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The connection between stress and skin disease has been extensively documented; however, there are no empirical studies investigating the incidence of traumatic event exposure and posttraumatic stress (PTS) symptoms among dermatology patients. To address this gap in the literature and begin to understand the associations between PTS symptoms and skin disease symptoms, this study used a sample of adults with self-reported skin disease symptoms to examine: (1) rates of potentially traumatic event (PTE) exposure and PTS symptoms; and (2) the association between PTS symptoms and skin-related quality of life, controlling for relevant covariates. Data were collected online through Cloud Research, and participants completed a battery of self-report measures. The sample included 310 participants (68.4% female) who endorsed current skin disease symptoms. Results indicated that 47.1% of participants endorsed clinical levels of PTS symptoms. Consistent with hypotheses, greater levels of PTS symptoms were associated with worse skin-related quality of life, and this association was particularly robust for arousal-related symptoms. Results shed light on the occurrence of trauma-related experiences among individuals with self-reported skin disease and indicate a link between PTS symptoms and the perceived burden of skin disease symptoms on daily living. However, this study was cross-sectional and relied on self-report measures; therefore, findings should be interpreted with caution, particularly since diagnoses could not be verified. Replication of this work in dermatology patients is needed to further understand these connections. [ABSTRACT FROM AUTHOR]

Background: Health-related stigma and its internalization among individuals with chronic health conditions contribute to impaired mental and physical health and quality of life. Research on health-related stigma has been siloed, with disease-specific measures that may not capture the experiences of individuals with multiple health conditions and that prevent comparisons across health conditions. The current study aimed to develop and test a transdiagnostic measure of internalized health-related stigma for use among adults with different physical health conditions. Methods: An existing measure of internalized mental health stigma was adapted to assess stigma due to chronic physical health conditions following COSMIN procedures, with input from advisory boards of community members living with a range of stigmatized health conditions (obesity, type 1 and type 2 diabetes, skin diseases, HIV, chronic pain, and cancers) and of health professionals who specialized in these conditions. The new Internalized Health-Related Stigma (I-HEARTS) Scale was tested in an online sample of 300 adults with these health conditions, recruited from ResearchMatch. Additional psychosocial measures of mental health and quality of life were administered, and participants provided information about their health conditions and demographic characteristics. Exploratory factor analysis and tests of reliability and validity were conducted to determine the psychometric properties of the I-HEARTS Scale, and k-means clustering and receiver of characteristic curve analysis were used to determine a clinically meaningful cutoff score indicating high levels of internalized stigma. Results: Factor analysis results yielded a 25-item scale with a 3-factor solution, with subscales of Perceived and Anticipated Stigma, Stereotype Application and Self-Devaluation, and Stigma Resistance. Psychometric properties for internal consistency, inter-item and item-total correlations, and test-retest reliability were strong. Certain demographics (e.g., younger age) and characteristics related to health conditions (e.g., greater symptom severity) were associated with higher levels of internalized stigma. I-HEARTS Scale scores correlated moderately to strongly with related but distinct psychosocial measures, and a cutoff score of 3.40 or higher on the 1–7 rating scale was determined to indicate clinically meaningful levels of internalized stigma. Conclusions: The I-HEARTS Scale is a reliable and valid measure for the assessment of internalized health-related stigma among adults with varied stigmatized chronic health conditions. Study pre-registration: https://osf.io/84c5d/?view_only=87238512f6d6475c87f8f64280a8a15f. [ABSTRACT FROM AUTHOR]

Ayurveda, the ancient system of medicine, comprehensively categorises skin disorders under the term "Kushtharoga", encompassing a wide spectrum of dermatological conditions. This classification is further elucidated into "Mahakushtha" and "Kshudra Kushtha", representing major and minor skin diseases, respectively. Major skin ailments include psoriasis, eczema, leprosy, and vitiligo, while minor conditions encompass common issues such as acne and dermatitis. Vicharchika, a term in Ayurveda associated with symptoms akin to eczema, poses a challenge in contemporary medical practices, where treatment options are often limited to antihistamines and topical steroids. The present case report describes the successful Ayurvedic management of a patient presenting with complaints of itching, discharge and erythematous skin lesions on the foot. The 36-year-old female patient was diagnosed with Vicharchika (eczema) and received treatments such as Bahir Parimarjana Chikitsa (External treatment) and Shaman Chikitsa (alleviating treatment) in place of Shodhana (Purification therapy) due to Alpadoshaavastha (immature body tissues), which resulted in significant improvement. The present case underscores the potential efficacy of Ayurvedic interventions, emphasising the importance of personalised treatment strategies in addressing dermatological conditions. [ABSTRACT FROM AUTHOR]

Skin cancer is a dangerous and prevalent cancer illness. It is the abnormal growth of cells in the outermost of the skin. Currently, it has received tremendous attention, highlighting an urgent need to address this worldwide public health crisis. The purpose of this study is to propose a convolutional neural network (CNN) to help dermatology physicians in the inspection, identification, and diagnosis of skin cancer. More precisely, we offer an automated method that leverages deep learning techniques to categorize binary categories of skin lesions. Our technique enlarges skin cancer by utilizing data pre-processing and augmentation to address the imbalanced class problem. Subsequently, fine-tuning is conducted on the pre-trained models visual geometry group (VGG-19) and MobileNetV2 to extract and classify the image features using transfer learning. The model is tested on the society for imaging informatics in medicine international skin imaging collaboration (SIIM-ISIC) 2020 dataset and achieved an accuracy of 95.16%, sensitivity of 90.83%, specificity of 99.2%, area under curve (AUC) of 97.57%, and precision of 99.06%. The proposed model based on MobileNetV2 outperforms the other techniques. [ABSTRACT FROM AUTHOR]

Objective: Skin involvement is common in systemic lupus erythematosus (SLE), but may be resistant to conventional treatment. We sought to evaluate the efficacy of anifrolumab (ANI) in refractory cutaneous manifestations of SLE. Methods: Case series of patients with refractory cutaneous SLE from three Rheumatology Departments in Greece. Outcome measures were improvement in Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K), physician global assessment (PGA) and Cutaneous Lupus Erythematosus Disease Area and Severity Index (CLASI). Clinically relevant improvement in skin was defined as decrease ≥50% (CLASI50) from baseline values. Results: Eighteen patients received ANI; all had active skin involvement at baseline. Mean (SD) SLEDAI and PGA at ANI initiation were 7.4 (2.7) and 1.4 (0.5), respectively, with a mean prednisone dose 4.9 (4.5) mg/day. Mean CLASI (Activity/Damage) at baseline was 13.9 (9.7)/2.9 (4.6). Patients were refractory to a mean 6.3 (1.5) immunomodulatory agents (including hydroxychloroquine and glucocorticoids) before the initiation of ANI. After a mean 8.5 (4.6) months, 89% (n = 16/18) of patients demonstrated significant improvement in general lupus and cutaneous disease activity, and glucocorticoid tapering. Mean SLEDAI and mean CLASI at last visit were 3.4 (1.9) and 2.1 (2.4)/1.4 (2.2), respectively, and mean daily prednisone dose decreased to 2.4 (2.2). Of note, in this group of highly refractory patients CLASI50 was achieved in 16/18 (89%) patients. One patient discontinued ANI after 4 infusions due to a varicella-zoster virus infection and one patient, who initially responded to treatment with ANI, experienced a skin flare due to temporary discontinuation due to Covid 19 infection. DORIS remission and LLDAS were attained in two (11.1%) and eleven (61.1%) patients, respectively. Conclusion: Anifrolumab is highly effective in various skin manifestations of SLE, even after prior failure to multiple treatments. [ABSTRACT FROM AUTHOR]

