Andrei Dragomir

Gene regulatory networks modelling using a dynamic evolutionary hybrid.

BackgroundInference of gene regulatory networks is a key goal in the quest for understanding fundamental cellular processes and revealing underlying relations among genes. With the availability of gene expression data, computational methods aiming at regulatory networks reconstruction are facing challenges posed by the datas high dimensionality, temporal dynamics or measurement noise. We propose an approach based on a novel multi-layer evolutionary trained neuro-fuzzy recurrent network (ENFRN) that is able to select potential regulators of target genes and describe their regulation type.ResultsThe recurrent, self-organizing structure and evolutionary training of our network yield an optimized pool of regulatory relations, while its fuzzy nature avoids noise-related problems. Furthermore, we are able to assign scores for each regulation, highlighting the confidence in the retrieved relations. The approach was tested by applying it to several benchmark datasets of yeast, managing to acquire biologically validated relations among genes.ConclusionsThe results demonstrate the effectiveness of the ENFRN in retrieving biologically valid regulatory relations and providing meaningful insights for better understanding the dynamics of gene regulatory networks.The algorithms and methods described in this paper have been implemented in a Matlab toolbox and are available from: http://bioserver-1.bioacademy.gr/DataRepository/Project_ENFRN_GRN/.

Investigating the complexity of respiratory patterns during the laryngeal chemoreflex

BackgroundThe laryngeal chemoreflex exists in infants as a primary sensory mechanism for defending the airway from the aspiration of liquids. Previous studies have hypothesized that prolonged apnea associated with this reflex may be life threatening and might be a cause of sudden infant death syndrome.MethodsIn this study we quantified the output of the respiratory neural network, the diaphragm EMG signal, during the laryngeal chemoreflex and eupnea in early postnatal (3–10 days) piglets. We tested the hypothesis that diaphragm EMG activity corresponding to reflex-related events involved in clearance (restorative) mechanisms such as cough and swallow exhibit lower complexity, suggesting that a synchronized homogeneous group of neurons in the central respiratory network are active during these events. Nonlinear dynamic analysis was performed using the approximate entropy to asses the complexity of respiratory patterns.ResultsDiaphragm EMG, genioglossal activity EMG, as well as other physiological signals (tracheal pressure, blood pressure and respiratory volume) were recorded from 5 unanesthetized chronically instrumented intact piglets. Approximate entropy values of the EMG during cough and swallow were found significantly (p < 0.05 and p < 0.01 respectively) lower than those of eupneic EMG.ConclusionReduced complexity values of the respiratory neural network output corresponding to coughs and swallows suggest synchronous neural activity of a homogeneous group of neurons. The higher complexity values exhibited by eupneic respiratory activity are the result of a more random behaviour, which is the outcome of the integrated action of several groups of neurons involved in the respiratory neural network.

Complexity of VTA DA neural activities in response to PFC transection in nicotine treated rats.

BackgroundThe dopaminergic (DA) neurons in the ventral tegmental area (VTA) are widely implicated in the addiction and natural reward circuitry of the brain. These neurons project to several areas of the brain, including prefrontal cortex (PFC), nucleus accubens (NAc) and amygdala. The functional coupling between PFC and VTA has been demonstrated, but little is known about how PFC mediates nicotinic modulation in VTA DA neurons. The objectives of this study were to investigate the effect of acute nicotine exposure on the VTA DA neuronal firing and to understand how the disruption of communication from PFC affects the firing patterns of VTA DA neurons.MethodsExtracellular single-unit recordings were performed on Sprague-Dawley rats and nicotine was administered after stable recording was established as baseline. In order to test how input from PFC affects the VTA DA neuronal firing, bilateral transections were made immediate caudal to PFC to mechanically delete the interaction between VTA and PFC.ResultsThe complexity of the recorded neural firing was subsequently assessed using a method based on the Lempel-Ziv estimator. The results were compared with those obtained when computing the entropy of neural firing. Exposure to nicotine triggered a significant increase in VTA DA neurons firing complexity when communication between PFC and VTA was present, while transection obliterated the effect of nicotine. Similar results were obtained when entropy values were estimated.ConclusionsOur findings suggest that PFC plays a vital role in mediating VTA activity. We speculate that increased firing complexity with acute nicotine administration in PFC intact subjects is due to the close functional coupling between PFC and VTA. This hypothesis is supported by the fact that deletion of PFC results in minor alterations of VTA DA neural firing when nicotine is acutely administered.

