Correlation between clinical and radiologic features of patients with Gerstmann-Sträussler-Scheinker syndrome (Pro102Leu)
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Gerstmann-Sträussler-Scheinker syndrome is a rare hereditary neurodegenerative disorder with clinical heterogeneity. This study is aim to demonstrate the clinical spectrum and radiologic characteristics of patients caused by Pro102Leu mutation in PRNP. MATERIALS AND METHODS: We retrospect clinical manifestations of five patients from four Japanese families, and comprehensively analyzed their brain MRI, SPECT (N-isopropyl-p-[123I] iodoamphetamine), and PET (18F-2-fluoro-2-deoxy-d-glucose) images. RESULTS: All patients developed ataxia of lower limbs and trunk, gait disturbance, dysesthesia in legs, and lower limb hyporeflexia. In the early clinical stage before dementia began, no noticeable abnormalities could be observed from brain MRI, but SPECT and PET revealed mosaic-like pattern of blood flow and glucose metabolism of the brain. Predominant abnormalities were found in the occipital and frontal lobes on SPECT and PET analysis, respectively. In SPECT analysis, blood flow of the anterior cerebellar lobes was lower than that of the posterior cerebellar lobes. CONCLUSIONS: Clinical symptoms resulting from failure of dorsal horn of spinal cord and spinocerebellar tracts were observed in all cases. Radiologic findings revealed individual differences of involved region in their brain, which could produce clinical diversity. We identified a downtrend of blood flow in the anterior cerebellar lobes, a projection field of the spinocerebellar tracts, which is an important feature of Gerstmann-Sträussler-Scheinker syndrome.
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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) | 0.002 | 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".