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Record W2598700579 · doi:10.1002/jez.2067

Insect Immunity Varies Idiosyncratically During Overwintering

2017· article· en· W2598700579 on OpenAlexafffund
Laura V. Ferguson, Brent J. Sinclair

Bibliographic record

VenueJournal of Experimental Zoology Part A Ecological and Integrative Physiology · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicInvertebrate Immune Response Mechanisms
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOverwinteringBiologyCurculioInsectEcologyZoologyLarvaWeevilTemperate climateImmune systemCurculionidaeBotanyImmunology

Abstract

fetched live from OpenAlex

Overwintering insects face multiple stressors, including pathogen and parasite pressures that shift with seasons. However, we know little of how the insect immune system fluctuates with season, particularly in the overwintering period. To understand how immune activity changes across autumn, winter, and spring, we tracked immune activity of three temperate insects that overwinter as larvae: a weevil (Curculio sp., Coleoptera), gallfly (Eurosta solidaginis, Diptera), and larvae of the lepidopteran Pyrrharctia isabella. We measured baseline circulating hemocyte numbers, phenoloxidase activity, and humoral antimicrobial activity, as well as survival of fungal infection and melanization response at 12°C and 25°C to capture any potential plasticity in thermal performance. In Curculio sp. and E. solidaginis, hemocyte concentrations remained unchanged across seasons and antimicrobial activity against Gram-positive bacteria was lowest in autumn; however, Curculio sp. were less likely to survive fungal infection in autumn, whereas E. solidaginis were less likely to survive infection during the winter. Furthermore, hemocyte concentrations and antimicrobial activity decreased in P. isabella overwintering beneath snow cover. Overall, seasonal changes in activity were largely species dependent, thus it may be difficult to create generalizable predictions about the effects of a changing climate on seasonal immune activity in insects. However, we suggest that the relationship between the response to multiple stressors (e.g., cold and pathogens) drives changes in immune activity, and that understanding the physiology underlying these relationships will inform our predictions of the effects of environmental change on insect overwintering success.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.125
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.025
GPT teacher head0.274
Teacher spread0.249 · 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 teacher head, not a consensus.

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

Citations41
Published2017
Admission routes2
Has abstractyes

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