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Record W4386051133 · doi:10.3390/polym15173493

3D Embedded Printing of Complex Biological Structures with Supporting Bath of Pluronic F-127

2023· article· en· W4386051133 on OpenAlexaff
Tianzhou Hu, Zhengwei Cai, Ruixue Yin, Wenjun Zhang, Chunyan Bao, Linyong Zhu, Honbo Zhang

Bibliographic record

VenuePolymers · 2023
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsBiofabricationPoloxamerGelatinNanotechnologyMaterials scienceMicrofluidicsNozzleTissue engineeringComputer scienceBiomedical engineeringPolymerMechanical engineeringChemistryComposite materialEngineering

Abstract

fetched live from OpenAlex

Biofabrication is crucial in contemporary tissue engineering. The primary challenge in biofabrication lies in achieving simultaneous replication of both external organ geometries and internal structures. Particularly for organs with high oxygen demand, the incorporation of a vascular network, which is usually intricate, is crucial to enhance tissue viability, which is still a difficulty in current biofabrication technology. In this study, we address this problem by introducing an innovative three-dimensional (3D) printing strategy using a thermo-reversible supporting bath which can be easily removed by decreasing the temperature. This technology is capable of printing hydrated materials with diverse crosslinked mechanisms, encompassing gelatin, hyaluronate, Pluronic F-127, and alginate. Furthermore, the technology can replicate the external geometry of native tissues and organs from computed tomography data. The work also demonstrates the capability to print lines around 10 μm with a nozzle with a diameter of 60 μm due to the extra force exerted by the supporting bath, by which the line size was largely reduced, and this technique can be used to fabricate intricate capillary networks.

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)0.000
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 score0.338
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.042
GPT teacher head0.307
Teacher spread0.266 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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