Miradas colectivas del departamento de Bolívar y Sucre, municipios Cartagena, Magangué, Corozal, San Benito y Morroa

Estas investigaciones surgen de las necesidades de conocer las problemáticas por las cuales atraviesan las diferentes comunidades en donde se desarrolló los diferentes proyectos, en los escenarios educativo y familiares en los departamentos de Sucre y Bolívar comprendido en los municipios de Cartagena, Magangue, Corozal, San Benito y Morroa, en las cuales se realizó el diagnóstico, mediante las técnicas de observación participante, entrevista semiestructurada, narraciones, diarios de campo árbol de problemas, y relatos de las experiencias o vivencias familiares. Teniendo diferentes resultados e identificando las diferentes problemáticas entre ellas Bajo rendimiento escolar, violencia intrafamiliar, falta de habilidades sociales y falta de oportunidades laborales (desempleo). Esta investigación nos llevó a realizar unas estrategias para disminuir dichas problemáticas así estas comunidades intervenidas puedan tener una perspectiva diferentes de supervivencia, dentro de su entorno con miras a cambiar su calidad de vida y por ende de sus generaciones con mentalidades emprendedoras y creativas, creyendo que los seres humanos tenemos capacidades para iniciar un proceso de mejoramiento que nos conlleve a un buen desarrollo, tanto económicos como psicosociales.These investigations arise from the needs of knowing the problems that cross the different communities where the different projects were developed, in the educational and family settings in the departments of Sucre and Bolivar, included in the municipalities of Cartagena, Magangue, Corozal, San Benito and Morroa, in which the diagnosis was made, through the techniques of participant observation, semi-structured interview, narratives, field diaries, problem tree, and stories of family experiences or experiences. Having different results and identifying the different problems among them Low school performance, intrafamily violence, lack of social skills and lack of job opportunities (unemployment). This research led us to carry out strategies to reduce these problems so that these intervened communities may have a different perspective of survival, within their environment with a view to changing their quality of life and therefore of their generations with entrepreneurial and creative mentalities, believing that Human beings have the capacity to initiate a process of improvement that leads to a good development, both economic and psychosocial

QUANTIFICATION OF NORMAL BRAIN AGING USING FULLY DEFORMABLE REGISTRATION

Over the next twenty-five years, the proportion of the population over age 65 will increase 76%; therefore understanding both the normal and pathological processes involved in the aging of the human brain is of the highest public health priority. We report here the use of a computational method that provides estimates of the “brain age” of individuals that is based solely on a high resolution Magnetic Resonance Image (MRI) of the brain of the individual, and is blinded to his or her true chronological age. The method proceeds in two phases: first, a statistical learning algorithm is used to determine the numerical MRI-based features that predict true age on a training set of 198 healthy elderly individuals; second, these features are used to predict the true age of previously-unseen individuals. In cross-validation experiments, the brain age estimates differed from true age by a mean absolute error of 5.35 years in an elderly cohort, reflecting the broad heterogeneity in structural integrity of the elderly brain. The “brain age” of female subjects was significantly lower than that of male subjects who had the same true age (3.0 years younger for 50-year-olds and 1.6 years younger for 79 year olds), reflecting the longer life expectancy of females. Across the elderly age spectrum, the “brain age” of individuals with Alzheimer's Disease (AD) was significantly higher than that of cognitively-healthy elderly subjects with equivalent true age; however, this was not the case for the subjects with mild cognitive impairment (MCI), a possible AD prodrome

Medial prefrontal cortex serotonin 1A and 2A receptor binding interacts to predict threat-related amygdala reactivity

Background\ud The amygdala and medial prefrontal cortex (mPFC) comprise a key corticolimbic circuit that helps shape individual differences in sensitivity to threat and the related risk for psychopathology. Although serotonin (5-HT) is known to be a key modulator of this circuit, the specific receptors mediating this modulation are unclear. The colocalization of 5-HT1A and 5-HT2A receptors on mPFC glutamatergic neurons suggests that their functional interactions may mediate 5-HT effects on this circuit through top-down regulation of amygdala reactivity. Using a multimodal neuroimaging strategy in 39 healthy volunteers, we determined whether threat-related amygdala reactivity, assessed with blood oxygen level-dependent functional magnetic resonance imaging, was significantly predicted by the interaction between mPFC 5-HT1A and 5-HT2A receptor levels, assessed by positron emission tomography.\ud \ud Results\ud 5-HT1A binding in the mPFC significantly moderated an inverse correlation between mPFC 5-HT2A binding and threat-related amygdala reactivity. Specifically, mPFC 5-HT2A binding was significantly inversely correlated with amygdala reactivity only when mPFC 5-HT1A binding was relatively low.\ud \ud Conclusions\ud Our findings provide evidence that 5-HT1A and 5-HT2A receptors interact to shape serotonergic modulation of a functional circuit between the amygdala and mPFC. The effect of the interaction between mPFC 5-HT1A and 5-HT2A binding and amygdala reactivity is consistent with the colocalization of these receptors on glutamatergic neurons in the mPFC

Atlas-based hippocampus segmentation in Alzheimer's disease and mild cognitive impairment.

This study assesses the performance of public-domain automated methodologies for MRI-based segmentation of the hippocampus in elderly subjects with Alzheimer's disease (AD) and mild cognitive impairment (MCI). Structural MR images of 54 age- and gender-matched healthy elderly individuals, subjects with probable AD, and subjects with MCI were collected at the University of Pittsburgh Alzheimer's Disease Research Center. Hippocampi in subject images were automatically segmented by using AIR, SPM, FLIRT, and the fully deformable method of Chen to align the images to the Harvard atlas, MNI atlas, and randomly selected, manually labeled subject images ("cohort atlases"). Mixed-effects statistical models analyzed the effects of side of the brain, disease state, registration method, choice of atlas, and manual tracing protocol on the spatial overlap between automated segmentations and expert manual segmentations. Registration methods that produced higher degrees of geometric deformation produced automated segmentations with higher agreement with manual segmentations. Side of the brain, presence of AD, choice of reference image, and manual tracing protocol were also significant factors contributing to automated segmentation performance. Fully automated techniques can be competitive with human raters on this difficult segmentation task, but a rigorous statistical analysis shows that a variety of methodological factors must be carefully considered to insure that automated methods perform well in practice. The use of fully deformable registration methods, cohort atlases, and user-defined manual tracings are recommended for highest performance in fully automated hippocampus segmentation