Local Increase of Arginase Activity in Lesions of Patients with Cutaneous Leishmaniasis in Ethiopia

The leishmaniases are a complex of diseases caused by Leishmania parasites. Currently, the diseases affect an estimated 12 million people in 88 countries, and approximately 350 million more people are at risk. The leishmaniases belong to the most neglected tropical diseases, affecting the poorest populations, for whom access to diagnosis and effective treatment are often not available. Leishmania parasites infect cells of the immune system called macrophages, which have the capacity to eliminate the intracellular parasites when they receive the appropriate signals from other cells of the immune system. In nonhealing persistent leishmaniasis, lymphocytes are unable to transmit the signals to macrophages required to kill the intracellular parasites. The local upregulation of the enzyme arginase has been shown to impair lymphocyte effector functions at the site of pathology. In this study, we tested the activity of this enzyme in skin lesions of patients presenting with localized cutaneous leishmaniasis. Our results show that arginase is highly upregulated in these lesions. This increase in arginase activity coincides with lower expression of a signalling molecule in lymphocytes, which is essential for efficient activation of these cells. These results suggest that increased arginase expression in the localized cutaneous lesions might contribute to persistent disease in patients presenting with cutaneous leishmaniasis

The AgMIP Coordinated Climate-Crop Modeling Project (C3MP): Methods and Protocols

Climate change is expected to alter a multitude of factors important to agricultural systems, including pests, diseases, weeds, extreme climate events, water resources, soil degradation, and socio-economic pressures. Changes to carbon dioxide concentration ([CO2]), temperature, andwater (CTW) will be the primary drivers of change in crop growth and agricultural systems. Therefore, establishing the CTW-change sensitivity of crop yields is an urgent research need and warrants diverse methods of investigation. Crop models provide a biophysical, process-based tool to investigate crop responses across varying environmental conditions and farm management techniques, and have been applied in climate impact assessment by using a variety of methods (White et al., 2011, and references therein). However, there is a significant amount of divergence between various crop models’ responses to CTW changes (R¨otter et al., 2011). While the application of a site-based crop model is relatively simple, the coordination of such agricultural impact assessments on larger scales requires consistent and timely contributions from a large number of crop modelers, each time a new global climate model (GCM) scenario or downscaling technique is created. A coordinated, global effort to rapidly examine CTW sensitivity across multiple crops, crop models, and sites is needed to aid model development and enhance the assessment of climate impacts (Deser et al., 2012)..

Meaning in life: Clinical relevance and predictive power

The clinical relevance of the meaning in life construct is examined by evaluating its ability to predict patients' general and psychological well-being and their posttreatment functioning. Evidence is obtained for the notion that meaning in Life (a) would affect both positive and negative aspects of well-being, (b) that it would be related to improvement during psychotherapy, and (c) that it would predict the outcome of psychotherapy, independently of patients' pre-treatment levels of wellbeing. The findings not only support the clinical relevance of the meaning in life concept, but they also favour the construct validity of the Life Regard Index, an instrument that was designed to measure the relevant construct. It is concluded that the neglected meaning in life issue deserves greater therapeutic and scientific consideration. Clinical implications and suggestions for future research are discussed

A generalized computer vision approach to mapping crop fields in heterogeneous agricultural landscapes

Smallholder farms dominate in many parts of the world, particularly Sub-Saharan Africa. These systems are characterized by small, heterogeneous, and often indistinct field patterns, requiring a specialized methodology to map agricultural land cover. Using a variety of sites in South Africa, we present a new approach to mapping agricultural fields, based on efficient extraction of a vast set of simple, highly correlated, and interdependent features, followed by a random forest classifier. We achieved similar high performance across agricultural types, including the spectrally indistinct smallholder fields as well as the more easily distinguishable commercial fields, and demonstrated the ability to generalize performance across large geographic areas. In sensitivity analyses, we determined multi-temporal information provided greater gains in performance than the addition of multi-spectral bands available in DigitalGlobe Worldview-2 imagery

Spatial and temporal variations in cervical cancer screening participation among indigenous and non-indigenous women, Queensland, Australia, 2008–2017

Background: Cervical cancer incidence and mortality have declined in Australia since the implementation of a national cervical screening program in 1991, however, disparities in both measures between Indigenous and non-Indigenous women remain. We describe spatial and temporal changes in Pap test participation rates by Indigenous status for Queensland (Australia). Analyses were done in the context of renewed screening program in December 2017. Methods: Population-based study 2,132,925 Queensland female residents, aged 20−69 years who underwent cervical screening from 2008 to December 2017; 47,136 were identified as Indigenous through linkage to hospital records. Bayesian spatial models were used to generate smoothed estimates of participation across 528 small areas during 2008−2012 and 2013−2017 compared to the overall state average (2008–2017). Results are presented as thematic maps and graphs showing the associated uncertainty of the estimates. Results: Overall screening participation decreased over time for both Indigenous and non-Indigenous women. Strong spatial patterns were evident in five-year participation for both groups. Indigenous women had significantly lower participation than the Queensland average for ≥ 88 % of areas during both reporting periods whereas corresponding estimates were lower than average for <30 % of areas among non-Indigenous women. Disparities by Indigenous status persisted over time and remained across broader geographical groups of accessibility and area disadvantage. Conclusions: Cervical cancer burden in Australia can only be reduced through concentrated efforts on identifying and addressing key drivers of the continuing disparities in screening participation. Achieving equitable screening participation for all women especially Indigenous women requires community engagement and localised interventions