High‐caloric intake rescues early symptomatic AD‐induced hippocampal neurovascular coupling deficits
Bibliographic record
Abstract
INTRODUCTION: Alzheimer's disease (AD) involves progressive hippocampal dysfunction and atrophy. Obesity, common in AD patients, is a known dementia risk factor. Studying their interaction is difficult in humans due to AD's slow progression. Experimental AD models comorbid with obesity are needed for translational insights. This study examined the effects of a high-carbohydrate, high-fat (HCHF) diet in 12-month-old TgF344-AD rats. METHODS: Nontransgenic (nTg) and TgAD rats received CHOW or CHOW and HCHF diet items from 9 to 12 months of age. Hippocampal neurovascular function was assessed using pseudo continuous arterial spin labeling (pCASL)-MRI during forepaw stimulation. Neuronal activity was recorded with Neuropixels probes. RESULTS: CHOW-fed TgAD rats showed reduced hippocampal cerebral blood flow (CBF), CBF changes spread, and neuronal power responses to somatosensory stimulation; all of these deficits were improved on the HCHF diet. DISCUSSION: This approach provides a sensitive, task-free assay of hippocampal neurovascular coupling. The transiently improved neurovascular and electrophysiological metrics in HCHF-fed TgAD rats may be a manifestation of metabolically dysregulated AD brain benefitting from increased metabolite availability. HIGHLIGHTS: Pseudo-continuous arterial spin labeling (pCASL) magnetic resonance imaging (MRI) -based characterization of hippocampal functional hyperemia. Hippocampal functional hyperemia is attenuated in symptomatic Alzheimer's disease (AD) pathology. A high-carbohydrate, high-fat (HCHF) diet transiently restores hippocampal functional hyperemia in symptomatic AD pathology.
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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 | 0.000 | 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".