Visualizing biointerfaces in three dimensions: electron tomography of the bone–hydroxyapatite interface
Bibliographic record
Abstract
A positive interaction between human bone tissue and synthetics is crucial for the success of bone-regenerative materials. A greater understanding of the mechanisms governing bone-bonding is often gained via visualization of the bone-implant interface. Interfaces to bone have long been imaged with light, X-rays and electrons. Most of these techniques, however, only provide low-resolution or two-dimensional information. With the advances in modern day transmission electron microscopy, including new hardware and increased software computational speeds, the high-resolution visualization and analysis of three-dimensional structures is possible via electron tomography. We report, for the first time, a three-dimensional reconstruction of the interface between human bone and a hydroxyapatite implant using Z-contrast electron tomography. Viewing this structure in three dimensions enabled us to observe the nanometre differences in the orientation of hydroxyapatite crystals precipitated on the implant surface in vivo versus those in the collagen matrix of bone. Insight into the morphology of biointerfaces is considerably enhanced with three-dimensional techniques. In this regard, electron tomography may revolutionize the approach to high-resolution biointerface characterization.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".