Adaptation of a Commonly Used, Chemically Defined\nMedium for Human Embryonic Stem Cells to Stable Isotope Labeling with\nAmino Acids in Cell Culture
Bibliographic record
Abstract
Metabolic\nlabeling with stable isotopes is a prominent technique\nfor comparative quantitative proteomics, and stable isotope labeling\nwith amino acids in cell culture (SILAC) is the most commonly used\napproach. SILAC is, however, traditionally limited to simple tissue\nculture regimens and only rarely employed in the context of complex\nculturing conditions as those required for human embryonic stem cells\n(hESCs). Classic hESC culture is based on the use of mouse embryonic\nfibroblasts (MEFs) as a feeder layer, and as a result, possible xenogeneic\ncontamination, contribution of unlabeled amino acids by the feeders,\ninterlaboratory variability of MEF preparation, and the overall complexity\nof the culture system are all of concern in conjunction with SILAC.\nWe demonstrate a feeder-free SILAC culture system based on a customized\nversion of a commonly used, chemically defined hESC medium developed\nby Ludwig et al. and commercially available as mTeSR1 [mTeSR1 is a\ntrade mark of WiCell (Madison, WI) licensed to STEMCELL Technologies\n(Vancouver, Canada)]. This medium, together with adjustments to the\nculturing protocol, facilitates reproducible labeling that is easily\nscalable to the protein amounts required by proteomic work flows.\nIt greatly enhances the usability of quantitative proteomics as a\ntool for the study of mechanisms underlying hESCs differentiation\nand self-renewal. Associated data have been deposited to the ProteomeXchange\nwith the identifier PXD000151.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".