Healthy Retina Research Articles

Exosome-loaded degradable polymeric microcapsules for the treatment of vitreoretinal diseases.

The therapeutic benefits of many cell types involve paracrine mechanisms. Inspired by the paracrine functions of exosomes and the sustained degradation properties of microcapsules, here we report the therapeutic benefits of exosome-loaded degradable poly(lactic-co-glycolic acid) microcapsules with micrometric pores for the treatment of vitreoretinal diseases. On intravitreal injection in a mouse model of retinal ischaemia-reperfusion injury, microcapsules encapsulating mouse mesenchymal-stem-cell-derived exosomes settled in the inferior vitreous cavity, released exosomes for over one month as they underwent degradation and led to the restoration of retinal thickness to nearly that of the healthy retina. In mice and non-human primates with primed mycobacterial uveitis, intravitreally injected microcapsules loaded with exosomes from monkey regulatory T cells resulted in a substantial reduction in the levels of inflammatory cells. The exosome-encapsulating microcapsules, which can be lyophilised, may offer alternative treatment options for vitreoretinal diseases.

Test-retest repeatability in macular retinal oximetry

ABSTRACT Clinical relevance Evaluation of retinal macular oxygen saturation in healthy controls can aid in understanding the pathological changes seen in similar locations of those with vascular diseases like diabetes. Background The aim of this study was to determine the test-retest repeatability of localised retinal oximetry measurements in the macula on the Zilia Oximeter within healthy subjects of different races, 18–40 years old. Oxygen saturation was measured between three time points within the same locations of the right eye. Methods Twenty seven subjects were included (aged 26.3 ± 3.6 years). All were confirmed to have healthy retinas and at least 6/9 vision. Oximetry measurements were taken using the Zilia to acquire local oxygen saturation measurements (300 µm diameter) at four points 3.1 degrees from the fovea in the superior/temporal, superior/nasal, inferior/temporal, and inferior/nasal locations. Oximetry measurements were taken twice on the same day 20 minutes apart and then again 1–2 weeks later. Oximetry data was analysed with intraclass correlation between visits. To assess intrasubject repeatability, the Bland-Altman repeatability coefficient and coefficient of variation were calculated. Results Average Intraclass correlation for the three acquisition times of the right eye was 0.78. The averaged intrasubject repeatability coefficient for the three acquisition times was 8.4. The averaged coefficient of variation was 5.4%. Conclusion The Zilia oximeter has good macular test-retest repeatability; however, multiple measurements may be needed to ensure accuracy.

The effect of optical degradation from cataract using a new Deep Learning optical coherence tomography segmentation algorithm.

To assess the validity of the results of a freely available online Deep Learning segmentation tool and its sensitivity to noise introduced by cataract. The OCT images were collected with a Spectralis SD-OCT (Heidelberg Engineering, Heidelberg, Germany) as part of normal clinical practice. Data were segmented using a freely available online tool called Relayer ( https://www.relayer.online/ ), based on a cross-platform Deep Learning segmentation architecture specifically adapted for retinal OCT images. The segmentations were read into MATLAB (The MathWorks, Natick, MA, USA) and analyzed. There was an excellent agreement between the ETDRS measurements obtained from the two algorithms. Upon visual inspection, the segmentation based on Deep Learning obtained with Relayer appeared more accurate except in one case of apparent good quality image showing interrupted segmentations in some of the B-scans. A freely available online Deep Learning segmentation tool showed good and promising performance in healthy retinas before and after cataract surgery, proving robust to optical degradation of the image from media opacities.

Diagnostics of retinal pathologies by optical coherence tomography images using artificial intelligence tools

