ArticleChinese medical journal2016
Correlation of Vascular Endothelial Growth Factor Production with Photochemical Reaction-induced Retinal Edema.
Article in Chinese medical journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Concentrations of VEGF and PlGF Decrease in Eyes After Intravitreal Conbercept Injection.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2018Article
- Analysis of Macular and Retinal Nerve Fiber Layer Thickness in Children with Refractory Amblyopia after Femtosecond Laser-assisted LaserChinese medical journal · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRetinal edema is the major complication of retinal vein occlusion and diabetic retinopathy; it can damage visual function by influencing macular region. This study was to establish a rat retinal edema model and explore the related VEGF expression and observe the responses to anti-VEGF drugs in this model.
methodsA rat retinal edema model was established by inducing photochemical reaction using a 532 nm laser after the intravenous injection of Erythrosin B. Immediately after the laser treatment, models were given intravitreal injections of Ranibizumab or Conbercept to inhibit VEGF expression, and the changes of retinal thickness were measured. Retinal edema was observed using fundus photography (FP), optical coherence tomography (OCT), and fluoresce in fundus angiography (FFA) at 0, 1, 2, 4, 7 and 14 days after intervention. The retinal VEGF expression was measured using enzyme-linked immunosorbent assay (ELISA) and western blotting at each time point. The rat retinal edema model was also used to verify the function of anti-VEGF polypeptide ZY1.
resultsBoth retinal edema and vascular leakage were clearly observed at 1, 2 and 4 days after photochemical induction and the retinal thickness increased notably over the same period. The retinal VEGF expression peaked at day 1 and retina became thickening simultaneously. After the interventions, the VEGF expression of the Ranibizumab and Conbercept groups decreased at each time point compared to the edema group (26.90 ± 3.57 vs. 40.29 ± 6.68, F = 31.269 on day 1 and 22.36 ± 1.12 vs. 29.92 ± 0.93 F = 163.789 on day 2, both P < 0.01); the mean RT (278 ± 4 vs. 288 ± 3, F = 134.190 on day 1 and 274 ± 7 vs. 284 ± 6, F = 64.367 on day 2, both P < 0.05) and vascular leakage in these groups also decreased. The same results were observed in the ZY1 group, particularly at day 2 (P < 0.05).
conclusionsThis retinal edema model induced by a photochemical reaction is reliable and repeatable. Induced edema increases expression of VEGF. This model can be used to test new drugs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.