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Abstract Background Cranio-lenticulo-sutural dysplasia (CLSD) is a rare dysmorphic syndrome characterized by skeletal dysmorphism, late-closing fontanels, and cataracts. CLSD is caused by mutations in the SEC23A gene (OMIM# 607812) and can be inherited in either an autosomal dominant or autosomal recessive pattern. To date, only four mutations have been reported to cause CLSD. This study aims to identify the disease-causing variants in a large cohort of congenital cataract patients, to expand the genotypic and phenotypic spectrum of CLSD, and to confirm the association between SEC23A and autosomal recessive CLSD (ARCLSD). Methods We collected detailed medical records and performed comprehensive ocular examinations and whole-exome sequencing (WES) on 115 patients with congenital cataracts. After suspecting that a patient may have CLSD based on the sequencing results, we proceeded to conduct transmission electron microscopy (TEM) on the cultured skin fibroblasts. The clinical validity of the reported gene-disease relationships for the gene and the disease was evaluated using the ClinGen gene curation framework. Results Two novel compound heterozygous variants (c.710A > C p.Asp237Ala, c.1946T > C p.Leu649Pro) of the SEC23A gene, classified as variant of uncertain significance, were identified in the proband with skeletal, cardiac, ocular, and hearing defects. The observation of typical distended endoplasmic reticulum cisternae further supported the diagnosis of CLSD. Application of the ClinGen gene curation framework confirmed the association between SEC23A and ARCLSD. Conclusion This study expands the genotypic and phenotypic spectrum of CLSD, proposes TEM as a supplemental diagnostic method, and indicates that congenital cataracts are a typical sign of ARCLSD.

BackgroundThis study aimed to explore the postoperative myopic shift and its relationship to visual acuity rehabilitation in patients with bilateral congenital cataracts (CCs).MethodsBilateral CC patients who underwent cataract extraction and primary intraocular lens implantations before 6 years old were included and divided into five groups according to surgical ages (

Abstract A challenge of chronic diseases that remains to be solved is how to liberate patients and medical resources from the burdens of long-term monitoring and periodic visits. Precise management based on artificial intelligence (AI) holds great promise; however, a clinical application that fully integrates prediction and telehealth computing has not been achieved, and further efforts are required to validate its real-world benefits. Taking congenital cataract as a representative, we used Bayesian and deep-learning algorithms to create CC-Guardian, an AI agent that incorporates individualized prediction and scheduling, and intelligent telehealth follow-up computing. Our agent exhibits high sensitivity and specificity in both internal and multi-resource validation. We integrate our agent with a web-based smartphone app and prototype a prediction-telehealth cloud platform to support our intelligent follow-up system. We then conduct a retrospective self-controlled test validating that our system not only accurately detects and addresses complications at earlier stages, but also reduces the socioeconomic burdens compared to conventional methods. This study represents a pioneering step in applying AI to achieve real medical benefits and demonstrates a novel strategy for the effective management of chronic diseases.

The expansion of urban areas has resulted in a substantial increase in demand for water ecosystem services. To address this issue, this study aims to investigate how the interaction between urbanization and water ecosystem services changed in response to different levels of urbanization in the Dongjiang River Basin from 1985 to 2020. The research examines four water ecosystem services (water yield, soil retention, and water purifications of N and P) and three types of urbanizations (population urbanization, economic urbanization, and land urbanization) to identify spatial heterogeneities among developed urban areas, developing urban areas, and rural regions, as well as their dynamic interactions. The findings indicate that water ecosystem services and urbanizations tend to be spatially polarized, with high values downstream and low values upstream. Although they have become more closely aligned, there is a local mismatch under basin-level homogeneity. Urbanization has migrated and centralized in a southward direction, while water ecosystem services have moved westward. This difference of migration results in an increasing trade-off in the west band of Dongjiang River. In particular, the developing urban area has been strengthening the function of the transition zone between the developed urban area and rural area, resulting in a dramatic decrease in synergy. The synergy of the rural area dominates the increasing synergy of the entire basin, but the developed urban area tends to lower the water ecosystem services that lag behind urbanization. The study recommends that policymakers consider different urban levels when developing urbanization plans and water resource management strategies, and implement measures to maintain the synergy in the rural area and mitigate the trade-off in the developing area.

