Anti-VEGF reduces inflammatory features in macular edema secondary to retinal vein occlusion

Relationship between retinal volume changes and the prognosis of BRVO-ME treated with ranibizumab

Background

This study aimed to evaluate the efficacy of ranibizumab for the treatment of macular edema secondary to branch retinal vein occlusion (BRVO-ME), changes in retinal volume and central retinal thickness (CRT) before and after therapy, and the connection between visual prognosis and changes in retinal volume.

Methods

The 120 patients(121 eyes) of BRVO-ME were recruited from July 2020 to October 2022 at the Affiliated Hospital of Weifang Medical University. The clinical data of patients were retrospectively examined for changes in best-corrected visual acuity (BCVA), retinal volume, and CRT at 1 day, 1 week, 1 month, 3 months, 6 months and 1year after treatment.

Findings

Visual acuity improved gradually and became steady approximately 1 months after treatment, whereas retinal volume decreased gradually in both the outer and full layers and stabilized around 6 month after treatment. The decline in retinal volume and CRT was more visible in the deeper layers than in the inner levels. A higher correlation was observed between retinal volume and BCVA than between CRT and BCVA. BCVA after one year of treatment had a high correlation with baseline outer retinal volume.

Interpretation

Treatment of BRVO-ME with ranibizumab is highly effective, and the recovery of visual function was depends more on early treatment. The outer retina is the major site of edema. Changes in retinal volume may serve as a better predictor of visual prognosis than changes in CRT. Baseline ourter retinal volume is correlated with long-term visual prognosis.

Modified Guo-Min decoction ameliorates PM2.5-induced lung injury by inhibition of PI3K-AKT and MAPK signaling pathways

BACKGROUND/PURPOSE

Exposure to particles with an aerodynamic diameter of ≤2.5 μm (PM2.5) increased various lung diseases, which lack effective treatment. Massive evidence links PM2.5 to the development of allergic lung diseases like asthma. Modified Guo-Min Decoction (MGMD) is a traditional Chinese formula for allergic diseases. However, whether MGMD could improve PM2.5-induced lung injury and the underlying mechanism remain unclear and we aimed to explore.

STUDY DESIGN/METHODS

Male Wistar rats (200-220 g) were intratracheally instilled of PM2.5 suspension daily for 4 weeks to establish PM2.5-induced lung injury model. MGMD (2.1 g/kg) treatment by gavage was started 1 week before, at the same time or 1 week after the instillation of PM2.5 suspension, namely the pre-, sync- or post-administration groups. HE and Masson staining were used to observe morphological changes. Immunohistochemistry staining was used to detect macrophage and neutrophil infiltration. The levels of inflammatory cytokines in the bronchoalveolar lavage fluid were detected by ELISA. The main components of MGMD were detected by UHPLC-LTQ-Orbitrap MSn. Network pharmacology was used to identify the key targets mediating the effect of MGMD in treating PM2.5-induced lung injury. Changes in the expression of target proteins were examined by western blot. In-vitro experiments were carried out in Beas2b cells to evaluate the protective effect and mechanism of MGMD against PM2.5 induced injury.

RESULTS

Exposure to PM2.5 suspension resulted in disarrangement of tracheal epithelium, neutrophil and M1 macrophage infiltration and collagen deposition, and significantly increased IgE, IL-1β and IL-17 secretion and NLRP3 expression, which were inhibited by MDMD treatment and pre-MGMD treatment showed the best effect. By UHPLC-LTQ-Orbitrap MSn, 46 main compounds were identified in MGMD. Using network pharmacology approach, we found MGMD attenuate PM2.5-induced lung damage by targeting 216 genes, and PPI network, GO and KEGG analysis all indicated that PI3K-AKT and MAPK pathways were important. Western blot showed that PM2.5 suspension exposure increased PI3K, AKT, ERK and JNK phosphorylation, which were reversed by MGMD intervention significantly. In vitro, the viability of Beas2b cells was significantly decreased after PM2.5 suspension exposure, and was obviously upregulated after MGMD-containing serum or LY294002 treatment.

CONCLUSION

The present study demonstrated that MGMD could improve PM2.5-induced lung injury through reducing inflammation and pulmonary fibrosis, which was probably mediated by inhibition of the PI3K-AKT and MAPK signaling pathways, and NLRP3 inflammasome. The results of this study support and provide scientific evidence for the clinical application of MGMD on PM2.5-induced lung injury. Pre-treatment, sync-treatment, and post-treatment is the highlight of this study.

Optical coherence tomography angiography for macular microvessels in ischemic branch retinal vein occlusion treated with conbercept: predictive factors for the prognosis

AIM

To evaluate the predicative factors of visual prognosis using optical coherence tomography angiography (OCTA) in ischemic branch retinal vein occlusion (BRVO) patients with macular edema (ME) after anti-vascular endothelial growth factor (VEGF) treatment.

METHODS

In this retrospective analysis, data from 60 patients (60 eyes) with a definite diagnosis of ischemic BRVO with ME by fundus fluorescein angiography (FFA) were studied. The eyes with ME according to spectral domain optical coherence tomography (SD-OCT) underwent intravitreal conbercept (IVC) and 3+pro re nata (PRN) regimen. The injection times were recorded. Two weeks after injection, fundus laser photocoagulation was performed in the non-perfusion area of the retina. The patients were followed up once a month for 6mo. The best-corrected visual acuity (BCVA), foveal avascular zone (FAZ), and A-circularity index (AI), at 6mo and the baseline were compared.

