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13 protocols using agilent 6490

1

Separation and Quantification of Ecdysteroids

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Separation of ecdysteroid was performed on Agilent 1200 HPLC chromatographic system with a mobile phase solvent A (100% water containing 5‐mM ammonium formate in 0.02% formic acid)/B (Acetonitrile/water [90:10 v/v] containing 5mM ammonium formate and 0.02% formic acid) (v/v). A gradient elution program (A) and (B), was employed at a constant flow rate of 0.2 ml/min. The analysis run time is 10.5 and 4 min for the equilibrium time (post Run), the injection volume was 5 μl. A triple quadrupole mass spectrometer (Agilent 6,490, Palo Alto, CA, USA) with an ESI source in the positive ion mode was used with a drying gas flow of 15 L/min at 250°C, sheat gas flow of 11 L/min at 250°C the desolvatation temperature was set to 250°C and the nebulizer gas to 45 psi. The capillary voltage was 4 kV and the fragmentor voltage was fixed at 380 V, the parent compound and its metabolite were detected using the Multiple reaction monitoring (MRM) acquisition mode.
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2

Salivary PGE2 Quantification by LC-MS/MS

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Analysis of PGE2 was performed by LC-MS/MS (liquid chromatography–tandem mass spectrometry) at the Immunochemical Core Lab, Mayo Clinic. Saliva was combined with deuterated internal standard, indomethacin, formic acid, and acetonitrile before liquid-liquid extraction with ethyl acetate hexane. Extracts were injected onto a reversed-phase high-performance LC analytical column with C12 guard cartridge and analyzed via an Agilent 6490 tandem mass spectrometer (Agilent Technologies, Santa Clara, Calif) with electrospray ionization in negative mode. Interassay imprecision coefficient of variance (CV) was found to be 4.5% to 10.5% for samples ranging from 133 to 530 pg/mL, and lower limit of quantitation was defined as 77 pg/mL with a CV of 14.6%.
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3

Comprehensive Lipidomics Analysis of Alzheimer's

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A more detailed lipidomics method was applied in the ADNI-1 samples to obtain better coverage of the sphingolipidome. Methodology on the ADNI cohort was as described by Huynh et al.21 (link). In brief, extracted samples were run using reverse phase liquid chromatography coupled with a triple quadrupole mass spectrometer (Agilent 6490, Agilent). Characterization of sphingolipid isomers has been reported previously82 (link) where repeated pooled runs using differing mass spectrometry conditions to obtain structurally informative fragments in MS/MS. Ratios were generated using 112 sphingolipid species and log2-transformed. Linear regression with ADAS-Cog. 13 was done with age, sex, BMI, HDL-C, total cholesterol, clinical triglycerides, fasting status, and APOE e4 genotype as covariates. p-values were corrected for multiple correction comparison using the Benjamini and Hochberg approach83 .
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4

Plasma Protein Quantitation by LC-MRM-MS

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All steps of solution and sample preparation, LC/MRM-MS parameters, are described in the article [3 (link)]. LC/MRM-MS analysis was performed with a Zorbax Eclipse Plus RP-UHPLC column on a 1290 Infinity UPLC system (all from Agilent Technologies) that was interfaced to a triple quadrupole mass spectrometer (Agilent 6490) via Agilent’s Jet Stream™ source, operated in the positive-ion ESI mode. Plasma tryptic digests were analyzed only once. The MRM data was visualized and examined with MassHunter Quantitative Analysis software (version B.07.00; Agilent). Quantitation was done using linear regression analysis, as described previously [8 (link)].
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5

Quantitative Proteomics by SRM Mass Spectrometry

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Serum samples were analyzed in a triple-quadrupole mass spectrometer (Agilent 6490, Agilent, Santa Clara, CA) integrated with a nanospray ion source and Chip Cube nano-HPLC. Three to four pairs of light (endogenous) and heavy (stable C13N15 isotope-labeled (SIL) synthetic standards) transitions were monitored for each target peptide. A 90-min gradient of acetonitrile from 3% to 40% was used to elute peptides from a high-capacity nano-HPLC Chip (160 nL, 150 mm × 75 μm ID, Agilent, Santa Clara, CA) as described elsewhere 26 (link). Other settings included operating the nano-HPLC separation chip at 0.3 μL/min nano pump flow rate, 2 μg peptide loading amount, 1820 V capillary voltage and Dynamic MRM with 200 Delta EMV (+). Duplicate runs were performed for each sample. All SRM parameters and results are deposited in the SRM chromatographic repository at ISB and are publicly available (http://www.srmatlas.org and http://www.peptideatlas.org/passel/, PASS01453). The final SRM methods used for 174 proteotypic peptides are summarized in Supplement Table 3 in PeptideAtlas SRM Experiment Library (PASSEL) format.
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6

Quantitative Analysis of Plasma SFN

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Plasma samples were analysed for SFN and its conjugates using a method that has been described previously [13] with slight modifications. Briefly plasma samples (100 µl) were prepared by adding 20 µl precooled (4 °C) trichloroacetic acid followed by centrifugation at 11 600 g at 4 °C for 10 min. The injection volume was 5 µl, the HPLC column was a Luna (3 µm particle size, 100 × 2 mm from Phenomenex) using mobile phase flow 0.25 ml/min, the mobile phase were consisted of ammonium acetate buffer (13 mmol/L, pH4; solvent A) and acetonitrile plus 0.1% acetic acid (solvent B) in a linear gradient from 5% B to 35% B over 5 min with 6 min re equilibration time. Agilent 6490 Mass spectrometry analysis was performed with the use of electrospray ionization in positive ion mode with nitrogen gas and nitrogen sheath gas temperatures 160 °C and 400 °C, respectively, gas flow 16 l/min, Nebulizer pressure 30 psi, sheath gas flow 12 l/min and capillary voltage 4000 V.
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7

