Deep Learning-Based Automated Detection of Retinal Breaks and Detachments on Fundus Photography.

Purpose: The purpose of this study was to develop a deep learning algorithm, to detect retinal breaks and retinal detachments on ultra-widefield fundus (UWF) optos images using artificial intelligence (AI). Methods: Optomap UWF images of the database were annotated to four groups by two retina specialists: (1) retinal breaks without detachment, (2) retinal breaks with retinal detachment, (3) retinal detachment without visible retinal breaks, and (4) a combination of groups 1 to 3. The fundus image data set was split into a training set and an independent test set following an 80% to 20% ratio. Image preprocessing methods were applied. An EfficientNet classification model was trained with the training set and evaluated with the test set. Results: A total of 2489 UWF images were included into the dataset, resulting in a training set size of 2008 UWF images and a test set size of 481 images. The classification models achieved an area under the receiver operating characteristic curve (AUC) on the testing set of 0.975 regarding lesion detection, an AUC of 0.972 for retinal detachment and an AUC of 0.913 for retinal breaks. Conclusions: A deep learning system to detect retinal breaks and retinal detachment using UWF images is feasible and has a good specificity. This is relevant for clinical routine as there can be a high rate of missed breaks in clinics. Future clinical studies will be necessary to evaluate the cost-effectiveness of applying such an algorithm as an automated auxiliary tool in a large practices or tertiary referral centers. Translational Relevance: This study demonstrates the relevance of applying AI in diagnosing peripheral retinal breaks in clinical routine in UWF fundus images.

Cataract-1K Dataset for Deep-Learning-Assisted Analysis of Cataract Surgery Videos.

In recent years, the landscape of computer-assisted interventions and post-operative surgical video analysis has been dramatically reshaped by deep-learning techniques, resulting in significant advancements in surgeons' skills, operation room management, and overall surgical outcomes. However, the progression of deep-learning-powered surgical technologies is profoundly reliant on large-scale datasets and annotations. In particular, surgical scene understanding and phase recognition stand as pivotal pillars within the realm of computer-assisted surgery and post-operative assessment of cataract surgery videos. In this context, we present the largest cataract surgery video dataset that addresses diverse requisites for constructing computerized surgical workflow analysis and detecting post-operative irregularities in cataract surgery. We validate the quality of annotations by benchmarking the performance of several state-of-the-art neural network architectures for phase recognition and surgical scene segmentation. Besides, we initiate the research on domain adaptation for instrument segmentation in cataract surgery by evaluating cross-domain instrument segmentation performance in cataract surgery videos. The dataset and annotations are publicly available in Synapse.

Prediction of chronic central serous chorioretinopathy through combined manual annotation and AI-assisted volume measurement of flat irregular pigment epithelium.

INTRODUCTION: The aim of this study is to investigate the role of an artificial intelligence (AI)-developed OCT program to predict the clinical course of central serous chorioretinopathy (CSC ) based on baseline pigment epithelium detachment (PED) features. METHODS: Single-center, observational study with a retrospective design. Treatment-naïve patients with acute CSC and chronic CSC were recruited and OCTs were analyzed by an AI-developed platform (Discovery OCT Fluid and Biomarker Detector, RetinAI AG, Switzerland), providing automatic detection and volumetric quantification of PEDs. Flat irregular PED presence was annotated manually and afterwards measured by the AI program automatically. RESULTS: 115 eyes of 101 patients with CSC were included, of which 70 were diagnosed with chronic CSC and 45 with acute CSC. It was found that patients with baseline presence of foveal flat PEDs and multiple flat foveal and extrafoveal PEDs had a higher chance of developing chronic form. AI-based volumetric analysis revealed no significant differences between the groups. CONCLUSIONS: While more evidence is needed to confirm the effectiveness of AI-based PED quantitative analysis, this study highlights the significance of identifying flat irregular PEDs at the earliest stage possible in patients with CSC, to optimize patient management and long-term visual outcomes.

