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Record W2572738460 · doi:10.1055/s-0036-1582621

Evaluation of Tissue Repair Using MRI Imaging of Human Intervertebral Discs Cultured in a Bioreactor

2016· article· en· W2572738460 on OpenAlexaffabout
Derek H. Rosenzweig, Rahul Gawri, Janet Moir, Lorne Beckman, David Eglin, Thomas Steffen, Peter J. Roughley, Jean Ouellet, Lisbet Haglund

Bibliographic record

VenueGlobal Spine Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsMcGill University
Fundersnot available
KeywordsIntervertebral discContext (archaeology)MedicineDegenerative disc diseaseViability assayLow back painEx vivoBiomedical engineeringLumbarDegeneration (medical)In vivoPathologyCell cultureSurgeryBiologyBiotechnology

Abstract

fetched live from OpenAlex

Introduction Low back pain is a major problem world-wide, affecting the quality of life for millions of people. Low back pain also has a tremendous impact on direct and indirect global healthcare costs. Intervertebral disc (IVD) degeneration has been strongly associated with low back pain. Long-term organ culture of human IVDs is essential to study IVD degeneration and repair. Using an ex vivo approach, the relationship between mechanobiology, disc matrix composition and metabolism can be better understood in the context of degenerative disease. We have developed a bioreactor where intact human discs can be cultured in a controlled dynamically loaded environment. Here, we aimed to determine the most suitable loading parameters for human discs culture by assessing IVD tissue integrity and cell viability under low, medium and high magnitude cyclic load. Furthermore, we investigated the suitability of this model toward cell supplementation strategies for tissue repair and developed a novel, single disc MRI imaging sequence aimed at direct visualization of tissue repair. Materials and Methods Human IVDs were isolated from lumbar spine segments as previously described. Spines were obtained with consent through the Transplant Quebec Organ Donation Program from individuals who had undergone sustained brain death. Discs were cultured under 3 different loading schemes to mimic a sedentary lifestyle: low 0.1–0.3, medium 0.1–0.6 and high 0.1–1.2 MPa loads. Cell viability and matrix stability was assessed following 10 days of loading. Feasibility of cell/hydrogel implantation was determined over 14 days of medium dynamic loading. To determine whether isolated discs could be imaged by MRI, extracted individual discs were visualized for T1 and T2 signals using a novel sequence using a small animal Bruker 7.5 Tesla MRI. Results Cell viability was maintained at greater than 80% throughout the discs at low and medium loads. Viability dropped to ~60–70% throughout the discs under high loads. Proteoglycan content remained stable in all loading protocols (~50 μg sGAG/mg tissue), as did CHAD and newly synthesized collagen II protein. To test for feasibility of cell therapies in the bioreactors, NP cells combined with a hydrogel were injected into discs and cultured under medium load. 14 days after dynamic culture, the injected cells were mainly localized to the NP region with greater than 90% viability. The small animal MRI was able to obtain well-defined images of isolated discs, with details of tissue integrity and proteoglycan content. Conclusion Our ex vivo model of dynamic human IVD culture can be used as a platform on which to study mechanisms of degeneration as well as for novel avenues aimed at biological repair using bioactive substances or cell based therapies. Cells and bioactive substances can be administered within hydrogels thereby enhancing the reparative properties. Furthermore, it is feasible to assess repair potential of the therapies by comparing MRI scans pre- and post-therapy.

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)0.001
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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.049
GPT teacher head0.394
Teacher spread0.345 · 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".

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Citations0
Published2016
Admission routes2
Has abstractyes

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