Oxidative Stress and Inflammation as Targets for Novel Preventive and Therapeutic Approaches in Non-Communicable Diseases II

Non-communicable diseases (NCDs) are non-infectious chronic pathologies—including obesity, metabolic syndrome, chronic kidney disease (CKD), cardiovascular (CV) diseases, cancer, and chronic respiratory diseases—which represent the main cause of death and disability for the general population [...

Oxidative Stress and Inflammation as Targets for Novel Preventive and Therapeutic Approches in Non Communicable Diseases

As recently reported by the World Health Organization (WHO), Non-Communicable Diseases (NCDs) has been rising over the last century representing the main cause of death and disability for the general population regardless of age, region, or gender [...

Predire la borsa valori con language model neurali

Nonostante lo scetticismo di molti studiosi circa la possibilità di prevedere l'andamento della borsa valori, esistono svariate teorie ipotizzanti la possibilità di utilizzare le informazioni conosciute per predirne i movimenti futuri. L’avvento dell’intelligenza artificiale nella seconda parte dello scorso secolo ha permesso di ottenere risultati rivoluzionari in svariati ambiti, tanto che oggi tale disciplina trova ampio impiego nella nostra vita quotidiana in molteplici forme. In particolare, grazie al machine learning, è stato possibile sviluppare sistemi intelligenti che apprendono grazie ai dati, riuscendo a modellare problemi complessi. Visto il successo di questi sistemi, essi sono stati applicati anche all’arduo compito di predire la borsa valori, dapprima utilizzando i dati storici finanziari della borsa come fonte di conoscenza, e poi, con la messa a punto di tecniche di elaborazione del linguaggio naturale umano (NLP), anche utilizzando dati in linguaggio naturale, come il testo di notizie finanziarie o l’opinione degli investitori. Questo elaborato ha l’obiettivo di fornire una panoramica sull’utilizzo delle tecniche di machine learning nel campo della predizione del mercato azionario, partendo dalle tecniche più elementari per arrivare ai complessi modelli neurali che oggi rappresentano lo stato dell’arte. Vengono inoltre formalizzati il funzionamento e le tecniche che si utilizzano per addestrare e valutare i modelli di machine learning, per poi effettuare un esperimento in cui a partire da dati finanziari e soprattutto testuali si tenterà di predire correttamente la variazione del valore dell’indice di borsa S&P 500 utilizzando un language model basato su una rete neurale

Cultivating the future: Legal challenges of artificial intelligence in provincial agrarian law

En un mundo en constante evolución, la agricultura desafía la innovación y la tecnología para abordar los crecientes retos de la producción, la sostenibilidad y la seguridad alimentaria. En este contexto, la provincia de Santiago del Estero se destaca como una región de tradición agrícola que enfrenta desafíos únicos debido a factores como el cambio climático. De esta manera, el uso de la Inteligencia Artificial (IA) en la agricultura aparece como una solución prometedora para mejorar la productividad, la eficiencia y la toma de decisiones en este importante sector económico. Sin embargo, este cambio tecnológico no está exento de implicaciones éticas, sociales y medioambientales, por lo que su regulación legal resulta necesaria para garantizar que la implementación de la IA en la agricultura sea ética, responsable y sostenible. En consecuencia, en el presente trabajo se explorará la aplicación de la IA en la agricultura de la provincia de Santiago del Estero, señalando la necesidad de establecer una regulación legal provincial que guíe su integración.In a world in constant evolution, agriculture challenges innovation and technology to address the growing challenges of production, sustainability and food security. In this context, the province of Santiago del Estero stands out as a region with an agricultural tradition that faces unique challenges due to factors such as climate change. In this way, the use of Artificial Intelligence (AI) in agriculture appears as a promising solution to improve productivity, efficiency and decision-making in this important economic sector. However, this technological change is not exempt from ethical, social and environmental implications, which is why its legal regulation is necessary to guarantee that the implementation of AI in agriculture is ethical, responsible and sustainable. Consequently, in the present work the application of AI in agriculture in the province of Santiago del Estero will be explored, pointing out the need to establish a provincial legal regulation that guides its integration.Facultad de Ciencias Jurídicas y Sociale

Oleuropein, a bioactive compound from olea europaea L., as a potential preventive and therapeutic agent in non-communicable diseases

Growing scientific literature data suggest that the intake of natural bioactive compounds plays a critical role in preventing or reducing the occurrence of human chronic non-communicable diseases (NCDs). Oleuropein, the main phenolic component of Olea europaea L., has attracted scientific attention for its several health beneficial properties such as antioxidant, anti-inflammatory, cardio- and neuro-protective, and anti-cancer. This article is a narrative review focused on the current literature concerning the effect of oleuropein in NCDs, such as neuro- and cardiovascular diseases, diabetes mellitus, chronic kidney diseases, and cancer, by its putative antioxidant and anti-inflammatory activity, but also for its other peculiar actions such as an autophagy inducer and amyloid fibril growth inhibitor and, finally, for its anti-cancer effect. Despite the increasing number of published studies, looking at the beneficial effects of oleuropein, there is limited clinical evidence focused on the benefits of this polyphenol as a nutraceutical product in humans, and many problems are still to be resolved about its bioavailability, bioaccessibility, and dosage. Thus, future clinical randomized trials are needed to establish the relation between the beneficial effects and the mechanisms of action occurring in the human body in response to the intake of oleuropein

Antimicrobial Activities of Leaves Extracts of Mistol (Ziziphusmistol), Algarrobo blanco (Prosopisalba) and Tusca (Acacia Aroma) to be Applied to Meat Products Preservation

The aim of the present study is to analyze the in vitro antioxidant activity against pathogens such as Salmonella, Staphylococcus aureus, Staphylococcus sp, Bacillus cereus, Micrococcus, Escherichia coli and Listeria innocua using Ziziphus mistol (Mistol), Prosopis alba (Algarrobo blanco) and Acacia aroma (Tusca) extracts with 70% acetone and 50% ethanol as solvents extraction as antibacterial. Determination was made by agar disk diffusion method. All the extracts showed some antibacterial activity, however, Bacillus cereus was more resistant and Staphylococcus aureus was more sensitive to the extracts evaluated in comparison with the other strains of bacteria used in the test. Nevertheless, Algarrobo blanco extracts in 50% ethanol significantly inhibited the growth of Staphylococcus sp. Therefore, extracts Mistol, Algarrobo blanco and Tusca could have potential as natural preservatives for fresh meat products.EEA Santiago del EsteroFil: Ruiz, Silvana Cecilia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santiago del Estero; ArgentinaFil: Ruiz, Silvana Cecilia. Universidad Nacional de Santiago del Estero. Facultad de Agronomía y Agroindustria; ArgentinaFil: Nediani, Teresa. Universidad Nacional de Santiago del Estero. Facultad de Agronomía y Agroindustria; ArgentinaFil: Garcia, Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Martínez, Sandra Luz. Universidad Nacional de Santiago del Estero. Facultad de Agronomía y Agroindustria; Argentin