Progress in the study of cancer-associated retinopathy in breast cancer patients

Cancer-associated retinopathy (CAR) typically has a sudden or progressive onset of severe visual loss and an ominous association with an occult malignancy which contains breast cancer. Pathologically, CAR is the degeneration of photoreceptors. But the precise mechanism has not been fully established, CAR may result from autoimmune mediated apoptosis. And in recent years, there also have been some results demonstrating that tumor derived angiogenic factors such as VEGF may also confer the development of CAR, which may offer novel avenues for the therapeutic intervention in CAR. Early initiation of immunosuppressive therapy is critical for vision preservation. Future developments in rapid identification and longitudinal quantification of antibody levels would enable individualized management in these patients. The goal of this review was to analyze the epidemiology, the clinical features, the diagnosis and management of retinopathy in the context of recent advances in the elucidation of breast cancer-associated retinopathy (BCAR) pathogenesis.

Unraveling the role of cancer-associated fibroblasts in colorectal cancer

Within the intricate milieu of colorectal cancer(CRC)tissues,cancer-associated fibroblasts(CAFs)act as pivotal orchestrators,wielding considerable influence over tumor progression.This review endeavors to dissect the multifaceted functions of CAFs within the realm of CRC,thereby highlighting their indispensability in fostering CRC malignant microenvironment and indicating the development of CAFs-targeted therapeutic interventions.Through a comprehensive synthesis of current knowledge,this review delineates insights into CAFsmediated modulation of cancer cell proliferation,invasiveness,immune evasion,and neovascularization,elucidating the intricate web of interactions that sustain the pro-tumor metabolism and secretion of multiple factors.Additionally,recognizing the high level of heterogeneity within CAFs is crucial,as they encompass a range of subtypes,including myofibroblastic CAFs,inflammatory CAFs,antigen-presenting CAFs,and vessel-associated CAFs.Innovatively,the symbiotic relationship between CAFs and the intestinal microbiota is explored,shedding light on a novel dimension of CRC pathogenesis.Despite remarkable progress,the orchestrated dynamic functions of CAFs remain incompletely deciphered,underscoring the need for continued research endeavors for therapeutic advancements in CRC management.

CRABP2 regulates infiltration of cancer-associated fibroblasts and immune response in melanoma

Finding biomarkers for immunotherapy is an urgent issue in cancer treatment.Cellular retinoic acid-binding protein 2(CRABP2)is a controversial factor in the occurrence and development of human tumors.However,there is limited research on the relationship between CRABP2 and immunotherapy response.This study found that negative correlations of CRABP2 and immune checkpoint markers(PD-1,PD-L1,and CTLA-4)were observed in breast invasive carcinoma(BRCA),skin cutaneous melanoma(SKCM),stomach adenocarcinoma(STAD)and testicular germ cell tumors(TGCT).In particular,in SKCM patients who were treated with PD-1 inhibitors,high levels of CRABP2 predicted poor prognosis.Additionally,CRABP2 expression was elevated in cancer-associated fibroblasts(CAFs)at the single-cell level.The expression of CRABP2 was positively correlated with markers of CAFs,such as MFAP5,PDPN,ITGA11,PDGFRα/βand THY1 in SKCM.To validate the tumor-promoting effect of CRABP2 in vivo,SKCM xenograft mice models with CRABP2 overexpression have been constructed.These models showed an increase in tumor weight and volume.Enrichment analysis indicated that CRABP2 may be involved in immunerelated pathways of SKCM,such as extracellular matrix(ECM)receptor interaction and epithelial-mesenchymal transition(EMT).The study suggests that CRABP2 may regulate immunotherapy in SKCM patients by influencing infiltration of CAFs.In conclusion,this study provides new insights into the role of CRABP2 in immunotherapy response.The findings suggest that CRABP2 may be a promising biomarker for PD-1 inhibitors in SKCM patients.Further research is needed to confirm these findings and to explore the clinical implications of CRABP2 in immunotherapy.

Impact of STAT-signaling pathway on cancer-associated fibroblasts in colorectal cancer and its role in immunosuppression

Colorectal cancer(CRC)remains one of the most commonly diagnosed and deadliest types of cancer worldwide.CRC displays a desmoplastic reaction(DR)that has been inversely associated with poor prognosis;less DR is associated with a better prognosis.This reaction generates excessive connective tissue,in which cancer-associated fibroblasts(CAFs)are critical cells that form a part of the tumor microenvironment.CAFs are directly involved in tumorigenesis through different mechanisms.However,their role in immunosuppression in CRC is not well understood,and the precise role of signal transducers and activators of transcription(STATs)in mediating CAF activity in CRC remains unclear.Among the myriad chemical and biological factors that affect CAFs,different cytokines mediate their function by activating STAT signaling pathways.Thus,the harmful effects of CAFs in favoring tumor growth and invasion may be modulated using STAT inhibitors.Here,we analyze the impact of different STATs on CAF activity and their immunoregulatory role.

