met_pos_water_1000.rar<br> 4) Soil low As exposure: met_pos_soil_5.rar<br> 5) Soil high As exposure: met_pos_soil_50.rar<br> 6) QC samples: met_pos_qcs.rar</p> </blockquote> <p><strong>Metabolomics (negative ionization mode)</strong></p> <blockquote> <p>1) Control samples: met_neg_controls.rar<br> 2) Watering low As exposure: met_neg_water_1.rar<br> 3) Watering high As exposure: met_neg_water_1000.rar<br> 4) Soil low As exposure: met_neg_soil_5.rar<br> 5) Soil high As exposure: met_neg_soil_50.rar<br> 6) QC samples: met_neg_qcs.rar<br> &nbsp;</p> </blockquote> <p>&nbsp;</p> <p><strong>Experimental details</strong></p> <blockquote> <p><strong>Arsenic Exposure</strong></p> <p>Arsenic was supplied through two main routes: watering with contaminated water or soil containing arsenic. In addition, this new study includes metabolomic as well as lipidomic analysis, in order to have a more global overview of arsenic exposure.</p> <p>For the watering treatment, during the first 11 days, rice was irrigated with Milli-Q water. From that day until harvesting, plants were watered with 1 and 1000 &mu;M of As (V) for the two concentration levels of exposure, and with Milli-Q water for control samples. The lowest concentration was established at 1 &mu;M as it is the limit of the acceptable arsenic concentration in water by European legislation. The upper concentration was set at 1000 &mu;M, a threshold established to ensure that the experiment was performed under sub-lethal arsenic concentration for the plant, based on previous studies.</p> <p>For the soil treatment, two containers were prepared with 1 kg of soil two days before planting. Soil from the container was exposed to two arsenic concentration levels (5 and 50 mg L<sup>-1</sup>). Once sowing, rice was irrigated the whole growth period with a solution containing 0.001 &mu;M of As (V). The lowest arsenic limit in this treatment was set at 5 mg L<sup>-1</sup> as a maximum value of common arsenic leaches without toxic characteristics, although background soil content of arsenic varies between one and 40 ppm according to the US food and drug administration (FDA) report. The highest arsenic limit was established to 50 mg L<sup>-1</sup>, as a considerably high arsenic content in the soil, slightly above the maximum frequently encountered levels.</p> <p><strong>Lipidomic Analysis</strong></p> <p>The lipidomic analysis was performed using a Waters Acquity UPLC system (Waters Corporation, MA, USA), connected to a Waters LCT Premier orthogonal accelerated time of flight mass spectrometer (Waters), operated in both positive and negative electrospray (ESI) ionization modes. Full scan spectra were acquired from 50 to 1500 Da.</p> <p>The chromatographic column employed was a Kinetex C8 (100 x 2.1 mm, 1.7 &mu;m) (Phenomenex) under the following conditions (already used in [47]): temperature at 30˚C, injection volume at 10 &mu;L, and flow rate at 0.3 mL min<sup>-1</sup>. Mobile phases selected were (A) MeOH 1mM ammonium formate, and (B) H<sub>2</sub>O 2mM ammonium formate, both at 0.2% formic acid. The gradient started at 80% A, increased to 90% A in 3 min, from 3 to 6 min remained at 90% A, changed to 99 % A until minute 15, remained constant 1 min, and returned to initial conditions until minute 20.</p> <p><strong>Metabolomic analysis</strong></p> <p>The metabolomic analysis was performed using a Waters Acquity UPLC system connected to a Q-Exactive (Thermo Fisher Scientific, Hemel Hempstead, UK) equipped with a quadrupole-Orbitrap mass analyzer. Electrospray (ESI) was used as an ionization source in both positive and negative ion modes. Full scan mass range was set from <em>m/z</em> 90 to 1000, and all ion fragmentation (AIF) was performed with normalized collision energy (NCE) of 35 eV.</p> <p>The column employed was an HILIC TSK gel amide-80 column (250 x 2.0 mm i.d., 5 &mu;m) provided by Tosoh Bioscience (Tokyo, Japan), under the following experimental conditions (already employed in [45]): flow rate at 0.15 mL min<sup>-1</sup>, at room temperature, and 5 &mu;L injection volume. Mobile phases were (A) AcN, and (B) 5 mM ammonium acetate, adjusted at pH 5.5 with acetic acid. The gradient employed was: starting conditions at 25% B, then increased until 30% B in 8 min; a 60% B was reached at 10 min, held for 2 min more and then back to 25% B until minute 14 min; lastly, a re-equilibration step was added and from 14 to 20 min at 25% B.</p> </blockquote> <p>&nbsp;</p> <p><strong>Funding:</strong> This research was funded by the Spanish Ministry of Science and Innovation (MCI, Grant CTQ2017-82598-P) and Severo Ochoa Project CEX2018-000794-S (funded by MCIN/AEI/ 10.13039/501100011033), and supported from the Catalan Agency for Management of University and Research Grants (AGAUR, Grant 2017SGR753). MPC was funded by a predoctoral FPU 16/02640 scholarship from the Spanish Ministry of Education and Vocational Training (MEFP).&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Dec 2021View details →
zenodo32/100