The importance of early detection and monitoring of retinal diseases determines the relevance of the study devoted to the diagnosis of retinal pathologies by OCT images using artificial intelligence (AI) tools.The purpose is to develop algorithms for diagnosing retinal pathologies from OCT images by machine learning methods.Material and methods. The study used a dataset (20,000 eyes), publicly available on the Internet, which contains OCT images of healthy retina (5,000 eyes) and retina affected by three different pathologies (choroid neovascularization, macular edema, multiple drusen, 15,000 eyes). The retinal pathology recognition system is based on a trained neural network VGG16 (developed by a visual geometry group of Oxford University).Results. The main result of the research is the development of an algorithm, implemented on Python, for the diagnosis of retinal diseases from OCT images based on convolutional neural network AI tool. The sensitivity and selectiveness of the neural network model during the diagnosis of retinal diseases were 97 and 98%, respectively.Conclusion. AI methods used in the retinal pathology automatic detection system developed at the Helmholtz National Medical Research Center of Eye Diseases as part of automated medical decision-making system have been shown to have high potential and efficiency. In the future, this service can be used to improve the effectiveness of early diagnosis and monitoring of retinal diseases in conditions of reduced availability of primary ophthalmological care in some of the territories of the Russian Federation, including that provided at the pre-doctoral stage.

Automated detection of crystalline retinopathy via fundus photography using multistage generative adversarial networks

PurposeCrystalline retinopathy is characterized by reflective crystal deposits in the macula and is caused by various systemic conditions including hereditary, toxic, and embolic etiologies. Herein, we introduce a novel application of deep learning with a multistage generative adversarial network (GAN) to detect crystalline retinopathy using fundus photography. MethodsThe dataset comprised major classes (healthy retina, diabetic retinopathy, exudative age-related macular degeneration, and drusen) and a crystalline retinopathy class (minor set). To overcome the limited data on crystalline retinopathy, we proposed a novel multistage GAN framework. The GAN was retrained after CutMix combination by inputting the GAN-generated synthetic data as new inputs to the original training data. After the multistage CycleGAN augmented the data for crystalline retinopathy, we built a deep-learning classifier model for detection. ResultsUsing the multistage CycleGAN facilitated realistic fundus photography synthesis with the characteristic features of retinal crystalline deposits. The proposed method outperformed typical transfer learning, prototypical networks, and knowledge distillation for both multiclass and binary classifications. The final model achieved an area under the curve of the receiver operating characteristics of 0.962 for internal validation and 0.987 for external validation for the detection of crystalline retinopathy. ConclusionWe introduced a deep learning approach for detecting crystalline retinopathy, a potential biomarker of underlying systemic pathological conditions. Our approach enables realistic pathological image synthesis and more accurate prediction of crystalline retinopathy, an essential but minor retinal condition.

Robust expression of the TRPC1 channel associated with photoreceptor loss in the rat retina

Baseline intracellular calcium levels are significantly higher in neuronal and glial cells of rat retinas with retinitis pigmentosa (RP). Although this situation could initiate multiple detrimental pathways that lead to cell death, we considered the possibility of TRPC1 being involved in maintaining calcium homeostasis in the retina by acting as a component of store-operated calcium (SOC) channels with special relevance during photoreceptor degeneration. In this study, we examined by Western blot the expression of TRPC1 in healthy control rat retinas (Sprague-Dawley, SD) and retinas with RP (P23H-1 rats). We also analyzed its specific cellular distribution by immunofluorescence to recognize changes during neurodegeneration and to determine whether its presence is consistent with high basal calcium levels and cellular survival in degenerating retinas. We found that TRPC1 immunostaining was widely distributed across the retina in both rat strains, SD and P23H, and its expression levels significantly increased in the retinas with advanced degeneration compared to the age-control SD rats. In the outer retina, TRPC1 immunoreactivity was distributed in pigment epithelium cells, the photoreceptor inner segments of older animals, and the outer plexiform layer. In the inner retina, TRPC1 labeling was detected in horizontal cells, specific somata of bipolar and amacrine cells, and cellular processes in all the strata of the inner plexiform layer. Somata and processes were also highly immunoreactive in the ganglion cell layer and astrocytes in the nerve fiber layer in all animals. In the P23H rat retinas, the TRPC1 distribution pattern changed according to advancing photoreceptor degeneration and the gliosis reaction, with TRPC1 immunoreactive Müller cells mainly in advanced stages of disease. The cellular TRPC1 immunoreactivity found in this work suggests different mechanisms of activation of these channels depending on the cell type. Furthermore, the results support the idea that photoreceptor loss due to RP is associated with robust TRPC1 protein expression in the rat inner retina and raise the possibility of TRPC1 channels contributing to maintain high basal calcium levels during neurodegeneration and/or maintenance processes of the inner retina.

Macular retinal circulation in healthy eyes examined by optical coherence tomography angiography extended interscan time analysis.

