A computational study on altered theta-gamma coupling during learning and phase coding

There is considerable interest in the role of coupling between theta and gamma oscillations in the brain in the context of learning and memory. Here we have used a neural network model which is capable of producing coupling of theta phase to gamma amplitude firstly to explore its ability to reproduce reported learning changes and secondly to memory-span and phase coding effects. The spiking neural network incorporates two kinetically different GABAA receptor-mediated currents to generate both theta and gamma rhythms and we have found that by selective alteration of both NMDA receptors and GABAA,slow receptors it can reproduce learning-related changes in the strength of coupling between theta and gamma either with or without coincident changes in theta amplitude. When the model was used to explore the relationship between theta and gamma oscillations, working memory capacity and phase coding it showed that the potential storage capacity of short term memories, in terms of nested gamma-subcycles, coincides with the maximal theta power. Increasing theta power is also related to the precision of theta phase which functions as a potential timing clock for neuronal firing in the cortex or hippocampus

Shaping bursting by electrical coupling and noise

Gap-junctional coupling is an important way of communication between neurons and other excitable cells. Strong electrical coupling synchronizes activity across cell ensembles. Surprisingly, in the presence of noise synchronous oscillations generated by an electrically coupled network may differ qualitatively from the oscillations produced by uncoupled individual cells forming the network. A prominent example of such behavior is the synchronized bursting in islets of Langerhans formed by pancreatic \beta-cells, which in isolation are known to exhibit irregular spiking. At the heart of this intriguing phenomenon lies denoising, a remarkable ability of electrical coupling to diminish the effects of noise acting on individual cells. In this paper, we derive quantitative estimates characterizing denoising in electrically coupled networks of conductance-based models of square wave bursting cells. Our analysis reveals the interplay of the intrinsic properties of the individual cells and network topology and their respective contributions to this important effect. In particular, we show that networks on graphs with large algebraic connectivity or small total effective resistance are better equipped for implementing denoising. As a by-product of the analysis of denoising, we analytically estimate the rate with which trajectories converge to the synchronization subspace and the stability of the latter to random perturbations. These estimates reveal the role of the network topology in synchronization. The analysis is complemented by numerical simulations of electrically coupled conductance-based networks. Taken together, these results explain the mechanisms underlying synchronization and denoising in an important class of biological models

Preparation and Characterization of Fluorescence Probe from Assembly Hydroxyapatite Nanocomposite

A new nanocomposite fluorescence probe with thioglycolic acid (TA) functional layers embedded inside the hydroxyapatite nanoribbon spherulites has been synthesized. The fluorescence intensity of the novel probe is about 1.5–3.3-fold increase compared with the probe containing no TA. When used to detect cadmium ion, the most of original assembly nanoribbon spherulites structure in the novel probe is found to have been damaged to new flake structures. The mechanism of determining cadmium ion in alcohol solution has been studied. The present systematic study provides significant information on the effect of assembly nanostructure on the metal-enhanced fluorescence phenomenon

Investigation of the Role of TNF-α Converting Enzyme (TACE) in the Inhibition of Cell Surface and Soluble TNF-α Production by Acute Ethanol Exposure

Toll-like receptors (TLRs) play a fundamental role in the immune system by detecting pathogen associated molecular patterns (PAMPs) to sense host infection. Ethanol at doses relevant for humans inhibits the pathogen induced cytokine response mediated through TLRs. The current study was designed to investigate the mechanisms of this effect by determining whether ethanol inhibits TLR3 and TLR4 mediated TNF-α secretion through inhibition of transcription factor activation or post-transcriptional effects. In NF-κB reporter mice, activation of NF-κB in vivo by LPS was inhibited by ethanol (LPS alone yielded 170,000±35,300 arbitrary units of light emission; LPS plus ethanol yielded 56,120±16880, p = 0.04). Inhibition of protein synthesis by cycloheximide revealed that poly I:C- or LPS-induced secreted TNF-α is synthesized de novo, not released from cellular stores. Using real time RT-PCR, we found inhibition of LPS and poly I:C induced TNF-α gene transcription by ethanol. Using an inhibitor of tumor necrosis factor alpha converting enzyme (TACE), we found that shedding caused by TACE is a prerequisite for TNF-α release after pathogen challenge. Flow cytometry was used to investigate if ethanol decreases TNF-α secretion by inhibition of TACE. In cells treated with LPS, ethanol decreased both TNF-α cell surface expression and secretion. For example, 4.69±0.60% of untreated cells were positive for cell surface TNF-α, LPS increased this to 25.18±0.85%, which was inhibited by ethanol (86.8 mM) to 14.29±0.39% and increased by a TACE inhibitor to 57.88±0.62%. In contrast, cells treated with poly I:C had decreased secretion of TNF-α but not cell surface expression. There was some evidence for inhibition of TACE by ethanol in the case of LPS, but decreased TNF-α gene expression seems to be the major mechanism of ethanol action in this system

A Bayesian Network Driven Approach to Model the Transcriptional Response to Nitric Oxide in Saccharomyces cerevisiae

