TCERG1L hypermethylation is a risk factor of diabetic retinopathy in Chinese children with type 1 diabetes

●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.

HHO optimized support vector machine classifier for traditional Chinese medicine syndrome differentiation of diabetic retinopathy

AIM:To develop a classifier for traditional Chinese medicine(TCM)syndrome differentiation of diabetic retinopathy(DR),using optimized machine learning algorithms,which can provide the basis for TCM objective and intelligent syndrome differentiation.METHODS:Collated data on real-world DR cases were collected.A variety of machine learning methods were used to construct TCM syndrome classification model,and the best performance was selected as the basic model.Genetic Algorithm(GA)was used for feature selection to obtain the optimal feature combination.Harris Hawk Optimization(HHO)was used for parameter optimization,and a classification model based on feature selection and parameter optimization was constructed.The performance of the model was compared with other optimization algorithms.The models were evaluated with accuracy,precision,recall,and F1 score as indicators.RESULTS:Data on 970 cases that met screening requirements were collected.Support Vector Machine(SVM)was the best basic classification model.The accuracy rate of the model was 82.05%,the precision rate was 82.34%,the recall rate was 81.81%,and the F1 value was 81.76%.After GA screening,the optimal feature combination contained 37 feature values,which was consistent with TCM clinical practice.The model based on optimal combination and SVM(GA_SVM)had an accuracy improvement of 1.92%compared to the basic classifier.SVM model based on HHO and GA optimization(HHO_GA_SVM)had the best performance and convergence speed compared with other optimization algorithms.Compared with the basic classification model,the accuracy was improved by 3.51%.CONCLUSION:HHO and GA optimization can improve the model performance of SVM in TCM syndrome differentiation of DR.It provides a new method and research idea for TCM intelligent assisted syndrome differentiation.

Enhancing diabetic retinopathy screening:Non-mydriatic fundus photography-assisted telemedicine for improved clinical management

The utilization of non-mydriatic fundus photography-assisted telemedicine to screen patients with diabetes mellitus for diabetic retinopathy provides an accurate,efficient,and cost-effective method to improve early detection of disease.It has also been shown to correlate with increased participation of patients in other aspects of diabetes care.In particular,patients who undergo teleretinal imaging are more likely to meet Comprehensive Diabetes Care Healthcare Effectiveness Data and Information Set metrics,which are linked to preservation of quality-adjusted life years and additional downstream healthcare savings.

Application of non-mydriatic fundus photography-assisted telemedicine in diabetic retinopathy screening

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.

Genipin relieves diabetic retinopathy by down-regulation of advanced glycation end products via the mitochondrial metabolism related signaling pathway

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.

Quantifying peripapillary vessel density and retinal nerve fibre layer in type 1 diabetic children without clinically detectable retinopathy using OCTA

AIM:To quantify changes in radial peripapillary capillary vessel density(ppVD)and the peripapillary retinal nerve fiber layer(pRNFL)in children with type 1 diabetes without clinical diabetic retinopathy by optical coherence tomography angiography(OCTA),providing a basis for early retinopathy in children with type 1 diabetes.METHODS:This was a retrospective study.A total of 30 patients(3–14y)with type 1 diabetes without clinical diabetic retinopathy(NDR group)were included.A total of 30 age-matched healthy subjects were included as the normal control group(CON group).The HbA1c level in the last 3mo was measured once in the NDR group.The pRNFL thickness and ppVD were automatically measured,and the mean pRNFL and ppVD were calculated in the nasal,inferior,temporal,and superior quadrants.The changes in ppVD and pRNFL in the two groups were analyzed.RESULTS:Compared with CON group,the nasal and superior ppVDs decreased in the NDR group(all P<0.01).The thickness of the nasal pRNFL decreased significantly(P<0.01),while the inferior,temporal and superior pRNFLs slightly decreased but not significant in the NDR group(all P>0.05).Person and Spearman correlation analysis of ppVD and pRNFL thickness in each quadrant of the NDR group showed a positive correlation between nasal and superior(all P<0.01),while inferior and temporal had no significant correlation(all P>0.05).There was no significant correlation between the HbA1c level and ppVD and pRNFL in any quadrant(all P>0.05).There was no significant correlation between the course of diabetes mellitus and ppVD and pRNFL in any quadrant(all P>0.05).CONCLUSION:ppVD and pRNFL decrease in eyes of children with type 1 diabetes before clinically detectable retinopathy and OCTA is helpful for early monitoring.