Background and Aim: Allergenic foods can trigger skin conditions, yet their impact in Bangladesh remains underexplored. This study aims to investigate the potential association between exposure to allergenic foods and the development of skin disease across Bangladesh. Methods: We conducted a cross‐sectional survey with 970 respondents from the divisions of Dhaka, Sylhet, Rangpur, and Chattogram who self‐reported skin disease triggered by food allergens. We analyzed the data using multiple response analysis and principal component logistic regression. Results: Approximately 64% of respondents had skin disease attributable to allergenic foods, with a relatively higher proportion among females (52%) than males (48%). Beef (67%), Brinjal (47.1%), Hilsa (45.8%), and Shrimp (23.7%) were the most frequently cited allergenic foods. Principal component logistic regression identified two highly significant principal components: the first representing Hilsa, Beef, and Brinjal (odds ratio = 2.256), and the sixth reflecting Corn (odds ratio = 1.342). Individuals who consumed foods with high loadings of the first principal component were 125.6% more likely to develop skin disease than nonconsumers, while those exposed to Corn had a 34.2% higher risk. Conclusion: The findings highlight prevalent allergenic foods in Bangladesh and their substantial impact on skin health, underscoring the need for dietary awareness and tailored interventions to mitigate allergic skin conditions in this population. [ABSTRACT FROM AUTHOR]

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Summary: Vitiligo is a common disorder characterized by the visible loss of skin pigmentation. Non‐segmental vitiligo (NSV) is the major subtype. The disease is caused by autoimmune‐mediated destruction of melanocytes. Vitiligo leads to stigmatization and a significant reduction in quality of life. Disregarding the psychosocial burden, vitiligo is sometimes viewed solely as a cosmetic problem and, according to a global survey, is diagnosed on average only after 2.4 years. This delay contributes to a considerable burden of disease, including suicidal ideation. Stigmatization promotes the development of psychological comorbidities such as anxiety and depressive disorders, with prevalence rates varying by country and study (0.1%–67.9%). Data for Germany are heterogeneous and largely based on estimates. Due to psychosocial factors, the inflammatory component, and a higher incidence of somatic comorbidities, NSV may be regarded as an inflammatory systemic disease. We recommend optimizing care by incorporating the assessment of quality of life as a standard in routine care, in addition to monitoring disease activity. Moreover, early screening for psychological comorbidities is crucial to initiate appropriate treatment before the condition becomes chronic and cumulative (irreversible) impairments occur. The goal is a personalized and patient‐centered integrated care approach that sustainably improves the health status of those affected. [ABSTRACT FROM AUTHOR]

Follicular skin disorders, including hidradenitis suppurativa (HS), frequently coexist with systemic autoinflammatory diseases, such as inflammatory bowel disease (IBD) and its subtypes, Crohn's disease and ulcerative colitis. Previous studies suggest that dysbiosis of the human gut microbiome may serve as a pathogenic link between HS and IBD. However, the role of the microbiome (gut, skin, and blood) in the context of IBD and various follicular disorders remains underexplored. Here, we performed a systematic review to investigate the relationship between follicular skin disorders, IBD, and the microbiome. Of the sixteen included studies, four evaluated the impact of diet on the microbiome in HS patients, highlighting a possible link between gut dysbiosis and yeast-exclusion diets. Ten studies explored bacterial colonization and HS severity with specific gut and skin microbiota, including Enterococcus and Veillonella. Two studies reported on immunological or serological biomarkers in HS patients with autoinflammatory disease, including IBD, and identified common markers including elevated cytokines and T-lymphocytes. Six studies investigated HS and IBD patients concurrently. Our systematic literature review highlights the complex interplay between the human microbiome, IBD, and follicular disorders with a particular focus on HS. The results indicate that dietary modifications hold promise as a therapeutic intervention to mitigate the burden of HS and IBD. Microbiota analyses and the identification of key serological biomarkers are crucial for a deeper understanding of the impact of dysbiosis in these conditions. Future research is needed to more thoroughly delineate the causal versus associative roles of dysbiosis in patients with both follicular disorders and IBD. [ABSTRACT FROM AUTHOR]

Particulate matter (PM) is a harmful air pollutant composed of chemicals and metals which affects human health by penetrating both the respiratory system and skin, causing oxidative stress and inflammation. This review investigates the association between PM and skin disease, focusing on the underlying molecular mechanisms and specific disease pathways involved. Studies have shown that PM exposure is positively associated with skin diseases such as atopic dermatitis, psoriasis, acne, and skin aging. PM-induced oxidative stress damages lipids, proteins, and DNA, impairing cellular functions and triggering inflammatory responses through pathways like aryl hydrocarbon receptor (AhR), NF-κB, and MAPK. This leads to increased production of inflammatory cytokines and exacerbates skin conditions. PM exposure exacerbates AD by triggering inflammation and barrier disruption. It disrupts keratinocyte differentiation and increases pro-inflammatory cytokines in psoriasis. In acne, it increases sebum production and inflammatory biomarkers. It accelerates skin aging by degrading ECM proteins and increasing MMP-1 and COX2. In conclusion, PM compromises skin health by penetrating skin barriers, inducing oxidative stress and inflammation through mechanisms like ROS generation and activation of key pathways, leading to cellular damage, apoptosis, and autophagy. This highlights the need for protective measures and targeted treatments to mitigate PM-induced skin damage. [ABSTRACT FROM AUTHOR]

Skin conditions are becoming increasingly prevalent across the world in current times. With the rise in dermatological disorders, there is a need for computerized techniques that are completely noninvasive to patients' skin. As a result, deep learning models have become standard for the computerized detection of skin diseases. The performance efficiency of these models improves with access to more data with their primary aim being image classification. In this paper, we present a skin disease detection methodology using image processing techniques, non-local means denoising and convolutional neural network (CNN) backed by sparse dictionary learning. Here, the major benefit of using NLM denoising followed by sparse dictionary learning with CNNs in image classification lies in leveraging a multi-stage approach that enhances the quality of input data, extracts meaningful and discriminative features, and improves the overall performance of the classification model. This combined approach addresses challenges such as noise robustness, feature extraction, and classification accuracy, making it particularly effective in complex image analysis tasks. For denoising, the average Peak Signal to Noise Ratio (PSNR) obtained for images from HAM-10000 dataset is 33.59 dB. For the ISIC-2019 dataset, the average PSNR for the train folder is 34.37 dB, and for the test folder it is 34.39 dB. The deep learning network is trained for the analysis of skin cancer images using a CNN model and is achieving acceptable results in classifying skin cancer types. The datasets used contain high-resolution images. After all the tests, the accuracy obtained is 85.61% for the HAM-10000 dataset and 81.23% for the ISIC-2019 dataset, which is on par with existing approaches validated by benchmarking results. [ABSTRACT FROM AUTHOR]

Dermatological conditions are primarily prevalent in humans and are primarily caused by environmental and climatic fluctuations, as well as various other reasons. Timely identification is the most effective remedy to avert minor ailments from escalating into severe conditions. Diagnosing skin illnesses is consistently challenging for health practitioners. Presently, they rely on conventional methods, such as examining the condition of the skin. State-of-the-art technologies can enhance the accuracy of skin disease diagnosis by utilizing data-driven approaches. This paper presents a Computer Assisted Diagnosis (CAD) framework that has been developed to detect skin illnesses at an early stage. We suggest a computationally efficient and lightweight deep learning model that utilizes a CNN architecture. We then do thorough experiments to compare the performance of shallow and deep learning models. The CNN model under consideration consists of seven convolutional layers and has obtained an accuracy of 87.64% when applied to three distinct disease categories. The studies were conducted using the International Skin Imaging Collaboration (ISIC) dataset, which exclusively consists of dermoscopic images. This study enhances the field of skin disease diagnostics by utilizing state-of-the-art technology, attaining exceptional levels of accuracy, and striving for efficiency improvements. The unique features and future considerations of this technology create opportunities for additional advancements in the automated diagnosis of skin diseases and tailored treatment. [ABSTRACT FROM AUTHOR]

