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Record W2054241460 · doi:10.1369/jhc.2010.955682

Nestin Action During Insulin-secreting Cell Differentiation

2010· article· en· W2054241460 on OpenAlexaff
So Yoon Kim, Song Lee, Seok‐Woo Hong, Bon-Hong Min, Ki‐Up Lee, Moı̈se Bendayan, In-Sun Park

Bibliographic record

VenueJournal of Histochemistry & Cytochemistry · 2010
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversité de Montréal
FundersKorea Science and Engineering Foundation
KeywordsNestinStem cellBiologyHomeobox protein NANOGCell biologyCellular differentiationNeural stem cellAdult stem cellEmbryoid bodyStem cell markerEmbryonic stem cellInduced pluripotent stem cell

Abstract

fetched live from OpenAlex

Nestin, which was initially identified as a marker of neural stem cells, has been reported in regenerating pancreas as well as in early embryonic stem (ES) cell derivatives. However, little is known about its specific roles in stem cells as a functional regulator. We investigated the source of the action of nestin in ES and adult pancreatic ductal stem (PDS) cells in regard to the neogenesis of insulin-secreting beta-cells. In ES cells, suppression of nestin by gene silencing led to an increased expression of the pluripotency-associated genes, including Oct 4, Nanog, and SSEA-1, before embryoid body (EB) formation, whereas it reduced endodermal and pancreatic transcription factors in EBs. Inhibition of nestin expression in adult PDS cells caused a low expression of pancreatic transcription factors and islet hormones, leading to poor beta-cell development and insulin secretion. These data may indicate not only that nestin is a simple stem cell marker, but also that it constitutes a functional factor at the time of stem cell differentiation. We suggest that nestin plays pivotal roles as an intermediate regulator governing both stemness and differentiation of stem cells in the process of their differentiation into insulin-secreting cells.

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)0.001
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 score0.008
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
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 head0.010
GPT teacher head0.244
Teacher spread0.234 · 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

Citations17
Published2010
Admission routes1
Has abstractyes

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