Catalpol Protects Against Retinal Ischemia Through Antioxidation, Anti-Ischemia, Downregulation of β-Catenin, VEGF, and Angiopoietin-2: In Vitro and In Vivo Studies
Bibliographic record
Abstract
Retinal ischemic disorders present significant threats to vision, characterized by inadequate blood supply oxygen–glucose deprivation (OGD), oxidative stress, and cellular injury, often resulting in irreversible injury. Catalpol, an iridoid glycoside derived from Rehmannia glutinosa, has demonstrated antioxidative and neuroprotective effects. This study aimed at investigating the protective effects and mechanisms of catalpol against oxidative stress or OGD in vitro and retinal ischemia in vivo, focusing on the modulation of key biomarkers of retinal ischemia, including HIF-1α, vascular endothelial growth factor (VEGF), angiopoietin-2, MCP-1, and the Wnt/β-catenin pathway. Cellular viability was assessed using retinal ganglion cell-5 (RGC-5) cells cultured in DMEM; a 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay was performed. H2O2 (1 mM)/OGD was utilized. Vehicle or different catalpol concentrations were administered 15 min before the ischemic-like insults. The Wistar rat eyes’ intraocular pressure was increased to 120 mmHg for 60 min to induce retinal ischemia. Intravitreous injections of catalpol (0.5 or 0.25 mM), Wnt inhibitor DKK1 (1 μg/4 μL), anti-VEGF Lucentis (40 μg/4 μL), or anti-VEGF Eylea (160 μg/4 μL) were administered to the rats’ eyes 15 min before or after retinal ischemia. Electroretinogram (ERG), fluorogold retrograde labeling RGC, Western blotting, ELISA, RT-PCR, and TUNEL were utilized. In vitro, both H2O2 and OGD models significantly (p < 0.001/p < 0.001; H2O2 and OGD) induced oxidative stress/ischemic-like insults, decreasing RGC-5 cell viability (from 100% to 55.14 ± 2.19%/60.84 ± 4.57%). These injuries were insignificantly (53.85 ± 1.28% at 0.25 mM)/(63.46 ± 3.30% at 0.25 mM) and significantly (p = 0.003/p = 0.012; 64.15 ± 2.41%/77.63 ± 8.59% at 0.5 mM) altered by the pre-administration of catalpol, indicating a possible antioxidative and anti-ischemic effect of 0.5 mM catalpol. In vivo, catalpol had less effect at 0.25 mM for ERG amplitude ratio (median [Q1, Q3] 14.75% [12.64%, 20.48%]) and RGC viability (mean ± SE 63.74 ± 5.13%), whereas (p < 0.05 and p < 0.05) at 0.5 mM ERG’s ratio (35.43% [24.35%, 43.08%]) and RGC’s density (74.34 ± 5.10%) blunted the ischemia-associated significant (p < 0.05 and p < 0.01) reduction in ERG b-wave amplitude (6.89% [4.24%, 10.40%]) and RGC cell viability (45.64 ± 3.02%). Catalpol 0.5 mM also significantly protected against retinal ischemia supported by the increased amplitude ratio of ERG a-wave and oscillatory potential, along with recovering a delayed a-/b-wave response time ratio. When contrasted with DKK1 or Lucentis, catalpol exhibited similar protective effects against retinal ischemia via significantly (p < 0.05) blunting the ischemia-induced overexpression of β-catenin, VEGF, or angiopoietin-2. Moreover, ischemia-associated significant increases in apoptotic cells in the inner retina, inflammatory biomarker MCP-1, and ischemic indicator HIF-1α were significantly nullified by catalpol. Catalpol demonstrated antiapoptotic, anti-inflammatory, anti-ischemic (in vivo retinal ischemia or in vitro OGD), and antioxidative (in vitro) properties, counteracting retinal ischemia via suppressing upstream Wnt/β-catenin and inhibiting downstream HIF-1α, VEGF, and angiopoietin-2, together with its decreasing TUNEL apoptotic cell number and inflammatory MCP-1 concentration.
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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".