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.

A urine extracellular vesicle circRNA classifier for detection of high-grade prostate cancer in patients with prostate-specific antigen 2-10 ng/mL at initial biopsy.

The aim of this study was to identify a urine extracellular vesicle circular RNA (circRNA) classifier that could detect high-grade prostate cancer (PCa) of Grade Group (GG) 2 or greater. For this purpose, we used RNA sequencing to identify candidate circRNAs from urinary extracellular vesicles from 11 patients with high-grade PCa and 11 case-matched patients with benign prostatic hyperplasia. Using ddPCR in a training cohort (n = 263), we built a urine extracellular vesicle circRNA classifier (Ccirc, containing circPDLIM5, circSCAF8, circPLXDC2, circSCAMP1, and circCCNT2), which was evaluated in two independent cohorts (n = 497, n = 505). Ccirc showed higher accuracy than two standard of care risk calculators (RCs) (PCPT-RC 2.0 and ERSPC-RC) in both the training cohort and the validation cohorts. In all three cohorts, this novel urine extracellular vesicle circRNA classifier plus RCs was statistically more predictive than RCs alone for predicting ≥ GG2 PCa. This assay, which does not require precollection digital rectal examination nor special handling, is repeatable, noninvasive, and can be easily implemented as part of the basic clinical workflow.

Prospective validation of DACH2 as a novel biomarker for prediction of metastasis and prognosis in muscle-invasive urothelial carcinoma of the bladder.

Metastasis is the main cause of death from muscle-invasive urothelial carcinoma of the bladder (UCB), and the metastatic potential of tumors is often unpredictable. The role of Dachshund homolog 2 gene (DACH2) in tumorigenesis remains unexplored. We aimed to investigate whether DACH2 can be used as a biomarker to predict metastasis and prognosis of muscle-invasive UCB in a sequential training and validation fashion. For the training set (n = 40), compared with UCB patients without lymph node (LN) metastasis, both DACH2 protein and mRNA expression were greatly increased in case-matched patients with LN metastasis. For the independent validation set (n = 243), patients with primary UCB that did not express DACH2 had a longer metastasis-free survival (MFS) and overall survival (OS) than did those with tumors expressing DACH2 (5-year MFS: 88% [95% CI 80-96] versus 19% [95% CI 7-31], p < 0.001; 5-year OS: 93% [95% CI 87-99] versus 37% [95% CI 23-51], p < 0.001). Multivariable analysis of DACH2 status showed hazard ratios of 7.34 (95% CI 3.15-11.87, p < 0.001) for MFS and 3.96 (95% CI 2.04-7.16, p < 0.001) for OS which were much higher than hazard ratios associated with other independent risk factors. Collectively, DACH2 is an independent prognostic marker that can be used at initial diagnosis of UCB to identify patients who have a high potential to develop metastasis.

An endoplasmic reticulum stress-related signature featuring ASNS for predicting prognosis and immune landscape in prostate cancer.

Prostate cancer (PRAD) is one of the common malignant tumors of the urinary system. In order to predict the treatment results for PRAD patients, this study proposes to develop a risk profile based on endoplasmic reticulum stress (ERS). Based on the Memorial Sloan-Kettering Cancer Center (MSKCC) cohort and the Gene Expression Omnibus database (GSE70769), we verified the predictive signature. Using a random survival forest analysis, prognostically significant ERS-related genes were found. An ERS-related risk score (ERscore) was created using multivariable Cox analysis. In addition, the biological functions, genetic mutations and immune landscape related to ERscore are also studied to reveal the underlying mechanisms related to ERS in PRAD. We further explored the ERscore-related mechanisms by profiling a single-cell RNA sequencing (scRNA-seq) dataset (GSE137829) and explored the oncogenic role of ASNS in PRAD through in vitro experiments. The risk signature composed of eight ERS-related genes constructed in this study is an independent prognostic factor and validated in the MSKCC and GSE70769 data sets. The scRNA-seq data additionally revealed that several carcinogenic pathways were noticeably overactivated in the group with high ERS scores. As one of the prognostic genes, ASNS will significantly inhibit the proliferation, migration and invasion abilities of PRAD cells after its expression is interfered with. In conclusion, this study developed a novel risk-specific ERS-based clinical treatment strategy for patients with PRAD.

