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Record W420535265 · doi:10.1016/j.jab.2015.04.004

The effect of different doses of atropine on gastric myoelectrical activity in fasting experimental pigs

2015· article· en· W420535265 on OpenAlexfundno aff
Jan Bureš, J Kvĕtina, Ilja Tachecí, Michal Pavlík, Martin Kuneš, Stanislav Rejchrt, Kamil Kuča, Marcela Kopáčová

Bibliographic record

VenueJournal of Applied Biomedicine · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsnot available
FundersMinisterstvo Zdravotnictví Ceské RepublikyValeant Pharmaceuticals International
KeywordsAtropineMedicineBasal (medicine)AnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

Electrogastrography (EGG) is a non-invasive method for the assessment of gastric myoelectrical activity. Porcine EGG is comparable with human one. There are no data on the impact of moderate to high doses of atropine on EGG, neither in humans nor experimental pigs. The purpose of this study was to evaluate the effect of different doses of atropine on EGG in experimental pigs.Six fasting pigs entered the study three times in a random order. The baseline EGG recording lasted 20 min, followed by a 105-min EGG trial recording. Intramuscular atropine 1.5 mg (part 1), 3.0 mg (part 2) and 4.5 mg (part 3) was administrated after the baseline EGG.Atropine doses of 1.5 and 3.0 mg revealed a similar pattern in the EGG power course. After an initial increase (at the first 15-min interval), the areas of amplitudes decreased back to values comparable with basal levels and subsequently increased significantly again to the maximum at 105 min. The EGG power was quite different after the administration of 4.5 mg of atropine. Areas of amplitudes decreased gradually to the minimum values at 105 min after atropine administration.In conclusion, different dose-dependent changes in the EGG pattern were found after moderate to high doses of atropine.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.181

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 science0.0000.000
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 head0.012
GPT teacher head0.266
Teacher spread0.254 · 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 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

Citations7
Published2015
Admission routes1
Has abstractyes

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