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Record W2040765416 · doi:10.1139/y2012-114

Protective effect of <i>C5</i> shRNA on myocardial ischemia–reperfusion injury in rats

2012· article· en· W2040765416 on OpenAlexvenueno aff
Kai Tang, Su‐Hua Wu, Lijuan Liu, Cheng Lingli

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicComplement system in diseases
Canadian institutionsnot available
Fundersnot available
KeywordsSmall hairpin RNAReperfusion injuryProtein kinase BPharmacologyMedicineIschemiaComplement systemPhosphorylationIschemic preconditioningInternal medicineChemistryEndocrinologyImmunologyApoptosisBiochemistryImmune systemGene knockdown

Abstract

fetched live from OpenAlex

Myocardial ischemia and reperfusion (MI/R) injury is associated with activation of the complement system. Complement activation generates a series of bioactive substances, including early (C3a, C3b) and terminal (C5a, C5b-9) components. The terminal complement components are key mediators of MI/R injury. This study investigated whether C5 shRNA preconditioning has protective effects following MI/R injury and its potential mechanism. Rats were injected with C5 shRNA 2 days before induction of ischemia. The effects of C5 shRNA were evaluated by the assessment of heart function, infarct size, histopathology, inflammatory cytokine levels, and the plasma level of troponin T. Akt phosphorylation was assessed by immunoblotting. C5 shRNA efficiently inhibited C5 expression both in vitro and in vivo, and attenuated MI/R injury. C5 shRNA preconditioning significantly decreased the level of troponin T and the production of pro-inflammatory cytokine. The infarct size was decreased by 40% in C5 shRNA treated rats. Akt phosphorylation increased after C5 shRNA preconditioning. These results suggest that C5 shRNA preconditioning in rats has protective effects following MI/R injury; this may be partly effected by mediating the activation of the PI3K pathway and by phosphorylation of Akt.

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 categoriesInsufficient payload (model declined to judge)
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 score0.016
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.008
GPT teacher head0.269
Teacher spread0.261 · 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.

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

Citations6
Published2012
Admission routes1
Has abstractyes

Explore more

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