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VidAanchoa: Estudio de vida útil de la anchoa en semiconserva y desarrollo de tecnologías para extenderla en la industria conservera
No full textLa anchoa del Cantábrico es uno de los alimentos españoles más emblemáticos y
lleva asociada una tradición pesquera, social y cultural de relevancia, partiendo de su
“cuna” en Santoña (Cantabria). La elaboración de la semiconserva de anchoa es un
procedimiento que logra la conservación de la anchoa durante un tiempo limitado
(vida útil) mediante la utilización de sal como conservante.
El proyecto pretende realizar una investigación con el fin último de extender su vida
útil, en línea con lo indicado en la convocatoria: prolongar “la vida útil de los
materiales y/o productos”.
Para extender la vida útil y mantener la calidad sensorial de las anchoas, una de las
líneas de investigación que parece más prometedora es la incorporación de
antioxidantes en su elaboración. La incorporación de extractos naturales y/o suero
de queso como antioxidantes aporta un valor añadido fundamental, tanto desde el
punto de vista tecnológico como de sostenibilidad.
Para alcanzar la meta propuesta, en primer lugar, se plantea realizar un estudio
experimental de la vida útil de semiconservas de anchoa y posteriormente explorar
vías para su extensión. La investigación a realizar conlleva alcanzar los siguientes
objetivos específicos:
1. Analizar la relación entre la composición lipídica estacional de las anchoas y su
susceptibilidad oxidativa.
2. Evaluar la vida útil de anchoas de otoño/invierno y de primavera/verano a través
de oxitest para establecer diferencias de vida útil en función del contenido graso.
3. Estudiar el efecto de antioxidantes naturales para inhibir la oxidación, ajustando
concentraciones según el perfil lipídico de la anchoa.
4. Analizar el efecto sobre las características organolépticas de la anchoa en función
de las concentraciones antioxidantes más efectivas.
5. Diseñar un proceso de mejora de la vida útil de las anchoas a través de la adición
de antioxidantes naturales considerando la influencia organoléptica
Ergosterol-Enriched Liposomes with Post-Processing Modifications for Serpylli Herba Polyphenol Delivery: Physicochemical, Stability and Antioxidant Assessment
Get PDFBackground/Objectives: In the present study, ergosterol, a novel natural and animal-free alternative sterol, was investigated, and its effects on liposomal properties were assessed. Importantly, ergosterol’s fungal origin offers a sustainable substitute for cholesterol, aligning with current trends in natural and vegan-friendly formulations. Methods: This study explored the effect of ergosterol content (10 mol% vs. 20 mol%) on the encapsulation efficiency (EE), physical properties, morphology, antioxidant activity, lipid peroxidation, and storage stability of Serpylli herba extract-loaded liposomes. Results: Liposomes with 20 mol% ergosterol exhibited significantly higher EE (~81.0%) than those with 10 mol% (~75.6%), along with improved resistance to UV- and freeze-drying-induced reduction in EE. Extract loading resulted in a reduced particle size, indicating favorable bilayer interactions, whereas lyophilization increased size and polydispersity, reflecting structural destabilization. However, 20 mol% ergosterol improved vesicle uniformity and surface charge stability, suggesting enhanced bilayer rigidity. Zeta potential and mobility trends supported improved colloidal stability in ergosterol-enriched systems under all tested conditions. Over 28 days at 4 °C, non-treated extract-loaded liposomes with a higher ergosterol content demonstrated enhanced vesicle integrity. During storage, UV-treated and lyophilized liposomes with 20 mol% ergosterol maintained more consistent size and charge profiles, indicating better membrane reorganization and stability. Nanoparticle tracking analysis demonstrated that ergosterol content modulates vesicle concentration in a dose-dependent manner, highlighting the role of membrane composition in liposome formation and potential dose uniformity. Transmission electron microscopy analysis of extract-loaded liposomes demonstrated well-defined vesicles with intact structural features. A study in a Franz diffusion cell revealed that ergosterol-enriched liposomes significantly delayed polyphenol release compared to free extract, confirming their potential for controlled