Histone H3K4 methylation In hippocampal memory formation and In Alzheimer’s disease
Bibliographic record
Abstract
Regulation of chromatin structure through posttranslational histone modifications is implicated in the induction of synaptic plasticity and memory formation. One such modification – histone H3 lysine 4 methylation (H3K4me) – has recently emerged as a key epigenetic modification necessary for consolidation of hippocampus-dependent memory. It is well-established that H3K4me levels across the genome are dynamically regulated by opposing activity of lysine methyltransferases (KMTs) and lysine demethylases (KDMs). They link dysregulation of H3K4 KMTs to neurodegenerative disorders, such as Alzheimer’s disease (AD). The major group of H3K4 KMTs in mammals are the Trithorax Group (TrxG) complexes, which can promote gene expression via distinct enzymatic (methylation of H3K4) and non-enzymatic (e.g. recruitment of other co-activators) mechanisms. In my project, I targeted the catalytic activity of TrxG complex and demonstrated that the loss of H3K4 methylation in mature hippocampal neurons leads to several intellectual abnormalities, such as the development of anxiety-like behaviour, recognition memory deficit, and impaired reversal memory with normal locomotory coordination in mice. Furthermore, I provided evidence of reduced H3K4 methylation in the hippocampus of AD by using a combination of patient samples and rodent disease model. Collectively, these results suggest that TrxG-mediated H3K4 methylation is required for a proper formation of hippocampal memory and may help shed light on H3K4 methylation as a novel therapeutic target for the treatment and prevention of AD.
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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 | 0.001 | 0.001 |
| 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".