113 resultados para Reduced topologies


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OBJECTIVE: The frequency and emotional response to bullying victimisation are known to be associated with adolescent mental ill health. A potentially important under-investigated factor is the form of bullying. Four common forms of bullying behaviours are name-calling, physical threats or harm, rumour spreading and social exclusion. To more comprehensively understand bullying victimisation in adolescence, we examined the association of all three factors (frequency, emotional response, form) to psychological distress and emotional wellbeing. METHOD: A stratified, random sample of adolescents (n = 10, 273; mean age = 14.33 years, standard deviation = 1.68 years) completed validated measures of bullying victimisation (Gatehouse Bullying Questionnaire), psychological distress (K10) and emotional wellbeing (Mental Health Inventory) in classroom time. Associations between the form of bullying victimisation and mental health outcomes were examined. RESULTS: Adolescents reported a high prevalence of all four forms of bullying: teased or called names (30.6%), rumour spreading (17.9%), social exclusion (14.3%) and physical threats or harm (10.7%). Victimisation was independently associated with significantly higher levels of psychological distress and reduced levels of emotional wellbeing for all forms of bullying. In particular, social exclusion had a strong association with mental ill health. Adolescents who experienced frequent bullying that was upsetting reported higher psychological distress and reduced emotional wellbeing. CONCLUSION: Different forms of bullying victimisation were independently associated with psychological distress and reduced emotional wellbeing. In particular, frequent and upsetting social exclusion requires a targeted and measured response by school communities and health practitioners.

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Social cognitive difficulties are common in the acute phase of bipolar disorder and, to a lesser extent, during the euthymic stage, and imaging studies of social cognition in euthymic bipolar disorder have implicated mirror system brain regions. This study aimed to use a novel multimodal approach (i.e., including both transcranial magnetic stimulation (TMS) and electroencephalogram (EEG)) to investigate mirror systems in bipolar disorder. Fifteen individuals with euthymic bipolar disorder and 16 healthy controls participated in this study. Single-pulse TMS was applied to the optimal site in the primary motor cortex (M1), which stimulates the muscle of interest during the observation of hand movements (goal-directed or interacting) designed to elicit mirror system activity. Single EEG electrodes (C3, CZ, C4) recorded mu rhythm modulation concurrently. Results revealed that the patient group showed significantly less mu suppression compared to healthy controls. Surprisingly, motor resonance was not significantly different overall between groups; however, bipolar disorder participants showed a pattern of reduced reactivity on some conditions. Although preliminary, this study indicates a potential mirror system deficit in euthymic bipolar disorder, which may contribute to the pathophysiology of the disorder.

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A sensitive electrochemical acetylcholinesterase (AChE) biosensor based on a reduced graphene oxide (rGO) and silver nanocluster (AgNC) modified glassy carbon electrode (GCE) was developed. rGO and AgNC nanomaterials with excellent conductivity, catalytic activity and biocompatibility offered an extremely hydrophilic surface, which facilitated the immobilization of AChE to fabricate the organophosphorus pesticide biosensor. Carboxylic chitosan (CChit) was used as a cross-linker to immobilize AChE on a rGO and AgNC modified GCE. The AChE biosensor showed favorable affinity to acetylthiocholine chloride (ATCl) and could catalyze the hydrolysis of ATCl. Based on the inhibition effect of organophosphorus pesticides on the AChE activity, using phoxim as a model compound, the inhibition effect of phoxim was proportional to its concentration ranging from 0.2 to 250 nM with a detection limit of 81 pM estimated at a signal-to-noise ratio of 3. The developed biosensor exhibited good sensitivity, stability and reproducibility, thus providing a promising tool for analysis of enzyme inhibitors and direct analysis of practical samples.

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We report on the synthesis of platinum nanoparticle-reduced graphene oxide (PtNP-rGO) composites and their application as a novel architecture in electrochemical detection of rutin. PtNPs anchored over rGO are synthesized through a facile one-pot synthesis method, where the reduction of GO and in situ generation of PtNPs occurred concurrently. The characterization results of transmission electron microscopy (TEM) demonstrate that PtNPs with small particle sizes are dispersed on the rGO matrix. Electrochemical measurements reveal that a PtNP-rGO modified glass carbon electrode (GCE) directly catalyzes rutin oxidation and displays an enhanced current response compared with a bare GCE. Under the optimal experimental conditions, the peak current was linear with rutin concentration in the range of 5 × 10-8 to 1 × 10-5 M with the detection limit of 1 × 10-8 M (S/N = 3) by differential pulse voltammetry. The proposed method was successfully applied to determine rutin in tablet samples with satisfactory results. This journal is

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Two cases of zinc deficiency in breastfed neonates were investigated where zinc levels in the mothers' milk were reduced by more than 75 % compared to normal. The objective of this study was to find the molecular basis of the maternal zinc deficiency condition. Significant reductions in mRNA expression and protein levels of the zinc transporters SLC30A5 and SLC30A6 were found in maternal tissue, suggesting a causal link to the zinc-deficient milk. Novel splice variants of the SLC30A6 transcript were detected. No modifications were found in coding regions, or in transcription binding sites of promoter regions or in 5' and 3' untranslated regions of both transporters in lymphoblasts and fibroblasts isolated from both mothers. Altered DNA methylation in SLC30A5 at two CpG sites was detected and may account for the reduced levels of SLC30A5 mRNA and protein in lymphoblasts. Reduced SLC30A6 mRNA and protein levels in lymphoblasts may be secondary to reduced SLC30A5 expression, as they function as a heterodimer in zinc transport. In conclusion, two cases of zinc deficiency are linked to low levels of the SLC30A5 and SLC30A6 zinc transporters. These two zinc transporters have not been previously associated with zinc deficiency in milk.

