Atopic dermatitis (AD) is a common inflammatory skin disease with a complex pathophysiology, intertwining immune dysregulation, epidermal barrier dysfunction, IgE sensitization, environmental factors and genetic predisposition. It has been recently identified that interleukins -4 and -13 play crucial roles in the type-2-driven inflammation that characterizes AD, contributing to its symptomatology. Novel therapeutic approaches that target Th2 cytokines and their respective pathways have been developed, aiming to optimize the treatment of AD.

The emergence of systemic therapies and photoprotection against non-melanoma skin cancer (NMSC) raises questions on the broader systematic impact of the disease. Personalized medicine involves a holistic patient approach, through which the evaluation of systemic biomarkers can reveal the interconnected aspects of patient health and tailored therapies. Cumulative UV exposure disrupts redox equilibrium and triggers inflammation and cutaneous immunosuppression, processes that contribute independently or via their interplay to cutaneous carcinogenesis. This systemic impact can be further reinforced by biomolecules derived from the NMSC microenvironment, fueling a continuous cycle of oxidative stress and inflammation in the organism. Regarding investigation of the systemic burden of NMSC, we conducted a narrative review focusing on parameters related to redox status, inflammation, and immune suppression observed in the blood components (serum, plasma, and erythrocytes) of NMSC patients. Our findings revealed an association of NMSC patients with perturbations of redox homeostasis, as evidenced by the decreased antioxidant activity, lower levels of non-enzymatic antioxidants, and increased byproducts of lipid, protein, and DNA oxidative damage. Additionally, NMSC patients presented augmented levels of pro-inflammatory interleukins, reduced anti-tumor biomolecule levels, and enhanced immune response markers, as well as elevated vitamin D levels. These systemic changes may lead to the association of NMSC with a higher risk of secondary malignancies in other organs. Overall, the findings of the present study suggest that NMSC affects systemic health beyond the skin, underscoring the need for a comprehensive and individualized approach to the management and monitoring of the patient.

A comparison of dermatological cases generated by artificial intelligence (AI) versus those created without AI by medical students revealed that AI-created cases were characterized by detailed case descriptions, analysis of medical history, and clinical examinations, but lacked the depth, clinical relevance, and motivational elements found in non-AI cases, which were shorter, presented clinical dilemmas, and included challenging scenarios that students found more educational and engaging.

Dermoscopic features of actinic keratosis (AK) have been widely studied, but there is still little evidence for their diagnostic accuracy. Our study investigates whether established dermoscopic criteria are reliable predictors in differentiating non-pigmented actinic keratosis (NPAK) from pigmented actinic keratosis (PAK). For this purpose, dermoscopic images of 83 clinically diagnosed AK (45 NPAK, 38PAK) were examined, and the sensitivity (Se), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV) were assessed. Features with statistical significance were the red pseudo-network (p = 0.02) for NPAK and the pigmented pseudo-network (p < 0.001) with a pigment intensity value even less than 10% for PAK (p = 0.001). Pigmented pseudo-network (Se: 89%, Sp: 77%, PPV: 77%, NPV: 89%) with a pigment intensity value of more than 10% (Se: 90%, Sp: 86%, PPV: 79%, NPV: 93%) had excellent diagnostic accuracy for PAK. Scale and widened follicular openings with yellowish dots surrounded by white circles were equally represented in both variants of AK. Linear wavy vessels and shiny streaks were more prominently observed in NPAK, as were rosettes in PAK, but these results failed to meet statistical significance. The red starburst pattern was near statistical significance for PAK. Therefore, pigmentation is the strongest dermoscopic predictor for the differentiation between NPAK and PAK.

Background/Objectives: Alopecia is a common and distressing hair loss condition that poses a major diagnostic challenge. While histopathology is the gold standard, its invasive nature limits its routine use. Trichoscopy, a non-invasive imaging technique, has shown promises in diagnosing and differentiating the various alopecia subtypes. However, existing diagnostic algorithms primarily rely on dermoscopic findings. To address this, we developed a novel, three-step algorithm that integrates clinical and trichoscopic features and employs pattern analysis as a diagnostic tool. Methods: A comprehensive literature review was conducted to identify key trichoscopic features associated with different alopecia types. The gathered data were used as a base for the description of trichoscopic features and patterns for each subtype of alopecia, either scarring or non-scarring. Results: The proposed algorithm is analyzed into three steps. In the first step, alopecia is categorized by distribution into: patchy, patterned, or diffuse. In the second step, it distinguishes between scarring and non-scarring alopecia based on the absence or presence of follicular ostia, respectively. Lastly, in the third step, alopecias are distinguished based on specific trichoscopic clues, allowing for the identification of distinct trichoscopic patterns. Conclusions: The three-step diagnostic algorithm for alopecia, utilizing clinical and dermoscopic findings, performs a pattern analysis in trichoscopy, leading to a dermoscopic diagnosis with great confidence, and minimizing the need for invasive diagnostic procedures.

Introduction: Basal cell carcinoma (BCC) quite frequently presents as multiple tumors in individual patients. Neoplasm’s risk factors for local recurrence have a critical impact on therapeutic management. Objective: To detect risk factors for multiple BCCs (mBCC) in individual patients and to describe clinical and dermatoscopic features of low- and high-risk tumors. Materials & Methods: Our study included 225 patients with 304 surgically excised primary BCCs. All patients’ medical history and demographics were recorded. Clinical and dermatoscopic images of BCCs were evaluated for predefined criteria and statistical analyses were performed. Results: Grade II-III sunburns before adulthood (OR 2.146, p = 0.031) and a personal history of BCC (OR 3.403, p < 0.001) were the major predisposing factors for mBCC. Clinically obvious white color (OR 3.168, p < 0.001) and dermatoscopic detection of white shiny lines (OR 2.085, p = 0.025) represented strongly prognostic variables of high-risk BCC. Similarly, extensive clinico-dermatoscopic ulceration (up to 9.2-fold) and nodular morphology (3.6-fold) raise the possibility for high-risk BCC. On the contrary, dermatoscopic evidence of blue-black coloration had a negative prognostic value for high-risk neoplasms (light OR 0.269, p < 0.001/partial OR 0.198, p = 0.001). Conclusions: Profiling of mBCC patients and a thorough knowledge of high-risk tumors’ clinico-dermatoscopic morphology could provide physicians with important information towards prevention of this neoplasm.