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Record W4294001821 · doi:10.1016/j.ygeno.2022.110477

Zebrafish Danio rerio myotomal muscle structure and growth from a spatial transcriptomics perspective

2022· article· en· W4294001821 on OpenAlexaff
Guan‐Ting Liu, Takumi Ito, Yusuke Kijima, Kazutoshi Yoshitake, Shuichi Asakawa, Shugo Watabe, Shigeharu Kinoshita

Bibliographic record

VenueGenomics · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsUniversity of British Columbia
FundersJapan Society for the Promotion of ScienceChina Scholarship Council
KeywordsBiologyDanioMyogenesisZebrafishTranscriptomeMyocyteAnatomyFish finSkeletal muscleMuscle tissueCell biologyGene expressionGeneFish <Actinopterygii>GeneticsFishery

Abstract

fetched live from OpenAlex

Fish exhibit different muscle structures and growth characteristics compared with mammals. We used a spatial transcriptomics approach and examined myotomal muscle sections from zebrafish. Adult muscles were divided into eight regions according to spatial gene expression characteristics. Slow muscle was located in the wedge-shaped region near the lateral line and at the base of the dorsal fin, intermediate muscle was located in a ribbon-shaped region adjacent to slow muscle, and fast muscle was located in the deep region of the trunk, surrounded by intermediate muscle; the interior of fast muscle was further divided into 6 parts by their transcriptomic features. Combined analysis of adult and larval data revealed that adult muscles contain specific regions similar to larval muscles. These regions showed active myogenesis and a high expression of genes associated with muscle hyperplasia. This is the first study to apply spatial transcriptomics to fish myotomal muscle structure and growth.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.385
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.007
GPT teacher head0.191
Teacher spread0.184 · 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.

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

Citations17
Published2022
Admission routes1
Has abstractyes

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