Guidelines for the recording and evaluation of pharmaco-EEG data in man: the International Pharmaco-EEG Society (IPEG)

The International Pharmaco-EEG Society (IPEG) presents updated guidelines summarising the requirements for the recording and computerised evaluation of pharmaco-EEG data in man. Since the publication of the first pharmaco-EEG guidelines in 1982, technical and data processing methods have advanced steadily, thus enhancing data quality and expanding the palette of tools available to investigate the action of drugs on the central nervous system (CNS), determine the pharmacokinetic and pharmacodynamic properties of novel therapeutics and evaluate the CNS penetration or toxicity of compounds. However, a review of the literature reveals inconsistent operating procedures from one study to another. While this fact does not invalidate results per se, the lack of standardisation constitutes a regrettable shortcoming, especially in the context of drug development programmes. Moreover, this shortcoming hampers reliable comparisons between outcomes of studies from different laboratories and hence also prevents pooling of data which is a requirement for sufficiently powering the validation of novel analytical algorithms and EEG-based biomarkers. The present updated guidelines reflect the consensus of a global panel of EEG experts and are intended to assist investigators using pharmaco-EEG in clinical research, by providing clear and concise recommendations and thereby enabling standardisation of methodology and facilitating comparability of data across laboratories

Outlier Edge Detection Using Random Graph Generation Models and Applications

Outliers are samples that are generated by different mechanisms from other normal data samples. Graphs, in particular social network graphs, may contain nodes and edges that are made by scammers, malicious programs or mistakenly by normal users. Detecting outlier nodes and edges is important for data mining and graph analytics. However, previous research in the field has merely focused on detecting outlier nodes. In this article, we study the properties of edges and propose outlier edge detection algorithms using two random graph generation models. We found that the edge-ego-network, which can be defined as the induced graph that contains two end nodes of an edge, their neighboring nodes and the edges that link these nodes, contains critical information to detect outlier edges. We evaluated the proposed algorithms by injecting outlier edges into some real-world graph data. Experiment results show that the proposed algorithms can effectively detect outlier edges. In particular, the algorithm based on the Preferential Attachment Random Graph Generation model consistently gives good performance regardless of the test graph data. Further more, the proposed algorithms are not limited in the area of outlier edge detection. We demonstrate three different applications that benefit from the proposed algorithms: 1) a preprocessing tool that improves the performance of graph clustering algorithms; 2) an outlier node detection algorithm; and 3) a novel noisy data clustering algorithm. These applications show the great potential of the proposed outlier edge detection techniques.Comment: 14 pages, 5 figures, journal pape

Prescribing practices of primary-care veterinary practitioners in dogs diagnosed with bacterial pyoderma

Concern has been raised regarding the potential contributions of veterinary antimicrobial use to increasing levels of resistance in bacteria critically important to human health. Canine pyoderma is a frequent, often recurrent diagnosis in pet dogs, usually attributable to secondary bacterial infection of the skin. Lesions can range in severity based on the location, total area and depth of tissue affected and antimicrobial therapy is recommended for resolution. This study aimed to describe patient signalment, disease characteristics and treatment prescribed in a large number of UK, primary-care canine pyoderma cases and to estimate pyoderma prevalence in the UK vet-visiting canine population

Research interrupted: The impact of the COVID-19 pandemic on multiple sclerosis research in the field of rehabilitation and quality of life

Background The COVID-19 pandemic has likely had a negative impact on rehabilitation and quality of life (QoL) research in multiple sclerosis (MS). Method We explored perceived barriers to research among 87 researchers, representing 18 countries, both prior to and since COVID-19. Results A Wilcoxon signed-rank test found that significantly more researchers reported experiencing barriers to research since the onset of the pandemic compared to pre-COVID-19 (p &lt; .001), with 78% of respondents reporting at least some barriers since COVID-19. The most commonly-cited barriers related to participant access (n = 38) and interruptions/delays to projects (n = 19). Although no gender differences were found in the number of barriers reported, female respondents were more likely to cite time or competing demands as barriers to research. Females were also more likely to perceive being negatively impacted by the pandemic compared to other genders (p = .007). Conclusions Implications for the future landscape of rehabilitation research in MS are discussed. </jats:sec

?2-Microglobulin Amyloid Fibril-Induced Membrane Disruption Is Enhanced by Endosomal Lipids and Acidic pH