An outbreak of Psoroptes sp.-caused mange was detected in a llama herd of Larcas, Jujuy province, Argentina. Infested llamas showed alopecia, erythema, hyperpigmentation, hyperkeratosis, and inflammation of the ear pinnae, as well as crusts and serous, serosanguineous, or purulent drainage with unpleasant smell in the external ear canal. Microscopic evaluation of skin scrapings revealed 0.5- to 0.7-mm-long acari identified as Psoroptes sp. based on their morphology. Histology showed a typical allergic reaction with perivascular to periadnexal mixed inflammatory infiltrate. Phylogenetic tree analysis showed that the cytochrome c oxidase subunit I gene sequences analyzed from the sampled acari clustered into a single P. ovis clade including sequences isolated from rabbits and bighorn sheep, with P. natalensis as a sister taxon that infested bighorn sheep from the USA. Phylogenetic analysis of cytochrome b sequences showed three well-supported clades, one of which contained the sequences of the Larcas llamas and US bighorn sheep isolates. This is the first report on P. ovis infestation of llamas raised in their original location. Investigations on mange etiological agents acting on South American camelids and their distribution are necessary to implement control strategies to mitigate the negative impacts of these parasitic infections. [ABSTRACT FROM AUTHOR]

Skin disease image segmentation faces two major challenges: the complex and varied lesion morphology and the presence of interfering image backgrounds. To address these difficulties in skin disease image segmentation, we propose a Residual U-Net architecture with Channel-Space Separate Attention based on depthwise separable convolutions. The multi-scale residual U-Net modules in the encoder efficiently capture multi-scale texture information in lesions and backgrounds within a single stage, overcoming the limitations of U-Net in extracting just local features. The introduction of ConvMixer Block for global contextual modeling contributes to suppress complex background interference and enhances the overall understanding of lesion morphology. Additionally, we employ a Channel-Space Separate Attention mechanism with depthwise separable convolutions(CSSA-DSC) for feature fusion, effectively addressing the limited expressiveness issue associated with U-Net’s direct skip-connection concatenation. Experimental results on the PH2, ISIC 2017, and ISIC 2018 datasets demonstrate our method’s strong multi-scale modeling and feature expression capabilities. [ABSTRACT FROM AUTHOR]

Tirbanibulin 1% ointment is a synthetic antiproliferative agent approved in 2021 by the European Union for treating actinic keratoses (AK). Topical tirbanibulin has clinically resolved HPV-57 (+) squamous cell carcinoma (SCC), HPV-16 (+) vulvar high-grade squamous intraepithelial lesion, epidermodysplasia verruciformis, and condyloma. We examined how tirbanibulin might affect HPV oncoprotein expression and affect other cellular pathways involved in cell proliferation and transformation. We treated the HeLa cell line, containing integrated HPV-18, with increasing doses of tirbanibulin to determine the effects on cell proliferation. Immunoblotting was performed with antibodies against the Src canonical pathway, HPV 18 E6 and E7 transcription regulation, apoptosis, and invasion and metastasis pathways. Cell proliferation assays with tirbanibulin determined the half‐maximal inhibitory concentration (IC50) of HeLa cells to be 31.49 nmol/L. Increasing concentrations of tirbanibulin downregulates the protein expression of Src (p < 0.001), phospho-Src (p < 0.001), Ras (p < 0.01), c-Raf (p < 0.001), ERK1 (p < 0.001), phospho-ERK1 (p < 0.001), phospho-ERK2 (p < 0.01), phospho-Mnk1 (p < 0.001), eIF4E (p < 0.01), phospho-eIF4E (p < 0.001), E6 (p < 0.01), E7 (p < 0.01), Rb (p < 0.01), phospho-Rb (p < 0.001), MDM2 (p < 0.01), E2F1 (p < 0.001), phospho-FAK (p < 0.001), phospho-p130 Cas (p < 0.001), Mcl-1 (p < 0.01), and Bcl-2 (p < 0.001), but upregulates cPARP (p < 0.001), and cPARP/fPARP (p < 0.001). These results demonstrate that tirbanibulin may impact expression of HPV oncoproteins via the Src- MEK- pathway. Tirbanibulin significantly downregulates oncogenic proteins related to cell cycle regulation and cell proliferation while upregulating apoptosis pathways.Plain Language Summary: Tirbanibulin is Promising Novel Therapy for Human Papillomavirus (HPV)-associated Diseases. Tirbanibulin 1% ointment is an approved synthetic topical ointment for treating actinic keratoses (AK), a precancer of skin cancer. Topical tirbanibulin has previously been reported to clinically resolve human papillomavirus (HPV)-(+) diseases. In this study, we examine how tirbanibulin may affect the HPV and pathways associated with cancer. We treated the HeLa cell line to determine the effects on HPV cell proliferation. Increasing the concentration of tirbanibulin statistically significantly affected numerous cellular pathways often associated with cancer. These results demonstrate that tirbanibulin may impact expression of HPV oncoproteins and thereby kill cancer cells. [ABSTRACT FROM AUTHOR]

Background & Aim: Rosacea is a chronic inflammatory, multifactorial disease for which combination therapy could be an effective treatment. In this study, we evaluate the effect of the combination therapy of brimonidine 0.33% and ivermectin 1% as a single cream for the treatment of papulopustular rosacea. Method: A stable and appropriate formulation was prepared by adding the aqueous phase to the lipid phase while being stirred. The stability and physicochemical properties of the formulation were evaluated under accelerated conditions. Twelve patients (36–60 years) with mild to moderate papulopustular rosacea and a Demodex count of five or more were treated with the combination of brimonidine 0.33% and ivermectin 1% cream. Clinician's Erythema Assessment (CEA), Patients Self‐Assessment (PSA), skin erythema (ΔE) and lightness (ΔL), and skin biophysical parameters including transepidermal water loss (TEWL), skin hydration, pH, and sebum content, as well as erythema and melanin index and ultrasound parameters, were measured before treatment and 4 and 8 weeks after. Adverse drug reactions were also recorded. Results: CEA and PSA decreased significantly from 3 to 2 after 8 weeks, respectively (p‐value = 0.014 for CEA and 0.010 for PSA). ΔE and ΔL, as well as skin erythema index and TEWL improved after 8 weeks of treatment (p < 0.05). Two patients withdrew from the study in the first week because of local adverse effects; one developed flushing following treatment and left the investigation after 4 weeks and another patient withdrew from the study after 4 weeks due to deciding to become pregnant. Conclusion: Eight‐week treatment with the combination of brimonidine 0.33% and ivermectin 1% was shown to be effective for improvement of erythema and inflammatory lesions in mild to moderate papulopustular rosacea. [ABSTRACT FROM AUTHOR]

