Masshunter qualitative analysis 10
MassHunter Qualitative Analysis 10.0 software is a data analysis tool designed for use with Agilent's mass spectrometry instruments. The software provides functionality for the visualization, interpretation, and reporting of mass spectrometry data.
Lab products found in correlation
10 protocols using masshunter qualitative analysis 10
Quantitative HPLC Analysis of Levofloxacin
LC-MS Analysis of Small Molecules
Fatty Acid Composition and Nutritional Indices
HPLC-MS Analysis of Compounds
UHPLC-Q-TOF MS Analysis Protocol
Liquid Chromatography-Mass Spectrometry Drug Analysis
Agilent MassHunter Qualitative Analysis 10.0 software was used for data analysis. Retention time (RT, minutes), database scores (DBS), and library search scores (LSS) were used to determine positivity for all drugs in the scope based on validated criteria established during method development (33 (link)). A sample was considered positive if it met or exceeded the established criteria for RT, DBS, and LSS. Any results that met or exceeded the LSS, but did not meet RT or DBS criteria were manually reviewed for positivity. Results which did not meet these criteria were reported as none detected.
Metabolite Profiling by LC-MS
(Agilent G-6530) for metabolite identification. The instrument is
equipped with a C18 chromatographic column (100 mm × 2.7 μm
× 3.0 mm). The column oven was maintained at 35 °C. The
flow rate was 0.4 mL/min, and the mobile phase consisted of solvent
A (water, 0.1% formic acid) and solvent B (Acetonitrile, 0.1% formic
acid). Gradient elution conditions were set as follows: 0–0.5
min, 5% B; 0.5–7 min, 5 to 100% B; 7–8 min, 100% B;
8–8.1 min, 100 to 5% B; 8.1–10 min, 5%B.
Rely
on Agilent MassHunter Qualitative Analysis 10.0 for peak extraction
and filtering, sample retention time alignment, addition ion merging,
and missing value filling of raw data. Metabolite annotation was done
by comparison to the METLIN database.
Metabolites with a frequency
of occurrence greater than 50% in
all samples and greater than 66.6% in the same samples were labeled
as significant metabolites. Further, univariate analysis of variance
multiplicity (fold change) and T.TEST algorithm statistical tests
were used, BH correction was performed to obtain q-value, and metabolites with p-value less than 0.05
and log 2 (fold change) greater than 2 were labeled as significantly
differentiated metabolites.
Advancing Mass Spectrometry Analysis
Analysis 10.0 and IM-MS Browser 10.0 (Agilent Technologies) were used
for evaluation of the QTOFMS and IM-QTOFMS data, respectively. The
measured accurate masses are tabulated in
GC-QTOF Analysis of Chemical Samples
Mass Spectrometry Data Analysis
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