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Abstract Purpose and Background: To create awareness among dermatosurgeons about the versatility of keystone flaps in re-surfacing post-excisional small, medium and large skin defects. Aims and Objectives: Single-staged tension-free re-surfacing of various sized skin defects using keystone flap and to have least donor site morbidity, primary healing and maximum functional outcome. Material and Methods: This retrospective study was conducted, between October 2021 - January 2023 in Department of Plastic Surgery, PGIMS Rohtak, on 15 males and 1 female aged between 18 - 65 years. Sixteen Keystone flaps (type IIA n=13, Omega cum Sydney melanoma unit modification n=3) were utilized for resurfacing skin defects arising after excision of basal cell carcinoma (n=3) and benign hairy nevus (n=2) on cheek, basal cell carcinoma forehead (n=1), electric burns on deltoid (n=2), giant neurofibroma back (n=1), tattoo forearm (n=3), chronic non-specific granuloma thumb (n=2) and pilonidal sinus disease (n=2). Skin with maximum expansibility was chosen as donor site with utmost care of facial lines and its aesthetic subunits. Flaps were dissected all around preserving maximum number of hand-held Doppler-identified perforators in pedicular area. Sutures were removed on 10th to 15th post-operative day. Follow-ups ranged from 2 to 15 months. Results: None had wound dehiscence or loss of flap. Conclusion: Keystone flaps have defect-adaptive design, simple bio-geometry, technical simplicity, decreased downtime, cost effectivity and efficiency and can be designed to resurface post-excisional skin defect from head to toe with acceptable results, therefore should strongly be considered by dermatosurgeons while excising skin lesions. Keywords: Keystone flap, perforators, pedicular area, Author(s): Abhinav Singh (corresponding author) [1]; Rohini Singh [2]; Gaurav Chaturvedi [1]; Malika Singh [3]; RB Singh [4] Introduction Since many dermatologists have turned into dermatosurgeons, they need to know [...]

Background Objectives Animals Materials and Methods Results Conclusions and Clinical Relevance Hospital‐related dermatological conditions are well‐studied and reported in human medicine. However, studies about these dermatological disorders in veterinary medicine are lacking.To report the incidence, type and distribution of hospital‐acquired skin lesions (HASL) in dogs, and to investigate risk factors that may be associated with their development.Hospitalised client‐owned dogs with HASL and a control group of hospitalised dogs without skin lesions.Prospective clinical evaluation of all HASL and dermatological tests, when indicated, were performed, over 6 months. A variety of potentially predisposing factors also were recorded.Thirty‐one dogs with HASL and a matched control group of 60 hospitalised dogs without skin lesions were included. The incidence of HASL was 11.2% (31 of 278). The most common lesion was erythema in 74.2% of dogs (23 of 31) and the most affected area was the abdomen in 58.1% (18 of 31) of dogs. Faecal and/or urinary incontinence was identified as an important risk factor for the development of skin lesions during hospitalisation (odds ratio 14.445, 95% confidence interval 1.444–144.479, p = 0.023). Immobilisation and changes in body temperature also may play a role in the development of such lesions in dogs.Faecal and/or urinary incontinence was found to be an important factor in the development of HASL. The impact of HASL on patient outcomes and the prevention of these lesions requires further investigation. [ABSTRACT FROM AUTHOR]

Variational autoencoders (VAEs) are generative models known for learning compact and continuous latent representations of data. While they have proven effective in various applications, using latent representations for classification tasks presents challenges. Typically, a straightforward approach involves concatenating the mean and variance vectors and inputting them into a shallow neural network. In this paper, we introduce a novel approach for variational autoencoders, named VAE-GNA, which integrates Gaussian neurons into the latent space along with attention mechanisms. These neurons directly process mean and variance values through a suitable modified sigmoid function, not only improving classification, but also optimizing the training of the VAE in extracting features, in synergy with the classification network. Additionally, we investigate both additive and multiplicative attention mechanisms to enhance the model's capabilities. We applied the proposed method to automatic cancer detection using near-infrared (NIR) spectral data, showing that the experimental results of VAE-GNA surpass established baselines for spectral datasets. The results obtained indicate the feasibility and effectiveness of our approach. [ABSTRACT FROM AUTHOR]

Copyright of Summa, Animali da Compagnia is the property of Point Veterinaire Italie s.r.l. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives Extra-osseous (EO) manifestations are poorly characterized in chronic recurrent multifocal osteomyelitis (CRMO). This study aimed to further define the frequency, characteristics and treatment of EO events in CRMO and whether different phenotypes can be distinguished and benefit from special management. Methods This multicentre retrospective study included CRMO patients followed in several paediatric rheumatology departments in France between 2015 and 2022. EO manifestations were defined as skin lesions, gastrointestinal manifestations, arthritis, enthesitis, sacroiliitis, uveitis, vasculitis and fever. At the last visit, the physician defined CRMO as active in the presence of clinical manifestations including both osseous and EO symptoms. Results We included 133 patients; 87 (65.4%) were girls and the median age at first symptoms was 9.0 years (interquartile range 7.0–10.0). EO manifestations were described in 90 (67.7%) patients, with a predominance of skin lesions [ n  = 51/90 (56.7%)], followed by sacroiliitis [ n  = 38/90 (42.2%)], enthesitis [ n  = 21/90 (23.3%)], arthritis [ n  = 14/90 (15.6%)] and gastrointestinal manifestations [ n  = 6/90 (6.7%)]. The use of non-steroidal anti-inflammatory drugs and bisphosphonates did not differ by the presence or not of EO manifestations. Biologics were taken more frequently by patients with than without EO manifestations (P  < 0.001); TNF inhibitors were used in 33 (36.7%) EO-positive patients. Under this treatment, 18 (54.5%) patients achieved complete remission of osseous and EO manifestations. At the last visit, more EO+ than EO− patients were on treatment (P  = 0.009), with active disease in 58 (64.4%) patients. Conclusion The analysis of EO manifestations in CRMO delineates two groups of patients in terms of severity and treatments used. Our study opens up new pathophysiological leads that may underlie the wide range of CRMO phenotypes. [ABSTRACT FROM AUTHOR]

Introduction: In the aftermath of anthrax bioterrorism, the US military began its smallpox immunization program in 2002. Dryvax was superseded in 2008 by ACAM2000, a second-generation smallpox vaccine, after clinical trials demonstrated favorable outcomes. However, these trials focused on significant adverse effects and provided less specific classifications and descriptions of cutaneous eruptions. The purpose of this systematic review was to investigate the clinicopathological characteristics of skin lesions that emerged in US military personnel following the reinstatement of new smallpox immunizations. Methods: PubMed, ScienceDirect, and Google Scholar were searched. The search was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, using appropriate keywords. Results: Of the 467 studies initially identified, 5 (1%) were analyzed, with a sample size of 15. There were 10 men and 4 women. The mean age of presentation was 24.3 years. The interval between inoculation and eruption was 15 days. The length of the eruption until clearance was 36.26 days. Grossly, most skin lesions were described as having papules (n = 9). Histological examination revealed vesicles with spongiotic dermatitis and eosinophils (n = 5) and a dermal hypersensitivity reaction with lymphocytic vasculitis (capillaritis) (n = 2). Definitive diagnoses included acral and vesiculopustular dermatosis (n = 7), generalized vaccinia (GV) (n = 1), and progressive vaccinia (n = 1). Concurrent or near-concurrent vaccination was administered (n = 12). Conclusion: Although rare, clinically significant skin lesions can occur after ACAM2000 administration. A feared complication of progressive vaccinia has been reported; however, to determine its causal relationship, further clinical trials are required to provide universal guidelines. [ABSTRACT FROM AUTHOR]

