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Record W2135628534 · doi:10.5772/45879

Retinoid X Receptor Signalling in the Specification of Skeletal Muscle Lineage

2012· book-chapter· en· W2135628534 on OpenAlexfundno aff
Melanie Le, Qiao Li

Bibliographic record

VenueInTech eBooks · 2012
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSignallingRetinoidRetinoid X receptorSignalling pathwaysLineage (genetic)Skeletal muscleRetinoid X receptor betaEndocrinologyCell biologyInternal medicineBiologyNeuroscienceReceptorChemistryMedicineGeneticsNuclear receptorRetinoic acidGene

Abstract

fetched live from OpenAlex

Pluripotent stem cells have the capacity to develop into different cell lineages, and can be promoted into skeletal muscle lineage through the use of small molecule inducers. Retinoic acid (RA) signaling through the retinoic acid receptor (RAR) and retinoid X receptor (RXR), is important for embryonic development, and is able to enhance myogenic differentiation in vitro if used in combination with other small molecule inducers. Nevertheless, it only yields moderate results in promoting the differentiation of embryonic stem (ES) cells into skeletal myocytes. RXR is also known to be essential for embryonic development, but it is generally considered to act as a silent partner for other nuclear receptors such as RAR. We recently discovered that RXR selective ligand efficiently induces myogenic differentiation in mouse ES cells which respond poorly to RA. In addition, myogenic differentiation, enhanced by the RXR ligand, is mediated through a RAR independent mechanism, and recapitulates closely the sequential events observed in vivo. Since ES cell differentiation represents the properties of early developing embryo, efficiently generating skeletal myocytes with RXR selective ligand provides means to further scrutinize signaling pathways in skeletal myogenesis, in view of developing cell-based therapies for skeletal muscle-related diseases. In this chapter, we attempt to provide an in-depth analysis of recent research findings and the current stage of knowledge in the field of skeletal myogenesis.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.886
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0010.000
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 head0.019
GPT teacher head0.239
Teacher spread0.220 · 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.

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
Published2012
Admission routes1
Has abstractyes

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