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GC-MS raw data_Figure 6E_Lysophosphatidic Acid Shifts Metabolic and Transcriptional Landscapes to Induce a Distinct Cellular State in Human Pluripotent Stem Cells
<p><strong>Sample name</strong></p> <p>hESCs (H1 cells) were given treatments for two days and then collected for GC-MS analysis.</p> <p>E8: E8 medium</p> <p>AX: E8 + 1.6% AlbuMAX;</p> <p>BSA: E8 + 1% albumin;</p> <p>BSA+hCDL: E8 + 1% albumin + 0.1% hCDL;</p> <p>LPA+BSA: E8 + 1 μM LPA + 1% albumin;</p> <p>LPA+BSA+hCDL: E8 + 1 μM LPA + 1% albumin + 0.1% hCDL</p> <p>STD: standard lipids mixture used as reference</p> <p><strong>Extraction and Methylation</strong></p> <p>Sample preparation was conducted according to the previously reported method (Araujo et al., 2008) with the modification. Briefly, spent medium was removed, and cells were rinsed with 1 mL/well 0.9% (w/v) saline twice. Then 0.5 mL/well -80°C 80% methanol was added to quench the metabolism. Five wells of cells (from 6-well plate) were scrapped off into a glass screw-cap tube. Then 4 mL heptadecanoate containing chloroform (4 μg/mL, internal standard for fatty acids) was added into the tube. Vortex, and then centrifuge at 2000 rpm for 5 min. Cellular debris was carefully removed, and nitrogen blow the solution till dry. Add 1.5 mL hexane and 1.5 mL 14% boron trifluoride (BF<sub>3</sub>)/methanol solution. Seal the tube with nitrogen gas, heat it at 100°C for 1 h using MK200-2 dry bath incubator (Aosheng), and then cool down to room temperature. Add 1 mL water into the tube, vortex and then centrifuge at 3000 rpm for 10 min. The upper layer was transferred into a new 1.5-mL eppendorf tube and evaporated by nitrogen gas. The residue was re-dissolved in 100 μL hexane for GC-MS analysis.</p> <p><strong>GC-MS method</strong></p> <p>Samples were analyzed using an Agilent GC-MS system (Agilent) consisting of a 6890 gas chromatography and a 5973 mass spectrometer. Fatty acid methyl esters were separated by an Omegawax™ 250 fused silica capillary column (30 m × 0.25 mm i.d., 0.25 μm film thickness, Supelco, Bellefonte, PA). The optimized oven temperature program was: initial temperature set at 180°C and held for 3 min; ramped to 206°C at 2°C/min and held at 206°C for 25 min, then, ramped to 240°C at 10°C/min and held for 5 min. Overall, the total run time was 50 min. Carrier gas was high-purity helium at a flow rate of 1.5 mL/min. Injector temperature was set at 250°C. Injection volume was 2 μL with a split ratio of 1:15. The mass spectrometer was operated in electron-impact (EI) mode at 70 eV ionization energy. The temperatures of quadrupole and ionization source were set at 150°C and 280°C, respectively. The spectra from 3 to 50 min were acquired with the <em>m/z</em> range of 35–550 at a scan rate of 0.34 s per scan.</p>
LC-MS raw data_Lysophosphatidic Acid Shifts Metabolic and Transcriptional Landscapes to Induce a Distinct Cellular State in Human Pluripotent Stem Cells
