AIM:To identify different metabolites,proteins and related pathways to elucidate the causes of proliferative diabetic retinopathy(PDR)and resistance to anti-vascular endothelial growth factor(VEGF)drugs,and to provide...AIM:To identify different metabolites,proteins and related pathways to elucidate the causes of proliferative diabetic retinopathy(PDR)and resistance to anti-vascular endothelial growth factor(VEGF)drugs,and to provide biomarkers for the diagnosis and treatment of PDR.METHODS:Vitreous specimens from patients with diabetic retinopathy were collected and analyzed by Liquid Chromatography-Mass Spectrometry(LC-MS/MS)analyses based on 4D label-free technology.Statistically differentially expressed proteins(DEPs),Gene Ontology(GO),Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway representation and protein interactions were analyzed.RESULTS:A total of 12 samples were analyzed.The proteomics results showed that a total of 58 proteins were identified as DEPs,of which 47 proteins were up-regulated and 11 proteins were down-regulated.We found that C1q and tumor necrosis factor related protein 5(C1QTNF5),Clusterin(CLU),tissue inhibitor of metal protease 1(TIMP1)and signal regulatory protein alpha(SIRPα)can all be specifically regulated after aflibercept treatment.GO functional analysis showed that some DEPs are related to changes in inflammatory regulatory pathways caused by PDR.In addition,protein-protein interaction(PPI)network evaluation revealed that TIMP1 plays a central role in neural regulation.In addition,CD47/SIRPαmay become a key target to resolve anti-VEGF drug resistance in PDR.CONCLUSION:Proteomic analysis is an approach of choice to explore the molecular mechanisms of PDR.Our data show that multiple proteins are differentially changed in PDR patients after intravitreal injection of aflibercept,among which C1QTNF5,CLU,TIMP1 and SIRPαmay become targets for future treatment of PDR and resolution of anti-VEGF resistance.展开更多
BACKGROUND Neovascular glaucoma(NVG)is likely to occur after pars plana vitrectomy(PPV)for diabetic retinopathy(DR)in some patients,thus reducing the expected benefit.Understanding the risk factors for NVG occurrence ...BACKGROUND Neovascular glaucoma(NVG)is likely to occur after pars plana vitrectomy(PPV)for diabetic retinopathy(DR)in some patients,thus reducing the expected benefit.Understanding the risk factors for NVG occurrence and building effective risk prediction models are currently required for clinical research.AIM To develop a visual risk profile model to explore factors influencing DR after surgery.METHODS We retrospectively selected 151 patients with DR undergoing PPV.The patients were divided into the NVG(NVG occurrence)and No-NVG(No NVG occurrence)groups according to the occurrence of NVG within 6 months after surgery.Independent risk factors for postoperative NVG were screened by logistic regression.A nomogram prediction model was established using R software,and the model’s prediction accuracy was verified internally and externally,involving the receiver operator characteristic curve and correction curve.RESULTS After importing the data into a logistic regression model,we concluded that a posterior capsular defect,preoperative vascular endothelial growth factor≥302.90 pg/mL,glycosylated hemoglobin≥9.05%,aqueous fluid interleukin 6(IL-6)≥53.27 pg/mL,and aqueous fluid IL-10≥9.11 pg/mL were independent risk factors for postoperative NVG in patients with DR(P<0.05).A nomogram model was established based on the aforementioned independent risk factors,and a computer simulation repeated sampling method was used to internally and externally verify the nomogram model.The area under the curve(AUC),sensitivity,and specificity of the model were 0.962[95%confidence interval(95%CI):0.932-0.991],91.5%,and 82.3%,respectively.The AUC,sensitivity,and specificity of the external validation were 0.878(95%CI:0.746-0.982),66.7%,and 95.7%,respectively.CONCLUSION A nomogram constructed based on the risk factors for postoperative NVG in patients with DR has a high prediction accuracy.This study can help formulate relevant preventive and treatment measures.展开更多
AIM:To propose an algorithm for automatic detection of diabetic retinopathy(DR)lesions based on ultra-widefield scanning laser ophthalmoscopy(SLO).METHODS:The algorithm utilized the FasterRCNN(Faster Regions with CNN ...AIM:To propose an algorithm for automatic detection of diabetic retinopathy(DR)lesions based on ultra-widefield scanning laser ophthalmoscopy(SLO).METHODS:The algorithm utilized the FasterRCNN(Faster Regions with CNN features)+ResNet50(Residua Network 50)+FPN(Feature Pyramid Networks)method for detecting hemorrhagic spots,cotton wool spots,exudates,and microaneurysms in DR ultra-widefield SLO.Subimage segmentation combined with a deeper residual network FasterRCNN+ResNet50 was employed for feature extraction to enhance intelligent learning rate.Feature fusion was carried out by the feature pyramid network FPN,which significantly improved lesion detection rates in SLO fundus images.RESULTS:By analyzing 1076 ultra-widefield SLO images provided by our hospital,with a resolution of 2600×2048 dpi,the accuracy rates for hemorrhagic spots,cotton wool spots,exudates,and microaneurysms were found to be 87.23%,83.57%,86.75%,and 54.94%,respectively.CONCLUSION:The proposed algorithm demonstrates intelligent detection of DR lesions in ultra-widefield SLO,providing significant advantages over traditional fundus color imaging intelligent diagnosis algorithms.展开更多
BACKGROUND Early screening and accurate staging of diabetic retinopathy(DR)can reduce blindness risk in type 2 diabetes patients.DR’s complex pathogenesis involves many factors,making ophthalmologist screening alone ...BACKGROUND Early screening and accurate staging of diabetic retinopathy(DR)can reduce blindness risk in type 2 diabetes patients.DR’s complex pathogenesis involves many factors,making ophthalmologist screening alone insufficient for prevention and treatment.Often,endocrinologists are the first to see diabetic patients and thus should screen for retinopathy for early intervention.AIM To explore the efficacy of non-mydriatic fundus photography(NMFP)-enhanced telemedicine in assessing DR and its various stages.METHODS This retrospective study incorporated findings from an analysis of 93 diabetic patients,examining both NMFP-assisted telemedicine and fundus fluorescein angiography(FFA).It focused on assessing the concordance in DR detection between these two methodologies.Additionally,receiver operating characteristic(ROC)curves were generated to determine the optimal sensitivity and specificity of NMFP-assisted telemedicine,using FFA outcomes as the standard benchmark.RESULTS In the context of DR diagnosis and staging,the kappa coefficients for NMFPassisted telemedicine and FFA were recorded at 0.775 and 0.689 respectively,indicating substantial intermethod agreement.Moreover,the NMFP-assisted telemedicine’s predictive accuracy for positive FFA outcomes,as denoted by the area under the ROC curve,was remarkably high at 0.955,within a confidence interval of 0.914 to 0.995 and a statistically significant P-value of less than 0.001.This predictive model exhibited a specificity of 100%,a sensitivity of 90.9%,and a Youden index of 0.909.CONCLUSION NMFP-assisted telemedicine represents a pragmatic,objective,and precise modality for fundus examination,particularly applicable in the context of endocrinology inpatient care and primary healthcare settings for diabetic patients.Its implementation in these scenarios is of paramount significance,enhancing the clinical accuracy in the diagnosis and therapeutic management of DR.This methodology not only streamlines patient evaluation but also contributes substantially to the optimization of clinical outcomes in DR management.展开更多
Objective:To investigate the association between rs2110385 polymorphisms of the visfatin gene and the risk of type 2 diabetic retinopathy(DR).Methods:172 Han subjects were selected from Xi’an Shaanxi Province;140 pat...Objective:To investigate the association between rs2110385 polymorphisms of the visfatin gene and the risk of type 2 diabetic retinopathy(DR).Methods:172 Han subjects were selected from Xi’an Shaanxi Province;140 patients with type 2 diabetes mellitus(T2DM)and 32 normal controls(NC)were selected from our hospital.Patients with diabetes were divided into a non-DR group(T2DM)(n=69)and a nonproliferative diabetic retinopathy Group(DR)(n=71)after dilated fundus photography and fundus fluorescein angiography.rs2110385/AluⅠgenotypes were detected by standardized polymerase chain reaction-restriction fragment length polymorphism(PCR-RFLP),and the differences in the detection rates of different genotypes in the above populations were compared.Results:1)The visfatin level in the DR Group was significantly higher than that in the NC and T2DM groups(P<0.05).2)The frequency of GG genotype and G allele of rs2110385 in the DR Group were higher than those in the T2DM and NC groups(80.3,69.6,50.0,86.6,79,65.6,P<0.05).3)There were significant differences in allele frequency and genotype frequency distribution of rs2110385 between the DR Group and the NC group(P<0.01).Conclusion:Visfatin increased in the nonproliferative diabetic retinopathy group and could be a potential indicator for the clinical prediction of DR.The G allele of the rs2110385 polymorphic site may be related to the risk of DR.展开更多
