Optimal Artificial Intelligence Based Automated Skin Lesion Detection and Classification Model

Skin lesions have become a critical illness worldwide,and the earlier identification of skin lesions using dermoscopic images can raise the survival rate.Classification of the skin lesion from those dermoscopic images will be a tedious task.The accuracy of the classification of skin lesions is improved by the use of deep learning models.Recently,convolutional neural networks(CNN)have been established in this domain,and their techniques are extremely established for feature extraction,leading to enhanced classification.With this motivation,this study focuses on the design of artificial intelligence(AI)based solutions,particularly deep learning(DL)algorithms,to distinguish malignant skin lesions from benign lesions in dermoscopic images.This study presents an automated skin lesion detection and classification technique utilizing optimized stacked sparse autoen-coder(OSSAE)based feature extractor with backpropagation neural network(BPNN),named the OSSAE-BPNN technique.The proposed technique contains a multi-level thresholding based segmentation technique for detecting the affected lesion region.In addition,the OSSAE based feature extractor and BPNN based classifier are employed for skin lesion diagnosis.Moreover,the parameter tuning of the SSAE model is carried out by the use of sea gull optimization(SGO)algo-rithm.To showcase the enhanced outcomes of the OSSAE-BPNN model,a comprehensive experimental analysis is performed on the benchmark dataset.The experimentalfindings demonstrated that the OSSAE-BPNN approach outper-formed other current strategies in terms of several assessment metrics.

Bioengineered skin organoids:from development to applications

Signifcant advancements have been made in recent years in the development of highly sophisticated skin organoids.Serving as three-dimensional(3D)models that mimic human skin,these organoids have evolved into complex structures and are increasingly recognized as efective alternatives to traditional culture models and human skin due to their ability to overcome the limitations of two-dimensional(2D)systems and ethical concerns.The inherent plasticity of skin organoids allows for their construction into physiological and pathological models,enabling the study of skin development and dynamic changes.This review provides an overview of the pivotal work in the progression from 3D layered epidermis to cyst-like skin organoids with appendages.Furthermore,it highlights the latest advancements in organoid construction facilitated by state-of-the-art engineering techniques,such as 3D printing and microfuidic devices.The review also summarizes and discusses the diverse applications of skin organoids in developmental biology,disease modelling,regenerative medicine,and personalized medicine,while considering their prospects and limitations.

Overview of Recombinant Skin Models and Progress in Their Application in Vitro Assessment of Toxicity and Efficacy

A recombinant skin model is a model in which skin cells are grown in vitro on a bioactive scaffold and provided with adequate nutrition to promote cell proliferation and differentiation to produce a mock skin structure and biological features. The development of recombinant skin models allows for effective and scientifically sound in vitro evaluation tests. This review briefly summarizes the overview of recombinant skin models and the progress of their application in in vitro evaluation which focuses on three aspects: skin irritation, skin corrosivity, and anti-skin aging. Moreover, an outlook on the future development of recombinant skin models is also provided in this review.

Antitumor Activity of Diallyl Sulfide in Two-StageMouse Skin Model of Carcinogenesis

It has been reported that diallyl sulfide (DAS), a sulfur-containing volatile compound in garlic (Allium sativum ), exerts anticarcinogenic activity in various rodent tumor models. In the present study, the antitumor property of DAS was tested in Swiss albino mice in the two steqe initiation-promotion mouse skin carcinogenesis. Skin cancers were initiated topically with a single subcarcinOgenic dose (52μg) of 7, 12-dimethyl benz (a) anthracene (DMBA). Promotion was performed by twice weekly applications of 12-O-tetradecanoyl phorbol-13-acetate (TPA) at a dose of 5μg/animal for 32 weeks. DAS was applied topically (250μg/animal) thrice weekly for 3 weeks for anti-initiating and 1 h prior to each promotion treatment for anti-promoting studies. The results showed that the treatment schedule of DAS can effectively delay the onset of tumorigenesis and reduce the cumulative number of tumors and the average number of tumors per mouse. In groups in which DAS applied prior to initiation or promotion, a significant population of the aniinals remained tumor-free till the termination of experiment. These findings suggest that DAS can effectively inhibit chemically induced mouse skincarcinogenesis.

