Therapeutic potential of omega-3 fatty acids supplementation in a mouse model of dry macular degeneration
Bibliographic record
Abstract
Purpose To evaluate the therapeutic effects of omega-3 (ω-3) and omega-6 (ω-6) fatty acids in the CCL2−/− model of dry age-related macular degeneration (AMD). The blood level of eicosapentaenoic acid (EPA) and arachidonic acid (AA) served to adjust the treatment dosage (AA/EPA=1–1.5). Methods Nine-month-old animals were allocated to different groups: (A) C57BL/6 untreated , (B) CCL2−/− untreated, (C) CCL2−/− treated with ω-3+ω-6, and (D) CCL2−/− treated with ω-3. Treatment was daily administered by gavage for 3 months. Fatty acids analysis was performed and retinas were histologically examined. Three-month-old wild type mice were used for comparison purposes. Real-time PCR and Western blot were performed for retinal inflammatory mediators. Results Increased EPA and decreased AA levels were observed in both blood and retinas in the treatment groups. The outer nuclear layer thickness was increased in groups C (45.0±3.9 µm) and D (62.8±4.9 µm), compared with groups B (65.6±3.0 µm) and A (71.1±4.2 µm), and in younger mice, it was 98.0±3.9 µm. A decrease in NF-κB expression was noted in the treatment groups. Interleukin (IL) 18 protein levels demonstrated a significant reduction in the ω-3-treated group only. Conclusion Supplementation with ω-3+ω-6 or ω-3 alone (AA/EPA=1–1.5) suggests a protective mechanism in the CCL2−/− animal model of dry AMD, with a more beneficial effect when ω-3 are used alone. Our findings indicated that inflammation is not the only determining factor; perhaps a regenerative process might be involved following administration of ω-3 fatty acids.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".