51 resultados para Projective synchronization


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Time domain analysis of electroencephalography (EEG) can identify subsecond periods of quasi-stable brain states. These so-called microstates assumingly correspond to basic units of cognition and emotion. On the other hand, Global Field Synchronization (GFS) is a frequency domain measure to estimate functional synchronization of brain processes on a global level for each EEG frequency band [Koenig, T., Lehmann, D., Saito, N., Kuginuki, T., Kinoshita, T., Koukkou, M., 2001. Decreased functional connectivity of EEG theta-frequency activity in first-episode, neuroleptic-naive patients with schizophrenia: preliminary results. Schizophr Res. 50, 55-60.]. Using these time and frequency domain analyzes, several previous studies reported shortened microstate duration in specific microstate classes and decreased GFS in theta band in drug naïve schizophrenia compared to controls. The purpose of this study was to investigate changes of these EEG parameters after drug treatment in drug naïve schizophrenia. EEG analysis was performed in 21 drug-naive patients and 21 healthy controls. 14 patients were reevaluated 2-8 weeks (mean 4.3) after the initiation of drug administration. The results extended findings of treatment effect on brain functions in schizophrenia, and imply that shortened duration of specific microstate classes seems a state marker especially in patients with later neuroleptic responsive, while lower theta GFS seems a state-related phenomenon and that higher gamma GFS is a trait like phenomenon.

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A protein of a biological sample is usually quantified by immunological techniques based on antibodies. Mass spectrometry offers alternative approaches that are not dependent on antibody affinity and avidity, protein isoforms, quaternary structures, or steric hindrance of antibody-antigen recognition in case of multiprotein complexes. One approach is the use of stable isotope-labeled internal standards; another is the direct exploitation of mass spectrometric signals recorded by LC-MS/MS analysis of protein digests. Here we assessed the peptide match score summation index based on probabilistic peptide scores calculated by the PHENYX protein identification engine for absolute protein quantification in accordance with the protein abundance index as proposed by Mann and co-workers (Rappsilber, J., Ryder, U., Lamond, A. I., and Mann, M. (2002) Large-scale proteomic analysis of the human spliceosome. Genome Res. 12, 1231-1245). Using synthetic protein mixtures, we demonstrated that this approach works well, although proteins can have different response factors. Applied to high density lipoproteins (HDLs), this new approach compared favorably to alternative protein quantitation methods like UV detection of protein peaks separated by capillary electrophoresis or quantitation of protein spots on SDS-PAGE. We compared the protein composition of a well defined HDL density class isolated from plasma of seven hypercholesterolemia subjects having low or high HDL cholesterol with HDL from nine normolipidemia subjects. The quantitative protein patterns distinguished individuals according to the corresponding concentration and distribution of cholesterol from serum lipid measurements of the same samples and revealed that hypercholesterolemia in unrelated individuals is the result of different deficiencies. The presented approach is complementary to HDL lipid analysis; does not rely on complicated sample treatment, e.g. chemical reactions, or antibodies; and can be used for projective clinical studies of larger patient groups.

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Neural correlates of electroencephalographic (EEG) alpha rhythm are poorly understood. Here, we related EEG alpha rhythm in awake humans to blood-oxygen-level-dependent (BOLD) signal change determined by functional magnetic resonance imaging (fMRI). Topographical EEG was recorded simultaneously with fMRI during an open versus closed eyes and an auditory stimulation versus silence condition. EEG was separated into spatial components of maximal temporal independence using independent component analysis. Alpha component amplitudes and stimulus conditions served as general linear model regressors of the fMRI signal time course. In both paradigms, EEG alpha component amplitudes were associated with BOLD signal decreases in occipital areas, but not in thalamus, when a standard BOLD response curve (maximum effect at approximately 6 s) was assumed. The part of the alpha regressor independent of the protocol condition, however, revealed significant positive thalamic and mesencephalic correlations with a mean time delay of approximately 2.5 s between EEG and BOLD signals. The inverse relationship between EEG alpha amplitude and BOLD signals in primary and secondary visual areas suggests that widespread thalamocortical synchronization is associated with decreased brain metabolism. While the temporal relationship of this association is consistent with metabolic changes occurring simultaneously with changes in the alpha rhythm, sites in the medial thalamus and in the anterior midbrain were found to correlate with short time lag. Assuming a canonical hemodynamic response function, this finding is indicative of activity preceding the actual EEG change by some seconds.

