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2024

Artículo Materias > Biomedicina
Materias > Ingeniería
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto Inglés Background and objectives: As microbes are developing resistance to antibiotics, natural, botanical drugs or traditional herbal medicine are presently being studied with an eye of great curiosity and hope. Hence, complementary and alternative treatments for uncomplicated pelvic inflammatory disease (uPID) are explored for their efficacy. Therefore, this study determined the therapeutic efficacy and safety of Sesamum indicum Linn seeds with Rosa damascena Mill Oil in uPID with standard control. Additionally, we analyzed the data with machine learning. Materials and methods: We included 60 participants in a double-blind, double-dummy, randomized standard-controlled study. Participants in the Sesame and Rose oil group (SR group) (n = 30) received 14 days course of black sesame powder (5 gm) mixed with rose oil (10 mL) per vaginum at bedtime once daily plus placebo capsules orally. The standard group (SC), received doxycycline 100 mg twice and metronidazole 400 mg thrice orally plus placebo per vaginum for the same duration. The primary outcome was a clinical cure at post-intervention for visual analogue scale (VAS) for lower abdominal pain (LAP), and McCormack pain scale (McPS) for abdominal-pelvic tenderness. The secondary outcome included white blood cells (WBC) cells in the vaginal wet mount test, safety profile, and health-related quality of life assessed by SF-12. In addition, we used AdaBoost (AB), Naïve Bayes (NB), and Decision Tree (DT) classifiers in this study to analyze the experimental data. Results: The clinical cure for LAP and McPS in the SR vs SC group was 82.85% vs 81.48% and 83.85% vs 81.60% on Day 15 respectively. On Day 15, pus cells less than 10 in the SR vs SC group were 86.6% vs 76.6% respectively. No adverse effects were reported in both groups. The improvement in total SF-12 score on Day 30 for the SR vs SC group was 82.79% vs 80.04% respectively. In addition, our Naive Bayes classifier based on the leave-one-out model achieved the maximum accuracy (68.30%) for the classification of both groups of uPID. Conclusion: We concluded that the SR group is cost-effective, safer, and efficacious for curing uPID. Proposed alternative treatment (test drug) could be a substitute of standard drug used for Female genital tract infections. metadata Sumbul, X.; Sultana, Arshiya; Heyat, Md Belal Bin; Rahman, Khaleequr; Akhtar, Faijan; Parveen, Saba; Briones Urbano, Mercedes; Lipari, Vivian; De la Torre Díez, Isabel; Khan, Azmat Ali y Malik, Abdul mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, mercedes.briones@uneatlantico.es, vivian.lipari@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) Efficacy and classification of Sesamum indicum linn seeds with Rosa damascena mill oil in uncomplicated pelvic inflammatory disease using machine learning. Frontiers in Chemistry, 12. ISSN 2296-2646

Artículo Materias > Alimentación Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto Inglés Much of nutrition research has been conventionally based on the use of simplistic in vitro systems or animal models, which have been extensively employed in an effort to better understand the relationships between diet and complex diseases as well as to evaluate food safety. Although these models have undeniably contributed to increase our mechanistic understanding of basic biological processes, they do not adequately model complex human physiopathological phenomena, creating concerns about the translatability to humans. During the last decade, extraordinary advancement in stem cell culturing, three-dimensional cell cultures, sequencing technologies, and computer science has occurred, which has originated a wealth of novel human-based and more physiologically relevant tools. These tools, also known as “new approach methodologies,” which comprise patient-derived organoids, organs-on-chip, multi-omics approach, along with computational models and analysis, represent innovative and exciting tools to forward nutrition research from a human-biology-oriented perspective. After considering some shortcomings of conventional in vitro and vivo approaches, here we describe the main novel available and emerging tools that are appropriate for designing a more human-relevant nutrition research. Our aim is to encourage discussion on the opportunity to explore innovative paths in nutrition research and to promote a paradigm-change toward a more human biology-focused approach to better understand human nutritional pathophysiology, to evaluate novel food products, and to develop more effective targeted preventive or therapeutic strategies while helping in reducing the number and replacing animals employed in nutrition research. metadata Cassotta, Manuela; Cianciosi, Danila; Elexpuru Zabaleta, Maria; Elío Pascual, Iñaki; Sumalla Cano, Sandra; Giampieri, Francesca y Battino, Maurizio mail manucassotta@gmail.com, SIN ESPECIFICAR, maria.elexpuru@uneatlantico.es, inaki.elio@uneatlantico.es, sandra.sumalla@uneatlantico.es, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es (2024) Human‐based new approach methodologies to accelerate advances in nutrition research. Food Frontiers. pp. 1-32. ISSN 2643-8429

