1,240 research outputs found
Anxiety, psychosis and substance use: prevalence, correlates and recognition in an outpatient mental health setting
Objective: The current study examined anxiety in people with substance use disorder (SUD) and a psychotic disorder. It is hypothesised that: anxiety disorders (AD) would be highly prevalent (greater than 20%) in people identified as having SUD and psychotic disorders; those with comorbid AD would fair worse than those without, on measures of quality of life, severity of substance dependence, locus of control, suicidality and psychotic symptoms; and, the presence of such anxiety disorder symptomatology would be under-detected by their mental health case mangers. Method: Outpatients with co-occurring substance use disorder and psychosis were interviewed to collect data about their diagnosis, depressive and psychotic symptoms, severity of dependence on substances, quality of life and locus of control. Participants’ case managers made blind ratings of the presence and severity of participants’ anxiety. Results: Fifty eight percent of participants had at least one anxiety disorder. Of these, 56% – 70% had case managers who had identified them as having an anxiety problem. The occurrence of anxiety disorder was associated with more external locus of control, greater intensity of suicidal thinking, worse psychotic symptoms, lower quality of life and greater severity of dependence on substances. Conclusion: This research suggests anxiety in people with substance use disorder and psychosis is highly prevalent, is associated with poorer outcomes, and is under detected by case managers. Further examination of this issue may lead to important advances in the treatment and prognosis of people with substance use disorder and psychosis.Keywords: Anxiety disorders; Substance-related disorders; Psychotic disorders; Comorbidity; Diagnosis; Prevalence
Algorithms for the self-optimisation of chemical reactions
Self-optimising chemical systems have experienced a growing momentum in recent years, with the evolution of self-optimising platforms leading to their application for reaction screening and chemical synthesis. With the desire for improved process sustainability, self-optimisation provides a cheaper, faster and greener approach to the chemical development process. The use of such platforms aims to enhance the capabilities of the researcher by removing the need for labor-intensive experimentation, allowing them to focus on more challenging tasks. The establishment of these systems have enabled opportunities for self-optimising platforms to become a key element of a laboratory’s repertoire. To enable the wider adoption of self-optimising chemical platforms, this review summarises the history of algorithmic usage in chemical reaction self-optimisation, detailing the functionality of the algorithms and their applications in a way that is accessible for chemists and highlights opportunities for the further exploitation of algorithms in chemical synthesis moving forward
A Hybridised Optimisation of an Automated Photochemical Continuous Flow Reactor
A new hybridized algorithm that combines process optimisation with response surface mapping was developed and applied in an automated continuous flow reaction. Moreover, a photochemical cascade CSTR was developed and characterised by chemical actinometry, showing photon flux density of ten times greater than previously reported in batch. The success of the algorithm was then evaluated in the aerobic oxidation of sp3 C–H bonds using benzophenone as photosensitizer in the newly developed photo reactor
Automated Self-Optimisation of Multi-Step Reaction and Separation Processes Using Machine Learning
There has been an increasing interest in the use of automated self-optimising continuous flow platforms for the development and manufacture in synthesis in recent years. Such processes include multiple reactive and work-up steps, which need to be efficiently optimised. Here, we report the combination of multi-objective optimisation based on machine learning methods (TSEMO algorithm) with self-optimising platforms for the optimisation of multi-step continuous reaction processes. This is demonstrated for a pharmaceutically relevant Sonogashira reaction. We demonstrate how optimum reaction conditions are re-evaluated with the changing downstream work-up specifications in the active learning process. Furthermore, a Claisen-Schmidt condensation reaction with subsequent liquid-liquid separation was optimised with respect to three-objectives. This approach provides the ability to simultaneously optimise multi-step processes with respect to multiple objectives, and thus has the potential to make substantial savings in time and resources
Interleukin-1 regulates multiple atherogenic mechanisms in response to fat feeding
Background: Atherosclerosis is an inflammatory process that develops in individuals with known risk factors that include hypertension and hyperlipidaemia, influenced by diet. However, the interplay between diet, inflammatory mechanisms and vascular risk factors requires further research. We hypothesised that interleukin-1 (IL-1) signaling in the vessel wall would raise arterial blood pressure and promote atheroma.
Methodology/Principal Findings: Apoe(-/-) and Apoe(-/-)/IL-1R1(-/-) mice were fed high fat diets for 8 weeks, and their blood pressure and atherosclerosis development measured. Apoe(-/-)/IL-R1(-/-) mice had a reduced blood pressure and significantly less atheroma than Apoe(-/-) mice. Selective loss of IL-1 signaling in the vessel wall by bone marrow transplantation also reduced plaque burden (p<0.05). This was associated with an IL-1 mediated loss of endothelium-dependent relaxation and an increase in vessel wall Nox 4. Inhibition of IL-1 restored endothelium-dependent vasodilatation and reduced levels of arterial oxidative stress.
