MétaCan
Menu
Back to cohort
Record W2148116135 · doi:10.1177/0883911507078192

Self-renewal and Proliferation of Murine Embryonic Stem Cells: A Study of Glycosaminoglycans Effect on Feeder-Free Cultures

2007· article· en· W2148116135 on OpenAlexafffund
Shahriar Hojjati Emami, Muhammad Arshad S. Chaudhry

Bibliographic record

VenueJournal of Bioactive and Compatible Polymers · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsUniversity of British Columbia
FundersStem Cell Network
KeywordsChondroitin sulfateGlycosaminoglycanHeparinGelatinEmbryonic stem cellChemistryHeparan sulfateStem cellCell biologyChondroitinFibroblastMolecular biologyBiochemistryBiologyIn vitro

Abstract

fetched live from OpenAlex

The self-renewal and proliferation of murine embryonic stem (ES) cells can be preserved indefinitely in the presence of the mouse embryonic fibroblast (MEF) feeder layer. Since the feeder layer has several drawbacks, including viral contamination and large-scale production, gelatin solutions are the most prominent alternative to replacing it. In this investigation, self-renewal and proliferation of ES cells was carried out by supplementing the gelatin solution with glycosaminoglycan components, such as chondroitin sulfate and heparin. The methylcellulose-based embryoid body (EB) assay was used to evaluate the self-renewal ability of the ES cells. Chondroitin sulfate and heparin were mixed with 0.1% gelatin solution in 0:100, 50:50 and 100:0 (heparin/chondroitin sulfate) ratios and compared with 0.1% gelatin (positive control) and MEF (negative control) in three independent parallel experiments. Chondroitin sulfate addition to 0.1% gelatin enhanced the cell population and the number of EBs by 57 and 32%, respectively.

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 head0.010
GPT teacher head0.271
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

Citations3
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Bioactive and Compatible PolymersSame topicPluripotent Stem Cells ResearchFrench-language works237,207