Collagenase treatment decreases muscle stiffness in cerebral palsy: A preclinical ex vivo biomechanical analysis of hip adductor muscle fiber bundles
Bibliographic record
Abstract
Abstract Aim To determine the dose–response relationship of collagenase Clostridium histolyticum (CCH) on collagen content and the change in muscle fiber bundle stiffness after ex vivo treatment of adductor longus biopsies with CCH in children with cerebral palsy (CP). Method Biopsy samples of adductor longus from children with CP (classified in Gross Motor Function Classification System levels IV and V) were treated with 0 U/mL, 200 U/mL, 350 U/mL, or 500 U/mL CCH; percentage collagen reduction was measured to determine the dose–response. Peak and steady‐state stresses were determined at 1%, 2.5%, 5%, and 7.5% strain increments; Young's modulus was calculated. Results Eleven patients were enrolled (nine males, two females, mean age at surgery 6 years 5 months; range: 2–16 years). A linear CCH dose–response relationship was determined. Peak and steady‐state stress generation increased linearly at 5.9/2.3mN/mm2, 12.4/5.3mN/mm2, 22.2/9.7mN/mm2, and 33.3/15.5mN/mm2 at each percentage strain increment respectively. After CCH treatment, peak and steady‐state stress generation decreased to 3.2/1.2mN/mm2, 6.5/2.9mN/mm2, 12.2/5.7mN/mm2, and 15.4/7.7mN/mm2 respectively (p < 0.004). Young's modulus decreased from 205 kPa to 100 kPa after CCH (p = 0.003). Interpretation This preclinical ex vivo study provides proof of concept for the use of collagenase to decrease muscle stiffness in individuals with CP.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".