Artículo Materias > Biomedicina
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto Inglés Isoflavones are a group of (poly)phenols, also defined as phytoestrogens, with chemical structures comparable with estrogen, that exert weak estrogenic effects. These phytochemical compounds have been targeted for their proven antioxidant and protective effects. Recognizing the increasing prevalence of cardiovascular diseases (CVD), there is a growing interest in understanding the potential cardiovascular benefits associated with these phytochemical compounds. Gut microbiota may play a key role in mediating the effects of isoflavones on vascular and endothelial functions, as it is directly implicated in isoflavones metabolism. The findings from randomized clinical trials indicate that isoflavone supplementation may exert putative effects on vascular biomarkers among healthy individuals, but not among patients affected by cardiometabolic disorders. These results might be explained by the enzymatic transformation to which isoflavones are subjected by the gut microbiota, suggesting that a diverse composition of the microbiota may determine the diverse bioavailability of these compounds. Specifically, the conversion of isoflavones in equol—a microbiota-derived metabolite—seems to differ between individuals. Further studies are needed to clarify the intricate molecular mechanisms behind these contrasting results. metadata Laudani, Samuele; Godos, Justyna; Romano, Giovanni Luca; Gozzo, Lucia; Di Domenico, Federica Martina; Dominguez Azpíroz, Irma; Martínez Díaz, Raquel; Giampieri, Francesca; Quiles, José L.; Battino, Maurizio; Drago, Filippo; Galvano, Fabio y Grosso, Giuseppe mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, irma.dominguez@unini.edu.mx, raquel.martinez@uneatlantico.es, francesca.giampieri@uneatlantico.es, jose.quiles@uneatlantico.es, maurizio.battino@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) Isoflavones Effects on Vascular and Endothelial Outcomes: How Is the Gut Microbiota Involved? Pharmaceuticals, 17 (2). p. 236. ISSN 1424-8247

Artículo Materias > Alimentación Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica
Abierto Inglés The prevalence of sleep disorders, characterized by issues with quality, timing, and sleep duration is increasing globally. Among modifiable risk factors, diet quality has been suggested to influence sleep features. The Mediterranean diet is considered a landmark dietary pattern in terms of quality and effects on human health. However, dietary habits characterized by this cultural heritage should also be considered in the context of overall lifestyle behaviors, including sleep habits. This study aimed to systematically revise the literature relating to adherence to the Mediterranean diet and sleep features in observational studies. The systematic review comprised 23 reports describing the relation between adherence to the Mediterranean diet and different sleep features, including sleep quality, sleep duration, daytime sleepiness, and insomnia symptoms. The majority of the included studies were conducted in the Mediterranean basin and reported a significant association between a higher adherence to the Mediterranean diet and a lower likelihood of having poor sleep quality, inadequate sleep duration, excessive daytime sleepiness or symptoms of insomnia. Interestingly, additional studies conducted outside the Mediterranean basin showed a relationship between the adoption of a Mediterranean-type diet and sleep quality, suggesting that biological mechanisms sustaining such an association may exist. In conclusion, current evidence suggests a relationship between adhering to the Mediterranean diet and overall sleep quality and different sleep parameters. The plausible bidirectional association should be further investigated to understand whether the promotion of a healthy diet could be used as a tool to improve sleep quality. metadata Godos, Justyna; Ferri, Raffaele; Lanza, Giuseppe; Caraci, Filippo; Rojas Vistorte, Angel Olider; Yélamos Torres, Vanessa; Grosso, Giuseppe y Castellano, Sabrina mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, angel.rojas@uneatlantico.es, vanessa.yelamos@funiber.org, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) Mediterranean Diet and Sleep Features: A Systematic Review of Current Evidence. Nutrients, 16 (2). p. 282. ISSN 2072-6643

