Nutraceuticals for Diabetic Retinopathy: Recent Advances and Novel Delivery Systems
Bibliographic record
Abstract
Diabetic retinopathy (DR) is a major vision-threatening disease among the working-age population worldwide. Present therapeutic strategies such as intravitreal injection of anti-VEGF and laser photocoagulation mainly target proliferative DR. However, there is a need for early effective management in patients with early stage of DR before its progression into the more severe sight-threatening proliferative stage. Nutraceuticals, natural functional foods with few side effects, have been proposed to be beneficial in patients with DR. Over the decades, many studies, either in vitro or in vivo, have demonstrated the advantages of a number of nutraceuticals in DR with their antioxidative, anti-inflammatory, neuroprotective, or vasoprotective effects. However, only a few clinical trials have been conducted, and their outcomes varied. The low bioavailability and instability of many nutraceuticals have indeed hindered their utilization in clinical use. In this context, nanoparticle carriers have been developed to deliver nutraceuticals and to improve their bioavailability. Despite its preclinical nature, research of interventive nutraceuticals for DR may yield promising information in their clinical applications.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".