Shedding light (… electrons) on human bone ultrastructure with correlative on-axis electron tomography and energy dispersive X-ray spectroscopy tomography
Bibliographic record
Abstract
ABSTRACT Mineralized collagen fibrils are the building block units of bone at the nanoscale. While it is known that collagen fibrils are mineralized both inside their gap zones (intra-fibrillar mineralization) and on their outer surfaces (extra-fibrillar mineralization), a clear visualization of this architecture in three dimensions (3D), combining structural and compositional information over large volumes, but without compromising the resolution, remains challenging. In this study, we demonstrate the use of on-axis Z-contrast electron tomography (ET) with correlative energy-dispersive X-ray spectroscopy (EDX) tomography to examine rod-shaped samples with a diameter up to 700 nm prepared from individual osteonal lamellae in the human femur. Our work mainly focuses on two aspects: i) low-contrast nanosized circular spaces (“holes”) observed in sections of bone oriented perpendicular to the long axis of a long bone; and ii) extra-fibrillar mineral, especially in terms of morphology and spatial relationship with respect to intra-fibrillar mineral and collagen fibrils. From our analyses, it emerges quite clearly that most “holes” are cross-sectional views of collagen fibrils. While this had been postulated before, our 3D reconstructions and reslicing along meaningful two-dimensional (2D) cross-sections provide a direct visual confirmation. Extra-fibrillar mineral appears composed of thin plates that are interconnected and span over several collagen fibrils, confirming that mineralization is cross-fibrillar, at least for the extra-fibrillar phase. EDX tomography shows mineral signature (Ca and P) within the gap zones, but the signal appears weaker than that associated to the extra-fibrillar mineral, pointing towards the existence of dissimilarities between the two types of mineralization.
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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 | 0.001 | 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) | 0.002 | 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".