<p><strong>LC-MS/MS analysis</strong></p> <p><strong>Metabolite extraction</strong></p> <p>For LC-MS/MS quantification, cell sample preparation was conducted as described in the previous literatures (Ying, Kimmelman et al. 2012, Zhang, Badur et al. 2016). Briefly, the spent medium was removed, and cells were rinsed with 1 mL/well 0.9% (w/v) saline twice. Then 0.5 mL/well -80°C 0.2 μg/mL norvaline containing 80% methanol was added to quench the metabolism. Cells were scraped off into 1.5-mL eppendorf tube and stored in -80℃ overnight. The mixtures were vortexed and then centrifuged 12500 × <em>g </em>for 15 min at 4℃. The supernatant was used for LC-MS analysis.</p> <p><strong>LC-MS/MS method</strong></p> <p>Waters Xevo TQD coupled with Waters Acquity UPLC system was used for quantification. Acquity UPLC BEH HILIC column (2.1 × 100 mm, 1.7 μm), Acquity UPLC BEH C18 column (2.1 × 100 mm, 1.7 μm), and Acquity UPLC BEH amide column (2.1 × 100 mm, 1.7 μm) were used for the separation of metabolites. Column temperature was set at 40 °C.</p> <p>For the quantification of norvaline, amino acids, GSH, GSSG, SAH, SAM, ascorbic acid and myo-inositol, amide column was used for the separation. Acetonitrile with 0.1% formic acid (A) and water with 0.1% formic acid (B) were used as mobile phases. The gradient setting is: 0-4 min, 99% A to 90% A; 4-10 min, 90% A to 67% A; 10-13 min, 67% A to 1% A; 13-15 min, 1% A; 15-16.5 min, 1% A to 99% A; 16.5-20 min, 99% A. Flowrate was set as 0.4 mL/min.</p> <p>For the quantification of metabolites involved in TCA cycle, energy related and ribonucleotides, an amide column was used for the separation. Acetonitrile with 0.1% formic acid (A) and water with 0.1% formic acid (B) were used as mobile phases. The gradient setting is: 0-2 min, 80% A; 2-3 min, 80% A to 20% A; 3-5 min, 20% A; 5-6 min, 20% A to 80% A; 6-10 min, 80% A. Flowrate was set as 0.4 mL/min.</p> <p>For the quantification of acetate, acetyl-CoA and metabolites involved in glycolysis and pentose phosphate pathway, HILIC column was used for the separation. Acetonitrile (A) and 10 mM ammonium bicarbonate were used as mobile phases. The gradient setting is: 0-2 min, 10% A; 2-5 min, 10% A to 5% A; 5-6 min, 5% A to 10% A; 6-10 min, 10% A. Flowrate was set as 0.2 mL/min.</p> <p>For the quantification of LPA, LPC and PC, HILIC column was used for the separation. Acetonitrile (A) and 10 mM ammonium bicarbonate aqueous solution (B) were used as mobile phases. The gradient setting is: 0-2 min, 95% A; 2-4 min, 95% A to 10% A; 4-7 min, 10% A; 7-9 min, 10% A to 95% A; 9-15 min, 95% A. Flowrate was set as 0.2 mL/min.</p> <p>For the quantification of CDL lipids, C18 column was used for the separation. 98% Acetonitrile aqueous solution (A) and 10 mM ammonium acetate 90% acetonitrile aqueous solution (B) were used as mobile phases. The gradient setting is: 0-5 min, 0.1% A; 5-6 min, 0.1% A to 99.9% A; 6-11 min, 99.9% A; 11-12 min, 99.9% A to 0.1% A; 12-15 min, 0.1% A. Flowrate was set as 0.4 mL/min.</p> <p>Argon was used as source gas, capillary voltage was 3500 V, and desolvation temperature was 500 °C. Multiple reaction monitoring (MRM) was conducted, and the ion transitions are listed in the supplemental Table S2. Selected ion recording (SIR) was conducted for the detection of CDL-related lipids, and the setting is listed in the supplemental Table S3.</p> <p>Standard solutions of TCA metabolites (100 μg/mL) and intermediates of glycolysis and pentose phosphate pathway (10 μg/mL) were prepared to confirm the retention time. Peak intensity of product ion was used for the quantification. Data analysis was performed by TargetLynx software (Waters) with statistical analysis in Graphpad Prism (version 8.4.0) and R.</p>
Native MS dataset for: "Caldendrin and myosin V regulate synaptic spine apparatus localization via ER stabilization in dendritic spines."
