Disc Strain and Resulting Positive mRNA Expression from Application of a Noninvasive Treatment
Bibliographic record
Abstract
STUDY DESIGN: Bovine caudal intervertebral discs were exposed to a noninvasive vibrating intervention for 10 minutes at amplitudes of 0 or 0.5 to 5 g and frequencies of 0, 16, 50 to 80, and a combined 16+50 to 80 Hz treatment. Expression of mRNA for aggrecan, collagen type I, collagen type II, biglycan, decorin, and versican were assayed. OBJECTIVE: To determine if the intervention is effective in altering intervertebral disc gene expression. SUMMARY OF BACKGROUND DATA: Studies have variously suggested either an increased risk of disc degeneration with vibrations, no effect, analgesic effect, or even positive effects within certain loading parameters. The KKT intervention is in clinical use for spinal ailment pain reduction. METHODS: The intervention was applied in a clinic emulation set-up. Gene expression in the nucleus pulposus was assessed using real-time RT-PCR and SYBR Green chemistry. RESULTS: Expression of mRNAs for aggrecan, collagen type II, and versican were significantly effected by the intervention. Collagen type I, biglycan, and decorin were uneffected. CONCLUSION: Expression of the extracellular matrix genes were significantly up-regulated when vibrated with the intervention under specific loading patterns, indicating a potential therapeutic stimulus. Further studies on the protein-level and long-term effects are warranted. Previous studies have indicated a mixed effect of vibrations in the human spine. In this study, a clinical intervention using vibrations was applied to bovine intervertebral discs, and gene expression in the nucleus pulposus was measured. Several extracellular matrix genes were up-regulated, suggesting a potential therapeutic effect.
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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) | 0.004 | 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".