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The synchronization of dynamic multileaf collimator (DMLC) response with respiratory motion is critical to ensure the accuracy of DMLC-based four dimensional (4D) radiation delivery. In practice, however, a finite time delay (response time) between the acquisition of tumor position and multileaf collimator response necessitates predictive models of respiratory tumor motion to synchronize radiation delivery. Predicting a complex process such as respiratory motion introduces geometric errors, which have been reported in several publications. However, the dosimetric effect of such errors on 4D radiation delivery has not yet been investigated. Thus, our aim in this work was to quantify the dosimetric effects of geometric error due to prediction under several different conditions. Conformal and intensity modulated radiation therapy (IMRT) plans for a lung patient were generated for anterior-posterior/posterior-anterior (AP/PA) beam arrangements at 6 and 18 MV energies to provide planned dose distributions. Respiratory motion data was obtained from 60 diaphragm-motion fluoroscopy recordings from five patients. A linear adaptive filter was employed to predict the tumor position. The geometric error of prediction was defined as the absolute difference between predicted and actual positions at each diaphragm position. Distributions of geometric error of prediction were obtained for all of the respiratory motion data. Planned dose distributions were then convolved with distributions for the geometric error of prediction to obtain convolved dose distributions. The dosimetric effect of such geometric errors was determined as a function of several variables: response time (0-0.6 s), beam energy (6/18 MV), treatment delivery (3D/4D), treatment type (conformal/IMRT), beam direction (AP/PA), and breathing training type (free breathing/audio instruction/visual feedback). Dose difference and distance-to-agreement analysis was employed to quantify results. Based on our data, the dosimetric impact of prediction (a) increased with response time, (b) was larger for 3D radiation therapy as compared with 4D radiation therapy, (c) was relatively insensitive to change in beam energy and beam direction, (d) was greater for IMRT distributions as compared with conformal distributions, (e) was smaller than the dosimetric impact of latency, and (f) was greatest for respiration motion with audio instructions, followed by visual feedback and free breathing. Geometric errors of prediction that occur during 4D radiation delivery introduce dosimetric errors that are dependent on several factors, such as response time, treatment-delivery type, and beam energy. Even for relatively small response times of 0.6 s into the future, dosimetric errors due to prediction could approach delivery errors when respiratory motion is not accounted for at all. To reduce the dosimetric impact, better predictive models and/or shorter response times are required.

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Glucocorticoids are anti-inflammatory steroids with important applications in the treatment of inflammatory diseases. Endogenous glucocorticoids are mainly produced by the adrenal glands, although there is increasing evidence for extra-adrenal sources. Recent findings show that intestinal crypt cells produce glucocorticoids, which contribute to the maintenance of intestinal immune homeostasis. Intestinal glucocorticoid synthesis is critically regulated by the transcription factor liver receptor homologue-1 (LRH-1). As expression of steroidogenic enzymes and LRH-1 is restricted to the proliferating cells of the crypts, we aimed to investigate the role of the cell cycle in the regulation of LRH-1 activity and intestinal glucocorticoid synthesis. We here show that either pharmacological or molecular modulation of cell cycle progression significantly inhibited expression of steroidogenic enzymes and synthesis of glucocorticoids in intestinal epithelial cells. Synchronization of intestinal epithelial cells in the cell cycle revealed that expression of steroidogenic enzymes is preferentially induced at the G(1)/S stage. Differentiation of immature intestinal epithelial cells to mature nonproliferating cells also resulted in reduced expression of steroidogenic enzymes. This cell cycle-related effect on intestinal steroidogenesis was found to be mediated through the regulation of LRH-1 transcriptional activity. This mechanism may restrict intestinal glucocorticoid synthesis to the proliferating cells of the crypts.

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Motor-evoked potentials (MEPs) vary in size from one stimulus to the next. The objective of this study was to determine the cause and source of trial-to-trial MEP size variability. In two experiments involving 10 and 14 subjects, the variability of MEPs to cortical stimulation (cortical-MEPs) in abductor digiti minimi (ADM) and abductor hallucis (AH) was compared to those responses obtained using the triple stimulation technique (cortical-TST). The TST eliminates the effects of motor neuron (MN) response desynchronization and of repetitive MN discharges. Submaximal stimuli were used in both techniques. In six subjects, cortical-MEP variability was compared to that of brainstem-MEP and brainstem-TST. Variability was greater for MEPs than that for TST responses, by approximately one-third. The variability was the same for cortical- and brainstem-MEPs and was similar in ADM and AH. Variability concerned at least 10-15% of the MN pool innervating the target muscle. With the stimulation parameters used, repetitive MN discharges did not influence variability. For submaximal stimuli, approximately two-third of the observed MEP size variability is caused by the variable number of recruited alpha-MNs and approximately one-third by changing synchronization of MN discharges. The source of variability is most likely localized at the spinal segmental level.

