Introduction: Chronic ulcers significantly burden healthcare systems, requiring precise measurement and assessment for effective treatment. Traditional methods, such as manual segmentation, are time-consuming and error-prone. This review evaluates the potential of artificial intelligence AI-powered mobile apps for automated ulcer segmentation and their application in clinical settings. Methods: A comprehensive literature search was conducted across PubMed, CINAHL, Cochrane, and Google Scholar databases. The review focused on mobile apps that use fully automatic AI algorithms for wound segmentation. Apps requiring additional hardware or needing more technical documentation were excluded. Vital technological features, clinical validation, and usability were analysed. Results: Ten mobile apps were identified, showing varying levels of segmentation accuracy and clinical validation. However, many apps did not publish sufficient information on the segmentation methods or algorithms used, and most lacked details on the databases employed for training their AI models. Additionally, several apps were unavailable in public repositories, limiting their accessibility and independent evaluation. These factors challenge their integration into clinical practice despite promising preliminary results. Discussion: AI-powered mobile apps offer significant potential for improving wound care by enhancing diagnostic accuracy and reducing the burden on healthcare professionals. Nonetheless, the lack of transparency regarding segmentation techniques, unpublished databases, and the limited availability of many apps in public repositories remain substantial barriers to widespread clinical adoption. Conclusions: AI-driven mobile apps for ulcer segmentation could revolutionise chronic wound management. However, overcoming limitations related to transparency, data availability, and accessibility is essential for their successful integration into healthcare systems.

Background: Acral amelanotic melanomas (AAMs), a rare subset of melanomas located on acral sites such as the palms, soles, and subungual areas, are diagnostically challenging due to their lack of typical pigmentation and often benign clinical appearance. Misdiagnosis is common, leading to delays in treatment and potentially worse outcomes. This systematic review aims to synthesise evidence on cases of AAM initially misdiagnosed as other conditions, to better understand their clinical and epidemiological characteristics, diagnostic pitfalls, and management strategies. Methods: A comprehensive search of the MEDLINE/PubMed, EMBASE, and SCOPUS databases was conducted up to March 2024. Case reports and small case series of AAMs initially misdiagnosed as other conditions were included. Data on patient demographics, clinical presentation, and diagnostic methods were collected and analyzed. Results: Of the 152 records identified, 26 cases from 23 articles met the inclusion criteria. A demographic analysis revealed that the gender distribution appears to be perfectly balanced, with an age range of 38 to 91 years. Misdiagnoses included non-healing ulcers or traumatic lesions (37.5%), benign proliferative lesions (29.2%) and infectious lesions (20.8%). The foot was the most affected site (53.8%). Notably, a histological evaluation was performed in 50% of cases involving the upper extremities, in contrast to only 7.1% of cases involving the foot and 0% of cases of the heel. This discrepancy suggests a reluctance to perform biopsies in the lower extremities, which may contribute to a higher misdiagnosis rate in these areas. Conclusions: The underutilization of biopsy in the diagnosis of lower extremity lesions contributes significantly to the misdiagnosis and delay in treatment of AAMs. Especially when the clinical assessment and dermoscopy are inconclusive, biopsies of suspicious lesions are essential. Immunohistochemistry and markers such as PRAME are critical in differentiating melanoma from other malignancies such as clear cell sarcoma. This review highlights the need for increased vigilance and a proactive diagnostic approach to increase early detection rates and improve prognostic outcomes.

In the present study, Monarda didyma L. essential oil (isolated from the flowering aerial parts of the plant) was examined to characterize its chemotype and to evaluate, in addition to the quali-quantitative chemical analysis, the associated antioxidant and anti-inflammatory activities. The plants were grown in central Italy, Urbino (PU), Marche region. Different analyses (TLC, GC-FID, GC-MS and ¹H-NMR) allowed the identification of twenty compounds among which carvacrol, p-cymene and thymol were the most abundant. On this basis, the chemotype examined in the present study was indicated as Monarda didyma ct. carvacrol. The antioxidant effect was assessed by DPPH assay. Moreover, this chemotype was investigated for the anti-inflammatory effect in an in vitro setting (i.e., LPS-stimulated U937 cells). The decreased expression of pro-inflammatory cytokine IL-6 and the increased expression of miR-146a are suggestive of the involvement of the Toll-like receptor-4 signaling pathway. Although further studies are needed to better investigate the action mechanism/s underlying the results observed in the experimental setting, our findings show that M. didyma essential oil is rich in bioactive compounds (mainly aromatic monoterpenes and phenolic monoterpenes) which are most likely responsible for its beneficial effect.

Dermatofibrosarcoma protuberans (DFSP) is a rare, low-grade sarcoma that presents diagnostic challenges due to its resemblance to benign lesions