Mechanisms of Interaction of Biomolecule Phosphate Side Chains with Calcite during Dissolution
Bibliographic record
Abstract
In proteins, phosphorylation of amino acid residues confers unique functions, including mineral-binding properties. For example, osteopontin, an abundant phosphoprotein in many biomineralized tissues and structures including bones, teeth, otoconia, and shells, can be variably and extensively phosphorylated. This post-translational modification of osteopontin imparts potent mineralization-regulating functional properties for both calcium phosphate- and calcium carbonate-containing tissues/structures. The local environment in which crystal formation (and dissolution) occurs is also rich in other nonprotein phosphate complexes such as pyrophosphate, polyphosphate (PP), and adenosine triphosphate. Here, we investigated the interaction of various small phospho-molecules with calcite under dissolution conditions. Using atomic force microscopy (AFM), we report on nanotopographic surface alterations resulting from dissolution of the (1 0 4) cleavage surface of calcite exposed to (i) a short-chain PP containing five phosphates (PP5), (ii) the phospho-amino acids P-serine, P-threonine, and P-tyrosine, and (iii) phosphorylethanolamine. We compared CORINA software-measured distances with Ca–Ca spacings characteristic of the step edges visualized experimentally by AFM to provide best-spacing matches on the (1 0 4) calcite acute and obtuse surface step directions during dissolution—this allowed for determination of plausible chiral or achiral molecular footprints for the phospho-molecules docked to Ca atoms at the dissolving calcite surface.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".