Form-deprivation myopia promotes sclera M2-type macrophages polarization in mice.

PURPOSE: To explore the phenotype of sclera macrophages in form-deprivation (FD) myopia mice and the effects of M2 macrophage in FD myopia development. METHODS: C57BL/6 mice were under 2 weeks of unilateral FD treatment. and they were separated into two groups, including an intraperitoneally injected(IP) vehicle group and Panobinostat (LBH589) (10 mg/kg per body weight) treatment group. All biometric parameters were measured before and after treatments, and the type and density of sclera macrophages were identified by immunofluorescence and RT-qPCR. In vitro, we analyzed the M2 macrophage and primary human sclera fibroblast (HSF) co-culture system by using the transcriptome sequencing method. Gene ontology (GO) and KEGG enrichment analyses were used to pinpoint the biological functions and pathways associated with the identified Differentially Expressed Genes (DEGs). The hub genes were investigated using the STRING database and Cytoscape software and were confirmed using RT-qPCR. RESULTS: We found that the M2-type sclera macrophage density and expression increased in FD-treated eyes. The results showed that LBH589 inhibited the M2 macrophage polarization, and reduced FDM development. GO and KEGG analyses revealed that the DEGs were predominantly involved in the synthesis and breakdown of the extracellular matrix (ECM), as well as in pathways related to ECM-receptor interaction and the PI3K-Akt signaling pathway. Five hub genes (FN-1, MMP-2, COL1A1, CD44, and IL6) were identified, and RT-qPCR validated the variation in expression levels among these genes. CONCLUSION: M2 macrophage polarization occurred in the sclera in FDM mice. Panobinostat-mediated inhibition of M2 macrophage polarization may decrease FDM progression, as M2 macrophages are crucial in controlling ECM remodeling by HSFs.

Unveiling the Evolution of Virtual Reality in Medicine: A Bibliometric Analysis of Research Hotspots and Trends over the Past 12 Years.

BACKGROUND: Virtual reality (VR), widely used in the medical field, may affect future medical training and treatment. Therefore, this study examined VR's potential uses and research directions in medicine. METHODS: Citation data were downloaded from the Web of Science Core Collection database (WoSCC) to evaluate VR in medicine in articles published between 1 January 2012 and 31 December 2023. These data were analyzed using CiteSpace 6.2. R2 software. Present limitations and future opportunities were summarized based on the data. RESULTS: A total of 2143 related publications from 86 countries and regions were analyzed. The country with the highest number of publications is the USA, with 461 articles. The University of London has the most publications among institutions, with 43 articles. The burst keywords represent the research frontier from 2020 to 2023, such as "task analysis", "deep learning", and "machine learning". CONCLUSION: The number of publications on VR applications in the medical field has been steadily increasing year by year. The USA is the leading country in this area, while the University of London stands out as the most published, and most influential institution. Currently, there is a strong focus on integrating VR and AI to address complex issues such as medical education and training, rehabilitation, and surgical navigation. Looking ahead, the future trend involves integrating VR, augmented reality (AR), and mixed reality (MR) with the Internet of Things (IoT), wireless sensor networks (WSNs), big data analysis (BDA), and cloud computing (CC) technologies to develop intelligent healthcare systems within hospitals or medical centers.

Bifunctional black phosphorus quantum dots platform: Delivery and remarkable immunotherapy enhancement of STING agonist.

Cancer immunotherapy has been developed to improve therapeutic effects for patients by activating the innate immune stimulator of interferon gene (STING) pathway. However, most patients cannot benefit from this therapy, mainly due to the problems of excessively low immune responses and lack of tumor specificity. Herein, we report a solution to these two problems by developing a bifunctional platform of black phosphorus quantum dots (BPQDs) for STING agonists. Specifically, BPQDs could connect targeted functional groups and regulate surface zeta potential by coordinating metal ions to increase loading (over 5 times) while maintaining high universality (7 STING agonists). The controlled release of STING agonists enabled specific interactions with their proteins, activating the STING pathway and stimulating the secretion release of immunosuppressive factors by phosphorylating TBK1 and IFN-IRF3 and secreting high levels of immunostimulatory cytokines, including IL-6, IFN-α, and IFN-ß. Moreover, the immunotherapy was enhanced was enhanced mild photothermal therapy (PTT) of BPQDs platform, producing enough T cells to eliminate tumors and prevent tumor recurrence. This work facilitates further research on targeted delivery of small-molecule immune drugs to enhance the development of clinical immunotherapy.

