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Background: Leprosy incidence remained at around 200,000 new cases globally for the last decade. Current strategies to reduce the number of new patients include early detection and providing post-exposure prophylaxis (PEP) to at-risk populations. Because leprosy is distributed unevenly, it is crucial to identify high-risk clusters of leprosy cases for targeting interventions. Geographic Information Systems (GIS) methodology can be used to optimize leprosy control activities by identifying clustering of leprosy cases and determining optimal target populations for PEP.Methods: The geolocations of leprosy cases registered from 2014 to 2018 in Pasuruan and Pamekasan (Indonesia) were collected and tested for spatial autocorrelation with the Moran's I statistic. We did a hotspot analysis using the Heatmap tool of QGIS to identify clusters of leprosy cases in both areas. Fifteen cluster settings were compared, varying the heatmap radius (i.e., 500 m, 1000 m, 1500 m, 2000 m, or 2500 m) and the density of clustering (low, moderate, and high). For each cluster setting, we calculated the number of cases in clusters, the size of the cluster (km2), and the total population targeted for PEP under various strategies.Results: The distribution of cases was more focused in Pasuruan (Moran's I = 0.44) than in Pamekasan (0.27). The proportion of total cases within identified clusters increased with heatmap radius and ranged from 3% to almost 100% in both areas. The proportion of the population in clusters targeted for PEP decreased with heatmap radius from > 100% to 5% in high and from 88 to 3% in moderate and low density clusters. We have developed an example of a practical guideline to determine optimal cluster settings based on a given PEP strategy, distribution of cases, resources available, and proportion of population targeted for PEP.Conclusion: Policy and operational decisions related to leprosy control programs can be guided by a hotspot analysis which aid in identifying high-risk clusters and estimating the number of people targeted for prophylactic interventions. [ABSTRACT FROM AUTHOR]

Arctic tundra vegetation composition is expected to undergo rapid changes during the coming decades because of changes in climate. Higher air temperatures generally favor growth of deciduous shrubs, often at the cost of moss growth. Mosses are considered to be very important to critical tundra ecosystem processes involved in water and energy exchange, but very little empirical data are available. Here, we studied the effect of experimental moss removal on both understory evapotranspiration and ground heat flux in plots with either a thin or a dense low shrub canopy in a tundra site with continuous permafrost in Northeast Siberia. Understory evapotranspiration increased with removal of the green moss layer, suggesting that most of the understory evapotranspiration originated from the organic soil layer underlying the green moss layer. Ground heat flux partitioning also increased with green moss removal indicating the strong insulating effect of moss. No significant effect of shrub canopy density on understory evapotranspiration was measured, but ground heat flux partitioning was reduced by a denser shrub canopy. In summary, our results show that mosses may exert strong controls on understory water and heat fluxes. Changes in moss or shrub cover may have important consequences for summer permafrost thaw and concomitant soil carbon release in Arctic tundra ecosystems. [ABSTRACT FROM AUTHOR]

Climate change is expected to cause extensive vegetation changes in the Arctic: deciduous shrubs are already expanding, in response to climate warming. The results from transect studies suggest that increasing shrub cover will impact significantly on the surface energy balance. However, little is known about the direct effects of shrub cover on permafrost thaw during summer. We experimentally quantified the influence of Betula nana cover on permafrost thaw in a moist tundra site in northeast Siberia with continuous permafrost. We measured the thaw depth of the soil, also called the active layer thickness (ALT), ground heat flux and net radiation in 10 m diameter plots with natural B. nana cover (control plots) and in plots in which B. nana was removed (removal plots). Removal of B. nana increased ALT by 9% on average late in the growing season, compared with control plots. Differences in ALT correlated well with differences in ground heat flux between the control plots and B. nana removal plots. In the undisturbed control plots, we found an inverse correlation between B. nana cover and late growing season ALT. These results suggest that the expected expansion of deciduous shrubs in the Arctic region, triggered by climate warming, may reduce summer permafrost thaw. Increased shrub growth may thus partially offset further permafrost degradation by future temperature increases. Permafrost models need to include a dynamic vegetation component to accurately predict future permafrost thaw. [ABSTRACT FROM AUTHOR]

Abstract. This article reviews the labelling of peptides that are recognised to be of interest for nuclear medicine or are the subject of ongoing nuclear medicine research. Applications and approaches to the labelling of peptide radiopharmaceuticals are discussed, and drawbacks in their development considered. [ABSTRACT FROM AUTHOR]