Macrophages coordinate immune response to laser-induced injury via extracellular traps.

BACKGROUND: Retinal degeneration results from disruptions in retinal homeostasis due to injury, disease, or aging and triggers peripheral leukocyte infiltration. Effective immune responses rely on coordinated actions of resident microglia and recruited macrophages, critical for tissue remodeling and repair. However, these phagocytes also contribute to chronic inflammation in degenerated retinas, yet the precise coordination of immune response to retinal damage remains elusive. Recent investigations have demonstrated that phagocytic cells can produce extracellular traps (ETs), which are a source of self-antigens that alter the immune response, which can potentially lead to tissue injury. METHODS: Innovations in experimental systems facilitate real-time exploration of immune cell interactions and dynamic responses. We integrated in vivo imaging with ultrastructural analysis, transcriptomics, pharmacological treatments, and knockout mice to elucidate the role of phagocytes and their modulation of the local inflammatory response through extracellular traps (ETs). Deciphering these mechanisms is essential for developing novel and enhanced immunotherapeutic approaches that can redirect a specific maladaptive immune response towards favorable wound healing in the retina. RESULTS: Our findings underscore the pivotal role of innate immune cells, especially macrophages/monocytes, in regulating retinal repair and inflammation. The absence of neutrophil and macrophage infiltration aids parenchymal integrity restoration, while their depletion, particularly macrophages/monocytes, impedes vascular recovery. We demonstrate that macrophages/monocytes, when recruited in the retina, release chromatin and granular proteins, forming ETs. Furthermore, the pharmacological inhibition of ETosis support retinal and vascular repair, surpassing the effects of blocking innate immune cell recruitment. Simultaneously, the absence of ETosis reshapes the inflammatory response, causing neutrophils, helper, and cytotoxic T-cells to be restricted primarily in the superficial capillary plexus instead of reaching the damaged photoreceptor layer. CONCLUSIONS: Our data offer novel insights into innate immunity's role in responding to retinal damage and potentially help developing innovative immunotherapeutic approaches that can shift the immune response from maladaptive to beneficial for retinal regeneration.

Dupilumab-associated ocular surface disease is characterized by a shift from Th2/Th17 toward Th1/Th17 inflammation.

BACKGROUND: Dupilumab is used for the treatment of atopic dermatitis (AD). Approximately one third of AD patients develop a dupilumab-associated ocular surface disease (DAOSD), of which the pathomechanism is poorly understood. This study aimed at investigating inflammatory markers in tear fluids of patients on dupilumab therapy. METHODS: Tear fluids were collected from AD patients with DAOSD (ADwDAOSD), AD patients without DAOSD (ADw/oDAOSD), and non-AD patients before and during dupilumab therapy, and analyzed using a specialized proteomic approach quantifying inflammatory markers. The ocular surface microbiome was determined by next generation sequencing technology. RESULTS: Upon dupilumab therapy, an upregulation of 31 inflammatory markers was observed in DAOSD tear fluids compared to baseline in AD patients. While IL-12B was upregulated in both ADwDAOSD and ADw/oDAOSD groups, the pattern of inflammatory markers significantly differed between groups and over time. In the ADwDAOSD group, a shift from a mixed Th2/Th17 pattern at baseline toward a Th1/Th17 profile under dupilumab was observed. Furthermore, an upregulation of remodeling and fibrosis markers was seen in DAOSD. Semantic map and hierarchical cluster analyses of baseline marker expression revealed four clusters distinguishing between AD and non-AD as well as ADwDAOSD and ADw/oDAOSD patient groups. In a pilot study, dupilumab therapy was associated with a decrease in richness of the ocular surface microbiome. CONCLUSIONS: DAOSD is characterized by a Th1/Th17 cytokine profile and an upregulation of markers known to promote remodeling and fibrosis. The expression pattern of inflammatory markers in tear fluids at baseline might serve as a prognostic factor for DAOSD.

