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Record W2179255723 · doi:10.1089/ten.tec.2015.0307

Analyzing Biological Performance of 3D-Printed, Cell-Impregnated Hybrid Constructs for Cartilage Tissue Engineering

2015· article· en· W2179255723 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueTissue Engineering Part C Methods · 2015
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsUniversity of Saskatchewan
FundersCanadian Institutes of Health Research
KeywordsBiofabricationTissue engineering3D bioprintingSelf-healing hydrogelsCartilageBiomedical engineeringBiocompatibilityMaterials scienceChemistryAnatomyBiologyPolymer chemistryMedicine

Abstract

fetched live from OpenAlex

Three-dimensional (3D) bioprinting of hybrid constructs is a promising biofabrication method for cartilage tissue engineering because a synthetic polymer framework and cell-impregnated hydrogel provide structural and biological features of cartilage, respectively. During bioprinting, impregnated cells may be subjected to high temperatures (caused by the adjacent melted polymer) and process-induced mechanical forces, potentially compromising cell function. This study addresses these biofabrication issues, evaluating the heat distribution of printed polycaprolactone (PCL) strands and the rheological property and structural stability of alginate hydrogels at various temperatures and concentrations. The biocompatibility of parameters from these studies was tested by culturing 3D hybrid constructs bioprinted with primary cells from embryonic chick cartilage. During initial two-dimensional culture expansion of these primary cells, two morphologically and molecularly distinct cell populations ("rounded" and "fibroblastic") were isolated. The biological performance of each population was evaluated in 3D hybrid constructs separately. The cell viability, proliferation, and cartilage differentiation were observed at high levels in hybrid constructs of both cell populations, confirming the validity of these 3D bioprinting parameters for effective cartilage tissue engineering. Statistically significant performance variations were observed, however, between the rounded and fibroblastic cell populations. Molecular and morphological data support the notion that such performance differences may be attributed to the relative differentiation state of rounded versus fibroblastic cells (i.e., differentiated chondrocytes vs. chondroprogenitors, respectively), which is a relevant issue for cell-based tissue engineering strategies. Taken together, our study demonstrates that bioprinting 3D hybrid constructs of PCL and cell-impregnated alginate hydrogel is a promising approach for cartilage tissue engineering.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.253
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.043
GPT teacher head0.322
Teacher spread0.279 · 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