968 resultados para Abnormal Subgroups


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In general, the biological activation of nephrocarcinogenic chlorinated hydrocarbons proceeds via conjugatiton with glutathione. It has mostly been assamed that the main site of initial conjugation is the liver, followed by a mandatory transfer of intermediates to the kidney. It was therefore of interest to study the enzyme activities of subgroups of glutathione transferases (GSTs) in renal cancers and the surrounding normal renal tissues of the same individuals (n = 21). For genotyping the individuals with respect to known polymorphic GST isozymes the following substrates with differential specificity were used: 1-chloro-2,4-dinitrobenzene for overall GST activity (except GST θ); 7-chloro-4-nitrobenzo-2-oxa-1,3-diazole for GST α; 1,2-dichloro-4-nitro-benzene for GST μ; ethacrynic acid and 4-vinylpyridine for GST π; and methyl chloride for GST θ. In general, the normal tissues were able to metabolize the test substrates. A general decrease in individual GST enzyme activities was apparent in the course of cancerization, and in some (exceptional) cases individual activities, expressed in the normal renal tissue, were lost in the tumour tissue. The GST enzyme activities in tumours were independent of tumour stage, or the age and gender of the patients. There was little influence of known polymorphisms of GSTM1, GSTM3 and GSTP1 upon the activities towards the test substrates, whereas the influence of GSTT1 polymorphism on the activity towads methyl chloride was straightforward. In general, the present findings support the concept that the initial GST-dependent bioactivation step of nephrocarcinogenic chlorinated hydrocarbons may take place in the kidney itself. This should be a consideration in toxicokinetic modelling.

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Purpose: Several occupational carcinogens are metabolized by polymorphic enzymes. The distribution of the polymorphic enzymes N-acetyltransferase 2 (NAT2; substrates: aromatic amines), glutathione S-transferase M1 (GSTM1; substrates: e.g., reactive metabolites of polycyclic aromatic hydrocarbons), and glutathione S-transferase T1 (GSTT1; substrates: small molecules with 1-2 carbon atoms) were investigated. Material and Methods: At the urological department in Lutherstadt Wittenberg, 136 patients with a histologically proven transitional cell cancer of the urinary bladder were investigated for all occupations performed for more than 6 months. Several occupational and non-occupational risk factors were asked. The genotypes of NAT2, GSTM1, and GSTT1 were determined from leucocyte DNA by PCR. Results: Compared to the general population in Middle Europe, the percentage of GSTT1 negative persons (22.1 %) was ordinary; the percentage of slow acetylators (59.6%) was in the upper normal range, while the percentage of GSTM1 negative persons (58.8%) was elevated in the entire group. Shifts in the distribution of the genotypes were observed in subgroups who had been exposed to asbestos (6/6 GSTM1 negative, 5/6 slow acetylators), rubber manufacturing (8/10 GSTM1 negative), and chlorinated solvents (9/15 GSTM1 negative). Conclusions: The overrepresentation of GSTM1 negative bladder cancer patients also in this industrialized area and more pronounced in several occupationally exposed subgroups points to an impact of the GSTM1 negative genotype in bladder carcinogenesis. [Article in German]

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In explaining how communication quality predicts TMS in multidisciplinary teams, we drew on the social identity approach to investigate the mediating role of team identification and the moderating role of professional identification. Recognizing that professional identification could trigger intergroup biases among professional subgroups, or alternatively, could bring resources to the team, we explored the potential moderating role of professional identification in the relationship between team identification and TMS. Using data collected from 882 healthcare personnel working in 126 multidisciplinary hospital teams, results supported our hypothesis that perceived communication quality predicted TMS through team identification. Furthermore, findings provided support for a resource view of professional subgroup identities with results indicating that high levels of professional identification compensated for low levels of team identification in predicting TMS. We provide recommendations on how social identities may be used to promote TMS in multidisciplinary teams.

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Background: Seizures and interictal spikes in mesial temporal lobe epilepsy (MTLE) affect a network of brain regions rather than a single epileptic focus. Simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) studies have demonstrated a functional network in which hemodynamic changes are time-locked to spikes. However, whether this reflects the propagation of neuronal activity from a focus, or conversely the activation of a network linked to spike generation remains unknown. The functional connectivity (FC) changes prior to spikes may provide information about the connectivity changes that lead to the generation of spikes. We used EEG-fMRI to investigate FC changes immediately prior to the appearance of interictal spikes on EEG in patients with MTLE. Methods/principal findings: Fifteen patients with MTLE underwent continuous EEG-fMRI during rest. Spikes were identified on EEG and three 10 s epochs were defined relative to spike onset: spike (0–10 s), pre-spike (−10 to 0 s), and rest (−20 to −10 s, with no previous spikes in the preceding 45s). Significant spike-related activation in the hippocampus ipsilateral to the seizure focus was found compared to the pre-spike and rest epochs. The peak voxel within the hippocampus ipsilateral to the seizure focus was used as a seed region for FC analysis in the three conditions. A significant change in FC patterns was observed before the appearance of electrographic spikes. Specifically, there was significant loss of coherence between both hippocampi during the pre-spike period compared to spike and rest states. Conclusion/significance: In keeping with previous findings of abnormal inter-hemispheric hippocampal connectivity in MTLE, our findings specifically link reduced connectivity to the period immediately before spikes. This brief decoupling is consistent with a deficit in mutual (inter-hemispheric) hippocampal inhibition that may predispose to spike generation.

