●AIM:To identify the differential methylation sites(DMS)and their according genes associated with diabetic retinopathy(DR)development in type 1 diabetes(T1DM)children.●METHODS:This study consists of two surveys.A to...●AIM:To identify the differential methylation sites(DMS)and their according genes associated with diabetic retinopathy(DR)development in type 1 diabetes(T1DM)children.●METHODS:This study consists of two surveys.A total of 40 T1DM children was included in the first survey.Because no participant has DR,retina thinning was used as a surrogate indicator for DR.The lowest 25%participants with the thinnest macular retinal thickness were included into the case group,and the others were controls.The DNA methylation status was assessed by the Illumina methylation 850K array BeadChip assay,and compared between the case and control groups.Four DMS with a potential role in diabetes were identified.The second survey included 27 T1DM children,among which four had DR.The methylation patterns of the four DMS identified by 850K were compared between participants with and without DR by pyrosequencing.●RESULTS:In the first survey,the 850K array revealed 751 sites significantly and differentially methylated in the case group comparing with the controls(|Δβ|>0.1 and Adj.P<0.05),and 328 of these were identified with a significance of Adj.P<0.01.Among these,319 CpG sites were hypermethylated and 432 were hypomethylated in the case group relative to the controls.Pyrosequencing revealed that the transcription elongation regulator 1 like(TCERG1L,cg07684215)gene was hypermethylated in the four T1DM children with DR(P=0.018),which was consistent with the result from the first survey.The methylation status of the other three DMS(cg26389052,cg25192647,and cg05413694)showed no difference(all P>0.05)between participants with and without DR.●CONCLUSION:The hypermethylation of the TCERG1L gene is a risk factor for DR development in Chinese children with T1DM.展开更多
Early screening of diabetes retinopathy(DR)plays an important role in preventing irreversible blindness.Existing research has failed to fully explore effective DR lesion information in fundus maps.Besides,traditional ...Early screening of diabetes retinopathy(DR)plays an important role in preventing irreversible blindness.Existing research has failed to fully explore effective DR lesion information in fundus maps.Besides,traditional attention schemes have not considered the impact of lesion type differences on grading,resulting in unreasonable extraction of important lesion features.Therefore,this paper proposes a DR diagnosis scheme that integrates a multi-level patch attention generator(MPAG)and a lesion localization module(LLM).Firstly,MPAGis used to predict patches of different sizes and generate a weighted attention map based on the prediction score and the types of lesions contained in the patches,fully considering the impact of lesion type differences on grading,solving the problem that the attention maps of lesions cannot be further refined and then adapted to the final DR diagnosis task.Secondly,the LLM generates a global attention map based on localization.Finally,the weighted attention map and global attention map are weighted with the fundus map to fully explore effective DR lesion information and increase the attention of the classification network to lesion details.This paper demonstrates the effectiveness of the proposed method through extensive experiments on the public DDR dataset,obtaining an accuracy of 0.8064.展开更多
AIM:To investigate systemic immune-inflammation index(SII),neutrophil-to-lymphocyte ratio(NLR),and plateletto-lymphocyte ratio(PLR)levels in patients with type 2 diabetes at different stages of diabetic retinopathy(DR...AIM:To investigate systemic immune-inflammation index(SII),neutrophil-to-lymphocyte ratio(NLR),and plateletto-lymphocyte ratio(PLR)levels in patients with type 2 diabetes at different stages of diabetic retinopathy(DR).METHODS:This retrospective study included 141 patients with type 2 diabetes mellitus(DM):45 without diabetic retinopathy(NDR),47 with non-proliferative diabetic retinopathy(NPDR),and 49 with proliferative diabetic retinopathy(PDR).Complete blood counts were obtained,and NLR,PLR,and SII were calculated.The study analysed the ability of inflammatory markers to predict DR using receiver operating characteristic(ROC)curves.The