Hermansky-Pudlak Syndrome Type 2: A Case Report on an Ultra-Rare Disorder.

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.

Pathological skin manifestations following smallpox vaccination (ACAM2000) in US military personnel, 2009-2023: a systematic review.

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 Dryvax was superseded in 2008 by ACAM2000, a second-generation smallpox vaccine, after clinical trials demonstrated favorable outcomes.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.

Lichenoid Drug Eruption Secondary to Adalimumab: A Case Report.

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.

Human infection with IsrRAPXV, a novel zoonotic bat-derived poxvirus.

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.

Infantile Bullous Pemphigoid: A Case Report.

Background: Infantile bullous pemphigoid (IBP) is an exceptionally rare acquired autoimmune subepidermal bullous disorder characterized by vesicles, bullae, and additional manifestations, such as urticarial and infiltrated papules, plaques, or eczematous lesions. These skin lesions can lead to eroded and crusted regions after healing, and in some cases, rapid blister rupturing causes extensively eroded areas. Reporting these rare cases is crucial to improving our understanding, diagnosis, and treatment of IBP. Case Presentation: In this report, we present the clinical case of a 4-month-old male infant with generalized tense bullae causing irritability and sleeplessness. This case highlights the distinctive clinical features of IBP, including the development of multiple generalized tense bullae over 2 weeks. The pathological examination findings confirmed the diagnosis of IBP. Conclusion: This case emphasizes the significance of early identification and proper management of IBP. Our thorough assessment, which incorporates pathological verification and therapeutic interventions, has advanced our understanding of IBP. Additionally, this case underscores the vital need for timely diagnosis and personalized treatment approaches for affected infants.

Bayesian-Edge system for classification and segmentation of skin lesions in Internet of Medical Things.

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.

SkinLiTE: Lightweight Supervised Contrastive Learning Model for Enhanced Skin Lesion Detection and Disease Typification in Dermoscopic Images.

INTRODUCTION: 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. CONCLUSION: This research contributes to the evolving landscape of AI in healthcare, demonstrating the impact of innovative learning methodologies in medical image analysis.

An Intelligent Mechanism to Detect Multi-Factor Skin Cancer.

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.

Manifestations Reported by Inflammatory Bowel Disease Patients in University Hospital.

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.

Swinepox virus: an unusual outbreak in free-range pig farms in Sicily (Italy).

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.

Dermatomyositis-like skin eruptions under hydroxyurea therapy conceal TP53-mutated atypical keratinocytes: A histopathologic and molecular pathologic case series.

Hydroxyurea is an antimetabolite that inhibits DNA synthesis and is used as a treatment option in chronic myeloproliferative disorders. Rarely, "dermatomyositis (DM)-like" skin lesions are observed after long-term therapy. In this case series, five skin biopsies of four patients were evaluated by histology, immunohistochemistry, and next-generation sequencing of the TP53 gene locus. All biopsies showed focal basal pleomorphic keratinocytes and suprabasal aberrant p53 expression as well as sparse to severe vacuolar interface dermatitis. Histopathologically, "DM-like" skin lesions can be clearly distinguished from DM by marked subepidermal fibrosis, vascular proliferation, and the absence of dermal mucin deposits. In 75% of the specimens multiple, partly inactivating and/or pathogenic point mutations of TP53 were found in low frequencies. "DM-like" skin eruptions as a long-term consequence of hydroxyurea therapy are possibly not chemotherapy-associated benign toxic changes, but rather inflammatory reactions to complex keratinocyte alterations that clinically mimic the picture of DM. Synergistic mutagenic effects of hydroxyurea and sunlight might be responsible for this unique drug side effect and could provide a pathogenic link to the known increased risk of skin cancer in these patients.

Federated Active Learning Framework for Efficient Annotation Strategy in Skin-Lesion Classification.

Federated learning (FL) enables multiple institutes to train models collaboratively without sharing private data. Current FL research focuses on communication efficiency, privacy protection, and personalization and assumes that the data of FL have already been ideally collected. However, in medical scenarios, data annotation demands both expertise and intensive labor, which is a critical problem in FL. Active learning (AL) has shown promising performance in reducing the number of data annotations in medical image analysis. We propose a federated AL framework in which AL is executed periodically and interactively under FL. We exploit a local model in each hospital and a global model acquired from FL to construct an ensemble. We use ensemble entropy-based AL as an efficient data-annotation strategy in FL. Therefore, our federated AL framework can decrease the amount of annotated data and preserve patient privacy while maintaining the performance of FL. To our knowledge, this federated AL framework applied to medical images has not been previously reported. We validated our framework on real-world dermoscopic datasets. Using only 50% of samples, our framework was able to achieve state-of-the-art performance on a skin-lesion classification task. Our framework performed better than several state-of-the-art AL methods under FL and achieved comparable performance with full-data FL.

Metastatic Fibrosarcomatous Transformation of Dermatofibrosarcoma Protuberans With Lung Metastasis: A Case Report.