To examine whether extended interscan time (IST) on optical coherence tomography angiography (OCTA) can detect slow retinal blood flow, which is undetectable on default IST, in the healthy macula. OCTA (OCT-A1, Canon Inc.) scanning of a macular area measuring 4 × 4 mm2 of 14 healthy eyes of 14 healthy volunteers with no history or evidence of systemic and macular diseases was performed. ISTs were set at 7.6 (IST7.6, default setting), 12.0 (IST12.0), and 20.6 msec (IST20.6). Ten OCTA images were acquired at each IST, and an averaged image was created. For each averaged OCTA image obtained at IST7.6, IST12.0, and IST20.6, we defined the area surrounded by the innermost capillary ring as the foveal avascular zone (FAZ). We qualitatively evaluated the delineation of the capillaries consisting of the FAZ and quantitatively measured the FAZ area at each IST. Extensions from IST7.6 to IST12.0 and IST20.6 could newly delineated retinal capillaries that were undetectable at the default IST; new capillaries were detected in 10 (71%) eyes at IST12.0 and 11 (78%) eyes at IST20.0. The FAZ areas were 0.334 ± 0.137 mm2, 0.320 ± 0.132 mm2, and 0.319 ± 0.129 mm2 for IST7.6, IST12.0, and IST20.0, respectively; the FAZ areas at IST12.0 and IST20.0 were significantly decreased compared with that at IST7.6 (p = 0.004 and 0.002, respectively). In OCTA for healthy participants, extensions of the ISTs newly detected retinal capillaries with slow blood flow around FAZ. The FAZ shapes varied with different ISTs. Thus, the blood flow dynamics are not physiologically uniform around FAZ. Compared with conventional OCTA, this protocol enables a more detailed evaluation of retinal circulation and provides a better understanding of the physiological circulatory status of the healthy retina, and may enable the assessment of circulation in the very early stages in diseased eyes.

Diabetic Retinopathy Severity Identification Using 3D Dual-Domain Attention Approach

The diabetic retinopathy (DR) is one of prominent reason of visual impairment among the people around the globe suffers from diabetes. Early and timely diagnosis of this problem can minimise the risk of proliferated diabetic retinopathy. Diabetes is caused by persistently high blood glucose levels, which leads to blood vessel aggravations and vision loss. Therefore, it becomes important to classify DR stages. An automated system for this purpose contains several phases like identification and classification of DR stages in fundus images. Deep learning techniques based on extraction of features and automatic extraction of features with a hybrid network have been presented for diabetic retinopathy detection. This method effectively identify diabetic retinopathy identification from the chest region by using the 3D Dual-Domain Attention Approach. The dual-domain attention module propised learns local and global information in spatial and context domains from encoding feature maps in Unet. Our attention module generates refined feature maps from the enlarged reception field at every stage by attention mechanisms and residual learning to focus on complex tumor regions. Experimental results show that the proposed network can identify the DR stages with high accuracy. The proposed method attains an F1-score of 91.34%, precision of 92.34%, accuracy of 98.65%, on the healthy retina, stage 1, stage 2, and stage 3 fundus images. Compared with other models, our proposed network achieves comparable performance.

OCT-based deep-learning models for the identification of retinal key signs

A new system based on binary Deep Learning (DL) convolutional neural networks has been developed to recognize specific retinal abnormality signs on Optical Coherence Tomography (OCT) images useful for clinical practice. Images from the local hospital database were retrospectively selected from 2017 to 2022. Images were labeled by two retinal specialists and included central fovea cross-section OCTs. Nine models were developed using the Visual Geometry Group 16 architecture to distinguish healthy versus abnormal retinas and to identify eight different retinal abnormality signs. A total of 21,500 OCT images were screened, and 10,770 central fovea cross-section OCTs were included in the study. The system achieved high accuracy in identifying healthy retinas and specific pathological signs, ranging from 93 to 99%. Accurately detecting abnormal retinal signs from OCT images is crucial for patient care. This study aimed to identify specific signs related to retinal pathologies, aiding ophthalmologists in diagnosis. The high-accuracy system identified healthy retinas and pathological signs, making it a useful diagnostic aid. Labelled OCT images remain a challenge, but our approach reduces dataset creation time and shows DL models’ potential to improve ocular pathology diagnosis and clinical decision-making.

