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Record W3195587430 · doi:10.11159/icnfa21.002

Nano and Microscale Light-based 3D Bioprinting for Tissue Engineering and Regenerative Medicine

2021· article· en· W3195587430 on OpenAlexvenueno aff
Shaochen Chen

Bibliographic record

VenueProceedings of the World Congress on New Technologies · 2021
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsnot available
Fundersnot available
KeywordsMicroscale chemistryRegenerative medicine3D bioprintingNano-Tissue engineeringComputer scienceNanotechnologyMaterials scienceBiomedical engineeringEngineeringStem cellBiologyCell biologyChemical engineering

Abstract

fetched live from OpenAlex

In this talk, I will present our laboratory's recent research efforts in developing micro and nano-scale bioprinting methods to create 3D tissue constructs using a variety of biomaterials and cells. These 3D printed scaffolds are functionalized with precise control of micro-architecture, mechanical (e.g. stiffness), chemical, and biological properties. Such functional scaffolds allow us to investigate cell-microenvironment interactions at nano-and micro-scales in response to integrated mechanical and chemical stimuli. From these fundamental studies we have been creating both in vitro and in vivo precision tissues for tissue regeneration, disease modeling, and drug discovery. Examples including 3D bioprinted liver and heart models will be discussed. I will also showcase 3D printed biomimetic scaffolds for treating spinal cord injury. Throughout the presentation, I will discuss engineer's perspectives in terms of design innovation, biomaterials, mechanics, and scalable biomanufacturing.

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)0.002
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 score0.039
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0000.000

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 head0.258
Teacher spread0.245 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the World Congress on New TechnologiesSame topic3D Printing in Biomedical ResearchFrench-language works237,207