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Record W2152492629 · doi:10.1002/mabi.201200170

Human Elastin‐Based Recombinant Biopolymers Improve Mesenchymal Stem Cell Differentiation

2012· article· en· W2152492629 on OpenAlex
Betül Çelebi‐Saltik, Maxime Cloutier, Rodrigo Balloni, Diego Mantovani, Antonella Bandiera

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMacromolecular Bioscience · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective tissue disorders research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsElastinMesenchymal stem cellRegenerative medicineTissue engineeringRecombinant DNAChemistryCellCell cultureCell biologyBiopolymerScaffoldNanotechnologyC2C12Materials scienceBiomedical engineeringBiologyBiochemistryIn vitroPolymerEngineering

Abstract

fetched live from OpenAlex

Elastin-based polypeptides are a class of smart biopolymers representing an important model in the design of biomaterials. The combination of biomimetic materials with cells that have great plasticity provides a promising strategy for the realization of highly engineered cell-based constructs for regenerative medicine and tissue repair applications. Two recombinant biopolymers inspired by human elastin are assessed as coating agents to prepare biomimetic surfaces for cell culture. These substrates are assayed for hBM MSC culture. The coated surfaces are also characterized with AFM to evaluate the topographical features of the deposited biopolymers. The results suggest that the elastin-derived biomimetic surfaces play a stimulatory role on osteogenic differentiation of MSCs.

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.

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)0.000
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 score0.017
Threshold uncertainty score0.917

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.013
GPT teacher head0.275
Teacher spread0.262 · 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