Image-based insilico investigation of hemodynamics and biomechanics in healthy and diabetic human retinas

Retinal hemodynamics and biomechanics play a significant role in understanding the pathophysiology of several ocular diseases. However, these parameters are significantly affected due to changed blood vessel morphology ascribed to pathological conditions, particularly diabetes. In this study, an image-based computational fluid dynamics (CFD) model is applied to examine the effects of changed vascular morphology due to diabetes on blood flow velocity, vorticity, wall shear stress (WSS), and oxygen distribution and compare it with healthy. The 3D patient-specific vascular architecture of diabetic and healthy retina is extracted from Optical Coherence Tomography Angiography (OCTA) images and fundus to extract the capillary level information. Further, Fluid-structure interaction (FSI) simulations have been performed to compare the induced tissue stresses in diabetic and healthy conditions. Results illustrate that most arterioles possess higher velocity, vorticity, WSS, and lesser oxygen concentration than arteries for healthy and diabetic cases. However, an opposite trend is observed for venules and veins. Comparisons show that, on average, the blood flow velocity in the healthy case decreases by 42 % in arteries and 21 % in veins, respectively, compared to diabetic. In addition, the WSS and von Mises stress (VMS) in healthy case decrease by 49 % and 72 % in arteries and by 6 % and 28 % in veins, respectively, when compared with diabetic, making diabetic blood vessels more susceptible to wall rupture and tissue damage. The in-silico results may help predict the possible abnormalities region early, helping the ophthalmologists use these estimates as prognostic tools and tailor patient-specific treatment plans.

Depleted hexokinase1 and lack of AMPKα activation favor OXPHOS-dependent energetics in retinoblastoma tumors

Lack of retinoblastoma (Rb) protein causes aggressive intraocular retinal tumors in children. Recently, Rb tumors have been shown to have a distinctly altered metabolic phenotype, such as reduced expression of glycolytic pathway proteins alongside altered pyruvate and fatty acid levels. In this study, we demonstrate that loss of hexokinase 1(HK1) in tumor cells rewires their metabolism allowing enhanced oxidative phosphorylation-dependent energy production. We show that rescuing HK1 or retinoblastoma protein 1 (RB1) in these Rb cells reduced cancer hallmarks such as proliferation, invasion, and spheroid formation and increased their sensitivity to chemotherapy drugs. Induction of HK1 was accompanied by a metabolic shift of the cells to glycolysis and a reduction in mitochondrial mass. Cytoplasmic HK1 bound Liver Kinase B1 and phosphorylated AMP-activated kinase-α (AMPKα Thr172), thereby reducing mitochondria-dependent energy production. We validated these findings in tumor samples from Rb patients compared to age-matched healthy retinae. HK1 or RB1 expression in Rb-/- cells led to a reduction in their respiratory capacity and glycolytic proton flux. HK1 overexpression reduced tumor burden in an intraocular tumor xenograft model. AMPKα activation by AICAR also enhanced the tumoricidal effects of the chemotherapeutic drug topotecan in vivo. Therefore, enhancing HK1 or AMPKα activity can reprogram cancer metabolism and sensitize Rb tumors to lower doses of existing treatments, a potential therapeutic modality for Rb.

Clinical and Molecular Aspects of C2orf71/PCARE in Retinal Diseases.

Mutations in the photoreceptor-specific C2orf71 gene (also known as photoreceptor cilium actin regulator protein PCARE) cause autosomal recessive retinitis pigmentosa type 54 and cone-rod dystrophy. No treatments are available for patients with C2orf71 retinal ciliopathies exhibiting a severe clinical phenotype. Our understanding of the disease process and the role of PCARE in the healthy retina significantly limits our capacity to transfer recent technical developments into viable therapy choices. This study summarizes the current understanding of C2orf71-related retinal diseases, including their clinical manifestations and an unclear genotype-phenotype correlation. It discusses molecular and functional studies on the photoreceptor-specific ciliary PCARE, focusing on the photoreceptor cell and its ciliary axoneme. It is proposed that PCARE is an actin-associated protein that interacts with WASF3 to regulate the actin-driven expansion of the ciliary membrane during the development of a new outer segment disk in photoreceptor cells. This review also introduces various cellular and animal models used to model these diseases and provides an overview of potential treatments.

