Bibliographic record
Abstract
Ocular neovascular disease (OND), characterized by the aberrant formation of immature blood vessels, is the leading cause of vision impairment and blindness. It is important to find effective ways to diagnose and treat these diseases. Circular RNA (circRNA) is a group of endogenous non-coding RNA that play a crucial role in regulating different biological processes. Due to their close association with ocular disease and angiogenesis, circRNAs have become a hotspot in OND research. In this review, we intensively investigate the possibility of using circRNAs in the management of ONDs. In general, angiogenesis is divided into five phases. On the basis of these five steps, we describe the potential of using circRNAs by introducing how they regulate angiogenesis. Subsequently, the interactions between circRNAs and ONDs, including pterygium, corneal neovascularization, age-related macular degeneration, diabetic retinopathy, and retinopathy of prematurity, are analyzed in detail. We also introduce the potential use of circRNAs as OND diagnostic biomarkers. Finally, we summarize the prospects of using circRNAs as a potential strategy in OND management. The gaps in recent research are also pointed out with the purpose of promoting the introduction of circRNAs into clinical applications.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".