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Restricted genetic diversity can supply only a limited number of elite genes for modern plant cultivation and transgenesis. In this study, we demonstrate that rational design enables the engineering of geranylgeranyl diphosphate synthase (NtGGPPS), an enzyme of the methylerythritol phosphate pathway (MEP) in the model plant Nicotiana tabacum. As the crucial bottleneck in carotenoid biosynthesis, NtGGPPS1 interacts with phytoene synthase (NtPSY1) to channel GGPP into the production of carotenoids. Loss of this enzyme in the ntggpps1 mutant leads to decreased carotenoid accumulation. With the aim of enhancing NtGGPPS1 activity, we undertook structure-guided rational redesign of its substrate binding pocket in combination with sequence alignment. The activity of the designed NtGGPPS1 (a pentuple mutant of five sites V154A/I161L/F218Y/I209S/V233E, d-NtGGPPS1) was measured by a high-throughput colorimetric assay. d-NtGGPPS1 exhibited significantly higher conversion of IPP and each co-substrate (DMAPP ~1995.5-fold, GPP ~25.9-fold, and FPP ~16.7-fold) for GGPP synthesis compared with wild-type NtGGPPS1. Importantly, the transient and stable expression of d-NtGGPPS1 in the ntggpps1 mutant increased carotenoid levels in leaves, improved photosynthetic efficiency, and increased biomass relative to NtGGPPS1. These findings provide a firm basis for the engineering of GGPPS and will facilitate the development of quality and yield traits. Our results open the door for the structure-guided rational design of elite genes in higher plants.

Purpose Previous studies have indicated that the global topology of the brain functional network in patients with major depressive disorder (MDD) differs from that of those with normal controls (NCs). However, the relationship between an altered global topology and the response to antidepressants remains unclear. Here, we investigated whether differences in global topology affect the efficacy of antidepressants in MDD patients. Methods 108 MDD patients and 61 NCs were recruited. A magnetic resonance imaging (MRI) scan was performed at the baseline, and the Hamilton Depression Scale-24 (HAMD-24) was assessed at baseline and after 2 and 8 weeks of antidepressant treatment. Seven global topological parameters of the brain functional network were measured and compared between groups. A correlation analysis was performed to identify the relationships between global topological parameters and antidepressant efficacy. Results The brain networks of MDD patients and NCs were both small-world networks. The clustering coefficient (Cp) and local efficiency (Eloc) were significantly smaller in MDD patients compared with those in NCs. The characteristic path length (Lp) were negatively correlated with the 8-week reductive rate of HAMD-24 in the MDD group. Conclusion The present research found that the brain functional network of MDD patients still had a small-world organization but with a lower Cp and Eloc than the NCs. In addition, the brain network global topology might have an impact on the antidepressant response and thus had the potential to become a treatment predictor of MDD.

The pathophysiology of major depressive disorder (MDD) has been explored to be highly associated with the dysfunctional integration of brain networks. It is therefore imperative to explore neuroimaging biomarkers to aid diagnosis and treatment. In this study, we developed a spatiotemporal graph convolutional network (STGCN) framework to learn discriminative features from functional connectivity for automatic diagnosis and treatment response prediction of MDD. Briefly, dynamic functional networks were first obtained from the resting‐state fMRI with the sliding temporal window method. Secondly, a novel STGCN approach was proposed by introducing the modules of spatial graph attention convolution (SGAC) and temporal fusion. A novel SGAC was proposed to improve the feature learning ability and special anatomy prior guided pooling was developed to enable the feature dimension reduction. A temporal fusion module was proposed to capture the dynamic features of functional connectivity between adjacent sliding windows. Finally, the STGCN proposed approach was utilized to the tasks of diagnosis and antidepressant treatment response prediction for MDD. Performances of the framework were comprehensively examined with large cohorts of clinical data, which demonstrated its effectiveness in classifying MDD patients and predicting the treatment response. The sound performance suggests the potential of the STGCN for the clinical use in diagnosis and treatment prediction., In this study, we developed a spatiotemporal graph convolutional network framework to learn discriminative features from functional connectivity for automatic diagnosis and treatment response prediction of major depressive disorder. Performances of the framework were comprehensively examined with large cohorts of clinical data, which demonstrated its effectiveness in classifying major depressive disorder patients and predicting the treatment response.

Background:Lycopene epsilon-cyclase (ε-LCY) is a key enzyme in the carotenoid biosynthetic pathway (CBP) of higher plants. In previous work, we cloned two Ntε-LCY genes from allotetraploid tobacco (Nicotiana tabacum), Ntε-LCY2 and Ntε-LCY1, and demonstrated the overall effect of Ntε-LCY genes on carotenoid biosynthesis and stress resistance. However, their genetic and functional characteristics require further research in polyploid plants.Results: Here, we used CRISPR/Cas9 to obtain Ntε-LCY2 and Ntε-LCY1 mutants in allotetraploid N.tabacum K326. Ntε-LCY2 and Ntε-LCY1 had similar promoter cis-acting elements, including light-responsive elements. The Ntε-LCY genes were expressed in roots, stems, leaves, flowers, and young fruit, and their highest expression levels were found in leaves. Ntε-LCY2 and Ntε-LCY1 genes responded differently to normal light and high light stress. Both the Ntε-LCY2 and the Ntε-LCY1 mutants had a more rapid leaf growth rate, especially ntε-lcy2-1. The expression levels of CBP genes were increased in the ntε-lcy mutants, and their total carotenoid content was higher. Under both normal light and high light stress, the ntε-lcy mutants had higher photosynthetic capacities and heat dissipation levels than the wild type, and this was especially true of ntε-lcy2-1. The reactive oxygen species content was lower in leaves of the ntε-lcy mutants.Conclusion: In summary, the expression patterns and biological functions of the Ntε-LCY genes Ntε-LCY1 and Ntε-LCY2 differed in several respects. The mutation of Ntε-LCY2 was associated with a greater increase in the content of chlorophyll and various carotenoid components, and it enhanced the stress resistance of tobacco plants under high light.

