15 research outputs found

    Aplicación de modelos ecológicos para el análisis de la estructura y dinámica de bosques Ibéricos en respuesta al cambio climático

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    Los modelos son simplificaciones de la realidad, su uso en Ecología permite estudiar patrones y procesos en sistemas naturales complejos de manera objetiva y relativamente sencilla. Los ecosistemas forestales son especialmente complejos de estudiar al estar formados por especies longevas y de gran tamaño, donde la experimentación es difícil. La combinación de modelos y datos observacionales a escalas espaciales regionales y continentales es particularmente útil para analizar patrones y procesos en bosques. La distribución y abundancia de organismos a lo largo del espacio y el tiempo está determinada por factores ambientales, bióticos y antrópicos, como por ejemplo las condiciones climáticas, la competencia inter- e intra-específica, la adaptación local, la plasticidad fenotípica o la gestión forestal. Por lo tanto, para el estudio de la respuesta de los bosques frente al cambio global es aconsejable el uso de modelos que incluyan estos factores de cambio y su efecto en los patrones y procesos observados. De hecho, el uso de modelos apropiadas a escalas regionales supone un paso fundamental para estimar los posibles impactos, la vulnerabilidad de los bosques y establecer prioridades en las estrategias de mitigación y adaptación al cambio climático. En el presente capítulo presentamos brevemente las técnicas más utilizadas para la parametrización de modelos en Ecología, y la aplicación de ciertos modelos para analizar los impactos y la vulnerabilidad de los bosques frente al cambio global. Dentro de las aplicaciones, incluimos desde modelos estadísticos correlacionales para analizar patrones (e.g. Modelos de Distribución de Especies o modelos de procesos demográficos) hasta modelos dinámicos que incorporan procesos demográficos para explicar patrones de distribución. Finalmente, discutimos  el uso de estos modelos como herramientas para el diagnóstico de los impactos del cambio climático sobre los bosques Ibéricos y su importancia para el diseño de estrategias de adaptación

    Brain clocks capture diversity and disparities in aging and dementia

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    Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries). Based on higher-order interactions, we developed a brain-age gap deep learning architecture for functional magnetic resonance imaging (2,953) and electroencephalography (2,353). The datasets comprised healthy controls and individuals with mild cognitive impairment, Alzheimer disease and behavioral variant frontotemporal dementia. LAC models evidenced older brain ages (functional magnetic resonance imaging: mean directional error = 5.60, root mean square error (r.m.s.e.) = 11.91; electroencephalography: mean directional error = 5.34, r.m.s.e. = 9.82) associated with frontoposterior networks compared with non-LAC models. Structural socioeconomic inequality, pollution and health disparities were influential predictors of increased brain-age gaps, especially in LAC (R² = 0.37, F² = 0.59, r.m.s.e. = 6.9). An ascending brain-age gap from healthy controls to mild cognitive impairment to Alzheimer disease was found. In LAC, we observed larger brain-age gaps in females in control and Alzheimer disease groups compared with the respective males. The results were not explained by variations in signal quality, demographics or acquisition methods. These findings provide a quantitative framework capturing the diversity of accelerated brain aging.</p

    Uso de interferon alfa-2b recombinante en Neuropatia Epidemica. Prueba Terapeutica. Pinar del Rio

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    Debido a la existencia de un estado de emergencia nacional, se realizo este estudio motivados por la posible etiologia viral y conociendo los favorables resultados obtenidos con el uso del interferon en diversas entidades virales

    Treatment Delivery Preferences Associated With Type of Mental Disorder and Perceived Treatment Barriers Among Mexican University Students

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    PURPOSE: Although Internet-based electronic health (eHealth) interventions could potentially reduce mental health disparities, especially in college students in under-resourced countries, little is known about the relative acceptability of eHealth versus in-person treatment modalities and the treatment barriers associated with a preference for one type over the other. METHODS: Participants were from the 2018-2019 cohort of the University Project for Healthy Students (PUERTAS), a Web-based survey of incoming first-year students in Mexico and part of the World Mental Health International College Student Survey initiative. A total of 7,849 first-year students, 54.73% female, from five Mexican universities participated. We estimated correlates of preference for eHealth delivery over in-person modalities with a multivariate logistic regression. RESULTS: Thirty-eight percent of students prefer in-person services, 36% showed no preference for in-person over eHealth, 19% prefer not to use services of any kind, and 7% preferred eHealth over in-person treatment delivery. Being embarrassed, worried about harm to one's academic career, wanting to handle problems on one's own, beliefs about treatment efficacy, having depression, and having attention-deficient hyperactivity disorder were associated with a clear preference for eHealth delivery methods with odds ratios ranging from 1.47 to 2.59. CONCLUSIONS: Although more students preferred in-person services over eHealth, those reporting attitudinal barriers (i.e., embarrassment, stigma, wanting to handle problems on one's own, and beliefs about treatment efficacy) and with depression or attention-deficit hyperactivity disorder had a greater preference for eHealth interventions suggesting these are students to whom eHealth interventions could be targeted to alleviate symptoms and/or as a bridge to future in-person treatment.status: publishe
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