Evidence map›Paper›PMID 38082987›Full record

ArticleAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference2023

Reactive-Accelerated-Aging Testing of Thinned Tissue-Engineered Electronic Nerve Interfaces.

Ladan Jiracek-Sapieha, Kenneth Fluker, Jack Judy

Abstract read
In one paragraph

Article in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Ladan Jiracek-Sapieha
Kenneth Fluker
Jack Judy

Funding

The Tissue-Engineered Electronic Nerve Interface (TEENI)R01NS111518 · NINDS · UNIVERSITY OF FLORIDA · PI JUDY, JACK W · 2019 to 2022
$2.4M
NINDS NIH HHS R01 NS111518
6 · The paper itself

Abstract

Tissue responses can cause a significant reduction in the performance of microelectrode-based devices implanted into neural tissue. Since the reduction of the thickness of implants has been shown to reduce tissue response, in this work we report on our effects to reduce the thickness of our tissue-engineered-electronic-nerve-interface (TEENI) devices and characterize their long-term reliability in a harsh environment. We were able to reduce the thickness of the TEENI threads that are to be located in nerve tissue from ~10 μm to ~2.5 μm in total thickness. To maintain the handleability needed during the assembly of the TEENI device into the hydrogel-based scaffold, we maintained full thickness elsewhere in the TEENI device and added support rails. During longitudinal reactive-accelerated-aging (RAA) experiments performed over 6 days and at 67°C, which corresponds to ~48 days in tissue, we observed that some channels maintain a stable impedance and others do not. Although analyses performed using a scanning electron microscope could clearly reveal delamination in some channels that exhibited large changes in impedance, it did not always correlate. Some channels with significant changes in impedance did not exhibit any observable delamination. Additional work is needed to study the relationship between changes in impedance and structural changes in the device, with the goal of improving device design to achieve longer-lasting devices.

Indexed as

Nerve TissueElectrodes, ImplantedElectronicsMicroelectrodesReproducibility of Results

Identifiers

PMID38082987
PMCPMC13004534

What OpenQuestion holds

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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.