Low-light image enhancement using generative adversarial networks.

In low-light environments, the amount of light captured by the camera sensor is reduced, resulting in lower image brightness. This makes it difficult to recognize or completely lose details in the image, which affects subsequent processing of low-light images. Low-light image enhancement methods can increase image brightness while better-restoring color and detail information. A generative adversarial network is proposed for low-quality image enhancement to improve the quality of low-light images. This network consists of a generative network and an adversarial network. In the generative network, a multi-scale feature extraction module, which consists of dilated convolutions, regular convolutions, max pooling, and average pooling, is designed. This module can extract low-light image features from multiple scales, thereby obtaining richer feature information. Secondly, an illumination attention module is designed to reduce the interference of redundant features. This module assigns greater weight to important illumination features, enabling the network to extract illumination features more effectively. Finally, an encoder-decoder generative network is designed. It uses the multi-scale feature extraction module, illumination attention module, and other conventional modules to enhance low-light images and improve quality. Regarding the adversarial network, a dual-discriminator structure is designed. This network has a global adversarial network and a local adversarial network. They determine if the input image is actual or generated from global and local features, enhancing the performance of the generator network. Additionally, an improved loss function is proposed by introducing color loss and perceptual loss into the conventional loss function. It can better measure the color loss between the generated image and a normally illuminated image, thus reducing color distortion during the enhancement process. The proposed method, along with other methods, is tested using both synthesized and real low-light images. Experimental results show that, compared to other methods, the images enhanced by the proposed method are closer to normally illuminated images for synthetic low-light images. For real low-light images, the images enhanced by the proposed method retain more details, are more apparent, and exhibit higher performance metrics. Overall, compared to other methods, the proposed method demonstrates better image enhancement capabilities for both synthetic and real low-light images.

Defect detection of photovoltaic modules based on improved VarifocalNet.

Detecting and replacing defective photovoltaic modules is essential as they directly impact power generation efficiency. Many current deep learning-based methods for detecting defects in photovoltaic modules focus solely on either detection speed or accuracy, which limits their practical application. To address this issue, an improved VarifocalNet has been proposed to enhance both the detection speed and accuracy of defective photovoltaic modules. Firstly, a new bottleneck module is designed to replace the first bottleneck module of the last stage convolution group in the backbone. This new module includes both standard convolution and dilated convolution, enabling an increase in network depth and receptive field without reducing the output feature map size. This improvement can help to enhance the accuracy of defect detection for photovoltaic modules. Secondly, another bottleneck module is also designed and used to replace the original bottleneck module used in the fourth stage convolution group of the backbone. This new module has smaller parameters than the original bottleneck module, which is useful to improve the defect detection speed of the photovoltaic module. Thirdly, a feature interactor is designed in the detection head to enhance feature expression in the classification branch. This helps improve detection accuracy. Besides, an improved intersection over union is proposed and introduced into the loss function to measure the difference between the predicted and ground truth boxes. This is useful for improving defect detection accuracy. Compared to other methods, the proposed method has the highest detection accuracy. Additionally, it also has a faster detection speed than other methods except for the DDH-YOLOv5 method and the improved YOLOv7 method.

Nighttime road scene image enhancement based on cycle-consistent generative adversarial network.

During nighttime road scenes, images are often affected by contrast distortion, loss of detailed information, and a significant amount of noise. These factors can negatively impact the accuracy of segmentation and object detection in nighttime road scenes. A cycle-consistent generative adversarial network has been proposed to address this issue to improve the quality of nighttime road scene images. The network includes two generative networks with identical structures and two adversarial networks with identical structures. The generative network comprises an encoder network and a corresponding decoder network. A context feature extraction module is designed as the foundational element of the encoder-decoder network to capture more contextual semantic information with different receptive fields. A receptive field residual module is also designed to increase the receptive field in the encoder network.The illumination attention module is inserted between the encoder and decoder to transfer critical features extracted by the encoder to the decoder. The network also includes a multiscale discriminative network to discriminate better whether the image is a real high-quality or generated image. Additionally, an improved loss function is proposed to enhance the efficacy of image enhancement. Compared to state-of-the-art methods, the proposed approach achieves the highest performance in enhancing nighttime images, making them clearer and more natural.

