Evidence map›Paper›PMID 27480807›Full record

ArticleScientific reports2016

Strain and rate-dependent neuronal injury in a 3D in vitro compression model of traumatic brain injury.

Eyal Bar-Kochba, Mark T Scimone, Jonathan B Estrada, Christian Franck

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed
11.4field-weighted citation impact, top 1% 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

82 citing papers in PubMed, 174 citations in OpenAlex.

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  16. Cellular mechanisms of traumatic brain injury.npj biological physics and mechanics · 2025
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22 more citing papers are in PubMed but not listed here.

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 at 1 institution in 1 country.

Eyal Bar-KochbaBrown University, School of Engineering, Providence, RI, United States of America.
Mark T ScimoneBrown University, School of Engineering, Providence, RI, United States of America.
Jonathan B EstradaBrown University, School of Engineering, Providence, RI, United States of America.
Christian FranckBrown University, School of Engineering, Providence, RI, United States of America.
Brown University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the United States over 1.7 million cases of traumatic brain injury are reported yearly, but predictive correlation of cellular injury to impact tissue strain is still lacking, particularly for neuronal injury resulting from compression. Given the prevalence of compressive deformations in most blunt head trauma, this information is critically important for the development of future mitigation and diagnosis strategies. Using a 3D in vitro neuronal compression model, we investigated the role of impact strain and strain rate on neuronal lifetime, viability, and pathomorphology. We find that strain magnitude and rate have profound, yet distinctively different effects on the injury pathology. While strain magnitude affects the time of neuronal death, strain rate influences the pathomorphology and extent of population injury. Cellular injury is not initiated through localized deformation of the cytoskeleton but rather driven by excess strain on the entire cell. Furthermore we find that, mechanoporation, one of the key pathological trigger mechanisms in stretch and shear neuronal injuries, was not observed under compression.

Indexed as

AnimalsBrain Injuries, TraumaticCell Culture TechniquesCell SurvivalIn Vitro TechniquesModels, BiologicalNeuronsRatsShear StrengthStress, Mechanical

Identifiers

PMID27480807
PMCPMC4969749
OpenAlexW2486492325

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.