DeepPyramid+: medical image segmentation using Pyramid View Fusion and Deformable Pyramid Reception.

PURPOSE: Semantic segmentation plays a pivotal role in many applications related to medical image and video analysis. However, designing a neural network architecture for medical image and surgical video segmentation is challenging due to the diverse features of relevant classes, including heterogeneity, deformability, transparency, blunt boundaries, and various distortions. We propose a network architecture, DeepPyramid+, which addresses diverse challenges encountered in medical image and surgical video segmentation. METHODS: The proposed DeepPyramid+ incorporates two major modules, namely "Pyramid View Fusion" (PVF) and "Deformable Pyramid Reception" (DPR), to address the outlined challenges. PVF replicates a deduction process within the neural network, aligning with the human visual system, thereby enhancing the representation of relative information at each pixel position. Complementarily, DPR introduces shape- and scale-adaptive feature extraction techniques using dilated deformable convolutions, enhancing accuracy and robustness in handling heterogeneous classes and deformable shapes. RESULTS: Extensive experiments conducted on diverse datasets, including endometriosis videos, MRI images, OCT scans, and cataract and laparoscopy videos, demonstrate the effectiveness of DeepPyramid+ in handling various challenges such as shape and scale variation, reflection, and blur degradation. DeepPyramid+ demonstrates significant improvements in segmentation performance, achieving up to a 3.65% increase in Dice coefficient for intra-domain segmentation and up to a 17% increase in Dice coefficient for cross-domain segmentation. CONCLUSIONS: DeepPyramid+ consistently outperforms state-of-the-art networks across diverse modalities considering different backbone networks, showcasing its versatility. Accordingly, DeepPyramid+ emerges as a robust and effective solution, successfully overcoming the intricate challenges associated with relevant content segmentation in medical images and surgical videos. Its consistent performance and adaptability indicate its potential to enhance precision in computerized medical image and surgical video analysis applications.

Functional and Morphological Outcomes after Trabeculectomy and Deep Sclerectomy-Results from a Monocentric Registry Study.

The aim of this study was to compare the effectiveness of trabeculectomy (TE) and deep sclerectomy (DS) in lowering intraocular pressure (IOP) and thereby preserving visual field and peripapillary retinal nerve fiber layer (RNFL) tissue in primary open-angle glaucoma (POAG) cases. IOP, number of IOP-lowering medications, visual acuity, mean defect of standard automated perimetry, and mean peripapillary RNFL thickness were retrospectively collected and followed up for 3 years after surgery. TE was performed in 104 eyes and DS in 183 eyes. Age, gender, laterality, IOP, number of medications, visual acuity, perimetry mean defect, and peripapillary RNFL thickness were equally distributed at baseline. Mean IOP decreased from 23.8 ± 1.4 mmHg and 23.1 ± 0.4 mmHg to 13.4 ± 0.6 mmHg (p < 0.001) and 15.4 ± 0.7 mmHg (p = 0.001) in the TE and DS groups, respectively. Mean defect remained stable (TE: -11.5 ± 0.9 dB to -12.0 ± 1.1 (p = 0.090); DS: -10.5 ± 0.9 dB to -11.0 ± 1.0 dB (p = 0.302)), while mean peripapillary RNFL thickness showed further deterioration during follow-up (TE group: 64.4 ± 2.1 µm to 59.7 ± 3.5 µm (p < 0.001); DS group: 64.9 ± 1.9 µm to 58.4 ± 2.1 µm (p < 0.001)). Both TE and DS were comparably effective concerning postoperative reduction in IOP and medication. However, glaucoma disease further progressed during follow-up.

BASELINE SPECTRAL DOMAIN OPTICAL COHERENCE TOMOGRAPHIC RETINAL LAYER FEATURES IDENTIFIED BY ARTIFICIAL INTELLIGENCE PREDICT THE COURSE OF CENTRAL SEROUS CHORIORETINOPATHY.