Somatostatin,a naturally produced neuroprotective peptide,depresses excitatory neurotransmission and exerts anti-proliferative and anti-inflammatory effects on the retina.In this review,we summarize the progress of so...Somatostatin,a naturally produced neuroprotective peptide,depresses excitatory neurotransmission and exerts anti-proliferative and anti-inflammatory effects on the retina.In this review,we summarize the progress of somatostatin treatment of diabetic retinopathy through analysis of relevant studies published from February 2019 to February 2023 extracted from the PubMed and Google Scholar databases.Insufficient neuroprotection,which occurs as a consequence of declined expression or dysregulation of retinal somatostatin in the very early stages of diabetic retinopathy,triggers retinal neurovascular unit impairment and microvascular damage.Somatostatin replacement is a promising treatment for retinal neurodegeneration in diabetic retinopathy.Numerous pre-clinical and clinical trials of somatostatin analog treatment for early diabetic retinopathy have been initiated.In one such trial(EUROCONDOR),topical administration of somatostatin was found to exert neuroprotective effects in patients with pre-existing retinal neurodysfunction,but had no impact on the onset of diabetic retinopathy.Overall,we concluded that somatostatin restoration may be especially beneficial for the growing population of patients with early-stage retinopathy.In order to achieve early prevention of diabetic retinopathy initiation,and thereby salvage visual function before the appearance of moderate non-proliferative diabetic retinopathy,several issues need to be addressed.These include the needs to:a)update and standardize the retinal screening scheme to incorporate the detection of early neurodegeneration,b)identify patient subgroups who would benefit from somatostatin analog supplementation,c)elucidate the interactions of somatostatin,particularly exogenously-delivered somatostatin analogs,with other retinal peptides in the context of hyperglycemia,and d)design safe,feasible,low cost,and effective administration routes.展开更多
Diabetic retinopathy, characterized as a microangiopathy and neurodegenerative disease, is the leading cause of visual impairment in diabetic patients. Many clinical features observed in diabetic retinopathy, such as ...Diabetic retinopathy, characterized as a microangiopathy and neurodegenerative disease, is the leading cause of visual impairment in diabetic patients. Many clinical features observed in diabetic retinopathy, such as capillary occlusion, acellular capillaries and retinal non-perfusion, aggregate retinal ischemia and represent relatively late events in diabetic retinopathy. In fact, retinal microvascular injury is an early event in diabetic retinopathy involving multiple biochemical alterations, and is manifested by changes to the retinal neurovascular unit and its cellular components. Currently, intravitreal anti-vascular endothelial growth factor therapy is the firstline treatment for diabetic macular edema, and benefits the patient by decreasing the edema and improving visual acuity. However, a significant proportion of patients respond poorly to anti-vascular endothelial growth factor treatments, indicating that factors other than vascular endothelial growth factor are involved in the pathogenesis of diabetic macular edema. Accumulating evidence confirms that low-grade inflammation plays a critical role in the pathogenesis and development of diabetic retinopathy as multiple inflammatory factors, such as interleukin-1β, monocyte chemotactic protein-1 and tumor necrosis factor-α, are increased in the vitreous and retina of diabetic retinopathy patients. These inflammatory factors, together with growth factors such as vascular endothelial growth factor, contribute to blood-retinal barrier breakdown, vascular damage and neuroinflammation, as well as pathological angiogenesis in diabetic retinopathy, complicated by diabetic macular edema and proliferative diabetic retinopathy. In addition, retinal cell types including microglia, Müller glia, astrocytes, retinal pigment epithelial cells, and others are activated, to secrete inflammatory mediators, aggravating cell apoptosis and subsequent vascular leakage. New therapies, targeting these inflammatory molecules or related signaling pathways, have the potential to inhibit retinal inflammation and prevent diabetic retinopathy progression. Here, we review the relevant literature to date, summarize the inflammatory mechanisms underlying the pathogenesis of diabetic retinopathy, and propose inflammation-based treatments for diabetic retinopathy and diabetic macular edema.展开更多
Epigenetics focuses on DNA methylation,histone modification,chromatin remodeling,noncoding RNAs,and other gene regulation mechanisms beyond the DNA sequence.In the past decade,epigenetic modifications have drawn more ...Epigenetics focuses on DNA methylation,histone modification,chromatin remodeling,noncoding RNAs,and other gene regulation mechanisms beyond the DNA sequence.In the past decade,epigenetic modifications have drawn more attention as they participate in the development and progression of diabetic retinopathy despite tight control of glucose levels.The underlying mechanisms of epigenetic modifications in diabetic retinopathy still urgently need to be elucidated.The diabetic condition facilitates epigenetic changes and influences target gene expression.In this review,we summarize the involvement of epigenetic modifications and metabolic memory in the development and progression of diabetic retinopathy and propose novel insights into the treatment of diabetic retinopathy.展开更多
BACKGROUND Retinopathy is the most common microvascular disease of type 2 diabetes,and seriously threatens the life,health and quality of life of patients.It is worth noting that the development of diabetic retinopath...BACKGROUND Retinopathy is the most common microvascular disease of type 2 diabetes,and seriously threatens the life,health and quality of life of patients.It is worth noting that the development of diabetic retinopathy(DR)can be hidden,with few symptoms.Therefore,the preliminary screening of diabetic patients should identify DR as soon as possible,delay disease progression,and play a vital role in its diagnosis and treatment.AIM To investigate the correlation between glycated hemoglobin A1c(HbA1c),urinary microalbumin(U-mALB),urinary creatinine(U-CR),mALB/U-CR ratio,β2 microglobulin(β2MG),retinol binding protein(RBP)and DR.METHODS A total of 180 patients with type 2 diabetes mellitus attending the Second People’s Hospital of Hefei from January 2022 to August 2022 were retrospectively enrolled by ophthalmologists.Based on whether they had combined retinopathy and its degree,68 patients with diabetes mellitus without retinopathy(NDR)were assigned to the NDR group,54 patients with non-proliferative DR(NPDR)to the NPDR group,and 58 patients with proliferative DR to the PDR group.General data,and HbA1c,mALB,β2MG,RBP,mALB/U-CR and U-CR results were collected from the patients and compared among the groups.Pearson's correlation method was used to analyze the correlation between HbA1c,mALB,β2MG,RBP,mALB/U-CR and U-CR indices,and multiple linear regression was applied to identify the risk factors for DR.Receiver operator characteristic(ROC)curves were also drawn.RESULTS The differences in age,gender,systolic and diastolic blood pressure between the groups were not statistically significantly(P>0.05),but the difference in disease duration was statistically significant(P<0.05).The differences in fasting blood glucose,high-density lipoprotein cholesterol,low-density lipoprotein cholesterol,total cholesterol,and triglyceride between the groups were not statistically significant(P>0.05).HbA1c in the PDR group was higher than that in the NPDR and NDR groups(P<0.05).The levels of mALB,β2MG,RBP,mALB/U-CR and UCR in the PDR group were higher than those in the NPDR and NDR groups(P<0.05).Multiple linear regression analysis showed that disease duration,HbA1c,mALB,β2MG,RBP,mALB/U-CR and U-CR were risk factors for the development of DR.The ROC curve showed that the area under the curve(AUC)for the combination of indices(HbA1c+mALB+mALB/U-CR+U-CR+β2MG+RBP)was 0.958,with a sensitivity of 94.83%and specificity of 96.72%,which was higher than the AUC for single index prediction(P<0.05).CONCLUSION HbA1c,mALB,mALB/U-CR,U-CR,β2MG and RBP can reflect the development of DR and are risk factors affecting PDR,and the combination of these six indices has predictive value for PDR.展开更多
Diabetic retinopathy(DR)is one of the most common retinal vascular diseases and one of the main causes of blindness worldwide.Early detection and treatment can effectively delay vision decline and even blindness in pa...Diabetic retinopathy(DR)is one of the most common retinal vascular diseases and one of the main causes of blindness worldwide.Early detection and treatment can effectively delay vision decline and even blindness in patients with DR.In recent years,artificial intelligence(AI)models constructed by machine learning and deep learning(DL)algorithms have been widely used in ophthalmology research,especially in diagnosing and treating ophthalmic diseases,particularly DR.Regarding DR,AI has mainly been used in its diagnosis,grading,and lesion recognition and segmentation,and good research and application results have been achieved.This study summarizes the research progress in AI models based on machine learning and DL algorithms for DR diagnosis and discusses some limitations and challenges in AI research.展开更多
Biomedical image processing is finding useful in healthcare sector for the investigation,enhancement,and display of images gathered by distinct imaging technologies.Diabetic retinopathy(DR)is an illness caused by diab...Biomedical image processing is finding useful in healthcare sector for the investigation,enhancement,and display of images gathered by distinct imaging technologies.Diabetic retinopathy(DR)is an illness caused by diabetes complications and leads to irreversible injury to the retina blood vessels.Retinal vessel segmentation techniques are a basic element of automated retinal disease screening system.In this view,this study presents a novel blood vessel segmentation with deep learning based classification(BVS-DLC)model forDRdiagnosis using retinal fundus images.The proposed BVS-DLC model involves different stages of operations such as preprocessing,segmentation,feature extraction,and classification.Primarily,the proposed model uses the median filtering(MF)technique to remove the noise that exists in the image.In addition,a multilevel thresholding based blood vessel segmentation process using seagull optimization(SGO)with Kapur’s entropy is performed.Moreover,the shark optimization algorithm(SOA)with Capsule Networks(CapsNet)model with softmax layer is employed for DR detection and classification.Awide range of simulations was performed on the MESSIDOR dataset and the results are investigated interms of different measures.The simulation results ensured the better performance of the proposed model compared to other existing techniques interms of sensitivity,specificity,receiver operating characteristic(ROC)curve,accuracy,and F-score.展开更多
