Flow diverters treatment planning of small- and medium-sized intracranial saccular aneurysms on the internal carotid artery via constraint-based virtual deployment.

PURPOSE: The internal carotid artery (ICA) is a region with a high incidence for small- and medium-sized saccular aneurysms. However, the treatment relies heavily on the surgeon's experience to achieve optimal outcome. Although the finite element method (FEM) and computational fluid dynamics can predict the postoperative outcomes, due to the computational complexity of traditional methods, there is an urgent need for investigating the fast but versatile approaches related to numerical simulations of flow diverters (FDs) deployment coupled with the hemodynamic analysis to determine the treatment plan. METHODS: We collected the preoperative and postoperative data from 34 patients (29 females, 5 males; mean age 55.74 ± 9.98 years) who were treated with a single flow diverter for small- to medium-sized intracranial saccular aneurysms on the ICA. The constraint-based virtual deployment (CVD) method is proposed to simulate the FDs expanding outward along the vessel centerline while be constrained by the inner wall of the vessel. RESULTS: The results indicate that there were no significant differences in the reduction rates of wall shear stress and aneurysms neck velocity between the FEM and methods. However, the solution time of CVD was greatly reduced by 98%. CONCLUSION: In the typical location of small- and medium-sized saccular aneurysms, namely the ICA, our virtual FDs deployment simulation effectively balances the computational accuracy and efficiency. Combined with hemodynamics analysis, our method can accurately represent the blood flow changes within the lesion region to assist surgeons in clinical decision-making.

Prognostic Value of a Combined Nomogram Model Integrating 3-Dimensional Deep Learning and Radiomics for Head and Neck Cancer.

OBJECTIVE: The preoperative prediction of the overall survival (OS) status of patients with head and neck cancer (HNC) is significant value for their individualized treatment and prognosis. This study aims to evaluate the impact of adding 3D deep learning features to radiomics models for predicting 5-year OS status. METHODS: Two hundred twenty cases from The Cancer Imaging Archive public dataset were included in this study; 2212 radiomics features and 304 deep features were extracted from each case. The features were selected by univariate analysis and the least absolute shrinkage and selection operator, and then grouped into a radiomics model containing Positron Emission Tomography /Computed Tomography (PET/CT) radiomics features score, a deep model containing deep features score, and a combined model containing PET/CT radiomics features score +3D deep features score. TumorStage model was also constructed using initial patient tumor node metastasis stage to compare the performance of the combined model. A nomogram was constructed to analyze the influence of deep features on the performance of the model. The 10-fold cross-validation of the average area under the receiver operating characteristic curve and calibration curve were used to evaluate performance, and Shapley Additive exPlanations (SHAP) was developed for interpretation. RESULTS: The TumorStage model, radiomics model, deep model, and the combined model achieved areas under the receiver operating characteristic curve of 0.604, 0.851, 0.840, and 0.895 on the train set and 0.571, 0.849, 0.832, and 0.900 on the test set. The combined model showed better performance of predicting the 5-year OS status of HNC patients than the radiomics model and deep model. The combined model was shown to provide a favorable fit in calibration curves and be clinically useful in decision curve analysis. SHAP summary plot and SHAP The SHAP summary plot and SHAP force plot visually interpreted the influence of deep features and radiomics features on the model results. CONCLUSIONS: In predicting 5-year OS status in patients with HNC, 3D deep features could provide richer features for combined model, which showed outperformance compared with the radiomics model and deep model.

Assessment of Inner Blood-Retinal Barrier: Animal Models and Methods.