Reduced folate carrier 1 is present in retinal microvessels and crucial for the inner blood retinal barrier integrity

BackgroundReduced folate carrier 1 (RFC1; SLC19a1) is the main responsible transporter for the B9 family of vitamins named folates, which are essential for normal tissue growth and development. While folate deficiency resulted in retinal vasculopathy, the expression and the role of RFC1 in blood-retinal barrier (BRB) are not well known.MethodsWe used whole mount retinas and trypsin digested microvessel samples of adult mice. To knockdown RFC1, we delivered RFC1-targeted short interfering RNA (RFC1-siRNA) intravitreally; while, to upregulate RFC1 we delivered lentiviral vector overexpressing RFC1. Retinal ischemia was induced 1-h by applying FeCl3 to central retinal artery. We used RT-qPCR and Western blotting to determine RFC1. Endothelium (CD31), pericytes (PDGFR-beta, CD13, NG2), tight-junctions (Occludin, Claudin-5 and ZO-1), main basal membrane protein (Collagen-4), endogenous IgG and RFC1 were determined immunohistochemically.ResultsOur analyses on whole mount retinas and trypsin digested microvessel samples of adult mice revealed the presence of RFC1 in the inner BRB and colocalization with endothelial cells and pericytes. Knocking down RFC1 expression via siRNA delivery resulted in the disintegration of tight junction proteins and collagen-4 in twenty-four hours, which was accompanied by significant endogenous IgG extravasation. This indicated the impairment of BRB integrity after an abrupt RFC1 decrease. Furthermore, lentiviral vector-mediated RFC1 overexpression resulted in increased tight junction proteins and collagen-4, confirming the structural role of RFC1 in the inner BRB. Acute retinal ischemia decreased collagen-4 and occludin levels and led to an increase in RFC1. Besides, the pre-ischemic overexpression of RFC1 partially rescued collagen-4 and occludin levels which would be decreased after ischemia.ConclusionIn conclusion, our study clarifies the presence of RFC1 protein in the inner BRB, which has recently been defined as hypoxia–immune-related gene in other tissues and offers a novel perspective of retinal RFC1. Hence, other than being a folate carrier, RFC1 is an acute regulator of the inner BRB in healthy and ischemic retinas.

Electrophysiological effects of hyperbaric oxygen treatment on the healthy retina

Purpose The study aimed to investigate the electrophysiological effects of hyperbaric oxygen treatment (HBOT) on the retina after ten sessions in healthy eyes. Methods This prospective, interventional study evaluated forty eyes of twenty patients who were treated with HBOT of ten sessions with the diagnosis of an extraocular health problem. All patients underwent a complete ophthalmologic examination, including assessments of best-corrected visual acuity (BCVA), slit-lamp and pupil-dilated fundus examinations, full-field electroretinography (ffERG) measurements before and after HBOT within 24 h of the 10th session. The ffERG was recorded according to the International Society for Clinical Electrophysiology of Vision protocol using the RETI-port system. Results The mean age of patients was 40.5 years ranging from 20 to 59 years. Thirteen patients were administered HBOT for avascular necrosis, six patients for sudden hearing loss, and one patient for chronic osteomyelitis of the vertebra. BCVA acuity was 20/20 in all eyes. The mean spherical refractive was 0.56 dioptre (D), and the mean cylindrical refractive error was 0.75 D. Dark-adapted b-wave amplitude in 3.0 ERG was the only variable for the b-wave that showed a statistically significant decrease (p = 0.017). The amplitude of the a-waves in dark-adapted 10.0 ERG and light-adapted 3.0 ERG reduced significantly (p = 0.024, p = 0.025). The amplitude of N 1-P 1 in light-adapted 30 Hz Flicker ERG also demonstrated a statistically significant decrease (p = 0.011). Implicit times did not differ significantly in any of the ffERG data (p > 0.05). Conclusions HBOT caused the deterioration of a-wave and b-wave amplitudes in ffERG after ten treatment sessions. The results showed that photoreceptors were adversely affected in the short term after HBOT treatment.