<p>Native mass spectrometry dataset used in: <strong>Caldendrin and myosin V regulate synaptic spine apparatus localization via ER stabilization in dendritic spines.</strong> Anja Konietzny, Jasper Grendel, Alan Kadek, Michael Bucher, Yuhao Han, Nathalie Hertrich, Dick H. W. Dekkers, Jeroen A. A. Demmers, Kay Grünewald, Charlotte Uetrecht and Marina Mikhaylova. <i>The EMBO Journal</i> (2021) e106523. doi:<a href="https://doi.org/10.15252/embj.2020106523">10.15252/embj.2020106523</a></p><p> </p><p><strong>Description:</strong></p><p>Native mass spectrometry (MS) analysis of the stoichiometry and ion occupancy of recombinant human calmodulin (CaM) and recombinant rat caldendrin (CaD) complex with synthetic mouse myosinV IQ1 (myoIQ) motif in the presence / absence of excess Ca2+ and Mg2+ ions.</p><p><strong>Sample processing:</strong></p><p>Full-length CaD and CaM as well as the synthetic myoVa peptide were buffer exchanged into 150 mM aqueous ammonium acetate solution (pH 7.4). CaM was twice passed through a Bio-Spin P-6 gel filtration spin column (6 kDa cut-off, <i>Bio-Rad</i>), CaD and the myoVa peptide were buffer exchanged through five cycles of tenfold dilution and re-concentration using centrifugal concentrators Vivaspin 500 (10 kDa cut-off, <i>Sartorius</i>) or Amicon Ultra 0.5mL (3 kDa cut-off, <i>Merck/Millipore</i>), respectively. Desalted proteins were introduced into an Orbitrap Q Exactive UHMR mass spectrometer (<i>Thermo Scientific</i>) via static nanoelectrospray ionization from in-house prepared gold-coated borosilicate glass capillaries Kwik-Fil 1B120F-4 (<i>World Precision Instruments</i>). Proteins were sprayed and analysed at 8.5 µM concentration in ammonium acetate alone or supplemented with 200 µM calcium acetate and 100 µM magnesium acetate (both for trace metal analysis, <i>Sigma-Aldrich</i>). For interaction analysis, CaM and/or caldendrin were mixed with myoVa peptide which had final concentration of 8.5 µM (low concentration) or 34 µM (high concentration). The mass spectrometer was tuned for best signal quality and intensity, keeping ion activation and unfolding minimal. Namely, electrospray voltage was kept at 1.3 kV, source desolvation temperature 250°C, in-source desolvation -50 V, ion transfer profile "high m/z", analyzer profile "low m/z", analyzer target resolution 12500 acquiring in mass range 500 – 9000 m/z. Nitrogen was used as collision gas in HCD cell at relative gas pressure setting 7.0 with gentle collisional activation by 10 V HCD voltage gradient.</p><p><strong>Data processing:</strong></p><p>Raw spectra were averaged over at least 50 scans for mass deconvolution and peak assignment in UniDec 4.4.1 package (<i>Marty et al., 2015</i>). The averaged spectra were exported for ZENODO deposition using <i>Thermo Scientific</i> FreeStyle 1.5.93.34 as single-scan Thermo .raw files (including instrumental parameters metadata) as well as in plain m/z vs intensity .txt files.</p>
CX-MS Datasets for "Comprehensive Structure and Functional Adaptations of the Yeast Nuclear Pore Complex"
<p>This repository contains chemical cross-linking mass spectrometry data of affinity-purified Yeast nuclear pore complexes.</p> <p>Data Files Description:</p> <p>NPC_XL_Identification_Inter_Crosslinked.csv: Inter-protein cross-links identified by pLink 2.</p> <p>NPC_XL_spectra.mgf: MS2 spectra data for the identified cross-links.</p> <p>NPC_XL_proteins.fasta : Protein sequences used for search.</p> <p>Sample Processing:</p> <p>NPCs were immuno-purified from Mlp1 tagged S. cerevisiae strains (Kim et al., 2018). After native elution, 1.0 mM disuccinimidyl suberate (DSS) was added and the sample was incubated at 25ºC for 40 min with shaking (1,200 rpm). The reaction was quenched by adding a final concentration of 50 mM freshly prepared ammonium bicarbonate and incubating for 20 min with shaking (1,200 rpm) at 25ºC. The sample (50 µg) was then concentrated and denatured at 98ºC for 5 min in a solubilization buffer (10% solution of 1-dodecyl-3-methylimidazolium chloride (C12-mim-Cl) in 50 mM ammonium bicarbonate, pH 8.0, 100 mM DTT). After denaturation, the sample was centrifuged at 21,130 g for 10 min and the supernatant was transferred to a 100 kDa MWCO ultrafiltration unit (MRCF0R100, Microcon). The sample was quickly spun at 1,000 g for 2 min and washed twice with 50 mM ammonium bicarbonate. After alkylation (50 mM iodoacetamide), the cross-linked NPC in-filter was digested by trypsin and lysC O/N at 37ºC. After proteolysis, the sample was recovered by centrifugation and peptides were fractionated into 10-12 fractions by using a stage tip self-packed with basic C18 resins (Dr. Masch GmbH). Fractionated samples were pooled prior to LC/MS analysis.