Evidence map›Paper›PMID 30577783›Full record

ArticleBMC systems biology2018

Classifying mild traumatic brain injuries with functional network analysis.

F Anthony San Lucas, John Redell, Dash Pramod, Yin Liu

Abstract read
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In one paragraph

Article in BMC systems biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

F Anthony San LucasDepartment of Epidemiology, University of Texas M.D. Anderson Cancer Center, 1155 Pressler Street, Houston, TX, USA.
John RedellDepartment of Neurobiology and Anatomy, University of Texas Health Science Center at Houston, 6431 Fannin Street, Houston, TX, USA.
Dash PramodDepartment of Neurobiology and Anatomy, University of Texas Health Science Center at Houston, 6431 Fannin Street, Houston, TX, USA.
Yin LiuDepartment of Neurobiology and Anatomy, University of Texas Health Science Center at Houston, 6431 Fannin Street, Houston, TX, USA. Yin.Liu@uth.tmc.edu.

Funding

Identifying the cellular hierarchy and drug response of AML using cytometric dataR01CA163481 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI QIU, PENG · 2012 to 2015
$1.1M
Bayesian Methods in Signal Transduction Network AnalysisR01LM010022 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI LIU, YIN · 2011 to 2014
$901k
NCI NIH HHS R01 CA163481NLM NIH HHS R01 LM010022
6 · The paper itself

Abstract

backgroundTraumatic brain injury (TBI) represents a critical health problem of which timely diagnosis and treatment remain challenging. TBI is a result of an external force damaging brain tissue, accompanied by delayed pathogenic events which aggravate the injury. Molecular responses to different mild TBI subtypes have not been well characterized. TBI subtype classification is an important step towards the development and application of novel treatments. The computational systems biology approach is proved to be a promising tool in biomarker discovery for central nervous system injury.

resultsIn this study, we have performed a network-based analysis on gene expression profiles to identify functional gene subnetworks. The gene expression profiles were obtained from two experimental models of injury in rats: the controlled cortical impact and the fluid percussion injury. Our method integrates protein interaction information with gene expression profiles to identify subnetworks of genes as biomarkers. We have demonstrated that the selected gene subnetworks are more accurate to classify the heterogeneous responses to different injury models, compared to conventional analysis using individual marker genes selected without network information.

conclusionsThe systems approach can lead to a better understanding of the underlying complexities of the molecular responses after TBI and the identified subnetworks will have important prognostic functions for patients who sustain mild TBIs.

Indexed as

AnimalsBiomarkersBrain Injuries, TraumaticMaleRatsRats, Sprague-DawleySystems BiologyTranscriptomeBiomarkersBiomarkersGene ontology annotationmTBI subtype classificationSubnetwork modularityWeighted protein interaction network

Identifiers

PMID30577783
PMCPMC6302365

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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.