Extracellular lactate improves neurogenesis by modulating H3K9 lactylation and SnoN expression under hypoxic conditions
Bibliographic record
Abstract
Lactate has a beneficial effect on adult neurogenesis and has been identified as a mediator of lactylation of proteins. However, the regulatory role and function of histone lactylation in neurogenesis remain poorly understood. This study aimed to elucidate the relationship between lactate and the fate of neural stem cells (NSCs), and explore the role of histone lactylation in neurogenesis. Under hypoxic conditions, NSCs were treated with lactate to investigate its effects on cell fate. Western blot and immunofluorescence staining were performed to detect histone lactylation modifications. RNA-sequencing (RNA-seq) was used to characterize the transcriptome after lactate treatment, in conjunction with Chromatin immunoprecipitation sequencing (ChIP-seq), to identify potential target genes for histone lactylation. Under hypoxic conditions, L-lactate promotes neurogenesis and induces H3K9 histone lactylation (H3K9la). The inhibition of L-lactate uptake or production hinders neuronal development and is accompanied by decreased H3K9la. And the inhibition of H3K9la inhibits the differentiation of NSCs into neurons. Furthermore, H3K9la was enriched in the SnoN (also known as Skil) promoter region, and siRNA targeting SnoN inhibits the generation of Doublecortin (DCX)+ neurons. L-lactate promotes neurogenesis through H3K9la/SnoN axis under hypoxic environments and SnoN potentially serves as a novel target for enhancing neurological recovery in cerebral ischemia.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".