PURPOSE: To identify optical coherence tomography (OCT) features to predict the course of central serous chorioretinopathy (CSC) with an artificial intelligence-based program. METHODS: Multicenter, observational study with a retrospective design. Treatment-naïve patients with acute CSC and chronic CSC were enrolled. Baseline OCTs were examined by an artificial intelligence-developed platform (Discovery OCT Fluid and Biomarker Detector, RetinAI AG, Switzerland). Through this platform, automated retinal layer thicknesses and volumes, including intaretinal and subretinal fluid, and pigment epithelium detachment were measured. Baseline OCT features were compared between acute CSC and chronic CSC patients. RESULTS: One hundred and sixty eyes of 144 patients with CSC were enrolled, of which 100 had chronic CSC and 60 acute CSC. Retinal layer analysis of baseline OCT scans showed that the inner nuclear layer, the outer nuclear layer, and the photoreceptor-retinal pigmented epithelium complex were significantly thicker at baseline in eyes with acute CSC in comparison with those with chronic CSC ( P < 0.001). Similarly, choriocapillaris and choroidal stroma and retinal thickness (RT) were thicker in acute CSC than chronic CSC eyes ( P = 0.001). Volume analysis revealed average greater subretinal fluid volumes in the acute CSC group in comparison with chronic CSC ( P = 0.041). CONCLUSION: Optical coherence tomography features may be helpful to predict the clinical course of CSC. The baseline presence of an increased thickness in the outer retinal layers, choriocapillaris and choroidal stroma, and subretinal fluid volume seems to be associated with acute course of the disease.

Assessment of choriocapillaris and choroidal vascular changes in posterior uveitis using swept-source wide-field optical coherence tomography angiography.

PURPOSE: To evaluate choriocapillaris (CC) and choroidal vascular changes in patients with posterior uveitis using swept-source (SS) wide-field optical coherence tomography angiography (OCTA). METHOD: Consecutive patients with posterior uveitis were evaluated using 3×3 mm and 12×12 mm OCTA scan patterns and montage images of 5×12×12 mm or 2×15×9 mm, covering approximately 70°-90° of the retina. The images were quantitatively and qualitatively analysed and compared with healthy controls. RESULTS: Eighty-six eyes of 56 patients with posterior uveitis (mean age 45.2±19.9 years; 58.9% female), and 38 eyes of 19 age-matched healthy controls (57.9% female) were included. The mean perfusion density (PD) in 3×3 mm and 12×12 mm CC scans was significantly lower in eyes with posterior uveitis compared with those of healthy controls. However, no significant difference in the mean PD of choroidal scans was found comparing eyes with posterior uveitis and healthy controls. The mean PD in eyes with active disease was significantly higher compared with the inactive eyes on 12×12 mm choroidal scans (55.61% vs 51.25%, p=0.02), while no difference was found in the CC slabs. CONCLUSION: CC and choroidal assessment using OCTA provides useful information in patients with posterior uveitis. SS-OCTA metrics of the CC and choroidal slabs are promising tools in uveitis patients in the future. TRIAL REGISTRATION NUMBER: NCT02811536.

Proliferative vitreoretinopathy: an update on the current and emerging treatment options.

Proliferative vitreoretinopathy (PVR) remains the main cause of failure in retinal detachment (RD) surgery and a demanding challenge for vitreoretinal surgeons. Despite the large improvements in surgical techniques and a better understanding of PVR pathogenesis in the last years, satisfactory anatomical and visual outcomes have not been provided yet. For this reason, several different adjunctive pharmacological agents have been investigated in combination with surgery. In this review, we analyze the current and emerging adjunctive treatment options for the management of PVR and we discuss their possible clinical application and beneficial role in this subgroup of patients.

Differences Between Keratometry and Total Keratometry Measurements in a Large Dataset Obtained With a Modern Swept Source Optical Coherence Tomography Biometer.