Summary: Background and Objectives: Adoption and acceptance of digital health services (DHS) in the German population and in persons with skin diseases is unclear. Both factors were analyzed in this survey. Methods: A standardized survey with items on digital competences and attitudes, use and acceptance of DHS was applied to a representative sample of the German adult population. Bivariate and multivariate analyses were conducted. Results: Out of 2,101 participants, 29.9% reported having had skin diseases in the last 12 months. Among them, adoption and acceptance were at 43.6% and 52.3%, respectively. Both values are significantly higher compared to participants without skin diseases (29.2%; p < 0.01 and 45.5%; p < 0.01). 18.9% of participants with a skin disease used digital diagnostic support, but only 9.7% applied it for a skin disease (p < 0.01). For all participants, with and without skin disease, the DHS most commonly used were passive health monitoring (14.3%) and diagnostic support (11.5%), telemedicine was least used (4.7% video‐consultation, 2.5% store‐and‐forward). Use and acceptance were associated with young age, education, low data privacy concerns, digital confidence, having a skin disease, and high severity of skin disease. Conclusions: DHS for skin diseases are used rarely but have a high potential. [ABSTRACT FROM AUTHOR]

Early diagnosis is paramount to preventing skin diseases and reducing mortality, given their global prevalence. Visual detection by experts using dermoscopy images has become the gold standard for detecting skin cancer. However, a significant challenge in skin cancer detection and classification lies in the similarity of appearance among skin disease lesions and the complexity of dermoscopic images. In response, we developed multi-model late feature fusion network (MLFF-Net), a multi-model late feature fusion network tailored for skin disease detection. Our approach begins with image pre-processing techniques to enhance image quality. We then employ a twostream network comprising an enhanced densely linked network (DenseNet121) and a vision transformer (ViTb16). We leverage shallow and deep feature fusion, late fusion, and an attention module to enhance the model's feature extraction efficiency. The subsequent feature fusion module constructs multi-receptive fields to capture disease information across various scales and uses generalized mean pooling (GeM) pooling to reduce the spatial dimensions of lesion characteristics. Finally, we implement and test our skin lesion categorization model, demonstrating its effectiveness. Despite the combination, convolutional neural network (CNN) outperforms ViT approaches, with our model enhancing the accuracy of the best model by 6.1%. [ABSTRACT FROM AUTHOR]

Dermatology is an important specialty in veterinary medicine, focusing on the skin and its appendages. Therefore, the present study highlighted the percentage of skin disorders, as well as their associated risk factors, from cases received at the Parasitology-Dermatology clinic of the Hassan II Institute of Agronomy and Veterinary Medicine (IAV Hassan II), Rabat, Morocco for two years. A total of 1561 dogs (1450 dogs were in 28 different pure breeds and 111 dogs were mongrels, 805 males, and 756 females, with an average age of 6.5 years old) were presented at the University Veterinary Teaching Hospital (UVTH) of the IAV Hassan II from the end of October 2020 to the end of May 2022 (including vaccinations) and 125 dogs were assessed and 161 skin diseases were found (a few dogs had more than one skin disease). Dermatological examinations represented an average of 8.00% (125/1561) of all canine cases received at the University Veterinary Teaching Hospital. The most common clinical signs were pruritus, alopecia, erythema, onychogryphosis, and visible ectoparasites. Parasitic dermatoses were the most frequent, representing 44.10% of all dermatological cases, followed by allergic dermatoses (25.47%) and fungal skin infections (19.25%). Bacterial skin infections and dermatological manifestations of endocrine disorders were infrequent, representing 8.70% and 2.48%, respectively of all observed cases. Risk factors contributing to the occurrence of canine skin disorders included age and lifestyle for sarcoptic mange. An apparent predilection for the living environment was observed in the case of canine leishmaniosis, and an apparent predilection for sex regarding otodectic mange was also demonstrated. Similar results were found for the living environment and lifestyle concerning canine atopic dermatitis. Data reported herein fill gaps in knowledge of skin disorders and their associated risk factors in dogs in Morocco, demonstrating the dominance of skin diseases of zoonotic interest, including flea bite allergy dermatitis (FBAD), dermatophytosis, and canine leishmaniosis. [ABSTRACT FROM AUTHOR]

Psoriasis, a systemic autoimmune disorder primarily affecting the skin, manifests through erythematous plaques and scales, impacting approximately 2–3% of the global population. Chronic periodontitis, a prevalent oral disease characterized by the destruction of tooth-supporting tissues, affects roughly 10–15% of adults worldwide. Emerging evidence suggests a bidirectional relationship between psoriasis and chronic periodontitis, supported by epidemiological studies indicating a higher prevalence of periodontitis among individuals with psoriasis and vice versa. Both conditions are chronic inflammatory diseases marked by dysregulated immune responses and altered cytokine profiles, notably involving proinflammatory cytokines such as TNF-α and IL-17. Clinical studies highlight a reciprocal impact of treating one condition on the other, underscoring the necessity of interdisciplinary collaboration between dermatologists and periodontists in managing patients with both conditions. This narrative review provides a comprehensive overview of the relationship between psoriasis and chronic periodontitis, examining epidemiological associations, shared inflammatory pathways, genetic insights, microbial dysbiosis, environmental factors, and clinical implications. The review emphasizes the importance of integrated care approaches and the potential for targeted therapeutic interventions to improve both psoriatic and periodontal patient outcomes, advocating for further research into the molecular and cellular mechanisms underpinning the comorbidity of these diseases. [ABSTRACT FROM AUTHOR]

Kathryn Haran,1 Chandler E Johnson,1 Payton Smith,1 Zoë Venable,2 Allison Kranyak,1 Tina Bhutani,1 Caleb Jeon,2 Wilson Liao1,3 1Department of Dermatology, University of California San Francisco, San Francisco, CA, USA; 2Department of Dermatology, Golden State Dermatology, Berkeley, CA, USA; 3Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USACorrespondence: Wilson Liao, Department of Dermatology, University of California San Francisco, 2340 Sutter Street, Box 0808, San Francisco, CA, 94143, USA, Tel +1 415 476-8364, Email wilson.liao@ucsf.eduAbstract: Psoriasis is an immune-mediated skin disease known to be associated with a higher risk of cardiometabolic comorbidities such as hypertension, myocardial infarction, and stroke. GLP-1 receptor agonists (GLP-1RAs) are medications approved to treat type 2 diabetes mellitus and obesity and have been reported to improve psoriasis. As more psoriasis patients start GLP-1RAs for approved indications, it is of interest to understand the impact of GLP-1RAs on both psoriasis and associated cardiovascular risk. In this review, we examine the effect of GLP-1RAs on psoriasis and cardiovascular comorbidities—defined as hypertension, stroke, and myocardial infarction. The majority of case reports and prospective cohort studies found GLP-1RAs improved psoriasis, while two randomized controlled trials showed conflicting results. For cardiovascular disease, most studies found GLP-1RAs reduced systolic blood pressure, total stroke, and myocardial mortality. These results suggest that GLP-1RAs may be a particularly promising treatment for psoriasis patients with diabetes or obesity comorbidities, offering both cardioprotective benefits and potential improvement in psoriatic symptoms.Keywords: skin disease, oxidative stress, hypertension, stroke, myocardial infarction

Ayurveda, the ancient system of medicine, comprehensively categorises skin disorders under the term “Kushtharoga”, encompassing a wide spectrum of dermatological conditions. This classification is further elucidated into “Mahakushtha” and “Kshudra Kushtha”, representing major and minor skin diseases, respectively. Major skin ailments include psoriasis, eczema, leprosy, and vitiligo, while minor conditions encompass common issues such as acne and dermatitis. Vicharchika, a term in Ayurveda associated with symptoms akin to eczema, poses a challenge in contemporary medical practices, where treatment options are often limited to antihistamines and topical steroids. The present case report describes the successful Ayurvedic management of a patient presenting with complaints of itching, discharge and erythematous skin lesions on the foot. The 36-year-old female patient was diagnosed with Vicharchika (eczema) and received treatments such as Bahir Parimarjana Chikitsa (External treatment) and Shaman Chikitsa (alleviating treatment) in place of Shodhana (Purification therapy) due to Alpadoshaavastha (immature body tissues), which resulted in significant improvement. The present case underscores the potential efficacy of Ayurvedic interventions, emphasising the importance of personalised treatment strategies in addressing dermatological conditions.

