Biomedical subjects

Thomas Maiwald

Publications and source records attributed to Thomas Maiwald.

6 recordsLinked to original sources

PubMed2006

Spatio-temporal patient-individual assessment of synchronization changes for epileptic seizure prediction.

OBJECTIVE: Abnormal synchronization of neurons plays a central role for the generation of epileptic seizures. Therefore, multivariate time series analysis techniques investigating relationships between the dynamics of different neural populations may offer advantages in predicting epileptic seizures. METHODS: We applied a phase and a lag synchronization measure to a selected subset of multicontact intracranial EEG recordings and assessed changes in synchronization with respect to seizure prediction. RESULTS: Patient individual results, group results, spatial aspects using focal and extra-focal electrode contacts as well as two evaluation schemes analyzing decreases and increases in synchronization were examined. Averaged sensitivity values of 60% are observed for a false prediction rate of 0.15 false predictions per hour, a seizure occurrence period of half an hour, and a prediction horizon of 10 min. For approximately half of all 21 patients, a statistically significant prediction performance is observed for at least one synchronization measure and evaluation scheme. CONCLUSIONS: The results indicate that synchronization changes in the EEG dynamics preceding seizures can be used for seizure prediction. Nevertheless, the underlying pathogenic mechanisms differ and both decreases and increases in synchronization may precede epileptic seizures depending on the structures investigated. SIGNIFICANCE: The prediction method, optimized values of intervention times, as well as preferred brain structures for the EEG recordings have to be determined for each patient individually offering the chance of a better patient-individual prediction performance.

Adolescent↗

PubMed2006

Host cell responses induced by hepatitis C virus binding.

Initiation of hepatitis C virus (HCV) infection is mediated by docking of the viral envelope to the hepatocyte cell surface membrane followed by entry of the virus into the host cell. Aiming to elucidate the impact of this interaction on host cell biology, we performed a genomic analysis of the host cell response following binding of HCV to cell surface proteins. As ligands for HCV-host cell surface interaction, we used recombinant envelope glycoproteins and HCV-like particles (HCV-LPs) recently shown to bind or enter hepatocytes and human hepatoma cells. Gene expression profiling of HepG2 hepatoma cells following binding of E1/E2, HCV-LPs, and liver tissue samples from HCV-infected individuals was performed using a 7.5-kd human cDNA microarray. Cellular binding of HCV-LPs to hepatoma cells resulted in differential expression of 565 out of 7,419 host cell genes. Examination of transcriptional changes revealed a broad and complex transcriptional program induced by ligand binding to target cells. Expression of several genes important for innate immune responses and lipid metabolism was significantly modulated by ligand-cell surface interaction. To assess the functional relevance and biological significance of these findings for viral infection in vivo, transcriptional changes were compared with gene expression profiles in liver tissue samples from HCV-infected patients or controls. Side-by-side analysis revealed that the expression of 27 genes was similarly altered following HCV-LP binding in hepatoma cells and viral infection in vivo. In conclusion, HCV binding results in a cascade of intracellular signals modulating target gene expression and contributing to host cell responses in vivo. Reprogramming of cellular gene expression induced by HCV-cell surface interaction may be part of the viral strategy to condition viral entry and replication and escape from innate host cell responses.

Antigens, Viral↗

PubMed2006

Testing statistical significance of multivariate time series analysis techniques for epileptic seizure prediction.

Nonlinear time series analysis techniques have been proposed to detect changes in the electroencephalography dynamics prior to epileptic seizures. Their applicability in practice to predict seizure onsets is hampered by the present lack of generally accepted standards to assess their performance. We propose an analytic approach to judge the prediction performance of multivariate seizure prediction methods. Statistical tests are introduced to assess patient individual results, taking into account that prediction methods are applied to multiple time series and several seizures. Their performance is illustrated utilizing a bivariate seizure prediction method based on synchronization theory.

Algorithms↗

PubMed2006

Do false predictions of seizures depend on the state of vigilance? A report from two seizure-prediction methods and proposed remedies.