PURPOSE: This study aimed to explore the concept of total keratometry (TK) by analyzing extensive international datasets representing diverse ethnic backgrounds. The primary objective was to quantify the disparities between traditional keratometry (K) and TK values in normal eyes and assess their impact on intraocular lens (IOL) power calculations using various formulas. DESIGN: Retrospective multicenter intra-instrument reliability analysis. METHODS: The study involved the analysis of biometry data collected from ten international centers across Europe, the United States, and Asia. Corneal power was expressed as equivalent power and astigmatic vector components for both K and TK values. The study assessed the influence of these differences on IOL power calculations using different formulas. The results were analyzed and plotted using Bland-Altman and double angle plots. RESULTS: The study encompassed a total of 116,982 measurements from 57,862 right eyes and 59,120 left eyes. The analysis revealed a high level of agreement between K and TK values, with 93.98% of eyes exhibiting an absolute difference of 0.25 D or less. Astigmatism vector differences exceeding 0.25 D and 0.50 D were observed in 39.43% and 1.08% of eyes, respectively. CONCLUSIONS: This large-scale study underscores the similarity between mean K and TK values in healthy eyes, with rare clinical implications for IOL power calculation. Noteworthy differences were observed in astigmatism values between K and TK. Future investigations should delve into the practicality of TK values for astigmatism correction and their implications for surgical outcomes.

PRESERFLO MicroShunt implantation versus trabeculectomy for primary open-angle glaucoma: a two-year follow-up study.

BACKGROUND: To compare the intermediate-term efficacy of PRESERFLO (PF) MicroShunt implantation with trabeculectomy (TE) in patients with primary open-angle glaucoma, focusing on longitudinal changes of functional and structural parameters. METHODS: This retrospective comparative study included 104 eyes of 104 patients who underwent TE and 83 eyes of 83 patients that underwent PF implantation between January 2019 and December 2020, with a minimum follow-up of two years. Baseline and postoperative intraocular pressure (IOP), number of IOP-lowering medications, visual field mean defect (MD) and peripapillary retinal nerve fibre layer (RNFL) thickness measured using optical coherence tomography were assessed and compared between groups. RESULTS: Baseline characteristics (age, sex, IOP, number of IOP-lowering medications, MD, RNFL thickness) were comparable between the two groups (all P > 0.05). During the two-year of follow-up, mean IOP decreased from 24.09 ± 1.15 mmHg and 21.67 ± 0.77 mmHg to 11.37 ± 1.13 mmHg (P < 0.001) and 15.50 ± 1.54 mmHg (P = 0.028), and the mean number of IOP-lowering medications decreased from 3.25 ± 0.14 and 3.51 ± 0.14 to 0.53 ± 0.14 (P < 0.001) and 1.06 ± 0.43 (P < 0.001) in the TE and PF groups, respectively. MD remained stable [- 11.54 ± 0.93 dB and - 11.17 ± 1.66 to - 10.67 ± 0.91 dB (P = 0.226) and - 10.40 ± 4.75 dB (P = 0.628) in the TE and PF groups, respectively] but RNFL thickness decreased continuously during follow-up [62.79 ± 1.94 µm and 62.62 ± 2.05 µm to 57.41 ± 1.81 µm (P < 0.001) and 60.22 ± 1.98 µm (P = 0.182) in the TE and PF groups, respectively]. CONCLUSION: PF implantation is comparably effective in the intermediate term in lowering IOP and reducing the use of IOP-lowering medications over a two-year follow-up period. Although visual field defects were stable, RNFL continued to decrease during postoperative follow-up.

"Application and accuracy of artificial intelligence-derived large language models in patients with age related macular degeneration".

