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Record W2082112715 · doi:10.1021/pr400099j

Adaptation of a Commonly Used, Chemically Defined Medium for Human Embryonic Stem Cells to Stable Isotope Labeling with Amino Acids in Cell Culture

2013· article· en· W2082112715 on OpenAlexaboutno aff
Albert Ryszard Liberski, Muna N. Al-Noubi, Zahra H. Rahman, Najeeb Halabi, Shaima S. Dib, Rasha Al-Mismar, A. Billing, Roopesh Krishnankutty, Faizzan S. Ahmad, Christophe M. Raynaud, Arash Rafii, Kasper Engholm‐Keller, Johannes Graumann

Bibliographic record

VenueJournal of Proteome Research · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsnot available
FundersWeill Cornell Medical CollegeQatar National Research FundNational Institutes of HealthQatar Foundation
KeywordsStable isotope labeling by amino acids in cell cultureEmbryonic stem cellQuantitative proteomicsProteomicsBiologyCell cultureContext (archaeology)Cell biologyBiochemistryComputational biologyProteomeAmino acidChemistryMolecular biologyGeneticsGene

Abstract

fetched live from OpenAlex

Metabolic labeling with stable isotopes is a prominent technique for comparative quantitative proteomics, and stable isotope labeling with amino acids in cell culture (SILAC) is the most commonly used approach. SILAC is, however, traditionally limited to simple tissue culture regimens and only rarely employed in the context of complex culturing conditions as those required for human embryonic stem cells (hESCs). Classic hESC culture is based on the use of mouse embryonic fibroblasts (MEFs) as a feeder layer, and as a result, possible xenogeneic contamination, contribution of unlabeled amino acids by the feeders, interlaboratory variability of MEF preparation, and the overall complexity of the culture system are all of concern in conjunction with SILAC. We demonstrate a feeder-free SILAC culture system based on a customized version of a commonly used, chemically defined hESC medium developed by Ludwig et al. and commercially available as mTeSR1 [mTeSR1 is a trade mark of WiCell (Madison, WI) licensed to STEMCELL Technologies (Vancouver, Canada)]. This medium, together with adjustments to the culturing protocol, facilitates reproducible labeling that is easily scalable to the protein amounts required by proteomic work flows. It greatly enhances the usability of quantitative proteomics as a tool for the study of mechanisms underlying hESCs differentiation and self-renewal. Associated data have been deposited to the ProteomeXchange with the identifier PXD000151.

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)0.002
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 score0.009
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
Research integrity0.0000.001
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 head0.044
GPT teacher head0.320
Teacher spread0.275 · 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

Citations10
Published2013
Admission routes1
Has abstractyes

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