Trans-Acting Effectors Versus RNA Cis-Elements: A Tightly Knit Regulatory Mesh
Bibliographic record
Abstract
Prokaryotic organisms often react instantly to environmental variations to ensure their survival. They can achieve this by rapidly and specifically modulating translation, the critical step of protein synthesis. The translation machinery responds to an array of cis-acting elements, located on the RNA transcript, which dictate the fate of mRNAs. These cis-encoded elements, such as RNA structures or sequence motifs, interact with a variety of regulators, among them small regulatory RNAs. These small regulatory RNAs (sRNAs) are especially effective at modulating translation initiation through their interaction with cis-encoded mRNA elements. Here, through selected examples of canonical and non-canonical regulatory events, we demonstrate the intimate connection between mRNA cis-encoded features and sRNA-dependent translation regulation. We also address how sRNA-based mechanistic studies can drive the discovery of new roles for cis-elements. Finally, we briefly overview the challenges of using translation regulation by synthetic regulators as a tool.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".