Antimicrobial Potential Of Some Plant Extracts Against Candida Species.

The increase in the resistance to antimicrobial drugs in use has attracted the attention of the scientific community, and medicinal plants have been extensively studied as alternative agents for the prevention of infections. The Candida genus yeast can become an opportunistic pathogen causing disease in immunosuppressive hosts. The purpose of this study was to evaluate dichloromethane and methanol extracts from Mentha piperita, Rosmarinus officinalis, Arrabidaea chica, Tabebuia avellanedae, Punica granatum and Syzygium cumini against Candida species through the analysis of Minimum Inhibitory Concentration (MIC). Results presented activity of these extracts against Candida species, especially the methanol extract.701065-

Comparison of Three-Dimensional in Situ Observations and Phase-Field Simulations of Microstructure Formation During Directional Solidification of Transparent Alloys Aboard the ISS

No abstract availabl

Comparative study of nonlinear properties of EEG signals of a normal person and an epileptic patient

Background: Investigation of the functioning of the brain in living systems has been a major effort amongst scientists and medical practitioners. Amongst the various disorder of the brain, epilepsy has drawn the most attention because this disorder can affect the quality of life of a person. In this paper we have reinvestigated the EEGs for normal and epileptic patients using surrogate analysis, probability distribution function and Hurst exponent. Results: Using random shuffled surrogate analysis, we have obtained some of the nonlinear features that was obtained by Andrzejak \textit{et al.} [Phys Rev E 2001, 64:061907], for the epileptic patients during seizure. Probability distribution function shows that the activity of an epileptic brain is nongaussian in nature. Hurst exponent has been shown to be useful to characterize a normal and an epileptic brain and it shows that the epileptic brain is long term anticorrelated whereas, the normal brain is more or less stochastic. Among all the techniques, used here, Hurst exponent is found very useful for characterization different cases. Conclusions: In this article, differences in characteristics for normal subjects with eyes open and closed, epileptic subjects during seizure and seizure free intervals have been shown mainly using Hurst exponent. The H shows that the brain activity of a normal man is uncorrelated in nature whereas, epileptic brain activity shows long range anticorrelation.Comment: Keywords:EEG, epilepsy, Correlation dimension, Surrogate analysis, Hurst exponent. 9 page

Stereoselective Synthesis of (-)-Spicigerolide

(-)-Spicigerolide was enantioselectively synthesized from a protected (S)-lactaldehyde. The synthesis of the polyacetylated framework relied on two Zn-mediated stereoselective additions of alkynes to aldehydes as well as a regiocontrolled [3,3]-sigmatropic rearrangement of an allylic acetate. The pyranone moiety was constructed via ring-closing metathesis

Action of Coriandrum sativum L. Essential Oil upon Oral Candida albicans Biofilm Formation

The efficacy of extracts and essential oils from Allium tuberosum, Coriandrum sativum, Cymbopogon martini, Cymbopogon winterianus, and Santolina chamaecyparissus was evaluated against Candida spp. isolates from the oral cavity of patients with periodontal disease. The most active oil was fractionated and tested against C. albicans biofilm formation. The oils were obtained by water-distillation and the extracts were prepared with macerated dried plant material. The Minimal Inhibitory Concentration—MIC was determined by the microdilution method. Chemical characterization of oil constituents was performed using Gas Chromatography and Mass Spectrometry (GC-MS). C. sativum activity oil upon cell and biofilm morphology was evaluated by Scanning Electron Microscopy (SEM). The best activities against planktonic Candida spp. were observed for the essential oil and the grouped F8–10 fractions from C. sativum. The crude oil also affected the biofilm formation in C. albicans causing a decrease in the biofilm growth. Chemical analysis of the F8–10 fractions detected as major active compounds, 2-hexen-1-ol, 3-hexen-1-ol and cyclodecane. Standards of these compounds tested grouped provided a stronger activity than the oil suggesting a synergistic action from the major oil constituents. The activity of C. sativum oil demonstrates its potential for a new natural antifungal formulation

Aneurismal subarachnoid hemorrhage in a Chilean population, with emphasis on risk factors

