Neuroprotective and Anti-Inflammatory Effects of Rhus coriaria Extract in a Mouse Model of Ischemic Optic Neuropathy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Modulating oxidative stresses and inflammation can potentially prevent or alleviate the pathological conditions of diseases associated with the nervous system, including ischemic optic neuropathy. In this study we evaluated the anti-neuroinflammatory and neuroprotective activities of Rhus coriaria (R. coriaria) extract in vivo. The half maximal inhibitory concentration (IC50) for DPPH, ABTS and β–carotene were 6.79 ± 0.009 µg/mL, 10.94 ± 0.09 µg/mL, and 6.25 ± 0.06 µg/mL, respectively. Retinal ischemia was induced by optic nerve crush injury in albino Balb/c mice. The anti-inflammatory activity of ethanolic extract of R. coriaria (ERC) and linoleic acid (LA) on ocular ischemia was monitored using Fluorescence Molecular Tomography (FMT). Following optic nerve crush injury, the mice treated with 400 mg/kg of ERC and LA exhibited an 84.87% and 86.71% reduction of fluorescent signal (cathepsin activity) respectively. The results of this study provide strong scientific evidence for the neuroprotective activity of the ERC, identifying LA as one of the main components responsible for the effect. ERC may be useful and worthy of further development for its adjunctive utilization in the treatment of optic neuropathy.
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.
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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it