Essential lipids enrich membrane-associated condensates to rescue synaptic morpho-functional deficits in a mouse model of autism
Bibliographic record
Abstract
Synaptic proteins form intracellular condensates with their scaffolds, but it is unknown whether and how essential lipids transform dynamic cytosolic condensates into stable, functional macromolecular assemblies at the membrane. We show that docosahexaenoic acid (DHA), independent of canonical fatty acid receptor 4 signaling, facilitates the re-localization of cytosolic "full-droplet" condensates composed of the key synaptic elements PSD95 and Kv1.2 to the plasma membrane as "half-droplets." To exploit the therapeutic potential of DHA in vivo, we briefly place juvenile wild-type and Fmr1 KO mice, modeling human fragile X syndrome (FXS), under DHA-enriched or -depleted diets. DHA reverses the inhibitory overtone by promoting the re-localization of presynaptic PSD95-Kv1.2 condensates to interneuron terminal membranes and corrects morpho-functional synaptic defects and stereotypic behaviors. These findings reveal an unexpected role of essential lipids in translocating dynamic condensates into stable synaptic condensates, providing long-lasting benefits for rectifying excitation-inhibition imbalance in FXS and potentially other neurodevelopmental disorders.
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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 | 0.001 |
| 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".