Additional file 2 of DNA methylation of insulin signaling pathways is associated with HOMA2-IR in primary myoblasts from older adults
Bibliographic record
Abstract
Additional file 2: Supplementary Table 1. List of HOMA2-IR dmCpGs. Supplementary Table 2. Top 20 GO and KEGG terms associated with the HOMA2-IR networks. Supplementary Table 3. IPA Networks from top 100 dmCpG associated genes with HOMA2-IR. Supplementary Table 4. IPA upstream regulators from top 100 dmCpG associated genes with HOMA2-IR. Supplementary Table 5. List of HOMA2-IR dmCpGs after adjustment for BMI. Supplementary Table 6. Top 20 GO and KEGG terms associated with the HOMA2-IR networks after adjustment for BMI. Supplementary Table 7. List of HOMA2-IR associated dmCpGs after adjustment for ALMi. Supplementary Table 8. List of HOMA2-IR associated dmCpGs after adjustment for grip strength. Supplementary Table 9. List of HOMA2-IR associated dmCpGs after adjustment for gait speed. Supplementary Table 10. Top 20 GO and KEGG terms associated with the HOMA2-IR networks after adjustment for ALMi. Supplementary Table 11. Top 20 GO and KEGG terms associated with the HOMA2-IR networks after adjustment for grip strength. Supplementary Table 12. Top 20 GO and KEGG terms associated with the HOMA2-IR networks after adjustment for gait speed. Supplementary Table 13. List of HbA1C associated dmCpGs. Supplementary Table 14. Common Overlapping dmCpGs. Supplementary Table 15. List of fasting HbA1c associated dmCpGs after adjustment for BMI. Supplementary Table 16. List of hbA1c associated dmCpGs after adjustment for ALMi. Supplementary Table 17. List of hbA1c associated dmCpGs after adjustment for grip strength. Supplementary Table 18. List of hbA1c associated dmCpGs after adjustment for gait speed. Supplementary Table 19. Top 20 GO and KEGG terms associated with the HbA1c networks. Supplementary Table 20. Top 20 GO and KEGG terms associated with the HbA1c networks after adjustment for BMI. Supplementary Table 21. Top 20 GO and KEGG terms associated with the hbA1c networks after adjustment for ALMi. Supplementary Table 22. Top 20 GO and KEGG terms associated with the hbA1c networks after adjustment for grip strength. Supplementary Table 23. Top 20 GO and KEGG terms associated with the hbA1c networks after adjustment for gait speed. Supplementary Table 24. HOMA2-IR asscoiated differentially methylated regions. Supplementary Table 25. Hba1c asscoiated differentially methylated regions. Supplementary Table 26. HOMA2-IR asscoiated differentially methylated regions adjusted for BMI. Supplementary Table 27. HOMA2-IR asscoiated differentially methylated regions after adjustment for grip strength. Supplementary Table 28. HOMA2-IR asscoiated differentially methylated regions after adjustment for gait speed. Supplementary Table 29. HOMA2-IR asscoiated differentially methylated regions after adjustment for ALMi. Supplementary Table 30. HbA1c asscoiated differentially methylated regions after adjustment for BMI. Supplementary Table 31. HbA1c asscoiated differentially methylated regions after adjustment for grip strength. Supplementary Table 32. HbA1c asscoiated differentially methylated regions after adjustment for gait speed. Supplementary Table 33. HbA1c asscoiated differentially methylated regions after adjustment for ALMi. Supplementary Table 34. MEAT methylation clock for HOMA2-IR and HbA1c unadjusted and adjusted for BMI.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.786 | 0.112 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".