Preserved dynamic cerebral autoregulation in the middle cerebral artery among persons with migraine

Migraine affects the autonomous nervous system and a recent investigation has also proposed a severe disturbance of dynamic cerebral blood flow regulation in the middle cerebral artery during spontaneous blood pressure oscillations. This study investigates whether dynamic cerebral autoregulation is impaired in persons with migraine among a normal cohort. Out of 94 adults studied to establish normal values for dynamic autoregulation, 19 suffered from migraine according to IHS criteria (10 of them with aura). Transcranial Doppler sonography and fingerplethysmography were used to determine dynamic autoregulation of both middle cerebral arteries following spontaneous low frequency (0.06-0.12 Hz) blood pressure fluctuations (phase and gain of transfer function, correlation coefficient indices Dx and Mx). No significant differences were found for the low frequency variability of blood pressure (power spectral density) and various indices of dynamic cerebral autoregulation between persons with and without migraine. Moreover, no differences were observed between persons with migraine, with and without aura. This study based on a normal cohort does not support the presence of generally impaired cerebral autoregulation dynamics in persons with migraine. Future studies should focus on posterior circulation and particular cerebellar autoregulation.

Microarray analysis reveals influence of the sesquiterpene lactone parthenolide on gene transcription profiles in human epithelial cells

Sesquiterpene lactones are known for their anti-inflammatory activity which has been proven in various assays on DNA, mRNA and protein level. Here we report on the change in the gene expression profile in TNF-alpha stimulated human 293 cells after treatment with parthenolide using a cDNA microarray analysis. Twenty-one of 7028 genes were found to be up- and 18 down-regulated. They encode for chemoattractants, immune system proteins, glycoproteins, metabolism, serine proteinases, and transcription factors. Confirmatory analyses were carried out using quantitative real-time RT-PCR (TaqMan). Additional studies with selected genes revealed the concentration-dependent influence of parthenolide on the expression of these genes.

Primary mouse hepatocytes for systems biology approaches: a standardized in vitro system for modelling of signal transduction pathways

Complex cellular networks regulate regeneration, detoxification and differentiation of hepatocytes. By combining experimental data with mathematical modelling, systems biology holds great promises to elucidate the key regulatory mechanisms involved and predict targets for efficient intervention. For the generation of high-quality quantitative data suitable for mathematical modelling a standardised in vitro system is essential. Therefore the authors developed standard operating procedures for the preparation and cultivation of primary mouse hepatocytes. To reliably monitor the dynamic induction of signalling pathways, the authors established starvation conditions and evaluated the extent of starvation-associated stress by quantifying several metabolic functions of cultured primary hepatocytes, namely activities of glutathione-S-transferase, glutamine synthetase, CYP3A as well as secretion of lactate and urea into the culture medium. Establishment of constant metabolic activities after an initial decrease compared with freshly isolated hepatocytes showed that the cultured hepatocytes achieve a new equilibrium state that was not affected by our starving conditions. To verify the highly reproducible dynamic activation of signalling pathways in the in vitro system, the authors examined the JAK-STAT, SMAD, PI3 kinase, MAP kinase, NF-kappaB and Wnt/beta-catenin signalling pathways. For the induction of gp130, JAK1 and STAT3 phosphorylation IL6 was used, whereas TGFbeta was applied to activate the phosphorylation of SMAD1, SMAD2 and SMAD3. Both Akt/PKB and ERK1/2 phosphorylation were stimulated by the addition of hepatocyte growth factor. The time-dependent induction of a pool of signalling competent beta-catenin was monitored in response to the inhibition of GSK3beta. To analyse whether phosphorylation is actually leading to transcriptional responses, luciferase reporter gene constructs driven by multiple copies of TGFbeta-responsive motives were applied, demonstrating a dose-dependent increase in luciferase activity. Moreover, the induction of apoptosis by the TNF-like cytokine Fas ligand was studied in the in vitro system. Thus, the mouse hepatocyte in vitro system provides an important basis for the generation of high-quality quantitative data under standardised cell culture conditions that is essential to elucidate critical hepatocellular functions by the systems biology approach.

Parameter estimation in stochastic biochemical reactions

Gene regulatory, signal transduction and metabolic networks are major areas of interest in the newly emerging field of systems biology. In living cells, stochastic dynamics play an important role; however, the kinetic parameters of biochemical reactions necessary for modelling these processes are often not accessible directly through experiments. The problem of estimating stochastic reaction constants from molecule count data measured, with error, at discrete time points is considered. For modelling the system, a hidden Markov process is used, where the hidden states are the true molecule counts, and the transitions between those states correspond to reaction events following collisions of molecules. Two different algorithms are proposed for estimating the unknown model parameters. The first is an approximate maximum likelihood method that gives good estimates of the reaction parameters in systems with few possible reactions in each sampling interval. The second algorithm, treating the data as exact measurements, approximates the number of reactions in each sampling interval by solving a simple linear equation. Maximising the likelihood based on these approximations can provide good results, even in complex reaction systems.

