EFFECTS OF MECHANICAL LOADING ON INTERVERTEBRAL DISC METABOLISM IN VIVO
Bibliographic record
Abstract
The overall goal of this work is to define more clearly which mechanical loading conditions are associated with accelerated disc degeneration. This article briefly reviews recent studies describing the effects of mechanical loading on the metabolism of intervertebral disc cells and defines hypothetical models that provide a framework for quantitative relationships between mechanical loading and disc-cell metabolism. Disc cells respond to mechanical loading in a manner that depends on loading magnitude, frequency, and duration. On the basis of the current data, four models have been proposed to describe the effects of continuous loading on cellular metabolism: (1) on/off response, in which messenger ribonucleic acid (mRNA) transcription remains altered for the duration of loading; (2) maintenance, characterized by an initial change in mRNA levels with return to baseline levels; (3) adaptation, in which mRNA transcription is altered and remains at a new steady state; and (4) no response. In addition, five hypothetical mechanisms that describe the long-term consequences of these metabolic changes on disc-remodeling are presented. The transient nature of gene expression along with enzyme activation/inhibition is associated with changes at the protein level. The hypothetical models presented provide a framework for obtaining quantitative relationships between mechanical loading, gene expression, and changes at the compositional level; however, additional factors, such as regulatory mechanisms, must also be considered when describing disc-remodeling. A more quantitative relationship between mechanical loading effects and the metabolic response of the disc will contribute to injury prevention, facilitate more effective rehabilitation treatments, and help realize the potential of biologic and tissue engineering approaches toward disc repair.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".