Evidence map›Paper›PMID 24971892›Full record

ArticlePloS one2014

A computational approach to estimate interorgan metabolic transport in a mammal.

Xiao Cui, Lars Geffers, Gregor Eichele, Jun Yan

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 40% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

4 authors at 2 institutions in 1 country.

Xiao CuiFunctional Genomics Group, CAS-MPG Partner Institute for Computational Biology, Shanghai, China.
Lars GeffersDepartment of Genes and Behavior, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany.
Gregor EicheleDepartment of Genes and Behavior, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany.
Jun YanFunctional Genomics Group, CAS-MPG Partner Institute for Computational Biology, Shanghai, China.
Max Planck Institute for Biophysical Chemistry · DEMax Planck Society · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In multicellular organisms metabolism is distributed across different organs, each of which has specific requirements to perform its own specialized task. But different organs also have to support the metabolic homeostasis of the organism as a whole by interorgan metabolite transport. Recent studies have successfully reconstructed global metabolic networks in tissues and cell types and attempts have been made to connect organs with interorgan metabolite transport. Instead of these complicated approaches to reconstruct global metabolic networks, we proposed in this study a novel approach to study interorgan metabolite transport focusing on transport processes mediated by solute carrier (Slc) transporters and their couplings to cognate enzymatic reactions. We developed a computational approach to identify and score potential interorgan metabolite transports based on the integration of metabolism and transports in different organs in the adult mouse from quantitative gene expression data. This allowed us to computationally estimate the connectivity between 17 mouse organs via metabolite transport. Finally, by applying our method to circadian metabolism, we showed that our approach can shed new light on the current understanding of interorgan metabolite transport at a whole-body level in mammals.

Indexed as

Metabolic Networks and PathwaysSoftwareAnimalsBiological TransportMembrane Transport ProteinsMiceProteomeMembrane Transport ProteinsProteome

Identifiers

PMID24971892
PMCPMC4074118
OpenAlexW2061976892

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.