Dynamic Cerebral Autoregulation in Acute Ischemic Stroke Assessed From Spontaneous Blood Pressure Fluctuations

Background and Purpose— This study investigates dynamic cerebral autoregulation assessed from spontaneous blood pressure (ABP) and cerebral blood flow velocity (CBFV) fluctuations and its time course in acute ischemic stroke.

Methods— Forty patients admitted with acute ischemic stroke in the territory of the middle cerebral artery (MCA) were enrolled. Admission National Institutes of Health Stroke score was 6±4. Study 1 was performed within 22 (±11) hours and study 2 was performed within 134 (±25) hours of ictus. The final analysis comprised 33 and 29 patients for study 1 and study 2, respectively. Twenty-five age- and sex-matched controls were studied. ABP (Finapres method) and CBFV in both MCAs (transcranial Doppler) were recorded over 10 minutes. Correlations between diastolic and mean ABP and CBFV fluctuations were averaged, yielding the correlation coefficient indices (Dx, Mx). Transfer function analysis was applied to obtain phase shift and gain between ABP and CBFV oscillations.

Results— No disturbance of autoregulation was indicated by all parameters at study 1. Separate analyses for clinical severity, stroke side, and size did not reveal significant differences for the various autoregulatory indices at study 1 and 2. At study 2, MCA flow velocity was significantly increased on both sides, the autoregulation index Mx was slightly but significantly ( P <0.05) worse on both sides in comparison to study 1, and phase showed a trend toward poorer values on affected sides. No significant differences to controls occurred. Clinical outcome in patients completing both studies was good in all but one patient.

Conclusions— Dynamic cerebral autoregulation assessed from spontaneous blood pressure fluctuations does not seem to be relevantly disturbed in early minor MCA stroke. At the subacute stage, slight autoregulatory disturbance may be present.

Mixing properties of the Rössler system and consequences for coherence and synchronization analysis

Cross-spectral and synchronization analysis of two independent, identical chaotic Rössler systems suggest a coupling although there is no interaction. This spuriously detected interaction can either be explained by the absence of mixing or by finite size effects. To decide which alternative holds the phase dynamics is studied by a model of the fluctuations derived from the system's equations. The basic assumption of the model is a diffusive character for the system which corresponds to mixing. Comparison of theoretical properties of the model with empirical properties of the Rössler system suggests that the system is mixing but the rate of mixing appears to be rather low.

On Studentising and Blocklength Selection for the Bootstrap on Time Series

For independent data, non-parametric bootstrap is realised by resampling the data with replacement. This approach fails for dependent data such as time series. If the data generating process is at least stationary and mixing, the blockwise bootstrap by drawing subsamples or blocks of the data saves the concept. For the blockwise bootstrap a blocklength has to be selected. We propose a method for selecting the optimal blocklength. To improve the finite size properties of the blockwise bootstrap, studentised statistics is considered. If the statistic can be represented as a smooth function model this studentisation can be approximated efficiently. The studentised blockwise bootstrap method is applied for testing hypotheses on medical time series.

Quantitative data generation for systems biology: the impact of randomisation, calibrators and normalisers

Systems biology is an approach to the analysis and prediction of the dynamic behaviour of biological networks through mathematical modelling based on experimental data. The current lack of reliable quantitative data, especially in the field of signal transduction, means that new methodologies in data acquisition and processing are needed. Here, we present methods to advance the established techniques of immunoprecipitation and immunoblotting to more accurate and quantitative procedures. We propose randomisation of sample loading to disrupt lane correlations and the use of normalisers and calibrators for data correction. To predict the impact of each method on improving the data quality we used simulations. These studies showed that randomisation reduces the standard deviation of a smoothed signal by 55% +/- 10%, independently from most experimental settings. Normalisation with appropriate endogenous or external proteins further reduces the deviation from the true values. As the improvement strongly depends on the quality of the normaliser measurement, a criteria-based normalisation procedure was developed. Our approach was experimentally verified by application of the proposed methods to time course data obtained by the immunoblotting technique. This analysis showed that the procedure is robust and can significantly improve the quality of experimental data.

Variations in substitution rate in human and mouse genomes

We present a method to quantify spatial fluctuations of the substitution rate on different length scales throughout genomes of eukaryotes. The fluctuations on large length scales are found to be predominantly a consequence of a coarse-graining effect of fluctuations on shorter length scales. This is verified for both the mouse and the human genome. We also found that the relative standard deviation of fluctuations in substitution rate is about a factor three smaller in mouse than in human. The method allows furthermore to determine time-resolved substitution rate maps of the genomes, where the corresponding autocorrelation functions quantify the velocity of spatial chromosomal reorganization.

Phase synchronization from noisy univariate signals

We present methods for detecting phase synchronization of two unidirectionally coupled, self-sustained noisy oscillators from a signal of the driven oscillator alone. One method detects soft phase locking; another hard phase locking. Both are applied to the problem of detecting phase synchronization in von Kármán vortex flow meters.

