Prospective mental imagery as its link with anxiety and depression in prisoners

Mental imagery is known to play a key role in the development and maintenance of depression and anxiety. Prisoners commonly experience psychological distress, but interventions to address this are currently lacking. We aimed to examine the link between prospective mental imagery and anxiety and depression among prisoners. One hundred twenty-three male prisoners from a Category C prison in southwest England participated in the study. They completed the Centre for Epidemiologic Studies Depression Scale (CES-D) and the General Anxiety Disorder Scale (GAD-7) to measure whether they experience depression and/or anxiety symptoms. Furthermore, they completed additional questionnaires to evaluate their prospective mental imagery. Results showed that 67.5% of prisoners presented with more depression symptoms and 27.7% with more anxiety symptoms. Supporting earlier findings, our data revealed that some dimensions of prospective mental imagery were significantly related with increased anxiety and depression symptoms in prisoners. Namely, intrusive negative personally relevant imagery was a positive predictor and likelihood of positive events a negative predictor of both anxiety and depression symptoms. The perceived likelihood of negative events was a positive predictor of depression. Intrusive verbal thought was a positive predictor of anxiety. The obtained results suggest the need to develop interventions not only targeting the reduction of prospective negative imagery but also the enhancement of positive mental imagery

Exploring the equity of GP practice prescribing rates for selected coronary heart disease drugs: a multiple regression analysis with proxies of healthcare need

Background There is a small, but growing body of literature highlighting inequities in GP practice prescribing rates for many drug therapies. The aim of this paper is to further explore the equity of prescribing for five major CHD drug groups and to explain the amount of variation in GP practice prescribing rates that can be explained by a range of healthcare needs indicators (HCNIs). Methods The study involved a cross-sectional secondary analysis in four primary care trusts (PCTs 1–4) in the North West of England, including 132 GP practices. Prescribing rates (average daily quantities per registered patient aged over 35 years) and HCNIs were developed for all GP practices. Analysis was undertaken using multiple linear regression. Results Between 22–25% of the variation in prescribing rates for statins, beta-blockers and bendrofluazide was explained in the multiple regression models. Slightly more variation was explained for ACE inhibitors (31.6%) and considerably more for aspirin (51.2%). Prescribing rates were positively associated with CHD hospital diagnoses and procedures for all drug groups other than ACE inhibitors. The proportion of patients aged 55–74 years was positively related to all prescribing rates other than aspirin, where they were positively related to the proportion of patients aged >75 years. However, prescribing rates for statins and ACE inhibitors were negatively associated with the proportion of patients aged >75 years in addition to the proportion of patients from minority ethnic groups. Prescribing rates for aspirin, bendrofluazide and all CHD drugs combined were negatively associated with deprivation. Conclusion Although around 25–50% of the variation in prescribing rates was explained by HCNIs, this varied markedly between PCTs and drug groups. Prescribing rates were generally characterised by both positive and negative associations with HCNIs, suggesting possible inequities in prescribing rates on the basis of ethnicity, deprivation and the proportion of patients aged over 75 years (for statins and ACE inhibitors, but not for aspirin)

General Strategy for Broadband Coherent Perfect Absorption and Multi-wavelength All-optical Switching Based on Epsilon-Near-Zero Multilayer Films

We propose a general, easy-to-implement scheme for broadband coherent perfect absorption (CPA) using epsilon-near-zero (ENZ) multilayer films. Specifically, we employ indium tin oxide (ITO) as a tunable ENZ material, and theoretically investigate CPA in the near-infrared region. We first derive general CPA conditions using the scattering matrix and the admittance matching methods. Then, by combining these two methods, we extract analytic expressions for all relevant parameters for CPA. Based on this theoretical framework, we proceed to study ENZ CPA in a single layer ITO film and apply it to all-optical switching. Finally, using an ITO multilayer of different ENZ wavelengths, we implement broadband ENZ CPA structures and investigate multi-wavelength all-optical switching in the technologically important telecommunication window. In our design, the admittance matching diagram was employed to graphically extract not only the structural parameters (the film thicknesses and incident angles), but also the input beam parameters (the irradiance ratio and phase difference between two input beams). We find that the multi-wavelength all-optical switching in our broadband ENZ CPA system can be fully controlled by the phase difference between two input beams. The simple but general design principles and analyses in this work can be widely used in various thin-film devicesopen