Acute primary angle closure during the Omicron outbreak.

AIM: To investigate Omicron's impact on clinical presentation of acute primary angle closure (APAC) in China. METHODS: A consecutive case series with historical controls was conducted at Shenzhen Eye Hospital, the largest specialized hospital in Shenzhen, China. Medical records from a two-month period during the Omicron pandemic (December 1, 2022, to January 31, 2023) were compared with records from two control groups (12/2018-1/2019 and 12/2021-1/2022) before pandemic. Patients with APAC were included, and the prevalence of APAC and demographic characteristics in Omicron-infected and non-infected patients were compared. RESULTS: Seventy-one (23.43%) out of 303 patients were diagnosed with APAC in the pandemic cohort, which was 2.98 and 2.61 times higher than that in control cohorts (7.87% in 2019, 8.96% in 2022, P<0.001). The pandemic cohort has significantly higher Omicron-infected rate (78.87% vs 0 vs 0; P<0.001), lower proportion of glaucoma history (16.90% vs 42.86% vs 41.67%, P=0.005), higher surgical rate (95.77% vs 83.33% vs 78.57%, P=0.024), higher total medical costs and larger pupil diameter (5.63±0.15 vs 4.68±0.15 vs 4.69±0.22 mm, P<0.01). In 83% Omicron-infected patients, ocular symptoms appeared within 3d after systemic symptoms onset. In multivariate analysis, Omicron infection (P<0.001) was the only independent predictor of pupil diameter. CONCLUSION: In the Omicron epidemic in China, there is an increase of prevalence and severity of APAC, particularly focusing on the first 3d following infection.

Diabetic retinopathy identification based on multi-source-free 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.

Glucagon-like peptide-1 receptor agonists rescued diabetic vascular endothelial damage through suppression of aberrant STING signaling.

Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) protect against diabetic cardiovascular diseases and nephropathy. However, their activity in diabetic retinopathy (DR) remains unclear. Our retrospective cohort study involving 1626 T2DM patients revealed superior efficacy of GLP-1 RAs in controlling DR compared to other glucose-lowering medications, suggesting their advantage in DR treatment. By single-cell RNA-sequencing analysis and immunostaining, we observed a high expression of GLP-1R in retinal endothelial cells, which was down-regulated under diabetic conditions. Treatment of GLP-1 RAs significantly restored the receptor expression, resulting in an improvement in retinal degeneration, vascular tortuosity, avascular vessels, and vascular integrity in diabetic mice. GO and GSEA analyses further implicated enhanced mitochondrial gene translation and mitochondrial functions by GLP-1 RAs. Additionally, the treatment attenuated STING signaling activation in retinal endothelial cells, which is typically activated by leaked mitochondrial DNA. Expression of STING mRNA was positively correlated to the levels of angiogenic and inflammatory factors in the endothelial cells of human fibrovascular membranes. Further investigation revealed that the cAMP-responsive element binding protein played a role in the GLP-1R signaling pathway on suppression of STING signaling. This study demonstrates a novel role of GLP-1 RAs in the protection of diabetic retinal vasculature by inhibiting STING-elicited inflammatory signals.

Protocol for performing deep learning-based fundus fluorescein angiography image analysis with classification and segmentation tasks.

Fundus fluorescein angiography (FFA) examinations are widely used in the evaluation of fundus disease conditions to facilitate further treatment suggestions. Here, we present a protocol for performing deep learning-based FFA image analytics with classification and segmentation tasks. We describe steps for data preparation, model implementation, statistical analysis, and heatmap visualization. The protocol is applicable in Python using customized data and can achieve the whole process from diagnosis to treatment suggestion of ischemic retinal diseases. For complete details on the use and execution of this protocol, please refer to Zhao et al.1.

Bibliometric analysis of hotspots and trends of global myopia research.

