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Several factors contribute to the increase in irrigation demand: population growth, demand for higher value-added products, and the impacts of climate change, among others. High-quality water is essential for irrigation, so knowledge of water quality is critical. Additionally, water use in agriculture has been increasing in the last decades. Lack of water quality can cause drip clog, a lack of application uniformity, cross-contamination, and direct and indirect impacts on plants and soil. Currently, there is a need for more automated methods for evaluating and monitoring water quality for irrigation purposes, considering different aspects, from impacts on soil to impacts on irrigation systems. This work proposes a data-driven method to address this gap and implemented it in a case study in the PCJ river basin in Brazil. The methodology contains nine components and considers the main steps of the data lifecycle and the traditional machine learning workflow, allowing for automated knowledge extraction and providing important information for improving decision making. The case study illustrates the use of the methodology, highlighting its main advantages and challenges. Clustering different scenarios in three hydrological years (high, average, and lower streamflows) and considering different inputs (soil-related metrics, irrigation system-related metrics, and all metrics) helped generate new insights into the area that would not be easily obtained using traditional methods. [ABSTRACT FROM AUTHOR]

This paper presents the Simulation Management System for Operational Coastal Hydrodynamic Models, or SMS-Coastal, and its novel methodology designed to automate forecast simulations of coastal models. Its working principle features a generic framework that can be easily configured for other applications, and it was implemented with the Python programming language. The system consists of three main components: the Forcing Processor, Simulation Manager, and Data Converter, which perform operations such as the management of forecast runs and the download and conversion of external forcing data. The SMS-Coastal was tested on two model realisations using the MOHID System: SOMA, a model of the Algarve coast in Portugal, and BASIC, a model of the Cartagena Bay in Colombia. The tool proved to be generic enough to handle the different aspects of the models, being able to manage both forecast cycles. [ABSTRACT FROM AUTHOR]

Plastic pollution has been observed in many marine environments surrounding the Iberian Peninsula, from the surface water to deeper waters, yet studies on their pathways and accumulation areas are still limited. In this study, a global ocean reanalysis model was combined with a particle-tracking Lagrangian model to provide insights into the pathways and accumulation patterns of microplastics originating in southern Portuguese coastal waters (SW Iberian). The study investigates microplastics floating on the surface as well as submerged at different water depths. Model results suggest that the North Atlantic Gyre is the main pathway for microplastics in surface and subsurface waters, transporting the microplastics southwards and eastwards towards the Mediterranean Sea and the Canary Islands. Currents flowing out of the Mediterranean Sea act as the main pathway for microplastics in deep waters, transporting the microplastics along western Iberia. An average residence time of twenty days in the coastal waters suggests that microplastics do not accumulate close to their sources due to their relatively fast transport to adjacent ocean areas. Notably, a significant proportion of microplastics leave the model domain at all depths, implying that SW Iberia may act as a source of microplastics for the adjacent areas, including the Mediterranean Sea, Morocco, the Canary Islands, Western Iberia, and the Bay of Biscay. [ABSTRACT FROM AUTHOR]

Non-alcoholic fatty liver disease (NAFLD) is associated with several other metabolic disorders, which are typically pro-inflammatory states. Body fat content is an important marker of metabolic health and abdominal fat is associated with harmful cardiometabolic outcomes. We aimed to evaluate the association between the risk of NAFLD (through Fatty Liver Index (FLI), and BMI, AST/ALT ratio, and presence of diabetes (BARD)), and anthropometric parameters, predictors of metabolic status, in patients with morbid obesity, and to evaluate the association of FLI and BARD scores with pro-inflammatory markers. We have retrospectively studied patients with morbid obesity followed in our center. In total, 2184 participants were included, with an average age of 42.8 ± 10.6 years, 84.5% being females. We report a positive association of FLI with waist circumference (β = 0.10 [0.09 to 0.11], p < 0.01) and waist-to-hip ratio (β = 8.68 [6.85 to 10.52, p < 0.01]), even after adjusting for age, sex, body mass index, diabetes, and dyslipidemia (p < 0.01 for both adjusted models). The associations of BARD with anthropometric measures were significant only in the non-adjusted model. There was a positive association between both FLI and BARD and C-reactive protein. Our results point towards a positive association between waist-to-hip ratio and the risk of hepatic steatosis, and between pro-inflammatory markers and both hepatic steatosis and fibrosis. [ABSTRACT FROM AUTHOR]