The single-cell landscape of alternative transcription start sites of diabetic retina

More than half of mammalian protein-coding genes have multiple transcription start sites. Alternative transcription start site (TSS) modulate mRNA stability, localization, and translation efficiency on post-transcription level, and even generate novel protein isoforms. However, differential TSS usage among cell types in healthy and diabetic retina remains poorly characterized. In this study, by using 5′-tag-based single-cell RNA sequencing, we identified cell type-specific alternative TSS events and key transcription factors for each of retinal cell types. We observed that lengthening of 5′- UTRs in retinal cell types are enriched for multiple RNA binding protein binding sites, including splicing regulators Rbfox1/2/3 and Nova1. Furthermore, by comparing TSS expression between healthy and diabetic retina, we identified elevated apoptosis signal in Müller glia and microglia, which can be served as a putative early sign of diabetic retinopathy. By measuring 5′UTR isoforms in retinal single-cell dataset, our work provides a comprehensive panorama of alternative TSS and its potential consequence related to post-transcriptional regulation. We anticipate our assay can not only provide insights into cellular heterogeneity driven by transcriptional initiation, but also open up the perspectives for identification of novel diagnostic indexes for diabetic retinopathy.

Corneal Collagen Cross-Linking for Late Onset Progressive Keratoconus in Iridocorneal Endothelial Syndrome.

The aim of this study was to report the first case of successful use of corneal collagen cross-linking (CXL) to halt the progression of keratoconus in a patient with concurrent iridocorneal endothelial (ICE) syndrome. A 30-year-old White man was referred to our subspecialty corneal clinic for further investigation of right corectopia. The patient was asymptomatic and was otherwise fit. Slit-lamp examination revealed a right oval-shaped pupil decentered superiorly, a transillumination defect at the 5-o'clock position, minimal gutta-like changes in the corneal endothelium, and few inferior peripheral anterior synechiae. Dilated fundoscopy was normal in both eyes, with healthy optic discs, maculae, and peripheral retinae. Specular microscopy and slit-lamp findings suggested ICE syndrome. Subsequent investigation with corneal tomography showed progressive signs of inferior corneal ectasia with steepening, and thinning in the right eye, consistent with keratoconus. The left eye was unremarkable. Epithelium-off accelerated corneal CXL was performed in the affected eye. Early post-CXL follow-up (1 week) was unremarkable, and further follow-ups were arranged at 3, 6, 12, and 24 months, respectively. In subsequent reviews, the patient's vision and corneal tomography findings were stable. We describe the first case of corneal CXL for progressive keratoconus with ICE syndrome. co-existing keratoconus and ICE syndrome can occur, and corneal cross-linking was used successfully in this case to halt keratoconus progression. However, further studies will need to establish the impact of epithelium-off corneal cross-linking, especially in more severely affected eyes.

Deep-learning automated quantification of longitudinal OCT scans demonstrates reduced RPE loss rate, preservation of intact macular area and predictive value of isolated photoreceptor degeneration in geographic atrophy patients receiving C3 inhibition treatment

ObjectiveTo evaluate the role of automated optical coherence tomography (OCT) segmentation, using a validated deep-learning model, for assessing the effect of C3 inhibition on the area of geographic atrophy (GA);...

Abstract 4273: Integration with benchmark data of paired bulk and single-cell RNA sequencing data substantially improves the accuracy of bulk tissue deconvolution