Proper functioning of the neural retina relies on the unique retinal environment regulated by the blood-retinal barrier (BRB), which restricts the passage of solutes, fluids, and toxic substances. BRB impairment occurs in many retinal vascular diseases and the breakdown of BRB significantly contributes to disease pathology. Understanding the different molecular constituents and signaling pathways involved in BRB development and maintenance is therefore crucial in developing treatment modalities. This review summarizes the major molecular signaling pathways involved in inner BRB (iBRB) formation and maintenance, and representative animal models of eye diseases with retinal vascular leakage. Studies on Wnt/ß-catenin signaling are highlighted, which is critical for retinal and brain vascular angiogenesis and barriergenesis. Moreover, multiple in vivo and in vitro methods for the detection and analysis of vascular leakage are described, along with their advantages and limitations. These pre-clinical animal models and methods for assessing iBRB provide valuable experimental tools in delineating the molecular mechanisms of retinal vascular diseases and evaluating therapeutic drugs.

An Analytical Method for Mechanical Analysis of Offshore Pipelines during Lifting Operation.

The lifting operation of offshore pipelines is an important step in ocean pipeline engineering. An effective analytical method is developed for investigating the mechanical properties of the pipeline based on mechanical, physical, and geometric relationships. By using the shooting and the secant methods to transform the boundary value problem into an initial value one and then solving them with the Runge-Kutta method, the deformation and mechanical properties of the pipeline are calculated. Furthermore, based on the Det Norske Veritas (DNV) offshore standard, the mechanical properties of the pipeline are checked. The finite element method (FEM) by Orcaflex is employed to verify the accuracy of the analytical model. The effects of some factors such as the current velocity and lifting point position on the mechanical properties of the pipeline are analyzed based on the analytical model. The results indicate that the change in current velocity during the lifting process has a minimal effect on the pipeline, but the change in lifting point position significantly affects the deformation and mechanical properties of the pipeline.

Deep learning PET/CT-based radiomics integrates clinical data: A feasibility study to distinguish between tuberculosis nodules and lung cancer.

BACKGROUND: Radiomic diagnosis models generally consider only a single dimension of information, leading to limitations in their diagnostic accuracy and reliability. The integration of multiple dimensions of information into the deep learning model have the potential to improve its diagnostic capabilities. The purpose of study was to evaluate the performance of deep learning model in distinguishing tuberculosis (TB) nodules and lung cancer (LC) based on deep learning features, radiomic features, and clinical information. METHODS: Positron emission tomography (PET) and computed tomography (CT) image data from 97 patients with LC and 77 patients with TB nodules were collected. One hundred radiomic features were extracted from both PET and CT imaging using the pyradiomics platform, and 2048 deep learning features were obtained through a residual neural network approach. Four models included traditional machine learning model with radiomic features as input (traditional radiomics), a deep learning model with separate input of image features (deep convolutional neural networks [DCNN]), a deep learning model with two inputs of radiomic features and deep learning features (radiomics-DCNN) and a deep learning model with inputs of radiomic features and deep learning features and clinical information (integrated model). The models were evaluated using area under the curve (AUC), sensitivity, accuracy, specificity, and F1-score metrics. RESULTS: The results of the classification of TB nodules and LC showed that the integrated model achieved an AUC of 0.84 (0.82-0.88), sensitivity of 0.85 (0.80-0.88), and specificity of 0.84 (0.83-0.87), performing better than the other models. CONCLUSION: The integrated model was found to be the best classification model in the diagnosis of TB nodules and solid LC.

Prognostic value of 18F-FDG PET/CT-based radiomics combining dosiomics and dose volume histogram for head and neck cancer.

