Peritoneal Dialysis Catheter Increases Leukocyte Recruitment in the Mouse Parietal Peritoneum Microcirculation and Causes Fibrosis
Bibliographic record
Abstract
UNLABELLED: ♦ BACKGROUND: The objective of this study was to examine the effects of a conventional dialysis solution and peritoneal catheter on leukocyte-endothelial cell interactions in the microcirculation of the parietal peritoneum in a subacute peritoneal dialysis (PD) mouse model. ♦ METHODS: An intraperitoneal (IP) catheter with a subcutaneous injection port was implanted into mice and, after a 2-week healing period, the animals were injected daily for 6 weeks with a 2.5% dextrose solution. Intravital microscopy (IVM) of the parietal peritoneum microcirculation was performed 4 hours after the last injection of the dialysis solution. Leukocyte-endothelial cell interactions were quantified and compared with catheterized controls without dialysis treatment and naïve mice. ♦ RESULTS: The number of rolling and extravascular leukocytes along with peritoneal fibrosis and neovascularization were significantly increased in the catheterized animals compared with naïve mice but did not significantly differ between the 2 groups of catheterized animals with sham injections or dialysis solution treatment. ♦ CONCLUSION: The peritoneal catheter implant increased leukocyte rolling and extravasation, peritoneal fibrosis and vascularization in the parietal peritoneum independently from the dialysis solution treatment.
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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) | 0.000 | 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".