The ketamine metabolite ( <i>2R,6R</i> )‐hydroxynorketamine rescues transcriptional pathways involved with immune activation and mRNA translation in APP/PS1 mice
Bibliographic record
Abstract
BACKGROUND: Hippocampal mRNA translation (i.e., protein synthesis) is crucial for synaptic plasticity and memory consolidation, and becomes defective in AD. We investigated here whether the ketamine metabolite HNK could rescue transcription profiles related to mRNA translation in aged APP/PS1 mice. METHOD: Mice were treated with HNK (0.5 mg/kg, i.p.) or saline daily for 14 days, and hippocampal transcriptomic changes were assessed by RNA-seq. These data were then analyzed by gene ontology (GO) enrichment and reactome analysis. RESULT: GO analyses revealed significantly upregulated pathways in APP/PS1 mice (compared to WT mice) that were corrected by HNK treatment. These included regulation of programmed cell death and response to hormones and stress. Reactome pathway analyses further implicated the innate immune system and, notably, three pathways associated with RNA metabolism and translation that were aberrantly regulated in APP/PS1 mice and were rescued by HNK. CONCLUSION: Altogether, these results indicate that HNK rescues transcriptional programs associated with inflammation, impaired proteostasis, calcium signaling, and synaptic proteins in aged APP/S1 mice.
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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".