Tremor analysis in two normal cohorts

OBJECTIVE

Quantitative tremor analyses using almost identical methods were compared between two independent large normal cohorts, to separate robust measures that may readily be used diagnostically from more critical ones needing lab-specific normalization.

METHODS

Hand accelerometry and surface EMG from forearm flexors and extensors were recorded with (500 and 1000 g) and without weight loading under postural conditions in 117 and 67 normal volunteers in two different specialty centers for movement disorders in Germany.

RESULTS

Tremor amplitude (total power) and frequency fell within a similar range but differed significantly. A significant reduction of tremor frequency under 1000 g weight load (>1 Hz), and a lack of rhythmic EMG activity at the tremor frequency in around 85-90% of the recordings were robust findings in both centers.

CONCLUSIONS

The differences in frequency and total power indicate that these measures critically depend on the details of the recording conditions being slightly different between the two centers. Thus each lab needs to establish its own normative data. We estimate that at least 25 normal subjects have to be recorded to obtain normal values. The reduction of tremor frequency under load and lacking tremor-related EMG activity were well reproducible allowing a differentiation of physiological from low amplitude pathological tremor.

SIGNIFICANCE

This study provides a framework for more standardized tremor analyses in clinical neurophysiology.

Effect of Carotid Endarterectomy or Stenting on Impairment of Dynamic Cerebral Autoregulation

Background and Purpose— Analysis of dynamic cerebral autoregulation (DCA) from spontaneous blood pressure fluctuations might contribute to prognosis of severe internal carotid artery stenosis, but its response to carotid recanalization has not been investigated so far. This study investigates the effect of carotid endarterectomy or stenting on various DCA parameters.

Methods— In 58 patients with severe unilateral stenosis undergoing carotid endarterectomy (n=41) or stenting (n=17), cerebral blood flow velocity (CBFV, transcranial Doppler) and arterial blood pressure (ABP, Finapres method) were recorded over 10 minutes before and on average 3 days after carotid recanalization. Nineteen patients were additionally examined after 7 months. Correlations between diastolic and mean ABP and CBFV fluctuations were averaged to form the correlation coefficient indices (diastolic [Dx] and mean values [Mx]). Transfer function parameters (low-frequency phase and high-frequency gain between ABP and CBFV oscillations) were calculated over the same 10 minutes. CO 2 reactivity was assessed via inhalation of 7% CO 2 .

Results— Before recanalization, all DCA parameters were clearly impaired ipsilaterally compared with contralateral sides. Phase, Dx, and Mx indicated early normalization of DCA after both endarterectomy and stenting. By multiple regression, the degree of DCA improvement was highly significantly related to the extent of impairment before recanalization. No significant change in DCA was found at follow-up. Ipsilateral gain and CO 2 reactivity increased significantly less after endarterectomy than after stenting ( P <0.05).

Conclusions— Dynamic cerebral dysautoregulation in patients with severe carotid obstruction is readily and completely remedied by carotid recanalization.

Aperiodic flow-induced oscillations of collapsible tubes: a critical reappraisal

The evidence for the aperiodic self-excited oscillations of flow-conveying collapsible tubes being mathematically chaotic is re-examined. Many cases which powerfully suggest nonlinear deterministic behaviour have not been recorded over time-spans which allow their exhaustive examination. The present investigation centred on a previously recorded robust and generic oscillation, but more recent and more discerning tests were applied. Despite hints that a low embedding dimension might suffice, the data appeared on most indices high-dimensional. A U-shaped return map was found and modelled using both radial basis functions and polynomials, but lack of detailed structure in the map prevented effective parameter estimation. On the basis of power-law rather than exponential divergence of nearby trajectories, and of inability to discriminate against behaviour which would also be manifested by a surrogate consisting of a noise-perturbed nonlinear periodic oscillator, it is concluded that the data do not support the idea that the aperiodicity in the particular oscillation examined is caused by deterministic chaos. There was evidence that the distributed nature of the physical system might underlie aspects of the high dimensionality. We advocate equally searching testing of any future candidate chaotic oscillations in the investigation of collapsed-tube flows.

Data-driven optimal filtering for phase and frequency of noisy oscillations: Application to vortex flow metering

A method for measuring the phase of oscillations from noisy time series is proposed. To obtain the phase, the signal is filtered in such a way that the filter output has minimal relative variation in the amplitude over all filters with complex-valued impulse response. The argument of the filter output yields the phase. Implementation of the algorithm and interpretation of the result are discussed. We argue that the phase obtained by the proposed method has a low susceptibility to measurement noise and a low rate of artificial phase slips. The method is applied for the detection and classification of mode locking in vortex flow meters. A measure for the strength of mode locking is proposed.

