DNA methylation and histone post-translational modification stability in post-mortem brain tissue
Bibliographic record
Abstract
BACKGROUND: Epigenetic (including DNA and histone) modifications occur in a variety of neurological disorders. If epigenetic features of brain autopsy material are to be studied, it is critical to understand the post-mortem stability of the modifications. METHODS: Pig and mouse brain tissue were formalin-fixed and paraffin-embedded, or frozen after post-mortem delays of 0, 24, 48, and 72 h. Epigenetic modifications frequently reported in the literature were studied by DNA agarose gel electrophoresis, DNA methylation enzyme-linked immunosorbent assays, Western blotting, and immunohistochemistry. We constructed a tissue microarray of human neocortex samples with devitalization or death to fixation times ranging from < 60 min to 5 days. RESULTS: In pig and mouse brain tissue, we found that DNA cytosine modifications (5mC, 5hmC, 5fC, and 5caC) were stable for ≥ 72 h post-mortem. Histone methylation was generally stable for ≥ 48 h (H3K9me2/K9me3, H3K27me2, H3K36me3) or ≥ 72 h post-mortem (H3K4me3, H3K27me3). Histone acetylation was generally less stable. The levels of H3K9ac, H3K27ac, H4K5ac, H4K12ac, and H4K16ac declined as early as ≤ 24 h post-mortem, while the levels of H3K14ac did not change at ≥ 48 h. Immunohistochemistry showed that histone acetylation loss occurred primarily in the nuclei of large neurons, while immunoreactivity in glial cell nuclei was relatively unchanged. In the human brain tissue array, immunoreactivity for DNA cytosine modifications and histone methylation was stable, while subtle changes were apparent in histone acetylation at 4 to 5 days post-mortem. CONCLUSION: We conclude that global epigenetic studies on human post-mortem brain tissue are feasible, but great caution is needed for selection of post-mortem delay matched controls if histone acetylation is of interest.
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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".