Effects of Topical 0.05% Cyclosporine A on Dry Eye Symptoms and Parameters Following Small Incision Lenticule Extraction.

PURPOSE: To evaluate the effects of topical 0.05% cyclosporine A on Ocular Surface Disease Index (OSDI) score and ocular surface parameters after small incision lenticule extraction (SMILE) for myopia. METHODS: In this study, 151 patients who underwent SMILE were randomized into the control group (71 eyes) and the 0.05% cyclosporine A group (80 eyes). Both groups received standard treatment during the 1 month after SMILE. Over the next 3 months, The control group continued standard therapy (0.3% sodium hyaluronate) and the 0.05% cyclosporine A group received additional 0.05% cyclosporine A. OSDI total and subscale scores, non-invasive tear break-up time (NIBUT), tear lipid layer thickness (LLT), and tear meniscus height (TMH) were assessed preoperatively and postoperatively. RESULTS: Compared to baseline, the OSDI scores significantly increased in both groups (P < .001). The 0.05% cyclosporine A group exhibited lower OSDI total scores after administering 0.05% cyclosporine A versus the control group (P = .026). At 1 month of follow-up, NIBUT, LLT, and TMH values significantly decreased in both groups compared to baseline (P < .05). The 0.05% cyclosporine A group exhibited higher NIBUT, LLT, and TMH versus the control group, returning to preoperative values after 2 months. Overall, the OSDI total score and NIBUT values during follow-up were not significantly different between the two groups; however, the LLT and TMH values were significantly different between the two groups (P < .001 and .041, respectively) by repeated measures analysis of variance. CONCLUSIONS: Topical 0.05% cyclosporine A was effective in relieving subjective dry eye symptoms and maintaining ocular surface stability in the early postoperative period of SMILE. [J Refract Surg. 2024;40(4):e229-e238.].

Perception-oriented generative adversarial network for retinal fundus image super-resolution.

Retinal fundus imaging is a crucial diagnostic tool in ophthalmology, enabling the early detection and monitoring of various ocular diseases. However, capturing high-resolution fundus images often presents challenges due to factors such as defocusing and diffraction in the digital imaging process, limited shutter speed, sensor unit density, and random noise in the image sensor or during image transmission. Super-resolution techniques offer a promising solution to overcome these limitations and enhance the visual details in retinal fundus images. Since the retina has rich texture details, the super-resolution images often introduce artifacts into texture details and lose some fine retinal vessel structures. To improve the perceptual quality of the retinal fundus image, a generative adversarial network that consists of a generator and a discriminator is proposed. The proposed generator mainly comprises 23 multi-scale feature extraction blocks, an image segmentation network, and 23 residual-in-residual dense blocks. These components are employed to extract features at different scales, acquire the retinal vessel grayscale image, and extract retinal vascular features, respectively. The generator has two branches that are mainly responsible for extracting global features and vascular features, respectively. The extracted features from the two branches are fused to better restore the super-resolution image. The proposed generator can restore more details and more accurate fine vessel structures in retinal images. The improved discriminator is proposed by introducing our designed attention modules to help the generator yield clearer super-resolution images. Additionally, an artifact loss function is also introduced to enhance the generative adversarial network, enabling more accurate measurement of the disparity between the high-resolution image and the restored image. Experimental results show that the generated images obtained by our proposed method have a better perceptual quality than the state-of-the-art image super-resolution methods.

Remote Sensing Image Dehazing through an Unsupervised Generative Adversarial Network.

