Items where Subject is "Subjects > Nutrition"

Up a level
Export as [feed] Atom [feed] RSS 1.0 [feed] RSS 2.0
Group by: Date | Title | Creators | Item Type
Jump to: 2020 | 2016 | 2015
Number of items at this level: 3.


Article Subjects > Nutrition Ibero-american International University > Research > Scientific Production Abierto Inglés University students frequently develop unhealthy eating habits. However, it is unknown if students enrolled in academic programs related to nutrition and culinary arts have healthier eating habits. We evaluated the relationship of eating habits and nutritional status of students in academic programs with knowledge on nutrition, as well as cooking methods and techniques. A descriptive cross-sectional study was conducted in spring of 2019, while we completed a survey measuring eating habits and knowledge on nutrition, as well as cooking methods and techniques. Anthropometric measurements were collected for nutritional status estimation. The non-probabilistic convenience sample comprised 93 students pursuing degrees at Universidad Ana G. Mendez, Puerto Rico. Inadequate body mass index (BMI) was observed in 59% of the students. Eating habits, knowledge on nutrition, and knowledge on cooking methods and techniques were inadequate in 86%, 68%, and 41% of the population, respectively. Eating habits were associated with knowledge on nutrition and academic program, but not with knowledge on cooking methods and techniques. Most students reported having inadequate eating habits and BMI. Nutrition and dietetics students had the best knowledge on nutrition compared to culinary management students, a majority of whom had inadequate knowledge. We can conclude that there are other factors inherent to students’ life that may have a stronger influence on eating habits metadata Rivera Medina, Christian and Briones Urbano, Mercedes and de Jesús Espinosa, Aixa and Toledo López, Ángel mail UNSPECIFIED,, UNSPECIFIED, UNSPECIFIED (2020) Eating Habits Associated with Nutrition-Related Knowledge among University Students Enrolled in Academic Programs Related to Nutrition and Culinary Arts in Puerto Rico. Nutrients, 12 (5). p. 1408. ISSN 2072-6643


Article Subjects > Nutrition Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Abierto Inglés It has been hypothesized that alterations in the composition of the gut microbiota might be associated with the onset of certain human pathologies, such as Alzheimer disease, a neurodegenerative syndrome associated with cerebral accumulation of amyloid-β fibrils. It has been shown that bacteria populating the gut microbiota can release significant amounts of amyloids and lipopolysaccharides, which might play a role in the modulation of signaling pathways and the production of proinflammatory cytokines related to the pathogenesis of Alzheimer disease. Additionally, nutrients have been shown to affect the composition of the gut microbiota as well as the formation and aggregation of cerebral amyloid-β. This suggests that modulating the gut microbiome and amyloidogenesis through specific nutritional interventions might prove to be an effective strategy to prevent or reduce the risk of Alzheimer disease. This review examines the possible role of the gut in the dissemination of amyloids, the role of the gut microbiota in the regulation of the gut–brain axis, the potential amyloidogenic properties of gut bacteria, and the possible impact of nutrients on modulation of microbiota composition and amyloid formation in relation to the pathogenesis of Alzheimer disease. metadata Pistollato, Francesca and Sumalla Cano, Sandra and Elío Pascual, Iñaki and Masias Vergara, Manuel and Giampieri, Francesca and Battino, Maurizio mail,,,,, (2016) Role of gut microbiota and nutrients in amyloid formation and pathogenesis of Alzheimer disease. Nutrition Reviews, 74 (10). pp. 624-634. ISSN 0029-6643


Article Subjects > Biomedicine
Subjects > Nutrition
Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Cerrado Inglés In the last decade, specific dietary patterns, mainly characterized by high consumption of vegetables and fruits, have been proven beneficial for the prevention of both metabolic syndrome (MetS)-related dysfunctions and neurodegenerative disorders, such as Alzheimer’s disease (AD). Nowadays, neuroimaging readouts can be used to diagnose AD, investigate MetS effects on brain functionality and anatomy, and assess the effects of dietary supplementations and nutritional patterns in relation to neurodegeneration and AD-related features. Here we review scientific literature describing the use of the most recent neuroimaging techniques to detect AD- and MetS-related brain features, and also to investigate associations between consolidated dietary patterns or nutritional interventions and AD, specifically focusing on observational and intervention studies in humans. metadata Pistollato, Francesca and Sumalla Cano, Sandra and Elío Pascual, Iñaki and Masías Vergara, Manuel and Giampieri, Francesca and Battino, Maurizio mail,,,,, (2015) The Use of Neuroimaging to Assess Associations Among Diet, Nutrients, Metabolic Syndrome, and Alzheimer’s Disease. Journal of Alzheimer's Disease, 48 (2). pp. 303-318. ISSN 13872877

This list was generated on Fri Dec 2 23:40:09 2022 UTC.

