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Record W2061095282 · doi:10.1073/pnas.1009412107

Efficient reprogramming of adult neural stem cells to monocytes by ectopic expression of a single gene

2010· article· en· W2061095282 on OpenAlexfundno aff
Magda Forsberg, Marie Carlén, Konstantinos Meletis, Maggie S. Y. Yeung, Fanie Barnabé‐Heider, Mats A. A. Persson, Johan Aarum, Jonas Frisén

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchVetenskapsrådetKnut och Alice Wallenbergs StiftelseHjärnfondenCancerfondenKarolinska InstitutetChristopher and Dana Reeve Foundation
KeywordsReprogrammingBiologyEctopic expressionEmbryonic stem cellNeural stem cellStem cellSomatic cellCell biologyInduced stem cellsInduced pluripotent stem cellCellular differentiationAdult stem cellTranscription factorNeural developmentGeneGenetics

Abstract

fetched live from OpenAlex

Neural stem cells have a broad differentiation repertoire during embryonic development and can be reprogrammed to pluripotency comparatively easily. We report that adult neural stem cells can be reprogrammed at very high efficiency to monocytes, a differentiated fate of an unrelated somatic lineage, by ectopic expression of the Ets transcription factor PU.1. The reprogrammed cells display a marker profile and functional characteristics of monocytes and integrate into tissues after transplantation. The failure to reprogram lineage-committed neural cells to monocytes with PU.1 suggests that neural stem cells are uniquely amenable to reprogramming.

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 score0.003

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 head0.025
GPT teacher head0.292
Teacher spread0.267 · 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

Citations38
Published2010
Admission routes1
Has abstractyes

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Same venueProceedings of the National Academy of SciencesSame topicPluripotent Stem Cells ResearchFrench-language works237,207