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Record W2012377092 · doi:10.1016/j.stemcr.2015.01.004

Acellular Lung Scaffolds Direct Differentiation of Endoderm to Functional Airway Epithelial Cells: Requirement of Matrix-Bound HS Proteoglycans

2015· article· en· W2012377092 on OpenAlexaff
Sharareh Shojaie, Leonardo Ermini, Cameron Ackerley, Jinxia Wang, Stephanie Chin, Behzad Yeganeh, Mélanie Bilodeau, Manpreet Sambi, Ian M. Rogers, Janet Rossant, Christine E. Bear, Martin Post

Bibliographic record

VenueStem Cell Reports · 2015
Typearticle
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsMount Sinai HospitalLunenfeld-Tanenbaum Research InstituteHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsDecellularizationEndodermExtracellular matrixCell biologyBiologyInduced pluripotent stem cellCellular differentiationEmbryonic stem cellStem cellMatrix (chemical analysis)ImmunologyAnatomyChemistryBiochemistry

Abstract

fetched live from OpenAlex

Efficient differentiation of pluripotent cells to proximal and distal lung epithelial cell populations remains a challenging task. The 3D extracellular matrix (ECM) scaffold is a key component that regulates the interaction of secreted factors with cells during development by often binding to and limiting their diffusion within local gradients. Here we examined the role of the lung ECM in differentiation of pluripotent cells in vitro and demonstrate the robust inductive capacity of the native lung matrix alone. Extended culture of stem cell-derived definitive endoderm on decellularized lung scaffolds in defined, serum-free medium resulted in differentiation into mature airway epithelia, complete with ciliated cells, club cells, and basal cells with morphological and functional similarities to native airways. Heparitinase I, but not chondroitinase ABC, treatment of scaffolds revealed that the differentiation achieved is dependent on heparan sulfate proteoglycans and its bound factors remaining on decellularized scaffolds.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentalhigh
grokno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentalhigh
opusno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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 score0.000

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 head0.022
GPT teacher head0.255
Teacher spread0.233 · 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

Labeled directly by 3 models reading the full record.

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

Citations103
Published2015
Admission routes1
Has abstractyes

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