SO005TRANSLATION OF ANTI FIBROTIC MICRORNA STRATEGIES INTO A MOUSE MODEL OF CHRONIC ALLOGRAFT DYSFUNCTION
Bibliographic record
Abstract
Introduction and Aims: Chronic allograft dysfunction (CAD) is the most limiting factor of long term graft survival and characterized by fibrotic remodeling, renal injury and chronic inflammation. Recent studies identified several microRNAs (miRs), small non-coding RNAs involved in gene regulation, that are enriched in kidneys in response to injury. Pro-fibrotic microRNA-21 (miR-21) was shown to be upregulated in CAD. This study investigates miR-21-inhibition as a potential therapeutic strategy in an evaluated murine model of CAD. Methods: Allogenic kidney transplantation (KTx) was performed from male C57BL/6 mice into female Balb/c mice. Recipient mice were treated at day -1 and day 7 either with LNA-scr (control) or LNA-21 (inhibitor of miR-21) (20mg/kg BW, i.p.). Kidneys were harvested and analyzed six weeks after KTx, e.g. by qRT-PCR, periodic-acid-schiff- and sirius-red-staining. Potential signal mechanisms were validated in vitro using renal fibroblast cell line NRK49F and macrophage-like cell line RAW264.7. Results: We determined via qRT-PCR increased expression levels of markers for fibrosis (Col1a2, Col3, FSP-1), inflammation (IL-6, MCP-1, IL-1β) and injury (NGAL, KIM-1) in transplanted kidneys which were rescued by miR-21 inhibition. Moreover, sirius red staining revealed significantly less fibrosis development due to miR-21 inhibition. Besides, allografts of LNA-21 treated mice showed less infiltrated immune cells and had a lower BANFF chronic rejection score.The miR-21 promoter region harbors a putative binding site of transcription factor STAT3, which is activated by IL-6. We identified upregulated IL-6 expression in RAW264.7 upon activation with LPS and hypothesized, that infiltrating immune cells produce and secrete cytokines that might affect resident renal cells causing fibrosis and injury development. Co-culture assays confirmed a crosstalk between RAW264.7 and renal fibroblasts NRK49F with increased expression levels of IL-6, CTGF and miR-21 in NRK49F. Similar results were observed due to IL-6 treatment of NRK49F.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".