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Abstract Diabetic macular edema (DME) has emerged as the foremost cause of vision loss in the population with diabetes. Early detection of DME is paramount, yet the prevailing screening, relying on two-dimensional and labor-intensive fundus photography (FP), results in frequent unwarranted referrals and overlooked diagnoses. Self-imaging optical coherence tomography (SI-OCT), offering fully automated, three-dimensional macular imaging, holds the potential to enhance DR screening. We conducted an observational study within a cohort of 1822 participants with diabetes, who received comprehensive assessments, including visual acuity testing, FP, and SI-OCT examinations. We compared the performance of three screening strategies: the conventional FP-based strategy, a combination strategy of FP and SI-OCT, and a simulated combination strategy of FP and manual SD-OCT. Additionally, we undertook a cost-effectiveness analysis utilizing Markov models to evaluate the costs and benefits of the three strategies for referable DR. We found that the FP + SI-OCT strategy demonstrated superior sensitivity (87.69% vs 61.53%) and specificity (98.29% vs 92.47%) in detecting DME when compared to the FP-based strategy. Importantly, the FP + SI-OCT strategy outperformed the FP-based strategy, with an incremental cost-effectiveness ratio (ICER) of $8016 per quality-adjusted life year (QALY), while the FP + SD-OCT strategy was less cost-effective, with an ICER of $45,754/QALY. Our results were robust to extensive sensitivity analyses, with the FP + SI-OCT strategy standing as the dominant choice in 69.36% of simulations conducted at the current willingness-to-pay threshold. In summary, incorporating SI-OCT into FP-based screening offers substantial enhancements in sensitivity, specificity for detecting DME, and most notably, cost-effectiveness for DR screening.

Abstract Fundus fluorescein angiography (FFA) is a crucial diagnostic tool for chorioretinal diseases, but its interpretation requires significant expertise and time. Prior studies have used Artificial Intelligence (AI)-based systems to assist FFA interpretation, but these systems lack user interaction and comprehensive evaluation by ophthalmologists. Here, we used large language models (LLMs) to develop an automated interpretation pipeline for both report generation and medical question-answering (QA) for FFA images. The pipeline comprises two parts: an image-text alignment module (Bootstrapping Language-Image Pre-training) for report generation and an LLM (Llama 2) for interactive QA. The model was developed using 654,343 FFA images with 9392 reports. It was evaluated both automatically, using language-based and classification-based metrics, and manually by three experienced ophthalmologists. The automatic evaluation of the generated reports demonstrated that the system can generate coherent and comprehensible free-text reports, achieving a BERTScore of 0.70 and F1 scores ranging from 0.64 to 0.82 for detecting top-5 retinal conditions. The manual evaluation revealed acceptable accuracy (68.3%, Kappa 0.746) and completeness (62.3%, Kappa 0.739) of the generated reports. The generated free-form answers were evaluated manually, with the majority meeting the ophthalmologists’ criteria (error-free: 70.7%, complete: 84.0%, harmless: 93.7%, satisfied: 65.3%, Kappa: 0.762–0.834). This study introduces an innovative framework that combines multi-modal transformers and LLMs, enhancing ophthalmic image interpretation, and facilitating interactive communications during medical consultation.

Abstract Age-related macular degeneration (AMD) is the leading cause of central vision impairment among the elderly. Effective and accurate AMD screening tools are urgently needed. Indocyanine green angiography (ICGA) is a well-established technique for detecting chorioretinal diseases, but its invasive nature and potential risks impede its routine clinical application. Here, we innovatively developed a deep-learning model capable of generating realistic ICGA images from color fundus photography (CF) using generative adversarial networks (GANs) and evaluated its performance in AMD classification. The model was developed with 99,002 CF-ICGA pairs from a tertiary center. The quality of the generated ICGA images underwent objective evaluation using mean absolute error (MAE), peak signal-to-noise ratio (PSNR), structural similarity measures (SSIM), etc., and subjective evaluation by two experienced ophthalmologists. The model generated realistic early, mid and late-phase ICGA images, with SSIM spanned from 0.57 to 0.65. The subjective quality scores ranged from 1.46 to 2.74 on the five-point scale (1 refers to the real ICGA image quality, Kappa 0.79–0.84). Moreover, we assessed the application of translated ICGA images in AMD screening on an external dataset (n = 13887) by calculating area under the ROC curve (AUC) in classifying AMD. Combining generated ICGA with real CF images improved the accuracy of AMD classification with AUC increased from 0.93 to 0.97 (P