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Diarrhoea is a common complication observed in critically ill patients. Relationships between diarrhoea, enteral nutrition and aerobic intestinal microflora have been disconnectedly examined in this patient cohort. This research used a two-study, observational design to examine these associations. Higher diarrhoea incidence rates were observed when patients received enteral tube feeding, had abnormal serum blood results, received multiple medications and had aerobic microflora dysbiosis. Further, significant aerobic intestinal microflora changes were observed over time in patients who experienced diarrhoea. These results establish a platform for further work to improve the intestinal health of critically ill patients.

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Background Australian national biomonitoring for persistent organic pollutants (POPs) relies upon age-specific pooled serum samples to characterize central tendencies of concentrations but does not provide estimates of upper bound concentrations. This analysis compares population variation from biomonitoring datasets from the US, Canada, Germany, Spain, and Belgium to identify and test patterns potentially useful for estimating population upper bound reference values for the Australian population. Methods Arithmetic means and the ratio of the 95th percentile to the arithmetic mean (P95:mean) were assessed by survey for defined age subgroups for three polychlorinated biphenyls (PCBs 138, 153, and 180), hexachlorobenzene (HCB), p,p-dichlorodiphenyldichloroethylene (DDE), 2,2′,4,4′ tetrabrominated diphenylether (PBDE 47), perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS). Results Arithmetic mean concentrations of each analyte varied widely across surveys and age groups. However, P95:mean ratios differed to a limited extent, with no systematic variation across ages. The average P95:mean ratios were 2.2 for the three PCBs and HCB; 3.0 for DDE; 2.0 and 2.3 for PFOA and PFOS, respectively. The P95:mean ratio for PBDE 47 was more variable among age groups, ranging from 2.7 to 4.8. The average P95:mean ratios accurately estimated age group-specific P95s in the Flemish Environmental Health Survey II and were used to estimate the P95s for the Australian population by age group from the pooled biomonitoring data. Conclusions Similar population variation patterns for POPs were observed across multiple surveys, even when absolute concentrations differed widely. These patterns can be used to estimate population upper bounds when only pooled sampling data are available.

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Overarching Research Questions Are ACT motorists aware of roadside saliva based drug testing operations? What is the perceived deterrent impact of the operations? What factors are predictive of future intentions to drug drive? What are the differences between key subgroups

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Background and Objectives: Although depression is a commonly occurring mental illness, research concerning strategies for early detection and prophylaxis has not until now focused on the possible utility of measures of Emotional Intelligence (EI) as a potential predictive factor. The current study aimed to investigate the relationship between EI and a clinical diagnosis of depression in a cohort of adults. Methods: Sixty-two patients (59.70% female) with a DSM-IV-TR diagnosis of a major affective disorder and 39 aged matched controls (56.40% female) completed self-report instruments assessing EI and depression in a cross-sectional study. Results: Significant associations were observed between severity of depression and the EI dimensions of Emotional Management (r = -0.56) and Emotional Control (r = -0.62). The results show a reduced social involvement, an increased prior institutionalization and an increased incidence of "Schizophrenic Psychosis" and "Abnormal Personalities" in the sub-group of repeated admissions. Conclusions: Measures of EI may have predictive value in terms of early identification of those at risk for developing depression. The current study points to the potential value of conducting further studies of a prospective nature.

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An estimated one in 10 Australians has asthma. In 2010, the burden of disease for asthma was ranked 7th highest for the overall population in Australasia. A less well-known condition that also affects breathing, is vocal cord dysfunction (VCD). People with asthma and VCD can both present with similar symptoms such as coughing, difficulty breathing, wheezing and throat tightness. Asthma and VCD attacks also share similar triggers such as breathing in lung irritants, exercising or having an upper respiratory infection. Asthma and VCD frequently coexist. They affect different parts of the respiratory system and appear to have separate aetiologies. Asthma is essentially a condition of airway inflammation, even though the most prominent clinical presentation is bronchoconstriction. which is responsible for symptoms such as wheezing and shortness of breath. The cause of VCD is not well understood, though the abnormal closing of the vocal cords during breathing does not appear to involve an immune reaction, or the lower airways...

