Evidence map›Paper›PMID 34075571›Full record

ReviewProgress in biomaterials2021

Poly (ε-caprolactone)-based electrospun nano-featured substrate for tissue engineering applications: a review.

B Sowmya, A B Hemavathi, P K Panda

Abstract readReview
In one paragraph

Review in Progress in biomaterials, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed.

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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

3 authors.

B SowmyaMaterials Science Division, CSIR - National Aerospace Laboratories, Bangalore, 560017, India.
A B HemavathiDepartment of Polymer Science and Technology, Sri Jayachamarajendra College of Engineering, JSS Science and Technology University, Mysuru, 570 006, India.
P K PandaMaterials Science Division, CSIR - National Aerospace Laboratories, Bangalore, 560017, India. pkpanda@nal.res.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The restoration of normal functioning of damaged body tissues is one of the major objectives of tissue engineering. Scaffolds are generally used as artificial supports and as substrates for regenerating new tissues and should closely mimic natural extracellular matrix (ECM). The materials used for fabricating scaffolds must be biocompatible, non-cytotoxic and bioabsorbable/biodegradable. For this application, specifically biopolymers such as PLA, PGA, PTMC, PCL etc. satisfying the above criteria are promising materials. Poly(ε-caprolactone) (PCL) is one such potential candidate which can be blended with other materials forming blends, copolymers and composites with the essential physiochemical and mechanical properties as per the requirement. Nanofibrous scaffolds are fabricated by various techniques such as template synthesis, fiber drawing, phase separation, self-assembly, electrospinning etc. Among which electrospinning is the most popular and versatile technique. It is a clean, simple, tunable and viable technique for fabrication of polymer-based nanofibrous scaffolds. The design and fabrication of electrospun nanofibrous scaffolds are of intense research interest over the recent years. These scaffolds offer a unique architecture at nano-scale with desired porosity for selective movement of small molecules and form a suitable three-dimensional matrix similar to ECM. This review focuses on PCL synthesis, modifications, properties and scaffold fabrication techniques aiming at the targeted tissue engineering applications.

Indexed as

BiocompatibleElectrospinningNanofibrous substratePoly(ε-caprolactone)ScaffoldsTissue engineering

Identifiers

PMID34075571
PMCPMC8271057

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Registered trials

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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.