General lysosomal hydrolysis can process prorenin accurately
Bibliographic record
Abstract
Renin, an aspartyl protease that catalyzes the rate-limiting step of the renin-angiotensin system, is first synthesized as an inactive precursor, prorenin. Prorenin is activated by the proteolytic removal of an amino terminal prosegment in the dense granules of the juxtaglomerular (JG) cells of the kidney by one or more proteases whose identity is uncertain but commonly referred to as the prorenin-processing enzyme (PPE). Because several extrarenal tissues secrete only prorenin, we tested the hypothesis that the unique ability of JG cells to produce active renin might be explained by the existence of a PPE whose expression is restricted to JG cells. We found that inducing renin production by the mouse kidney by up to 20-fold was not associated with the concomitant induction of candidate PPEs. Because the renin-containing granules of JG cells also contain several lysosomal hydrolases, we engineered mouse Ren1 prorenin to be targeted to the classical vesicular lysosomes of cultured HEK-293 cells, where it was accurately processed and stored. Furthermore, we found that HEK cell lysosomes hydrolyzed any artificial extensions placed on the protein and that active renin was extraordinarily resistant to proteolytic degradation. Altogether, our results demonstrate that accurate processing of prorenin is not restricted to JG cells but can occur in classical vesicular lysosomes of heterologous cells. The implication is that renin production may not require a specific PPE but rather can be achieved by general hydrolysis in the lysosome-like granules of JG cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".