Kinetic Study of the Replacement of Porcine Small Intestinal Submucosa Grafts and the Regeneration of Meniscal-Like Tissue in Large Avascular Meniscal Defects in Dogs
Bibliographic record
Abstract
Porcine small intestinal submucosa (SIS) was used to replace large, avascular defects in the medial menisci of dogs. Twelve dogs received SIS grafts and 3 dogs were left untreated as controls. Dogs were evaluated at 4, 8, and 12 weeks by means of lameness scoring and ultrasonography. Dogs were sacrificed at 1, 6, or 12 weeks after implantation, and the tissue at the site of meniscal resection was evaluated for gross and histologic appearance, cross-sectional and surface area, and collagen types I and II. The femoral and tibial condyles were assessed for articular cartilage damage. Control dogs were significantly more lame than grafted dogs 8 and 12 weeks after instrumentation. Grafted dogs' replacement tissue appeared meniscal-like when evaluated grossly and ultrasonographically 12 weeks after instrumentation. The amount of replacement tissue was significantly greater in both cross-sectional and surface area for grafted dogs than for controls at all time points. Histologically, the SIS biomaterial could be identified in all grafted dogs at 1 week post-implantation, but in none at 6 weeks post-implantation. Subjectively, grafted dogs' replacement tissue was histologically superior to that of controls with respect to tissue type, organization, and architecture. Collagen types I and II immunoreactivity in grafted menisci were similar to that of normal menisci. Control dogs had significantly more articular cartilage damage than grafted dogs. SIS appears to induce regeneration of meniscal-like tissue in large, avascular meniscal defects in dogs, resulting in superior clinical function and articular cartilage protection compared to ungrafted controls.
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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) | 0.000 | 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".