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Record W2238446973 · doi:10.1007/978-1-59745-060-7_2

Patterning Mouse and Human Embryonic Stem Cells Using Micro-contact Printing

2008· article· en· W2238446973 on OpenAlexaff
Raheem Peerani, Céline L. Bauwens, Eugenia Kumacheva, Peter W. Zandstra

Bibliographic record

VenueMethods in molecular biology · 2008
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEmbryonic stem cellCell biologyStem cellBiologyMaterials scienceGenetics

Abstract

fetched live from OpenAlex

Local micro-environmental cues consisting of soluble cytokines, extra-cellular matrix (ECM), and cell-cell contacts are determining factors in stem cell fate. These extrinsic cues form a 'niche' that governs a stem cell's decision to either self-renew or differentiate into one or more cell types. Recently, it has been shown that micro-patterning stem cells in two- and three-dimensions can provide direct control over several parameters of the local micro-environment, including colony size, distance between colonies, ECM substrate, and homotypic or heterotypic cell-cell contact. The protocol described here uses micro-contact printing to pattern ECM onto tissue culture substrates. Cells are seeded onto the patterned substrates in serum-free media and are confined to the patterned features. After patterning, stem cell phenotype is analyzed using quantitative immunocytochemistry and immunohistochemistry.

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)0.001
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: none
Teacher disagreement score0.154
Threshold uncertainty score0.771

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.050
GPT teacher head0.387
Teacher spread0.338 · 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

Citations40
Published2008
Admission routes1
Has abstractyes

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