Obesity, metabolic syndrome and diabetic retinopathy: Beyond hyperglycemia

Diabetic retinopathy(DR) is the most feared ocular manifestation of diabetes. DR is characterized by progressive retinal damage that may eventually result in blindness. Clinically, this blindness is caused by progressive damage to the retinal microvasculature, which leads to ischemia, retinal swelling, and neovascularization. Retinopathy is associated with both type 1 and type 2 diabetes, with DR being the leading cause of new onset blindness in United States adults. Despite this strong association with diabetes, it must be noted that the development of retinopathy lesions is multifactorial and may occur in individuals without an established history of diabetes. Metabolic syndrome is a multifactorial condition of central obesity, hypertriglyceridemia, dyslipidemia, hypertension, fasting hyperglycemia, and insulin resistance. Although several studies examined the individual components observed in the metabolic syndrome in relation to the development of DR, there is conflicting data as to the association of the metabolic syndrome with the development of retinopathy lesions in nondiabetic subjects. This review will summarize the current literature on the evidence of the metabolic syndrome on retinopathy in subjects with and without an established history of diabetes. This review will also discuss some of the mechanisms through which metabolic syndrome can contribute to the development of retinopathy.

Methylenetrahydrofolate Reductase Gene C677T Polymorphism and Diabetic Retinopathy: a Meta-Analysis

Objective To investigate the association between the methylenetetrahydrofolate reductase gene C677T(MTHFR C677T)polymorphism and diabetic retinopathy(DR).Methods A total of 6971 subjects including 2707 DR patients and 4264 controls from 23 studies were enrolled in the study.A random-effects model was applied to estimate the overall effects and the stratified effects of the MTHFR C677T polymorphism on the risk of DR,and study quality was also assessed.Results Strong associations were observed between the MTHFR C677T polymorphism and DR.The carries of MTHFR C677T were more likely to be found in the DR group in relative to the healthy control group with odds ratio 1.6&2.55,and 2.31 respectively in allele contrast model(T vs.C,95%CZ:1.29-2.18,P<0.001,f=7&4%),homozygous model(TT vs.CC,95%CZ:1.70-3.83,P=0.008,72=54.4%)and dominant model(TT+CT vs.CC,95%CZ:1.62-3.29,P<0.001,12=74.7%).This association can also be found in contrast to the Ned(non-complicated diabetic mellitus)group(allele contrast,OR—1.50,95%Ch 1.07-2.11,P=0.032,I2=62.1%;homozygous,OR—2.39,9S%CZ:1.06-5.38,P=0.017,Z2=66.7%;dominant,OR=1.59,95%CZ:0.97-2.62,P=0.056,I2=56.5%).For the heterozygous model(CT vs.CC),the association was significant in contrast to the healthy control group(OR=1.46,95%CZ:1.64-3.69,P=0,P=77.3%),while in contrast to the Ned control group the association was not statistically meaningful(OR=1.38,95%CZ:0.87-2.18,P=0.131,Z2=43.7%).For the recessive model,1.92-fold increased risk was found only in contrast to the Ned control group(95%C1:1.07-3.43,P=0.064,P=55.0%).There was no significant association found in the models in contrast to the DM control group.Conclusion In this meta-analysis,we found an association between the MTHFR C677T polymorphism and DR,especially in contrast to the Ned control group.Further studies are required to establish more definite relationship.

Key genes and regulatory networks for diabetic retinopathy based on hypoxia-related genes:a bioinformatics analysis

AIM:To prevent neovascularization in diabetic retinopathy(DR)patients and partially control disease progression.METHODS:Hypoxia-related differentially expressed genes(DEGs)were identified from the GSE60436 and GSE102485 datasets,followed by gene ontology(GO)functional annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis.Potential candidate drugs were screened using the CMap database.Subsequently,a protein-protein interaction(PPI)network was constructed to identify hypoxia-related hub genes.A nomogram was generated using the rms R package,and the correlation of hub genes was analyzed using the Hmisc R package.The clinical significance of hub genes was validated by comparing their expression levels between disease and normal groups and constructing receiver operating characteristic curve(ROC)curves.Finally,a hypoxia-related miRNA-transcription factor(TF)-Hub gene network was constructed using the NetworkAnalyst online tool.RESULTS:Totally 48 hypoxia-related DEGs and screened 10 potential candidate drugs with interaction relationships to upregulated hypoxia-related genes were identified,such as ruxolitinib,meprylcaine,and deferiprone.In addition,8 hub genes were also identified:glycogen phosphorylase muscle associated(PYGM),glyceraldehyde-3-phosphate dehydrogenase spermatogenic(GAPDHS),enolase 3(ENO3),aldolase fructose-bisphosphate C(ALDOC),phosphoglucomutase 2(PGM2),enolase 2(ENO2),phosphoglycerate mutase 2(PGAM2),and 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3(PFKFB3).Based on hub gene predictions,the miRNA-TF-Hub gene network revealed complex interactions between 163 miRNAs,77 TFs,and hub genes.The results of ROC showed that the except for GAPDHS,the area under curve(AUC)values of the other 7 hub genes were greater than 0.758,indicating their favorable diagnostic performance.CONCLUSION:PYGM,GAPDHS,ENO3,ALDOC,PGM2,ENO2,PGAM2,and PFKFB3 are hub genes in DR,and hypoxia-related hub genes exhibited favorable diagnostic performance.

