Remote preconditioning provides potent cardioprotection via PI3K/Akt activation and is associated with nuclear accumulation of β-catenin
Bibliographic record
Abstract
rIPC [remote IPC (ischaemic preconditioning)] has been shown to invoke potent myocardial protection in animal studies and recent clinical trials. Although the important role of PI3K (phosphoinositide 3-kinase)/Akt activation in the cardioprotection afforded by local IPC is well described, our understanding of the intracellular signalling of rIPC remains incomplete. We therefore examined the hypothesis that the myocardial protection afforded by rIPC is mediated via the PI3K/Akt/GSK3β (glycogen synthase kinase 3β) signalling pathway, activation of which is associated with nuclear accumulation of β-catenin. rIPC was induced in mice using four cycles of 5 min of ischaemia and 5 min of reperfusion of the hindlimb using a torniquet. This led to reduced infarct size (19 ± 4% in rIPC compared with 39 ± 7% in sham; P<0.05), improved functional recovery and reduced apoptosis after global I/R (ischaemia/reperfusion) injury using a Langendorff-perfused mouse heart model. These effects were reversed by pre-treatment with an inhibitor of PI3K activity. Furthermore, Western blot analysis demonstrated that, compared with control, rIPC was associated with activation of the PI3K/Akt signalling pathway, resulting in phosphorylation and inactivation of GSK3β, accumulation of β-catenin in the cytosol and its translocation to the nucleus. Finally, rIPC increased the expression of β-catenin target genes involved in cell-survival signalling, including E-cadherin and PPARδ (peroxisome-proliferator-activated receptor δ). In conclusion, we show for the first time that the myocardial protection afforded by rIPC is mediated via the PI3K/Akt/GSK3β signalling pathway, activation of which is associated with nuclear accumulation of β-catenin and the up-regulation of its downstream targets E-cadherin and PPARδ involved in cell survival.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".