Bone morphogenetic proteins -2 and -7 exert dose-dependent control over cellular and morphogenetic events during mammalian renal branching morphogenesis
Bibliographic record
Abstract
Mammalian kidney development requires the formation of a patterned, branched network of collecting ducts, a process termed renal branching morphogenesis. Disruption of this process during human kidney development results in Renal Dysplasia, the major cause of renal failure in young children. Genetic evidence, combined with in vitro data, have implicated secreted peptide growth factors, including the developmentally important bone morphogenetic proteins (BMPs), as critical regulators of renal branching morphogenesis. Specifically, mRNA for Bmp7 and Bmp2 are expressed in a spatiotemporal pattern consistent with essential functions in kidney development, and Bmp7 is required for normal mouse kidney development in vivo. In this thesis, I report the morphogenetic, cellular, and molecular effects of BMP2 and BMP7 during renal branching morphogenesis in vitro. In embryonic kidney organ culture and three-dimensional cell culture models of collecting duct development, BMP7 exerted dose-dependent, stimulatory and inhibitory effects on collecting duct growth and branching, cell proliferation, and apoptosis. In contrast, BMP2 only exerted inhibitory effects on embryonic collecting duct morphogenesis and cell survival. A SMAD-dependent signaling mechanism was identified for specifying the inhibitory activity of BMPs during collecting duct development, while a SMAD-independent mechanism evoked their stimulatory effects. This research identifies novel functions for BMPs during mammalian kidney development. It contributes to our understanding of the effects of BMP2 and BMP7 in experimental models of renal collecting duct development. In addition, it advances our knowledge of the developmental role of these BMPs during embryonic kidney morphogenesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".