OBJECTIVES: By comparing the prognostic performance of 18F-FDG PET/CT-based radiomics combining dose features [Includes Dosiomics feature and the dose volume histogram (DVH) features] with that of conventional radiomics in head and neck cancer (HNC), multidimensional prognostic models were constructed to investigate the overall survival (OS) in HNC. MATERIALS AND METHODS: A total of 220 cases from four centres based on the Cancer Imaging Archive public dataset were used in this study, 2260 radiomics features and 1116 dosiomics features and 8 DVH features were extracted for each case, and classified into seven different models of PET, CT, Dose, PET+CT, PET+Dose, CT+Dose and PET+CT+Dose. Features were selected by univariate Cox and Spearman correlation coefficients, and the selected features were brought into the least absolute shrinkage and selection operator (LASSO)-Cox model. A nomogram was constructed to visually analyse the prognostic impact of the incorporated dose features. C-index and Kaplan-Meier curves (log-rank analysis) were used to evaluate and compare these models. RESULTS: The cases from the four centres were divided into three different training and validation sets according to the hospitals. The PET+CT+Dose model had C-indexes of 0.873 (95% CI 0.812-0.934), 0.759 (95% CI 0.663-0.855) and 0.835 (95% CI 0.745-0.925) in the validation set respectively, outperforming the rest models overall. The PET+CT+Dose model did well in classifying patients into high- and low-risk groups under all three different sets of experiments (p < 0.05). CONCLUSION: Multidimensional model of radiomics features combining dosiomics features and DVH features showed high prognostic performance for predicting OS in patients with HNC.

Amino acid transporter SLC38A5 regulates developmental and pathological retinal angiogenesis.

Amino acid (AA) metabolism in vascular endothelium is important for sprouting angiogenesis. SLC38A5 (solute carrier family 38 member 5), an AA transporter, shuttles neutral AAs across cell membrane, including glutamine, which may serve as metabolic fuel for proliferating endothelial cells (ECs) to promote angiogenesis. Here, we found that Slc38a5 is highly enriched in normal retinal vascular endothelium, and more specifically, in pathological sprouting neovessels. Slc38a5 is suppressed in retinal blood vessels from Lrp5-/- and Ndpy/- mice, both genetic models of defective retinal vascular development with Wnt signaling mutations. Additionally, Slc38a5 transcription is regulated by Wnt/ß-catenin signaling. Genetic deficiency of Slc38a5 in mice substantially delays retinal vascular development and suppresses pathological neovascularization in oxygen-induced retinopathy modeling ischemic proliferative retinopathies. Inhibition of SLC38A5 in human retinal vascular ECs impairs EC proliferation and angiogenic function, suppresses glutamine uptake, and dampens vascular endothelial growth factor receptor 2. Together these findings suggest that SLC38A5 is a new metabolic regulator of retinal angiogenesis by controlling AA nutrient uptake and homeostasis in ECs.

Endothelial Cell Transcytosis Assay as an In Vitro Model to Evaluate Inner Blood-Retinal Barrier Permeability.

Dysfunction of the blood-retinal barrier (BRB) contributes to the pathophysiology of several vascular eye diseases, often resulting in retinal edema and subsequent vision loss. The inner blood-retinal barrier (iBRB) is mainly composed of retinal vascular endothelium with low permeability under physiological conditions. This feature of low permeability is tightly regulated and maintained by low rates of paracellular transport between adjacent retinal microvascular endothelial cells, as well as transcellular transport (transcytosis) through them. The assessment of retinal transcellular barrier permeability may provide fundamental insights into iBRB integrity in health and disease. In this study, we describe an endothelial cell (EC) transcytosis assay, as an in vitro model for evaluating iBRB permeability, using human retinal microvascular endothelial cells (HRMECs). This assay assesses the ability of HRMECs to transport transferrin and horseradish peroxidase (HRP) in receptor- and caveolae-mediated transcellular transport processes, respectively. Fully confluent HRMECs cultured on porous membrane were incubated with fluorescent-tagged transferrin (clathrin-dependent transcytosis) or HRP (caveolae-mediated transcytosis) to measure the levels of transferrin or HRP transferred to the bottom chamber, indicative of transcytosis levels across the EC monolayer. Wnt signaling, a known pathway regulating iBRB, was modulated to demonstrate the caveolae-mediated HRP-based transcytosis assay method. The EC transcytosis assay described here may provide a useful tool for investigating the molecular regulators of EC permeability and iBRB integrity in vascular pathologies and for screening drug delivery systems.

Pseudohalide Anions to Suppress Oxidative Degradation for Efficient Formamidinium-Based Sn-Pb Halide Perovskite Solar Cells.

