Abstract P193: Platelet-derived Growth Factor B: a Novel Determinant of Juxtaglomerular Cell Phenotypic Plasticity?
Bibliographic record
Abstract
Renin, a key component in the regulation of blood pressure in mammals, is produced by the rare and highly specialized juxtaglomerular (JG) cells of the kidney. JG cells may be derived from vascular smooth muscle cells (VSMC) and they can reversibly differentiate in response to changes in salt, blood pressure and treatment with anti-hypertensive medications. The biochemical mechanism responsible for this phenotypic plasticity is currently unknown. Ligands involved in VSMC differentiation include platelet-derived growth factor B (PDGF-B), secreted acidic protein rich in cysteine (SPARC), type-C natriuretic peptide (NPPC), follistatin related protein (FSTL1) and lactose-binding lectin 1 (LGALS1). To test for the role of these factors in JG cell plasticity we used (pro)renin-producing As4.1 cells derived from a mouse JG cell targeted tumor. As4.1 cells were incubated for 48 hours with conditioned medium derived from human embryonic kidney (HEK) 293 cells transfected with the mouse cDNA encoding these ligands, after which both medium and cell lysate were collected. Renin and prorenin were measured using the angiotensin I generation assay. Under control conditions, the medium contained predominantly (>95%) prorenin. In contrast, the cell lysate contained renin only, at levels corresponding to <1% of the total amount of renin+prorenin in the medium (i.e., 161±61 μg angiotensin I/ml.hr, mean±SEM). Among the tested ligands, only PDGF-B affected the medium prorenin and cellular renin levels, decreasing both in parallel by 68±5% and 53±10%, respectively. In addition, PDGF-B-exposed cells changed their morphology to display a more elongated, densely packed and aligned shape with no apparent alteration in their viability. In conclusion, our data suggest that PDGF-B might be one of the factors involved in JG cell phenotypic plasticity.
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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) | 0.004 | 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".