Purpose: To broaden the mutation and phenotype spectrum of the GJA8 and CHMP4B genes and to reveal genotype-phenotype correlations in a cohort of Chinese patients with congenital cataracts (CCs).Methods: Six Chinese Han families with CCs inherited in an autosomal dominant (AD) pattern were recruited for this study. All patients underwent full ocular examinations. Genomic DNA was extracted from the leukocytes of peripheral blood collected from all available patients and their unaffected family members. Whole-exome sequencing (WES) was performed on all probands and at least one of their parents. Candidate variants were further confirmed by Sanger sequencing. Bioinformatic analysis with several computational predictive programs was performed to assess the impacts of the candidate variants on the structure and function of the proteins.Results: Four heterozygous candidate variants in three different genes (CRYBB2, GJA8, and CHMP4B) were identified in affected individuals from the six families, including two novel missense variants (GJA8: c.64G > C/p. G22R, and CHMP4B: c.587C > G/p. S196C), one missense mutation (CRYBB2: c.562C > T/p. R188C), and one small deletion (GJA8: c.426_440delGCTGGAGGGGACCCT/p.143_147delLEGTL). The three missense mutations were predicted as deleterious in all four computational prediction programs. In the homologous model, the GJA8: p.143_147delLEGTL mutation showed a sequence deletion of five amino acids at the cytoplasmic loop of the Cx50 protein, close to the third transmembrane domain. Patients carrying mutations in the same gene showed similar cataract phenotypes at a young age, including total cataracts, Y-sutural with fetal nuclear cataracts, and subcapsular cataracts.Conclusion: This study further expands the mutation spectrum and genotype-phenotype correlation of CRYBB2, GJA8, and CHMP4B underlying CCs. This study sheds light on the importance of comparing congenital cataract phenotypes in patients at the same age stage. It offers clues for the pathogenesis of CCs and allows for an early prenatal diagnosis for families carrying these genetic variants.

Reliable validated methods are necessary to verify the performance of diagnosis and therapy-assisted models in clinical practice. However, some validated results have research bias and may not reflect the results of real-world application. In addition, the conduct of clinical trials has executive risks for the indeterminate effectiveness of models and it is challenging to finish validated clinical trials of rare diseases. Real world data (RWD) can probably solve this problem. In our study, we collected RWD from 251 patients with a rare disease, childhood cataract (CC) and conducted a retrospective study to validate the CC surgical decision model. The consistency of the real surgical type and recommended surgical type was 94.16%. In the cataract extraction (CE) group, the model recommended the same surgical type for 84.48% of eyes, but the model advised conducting cataract extraction and primary intraocular lens implantation (CE + IOL) surgery in 15.52% of eyes, which was different from the real-world choices. In the CE + IOL group, the model recommended the same surgical type for 100% of eyes. The real-recommended matched rates were 94.22% in the eyes of bilateral patients and 90.38% in the eyes of unilateral patients. Our study is the first to apply RWD to complete a retrospective study evaluating a clinical model, and the results indicate the availability and feasibility of applying RWD in model validation and serve guidance for intelligent model evaluation for rare diseases.