Diabetic Retinopathy (DR) is a serious hazard that can result inirreversible blindness if not addressed in a timely manner. Hence, numeroustechniques have been proposed for the accurate and timely detection ofthis dis...Diabetic Retinopathy (DR) is a serious hazard that can result inirreversible blindness if not addressed in a timely manner. Hence, numeroustechniques have been proposed for the accurate and timely detection ofthis disease. Out of these, Deep Learning (DL) and Computer Vision (CV)methods for multiclass categorization of color fundus images diagnosed withDiabetic Retinopathy have sparked considerable attention. In this paper,we attempt to develop an extended ResNet152V2 architecture-based DeepLearning model, named ResNet2.0 to aid the timely detection of DR. TheAPTOS-2019 datasetwas used to train the model. This consists of 3662 fundusimages belonging to five different stages of DR: no DR (Class 0), mild DR(Class 1), moderate DR (Class 2), severe DR (Class 3), and proliferativeDR (Class 4). The model was gauged based on ability to detect stage-wiseDR. The images were pre-processed using negative and positive weightedGaussian-based masks as feature engineering to further enhance the qualityof the fundus images by removing the noise and normalizing the images. Upsamplingand data augmentation methods were used to address the skewnessof the original dataset. The proposed model achieved an overall accuracyof 91% and an area under the receiver-operating characteristic curve (AUC)score of 95.1%, outperforming existing Deep Learning models by around 10%.Furthermore, the class-wise F1 score for No DR was 92%, Mild DR was 82%,Moderate DR was 66%, Severe was DR 89% and Proliferative DR was 80%.展开更多
Diabetic retinopathy is a critical eye condition that,if not treated,can lead to vision loss.Traditional methods of diagnosing and treating the disease are time-consuming and expensive.However,machine learning and dee...Diabetic retinopathy is a critical eye condition that,if not treated,can lead to vision loss.Traditional methods of diagnosing and treating the disease are time-consuming and expensive.However,machine learning and deep transfer learning(DTL)techniques have shown promise in medical applications,including detecting,classifying,and segmenting diabetic retinopathy.These advanced techniques offer higher accuracy and performance.ComputerAided Diagnosis(CAD)is crucial in speeding up classification and providing accurate disease diagnoses.Overall,these technological advancements hold great potential for improving the management of diabetic retinopathy.The study’s objective was to differentiate between different classes of diabetes and verify the model’s capability to distinguish between these classes.The robustness of the model was evaluated using other metrics such as accuracy(ACC),precision(PRE),recall(REC),and area under the curve(AUC).In this particular study,the researchers utilized data cleansing techniques,transfer learning(TL),and convolutional neural network(CNN)methods to effectively identify and categorize the various diseases associated with diabetic retinopathy(DR).They employed the VGG-16CNN model,incorporating intelligent parameters that enhanced its robustness.The outcomes surpassed the results obtained by the auto enhancement(AE)filter,which had an ACC of over 98%.The manuscript provides visual aids such as graphs,tables,and techniques and frameworks to enhance understanding.This study highlights the significance of optimized deep TL in improving the metrics of the classification of the four separate classes of DR.The manuscript emphasizes the importance of using the VGG16CNN classification technique in this context.展开更多
AIM:To evaluate the difference and the correlation between the concentrations of cytokines in the aqueous humor of eyes with macular edema secondary to diabetic retinopathy(DR)or retinal vein occlusion(RVO).METHODS:Th...AIM:To evaluate the difference and the correlation between the concentrations of cytokines in the aqueous humor of eyes with macular edema secondary to diabetic retinopathy(DR)or retinal vein occlusion(RVO).METHODS:This is a retrospective case control study.The aqueous humor samples were collected during intravitreal injection of anti-vascular endothelial growth factor(VEGF)for patients diagnosed with macular edema secondary to DR(DME)or RVO(RVO-ME)at Xijing Hospital from August 2021 to July 2022.Meanwhile,aqueous humor samples during vitrectomy from patients with idiopathic macular hole(IMH)were also collected and served as controls.The aqueous humor concentrations of VEGF,platelet-derived factor(PDGF),interleukin(IL)-6,IL-8,IL-18,tumor necrosis factor-α(TNF-α)and monocyte chemoattractant protein 1(MCP-1)were measured with Human Premixed Multi-Analyte Kit(Luminex).The difference of the aqueous cytokines and the correlation between the two diseases were analyzed.RESULTS:A total of 40 eyes of 38 patients were enrolled in the study,including 13 eyes of 11 DME patients(DME group),16 eyes of 16 RVO-ME patients(RVO-ME group)and 11 eyes of 11 IMH patients(control group).The VEGF,PDGF,IL-6,IL-8,and MCP-1 levels of the aqueous humor were higher in both DME and RVO-ME groups compared with the control group(all P<0.05),the levels of TNF-αwas higher in the DME group than in the control group(P<0.05).The VEGF,IL-6,MCP-1,and TNF-αlevels in the aqueous humor were significantly higher in the DR group than those in the RVO group(all P<0.05).Correlation analyses revealed that there were complex positive correlations between IL-6,IL-8,IL-18,MCP-1,and TNF-αlevels in the aqueous humor of eyes with two diseases.CONCLUSION:Although ischemic and inflammatory factors are similarly involved in the pathogenesis of DME and RVO-ME,the roles of these factors are more significant or more likely to be activated in DR patients,suggesting different treatment strategies should be considered for the two diseases.展开更多
·AIM:To determine the effects of protocatechuic acid(PCA)on streptozocin-induced diabetic retinopathy(DR)in rats.·METHODS:Wistar rats were given a 50 mg/kg intraperitoneal injection of streptozocin to induce...·AIM:To determine the effects of protocatechuic acid(PCA)on streptozocin-induced diabetic retinopathy(DR)in rats.·METHODS:Wistar rats were given a 50 mg/kg intraperitoneal injection of streptozocin to induce diabetes.Animals were assigned randomly one of four groups(8 rats per group):control,diabetic,diabetic plus PCA(25 mg/kg·d),and diabetic plus PCA(50 mg/kg·d).After inducing diabetes,treatments were started one week later and continued for eight weeks.After the experiment,the rats were sacrificed,and their retinas were taken for biochemical and molecular analysis.·RESULTS:PCA administration diminished the blood glucose and glycated haemoglobin levels relative to the diabetic group.In diabetic rats,PCA lowered elevated levels of advanced glycosylated end products(AGEs)and receptor for AGEs(RAGE).In the retina of diabetic rats,PCA effectively decreased inflammatory cytokine,nuclear factor-κB,tumour necrosis factor-α,interleukin-1β,and vascular endothelial growth factor,and increased antioxidant markers glutathione,superoxide dismutase,and catalase.·CONCLUSION:The protective benefits of PCA against DR may be attributable to its suppression of the AGEs and RAGE and its antioxidant and anti-inflammatory properties.展开更多
In the modern world,one of the most severe eye infections brought on by diabetes is known as diabetic retinopathy(DR),which will result in retinal damage,and,thus,lead to blindness.Diabetic retinopathy(DR)can be well ...In the modern world,one of the most severe eye infections brought on by diabetes is known as diabetic retinopathy(DR),which will result in retinal damage,and,thus,lead to blindness.Diabetic retinopathy(DR)can be well treated with early diagnosis.Retinal fundus images of humans are used to screen for lesions in the retina.However,detecting DR in the early stages is challenging due to the minimal symptoms.Furthermore,the occurrence of diseases linked to vascular anomalies brought on by DR aids in diagnosing the condition.Nevertheless,the resources required for manually identifying the lesions are high.Similarly,training for Convolutional Neural Networks(CNN)is more time-consuming.This proposed research aims to improve diabetic retinopathy diagnosis by developing an enhanced deep learning model(EDLM)for timely DR identification that is potentially more accurate than existing CNN-based models.The proposed model will detect various lesions from retinal images in the early stages.First,characteristics are retrieved from the retinal fundus picture and put into the EDLM for classification.For dimensionality reduction,EDLM is used.Additionally,the classification and feature extraction processes are optimized using the stochastic gradient descent(SGD)optimizer.The EDLM’s effectiveness is assessed on the KAG-GLE dataset with 3459 retinal images,and results are compared over VGG16,VGG19,RESNET18,RESNET34,and RESNET50.Experimental results show that the EDLM achieves higher average sensitivity by 8.28%for VGG16,by 7.03%for VGG19,by 5.58%for ResNet18,by 4.26%for ResNet 34,and by 2.04%for ResNet 50,respectively.展开更多