The degradation of visual quality in remote sensing images caused by haze presents significant challenges in interpreting and extracting essential information. To effectively mitigate the impact of haze on image quality, we propose an unsupervised generative adversarial network specifically designed for remote sensing image dehazing. This network includes two generators with identical structures and two discriminators with identical structures. One generator is focused on image dehazing, while the other generates images with added haze. The two discriminators are responsible for distinguishing whether an image is real or generated. The generator, employing an encoder-decoder architecture, is designed based on the proposed multi-scale feature-extraction modules and attention modules. The proposed multi-scale feature-extraction module, comprising three distinct branches, aims to extract features with varying receptive fields. Each branch comprises dilated convolutions and attention modules. The proposed attention module includes both channel and spatial attention components. It guides the feature-extraction network to emphasize haze and texture within the remote sensing image. For enhanced generator performance, a multi-scale discriminator is also designed with three branches. Furthermore, an improved loss function is introduced by incorporating color-constancy loss into the conventional loss framework. In comparison to state-of-the-art methods, the proposed approach achieves the highest peak signal-to-noise ratio and structural similarity index metrics. These results convincingly demonstrate the superior performance of the proposed method in effectively removing haze from remote sensing images.

Unsupervised Low-Light Image Enhancement Based on Generative Adversarial Network.

Low-light image enhancement aims to improve the perceptual quality of images captured under low-light conditions. This paper proposes a novel generative adversarial network to enhance low-light image quality. Firstly, it designs a generator consisting of residual modules with hybrid attention modules and parallel dilated convolution modules. The residual module is designed to prevent gradient explosion during training and to avoid feature information loss. The hybrid attention module is designed to make the network pay more attention to useful features. A parallel dilated convolution module is designed to increase the receptive field and capture multi-scale information. Additionally, a skip connection is utilized to fuse shallow features with deep features to extract more effective features. Secondly, a discriminator is designed to improve the discrimination ability. Finally, an improved loss function is proposed by incorporating pixel loss to effectively recover detailed information. The proposed method demonstrates superior performance in enhancing low-light images compared to seven other methods.

Quantitative changes in iris and retinal blood flow after femtosecond laser-assisted in situ keratomileusis and small-incision lenticule extraction.

Purpose: To investigate the quantitative changes in iris and retinal blood flow indices after femtosecond laser-assisted in situ keratomileusis (FS-LASIK) and small-incision lenticule extraction (SMILE). Methods: Seventy-nine patients who underwent FS-LASIK or SMILE were enrolled between July 2020 and September 2020. Participants were followed-up 1 day pre-operatively and 1 week, 1 month, 3 months post-operatively. Optical coherence tomography angiography (OCTA) was used to acquire and quantify the iris and retinal blood flow indices. Results: The iris vessel area density (VAD) and vessel skeleton density (VSD) decreased on post-operative day 1 but recovered on day 7. In both cases, the pupil diameter was positively associated with the post-operative iris blood flow indices (p = 0.0013, p = 0.0002). The retinal VAD and VSD in the superficial and deep capillary plexuses decreased after surgery and failed to recover after 90 days. The SMILE group showed significantly lower iris and retinal blood flow indices than the FS-LASIK group. For both procedures, axial length (p = 0.0345, p = 0.0499), spherical equivalence (p = 0.0063, p = 0.0070), and suction duration (p = 0.0025, p = 0.0130) were negatively correlated with the post-operative VAD and VSD. Conclusions: The SMILE and FS-LASIK procedures induced a short-term decrease in the iris and retinal blood flow indices, although patients finally showed full visual recovery. This phenomenon should be carefully considered, especially in patients prone to anterior segment lesions.

A lightweight deep neural network with higher accuracy.

To improve accuracy of the MobileNet network, a new lightweight deep neural network is designed based on the MobileNetV2 network. Firstly, it modifies the network depth of MobileNetV2 to balance the image resolution, network width and depth to keep the gradient stable, which reduces the generation of gradient vanishing or gradient exploding. Secondly, it proposes an improved Bottleneck module by introducing channel attention mechanism. It assigns different weights for different channels according to the degree of relevance between the object features and channels. Therefore, the network can extract more effective features from a complex background. In the end, a new usage strategy of the improved Bottleneck is proposed. It uses the improved Bottleneck module in the second, fourth and fifth stages of MobileNetV2, and uses the original Bottleneck module in other states. Compared with MobileNetV2, MobileNetV3, ShuffleNetV2, GhostNet and HBONetmethods, the proposed method has the highest classification accuracy on the ImageNet-1K dataset, CIFAR-10 and CIFAR-100. Compared with YOLOV4-Lite methods based on these lightweight network networks, YOLOV4-Lite based on our proposed network also has the highest detection accuracy on the PASCAL VOC07+12 dataset.

