Bmp7 drives proximal tubule expansion and determines nephron number in the developing kidney
Bibliographic record
Abstract
The mammalian kidney is composed of thousands of nephrons that are formed through reiterative induction of a mesenchymal-to-epithelial transformation by a population of nephron progenitor cells. The number of nephrons in human kidneys ranges from several hundred thousand to nearly a million, and low nephron number has been implicated as a risk factor for kidney disease as an adult. Bmp7 is among a small number of growth factors required to support the proliferation and self-renewal of nephron progenitor cells, in a process that will largely determine the final nephron number. Once induced, each nephron begins as a simple tubule that undergoes extensive proliferation and segmental differentiation. Bmp7 is expressed both by nephron progenitor cells and the ureteric bud derivative branches that induce new nephrons. Here, we show that, in mice, Bmp7 expressed by progenitor cells has a major role in determining nephron number; nephron number is reduced to one tenth its normal value in its absence. Postnatally, Bmp7 also drives proliferation of the proximal tubule cells, and these ultimately constitute the largest segment of the nephron. Bmp7 appears to act through Smad 1,5,9(8), p38 and JNK MAP kinase. In the absence of Bmp7, nephrons undergo a hypertrophic process that involves p38. Following a global inactivation of Bmp7, we also see evidence for Bmp7-driven growth of the nephron postnatally. Thus, we identify a role for Bmp7 in supporting the progenitor population and driving expansion of nephrons to produce a mature kidney.
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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) | 0.000 | 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) | 0.000 | 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".