Wedelolactone Attenuates N-methyl-N-nitrosourea-Induced Retinal Neurodegeneration through Suppression of the AIM2/CASP11 Pathway
Bibliographic record
Abstract
N-methyl-N-nitrosourea (NMU) is widely used to model oxidative stress and inflammation mediated retinal neurodegeneration. Wedelolactone (WD) is known to have antioxidant, anti-inflammatory, and neuroprotective roles. This study tested the therapeutic potential of WD in NMU-induced retinal neurodegeneration and investigated the underlying mechanisms in mice. NMU (40 mg/kg) was injected intraperitoneally into C57BL/6J mice with/without an intravitreal injection of WD (1 μL/eye, 200 μM). Seven days later, retinal function and structure were evaluated by electroretinography (ERG) and Spectral Domain Optical Coherence Tomography (SD-OCT). The expression of inflammasome components (Aim2, Caspase 1/11, and Il1b/Il18) in the total retina lysate was evaluated by RT-qPCR. In vitro, 661W photoreceptor cells were transfected with synthetic double-strand DNA (Poly(dA:dT)) with/without WD pre-incubation. The aim2-related inflammasome expression was evaluated by RT-qPCR and immunocytochemistry. The production of IL18 was measured by ELISA. NMU treatment significantly impaired A- and B-wave response (ERG) and reduced neuroretina thickness (OCT). This was significantly attenuated upon intravitreal injection of WD. The expression of Aim2, ACasp1, and Casp11 was increased in the retina from NMU-treated mice, and this was prevented by WD treatment. Transfection of Poly(dA:dT) upregulated Aim2, Casp11, and Il18 expression in 661W cells. WD prevented their upregulation and reduced IL18 production. Aim2 inflammasome activation is critically involved in NMU-induced retinal neurodegeneration and WD can protect the retina particularly through the suppression of this inflammasome-linked pathway.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".