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BACKGROUND: Heart failure is associated with high mortality and hospital readmissions. Beta-adrenergic blocking agents, angiotensin converting enzyme inhibitors (ACEIs), and angiotensin receptor blockers (ARBs) can improve survival and reduce hospital readmissions and are recommended as first-line therapy in the treatment of heart failure. Evidence has also shown that there is a dose-dependent relationship of these medications with patient outcomes. Despite this evidence, primary care physicians are reluctant to up-titrate these medications. New strategies aimed at facilitating this up-titration are warranted. Nurse-led titration (NLT) is one such strategy. OBJECTIVES: To assess the effects of NLT of beta-adrenergic blocking agents, ACEIs, and ARBs in patients with heart failure with reduced ejection fraction (HFrEF) in terms of safety and patient outcomes. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials in the Cochrane Library (CENTRAL Issue 11 of 12, 19/12/2014), MEDLINE OVID (1946 to November week 3 2014), and EMBASE Classic and EMBASE OVID (1947 to 2014 week 50). We also searched reference lists of relevant primary studies, systematic reviews, clinical trial registries, and unpublished theses sources. We used no language restrictions. SELECTION CRITERIA: Randomised controlled trials (RCTs) comparing NLT of beta-adrenergic blocking agents, ACEIs, and/or ARBs comparing the optimisation of these medications by a nurse to optimisation by another health professional in patients with HFrEF. DATA COLLECTION AND ANALYSIS: Two review authors (AD & JC) independently assessed studies for eligibility and risk of bias. We contacted primary authors if we required additional information. We examined quality of evidence using the GRADE rating tool for RCTs. We analysed extracted data by risk ratio (RR) with 95% confidence interval (CI) for dichotomous data to measure effect sizes of intervention group compared with usual-care group. Meta-analyses used the fixed-effect Mantel-Haenszel method. We assessed heterogeneity between studies by Chi(2) and I(2). MAIN RESULTS: We included seven studies (1684 participants) in the review. One study enrolled participants from a residential care facility, and the other six studies from primary care and outpatient clinics. All-cause hospital admission data was available in four studies (556 participants). Participants in the NLT group experienced a lower rate of all-cause hospital admissions (RR 0.80, 95% CI 0.72 to 0.88, high-quality evidence) and fewer hospital admissions related to heart failure (RR 0.51, 95% CI 0.36 to 0.72, moderate-quality evidence) compared to the usual-care group. Six studies (902 participants) examined all-cause mortality. All-cause mortality was also lower in the NLT group (RR 0.66, 95% CI 0.48 to 0.92, moderate-quality evidence) compared to usual care. Approximately 27 deaths could be avoided for every 1000 people receiving NLT of beta-adrenergic blocking agents, ACEIs, and ARBs. Only three studies (370 participants) reported outcomes on all-cause and heart failure-related event-free survival. Participants in the NLT group were more likely to remain event free compared to participants in the usual-care group (RR 0.60, 95% CI 0.46 to 0.77, moderate-quality evidence). Five studies (966 participants) reported on the number of participants reaching target dose of beta-adrenergic blocking agents. This was also higher in the NLT group compared to usual care (RR 1.99, 95% CI 1.61 to 2.47, low-quality evidence). However, there was a substantial degree of heterogeneity in this pooled analysis. We rated the risk of bias in these studies as high mainly due to a lack of clarity regarding incomplete outcome data, lack of reporting on adverse events associated with the intervention, and the inability to blind participants and personnel. Participants in the NLT group reached maximal dose of beta-adrenergic blocking agents in half the time compared with participants in usual care. Two studies reported on adverse events; one of these studies stated there were no adverse events, and the other study found one adverse event but did not specify the type or severity of the adverse event. AUTHORS' CONCLUSIONS: Participants in the NLT group experienced fewer hospital admissions for any cause and an increase in survival and number of participants reaching target dose within a shorter time period. However, the quality of evidence regarding the proportion of participants reaching target dose was low and should be interpreted with caution. We found high-quality evidence supporting NLT as one strategy that may improve the optimisation of beta-adrenergic blocking agents resulting in a reduction in hospital admissions. Despite evidence of a dose-dependent relationship of beta-adrenergic blocking agents, ACEIs, and ARBs with improving outcomes in patients with HFrEF, the translation of this evidence into clinical practice is poor. NLT is one strategy that facilitates the implementation of this evidence into practice.

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Probabilistic topic models have become a standard in modern machine learning to deal with a wide range of applications. Representing data by dimensional reduction of mixture proportion extracted from topic models is not only richer in semantics interpretation, but could also be informative for classification tasks. In this paper, we describe the Topic Model Kernel (TMK), a topicbased kernel for Support Vector Machine classification on data being processed by probabilistic topic models. The applicability of our proposed kernel is demonstrated in several classification tasks with real world datasets. TMK outperforms existing kernels on the distributional features and give comparative results on nonprobabilistic data types.