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Record W2533647589 · doi:10.1002/9781119126218.ch3

Gelatin‐Based Biomaterials For Tissue Engineering And Stem Cell Bioengineering

2016· other· en· W2533647589 on OpenAlexaff
Mehdi Nikkhah, Mohsen Akbari, Arghya Paul, Adnan Memić, Alireza Dolatshahi‐Pirouz, Ali Khademhosseini

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversity of Victoria
FundersOffice of Naval ResearchNational Science Foundation
KeywordsGelatinTissue engineeringStem cellBiopolymerBiocompatible materialBiomedical engineeringRegeneration (biology)Wound healingDrug deliveryGene deliveryMaterials scienceChemistryNanotechnologyCell biologyGenetic enhancementBiologyMedicineBiochemistryGeneImmunology

Abstract

fetched live from OpenAlex

Gelatin is a biocompatible, biodegradable and fully absorbable biopolymer. These properties have attracted significant interests in the use of gelatin for a wide range of tissue engineering applications. This chapter covers the studies that focused on using gelatin-based biomaterials for cardiovascular, bone, hepatic, skin and corneal tissue engineering. It discusses the application of gelatin for wound healing and injectable fillers. Stem cells hold great a potential in tissue regeneration applications due to their self renewal capacity and differentiation toward specialized cell types. The chapter discusses various strategies that have been utilized to modulate stem cell behavior by altering the biochemical and biophysical properties of gelatin. Gelatin-based delivery systems have found success in gene and siRNA delivery, to induce the expression of therapeutic proteins or trigger gene silencing, respectively. Overall, gelatin based drug delivery systems have demonstrated great utility and versatility in many biomedical applications.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.571
Threshold uncertainty score0.998

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)0.0030.000

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 head0.007
GPT teacher head0.235
Teacher spread0.228 · 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.

Study designBench or experimental
Domainnot available
GenreMethods

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

Citations80
Published2016
Admission routes1
Has abstractyes

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