Epidemiologic association and shared genetic architecture between cataract and hearing difficulties among middle-aged and older adults.

Age-related cataract and hearing difficulties are major sensory disorders that often co-exist in the global-wide elderly and have a tangible influence on the quality of life. However, the epidemiologic association between cataract and hearing difficulties remains unexplored, while little is known about whether the two share their genetic etiology. We first investigated the clinical association between cataract and hearing difficulties using the UK Biobank covering 502,543 individuals. Both unmatched analysis (adjusted for confounders) and a matched analysis (one control matched for each patient with cataract according to confounding factors) were undertaken and confirmed that cataract was associated with hearing difficulties (OR, 2.12; 95% CI, 1.98-2.27; OR, 2.03; 95% CI, 1.86-2.23, respectively). Furthermore, we explored and quantified the shared genetic architecture of these two complex sensory disorders at the common variant level using the bivariate causal mixture model (MiXeR) and conditional/conjunctional false discovery rate method based on the largest available genome-wide association studies of cataract (N = 585,243) and hearing difficulties (N = 323,978). Despite detecting only a negligible genetic correlation, we observe polygenic overlap between cataract and hearing difficulties and identify 6 shared loci with mixed directions of effects. Follow-up analysis of the shared loci implicates candidate genes QKI, STK17A, TYR, NSF, and TCF4 likely contribute to the pathophysiology of cataracts and hearing difficulties. In conclusion, this study demonstrates the presence of epidemiologic association between cataract and hearing difficulties and provides new insights into the shared genetic architecture of these two disorders at the common variant level.

Plasma Proteomics to Identify Drug Targets and Potential Drugs for Retinal Artery Occlusion: An Integrated Analysis in the UK Biobank.

Retinal artery occlusion (RAO), which is positively correlated with acute ischemic stroke (IS) and results in severe visual impairment, lacks effective intervention drugs. This study aims to perform integrated analysis using UK Biobank plasma proteome data of RAO and IS to identify potential targets and preventive drugs. A total of 7191 participants (22 RAO patients, 1457 IS patients, 8 individuals with both RAO and IS, and 5704 healthy age-gender-matched controls) were included in this study. Unique 1461 protein expression profiles of RAO, IS, and the combined data set, extracted from UK Biobank Plasma proteomics projects, were analyzed using both differential expression analysis and elastic network regression (Enet) methods to identify shared key proteins. Subsequent analyses, including single cell type expression assessment, pathway enrichment, and druggability analysis, were conducted for verifying shared key proteins and discovery of new drugs. Five proteins were found to be shared among the samples, with all of them showing upregulation. Notably, adhesion G-protein coupled receptor G1 (ADGRG1) exhibited high expression in glial cells of the brain and eye tissues. Gene set enrichment analysis revealed pathways associated with lipid metabolism and vascular regulation and inflammation. Druggability analysis unveiled 15 drug candidates targeting ADGRG1, which demonstrated protective effects against RAO, especially troglitazone (-8.5 kcal/mol). Our study identified novel risk proteins and therapeutic drugs associated with the rare disease RAO, providing valuable insights into potential intervention strategies.

EBD: an eye biomarker database.

MOTIVATION: Many ophthalmic disease biomarkers have been identified through comprehensive multiomics profiling, and hold significant potential in advancing the diagnosis, prognosis, and management of diseases. Meanwhile, the eye itself serves as a natural biomarker for several systemic diseases including neurological, renal, and cardiovascular systems. We aimed to collect and standardize this eye biomarkers information and construct the eye biomarker database (EBD) to provide ophthalmologists with a platform to search, analyze, and download these eye biomarker data. RESULTS: In this study, we present the EBD , a world-first online compilation comprising 889 biomarkers for 26 ocular diseases and 939 eye biomarkers for 181 systemic diseases. The EBD also includes the information of 78 "nonbiomarkers"-the objects that have been proven cannot be biomarkers. Biological function and network analysis were conducted for these ocular disease biomarkers, and several hub pathways and common network topology characteristics were newly identified, which may promote future ocular disease biomarker discovery and characterizes the landscape of biomarkers for eye diseases at the pathway and network level. The EBD is expected to yield broader utility among developmental biologists and clinical scientists in and outside of the eye field by assisting in the identification of biomarkers linked to eye disorders and related systemic diseases. AVAILABILITY AND IMPLEMENTATION: EBD is available at http://www.eyeseeworld.com/ebd/index.html.

Development and validation of a simple and practical model for early detection of diabetic macular edema in patients with type 2 diabetes mellitus using easily accessible systemic variables.

OBJECTIVE: Diabetic macular edema (DME) is the leading cause of visual impairment in patients with diabetes mellitus (DM). The goal of early detection has not yet achieved due to a lack of fast and convenient methods. Therefore, we aim to develop and validate a prediction model to identify DME in patients with type 2 diabetes mellitus (T2DM) using easily accessible systemic variables, which can be applied to an ophthalmologist-independent scenario. METHODS: In this four-center, observational study, a total of 1994 T2DM patients who underwent routine diabetic retinopathy screening were enrolled, and their information on ophthalmic and systemic conditions was collected. Forward stepwise multivariable logistic regression was performed to identify risk factors of DME. Machine learning and MLR (multivariable logistic regression) were both used to establish prediction models. The prediction models were trained with 1300 patients and prospectively validated with 104 patients from Guangdong Provincial People's Hospital (GDPH). A total of 175 patients from Zhujiang Hospital (ZJH), 115 patients from the First Affiliated Hospital of Kunming Medical University (FAHKMU), and 100 patients from People's Hospital of JiangMen (PHJM) were used as external validation sets. Area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity, and specificity were used to evaluate the performance in DME prediction. RESULTS: The risk of DME was significantly associated with duration of DM, diastolic blood pressure, hematocrit, glycosylated hemoglobin, and urine albumin-to-creatinine ratio stage. The MLR model using these five risk factors was selected as the final prediction model due to its better performance than the machine learning models using all variables. The AUC, ACC, sensitivity, and specificity were 0.80, 0.69, 0.80, and 0.67 in the internal validation, and 0.82, 0.54, 1.00, and 0.48 in prospective validation, respectively. In external validation, the AUC, ACC, sensitivity and specificity were 0.84, 0.68, 0.90 and 0.60 in ZJH, 0.89, 0.77, 1.00 and 0.72 in FAHKMU, and 0.80, 0.67, 0.75, and 0.65 in PHJM, respectively. CONCLUSION: The MLR model is a simple, rapid, and reliable tool for early detection of DME in individuals with T2DM without the needs of specialized ophthalmologic examinations.

Leading determinants of incident dementia among individuals with and without the apolipoprotein E ε4 genotype: a retrospective cohort study.

BACKGROUND: Little is known regarding the leading risk factors for dementia/Alzheimer's disease (AD) in individuals with and without APOE4. The identification of key risk factors for dementia/Alzheimer's disease (AD) in individuals with and without the APOE4 gene is of significant importance in global health. METHODS: Our analysis included 110,354 APOE4 carriers and 220,708 age- and sex-matched controls aged 40-73 years at baseline (between 2006-2010) from UK Biobank. Incident dementia was ascertained using hospital inpatient, or death records until January 2021. Individuals of non-European ancestry were excluded. Furthermore, individuals without medical record linkage were excluded from the analysis. Moderation analysis was tested for 134 individual factors. RESULTS: During a median follow-up of 11.9 years, 4,764 cases of incident all-cause dementia and 2065 incident AD cases were documented. Hazard ratios (95% CIs) for all-cause dementia and AD associated with APOE4 were 2.70(2.55-2.85) and 3.72(3.40-4.07), respectively. In APOE4 carriers, the leading risk factors for all-cause dementia included low self-rated overall health, low household income, high multimorbidity risk score, long-term illness, high neutrophil percentage, and high nitrogen dioxide air pollution. In non-APOE4 carriers, the leading risk factors included high multimorbidity risk score, low overall self-rated health, low household income, long-term illness, high microalbumin in urine, high neutrophil count, and low greenspace percentage. Population attributable risk for these individual risk factors combined was 65.1%, and 85.8% in APOE4 and non-APOE4 carriers, respectively. For 20 risk factors including multimorbidity risk score, unhealthy lifestyle habits, and particulate matter air pollutants, their associations with incident dementia were stronger in non-APOE4 carriers. For only 2 risk factors (mother's history of dementia, low C-reactive protein), their associations with incident all-cause dementia were stronger in APOE4 carriers. CONCLUSIONS: Our findings provide evidence for personalized preventative approaches to dementia/AD in APOE4 and non-APOE4 carriers. A mother's history of dementia and low levels of C-reactive protein were more important risk factors of dementia in APOE4 carriers whereas leading risk factors including unhealthy lifestyle habits, multimorbidity risk score, inflammation and immune-related markers were more predictive of dementia in non-APOE4 carriers.

EEG measurement for the effect of perceptual eye position and eye position training on comitant strabismus.

One of the clinical features of comitant strabismus is that the deviation angles in the first and second eye positions are equal. However, there has been no report of consistency in the electroencephalography (EEG) signals between the 2 positions. In order to address this issue, we developed a new paradigm based on perceptual eye position. We collected steady-state visual evoked potentials (SSVEPs) signals and resting-state EEG data before and after the eye position training. We found that SSVEP signals could characterize the suppression effect and eye position effect of comitant strabismus, that is, the SSVEP response of the dominant eye was stronger than that of the strabismus eye in the first eye position but not in the second eye position. Perceptual eye position training could modulate the frequency band activities in the occipital and surrounding areas. The changes in the visual function of comitant strabismus after training could also be characterized by SSVEP. There was a correlation between intermodulation frequency, power of parietal electrodes, and perceptual eye position, indicating that EEG might be a potential indicator for evaluating strabismus visual function.

Alterations of outer retinal reflectivity in diabetic patients without clinically detectable retinopathy.

PURPOSE: This study aimed to investigate alterations of outer retinal reflectivity on spectral-domain optical coherence tomography (OCT) in diabetic patients without clinically detectable retinopathy (NDR). METHODS: In this retrospective study, 64 NDR patients and 71 controls were included. Relative reflectivity (RR) of the ellipsoid zone (EZ), photoreceptor outer segment (OS) and inner segment (IS), and outer nuclear layer (ONL) at the foveola and at 500 µm, 1000 µm, and 2000 µm nasal (N), temporal (T), superior (S), and inferior (I) to the foveola was measured by cross-line OCT and ImageJ. Retinal vessel densities (VD) in fovea, parafovea, and perifovea areas were detected by OCT angiography (OCTA). RESULTS: EZ RR in most retinal locations was significantly lower in NDR eyes compared to controls (all P < 0.05), except the foveola. Compared with controls, NDR eyes also displayed lower RR at N2000, T2000, S1000, and I1000 of OS, at S500 and I500 of IS, and at I500 of ONL (all P < 0.05). Negative correlations could be observed between retinal RR and diabetes duration, HbA1c, and best-corrected visual acuity (BCVA) (r = - 0.303 to - 0.452). Compared to controls, EZ, OS, and IS RR of the NDR eyes showed lower correlation coefficients with whole image SCP and DCP VD of parafovea and perifovea regions. CONCLUSION: Outer retinal reflectivity, along with the coefficients between retinal reflectivity and VD, is reduced in NDR patients and is correlated with diabetes duration, HbA1c, and BCVA. The reduction of outer retinal reflectivity may be a potential biomarker of early retinal alterations in diabetic patients.

Multilayer factors associated with excess all-cause mortality during the omicron and non-omicron waves of the COVID-19 pandemic: time series analysis in 29 countries.

