Metodología para la creación de conocimiento en los entornos virtuales de enseñanza mediante herramientas de Business Intelligence. Caso de estudio en una institución educativa que emplea Moodle

Educational organisations search for differentiating factors in order to become more efficient and effective, so they can improve their competitiveness in the present market. Knowing what is happening within them is a differentiating factor that can be used by incorporating Business Intelligence methods and tools. Many educational organisations use learning virtual environments that automatically store data about any interaction of its users. These interactions are recorded in digital systems that are not usually used, mainly because of the few functionalities and flexibility of the analysis and costumizing of the indicator. This thesis adapts Business Intelligence methods in order to compile a knowledge based in the data stored in the learning virtual environments by using efficience and effectiveness criteria, it mainly focuses on how to transform the data into knowledge. In its conclusion, this thesis contextualises and incorporates methods of knowledge compilation within the framwork of the e-learning department of an online training institution. Thus, the characteristics of these kind of institutions are defined, the suggested methodology implements an empirical experimentation in order to establish the viability from an effeciency and effectiveness point of view.Las organizaciones educativas buscan factores diferenciadores que las hagan más eficientes y eficaces mejorando de esta manera su competitividad en el mercado actual. El conocimiento que poseen sobre lo que está ocurriendo dentro de ellas supone un factor diferenciador que puede ser explotado mediante métodos y herramientas propios del Business Intelligence. Muchas de las organizaciones educativas poseen entornos virtuales de aprendizaje que almacenan de forma automática cualquier interacción realizada por los usuarios. Estas interacciones se registran en sistemas digitales que no suele estar explotado debido, sobretodo, a las pocas funcionalidades y flexibilidad que disponen respecto al análisis y la personalización de indicadores. En esta tesis se adaptan métodos del Business intelligence para captar el conocimiento residente en los datos almacenados en los entornos virtuales de aprendizaje según criterios de eficiencia y eficacia, poniendo el foco en cómo se transforman estos datos en conocimiento. Como resultado de esta Tesis se contextualizan y aplican métodos de extracción de conocimiento en el marco del departamento de e-learning de una institución dedicada a impartir formación on-line. De esta forma, se definen las características propias de este tipo de instituciones y se aplica la experimentación empírica de la metodología propuesta estableciendo la viabilidad desde el punto de vista de la eficiencia y la eficacia.Postprint (published version

An effective method for lung cancer diagnosis from CT scan using deep learning-based support vector network

Producción CientíficaThe diagnosis of early-stage lung cancer is challenging due to its asymptomatic nature, especially given the repeated radiation exposure and high cost of computed tomography(CT). Examining the lung CT images to detect pulmonary nodules, especially the cell lung cancer lesions, is also tedious and prone to errors even by a specialist. This study proposes a cancer diagnostic model based on a deep learning-enabled support vector machine (SVM). The proposed computer-aided design (CAD) model identifies the physiological and pathological changes in the soft tissues of the cross-section in lung cancer lesions. The model is first trained to recognize lung cancer by measuring and comparing the selected profile values in CT images obtained from patients and control patients at their diagnosis. Then, the model is tested and validated using the CT scans of both patients and control patients that are not shown in the training phase. The study investigates 888 annotated CT scans from the publicly available LIDC/IDRI database. The proposed deep learning-assisted SVM-based model yields 94% accuracy for pulmonary nodule detection representing early-stage lung cancer. It is found superior to other existing methods including complex deep learning, simple machine learning, and the hybrid techniques used on lung CT images for nodule detection. Experimental results demonstrate that the proposed approach can greatly assist radiologists in detecting early lung cancer and facilitating the timely management of patients

Amyloid β-but not Tau-induced neurotoxicity is suppressed by Manuka honey via HSP-16.2 and SKN-1/Nrf2 pathways in an in vivo model of Alzheimer’s disease

Alzheimer’s is a chronic degenerative disease of the central nervous system considered the leading cause of dementia in the world. It is characterized by two etiopathological events related to oxidative stress: the aggregation of β-amyloid peptide and the formation of neurofibrillary tangles of hyperphosphorylated Tau protein in the brain. The incidence of this disease increases with age and has been associated with inadequate lifestyles. Some natural compounds have been shown to improve the hallmarks of the disease. However, despite its potential, there is no scientific evidence about Manuka honey (MH) in this regard. In the present work we evaluated the effect of MH on the toxicity induced by Aβ aggregation and Tau in a Caenorhabditis elegans model. Our results demonstrated that MH was able to improve indicators of oxidative stress and delayed Aβ-induced paralysis in the AD model CL4176 through HSP-16.2 and SKN-1/ NRF2 pathways. Nevertheless, its sugar content impaired the indicators of locomotion (an indicator of tau neurotoxicity) in both the transgenic strain BR5706 and in the wild-type N2 worms.MCIN/AEI FPU2017/04358FSE "El FSE invierte en tu futuro" FPU2018/05301JdC-I post-doctoral contract - NextGenerationEU IJC2020-043910-IFEDER/Junta de Andalucia-Consejeria de Economia y Conocimiento B-AGR-193-UGR1