Abstract Skin conditions are becoming increasingly prevalent across the world in current times. With the rise in dermatological disorders, there is a need for computerized techniques that are completely noninvasive to patients’ skin. As a result, deep learning models have become standard for the computerized detection of skin diseases. The performance efficiency of these models improves with access to more data with their primary aim being image classification. In this paper, we present a skin disease detection methodology using image processing techniques, non-local means denoising and convolutional neural network (CNN) backed by sparse dictionary learning. Here, the major benefit of using NLM denoising followed by sparse dictionary learning with CNNs in image classification lies in leveraging a multi-stage approach that enhances the quality of input data, extracts meaningful and discriminative features, and improves the overall performance of the classification model. This combined approach addresses challenges such as noise robustness, feature extraction, and classification accuracy, making it particularly effective in complex image analysis tasks. For denoising, the average Peak Signal to Noise Ratio (PSNR) obtained for images from HAM-10000 dataset is 33.59 dB. For the ISIC-2019 dataset, the average PSNR for the train folder is 34.37 dB, and for the test folder it is 34.39 dB. The deep learning network is trained for the analysis of skin cancer images using a CNN model and is achieving acceptable results in classifying skin cancer types. The datasets used contain high-resolution images. After all the tests, the accuracy obtained is 85.61% for the HAM-10000 dataset and 81.23% for the ISIC-2019 dataset, which is on par with existing approaches validated by benchmarking results.

Because of their convenience, rapidness and non-invasive advantages, non-invasive skin physiological monitoring technique can be auxiliary examination of many common skin diseases and is of great significance in guiding the diagnosis and treatment of diseases. Skin physiological monitor is a newly-developed non-invasive skin physiological monitoring technique, which can evaluate skin barrier by measuring transepidermal water loss rate (TEWL), skin surface pH, stratum corneum hydration (SCH), sebum content and so on. This manuscript reviews and discusses the applications and significance of non-invasive skin physiological monitors in dermatology. It will provide a basis for analyzing the correlation between skin barrier function and diagnostic and therapeutic outcomes.

This research aims to discover the role of skin diseases in the narrative structure of M. Bakir’s Hikayat Agung Sakti as well as its surrounding ideological, social, political, and cultural contexts. Mieke Bal’s narratological theory was applied to map and analyze the elements of the fabula: event, time, actor, and location. Methodologically, this research consisted of two levels: text and context. At the first level, lingual data were collected using the note-taking technique and then explained interpretatively using relevant theoretical concepts. At the second level, data were collected through literature study on ideology and context. The text and context data were explained through dialectics and interreference. This research yielded several main results. First, skin diseases (itches, smallpox, scabs, and Tinea corporis) are attached to the elements of the fabula. These diseases change circumstances, shape events and time, infect the characters (the Gods), and change the locations (from heaven to earth). Skin diseases were found to be the building block of the narrative structure. In this role, skin diseases become a means of articulating Islamism. This narrative is linked to the development of Islam in Malay-speaking lands and political resistance to polytheistic Hinduism, which is placed in opposition to the monotheistic Islam which places Allah as the only deity. This ideology was articulated and written down as a literary work to be disseminated among local Straits-born Chinese. This is also contextually related to the issues of manuscript rental, diseases in Malay tradition, and spread of diseases in Batavia in the 19th century.

Psoriasis, a systemic autoimmune disorder primarily affecting the skin, manifests through erythematous plaques and scales, impacting approximately 2–3% of the global population. Chronic periodontitis, a prevalent oral disease characterized by the destruction of tooth-supporting tissues, affects roughly 10–15% of adults worldwide. Emerging evidence suggests a bidirectional relationship between psoriasis and chronic periodontitis, supported by epidemiological studies indicating a higher prevalence of periodontitis among individuals with psoriasis and vice versa. Both conditions are chronic inflammatory diseases marked by dysregulated immune responses and altered cytokine profiles, notably involving proinflammatory cytokines such as TNF-α and IL-17. Clinical studies highlight a reciprocal impact of treating one condition on the other, underscoring the necessity of interdisciplinary collaboration between dermatologists and periodontists in managing patients with both conditions. This narrative review provides a comprehensive overview of the relationship between psoriasis and chronic periodontitis, examining epidemiological associations, shared inflammatory pathways, genetic insights, microbial dysbiosis, environmental factors, and clinical implications. The review emphasizes the importance of integrated care approaches and the potential for targeted therapeutic interventions to improve both psoriatic and periodontal patient outcomes, advocating for further research into the molecular and cellular mechanisms underpinning the comorbidity of these diseases.

Microemulsions (MEs) and nanoemulsions (NEs) are dispersions of two immiscible liquids which are usually transparent/translucent. Several reports are available on uses of MEs/NEs to increase efficacy of the loaded active ingredient(s) in topical dosage forms. This review aims to describe brief applications of MEs/NEs in common skin diseases as well as skincare products. Advantages of MEs/NEs in comparison with the traditional bulk form, including their improved efficacy and safety, have been discussed to highlight the importance of use of such delivery systems. The review briefs mechanism of action of MEs/NEs in enhancing delivery of the cargo. Furthermore, applications of MEs/NEs in common skin diseases including infectious rashes, pigmentation disorders (hyperpigmentaion and hypopigmentation), wound healing, skin cancers and scaling patches and plaques/papulosquamous disorders (psoriasis, atopic dermatitis and acne) have been discussed. MEs/NEs in skin care products have also been reviewed here.

Abstract Skin diseases are prevalent globally and can have detrimental effects on the individual’s health-related quality of life (HRQoL). The treatment of dermatological patients typically focuses on clinical signs and symptoms and a subjective view of the impact of the disease on the patient’s life. Assessing quality of life can help provide patients with better service, by acknowledging their real needs and interfering with treatment decisions. The aim of the study was therefore to assess quality of life of dermatology outpatients and its associated factors. An analytical cross-sectional study was conducted in the dermatology clinic of Halibet National Referral Hospital in Asmara, Eritrea. HRQoL data were collected between May 6 and August 18, 2022 using a validated standard tool (Skindex-29). Descriptive statistics, logistic regression and paired t-test were employed using Statistical Package for Social Sciences (Version-26.0). A total of 375 dermatology clinic out-patients with a median age of 29 (Interquartile range: 25) were included in the study. The most commonly seen skin diseases were eczema, seborrhoeic dermatitis and tinea pedis. Emotion, symptom, and functioning domains of HRQoL were severely impaired in 75.7%, 50.4% and 57.6% of all dermatology outpatients, respectively. More than half of the respondents (57.9%) had a severely impaired overall HRQoL. In the overall HRQoL, being a rural resident [Adjusted Odds Ratio (AOR) 1.98, 95% CI 1.18, 3.33] and presence of chronic illness (AOR 2.16, 95% CI 1.22, 3.82) were significantly associated with severely impaired overall quality of life. A significantly higher mean score (p

Background: When immunofluorescence on the frozen section is insufficient or unavailable, salvage immunofluorescence techniques can be used on formalin-fixed, paraffin-embedded tissue. The goal of the current investigation was to evaluate the diagnostic value of paraffin immunofluorescence following proteinase K digestion on skin biopsy samples in comparison to fresh frozen immunofluorescence. Materials and Methods: It was standardized and compared to the immunofluorescence on fresh frozen tissue (IF-Frozen) for paraffin immunofluorescence by proteinase K digestion of formalin-fixed paraffin-embedded skin biopsies (IF-FFPE). The study included 50 native skin biopsy cases, and fluorescein isothiocyanate-labeled IgA, IgG, IgM, and C3 intensity levels were evaluated in each case. Results: A total of 50 cases of native skin biopsy were included in the study, and their intensities for IgA, IgG, IgM, and C3 antibodies were compared. The average staining intensities in each disease group for the antibodies had equal intensity or had a minor difference (1+)/significant difference (2+). Paraffin immunofluorescence, proteinase K digestion had the best correlation, that is, had either equal or minor difference (1+) with fresh frozen immunofluorescence. The difference of 2+ intensity of antibodies between IF-FFPE and IF-Frozen was noted mainly in C3 antibody on paraneoplastic pemphigus. IF-FFPE showed a sensitivity of 100%, 97.6%, 100%, and 81.6% for IgA, IgG, IgM, and C3, respectively, whereas the specificity was 100% for IgA, IgG, IgM, and C3. Limitations: Small sample size and and the employment of one method of antigen retrieval in IF-FFPE. Conclusion: Immunofluorescence techniques done on formalin-fixed paraffin-embedded tissue can serve as salvage techniques in cases where immunofluorescence on the frozen section may not be adequate or may not be available.

