Heterogenous Nuclear Ribonucleoprotein F Modulates Angiotensinogen Gene Expression in Rat Kidney Proximal Tubular Cells
Bibliographic record
Abstract
An insulin-responsive element (IRE) in the rat angiotensinogen (ANG) gene promoter that binds to two nuclear proteins with apparent molecular weights of 48 and 70 kD was identified previously from rat immortalized renal proximal tubular cells (IRPTC). The present studies aimed to identify and clone the 48-kD nuclear protein and to define its action on ANG gene expression. Nuclear proteins were isolated from IRPTC and subjected to two-dimensional electrophoresis. The 48-kD nuclear protein was detected by Southwestern blotting and subsequently identified by mass spectrometry, revealing that it was identical to 46-kD heterogeneous nuclear ribonucleoprotein F (hnRNP F), a nuclear protein that binds to TATA-binding protein and associates with RNA polymerase II and also interacts with nuclear cap-binding complex. The hnRNP F cDNA was cloned from IRPTC by reverse transcriptase-PCR. Bacterially expressed recombinant hnRNP F bound to the rat ANG-IRE, as revealed by gel mobility shift assay. The addition of polyclonal antibodies against hnRNP F yielded a supershift in gel mobility. Transient transfer of sense and antisense hnRNP F cDNA in IRPTC inhibited and enhanced ANG gene expression, respectively. High glucose stimulated and insulin inhibited hnRNP F expression in IRPTC. Expression studies indicated that hnRNP F is present in the kidney, testis, liver, lung, and brain but not in the spleen. In conclusion, these studies demonstrate that hnRNP F binds to rANG-IRE and modulates renal ANG gene expression, implicating that dysregulation of hnRNP F might affect renin-angiotensin system activation and, subsequently, kidney injury in diabetes.
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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".