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.

Fear Reduction Processes in Imaginal and In Vivo Flooding: A Comment on James' Review

The research comparing imaginal and in vivo exposure in the treatment of clinically significant fear, recently reviewed by James (1986), is reexamined from the perspective of bioinformational theory and the concept of emotional processing. Fear is assumed to be stored in long term memory as a network of propositionally-coded information, which has to be processed if treatment is to be successful. Emotional processing is indicated by activation of fear responses and their habituation within and across treatment sessions. Consistent with the theory, our review indicates that successful treatment via imaginal and in vivo exposure is indeed related to activation and habituation of fear responses; interference with processing has a negative impact upon fear reduction, regardless of the specific treatment techniques employed. Furthermore, some apparently discrepant findings in the available research literature can be understood in terms of the theories cited. These ideas provide a useful perspective from which to plan future research efforts and to advance our understanding of the processes underlying reduction of pathological fear.

Sulphate reduction rates of arctic deep sea sediments measured at station MSM16/2_809-1 (REF, Reference)

Turnover rates were determined for surface sediment cores obtained in 2009 and 2010. Sulfate reduction (SR) were measured ex situ by the whole core injection method (doi:10.1080/01490457809377722). We incubated the samples at in situ temperature (1.0°C) for 12 hours with carrier-free 35**SO4 (dissolved in water, 50 kBq). Sediment was fixed in 20 ml 20% ZnAc solution for AOM or SR, respectively. Turnover rates were measured as previously described (doi:10.4319/lom.2004.2.171).

Sulphate reduction rates of Håkon Mosby mud volcano sediments measured at station MSM16/2_823-1 (Z3-S3, old flow surface)

Turnover rates were determined for surface sediment cores obtained in 2009 and 2010. Sulfate reduction (SR) were measured ex situ by the whole core injection method (doi:10.1080/01490457809377722). We incubated the samples at in situ temperature (1.0°C) for 12 hours with carrier-free 35**SO4 (dissolved in water, 50 kBq). Sediment was fixed in 20 ml 20% ZnAc solution for AOM or SR, respectively. Turnover rates were measured as previously described (doi:10.4319/lom.2004.2.171).

Sulphate reduction and methane oxidation rates of Håkon Mosby mud volcano sediments measured at station MSM16/2_855-1 (Z2-S3, aged flow surface)

Sulfate reduction (SR) and anaerobic oxidation of methane (AOM) were measured ex situ by the whole core injection method (doi:10.1080/01490457809377722). We incubated the samples at in situ temperature (1.0°C) for 12 hours with either 14** CH4 (dissolved in water, 2.5 kBq) or carrier-free 35** SO4 (dissolved in water, 50 kBq). Sediment was fixed in 25 ml 2.5% sodium hydroxide (NaOH) solution or 20 ml 20% ZnAc solution for AOM or SR, respectively. Turnover rates were measured as previously described (http://edoc.mpg.de/177065; doi:10.4319/lom.2004.2.171).

Sulphate reduction and methane oxidation rates of Håkon Mosby mud volcano sediments measured at station MSM16/2_847-1 (Z2-S2, aged flow surface)

Sulfate reduction (SR) and anaerobic oxidation of methane (AOM) were measured ex situ by the whole core injection method (doi:10.1080/01490457809377722). We incubated the samples at in situ temperature (1.0°C) for 12 hours with either 14** CH4 (dissolved in water, 2.5 kBq) or carrier-free 35** SO4 (dissolved in water, 50 kBq). Sediment was fixed in 25 ml 2.5% sodium hydroxide (NaOH) solution or 20 ml 20% ZnAc solution for AOM or SR, respectively. Turnover rates were measured as previously described (http://edoc.mpg.de/177065; doi:10.4319/lom.2004.2.171).

Sulphate reduction and methane oxidation rates of Håkon Mosby mud volcano sediments measured at station MSM16/2_838-1 (Z1-S3, new flow surface)

Sulfate reduction (SR) and anaerobic oxidation of methane (AOM) were measured ex situ by the whole core injection method (doi:10.1080/01490457809377722). We incubated the samples at in situ temperature (1.0°C) for 12 hours with either 14** CH4 (dissolved in water, 2.5 kBq) or carrier-free 35** SO4 (dissolved in water, 50 kBq). Sediment was fixed in 25 ml 2.5% sodium hydroxide (NaOH) solution or 20 ml 20% ZnAc solution for AOM or SR, respectively. Turnover rates were measured as previously described (http://edoc.mpg.de/177065; doi:10.4319/lom.2004.2.171).