The Molecular Weaponry Produced by the Bacterium Hafnia alvei in Foods

Hafnia alvei is receiving increasing attention from both a medical and veterinary point of view, but the diversity of molecules it produces has made the interest in this bacterium extend to the field of probiotics, the microbiota, and above all, to its presence and action on consumer foods. The production of Acyl Homoserine Lactones (AHLs), a type of quorum-sensing (QS) signaling molecule, is the most often-studied chemical signaling molecule in Gram-negative bacteria. H. alvei can use this communication mechanism to promote the expression of certain enzymatic activities in fermented foods, where this bacterium is frequently present. H. alvei also produces a series of molecules involved in the modification of the organoleptic properties of different products, especially cheeses, where it shares space with other microorganisms. Although some strains of this species are implicated in infections in humans, many produce antibacterial compounds, such as bacteriocins, that inhibit the growth of true pathogens, so the characterization of these molecules could be very interesting from the point of view of clinical medicine and the food industry. Lastly, in some cases, H. alvei is responsible for the production of biogenic amines or other compounds of special interest in food health. In this article, we will review the most interesting molecules that produce the H. alvei strains and will discuss some of their properties, both from the point of view of their biological activity on other microorganisms and the properties of different food matrices in which this bacterium usually thrives

Nutritional value and preventive role of Nigella sativa L. and its main component thymoquinone in cancer: an evidenced-based review of preclinical and clinical studies

In recent times, scientific attention has been paid to different foods and their bioactive components for the ability to inhibit the onset and progress of different types of cancer. Nigella sativa extract, powder and seed oil and its main components, thymoquinone and α-hederin, have showed potent anticancer and chemosensitizing effects against various types of cancer, such as liver, colon, breast, renal, cervical, lung, ovarian, pancreatic, prostate and skin tumors, through the modulation of various molecular signaling pathways. Herein, the purpose of this review was to highlight the anticancer activity of Nigella sativa and it constitutes, focusing on different in vitro, in vivo and clinical studies and projects, in order to underline their antiproliferative, proapoptotic, cytotoxic and antimetastatic effects. Particular attention has been also given to the synergistic effect of Nigella sativa and it constitutes with chemotherapeutic drugs, and to the synthesized analogs of thymoquinone that seem to enhance the chemo-sensitizing potential. This review could be a useful step towards new research on N. sativa and cancer, to include this plant in the dietary treatments in support to conventional therapies, for the best achievement of therapeutic goals

The molecular basis of different approaches for the study of cancer stem cells and the advantages and disadvantages of a three-dimensional culture

Cancer stem cells (CSCs) are a rare tumor subpopulation with high differentiation, proliferative and tumorigenic potential compared to the remaining tumor population. CSCs were first discovered by Bonnet and Dick in 1997 in acute myeloid leukemia. The identification and isolation of these cells in this pioneering study were carried out through the flow cytometry, exploiting the presence of specific cell surface molecular markers (CD34+/CD38−). In the following years, different strategies and projects have been developed for the study of CSCs, which are basically divided into surface markers assays and functional assays; some of these techniques also allow working with a cellular model that better mimics the tumor architecture. The purpose of this mini review is to summarize and briefly describe all the current methods used for the identification, isolation and enrichment of CSCs, describing, where possible, the molecular basis, the advantages and disadvantages of each technique with a particular focus on those that offer a three-dimensional culture

Evaluation of the Sustainable Development Goals in the Diagnosis and Prediction of the Sustainability of Projects Aimed at Local Communities in Latin America and the Caribbean

The purpose of this article is to help to bridge the gap between sustainability and its application to project management by developing a methodology based on artificial intelligence to diagnose, classify, and forecast the level of sustainability of a sample of 186 projects aimed at local communities in Latin American and Caribbean countries. First, the compliance evaluation with the Sustainable Development Goals (SDGs) within the framework of the 2030 Agenda served to diagnose and determine, through fuzzy sets, a global sustainability index for the sample, resulting in a value of 0.638, in accordance with the overall average for the region. Probabilistic predictions were then made on the sustainability of the projects using a series of supervised learning classifiers (SVM, Random Forest, AdaBoost, KNN, etc.), with the SMOTE resampling technique, which provided a significant improvement toward the results of the different metrics of the base models. In this context, the Support Vector Machine (SVM) + SMOTE was the best classification algorithm, with accuracy of 0.92. Lastly, the extrapolation of this methodology is to be expected toward other realities and local circumstances, contributing to the fulfillment of the SDGs and the development of individual and collective capacities through the management and direction of projects

Possible role of nutrition in the prevention of inflammatory bowel disease-related colorectal cancer: A focus on human studies

