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Record W2051916996 · doi:10.1371/journal.pone.0095373

Gene Targeting of Mouse Tardbp Negatively Affects Masp2 Expression

2014· article· en· W2051916996 on OpenAlexafffund
Samar Dib, Shangxi Xiao, Denise Miletic, Janice Robertson

Bibliographic record

VenuePLoS ONE · 2014
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsOccupational Cancer Research CentreUniversity of Toronto
FundersCanadian Institutes of Health ResearchALS Society of Canada
KeywordsTARDBPAmyotrophic lateral sclerosisBiologyGeneticsGeneGene targetingHeterozygote advantageGene expressionRNA-binding proteinGene knockinAlleleCell biologyDiseaseRNAMutantSOD1PathologyMedicine

Abstract

fetched live from OpenAlex

Amyotrophic Lateral Sclerosis (ALS) is a devastating adult onset neurodegenerative disease affecting both upper and lower motor neurons. TDP-43, encoded by the TARDBP gene, was identified as a component of motor neuron cytoplasmic inclusions in both familial and sporadic ALS and has become a pathological signature of the disease. TDP-43 is a nuclear protein involved in RNA metabolism, however in ALS, TDP-43 is mislocalized to the cytoplasm of affected motor neurons, suggesting that disease might be caused by TDP-43 loss of function. To investigate this hypothesis, we attempted to generate a mouse conditional knockout of the Tardbp gene using the classical Cre-loxP technology. Even though heterozygote mice for the targeted allele were successfully generated, we were unable to obtain homozygotes. Here we show that although the targeting vector was specifically designed to not overlap with Tardbp adjacent genes, the homologous recombination event affected the expression of a downstream gene, Masp2. This may explain the inability to obtain homozygote mice with targeted Tardbp.

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 score0.010

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 studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.053
GPT teacher head0.263
Teacher spread0.210 · 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

Citations3
Published2014
Admission routes2
Has abstractyes

Explore more

Same venuePLoS ONE→Same topicAmyotrophic Lateral Sclerosis Research→French-language works237,207→