MétaCan
Menu
Back to cohort
Record W4296047718 · doi:10.3389/fnut.2022.1003627

Antarctic krill (Euphausia superba) oil modulatory effects on ethanol-induced acute injury of the gastric mucosa in rats

2022· article· en· W4296047718 on OpenAlexaff
Luqiang Huang, Wenxin Wu, Linshan Huang, Jiaze Zhong, Lei Chen, Meiying Wang, Huibin Chen

Bibliographic record

VenueFrontiers in Nutrition · 2022
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversity of Guelph
FundersFujian Normal UniversityDepartment of Education, Fujian ProvinceNational Natural Science Foundation of China
KeywordsEicosapentaenoic acidMalondialdehydeSuperoxide dismutaseChemistryDocosahexaenoic acidNitric oxideOxidative stressAntioxidantMyeloperoxidasePharmacologyBiochemistryIn vivoFood scienceInternal medicineMedicineFatty acidPolyunsaturated fatty acidInflammationBiologyBiotechnology

Abstract

fetched live from OpenAlex

Antarctic krill oil (KO) prepared using supercritical carbon dioxide extraction and characterized using gas chromatography-mass spectrometry was used to investigate its preventive effect on ethanol-induced gastric tissue damage in a rat model in vivo . KO characterization showed that 74.96% of the unsaturated fatty acids consist of oleic acid, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA). Rats pre-treated with KO (100, 200, and 500 mg/kg) showed mitigated oxidative stress through enhanced antioxidant enzyme superoxide dismutase (SOD) and reducing enzymes malondialdehyde (MDA) and myeloperoxidase (MPO) in gastric mucosal injury induced by ethanol. Additionally, the secretion of pro-inflammatory cytokines (TNF-α, IL-6, and IL-1β), the expression of the IκBα/NF-κB signaling pathway, and nitric oxide (NO) production was suppressed. The results also demonstrated a significant decrease in histological injury and hemorrhage scores in a dose-dependent manner in the KO range. Therefore, KO has potential as a food supplement to alleviate ethanol-induced acute gastric mucosal injury.

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)0.001
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 score0.187
Threshold uncertainty score0.635

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.269
Teacher spread0.258 · 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

Citations18
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in NutritionSame topicFatty Acid Research and HealthFrench-language works237,207