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Record W4320488156 · doi:10.1039/d2mh01242a

Tissue-mimetic hybrid bioadhesives for intervertebral disc repair

2023· article· en· W4320488156 on OpenAlexafffund
Xuan Li, Yin Liu, Li Li, Ran Huo, Farshid Ghezelbash, Zhenwei Ma, Guangyu Bao, Shiyu Liu, Zhen Yang, Michael H. Weber, Nicole Y. K. Li‐Jessen, Lisbet Haglund, Jianyu Li

Bibliographic record

VenueMaterials Horizons · 2023
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsPolytechnique MontréalMcGill University
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsIntervertebral discSealantTissue engineeringFibrin glueMaterials scienceBiomedical engineeringMedicineSurgeryComposite material

Abstract

fetched live from OpenAlex

Intervertebral disc (IVD) degeneration and herniation often necessitate surgical interventions including a discectomy with or without a nucleotomy, which results in a loss of the normal nucleus pulposus (NP) and a defect in the annulus fibrosus (AF). Due to the limited regenerative capacity of the IVD tissue, the annular tear may remain a persistent defect and result in recurrent herniation post-surgery. Bioadhesives are promising alternatives but show limited adhesion performance, low regenerative capacity, and inability to prevent re-herniation. Here, we report hybrid bioadhesives that combine an injectable glue and a tough sealant to simultaneously repair and regenerate IVD post-nucleotomy. The glue fills the NP cavity while the sealant seals the AF defect. Strong adhesion occurs with the IVD tissues and survives extreme disc loading. Furthermore, the glue can match native NP mechanically, and support the viability and matrix deposition of encapsulated cells, serving as a suitable cell delivery vehicle to promote NP regeneration. Besides, biomechanical tests with bovine IVD motion segments demonstrate the capacity of the hybrid bioadhesives to restore the biomechanics of bovine discs under cyclic loading and to prevent permanent herniation under extreme loading. This work highlights the synergy of bioadhesive and tissue-engineering approaches. Future works are expected to further improve the tissue specificity of bioadhesives and prove their efficacy for tissue repair and regeneration.

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 categoriesInsufficient payload (model declined to judge)
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 score0.137
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.032
GPT teacher head0.328
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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

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

Citations34
Published2023
Admission routes2
Has abstractyes

Explore more

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