Paraneoplastic retinopathies: an update on pathogenesis, diagnosis and management

The paraneoplastic retinopathies are a heterogeneous group of disorders with significant visual consequences occuring in the setting of a systemic malignancy.These conditions may be characterized by the presence of antiretinal antibodies and may predate or follow the diagnosis of an underlying malignancy.Herein I review the clinical findings,pathophysiology,laboratory testing and management of the paraneoplastic retinopathies:cancer-associated retinopathy(CAR),melanoma-associated retinopathy(MAR),bilateral diffuse uveal melanocytic proliferation(BDUMP)and paraneoplastic vitelliform maculopathy(PVM).The pathophysiology of the paraneoplastic retinopathies varies from molecular mimicry resulting in anti-retinal antibody production(CAR,MAR)to relases of soluble factors either by the primary tumor(BDUMP)and/or immune system in response to the primary tumor(PVM)which result in retinal and/or retinal pigment epithelium dysfunction.For each condition,structural and functional multimodal retinal testing can be helpful in establishing the diagnosis.Treatment for the paraneoplastic retinopathies involves a combination of treating the underlying malignancy plus additional local and/or systemic immunosuppressive agents though no systemic therapeutic protocols exist.Despite these interventions,the retinopathy may be progressive or the retinopathy may be a harbinger of poor survival.Nevertheless,prompt diagnosis may help identify an underlying malignancy earlier and may thus improve cancer-related survival.

Correlation of periodontal inflamed surface area with glycated hemoglobin,interleukin-6 and lipoprotein(a)in type 2 diabetes with retinopathy

BACKGROUND The two-way relationship between periodontitis and type 2 diabetes mellitus(T2DM)is well established.Prolonged hyperglycemia contributes to increased periodontal destruction and severe periodontitis,accentuating diabetic complications.An inflammatory link exists between diabetic retinopathy(DR)and periodontitis,but the studies regarding this association and the role of lipoprotein(a)[Lp(a)]and interleukin-6(IL-6)in these conditions are scarce in the literature.AIM To determine the correlation of periodontal inflamed surface area(PISA)with glycated Hb(HbA1c),serum IL-6 and Lp(a)in T2DM subjects with retinopathy.METHODS This cross-sectional study comprised 40 T2DM subjects with DR and 40 T2DM subjects without DR.All subjects were assessed for periodontal parameters[bleeding on probing(BOP),probing pocket depth,clinical attachment loss(CAL),oral hygiene index-simplified,plaque index(PI)and PISA],and systemic parameters[HbA1c,fasting plasma glucose and postprandial plasma glucose,fasting lipid profile,serum IL-6 and serum Lp(a)].RESULTS The proportion of periodontitis in T2DM with and without DR was 47.5%and 27.5%respectively.Severity of periodontitis,CAL,PISA,IL-6 and Lp(a)were higher in T2DM with DR group compared to T2DM without DR group.Significant difference was observed in the mean percentage of sites with BOP between T2DM with DR(69%)and T2DM without DR(41%),but there was no significant difference in PI(P>0.05).HbA1c was positively correlated with CAL(r=0.351,P=0.001),and PISA(r=0.393,P≤0.001)in study subjects.A positive correlation was found between PISA and IL-6(r=0.651,P<0.0001);PISA and Lp(a)(r=0.59,P<0.001);CAL and IL-6(r=0.527,P<0.0001)and CAL and Lp(a)(r=0.631,P<0.001)among study subjects.CONCLUSION Despite both groups having poor glycemic control and comparable plaque scores,the periodontal parameters were higher in DR as compared to T2DM without DR.Since a bidirectional link exists between periodontitis and DM,the presence of DR may have contributed to the severity of periodontal destruction and periodontitis may have influenced the progression of DR.

Gut microbiota induced abnormal amino acids and their correlation with diabetic retinopathy

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.

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.