Dimensionality Reduction of Single-Cell RNA Sequencing Data by Combining Entropy and Denoising AutoEncoder.

ABSTRACT Single-cell RNA sequencing (scRNA-seq) can present cellular heterogeneity at higher resolution when measuring the gene expression in an individual cell. However, there are still some computational problems in scRNA-seq data, including high dimensionality, high sparseness, and high noise. To solve them, dimensionality reduction is essential as it reduces dimensions and also removes most of the zeros and noise. Therefore, we propose a hybrid dimensionality reduction algorithm for scRNA-seq data by integrating binning-based entropy and a denoising autoencoder, named ScEDA. In ScEDA, a novel binning-based entropy estimation method is performed to select efficient genes, while removing noise. For each gene, binning-based entropy is designed to describe the differences in its expression across all cells, that is, the distribution of expression of each gene in all cells. Genes are regarded as inefficient and removed when they achieve low binning-based entropy. Moreover, by combining Kullback-Leibler (KL) divergence with the autoencoder, the objective function is reconstructed to maximize the similarity in distribution between input data and reconstructed data. Furthermore, by adding Poisson-distributed noise to the original input data, the denoising autoencoder is used to improve robustness. Compared with three other clustering methods, ScEDA provides superior average performance on 16 real scRNA-seq datasets, with obvious enhancement in large-scale datasets.

Quantitative changes in iris vasculature and blood flow in patients with different refractive errors.

PURPOSE: To evaluate the association between microvascular changes in the iris and refractive errors. METHODS: A cross-sectional case study. Seventy eyes from 70 patients with refractive errors were enrolled. Iris microvasculature was analyzed using optical coherence tomography angiography (OCTA). We divided the iris images into three regions and calculated the vessel area density (VAD) and vessel skeleton density (VSD) of the inner one-third, inner two-thirds, and the entirety of the iris. RESULTS: The VADs and VSDs of the different regions were significantly different. The VAD and VSD of the inner one-third of the iris were higher than those of the other regions. The iris blood vessels were denser near the pupil margin, and blood vessels from the iris root to the pupil edge were radially distributed. The VAD and VSD of patients with mild hyperopia and emmetropia were higher than those of patients with moderate and high myopia. As the spherical equivalent increased, the VAD and VSD of the iris increased. Neither age nor sex contributed to significant differences in VAD and VSD. CONCLUSION: Quantitative changes in iris microvasculature may indicate the development of myopia.

Intravenous glucocorticoids therapy in the treatment of Graves' ophthalmopathy: a systematic review and Meta-analysis.

AIM: To evaluate the benefit and harms of high-dose intravenous glucocorticoids (IVGC) as first-line treatment for Graves' ophthalmopathy (GO). METHODS: A systematic review and Meta-analysis of randomized clinical trials (RCTs) comparing IVGC for the treatment of GO, with placebo or other treatments, were conducted. Electronic databases were searched, and standard methodological guidance of Cochrane Handbook for Systematic Reviews of Interventions was used. The primary outcome was overall response, and secondary outcomes included the improvement and change in clinical activity score (CAS), and adverse events. RESULTS: Ten RCTs were included in the Meta-analysis. Low quality evidence (one trial) showed that participants receiving IVGC achieved significantly higher response compared to participants receiving placebo [risk ratio (RR) 7.50, 95% confidence interval (CI) 1.14 to 49.26]. Moderate quality evidence (four trials) support appreciable benefit of IVGC in response compared with oral glucocorticoids (OGC), with of RR being 1.51 (95%CI 1.25 to 1.83). There was low quality evidence (one trial) compatible with appreciable benefit for IVGC plus orbital radiotherapy in response (RR 1.38, 95%CI 1.07 to 1.79), compared with OGC plus orbital radiotherapy. One IVGC versus rituximab trial provided moderate quality evidence suggesting that participants using IVGC achieved significantly lower response compared to participants using rituximab (RR 0.70, 95%CI 0.50 to 0.98). One IVGC versus mycophenolate mofetil (MMF) trial provided moderate quality evidence suggesting that participants using IVGC achieved significantly lower response compared to participants using MMF (RR 0.74, 95%CI 0.63 to 0.88). Very low quality evidence (one trial) showed that participants with dysthyroid optic neuropathy (DON) receiving IVGC were more likely to achieve response compared to participants receiving orbital decompression (RR 3.33, 95%CI 0.51 to 21.89). CONCLUSION: The current evidence is moderate quality, which is sufficient to support IVGC to be as the first-line treatment for moderate-to-severe GO, and the use of rituximab or MMF to be the second-line treatment instead of IVGC. However, the evidence is very low quality, which is insufficient to support the use of IVGC or orbital decompression as the first-line treatment of DON.

