Dynamical modulation of hypersynchronous seizure onset with transcranial magneto-acoustic stimulation in a hippocampal computational model

Hypersynchronous (HYP) seizure onset is one of the frequently observed seizure-onset patterns in temporal lobe epileptic animals and patients, often accompanied by hippocampal sclerosis. However, the exact mechanisms and ion dynamics of the transition to HYP seizures remain unclear. Transcranial magneto-acoustic stimulation (TMAS) has recently been proposed as a novel non-invasive brain therapy method to modulate neurological disorders. Therefore, we propose a biophysical computational hippocampal network model to explore the evolution of HYP seizure caused by changes in crucial physiological parameters and design an effective TMAS strategy to modulate HYP seizure onset. We find that the cooperative effects of abnormal glial uptake strength of potassium and excessive bath potassium concentration could produce multiple discharge patterns and result in transitions from the normal state to the HYP seizure state and ultimately to the depolarization block state. Moreover, we find that the pyramidal neuron and the PV+ interneuron in HYP seizure-onset state exhibit saddle-node-on-invariant-circle/saddle homoclinic (SH) and saddle-node/SH at onset/offset bifurcation pairs, respectively. Furthermore, the response of neuronal activities to TMAS of different ultrasonic waveforms revealed that lower sine wave stimulation can increase the latency of HYP seizures and even completely suppress seizures. More importantly, we propose an ultrasonic parameter area that not only effectively regulates epileptic rhythms but also is within the safety limits of ultrasound neuromodulation therapy. Our results may offer a more comprehensive understanding of the mechanisms of HYP seizure and provide a theoretical basis for the application of TMAS in treating specific types of seizures.

Examining the low-voltage fast seizure-onset and its response to optogenetic stimulation in a biophysical network model of the hippocampus

Low-voltage fast (LVF) seizure-onset is one of the two frequently observed temporal lobe seizure-onset patterns. Depth electroencephalogram profile analysis illustrated that the peak amplitude of LVF onset was deep temporal areas, e.g., hippocampus. However, the specific dynamic transition mechanisms between normal hippocampal rhythmic activity and LVF seizure-onset remain unclear. Recently, the optogenetic approach to gain control over epileptic hyper-excitability both in vitro and in vivo has become a novel noninvasive modulation strategy. Here, we combined biophysical modeling to study LVF dynamics following changes in crucial physiological parameters, and investigated the potential optogenetic intervention mechanism for both excitatory and inhibitory control. In an Ammon's horn 3 (CA3) biophysical model with light-sensitive protein channelrhodopsin 2 (ChR2), we found that the cooperative effects of excessive extracellular potassium concentration of parvalbumin-positive (PV+) inhibitory interneurons and synaptic links could induce abundant types of discharges of the hippocampus, and lead to transitions from gamma oscillations to LVF seizure-onset. Simulations of optogenetic stimulation revealed that the LVF seizure-onset and morbid fast spiking could not be eliminated by targeting PV+ neurons, whereas the epileptic network was more sensitive to the excitatory control of principal neurons with strong optogenetic currents. We illustrate that in the epileptic hippocampal network, the trajectories of the normal and the seizure state are in close vicinity and optogenetic perturbations therefore may result in transitions. The network model system developed in this study represents a scientific instrument to disclose the underlying principles of LVF, to characterize the effects of optogenetic neuromodulation, and to guide future treatment for specific types of seizures.

The seizure classification of focal epilepsy based on the network motif analysis

Due to the complexity of focal epilepsy and its risk for transiting to the generalized epilepsy, the development of reliable classification methods to accurately predict and classify focal and generalized seizures is critical for the clinical management of patients with epilepsy. In order to holistically understand the seizure propagation behavior of focal epilepsy, we propose a three-node motif reduced network by respectively simplifying the focal region, surrounding healthy region and their critical regions as the single node. Because three-node motif can richly characterize information evolutions, the motif analysis method could comprehensively investigate the seizure behavior of focal epilepsy. Firstly, we define a new seizure propagation marker value to capture the seizure onsets and intensity. Based on the three-node motif analysis, it is shown that the focal seizure and spreading can be categorized as inhibitory seizure, focal seizure, focal-critical seizure and generalized seizures, respectively. The four types of seizures correspond to specific modal types respectively, reflecting the strong correlation between seizure behavior and information flow evolution. In addition, it is found that the intensity difference of outflow and inflow information from the critical node (connection heterogeneity) and the excitability of the critical node significantly affected the distribution and transition of the four seizure types. In particular, the method of local linear stability analysis also verifies the effectiveness of four types of seizures classification. In sum, this paper computationally confirms the complex dynamic behavior of focal seizures, and the study of criticality is helpful to propose novel seizure control strategies.

A simplified coronary model for diagnosis of ischemia-causing coronary stenosis

BACKGROUND AND OBJECTIVE

The functional assessment of the severity of coronary stenosis from coronary computed tomography angiography (CCTA)-derived fractional flow reserve (FFR) has recently attracted interest. However, existing algorithms run at high computational cost. Therefore, this study proposes a fast calculation method of FFR for the diagnosis of ischemia-causing coronary stenosis.

