Establishing gold standard approaches to rapid tranquillisation: a review and discussion of the evidence on the safety and efficacy of medications currently used

Background: Rapid tranquillisation is used when control of agitation, aggression or excitement is required. Throughout the UK there is no consensus over the choice of drugs to be used as first line treatment. The NICE guideline on the management of violent behaviour involving psychiatric inpatients conducted a systematic examination of the literature relating to the effectiveness and safety of rapid tranquillisation (NICE, 2005). This paper presents the key findings from that review and key guideline recommendations generated, and discusses the implications for practice of more recent research and information. Aims: To examine the evidence on the efficacy and safety of medications used for rapid tranquillisation in inpatient psychiatric settings. Method: Systematic review of current guidelines and phase III randomised, controlled trials of medication used for rapid tranquillisation. Formal consensus methods were used to generate clinically relevant recommendations to support safe and effective prescribing of rapid tranquillisation in the development of a NICE guideline. Findings: There is a lack of high quality clinical trial evidence in the UK and therefore a ‘gold standard’ medication regime for rapid tranquillisation has not been established. Rapid tranquillisation and clinical practice: The NICE guideline produced 35 recommendations on rapid tranquillisation practice for the UK, with the primary aim of calming the service user to enable the use of psychosocial techniques. Conclusions and implications for clinical practice: Further UK specific research is urgently needed that provides the clinician with a hierarchy of options for the clinical practice of rapid tranquillisation

Sinorhizobium Meliloti, A Bacterium Lacking The Autoinducer-2 (AI-2) Synthase, Responds To AI-2 Supplied By Other Bacteria

Many bacterial species respond to the quorum-sensing signal autoinducer-2 (AI-2) by regulating different niche-specific genes. Here, we show that Sinorhizobium meliloti, a plant symbiont lacking the gene for the AI-2 synthase, while not capable of producing AI-2 can nonetheless respond to AI-2 produced by other species. We demonstrate that S. meliloti has a periplasmic binding protein that binds AI-2. The crystal structure of this protein (here named SmlsrB) with its ligand reveals that it binds (2R,4S)-2-methyl-2,3,3,4-tetrahydroxytetrahydrofuran (R-THMF), the identical AI-2 isomer recognized by LsrB of Salmonella typhimurium. The gene encoding SmlsrB is in an operon with orthologues of the lsr genes required for AI-2 internalization in enteric bacteria. Accordingly, S. meliloti internalizes exogenous AI-2, and mutants in this operon are defective in AI-2 internalization. S. meliloti does not gain a metabolic benefit from internalizing AI-2, suggesting that AI-2 functions as a signal in S. meliloti. Furthermore, S. meliloti can completely eliminate the AI-2 secreted by Erwinia carotovora, a plant pathogen shown to use AI-2 to regulate virulence. Our findings suggest that S. meliloti is capable of \u27eavesdropping\u27 on the AI-2 signalling of other species and interfering with AI-2-regulated behaviours such as virulence

Biological traits and the transfer of persistent organic pollutants through river food webs

Freshwater organisms remain at risk from bioaccumulation and biomagnification of persistent organic pollutants (POPs), but factors affecting their transfer through food webs are poorly understood. Here, we investigate transfer pathways of polychlorinated biphenyls, polybrominated diphenyl ethers, and organochlorine through a river food web, assessing the distribution and flux between basal resources (n = 3), macroinvertebrates (n = 22), and fish (n = 1). We investigate the effects of biological traits on the observed patterns and use trait-based models to predict POP bioaccumulation. Transfer pathways differed among POPs and traits such as habitat affinity, feeding behavior, and body size explained some variation in POP burdens between organisms. Trait-based models indicated that relationships between POPs, trophic transfers, and traits were relatively well conserved across a wider array of river food webs. Although providing more consistent predictions of POP bioaccumulation than steady-state models, variability in bioaccumulation across food webs limited the accuracy of trait-model predictions. As some of the first data to illustrate how ecological processes alter the flux of pollutants through river food webs, these results reveal important links between POPs and contrasting energetic pathways. These data also show the utility of trait-based methods in the assessment of persistent contaminants, but further field validations are required