Dermatofibrosarcoma protuberans (DFSP) is a low- to intermediate-grade dermal soft tissue malignant tumor (sarcoma) with a high local recurrence rate but low metastatic potential. DFSP is characterized by uniform spindle cell fascicles arranged classically in a storiform pattern and by CD34 immunoreactivity. On gross examination, DFSP usually manifests as a white or yellow soft tissue mass with a smooth outer surface and poor circumscription. In this study, we report a case of DFSP with fibrosarcomatous transformation, a rare but well-known phenomenon encountered in DFSP that is correlated with an increased risk of adverse outcomes in patients with DFSP. A 45-year-old male presented with a progressively enlarging lump on his left shoulder, initially suspected of being a lipoma but diagnosed as a fibrosarcomatous transformation of DFSP. Surgical resection was performed, with the subsequent identification of metastatic sarcoma in pulmonary nodules. Robotic-assisted thoracoscopy excised the nodules, confirming metastatic sarcoma with aggressive behavior. Despite negative adjuvant treatment plans, the patient remains under surveillance with imaging, showing no recurrence in recent scans. Continued follow-up with medical and surgical oncology is planned. DFSP is a rare soft tissue sarcoma characterized by indolent growth and low metastatic potential, except in fibrosarcomatous transformation cases. Molecularly, DFSP is defined by a COL1A1-PDGFB fusion transcript that is targetable with imatinib therapy. Treatment involves wide surgical resection, with adjuvant radiation therapy in select cases. Radiation therapy may be employed in cases with close or positive margins, while conventional chemotherapy has limited utility. Multidisciplinary collaboration is crucial for optimal management. Overall, this case underscores the challenges in diagnosing and managing aggressive sarcomas like fibrosarcomatous DFSP, emphasizing the importance of vigilant surveillance and multidisciplinary collaboration in optimizing patient outcomes. Further research is needed to understand the mechanisms underlying fibrosarcomatous transformation and to explore novel therapeutic avenues for this challenging malignancy.

High Prevalence of Terbinafine Resistance Among Trichophyton mentagrophytes/T. interdigitale Species Complex, a Cross-Sectional Study from 2021 to 2022 in Northern Parts of Iran.

Treatment-resistant dermatophytosis caused by the members of the Trichophyton mentagrophytes/Trichophyton interdigitale species group (TMTISG) is increasing worldwide. We aimed to determine the prevalence of TMTISG in patients with dermatophytosis in two centers from north of Iran and detect the possible mutations in the squalene epoxidase (SQLE) gene in relevant terbinafine (TRB) resistant pathogenic isolates. From November 2021 to December 2022, 1960 patients suspected to dermatophytosis and referred to two mycology referral laboratories in the north of Iran were included in the study. Identification of all dermatophyte isolates was confirmed by RFLP of rDNA internal transcribed spacer (ITS) regions. Antifungal susceptibility testing against five common antifungals using the CLSI-M38-A3 protocol was performed. The TMTISG isolates resistant to TRB, were further analyzed to determine the possible mutations in the SQLE gene. Totally, 647 cases (33%) were positive for dermatophytosis of which 280 cases (43.3%) were identified as members of TMTISG. These were more frequently isolated from tinea corporis 131 (44.56%) and tinea cruris 116 (39.46%). Of 280 TMTISG isolates, 40 (14.3%) were resistant to TRB (MIC ≥ 4 µg/mL), all found to be T. indotineae in ITS sequencing. In SQLE sequencing 34 (85%) of TRB-resistant isolates had coincident mutations of Phe397Leu and Ala448Thr whereas four and two isolates had single mutations of Phe397Leu and Leu393Ser, respectively. Overall, the resistance of Iranian TMTISG isolates to TRB greatly occurred by a mutation of Phe397Leu in the SQLE gene as alone or in combination with Ala448Thr. Nevertheless, for the occurrence of in vitro resistance, only the presence of Phe397Leu mutation seems to be decisive.

Systematic review of approaches to detection and classification of skin cancer using artificial intelligence: Development and prospects.

In recent years, there has been a significant improvement in the accuracy of the classification of pigmented skin lesions using artificial intelligence algorithms. Intelligent analysis and classification systems are significantly superior to visual diagnostic methods used by dermatologists and oncologists. However, the application of such systems in clinical practice is severely limited due to a lack of generalizability and risks of potential misclassification. Successful implementation of artificial intelligence-based tools into clinicopathological practice requires a comprehensive study of the effectiveness and performance of existing models, as well as further promising areas for potential research development. The purpose of this systematic review is to investigate and evaluate the accuracy of artificial intelligence technologies for detecting malignant forms of pigmented skin lesions. For the study, 10,589 scientific research and review articles were selected from electronic scientific publishers, of which 171 articles were included in the presented systematic review. All selected scientific articles are distributed according to the proposed neural network algorithms from machine learning to multimodal intelligent architectures and are described in the corresponding sections of the manuscript. This research aims to explore automated skin cancer recognition systems, from simple machine learning algorithms to multimodal ensemble systems based on advanced encoder-decoder models, visual transformers (ViT), and generative and spiking neural networks. In addition, as a result of the analysis, future directions of research, prospects, and potential for further development of automated neural network systems for classifying pigmented skin lesions are discussed.

