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Record W2954345736 · doi:10.1038/s41467-019-10732-w

A neurotoxin that specifically targets Anopheles mosquitoes

2019· article· en· W2954345736 on OpenAlexfundno aff
Estefanía Contreras, Geoffrey Masuyer, Nadia Qureshi, Swati Chawla, Harpal Dhillon, Han Lim Lee, Jianwu Chen, Pål Stenmark, Sarjeet S. Gill

Bibliographic record

VenueNature Communications · 2019
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesUniversity of California, RiversideDivision of Agriculture and Natural Resources, University of CaliforniaNational Institutes of HealthU.S. Department of Health and Human ServicesVetenskapsrådetEuropean Synchrotron Radiation FacilityCancer Research SocietyCenters for Disease Control and PreventionCancerfonden
KeywordsBiologyNeurotoxinAnophelesMalariaVirologyComputational biologyImmunologyBiochemistry

Abstract

fetched live from OpenAlex

Clostridial neurotoxins, including tetanus and botulinum neurotoxins, generally target vertebrates. We show here that this family of toxins has a much broader host spectrum, by identifying PMP1, a clostridial-like neurotoxin that selectively targets anopheline mosquitoes. Isolation of PMP1 from Paraclostridium bifermentans strains collected in anopheline endemic areas on two continents indicates it is widely distributed. The toxin likely evolved from an ancestral form that targets the nervous system of similar organisms, using a common mechanism that disrupts SNARE-mediated exocytosis. It cleaves the mosquito syntaxin and employs a unique receptor recognition strategy. Our research has an important impact on the study of the evolution of clostridial neurotoxins and provides the basis for the use of P. bifermentans strains and PMP1 as innovative, environmentally friendly approaches to reduce malaria through anopheline control.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.852

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 science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.028
GPT teacher head0.295
Teacher spread0.267 · 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 designNot applicable
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

Citations70
Published2019
Admission routes1
Has abstractyes

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