Evidence map›Paper›PMID 24699232›Full record

ArticlePloS one2014

RETRACTED: Comprehensive logic based analyses of Toll-like receptor 4 signal transduction pathway.

Mahesh Kumar Padwal, Uddipan Sarma, Bhaskar Saha

RetractedOpen access · goldAbstract readRetracted Publication
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. It has been retracted, and should not be counted. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

9 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
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  3. Antigout effects and mechanisms of total flavonoids from prunus tomentosa.Technology and health care : official journal of the European Society for Engineering and Medicine · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Mahesh Kumar PadwalLab-5, National Center for Cell Science, Pune, Maharashtra, India.
Uddipan SarmaLab-5, National Center for Cell Science, Pune, Maharashtra, India.
Bhaskar SahaLab-5, National Center for Cell Science, Pune, Maharashtra, India.
National Centre for Cell Science · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Among the 13 TLRs in the vertebrate systems, only TLR4 utilizes both Myeloid differentiation factor 88 (MyD88) and Toll/Interleukin-1 receptor (TIR)-domain-containing adapter interferon-β-inducing Factor (TRIF) adaptors to transduce signals triggering host-protective immune responses. Earlier studies on the pathway combined various experimental data in the form of one comprehensive map of TLR signaling. But in the absence of adequate kinetic parameters quantitative mathematical models that reveal emerging systems level properties and dynamic inter-regulation among the kinases/phosphatases of the TLR4 network are not yet available. So, here we used reaction stoichiometry-based and parameter independent logical modeling formalism to build the TLR4 signaling network model that captured the feedback regulations, interdependencies between signaling kinases and phosphatases and the outcome of simulated infections. The analyses of the TLR4 signaling network revealed 360 feedback loops, 157 negative and 203 positive; of which, 334 loops had the phosphatase PP1 as an essential component. The network elements' interdependency (positive or negative dependencies) in perturbation conditions such as the phosphatase knockout conditions revealed interdependencies between the dual-specific phosphatases MKP-1 and MKP-3 and the kinases in MAPK modules and the role of PP2A in the auto-regulation of Calmodulin kinase-II. Our simulations under the specific kinase or phosphatase gene-deficiency or inhibition conditions corroborated with several previously reported experimental data. The simulations to mimic Yersinia pestis and E. coli infections identified the key perturbation in the network and potential drug targets. Thus, our analyses of TLR4 signaling highlights the role of phosphatases as key regulatory factors in determining the global interdependencies among the network elements; uncovers novel signaling connections; identifies potential drug targets for infections.

Indexed as

Gene Regulatory NetworksModels, TheoreticalSignal TransductionAnimalsComputer SimulationEscherichia coliEscherichia coli InfectionsFeedback, PhysiologicalMiceMice, KnockoutPhosphoric Monoester HydrolasesPlagueToll-Like Receptor 4Yersinia pestisPhosphoric Monoester HydrolasesToll-Like Receptor 4

Identifiers

PMID24699232
PMCPMC3974726
OpenAlexW2051029372

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.