RESULTS

All patients showed significant improvement in BCVA from 0.82±0.32 to 0.39±0.11 logMAR (P<0.001). The mean central macular thickness (CMT) significantly decreased from 476.22±163.54 to 298.66±109.23 µm. Both the FAZ area and AI at 6mo were significantly higher than those at the baseline: the FAZ area increased (0.38±0.02 vs 0.39±0.02 mm2, P<0.05); the AI increased (1.27±0.02 vs 1.31±0.01, P=0.000). The baseline BCVA showed a significantly positive correlation with the baseline FAZ area, FAZ perimeter (PERIM) and AI, final visual gain (FVG) and injection times, respectively (P<0.001). FVG showed a significantly negative correlation with the FAZ area, PERIM, AI and injection times, but a significantly positive correlation with vessel densities (VDs) 300 µm area around FAZ (FD-300; P<0.001). Injection times was positively correlated with the baseline FAZ area, and AI, but inversely correlated with the baseline FD-300 (P<0.001). However macular ischemia was noted in 5 cases during follow-up.

CONCLUSION

Using OCTA to observe macular ischemia and quantify parameters can better predict the final visual prognosis of patients before treatment. The changes in FAZ parameters may influence the visual prognosis and injection times.

Automatic Diagnosis of Different Types of Retinal Vein Occlusion Based on Fundus Images

Retinal vein occlusion (RVO) is the second common cause of blindness following diabetic retinopathy. The manual screening of fundus images to detect RVO is time consuming. Deep-learning techniques have been used for screening RVO due to their outstanding performance in many applications. However, unlike other images, medical images have smaller lesions, which require a more elaborate approach. To provide patients with an accurate diagnosis, followed by timely and effective treatment, we developed an intelligent method for automatic RVO screening on fundus images. Swin Transformer learns the hierarchy of low-to high-level features like the convolutional neural network. However, Swin Transformer extracts features from fundus images through attention modules, which pay more attention to the interrelationship between the features and each other. The model is more universal, does not rely entirely on the data itself, and focuses not only on local information but has a diffusion mechanism from local to global. To suppress overfitting, we adopt a regularization strategy, label smoothing, which uses one-hot to add noise to reduce the weight of the categories of true sample labels when calculating the loss function. The choice of different models using a 5-fold cross-validation on our own datasets indicates that Swin Transformer performs better. The accuracy of classifying all datasets is 98.75 ± 0.000, and the accuracy of identifying MRVO, CRVO, BRVO, and normal, using the method proposed in the paper, is 94.49 ± 0.094, 99.98 ± 0.015, 98.88 ± 0.08, and 99.42 ± 0.012, respectively. The method will be useful to diagnose RVO and help decide grade through fundus images, which has the potency to provide patients with further diagnosis and treatment.

Automatic Segmentation of Hyperreflective Foci in OCT Images Based on Lightweight DBR Network

Hyperreflective foci (HF) reflects inflammatory responses for fundus diseases such as diabetic macular edema (DME), retina vein occlusion (RVO), and central serous chorioretinopathy (CSC). Shown as high contrast and reflectivity in optical coherence tomography (OCT) images, automatic segmentation of HF in OCT images is helpful for the prognosis of fundus diseases. Previous traditional methods were time-consuming and required high computing power. Hence, we proposed a lightweight network to segment HF (with a speed of 57 ms per OCT image, at least 150 ms faster than other methods). Our framework consists of two stages: an NLM filter and patch-based split to preprocess images and a lightweight DBR neural network to segment HF automatically. Experimental results from 3000 OCT images of 300 patients (100 DME,100 RVO, and 100 CSC) revealed that our method achieved HF segmentation successfully. The DBR network had the area under curves dice similarity coefficient (DSC) of 83.65%, 76.43%, and 82.20% in segmenting HF in DME, RVO, and CSC on the test cohort respectively. Our DBR network achieves at least 5% higher DSC than previous methods. HF in DME was more easily segmented compared with the other two types. In addition, our DBR network is universally applicable to clinical practice with the ability to segment HF in a wide range of fundus diseases.

Suppressing Inflammation for the Treatment of Diabetic Retinopathy and Age-Related Macular Degeneration: Dazdotuftide as a Potential New Multitarget Therapeutic Candidate

Diabetic retinopathy (DR) and age-related macular degeneration (AMD) are major causes of blindness globally. The primary treatment option for DME and neovascular AMD (nAMD) is anti-vascular endothelial growth factor (VEGF) compounds, but this treatment modality often yields insufficient results, and monthly injections can place a burden on the health system and patients. Although various inflammatory pathways and mediators have been recognized as key players in the development of DR and AMD, there are limited treatment options targeting these pathways. Molecular pathways that are interlinked, or triggers of multiple inflammatory pathways, could be promising targets for drug development. This review focuses on the role of inflammation in the pathogenesis of DME and AMD and presents current anti-inflammatory compounds, as well as a potential multitarget anti-inflammatory compound (dazdotuftide) that could be a candidate treatment option for the management of DME and AMD.