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Record W4251410456 · doi:10.3410/f.1716967.1224066

Faculty Opinions recommendation of Mesenchymal progenitors distinct from satellite cells contribute to ectopic fat cell formation in skeletal muscle.

2010· dataset· en· W4251410456 on OpenAlexaff
Fábio Rossi

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2010
Typedataset
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMesenchymal stem cellAdipogenesisProgenitor cellCell biologySkeletal muscleBiologySatelliteCellStem cellEndocrinologyGenetics

Abstract

fetched live from OpenAlex

Ectopic fat deposition in skeletal muscle is closely associated with several disorders, however, the origin of these adipocytes is not clear, nor is the mechanism of their formation. Satellite cells function as adult muscle stem cells but are proposed to possess multipotency. Here, we prospectively identify PDGFRalpha(+) mesenchymal progenitors as being distinct from satellite cells and located in the muscle interstitium. We show that, of the muscle-derived cell populations, only PDGFRalpha(+) cells show efficient adipogenic differentiation both in vitro and in vivo. Reciprocal transplantations between regenerating and degenerating muscles, and co-culture experiments revealed that adipogenesis of PDGFRalpha(+) cells is strongly inhibited by the presence of satellite cell-derived myofibres. These results suggest that PDGFRalpha(+) mesenchymal progenitors are the major contributor to ectopic fat cell formation in skeletal muscle, and emphasize that interaction between muscle cells and PDGFRalpha(+) mesenchymal progenitors, not the fate decision of satellite cells, has a considerable impact on muscle homeostasis. PMID: 20081842

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)0.014
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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.067
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.014
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0670.027

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 head0.023
GPT teacher head0.332
Teacher spread0.309 · 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
GenreDataset

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
Published2010
Admission routes1
Has abstractyes

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