Anti-oxidative activities of sorghum, foxtail millet and proso millet extracts

In this study, sorghum, foxtail millet and proso millet extracts were evaluated by various in vitro antioxidant assays, including 1,1-diphenyl-2-picryl-hydrazyl (DPPH) free radical scavenging activity, reducing power by Fe3+- Fe2+ transformation, and anti-lipid peroxidative activity by ferric thiocyanate. The sorghum extract contained high amount of phenolic compounds as well as a high level of antioxidant activity compared with foxtail millet and proso millet extracts. In addition, among the sorghum cultivar, me-susu (Sorghum dochna var. technicum, Snowden) extracts exhibited high levels of free radical scavenging activity, anti-oxidant capacity and anti-lipid peroxidative activity compared with - tocopherol. Taken together, these findings suggest that me-susu extracts can be considered good sources of natural anti-oxidants

LC–MS-based absolute metabolite quantification:Application to metabolic flux measurement in trypanosomes

Human African trypanosomiasis is a neglected tropical disease caused by the protozoan parasite, Trypanosoma brucei. In the mammalian bloodstream, the trypanosome’s metabolism differs significantly from that of its host. For example, the parasite relies exclusively on glycolysis for energy source. Recently, computational and mathematical models of trypanosome metabolism have been generated to assist in understanding the parasite metabolism with the aim of facilitating drug development. Optimisation of these models requires quantitative information, including metabolite concentrations and/or metabolic fluxes that have been hitherto unavailable on a large scale. Here, we have implemented an LC–MS-based method that allows large scale quantification of metabolite levels by using U-13C-labelled E. coli extracts as internal standards. Known amounts of labelled E. coli extract were added into the parasite samples, as well as calibration standards, and used to obtain calibration curves enabling us to convert intensities into concentrations. This method allowed us to reliably quantify the changes of 43 intracellular metabolites and 32 extracellular metabolites in the medium over time. Based on the absolute quantification, we were able to compute consumption and production fluxes. These quantitative data can now be used to optimise computational models of parasite metabolism

Perturbing Dynamin Reveals Potent Effects on the Drosophila Circadian Clock

BACKGROUND: Transcriptional feedback loops are central to circadian clock function. However, the role of neural activity and membrane events in molecular rhythms in the fruit fly Drosophila is unclear. To address this question, we expressed a temperature-sensitive, dominant negative allele of the fly homolog of dynamin called shibire(ts1) (shi(ts1)), an active component in membrane vesicle scission. PRINCIPAL FINDINGS: Broad expression in clock cells resulted in unexpectedly long, robust periods (>28 hours) comparable to perturbation of core clock components, suggesting an unappreciated role of membrane dynamics in setting period. Expression in the pacemaker lateral ventral neurons (LNv) was necessary and sufficient for this effect. Manipulation of other endocytic components exacerbated shi(ts1)'s behavioral effects, suggesting its mechanism is specific to endocytic regulation. PKA overexpression rescued period effects suggesting shi(ts1) may downregulate PKA pathways. Levels of the clock component PERIOD were reduced in the shi(ts1)-expressing pacemaker small LNv of flies held at a fully restrictive temperature (29 degrees C). Less restrictive conditions (25 degrees C) delayed cycling proportional to observed behavioral changes. Levels of the neuropeptide PIGMENT-DISPERSING FACTOR (PDF), the only known LNv neurotransmitter, were also reduced, but PERIOD cycling was still delayed in flies lacking PDF, implicating a PDF-independent process. Further, shi(ts1) expression in the eye also results in reduced PER protein and per and vri transcript levels, suggesting that shibire-dependent signaling extends to peripheral clocks. The level of nuclear CLK, transcriptional activator of many core clock genes, is also reduced in shi(ts1) flies, and Clk overexpression suppresses the period-altering effects of shi(ts1). CONCLUSIONS: We propose that membrane protein turnover through endocytic regulation of PKA pathways modulates the core clock by altering CLK levels and/or activity. These results suggest an important role for membrane scission in setting circadian period

Neuropeptide Receptor Transcriptome Reveals Unidentified Neuroendocrine Pathways

Neuropeptides are an important class of molecules involved in diverse aspects of metazoan development and homeostasis. Insects are ideal model systems to investigate neuropeptide functions, and the major focus of insect neuropeptide research in the last decade has been on the identification of their receptors. Despite these vigorous efforts, receptors for some key neuropeptides in insect development such as prothoracicotropic hormone, eclosion hormone and allatotropin (AT), remain undefined. In this paper, we report the comprehensive cloning of neuropeptide G protein-coupled receptors from the silkworm, Bombyx mori, and systematic analyses of their expression. Based on the expression patterns of orphan receptors, we identified the long-sought receptor for AT, which is thought to stimulate juvenile hormone biosynthesis in the corpora allata (CA). Surprisingly, however, the AT receptor was not highly expressed in the CA, but instead was predominantly transcribed in the corpora cardiaca (CC), an organ adjacent to the CA. Indeed, by using a reverse-physiological approach, we purified and characterized novel allatoregulatory peptides produced in AT receptor-expressing CC cells, which may indirectly mediate AT activity on the CA. All of the above findings confirm the effectiveness of a systematic analysis of the receptor transcriptome, not only in characterizing orphan receptors, but also in identifying novel players and hidden mechanisms in important biological processes. This work illustrates how using a combinatorial approach employing bioinformatic, molecular, biochemical and physiological methods can help solve recalcitrant problems in neuropeptide research

ICAR: endoscopic skull‐base surgery

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An open challenge to advance probabilistic forecasting for dengue epidemics

This is the final version. Available on open access from the National Academy of Sciences via the DOI in this recordData Availability: Data deposition: The data are available at https://github.com/cdcepi/dengue-forecasting-project-2015 (DOI: https://doi.org/10.5281/zenodo.3519270).A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue