226 resultados para Diagnosis Dual Psychiatry


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Catechol-O-methyl transferase (COMT) encodes an enzyme involved in the metabolism of dopamine and maps to a commonly deleted region that increases schizophrenia risk. A non-synonymous polymorphism (rs4680) in COMT has been previously found to be associated with schizophrenia and results in altered activity levels of COMT. Using a haplotype block-based gene-tagging approach we conducted an association study of seven COMT single nucleotide polymorphisms (SNPs) in 160 patients with a DSM-IV diagnosis of schizophrenia and 250 controls in an Australian population. Two polymorphisms including rs4680 and rs165774 were found to be significantly associated with schizophrenia. The rs4680 results in a Val/Met substitution but the strongest association was shown by the novel SNP, rs165774, which may still be functional even though it is located in intron five. Individuals with schizophrenia were more than twice as likely to carry the GG genotype compared to the AA genotype for both the rs165774 and rs4680 SNPs. This association was slightly improved when males were analysed separately possibly indicating a degree of sexual dimorphism. Our results confirm that COMT is a good candidate for schizophrenia risk, by replicating the association with rs4680 and identifying a novel SNP association.

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There is an urgent need to develop safe, effective, dual-purpose contraceptive agents that combine the prevention of pregnancy with protection against sexually transmitted diseases. Here we report the identification of a group of compounds that on contact with human spermatozoa induce a state of “spermostasis,” characterized by the extremely rapid inhibition of sperm movement without compromising cell viability. These spermostatic agents were more active and significantly less toxic than the reagent in current clinical use, nonoxynol 9, giving therapeutic indices (ratio of spermostatic to cytotoxic activity) that were orders of magnitude greater than this traditional spermicide. Although certain compounds could trigger reactive oxygen species generation by spermatozoa, this activity was not correlated with spermostasis. Rather, the latter was associated with alkylation of two major sperm tail proteins that were identified as A Kinase-Anchoring Proteins (AKAP3 and AKAP4) by mass spectrometry. As a consequence of disrupted AKAP function, the abilities of cAMP to drive protein kinase A-dependent activities in the sperm tail, such as the activation of SRC and the consequent stimulation of tyrosine phosphorylation, were suppressed. Furthermore, analysis of microbicidal activity using Chlamydia muridarum revealed powerful inhibitory effects at the same low micromolar doses that suppressed sperm movement. In this case, the microbicidal action was associated with alkylation of Major Outer Membrane Protein (MOMP), a major chlamydial membrane protein. Taken together, these results have identified for the first time a novel set of cellular targets and chemical principles capable of providing simultaneous defense against both fertility and the spread of sexually transmitted disease.

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This paper presents a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees. Classification and regression tree (CART) which is one of the decision tree methods is used as a feature selection procedure to select pertinent features from data set. The crisp rules obtained from the decision tree are then converted to fuzzy if-then rules that are employed to identify the structure of ANFIS classifier. The hybrid of back-propagation and least squares algorithm are utilized to tune the parameters of the membership functions. In order to evaluate the proposed algorithm, the data sets obtained from vibration signals and current signals of the induction motors are used. The results indicate that the CART–ANFIS model has potential for fault diagnosis of induction motors.

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The Electrocardiogram (ECG) is an important bio-signal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. The HRV signal can be used as a base signal to observe the heart's functioning. These signals are non-linear and non-stationary in nature. So, higher order spectral (HOS) analysis, which is more suitable for non-linear systems and is robust to noise, was used. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, we have extracted seven features from the heart rate signals using HOS and fed them to a support vector machine (SVM) for classification. Our performance evaluation protocol uses 330 subjects consisting of five different kinds of cardiac disease conditions. We demonstrate a sensitivity of 90% for the classifier with a specificity of 87.93%. Our system is ready to run on larger data sets.