Evidence map›Paper›PMID 30638142›Full record

ArticleTissue engineering. Part A2019

A Method for High-Throughput Robotic Assembly of Three-Dimensional Vascular Tissue.

Christopher J Nycz, Hannah A Strobel, Kathy Suqui, Jonian Grosha, Gregory S Fischer, Marsha W Rolle

Open access · greenAbstract read
In one paragraph

Article in Tissue engineering. Part A, 2019. 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
0.7field-weighted citation impact, top 33% 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, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
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

6 authors at 1 institution in 1 country.

Christopher J NyczRobotics Engineering Program, Worcester Polytechnic Institute, Worcester, Massachusetts.
Hannah A StrobelDepartment of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, Massachusetts.
Kathy SuquiDepartment of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, Massachusetts.
Jonian GroshaDepartment of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, Massachusetts.
Gregory S FischerRobotics Engineering Program, Worcester Polytechnic Institute, Worcester, Massachusetts.
Marsha W RolleDepartment of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, Massachusetts.
Worcester Polytechnic Institute · US

Funding

Engineering a functional human intimal hyperplasia modelR15HL137197 · NHLBI · WORCESTER POLYTECHNIC INSTITUTE · PI ROLLE, MARSHA W · 2018 to 2018
$438k
NHLBI NIH HHS R15 HL137197
6 · The paper itself

Abstract

impact statementSelf-assembled tissues have potential to serve both as implantable grafts and as tools for disease modeling and drug screening. For these applications, tissue production must ultimately be scaled-up and automated. Limited technologies exist for precisely manipulating self-assembled tissues, which are fragile early in culture. Here, we presented a method for automatically stacking self-assembled smooth muscle cell rings onto mandrels, using a custom-designed well plate and robotic punch system. Rings then fuse into tissue-engineered blood vessels (TEBVs). This is a critical step toward automating TEBV production that may be applied to other tubular tissues as well.

Indexed as

AnimalsCell LineCells, CulturedElectrophoresis, Agar GelMuscle, Smooth, VascularMyocytes, Smooth MusclePolymersRatsRobotic Surgical ProceduresTissue EngineeringTissue ScaffoldspolyetherimidePolymersadditive manufacturingbiofabricationself-assemblytissue-engineered blood vesseltissue manipulation

Identifiers

PMID30638142
PMCPMC6760183
OpenAlexW2908568568

What OpenQuestion holds

Textmetadata
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.