Plasma p tau 181 levels is associated with white matter microstructural changes in across the Alzheimer’s disease stages
Bibliographic record
Abstract
Abstract Alzheimer’s Disease (AD) is characterized by cognitive impairments and memory difficulties, which hinder daily activities and lead to personal and behavioral problems. In recent years, blood-based biomarkers like plasma phosphorylated tau protein at threonine 181 (p tau 181) emerged as new tools and showed sufficient power in detecting AD patients from healthy people. Here we investigate the correlation between p tau 181 and white matter microstructural changes in AD. We add 41 patients diagnosed with Alzheimer’s, 119 patients with mild cognitive impairments and 43 healthy controls with baseline plasma p tau 181 level and DTI values for each region of interest from the ADNI database. The analysis revealed that the plasma level of p tau 181 could predict changes of MD (Mean Diffusivity), RD (Radial Diffusivity), DA (Axial Diffusivity) and FA (Fractional Anisotropy) parameters in widespread regions and there is a significant association between white matter pathway alteration in different regions and p tau 181 plasma measurements within each group. In conclusion, our findings showed that plasma p tau 181 levels are associated with cellular and molecular changes in AD, which enhance the biomarkers for diagnostic procedures and support the application of plasma p tau 181 as a biomarker for white matter changes and neurodegeneration. Longitudinal studies are also necessary for proving the efficacy of these biomarkers and predicting the role in structural changes.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".