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Record W2060481500 · doi:10.4161/worm.29047

Deciphering genetic interactions between ALS genes using<i>C. elegans</i>

2014· article· nl· W2060481500 on OpenAlexaff
Martine Therrien, J. Alex Parker

Bibliographic record

VenueWorm · 2014
Typearticle
Languagenl
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsC9orf72Amyotrophic lateral sclerosisNeurodegenerationFrontotemporal dementiaTARDBPGeneBiologyGeneticsCaenorhabditis elegansNeuroscienceDementiaMutantSOD1DiseaseTrinucleotide repeat expansionMedicineAllele

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.004

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.

Opus teacher head0.063
GPT teacher head0.344
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2014
Admission routes1
Has abstractyes

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