Skin cancer diagnosis greatly benefits from advanced machine learning techniques, particularly fine-tuned deep learning models. In our research, we explored the impact of traditional machine learning and fine-tuned deep learning approaches on prediction accuracy. Our findings reveal significant improvements in predictability and accuracy with fine-tuning, particularly evident in deep learning models. The CNN, SVM, and Random Forest Classifier achieved high accuracy. However, fine-tuned deep learning models such as EfficientNetB0, ResNet34, VGG16, Inception _v3, and DenseNet121 demonstrated superior performance. To ensure comparability, we fine-tuned these models by incorporating additional layers, including one flatten layer and three densely interconnected layers. These layers play a crucial role in enhancing model efficiency and performance. The flatten layer preprocesses multidimensional feature maps, facilitating efficient information flow, while subsequent dense layers refine feature representations, capturing intricate patterns and relationships within the data. Leveraging LeakyReLU activation functions in the dense layers mitigates the vanishing gradient problem and promotes stable training. Finally, the output dense layer with a sigmoid activation function simplifies decision making for healthcare professionals by providing binary classification output. Our study underscores the significance of incorporating additional layers in fine-tuned neural network models for skin cancer classification, offering improved accuracy and reliability in diagnosis. [ABSTRACT FROM AUTHOR]

The phenomenon of child abuse/maltreatment is underestimated and often represents a difficult challenge for healthcare professionals and forensic pathologists who must proceed with the differential diagnosis with accidental or self-induced events, or with lesions due to pathologies that overlap with that of mistreatment, defined as "Mimics". This study presents a case series with the aim of discussing lesions that may mimic signs of physical abuse in children but are due to a different etiology to raise awareness and train healthcare professionals and forensic pathologists on possible confounding factors in order to avoid diagnostic errors. Six cases of "Mimics" out of 418 cases of suspected mistreatment (1.43% of cases) were identified, presenting skin lesions initially classified as injuries of abuse due to their location and type and, in particular, sexual abuse for three cases. Then, the lesions and the subjects, in particular the anamnestic history, were examined by a multidisciplinary team and the diagnosis of genital lichen sclerosus et atrophicus in three cases, and the results of popular healing techniques (i.e., "cupping") in the other three cases were ascertained. These situations require specific skills and a forensic background from healthcare professionals to conduct a correct differential diagnosis and the intervention of a multidisciplinary team to investigate every possible pathology or alternative therapeutic practice that could simulate child abuse. In particular, when "mimics" are due to alternative medicine, it should not strictly be considered child abuse, but professionals must be aware of the hypothesis of mistreatment in case of non-medical indication or potential personal injuries from other crimes, such as illegal practice of the medicine. This awareness is also crucial to direct the child toward appropriate medical care, and it is essential to recognize that these conditions can coexist within the same clinical presentation. [ABSTRACT FROM AUTHOR]

Abstract Background Two outbreaks of swinepox were investigated in free-range domestic pig farms located in the northeastern side of Sicily, Italy. The disease is generally self-limiting with a low mortality rate, but morbidity can reach high rates in case of poor sanitary conditions, improper husbandry practices and ectoparasitic infestation. The presented cases are the first ever reported on the island and part of the few cases reported in domestic pigs. Case presentation Carcasses condemned at the slaughterhouse and deceased pigs from Farm A and Farm B respectively, were referred for post-mortem examination and further investigations, with a strong suspect of SwinePox virus (SWPV) infection. Twelve deceased pigs were examined in total, showing poor body condition and pustular lesions scattered all over the cutaneous surfaces. Moreover, pigs from Farm B showed ocular lesions classified from Grade I to IV (from mild conjunctivitis to severe keratoconjunctivitis with corneal oedema, opacity, and ulcers). Final diagnosis was pursued by the microscopic assessment of skin lesions in both farms, which revealed the typical SWPV-lesion appearance, such as severe and disseminated ulcerative dermatitis and suspected inclusion bodies multifocally observed in the epidermis. Moreover, negative staining Electron Microscopy (nsEM) was performed on skin lesions and ocular swabs from Farm B, revealing in two samples the presence of brick-shaped viral particles, 220 nm long and 160 nm wide, with irregularly arranged surface tubules, identified as SWPV. The gene encoding the 482-bp fragment of the virus late transcription factor–3 was detected by PCR and sequencing revealed 99.79% identity and 100% query-cover with a strain previously isolated in Germany. Field clinical assessment was then performed in Farm B, revealing high overcrowding, poor sanitary conditions and improper husbandry practices, which are relevant risk factors for SWPV transmission. Conclusions The present is the first case report of SWPV in free-range pigs raised in Sicily, an island of the Southern coast of Italy, and wants to raise awareness on a neglected disease, and cause of animal health and welfare issues.

Background: Skin diseases are severe diseases. Identification of these severe diseases depends upon the abstraction of atypical skin regions. The segmentation of these skin diseases is essential to rheumatologists in risk impost and for valuable and vital decision‐making. Skin lesion segmentation from images is a crucial step toward achieving this goal—timely exposure of malignancy in psoriasis expressively intensifies the persistence ratio. Defies occur when people presume skin diseases they have without accurately and precisely incepted. However, analyzing malignancy at runtime is a big challenge due to the truncated distinction of the visual similarity between malignance and non‐malignance lesions. However, images' different shapes, contrast, and vibrations make skin lesion segmentation challenging. Recently, various researchers have explored the applicability of deep learning models to skin lesion segmentation. Materials and methods: This paper introduces a skin lesions segmentation model that integrates two intelligent methodologies: Bayesian inference and edge intelligence. In the segmentation model, we deal with edge intelligence to utilize the texture features for the segmentation of skin lesions. In contrast, Bayesian inference enhances skin lesion segmentation's accuracy and efficiency. Results: We analyze our work along several dimensions, including input data (datasets, preprocessing, and synthetic data generation), model design (architecture, modules), and evaluation aspects (data annotation requirements and segmentation performance). We discuss these dimensions from seminal works and a systematic viewpoint and examine how these dimensions have influenced current trends. Conclusion: We summarize our work with previously used techniques in a comprehensive table to facilitate comparisons. Our experimental results show that Bayesian‐Edge networks can boost the diagnostic performance of skin lesions by up to 87.80% without incurring additional parameters of heavy computation. [ABSTRACT FROM AUTHOR]

Accurate automatic segmentation of skin lesions is crucial to assist physicians in clinical diagnosis and treatment. Aiming at the problem that convolutional structure can extract local feature information but cannot model long-range dependencies, while Transformer can extract global context information but suffers from the loss of detail information, this paper proposed a parallel multi-scale automatic segmentation network PDTransCNN that integrated CNN and Transformer. Firstly, it constructed multi-level local correlation and captured long-range dependencies between contextual information by extracting the feature information of dermatological images in parallel with the CNN branch based on ResNet34 and Transformer branch. Secondly, it utilized the feature fusion module (FM) to complement the key information between the two branches of features and enhance the dependencies of the semantic information. Finally, it used the Transformer decoding unit to gradually fuse the semantic information extracted from the encoding block and the fusion unit in order to obtain the final segmentation result. The model was tested on ISIC2016, ISIC2017 and ISIC2018 datasets with Dice coefficients as high as 91.72%, 87.34% and 90.01%, and loU values of 85.60%, 79.55% and 83.67%, respectively. The experimental results show that PDTransCNN has better segmentation performance compared to other segmentation models and can segment skin lesion images clearly and effectively. [ABSTRACT FROM AUTHOR]

Persistent infections caused by Strongyloides stercoralis are probably underestimated in the elderly Italian population. This nematode is unique among helminths: it can last asymptomatically in the host for decades and may present with a broad range of clinical pictures upon reactivation. Misdiagnosis often occurs even when the clinical picture is suggestive. If undetected, this parasitosis can lead to serious consequences when hyperinfection occurs. Herein, we report two peculiar clinical cases of complicated strongyloidiasis with multiple skin lesions. The aim of our report is to lead clinicians to familiarize themselves with skin patterns and clinical features that can suggest a possible underlying strongyloidiasis. [ABSTRACT FROM AUTHOR]

