Developmental expression of the neuroligins and neurexins in fragile X mice
Bibliographic record
Abstract
Neuroligins and neurexins are transsynaptic proteins involved in the maturation of glutamatergic and GABAergic synapses. Research has identified synaptic proteins and function as primary contributors to the development of fragile X syndrome. Fragile X mental retardation protein (FMRP), the protein that is lacking in fragile X syndrome, binds neuroligin-1 and -3 mRNA. Using in situ hybridization, we examined temporal and spatial expression patterns of neuroligin (NLGN) and neurexin (NRXN) mRNAs in the somatosensory (S1) cortex and hippocampus in wild-type (WT) and fragile X knockout (FMR1-KO) mice during the first 5 weeks of postnatal life. Genotype-based differences in expression included increased NLGN1 mRNA in CA1 and S1 cortex, decreased NLGN2 mRNA in CA1 and dentate gyrus (DG) regions of the hippocampus, and increased NRXN3 mRNA in CA1, DG, and S1 cortex between female WT and FMR1-KO mice. In male mice, decreased expression of NRXN3 mRNA was observed in CA1 and DG regions of FMR1-KO mice. Sex differences in hippocampal expression of NLGN2, NRXN1, NRXN2, and NRXN3 mRNAs and in S1 cortex expression of NRXN3 mRNAs were observed WT mice, whereas sex differences in NLGN3, NRXN1, NRXN2, and NRXN3 mRNA expression in the hippocampus and in NLGN1, NRXN2 and NRXN3 mRNA expression in S1 cortex were detected in FMR1-KO mice. These results provide a neuroanatomical map of NLGN and NRXN expression patterns over postnatal development in WT and FMR1-KO mice. The differences in developmental trajectory of these synaptic proteins could contribute to long-term differences in CNS wiring and synaptic function.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".