Deciphering genetic interactions between ALS genes using<i>C. elegans</i>
Bibliographic record
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder causing selective death of motor neurons in which it is speculated that 10% of cases have a familial history. In the past 20 years, many genes causative for ALS have been discovered, but the link between them and their roles in neurodegeneration remain unknown. The identification of genes associated with both ALS and frontotemporal dementia (FTD), along with the observation of patients affected by both diseases, have suggested that they are part of the same neurodegenerative spectrum. Investigating possible genetic interactions among ALS/FTD genes could help understand the role of these genes in neurodegeneration. To pursue this goal, our group has developed several ALS models to study potential genetic interactions. More recently, we characterized the deletion mutant alfa-1, the ortholog of C9ORF72, to evaluate the potential genetic interactions between C9ORF72/alfa-1 and other ALS genes. Here, we discuss the genetic interactions identified in our models and how some of these proteins may also be linked to other neurodegenerative disorders.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".