Background: Two outbreaks of swinepox were investigated in free-range domestic pig farms located in the northeastern side of Sicily, Italy. The disease is generally self-limiting with a low mortality rate, but morbidity can reach high rates in case of poor sanitary conditions, improper husbandry practices and ectoparasitic infestation. The presented cases are the first ever reported on the island and part of the few cases reported in domestic pigs. Case presentation: Carcasses condemned at the slaughterhouse and deceased pigs from Farm A and Farm B respectively, were referred for post-mortem examination and further investigations, with a strong suspect of SwinePox virus (SWPV) infection. Twelve deceased pigs were examined in total, showing poor body condition and pustular lesions scattered all over the cutaneous surfaces. Moreover, pigs from Farm B showed ocular lesions classified from Grade I to IV (from mild conjunctivitis to severe keratoconjunctivitis with corneal oedema, opacity, and ulcers). Final diagnosis was pursued by the microscopic assessment of skin lesions in both farms, which revealed the typical SWPV-lesion appearance, such as severe and disseminated ulcerative dermatitis and suspected inclusion bodies multifocally observed in the epidermis. Moreover, negative staining Electron Microscopy (nsEM) was performed on skin lesions and ocular swabs from Farm B, revealing in two samples the presence of brick-shaped viral particles, 220 nm long and 160 nm wide, with irregularly arranged surface tubules, identified as SWPV. The gene encoding the 482-bp fragment of the virus late transcription factor–3 was detected by PCR and sequencing revealed 99.79% identity and 100% query-cover with a strain previously isolated in Germany. Field clinical assessment was then performed in Farm B, revealing high overcrowding, poor sanitary conditions and improper husbandry practices, which are relevant risk factors for SWPV transmission. Conclusions: The present is the first case report of SWPV in free-range pigs raised in Sicily, an island of the Southern coast of Italy, and wants to raise awareness on a neglected disease, and cause of animal health and welfare issues. [ABSTRACT FROM AUTHOR]

Artificial intelligence assists medical practitioners with disease diagnosis from acute to chronic illnesses and has brought significant breakthrough in image-oriented analysis of diseases. Skin cancer is one of the deadliest diseases, posing a great threat to human health. Skin cancer warrants early and precise examination of skin lesions to prevent mortality. Skin lesions can be examined by biopsy, an invasive procedure to remove piece of tissue, tested in a laboratory. Biopsy is a painful procedure. The predictive models in artificial intelligence are found to be useful in analyzing skin lesions-based images. Hence, in this paper, we have analyzed 10,015 skin lesion-based images and classified seven types of skin diseases among which, one of them is melanoma, a form indicative of skin cancer. This work proposes, a novel APFB (Adaptive Percentage Filger for Binarization) to remove the hairline noise from the skin images. The performance of the APFB filter is compared with the state-of-art hairline noise removal methods such as Contrast Limited Adaptive Histogram Equalization (CLAHE) and Bilateral methods and proven to be best in terms of image quality analysis metrics such as PSNR, SSIM, BRISQUE and NIQE. The original images and hairline noise removed images are then passed into custom built CNN models for skin disease classification. The model examines the lesions features like pigment, texture, color, lines, shapes and symmetry to classify the different types of skin diseases. Among the four CNN models we created, the CNN model that takes images of APFB hair line noise removal method obtains 99.98% training accuracy and 100% testing accuracy than the other models. Thus, the model may also be used to predict skin cancer without a biopsy. [ABSTRACT FROM AUTHOR]

Deep learning utilizing convolutional neural networks (CNNs) stands out among the state-of-the-art procedures in PC-supported medical findings. The method proposed in this paper consists of two key stages. In the first stage, the proposed deep sequential CNN model preprocesses images to isolate regions of interest from skin lesions and extracts features, capturing the relevant patterns and detecting multiple lesions. The second stage incorporates a web tool to increase the visualization of the model by promising patient health diagnoses. The proposed model was thoroughly trained, validated, and tested utilizing a database related to the HAM 10,000 dataset. The model accomplished an accuracy of 96.25% in classifying skin lesions, exhibiting significant areas of strength. The results achieved with the proposed model validated by evaluation methods and user feedback indicate substantial improvement over the current state-of-the-art methods for skin lesion classification (malignant/benign). In comparison to other models, sequential CNN surpasses CNN transfer learning (87.9%), VGG 19 (86%), ResNet-50 + VGG-16 (94.14%), Inception v3 (90%), Vision Transformers (RGB images) (92.14%), and the Entropy-NDOELM method (95.7%). The findings demonstrate the potential of deep learning, convolutional neural networks, and sequential CNN in disease detection and classification, eventually revolutionizing melanoma detection and, thus, upgrading patient consideration. [ABSTRACT FROM AUTHOR]

Atopic dermatitis (AD) is still a demanding challenge in clinical practice. Type 2 inflammation is the most common inflammatory pathway in children and adolescents with AD. Anti‐inflammatory drugs, mainly corticosteroids (CS) and immunomodulant agents are the primary therapeutic approach to dampening type 2 inflammation. However, AD patients may require long‐term high CS doses or drug combinations with possibly significant adverse effects to achieve and maintain disease control. In this regard, the advent of biologics constituted a breakthrough in managing this condition. Dupilumab is a monoclonal antibody directed against the IL‐4 receptor α‐subunit (IL‐4Rα), antagonizing both IL‐4 and IL‐13 and is approved for pediatric severe AD. This review presents and discusses the most recent published studies on dupilumab in children and adolescents with AD. There is convincing evidence that dupilumab is safe and effective in managing AD. It can reduce skin lesions and associated itching, reduce the need for additional medications, and improve disease control and quality of life. However, a thorough diagnostic pathway is mandatory, especially considering the different AD phenotypes. The ideal eligible candidate is a child or adolescent with AD requiring systemic treatment because of severe clinical manifestations and impaired quality of life. [ABSTRACT FROM AUTHOR]

This literature review assesses the most recent data to summarise the emerging potential uses, benefits and risks of pulsed electromagnetic field therapy (PEMF) in wound healing. Electromagnetic fields have mainly been used as an adjunct therapy for osteoarthritis and other diseases involving joints. However, PEMF has also been shown to influence various signalling molecules involved in wound healing, including MMP-2, IL-6 and TGF-β. Therefore, studies have begun to explore the use of PEMF in other diseases, such as incision wound repair, diabetes-related foot ulcers (DFU) and pressure ulcers. However, the cellular response to PEMF is highly variable and likely influenced by multiple factors -- frequency, duration, tissue type, stage of wound repair and field strength. This high degree of variability may explain why PEMF seems to promote cell proliferation under certain conditions and inhibit cell growth with different parameters. This review highlights the need for further research to determine precisely how different variables influence PEMF therapy. Before PEMF can be implemented widely in clinical practice, this review provides a starting point for further controlled trials. This review might also provide a solid base to propose standardised experimental guidelines to investigate PEMF efficacy in wound healing, ulcer treatment and type 2 diabetes. [ABSTRACT FROM AUTHOR]

Sporotrichosis is a fungal infection of worldwide importance caused by a saprophyte fungus of the genus Sporothrix. The objective of this study was to report the occurrence of feline sporotrichosis in the Metropolitan Region of the city of Recife and the anatomical distribution of lesions on the bodies of cats. Stray cats (n=100) with suggestive sporotrichosis lesions were examined. Material from the lesion was collected from all patients using an imprint and/or sterile swab for cytology. The material was placed on a glass slide and stained using rapid panoptic staining. Data on the localization of each skin lesion were recorded, and cigar-shaped yeast structures were searched at the microscopical examination. A heat map graphically represented the anatomical distribution of each lesion. In 70% (70/100) of samples were visualized fungal structure compatible with Sporothrix spp. There was a predominance of positive males (?2=6.691; p=0.0097). Skin lesions related to Sporothrix spp. infections were unevenly distributed throughout the animal's body. Based on the interpolation of data, the chance for detecting lesions was higher on the nose, anterior paw, and ears than on other body sites (H=40.0043; p=0.0000). Because of the high positivity in these cats, measures of health vigilance are imperative to reduce the risk of animal and human infection.