Infantile cataract is the main cause of infant blindness worldwide. Although previous studies developed artificial intelligence (AI) diagnostic systems for detecting infantile cataracts in a single center, its generalizability is not ideal because of the complicated noises and heterogeneity of multicenter slit-lamp images, which impedes the application of these AI systems in real-world clinics. In this study, we developed two lens partition strategies (LPSs) based on deep learning Faster R-CNN and Hough transform for improving the generalizability of infantile cataracts detection. A total of 1,643 multicenter slit-lamp images collected from five ophthalmic clinics were used to evaluate the performance of LPSs. The generalizability of Faster R-CNN for screening and grading was explored by sequentially adding multicenter images to the training dataset. For the normal and abnormal lenses partition, the Faster R-CNN achieved the average intersection over union of 0.9419 and 0.9107, respectively, and their average precisions are both > 95%. Compared with the Hough transform, the accuracy, specificity, and sensitivity of Faster R-CNN for opacity area grading were improved by 5.31, 8.09, and 3.29%, respectively. Similar improvements were presented on the other grading of opacity density and location. The minimal training sample size required by Faster R-CNN is determined on multicenter slit-lamp images. Furthermore, the Faster R-CNN achieved real-time lens partition with only 0.25 s for a single image, whereas the Hough transform needs 34.46 s. Finally, using Grad-Cam and t-SNE techniques, the most relevant lesion regions were highlighted in heatmaps, and the high-level features were discriminated. This study provides an effective LPS for improving the generalizability of infantile cataracts detection. This system has the potential to be applied to multicenter slit-lamp images.

The results of visual prediction reflect the tendency and speed of visual development during a future period, based on which ophthalmologists and guardians can know the potential visual prognosis in advance, decide on an intervention plan, and contribute to visual development. In our study, we developed an intelligent system based on the features of optical coherence tomography images for long-term prediction of best corrected visual acuity (BCVA) 3 and 5 years in advance. Two hundred eyes of 132 patients were included. Six machine learning algorithms were applied. In the BCVA predictions, small errors within two lines of the visual chart were achieved. The mean absolute errors (MAEs) between the prediction results and ground truth were 0.1482–0.2117 logMAR for 3-year predictions and 0.1198–0.1845 logMAR for 5-year predictions; the root mean square errors (RMSEs) were 0.1916–0.2942 logMAR for 3-year predictions and 0.1692–0.2537 logMAR for 5-year predictions. This is the first study to predict post-therapeutic BCVAs in young children. This work establishes a reliable method to predict prognosis 5 years in advance. The application of our research contributes to the design of visual intervention plans and visual prognosis.

Abstract Background Ocular images play an essential role in ophthalmological diagnoses. Having an imbalanced dataset is an inevitable issue in automated ocular diseases diagnosis; the scarcity of positive samples always tends to result in the misdiagnosis of severe patients during the classification task. Exploring an effective computer-aided diagnostic method to deal with imbalanced ophthalmological dataset is crucial. Methods In this paper, we develop an effective cost-sensitive deep residual convolutional neural network (CS-ResCNN) classifier to diagnose ophthalmic diseases using retro-illumination images. First, the regions of interest (crystalline lens) are automatically identified via twice-applied Canny detection and Hough transformation. Then, the localized zones are fed into the CS-ResCNN to extract high-level features for subsequent use in automatic diagnosis. Second, the impacts of cost factors on the CS-ResCNN are further analyzed using a grid-search procedure to verify that our proposed system is robust and efficient. Results Qualitative analyses and quantitative experimental results demonstrate that our proposed method outperforms other conventional approaches and offers exceptional mean accuracy (92.24%), specificity (93.19%), sensitivity (89.66%) and AUC (97.11%) results. Moreover, the sensitivity of the CS-ResCNN is enhanced by over 13.6% compared to the native CNN method. Conclusion Our study provides a practical strategy for addressing imbalanced ophthalmological datasets and has the potential to be applied to other medical images. The developed and deployed CS-ResCNN could serve as computer-aided diagnosis software for ophthalmologists in clinical application.

