MétaCan
Menu
Back to cohort
Record W2168395624 · doi:10.1242/jeb.02083

Distribution, activity and evidence for the release of an anti-diuretic peptide in the kissing bug <i>Rhodnius prolixus</i>

2006· article· en· W2168395624 on OpenAlexaff
Jean‐Paul Paluzzi, Ian Orchard

Bibliographic record

VenueJournal of Experimental Biology · 2006
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRhodnius prolixusDiureticDiuresisMalpighian tubule systemEndocrinologyInternal medicineBiologyInsectNeuropeptideHormoneFMRFamideEndogenyMidgutReceptorKidneyMedicine

Abstract

fetched live from OpenAlex

In the haematophagous insect Rhodnius prolixus, diuresis is accomplished through the combined actions of peptidergic diuretic hormones and 5-HT released from neurohaemal sites on the abdominal nerves. Preliminary work on anti-diuresis in this blood-feeder, previously believed to occur through a decrease in the levels of the diuretic factors, indicates that an anti-diuretic hormone, with properties similar to CAP2b (pELYAFPRVamide; recently renamed Mas-CAPA-1), might also be present in R. prolixus. Here, we present evidence from immunohistochemical analysis that suggests a PRXamide-like neuropeptide may be released from the abdominal neurohaemal sites beginning 3-4 h following feeding; a time that coincides with the cessation of diuresis. We also show evidence for an endogenous factor, isolated from the central nervous system using reversed-phase high performance liquid chromatography, which mimics the effects of Mas-CAPA-1. Specifically, this endogenous anti-diuretic factor inhibits rates of 5-HT-stimulated secretion in a dose-dependent manner and elevates intracellular cGMP levels of Malpighian tubules stimulated with 5-HT.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.059
GPT teacher head0.377
Teacher spread0.317 · 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 source (direct Gemma or distilled Codex), 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

Citations73
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Experimental BiologySame topicNeurobiology and Insect Physiology ResearchFrench-language works237,207