AIM:To explore the correlation between diabetic retinopathy(DR)and Helicobacter pylori(Hp)infection,based on data from a physical examination population.METHODS:This cross-sectional retrospective analysis included dat...AIM:To explore the correlation between diabetic retinopathy(DR)and Helicobacter pylori(Hp)infection,based on data from a physical examination population.METHODS:This cross-sectional retrospective analysis included data of 73824 health examination participants from December 2018 to December 2019.Participants were divided into the diabetic group and non-diabetic group,nondiabetic retinopathy(NDR)group,non-proliferative diabetic retinopathy(NPDR)group,proliferative diabetic retinopathy(PDR)group,and Hp infection group.Gender,age,body mass index(BMI),systolic blood pressure(SBP),diastolic blood pressure(DBP),fasting plasma glucose(FPG),glycated hemoglobin A1c(HbA1c),triglycerides(TG),total cholesterol(TC),low-density lipoprotein cholesterol(LDL-C),high-density lipoprotein cholesterol(HDL-C),and Hp data were recorded to compare the degree of DR lesions and Hp infection.Logistic regression analysis was used to evaluate the correlation between DR and Hp infection.RESULTS:There was a statistically significant difference between the diabetic and non-diabetic group(χ2=94.17,P<0.0001).Logistic regression analysis showed that male sex,age,BMI,SBP,TG,LDL-C,and Hp infection were independent risk factors for DR.There was no correlation between the degree of DR lesions and Hp infection(ρ=-0.00339,P=0.7753).Age[odds ratio(OR)=1.035,95%CI:1.024,1.046,P<0.0001]and SBP(OR=1.009,95%CI:1.004,1.015,P=0.0013)were independent risk factors for the degree of DR.CONCLUSION:There is a significant correlation between DR and Hp infection in the physical examination population.Hp infection is a risk factor for DR,and there is no significant difference between Hp infection and DR of different pathological degrees.Actively eradicating Hp may be of help to prevent DR.展开更多
BACKGROUND Glycation is an important step in aging and oxidative stress,which can lead to endothelial dysfunction and cause severe damage to the eyes or kidneys of diabetics.Inhibition of the formation of advanced gly...BACKGROUND Glycation is an important step in aging and oxidative stress,which can lead to endothelial dysfunction and cause severe damage to the eyes or kidneys of diabetics.Inhibition of the formation of advanced glycation end products(AGEs)and their cell toxicity can be a useful therapeutic strategy in the prevention of diabetic retinopathy(DR).Gardenia jasminoides Ellis(GJE)fruit is a selective inhibitor of AGEs.Genipin is an active compound of GJE fruit,which can be employed to treat diabetes.AIM To confirm the effect of genipin,a vital component of GJE fruit,in preventing human retinal microvascular endothelial cells(hRMECs)from AGEs damage in DR,to investigate the effect of genipin in the down-regulation of AGEs expression,and to explore the role of the CHGA/UCP2/glucose transporter 1(GLUT1)signal pathway in this process.METHODS In vitro,cell viability was tested to determine the effects of different doses of glucose and genipin in hRMECs.Cell Counting Kit-8(CCK-8),colony formation assay,flow cytometry,immunofluorescence,wound healing assay,transwell assay,and tube-forming assay were used to detect the effect of genipin on hRMECs cultured in high glucose conditions.In vivo,streptozotocin(STZ)induced mice were used,and genipin was administered by intraocular injection(IOI).To explore the effect and mechanism of genipin in diabetic-induced retinal dysfunction,reactive oxygen species(ROS),mitochondrial membrane potential(MMP),and 2-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino]-2-deoxy-d-glucose(2-NBDG)assays were performed to explore energy metabolism and oxidative stress damage in high glucose-induced hRMECs and STZ mouse retinas.Immunofluorescence and Western blot were used to investigate the expression of inflammatory cytokines[vascular endothelial growth factor(VEGF),SCG3,tumor necrosis factor-alpha(TNF-α),interleukin(IL)-1β,IL-18,and nucleotide-binding domain,leucine-rich-containing family,pyrin domain-containing 3(NLRP3)].The protein expression of the receptor of AGEs(RAGE)and the mitochondria-related signal molecules CHGA,GLUT1,and UCP2 in high glucose-induced hRMECs and STZ mouse retinas were measured and compared with the genipin-treated group.RESULTS The results of CCK-8 and colony formation assay showed that genipin promoted cell viability in high glucose(30 mmol/L D-Glucose)-induced hRMECs,especially at a 0.4μmol/L dose for 7 d.Flow cytometry results showed that high glucose can increase apoptosis rate by 30%,and genipin alleviated cell apoptosis in AGEs-induced hRMECs.A high glucose environment promoted ATP,ROS,MMP,and 2-NBDG levels,while genipin inhibited these phenotypic abnormalities in AGEs-induced hRMECs.Furthermore,genipin remarkably reduced the levels of the pro-inflammatory cytokines TNF-α,IL-1β,IL-18,and NLRP3 and impeded the expression of VEGF and SCG3 in AGEs-damaged hRMECs.These results showed that genipin can reverse high glucose induced damage with regard to cell proliferation and apoptosis in vitro,while reducing energy metabolism,oxidative stress,and inflammatory injury caused by high glucose.In addition,ROS levels and glucose uptake levels were higher in the retina from the untreated eye than in the genipin-treated eye of STZ mice.The expression of inflammatory cytokines and pathway protein in the untreated eye compared with the genipin-treated eye was significantly increased,as measured by Western blot.These results showed that IOI of genipin reduced the expression of CHGA,UCP2,and GLUT1,maintained the retinal structure,and decreased ROS,glucose uptake,and inflammation levels in vivo.In addition,we found that SCG3 expression might have a higher sensitivity in DR than VEGF as a diagnostic marker at the protein level.CONCLUSION Our study suggested that genipin ameliorates AGEs-induced hRMECs proliferation,apoptosis,energy metabolism,oxidative stress,and inflammatory injury,partially via the CHGA/UCP2/GLUT1 pathway.Control of advanced glycation by IOI of genipin may represent a strategy to prevent severe retinopathy and vision loss.展开更多
·AIM:To elucidate the relationship between macular sensitivity and time in range(TIR)obtained from continuous glucose monitoring(CGM)measures in diabetic patients with or without diabetic retinopathy(DR).·ME...·AIM:To elucidate the relationship between macular sensitivity and time in range(TIR)obtained from continuous glucose monitoring(CGM)measures in diabetic patients with or without diabetic retinopathy(DR).·METHODS:This was a cross-sectional study including 100 eyes of non-DR patients and 60 eyes of DR patients.An advanced microperimetry was used to quantitate the retinal mean sensitivity(MS)and fixation stability in central macula.TIR of 3.9-10.0 mmol/L was evaluated with CGM.Pearson coefficient analysis and multiple linear regression analysis were used to assess the correlation between TIR and retinal sensitivity.·RESULTS:In a comparison of non-DR patients,significant differences(P<0.05)were found in Hb A1c,TIR,coefficient of variation(CV),standard deviation of blood glucose(SDBG)and mean amplitude of glucose excursion(MAGE)values in DR patients.Besides,those DR patients had significantly poor best-corrected visual acuity(BCVA,log MAR,P=0.001).In terms of microperimetry parameters,retinal mean sensitivity(MS)and the percentages of fixation points located within 2°and 4°diameter circles were significantly decreased in the DR group(P<0.001,P<0.001,P=0.02,respectively).The bivariate contour ellipse area(BCEA)encompassing 68.2%,95.4%,99.6%of fixation points were all significantly increased in the DR group(P=0.01,P=0.006,P=0.01,respectively).Correlation analysis showed that MS were significantly correlated with Hb A1c(P=0.01).TIR was positively correlated with MS(r=0.23,P=0.01).SDBG was negatively correlated with MS(r=-0.24,P=0.01)but there was no correlation between CV and MAGE with MS(P>0.05).A multivariable linear regression analysis was performed to prove that TIR and SDBG were both independent risk factors for MS reduction in the DR group.·CONCLUSION:TIR is correlated with retinal MS reduction in DR patients,suggesting a useful option for evaluating DR progression.展开更多
The study aimed to apply to Machine Learning(ML)researchers working in image processing and biomedical analysis who play an extensive role in compre-hending and performing on complex medical data,eventually improving ...The study aimed to apply to Machine Learning(ML)researchers working in image processing and biomedical analysis who play an extensive role in compre-hending and performing on complex medical data,eventually improving patient care.Developing a novel ML algorithm specific to Diabetic Retinopathy(DR)is a chal-lenge and need of the hour.Biomedical images include several challenges,including relevant feature selection,class variations,and robust classification.Although the cur-rent research in DR has yielded favourable results,several research issues need to be explored.There is a requirement to look at novel pre-processing methods to discard irrelevant features,balance the obtained relevant features,and obtain a robust classi-fication.This is performed using the Steerable Kernalized Partial Derivative and Platt Scale Classifier(SKPD-PSC)method.The novelty of this method relies on the appropriate non-linear classification of exclusive image processing models in har-mony with the Platt Scale Classifier(PSC)to improve the accuracy of DR detection.First,a Steerable Filter Kernel Pre-processing(SFKP)model is applied to the Retinal Images(RI)to remove irrelevant and redundant features and extract more meaningful pathological features through Directional Derivatives of Gaussians(DDG).Next,the Partial Derivative Image Localization(PDIL)model is applied to the extracted fea-tures to localize candidate features and suppress the background noise.Finally,a Platt Scale Classifier(PSC)is applied to the localized features for robust classification.For the experiments,we used the publicly available DR detection database provided by Standard Diabetic Retinopathy(SDR),called DIARETDB0.A database of 130 image samples has been collected to train and test the ML-based classifiers.Experimental results show that the proposed method that combines the image processing and ML models can attain good detection performance with a high DR detection accu-racy rate with minimum time and complexity compared to the state-of-the-art meth-ods.The accuracy and speed of DR detection for numerous types of images will be tested through experimental evaluation.Compared to state-of-the-art methods,the method increases DR detection accuracy by 24%and DR detection time by 37.展开更多
基金Supported by Tianjin Key Medical Discipline Specialty Construction Project(No.TJYXZDXK-016A)Henan Provincial Department of Science and Technology(No.LHGJ20200802).
