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Record W4407865172 · doi:10.1017/s0031182025000265

Carry-over non-consumptive effects: impact of parasite exposure during larval stage on adult phenotype

2025· article· en· W4407865172 on OpenAlexaff
Caroline Liang, Lien T. Luong

Bibliographic record

VenueParasitology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBiologyLarvaParasite hostingPhenotypeZoologyStage (stratigraphy)EcologyGeneticsGene

Abstract

fetched live from OpenAlex

Abstract The presence of parasites can elicit host responses even in the absence of infection. These risk-induced trait responses include altered host behaviours, morphology, and/or physiology, which can trade off with other fitness-related traits. Studies of predator-induced non-consumptive effects (NCEs) have demonstrated that exposure at one life stage can lead to NCEs in the next stage, but no studies to date have examined such an effect of parasite exposure. Numerous NCEs have been demonstrated in larval, pupal and adult stages of Drosophila nigrospiracula exposed to ectoparasitic mites ( Macrocheles subbadius ). Here we experimentally investigated whether parasite-induced NCEs carry over into subsequent developmental stages (i.e. interstadial effects). We tested the prediction that when flies are exposed to mites during the larval and pupal stages, the subsequent adult stage will exhibit decreased body mass, fecundity and longevity. However, we did not detect downstream effects of parasite exposure on adult body mass, fecundity or longevity. The probability of survival and lifetime fecundity were comparable for previously exposed and unexposed groups. We suggest that when parasite exposure is confined to one developmental stage, and the risk of infection is removed in the subsequent stage, the long-term effects of parasite exposure dissipate. The potential to recover from the interim costs of parasite exposure may provide an added benefit to host dispersal.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.004
GPT teacher head0.292
Teacher spread0.288 · 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 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
Published2025
Admission routes1
Has abstractyes

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