Scheme Based on Multi-Level Patch Attention and Lesion Localization for Diabetic Retinopathy Grading

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.

DeepSVDNet:A Deep Learning-Based Approach for Detecting and Classifying Vision-Threatening Diabetic Retinopathy in Retinal Fundus Images

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.

Efficacy of recombinant human epidermal growth factor plus sodium hyaluronate eye drops in diabetic dry eye post-cataract surgery

BACKGROUND Dry eye syndrome(DES)after diabetic cataract surgery can seriously affect the patient’s quality of life.Therefore,effective alleviation of symptoms in patients with this disease has important clinical significance.AIM To explore the clinical effect of recombinant human epidermal growth factor(rhEGF)plus sodium hyaluronate(SH)eye drops on DES after cataract surgery in patients with diabetes.METHODS We retrospectively evaluated 82 patients with diabetes who experienced DES after cataract surgery at Tianjin Beichen Hospital,Affiliated Hospital of Nankai University between April 2021 and April 2023.They were classified into an observation group(42 cases,rhEGF+SH eye drops)and a control group(40 cases,SH eye drops alone),depending on the different treatment schemes.The therapeutic efficacy,dry eye symptom score,tear film breakup time(TFBUT),basic tear secretion score[assessed using Schirmer I test(SIt)],corneal fluorescein staining(FL)score,tear inflammatory markers,adverse reactions during treat-ment,and treatment satisfaction were compared between the two groups.RESULTS Therapeutic efficacy was higher in the observation group compared with the control group.Both groups showed improved TFBUT and dry eye,as well as improved SIt and FL scores after treatment,with a more pronounced improvement in the observation group.Although no marked differences in adverse reactions were observed between the two groups,treatment satisfaction was higher in the observation group.CONCLUSION rhEGF+SH eye drops rendered clinical benefits to patients by effectively ameliorating dry eye and visual impairment with favorable efficacy,fewer adverse reactions,and high safety levels.Thus,this treatment should be promoted in clinical practice.

Automatic diagnosis of diabetic retinopathy using vision transformer based on wide-field optical coherence tomography angiography

Diabetic retinopathy(DR)is one of the major causes of visual impairment in adults with diabetes.Optical coherence tomography angiography(OCTA)is nowadays widely used as the golden criterion for diagnosing DR.Recently,wide-field OCTA(WF-OCTA)provided more abundant information including that of the peripheral retinal degenerative changes and it can contribute in accurately diagnosing DR.The need for an automatic DR diagnostic system based on WF-OCTA pictures attracts more and more attention due to the large diabetic population and the prevalence of retinopathy cases.In this study,automatic diagnosis of DR using vision transformer was performed using WF-OCTA images(12 mm×12 mm single-scan)centered on the fovea as the dataset.WF-OCTA images were automatically classified into four classes:No DR,mild nonproliferative diabetic retinopathy(NPDR),moderate to severe NPDR,and proliferative diabetic retinopathy(PDR).The proposed method for detecting DR on the test set achieves accuracy of 99.55%,sensitivity of 99.49%,and specificity of 99.57%.The accuracy of the method for DR staging reaches up to 99.20%,which has been proven to be higher than that attained by classical convolutional neural network models.Results show that the automatic diagnosis of DR based on vision transformer and WF-OCTA pictures is more effective for detecting and staging DR.

Retinal vascular morphological characteristics in diabetic retinopathy: an artificial intelligence study using a transfer learning system to analyze ultra-wide field images

AIM:To investigate the morphological characteristics of retinal vessels in patients with different severity of diabetic retinopathy(DR)and in patients with or without diabetic macular edema(DME).METHODS:The 239 eyes of DR patients and 100 eyes of healthy individuals were recruited for the study.The severity of DR patients was graded as mild,moderate and severe non-proliferative diabetic retinopathy(NPDR)according to the international clinical diabetic retinopathy(ICDR)disease severity scale classification,and retinal vascular morphology was quantitatively analyzed in ultra-wide field images using RU-net and transfer learning methods.The presence of DME was determined by optical coherence tomography(OCT),and differences in vascular morphological characteristics were compared between patients with and without DME.RESULTS:Retinal vessel segmentation using RU-net and transfer learning system had an accuracy of 99%and a Dice metric of 0.76.Compared with the healthy group,the DR group had smaller vessel angles(33.68±3.01 vs 37.78±1.60),smaller fractal dimension(Df)values(1.33±0.05 vs 1.41±0.03),less vessel density(1.12±0.44 vs 2.09±0.36)and fewer vascular branches(206.1±88.8 vs 396.5±91.3),all P<0.001.As the severity of DR increased,Df values decreased,P=0.031.No significant difference between the DME and non-DME groups were observed in vascular morphological characteristics.CONCLUSION:In this study,an artificial intelligence retinal vessel segmentation system is used with 99%accuracy,thus providing with relatively satisfactory performance in the evaluation of quantitative vascular morphology.DR patients have a tendency of vascular occlusion and dropout.The presence of DME does not compromise the integral retinal vascular pattern.

