Incipient stages of collagen mineralization \nmonitored by atomic force microscopy
Bibliographic record
Abstract
The process of collagen mineralization represents a current challenge in tissue engineering \nand is extensively studied, since collagen and calcium phosphate are the main \nconstituents of natural human bone. In vitro biomineralization of collagen can lead \nto biomaterials which could resemble the bone structure and may be appropriate for \nuse as bone substitutes and implants in medical fields. \nDue to the fact that in vitro mineralization of collagen contributes to the understanding \nof mechanisms of mineralization in vivo, our research focused on the in situ \nmonitoring of the incipient stages of collagen/calcium phosphate composite formation \nas it happened, with the help of atomic force microscopy (AFM). Since AFM \nis an appropriate tool for characterizing the morphologic features of a surface and is \nable to show the modification of the surface by depositions, the effect of calcium and \nphosphate ion concentrations upon the mineralization process of a collagen matrix \nin aqueous medium has been studied and the stimulation of mineral deposition by \ncollagen has been established. Raman spectroscopy enabled us to identify the mineralization \nproducts as well as obtain a qualitative measure of mineralization efficiency. \nAccording to literature, glycosaminoglycans may enhance the efficiency of the collagen \nmineralization. Glucuronic acid, a major component of glycosaminoglycans (e.g. \nhyaluronic acid) in the extracellular matrix, has been previously shown to stimulate \ncollagen mineralization in vitro and to lead to the formation of the desired calcium phosphate phase, i.e. hydroxyapatite. We performed a comparison of glucuronic acid \nwith galacturonic acid (an epimer) which reveals differences in their effects on collagen \nfibrillogenesis. Our approach shows that while the presence of uronic acids in \nthe collagen matrix may build an efficient scaffold for collagen calcification, it also \nbrings modifications to the collagen matrix assembly. Using a surface-induced process \nfor collagen alignment and fibril formation, we can observe changes in fibril and film \nstructure with AFM. \nIn order to gain insight on how the glucuronic acid may potentially affect the \ncollagen matrix during fibrillogenesis, we studied the behaviour of glucuronic acid in \nalkaline and acidic media using AFM. In addition to AFM visualization of the various \npH-dependent aggregates formed by glucuronic acid in solution, our experiments led \nto the synthesis of α-polyglucuronic acid starting from glucuronic acid monomers in \nan acidic solution. The α-polyglucuronic acid fibers were observed by AFM and its \nstructure was confirmed by ¹³C solution NMR.
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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) | 0.002 | 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".