Non-Alcoholic Fatty Liver Disease, and the Underlying Altered Fatty Acid Metabolism, Reveals Brain Hypoperfusion and Contributes to the Cognitive Decline in APP/PS1 Mice
Bibliographic record
Abstract
Non-alcoholic fatty liver disease (NAFLD), the leading cause of chronic liver disease, is associated with cognitive decline in middle-aged adults, but the mechanisms underlying this association are not clear. We hypothesized that NAFLD would unveil the appearance of brain hypoperfusion in association with altered plasma and brain lipid metabolism. To test our hypothesis, amyloid precursor protein/presenilin-1 (APP/PS1) transgenic mice were fed a standard diet or a high-fat, cholesterol and cholate diet, inducing NAFLD without obesity and hyperglycemia. The diet-induced NAFLD disturbed monounsaturated and polyunsaturated fatty acid (MUFAs, PUFAs) metabolism in the plasma, liver, and brain, and particularly reduced n-3 PUFAs levels. These alterations in lipid homeostasis were associated in the brain with an increased expression of Tnfα, Cox2, p21, and Nox2, reminiscent of brain inflammation, senescence, and oxidative stress. In addition, compared to wild-type (WT) mice, while brain perfusion was similar in APP/PS1 mice fed with a chow diet, NAFLD in APP/PS1 mice reveals cerebral hypoperfusion and furthered cognitive decline. NAFLD reduced plasma β40- and β42-amyloid levels and altered hepatic but not brain expression of genes involved in β-amyloid peptide production and clearance. Altogether, our results suggest that in a mouse model of Alzheimer disease (AD) diet-induced NAFLD contributes to the development and progression of brain abnormalities through unbalanced brain MUFAs and PUFAs metabolism and cerebral hypoperfusion, irrespective of brain amyloid pathology that may ultimately contribute to the pathogenesis of AD.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".