Pharmacological and Genetic Disruption of C-Type Natriuretic Peptide (nppcl) Expression in Zebrafish (Danio rerio) Causes Stunted Growth during Development
Bibliographic record
Abstract
Human patients with mutations within NPPC or NPR2 genes (encoding C-type natriuretic peptide (CNP) and guanylyl cyclase-B (GC-B), respectively) display clinical signs associated with skeletal abnormalities, such as overgrowth or short stature. Mice with induced models of Nppc or Npr2 deletion display profound achondroplasia, dwarfism and early death. Recent pharmacological therapies to treat short stature are utilizing long-acting CNP analogues, but the effects of manipulating CNP expression during development remain unknown. Here, we use Danio rerio (zebrafish) as a model for vertebrate development, employing both pharmacological and reverse genetics approaches to alter expression of genes encoding CNP in zebrafish. Four orthologues of CNP were identified in zebrafish, and spatiotemporal expression profiling confirmed their presence during development. Bioinformatic analyses suggested that nppcl is the most likely the orthologue of mammalian CNP. Exogenous CNP treatment of developing zebrafish embryos resulted in impaired growth characteristics, such as body length, head width and eye diameter. This reduced growth was potentially caused by increased apoptosis following CNP treatment. Expression of endogenous nppcl was downregulated in these CNP-treated embryos, suggesting that negative feedback of the CNP system might influence growth during development. CRISPR knock-down of endogenous nppcl in developing zebrafish embryos also resulted in impaired growth characteristics. Collectively, these data suggest that CNP in zebrafish is crucial for normal embryonic development, specifically with regard to growth.
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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".