Excess of health care use in general practice and of comorbid chronic conditions in cancer patients compared to controls

<p>Abstract</p> <p>Background</p> <p>The number of cancer patients and the number of patients surviving initial treatments is expected to rise. Traditionally, follow-up monitoring takes place in secondary care. The contribution of general practice is less visible and not clearly defined.</p> <p>This study aimed to compare healthcare use in general practice of patients with cancer during the follow-up phase compared with patients without cancer. We also examined the influence of comorbid conditions on healthcare utilisation by these patients in general practice.</p> <p>Methods</p> <p>We compared health care use of N=8,703 cancer patients with an age and gender-matched control group of patients without cancer from the same practice. Data originate from the Netherlands Information Network of General Practice (LINH), a representative network consisting of 92 general practices with 350,000 enlisted patients. Health care utilisation was assessed using data on contacts with general practice, prescription and referral rates recorded between 1/1/2001 and 31/12/2007. The existence of additional comorbid chronic conditions (ICPC coded) was taken into account.</p> <p>Results</p> <p>Compared to matched controls, cancer patients had more contacts with their GP-practice (19.5 vs. 11.9, p<.01), more consultations with the GP (3.5 vs. 2.7, p<.01), more home visits (1.6 vs. 0.4, p<.01) and they got more medicines prescribed (18.7 vs. 11.6, p<.01) during the follow-up phase. Cancer patients more often had a chronic condition than their matched controls (52% vs. 44%, p<.01). Having a chronic condition increased health care use for both patients with and without cancer. Cancer patients with a comorbid condition had the highest health care use.</p> <p>Conclusion</p> <p>We found that cancer patients in the follow-up phase consulted general practice more often and suffered more often from comorbid chronic conditions, compared to patients without cancer. It is expected that the number of cancer patients will rise in the years to come and that primary health care professionals will be more involved in follow-up care. Care for comorbid chronic conditions, communication between specialists and GPs, and coordination of tasks then need special attention.</p

Interpretation and expectation in childhood anxiety disorders: age effects and social specificity

Theory and treatment for childhood anxiety disorders typically implicates children’s negative cognitions, yet little is known about the characteristics of thinking styles of clinically anxious children. In particular, it is unclear whether differences in thinking styles between children with anxiety disorders and non-anxious children vary as a function of child age, whether particular cognitive distortions are associated with childhood anxiety disorders at different child ages, and whether cognitive content is disorder-specific. The current study addressed these questions among 120 7 - 12 year old children (53% female) who met diagnostic criteria for social anxiety disorder, other anxiety disorder, or who were not currently anxious. Contrary to expectations, threat interpretation was not inflated amongst anxious compared to non-anxious children at any age, although older (10 - 12 year old) anxious children did differ from non-anxious children on measures of perceived coping. The notion of cognitive-content specificity was not supported across the age-range. The findings challenge current treatment models of childhood anxiety, and suggest that a focus on changing anxious children’s cognitions is not warranted in mid-childhood, and in late childhood cognitive approaches may be better focussed on promoting children’s perceptions of control rather than challenging threat interpretations

A Brain-Computer Interface Based Attention Training Program for Treating Attention Deficit Hyperactivity Disorder

10.1371/journal.pone.0046692PLoS ONE710

Zinc Finger Nuclease mediated knockout of ADP dependent Glucokinase in Cancer cell lines: Effects on cell survival and Mitochondrial Oxidative Metabolism

