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6. Additional file 1: of miR-520d-5p can reduce the mutations in hepatoma cancer cells and iPSCs-derivatives

10. Additional file 9: Table S4. of Tumor-suppressive effects of atelocollagen-conjugated hsa-miR-520d-5p on un-differentiated cancer cells in a mouse xenograft model

11. Additional file 6: Figure S1. of Tumor-suppressive effects of atelocollagen-conjugated hsa-miR-520d-5p on un-differentiated cancer cells in a mouse xenograft model

12. Additional file 3: Table S2. of Tumor-suppressive effects of atelocollagen-conjugated hsa-miR-520d-5p on un-differentiated cancer cells in a mouse xenograft model

13. Additional file 7: Figure S2. of Tumor-suppressive effects of atelocollagen-conjugated hsa-miR-520d-5p on un-differentiated cancer cells in a mouse xenograft model

14. Additional file 5: Figure S6. of Tumor-suppressive effects of atelocollagen-conjugated hsa-miR-520d-5p on un-differentiated cancer cells in a mouse xenograft model

15. Additional file 4: Table S3. of Tumor-suppressive effects of atelocollagen-conjugated hsa-miR-520d-5p on un-differentiated cancer cells in a mouse xenograft model

16. Additional file 1: Table S1. of Tumor-suppressive effects of atelocollagen-conjugated hsa-miR-520d-5p on un-differentiated cancer cells in a mouse xenograft model

17. Additional file 2: Figure S5. of Tumor-suppressive effects of atelocollagen-conjugated hsa-miR-520d-5p on un-differentiated cancer cells in a mouse xenograft model

18. Additional file 8: Figure S3. of Tumor-suppressive effects of atelocollagen-conjugated hsa-miR-520d-5p on un-differentiated cancer cells in a mouse xenograft model

23. Comparative study of 18 F‐ FDG ‐ PET / CT imaging and serum hTERT mRNA quantification in cancer diagnosis

25. Tumor-suppressive effects of atelocollagen-conjugated hsa-miR-520d-5p on un-differentiated cancer cells in a mouse xenograft model.

27. Comparative study of 18F- FDG- PET/ CT imaging and serum hTERT mRNA quantification in cancer diagnosis.

33. On-Line Physiological State Recognition and Parameter Estimation in the Metabolic Reaction Model Using Error Vectors

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