MicroRNAs-Based Therapeutic Strategy for Virally Induced Diseases
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
MicroRNAs (miRNAs) are endogenous, short, double-stranded and noncoding RNA molecules that have been identified in a variety of organisms and certain viruses. This group of new molecules is transcribed mainly from the introns and/or exons or intergenic regions and plays important regulatory roles in development and gene expression. Mature miRNAs are typically 20-24 nucleotides in length and regulate target mRNAs post transcriptionally by interactions with partially mismatched sequences in the 3'untraslated regions of these messengers. These interactions result in the suppression of translation or degradation of target mRNAs. At the present, although the biological functions of miRNAs are not completely revealed, a growing body of evidence implicates that miRNA pathway is a new mechanism of gene regulation in both normal and diseased conditions and therefore investigation of miRNA biogenesis and function may add new tools for gene functional study and drug development. In this article, we will briefly review the structure, biogenesis and basic mechanism of action of miRNAs identified in higher organisms and viruses and then focus on the recent progress in research for drug development using the miRNA pathway as a strategy. Particularly, we will discuss the advance, challenge and future directions on antiviral drug development using miRNA as a target or a gene silencing tool for the treatment of viral infections.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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 it