<p>Abstract</p> <p>Background</p> <p>Subarachnoid Hemorrhage (SAH) is caused principally by the rupture of intracranial aneurisms. Important risk factors have been described such as age, sex, hypertension (HT) and season of the year, among others. The objective is to investigate the demographic characteristics and possible risk factors in a population of Chilean patients.</p> <p>Methods</p> <p>This retrospective study was based on the analysis of 244 clinical records of patients diagnosed with aneurismal SAH who were discharged from the Instituto de Neurocirugía ASENJO in Santiago, Chile.</p> <p>Results</p> <p>The mean age of patients was 49.85 years and the male:female ratio was 1:2.7. The signs and symptoms were not different between sexes; cephalea (85.7%) was predominant, followed by loss of consciousness, vomiting/nausea and meningeal signs. Risk factors included sex, age and HT. Concordant with other reports, the incidence of SAH was greatest in spring.</p> <p>Conclusions</p> <p>The demographic characteristics and risk factors observed in patients with aneurismal SAH treated in ASENJO were comparable to those of other populations. We were not able to conclude that tobacco and alcohol consumption were risk factors for this population.</p

HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity

The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis

Genetic connectivity and hybridization with its siter species challenge the current management paradigm of white anglerfish (Lophius piscatorius)

Understanding the inter and intraspecific dynamics of fish populations is essential to promote effective management and conservation actions and to predict adaptation to changing conditions. This is possible through the analysis of thousands of genetic markers, which has proven useful to resolve connectivity among populations. Here, we have tackled this issue in the white anglerfish (Lophius piscatorius), which inhabits the Northeast Atlantic and Mediterranean Sea and coexists with its morphologically almost identical sister species, the black anglerfish (L. budegassa). Our genetic analyses based on 16,000 SNP markers and 700 samples reveal that i) the white anglerfish from the Mediterranean Sea and the Atlantic Ocean are genetically isolated, but that no differentiation can be observed within the later, and that ii) black and white anglerfish naturally hybridize, resulting in a population of about 20% of, most likely sterile, hybrids in some areas. These findings challenge the current paradigm of white anglerfish management, which considers three independent management units within the North East Atlantic and assumes that all mature fish have reproductive potential. Additionally, the northwards distribution of both species, likely due to temperature raises, calls for further monitoring of the abundance and distribution of hybrids to anticipate the effects of climate change in the interactions between both species and their potential resilience

MEG resting state functional connectivity in Parkinson's disease related dementia

Parkinson's disease (PD) related dementia (PDD) develops in up to 60% of patients, but the pathophysiology is far from being elucidated. Abnormalities of resting state functional connectivity have been reported in Alzheimer's disease (AD). The present study was performed to determine whether PDD is likewise characterized by changes in resting state functional connectivity. MEG recordings were obtained in 13 demented and 13 non-demented PD patients. The synchronization likelihood (SL) was calculated within and between cortical areas in six frequency bands. Compared to non-demented PD, PDD was characterized by lower fronto-temporal SL in the alpha range, lower intertemporal SL in delta, theta and alpha1 bands as well as decreased centro-parietal gamma band synchronization. In addition, higher parieto-occipital synchronization in the alpha2 and beta bands was found in PDD. The observed changes in functional connectivity are reminiscent of changes in AD, and may reflect reduced cholinergic activity and/or loss of cortico-cortical anatomical connections in PDD. © 2008 The Author(s)

Transfer entropy—a model-free measure of effective connectivity for the neurosciences

Understanding causal relationships, or effective connectivity, between parts of the brain is of utmost importance because a large part of the brain’s activity is thought to be internally generated and, hence, quantifying stimulus response relationships alone does not fully describe brain dynamics. Past efforts to determine effective connectivity mostly relied on model based approaches such as Granger causality or dynamic causal modeling. Transfer entropy (TE) is an alternative measure of effective connectivity based on information theory. TE does not require a model of the interaction and is inherently non-linear. We investigated the applicability of TE as a metric in a test for effective connectivity to electrophysiological data based on simulations and magnetoencephalography (MEG) recordings in a simple motor task. In particular, we demonstrate that TE improved the detectability of effective connectivity for non-linear interactions, and for sensor level MEG signals where linear methods are hampered by signal-cross-talk due to volume conduction