relationships between DR stages and SII,PLR,and NLP were assessed using multivariate logistic regression.RESULTS:The average NLR,PLR,and SII were higher in the PDR group than in the NPDR group(P=0.011,0.043,0.009,respectively);higher in the NPDR group than in the NDR group(P<0.001 for all);and higher in the PDR group than in the NDR group(P<0.001 for all).In the ROC curve analysis,the NLR,PLR,and SII were significant predictors of DR(P<0.001 for all).The highest area under the curve(AUC)was for the PLR(0.929 for PLR,0.925 for SII,and 0.821 for NLR).Multivariate regression analysis indicated that NLR,PLR,and SII were statistically significantly positive and independent predictors for the DR stages in patients with DM[odds ratio(OR)=1.122,95%confidence interval(CI):0.200–2.043,P<0.05;OR=0.038,95%CI:0.018–0.058,P<0.05;OR=0.007,95%CI:0.001–0.01,P<0.05,respectively).CONCLUSION:The NLR,PLR,and SII may be used as predictors of DR.展开更多
Artificial Intelligence(AI)is being increasingly used for diagnosing Vision-Threatening Diabetic Retinopathy(VTDR),which is a leading cause of visual impairment and blindness worldwide.However,previous automated VTDR ...Artificial Intelligence(AI)is being increasingly used for diagnosing Vision-Threatening Diabetic Retinopathy(VTDR),which is a leading cause of visual impairment and blindness worldwide.However,previous automated VTDR detection methods have mainly relied on manual feature extraction and classification,leading to errors.This paper proposes a novel VTDR detection and classification model that combines different models through majority voting.Our proposed methodology involves preprocessing,data augmentation,feature extraction,and classification stages.We use a hybrid convolutional neural network-singular value decomposition(CNN-SVD)model for feature extraction and selection and an improved SVM-RBF with a Decision Tree(DT)and K-Nearest Neighbor(KNN)for classification.We tested our model on the IDRiD dataset and achieved an accuracy of 98.06%,a sensitivity of 83.67%,and a specificity of 100%for DR detection and evaluation tests,respectively.Our proposed approach outperforms baseline techniques and provides a more robust and accurate method for VTDR detection.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
AIM:To explore the correlation of gut microbiota and the metabolites with the progression of diabetic retinopathy(DR)and provide a novel strategy to elucidate the pathological mechanism of DR.METHODS:The fecal samples...AIM:To explore the correlation of gut microbiota and the metabolites with the progression of diabetic retinopathy(DR)and provide a novel strategy to elucidate the pathological mechanism of DR.METHODS:The fecal samples from 32 type 2 diabetes patients with proliferative retinopathy(PDR),23 with nonproliferative retinopathy(NPDR),27 without retinopathy(DM),and 29 from the sex-,age-and BMI-matched healthy controls(29 HC)were analyzed by 16S rDNA gene sequencing.Sixty fecal samples from PDR,DM,and HC groups were assayed by untargeted metabolomics.Fecal metabolites were measured using liquid chromatographymass spectrometry(LC-MS)analysis.Associations between gut microbiota and fecal metabolites were analyzed.RESULTS:A cluster of 2 microbiome and 12 metabolites accompanied with the severity of DR,and the close correlation of the disease progression with PDR-related microbiome and metabolites were found.To be specific,the structure of gut microbiota differed in four groups.Diversity and richness of gut microbiota were significantly lower in PDR and NPDR groups,than those in DM and HC groups.A cluster of microbiome enriched in PDR group,including Pseudomonas,Ruminococcaceae-UCG-002,Ruminococcaceae-UCG-005,Christensenellaceae-R-7,was observed.Functional analysis showed that the glucose and nicotinate degradations were significantly higher in PDR group than those in HC group.Arginine,serine,ornithine,and arachidonic acid were significantly enriched in PDR group,while proline was enriched in HC group.Functional analysis illustrated that arginine biosynthesis,lysine degradation,histidine catabolism,central carbon catabolism in cancer,D-arginine and D-ornithine catabolism were elevated in PDR group.Correlation analysis revealed that Ruminococcaceae-UCG-002 and Christensenellaceae-R-7 were positively associated with L-arginine,ornithine levels in fecal samples.CONCLUSION:This study elaborates the different microbiota structure in the gut from four groups.The relative abundance of Ruminococcaceae-UCG-002 and Parabacteroides are associated with the severity of DR.Amino acid and fatty acid catabolism is especially disordered in PDR group.This may help provide a novel diagnostic parameter for DR,especially PDR.