Peripheral Blood mRNA Profiling of SGCE and TOR1A in Myoclonus-Dystonia Syndrome: A Genetic Expression Study.
Bibliographic record
Abstract
Myoclonus-Dystonia (M-D) is a rare autosomal-dominant movement disorder characterized by myoclonic jerks and dystonic symptoms. Myoclonus-Dystonia has been linked to mutations affecting the epsilon-sarcoglycan (SGCE, DYT11) gene. The syndrome has also been associated with mutations in the TOR1A (DYT1) gene. Herein we propose for the first time a link between the mRNA expression levels of SGCE and TOR1A. The main aim of this study was to detect the SGCE and TOR1A mRNA levels in peripheral blood of M-D patients and to explore the correlation between their mRNA levels. We have demonstrated that SGCE mRNA was highly expressed in peripheral blood of M-D patients compared to healthy controls (P = 0.04). We also observed that TOR1A mRNA levels were markedly higher in M-D patients than in healthy controls (P = 0.009). Furthermore, we have demonstrated a significant positive correlation between the SGCE and TOR1A mRNA levels in M-D patients (r = 0.659, p = 0.01). These findings suggest that the analysis of SGCE and TOR1A mRNA levels in peripheral blood could serve as a potential molecular biomarker for distinguishing M-D patients from healthy controls.
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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".