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Record W3107306959 · doi:10.1126/science.aaz2121

The N-glycome regulates the endothelial-to-hematopoietic transition

2020· article· en· W3107306959 on OpenAlexaff
Dionna M. Kasper, Jared Hintzen, Yinyu Wu, Joey J. Ghersi, Hanna K. Mandl, Kevin E. Salinas, William Armero, Zhiheng He, Ying Sheng, Yixuan Xie, Daniel W. Heindel, Eon Joo Park, William C. Sessa, Lara K. Mahal, Carlito B. Lebrilla, Karen K. Hirschi, Stefania Nicoli

Bibliographic record

VenueScience · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicZebrafish Biomedical Research Applications
Canadian institutionsUniversity of Alberta
FundersNational Institute of General Medical SciencesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood InstituteNational Institutes of HealthAmerican Heart Association
KeywordsGlycomeHaematopoiesisTransition (genetics)Hematopoietic cellBiologyComputational biologyCell biologyEvolutionary biologyGeneticsStem cellGlycoproteinGene

Abstract

fetched live from OpenAlex

Sugar code regulates blood stem cells During embryonic development, blood stem cells are derived from vascular endothelial cells that line the walls of developing arteries. The transition from endothelial cells to blood stem cells is highly regulated and restricted to a small portion of endothelial cells during a brief period of time. The mechanisms regulating this transition are also poorly understood. Kasper et al. found that microRNA-223 intrinsically restrains the vascular hematopoietic transition by regulating N-glycan biosynthesis to restrict hematopoietic stem and progenitor cell production and differentiation. Genetics or chemicals could be used to alter the sugar code and change the efficiency of blood production in embryos. Thus, genetically or pharmacologically altering N-glycan biosynthesis in endothelial cells could improve the efficiency of the production of blood stem cells, which could then be used to treat blood diseases such as leukemia. Science , this issue p. 1186

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 score0.287
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.284
Teacher spread0.270 · 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

Citations47
Published2020
Admission routes1
Has abstractyes

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