MétaCan
Menu
← Back to cohort
Record W4281717222 · doi:10.1242/jeb.243489

How distinct killifish populations respond differently to stress

2022· article· en· W4281717222 on OpenAlexaffabout
Andrea Murillo

Bibliographic record

VenueJournal of Experimental Biology · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsMcMaster University
Fundersnot available
KeywordsKillifishFundulusPopulationBiologyFisheryZoologyEcologyFish <Actinopterygii>GeographyDemography

Abstract

fetched live from OpenAlex

Down the east coast of North America, populations of Atlantic killifish, Fundulus heteroclitus, experience wildly different thermal environments. Southern populations experience water that is, on average, 12°C hotter than northern populations annually. These northern and southern killifish populations cope with stress differently. When fish are stressed, such as when predators are nearby, they activate a suite of mechanisms that regulate the release of the stress hormone cortisol, allowing the fish to remain in good condition. Researchers found previously that killifish from southern populations had higher plasma cortisol levels than killifish from northern populations after they experienced the same stress. To figure out why some fish respond strongly to stress while others do not, Madison Earhart and co-workers from the University of British Columbia, Canada, with colleagues from the University of Manitoba, Canada, and the University of Glasgow, UK, set out to determine what genes are responsible for the differences in killifish stress responses by investigating different mechanisms that trigger cortisol release after experiencing stress.Earhart and colleagues travelled to the USA and collected adult killifish from northern New Hampshire and southern Georgia populations. Then, they brought the fish back to the lab in British Columbia. First, the team wanted to see whether the differences in population stress response changed when the fish experienced stress briefly or were exposed to the same stress repeatedly over the period of a week by either putting the fish in buckets and shaking them for half an hour or repeatedly shaking them every day for a week. After stressing the fish, the team collected samples of the fish's blood to measure their cortisol plasma levels, in addition to collecting samples of the fish's brain, head kidney – the organ that produces cortisol – and liver – the organ that produces and breaks down glucose – to measure the expression of genes important for the production and release of cortisol due to stress.After experiencing the single stressful situation, the southern killifish population had higher cortisol levels than the northern killifish population. However, when the fish were repeatedly stressed over the period of a week, there was no difference in cortisol levels between the northern and southern populations. The southern population of killifish, which had a stronger response to the individual stressful situation, expressed more of the genes involved in cortisol production in the brain and head kidney. In addition, the livers of fish from the southern population were more responsive to the cortisol stress hormone as they expressed larger amounts of the gene for the protein that triggers the protective mechanisms that are activated by cortisol when a fish is stressed.The team also measured the condition of the fish after repeated stress. They found that the southern killifish, which were more stress responsive than the northern killifish, were in better condition after experiencing repeated stress than were northern populations. This showed that responding to stress by increasing cortisol was beneficial for the southern population of fish.Earhart and colleagues noted that the answer as to why some fish respond more strongly to stress than others is more complex than simply increasing cortisol levels in the body. They showed that there are differences in the expression of genes all along the pathways that make cortisol, respond to cortisol and cease cortisol production in these two different populations of fish. Therefore, it is important to continue to study these differences in populations of the same species adapted to different environments.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.023
GPT teacher head0.283
Teacher spread0.261 · 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 designObservational
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
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Experimental Biology→Same topicAquaculture disease management and microbiota→French-language works237,207→