BACKGROUND: The COVID-19 pandemic has resulted in significant excess mortality globally. However, the differences in excess mortality between the Omicron and non-Omicron waves, as well as the contribution of local epidemiological characteristics, population immunity, and social factors to excess mortality, remain poorly understood. This study aims to solve the above problems. METHODS: Weekly all-cause death data and covariates from 29 countries for the period 2015-2022 were collected and used. The Bayesian Structured Time Series Model predicted expected weekly deaths, stratified by gender and age groups for the period 2020-2022. The quantile-based g-computation approach accounted for the effects of factors on the excess all-cause mortality rate. Sensitivity analyses were conducted using alternative Omicron proportion thresholds. RESULTS: From the first week of 2021 to the 30th week of 2022, the estimated cumulative number of excess deaths due to COVID-19 globally was nearly 1.39 million. The estimated weekly excess all-cause mortality rate in the 29 countries was approximately 2.17 per 100,000 (95% CI: 1.47 to 2.86). Weekly all-cause excess mortality rates were significantly higher in both male and female groups and all age groups during the non-Omicron wave, except for those younger than 15 years (P < 0.001). Sensitivity analysis confirmed the stability of the results. Positive associations with all-cause excess mortality were found for the constituent ratio of non-Omicron in all variants, new cases per million, positive rate, cardiovascular death rate, people fully vaccinated per hundred, extreme poverty, hospital patients per million humans, people vaccinated per hundred, and stringency index. Conversely, other factors demonstrated negative associations with all-cause excess mortality from the first week of 2021 to the 30th week of 2022. CONCLUSION: Our findings indicate that the COVID-19 Omicron wave was associated with lower excess mortality compared to the non-Omicron wave. This study's analysis of the factors influencing excess deaths suggests that effective strategies to mitigate all-cause mortality include improving economic conditions, promoting widespread vaccination, and enhancing overall population health. Implementing these measures could significantly reduce the burden of COVID-19, facilitate coexistence with the virus, and potentially contribute to its elimination.

Impaired retinal microcirculation in patients with non-obstructive coronary artery disease.

PURPOSE: To quantitatively investigate alterations of retinal microcirculation in patients with non-obstructive coronary artery disease (NOCAD) using optical coherence tomography angiography (OCTA), and to identify the ability of retinal microcirculation parameters in differentiating coronary artery disease (CAD) subtypes. METHODS: All participants with angina pectoris underwent coronary computed tomography angiography. Patients with lumen diameter reduction of 20-50 % in all major coronary arteries were defined as NOCAD, while patients with at least one major coronary artery lumen diameter reduction ≥ 50 % were recruited as obstructive coronary artery disease (OCAD). Participants without a history of ophthalmic or systemic vascular disease were recruited as healthy controls. Retinal neural-vasculature was measured quantitatively by OCTA, including peripapillary retinal nerve fiber layer (RNFL) thickness and vessel density (VD) of the optic disc, superficial vessel plexus (SVP), deep vessel plexus (DVP), and foveal density (FD 300). p < 0.017 is considered significant in multiple comparisons. RESULTS: A total of 185 participants (65 NOCAD, 62 OCAD, and 58 controls) were enrolled. Except for the DVP fovea (p = 0.069), significantly reduced VD in all other regions of SVP and DVP was detected in both the NOCAD and OCAD groups compared to control group (all p < 0.017), while a more significant decrease was found in OCAD compared to NOCAD. Multivariate regression analysis showed that lower VD in superior hemi part of whole SVP (OR: 0.582, 95 % CI: 0.451-0.752) was an independent risk factor for NOCAD compared to controls, while lower VD in the whole SVP (OR: 0.550, 95 % CI: 0.421-0.719) was an independent risk factor for OCAD compared to NOCAD. Using the integration of retinal microvascular parameters, the area under the receiver operating characteristic curve (AUC) for NOCAD versus control and OCAD versus NOCAD were 0.840 and 0.830, respectively. CONCLUSION: Significant retinal microcirculation impairment, while milder than that in OCAD was observed in NOCAD patients, indicating retinal microvasculature assessment might provide a new systemic microcirculation observation window for NOCAD. Furthermore, retinal microvasculature may serve as a new indicator to assess the severity of CAD with good performance of retinal microvascular parameters in identifying different CAD subtypes.