<a href="/512/1/43.%20qCOVID%20vs%20NEWS.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>



One-on-one comparison between qCSI and NEWS scores for mortality risk assessment in patients with COVID-19

Objective To compare the predictive value of the quick COVID-19 Severity Index (qCSI) and the National Early Warning Score (NEWS) for 90-day mortality amongst COVID-19 patients. Methods Multicenter retrospective cohort study conducted in adult patients transferred by ambulance to an emergency department (ED) with suspected COVID-19 infection subsequently confirmed by a SARS-CoV-2 test (polymerase chain reaction). We collected epidemiological data, clinical covariates (respiratory rate, oxygen saturation, systolic blood pressure, heart rate, temperature, level of consciousness and use of supplemental oxygen) and hospital variables. The primary outcome was cumulative all-cause mortality during a 90-day follow-up, with mortality assessment monitoring time points at 1, 2, 7, 14, 30 and 90 days from ED attendance. Comparison of performances for 90-day mortality between both scores was carried out by univariate analysis. Results From March to November 2020, we included 2,961 SARS-CoV-2 positive patients (median age 79 years, IQR 66–88), with 49.2% females. The qCSI score provided an AUC ranging from 0.769 (1-day mortality) to 0.749 (90-day mortality), whereas AUCs for NEWS ranging from 0.825 for 1-day mortality to 0.777 for 90-day mortality. At all-time points studied, differences between both scores were statistically significant (p < .001). Conclusion Patients with SARS-CoV-2 can rapidly develop bilateral pneumonias with multiorgan disease; in these cases, in which an evacuation by the EMS is required, reliable scores for an early identification of patients with risk of clinical deterioration are critical. The NEWS score provides not only better prognostic results than those offered by qCSI at all the analyzed time points, but it is also better suited for COVID-19 patients.

Producción Científica

Francisco Martín-Rodríguez mail , Ancor Sanz-García mail , Guillermo J. Ortega mail , Juan F. Delgado-Benito mail , Eduardo Garcia Villena mail, Cristina Mazas Pérez-Oleaga mail, Raúl López-Izquierdo mail , Miguel A. Castro Villamor mail ,




FairHealth: Long-Term Proportional Fairness-Driven 5G Edge Healthcare in Internet of Medical Things

Recently, the Internet of Medical Things (IoMT) could offload healthcare services to 5 G edge computing for low latency. However, some existing works assumed altruistic patients will sacrifice Quality of Service (QoS) for the global optimum. For priority-aware and deadline-sensitive healthcare, this sufficient and simplified assumption will undermine the engagement enthusiasm, i.e., unfairness. To address this issue, we propose a long-term proportional fairness-driven 5 G edge healthcare, i.e., FairHealth. First, we establish a long-term Nash bargaining game to model the service offloading, considering the stochastic demand and dynamic environment. We then design a Lyapunov-based proportional-fairness resource scheduling algorithm, which decouples the long-term fairness problem into single-slot sub-problems, realizing a trade-off between service stability and fairness. Moreover, we propose a block-coordinate descent method to iteratively solve non-convex fair sub-problems. Simulation results show that our scheme can improve 74.44% of the fairness index (i.e., Nash product), compared with the classic global time-optimal scheme.

Producción Científica

Xi Lin mail , Jun Wu mail , Ali Kashif Bashir mail , Wu Yang mail , Aman Singh mail, Ahmad Ali AlZubi mail ,


<a href="/3058/1/socsci-11-00334.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>



Inequalities and Asymmetries in the Development of Angola’s Provinces: The Impact of Colonialism and Civil War