METHODS

We combined CCTA and machine learning to develop a simplified single-vessel coronary model for rapid calculation of FFR. First, a zero-dimensional model of single-vessel coronary was established based on CCTA, and microcirculation resistance was determined through the relationship between coronary pressure and flow. In addition, a coronary stenosis model based on machine learning was introduced to determine stenosis resistance. Computational FFR (cFFR) was then obtained by combining the zero-dimensional model and the stenosis model with inlet boundary conditions for resting (cFFRr) and hyperemic (cFFRh) aortic pressure, respectively. We retrospectively analyzed 75 patients who underwent clinically invasive FFR (iFFR), and verified the model accuracy by comparison of cFFR with iFFR.

RESULTS

The average computing time of cFFR was less than 2 s. The correlations between cFFRr and cFFRh with iFFR were r = 0.89 (p < 0.001) and r = 0.90 (p < 0.001), respectively. Diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio for cFFRr and cFFRh were 90.7%, 95.0%, 89.1%, 76.0%, 98.0%, 8.7, 0.1 and 92.0%, 95.0%, 90.9%, 79.2%, 98.0%, 10.5, 0.1, respectively.

CONCLUSIONS

The proposed model enables rapid prediction of cFFR and exhibits high diagnostic performance in selected patient cohorts. The model thus provides an accurate and time-efficient computational tool to detect ischemia-causing stenosis and assist with clinical decision-making.

Extracting the transition network of epileptic seizure onset

In presurgical monitoring, focal seizure onset is visually assessed from intracranial electroencephalogram (EEG), typically based on the selection of channels that show the strongest changes in amplitude and frequency. As epileptic seizure dynamics is increasingly considered to reflect changes in potentially distributed neural networks, it becomes important to also assess the interrelationships between channels. We propose a workflow to quantitatively extract the nodes and edges contributing to the seizure onset using an across-seizure scoring. We propose a quantification of the consistency of EEG channel contributions to seizure onset within a patient. The workflow is exemplified using recordings from patients with different degrees of seizure-onset consistency.

Band power modulation through intracranial EEG stimulation and its cross-session consistency

OBJECTIVE

Direct electrical stimulation of the brain through intracranial electrodes is currently used to probe the epileptic brain as part of pre-surgical evaluation, and it is also being considered for therapeutic treatments through neuromodulation. In order to effectively modulate neural activity, a given neuromodulation design must elicit similar responses throughout the course of treatment. However, it is unknown whether intracranial electrical stimulation responses are consistent across sessions. The objective of this study was to investigate the within-subject, cross-session consistency of the electrophysiological effect of electrical stimulation delivered through intracranial electroencephalography (iEEG).

APPROACH

We analysed data from 79 epilepsy patients implanted with iEEG who underwent brain stimulation as part of a memory experiment. We quantified the effect of stimulation in terms of band power modulation and compared this effect from session to session. As a reference, we made the same measurements during baseline periods.

MAIN RESULTS

In most sessions, the effect of stimulation on band power could not be distinguished from baseline fluctuations of band power. Stimulation effect was consistent in a third of the session pairs, while the rest had a consistency measure not exceeding the baseline standards. Cross-session consistency was highly correlated with the degree of band power increase, and it also tended to be higher when the baseline conditions were more similar between sessions.

SIGNIFICANCE

These findings can inform our practices for designing neuromodulation with greater efficacy when using direct electrical brain stimulation as a therapeutic treatment.

Spontaneous transitions to focal-onset epileptic seizures: A dynamical study

Given the complex temporal evolution of epileptic seizures, understanding their dynamic nature might be beneficial for clinical diagnosis and treatment. Yet, the mechanisms behind, for instance, the onset of seizures are still unknown. According to an existing classification, two basic types of dynamic onset patterns plus a number of more complex onset waveforms can be distinguished. Here, we introduce a basic three-variable model with two time scales to study potential mechanisms of spontaneous seizure onset. We expand the model to demonstrate how coupling of oscillators leads to more complex seizure onset waveforms. Finally, we test the response to pulse perturbation as a potential biomarker of interictal changes.

Effects of brain-derived neurotrophic factor and noise on transitions in temporal lobe epilepsy in a hippocampal network

Brain-derived neurotrophic factor (BDNF) has recently been implicated in the modulation of receptor activation leading to dynamic state transitions in temporal lobe epilepsy (TLE). In addition, the crucial role of neuronal noise in these transitions has been studied in electrophysiological experiments. However, the precise role of these factors during seizure generation in TLE is not known. Building on a previously proposed model of an epileptogenic hippocampal network, we included the actions of BDNF-regulated receptors and intrinsic noise. We found that the effects of both BDNF and noise can increase the activation of N-methyl-D-aspartate receptors leading to excessive C a 2 + flux, which induces abnormal fast spiking and bursting. Our results indicate that the combined effects have a strong influence on the seizure-generating network, resulting in higher firing frequency and amplitude. As correlations between firing increase, the synchronization of the entire network increases, a marker of the ictogenic transitions from normal to seizures-like dynamics. Our work on the effects of BDNF dynamics in a noisy environment might lead to an improved model-based understanding of the pathological mechanisms in TLE.