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 a prevalent microvascular complication of diabetes and the leading cause of blindness and severe visual impairment in adults.The high levels of glucose trigger multiple intracellular oxidati...Diabetic retinopathy(DR)is a prevalent microvascular complication of diabetes and the leading cause of blindness and severe visual impairment in adults.The high levels of glucose trigger multiple intracellular oxidative stress pathways,such as POLDIP2,resulting in excessive reactive oxygen species(ROS)production and increased expression of vascular cell adhesion molecule-1(VCAM-1),hypoxia-inducible factor 1a(HIF-1a),and vascular endothelial growth factor(VEGF),causing microvascular dysfunction.Dihydromyricetin(DMY)is a natural flavonoid small molecule antioxidant.However,it exhibits poor solubility in physiological environments,has a short half-life in vivo,and has low oral bioavailability.In this study,we present,for the first time,the synthesis of ultra-small Fe-DMY nano-coordinated polymer particles(Fe-DMY NCPs),formed by combining DMY with low-toxicity iron ions.In vitro and in vivo experiments confirm that Fe-DMY NCPs alleviate oxidative stress-induced damage to vascular endothelial cells by high glucose,scavenge excess ROS,and improve pathological features of DR,such as retinal vascular leakage and neovascularization.Mechanistic validation indicates that Fe-DMY NCPs can inhibit the activation of the Poldip2-Nox4-H_(2)O_(2) signaling pathway and downregulate vital vascular function indicators such as VCAM-1,HIF-1a,and VEGF.These findings suggest that Fe-DMY NCPs could serve as a safe and effective antioxidant and microangio-protective agent,with the potential as a novel multimeric drug for DR therapy.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
基金Supported by the National Key Research and Development Program of China(No.2016YFC0904800)National Natural Science Foundation of China(No.82101181)+1 种基金China Scholarship Council(No.201506230096)Shanghai Sailing Program(No.19YF1439700).
文摘●AIM:To identify the differential methylation sites(DMS)and their according genes associated with diabetic retinopathy(DR)development in type 1 diabetes(T1DM)children.●METHODS:This study consists of two surveys.A total of 40 T1DM children was included in the first survey.Because no participant has DR,retina thinning was used as a surrogate indicator for DR.The lowest 25%participants with the thinnest macular retinal thickness were included into the case group,and the others were controls.The DNA methylation status was assessed by the Illumina methylation 850K array BeadChip assay,and compared between the case and control groups.Four DMS with a potential role in diabetes were identified.The second survey included 27 T1DM children,among which four had DR.The methylation patterns of the four DMS identified by 850K were compared between participants with and without DR by pyrosequencing.●RESULTS:In the first survey,the 850K array revealed 751 sites significantly and differentially methylated in the case group comparing with the controls(|Δβ|>0.1 and Adj.P<0.05),and 328 of these were identified with a significance of Adj.P<0.01.Among these,319 CpG sites were hypermethylated and 432 were hypomethylated in the case group relative to the controls.Pyrosequencing revealed that the transcription elongation regulator 1 like(TCERG1L,cg07684215)gene was hypermethylated in the four T1DM children with DR(P=0.018),which was consistent with the result from the first survey.The methylation status of the other three DMS(cg26389052,cg25192647,and cg05413694)showed no difference(all P>0.05)between participants with and without DR.●CONCLUSION:The hypermethylation of the TCERG1L gene is a risk factor for DR development in Chinese children with T1DM.
基金supported in part by the Research on the Application of Multimodal Artificial Intelligence in Diagnosis and Treatment of Type 2 Diabetes under Grant No.2020SK50910in part by the Hunan Provincial Natural Science Foundation of China under Grant 2023JJ60020.
