TGF‐β1‐activated type 2 dendritic cells promote wound healing and induce fibroblasts to express tenascin c following corneal full‐thickness hydrogel transplantation
Bibliographic record
Abstract
We showed previously that 1-ethyl-3-(3-dimethylamino-propyl)-carbodiimide hydrochloride (EDC) cross-linked recombinant human collagen III hydrogels promoted stable regeneration of the human cornea (continued nerve and stromal cell repopulation) for over 4 years. However, as EDC cross linking kinetics were difficult to control, we additionally tested a sterically bulky carbodiimide. Here, we compared the effects of two carbodiimide cross linkers—bulky, aromatic N-cyclohexyl-N0-(2-morpholinoethyl)-carbodiimide (CMC), and nonbulky EDC—in a mouse corneal graft model. Murine corneas undergoing full-thickness implantation with these gels became opaque due to dense retro-corneal membranes (RCM). Corneal epithelial cytokeratin 12 and alpha smooth muscle actin indicative of functional tissue regeneration and wound contraction were observed in RCM surrounding both hydrogel types. However, quantitatively different levels of infiltrating CD11c+ dendritic cells (DC) were found, suggesting a hydrogel-specific innate immune response. More DC infiltrated the stroma surrounding EDC-N-hydroxysuccinimide (NHS) hydrogels concurrently with higher fibrosis-associated tenascin c expression. The opposite was true for CMC-NHS gels that had previously been shown to be more tolerising to DC. In vitro studies showed that DC cultured with transforming growth factor β1 (TGF-β1) induced fibroblasts to secrete more tenascin c than those cultured with lipopolysaccharide and this effect was blocked by TGF-β1 neutralisation. Furthermore, tenascin c staining was found in 40- to 50μm long membrane nanotubes formed in fibroblast/DC cocultures. We suggest that TGF-β1 alternatively activated (tolerising) DC regulate fibroblast-mediated tenascin c secretion, possibly via local production of TGF-β1 in early wound contraction, and that this is indirectly modulated by different hydrogel chemistries.
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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 | 0.001 |
| 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".