Investigation of anti-angiogenic effects of 3,4 dihydroxyphenyl ethanol in macular degeneration
Bibliographic record
Abstract
Age Related Macular Degeneration (AMD) is the most common cause of vision loss among the elderly in developed countries. It occurs primarily in individuals over the age of 50. Currently, 1.75 million people in the US suffer from the advanced form of AMD. AMD is characterised as an abnormality of retinal pigment epithelium (RPE) and/or choroid leading to photoreceptor degeneration of central retina (macula). There are two forms of AMD: Dry AMD (characterized by the build-up of drusen between the choroid and RPE layer resulting in RPE and photoreceptor cell death) and Wet AMD (characterized by abnormal blood vessel growth from the choroid into the retinal pigment epithelium). Current pharmacotherapies in AMD include anti-angiogenics (anti-VEGF) such as Macugen, Avastin, and Lucentis. Thus current research is focusing on trying to form combination therapies (such as anti-VEGF and other agents) to achieve better clinical efficacy. We will be investigating the compound 3,4 dihydroxyphenyl ethanol (DPE), which is a polyphenol present in virgin olive oil known to have antioxidant, anti-angiogenic, anti-inflammatory, and antithrombotic properties. Previous studies have investigated DPE and its ability to prevent cardiovascular diseases and treat different types of cancer. We believe that DPE can reduce angiogenic signalling in the macula. Our objective is to assess the potential utility of DPE as a therapeutic agent in combination with anti-VEGF drugs. ARPE-19 cells were treated with 0.25 mg/ml bevacizumab to study the effects of bevacizumab on the secretion of pro-angiogenic cytokines. The cells were then treated with 100M DPE for 24 hours in culture in both normoxic and CoCl₂-simulated hypoxic conditions. RPE cells were also treated with the combination of DPE and bevacizumab in order to determine the effectiveness of the combination therapy on RPE cells. Media was then harvested after 24 hours for sandwich ELISA-based angiogenesis arrays. The secretion of the following 10 pro-angiogenic cytokines was measured: Angiogenin, ANG-2, EGF, bFGF, HB-EGF, PDGF-BB, Leptin, PlGF, HGF, and VEGF-A. The secretion of three (Angiogenin, ANG-2, and EGF) was increased following treatment with bevacizumab, however only Angiogenin was significant. Angiogenin and VEGF-A were secreted under normoxia, and significantly increased under CoCl₂-simulated hypoxia, whereas ANG-2, HB-EGF, and PlGF were increased under hypoxia. Following treatment with DPE, levels of Angiogenin and VEGF-A were significantly reduced under normoxia, whereas secretion of all 5 secreted cytokines were significantly decreased under hypoxia. The combination of DPE and bevacizumab significantly reduced the secretion of Angiogenin under both normoxic and hypoxic conditions compared to bevacizumab alone. Considering the implications of angiogenesis in AMD, these studies could provide the framework for future studies to further investigate a potential therapeutic role for DPE. DPE may reduce the secretion of pro-angiogenic cytokines, such as Angiogenin, that are up-regulated following treatment with bevacizumab as a possible compensatory mechanism. Therefore, the combination of DPE and bevacizumab may represent a valuable therapeutic option for the wet form of AMD.
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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 | 0.000 |
| 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".