Non-linear relationship between age and subfoveal choroidal thickness in Chinese patients with proliferative diabetic retinopathy

BACKGROUND No study has investigated the change regularity between age and subfoveal choroidal thickness(SFCT)in proliferative diabetic retinopathy(PDR).AIM To investigate the relationship between the SFCT and age in Chinese patients with PDR.METHODS This was a cross-sectional retrospective study.The participants were hospitalized individuals with type 2 diabetes who underwent vitrectomy for PDR.Contralateral eyes that met the criteria were included in the study.All necessary laboratory tests were performed at the time of admission.Central macular thickness(CMT)and SFCT were two quantitative assessments made using enhanced depth imaging optical coherence tomography.CMT was measured automatically and SFCT was measured manually with digital calipers provided by the Heidelberg Eye Explorer software.RESULTS The final analysis included a total of 234 individuals with PDR.The average age was 55.60 years old±10.03 years old,and 57.69%of the population was male.Univariate analysis revealed a significant negative connection between age and SFCT in patients with PDR[β=-2.44,95%confidence interval(95%CI):-3.46 to-1.42;P<0.0001].In the fully adjusted model,the correlation between SFCT and age remained steady(β=-1.68,95%CI:-2.97 to-0.39;P=0.0117).Spline smoothing showed that the relationship between SFCT and age in patients with PDR was non-linear,with an inflection point at 54 years of age.CONCLUSION Our findings suggest that age is a key determinant of choroidal thickness.The non-linear link between SFCT and age in PDR patients should be taken into account.

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.

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.

Prophylactic Pattern Scanning Laser Retinal Photocoagulation for Diabetic Retinopathy in Spontaneously Diabetic Torii Fatty Rats: Preliminary Experimental Results

Research Background and Purpose: The number of diabetic patients is rapidly increasing, making it crucial to find methods to prevent diabetic retinopathy (DR), a leading cause of blindness. We investigated the effects of prophylactic pattern scanning laser retinal photocoagulation on DR development in Spontaneously Diabetic Torii (SDT) fatty rats as a new prevention approach. Methods: Photocoagulation was applied to the right eyes of 8-week-old Spontaneously Diabetic Torii (SDT) fatty rats, with the left eyes serving as untreated controls. Electroretinography at 9 and 39 weeks of age and pathological examinations, including immunohistochemistry for vascular endothelial growth factor and glial fibrillary acidic protein at 24 and 40 weeks of age, were performed on both eyes. Results: There were no significant differences in amplitude and prolongation of the OP waves between the right and left eyes in SDT fatty rats at 39 weeks of age. Similarly, no significant differences in pathology and immunohistochemistry were observed between the right and left eyes in SDT fatty rats at 24 and 40 weeks of age. Conclusion: Prophylactic pattern scanning retinal laser photocoagulation did not affect the development of diabetic retinopathy in SDT fatty rats.

Interconnections between diabetic corneal neuropathy and diabetic retinopathy:diagnostic and therapeutic implications

Diabetic corneal neuropathy and diabetic retinopathy are ocular complications occurring in the context of diabetes mellitus.Diabetic corneal neuropathy refers to the progressive damage of corneal nerves.Diabetic retinopathy has traditionally been considered as damage to the retinal microvasculature.However,growing evidence suggests that diabetic retinopathy is a complex neurovascular disorder resulting from dysfunction of the neurovascular unit,which includes both the retinal vascular structures and neural tissues.Diabetic retinopathy is one of the leading causes of blindness and is frequently screened for as part of diabetic ocular screening.However,diabetic corneal neuropathy is commonly overlooked and underdiagnosed,leading to severe ocular surface impairment.Several studies have found that these two conditions tend to occur together,and they share similarities in their pathogenesis pathways,being triggered by a status of chronic hyperglycemia.This review aims to discuss the interconnection between diabetic corneal neuropathy and diabetic retinopathy,whether diabetic corneal neuropathy precedes diabetic retinopathy,as well as the relation between the stage of diabetic retinopathy and the severity of corneal neuropathy.We also endeavor to explore the relevance of a corneal screening in diabetic eyes and the possibility of using corneal nerve measurements to monitor the progression of diabetic retinopathy.

Diabetic retinopathy identification based on multi-sourcefree domain adaptation

AIM:To address the challenges of data labeling difficulties,data privacy,and necessary large amount of labeled data for deep learning methods in diabetic retinopathy(DR)identification,the aim of this study is to develop a source-free domain adaptation(SFDA)method for efficient and effective DR identification from unlabeled data.METHODS:A multi-SFDA method was proposed for DR identification.This method integrates multiple source models,which are trained from the same source domain,to generate synthetic pseudo labels for the unlabeled target domain.Besides,a softmax-consistence minimization term is utilized to minimize the intra-class distances between the source and target domains and maximize the inter-class distances.Validation is performed using three color fundus photograph datasets(APTOS2019,DDR,and EyePACS).RESULTS:The proposed model was evaluated and provided promising results with respectively 0.8917 and 0.9795 F1-scores on referable and normal/abnormal DR identification tasks.It demonstrated effective DR identification through minimizing intra-class distances and maximizing inter-class distances between source and target domains.CONCLUSION:The multi-SFDA method provides an effective approach to overcome the challenges in DR identification.The method not only addresses difficulties in data labeling and privacy issues,but also reduces the need for large amounts of labeled data required by deep learning methods,making it a practical tool for early detection and preservation of vision in diabetic patients.

