CSF total tau, plasma and CSF p tau 181 associated with structural changes in the early stage of Alzheimer's disease
Bibliographic record
Abstract
Abstract Alzheimer's disease (AD) is the most important cause of dementia and is a serious concern for individuals and governments worldwide. Changes in the brain appear about 15 years before the first clinical symptoms; with this in mind, it can clear the role of biomarkers in monitoring Alzheimer's development. P tau 181 level in plasma recently emerged as a new biomarker and rises obviously in AD patients, preclinical AD, and MCI patients. The role of gray matter atrophy and white matter damages in cognitive decline is well established, which is detectable by magnetic resonance imaging (MRI). In this investigation, we measured the association between CSF (total tau, and p tau 181) and plasma p tau 181 with structural changes (cortical thickness, cortical volume, surface area, and subcortical volume) in MCI patients. We performed a cross-sectional study on the ADNI cohort between 461 MCI patients. Results of voxel-wise partial correlation analysis in our participants showed a significant correlation between plasma p tau 181, CSF total tau and p tau 181 with changes in structural values in different regions. Our study revealed a significant correlation between plasma p tau and structural changes in the brain regions associated with Alzheimer's disease physiopathology. These results provide evidence for using plasma p tau 181 as a diagnostic factor in the early onset of AD patients and neurodegeneration.
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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 | 0.001 | 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".