Evidence map›Paper›PMID 27239287›Full record

ReviewF1000Research2016

Network science for the identification of novel therapeutic targets in epilepsy.

Rod C Scott

Abstract readReview
In one paragraph

Review in F1000Research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. 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

1 author.

Rod C ScottDepartment of Neurological Sciences, University of Vermont, Burlington, VT, USA; Neurosciences Unit, UCL Institute of Child Health, London, UK.

Funding

Mechanisms of cognitive deficits after seizures in rats with brain malformationsR01NS075249 · NINDS · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI SCOTT, RODNEY CRAIG · 2011 to 2015
$1.7M
NINDS NIH HHS R01 NS075249
6 · The paper itself

Abstract

The quality of life of children with epilepsy is a function of seizures and associated cognitive and behavioral comorbidities. Current treatments are not successful at stopping seizures in approximately 30% of patients despite the introduction of multiple new antiepileptic drugs over the last decade. In addition, modification of seizures has only a modest impact on the comorbidities. Therefore, novel approaches to identify therapeutic targets that improve seizures and comorbidities are urgently required. The potential of network science as applied to genetic, local neural network, and global brain data is reviewed. Several examples of possible new therapeutic approaches defined using novel network tools are highlighted. Further study to translate the findings into clinical practice is now required.

Indexed as

epilepsynetwork sciencetherapeutic targets

Identifiers

PMID27239287
PMCPMC4870991

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.