Evidence map›Paper›PMID 24473230›Full record

ArticleScientific reports2014

Network reconstruction of platelet metabolism identifies metabolic signature for aspirin resistance.

Alex Thomas, Sorena Rahmanian, Aarash Bordbar, Bernhard Ø Palsson, Neema Jamshidi

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
6.5field-weighted citation impact, top 4% 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

23 citing papers in PubMed, 45 citations in OpenAlex.

  1. Genome-scale models in human metabologenomics.Nature reviews. Genetics · 2025
    Review
  2. Review
  3. NAR genomics and bioinformatics · 2024
    Article
  4. Article
  5. Machine Learning and Hybrid Methods for Metabolic Pathway Modeling.Methods in molecular biology (Clifton, N.J.) · 2023
    Review
  6. Review
  7. Article
  8. Isotopically nonstationaryMetabolic engineering · 2022
    Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. IDENTIFYING CANCER SPECIFIC METABOLIC SIGNATURES USING CONSTRAINT-BASED MODELS.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2017
    Article
  20. 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.

Alex Thomas1] Department of Bioinformatics and Systems Biology, 9500 Gilman Drive, Mail Code 0412, La Jolla, CA 92093-0412 [2] University of California, San Diego, 9500 Gilman Drive, Mail Code 0412, La Jolla, CA 92093-0412.
Sorena Rahmanian1] Department of Bioengineering, 9500 Gilman Drive, Mail Code 0412, La Jolla, CA 92093-0412 [2] University of California, San Diego, 9500 Gilman Drive, Mail Code 0412, La Jolla, CA 92093-0412.
Aarash Bordbar1] Department of Bioengineering, 9500 Gilman Drive, Mail Code 0412, La Jolla, CA 92093-0412 [2] University of California, San Diego, 9500 Gilman Drive, Mail Code 0412, La Jolla, CA 92093-0412.
Bernhard Ø Palsson1] Department of Bioengineering, 9500 Gilman Drive, Mail Code 0412, La Jolla, CA 92093-0412 [2] Institute of Engineering and Medicine, 9500 Gilman Drive, Mail Code 0412, La Jolla, CA 92093-0412 [3] University of California, San Diego, 9500 Gilman Drive, Mail Code 0412, La Jolla, CA 92093-0412.
Neema Jamshidi1] Institute of Engineering and Medicine, 9500 Gilman Drive, Mail Code 0412, La Jolla, CA 92093-0412 [2] University of California, San Diego, 9500 Gilman Drive, Mail Code 0412, La Jolla, CA 92093-0412 [3] Department of Radiological Sciences, University of California, Los Angeles, BOX 951721, Los Angeles, CA 90095-1721.
La Jolla Bioengineering Institute · US

Funding

Network-based Analysis of Kinetics and RegulationR01GM068837 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PALSSON, BERNHARD O · 2003 to 2012
$2.4M
NIGMS NIH HHS GM068837NIGMS NIH HHS R01 GM068837
6 · The paper itself

Abstract

Recently there has not been a systematic, objective assessment of the metabolic capabilities of the human platelet. A manually curated, functionally tested, and validated biochemical reaction network of platelet metabolism, iAT-PLT-636, was reconstructed using 33 proteomic datasets and 354 literature references. The network contains enzymes mapping to 403 diseases and 231 FDA approved drugs, alluding to an expansive scope of biochemical transformations that may affect or be affected by disease processes in multiple organ systems. The effect of aspirin (ASA) resistance on platelet metabolism was evaluated using constraint-based modeling, which revealed a redirection of glycolytic, fatty acid, and nucleotide metabolism reaction fluxes in order to accommodate eicosanoid synthesis and reactive oxygen species stress. These results were confirmed with independent proteomic data. The construction and availability of iAT-PLT-636 should stimulate further data-driven, systems analysis of platelet metabolism towards the understanding of pathophysiological conditions including, but not strictly limited to, coagulopathies.

Indexed as

AspirinBiochemical PhenomenaBlood PlateletsEicosanoidsFatty AcidsGlycolysisHumansNucleotidesProteomeProteomicsReactive Oxygen SpeciesAspirinEicosanoidsFatty AcidsNucleotidesProteomeReactive Oxygen Species

Identifiers

PMID24473230
PMCPMC3905279
OpenAlexW2058279507

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.