2023

Otro Materias > Biomedicina
Materias > Ingeniería
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Proyectos I+D+I
Universidad Internacional do Cuanza > Investigación > Proyectos I+D+I
Cerrado Inglés CLINICALSIM is a capability building project targeted to Angola Higher Education Institutions with the aim of improving the practical training of nurses. Nurses are in the focus of health challenges in Angola and they are highly demanded in healthcare, meanwhile their practical competencies are considered as a critical issue. The consortium pursues filling the gap in practical skills (decision-making, interpersonal skills, human nutrition) and promoting HEIs social commitment. We will take advantage of simulation suites and multimedia digital tools to deploy experiential learnings and to promote a Community Service/Service-Learning into the universities. The experiential learning will take place in three different scenarios: simulation suites, digital multimedia and real patients. A reflective practice methodology with a debriefing process will be followed. In the context of Service-Learning, we also introduce the social aim of CLINICALSIM and we appoint special considerations to individuals with socio-economic obstacles and health problems and the promotion of better nutrition habits. CLINICALSIM es un proyecto de desarrollo de capacidades dirigido a las Instituciones de Educación Superior (IES) de Angola con el objetivo de mejorar la formación práctica de los profesionales de la enfermería. Este colectivo se encuentra en el centro de los retos sanitarios en Angola y es muy solicitado en la asistencia sanitaria, mientras que sus competencias prácticas se consideran una cuestión crítica. El consorcio pretende llenar el vacío existente en las habilidades prácticas (toma de decisiones, habilidades interpersonales, nutrición humana) y promover el compromiso social de las IES. Se aprovecharán las suites de simulación y las herramientas digitales multimedia para desplegar aprendizajes experienciales y promover un Servicio Comunitario/Aprendizaje-Servicio en las universidades. El aprendizaje experiencial se llevará a cabo en tres escenarios diferentes: salas de simulación, multimedia digital y pacientes reales, siguiendo una metodología de práctica reflexiva con un proceso de debriefing. En el contexto del Aprendizaje-Servicio, también se introduce el objetivo social de CLINICALSIM y se nombran consideraciones especiales a individuos con obstáculos socioeconómicos y problemas de salud y la promoción de mejores hábitos de nutrición. metadata SIN ESPECIFICAR mail SIN ESPECIFICAR (2023) CLINICALSIM: Clinical simulation practice-based learning in nursing. Repositorio de la Universidad.

Artículo Materias > Alimentación Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto Inglés There is growing evidence that Alzheimer’s disease (AD) can be prevented by reducing risk factors involved in its pathophysiology. Food-derived bioactive molecules can help in the prevention and reduction of the progression of AD. Honey, a good source of antioxidants and bioactive molecules, has been tied to many health benefits, including those from neurological origin. Monofloral avocado honey (AH) has recently been characterized but its biomedical properties are still unknown. The aim of this study is to further its characterization, focusing on the phenolic profile. Moreover, its antioxidant capacity was assayed both in vitro and in vivo. Finally, a deep analysis on the pathophysiological features of AD such as oxidative stress, amyloid-β aggregation, and protein-tau-induced neurotoxicity were evaluated by using the experimental model C. elegans. AH exerted a high antioxidant capacity in vitro and in vivo. No toxicity was found in C. elegans at the dosages used. AH prevented ROS accumulation under AAPH-induced oxidative stress. Additionally, AH exerted a great anti-amyloidogenic capacity, which is relevant from the point of view of AD prevention. AH exacerbated the locomotive impairment in a C. elegans model of tauopathy, although the real contribution of AH remains unclear. The mechanisms under the observed effects might be attributed to an upregulation of daf-16 as well as to a strong ROS scavenging activity. These results increase the interest to study the biomedical applications of AH; however, more research is needed to deepen the mechanisms under the observed effects metadata Romero-Márquez, Jose M.; Navarro-Hortal, María D.; Orantes, Francisco J.; Esteban-Muñoz, Adelaida; Mazas Pérez-Oleaga, Cristina; Battino, Maurizio; Sánchez-González, Cristina; Rivas-García, Lorenzo; Giampieri, Francesca; Quiles, José L. y Forbes-Hernandez, Tamara Y. mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, cristina.mazas@uneatlantico.es, maurizio.battino@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, francesca.giampieri@uneatlantico.es, jose.quiles@uneatlantico.es, tamara.forbes@unini.edu.mx (2023) In Vivo Anti-Alzheimer and Antioxidant Properties of Avocado (Persea americana Mill.) Honey from Southern Spain. Antioxidants, 12 (2). p. 404. ISSN 2076-3921

