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Record W2128697298 · doi:10.3390/ijms12031991

Effect of Ligusticum wallichii Aqueous Extract on Oxidative Injury and Immunity Activity in Myocardial Ischemic Reperfusion Rats

2011· article· en· W2128697298 on OpenAlexaff
Ma Jiangwei

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2011
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacological Effects of Natural Compounds
Canadian institutionsJuvenile Diabetes Research Foundation
Fundersnot available
KeywordsMyocardial Reperfusion InjuryPharmacologyTraditional medicineImmunityReperfusion injuryAqueous extractOxidative phosphorylationOxidative stressIschemic reperfusion injuryMedicineChemistryIschemiaCardiologyImmune systemImmunologyInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

We investigated the efficacy of Ligusticum wallichi aqueous extract (LWE) for myocardial protection against ischemia-reperfusion injury. Rats were fed for five weeks with either a control diet (sham and ischemia reperfusion (IR) model control groups) or a diet mixed with 0.2%, 0.4% or 0.6% Ligusticum wallichi extract. At the end of the five week period, hearts were excised and subjected to global ischemia for 30 min followed by reperfusion for 2 h. The hearts were compared for indices of oxidative stress and immunity activities. Administration of Ligusticum wallichi extract significantly decreased serum TNF-α, IL-6, IL-8, NO, MIP-1α, CRP and myocardium MDA levels, and serum CK, LDH and AST activities, and increased myocardium Na(+)-K(+)-ATPase, Ca(2+)-Mg(2+)-ATPase, NOS, SOD, CAT, GSH-Px and TAOC activities. The results indicate that Ligusticum wallichii extract treatment can enhance myocardial antioxidant status and improve the immunity profile in ischemic-reperfusion 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.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.044
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 science0.0010.000
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 head0.060
GPT teacher head0.429
Teacher spread0.369 · 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

Citations25
Published2011
Admission routes1
Has abstractyes

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