Fragile X mental retardation protein regulates heterosynaptic plasticity in the hippocampus
Bibliographic record
Abstract
Silencing of a single gene, FMR1, is linked to a highly prevalent form of mental retardation, characterized by social and cognitive impairments, known as fragile X syndrome (FXS). The FMR1 gene encodes fragile X mental retardation protein (FMRP), which negatively regulates translation. Knockout of Fmr1 in mice results in enhanced long-term depression (LTD) induced by metabotropic glutamate receptor (mGluR) activation. Despite the evidence implicating FMRP in LTD, the role of FMRP in long-term potentiation (LTP) is less clear. Synaptic strength can be augmented heterosynaptically through the generation and sequestration of plasticity-related proteins, in a cell-wide manner. If heterosynaptic plasticity is altered in Fmr1 knockout (KO) mice, this may explain the cognitive deficits associated with FXS. We induced homosynaptic plasticity using the β-adrenergic receptor (β-AR) agonist, isoproterenol (ISO), which facilitated heterosynaptic LTP that was enhanced in Fmr1 KO mice relative to wild-type (WT) controls. To determine if enhanced heterosynaptic LTP in Fmr1 KO mouse hippocampus requires protein synthesis, we applied a translation inhibitor, emetine (EME). EME blocked homo- and heterosynaptic LTP in both genotypes. We also probed the roles of mTOR and ERK in boosting heterosynaptic LTP in Fmr1 KO mice. Although heterosynaptic LTP was blocked in both WT and KOs by inhibitors of mTOR and ERK, homosynaptic LTP was still enhanced following mTOR inhibition in slices from Fmr1 KO mice. Because mTOR will normally stimulate translation initiation, our results suggest that β-AR stimulation paired with derepression of translation results in enhanced heterosynaptic plasticity.
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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 | 0.000 | 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 | 0.001 |
| 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".