Mechanisms of Neuronal Alternative Splicing and Strategies for Therapeutic Interventions
Bibliographic record
Abstract
Many cellular and physiological processes are coordinated by regulatory networks that produce a remarkable complexity of transcript isoforms. In the mammalian nervous system, alternative pre-mRNA splicing generates functionally distinct isoforms that play key roles in normal physiology, supporting development, plasticity, complex behaviors, and cognition. Neuronal splicing programs controlled by RNA-binding proteins, are influenced by chromatin modifications and can exhibit neuronal subtype specificity. As highlighted in recent publications, aberrant alternative splicing is a major contributor to disease phenotypes. Therefore, understanding the underlying mechanisms of alternative splicing regulation and identifying functional splicing isoforms with critical phenotypic roles are expected to provide a comprehensive resource for therapeutic development, as illuminated by recent successful interventions of spinal muscular atrophy. Here, we discuss the latest progress in the study of the emerging complexity of alternative splicing mechanisms in neurons, and how these findings inform new therapies to correct and control splicing defects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".