Spatial scaling of species abundance distributions

Copyright © 2012 The Authors. Ecography © 2012 Nordic Society Oikos.Species abundance distributions are an essential tool in describing the biodiversity of ecological communities. We now know that their shape changes as a function of the size of area sampled. Here we analyze the scaling properties of species abundance distributions by using the moments of the logarithmically transformed number of individuals. We find that the moments as a function of area size are well fitted by power laws and we use this pattern to estimate the species abundance distribution for areas larger than those sampled. To reconstruct the species abundance distribution from its moments, we use discrete Tchebichef polynomials. We exemplify the method with data on tree and shrub species from a 50 ha plot of tropical rain forest on Barro Colorado Island, Panama. We test the method within the 50 ha plot, and then we extrapolate the species abundance distribution for areas up to 5 km2. Our results project that for areas above 50 ha the species abundance distributions have a bimodal shape with a local maximum occurring for the singleton classes and that this maximum increases with sampled area size

Interoceptive and metacognitive facets of fatigue in multiple sclerosis

Numerous disorders are characterised by fatigue as a highly disabling symptom. Fatigue plays a particularly important clinical role in multiple sclerosis (MS) where it exerts a profound impact on quality of life. Recent concepts of fatigue grounded in computational theories of brain-body interactions emphasise the role of interoception and metacognition in the pathogenesis of fatigue. So far, however, for MS, empirical data on interoception and metacognition are scarce. This study examined interoception and (exteroceptive) metacognition in a sample of 71 persons with a diagnosis of MS. Interoception was assessed by prespecified subscales of a standard questionnaire (Multidimensional Assessment of Interoceptive Awareness [MAIA]), while metacognition was investigated with computational models of choice and confidence data from a visual discrimination paradigm. Additionally, autonomic function was examined by several physiological measurements. Several hypotheses were tested based on a preregistered analysis plan. In brief, we found the predicted association of interoceptive awareness with fatigue (but not with exteroceptive metacognition) and an association of autonomic function with exteroceptive metacognition (but not with fatigue). Furthermore, machine learning (elastic net regression) showed that individual fatigue scores could be predicted out-of-sample from our measurements, with questionnaire-based measures of interoceptive awareness and sleep quality as key predictors. Our results support theoretical concepts of interoception as an important factor for fatigue and demonstrate the general feasibility of predicting individual levels of fatigue from simple questionnaire-based measures of interoception and sleep

Mulsemedia: State of the art, perspectives, and challenges

Mulsemedia-multiple sensorial media-captures a wide variety of research efforts and applications. This article presents a historic perspective on mulsemedia work and reviews current developments in the area. These take place across the traditional multimedia spectrum-from virtual reality applications to computer games-as well as efforts in the arts, gastronomy, and therapy, to mention a few. We also describe standardization efforts, via the MPEG-V standard, and identify future developments and exciting challenges the community needs to overcome

Linear and Non-linear associations between vitamin D and grip strength: a Mendelian Randomisation study in UK Biobank

