Modeling the gait of normal and Parkinsonian persons for improving the diagnosis

In this study, we present a model for the gait of normal and Parkinson's disease (PD) persons. Gait is semi-periodic and has fractal properties. Sine circle map (SCM) relation has a sinusoidal term and can show chaotic behaviour. Therefore, we used SCM as a basis for our model structure. Moreover, some similarities exist between the parameters of this relation and basal ganglia (BG) structure. This relation can explain the complex behaviours and the complex structure of BG. The presented model can simulate the BG behaviour globally. A model parameter, Ω, has a key role in the model response. We showed that when Ω is between 0.6 and 0.8, the model simulates the behaviour of normal persons; the amounts greater or less than this range correspond to PD persons. Our statistical tests show that there is a significant difference between the Ω of normal and PD patients. We conclude that Ω can be introduced as a parameter to distinguish normal and PD persons. Additionally, our results showed that Spearman correlation between the Ω and the severity of PD is 0.586. This parameter may be a good index of PD severity.     

Design and testing of statistical methods to classify the severity of steppage gait based on center of pressure data

In this research kinematics parameters derived from ground reaction forces were evaluated to limit differential diagnoses and measure the degree of disabilities during walking among neuropathic subjects. 25 neuropathic subjects affected by drop foot and 20 normal subjects were enrolled in the study. Each subject was tested in average 10±2 times for calculating kinetics parameters derived from ground reaction forces. The results revealed that the center of pressure displacement pattern in sole of foot can be a good index for differential diagnoses and measuring the degree of disabilities. This research can extend the clinical applications of ground reaction force plate and introduce suitable criteria to measure the degree of disability among neuropathic patients.     

Acute Poisoning in Children; a Population Study in Isfahan,Iran, 2008-2010

Objective

Acute accidental poisoning in children is still an important public health problem. The epidemiological investigation specific for each country is necessary to determine the extent and characteristics of the problem. The aim of our study was to elucidate the current pattern of acute poisoning among children.

Methods

The present retrospective study describes the epidemiology of acute accidental poisoning in children (less than 10 years old) admitted to the Emergency Department of two teaching hospitals during a period of two years.

Findings

Three hundred and forty four children under 10 years old were admitted to emergency department of two teaching hospitals due to acute accidental poisoning. Drugs were the most common agents causing the poisoning (58.1%), followed by Hydrocarbons (13.1%), and opioids (9.3%). Common signs were neurological (42.6%) with lethargy being the most common (39.1%). 50.6% of cases were discharged from hospital within 6-12 hours, 91.6% of them without any complication.

Conclusion

Accidental poisonings are still a significant cause of morbidity among children in developing countries. Regarding the high prevalence of pharmaceutical drug poisoning and because lethargic was the most frequent neurological sign, comprehensive toxicology screen tests should be included as part of the routine evaluation of children presenting to an ED with an apparent life-threatening event.     

Designing a Decision Support System for Distinguishing ADHD from Similar Children Behavioral Disorders

In this study, a decision support system was designed to distinguish children with ADHD from other similar children behavioral disorders such as depression, anxiety, comorbid depression and anxiety and conduct disorder based on the signs and symptoms. Accuracy of classifying with Radial basis function and multilayer neural networks were compared. Finally, the average accuracy of the networks in classification reached to 95.50% and 96.62% by multilayer and radial basis function networks respectively. Our results indicate that a decision support system, especially RBF, may be a good preliminary assistant for psychiatrists in diagnosing high risk behavioral disorders of children.     

Use of ambulance dispatch data as an early warning system for communitywide influenzalike illness,New York City

In 1998, the New York City Department of Health and the Mayor’s Office of Emergency Management began monitoring the volume of ambulance dispatch calls as a surveillance tool for biologic terrorism. We adapted statistical techniques designed to measure excess influenza mortality and applied them to outbreak detection using ambulance dispatch data. Since 1999, we have been performing serial daily regressions to determine the alarm threshold for the current day. In this article, we evaluate this approach by simulating a series of 2,200 daily regressions. In the influenza detection implementation of this model, there were 71 (3.2%) alarms at the 99% level. Of these alarms, 64 (90%) occurred shortly before or during a period of peak influenza in each of six influenza seasons. In the bioterrorism detection implementation of this methodology, after accounting for current influenza activity, there were 24 (1.1%) alarms at the 99% level. Two occurred during a large snowstorm, 1 is unexplained, and 21 occurred shortly before or during a period of peak influenza activity in each of six influenza seasons. Our findings suggest that this surveillance system is sensitive to communitywide respiratory outbreaks with relatively few false alarms. More work needs to be done to evaluate the sensitivity of this approach for detecting nonrespiratory illness and more localized outbreaks.     

Fully automatic segmentation of multiple sclerosis lesions in brain MR FLAIR images using adaptive mixtures method and Markov random field model

In this paper, an approach is proposed for fully automatic segmentation of MS lesions in fluid attenuated inversion recovery (FLAIR) Magnetic Resonance (MR) images. The proposed approach, based on a Bayesian classifier, utilizes the adaptive mixtures method (AMM) and Markov random field (MRF) model to obtain and upgrade the class conditional probability density function (CCPDF) and the a priori probability of each class. To compare the performance of the proposed approach with those of previous approaches including manual segmentation, the similarity criteria of different slices related to 20 MS patients were calculated. Also, volumetric comparison of lesions volume between the fully automated segmentation and the gold standard was performed using correlation coefficient (CC). The results showed a better performance for the proposed approach, compared to those of previous works.     

Measurement of human and mouse anti-tetanus antibodies and isotype analysis by ELISA

A rapid and sensitive enzyme immunoassay (ELISA) was developed for the quantitation of anti-tetanus antibodies. This technique was used to measure antibody levels in the plasma of immunized donors, in human anti-tetanus IgG preparations and in human and mouse hybridomas producing monoclonal antibodies to tetanus toxoid. The assay was capable of detecting antibody levels as low as 5 X 10(-4) IU/ml. By inclusion of an extra step involving antibodies to mouse Ig isotypes, a sandwich enzyme immunoassay (SEI) was developed which permitted determination of the Ig isotype of mouse anti-tetanus antibodies including tetanus-specific mouse monoclonal antibodies. SEI confirmed Protein A-Sepharose fractionation of mouse ascites fluid containing anti-tetanus antibody. The tetanus toxoid-coated plates have a shelf life of at least 1 year.