delivery. Antioxidant activity was preserved in all liposomal systems, with higher ergosterol content supporting improved ABTS radical scavenging potential after stress treatments. FRAP assay results remained stable across formulations, with no major differences between sterol levels. TBARS analysis demonstrated that Serpylli herba extract significantly reduced UV-induced lipid peroxidation in ergosterol-enriched liposomes, underscoring its protective antioxidant role. Conclusions: Higher ergosterol content enhanced liposomal performance in terms of encapsulation, structural resilience, and antioxidant retention, particularly under UV and lyophilization stress. Ergosterol-containing liposomes exhibited improved stability, favorable particle size distribution, and high encapsulation efficiency, while maintaining the antioxidant functionality of the incorporated Serpylli herba polyphenol-rich extract. These findings highlight the potential of ergosterol-based liposomes as robust carriers for bioactive compounds in pharmaceutical and nutraceutical applications that align with current trends in green and vegan-friendly formulations
Efectos del juego terapéutico Creciendo en Mindfulness (CEM) sobre los problemas emocionales y de conducta de los menores en conflicto con la Ley Penal del CPI “Jalteva” en Honduras
No full textEste estudio evaluó la eficacia del juego terapéutico Creciendo en Mindfulness (CEM) para disminuir los problemas emocionales y de conducta en adolescentes internados en el Centro Pedagógico de Internamiento “Jalteva”, Honduras. Se adoptó un diseño preexperimental de preprueba-posprueba con un único grupo (n = 27; 13-18 años). Antes y después de cuatro sesiones del CEM, se aplicaron el Cuestionario para la Evaluación de Problemas en Adolescentes (Q-PAD) y el Inventario de Evaluación de la Personalidad para Adolescentes (PAI-A). Los cambios se analizaron mediante la prueba de rangos con signo de Wilcoxon y se estimó el índice g de Hedges. Tras la intervención, la incertidumbre sobre el futuro bajó del percentil 86 al 71 (p = .011; g = −0.46) y la percepción de falta de apoyo social descendió de T = 64 a 58 (p = .032; g = −0.45). Sin embargo, la actitud agresiva aumentó de T = 55 a 58 (p = .037; g = 0.28). El patrón de correlaciones entre escalas se volvió más coherente, lo que sugiere una mayor conciencia emocional. Los hallazgos indican que el CEM genera mejoras puntuales en variables internas asociadas con la ansiedad anticipatoria y el apoyo percibido, aunque su impacto global sobre la sintomatología emocional y conductual fue limitado. Factores institucionales, la ausencia de un grupo control y el corto seguimiento restringen la atribución causal y la generalización. Se recomienda complementar el programa con intervenciones individualizadas y acompañamiento familiar para potenciar la reinserción social de los adolescentes
Generación de modelos de aprendizaje automático para la creación de grafos de conocimiento a partir de datos no estructurados (AI.NEEDS.DATA)
No full textEl presente proyecto se orienta a diseñar una metodología que permita generar
modelos de aprendizaje automático para la creación de grafos de conocimiento a
partir de datos no estructurados. El proyecto se enmarca en el constante reto por
obtener conocimiento e información de fuentes digitales de datos que no se pueden
aprovechar de forma directa. Se vincula también a la creciente necesidad que tiene
la inteligencia artificial para acceder a ”información y conocimiento”. Se trata de
buscar soluciones para extraer información de datos no estructurados, donde
podemos partir de “datos” en forma de textos libres con la finalidad de obtener
conocimiento en forma de estructuras de grafos de conocimiento - también
conocidos como knowledge graphs
Influence of Physiological Variables and Comorbidities on Plasma Aβ40, Aβ42, and p-tau181 Levels in Cognitively Unimpaired Individuals
