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Record W2526181785 · doi:10.11159/iccpe16.103

Self-Assembled Hyaluronic Acid-Gelatin Microhydrogel for Regenerating Neurite-Like Cells from Induced Pluripotent Stem Cells

2016· article· en· W2526181785 on OpenAlexvenueno aff
Yung‐Chih Kuo, Yu‐Chun Chen

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2016
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsnot available
Fundersnot available
KeywordsHyaluronic acidInduced pluripotent stem cellGelatinNeuriteStem cellCell biologyChemistryBiophysicsBiologyBiochemistryAnatomyEmbryonic stem cellIn vitro

Abstract

fetched live from OpenAlex

Neuronal differentiation of induced pluripotent stem cells (iPSCs) in repeating particulate units of microhydrogel with hybrid hyaluronic acid (HA) and gelatin (Gel) was investigated.HA and Gel were photocrosslinked, assembled, and further used to regenerate neurons from iPSCs.Stained fluorescent images evidenced that the self-assembled microhydrogel comprising 50% HA and 50% Gel was able to preserved phenotypic iPSCs, leading to an improved production of neuronal lineage after induction with nerve growth factor.The current self-assembled HA-Gel microhydrogel constructs can be properly self-assembled for engineered biomaterials in the duplication of nervous tissue from iPS cells after incubation with neurite-inductive factor.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.009
GPT teacher head0.203
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), 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
Published2016
Admission routes1
Has abstractyes

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Same venueProceedings of the World Congress on Mechanical, Chemical, and Material EngineeringSame topic3D Printing in Biomedical ResearchFrench-language works237,207