A Light-Weight On-Chip Monitoring Network for Dynamic Adaptation and Calibration

Current nanometer technologies suffer within-die parameter uncertainties, varying workload conditions, aging, and temperature effects that cause a serious reduction on yield and performance. In this scenario, monitoring, calibration, and dynamic adaptation become essential, demanding systems with a collection of multi purpose monitors and exposing the need for light-weight monitoring networks. This paper presents a new monitoring network paradigm able to perform an early prioritization of the information. This is achieved by the introduction of a new hierarchy level, the threshing level. Targeting it, we propose a time-domain signaling scheme over a single-wire that minimizes the network switching activity as well as the routing requirements. To validate our approach, we make a thorough analysis of the architectural trade-offs and expose two complete monitoring systems that suppose an area improvement of 40% and a power reduction of three orders of magnitude compared to previous works.

Feature selection in the reconstruction of complex network representations of spectral data

Complex networks have been extensively used in the last decade to characterize and analyze complex systems, and they have been recently proposed as a novel instrument for the analysis of spectra extracted from biological samples. Yet, the high number of measurements composing spectra, and the consequent high computational cost, make a direct network analysis unfeasible. We here present a comparative analysis of three customary feature selection algorithms, including the binning of spectral data and the use of information theory metrics. Such algorithms are compared by assessing the score obtained in a classification task, where healthy subjects and people suffering from different types of cancers should be discriminated. Results indicate that a feature selection strategy based on Mutual Information outperforms the more classical data binning, while allowing a reduction of the dimensionality of the data set in two orders of magnitude

Proton uptake by bacterial reaction centers: The protein complex responds in a similar manner to the reduction of either quinone acceptor

In bacterial photosynthetic reaction centers, the protonation events associated with the different reduction states of the two quinone molecules constitute intrinsic probes of both the electrostatic interactions and the different kinetic events occurring within the protein in response to the light-generated introduction of a charge. The kinetics and stoichiometries of proton uptake on formation of the primary semiquinone QA− and the secondary acceptor QB− after the first and second flashes have been measured, at pH 7.5, in reaction centers from genetically modified strains and from the wild type. The modified strains are mutated at the L212Glu and/or at the L213Asp sites near QB; some of them carry additional mutations distant from the quinone sites (M231Arg → Leu, M43Asn → Asp, M5Asn → Asp) that compensate for the loss of L213Asp. Our data show that the mutations perturb the response of the protein system to the formation of a semiquinone, how distant compensatory mutations can restore the normal response, and the activity of a tyrosine residue (M247Ala → Tyr) in increasing and accelerating proton uptake. The data demonstrate a direct correlation between the kinetic events of proton uptake that are observed with the formation of either QA− or QB−, suggesting that the same residues respond to the generation of either semiquinone species. Therefore, the efficiency of transferring the first proton to QB is evident from examination of the pattern of H+/QA− proton uptake. This delocalized response of the protein complex to the introduction of a charge is coordinated by an interactive network that links the Q− species, polarizable residues, and numerous water molecules that are located in this region of the reaction center structure. This could be a general property of transmembrane redox proteins that couple electron transfer to proton uptake/release reactions.

Nitrate reduction at Pt(1 0 0) single crystals and preferentially oriented nanoparticles in neutral media

The electroreduction of nitrate on Pt(1 0 0) electrodes in phosphate buffer neutral solution, pH 7.2, is reported. The sensitivity of the reaction to the crystallographic order of the surface is studied through the controlled introduction of defects by using stepped surfaces with (1 0 0) terraces of different length separated by monoatomic steps, either with (1 1 1) or (1 1 0) symmetry. The results of this study show that nitrate reduction occurs mainly on the well defined (1 0 0) terraces in the potential region where H adsorption starts to decrease, allowing the nitrate anion to access the surface. Adsorbed NO has been detected as a stable intermediate in this media. An oxidation process observed at 0.8 V has been identified as leading to the formation of adsorbed NO and being responsible for a secondary reduction process observed in the subsequent negative scan. Using in situ FTIRS, ammonium was found to be the main product of nitrate reduction. This species can be oxidized at high potentials resulting in adsorbed NO and nitrate (probably with nitrite as intermediate).

Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organising Maps (GHSOMs) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labelled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.