Network dynamics in the healthy and epileptic developing brain

Electroencephalography (EEG) allows recording of cortical activity at high temporal resolution. EEG recordings can be summarized along different dimensions using network-level quantitative measures, such as channel-to-channel correlation, or band power distributions across channels. These reveal network patterns that unfold over a range of different timescales and can be tracked dynamically. Here we describe the dynamics of network state transitions in EEG recordings of spontaneous brain activity in normally developing infants and infants with severe early infantile epileptic encephalopathies (n = 8, age: 1–8 months). We describe differences in measures of EEG dynamics derived from band power, and correlation-based summaries of network-wide brain activity. We further show that EEGs from different patient groups and controls may be distinguishable on a small set of the novel quantitative measures introduced here, which describe dynamic network state switching. Quantitative measures related to the sharpness of switching from one correlation pattern to another show the largest differences between groups. These findings reveal that the early epileptic encephalopathies are associated with characteristic dynamic features at the network level. Quantitative network-based analyses like the one presented here may in the future inform the clinical use of quantitative EEG for diagnosis.

Liposome-Mediated Gene Transfer into Established CNS Cell Lines, Primary Glial Cells, and in Vivo

Sufficient gene transfer into CNS-derived cells is the most crucial step to develop strategies for gene therapy. In this study liposome-mediated gene transfer using a β-galactosidase (β-GAL) reporter gene was performed in vitro (C6 glioma cells, NT2 neuronal precursor cells, 3T3 fibroblasts, primary glial cells) and in vivo. Using Trypan blue exclusion staining, optimal lipid concentration was observed in the range of 10-12 μg/mL. Under optimal conditions (80,000 cells/16 mm well, incubation overnight, lipid/DNA ratio = 1:18) a high transfection rate was achieved (<9% for C6 cells; <1% for NT2 cells). In primary cultures of glial cells a fair amount of positive stained cells (glial cell) was found, but the transfection efficiency was lower (<0.1%). A “boost-lipofection” markedly increased (twice) lipofection efficiency in C6 cells. Expression of β-GAL reached a maximum after 3-5 days. When the liposome–DNA complexes were injected/infused directly into the brains of adult rats, several weakly stained cells could be observed in the brain region adjacent to the injection site. It is concluded that liposome-mediated gene transfer is an efficient method for gene transfer into CNS cells in vitro, but the transfection efficiency into the rat brain in vivo is far too low and therefore not applicable.

Understanding Epileptiform After-Discharges as Rhythmic Oscillatory Transients

Electro-cortical activity in patients with epilepsy may show abnormal rhythmic transients in response to stimulation. Even when using the same stimulation parameters in the same patient, wide variability in the duration of transient response has been reported. These transients have long been considered important for the mapping of the excitability levels in the epileptic brain but their dynamic mechanism is still not well understood. To investigate the occurrence of abnormal transients dynamically, we use a thalamo-cortical neural population model of epileptic spike-wave activity and study the interaction between slow and fast subsystems. In a reduced version of the thalamo-cortical model, slow wave oscillations arise from a fold of cycles (FoC) bifurcation. This marks the onset of a region of bistability between a high amplitude oscillatory rhythm and the background state. In vicinity of the bistability in parameter space, the model has excitable dynamics, showing prolonged rhythmic transients in response to suprathreshold pulse stimulation. We analyse the state space geometry of the bistable and excitable states, and find that the rhythmic transient arises when the impending FoC bifurcation deforms the state space and creates an area of locally reduced attraction to the fixed point. This area essentially allows trajectories to dwell there before escaping to the stable steady state, thus creating rhythmic transients. In the full thalamo-cortical model, we find a similar FoC bifurcation structure. Based on the analysis, we propose an explanation of why stimulation induced epileptiform activity may vary between trials, and predict how the variability could be related to ongoing oscillatory background activity. We compare our dynamic mechanism with other mechanisms (such as a slow parameter change) to generate excitable transients, and we discuss the proposed excitability mechanism in the context of stimulation responses in the epileptic cortex.

Complementary analysis of the hard and soft protein corona: sample preparation critically effects corona composition

Here we demonstrate how a complementary analysis of nanocapsule-protein interactions with and without application media allows gaining insights into the so called hard and soft protein corona. We have investigated how both human plasma and individual proteins (human serum albumin (HSA), apolipoprotein A-I (ApoA-I)) adsorb and interact with hydroxyethyl starch (HES) nanocapsules possessing different functionalities. To analyse the hard protein corona we used sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) and a protein quantitation assay. No significant differences were observed with regards to the hard protein corona. For analysis of the soft protein corona we characterized the nanocapsule-protein interaction with isothermal titration calorimetry (ITC) and dynamic light scattering (DLS). DLS and ITC measurements revealed that a high amount of plasma proteins were adsorbed onto the capsules' surface. Although HSA was not detected in the hard protein corona, ITC measurements indicated the adsorption of an HSA amount similar to plasma with a low binding affinity and reaction heat. In contrast, only small amounts of ApoA-I protein adsorb to the capsules with high binding affinities. Through a comparison of these methods we have identified ApoA-I to be a component of the hard protein corona and HSA as a component of the soft corona. We demonstrate a pronounced difference in the protein corona observed depending on the type of characterization technique applied. As the biological identity of a particle is given by the protein corona it is crucial to use complementary characterization techniques to analyse different aspects of the protein corona.