PURPOSE: Available seizure-prediction algorithms are accompanied by high numbers of false predictions to achieve high sensitivity. Little is known about the extent to which changes in EEG dynamics contribute to false predictions. This study addresses potential causes and the circadian distribution of false predictions as well as their relation to the sleep-wake cycle. METHODS: In 21 patients, each with 24 h of interictal invasive EEG recordings, two methods, the dynamic similarity index and the mean phase coherence, were assessed with respect to time points of false predictions. Visual inspection of the invasive EEG data and additional scalp electroencephalogram data was performed at times of false predictions to identify possible correlates of changes in the EEG dynamics. RESULTS: A dependency of false predictions on the time of day is shown. Renormalized to the duration of the period patients are asleep and awake, 86% of all false predictions occurred during sleep for the dynamic similarity index and 68% for the mean phase coherence, respectively. Combining two reference intervals, one during sleep and one in an awake state, the dynamic similarity index increases its performance by reducing the number of false predictions by almost 50% without major changes in sensitivity. No obvious dependence of false predictions was noted on visible epileptic activity, such as spikes, sharp waves, or subclinical ictal patterns. CONCLUSIONS: Changes in the EEG dynamics related to the sleep-wake cycle contribute to limits of specificity of both seizure-prediction methods investigated. This may provide a clue for improving prediction methods in general. The combination of reference states yields promising results and may offer opportunities to increase further the performance of prediction methods.

Adolescent↗

PubMed2005

Gene expression profiling in polycythaemia vera: overexpression of transcription factor NF-E2.

Summary The molecular aetiology of polycythaemia vera (PV) remains unknown and the differential diagnosis between PV and secondary erythrocytosis (SE) can be challenging. Gene expression profiling can identify candidates involved in the pathophysiology of PV and generate a molecular signature to aid in diagnosis. We thus performed cDNA microarray analysis on 40 PV and 12 SE patients. Two independent data sets were obtained: using a two-step training/validation design, a set of 64 genes (class predictors) was determined, which correctly discriminated PV from SE patients. Separately 253 genes were identified to be upregulated and 391 downregulated more than 1.5-fold in PV compared with healthy controls (P < 0.01). Of the genes overexpressed in PV, 27 contained Sp1 sites: we therefore propose that altered activity of Sp1-like transcription factors may contribute to the molecular aetiology of PV. One Sp1 target, the transcription factor NF-E2 [nuclear factor (erythroid-derived 2)], is overexpressed 2- to 40-fold in PV patients. In PV bone marrow, NF-E2 is overexpressed in megakaryocytes, erythroid and granulocytic precursors. It has been shown that overexpression of NF-E2 leads to the development of erythropoietin-independent erythroid colonies and that ectopic NF-E2 expression can reprogram monocytic cells towards erythroid and megakaryocytic differentiation. Transcription factor concentration may thus control lineage commitment. We therefore propose that elevated concentrations of NF-E2 in PV patients lead to an overproduction of erythroid and, in some patients, megakaryocytic cells/platelets. In this model, the level of NF-E2 overexpression determines both the severity of erythrocytosis and the concurrent presence or absence of thrombocytosis.

Blotting, Northern↗

PubMed2005

Computational processing and error reduction strategies for standardized quantitative data in biological networks.

High-quality quantitative data generated under standardized conditions is critical for understanding dynamic cellular processes. We report strategies for error reduction, and algorithms for automated data processing and for establishing the widely used techniques of immunoprecipitation and immunoblotting as highly precise methods for the quantification of protein levels and modifications. To determine the stoichiometry of cellular components and to ensure comparability of experiments, relative signals are converted to absolute values. A major source for errors in blotting techniques are inhomogeneities of the gel and the transfer procedure leading to correlated errors. These correlations are prevented by randomized gel loading, which significantly reduces standard deviations. Further error reduction is achieved by using housekeeping proteins as normalizers or by adding purified proteins in immunoprecipitations as calibrators in combination with criteria-based normalization. Additionally, we developed a computational tool for automated normalization, validation and integration of data derived from multiple immunoblots. In this way, large sets of quantitative data for dynamic pathway modeling can be generated, enabling the identification of systems properties and the prediction of targets for efficient intervention.

Algorithms↗