Evidence map›Paper›PMID 33102921›Full record

ArticleInternational journal of bioprinting2018

Uncovering 3D bioprinting research trends: A keyword network mapping analysis.

Leonardo Azael Garcia-Garcia, Marisela Rodriguez-Salvador

Open access · diamondAbstract read
In one paragraph

Article in International journal of bioprinting, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

6 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
  2. Materials today. Bio · 2024
    Review
  3. Article
  4. Article
  5. Bioprinting science.International journal of bioprinting · 2018
    Article
  6. 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

2 authors at 1 institution in 1 country.

Leonardo Azael Garcia-GarciaTecnologico de Monterrey, Escuela de Ingenieria y Ciencias, Laboratorio Nacional de Manufactura Aditiva y Digital (MADiT), Monterrey, N.L., Mexico.
Marisela Rodriguez-SalvadorTecnologico de Monterrey, Escuela de Ingenieria y Ciencias, Laboratorio Nacional de Manufactura Aditiva y Digital (MADiT), Monterrey, N.L., Mexico.
Tecnológico de Monterrey · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A scientometric analysis as part of a Competitive Technology Intelligence methodology was used to determine the main research efforts in 3D bioprinting. Papers from Scopus and Web of Science (WoS) published between 2000 and 2017 were analysed. A network map of the most frequently occurring keywords in these articles was created, and their average publication year (APY) was determined. The analysis focused on the most relevant keywords that occurred at least five times. A total of 1,759 keywords were obtained, and a co-occurrence analysis was developed for APYs with more keywords: 2011-2016. The results indicated that Polylactic Acid (PLA) is the material used most often. Applications mainly focused on bone tissue engineering and regeneration. The most frequently used technique was inkjet printing, and the main cell sources were Mesenchymal Stem Cells (MSC). From a general perspective, 'Treatment' and 'Bioink' were the most frequent keywords. The former was mainly related to cancer, regenerative medicine, and MSC and the latter, to multicellular spheroid deposition and the use of hydrogels like GelMA (gelatin methacryloyl). This analysis provides insights to stakeholders involved in 3D bioprinting research and development who need to keep abreast of scientific progress in the field.

Indexed as

3D bioprintingcompetitive technology intelligencedata miningscientometric analysis

Identifiers

PMID33102921
PMCPMC7582012
OpenAlexW2837245615

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.