Effectiveness of non-steroidal anti-inflammatory drugs for the treatment of pain in knee and hip osteoarthritis: a network meta-analysis.

BACKGROUND Non-steroidal anti-inflammatory drugs (NSAIDs) are the backbone of osteoarthritis pain management. We aimed to assess the effectiveness of different preparations and doses of NSAIDs on osteoarthritis pain in a network meta-analysis. METHODS For this network meta-analysis, we considered randomised trials comparing any of the following interventions: NSAIDs, paracetamol, or placebo, for the treatment of osteoarthritis pain. We searched the Cochrane Central Register of Controlled Trials (CENTRAL) and the reference lists of relevant articles for trials published between Jan 1, 1980, and Feb 24, 2015, with at least 100 patients per group. The prespecified primary and secondary outcomes were pain and physical function, and were extracted in duplicate for up to seven timepoints after the start of treatment. We used an extension of multivariable Bayesian random effects models for mixed multiple treatment comparisons with a random effect at the level of trials. For the primary analysis, a random walk of first order was used to account for multiple follow-up outcome data within a trial. Preparations that used different total daily dose were considered separately in the analysis. To assess a potential dose-response relation, we used preparation-specific covariates assuming linearity on log relative dose. FINDINGS We identified 8973 manuscripts from our search, of which 74 randomised trials with a total of 58 556 patients were included in this analysis. 23 nodes concerning seven different NSAIDs or paracetamol with specific daily dose of administration or placebo were considered. All preparations, irrespective of dose, improved point estimates of pain symptoms when compared with placebo. For six interventions (diclofenac 150 mg/day, etoricoxib 30 mg/day, 60 mg/day, and 90 mg/day, and rofecoxib 25 mg/day and 50 mg/day), the probability that the difference to placebo is at or below a prespecified minimum clinically important effect for pain reduction (effect size [ES] -0·37) was at least 95%. Among maximally approved daily doses, diclofenac 150 mg/day (ES -0·57, 95% credibility interval [CrI] -0·69 to -0·46) and etoricoxib 60 mg/day (ES -0·58, -0·73 to -0·43) had the highest probability to be the best intervention, both with 100% probability to reach the minimum clinically important difference. Treatment effects increased as drug dose increased, but corresponding tests for a linear dose effect were significant only for celecoxib (p=0·030), diclofenac (p=0·031), and naproxen (p=0·026). We found no evidence that treatment effects varied over the duration of treatment. Model fit was good, and between-trial heterogeneity and inconsistency were low in all analyses. All trials were deemed to have a low risk of bias for blinding of patients. Effect estimates did not change in sensitivity analyses with two additional statistical models and accounting for methodological quality criteria in meta-regression analysis. INTERPRETATION On the basis of the available data, we see no role for single-agent paracetamol for the treatment of patients with osteoarthritis irrespective of dose. We provide sound evidence that diclofenac 150 mg/day is the most effective NSAID available at present, in terms of improving both pain and function. Nevertheless, in view of the safety profile of these drugs, physicians need to consider our results together with all known safety information when selecting the preparation and dose for individual patients. FUNDING Swiss National Science Foundation (grant number 405340-104762) and Arco Foundation, Switzerland.

Psychological therapies for panic disorder with or without agoraphobia in adults: a network meta-analysis.