PurposeMethodsResultsConclusionsThe aim of this study is to evaluate the effect of blepharoplasty, ptosis or eyebrow surgery to quality of life and use of medication related to headache or eyelid skin disease.A longitudinal, prospective study including 90 consecutive patients who underwent blepharoplasty, ptosis, eyebrow or combined surgery.  The quality of life related to headache was evaluated by HIT6™ and to eyelid skin disease by Skindex-Mini SDM. Use of medication was measured by number of days per week medication was used for headache or eyelid skin disease.Preoperatively 46 (51%) had headache, 4 (4%) eyelid skin and 2 (2%) headache and eyelid skin symptoms. The median HIT-6 difference was −21 (range –36–0; p < .0001) and the median SDM difference was −13 (range = –15 to –1; p = .036). The median difference in medication days/week related to headache was −1 (range −4–0; p < .0001) and to eyelid skin disease −1.5 (range –3 to –1; p = .034).This study shows that after upper eyelid blepharoplasty, ptosis or brow ptosis surgery, headache or eyelid skin disease-related quality of life measures are significantly improved, and the use of headache or eyelid skin-related medication is significantly less. [ABSTRACT FROM AUTHOR]

The aim of this review is to increase obstetrician awareness of pregnancy‐associated Sweet syndrome. Patients present with fever, leukocytosis, and skin eruption, which can mimic other infectious or inflammatory conditions, but do not respond to antibiotics. A search using PubMed, EMBASE, and Web of Science Core Collection was conducted to review all reported cases of pregnancy‐associated Sweet syndrome, an acute febrile neutrophilic dermatosis occurring during pregnancy or postpartum. A total of 33 episodes among 30 patients were identified, with the majority (54.5% [18]) of cases occurring within the second trimester. Among the 30 patients, skin lesions most commonly affected the head and neck (73.3% [22]), with rare oral or ocular involvement. Leukocytosis was the most common laboratory finding, reported in 96.7% [29] of patients, with neutrophil predominance noted in 70.0% [21]. The diagnosis was confirmed for all patients with pathognomonic results of skin biopsies. Of the 27 cases detailing treatment, systemic corticosteroids were most frequently used (19 cases), followed by conservative management (seven cases), and dapsone (one case). The dapsone‐treated patient and 15 of the 19 steroid‐treated patients experienced resolution, but additional management strategies were required in the remaining four individuals. Spontaneous resolution occurred during pregnancy in six of the seven conservatively managed individuals, with one patient experiencing spontaneous abortion shortly after skin eruption at 10 weeks of gestation. No associated maternal deaths were reported. Obstetric complications of pregnancy‐associated Sweet syndrome included endomyometritis, sterile placental abscesses, and abdominal wall necrosis. Delivery of healthy infants occurred in 24 of the 25 cases that presented fetal outcome, which included two infants who underwent medically indicated preterm deliveries. Synopsis: There are 30 documented cases of pregnancy‐associated Sweet syndrome. One early miscarriage, delayed diagnosis, and extracutaneous neutrophil infiltration contributing to maternal morbidity have been reported. [ABSTRACT FROM AUTHOR]

The changes in human lifestyle over the past few decades have impacted the prevalence of skin diseases within different societies. Skin diseases may result in various physical and mental disorders. The most common mental disorders observed among the patients are stress, anxiety, and depression. This study aims to investigate the global prevalence of anxiety, depression, and stress in patients with skin diseases. In this Systematic Review and Meta-Analysis study, the PubMed, Scopus, Science Direct, Embase, Web of science, and Google Scholar repositories were searched without a lower time limit. Heterogeneity among the identified studies was examined using the I2 index, and accordingly random effects model was adopted for analysis. Data analysis was conducted within the Comprehensive Meta-Analysis software (v. 2). In total, 113 studies were included for the final analysis. The overall pooled prevalence of stress, depression, and anxiety in skin disease patients was found to be 39.4%, 27.2% and 28.8%, respectively. Among patients with psoriasis, acne, vitiligo or atopic dermatitis diseases, the highest number of patients suffering from stress was related to patients with acne (75.7%). The highest prevalence of depression, and anxiety was reported in patients with vitiligo (38.3%) and acne (36.5%), respectively. Considering the high prevalence of mental disorders among patients with skin diseases and recognising the impacts of mental health challenges on patients' well-being, the findings of this study provide valuable insights for identifying specific populations that require targeted interventions for the diagnosis, treatment, and prevention of mental illnesses. Accordingly, healthcare policymakers should incorporate psychological treatment and support measures as integral components of comprehensive care strategies for patients with skin diseases. [ABSTRACT FROM AUTHOR]

Acne is a chronic inflammatory disease of the pilosebaceous unit resulting from androgen-induced increased sebum production, altered keratinization, inflammation, and bacterial colonization of the hair follicles of the face, neck, chest and back by Propionibacterium acnes. Overall, inflammation and immune responses are strongly implicated in the pathogenesis of acne. Although early colonization with Propionibacterium acnes and family history may play an important role in the disease, it remains unclear exactly what triggers acne and how treatment affects disease progression. The influence of diet on acne disease is a growing research topic, yet few studies have examined the effects of diet on the development and clinical severity of acne disease, and the results have often been contradictory. Interestingly, very low-calorie ketogenic diet (VLCKD) has been associated with both significant reductions in body weight and inflammatory status through the production of ketone bodies and thus it has been expected to reduce the exacerbation of clinical manifestations or even block the trigger of acne disease. Given the paucity of studies regarding the implementation of VLCKD in the management of acne, this review aims to provide evidence from the available scientific literature to support the speculative use of VLCKD in the treatment of acne. [ABSTRACT FROM AUTHOR]