文摘AIM:To identify different metabolites,proteins and related pathways to elucidate the causes of proliferative diabetic retinopathy(PDR)and resistance to anti-vascular endothelial growth factor(VEGF)drugs,and to provide biomarkers for the diagnosis and treatment of PDR.METHODS:Vitreous specimens from patients with diabetic retinopathy were collected and analyzed by Liquid Chromatography-Mass Spectrometry(LC-MS/MS)analyses based on 4D label-free technology.Statistically differentially expressed proteins(DEPs),Gene Ontology(GO),Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway representation and protein interactions were analyzed.RESULTS:A total of 12 samples were analyzed.The proteomics results showed that a total of 58 proteins were identified as DEPs,of which 47 proteins were up-regulated and 11 proteins were down-regulated.We found that C1q and tumor necrosis factor related protein 5(C1QTNF5),Clusterin(CLU),tissue inhibitor of metal protease 1(TIMP1)and signal regulatory protein alpha(SIRPα)can all be specifically regulated after aflibercept treatment.GO functional analysis showed that some DEPs are related to changes in inflammatory regulatory pathways caused by PDR.In addition,protein-protein interaction(PPI)network evaluation revealed that TIMP1 plays a central role in neural regulation.In addition,CD47/SIRPαmay become a key target to resolve anti-VEGF drug resistance in PDR.CONCLUSION:Proteomic analysis is an approach of choice to explore the molecular mechanisms of PDR.Our data show that multiple proteins are differentially changed in PDR patients after intravitreal injection of aflibercept,among which C1QTNF5,CLU,TIMP1 and SIRPαmay become targets for future treatment of PDR and resolution of anti-VEGF resistance.
基金Supported by the Tianjin Key Medical Discipline(Specialty)Construction Project,No.TJYXZDXK-037A.
文摘BACKGROUND Neovascular glaucoma(NVG)is likely to occur after pars plana vitrectomy(PPV)for diabetic retinopathy(DR)in some patients,thus reducing the expected benefit.Understanding the risk factors for NVG occurrence and building effective risk prediction models are currently required for clinical research.AIM To develop a visual risk profile model to explore factors influencing DR after surgery.METHODS We retrospectively selected 151 patients with DR undergoing PPV.The patients were divided into the NVG(NVG occurrence)and No-NVG(No NVG occurrence)groups according to the occurrence of NVG within 6 months after surgery.Independent risk factors for postoperative NVG were screened by logistic regression.A nomogram prediction model was established using R software,and the model’s prediction accuracy was verified internally and externally,involving the receiver operator characteristic curve and correction curve.RESULTS After importing the data into a logistic regression model,we concluded that a posterior capsular defect,preoperative vascular endothelial growth factor≥302.90 pg/mL,glycosylated hemoglobin≥9.05%,aqueous fluid interleukin 6(IL-6)≥53.27 pg/mL,and aqueous fluid IL-10≥9.11 pg/mL were independent risk factors for postoperative NVG in patients with DR(P<0.05).A nomogram model was established based on the aforementioned independent risk factors,and a computer simulation repeated sampling method was used to internally and externally verify the nomogram model.The area under the curve(AUC),sensitivity,and specificity of the model were 0.962[95%confidence interval(95%CI):0.932-0.991],91.5%,and 82.3%,respectively.The AUC,sensitivity,and specificity of the external validation were 0.878(95%CI:0.746-0.982),66.7%,and 95.7%,respectively.CONCLUSION A nomogram constructed based on the risk factors for postoperative NVG in patients with DR has a high prediction accuracy.This study can help formulate relevant preventive and treatment measures.
基金Supported by Hunan Provincial Science and Technology Department Clinical Medical Technology Innovation Guidance Project(No.2021SK50103)。
文摘AIM:To propose an algorithm for automatic detection of diabetic retinopathy(DR)lesions based on ultra-widefield scanning laser ophthalmoscopy(SLO).METHODS:The algorithm utilized the FasterRCNN(Faster Regions with CNN features)+ResNet50(Residua Network 50)+FPN(Feature Pyramid Networks)method for detecting hemorrhagic spots,cotton wool spots,exudates,and microaneurysms in DR ultra-widefield SLO.Subimage segmentation combined with a deeper residual network FasterRCNN+ResNet50 was employed for feature extraction to enhance intelligent learning rate.Feature fusion was carried out by the feature pyramid network FPN,which significantly improved lesion detection rates in SLO fundus images.RESULTS:By analyzing 1076 ultra-widefield SLO images provided by our hospital,with a resolution of 2600×2048 dpi,the accuracy rates for hemorrhagic spots,cotton wool spots,exudates,and microaneurysms were found to be 87.23%,83.57%,86.75%,and 54.94%,respectively.CONCLUSION:The proposed algorithm demonstrates intelligent detection of DR lesions in ultra-widefield SLO,providing significant advantages over traditional fundus color imaging intelligent diagnosis algorithms.
基金Supported by the Project of National Natural Science Foundation of China,No.82270863Major Project of Anhui Provincial University Research Program,No.2023AH040400Joint Fund for Medical Artificial Intelligence,No.MAI2023Q026.
文摘BACKGROUND Early screening and accurate staging of diabetic retinopathy(DR)can reduce blindness risk in type 2 diabetes patients.DR’s complex pathogenesis involves many factors,making ophthalmologist screening alone insufficient for prevention and treatment.Often,endocrinologists are the first to see diabetic patients and thus should screen for retinopathy for early intervention.AIM To explore the efficacy of non-mydriatic fundus photography(NMFP)-enhanced telemedicine in assessing DR and its various stages.METHODS This retrospective study incorporated findings from an analysis of 93 diabetic patients,examining both NMFP-assisted telemedicine and fundus fluorescein angiography(FFA).It focused on assessing the concordance in DR detection between these two methodologies.Additionally,receiver operating characteristic(ROC)curves were generated to determine the optimal sensitivity and specificity of NMFP-assisted telemedicine,using FFA outcomes as the standard benchmark.RESULTS In the context of DR diagnosis and staging,the kappa coefficients for NMFPassisted telemedicine and FFA were recorded at 0.775 and 0.689 respectively,indicating substantial intermethod agreement.Moreover,the NMFP-assisted telemedicine’s predictive accuracy for positive FFA outcomes,as denoted by the area under the ROC curve,was remarkably high at 0.955,within a confidence interval of 0.914 to 0.995 and a statistically significant P-value of less than 0.001.This predictive model exhibited a specificity of 100%,a sensitivity of 90.9%,and a Youden index of 0.909.CONCLUSION NMFP-assisted telemedicine represents a pragmatic,objective,and precise modality for fundus examination,particularly applicable in the context of endocrinology inpatient care and primary healthcare settings for diabetic patients.Its implementation in these scenarios is of paramount significance,enhancing the clinical accuracy in the diagnosis and therapeutic management of DR.This methodology not only streamlines patient evaluation but also contributes substantially to the optimization of clinical outcomes in DR management.
基金Xi’an Science and Technology Bureau Fund(23YXYJ0103)Shaanxi Provincial Science and Technology Department Fund(S2022-YF-YBSF-0939).
文摘Objective:To investigate the association between rs2110385 polymorphisms of the visfatin gene and the risk of type 2 diabetic retinopathy(DR).Methods:172 Han subjects were selected from Xi’an Shaanxi Province;140 patients with type 2 diabetes mellitus(T2DM)and 32 normal controls(NC)were selected from our hospital.Patients with diabetes were divided into a non-DR group(T2DM)(n=69)and a nonproliferative diabetic retinopathy Group(DR)(n=71)after dilated fundus photography and fundus fluorescein angiography.rs2110385/AluⅠgenotypes were detected by standardized polymerase chain reaction-restriction fragment length polymorphism(PCR-RFLP),and the differences in the detection rates of different genotypes in the above populations were compared.Results:1)The visfatin level in the DR Group was significantly higher than that in the NC and T2DM groups(P<0.05).2)The frequency of GG genotype and G allele of rs2110385 in the DR Group were higher than those in the T2DM and NC groups(80.3,69.6,50.0,86.6,79,65.6,P<0.05).3)There were significant differences in allele frequency and genotype frequency distribution of rs2110385 between the DR Group and the NC group(P<0.01).Conclusion:Visfatin increased in the nonproliferative diabetic retinopathy group and could be a potential indicator for the clinical prediction of DR.The G allele of the rs2110385 polymorphic site may be related to the risk of DR.
