Molecular dynamics, density functional, ADMET predictions, virtual screening, and molecular interaction field studies for identification and evaluation of novel potential CDK2 inhibitors in cancer therapy

In this work, we have used molecular dynamics, density functional theory, virtual screening, ADMET predictions, and molecular interaction field studies to design and propose eight novel potential inhibitors of CDK2. The eight molecules proposed showed interesting structural characteristics that are required for inhibiting the CDK2 activity and show potential as drug candidates for the treatment of cancer. The parameters related to the Rule of Five were calculated, and only one of the molecules violated more than one parameter. One of the proposals and one of the drug-like compounds selected by virtual screening indicated to be promising candidates for CDK2-based cancer therapy.

Decision rules for egg recognition are related to functional roles and chemical cues in the queenless ant Dinoponera quadriceps

The capacity to distinguish colony members from strangers is a key component in social life. In social insects, this extends to the brood and involves discrimination of queen eggs. Chemical substances communicate colony affiliation for both adults and brood; thus, in theory, all colony members should be able to recognize fellow nestmates. In this study, we investigate the ability of Dinoponera quadriceps workers to discriminate nestmate and non-nestmate eggs based on cuticular hydrocarbon composition. We analyzed whether cuticular hydrocarbons present on the eggs provide cues of discrimination. The results show that egg recognition in D. quadriceps is related to both age and the functional role of workers. Brood care workers were able to distinguish nestmate from non-nestmate eggs, while callow and forager workers were unable to do so.

Existence results for a damped second order abstract functional differential equation with impulses

In this work we study the existence and regularity of mild solutions for a damped second order abstract functional differential equation with impulses. The results are obtained using the cosine function theory and fixed point criterions. (C) 2009 Elsevier Ltd. All rights reserved.

Existence results for abstract impulsive second-order neutral functional differential equations

We establish the existence of mild solutions for a class of impulsive second-order partial neutral functional differential equations with infinite delay in a Banach space. (C) 2009 Published by Elsevier Ltd

Approximate controllability of second-order distributed implicit functional systems

In this paper we study the approximate controllability of control systems with states and controls in Hilbert spaces, and described by a second-order semilinear abstract functional differential equation with infinite delay. Initially we establish a characterization for the approximate controllability of a second-order abstract linear system and, in the last section, we compare the approximate controllability of a semilinear abstract functional system with the approximate controllability of the associated linear system. (C) 2008 Elsevier Ltd. All rights reserved.

Existence of solutions for second order partial neutral functional differential equations

We establish existence of mild solutions for a class of abstract second-order partial neutral functional differential equations with unbounded delay in a Banach space.

Almost automorphic mild solutions to some partial neutral functional-differential equations and applications

The paper considers the existence and uniqueness of almost automorphic mild solutions to some classes of first-order partial neutral functional-differential equations. Sufficient conditions for the existence and uniqueness of almost automorphic mild solutions to the above-mentioned equations are obtained. As an application, a first-order boundary value problem arising in control systems is considered. (C) 2007 Elsevier Ltd. All fights reserved.

On a class of abstract neutral functional differential equations

By using the theory of semigroups of growth a, we discuss the existence of mild solutions for a class of abstract neutral functional differential equations. A concrete application to partial neutral functional differential equations is considered. (C) 2011 Elsevier Ltd. All rights reserved.

Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI

Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

From EEG to BOLD: Brain mapping and estimating transfer functions in simultaneous EEG-fMRI acquisitions

Simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) aims to disentangle the description of brain processes by exploiting the advantages of each technique. Most studies in this field focus on exploring the relationships between fMRI signals and the power spectrum at some specific frequency bands (alpha, beta, etc.). On the other hand, brain mapping of EEG signals (e.g., interictal spikes in epileptic patients) usually assumes an haemodynamic response function for a parametric analysis applying the GLM, as a rough approximation. The integration of the information provided by the high spatial resolution of MR images and the high temporal resolution of EEG may be improved by referencing them by transfer functions, which allows the identification of neural driven areas without strong assumptions about haemodynamic response shapes or brain haemodynamic`s homogeneity. The difference on sampling rate is the first obstacle for a full integration of EEG and fMRI information. Moreover, a parametric specification of a function representing the commonalities of both signals is not established. In this study, we introduce a new data-driven method for estimating the transfer function from EEG signal to fMRI signal at EEG sampling rate. This approach avoids EEG subsampling to fMRI time resolution and naturally provides a test for EEG predictive power over BOLD signal fluctuations, in a well-established statistical framework. We illustrate this concept in resting state (eyes closed) and visual simultaneous fMRI-EEG experiments. The results point out that it is possible to predict the BOLD fluctuations in occipital cortex by using EEG measurements. (C) 2010 Elsevier Inc. All rights reserved.

Depression in Parkinson`s disease: Convergence from voxel-based morphometry and functional magnetic resonance imaging in the limbic thalamus

Depression is the most frequent psychiatric disorder in Parkinson`s disease (PD). Although evidence Suggests that depression in PD is related to the degenerative process that underlies the disease, further studies are necessary to better understand the neural basis of depression in this population of patients. In order to investigate neuronal alterations underlying the depression in PD, we studied thirty-six patients with idiopathic PD. Twenty of these patients had the diagnosis of major depression disorder and sixteen did not. The two groups were matched for PD motor severity according to Unified Parkinson Disease Rating Scale (UPDRS). First we conducted a functional magnetic resonance imaging (fMRI) using an event-related parametric emotional perception paradigm with test retest design. Our results showed decreased activation in the left mediodorsal (MD) thalamus and in medial prefrontall cortex in PD patients with depression compared to those without depression. Based upon these results and the increased neuron count in MD thalamus found in previous studies, we conducted a region of interest (ROI) guided voxel-based morphometry (VBM) study comparing the thalamic volume. Our results showed an increased volume in mediodorsal thalamic nuclei bilaterally. Converging morphological changes and functional emotional processing in mediodorsal thalamus highlight the importance of limbic thalamus in PD depression. In addition this data supports the link between neurodegenerative alterations and mood regulation. (C) 2009 Elsevier Inc. All rights reserved.