BACKGROUND Panic disorder is characterised by the presence of recurrent unexpected panic attacks, discrete periods of fear or anxiety that have a rapid onset and include symptoms such as racing heart, chest pain, sweating and shaking. Panic disorder is common in the general population, with a lifetime prevalence of 1% to 4%. A previous Cochrane meta-analysis suggested that psychological therapy (either alone or combined with pharmacotherapy) can be chosen as a first-line treatment for panic disorder with or without agoraphobia. However, it is not yet clear whether certain psychological therapies can be considered superior to others. In order to answer this question, in this review we performed a network meta-analysis (NMA), in which we compared eight different forms of psychological therapy and three forms of a control condition. OBJECTIVES To assess the comparative efficacy and acceptability of different psychological therapies and different control conditions for panic disorder, with or without agoraphobia, in adults. SEARCH METHODS We conducted the main searches in the CCDANCTR electronic databases (studies and references registers), all years to 16 March 2015. We conducted complementary searches in PubMed and trials registries. Supplementary searches included reference lists of included studies, citation indexes, personal communication to the authors of all included studies and grey literature searches in OpenSIGLE. We applied no restrictions on date, language or publication status. SELECTION CRITERIA We included all relevant randomised controlled trials (RCTs) focusing on adults with a formal diagnosis of panic disorder with or without agoraphobia. We considered the following psychological therapies: psychoeducation (PE), supportive psychotherapy (SP), physiological therapies (PT), behaviour therapy (BT), cognitive therapy (CT), cognitive behaviour therapy (CBT), third-wave CBT (3W) and psychodynamic therapies (PD). We included both individual and group formats. Therapies had to be administered face-to-face. The comparator interventions considered for this review were: no treatment (NT), wait list (WL) and attention/psychological placebo (APP). For this review we considered four short-term (ST) outcomes (ST-remission, ST-response, ST-dropouts, ST-improvement on a continuous scale) and one long-term (LT) outcome (LT-remission/response). DATA COLLECTION AND ANALYSIS As a first step, we conducted a systematic search of all relevant papers according to the inclusion criteria. For each outcome, we then constructed a treatment network in order to clarify the extent to which each type of therapy and each comparison had been investigated in the available literature. Then, for each available comparison, we conducted a random-effects meta-analysis. Subsequently, we performed a network meta-analysis in order to synthesise the available direct evidence with indirect evidence, and to obtain an overall effect size estimate for each possible pair of therapies in the network. Finally, we calculated a probabilistic ranking of the different psychological therapies and control conditions for each outcome. MAIN RESULTS We identified 1432 references; after screening, we included 60 studies in the final qualitative analyses. Among these, 54 (including 3021 patients) were also included in the quantitative analyses. With respect to the analyses for the first of our primary outcomes, (short-term remission), the most studied of the included psychological therapies was CBT (32 studies), followed by BT (12 studies), PT (10 studies), CT (three studies), SP (three studies) and PD (two studies).The quality of the evidence for the entire network was found to be low for all outcomes. The quality of the evidence for CBT vs NT, CBT vs SP and CBT vs PD was low to very low, depending on the outcome. The majority of the included studies were at unclear risk of bias with regard to the randomisation process. We found almost half of the included studies to be at high risk of attrition bias and detection bias. We also found selective outcome reporting bias to be present and we strongly suspected publication bias. Finally, we found almost half of the included studies to be at high risk of researcher allegiance bias.Overall the networks appeared to be well connected, but were generally underpowered to detect any important disagreement between direct and indirect evidence. The results showed the superiority of psychological therapies over the WL condition, although this finding was amplified by evident small study effects (SSE). The NMAs for ST-remission, ST-response and ST-improvement on a continuous scale showed well-replicated evidence in favour of CBT, as well as some sparse but relevant evidence in favour of PD and SP, over other therapies. In terms of ST-dropouts, PD and 3W showed better tolerability over other psychological therapies in the short term. In the long term, CBT and PD showed the highest level of remission/response, suggesting that the effects of these two treatments may be more stable with respect to other psychological therapies. However, all the mentioned differences among active treatments must be interpreted while taking into account that in most cases the effect sizes were small and/or results were imprecise. AUTHORS' CONCLUSIONS There is no high-quality, unequivocal evidence to support one psychological therapy over the others for the treatment of panic disorder with or without agoraphobia in adults. However, the results show that CBT - the most extensively studied among the included psychological therapies - was often superior to other therapies, although the effect size was small and the level of precision was often insufficient or clinically irrelevant. In the only two studies available that explored PD, this treatment showed promising results, although further research is needed in order to better explore the relative efficacy of PD with respect to CBT. Furthermore, PD appeared to be the best tolerated (in terms of ST-dropouts) among psychological treatments. Unexpectedly, we found some evidence in support of the possible viability of non-specific supportive psychotherapy for the treatment of panic disorder; however, the results concerning SP should be interpreted cautiously because of the sparsity of evidence regarding this treatment and, as in the case of PD, further research is needed to explore this issue. Behaviour therapy did not appear to be a valid alternative to CBT as a first-line treatment for patients with panic disorder with or without agoraphobia.

Using the contribution matrix to evaluate complex study limitations in a network meta-analysis: a case study of bipolar maintenance pharmacotherapy review.

BACKGROUND Limitations in the primary studies constitute one important factor to be considered in the grading of recommendations assessment, development, and evaluation (GRADE) system of rating quality of evidence. However, in the network meta-analysis (NMA), such evaluation poses a special challenge because each network estimate receives different amounts of contributions from various studies via direct as well as indirect routes and because some biases have directions whose repercussion in the network can be complicated. FINDINGS In this report we use the NMA of maintenance pharmacotherapy of bipolar disorder (17 interventions, 33 studies) and demonstrate how to quantitatively evaluate the impact of study limitations using netweight, a STATA command for NMA. For each network estimate, the percentage of contributions from direct comparisons at high, moderate or low risk of bias were quantified, respectively. This method has proven flexible enough to accommodate complex biases with direction, such as the one due to the enrichment design seen in some trials of bipolar maintenance pharmacotherapy. CONCLUSIONS Using netweight, therefore, we can evaluate in a transparent and quantitative manner how study limitations of individual studies in the NMA impact on the quality of evidence of each network estimate, even when such limitations have clear directions.

Cognitive-Behavioural Analysis System of Psychotherapy (CBASP), a drug, or their combination: differential therapeutics for persistent depressive disorder: a study protocol of an individual participant data network meta-analysis.

