Nucleolar Enrichment of Brain Proteins with Critical Roles in Human Neurodevelopment
Bibliographic record
Abstract
To study nucleolar involvement in brain development, the nuclear and nucleolar proteomes from the rat cerebral cortex at postnatal day 7 were analyzed using LC-MS/iTRAQ methodology. Data of the analysis are available via ProteomeXchange with identifier PXD002188. Among 504 candidate nucleolar proteins, the overrepresented gene ontology terms included such cellular compartmentcategories as "nucleolus", "ribosome" and "chromatin". Consistent with such classification, the most overrepresented functional gene ontology terms were related to RNA metabolism/ribosomal biogenesis, translation, and chromatin organization. Sixteen putative nucleolar proteins were associated with neurodevelopmental phenotypes in humans. Microcephaly and/or cognitive impairment were the most common phenotypic manifestations. Although several such proteins have links to ribosomal biogenesis and/or genomic stability/chromatin structure (e.g. EMG1, RPL10, DKC1, EIF4A3, FLNA, SMC1, ATRX, MCM4, NSD1, LMNA, or CUL4B), others including ADAR, LARP7, GTF2I, or TCF4 have no such connections known. Although neither the Alazami syndrome-associated LARP7nor the Pitt-Hopkins syndrome-associated TCF4 were reported in nucleoli of non-neural cells, in neurons, their nucleolar localization was confirmed by immunostaining. In cultured rat hippocampal neurons, knockdown of LARP7 reduced both perikaryal ribosome content and general protein synthesis. Similar anti-ribosomal/anti-translation effects were observed after knockdown of the ribosomal biogenesis factor EMG1 whose deficiency underlies Bowen-Conradi syndrome. Finally, moderate reduction of ribosome content and general protein synthesis followed overexpression of two Pitt-Hopkins syndrome mutant variants of TCF4. Therefore, dysregulation of ribosomal biogenesis and/or other functions of the nucleolus may disrupt neurodevelopment resulting in such phenotypes as microcephaly and/or cognitive impairment.
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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) | 0.000 | 0.000 |
| 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".