Comparison of the Biocompatibility of Phosphate-Buffered Saline Alone, Phosphate-Buffered Saline Supplemented with Glucose, and Dianeal 3.86%
Bibliographic record
Abstract
OBJECTIVE: We compared the effects of intraperitoneal infusion of phosphate-buffered saline (PBS, pH 7.4), of PBS supplemented with 3.86% glucose (G), and of standard dialysis solution [Dianeal 3.86%: Baxter Healthcare Corporation, Deerfield, IL, U.S.A. (D)] on intraperitoneal inflammation in dialyzed rats. METHODS: After catheter implantation, rats were infused on day 1 with PBS, on day 3 with PBS+G, on day 5 with D, and on day 7 again with PBS (PBS-2). After a 4-hour dwell, dialysate samples were collected and analyzed. RESULTS: All dialysate parameters studied [dialysate cell count, neutrophil:macrophage ratio (Ne:Ma), and total protein], except tumor necrosis factor alpha (TNFalpha), were comparable during both PBS infusions. During dialysis with PBS+G, the inflammatory response was suppressed as compared with the first dialysis with PBS (cell count, p < 0.001; Ne:Ma, p < 0.05; TNFalpha, p < 0.001; total protein, p < 0.001). During dialysis with D, peritoneal inflammatory parameters were further suppressed (cell count, p < 0.001 vs PBS and p < 0.01 vs PBS+G; Ne:Ma, p < 0.001 vs PBS and p < 0.05 vs PBS+G; TNFalpha, p < 0.001 vs PBS and p < 0.001 vs PBS+G; total protein, p < 0.001 vs PBS and p < 0.01 vs PBS+G). CONCLUSIONS: Hypertonicity of the dialysis fluid suppresses intraperitoneal inflammatory parameters in rats. The suppression was even more severe when Dianeal 3.86% was used. That finding could be due to the low pH and presence of GDPs in the fluid.
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 | 0.000 |
| 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 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".