Skin diseases are prevalent globally and can have detrimental effects on the individual’s health-related quality of life (HRQoL). The treatment of dermatological patients typically focuses on clinical signs and symptoms and a subjective view of the impact of the disease on the patient’s life. Assessing quality of life can help provide patients with better service, by acknowledging their real needs and interfering with treatment decisions. The aim of the study was therefore to assess quality of life of dermatology outpatients and its associated factors. An analytical cross-sectional study was conducted in the dermatology clinic of Halibet National Referral Hospital in Asmara, Eritrea. HRQoL data were collected between May 6 and August 18, 2022 using a validated standard tool (Skindex-29). Descriptive statistics, logistic regression and paired t-test were employed using Statistical Package for Social Sciences (Version-26.0). A total of 375 dermatology clinic out-patients with a median age of 29 (Interquartile range: 25) were included in the study. The most commonly seen skin diseases were eczema, seborrhoeic dermatitis and tinea pedis. Emotion, symptom, and functioning domains of HRQoL were severely impaired in 75.7%, 50.4% and 57.6% of all dermatology outpatients, respectively. More than half of the respondents (57.9%) had a severely impaired overall HRQoL. In the overall HRQoL, being a rural resident [Adjusted Odds Ratio (AOR) 1.98, 95% CI 1.18, 3.33] and presence of chronic illness (AOR 2.16, 95% CI 1.22, 3.82) were significantly associated with severely impaired overall quality of life. A significantly higher mean score (p < 0.001) was observed in emotion [Mean (M) = 55.60, Standard Deviation (SD) = 21.0] as compared to functioning (M = 46.89, SD = 21.2). On the other hand, significantly higher mean score (p < 0.001) was observed on symptom (M = 54.08, SD = 20.5) as compared to functioning (M = 46.89, SD = 21.2). Skin diseases severely affected the emotion, functioning, and symptom domains of health-related quality of life. This highlights the importance of providing physical and psychosocial support to patients with dermatologic problems. [ABSTRACT FROM AUTHOR]

Skin is one of the outermost parts of the human body and is frequently exposed to various diseases. Healthcare professionals have endeavored to treat these conditions. However, the conventional methods often fall short in effectively distinguishing between diseases that visually present with similar characteristics and appearances. Therefore, Deep Learning was developed to facilitate image classification using the Convolutional Neural Network (CNN) model. Although CNN has achieved success in the form of high accuracy in image detection, research continues for the development of sustainable technology. Deep Learning has led to the discovery of the Vision Transformer (ViT) which is considered a popular new discovery model with intelligence that rivals CNN in object detection, offering greater accuracy and performance. This paper compares ResNet152 as one of the best models in CNN with ViT in classifying skin diseases. This comparison applies the HAM10000 dataset with a large number of images reaching 10,015 images divided for training, testing, and validation processes. In the process of applying the model to the selected dataset, ViT achieved 98.28% accuracy, while the classification accuracy of ResNet152 was 96.70%. Other metrics also proved ViT's superiority over ResNet152. However, ViT has major drawbacks in computation time and potential overfitting. [ABSTRACT FROM AUTHOR]

Background: There are limited data on the epidemiology and costs associated with managing dermatologic conditions in emergency departments (EDs). Objective: To assess the incidence and mean cost per case of skin diseases in EDs in Alberta. Methods: Alberta Health Services' Interactive Health Data Application was used to determine the epidemiology and costs associated with nonneoplastic dermatologic diseases in EDs in the province of Alberta, Canada, from 2018 to 2022. Skin conditions were identified using the International Classification of Disease 10th edition diagnostic groupings. Results: Skin disease represented 3.59% of all ED presentations in Alberta in 2022. The total costs associated with managing dermatologic conditions have remained stable over time at approximately 15 million Canadian Dollars (CAD) annually, but the mean cost per case has risen from 188.88 (SD 15.42) in 2018 to 246.25 CAD (SD 27.47) in 2022 (7.59%/year). Infections of skin and subcutaneous tissue were the most expensive diagnostic grouping. The most common dermatologic diagnostic groupings presenting to the ED were infections of skin and subcutaneous tissue [mean age-standardized incidence rate (ASIR) of 143.67 per 100,000 standard population (SD 241.99)], urticaria and erythema [mean ASIR 33.57 per 100,000 standard population (SD 59.13)], and dermatitis and eczema [mean ASIR 18.59 per 100,000 standard population (SD 23.65)]. Cellulitis was both the most common and the costliest individual diagnosis. The majority of patients were triaged as less urgent or nonurgent. Conclusions: Skin disease represents a substantial public health burden in EDs. Further research into drivers of cost change and areas for cost savings is essential. [ABSTRACT FROM AUTHOR]

Background: Ichthyosis is a diverse skin disease characterized by dry skin and itching, particularly affecting the hands. Most forms of this condition are hereditary. Objectives: In this study, we investigated potential new mutations associated with this disease using the new technique of whole-exome sequencing. Methods: In this study, after collecting the patient's blood sample in an EDTA tube and extracting DNA using the salting-out method, next-generation sequencing was performed using the WES method. Following the analysis of the results and identification of the candidate gene, PCR technique and Chromas software were used to confirm the findings. Results: The results indicated the presence of a new variant, NM_001099287: Exon 6:c.C1083A: p.Y361X, in the NIPAL4 gene in a heterozygous form in the parents and a homozygous form in the patient. This variant occurred as a nucleotide substitution in the exon 6 region of the NIPAL4 mRNA sequence. Conclusions: Using the WES technique, it is possible to investigate the presence of new variants related to ichthyosis in a short time and at a low cost. [ABSTRACT FROM AUTHOR]

Skin diseases are among the leading causes of disability worldwide and are a significant cause of morbidity in sub‐Saharan Africa. It can be cured if identified early. Only an expert dermatologist can classify skin disease by examining clinical signs. Sometimes, it can happen that dermatologists do not correctly classify the Skin disease, and therefore prescribe inappropriate drugs to the patient. Various research has been done to automate skin disease classification. Almost all the studies were concentrated on classifying three to four types of skin diseases. Developing a model that can be used in real‐world practical AI applications is important. In this study, we present an ensemble model based on the hard‐voting scheme of three deep CNN architectures: SKDCNET, FVGG16, and InceptionV3 for automatic classification of the top eight skin diseases. The proposed model utilizes three architectural diversities: training from scratch, fine‐tuning, and transfer learning. We used median filter noise removal and data augmentation technique to increase the number of training datasets. The proposed ensemble model produces 98% of accuracy. As an outcome of this study, the proposed model has the potential to be used as a decision support method for dermatologists. It can also contribute to the early identification (treatment) of skin diseases to reduce their further spread. [ABSTRACT FROM AUTHOR]

Background: When immunofluorescence on the frozen section is insufficient or unavailable, salvage immunofluorescence techniques can be used on formalin‑fixed, paraffin‑embedded tissue. The goal of the current investigation was to evaluate the diagnostic value of paraffin immunofluorescence following proteinase K digestion on skin biopsy samples in comparison to fresh frozen immunofluorescence. Materials and Methods: It was standardized and compared to the immunofluorescence on fresh frozen tissue (IF‑Frozen) for paraffin immunofluorescence by proteinase K digestion of formalin-fixed paraffin‑embedded skin biopsies (IF‑FFPE). The study included 50 native skin biopsy cases, and fluorescein isothiocyanate‑labeled IgA, IgG, IgM, and C3 intensity levels were evaluated in each case. Results: A total of 50 cases of native skin biopsy were included in the study, and their intensities for IgA, IgG, IgM, and C3 antibodies were compared. The average staining intensities in each disease group for the antibodies had equal intensity or had a minor difference (1+)/significant difference (2+). Paraffin immunofluorescence, proteinase K digestion had the best correlation, that is, had either equal or minor difference (1+) with fresh frozen immunofluorescence. The difference of 2+ intensity of antibodies between IF‑FFPE and IF‑Frozen was noted mainly in C3 antibody on paraneoplastic pemphigus. IF‑FFPE showed a sensitivity of 100%, 97.6%, 100%, and 81.6% for IgA, IgG, IgM, and C3, respectively, whereas the specificity was 100% for IgA, IgG, IgM, and C3. Limitations: Small sample size and and the employment of one method of antigen retrieval in IF‑FFPE. Conclusion: Immunofluorescence techniques done on formalin‑fixed paraffin‑embedded tissue can serve as salvage techniques in cases where immunofluorescence on the frozen section may not be adequate or may not be available. [ABSTRACT FROM AUTHOR]

