The expansion of mobile phone technology has raised concerns regarding the effect of 900-MHz electromagnetic field (EMF) exposure on the central nervous system. At present, the developing human brain is regularly exposed to mobile telephones, pre- and postnatally. Several studies have demonstrated the acute effects of EMF exposure during pre- or postnatal periods; however, the chronic effects of EMF exposure are less understood. Thus, the aim of the present study was to determine the chronic effects of EMF on the pre- and postnatal rat cerebellum. The control group was maintained in the same conditions as the experimental groups, without the exposure to EMF. In the EMF1 group, the rats were exposed to EMF during pre- and postnatal periods (until postnatal day 80). In the EMF2 group, the rats were also exposed to EMF pre- and postnatally; in addition, however, they were provided with a daily oral supplementation of Lycopersicon esculentum extract (∼2 g/kg). The number of caspase-3-labeled Purkinje neurons and granule cells present in the rats in the control and experimental groups were then counted. The neurodegenerative changes were studied using cresyl violet staining, and these changes were evaluated. In comparison with the control animals, the EMF1 group demonstrated a significant increase in the number of caspase-3-labeled Purkinje neurons and granule cells present in the cerebellum (P<0.001). However, in comparison with the EMF1 group, the EMF2 group exhibited significantly fewer caspase-3-labeled Purkinje neurons and granule cells in the cerebellum. In the EMF1 group, the Purkinje neurons were revealed to have undergone dark neuron degenerative changes. However, the presence of dark Purkinje neurons was reduced in the EMF2 group, compared with the EMF1 group. The results indicated that apoptosis and neurodegeneration in rats exposed to EMF during pre- and postnatal periods may be reduced with Lycopersicon esculentum extract therapy.
SummaryBackgroundLow back pain (LBP) is a common disease among people under the age of 20. To the best of our knowledge few studies have been carried out on LBP among school children in Turkey, and none of them studied the correlation between pain intensity and related variables with LBP.Material/MethodsThis cross-sectional study was carried out to investigate the risk factors and their correlations with pain intensity among 222 school children (106 girls and 116 boys) aged 10–18 years in the city of Denizli. A self-reported questionnaire was used to collect the data. The regression tree method (RTM) was used to determine the risk factors by using the STATISTICA program package. Pain intensity was the outcome variable, and 8 independent variables (body mass index (BMI), sex, regular exercise habit, studying posture, transportation to/from school, duration of studying, bag handling, and type of bed) were used to detect their effect on pain intensity.ResultsThe results showed that pain intensity is significantly affected by 4 independent variables: duration of studying, type of bed, transportation to/from school, and BMI. The overall mean and standard deviation of pain intensity was 2.58±0.86 (minimum=1, maximum=5).ConclusionsResults from the literature, as well as our study, show that taking parents’ and teachers’ concerns seriously is of vital importance. Our results indicate that parents and teachers should be informed about duration of studying, type of bed, transportation and obesity as risk factors predicting NLBP in school children.
Low back pain (LBP) is one of the common problems encountered in medical applications. This paper proposes two expert systems (artificial neural network and adaptive neuro-fuzzy inference system) for the assessment of the LBP level objectively. The skin resistance and visual analog scale (VAS) values have been accepted as the input variables for the developed systems. The results showed that the expert systems behave very similar to real data and that use of the expert systems can be used to successfully diagnose the back pain intensity. The suggested systems were found to be advantageous approaches in addition to existing unbiased approaches. So far as the authors are aware, this is the first attempt of using the two expert systems achieving very good performance in a real application. In light of some of the limitations of this study, we also identify and discuss several areas that need continued investigation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.