Galectin-3/Gelatin Electrospun Scaffolds Modulate Collagen Synthesis in Skin Healing but Do Not Improve Wound Closure Kinetics
Why this work is in the frame
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Bibliographic record
Abstract
Chronic wounds remain trapped in a pro-inflammatory state, with strategies targeted at inducing re-epithelialization and the proliferative phase of healing desirable. As a member of the lectin family, galectin-3 is implicated in the regulation of macrophage phenotype and epithelial migration. We investigated if local delivery of galectin-3 enhanced skin healing in a full-thickness excisional C57BL/6 mouse model. An electrospun gelatin scaffold loaded with galectin-3 was developed and compared to topical delivery of galectin-3. Electrospun gelatin/galectin-3 scaffolds had an average fiber diameter of 200 nm, with 83% scaffold porosity approximately and an average pore diameter of 1.15 μm. The developed scaffolds supported dermal fibroblast adhesion, matrix deposition, and proliferation in vitro. In vivo treatment of 6 mm full-thickness excisional wounds with gelatin/galectin-3 scaffolds did not influence wound closure, re-epithelialization, or macrophage phenotypes, but increased collagen synthesis. In comparison, topical delivery of galectin-3 [6.7 µg/mL] significantly increased arginase-I cell density at day 7 versus untreated and gelatin/galectin-3 scaffolds (p < 0.05). A preliminary assessment of increasing the concentration of topical galectin-3 demonstrated that at day 7, galectin-3 [12.5 µg/mL] significantly increased both epithelial migration and collagen content in a concentration-dependent manner. In conclusion, local delivery of galectin 3 shows potential efficacy in modulating skin healing in a concentration-dependent manner.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it