AIM: To gain insights into the global research hotspots and trends of myopia. METHODS: Articles were downloaded from January 1, 2013 to December 31, 2022 from the Science Core Database website and were mainly statistically analyzed by bibliometrics software. RESULTS: A total of 444 institutions in 87 countries published 4124 articles. Between 2013 and 2022, China had the highest number of publications (n=1865) and the highest H-index (61). Sun Yat-sen University had the highest number of publications (n=229) and the highest H-index (33). Ophthalmology is the main category in related journals. Citations from 2020 to 2022 highlight keywords of options and reference, child health (pediatrics), myopic traction mechanism, public health, and machine learning, which represent research frontiers. CONCLUSION: Myopia has become a hot research field. China and Chinese institutions have the strongest academic influence in the field from 2013 to 2022. The main driver of myopic research is still medical or ophthalmologists. This study highlights the importance of public health in addressing the global rise in myopia, especially its impact on children's health. At present, a unified theoretical system is still needed. Accurate surgical and therapeutic solutions must be proposed for people with different characteristics to manage and intervene refractive errors. In addition, the benefits of artificial intelligence (AI) models are also reflected in disease monitoring and prediction.

Long-term follow-up of the cognitive function in children after intravitreal ranibizumab for retinopathy of prematurity.

PURPOSE: To evaluate the long-term cognitive function in children treated with intravitreal ranibizumab (IVR) for retinopathy of prematurity(ROP), and the impact of IVR on the growth and ocular development. METHODS: In this retrospective study, the premature children aged 4 to 9 years who received monotherapy of IVR (IVR group, n = 25) or monotherapy of laser photocoagulation (LP) (LP group, n = 33) for ROP, and the same age premature children with no ROP (Control group, n = 26) were enrolled from 2020 to 2022 in the pediatric fundus clinic of Shenzhen Eye Hospital. Main outcome measures were full-scale intelligence quotient (FSIQ) and index score using the Chinese version of the Wechsler intelligence scale for children-fourth edition (WISC-IV) and Wechsler preschool and primary scale of intelligence-fourth edition (WPPSI-IV). All children were examined and analyzed for growth and ocular development by recording the height, weight, head circumference, spherical equivalent (SE), best corrected visual acuity (BCVA) and axial length (AL). RESULTS: There were 17 children in IVR group, 17 in LP group, and 11 in Control group who received the WISC-IV assessment. There were no significant differences in FSIQ, verbal comprehension index, perceptual reasoning index, working memory index, processing speed index, general ability index and cognitive efficiency index among the three groups. There were 8 children in IVR group, 16 in LP group, and 15 in Control group who received the WPPSI-IV assessment. There were no significant differences in FSIQ, verbal comprehension index, visuospatial index, fluid reasoning index, working memory index, non-verbal index, general ability index and cognitive efficiency index among the three groups. There was no significant difference in BCVA among the three groups (P = 0.74), however, there is an increase for AL in IVR group when compared with LP group (22.60 ± 0.58 vs. 22.13 ± 0.84, P = 0.003), and the ROP patients of IVR group have a significant increase in the AL compared to the Control group(22.60 ± 0.58 vs. 22.03 ± 0.71, P < 0.0001). CONCLUSIONS: Children with a history of IVR have a similar cognitive function outcomes compared to those with a history of LP or were premature without ROP. ROP children with a history of IVR has longer AL than those treated with LP.

Age-period-cohort analysis of the global burden of visual impairment according to major causes: an analysis of the Global Burden of Disease Study 2019.