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Phase locking or synchronization of brain areas is a key concept of information processing in the brain. Synchronous oscillations have been observed and investigated extensively in EEG during the past decades. EEG oscillations occur over a wide frequency range. In EEG, a prominent type of oscillations is alpha-band activity, present typically when a subject is awake, but at rest with closed eyes. The spectral power of alpha rhythms has recently been investigated in simultaneous EEG/fMRI recordings, establishing a wide-range cortico-thalamic network. However, spectral power and synchronization are different measures and little is known about the correlations between BOLD effects and EEG synchronization. Interestingly, the fMRI BOLD signal also displays synchronous oscillations across different brain regions. These oscillations delineate so-called resting state networks (RSNs) that resemble the correlation patterns of simultaneous EEG/fMRI recordings. However, the nature of these BOLD oscillations and their relations to EEG activity is still poorly understood. One hypothesis is that the subunits constituting a specific RSN may be coordinated by different EEG rhythms. In this study we report on evidence for this hypothesis. The BOLD correlates of global EEG synchronization (GFS) in the alpha frequency band are located in brain areas involved in specific RSNs, e.g. the 'default mode network'. Furthermore, our results confirm the hypothesis that specific RSNs are organized by long-range synchronization at least in the alpha frequency band. Finally, we could localize specific areas where the GFS BOLD correlates and the associated RSN overlap. Thus, we claim that not only the spectral dynamics of EEG are important, but also their spatio-temporal organization.

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Rationale: Focal onset epileptic seizures are due to abnormal interactions between distributed brain areas. By estimating the cross-correlation matrix of multi-site intra-cerebral EEG recordings (iEEG), one can quantify these interactions. To assess the topology of the underlying functional network, the binary connectivity matrix has to be derived from the cross-correlation matrix by use of a threshold. Classically, a unique threshold is used that constrains the topology [1]. Our method aims to set the threshold in a data-driven way by separating genuine from random cross-correlation. We compare our approach to the fixed threshold method and study the dynamics of the functional topology. Methods: We investigate the iEEG of patients suffering from focal onset seizures who underwent evaluation for the possibility of surgery. The equal-time cross-correlation matrices are evaluated using a sliding time window. We then compare 3 approaches assessing the corresponding binary networks. For each time window: * Our parameter-free method derives from the cross-correlation strength matrix (CCS)[2]. It aims at disentangling genuine from random correlations (due to finite length and varying frequency content of the signals). In practice, a threshold is evaluated for each pair of channels independently, in a data-driven way. * The fixed mean degree (FMD) uses a unique threshold on the whole connectivity matrix so as to ensure a user defined mean degree. * The varying mean degree (VMD) uses the mean degree of the CCS network to set a unique threshold for the entire connectivity matrix. * Finally, the connectivity (c), connectedness (given by k, the number of disconnected sub-networks), mean global and local efficiencies (Eg, El, resp.) are computed from FMD, CCS, VMD, and their corresponding random and lattice networks. Results: Compared to FMD and VMD, CCS networks present: *topologies that are different in terms of c, k, Eg and El. *from the pre-ictal to the ictal and then post-ictal period, topological features time courses that are more stable within a period, and more contrasted from one period to the next. For CCS, pre-ictal connectivity is low, increases to a high level during the seizure, then decreases at offset. k shows a ‘‘U-curve’’ underlining the synchronization of all electrodes during the seizure. Eg and El time courses fluctuate between the corresponding random and lattice networks values in a reproducible manner. Conclusions: The definition of a data-driven threshold provides new insights into the topology of the epileptic functional networks.

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We explored and refined the hypothesis that during a first episode of acute schizophrenia a disorganization of brain functioning is present. A novel EEG measure was introduced, Global Field Synchronization (GFS), that estimates functional connectivity of brain processes in different EEG frequency bands. The measure was applied to EEG's from 11 never-treated, first-episode, young patients with an acute, positive, schizophrenic symptomatology and from 19 controls, residing in Bern, Switzerland. In comparison to age- and sex- matched controls, patients had significantly decreased GFS in the theta EEG frequency band, indicating a loosened functional connectivity of processes in this frequency. The result was confirmed in an independent, comparable patient group from Osaka, Japan (9 patients and 9 controls), thus making a total of 20 analyzed patients. Previous EEG research in healthy, awake subjects indicated a positive correlation of theta activity with memory functions. Thus, our result suggests a loss of mutual interdependence of memory functions in patients with acute schizophrenia, which agrees well with previous reports of working memory dysfunction in schizophrenia.

