Unloaded Organ Culturing Has a Detrimental Effect on the Axial Mechanical Properties of the Intervertebral Disc
Bibliographic record
Abstract
Healthy function of intervertebral discs (IVDs) depends on their tissue mechanical properties. Native cells embedded within IVD tissues are responsible for building, maintaining, and repairing IVD structures in response to genetic, biochemical, and mechanical signals. Organ culturing provides a method for investigating how cells respond to these stimuli in their natural architectural environment. The purpose of this study was to determine how organ culturing affects the mechanical characteristics of functional spine units (FSUs) across the entire range of axial loading, including the neutral zone (NZ), using a rat tail model. Rat tail FSUs were organ cultured at 37 °C in an unloaded state in standard culture media for either 1-day (n = 8) or 6-days (n = 12). Noncultured FSUs (n = 12) were included as fresh control specimens. Axial mechanical properties were tested by applying cyclical compression and tension. A novel mathematical approach was developed to fully characterize the relationship between load, stiffness, and deformation through the entire range of loading. Culturing FSUs for 1-day did not affect any of the axial mechanical outcome measures compared to noncultured IVDs; however, culturing for 6 days increased the size of NZ by 112% and decreased the stiffness in NZ, compressive, and tensile regions by 53%, 19%, and 15%, respectively, compared to noncultured FSUs. These results highlight the importance of considering how the mechanical integrity of IVD tissues may affect the transmission of mechanical signals to cells in unloaded organ culturing experiments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".