Doxycycline Attenuates Renal Injury In A Swine Model Of Neonatal Hypoxia-Reoxygenation
Bibliographic record
Abstract
Acute kidney injury in asphyxiated neonates is common. The renal protective effects of doxycycline, a known matrix metalloproteinase (MMP) inhibitor, have been demonstrated in rat ischemic-reperfusion models of injury. These effects have not been tested in large-animal models designed to reflect true clinical scenarios of neonatal hypoxia-reoxygenation (H-R). Newborn piglets were surgically instrumented for hemodynamic monitoring and subjected to 2 h of hypoxia followed by 4 h of normoxic reoxygenation. Piglets were blindly randomized to receive i.v. saline or doxycycline (3, 10, or 30 mg/kg) 5 min into reoxygenation (n = 7 per group). Sham-operated piglets (n = 5) received no H-R. Renal injury was investigated by histologic examination and measuring serum creatinine, urinary N-acetyl-D-glucosaminidase activity and renal tissue lactate with enzyme-linked immunosorbent assay. Renal tissue oxidative stress (lipid hydroperoxides) and total MMP-2 activity were measured with enzyme-linked immunosorbent assay and gelatin zymography, respectively. Piglets treated with doxycycline had significantly improved cardiac index, systemic arterial pressure, renal artery blood flow, and oxygen delivery, with no difference observed in heart rate compared with controls. The H-R piglets had significantly higher urinary N-acetyl-D-glucosaminidase activity, renal tissue lipid hydroperoxides, lactate, and MMP-2 activity, which were attenuated to varied degrees in a dose-related manner in piglets treated with doxycycline (P = 0.08 to P < 0.05). Serum creatinine and histologic features of H-R were not different among groups. Postresuscitation administration of doxycycline improved renal perfusion, attenuated renal injury, and reduced tissue oxidative stress and MMP-2 activity in a clinically translatable newborn swine model of H-R.
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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 | 0.001 | 0.001 |
| 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".