Publications by authors named "Cuidie Ma"

Introduction: Early diagnosis is crucial for improving the prognosis of patients with gastric cancer (GC). However, the currently used biomarkers for diagnosing GC have limited sensitivity and specificity. This study aimed to develop a novel diagnostic model based on miRNAs from glycosylated extracellular vesicles and evaluate its effectiveness in diagnosing gastric cancer.

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Hepatocellular carcinoma (HCC) is a prevalent and aggressive cancer that presents significant challenges for early detection. This study introduces the GlyExo-Capture method for isolating fucosylated extracellular vesicles (Fu-EVs) from serum. We analyze microRNA (miRNA) profiles from Fu-EVs in 88 HCC patients and 179 non-HCC controls using next-generation sequencing (NGS) and identify five miRNAs (hsa-let-7a, hsa-miR-21, hsa-miR-125a, hsa-miR-200a, and hsa-miR-150) as biomarkers for HCC diagnosis.

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Extracellular vesicles (EVs) are pivotal in intercellular communication, disease mechanisms. Despite numerous methods for EVs isolation, challenges persist in yield, purity, reproducibility, cost, time, and automation. We introduce a EVs isolation technique using FeO@ZrO beads, leveraging ZrO-phosphate interaction.

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MicroRNAs (miRNAs) are promising biomarkers for the early detection of disease, and many miRNA-based diagnostic models have been constructed to distinguish patients and healthy individuals. To thoroughly utilize the miRNA-profiling data across different sequencing platforms or multiple centers, the models accounting the batch effects were demanded for the generalization of medical application. We conducted transcription factor (TF)-mediated miRNA-miRNA interaction network analysis and adopted the within-sample expression ratios of miRNA pairs as predictive markers.

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Extracellular vesicle (EV) miRNAs are promising biomarkers for clinical diagnosis. However, their stability is a crucial concern affecting reliability and accuracy. Factors such as sample collection, processing, storage conditions, and experimental procedures impact EV miRNA stability.

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Background: Tuberculosis (TB) and non-tuberculous mycobacteriosis are serious threats to health worldwide. A simple non-sequencing method is needed for rapid diagnosis, especially in less experienced hospitals, but there is no specific biomarker commonly used for all mycobacteria. The gene of the prokaryotic error-prone non-homologous end joining system (NHEJ) has the potential to be a highly specific detection biomarker for mycobacteria.

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