Neuro-Metabolic and Vascular Dysfunction as an Early Diagnostic for Alzheimer’s Disease and Related Dementias
Bibliographic record
Abstract
Alzheimer's disease (AD) is the most prevalent neurodegenerative condition characterized by significant cognitive decline. Recent studies suggest that the brain undergoes anatomical and functional restructuring, resulting in neuro-metabolic and vascular dysregulation (MVD) prior to amyloid-β accumulation, which begins at an early age and leads to the onset of AD. Using a retrospective clinical population (N=403) of subjects with varying disease stages from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we identified that disease progression follows a stage-dependent MVD pattern, facilitating the identification of at-risk and resilient brain regions. Although each region progresses at a different pace, regions associated with memory, cognitive tasks, and motor function showed significant early dysregulation. These changes aligned with transcriptomics and cognitive signatures. This study underscores that MVD in brain regions varies by sex and disease stage, making it a sensitive tool for early AD diagnosis. Furthermore, this approach could improve patient monitoring, stratification, and therapeutic testing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".