33 research outputs found

    Immobilization on Metalā€“Organic Framework Engenders High Sensitivity for Enzymatic Electrochemical Detection

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    The protection effect of metalā€“organic framework (MOF) provides high stability for immobilized enzyme. The small cavities of MOFs, however, usually result in decreased apparent substrate affinity and enzymatic activity of immobilized enzyme, compared to native enzyme. We synthesized zeolitic imidazolate framework-8 (ZIF-8) with a combination of mesoporous and microporous channels for cytochrome <i>c</i> (Cyt <i>c</i>) immobilization. Compared with native Cyt <i>c</i>, the immobilized Cyt <i>c</i> displayed increased apparent substrate affinity (Michaelis constant <i>K</i><sub>m</sub> reduced by āˆ¼50%), āˆ¼128% increased enzymatic activity, and 1.4-fold increased sensitivity in the enzymatic electrochemical detection of H<sub>2</sub>O<sub>2</sub>. The immobilized Cyt <i>c</i>-coated screen-printed electrode was applied for the fast detection of residual H<sub>2</sub>O<sub>2</sub> in microliter food samples such as milk and beer, making it promising for the development of efficient biosensors

    Image_3_Identification and validation of a novel CD8+ T cell-associated prognostic model based on ferroptosis in acute myeloid leukemia.tif

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    Acute myeloid leukemia (AML) is a highly aggressive cancer with great heterogeneity and variability in prognosis. Though European Leukemia Net (ELN) 2017 risk classification has been widely used, nearly half of patients were stratified to ā€œintermediateā€ risk and requires more accurate classification via excavating biological features. As new evidence showed that CD8+ T cell can kill cancer cells through ferroptosis pathway. We firstly use CIBERSORT algorithm to divide AMLs into CD8+ high and CD8+ low T cell groups, then 2789 differentially expressed genes (DEGs) between groups were identified, of which 46 ferroptosis-related genes associated with CD8+ T cell were sorted out. GO, KEGG analysis and PPI network were conducted based on these 46 DEGs. By jointly using LASSO algorithm and Cox univariate regression, we generated a 6-gene prognostic signature comprising VEGFA, KLHL24, ATG3, EIF2AK4, IDH1 and HSPB1. Low-risk group shows a longer overall survival. We then validated the prognostic value of this 6-gene signature using two independent external datasets and patient sample collection dataset. We also proved that incorporation of the 6-gene signature obviously enhanced the accuracy of ELN risk classification. Finally, gene mutation analysis, drug sensitive prediction, GSEA and GSVA analysis were conducted between high-risk and low-risk AML patients. Collectively, our findings suggested that the prognostic signature based on CD8+ T cell-related ferroptosis genes can optimize the risk stratification and prognostic prediction of AML patients.</p

    Image_1_Identification and validation of a novel CD8+ T cell-associated prognostic model based on ferroptosis in acute myeloid leukemia.tif

    No full text
    Acute myeloid leukemia (AML) is a highly aggressive cancer with great heterogeneity and variability in prognosis. Though European Leukemia Net (ELN) 2017 risk classification has been widely used, nearly half of patients were stratified to ā€œintermediateā€ risk and requires more accurate classification via excavating biological features. As new evidence showed that CD8+ T cell can kill cancer cells through ferroptosis pathway. We firstly use CIBERSORT algorithm to divide AMLs into CD8+ high and CD8+ low T cell groups, then 2789 differentially expressed genes (DEGs) between groups were identified, of which 46 ferroptosis-related genes associated with CD8+ T cell were sorted out. GO, KEGG analysis and PPI network were conducted based on these 46 DEGs. By jointly using LASSO algorithm and Cox univariate regression, we generated a 6-gene prognostic signature comprising VEGFA, KLHL24, ATG3, EIF2AK4, IDH1 and HSPB1. Low-risk group shows a longer overall survival. We then validated the prognostic value of this 6-gene signature using two independent external datasets and patient sample collection dataset. We also proved that incorporation of the 6-gene signature obviously enhanced the accuracy of ELN risk classification. Finally, gene mutation analysis, drug sensitive prediction, GSEA and GSVA analysis were conducted between high-risk and low-risk AML patients. Collectively, our findings suggested that the prognostic signature based on CD8+ T cell-related ferroptosis genes can optimize the risk stratification and prognostic prediction of AML patients.</p

    DataSheet_1_Identification and validation of a novel CD8+ T cell-associated prognostic model based on ferroptosis in acute myeloid leukemia.docx

    No full text
    Acute myeloid leukemia (AML) is a highly aggressive cancer with great heterogeneity and variability in prognosis. Though European Leukemia Net (ELN) 2017 risk classification has been widely used, nearly half of patients were stratified to ā€œintermediateā€ risk and requires more accurate classification via excavating biological features. As new evidence showed that CD8+ T cell can kill cancer cells through ferroptosis pathway. We firstly use CIBERSORT algorithm to divide AMLs into CD8+ high and CD8+ low T cell groups, then 2789 differentially expressed genes (DEGs) between groups were identified, of which 46 ferroptosis-related genes associated with CD8+ T cell were sorted out. GO, KEGG analysis and PPI network were conducted based on these 46 DEGs. By jointly using LASSO algorithm and Cox univariate regression, we generated a 6-gene prognostic signature comprising VEGFA, KLHL24, ATG3, EIF2AK4, IDH1 and HSPB1. Low-risk group shows a longer overall survival. We then validated the prognostic value of this 6-gene signature using two independent external datasets and patient sample collection dataset. We also proved that incorporation of the 6-gene signature obviously enhanced the accuracy of ELN risk classification. Finally, gene mutation analysis, drug sensitive prediction, GSEA and GSVA analysis were conducted between high-risk and low-risk AML patients. Collectively, our findings suggested that the prognostic signature based on CD8+ T cell-related ferroptosis genes can optimize the risk stratification and prognostic prediction of AML patients.</p

    Observation of <i>Fusarium verticillioides</i> wild strains and their enhanced green fluorescent protein <i>(EGFP)</i> transformants.