Abstract Background To investigate the distribution of the height, weight and body mass index (BMI) of children with congenital cataracts (CC) before surgical treatment. Methods This prospective study included children with CC ≤14 years of age presenting at the Zhongshan Ophthalmic Center from Jan. 2013 to Aug. 2016. The height, weight, and BMI measurements of all participating children were obtained and compared with the World Health Organization Child Growth Reference (WHO Reference), matched by age and gender. The presence of a family history of CC or complicated systemic diseases as well as parental education levels and family income were also recorded. Results In total, 595 children with CC were included. The mean age was 52.75 ± 33.99 months, and 34.29% (204/595) of them were unilateral cases. Among all of the children, 6.72% (40/595) of cases were complicated by systemic diseases. More than 1/5 (21.01%, 125/595) of the children had a family history of CC and exhibited bilateral involvement. Less than 1/4 (23.2) of the mothers were highly educated, and more than half of the families had a family income below the city average. Height, weight, and BMI measurements of most children with CC were within the normal ranges (±95% CI of the WHO Reference). Compared to the WHO Reference, both girls and boys aged 2–5 years revealed shorter heights, and the girls aged 5–14 years exhibited a shorter height, lower body weight and lower BMI. The heights of the children with CC and systemic diseases were also shorter than the WHO Reference. The children with CC who had a family history of disease had shorter heights and lower BMIs than children with CC but no family history, and the measurements of both groups were lower than the WHO Reference values. Conclusions The height, weight and BMI of most of the children with CC in this study were within the normal ranges of the WHO Reference. However, the children with CC and concomitant systemic diseases and those with a family history of CC had shorter heights and lower BMIs. This information aids in our understanding of the physical development of children with CC.

Abstract Background The majority of rare diseases are complex diseases caused by a combination of multiple morbigenous factors. However, uncovering the complex etiology and pathogenesis of rare diseases is difficult due to limited clinical resources and conventional statistical methods. This study aims to investigate the interrelationship and the effectiveness of potential factors of pediatric cataract, for the exploration of data mining strategy in the scenarios of rare diseases. Methods We established a pilot rare disease specialized care center to systematically record all information and the entire treatment process of pediatric cataract patients. These clinical records contain the medical history, multiple structural indices, and comprehensive functional metrics. A two-layer structural equation model network was applied, and eight potential factors were filtered and included in the final modeling. Results Four risk factors (area, density, location, and abnormal pregnancy experience) and four beneficial factors (axis length, uncorrected visual acuity, intraocular pressure, and age at diagnosis) were identified. Quantifiable results suggested that abnormal pregnancy history may be the principle risk factor among medical history for pediatric cataracts. Moreover, axis length, density, uncorrected visual acuity and age at diagnosis served as the dominant factors and should be emphasized in regular clinical practice. Conclusions This study proposes a generalized evidence-based pattern for rare and complex disease data mining, provides new insights and clinical implications on pediatric cataract, and promotes rare-disease research and prevention to benefit patients.

Background: Approximately 1 in 33 newborns is affected by congenital anomalies worldwide. We aimed to develop a practical model for identifying infants with a high risk of congenital cataracts (CCs), which is the leading cause of avoidable childhood blindness. Methods: This case-control study was performed in the Zhongshan Ophthalmic Center and involved 2005 subjects, including 1274 children with CCs and 731 healthy controls. The CC identification models were established based on birth conditions, family medical history, and family environmental factors using the random forest (RF) and adaptive boosting methods (trained by 1129 CC cases and 609 healthy controls), which were tested by internal 4-fold cross-validation and external validation (145 CC cases and 122 healthy controls). The models were also tested using 4 datasets with gradually reduced proportions of CC patients (bilateral cases) to validate their performance in an approximate simulation of a clinical environment with a relatively low disease prevalence. Findings: The CC identification models showed high discrimination in both the 4-fold cross validation (area under the curve (AUC)=0.91 [95% confidence interval: 0.88–0.94] in bilateral cases; 0.82 [0.77–0.89] in unilateral cases) and external validation (AUC=0.93±0.05 in bilateral cases; 0.86±0.01 in unilateral cases), and achieved stable performance in the clinical tests (AUC=0.94–0.96 in the four subgroups by RF). Furthermore, family history of CC, low parental education level, and comorbidity were identified as the top three most relevant factors to both bilateral and unilateral CC diagnosis. Interpretation: Our CC identification models can accurately discriminate CC patients from healthy children and have the potential to serve as a complementary screening procedure, especially in undeveloped and remote areas. Keywords: Congenital anomaly, Congenital cataract, Identification model, Machine learning