Establishment of Mus Skin Photo-damage Model by 8-MOP plus UVA Irradiation

To establish a simple and reliable animal model of skin photo-damage, 20 mice were treated with 8-MOP and exposed to UVA （UVA 320-400 nm） for 24 h. After irradiation, the structure of the epidermis and dermis, collagen fibers, elastic fibers were observed by using HE staining and Weigert technique and compared with the normal controls. The acanthosis and epidemis proliferation with accompanying hyperkeratosis and parakeratosis were observed. Inflammatory infiltration was noted in the dermis. The elastic fibers became coarse, irregularly arranged and clustered, with their number increased. The collagen fibers showed obvious degeneration and some amorphous materials could also be observed. The blood vessels were irregularly dilated and vascular walls were thickened, with infiltration of inflammatory cells. It is concluded that murine photodamage model can be quickly, conveniently and reliably established by means of 8-MOP/UVA.

Chemopreventive Effects of Black Tea Polyphenols in Mouse Skin Model of Carcinogenesis

In the present investigations, the antitumorigenic effect of black tea polyphenols (BTP) in twcrstage mouse skin model of carcinogenesis was studied. The animals were initiated with a single 'subcarcinogenic' topical dose (52 μg/200 μl acetone ) of 7, 12-dimethylbenzanthracene (DMBA). To evaluate the anti-tumour initiating activity, BTP was topically applied twice a week for three weeks prior to DMBA application, followed by topical treatment with 12-o-tetradecanoyl phorbol-13-acetate (TPA) (5 μg/200 μl acetone, 2x/wk. ) as promoter. For evaluation of antitumor promoting activity, BTP was applied prior to each treatment of TPA. BTP application showed marked inhibitory effect as antitumour initiator as well as antitumour promoter in mouse skin medel of two-stage carcinogenesis. Since initiation involves genetic pathway and tumour promotion involves epigenetic pathway, it seems that BTP exerts its antitumorigenic effect by altering both genetic and epigenetic pathways

Modelling and Backstepping Motion Control of the Aircraft Skin Inspection Robot

Aircraft skin health concerns whether the aircraft can fly safely.In this paper,an improved mechanical structure of the aircraft skin inspection robot was introduced.Considering that the aircraft skin surface is a curved environment,we assume that the curved environment is equivalent to an inclined plane with a change in inclination.Based on this assumption,the Cartesian dynamics model of the robot is established using the Lagrange method.In order to control the robot’s movement position accurately,a position backstepping control scheme for the aircraft skin inspection robot was presented.According to the dynamic model and taking into account the problems faced by the robot during its movement,a position constrained controller of the aircraft skin inspection robot is designed using the barrier Lyapunov function.Aiming at the disturbances in the robot,we adopt a fuzzy system to approximate the unknown dynamics related with system states.Finally,the simulation results of the designed position constrained controller were compared with the sliding mode controller,and prove the validity of the position constrained controller.

Numerical Model of Thermal Responses in Human Skin under Low-Level Radiant Exposure

For improving the evaluative accuracy of thermal protective clothing performance,the estimated methods of thermal response of skin and the human body were comprehensively described and analyzed.This study reviewed the one-dimensional(1D)and multi-dimensional heat transfer models of the skin heat transfer model,including the corresponding heat and moisture transfer.Further,it investigated the influence of moisture transfer in vivo heat transfer.Moreover,the thermo-physiological model with active regulation was analyzed,especially in the local extremes,such as fingers and toes.Additionally,future research trends are discussed in estimating thermal protective performance.In developing the thermal protective model,it is essential to consider the geometric structure,local heat thermoregulation of extremities,and mass transfer inside the skin.

