RESUMEN
BACKGROUND: Spinal muscular atrophy (SMA) is a genetic motor neuron disease related to deletions in the SMN1 gene. There is mounting evidence that the disease is not restricted to motor neurons. In this neuroimaging study, we aimed to investigate the presence of in-vivo cerebellar damage in adult SMA patients not treated with disease-modifying treatment. METHODS: Twenty-five molecularly confirmed patients with SMA type III or IV and 25 healthy controls underwent MRI with cerebellar focused structural analysis by the CERES automated pipeline. Volumetry (total and gray matter-GM) as well as cortical thickness of the cerebellar lobules were compared in both groups. Full clinical and demographic data were then assessed for correlations with cerebellar imaging findings. RESULTS: Volumes of cerebellar lobules VIIIB (right), IX and X were significantly smaller in patients with SMA. Lobule IX also had GM atrophy in comparison to controls. We found no significant correlation between clinical findings and cerebellar damage. CONCLUSIONS: Neuroimaging detects cerebellar structural changes in adult SMA patients, suggesting that neurodegeneration is not confined to the lower motor neurons in the disease.
Asunto(s)
Enfermedades Cerebelosas , Atrofia Muscular Espinal , Atrofias Musculares Espinales de la Infancia , Adulto , Cerebelo/diagnóstico por imagen , Humanos , Imagen por Resonancia Magnética , Atrofia Muscular Espinal/diagnóstico por imagenRESUMEN
Spinocerebellar ataxia type 1 is an autosomal dominant disorder caused by a CAG repeat expansion in ATXN1, characterized by progressive cerebellar and extracerebellar symptoms. MRI-based studies in SCA1 focused in the cerebellum and connections, but there are few data about supratentorial/spinal damage and its clinical relevance. We have thus designed this multimodal MRI study to uncover the structural signature of SCA1. To accomplish that, a group of 33 patients and 33 age-and gender-matched healthy controls underwent MRI on a 3T scanner. All patients underwent a comprehensive neurological and neuropsychological evaluation. We correlated the structural findings with the clinical features of the disease. In addition, we evaluated the disease progression looking at differences in SCA1 subgroups defined by disease duration. Ataxia and pyramidal signs were the main symptoms. Neuropsychological evaluation disclosed cognitive impairment in 53% with predominant frontotemporal dysfunction. Gray matter analysis unfolded cortical thinning of primary and associative motor areas with more restricted impairment of deep structures. Deep gray matter atrophy was associated with motor handicap and poor cognition skills. White matter integrity loss was diffuse in the brainstem but restricted in supratentorial structures. Cerebellar cortical thinning was found in multiple areas and correlated not only with motor disability but also with verbal fluency. Spinal cord atrophy correlated with motor handicap. Comparison of MRI findings in disease duration-defined subgroups identified a peculiar pattern of progressive degeneration.
Asunto(s)
Ataxias Espinocerebelosas/diagnóstico por imagen , Adulto , Atrofia , Encéfalo/diagnóstico por imagen , Estudios de Cohortes , Imagen de Difusión Tensora , Progresión de la Enfermedad , Femenino , Sustancia Gris/diagnóstico por imagen , Humanos , Imagen por Resonancia Magnética , Masculino , Persona de Mediana Edad , Pruebas Neuropsicológicas , Tamaño de los Órganos , Fenotipo , Médula Espinal/diagnóstico por imagen , Ataxias Espinocerebelosas/fisiopatología , Ataxias Espinocerebelosas/psicologíaRESUMEN
Simulation models of crops are referred as an efficient complement for the experimental study. Also crop simulation models can be useful for making appropriate decisions on agricultural systems. So this study aimed to simulate the growth of maize under different sowing times and deficit irrigation conditions, using the Decision Support System for Agrotechnology Transfer (DSSAT) model in 2014 year. This study was conducted in the research field of Islamic Azad University of Karaj in 2013 year. The experiment was designed in a split-block with four replications. Treatments included four sowing times of April 30 (S1), May 20 (S2), June 10 (S3), and June 27 (S4) in the main plots and three irrigation levels of 40% available water depletion (W1), 60% available water depletion (W2), and 80% available water depletion in the sub-plots. Root Mean Square Error (RMSE) of grain yield for all four sowing times on three levels of irrigation in Karaj region varied from 581.43 to 1,990.81 kg per hectare. It was also calculated the model efficiency coefficient (d) ranged 0.87-0.98 for the trait. The RMSE of the total dry matter was determined 861.88-2,173.66 kg per hectare; that was while R2 (1:1) of total dry weight varied 0.89-0.98. The results indicate that the model's ability to predict dry matter yield of maize is good enough.