</p> <p>Desalted cross-link peptides were dissolved in the sample loading buffer (5% Methanol, 0.2% FA), separated with an automated nanoLC device (nLC1200, Thermo Fisher), and analyzed by an Orbitrap Q Exactive HFX (Pharma mode) mass spectrometer (Thermo Fisher) as previously described (Xiang et al., 2020; Xiang et al., 2021). Briefly, peptides were loaded onto an analytical column (C18, 1.6 μm particle size, 100 Å pore size, 75 μm × 25 cm; IonOpticks) and eluted using a 120-min liquid chromatography gradient. The flow rate was approximately 300 nl/min. The spray voltage was 1.7 kV. The QE HF-X instrument was operated in the data-dependent mode, where the top 10 most abundant ions (mass range 380 – 2,000, charge state 4 - 8) were fragmented by high-energy collisional dissociation (HCD). The target resolution was 120,000 for MS and 15,000 for tandem MS (MS/MS) analyses. The quadrupole isolation window was 1.8 Th; the maximum injection time for MS/MS was set at 200 ms.</p> <p>Data Processing:</p> <p>The raw data were searched with pLink2 (Chen et al., 2019b). An initial MS1 search window of 5 Da was allowed to cover all isotopic peaks of the cross-linked peptides. The data were automatically filtered using a mass accuracy of MS1 ≤ 10 ppm (parts per million) and MS2 ≤ 20 ppm of the theoretical monoisotopic (A0) and other isotopic masses (A+1, A+2, A+3, and A+4) as specified in the software. Other search parameters included cysteine carbamidomethyl as a fixed modification and methionine oxidation as a variable modification. A maximum of two trypsin missed-cleavage sites was allowed. The initial search results were obtained using a default 5% false discovery rate (FDR) expected by the target-decoy search strategy. Spectra were manually verified to improve data quality (Kim et al., 2018; Shi et al., 2014). Cross-linking data were analyzed and plotted with CX-Circos (http://cx-circos.net).</p>
MetaPro: a web-based metabolomics application for MS data batch inspection and library curation
<p>MetaPro is a metabolomics web analysis platform built on the Aird data format with high performance and high compression. This platform includes a series of necessary functions for metabolomics analysis such as quality control, retention time(RT) alignment, target analysis, untarget analysis, manual integration, batch inspection, MS2 library establishment, and report export, providing efficient data analysis, management and visualization capabilities</p>
Supplementary files - Evaluation of MALDI-TOF MS technology in small ruminant milk adulteration using raw bovine milk
<p>The dataset is a part of Supplementary file for the manuscript:</p> <p><strong>Evaluation of MALDI-TOF MS technology in small ruminant milk adulteration using raw bovine milk</strong> by L. Rysova, P. Cejnar, O. Hanus, V. Legarova, J. Havlik, H. Nejeschlebova, I. Nemeckova, R. Jedelska, M. Bozik, submitted to <em>Journal of Dairy Science</em> (Manuscript ID JDS.2021-21396), Received October 8, 2021, Accepted January 31, 2022, Corresponding author: bozik@af.czu.cz, <a href="https://doi.org/10.3168/jds.2021-21396">https://doi.org/10.3168/jds.2021-21396</a></p> <p><strong>File 1:</strong> Detailed MALDI-TOF method description</p> <p><strong>File 2: </strong>Quantification of milk adulteration – calibration of the model Quantification of milk adulteration – calibration of the model</p> <p><strong>Table S1: </strong>Baseline characteristics of pure bovine milk which was used as an adulterant of caprine milk<strong> </strong></p> <p><strong>Table S2: </strong>Baseline characteristics of pure bovine milk which was used as an adulterant of ovine milk</p> <p><strong>Table S3: </strong>Root mean squared error (RMSE) of predicted caprine and ovine adulterated milk samples using set A as the training set and set B as the test set.</p> <p><strong>Table S4: </strong>Root mean squared error (RMSE) of predicted caprine and ovine adulterated milk samples using both, set A and set B , as the one training set and set C as the test set.</p> <p><strong>Table S5: </strong>Root mean squared error (RMSE) of predicted caprine and ovine adulterated milk samples using set AB as the training set and set C as the test set.</p> <p>In this version <strong>SD values in Table S2 were corrected</strong>.</p>
Raw data of compounds extracted by GC-MS from each population replicate's of I. uriae ticks from Iceland.