Although the molecular mechanisms underlying the pathology of amyloidoses are not well understood, the interaction between amyloid proteins and cell membranes is thought to play a role in several amyloid diseases. Amyloid fibrils of ?2-microglobulin (?2m), associated with dialysis-related amyloidosis (DRA), have been shown to cause disruption of anionic lipid bilayers in vitro. However, the effect of lipid composition and the chemical environment in which ?2m-lipid interactions occur have not been investigated previously. Here we examine membrane damage resulting from the interaction of ?2m monomers and fibrils with lipid bilayers. Using dye release, tryptophan fluorescence quenching and fluorescence confocal microscopy assays we investigate the effect of anionic lipid composition and pH on the susceptibility of liposomes to fibril-induced membrane damage. We show that ?2m fibril-induced membrane disruption is modulated by anionic lipid composition and is enhanced by acidic pH. Most strikingly, the greatest degree of membrane disruption is observed for liposomes containing bis(monoacylglycero)phosphate (BMP) at acidic pH, conditions likely to reflect those encountered in the endocytic pathway. The results suggest that the interaction between ?2m fibrils and membranes of endosomal origin may play a role in the molecular mechanism of ?2m amyloid-associated osteoarticular tissue destruction in DRA

The influence of the accessory genome on bacterial pathogen evolution

Bacterial pathogens exhibit significant variation in their genomic content of virulence factors. This reflects the abundance of strategies pathogens evolved to infect host organisms by suppressing host immunity. Molecular arms-races have been a strong driving force for the evolution of pathogenicity, with pathogens often encoding overlapping or redundant functions, such as type III protein secretion effectors and hosts encoding ever more sophisticated immune systems. The pathogens’ frequent exposure to other microbes, either in their host or in the environment, provides opportunities for the acquisition or interchange of mobile genetic elements. These DNA elements accessorise the core genome and can play major roles in shaping genome structure and altering the complement of virulence factors. Here, we review the different mobile genetic elements focusing on the more recent discoveries and highlighting their role in shaping bacterial pathogen evolution

Microfluidic Perfusion for Regulating Diffusible Signaling in Stem Cells

Background Autocrine & paracrine signaling are widespread both in vivo and in vitro, and are particularly important in embryonic stem cell (ESC) pluripotency and lineage commitment. Although autocrine signaling via fibroblast growth factor-4 (FGF4) is known to be required in mouse ESC (mESC) neuroectodermal specification, the question of whether FGF4 autocrine signaling is sufficient, or whether other soluble ligands are also involved in fate specification, is unknown. The spatially confined and closed-loop nature of diffusible signaling makes its experimental control challenging; current experimental approaches typically require prior knowledge of the factor/receptor in order to modulate the loop. A new approach explored in this work is to leverage transport phenomena at cellular resolution to downregulate overall diffusible signaling through the physical removal of cell-secreted ligands. Methodology/Principal Findings We develop a multiplex microfluidic platform to continuously remove cell-secreted (autocrine\paracrine) factors to downregulate diffusible signaling. By comparing cell growth and differentiation in side-by-side chambers with or without added cell-secreted factors, we isolate the effects of diffusible signaling from artifacts such as shear, nutrient depletion, and microsystem effects, and find that cell-secreted growth factor(s) are required during neuroectodermal specification. Then we induce FGF4 signaling in minimal chemically defined medium (N2B27) and inhibit FGF signaling in fully supplemented differentiation medium with cell-secreted factors to determine that the non-FGF cell-secreted factors are required to promote growth of differentiating mESCs. Conclusions/Significance Our results demonstrate for the first time that flow can downregulate autocrine\paracrine signaling and examine sufficiency of extracellular factors. We show that autocrine\paracrine signaling drives neuroectodermal commitment of mESCs through both FGF4-dependent and -independent pathways. Overall, by uncovering autocrine\paracrine processes previously hidden in conventional culture systems, our results establish microfluidic perfusion as a technique to study and manipulate diffusible signaling in cell systems.National Institutes of Health (U.S.) (NIH grant No. EB007278)Swiss National Science FoundationSwiss National Science Foundatio

Identification and Characterization of a Novel Multipotent Sub-Population of Sca-1+ Cardiac Progenitor Cells for Myocardial Regeneration

