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Record W2892264511 · doi:10.1111/jfb.13798

A transcriptomic investigation of appetite‐regulation and digestive processes in giant grouper <i>Epinephelus lanceolatus</i> during early larval development

2018· article· en· W2892264511 on OpenAlexaff
Kelli Anderson, Richard Knuckey, Maximiliano Cánepa, Abigail Elizur

Bibliographic record

VenueJournal of Fish Biology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsMiller Group (Canada)
FundersAustralian Centre for International Agricultural Research
KeywordsBiologyAppetiteGrouperTranscriptomeLarvaZoologyEpinephelusGene expressionInternal medicineGeneEndocrinologyEcologyGeneticsFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The giant grouper Epinephelus lanceolatus is an ecologically vulnerable species with high market demand. However, efforts to improve larval husbandry are hindered by a lack of knowledge surrounding larval developmental physiology. To address this shortfall, a transcriptomic approach was applied to larvae between 1 and 14 days post hatch (dph) to characterise the molecular ontogenesis of genes that influence appetite and digestion. Appetite regulating factors were detected from 1 dph, including neuropeptide Y, nesfatin-1, cocaine and amphetamine regulated transcript, cholecystokinin and pituitary adenylate cyclase activating peptide and the expression level of several genes changed sharply with the onset of exogenous feeding. The level of expression for proteases, chitinases, lipases and amylases typically followed one of two expression patterns, a general increase as development progressed, or an inverted U-shape with maximal expression at c. 6 dph. Similarly, the tendency among both expression patterns was for the level of expression to increase around the time of mouth-opening. There was also evidence to suggest the presence of putative isoforms for several digestion-related genes. We have provided an insight into appetite-regulation and digestive processes in groupers during early larval development and have developed a transcriptomic database that will aid future efforts to rear this species in an aquaculture setting.

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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.013
GPT teacher head0.207
Teacher spread0.194 · 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

Citations12
Published2018
Admission routes1
Has abstractyes

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