Evidence map›Paper›PMID 27928514›Full record

ArticleMicromachines2016

A Microchip for High-throughput Axon Growth Drug Screening.

Hyun Soo Kim, Sehoon Jeong, Chiwan Koo, Arum Han, Jaewon Park

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Micromachines, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

3 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

5 authors at 3 institutions in 3 countries.

Hyun Soo KimDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.
Sehoon JeongDepartment of Biomedical Engineering, Texas A&M University, College Station, TX, USA.
Chiwan KooDepartment of Electronics and Control Engineering, Hanbat National University, Daejeon, Korea.
Arum HanDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA; Department of Biomedical Engineering, Texas A&M University, College Station, TX, USA.
Jaewon ParkDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA; Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China; Neural and Cognitive Sciences Research Center, Southern University of Science and Technology, Shenzhen, China.
Texas A&M University · USHanbat National University · KRSouthern University of Science and Technology · CN

Funding

A High-Throughput Microfluidic in vitro CNS Myelination Model towards Drug ScreeningR21EB021005 · NIBIB · TEXAS ENGINEERING EXPERIMENT STATION · PI HAN, ARUM · 2015 to 2016
$396k
CNS Myelination Co-Culture Microsystem for Axon-Gila SignalingR21MH085267 · NIMH · TEXAS ENGINEERING EXPERIMENT STATION · PI HAN, ARUM · 2009 to 2010
$387k
NIMH NIH HHS R21 MH085267
6 · The paper itself

Abstract

It has been recently known that not only the presence of inhibitory molecules associated with myelin but also the reduced growth capability of the axons limit mature central nervous system (CNS) axonal regeneration after injury. Conventional axon growth studies are typically conducted using multi-well cell culture plates that are very challenging to investigate localized effects of drugs and limited to low throughput. Unfortunately, there is currently no other

Indexed as

compartmentalized culturehigh-throughput screeninglocalized biomolecular treatmentMicrofluidic neuron culture platform

Identifiers

PMID27928514
PMCPMC5137948
OpenAlexW2469095026

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.