Complexity measures of the central respiratory networks during wakefulness and sleep

Since sleep is known to influence respiratory activity we studied whether the sleep state would affect the complexity value of the respiratory network output. Specifically, we tested the hypothesis that the complexity values of the diaphragm EMG (EMGdia) activity would be lower during REM compared to NREM. Furthermore, since REM is primarily generated by a homogeneous population of neurons in the medulla, the possibility that REM-related respiratory output would be less complex than that of the awake state was also considered. Additionally, in order to examine the influence of neuron vulnerabilities within the rostral ventral medulla (RVM) on the complexity of the respiratory network output, we inhibited respiratory neurons in the RVM by microdialysis of GABA(A) receptor agonist muscimol. Diaphragm EMG, nuchal EMG, EEG, EOG as well as other physiological signals (tracheal pressure, blood pressure and respiratory volume) were recorded from five unanesthetized chronically instrumented intact piglets (3-10 days old). Complexity of the diaphragm EMG (EMGdia) signal during wakefulness, NREM and REM was evaluated using the approximate entropy method (ApEn). ApEn values of the EMGdia during NREM and REM sleep were found significantly (p < 0.05 and p < 0.001, respectively) lower than those of awake EMGdia after muscimol inhibition. In the absence of muscimol, only the differences between REM and wakefulness ApEn values were found to be significantly different.

Investigating the Influence of HUVECs in the Formation of Glioblastoma Spheroids in High-Throughput Three-Dimensional Microwells

Glioblastoma (GBM) is the most common form of primary brain tumor with a high infiltrative capacity, increased vascularity, and largely elusive tumor progression mechanism. The current GBM treatment methods do not increase the patient survival rate and studies using two-dimensional (2D) cell cultures and in vivo animal models to investigate GBM behavior and mechanism have limitations. Therefore, there is an increasing need for in vitro three-dimensional (3D) models that closely mimic in vivo microenvironment of the GBM tumors to understand the underlying mechanisms of the tumor progression. In this study we propose to use a 3D in vitro model to overcome these limitations, using poly (ethylene glycol) dimethyl acrylate (PEGDA) hydrogel-based microwells and co-culture GBM (U87) cells and endothelial cells (HUVEC) in the 3D microwells to provide a 3D in vitro simulation of the tumor microenvironment. Furthermore, we investigated the gene expression differences of co-cultures by quantitative real-time PCR. Our results suggested that the relative expression profiles of tumor angiogenesis markers, PECAM1/CD31, and VEGFR2, in co-cultures are consistent with in vivo GBM studies. Furthermore, we suggest that our microwell platform could provide robust and useful 3D co-culture models for high-throughput drug screening and treatment of the GBM.

Gene Networks Inference From Expression Data Using a Recurrent Neuro-Fuzzy Approach

The reverse engineering paradigm is given increasing attention in computational molecular biology lately. One of the goals is to understand how gene regulatory networks (complex systems of genes, proteins and other molecules) function and interact to carry out specific cell functions. We present an approach for inferring the complex causal relationships among genes from microarray experimental data based on a recurrent neuro-fuzzy method. The method derives information on the gene interactions in a highly interpretable form (fuzzy rules) and takes into account dynamical aspects of genes regulation through its recurrent structure. We tested our approach on a set of genes known to be highly regulated during the yeast cell-cycle. The retrieved gene interactions correspond to the ones validated by previous biological studies, while our method surpasses previous computational techniques that attempted gene networks reconstruction, being able to retrieve significantly more biologically valid relationships among genes. At the same time, our method is able to predict time series for the expression of the genes based on the information extracted from a training subset of the data. The results prove highly accurate prediction capability

A Novel Data-Mining Approach Leveraging Social Media to Monitor Consumer Opinion of Sitagliptin

A novel data mining method was developed to gauge the experience of the drug Sitagliptin (trade name Januvia) by patients with diabetes mellitus type 2. To this goal, we devised a two-step analysis framework. Initial exploratory analysis using self-organizing maps was performed to determine structures based on user opinions among the forum posts. The results were a compilation of users clusters and their correlated (positive or negative) opinion of the drug. Subsequent modeling using network analysis methods was used to determine influential users among the forum members. These findings can open new avenues of research into rapid data collection, feedback, and analysis that can enable improved outcomes and solutions for public health and important feedback for the manufacturer.

