Evidence map›Paper›PMID 23579186›Full record

ArticleMolecular & cellular proteomics : MCP2013

Protein sets define disease states and predict in vivo effects of drug treatment.

David Meierhofer, Christopher Weidner, Ludger Hartmann, Johannes A Mayr, Chung-Ting Han, Frank C Schroeder, Sascha Sauer

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

11 citing papers in PubMed.

  1. Article
  2. Natural Salicylates and Their Roles in Human Health.International journal of molecular sciences · 2020
    Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Proteomics for systems toxicology.Computational and structural biotechnology journal · 2014
    Review
  10. Article
  11. 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

7 authors.

David MeierhoferOtto Warburg Laboratory, Max Planck Institute for Molecular Genetics, Berlin, Germany.
Christopher Weidner
Ludger Hartmann
Johannes A Mayr
Chung-Ting Han
Frank C Schroeder
Sascha Sauer

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gaining understanding of common complex diseases and their treatments are the main drivers for life sciences. As we show here, comprehensive protein set analyses offer new opportunities to decipher functional molecular networks of diseases and assess the efficacy and side-effects of treatments in vivo. Using mass spectrometry, we quantitatively detected several thousands of proteins and observed significant changes in protein pathways that were (dys-) regulated in diet-induced obesity mice. Analysis of the expression and post-translational modifications of proteins in various peripheral metabolic target tissues including adipose, heart, and liver tissue generated functional insights in the regulation of cell and tissue homeostasis during high-fat diet feeding and medication with two antidiabetic compounds. Protein set analyses singled out pathways for functional characterization, and indicated, for example, early-on potential cardiovascular complication of the diabetes drug rosiglitazone. In vivo protein set detection can provide new avenues for monitoring complex disease processes, and for evaluating preclinical drug candidates.

Indexed as

Adipose Tissue, WhiteAnimalsDiet, High-FatHypoglycemic AgentsLiverMaleMiceMice, Inbred C57BLMyocardiumObesityPPAR gammaProtein Processing, Post-TranslationalProteomicsRosiglitazoneSalicylatesThiazolidinedionesHypoglycemic AgentsPPAR gammaRosiglitazoneSalicylatesThiazolidinediones

Identifiers

PMID23579186
PMCPMC3708179

What OpenQuestion holds

Textmetadata
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.