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Background Tralokinumab was recently approved for the treatment of moderate-to-severe atopic dermatitis (AD) and is the first selective interleukin (IL)-13 inhibitor that specifically neutralizes IL-13 with high affinity. Objectives To determine the real-life short-term effectiveness and safety of tralokinumab treatment in patients with moderate-to-severe AD. Methods A multicentre retrospective study was conducted including adult patients with moderate-to-severe AD who started tralokinumab treatment from 1 April to 30 June 2022 in 16 Spanish hospitals. Demographic and disease characteristics, severity and quality of life scales were collected at the baseline visit and at weeks 4 and 16. Results Eighty-five patients were included. Twenty-seven patients (32%) were non-naive to advanced therapy (biological or Janus kinase inhibitors inhibitors). All included patients had severe disease with baseline Eczema Area and Severity Index (EASI) scores of 25.4 (SD 8.1), Dermatology Life Quality Index (DLQI) 15.8 (5.4) and peak pruritus numerical rating scale (PP-NRS) 8.1 (1.8) and 65% had an Investigator's Global Assessment (IGA) of 4. At week 16, there was improvement on all scales. The mean EASI decreased to 7.5 (SD 6.9, 70% improvement), SCORing Atopic Dermatitis improved 64% and PP-NRS, 57%. Also, 82%, 58% and 21% of the patients achieved EASI 50, 75 and 90, respectively. The percentage of EASI 75 responders was significantly higher among the naive vs. non-naive groups (67% vs. 41%). The safety profile was acceptable. Conclusions Patients, with a long history of disease and prior multidrug failure, showed a good response to tralokinumab, confirming clinical trial results. [ABSTRACT FROM AUTHOR]

Background and Objective. Skin cancer is the most common cancer worldwide. One of the most common non-melanoma tumors is basal cell carcinoma (BCC), which accounts for 75% of all skin cancers. There are many benign lesions that can be confused with these types of cancers, leading to unnecessary biopsies. In this paper, a new method to identify the different BCC dermoscopic patterns present in a skin lesion is presented. In addition, this information is applied to classify skin lesions into BCC and non-BCC. Methods. The proposed method combines the information provided by the original dermoscopic image, introduced in a convolutional neural network (CNN), with deep and handcrafted features extracted from color and texture analysis of the image. This color analysis is performed by transforming the image into a uniform color space and into a color appearance model. To demonstrate the validity of the method, a comparison between the classification obtained employing exclusively a CNN with the original image as input and the classification with additional color and texture features is presented. Furthermore, an exhaustive comparison of classification employing different color and texture measures derived from different color spaces is presented. Results. Results show that the classifier with additional color and texture features outperforms a CNN whose input is only the original image. Another important achievement is that a new color cooccurrence matrix, proposed in this paper, improves the results obtained with other texture measures. Finally, sensitivity of 0.99, specificity of 0.94 and accuracy of 0.97 are achieved when lesions are classified into BCC or non-BCC. Conclusions. To the best of our knowledge, this is the first time that a methodology to detect all the possible patterns that can be present in a BCC lesion is proposed. This detection leads to a clinically explainable classification into BCC and non-BCC lesions. In this sense, the classification of the proposed tool is based on the detection of the dermoscopic features that dermatologists employ for their diagnosis. [ABSTRACT FROM AUTHOR]

Color has great diagnostic significance in dermatoscopy. Several diagnosis methods are based on the colors detected within a lesion. Malignant lesions frequently show more than three colors, whereas in benign lesions, three or fewer colors are usually observed. Black, red, white, and blue-gray are found more frequently in melanomas than in benign nevi. In this paper, a method to automatically identify the colors of a lesion is presented. A color label identification problem is proposed and solved by maximizing the posterior probability of a pixel to belong to a label, given its color value and the neighborhood color values. The main contribution of this paper is the estimation of the different terms involved in the computation of this probability. Two evaluations are performed on a database of 200 dermoscopic images. The first one evaluates if all the colors detected in a lesion are indeed present in it. The second analyzes if each pixel within a lesion is assigned the correct color label. The results show that the proposed method performs correctly and outperforms other methods, with an average F-measure of 0.89, an accuracy of 0.90, and a Spearman correlation of 0.831. [ABSTRACT FROM AUTHOR]

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Copyright of Revista Cuidarte is the property of Universidad de Santander and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Dysregulated energy metabolism is a major contributor to a multitude of pathologies, including obesity and diabetes. Understanding the regulation of metabolic homeostasis is of utmost importance for the identification of therapeutic targets for the treatment of metabolically driven diseases. We previously identified the deubiquitinase OTUB1 as substrate for the cellular oxygen sensor factor-inhibiting HIF (FIH) with regulatory effects on cellular energy metabolism, but the physiological relevance of OTUB1 is unclear. Here, we report that the induced global deletion of OTUB1 in adult mice (Otub1 iKO) elevated energy expenditure, reduced age-dependent body weight gain, facilitated blood glucose clearance and lowered basal plasma insulin levels. The respiratory exchange ratio was maintained, indicating an unaltered nutrient oxidation. In addition, Otub1 deletion in cells enhanced AKT activity, leading to a larger cell size, higher ATP levels and reduced AMPK phosphorylation. AKT is an integral part of insulin-mediated signaling and Otub1 iKO mice presented with increased AKT phosphorylation following acute insulin administration combined with insulin hypersensitivity. We conclude that OTUB1 is an important regulator of metabolic homeostasis. [ABSTRACT FROM AUTHOR]

Atopic dermatitis (AD) is the most frequent chronic inflammatory skin disease, and its incidence has been rapidly increasing in developed countries in the last years. AD presents a high degree of heterogeneity due to biases and confounding factors such as age range, sex, or ethnicity. For those reasons, the search for new biomarkers is crucial. At the same time, obesity, which is a global health problem, has also increased over the years. It has been associated with many pathophysiological states, including skin diseases such as AD, mostly in childhood. Obesity promotes a low grade inflammation driven by many different cytokines and adipokines, including leptin, which has a key role in many other diseases due to its pleiotropic effects. Leptin also has a role in both skin and allergic diseases very related to AD. Thus, this adipokine could have an important role in the pathogenesis of AD, especially in its chronicity. Despite the limited literature available, there is some evidence that leads us to consider leptin as an important adipokine in this skin disease. For this reason, here we have reviewed the role of leptin in the pathophysiology of AD. [ABSTRACT FROM AUTHOR]