BACKGROUND: Low vitamin D status is a widespread phenomenon. Similarly, muscle weakness, often indicated by low grip strength, is another public health concern; however, the vitamin D-grip strength relationship is equivocal. It is important to understand whether variation in vitamin D status causally influences muscle strength to elucidate whether supplementation may help prevent/treat muscle weakness. METHODS: UK Biobank participants, aged 37-73 years, with valid data on Vitamin D status (circulating 25-hydroxyvitamin D (25(OH)D) concentration) and maximum grip strength were included (N=368,890). We examined sex-specific cross-sectional associations between 25(OH)D and grip strength. Using Mendelian randomisation (MR), we estimated the strength of the 25(OH)D-grip strength associations using genetic instruments for 25(OH)D as our exposure. Crucially, because potential effects of vitamin D supplementation on strength could vary by underlying 25(OH)D status, we allowed for non-linear relationships between 25(OH)D and strength in all analyses. RESULTS: Mean(SD) of 25(OH)D was 50(21)nmol/L in males and females. In cross-sectional analyses there was evidence of non-linear associations between 25(OH)D and strength: e.g., compared to males with 50nmol/L circulating 25(OH)D, males with 75nmol/L had 0.36kg (0.31,0.40) stronger grip; males with 25nmol/L had 1.01kg (95% CI: 0.93,1.08) weaker grip. In MR analyses, linear and non-linear models fitted the data similarly well: e.g., 25nmol/L higher circulating 25(OH)D in males was associated with 0.25kg (-0.05,0.55) greater grip (regardless of initial 25(OH)D status). Results were similar, albeit weaker, for females. CONCLUSIONS: Using two different methods to triangulate evidence, our findings suggest moderate to small causal links between circulating 25(OH)D and grip strength

Effect of interpregnancy interval on gestational diabetes: a retrospective matched cohort study

© 2019 The Authors Purpose: To examine the association between interpregnancy interval (IPI) and gestational diabetes using both within-mother and between-mother comparisons. Methods: A retrospective cohort study of 103,909 women who delivered three or more consecutive singleton births (n = 358,046) between 1 January 1980 and 31 December 2015 in Western Australia. The association between IPI and gestational diabetes was estimated using conditional logistic regression, matching pregnancies to the same mother and adjusted for factors that vary within-mother across pregnancies. For comparison with previous studies, we also applied unmatched logistic regression (between-mother analysis). Results: The conventional between-mother analysis resulted in adjusted odds ratios (aOR) of 1.13 (95% CI, 1.06–1.21) for intervals of 24–59 months and 1.51 (95% CI, 1.33–1.70) for intervals of 120 or more months, compared with IPI of 18–23 months. In addition, short IPIs were associated with lower odds of gestational diabetes with (aOR: 0.89; 95% CI, 0.82–0.97) for 6–11 months and (aOR: 0.92; 95% CI, 0.85–0.99) for 12–17-month. In comparison, the adjusted within-mother matched analyses showed no statistically significant association between IPIs and gestational diabetes. All effect estimates were attenuated using the within-mother matched model. Conclusion: Our findings do not support the hypothesis that short IPI (<6 months) increases the risk of gestational diabetes and suggest that observed associations in previous research might be attributable to confounders that vary between mothers

Power transformer dissolved gas analysis through Bayesian networks and hypothesis testing

Accurate diagnosis of power transformers is critical for the reliable and cost-effective operation of the power grid. Presently there are a range of methods and analytical models for transformer fault diagnosis based on dissolved gas analysis. However, these methods give conflicting results and they are not able to generate uncertainty information associated with the diagnostics outcome. In this situation it is not always clear which model is the most accurate. This paper presents a novel multiclass probabilistic diagnosis framework for dissolved gas analysis based on Bayesian networks and hypothesis testing. Bayesian network models embed expert knowledge, learn patterns from data and infer the uncertainty associated with the diagnostics outcome, and hypothesis testing aids in the data selection process. The effectiveness of the proposed framework is validated using the IEC TC 10 dataset and is shown to have a maximum diagnosis accuracy of 88.9%

Improving the accuracy of transformer DGA diagnosis in the presence of conflicting evidence

Transformers are critical assets for the reliable and cost-effective operation of the power grid. Transformers may fail if condition monitoring does not identify degraded conditions in time. Dissolved Gas Analysis (DGA) focuses on the examination of the dissolved gasses in the transformer oil and there exist different methods for transformer fault diagnosis based on different analyses of the gassing levels. However, these methods can give conflicting results, and it is not always clear which model is most accurate in a given situation. This paper presents a novel evidence combination framework for DGA based on Bayesian networks. Bayesian network models embed expert knowledge along with learned data patterns and evidence combination which aids in the consistency of analysis. The effectiveness of the proposed framework is validated using the IEC TC 10 dataset with a maximum diagnosis accuracy of 88.3%