Evidence map›Paper›PMID 23236254›Full record

ArticleBioinformatics and biology insights2012

Analyzing Thiol-Dependent Redox Networks in the Presence of Methylene Blue and Other Antimalarial Agents with RT-PCR-Supported in silico Modeling.

J Zirkel, A Cecil, F Schäfer, S Rahlfs, A Ouedraogo, K Xiao, S Sawadogo, B Coulibaly, K Becker, T Dandekar

Open access · goldAbstract read
In one paragraph

Article in Bioinformatics and biology insights, 2012. 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
0.6field-weighted citation impact, top 24% 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, 5 citations in OpenAlex.

  1. Frontiers in cellular and infection microbiology · 2019
    Article
  2. Identification of Antifungal Targets Based on Computer Modeling.Journal of fungi (Basel, Switzerland) · 2018
    Review
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

10 authors at 3 institutions in 2 countries.

J ZirkelDepartment of Bioinformatics, Biocenter, University of Würzburg, Germany. ; Centre de Recherche en Santé de Nouna, Nouna, Burkina Faso.
A Cecil
F Schäfer
S Rahlfs
A Ouedraogo
K Xiao
S Sawadogo
B Coulibaly
K Becker
T Dandekar
Centre de Recherche en Santé de Nouna · BFUniversity of Würzburg · DEUniversity of Giessen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the face of growing resistance in malaria parasites to drugs, pharmacological combination therapies are important. There is accumulating evidence that methylene blue (MB) is an effective drug against malaria. Here we explore the biological effects of both MB alone and in combination therapy using modeling and experimental data.

resultsWe built a model of the central metabolic pathways in P. falciparum. Metabolic flux modes and their changes under MB were calculated by integrating experimental data (RT-PCR data on mRNAs for redox enzymes) as constraints and results from the YANA software package for metabolic pathway calculations. Several different lines of MB attack on Plasmodium redox defense were identified by analysis of the network effects. Next, chloroquine resistance based on pfmdr/and pfcrt transporters, as well as pyrimethamine/sulfadoxine resistance (by mutations in DHF/DHPS), were modeled in silico. Further modeling shows that MB has a favorable synergism on antimalarial network effects with these commonly used antimalarial drugs.

conclusionsTheoretical and experimental results support that methylene blue should, because of its resistance-breaking potential, be further tested as a key component in drug combination therapy efforts in holoendemic areas.

Indexed as

combination therapydrugelementary mode analysismalariametabolic fluxmethylene bluepathwayresistance

Identifiers

PMID23236254
PMCPMC3516044
OpenAlexW2064827069

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.