Two pathways differentially linking tau depositions, oxidative stress, and neuronal loss to apathetic phenotypes in progressive supranuclear palsy
Bibliographic record
Abstract
Patients with progressive supranuclear palsy (PSP) frequently exhibit apathy but the neuropathological processes leading to this phenotype remain elusive. We aimed to examine the involvement of tau protein depositions, oxidative stress (OS), and neuronal loss in the apathetic manifestation of PSP. Twenty patients with PSP and twenty-three healthy controls were enrolled. Tau depositions and brain volumes were evaluated via positron-emission tomography (PET) using a specific probe, 18 F-PM-PBB3, and magnetic resonance imaging, respectively. Glutathione (GSH) levels in the anterior and posterior cingulate cortices were quantified by magnetic resonance spectroscopy. Tau pathologies were observed in the subcortical and cortical structures of the patient brains. The angular gyrus exhibited a positive correlation between tau accumulations and apathy scale (AS). Although PSP cases did not show GSH level alterations compared with healthy controls, GSH levels in posterior cingulate cortex were correlated with AS and tau depositions in the angular gyrus. Marked atrophy was observed in subcortical areas, and gray matter volumes in the inferior frontal gyrus and anterior cingulate cortex were positively correlated with AS but showed no correlation with tau depositions and GSH levels. Path analysis highlighted synergistic contributions of tau pathologies and GSH reductions in the posterior cortex to AS, in parallel with associations of gray matter atrophy in the anterior cortex with AS. Apathetic phenotypes may arise from PET-visible tau aggregation and OS compromising the neural circuit resilience in the posterior cortex, along with neuronal loss, with neither PET-detectable tau pathologies nor OS in the anterior cortex.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".