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Record W3168320615 · doi:10.19080/ctbeb.2021.20.556028

Female Bioengineering: Primordial Germ Cell Differentiation of Mesenchymal Stem Cells onto Placental Scaffolds

2021· article· en· W3168320615 on OpenAlexaff
Amanda Baracho Trindade Hill

Bibliographic record

VenueCurrent Trends in Biomedical Engineering & Biosciences · 2021
Typearticle
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsUniversité de MontréalOttawa Fertility Centre
Fundersnot available
KeywordsMesenchymal stem cellCD90Stem cellCell biologyRegenerative medicineScaffoldBiologyTissue engineeringCD34Adipose tissueAnatomyBiomedical engineeringMedicineEndocrinologyGenetics

Abstract

fetched live from OpenAlex

Introduction: Female infertility is a condition that is currently treated through the maximization of existing reserves; a necessity due to the fact that a true reversal of the processes leading to infertility is not yet technologically possible. This experiment examined the ability of mesenchymal stem cells to differentiate into primordial germ cells (PGC) when cultured onto the placental scaffold. Methods: To produce the scaffolds, the cotelydons were collected and decellularized by umbilical vessel SDS perfusion. Adipose derived cells were isolated based on rapid adherence to the plastic. Results: The isolated cells displayed the markers CD90 and 105, while lacked CD34 and CD45. When seeded onto the scaffold, the cells successfully differentiated into PGC like cells, displaying typical PGCs markers, including STELLA, OCT4, DAZL and VASA. Discussion: These materials were chosen for their low cost and wide availability. The data in this study show the promising potential of cell-scaffold complex to support the development of female tissue engineering-based regenerative medicine therapies.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.022
GPT teacher head0.278
Teacher spread0.257 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations1
Published2021
Admission routes1
Has abstractyes

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