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1. Clinical investigation of enamel demineralization during clear aligner treatment

4. A Non-covalent Ligand Reveals Biased Agonism of the TRPA1 Ion Channel

5. Advances in mechanism study on novel tetracycline-inactivating enzymes tet(X) causing emerging tigecycline resistance

6. Ultra-processed food consumption and the risk of incident chronic kidney disease: a systematic review and meta-analysis of cohort studies.

8. Review of Machine Learning for Short Term Load Forecasting

14. Single-cell sequencing of the vermiform appendix during development identifies transcriptional relationships with appendicitis in preschool children.

15. Screening of irregular antibodies in pregnancy of different gestational weeks in Shanghai: cliniacal significance and safety strategy

18. Discovery of TRPA1 Antagonist GDC-6599: Derisking Preclinical Toxicity and Aldehyde Oxidase Metabolism with a Potential First-in-Class Therapy for Respiratory Disease

19. PROTACs Targeting BRM (SMARCA2) Afford Selective In Vivo Degradation over BRG1 (SMARCA4) and Are Active in BRG1 Mutant Xenograft Tumor Models

23. SPOP mutation induces DNA methylation via stabilizing GLP/G9a

30. Data from ERK Inhibition Overcomes Acquired Resistance to MEK Inhibitors

31. Supplementary Figures 1-7, Methods from ERK Inhibition Overcomes Acquired Resistance to MEK Inhibitors

32. PROTACs Targeting BRM (SMARCA2) Afford Selective In VivoDegradation over BRG1 (SMARCA4) and Are Active in BRG1 Mutant Xenograft Tumor Models

35. Application of Two-Stage Stochastic Linear Program for Portfolio Selection Problem

36. Novel advances in biotransformation and bioactivation research – 2020 year in review

41. Additional file 1 of Interaction of miR-200a-3p with YAP regulates cell proliferation and metastasis differentially in HPV-positive and HPV-negative cervical cancer cells

42. Additional file 3 of Machine learning algorithms’ accuracy in predicting kidney disease progression: a systematic review and meta-analysis

43. Additional file 1 of Machine learning algorithms’ accuracy in predicting kidney disease progression: a systematic review and meta-analysis

44. Additional file 2 of Machine learning algorithms’ accuracy in predicting kidney disease progression: a systematic review and meta-analysis

45. Additional file 2 of Interaction of miR-200a-3p with YAP regulates cell proliferation and metastasis differentially in HPV-positive and HPV-negative cervical cancer cells

50. Structure-Based Design of Potent, Selective, and Orally Bioavailable VPS34 Kinase Inhibitors

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