基金supported by the Natural Science Foundation of Chongqing of China,Nos.cstc2020jcyj-msxmX0698(to YF),cstc2021jcyjbshX0147(to KO)a grant from Chongqing Jiangjin District Bureau of Science and Technology,No.Y2022017(to YF).
文摘Somatostatin,a naturally produced neuroprotective peptide,depresses excitatory neurotransmission and exerts anti-proliferative and anti-inflammatory effects on the retina.In this review,we summarize the progress of somatostatin treatment of diabetic retinopathy through analysis of relevant studies published from February 2019 to February 2023 extracted from the PubMed and Google Scholar databases.Insufficient neuroprotection,which occurs as a consequence of declined expression or dysregulation of retinal somatostatin in the very early stages of diabetic retinopathy,triggers retinal neurovascular unit impairment and microvascular damage.Somatostatin replacement is a promising treatment for retinal neurodegeneration in diabetic retinopathy.Numerous pre-clinical and clinical trials of somatostatin analog treatment for early diabetic retinopathy have been initiated.In one such trial(EUROCONDOR),topical administration of somatostatin was found to exert neuroprotective effects in patients with pre-existing retinal neurodysfunction,but had no impact on the onset of diabetic retinopathy.Overall,we concluded that somatostatin restoration may be especially beneficial for the growing population of patients with early-stage retinopathy.In order to achieve early prevention of diabetic retinopathy initiation,and thereby salvage visual function before the appearance of moderate non-proliferative diabetic retinopathy,several issues need to be addressed.These include the needs to:a)update and standardize the retinal screening scheme to incorporate the detection of early neurodegeneration,b)identify patient subgroups who would benefit from somatostatin analog supplementation,c)elucidate the interactions of somatostatin,particularly exogenously-delivered somatostatin analogs,with other retinal peptides in the context of hyperglycemia,and d)design safe,feasible,low cost,and effective administration routes.
基金supported by the National Natural Science Foundation of China,No. 82171062 (to JFZ)。
文摘Diabetic retinopathy, characterized as a microangiopathy and neurodegenerative disease, is the leading cause of visual impairment in diabetic patients. Many clinical features observed in diabetic retinopathy, such as capillary occlusion, acellular capillaries and retinal non-perfusion, aggregate retinal ischemia and represent relatively late events in diabetic retinopathy. In fact, retinal microvascular injury is an early event in diabetic retinopathy involving multiple biochemical alterations, and is manifested by changes to the retinal neurovascular unit and its cellular components. Currently, intravitreal anti-vascular endothelial growth factor therapy is the firstline treatment for diabetic macular edema, and benefits the patient by decreasing the edema and improving visual acuity. However, a significant proportion of patients respond poorly to anti-vascular endothelial growth factor treatments, indicating that factors other than vascular endothelial growth factor are involved in the pathogenesis of diabetic macular edema. Accumulating evidence confirms that low-grade inflammation plays a critical role in the pathogenesis and development of diabetic retinopathy as multiple inflammatory factors, such as interleukin-1β, monocyte chemotactic protein-1 and tumor necrosis factor-α, are increased in the vitreous and retina of diabetic retinopathy patients. These inflammatory factors, together with growth factors such as vascular endothelial growth factor, contribute to blood-retinal barrier breakdown, vascular damage and neuroinflammation, as well as pathological angiogenesis in diabetic retinopathy, complicated by diabetic macular edema and proliferative diabetic retinopathy. In addition, retinal cell types including microglia, Müller glia, astrocytes, retinal pigment epithelial cells, and others are activated, to secrete inflammatory mediators, aggravating cell apoptosis and subsequent vascular leakage. New therapies, targeting these inflammatory molecules or related signaling pathways, have the potential to inhibit retinal inflammation and prevent diabetic retinopathy progression. Here, we review the relevant literature to date, summarize the inflammatory mechanisms underlying the pathogenesis of diabetic retinopathy, and propose inflammation-based treatments for diabetic retinopathy and diabetic macular edema.
基金supported by the National Natural Science Foundation of China,No.82171062(to JFZ)Aier Eye Hospital Group Scientific Research Fund,No.AF2101D8(to LMG).
文摘Epigenetics focuses on DNA methylation,histone modification,chromatin remodeling,noncoding RNAs,and other gene regulation mechanisms beyond the DNA sequence.In the past decade,epigenetic modifications have drawn more attention as they participate in the development and progression of diabetic retinopathy despite tight control of glucose levels.The underlying mechanisms of epigenetic modifications in diabetic retinopathy still urgently need to be elucidated.The diabetic condition facilitates epigenetic changes and influences target gene expression.In this review,we summarize the involvement of epigenetic modifications and metabolic memory in the development and progression of diabetic retinopathy and propose novel insights into the treatment of diabetic retinopathy.
文摘BACKGROUND Retinopathy is the most common microvascular disease of type 2 diabetes,and seriously threatens the life,health and quality of life of patients.It is worth noting that the development of diabetic retinopathy(DR)can be hidden,with few symptoms.Therefore,the preliminary screening of diabetic patients should identify DR as soon as possible,delay disease progression,and play a vital role in its diagnosis and treatment.AIM To investigate the correlation between glycated hemoglobin A1c(HbA1c),urinary microalbumin(U-mALB),urinary creatinine(U-CR),mALB/U-CR ratio,β2 microglobulin(β2MG),retinol binding protein(RBP)and DR.METHODS A total of 180 patients with type 2 diabetes mellitus attending the Second People’s Hospital of Hefei from January 2022 to August 2022 were retrospectively enrolled by ophthalmologists.Based on whether they had combined retinopathy and its degree,68 patients with diabetes mellitus without retinopathy(NDR)were assigned to the NDR group,54 patients with non-proliferative DR(NPDR)to the NPDR group,and 58 patients with proliferative DR to the PDR group.General data,and HbA1c,mALB,β2MG,RBP,mALB/U-CR and U-CR results were collected from the patients and compared among the groups.Pearson's correlation method was used to analyze the correlation between HbA1c,mALB,β2MG,RBP,mALB/U-CR and U-CR indices,and multiple linear regression was applied to identify the risk factors for DR.Receiver operator characteristic(ROC)curves were also drawn.RESULTS The differences in age,gender,systolic and diastolic blood pressure between the groups were not statistically significantly(P>0.05),but the difference in disease duration was statistically significant(P<0.05).The differences in fasting blood glucose,high-density lipoprotein cholesterol,low-density lipoprotein cholesterol,total cholesterol,and triglyceride between the groups were not statistically significant(P>0.05).HbA1c in the PDR group was higher than that in the NPDR and NDR groups(P<0.05).The levels of mALB,β2MG,RBP,mALB/U-CR and UCR in the PDR group were higher than those in the NPDR and NDR groups(P<0.05).Multiple linear regression analysis showed that disease duration,HbA1c,mALB,β2MG,RBP,mALB/U-CR and U-CR were risk factors for the development of DR.The ROC curve showed that the area under the curve(AUC)for the combination of indices(HbA1c+mALB+mALB/U-CR+U-CR+β2MG+RBP)was 0.958,with a sensitivity of 94.83%and specificity of 96.72%,which was higher than the AUC for single index prediction(P<0.05).CONCLUSION HbA1c,mALB,mALB/U-CR,U-CR,β2MG and RBP can reflect the development of DR and are risk factors affecting PDR,and the combination of these six indices has predictive value for PDR.
基金Supported by Huzhou Science and Technology Planning Program(No.2019GY13).
文摘Diabetic retinopathy(DR)is one of the most common retinal vascular diseases and one of the main causes of blindness worldwide.Early detection and treatment can effectively delay vision decline and even blindness in patients with DR.In recent years,artificial intelligence(AI)models constructed by machine learning and deep learning(DL)algorithms have been widely used in ophthalmology research,especially in diagnosing and treating ophthalmic diseases,particularly DR.Regarding DR,AI has mainly been used in its diagnosis,grading,and lesion recognition and segmentation,and good research and application results have been achieved.This study summarizes the research progress in AI models based on machine learning and DL algorithms for DR diagnosis and discusses some limitations and challenges in AI research.
基金Ministry of Education in Saudi Arabia for funding this research work through the project number (IFP-2020-66).
