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Record W3003584875 · doi:10.1111/febs.15228

Evolutionary repression of chondrogenic genes in the vertebrate osteoblast

2020· review· en· W3003584875 on OpenAlexafffund
Jason K. B. Nguyen, B. Frank Eames

Bibliographic record

VenueFEBS Journal · 2020
Typereview
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsUniversity of Saskatchewan
FundersNational Research Council CanadaWestern Economic Diversification CanadaNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchCanadian Light Source
KeywordsChondrogenesisBiologyZebrafishVertebrateExtant taxonGeneCartilageEvolutionary biologyOsteoblastCell typeGene duplicationCell biologyAnatomyCellGenetics

Abstract

fetched live from OpenAlex

Gene expression in extant animals might reveal how skeletal cells have evolved over the past 500 million years. The cells that make up cartilage (chondrocytes) and bone (osteoblasts) express many of the same genes, but they also have important molecular differences that allow us to distinguish them as separate cell types. For example, traditional studies of later-diverged vertebrates, such as mouse and chick, defined the genes Col2a1 and sex-determining region Y-box 9 as cartilage-specific. However, recent studies have shown that osteoblasts of earlier-diverged vertebrates, such as frog, gar, and zebrafish, express these 'chondrogenic' markers. In this review, we examine the resulting hypothesis that chondrogenic gene expression became repressed in osteoblasts over evolutionary time. The amphibian is an underexplored skeletal model that is uniquely positioned to address this hypothesis, especially given that it diverged when life transitioned from water to land. Given the relationship between phylogeny and ontogeny, a novel discovery for skeletal cell evolution might bolster our understanding of skeletal cell development.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.044
GPT teacher head0.322
Teacher spread0.279 · 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

Citations13
Published2020
Admission routes2
Has abstractyes

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