Accumulation of major depressive episodes over time in a prospective study indicates that retrospectively assessed lifetime prevalence estimates are too low

<p>Abstract</p> <p>Background</p> <p>Most epidemiologic studies concerned with Major Depressive Disorder have employed cross-sectional study designs. Assessment of lifetime prevalence in such studies depends on recall of past depressive episodes. Such studies may underestimate lifetime prevalence because of incomplete recall of past episodes (recall bias). An opportunity to evaluate this issue arises with a prospective Canadian study called the National Population Health Survey (NPHS).</p> <p>Methods</p> <p>The NPHS is a longitudinal study that has followed a community sample representative of household residents since 1994. Follow-up interviews have been completed every two years and have incorporated the Composite International Diagnostic Interview short form for major depression. Data are currently available for seven such interview cycles spanning the time frame 1994 to 2006. In this study, cumulative prevalence was calculated by determining the proportion of respondents who had one or more major depressive episodes during this follow-up interval.</p> <p>Results</p> <p>The annual prevalence of MDD ranged between 4% and 5% of the population during each assessment, consistent with existing literature. However, 19.7% of the population had at least one major depressive episode during follow-up. This included 24.2% of women and 14.2% of men. These estimates are nearly twice as high as the lifetime prevalence of major depressive episodes reported by cross-sectional studies during same time interval.</p> <p>Conclusion</p> <p>In this study, prospectively observed cumulative prevalence over a relatively brief interval of time exceeded lifetime prevalence estimates by a considerable extent. This supports the idea that lifetime prevalence estimates are vulnerable to recall bias and that existing estimates are too low for this reason.</p

A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems

In order for agents in multi-agent systems (MAS) to be safe, they need to take into account the risks posed by the actions of other agents. However, the dominant paradigm in game theory (GT) assumes that agents are not affected by risk from other agents and only strive to maximise their expected utility. For example, in hybrid human-AI driving systems, it is necessary to limit large deviations in reward resulting from car crashes. Although there are equilibrium concepts in game theory that take into account risk aversion, they either assume that agents are risk-neutral with respect to the uncertainty caused by the actions of other agents, or they are not guaranteed to exist. We introduce a new GT-based Risk-Averse Equilibrium (RAE) that always produces a solution that minimises the potential variance in reward accounting for the strategy of other agents. Theoretically and empirically, we show RAE shares many properties with a Nash Equilibrium (NE), establishing convergence properties and generalising to risk-dominant NE in certain cases. To tackle large-scale problems, we extend RAE to the PSRO multi-agent reinforcement learning (MARL) framework. We empirically demonstrate the minimum reward variance benefits of RAE in matrix games with high-risk outcomes. Results on MARL experiments show RAE generalises to risk-dominant NE in a trust dilemma game and that it reduces instances of crashing by 7x in an autonomous driving setting versus the best performing baseline

Classification of migraine stages based on resting-state EEG power

© 2015 IEEE. Migraine is a chronic neurological disease characterized by recurrent moderate to severe headaches during a period like one month often in association with symptoms in human brain and autonomic nervous system. Normally, migraine symptoms can be categorized into four different stages: inter-ictal, pre-ictal, ictal, and post-ictal stages. Since migraine patients are difficulty knowing when they will suffer migraine attacks, therefore, early detection becomes an important issue, especially for low-frequency migraine patients who have less than 5 times attacks per month. The main goal of this study is to develop a migraine-stage classification system based on migraineurs' resting-state EEG power. We collect migraineurs' O1 and O2 EEG activities during closing eyes from occipital lobe to identify pre-ictal and non-pre-ictal stages. Self-Constructing Neural Fuzzy Inference Network (SONFIN) is adopted as the classifier in the migraine stages classification which can reach the better classification accuracy (66%) in comparison with other classifiers. The proposed system is helpful for migraineurs to obtain better treatment at the right time

Dislocation network at InN/GaN interface revealed by scanning tunneling microscopy

