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Record W2899799360 · doi:10.1111/jcmm.13889

Bmi‐1 high‐expressing cells enrich cardiac stem/progenitor cells and respond to heart injury

2018· article· en· W2899799360 on OpenAlexaff
Yuewang Song, Mengmeng Zhao, Yuan Xie, Tingfang Zhu, Wenbin Liang, Baiming Sun, Weixin Liu, Liqun Wu, Guoping Lü, Tao‐Sheng Li, Tong Yin

Bibliographic record

VenueJournal of Cellular and Molecular Medicine · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsUniversity of Ottawa
FundersNational Natural Science Foundation of China
KeywordsSide populationProgenitor cellStem cellBiologyPopulationFlow cytometryCell biologyMyocardial infarctionProgenitorInternal medicineAndrologyImmunologyMedicineCancer stem cell

Abstract

fetched live from OpenAlex

Abstract Bmi‐1 gene is well recognized as an oncogene, but has been recently demonstrated to play a role in the self‐renewal of tissue‐specific stem cells. By using Bmi‐1GFP/+ mice, we investigated the role of Bmi‐1 in cardiac stem/progenitor cells and myocardial repair. RT‐PCR and flow cytometry analysis indicated that the expression of Bmi‐1 was significantly higher in cardiac side population than the main population from CD45−Ter119−CD31− heart cells. More Sca‐1+ cardiac stem/progenitor cells were found in Bmi‐1 GFPhi subpopulation, and these Bmi‐1 GFPhi heart cells showed the potential of differentiation into SMM+ smooth muscle‐like cells and TnT+ cardiomyocyte‐like cells in vitro. The silencing of Bmi‐1 significantly inhibited the proliferation and differentiation of heart cells. Otherwise, myocardial infarction induced a significantly increase (2.7‐folds) of Bmi‐1 GFPhi population, mainly within the infarction and border zones. These preliminary data suggest that Bmi‐1hi heart cells are enriched in cardiac stem/progenitor cells and may play a role in myocardial repair.

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 score0.003
Threshold uncertainty score0.009

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.270
Teacher spread0.261 · 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

Citations11
Published2018
Admission routes1
Has abstractyes

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