Phosphorylation of Osteopontin Peptides Mediates Adsorption to and Incorporation into Calcium Oxalate Crystals
Bibliographic record
Abstract
Phosphorylated peptides of osteopontin (OPN) have been shown to inhibit the growth of the {100} face of calcium oxalate monohydrate (COM). The inhibitory potency has been shown to be dependent on the phosphate content of the peptide. The purpose of this study is to better understand the means by which phosphate groups promote crystal growth inhibition by OPN peptides. Peptides of rat bone OPN 220-235 peptides have been synthesized with zero (P0), 1 (P1) or 3 (P3) phosphate modifications. COM crystals were grown in the presence of 0.1-10 microg of P0, P1 or P3. P0 incorporation into COM crystals was evident at 10 microg/ml of peptide, whereas the phosphorylated peptides P1 and P3 were incorporated at all tested concentrations. At 5 microg/ml of P3, COM crystals exhibited a 'dumbbell' morphology. To study the peptide-mineral interaction, surface frequency plots were constructed from molecular dynamics simulations of OPN peptide adsorption. Carboxylate and phosphate groups were found to adsorb in specific orientations to the COM {100} surface. In conclusion, it appears that the phosphate groups on OPN peptides are capable of interacting with the COM {100} surface. This interaction appears to increase the adsorption energy of the peptide to the surface, thus enhancing its inhibitory potency.
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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".