Mammalian Smaug Is a Translational Repressor That Forms Cytoplasmic Foci Similar to Stress Granules
Bibliographic record
Abstract
Cytoplasmic events depending on RNA-binding proteins contribute to the fine-tuning of gene expression. Sterile alpha motif-containing RNA-binding proteins constitute a novel family of post-transcriptional regulators that recognize a specific RNA sequence motif known as Smaug recognition element (SRE). The Drosophila member of this family, dSmaug, triggers the translational repression and deadenylation of maternal mRNAs by independent mechanisms, and the yeast homologue Vts1 stimulates degradation of SRE-containing messengers. Two homologous genes are present in the mammalian genome. Here we showed that hSmaug 1, encoded in human chromosome 14, represses the translation of reporter transcripts carrying SRE motifs. When expressed in fibroblasts, hSmaug 1 forms cytoplasmic granules that contain polyadenylated mRNA and the RNA-binding proteins Staufen, TIAR, TIA-1, and HuR. Smaug 1 foci are distinct from degradation foci. The murine protein mSmaug 1 is expressed in the central nervous system and is abundant in post-synaptic densities, a subcellular region where translation is tightly regulated by synaptic stimulation. Biochemical analysis indicated that mSmaug 1 is present in synaptoneurosomal 20 S particles. These results suggest a role for mammalian Smaug 1 in RNA granule formation and translation regulation in neurons.
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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 | 0.000 | 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 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".