A Systematic Review and Meta-Analysis of Clinical Outcomes of Intravitreal Anti-VEGF Agent Treatment Immediately after Cataract Surgery for Patients with Diabetic Retinopathy.

AIMS: To examine possible benefits of intravitreal anti-vascular endothelial growth factor (VEGF) agent treatment immediately after cataract surgery for patients with diabetic retinopathy (DR). METHODS: A comprehensive literature search was performed using the Cochrane collaboration methodology to identify randomized controlled trials (RCTs) and comparative studies of cataract surgery with or without anti-VEGF agent treatment for any diabetic retinopathy. Meta-analyses were performed for clinical outcome parameters including changes in macular thickness (MT), best-corrected visual acuity (BCVA), incidence of diabetic retinopathy and maculopathy progression, laser treatment rate, and other complications. RESULTS: Nine RCTs and 3 nonrandomized comparative studies were identified and used for comparing cataract surgery with intravitreal bevacizumab (IVB) or intravitreal ranibizumab (IVR) treatment (338 eyes, intervention group) to cataract surgery alone (329 eyes, control group). Analysis of all data showed that the mean BCVA at 1 week postoperatively had no statistically significant difference in the two groups, but at 1, 3, and 6 months postoperatively, the mean BCVA was statistically significantly better in the anti-VEGF treatment group than that in cataract surgery alone group. Analysis of all data showed that the mean MT was statistically significantly less in the anti-VEGF treatment group at 1 week and 1, 3, and 6 months postoperatively (P=0.05, P=0.006, P=0.0001, and P=0.0001, respectively); but postoperative clinical outcomes were differentiated from the type of anti-VEGF agents, IVB or IVR, and the existing macular edema preoperatively. Intravitreal anti-VEGF agent treatment statistically significantly reduced the incidence of diabetic retinopathy progression and maculopathy progression compared to the control group (P=0.0003, P < 0.00001, respectively). CONCLUSION: IVB or IVR treatment immediately after cataract surgery may represent a safe and effective strategy to prevent postoperative macular thickening or reduce macular edema and result in greater mean improvements in visual acuity for diabetic patients.

A Weak Selection Stochastic Gradient Matching Pursuit Algorithm.

In the existing stochastic gradient matching pursuit algorithm, the preliminary atomic set includes atoms that do not fully match the original signal. This weakens the reconstruction capability and increases the computational complexity. To solve these two problems, a new method is proposed. Firstly, a weak selection threshold method is proposed to select the atoms that best match the original signal. If the absolute gradient coefficients were greater than the product of the maximum absolute gradient coefficient and the threshold that was set according to the experiments, then we selected the atoms that corresponded to the absolute gradient coefficients as the preliminary atoms. Secondly, if the scale of the current candidate atomic set was equal to the previous support atomic set, then the loop was exited; otherwise, the loop was continued. Finally, before the transition estimation of the original signal was calculated, we determined whether the number of columns of the candidate atomic set was smaller than the number of rows of the measurement matrix. If this condition was satisfied, then the current candidate atomic set could be regarded as the support atomic set and the loop was continued; otherwise, the loop was exited. The simulation results showed that the proposed method has better reconstruction performance than the stochastic gradient algorithms when the original signals were a one-dimensional sparse signal, a two-dimensional image signal, and a low-rank matrix signal.

