1,271 research outputs found

    Impacts of the Madden-Julian oscillation on Australian rainfall and circulation

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    Impacts of the Madden¿Julian oscillation (MJO) on Australian rainfall and circulation are examined during all four seasons. The authors examine circulation anomalies and a number of different rainfall metrics, each composited contemporaneously for eight MJO phases derived from the real-time multivariate MJO index. Multiple rainfall metrics are examined to allow for greater relevance of the information for applications. The greatest rainfall impact of the MJO occurs in northern Australia in (austral) summer, although in every season rainfall impacts of various magnitude are found in most locations, associated with corresponding circulation anomalies. In northern Australia in all seasons except winter, the rainfall impact is explained by the direct influence of the MJO's tropical convective anomalies, while in winter a weaker and more localized signal in northern Australia appears to result from the modulation of the trade winds as they impinge upon the eastern coasts, especially in the northeast. In extratropical Australia, on the other hand, the occurrence of enhanced (suppressed) rainfall appears to result from induced upward (downward) motion within remotely forced extratropical lows (highs), and from anomalous low-level northerly (southerly) winds that transport moisture from the tropics. Induction of extratropical rainfall anomalies by remotely forced lows and highs appears to operate mostly in winter, whereas anomalous meridional moisture transport appears to operate mainly in the summer, autumn, and to some extent in the sprin

    Differential Interleukin-2 Transcription Kinetics Render Mouse but Not Human T Cells Vulnerable to Splicing Inhibition Early after Activation

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    T cells are nodal players in the adaptive immune response against pathogens and malignant cells. Alternative splicing plays a crucial role in T cell activation, which is analyzed mainly at later time points upon stimulation. Here we have discovered a 2-h time window early after stimulation where optimal splicing efficiency or, more generally, gene expression efficiency is crucial for successful T cell activation. Reducing the splicing efficiency at 4 to 6 h poststimulation significantly impaired murine T cell activation, which was dependent on the expression dynamics of the Egr1-Nab2-interleukin-2 (IL-2) pathway. This time window overlaps the time of peak IL-2 de novo transcription, which, we suggest, represents a permissive time window in which decreased splicing (or transcription) efficiency reduces mature IL-2 production, thereby hampering murine T cell activation. Notably, the distinct expression kinetics of the Egr1-Nab2-IL-2 pathway between mouse and human render human T cells refractory to this vulnerability. We propose that the rational temporal modulation of splicing or transcription during peak de novo expression of key effectors can be used to fine-tune stimulation-dependent biological outcomes. Our data also show that critical consideration is required when extrapolating mouse data to the human system in basic and translational research

    Probabilistic methods for seasonal forecasting in a changing climate: Cox-type regression models.

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    For climate risk management, cumulative distribution functions (CDFs) are an important source of information. They are ideally suited to compare probabilistic forecasts of primary (e.g. rainfall) or secondary data (e.g. crop yields). Summarised as CDFs, such forecasts allow an easy quantitative assessment of possible, alternative actions. Although the degree of uncertainty associated with CDF estimation could influence decisions, such information is rarely provided. Hence, we propose Cox-type regression models (CRMs) as a statistical framework for making inferences on CDFs in climate science. CRMs were designed for modelling probability distributions rather than just mean or median values. This makes the approach appealing for risk assessments where probabilities of extremes are often more informative than central tendency measures. CRMs are semi-parametric approaches originally designed for modelling risks arising from time-to-event data. Here we extend this original concept beyond time-dependent measures to other variables of interest. We also provide tools for estimating CDFs and surrounding uncertainty envelopes from empirical data. These statistical techniques intrinsically account for non-stationarities in time series that might be the result of climate change. This feature makes CRMs attractive candidates to investigate the feasibility of developing rigorous global circulation model (GCM)-CRM interfaces for provision of user-relevant forecasts. To demonstrate the applicability of CRMs, we present two examples for El Ni ? no/Southern Oscillation (ENSO)-based forecasts: the onset date of the wet season (Cairns, Australia) and total wet season rainfall (Quixeramobim, Brazil). This study emphasises the methodological aspects of CRMs rather than discussing merits or limitations of the ENSO-based predictors

    Western corn rootworm pyrethroid resistance confirmed by aerial application simulations of commercial insecticides

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    The western corn rootworm (Diabrotica virgifera virgifera LeConte) (WCR) is a major insect pest of corn (Zea mays L.) in the United States (US) and is highly adaptable to multiple management tactics. A low level of WCR field-evolved resistance to pyrethroid insecticides has been confirmed in the US western Corn Belt by laboratory dose-response bioassays. Further investigation has identified detoxification enzymes as a potential part of the WCR resistance mechanism, which could affect the performance of insecticides that are structurally related to pyrethroids, such as organophosphates. Thus, the responses of pyrethroid-resistant and -susceptible WCR populations to the commonly used pyrethroid bifenthrin and organophosphate dimethoate were compared in active ingredient bioassays. Results revealed a relatively low level of WCR resistance to both active ingredients. Therefore, a simulated aerial application bioassay technique was developed to evaluate how the estimated resistance levels would affect performance of registered rates of formulated products. The simulated aerial application technique confirmed pyrethroid resistance to formulated rates of bifenthrin whereas formulated dimethoate provided optimal control. Results suggest that the relationship between levels of resistance observed in dose-response bioassays and actual efficacy of formulated product needs to be further explored to understand the practical implications of resistance
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