The effects of short‐term load duration on anabolic and catabolic gene expression in the rat tail intervertebral disc
Bibliographic record
Abstract
The goal of this study was to determine the time-dependent response of the intervertebral disc cells to in vivo dynamic compression. Forty-seven skeletally mature Wistar rats (>12 months old) were instrumented with an Ilizarov-type device spanning caudal disc 8-9. Using a load magnitude (1 MPa) and frequency (1.0 Hz) that were previously shown to significantly alter mRNA levels in the disc, the effects of 0.5 and 4 h of loading were investigated and compared to a sham group and our previous 2 h results. Annulus and nucleus tissue of loaded (c8-9) and internal control discs (c6-7 and c10-11) were separately analyzed by real-time RT-PCR for levels of mRNA coding for various anabolic (collagen-1A1, collagen-2A1, aggrecan) and catabolic (MMP-3, MMP-13, ADAMTs-4) proteins. In the annulus, mRNA levels increased for Collagen types I & II, and MMP 3 & 13 with increasing load duration. In contrast, the nucleus had the largest increases in aggrecan, ADAMTs-4, MMP-3 and MMP-13 after 2 h of loading, with aggrecan and MMP-13 mRNA levels returning to control values after 4 h of loading. Taken in context with our previous studies, we conclude that intervertebral disc cells from the nucleus and annulus have distinct responses to dynamic mechanical compression in vivo with sensitivity to compression magnitude, frequency and duration.
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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 | 0.001 |
| 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".