Estimation of Delay Times in Biological Systems

The problem of delay time estimation in biological systems is addressed with the focus on practical applicability of methods. Four delay time estimators are described: a cross correlation method and three increasingly sophisticated interpretations of the phase spectrum, ranging from a pointwise interpretation of the phase spectrum in terms of a delay to a Hilbert transform method. The four methods are compared through simulation studies showing that, in general, the Hilbert transform method performs best. The methods are then used to estimate delay times in three physiological systems: vestibular stimulation, cerebral autoregulation, and human orthostatic tremor. In all three cases, the Hilbert transform method yields the best results, leading in some cases to physiologically more sensible interpretations of experiments than the other methods.

Bilateral severe carotid artery stenosis or occlusion - cerebral autoregulation dynamics and collateral flow patterns

BACKGROUND

Bilateral severe obstruction of the internal carotid artery is a hemodynamically critical state. We aimed to (1) analyze dynamic cerebral autoregulation (DCA) in affected patients, and (2) to correlate DCA data with different collateral flow patterns.

METHODS

DCA was assessed noninvasively by transfer function analysis (phase shift) of respiratory-induced oscillations at 0.1 Hz of arterial blood pressure (Finapres method) and cerebral blood flow velocity (transcranial Doppler) in 30 patients with severe bilateral carotid stenosis (> or =75%) or occlusion. CO(2)-reactivity was measured via inhalation of 7% CO(2). 30 patients with unilateral stenosis were recruited as controls.

RESULTS

Patients with bilateral 75-89% stenosis had a virtually preserved phase shift. A pronounced reduction was found in bilateral critical stenosis or obstruction (90-100%). Patients with ipsilateral 90-100% and contralateral 75-89% stenosis had a significantly less severe reduction of phase shift on the ipsilateral side. CO(2)-reactivity showed a less marked reduction in patients with bilateral critical stenosis or occlusion. Phase shift was best if "Willisian" collaterals were present. Significantly reduced values were found if only secondary collaterals (ophthalmic artery, leptomeningeal flow) were detected. Poorest values occurred with recruitment of functionally stenosed "Willisian" collaterals. CO(2)-reactivity showed poor values with sole recruitment of secondary collaterals, whereas functionally stenosed primary collaterals did not show values as poor as for phase shift. Clinically symptomatic patients had significantly lower phase shift and CO(2)-reactivity values.

CONCLUSIONS

DCA is severely impaired in bilateral critical carotid stenosis or occlusion. Sole recruitment of secondary collaterals and signs of a functional stenosis in primary ("Willisian") collaterals reflect insufficient collateral supply with a poor hemodynamic status. CO(2)-reactivity assessing the vasodilatory reserve and DCA represent different information for characterizing cerebral hemodynamic impairment. Determining transfer function phase might be a physiologically well supported approach for analysis of cerebral hemodynamic compromise.

Normalization of DNA-Microarray Data by Nonlinear Correlation Maximization

Signal data from DNA-microarray ("chip") technology can be noisy; i.e., the signal variation of one gene on a series of repetitive chips can be substantial. It is becoming more and more recognized that a sufficient number of chip replicates has to be made in order to separate correct from incorrect signals. To reduce the systematic fraction of the noise deriving from pipetting errors, from different treatment of chips during hybridization, and from chip-to-chip manufacturing variability, normalization schemes are employed. We present here an iterative nonparametric nonlinear normalization scheme called simultaneous alternating conditional expectation (sACE), which is designed to maximize correlation between chip repeats in all-chip-against-all space. We tested sACE on 28 experiments with 158 Affymetrix one-color chips. The procedure should be equally applicable to other DNA-microarray technologies, e.g., two-color chips. We show that the reduction of noise compared to a simple normalization scheme like the widely used linear global normalization leads to fewer false-positive calls, i.e., to fewer genes which have to be laboriously confirmed by independent methods such as TaqMan or quantitative PCR.

How well can epileptic seizures be predicted? An evaluation of a nonlinear method

The unpredictability of the occurrence of epileptic seizures contributes to the burden of the disease to a major degree. Thus, various methods have been proposed to predict the onset of seizures based on EEG recordings. A nonlinear feature motivated by the correlation dimension is a seemingly promising approach. In a previous study this method was reported to identify 'preictal dimension drops' up to 19 min before seizure onset, exceeding the variability of interictal data sets of 30-50 min duration. Here we have investigated the sensitivity and specificity of this method based on invasive long-term recordings from 21 patients with medically intractable partial epilepsies, who underwent invasive pre-surgical monitoring. The evaluation of interictal 24-h recordings comprising the sleep-wake cycle showed that only one out of 88 seizures was preceded by a significant preictal dimension drop. In a second analysis, the relation between dimension drops within time windows of up to 50 min before seizure onset and interictal periods was investigated. For false-prediction rates below 0.1/h, the sensitivity ranged from 8.3 to 38.3% depending on the prediction window length. Overall, the mean length and amplitude of dimension drops showed no significant differences between interictal and preictal data sets.

Cerebral autoregulation in carotid artery occlusive disease assessed from spontaneous blood pressure fluctuations by the correlation coefficient index

BACKGROUND AND PURPOSE

Estimation of dynamic cerebral autoregulation from spontaneous fluctuations of arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) is an attractive monitoring option for cerebral hemodynamic impairment. We evaluated the correlation coefficient index method in patients with severe obstructive carotid disease and compared it with transfer function analysis (frequency domain approach to cerebral autoregulation) and CO2 vasomotor reactivity.

