Burden of visual impairment in mainland China: the Handan Eye Study and Beijing Eye Study.

PURPOSE: To determine the impact of visual impairment (VI) on health-related quality of life (HRQoL) and to compare the health burden of VI in different areas in mainland China. METHODS: A cohort of 6830 people from rural villages and a cohort of 3251 people from an urban city were included to receive comprehensive ophthalmologic examinations and complete the European Quality of Life-5 Dimensions 3 Levels (EQ-5D-3L) questionnaire. For urban and rural populations, a unified VI grouping standard was adopted: the eyes were classified into normal group, mild-moderate group, and severe group according to WHO standards, and then divided into 6 groups considering both eyes. We estimated the effects of VI on the EQ-5D index score using linear regression models and the association between VI and self-reported EQ-5D health problems using logistic regression models. Associations were assessed by the Spearman correlation coefficient. RESULTS: The prevalence of VI and the index scores of EQ-5D-3L for each subgroup of VI were higher for the rural cohort. In these two cohorts, the severity of VI in rural population (Spearman r = 0.205; p < 0.0001) and urban population (Spearman r = 0.164; p < 0.0001) is correlated with the EQ-5D index score. In the rural cohort, the difference in index scores with bilateral severe VI compared to those without VI, after adjusting for covariates, was - 0.053 for the rural cohort and - 0.084 for the urban cohort, respectively. In the rural cohort, the odds ratio for bilateral severe VI was 4.39 for mobility, 6.33 for self-care, and 5.88 for usual activities. The incidence of anxiety or depression and pain or discomfort in the urban cohort was greater; the OR for bilateral severe VI in the urban cohort was 4.75. CONCLUSIONS: VI has a negative impact on HRQoL in the rural and urban areas of China, especially in urban population. It is also more likely to cause anxiety or depression among the urban cohort, which deserves special attention.

Integrating Clinical Data and Radiomics and Deep Learning Features for End-to-End Delayed Cerebral Ischemia Prediction on Noncontrast CT.

BACKGROUND AND PURPOSE: Delayed cerebral ischemia is hard to diagnose early due to gradual, symptomless development. This study aimed to develop an automated model for predicting delayed cerebral ischemia following aneurysmal SAH on NCCT. MATERIALS AND METHODS: This retrospective study included 400 patients with aneurysmal SAH (156 with delayed cerebral ischemia) who underwent NCCT. The study used ATT-Deeplabv3+ for automatically segmenting hemorrhagic regions using semisupervised learning. Principal component analysis was used for reducing the dimensionality of deep learning features extracted from the average pooling layer of ATT-DeepLabv3+. The classification model integrated clinical data, radiomics, and deep learning features to predict delayed cerebral ischemia. Feature selection involved Pearson correlation coefficients, least absolute shrinkage, and selection operator regression. We developed models based on clinical features, clinical-radiomics, and a combination of clinical, radiomics, and deep learning. The study selected logistic regression, Naive Bayes, Adaptive Boosting (AdaBoost), and multilayer perceptron as classifiers. The performance of segmentation and classification models was evaluated on their testing sets using the Dice similarity coefficient for segmentation, and the area under the receiver operating characteristic curve (AUC) and calibration curves for classification. RESULTS: The segmentation process achieved a Dice similarity coefficient of 0.91 and the average time of 0.037 s/image. Seventeen features were selected to calculate the radiomics score. The clinical-radiomics-deep learning model with multilayer perceptron achieved the highest AUC of 0.84 (95% CI, 0.72-0.97), which outperformed the clinical-radiomics model (P = .002) and the clinical features model (P = .001) with multilayer perceptron. The performance of clinical-radiomics-deep learning model using AdaBoost was significantly superior to its clinical-radiomics model (P = .027). The performance of the clinical-radiomics-deep learning model and the clinical-radiomics model with logistic regression notably exceeded that of the model based solely on clinical features (P = .028; P = .046). The AUC of the clinical-radiomics-deep learning model with multilayer perceptron (P < .001) and the clinical-radiomics model with logistic regression (P = .046) were significantly higher than the clinical model with logistic regression. Of all models, the clinical-radiomics-deep learning model with multilayer perceptron showed best calibration. CONCLUSIONS: The proposed 2-stage end-to-end model not only achieves rapid and accurate segmentation but also demonstrates superior diagnostic performance with high AUC values and good calibration in the clinical-radiomics-deep learning model, suggesting its potential to enhance delayed cerebral ischemia detection and treatment strategies.

