Bone mineral tessellation: Atomic force microscopy of the volume-filling mineralization pattern in hydrated and dehydrated states
Bibliographic record
Abstract
Bone is a specialized hard connective tissue with a hierarchical organization of its components. At the micrometer scale, mineral entities of roughly uniform shape tessellate in 3D within an organized, crosslinked and hydrated scaffold of mostly type I collagen. Here we report on the visualization by atomic force microscopy (AFM) of the volume-filling mineralization pattern of tesselles in lamellar bone, in hydrated and dehydrated conditions (for human, bovine, porcine and ovine bone). Microscale mineral tessellation was clearly visible when bulk lamellar bone was hydrated, whereas dry bone showed submicron nanogranularity instead of tesselle boundaries. Time-lapse AFM experiments of gradual passive dehydration of bone revealed topographical changes for all bone species with the tessellation appearance vanishing after two weeks of dehydration. AFM adhesion forces dropped within the first days of dehydration in all bone species, indicating that surface stickiness is more sensitive to passive dehydration than is stiffness. Irrespective of the bone species, AFM stiffness measurements found that hydrated bone was more compliant than dehydrated bone. AFM Young's modulus measurements of more recently formed osteonal lamellae intersecting with older interstitial lamellae found that the modulus in both hydrated and dehydrated states was lower in the osteonal lamellae. Modelling of water sorption to the surface of stochiometric hydroxyapatite showed that the presence of rigid hydration shells delineates the tesselle boundaries and smoothens the nanogranularity, confirming the AFM observations. This study highlights the importance of regarding water as a fundamental architecting component of bone. STATEMENT OF SIGNIFICANCE: Here we report on visualization of the mineral tessellation pattern in lamellar bone by atomic force microscopy (AFM) in hydrated and dehydrated conditions. We show that lamellar bone (human, bovine, porcine and ovine) contains a universal volume-filling mineral tessellation. The visibility of the tessellation pattern by AFM strongly depends on the state of bone hydration. Modelling water sorption to the surface of stochiometric hydroxyapatite indicated that mechanical and morphological characteristics of lamellar bone (e.g., stiffness, adhesion, contours of tesselle boundaries) can be attributed to the presence of rigid hydration shells. This study highlights the importance of water incorporation as a fundamental component of bone, on par with the mineral and the organic extracellular matrix.
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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 | 0.001 |
| 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".