Deep Learning with Backtracking Search Optimization Based Skin Lesion Diagnosis Model

Nowadays,quality improvement and increased accessibility to patient data,at a reasonable cost,are highly challenging tasks in healthcare sector.Internet of Things(IoT)and Cloud Computing(CC)architectures are utilized in the development of smart healthcare systems.These entities can support real-time applications by exploiting massive volumes of data,produced by wearable sensor devices.The advent of evolutionary computation algorithms andDeep Learning(DL)models has gained significant attention in healthcare diagnosis,especially in decision making process.Skin cancer is the deadliest disease which affects people across the globe.Automatic skin lesion classification model has a highly important application due to its fine-grained variability in the presence of skin lesions.The current research article presents a new skin lesion diagnosis model i.e.,Deep Learning with Evolutionary Algorithm based Image Segmentation(DL-EAIS)for IoT and cloud-based smart healthcare environments.Primarily,the dermoscopic images are captured using IoT devices,which are then transmitted to cloud servers for further diagnosis.Besides,Backtracking Search optimization Algorithm(BSA)with Entropy-Based Thresholding(EBT)i.e.,BSA-EBT technique is applied in image segmentation.Followed by,Shallow Convolutional Neural Network(SCNN)model is utilized as a feature extractor.In addition,Deep-Kernel Extreme LearningMachine(D-KELM)model is employed as a classification model to determine the class labels of dermoscopic images.An extensive set of simulations was conducted to validate the performance of the presented method using benchmark dataset.The experimental outcome infers that the proposed model demonstrated optimal performance over the compared techniques under diverse measures.

Apple of Sodom (<em>Calatropis procera</em>) Callus Extract, a Novel Skincare Active and Its Biological Activity in Skin Models When Combined with Dead Sea Water

Background: Calotropis procera (C. procera), is an authentic plant naturally grown in the flora of Dead Sea region. Despite its toxicity, C. procera presents healing properties. However, it has not been implemented yet in cosmetics as an active ingredient. Objective: The biological effects of C. procera callus extract on skin were elucidated solely and in combination with Dead Sea water (DSW). Methods: The capability of C. procera extract to protect against skin inflammation and irritation was tested on ex vivo human skin organ culture by LPS and SDS addition respectively. Viability and cytokine secretion were evaluated. The combination of C. procera extract with Dead Sea water was tested on full thickness skin equivalents. Gene expression and relevant biochemical markers for glycolysis, hypoxia and extracellular matrix balance were tested. Results: C. procera extract exhibits a protective biological activity against skin irritation and inflammation at the biochemical level. Furthermore, a combination of C. procera extract and DSW demonstrates a potential contribution for skin wellbeing via enhance energy production, resistance to hypoxia and extracellular matrix balance. Conclusions: Topical application of C. procera callus extract might support skin balance and wellbeing at the molecular level. Hence, it is recommended for new cosmetic formulae as standalone or in combination with Dead Sea water, in the effort to achieve anti-aging bio-activity that is working beyond skin aging symptoms, especially via skin calming effects and skin energy enhancement.

Influence of Surface Topography on the Tactile Friction of Medical Compression Textiles against a Mechanical Skin Model

Influence of surface topography on the tactile friction of medical compression textiles was studied in this paper. The friction behavior was investigated for three kinds of medical textiles with various structures and compositions by using a textile friction analyzer under dry condition. In order to simulate the contacts of textiles/human finger, a mechanical skin model with similar texture to the skin and applied normal load oflN were selected. Meanwhile, the 3D surface topography of textiles was measured using a digital microscope. The topographical data were analyzed concerning height distribution and material ratio, and the real contact area was estimated as a function of penetration depth. Results showed that the investigated textiles revealed a significant variation on the friction coefficients, which were （ 0.41 ± 0.01 ） （ polyamide, jersey 2 × 2 ）, （0.56 ± 0. 01） （cotton, jersey 2×2） and （0. 47 ± 0. 01） （polyamide, jersey 1 × 1 ）, respectively. The textile with higher friction coefficient was found to own a relative compact and homogenous surface and larger contact area, vice versa.