Abstract The accuracy of current deconvolution methods largely relies on the quality of cell-type expression references. However, single-cell (sc) and single-nuclei (sn) RNA-seq data used for building the reference are usually generated from independent studies that are distinct from the bulk RNA-seq data to be deconvolved. This study design inherently introduces technical confounding factors as unwanted variations, which is not fully addressed by current methods. To evaluate the impact of this variation on deconvolution accuracy, we generated a benchmark dataset where bulk and snRNA-seq profiling were performed from the same aliquot of single-nuclei that were extracted from 24 healthy retina samples. All donor eye samples were collected within six hours post-mortem and were absent of any disease. This study design guarantees the matched sequencing data to present the same cell-type compositions, so that cross-platform technical artifacts become the remaining confounding factor. We used the benchmark dataset to evaluate the performance of seven current deconvolution methods and found they performed much worse in matched real-bulk data than in matched pseudo-bulks that were summations of the single-cell data. This finding suggests that none of these methods have fully addressed the major technical artifacts between bulk and single-cell sequencing platforms. We therefore propose DeMix.SC, a new deconvolution framework that optimizes deconvolution parameters using a small set of matched bulk and sc/snRNA-seq data from the same tissue type. DeMix.SC includes two major steps. First, we measure the technical variations across genes and across platforms using the benchmark data. Second, we introduce a new weight function for each gene that produces a ranking order that accounts for both the platform-specific technical variations and cell-type specific expressions at gene level. Using the benchmark data for retina, we applied DeMix.SC to previously published human retinal RNA-seq data from 523 individuals with different stages of age-related macular degeneration (AMD). We observed that DeMix.SC can accurately capture the cell-type composition shifts in the AMD retina. DeMix.SC revealed a significant drop of rod cells as well as increased astrocytes, bipolar cells, and Müller cells in the AMD retina compared to the non-AMD group. The proportion changes of the later three minor cell types were not identified by other methods, while DeMix.SC could reveal such tendency. In summary, DeMix.SC integrates benchmark data to improve the deconvolution accuracy in retina samples. Our method is generic and can be applied to other disease conditions, such as deciphering the cell-type heterogeneity in cancer. We expect DeMix.SC will help revolutionize the downstream cell-type specific analysis of bulk RNA-seq data and identify cellular targets of human diseases. Citation Format: Shuai Guo, Xuesen Cheng, Andrew Koval, Shuangxi Ji, Qingnan Liang, Yumei Li, Leah A. Owen, Ivana K. Kim, John Weinstein, Scott Kopetz, John Paul Shen, Margaret M. DeAngelis, Rui Chen, Wenyi Wang. Integration with benchmark data of paired bulk and single-cell RNA sequencing data substantially improves the accuracy of bulk tissue deconvolution. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4273.

Posttranslational modifications of proteins in diseased retina.

Posttranslational modifications (PTMs) are known to constitute a key step in protein biosynthesis and in the regulation of protein functions. Recent breakthroughs in protein purification strategies and current proteome technologies make it possible to identify the proteomics of healthy and diseased retinas. Despite these advantages, the research field identifying sets of posttranslationally modified proteins (PTMomes) related to diseased retinas is significantly lagging, despite knowledge of the major retina PTMome being critical to drug development. In this review, we highlight current updates regarding the PTMomes in three retinal degenerative diseases-namely, diabetic retinopathy (DR), glaucoma, and retinitis pigmentosa (RP). A literature search reveals the necessity to expedite investigations into essential PTMomes in the diseased retina and validate their physiological roles. This knowledge would accelerate the development of treatments for retinal degenerative disorders and the prevention of blindness in affected populations.

Optic disc and retinal vascular features in first 6 years of Chinese children.

Retinal microvasculature plays an important role in children's fundus lesions and even in their later life. However, little was known on the features of normal retina in early life. The purpose of this study was to explore the normal retinal features in the first 6 years of life and provide information for future research. Children, aged from birth to 6 years old and diagnosed with various unilateral ocular diseases were included. Venous phase fundus fluorescein angiography images with the optic disc at the center were collected. Based on the ResUNet convolutional neural network, optic disc and retinal vascular features in the posterior retina were computed automatically. A total of 146 normal eyes of 146 children were included. Among different age groups, no changes were shown in the optic disc diameter (y = -0.00002x + 1.362, R2 = 0.025, p = 0.058). Retinal vessel density and fractal dimension are linearly and strongly correlated (r = 0.979, p < 0.001). Older children had smaller value of fractal dimension (y = -0.000026x + 1.549, R2 = 0.075, p = 0.001) and narrower vascular caliber if they were less than 3 years old (y = -0.008x + 84.861, R2 = 0.205, p < 0.001). No differences were in the density (y = -0.000007x + 0.134, R2 = 0.023, p = 0.067) and the curvature of retinal vessels (lnC = -0.00001x - 4.657, R2 = 0.001, p = 0.667). Age and gender did not impact the optic disc diameter, vessel density, and vessel curvature significantly in this group of children. Trends of decreased vessel caliber in the first 3 years of life and decreased vessel complexity with age were observed. The structural characteristics provide information for future research to better understand the developmental origin of the healthy and diseased retina.