Project Design and Management

<a href="/26722/1/nutrients-18-00257.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

en

open

Innovative Application of Chatbots in Clinical Nutrition Education: The E+DIEting_Lab Experience in University Students

Background/Objectives: The growing integration of Artificial Intelligence (AI) and chatbots in health professional education offers innovative methods to enhance learning and clinical preparedness. This study aimed to evaluate the educational impact and perceptions in university students of Human Nutrition and Dietetics, regarding the utility, usability, and design of the E+DIEting_Lab chatbot platform when implemented in clinical nutrition training. Methods: The platform was piloted from December 2023 to April 2025 involving 475 students from multiple European universities. While all 475 students completed the initial survey, 305 finished the follow-up evaluation, representing a 36% attrition rate. Participants completed surveys before and after interacting with the chatbots, assessing prior experience, knowledge, skills, and attitudes. Data were analyzed using descriptive statistics and independent samples t-tests to compare pre- and post-intervention perceptions. Results: A total of 475 university students completed the initial survey and 305 the final evaluation. Most university students were females (75.4%), with representation from six languages and diverse institutions. Students reported clear perceived learning gains: 79.7% reported updated practical skills in clinical dietetics and communication were updated, 90% felt that new digital tools improved classroom practice, and 73.9% reported enhanced interpersonal skills. Self-rated competence in using chatbots as learning tools increased significantly, with mean knowledge scores rising from 2.32 to 2.66 and skills from 2.39 to 2.79 on a 0–5 Likert scale (p < 0.001 for both). Perceived effectiveness and usefulness of chatbots as self-learning tools remained positive but showed a small decline after use (effectiveness from 3.63 to 3.42; usefulness from 3.63 to 3.45), suggesting that hands-on experience refined, but did not diminish, students’ overall favorable views of the platform. Conclusions: The implementation and pilot evaluation of the E+DIEting_Lab self-learning virtual patient chatbot platform demonstrate that structured digital simulation tools can significantly improve perceived clinical nutrition competences. These findings support chatbot adoption in dietetics curricula and inform future digital education innovations.

Producción Científica

Iñaki Elío Pascual mail inaki.elio@uneatlantico.es, Kilian Tutusaus mail kilian.tutusaus@uneatlantico.es, Imanol Eguren García mail imanol.eguren@uneatlantico.es, Álvaro Lasarte García mail , Arturo Ortega-Mansilla mail arturo.ortega@uneatlantico.es, Thomas Prola mail thomas.prola@uneatlantico.es, Sandra Sumalla Cano mail sandra.sumalla@uneatlantico.es,

Elío Pascual

<a class="ep_document_link" href="/26964/1/s44196-025-01123-9_reference.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

en

open

Suicide Ideation Detection Using Social Media Data and Ensemble Machine Learning Model

Identifying the emotional state of individuals has useful applications, particularly to reduce the risk of suicide. Users’ thoughts on social media platforms can be used to find cues on the emotional state of individuals. Clinical approaches to suicide ideation detection primarily rely on evaluation by psychologists, medical experts, etc., which is time-consuming and requires medical expertise. Machine learning approaches have shown potential in automating suicide detection. In this regard, this study presents a soft voting ensemble model (SVEM) by leveraging random forest, logistic regression, and stochastic gradient descent classifiers using soft voting. In addition, for the robust training of SVEM, a hybrid feature engineering approach is proposed that combines term frequency-inverse document frequency and the bag of words. For experimental evaluation, “Suicide Watch” and “Depression” subreddits on the Reddit platform are used. Results indicate that the proposed SVEM model achieves an accuracy of 94%, better than existing approaches. The model also shows robust performance concerning precision, recall, and F1, each with a 0.93 score. ERT and deep learning models are also used, and performance comparison with these models indicates better performance of the SVEM model. Gated recurrent unit, long short-term memory, and recurrent neural network have an accuracy of 92% while the convolutional neural network obtains an accuracy of 91%. SVEM’s computational complexity is also low compared to deep learning models. Further, this study highlights the importance of explainability in healthcare applications such as suicidal ideation detection, where the use of LIME provides valuable insights into the contribution of different features. In addition, k-fold cross-validation further validates the performance of the proposed approach.

