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Record W1874599540 · doi:10.1074/jbc.m111.312769

Loss of Protein-tyrosine Phosphatase α (PTPα) Increases Proliferation and Delays Maturation of Oligodendrocyte Progenitor Cells

2012· article· en· W1874599540 on OpenAlexafffund
Pei‐Shan Wang, Jing Wang, Yi Zheng, Catherine J. Pallen

Bibliographic record

VenueJournal of Biological Chemistry · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Tyrosine Phosphatases
Canadian institutionsChild and Family Research InstituteUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsCell biologyProgenitor cellBiologyEmbryonic stem cellProtein tyrosine phosphataseNeural stem cellOligodendrocyteFYNStem cellCellular differentiationMyelinTyrosine kinaseSignal transductionEndocrinologyBiochemistry

Abstract

fetched live from OpenAlex

Tightly controlled termination of proliferation determines when oligodendrocyte progenitor cells (OPCs) can initiate differentiation and mature into myelin-forming cells. Protein-tyrosine phosphatase α (PTPα) promotes OPC differentiation, but its role in proliferation is unknown. Here we report that loss of PTPα enhanced in vitro proliferation and survival and decreased cell cycle exit and growth factor dependence of OPCs but not neural stem/progenitor cells. PTPα(-/-) mice have more oligodendrocyte lineage cells in embryonic forebrain and delayed OPC maturation. On the molecular level, PTPα-deficient mouse OPCs and rat CG4 cells have decreased Fyn and increased Ras, Cdc42, Rac1, and Rho activities, and reduced expression of the Cdk inhibitor p27Kip1. Moreover, Fyn was required to suppress Ras and Rho and for p27Kip1 accumulation, and Rho inhibition in PTPα-deficient cells restored expression of p27Kip1. We propose that PTPα-Fyn signaling negatively regulates OPC proliferation by down-regulating Ras and Rho, leading to p27Kip1 accumulation and cell cycle exit. Thus, PTPα acts in OPCs to limit self-renewal and facilitate differentiation.

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 score0.028
Threshold uncertainty score0.527

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 head0.011
GPT teacher head0.238
Teacher spread0.227 · 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

Citations12
Published2012
Admission routes2
Has abstractyes

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