[Ischemic cortical neuronal damage and cognitive impairments in atherosclerotic occlusive disease of the major cerebral artery: a PET study].
Bibliographic record
Abstract
In atherosclerotic internal carotid artery (ICA) or middle cerebral artery (MCA) disease, selective neuronal damage can be detected as a decrease in central benzodiazepine receptors (BZRs) in an apparently normal cerebral cortex. To investigate the association between cortical BZRs decreases and executive dysfunctions, we measured BZRs using positron emission tomography (PET) and (11)C-flumazenil in 60 non-disabled patients with unilateral atherosclerotic ICA or MCA disease and no cortical infarction. Using 3-dimensional stereotactic surface projections, we calculated the BZR index, a measure of abnormally decreased BZRs in the cerebral cortex within the anterior cerebral artery (ACA) or MCA territory, and found that it to be correlated with the patient's score on the Wisconsin Card Sorting Test (WCST). Based on the WCST results, 39 patients were considered abnormal (low categories achieved) for their age. The BZR index of the ACA territory in the hemisphere affected by arterial disease was significantly higher in abnormal patients than in normal patients. The BZR index of the MCA territory differed significantly between the 2 groups when patients with left arterial disease (n = 28) were analyzed separately. The BZR indices of the anterior cingulate gyrus and the middle frontal gyrus carrelated significantly and positively with the total number of WCST errors. In atherosclerotic ICA or MCA disease, selective neuronal damage that is manifested as a decrease in BZRs in the non-infarcted cerebral cortex is associated with executive dysfunction. PET imaging of BZRs is useful as an objective measure of cognitive impairments in atherosclerotic occlusive disease of the major cerebral artery.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".