The Effect of Erythropoietin on Microcirculation Perfusion and Tissue Bioenergetics of the Small Intestine in a Hemorrhagic Shock and Resuscitation Rat Model
Bibliographic record
Abstract
BACKGROUND: Erythropoietin (EPO) can exert acute hemodynamic and anti-inflammatory effects in addition to erythropoiesis. We tested the hypothesis that EPO given at resuscitation with saline will improve capillary perfusion and tissue oxygenation in the gut using a hemorrhagic shock model. METHODS: Sprague-Dawley rats were bled 30 mL/kg to maintain a mean arterial blood pressure of 40 mm Hg for 50 minutes and then randomized to one of four resuscitation groups (n = 6 per group): blood, blood + recombinant human EPO (rHuEPO), saline, and saline + rHuEPO. Intravenous rHuEPO (1,000 U/kg) was given at the start of resuscitation. Intravital microscopy was used to measure perfused capillary density, flow motion of red blood cell (RBC), and tissue NADH fluorescence 60 minutes after resuscitation. Venous oxygenation saturation (Svo2) was also measured in a second experiment. RESULTS: In the blood +/- rHuEPO resuscitation group, the perfused capillary density, RBC flow motion scores, and NADH fluorescence returned to near normal values. The saline + rHuEPO group compared with the saline group demonstrated an increased RBC flow motion score (2.32 vs. 1.60; p < 0.01); however, the perfused capillary density was not significantly increased (23.03 Cap/mm vs. 21.61 Cap/mm; p = 0.40). The saline + rHuEPO group also demonstrated statistically significant lower NADH fluorescence than the saline group after shock following resuscitation (110% +/- 3.64% vs. 122% +/- 4.26%; p < 0.05) suggesting decreased tissue dysoxia. The Svo2 in the saline + rHuEPO group was higher when compared with the saline group (45% vs. 38% by continuous oximetry; 38% vs. 29% by co-oximetry; p < 0.05). CONCLUSION: Our results suggest that the addition of rHuEPO at the time of saline resuscitation may have beneficial effects in hemorrhagic shock by improving tissue perfusion and decreasing dysoxia in the gut.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".