Erythropoietin Accelerates the Regeneration of Ureteral Function in a Murine Model of Obstructive Uropathy
Bibliographic record
Abstract
PURPOSE: Unilateral ureteral obstruction halts ureteral peristalsis, and may cause pain and lead to infection. Ureteral ability to recover after obstruction removal remains unclear. Erythropoietin has protective effects in nonhematopoietic organs and restores peristalsis in hypocontractile intestinal smooth muscle cells. We investigated the role of erythropoietin in ureteral smooth muscle function and its therapeutic value for unilateral ureteral obstruction. MATERIALS AND METHODS: Unilateral ureteral obstruction was created for 24, 48 and 72 hours in 22 mice per group using a nontraumatic microclip via laparotomy. We determined erythropoietin, erythropoietin receptor and β-common receptor expression in obstructed and unobstructed ureters by reverse transcriptase-polymerase chain reaction and immunohistochemistry. Ten mice per group received 20 IU erythropoietin for 4 days and controls received saline. Hydronephrosis regression after obstruction removal was assessed by ultrasound. Peristalsis was determined microscopically before and after obstruction removal. RESULTS: Erythropoietin, erythropoietin receptor and β-common receptor were expressed in the unobstructed and obstructed ureters of untreated mice. Erythropoietin mRNA was up-regulated in response to obstruction and erythropoietin expression was identified in ureteral smooth muscle. After obstruction removal hydronephrosis and ureteral dysfunction correlated with obstruction duration. Hydronephrosis resolution and ureteral peristalsis restoration were significantly accelerated in erythropoietin treated mice compared to controls. CONCLUSIONS: Erythropoietin treatment significantly promoted functional recovery of the ureter after obstruction removal. Erythropoietin may be a helpful strategy for ureteral motility recovery and hydronephrosis resolution in ureteral obstruction.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".