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.

BACKGROUND: Bats are recognized as the natural reservoir of several zoonotic viruses that pose a threat to public health worldwide. In our recent reports we describe the identification of a novel poxvirus, IsrRAPXV, in Egyptian fruit bats. This poxvirus is associated with high morbidity and mortality in bats.
METHODS: Herein, we describe the identification of poxvirus in a female patient hospitalized with systemic symptoms and severe painful skin lesions on her hands. We performed qPCR, whole genome sequencing and phylogenetic analysis to identify and characterize this poxvirus as the etiologic agent.
RESULTS: The patient interacted with wounded and sick bats as a volunteer in a bat shelter run by the Israel bat sanctuary organization. Samples collected from the patient\'s skin lesions were positive for the presence of IsrRAPXV by PCR. Additionally, phylogenetic analysis showed that this virus is identical to IsrRAPXV originally described by us as the causative agent of skin lesions in fruit bats.
CONCLUSIONS: Our finding suggest that IsrRAPXV is zoonotic and therefore veterinarians and volunteers working in bats shelter should meticulously follow the guidelines of working with bats and use required personal protective equipment.

Hermansky-Pudlak syndrome (HPS) is an infrequent entity, with a multisystem involvement and autosomal recessive inheritance involving genetic mutations that lead to defective organelles of lysosomes. HPS is characterized by oculocutaneous albinism, platelet storage deficiency associated with prolonged bleeding, pulmonary fibrosis, and granulomatous colitis. In our case report, we describe a two-year-old boy with the clinical presentation of oculocutaneous albinism, generalized skin lesions, and recurrent bilateral epistaxis since the age of one year. He was diagnosed with HPS type 2 based on the clinical findings and supported by a genetic study that confirmed the loss of exon 23-24 of the AP3B1 gene.

UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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).
UNASSIGNED: 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.

Adalimumab, an anti-tumor necrosis factor-α (TNF-α), is widely prescribed for many autoimmune diseases and chronic inflammatory skin diseases such as hidradenitis suppurative, psoriasis, etc. We report a case of lichenoid drug eruption secondary to adalimumab, a rare side effect, in a 62-year-old female with ulcerative colitis. The skin eruption appeared two weeks after initiating adalimumab. A skin biopsy was taken, and the histopathological findings correlated with a lichenoid drug eruption. Although rare, drug-induced lichen planus has been associated with adalimumab. Early recognition and a high index of suspicion are key in the prompt management of these cases. The discontinuation of adalimumab must be carefully weighed against its therapeutic benefits, as the discontinuation might trigger a severe form of inflammation in the primary autoimmune disease being treated. Extreme caution, early intervention, and a multidisciplinary approach are best for the overall well-being and optimal care of the individual.

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.
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.
CONCLUSIONS: 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.

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.
METHODS: 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: This study introduces SkinLiTE, a lightweight supervised contrastive learning model tailored to enhance the detection and typification of skin lesions in dermoscopic images. The core of SkinLiTE lies in its unique integration of supervised and contrastive learning approaches, which leverages labeled data to learn generalizable representations. This approach is particularly adept at handling the challenge of complexities and imbalances inherent in skin lesion datasets.
METHODS: The methodology encompasses a two-phase learning process. In the first phase, SkinLiTE utilizes an encoder network and a projection head to transform and project dermoscopic images into a feature space where contrastive loss is applied, focusing on minimizing intra-class variations while maximizing inter-class differences. The second phase freezes the encoder\'s weights, leveraging the learned representations for classification through a series of dense and dropout layers. The model was evaluated using three datasets from Skin Cancer ISIC 2019-2020, covering a wide range of skin conditions.
RESULTS: SkinLiTE demonstrated superior performance across various metrics, including accuracy, AUC, and F1 scores, particularly when compared with traditional supervised learning models. Notably, SkinLiTE achieved an accuracy of 0.9087 using AugMix augmentation for binary classification of skin lesions. It also showed comparable results with the state-of-the-art approaches of ISIC challenge without relying on external data, underscoring its efficacy and efficiency. The results highlight the potential of SkinLiTE as a significant step forward in the field of dermatological AI, offering a robust, efficient, and accurate tool for skin lesion detection and classification. Its lightweight architecture and ability to handle imbalanced datasets make it particularly suited for integration into Internet of Medical Things environments, paving the way for enhanced remote patient monitoring and diagnostic capabilities.
CONCLUSIONS: This research contributes to the evolving landscape of AI in healthcare, demonstrating the impact of innovative learning methodologies in medical image analysis.

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.

UNASSIGNED: 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.
UNASSIGNED: 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).
UNASSIGNED: 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).
UNASSIGNED: 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.
UNASSIGNED: Uždegiminių žarnų ligų (UŽL) metu gali atsirasti vadinamųjų ekstražarninių pažeidimų, kurie apima odą, sąnarius, akis ir kitus organus. Duomenų apie odos ir gleivinių pažeidimų paplitimą sergant UŽL labai trūksta, todėl šio tyrimo tikslas buvo įvertinti odos ir gleivinių pažeidimų paplitimą bei nustatyti jų ryšį su demografiniais veiksniais, klinikiniais požymiais ir sisteminiu gydymu.
UNASSIGNED: Prospektyviajame tyrime dalyvavo 162 UŽL sergantys pacientai, kurie kreipėsi gydytojo gastroenterologo konsultacijos į tretinio lygio sveikatos priežiūros centrą. Opinis kolitas (OK) diagnozuotas 117 pacientų, Krono liga (KL) – 45 pacientams. Anketinės apklausos būdu surinkti duomenys apie tiriamųjų demografinius ir UŽL klinikinius duomenis, odos ir gleivinių pažeidimus (buvusius ir esamus).
UNASSIGNED: Iš viso odos ir gleivinių pažeidimai nustatyti 48,1 proc. UŽL ligonių. Apie odos pažeidimus pranešė 40,7 proc. pacientų, esant burnos gleivinės pažeidimų nurodė 16,7 proc. Reikšmingų skirtumų lyginant pagal lytį ar UŽL tipą nenustatyta. 47 (29 proc.) pacientams odos pažeidimų atsirado kartu su UŽL arba ligos eigoje. Dažniausiai pacientų nurodyti odos pažeidimai buvo psoriazė (8,0 proc.), mazginė eritema (5,6 proc.), gangreninė pioderma ir aknė (po 3,7 proc.). OK sergantys pacientai dažniausiai pranešė apie žvynelinę (9,4 proc.), o sergantieji KL – apie mazginę eritemą (11,1 proc.). Pacientams, kuriems OK buvo labiau išplitęs žarnyne, odos pažeidimų buvo dažniau (p = 0,01), o skirtumų tarp skirtingų KL tipų nenustatyta. Vidutinė UŽL trukmė pacientų, turinčių odos pažeidimų, buvo panaši kaip ir jų neturinčiųjų (9,3±6,7 ir 9,4±6,7 metų atitinkamai).
UNASSIGNED: 48,1 proc. pacientų, sergančių uždegimine žarnyno liga, pranešė apie gleivinės ir odos pažeidimus. Odos ir gleivinės pažeidimų dažnis sergančių OK ir KL pacientų reikšmingai nesiskiria, o ilgesnė ligos trukmė nėra prognostinis veiksnys, nurodantis didesnę pažeidimų atsiradimo riziką. Labiau žarnyne išplitęs OK yra susijęs su didesniu odos pažeidimų dažniu.