Ocular images play an essential role in ophthalmology. Current research mainly focuses on computer-aided diagnosis using slit-lamp images, however few studies have been done to predict the progression of ophthalmic disease. Therefore exploring an effective approach of prediction can help to plan treatment strategies and to provide early warning for the patients. In this study, we present an end-to-end temporal sequence network (TempSeq-Net) to automatically predict the progression of ophthalmic disease, which includes employing convolutional neural network (CNN) to extract high-level features from consecutive slit-lamp images and applying long short term memory (LSTM) method to mine the temporal relationship of features. First, we comprehensively compare six potential combinations of CNNs and LSTM (or recurrent neural network) in terms of effectiveness and efficiency, to obtain the optimal TempSeq-Net model. Second, we analyze the impacts of sequence lengths on model's performance which help to evaluate their stability and validity and to determine the appropriate range of sequence lengths. The quantitative results demonstrated that our proposed model offers exceptional performance with mean accuracy (92.22), sensitivity (88.55), specificity (94.31) and AUC (97.18). Moreover, the model achieves real-time prediction with only 27.6ms for single sequence, and simultaneously predicts sequence data with lengths of 3-5. Our study provides a promising strategy for the progression of ophthalmic disease, and has the potential to be applied in other medical fields.

Slit-lamp images play an essential role for diagnosis of pediatric cataracts. We present a computer vision-based framework for the automatic localization and diagnosis of slit-lamp images by identifying the lens region of interest (ROI) and employing a deep learning convolutional neural network (CNN). First, three grading degrees for slit-lamp images are proposed in conjunction with three leading ophthalmologists. The lens ROI is located in an automated manner in the original image using two successive applications of Candy detection and the Hough transform, which are cropped, resized to a fixed size and used to form pediatric cataract datasets. These datasets are fed into the CNN to extract high-level features and implement automatic classification and grading. To demonstrate the performance and effectiveness of the deep features extracted in the CNN, we investigate the features combined with support vector machine (SVM) and softmax classifier and compare these with the traditional representative methods. The qualitative and quantitative experimental results demonstrate that our proposed method offers exceptional mean accuracy, sensitivity and specificity: classification (97.07%, 97.28%, and 96.83%) and a three-degree grading area (89.02%, 86.63%, and 90.75%), density (92.68%, 91.05%, and 93.94%) and location (89.28%, 82.70%, and 93.08%). Finally, we developed and deployed a potential automatic diagnostic software for ophthalmologists and patients in clinical applications to implement the validated model.

Objectives To explore the characteristics of the low-income elderly who underwent free cataract surgery and to determine the degree of patient satisfaction with the free cataract surgery programme in urban China.Methods A free cataract surgery management workflow was designed as a poverty relief project in Guangzhou. In this study, participants who underwent free cataract surgery between January and August 2014 received a telephone interview based on a structured questionnaire. Data were collected on patient demographics, resources, health conditions, reasons for undergoing the free surgery and overall evaluation of the free cataract surgery programme.Results Among the 833 participants, the mean surgical age was 76.85±7.46 years (95% CI 76.34 to 77.36), and the male to female ratio was 385:448. The majority (94.31%, 746/791) of patients resided in the main urban districts. Patients underwent surgery 61.08±60.15 months (95% CI 56.17 to 66.00) after becoming aware of the cataract, although 66.83% of them reported that their daily lives were influenced by cataracts. Only 21.5% of the respondents underwent physical examinations that included regular eye screening, and only 6.30% were highly educated patients. Financial problems were the primary reason cited by patients for participating in the free surgery programme. Those patients with a monthly family income of 1000–2999¥ (US$161–482) per capita constituted the largest patient population. The free clinics in the parks and the free cataract surgery were highly rated (9.46 and 9.11 of 10 points) by the beneficiaries.Conclusions The telephone survey revealed a high level of patient satisfaction regarding the free cataract surgery programme. Most of the patients who participated in the programme resided in major urban districts and had poor health awareness and a low level of education. The information provided by this study is crucial for improving and expanding the management of free cataract surgery programmes.Trial registration number NCT02633865; Post-results.

