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Record W2953585780 · doi:10.1242/jeb.192906

Deep breathing in tired trout

2019· article· en· W2953585780 on OpenAlexaff
Andy J. Turko

Bibliographic record

VenueJournal of Experimental Biology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsMcMaster UniversityUniversity of Windsor
Fundersnot available
KeywordsGillBreathingTroutRespirationRainbow troutOxygenRespiratory systemFish <Actinopterygii>BiologyControl of respirationVentilation (architecture)AnatomyPhysiologyAnimal scienceChemistryFishery

Abstract

fetched live from OpenAlex

How do animals know when to take a breath? Whether the animal is awake or asleep, and during exercise or at rest, the respiratory system carefully regulates breathing patterns to maintain oxygen uptake without the need for conscious thought. Scientists have long known that specialized cells continually monitor the pH and levels of oxygen and carbon dioxide in the blood and these cells send neural impulses to stimulate breathing if these parameters move away from normal values. More recently, experiments in rats and mice have found that the common organic compound lactate, produced by animals when not enough oxygen is available, also stimulates breathing. However, it is unknown whether this mechanism of respiratory control is unique to mammals or a trait shared by all vertebrates.A new study, led by Mikkel Thomsen at Aarhus University, Denmark, tested the hypothesis that respiration in fishes is controlled by the amount of lactate in the blood just like it is in mammals. The authors performed careful surgeries on rainbow trout (Oncorhynchus mykiss), inserting a tiny tube into the bloodstream so that they could inject lactate to directly manipulate levels in the blood. They also attached an electrical probe to the bony plate that covers the gills, allowing them to measure the amplitude and frequency of the fish's breathing movements.Just as the authors hypothesized, addition of lactate to the bloodstream stimulated trout to take larger, deeper breaths, but the frequency of breathing did not change. To see whether the fish could respond to the precise amount of lactate in the blood, the authors added different quantities through the plastic tubing and found that the more lactate they added, the deeper the breaths of the fish. Thus, lactate seems capable of transmitting detailed information about the oxygen requirements of the fish.Next, the authors asked how trout sense changes in circulating lactate levels. Specialized cells in the gills of other fishes are known to sense oxygen levels in the blood and signal for increased breathing, so perhaps these could also sense lactate. First, Thomsen and his colleagues painstakingly removed the gills that contain most of these sensory cells and, as predicted, the breathing of these fish hardly increased when they were given lactate injections. Next, the authors injected intact fish with a variety of drugs that are known to target the gill sensory cells. In the presence of these drugs, lactate injections did not stimulate breathing, strongly indicating that the lactate signal is received by sensory cells in the trout's gills. Finally, the researchers wanted to know whether the lactate sensors in trout shared an evolutionary history with those already discovered in mammals, or whether the fish used a different mechanism to keep tabs on blood lactate. Searching through the genetic code of the trout, the authors found a gene that looked remarkably like the one that codes for the lactate sensor in mammals. Thus, it seems that all vertebrates, whether furry or fishy, may share a signalling system that uses lactate to stimulate breathing.Of course, many more animals should be investigated before we can conclude that lactate is a universal respiratory stimulant, but the benefits of this simple signalling system are clear. When oxygen is limited, animals take an energetic loan in the form of lactate. Then, to pay off this ‘oxygen debt’, lactate acts as its very own debt collector, stimulating deeper breathing and hence increased oxygen uptake. No middlemen required.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.264
Teacher spread0.248 · 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
Published2019
Admission routes1
Has abstractyes

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