<i>In vitro</i> and <i>in silico</i> investigations of disc nucleus replacement
Bibliographic record
Abstract
Currently, numerous hydrogels are under examination as potential nucleus replacements. The clinical success, however, depends on how well the mechanical function of the host structure is restored. This study aimed to evaluate the extent to and mechanisms by which surgery for nucleus replacements influence the mechanical behaviour of the disc. The effects of an annulus defect with and without nucleus replacement on disc height and nucleus pressure were measured using 24 ovine motion segments. The following cases were considered: intact; annulus incision repaired by suture and glue; annulus incision with removal and re-implantation of nucleus tissue repaired by suture and glue or plug. To identify the likely mechanisms observed in vitro, a finite-element model of a human disc (L4-L5) was employed. Both studies were subjected to physiological cycles of compression and recovery. A repaired annulus defect did not influence the disc behaviour in vitro, whereas additional nucleus removal and replacement substantially decreased disc stiffness and nucleus pressure. Model predictions demonstrated the substantial effects of reductions in replaced nucleus water content, bulk modulus and osmotic potential on disc height loss and pressure, similar to measurements. In these events, the compression load transfer in the disc markedly altered by substantially increasing the load on the annulus when compared with the nucleus. The success of hydrogels for nucleus replacements is not only dependent on the implant material itself but also on the restoration of the environment perturbed during surgery. The substantial effects on the disc response of disruptions owing to nucleus replacements can be simulated by reduced nucleus water content, elastic modulus and osmotic potential.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".