Pre-arrest doxycycline protects donation after circulatory death kidneys
Bibliographic record
Abstract
Kidney injury during donation after circulatory determination of death (DCDD) includes warm ischemic (WI) injury from around the time of asystole, and cold ischemic (CI) injury during cold preservation. We have previously shown that Matrix Metalloproteinases (MMPs) are involved in CI injury and that Doxycycline (Doxy), an antibiotic and known MMP inhibitor, protects the transplant kidney during CI. The purpose of our study was to determine if Doxy given before asystole can also prevent injury during WI. A rat model of DCDD was used, including Control, Preemptive Doxy (45 mg/kg iv), and Preemptive and Perfusion (100 microM) Doxy groups. Thirty minutes after asystole, both kidneys were removed. The left kidney was perfused at 4 °C for 22 h, whereas the right was used to establish the degree of warm ischemic injury prior to cold preservation. MMP-2 in the perfusate was significantly reduced in both treatment groups [Control 43.7 ± 7.2 arbitrary units, versus Preemptive Doxy group 23.2 ± 5.5 (p = 0.03), and 'Preemptive and Perfusion' group 18.0 ± 5.6 (p = 0.02)]. Reductions in NGAL, LDH, and MMP-9 were also seen. Electron microscopy showed a marked reduction in mitochondrial injury scores in the treatment groups. Pre-arrest Doxy was associated with a reduction in injury markers and morphologic changes. Doxy may be a simple and safe means of protecting transplant kidneys from both WI and CI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 |
| 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".