Producción Científica

Erol KINA mail , Jin-Ghoo Choi mail , Abid Ishaq mail , Rahman Shafique mail , Mónica Gracia Villar mail monica.gracia@uneatlantico.es, Eduardo René Silva Alvarado mail eduardo.silva@funiber.org, Isabel de la Torre Diez mail , Imran Ashraf mail ,

KINA

<a href="/26965/1/s40203-025-00539-7.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

en

open

In silico prediction, molecular docking and simulation of natural flavonoid apigenin and xanthoangelol E against human metapneumovirus

Human metapneumovirus (hMPV) is one of the potential pandemic pathogens, and it is a concern for elderly subjects and immunocompromised patients. There is no vaccine or specific antiviral available for hMPV. We conducted an in-silico study to predict initial antiviral candidates against human metapneumovirus. Our methodology included protein modeling, stability assessment, molecular docking, molecular simulation, analysis of non-covalent interactions, bioavailability, carcinogenicity, and pharmacokinetic profiling. We pinpointed four plant-derived bio-compounds as antiviral candidates. Among the compounds, apigenin showed the highest binding affinity, with values of − 8.0 kcal/mol for the hMPV-F protein and − 7.6 kcal/mol for the hMPV-N protein. Molecular dynamic simulations and further analyses confirmed that the protein-ligand docked complexes exhibited acceptable stability compared to two standard antiviral drugs. Additionally, these four compounds yielded satisfactory outcomes in bioavailability, drug-likeness, and ADME-Tox (absorption, distribution, metabolism, excretion, and toxicity) and STopTox analyses. This study highlights the potential of apigenin and xanthoangelol E as an initial antiviral candidate, underscoring the necessity for wet-lab evaluation, preclinical and clinical trials against human metapneumovirus infection.

Producción Científica

Hasan Huzayfa Rahaman mail , Afsana Khan mail , Nadim Sharif mail , Wasifuddin Ahmed mail , Nazmul Sharif mail , Rista Majumder mail , Silvia Aparicio Obregón mail silvia.aparicio@uneatlantico.es, Rubén Calderón Iglesias mail ruben.calderon@uneatlantico.es, Isabel De la Torre Díez mail , Shuvra Kanti Dey mail ,

Rahaman

es

close

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

Este 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.

Producción Científica

José Rubén Martínez Martínez mail , Juan Luis Martín Ayala mail juan.martin@uneatlantico.es,

Martínez Martínez

<a href="/26848/1/nutrients-17-03853.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

en

open

Yerba Mate (Ilex paraguariensis) and Rheumatoid Arthritis: A Systematic Review of Mechanistic and Clinical Evidence

Background: Rheumatoid arthritis (RA) is a chronic autoimmune disease driven by persistent inflammation and oxidative stress. Ilex paraguariensis (yerba mate) contains bioactive compounds—particularly chlorogenic acids, quercetin, and rutin—with documented antioxidant and anti-inflammatory properties. Objectives: To systematically review the mechanistic and clinical evidence on Ilex paraguariensis and its main constituents in RA-relevant inflammatory, oxidative, and bone metabolic pathways. Methods: Following PRISMA 2020, PubMed/MEDLINE, LILACS, and SciELO were searched up to September 2025. Eligible studies included yerba mate preparations (last 10 years) or isolated compounds (last 5 years) assessing RA-relevant clinical, inflammatory, oxidative, or bone metabolic outcomes. Non-original studies were excluded. Owing to heterogeneity, findings were narratively synthesized, and risk of bias was evaluated using RoB 2, ROBINS-I, OHAT, and SYRCLE. Results: Twenty-three studies met inclusion criteria: 11 human (clinical or observational), 7 human-based in vitro, and 5 animal studies. Interventions with yerba mate infusions or standardized extracts suggest reductions in inflammatory markers (e.g., C-reactive protein, interleukin-6) and indicate improvements in glutathione-related oxidative balance. Evidence from isolated compounds, particularly quercetin and rutin, suggests comparable anti-inflammatory and antioxidant effects. Preclinical studies appear to indicate modulation of inflammatory and redox pathways relevant to RA. Conclusions: Yerba mate and its constituents show preliminary indications of anti-inflammatory and antioxidant effects with potential relevance to RA pathophysiology. However, in the absence of clinical trials in RA patients, conclusions remain tentative, constrained by small sample sizes, methodological heterogeneity, species differences, and internal validity concerns. Future research should include rigorously designed randomized trials and mechanistic studies using advanced human-relevant platforms, such as organoids and organ-on-chip systems.

Producción Científica

Manuela Cassotta mail manucassotta@gmail.com, Qingwei Cao mail , Haixia Hu mail , Carlos Rabeiro Martinez mail , Luis Alonso Dzul López mail luis.dzul@uneatlantico.es, Santos Gracia Villar mail santos.gracia@uneatlantico.es, Maurizio Battino mail maurizio.battino@uneatlantico.es, Francesca Giampieri mail francesca.giampieri@uneatlantico.es,

Cassotta