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Not all cartilages are the same! Differential effects in the cranial vs caudal skeleton after BMP inhibition in zebrafish

2020· article· en· W3016558123 on OpenAlexaffabout
Tamara A. Franz‐Odendaal, Nicholas W. Zinck

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsDalhousie UniversityMount Saint Vincent University
Fundersnot available
KeywordsCartilageBone morphogenetic proteinZebrafishCell biologySkeleton (computer programming)BiologyAnatomyMorphogenesisBone morphogenetic protein 2GeneticsGene

Abstract

fetched live from OpenAlex

Several signaling factors are known to be involved in cartilage morphogenesis via the regulation of condensation size, shape, and location. Of these signaling factors, the bone morphogenetic proteins (BMPs) are known to be crucial in regulating the formation of condensations, cellular differentiation, and in the expression of the downstream transcription factors. Furthermore, interference with the BMP signaling pathway results in disrupted bone and cartilage development in various vertebrates. This study aims to elucidate the effects of BMP inhibition on cartilage morphology in the zebrafish. We utilise a pharmaceutical BMP pathway inhibitor at specific early time points of development. We focus on two cartilages, one cranial and one caudal, that develop concurrently but which have different developmental origins. Our data shows that the cranial cartilage, namely the scleral cartilage, is highly robust and unaffected by the BMP inhibitor. This is in stark contrast to the caudal cartilages, for example the hypurals, which are dramatically affected. These effects include fusion of elements, missing elements and altered morphology. Understanding these variable effects provides insight into the mechanisms that limit versus enable cartilages from altering their shape and/or size. The robustness of the cranial skeleton is particularly noteworthy given the multitude of disorders that affect this part of the skeleton. Support or Funding Information Funding was provided by the Natural Science and Engineering Research Council of Canada

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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.247
Teacher spread0.236 · 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
Published2020
Admission routes2
Has abstractyes

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