Artículo Materias > Alimentación Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto Inglés Alzheimer’s Disease (AD) is the cause of around 60–70% of global cases of dementia and approximately 50 million people have been reported to suffer this disease worldwide. The leaves of olive trees (Olea europaea) are the most abundant by-products of the olive grove industry. These by-products have been highlighted due to the wide variety of bioactive compounds such as oleuropein (OLE) and hydroxytyrosol (HT) with demonstrated medicinal properties to fight AD. In particular, the olive leaf (OL), OLE, and HT reduced not only amyloid-β formation but also neurofibrillary tangles formation through amyloid protein precursor processing modulation. Although the isolated olive phytochemicals exerted lower cholinesterase inhibitory activity, OL demonstrated high inhibitory activity in the cholinergic tests evaluated. The mechanisms underlying these protective effects may be associated with decreased neuroinflammation and oxidative stress via NF-κB and Nrf2 modulation, respectively. Despite the limited research, evidence indicates that OL consumption promotes autophagy and restores loss of proteostasis, which was reflected in lower toxic protein aggregation in AD models. Therefore, olive phytochemicals may be a promising tool as an adjuvant in the treatment of AD. metadata Romero-Márquez, Jose M.; Forbes-Hernández, Tamara Y.; Navarro-Hortal, María D.; Quirantes-Piné, Rosa; Grosso, Giuseppe; Giampieri, Francesca; Lipari, Vivian; Sánchez-González, Cristina; Battino, Maurizio y Quiles, José L. mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, francesca.giampieri@uneatlantico.es, vivian.lipari@uneatlantico.es, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es, jose.quiles@uneatlantico.es (2023) Molecular Mechanisms of the Protective Effects of Olive Leaf Polyphenols against Alzheimer’s Disease. International Journal of Molecular Sciences, 24 (5). p. 4353. ISSN 1422-0067

Artículo Materias > Alimentación Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Cerrado Inglés Inflammatory bowel disease (IBD) patients are at substantially higher risk of colorectal cancer (CRC) and IBD-associated CRC accounts for roughly 10-15% of the annual mortality in IBD patients. IBD-related CRC also affects younger patients if compared with sporadic CRC, with a 5-year survival rate of 50%. Regardless of medical therapies, the persistent inflammation 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 disfunction, 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. In addition, in the last years, results from broad epidemiological and experimental studies have associated certain foods or nutritional patterns with the risk of colorectal neoplasia. Here we review the possible role of nutrition in the prevention of IBD-related CRC, focusing specifically on human studies. In conclusion it emerges that nutritional interventions based on healthy, nutrient-dense dietary patterns characterized by a high intake of fiber, vegetables, fruit, Omega-3 PUFAs, and 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. metadata Cassotta, Manuela; Cianciosi, Danila; De Giuseppe, Rachele; Navarro-Hortal, Maria Dolores; Diaz, Yasmany Armas; Forbes-Hernández, Tamara Yuliett; Tutusaus, Kilian; Pascual Barrera, Alina Eugenia; Grosso, Giuseppe; Xiao, Jianbo; Battino, Maurizio y Giampieri, Francesca mail manucassotta@gmail.com, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, kilian.tutusaus@uneatlantico.es, alina.pascual@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es, francesca.giampieri@uneatlantico.es (2023) Possible role of nutrition in the prevention of Inflammatory Bowel Disease-related colorectal cancer: a focus on human studies. Nutrition. p. 111980. ISSN 08999007

