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Record W1979816193 · doi:10.1002/ajmg.a.36251

Solving the puzzle of spinal muscular atrophy: What are the missing pieces?

2013· review· en· W1979816193 on OpenAlexaff
Francesco Danilo Tiziano, Judith Melki, Louise R. Simard

Bibliographic record

VenueAmerican Journal of Medical Genetics Part A · 2013
Typereview
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSMN1SMA*Spinal muscular atrophyExonMotor neuronGeneticsGeneBiologyDiseaseMutationNeuroscienceBioinformaticsMedicinePathologyComputer science

Abstract

fetched live from OpenAlex

Spinal muscular atrophy (SMA) is an autosomal recessive, lower motor neuron disease. Clinical heterogeneity is pervasive: three infantile (type I-III) and one adult-onset (type IV) forms are recognized. Type I SMA is the most common genetic cause of death in infancy and accounts for about 50% of all patients with SMA. Most forms of SMA are caused by mutations of the survival motor neuron (SMN1) gene. A second gene that is 99% identical to SMN1 (SMN2) is located in the same region. The only functionally relevant difference between the two genes identified to date is a C → T transition in exon 7 of SMN2, which determines an alternative spliced isoform that predominantly excludes exon 7. Thus, SMN2 genes do not produce sufficient full length SMN protein to prevent the onset of the disease. Since the identification of the causative mutation, biomedical research of SMA has progressed by leaps and bounds: from clues on the function of SMN protein, to the development of different models of the disease, to the identification of potential treatments, some of which are currently in human trials. The aim of this review is to elucidate the current state of knowledge, emphasizing how close we are to the solution of the puzzle that is SMA, and, more importantly, to highlight the missing pieces of this puzzle. Filling in these gaps in our knowledge will likely accelerate the development and delivery of efficient treatments for SMA patients and be a prerequisite towards achieving our final goal, the cure of SMA.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score0.801

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.069
GPT teacher head0.395
Teacher spread0.326 · 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 designOther design
Domainnot available
GenreReview

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

Citations26
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Medical Genetics Part ASame topicNeurogenetic and Muscular Disorders ResearchFrench-language works237,207