Fingertip skin models for analysis of the haptic perception of textiles

This paper presents finite element models of the fingertip skin which have been created to simulate the contact of textile objects with the skin to gain a better understanding of the perception of textiles through the skin, the so-called hand of textiles. Many objective and subjective techniques have already been developed for analysing the hand of textiles;however, none of them provide exact overall information concerning the sensation of textiles through the skin. As the human skin is a complex heterogeneous hyperelastic body composed of many particles, some simplifications had to be made at the early stage of building the models;however, their utilitarian value was maintained. The models relate only to mechanical loading of the skin. They predict a low deformation of the fingertip skin under the pressure of virtual heterogeneous material: acrylic, coarse wool, and steel.

3D Numerical Simulation of Epidermal Skin Turnover Process Using a Particle Model

Skin is the largest organ of the human body. In recent years, concern regarding the cosmetics area has increased, and research studies on anti-aging therapy or cosmetics have been rapidly conducted. Skin cells are not only changing its shape but also its physical properties during the epidermal skin turnover process. Computational simulation can be useful in further understanding the mechanisms of skin formation. We propose a particle model that can handle complex biological phenomena, including cell interactions and is a suitable method for simulating skin formation. The particle model was applied to simulate three-dimensional skin formation accompanied by proliferation and cornification of skin cells. The simulation results represented and reproduced the epidermal skin turnover phenomenon.

Integrated Organ-on-a-chip with Human-induced Pluripotent Stem Cells Directional Differentiation for 3D Skin Model Generation

Keratinocytes and fibroblasts,derived from hiPSCs,were used to construct the human epidermal model by a culture patch made by monolayer poly-(lactic-co-glycolic acid)(PLGA)nanofibers and a human skin-on-a-chip device.Unlike the conventional culture dish method,two different epidermal cells are successfully adhered to the front and back sides of the patch,which produces a three-dimensional nanofibrous scaffold similar to a natural extracellular matrix before the patch was cultured in the skin-on-a-chip device to mimic the physiological conditions of human skin.As expected,the differentiated hiPSCs show the expression of keratinocyte-and fibroblast-specific proteins on the patch,and the layering is found between these two kinds of cells,indicating that this approach creates a powerful in vitro system for modeling skin development and diseases.

Use of Acellular Fish Skin for Dura Repair in an Ovine Model: A Pilot Study

Recently the use of biologic materials as dura mater repair patches has been increasing. The purpose of this study is to assess the basis for efficacy and safety of using a novel fish derived acellular dermis (Kerecis Omega3 DuraTM). In an ovine model a craniotomy under general anaesthesia was performed. A defect was produced in the dural covering of approximately 1 × 2 cm and closed with an onlay technique, with Kerecis Omega3 Dura. The bone defect was covered with the bony flap and the overlying tissues closed in layers. At 2, 5, 8 and 11 weeks the sheep underwent MRI scanning followed by euthanasia, necropsy and histological assessment. MRI images taken at 2, 5, 8 and 11 weeks showed initially moderate inflammatory response, which diminished over time, and at 11 weeks no evidence of inflammation existed. There was evidence of cerebrospinal fluid leakage at no time point. Necropsy revealed some adhesions at 5 and 8 weeks, in particular at 5 weeks, but at 11 weeks there were no adhesions found. From 2 - 11 weeks, there was evidence of initially an inflammatory reaction followed by neodura formation at the defect site through cellular ingrowth and remodeling of the acellular fish skin. Histology showed a histiocytic foreign body reaction initially that subsided over time. As early as 8 weeks there was evidence of neodura formation and by 11 weeks there was a minimal inflammatory response with an intact neodura formed. In this pilot study the Kerecis Omega3 Dura patches performed in a safe and efficacious manner. This new material needs to be fully assessed and compared with other products that are currently on the market in a larger scale animal study.

Mutual Learning Model for Skin Lesion Classification

Skin lesion classification in the dermoscopy images exerts an enormous function on the improvement of diagnostic performance and reduction of melanoma deaths. This skin lesion classification task remains a challenge. Deep learning requires a lot of training data, and the classification algorithms of skin lesions have certain limitations. These two points make the accuracy of the skin lesion classification needs to be further improved. In this paper, a mutual learning model was presented to separate malignant from benign skin lesions using the skin dataset. This model enabled dual deep convolutional neural networks to mutually learn from each other. Experimental results on the ISIC 2016 Skin Lesion Classification dataset indicate that the mutual learning model obtains the most advanced performance.