INTRODUCTION: Age-related macular degeneration (AMD) affects millions of people globally, leading to a surge in online research of putative diagnoses, causing potential misinformation and anxiety in patients and their parents. This study explores the efficacy of artificial intelligence-derived large language models (LLMs) like in addressing AMD patients' questions. METHODS: ChatGPT 3.5 (2023), Bing AI (2023), and Google Bard (2023) were adopted as LLMs. Patients' questions were subdivided in two question categories, (a) general medical advice and (b) pre- and post-intravitreal injection advice and classified as (1) accurate and sufficient (2) partially accurate but sufficient and (3) inaccurate and not sufficient. Non-parametric test has been done to compare the means between the 3 LLMs scores and also an analysis of variance and reliability tests were performed among the 3 groups. RESULTS: In category a) of questions, the average score was 1.20 (± 0.41) with ChatGPT 3.5, 1.60 (± 0.63) with Bing AI and 1.60 (± 0.73) with Google Bard, showing no significant differences among the 3 groups (p = 0.129). The average score in category b was 1.07 (± 0.27) with ChatGPT 3.5, 1.69 (± 0.63) with Bing AI and 1.38 (± 0.63) with Google Bard, showing a significant difference among the 3 groups (p = 0.0042). Reliability statistics showed Chronbach's α of 0.237 (range 0.448, 0.096-0.544). CONCLUSION: ChatGPT 3.5 consistently offered the most accurate and satisfactory responses, particularly with technical queries. While LLMs displayed promise in providing precise information about AMD; however, further improvements are needed especially in more technical questions.

Predicting OCT biological marker localization from weak annotations.

Recent developments in deep learning have shown success in accurately predicting the location of biological markers in Optical Coherence Tomography (OCT) volumes of patients with Age-Related Macular Degeneration (AMD) and Diabetic Retinopathy (DR). We propose a method that automatically locates biological markers to the Early Treatment Diabetic Retinopathy Study (ETDRS) rings, only requiring B-scan-level presence annotations. We trained a neural network using 22,723 OCT B-Scans of 460 eyes (433 patients) with AMD and DR, annotated with slice-level labels for Intraretinal Fluid (IRF) and Subretinal Fluid (SRF). The neural network outputs were mapped into the corresponding ETDRS rings. We incorporated the class annotations and domain knowledge into a loss function to constrain the output with biologically plausible solutions. The method was tested on a set of OCT volumes with 322 eyes (189 patients) with Diabetic Macular Edema, with slice-level SRF and IRF presence annotations for the ETDRS rings. Our method accurately predicted the presence of IRF and SRF in each ETDRS ring, outperforming previous baselines even in the most challenging scenarios. Our model was also successfully applied to en-face marker segmentation and showed consistency within C-scans, despite not incorporating volume information in the training process. We achieved a correlation coefficient of 0.946 for the prediction of the IRF area.

Investigational drugs inhibiting complement for the treatment of geographic atrophy.

INTRODUCTION: Geographic atrophy (GA) is a progressive form of age-related macular degeneration (AMD) that leads to severe visual impairment and central vision loss. Traditional treatment options for GA are limited, highlighting the need for new therapeutic approaches. In recent years, targeting the complement system has emerged as a promising strategy for the treatment of GA. AREAS COVERED: This expert opinion article reviews the investigational drugs inhibiting the complement cascade for the treatment of GA. Specifically, it focuses on the recent FDA approved pegcetacoplan, a C3 complement inhibitor, and avacincaptad pegol, a C5 complement inhibitor, highlighting their potential efficacy and safety profiles based on clinical trial data. EXPERT OPINION: FDA approval of intravitreal pegcetacoplan and avacincaptad pegol marks significant progress in the landscape of GA treatment. However, variable results from trials underscore the complex nature of GA and the importance of patient selection. Complement inhibition holds promise, but ongoing research is vital to refine treatment strategies and offer improved outcomes for GA patients.

Challenges and insights in the exploration of the low abundance human ocular surface microbiome.

