<i>In Vivo</i> Assessment of Astrocyte Reactivity in Patients with Progressive Supranuclear Palsy
Bibliographic record
Abstract
OBJECTIVE: Although astrocytic pathology is a pathological hallmark of progressive supranuclear palsy (PSP), its pathophysiological role remains unclear. This study aimed to assess astrocyte reactivity in vivo in patients with PSP. Furthermore, we investigated alterations in brain lactate levels and their relationship with astrocyte reactivity. METHODS: F-florzolotau positron emission tomography. Myo-inositol, an astroglial marker, and lactate were quantified in the anterior cingulate cortex through magnetic resonance spectroscopy. We measured plasma biomarkers, including glial fibrillary acidic protein as another astrocytic marker. The anterior cingulate cortex was histologically assessed in postmortem samples of another 3 patients with PSP with comparable disease durations. RESULTS: The levels of myo-inositol and plasma glial fibrillary acidic protein were significantly higher in patients than those in healthy controls (p < 0.05); these increases were significantly associated with PSP rating scale and cognitive function scores (p < 0.05). The lactate level was high in patients, and correlated significantly with high myo-inositol levels. Histological analysis of the anterior cingulate cortex in patients revealed reactive astrocytes, despite mild tau deposition, and no marked synaptic loss. INTERPRETATION: We discovered high levels of astrocyte biomarkers in patients with PSP, suggesting astrocyte reactivity. The association between myo-inositol and lactate levels suggests a link between reactive astrocytes and brain energy metabolism changes. Our results indicate that astrocyte reactivity in the anterior cingulate cortex precedes pronounced tau pathology and neurodegenerative processes in that region, and affects brain function in PSP. ANN NEUROL 2024;96:247-261.
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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 | 0.000 |
| 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".