Neurochemical effects of the synthetic ACTH4-9-analog Hoe 427 (Ebiratide) in rat brain

The ACTH4-9-analog Hoe 427 systemically injected in a dose range from 0.01-10 micrograms/kg caused a fall in acetylcholine (ACh) content in different brain areas of the rat. This effect occurred 0.5 hour after a single administration and lasted up to 24 hours. The decrease in ACh content induced by Hoe 427 was more pronounced when the animals were pretreated with dexamethasone (over 7 days 1 mg/kg SC, daily). Coadministration of the choline uptake inhibitor hemicholinium-3 (HC-3) and Hoe 427 potentiated the decrease in ACh content induced by HC-3. In the same dose range Hoe 427 acutely evoked an increase of the activity of the enzyme choline acetyltransferase as well as an elevation of brain cyclic GMP content. These data indicate that Hoe 427 enhances ACh metabolism in rat brain after systemic administration.     

Using heterogeneous data to identify signatures of dengue outbreaks at fine spatio-temporal scales across Brazil

Dengue virus remains a significant public health challenge in Brazil, and seasonal preparation efforts are hindered by variable intra- and interseasonal dynamics. Here, we present a framework for characterizing weekly dengue activity at the Brazilian mesoregion level from 2010–2016 as time series properties that are relevant to forecasting efforts, focusing on outbreak shape, seasonal timing, and pairwise correlations in magnitude and onset. In addition, we use a combination of 18 satellite remote sensing imagery, weather, clinical, mobility, and census data streams and regression methods to identify a parsimonious set of covariates that explain each time series property. The models explained 54% of the variation in outbreak shape, 38% of seasonal onset, 34% of pairwise correlation in outbreak timing, and 11% of pairwise correlation in outbreak magnitude. Regions that have experienced longer periods of drought sensitivity, as captured by the “normalized burn ratio,” experienced less intense outbreaks, while regions with regular fluctuations in relative humidity had less regular seasonal outbreaks. Both the pairwise correlations in outbreak timing and outbreak trend between mesoresgions were best predicted by distance. Our analysis also revealed the presence of distinct geographic clusters where dengue properties tend to be spatially correlated. Forecasting models aimed at predicting the dynamics of dengue activity need to identify the most salient variables capable of contributing to accurate predictions. Our findings show that successful models may need to leverage distinct variables in different locations and be catered to a specific task, such as predicting outbreak magnitude or timing characteristics, to be useful. This advocates in favor of “adaptive models” rather than “one-size-fits-all” models. The results of this study can be applied to improving spatial hierarchical or target-focused forecasting models of dengue activity across Brazil.