For heteroepitaxy of InN on GaN(0001) by molecular-beam epitaxy, the lattice misfit strain is relieved by misfit dislocations (MDs) formed at the interface between InN and GaN. Imaging by scanning tunneling microscopy (STM) of the surfaces of thin InN epifilms reveals line feature parallel to 〈112 0〉. Their contrast becomes less apparent for thicker epifilms. From the interline spacing as well as a comparison with transmission electron microscopy studies, it is suggested that they correspond to the MDs beneath the surface. The STM contrast originates from both the surface distortion caused by the local strain at MDs and the electronic states of the defects. © 2008 American Institute of Physics.published_or_final_versio

Anti-epileptic effect of Ganoderma lucidum polysaccharides by inhibition of intracellular calcium accumulation and stimulation of expression of CaMKII a in epileptic hippocampal neurons

Purpose: To investigate the mechanism of the anti-epileptic effect of Ganoderma lucidum polysaccharides (GLP), the changes of intracellular calcium and CaMK II a expression in a model of epileptic neurons were investigated. Method: Primary hippocampal neurons were divided into: 1) Control group, neurons were cultured with Neurobasal medium, for 3 hours; 2) Model group I: neurons were incubated with Mg2+ free medium for 3 hours; 3) Model group II: neurons were incubated with Mg2+ free medium for 3 hours then cultured with the normal medium for a further 3 hours; 4) GLP group I: neurons were incubated with Mg2+ free medium containing GLP (0.375 mg/ml) for 3 hours; 5) GLP group II: neurons were incubated with Mg2+ free medium for 3 hours then cultured with a normal culture medium containing GLP for a further 3 hours. The CaMK II a protein expression was assessed by Western-blot. Ca2+ turnover in neurons was assessed using Fluo-3/AM which was added into the replacement medium and Ca2+ turnover was observed under a laser scanning confocal microscope. Results: The CaMK II a expression in the model groups was less than in the control groups, however, in the GLP groups, it was higher than that observed in the model group. Ca2+ fluorescence intensity in GLP group I was significantly lower than that in model group I after 30 seconds, while in GLP group II, it was reduced significantly compared to model group II after 5 minutes. Conclusion: GLP may inhibit calcium overload and promote CaMK II a expression to protect epileptic neuron

p38 Mapk signal pathway involved in anti-inflammatory effect of chaihu-shugan-san and shen-ling-bai-zhu-san on hepatocyte in non-alcoholic steatohepatitis rats

Background: Traditional Chinese Medicine (TCM), has over thousands-of-years history of use. Chaihu-Shugan-San (CSS), and Shen-ling-bai-zhu-San (SLBZS), are famous traditional Chinese herbal medicine formulas, which have been used in China, for the treatment of many chronic diseases.Materials and Methods:This study investigated the anti-inflammatory effects of CSS and SLBZS on signaling molecules involved in p38 mitogen-activated protein kinase (p38 MAPK), pathway on hepatocytes of non-alcoholic steatohepatitis (NASH), rats induced by high fat diet. SD male rats were randomly divided into 8 groups: negative control group, model control group, high (9.6g/kg/day)/low (3.2g/kg/day)-dose CSS group, high (30g/kg/day)/low (10g/kg/day)-dose SLBZS group, high (39.6g/kg/day)/low (13.2g/kg/day)-dose integrated group. The rats of NASH model were induced by feeding a high-fat diet. After 16, wks, Hepatocytes were isolated from 6, rats in each group by collagenase perfusion. The liver histopathological changes and serum inflammatory cytokines TNF-α, IL-6 were determined. The proteins of TLR4,  phosphor-p38 MAPK and p38 MAPK involved in p38 MAPK signal pathway were assayed.Results: The statistical data indicated the NASH model rats reproduced typical histopathological features of NASH in human. CSS and SLBZS ameliorated lipid metabolic disturbance, attenuated NASH progression, decreased the levels of TNF-α and IL-6 in serum, as well as inhibited TLR4 protein expression, p38 MAPK phosphorylation, and activation of p38 MAPK. In conclusion, CSS and SLBZS might work as a significant anti-inflammatory effect on hepatocyte of NASH by inhibiting the activation of TLR4, p-p38 MAPK and p38 MAPK involved in p38 MAPK signal pathway.Conclusion: To some extent, CSS and SLBZS may be a potential alternative and complementary medicine to protect against liver injury, alleviate the inflammation reaction, moderate NASH progression.Key words: p38 mitogen-activated protein kinase; Toll like receptor 4; Hepatocytes; Non-alcoholic Steatohepatitis; Traditional Chinese medicine

