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Record W3127403853 · doi:10.2217/rme-2020-0045

Adipose Tissue-Derived Mesenchymal Stem Cells for Breast Tisssue Regeneration

2021· review· en· W3127403853 on OpenAlexaff
Mohammed A Banani, Mohammed Rahmatullah, Nawras Farhan, Zoe Hancox, Safiyya Yousaf, Zohreh Arabpour, Zoha Salehi Moghaddam, Masoud Mozafari, Farshid Sefat

Bibliographic record

VenueRegenerative Medicine · 2021
Typereview
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsAdipose tissueMesenchymal stem cellRegeneration (biology)Breast cancerStem cellTissue engineeringMedicineBiologyPathologyBioinformaticsCancerCell biologyBiomedical engineeringInternal medicine

Abstract

fetched live from OpenAlex

With an escalating incidence of breast cancer cases all over the world and the deleterious psychological impact that mastectomy has on patients along with several limitations of the currently applied modalities, it's plausible to seek unconventional approaches to encounter such a burgeoning issue. Breast tissue engineering may allow that chance via providing more personalized solutions which are able to regenerate, mimicking natural tissues also facing the witnessed limitations. This review is dedicated to explore the utilization of adipose tissue-derived mesenchymal stem cells for breast tissue regeneration among postmastectomy cases focusing on biomaterials and cellular aspects in terms of harvesting, isolation, differentiation and new tissue formation as well as scaffolds types, properties, material–host interaction and an in vitro breast tissue modeling.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.003

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 head0.136
GPT teacher head0.413
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), 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

Citations21
Published2021
Admission routes1
Has abstractyes

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