Bandage Contact Lens Application Reduces Fibrotic Wound Healing of Flap Margins after FS-LASIK: A Prospective Randomized Clinical Trial.

PURPOSE: To assess the efficacy of applying bandage contact lens (BCL) in reducing the fibrotic healing response of flap margins following femtosecond laser in situ keratomileusis (FS-LASIK). METHODS: In this prospective, randomized, interventional, observer-masked trial, 41 patients (82 eyes) with myopia and/or myopic astigmatism were scheduled to undergo FS-LASIK. After surgery, patients were fitted with a BCL in one eye (BCL eyes, n=41) but not in the contralateral eye (control eyes, n=41), following randomized allocation of the BCL to the left or right eye of each patient. The BCL was left in place overnight and removed the following morning. All eyes subsequently received standardized postoperative treatments. Patients were followed up for 6 months. We evaluated patients' self-reported postoperative symptom scores for pain, photophobia, tearing, and foreign-body sensation. At 6 months after surgery, we examined the corneal flap margin and adjacent regions, and photographed them using slit-lamp biomicroscopy, to subjectively evaluate the wound healing response. RESULTS: Postoperative pain and photophobia were milder in the BCL group than in the control group (P=0.041 and P=0.003, respectively), but patients felt more foreign-body sensation in the eye with a BCL than in the control eye (P=0.001). There was no significant difference in tearing score between BCL eyes and control eyes (P=0.118). Regarding the fibrotic healing response of the flap margin, control eyes showed a wide, bright peripheral circumferential band with a spiculated edge and high reflectivity; conversely, BCL eyes showed a markedly narrower and smoother peripheral circumferential band, with a less spiculated edge and lower reflectivity (P < 0.001). CONCLUSION: Patients felt less discomfort in eyes treated with a BCL after FS-LASIK than in control eyes. BCL-treated eyes also had a less intense wound healing response at the flap margins than control eyes in some of patients. BCLs may merit consideration as a treatment option after FS-LASIK for special patients. This trial is registered with ChiCTR1800016579.

Laser-Assisted Subepithelial Keratectomy versus Laser In Situ Keratomileusis in Myopia: A Systematic Review and Meta-Analysis.

This systematic review was to compare the clinical outcomes between laser-assisted subepithelial keratectomy (LASEK) and laser in situ keratomileusis (LASIK) for myopia. Primary parameters included mean manifest refraction spherical equivalent (MRSE), MRSE within ±0.50 diopters, uncorrected visual acuity (UCVA) ≥20/20, and loss of ≥1 line of best-corrected visual acuity (BCVA). Secondary parameters included flap complications and corneal haze. Twelve clinical controlled trials were identified and used for comparing LASEK (780 eyes) to LASIK (915 eyes). There were no significant differences in visual and refractive outcomes between the two surgeries for low to moderate myopia. The incidence of loss of ≥1 line of BCVA was significantly higher in moderate to high myopia treated by LASEK than LASIK in the mid-term and long-term followup. The efficacy (MRSE and UCVA) of LASEK appeared to be a significant worsening trend in the long-term followup. Corneal haze was more severe in moderate to high myopia treated by LASEK than LASIK in the mid-term and long-term followup. The flap-related complications still occurred in LASIK, but the incidence was not significantly higher than that in LASEK. LASEK and LASIK were safe and effective for low to moderate myopia. The advantage of LASEK was the absence of flap-related complications, and such procedure complication may occur in LASIK and affect the visual results. The increased incidence of stromal haze and regression in LASEK significantly affected the visual and refractive results for high myopia.

Excimer laser phototherapeutic keratectomy for the treatment of clinically presumed fungal keratitis.

