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Record W2614562038 · doi:10.1002/acn3.423

New insights into SMA pathogenesis: immune dysfunction and neuroinflammation

2017· article· en· W2614562038 on OpenAlexafffund
Marc‐Olivier Deguise, Rashmi Kothary

Bibliographic record

VenueAnnals of Clinical and Translational Neurology · 2017
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersE-RareCanadian Institutes of Health ResearchCure SMAServierMuscular Dystrophy Association
KeywordsMedicineNeuroinflammationPathogenesisSMA*Immune DysfunctionImmune systemImmunologyNeuroscienceInflammationBiology

Abstract

fetched live from OpenAlex

Spinal muscular atrophy (SMA) is a neuromuscular disorder characterized by motor neuron degeneration, although defects in multiple cell types and tissues have also been implicated. Three independent laboratories recently identified immune organ defects in SMA. We therefore propose a novel pathogenic mechanism contributory to SMA, resulting in higher susceptibility to infection and exacerbated disease progression caused by neuroinflammation. Overall, compromised immune function could significantly affect survival and quality of life of SMA patients. We highlight the recent findings in immune organ defects, their potential consequences on patients, our understanding of neuroinflammation in SMA, and new research hypotheses in SMA pathogenesis.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.441
Threshold uncertainty score0.316

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)0.0000.000

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 head0.112
GPT teacher head0.411
Teacher spread0.299 · 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 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

Citations49
Published2017
Admission routes2
Has abstractyes

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