Evidence map›Paper›PMID 39057298›Full record

ArticleJournal of functional biomaterials2024

Formulation Effects on the Mechano-Physical Properties of In Situ-Forming Resilient Hydrogels for Breast Tissue Regeneration.

Daniella Goder Orbach, Meital Zilberman

Abstract read
In one paragraph

Article in Journal of functional biomaterials, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Applications of Hydrogels in Emergency Therapy.Gels (Basel, Switzerland) · 2025
    Review
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

2 authors.

Daniella Goder OrbachDepartment of Biomedical Engineering, Faculty of Engineering, Tel-Aviv University, Tel-Aviv 69978, Israel.ORCID 0000-0003-1935-7790
Meital ZilbermanDepartment of Biomedical Engineering, Faculty of Engineering, Tel-Aviv University, Tel-Aviv 69978, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The need for a long-term solution for filling the defects created during partial mastectomies due to breast cancer diagnosis has not been met to date. All available defect-filling methods are non-permanent and necessitate repeat procedures. Here, we report on novel injectable porous hydrogel structures based on the natural polymers gelatin and alginate, which are designed to serve for breast reconstruction and regeneration following partial mastectomy. The effects of the formulation parameters on the mechanical and physical properties were thoroughly studied. The modulus in compression and tension were in the range of native breast tissue. Both increased with the increase in the crosslinker concentration and the polymer-air ratio. Resilience was very high, above 93% for most studied formulations, allowing the scaffold to be continuously deformed without changing its shape. The combination of high resilience and low elastic modulus is favored for adipose tissue regeneration. The physical properties of gelation time and water uptake are controllable and are affected mainly by the alginate and N-(3-dimethylaminopropyl)-N'-ethylcarbodiimide hydrochloride (EDC) concentrations and less by the polymer-air ratio. In vitro cell viability tests were performed on mouse preadipocytes and indicated high biocompatibility. The minimally invasive nature of this approach, along with the excellent properties of the scaffold, will enable the filling of complex voids while simultaneously decreasing surgical costs and greatly improving patient well-being.

Indexed as

adipose tissue regenerationgelatinporous hydrogelresilience

Identifiers

PMID39057298
PMCPMC11277960

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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.