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Record W4318539440 · doi:10.1139/cjpp-2022-0498

Colorectal and bladder prokinetic activity of [Lys<sup>5</sup>, MeLeu<sup>9</sup>, Nle<sup>10</sup>]-NKA<sub>(4–10)</sub> after intranasal or sublingual delivery in dogs

2023· article· en· W4318539440 on OpenAlexvenueno aff
N.M.J. Rupniak, Mary A. Katofiasc, Jung‐Eun Bae, Karl B. Thor, Lesley Marson

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2023
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvanced Drug Delivery Systems
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryNasal administrationPharmacologyMedicine

Abstract

fetched live from OpenAlex

, was examined using prototype formulations in dogs. In anesthetized animals, administration of 100 or 300 µg/kg IN or 2.0-6.7 mg/kg SL increased colorectal peak pressure and area under the curve. Peak bladder pressure was also increased at the same doses, and this was accompanied by highly efficient voiding at normal physiological bladder pressure. The onset of these effects was rapid (≤2.5 min), and the primary contractions lasted ∼25 min, returning to baseline in <60 min. Slight hypotension lasting a few minutes and causing <10% change from baseline was detected after higher doses and was statistically significant after only 100 µg/kg IN. In conscious dogs, there was a dose-related increase in voiding responses and reduction in the latency to urinate and defecate after 300 and 1000 µg/kg IN; emesis was also observed at these doses. SL administration of 6.7 mg/kg induced urination within 10 min, but not defecation or emesis. These findings support the feasibility of developing a convenient dosage form of small peptide NK2 receptor agonists as on-demand defecation or urination therapies.

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: Bench or experimental · Consensus signal: Bench or experimental
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 head0.040
GPT teacher head0.339
Teacher spread0.299 · 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 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

Citations2
Published2023
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Physiology and PharmacologySame topicAdvanced Drug Delivery SystemsFrench-language works237,207