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Record W2053771385 · doi:10.1073/pnas.1303386110

Retinoblastoma tumor suppressor protein in pancreatic progenitors controls α- and β-cell fate

2013· article· en· W2053771385 on OpenAlexafffund
Erica P. Cai, Xiaohong Wu, Stephanie A. Schroer, Andrew Elia, M. Cristina Nostro, Eldad Zacksenhaus, Minna Woo

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2013
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health ResearchCanadian Diabetes Association
KeywordsProgenitor cellBiologyNeogenesisIsletEndocrinologyInternal medicineRetinoblastomaCell biologyCell growthRetinoblastoma proteinPopulationEnteroendocrine cellCellSuppressorStem cellEndocrine systemCell cycleInsulinMedicineGenetics

Abstract

fetched live from OpenAlex

Pancreatic endocrine cells expand rapidly during embryogenesis by neogenesis and proliferation, but during adulthood, islet cells have a very slow turnover. Disruption of murine retinoblastoma tumor suppressor protein (Rb) in mature pancreatic β-cells has a limited effect on cell proliferation. Here we show that deletion of Rb during embryogenesis in islet progenitors leads to an increase in the neurogenin 3-expressing precursor cell population, which persists in the postnatal period and is associated with increased β-cell mass in adults. In contrast, Rb-deficient islet precursors, through repression of the cell fate factor aristaless related homeobox, result in decreased α-cell mass. The opposing effect on survival of Rb-deficient α- and β-cells was a result of opposing effects on p53 in these cell types. As a consequence, loss of Rb in islet precursors led to a reduced α- to β-cell ratio, leading to improved glucose homeostasis and protection against diabetes.

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 score0.002

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 head0.019
GPT teacher head0.261
Teacher spread0.242 · 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

Citations16
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of Sciences→Same topicPancreatic function and diabetes→French-language works237,207→