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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".