Reduced sympathetic innervation after alteration of target cell neurotransmitter phenotype in transgenic mice.

Neurotransmitters play a variety of important roles during nervous system development. In the present study, we hypothesized that neurotransmitter phenotype of both projecting and target cells is an important factor for the final synaptic linkage and its specificity. To test this hypothesis, we used transgenic techniques to convert serotonin/melatonin-producing cells of the pineal gland into cells that also produce dopamine and investigated the innervation of the phenotypically altered target cells. This phenotypic alteration markedly reduced the noradrenergic innervation originating from the superior cervical ganglia. Although the mechanism by which the reduction occurs is presently unknown, quantitative enzyme-linked immunoassay showed the presence of the equivalent amounts of nerve growth factor (NGF) in the control and transgenic pineal glands, suggesting that it occurred in a NGF-independent manner. The results suggest that target neurotransmitter phenotype influences the formation of afferent connections during development.

A treatise on neuralgic diseases, dependent upon irritation of the spinal marrow and ganglia of the sympathetic nerve.

Mode of access: Internet.

Differential expression of calcium channels in sympathetic and parasympathetic preganglionic inputs to neurons in paracervical ganglia of guinea-pigs

Neurons in pelvic ganglia receive nicotinic excitatory post-synaptic potentials (EPSPs) from sacral preganglionic neurons via the pelvic nerve, lumbar preganglionic neurons via the hypogastric nerve or both. We tested the effect of a range of calcium channel antagonists on EPSPs evoked in paracervical ganglia of female guinea-pigs after pelvic or hypogastric nerve stimulation. omega-Conotoxin GVIA (CTX GVIA, 100 nM) or the novel N-type calcium channel antagonist, CTX CVID (100 nM) reduced the amplitude of EPSPs evoked after pelvic nerve stimulation by 50-75% but had no effect on EPSPs evoked by hypogastric nerve stimulation. Combined addition of CTX GVIA and CTX CVID was no more effective than either antagonist alone. EPSPs evoked by stimulating either nerve trunk were not inhibited by the P/Q calcium channel antagonist, omega-agatoxin IVA (100 nM), nor the L-type calcium channel antagonist, nifedipine (30 muM). SNX 482 (300 nM), an antagonist at some R-type calcium channels, inhibited EPSPs after hypogastric nerve stimulation by 20% but had little effect on EPSPs after pelvic nerve stimulation. Amiloride (100 muM) inhibited EPSPs after stimulation of either trunk by 40%, while nickel (100 muM) was ineffective. CTX GVIA or CTX CVID (100 nM) also slowed the rate of action potential repolarization and reduced afterhyperpolarization amplitude in paracervical neurons. Thus, release of transmitter from the terminals of sacral preganglionic neurons is largely dependent on calcium influx through N-type calcium channels, although an unknown calcium channel which is resistant to selective antagonists also contributes to release. Release of transmitter from lumbar preganglionic neurons does not require calcium entry through either conventional N-type calcium channels or the variant CTX CVID-sensitive N-type calcium channel and seems to be mediated largely by a novel calcium channel. (C) 2004 IBRO. Published by Elsevier Ltd. All rights reserved.

Nervous and muscle system development in Phascolion strombus (Sipuncula)

Recent interpretations of developmental gene expression patterns propose that the last common metazoan ancestor was segmented, although most animal phyla show no obvious signs of segmentation. Developmental studies of non-model system trochozoan taxa may shed light on this hypothesis by assessing possible cryptic segmentation patterns. In this paper, we present the first immunocytochemical data on the ontogeny of the nervous system and the musculature in the sipunculan Phascolion strombus. Myogenesis of the first anlagen of the body wall ring muscles occurs synchronously and not subsequently from anterior to posterior as in segmented spiralian taxa (i.e. annelids). The number of ring muscles remains constant during the initial stages of body axis elongation. In the anterior-posteriorly elongated larva, newly formed ring muscles originate along the entire body axis between existing myocytes, indicating that repeated muscle bands do not form from a posterior growth zone. During neurogenesis, the Phascolion larva expresses a non-metameric, paired, ventral nerve cord that fuses in the mid-body region in the late-stage elongated larva. Contrary to other trochozoans, Phascolion lacks any larval serotonergic structures. However, two to three FMRFamide-positive cells are found in the apical organ. In addition, late larvae show commissure-like neurones interconnecting the two ventral nerve cords, while early juveniles exhibit a third, medially placed FMRFamidergic ventral nerve. Although we did not find any indications for cryptic segmentation, certain neuro-developmental traits in Phascolion resemble the conditions found in polychaetes (including echiurans) and myzostomids and support a close relationship of Sipuncula and Annelida.

