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Record W2965097553 · doi:10.1242/jeb.210328

Unintentionally evolved fruit flies show how insects survive CO2 knockout

2019· article· en· W2965097553 on OpenAlexaboutno aff
Kathryn Knight

Bibliographic record

VenueJournal of Experimental Biology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyLongevityQueen (butterfly)Drosophila (subgenus)Zoology

Abstract

fetched live from OpenAlex

It's a cute resurrection party trick: give a fruit fly (Drosophila melanogaster) a puff of CO2 and the insect topples over apparently dead, only to revive minutes later as it emerges from a coma triggered by the anaesthetic. So, when evolutionary biologist Adam Chippindale, from Queen's University, Canada, heard that Chengfeng Xiao and Meldrum Robertson from down the corridor were curious about the physiological mechanisms underpinning the insects’ powers of recovery from anoxia (oxygen deprivation), he realised that he already had populations of the animals ideally suited to investigate the phenomenon.‘Back in the 1980s, my PhD supervisor, Michael Rose, began a famous experiment’, says Chippindale. Curious about the effects of aging, Rose, at the University of California, Irvine, USA, began mixing aged insects together in the hope of evolving populations of fruit fly super-agers. However, he also kept other populations of flies descended from the same ancestors in small vials – which had to be mixed together manually every 2 weeks to breed – to ensure that the changes that occurred in the elderly populations were truly down to evolved longevity. To sort male and female vial-housed flies from each other before setting up their blind dates, Rose knocked out the insects with CO2. Chippindale realised that these other ‘control’ populations had inadvertently been performing an evolutionary experiment of their own for the last four decades. They had been naturally selected to withstand the effects of CO2 and oxygen deprivation, which was exactly what Xiao and Robertson were curious about. Chippindale also had alternative populations of flies that had simply been allowed to live naturally with no interference, for comparison with the CO2-anaesthetised populations. ‘We decided it would be fun to see if the different kinds of populations had evolved to have different responses to anoxia’, says Chippindale.Faced with the immense task of screening almost 2000 flies – some from the populations that had been knocked out for almost four decades and others from the populations that had never had a whiff of CO2 – Xiao designed and built an arena that would allow him, Kaylen Brzezinski and Niki Bayat Fard to keep track of up to 128 flies simultaneously. Ten seconds after delivering a puff of CO2 to the fruit flies, Xiao and Brzezinski saw the animals have a mini seizure before collapsing in a coma. However, the fruit flies from the populations that had been treated with CO2 for decades recovered much faster; they began waking within ∼4 min, whereas the insects that had never been anaesthetised showed no sign of recovery for 7–8 min. Investigating further, the team noticed that females from the CO2-treated populations were back on their feet 30% faster than males from the same populations. And when Bayat checked how the flies fared when knocked out with an alternative anaesthetic – nitrogen – the evolved populations recovered even faster, beginning to come to about 3 min after inhaling the gas.Rose and Chippindale's accidental evolutionary experiment has conveniently provided Xiao and Robertson with an ideal ‘animal of choice’ in which to investigate how insects and other animals withstand the effects of plummeting oxygen levels. And Xiao is optimistic that he has already identified one gene that could help. ‘We have reported that the classic eye colour gene white in Drosophila speeds up the recovery from nitrogen anoxia’, Xiao explains and he is keen to discover whether the same gene contributes to the CO2 resilience of Chippindale and Rose's unintentionally evolved fruit flies.

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 score0.004
Threshold uncertainty score0.015

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 studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.014
GPT teacher head0.256
Teacher spread0.242 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

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