BACKGROUND: Cataract, glaucoma and age-related macular degeneration (AMD) are major causes of visual impairment. As these are age-related conditions, the prevalence of associated visual impairment is anticipated to increase as the population ages. However, age-period-cohort effects on the disease burden have not been investigated. METHODS: This was a population-based study using aggregated data from the Global Burden of Disease Study 2019. Age-period-cohort analysis was conducted using age-standardised prevalence rates (ASPRs) of visual impairment caused by cataract, glaucoma and AMD as disease burden indicator. RESULTS: In 2019, the estimated global ASPRs of visual impairment due to cataract, glaucoma and AMD were 1207.9, 94.7 and 96.8 per 100 000 people, respectively. Between 1990 and 2019, the global visual impairment ASPRs for glaucoma and AMD declined by 15.4% and 2.0%, respectively, whereas that for cataract increased by 5.0%. Wide heterogeneity was observed in age-period-cohort effects on ASPRs across different Sociodemographic Index (SDI) regions. Low-middle SDI regions had the largest ASPR reductions for all three eye diseases and showed improvement in both period and cohort effects. In contrast, in high-middle SDI regions, visual impairment ASPRs significantly increased during the study period with unfavourable patterns. CONCLUSIONS: The wide heterogeneity in age-period-cohort effects reflects different stages of societal transition and vision health. The unfavourable trends in age-period-cohort effects on disease prevalence identified in specific groups provide key information that may be used to identify priority groups in need of treatment and prevention.

UWAFA-GAN: Ultra-Wide-Angle Fluorescein Angiography Transformation via Multi-Scale Generation and Registration Enhancement.

Fundus photography, in combination with the ultra-wide-angle fundus (UWF) techniques, becomes an indispensable diagnostic tool in clinical settings by offering a more comprehensive view of the retina. Nonetheless, UWF fluorescein angiography (UWF-FA) necessitates the administration of a fluorescent dye via injection into the patient's hand or elbow unlike UWF scanning laser ophthalmoscopy (UWF-SLO). To mitigate potential adverse effects associated with injections, researchers have proposed the development of cross-modality medical image generation algorithms capable of converting UWF-SLO images into their UWF-FA counterparts. Current image generation techniques applied to fundus photography encounter difficulties in producing high-resolution retinal images, particularly in capturing minute vascular lesions. To address these issues, we introduce a novel conditional generative adversarial network (UWAFA-GAN) to synthesize UWF-FA from UWF-SLO. This approach employs multi-scale generators and an attention transmit module to efficiently extract both global structures and local lesions. Additionally, to counteract the image blurriness issue that arises from training with misaligned data, a registration module is integrated within this framework. Our method performs non-trivially on inception scores and details generation. Clinical user studies further indicate that the UWF-FA images generated by UWAFA-GAN are clinically comparable to authentic images in terms of diagnostic reliability. Empirical evaluations on our proprietary UWF image datasets elucidate that UWAFA-GAN outperforms extant methodologies.

Morphologic and Functional Assessment of Photoreceptors in Laser-Induced Retinopathy Using Adaptive Optics Scanning Laser Ophthalmoscopy and Microperimetry.

PURPOSE: To assess the cone photoreceptors' morphology and associated retinal sensitivity in laser-induced retinopathy (LIR) using adaptive optics scanning laser ophthalmoscopy (AO-SLO) and microperimetry (MP). DESIGN: Cohort study. METHODS: This study included 13 patients (15 eyes) with LIR and 38 age-matched healthy volunteers (38 eyes). Participants underwent comprehensive evaluations including AO-SLO, MP, and spectral-domain OCT. Lesion morphology, cone density, dispersion, and regularity in AO-SLO were assessed and correlated with visual function. RESULTS: In AO-SLO images, LIR lesions were predominantly characterized by hyporeflective regions, suggesting potential cone loss at the fovea, accompanied by the presence of sizable clumps of hyperreflective material within these lesions. The average size of lesions in affected eyes was 97,128±107,478 µm², ranging from 6705 to 673,348 µm². Compared with the healthy contralateral eye and control group, LIR demonstrated significantly reduced cone density, increased cone dispersion, and notably decreased cone regularity in all 4 quadrants at 3° eccentricity (all P values < .05). Lesion morphology in AO-SLO correlated with ellipsoid zone defects observed in OCT, showing a positive correlation in size (r = 0.84, P < .001) but not with retinal sensitivities (P = .09). Similarly, cone density at 3° eccentricity did not correlate with retinal sensitivities (P = .13). CONCLUSIONS AND RELEVANCE: The study provides crucial insights into the morphologic and functional impacts of LIR on cone photoreceptors, revealing significant morphologic changes in cones that do not consistently align with functional outcomes. This research highlights the need for continued exploration into the relationship between retinal structure and function in LIR, and the importance of heightened public awareness and preventive strategies to mitigate the risk of LIR.

