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Record W4224280907 · doi:10.21203/rs.3.rs-1555653/v1

Transgenic TDP-43 and endogenous TDP-1 Caenorhabditis elegans ALS models show motor deficits and age-dependent neurodegeneration

2022· preprint· en· W4224280907 on OpenAlexaff
Jennifer Parker, Sarah Duhaime, Constantin Bretonneau

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsNeurodegenerationTARDBPAmyotrophic lateral sclerosisCaenorhabditis elegansTransgeneBiologyNeuroscienceMutationPhenotypeGenetically modified mouseMutantGeneticsGeneSOD1DiseaseMedicinePathology

Abstract

fetched live from OpenAlex

Abstract Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by a progressive and selective loss of motor neurons. ALS is incurable and there are no effective treatments available for people living with the disease. About 90% of the cases are sporadic whereas 10% are familial, and patients usually die two to five years after symptom onset. Many genes are associated with ALS, including mutations in the gene encoding TDP-43. We developed a transgenic Caenorhabditis elegans model expressing human mutant TDP-43(Q331K) in GABAergic motor neurons. We also obtained by mutagenesis and CRISPR-Cas9 gene-editing physiologically accurate models based on mutations in tdp-1, the C. elegans orthologue of TARDBP. Our results show that both transgenic TDP-43 and endogenous TDP-1 models recapitulate key aspects of ALS such as motor deficits and age-dependent neurodegeneration causing paralysis. However, only the TDP-43 mutation had a negative effect on lifespan. These models provide different physiological expression of mutant proteins and thus phenotypes of varying intensity levels. They will be useful tools to elucidate new pathogenic mechanisms of ALS as well as being suitable for drug discovery and therapeutic development.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.169
GPT teacher head0.371
Teacher spread0.202 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2022
Admission routes1
Has abstractyes

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