Bone Mineralization Regulation: Using Zebrafish as a Model to Study ANKH-associated Mineralization Disorders
Bibliographic record
Abstract
Abstract Craniometaphyseal Dysplasia (CMD) is a rare skeletal disorder that can result from mutations in the ANKH gene. This gene encodes progressive ankylosis (ANK), which is responsible for transporting inorganic pyrophosphate (PPi) and ATP from the intracellular to the extracellular environment, where PPi inhibits bone mineralization. When ANK is dysfunctional, as in patients with CMD, the passage of PPi to the extracellular environment is reduced, leading to excess mineralization, particularly in bones of the skull. Zebrafish may serve as a promising model to study the mechanistic basis of CMD. Here we provide a detailed analysis of the zebrafish ankh paralogs, ankha and ankhb, in terms of their phylogenic relationship with ANKH in other vertebrates as well as their spatiotemporal expression patterns during zebrafish development. We found a closer evolutionary relationship exists between the zebrafish ankhb protein and its human and other “higher” vertebrate counterparts. Furthermore, we noted distinct temporal expression patterns with ankha more prominently expressed in early development stages, and ankhb expression at larval growth stages. Whole mount in situ hybridization was used to compare spatial expression patterns of each paralog during bone development. Both paralogs showed strong expression in the craniofacial region as well as the notochord and somites, with only subtle patterning differences. Given the substantial overlap in spatiotemporal expression of ankha and ankhb , the exact roles of these genes remain speculative. However, this study lays the groundwork for functional analyses of each ankh paralog and the potential of using zebrafish to find possible targeted therapies for CMD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".