Development of a nomogram for predicting myopia risk among school-age children: a case-control study.

OBJECTIVES: To analyze the factors influencing myopia and construct a nomogram to forecast the risk of myopia among school-age children, providing a reference for identifying high-risk groups to aid prevention and control. METHODS: This case-control study enrolled 3512 students from three primary schools in Shenzhen using random cluster sampling for a questionnaire survey, myopia screening and ocular biometric parameter measurement. Logistic regression was used to analyze the influencing factors of myopia, and a nomogram was constructed to forecast myopia risk. Bootstrap resampling was used to verify the practicability of the nomogram. RESULTS: Older age (odds ratio[OR] = 1.164; 95% confidence interval [CI]: 1.111-1.219), female sex (OR = 2.405; 95% CI: 2.003-2.887), maternal myopia (OR = 1.331; 95% CI: 1.114-1.589), incorrect posture during reading and writing (OR = 1.283; 95% CI: 1.078-1.528) and axial length (OR = 7.708; 95% CI: 6.044-8.288) are risk factors for myopia, whereas an increase in corneal radius (OR = 0.036; 95% CI: 0.025-0.052) is a protective factor against myopia. The area under the receiver operating characteristic (ROC) curve of the nomogram was 0.857, and the net benefit was high when the risk threshold of the decision curve analyses (DCA) ranged from 0.20 to 1.00. The measured values were consistent with the prediction. CONCLUSION: The nomogram was accurate in predicting the risk of myopia among schoolchildren. This study provides a reference for screening high-risk students and for individualized myopia prevention and control.

Older age, female sex, maternal myopia, incorrect posture during reading and writing, and prolonged axial length are risk factors for myopia among primary school students.The nomogram constructed based on age, sex, maternal myopia, incorrect posture during reading and writing, axial length and corneal radius showed good predictive accuracy and practicability.The nomogram constructed in this study can be used for individualized myopia risk assessment.

An anti-GD2 aptamer-based bifunctional spherical nucleic acid nanoplatform for synergistic therapy targeting MDM2 for retinoblastoma.

Retinoblastoma (RB) is a type of pediatric solid tumor in the fundus. The lack of precision therapies combined with the difficulty of delivering small interfering RNA (siRNA) into the eyes means that there is currently no nucleic acid-based therapy for RB in clinical practice. Here, we reported on anti-GD2 and glutathione-responsive spherical nucleic acids (SNAs), loaded with siRNA and the inhibitor NVP-CGM097, which jointly blocked the oncogenic factor n in RB cells (Y79 and WERI-RB-1). The SNAs were formed through the self-assembly of bifunctional cholesterol amphiphiles containing aptamers that specifically targeted GD2-positive RB cells, allowing for the formation of an SNA with a dense DNA shell. The aptamer/siRNA component functioned both as a carrier and a payload, enhancing the specific recognition and delivery of both components and constituting an active agent for MDM2 regulation. Following SNA endocytosis by RB cells, siRNA and NVP-CGM097 were released from the SNA particles by glutathione, which synergistically blocked the MDM2-p53 pathway, increasing p53 protein content and inducing cell apoptosis. This study showed a potent antitumor effect following intravitreal injection of SNAs in Y79 tumor-bearing mice through clinical manifestation and tumor pathological analysis. In hematological analysis and hepatotoxicity assays, SNAs were safer for mice than melphalan, the favored drug for treating RB in clinical practice. Our results illustrated the potential of intravitreally injected SNAs as a precision medicine for treating RB.

A new segmentation algorithm for peripapillary atrophy and optic disk from ultra-widefield Photographs1.

