Correlação entre o sinal mecanomiográfico e a escala modificada de Ashworth durante avaliação clínica da espasticidade

Spasticity is a common disorder in people who have upper motor neuron injury. The involvement may occur at different levels. The Modified Ashworth Scale (MAS) is the most used method to measure involvement levels. But it corresponds to a subjective evaluation. Mechanomyography (MMG) is an objective technique that quantifies the muscle vibration during the contraction and stretching events. So, it may assess the level of spasticity accurately. This study aimed to investigate the correlation between spasticity levels determined by MAS with MMG signal in spastic and not spastic muscles. In the experimental protocol, we evaluated 34 members of 22 volunteers, of both genders, with a mean age of 39.91 ± 13.77 years. We evaluated the levels of spasticity by MAS in flexor and extensor muscle groups of the knee and/or elbow, where one muscle group was the agonist and one antagonist. Simultaneously the assessment by the MAS, caught up the MMG signals. We used a custom MMG equipment to register and record the signals, configured in LabView platform. Using the MatLab computer program, it was processed the MMG signals in the time domain (median energy) and spectral domain (median frequency) for the three motion axes: X (transversal), Y (longitudinal) and Z (perpendicular). For bandwidth delimitation, we used a 3rd order Butterworth filter, acting in the range of 5-50 Hz. Statistical tests as Spearman's correlation coefficient, Kruskal-Wallis test and linear correlation test were applied. As results in the time domain, the Kruskal-Wallis test showed differences in median energy (MMGME) between MAS groups. The linear correlation test showed high linear correlation between MAS and MMGME for the agonist muscle as well as for the antagonist group. The largest linear correlation occurred between the MAS and MMG ME for the Z axis of the agonist muscle group (R2 = 0.9557) and the lowest correlation occurred in the X axis, for the antagonist muscle group (R2 = 0.8862). The Spearman correlation test also confirmed high correlation for all axes in the time domain analysis. In the spectral domain, the analysis showed an increase in the median frequency (MMGMF) in MAS’ greater levels. The highest correlation coefficient between MAS and MMGMF signal occurred in the Z axis for the agonist muscle group (R2 = 0.4883), and the lowest value occurred on the Y axis for the antagonist group (R2 = 0.1657). By means of the Spearman correlation test, the highest correlation occurred between the Y axis of the agonist group (0.6951; p <0.001) and the lowest value on the X axis of the antagonist group (0.3592; p <0.001). We conclude that there was a significantly high correlation between the MMGME and MAS in both muscle groups. Also between MMG and MAS occurred a significant correlation, however moderate for the agonist group, and low for the antagonist group. So, the MMGME proved to be more an appropriate descriptor to correlate with the degree of spasticity defined by the MAS.

Interação genótipo-ambiente na densidade de gemas e comprimento de ramos de pessegueiro

The instability of environment between years in climates of subtropical regions difficult to obtain peach trees genotypes with wide adaptation and stable production, contributing to poor crop. The climate instability can affect development stages as flower bud and vegetative bud formation. The factors understanding that control the bud formation, presents elementary importance for effective solutions search to these problems. The objective this work is verify the temperature effect, relative humidity and rainfall on bud density and length shoot (Brindilas) and identify genotypes with more adaptability and stability for this character. Was used 12 peach trees genotypes growing in experimental orchard in the Technology Federal of Paraná State University, Campus Pato Branco with Cfa Köppen climate according to the classification. Data of rainfall, hourly temperature were collected by the weather station of Simepar. They were used three plants for genotype (rehearsal), identify five shoots per tree, in May of each year. Were carried analyzes of length shoot CR (cm), count number of flower bud (GF) and vegetative bud (GV). Also calculated the relationship between GF/GV and flower bud density and vegetative bud density. Evaluations were performer annual 2007-2014. With these data adaptability and stability analyzes were performed using Biplot methodology and correlations analyzes (Pearson) with climates variables. They used the weather data to calculate the sums of hours with temperatures below 20 °C, temperatures between 20-25 °C, temperature between 25-30 °C and temperature above 30 °C, considering the period of August 1fst of the previous period to February 28 of the following year. Pearson correlation coefficients were used for path analysis, GF and DGF as basic variables. For CR, GV and GF the highest average occurred in 2009/10 period. The genotypes ‘BRS Kampai’ and ‘BRS Libra’ highest CR. They are considered stable and adapted as the CR genotypes ‘Casc. 967’ and ‘BRS Kampai’. There was negative correlation between CR and GV for Σh <20 ° C, Σh> 30 °C and Σh with URA <50% and positive correlation between these variables and Σh 25-30 °C and Σh with URA> 70%. The evaluation of GV ‘Cons. 681’ and ‘Casc. 1055’ can be considered adapted and stable. The lowest average was presented by the genotype ‘Sta. Áurea’ though the genotype is also stable. In GF evaluation genotypes are considered adapted ‘BRS Bonão’, ‘Casc. 1055’, ‘Cons. 681’ with adaptability to all evaluated period. In path analysis was direct effect Σh 25-30 °C on flower bud density. In evaluating DGV and DGF and the variations are due to genetic effect. The most adapted and stable genotypes for DGV were ‘T. Beauty’, ‘T. Snow’, ‘Casc. 1055’ and ‘Cons. 681’. CR and GV variables are strongly affected by environment. GF is strongly affected by genetic conditions and moderately affected by environment. DGV and DGF are affected basically by genetic conditions.