Publications by authors named "Z M Zhu"

The HKT-type proteins have been extensively studied and have been shown to play important roles in long-distance Na transport, maintaining ion homoeostasis and improving salt tolerance in plants. However, there have been no reports on the types, characteristics and functions of HKT-type proteins in Limonium bicolor, a recretohalophyte species with the typical salt gland structure. In this study, five LbHKT genes were identified in L.

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Early antiretroviral therapy (ART) initiation is known to limit the establishment of the HIV reservoir, with studies suggesting benefits such as a reduced number of infected cells and a smaller latent reservoir. However, the long-term impact of early ART initiation on the dynamics of the infected cell pool remains unclear, and clinical evidence directly comparing proviral integration site counts between early and late ART initiation is limited. In this study, we used Linear Target Amplification-PCR (LTA-PCR) and Next Generation Sequencing to compare unique integration site (UIS) clonal counts between individuals who initiated ART during acute HIV infection stage (Acute-ART group) and those in the AIDS stage (AIDS-ART group).

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Acute ischemic stroke (AIS) is a dangerous neurological disease associated with an imbalance in Th17/Treg cells and abnormal activation of the Wnt/β-catenin signaling pathway. This study aims to investigate whether inhibition of miR-155 can activate the Wnt/β-catenin signaling pathway to improve Th17/Treg imbalance and provide neuroprotective effects against stroke. We employed a multi-level experimental design.

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Microbe-Assisted Phytoremediation (MAP) is an eco-friendly method for remediating soil contaminated with heavy metals such as cadmium (Cd) and chromium (Cr). This study demonstrates the potential of a king grass-Serratia marcescens strain S27 (KS) co-symbiotic system to enhance heavy metal remediation. The KS symbiosis increased the biomass of king grass by 48 % and enhanced the accumulation of Cd and Cr in the whole plant by 2.

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Spiking neural networks (SNNs) have attracted significant interest in the development of brain-inspired computing systems due to their energy efficiency and similarities to biological information processing. In contrast to continuous-valued artificial neural networks, which produce results in a single step, SNNs require multiple steps during inference to achieve a desired accuracy level, resulting in a burden in real-time response and energy efficiency. Inspired by the tradeoff between speed and accuracy in human and animal decision-making processes, which exhibit correlations among reaction times, task complexity, and decision confidence, an inquiry emerges regarding how an SNN model can benefit by implementing these attributes.

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