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Record W3172042401 · doi:10.3390/ijms22126203

Advanced Hydrogels as Exosome Delivery Systems for Osteogenic Differentiation of MSCs: Application in Bone Regeneration

2021· review· en· W3172042401 on OpenAlexaff
Elham Pishavar, Hongrong Luo, Mahshid Naserifar, Maryam Hashemi, Shirin Toosi, Anthony Atala, Seeram Ramakrishna, Javad Behravan

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsUniversity of Waterloo
FundersAgence Nationale de la Recherche
KeywordsSelf-healing hydrogelsMesenchymal stem cellExosomeMicrovesiclesTissue engineeringRegeneration (biology)Regenerative medicineBiomedical engineeringCell biologyNanotechnologyChemistryStem cellMaterials scienceBiologyMedicinemicroRNABiochemistry

Abstract

fetched live from OpenAlex

Hydrogels are known as water-swollen networks formed from naturally derived or synthetic polymers. They have a high potential for medical applications and play a crucial role in tissue repair and remodeling. MSC-derived exosomes are considered to be new entities for cell-free treatment in different human diseases. Recent progress in cell-free bone tissue engineering via combining exosomes obtained from human mesenchymal stem cells (MSCs) with hydrogel scaffolds has resulted in improvement of the methodologies in bone tissue engineering. Our research has been actively focused on application of biotechnological methods for improving osteogenesis and bone healing. The following text presents a concise review of the methodologies of fabrication and preparation of hydrogels that includes the exosome loading properties of hydrogels for bone regenerative 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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.018
GPT teacher head0.323
Teacher spread0.306 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations95
Published2021
Admission routes1
Has abstractyes

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Same venueInternational Journal of Molecular SciencesSame topicExtracellular vesicles in diseaseFrench-language works237,207