In Situ Assessment of the Brain Microcirculation in Mechanically-Ventilated Rabbits Using Sidestream Dark-Field (SDF) Imaging
Bibliographic record
Abstract
Assessment of the cerebral microcirculation by on-line visualization has been impossible for a long time. Sidestream dark-field (SDF) imaging is a relatively new method allowing direct visualization of cerebral surface layer microcirculation using hand-held probe for direct contact with target tissue. The aim of this study was to elucidate the feasibility of studying the cerebral microcirculation in situ by SDF imaging and to assess the basic cerebral microcirculatory parameters in mechanically ventilated rabbits. Images were obtained using SDF imaging from the surface of the brain via craniotomy. Clear high contrast SDF images were successfully obtained. Total small-vessel density was 14.6+/-1.8 mm/mm(2), total all-vessel density was 17.9+/-1.7 mm/mm(2), DeBacker score was 12.0+/-1.6 mm(-1) and microvascular flow index was 3.0+/-0.0. This method seems to be applicable in animal studies with possibility to use SDF imaging also intraoperatively, providing unique opportunity to study cerebral microcirculation during various experimental and clinical settings.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".