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Record W4206183230 · doi:10.1007/s11033-021-06997-4

Role and relevance of fish cell lines in advanced in vitro research

2022· review· en· W4206183230 on OpenAlexaff
Mukunda Goswami, B. S. Yashwanth, Vance L. Trudeau, W. S. Lakra

Bibliographic record

VenueMolecular Biology Reports · 2022
Typereview
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsOntario GenomicsUniversity of Ottawa
FundersICAR-National Bureau of Fish Genetic ResourcesIndian Council of Agricultural Research
KeywordsBiologyAquacultureCell cultureBiotechnologyFish <Actinopterygii>In vitroOrganismFish farmingCell biologyComputational biologyGeneticsFishery

Abstract

fetched live from OpenAlex

INTRODUCTION: Cell line derived from fish has been established as a promising tool for studying many key issues of aquaculture covering fish growth, disease, reproduction, genetics, and biotechnology. In addition, fish cell lines are very useful in vitro models for toxicological, pathological, and immunological studies. The easier maintenance of fish cell lines in flexible temperature regimes and hypoxic conditions make them preferable in vitro tools over mammalian cell lines. Great excitement has been observed in establishing and characterizing new fish cell lines representing diverse fish species and tissue types. The well-characterized and authenticated cell lines are of utmost essential as these represent cellular functions very similar to in vivo state of an organism otherwise it would affect the reproducibility of scientific research. CONCLUSION: The fish cell lines have exhibited encouraging results in several key aspects of in vitro research in aquaculture including virology, nutrition and metabolism, production of vaccines, and transgenic fish production. The review paper reports the cell lines developed from fish, their characterization, and biobanking along with their potential applications and challenges in in vitro research.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.022
GPT teacher head0.335
Teacher spread0.312 · 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 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

Citations139
Published2022
Admission routes1
Has abstractyes

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