Introduction and Objective: Pemphigoid gestationis (PG) is a rare, self-limiting autoimmune disorder, typically appearing in the second or third trimester of pregnancy. It can lead to postpartum exacerbations, and studies suggest an increased risk of preterm birth and the development of Graves' disease in the mother. The aim of this article is to gather the latest information on pemphigoid gestationis. Review Methods: A review of studies available in the PubMed database was conducted using the keywords "pemphigoid gestationis" and "dermatoses of pregnancy" in order to find publications from the last 8 years. Brief Description of the State of Knowledge: Pemphigoid gestationis (PG) is characterized by the production of IgG1 antibodies against bullous pemphigoid antigen 180 (BP180). The primary symptom of PG is intense itching, which often occurs before skin lesions develop. Diagnosis is typically confirmed through direct immunofluorescence (DIF) of perilesional skin. Treatment focuses on relieving itching and preventing new blister formation, usually starting with topical corticosteroids for mild cases, while systemic corticosteroids are reserved for more severe presentations. Recent research indicates that biologic therapies may also offer effective management options for PG. Summary: The authors highlight the need for further research due to the limited sample sizes in existing studies, as well as the potential complications during pregnancy and long-term health effects.

Background: Inflammatory bowel disease (IBD)` may affect organs outside the intestines, it is called extraintestinal manifestations of IBD. Data on the prevalence of mu-cocutaneous manifestations in IBD patients are very limited, therefore, the aim of this study was to assess the prevalence of skin and mucosal lesions and to determine the relationship with demographic factors, clinical features, and systemic treatment. Materials and methods: Prospective study included 162 out-patients with IBD who were managed in the tertiary care center. Ulcerative colitis (UC) was diagnosed in 117 patients, Crohn‘s disease (CD) in 45. Patients completed the questionnaire containing demographic and IBD data, questions about mucocutaneous lesions (in past or present state). Results: Overall mucocutaneous lesions were reported by 48.1% of IBD patients. Skin lesions were reported by 40.7% of patients, oral mucosal lesions were reported by 16.7%, without significant differences between sexes or IBD types. In 47 (29%) of patients, skin lesions appeared together with IBD or during the course of the disease. The most common skin lesions were psoriasis (8.0%), erythema nodosum (5.6%), pyoderma gangrenosum and acne (3.7% each). UC patients mostly reported about psoriasis (9.4%), while CD patients about erythema nodosum (11.1%). There were more frequent skin lesions in patients with more extensive UC type (p = 0.01), while no difference was noticed between different types of CD. The average duration of IBD in patients with skin lesions was similar to those without lesions (9.3±6.7 vs. 9.4±6.7 years). Conclusions: Mucocutaneous lesions were reported by 48.1% of inflammatory bowel disease patients. The frequency of mucocutaneous lesions does not differ significantly between UC and CD, and a longer duration of illness is not a predictive factor for the appearance of lesions. More extensive UC is related to higher frequency of skin lesions. Erratum note The title, author's name, and abstract have been updated to reflect the correct information following a typographical error during typesetting. We apologize for any inconvenience caused by these errors. Corrections were made on 2024-09-01.

Abstract Occupational health must be strictly considered in industries particularly in nanoparticle factories where workers were exposed to different types of chemicals. We measured the serum levels of inflammatory cytokines in workers who developed skin lesions after exposure to silver and silica nanoparticles. Using a questionnaire in this cross-sectional study, we identified 110 workers in nanoparticle industries who were exposed to silver and silica nanoparticles. We also included 40 healthy subjects as controls from the administrative department of the same factories who were not exposed to nanoparticles. Peripheral blood samples used to measure the mRNA levels of inflammatory cytokines by qRT-PCR. In comparison with the control group, the workers who developed skin lesions had significantly higher levels of interleukin IL4, IL6, IL8, and TNF-α, particularly after two or three decades of exposure to silver and silica nanoparticles. Participants who were exposed to silver had higher levels of IL6 and IL8 compared with those who were exposed to silica. Necessary measures must be considered to protect workers in nanoparticle industries against the potential toxic effects of these compounds. Our network pharmacology study suggests corresponding biochemical pathways for these disorders.

Background: Skin cancer is the most common form of cancer worldwide. As artificial intelligence (AI) expands its scope within dermatology, leveraging technology may aid skin cancer detection. Objective: To assess the safety and effectiveness of an elastic-scattering spectroscopy (ESS) device in evaluating lesions suggestive of skin cancer. Methods: This prospective, multicenter clinical validation study was conducted at 4 US investigational sites. Patients with skin lesions suggestive of melanoma and nonmelanoma skin cancers were clinically assessed by expert dermatologists and evaluated by a device using AI algorithms comparing current ESS lesion readings with training data sets. Statistical analyses included sensitivity, specificity, AUROC, negative predictive value (NPV), and positive predictive value (PPV). Results: Overall device sensitivity was 97.04%, with subgroup sensitivity of 96.67% for melanoma, 97.22% for basal cell carcinoma, and 97.01% for squamous cell carcinoma. No statistically significant difference was found between the device and dermatologist performance (P = .8203). Overall specificity of the device was 26.22%. Overall NPV of the device was 89.58% and PPV was 57.54%. Conclusion: The ESS device demonstrated high sensitivity in detecting skin cancer. Use of this device may assist primary care clinicians in assessing suspicious lesions, potentially reducing skin cancer morbidity and mortality through expedited and enhanced detection and intervention.

In recent decades, skin cancer has emerged as a significant global health concern, demanding timely detection and effective therapeutic interventions. Automated image classification via computational algorithms holds substantial promise in significantly improving the efficacy of clinical diagnoses. This study is committed to mitigating the challenge of diagnostic accuracy in the classification of multiclass skin lesions. This endeavor is inherently formidable owing to the resemblances among various lesions and the constraints associated with extracting precise global and local image features within diverse dimensional spaces using conventional convolutional neural network methodologies. Consequently, this study introduces the SkinSwinViT methodology for skin lesion classification, a pioneering model grounded in the Swin Transformer framework featuring a global attention mechanism. Leveraging the inherent cross-window attention mechanism within the Swin Transformer architecture, the model adeptly captures local features and interdependencies within skin lesion images while additionally incorporating a global self-attention mechanism to discern overarching features and contextual information effectively. The evaluation of the model's performance involved the ISIC2018 challenge dataset. Furthermore, data augmentation techniques augmented training dataset size and enhanced model performance. Experimental results highlight the superiority of the SkinSwinViT method, achieving notable metrics of accuracy, recall, precision, specificity, and F1 score at 97.88%, 97.55%, 97.83%, 99.36%, and 97.79%, respectively. [ABSTRACT FROM AUTHOR]