Eyecare-cloud: an innovative electronic medical record cloud platform for pediatric research and clinical care.

Background and objectives: Clinical data are essential for developing cloud platforms for intelligent diagnosis and treatment decision of diseases. However, cloud platforms for data sharing and exchange with clinicians are poorly suited. We aim to establish Eyecare-cloud, a platform which provide a novel method for clinical data and medical image sharing, to provide a convenient tool for clinicians. Methods: In this study, we displayed the main functions of Eyecare-cloud that we established. Based on clinical data from the cloud platform, we analyzed the incidence trend of the most common infantile retinal diseases, such as retinopathy of prematurity (ROP), over the past 20 years, as well as the associated risk factors for ROP occurrence. Statistical analyses were performed using GraphPad Prism (V.8.0) and SPSS software (V.26.0). Results: The Eyecare-cloud offers numerous advantages, including systematic archiving of patient information, one-click export data, simplifying data collection and management, eliminating the need for manual input of clinical information, reducing clinical data migration time, and lowering data management costs significantly. A total of 22,913 premature infants from Eyecare-cloud were included in the data analysis. Based on 20 years of premature infant screening data analysis, we found that the ROP incidence began to slowly decline starting in 2003 but showed a gradual increase trend again in 2016. The incidence of severe ROP remained relatively stable at a low level since 2010. The number of premature infants increased steadily before 2016 but decreased since then. ROP occurrence was significantly associated with male sex, lower gestational age, and lower birth weight (P < 0.001). Conclusion: Eyecare-cloud provides clinicians and researchers with convenient tools for big data analysis, which helps alleviate clinical workloads and integrate research data. This cloud platform supports the principles of predictive, preventive, and personalized medicine (PPPM/3PM), empowering clinicians and researchers to deliver more precise, proactive, and patient-centered eye care.

Multi-risk factors joint prediction model for risk prediction of retinopathy of prematurity.

Purpose: Retinopathy of prematurity (ROP) is a retinal vascular proliferative disease common in low birth weight and premature infants and is one of the main causes of blindness in children.In the context of predictive, preventive and personalized medicine (PPPM/3PM), early screening, identification and treatment of ROP will directly contribute to improve patients' long-term visual prognosis and reduce the risk of blindness. Thus, our objective is to establish an artificial intelligence (AI) algorithm combined with clinical demographics to create a risk model for ROP including treatment-requiring retinopathy of prematurity (TR-ROP) infants. Methods: A total of 22,569 infants who underwent routine ROP screening in Shenzhen Eye Hospital from March 2003 to September 2023 were collected, including 3335 infants with ROP and 1234 infants with TR-ROP among ROP infants. Two machine learning methods of logistic regression and decision tree and a deep learning method of multi-layer perceptron were trained by using the relevant combination of risk factors such as birth weight (BW), gestational age (GA), gender, whether multiple births (MB) and mode of delivery (MD) to achieve the risk prediction of ROP and TR-ROP. We used five evaluation metrics to evaluate the performance of the risk prediction model. The area under the receiver operating characteristic curve (AUC) and the area under the precision-recall curve (AUCPR) were the main measurement metrics. Results: In the risk prediction for ROP, the BW + GA demonstrated the optimal performance (mean ± SD, AUCPR: 0.4849 ± 0.0175, AUC: 0.8124 ± 0.0033). In the risk prediction of TR-ROP, reasonable performance can be achieved by using GA + BW + Gender + MD + MB (AUCPR: 0.2713 ± 0.0214, AUC: 0.8328 ± 0.0088). Conclusions: Combining risk factors with AI in screening programs for ROP could achieve risk prediction of ROP and TR-ROP, detect TR-ROP earlier and reduce the number of ROP examinations and unnecessary physiological stress in low-risk infants. Therefore, combining ROP-related biometric information with AI is a cost-effective strategy for predictive diagnostic, targeted prevention, and personalization of medical services in early screening and treatment of ROP.