Background: Fortaleza (Brazil) is high endemic for coronavirus disease 2019 (COVID-19), tuberculosis (TB) and leprosy. These three diseases share respiratory droplets through coughing or sneezing as the main mode of transmission but differ in incubation time, with COVID-19 having a short and leprosy a long incubation time. Consequently, contacts of a patient are at higher risk of infection and developing these diseases. There might be scope for combined preventive measures, but a better understanding of the geographical distribution and relevant socioeconomic risk factors of the three diseases is needed first. This study aims to describe the geographic distribution of COVID-19, TB and leprosy incidence and to identify common socioeconomic risk factors. Methods: The total number of new cases of COVID-19, TB and leprosy, as well as socioeconomic and demographic variables, were retrieved from official registers. The geographical distribution of COVID-19, TB and leprosy rates per neighbourhood was visualised in Quantum GIS, and spatial autocorrelation was measured with Moran's I in GeoDa. A spatial regression model was applied to understand the association between COVID-19, TB, leprosy rates, and socioeconomic factors. Results: COVID-19 and TB showed a more homogenous distribution, whereas leprosy is located more in the south and west of Fortaleza. One neighbourhood (Pedras) in the southeast was identified as high endemic for all three diseases. Literacy was a socioeconomic risk factor for all three diseases: a high literacy rate increases the risk of COVID-19, and a low literacy rate (i.e., illiteracy) increases the risk of TB and leprosy. In addition, high income was associated with COVID-19, while low income with TB. Conclusions: Despite the similar mode of transmission, COVID-19, TB and leprosy show a different distribution of cases in Fortaleza. In addition, associated risk factors are related to wealth in COVID-19 and to poverty in TB and leprosy. These findings may support policymakers in developing (partially combined) primary and secondary prevention considering the efficient use of resources. [ABSTRACT FROM AUTHOR]

In recent years, many complex oral drug delivery systems have been developed using various polymers in order to achieve better drug targeting and drug absorption in the intestinal tract. Superporous hydrogel (SPH) and SPH composite (SPHC)-based drug delivery systems were also developed for the targeted delivery of peptide drugs into the intestinal tract. In the present study, the retention time of SPHC polymer is studied in man using the scintigraphy technique. To that purpose, SPHC polymers were radiolabelled with Tc-99m and administered orally in an enteric-coated gelatin capsule. The location of the radiolabelled polymer was monitored in five healthy volunteers while the subjects were sitting in front of a large field of view gamma camera. The results showed that enteric-coated gelatin capsules remained in the stomach for 75 to 150 min after oral administration to fasted volunteers and that the SPHC polymers thereafter attached to the upper part of the small intestine for at least 45 to 60 min due to their mechanical fixation properties. No discomfort was observed in any of the volunteers after oral administration of these polymers, which indicates that they are safe to be applied for oral drug delivery systems in man. [Copyright &y& Elsevier]

Aim: Plant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional groups explain a large proportion of trait variation among species. We test whether four commonly used plant functional groups represent variation in six ecologically important plant traits. Location: Tundra biome. Time period: Data collected between 1964 and 2016. Major taxa studied: 295 tundra vascular plant species. Methods: We compiled a database of six plant traits (plant height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, seed mass) for tundra species. We examined the variation in species‐level trait expression explained by four traditional functional groups (evergreen shrubs, deciduous shrubs, graminoids, forbs), and whether variation explained was dependent upon the traits included in analysis. We further compared the explanatory power and species composition of functional groups to alternative classifications generated using post hoc clustering of species‐level traits. Results: Traditional functional groups explained significant differences in trait expression, particularly amongst traits associated with resource economics, which were consistent across sites and at the biome scale. However, functional groups explained 19% of overall trait variation and poorly represented differences in traits associated with plant size. Post hoc classification of species did not correspond well with traditional functional groups, and explained twice as much variation in species‐level trait expression. Main conclusions: Traditional functional groups only coarsely represent variation in well‐measured traits within tundra plant communities, and better explain resource economic traits than size‐related traits. We recommend caution when using functional group approaches to predict tundra vegetation change, or ecosystem functions relating to plant size, such as albedo or carbon storage. We argue that alternative classifications or direct use of specific plant traits could provide new insights for ecological prediction and modelling. [ABSTRACT FROM AUTHOR]