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Automating pruning tasks entails overcoming several challenges, encompassing not only robotic manipulation but also environment perception and detection. To achieve efficient pruning, robotic systems must accurately identify the correct cutting points. A possible method to define these points is to choose the cutting location based on the number of nodes present on the targeted cane. For this purpose, in grapevine pruning, it is required to correctly identify the nodes present on the primary canes of the grapevines. In this paper, a novel method of node detection in grapevines is proposed with four distinct state-of-the-art versions of the YOLO detection model: YOLOv7, YOLOv8, YOLOv9 and YOLOv10. These models were trained on a public dataset with images containing artificial backgrounds and afterwards validated on different cultivars of grapevines from two distinct Portuguese viticulture regions with cluttered backgrounds. This allowed us to evaluate the robustness of the algorithms on the detection of nodes in diverse environments, compare the performance of the YOLO models used, as well as create a publicly available dataset of grapevines obtained in Portuguese vineyards for node detection. Overall, all used models were capable of achieving correct node detection in images of grapevines from the three distinct datasets. Considering the trade-off between accuracy and inference speed, the YOLOv7 model demonstrated to be the most robust in detecting nodes in 2D images of grapevines, achieving F1-Score values between 70% and 86.5% with inference times of around 89 ms for an input size of 1280 × 1280 px. Considering these results, this work contributes with an efficient approach for real-time node detection for further implementation on an autonomous robotic pruning system. [ABSTRACT FROM AUTHOR]

This study investigates how grapevines (Vitis vinifera L.) respond to shading induced by artificial nets, focusing on physiological and metabolic changes. Through a multidisciplinary approach, grapevines' adaptations to shading are presented via biochemical analyses and hyperspectral data that are then combined with systems biology techniques. In the study, conducted in a 'Moscatel Galego Branco' vineyard in Portugal's Douro Wine Region during post-veraison, shading was applied and predawn leaf water potential ( Ψ p d ) was then measured to assess water stress. Biochemical analyses and hyperspectral data were integrated to explore adaptations to shading, revealing higher chlorophyll levels (chlorophyll a-b 117.39% higher) and increased Reactive Oxygen Species (ROS) levels in unshaded vines (52.10% higher). Using a self-learning artificial intelligence algorithm (SL-AI), simulations highlighted ROS's role in stress response and accurately predicted chlorophyll a (R2: 0.92, MAPE: 24.39%), chlorophyll b (R2: 0.96, MAPE: 17.61%), and ROS levels (R2: 0.76, MAPE: 52.17%). In silico simulations employing flux balance analysis (FBA) elucidated distinct metabolic phenotypes between shaded and unshaded vines across cellular compartments. Integrating these findings provides a systems biology approach for understanding grapevine responses to environmental stressors. The leveraging of advanced omics technologies and precise metabolic models holds immense potential for untangling grapevine metabolism and optimizing viticultural practices for enhanced productivity and quality. [ABSTRACT FROM AUTHOR]

Chemotherapy-induced peripheral neuropathy (CIPN) is a side effect of cancer treatment, often linked with pain complaints. Patients report mechanical and thermal hypersensitivity that may emerge during chemotherapy treatment and may persist after cancer remission. Whereas the latter situation disturbs the quality of life, life itself may be endangered by the appearance of CIPN during cancer treatment. The causes of CIPN have almost entirely been ascribed to the neurotoxicity of chemotherapeutic drugs in the peripheral nervous system. However, the central consequences of peripheral neuropathy are starting to be unraveled, namely in the supraspinal pain modulatory system. Based on our interests and experience in the field, we undertook a review of the brain-centered alterations that may underpin pain in CIPN. The changes in the descending pain modulation in CIPN models along with the functional and connectivity abnormalities in the brain of CIPN patients are analyzed. A translational analysis of preclinical findings about descending pain regulation during CIPN is reviewed considering the main neurochemical systems (serotoninergic and noradrenergic) targeted in CIPN management in patients, namely by antidepressants. In conclusion, this review highlights the importance of studying supraspinal areas involved in descending pain modulation to understand the pathophysiology of CIPN, which will probably allow a more personalized and effective CIPN treatment in the future. [ABSTRACT FROM AUTHOR]

Magnesium oxide is typically white and can be colorized with transition metal insertion by doping. We present the preparation of a green-colored hydroxide by the exchange of Mg2+ on the crystalline lattice with Ni2+ in MgO, using three nickel salts. MgOst was prepared by the colloidal starch suspension method, using cassava starch. The oxides and hydroxides, before and after, were characterized by X-ray diffraction (XRD), and show that a phase change occurs: a transition from periclase (MgO) to brucite (Mg(OH)2) due to the incorporation of nickel ions from different salts (acetate, chloride, and nitrate), resulting in the solid solution [NixMg1−x(OH)2]. The FTIR spectrum corroborates the crystallographic structure identified through XRD patterns, confirming the formation of a crystal structure resembling brucite. The new samples present a green color, indicative of the incorporation of the Ni2+ ions. The antimicrobial activity of products resulting from the doping of magnesium oxide with nickel and the precursor MgOst was assessed through the minimum inhibitory concentration (MIC) test. The evaluation included three bacterial strains: Staphylococcus aureus (ATCC 25923), Escherichia coli (ATCC 25922), Salmonella gallinarum (ATCC 9184), and a yeast strain, Candida albicans (ATCC 10231). The obtained results were promising; the tested samples exhibited antimicrobial activity, with a MIC ranging from 0.312 to 0.625 μg.μL−1. The nickel compound, derived from the precursor chloride salt, demonstrated superior MIC activity. Notably, all tested samples displayed bactericidal activity against the S. aureus strain and exhibited a broad spectrum of inhibition, encompassing both Gram-positive and Gram-negative strains. Only the nickel compounds derived from precursors with acetate and nitrate anions demonstrated antimicrobial activity against C. albicans, exhibiting a fungistatic behavior. Based on the conducted studies, [NixMg1−x(OH)2] has emerged as a promising antimicrobial agent, suitable for applications requiring the delay or inhibition of bacterial growth. [ABSTRACT FROM AUTHOR]

Phytochemical studies have shown extracts obtained from the aerial parts of Baccharis trimera (Less.) DC has antioxidant and antimicrobial activities and the potential to treat some diseases. This study investigated the phenolic compounds, antioxidant and antimicrobial activity, and phytochemical potential of B. trimera leaf extract obtained by decoction on ATCC standard bacterial strains and 23 swine clinical isolates. Water was used as an extraction solvent based on the principles of green chemistry and at a low cost. The decoction process resulted in an extract rich in phenolic compounds and a high capacity for scavenging DPPH and ABTS radicals. Phytochemical analysis of aqueous extracts was performed using HPLC-DAD, and high concentrations of chlorogenic, ferulic, caffeic, and cinnamic phenolic acids were found. Antimicrobial activity was observed against gram-negative bacteria. B. trimera aqueous extract may be a promising low-cost agent for prophylactic treatment against swine enteropathogens and contribute to reducing production costs. [ABSTRACT FROM AUTHOR]