Willingness to practice medicine and related influential factors among medical undergraduates during COVID-19: a cross-sectional study.

BACKGROUND: As the medical undergraduates constitute the future workforce in China, their career preferences hold a significant bearing on the quality of healthcare services, particularly in light of the ongoing COVID-19 pandemic. We aim to understand the current state of the willingness to practice medicine among medical undergraduates and to analyze the related influential factors. METHODS: During the COVID-19 epidemic, we conducted a cross-sectional survey via an online platform from February 15, 2022, to May 31, 2022, to collect participants' demographic information, psychology, and factors influencing their career choices. The general self-efficacy scale (GSES) was used to evaluate medical students' perceptions of their self-efficacy. Futhermore, we conducted multivariate logistic regression analyses to explore the influencing factors of medical undergraduates' willingness to pursure a caree in medicine. RESULTS: A total of 2348 valid questionnaires were included, and 1573 (66.99%) were willing to practice medicine for medical undergraduates after graduation. The mean GESE scores in the willingness group (2.87 ± 0.54) were significantly higher than those of the unwillingness group (2.73 ± 0.49). The multiple logistic regression showed that several factors were positively associated with willingness to practice medicine as a career, including students' GSES score (OR = 1.87), current major, household income, personal ideals (OR = 1.97), family support (OR = 1.44), high income (OR = 1.77), and social respect (OR = 2.19). Compared with those who were very afraid of COVID-19, students who did not express any fear towards the COVID-19 pandemic had a higher preference for choosing the medical profession as a career. Conversely, students thinking of high tension in the doctor-patient relationship, heavy workload, and long training were less likely to choose medical work after graduation. CONCLUSIONS: The study highlights a noteworthy prevalence of medical undergraduates who expressed their willingness to pursue medicine as a career post-graduation. Several factors, including but not limited to current major, household income, psychological factors, personal preferences, and career needs or preferences, were significantly associated with this willingness. Moreover, the impact of the COVID-19 pandemic on medical students' career choices cannot be overlooked.

Real-Time Ocean Current Compensation for AUV Trajectory Tracking Control Using a Meta-Learning and Self-Adaptation Hybrid Approach.

Autonomous underwater vehicles (AUVs) may deviate from their predetermined trajectory in underwater currents due to the complex effects of hydrodynamics on their maneuverability. Model-based control methods are commonly employed to address this problem, but they suffer from issues related to the time-variability of parameters and the inaccuracy of mathematical models. To improve these, a meta-learning and self-adaptation hybrid approach is proposed in this paper to enable an underwater robot to adapt to ocean currents. Instead of using a traditional complex mathematical model, a deep neural network (DNN) serving as the basis function is trained to learn a high-order hydrodynamic model offline; then, a set of linear coefficients is adjusted dynamically by an adaptive law online. By conjoining these two strategies for real-time thrust compensation, the proposed method leverages the potent representational capacity of DNN along with the rapid response of adaptive control. This combination achieves a significant enhancement in tracking performance compared to alternative controllers, as observed in simulations. These findings substantiate that the AUV can adeptly adapt to new speeds of ocean currents.

Plasma metabolomic profiles of dementia: a prospective study of 110,655 participants in the UK Biobank.

