Evidence map›Paper›PMID 39458681›Full record

ReviewPolymers2024

Advances in Electrospun Poly(ε-caprolactone)-Based Nanofibrous Scaffolds for Tissue Engineering.

Karla N Robles, Fatima Tuz Zahra, Richard Mu, Todd Giorgio

Abstract readReview
In one paragraph

Review in Polymers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Review
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  9. Review
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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.

Karla N RoblesTIGER Institute, Tennessee State University, Nashville, TN 37209, USA.
Fatima Tuz ZahraTIGER Institute, Tennessee State University, Nashville, TN 37209, USA.ORCID 0000-0003-4134-3002
Richard MuTIGER Institute, Tennessee State University, Nashville, TN 37209, USA.
Todd GiorgioTIGER Institute, Tennessee State University, Nashville, TN 37209, USA.ORCID 0000-0002-9557-1425

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tissue engineering has great potential for the restoration of damaged tissue due to injury or disease. During tissue development, scaffolds provide structural support for cell growth. To grow healthy tissue, the principal components of such scaffolds must be biocompatible and nontoxic. Poly(ε-caprolactone) (PCL) is a biopolymer that has been used as a key component of composite scaffolds for tissue engineering applications due to its mechanical strength and biodegradability. However, PCL alone can have low cell adherence and wettability. Blends of biomaterials can be incorporated to achieve synergistic scaffold properties for tissue engineering. Electrospun PCL-based scaffolds consist of single or blended-composition nanofibers and nanofibers with multi-layered internal architectures (i.e., core-shell nanofibers or multi-layered nanofibers). Nanofiber diameter, composition, and mechanical properties, biocompatibility, and drug-loading capacity are among the tunable properties of electrospun PCL-based scaffolds. Scaffold properties including wettability, mechanical strength, and biocompatibility have been further enhanced with scaffold layering, surface modification, and coating techniques. In this article, we review nanofibrous electrospun PCL-based scaffold fabrication and the applications of PCL-based scaffolds in tissue engineering as reported in the recent literature.

Indexed as

biocompatibilitybiomaterialscomposite scaffoldselectrospinningnanofiberspoly(ε-caprolactone) (PCL)scaffold fabricationscaffold wettabilitytissue engineering

Identifiers

PMID39458681
PMCPMC11511575

What Socratic 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 Socratic graph.