272 research outputs found

    Does menopause transition influence viral suppression and adherence in Women living with HIV?

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    BACKGROUND Increasing numbers of women living with HIV transition through menopause. It is unclear if this transition has an impact on treatment adherence, viral suppression, psychiatric comorbidities or drug use. We aimed at examining adherence and viral suppression during the perimenopausal period and explored the influence of psychiatric comorbidities and active injection drug use (IDU). SETTING Retrospective Swiss HIV Cohort Study analysis from 01/2010 to 12/2018. METHODS We explored peri- and postmenopausal trends of viral blips, low-level viremia, viral failure, adherence, psychiatric comorbidities and IDU using interrupted time series (ITS) models. RESULTS Rates of depression and psychiatric care increased during perimenopause before decreasing afterwards. Negative treatment outcomes such as viral blips, low-level viremia, viral failure and low adherence steadily declined while transitioning through menopause - this was also true for subgroups of women with depression, psychiatric treatment and active IDU. CONCLUSIONS Increased rates of depression and psychiatric care while transitioning through menopause do not result in lower rates of adherence or viral suppression in women living with HIV in Switzerland

    Energy, forest, and indoor air pollution models for Sagarmatha National Park and Buffer Zone, Nepal

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    This paper presents the results of management-oriented research on energy, forest, and human health issues in a remote mountain area, the Sagarmatha National Park and Buffer Zone (SNPBZ), Nepal. The research was based on a broader, integrated participatory framework ultimately intended for use in adaptive management. The present study focused on the application of a participatory modeling framework to address problems related to energy demand and consumption, forest condition, and indoor air pollution, which were defined by the stakeholders as important issues to be addressed. The models were developed using a generalizing design that allows for user-friendly adaptation to other contexts (free download at http://hkkhpartnership.org). Moreover, we simulated management scenarios in collaboration with all modeling actors with the aim of building consensus on the understanding of the system as well as supporting decision-makers' capacity not only to respond to changes, but also to anticipate them. Importantly, the system dynamics assessment found that the SNPBZ forests are affected by an increasing demand for fuelwood (occurring due to tourism growth), as one of the main sources of energy. Selected forests show an average reduction of 38 in forest biomass from 1992 to 2008. This shows that the business-as-usual scenario is unlikely to result in the preservation of the current forest status; in fact, such preservation would require 75 of fuelwood to be replaced with alternative energy sources. At the same time, a 75 reduction of fuelwood use (and an 80 reduction of dung use) would reduce indoor carbon monoxide (CO) concentrations to the standard limits for CO exposure set by the World Health Organization

    Similar but different: Integrated phylogenetic analysis of Austrian and Swiss HIV-1 sequences reveal differences in transmission patterns of the local HIV-1 epidemics.

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    OBJECTIVES Phylogenetic analyses of two or more countries allow to detect differences in transmission dynamics of local HIV-1 epidemics beyond differences in demographic characteristics. METHODS A maximum-likelihood phylogenetic tree was built using pol-sequences of the Swiss HIV Cohort Study (SHCS) and the Austrian HIV Cohort Study (AHIVCOS), with international background sequences. Three types of phylogenetic cherries (clusters of size 2) were analyzed further: 1) Domestic cherries, 2) International cherries and 3) SHCS/AHIVCOS-cherries. Transmission group and ethnicities observed within the cherries were compared to the respective distribution expected from a random distribution of patients on the phylogeny. RESULTS The demographic characteristics of the AHIVCOS (included patients: 3'141) and the SHCS (included patients: 12'902) are very similar. In the AHIVCOS, 36.5% of the patients were in domestic cherries, 8.3% in international cherries, and 7.0% in SHCS/AHIVCOS cherries. Similarly, in the SHCS, 43.0% of the patients were in domestic cherries, 8.2% in international cherries, and 1.7% in SHCS/AHIVCOS cherries. While international cherries in the SHCS were dominated by heterosexuals (HET) with MSM being underrepresented, the opposite was the case for the AHIVCOS. In both cohorts, cherries with one patient belonging to the transmission group intravenous drug user (IDU) and the other one non-IDU were underrepresented. CONCLUSION In both cohorts, international HIV transmission plays a major role in the local epidemics, mostly driven by MSM in the AHIVOS, and by HET in the SHCS, highlighting the importance of international collaborations to understand global HIV transmission links on the way to eliminate HIV

    Independent Component Analysis-motivated Approach to Classificatory Decomposition of Cortical Evoked Potentials