This retrospective study was to evaluate treatment outcomes of excimer laser phototherapeutic keratectomy (PTK) for clinically presumed fungal keratitis. Forty-seven eyes of 47 consecutive patients underwent manual superficial debridement and PTK. All corneal lesions were located in the anterior stroma and were resistant to medication therapy for at least one week. Data were collected by a retrospective chart review with at least six months of follow-up data available. After PTK, infected corneal lesions were completely removed and the clinical symptoms resolved in 41 cases (87.2%). The mean ablation depth was 114.39 ± 45.51 µ m and diameter of ablation was 4.06 ± 1.07 mm. The mean time for healing of the epithelial defect was 8.8 ± 5.6 days. Thirty-four eyes (82.9%) showed an improvement in best spectacle-corrected visual acuity of two or more lines. PTK complications included mild to moderate corneal haze, hyperopic shift, irregular astigmatism, and thinning cornea. Six eyes (12.8%) still showed progressed infection, and conjunctival flap covering, amniotic membrane transplantation, or penetrating keratoplasty were given. PTK is a valuable therapeutic alternative for superficial infectious keratitis. It can effectively eradicate lesions, hasten reepithelialization, and restore and preserve useful visual function. However, the selection of surgery candidates should be conducted carefully.

The effect of multivitamin/mineral supplements on age-related cataracts: a systematic review and meta-analysis.

Antioxidant vitamins supplements have been suggested as a strategy to decrease the risk of age-related cataract development. However, the results from observational studies and interventional trials of associations between antioxidant vitamins A, C, and E and cataract development have been inconsistent. We aim to evaluate the effectiveness of multivitamin/mineral supplements for decreasing the risk of age-related cataracts by conducting a systematic review and meta-analysis. In September 2013, we searched multiple databases to identify relevant studies including both cohort studies and randomized controlled trials (RCTs). A random-effects model was used to calculate the pooled relative risks (RR) with a 95% confidence interval (CI). Twelve prospective cohort studies and two RCTs were included. Pooled results from the cohort studies indicated that multivitamin/mineral supplements have a significant beneficial effect in decreasing the risk of nuclear cataracts (RR: 0.73; 95% CI: 0.64-0.82), cortical cataracts (RR: 0.81; 95% CI: 0.68-0.94), and any cataracts (RR: 0.66; 95% CI: 0.39-0.93). In addition, there were no decreases in the risk of posterior capsular cataracts (RR: 0.96; 95% CI: 0.72-1.20) or cataract surgery (RR: 1.00; 95% CI: 0.92-1.08). The two RCTs demonstrated that multivitamin/mineral supplements could decrease the risk of nuclear cataracts. There is sufficient evidence to support the role of dietary multivitamin/mineral supplements for the decreasing the risk of age-related cataracts.

High prevalence of myopia and high myopia in 5060 Chinese university students in Shanghai.

PURPOSE: Myopia is an important cause of correctable visual impairment worldwide. Genetic and environmental factors contribute to its development. The population of Chinese university students consists of approximately 30 million young people characterized by academic excellence and similar ages. To date, little is known about their refractive status. Our study is designed to investigate the prevalence of myopia in this specific population. METHODS: This is a cross-sectional study of myopia among university students in Shanghai, China; 5083 students from Donghua University were enrolled. All participants first responded to a detailed questionnaire, including questions on ethnicity, birth date, and family history, and then undertook a standardized ophthalmologic examination, including visual acuity, a slit-lamp examination, and non-cycloplegic autorefraction. RESULTS: The mean spherical equivalent refraction (SER) of the university students was -4.1 diopters (D). Of the subjects 95.5% were myopic (SER < -0.50 D), 19.5% were highly myopic (SER < -6.0 D), and only 3.3% were emmetropic (-0.5 D ≤ SER ≤ 0.5 D). The postgraduates were more myopic than the undergraduates (96.9% and 94.9%, respectively). Being female (-4.1 ± 2.4 D in female versus -3.8 ± 2.4 D in male subjects), of Han ethnicity (-4.1 ± 2.4 D in Han versus -3.4 ± 2.2 D in minorities), and of older age were associated with a higher probability of myopia only in the undergraduate population. CONCLUSIONS: The prevalence of myopia and high myopia in this university student population was high. The refractive status of this population deserves further attention.