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Record W1970510383 · doi:10.1007/s12576-013-0288-1

Regulation of gastric motility and blood flow during acute nociceptive stimulation of the paraspinal muscles in urethane-anaesthetised rats

2013· article· en· W1970510383 on OpenAlexafffund
Mathieu Piché, Nobuhiro Watanabe, Harumi Hotta

Bibliographic record

VenueThe Journal of Physiological Sciences · 2013
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersJapan Society for the Promotion of ScienceNatural Sciences and Engineering Research Council of Canada
KeywordsNociceptionMedicineStimulationSalineBlood flowAnesthesiaSpinal cordHypertonic salineStomachMotilityTonicityBlood pressureInternal medicineReceptor

Abstract

fetched live from OpenAlex

The aim of this study was to examine gastric motility and blood flow during nociceptive hypertonic saline injections (HS) in paraspinal muscles of urethane-anaesthetised rats. Gastric pressure was not affected by HS in intact or vagotomised conditions. After cervical spinalisation, it was decreased by injections at T13 or L6 but not T2. Moreover, HS injections at T13 produced greater gastric pressure decreases compared with L6 and T2 and increased gastric sympathetic nerve activity. Blood pressure and gastric blood flow were decreased by T13 injections in spinal cord intact but not spinalised rats. Besides, isotonic saline injections (non-nociceptive) produced non-significant or marginal effects. These results indicate that gastric motility is decreased by nociceptive input from paraspinal muscles in spinalised rats through activation of the gastric sympathetic nerve. Although gastric blood flow was also decreased by nociceptive stimulation at T13 in spinal cord intact rats, these changes seem to depend on blood pressure.

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 score0.002
Threshold uncertainty score0.006

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.277
Teacher spread0.250 · 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

Citations6
Published2013
Admission routes2
Has abstractyes

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