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Record W2105213907 · doi:10.1002/jnr.22044

N‐cadherin mediates interaction between precursor cells in the subventricular zone and regulates further differentiation

2009· article· en· W2105213907 on OpenAlexaff
Yoshiki Yagita, Takeshi Sakurai, Hidekazu Tanaka, Kazuo Kitagawa, David Colman, Weisong Shan

Bibliographic record

VenueJournal of Neuroscience Research · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeurogenesis and neuroplasticity mechanisms
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersNational Institute of Neurological Disorders and Stroke
KeywordsSubventricular zoneNeurogenesisCell biologyRostral migratory streamCadherinNeurosphereBiologyCellPrecursor cellCell adhesion moleculeCellular differentiationStem cellNeural stem cellAdult stem cellGenetics

Abstract

fetched live from OpenAlex

Neurogenesis and cell differentiation in the brain continues throughout life. In the subventricular zone and rostral migratory stream, precursor cells contact each other. Cell-cell interactions mediated via adhesion molecules are no doubt involved in establishing and maintaining the neurogenic ability of these cells. Here, we demonstrate that N-cadherin plays important roles in forming cell clusters and in regulating cell differentiation. N-cadherin is abundantly expressed in chain migrating cells in the subventricular zone and rostral migratory stream but is down-regulated after cells exit these regions. We also show that neurosphere formation is inhibited via suppression of N-cadherin function and that N-cadherin expression is decreased after induction of neurosphere differentiation. Furthermore, we demonstrate that functional blockade of N-cadherin can enhance glial cell differentiation in explant cultures of precursors from the subventricular zone.

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 score0.001
Threshold uncertainty score0.004

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.104
GPT teacher head0.362
Teacher spread0.258 · 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

Citations45
Published2009
Admission routes1
Has abstractyes

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