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Record W3166794517 · doi:10.1073/pnas.2022115118

Chemical and genetic rescue of in vivo progranulin-deficient lysosomal and autophagic defects.

2021· article· en· W3166794517 on OpenAlexaff
James J Doyle, Claudia Maios, Céline Vrancx, Sarah Duhaime, Babykumari P. Chitramuthu, H.P.J. Bennett, Andrew Bateman, J. Alex Parker

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2021
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsMcGill UniversityCentre Hospitalier de l’Université de MontréalUniversité de MontréalMcGill University Health Centre
FundersNational Institutes of Health
KeywordsNeurodegenerationBiologyAutophagyFrontotemporal dementiaPhenotypeGenetic screenNeuroscienceComputational biologyMutationModel organismDiseaseGeneticsGeneDementiaMedicinePathology

Abstract

fetched live from OpenAlex

Significance Uncovering the genetic and cellular mechanisms of frontotemporal dementia (FTD) may lead to new therapeutic strategies. Mutations in the GRN gene are linked to FTD; the underlying cellular mechanisms are still unknown, but current research points to lysosomal dysfunction. Using the model organism Caenorhabditis elegans , we found a link between pgrn-1 / GRN mutations, and sphingolipid metabolism and autophagy. We further identified small molecules that attenuated several pgrn-1 / GRN phenotypes in vivo. These results offer sphingolipid metabolism as a potential mechanism contributing to FTD pathogenesis and suggest that efforts to restore sphingolipid homeostasis may be a beneficial therapeutic approach.

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 score0.006

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.320
Teacher spread0.281 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicAmyotrophic Lateral Sclerosis ResearchFrench-language works237,207