Evidence map›Paper›PMID 30664915›Full record

ArticleJournal of neuroscience methods2019

A graphical user interface to assess the neuroinflammatory response to intracortical microelectrodes.

Sydney C Lindner, Marina Yu, Jeffrey R Capadona, Andrew J Shoffstall

Abstract read
In one paragraph

Article in Journal of neuroscience methods, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.2field-weighted citation impact, top 53% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

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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 2 institutions in 1 country.

Sydney C LindnerDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States.
Marina YuDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States; Advanced Platform Technology Center, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, United States.
Jeffrey R CapadonaDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States; Advanced Platform Technology Center, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, United States.
Andrew J ShoffstallDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States; Advanced Platform Technology Center, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, United States. Electronic address: Ajs215@case.edu.
Louis Stokes Cleveland VA Medical Center · USCase Western Reserve University · US

Funding

CD14 facilitates neural device integration and performanceR01NS082404 · NINDS · CASE WESTERN RESERVE UNIVERSITY · PI CAPADONA, JEFFREY R · 2013 to 2016
$1.8M
Resveratrol Prevents Microelectrode Mediated NeurodegenerationI01RX001495 · VA · LOUIS STOKES CLEVELAND VA MEDICAL CENTER · PI CAPADONA, JEFFREY R · 2015 to 2017
–
Antioxidative Microelectrodes to Improve Neural Recording PerformanceI01RX002611 · VA · LOUIS STOKES CLEVELAND VA MEDICAL CENTER · PI CAPADONA, JEFFREY R · 2018 to 2022
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Dynamically Softening Microelectrodes to Improve Neural Recording PerformanceIK1RX002492 · VA · LOUIS STOKES CLEVELAND VA MEDICAL CENTER · PI SHOFFSTALL, ANDREW · 2018 to 2019
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Senior Research Career ScientistIK6RX003077 · VA · LOUIS STOKES CLEVELAND VA MEDICAL CENTER · PI Jeffrey R Capadona · 2019 to 2026
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NINDS NIH HHS R01 NS082404RRD VA I01 RX001495RRD VA I01 RX002611RRD VA IK1 RX002492RRD VA IK6 RX003077
6 · The paper itself

Abstract

backgroundBrain-implanted devices, including intracortical microelectrodes, are used in neuroscience applications ranging from research to rehabilitation and beyond. Significant efforts are focused on developing new device designs and insertion strategies that mitigate initial trauma and subsequent neuroinflammation that occurs as a result of implantation. A frequently published metric is the neuroinflammatory response quantified as a function of distance from the interface edge, using fluorescent immunohistochemical markers. NEW

methodHere, we sought to develop a graphical user interface software in Matlab to provide an objective, repeatable, and easy-to-use method for analyzing fluorescence immunohistochemistry images of neuroinflammation. The user interface allows for efficient batch-processing and review of images, and incorporates zoom and contrast features to improve the accuracy of identifying the 'region of interest' (ROI).

resultsThe software was validated against previously published results and demonstrated equivalent scientific conclusions. Furthermore, a comparison between novice and expert users demonstrated consistency across levels of training and a rapid learning-curve. COMPARISON WITH EXISTING METHOD(S): Existing methods published in the intracortical microelectrode literature include a wide variety of procedures within ImageJ and Matlab. However, specific procedural details are often lacking.

conclusionsThe distribution of the methodology may promote efficiency and reproducibility across the field seeking to characterize the tissue response to implanted neural interfaces. It may also serve as a template for researchers seeking to perform other types of histological quantification as a function of distance from an ROI.

Indexed as

AnimalsCerebral CortexElectrodes, ImplantedEncephalitisFluorescent Antibody TechniqueImage Interpretation, Computer-AssistedRatsSoftwareUser-Computer InterfaceBrain implantCraniotomyIntracortical microelectrodeMatlabNeurodegenerationNeuroinflammation

Identifiers

PMID30664915
PMCPMC6914213
OpenAlexW2910537898

What OpenQuestion holds

Textmetadata
LicenceTDM
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.