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.

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.

Diabetic Retinopathy Detection: A Hybrid Intelligent Approach

Diabetes is a serious health condition that can cause several issues in human body organs such as the heart and kidney as well as a serious eye disease called diabetic retinopathy(DR).Early detection and treatment are crucial to prevent complete blindness or partial vision loss.Traditional detection methods,which involve ophthalmologists examining retinal fundus images,are subjective,expensive,and time-consuming.Therefore,this study employs artificial intelligence(AI)technology to perform faster and more accurate binary classifications and determine the presence of DR.In this regard,we employed three promising machine learning models namely,support vector machine(SVM),k-nearest neighbors(KNN),and Histogram Gradient Boosting(HGB),after carefully selecting features using transfer learning on the fundus images of the Asia Pacific Tele-Ophthalmology Society(APTOS)(a standard dataset),which includes 3662 images and originally categorized DR into five levels,now simplified to a binary format:No DR and DR(Classes 1-4).The results demonstrate that the SVM model outperformed the other approaches in the literature with the same dataset,achieving an excellent accuracy of 96.9%,compared to 95.6%for both the KNN and HGB models.This approach is evaluated by medical health professionals and offers a valuable pathway for the early detection of DR and can be successfully employed as a clinical decision support system.

Mendelian randomization analysis of causal relationship between cheese intake and diabetic retinopathy

AIM:To assess whether there is a possible causal link between the intake of cheese and the risk of diabetic retinopathy(DR)utilizing a two-sample Mendelian randomization(MR)analysis.METHODS:The research data were obtained from summary statistics of genome-wide association studies(GWAS).Genetic loci closely related to cheese intake were extracted as instrumental variables(IVs),and DR was the outcome variable.The data were extracted from individuals of European ethnicity.The data of cheese intake consisted of 451486 samples with 9851867 single nucleotide polymorphisms(SNPs),while the DR data consisted of 206234 samples with 16380446 SNPs.Sixty-one genetic loci closely related to cheese intake were selected as IVs.MR analysis was performed by inverse-variance weighted(IVW)method and MR-Egger regression respectively.The causal relationship between cheese intake and DR was evaluated using odds ratios(ORs)and 95%confidence intervals(CIs).Egger-intercept test was used to test horizontal pleiotropy and sensitivity analysis was performed by leave-one-out test.RESULTS:The P value of the IVW method was less than 0.05,indicating a significant negative correlation between cheese intake and DR.MR-Egger regression showed that the intercept was 0.01 with a standard error of 0.022,and a P-value of 0.634,indicating no evidence of horizontal pleiotropy affecting the IVs related to the exposure factors.Besides,heterogeneity tests confirmed the absence of heterogeneity,and the“leave-one-out”sensitivity analysis demonstrated that the results were stable.CONCLUSION:Cheese intake is causally negatively correlated with the occurrence of DR,and cheese intake could reduce the risk of DR.

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.

Risk evaluation for diabetic retinopathy in Chinese renalbiopsied type 2 diabetes mellitus patients

AIM:To investigate diabetic retinopathy(DR)prevalence in Chinese renal-biopsied type 2 diabetes mellitus(T2DM)patients with kidney dysfunction,and to further evaluate its relationship with diabetic nephropathy(DN)incidence and the risk factors for DR development in this population.METHODS:A total of 84 renal-biopsied T2DM patients were included.Fundus and imaging examinations were employed for DR diagnosis.Demographic information and clinical measures along with renal histopathology were analyzed for comparisons between the DR and non-DR groups.Risk factors on DR development were analyzed with multiple logistic regression.RESULTS:DR prevalence was 50%in total.The incidences of DN,non-diabetic renal disease(NDRD)and mixed-type pathology were 47.6%,19.0%and 33.3%in the DR group respectively,while 11.9%,83.3%and 4.8%in the non-DR group.Systolic blood pressure,ratio of urinary albumin to creatine ratio,urinary albumin,24-hours urinary protein,the incidence and severity of DN histopathology were found statistically increased in the DR group.Multiple logistic regression analysis showed histopathological DN incidence significantly increased the risk of DR development[odds ratio(OR)=21.664,95%confidential interval(CI)5.588 to 83.991,P<0.001 for DN,and OR=45.475,95%CI 6.949 to 297.611,P<0.001 for mixed-type,respectively,in reference to (NDRD)],wherein DN severity positively correlated.CONCLUSION:Renal histopathological evidence indicates DN incidence and severity increases the risk of DR development in Chinese T2DM patients inexperienced of regular fundus examinations.