Although binary Sn-Pb perovskites possess optimal band gap approaching to the Shockley-Queisser limit efficiency, the enhancement on power conversion efficiency (PCE) of Sn-Pb perovskite solar cells (PSCs) is impeded by the detrimental oxidation of Sn2+. Herein, a novel and effective strategy is developed to introduce pseudohalide anion thiocyanate (SCN-) with similar ionic radius to iodide to occupy the X-site of the perovskite lattice, thus restraining the rapid oxidation of Sn2+ to Sn4+. The incorporation of SCN- into perovskite stabilizes the perovskite crystal structure thermodynamically and increases the adsorption-energy-barrier of oxygen molecules. The coordination between Sn2+ and SCN- can reduce the defect density by healing the undercoordinated Sn2+ and suppressing the Sn and I vacancies. With the incorporation of SCN-, the ion migration behavior and lattice strain associated with the defects are remarkably relaxed. The study on carrier dynamics based on steady-state and time-resolved photoluminescence suggests that the carrier lifetime and non-radiative recombination rate of SCN- PSCs can be remarkably prolonged and depressed, respectively. As a result, FASn0.5Pb0.5I3-based PSCs achieve a 14.5% increase in PCE, reaching 13.74% under AM 1.5G illumination. This strategy takes a noteworthy step toward high efficiency and high stability FA-based Sn-Pb PSCs.

Superimposed Effect of La Doping and Structural Engineering to Achieve Oxygen-Deficient TiNb2O7 for Ultrafast Li-Ion Storage.

TiNb2O7 (TNO) is a competitive candidate of a fast-charging anode due to its high specific capacity. However, the insulator nature seriously hinders its rate performance. Herein, the La3+-doped mesoporous TiNb2O7 materials (La-M-TNO) were first synthesized via a facile one-step solvothermal method with the assistance of polyvinyl pyrrolidone (PVP). The synergic effect of La3+ doping and the mesoporous structure enables a dual improvement on the electronic conductivity and ionic diffusion coefficient, which delivers an impressive specific capacity of 213 mAh g-1 at 30 C. The capacity retention (@30C/@1C) increases from 33 to 53 and 74% for TNO, M-TNO, and La-M-TNO (0.03), respectively, demonstrating a step-by-step improvement of rate performance by making porous structures and intrinsic conductivity enhancement. DFT calculations verify that the enhancement in electronic conductivity due to La3+ doping and oxygen vacancy, which induce localized energy levels via slight hybridization of O 2p, Ti 3d, and Nb 4d orbits. Meanwhile, the GITT result indicates that PVP-induced self-assembly of TNO accelerates the lithium ion diffusion rate by shortening the Li+ diffusion path. This work verifies the effectiveness of the porous structure and highlights the significance of electronic conductivity to rate performance, especially at >30C. It provides a general approach to low-conductivity electrode materials for fast Li-ion storage.

REV-ERBα regulates age-related and oxidative stress-induced degeneration in retinal pigment epithelium via NRF2.

Retinal pigment epithelium (RPE) dysfunction and atrophy occur in dry age-related macular degeneration (AMD), often leading to photoreceptor degeneration and vision loss. Accumulated oxidative stress during aging contributes to RPE dysfunction and degeneration. Here we show that the nuclear receptor REV-ERBα, a redox sensitive transcription factor, protects RPE from age-related degeneration and oxidative stress-induced damage. Genetic deficiency of REV-ERBα leads to accumulated oxidative stress, dysfunction and degeneration of RPE, and AMD-like ocular pathologies in aging mice. Loss of REV-ERBα exacerbates chemical-induced RPE damage, and pharmacological activation of REV-ERBα protects RPE from oxidative damage both in vivo and in vitro. REV-ERBα directly regulates transcription of nuclear factor erythroid 2-related factor 2 (NRF2) and its downstream antioxidant enzymes superoxide dismutase 1 (SOD1) and catalase to counter oxidative damage. Moreover, aged mice with RPE specific knockout of REV-ERBα also exhibit accumulated oxidative stress and fundus and RPE pathologies. Together, our results suggest that REV-ERBα is a novel intrinsic protector of the RPE against age-dependent oxidative stress and a new molecular target for developing potential therapies to treat age-related retinal degeneration.