A computational study of stimulus driven epileptic seizure abatement

Active brain stimulation to abate epileptic seizures has shown mixed success. In spike-wave (SW) seizures, where the seizure and background state were proposed to coexist, single-pulse stimulations have been suggested to be able to terminate the seizure prematurely. However, several factors can impact success in such a bistable setting. The factors contributing to this have not been fully investigated on a theoretical and mechanistic basis. Our aim is to elucidate mechanisms that influence the success of single-pulse stimulation in noise-induced SW seizures. In this work, we study a neural population model of SW seizures that allows the reconstruction of the basin of attraction of the background activity as a four dimensional geometric object. For the deterministic (noise-free) case, we show how the success of response to stimuli depends on the amplitude and phase of the SW cycle, in addition to the direction of the stimulus in state space. In the case of spontaneous noise-induced seizures, the basin becomes probabilistic introducing some degree of uncertainty to the stimulation outcome while maintaining qualitative features of the noise-free case. Additionally, due to the different time scales involved in SW generation, there is substantial variation between SW cycles, implying that there may not be a fixed set of optimal stimulation parameters for SW seizures. In contrast, the model suggests an adaptive approach to find optimal stimulation parameters patient-specifically, based on real-time estimation of the position in state space. We discuss how the modelling work can be exploited to rationally design a successful stimulation protocol for the abatement of SW seizures using real-time SW detection.

A New Model System for the Study of Complex Dynamical Enzyme Reactions. I. A Nonlinear Enzyme Reaction in a Chemical Gradient

An experimental system for the study of biochemical reaction dynamics is introduced and de­ scribed. A one-enzyme reaction is extended by an artificial feedback loop in an electrochemical device. Cyclic voltammetry is used to show that the reaction rate depends nonlinearly on the amount of cosubstrate offered. For some sets of fixed parameter values a damped oscillatory approach of the steady state was observed. The usefulness of the systems theoretical concepts is discussed.

Dynamical Instabilities in a Diffusion Layer

We investigate the dynamics of a reaction-diffusion-convection enzyme system as a function of relevant parameters and observe reproducible types of periodic and aperiodic oscillations. These oscillations arise within a narrow diffusion layer only. Some implications for more complex reaction networks are considered

Transition to Higher Chaos in Diffusively Coupled Chemical Oscillators

A one-dimensional array of diffusively coupled identical oscillators is considered. It is demon­strated that coupling of two, three, four, and six oscillators can create chaos with one, two, three, and four positive Lyapunov characteristic exponents, respectively. We suggest that the turbulent behavior found with many coupled cells can be explained in terms of a high-order chaotic attractor.

A meeting of two chronobiological systems: circadian proteins Period1 and BMAL1 modulate the human hair cycle clock

The hair follicle (HF) is a continuously remodeled mini organ that cycles between growth (anagen), regression (catagen), and relative quiescence (telogen). As the anagen-to-catagen transformation of microdissected human scalp HFs can be observed in organ culture, it permits the study of the unknown controls of autonomous, rhythmic tissue remodeling of the HF, which intersects developmental, chronobiological, and growth-regulatory mechanisms. The hypothesis that the peripheral clock system is involved in hair cycle control, i.e., the anagen-to-catagen transformation, was tested. Here we show that in the absence of central clock influences, isolated, organ-cultured human HFs show circadian changes in the gene and protein expression of core clock genes (CLOCK, BMAL1, and Period1) and clock-controlled genes (c-Myc, NR1D1, and CDKN1A), with Period1 expression being hair cycle dependent. Knockdown of either BMAL1 or Period1 in human anagen HFs significantly prolonged anagen. This provides evidence that peripheral core clock genes modulate human HF cycling and are an integral component of the human hair cycle clock. Specifically, our study identifies BMAL1 and Period1 as potential therapeutic targets for modulating human hair growth.

Towards a large-scale model of patient-specific epileptic spike-wave discharges

Clinical electroencephalographic (EEG) recordings of the transition into generalised epileptic seizures show a sudden onset of spike-wave dynamics from a low-amplitude irregular background. In addition, non-trivial and variable spatio-temporal dynamics are widely reported in combined EEG/fMRI studies on the scale of the whole cortex. It is unknown whether these characteristics can be accounted for in a large-scale mathematical model with fixed heterogeneous long-range connectivities. Here, we develop a modelling framework with which to investigate such EEG features. We show that a neural field model composed of a few coupled compartments can serve as a low-dimensional prototype for the transition between irregular background dynamics and spike-wave activity. This prototype then serves as a node in a large-scale network with long-range connectivities derived from human diffusion-tensor imaging data. We examine multivariate properties in 42 clinical EEG seizure recordings from 10 patients diagnosed with typical absence epilepsy and 50 simulated seizures from the large-scale model using 10 DTI connectivity sets from humans. The model can reproduce the clinical feature of stereotypy where seizures are more similar within a patient than between patients, essentially creating a patient-specific fingerprint. We propose the approach as a feasible technique for the investigation of patient-specific large-scale epileptic features in space and time.