An updated reappraisal of dupilumab in children and adolescents with moderate-severe atopic dermatitis.

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.

Two-step hierarchical binary classification of cancerous skin lesions using transfer learning and the random forest algorithm.

Skin lesion classification plays a crucial role in the early detection and diagnosis of various skin conditions. Recent advances in computer-aided diagnostic techniques have been instrumental in timely intervention, thereby improving patient outcomes, particularly in rural communities lacking specialized expertise. Despite the widespread adoption of convolutional neural networks (CNNs) in skin disease detection, their effectiveness has been hindered by the limited size and data imbalance of publicly accessible skin lesion datasets. In this context, a two-step hierarchical binary classification approach is proposed utilizing hybrid machine and deep learning (DL) techniques. Experiments conducted on the International Skin Imaging Collaboration (ISIC 2017) dataset demonstrate the effectiveness of the hierarchical approach in handling large class imbalances. Specifically, employing DenseNet121 (DNET) as a feature extractor and random forest (RF) as a classifier yielded the most promising results, achieving a balanced multiclass accuracy (BMA) of 91.07% compared to the pure deep-learning model (end-to-end DNET) with a BMA of 88.66%. The RF ensemble exhibited significantly greater efficiency than other machine-learning classifiers in aiding DL to address the challenge of learning with limited data. Furthermore, the implemented predictive hybrid hierarchical model demonstrated enhanced performance while significantly reducing computational time, indicating its potential efficiency in real-world applications for the classification of skin lesions.

Coumarin/ß-Cyclodextrin Inclusion Complexes Promote Acceleration and Improvement of Wound Healing.

Coumarins have great pharmacotherapeutic potential, presenting several biological and pharmaceutical applications, like antibiotic, fungicidal, anti-inflammatory, anticancer, anti-HIV, and healing activities, among others. These molecules are practically insoluble in water, and for biological applications, it became necessary to complex them with cyclodextrins (CDs), which influence their bioavailability in the target organism. In this work, we studied two coumarins, and it was possible to conclude that there were structural differences between 4,7-dimethyl-2H-chromen-2-one (DMC) and 7-methoxy-4-methyl-2H-chromen-2-one (MMC)/ß-CD that were solubilized in ethanol, frozen, and lyophilized (FL) and the mechanical mixtures (MM). In addition, the inclusion complex formation improved the solubility of DMC and MMC in an aqueous medium. According to the data, the inclusion complexes were formed and are more stable at a molar ratio of 2:1 coumarin/ß-CD, and hydrogen bonds along with π-π stacking interactions are responsible for the better stability, especially for (MMC)2@ß-CD. In vivo wound healing studies in mice showed faster re-epithelialization and the best deposition of collagen with the (DMC)2@ß-CD (FL) and (MMC)2@ß-CD (FL) inclusion complexes, demonstrating clearly that they have potential in wound repair. Therefore, (DMC)2@ß-CD (FL) deserves great attention because it presented excellent results, reducing the granulation tissue and mast cell density and improving collagen remodeling. Finally, the protein binding studies suggested that the anti-inflammatory activities might exert their biological function through the inhibition of MEK, providing the possibility of development of new MEK inhibitors.

Iatrogenic Kaposi's Sarcoma: A Unique Case Unraveling Gastrointestinal Manifestations and Therapeutic Implications.

Kaposi's sarcoma (KS), linked to human herpesvirus 8 (HHV8), manifests in various clinical forms with iatrogenic KS uniquely tied to immune dysregulation induced by medical interventions. This study describes a 58-year-old male of sub-Saharan origin with a medical history of segmental and focal hyalinosis treated with methylprednisolone and mycophenolate mofetil. The patient developed skin lesions on both thighs, accompanied by post-prandial vomiting and abdominal pain. Clinical examination revealed flesh-colored nodules on the thighs and inguinal lymphadenopathy. Biopsy confirmed the diagnosis of KS, exhibiting positive nuclear labeling to anti-HHV8 and negative HIV serology. Additionally, radiological findings from the thoracic-abdominal-pelvic computed tomography (CT) scan significantly contribute to our understanding of the multiorgan involvement associated with KS in this case, providing valuable insights for diagnosis and therapeutic considerations. This case highlights the iatrogenic subtype of KS, linked to immunosuppression from prior medical interventions. Notably, gastrointestinal involvement was evident, with lesions in the stomach and small intestine. Intravenous paclitaxel administration resulted in a positive clinical response. This study underscores the importance of clinical vigilance, endoscopic evaluation, and early intervention in the nuanced diagnosis and management of iatrogenic KS.