Altering 5-hydroxymethylcytosine modification impacts ischemic brain injury
Bibliographic record
Abstract
Epigenetic modifications such as cytosine methylation and histone modification are linked to the pathology of ischemic brain injury. Recent research has implicated 5-hydroxymethylcytosine (5hmC), a DNA base derived from 5-methylcytosine (5mC) via oxidation by ten-eleven translocation (Tet) enzymes, in DNA methylation-related plasticity. Here we show that 5hmC abundance was increased after ischemic injury, and Tet2 was responsible for this increase; furthermore, inhibiting Tet2 expression abolished the increase of 5hmC caused by ischemic injury. The decrease in 5hmC modifications from inhibiting Tet2 activity was accompanied by increased infarct volume after ischemic injury. Genome-wide profiling of 5hmC revealed differentially hydroxymethylated regions (DhMRs) associated with ischemic injury, and DhMRs were enriched among the genes involved in cell junction, neuronal morphogenesis and neurodevelopment. In particular, we found that 5hmC modifications at the promoter region of brain-derived neurotrophic factor (BDNF) increased, which was accompanied by increased BDNF mRNA, whereas the inhibition of Tet2 reduced BDNF mRNA and protein expression. Finally, we show that the abundance of 5hmC in blood samples from patients with acute ischemic stroke was also significantly increased. Together, these data suggest that 5hmC modification could serve as both a potential biomarker and a therapeutic target for the treatment of ischemic stroke.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".