Microbial fuel cells: a green and alternative source for bioenergy production

Microbial fuel cell (MFC) represents one of the green technologies for the production of bioenergy. MFCs using microalgae produce bioenergy by converting solar energy into electrical energy as a function of metabolic and anabolic pathways of the cells. In the MFCs with bacteria, bioenergy is generated as a result of the organic substrate oxidation. MFCs have received high attention from researchers in the last years due to the simplicity of the process, the absence in toxic by-products, and low requirements for the algae growth. Many studies have been conducted on MFC and investigated the factors affecting the MFC performance. In the current chapter, the performance of MFC in producing bioenergy as well as the factors which influence the efficacy of MFCs is discussed. It appears that the main factors affecting MFC’s performance include bacterial and algae species, pH, temperature, salinity, substrate, mechanism of electron transfer in an anodic chamber, electrodes materials, surface area, and electron acceptor in a cathodic chamber. These factors are becoming more influential and might lead to overproduction of bioenergy when they are optimized using response surface methodology (RSM)

MicroRNA expression profiles in pediatric dysembryoplastic neuroepithelial tumors.

© Springer Science+Business Media New York 2015Among noncoding RNAs, microRNAs (miRNAs) have been most extensively studied, and their biology has repeatedly been proven critical for central nervous system pathological conditions. The diagnostic value of several miRNAs was appraised in pediatric dysembryoplastic neuroepithelial tumors (DNETs) using miRNA microarrays and receiving operating characteristic curves analyses. Overall, five pediatric DNETs were studied. As controls, 17 samples were used: the FirstChoice Human Brain Reference RNA and 16 samples from deceased children who underwent autopsy and were not present with any brain malignancy. The miRNA extraction was carried out using the mirVANA miRNA Isolation Kit, while the experimental approach included miRNA microarrays covering 1211 miRNAs. Quantitative real-time polymerase chain reaction was performed to validate the expression profiles of miR-1909* and miR-3138 in all samples initially screened with miRNA microarrays. Our findings indicated that miR-3138 might act as a tumor suppressor gene when down-regulated and miR-1909* as a putative oncogenic molecule when up-regulated in pediatric DNETs compared to the control cohort. Subsequently, both miRNA signatures might serve as putative diagnostic biomarkers for pediatric DNETs.Peer reviewedFinal Accepted Versio

The impact of epilepsy surgery on the structural connectome and its relation to outcome

BACKGROUND: Temporal lobe surgical resection brings seizure remission in up to 80% of patients, with long-term complete seizure freedom in 41%. However, it is unclear how surgery impacts on the structural white matter network, and how the network changes relate to seizure outcome. METHODS: We used white matter fibre tractography on preoperative diffusion MRI to generate a structural white matter network, and postoperative T1-weighted MRI to retrospectively infer the impact of surgical resection on this network. We then applied graph theory and machine learning to investigate the properties of change between the preoperative and predicted postoperative networks. RESULTS: Temporal lobe surgery had a modest impact on global network efficiency, despite the disruption caused. This was due to alternative shortest paths in the network leading to widespread increases in betweenness centrality post-surgery. Measurements of network change could retrospectively predict seizure outcomes with 79% accuracy and 65% specificity, which is twice as high as the empirical distribution. Fifteen connections which changed due to surgery were identified as useful for prediction of outcome, eight of which connected to the ipsilateral temporal pole. CONCLUSIONS: Our results suggest that the use of network change metrics may have clinical value for predicting seizure outcome. This approach could be used to prospectively predict outcomes given a suggested resection mask using preoperative data only