Validation of the Suitability of Stripped Lipid as a Skin Model in Plasma Medical Investigations

In this work, the suitability of lipid stripping as an alternative model of stratum corneum for plasma medical studies was investigated. Plasma treatment experiments were performed on samples prepared by the cyanoacrylat stripping method. Therefore, two different dielectric barrier discharge-based plasma sources driven by high-voltage pulses in the microsecond and nanosecond range were applied. The lipid sample heating, change in pH-value, and the interaction with plasma-induced UV-radiation are presented and discussed with respect to existing findings on skin samples. After the plasma treatment, the lipid stripping shows similar changes compared to human skin relating to sample heating and pH-value. The investigation of the interplay with UV- radiation shows a high absorption in the wavelength range of 250 nm up to 400 nm. Further, the thickness, surface structure, and composition of lipid stripping samples were determined. The stripped sample shows a thickness of 3 ± 1 μm whereby approximately 30% of the sample surface is covered by lipids. In addition, it was shown that there are no changes in structure caused by the sample preparation. Based on the results of this work, it can be stated that lipid stripping represents an appropriate skin model for plasma medical investigations.

Reconstruction of 3D Skin Model and Its Application in Evaluation the Efficacy of Cosmetic Raw Materials and Active Intredients

Via the use of Mimedisc~? as a scaffold, the normal human dermal fibroblasts were first seeding into the scaffold to form a dermal equivalent after three weeks, and then seeding normal human epidermal keratinocytes on it, followed by immersion and air-liquid interphase culture stage, to finally form a 3 D sponge matrix skin model which has a very similar structure of normal human skin(NHS). The results of Masson staining, and immunohistochemistry(IHC), immunofluorescence(IF) staininccg show that this skin model has a very similar structure and key protein expression of NHS. Meanwhile, this model was used as a tool to investigate the effect of Himalaya cedar extract on Dermal-Epidermal Junction(DEJ) in vitro. Results show that the Himalayan cedar extract can significantly increase the thickness of the epidermis, thus increase the barrier capacity of the skin to resist external environment. Further, this Himalaya cedar extract can promote the expressions of Laminin 5 and Collagen VII of DEJ. The expressions of the Laminin 5 and Collagen VII increased 20% and 47% respectively.So the Himalaya cedar extract displays the potential to be applied in development of anti-aging cosmetics.

ICU脓毒性休克患者发生急性皮肤衰竭风险预测模型构建及验证

目的构建ICU脓毒性休克患者发生急性皮肤衰竭风险预测模型。方法选取2020年1月至2022年1月某医院ICU收治的491例脓毒性休克患者临床资料,单因素和多因素分析筛选出ICU脓毒性休克患者发生急性皮肤衰竭的影响因素,基于影响因素构建预警模型并验证模型的预测效果。结果491例ICU脓毒性休克患者发生急性皮肤衰竭71例(14.46%)。体表面积(OR=38.030)、国家早期预警评分(OR=2.457)、序贯器官衰竭评分(OR=4.018)、动脉血乳酸值(OR=7.404)、外周灌注指数(OR=0.003)、毛细血管再充盈时间(OR=36.864)均为ICU脓毒性休克患者发生急性皮肤衰竭的影响因素(P<0.01或P<0.05)。基于上述影响因素建立预测模型和绘制列线图,模型ROC曲线下面积为0.964,最大约登指数对应的风险预测值82.71%,预测临界值评分为≥233分,Hosmer-Lemeshow拟合优度检验χ2=0.586,P=0.996,模型校准曲线的实际曲线与理想曲线几乎重合。结论基于ICU脓毒性休克患者发生急性皮肤衰竭风险因素构建的列线图预测模型具有良好的一致性与区分度,风险预测值评分为≥233分,为ICU脓毒性休克患者发生急性皮肤衰竭风险预警与防治提供依据。