Regulatory RNAs Involved in Bacterial Antibiotic Resistance
Bibliographic record
Abstract
What Are Small Regulatory RNAs?An increasing number of RNAs have been recently shown to possess regulatory functions similar to those of proteins.In bacteria, these regulatory RNAs are usually noncoding and are short size (50-500 nts) transcripts that are often referred to as small RNAs (sRNAs) [1,2].These sRNAs are synthesized under specific environmental conditions and play a major role in the regulation of various cellular processes (Figure 1) [3].Most of them act via an imperfect antisense base-pairing with their target mRNAs.Duplex formation usually results in inhibition or stimulation of mRNA target translation.In some cases, sRNAs can also bind proteins to influence their activities (e.g., 6S RNA).Compared to protein-dependent mechanisms, sRNAs require less energy, act faster and also allow a coordinated regulation of several targets.Owing to these characteristics, sRNAs allow efficient adaptation of bacteria to their ever-changing environment.Therefore, the possibility exists that some sRNAs may be involved in antibiotic resistance.In this report, we provide evidence that illustrates the growing number of sRNAs that influence bacterial resistance to antibiotics.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".