文摘Biomedical image processing is finding useful in healthcare sector for the investigation,enhancement,and display of images gathered by distinct imaging technologies.Diabetic retinopathy(DR)is an illness caused by diabetes complications and leads to irreversible injury to the retina blood vessels.Retinal vessel segmentation techniques are a basic element of automated retinal disease screening system.In this view,this study presents a novel blood vessel segmentation with deep learning based classification(BVS-DLC)model forDRdiagnosis using retinal fundus images.The proposed BVS-DLC model involves different stages of operations such as preprocessing,segmentation,feature extraction,and classification.Primarily,the proposed model uses the median filtering(MF)technique to remove the noise that exists in the image.In addition,a multilevel thresholding based blood vessel segmentation process using seagull optimization(SGO)with Kapur’s entropy is performed.Moreover,the shark optimization algorithm(SOA)with Capsule Networks(CapsNet)model with softmax layer is employed for DR detection and classification.Awide range of simulations was performed on the MESSIDOR dataset and the results are investigated interms of different measures.The simulation results ensured the better performance of the proposed model compared to other existing techniques interms of sensitivity,specificity,receiver operating characteristic(ROC)curve,accuracy,and F-score.
文摘Diabetic Retinopathy (DR) is a serious hazard that can result inirreversible blindness if not addressed in a timely manner. Hence, numeroustechniques have been proposed for the accurate and timely detection ofthis disease. Out of these, Deep Learning (DL) and Computer Vision (CV)methods for multiclass categorization of color fundus images diagnosed withDiabetic Retinopathy have sparked considerable attention. In this paper,we attempt to develop an extended ResNet152V2 architecture-based DeepLearning model, named ResNet2.0 to aid the timely detection of DR. TheAPTOS-2019 datasetwas used to train the model. This consists of 3662 fundusimages belonging to five different stages of DR: no DR (Class 0), mild DR(Class 1), moderate DR (Class 2), severe DR (Class 3), and proliferativeDR (Class 4). The model was gauged based on ability to detect stage-wiseDR. The images were pre-processed using negative and positive weightedGaussian-based masks as feature engineering to further enhance the qualityof the fundus images by removing the noise and normalizing the images. Upsamplingand data augmentation methods were used to address the skewnessof the original dataset. The proposed model achieved an overall accuracyof 91% and an area under the receiver-operating characteristic curve (AUC)score of 95.1%, outperforming existing Deep Learning models by around 10%.Furthermore, the class-wise F1 score for No DR was 92%, Mild DR was 82%,Moderate DR was 66%, Severe was DR 89% and Proliferative DR was 80%.
文摘Diabetic retinopathy is a critical eye condition that,if not treated,can lead to vision loss.Traditional methods of diagnosing and treating the disease are time-consuming and expensive.However,machine learning and deep transfer learning(DTL)techniques have shown promise in medical applications,including detecting,classifying,and segmenting diabetic retinopathy.These advanced techniques offer higher accuracy and performance.ComputerAided Diagnosis(CAD)is crucial in speeding up classification and providing accurate disease diagnoses.Overall,these technological advancements hold great potential for improving the management of diabetic retinopathy.The study’s objective was to differentiate between different classes of diabetes and verify the model’s capability to distinguish between these classes.The robustness of the model was evaluated using other metrics such as accuracy(ACC),precision(PRE),recall(REC),and area under the curve(AUC).In this particular study,the researchers utilized data cleansing techniques,transfer learning(TL),and convolutional neural network(CNN)methods to effectively identify and categorize the various diseases associated with diabetic retinopathy(DR).They employed the VGG-16CNN model,incorporating intelligent parameters that enhanced its robustness.The outcomes surpassed the results obtained by the auto enhancement(AE)filter,which had an ACC of over 98%.The manuscript provides visual aids such as graphs,tables,and techniques and frameworks to enhance understanding.This study highlights the significance of optimized deep TL in improving the metrics of the classification of the four separate classes of DR.The manuscript emphasizes the importance of using the VGG16CNN classification technique in this context.
基金Supported by National Natural Science Foundation of China(No.81470654)Natural Science Foundation of Shaanxi Province(No.2019SF-047)。
文摘AIM:To evaluate the difference and the correlation between the concentrations of cytokines in the aqueous humor of eyes with macular edema secondary to diabetic retinopathy(DR)or retinal vein occlusion(RVO).METHODS:This is a retrospective case control study.The aqueous humor samples were collected during intravitreal injection of anti-vascular endothelial growth factor(VEGF)for patients diagnosed with macular edema secondary to DR(DME)or RVO(RVO-ME)at Xijing Hospital from August 2021 to July 2022.Meanwhile,aqueous humor samples during vitrectomy from patients with idiopathic macular hole(IMH)were also collected and served as controls.The aqueous humor concentrations of VEGF,platelet-derived factor(PDGF),interleukin(IL)-6,IL-8,IL-18,tumor necrosis factor-α(TNF-α)and monocyte chemoattractant protein 1(MCP-1)were measured with Human Premixed Multi-Analyte Kit(Luminex).The difference of the aqueous cytokines and the correlation between the two diseases were analyzed.RESULTS:A total of 40 eyes of 38 patients were enrolled in the study,including 13 eyes of 11 DME patients(DME group),16 eyes of 16 RVO-ME patients(RVO-ME group)and 11 eyes of 11 IMH patients(control group).The VEGF,PDGF,IL-6,IL-8,and MCP-1 levels of the aqueous humor were higher in both DME and RVO-ME groups compared with the control group(all P<0.05),the levels of TNF-αwas higher in the DME group than in the control group(P<0.05).The VEGF,IL-6,MCP-1,and TNF-αlevels in the aqueous humor were significantly higher in the DR group than those in the RVO group(all P<0.05).Correlation analyses revealed that there were complex positive correlations between IL-6,IL-8,IL-18,MCP-1,and TNF-αlevels in the aqueous humor of eyes with two diseases.CONCLUSION:Although ischemic and inflammatory factors are similarly involved in the pathogenesis of DME and RVO-ME,the roles of these factors are more significant or more likely to be activated in DR patients,suggesting different treatment strategies should be considered for the two diseases.
基金Supported by Model Construction of Regional Prevention and Treatment of Diabetic Retinopathy,Sichuan Science and Technology Support Program (No.2016FZ0091)。
文摘·AIM:To determine the effects of protocatechuic acid(PCA)on streptozocin-induced diabetic retinopathy(DR)in rats.·METHODS:Wistar rats were given a 50 mg/kg intraperitoneal injection of streptozocin to induce diabetes.Animals were assigned randomly one of four groups(8 rats per group):control,diabetic,diabetic plus PCA(25 mg/kg·d),and diabetic plus PCA(50 mg/kg·d).After inducing diabetes,treatments were started one week later and continued for eight weeks.After the experiment,the rats were sacrificed,and their retinas were taken for biochemical and molecular analysis.·RESULTS:PCA administration diminished the blood glucose and glycated haemoglobin levels relative to the diabetic group.In diabetic rats,PCA lowered elevated levels of advanced glycosylated end products(AGEs)and receptor for AGEs(RAGE).In the retina of diabetic rats,PCA effectively decreased inflammatory cytokine,nuclear factor-κB,tumour necrosis factor-α,interleukin-1β,and vascular endothelial growth factor,and increased antioxidant markers glutathione,superoxide dismutase,and catalase.·CONCLUSION:The protective benefits of PCA against DR may be attributable to its suppression of the AGEs and RAGE and its antioxidant and anti-inflammatory properties.
文摘In the modern world,one of the most severe eye infections brought on by diabetes is known as diabetic retinopathy(DR),which will result in retinal damage,and,thus,lead to blindness.Diabetic retinopathy(DR)can be well treated with early diagnosis.Retinal fundus images of humans are used to screen for lesions in the retina.However,detecting DR in the early stages is challenging due to the minimal symptoms.Furthermore,the occurrence of diseases linked to vascular anomalies brought on by DR aids in diagnosing the condition.Nevertheless,the resources required for manually identifying the lesions are high.Similarly,training for Convolutional Neural Networks(CNN)is more time-consuming.This proposed research aims to improve diabetic retinopathy diagnosis by developing an enhanced deep learning model(EDLM)for timely DR identification that is potentially more accurate than existing CNN-based models.The proposed model will detect various lesions from retinal images in the early stages.First,characteristics are retrieved from the retinal fundus picture and put into the EDLM for classification.For dimensionality reduction,EDLM is used.Additionally,the classification and feature extraction processes are optimized using the stochastic gradient descent(SGD)optimizer.The EDLM’s effectiveness is assessed on the KAG-GLE dataset with 3459 retinal images,and results are compared over VGG16,VGG19,RESNET18,RESNET34,and RESNET50.Experimental results show that the EDLM achieves higher average sensitivity by 8.28%for VGG16,by 7.03%for VGG19,by 5.58%for ResNet18,by 4.26%for ResNet 34,and by 2.04%for ResNet 50,respectively.
