Intraskeletal consistency in patterns of vascularity within bat limb bones
Bibliographic record
Abstract
Bats are the only mammals to have achieved powered flight. A key innovation allowing for bats to conquer the skies was a forelimb modified into a flexible wing. The wing bones of bats are exceptionally long and dynamically bend with wingbeats. Bone microarchitectural features supporting these novel performance attributes are still largely unknown. The humeri and femora of bats are typically avascular, except for large-bodied taxa (e.g., pteropodid flying foxes). No thorough investigation of vascular canal regionalization and morphology has been undertaken as historically it has been difficult to reconstruct the 3D architecture of these canals. This study augments our understanding of the vascular networks supporting the bone matrix of a sample of bats (n = 24) of variable body mass, representing three families (Pteropodidae [large-bodied, species = 6], Phyllostomidae [medium-bodied, species = 2], and Molossidae [medium-bodied, species = 1]). We employed Synchrotron Radiation-based micro-Computed Tomography (SRμCT) to allow for a detailed comparison of canal morphology within humeri and femora. Results indicate that across selected bats, canal number per unit volume is similar independent of body size. Differences in canal morphometry based on body size and bone type appear primarily related to a broader distribution of the canal network as cortical volume increases. Heavier bats display a relatively rich vascular network of mostly longitudinally-oriented canals that are localized mainly to the mid-cortical and endosteal bone envelopes. Taken together, our results suggest that relative vascularity of the limb bones of heavier bats forms support for nutrient exchange in a regional pattern.
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) | 0.000 | 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 | 0.000 |
| 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".