<p>Raw data representing all the compounds extracted by GC-MS from each population replicate’s of <em>I. uriae</em> ticks from three sites in Iceland. Each replicate contain a pool of 10 living flat female ticks.</p> <p>Site: name of the site where ticks were collected.</p> <p>Host: name of the host bird.</p> <p>Replicate: number of the replicate (1 to 4).</p> <p>Peak: number of the detected peaks correponding to extracted compounds.</p> <p>Retention Time: time elapsed between sample introduction and the maximum signal of the given compound.</p> <p>Area: area under the curves of each detected coumpounds on the chromatogram.</p>
Code and data sets for "MS²Rescore: Data-driven rescoring dramatically boosts immunopeptide identification rates"
<p>Code used to prepare data sets, train and evaluate new MS²PIP models, evaluate MS²Rescore for immunopeptidomics, and generate figures. See README.md for more information on how to use these files and reproduce the results reported in the manuscript titled "MS²Rescore: Data-driven rescoring dramatically boosts immunopeptide identification rates".</p>
Gregory-MS: list of research papers relevant/not relevant for Multiple Sclerosis research (for machine learning training)
<p>This dataset represents the list of research papers' data that was used to train and test different machine learning algorithms in the Gregory-MS project. The list includes the title and abstract (when available) of the research papers and an annotated field (relevant) that specifies if the given research paper is relevant or not for multiple sclerosis research.</p>
LC-MS² meta data for each MassBank (MB) subset
<p>The CSV-file (tab used as separator) provides the Liquid-chromatography (LC) and Tandem-mass spectrometry (MS²) configurations for each MassBank (MB) subset used in the publication: "Joint structural annotation of small molecules using liquid chromatography retention order and tandem mass spectrometry data" by Bach et al. (2022).</p>
MS data linked to the manuscript : DOI: 10.3390/pharmaceutics14030616
<p>Data set containing Extract_E_Chevalieri_EtOAc_DCM .raw file of the LC-MS/MS acquisition.</p>
MS data linked to the manuscript : DOI: 10.3390/pharmaceutics14030616
<p>Data set containing Extract_E_Chevalieri_EtOAc_DCM .raw file of the LC-MS/MS acquisition.</p> <p> </p>
Initial relevant routes and geospatial objects for refugees and asylum seekers in MS
<p>Open geospatial dataset with an initial collection of routes, landmarks, and decision and confirmation points relevant for young refugees and asylum seekers arriving to Münster (MS), Germany. The information here collected were the results of participatory workshops done with young forced migrants in 2016.</p> <p>The information of the routes, landmarks (reference objects), points (origin, destination, decision, and confirmation points) and the relationship between points and reference objects is available in .JSON format. It has as an example, the images collected for one of the relevant routes (R2) identified by the group of young forced migrants. This route is the one from the main mall downtown (Arkaden) MS to the central train station. The pictures are available in .zip format.</p> <p> </p>
Figure 3. Using the ADX agent for obtaining definitions, synonyms and antonyms, for a given word, during MS Word editing-ADX – Agent for Morphologic Analysis of Lexical Entries in a Dictionary
