Human inner ear blood supply revisited: the Uppsala collection of temporal bone—an international resource of education and collaboration
Bibliographic record
Abstract
BACKGROUND: The Uppsala collection of human temporal bones and molds is a unique resource for education and international research collaboration. Micro-computerized tomography (micro-CT) and synchrotron imaging are used to investigate the complex anatomy of the inner ear. Impaired microcirculation is etiologically linked to various inner ear disorders, and recent developments in inner ear surgery promote examination of the vascular system. Here, for the first time, we present three-dimensional (3D) data from investigations of the major vascular pathways and corresponding bone channels. METHODS: We used the archival Uppsala collection of temporal bones and molds consisting of 324 inner ear casts and 113 macerated temporal bones. Micro-CT was used to investigate vascular bone channels, and 26 fresh human temporal bones underwent synchrotron radiation phase contrast imaging (SR-PCI). Data were processed by volume-rendering software to create 3D reconstructions allowing orthogonal sectioning, cropping, and soft tissue analyses. RESULTS: Micro-CT with 3D rendering was superior in reproducing the anatomy of the vascular bone channels, while SR-PCI replicated soft tissues. Arterial bone channels were traced from scala vestibuli (SV) arterioles to the fundus, cochlea, and vestibular apparatus. Drainage routes along the aqueducts were examined. CONCLUSION: Human inner ear vessels are difficult to study due to the adjoining hard bone. Micro-CT and SR-PCI with 3D reconstructions revealed large portions of the micro-vascular system in un-decalcified specimens. The results increase our understanding of the organization of the vascular system in humans and how altered microcirculation may relate to inner ear disorders. The findings may also have surgical implications.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".