Loss of PIDD limits NF-κB activation and cytokine production but not cell survival or transformation after DNA damage

Activation of NF-κB (nuclear factor of kappa light chain gene enhancer in B cells) in response to DNA damage is considered to contribute to repair of genetic lesions, increased cell survival and cytokine release. The molecular mechanisms orchestrating this cytoplasmic event involve core components of the nuclear DNA damage response machinery, including ATM-kinase (ataxia telangiectasia mutated kinase) and PARP-1 (poly (ADP-ribose) polymerase 1). The physiological consequences of defective NF-κB activation in this context, however, remain poorly investigated. Here we report on the role of the 'p53-induced protein with a death domain', PIDD, which appears rate limiting in this process, as is PARP-1. Despite impaired NF-κB activation, DNA damage did not increase cell death or reduce clonal survival of various cell types lacking PIDD, such as mouse embryonic fibroblasts or stem and progenitor cells of the hematopoietic system. Furthermore, lymphomagenesis induced by γ-irradiation (IR) was unaffected by deficiency for PIDD or PARP-1, indicating that loss of DNA damage-triggered NF-κB signalling does not affect IR-driven tumorigenesis. However, loss of either gene compromised cytokine release after acute IR injury. Hence, we propose that NF-κB's most notable function after DNA damage in primary cells is related to the release of cytokines, thereby contributing to sterile inflammation.

The importance of modeling epileptic seizure dynamics as spatio-temporal patterns

The occurrence of seizures is the common feature across the spectrum of epileptic disorders. We describe how the use of mechanistic neural population models leads to novel insight into the dynamic mechanisms underlying two important types of epileptic seizures. We specifically stress the need for a spatio-temporal description of the rhythms to deal with the complexity of the pathophenotype. Adapted to functional and structural patient data, the macroscopic models may allow a patient-specific description of seizures and prediction of treatment outcome.

Phase space approach for modeling of epileptic dynamics

Epileptic electroencephalography recordings can be described in terms of four prototypic wave forms: fast sinusoidal oscillations, large slow waves, fast spiking, and spike waves. On the macroscopic level, these wave forms have been modeled by different mechanistic models which share canonical features. Here we derive a minimal model of excitatory and inhibitory processes with features common to all previous models. We can infer that at least three interacting processes are required to support the prototypic epileptic dynamics. Based on a separation of time scales we analyze the model in terms of interacting manifolds in phase space. This allows qualitative reverse engineering of all epileptic wave forms and transitions between them. We propose this method as a complement to traditional approaches to modeling epileptiform rhythms.

A spatially extended model for macroscopic spike-wave discharges

Spike-wave discharges are a distinctive feature of epileptic seizures. So far, they have not been reported in spatially extended neural field models. We study a space-independent version of the Amari neural field model with two competing inhibitory populations. We show that this competition leads to robust spike-wave dynamics if the inhibitory populations operate on different time-scales. The spike-wave oscillations present a fold/homoclinic type bursting. From this result we predict parameters of the extended Amari system where spike-wave oscillations produce a spatially homogeneous pattern. We propose this mechanism as a prototype of macroscopic epileptic spike-wave discharges. To our knowledge this is the first example of robust spike-wave patterns in a spatially extended neural field model.

[Traumatic optic neuropathy: a review of the literature in the light of personal experiences]

BACKGROUND

Therapy of traumatic optic neuropathy (TON) is still discussed controversially. Studies of medical treatment and surgical decompression of the nerve could not find any correlation between therapy and result. Today's knowledge of the treatment in TON is to be analyzed by the latest results in the literature, supplemented by personal experiences with our own patients, who underwent a combination of corticosteroids and surgical decompression.

METHODS

The study group consisted of 9 patients at the age of 13-58 years. 8 patients suffered from a cranial trauma, 1 patient had sinus surgery, which resulted in an indirect damage of the optic nerve. Pretherapeutically, 5 patients had residual vision, 4 patients were blind. A fracture line through the optic canal in the CT-scan was seen in 6 cases. Decompression was performed within 24 hours in 3 cases; in the worst 3 cases it took up to 8 days. In 8 patients the intervention was performed via an endonasal, microscopic-endoscopic approach, once it was done transfacially. Simultaneously, high-dose corticosteroids were administered.

RESULTS

All patients with a residual vision before therapy showed an improvement of their visual acuity: In the best case visual acuity changed from perception of light to 0.8. All patients with posttraumatic blindness remained blind after therapy.

CONCLUSION

A surgical decompression may be considered in patients with residual vision. Referring to the latest data in the literature endonasal, microscopic-endoscopic decompression is then to be combined with simultaneous application of high-dose corticosteroids. In our opinion, a mere wait-and-see strategy completely without any treatment can hardly be recommended.

