Dynamic Light Scattering Study of Inhibition of Nucleation and Growth of Hydroxyapatite Crystals by Osteopontin
Bibliographic record
Abstract
We study the effect of isoforms of osteopontin (OPN) on the nucleation and growth of crystals from a supersaturated solution of calcium and phosphate ions. Dynamic light scattering is used to monitor the size of the precipitating particles and to provide information about their concentration. At the ion concentrations studied, immediate precipitation was observed in control experiments with no osteopontin in the solution, and the size of the precipitating particles increased steadily with time. The precipitate was identified as hydroxyapatite by X-ray diffraction. Addition of native osteopontin (nOPN) extracted from rat bone caused a delay in the onset of precipitation and reduced the number of particles that formed, but the few particles that did form grew to a larger size than in the absence of the protein. Recombinant osteopontin (rOPN), which lacks phosphorylation, caused no delay in initial calcium phosphate precipitation but severely slowed crystal growth, suggesting that rOPN inhibits growth but not nucleation. rOPN treated with protein kinase CK2 to phosphorylate the molecule (p-rOPN) produced an effect similar to that of nOPN, but at higher protein concentrations and to a lesser extent. These results suggest that phosphorylations are critical to OPN's ability to inhibit nucleation, whereas the growth of the hydroxyapatite crystals is effectively controlled by the highly acidic OPN polypeptide. This work also demonstrates that dynamic light scattering can be a powerful tool for delineating the mechanism of protein modulation of mineral formation.
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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 | 0.001 |
| 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".