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Record W2944203705 · doi:10.1039/c8lc01037d

Effective bioprinting resolution in tissue model fabrication

2019· article· en· W2944203705 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueLab on a Chip · 2019
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsnot available
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institute of Arthritis and Musculoskeletal and Skin DiseasesSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchConsellería de Cultura, Educación e Ordenación Universitaria, Xunta de GaliciaNational Cancer InstituteNational Institutes of Health
Keywords3D bioprintingNanotechnologyFabricationMaterials scienceHigh resolutionComputer scienceEngineeringBiomedical engineeringTissue engineering

Abstract

fetched live from OpenAlex

Recent advancements in bioprinting techniques have enabled convenient fabrication of micro-tissues in organ-on-a-chip platforms. In a sense, the success of bioprinted micro-tissues depends on how close their architectures are to the anatomical features of their native counterparts. The bioprinting resolution largely relates to the technical specifications of the bioprinter platforms and the physicochemical properties of the bioinks. In this article, we compare inkjet, extrusion, and light-assisted bioprinting technologies for fabrication of micro-tissues towards construction of biomimetic organ-on-a-chip platforms. Our theoretical analyses reveal that for a given printhead diameter, surface contact angle dominates inkjet bioprinting resolution, while nozzle moving speed and the nonlinearity of viscosity for bioinks regulate extrusion bioprinting resolution. The resolution of light-assisted bioprinting is strongly affected by the photocrosslinking behavior and light characteristics. Our tutorial guideline for optimizing bioprinting resolution would potentially help model the complex microenvironment of biological tissues in organ-on-a-chip platforms.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score1.000

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)0.0000.001

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 head0.012
GPT teacher head0.274
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