Developing a Simple Burn Model in Rats of Different Ages

Segmentation and quantitative analysis of optical coherence tomography (OCT) images of laser burned skin based on deep learning

Evaluation of skin recovery is an important step in the treatment of burns. However, conventional methods only observe the surface of the skin and cannot quantify the injury volume. Optical coherence tomography (OCT) is a non-invasive, non-contact, real-time technique. Swept source OCT uses near infrared light and analyzes the intensity of light echo at different depths to generate images from optical interference signals. To quantify the dynamic recovery of skin burns over time, laser induced skin burns in mice were evaluated using deep learning of Swept source OCT images. A laser-induced mouse skin thermal injury model was established in thirty Kunming mice, and OCT images of normal and burned areas of mouse skin were acquired at day 0, day 1, day 3, day 7, and day 14 after laser irradiation. This resulted in 7000 normal and 1400 burn B-scan images which were divided into training, validation, and test sets at 8:1.5:0.5 ratio for the normal data and 8:1:1 for the burn data. Normal images were manually annotated, and the deep learning U-Net model (verified with PSPNe and HRNet models) was used to segment the skin into three layers: the dermal epidermal layer, subcutaneous fat layer, and muscle layer. For the burn images, the models were trained to segment just the damaged area. Three-dimensional reconstruction technology was then used to reconstruct the damaged tissue and calculate the damaged tissue volume. The average IoU value and f-score of the normal tissue layer U-Net segmentation model were 0.876 and 0.934 respectively. The IoU value of the burn area segmentation model reached 0.907 and f-score value reached 0.951. Compared with manual labeling, the U-Net model was faster with higher accuracy for skin stratification. OCT and U-Net segmentation can provide rapid and accurate analysis of tissue changes and clinical guidance in the treatment of burns.

In Vitro and In Vivo Evaluation of Metformin Hydrochloride Hydrogels Developed with Experimental Design in the Treatment of Burns

Burns alter the normal skin barrier and affect various host defense processes that help prevent infections. An ineffective repair process can lead to serious damage, such as the onset of an infection or skin loss, which can then harm the surrounding tissues and ultimately the entire organism. This study aims to prepare in situ gels containing metformin hydrochloride, a compound known for its wound healing properties. To achieve this, in situ gels were prepared using three different gelling agents (Poloxamer 407®, Carbopol 934®, and sodium carboxymethyl cellulose (Na-CMC)) and three different concentrations of metformin hydrochloride (4 mg/g, 6 mg/g, and 8 mg/g), which were optimized through experimental design. Metformin concentration and gelling agent type were independent variables, and the loaded amount and the percentage of metformin released after 150 min were chosen as dependent variables in the optimization process. After determining the optimum values of the dependent variables according to the ANOVA analysis results, in vivo studies were conducted with optimized hydrogel formulations. Two groups, each consisting of seven Wistar rats with a burn model, were treated with metformin-poloxamer 407® gels at doses of 4 mg/g and 8 mg/g for 29 days. The results were then compared to untreated and placebo gel groups. Rats treated with in situ Poloxamer 407® hydrogels containing metformin hydrochloride showed a significant reduction in the size of the burned area after 29 days of treatment. However, for a comprehensive understanding of the wound healing mechanism, further studies such as immuno-histochemical and cell culture studies are needed.

Small animal models of thermal injury

Burns are a severe form of trauma that account for 1.1 million cases necessitating medical attention and 4500 mortalities annually in the United States alone. Importantly, the initial trauma is succeeded by extensive, prolonged physiological alterations that detrimentally impact multiple organ systems. Given the complexity of post-burn pathophysiology, in vitro experiments are insufficient to model thermal injuries. Therefore, compatible animal burn models are essential for studying burn-related phenomena. In this chapter, we discuss commonly employed small animal burn models and their comparability and applicability to human studies. In particular, we compare post-burn wound healing between the species as well as relevant hypermetabolic and inflammatory characteristics, providing a better understanding of the pros and cons of utilizing a small animal surrogate for human burns. We further provide an overview of the rodent scald burn model methodology as well as a comparison between elderly, aged and young animals, providing a guide for tailoring animal model choice based on the relevant research question.

Fractal analysis of rat dermal tissue in the different injury states

Scar formation and chronic ulcers can develop following a skin injury. They are the result of the over- or underproduction of collagen. It is very important to evaluate the quality and quantity of the collagen that is produced during wound healing, especially with respect to its structure, as these factors are very important to a complicated outcome. However, there is no standard way to quantitatively analyse dermal collagen. As prior work characterised some potentially fractal properties of collagen, it was hypothesised that collagen structure could be evaluated with fractal dimension analysis. Small-angle X-ray scattering technology (SAXS) was used to evaluate the dermis of rats exposed to graft harvest, burn, and diabetic pathologic states. It was found that almost all collagen structures could be quantitatively measured with fractal dimension analysis. Further, there were significant differences in the three-dimensional (3-D) structure of normal collagen versus that measured in pathologic tissues. There was a significant difference in the 3-D structure of collagen at different stages of healing. The findings of this work suggest that fractal analysis is a good tool for wound healing analysis, and that quantitative collagen analysis is very useful for assessing the structure of dermal collagen.