A novel, cell‐permeable, collagen‐based membrane promotes fibroblast migration
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Growth factors are frequently incorporated into scaffolds to promote periodontal regeneration but many currently used scaffolds do not encourage cell migration towards the dentogingival junction. We examined the proliferation and migration of human gingival fibroblasts in a novel, physically robust, collagen-Vicryl™ membrane loaded with fibronectin (FN) and/or insulin-like growth factor (IGF-I). Biocompatibility of the membranes was evaluated in rat dorsal skin. MATERIAL AND METHODS: Chemotaxis was examined in Boyden chambers and cell migration by confocal imaging of membranes, which were fabricated from rat tail type I collagen with embedded Vicryl knitted mesh, IGF-I (50, 100 ng/mL) and FN (10 μg/mL). Membranes (Vicryl alone, collagen+Vicryl, collagen+Vicryl+IGF-I, collagen+Vicryl+FN') were implanted subcutaneously in 8 rats and were evaluated by histomorphometry after 7 and 14 days. RESULTS: IGF-I (50 or 100 ng/mL) promoted chemotaxis compared with vehicle controls (P = .02, P = .001, respectively). IGF-I did not affect cell proliferation. Incorporation of FN retarded time-dependent release of IGF-I from collagen gels. Three dimensional confocal microscopy imaging of cell migration through collagen+Vicryl membranes showed enhanced migration in the IGF+FN group compared to all other groups at 8, 10 and 14 days (P < .05). In a rat skin model, implanted membranes were surrounded by thin collagen capsules and mild inflammatory infiltrates. CONCLUSION: Incorporation of FN into IGF-I-loaded collagen+Vicryl membranes reduced IGF release from collagen and increased the migration of human gingival fibroblasts. The new membrane may promote healing and reformation of the dentogingival junction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 teacher head, 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".