Wnt Signaling in Inner Blood-Retinal Barrier Maintenance.

The retina is a light-sensing ocular tissue that sends information to the brain to enable vision. The blood-retinal barrier (BRB) contributes to maintaining homeostasis in the retinal microenvironment by selectively regulating flux of molecules between systemic circulation and the retina. Maintaining such physiological balance is fundamental to visual function by facilitating the delivery of nutrients and oxygen and for protection from blood-borne toxins. The inner BRB (iBRB), composed mostly of inner retinal vasculature, controls substance exchange mainly via transportation processes between (paracellular) and through (transcellular) the retinal microvascular endothelium. Disruption of iBRB, characterized by retinal edema, is observed in many eye diseases and disturbs the physiological quiescence in the retina's extracellular space, resulting in vision loss. Consequently, understanding the mechanisms of iBRB formation, maintenance, and breakdown is pivotal to discovering potential targets to restore function to compromised physiological barriers. These unraveled targets can also inform potential drug delivery strategies across the BRB and the blood-brain barrier into retinas and brain tissues, respectively. This review summarizes mechanistic insights into the development and maintenance of iBRB in health and disease, with a specific focus on the Wnt signaling pathway and its regulatory role in both paracellular and transcellular transport across the retinal vascular endothelium.

Exome sequencing of 112 trios identifies recessive genetic variants in brain arteriovenous malformations.

BACKGROUND: Brain arteriovenous malformation (BAVM) is a main cause of cerebral hemorrhage and hemorrhagic stroke in adolescents. Morphologically, a BAVM is an abnormal connection between cerebrovascular arteries and veins. The genetic etiology of BAVMs has not been fully elucidated. In this study, we aim to investigate potential recessive genetic variants in BAVMs by interrogation of rare compound heterozygous variants. METHODS: We performed whole exome sequencing (WES) on 112 BAVM trios and analyzed the data for rare and deleterious compound heterozygous mutations associated with the disease. RESULTS: We identified 16 genes with compound heterozygous variants that were recurrent in more than one trio. Two genes (LRP2, MUC5B) were recurrently mutated in three trios. LRP2 has been previously associated with BAVM pathogenesis. Fourteen genes (MYLK, HSPG2, PEAK1, PIEZO1, PRUNE2, DNAH14, DNAH5, FCGBP, HERC2, HMCN1, MYH1, NHSL1, PLEC, RP1L1) were recurrently mutated in two trios, and five of these genes (MYLK, HSPG2, PEAK1, PIEZO1, PRUNE2) have been reported to play a role in angiogenesis or vascular diseases. Additionally, abnormal expression of the MYLK protein is related to spinal arteriovenous malformations. CONCLUSION: Our study indicates that rare recessive compound heterozygous variants may underlie cases of BAVM. These findings improve our understanding of BAVM pathology and indicate genes for functional validation.

Dynamic contrast-enhanced MRI analysis for prognosis of intracranial dissecting aneurysm with intramural haematoma after endovascular treatment: an observational registry study.

