The characterization of α<sub>5</sub>-integrin expression on tubular epithelium during renal injury
Bibliographic record
Abstract
The hallmark of progressive chronic kidney disease is the deposition of extracellular matrix proteins and tubulointerstitial fibrosis. Integrins mediate cell-extracellular matrix interaction and may play a role tubular epithelial injury. Murine primary tubular epithelial cells (TECs) express alpha(5)-integrin, a fibroblast marker and the natural receptor for fibronectin. Microscopy localized alpha(5)-integrin on E-cadherin-positive cells, confirming epithelial expression. The expression of alpha(5)-integrin increased in TECs grown on fibronectin and occurred in parallel with an upregulation of alpha-smooth muscle actin (alphaSMA), a marker of epithelial-mesenchymal transition (EMT). Exposure of TECs to transforming growth factor (TGF)-beta also increased TEC alpha(5)-integrin expression in association with alphaSMA and EMT. Knock-down of alpha5-integrin expression with short interfering RNA attenuated the TGF-beta induction of alphaSMA but did not alter morphologic EMT. Rather, alpha5-integrin was necessary for epithelial cell migration on fibronectin but not type IV collagen during cell spreading and epithelial wound healing in vitro. Immunohistochemistry revealed basolateral tubular epithelial alpha(5)-integrin expression in mouse kidneys after unilateral ureteric obstruction but not in contralateral control kidneys. In patient biopsies of nondiabetic kidney disease, alpha(5)-integrin expression was increased significantly in the renal interstitium. Focal basolateral staining was also detected in injured, but not in normal, tubular epithelium. In summary, these data show that TECs are induced to express alpha(5)-integrin during EMT and tubular epithelial injury in vitro and in vivo. These results increase our understanding of the biology of integrins during EMT and tubular injury in chronic kidney disease.
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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 | 0.000 | 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 | 0.000 |
| 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".