Serial changes in regional cerebral blood flow in Gerstmann–Sträussler–Scheinker disease caused by a Pro-to-Leu mutation at codon 105 in the prion protein gene
Bibliographic record
Abstract
Gerstmann-Sträussler-Scheinker disease with a Pro-to-Leu substitution at codon 105 in the prion protein gene (GSS-P105L) is a rare variant of human genetic prion disease. Herein, we report the case of a patient with GSS-P105L, who showed serial changes in regional cerebral blood flow (rCBF) on single-photon emission computed tomography (SPECT). A 42-year-old woman, with an affected father presenting with similar symptoms, had a 1-year history of progressive gait disturbance, lower-limb spasticity, and psychiatric symptoms. Genetic analysis confirmed the diagnosis of GSS-P105L. Eleven months after disease onset, brain magnetic resonance imaging (MRI) showed bilateral frontal lobe-dominant cerebral atrophy without hyperintensity on diffusion-weighted imaging (DWI) sequences; meanwhile, SPECT revealed non-specific mild hypoperfusion. Follow-up MRI at 52 months after onset demonstrated progressive frontal lobe-dominant cerebral atrophy without hyperintensity on DWI, while SPECT revealed a marked decrease in rCBF in the bilateral right-dominant frontal lobe. Patients with GSS with a Pro-to-Leu substitution at codon 102 (GSS-P102L) have been reported to exhibit hyperintensity on DWI-MRI and a diffuse decrease in CBF with a mosaic-like pattern on SPECT, which is absent in patients with GSS-P105L, thereby possibly reflecting the differences in pathophysiology between GSS-P102L and GSS-P105L.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".