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Record W1590631407 · doi:10.1002/jcp.24681

microRNA‐Mediated Survivin Control of Pluripotency

2014· article· en· W1590631407 on OpenAlexaff
Kristina Kapinas, Heesun Kim, Matthew Mandeville, Lori A. Martin‐Buley, Carlo M. Croce, Jane B. Lian, André J. van Wijnen, Janet L. Stein, Dario C. Altieri, Gary S. Stein

Bibliographic record

VenueJournal of Cellular Physiology · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsStemcell Technologies
FundersNational Institute of Dental and Craniofacial ResearchNational Cancer InstituteNational Institute on AgingNational Institutes of Health
KeywordsSurvivinHomeobox protein NANOGNanog Homeobox ProteinEmbryonic stem cellBiologymicroRNACell biologyGene isoformCancer cellTranscription factorSOX2Cancer researchInduced pluripotent stem cellCancerGeneticsGene

Abstract

fetched live from OpenAlex

Understanding the mechanisms that sustain pluripotency in human embryonic stem cells (hESCs) is an active area of research that may prove useful in regenerative medicine and will provide fundamental information relevant to development and cancer. hESCs and cancer cells share the unique ability to proliferate indefinitely and rapidly. Because the protein survivin is uniquely overexpressed in virtually all human cancers and in hESCs, we sought to investigate its role in supporting the distinctive capabilities of these cell types. Results presented here suggest that survivin contributes to the maintenance of pluripotency and that post-transcriptional control of survivin isoform expression is selectively regulated by microRNAs. miR-203 has been extensively studied in human tumors, but has not been characterized in hESCs. We show that miR-203 expression and activity is consistent with the expression and subcellular localization of survivin isoforms that in turn modulate expression of the Oct4 and Nanog transcription factors to sustain pluripotency. This study contributes to understanding of the complex regulatory mechanisms that govern whether hESCs proliferate or commit to lineages.

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)0.001
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 score0.030
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.006
GPT teacher head0.225
Teacher spread0.219 · 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

Citations15
Published2014
Admission routes1
Has abstractyes

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