Evidence map›Paper›PMID 33943034›Full record

ArticleAdvanced healthcare materials2021

Hydrodynamic Mixing Tunes the Stiffness of Proteoglycan-Mimicking Physical Hydrogels.

James P Warren, Danielle E Miles, Nikil Kapur, Ruth K Wilcox, Paul A Beales

Abstract read
In one paragraph

Article in Advanced healthcare materials, 2021. 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
  2. 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

5 authors.

James P WarrenSchool of Chemistry, University of Leeds, Leeds, LS2 9JT, UK.
Danielle E MilesSchool of Chemistry, University of Leeds, Leeds, LS2 9JT, UK.
Nikil KapurSchool of Mechanical Engineering, University of Leeds, Leeds, LS2 9JT, UK.
Ruth K WilcoxSchool of Mechanical Engineering, University of Leeds, Leeds, LS2 9JT, UK.
Paul A BealesSchool of Chemistry, University of Leeds, Leeds, LS2 9JT, UK.ORCID 0000-0001-9076-9793

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Self-assembling hydrogels are promising materials for regenerative medicine and tissue engineering. However, designing hydrogels that replicate the 3-4 order of magnitude variation in soft tissue mechanics remains a major challenge. Here hybrid hydrogels are investigated formed from short self-assembling β-fibril peptides, and the glycosaminoglycan chondroitin sulfate (CS), chosen to replicate physical aspects of proteoglycans, specifically natural aggrecan, which provides structural mechanics to soft tissues. Varying the peptide:CS compositional ratio (1:2, 1:10, or 1:20) can tune the mechanics of the gel by one to two orders of magnitude. In addition, it is demonstrated that at any fixed composition, the gel shear modulus can be tuned over approximately two orders of magnitude through varying the initial vortex mixing time. This tuneability arises due to changes in the mesoscale structure of the gel network (fibril width, length, and connectivity), giving rise to both shear-thickening and shear-thinning behavior. The resulting hydrogels range in shear elastic moduli from 0.14 to 220 kPa, mimicking the mechanical variability in a range of soft tissues. The high degree of discrete tuneability of composition and mechanics in these hydrogels makes them particularly promising for matching the chemical and mechanical requirements of different applications in tissue engineering and regenerative medicine.

Indexed as

HydrogelsProteoglycansHydrodynamicsPeptidesTissue EngineeringHydrogelsPeptidesProteoglycansbiomimetic materialsbiopolymer networksgel mechanicsnetwork connectivityself-assembling peptidesshear rheology

Identifiers

PMID33943034
PMCPMC11468938

What OpenQuestion holds

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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.