217 research outputs found

    A spatial epidemiological analysis of self-rated mental health in the slums of Dhaka

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    Grübner O, Khan MH, Lautenbach S, et al. A spatial epidemiological analysis of self-rated mental health in the slums of Dhaka. International Journal of Health Geographics. 2011;10(1): 36.Background: The deprived physical environments present in slums are well-known to have adverse health effects on their residents. However, little is known about the health effects of the social environments in slums. Moreover, neighbourhood quantitative spatial analyses of the mental health status of slum residents are still rare. The aim of this paper is to study self-rated mental health data in several slums of Dhaka, Bangladesh, by accounting for neighbourhood social and physical associations using spatial statistics. We hypothesised that mental health would show a significant spatial pattern in different population groups, and that the spatial patterns would relate to spatially-correlated health-determining factors (HDF). Methods: We applied a spatial epidemiological approach, including non-spatial ANOVA/ANCOVA, as well as global and local univariate and bivariate Moran's / statistics. The WHO-5 Well-being Index was used as a measure of self-rated mental health. Results: We found that poor mental health (WHO-5 scores = 15) was prevalent in all slum settlements. We detected spatially autocorrelated WHO-5 scores (i.e., spatial clusters of poor and good mental health among different population groups). Further, we detected spatial associations between mental health and housing quality, sanitation, income generation, environmental health knowledge, education, age, gender, flood non-affectedness, and selected properties of the natural environment. Conclusions: Spatial patterns of mental health were detected and could be partly explained by spatially correlated HDF. We thereby showed that the socio-physical neighbourhood was significantly associated with health status, i.e., mental health at one location was spatially dependent on the mental health and HDF prevalent at neighbouring locations. Furthermore, the spatial patterns point to severe health disparities both within and between the slums. In addition to examining health outcomes, the methodology used here is also applicable to residuals of regression models, such as helping to avoid violating the assumption of data independence that underlies many statistical approaches. We assume that similar spatial structures can be found in other studies focussing on neighbourhood effects on health, and therefore argue for a more widespread incorporation of spatial statistics in epidemiological studies

    Elevation as a proxy for mosquito-borne Zika virus transmission in the Americas.

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    INTRODUCTION: When Zika virus (ZIKV) first began its spread from Brazil to other parts of the Americas, national-level travel notices were issued, carrying with them significant economic consequences to affected countries. Although regions of some affected countries were likely unsuitable for mosquito-borne transmission of ZIKV, the absence of high quality, timely surveillance data made it difficult to confidently demarcate infection risk at a sub-national level. In the absence of reliable data on ZIKV activity, a pragmatic approach was needed to identify subnational geographic areas where the risk of ZIKV infection via mosquitoes was expected to be negligible. To address this urgent need, we evaluated elevation as a proxy for mosquito-borne ZIKV transmission. METHODS: For sixteen countries with local ZIKV transmission in the Americas, we analyzed (i) modelled occurrence of the primary vector for ZIKV, Aedes aegypti, (ii) human population counts, and (iii) reported historical dengue cases, specifically across 100-meter elevation levels between 1,500m and 2,500m. Specifically, we quantified land area, population size, and the number of observed dengue cases above each elevation level to identify a threshold where the predicted risks of encountering Ae. aegypti become negligible. RESULTS: Above 1,600m, less than 1% of each country's total land area was predicted to have Ae. aegypti occurrence. Above 1,900m, less than 1% of each country's resident population lived in areas where Ae. aegypti was predicted to occur. Across all 16 countries, 1.1% of historical dengue cases were reported above 2,000m. DISCUSSION: These results suggest low potential for mosquito-borne ZIKV transmission above 2,000m in the Americas. Although elevation is a crude predictor of environmental suitability for ZIKV transmission, its constancy made it a pragmatic input for policy decision-making during this public health emergency

    FONZIE: An optimized pipeline for minisatellite marker discovery and primer design from large sequence data sets

