Editorial: Mechanisms of Ischemia-Reperfusion Injury in Animal Models and Clinical Conditions: Current Concepts of Pharmacological Strategies
Bibliographic record
Abstract
Concepts of Pharmacological StrategiesIschemia-reperfusion (IR) injury is defined as the paradoxical worsening of cellular dysfunction and death following the restoration of blood flow to previously ischaemic tissues.The restorations of blood flow are essential to salvage ischaemic tissues.However, reperfusion itself causes further damage contributing to reversible and irreversible changes in tissue viability and organ function, the basic pathophysiology of IR injury, especially oxidative stress, and cell death mechanism.When the blood supply is re-established, local inflammation and oxidative stress production increase, leading to secondary injury.Cell damage induced by prolonged IR injury may lead to apoptosis, autophagy, necrosis, and necroptosis.It occurs in a wide range of organs system, including the heart, lung, kidney, and brain.It may involve not only the ischaemic organ itself but may also induce systemic damage to distant organs, potentially leading to multi-system organ failure, as different animal models have shown.Similar responses are seen in clinical patients exposed to acute and chronic IR, but the intensity of the physiological response would determine the activated cellular mechanisms.However, short-term and longlasting effects are still unclear.Pharmacological strategies have been proven to be reproducible in preclinical studies across a range of studies with in vitro and ex vivo experimental models.However, novel pharmacological approaches should be further tested in vitro studies as referred to in the articles published in this Research Topic (Flores-Vegara et al., and Chi et al.).This type of approach allows defining the pathophysiological mechanisms and a design towards a more precise clinical trial as developed by translational medicine.Regarding tissue engineering in hypoxic conditions, described by Zamorano et al., this technique offers a promising toolset to tackle ischemia-reperfusion injuries.It devises tissue-mimetics by using the following principles: 1) the unique therapeutic features of stem cells, i.e., self-renewal, differentiability, anti-inflammatory, and immunosuppressants effects; 2) directed growth factors to drive cell growth and development; 3) functional biomaterials, to provide defined microarchitecture for cell-cell interactions; 4) bioprocess design tools to emulate the macroscopic environment that interacts with tissues.This strategy allows cell therapeutics to
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.011 | 0.017 |
| Insufficient payload (model declined to judge) | 0.016 | 0.016 |
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".