47 research outputs found

    Do continuum beliefs reduce schizophrenia stigma? Effects of a laboratory intervention on behavioral and self-reported stigma

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    Background and objectives Correlational research shows that belief in a continuum of psychiatric problems predicts decreased public stigma. However, the correlational findings fail to inform the stigma reduction prospects of manipulating continuum beliefs. All extant experimental work has been executed online. This study examined effects of a laboratory-based continuum intervention on behavioral and self-report measures of psychiatric stigma. Methods Sixty-nine undergraduates believed that they would meet a man with schizophrenia. They then read a bogus scientific article that attested to a categorical view of schizophrenia, a continuum view, or that merely described schizophrenia. Some participants then completed a task that required reflection on their differences from (categorical group) or similarities to (continuum group) the man with schizophrenia. Participants eventually moved to an adjacent room and sat in one of several seats that varied in their proximity to a seat ostensibly occupied by the man with schizophrenia. Results The continuum intervention decreased self-reported social distance and the categorical intervention increased endorsement of damaging stereotypes. Seat selection was unaffected by our manipulation, but we obtained evidence of significant links to validated stigma measures. Limitations Our sample was small, and our behavioral stigma measure could be modified to maximize variability in participants\u27 seat selection. Conclusions The study offers modest support of the stigma reduction effect of continuum belief intervention. It offers new evidence of the pernicious consequences of interventions that inflate perceptions of the “otherness” of individuals with psychiatric problems. Finally, it shines new light on stigma-related behavior measurable in the laboratory

    The Sec1p/Munc18 protein Vps45p binds its cognate SNARE proteins via two distinct modes

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    Sec1p/Munc18 (SM) proteins are essential for SNARE-mediated membrane trafficking. The formulation of unifying hypotheses for the function of the SM protein family has been hampered by the observation that two of its members bind their cognate syntaxins (Sxs) in strikingly different ways. The SM protein Vps45p binds its Sx Tlg2p in a manner analogous to that captured by the Sly1p–Sed5p crystal structure, whereby the NH2-terminal peptide of the Sx inserts into a hydrophobic pocket on the outer face of domain I of the SM protein. In this study, we report that although this mode of interaction is critical for the binding of Vps45p to Tlg2p, the SM protein also binds Tlg2p-containing SNARE complexes via a second mode that involves neither the NH2 terminus of Tlg2p nor the region of Vps45p that facilitates this interaction. Our findings point to the possibility that SM proteins interact with their cognate SNARE proteins through distinct mechanisms at different stages in the SNARE assembly/disassembly cycle

    Effect of meteorological factors on clinical malaria risk among children: an assessment using village-based meteorological stations and community-based parasitological survey

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    <p>Abstract</p> <p>Background</p> <p>Temperature, rainfall and humidity have been widely associated with the dynamics of malaria vector population and, therefore, with spread of the disease. However, at the local scale, there is a lack of a systematic quantification of the effect of these factors on malaria transmission. Further, most attempts to quantify this effect are based on proxy meteorological data acquired from satellites or interpolated from a different scale. This has led to controversies about the contribution of climate change to malaria transmission risk among others. Our study addresses the original question of relating meteorological factors measured at the local scale with malaria infection, using data collected at the same time and scale.</p> <p>Methods</p> <p>676 children (6–59 months) were selected randomly from three ecologically different sites (urban and rural). During weekly home visits between December 1, 2003, and November 30, 2004, fieldworkers tested children with fever for clinical malaria. They also collected data on possible confounders monthly. Digital meteorological stations measured ambient temperature, humidity, and rainfall in each site. Logistic regression was used to estimate the risk of clinical malaria given the previous month's meteorological conditions.</p> <p>Results</p> <p>The overall incidence of clinical malaria over the study period was 1.07 episodes per child. Meteorological factors were associated with clinical malaria with mean temperature having the largest effect.</p> <p>Conclusion</p> <p>Temperature was the best predictor for clinical malaria among children under five. A systematic measurement of local temperature through ground stations and integration of such data in the routine health information system could support assessment of malaria transmission risk at the district level for well-targeted control efforts.</p

    The Sec1/Munc18 protein Vps45 regulates cellular levels of its SNARE binding partners Tlg2 and Snc2 in Saccharomyces cerevisiae