METHODS

In 139 patients with severe unilateral carotid stenosis (>or=70%) or occlusion, CBFV (transcranial Doppler) and ABP (Finapres method) were recorded over 10 minutes. Correlations between systolic pressure, diastolic pressure, and mean ABP and CBFV oscillations over 1-minute epochs were averaged over 10 minutes to form the correlation coefficient indexes (Sx, Dx, Mx, respectively). Transfer function parameters (phase shift and gain between ABP and CBFV oscillations) were determined from the entire 10-minute period. CO2 reactivity was assessed by inhalation of 7% CO2.

RESULTS

The correlation indexes Dx and Mx were significantly higher ipsilateral to stenosis and increased with degree of stenosis, indicating increasing dependence of CBFV on ABP and thus impairment of cerebral autoregulation. Dx and Mx correlated moderately but highly significantly with transfer function parameters and CO2 reactivity and showed a good level of agreement in detecting pathological values. Patients with a small variance of the 1-minute source correlations of Dx and Mx showed clearly better correlation values. Transfer function parameters and CO2 reactivity but not Dx and Mx were significantly poorer in patients with symptomatic stenosis or occlusion.

CONCLUSIONS

The potential of the correlation coefficient indexes Dx and Mx in detecting hemodynamic impairment in patients with carotid stenosis is comparable to that of transfer function analysis and CO2 reactivity testing. In future, a combination of various hemodynamic tests might help to identify patients at risk for ischemic events.

Dynamic cerebral autoregulation and collateral flow patterns in patients with severe carotid stenosis or occlusion

The quality of collateral blood supply in carotid disease is pivotal for the resulting hemodynamic compromise. However, the interrelation between different patterns of collateral blood flow and actual impairment of cerebral autoregulation (CAR) has not been analyzed so far. Dynamic CAR was assessed noninvasively by the phase shift between respiratory-induced 0.1-Hz oscillations of arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) in 101 patients with severe unilateral carotid stenosis (> or = 75%) or occlusion. CO(2)-vasomotor reactivity was assessed via inhalation of 7% CO(2). Spontaneously activated collaterals via primary (anterior/posterior communicating artery, type I, n = 65) and secondary (ophthalmic artery / leptomeningeal with or without primary pathways, group II, n = 24) pathways were assessed by transcranial Doppler/duplex sonography. Signs of functional stenosis in the anterior collateral pathways were subsumed under type III (n = 12). Best dynamic CAR (phase shift) on affected sides was observed for type I (n = 65), in which values did not differ significantly from contralateral sides. Reduced phase shift values were present in type II; poorest values were observed for type III. CO(2)-reactivity differed mainly between type I and the other types. A less distinct differentiation of autoregulatory impairment was found when dividing patients into groups of different degrees of stenosis. Symptomatic patients (previous TIA/stroke) were significantly less frequent in the group with type I collateral flow and had significantly lower phase shift and CO(2)-reactivity values. In conclusion, we found that dynamic CAR is substantially impaired if secondary collateral pathways are activated or if functional stenosis in the activated anterior collateral pathway is present. These hemodynamic constellations are also associated with a higher proportion of clinically symptomatic patients. Determination of dynamic CAR by transfer function analysis represents a convenient, sensitive method for detection of cerebral hemodynamic compromise in obstructive carotid disease.

Dynamic synchronisation of central oscillators in essential tremor

OBJECTIVE

Coherence analysis of electromyography (EMG) signals in essential tremor (ET) suggests that tremor in the right and left arm is induced by independent central oscillators. The sensorimotor cortex seems to be part of the tremor-generating neuronal network in ET. Here, we investigated using electroencephalography (EEG) whether the independence of central oscillators in ET is supported by the analysis of cortical activity.

METHODS

In 8 patients with ET, bilateral hand tremor was activated by wrist extension. EMGs from the wrist flexors and extensors were recorded simultaneously with an EEG. EEG-EMG coherence was estimated for 74 epochs of 60 s duration.

RESULTS

In 42.6% of the cases, EEG-EMG coherence at the tremor frequency existed only with the contralateral sensorimotor cortex. However, 21.6% of the tremor-EMGs were coherent with EEG activity over both the contralateral and ipsilateral sensorimotor cortex. Bilateral and exclusively contralateral EEG-EMG coherence could alternate within the same recording. Bilateral EEG-EMG coherence was associated with increased right-left EEG-EEG coherence, increased right-left EMG-EMG coherence as well as with increased tremor strength.

CONCLUSIONS

In ET, central oscillators in the right and left brain are not entirely independent of each other. They may dynamically synchronise, presumably by interhemispheric coupling via the corpus callosum.