A review of 6 years of hospitalization charts from Zhongshan Ophthalmic Center (ZOC) revealed that congenital cataracts (CC) accounted for 2.39% of all cataract in-patient cases and that the age at surgery was decreasing before the establishment of the Childhood Cataract Program of the Chinese Ministry of Health (CCPMOH) in December 2010. We aimed to investigate data from the 4 years (January 2011 to December 2014) following the establishment of the CCPMOH, compared, and combined with data from the previous study period (January 2005 to December 2010) to generate a 10-year overview of the hospital-based prevalence and treatment of CC. In the 4-year period after CCPMOH establishment, the prevalence of CC was 2.01% in all hospitalizations, and was 2.78% in all cataract in-patients. Most of the eligible CC in-patients (71%) lived in south China. The ratio of boys to girls was 1.42:1. Nearly 2/3 of the patients underwent cataract extraction with primary intraocular lens (IOL) implantation at a mean age of 78.40±51.45 months, and cataract extraction surgeries without IOL implantation were performed in the remaining 1/3 of patients at a mean age of 10.03±15.92 months. After CCPMOH establishment, an increased incidence of CC was revealed, and the CC in-patients were younger than the patients in the previous period. The 10-year overview (2421 CC in-patients from 206630 hospitalizations) revealed upward trends in both the number and the prevalence of CC and a further reduction in age at surgery. In conclusion, the data from 4-year period after CCPMOH establishment and the 10-year overview showed upward trends in the hospital-based prevalence of CC cases and a further reduction in age at surgery, likely reflecting the effects of the CCPMOH establishment and providing useful information for further CC studies and a valuable foundation for the prevention and treatment of this cause of childhood blindness.

To compare the efficacy and safety of the intraocular lens (IOL)-shell procedure versus conventional phacoemulsification for the surgical treatment of dense cataracts.Eighty eyes with dense nuclear cataracts were enrolled in a prospective, randomized controlled study. Patients were assigned to two groups. In Group I, the IOL was traditionally implanted after all nuclear fragments were completely removed, and in Group II, the IOL was innovatively implanted in the bag before the last residual nuclear fragment was removed. This novel adjusted surgical procedure, named the "IOL-shell technique", features use of the IOL as a protective barrier rather than simply as a refractive alternative, and it is conceptually different from the traditional step-by-step procedure. Clinical examinations, including uncorrected visual acuity, central corneal thickness (CCT), temporal clear corneal incision thickness and corneal endothelial cell density, were carried out.The inter-group difference in temporal corneal thickness was found to be of no statistical significance at any of the visits. Compared to eyes in Group I, those in Group II were shown to have significantly less corneal endothelial cell loss on both the 7th and 30th day following surgery. At 7 days after surgery, the mean corneal endothelial cell loss in Group II was 10.29%, compared to 14.37% in Group I (P

Congenital cataract (CC) is the primary cause of treatable childhood blindness. Population-based assessments of prevalence and surgery age of CC, which are critical for improving management strategies, have been unavailable in China until now. We conducted a hospital-based, cross-sectional study of the hospital charts of CC patients younger than 18 years old from January 2005 to December 2010 at Zhongshan Ophthalmic Center (ZOC) in Guangzhou, China. Residence, gender, age at surgery, hospitalization time, and the presence of other ocular abnormalities were extracted and statistically analyzed in different subgroups. The search identified 1314 patients diagnosed with CC from a total of 136154 hospitalizations, which accounted for 2.39% of all the cataract in-patients and 1.06% of the total in-patients over the six-year study period. Of the identified CC patients, 9.2% had ≥ 2 hospitalizations due to the necessity of additional surgeries, with a total ratio of boys to girls of 1.75 ∶ 1. Based on a subgroup analysis according to age, patients 2-6 years old constituted the highest proportion (29.22%) of all hospitalized CC patients, and those 13-18 years old constituted the lowest proportion (13.47%) of the total number. The average age at surgery was 27.62 ± 23.36 months, but CC patients ≤ 6 years old (especially ≤ 6 months old) became increasingly prevalent throughout the 6-year study period. A total of 276 cases (20.93%) of CC were associated with one or more other ocular abnormalities, the highest incidence rates were observed for exotropia (6.24%), nystagmus (6.16%), and refractive error (3.65%). In conclusion, CC patients accounted for 2.39% of all cataract in-patients in a review of 6 years of hospitalization charts from ZOC. The age at the time of surgery decreased over the 6-year study period, which probably reflects the continuing improvement of public awareness of children's eye care in China.

