Glymphatic alterations are linked to white matter topological network dysfunction in Alzheimer's Disease
Bibliographic record
Abstract
BACKGROUND: Although glymphatic dysfunction and impairment of the structural topological network dysfunction are involved in Alzheimer's Disease (AD), their associations and the mediators of the association in the AD spectrum remain unclear. METHOD: Glymphatic activity of the whole brain was evaluated by diffusion tensor imaging along perivascular spaces (DTI-ALPS) and structural topological network was calculated by DTI data in participants with AD dementia (n = 46), mild cognitive impairment (MCI, n = 43), and normal controls (n = 167) from the TRIAD cohort. Blood was collected and plasma GFAP concentrations were analyzed. RESULT: Significant positive correlations were found between ALPS and global efficiency, local efficiency, and hierarchy, and a significant negative correlation with the shortest path length. Lower clustering coefficiency, shortest path length, global efficiency, local efficiency, and hierarchy when comparing the global properties between low and high ALPS groups. ALPS was associated with the nodal efficiency of the nodes in the occipital-parietal lobes. The first principal component (PC1) of the brain regions associated with disease severity was positively correlated with ALPS (top brain regions of PC1 included bilateral superior parietal gyrus, bilateral precuneus gyrus, and superior occipital gyrus). Mediation analysis identified multiple mechanisms including Aβ, Tau, neurodegeneration, inflammation, and synaptic dysfunction as mediators between ALPS and the structural topological network. In further structural equation analysis, ALPS affects the structural topological network through Aβ to Tau and Aβ to neurodegeneration pathways. CONCLUSION: ALPS is associated with alterations in the structural topological network in AD. Mediators such as Aβ, Tau, neurodegeneration, inflammation, and synaptic dysfunction play significant roles in the association. The Aβ to Tau and Aβ to neurodegeneration pathways also mediate the association.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".