Quantitative Assessment of Fundus Tessellated Density in Highly Myopic Glaucoma Using Deep Learning.

Purpose: To characterize the fundus tessellated density (FTD) in highly myopic glaucoma (HMG) and high myopia (HM) for discovering early signs and diagnostic markers. Methods: This retrospective cross-sectional study included hospital in-patients with HM (133 eyes) and HMG (73 eyes) with an axial length ≥26 mm at Zhongshan Ophthalmic Center. Using deep learning, FTD was quantified as the average exposed choroid area per unit area on fundus photographs in the global, macular, and disc regions. FTD-associated factors were assessed using partial correlation. Diagnostic efficacy was analyzed using the area under the curve (AUC). Results: HMG patients had lower global (0.20 ± 0.12 versus 0.36 ± 0.09) and macular FTD (0.25 ± 0.14 vs. 0.40 ± 0.09) but larger disc FTD (0.24 ± 0.11 vs. 0.19 ± 0.07) than HM patients in the tessellated fundus (all P < 0.001). In the macular region, nasal FTD was lowest in the HM (0.26 ± 0.13) but highest in the HMG (0.32 ± 0.13) compared with the superior, inferior, and temporal subregions (all P < 0.05). A fundus with a macular region nasal/temporal (NT) FTD ratio > 0.96 (AUC = 0.909) was 15.7 times more indicative of HMG than HM. A higher macular region NT ratio with a lower horizontal parapapillary atrophy/disc ratio indicated a higher possibility of HMG than HM (AUC = 0.932). Conclusions: FTD differs in degree and distribution between HMG and HM. A higher macular NT alone or with a lower horizontal parapapillary atrophy/disc ratio may help differentiate HMG. Translational Relevance: Deep learning-based FTD measurement could potentially assist glaucoma diagnosis in HM.

Automated detection of nine infantile fundus diseases and conditions in retinal images using a deep learning system.

Purpose: We developed an Infant Retinal Intelligent Diagnosis System (IRIDS), an automated system to aid early diagnosis and monitoring of infantile fundus diseases and health conditions to satisfy urgent needs of ophthalmologists. Methods: We developed IRIDS by combining convolutional neural networks and transformer structures, using a dataset of 7697 retinal images (1089 infants) from four hospitals. It identifies nine fundus diseases and conditions, namely, retinopathy of prematurity (ROP) (mild ROP, moderate ROP, and severe ROP), retinoblastoma (RB), retinitis pigmentosa (RP), Coats disease, coloboma of the choroid, congenital retinal fold (CRF), and normal. IRIDS also includes depth attention modules, ResNet-18 (Res-18), and Multi-Axis Vision Transformer (MaxViT). Performance was compared to that of ophthalmologists using 450 retinal images. The IRIDS employed a five-fold cross-validation approach to generate the classification results. Results: Several baseline models achieved the following metrics: accuracy, precision, recall, F1-score (F1), kappa, and area under the receiver operating characteristic curve (AUC) with best values of 94.62% (95% CI, 94.34%-94.90%), 94.07% (95% CI, 93.32%-94.82%), 90.56% (95% CI, 88.64%-92.48%), 92.34% (95% CI, 91.87%-92.81%), 91.15% (95% CI, 90.37%-91.93%), and 99.08% (95% CI, 99.07%-99.09%), respectively. In comparison, IRIDS showed promising results compared to ophthalmologists, demonstrating an average accuracy, precision, recall, F1, kappa, and AUC of 96.45% (95% CI, 96.37%-96.53%), 95.86% (95% CI, 94.56%-97.16%), 94.37% (95% CI, 93.95%-94.79%), 95.03% (95% CI, 94.45%-95.61%), 94.43% (95% CI, 93.96%-94.90%), and 99.51% (95% CI, 99.51%-99.51%), respectively, in multi-label classification on the test dataset, utilizing the Res-18 and MaxViT models. These results suggest that, particularly in terms of AUC, IRIDS achieved performance that warrants further investigation for the detection of retinal abnormalities. Conclusions: IRIDS identifies nine infantile fundus diseases and conditions accurately. It may aid non-ophthalmologist personnel in underserved areas in infantile fundus disease screening. Thus, preventing severe complications. The IRIDS serves as an example of artificial intelligence integration into ophthalmology to achieve better outcomes in predictive, preventive, and personalized medicine (PPPM / 3PM) in the treatment of infantile fundus diseases. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00350-y.

