Bibliographic record
Abstract
It has long been known that gene regulation is mostly achieved via protein-nucleic acid interactions. However, the role of RNA factors in gene control has been recently growing given the implication of new RNA-based gene regulation mechanisms such as microRNAs and related short-interfering RNAs gene expression inactivation mechanisms. Recent studies have demonstrated that the involvement of RNA in fundamental gene-control processes is even more extensive. Prokaryotic messenger RNAs carry highly structured domains known as riboswitches within their 5'-untranslated regions. Each riboswitch is able to bind with high specificity their cellular target metabolite, without the involvement of a protein cofactor. Upon metabolite binding, the messenger RNA undergoes structural change that will ultimately lead to the modulation of its genetic expression. Riboswitches can alter gene expression at the level of transcription attenuation or translation initiation, and can up- or down-regulate gene expression by harnessing appropriate changes in the mRNA structure. Here, we provide an overview of the adenine riboswitch, one of the smallest riboswitch and one of the few that activates gene expression upon ligand binding. Several crystal structures have been obtained for the ligand-binding domain of this riboswitch providing us with an unprecedented glimpse about how riboswitches use their ligand to regulate gene expression. Moreover, mechanistic studies have recently shed light on the transcriptional regulation mechanisms of the adenine riboswitch suggesting that riboswitches may rely on the kinetics of ligand binding and the speed of RNA transcription, rather than simple ligand affinity. Riboswitches are particularly interesting because RNA-ligand interactions are potentially very important in the elaboration of antimicrobial agents.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".