BACKGROUND AND PURPOSE: Intracranial dissecting aneurysm (IDA) with intramural haematoma (IMH) is an intractable cerebrovascular disease. The outcome of IDA with IMH after endovascular treatment varies across different individuals: some IMHs stop growing after endovascular treatment, while others continue to grow, even after embolisation of the parent artery. Currently, the mechanism for the continuous growth of IMH after endovascular treatment is still unclear. Continuous haemorrhage of the vasa vasorum in the IMH is considered to be associated with continuous enlargement of the IMH; however, this theory has not been proved by in vivo imaging. METHODS AND ANALYSIS: This study will establish a prospective cohort of 80 patients who had an IDA with IMH and received endovascular treatment. Demographic characteristics, IDA morphological characteristics and treatment characteristics will be collected prospectively. All patients will undergo dynamic contrast-enhanced MRI (DCE-MRI) before and 6 months after the endovascular treatment. According to the follow-up results of the MRI, the IDAs will be divided into two groups: a haematoma stabilisation group and a haematoma enlargement group. Then, quantitative analysis of the vasa vasorum in the IMH will be performed, and differences between the two groups will be compared with determine the association between DCE-MRI related parameters and the outcomes of IMH changes. ETHICS AND DISSEMINATION: The research was approved by the ethics committee of Beijing Tian Tan Hospital (KY 2019-024-03) and written informed consents would be obtained from all patients included in this study. The results of this study will be disseminated in professional printed media. TRIAL REGISTRATION NUMBER: NCT03940859. Registered: 7 May, 2019. https://clinicaltrials.gov/ct2/show/NCT03940859.

AI-assisted CT imaging analysis for COVID-19 screening: Building and deploying a medical AI system.

The sudden outbreak of novel coronavirus 2019 (COVID-19) increased the diagnostic burden of radiologists. In the time of an epidemic crisis, we hope artificial intelligence (AI) to reduce physician workload in regions with the outbreak, and improve the diagnosis accuracy for physicians before they could acquire enough experience with the new disease. In this paper, we present our experience in building and deploying an AI system that automatically analyzes CT images and provides the probability of infection to rapidly detect COVID-19 pneumonia. The proposed system which consists of classification and segmentation will save about 30%-40% of the detection time for physicians and promote the performance of COVID-19 detection. Specifically, working in an interdisciplinary team of over 30 people with medical and/or AI background, geographically distributed in Beijing and Wuhan, we are able to overcome a series of challenges (e.g. data discrepancy, testing time-effectiveness of model, data security, etc.) in this particular situation and deploy the system in four weeks. In addition, since the proposed AI system provides the priority of each CT image with probability of infection, the physicians can confirm and segregate the infected patients in time. Using 1,136 training cases (723 positives for COVID-19) from five hospitals, we are able to achieve a sensitivity of 0.974 and specificity of 0.922 on the test dataset, which included a variety of pulmonary diseases.

Deep Neural Networks Offer Morphologic Classification and Diagnosis of Bacterial Vaginosis.

Bacterial vaginosis (BV) is caused by the excessive and imbalanced growth of bacteria in vagina, affecting 30 to 50% of women. Gram staining followed by Nugent scoring based on bacterial morphotypes under the microscope is considered the gold standard for BV diagnosis; this method is often labor-intensive and time-consuming, and results vary from person to person. We developed and optimized a convolutional neural network (CNN) model and evaluated its ability to automatically identify and classify three categories of Nugent scores from microscope images. The CNN model was first established with a panel of microscopic images with Nugent scores determined by experts. The model was trained by minimizing the cross-entropy loss function and optimized by using a momentum optimizer. The separate test sets of images collected from three hospitals were evaluated by the CNN model. The CNN model consisted of 25 convolutional layers, 2 pooling layers, and a fully connected layer. The model obtained 82.4% sensitivity and 96.6% specificity with the 5,815 validation images when altered vaginal flora and BV were considered the positive samples, which was better than the rates achieved by top-level technologists and obstetricians in China. The capability of our model for generalization was so strong that it exhibited 75.1% accuracy in three categories of Nugent scores on the independent test set of 1,082 images, which was 6.6% higher than the average of three technologists, who are hold bachelor's degrees in medicine and are qualified to make diagnostic decisions. When three technologists ran one specimen in triplicate, the precision of three categories of Nugent scores was 54.0%. One hundred three samples diagnosed by two technologists on different days showed a repeatability of 90.3%. The CNN model outperformed human health care practitioners in terms of accuracy and stability for three categories of Nugent score diagnosis. The deep learning model may offer translational applications in automating diagnosis of bacterial vaginosis with proper supporting hardware.

