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173 results for “HPLC”
Gradients2-MGL1704-HPLC_2020-03-25_v1.0
<p>Cruise: Gradients 2, MGL1704</p> <p>Project Name: Simons Foundation Gradients 2 NPSG</p> <p>Description: Samples were processed to detect and quantify phytoplankton pigments using a modified version of the high-performance liquid chromatography (HPLC) method of Wright et al. (1991) as described by Bidigare et al. (2005). HPLC samples were collected by semi-automated and sequential filtration of the ship's underway flow through seawater onto Whatman GF/F filters (0.7 µm nominal pore size) and stored at -80°C until analysis. Filters were extracted in 100% acetone for 24 h at 4°C. Extracts were processed in reverse-phase on a 250 mm C18 column using a Waters separations module and photodiode detector array. Empower chromatography software was used for integration and pigment quantification. The instrument was calibrated using chlorophyll a from Anacystis nidulans (Sigma USA) and mixed pigment standards were obtained from DHI in Denmark.</p>
Automated analysis of HPLC chromatograms obtained during the dehydration of N-Acetylglucosamine into 3-Acetamido-5-acetylfurane using Python
<p><strong>Content: </strong>This dataset contains High Performance Liquid Chromatography (HPLC) chromatograms, obtained while studying the dehydration of N-Acetylglucosamine into 3-Acetamido-5-acetylfurane in DMAc, DMF and NMP employing various catalysts and screening different reaction conditions. Reaction conditions can be retrieved from the metadata attached. Importantly, a python script to automatically extract, plot and analyze the HPLC-data obtained is provided.</p><p><strong>Acknowledgements</strong>: The authors acknowledge support by the German Research Foundation (DFG) within NFDI4Cat (ID 441926934). Parts of this work were funded by the Cluster of Excellence Fuel Science Center (EXC 2186, ID: 390919832) funded by the Excellence Initiative by the German federal and state governments. Furthermore, the authors thank Jens Heller and Frederic Thilmany for performing the HPLC measurements.</p><p> </p>
Development of a HPLC Method for Improved Detection and Analysis in Glycerol Electrooxidation Studies
<p># Dataset of "Development of a HPLC Method for Improved Detection and Analysis in Glycerol Electrooxidation Studies"</p> <p>---</p> <p>## GENERAL INFORMATION<br>----------------------</p> <p>1. Dataset title: "Development of a HPLC Method for Improved Detection and Analysis in Glycerol Electrooxidation Studies"</p> <p>2. Authorship: <br> Name: Eva Ng <br> Institution: Institute of Advanced Materials (INAM), Universitat Jaume I, 12006 Castelló, Spain<br> ORCID: 0009-0003-4184-5579</p> <p> Name: Camilo A. Mesa<br> Institution: Institute of Advanced Materials (INAM), Universitat Jaume I, 12006 Castelló, Spain<br> ORCID: 0000-0002-8450-2563</p> <p> Name: Sixto Giménez<br> Institution: Institute of Advanced Materials (INAM), Universitat Jaume I, 12006 Castelló, Spain<br> Email: <sjulia@uji.es> <br> ORCID: 0000-0002-4522-3174</p> <p>## FILE DESCRIPTION<br>--------------<br>### Figure 1<br>- Fig1a.txt : Chromatogram obtained from the analysis of the analytical standards containing glycerol electrooxidation products previously reported. <br>- Fig1b.txt : Chromatogram obtained from the analysis of the analytical standards containing glycerol electrooxidation products in this work.</p> <p><br>### Figure 2<br>- Fig2a.txt : Referential chromatograms from analytical standards that can be produced during Glycerol Electrooxidation Reaction (GEOR). Reported method.<br>- Fig2b.txt : Referential chromatograms from analytical standards that can be produced during Glycerol Electrooxidation Reaction (GEOR). New developed method.</p> <p><br>### Figure 3<br>- Fig3a.txt : Calibration curve for oxalic acid analytical standard from 0.1 mM to 5 mM and its standard deviation. Each point was measured by triplicate.<br>- Fig3b.txt : Calibration curve for tartronic acid analytical standard from 0.1 mM to 5 mM and its standard deviation. Each point was measured by triplicate.<br>- Fig3c.txt : Calibration curve for L-sodium glycerate analytical standard from 0.1 mM to 5 mM and its standard deviation. Each point was measured by triplicate.<br>- Fig3d.txt : Calibration curve for glycolic acid analytical standard from 0.1 mM to 5 mM and its standard deviation. Each point was measured by triplicate.<br>- Fig3e.txt : Calibration curve for formic acid analytical standard from 0.1 mM to 5 mM and its standard deviation. Each point was measured by triplicate.