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2. Fine-mapping analysis including over 254,000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes

3. Supplementary Methods from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

4. Supplementary Table 2 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

5. Supplementary Figure 4 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

6. Data from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

7. Supplementary Methods from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

8. Supplementary Table 1 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

9. Supplementary Figure 1 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

10. Supplementary Figure 1 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

11. Supplementary Table 2 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

12. Supplementary Figure 2 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

13. Supplementary Figure 2 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

14. Supplementary Figure 3 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

15. Data from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

16. Supplementary Figure 4 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

17. Supplementary Figure 5 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

18. Supplementary Table 1 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

19. Supplementary Figure 3 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

20. Supplementary Figure 5 from Genome-Wide Gene–Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk

21. Genome-wide gene-environment interaction analyses to understand the relationship between red meat and processed meat intake and colorectal cancer risk.

22. Recommendations of the Spanish Antibiogram Committee (COESANT) for in vitro susceptibility testing of antimicrobial agents by disk diffusion

24. Heterozygote advantage at HLA class I and II loci and reduced risk of colorectal cancer

25. Spanish Antibiogram Committee (COESANT) recommendations for cumulative antibiogram reports

26. Identification of a Twelve-microRNA Signature with Prognostic Value in Stage II Microsatellite Stable Colon Cancer

27. Author Correction: Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries

28. Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries

29. Author Correction: COLONOMICS - integrative omics data of one hundred paired normal-tumoral samples from colon cancer patients

30. COLONOMICS - integrative omics data of one hundred paired normal-tumoral samples from colon cancer patients

33. Meta-Analysis and Validation of a Colorectal Cancer Risk Prediction Model Using Deep Sequenced Fecal Metagenomes

35. Recommendations of the Spanish Antibiogram Committee (COESANT) for in vitro susceptibility testing of antimicrobial agents by disk diffusion

36. Evaluating the Potential of Polygenic Risk Score to Improve Colorectal Cancer Screening

38. Prevalence and seasonality of viral respiratory infections in a temperate climate region: A 24‐year study (1997–2020)

39. Recomendaciones del Comité Español del Antibiograma (COESANT) para la realización de los Informes de Sensibilidad Antibiótica Acumulada

41. Novel insights into the molecular mechanisms underlying risk of colorectal cancer from smoking and red/processed meat carcinogens by modeling exposure in normal colon organoids

42. Transcriptome-Wide Association Study for Inflammatory Bowel Disease Reveals Novel Candidate Susceptibility Genes in Specific Colon Subsites and Tissue Categories

45. Bacteriophages immunomodulate the response of monocytes

47. Genetic Effects on Transcriptome Profiles in Colon Epithelium Provide Functional Insights for Genetic Risk Loci

48. Intraoperative Bacterial Contamination and Activity of Different Antimicrobial Prophylaxis Regimens in Primary Knee and Hip Replacement

50. Do Prosthetic Joint Infections Worsen the Functional Ambulatory Outcome of Patients with Joint Replacements? A Retrospective Matched Cohort Study

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