Wnt signaling activates MFSD2A to suppress vascular endothelial transcytosis and maintain blood-retinal barrier.

Breakdown of the blood-retinal barrier (BRB) causes retinal edema and vision loss. We investigated the role of Wnt signaling in maintaining the BRB by limiting transcytosis. Mice lacking either the Wnt co-receptor low-density lipoprotein receptor-related protein 5 (Lrp5-/- ) or the Wnt ligand Norrin (Ndpy/- ) exhibit increased retinal vascular leakage and enhanced endothelial transcytosis. Wnt signaling directly controls the transcription of an endothelium-specific transcytosis inhibitor, major facilitator superfamily domain-containing protein 2a (MFSD2A), in a ß-catenin-dependent manner. MFSD2A overexpression reverses Wnt deficiency-induced transcytosis in endothelial cells and in retinas. Moreover, Wnt signaling mediates MFSD2A-dependent vascular endothelium transcytosis through a caveolin-1 (CAV-1)-positive caveolae pathway. In addition, levels of omega-3 fatty acids are also decreased in Wnt signaling-deficient retinas, reflecting the basic function of MFSD2A as a lipid transporter. Our findings uncovered the Wnt/ß-catenin/MFSD2A/CAV-1 axis as a key pathway governing endothelium transcytosis and inner BRB integrity.

Long-Acting FGF21 Inhibits Retinal Vascular Leakage in In Vivo and In Vitro Models.

The aim of the current study was to investigate the impact of long-acting fibroblast growth factor 21 (FGF21) on retinal vascular leakage utilizing machine learning and to clarify the mechanism underlying the protection. To assess the effect on retinal vascular leakage, C57BL/6J mice were pre-treated with long-acting FGF21 analog or vehicle (Phosphate Buffered Saline; PBS) intraperitoneally (i.p.) before induction of retinal vascular leakage with intravitreal injection of mouse (m) vascular endothelial growth factor 164 (VEGF164) or PBS control. Five hours after mVEGF164 injection, we retro-orbitally injected Fluorescein isothiocyanate (FITC) -dextran and quantified fluorescence intensity as a readout of vascular leakage, using the Image Analysis Module with a machine learning algorithm. In FGF21- or vehicle-treated primary human retinal microvascular endothelial cells (HRMECs), cell permeability was induced with human (h) VEGF165 and evaluated using FITC-dextran and trans-endothelial electrical resistance (TEER). Western blots for tight junction markers were performed. Retinal vascular leakage in vivo was reduced in the FGF21 versus vehicle- treated mice. In HRMECs in vitro, FGF21 versus vehicle prevented hVEGF-induced increase in cell permeability, identified with FITC-dextran. FGF21 significantly preserved TEER compared to hVEGF. Taken together, FGF21 regulates permeability through tight junctions; in particular, FGF21 increases Claudin-1 protein levels in hVEGF-induced HRMECs. Long-acting FGF21 may help reduce retinal vascular leakage in retinal disorders and machine learning assessment can help to standardize vascular leakage quantification.

Targeting Neurovascular Interaction in Retinal Disorders.

The tightly structured neural retina has a unique vascular network comprised of three interconnected plexuses in the inner retina (and choroid for outer retina), which provide oxygen and nutrients to neurons to maintain normal function. Clinical and experimental evidence suggests that neuronal metabolic needs control both normal retinal vascular development and pathological aberrant vascular growth. Particularly, photoreceptors, with the highest density of mitochondria in the body, regulate retinal vascular development by modulating angiogenic and inflammatory factors. Photoreceptor metabolic dysfunction, oxidative stress, and inflammation may cause adaptive but ultimately pathological retinal vascular responses, leading to blindness. Here we focus on the factors involved in neurovascular interactions, which are potential therapeutic targets to decrease energy demand and/or to increase energy production for neovascular retinal disorders.