Angola, as with many countries on the African continent, has great inequalities or asymmetries between its provinces. At the economic, financial, and technological level, there is a great disparity between them, where it is observed that the province of Luanda is the largest financial business center to the detriment of others, such as Moxico, Zaire, and Cabinda. In the latter, despite the advantages of high oil production, from a regional point of view, they remain almost stagnant in time, in a social dysfunction where the population lives on extractivism and artisanal fishing. This article analyzes the most important events in contemporary regional history, the Portuguese occupation that was the Portuguese colonial rule over Angola (1890–1930) and the civil war that was a struggle between Angolans for control of the country (1975–2002), in the consolidation of the asymmetries between provinces. For this work, a theoretical-reflective study was conducted based on the reading of books, articles, and previous investigations on the phenomenon studied. Considering the interpretation and analysis of the theoretical content obtained through the bibliographic research conducted, this theoretical construction approaches the qualitative approach. We conclude that the deep inequalities between regions and within them, between the provinces studied, originated historically in the form of exploitation of the regions and from the consequences of the war. The asymmetries, observed through the variables studied show that the provinces historically explored and considered object regions present a lower growth compared to those that were considered subject regions in which the applied geopolitical strategy, as they are centers of primary production flows, was different. We also observe that, due to the conflicts of the civil war in the less developed regions, the inequalities have deepened, contributing seriously to a higher level of poverty and a lower development of the provinces where these conflicts took place.

Producción Científica

João Adolfo Catoto Capitango mail , Mirtha Silvana Garat de Marin mail, Emmanuel Soriano Flores mail, Marco Antonio Rojo Gutiérrez mail, Mónica Gracia Villar mail, Frigdiano Álvaro Durántez Prados mail,

Catoto Capitango

<a class="ep_document_link" href="/3480/1/cancers-14-03914-v2.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>



Thyroid Disease Prediction Using Selective Features and Machine Learning Techniques

Thyroid disease prediction has emerged as an important task recently. Despite existing approaches for its diagnosis, often the target is binary classification, the used datasets are small-sized and results are not validated either. Predominantly, existing approaches focus on model optimization and the feature engineering part is less investigated. To overcome these limitations, this study presents an approach that investigates feature engineering for machine learning and deep learning models. Forward feature selection, backward feature elimination, bidirectional feature elimination, and machine learning-based feature selection using extra tree classifiers are adopted. The proposed approach can predict Hashimoto’s thyroiditis (primary hypothyroid), binding protein (increased binding protein), autoimmune thyroiditis (compensated hypothyroid), and non-thyroidal syndrome (NTIS) (concurrent non-thyroidal illness). Extensive experiments show that the extra tree classifier-based selected feature yields the best results with 0.99 accuracy and an F1 score when used with the random forest classifier. Results suggest that the machine learning models are a better choice for thyroid disease detection regarding the provided accuracy and the computational complexity. K-fold cross-validation and performance comparison with existing studies corroborate the superior performance of the proposed approach.

Producción Científica

Rajasekhar Chaganti mail , Furqan Rustam mail , Isabel De La Torre Díez mail , Juan Luis Vidal Mazón mail, Carmen Lilí Rodríguez Velasco mail, Imran Ashraf mail ,


<a href="/3487/1/s41598-022-16916-7.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>



Improvement of energy conservation using blockchain-enabled cognitive wireless networks for smart cities

In Smart Cities’ applications, Multi-node cooperative spectrum sensing (CSS) can boost spectrum sensing efficiency in cognitive wireless networks (CWN), although there is a non-linear interaction among number of nodes and sensing efficiency. Cooperative sensing by nodes with low computational cost is not favorable to improving sensing reliability and diminishes spectrum sensing energy efficiency, which poses obstacles to the regular operation of CWN. To enhance the evaluation and interpretation of nodes and resolves the difficulty of sensor selection in cognitive sensor networks for energy-efficient spectrum sensing. We examined reducing energy usage in smart cities while substantially boosting spectrum detecting accuracy. In optimizing energy effectiveness in spectrum sensing while minimizing complexity, we use the energy detection for spectrum sensing and describe the challenge of sensor selection. This article proposed the algorithm for choosing the sensing nodes while reducing the energy utilization and improving the sensing efficiency. All the information regarding nodes is saved in the fusion center (FC) through which blockchain encrypts the information of nodes ensuring that a node’s trust value conforms to its own without any ambiguity, CWN-FC pick high-performance nodes to engage in CSS. The performance evaluation and computation results shows the comparison between various algorithms with the proposed approach which achieves 10% sensing efficiency in finding the solution for identification and triggering possibilities with the value of α=1.5 and γ=2.5 with the varying number of nodes.

Producción Científica

Shalli Rani mail , Himanshi Babbar mail , Syed Hassan Ahmed Shah mail , Aman Singh mail,