Mimicry, deception and competition: The life of competing endogenous RNAs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Since their discovery, small regulatory RNAs (sRNAs) were thought to be regulated exclusively at the transcriptional level. However, accumulating data from recent reports indicate that posttranscriptional signals can also modulate the function and stability of sRNAs. One of these posttranscriptional signals are competing endogenous RNAs (ceRNAs). Commonly called RNA sponges, ceRNAs can effectively sequester sRNAs and prevent them from binding their cognate target messenger RNAs (mRNAs). Subsequently, they prevent sRNA-dependent regulation of translation and stability of mRNA targets. While some ceRNAs seem to be expressed constitutively, others are intricately regulated according to environmental conditions. The outcome of ceRNA binding to a sRNA reaches beyond simple sequestration. Various effects observed on sRNA functions extend from reducing transcriptional noise to promote RNA turnover. Here, we present a historical perspective of the discovery of ceRNAs in eukaryotic organisms and mainly focus on the synthesis and function of select, well-described, ceRNAs in bacterial cells. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Small Molecule-RNA Interactions Translation > Translation Regulation RNA Turnover and Surveillance > Regulation of RNA Stability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it