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Record W4303473191 · doi:10.1101/2022.10.07.511246

Surface glia predominantly contribute to the development of ALS/FTD in <i>Drosophila</i> model

2022· preprint· en· W4303473191 on OpenAlexafffund
Brittany Anne Snow, Ciara Crowley Stevenson, Jasdeep Kaur, Seung Gee Lee, Yanan Wei, Hongyu Miao, Woo Jae Kim

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsUniversity of Ottawa
FundersMitacsNational Research FoundationUniversity of OttawaNational Institutes of HealthNvidia
KeywordsAmyotrophic lateral sclerosisC9orf72NeuroscienceDrosophila melanogasterMotor neuronBiologyDiseaseMutationPathogenesisTrinucleotide repeat expansionGeneMedicineGeneticsImmunologyPathology

Abstract

fetched live from OpenAlex

ABSTRACT Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disorder characterized by motor neuron degeneration in the primary motor neurons. C9orf72 repeat expansion mutation is the most prevalent genetic causes of ALS/FTD. Due to the complexity of ALS, there has been no successful therapy for the condition. The traditional neurocentric concept of ALS derives in part from the assumption that the degradation of motor neuron (MN) cells in ALS is driven by cell-autonomous mechanisms, however, recent research has focused on the non-cell-autonomous pathogenic mechanisms such as glial, immune cells and blood-brain barriers participate in the degeneration of MNs in ALS. Drosophila melanogaster is widely used as a genetic model for ALS, giving essential mechanistic data on disease onset and development. Using newly developed genetic tools to individually mark each subtype of the adult glial system in the fruit fly, we demonstrate that surface glia are the major glial subtypes for the pathogenesis of C9orf72 -mediated ALS/FTD.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.030
GPT teacher head0.273
Teacher spread0.243 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicAmyotrophic Lateral Sclerosis Research→French-language works237,207→