Protein-crystal Interactions in Calcium Oxalate Kidney Stone Formation
Bibliographic record
Abstract
We have studied the ability of urinary molecules in altering the precipitation of kidney stone-related calcium oxalate monohydrate (COM) crystals and correlated the resulting morphologies with those of idiopathic COM kidney stones. We found that weakly acidic but highly glycosylated polyelectrolytes (Tamm Horsfall protein (THP), fetuinA, hyaluronic acid) do not significantly affect crystallization, and that THP and fetuinA show the tendency to aggregate in the presence of nascent crystals. It is proposed that highly glycosylated polyelectrolytes encapsulate nascent urinary crystals, prevent their aggregation, and thus act supportive in crystal excretion. Strong effects on crystallization were observed in the presence of the highly acidic molecules osteopontin (OPN), citrate, and the non-urinary glycosaminoglycans heparin and dextran sulfate. OPN formed non-structured concretions comparable with those found in the core of stones, while citrate formed platelets closely resembling crystal shapes found in the mantle region. However, it is unclear how the columnar growth in the mantle takes place. It is assumed that changing polyelectrolyte compilations/concentrations affect stone forming processes (e.g. equilibria, enhanced self-assembly), perhaps resulting in these structures. We have indeed shown that peptides can induce the formation of such structures. Moreover, heparin and dextran sulfate inhibited COM formation; implicating that these molecules could assist OPN, citrate but also THP in preventing stone 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 | 0.000 |
| 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".