Showing 99,581 - 99,600 results of 106,178 for search '(( 12 mean decrease ) OR ( 5 ((((mean decrease) OR (nn decrease))) OR (a decrease)) ))', query time: 1.72s Refine Results
  1. 99581
  2. 99582

    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.…”
  3. 99583

    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.…”
  4. 99584

    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.…”
  5. 99585

    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.…”
  6. 99586

    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.…”
  7. 99587

    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.…”
  8. 99588

    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.…”
  9. 99589

    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.…”
  10. 99590
  11. 99591

    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. …”
  12. 99592

    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. …”
  13. 99593

    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. …”
  14. 99594

    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. …”
  15. 99595
  16. 99596
  17. 99597
  18. 99598
  19. 99599
  20. 99600