The seizure prediction characteristic: a general framework to assess and compare seizure prediction methods

The unpredictability of seizures is a central problem for all patients suffering from uncontrolled epilepsy. Recently, numerous methods have been suggested that claim to predict from the EEG the onset of epileptic seizures. In parallel, new therapeutic devices are in development that could control upcoming seizures provided that their onset is known in advance. A reliable clinical application controlling seizures, consisting of a seizure prediction method and an intervention system, would improve patient quality of life. The question therefore arises as to whether the performance of the seizure prediction methods is already sufficient for clinical applications. The answer requires assessment criteria to judge and compare these methods, but recognized criteria still do not exist. Based on clinical, behavioral, and statistical considerations, we suggest the "seizure prediction characteristic" to evaluate seizure prediction methods. Results of this approach are exemplified by its application to the "dynamical similarity index" seizure prediction method using 582 hours of intracranial EEG data, including 88 seizures.

Identification of nucleocytoplasmic cycling as a remote sensor in cellular signaling by databased modeling

Considerable progress has been made in identifying the molecular composition of complex signaling networks controlling cell proliferation, differentiation, and survival. However, to discover general building principles and predict the dynamic behavior of signaling networks, it is necessary to develop quantitative models based on experimental observations. Here we report a mathematical model of the core module of the Janus family of kinases (JAK)-signal transducer and activator of transcription (STAT) signaling pathway based on time-resolved measurements of receptor and STAT5 phosphorylation. Applying the fitted model, we can determine the quantitative behavior of STAT5 populations not accessible to experimental measurement. By in silico investigations, we identify the parameters of nuclear shuttling as the most sensitive to perturbations and verify experimentally the model prediction that inhibition of nuclear export results in a reduced transcriptional yield. The model reveals that STAT5 undergoes rapid nucleocytoplasmic cycles, continuously coupling receptor activation and target gene transcription, thereby forming a remote sensor between nucleus and receptor. Thus, dynamic modeling of signaling pathways can promote functional understanding at the systems level.

Transfer function analysis for clinical evaluation of dynamic cerebral autoregulation--a comparison between spontaneous and respiratory-induced oscillations

Oscillations of arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) can be used for non-invasive assessment of cerebral autoregulation using transfer function analysis. Either spontaneous oscillations (SPO) around 0.1 Hz or respiratory induced oscillations during deep breathing (DB) at a rate of 6/min have been used so far. We investigated 168 patients with severe carotid stenosis or occlusion to evaluate transfer function analysis and compare the SPO and DB approaches. ABP was assessed non-invasively (Finapres), CBFV was measured in the middle cerebral artery using transcranial Doppler sonography. Transfer function phase (P) and gain (G) were extracted from the respective spectra in a low (0.06-0.12 Hz) and high (0.20-0.30 Hz) frequency range (LF, HF) of SPO and from the 0.1 (LF) and 0.2 (HF) Hz peaks induced by DB. For SPO, significant side-to-side differences and differences between groups of severe and critical stenosis were found for P(LF), while P(HF) did not prove to be a significant parameter. G(LF) showed significant side-to-side differences, while G(HF) additionally differed significantly between severe and critical stenosis and occlusion, respectively. For DB, significant side-to-side differences were found for P(LF, HF). Mainly G(HF) differed significantly between the affected and contralateral sides, while both HF and LF gains showed lower values in groups with a higher degree of stenosis. Correlation between G and P values was generally poor. Using Bland-Altman plots a poor inter-method agreement was found mainly for P. Correlations between SPO and DB were higher for G than for P (LF r = 0.64 versus 0.44, HF 0.69 versus 0.28). Analysing reproducibility in 16 patients, only for P(LF, HF) of DB was a highly significant correlation found (Spearman's r up to 0.78). For G(LF, HF) correlations were significant for both SPO and DB with slightly higher r coefficients for SPO. In conclusion, the present study showed that (1) transfer functions P and G represent different information for characterization of dynamic cerebral autoregulation in the frequency domain. (2) Inter-method agreement between DB and SPO is poor for P and moderate for G values. (3) P extracted from DB has a higher reproducibility. (4) The extraction of P and G from the SPO phase spectra is critical and future work on standardizing this process is needed. (5) At present, the DB protocol might be slightly advantageous as a routine diagnostic tool.

Detection of very low-frequency oscillations of cerebral haemodynamics is influenced by data detrending

Recent studies were investigated that report spontaneous oscillations of cerebral perfusion in the very low-frequency range (0.01-0.04 Hz), emphasising details of spectral estimation. The effects of different spectral estimation procedures were compared, using simulated and clinical data. It was shown that data detrending, as used in many studies, can lead to an artifactual peak in the very low-frequency region of estimated power spectra, indicating that the peak cannot be taken as evidence of physiological oscillations. A quantitative, reliable method is described that can be used to assess very low-frequency oscillations. Using the method, very low-frequency oscillations were found in ten out of 17 healthy adults measured with transcranial Doppler (average frequency, 0.021 +/- 0.007 Hz, mean +/- SD), confirming earlier findings based on visual inspection of data.

