MétaCan
Menu
Back to cohort
Record W4404404652 · doi:10.3791/66717

Fibro-Adipogenic Progenitor Isolation, Expansion, and Differentiation from the Spiny Mouse Model

2024· article· en· W4404404652 on OpenAlexaff
Bruce Lin, H. S. Soliman, Fábio Rossi, Marine Théret

Bibliographic record

VenueJournal of Visualized Experiments · 2024
Typearticle
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsProgenitor cellAdipogenesisCell biologyBiologyRegeneration (biology)ProgenitorSkeletal muscleRegenerative medicineExtracellular matrixPopulationStem cellMesenchymal stem cellAnatomyMedicine

Abstract

fetched live from OpenAlex

Due to its exceptional repair program, the spiny mouse is an emerging research model for regenerative medicine. Fibro-adipogenic progenitors are tissue-resident cells that are able to differentiate into adipocytes, fibroblasts, and chondrocytes. Fibro-adipogenic progenitors are fundamental for orchestrating tissue regeneration as they are responsible for extracellular matrix remodeling after injury. This study focuses on investigating the specific role of fibro-adipogenic progenitors in spiny mouse cardiac repair and skeletal muscle regeneration. To this end, a protocol has been optimized for the purification of spiny mouse fibro-adipogenic progenitors by flow cytometry from enzymatically dissociated skeletal and cardiac muscle. The population obtained from this protocol is capable of expanding in vitro, and can be differentiated to myofibroblasts and adipocytes. This protocol offers a valuable tool for researchers to examine the distinctive properties of spiny mouse, and to compare them to the Mus musculus. This will provide insights that could advance the understanding of regenerative mechanisms in this intriguing model.

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)0.000
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.028
GPT teacher head0.387
Teacher spread0.359 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Visualized ExperimentsSame topicTissue Engineering and Regenerative MedicineFrench-language works237,207