Neuro-Vascular-Metabolic Dysregulation, Metabolic Connectomics, and Metabolic Functional Changes in Alzheimer’s Disease: A Preclinical and Clinical Comparison
Bibliographic record
Abstract
Historically, imaging diagnostics in Alzheimer's disease (AD) have focused primarily on amyloid and tau accumulation; however, recent work suggests that neurometabolic and vascular dysregulation (MVD) may precede protein deposition and persist throughout the disease spectrum, preclinically and clinically. Translating these findings between human patients and preclinical mouse models remains challenging due to cross-species differences. To address this, regional MVD phenotypes were identified using cerebral metabolism and blood flow, and region-set enrichment analysis (RSEA) was conducted to assess brain functional category (BFC) changes based on metabolic variations, facilitating systematic cross-species comparisons. Clinically, MVD showed progressive alterations across the AD spectrum, while mouse models demonstrated similar genotype- and age-dependent changes. Although direct one-to-one regional correspondence is limited, RSEA revealed changes in comparable BFCs. Our findings suggest that imaging-based MVD mapping and RSEAs can bridge species differences, offering a translational framework to support early diagnostics of AD, enhance disease stratification, and enable therapeutic testing.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".