P2‐329: TRACKING WHITE MATTER DEGENERATION IN ASYMPTOMATIC AND SYMPTOMATIC <i>MAPT</i> MUTATION CARRIERS WITH DTI
Bibliographic record
Abstract
White matter injury caused by tau pathology is commonly observed in postmortem examinations of genetic and sporadic cases of patients with frontotemporal lobar degeneration. The objective of this study was to investigate the patterns and trajectories of white matter (WM) diffusion abnormalities in microtubule-associated protein tau (MAPT) mutations carriers. We studied 22 MAPT mutation carriers (12 asymptomatic, 10 symptomatic) and 20 non-carriers from 8 individual families, who underwent diffusion tensor imaging (DTI) and were followed annually (median=4 years) from the Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects Study at the Mayo Clinic sites. Cross-sectional and longitudinal changes in mean diffusivity (MD) and fractional anisotropy (FA) were analyzed. The mean of the tract-based values derived from white matter John's Hopkins University atlas combing the right and left hemispheric regions were determined. We ranked the 43 regions of interest according to the area-under-the-receiver-operating-characteristics curves for distinguishing asymptomatic and symptomatic MAPT mutation carriers from non-carriers using baseline MD and FA values. The association of MD and FA values with time to expected age of onset and time past age of onset were tested using multiple linear regression analysis after adjusting for age. To assess the longitudinal abnormalities, the annual changes in MD and FA were modeled to compare MAPT mutation carriers to non-carriers using linear mixed-effect models. We found that elevated MD in the entorhinal white matter is present as early as the asymptomatic stage in MAPT mutation carriers (p=0.046), which propagated to the limbic tracts and frontotemporal projections in the symptomatic stage compared to non-carriers (Figure 1). Reduced FA (p<0.001) and increased MD (p=0.004) in the entorhinal white matter were associated with the proximity to estimated and actual age of symptom onset. The annualized change of entorhinal MD on serial DTI was accelerated in MAPT mutation carriers compared to non-carriers (p=0.002, Figure 2).
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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 | 0.000 | 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) | 0.001 | 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".