Evidence map›Paper›PMID 38136583›Full record

ArticleBiomolecules2023

Improved Physiochemical Properties of Chitosan@PCL Nerve Conduits by Natural Molecule Crosslinking.

Marta Bianchini, Ciro Zinno, Silvestro Micera, Eugenio Redolfi Riva

Abstract read
In one paragraph

Article in Biomolecules, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
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  5. 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.

Marta BianchiniThe BioRobotics Institute, Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy.
Ciro ZinnoThe BioRobotics Institute, Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy.ORCID 0000-0001-8873-8875
Silvestro MiceraThe BioRobotics Institute, Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy.
Eugenio Redolfi RivaThe BioRobotics Institute, Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy.ORCID 0000-0001-8342-7058

Funding

National Recovery and Resilience Plan (NRRP) MNESYS (PE0000006)National Recovery and Resilience Plan (NRRP) THE (IECS00000017)
6 · The paper itself

Abstract

Nerve conduits may represent a valuable alternative to autograft for the regeneration of long-gap damages. However, no NCs have currently reached market approval for the regeneration of limiting gap lesions, which still represents the very bottleneck of this technology. In recent years, a strong effort has been made to envision an engineered graft to tackle this issue. In our recent work, we presented a novel design of porous/3D-printed chitosan/poly-ε-caprolactone conduits, coupling freeze drying and additive manufacturing technologies to yield conduits with good structural properties. In this work, we studied genipin crosslinking as strategy to improve the physiochemical properties of our conduit. Genipin is a natural molecule with very low toxicity that has been used to crosslink chitosan porous matrix by binding the primary amino group of chitosan chains. Our characterization evidenced a stabilizing effect of genipin crosslinking towards the chitosan matrix, with reported modified porosity and ameliorated mechanical properties. Given the reported results, this method has the potential to improve the performance of our conduits for the regeneration of long-gap nerve injuries.

Indexed as

ChitosanIridoidsNerve RegenerationTissue ScaffoldsChitosangenipinIridoidschitosangenipinnerve conduitnerve regenerationtissue engineering

Identifiers

PMID38136583
PMCPMC10741752

What OpenQuestion holds

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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.