Proteomic study of vitreous in proliferative diabetic retinopathy patients after treatment with aflibercept:a quantitative analysis based on 4D label-free technique

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.

Systemic immune-inflammation index,neutrophilto-lymphocyte ratio,and platelet-to-lymphocyte ratio in patients with type 2 diabetes at different stages of diabetic retinopathy

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.

Intravitreal conbercept injection with panretinal photocoagulation for high-risk proliferative diabetic retinopathy with vitreous hemorrhage

AIM:To assess the clinical efficacy and safety of combining panretinal photocoagulation(PRP)with intravitreal conbercept(IVC)injections for patients with high-risk proliferative diabetic retinopathy(HR-PDR)complicated by mild or moderate vitreous hemorrhage(VH),with or without diabetic macular edema(DME).METHODS:Patients diagnosed with VH with/without DME secondary to HR-PDR and received PRP combined with IVC injections were recruited in this retrospective study.Upon establishing the patient’s diagnosis,an initial IVC was performed,followed by prompt administration of PRP.In cases who significant bleeding persisted and impeded the laser operation,IVC was sustained before supplementing with PRP.Following the completion of PRP,patients were meticulously monitored for a minimum of six months.Laser therapy and IVC injections were judiciously adjusted based on fundus fluorescein angiography(FFA)results.Therapeutic effect and the incidence of adverse events were observed.RESULTS:Out of 42 patients(74 eyes),29 were male and 13 were female,with a mean age of 59.17±12.74y(33-84y).The diabetic history was between 1wk and 26y,and the interval between the onset of visual symptoms and diagnosis of HR-PDR was 1wk-1y.The affected eye received 2.59±1.87(1-10)IVC injections and underwent 5.5±1.02(4-8)sessions of PRP.Of these,68 eyes received PRP following 1 IVC injection,5 eyes after 2 IVC injections,and 1 eye after 3 IVC injections.Complete absorption of VH was observed in all 74 eyes 5-50wk after initial treatment,with resolution of DME in 51 eyes 3-48wk after initial treatment.A newly developed epiretinal membrane was noted in one eye.Visual acuity significantly improved in 25 eyes.No complications such as glaucoma,retinal detachment,or endophthalmitis were reported.CONCLUSION:The study suggests that the combination of PRP with IVC injections is an effective and safe modality for treating diabetic VH in patients with HR-PDR.

Construction and validation of a neovascular glaucoma nomogram in patients with diabetic retinopathy after pars plana vitrectomy

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.

Algorithm of automatic identification of diabetic retinopathy foci based on ultra-widefield scanning laser ophthalmoscopy

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.

Efficacy comparison of multipoint and single point scanning panretinal laser photocoagulation in non-proliferative diabetic retinopathy treatment

BACKGROUND Non-proliferative diabetic retinopathy(NPDR)poses a significant challenge in diabetes management due to its microvascular changes in the retina.Laser photocoagulation,a conventional therapy,aims to mitigate the risk of progressing to proliferative diabetic retinopathy(PDR).AIM To compare the efficacy and safety of multi-spot vs single-spot scanning panretinal laser photocoagulation in NPDR patients.METHODS Forty-nine NPDR patients(86 eyes)treated between September 2020 and July 2022 were included.They were randomly allocated into single-spot(n=23,40 eyes)and multi-spot(n=26,46 eyes)groups.Treatment outcomes,including bestcorrected visual acuity(BCVA),central macular thickness(CMT),and mean threshold sensitivity,were assessed at predetermined intervals over 12 months.Adverse reactions were also recorded.RESULTS Energy levels did not significantly differ between groups(P>0.05),but the multi-spot group exhibited lower energy density(P<0.05).BCVA and CMT improvements were noted in the multi-spot group at one-month posttreatment(P<0.05).Adverse reaction incidence was similar between groups(P>0.05).CONCLUSION While energy intensity and safety were comparable between modalities,multi-spot scanning demonstrated lower energy density and showed superior short-term improvements in BCVA and CMT for NPDR patients,with reduced laser-induced damage.