Finding influential nodes in complex networks based on Kullback-Leibler model within the neighborhood.

As a research hot topic in the field of network security, the implementation of machine learning, such as federated learning, involves information interactions among a large number of distributed network devices. If we regard these distributed network devices and connection relationships as a complex network, we can identify the influential nodes to find the crucial points for optimizing the imbalance of the reliability of devices in federated learning system. This paper will analyze the advantages and disadvantages of existing algorithms for identifying influential nodes in complex networks, and propose a method from the perspective of information dissemination for finding influential nodes based on Kullback-Leibler divergence model within the neighborhood (KLN). Firstly, the KLN algorithm removes a node to simulate the scenario of node failure in the information dissemination process. Secondly, KLN evaluates the loss of information entropy within the neighborhood after node removal by establishing the KL divergence model. Finally, it assesses the damage influence of the removed node by integrating the network attributes and KL divergence model, thus achieving the evaluation of node importance. To validate the performance of KLN, this paper conducts an analysis and comparison of its results with those of 11 other algorithms on 10 networks, using SIR model as a reference. Additionally, a case study was undertaken on a real epidemic propagation network, leading to the proposal of management and control strategies for daily protection based on the influential nodes. The experimental results indicate that KLN effectively evaluates the importance of the removed node using KL model within the neighborhood, and demonstrate better accuracy and applicability across networks of different scales.

TMM-Nets: Transferred Multi- to Mono-Modal Generation for Lupus Retinopathy Diagnosis.

Rare diseases, which are severely underrepresented in basic and clinical research, can particularly benefit from machine learning techniques. However, current learning-based approaches usually focus on either mono-modal image data or matched multi-modal data, whereas the diagnosis of rare diseases necessitates the aggregation of unstructured and unmatched multi-modal image data due to their rare and diverse nature. In this study, we therefore propose diagnosis-guided multi-to-mono modal generation networks (TMM-Nets) along with training and testing procedures. TMM-Nets can transfer data from multiple sources to a single modality for diagnostic data structurization. To demonstrate their potential in the context of rare diseases, TMM-Nets were deployed to diagnose the lupus retinopathy (LR-SLE), leveraging unmatched regular and ultra-wide-field fundus images for transfer learning. The TMM-Nets encoded the transfer learning from diabetic retinopathy to LR-SLE based on the similarity of the fundus lesions. In addition, a lesion-aware multi-scale attention mechanism was developed for clinical alerts, enabling TMM-Nets not only to inform patient care, but also to provide insights consistent with those of clinicians. An adversarial strategy was also developed to refine multi- to mono-modal image generation based on diagnostic results and the data distribution to enhance the data augmentation performance. Compared to the baseline model, the TMM-Nets showed 35.19% and 33.56% F1 score improvements on the test and external validation sets, respectively. In addition, the TMM-Nets can be used to develop diagnostic models for other rare diseases.

Enhancing fractalkine/CX3CR1 signalling pathway can reduce neuroinflammation by attenuating microglia activation in experimental diabetic retinopathy.

The concept of diabetic retinopathy (DR) has been extended from microvascular disease to neurovascular disease in which microglia activation plays a remarkable role. Fractalkine (FKN)/CX3CR1 is reported to regulate microglia activation in central nervous system diseases. To characterize the effect of FKN on microglia activation in DR, we employed streptozotocin-induced diabetic rats, glyoxal-treated R28 cells and hypoxia-treated BV2 cells to mimic diabetic conditions and explored retinal neuronal apoptosis, reactive oxygen species (ROS), as well as the expressions of FKN, Iba-1, TSPO, NF-κB, Nrf2 and inflammation-related cytokines. The results showed that FKN expression declined with diabetes progression and in glyoxal-treated R28 cells. Compared with normal control, retinal microglia activation and inflammatory factors surged in both diabetic rat retinas and hypoxia-treated microglia, which was largely dampened by FKN. The NF-κB and Nrf2 expressions and intracellular ROS were up-regulated in hypoxia-treated microglia compared with that in normoxia control, and FKN significantly inhibited NF-κB activation, activated Nrf2 pathway and decreased intracellular ROS. In conclusion, the results demonstrated that FKN deactivated microglia via inhibiting NF-κB pathway and activating Nrf2 pathway, thus to reduce the production of inflammation-related cytokines and ROS, and protect the retina from diabetes insult.

Anti-VEGF therapy prevents Müller intracellular edema by decreasing VEGF-A in diabetic retinopathy.

