Executive dysfunction and blockage of brain microvessels in a rat model of vascular cognitive impairment
Bibliographic record
Abstract
Most research focuses on overt stroke caused by blockage of major blood vessels. Less attention has been paid to small vessel disease which gives rise to covert stroke that often leads to vascular cognitive impairment (VCI). One reason for this may be the relative lack of relevant animal models. Herein, we describe, a model of VCI induced in middle-aged Sprague-Dawley rats exposed to a diet high in saturated fats, salt and refined sugar (HFSS). In Experiment 1, rats were fed HFSS and subjected to a small mediodorsal (MD) thalamic stroke with or without concomitant permanent bilateral carotid artery occlusion. MD lesions produce significant executive dysfunction in an attention set-shift task ( p = 0.012). In Experiment 2, rats were exposed to either HFSS or control diet and functional effects assessed. We found significant hypertension ( p = 0.013), blockage of brain microvessels ( p = 0.018) and white matter atrophy ( p = 0.039) in HFSS diet animals. As in Experiment 1, profound, specific set-shifting executive dysfunction was noted ( p = 0.003) following both small MD infarcts (0.332 mm 3 ) and the HFSS diet. In summary, these data describe a middle-aged animal model of VCI that includes clinically relevant metabolic disturbances and small vessel disease and as such may be helpful in developing new cognitive therapies.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".