<p>In figure 3 we present a capture screen of using the ADX1 agent in editing the text in<br> Microsoft Word. It displays the definition of the current word, but it also generates the synonyms,<br> used in the application of some web searching rules, used by another intelligent agent, called ASR.<br> The ASR agent will automatically compose some search strings to use for a web search engine, like<br> Google, Yahoo, or other. For example, if the user will search the word zăpadă (snow) on Yahoo<br> search engine, then one can also generate a search for the word nea (synonym of zăpadă) by using<br> the following ASR rule:<br> # Yahoo search<br> IF<br> http://search.yahoo.com/search?p=^X^&fr=yfp-t-309&toggle=1&cop=mss&ei=UTF-8<br> THEN<br> http://search.yahoo.com/search?p=^Clasa(X)^&fr=yfp-t-309&toggle=1&cop=mss&ei=UTF-8</p>
The BrainTeaser Ontology for ALS and MS Clinical Data
<p>This repository contains the <strong>BrainTeaser Ontology</strong> (BTO) whose purpose is to jointly model both <em>Amyotrophic Lateral Sclerosis (ALS)</em> and <em>Multiple Sclerosis (MS)</em>.</p> <p>BTO serves multiple purposes:</p> <ul> <li>to provide a unified and comprehensive conceptual view about ALS and MS, which are typically dealt with separately, allowing us to coherently integrate the data coming from the different medical partners in the project;</li> <li>to seamlessly represent both <em>retrospective</em> data and <em>prospective</em> data, produced during the lifetime of BRAINTEASER</li> <li>to allow for sharing and re-using the BRAINTEASER datasets according to Open Science and FAIR principles.</li> </ul> <p>BTO is innovative since it relies on very few seed concepts - Patient, Clinical Trial, Disease, Event - which allow us to jointly model ALS and MS and to grasp the time dimension entailed by the progression of such diseases.</p> <p>Indeed, the core idea is that a Patient participates in a Clinical Trial, suffers from some Diseases, and undergoes Events. These Events are different in nature and cover a wide range of cases, e.g. Onset, Pregnancy, Symptom, Trauma, Diagnostic Procedure (like evoked potentials or ALS-FRS questionnaires) Therapeutic Procedure (like Mechanical Ventilation for ALS or Disease-Modifying Therapy for MS), Relapse, and more. Overall, this event-based approach allows us to model ALS and MS in an unified way, sharing concepts among these two diseases, and to track what happens during their progression. </p> <p>The full BTO documentation can be accessed at <a href="https://brainteaser.dei.unipd.it/ontology/">https://brainteaser.dei.unipd.it/ontology/</a>.</p> <p>The BTO has been used to share the <a title="BRAINTEASER ALS and MS Datasets" href="https://doi.org/10.5281/zenodo.12789962" target="_blank" rel="noopener">BRAINTEASER ALS and MS Datasets</a>.</p>
◂Fig. 10 Iberozospeum praetermissum. Purple clade; a–f. (a) NMBE 557144, Cantabria, Cabezon-MS, Udias, Udias (Cobijon), 28.8.2016, sh: 1.25 mm; (b) NMBE 557253, Asturias, Llanes, Cueva La Herrería, 23.12.2017, sh: 1.34 mm; (c) NMBE 557255, Leon, Soto de Sajambre, Cueva Busecu, 10.3.2018, sh: 1.37 mm; (d) NMBE 557246, Asturias, Candamo, Cueva de la Peñona de Valdemora, 5.3.2018, sh: 1.22 mm; (e) NMBE 557140, Asturias, Llanes, Collubina, 18.7.2017, sh: 1.35 mm; (f) NMBE 559620, Cantabria, Cueva Puente Inguanzo, 6.4.2018, sh: 1.29 mm. — Iberozospeum spp. Green clade; g–n. (g) NMBE 559622, Cantabria, Cueva La Zurra, 6.4.2018, sh: 1.31 mm; (h) NMBE 557136, Asturias, Llanes, La Herrería, 18.7.2017, sh: 1.14 mm; (i) NMBE 557226, Cantabria, Lamason, El Toyo, 11.7.2015, sh: 1.7 mm; (j) NMBE 557225, Cantabria, Lamason, El Toyo, 11.7.2015, sh: 1.33 mm; (k) NMBE 557142, Asturias, Picos, Cabrales, Torca Cumbre,.8.2016, sh: 1.45 mm; (l) NMBE 557251, Asturias, Parres, Cueva El Caleru, 10.3.2018, sh: 1.41 mm; (m) NMBE 557249, Asturias, Yernes y Tameza, Cueva Llagar, 2.2.2018, sh: 1.49 mm; (n) NMBE 557247, Asturias, Candamo, Cueva de la Peñona de Valdemora, 5.3.2018, sh: 1.48 mm. — All phot.× 40 in Molecular investigation and description of Iberozospeum n. gen., including the description of one new species (Eupulmonata, Ellobioidea, Carychiidae)