Purpose: The low microbial abundance on the ocular surface results in challenges in the characterization of its microbiome. The purpose of this study was to reveal factors introducing bias in the pipeline from sample collection to data analysis of low-abundant microbiomes. Methods: Lower conjunctiva and lower lid swabs were collected from six participants using either standard cotton or flocked nylon swabs. Microbial DNA was isolated with two different kits (with or without prior host DNA depletion and mechanical lysis), followed by whole-metagenome shotgun sequencing with a high sequencing depth set at 60 million reads per sample. The relative microbial compositions were generated using the two different tools MetaPhlan3 and Kraken2. Results: The total amount of extracted DNA was increased by using nylon flocked swabs on the lower conjunctiva. In total, 269 microbial species were detected. The most abundant bacterial phyla were Actinobacteria, Firmicutes and Proteobacteria. Depending on the DNA extraction kit and tool used for profiling, the microbial composition and the relative abundance of viruses varied. Conclusion: The microbial composition on the ocular surface is not dependent on the swab type, but on the DNA extraction method and profiling tool. These factors have to be considered in further studies about the ocular surface microbiome and other sparsely colonized microbiomes in order to improve data reproducibility. Understanding challenges and biases in the characterization of the ocular surface microbiome may set the basis for microbiome-altering interventions for treatment of ocular surface associated diseases.

The Human Ocular Surface Microbiome and Its Associations with the Tear Proteome in Dry Eye Disease.

Although dry eye disease (DED) is one of the most common ocular surface diseases worldwide, its pathogenesis is incompletely understood, and treatment options are limited. There is growing evidence that complex interactions between the ocular surface microbiome (OSM) and tear fluid constituents, potentially leading to inflammatory processes, are associated with ocular surface diseases such as DED. In this study, we aimed to find unique compositional and functional features of the OSM associated with human and microbial tear proteins in patients with DED. Applying whole-metagenome shotgun sequencing of forty lid and conjunctival swabs, we identified 229 taxa, with Actinobacteria and Proteobacteria being the most abundant phyla and Propionibacterium acnes the dominating species in the cohort. When DED patients were compared to controls, the species Corynebacterium tuberculostearicum was more abundant in conjunctival samples, whereas the family Propionibacteriaceae was more abundant in lid samples. Functional analysis showed that genes of L-lysine biosynthesis, tetrapyrrole biosynthesis, 5-aminoimidazole ribonucleotide biosynthesis, and the super pathway of L-threonine biosynthesis were enriched in conjunctival samples of controls. The relative abundances of Acinetobacter johnsonii correlated with seven human tear proteins, including mucin-16. The three most abundant microbial tear proteins were the chaperone protein DnaK, the arsenical resistance protein ArsH, and helicase. Compositional and functional features of the OSM and the tear proteome are altered in patients with DED. Ultimately, this may help to design novel interventional therapeutics to target DED.

High-Resolution Optical Coherence Tomography in Healthy Individuals Provides Resolution at the Cellular and Subcellular Levels.

Purpose: To assess the clinical resolution capacities of a novel high-resolution optical coherence tomography (High-Res OCT). Methods: Eight healthy volunteers were included in this observational study. Using the SPECTRALIS High-Res OCT device (Heidelberg Engineering, Heidelberg) macular b-scans were taken and compared with b-scans acquired with a SPECTRALIS HRA+OCT device (Heidelberg Engineering, Heidelberg). High-Res OCT scans were also compared with hematoxylin and eosin-stained sections from a human donor retina. Results: High-Res OCT allowed identification of several retinal structures at the cellular and subcellular levels, namely, cell nuclei of ganglion cells, displaced amacrine cells, cone photoreceptors and retinal pigment epithelial cells compared with the commercial device. Rod photoreceptor nuclei were partially detectable. Localization of cell type-specific nuclei were confirmed by histological sections of human donor retina. Additionally, all three plexus of the retinal vasculature could be visualized. Conclusions: SPECTRALIS High-Res OCT device provides improved resolution compared with the conventional SPECTRALIS HRA+OCT device and allows to identify structures at the cellular level, similar to histological sections. Translational Relevance: High-Res OCT shows improved visualization of retinal structures in healthy individuals and can be used to assess individual cells within the retina.