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Record W1968683223 · doi:10.1139/bcb-2012-0094

Supraphysiological expression of survival motor neuron protein from an adenovirus vector does not adversely affect cell function

2013· article· en· W1968683223 on OpenAlexafffundvenue
Benoit Goulet, Emily McFall, Carmen Wong, Rashmi Kothary, Robin J. Parks

Bibliographic record

VenueBiochemistry and Cell Biology · 2013
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health ResearchMultiple Sclerosis SocietyOttawa Hospital Research Institute
KeywordsSpinal muscular atrophyBiologyMotor neuronSMA*CellViral vectorAlternative splicingCell biologyCell typeRNA splicingCancer researchGeneNeuroscienceGeneticsExonSpinal cordRNA

Abstract

fetched live from OpenAlex

Spinal muscular atrophy (SMA) is the most common inherited neurodegenerative disease that leads to infant mortality. It is caused by mutations in the survival motor neuron (SMN) protein resulting in death of alpha motor neurons. Increasing evidence suggests that several other tissues are also affected in SMA, including skeletal and cardiac muscle, liver, and pancreas, indicating that systemic delivery of therapeutics may be necessary for true disease correction. Due to the natural biodistribution of therapeutics, a level of SMN several-fold above physiological levels can be achieved in some tissues. In this study, we address whether supraphysiological levels of SMN adversely affects cell function. Infection of a variety of cell types with an adenovirus (Ad) vector encoding SMN leads to very high expression, but the resulting protein correctly localizes within the cell, and associates with normal cellular partners. Although SMN affects transcription of certain target genes and can alter the splicing pattern of others, we did not observe any difference in select target gene splicing or expression in cells overexpressing SMN. However, normal human fibroblasts treated with Ad-SMN showed a slight reduction in growth rate, suggesting that certain cell types may be differently impacted by high levels of SMN.

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 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 score0.038
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.014
GPT teacher head0.254
Teacher spread0.239 · 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 teacher head, 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

Citations7
Published2013
Admission routes3
Has abstractyes

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