Diabetic retinopathy causes vascular damage to retinal neurons, presenting characteristics of chronic inflammation. The development of new therapies capable of combating vision loss involves knowledge of inflammatory retinal changes. Studies in animal models and patients with diabetes have shown a high expression of the inflammatory molecules that are involved in the progression of diabetic retinopathy. Uveal melanoma is an eye tumour that remains highly deadly, because despite the correct treatment, it still causes metastasis in about 50% of patients. This type of tumour has the ability to produce and store melanin, which may result in resistance to therapy. Over time there has been development of new therapies for this disease, such as radiotherapy and surgical resection. In this review, we discuss diabetic retinopathy and ocular melanoma, their relationship with angiogenesis and the current anti-angiogenic therapies for their treatment. [ABSTRACT FROM AUTHOR]

Proteomics is a powerful approach to study the molecular mechanisms of cancer. In this study, we aim to characterize the proteomic profile of gastric cancer (GC) in patients with diabetes mellitus (DM) type 2. Forty GC tissue samples including 19 cases from diabetic patients and 21 cases from individuals without diabetes (control group) were selected for the proteomics analysis. Gastric tissues were processed following the single-pot, solid-phase-enhanced sample preparation approach—SP3 and enzymatic digestion with trypsin. The resulting peptides were analyzed by LC-MS Liquid Chromatography—Mass Spectrometry (LC-MS). The comparison of protein expression levels between GC samples from diabetic and non-diabetic patients was performed by label-free quantification (LFQ). A total of 6599 protein groups were identified in the 40 samples. Thirty-seven proteins were differentially expressed among the two groups, with 16 upregulated and 21 downregulated in the diabetic cohort. Statistical overrepresentation tests were considered for different annotation sets including the Gene Ontology(GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Disease functional databases. Upregulated proteins in the GC samples from diabetic patients were particularly enriched in respiratory electron transport and alcohol metabolic biological processes, while downregulated proteins were associated with epithelial cancers, intestinal diseases, and cell–cell junction cellular components. Taken together, these results support the data already obtained by previous studies that associate diabetes with metabolic disorders and diabetes-associated diseases, such as Alzheimer's and Parkinson's, and also provide valuable insights into seven GC-associated protein targets, claudin-3, polymeric immunoglobulin receptor protein, cadherin-17, villin-1, transglutaminase-2, desmoglein-2, and mucin-13, which warrant further investigation. [ABSTRACT FROM AUTHOR]

Today, elasmobranchs are one the most threatened vertebrate groups worldwide. In fact, at least 90% of elasmobranch species are listed in the International Union for Conservation of Nature (IUCN) Red List, while more than 40% are data-deficient. Although these vertebrates are mainly affected by unsustainable fishery activities, bycatch is also one of the major threats to sharks and batoids worldwide, and represents a challenge for both sustainable fishery management and for biodiversity and conservational efforts. Thus, in this study, DNA barcode methodology was used to identify the bycatch composition of batoid species from small-scale industrial fisheries in the southwest Atlantic and artisanal fisheries from southeast Brazil. A total of 228 individuals belonging to four Chondrichthyes orders, seven families, and at least 17 distinct batoid species were sequenced; among these individuals, 131 belonged to species protected in Brazil, 101 to globally threatened species, and some to species with trade restrictions provided by Appendix II of the Convention on International Trade in Endangered Species (CITES). These results highlight the impacts on marine biodiversity of bycatch by small-scale industrial and unmanaged artisanal fisheries from the southwest Atlantic, and support the implementation of DNA-based methodologies for species-specific identification in data-poor fisheries as a powerful tool for improving the quality of fisheries' catch statistics and for keeping precise bycatch records. [ABSTRACT FROM AUTHOR]