The cycling hair follicle as an ideal systems biology research model

In the postgenomic era, systems biology has rapidly emerged as an exciting field predicted to enhance the molecular understanding of complex biological systems by the use of quantitative experimental and mathematical approaches. Systems biology studies how the components of a biological system (e.g. genes, transcripts, proteins, metabolites) interact to bring about defined biological function or dysfunction. Living systems may be divided into five dimensions of complexity: (i) molecular; (ii) structural; (iii) temporal; (iv) abstraction and emergence; and (v) algorithmic. Understanding the details of these dimensions in living systems is the challenge that systems biology aims to address. Here, we argue that the hair follicle (HF), one of the signature features of mammals, is a perfect and clinically relevant model for systems biology research. The HF represents a stem cell-rich, essentially autonomous mini-organ, whose cyclic transformations follow a hypothetical intrafollicular "hair cycle clock" (HCC). This prototypic neuroectodermal-mesodermal interaction system, at the cross-roads of systems and chronobiology, encompasses various levels of complexity as it is subject to both intrafollicular and extrafollicular inputs (e.g. intracutaneous timing mechanisms with neural and systemic stimuli). Exploring how the cycling HF addresses the five dimensions of living systems, we argue that a systems biology approach to the study of hair growth and cycling, in man and mice, has great translational medicine potential. Namely, the easily accessible human HF invites preclinical and clinical testing of novel hypotheses generated with this approach.

Systems biology and modeling in neuroblastoma: practicalities and perspectives

Neuroblastoma (NB) is a common pediatric malignancy characterized by clinical and biological heterogeneity. A host of prognostic markers are available, contributing to accurate risk stratification and appropriate treatment allocation. Unfortunately, outcome is still poor for many patients, indicating the need for a new approach with enhanced utilization of the available biological data. Systems biology is a holistic approach in which all components of a biological system carry equal importance. Systems biology uses mathematical modeling and simulation to investigate dynamic interactions between system components, as a means of explaining overall system behavior. Systems biology can benefit the biomedical sciences by providing a more complete understanding of human disease, enhancing the development of targeted therapeutics. Systems biology is largely contiguous with current approaches in NB, which already employ an integrative and pseudo-holistic approach to disease management. Systems modeling of NB offers an optimal method for continuing progression in this field, and conferring additional benefit to current risk stratification and management. Likewise, NB provides an opportunity for systems biology to prove its utility in the context of human disease, since the biology of NB is comprehensively characterized and, therefore, suited to modeling. The purpose of this review is to outline the benefits, challenges and fundamental workings of systems modeling in human disease, using a specific example of bottom-up modeling in NB. The intention is to demonstrate practical requirements to begin bridging the gap between biological research and applied mathematical approaches for the mutual gain of both fields, and with additional benefits for clinical management.

[Atypical gout tophi for differential diagnosis of head and neck tumors : case report and review of the literature]

Gout is a mostly hereditary metabolic disease and is considered a disease of affluence. The disease is promoted by a purine-rich diet and shows an intermittent course of inflammatory joint manifestations and periods free of symptoms. The pathognomonic sign of the disease is an acute and very painful monarthritis with typical local deposits of uric acid, so-called gout tophi. No or inadequate treatment leads to the chronic form of gouty arthritis characterized more by joint destruction than by persistent pain. In head and neck gout tophi are seen as nodular lesions along the outer helical edges of the auricle. A case report of gout manifestation in the infratemporal fossa, deriving from the temporomandibular joint, with arrosion of the bony skull base demonstrates gout as a relevant disease for the ENT clinician. Potential diagnostic difficulties as well as recommendations for a therapeutic regimen of gouty lesions in such critical localizations will be reviewed.

[Short and long term results of endolymphatic sac surgery: a patient-questionnaire based study]

INTRODUCTION

The endolymphatic sac surgery for the treatment of Meniere's disease has been described since the 1920s. The success rate of this technique in terms of vertigo control has been reported to be 50-80%. However, the value of this treatment method remained controversial. Furthermore, the reliable identification of the endolymphatic sac intraoperatively can be challenging in some cases. This study examines the short-, middle- and long-term results in a larger cohort of patients.

MATERIALS AND METHODS

In 74 patients, vertigo control, tinnitus and degree of satisfaction was evaluated by means of a questionnaire retrospectively. Additionally, the diagnostic value of the electrocochleography (EcochG) was determined.

RESULTS

The overall vertigo control rate was more than 70% in patients followed up for two years and has reached 81% in patients followed up for more than two years. Hearing preservation rate was 61%. Tinnitus has disappeared in 11% and improved in 23% of the patients. In 47% of the patients it was unchanged and in 19% worsened. The difference in EcochG results pre- versus postoperative was highly significant.

CONCLUSIONS

ELSS is a useful tool in the management of Ménière's disease, in particular in patients that do not benefit sufficiently from conservative therapy.

[Results in otosurgically treated patients with acoustic neuroma. Part 1: Facial nerve function after translabyrinthine and middle fossa resection]

BACKGROUND

Regardless of all efforts to preserve a residual hearing, facial nerve function is still the primary issue for patients with acoustic neuromas. Since alternative methods like the gamma-knife treatment are of increasing importance, results after surgery have to be compared and discussed critically.