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Article preview View full access options BoneKEy Reports | Review Print Email Share/bookmark Finite element analysis for prediction of bone strength Philippe K Zysset, Enrico Dall'Ara, Peter Varga & Dieter H Pahr Affiliations Corresponding author BoneKEy Reports (2013) 2, Article number: 386 (2013) doi:10.1038/bonekey.2013.120 Received 03 January 2013 Accepted 25 June 2013 Published online 07 August 2013 Article tools Citation Reprints Rights & permissions Abstract Abstract• References• Author information Finite element (FE) analysis has been applied for the past 40 years to simulate the mechanical behavior of bone. Although several validation studies have been performed on specific anatomical sites and load cases, this study aims to review the predictability of human bone strength at the three major osteoporotic fracture sites quantified in recently completed in vitro studies at our former institute. Specifically, the performance of FE analysis based on clinical computer tomography (QCT) is compared with the ones of the current densitometric standards, bone mineral content, bone mineral density (BMD) and areal BMD (aBMD). Clinical fractures were produced in monotonic axial compression of the distal radii, vertebral sections and in side loading of the proximal femora. QCT-based FE models of the three bones were developed to simulate as closely as possible the boundary conditions of each experiment. For all sites, the FE methodology exhibited the lowest errors and the highest correlations in predicting the experimental bone strength. Likely due to the improved CT image resolution, the quality of the FE prediction in the peripheral skeleton using high-resolution peripheral CT was superior to that in the axial skeleton with whole-body QCT. Because of its projective and scalar nature, the performance of aBMD in predicting bone strength depended on loading mode and was significantly inferior to FE in axial compression of radial or vertebral sections but not significantly inferior to FE in side loading of the femur. Considering the cumulated evidence from the published validation studies, it is concluded that FE models provide the most reliable surrogates of bone strength at any of the three fracture sites.

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Background: Synchronization programs have become standard in the dairy industry. In Switzerland, these programs are used but newly. The objective of this study was A) to estimate the pregnancy rate after a Select-Synch protocol in- cluding a low dosage of progesterone in CIDR (1.38 g). As a second step B) this pregnancy rate should be compared to cows from another Swiss study that used a Select-Synch protocol with the 1.9 g insert (Rudolph et al., 2011). Methods: A) 196 cows were included in the study. Cows received a CIDR 1.38 g and 2.5 ml of buserelin i.m. on d 0. On d 7, the CIDR insert was removed and 5 ml of dinoprost was administered i.m. On d 0 a milk sample for progesterone analysis was taken. Pregnancy was determined at or more than 35 days after artificial insemination. B) The 1.38 g group and the 1.9 g group were compared as to cow and farm factors, number of preceding AI’s, gynecological and uterine pretreat- ment and treatment itself. A forward selection procedure was used (test result considered significant if p-value  0.05). Results: A) The pregnancy rate, using the Select-Synch protocol with the CIDR 1.38 g was 44.4%. B) The CIDR 1.9 g Select-Synch group revealed a pregnancy rate of 50.4% (Rudolph et al., 2011). Significant differences between the groups were not found. Conclusion: The 1.38 g CIDR-Select-Synch protocol may be recommended for multiparous dairy cows. The pregnancy rate compared to the 1.9 g CIDR-Select-Synch protocol was 8% lower, but this difference was not significant.

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The Toba eruption that occurred some 74 ka ago in Sumatra, Indonesia, is among the largest volcanic events on Earth over the last 2 million years. Tephra from this eruption has been spread over vast areas in Asia, where it constitutes a major time marker close to the Marine Isotope Stage 4/5 boundary. As yet, no tephra associated with Toba has been identified in Greenland or Antarctic ice cores. Based on new accurate dating of Toba tephra and on accurately dated European stalagmites, the Toba event is known to occur between the onsets of Greenland interstadials (GI) 19 and 20. Furthermore, the existing linking of Greenland and Antarctic ice cores by gas records and by the bipolar seesaw hypothesis suggests that the Antarctic counterpart is situated between Antarctic Isotope Maxima (AIM) 19 and 20. In this work we suggest a direct synchronization of Greenland (NGRIP) and Antarctic (EDML) ice cores at the Toba eruption based on matching of a pattern of bipolar volcanic spikes. Annual layer counting between volcanic spikes in both cores allows for a unique match. We first demonstrate this bipolar matching technique at the already synchronized Laschamp geomagnetic excursion (41 ka BP) before we apply it to the suggested Toba interval. The Toba synchronization pattern covers some 2000 yr in GI-20 and AIM-19/20 and includes nine acidity peaks that are recognized in both ice cores. The suggested bipolar Toba synchronization has decadal precision. It thus allows a determination of the exact phasing of inter-hemispheric climate in a time interval of poorly constrained ice core records, and it allows for a discussion of the climatic impact of the Toba eruption in a global perspective. The bipolar linking gives no support for a long-term global cooling caused by the Toba eruption as Antarctica experiences a major warming shortly after the event. Furthermore, our bipolar match provides a way to place palaeo-environmental records other than ice cores into a precise climatic context.