<br>- Fig3f.txt : Calibration curve for dihydroxyacetone analytical standard from 0.1 mM to 5 mM and its standard deviation. Each point was measured by triplicate.<br>- Fig3g.txt : Calibration curve for glyceraldehyde analytical standard from 0.1 mM to 5 mM and its standard deviation. Each point was measured by triplicate.<br>- Fig3h.txt : Calibration curve for glycerol analytical standard from 0.1 mM to 5 mM and its standard deviation. Each point was measured by triplicate.</p> <p>### Figure 4<br>- Fig4.txt : Glyceraldehyde standard concentrations as a function of different wavelengths. Each measurement was performed by triplicate and it is shown with its standard deviation.</p> <p>### Figure 5<br>- Fig5.txt : Experimental concentrations at different calibration levels for glyceraldehyde and formic acid quantification with their standard deviation. Each measurement was performed by triplicate.</p> <p>### Figure 6<br>-Fig6a.txt : Chromatograms obtained from a potentiostatic measurement performed at 1.62 V vs RHE in a solution containing LiOH 0.1 M and glycerol 50 mM and analytical standards as a reference. <br>-Fig6b.txt : Product distribution represented in terms of Faradaic Efficiency (FE). The percentages above the bars represent the total (FE) while inside the bars, they refer to the different products. </p>
HPLC Data associated with PI3KC3-C1 activation paper
<p>HPLC data of bound nucleotides and nucleotide standards</p>
Implementación del proyecto Fortalecimiento de la capacidad instalada del laboratorio de cromatografía líquida, HPLC-MS (Bioanalitics) de la Universidad del Valle, para la investigación en la región pacífico - Valle del Cauca"
<p>Dentro del Plan Estratégico de Desarrollo 2015-2025 de la Universidad del Valle (UNIVALLE)1, se creó el Programa para el Fortalecimiento del Sistema de Laboratorios. De manera complementaria, se plantea crear el sistema de laboratorios articuladores tipo core facilities también llamados laboratorios centralizados, laboratorios articuladores o Laboratorios Estratégicos Compartidos (LEC´s). Este mismo tipo de sistemas de laboratorios ya se encuentran funcionando en otras universidades en Colombia2-5. Para determinar cuál debería ser el primer LEC de la Universidad del Valle, se procedió a hacer una investigación de las necesidades más apremiantes de los grupos de investigación dentro de la Institución, y que también puedan fortalecer las necesidades de la región pacífico desde el centro universitario. Es por ello que con el estudio realizado, se determina que la Universidad cuenta con más de 30 grupos de investigación y más de 15 laboratorios investigando en temas relacionados con biodiversidad, agroindustria, sistemas agropecuarios, alimentos, medio ambiente y salud. Pero la universidad no cuenta con la tecnología necesaria que respalde la realización de investigaciones que permitan la caracterización e identificación de compuestos conocidos y desconocidos en las muestras relacionadas con las áreas anteriormente mencionadas. Para fortalecer la infraestructura tecnológica para el desarrollo de actividades que sirvan a la identificación y caracterización de compuestos (análisis molecular) se propone crear el laboratorio articulador BIOANALITICS. Un laboratorio de uso compartido e interdisciplinario para los grupos de investigación que impactan en los focos Agroindustria y Agropecuario, Salud (farmacia y nutrición), Biodiversidad y Medio Ambiente. BIOANALITICS tendrá como base la compra de un equipo de cromatografía líquida (LC) acoplado a espectrometría de masas de alta resolución (HRMS). Con este trabajo se pretende presentar el desarrollo investigativo que se llevó a cabo desde la propuesta del programa de Fortalecimiento del Sistema de Laboratorios hasta la puesta en marcha del laboratorio bioanalitics financiado por el Sistema General de Regalías con recursos que provienen del fondo de ciencia, tecnología e innovación de las regiones del Cauca, Chocó, Nariño y Valle del Cauca, complementado con recursos propios de la Universidad del Valle, y al mismo tiempo se pretende presentar cómo se proyecta el laboratorio y como plantea su funcionamiento de acuerdo a los principios básicos de los laboratorios tipo core-shell6 Entre los resultados esperados se encuentran la articulación de grupos de investigación en proyectos interdisciplinarios, apoyar los procesos de formación para estudiantes de maestría y doctorado, y tener posgrados competitivos a nivel internacional con atracción de nuevos estudiantes de maestría y doctorado, incluso internacionales, con lo que se espera fomentar las publicaciones de alto impacto, permitiendo el retorno de la diáspora de investigadores colombianos que deseen hacer investigación aplicando estas técnicas analíticas. Se discutirá acerca de los problemas, y los beneficios que se han identificado durante la implementación de Bioanalitics, desde su concepción, hasta la realidad transformada al día de hoy, al igual que la implementación de políticas para la administración, manejo y uso de los laboratorios articuladores dentro del sistema de gestión de calidad de la UNIVALLE.</p>
