Sensory Experience Differentially Modulates the mRNA Expression of the Polysialyltransferases ST8SiaII and ST8SiaIV in Postnatal Mouse Visual Cortex
Bibliographic record
Abstract
Polysialic acid (PSA) is a unique carbohydrate composed of a linear homopolymer of α-2,8 linked sialic acid, and is mainly attached to the fifth immunoglobulin-like domain of the neural cell adhesion molecule (NCAM) in vertebrate neural system. In the brain, PSA is exclusively synthesized by the two polysialyltransferases ST8SiaII (also known as STX) and ST8SiaIV (also known as PST). By modulating adhesive property of NCAM, PSA plays a critical role in several neural development processes such as cell migration, neurite outgrowth, axon pathfinding, synaptogenesis and activity-dependent plasticity. The expression of PSA is temporally and spatially regulated during neural development and a tight regulation of PSA expression is essential to its biological function. In mouse visual cortex, PSA is downregulated following eye opening and its decrease allows the maturation of GABAergic synapses and the opening of the critical period for ocular dominance plasticity. Relatively little is known about how PSA levels are regulated by sensory experience and neuronal activity. Here, we demonstrate that while both ST8SiaII and ST8SiaIV mRNA levels decrease around the time of eye opening in mouse visual cortex, only ST8SiaII mRNA level reduction is regulated by sensory experience. Using an organotypic culture system from mouse visual cortex, we further show that ST8SiaII gene expression is regulated by spiking activity and NMDA-mediated excitation. Further, we show that both ST8SiaII and ST8SiaIV mRNA levels are positively regulated by PKC-mediated signaling. Therefore, sensory experience-dependent ST8SiaII gene expression regulates PSA levels in postnatal visual cortex, thus acting as molecular link between visual activity and PSA expression.
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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) | 0.000 | 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 | 0.000 | 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".