Mutant mice with rod-specific VPS35 deletion exhibit retinal α-synuclein pathology-associated degeneration.

Vacuolar protein sorting 35 (VPS35), the core component of the retromer complex which regulates endosomal trafficking, is genetically linked with Parkinson's disease (PD). Impaired vision is a common non-motor manifestation of PD. Here, we show mouse retinas with VPS35-deficient rods exhibit synapse loss and visual deficit, followed by progressive degeneration concomitant with the emergence of Lewy body-like inclusions and phospho-α-synuclein (P-αSyn) aggregation. Ultrastructural analyses reveal VPS35-deficient rods accumulate aggregates in late endosomes, deposited as lipofuscins bound to P-αSyn. Mechanistically, we uncover a protein network of VPS35 and its interaction with HSC70. VPS35 deficiency promotes sequestration of HSC70 and P-αSyn aggregation in late endosomes. Microglia which engulf lipofuscins and P-αSyn aggregates are activated, displaying autofluorescence, observed as bright dots in fundus imaging of live animals, coinciding with pathology onset and progression. The Rod∆Vps35 mouse line is a valuable tool for further mechanistic investigation of αSyn lesions and retinal degenerative diseases.

A fundus image dataset for intelligent retinopathy of prematurity system.

Image-based artificial intelligence (AI) systems stand as the major modality for evaluating ophthalmic conditions. However, most of the currently available AI systems are designed for experimental research using single-central datasets. Most of them fell short of application in real-world clinical settings. In this study, we collected a dataset of 1,099 fundus images in both normal and pathologic eyes from 483 premature infants for intelligent retinopathy of prematurity (ROP) system development and validation. Dataset diversity was visualized with a spatial scatter plot. Image classification was conducted by three annotators. To the best of our knowledge, this is one of the largest fundus datasets on ROP, and we believe it is conducive to the real-world application of AI systems.

Refractive Status and Biometric Characteristics of Children With Familial Exudative Vitreoretinopathy.

Purpose: To compare biometric characteristics between patients with early-stage familial exudative vitreoretinopathy (FEVR) and healthy controls. Methods: This case-control study included 50 FEVR eyes in stage 1-2 and 50 control eyes matched by age, gender and spherical equivalent (SE). Biometric parameters including axial length (AL), white-to-white diameter (WTW), central corneal thickness (CCT), anterior chamber depth (ACD), lens thickness (LT), pupil diameter, vitreous chamber depth, anterior and posterior corneal surface curvature radius (ACR and PCR), anterior lens surface curvature radius (ALR) and posterior lens surface curvature radius were measured using IOLMaster 700 and compared between cases and controls using paired t-test. Correlations between SE and biometric measures were assessed using Pearson correlation coefficient (r) in cases and controls. Results: Both FEVR cases and matched controls had a mean age of 7.6 years, 48% female and mean SE of -5.3 D (80% myopia). Compared to controls, FEVR eyes had smaller AL (P = 0.009), WTW (P = 0.001), ACD (P < 0.001), and ALR (P = 0.03), but larger CCT (P = 0.02) and LT (P = 0.01). In FEVR eyes, SE was negatively correlated with AL (r = -0.79, P < 0.001), positively correlated with ACR (r = 0.29, P = 0.04) and PCR (r = 0.33, P = 0.02), whereas in controls, SE was negatively correlated with AL (r = -0.82, P < 0.001) and LT (r = -0.34, P = 0.02), positively correlated with ALR (r = 0.29, P = 0.04). Conclusions: Patients at early stage of FEVR exhibited a unique eye morphology resembling ocular development arrest, which may help to develop screening and early detection tools for FEVR. In FEVR patients, myopia is very prevalent and significantly associated with corneal curvature increase.