Artículo Materias > Biomedicina
Materias > Ingeniería
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Cerrado Inglés Obesity and overweight has increased in the last year and has become a pandemic disease, the result of sedentary lifestyles and unhealthy diets rich in sugars, refined starches, fats and calories. Machine learning (ML) has proven to be very useful in the scientific community, especially in the health sector. With the aim of providing useful tools to help nutritionists and dieticians, research focused on the development of ML and Deep Learning (DL) algorithms and models is searched in the literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol has been used, a very common technique applied to carry out revisions. In our proposal, 17 articles have been filtered in which ML and DL are applied in the prediction of diseases, in the delineation of treatment strategies, in the improvement of personalized nutrition and more. Despite expecting better results with the use of DL, according to the selected investigations, the traditional methods are still the most used and the yields in both cases fluctuate around positive values, conditioned by the databases (transformed in each case) to a greater extent than by the artificial intelligence paradigm used. Conclusions: An important compilation is provided for the literature in this area. ML models are time-consuming to clean data, but (like DL) they allow automatic modeling of large volumes of data which makes them superior to traditional statistics. metadata Ferreras, Antonio; Sumalla Cano, Sandra; Martínez-Licort, Rosmeri; Elío Pascual, Iñaki; Tutusaus, Kilian; Prola, Thomas; Vidal Mazón, Juan Luis; Sahelices, Benjamín y de la Torre Díez, Isabel mail SIN ESPECIFICAR, sandra.sumalla@uneatlantico.es, SIN ESPECIFICAR, inaki.elio@uneatlantico.es, kilian.tutusaus@uneatlantico.es, thomas.prola@uneatlantico.es, juanluis.vidal@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR (2023) Systematic Review of Machine Learning applied to the Prediction of Obesity and Overweight. Journal of Medical Systems, 47 (1). ISSN 1573-689X

2022

Artículo Materias > Alimentación Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Abierto Inglés 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 metadata Gastaldello, Annalisa; Giampieri, Francesca; Quiles, José L.; Navarro-Hortal, María D.; Aparicio Obregón, Silvia; García Villena, Eduardo; Tutusaus, Kilian; De Giuseppe, Rachele; Grosso, Giuseppe; Cianciosi, Danila; Forbes-Hernández, Tamara Y.; Nabavi, Seyed M. y Battino, Maurizio mail SIN ESPECIFICAR, francesca.giampieri@uneatlantico.es, jose.quiles@uneatlantico.es, SIN ESPECIFICAR, silvia.aparicio@uneatlantico.es, eduardo.garcia@uneatlantico.es, kilian.tutusaus@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es (2022) Adherence to the Mediterranean-Style Eating Pattern and Macular Degeneration: A Systematic Review of Observational Studies. Nutrients, 14 (10). p. 2028. ISSN 2072-6643

Revista Materias > Alimentación Universidad Europea del Atlántico > Investigación > Revistas Científicas
Universidad Internacional Iberoamericana México > Investigación > Revistas Científicas
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Revistas Científicas
Universidad Internacional do Cuanza > Investigación > Revistas Científicas
Fundación Universitaria Internacional de Colombia > Investigación > Revistas Científicas
Abierto Inglés La revista MLS Health and Nutrition Research nace como una publicación semestral con el objetivo de publicar artículos originales de investigación y de revisión tanto en áreas básicas como aplicadas y metodológicas que supongan una contribución científica al progreso de cualquier ámbito de la salud y nutrición como objetivo principal. Los artículos incluidos en esta revista se publican en español, portugués e inglés. La vocación internacional de esta revista promueve la difusión del conocimiento en sus diferentes áreas. metadata SIN ESPECIFICAR mail mls@devnull.funiber.org (2022) MLS Health and Nutrition Research. [Revista]

