Modalities for Visualization of Cortical Bone Remodeling: The Past, Present, and Future
Bibliographic record
Abstract
Bone's ability to respond to load-related phenomena and repair microdamage is achieved through the remodeling process, which renews bone by activating groups of cells known as basic multicellular units (BMUs). The products of BMUs, secondary osteons, have been extensively studied via classic two-dimensional techniques, which have provided a wealth of information on how histomorphology relates to skeletal structure and function. Remodeling is critical in maintaining healthy bone tissue; however, in osteoporotic bone, imbalanced resorption results in increased bone fragility and fracture. With increasing life expectancy, such degenerative bone diseases are a growing concern. The three-dimensional (3D) morphology of BMUs and their correlation to function, however, are not well-characterized and little is known about the specific mechanisms that initiate and regulate their activity within cortical bone. We believe a key limitation has been the lack of 3D information about BMU morphology and activity. Thus, this paper reviews methodologies for 3D investigation of cortical bone remodeling and, specifically, structures associated with BMU activity (resorption spaces) and the structures they create (secondary osteons), spanning from histology to modern ex vivo imaging modalities, culminating with the growing potential of in vivo imaging. This collection of papers focuses on the theme of "putting the 'why' back into bone architecture." Remodeling is one of two mechanisms "how" bone structure is dynamically modified and thus an improved 3D understanding of this fundamental process is crucial to ultimately understanding the "why."
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| 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".