An Artificial Intelligence System for Screening and Recommending the Treatment Modalities for Retinopathy of Prematurity.

PURPOSE: The purpose of this study was to develop an artificial intelligence (AI) system for the identification of disease status and recommending treatment modalities for retinopathy of prematurity (ROP). METHODS: This retrospective cohort study included a total of 24,495 RetCam images from 1075 eyes of 651 preterm infants who received RetCam examination at the Shenzhen Eye Hospital in Shenzhen, China, from January 2003 to August 2021. Three tasks included ROP identification, severe ROP identification, and treatment modalities identification (retinal laser photocoagulation or intravitreal injections). The AI system was developed to identify the 3 tasks, especially the treatment modalities of ROP. The performance between the AI system and ophthalmologists was compared using extra 200 RetCam images. RESULTS: The AI system exhibited favorable performance in the 3 tasks, including ROP identification [area under the receiver operating characteristic curve (AUC), 0.9531], severe ROP identification (AUC, 0.9132), and treatment modalities identification with laser photocoagulation or intravitreal injections (AUC, 0.9360). The AI system achieved an accuracy of 0.8627, a sensitivity of 0.7059, and a specificity of 0.9412 for identifying the treatment modalities of ROP. External validation results confirmed the good performance of the AI system with an accuracy of 92.0% in all 3 tasks, which was better than 4 experienced ophthalmologists who scored 56%, 65%, 71%, and 76%, respectively. CONCLUSIONS: The described AI system achieved promising outcomes in the automated identification of ROP severity and treatment modalities. Using such algorithmic approaches as accessory tools in the clinic may improve ROP screening in the future.

FIT-Net: Feature Interaction Transformer Network for Pathologic Myopia Diagnosis.

Automatic and accurate classification of retinal optical coherence tomography (OCT) images is essential to assist physicians in diagnosing and grading pathological changes in pathologic myopia (PM). Clinically, due to the obvious differences in the position, shape, and size of the lesion structure in different scanning directions, ophthalmologists usually need to combine the lesion structure in the OCT images in the horizontal and vertical scanning directions to diagnose the type of pathological changes in PM. To address these challenges, we propose a novel feature interaction Transformer network (FIT-Net) to diagnose PM using OCT images, which consists of two dual-scale Transformer (DST) blocks and an interactive attention (IA) unit. Specifically, FIT-Net divides image features of different scales into a series of feature block sequences. In order to enrich the feature representation, we propose an IA unit to realize the interactive learning of class token in feature sequences of different scales. The interaction between feature sequences of different scales can effectively integrate different scale image features, and hence FIT-Net can focus on meaningful lesion regions to improve the PM classification performance. Finally, by fusing the dual-view image features in the horizontal and vertical scanning directions, we propose six dual-view feature fusion methods for PM diagnosis. The extensive experimental results based on the clinically obtained datasets and three publicly available datasets demonstrate the effectiveness and superiority of the proposed method. Our code is avaiable at: https://github.com/chenshaobin/FITNet.

Predicting Optical Coherence Tomography-Derived High Myopia Grades From Fundus Photographs Using Deep Learning.

