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Record W2789233544 · doi:10.1111/joa.12803

Interpreting the three‐dimensional orientation of vascular canals and cross‐sectional geometry of cortical bone in birds and bats

2018· article· en· W2789233544 on OpenAlexafffund
Isaac Pratt, James D. Johnston, Ernie Walker, David M. L. Cooper

Bibliographic record

VenueJournal of Anatomy · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsUniversity of Saskatchewan
FundersNational Research Council CanadaCanadian Institutes of Health ResearchWestern Economic Diversification CanadaNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsUniversity of Saskatchewan
KeywordsAnatomyCortical boneOrientation (vector space)Cortex (anatomy)GeologyCross section (physics)HumerusBiologyGeometryFemurMaterials scienceBiomedical engineeringMathematicsMedicinePaleontologyPhysics

Abstract

fetched live from OpenAlex

Cortical bone porosity and specifically the orientation of vascular canals is an area of growing interest in biomedical research and comparative/paleontological anatomy. The potential to explain microstructural adaptation is of great interest. However, the determinants of the development of canal orientation remain unclear. Previous studies of birds have shown higher proportions of circumferential canals (called laminarity) in flight bones than in hindlimb bones, and interpreted this as a sign that circumferential canals are a feature for resistance to the torsional loading created by flight. We defined the laminarity index as the percentage of circumferential canal length out of the total canal length. In this study we examined the vascular canal network in the humerus and femur of a sample of 31 bird and 24 bat species using synchrotron micro-computed tomography (micro-CT) to look for a connection between canal orientation and functional loading. The use of micro-CT provides a full three-dimensional (3D) map of the vascular canal network and provides measurements of the 3D orientation of each canal in the whole cross-section of the bone cortex. We measured several cross-sectional geometric parameters and strength indices including principal and polar area moments of inertia, principal and polar section moduli, circularity, buckling ratio, and a weighted cortical thickness index. We found that bat cortices are relatively thicker and poorly vascularized, whereas those of birds are thinner and more highly vascularized, and that according to our cross-sectional geometric parameters, 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 (P = 0.031) higher laminarity index than bats, with birds having a mean laminarity index of 0.183 in the humerus and 0.232 in the femur, and bats having a mean laminarity index of 0.118 in the humerus and 0.119 in the femur. Counter to our expectation, the birds had a significantly higher laminarity index in the femur than in the humerus (P = 0.035). To evaluate whether this discrepancy was a consequence of methodology we conducted a comparison between our 3D method and an analogue to two-dimensional (2D) histological measurements. This comparison revealed that 2D methods significantly underestimate (P < 0.001) the amount of longitudinal canals by an average of 20% and significantly overestimate (P < 0.001) the laminarity index by an average of 7.7%, systematically mis-estimating indices of vascular canal orientations. In comparison with our 3D results, our approximated 2D measurement had the same results for comparisons between the birds and bats but found significant differences only in the longitudinal index between the humerus and the femur for both groups. The differences between our 3D and pseudo-2D results indicate that differences between our findings and the literature may be partially based in methodology. Overall, our results do not support the hypothesis that the bones of flight are more laminar, suggesting a complex relation between functional loading and microstructural adaptation.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.280
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations30
Published2018
Admission routes2
Has abstractyes

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