Modification of the radioactive microsphere technique for assessment of regional blood flow to the craniofacial skeleton in the New Zealand rabbit
Bibliographic record
Abstract
Background The radioactive microsphere technique has been used extensively for the accurate measurement of tissue blood flow in experimental animals. However, the need for carotid artery cannulation for injection of microspheres may significantly impair blood flow to the head and neck region. Objective This study assessed an alternative technique of injecting microspheres directly into the left ventricle to ensure a symmetric distribution of microspheres to the head. Methods Twenty-five New Zealand rabbits (seven to nine weeks of age) underwent blood flow measurement to the orbitozygomatic complex (OZC) regions bilaterally. Under general anesthesia, a sternotomy was performed and a cannula was inserted into the left ventricle. Radioactive microspheres were injected after a stabilization period of 15 min. Blood pressure and cardiac output were measured during the procedure and the animals were sacrificed at the end of the experiment. Tissue samples were harvested bilaterally from the OZC, hemimandibles, masseter muscles and overlying skin for measurement of blood flow. Results There was no significant difference in blood flow between the right and left side specimens. Animals were hemodynamically stable during the procedure. Conclusion Assessment of blood flow to the craniofacial region in experimental animals using radioactive microspheres may be facilitated by sternotomy and direct intracardiac injection.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".