Prenatal low-dose methylmercury exposure causes premature neuronal differentiation and autism-like behaviors in a rodent model
Bibliographic record
Abstract
Aberrant neurodevelopment is a core deficit of autism spectrum disorder (ASD). Here we ask whether a non-genetic factor, prenatal exposure to the environmental pollutant methylmercury (MeHg), is a contributing factor in ASD onset. We showed that adult mice prenatally exposed to non-apoptotic MeHg exhibited key ASD characteristics, including impaired communication, reduced sociability, and increased restrictive repetitive behaviors, whereas in the embryonic cortex, prenatal MeHg exposure caused premature neuronal differentiation. Further single-cell RNA sequencing (scRNA-seq) analysis disclosed that prenatal exposure to MeHg resulted in cortical radial glial precursors (RGPs) favoring asymmetric differentiation to directly generate cortical neurons, omitting the intermediate progenitor stage. In addition, MeHg exposure in cultured RGPs increased CREB phosphorylation and enhanced the interaction between CREB and CREB binding protein (CBP). Intriguingly, metformin, an FDA-approved drug, can reverse MeHg-induced premature neuronal differentiation via CREB/CBP repulsion. These findings provide insights into ASD etiology, its underlying mechanism, and a potential therapeutic strategy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".