BACKGROUND: Plasma metabolomic profile is disturbed in dementia patients, but previous studies have discordant conclusions. METHODS: Circulating metabolomic data of 110,655 people in the UK Biobank study were measured with nuclear magnetic resonance technique, and incident dementia records were obtained from national health registers. The associations between plasma metabolites and dementia were estimated using Cox proportional hazard models. The 10-fold cross-validation elastic net regression models selected metabolites that predicted incident dementia, and a 10-year prediction model for dementia was constructed by multivariable logistic regression. The predictive values of the conventional risk model, the metabolites model, and the combined model were discriminated by comparison of area under the receiver operating characteristic curves (AUCs). Net reclassification improvement (NRI) was used to estimate the change of reclassification ability when adding metabolites into the conventional prediction model. RESULTS: Amongst 110,655 participants, the mean (standard deviation) age was 56.5 (8.1) years, and 51 186 (46.3%) were male. A total of 1439 (13.0%) developed dementia during a median follow-up of 12.2 years (interquartile range: 11.5-12.9 years). A total of 38 metabolites, including lipids and lipoproteins, ketone bodies, glycolysis-related metabolites, and amino acids, were found to be significantly associated with incident dementia. Adding selected metabolites (n=24) to the conventional dementia risk prediction model significantly improved the prediction for incident dementia (AUC: 0.824 versus 0.817, p =0.042) and reclassification ability (NRI = 4.97%, P = 0.009) for identifying high risk groups. CONCLUSIONS: Our analysis identified various metabolomic biomarkers which were significantly associated with incident dementia. Metabolomic profiles also provided opportunities for dementia risk reclassification. These findings may help explain the biological mechanisms underlying dementia and improve dementia prediction.

Optimal Control of Background-Based Uncertain Systems with Applications in DC Pension Plan.

In this paper, we propose a new optimal control model for uncertain systems with jump. In the model, the background-state variables are incorporated, where the background-state variables are governed by an uncertain differential equation. Meanwhile, the state variables are governed by another uncertain differential equation with jump, in which both the background-state variables and the control variables are involved. Under the optimistic value criterion, using uncertain dynamic programming method, we establish the principle and the equation of optimality. As an application, the optimal investment strategy and optimal payment rate for DC pension plans are given, where the corresponding background-state variables represent the salary process. This application in DC pension plans illustrates the effectiveness of the proposed model.

DETECTION OF MORPHOLOGIC PATTERNS OF DIABETIC MACULAR EDEMA USING A DEEP LEARNING APPROACH BASED ON OPTICAL COHERENCE TOMOGRAPHY IMAGES.

PURPOSE: To develop a deep learning (DL) model to detect morphologic patterns of diabetic macular edema (DME) based on optical coherence tomography (OCT) images. METHODS: In the training set, 12,365 OCT images were extracted from a public data set and an ophthalmic center. A total of 656 OCT images were extracted from another ophthalmic center for external validation. The presence or absence of three OCT patterns of DME, including diffused retinal thickening, cystoid macular edema, and serous retinal detachment, was labeled with 1 or 0, respectively. A DL model was trained to detect three OCT patterns of DME. The occlusion test was applied for the visualization of the DL model. RESULTS: Applying 5-fold cross-validation method in internal validation, the area under the receiver operating characteristic curve for the detection of three OCT patterns (i.e., diffused retinal thickening, cystoid macular edema, and serous retinal detachment) was 0.971, 0.974, and 0.994, respectively, with an accuracy of 93.0%, 95.1%, and 98.8%, respectively, a sensitivity of 93.5%, 94.5%, and 96.7%, respectively, and a specificity of 92.3%, 95.6%, and 99.3%, respectively. In external validation, the area under the receiver operating characteristic curve was 0.970, 0.997, and 0.997, respectively, with an accuracy of 90.2%, 95.4%, and 95.9%, respectively, a sensitivity of 80.1%, 93.4%, and 94.9%, respectively, and a specificity of 97.6%, 97.2%, and 96.5%, respectively. The occlusion test showed that the DL model could successfully identify the pathologic regions most critical for detection. CONCLUSION: Our DL model demonstrated high accuracy and transparency in the detection of OCT patterns of DME. These results emphasized the potential of artificial intelligence in assisting clinical decision-making processes in patients with DME.