BACKGROUND AND OBJECTIVE: The prevalence of myopia and high myopia is increasing globally, underscoring the growing importance of diagnosing high myopia-related pathologies. While existing image segmentation models, such as U-Net, UNet++, ResU-Net, and TransUNet, have achieved significant success in medical image segmentation, they still face challenges when dealing with ultra-widefield (UWF) fundus images. This study introduces a novel automatic segmentation algorithm for the optic disc and peripapillary atrophy (PPA) based on UWF fundus images, aimed at assisting ophthalmologists in more accurately diagnosing high myopia-related diseases. METHODS: In this study, we developed a segmentation model leveraging a Transformer-based network structure, complemented by atrous convolution and selective boundary aggregation modules, to elevate the accuracy of segmenting the optic disc and PPA in UWF photography. The atrous convolution module adeptly manages multi-scale features, catering to the variances in target sizes and expanding the deep network's receptive field. Concurrently, the incorporation of the selective boundary aggregation module in the skip connections of the model significantly improves the differentiation of boundary information between segmentation targets. Moreover, the comparison of our proposed algorithm with classical segmentation models like U-Net, UNet++, ResU-Net, and TransUNet highlights its considerable advantages in processing UWF photographs. RESULTS: The experimental results show that, compared to the other four models, our algorithm demonstrates substantial improvements in segmenting the optic disc and PPA in UWF photographs. In PPA segmentation, our algorithm improves by 0.8% in Dice, 1.8% in sensitivity, and 1.3% in intersection over union (IOU). In optic disc segmentation, our algorithm improves by 0.3% in Dice, 0.6% in precision, and 0.4% in IOU. CONCLUSION: Our proposed method improves the segmentation accuracy of PPA and optic disks based on UWF photographs, which is valuable for diagnosing high myopia-related diseases in ophthalmology clinics.

Exposure to mixtures of PM2.5 components and term premature rupture of membranes: a case-crossover study in Shijiazhuang, China.

This study aims to explore the acute effects of short-term exposure to PM2.5 components and their mixture on PROM. Counts of hospital admissions due to PROM were collected at the Fourth Hospital of Shijiazhuang. The associations between the PROM and PM2.5 components was examined using a time-stratified case-crossover approach. The overall effects of components on TPROM were examined using the BKMR. During the study period 30,709 cases of PROMwere identified. The relative risks and the 95% CI of TPROM were 1.013 (1.002, 1.028) and 1.015 (1.003, 1.028) associated with per interquartile range increase in nitrate and ammonium ion on the current day and they were 1.007 (1.001, 1.013) and 1.003 (1.000, 1.005) on the previous day. The results from the BKMR models showed a higher risk of TPROM was associated with exposure to mixtures, in which, nitrate and organic matter were the main contributors to the overall effect.

Intelligent diagnosis of retinal vein occlusion based on color fundus photographs.

AIM: To develop an artificial intelligence (AI) diagnosis model based on deep learning (DL) algorithm to diagnose different types of retinal vein occlusion (RVO) by recognizing color fundus photographs (CFPs). METHODS: Totally 914 CFPs of healthy people and patients with RVO were collected as experimental data sets, and used to train, verify and test the diagnostic model of RVO. All the images were divided into four categories [normal, central retinal vein occlusion (CRVO), branch retinal vein occlusion (BRVO), and macular retinal vein occlusion (MRVO)] by three fundus disease experts. Swin Transformer was used to build the RVO diagnosis model, and different types of RVO diagnosis experiments were conducted. The model's performance was compared to that of the experts. RESULTS: The accuracy of the model in the diagnosis of normal, CRVO, BRVO, and MRVO reached 1.000, 0.978, 0.957, and 0.978; the specificity reached 1.000, 0.986, 0.982, and 0.976; the sensitivity reached 1.000, 0.955, 0.917, and 1.000; the F1-Sore reached 1.000, 0.955 0.943, and 0.887 respectively. In addition, the area under curve of normal, CRVO, BRVO, and MRVO diagnosed by the diagnostic model were 1.000, 0.900, 0.959 and 0.970, respectively. The diagnostic results were highly consistent with those of fundus disease experts, and the diagnostic performance was superior. CONCLUSION: The diagnostic model developed in this study can well diagnose different types of RVO, effectively relieve the work pressure of clinicians, and provide help for the follow-up clinical diagnosis and treatment of RVO patients.

Association between choroidopathy and photoreceptors during the early stage of diabetic retinopathy: a cross-sectional study.

