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103541
Data Sheet 4_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv
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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103542
Data Sheet 6_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv
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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103543
Data Sheet 3_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv
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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103544
Data Sheet 2_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.csv
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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103545
Image 1_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.jpeg
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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103546
Image 3_Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods.jpeg
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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103547
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103548
Upshift of Phase Transition Temperature in Nanostructured PbTiO<sub>3</sub> Thick Film for High Temperature Applications
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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103549
Upshift of Phase Transition Temperature in Nanostructured PbTiO<sub>3</sub> Thick Film for High Temperature Applications
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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103550
Upshift of Phase Transition Temperature in Nanostructured PbTiO<sub>3</sub> Thick Film for High Temperature Applications
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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103551
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103552
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103553
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103554
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103555
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103556
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103557
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103558
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103559
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103560