文摘Early screening of diabetes retinopathy(DR)plays an important role in preventing irreversible blindness.Existing research has failed to fully explore effective DR lesion information in fundus maps.Besides,traditional attention schemes have not considered the impact of lesion type differences on grading,resulting in unreasonable extraction of important lesion features.Therefore,this paper proposes a DR diagnosis scheme that integrates a multi-level patch attention generator(MPAG)and a lesion localization module(LLM).Firstly,MPAGis used to predict patches of different sizes and generate a weighted attention map based on the prediction score and the types of lesions contained in the patches,fully considering the impact of lesion type differences on grading,solving the problem that the attention maps of lesions cannot be further refined and then adapted to the final DR diagnosis task.Secondly,the LLM generates a global attention map based on localization.Finally,the weighted attention map and global attention map are weighted with the fundus map to fully explore effective DR lesion information and increase the attention of the classification network to lesion details.This paper demonstrates the effectiveness of the proposed method through extensive experiments on the public DDR dataset,obtaining an accuracy of 0.8064.
基金Affiliated Jinling Hospital,Medical School of Nanjing University(No.22JCYYYB29).
文摘AIM:To investigate systemic immune-inflammation index(SII),neutrophil-to-lymphocyte ratio(NLR),and plateletto-lymphocyte ratio(PLR)levels in patients with type 2 diabetes at different stages of diabetic retinopathy(DR).METHODS:This retrospective study included 141 patients with type 2 diabetes mellitus(DM):45 without diabetic retinopathy(NDR),47 with non-proliferative diabetic retinopathy(NPDR),and 49 with proliferative diabetic retinopathy(PDR).Complete blood counts were obtained,and NLR,PLR,and SII were calculated.The study analysed the ability of inflammatory markers to predict DR using receiver operating characteristic(ROC)curves.The relationships between DR stages and SII,PLR,and NLP were assessed using multivariate logistic regression.RESULTS:The average NLR,PLR,and SII were higher in the PDR group than in the NPDR group(P=0.011,0.043,0.009,respectively);higher in the NPDR group than in the NDR group(P<0.001 for all);and higher in the PDR group than in the NDR group(P<0.001 for all).In the ROC curve analysis,the NLR,PLR,and SII were significant predictors of DR(P<0.001 for all).The highest area under the curve(AUC)was for the PLR(0.929 for PLR,0.925 for SII,and 0.821 for NLR).Multivariate regression analysis indicated that NLR,PLR,and SII were statistically significantly positive and independent predictors for the DR stages in patients with DM[odds ratio(OR)=1.122,95%confidence interval(CI):0.200–2.043,P<0.05;OR=0.038,95%CI:0.018–0.058,P<0.05;OR=0.007,95%CI:0.001–0.01,P<0.05,respectively).CONCLUSION:The NLR,PLR,and SII may be used as predictors of DR.
基金This research was funded by the National Natural Science Foundation of China(Nos.71762010,62262019,62162025,61966013,12162012)the Hainan Provincial Natural Science Foundation of China(Nos.823RC488,623RC481,620RC603,621QN241,620RC602,121RC536)+1 种基金the Haikou Science and Technology Plan Project of China(No.2022-016)the Project supported by the Education Department of Hainan Province,No.Hnky2021-23.
文摘Artificial Intelligence(AI)is being increasingly used for diagnosing Vision-Threatening Diabetic Retinopathy(VTDR),which is a leading cause of visual impairment and blindness worldwide.However,previous automated VTDR detection methods have mainly relied on manual feature extraction and classification,leading to errors.This paper proposes a novel VTDR detection and classification model that combines different models through majority voting.Our proposed methodology involves preprocessing,data augmentation,feature extraction,and classification stages.We use a hybrid convolutional neural network-singular value decomposition(CNN-SVD)model for feature extraction and selection and an improved SVM-RBF with a Decision Tree(DT)and K-Nearest Neighbor(KNN)for classification.We tested our model on the IDRiD dataset and achieved an accuracy of 98.06%,a sensitivity of 83.67%,and a specificity of 100%for DR detection and evaluation tests,respectively.Our proposed approach outperforms baseline techniques and provides a more robust and accurate method for VTDR detection.