Congenital cataract is a major cause of visual impairment and childhood blindness. The solubility and stability of crystallin proteins play critical roles in maintaining the optical transparency of the lens during the life span. Previous studies have shown that approximately 8.3%~25% of congenital cataracts are inherited, and mutations in crystallins are the most common. In this study, we attempted to identify the genetic defect in a four-generation family affected with congenital cataracts. The congenital cataract phenotype of this four-generation family was identified as membranous cataract by slit-lamp photography. Mutation screening of the candidate genes detected a heterozygous c.465G → C change in the exon6 of the βB2-crystallin gene (CRYBB2) in all family members affected with cataracts, resulting in the substitution of a highly conserved Tryptophan to Cystine (p.W151C). The mutation was confirmed by restriction fragment length polymorphism (RFLP) analysis and found that the transition resulted in the absence of a BslI restriction site in the affected members of the pedigree. The outcome of PolyPhen-2 and SIFT analysis predicted that this W151C mutation would probably damage to the structure and function of βB2-crystallin. Wild type (wt) and W151C mutant βB2-crystallin were expressed in human lens epithelial cells (HLECs), and the fluorescence results showed that Wt-βB2-crystallin was evenly distributed throughout the cells, whereas approximately 34.7% of cells transfected with the W151C mutant βB2-crystallin formed intracellular aggregates. Taken together, these data suggest that the missense mutation in CRYBB2 gene leads to progressive congenital membranous cataract by impacting the solubility and function of βB2-crystallin.

Pediatric ophthalmologists increasingly recognize that the ideal site for intraocular lens (IOL) implantation is in the bag for aphakic eyes, but it is always very difficult via conventional technique. We conducted a prospective case series study to investigate the success rate and clinical outcomes of capsular bag reestablishment and in-the-bag IOL implantation via secondary capsulorhexis with radiofrequency diathermy (RFD) in pediatric aphakic eyes, in which twenty-two consecutive aphakic pediatric patients (43 aphakic eyes) enrolled in the Childhood Cataract Program of the Chinese Ministry of Health were included. The included children underwent either our novel technique for secondary IOL implantation (with RFD) or the conventional technique (with a bent needle or forceps), depending on the type of preoperative proliferative capsular bag present. In total, secondary capsulorhexis with RFD was successfully applied in 32 eyes (32/43, 74.4%, age 5.6±2.3 years), of which capsular bag reestablishment and in-the-bag IOL implantation were both achieved in 30 eyes (30/43, 70.0%), but in the remaining 2 eyes (2/32, 6.2%) the IOLs were implanted in the sulcus with a capsular bag that was too small. Secondary capsulorhexis with conventional technique was applied in the other 11 eyes (11/43, 25.6%, age 6.9±2.3 years), of which capsular bag reestablishment and in-the-bag IOL implantation were both achieved only in 3 eyes(3/43, 7.0%), and the IOLs were implanted in the sulcus in the remaining 8 eyes. A doughnut-like proliferative capsular bag with an extensive Soemmering ring (32/43, 74.4%) was the main success factor for secondary capsulorhexis with RFD, and a sufficient capsular bag size (33/43, 76.7%) was an additional factor in successful in-the-bag IOL implantation. In conclusion, RFD secondary capsulorhexis technique has 70% success rate in the capsular bag reestablishment and in-the-bag IOL implantation in pediatric aphakic eyes, particularly effective in cases with a doughnut-like, extensively proliferative Soemmering ring.