In-situ observations of surface Chlorophyll-a (HPLC) in the Western Antarctic Peninsula during 2008-2018 (GOAL-FURG)
<p>This dataset contains observations of in-situ chlorophyll-a (mg/m3) along the Western Antarctic Peninsula from 2008 to 2018. All data included in this dataset were collected by the Brazillian High Latitude Oceanography Group (GOAL), based at the Federal University of Rio Grande (FURG), aboard research vessels from the Brazillian Navy.</p> <p>All chlorophyll-a samples were collected at 5 metres depth. Chlorophyll-a concentration was determined through High Pressure Liquid Chromatography. This dataset has been collected thanks to a 10 year effort of sampling by GOAL in the Western Antarctic Peninsula. As such, many researchers, students, and crew members contributed to this valuable dataset. Therefore, we ask that users acknowledge the use of the dataset.</p> <p>Please consult Ferreira et al. 2024 for more information on how the data was collected and analysed.</p>
Gradients 4 - TN397 - HPLC - CTD
<p>Cruise Name: Gradients 4 , TN397</p> <p>Vessel: R/V Thompson</p> <p>Funding: Simons Collaboration on Ocean Processes and Ecology (SCOPE)</p> <p>Dataset description:</p> <p>This dataset was collected on the R/V Thompson during the Gradients IV cruise which departed from San Diego, CA and ended in Honolulu, HI. A transect was performed on the 140 degree longitude line from roughly 19 degrees N to 2.5 degrees S before heading to Honolulu. Samples were processed to detect and quantify phytoplankton pigments using a modified version of the high-performance liquid chromatography (HPLC) method of Wright et al. (1991) as described by Bidigare et al. (2005). HPLC samples were collected from CTD niskin bottles and filtered onto Whatman GF/F filters and stored at -80°C until analysis. Filters were extracted in 100% acetone for 24 h at 4°C. Extracts were processed in reverse-phase on a 250 mm C18 column using a Waters separations module and photodiode detector array. Empower chromatography software was used for integration and pigment quantification. The instrument was calibrated using chlorophyll a from Anacystis nidulans (Sigma USA) and mixed pigment standards were obtained from DHI in Denmark. Timestamps are in UTC time.</p> <p> </p>
BiG RAPA Water Column HPLC Pigments from R/V Melville MV1015 in the South Pacific from Arica, Chile to Easter Island from November to December 2010 (C-MORE project)
<p>“The South East Pacific (SEP) is characterized by very high nutrient concentrations in the waters adjacent to the Chilean coast, but very low nutrient concentrations (oligotrophic) in the mid- South Pacific Subtropical Gyre (SPSG), near Easter Island. The steep gradient in nutrient concentrations across the region affects the level of marine production, the composition of the microbial community, and the operation of major biogeochemical cycles in ways that are not fully understood. Despite the remarkable diversity of trophic conditions, strong gradients and even some unique singularities, the SEP is still the most sparsely sampled oceanic region of the global ocean from hydrodynamic, biological and biogeochemical points of view. The SPSG is also the most oligotrophic of all sub-tropical gyres. Previous expeditions and remote sensing studies have describes the nutrient and chlorophyll field, but there have been few simultaneous measurements of chemical properties with microbial community structure and function. This expedition is designed to investigate the impact of elemental nutrient (nitrogen, phosphorus, iron, silicon, carbon) ratios on marine productivity and microbial community composition.” This BiG RAPA dataset contains water column HPLC pigment data from samples collected via Niskin bottles attached to a CTD. Time is in GMT.</p> <p><br> This description has been reproduced using the following source:</p> <p><br> http://dmoserv3.bco-dmo.org/jg/info/BCO-DMO/CMORE/bigrapa/pigments_watcol%7Bdir=dmoserv3.bco-dmo.org:80/jg/dir,data=dmoserv3.bco-dmo.org:80/jg/serv/BCO-DMO/CMORE/bigrapa/pigments_watcol.html1%7D?</p>
Ability of Mayo Clinic High-performance Liquid Chromatography (HPLC) Method to Measure Fecal Bile Acids
ClinicalTrials.gov study NCT02111603. IPD Sharing: YES. Countries: 1. Publications: 1.
