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Record W4200496366 · doi:10.1002/cpz1.331

Drug‐releasing Microspheres for Stem Cell Differentiation

2021· article· en· W4200496366 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

VenueCurrent Protocols · 2021
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsUniversity of British ColumbiaUniversity of Victoria
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsMichael Smith Health Research BC
KeywordsDrug deliveryTissue engineeringStem cellBiocompatibilityNanotechnologyMaterials scienceRegeneration (biology)MicrosphereBiomedical engineeringChemistryCell biologyChemical engineeringBiology

Abstract

fetched live from OpenAlex

The ability of stem cells to differentiate into specialized cells make them a valuable tool for therapeutic applications. 3D bioprinting, a subset of additive manufacturing, uses bioinks composed of cells and biomaterials to create living tissues. The use of bioactive factors like small molecules and proteins can promote stem cell differentiation into the desired cell phenotypes for tissue regeneration. Small molecules can accelerate the process of regeneration in tissue engineering, maintain bioactivity in a biological environment, and minimize the costs associated with this process. Additionally, they can be encapsulated in specialized drug-delivery devices called microspheres for controlled release. Microspheres are small (1-1000 μm) spherical particles usually made from biodegradable and biocompatible polymers that can be loaded with drugs and other bioactive components. They can then be integrated into stem-cell-laden bioinks used to form bioprinted tissues, where they will release the encapsulated drug and promote differentiation of stem cells into the desired mature cell type. Microspheres can be widely used to encapsulate a broad range of therapeutic agents, including hydrophilic and hydrophobic small molecule drugs, DNA, and proteins. The release of encapsulated molecules occurs through degradation and erosion of the polymer matrix. This article provides detailed protocols for fabricating and sterilizing drug-releasing microspheres made from poly-ε-caprolactone, a promising biodegradable polymer often used for controlled drug delivery due to its biocompatibility and biodegradation kinetics. Additional protocols describe characterization of the loading and size of microspheres as well as incorporation of microspheres into a fibrin-based bioink for 3D bioprinting. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Fabrication of drug-releasing PCL microspheres Support Protocol 1: Preparation of microspheres for determination of encapsulation efficiency by HPLC Support Protocol 2: Preparation of microspheres for SEM analysis Basic Protocol 2: Incorporation of microspheres into fibrin-based bioink.

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 categoriesnone
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 score0.761
Threshold uncertainty score0.523

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)0.0000.000

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 head0.046
GPT teacher head0.343
Teacher spread0.296 · 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