Summary of Study ST001270

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000855. The data can be accessed directly via it's Project DOI: 10.21228/M85H5H This work is supported by NIH grant, U2C- DK119886.

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Study IDST001270
Study TitleNecrotizing soft-tissue infections (NSTIs) metabolomics
Study SummaryNecrotizing soft-tissue infections (NSTIs) have multiple causes, risk factors, anatomical locations, and pathogenic mechanisms. In patients with NSTI, circulating metabolites may serve as substrate having impact on bacterial adaptation at the site of infection. Metabolic signatures associated with NSTI may reveal potential be useful as diagnostic and prognostic markers, as well as novel targets for therapy. This study used untargeted metabolomics analyses of plasma from NSTI patients (n=34) and healthy (non-infected) controls (n=24) to identify the metabolic signatures and connectivity patterns among metabolites associated with NSTI.
Institute
Wageningen University & Research
Last NameEdoardo
First NameSaccenti
AddressStippeneng 4, 6708 Wageningen, the Netherlands
Emailedoardo.saccenti@wur.nl
Phone+31644482628
Submit Date2019-10-28
Raw Data AvailableYes
Raw Data File Type(s)cdf
Analysis Type DetailGC-MS
Release Date2020-01-06
Release Version1
Saccenti Edoardo Saccenti Edoardo
https://dx.doi.org/10.21228/M85H5H
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Combined analysis:

Analysis ID AN002110
Analysis type MS
Chromatography type GC
Chromatography system Leco Pegasus III GC
Column Agilent DB 5-MS (10 m x 0.18 mm x 0.18 um)
MS Type EI
MS instrument type GC-TOF
MS instrument name Leco Pegasus III GC TOF
Ion Mode POSITIVE
Units Peak area

MS:

MS ID:MS001961
Analysis ID:AN002110
Instrument Name:Leco Pegasus III GC TOF
Instrument Type:GC-TOF
MS Type:EI
MS Comments:Raw data from MS-files were exported from the ChromaTOF software in NetCDF format to Matlab (Mathworks, Natick, MA, USA) format; data pre-processing, such as baseline correction, chromatogram alignment, data compression and Multivariate Curve Resolution were performed using in-house custom Matlab scripts. The extracted mass spectra were identified by comparisons of their retention index and mass spectra with libraries of retention time indices and mass spectra. Mass spectra and retention index comparison was performed using NIST MS 2.0 software. Annotation of mass spectra was based on reverse and forward searches in the library. Masses and ratio between masses indicative for a derivatized metabolite were especially notified.
Ion Mode:POSITIVE
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