<div><p>Zinc finger nucleases (ZFN) are powerful tools for editing genes in cells. Here we use ZFNs to interrogate the biological function of <i>ADPGK</i>, which encodes an ADP-dependent glucokinase (ADPGK), in human tumour cell lines. The hypothesis we tested is that ADPGK utilises ADP to phosphorylate glucose under conditions where ATP becomes limiting, such as hypoxia. We characterised two ZFN knockout clones in each of two lines (H460 and HCT116). All four clones had frameshift mutations in all alleles at the target site in exon 1 of <i>ADPGK,</i> and were ADPGK-null by immunoblotting. <i>ADPGK</i> knockout had little or no effect on cell proliferation, but compromised the ability of H460 cells to survive siRNA silencing of hexokinase-2 under oxic conditions, with clonogenic survival falling from 21±3% for the parental line to 6.4±0.8% (p = 0.002) and 4.3±0.8% (p = 0.001) for the two knockouts. A similar increased sensitivity to clonogenic cell killing was observed under anoxia. No such changes were found when <i>ADPGK</i> was knocked out in HCT116 cells, for which the parental line was less sensitive than H460 to anoxia and to hexokinase-2 silencing. While knockout of <i>ADPGK</i> in HCT116 cells caused few changes in global gene expression, knockout of <i>ADPGK</i> in H460 cells caused notable up-regulation of mRNAs encoding cell adhesion proteins. Surprisingly, we could discern no consistent effect on glycolysis as measured by glucose consumption or lactate formation under anoxia, or extracellular acidification rate (Seahorse XF analyser) under oxic conditions in a variety of media. However, oxygen consumption rates were generally lower in the <i>ADPGK</i> knockouts, in some cases markedly so. Collectively, the results demonstrate that <i>ADPGK</i> can contribute to tumour cell survival under conditions of high glycolytic dependence, but the phenotype resulting from knockout of <i>ADPGK</i> is cell line dependent and appears to be unrelated to priming of glycolysis in these lines.</p></div

Impacts of climate change on plant diseases – opinions and trends

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods

Predicting risk for Alcohol Use Disorder using longitudinal data with multimodal biomarkers and family history: a machine learning study.

Predictive models have succeeded in distinguishing between individuals with Alcohol use Disorder (AUD) and controls. However, predictive models identifying who is prone to develop AUD and the biomarkers indicating a predisposition to AUD are still unclear. Our sample (n = 656) included offspring and non-offspring of European American (EA) and African American (AA) ancestry from the Collaborative Study of the Genetics of Alcoholism (COGA) who were recruited as early as age 12 and were unaffected at first assessment and reassessed years later as AUD (DSM-5) (n = 328) or unaffected (n = 328). Machine learning analysis was performed for 220 EEG measures, 149 alcohol-related single nucleotide polymorphisms (SNPs) from a recent large Genome-wide Association Study (GWAS) of alcohol use/misuse and two family history (mother DSM-5 AUD and father DSM-5 AUD) features using supervised, Linear Support Vector Machine (SVM) classifier to test which features assessed before developing AUD predict those who go on to develop AUD. Age, gender, and ancestry stratified analyses were performed. Results indicate significant and higher accuracy rates for the AA compared with the EA prediction models and a higher model accuracy trend among females compared with males for both ancestries. Combined EEG and SNP features model outperformed models based on only EEG features or only SNP features for both EA and AA samples. This multidimensional superiority was confirmed in a follow-up analysis in the AA age groups (12-15, 16-19, 20-30) and EA age group (16-19). In both ancestry samples, the youngest age group achieved higher accuracy score than the two other older age groups. Maternal AUD increased the model's accuracy in both ancestries' samples. Several discriminative EEG measures and SNPs features were identified, including lower posterior gamma, higher slow wave connectivity (delta, theta, alpha), higher frontal gamma ratio, higher beta correlation in the parietal area, and 5 SNPs: rs4780836, rs2605140, rs11690265, rs692854, and rs13380649. Results highlight the significance of sampling uniformity followed by stratified (e.g., ancestry, gender, developmental period) analysis, and wider selection of features, to generate better prediction scores allowing a more accurate estimation of AUD development