Simple Summary: This study aimed to describe the epidemiological, clinicopathological, and therapeutic aspects of allergic dermatitis caused by Culicoides spp. bites in donkeys. Clinical signs included restlessness and severe itching. Skin lesions were observed across various parts of the body and included areas of alopecia with crusts and serosanguinous exudates. Overall, 378 Culicoides insects were collected and Culicoides ocumarensis Ortiz was identified as the most common species. These findings suggest an association between allergic dermatitis and Culicoides. Additionally, a combination of copaiba oil and a multivitamin emulsion showed therapeutic potential. To date, this is the first study on allergic dermatitis in donkeys in Brazil. An allergy to bites from Culicoides (Diptera: Ceratopogonidae) occurs because of a hypersensitivity reaction caused by the inoculation of insect salivary antigens during the bite, resulting in immune-mediated dermatitis. To the best of our knowledge, no previous studies have focused on allergic dermatitis in donkeys in Brazil. Therefore, this study aimed to describe the epidemiological, clinicopathological, and therapeutic aspects of allergic dermatitis in donkeys and to identify the insects involved in its epidemiology. This study reported the occurrence of dermatitis in 17 animals. The clinical signs were restlessness and severe itching. Skin lesions were found on the head, depigmented areas of the muzzle and cheeks, flanks, pelvic and thoracic limbs, and the scrotal sac. The lesions were characterized by areas of alopecia with crusts accompanied by serosanguineous exudates. Histologically, the lesions were characterized as moderate superficial dermatitis with irregular epidermal acanthosis and pronounced diffuse orthokeratotic hyperkeratosis. In total, 378 Culicoides specimens were collected, with Culicoides ocumarensis Ortiz being the most abundant species. The combined application of copaiba oil and a multivitamin emulsion exhibited potential for topical treatment of allergic dermatitis caused by insect bites in donkeys. Our study revealed an association between allergic dermatitis in donkeys and Culicoides. [ABSTRACT FROM AUTHOR]

Background: The high prevalence and negative outcomes associated with skin cancer demand effective strategies to prepare nurse practitioner students to detect cancerous lesions and manage patient care. However, few studies have examined dermatologic simulations to prepare nurse practitioner students to detect and manage skin cancer. Purpose: An exploratory--descriptive qualitative approach was used to examine nurse practitioner students' experiences with simulations involving standardized patients wearing three-dimensional (3-D) prosthetic skin lesions, perceptions of ability to apply the simulations to clinical practice, and preferences for learning dermatologic care. Methodology: A convenience sample of 39 nurse practitioner students participated in simulations with standardized patients wearing 3-D skin lesions. Focus groups were conducted following simulation participation, and thematic analysis was performed by two researchers. Results: Four themes emerged: Simulation provides a safe place to practice, Dermatology should be an integral part of education, Realism makes a difference, and Improved confidence and preparation for practice. Conclusions: Simulations with standardized patients wearing 3-D skin lesion prosthetics provided students the opportunity to assess, diagnose, and manage the care of patients with cancerous skin lesions. Participants valued the realistic practice with dermatologic care and reported improved confidence and preparation for practice. Implications: Faculty can use simulations to provide experiential learning about the provider role in general and as it pertains to skin cancer care. Attention to realism is important to aid in building students' confidence and preparation for practice. [ABSTRACT FROM AUTHOR]

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In the field of medical image segmentation, achieving fast and accurate semantic segmentation of tumor cell nuclei and skin lesions is of significant importance. However, the considerable variations in skin lesion forms and cell types pose challenges to attaining high network accuracy and robustness. Additionally, as network depth increases, the growing parameter size and computational complexity make practical implementation difficult. To address these issues, this paper proposes MD-UNet, a fast cell nucleus segmentation network that integrates Tokenized Multi-Layer Perceptron modules, attention mechanisms, and Inception structures. Firstly, tokenized MLP modules are employed to label and project convolutional features, reducing computational complexity. Secondly, the paper introduces Depthwise Attention blocks and Multi-layer Feature Extraction modules. The Depthwise Attention blocks eliminate irrelevant and noisy responses from coarse-scale extracted information, serving as alternatives to skip connections in the UNet architecture. The Multilayer Feature Extraction modules capture a wider range of high-level and lowlevel semantic features during decoding and facilitate feature fusion. The proposed MD-UNet approach is evaluated on two datasets: the International Skin Imaging Collaboration (ISIC2018) dataset and the PanNuke dataset. The experimental results demonstrate that MD-UNet achieves the best performance on both datasets. [ABSTRACT FROM AUTHOR]

Skin cancer has become more common in recent decades, raising severe concerns about world health. Creating an automated system to distinguish between benign and malignant images is challenging because of the subtle variations in how skin lesions appear. This study introduces Computer-Aided Diagnosis (CAD) system that offers high classification accuracy while maintaining low computing complexity for categorizing skin lesions. The system incorporates a pre-processing stage that uses morphological filtering to remove hair and artefacts. With the least minimum of human interaction, deep learning techniques are employed to separate skin lesions automatically. Image processing methods are currently being utilized to investigate the automated implementation of the prediction criteria for distinguishing between benign and malignant melanoma lesions. Various pre-trained convolutional neural networks (CNNs) with multi-layered (ML-CNN) are under examination for the classification of skin lesions as either benign or malignant. The best performance is achieved when RF, k-NN and XGBoost are combined, according to average 5-fold cross-validation findings. The outcomes also demonstrate that data augmentation works better than acquiring novel images for training and testing purposes. The experiment results show that the suggested diagnostic framework performs better than existing methods when used on actual clinical skin lesions, with accuracy at 97.5%, F1-score at 91.3%, precision at 96.5%, sensitivity at 89.2% and specificity at 96.7%. It also takes 2.6 seconds to complete with the MNIST dataset and accuracy at 98.2%, F1-score at 92.5%, precision at 98.4%, sensitivity at 92.3% and specificity of 97.2% with the ISIC dataset. This indicates that medical professionals can benefit from using the suggested framework to classify various skin lesions. [ABSTRACT FROM AUTHOR]

In the field of skin disease diagnosis, the segmentation of lesions is a crucial step in auxiliary diagnosis. The U-Net network has achieved many successes in the field of medical segmentation. However, due to the relatively simple encoder and decoder of traditional U-Net, it is easy to be affected by factors such as small sample size, insufficient feature expression, and irregular shape of segmented targets, the good features cannot be extracted, resulting in incorrect segmentation results. In order to solve these problems and improve the performance of lesion segmentation. We designed a new U-Net network by improving the traditional architecture in two ways: 1) We replaced the encoder with a robust classification network to effectively extract feature information. 2) To thoroughly exploit the potential perceptual clues in the multi-scale feature maps generated by the encoder, we designed the Multi-Scale Depth Feature Exploration (MSD) module as the decoder. Additionally, we propose a novel segmentation loss function named Weighted Contour Cross Entropy loss (WCCE), which forces the network pay more attettion to lesion contour information and improve the contour quality of lesion segmentation to achieve better segmentation accuracy. All experiments were conducted on two skin lesion datasets, ISIC2018 and XJUSL. Experimental analysis reveals that the improved U-Net assisted with proposed loss surpasses the traditional U-Net and other typical methods in the performance of all evaluation metrics used in this study. This result reflects that the proposed method can effectively segment the lesion contour and improve the performance of lesion segmentation. [ABSTRACT FROM AUTHOR]

