The gene transfer of soluble VEGF type I receptor (Flt-1) attenuates peritoneal fibrosis formation in mice but not soluble TGF-β type II receptor gene transfer
Bibliographic record
Abstract
Peritoneal fibrosis formation is a consequence of inflammation/injury and a significant medical problem to be solved. The effects of soluble VEGF receptor type I (sFlt-1) gene transfer on experimental peritoneal fibrosis were examined and compared with soluble transforming growth factor-beta (TGF-beta) receptor type II (sTGF beta RII) gene transfer. Male C57BL/6 mice were injected with 1.5 x 10(8) plaque-forming unit of adenovirus encoding active TGF-beta (AdTGF beta) intraperitoneally. Some mice had been treated with sTGF betaRII or sFlt-1 plasmid injection into skeletal muscle with electroporation 4 days before virus administration. Mice were euthanized at day 14 after virus administration. AdTGF beta induced significant elevation of serum active TGF-beta, caused significant inflammatory response [weight loss, elevation of serum amyloid-P (SAP) and IL-12, increased expression of monocyte chemoattractant protein-1 (MCP-1) mRNA], and induced marked thickening of the peritoneum and collagen deposition. Gene transfer of sFlt-1 reduced the collagen deposition approximately 81% in mesenteric tissue. Treatment with sFlt-1 decreased ICAM-1 and MCP-1 mRNA expression significantly. Significant negative correlation between serum sFlt-1 and placental growth factor level was observed, whereas there was no significant negative correlation between sFlt-1 and VEGF. On the other hand, sTGF beta RII treatment enhanced the AdTGF beta-induced inflammation (significant elevation of SAP, TNF-alpha, and IL-12 levels and upregulation of ICAM-1 and MCP-1 mRNA expressions) and failed to prevent collagen deposition. These observations indicate that sFlt-1 gene transfer might be of therapeutic benefit in peritoneal fibrosis.
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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 | 0.000 |
| 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 | 0.001 | 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".