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Showing 99,721 - 99,740 results of 105,872 for search '(( 1 wt decrease ) OR ( 5 ((point decrease) OR (((mean decrease) OR (a decrease)))) ))', query time: 1.77s Refine Results
  1. 99721
    Image 2_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.jpeg

    Image 2_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.jpeg by Xiuping Xuan (8686266)

    Published 2025
    “…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”
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  2. 99722
    Data Sheet 1_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv

    Data Sheet 1_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv by Xiuping Xuan (8686266)

    Published 2025
    “…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”
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  3. 99723
    Data Sheet 4_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv

    Data Sheet 4_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv by Xiuping Xuan (8686266)

    Published 2025
    “…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”
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  4. 99724
    Data Sheet 6_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv

    Data Sheet 6_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv by Xiuping Xuan (8686266)

    Published 2025
    “…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”
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  5. 99725
    Data Sheet 3_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv

    Data Sheet 3_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv by Xiuping Xuan (8686266)

    Published 2025
    “…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”
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  6. 99726
    Data Sheet 2_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv

    Data Sheet 2_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv by Xiuping Xuan (8686266)

    Published 2025
    “…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”
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  7. 99727
    Image 1_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.jpeg

    Image 1_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.jpeg by Xiuping Xuan (8686266)

    Published 2025
    “…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”
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  8. 99728
    Image 3_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.jpeg

    Image 3_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.jpeg by Xiuping Xuan (8686266)

    Published 2025
    “…Additionally, drugs prediction analysis revealed 2(S)-amino-6-boronohexanoic acid, difluoromethylornithine, and compound 9 could target ARG2, while metformin was a candidate drug for SCL2A2. Finally, all five genes were confirmed to be decreased in MIN6 cells treated with high glucose and palmitic acid.…”
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  9. 99729
    DataSheet1_D-Cysteine Ethyl Ester Reverses the Deleterious Effects of Morphine on Breathing and Arterial Blood–Gas Chemistry in Freely-Moving Rats.docx

    DataSheet1_D-Cysteine Ethyl Ester Reverses the Deleterious Effects of Morphine on Breathing and Arterial Blood–Gas Chemistry in Freely-Moving Rats.docx by Paulina M. Getsy (11465254)

    Published 2022
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  10. 99730
    Distinct Roles of MicroRNA-1 and -499 in Ventricular Specification and Functional Maturation of Human Embryonic Stem Cell-Derived Cardiomyocytes

    Distinct Roles of MicroRNA-1 and -499 in Ventricular Specification and Functional Maturation of Human Embryonic Stem Cell-Derived Cardiomyocytes by Ji-Dong Fu (196646)

    Published 2011
    “…</p> <h3>Methods and Results</h3><p>We hypothesized that miRs that figure prominently in cardiac differentiation are differentially expressed in differentiating, developing, and terminally mature human cardiomyocytes (CMs). As a first step, we mapped the miR profiles of human (h) embryonic stem cells (ESCs), hESC-derived (hE), fetal (hF) and adult (hA) ventricular (V) CMs. 63 miRs were differentially expressed between hESCs and hE-VCMs. …”
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  11. 99731
    Upshift of Phase Transition Temperature in Nanostructured PbTiO<sub>3</sub> Thick Film for High Temperature Applications

    Upshift of Phase Transition Temperature in Nanostructured PbTiO<sub>3</sub> Thick Film for High Temperature Applications by Jungho Ryu (1587565)

    Published 2014
    “…A large-signal effective <i>d</i><sub>33,eff</sub> value of >60 pm/V is achieved at room temperature. …”
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  12. 99732
    Upshift of Phase Transition Temperature in Nanostructured PbTiO<sub>3</sub> Thick Film for High Temperature Applications

    Upshift of Phase Transition Temperature in Nanostructured PbTiO<sub>3</sub> Thick Film for High Temperature Applications by Jungho Ryu (1587565)

    Published 2014
    “…A large-signal effective <i>d</i><sub>33,eff</sub> value of >60 pm/V is achieved at room temperature. …”
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  13. 99733
    Upshift of Phase Transition Temperature in Nanostructured PbTiO<sub>3</sub> Thick Film for High Temperature Applications

    Upshift of Phase Transition Temperature in Nanostructured PbTiO<sub>3</sub> Thick Film for High Temperature Applications by Jungho Ryu (1587565)

    Published 2014
    “…A large-signal effective <i>d</i><sub>33,eff</sub> value of >60 pm/V is achieved at room temperature. …”
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  14. 99734
    Additional file 3 of Sub-minute acquisition with deep learning-based image filter in the diagnosis of colorectal cancers using total-body 18F-FDG PET/CT

    Additional file 3 of Sub-minute acquisition with deep learning-based image filter in the diagnosis of colorectal cancers using total-body 18F-FDG PET/CT by Entao Liu (385423)

    Published 2023
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  15. 99735
    Intracellular Zn2+ Promotes Extracellular Matrix Remodeling in Dexamethasone-Treated Trabecular Meshwork

    Intracellular Zn2+ Promotes Extracellular Matrix Remodeling in Dexamethasone-Treated Trabecular Meshwork by ying Liu (18009823)

    Published 2024
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  16. 99736
    Growth and contents of organic and inorganic solutes in amaranth under salt stress

    Growth and contents of organic and inorganic solutes in amaranth under salt stress by Renata Velasques Menezes (10448393)

    Published 2021
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  17. 99737
    After 48 h of incubation IFNγ dose-dependently induced an arrest in the S-phase of the cell cycle of BON cells

    After 48 h of incubation IFNγ dose-dependently induced an arrest in the S-phase of the cell cycle of BON cells by Michael Höpfner (56461)

    Published 2011
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  18. 99738
    After 48 h of incubation IFNγ dose-dependently induced an arrest in the S-phase of the cell cycle of BON cells

    After 48 h of incubation IFNγ dose-dependently induced an arrest in the S-phase of the cell cycle of BON cells by Michael Höpfner (56461)

    Published 2011
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  19. 99739
    SURVIVAL MECHANISMS OF Fusarium oxysporum f. sp. passiflorae ARE AFFECTED BY APPLICATION OF CABBAGE AND CASSAVA DEBRIS

    SURVIVAL MECHANISMS OF Fusarium oxysporum f. sp. passiflorae ARE AFFECTED BY APPLICATION OF CABBAGE AND CASSAVA DEBRIS by JOYSE BRITO VIEIRA (13289104)

    Published 2022
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  20. 99740
    Lipid production in Dunaliella bardawil under autotrophic, heterotrophic and mixotrophic conditions

    Lipid production in Dunaliella bardawil under autotrophic, heterotrophic and mixotrophic conditions by Zohreh Zare Chavoshi (7577744)

    Published 2019
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