No full textPlasma biomarkers for Alzheimer’s disease (AD) are a promising tool that may help in early diagnosis. However, their levels may be influenced by physiological parameters and comorbidities that should be considered before they can be used at the population level. For this purpose, we assessed the influences of different comorbidities on AD plasma markers in 208 cognitively unimpaired subjects. We analyzed both plasma and cerebrospinal fluid levels of Aβ40, Aβ42, and p-tau181 using the fully automated Lumipulse platform. The relationships between the different plasma markers and physiological variables were studied using linear regression models. The mean differences in plasma markers according to comorbidity groups were also studied. The glomerular filtration rate showed an influence on plasma Aβ40 and Aβ42 levels but not on the Aβ42/Aβ40 ratio. The amyloid ratio was significantly lower in diabetic and hypertensive subjects, and the mean p-tau181 levels were higher in hypertensive subjects. The glomerular filtration rate may have an inverse relationship on plasma Aβ40 and Aβ42 levels but not on the amyloid ratio, suggesting that the latter is a more stable marker to use in the general population. Cardiovascular risk factors might have a long-term effect on the amyloid ratio and plasma levels of p-tau181
The Acute: Chronic Workload Ratio and Injury Risk in Semiprofessional Football Players
No full textThe purpose of this study was to analyze the association and predictive capacity between the acute:chronic workload ratio (ACWR) and non-contact injuries in a semiprofessional football team. Seventeen football or soccer players from a Spanish Third Division football team participated voluntarily in this study. A prospective longitudinal study was developed during the 2020/2021 season. Twenty-four weeks were analyzed from October to March, including a regenerative microcycle due to the absence of competition during Christmas. Rate of perceived exertion (RPE) and session-rate of perceived exertion (sRPE) were registered for every training and game session. Afterward, acute and chronic workloads were calculated, and ACWR was subsequently derived from them. Furthermore, non-contact injuries were registered during the period mentioned. The main findings were that there is a poor correlation between the ACWR and non-contact injuries (r=0.069 (p<0.05)), and the use of the ACWR by itself is insufficient to predict the occurrence of non-contact injuries in a semiprofessional football team. Consequently, the ACWR is not an useful predictive tool for injuries in semiprofessional football teams
Blue light inhibits gray mold infection by inducing disease resistance in cherry tomato
No full textInduced resistance is considered as a sustainable strategy to control postharvest decay of fruits, while light emitting diodes (LEDs) as a green physical technology are of more and more interest in postharvest fruit preservation field. In this study, we evaluated for the first time the resistance inducing ability of LED irradiation with different light wavelengths and photoperiods for cherry tomatoes (Solanum lycopersicum L. ‘Qianxi’). Results indicated the exposure to 40 W m-2 of four light wavelengths for 3 d decreased B. cinerea lesion diameter on harvested cherry tomatoes, notably the best effect in blue light (470 nm). Meanwhile, the mechanism of blue light-induced disease resistance is the enhancement of defense-enzyme activity and the expression of defense-related genes. Moreover, results revealed that blue light enhanced vitamin C content and the firmness of the fruit exocarp, suggesting the potential usage of blue light in the postharvest preservation of cherry tomatoes
DiabSense: early diagnosis of non-insulin-dependent diabetes mellitus using smartphone-based human activity recognition and diabetic retinopathy analysis with Graph Neural Network
No full textNon-Insulin-Dependent Diabetes Mellitus (NIDDM) is a chronic health condition caused by high blood sugar levels, and if not treated early, it can lead to serious complications i.e. blindness. Human Activity Recognition (HAR) offers potential for early NIDDM diagnosis, emerging as a key application for HAR technology. This research introduces DiabSense, a state-of-the-art smartphone-dependent system for early staging of NIDDM. DiabSense incorporates HAR and Diabetic Retinopathy (DR) upon leveraging the power of two different Graph Neural Networks (GNN). HAR uses a comprehensive array of 23 human activities resembling Diabetes symptoms, and DR is a prevalent complication of NIDDM. Graph Attention Network (GAT) in HAR achieved 98.32% accuracy on sensor data, while Graph Convolutional Network (GCN) in the Aptos 2019 dataset scored 84.48%, surpassing other state-of-the-art models. The trained GCN analyzed retinal images of four experimental human subjects for DR report generation, and GAT generated