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Record W2677319605 · doi:10.1017/s0031182017000890

State-dependent parasitism by a facultative parasite of fruit flies

2017· article· en· W2677319605 on OpenAlexaff
Lien T. Luong, Taylor Brophy, Emily Stolz, SOLOMON J. CHAN

Bibliographic record

VenueParasitology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFacultativeBiologyMiteParasitismHost (biology)Phenotypic plasticityParasite hostingZoologyEcologyRange (aeronautics)Life history theoryLife history

Abstract

fetched live from OpenAlex

Parasites can evolve phenotypically plastic strategies for transmission such that a single genotype can give rise to a range of phenotypes depending on the environmental condition. State-dependent plasticity in particular can arise from individual differences in the parasite's internal state or the condition of the host. Facultative parasites serve as ideal model systems for investigating state-dependent plasticity because individuals can exhibit two life history strategies (free-living or parasitic) depending on the environment. Here, we experimentally show that the ectoparasitic mite Macrocheles subbadius is more likely to parasitize a fruit fly host if the female mite is mated; furthermore, the propensity to infect increased with the level of starvation experienced by the mite. Host condition also played an important role; hosts infected with moderate mite loads were more likely to gain additional infections in pairwise choice tests than uninfected flies. We also found that mites preferentially infected flies subjected to mechanical injury over uninjured flies. These results suggest that a facultative parasite's propensity to infect a host (i.e. switch from a free-living strategy) depends on both the parasite's internal state and host condition. Parasites often live in highly variable and changing environments, an infection strategy that is plastic is likely to be adaptive.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.252
Threshold uncertainty score0.735

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 head0.009
GPT teacher head0.321
Teacher spread0.311 · 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.

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

Citations14
Published2017
Admission routes1
Has abstractyes

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