Conclusions/Significance: The IL-1 cytokine system links atherogenic environmental stimuli with arterial inflammation, oxidative stress, increased blood pressure and atherosclerosis. This is the first demonstration that inhibition of a single cytokine can block the rise in blood pressure in response to an environmental stimulus. IL-1 inhibition may have profound beneficial effects on atherogenesis in man
External sources of clean technology: evidence from the clean development mechanism
New technology is fundamental to sustainable development. However, inventors from industrialized countries often refuse technology transfer because they worry about reverse-engineering. When can clean technology transfer succeed? We develop a formal model of the political economy of North–South technology transfer. According to the model, technology transfer is possible if (1) the technology in focus has limited global commercial potential or (2) the host developing country does not have the capacity to absorb new technologies for commercial use. If both conditions fail, inventors from industrialized countries worry about the adverse competitiveness effects of reverse-engineering, so technology transfer fails. Data analysis of technology transfer in 4,894 projects implemented under the Kyoto Protocol’s Clean Development Mechanism during the 2004–2010 period provides evidence in support of the model
Callers’ attitudes and experiences of UK breastfeeding helpline support
Background: Breastfeeding peer support, is considered to be a key intervention for increasing breastfeeding duration rates. Whilst a number of national organisations provide telephone based breastfeeding peer support, to date there have been no published evaluations into callers’ experiences and attitudes of this support. In this study we report on the descriptive and qualitative insights provided by 908 callers as part of an evaluation of UK-based breastfeeding helpline(s).
Methods: A structured telephone interview, incorporating Likert scale responses and open-ended questions was undertaken with 908 callers over May to August, 2011 to explore callers’ experiences of the help and support received via the breastfeeding helpline(s).
Results: Overall satisfaction with the helpline was high, with the vast majority of callers’ recalling positive experiences of the help and support received. Thematic analysis was undertaken on all qualitative and descriptive data recorded during the evaluation, contextualised within the main areas addressed within the interview schedule in terms of ‘contact with the helplines’; ‘experiences of the helpline service’, ‘perceived effectiveness of support provision’ and ‘impact on caller wellbeing’.
Conclusion: Callers valued the opportunity for accessible, targeted, non-judgmental and convenient support. Whilst the telephone support did not necessarily influence women’s breastfeeding decisions, the support they received left them feeling reassured, confident and more determined to continue breastfeeding. We recommend extending the helpline service to ensure support can be accessed when needed, and ongoing training and support for volunteers. Further advertising and promotion of the service within wider demographic groups is warranted
Rapid, Automated Determination of Reaction Models and Kinetic Parameters
We herein report a novel kinetic modelling methodology whereby identification of the correct reaction model and kinetic parameters is conducted by an autonomous framework combined with transient flow measurements to enable comprehensive process understanding with minimal user input. An automated flow chemistry platform was employed to initially conduct linear flow-ramp experiments to rapidly map the reaction profile of three processes using transient flow data. Following experimental data acquisition, a computational approach was utilised to discriminate between all possible reaction models as well as identify the correct kinetic parameters for each process. Species that are known to participate in the process (starting materials, intermediates, products) are initially inputted by the user prior to flow ramp experiments, then all possible model candidates are compiled into a model library based on their potential to occur after mass balance assessment. Parallel computational optimisation then evaluates each model by algorithmically altering the kinetic parameters of the model to allow convergence of a simulated kinetic curve to the experimental data provided. Statistical analysis then determines the most likely reaction model based on model simplicity and agreement with experimental data. This automated approach to gaining full process understanding, whereby a small number of data-rich experiments are conducted, and the kinetics are evaluated autonomously, shows significant improvements on current industrial optimisation techniques in terms of labour, time and overall cost. The computational approach herein described can be employed using data from any set of experiments and the code is open-source
Are mice good models for human neuromuscular disease? Comparing muscle excursions in walking between mice and humans
The mouse is one of the most widely used animal models to study neuromuscular diseases and test new therapeutic strategies. However, findings from successful pre-clinical studies using mouse models frequently fail to translate to humans due to various factors. Differences in muscle function between the two species could be crucial but often have been overlooked. The purpose of this study was to evaluate and compare muscle excursions in walking between mice and humans
Stable isotope analysis provides new information on winter habitat use of declining avian migrants that is relevant to their conservation
Winter habitat use and the magnitude of migratory connectivity are important parameters when assessing drivers of the marked declines in avian migrants. Such information is unavailable for most species. We use a stable isotope approach to assess these factors for three declining African-Eurasian migrants whose winter ecology is poorly known: wood warbler Phylloscopus sibilatrix, house martin Delichon urbicum and common swift Apus apus. Spatially segregated breeding wood warbler populations (sampled across a 800 km transect), house martins and common swifts (sampled across a 3,500 km transect) exhibited statistically identical intra-specific carbon and nitrogen isotope ratios in winter grown feathers. Such patterns are compatible with a high degree of migratory connectivity, but could arise if species use isotopically similar resources at different locations. Wood warbler carbon isotope ratios are more depleted than typical for African-Eurasian migrants and are compatible with use of moist lowland forest. The very limited variance in these ratios indicates specialisation on isotopically restricted resources, which may drive the similarity in wood warbler populations' stable isotope ratios and increase susceptibility to environmental change within its wintering grounds. House martins were previously considered to primarily use moist montane forest during the winter, but this seems unlikely given the enriched nature of their carbon isotope ratios. House martins use a narrower isotopic range of resources than the common swift, indicative of increased specialisation or a relatively limited wintering range; both factors could increase house martins' vulnerability to environmental change. The marked variance in isotope ratios within each common swift population contributes to the lack of population specific signatures and indicates that the species is less vulnerable to environmental change in sub-Saharan Africa than our other focal species. Our findings demonstrate how stable isotope research can contribute to understanding avian migrants' winter ecology and conservation status
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