Immune Modulation as a Key Mechanism for the Protective Effects of Remote Ischemic Conditioning After Stroke
Bibliographic record
Abstract
Remote ischemic conditioning (RIC), which involves a series of short cycles of ischemia in an organ remote to the brain (typically the limbs), has been shown to protect the ischemic penumbra after stroke and reduce ischemia/reperfusion (IR) injury. Although the exact mechanism by which this protective signal is transferred from the remote site to the brain remains unclear, preclinical studies suggest that the mechanisms of RIC involve a combination of circulating humoral factors and neuronal signals. An improved understanding of these mechanisms will facilitate translation to more effective treatment strategies in clinical settings. In this review, we will discuss potential protective mechanisms in the brain and cerebral vasculature associated with RIC. We will discuss a putative role of the immune system and circulating mediators of inflammation in these protective processes, including the expression of pro-and anti-inflammatory genes in peripheral immune cells that may influence the outcome. We will also review the potential role of extracellular vesicles (EVs), biological vectors capable of delivering cell-specific cargo such as proteins and miRNAs to cells, in modulating the protective effects of RIC in the brain and vasculature.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".