Artículo Materias > Biomedicina
Materias > Alimentación
Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica
Cerrado Inglés Cactus has been used in traditional folk medicine because of its role in treating a number of diseases and conditions. Prickly pear fruit is an excellent source of secondary metabolites (i.e., betalains, flavonoids, and ascorbic acid) with health-promoting properties against many common human diseases, including diabetes, hypertension, hypercholesterolemia, rheumatic pain, gastric mucosa diseases and asthma. In addition, prickly pears are potential candidates for the development of low-cost functional foods because they grow with low water requirements in arid regions of the world. This review describes the main bioactive compounds found in this fruit and shows the in vitro and some clinical studies about the fruit of most important cactus (Opuntia ficus-indica) and its relationship with some chronic diseases. Even though a lot of effort have been done to study the relationship between this fruit and the human health, more studies on Opuntia ficus-indica could help better understand its pharmacological mechanism of action to provide clear scientific evidence to explain its traditional uses, and to identify its therapeutic potential in other diseases. metadata Armas Diaz, Yasmany; Machì, Michele; Salinari, Alessia; Mazas Pérez-Oleaga, Cristina; Martínez López, Nohora Milena; Briones Urbano, Mercedes y Cianciosi, Danila mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, cristina.mazas@uneatlantico.es, nohora.martinez@uneatlantico.es, mercedes.briones@uneatlantico.es, SIN ESPECIFICAR (2022) Prickly pear fruits from "Opuntia ficus-indica" varieties as a source of potential bioactive compounds in the Mediterranean diet. Mediterranean Journal of Nutrition and Metabolism, 15 (4). pp. 581-592. ISSN 1973798X

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Efficacy and classification of Sesamum indicum linn seeds with Rosa damascena mill oil in uncomplicated pelvic inflammatory disease using machine learning

Background and objectives: As microbes are developing resistance to antibiotics, natural, botanical drugs or traditional herbal medicine are presently being studied with an eye of great curiosity and hope. Hence, complementary and alternative treatments for uncomplicated pelvic inflammatory disease (uPID) are explored for their efficacy. Therefore, this study determined the therapeutic efficacy and safety of Sesamum indicum Linn seeds with Rosa damascena Mill Oil in uPID with standard control. Additionally, we analyzed the data with machine learning. Materials and methods: We included 60 participants in a double-blind, double-dummy, randomized standard-controlled study. Participants in the Sesame and Rose oil group (SR group) (n = 30) received 14 days course of black sesame powder (5 gm) mixed with rose oil (10 mL) per vaginum at bedtime once daily plus placebo capsules orally. The standard group (SC), received doxycycline 100 mg twice and metronidazole 400 mg thrice orally plus placebo per vaginum for the same duration. The primary outcome was a clinical cure at post-intervention for visual analogue scale (VAS) for lower abdominal pain (LAP), and McCormack pain scale (McPS) for abdominal-pelvic tenderness. The secondary outcome included white blood cells (WBC) cells in the vaginal wet mount test, safety profile, and health-related quality of life assessed by SF-12. In addition, we used AdaBoost (AB), Naïve Bayes (NB), and Decision Tree (DT) classifiers in this study to analyze the experimental data. Results: The clinical cure for LAP and McPS in the SR vs SC group was 82.85% vs 81.48% and 83.85% vs 81.60% on Day 15 respectively. On Day 15, pus cells less than 10 in the SR vs SC group were 86.6% vs 76.6% respectively. No adverse effects were reported in both groups. The improvement in total SF-12 score on Day 30 for the SR vs SC group was 82.79% vs 80.04% respectively. In addition, our Naive Bayes classifier based on the leave-one-out model achieved the maximum accuracy (68.30%) for the classification of both groups of uPID. Conclusion: We concluded that the SR group is cost-effective, safer, and efficacious for curing uPID. Proposed alternative treatment (test drug) could be a substitute of standard drug used for Female genital tract infections.

