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Record W4406947950 · doi:10.1126/sciadv.adq8771

Parasitoid wasp venoms degrade <i>Drosophila</i> imaginal discs for successful parasitism

2025· article· en· W4406947950 on OpenAlexfundno aff
Takumi Kamiyama, Yuko Shimada‐Niwa, Hitoha Mori, Naoki Tani, Hitomi Takemata-Kawabata, Mitsuki Fujii, Akira Takasu, Minami Katayama, Takayoshi Kuwabara, Kazuki Seike, Noriko Matsuda–Imai, Toshiya Senda, Susumu Katsuma, Akira Nakamura, Ryusuke Niwa

Bibliographic record

VenueScience Advances · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect symbiosis and bacterial influences
Canadian institutionsnot available
FundersNational Institute for Basic BiologyInstitute of GeneticsJapan Society for the Promotion of ScienceNational Institutes of HealthOhsumi Frontier Science Foundation
KeywordsParasitoidBiologyParasitismVenomParasitoid waspInsectHost (biology)LarvaZoologyDrosophila (subgenus)MetamorphosisDrosophila melanogasterCell biologyEcologyGeneticsGene

Abstract

fetched live from OpenAlex

Parasitoid wasps, one of the most diverse and species-rich animal groups on Earth, produce venoms that manipulate host development and physiology to exploit resources. However, mechanisms of actions of these venoms remain poorly understood. Here, we discovered that the endoparasitoid wasp, Asobara japonica , induces apoptosis, autophagy, and mitotic arrest in the adult tissue precursors of its host Drosophila larvae. We termed this phenomenon imaginal disc degradation (IDD). A multi-omics approach facilitated identification of two venom proteins of A. japonica necessary for IDD, which is critical for parasitism success. Our study highlights a venom-mediated hijacking strategy of the parasitoid wasp that allows the host larvae to grow, but ultimately prevents their metamorphosis.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.274
Teacher spread0.265 · 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 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

Citations10
Published2025
Admission routes1
Has abstractyes

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