Post-transcriptional and Post-translational Modifications of Primary Cilia: How to Fine Tune Your Neuronal Antenna
Bibliographic record
Abstract
Primary cilia direct cellular signaling events during brain development and neuronal differentiation. The primary cilium is a dynamic organelle formed in a multistep process termed ciliogenesis that is tightly coordinated with the cell cycle. Genetic alterations, such as ciliary gene mutations, and epigenetic alterations, such as post-translational modifications and RNA processing of cilia related factors, give rise to human neuronal disorders and brain tumors such as glioblastoma and medulloblastoma. This review discusses the important role of genetics/epigenetics, as well as RNA processing and post-translational modifications in primary cilia function during brain development and cancer formation. We summarize mouse and human studies of ciliogenesis and primary cilia activity in the brain, and detail how cilia maintain neuronal progenitor populations and coordinate neuronal differentiation during development, as well as how cilia control different signaling pathways such as WNT, Sonic Hedgehog (SHH) and PDGF that are critical for neurogenesis. Moreover, we describe how post-translational modifications alter cilia formation and activity during development and carcinogenesis, and the impact of missplicing of ciliary genes leading to ciliopathies and cell cycle alterations. Finally, cilia genetic and epigenetic studies bring to light cellular and molecular mechanisms that underlie neurodevelopmental disorders and brain tumors.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".