PATIENTS

The results of 538 patients operated at the Dept. of Otolaryngology, Head and Neck Surgery, University of Wuerzburg between 1989 and 2004 are presented. 392 had surgery via a middle fossa, 146 via a translabyrinthine approach.

RESULTS

Shortly after surgery 82.2 % of patients showed no facial palsy. 74 patients had an incomplete, 7 a complete paresis. After 12 months 144 of the patients operated on via middle fossa approach showed no palsy, 13 had an incomplete and one a complete paresis. Out of 76 patients operated on translabyrinthine approach 75 had no paresis, one had an incomplete, and no patient had a complete paresis. There was no difference between intrameatal tumors and tumors extending beyond the porus. Regular facial nerve function was seen in 93 %, postoperatively. Permanent paresis was seen in 0.4 % of cases.

CONCLUSION

Acoustic neuroma confined to the internal meatus or with minor extension into the cerebello-pontine angle (i. e. no contact to structures of the brain stem or vessels of the posterior fossa) are feasible for resection via a middle fossa or translabyrinthine approach. The possibility of hearing preservation combined with low morbidity and good results of facial nerve function makes these approaches the treatment of choice for this group of tumors.

[Predictors of nodal metastasising in laryngeal squamous cell carcinomas as decision support for neck dissection: comprehensive analysis of literature]

BACKGROUND

A subset of advanced laryngeal squamous cell carcinomas (SCC) does not metastasize in regional lymph nodes (pN0). However, more than 30 % of tumors without signs of metastasizing in the clinical examination (cN0) show occult metastases. The guidelines of the German ENT-Society intend the extent of neck dissection (ND) depending on clinical stage of tumor and lymph nodes. If laryngeal surgery is followed by an adjuvant radiation/chemotherapy, ND is not always necessary. Histomorphological, immunohistochemical, or molecular parameters with predictive value for nodal metastasizing could support the planning for ND, especially in patients with cN0.

METHODS

Within the last 20 years there were many publications concerning this problem. Herein, we analyzed the results of 455 publications. We have chosen studies regarding the predictive value of tumor stage, grading, peritumorous inflammation, invasion of lymphatic vessels, angioneogenesis, proliferation, overexpression of p53 or cyclin D1, inhibitors of cyclin-dependent kinases, growth factors, apoptosis, cell-adhesion, nm23, metalloproteinases, DNA/ploidy as well as tumor genetics.

RESULTS

All examined parameters did not allow a fail-safe prediction of the risk for nodal metastasizing.

CONCLUSIONS

Up to now, reliable predictors do not exist. The investigation of above mentioned parameters in pre-operative tumor biopsies is not helpful for the planning of ND in the stage cN0 (out of T1).

The influence of static correlations on multivariate correlation analysis of the EEG

The choice of the EEG reference strongly influences the results derived from different correlation measures. Such a dependence may easily mislead the interpretation of the correlation structure of the brain activity. We provide a systematic study of the influence of the choice of reference on linear multivariate EEG correlation patterns as determined by sensitive correlation measures derived from the equal-time correlation matrix. In addition, an effective algorithm to extract the effect of static correlations is developed. The eigenvalues of the correlation matrix and their spacing statistics are studied for artificial time series with known correlation structure and for an epileptic EEG in various montages. The correction method proposed in this paper works with varying quality for different choices of the EEG reference. Furthermore, the optimal choice of the reference depends also on the correlation structure of the underlying system.

Event-based sonification of EEG rhythms in real time

OBJECTIVE

To introduce a sound synthesis tool for human EEG rhythms that is applicable in real time.

METHODS

We design an event-based sonification which suppresses irregular background and highlights normal and pathologic rhythmic activity.

RESULTS

We generated sound examples with rhythms from well-known epileptic disorders and find stereotyped rhythmic auditory objects in single channel and stereo display from generalized spike-wave runs. For interictal activity, we were able to separate focal rhythms from background activity and thus enable the listener to perceive its frequency, duration, and intensity while monitoring.

CONCLUSIONS

The proposed event-based sonification allows quick detection and identification of different types of rhythmic EEE events in real time and can thus be used to complement visual displays in monitoring and EEG feedback tasks.

SIGNIFICANCE

The significance of the work lies in the fact that it can be implemented for on-line monitoring of clinical EEG and for EEG feedback applications where continuous screen watching can be substituted or improved by the auditory information stream.

Localized short-range correlations in the spectrum of the equal-time correlation matrix

We suggest a procedure to identify those parts of the spectrum of the equal-time correlation matrix C where relevant information about correlations of a multivariate time series is induced. Using an ensemble average over each of the distances between eigenvalues, all nearest-neighbor distributions can be calculated individually. We present numerical examples, where (a) information about cross correlations is found in the so-called "bulk" of eigenvalues (which generally is thought to contain only random correlations) and where (b) the information extracted from the lower edge of the spectrum of C is statistically more significant than that extracted from the upper edge. We apply the analysis to electroencephalographic recordings with epileptic events.