their average duration of daily activities over 30 days. The daily activities in non-diabetic periods of diabetic patients were measured and compared with the daily activities of the experimental subjects, which helped generate risk factors. Fusing risk factors with DR conditions enabled early diagnosis recommendations for the experimental subjects despite the absence of any apparent symptoms. The comparison of DiabSense system outcome with clinical diagnosis reports in the experimental subjects was conducted using the A1C test. The test results confirmed the accurate assessment of early diagnosis requirements for experimental subjects by the system. Overall, DiabSense exhibits significant potential for ensuring early NIDDM treatment, improving millions of lives worldwide
EEG-based motor imagery channel selection and classification using hybrid optimization and two-tier deep learning
No full textBrain–computer interface (BCI) technology holds promise for individuals with profound motor impairments, offering the potential for communication and control. Motor imagery (MI)-based BCI systems are particularly relevant in this context. Despite their potential, achieving accurate and robust classification of MI tasks using electroencephalography (EEG) data remains a significant challenge. In this paper, we employed the Minimum Redundancy Maximum Relevance (MRMR) algorithm to optimize channel selection. Furthermore, we introduced a hybrid optimization approach that combines the War Strategy Optimization (WSO) and Chimp Optimization Algorithm (ChOA). This hybridization significantly enhances the classification model’s overall performance and adaptability. A two-tier deep learning architecture is proposed for classification, consisting of a Convolutional Neural Network (CNN) and a modified Deep Neural Network (M-DNN). The CNN focuses on capturing temporal correlations within EEG data, while the M-DNN is designed to extract high-level spatial characteristics from selected EEG channels. Integrating optimal channel selection, hybrid optimization, and the two-tier deep learning methodology in our BCI framework presents an enhanced approach for precise and effective BCI control. Our model got 95.06% accuracy with high precision. This advancement has the potential to significantly impact neurorehabilitation and assistive technology applications, facilitating improved communication and control for individuals with motor impairment
Medical Professionalism and Its Association with Dropout Intention in Peruvian Medical Students during the COVID-19 Pandemic
No full textBackground: The COVID-19 pandemic introduced unprecedented challenges to medical education systems and medical students worldwide, making it necessary to adapt teaching to a remote methodology during the academic year 2020–2021. The aim of this study was to characterize the association between medical professionalism and dropout intention during the pandemic in Peruvian medical schools. Methods: A cross-sectional online-survey-based study was performed in four Peruvian medical schools (two public) during the academic year 2020–2021. Medical students, attending classes from home, answered three scales measuring clinical empathy, teamwork, and lifelong learning abilities (three elements of medical professionalism) and four scales measuring loneliness, anxiety, depression, and subjective wellbeing. In addition, 15 demographic, epidemiological, and academic variables (including dropout intention) were collected. Variables were assessed using multiple logistic regression analysis. Results: The study sample was composed of 1107 students (390 male). Eight variables were included in an explanatory model (Nagelkerke-R2 = 0.35). Anxiety, depression, intention to work in the private sector, and teamwork abilities showed positive associations with dropout intention while learning abilities, subjective wellbeing, studying in a public medical school, and acquiring a better perception of medicine during the pandemic showed a negative association with dropout intention. No association was observed for empathy. Conclusions: Each element measured showed a different role, providing new clues on the influence that medical professionalism had on dropout intention during the pandemic. This information can be useful for medical educators to have a better understanding of the influence that professionalism plays in dropout intention