Evidence map›Paper›PMID 26839559›Full record

ReviewStem cells international2016

Engineering Tendon: Scaffolds, Bioreactors, and Models of Regeneration.

Daniel W Youngstrom, Jennifer G Barrett

Abstract readReview
In one paragraph

Review in Stem cells international, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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  14. A brief history of tendon and ligament bioreactors: Impact and future prospects.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2020
    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

2 authors.

Daniel W YoungstromDepartment of Large Animal Clinical Sciences, Marion duPont Scott Equine Medical Center, Virginia Tech, 17690 Old Waterford Road, Leesburg, VA 20176, USA.
Jennifer G BarrettDepartment of Large Animal Clinical Sciences, Marion duPont Scott Equine Medical Center, Virginia Tech, 17690 Old Waterford Road, Leesburg, VA 20176, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tendons bridge muscle and bone, translating forces to the skeleton and increasing the safety and efficiency of locomotion. When tendons fail or degenerate, there are no effective pharmacological interventions. The lack of available options to treat damaged tendons has created a need to better understand and improve the repair process, particularly when suitable autologous donor tissue is unavailable for transplantation. Cells within tendon dynamically react to loading conditions and undergo phenotypic changes in response to mechanobiological stimuli. Tenocytes respond to ultrastructural topography and mechanical deformation via a complex set of behaviors involving force-sensitive membrane receptor activity, changes in cytoskeletal contractility, and transcriptional regulation. Effective ex vivo model systems are needed to emulate the native environment of a tissue and to translate cell-matrix forces with high fidelity. While early bioreactor designs have greatly expanded our knowledge of mechanotransduction, traditional scaffolds do not fully model the topography, composition, and mechanical properties of native tendon. Decellularized tendon is an ideal scaffold for cultivating replacement tissue and modeling tendon regeneration. Decellularized tendon scaffolds (DTS) possess high clinical relevance, faithfully translate forces to the cellular scale, and have bulk material properties that match natural tissue. This review summarizes progress in tendon tissue engineering, with a focus on DTS and bioreactor systems.

Identifiers

PMID26839559
PMCPMC4709784

What OpenQuestion holds

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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.