Ni-MOF derivatives are fabricated through calcining in air at different temperatures without leading to original structure collapsing. The results indicate that the obtained NiO has fine electrochemical performance at the calcining temperature of 350 °C, which possesses a reversible specific capacitance of 485 F g−1 at the current of 1 A g−1, and nearly 87% retention after 5000 cycles. The superior electrochemical properties of Ni-MOF derived hexagonal flaky NiO is attributed to the enlarged surfaces and stable structure after calcination.

A modern GPU aims to simultaneously execute more warps for higher Thread-Level Parallelism (TLP) and performance. When generating many memory requests, however, warps contend for limited cache space and thrash cache, which in turn severely degrades performance. To reduce such cache thrashing, we may adopt cache locality-aware warp scheduling which gives higher execution priority to warps with higher potential of data locality. However, we observe that warps with high potential of data locality often incurs far more cache thrashing or interference than warps with low potential of data locality. Consequently, cache locality-aware warp scheduling may undesirably increase cache interference and/or unnecessarily decrease TLP. In this paper, we propose Cache Interference-Aware throughput-Oriented (CIAO) on-chip memory architecture and warp scheduling which exploit unused shared memory space and take insight opposite to cache locality-aware warp scheduling. Specifically, CIAO on-chip memory architecture can adaptively redirect memory requests of severely interfering warps to unused shared memory space to isolate memory requests of these interfering warps from those of interfered warps. If these interfering warps still incur severe cache interference, CIAO warp scheduling then begins to selectively throttle execution of these interfering warps. Our experiment shows that CIAO can offer 54% higher performance than prior cache locality-aware scheduling at a small chip cost., IPDPS 2018

Metal-organic frameworks (MOFs), serving as a promising electrode material in the supercapacitors, have attracted tremendous interests in recent years. Here, through modifying the molar ratio of the Ni2+ and Co2+, we have successfully fabricated Ni-MOF and Ni/Co-MOF by a facile hydrothermal method. The Ni/Co-MOF with a dandelion-like hollow structure shows an excellent specific capacitance of 758 F g−1 at 1 A g−1 in the three-electrode system. Comparing with Ni-MOF, the obtained Ni/Co-MOF has a better rate capacitance (89% retention at 10 A g−1) and cycling life (75% retention after 5000 circulations). Besides, the assembled asymmetric supercapacitor based on Ni/Co-MOF and active carbon exhibits a high specific energy density of 20.9 W h kg−1 at the power density of 800 W kg−1. All these results demonstrate that the mixed-metal strategy is an effective way to optimize the morphology and improve the electrochemical property of the MOFs.

A series of nickel sulfides derived from the hexagonal Ni-MOF are vulcanized through adjusting the hydrothermal time and the thiourea concentration. Among all the obtained nickel sulfides, one sample Ni-S2-3, which inherits the Ni-MOF’s morphology, shows the best electrochemical performance with a remarkable specific capacitance of 1128[Formula: see text]Fg[Formula: see text] at 1[Formula: see text]Ag[Formula: see text], a rate capacitance of 50% and a long cycle life of 74% retention after 5000 cycles. Furthermore, the asymmetrical supercapacitors (SCs) based on Ni-S2-3//AC exhibit a good supercapacitive performance with a maximum power density of 16.3[Formula: see text]Wh kg[Formula: see text] at a power density of 800[Formula: see text]Wkg[Formula: see text]. All these results indicate that vulcanizing Ni-MOF is an effective way to fabricate a superior electrode material with excellent electrochemical performance for SCs.

As the popularity of NAND flash expands in arenas from embedded systems to high-performance computing, a high-fidelity understanding of its specific properties becomes increasingly important. Further, with the increasing trend toward multiple-die, multiple-plane architectures and high-speed interfaces, flash memory systems are expected to continue to scale and cheapen, resulting in their broader proliferation. However, when designing NAND-based devices, making decisions about the optimal system configuration is nontrivial, because flash is sensitive to a number of parameters and suffers from inherent latency variations, and no available tools suffice for studying these nuances. The parameters include the architectures, such as multidie and multiplane, diverse node technologies, bit densities, and cell reliabilities. Therefore, we introduce NANDFlashSim, a high-fidelity, latency-variation-aware, and highly configurable NAND-flash simulator, which implements a detailed timing model for 16 state-of-the-art NAND operations. Using NANDFlashSim, we notably discover the following. First, regardless of the operation, reads fail to leverage internal parallelism. Second, MLC provides lower I/O bus contention than SLC, but contention becomes a serious problem as the number of dies increases. Third, many-die architectures outperform many-plane architectures for disk-friendly workloads. Finally, employing a high-performance I/O bus or an increased page size does not enhance energy savings. Our simulator is available at http://nfs.camelab.org.