PURPOSE: To explore the role of choroidopathy in diabetic retinopathy (DR) by investigating the correlation between alterations of choroidal vessel and photoreceptors during the early stage of DR. METHODS: We performed a cross-sectional comparison of diabetic patients without DR (NDR group; n=16) and those with mild nonproliferative diabetic retinopathy (NPDR group; n=39). Optical coherence tomography (OCT) images of choroidal vessel alterations and photoreceptor structures were evaluated using the choroidal vascularity index (CVI) and adjusted ellipsoid zone (EZ) reflectivity, respectively. To evaluate the function of cone photoreceptors, the fundamental, harmonic amplitudes, the parameters S and Rmp3 were calculated from the electroretinogram (ERG). These factors were compared between groups. The correlation between the CVI and parameters describing the function and structure of the photoreceptors was evaluated. RESULTS: The significant decrease was observed in the CVI in the NPDR group compared to the NDR group (0.67 ± 0.04 vs. 0.70 ± 0.06; p = 0.028), but not in the adjusted EZ reflectivity or ERG parameters. In NPDR group and merging the 2 groups, CVI was moderately positively correlated with the fundamental amplitude obtained by the flicker ERG (NPDR only: r = 0.506; p = 0.001; merge the 2 groups: r = 0.423; p = 0.001), which was regulated by the response of the cone photoreceptors. The CVI was positively and moderately correlated with the logS (NPDR only: r = 0.462; p = 0.003; merge the 2 groups: r = 0.355; p = 0.008), indicating the sensitivity of cone cell light transduction. CONCLUSION: Compared to eyes without DR, CVI decreased representing choroidal vascular changes in eyes with mild NPDR. These changes may be related to the functional impairment of cone photoreceptors, especially phototransduction sensitivity, as the DR develops.

Research on an artificial intelligence-based myopic maculopathy grading method using EfficientNet.

PURPOSE: We aimed to develop an artificial intelligence-based myopic maculopathy grading method using EfficientNet to overcome the delayed grading and diagnosis of different myopic maculopathy degrees. METHODS: The cooperative hospital provided 4642 healthy and myopic maculopathy color fundus photographs, comprising the four degrees of myopic maculopathy and healthy fundi. The myopic maculopathy grading models were trained using EfficientNet-B0 to EfficientNet-B7 models. The diagnostic results were compared with those of the VGG16 and ResNet50 classification models. The leading evaluation indicators were sensitivity, specificity, F1 score, area under the receiver operating characteristic (ROC) curve area under curve (AUC), 95% confidence interval, kappa value, and accuracy. The ROC curves of the ten grading models were also compared. RESULTS: We used 1199 color fundus photographs to evaluate the myopic maculopathy grading models. The size of the EfficientNet-B0 myopic maculopathy grading model was 15.6 MB, and it had the highest kappa value (88.32%) and accuracy (83.58%). The model's sensitivities to diagnose tessellated fundus (TF), diffuse chorioretinal atrophy (DCA), patchy chorioretinal atrophy (PCA), and macular atrophy (MA) were 96.86%, 75.98%, 64.67%, and 88.75%, respectively. The specificity was above 93%, and the AUCs were 0.992, 0.960, 0.964, and 0.989, respectively. CONCLUSION: The EfficientNet models were used to design grading diagnostic models for myopic maculopathy. Based on the collected fundus images, the models could diagnose a healthy fundus and four types of myopic maculopathy. The models might help ophthalmologists to make preliminary diagnoses of different degrees of myopic maculopathy.

Spatial epidemiological characteristics and driving factors of myopia among school-age children based on geographical detector: a national study.

The present study aimed to examine the spatial characteristics of myopia and identify the socioeconomic and environmental factors influencing its prevalence. Myopia prevalence among children of school age of Han ethnicity in China was 56.6% in 2019, with the highest and lowest prevalence's in Shandong (66.8%) and Guizhou (47.3%), respectively. There was a spatial aggregation of myopia prevalence in China. Environmental factors (atmospheric PM2.5 concentration and forest coverage) and socioeconomic factors (gross domestic product per capita, per capita disposable income, hospital beds per thousand people, and Engel coefficient) have significant influences on myopia prevalence. The interaction of each factor on myopia showed nonlinear enhancement. Myopia prevalence among children of school age was spatially clustered, and environmental and socioeconomic conditions are associated with myopia prevalence. Our findings provide novel perspectives for the comprehensive prevention and control of myopia.