Evidence map›Paper›PMID 26635801›Full record

ArticleFrontiers in immunology2015

Cardiac Arrest Disrupts Caspase-1 and Patterns of Inflammatory Mediators Differently in Skin and Muscle Following Localized Tissue Injury in Rats: Insights from Data-Driven Modeling.

Ravi Starzl, Dolores Wolfram, Ruben Zamora, Bahiyyah Jefferson, Derek Barclay, Chien Ho, Vijay Gorantla, Gerald Brandacher, Stefan Schneeberger, W P Andrew Lee and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2015. 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
1.2field-weighted citation impact, top 18% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

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

12 authors at 6 institutions in 2 countries.

Ravi StarzlLanguage Technologies Institute, Carnegie Mellon University , Pittsburgh, PA , USA ; Department of Plastic and Reconstructive Surgery, University of Pittsburgh , Pittsburgh, PA , USA ; Department of Plastic and Reconstructive Surgery, Johns Hopkins Medicine , Baltimore, MD , USA.
Dolores WolframDepartment of Plastic and Reconstructive Surgery, Innsbruck Medical University , Innsbruck , Austria.
Ruben ZamoraDepartment of Surgery, University of Pittsburgh , Pittsburgh, PA , USA ; Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh , Pittsburgh, PA , USA.
Bahiyyah JeffersonDepartment of Surgery, University of Pittsburgh , Pittsburgh, PA , USA.
Derek BarclayDepartment of Surgery, University of Pittsburgh , Pittsburgh, PA , USA.
Chien HoDepartment of Biological Sciences, Carnegie Mellon University , Pittsburgh, PA , USA.
Vijay GorantlaDepartment of Plastic and Reconstructive Surgery, University of Pittsburgh , Pittsburgh, PA , USA.
Gerald BrandacherDepartment of Plastic and Reconstructive Surgery, Johns Hopkins Medicine , Baltimore, MD , USA.
Stefan SchneebergerDepartment of Plastic and Reconstructive Surgery, Johns Hopkins Medicine , Baltimore, MD , USA.
W P Andrew LeeDepartment of Plastic and Reconstructive Surgery, Johns Hopkins Medicine , Baltimore, MD , USA.
Jaime CarbonellLanguage Technologies Institute, Carnegie Mellon University , Pittsburgh, PA , USA.
Yoram VodovotzDepartment of Surgery, University of Pittsburgh , Pittsburgh, PA , USA ; Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh , Pittsburgh, PA , USA.
University of Pittsburgh · USCarnegie Mellon University · USJohns Hopkins Medicine · USJohns Hopkins University · USInnsbruck Medical University · ATMcGowan Institute for Regenerative Medicine · US

Funding

Regulation of Intestinal Mucosal Injury & Repair After Trauma/Hemorrhagic ShockP50GM053789 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BILLIAR, TIMOTHY R · 1997 to 2013
$18.0M
NIGMS NIH HHS P50 GM053789
6 · The paper itself

Abstract

backgroundTrauma often cooccurs with cardiac arrest and hemorrhagic shock. Skin and muscle injuries often lead to significant inflammation in the affected tissue. The primary mechanism by which inflammation is initiated, sustained, and terminated is cytokine-mediated immune signaling, but this signaling can be altered by cardiac arrest. The complexity and context sensitivity of immune signaling in general has stymied a clear understanding of these signaling dynamics. METHODOLOGY/PRINCIPAL

findingsWe hypothesized that advanced numerical and biological function analysis methods would help elucidate the inflammatory response to skin and muscle wounds in rats, both with and without concomitant shock. Based on the multiplexed analysis of inflammatory mediators, we discerned a differential interleukin (IL)-1α and IL-18 signature in skin vs. muscle, which was suggestive of inflammasome activation in the skin. Immunoblotting revealed caspase-1 activation in skin but not muscle. Notably, IL-1α and IL-18, along with caspase-1, were greatly elevated in the skin following cardiac arrest, consistent with differential inflammasome activation. CONCLUSION/SIGNIFICANCE: Tissue-specific activation of caspase-1 and the NLRP3 inflammasome appear to be key factors in determining the type and severity of the inflammatory response to tissue injury, especially in the presence of severe shock, as suggested via data-driven modeling.

Indexed as

cardiac arrest and traumacomputational modelingdata driven modelinghemorrhagic shockimmunoregulatoryInflammasomeinflammatory mediatorslocalized tissue injury

Identifiers

PMID26635801
PMCPMC4653302
OpenAlexW2178418063

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.