Effects of hypercapnia, hypocapnia, and hyperoxemia on blood oxygenation level–dependent signal intensity determined by use of susceptibility-weighted magnetic resonance imaging in isoflurane-anesthetized dogs
Bibliographic record
Abstract
OBJECTIVE: To assess the effects of alterations in PaCO(2) and PaO(2) on blood oxygenation level-dependent (BOLD) signal intensity determined by use of susceptibility-weighted magnetic resonance imaging in brains of isoflurane-anesthetized dogs. ANIMALS: 6 healthy dogs. PROCEDURES: In each dog, anesthesia was induced with propofol (6 to 8 mg/kg, IV) and maintained with isoflurane (1.7%) and atracurium (0.2 mg/kg, IV, q 30 min). During 1 magnetic resonance imaging session in each dog, targeted values of PaCO(2) (20, 40, or 80 mm Hg) and PaO(2) (100 or 500 mm Hg) were combined to establish 6 experimental conditions, including a control condition (PaCO(2), 40 mm Hg; PaO(2), 100 mm Hg). Dogs were randomly assigned to different sequences of conditions. Each condition was established for a period of >or= 5 minutes before susceptibility-weighted imaging was performed. Signal intensity was measured in 6 regions of interest in the brain, and data were analyzed by use of an ANCOVA and post hoc Tukey-Kramer adjustments. RESULTS: Compared with control condition findings, BOLD signal intensity did not differ significantly in any region of interest. However, signal intensities in the thalamus and diencephalic gray matter decreased significantly during both hypocapnic conditions, compared with all other conditions except for the control condition. CONCLUSIONS AND CLINICAL RELEVANCE: In isoflurane-anesthetized dogs, certain regions of gray matter appeared to have greater cerebrovascular responses to changes in PaCO(2) and PaO(2) than did others. Both PaO(2) and PaCO(2) should be controlled during magnetic resonance imaging procedures that involve BOLD signaling and taken into account when interpreting findings.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".