Syndecan-1 (CD138) deficiency increases Staphylococcus aureus infection but has no effect on pathology in a mouse model of peritoneal dialysis
Bibliographic record
Abstract
BACKGROUND: Technique failure in peritoneal dialysis (PD) due to fibrosis and angiogenesis is complicated by peritonitis. Staphylococcus aureus infection is one of the most common causes of peritonitis in PD. The heparan sulfate proteoglycan, syndecan-1 (CD138), was reported to regulate fibrosis, angiogenesis, inflammation and S. aureus infection. The objectives of this study were to examine the effects of syndecan-1 on S. aureus infection and histopathology in a PD model. RESULTS: Syndecan-1(-/-) and wild type mice were dialyzed for 4 weeks and infected intraperitoneally with S. aureus. Tissues were collected after 4 h for histomorphometric analysis. Intravital microscopy was used to observe leukocyte recruitment and to quantify syndecan-1 in the parietal peritoneum microcirculation. The dialyzed syndecan-1(-/-) mice were more susceptible to S. aureus infection than undialyzed syndecan-1(-/-) controls and wild type animals. However, peritoneal fibrosis and neovascularization due to PD did not differ between syndecan-1(-/-) and wild type mice. Intravital microscopy showed that in S. aureus infection, syndecan-1 was removed from the subendothelial layer of peritoneal venules but syndecan-1 deficiency did not affect leukocyte recruitment. CONCLUSIONS: This study indicates that, while syndecan-1 is important for providing a barrier to acute S. aureus infection in PD, it does not affect peritoneal fibrosis and angiogenesis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".