Data from: Paralytic shellfish toxin concentrations measured in alaskan arctic clams using ELISA and HPLC methods
Open the record for dataset details and reuse information.
Deep eutectic solvent-based emulsification liquid-liquid microextraction coupled with HPLC-UV for the analysis of phenoxy acid herbicides in paddy field water samples
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Supplementary material 1 from: Sharmin S, Sohrab MH, Moni F, Afroz F, Rony SR, Akhter S (2020) Simple RP-HPLC method for Aceclofenac quantitative analysis in pharmaceutical tablets. Pharmacia 67(4): 383-391. https://doi.org/10.3897/pharmacia.67.e57981
Table S1. HPLC Analytical methods for simultaneous estimation of Aceclofenac with other constituents
Factorial design assisted RP-HPLC method for simultaneous determination of fluconazole, itraconazole, and terbinafine
<p>A 2<sup>3</sup> full factorial design model was utilized for development of a new HPLC method with UV detection to estimate three antifungal drugs simultaneously. Fluconazole (FLU), itraconazole (ITR) and terbinafine (TRH), which are co-administered for severe fungal infections have been determined using MOS-1 Hypersil C18 column and an isocratic eluent; methanol 95% and phosphate buffer 5% with 0.001% triethylamine. The pH adjusted 7, and flow rate of 0.7 mL/min. The three drugs were separated within less than 7 minutes at 210 nm. The developed method gave linear response over 5-80, 5-50 and 1-50 μg/mL for FLU, ITR and TRH, respectively. It showed detection limits of 0.8761, 0.293 and 0.1965 μg/mL and quantification limits of 2.655, 0.8788 and 0.5956 μg/mL for the three drugs, respectively. The design of experiment facilitated the optimization of different variables affecting the separation of the three drugs. The designed method sensitivity permitted the simultaneous estimation of ITR and TRH in spiked human plasma successfully.</p>
Proteolytic Profiling of Streptococcal Pyrogenic Exotoxin B (SpeB) by Complementary HPLC-MS Approaches.
<p>Streptococcal pyrogenic exotoxin B (SpeB) is a cysteine protease expressed during group A streptococcal infection that represents a major virulence factor. Although subject to several studies, its role during infection is still under debate, and its proteolytic properties remain insufficiently characterized. Here, we revisited this protease through a set of complementary approaches relying on state of-the-art HPLC-MS methods. After conceiving an efficient protocol to recombinantly express SpeB, the zymogen of the protease and its activation were characterized. Employing proteome-derived peptide libraries, a strong preference for hydrophobic and aromatic residues at P2 alongside negatively charged amino acids at P3′ to P6′ was revealed. To identify relevant in vivo substrates, native proteins were obtained from monocytic secretome and plasma to assess their cleavage under physiological conditions. Besides corroborating our findings concerning specificity, more than 200 cleaved proteins were identified, including proteins of the extracellular matrix, proteins of the immune system, and proteins involved in inflammation. Finally, the cleavage of IgG subclasses was studied in detail. This study precisely depicts the proteolytic properties of SpeB and provides a library of potential host substrates, including their exact cleavage positions, as a valuable source for further research to unravel the role of SpeB during streptococcal infection.</p>
HPLC data of NEREA Augmented Observatory
<p>The water used for the determination of the pigment spectrum by HPLC accounts for 2-3 litres for each depth. The seawater is filtered on GF/F filters (diameter 47mm). The filters are stored in liquid nitrogen until pigments HPLC analysis. HPLC pigments separations were made on an Agilent 1100 HPLC (Agilent technologies, United States). The system was equipped with an HP 1050 photodiode array detector and a HP 1046A fluorescence detector for the determination of chlorophyll degradation products. Instrument calibration was carried out with external standard pigments provided by the International Agency for 14C determination-VKI Water Quality Institute. </p>
Supplemental Table S1. Total AA profile (exclusive Tyr and Trp) (g/kg DM) analysed with HPLC after acid hydrolysis (EC, 1998) for the feed stuffs used in the low protein diet during the experiment.
