Static and dynamic compression application and removal on the intervertebral discs of growing rats
Bibliographic record
Abstract
Fusionless implants are used to correct pediatric progressive spinal deformities, most of them spanning the intervertebral disc. This study aimed at investigating the effects of in vivo static versus dynamic compression application and removal on discs of growing rats. A microloading device applied compression. 48 immature rats (28 d.o.) were divided into two groups (43d, 53d). Each group included four subgroups: control (no surgery), sham (device installed without loading), static (0.2 MPa) and dynamic compressions (0.2 MPa ± 30% with 0.1 Hz). In 43d subgroups, compression was applied for 15 days. In 53d subgroups, compression was followed by 10 days without loading. Disc heights, nucleus/annulus volumetric proportions and nucleus proteoglycan contents were analyzed using one-way ANOVA and post-hoc Tukey comparisons (p < 0.05). Disc heights of 43d and 53d static and dynamic loading rats were lower than shams (p < 0.05). Volumetric proportions remained similar. At 43d, nucleus proteoglycan contents increased in both static and dynamic loading rats. However, at 53d, static loading rats had lower proteoglycan content than dynamic loading rats (p < 0.05). Disc structure is altered following static compression removal, but nucleus proteoglycan content remaining elevated in dynamic group. Dynamic fusionless implants would better preserve disc integrity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".