Evidence map›Paper›PMID 25383071›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2014

Xuan Wang, Mary Hu, Ju Feng, Maili Liu, Jian Zhi Hu

Open access · greenAbstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.3field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Metabolomics Based onFoods (Basel, Switzerland) · 2021
    Article
  5. One extraction tool forJournal of pharmaceutical analysis · 2021
    Article
  6. Review
  7. Article
  8. Article
  9. Metabolomics : Official journal of the Metabolomic Society · 2018
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Metabolomics : open access
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Xuan WangPacific Northwest National Laboratory, Richland, WA 99352, USA ; Wuhan Institute of Physics and Mathematics, the Chinese Academy of Sciences, Wuhan, 430071, PR China.
Mary HuPacific Northwest National Laboratory, Richland, WA 99352, USA.
Ju FengPacific Northwest National Laboratory, Richland, WA 99352, USA.
Maili LiuWuhan Institute of Physics and Mathematics, the Chinese Academy of Sciences, Wuhan, 430071, PR China.
Jian Zhi HuPacific Northwest National Laboratory, Richland, WA 99352, USA.
Pacific Northwest National Laboratory · US

Funding

A 1.5-T superconducting solenoid-dipole magnet for a magic-angle spinning fieldR01EB013231 · NIBIB · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI IWASA, YUKIKAZU · 2011 to 2013
$1.9M
Slow-MAS NMR MetabolomicsR01ES022176 · NIEHS · BATTELLE PACIFIC NORTHWEST LABORATORIES · PI HU, JIAN ZHI · 2012 to 2015
$1.6M
NIBIB NIH HHS R01 EB013231NIEHS NIH HHS R01 ES022176
6 · The paper itself

Abstract

Melanoma is a malignant tumor of melanocytes. Although extensive investigations have been done to study metabolic changes in primary melanoma in vivo and in vitro, little effort has been devoted to metabolic profiling of metastatic tumors in organs other than lymph nodes. In this work, NMR-based metabolomics combined with multivariate data analysis is used to study metastatic B16-F10 melanoma in C57BL/6J mouse spleen. Principal Component Analysis (PCA), an unsupervised multivariate data analysis method, is used to detect possible outliers, while Orthogonal Projection to Latent Structure (OPLS), a supervised multivariate data analysis method, is employed to find important metabolites responsible for discriminating the control and the melanoma groups. Two different strategies, i.e. spectral binning and spectral deconvolution, are used to reduce the original spectral data before statistical analysis. Spectral deconvolution is found to be superior for identifying a set of discriminatory metabolites between the control and the melanoma groups, especially when the sample size is small. OPLS results show that the melanoma group can be well separated from its control group. It is found that taurine, glutamate, aspartate, O-Phosphoethanolamine, niacinamide,ATP, lipids and glycerol derivatives are decreased statistically and significantly while alanine, malate, xanthine, histamine, dCTP, GTP, thymidine, 2'-Deoxyguanosine are statistically and significantly elevated. These significantly changed metabolites are associated with multiple biological pathways and may be potential biomarkers for metastatic melanoma in spleen.

Indexed as

1HNMR metabolomics, B16-F10 melanomametabolomicsmultivariate analysisOPLS, and PCAspleen

Identifiers

PMID25383071
PMCPMC4220309
OpenAlexW2006272991

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.