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Record W4378374084 · doi:10.1139/cjpp-2023-0078

Vitamins E and A increase the passing of the P-gp substrate ivermectin into the brain in mice

2023· article· en· W4378374084 on OpenAlexvenueno aff
Bünyamin Traş, Kamil Üney, Tuğba Melike Parlak, Öznur Tufan

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2023
Typearticle
Languageen
FieldMedicine
TopicPharmacological Effects and Toxicity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIvermectinSubstrate (aquarium)ChemistryPharmacologyBiologyEndocrinologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

This study aimed to determine the effect of administration of oral vitamins A and E at different doses on plasma and brain concentrations of ivermectin in mice. The study was carried out on 174 Swiss Albino male mice aged 8–10 weeks. After leaving six mice for method validation, the remaining mice were randomly divided into seven groups with equal numbers of animals. Mice received ivermectin (0.2 mg/kg, subcutaneous) alone and in combination with low (vitamin A: 4000 IU/kg; vitamin E: 35 mg/kg) and high (vitamin A: 30 000 IU/kg; vitamin E: 500 mg/kg) oral doses of vitamins A and E. The plasma and brain concentrations of ivermectin were measured using high-performance liquid chromatography-fluorescence detector. We determined that high doses of vitamins A and E and their combinations increased the passing ratio of ivermectin into the brain significantly. The high-dose vitamin E and the combination of high-concentration vitamins E and A significantly increased the plasma concentration of ivermectin ( P < 0.05). The high-dose vitamins E and A and their high-dose combination increased the brain concentration of ivermectin by 3, 2, and 2.7 times, respectively. This research is the first in vivo study to determine the interaction between P-gp substrates and vitamins E and A.

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 score0.005

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 integrity0.0000.001
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 head0.018
GPT teacher head0.300
Teacher spread0.281 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Physiology and PharmacologySame topicPharmacological Effects and Toxicity StudiesFrench-language works237,207