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    BACKGROUND: Independent Component Analysis (ICA) proves to be useful in the analysis of neural activity, as it allows for identification of distinct sources of activity. Applied to measurements registered in a controlled setting and under exposure to an external stimulus, it can facilitate analysis of the impact of the stimulus on those sources. The link between the stimulus and a given source can be verified by a classifier that is able to "predict" the condition a given signal was registered under, solely based on the components. However, the ICA's assumption about statistical independence of sources is often unrealistic and turns out to be insufficient to build an accurate classifier. Therefore, we propose to utilize a novel method, based on hybridization of ICA, multi-objective evolutionary algorithms (MOEA), and rough sets (RS), that attempts to improve the effectiveness of signal decomposition techniques by providing them with "classification-awareness." RESULTS: The preliminary results described here are very promising and further investigation of other MOEAs and/or RS-based classification accuracy measures should be pursued. Even a quick visual analysis of those results can provide an interesting insight into the problem of neural activity analysis. CONCLUSION: We present a methodology of classificatory decomposition of signals. One of the main advantages of our approach is the fact that rather than solely relying on often unrealistic assumptions about statistical independence of sources, components are generated in the light of a underlying classification problem itself

    Live cell dynamics of production, explosive release and killing activity of phage tail-like weapons for Pseudomonas kin exclusion.

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    Interference competition among bacteria requires a highly specialized, narrow-spectrum weaponry when targeting closely-related competitors while sparing individuals from the same clonal population. Here we investigated mechanisms by which environmentally important Pseudomonas bacteria with plant-beneficial activity perform kin interference competition. We show that killing between phylogenetically closely-related strains involves contractile phage tail-like devices called R-tailocins that puncture target cell membranes. Using live-cell imaging, we evidence that R-tailocins are produced at the cell center, transported to the cell poles and ejected by explosive cell lysis. This enables their dispersal over several tens of micrometers to reach targeted cells. We visualize R-tailocin-mediated competition dynamics between closely-related Pseudomonas strains at the single-cell level, both in non-induced condition and upon artificial induction. We document the fatal impact of cellular self-sacrifice coupled to deployment of phage tail-like weaponry in the microenvironment of kin bacterial competitors, emphasizing the necessity for microscale assessment of microbial competitions

    Role of Caustic Addition in Bitumen-Clay Interactions

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    Coating of bitumen by clays, known as slime coating, is detrimental to bitumen recovery from oil sands using the warm slurry extn. process. Sodium hydroxide (caustic) is added to the extn. process to balance many competing processing challenges, which include undesirable slime coating. The current research aims at understanding the role of caustic addn. in controlling interactions of bitumen with various types of model clays. The interaction potential was studied by quartz crystal microbalance with dissipation monitoring (QCM-D). After confirming the slime coating potential of montmorillonite clays on bitumen in the presence of calcium ions, the interaction of kaolinite and illite with bitumen was studied. To represent more closely the industrial applications, tailings water from bitumen extn. tests at different caustic dosage was used. At caustic dosage up to 0.5 wt % oil sands ore, a negligible coating of kaolinite on the bitumen was detd. However, at a lower level of caustic addn., illite was shown to attach to the bitumen, with the interaction potential decreasing with increasing caustic dosage. Increasing concn. of humic acids as a result of increasing caustic dosage was identified to limit the interaction potential of illite with bitumen. This fundamental study clearly shows that the crit. role of caustics in modulating interactions of clays with bitumen depends upon the type of clays. Thus, clay type was identified as a key operational variable

    Non-stationary covariance function modelling in 2D least-squares collocation

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    Standard least-squares collocation (LSC) assumes 2D stationarity and 3D isotropy, and relies on a covariance function to account for spatial dependence in the ob-served data. However, the assumption that the spatial dependence is constant through-out the region of interest may sometimes be violated. Assuming a stationary covariance structure can result in over-smoothing of, e.g., the gravity field in mountains and under-smoothing in great plains. We introduce the kernel convolution method from spatial statistics for non-stationary covariance structures, and demonstrate its advantage fordealing with non-stationarity in geodetic data. We then compared stationary and non-stationary covariance functions in 2D LSC to the empirical example of gravity anomaly interpolation near the Darling Fault, Western Australia, where the field is anisotropic and non-stationary. The results with non-stationary covariance functions are better than standard LSC in terms of formal errors and cross-validation against data not used in the interpolation, demonstrating that the use of non-stationary covariance functions can improve upon standard (stationary) LSC
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