Background Altered tibiofemoral contact mechanics contribute to cartilage degeneration in knee osteoarthritis (OA) and anterior cruciate ligament (ACL) deficiency. Predicting focal cartilage overload is challenging due to biomechanical complexity. Hertzian contact theory, though simplified, provides a physically robust framework to estimate stress distributions from geometry and material properties. Objective To apply Hertzian theory to model tibiofemoral contact pressures and areas in healthy, osteoarthritic, and ACL-deficient knees, and assess its capability to identify patterns linked to cartilage degeneration. Methods A Hertzian-based model was built for three conditions using standardized cartilage properties (E = 10 MPa, ν = 0.45) and representative sagittal radii of curvature. A 700-N vertical load simulated single-leg stance. Peak contact pressure, contact area, and stress patterns were computed. Sensitivity analyses varied modulus, curvature, and load. Outputs were compared qualitatively with anatomical degeneration regions reported in imaging studies. Results Compared with the healthy model (3.21 MPa; 258.3 mm2), OA showed a 26.2 % higher peak pressure and 14.2 % smaller contact area; ACL deficiency showed a 33.3 % increase in peak pressure and 19.3 % reduction in area. OA overload localized medially, ACL deficiency shifted posteriorly. Geometry changes had greater influence on contact mechanics than stiffness or load changes. Conclusions Hertzian theory captures key biomechanical changes in OA and ACL deficiency, identifying clinically relevant overload zones. This simplified approach underscores the dominant role of joint geometry and supports practical biomechanical risk assessment.
Background: Nutritional status assessment is the cornerstone of the Nutrition Care Process, guiding diagnosis, intervention, and monitoring. The classical ABCD model (Anthropometry, Biochemical, Clinical, Dietary) has been widely applied; however, it presents limitations in addressing current nutritional and epidemiological challenges. Objective: This narrative review aims to synthesize and update the scientific evidence on the expanded nutritional assessment model, known as ABCDEFG, which incorporates the Ecological–microbiota (E), Functional (F), and Genomic–nutrigenomic (G) approaches. Methods: A narrative review of the literature was conducted through PubMed, Scopus, and Web of Science, covering publications from 2013 to 2025. Articles were selected based on relevance to at least one of the seven assessment domains. Findings were synthesized descriptively and critically, highlighting applications, strengths, and limitations. Results: The ABCDEFG framework offers a multidimensional perspective of nutritional assessment. While anthropometric, biochemical, clinical, and dietary methods remain essential, the inclusion of ecological dimensions (gut microbiota, environmental influences), functional measures (e.g., muscle strength, physical performance), and genomics enables a more sensitive and personalized evaluation. This integrative approach supports better clinical decision-making and research innovation in nutrition and health sciences. Conclusions: The seven-method model broadens the scope of nutritional assessment, bridging traditional and emerging tools. Its application enhances the capacity to identify nutritional risks, design targeted interventions, and advance precision nutrition.
Este estudio analiza la percepción de estudiantes universitarios sobre el aporte de la Inteligencia Artificial (IA) al desarrollo de iniciativas emprendedoras. Se aplicó un diseño cuantitativo, no experimental y transversal con una muestra intencional de 98 estudiantes de pregrado vinculados a programas de emprendimiento de la Universidad de Guayaquil. Se utilizó un cuestionario tipo Likert (1–5) estructurado en seis dimensiones: infraestructura, capital humano, regulación, participación, adopción y percepción del aporte de la IA. El instrumento evidenció alta consistencia interna (α de Cronbach: infraestructura = .85; capital humano = .88; regulación = .89; participación = .86; adopción = .84; percepción = .91). Los resultados descriptivos muestran acuerdos moderados respecto a que la IA mejora la toma de decisiones y la competitividad, y menor acuerdo con afirmaciones más exigentes (por ejemplo, que el emprendimiento no habría avanzado sin IA). El análisis de regresión múltiple (OLS) indica que la adopción —entendida como uso personal y fomento institucional— es el principal predictor de una valoración positiva de la IA (β = 0.657, p < .01), mientras que las demás dimensiones no resultan significativas cuando se consideran simultáneamente. Se concluye que promover usos cotidianos y experiencias formativas con IA, mediante cursos, talleres y proyectos universidad–empresa, potencia su valoración e impacto en la formación emprendedora.
Pneumonia remains a significant public health concern, particularly in regions with limited access to radiological expertise. This study presents a Convolutional Neural Network model for automatic classification of chest X-ray images into NORMAL and PNEUMONIA categories using the Kaggle Chest X-Ray dataset. The proposed model achieved 87.98
Sport-related concussion (SRC) in children and adolescents presents unique diagnostic challenges due to heterogeneous clinical presentations and rapid neurodevelopmental trajectories. This focused review emphasizes that diagnosis fundamentally relies on symptomatic reporting and objective physiological assessments spanning multiple domains, integrating age-specific tools such as the revised Sport Concussion Assessment Tool 6 (SCAT6) and the Sport Concussion Office Assessment Tool 6 (SCOAT6). While the SCAT6 (ages >13) and Child SCAT6 (ages 8-12) are optimized for acute evaluation within the initial 72 hours, the SCOAT6 framework facilitates comprehensive multidomain assessment during the subacute phase (3-30 days). Clinicians must prioritize visio-vestibular and oculomotor screenings, as dysfunction in these areas is highly prevalent and associated with protracted recovery. For younger children (ages 5-9), the specialized VOMS-Child (VOMS-C) uses developmentally appropriate binary symptom reporting to accurately identify injury. Management paradigms have shifted toward active rehabilitation; the cornerstone of modern care is Sub-Symptom Threshold Aerobic Exercise (STTAE), which, when initiated within 2-10 days post-injury, significantly accelerates recovery. While computerized neurocognitive testing and emerging biomarkers offer insights, clinical decision-making must remain anchored in validated functional assessments while accounting for suboptimal effort in youth populations.