Simple Summary: This work describes a case study of pseudocowpoxvirus (PCPV) infection in Russia (Irkutsk region). The clinical manifestation, molecular identification, and molecular characterization of the disease were established. Epidemiological information were provided by the state veterinary service; additionally, the cows' owners were interviewed using a semi-structured questionnaire. The description of clinical symptoms was based on clinical examination and farmer interviewing. Samples (blood, serum, scab) were collected from the affected cattle for virological studies and molecular analyses. The identification of PCPV was accomplished through the B2L gene fragment amplification, sequencing, and phylogenetic analysis. Based on the nucleotide identities and phylogenetic analysis of the partial-length B2L gene, the Irkutsk 2019 isolate was classified as PCPV. Because of high rates of virus transmission amongst cattle-to-cattle and cattle-to-humans through direct contact, it is important to raise farmers' awareness of the clinical signs of the disease, highlight its preventive measures, and to develop a strategy to motivate them to seek qualified veterinary care. Parapoxviruses are worldwide epitheliotropic viruses that affect ruminants. Viruses of this genus have a narrow host range; however, the pseudocowpox virus (PCPV) also infects humans. Unfortunately, these cases are not well documented, and the epidemiology and the properties of the causative agents are not properly described. Here, we report the first case of PCPV in northern Russia (the Irkutsk region). The infection occurred in non-immune herds where no new arrivals of animals had been reported. Moreover, clinical signs of infection (skin lesions) were observed in humans. Based on the nucleotide identity and phylogenetic analysis of the partial-length B2L gene, the Irkutsk 2019 isolate was classified as PCPV. Phylogenetic analysis based on the nucleotide sequence of the B2L gene fragment of PCPV revealed a close phylogenetic relationship between the Irkutsk 2019 isolate and the PCPV strains isolated in Europe and the USA. The high degree of conservatism of the B2L gene does not allow for finding a correlation between their geographical origin and the results of phylogenetic analysis. [ABSTRACT FROM AUTHOR]

Occupational health must be strictly considered in industries particularly in nanoparticle factories where workers were exposed to different types of chemicals. We measured the serum levels of inflammatory cytokines in workers who developed skin lesions after exposure to silver and silica nanoparticles. Using a questionnaire in this cross-sectional study, we identified 110 workers in nanoparticle industries who were exposed to silver and silica nanoparticles. We also included 40 healthy subjects as controls from the administrative department of the same factories who were not exposed to nanoparticles. Peripheral blood samples used to measure the mRNA levels of inflammatory cytokines by qRT-PCR. In comparison with the control group, the workers who developed skin lesions had significantly higher levels of interleukin IL4, IL6, IL8, and TNF-α, particularly after two or three decades of exposure to silver and silica nanoparticles. Participants who were exposed to silver had higher levels of IL6 and IL8 compared with those who were exposed to silica. Necessary measures must be considered to protect workers in nanoparticle industries against the potential toxic effects of these compounds. Our network pharmacology study suggests corresponding biochemical pathways for these disorders. [ABSTRACT FROM AUTHOR]

Introduction: This research discusses the potential of Orthosiphon aristatus, a medicinal plant, in improving skin lesions in Atopic Dermatitis by regulating Th2 cytokines and showing anti-allergic activity. Methods: The study was conducted using BALB/C mice induced with DNCB for 21 days to create an atopic dermatitis model. Then, the mice were orally administered Orthosiphon aristatus extract for 14 days (after 7 days of induction). The doses given were divided into six groups: 17.5 mg/kgbw, 35 mg/kgbw, 70 mg/kgbw, and 140 mg/kgbw. Molecular levels such as IgE, IL4, IL22, and PGE2 were analyzed from blood samples. In addition, the severity of skin lesions was assessed morphologically, and histological examination was performed to confirm clinical improvement. Results: This study showed that the administration of Orthosiphon aristatus extract reduced the severity of skin lesions in all intervention groups. Histologically, this extract reduced epidermal thickness and mast cell infiltration. These findings were also supported by dose-dependent decreases in IgE, IL4, IL22, and PGE2 levels. So, the conclusion of this study is that Orthosiphon aristatus extract shows potential for improving skin lesions in atopic dermatitis by regulating Th2 cytokines and demonstrating anti-allergic activity in a mice model with DNCBinduced atopic dermatitis. Conclusion; The administration of Orthosiphon aristatus extract clinically and histologically exhibits anti-atopic effects that can be explained through the regulation of molecules such as IgE, IL4, IL22, PGE2, and NO. Orthosiphon aristatus has the potential to be a valuable herbal therapy for managing atopic dermatitis. [ABSTRACT FROM AUTHOR]

Ophidiomycosis (formerly snake fungal disease) is an emerging disease in snakes caused by the fungal pathogen Ophidiomyces ophidiicola (Oo). The disease is characterized by skin lesions that can range from mild to severe with associated fatalities documented. Subclinical infections have also been described presenting a wide variability of the impact Oo has on the host. In wild snakes, infections have most often been documented in North America, but increasing numbers of reports are becoming available from other parts of the world, including Europe. While monitoring dice snake (Natrix tessellata) populations in 2018 at Schleuse Hollerich/Lahn, a nature reserve in Germany, three dice snakes were observed with cutaneous granulomas. One year later, snakes with granulomas were also observed, and two dice snakes were captured and examined. Fungal hyphae were found in skin biopsies of the lesions, and Oo was detected by PCR in the shed skin from one of the snakes. After shedding, the snakes appeared clinically healthy and were released back to the location at which they had been found. This is the first report of histologically confirmed ophidiomycosis in dice snakes and the first confirmed report of ophidiomycosis in a wild snake in Germany. [ABSTRACT FROM AUTHOR]

Only ultraviolet-C (UV-C) from UV lights, which are emitted by the sun and absorbed by the atmosphere's ozone layer, does not reach the Earth's surface. UV-C is a powerful disinfection method that is commonly used to sterilize fluids, air, and surfaces. There is a little knowledge of the effects of UV-C radiation on living bodies. The purpose of this study is to examine the ameliorative effect of UV-C on skin lesions in mice that have been experimentally created and infected with Staphylococcus aureus, Staphylococcus epidermidis, and Streptococcus sp. In total, 32 mice were used, and 4 mm skin defects were created and lesions infected with bacteria. Half of the mice in each group were treated with 254 nm UV-C twice a day for 4 days before being euthanatized. Blood samples were collected for hematological analysis, while skin samples were collected for microbiological, pathological, and immunohistochemical examinations. In addition, pathological examinations were performed on visceral organ samples. UV-C treatment caused rapid healing and complete or significant disinfection of skin lesions. Moreover, UV-C treatment reduced caspase-3 expressions in lesioned areas, according to immunochemistry. There were no pathological findings in visceral organs as a result of UV-C treatment. This study found that UV-C can be used to treat and disinfect infected skin lesions in short period and repeated doses. [ABSTRACT FROM AUTHOR]

Every year, ulcerative dermal necrosis (UDN) affects salmonids that spend most of their lives in the sea during their migration to the rivers of northern Poland to spawn. The clinical form of the disease manifests itself in ulcerative skin lesions, which lead to significant weakening of the fish and, in most cases, result in their death. This study was carried out on samples taken from sea trout in the Słupia River in northern Poland. In order to identify the pathogen, experiments on the transmission of the disease were carried out, and additional histopathological, microbiological and electron microscopic examinations were performed. As a result of these studies, it was possible to experimentally transfer the disease from sick to healthy fish. The results indicate a complex etiology of the disease (lack of a clearly defined pathogen), in which the change in the environment from salty to freshwater triggers the related changes in skin physiology, which are the main causes of increased susceptibility to the development of the disease. [ABSTRACT FROM AUTHOR]

Several measures of non-convexity (departures from convexity) have been introduced in the literature, both for sets and functions. Some of them are of geometric nature, while others are more of topological nature. We address the statistical analysis of some of these measures of non-convexity of a set S, by dealing with their estimation based on a sample of points in S. We introduce also a new measure of non-convexity. We discuss briefly about these different notions of non-convexity, prove consistency and find the asymptotic distribution for the proposed estimators. We also consider the practical implementation of these estimators and illustrate their applicability to a real data example. [ABSTRACT FROM AUTHOR]