Quantification of Nafamostat by LC-MS/MS

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The LC-MS/MS analysis was performed by Agilent 6490 (Agilent Technologies, Santa Clara, CA, USA) coupled with Agilent 1260 HPLC system (Agilent Technologies). The analyte was separated on a Gemini 5 μm C18 110A column (150 × 2 mm i.d., 5 μm, Phenomenex, Torrence, CA, USA) with SecurityGuard Cartridge Kit (Phenomenex). An isocratic mobile phase composed of 0.1% aqueous formic acid and methanol (50:50 v/v %) was used with a flow rate of 0.3 mL/min. The column oven temperature was 40 °C and the total run time was 6 min.
The electrospray ionization (ESI) source was operated in positive mode, and the mass spectrometer was operated in the multiple reaction monitoring (MRM) mode with a dwell time of 200 ms per MRM channel. Gas temperature, gas flow rate, and nebulizer gas pressure were set at 220 °C, 17 L/min, and 45 psi, respectively. The selected precursor/product ion pairs were m/z 174.4 → 165.8 for nafamostat and 177.4 → 168.9 for IS. The fragment voltage was 380 V, and the collision energy was set at 11 eV for both nafamostat and IS. The mass spectrometric data were processed by MassHunter Quantitative Analysis (Agilent Technologies).
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8

Urinary Phthalate Metabolites and BPA Quantification

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Eight urinary phthalate metabolites, including mono (2-ethyl5-hydroxyhexyl) phthalate (MEHHP), mono (2-ethyl-5-oxohexyl) phthalate (MEOHP), mono (2-ethyl-5-carboxypentyl) phthalate (MECPP), mono-benzyl-phthalate (MBzP), mono (carboxyoctyl) phthalate (MCOP), mono (carboxy-isononyl) phthalate (MCNP), mono (3-carboxypropyl) phthalate (MCPP), and mono-n-butyl-phthalate (MnBP), and BPA were analyzed. After collecting the participants’ midstream voided urine, the collection container was shielded, immediately stored at 2°C to 6°C, and frozen at –20°C until analysis. Ultra-performance liquid chromatography-mass spectrometry (Agilent 6490, Agilent Technologies Inc., Santa Clara, CA, USA) was used to analyze the concentrations of urinary phthalate metabolites and BPA. Quality control procedures for the analytes were carried out in accordance with the recommendations of the NIER [11 (link)].
Before statistical analysis, each concentration below the limit of detection (LOD) was imputed as the LOD value divided by √2. The LOD values were as follows: MEHHP, 0.056 µg/L; MEOHP, 0.048 µg/L; MECPP, 0.141 µg/L; MBzP, 0.066 µg/L; MCOP, 0.048 µg/L; MCNP, 0.139 µg/L; MCPP, 0.078 µg/L; MnBP, 0.040 µg/L; and BPA, 0.075 µg/L [11 (link)].
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9

Targeted Serum Proteomics for Obesity

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Serum samples were processed following a previously published protocol that ensured maximum yield of signal (49 (link)). We targeted a curated selection of 22 mostly organ-specific proteins with known genetic variants associated with obesity or metabolic syndrome (Table S1). Prepared samples, along with spiked-in heavy-isotope-labeled synthetic standard peptides, were quantified using a triple-quadrupole mass spectrometer (Agilent 6490; Agilent, Santa Clara, CA) with a nanospray ion source and Chip Cube nano-HPLC. Three to four transitions were monitored for each target peptide (see Table S1). Two micrograms of tryptically digested Mars-14 (Agilent, Santa Clara, CA) depleted serum was eluted from a high-capacity nano-HPLC chip (160 nl, 150 mm by 75 μm inside diameter [i.d.]; Agilent, Santa Clara, CA) with a 30-min gradient of 3 to 40% acetonitrile as described previously (49 (link), 50 (link)). Raw selective reaction monitoring (SRM) mass spectrometry data were analyzed with the Skyline targeted proteomics environment (51 (link)). Each detected peptide was quantified by the light/heavy (L/H) ratio of monitored transitions, after adjusting for the volume of the original serum sample.
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10

Lipid Separation and Quantification Protocol

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Lipids from the isolated “fat pads” were resuspended in butanol:methanol (1:1, v/v) to a final concentration of 1 mg mL−1. Lipids were chromatographically separated using a Waters BEH C8 column (Waters, Milford, MA) and a binary gradient with a flow rate of 0.2 mL min−1 on an Agilent 1290 liquid chromatography (Agilent Technologies). The mobile phases were: A. H2O:acetonitrile (10:90, v:v) with 10 mM ammonium formate and 0.2% acetic acid; B. H2O:acetonitrile:isopropanol (5:15:80, v:v:v) with 10 mM ammonium formate and 0.2% acetic acid. The gradient was initially held at 1% B for 2 min, then increased to 20% B over the next 3 min, then increased to 70% B over 7 min, followed by a final increase to 90% B over 2 min. The eluted lipids were analyzed on an Agilent 6490 (Agilent Technologies) based on previously published methods (Reynolds et al., 2015 (link)). Results were analyzed by integration using Mass Hunter Quantitative Analysis for QQQ, version B.07.01 (Agilent Technologies) followed by export of the data to csv format and analysis in R (R Core Team, 2016 ).
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