Hyperplane navigation: A method to set individual scores in fMRI group datasets

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.

Abnormal Amygdala-Prefrontal Effective Connectivity to Happy Faces Differentiates Bipolar from Major Depression

Background: Bipolar disorder is frequently misdiagnosed as major depressive disorder, delaying appropriate treatment and worsening outcome for many bipolar individuals. Emotion dysregulation is a core feature of bipolar disorder. Measures of dysfunction in neural systems supporting emotion regulation might therefore help discriminate bipolar from major depressive disorder. Methods: Thirty-one depressed individuals-15 bipolar depressed (BD) and 16 major depressed (MDD), DSM-IV diagnostic criteria, ages 18-55 years, matched for age, age of illness onset, illness duration, and depression severity-and 16 age- and gender-matched healthy control subjects performed two event-related paradigms: labeling the emotional intensity of happy and sad faces, respectively. We employed dynamic causal modeling to examine significant among-group alterations in effective connectivity (EC) between right- and left-sided neural regions supporting emotion regulation: amygdala and orbitomedial prefrontal cortex (OMPFC). Results: During classification of happy faces, we found profound and asymmetrical differences in EC between the OMPFC and amygdala. Left-sided differences involved top-down connections and discriminated between depressed and control subjects. Furthermore, greater medication load was associated with an amelioration of this abnormal top-down EC. Conversely, on the right side the abnormality was in bottom-up EC that was specific to bipolar disorder. These effects replicated when we considered only female subjects. Conclusions: Abnormal, left-sided, top-down OMPFC-amygdala and right-sided, bottom-up, amygdala-OMPFC EC during happy labeling distinguish BD and MDD, suggesting different pathophysiological mechanisms associated with the two types of depression.

A Voxel-Based Morphometry Study of Frontal Gray Matter Correlates of Impulsivity

Impulsivity is a personality trait exhibited by healthy individuals, but excessive impulsivity is associated with some mental disorders. Lesion and functional, neuroimaging Studies indicate that the ventromedial prefrontal region (VMPFC), including the orbitofrontal cortex (OFC), anterior cingulate cortex (ACC) and medial prefrontal cortex, and the amygdala may modulate impulsivity and aggression. However, no morphometric study has examined the association between VMPFC and impulsivity. We hypothesized that healthy subjects with high impulsivity would have smaller volumes in these brain regions compared with those with low impulsivity. Sixty-two healthy Subjects were Studied (age 35.4 +/- 12.1 years) using a 1.5-T MRI system. The Barratt impulsiveness scale (BIS) was used to assess impulsivity. Images were processed using an optimized voxel-based morphometry (VBM) protocol. We calculated the correlations between BIS scale scores and the gray matter (GM) and white matter (WM) volumes of VMPFC and amygdala. GM volumes of the left and right OFC were inversely correlated with the BIS total score (P = 0.04 and 0.02, respectively). Left ACC GM Volumes had a tendency to be inversely correlated with the BIS total score (P = 0.05. Right OFC GM Volumes were inversely correlated with BIS nonplanning impulsivity, and left OFC GM volumes were inversely correlated with motor impulsivity. There were no significant WM volume correlations with impulsivity. The results Of this morphometry Study indicate that small OFC volume relate to high impulsivity and extend the prior finding that the VMPFC is involved in the circuit modulating impulsivity. HUM Brain Mapp 30:1188-1195, 2009. (C) 2008 Wiley-Liss, Inc.

Elevated striatal and decreased dorsolateral prefrontal cortical activity in response to emotional stimuli in euthymic bipolar disorder: no associations with psychotropic medication load

To examine abnormal patterns of frontal cortical-subcortical activity in response to emotional stimuli in euthymic individuals with bipolar disorder type I in order to identify trait-like, pathophysiologic mechanisms of the disorder. We examined potential confounding effects of total psychotropic medication load and illness variables upon neural abnormalities. We analyzed neural activity in 19 euthymic bipolar and 24 healthy individuals to mild and intense happy, fearful and neutral faces. Relative to healthy individuals, bipolar subjects had significantly increased left striatal activity in response to mild happy faces (p < 0.05, corrected), decreased right dorsolateral prefrontal cortical (DLPFC) activity in response to neutral, mild and intense happy faces, and decreased left DLPFC activity in response to neutral, mild and intense fearful faces (p < 0.05, corrected). Bipolar and healthy individuals did not differ in amygdala activity in response to either emotion. In bipolar individuals, there was no significant association between medication load and abnormal activity in these regions, but a negative relationship between age of illness onset and amygdala activity in response to mild fearful faces (p = 0.007). Relative to those without comorbidities, bipolar individuals with comorbidities showed a trend increase in left striatal activity in response to mild happy faces. Abnormally increased striatal activity in response to potentially rewarding stimuli and decreased DLPFC activity in response to other emotionally salient stimuli may underlie mood instabilities in euthymic bipolar individuals, and are more apparent in those with comorbid diagnoses. No relationship between medication load and abnormal neural activity in bipolar individuals suggests that our findings may reflect pathophysiologic mechanisms of the illness rather than medication confounds. Future studies should examine whether this pattern of abnormal neural activity could distinguish bipolar from unipolar depression.