Background: Lupus patients frequently exhibit specific and nonspecific skin lesions and lesions associated with skin infections. This study aimed to determine the frequency of lupus-specific and non-specific skin lesions and the incidence of skin infections. Methods: This study was conducted in the Department of Rheumatology at Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh, from 2014 to 2016. After obtaining ethical clearance from the Institutional Review Board of BSMMU, 136 consecutive patients fulfilling the ACR criteria for SLE were enrolled and followed up for at least one year. A dermatologist confirmed lupus-specific, non-specific, and skin lesions related to infections and noted them in a datasheet. Relevant investigations were performed at baseline and during subsequent follow-up visits. Results: One hundred thirty-one patients completed their follow-up period. The mean (standard deviation) follow-up period was 13.3 (2.0) months. The patients' mean (standard deviation) age was 28.8 (8.2) years. Skin lesions and skin infections were present in 71.8% and 26.7%, respectively of patients. Common lupus-specific lesions were malar rash (75.4%) and DLE (12.3%). Photosensitivity (72.6%), non-scarring alopecia (67.9%), mucosal ulcers (47.6%), Raynaud’s phenomenon (23.8%), and hyperpigmentation (23.8%) were the prevalent lupus non-specific skin lesions. The common skin infections were tinea (42.9%), herpes infection (34.3%), paronychia (20%), and scabies (17%). Conclusions: Skin lesions related to infections were common, along with lupus-specific and nonspecific lesions skin lesions. Tinea and herpes infections were more common skin infections.

A 54-year-old woman presented to our emergency department two months after the removal by Video-Assisted Thoracoscopic Surgery (VATS) of her middle lung lobe affected by severe inflammation and fibrosis. She was experiencing pain from a large ulcer (diameter 13 cm) starting from the surgical scar. She suffered from Calcinosis, Raynaud phenomenon, Esophageal dysmotility, Sclerodactyly, and Telangiectasia (CREST) syndrome, and hypothyroidism. The laboratory results showed White Blood Cell count (WBC) 13,600/mm3 (N 76%), C-Reactive Protein (CRP) 12 mg/L (nv

Resumen: La atención a pacientes migrantes abarca el cribado inicial y su seguimiento a lo largo del proceso vital, de ahí la importancia de la prevención y del seguimiento de las enfermedades crónicas, transmisibles o no.La prevalencia de hipertensión arterial, diabetes mellitus, dislipemia y obesidad varían según la etnia, esto se atribuye a factores genéticos, además del estilo de vida y de la situación socioeconómica. Es fundamental la prevención y la promoción de la salud, y la detección de los factores de riesgo.Las enfermedades crónicas transmisibles pueden cronificarse y dar clínica años después de su transmisión, siendo fundamental el cribado desde atención primaria de poblaciones procedentes de zonas endémicas y en riesgo.Las lesiones cutáneas importadas son un motivo de consulta frecuente en los pacientes migrantes y los viajeros. La etiología es variada, desde algunas frecuentes en nuestro medio; como escabiosis, micosis, urticaria, etc., a dermatosis tropicales como la filariasis y la lepra. Abstract: The care of migrant patients includes initial screening and lifelong monitoring, highlighting the importance of preventing and tracking chronic, communicable and non-communicable diseases.The prevalence of hypertension, diabetes mellitus, dyslipidemia, and obesity varies by ethnicity, influenced by genetic factors, lifestyle, and socio-economic status. Preventive measures, health promotion, and risk factor identification are crucial.Chronic communicable diseases may manifest years after transmission, underscoring the necessity of primary care screening, especially for populations from endemic or high-risk areas.Imported skin lesions are a common reason for consultation among migrant and traveller patients. Their ethiology is varied, ranging from common conditions such as scabies, mycoses, and urticaria to tropical dermatoses like filariasis and leprosy.

The classification of skin lesions is crucial because it increases the likelihood that malignant skin lesions will be discovered early on, allowing for more effective treatment. Due to the abundance of lesion images and the possibility of human error, early detection can be difficult for dermatologists. This work aims to classify skin lesions using two pipelines that were designed using support vector machine (SVM) and AlexNet convolutional neural network (CNN) models. Pipeline-1 uses the AlexNet CNN, while pipeline-2 proposes a bisectional feature extraction approach with an SVM model. The skin lesion images are initially preprocessed and the lesion regions are segmented. The lesion regions are further subdivided into four regions based on the intensity mapping function. The bisectional features are then extracted from the subdivided regions and the extracted features are trained with the SVM model. The dataset used in the experiment is the HAM-10000 dataset and the PAD-UFES-20 dataset, which consists of dermatoscopic skin lesions images. Based on the models’ accuracy, sensitivity, DCI, specificity, and F1-score, the experiment’s findings will be assessed for five different skin lesion conditions. By accurately and effectively classifying skin lesions, the study’s findings will help in the diagnosis and treatment of skin disorders. The SVM pipeline performs better than the AlexNet CNN pipeline where the SVM pipeline and AlexNet CNN pipeline result in an accuracy of 98.66% and 97.68% respectively for the HAM-10000 dataset. The AlexNet CNN and SVM pipeline structure results in an accuracy of 96.87% and 98.10% respectively for the PAD-UFES-20 dataset.

Deep convolutional neural networks have made some progress in skin lesion classification and cancer diagnosis, but there are still some problems to be solved, such as the challenge of small inter-class feature differences and large intra-class feature differences, which might limit the classification performance of the model as high-level and low-level features are not properly utilized. This paper proposes a multi-scale skin cancer image identification network using self-interactive attention pyramid and cross-layer bilinear-trilinear pooling(SPCB-Net), which mainly consists of three proposed sub-modules that are the self-interacting attention pyramid (SAP), the across-layer bilinear-trilinear pooling operation and the global average algorithm(GAA). The SPCB-Net is applied to two representative datasets of medical images in dermatology and histopathology (HAM10000 and NCT-CRC-HE-100K) to demonstrate the effectiveness of in the skin lesion classification. SPCB-Net(ResNet101) achieves 97.10% and 99.87% accuracy on HAM10000 and NCT-CRC-HE-100K respectively, which are both achieved performance improvements of 0.4% compared to the state-of-the-art models. In addition, a large number of experiments on HAM10000 show that the interactive attention pyramid(SPA) proposed in this paper is superior to the common attention module, and the method with a cross-layer bilinear-trilinear pooling is superior to the cross-layer trilinear pooling method. SPCB-Net is configured on Vgg19 and ResNet101 to evaluate the effectiveness of our proposed module. The experimental results show that SPCB-Net has shown state-of-the-art performance in the two field of dermatology and histopathology. Therefore, it is not only well qualified for the task of identifying skin cancer image but also has the potential to identify skin cancer by identifying pathological tissue.

The study aimed to assess the prevalence of arsenic-induced skin lesions and associated factors among the population in the Adami Tulu Jido Kombolcha district, Ethiopia. A community-based cross-sectional study design was employed among 403 participants from June 02–20, 2022. A two-stage cluster sampling method was conducted to select study subjects. A pretested structured and semi-structured interview questionnaire and observation using a WHO flow chart were used for data collection. Data analysis was performed using SPSS version 24 statistical software for Windows. A multivariable binary logistic regression model was applied to examine the relationship between predictor variables and an outcome variable. The degrees of association between outcomes and predictor variables were assessed using ORs and 95% CIs, and P-values

The phenomenon of child abuse/maltreatment is underestimated and often represents a difficult challenge for healthcare professionals and forensic pathologists who must proceed with the differential diagnosis with accidental or self-induced events, or with lesions due to pathologies that overlap with that of mistreatment, defined as “Mimics”. This study presents a case series with the aim of discussing lesions that may mimic signs of physical abuse in children but are due to a different etiology to raise awareness and train healthcare professionals and forensic pathologists on possible confounding factors in order to avoid diagnostic errors. Six cases of “Mimics” out of 418 cases of suspected mistreatment (1.43% of cases) were identified, presenting skin lesions initially classified as injuries of abuse due to their location and type and, in particular, sexual abuse for three cases. Then, the lesions and the subjects, in particular the anamnestic history, were examined by a multidisciplinary team and the diagnosis of genital lichen sclerosus et atrophicus in three cases, and the results of popular healing techniques (i.e., “cupping”) in the other three cases were ascertained. These situations require specific skills and a forensic background from healthcare professionals to conduct a correct differential diagnosis and the intervention of a multidisciplinary team to investigate every possible pathology or alternative therapeutic practice that could simulate child abuse. In particular, when “mimics” are due to alternative medicine, it should not strictly be considered child abuse, but professionals must be aware of the hypothesis of mistreatment in case of non-medical indication or potential personal injuries from other crimes, such as illegal practice of the medicine. This awareness is also crucial to direct the child toward appropriate medical care, and it is essential to recognize that these conditions can coexist within the same clinical presentation.

