Circular RNAs constitute an inherent gene regulatory axis in the mammalian eye and brain
Bibliographic record
Abstract
Circular RNAs (circRNAs) are being hailed as a newly rediscovered class of covalently closed transcripts that are produced via alternative, noncanonical pre-mRNA back-splicing events. These single-stranded RNA molecules have been identified in organisms ranging from the worm (Cortés-López et al. 2018. BMC Genomics, 19: 8; Ivanov et al. 2015. Cell Rep. 10: 170–177) to higher eukaryotes (Yang et al. 2017. Cell Res. 27: 626–641) to plants (Li et al. 2017. Biochem. Biophys. Res. Commun. 488: 382–386). At present, research on circRNAs is an active area because of their diverse roles in development, health, and diseases. Partly because their circularity makes them resistant to degradation, they hold great promise as unique biomarkers for ocular and central nervous system (CNS) disorders. We believe that further work on their applications could help in developing them as “first-in-class” diagnostics, therapeutics, and prognostic targets for numerous eye conditions. Interestingly, many circRNAs play key roles in transcriptional regulation by acting as miRNAs sponges, meaning that they serve as master regulators of RNA and protein expression. Since the retina is an extension of the brain and is part of the CNS, we highlight the current state of circRNA biogenesis, properties, and function and we review the crucial roles that they play in the eye and the brain. We also discuss their regulatory roles as miRNA sponges, regulation of their parental genes or linear mRNAs, translation into micropeptides or proteins, and responses to cellular stress. We posit that future advances will provide newer insights into the fields of RNA metabolism in general and diseases of the aging eye and brain in particular. Furthermore, in keeping pace with the rapidly evolving discipline of RNA“omics”-centered metabolism and to achieve uniformity among researchers, we recently introduced the term “cromics” (circular ribonucleic acids based omics) (Singh et al. 2018. Exp. Eye Res. 174: 80–92).
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".