Comment on "Kullback-Leibler and renormalized entropies: applications to electroencephalograms of epilepsy patients"

In a recent paper Quian Quiroga et al. [R. Quian Quiroga et al., Phys. Rev. E 62, 8380 (2000)] found renormalized entropy, formerly introduced as a complexity measure for the different regimes of a dynamical system, to be closely related to the standard Kullback-Leibler entropy. They assure this finding by reanalyzing electroencephalographic data of epilepsy patients, previously examined by exclusive use of renormalized entropy [K. Kopitzki et al., Phys. Rev. E 58, 4859 (1998)]. We argue that the general considerations undertaken by the authors and the experimental results do not justify this conclusion.

Essential tremor and cerebellar dysfunction: abnormal ballistic movements

BACKGROUND

Clinical characteristics reminiscent of cerebellar tremor occur in patients with advanced essential tremor. Ballistic movements are known to be abnormal in cerebellar disease. The hypothesis was proposed that ballistic movements are abnormal in essential tremor, reflecting cerebellar dysfunction.

OBJECTIVE

To elucidate the role of the cerebellum in the pathophysiology of essential tremor.

METHODS

Kinematic parameters and the triphasic electromyographic (EMG) components of ballistic flexion elbow movements were analysed in patients assigned to the following groups: healthy controls (n = 14), pure essential postural tremor (ET(PT); n = 17), and essential tremor with an additional intention tremor component (ET(IT); n = 15).

RESULTS

The main findings were a delayed second agonist burst (AG(2)) and a relatively shortened deceleration phase compared with acceleration in both the essential tremor groups. These abnormalities were most pronounced in the ET(IT) group, which had additional prolongation of the first agonist burst (AG(1)) and a delayed antagonist burst (ANT).

CONCLUSIONS

Abnormalities of the triphasic pattern and kinematic parameters are consistent with a disturbed cerebellar timing function in essential tremor. These abnormalities were most pronounced in the ET(IT) group. The cerebellar dysfunction in essential tremor could indicate a basic pathophysiological mechanism underlying this disorder. ET(PT) and ET(IT) may represent two expressions within a continuous spectrum of cerebellar dysfunction in relation to the timing of muscle activation during voluntary movements.

Parameter identification in dynamical models of anaerobic waste water treatment

Biochemical reactions can often be formulated mathematically as ordinary differential equations. In the process of modeling, the main questions that arise are concerned with structural identifiability, parameter estimation and practical identifiability. To clarify these questions and the methods how to solve them, we analyze two different second order models for anaerobic waste water treatment processes using two data sets obtained from different experimental setups. In both experiments only biogas production rate was measured which complicates the analysis considerably. We show that proving structural identifiability of the mathematical models with currently used methods fails. Therefore, we introduce a new, general method based on the asymptotic behavior of the maximum likelihood estimator to show local structural identifiability. For parameter estimation we use the multiple shooting approach which is described. Additionally we show that the Hessian matrix approach to compute confidence intervals fails in our examples while a method based on Monte Carlo Simulation works well.

A rational approach to dose reduction in CT: individualized scan protocols

The aim of this study was to demonstrate that dose reduction and constant image quality can be achieved by adjusting X-ray dose to patient size. To establish the relation between patient size, image quality and dose we scanned 19 patients with reduced dose. Image noise was measured. Four radiologists scored image quality subjectively, whereby a higher score meant less image quality. A reference patient diameter was determined for which the dose was just sufficient. Then 22 patients were scanned with the X-ray dose adjusted to their size. Again, image noise was measured and subjective image quality was scored. The dose reduction compared with the standard protocol was calculated. In the first group the measured noise was correlated to the patient diameter (rho=0.78). This correlation is lost in the second group (rho=-0.13). The correlation between patient diameter and subjective image quality scores changes from rho=0.60 (group 1) to rho=-0.69 (group 2). Compared with the standard protocol, the dose was reduced (mean 28%, range 0-76%) in 19 of 22 patients (86%). Dose reduction and constant noise can be achieved when the X-ray dose is adjusted to the patient diameter. With constant image noise the subjective image quality increases with larger patients.

Artifact analysis of approximate helical cone-beam CT reconstruction algorithms

In this paper, four approximate cone-beam CT reconstruction algorithms are compared: Advanced single slice rebinning (ASSR) as a representative of algorithms employing a two dimensional approximation, PI, PI-SLANT, and 3-PI which all use a proper three dimensional back-projection. A detailed analysis of the image artifacts produced by these techniques shows that aliasing in the z-direction is the predominant source of artifacts for a 16-row scanner with 1.25 mm nominal slice thickness. For a detector with isotropic resolution of 0.5 mm, we found that ASSR and PI produce different kinds of artifacts which are almost at the same level, while PI-SLANT produces none of these artifacts. It is shown that the use of redundant data in the 3-PI method suppresses aliasing artifacts efficiently for both scanners.