The transcriptional response to exogenously supplied nitric oxide in Saccharomyces cerevisiae was modeled using an integrated framework of Bayesian network learning and experimental feedback. A Bayesian network learning algorithm was used to generate network models of transcriptional output, followed by model verification and revision through experimentation. Using this framework, we generated a network model of the yeast transcriptional response to nitric oxide and a panel of other environmental signals. We discovered two environmental triggers, the diauxic shift and glucose repression, that affected the observed transcriptional profile. The computational method predicted the transcriptional control of yeast flavohemoglobin YHB1 by glucose repression, which was subsequently experimentally verified. A freely available software application, ExpressionNet, was developed to derive Bayesian network models from a combination of gene expression profile clusters, genetic information and experimental conditions

Comparison of hemolytic activity of the intermediate subunit of Entamoeba histolytica and Entamoeba dispar lectins

Galactose and N-acetyl-D-galactosamine-inhibitable lectin of Entamoeba histolytica has roles in pathogenicity and induction of protective immunity in rodent models of amoebiasis. Recently, the intermediate subunit of the lectin, Igl1, of E. histolytica has been shown to have hemolytic activity. However, the corresponding lectin is also expressed in a non-virulent species, Entamoeba dispar, and another subunit, Igl2, is expressed in the protozoa. Therefore, in this study, we compared the activities of Igl1 and Igl2 subunits from E. histolytica and E. dispar using various regions of recombinant Igl proteins expressed in Escherichia coli. The recombinant E. dispar Igl proteins had comparable hemolytic activities with those of E. histolytica Igl proteins. Furthermore, Igl1 gene-silenced E. histolytica trophozoites showed less hemolytic activity compared with vector-transfected trophozoites, indicating that the expression level of Igl1 protein influences the activity. These results suggest that the lower hemolytic activity in E. dispar compared with E. histolytica reflects the lower expression level of Igl1 in the E. dispar parasite

Clinical and epidemiological aspects of a hepatitis E outbreak in Bangui, Central African Republic

<p>Abstract</p> <p>Background</p> <p>Outbreaks of hepatitis E frequently occur in tropical developing countries during the rainy season due to overflowing drains, short-circuiting of networks of clean water and use of contaminated water from wells. Hepatitis E virus (HEV) infections are usually accompanied by general symptoms of acute liver disease. This study was conducted to define the clinical and epidemiological aspects of the HEV outbreak that occurred in May 2004 in Bangui.</p> <p>Methods</p> <p>Blood samples were collected from 411 patients aged 1-87 years, most of whom presented with jaundice, asthenia or signs of uncomplicated malaria, for a transversal study from June 2004 to September 2005. Patients were recruited at 11 health care centres, including two referral hospitals, after they had given informed consent. The diagnosis of HEV was made with a commercial ELISA test to detect IgM and/or IgG antibodies. HEV RNA was amplified by RT-PCR to confirm the presence of the viral genome.</p> <p>Results</p> <p>The most frequent clinical signs found were jaundice (93.4%), vomiting (50.7%), hepatalgia (47.4%), hepatomegaly (30.9%) and asthenia (26.8%), which are the general clinical signs of hepatic disease. Acute hepatitis E was found in 213 patients (51.8%) who were positive for HEV IgM antibodies. The IgG anti-HEV seroprevalence during this outbreak was high (79.5%). The age group 18-34 years was more frequently infected (91.2%) than those aged 1-17 (78.0%) or over 34 (64.9%) (p < 10^-6). RT-PCR performed on 127 sera from the 213 IgM-HEV-positive patients was amplified, and the presence of the viral genome was found in 65 samples.</p> <p>Conclusion</p> <p>Although no specific clinical signs exist for hepatitis E infection, people presenting with jaundice, vomiting, hepatalgia, asthenia, hepatomegaly or distended abdomen with no signs of uncomplicated malaria in tropical developing countries should be sent to a laboratory for testing for hepatitis E.</p

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Selective Killing of Cancer Cells by Ashwagandha Leaf Extract and Its Component Withanone Involves ROS Signaling

Ashwagandha is a popular Ayurvedic herb used in Indian traditional home medicine. It has been assigned a variety of health-promoting effects of which the mechanisms remain unknown. We previously reported the selective killing of cancer cells by leaf extract of Ashwagandha (i-Extract) and its purified component Withanone. In the present study, we investigated its mechanism by loss-of-function screening (abrogation of i-Extract induced cancer cell killing) of the cellular targets and gene pathways.Randomized ribozyme library was introduced into cancer cells prior to the treatment with i-Extract. Ribozymes were recovered from cells that survived the i-Extract treatment. Gene targets of the selected ribozymes (as predicted by database search) were analyzed by bioinformatics and pathway analyses. The targets were validated for their role in i-Extract induced selective killing of cancer cells by biochemical and molecular assays. Fifteen gene-targets were identified and were investigated for their role in specific cancer cell killing activity of i-Extract and its two major components (Withaferin A and Withanone) by undertaking the shRNA-mediated gene silencing approach. Bioinformatics on the selected gene-targets revealed the involvement of p53, apoptosis and insulin/IGF signaling pathways linked to the ROS signaling. We examined the involvement of ROS-signaling components (ROS levels, DNA damage, mitochondrial structure and membrane potential) and demonstrate that the selective killing of cancer cells is mediated by induction of oxidative stress.Ashwagandha leaf extract and Withanone cause selective killing of cancer cells by induction of ROS-signaling and hence are potential reagents that could be recruited for ROS-mediated cancer chemotherapy