Evidence map›Paper›PMID 24505402›Full record

ArticlePloS one2014

Visualization of network target crosstalk optimizes drug synergism in myocardial ischemia.

Xiaojing Wan, Jia Meng, Yingnan Dai, Yina Zhang, Shuang 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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 22% 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

3 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Liposomal Curcumin Enhances the Effect of Naproxen in a Rat Model of Migraine.Medical science monitor : international medical journal of experimental and clinical research · 2019
    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 3 institutions in 1 country.

Xiaojing WanDepartment of Geriatrics, the Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
Jia MengDepartment of Geriatrics, the Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Yingnan DaiDepartment of Cardiology, the Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
Yina ZhangDepartment of Geriatrics, the Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Shuang YanDepartment of Endocrinology, the Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
Fourth Affiliated Hospital of Harbin Medical University · CNSecond Affiliated Hospital of Harbin Medical University · CNHarbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Numerous drugs and compounds have been validated as protecting against myocardial ischemia (MI), a leading cause of heart failure; however, synergistic possibilities among them have not been systematically explored. Thus, there appears to be significant room for optimization in the field of drug combination therapy for MI. Here, we propose an easy approach for the identification and optimization of MI-related synergistic drug combinations via visualization of the crosstalk between networks of drug targets corresponding to different drugs (each drug has a unique network of targets). As an example, in the present study, 28 target crosstalk networks (TCNs) of random pairwise combinations of 8 MI-related drugs (curcumin, capsaicin, celecoxib, raloxifene, silibinin, sulforaphane, tacrolimus, and tamoxifen) were established to illustrate the proposed method. The TCNs revealed a high likelihood of synergy between curcumin and the other drugs, which was confirmed by in vitro experiments. Further drug combination optimization showed a synergistic protective effect of curcumin, celecoxib, and sililinin in combination against H₂O₂-induced ischemic injury of cardiomyocytes at a relatively low concentration of 500 nM. This result is in agreement with the earlier finding of a denser and modular functional crosstalk between their networks of targets in the regulation of cell apoptosis. Our study offers a simple approach to rapidly search for and optimize potent synergistic drug combinations, which can be used for identifying better MI therapeutic strategies. Some new light was also shed on the characteristic features of drug synergy, suggesting that it is possible to apply this method to other complex human diseases.

Indexed as

Drug SynergismAnimalsAnti-Inflammatory Agents, Non-SteroidalAntioxidantsCelecoxibCells, CulturedCurcuminCyclooxygenase 2 InhibitorsDrug Therapy, CombinationHumansMolecular Targeted TherapyMyocardial IschemiaMyocytes, CardiacPyrazolesRatsRats, Sprague-DawleyAnti-Inflammatory Agents, Non-SteroidalAntioxidantsCelecoxibCurcuminCyclooxygenase 2 InhibitorsPyrazolesSilybinSilymarinSulfonamides

Identifiers

PMID24505402
PMCPMC3914923
OpenAlexW2047400822

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.