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Record W4281673190 · doi:10.1242/jeb.244097

Rapid cold hardening increases axonal Na+/K+-ATPase activity and enhances performance of a visual motion detection circuit in <i>Locusta migratoria</i>

2022· article· en· W4281673190 on OpenAlexafffund
R. Meldrum Robertson, Christopher D. Moyes

Bibliographic record

VenueJournal of Experimental Biology · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNeuroscienceBiologyElectrophysiologyInterneuronAxonLocustBiophysicsHyperpolarization (physics)OuabainInhibitory postsynaptic potentialChemistry

Abstract

fetched live from OpenAlex

Rapid cold hardening (RCH) is a type of phenotypic plasticity that delays the occurrence of chill coma in insects. Chill coma is mediated by a spreading depolarization of neurons and glia in the CNS, triggered by a failure of ion homeostasis. We used biochemical and electrophysiological approaches in the locust, Locusta migratoria, to test the hypothesis that the protection afforded by RCH is mediated by activation of the Na+/K+-ATPase (NKA) in neural tissue. RCH did not affect NKA activity measured in a biochemical assay of homogenized thoracic ganglia. However, RCH hyperpolarized the axon of a visual interneuron (DCMD) and increased the amplitude of an activity-dependent hyperpolarization (ADH) shown previously to be blocked by ouabain. RCH also improved performance of the visual circuitry presynaptic to DCMD to minimize habituation and increase excitability. We conclude that RCH enhances in situ NKA activity in the nervous system but also affects other neuronal properties that promote visual processing in locusts.

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 score0.004

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 head0.027
GPT teacher head0.302
Teacher spread0.275 · 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

Citations14
Published2022
Admission routes2
Has abstractyes

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