[Malignant paranasal sinus tumors. Diagnosis, therapy and results]

BACKGROUND

Malignant neoplasmas of the paranasal sinuses are rare and present usually in advanced tumor stage due to the lack of early clinical symptoms.

PATIENTS AND METHODS

In the last 10 years, 63 patients with paranasal malignancies were treated at the Department of Otolaryngology, Head and Neck Surgery of the University of Würzburg. 33% of the patients showed an occupational exposition (wood-processing or metal industry). At the time of the first visit to our institution 95% of the patients presented with an extensive disease, staged T3 and T4. Adenocarcinoma (24%), squamous cell carcinoma (22%) and malignant melanoma (19%) were the most common histologies. Surgery combined with radiotherapy was the treatment strategy in 55 patients (87%).

RESULTS

Patients with a complete surgical resection showed a higher 5-year-survival rate (77%) than patients with an incomplete resection (56%). In 38% (n=21) of the patients treated with surgery and radiotherapy, a local recurrence of the tumor was observed. This recurrence localised in the skull base and/or the orbita/periorbita occurred most frequently in the first (46%) or the second year (31%).

CONCLUSION

The prognosis of malignant paranasal tumors depends mainly on the control of the local tumor growth. Modern strategies of surgical treatment in combination with radiotherapy need to be implemented in an effort to achieve a continuous remission.

Quantification of cross correlations in complex spatiotemporal systems

We propose a design of the equal time correlation matrix suitable for the analysis of multivariate time series with ill-defined phases. We present the cross-correlation analysis of model data sets taken from coupled stochastic oscillators and compare the concept with the results obtained from a conventional correlation matrix analysis. We show that the concept provides a higher sensitivity combined with a better statistical significance when quantifying weak cross correlations.

EEG analysis with nonlinear excitable media

The detection of patterns embedded within a complex, nonstationary, and noisy background activity is a crucial and important task in EEG analysis. The authors present a biologically inspired, analog approach to EEG analysis that is conceptually different from a variety of statistical approaches currently used. A nonlinear, excitable, spatially extended medium that is composed of diffusively coupled model neurons is considered. When EEG recordings are applied as local perturbations to such an excitable neural tissue, the induced transient changes in the dynamics of the perturbed system can be regarded as an instantaneous characterization of transient processes in the brain reflected by the EEG, e.g., in the form of a sequence of correlated dynamical events (patterns). Nonlinear excitable media can be implemented in form of an array of locally coupled integrated analog nonlinear electrical circuits called cellular neural networks, which represent a next evolutionary step in the parallel analog computer architecture. Using cellular neural networks, the authors show that the concept of signal-induced pattern generation allows an almost instantaneous and unsupervised detection of seizure onsets in EEG recordings. In addition, they show that a cellular neural network can be trained in a supervised way to approximate the degree of synchronization in EEG recordings. The resulting pattern-recognition device may be suitable for the prediction of epileptic seizures.

[Injuries of the head and neck in suicidal intention]

BACKGROUND

Injuries of the head and neck with suicidal intention might create serious situations that require rapid and interdisciplinary treatment.

METHODS AND PATIENTS

Twenty-seven patients with suicidal head and neck injuries were treated at the Department of oto-rhino-laryngology, head and neck surgery, University of Wurzburg/Germany, between 1991 and 2002. The medical histories were analyzed retrospectively.

RESULTS

Twenty-three of them were male, 4 female. Mean age at time of attempted suicidal was 48 years (18 - 90). One patient was already treated for a psychiatric disorder. None of the patients had a suicidal attempt in the history. Nine patients suffered from a pharynx or larynx trauma after strangulation. Four out of seven patients with cutting or stabbing injuries showed a perforation of the upper airways. Nine patients had gunshot traumas, one of them with perforation of the pharynx. Thirteen patients underwent immediate endoscopy under general anaesthesia followed by a neck exploration in 3 patients. Six patients received a temporary tracheotomy. All patients were considered suicidal for the duration of stay in the ENT-department resulting in a permanent supervision. All patients were transferred to a psychiatric unit as soon as possible for further treatment. A statistically significant accumulation was observed during the last third of a year. Over the period of 11 years, suicidal injuries of the head and neck tend to occur more frequently.

CONCLUSIONS

The presented study emphasizes the need of immediate surgical and intensive care treatment of patients with head and neck injuries due to suicide attempts as well as an adequate psychiatric supervision during as well as after the surgical treatment.

Detection and characterization of changes of the correlation structure in multivariate time series

We propose a method based on the equal-time correlation matrix as a sensitive detector for phase-shape correlations in multivariate data sets. The key point of the method is that changes of the degree of synchronization between time series provoke level repulsions between eigenstates at both edges of the spectrum of the correlation matrix. Consequently, detailed information about the correlation structure of the multivariate data set is imprinted into the dynamics of the eigenvalues and into the structure of the corresponding eigenvectors. The performance of the technique is demonstrated by application to N(f)-tori, autoregressive models, and coupled chaotic systems. The high sensitivity, the comparatively small computational effort, and the excellent time resolution of the method recommend it for application to the analysis of complex, spatially extended, nonstationary systems.