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Record W2765278608 · doi:10.1242/jeb.171223

Fish feel gravity

2017· article· en· W2765278608 on OpenAlexaboutno aff
Kathryn Knight

Bibliographic record

VenueJournal of Experimental Biology · 2017
Typearticle
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsnot available
Fundersnot available
KeywordsFish <Actinopterygii>CreaturesWrightDry landEcologyArchaeologyFisheryBiologyGeographyHistoryNatural (archaeology)Art history

Abstract

fetched live from OpenAlex

There is a very good reason why the largest creatures reside in our oceans. ‘The buoyant support of water can explain why whales are so much larger than elephants’, says Andy Turko, from the University of Guelph, Canada. In contrast, the skeletons of terrestrial animals are moulded by the effects of gravity: they can detect and adjust to changes as they gain or lose weight. Which begs the question: can fish skeletons also detect and respond to gravity? ‘Some researchers have assumed that they would never have needed to evolve the ability to sense or respond to gravity’, says Turko; terrestrial animals – including the whale's ancestors – were believed to have evolved the sense only after they left their fish cousins in the water. However, Turko and his colleagues Patricia Wright and Doug Fudge wondered whether the ability to sense gravity is more ancient. Knowing that amphibious fish, such as the mangrove rivulus (Kryptolebias marmoratus), routinely experience the effects of gravity when they clamber onto land, Wright, Fudge and Turko wondered whether the tiny fish can stiffen their skeletons when their weight increases after leaving the water.Fixing on the 1 mm long gill arch as the most suitable bone in the fish's body to test, Turko and Fudge kept some of the fish on dry land for 1 and 2 weeks, while another group of fish was allowed to remain in water, before comparing the stiffness of their gill arches. Impressively, the gill arch bones of the fish that were out of water were 60% stiffer than those of the submerged fish after 1 week and the effects of gravity persisted for more than 2 weeks after the fish's return to water. However, the team wasn't entirely convinced that they could attribute the bone's increased stiffness to the effect of gravity alone: were they becoming stiffer as a result of drying? Turko and Wright realised that they would have to simulate weightless conditions while the fish were out of water before they could be convinced that gravity was the culprit.Recalling that Roger Croll, Frank Smith and Matthew Stoyek, from Dalhousie University, used a random positioning machine to simulate the effects of low gravity on developing zebrafish embryos, Wright sent Turko to Dalhousie to test whether the fish's bones became stiffer when they were effectively weightless while out of water. After a week of gyrating the air-exposed fish in microgravity – to simulate weightlessness out of water – and measuring the stiffness of their gill arches, the bones were as flexible as those of the fish that were swimming free. So the bones had not become stiffer because they were drying out. Fish that climb out of water onto land are able to sense the effects of gravity and increase the stiffness of their bones to bear the extra weight.But how were the high-and-dry fish modifying their bones to increase their stiffness? Extracting proteins from the bones of fish that had spent 2 weeks out of water, Dietmar Kültz, from the University of California, Davis, USA, was impressed to see an extraordinary (ninefold) increase in one protein, type X collagen, which is known to be involved in bone growth. ‘To see such a dramatic increase was exciting evidence that gravity exposure causes bone growth’, says Turko.Having found that fish are able to sense the effects of gravity, Turko suspects that this ability may help fish to adapt their skeletons to withstand the stresses and strains of swimming. He also suggests that our ancient fish ancestors may have been able to stiffen their skeletons in response to weight gains when they first pulled themselves out of the water. ‘This may mean that something considered a major challenge during the invasion of land by vertebrates (supporting their own body weight) may not actually have been that challenging of an evolutionary problem’, says Turko.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.005
Scholarly communication0.0020.002
Open science0.0000.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0170.006

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 head0.028
GPT teacher head0.372
Teacher spread0.343 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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Same venueJournal of Experimental BiologySame topicSpaceflight effects on biologyFrench-language works237,207