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Record W4401482592 · doi:10.3390/eng5030098

Exploring the Frontier of 3D Bioprinting for Tendon Regeneration: A Review

2024· review· en· W4401482592 on OpenAlexaff
Josée Rosset, Emmanuel Olaniyanu, Kevin Y. Stein, Nátaly Domingues Almeida, Rodrigo França

Bibliographic record

VenueEng—Advances in Engineering · 2024
Typereview
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsRegeneration (biology)3D bioprintingScaffoldTendonFrontierComputer scienceTissue engineeringEngineeringMedicineBiomedical engineeringBiologySurgeryCell biologyPolitical science

Abstract

fetched live from OpenAlex

The technology of 3D bioprinting has sparked interest in improving tendon repair and regeneration, promoting quality of life. To perform this procedure, surgical intervention is often necessary to restore functional capacity. In this way, 3D bioprinting offers a scaffold design, producing tendons with precise microarchitectures, promoting the growth of new tissues. Furthermore, it may incorporate bioactive compounds that can further stimulate repair. This review elucidates how 3D bioprinting holds promise for tendon repair and regeneration, detailing the steps involved and the various approaches employed. They demonstrate future challenges and perspectives and provide valuable information on the concept, bioprinting design, and 3D bioprinting techniques for the repair of tendon injuries.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.880
Threshold uncertainty score0.839

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.073
GPT teacher head0.347
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractyes

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