Producción Científica

X. Sumbul mail , Arshiya Sultana mail , Md Belal Bin Heyat mail , Khaleequr Rahman mail , Faijan Akhtar mail , Saba Parveen mail , Mercedes Briones Urbano mail mercedes.briones@uneatlantico.es, Vivian Lipari mail vivian.lipari@uneatlantico.es, Isabel De la Torre Díez mail , Azmat Ali Khan mail , Abdul Malik mail ,

Sumbul

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Adaptive neighborhood rough set model for hybrid data processing: a case study on Parkinson’s disease behavioral analysis

Extracting knowledge from hybrid data, comprising both categorical and numerical data, poses significant challenges due to the inherent difficulty in preserving information and practical meanings during the conversion process. To address this challenge, hybrid data processing methods, combining complementary rough sets, have emerged as a promising approach for handling uncertainty. However, selecting an appropriate model and effectively utilizing it in data mining requires a thorough qualitative and quantitative comparison of existing hybrid data processing models. This research aims to contribute to the analysis of hybrid data processing models based on neighborhood rough sets by investigating the inherent relationships among these models. We propose a generic neighborhood rough set-based hybrid model specifically designed for processing hybrid data, thereby enhancing the efficacy of the data mining process without resorting to discretization and avoiding information loss or practical meaning degradation in datasets. The proposed scheme dynamically adapts the threshold value for the neighborhood approximation space according to the characteristics of the given datasets, ensuring optimal performance without sacrificing accuracy. To evaluate the effectiveness of the proposed scheme, we develop a testbed tailored for Parkinson’s patients, a domain where hybrid data processing is particularly relevant. The experimental results demonstrate that the proposed scheme consistently outperforms existing schemes in adaptively handling both numerical and categorical data, achieving an impressive accuracy of 95% on the Parkinson’s dataset. Overall, this research contributes to advancing hybrid data processing techniques by providing a robust and adaptive solution that addresses the challenges associated with handling hybrid data, particularly in the context of Parkinson’s disease analysis.

Producción Científica

Imran Raza mail , Muhammad Hasan Jamal mail , Rizwan Qureshi mail , Abdul Karim Shahid mail , Angel Olider Rojas Vistorte mail angel.rojas@uneatlantico.es, Md Abdus Samad mail , Imran Ashraf mail ,

Raza

<a href="/11265/1/Food%20Frontiers%20-%202024%20-%20Cassotta%20-%20Human%E2%80%90based%20new%20approach%20methodologies%20to%20accelerate%20advances%20in%20nutrition%20research.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

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Human‐based new approach methodologies to accelerate advances in nutrition research

Much of nutrition research has been conventionally based on the use of simplistic in vitro systems or animal models, which have been extensively employed in an effort to better understand the relationships between diet and complex diseases as well as to evaluate food safety. Although these models have undeniably contributed to increase our mechanistic understanding of basic biological processes, they do not adequately model complex human physiopathological phenomena, creating concerns about the translatability to humans. During the last decade, extraordinary advancement in stem cell culturing, three-dimensional cell cultures, sequencing technologies, and computer science has occurred, which has originated a wealth of novel human-based and more physiologically relevant tools. These tools, also known as “new approach methodologies,” which comprise patient-derived organoids, organs-on-chip, multi-omics approach, along with computational models and analysis, represent innovative and exciting tools to forward nutrition research from a human-biology-oriented perspective. After considering some shortcomings of conventional in vitro and vivo approaches, here we describe the main novel available and emerging tools that are appropriate for designing a more human-relevant nutrition research. Our aim is to encourage discussion on the opportunity to explore innovative paths in nutrition research and to promote a paradigm-change toward a more human biology-focused approach to better understand human nutritional pathophysiology, to evaluate novel food products, and to develop more effective targeted preventive or therapeutic strategies while helping in reducing the number and replacing animals employed in nutrition research.

