Evidence map›Paper›PMID 37902084›Full record

ArticleAdvanced healthcare materials2024

Microfluidically Aligned Collagen to Maintain the Phenotype of Tenocytes In Vitro.

Francesca Giacomini, David Baião Barata, Hoon Suk Rho, Zeinab Tahmasebi Birgani, Clemens van Blitterswijk, Stefan Giselbrecht, Roman Truckenmüller, Pamela Habibović

Open access · hybridAbstract read
In one paragraph

Article in Advanced healthcare materials, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
4.6field-weighted citation impact, top 4% of its field
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

13 citing papers in PubMed, 19 citations in OpenAlex.

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  12. Tunable Macroscopic Alignment of Self-Assembling Peptide Nanofibers.bioRxiv : the preprint server for biology · 2024
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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

8 authors at 2 institutions in 2 countries.

Francesca GiacominiDepartment of Instructive Biomaterials Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, Universiteitssingel 40, Maastricht, 6229 ER, The Netherlands.
David Baião BarataDepartment of Instructive Biomaterials Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, Universiteitssingel 40, Maastricht, 6229 ER, The Netherlands.
Hoon Suk RhoDepartment of Instructive Biomaterials Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, Universiteitssingel 40, Maastricht, 6229 ER, The Netherlands.
Zeinab Tahmasebi BirganiDepartment of Instructive Biomaterials Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, Universiteitssingel 40, Maastricht, 6229 ER, The Netherlands.
Clemens van BlitterswijkDepartment of Instructive Biomaterials Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, Universiteitssingel 40, Maastricht, 6229 ER, The Netherlands.
Stefan GiselbrechtDepartment of Instructive Biomaterials Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, Universiteitssingel 40, Maastricht, 6229 ER, The Netherlands.
Roman TruckenmüllerDepartment of Instructive Biomaterials Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, Universiteitssingel 40, Maastricht, 6229 ER, The Netherlands.ORCID 0000-0001-7541-525X
Pamela HabibovićDepartment of Instructive Biomaterials Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, Universiteitssingel 40, Maastricht, 6229 ER, The Netherlands.
Maastricht University · NLUniversity of Lisbon · PT

Funding

Interreg Vlaanderen-Nederland 0433Limburg INvesteert in haar Kenniseconomie/LINK SAS-2014-00837Limburg INvesteert in haar Kenniseconomie/LINK SAS-2018-02477Netherlands Organization for Scientific Research 024.003.013Netherlands Organization for Scientific Research 15604Netherlands Organization for Scientific Research 18748
6 · The paper itself

Abstract

Tendon is a highly organized tissue that transmits forces between muscle and bone. The architecture of the extracellular matrix of tendon, predominantly from collagen type I, is important for maintaining tenocyte phenotype and function. Therefore, in repair and regeneration of damaged and diseased tendon tissue, it is crucial to restore the aligned arrangement of the collagen type I fibers of the original matrix. To this end, a novel, user-friendly microfluidic piggyback platform is developed allowing the controlled patterned formation and alignment of collagen fibers simply on the bottom of culture dishes. Rat tenocytes cultured on the micropatterns of aligned fibrous collagen exhibit a more elongated morphology. The cells also show an increased expression of tenogenic markers at the gene and protein level compared to tenocytes cultured on tissue culture plastic or non-fibrillar collagen coatings. Moreover, using imprinted polystyrene replicas of aligned collagen fibers, this work shows that the fibrillar structure of collagen per se affects the tenocyte morphology, whereas the biochemical nature of collagen plays a prominent role in the expression of tenogenic markers. Beyond the controlled provision of aligned collagen, the microfluidic platform can aid in developing more physiologically relevant in vitro models of tendon and its regeneration.

Indexed as

Collagen Type ITenocytesAnimalsCollagenExtracellular MatrixPhenotypeRatsCollagenCollagen Type Icell morphology/shapecollagen alignmentmicrofluidicsphenotype maintenancetenocytes

Identifiers

PMID37902084
PMCPMC11468977
OpenAlexW4388014384

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.