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Record W3195698145 · doi:10.1016/j.biopha.2021.112077

Allicin ameliorates renal ischemia/reperfusion injury via inhibition of oxidative stress and inflammation in rats

2021· article· en· W3195698145 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBiomedicine & Pharmacotherapy · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGarlic and Onion Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAllicinOxidative stressInflammationPharmacologyRenal ischemiaIschemiaReperfusion injuryKidneyRenal functionApoptosisMedicineAntioxidantChemistryInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Allicin has been reported to play a biological role in human pathophysiological processes via interaction with numerous signaling pathways and gene expression alteration. The purpose of the present study was to evaluate the protective effects of allicin against renal ischemia/reperfusion injury (RIRI) in rats. In the present study, the RIRI model with 45-min ischemia and 22-h reperfusion in rats was generated and allicin was used as the intervention. Changes in renal tissue pathomorphology, renal function, oxidative stress, inflammatory response and apoptosis were evaluated in the RIRI model in rats. Compared with those in the RIRI group, renal function, renal pathological injury, and anti-inflammatory and antioxidant properties were markedly improved in the RIRI+allicin group. Thus, our research suggested that allicin exerted its protective effect against ischemia/reperfusion-induced renal injury by regulating apoptosis, oxidative stress and inflammatory response in rats.

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.

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 score0.131
Threshold uncertainty score0.352

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 head0.016
GPT teacher head0.276
Teacher spread0.260 · 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