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Record W2744114092 · doi:10.1002/nau.23367

Biomimetic implants for pelvic floor repair

2017· review· en· W2744114092 on OpenAlexaff
Mahshid Vashaghian, Sebastianus J. Zaat, Theo H. Smit, Jan‐Paul Roovers

Bibliographic record

VenueNeurourology and Urodynamics · 2017
Typereview
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsInstitute of Infection and Immunity
FundersU.S. Food and Drug AdministrationUniversiteit van Amsterdam
KeywordsExtracellular matrixMedicineSoft tissueImplantTissue engineeringBiomedical engineeringIn vivoNative tissueSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Polypropylene implants are used for the reconstructive surgery of urogynaecological disorders like pelvic organ prolapse, but severe complications associated with their use have been reported. There is evidence that surface properties and a difference in mechanical stiffness between the implant and the host tissue contribute to these adverse events. Electrospinning is an innovative engineering alternative that provides a biomimetic microstructure for implants, resulting in a different mechano-biological performance. AIM: The main objective of this review is to inform about the potential of electrospun matrices as an alternative modality for pelvic floor repair. METHODS: Publications with the following studies of electrospun matrices were reviewed: (i) the technique; (ii) in vitro use for soft tissue engineering; (iii) in vivo use for reconstruction of soft tissues in animals; and (iv) clinical use in humans. RESULTS: Electrospun matrices provide a synthetic mimic of natural extracellular matrix (ECM), favoring cellular attachment, proliferation and matrix deposition, through which a proper, low-inflammatory tissue-implant interaction can be established. Electrospun sheets can also be created with sufficient mechanical strength and stiffness for usage in prolapse surgery. CONCLUSION: Electrospun matrices mimic the structural topography of the extracellular matrix and can be functionalized for better biological performance. As such, they have great potential for the next generation of urogynecological implants. However, their long-term safety and efficacy must still be established in vivo.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.091
GPT teacher head0.398
Teacher spread0.307 · 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.

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

Citations34
Published2017
Admission routes1
Has abstractyes

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