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Record W3178432842 · doi:10.1098/rspb.2021.0731

The cibarial pump of the xylem-feeding froghopper<i>Philaenus spumarius</i>produces negative pressures exceeding 1 MPa

2021· article· en· W3178432842 on OpenAlexafffund
Elisabeth Anne Bergman, Emma L. Green, Philip G. D. Matthews

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytoplasmas and Hemiptera pathogens
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsXylemBiologyBotany

Abstract

fetched live from OpenAlex

The xylem sap of vascular plants is an unlikely source of nutrition, being both nutrient poor and held under tensions (negative pressures) that can exceed 1 MPa. But some insects feed on xylem sap exclusively, extracting copious quantities using a muscular cibarial pump. However, neither the strength of the insect's suction, nor the direct energetic cost of xylem ingestion, have ever been quantified. Philaenus spumarius froghoppers were used to address these gaps in our knowledge. Micro-CT scans of its cibarium and measurements of cibarial muscle sarcomere length revealed that P. spumarius can generate a maximum tension of 1.3 ± 0.2 MPa within its cibarium. The energetic cost of xylem extraction was quantified using respirometry to measure the metabolic rate (MR) of P. spumarius while they fed on hydroponically grown legumes, while xylem sap excretion rate and cibarial pumping frequency were simultaneously recorded. Increasing the plants' xylem tensions up to 1.1 MPa by exposing their roots to polyethylene glycol did not reduce the insects’ rate of xylem excretion, but significantly increased both MR and pumping frequency. We conclude that P. spumarius can gain energy feeding on xylem sap containing previously reported energy densities and at xylem tensions up to their maximum suction capacity.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.118
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.024
GPT teacher head0.217
Teacher spread0.193 · 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

Citations10
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Royal Society B Biological SciencesSame topicPhytoplasmas and Hemiptera pathogensFrench-language works237,207