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    <p>Colony growth (5-day-culture) of each strain. (a) stalk rot wild strain Fv-s, (b) Fv-eGFPs1, an <i>EGFP</i> transformant of Fv-s, (c) Fv-eGFPs2, an <i>EGFP</i> transformant of Fv-s, (d) Fv-eGFPs3, an <i>EGFP</i> transformant of Fv-s, (e) ear rot wild strain Fv-e, (f) Fv-eGFPe1, an <i>EGFP</i> transformant of Fv-e, (g) Fv-eGFPe2, an <i>EGFP</i> transformant of Fv-e, (h) Fv-eGFPe3, an <i>EGFP</i> transformant of Fv-e.</p

    Different degrees of enhanced green fluorescent protein <i>(EGFP)</i>-tagged <i>Fusarium verticillioides</i> infection in stalks of maize.

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    <p>A) The highest infected internode under the natural light and blue light (Fv-eGFPe1); B) the internode above the ear under the natural light and blue light (Fv-eGFPs1); C) the internode below the ear under the natural light and blue light (Fv-eGFPe1); D and E) the below infected internode under blue light (Fv-eGFPs1).</p

    sj-docx-2-dhj-10.1177_20552076241234628 - Supplemental material for Barriers and facilitators to acceptance and implementation of eMental-health intervention among older adults: A qualitative systematic review

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    Supplemental material, sj-docx-2-dhj-10.1177_20552076241234628 for Barriers and facilitators to acceptance and implementation of eMental-health intervention among older adults: A qualitative systematic review by Ruotong Peng, Xiaoyang Li, Yongzhen Guo, Hongting Ning, Jundan Huang, Dian Jiang, Hui Feng and Qingcai Liu in DIGITAL HEALTH</p

    DataSheet_2_Identification and validation of a novel CD8+ T cell-associated prognostic model based on ferroptosis in acute myeloid leukemia.zip

    No full text
    Acute myeloid leukemia (AML) is a highly aggressive cancer with great heterogeneity and variability in prognosis. Though European Leukemia Net (ELN) 2017 risk classification has been widely used, nearly half of patients were stratified to ā€œintermediateā€ risk and requires more accurate classification via excavating biological features. As new evidence showed that CD8+ T cell can kill cancer cells through ferroptosis pathway. We firstly use CIBERSORT algorithm to divide AMLs into CD8+ high and CD8+ low T cell groups, then 2789 differentially expressed genes (DEGs) between groups were identified, of which 46 ferroptosis-related genes associated with CD8+ T cell were sorted out. GO, KEGG analysis and PPI network were conducted based on these 46 DEGs. By jointly using LASSO algorithm and Cox univariate regression, we generated a 6-gene prognostic signature comprising VEGFA, KLHL24, ATG3, EIF2AK4, IDH1 and HSPB1. Low-risk group shows a longer overall survival. We then validated the prognostic value of this 6-gene signature using two independent external datasets and patient sample collection dataset. We also proved that incorporation of the 6-gene signature obviously enhanced the accuracy of ELN risk classification. Finally, gene mutation analysis, drug sensitive prediction, GSEA and GSVA analysis were conducted between high-risk and low-risk AML patients. Collectively, our findings suggested that the prognostic signature based on CD8+ T cell-related ferroptosis genes can optimize the risk stratification and prognostic prediction of AML patients.</p

    Image_2_Identification and validation of a novel CD8+ T cell-associated prognostic model based on ferroptosis in acute myeloid leukemia.tif

    No full text
    Acute myeloid leukemia (AML) is a highly aggressive cancer with great heterogeneity and variability in prognosis. Though European Leukemia Net (ELN) 2017 risk classification has been widely used, nearly half of patients were stratified to ā€œintermediateā€ risk and requires more accurate classification via excavating biological features. As new evidence showed that CD8+ T cell can kill cancer cells through ferroptosis pathway. We firstly use CIBERSORT algorithm to divide AMLs into CD8+ high and CD8+ low T cell groups, then 2789 differentially expressed genes (DEGs) between groups were identified, of which 46 ferroptosis-related genes associated with CD8+ T cell were sorted out. GO, KEGG analysis and PPI network were conducted based on these 46 DEGs. By jointly using LASSO algorithm and Cox univariate regression, we generated a 6-gene prognostic signature comprising VEGFA, KLHL24, ATG3, EIF2AK4, IDH1 and HSPB1. Low-risk group shows a longer overall survival. We then validated the prognostic value of this 6-gene signature using two independent external datasets and patient sample collection dataset. We also proved that incorporation of the 6-gene signature obviously enhanced the accuracy of ELN risk classification. Finally, gene mutation analysis, drug sensitive prediction, GSEA and GSVA analysis were conducted between high-risk and low-risk AML patients. Collectively, our findings suggested that the prognostic signature based on CD8+ T cell-related ferroptosis genes can optimize the risk stratification and prognostic prediction of AML patients.</p
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