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Record W2345723214 · doi:10.1242/dev.118638

RGMB and neogenin control cell differentiation in the developing olfactory epithelium

2016· article· en· W2345723214 on OpenAlexafffund
Joseph Wai Keung Kam, Émilie Dumontier, Christopher Baim, Alexandra Brignall, David Mendes da Silva, Mitra Cowan, Timothy E. Kennedy, Jean‐François Cloutier

Bibliographic record

VenueDevelopment · 2016
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsCentre Hospitalier de l’Université de MontréalMcGill UniversityMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health Research
KeywordsBiologyOlfactory epitheliumEpitheliumCellCell biologyOlfactory systemNeuroscienceGenetics

Abstract

fetched live from OpenAlex

Cellular interactions are key for the differentiation of distinct cell types within developing epithelia, yet the molecular mechanisms engaged in these interactions remain poorly understood. In the developing olfactory epithelium (OE), neural stem/progenitor cells give rise to odorant-detecting olfactory receptor neurons (ORNs) and glial-like sustentacular (SUS) cells. Here, we show in mice that the transmembrane receptor neogenin (NEO1) and its membrane-bound ligand RGMB control the balance of neurons and glial cells produced in the OE. In this layered epithelium, neogenin is expressed in progenitor cells, while RGMB is restricted to adjacent newly born ORNs. Ablation of Rgmb via gene-targeting increases the number of dividing progenitor cells in the OE and leads to supernumerary SUS cells. Neogenin loss-of-function phenocopies these effects observed in Rgmb(-/-) mice, supporting the proposal that RGMB-neogenin signaling regulates progenitor cell numbers and SUS cell production. Interestingly, Neo1(-/-) mice also exhibit increased apoptosis of ORNs, implicating additional ligands in the neogenin-dependent survival of ORNs. Thus, our results indicate that RGMB-neogenin-mediated cell-cell interactions between newly born neurons and progenitor cells control the ratio of glia and neurons produced in the OE.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.258

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 head0.101
GPT teacher head0.233
Teacher spread0.131 · 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

Citations35
Published2016
Admission routes2
Has abstractyes

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