INTERPRETING THE 3D ORIENTATION OF VASCULAR CANALS IN CORTICAL BONE IN BIRDS AND BATS
Bibliographic record
Abstract
Vascular canals in cortical bone during growth and development typically show an anisotropic pattern with canals falling into three main categories: circumferential, radial, and longitudinal. Two major hypotheses attempt to explain the preferred orientations in bone: that vascular canal orientation is optimized to resist a predominant strain direction from functional loading, or that it reflects growth requirements and velocity. This thesis presents a novel method to measure the three dimensional (3D) orientation of vascular canals. Image data are obtained from micro-CT scans and two angles are measured: phi, determining how longitudinal a canal is; and theta, determining whether a canal is radial or circumferential. This method offers a direct (3D) method for quantifying features of canal orientation and can be applied easily and non-destructively to multiple species and bones. This thesis describes two major studies to examine the orientation of vascular canals in birds and bats, the two extant groups of flying vertebrates. The first study examined the vascular canal network in the humerus and femur of a comparative sample of 31 bird and 24 bat species to look for a connection between canal orientation and functional loading. In addition to canal orientation several cross-sectional geometric parameters and strength indices were measured. The results indicated that the bat cortices are relatively thicker and poorly vascularized, whereas those of birds are thinner and more highly vascularized, and that bird bones have a greater resistance to torsional stress than the bats; in particular, the humerus in birds is more adapted to resist torsional stresses than the femur. Our results show that birds have a significantly higher laminarity index than bats. Counter to expectation, the birds had a significantly higher laminarity index in the femur than in the humerus. We conducted a comparison between our 3D method and an analogue to 2D histological measurements. This comparison revealed that 2D methods significantly underestimate the amount of longitudinal canals by an average of 20% and significantly overestimate the laminarity index by an average of 7.7%, systematically mis-estimating indices of vascular canal orientations. The second study was a controlled growth experiment using broiler chickens to investigate the effect of growth rate on vascular canal orientation. Using feed restriction we set up a fast growing control group and a slow growing restricted group. We found consistent patterns in the comparison between the humerus and the femur in both groups, with the humerus having higher laminar and longitudinal indices and a lower radial index than the femur. The faster growing group had higher radial indices and lower laminar and longitudinal indices in both the humerus and the femur than the restricted group. The higher radial indices in our control group point to a link between radial canals and faster growth, and laminar canals and slower growth, while the higher laminar indices in the humerus contradict the results of the first study and point to a link between circumferential canals and torsional loading. We believe this difference is due to differences in femoral loading between chickens and other birds. Overall our results indicate that the orientation of the cortical canal network in a bone is the consequence of a complex interaction between that bone’s growth rate and functional loading environment.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".