Purpose: To develop an artificial intelligence (AI) system that can predict optical coherence tomography (OCT)-derived high myopia grades based on fundus photographs. Methods: In this retrospective study, 1,853 qualified fundus photographs obtained from the Zhongshan Ophthalmic Center (ZOC) were selected to develop an AI system. Three retinal specialists assessed corresponding OCT images to label the fundus photographs. We developed a novel deep learning model to detect and predict myopic maculopathy according to the atrophy (A), traction (T), and neovascularisation (N) classification and grading system. Furthermore, we compared the performance of our model with that of ophthalmologists. Results: When evaluated on the test set, the deep learning model showed an area under the receiver operating characteristic curve (AUC) of 0.969 for category A, 0.895 for category T, and 0.936 for category N. The average accuracy of each category was 92.38% (A), 85.34% (T), and 94.21% (N). Moreover, the performance of our AI system was superior to that of attending ophthalmologists and comparable to that of retinal specialists. Conclusion: Our AI system achieved performance comparable to that of retinal specialists in predicting vision-threatening conditions in high myopia via simple fundus photographs instead of fundus and OCT images. The application of this system can save the cost of patients' follow-up, and is more suitable for applications in less developed areas that only have fundus photography.

Comparison of clinical outcomes of conbercept versus ranibizumab treatment for retinopathy of prematurity: a multicentral prospective randomised controlled trial.

PURPOSE: To compare the recurrence rate and surgical complications of retinopathy of prematurity (ROP) between patients treated with intravitreal injection of conbercept (IVC) and intravitreal injection of ranibizumab (IVR) within 6 months. METHODS: A multicentral prospective, randomised controlled trial was applied from May 2017 to February 2019 for the infants diagnosed as aggressive posterior-ROP, zone I or posterior zone II treatment-requiring ROP by binocular indirect ophthalmoscope and RetCam3. These infants were assigned to randomly receive either intravitreal injection of 0.25 mg conbercept or 0.25 mg ranibizumab. The recurrence rate, fundus fluorescence angiography (FFA) and surgical complications were examined during the follow-up period of 6 months. Recurrent eyes were retreated by laser or another intravitreal injection within the 72 hours. RESULTS: A total of 30 infant patients (60 eyes) underwent IVC and 30 patients (60 eyes) underwent IVR. A total of 10 eyes (16.67%) in the IVC group and 14 eyes (23.34%) in the IVR group developed recurrence. There was no significant statistical difference in the recurrence rate between the two groups (χ2=0.83, p=0.36). The postmenstrual age (PMA) at first injection was (34.60±3.47) weeks in IVC and (35.14±1.76) in IVR group. In recurrent cases, the mean PMA at second treatment were (43.31±3.85) and (43.43±3.89) weeks in the IVC and IVR group, respectively. The period between two treatments was (8.71±6.62) for the IVC and (8.29±2.56) weeks for the IVR group. All these results showed no significant statistical difference between these two groups. The fluorescein leakage were observed in the eyes of recurrent infants by FFA. There were no other complications in the two groups except for complicated cataract in three eyes. CONCLUSION: Both IVC and IVR are effective therapies for the treatment of ROP. Conbercept is a new option for treating ROP.

[Expressions of CD4+ CD25(high) regulatory T cells, TGF-beta 1 and COX-2 in the peripheral blood of prostate cancer patients].