Dynamic Risk Measures for Processes via Backward Stochastic Differential Equations Associated with Lévy Processes.

In this paper, we study the dynamic risk measures for processes induced by backward stochastic differential equations driven by Teugel's martingales associated with Lévy processes (BSDELs). The representation theorem for generators of BSDELs is provided. Furthermore, the time consistency of the coherent and convex dynamic risk measures for processes is characterized by means of the generators of BSDELs. Moreover, the coherency and convexity of dynamic risk measures for processes are characterized by the generators of BSDELs. Finally, we provide two numerical examples to illustrate the proposed dynamic risk measures.

Dynamic Risk Measures for Anticipated Backward Doubly Stochastic Volterra Integral Equations.

Inspired by the consideration of some inside and future market information in financial market, a class of anticipated backward doubly stochastic Volterra integral equations (ABDSVIEs) are introduced to induce dynamic risk measures for risk quantification. The theory, including the existence, uniqueness and a comparison theorem for ABDSVIEs, is provided. Finally, dynamic convex risk measures by ABDSVIEs are discussed.

INCREASED SYSTEMIC HEPARANASE IN RETINAL VEIN OCCLUSION IS ASSOCIATED WITH ACTIVATION OF INFLAMMATION AND THROMBOPHILIA.

PURPOSE: To investigate the levels of systemic heparanase, inflammatory markers, and coagulation factor activities in patients with retinal vein occlusion (RVO). METHODS: This prospective study included 18 patients with central RVO, 22 patients with branch RVO, and 40 patients with age-related cataract as the control group. Serum heparanase protein levels and activities were measured by ELISA and a heparan degrading enzyme assay kit, respectively. Serum levels of MMP-2, MMP-9, TLR-2, and TLR-4 were measured by ELISA kits. The activities of coagulation factors (V, VII, VIII, and IX) were determined with an autoanalyzer. The Mann-Whitney U test was used to compare the above parameters between patients with RVO and control subjects. The relationship between two of the above parameters was analyzed by Spearman's correlation. RESULTS: Patients with RVO had higher levels of systemic heparanase protein, heparanase activities, coagulation factors' (V, VIII, and IX) activities, MMP-2, MMP-9, TLR-2, and TLR-4 compared with the control group. Systemic heparanase levels were correlated with serum levels of MMP-2, MMP-9, TLR-2, TLR-4, and activities of coagulation factors VIII and IX. CONCLUSION: Increase of systemic heparanase in RVO is associated with activation of systemic inflammation and blood hypercoagulability.

Transient ocular surface non-perfusion during cataract phacoemulsification surgery.

BACKGROUND: Complete non-perfusion of the anterior segment vasculature during cataract phacoemulsification surgery is rarely reported. CASE PRESENTATION: We present two cases of transient ocular surface non-perfusion (TOSN) during cataract phacoemulsification surgery. The TOSN happened during intraocular lens (IOL) implantation with complete vanish of blood flow in the conjunctival, episcleral and limbal vessels. Reperfusion started within 30 s and part of the blood supply of the conjunctiva and episclera was restored within 2 min. However, the blood flow in the limbal vessels was not restored until 5 min later. The postoperative examination of both eyes was normal. These two rare cases are the TOSN during cataract surgery. We speculated that the significantly increased intraocular pressure during IOL implantation might be the cause of this rare phenomenon. CONCLUSION: Non-perfusion of the ocular structures may occur if the IOP peak during IOL injection exceeds the perfusion pressure of the anterior vasculature.

Comparison of clinical outcomes of different components of diabetic macular edema on optical coherence tomography.