In order to effectively treat skin diseases, an accurate and prompt diagnosis is required. In this article, a novel method for classifying skin disorders using a multimodal classifier is presented. The proposed classifier utilizes multiple information sources to enhance the accuracy of disease classification. It incorporates images of skin lesions and patient-specific data. The multimodal classifier simultaneously classifies diseases by combining image and structured data inputs. The effectiveness of the proposed classifier was evaluated using the ISIC 2018 dataset, which includes images and clinical data for seven categories of skin diseases. The results indicate that the proposed model outperforms conventional single-modal and single-task classifiers, achieving an accuracy of 98.66% for image classification and 94.40% for clinical data classification. In addition, we compare the performance of the proposed model with that of other methodologies, demonstrating its superiority. Despite yielding promising results, the proposed method has limitations in terms of data requirements and generalizability. Future research directions include incorporating additional information sources, investigating genetic data integration, and applying the method to various medical conditions. This study illustrates the potential of integrating multimodal techniques with transfer learning in deep neural networks to enhance the classification accuracy of cutaneous diseases. [ABSTRACT FROM AUTHOR]

Bacterial infections and resistance to antibiotics are increasingly severe problems. In recent years, Staphylococcus species have emerged as important pathogens in animals and humans. Current therapeutic methods against these species have serious disadvantages; therefore new agents with antibacterial potential, such as plant-based substances, are very important in therapy. We report a pilot study with new method of fractioning the dehydrogenate polymer DHP obtained from coniferyl alcohol and application of the low-MW fractions of 200–3000 Da for antibacterial activity in healing animal lesions. In vivo experiments were conducted on the dogs having a skin lesion. Dogs were treated with the suspension containing the low-MW DHP fractions as the active ingredient, in combination with alginate for 7 days. Cytological smears and microbiological analyses of the affected area were performed. Staphylococcus spp. was isolated from lesions in all dogs from our research. The results show that the low-MW DHP suspension in alginate promotes skin healing and reduction of the infection of the lesions in the affected animals. Pharmaceutical composition containing the low-MW DHP fractions exerts a soothing effect on the subject in wound treatment. Reduction in the number of bacteria by 30% and more were noticed in 6 dogs, while in 4 dogs this percentage is above 50%. No side effects were noticed. Synthesized lignin oligomers may have a significant place as antimicrobial and skin healing agents, especially since an increasing number of multidrug-resistant staphylococci are found on the skin lesions in animals. [ABSTRACT FROM AUTHOR]

Mueller polarimetry has proven to be a powerful optical technique to complement medical doctors in their conventional histology analysis. In this work, various degenerative and malignant human skin lesions were evaluated ex vivo using imaging Mueller polarimetry. The Mueller matrix images of thin sections of biopsies were recorded and the differential decomposition of Mueller matrices was applied pixel-wise to extract the polarization fingerprint of the specimens under study. To improve the classification accuracy, a deep learning model was created. The results indicate the sensitivity of polarimetry to different skin lesions and healthy skin zones and their differentiation, while using standard histological analysis as a ground truth. In particular, the deep learning model was found sufficiently accurate to detect and differentiate between all eight classes in the data set. Special attention was paid to the overfitting problem and the reduction of the loss function of the model. Our approach is an effort in establishing digital histology for clinical applications by complementing medical doctors in their diagnostic decisions. [ABSTRACT FROM AUTHOR]

Introduction: Azathioprine hypersensitivity can occasionally present as Sweet‐like syndrome, a dose‐independent side effect characterized by the unanticipated onset of macules, papules, and pustules. Case presentation: A 35‐year‐old woman with systemic lupus erythematosus presented with complaints of generalized maculopapular rash, facial swelling, and bilateral lower extremity edema with a duration of 4 days and a 2‐day history of constitutional symptoms within 2 weeks of the beginning of azathioprine therapy to treat existing lupus nephritis (class 2/3). Discussion: Patients who experience azathioprine hypersensitivity syndrome can present with erythema nodosum, small‐vessel vasculitis, acute generalized exanthematous pustulosis, Sweet syndrome, and nonspecific dermatosis. The following signs and symptoms are used as criteria to diagnose drug‐induced Sweet syndrome: (a) abrupt onset of painful erythematous plaques, (b) histopathological evidence of dense neutrophilic infiltrate without evidence of leukocytoclastic vasculitis, (c) temperature higher than 39.7°C, (d) temporal relationship between drug ingestion and clinical presentation, and (e) temporal resolution of lesions after drug withdrawal. Our patient met three out of five criteria and was diagnosed with Sweet‐like syndrome. Conclusion: Our case highlights the uncommonly presented azathioprine‐induced Sweet‐like syndrome that occurs abruptly after the commencement of the offending drug. This diagnosis can be established through basic laboratory workup and skin biopsy findings. [ABSTRACT FROM AUTHOR]

BACKGROUND: The skin, being the greatest sensory organ of the body, serves as a defensive shield against a wide range of harmful environmental substances. Consequently, it is implicated in a broad range of illnesses, including both inflammatory and neoplastic conditions. A skin biopsy, together with histological analysis, is necessary to achieve a precise diagnosis, thus aiding clinicians in determining the most suitable treatment. AIMS: This study aims to provide a comprehensive description of the histopathological range of all skin lesions, establish their distribution by age and sex, and identify the most prevalent skin lesions in a tertiary care hospital. MATERIALS & METHODS: A retrospective, cross-sectional, non-interventional study was carried out on 255 skin biopsies received in the department of pathology at Government Medical College, Ananthapuram, Andhra Pradesh, for a period of four years, from January 2019 to June 2023. RESULTS: Among the 255 skin biopsies analysed, the demographic most significantly impacted were those aged 31 to 70 years, with a male preponderance in all the categories of skin lesions. 63 (24.7%) were non-neoplastic, and 192 (75.3%) were neoplastic. Among the neoplastic cases, 84.9% were classified as benign. CONCLUSION: Dermatological lesions exhibit a wide spectrum of clinical presentations, with a wide age distribution and histopathology. The significance of specific histomorphological characteristics lies in differentiating various skin lesions and is crucial in establishing the definitive diagnosis of these heterogeneous skin lesions. This underscores the significance of conducting a histopathological study to ensure proper patient management. [ABSTRACT FROM AUTHOR]

The growing number of patients with skin cancer has highlighted the need for diagnostic expert systems to help detect lesions with high accuracy. The detection of dangerous diseases associated with skin lesions, especially malignant neoplasms, requires the detection of pigmented skin lesions. Methods of image recognition and computerized classification capabilities can improve the accuracy of skin cancer detection. In this paper, an approach based on leverage algorithm has been proposed. Statistical analysis based on feature acquisition from images is used to optimize the lightweight classification methods. Numerical experiments have shown the high efficiency of the approach, and the accuracy is comparable to the use of deep learning neural networks. [ABSTRACT FROM AUTHOR]