IL-18 contributes to susceptibility to Leishmania amazonensis infection by macrophage-independent mechanisms

AbstractWe evaluated the role of IL-18 during Leishmania amazonensis infection in C57BL/6 mice, using IL-18KO mice. We showed that IL-18 is involved in susceptibility to L. amazonensis, since IL-18KO mice presented reduced lesions and parasite loads. Because macrophages are the host cells of the parasite, we investigated if macrophages were involved in IL-18-mediated susceptibility to L. amazonensis. We showed that macrophages obtained from WT or IL-18KO responded similarly to L. amazonensis infection. Moreover, we showed that C57BL/6 macrophages do not respond to IL-18, since they do not express IL-18R. Therefore, macrophages are not involved in IL-18-mediated susceptibility to L. amazonensis

Early and Late Pathogenic Events of Newborn Mice Encephalitis Experimentally Induced by Itacaiunas and Curionópolis Bracorhabdoviruses Infection

In previous reports we proposed a new genus for Rhabdoviridae and described neurotropic preference and gross neuropathology in newborn albino Swiss mice after Curionopolis and Itacaiunas infections. In the present report a time-course study of experimental encephalitis induced by Itacaiunas and Curionopolis virus was conducted both in vivo and in vitro to investigate cellular targets and the sequence of neuroinvasion. We also investigate, after intranasal inoculation, clinical signs, histopathology and apoptosis in correlation with viral immunolabeling at different time points. Curionopolis and Itacaiunas viral antigens were first detected in the parenchyma of olfactory pathways at 2 and 3 days post-inoculation (dpi) and the first clinical signs were observed at 4 and 8 dpi, respectively. After Curionopolis infection, the mortality rate was 100% between 5 and 6 dpi, and 35% between 8 and 15 dpi after Itacaiunas infection. We identified CNS mice cell types both in vivo and in vitro and the temporal sequence of neuroanatomical olfactory areas infected by Itacaiunas and Curionopolis virus. Distinct virulences were reflected in the neuropathological changes including TUNEL immunolabeling and cytopathic effects, more intense and precocious after intracerebral or in vitro inoculations of Curionopolis than after Itacaiunas virus. In vitro studies revealed neuronal but not astrocyte or microglial cytopathic effects at 2 dpi, with monolayer destruction occurring at 5 and 7 dpi with Curionopolis and Itacaiunas virus, respectively. Ultrastructural changes included virus budding associated with interstitial and perivascular edema, endothelial hypertrophy, a reduced and/or collapsed small vessel luminal area, thickening of the capillary basement membrane, and presence of phagocytosed apoptotic bodies. Glial cells with viral budding similar to oligodendrocytes were infected with Itacaiunas virus but not with Curionopolis virus. Thus, Curionopolis and Itacaiunas viruses share many pathological and clinical features present in other rhabdoviruses but distinct virulence and glial targets in newborn albino Swiss mice brain

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio