Visual–spatial learning impairments are associated with hippocampal PSD-95 protein dysregulation in a mouse model of fragile X syndrome
Bibliographic record
Abstract
Fragile X syndrome is the most common cause of inherited intellectual disability and is caused by the lack of fragile X mental retardation protein (FMRP) expression. In-vitro findings in mice and post-mortem autopsies in humans are characterized by dendritic spine abnormalities in the absence of Fmrp/FMRP. Biochemical and electrophysiological studies have identified postsynaptic density protein (PSD)-95 as having an established role in dendritic morphology as well as a molecular target of Fmrp. How Fmrp affects the expression of PSD-95 following behavioral learning is unknown. In the current study, wild type controls and Fmr1 knockout mice were trained in a subset of the Hebb-Williams (H-W) mazes. Dorsal hippocampal PSD-95 protein levels relative to a stable cytoskeleton protein (β-tubulin) were measured. We report a significant upregulation of PSD-95 protein levels in wild type mice, whereas training-related protein increases were blunted in Fmr1 knockout mice. In addition, there was a significant negative correlation between mean total errors on the mazes and PSD-95 protein levels. The coefficient of determination indicated that the mean total errors on the H-W mazes accounted for 35% of the variance in PSD-95 protein levels. These novel findings suggest that reduced PSD-95-associated postsynaptic plasticity may contribute to the learning and memory deficits observed in human fragile X syndrome patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".