Plasma obtained following murine hindlimb ischemic conditioning protects against oxidative stress in zebrafish models through activation of nrf2a and downregulation of duox
Bibliographic record
Abstract
Ischemia/reperfusion of organ systems in trauma patients with resuscitated hemorrhagic shock (HSR) contributes to tissue injury and organ dysfunction. Previous studies using a murine model of HSR showed that remote ischemic preconditioning (RIC) protected against organ injury and that the plasma was able to prevent neutrophil migration in a zebrafish tailfin-cut inflammation model. In this study, we hypothesized that RIC plasma inhibits neutrophil function through a decrease in reactive oxygen species (ROS) production via the upregulation of the transcription factor Nrf2 and downstream antioxidative genes. Plasma from mice subjected to RIC (4 cycles of 5-min hindlimb ischemia/reperfusion) was microinjected into zebrafish. The results show that RIC plasma caused a reduction of ROS generation in response to tail injury. In addition, RIC plasma protected the fish larvae in the survival studies when exposed to either H2O2 or LPS. Oxidative stress PCR Array showed that RIC plasma treatment led to upregulation of antioxidative related genes including hsp70, hmox1a, nqo1 as well as downregulation of duox, the producer of H2O2. To explore the role of nrf2 in RIC, RIC plasma from Nrf2 KO mice were injected to the zebrafish and showed no inhibitory effect on neutrophil migration. Moreover, knockdown of nrf2a attenuated the anti-inflammatory and protective effect of RIC plasma. The downregulation of duox and upregulation of hmox1a were confirmed to require the activation of nrf2a. Therefore, we show that the protective effect of RIC may be related to the elaboration of humoral factors which counter injury-induced ROS generation in a nrf2-dependent fashion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".