Prevalence of cataract and cataract surgery in urban and rural Chinese populations over 50 years old: a systematic review and Meta-analysis.

AIM: To summarize the data of epidemiological studies on cataract prevalence over 50 years old in urban and rural areas of China from 2000 to 2020, and to analyze the prevalence of cataract and operation rate in China. METHODS: By searching PubMed, EMBASE, Web of Science, Wanfang Data and CNKI, Chinese and English literatures on the prevalence of cataract in China were retrieved, and the relevant characteristic data were extracted. Then, Stata v15SE software was used for Meta-analysis and heterogeneity test. According to the results of heterogeneity, the corresponding effect models were selected to combine the extracted data. RESULTS: A total of 20 studies were included in this study, with a total of 111 434 cases. Meta-analysis showed heterogeneity. According to the random effect model, the overall prevalence of cataract in Chinese people over 50 years old was 27.45%, that in rural was 28.79%, and that in urban was 26.66%. The overall coverage rate of cataract surgery was 9.19%. CONCLUSION: The prevalence of cataract is high in China, and there is still room for improvement in surgical coverage, so it is very important to promote cataract screening and prevention.

A Temporal Signal-Processing Circuit Based on Spiking Neuron and Synaptic Learning.

Time is a continuous, homogeneous, one-way, and independent signal that cannot be modified by human will. The mechanism of how the brain processes temporal information remains elusive. According to previous work, time-keeping in medial premotor cortex (MPC) is governed by four kinds of ramp cell populations (Merchant et al., 2011). We believe that these cell populations participate in temporal information processing in MPC. Hence, in this the present study, we present a model that uses spiking neuron, including these cell populations, to construct a complete circuit for temporal processing. By combining the time-adaptive drift-diffusion model (TDDM) with the transmission of impulse information between neurons, this new model is able to successfully reproduce the result of synchronization-continuation tapping task (SCT). We also discovered that the neurons that we used exhibited some of the firing properties of time-related neurons detected by electrophysiological experiments in other studies. Therefore, we believe that our model reflects many of the physiological of neural circuits in the biological brain and can explain some of the phenomena in the temporal-perception process.

Kinetics and model development of iohexol degradation during UV/H2O2 and UV/S2O82- oxidation.

The degradation rates and kinetics of one commonly used iodinated contrast medium, iohexol, were investigated and compared during ultraviolet (UV) photolysis, UV/H2O2 and UV/S2O82- advanced oxidation processes (AOPs). Results indicate that the iohexol degradation rate increased in the order of UV/H2O2 < UV irradiation < UV/S2O82- and followed pseudo-first-order kinetics. Increasing persulfate concentration significantly increased iohexol degradation rate, whereas increasing H2O2 concentration caused reverse effect. Radical scavenging test results show that UV photolysis, OH and radicals all contributed to iohexol degradation during UV/S2O82-, but OH was the main contributor during UV/H2O2 and was consumed by excess H2O2. The kinetic models of iohexol degradation by both AOPs were developed, and the reaction rate constants with OH and were calculated as 5.73 (±0.02) × 108 and 3.91 (±0.01) × 1010 M-1 s-1, respectively. Iohexol degradation rate remained stable at pH 5-9 during UV irradiation and UV/H2O2, but gradually decreased at pH 5-7 and remained stable at pH 7-9 during UV/S2O82-. The presence of anions displayed inhibitory effects on iohexol degradation during UV/S2O82- in the order of Cl- >HCO3- ≫ SO42-. UV/S2O82- AOP exhibited high degradation efficiency and stability on the basis of UV irradiation, which can be applied as a promising degradation method for iohexol. UV/S2O82- AOP can effectively mineralize iohexol to CO2 but promoted the generation of toxic iodoform (CHI3), and the subsequent chlorination had the potential to reduce the content of disinfection by-products; therefore, further evaluation of possible environmental hazards is warranted.