Transcriptome analysis of signaling pathways of human peritoneal mesothelial cells in response to different osmotic agents in a peritoneal dialysis solution
Bibliographic record
Abstract
BACKGROUND: Glucose is a primary osmotic agent in peritoneal dialysis (PD) solutions, but its long-term use causes structural alteration of the peritoneal membrane (PM). Hyperbranched polyglycerol (HPG) is a promising alternative to glucose. This study was designed to compare the cellular responses of human peritoneal mesothelial cells (HPMCs) to these two different osmotic agents in a hypertonic solution using transcriptome analysis. METHODS: Cultured HPMCs were repeatedly exposed to HPG-based or Physioneal 40 (PYS, glucose 2.27%) hypertonic solutions. Transcriptome datasets were produced using Agilent SurePrint G3 Human GE 8 × 60 microarray. Cellular signaling pathways were examined by Ingenuity Pathway Analysis (IPA). Protein expression was examined by flow cytometry analysis and Western blotting. RESULTS: The HPG-containing solution was better tolerated compared with PYS, with less cell death and disruption of cell transcriptome. The levels of cell death in HPG- or PYS- exposed cells were positively correlated with the number of affected transcripts (HPG: 128 at day 3, 0 at day 7; PYS: 1799 at day 3, 212 at day 7). In addition to more affected "biosynthesis" and "cellular stress and death" pathways by PYS, both HPG and PYS commonly affected "sulfate biosynthesis", "unfolded protein response", "apoptosis signaling" and "NRF2-mediated oxidative stress response" pathways at day 3. PYS significantly up-regulated HLA-DMB and MMP12 in a time-dependent manner, and stimulated T cell adhesion to HPMCs. CONCLUSION: The lower cytotoxicity of hypertonic HPG solution is in agreement with its transient and minimal impact on the pathways for the "biosynthesis of cell constituents" and the "cellular stress and death". The significant up-regulation of HLA-DMB and MMP12 by PYS may be part of its initiation of immune response in the PM.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".