Osteopontin: correlation with interstitial fibrosis in human diabetic kidney and PI3‐kinase‐mediated enhancement of expression by glucose in human proximal tubular epithelial cells
Bibliographic record
Abstract
AIMS: To examine the expression and localization of osteopontin (OPN), a secreted phosphoprotein implicated in the development of tubulointerstitial inflammation in various models of renal disease, in human diabetic kidneys, and to study the regulation of OPN expression in primary cultures of human renal proximal tubular epithelial cells (RPTEC). METHODS AND RESULTS: Differential gene expression profiling through subtractive hybridization demonstrated increased renal OPN mRNA expression in a patient with diabetic nephropathy. Immunohistochemical staining of normal and diabetic human kidney samples confirmed that OPN was localized to cortical tubular, interstitial and juxtaglomerular compartments. Quantification of OPN immunostaining revealed a marked increase in the percentage of OPN-positive tubular profiles in diabetic kidneys (47 +/- 9% versus 5 +/- 3%, diabetic versus minimal change disease) that correlated strongly with the degree of cortical scarring (r2 = 0.91). Results of Northern hybridization, flow cytometry and Western blotting indicated that glucose up-regulates OPN mRNA and protein expression in primary cultures of human RPTECs. This effect was independent of the osmotic effects of glucose and independent of insulin. Finally, glucose-stimulated OPN expression was inhibited by LY294002, an inhibitor of phosphatidylinositol 3-kinase activity, in a dose-dependent manner. CONCLUSIONS: OPN is expressed in human diabetic kidneys and regulation of OPN expression is via a glucose-mediated, phosphatidylinositol 3-kinase-dependent pathway.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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".