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

The mutation rate is a pivotal biological characteristic, intricately governed by natural selection and historically garnering considerable attention. Recent advances in high-throughput sequencing and analytical methodologies have profoundly transformed our understanding in this domain, ushering in an unprecedented era of mutation rate research. This paper aims to provide a comprehensive overview of the key concepts and methodologies frequently employed in the study of mutation rates. It examines various types of mutations, explores the evolutionary dynamics and associated theories, and synthesizes both classical and contemporary hypotheses. Furthermore, this review comprehensively explores recent advances in understanding germline and somatic mutations in animals and offers an overview of experimental methodologies, mutational patterns, molecular mechanisms, and driving forces influencing variations in mutation rates across species and tissues. Finally, it proposes several potential research directions and pressing questions for future investigations.

AIM: To evaluate the application of an intelligent diagnostic model for pterygium. METHODS: For intelligent diagnosis of pterygium, the attention mechanisms—SENet, ECANet, CBAM, and Self-Attention—were fused with the lightweight MobileNetV2 model structure to construct a tri-classification model. The study used 1220 images of three types of anterior ocular segments of the pterygium provided by the Eye Hospital of Nanjing Medical University. Conventional classification models—VGG16, ResNet50, MobileNetV2, and EfficientNetB7—were trained on the same dataset for comparison. To evaluate model performance in terms of accuracy, Kappa value, test time, sensitivity, specificity, the area under curve (AUC), and visual heat map, 470 test images of the anterior segment of the pterygium were used. RESULTS: The accuracy of the MobileNetV2+Self-Attention model with 281 MB in model size was 92.77%, and the Kappa value of the model was 88.92%. The testing time using the model was 9ms/image in the server and 138ms/image in the local computer. The sensitivity, specificity, and AUC for the diagnosis of pterygium using normal anterior segment images were 99.47%, 100%, and 100%, respectively; using anterior segment images in the observation period were 88.30%, 95.32%, and 96.70%, respectively; and using the anterior segment images in the surgery period were 88.18%, 94.44%, and 97.30%, respectively. CONCLUSION: The developed model is lightweight and can be used not only for detection but also for assessing the severity of pterygium.

AIM: To examine the regulatory role of microRNA-204 (miR-204) on silent information regulator 1 (SIRT1) and vascular endothelial growth factor (VEGF) under high-glucose-induced metabolic memory in human retinal pigment epithelial (hRPE) cells. METHODS: Cells were cultured with either normal (5 mmol/L) or high D-glucose (25 mmol/L) concentrations for 8d to establish control and high-glucose groups, respectively. To induce metabolic memory, cells were cultured with 25 mmol/L D-glucose for 4d followed by culture with 5 mmol/L D-glucose for 4d. In addition, exposed in 25 mmol/L D-glucose for 4d and then transfected with 100 nmol/L miR-204 control, miR-204 inhibitor or miR-204 mimic in 5 mmol/L D-glucose for 4d. Quantitative reverse transcription-polymerase chain reaction (RT-qPCR) was used to detect miR-204 mRNA levels. SIRT1 and VEGF protein levels were assessed by immunohistochemical and Western blot. Flow cytometry was used to investigate apoptosis rate. RESULTS: It was found that high glucose promoted miR-204 and VEGF expression, and inhibited SIRT1 activity, even after the return to normal glucose culture conditions. Upregulation of miR-204 promoted apoptosis inhibiting SIRT1 and increasing VEGF expression. However, downregulation of miR-204 produced the opposite effects. CONCLUSION: The study identifies that miR-204 is the upstream target of SIRT1and VEGF, and that miR-204 can protect hRPE cells from the damage caused by metabolic memory through increasing SIRT1 and inhibiting VEGF expression.