Investigating the influence of PFC transection and nicotine on dynamics of AMPA and NMDA receptors of VTA dopaminergic neurons.

BackgroundAll drugs of abuse, including nicotine, activate the mesocorticolimbic system that plays critical roles in nicotine reward and reinforcement development and triggers glutamatergic synaptic plasticity on the dopamine (DA) neurons in the ventral tegmental area (VTA). The addictive behavior and firing pattern of the VTA DA neurons are thought to be controlled by the glutamatergic synaptic input from prefrontal cortex (PFC). Interrupted functional input from PFC to VTA was shown to decrease the effects of the drug on the addiction process. Nicotine treatment could enhance the AMPA/NMDA ratio in VTA DA neurons, which is thought as a common addiction mechanism. In this study, we investigate whether or not the lack of glutamate transmission from PFC to VTA could make any change in the effects of nicotine.MethodsWe used the traditional AMPA/NMDA peak ratio, AMPA/NMDA area ratio, and KL (Kullback-Leibler) divergence analysis method for the present study.ResultsOur results using AMPA/NMDA peak ratio showed insignificant difference between PFC intact and transected and treated with saline. However, using AMPA/NMDA area ratio and KL divergence method, we observed a significant difference when PFC is interrupted with saline treatment. One possible reason for the significant effect that the PFC transection has on the synaptic responses (as indicated by the AMPA/NMDA area ratio and KL divergence) may be the loss of glutamatergic inputs. The glutamatergic input is one of the most important factors that contribute to the peak ratio level.ConclusionsOur results suggested that even within one hour after a single nicotine injection, the peak ratio of AMPA/NMDA on VTA DA neurons could be enhanced.

Nicotine exposure increases the complexity of dopamine neurons in the parainterfascicular nucleus (PIF) sub-region of VTA

BackgroundRecent publications highlight differences within the sub-regions of the ventral tegmental area (VTA) including the parabrachial pigmented nucleus (PBP), parainterfascicular nucleus (PIF) and paranigral nucleus (PN) in the projections to the prefrontal cortex (PFC) and the glutamatergic pathway.MethodsIn order to characterize the effects of prenatal nicotine exposure on the mesocorticolimbic system of the rat offspring, local field potentials were recorded from 27 sites across the VTA of 9 rats aged 40–55 days. The extracellular VTA neural activities were analyzed using Approximate Entropy (ApEn) method. Approximate entropy values were then grouped according to each anatomic location including the PBP, PIF and PN.ResultsOur results have shown that the local field potentials corresponding to the neurons located in the PIF region of the VTA have ApEn values significantly higher (p = 2x10-4) in the maternal nicotine cases when compared to the saline.ConclusionTherefore, we speculate that the dopamine neurons located in the PIF sub-region of the VTA are very likely involved with the nicotine addiction.

Nonlinear dynamical analysis of carbachol induced hippocampal oscillations in mice

AbstractAim:Hippocampal neuronal network and synaptic impairment underlie learning and memory deficit in Alzheimers disease (AD) patients and animal models. In this paper, we analyzed the dynamics and complexity of hippocampal neuronal network synchronization induced by acute exposure to carbachol, a nicotinic and muscarinic receptor co-agonist, using the nonlinear dynamical model based on the Lempel-Ziv estimator. We compared the dynamics of hippocampal oscillations between wild-type (WT) and triple-transgenic (3xTg) mice, as an AD animal model. We also compared these dynamic alterations between different age groups (5 and 10 months). We hypothesize that there is an impairment of complexity of CCh-induced hippocampal oscillations in 3xTg AD mice compared to WT mice, and that this impairment is age-dependent.Methods:To test this hypothesis, we used electrophysiological recordings (field potential) in hippocampal slices.Results:Acute exposure to 100 μmol/L CCh induced field potential oscillations in hippocampal CA1 region, which exhibited three distinct patterns: (1) continuous neural firing, (2) repeated burst neural firing and (3) the mixed (continuous and burst) pattern in both WT and 3xTg AD mice. Based on Lempel-Ziv estimator, pattern (2) was significantly lower than patterns (1) and (3) in 3xTg AD mice compared to WT mice (P<0.001), and also in 10-month old WT mice compared to those in 5-month old WT mice (P<0.01).Conclusion:These results suggest that the burst pattern (theta oscillation) of hippocampal network is selectively impaired in 3xTg AD mouse model, which may reflect a learning and memory deficit in the AD patients.