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Background: While weight gain following breast cancer is considered common, results supporting these findings are dated. This work describes changes in body weight following breast cancer over 72 months, compares weight with normative data and explores whether weight changes over time are associated with personal, diagnostic, treatment or behavioral characteristics. Methods: A population-based sample of 287 Australian women diagnosed with early-stage invasive breast cancer was assessed prospectively at six, 12, 18 and 72 months post-surgery. Weight was clinically measured and linear mixed models were used to explore associations between weight and participant characteristics (collected via self-administered questionnaire). Those with BMI changes of one or more units were considered to have experienced clinically significant changes in weight. Results: More than half (57%) of participants were overweight or obese at 6 months post-surgery, and by 72 months post-surgery 68% of women were overweight or obese. Among those who gained more weight than age-matched norms, clinically significant weight gain between 6 and 18 months and 6 and 72 months post-surgery was observed in 24% and 39% of participants, respectively (median [range] weight gain: 3.9kg [2.0-11.3kg] and 5.2kg [0.6-28.7], respectively). Clinically-significant weight losses were observed in up to 24% of the sample (median [range] weight loss between 6 and 72 months post-surgery: -6.4kg [-1.9--24.6kg]). More extensive lymph node removal, being treated on the non-dominant side, receiving radiation therapy and lower physical activity levels at 6 months was associated with higher body weights post-breast cancer (group differences >3kg; all p<0.05). Conclusions: While average weight gain among breast cancer survivors in the long-term is small, subgroups of women experience greater gains linked with adverse health and above that experienced by age-matched counterparts. Weight change post-breast cancer is a contemporary public health issue and the integration of healthy weight education and support into standard breast cancer care has potential to significantly improve the length and quality of cancer survivorship.

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Experimental work could be conducted in either laboratory or at field site. Generally, the laboratory experiments are carried out in an artificial setting and with a highly controlled environment. By contrast, the field experiments often take place in a natural setting, subject to the influences of many uncontrolled factors. Therefore, it is necessary to carefully assess the possible limitations and appropriateness of an experiment before embarking on it. In this paper, a case study of field monitoring of the energy performance of air conditioners is presented. Significant challenges facing the experimental work are described. Lessons learnt from this case study are also discussed. In particular, it was found that on-going analysis of the monitoring data and the correction of abnormal issues are two of the keys for a successful field test program. It was also shown that the installation of monitoring systems could have a significant impact on the accuracy of the data being collected. Before monitoring system was set up to collect monitoring data, it is recommended that an initial analysis of sample monitored data should be conducted to make sure that the monitoring data can achieve the expected precision. In the case where inevitable inherent errors were induced from the installation of field monitoring systems, appropriate remediation may need to be developed and implemented for the improved accuracy of the estimation of results. On-going analysis of monitoring data and correction of any abnormal issues would be the key to a successful field test program.

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This article examines whether investors are able to generate abnormal risk-adjusted returns in the Australian market based on media-specific firm reputational factors under market uncertainty between 2004 and 2012. The findings suggest that after controlling for crisis-centric time periods and market risk factors, contrarian trading strategies produce abnormal returns for poor corporate reputation firms but not for their good corporate reputation counterparts. Corporate reputation may be a driver of performance for poorly performing Australian firms and could be considered a stimulus for trading activity due to its explanatory capabilities.

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In this chapter we aim to explore how videogames can lead to improvements in wellbeing. Following Keyes (2007) and Huppert and So (2012) we view wellbeing as a multidimensional concept with both hedonic and eudaimonic aspects. In this chapter we take a broad approach in terms of exploring the impact of videogames on the psychological, social, and physical components of wellbeing. We explore how videogames have been shown to have an impact in each of these domains. Although there is a great deal of evidence for the actual and potential positive impacts of videogames, there are many unanswered questions regarding the situations in which there is likely to be an impact of videogame play on wellbeing, as well as the aspects of wellbeing that are likely to be impacted by videogame play. We conclude the chapter by outlining the key questions for future research. Our focus in this chapter is on the positive influences of videogames. We do not explore research on contexts in which negative impacts are possible or subgroups for which videogames could cause harm. However, these questions are obviously important and we see balanced engagement with age-appropriate videogames as a key prerequisite for any of the wellbeing benefits discussed below.