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 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>

opencc-by-4.0Oct 2022View details →
zenodo32/100

Tooth enamel LC-MS dataset for: "Enamel histomorphometry, growth patterns and developmental trajectories of the first decidous molar in an Italian early medieval skeletal series"

<p>(n)LC-MS .raw data of tooth enamel samples from archaeological human remains.&nbsp;</p> <p>The dataset is related to the publication of Magri et al.&nbsp;</p>

opencc-by-4.0Apr 2024View details →
zenodo32/100

LC-MS data for Hirschi et al. (2024)

<p>Additional data related to the LC-MS experiments (Suppl. Figs. 7 and 8). MRM method, calibration curves and quantifications as well as .wiff files.</p>

opencc-by-4.0Apr 2024View details →
zenodo32/100

Label-Free Quantification (LFQ) LC-MS Data for the Profiling of Domain-specific VCP/p97 Interactions in Living Cells

<p>This deposit includes LFQ LC-MS data for tandem-IP samples from VCP-L278AbK and VCP-D592AbK crosslinking experiments, their VCP-L278BocK and VCP-D592BocK controls, and SpectroMine output files.</p>

opencc-by-4.0Sep 2024View details →
zenodo32/100

Positive mode DDA LC-MS/MS analysis of organic plant extracts (Malaga)

<p>Organic Plant extracts from Malaga resuspended in 8/2 MeOH/water and analysed on Exploris 480 in positive DDA mode.</p>

opencc-by-4.0Oct 2024View details →
zenodo32/100

Lactobacillus johnsonii N6.2 total lipid and fractionated lipids profiling by qualitative lipidomic LC-MS/MS analysis

<p>Table presents both MS-1 (precursor mass-matched) and MS-2 (precursor mass- and spectral-matched) annotations. The values in the table represent the peak area. The column labels, RT: retention time; m/z: mass-to-charge ratio; SL (simple lipids), GL (glycolipids), and PL (phospholipids) represent lipid fractions and TL: total lipids. Table is provided as an xlsx file.</p>

opencc-by-4.0Jun 2023View details →
zenodo32/100

LC-MS results for unconjugated antibody (Atezolizumab (AtZ)) , pemetrexed-PEG-Atezolizumab (PemPEG-AtZ conjugate), and pemetrexed-GABA-Atezolizumab (PemGABA-AtZ conjugate)

<p>This data represent the figures of&nbsp;LC-MS results for unconjugated antibody (Atezolizumab (AtZ)) , pemetrexed-PEG-Atezolizumab (PemPEG-AtZ conjugate), and pemetrexed-GABA-Atezolizumab (PemGABA-AtZ conjugate)</p>

opencc-by-4.0Jul 2023View details →
zenodo32/100

Supplementary Table 1. Identification of protein bands content by LC-MS/MS from fractions obtained from B. arietans venom after size exclusion chromatography.

<p>FG1 to FG6 were cut from the gel and subjected to in-gel digestion with trypsin. Analysis was performed using an Easy-nLC Proxeon nanoHPLC system coupled to an LTQ-Orbitrap Velos. The results obtained were compared with the &ldquo;<em>Bitis</em>&rdquo; and &ldquo;Snakes&rdquo; database downloaded from Uniprot (Taxid: 8570).</p>

opencc-by-4.0Jul 2023View details →
zenodo32/100

LC-MS/MS analysis of Buxus

<p>Lc-MS/MS analysis of the polar extracts of <em>Buxus</em></p>

opencc-by-4.0Aug 2023View details →
zenodo32/100

Fig. 5. A in Assessing specialized metabolite diversity of Alnus species by a digitized LC-MS/MS data analysis workflow

Fig. 5. A boxplot showing the ion intensities of MS/MS feature 10 (gallic acid) in extracts which were active (IC50 &lt;30 μg/mL) and inactive against α-glucosidase.

opennotspecifiedMay 2020View details →
zenodo32/100

Fig. 4 in Assessing specialized metabolite diversity of Alnus species by a digitized LC-MS/MS data analysis workflow

Fig. 4. Discrimination of the analyzed Alnus extracts into chemogroups. The analyzed extracts can be discriminated into three chemogroups by visualizing the CSCS distance metric between samples as PCoA plot (A) and chemical dendrogram (B). On the other hand, conventional methods such as PCA score plot (C) or hierarchical clustering analysis (HCA) using the Euclidean distance (D; chemogroups 1–3 are visualized with same colors used in B to make it easy to be compared) could not discriminate the samples into the same chemotypes. By mapping the chemogrouping of samples on the molecular network, it could be visualized that the three chemogroups were rich in diarylheptanoid, flavonoid, and tannins, respectively (E). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

opennotspecifiedMay 2020View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record