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Record W4295959588 · doi:10.1016/j.scr.2022.102919

Generation of patient-derived pluripotent stem cell-lines and CRISPR modified isogenic controls with mutations in the Parkinson’s associated GBA gene

2022· article· en· W4295959588 on OpenAlexafffund
Carol X.‐Q. Chen, Éric Deneault, Narges Abdian, Zhipeng You, Julien Sirois, Michaël Nicouleau, Irina Shlaifer, L. Gutiérrez Villegas, Marie‐Noëlle Boivin, Lydiane Gaborieau, Jason Karamchandani, Lenore K. Beitel, Edward A. Fon, Thomas M. Durcan

Bibliographic record

VenueStem Cell Research · 2022
Typearticle
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsMontreal Neurological Institute and HospitalMcGill University
FundersCanadian Institutes of Health ResearchCanada First Research Excellence FundQuébec Consortium for Drug DiscoveryMcGill University
KeywordsBiologyInduced pluripotent stem cellGlucocerebrosidaseCRISPRGenome editingParkinson's diseaseGeneticsMutationStem cellGeneEmbryonic stem cellCell biologyDiseasePathology

Abstract

fetched live from OpenAlex

The GBA gene encodes the lysosomal enzyme glucocerebrosidase (GCase), responsible for the hydrolysis of glucocerebroside to glucose and ceramide. Heterozygous GBA mutations have been associated with the development of Parkinson's disease (PD) and dementia with Lewy bodies (DLB). We generated two induced pluripotent stem cell (iPSC) lines from PD patients carrying heterozygous GBA W378G or N370S mutations and subsequently produced isogenic control lines using CRISPR/Cas9 genome editing. The patient-derived iPSCs and isogenic control lines maintained full pluripotency, normal karyotypes, and differentiation capacity. All iPSC lines could be differentiated into dopaminergic neurons, thus providing valuable tools for studying PD 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 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)0.001
metaresearch head score (Gemma)0.001
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 score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.086
GPT teacher head0.326
Teacher spread0.240 · 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
Published2022
Admission routes2
Has abstractyes

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