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Record W3006215028 · doi:10.3389/fbioe.2020.00057

3D Bioprinting Pluripotent Stem Cell Derived Neural Tissues Using a Novel Fibrin Bioink Containing Drug Releasing Microspheres

2020· article· en· W3006215028 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

VenueFrontiers in Bioengineering and Biotechnology · 2020
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of British ColumbiaUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsInnovate BCMichael Smith Health Research BCAlzheimer's Association
KeywordsNeural stem cellInduced pluripotent stem cellSOX2Cell biologyChemistry3D bioprintingPAX6Tyrosine hydroxylaseProgenitor cellStem cellMolecular biologyBiomedical engineeringTissue engineeringBiologyEmbryonic stem cellBiochemistryMedicine

Abstract

fetched live from OpenAlex

3D bioprinting combines cells with a supportive bioink to fabricate multiscale, multi-cellular structures that imitate native tissues. Here, we demonstrate how our novel fibrin-based bioink formulation combined with drug releasing microspheres can serve as a tool for bioprinting tissues using human induced pluripotent stem cell (hiPSC)-derived neural progenitor cells (NPCs). Microspheres, small spherical particles, can provide a controlled release rate for drugs like guggulsterone, shown to promote hiPSC differentiation into dopaminergic neurons, making them a valuable tool for tissue engineering. We printed dome shaped structures with a 1 cm diameter using the Aspect Biosystems RX1 bioprinter with our novel bioink consisting of fibrin, alginate and genipin containing guggulsterone microspheres crosslinked by a mixture of calcium chloride, chitosan and thrombin. Cell viability one day post printing was over 90% for the cells printed using our bioink containing guggulsterone microspheres that increased to 95%, 7 days after printing. The bioprinted tissues expressed the early neuronal marker, TUJ1 and the early midbrain marker, forkhead/winged helix transcription factor (FOXA2) (Forkhead Box A2) after 15 days of culture. These bioprinted neural tissues expressed TUJ1, (15 ± 1.3%), the dopamine marker, tyrosine hydroxylase (TH) (8 ± 0.6%) and other glial markers such as glial fibrillary acidic protein (GFAP) (15 ± 3.5%) and oligodendrocyte progenitor marker (O4) (4 ± 0.9%) as showed by flow cytometry after 30 days. Also, relative gene expression by quantitative polymerase chain reaction (qPCR) showed expression of TUBB3 (TUJ1) and specific midbrain dopaminergic neurons Nuclear receptor related 1 protein (NURR1), LIM Homeobox Transcription Factor 1 Beta (LMX1B), TH, and Paired Box 6 (PAX6) in these tissues after 30 days. In conclusion, we have demonstrated that 3D bioprinting pluripotent stem cell derived neural tissues using a microsphere-laden bioink can promote the differentiation of neural tissue when used to bioprint hiPSC-derived NPCs.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.218
Teacher spread0.202 · 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