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Ventricular assist devices (VADs) are blood pumps that offer an option to support the circulation of patients with severe heart failure. Since a failing heart has a remaining pump function, its interaction with the VAD influences the hemodynamics. Ideally, the heart's action is taken into account for actuating the device such that the device is synchronized to the natural cardiac cycle. To realize this in practice, a reliable real-time algorithm for the automatic synchronization of the VAD to the heart rate is required. This paper defines the tasks such an algorithm needs to fulfill: the automatic detection of irregular heart beats and the feedback control of the phase shift between the systolic phases of the heart and the assist device. We demonstrate a possible solution to these problems and analyze its performance in two steps. First, the algorithm is tested using the MIT-BIH arrhythmia database. Second, the algorithm is implemented in a controller for a pulsatile and a continuous-flow VAD. These devices are connected to a hybrid mock circulation where three test scenarios are evaluated. The proposed algorithm ensures a reliable synchronization of the VAD to the heart cycle, while being insensitive to irregularities in the heart rate.

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Lake Van sediment cores from the Ahlat Ridge and Northern Basin drill sites of the ICDP project PALEOVAN contain a wealth of information about past environmental processes. The sedimentary sequence was dated using climatostratigraphic alignment, varve chronology, tephrostratigraphy, argon-argon single-crystal dating, radiocarbon dating, magnetostratigraphy, and cosmogenic nuclides. Based on the lithostratigraphic framework, the different age constraints are compiled and a robust and precise chronology of the 600,000 year-old Lake Van record is constructed. Proxy records of total organic carbon content and sediment color, together with the calcium/potassium-ratios and arboreal pollen percentages of the 174-meter-long Ahlat Ridge record, mimic the Greenland isotope stratotype (NGRIP). Therefore, the proxy records are systematically aligned to the onsets of interstadials reflected in the NGRIP or synthesized Greenland ice-core stratigraphy. The chronology is constructed using 27 age control points derived from visual synchronization with the GICC05 timescale, an absolutely-dated speleothem record (e.g., Hulu, Sanbao, Linzhu cave) and the Epica Dome C timescale. In addition, the uppermost part of the sequence is complemented with four ages from Holocene varve chronology and two calibrated radiocarbon ages. Furthermore, nine argon-argon ages and a comparison of the relative paleointensity record of the magnetic field with reference curve PISO-1500 confirm the accuracy of the age model. Also the identification of the Laschamp event via measurements of 10Be in the sediment confirms the presented age model. The chronology of the Ahlat Ridge record is transferred to the 79-meter-long event-corrected composite record from the Northern Basin and supplemented by additional radiocarbon dating on organic marco-remains. The basal age of the Northern Basin record is estimated at ~90 ka. The variations of the time series of total organic carbon content, the Ca/K ratio, and the arboreal pollen percentages illustrate that the presented chronology and paleoclimate data are suited for reconstructions and modeling of the Quaternary and Pleistocene climate evolution in the Near East at millennial timescales. Furthermore, the chronology of the last 250 kyr can be used to test other dating techniques.

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Heart rate and breathing rate fluctuations represent interacting physiological oscillations. These interactions are commonly studied using respiratory sinus arrhythmia (RSA) of heart rate variability (HRV) or analyzing cardiorespiratory synchronization. Earlier work has focused on a third type of relationship, the temporal ratio of respiration rate and heart rate (HRR). Each method seems to reveal a specific aspect of cardiorespiratory interaction and may be suitable for assessing states of arousal and relaxation of the organism. We used HRR in a study with 87 healthy subjects to determine the ability to relax during 5 day-resting periods in comparison to deep sleep relaxation. The degree to which a person during waking state could relax was compared to somatic complaints, health-related quality of life, anxiety and depression. Our results show, that HRR is barely connected to balance (LF/HF) in HRV, but significantly correlates to the perception of general health and mental well-being as well as to depression. If relaxation, as expressed in HRR, during day-resting is near to deep sleep relaxation, the subjects felt healthier, indicated better mental well-being and less depressive moods.