OBJECTIVE: To investigate the expressions of CD4+ CD25(high) regulatory T cells, TGF-beta 1 and COX-2 in the peripheral blood of prostate cancer (PCa) patients, and analyze the role of CD4+ CD25(high) regulatory T cells in the pathogenesis of PCa and their relationship with TGF-beta 1 and COX-2. METHODS: We used flow cytometry to calculate the percentage of CD4+ CD25(high) regulatory T cells in the CD4+ T cells in the peripheral blood mononuclear cells (PBMC) from 30 PCa patients (11 localized and 19 non-localized cases) and 20 healthy volunteer controls, determined the expressions of TGF-beta 1 and COX-2 in the serum by ELISA, and analyzed their correlation with the CD4+ CD25(high) regulatory T cells in the PCa patients as well as the differences between the localized and non- localized cases. RESULTS: CD4+ CD25(high) regulatory T cells accounted for (18.32 +/- 7.49) % in the CD4+ T cells in PBMCs from the PCa patients, significantly higher than (7.77 +/- 1.86) % from the controls (P < 0.05), but with no statistically significant difference between pre- and post-treatment in the PCa patients (P > 0.05). The expressions of TGF-beta 1 and COX-2 in the peripheral blood were (215.97 +/- 55.16) ng/ml and (6.88 +/- 5.14) ng/ml in the PCa patients, in comparison with (149.75 +/- 47.11) ng/ml (P < 0.05) and (6.88 +/- 5.14) ng/ml (P > 0.05) in the controls. Multiple linear regression analysis showed no significant correlation between the expression of CD4+ CD25(high) regulatory T cells in PBMCs and those of TGF-beta 1 and COX-2 in the peripheral blood of the PCa patients. There were no significant differences between the localized and non-localized PCa groups in the expressions of CD4+ CD25(high) regulatory T cells, TGF-beta 1 and COX-2 (P > 0.05). CONCLUSION: CD4+ CD25(high) regulatory T cells in in PBMCs are involved in the pathogenesis of PCa. The proliferation of CD4+ CD25(high) regulatory T cells is not significantly correlated to the expressions of TGF-beta 1 and COX-2 in the peripheral blood, but maybe to the tumor itself and the local tumor microenvironment.

Efficacy and safety of scleral crosslinking using poly(ethylene glycol)ether tetrasuccinimidyl glutarate for form-deprivation myopia progression in rabbits.

Myopia is becoming increasingly prevalent worldwide at an alarming rate. However, no effective treatment is available for inhibiting myopia progression. Materials chemistry advancements have made it possible to regulate mechanical properties and rate of degradation with good compatibility by developing newly crosslinking systems such as the branched polyethylene glycol (PEG) systems. Herein, we presented a PEG molecule with N-hydroxysuccinimide (NHS) ester functional groups at the chain ends as a macromolecular crosslinking agent for the treatment of myopia. We found that the scleral collagen crosslinked with the four-armed star-shaped PEG molecule with NHS ester functional group (4S-PEG) showed better biomechanical properties, increased thermal stability and higher resistance to degradation. 4S-PEG exhibited relatively low cytotoxicity for human fetal scleral fibroblasts. The retrobulbar injection of 4S-PEG at a relatively low concentration (2.5 mM) showed good effective control of the progression of form-deprivation myopia in rabbits. There were no signs of adverse effect or damage by repeated injections with 4S-PEG in rabbits. The results of this work demonstrate that 4S-PEG can serve as a robust macromolecular crosslinking agent and is expected to have promise for application in the treatment of the progression of myopia.

Changes in the Incidence of Retinopathy of Prematurity in Extremely Low Birth Weight Infants in South China From 2004 to 2018.

PURPOSE: To report the changes in incidence and risk factors of retinopathy of prematurity (ROP) in extremely low birth weight (ELBW) infants over a 15-year period in South China. METHODS: The medical records of ELBW infants were retrospectively reviewed through established database of Shenzhen Screening for ROP Cooperative Group. The incidence and severity of ROP were compared among three successive 5-year periods (P1: 2004-2008, P2: 2009-2013, P3: 2014-2018). Gestational age, birth weight, plurality, mode of delivery and gender were analyzed as risk factors for ROP in ELBW infants. RESULTS: Among the 1099 included ELBW infants, 557 (50.7%) had ROP, and 328 (29.9%) had severe ROP. The highest incidence of ROP (87.5%) and severe ROP (82.5%) were seen in P1. From P2 to P3, the incidence of ROP and severe ROP increased from 45.9% to 50.3% for ROP (P < .05) and from 26.4% to 28.3% for severe ROP (P < .05), respectively. Multivariate logistic regression analysis found only gestational age has a significant effect on the incidence of ROP and severe ROP. CONCLUSIONS: From 2004 to 2018, the incidence of ROP and severe ROP in ELBW infants in South China was 50.7% and 29.9%, respectively. Controlling for the other risk factors, only gestational age was statistically associated with ROP in ELBW infants.

