Kanglexin promotes diabetic wound healing through activating FGFR/ERK1/2 signaling pathway mediated angiogenesis.
Bibliographic record
Abstract
Abstract Background: Diabetic wounds (DWs), especially leg or foot ulcers, are common diabetic complications, accounting for about 20% of diabetic patients. At present, there is still lack of effective measures to treat DWs in clinical practice. Kanglexin (KLX) is an anthraquinone compound with vasoprotective effect. This study will explore the therapeutic effects of KLX on DWs and the underlying mechanisms.Method: KM mice were injected with streptozocin (180 mg/kg) intraperitoneally to establish animal model of Type 1 Diabetes. The full-thickness skin wounds with the diameter of 5 mm were prepared on the back of diabetic mice with a skin punch. KLX is dissolved in sterile injection oil and applied to the wound once a day for 14 consecutive days. The wounds were photographed every day and the wound size was analyzed by Image Pro Plus software. On the 3rd, 7th, 11th day after KLX administration, skin tissues with a diameter of 1cm around the wound were fixed in paraformaldehyde and subjected to HE, Masson and immunohistochemical staining. Collagen deposition were evaluated by hydroxyproline kit. Angiogenesis of wound skin was evaluated by recording the formation of new blood vessels on its subsurface. In vitro study, human umbilical vein endothelial cells (HUVECs) were treated with advanced glycation end products (AGEs, 100 μg/mL) to establish the cell model of DWs. The proliferation, migration and tubular structure formation of HUVECs were measured by MTT, scratch and tubule formation experiments, respectively. Phosphorylation of ERK1/2 was detected by Western blot analysis.ResultsFirstly, in-vivo study showed that KLX significantly accelerated the closure of diabetic wounds through promoting granulation tissue formation, collagen synthesis and angiogenesis. Secondly, in vitro study results further confirmed that KLX promoted the proliferation, migration and tubular structure formation of HUVECs. Besides, KLX significantly up-regulated phospho-ERK1/2 both in diabetic wounds and AGEs-treated HUVECs. Thirdly, molecular docking simulation results indicated that there were multiple hydrogen bonds between KLX and FGFR amino acid residues, and FGFR inhibitor PD173074 significantly reversed KLX’s promotion of ERK1/2 phosphorylation and angiogenesis. Conclusions:KLX promotes angiogenesis and accelerates the healing of diabetic wounds by activating FGFR and ERK1/2 signaling pathway.
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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) | 0.002 | 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".