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    <p>Abstract</p> <p>Background</p> <p>Micro-and minisatellites are among the most powerful genetic markers known to date. They have been used as tools for a large number of applications ranging from gene mapping to phylogenetic studies and isolate typing. However, identifying micro-and minisatellite markers on large sequence data sets is often a laborious process.</p> <p>Results</p> <p>FONZIE was designed to successively 1) perform a search for markers via the external software Tandem Repeat Finder, 2) exclude user-defined specific genomic regions, 3) screen for the size and the percent matches of each relevant marker found by Tandem Repeat Finder, 4) evaluate marker specificity (i.e., occurrence of the marker as a single copy in the genome) using BLAST2.0, 5) design minisatellite primer pairs via the external software Primer3, and 6) check the specificity of each final PCR product by BLAST. A final file returns to users all the results required to amplify markers. A biological validation of the approach was performed using the whole genome sequence of the phytopathogenic fungus <it>Leptosphaeria maculans</it>, showing that more than 90% of the minisatellite primer pairs generated by the pipeline amplified a PCR product, 44.8% of which showed agarose-gel resolvable polymorphism between isolates. Segregation analyses confirmed that the polymorphic minisatellites corresponded to single-locus markers.</p> <p>Conclusion</p> <p>FONZIE is a stand-alone and user-friendly application developed to minimize tedious manual operations, reduce errors, and speed up the search for efficient minisatellite and microsatellite markers departing from whole-genome sequence data. This pipeline facilitates the integration of data and provides a set of specific primer sequences for PCR amplification of single-locus markers. FONZIE is freely downloadable at: <url>http://www.versailles-grignon.inra.fr/bioger/equipes/leptosphaeria_maculans/outils_d_analyses/fonzie</url></p

    Development of HDAC Inhibitors Exhibiting Therapeutic Potential in T-Cell Prolymphocytic Leukemia

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    Epigenetic targeting has emerged as an efficacious therapy for hematological cancers. The rare and incurable T-cell prolymphocytic leukemia (T-PLL) is known for its aggressive clinical course. Current epigenetic agents such as histone deacetylase (HDAC) inhibitors are increasingly used for targeted therapy. Through a structure-activity relationship (SAR) study, we developed an HDAC6 inhibitor KT-531, which exhibited higher potency in T-PLL compared to other hematological cancers. KT-531 displayed strong HDAC6 inhibitory potency and selectivity, on-target biological activity, and a safe therapeutic window in nontransformed cell lines. In primary T-PLL patient cells, where HDAC6 was found to be overexpressed, KT-531 exhibited strong biological responses, and safety in healthy donor samples. Notably, combination studies in T-PLL patient samples demonstrated KT-531 synergizes with approved cancer drugs, bendamustine, idasanutlin, and venetoclax. Our work suggests HDAC inhibition in T-PLL could afford sufficient therapeutic windows to achieve durable remission either as standalone or in combination with targeted drugs.Peer reviewe

    Determination of alpha_s using Jet Rates at LEP with the OPAL detector

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    Hadronic events produced in e+e- collisions by the LEP collider and recorded by the OPAL detector were used to form distributions based on the number of reconstructed jets. The data were collected between 1995 and 2000 and correspond to energies of 91 GeV, 130-136 GeV and 161-209 GeV. The jet rates were determined using four different jet-finding algorithms (Cone, JADE, Durham and Cambridge). The differential two-jet rate and the average jet rate with the Durham and Cambridge algorithms were used to measure alpha(s) in the LEP energy range by fitting an expression in which order alpah_2s calculations were matched to a NLLA prediction and fitted to the data. Combining the measurements at different centre-of-mass energies, the value of alpha_s (Mz) was determined to be alpha(s)(Mz)=0.1177+-0.0006(stat.)+-0.0012$(expt.)+-0.0010(had.)+-0.0032(theo.) \.Comment: 40 pages, 17 figures, Submitted to Euro. Phys. J.

    Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus

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    The global population at risk from mosquito-borne diseases—including dengue, yellow fever, chikungunya and Zika—is expanding in concert with changes in the distribution of two key vectors: Aedes aegypti and Aedes albopictus. The distribution of these species is largely driven by both human movement and the presence of suitable climate. Using statistical mapping techniques, we show that human movement patterns explain the spread of both species in Europe and the United States following their introduction. We find that the spread of Ae. aegypti is characterized by long distance importations, while Ae. albopictus has expanded more along the fringes of its distribution. We describe these processes and predict the future distributions of both species in response to accelerating urbanization, connectivity and climate change. Global surveillance and control efforts that aim to mitigate the spread of chikungunya, dengue, yellow fever and Zika viruses must consider the so far unabated spread of these mosquitos. Our maps and predictions offer an opportunity to strategically target surveillance and control programmes and thereby augment efforts to reduce arbovirus burden in human populations globally

    First narrow-band search for continuous gravitational waves from known pulsars in advanced detector data

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    Spinning neutron stars asymmetric with respect to their rotation axis are potential sources of continuous gravitational waves for ground-based interferometric detectors. In the case of known pulsars a fully coherent search, based on matched filtering, which uses the position and rotational parameters obtained from electromagnetic observations, can be carried out. Matched filtering maximizes the signalto- noise (SNR) ratio, but a large sensitivity loss is expected in case of even a very small mismatch between the assumed and the true signal parameters. For this reason, narrow-band analysis methods have been developed, allowing a fully coherent search for gravitational waves from known pulsars over a fraction of a hertz and several spin-down values. In this paper we describe a narrow-band search of 11 pulsars using data from Advanced LIGO’s first observing run. Although we have found several initial outliers, further studies show no significant evidence for the presence of a gravitational wave signal. Finally, we have placed upper limits on the signal strain amplitude lower than the spin-down limit for 5 of the 11 targets over the bands searched; in the case of J1813-1749 the spin-down limit has been beaten for the first time. For an additional 3 targets, the median upper limit across the search bands is below the spin-down limit. This is the most sensitive narrow-band search for continuous gravitational waves carried out so far

    Spread of yellow fever virus outbreak in Angola and the Democratic Republic of the Congo 2015-16: a modelling study.

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    BACKGROUND: Since late 2015, an epidemic of yellow fever has caused more than 7334 suspected cases in Angola and the Democratic Republic of the Congo, including 393 deaths. We sought to understand the spatial spread of this outbreak to optimise the use of the limited available vaccine stock. METHODS: We jointly analysed datasets describing the epidemic of yellow fever, vector suitability, human demography, and mobility in central Africa to understand and predict the spread of yellow fever virus. We used a standard logistic model to infer the district-specific yellow fever virus infection risk during the course of the epidemic in the region. FINDINGS: The early spread of yellow fever virus was characterised by fast exponential growth (doubling time of 5-7 days) and fast spatial expansion (49 districts reported cases after only 3 months) from Luanda, the capital of Angola. Early invasion was positively correlated with high population density (Pearson's r 0·52, 95% CI 0·34-0·66). The further away locations were from Luanda, the later the date of invasion (Pearson's r 0·60, 95% CI 0·52-0·66). In a Cox model, we noted that districts with higher population densities also had higher risks of sustained transmission (the hazard ratio for cases ceasing was 0·74, 95% CI 0·13-0·92 per log-unit increase in the population size of a district). A model that captured human mobility and vector suitability successfully discriminated districts with high risk of invasion from others with a lower risk (area under the curve 0·94, 95% CI 0·92-0·97). If at the start of the epidemic, sufficient vaccines had been available to target 50 out of 313 districts in the area, our model would have correctly identified 27 (84%) of the 32 districts that were eventually affected. INTERPRETATION: Our findings show the contributions of ecological and demographic factors to the ongoing spread of the yellow fever outbreak and provide estimates of the areas that could be prioritised for vaccination, although other constraints such as vaccine supply and delivery need to be accounted for before such insights can be translated into policy. FUNDING: Wellcome Trust
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