Publications by authors named "Ke Mu"

Cytosine-rich and poly(adenine)-tailed tetrahedral DNA framework (TDF) is designed as template (A-TDF) for anchoring silver nanoclusters (AgNCs) and igniting the dual-color fluorescence of AgNCs. The resultant DNA-AgNCs simultaneously emits red and green fluorescence, and the quantum yield of red fluorescence is as high as 44.8%.

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Accurate identification and localization of multiple abnormalities are crucial steps in the interpretation of chest X-rays (CXRs); however, the lack of a large CXR dataset with bounding boxes severely constrains accurate localization research based on deep learning. We created a large CXR dataset named CXR-AL14, containing 165,988 CXRs and 253,844 bounding boxes. On the basis of this dataset, a deep-learning-based framework was developed to identify and localize 14 common abnormalities and calculate the cardiothoracic ratio (CTR) simultaneously.

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Background: Hepatocellular carcinoma (HCC) is a highly heterogeneous cancer. Accurate preoperative prediction of histological grade holds potential for improving clinical management and disease prognostication.

Purpose: To evaluate the performance of a radiomics signature based on multiphase MRI in assessing histological grade in solitary HCC.

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Background: The incidence of colorectal cancer increases with aging. Curative-intent surgery based on a minimally invasive concept is expected to bring survival benefits to elderly patients (aged over 80 years) with colorectal cancer who are frequently with fragile health status and advanced tumors. The study explored survival outcomes in this patient population who received robotic or laparoscopic surgery and aimed to identify an optimal surgical option for those patients.

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Background: Immunodeficiency diseases (IDDs) are associated with an increased proportion of cancer-related morbidity. However, the relationship between IDDs and malignancy readmissions has not been well described. Understanding this relationship could help us to develop a more reasonable discharge plan in the special tumor population.

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Background: Immunotherapy is considered as a powerful and promising clinical approach for the treatment of gastric cancer (GC). However, it is still challenging to precisely screen patients who potentially benefit from immune checkpoint therapy (ICT). Identification of potential biomarkers for selecting patients sensitive to immunotherapy was urgently needed.

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To study the improvement of the entrepreneurial performance of start-ups and achieve an organic combination of entrepreneurship education and entrepreneurial performance, the entrepreneurial group of college students was taken as the springboard to discuss the entrepreneurial performance of start-ups initiated by college students. First, through questionnaire design and scale selection, the results of the questionnaire survey and the reliability and validity of the scale tool were tested. Second, the variable of college students' entrepreneurial self-efficacy based on psychological factor analysis was introduced.

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Article Synopsis
  • Aberrant DNA methylation plays a key role in the development of breast cancer, and this study aimed to identify a new set of biomarkers for prognosis using gene expression and methylation data.
  • Researchers analyzed data from The Cancer Genome Atlas and discovered 879 methylation-driven genes, ultimately identifying 50 of these as survival-related.
  • They developed an eight-gene panel that can predict patient prognosis, enhancing the understanding of biological processes and genetic factors in breast cancer.
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Asphalt pavement consists of multiple layers of asphalt with a progressive decrease of nominal maximum aggregate size from the bottom to the top, which can be constructed by the double-decked or the conventional paving method (i.e., layer by layer).

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