Sympathetic innervation of ciliary muscle and oculomotor function in emmetropic and myopic young adults

Purpose: Evidence exists for an additional inhibitory accommodative control system mediated by the sympathetic branch of the autonomic nervous system (ANS). This work aims to show the relative prevalence of sympathetic inhibition in young emmetropic and myopic adults, and to evaluate the effect of sympathetic facility on accommodative and oculomotor function. Methods: Profiling of ciliary muscle innervation was carried out in 58 young adult subjects (30 emmetropes, 14 early onset myopes, 14 late onset myopes) by examining post-task open-loop accommodation responses, recorded continuously by a modified open-view infrared optometer. Measurements of amplitude of accommodation, tonic accommodation, accommodative lag at near, AC/A ratio, and heterophoria at distance and near were made to establish a profile of oculomotor function. Results: Evidence of sympathetic inhibitory facility in ciliary smooth muscle was observed in 27% of emmetropes, 21% of early-onset myopes and 29% of late-onset myopes. Twenty-six percent of all subjects demonstrated access to sympathetic facility. Closed-loop oculomotor function did not differ significantly between subjects with sympathetic facility, and those with sympathetic deficit. Conclusions: Emmetropic and myopic groups cannot be distinguished in terms of the relative proportions having access to sympathetic inhibition. Presence of sympathetic innervation does not have a significant effect on accommodative function under closed-loop viewing conditions. © 2005 Elsevier Ltd. All rights reserved.

Cardiac state diagnosis using higher order spectra of heart rate variability

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. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computer-based intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are nonlinear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of nonlinear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and seven classes of arrhythmia. We present some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. We also extracted features from the HOS and performed an analysis of variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test.

Analysis of cardiac and epileptic signals using higher order spectra

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal 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. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

Cardiac health diagnosis using higher order spectra and support vector machine

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.

The biology of the glutamatergic system and potential role in migraine

Migraine is a common genetically linked neurovascular disorder. Approximately ~12% of the Caucasian population are affected including 18% of adult women and 6% of adult men (1, 2). A notable female bias is observed in migraine prevalence studies with females affected ~3 times more than males and is credited to differences in hormone levels arising from reproductive achievements. Migraine is extremely debilitating with wide-ranging socioeconomic impact significantly affecting people's health and quality of life. A number of neurotransmitter systems have been implicated in migraine, the most studied include the serotonergic and dopaminergic systems. Extensive genetic research has been carried out to identify genetic variants that may alter the activity of a number of genes involved in synthesis and transport of neurotransmitters of these systems. The biology of the Glutamatergic system in migraine is the least studied however there is mounting evidence that its constituents could contribute to migraine. The discovery of antagonists that selectively block glutamate receptors has enabled studies on the physiologic role of glutamate, on one hand, and opened new perspectives pertaining to the potential therapeutic applications of glutamate receptor antagonists in diverse neurologic diseases. In this brief review, we discuss the biology of the Glutamatergic system in migraine outlining recent findings that support a role for altered Glutamatergic neurotransmission from biochemical and genetic studies in the manifestation of migraine and the implications of this on migraine treatment.

Higher order spectra based support vector machine for arrhythmia classification

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. HRV analysis is an important tool to observe the heart’s ability to respond to normal regulatory impulses that affect its rhythm. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. A computer-based arrhythmia detection system of cardiac states is very useful in diagnostics and disease management. In this work, we studied the identification of the HRV signals using features derived from HOS. These features were fed to the support vector machine (SVM) for classification. Our proposed system can classify the normal and other four classes of arrhythmia with an average accuracy of more than 85%.

Sovelletun rentoutuksen vaikutus psyykkiseen työhyvinvointiin ja sykevaihteluun

Research reveals that more than every fourth Finn experiences work-related exhaustion to some degree. Stress and exhaustion have psychological and physical expressions. The main physical factor in stress is the overloading of the autonomic nervous system, which can be measured for instance by variations of heart rate. Studies show that the work field, management and authority of the work, skill developmental possibilities, and social support inhibit stress overload. The practising of self-relaxation techniques possible inhibits working stress and exhaustion. In this study of preventive rehabilitation, the focus was on the effects of the training of applied relaxation on psychological and physiological variables of stress and empowerment of resources. Participants (n=73) were basically healthy and capable of working, 25-40 of age, workers from the field of mental work. They practised applied relaxation under group conduction for seven weeks. The aim was to learn to relax easily even in everyday occasions. The subjects were tested thirdly. After the first measurement, they were grouped into two groups, of which the first group started the relaxation training. The second group began practising half a year after the second measurement. The third measurement was done one year after the beginning of the study. It was hypothesised that the training of applied relaxation would significantly reduce stress on both psychological and physiological variables and that these variables would correlate positively. Results revealed that the training of applied relaxation reduced psychological stress symptoms rather modestly. The changes were more significant in women, who experienced a slight increase in self-directivity. Physical changes were slight decreases of the sympathetic activation. The correlations of psychological and physiological variables were modest. Some changes were reduced after the active training. There was a positive interrelation between experienced work-related demands of efficiency, insufficient social support and exhaustion. There was a tendency to significance between skill developmental possibilities and psychological stress symptoms. Further implications of the results were discussed.