: Patients with inflammatory bowel disease (IBD) are at substantially high risk for colorectal cancer (CRC). IBD-associated CRC accounts for roughly 10% to 15% of the annual mortality in patients with IBD. IBD-related CRC also affects younger patients compared with sporadic CRC, with a 5-y survival rate of 50%. Regardless of medical therapies, the persistent inflammatory state characterizing IBD raises the risk for precancerous changes and CRC, with additional input from several elements, including genetic and environmental risk factors, IBD-associated comorbidities, intestinal barrier dysfunction, and gut microbiota modifications. It is well known that nutritional habits and dietary bioactive compounds can influence IBD-associated inflammation, microbiome abundance and composition, oxidative stress balance, and gut permeability. Additionally, in recent years, results from broad epidemiologic and experimental studies have associated certain foods or nutritional patterns with the risk for colorectal neoplasia. The present study aimed to review the possible role of nutrition in preventing IBD-related CRC, focusing specifically on human studies. It emerges that nutritional interventions based on healthy, nutrient-dense dietary patterns characterized by a high intake of fiber, vegetables, fruit, ω-3 polyunsaturated fatty acids, and a low amount of animal proteins, processed foods, and alcohol, combined with probiotic supplementation have the potential of reducing IBD-activity and preventing the risk of IBD-related CRC through different mechanisms, suggesting that targeted nutritional interventions may represent a novel promising approach for the prevention and management of IBD-associated CRC

Adherence to the Mediterranean-Style Eating Pattern and Macular Degeneration: A Systematic Review of Observational Studies

Age-related macular degeneration (AMD) is a serious degenerative disease affecting the eyes, and is the main cause of severe vision loss among people >55 years of age in developed countries. Its onset and progression have been associated with several genetic and lifestyle factors, with diet appearing to play a pivotal role in the latter. In particular, dietary eating patterns rich in plant foods have been shown to lower the risk of developing the disease, and to decrease the odds of progressing to more advanced stages in individuals already burdened with early AMD. We systematically reviewed the literature to analyse the relationship between the adherence to a Mediterranean diet, a mainly plant-based dietary pattern, and the onset/progression of AMD. Eight human observational studies were analysed. Despite some differences, they consistently indicate that higher adherence to a Mediterranean eating pattern lowers the odds of developing AMD and decreases the risk of progression to more advanced stages of the disease, establishing the way for preventative measures emphasizing dietary patterns rich in plant-foods

Effects of Mediterranean diet or mindfulness-based stress reduction on fetal and neonatal brain development : a secondary analysis of a randomized clinical trial

BACKGROUND: Maternal suboptimal nutrition and high stress levels are associated with adverse fetal and infant neurodevelopment. OBJECTIVE: This study aimed to investigate if structured lifestyle interventions involving a Mediterranean diet or mindfulness-based stress reduction during pregnancy are associated with differences in fetal and neonatal brain development. STUDY DESIGN: This was a secondary analysis of the randomized clinical trial Improving Mothers for a Better Prenatal Care Trial Barcelona that was conducted in Barcelona, Spain, from 2017 to 2020. Participants with singleton pregnancies were randomly allocated into 3 groups, namely Mediterranean diet intervention, stress reduction program, or usual care. Participants in the Mediterranean diet group received monthly individual sessions and free provision of extra-virgin olive oil and walnuts. Pregnant women in the stress reduction group underwent an 8-week mindfulness-based stress reduction program adapted for pregnancy. Magnetic resonance imaging of 90 fetal brains was performed at 36 to 39 weeks of gestation and the Neonatal Neurobehavioral Assessment Scale was completed for 692 newborns at 1 to 3 months. Fetal outcomes were the total brain volume and lobular or regional volumes obtained from a 3-dimensional reconstruction and semiautomatic segmentation of magnetic resonance images. Neonatal outcomes were the 6 clusters scores of the Neonatal Neurobehavioral Assessment Scale. Multiple regression analyses were conducted to assess the association between the interventions and the fetal and neonatal outcomes. RESULTS: When compared with the usual care group, the offspring exposed to a maternal Mediterranean diet had a larger total fetal brain volume (mean, 284.11 cm; standard deviation, 23.92 cm vs 294.01 cm; standard deviation, 26.29 cm; P=.04), corpus callosum (mean, 1.16 cm; standard deviation, 0.19 cm vs 1.26 cm; standard deviation, 0.22 cm; P=.03), and right frontal lobe (44.20; standard deviation, 4.09 cm vs 46.60; standard deviation, 4.69 cm; P=.02) volumes based on magnetic resonance imaging measures and higher scores in the Neonatal Neurobehavioral Assessment Scale clusters of autonomic stability (mean, 7.4; standard deviation, 0.9 vs 7.6; standard deviation, 0.7; P=.04), social interaction (mean, 7.5; standard deviation, 1.5 vs 7.8; standard deviation, 1.3; P=.03), and range of state (mean, 4.3; standard deviation, 1.3 vs 4.5; standard deviation, 1.0; P=.04). When compared with the usual care group, offspring from the stress reduction group had larger fetal left anterior cingulate gyri volume (1.63; standard deviation, 0.32 m vs 1.79; standard deviation, 0.30 cm; P=.03) based on magnetic resonance imaging and higher scores in the Neonatal Neurobehavioral Assessment Scale for regulation of state (mean, 6.0; standard deviation, 1.8 vs 6.5; standard deviation, 1.5; P<.01). CONCLUSION: Maternal structured lifestyle interventions involving the promotion of a Mediterranean diet or stress reduction during pregnancy were associated with changes in fetal and neonatal brain development