Peritoneal dialysis with solutions low in glucose degradation products is associated with improved biocompatibility profile towards peritoneal mesothelial cells
Bibliographic record
Abstract
BACKGROUND: In vitro experiments point to a better biocompatibility profile of new pH-neutral peritoneal dialysis fluids (PDFs) containing low levels of glucose degradation products (GDPs). The present study examines the impact on human peritoneal mesothelial cells (HPMCs) of equilibrated dialysates obtained during dialysis with either conventional or new PDFs. METHODS: Peritoneal dialysate was collected from 17 patients participating in a randomized, controlled, cross-over trial comparing a pH-neutral low-GDP solution (Balance) to a conventional solution (S-PDF). All patients were treated sequentially for 3 months with both PDFs. At the end of each treatment phase, peritoneal effluent was drained after a timed 10 h dwell. Samples of dialysate were then mixed with standard culture medium and added to in vitro cultures of HPMCs from healthy donors. Cells were assessed for proliferation, viability and cytokine release. RESULTS: Proliferation and viability of HPMCs were better preserved in the presence of effluent obtained during dialysis with Balance (P<0.046 and P<0.035, respectively). The proliferative response of HPMCs correlated with the concentration of fibronectin in dialysates (P = 0.0024). Effluent drained following a 3 month dialysis with Balance contained significantly increased levels of fibronectin (P = 0.004) and CA125 antigen (P = 0.0004) compared with S-PDF. There was no significant difference in constitutive and stimulated cytokine (IL-6, MCP-1, VEGF) synthesis by HPMCs treated with either Balance- or S-PDF-derived effluents. CONCLUSIONS: These results suggest that therapy with new pH-neutral low-GDP solutions contribute to an intraperitoneal milieu that improves mesothelial cell proliferation and viability. It may positively impact on the preservation of the peritoneal membrane integrity during long-term dialysis.
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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 | 0.001 |
| 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) | 0.001 | 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".