Mesoscale mineral clusters in osteonal bone follow the twisted plywood structure of collagen
Bibliographic record
Abstract
The structure of bone at the nano to microscale contributes to its functions, including its mechanical strength. A new hierarchical feature was recently discovered at the mesoscale: ellipsoidal-shaped mineral clusters. While a great deal of imaging has been completed on bone, the packing and spatial organization between the mesoscale mineral clusters and nanoscale features, such as collagen fibrils, is largely absent. This is partly due to the technical 3D nanoscale imaging challenges, which have impacted the ability to resolve collagen fibril banding in fully mineralized bone in multiple planes, and partly due to a lack of image processing tools to visualize characteristic details of the collagen fibril and mineral cluster arrangement from 3D volumes. Herein, FIB-SEM nanotomography of mineralized osteonal bone revealed mineral clusters with an average diameter of 600-700 nm yielding an estimate of 8 clusters per lamellae. Mineral clusters were found to follow the well-known twisted plywood organization of collagen fibrils and low-mineralized collagen fibrils defining the border of the clusters were found to be within ±30° of the long axis of the mineral cluster. Clusters were also found to be spatially correlated with distinct symmetry motifs, indicating some degree of local ordering. Further, we show that what was previously thought to be pores or nanochannels surrounding mineral clusters may be, in large part, collagen fibrils. This work unveils new insights into the links between the meso‑ and nanoscale organization of bone, reinforcing its hierarchical nature. STATEMENT OF SIGNIFICANCE: Advances in 3D-focused ion beam scanning electron nanotomography have enabled high-resolution visualization of the relationship between the mineral and organic content within the osteonal bone. While the nanoscale collagen fibril organization has been heavily investigated using 2D and 3D imaging techniques, the arrangement of mesoscale mineral ellipsoids has not been characterized in depth. Using FIB-SEM nanotomography and advanced image processing tools, including deep learning segmentation, FFT processing with azimuthal profile integration, and autocorrelation analysis, our results display the close association of the mineral ellipsoids and the collagen fibril network within human osteonal bone where the mineral ellipsoids appear to have local ordering that follows a twisted plywood organization similar to the collagenous matrix.
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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".