INTRODUCTION Despite important advances in psychological and pharmacological treatments of persistent depressive disorders in the past decades, their responses remain typically slow and poor, and differential responses among different modalities of treatments or their combinations are not well understood. Cognitive-Behavioural Analysis System of Psychotherapy (CBASP) is the only psychotherapy that has been specifically designed for chronic depression and has been examined in an increasing number of trials against medications, alone or in combination. When several treatment alternatives are available for a certain condition, network meta-analysis (NMA) provides a powerful tool to examine their relative efficacy by combining all direct and indirect comparisons. Individual participant data (IPD) meta-analysis enables exploration of impacts of individual characteristics that lead to a differentiated approach matching treatments to specific subgroups of patients. METHODS AND ANALYSIS We will search for all randomised controlled trials that compared CBASP, pharmacotherapy or their combination, in the treatment of patients with persistent depressive disorder, in Cochrane CENTRAL, PUBMED, SCOPUS and PsycINFO, supplemented by personal contacts. Individual participant data will be sought from the principal investigators of all the identified trials. Our primary outcomes are depression severity as measured on a continuous observer-rated scale for depression, and dropouts for any reason as a proxy measure of overall treatment acceptability. We will conduct a one-step IPD-NMA to compare CBASP, medications and their combinations, and also carry out a meta-regression to identify their prognostic factors and effect moderators. The model will be fitted in OpenBUGS, using vague priors for all location parameters. For the heterogeneity we will use a half-normal prior on the SD. ETHICS AND DISSEMINATION This study requires no ethical approval. We will publish the findings in a peer-reviewed journal. The study results will contribute to more finely differentiated therapeutics for patients suffering from this chronically disabling disorder. TRIAL REGISTRATION NUMBER CRD42016035886.

Network-based analysis of genome-wide scans of natural selection

The genomic era brought by recent advances in the next-generation sequencing technology makes the genome-wide scans of natural selection a reality. Currently, almost all the statistical tests and analytical methods for identifying genes under selection was performed on the individual gene basis. Although these methods have the power of identifying gene subject to strong selection, they have limited power in discovering genes targeted by moderate or weak selection forces, which are crucial for understanding the molecular mechanisms of complex phenotypes and diseases. Recent availability and rapid completeness of many gene network and protein-protein interaction databases accompanying the genomic era open the avenues of exploring the possibility of enhancing the power of discovering genes under natural selection. The aim of the thesis is to explore and develop normal mixture model based methods for leveraging gene network information to enhance the power of natural selection target gene discovery. The results show that the developed statistical method, which combines the posterior log odds of the standard normal mixture model and the Guilt-By-Association score of the gene network in a naïve Bayes framework, has the power to discover moderate/weak selection gene which bridges the genes under strong selection and it helps our understanding the biology under complex diseases and related natural selection phenotypes.^

Descriptive analysis of the knowledge network formation in East Asia

This paper shows descriptively how the knowledge network in East Asia has been formed. In addition, the correlation between the knowledge network and economic growth is also examined. Evidence is provided to show that plugging into the knowledge network of developed countries could be a key for increasing innovativeness in a country.

Tomas Lopez's Geographic Atlas of Spain (1787) and its Hydrographic Network: GIS analysis of the Reyno de Jaen

Knowledge of the development of hydrographic networks can be useful for a number of research works in hydraulic engineering. We thus, intend to analyse the cartography regarding the first work that systematically encompasses the entire hydrographic network: Tomas Lopez’s Geographic Atlas of Spain (1787). In order to achieve this goal, we will first analyze –by way of the Geographic Information System (GIS) – both the present and referred historical cartographies. In comparing them, we will use the then-existing population centres that correspond to modern ones. The aim is to compare the following research variables in the hydrographic network: former toponyms, length of riverbeds and distance to population centres. The results of this study will show the variation in the riverbeds and the probable change in their denomination.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure (versión actualizada)

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Artificial analysis of molecular marker loci linked to tree resistance response by an artificial neural network

One of the biggest challenges that software developers face is to make an accurate estimate of the project effort. Radial basis function neural networks have been used to software effort estimation in this work using NASA dataset. This paper evaluates and compares radial basis function versus a regression model. The results show that radial basis function neural network have obtained less Mean Square Error than the regression method.

La Région Méditerranéenne en 2020 et son Rôle dans le Réseau Energétjgue Européen, Vol. I: Analyse de la demande d'energie dans les PSEM (Horizons 2000-2010-2020)= The Mediterranean region in 2020 and its Role in the European Energy Network, Vol. I: Analysis of the energy demand in the SEMC (Horizons 2000-2010-2020).

None.

Comparative Analysis of Existing Guidelines for Gender-Fair Language within the ITN LCG Network. ITN-LCG, Workpackage B: Report on Milestone 1

Guidelines for a gender-fair use of the languages represented in the ITN LCG network were analyzed comparatively for specific criteria. All institutional or governmental guidelines aim at attenuating male-biased representations that are brought about by certain grammatical structures of the respective language. These guidelines primarily focus on the use of masculine forms as generics because they reduce the visibility of women in language. The comparison shows that guidelines for English, a language without grammatical gender, emphasize neutralization as a means of referring to both sexes. This differs from grammatical gender languages, such as German and Italian, in which feminine-masculine word-pairs are recommended in order to avoid the masculine bias. The guidelines all aim to promote the formulation of comprehensive and readable texts that are free of discrimination.