Microemulsions (MEs) and nanoemulsions (NEs) are dispersions of two immiscible liquids which are usually transparent/translucent. Several reports are available on uses of MEs/NEs to increase efficacy of the loaded active ingredient(s) in topical dosage forms. This review aims to describe brief applications of MEs/NEs in common skin diseases as well as skincare products. Advantages of MEs/NEs in comparison with the traditional bulk form, including their improved efficacy and safety, have been discussed to highlight the importance of use of such delivery systems. The review briefs mechanism of action of MEs/NEs in enhancing delivery of the cargo. Furthermore, applications of MEs/NEs in common skin diseases including infectious rashes, pigmentation disorders (hyperpigmentaion and hypopigmentation), wound healing, skin cancers and scaling patches and plaques/papulosquamous disorders (psoriasis, atopic dermatitis and acne) have been discussed. MEs/NEs in skin care products have also been reviewed here. [ABSTRACT FROM AUTHOR]

Background: Acne vulgaris (AV) is a common skin disorder that affects up 10% of the worldwide population. Its pathogenesis involves a complex interplay of factors, leading to the development of cutaneous lesions (papules, pustules, and comedones). This clinical trial aimed to evaluate the efficacy of a specific probiotic formulation composed by Lactiplantibacillus plantarum PBS067, Lacticaseibacillus rhamnosus LRH020, and Limosilactobacillus reuteri PBS072 in improving AV symptoms in adult subject from the APAC region. Materials and methods: A double-blind randomized placebo-controlled clinical study was carried out on 64 women supplemented for 56 days plus a follow-up period. Instrumental evaluations of different skin parameters and clinical assessments of lesions were performed at 28 and 56 days after supplementation (T28 and T56, respectively) and during follow-up (T70). Results: A significant increase in skin hydration was achieved by probiotic group compared to the placebo (p < 0.05). An improved trend in sebum content and pH resulted in a statistically significant difference with respect to placebo (p < 0.05 for the former parameter at T28 and T70; p < 0.05 for the latter at T70). A progressive decrement of lesions was demonstrated at each endpoint considered by probiotic supplementation, reaching significant values for non-inflammatory ones at T56 and T70 (p < 0.05 and p < s0.01, respectively). Conclusions: This specific probiotic formulation may help improving acne symptoms, offering a possible adjuvant therapy to the conventional one and thus overall ameliorating the patient’s quality of life. [ABSTRACT FROM AUTHOR]

Lichen planus (LP) is a chronic skin, mucous membrane, and nail disease. Lichen planus is a rare skin condition occurring in less than 1% of the general population, affecting both children and adults. Oral lichen planus (OLP) involvement is much more common. It is an autoimmune disease caused by T lymphocytes, with epigenetic factors playing a significant role in the development of autoimmune skin diseases. MicroRNAs (miRNAs), a group of non-coding RNAs, play a substantial role in regulating the immune response.1 The etiology of lichen planus in not fully understood. It can be triggered by antihypertensive drugs, betablockers, infections, viral hepatitis, psychological stress, and others. Cases of lichen planus appearing after recovering from COVID-19 have been reported, as well as a significant increase in cases after COVID-19 vaccination.2-5 Diagnosis is based on clinical presenstation and characteristic histopathological findings. The disease is often self-limiting, accompanied by persistent itching and painful erosions of the mucous membrane, affecting the patient's quality of life and mental well-being. First-line treatments inculde topical corticosteroids and/or oral corticosteroids. There are reports of new potential treatments, such as biologic drugs (anti-IL12/13, anti-IL17) and Janus kinase inhibitors. Consequently, a dramatic change in lichen planus treatment can be expected in the near future. The majority of patients suffering from lichen planus develop metabolic syndrome which is the cause of other diseases. This article provides a comprehensive overview of current knowledge about lichen planus and its variants. [ABSTRACT FROM AUTHOR]

Melanoma is rare and can shorten a patient's life. It can be cured if found early. Early cost, pain and timing prediction affect patients. Thus, many researchers use Artificial Intelligence (AI) to identify Melanoma skin cancer. However, complicated skin lesions, illumination, and a lot of training data make diagonalising Melanoma skin cancer diagnosis tough. The Spiking Herd Search Learning (SHSL) approach for optimal feature selection-based classification promotes the category to overcome this issue. The method combines a unique hybrid metaheuristic algorithm, Horse herd Optimisation Algorithm (HOA), and Squirrel Search Optimisation (SSO) with deep hybrid learning as Spiking Neural Network (SNN) and Convolutional Neural Network (CNN) classifiers. In preprocessing, a Gaussian filter removes skin lesion noise using Image Processing techniques. The k-means clustering method performs the segmentation and excellent feature extraction techniques locate the lesion exactly. The Horse herd Optimisation Algorithm (HOA) and Squirrel Search Optimisation (SSO) algorithms and techniques are used toimprove Spike Neural Network classification (SNN) accurate features. Finally, using the DermIS Image dataset, the SHSL algorithm is evaluated and compared to other methods. The proposed method detects Melanoma Skin Disease with 98.91% accuracy. [ABSTRACT FROM AUTHOR]

Background: In recent years, computer-aided diagnosis for skin conditions has made significant strides, primarily driven by artificial intelligence (AI) solutions. However, despite this progress, the efficiency of AI-enabled systems remains hindered by the scarcity of high-quality and large-scale datasets, primarily due to privacy concerns. Methods: This research circumvents privacy issues associated with real-world acne datasets by creating a synthetic dataset of human faces with varying acne severity levels (mild, moderate, and severe) using Generative Adversarial Networks (GANs). Further, three object detection models—YOLOv5, YOLOv8, and Detectron2—are used to evaluate the efficacy of the augmented dataset for detecting acne. Results: Integrating StyleGAN with these models, the results demonstrate the mean average precision (mAP) scores: YOLOv5: 73.5%, YOLOv8: 73.6%, and Detectron2: 37.7%. These scores surpass the mAP achieved without GANs. Conclusions: This study underscores the effectiveness of GANs in generating synthetic facial acne images and emphasizes the importance of utilizing GANs and convolutional neural network (CNN) models for accurate acne detection. [ABSTRACT FROM AUTHOR]

Proliferative, lymphocytic, infundibular mural folliculitis and dermatitis have been reported in six female Labrador retrievers from North America. This is the first report of the disease outside North America, describing the clinical and histopathological diagnosis and dermoscopic aspect of the verrucous plaques, treatment and co‐morbidities in a female Labrador retriever dog. [ABSTRACT FROM AUTHOR]

The prevalence of skin illnesses is higher than that of other diseases. Fungal infection, bacteria, allergies, viruses, genetic factors, and environmental factors are among important causative factors that have continuously escalated the degree and incidence of skin diseases. Medical technology based on lasers and photonics has made it possible to identify skin illnesses considerably more rapidly and correctly. However, the cost of such a diagnosis is currently limited and prohibitively high and restricted to developed areas. The present paper develops a holistic, critical, and important skin disease prediction system that utilizes machine learning and deep learning algorithms to accurately identify up to 20 different skin diseases with a high F1 score and efficiency. Deep learning algorithms like Xception, Inception-v3, Resnet50, DenseNet121, and Inception-ResNet-v2 were employed to accurately classify diseases based on the images. The training and testing have been performed on an enlarged dataset, and classification was performed for 20 diseases. The algorithm developed was free from any inherent bias and treated all classes equally. The present model, which was trained using the Xception algorithm, is highly efficient and accurate for 20 different skin conditions, with a dataset of over 10,000 photos. The developed system was able to classify 20 different dermatological diseases with high accuracy and precision. [ABSTRACT FROM AUTHOR]

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