The cardiac stem/progenitor cells from adult mice were seeded at low density in serum-free medium. The colonies thus obtained were expanded separately and assessed for expression of stem cell antigen-1 (Sca-1). Two colonies each with high Sca-1 (CSH1; 95.9%; CSH2; 90.6%) and low Sca-1 (CSL1; 37.1%; CSL2; 17.4%) expressing cells were selected for further studies. Sca-1⁺ cells (98.4%) isolated using Magnetic Cell Sorting System (MACS) from the hearts were used as a control. Although the selected populations were similar in surface marker expression (low in c-kit, CD45, CD34, CD31 and high in CD29), these cells exhibited diverse differentiation potential. Unlike CSH1, CSH2 expressed Nanog, TERT, Bcrp1, Nestin, Musashi1 and Isl-1, and also showed differentiation into osteogenic, chondrogenic, smooth muscle, endothelial and cardiac lineages. MACS sorted cells exhibited similar tendency albeit with relatively weaker differentiation potential. Transplantation of CSH2 cells into infarcted heart showed attenuated infarction size, significantly preserved left ventricular function and anterior wall thickness, and increased capillary density. We also observed direct differentiation of transplanted cells into endothelium and cardiomyocytes.The cardiac stem/progenitor cells isolated by a combined clonal selection and surface marker approach possessed multiple stem cell features important for cardiac regeneration

Progression of Biopsy-Measured Liver Fibrosis in Untreated Patients with Hepatitis C Infection: Non-Markov Multistate Model Analysis

BACKGROUND: Fibrosis stages from liver biopsies reflect liver damage from hepatitis C infection, but analysis is challenging due to their ordered but non-numeric nature, infrequent measurement, misclassification, and unknown infection times. METHODS: We used a non-Markov multistate model, accounting for misclassification, with multiple imputation of unknown infection times, applied to 1062 participants of whom 159 had multiple biopsies. Odds ratios (OR) quantified the estimated effects of covariates on progression risk at any given time. RESULTS: Models estimated that progression risk decreased the more time participants had already spent in the current stage, African American race was protective (OR 0.75, 95% confidence interval 0.60 to 0.95, p = 0.018), and older current age increased risk (OR 1.33 per decade, 95% confidence interval 1.15 to 1.54, p = 0.0002). When controlled for current age, older age at infection did not appear to increase risk (OR 0.92 per decade, 95% confidence interval 0.47 to 1.79, p = 0.80). There was a suggestion that co-infection with human immunodeficiency virus increased risk of progression in the era of highly active antiretroviral treatment beginning in 1996 (OR 2.1, 95% confidence interval 0.97 to 4.4, p = 0.059). Other examined risk factors may influence progression risk, but evidence for or against this was weak due to wide confidence intervals. The main results were essentially unchanged using different assumed misclassification rates or imputation of age of infection. DISCUSSION: The analysis avoided problems inherent in simpler methods, supported the previously suspected protective effect of African American race, and suggested that current age rather than age of infection increases risk. Decreasing risk of progression with longer time already spent in a stage was also previously found for post-transplant progression. This could reflect varying disease activity, with recent progression indicating active disease and high risk, while longer time already spent in a stage indicates quiescent disease and low risk

Microarray Analysis in the Archaeon Halobacterium salinarum Strain R1

Background: Phototrophy of the extremely halophilic archaeon Halobacterium salinarum was explored for decades. The research was mainly focused on the expression of bacteriorhodopsin and its functional properties. In contrast, less is known about genome wide transcriptional changes and their impact on the physiological adaptation to phototrophy. The tool of choice to record transcriptional profiles is the DNA microarray technique. However, the technique is still rarely used for transcriptome analysis in archaea. Methodology/Principal Findings: We developed a whole-genome DNA microarray based on our sequence data of the Hbt. salinarum strain R1 genome. The potential of our tool is exemplified by the comparison of cells growing under aerobic and phototrophic conditions, respectively. We processed the raw fluorescence data by several stringent filtering steps and a subsequent MAANOVA analysis. The study revealed a lot of transcriptional differences between the two cell states. We found that the transcriptional changes were relatively weak, though significant. Finally, the DNA microarray data were independently verified by a real-time PCR analysis. Conclusion/Significance: This is the first DNA microarray analysis of Hbt. salinarum cells that were actually grown under phototrophic conditions. By comparing the transcriptomics data with current knowledge we could show that our DNA microarray tool is well applicable for transcriptome analysis in the extremely halophilic archaeon Hbt. salinarum. The reliability of our tool is based on both the high-quality array of DNA probes and the stringent data handling including MAANOVA analysis. Among the regulated genes more than 50% had unknown functions. This underlines the fact that haloarchaeal phototrophy is still far away from being completely understood. Hence, the data recorded in this study will be subject to future systems biology analysis