Stressed volume around vascular canals explains compressive fatigue life variation of secondary osteonal bone but not plexiform bone
Bibliographic record
Abstract
The fatigue life of bone illustrates a large degree of scatter that is likely related to underlying differences in composition and microarchitecture. Vascular canals act as stress concentrations, the magnitude and volume of which may depend on the size and spatial distribution of canals. The purpose of this study was to establish the relationship between vascular canal microarchitecture, stressed volume and the fatigue life of both secondary osteonal and plexiform bovine bone. Twenty-one cortical bone samples were prepared from bovine femora and tibiae and imaged using micro-computed tomography (μCT) to quantify canal diameter, canal separation and canal number. Samples were cyclically loaded in zero-compression to a peak magnitude of 95 MPa, and fatigue life was defined as the number of cycles until fracture. Finite element models were created from μCT images and used to quantify the stressed volume, i.e., the volume of bone stressed higher than a yield stress of 108 MPa. Fatigue life ranged from 162-633,437 cycles with the fatigue life of plexiform bone (n = 15) being more than 4.5 times longer than secondary bone (n = 6). The fatigue life of secondary bone was negatively correlated with canal diameter (r2 = 0.73) and canal separation (r2 = 0.56), while the fatigue life of plexiform bone was negatively correlated with canal separation (r2 = 0.41), but positively correlated with canal number (r2 = 0.36). Stressed volume was related to canal microarchitecture in secondary bone only, where canal diameters and canal separation were larger than approximately 50 μm and 200 μm, respectively. Consequently, stressed volume explained 89% of the fatigue life variance in secondary bone but was not related to the fatigue life of plexiform bone. These findings suggest that the volume of the stress concentration surrounding vascular canals is dictated by canal size and spacing and may play an important role in the fatigue failure of osteonal bone. We suspect that a larger stressed volume is more likely to encounter and facilitate the propagation of pre-existing microcracks, thereby leading to a reduction in fatigue life.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".