Human adipose stem cells (ASCs) have emerged as a promising treatment paradigm for skin wounds. Recent works demonstrate that the therapeutic effect of stem cells is partially mediated by extracellular vesicles, which comprise exosomes and microvesicles. In this study, we investigate the regenerative effects of isolated microvesicles from ASCs and evaluate the mechanisms how ASC microvesicles promote wound healing. Adipose stem cell-derived microvesicles (ASC-MVs) were isolated by differential ultracentrifugation, stained by PKH26, and characterized by electron microscopy and dynamic light scattering (DLS). We examined ASC-MV effects on proliferation, migration, and angiogenesis of keratinocytes, fibroblasts, and endothelial cells both in vitro and in vivo. Next, we explored the underlying mechanisms by gene expression analysis and the activation levels of AKT and ERK signaling pathways in all three kinds of cells after ASC-MV stimulation. We then assessed the effect of ASC-MVs on collagen deposition, neovascularization, and re-epithelialization in an in vivo skin injury model. ASC-MVs could be readily internalized by human umbilical vein endothelial cells (HUVECs), HaCAT, and fibroblasts and significantly promoted the proliferation, migration, and angiogenesis of these cells both in vitro and in vivo. The gene expression of proliferative markers (cyclin D1, cyclin D2, cyclin A1, cyclin A2) and growth factors (VEGFA, PDGFA, EGF, FGF2) was significantly upregulated after ASC-MV treatment. Importantly, ASC-MVs stimulated the activation of AKT and ERK signaling pathways in those cells. The local injection of ASC-MVs at wound sites significantly increased the re-epithelialization, collagen deposition, and neovascularization and led to accelerated wound closure. Our data suggest that ASC-MVs can stimulate HUVEC, HaCAT, and fibroblast functions. ASC-MV therapy significantly accelerates wound healing, and the benefits of ASC-MVs may due to the involvement of AKT and ERK signaling pathways. This illustrates the therapeutic potential of ASC-MVs which may become a novel treatment paradigm for cutaneous wound healing.

Injuries to our skin trigger a cascade of spatially- and temporally-synchronized healing processes. During such endogenous wound repair, the role of fibroblasts is multifaceted, ranging from the activation and recruitment of innate immune cells through the synthesis and deposition of scar tissue to the conveyor belt-like transport of fascial connective tissue into wounds. A comprehensive understanding of fibroblast diversity and versatility in the healing machinery may help to decipher wound pathologies whilst laying the foundation for novel treatment modalities. In this review, we portray the diversity of fibroblasts and delineate their unique wound healing functions. In addition, we discuss future directions through a clinical-translational lens.

Oxidative damage is a critical cause of diabetic wounds. Exosomes from various stem cells could promote wound repair. Here, we investigated the potential mechanism by which exosomes from adipose-derived stem cells (ADSC-EXOs) promote diabetic wound healing through the modulation of oxidative stress. We found that ADSC-EXOs could promote proliferation, migration, and angiogenesis in keratinocytes, fibroblasts, and endothelial cells. Furthermore, ADSC-EXOs reduced the reactive oxygen species (ROS) levels in these cells and protected them against hypoxic and oxidative stress damage. Finally, the local injection of ADSC-EXOs at wound sites significantly increased collagen deposition and neovascularization while reducing ROS levels and cell death; thus, it led to accelerated diabetic wound closure. The mechanism underlying ADSC-EXO functions involved heat-shock protein 90 (HSP90) expressed on the cell surface; these functions could be inhibited by an anti-HSP90 antibody. Exosomal HSP90 could bind to the low-density lipoprotein receptor-related protein 1 (LRP1) receptor on the recipient cell membrane, leading to activation of the downstream AKT signaling pathway. Knockdown of LRP1 and inhibition of the AKT signaling pathway by LY294002 in fibroblasts was sufficient to impair the beneficial effect of ADSC-EXOs. In summary, ADSC-EXOs significantly accelerated diabetic wound closure through an exosomal HSP90/LRP1/AKT signaling pathway.

Background: The grading process in facial palsy (FP) patients is crucial for time- and cost-effective therapy decision-making. The House-Brackmann scale (HBS) represents the most commonly used classification system in FP diagnostics. This study investigated the benefits of linking machine learning (ML) techniques with the HBS. Methods: Image datasets of 51 patients seen at the Department of Plastic, Hand, and Reconstructive Surgery at the University Hospital Regensburg, Germany, between June 2020 and May 2021, were used to build the neural network. A total of nine facial poses per patient were used to automatically determine the HBS. Results: The algorithm had an accuracy of 98%. The algorithm processed the real patient image series (i.e., nine images per patient) in 112 ms. For optimized accuracy, we found 30 training runs to be the most effective training length. Conclusion: We have developed an easy-to-use, time- and cost-efficient algorithm that provides highly accurate automated grading of FP patient images. In combination with our application, the algorithm may facilitate the FP surgeon’s clinical workflow.

Background: Reliable, time- and cost-effective, and clinician-friendly diagnostic tools are cornerstones in facial palsy (FP) patient management. Different automated FP grading systems have been developed but revealed persisting downsides such as insufficient accuracy and cost-intensive hardware. We aimed to overcome these barriers and programmed an automated grading system for FP patients utilizing the House and Brackmann scale (HBS). Methods: Image datasets of 86 patients seen at the Department of Plastic, Hand, and Reconstructive Surgery at the University Hospital Regensburg, Germany, between June 2017 and May 2021, were used to train the neural network and evaluate its accuracy. Nine facial poses per patient were analyzed by the algorithm. Results: The algorithm showed an accuracy of 100%. Oversampling did not result in altered outcomes, while the direct form displayed superior accuracy levels when compared to the modular classification form (n = 86; 100% vs. 99%). The Early Fusion technique was linked to improved accuracy outcomes in comparison to the Late Fusion and sequential method (n = 86; 100% vs. 96% vs. 97%). Conclusions: Our automated FP grading system combines high-level accuracy with cost- and time-effectiveness. Our algorithm may accelerate the grading process in FP patients and facilitate the FP surgeon’s workflow.