Publications by authors named "Z M Qi"

R-loops are critical structures that play pivotal roles in regulating genomic stability and modulating gene expression. This study investigates the interactions between the 5-methylcytosine (mC) methyltransferase NOP2/Sun RNA methyltransferase 2 (NSUN2) and R-loops in the transcriptional dynamics and damage repair process of bladder cancer (BCa) cells. We observed markedly elevated levels of R-loops in BCa cells relative to normal urothelial cells.

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Surface electromyography (sEMG) signals reflect the local electrical activity of muscle fibers and the synergistic action of the overall muscle group, making them useful for gesture control of myoelectric manipulators. In recent years, deep learning methods have increasingly been applied to sEMG gesture recognition due to their powerful automatic feature extraction capabilities. sEMG signals contain rich local details and global patterns, but single-scale convolutional networks are limited in their ability to capture both comprehensively, which restricts model performance.

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Objective: Qingdai (QD) is a traditional Chinese medicine (TCM) commonly used in clinical practice to treat acute lung injury/acute respiratory distress syndrome (ALI/ARDS). However, the mechanisms underlying the effects of QD remain not fully understood. This investigation demonstrated QD alleviated LPS-induced ALI in mice and exerted anti-inflammatory effects by inhibiting the JAK2/STAT3 signaling pathway.

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Ultra-flexible nanoliposomes (UNL) coated with sodium cholate were fabricated using the thin film hydration technique to encapsulate oleocanthal (OLEO), oleacein (OLEA), oleuropein (OLEU), and hydroxytyrosol (HT) for improving their stability and bioactivity. Their physicochemical properties were further validated through DLS, FTIR, XRD, TGA, and DSC analyses. Negative-staining TEM imaging revealed well-dispersed UNL with laminar vesicles inside.

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Objective: Although online health communities offer a new approach to patient interaction, the help-seeking behaviors of cancer patients within these platforms remain unexplored. This study aims to identify the determinants influencing online help-seeking behaviors among cancer patients.

Method: Based on motivation theory, we proposed six hypotheses and developed a research model.

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