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.
文摘AIM:To explore the correlation of gut microbiota and the metabolites with the progression of diabetic retinopathy(DR)and provide a novel strategy to elucidate the pathological mechanism of DR.METHODS:The fecal samples from 32 type 2 diabetes patients with proliferative retinopathy(PDR),23 with nonproliferative retinopathy(NPDR),27 without retinopathy(DM),and 29 from the sex-,age-and BMI-matched healthy controls(29 HC)were analyzed by 16S rDNA gene sequencing.Sixty fecal samples from PDR,DM,and HC groups were assayed by untargeted metabolomics.Fecal metabolites were measured using liquid chromatographymass spectrometry(LC-MS)analysis.Associations between gut microbiota and fecal metabolites were analyzed.RESULTS:A cluster of 2 microbiome and 12 metabolites accompanied with the severity of DR,and the close correlation of the disease progression with PDR-related microbiome and metabolites were found.To be specific,the structure of gut microbiota differed in four groups.Diversity and richness of gut microbiota were significantly lower in PDR and NPDR groups,than those in DM and HC groups.A cluster of microbiome enriched in PDR group,including Pseudomonas,Ruminococcaceae-UCG-002,Ruminococcaceae-UCG-005,Christensenellaceae-R-7,was observed.Functional analysis showed that the glucose and nicotinate degradations were significantly higher in PDR group than those in HC group.Arginine,serine,ornithine,and arachidonic acid were significantly enriched in PDR group,while proline was enriched in HC group.Functional analysis illustrated that arginine biosynthesis,lysine degradation,histidine catabolism,central carbon catabolism in cancer,D-arginine and D-ornithine catabolism were elevated in PDR group.Correlation analysis revealed that Ruminococcaceae-UCG-002 and Christensenellaceae-R-7 were positively associated with L-arginine,ornithine levels in fecal samples.CONCLUSION:This study elaborates the different microbiota structure in the gut from four groups.The relative abundance of Ruminococcaceae-UCG-002 and Parabacteroides are associated with the severity of DR.Amino acid and fatty acid catabolism is especially disordered in PDR group.This may help provide a novel diagnostic parameter for DR,especially PDR.
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.
文摘Diabetic retinopathy(DR)is a prevalent microvascular complication of diabetes and the leading cause of blindness and severe visual impairment in adults.The high levels of glucose trigger multiple intracellular oxidative stress pathways,such as POLDIP2,resulting in excessive reactive oxygen species(ROS)production and increased expression of vascular cell adhesion molecule-1(VCAM-1),hypoxia-inducible factor 1a(HIF-1a),and vascular endothelial growth factor(VEGF),causing microvascular dysfunction.Dihydromyricetin(DMY)is a natural flavonoid small molecule antioxidant.However,it exhibits poor solubility in physiological environments,has a short half-life in vivo,and has low oral bioavailability.In this study,we present,for the first time,the synthesis of ultra-small Fe-DMY nano-coordinated polymer particles(Fe-DMY NCPs),formed by combining DMY with low-toxicity iron ions.In vitro and in vivo experiments confirm that Fe-DMY NCPs alleviate oxidative stress-induced damage to vascular endothelial cells by high glucose,scavenge excess ROS,and improve pathological features of DR,such as retinal vascular leakage and neovascularization.Mechanistic validation indicates that Fe-DMY NCPs can inhibit the activation of the Poldip2-Nox4-H_(2)O_(2) signaling pathway and downregulate vital vascular function indicators such as VCAM-1,HIF-1a,and VEGF.These findings suggest that Fe-DMY NCPs could serve as a safe and effective antioxidant and microangio-protective agent,with the potential as a novel multimeric drug for DR therapy.
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.
