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Record W4409470661 · doi:10.1038/s41540-025-00515-z

Single cell RNAseq to identify subpopulations of glial progenitors in iPSC-derived oligodendroglial lineage cultures

2025· article· en· W4409470661 on OpenAlexafffund
Gabriela J. Blaszczyk, Valerio E. C. Piscopo, Taylor Goldsmith, Alexandra Chapleau, Julien Sirois, Geneviève Bernard, Jack P. Antel, Thomas M. Durcan

Bibliographic record

Venuenpj Systems Biology and Applications · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsMcGill UniversityMcGill University Health CentreMcGill Genome CentreMontreal Neurological Institute and Hospital
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchCanada First Research Excellence FundMcGill University
KeywordsLineage (genetic)BiologyProgenitor cellProgenitorOligodendroglial TumorCell biologyComputational biologyGeneticsStem cellGeneOligodendroglioma

Abstract

fetched live from OpenAlex

Cellular heterogeneity is a common issue in differentiation protocols of oligodendrocytes (OLs) from human induced pluripotent stem cells. Our previous work described a novel method to generate OLs and highlighted the presence of glial progenitors. Here, we unravel the glial heterogeneity and characterize the response of isolated subpopulations to differentiation. This study provides a novel tool for studying the dynamics of glial development in vitro and on a transcriptomic level.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.477

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 head0.029
GPT teacher head0.334
Teacher spread0.306 · 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 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

Citations1
Published2025
Admission routes2
Has abstractyes

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