Molecular Cloning of a 70‐kiloDalton (kDa) Nuclear Protein That Binds to Insulin Responsive Element (IRE) of Rat Angiotensinogen (ANG) Gene Promoter and Modulates ANG Gene Expression in Kidney Proximal Tubular Cells
Bibliographic record
Abstract
We reported previously an IRE in rat ANG gene promoter that binds to two nuclear proteins with apparent molecular weights of 48‐ and 70‐kDa from rat immortalized renal proximal tubular cells (IRPTCs). We recently identified the 48‐kDa nuclear protein as the 46 kDa heterogenous nuclear ribonucleoprotein F (hnRNP F) that binds to rANG‐IRE and inhibits ANG gene expression in IRPTCs. The present studies aimed to clone the 70‐kDa nuclear protein and to study its action on ANG gene expression. Nuclear proteins isolated from IRPTCs were subjected to 2‐dimensional gel electrophoresis. The 70‐kDa nuclear protein was detected by Southwestern blotting and subsequently identified by mass spectrometry, which revealed that it was identical to 65‐kDa hnRNP K. Transient transfection of hnRNP K cDNA inhibits ANG mRNA expression and ANG gene promoter activity in IRPTCs. Most interestingly, hnRNP K pulls down with hnRNP F. Co‐transfection of hnRNP K with hnRNP F positively regulates ANG gene expression in IRPTCs. In conclusion, our studies demonstrate that 65‐kDa hnRNP K is a novel nuclear protein that interacts with hnRNP F and binds to IRE of the rat ANG gene promoter and subsequently modulates ANG gene expression in IRPTCs. These data indicate that 65‐kDa hnRNP K plays an important role in modulating intrarenal ANG gene expression and renin‐angiotensin system activation and subsequently kidney injury. These observations open a novel research route to study renal ANG gene regulation.
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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 | 0.001 |
| 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 | 0.001 |
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".