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Record W3164871099 · doi:10.1021/acsami.1c02297

Noninvasive Three-Dimensional <i>In Situ</i> and <i>In Vivo</i> Characterization of Bioprinted Hydrogel Scaffolds Using the X-ray Propagation-Based Imaging Technique

2021· article· en· W3164871099 on OpenAlexafffund
Liqun Ning, Ning Zhu, A.C.J. Smith, Ajay Rajaram, Huishu Hou, Subashree Srinivasan, Fatemeh Mohabatpour, Lihong He, A. G. P. Mclnnes, Vahid Serpooshan, Pétros Papagerakis, Daniel Chen

Bibliographic record

VenueACS Applied Materials & Interfaces · 2021
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsCanadian Light Source (Canada)University of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceScaffoldBiomedical engineering3D bioprintingCharacterization (materials science)Tissue engineeringIn situSelf-healing hydrogelsStructural integrity3D printingNanotechnologyComposite materialChemistry

Abstract

fetched live from OpenAlex

Hydrogel-based three-dimensional (3D) bioprinting has been illustrated as promising to fabricate tissue scaffolds for regenerative medicine. Notably, bioprinting of hydrated and soft 3D hydrogel scaffolds with desired structural properties has not been fully achieved so far. Moreover, due to the limitations of current imaging techniques, assessment of bioprinted hydrogel scaffolds is still challenging, yet still essential for scaffold design, fabrication, and longitudinal studies. This paper presents our study on the bioprinting of hydrogel scaffolds and on the development of a novel noninvasive imaging method, based on synchrotron propagation-based imaging with computed tomography (SR-PBI-CT), to study the structural properties of hydrogel scaffolds and their responses to environmental stimuli both in situ and in vivo. Hydrogel scaffolds designed with varying structural patterns were successfully bioprinted through rigorous printing process regulations and then imaged by SR-PBI-CT within physiological environments. Subjective to controllable compressive loadings, the structural responses of scaffolds were visualized and characterized in terms of the structural deformation caused by the compressive loadings. Hydrogel scaffolds were later implanted in rats as nerve conduits for SR-PBI-CT imaging, and the obtained images illustrated their high phase contrast and were further processed for the 3D structure reconstruction and quantitative characterization. Our results show that the scaffold design and printing conditions play important roles in the printed scaffold structure and mechanical properties. More importantly, our obtained images from SR-PBI-CT allow us to visualize the details of hydrogel 3D structures with high imaging resolution. It demonstrates unique capability of this imaging technique for noninvasive, in situ characterization of 3D hydrogel structures pre- and post-implantation in diverse physiological milieus. The established imaging platform can therefore be utilized as a robust, high-precision tool for the design and longitudinal studies of hydrogel scaffold in 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.

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)0.001
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 score0.002
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.010
GPT teacher head0.238
Teacher spread0.227 · 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

Citations40
Published2021
Admission routes2
Has abstractyes

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