Evidence map›Paper›PMID 39543160›Full record

ArticleScientific reports2024

Characterization of Schiff base self-healing hydrogels by dynamic speckle pattern analysis.

Madeh Sajjadi, Ramin Jamali, Tahereh Kiyani, Zahra Mohamadnia, Ali-Reza Moradi

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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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

5 authors.

Madeh Sajjadi *Department of Physics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, 45137-66731, Iran.
Ramin Jamali *Department of Physics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, 45137-66731, Iran.
Tahereh Kiyani *Department of Chemistry, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, 45137-66731, Iran.
Zahra MohamadniaDepartment of Chemistry, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, 45137-66731, Iran.
Ali-Reza MoradiDepartment of Physics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, 45137-66731, Iran. moradika@iasbs.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Self-healing hydrogels are emerging materials capable of restoring functionality after damage, making them highly suitable for biomedical applications, such as tissue engineering, wound healing, and drug delivery. In this study, we synthesize and characterize a novel biodegradable, conductive, and self-healing hydrogel. The synthesis is based on a Schiff base formed between gelatin and hyaluronic acid, and the dynamic reversible Schiff base bond provides the self-healing property. To characterize and assess the self-healing behavior of the hydrogel, dynamic speckle pattern (DSP) analysis is introduced as a non-destructive, non-contact, and easy-to-implement method. Speckle patterns are formed upon scattering of laser light from a diffusive matter and includes a huge overall information about the sample, to be extracted by statistical processing. DSP analysis is employed to monitor the self-healing process of the hydrogel at both macroscopic and microscopic scales. Experimental procedure involve in situ acquisition of speckle patterns over time under controlled environmental conditions, followed by statistical analysis to evaluate the internal dynamics of the healing process. Several statistical parameters are computed for real-time monitoring of the self-healing property of the hydrogel. The findings, on the one hand, underscore the potential of Schiff base hydrogels in advanced biomedical applications where self-healing properties are critical for sustained performance and longevity. On the other hand, the introduced analysis method shows its potential to serve as an effective approach for biomaterial characterization.

Identifiers

PMID39543160
PMCPMC11564514

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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.