◂Fig. 10 Iberozospeum praetermissum. Purple clade; a–f. (a) NMBE 557144, Cantabria, Cabezon-MS, Udias, Udias (Cobijon), 28.8.2016, sh: 1.25 mm; (b) NMBE 557253, Asturias, Llanes, Cueva La Herrería, 23.12.2017, sh: 1.34 mm; (c) NMBE 557255, Leon, Soto de Sajambre, Cueva Busecu, 10.3.2018, sh: 1.37 mm; (d) NMBE 557246, Asturias, Candamo, Cueva de la Peñona de Valdemora, 5.3.2018, sh: 1.22 mm; (e) NMBE 557140, Asturias, Llanes, Collubina, 18.7.2017, sh: 1.35 mm; (f) NMBE 559620, Cantabria, Cueva Puente Inguanzo, 6.4.2018, sh: 1.29 mm. — Iberozospeum spp. Green clade; g–n. (g) NMBE 559622, Cantabria, Cueva La Zurra, 6.4.2018, sh: 1.31 mm; (h) NMBE 557136, Asturias, Llanes, La Herrería, 18.7.2017, sh: 1.14 mm; (i) NMBE 557226, Cantabria, Lamason, El Toyo, 11.7.2015, sh: 1.7 mm; (j) NMBE 557225, Cantabria, Lamason, El Toyo, 11.7.2015, sh: 1.33 mm; (k) NMBE 557142, Asturias, Picos, Cabrales, Torca Cumbre,.8.2016, sh: 1.45 mm; (l) NMBE 557251, Asturias, Parres, Cueva El Caleru, 10.3.2018, sh: 1.41 mm; (m) NMBE 557249, Asturias, Yernes y Tameza, Cueva Llagar, 2.2.2018, sh: 1.49 mm; (n) NMBE 557247, Asturias, Candamo, Cueva de la Peñona de Valdemora, 5.3.2018, sh: 1.48 mm. — All phot.× 40
Dataset for "Atmospheric CFC-11 and CCl4: a Free Calibration Standard for PTR-MS"
<p>Dataset for the publication: Notø and Holzinger (2024), “Atmospheric CFC-11 and CCl4: a Free Calibration Standard for PTR-MS”, <br><a title="Atmospheric CFC-11 and CCl4: a Free Calibration Standard for PTR-MS" href="https://doi.org/10.1016/j.ijms.2024.117311">https://doi.org/10.1016/j.ijms.2024.117311</a></p> <p>The data consists of raw data files of measurements and the processing code to calculate pseudo reaction rate constants of CFC-11 and CCl4 with H3O+.</p>
Yeast proteomics microflow 23 min gradient DIA-MS
<p><em>Saccharomyces cerevisiae</em> (BY4743 rendered prototrophic with a plasmid encoding for HIS3, LEU2 and URA3 <a href="https://paperpile.com/c/AXHME6/nwrF">[25]</a>) were grown to exponential phase in minimal synthetic nutrient media. Proteins were extracted by bead beating for 5min at 1500rpm in 8M urea/0.1M ammonium bicarbonate. Proteins were reduced with 5mM dithiothreitol, alkylated with 10mM iodoacetamide. The sample was diluted to 1.5M urea/0.1M ammonium bicarbonate before the proteins were digested overnight with Trypsin (1:30 Trypsin to total protein ratio). Peptides were cleaned-up with 96-well MacroSpin plates (Nest Group) and iRT peptides (Biognosys AG) were spiked in.</p> <p>The digested peptides were analysed on a nanoAcquity (Waters) coupled to a TripleTOF 6600 (Sciex). Peptides were separated with a 23 minute non-linear gradient (4% Acetonitrile/0.1 % formic acid to 36% Acetonitrile/0.1% formic acid) on a Waters HSS T3 column (150mm x 300μm, 1.8μm Particles) with a 5μl/min flow rate. The DIA method consisted of an MS1 scan from m/z 400 to m/z 1250 (50ms accumulation time) and 40 MS2 scans (35ms accumulation time) with variable precursor isolation width covering the mass range from m/z 400 to m/z 1250.</p>
PLD results with BRES-Ms. 1333
<p>Combination of screenshots with 'color' and 'shaded' shaders of KU Leuven Libraries, Special Collections: BRES-Ms. 1333; A and B details with incorporated measure tool activated, rendered in PLDviewer 7.0.05.</p>
MALDI-TOF MS spectra data included in Dumolin et al. 2019
<p>MALDI-TOF MS and genome assembly data used for benchmarking of the SPeDE dereplication program.</p> <p> </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.