Comparison of OCT angiography in children with a history of intravitreal injection of ranibizumab versus laser photocoagulation for retinopathy of prematurity.

PURPOSE: To compare the foveal microvascular structure characteristics in children with a history of intravitreal injection of ranibizumab (IVR) versus laser photocoagulation (LP) for retinopathy of prematurity by optical coherence tomography angiography (OCTA). METHODS: In this cross-sectional study, a total of 17 children (28 eyes) underwent IVR and 20 children (37 eyes) underwent LP were recruited. The age of doing OCTA examination of the two groups are 5.4±1.1 years and 6.3±1.8 years, respectively (p=0.07). Spectral-domain OCTA was performed for all the eyes with a scan size of 3×3 mm. The data of the superficial retinal layer were analysed. The foveal avascular zone (FAZ) and vessel density (including vessel length density (VLD) and perfusion density (PD)) were measured using the software of OCTA (Cirrus AngioPlex 5000, Carl Zeiss, Meditec, Dubin, California, USA). The central foveal thicknesses (CFT) were measured by cross-sectional OCT. RESULTS: In the central fovea, the retinal VLD and PD of patients with IVR were 13.82±2.99 mm/mm2 and 0.25±0.05 mm2/mm2, respectively, which were significantly lower than those of the LP group (15.64±2.71 mm/mm2 and 0.28±0.05 mm2/mm2, p=0.01 and p=0.006). The FAZ area of patients with IVR and LP were 0.13±0.09 mm2 and 0.09±0.07 mm2, respectively (p=0.048). The CFT of patients with IVR and LP were 200.7±16.7 µm and 220.9±22.7 µm, respectively (p<0.01). The logarithm of the minimal angle of resolution best-corrected visual acuity of patients with IVR and LP were 0.2±0.1 and 0.1±0.1, respectively (p=0.01). There was no significant difference in the parafoveal and foveal VLD and PD, FAZ morphological index and spherical equivalent refraction (SER) between the two groups. CONCLUSION: The IVR might contribute to microvascular changes in the macular zone, such as reducing the central foveal VLD and PD, while the LP might contribute to microstructural changes, such as smaller FAZ and thicker CFT.

Targeted Blood Metabolomic Study on Retinopathy of Prematurity.

Purpose: This study aims at exploring alterations of major metabolites and metabolic pathways in retinopathy of prematurity (ROP) infants and identifying biomarkers that may merit early diagnosis of ROP. Methods: We analyzed targeted metabolites from 81 premature infants (<34 weeks of gestational age), including 40 ROP cases (15 males and 25 females, birth weight 1.263 ± 0. 345 kg, gestational age 31.20 ± 4.62 weeks) and 41 cases (30 males, 11 females, birth weight 1.220 ± 0.293 kg, gestational age 30.96 ± 4.17 weeks) of well-matched non-ROP controls. Metabolites were measured by ultra-performance liquid chromatography-tandem mass spectrometry. Standard multivariate and univariate analysis was performed to interpret metabolomic results. Results: Glycine, glutamate, leucine, serine, piperidine, valine, tryptophan, citrulline, malonyl carnitine (C3DC), and homocysteine were identified as the top discriminant metabolites. In particular, discriminant concentrations of C3DC and glycine were also confirmed by univariate analysis as statistically significant different between ROP and non-ROP infants. Conclusions: This study gained an insight into the metabolomic aspects of ROP development. We suggest that higher blood levels of C3DC and glycine can be promising biomarkers to predict the occurrence, but not the severity of ROP.