基金Supported by The Project of National Key Research and Development(No.2018YFC1106103)。
文摘AIM:To explore the correlation between diabetic retinopathy(DR)and Helicobacter pylori(Hp)infection,based on data from a physical examination population.METHODS:This cross-sectional retrospective analysis included data of 73824 health examination participants from December 2018 to December 2019.Participants were divided into the diabetic group and non-diabetic group,nondiabetic retinopathy(NDR)group,non-proliferative diabetic retinopathy(NPDR)group,proliferative diabetic retinopathy(PDR)group,and Hp infection group.Gender,age,body mass index(BMI),systolic blood pressure(SBP),diastolic blood pressure(DBP),fasting plasma glucose(FPG),glycated hemoglobin A1c(HbA1c),triglycerides(TG),total cholesterol(TC),low-density lipoprotein cholesterol(LDL-C),high-density lipoprotein cholesterol(HDL-C),and Hp data were recorded to compare the degree of DR lesions and Hp infection.Logistic regression analysis was used to evaluate the correlation between DR and Hp infection.RESULTS:There was a statistically significant difference between the diabetic and non-diabetic group(χ2=94.17,P<0.0001).Logistic regression analysis showed that male sex,age,BMI,SBP,TG,LDL-C,and Hp infection were independent risk factors for DR.There was no correlation between the degree of DR lesions and Hp infection(ρ=-0.00339,P=0.7753).Age[odds ratio(OR)=1.035,95%CI:1.024,1.046,P<0.0001]and SBP(OR=1.009,95%CI:1.004,1.015,P=0.0013)were independent risk factors for the degree of DR.CONCLUSION:There is a significant correlation between DR and Hp infection in the physical examination population.Hp infection is a risk factor for DR,and there is no significant difference between Hp infection and DR of different pathological degrees.Actively eradicating Hp may be of help to prevent DR.
基金the National Natural Science Foundation of China,No.81870650,No.81570832,and No.81900885Science and Technology Program Chongqing,No.2018GDRC008 and No.XKTS049。
文摘BACKGROUND Glycation is an important step in aging and oxidative stress,which can lead to endothelial dysfunction and cause severe damage to the eyes or kidneys of diabetics.Inhibition of the formation of advanced glycation end products(AGEs)and their cell toxicity can be a useful therapeutic strategy in the prevention of diabetic retinopathy(DR).Gardenia jasminoides Ellis(GJE)fruit is a selective inhibitor of AGEs.Genipin is an active compound of GJE fruit,which can be employed to treat diabetes.AIM To confirm the effect of genipin,a vital component of GJE fruit,in preventing human retinal microvascular endothelial cells(hRMECs)from AGEs damage in DR,to investigate the effect of genipin in the down-regulation of AGEs expression,and to explore the role of the CHGA/UCP2/glucose transporter 1(GLUT1)signal pathway in this process.METHODS In vitro,cell viability was tested to determine the effects of different doses of glucose and genipin in hRMECs.Cell Counting Kit-8(CCK-8),colony formation assay,flow cytometry,immunofluorescence,wound healing assay,transwell assay,and tube-forming assay were used to detect the effect of genipin on hRMECs cultured in high glucose conditions.In vivo,streptozotocin(STZ)induced mice were used,and genipin was administered by intraocular injection(IOI).To explore the effect and mechanism of genipin in diabetic-induced retinal dysfunction,reactive oxygen species(ROS),mitochondrial membrane potential(MMP),and 2-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino]-2-deoxy-d-glucose(2-NBDG)assays were performed to explore energy metabolism and oxidative stress damage in high glucose-induced hRMECs and STZ mouse retinas.Immunofluorescence and Western blot were used to investigate the expression of inflammatory cytokines[vascular endothelial growth factor(VEGF),SCG3,tumor necrosis factor-alpha(TNF-α),interleukin(IL)-1β,IL-18,and nucleotide-binding domain,leucine-rich-containing family,pyrin domain-containing 3(NLRP3)].The protein expression of the receptor of AGEs(RAGE)and the mitochondria-related signal molecules CHGA,GLUT1,and UCP2 in high glucose-induced hRMECs and STZ mouse retinas were measured and compared with the genipin-treated group.RESULTS The results of CCK-8 and colony formation assay showed that genipin promoted cell viability in high glucose(30 mmol/L D-Glucose)-induced hRMECs,especially at a 0.4μmol/L dose for 7 d.Flow cytometry results showed that high glucose can increase apoptosis rate by 30%,and genipin alleviated cell apoptosis in AGEs-induced hRMECs.A high glucose environment promoted ATP,ROS,MMP,and 2-NBDG levels,while genipin inhibited these phenotypic abnormalities in AGEs-induced hRMECs.Furthermore,genipin remarkably reduced the levels of the pro-inflammatory cytokines TNF-α,IL-1β,IL-18,and NLRP3 and impeded the expression of VEGF and SCG3 in AGEs-damaged hRMECs.These results showed that genipin can reverse high glucose induced damage with regard to cell proliferation and apoptosis in vitro,while reducing energy metabolism,oxidative stress,and inflammatory injury caused by high glucose.In addition,ROS levels and glucose uptake levels were higher in the retina from the untreated eye than in the genipin-treated eye of STZ mice.The expression of inflammatory cytokines and pathway protein in the untreated eye compared with the genipin-treated eye was significantly increased,as measured by Western blot.These results showed that IOI of genipin reduced the expression of CHGA,UCP2,and GLUT1,maintained the retinal structure,and decreased ROS,glucose uptake,and inflammation levels in vivo.In addition,we found that SCG3 expression might have a higher sensitivity in DR than VEGF as a diagnostic marker at the protein level.CONCLUSION Our study suggested that genipin ameliorates AGEs-induced hRMECs proliferation,apoptosis,energy metabolism,oxidative stress,and inflammatory injury,partially via the CHGA/UCP2/GLUT1 pathway.Control of advanced glycation by IOI of genipin may represent a strategy to prevent severe retinopathy and vision loss.
文摘·AIM:To elucidate the relationship between macular sensitivity and time in range(TIR)obtained from continuous glucose monitoring(CGM)measures in diabetic patients with or without diabetic retinopathy(DR).·METHODS:This was a cross-sectional study including 100 eyes of non-DR patients and 60 eyes of DR patients.An advanced microperimetry was used to quantitate the retinal mean sensitivity(MS)and fixation stability in central macula.TIR of 3.9-10.0 mmol/L was evaluated with CGM.Pearson coefficient analysis and multiple linear regression analysis were used to assess the correlation between TIR and retinal sensitivity.·RESULTS:In a comparison of non-DR patients,significant differences(P<0.05)were found in Hb A1c,TIR,coefficient of variation(CV),standard deviation of blood glucose(SDBG)and mean amplitude of glucose excursion(MAGE)values in DR patients.Besides,those DR patients had significantly poor best-corrected visual acuity(BCVA,log MAR,P=0.001).In terms of microperimetry parameters,retinal mean sensitivity(MS)and the percentages of fixation points located within 2°and 4°diameter circles were significantly decreased in the DR group(P<0.001,P<0.001,P=0.02,respectively).The bivariate contour ellipse area(BCEA)encompassing 68.2%,95.4%,99.6%of fixation points were all significantly increased in the DR group(P=0.01,P=0.006,P=0.01,respectively).Correlation analysis showed that MS were significantly correlated with Hb A1c(P=0.01).TIR was positively correlated with MS(r=0.23,P=0.01).SDBG was negatively correlated with MS(r=-0.24,P=0.01)but there was no correlation between CV and MAGE with MS(P>0.05).A multivariable linear regression analysis was performed to prove that TIR and SDBG were both independent risk factors for MS reduction in the DR group.·CONCLUSION:TIR is correlated with retinal MS reduction in DR patients,suggesting a useful option for evaluating DR progression.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R195),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘The study aimed to apply to Machine Learning(ML)researchers working in image processing and biomedical analysis who play an extensive role in compre-hending and performing on complex medical data,eventually improving patient care.Developing a novel ML algorithm specific to Diabetic Retinopathy(DR)is a chal-lenge and need of the hour.Biomedical images include several challenges,including relevant feature selection,class variations,and robust classification.Although the cur-rent research in DR has yielded favourable results,several research issues need to be explored.There is a requirement to look at novel pre-processing methods to discard irrelevant features,balance the obtained relevant features,and obtain a robust classi-fication.This is performed using the Steerable Kernalized Partial Derivative and Platt Scale Classifier(SKPD-PSC)method.The novelty of this method relies on the appropriate non-linear classification of exclusive image processing models in har-mony with the Platt Scale Classifier(PSC)to improve the accuracy of DR detection.First,a Steerable Filter Kernel Pre-processing(SFKP)model is applied to the Retinal Images(RI)to remove irrelevant and redundant features and extract more meaningful pathological features through Directional Derivatives of Gaussians(DDG).Next,the Partial Derivative Image Localization(PDIL)model is applied to the extracted fea-tures to localize candidate features and suppress the background noise.Finally,a Platt Scale Classifier(PSC)is applied to the localized features for robust classification.For the experiments,we used the publicly available DR detection database provided by Standard Diabetic Retinopathy(SDR),called DIARETDB0.A database of 130 image samples has been collected to train and test the ML-based classifiers.Experimental results show that the proposed method that combines the image processing and ML models can attain good detection performance with a high DR detection accu-racy rate with minimum time and complexity compared to the state-of-the-art meth-ods.The accuracy and speed of DR detection for numerous types of images will be tested through experimental evaluation.Compared to state-of-the-art methods,the method increases DR detection accuracy by 24%and DR detection time by 37.