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    Intracellular membrane trafficking pathways must be tightly regulated to ensure proper functioning of all eukaryotic cells. Central to membrane trafficking is the formation of specific SNARE (soluble N-ethylmeleimide-sensitive factor attachment protein receptor) complexes between proteins on opposing lipid bilayers. The Sec1/Munc18 (SM) family of proteins play an essential role in SNARE-mediated membrane fusion, and like the SNAREs are conserved through evolution from yeast to humans. The SM protein Vps45 is required for the formation of yeast endosomal SNARE complexes and is thus essential for traffic through the endosomal system. Here we report that, in addition to its role in regulating SNARE complex assembly, Vps45 regulates cellular levels of its SNARE binding partners: the syntaxin Tlg2 and the v-SNARE Snc2: Cells lacking Vps45 have reduced cellular levels of Tlg2 and Snc2; and elevation of Vps45 levels results in concomitant increases in the levels of both Tlg2 and Snc2. As well as regulating traffic through the endosomal system, the Snc v-SNAREs are also required for exocytosis. Unlike most vps mutants, cells lacking Vps45 display multiple growth phenotypes. Here we report that these can be reversed by selectively restoring Snc2 levels in vps45 mutant cells. Our data indicate that as well as functioning as part of the machinery that controls SNARE complex assembly, Vps45 also plays a key role in determining the levels of its cognate SNARE proteins; another key factor in regulation of membrane traffic

    Indian Ocean Dipole drives malaria resurgence in East African highlands

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    Malaria resurgence in African highlands in the 1990s has raised questions about the underlying drivers of the increase in disease incidence including the role of El-Niño-Southern Oscillation (ENSO). However, climatic anomalies other than the ENSO are clearly associated with malaria outbreaks in the highlands. Here we show that the Indian Ocean Dipole (IOD), a coupled ocean-atmosphere interaction in the Indian Ocean, affected highland malaria re-emergence. Using cross-wavelet coherence analysis, we found four-year long coherent cycles between the malaria time series and the dipole mode index (DMI) in the 1990s in three highland localities. Conversely, we found a less pronounced coherence between malaria and DMI in lowland localities. The highland/lowland contrast can be explained by the effects of mesoscale systems generated by Lake Victoria on its climate basin. Our results support the need to consider IOD as a driving force in the resurgence of malaria in the East African highlands

    One-year delayed effect of fog on malaria transmission: a time-series analysis in the rain forest area of Mengla County, south-west China

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    Background: Malaria is a major public health burden in the tropics with the potential to significantly increase in response to climate change. Analyses of data from the recent past can elucidate how short-term variations in weather factors affect malaria transmission. This study explored the impact of climate variability on the transmission of malaria in the tropical rain forest area of Mengla County, south-west China. Methods: Ecological time-series analysis was performed on data collected between 1971 and 1999. Auto-regressive integrated moving average (ARIMA) models were used to evaluate the relationship between weather factors and malaria incidence. Results: At the time scale of months, the predictors for malaria incidence included: minimum temperature, maximum temperature, and fog day frequency. The effect of minimum temperature on malaria incidence was greater in the cool months than in the hot months. The fog day frequency in October had a positive effect on malaria incidence in May of the following year. At the time scale of years, the annual fog day frequency was the only weather predictor of the annual incidence of malaria. Conclusion: Fog day frequency was for the first time found to be a predictor of malaria incidence in a rain forest area. The one-year delayed effect of fog on malaria transmission may involve providing water input and maintaining aquatic breeding sites for mosquitoes in vulnerable times when there is little rainfall in the 6-month dry seasons. These findings should be considered in the prediction of future patterns of malaria for similar tropical rain forest areas worldwide

    Assessing the risk of self-diagnosed malaria in urban informal settlements of Nairobi using self-reported morbidity survey