Delay estimation for cortico-peripheral relations

In neurophysiology, time delays between concurrently measured time series are usually estimated from the slope of a straight line fitted to the phase spectrum. We point out that this estimate is valid only in the case in which, one signal is a mere time-delayed copy of the other one. We present a procedure for delay estimation that applies to a much wider class of systems with nontrivial phase spectrum like for example lowpass filters. The procedure is based on the Hilbert transform relation between the phase of a linear system and its log gain. The Hilbert transform relation is nonlocal in frequency space, a fact that limits its applicability to experimental data. We explore these limits, and demonstrate that the method is applicable to neurophysiological time series. We present the successful application of the Hilbert transform behavior method to concurrently recorded epicortical brain activity and peripheral tremor. We point out and explain physiologically unreasonable delay estimates given by the traditional method. Finally, we discuss the assumptions underlying the applicability of the Hilbert transform method in the neuroscience context.

Variability of frequency and phase between antagonistic muscle pairs in pathological human tremors

We investigated the electromyographic activity (EMG) of flexor and extensor muscles with different hand positions in patients with essential (ET) and parkinsonian (PD) tremor. Using a previously developed bootstrap method and standard cross-spectral analysis, we performed statistical tests to assess the effect of hand position on: (1) the frequency of the EMG; and (2) the phase between the EMGs recorded from antagonistic muscle pairs. Frequency as well as phases changed significantly with different positions of the hands but not during the recordings when the position was left unchanged. Besides confirmation that frequency and phase are stationary and reliable parameters during short-term recordings under controlled laboratory conditions, these results are of particular interest for ambulatory long-term tremor measurements. A higher variability of the estimated parameters reported in long-term recordings may perhaps reflect a patient's mobility only. Our study shows that long-term recording systems should have the means to monitor the patient's movements to provide reliable results.

Identifying physical properties of a CO2 laser by dynamical modeling of measured time series

We estimate internal parameters of a Q-switched CO2 laser by fitting trajectories of the four-level model to measured scalar time series. The four-level model is a five-dimensional nonlinear system of ordinary differential equations. A multiple shooting technique is used to construct the unobserved time courses of the population densities and to reveal the dependence of the parameters on the excitation current. For excitations barely above the laser threshold large pulse variations are identified as an effect of small variations of the pump parameter.

Analysis of forced expired volume signals using multi-exponential functions

Patients with pulmonary disease are often unable to complete forced expiration manoeuvres. The aim of the study is to evaluate whether forced vital capacity (FVC), the volume exhaled at the end of completed forced expiration, can be estimated by extrapolating volume-time curves obtained from uncompleted manoeuvres. The suitability of mono-, bi-, and tri-exponential functions to characterise complete volume-time curves from 50 subjects is investigated. Mono-exponential modelling is insufficient, whereas bi-exponential fitting yields an adequate description for 47 data sets. Tri-exponential models lead to overfitting in all but three cases (normalised sum of least squares: 50.2 +/- 34.5 for mono-, 2.76 +/- 4.11 for bi-, 2.74 +/- 4.19 for tri-exponential modelling; condition number of the correlation matrix: 1.0025 +/- 0.0004 for mono-, 1.08 +/- 0.08 for bi-, 34.7 +/- 100.1 for tri-exponential fitting (mean +/- SD)). Thus, FVC is estimated by the extrapolation of 27 uncompleted spirograms using bi- or tri-exponential models, depending on their accordance with measured data and on the identifiability of their parameters. This algorithm yields unbiased estimates (difference from measured inspiratory vital capacity: 0.01 +/- 0.21 L). This method can be used for investigation of the lung function of subjects who cannot complete the forced expiration manoeuvre.

Detection of sleep apnea with the forced oscillation technique compared to three standard polysomnographic signals

BACKGROUND

The forced oscillation technique (FOT) allows analysis of the upper airway impedance and, hence, detection of obstructive sleep apnea.

OBJECTIVE

To evaluate FOT with respect to sensitivity and to specificity in online detection of sleep-disordered breathing patterns and to compare algorithmic onset detection time with manual onset time markers of staff physicians.

METHODS

We compared the absolute value mid R:Zmid R: of the impedance with three routinely obtained polysomnographic signals - nasal airflow V(nasal), thoracic excursion Thox and esophageal pressure P(es) - by retrospective analysis of the diagnostic polysomnograms of 51 patients. For each signal we evaluated algorithms for online detection of respiratory events. For each out of five apnea classes, 50 respiratory events marked by staff physicians were drawn randomly from the 51 polysomnograms to optimize the online detection algorithms (learning set). The algorithm analyzes relative changes of signal baseline and amplitude. Again 50 respiratory events were drawn randomly for each apnea class to examine to what extent it is possible to detect event onsets with the algorithms (test set).

RESULTS

The sensitivity of the signals varied between 56 and 94% and was on average 74%. The specificity was 96 +/- 1.5% on average. The onset was detected 4-6 s after the initially evaluated onset of the staff physicians.

CONCLUSION

We conclude that nasal airflow and FOT are equivalent sensitive measurands for detection of respiratory events.