SMN1 copy number as a modifying factor of survival in Serbian patients with sporadic amyotrophic lateral sclerosis
Bibliographic record
Abstract
Introduction/Objective. Amyotrophic lateral sclerosis (ALS) is a devastating motor neuron disease. The majority of cases are apparently sporadic ALS (SALS) with variants in susceptibility genes or sometimes in high-risk ALS genes. Two ALS susceptibility genes are SMN1, whose functional loss causes spinal muscular atrophy (SMA), and a nearly identical SMN2 gene, which modulates SMA severity. In this study we examined the association of copy number variations (CNVs) of SMN1 and SMN2 genes and two additional genes, SERF1 and NAIP, residing in the same genomic region (i.e. 5q13.2 segmental duplication), with SALS in patients from Serbia. Methods. Multiplex ligation-dependent probe amplification was used to determine CNVs of each gene in a clinically well-characterised group of 153 Serbian SALS patients and 153 controls. Results. Individual association between SMN1, SMN2, SERF1 or NAIP CNVs and SALS susceptibility or survival was not found. Survival curves based on the multivariable Cox regression analysis showed that three SMN1 copies, lower ALS Functional Rating Scale Revised (ALSFRS-R) score at the time of diagnosis, faster decline of the ALSFRS-R score over time, and shorter diagnostic delay result in shorter survival of Serbian SALS patients. Conclusion. Clinical variables might be complemented with the SMN1 copy number to improve prediction of survival in Serbian SALS patients.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".