Early treatment of Aicardi syndrome with vigabatrin can improve outcome
Bibliographic record
Abstract
Tubular epithelium constitutes the majority of the renal parenchyma and is the primary target of various kidney injuries. However, how the injured tubules drive interstitial fibroblast activation and proliferation remains poorly understood. Here, we investigated the role of sonic hedgehog (Shh), a secreted extracellular signaling protein, in fibroblast proliferation. Shh was induced in renal tubular epithelia in animal models of CKD induced by ischemia/reperfusion injury (IRI), adriamycin, or renal mass ablation, and in renal tubules of kidney biopsy specimens from CKD patients with different etiologies. Using Gli1-CreERT2 reporter mice, we identified interstitial fibroblasts as the principal targets of renal Shh signaling in vivo. In vitro, incubation with Shh promoted normal rat kidney fibroblast proliferation, which was assessed by cell counting, MTT assay, and BrdU incorporation assay, and stimulated the induction of numerous proliferation-related genes. However, Shh had no effect on the proliferation of renal tubular epithelial cells. In vivo, overexpression of Shh promoted fibroblast expansion and aggravated kidney fibrotic lesions after IRI. Correspondingly, blockade of Shh signaling by cyclopamine, a small molecule inhibitor of Smoothened, inhibited fibroblast proliferation, reduced myofibroblast accumulation, and attenuated renal fibrosis. These studies identify Shh as a novel, specific, and potent tubule-derived growth factor that promotes interstitial fibroblast proliferation and activation. Our data also suggest that blockade of Shh signaling is a plausible strategy for therapeutic intervention of renal 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) | 0.000 | 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 | 0.000 | 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".