<p><strong>Supplemental Table S1.</strong> Total AA profile (exclusive Tyr and Trp) (g/kg DM) analysed with HPLC after acid hydrolysis (EC, 1998) for the feed stuffs used in the low protein diet during the experiment.</p>
Fig. 7 in Glucosinolate profiles and phylogeny in Barbarea compared to other tribe Cardamineae (Brassicaceae) and Reseda (Resedaceae), based on a library of ion trap HPLC-MS/MS data of reference desulfoglucosinolates
Fig. 7. Levels of major glucosinolates in leaves of first year rosette plants of the Gtype (A) and P-type (B) of Barbarea vulgaris in plants subjected to various challenges or no challenge as control. The contrasting general profile of the types is evident from dominance of BAR in the G-type and EBAR in the P-type. Treatment codes are: Control, un-challenged plants harvested after 7 days; Pieris 3d and Pieris 7d, herbivory by Pieris brassicae larvae until harvest at either day 3 or day 7; Plutella, herbivory by Plutella xylostella for 4 days; CuCl2, spraying of leaves with 10 mM CuCl2 (aq.) followed by recovery for 4 days. Bars represent means, whiskers indicate standard deviation (N = 3 for each group).
Fig. 6 in Glucosinolate profiles and phylogeny in Barbarea compared to other tribe Cardamineae (Brassicaceae) and Reseda (Resedaceae), based on a library of ion trap HPLC-MS/MS data of reference desulfoglucosinolates
Fig. 6. Lack of the aliphatic glucosinolate (GSL) Pren (107) in B. vulgaris and spiking of pure (intact) Pren for establishing the limit of detection. A. Total ion chromatogram for the three dominating peaks in G-type B. vulgaris (dGSL preparation). B. Extracted ion trace for desulfo Pren in the same extract as A, showing lack of detection. C, D, E. Results of serial spiking of the crude extract with serial 10-fold dilutions of Pren before the desulfation procedure, showing linearity also at low levels and ability to detect trace levels.
Fig. 9 in Glucosinolate profiles and phylogeny in Barbarea compared to other tribe Cardamineae (Brassicaceae) and Reseda (Resedaceae), based on a library of ion trap HPLC-MS/MS data of reference desulfoglucosinolates
Fig. 9. Extracted ion HPLC-MS chromatograms of desulfoglucosinolates prepared from glucosinolates (GSLs) in seeds (A–F) or leaves (G) of Reseda luteola and seeds of Reseda odorata (H). The three major peaks (A, B, C) represent PE, IM and BAR, much like many Barbarea spp. Focus on minor peaks (D) allowed conclusive identification of EBAR, confirmed by tR and the characteristic MS2 spectrum. A range of putative derivatives were not detected (E, F), but an unidentified hydroxybutylGSL was present (G), as was a known glycoside in R. odorata.
Fig. 5 in Glucosinolate profiles and phylogeny in Barbarea compared to other tribe Cardamineae (Brassicaceae) and Reseda (Resedaceae), based on a library of ion trap HPLC-MS/MS data of reference desulfoglucosinolates
Fig. 5. MS2 spectra of desulfated glucosinolates (GSLs) confirming the identity of two 2-3homoMet-derived GSLs in C. hirsuta. While the spectrum of desulfo Buen contains only the usual fragments for this type of dGSL (a, [anhydroGlc+Na]+; b, [thioGlc+Na]+), the spectrum of desulfo Peen contains an additional usual fragment (c, [M-anhydroGlc Na]+) and two unusual + fragment ions suggesting a structure-specific cyclization and exchange of O during fragmentation: 201, [gluconolactone Na]+ and 152, [C H NS Na]+. + 6 11 + The unusual fragments can be rationalized as fragment a plus O and fragment c minus O, respectively.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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