Os modelos de simulação de culturas são referidos como um complemento eficaz para o estudo experimental. Os modelos de simulação de culturas também podem ser úteis para a tomada de decisões adequadas em sistemas agrícolas. Portanto, este estudo teve como objetivo simular o crescimento do milho sob diferentes épocas de semeadura e condições de déficit de irrigação, utilizando o Sistema de Apoio à Decisão para o modelo de Transferência de Agrotecnologia (DSSAT) no ano de 2014. Este estudo foi realizado no campo experimental da Islâmica Azad Universidade de Karaj no ano de 2013. O experimento foi desenvolvido com delineamento em faixas com 4 repetições. Os tratamentos incluíram quatro épocas de semeaduras de 30 de Abril (S1), 20 de maio (S2), 10 de junho (S3), e 27 de junho (S4) nas parcelas principais e três níveis de irrigação de esgotamento de 40% de água disponível (W1), 60% depleção de água disponível (W2), e 80% esgotamento da água disponível nos sub-parcelas. O erro da raiz do quadrado médio (RMSE) do rendimento de grãos para todas as quatro épocas de semeadura nos três níveis de irrigação na região Karaj variou de 581,43 a 1,990,81 kg por hectare. Também foi calculado o coeficiente de eficiência do modelo (d) que variou de 0,87 a 0,98 para a característica. O RMSE da matéria seca total foi determinada entre 861.88 e 2,173.66 kg por hectare; enquanto R2 (1:1) da massa total variou de 0,89 a 0,98. Os resultados indicam que a capacidade do modelo para prever a produção de matéria seca de milho é suficientemente boa.
Asunto(s)
Producción de Cultivos , Zea mays/crecimiento & desarrollo , Riego AgrícolaRESUMEN
A utilização dos computadores na agricultura tem trazido inúmeros benefícios ao empresário rural. Entre tais benefícios, a utilização de programas de computador para simular o crescimento e desenvolvimento de plantas; bem como o seu uso na otimização de práticas culturais, tem se mostrado como uma opção. Objetivou-se, neste trabalho, avaliar o programa CERES-Maize na simulação do florescimento e produção de milho (Zea mays L.), em diferentes cenários de investimento. Os resultados das simulações com o programa CERES-Maize mostraram que as diferenças entre as produções simuladas, comparadas com os dados obtidos em campo, estão entre os limites de 5% a 8% de erro, aceitáveis pelo programa. A mesma tendência foi verificada entre os valores observados e simulados para os dias de florescimento, em todos os cenarios. O programa CERES-Maize mostrou-se bastante robusto e eficiente nas simulações efetuadas. O uso desse programa pode ser visto como uma ferramenta adicional ao produtor no processo decisório, durante o planejamento da implantação da cultura.
The use of computers in agriculture has brought several benefits to the farmers. Among these benefits, the use of crop models to simulate plant growth and development, as well as a tool for optimization process and decision support aid, has been an option. The aim of this study was to evaluate the efficiency of Ceres-Maize model to simulate maize blooming date and yield at different investment scenarios. Simulation results showed that the difference between simulated and observed yield data were in the 5% and 8% error range, acceptable for the program. The same tendency was observed when comparing blooming dates in all scenarios. The model was very efficient and suitable for all of the simulations performed. Without any doubt CERES-Maize may be used as a tool, by farmers, in the crop planning process.