Monitoring intraocular pressure (IOP) is essential for pediatric cataract treatment but always difficult due to lack of cooperation in young children. We present the baseline characteristics and the first-year results of a long-term prospective cohort study, which are aimed to determine the relationship of the incidence of ocular hypertension (OH) in children after cataract surgery during the first-year period and the risk of developing late-onset glaucoma. Children were included with the following criteria: they were ≤10 years old and scheduled to undergo cataract surgery with/without intraocular lens implantation; they were compliant with our follow-up protocol, which included monitoring IOP using a Tono-Pen under sedation or anesthesia. Incidence of OH, peak OH value, OH onset time and OH duration within a 12-month period following surgery were measured. In brief, 206 patients (379 eyes) were included and OH developed in 66 of 379 (17.4%) eyes. The mean follow-up period was 14.0±3.2 months (median, 12 months; range, 10-16 months). Moreover, 33 of 196 (16.8%) aphakic eyes and 33 of 183 (18.0%) IOL eyes were diagnosed with OH. The peak OH onset times were at 1-week (34/66, 51.5%) and 1-month (14/66, 21.2%) appointments postsurgery. The peak IOP value in the OH eyes was 29.9±7.5 mmHg (median, 29 mmHg; range, 21-48 mmHg). The duration of OH was 30.9±31.2 days (median, 30 days; range, 3-150 days). OH recurred in 13 eyes with a history of OH diagnosed within 1 month postsurgery (13/54, 24.1%), which needed temporary or long term use of antiglaucoma medications. In conclusion, the incidence of OH in children after cataract surgery was 17.4% during the first-year period. Children who have suffered elevated IOP in the first year after cataract surgery should be followed closely to determine if there is an increased risk of developing late-onset glaucoma.

Aims To report the incidence and associated risk factors for developing suspected and definitive glaucoma after bilateral congenital cataract (CC) removal with a 5-year follow-up. Methods Secondary analysis of a prospective longitudinal cohort study. Bilateral CC patients who had undergone cataract surgery between January 2011 and December 2014 at Zhongshan Ophthalmic Centre were recruited. Suspected glaucoma was defined as persistent ocular hypertension requiring medical treatment. Definitive glaucoma was defined as accompanied by the progression of glaucomatous clinical features. According to postoperative lens status in 5 years follow-up: 130 eyes in the aphakia group; 219 in the primary intraocular lens (IOL) implantation group and 337 in the secondary IOL implantation group. The Kaplan-Meier survival and Cox regression analyses were used to explore the cumulative incidence and risk factors for suspected and definitive glaucoma. Results Three hundred fifty-one children (686 eyes) with bilateral CCs were enrolled in the study. The mean age at surgery was 1.82±2.08 years, and the mean follow-up duration was 6.26±0.97 years. Suspected and definitive glaucoma developed at a mean time of 2.84±1.75 years (range 0.02-7.33 years) postoperatively. The cumulative incidence of suspected and definitive glaucoma was 9.97% (35 of 351 patients), including 6.12% (42 eyes) for definitive glaucoma and 2.48% (17 eyes) for suspected glaucoma. Microcornea (HR 4.103, p<0.0001), CC family history (HR 3.285, p=0.001) and initial anterior vitrectomy (HR 2.365 p=0.036) were risk factors for suspected and definitive glaucoma. Gender, age at surgery, intraocular surgery frequency, length of follow-up and frequency of neodymium-doped yttrium aluminumaluminium garnet laser were non-statistically significant. Primary IOL implantation was a protective factor (HR 0.378, p=0.007). Conclusions Identifying suspected and definitive glaucoma after bilateral CC surgery can lower the risk of secondary blindness in children. Patients with related risk factors need to pay more attention and thus reach early intervention and treatment during clinical practice. Primary IOL implantation may be a potential protective factor, need more clinical trials to be verified. [ABSTRACT FROM AUTHOR]