BACKGROUND: Although vascular endothelial growth factor A (VEGF-A) is known to play a key role in causing retinal edema, whether and how VEGF-A induces intracellular edema in the retina still remains unclear. METHODS: Sprague-Dawley rats were rendered diabetic with intraperitoneal injection of streptozotocin. Intravitreal injection of ranibizumab was performed 8 weeks after diabetes onset. rMC-1 cells (rat Müller cell line) were treated with glyoxal for 24 h with or without ranibizumab. The expression levels of inwardly rectifying K+ channel 4.1 (Kir4.1), aquaporin 4 (AQP4), Dystrophin 71 (Dp71), VEGF-A, glutamine synthetase (GS) and sodium-potassium-ATPase (Na+-K+-ATPase) were examined using Western blot. VEGF-A in the supernatant of the cell culture was detected with ELISA. The intracellular potassium and sodium levels were detected with specific indicators. RESULTS: Compared with normal control, protein expressions of Kir4.1 and AQP4 were down-regulated significantly in diabetic rat retinas, which were prevented by ranibizumab. The above changes were recapitulated in vitro. Similarly, the intracellular potassium level in glyoxal-treated rMC-1 cells was increased, while the intracellular sodium level and Na+-K+-ATPase protein level remained unchanged, compared with control. However, ranibizumab treatment decreased intracellular sodium, but not potassium. CONCLUSION: Ranibizumab protected Müller cells from diabetic intracellular edema through the up-regulation of Kir4.1 and AQP4 by directly binding VEGF-A. It also caused a reduction in intracellular osmotic pressure.

Erythropoietin protects the inner blood-retinal barrier by inhibiting microglia phagocytosis via Src/Akt/cofilin signalling in experimental diabetic retinopathy.

AIMS/HYPOTHESIS: Microglial activation in diabetic retinopathy and the protective effect of erythropoietin (EPO) have been extensively studied. However, the regulation of microglia in the retina and its relationship to inner blood-retinal barrier (iBRB) maintenance have not been fully characterised. In this study, we investigated the role of microglia in iBRB breakdown in diabetic retinopathy and the protective effects of EPO in this context. METHODS: Male Sprague Dawley rats were injected intraperitoneally with streptozotocin (STZ) to establish the experimental model of diabetes. At 2 h after STZ injection, the right and left eyes were injected intravitreally with EPO (16 mU/eye, 2 µl) and an equivalent volume of normal saline (NaCl 154 mmol/l), respectively. The rats were killed at 2 or 8 weeks after diabetes onset. Microglia activation was detected by ionised calcium binding adaptor molecule (IBA)-1 immunolabelling. Leakage of the iBRB was evaluated by albumin staining and FITC-dextran permeability assay. BV2 cells and primary rat microglia under hypoxic conditions were used to model microglial activation in diabetic retinopathy. Phagocytosis was examined by confocal microscopy in flat-mounted retina preparations and in microglia and endothelial cell cocultures. Protein levels of IBA-1, CD11b, complement component 1r (C1r), and Src/Akt/cofilin signalling pathway components were assessed by western blotting. RESULTS: In diabetic rat retinas, phagocytosis of endothelial cells by activated microglia was observed at 8 weeks, resulting in an increased number of acellular capillaries (increased by 426.5%) and albumin leakage. Under hypoxic conditions, activated microglia transmigrated to the opposite membrane of the transwell, where they disrupted the endothelial cell monolayer by engulfing endothelial cells. The activation and phagocytic activity of microglia was blocked by intravitreal injection of EPO. In vitro, IBA-1, CD11b and C1r protein levels were increased by 50.9%, 170.0% and 135.5%, respectively, by hypoxia, whereas the phosphorylated proteins of Src/Akt/cofilin signalling pathway components were decreased by 74.2%, 47.8% and 39.7%, respectively, compared with the control; EPO treatment abrogated these changes. CONCLUSIONS/INTERPRETATION: In experimental diabetic retinopathy, activated microglia penetrate the basement membrane of the iBRB and engulf endothelial cells, leading to iBRB breakdown. EPO exerts a protective effect that preserves iBRB integrity via activation of Src/Akt/cofilin signalling in microglia, as demonstrated in vitro. These data support a causal role for activated microglia in iBRB breakdown and highlight the therapeutic potential of EPO for the treatment of diabetic retinopathy. Graphical abstract.