Producción Científica

Manuela Cassotta mail manucassotta@gmail.com, Danila Cianciosi mail , Maria Elexpuru Zabaleta mail maria.elexpuru@uneatlantico.es, Iñaki Elío Pascual mail inaki.elio@uneatlantico.es, Sandra Sumalla Cano mail sandra.sumalla@uneatlantico.es, Francesca Giampieri mail francesca.giampieri@uneatlantico.es, Maurizio Battino mail maurizio.battino@uneatlantico.es,

Cassotta

<a href="/11322/1/journal.pone.0298582.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

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Design and development of patient health tracking, monitoring and big data storage using Internet of Things and real time cloud computing

With the outbreak of the COVID-19 pandemic, social isolation and quarantine have become commonplace across the world. IoT health monitoring solutions eliminate the need for regular doctor visits and interactions among patients and medical personnel. Many patients in wards or intensive care units require continuous monitoring of their health. Continuous patient monitoring is a hectic practice in hospitals with limited staff; in a pandemic situation like COVID-19, it becomes much more difficult practice when hospitals are working at full capacity and there is still a risk of medical workers being infected. In this study, we propose an Internet of Things (IoT)-based patient health monitoring system that collects real-time data on important health indicators such as pulse rate, blood oxygen saturation, and body temperature but can be expanded to include more parameters. Our system is comprised of a hardware component that collects and transmits data from sensors to a cloud-based storage system, where it can be accessed and analyzed by healthcare specialists. The ESP-32 microcontroller interfaces with the multiple sensors and wirelessly transmits the collected data to the cloud storage system. A pulse oximeter is utilized in our system to measure blood oxygen saturation and body temperature, as well as a heart rate monitor to measure pulse rate. A web-based interface is also implemented, allowing healthcare practitioners to access and visualize the collected data in real-time, making remote patient monitoring easier. Overall, our IoT-based patient health monitoring system represents a significant advancement in remote patient monitoring, allowing healthcare practitioners to access real-time data on important health metrics and detect potential health issues before they escalate.

Producción Científica

Md. Milon Islam mail , Imran Shafi mail , Sadia Din mail , Siddique Farooq mail , Isabel de la Torre Díez mail , Jose Breñosa mail josemanuel.brenosa@uneatlantico.es, Julio César Martínez Espinosa mail ulio.martinez@unini.edu.mx, Imran Ashraf mail ,

Islam

<a href="/11666/1/Pneumonia_Detection_Using_Chest_Radiographs_With_Novel_EfficientNetV2L_Model.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

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Pneumonia Detection Using Chest Radiographs With Novel EfficientNetV2L Model

Pneumonia is a potentially life-threatening infectious disease that is typically diagnosed through physical examinations and diagnostic imaging techniques such as chest X-rays, ultrasounds or lung biopsies. Accurate diagnosis is crucial as wrong diagnosis, inadequate treatment or lack of treatment can cause serious consequences for patients and may become fatal. The advancements in deep learning have significantly contributed to aiding medical experts in diagnosing pneumonia by assisting in their decision-making process. By leveraging deep learning models, healthcare professionals can enhance diagnostic accuracy and make informed treatment decisions for patients suspected of having pneumonia. In this study, six deep learning models including CNN, InceptionResNetV2, Xception, VGG16, ResNet50 and EfficientNetV2L are implemented and evaluated. The study also incorporates the Adam optimizer, which effectively adjusts the epoch for all the models. The models are trained on a dataset of 5856 chest X-ray images and show 87.78%, 88.94%, 90.7%, 91.66%, 87.98% and 94.02% accuracy for CNN, InceptionResNetV2, Xception, VGG16, ResNet50 and EfficientNetV2L, respectively. Notably, EfficientNetV2L demonstrates the highest accuracy and proves its robustness for pneumonia detection. These findings highlight the potential of deep learning models in accurately detecting and predicting pneumonia based on chest X-ray images, providing valuable support in clinical decision-making and improving patient treatment.

Producción Científica

Mudasir Ali mail , Mobeen Shahroz mail , Urooj Akram mail , Muhammad Faheem Mushtaq mail , Stefanía Carvajal-Altamiranda mail stefania.carvajal@uneatlantico.es, Silvia Aparicio Obregón mail silvia.aparicio@uneatlantico.es, Isabel De La Torre Díez mail , Imran Ashraf mail ,

Ali