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Synaptic changes are closely associated with cognitive deficits. In addition, testosterone (T) is known to exert regulative effects on synaptic plasticity. T may improve cognitive deficits in Alzheimer's disease (AD) patients, but the underlying mechanisms of androgenic action on cognitive performance remain unclear. The aim of this study was thus to examine the protective mechanism attributed to T on cognitive performance in an AD senescence, accelerated mouse prone 8 (SAMP8) animal model. Using Golgi staining to quantify the dendritic spine density in hippocampal CA1 region, molecular biomarkers of synapse function were analyzed using immunohistochemistry and western blot. T significantly increased the dendritic spine density in hippocampal CA1 region, while flutamide (F) inhibited these T-mediated effects. Immunohistochemistry and western blot analysis showed that the expression levels of brain derived neurotrophic factor (BDNF), postsynaptic density 95 (PSD-95), and p-cyclic-AMP response element binding protein (CREB)/CREB levels were significantly elevated in the T group, but F reduced the T-induced effects in these biomarkers to control levels. There were no significant differences in the expression levels of PSD-95, BDNF, and p-CREB/CREB between C and F. These findings indicate that the effects of T on improvement in synaptic plasticity were mediated via androgen receptor (AR). It is conceivable that new treatments targeted toward preventing synaptic pathology in AD may involve the use of androgen-acting drugs.

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Airborne hyperspectral images are used for crop identification with a high classification accuracy because of their high spectral resolution, spatial resolution, and signal-to-noise ratio (SNR). However, the tradeoffs between the three core parameters of a hyperspectral imager (SNR, spatial resolution, and spectral resolution) should be considered for designing an efficient imaging system. Only a few reported studies on the analysis of the impact of SNR on identification accuracy are available. Further, the tradeoffs and mutual interactions among these parameters are rarely considered. In this empirical study, our aim was to understand the relationship among the core parameters and their effects on crop identification accuracy by analyzing the tradeoffs and mutual interactions among these parameters. We analyzed the hyperspectral images of a typical plain agricultural area in Xiongan, China, acquired by the newly developed sensor airborne multimodular imaging spectrometer