Abstract
Melanoma is considered the deadliest type of skin cancer and in the last decade, the incidence rate has increased substantially. However, automatic melanoma classification has been widely used to aid the detection of lesions as well as prevent eventual death. Therefore, in this paper we decided to investigate how an attention mechanism combined with a classical backbone network would affect the classification of melanomas. This mechanism is known as triplet attention, a lightweight method that allows to capture cross-domain interactions. This characteristic helps to acquire rich discriminative feature representations. The different experiments demonstrate the effectiveness of the model in five different datasets. The model was evaluated based on sensitivity, specificity, accuracy, and F1-Score. Even though it is a simple method, this attention mechanism shows that its application could be beneficial in classification tasks.

Abstract
Aim: Aloysia citrodora has a long history of traditional use in treating various ailments. This study evaluated the in vivo chemopreventive efficacy and systemic toxicity of an extract of A. citrodora in a transgenic mouse model of HPV16 (human papillomavirus type 16)-induced cancer. Methods: The experiment involved six groups (n = 5): group 1 (G1, wild-type (WT), water), group 2 (G2, HPV, water), group 3 (G3, WT, 0.013 g/mL), group 4 (G4, HPV, 0.006 g/mL), group 5 (G5, HPV, 0.008 g/mL), and group 6 (G6, HPV, 0.013 g/mL). Throughout the assay, humane endpoints, body weight, food, and water consumption were recorded weekly. The internal organs and skin of the mice were collected for analysis after they were sacrificed. Toxicological parameters that were studied included hematological and biochemical blood markers, splenic and hepatic histology, and hepatic oxidative stress. Results: A. citrodora extract seems to reduce the incidence of dysplastic and in situ carcinoma skin lesions induced by HPV16 in this model, suggesting that dietary supplementation with concentrations of 0.008 g/mL and 0.013 g/mL may have beneficial chemopreventive effects. Conclusions: The extract did not induce any concentration-dependent toxicological effects on any of the parameters included in the study, indicating a favorable toxicological profile under these experimental conditions. © 2024 Open Exploration Publishing Inc. All rights reserved.

Abstract
Background and Aim: Papillomaviruses (PVs) infections have been documented in numerous animal species across different regions worldwide. They often exert significant impacts on animal health and livestock production. Scientists have studied natural products for over half a century due to their diverse chemical composition, acknowledging their value in fighting cancer. Acorns (Quercus ilex) are believed to have several unexplored pharmacological properties. This study aimed to evaluate the in vivo safety and cancer chemopreventive activity of an infusion extract of Q. ilex in a transgenic mouse model of human PV (HPV)-16, which developed squamous cell carcinomas through a multistep process driven by HPV16 oncogenes. Materials and Methods: Q. ilex extract was prepared by heating in water at 90 degrees C and then characterized by mass spectrometry. Phenolic compounds from this extract were administered in drinking water to female mice in three different concentrations (0.03, 0.06, and 0.09 g/mL) over a period of 28 consecutive days. Six groups (n = 6) were formed for this study: group 1 (G1, wildtype [WT], water), group 2 (G2, HPV, water), group 3 (G3, WT, 0.09 g/mL), group 4 (G4, HPV, 0.03 g/mL), group 5 (G5, HPV, 0.06 g/ mL), and group 6 (G6, HPV, 0.09 g/mL). Throughout the experiment, humane endpoints, body weight, food intake, and water consumption were recorded weekly. Following the experimental period, all mice were sacrificed, and blood, internal organs, and skin samples were collected. Blood was used to measure glucose and microhematocrit and later biochemical parameters, such as creatinine, urea, albumin, alanine aminotransferase, and total proteins. Histological analysis was performed on skin and organ samples. Results: The administration of Q. ilex extract resulted in a statistically significant increase in relative organ weight among HPV transgenic animals, indicating adaptive biological response to the tested concentrations. Moreover, a reduction in characteristic skin lesions was observed in animals treated with the 0.06 and 0.09 g/mL extract. Conclusion: These results provide a favorable chemopreventive profile for Q. ilex extract at concentrations of 0.06 and 0.09 g/mL. This study highlights the potential of Q. ilex extract as a safe and effective therapeutic strategy against HPV16associated lesions in transgenic mouse models. The limitation of our study was the durability of transgenic animals. As a more sensitive species, we must always be careful with the durability of the test. We intend to study concentrations of 0.06 and 0.09 g/mL for longer to further investigate their possible effects.

Abstract
The Regulation (EU) 2019/6 establishes that the veterinary prescriptions should follow a cascade, according to their availability of the market. In sum, the veterinarian is authorized to use a medicine for human use only if there is no product available for the same or other therapeutic indication, in the same or another animal species. This study aims to analyse the application of Regulation (EU) 2019/6 in the pharmacological prescription at the Veterinary Hospital of the University of León. A total of 121 clinical cases, 89 dogs (73.55%) and 32 cats (26.45%) were included. Results revealed that 95 medicines were prescribed, 51 (53.68 %) as veterinary medicines and 44 (46.32 %) as human medicines. From the human medicines, 22 (50.00%) did not have a veterinary alternative in the market; four (9.00%) presented a veterinary medicine in the appropriate formulation for the species; 10 (23.00%) had no alternative in the desired formulation; and 8 (18.00%) had no alternatives for the target species. This study suggested that the cascade was not strictly followed, and several reasons may justify it, such as the lack of veterinary products, different formulations, and differences in costs. An effective, safe and sustainable use of the therapeutic option available can only be accomplished with a rational use of the prescription cascade and a correct use of the Regulation (EU) 2019/6. © 2024 State University of Santa Catarina. All rights reserved.

Abstract
Riding a motorcycle involves risks that can be minimized through advanced sensing and response systems to assist the rider. The use of camera-collected images to monitor road conditions can aid in the development of tools designed to enhance rider safety and prevent accidents. This paper proposes a method for developing deep learning models designed to operate efficiently on embedded systems like the Raspberry Pi, facilitating real-time decisions that consider the road condition. Our research tests and compares several state-of-the-art convolutional neural network architectures, including EfficientNet and Inception, to determine which offers the best balance between inference time and accuracy. Specifically, we measured top-1 accuracy and inference time on a Raspberry Pi, identifying EfficientNetV2 as the most suitable model due to its optimal trade-off between performance and computational demand. The model's top-1 accuracy significantly outperformed other models while maintaining competitive inference speeds, making it ideal for real-time applications in traffic-dense urban settings.

Abstract
In the modern world, making healthy food choices is increasingly important due to the rise in food-related illnesses. Existing tools, such as Nutri-Score and comprehensive food labels, often pose challenges for many consumers. This paper proposes an application that uses Optical Character Recognition (OCR) technologies to read and interpret food labels, thus upgrading current solutions that rely mainly on reading product barcodes. By using advanced optical character recognition and machine learning techniques, the system aims to accurately extract and analyze nutritional information directly from food packaging without relying on a database of pre-registered products. This innovative approach not only increases consumer awareness, but also supports personalized diet management for diseases such as diabetes and hypertension, while promoting healthier eating habits and better health outcomes. Two minimalist functional prototypes were developed as a result of this work: a desktop application and a mobile application.