Project description:Mass spectrometry-based metabolomics is developed rapidly in the past few decades. There are few major vendors for LC-MS platform instruments, for example, Thermo ScientificTM LTQ Orbitrap Velos and Agilent 6510 Q-TOF mass spectrometer were used for metabolomics research. The data acquired cross different platform are rarely compared other than the comparison of the instrument itself on resolution, mass accuracy, sensitivity, dynamic range, scan speed etc., which is largely due to the foundation and principle of the instrument design. Other than this, there are many choice for data preprocessing, i.e., the data acquired from the same platform may have been processed with different feature extraction software tools. The discrepancy for the feature detections with different software will lead to the variation of the down-stream statistics analysis and metabolomics pathway interpretation. In addition, the impact of the LC-MS platform and data preprocessing software tools on the quantitative capabilities is also an interesting topic. In this research, XCMS, mzMine 2.37 and apLCMS are three tools used for the feature extraction of data acquired with Thermo ScientificTM LTQ Orbitrap Velos and Agilent 6510 Q-TOF LC-MS platform by serial dilution experiment. The quantification capability is estimated at the same time based on the linearity, accuracy, and precision
Project description:Mass spectrometry-based metabolomics is developed rapidly in the past few decades. There are few major vendors for LC-MS platform instruments, for example, Thermo ScientificTM LTQ Orbitrap Velos and Agilent 6510 Q-TOF mass spectrometer were used for metabolomics research. The data acquired cross different platform are rarely compared other than the comparison of the instrument itself on resolution, mass accuracy, sensitivity, dynamic range, scan speed etc., which is largely due to the foundation and principle of the instrument design. Other than this, there are many choice for data preprocessing, i.e., the data acquired from the same platform may have been processed with different feature extraction software tools. The discrepancy for the feature detections with different software will lead to the variation of the down-stream statistics analysis and metabolomics pathway interpretation. In addition, the impact of the LC-MS platform and data preprocessing software tools on the quantitative capabilities is also an interesting topic. In this research, XCMS, mzMine 2.37 and apLCMS are three tools used for the feature extraction of data acquired with Thermo ScientificTM LTQ Orbitrap Velos and Agilent 6510 Q-TOF LC-MS platform by serial dilution experiment. The quantification capability is estimated at the same time based on the linearity, accuracy, and precision.
Project description:Lung transcriptome sequencing anlysis in LPS-induced ALI model rats (Male Sprague-Dawley rats) after treatment with Ma Xing Shi Gan Decoction, In summary, our study suggests that MXSG inhibits viral invasion, proliferation, and mitigation of virus-induced lung injury, which may be a key mechanism of its therapeutic effect on COVID-19. These results provide experience for the treatment of infectious diseases and lung injury. we dissected the chemical components of MXSG by liquid chromatography-mass spectrometry (LC-ESI-MS/MS) and analyzed the intervention pathways of MXSG based on components detected through network pharmacology. At the same time, the therapeutic effect of MXSG on COVID-19 was explained through published articles, and the relevant regulatory mechanism was proposed. Then, in this study, the regulatory effect of MXSG on inflammatory lung injury was explorated through transcriptome results.
Project description:The concentrations of twenty kinds of hormones in the follicular fluid were detected by high-performance liquid chromatography–mass spectrometry (HPLC-MS/MS). An Agilent 1200 series high-performance liquid chromatography (HPLC) instrument (Agilent, USA) was utilized. A PAL autosampler (CTC, Swiss) and a Gemini-NX-C18 column (2.0 mm×50 mm, 3 μm, Waters, USA) were used. The ion source was an API-4000 quadrupole electrostatic field orbit trap high-resolution mass spectrometer (Applied Biosystems, USA). The scanning mode was multiple reaction monitoring (MRM) (Agilent-1200 LC system coupled to an API400 mass spectrometer).
Project description:MIADB: a cumulative collection of 172 tandem mass spectrometry (MS/MS) of a vast array of monoterpene indole alkaloids. Samples were analyzed using an Agilent LC-MS system composed of an Agilent 1260 Infinity HPLC coupled to an Agilent 6530 ESI-Q-TOF-MS operating in positive mode. A Sunfire analytical C18 column (150 × 2.1 mm; i.d. 3.5 μm, Waters) was used, with a flow rate of 250 μL/min and a linear gradient from 5% B (A: H2O + 0.1% formic acid, B: MeOH) to 100% B over 30 min. ESI conditions were set with the capillary temperature at 320 °C, source voltage at 3.5 kV, and a sheath gas flow rate of 10 L/min. The divert valve was set to waste for the first 3 min. There were four scan events: positive MS, window from m/z 100−1200, then three data-dependent MS/MS scans of the first, second, and third most intense ions from the first scan event. MS/MS settings were three fixed collision energies (30, 50, and 70 eV), default charge of 1, minimum intensity of 5000 counts, and isolation width of m/z 2. In the positive-ion mode, purine C5H4N4 [M + H]+ ion (m/z 121.050873) and the hexakis(1H,1H,3H-tetrafluoropropoxy)-phosphazene C18H18F24N3O6P3 [M + H]+ ion (m/z 922.009 798) were used as internal lock masses. Full scans were acquired at a resolution of 11 000 (at m/z 922). A permanent MS/MS exclusion list criterion was set to prevent oversampling of the internal calibrant.