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Background There is evidence that family and friends influence children's decisions to smoke. Objectives To assess the effectiveness of interventions to help families stop children starting smoking. Search methods We searched 14 electronic bibliographic databases, including the Cochrane Tobacco Addiction Group specialized register, MEDLINE, EMBASE, PsycINFO, CINAHL unpublished material, and key articles' reference lists. We performed free-text internet searches and targeted searches of appropriate websites, and hand-searched key journals not available electronically. We consulted authors and experts in the field. The most recent search was 3 April 2014. There were no date or language limitations. Selection criteria Randomised controlled trials (RCTs) of interventions with children (aged 5-12) or adolescents (aged 13-18) and families to deter tobacco use. The primary outcome was the effect of the intervention on the smoking status of children who reported no use of tobacco at baseline. Included trials had to report outcomes measured at least six months from the start of the intervention. Data collection and analysis We reviewed all potentially relevant citations and retrieved the full text to determine whether the study was an RCT and matched our inclusion criteria. Two authors independently extracted study data for each RCT and assessed them for risk of bias. We pooled risk ratios using a Mantel-Haenszel fixed effect model. Main results Twenty-seven RCTs were included. The interventions were very heterogeneous in the components of the family intervention, the other risk behaviours targeted alongside tobacco, the age of children at baseline and the length of follow-up. Two interventions were tested by two RCTs, one was tested by three RCTs and the remaining 20 distinct interventions were tested only by one RCT. Twenty-three interventions were tested in the USA, two in Europe, one in Australia and one in India. The control conditions fell into two main groups: no intervention or usual care; or school-based interventions provided to all participants. These two groups of studies were considered separately. Most studies had a judgement of 'unclear' for at least one risk of bias criteria, so the quality of evidence was downgraded to moderate. Although there was heterogeneity between studies there was little evidence of statistical heterogeneity in the results. We were unable to extract data from all studies in a format that allowed inclusion in a meta-analysis. There was moderate quality evidence family-based interventions had a positive impact on preventing smoking when compared to a no intervention control. Nine studies (4810 participants) reporting smoking uptake amongst baseline non-smokers could be pooled, but eight studies with about 5000 participants could not be pooled because of insufficient data. The pooled estimate detected a significant reduction in smoking behaviour in the intervention arms (risk ratio [RR] 0.76, 95% confidence interval [CI] 0.68 to 0.84). Most of these studies used intensive interventions. Estimates for the medium and low intensity subgroups were similar but confidence intervals were wide. Two studies in which some of the 4487 participants already had smoking experience at baseline did not detect evidence of effect (RR 1.04, 95% CI 0.93 to 1.17). Eight RCTs compared a combined family plus school intervention to a school intervention only. Of the three studies with data, two RCTS with outcomes for 2301 baseline never smokers detected evidence of an effect (RR 0.85, 95% CI 0.75 to 0.96) and one study with data for 1096 participants not restricted to never users at baseline also detected a benefit (RR 0.60, 95% CI 0.38 to 0.94). The other five studies with about 18,500 participants did not report data in a format allowing meta-analysis. One RCT also compared a family intervention to a school 'good behaviour' intervention and did not detect a difference between the two types of programme (RR 1.05, 95% CI 0.80 to 1.38, n = 388). No studies identified any adverse effects of intervention. Authors' conclusions There is moderate quality evidence to suggest that family-based interventions can have a positive effect on preventing children and adolescents from starting to smoke. There were more studies of high intensity programmes compared to a control group receiving no intervention, than there were for other compairsons. The evidence is therefore strongest for high intensity programmes used independently of school interventions. Programmes typically addressed family functioning, and were introduced when children were between 11 and 14 years old. Based on this moderate quality evidence a family intervention might reduce uptake or experimentation with smoking by between 16 and 32%. However, these findings should be interpreted cautiously because effect estimates could not include data from all studies. Our interpretation is that the common feature of the effective high intensity interventions was encouraging authoritative parenting (which is usually defined as showing strong interest in and care for the adolescent, often with rule setting). This is different from authoritarian parenting (do as I say) or neglectful or unsupervised parenting.

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The use of expert knowledge to quantify a Bayesian Network (BN) is necessary when data is not available. This however raises questions regarding how opinions from multiple experts can be used in a BN. Linear pooling is a popular method for combining probability assessments from multiple experts. In particular, Prior Linear Pooling (PrLP), which pools opinions then places them into the BN is a common method. This paper firstly proposes an alternative pooling method, Posterior Linear Pooling (PoLP). This method constructs a BN for each expert, then pools the resulting probabilities at the nodes of interest. Secondly, it investigates the advantages and disadvantages of using these pooling methods to combine the opinions of multiple experts. Finally, the methods are applied to an existing BN, the Wayfinding Bayesian Network Model, to investigate the behaviour of different groups of people and how these different methods may be able to capture such differences. The paper focusses on 6 nodes Human Factors, Environmental Factors, Wayfinding, Communication, Visual Elements of Communication and Navigation Pathway, and three subgroups Gender (female, male),Travel Experience (experienced, inexperienced), and Travel Purpose (business, personal) and finds that different behaviors can indeed be captured by the different methods.