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    <p>Abstract</p> <p>Background</p> <p>Because of the belief that Nairobi is a low risk zone for malaria, little empirical data exists on malaria risk in the area. The aim of this study was to explore the risk of perceived malaria and some associated factors in Nairobi informal settlements using self-reported morbidity survey.</p> <p>Methods</p> <p>The survey was conducted from May to August 2004 on 7,288 individuals in two informal settlements of Nairobi. Participants were asked to report illnesses they experienced in the past 14 days. Logistic regression was used to estimate the odds of perceived-malaria. The model included variables such as site of residence, age, ethnicity and number of reported symptoms.</p> <p>Results</p> <p>Participants reported 165 illnesses among which malaria was the leading cause (28.1%). The risk of perceived-malaria was significantly higher in Viwandani compared to Korogocho (OR 1.61, 95%CI: 1.10–2.26). Participants in age group 25–39 years had significantly higher odds of perceived-malaria compared to those under-five years (OR 2.07, 95%CI: 1.43–2.98). The Kikuyu had reduced odds of perceived-malaria compared to other ethnic groups. Individuals with five and more symptoms had higher odds compared to those with no symptoms (OR 23.69, 95%CI: 12.98–43.23).</p> <p>Conclusion</p> <p>Malaria was the leading cause of illness as perceived by the residents in the two informal settlements. This was rational as the number of reported symptoms was highly associated with the risk of reporting the illness. These results highlight the need for a more comprehensive assessment of malaria epidemiology in Nairobi to be able to offer evidence-based guidance to policy on malaria in Kenya and particularly in Nairobi.</p

    Climatic variables and malaria transmission dynamics in Jimma town, South West Ethiopia

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    <p>Abstract</p> <p>Background:-</p> <p>In Ethiopia, malaria is seasonal and unstable, causing frequent epidemics. It usually occurs at altitudes < 2,000 m above sea level. Occasionally, transmission of malaria occurs in areas previously free of malaria, including areas > 2,000 m above sea level. For transmission of malaria parasite, climatic factors are important determinants as well as non-climatic factors that can negate climatic influences. Indeed, there is a scarcity of information on the correlation between climatic variability and malaria transmission risk in Ethiopia in general and in the study area in particular. Therefore, the aim of this study was to determine the level of correlation between meteorological variables and malaria cases.</p> <p>Methods: -</p> <p>Time-series analysis was conducted using data on monthly meteorological variables and monthly total malaria in Jimma town, south west Ethiopia, for the period 2000-2009. All the data were entered and analyzed using SPSS-15 database program. Spearman correlation and linear regression analysis were used to asses association between the variables.</p> <p>Results: -</p> <p>During last ten years (2000-2009), a fluctuating trend of malaria transmission was observed with <it>P.vivax </it>becoming predominant species. Spearman correlation analysis showed that monthly minimum temperature, total rainfall and two measures of relative humidity were positively related with malaria but monthly maximum temperature negatively related. Also regression analysis suggested that monthly minimum (p = 0.008), monthly maximum temperature (p = 0.013) and monthly total rainfall (p = 0.040), at one month lagged effect, were significant meteorological factors for transmission of malaria in the study area.</p> <p>Conclusion: -</p> <p>Malaria incidences in the last decade seem to have a significant association with meteorological variables. In future, prospective and multidisciplinary cooperative research involving researchers from the fields of parasitology, epidemiology, botany, agriculture and climatology is necessary to identify the real effect of meteorological factors on vector- borne diseases like malaria.</p

    Science Forum: Consensus-based guidance for conducting and reporting multi-analyst studies

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    Any large dataset can be analyzed in a number of ways, and it is possible that the use of different analysis strategies will lead to different results and conclusions. One way to assess whether the results obtained depend on the analysis strategy chosen is to employ multiple analysts and leave each of them free to follow their own approach. Here, we present consensus-based guidance for conducting and reporting such multi-analyst studies, and we discuss how broader adoption of the multi-analyst approach has the potential to strengthen the robustness of results and conclusions obtained from analyses of datasets in basic and applied research

    Consensus-based guidance for conducting and reporting multi-analyst studies

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    International audienceAny large dataset can be analyzed in a number of ways, and it is possible that the use of different analysis strategies will lead to different results and conclusions. One way to assess whether the results obtained depend on the analysis strategy chosen is to employ multiple analysts and leave each of them free to follow their own approach. Here, we present consensus-based guidance for conducting and reporting such multi-analyst studies, and we discuss how broader adoption of the multi-analyst approach has the potential to strengthen the robustness of results and conclusions obtained from analyses of datasets in basic and applied research
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