Age Related Changes in 5‐methylcytosine Content in Human Peripheral Leukocytes and Placentas: an HPLC‐based Study
Bibliographic record
Abstract
The goal of the present study was to investigate inter-individual and age-dependent variation of global DNA methylation in human tissues. In this work, we examined 5-methyldeoxycytidine ((met)C) content by HPLC in human peripheral blood leukocytes obtained from 76 healthy individuals of ages varying from 4 to 94 years (yr), and 39 human placentas from various gestational stages. The HPLC analysis revealed a significant variation of (met)C across individuals and is consistent with the previous findings of age-dependent decrease of global methylation levels in human tissues. The age-dependent decrease of (met)C was relatively small, but statistically highly significant (p= 0.0002) in the aged group (65.9 +/- 8.9 [mean age +/- SD] yr; n = 22) in comparison to the young adult group (19.3 +/- 1.4 yr; n = 21). Males showed a subtle but statistically significant higher mean (met)C content than females. In contrast to the peripheral blood samples, DNA extracted from placentas exhibited gestational stage-dependent increase of methylation levels that appeared to inversely correlate with the expression levels of human endogenous retroviruses. These data may be helpful in further studies of DNA methylation, such as inheritance of epigenetic patterns, environment-induced changes, and involvement of epigenetic changes in disease.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".