Showing 98,261 - 98,280 results of 104,446 for search '(( a step decrease ) OR ( 5 ((point decrease) OR (((mean decrease) OR (a decrease)))) ))', query time: 1.72s Refine Results
  1. 98261

    Functional characterization of GF-TTMn synaptic defects of mutant L1CAM protein expressions in <i>nrg<sup>14</sup></i>;P[nrg180<sup>ΔFIGQY</sup>] background. by Sirisha Kudumala (470461)

    Published 2013
    “…However, in most responding animals that had a decreased ability to follow at a one-to-one ratio at 100 Hz, the Response Latency was increased indicating a reduction in synaptic strength for the GF to TTMn connection.…”
  2. 98262
  3. 98263

    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.…”
  4. 98264

    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.…”
  5. 98265

    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.…”
  6. 98266

    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.…”
  7. 98267

    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.…”
  8. 98268

    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.…”
  9. 98269

    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.…”
  10. 98270

    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.…”
  11. 98271
  12. 98272

    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. 98273

    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. 98274

    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. 98275
  16. 98276
  17. 98277
  18. 98278
  19. 98279
  20. 98280