10,446 research outputs found

    A CRY-BIC negative-feedback circuitry regulating blue light sensitivity of Arabidopsis.

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    Cryptochromes are blue light receptors that regulate various light responses in plants. Arabidopsis cryptochrome 1 (CRY1) and cryptochrome 2 (CRY2) mediate blue light inhibition of hypocotyl elongation and long-day (LD) promotion of floral initiation. It has been reported recently that two negative regulators of Arabidopsis cryptochromes, Blue light Inhibitors of Cryptochromes 1 and 2 (BIC1 and BIC2), inhibit cryptochrome function by blocking blue light-dependent cryptochrome dimerization. However, it remained unclear how cryptochromes regulate the BIC gene activity. Here we show that cryptochromes mediate light activation of transcription of the BIC genes, by suppressing the activity of CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1), resulting in activation of the transcription activator ELONGATED HYPOCOTYL 5 (HY5) that is associated with chromatins of the BIC promoters. These results demonstrate a CRY-BIC negative-feedback circuitry that regulates the activity of each other. Surprisingly, phytochromes also mediate light activation of BIC transcription, suggesting a novel photoreceptor co-action mechanism to sustain blue light sensitivity of plants under the broad spectra of solar radiation in nature

    Effects of Temperature on Development and Voltinism of Chaetodactylus krombeini (Acari: Chaetodactylidae): Implications for Climate Change Impacts

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    Temperature plays an important role in the growth and development of arthropods, and thus the current trend of climate change will alter their biology and species distribution. We used Chaetodactylus krombeini (Acari: Chaetodactylidae), a cleptoparasitic mite associated with Osmia bees (Hymenoptera: Megachilidae), as a model organism to investigate how temperature affects the development and voltinism of C. krombeini in the eastern United States. The effects of temperature on the stage-specific development of C. krombeini were determined at seven constant temperatures (16.1, 20.2, 24.1, 27.5, 30.0, 32.4 and 37.8°C). Parameters for stage-specific development, such as threshold temperatures and thermal constant, were determined by using empirical models. Results of this study showed that C. krombeini eggs developed successfully to adult at all temperatures tested except 37.8°C. The nonlinear and linear empirical models were applied to describe quantitatively the relationship between temperature and development of each C. krombeini stage. The nonlinear Lactin model estimated optimal temperatures as 31.4, 32.9, 32.6 and 32.5°C for egg, larva, nymph, and egg to adult, respectively. In the linear model, the lower threshold temperatures were estimated to be 9.9, 14.7, 13.0 and 12.4°C for egg, larva, nymph, and egg to adult, respectively. The thermal constant for each stage completion were 61.5, 28.1, 64.8 and 171.1 degree days for egg, larva, nymph, and egg to adult, respectively. Under the future climate scenarios, the number of generations (i.e., voltinism) would increase more likely by 1.5 to 2.0 times by the year of 2100 according to simulation. The findings herein firstly provided comprehensive data on thermal development of C. krombeini and implications for the management of C. krombeini populations under global warming were discussed

    DNS study of a pipe flow following a step increase in flow rate

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    Direct numerical simulation (DNS) is conducted to study the transient flow in a pipe following a near-step increase of flow rate from an initial turbulent flow. The results are compared with those of the transient flow in a channel reported in He and Seddighi (2013). It is shown that the flow again exhibits a laminar–turbulent transition, similar to that in a channel. The behaviours of the flow in a pipe and a channel are the same in the near-wall region, but there are significant differences in the centre of the flow. The correlation between the critical Reynolds number and free stream turbulence previously established for a channel flow has been shown to be applicable to the pipe flow. The responses of turbulent viscosity, vorticity Reynolds number, and budget terms are analysed. Some significant differences have been found to exist between the developments of the vorticity Reynolds number in the pipe and channel flows
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