PURPOSE: To evaluate the edema reduction after intravitreal injection of ranibizumab (IVR) in two diabetic macular edema (DME) components in the same eye using optical coherence tomography (OCT). METHODS: Totally 113 eyes with mixed OCT pattern of DME were included. All the eyes underwent best-corrected visual acuity (BCVA) examination and OCT scanning at baseline and follow-up visits (1, 3, and 6 months after 3 monthly consecutive IVR). The mixed OCT pattern of DME was classified into 2 OCT components: serous retinal detachment (SRD) component and non-SRD component. Foveal thickness of the SRD component (SRDFT) and the non-SRD component (NSRDFT) was compared between baseline and follow-up visits. Reduction and reduction ratio of the SRDFT and the NSRDFT at each follow-up were compared. When calculating the NSRDFT reduction ratio, we innovatively optimized a commonly used formula by subtracting the normal foveal thickness from the baseline NSRDFT. RESULTS: SRDFT was 265.6 ± 175.4 µm at baseline and was significantly decreased to 126.7 ± 114.4 µm at 1 month, to 110.5 ± 103.4 µm at 3 months, and to 110.4 ± 89.6 µm at 6 months (all P < 0.001). NSRDFT was 409.5 ± 173.1 µm at baseline and was significantly decreased to 274.1 ± 140.4 µm at 1 month, to 249.1 ± 95.9 µm at 3 months, and to 254.1 ± 90.4 µm at 6 months (all P < 0.001). There was no significant difference in reduction or reduction ratio between NSRDFT and SRDFT during follow-up (all P > 0.05). The correlation between BCVA and SRDFT was most significant at baseline (r = 0.366, P < 0.001) and the correlation between BCVA and NSRDFT was most significant at 6 months (r = 0.426, P < 0.001). BCVA improvement was more significantly correlated with reduction or reduction ratio of SRDFT at each follow-up timepoint (r = 0.271-0.426, all P < 0.01). CONCLUSIONS: IVR was effective in reducing both the SRD and non-SRD components of DME according to our optimized formula. The association between BCVA improvement and edema reduction was more significant in the SRD component.

Heparanase mediates vascular endothelial growth factor gene transcription in high-glucose human retinal microvascular endothelial cells.

PURPOSE: To observe the nuclear expression and interaction of heparanase and RNA polymerase II (RNA Pol II), an enzyme that catalyzes the transcription of DNA in eukaryotic cells) in human retinal microvascular endothelial cells (HRECs) under high glucose condition and to investigate the association of heparanase with the transcription activity of the vascular endothelial growth factor (VEGF) gene promoter. METHODS: Cultured HRECs were maintained for 3 days in media with high or normal glucose. The expressions of heparanase and RNA Pol II in each group were analyzed with immunofluorescence. Co-immunoprecipitation was applied to detect the interaction of heparanase and Pol II proteins. Cells in both groups were used for chromatin immunoprecipitation (ChIP) with anti-heparanase and anti-RNA Pol II antibodies to identify high-confidence heparanase-binding regions across the entire VEGF gene promoter. Moreover, real-time PCR was used to demonstrate the interaction between heparanase and the VEGF gene promoter region. RESULTS: The immunofluorescence studies showed that the nuclear expression of heparanase was intense in high-glucose HRECs but faint in the normal group; RNA Pol II in the nucleus was also intense in high glucose HRECs, and the distribution of heparanase was consistent with that of RNA Pol II. The co-immunoprecipitation data showed that heparanase combined with RNA Pol II in HRECs cells treated with high glucose, and the molecular size of HPA interacted with RNA Pol II was 50 kDa, while no combination of two proteins was evident in normal HRECs cells. Real-time PCR-based ChIP results showed that the high-confidence HPA-binding region was -1155 to -1018 (containing hypoxia response element) in the VEGF gene promoter, and the cells treated with high glucose showed increases in heparanase and RNA Pol II in the VEGF gene promoter region compared with the normal glucose treated cells (t = -3.244, p = 0.032; t = -6.096, p = 0.004, respectively). CONCLUSIONS: Nuclear heparanase combines directly with the VEGF gene promoter and is involved in the regulation of VEGF gene transcription in high-glucose HRECs.