Background Arthroscopic surgery has been established as an efficacious intervention for the treatment of rotator cuff tears. The primary aim of this study was to analyze the modifications in the lateral acromial angle (LAA) subsequent to rotator cuff repair surgery using single‐row rivet fixation and double‐row rivet fixation techniques. Furthermore, we sought to investigate the influence of LAA on the prognosis of rotator cuff repair surgery. Method This observational study retrospectively enrolled 105 patients diagnosed with degenerative rotator cuff tears who underwent arthroscopic rotator cuff repair between 2016 and 2019. Following the exclusion of two patients with subscapularis or superior labrum anterior and posterior (SLAP) tears, as well as three patients who were lost to follow‐up, a cohort of 100 patients was included for clinical and imaging evaluation. Among these individuals, 50 were assigned to the double‐row repair group, whereas the remaining 50 comprised the single‐row repair group. Bilateral shoulder magnetic resonance imaging (MRI) scans were conducted no less than 24 months post‐surgery. Experienced arthroscopic surgeons, blinded to the LAA measurements, assessed the rotator interval (RI) using a control MRI. Functional assessment was performed using the University of California, Los Angeles (UCLA) quick disability of the shoulder and arm, shoulder and hand (qDASH) score. The Wilcoxon signed‐rank test for dependent samples was employed to compare data between the pre‐ and post‐intervention groups. Pearson correlation coefficients were calculated to evaluate the relationship between different parameters. Results The study population consisted of 73 female patients and 27 male patients, with a mean age of 58.32 ± 5.29 years and a mean follow‐up duration of 25.88 ± 8.11 months. Preoperatively, the mean LAA was 75.81° ± 11.28°, RI was 4.78 ± 0.62, UCLA score was 17.54 ± 2.44, and qDASH score was 2.45 ± 0.25. The average tear size was 8.95 ± 2.11 mm. A statistically significant difference in LAA was observed between the preoperative and postoperative measurements, with the double‐row repair group exhibiting a greater LAA than the single‐row repair group. Finally, a significant correlation was identified between LAA, RI, and qDASH scores after a 24‐month follow‐up period. Conclusion According to our findings, the utilization of double‐row rivet fixation has a greater LAA angle than single‐row rivet fixation. Moreover, this preservation of LAA is significantly associated with the functional recovery of the shoulder joint.

Purpose: We aim to use fundus fluorescein angiography (FFA) to label the capillaries on color fundus (CF) photographs and train a deep learning model to quantify retinal capillaries noninvasively from CF and apply it to cardiovascular disease (CVD) risk assessment. Design: Cross-sectional and longitudinal study. Participants: A total of 90732 pairs of CF-FFA images from 3893 participants for segmentation model development, and 49229 participants in the UK Biobank for association analysis. Methods: We matched the vessels extracted from FFA and CF, and used vessels from FFA as labels to train a deep learning model (RMHAS-FA) to segment retinal capillaries using CF. We tested the model's accuracy on a manually labeled internal test set (FundusCapi). For external validation, we tested the segmentation model on 7 vessel segmentation datasets, and investigated the clinical value of the segmented vessels in predicting CVD events in the UK Biobank. Main Outcome Measures: Area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity for segmentation. Hazard ratio (HR; 95% confidence interval [CI]) for Cox regression analysis. Results: On the FundusCapi dataset, the segmentation performance was AUC = 0.95, accuracy = 0.94, sensitivity = 0.90, and specificity = 0.93. Smaller vessel skeleton density had a stronger correlation with CVD risk factors and incidence (P < 0.01). Reduced density of small vessel skeletons was strongly associated with an increased risk of CVD incidence and mortality for women (HR [95% CI] = 0.91 [0.84-0.98] and 0.68 [0.54-0.86], respectively). Conclusions: Using paired CF-FFA images, we automated the laborious manual labeling process and enabled noninvasive capillary quantification from CF, supporting its potential as a sensitive screening method for identifying individuals at high risk of future CVD events. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Purpose: To perform one-shot retinal artery and vein segmentation with cross-modality artery-vein (AV) soft-label pretraining. Design: Cross-sectional study. Subjects: The study included 6479 color fundus photography (CFP) and arterial-venous fundus fluorescein angiography (FFA) pairs from 1964 participants for pretraining and 6 AV segmentation data sets with various image sources, including RITE, HRF, LES-AV, AV-WIDE, PortableAV, and DRSplusAV for one-shot finetuning and testing. Methods: We structurally matched the arterial and venous phase of FFA with CFP, the AV soft labels were automatically generated by utilizing the fluorescein intensity difference of the arterial and venous-phase FFA images, and the soft labels were then used to train a generative adversarial network to learn to generate AV soft segmentations using CFP images as input. We then finetuned the pretrained model to perform AV segmentation using only one image from each of the AV segmentation data sets and test on the remainder. To investigate the effect and reliability of one-shot finetuning, we conducted experiments without finetuning and by finetuning the pretrained model on an iteratively different single image for each data set under the same experimental setting and tested the models on the remaining images. Main Outcome Measures: The AV segmentation was assessed by area under the receiver operating characteristic curve (AUC), accuracy, Dice score, sensitivity, and specificity. Results: After the FFA-AV soft label pretraining, our method required only one exemplar image from each camera or modality and achieved similar performance with full-data training, with AUC ranging from 0.901 to 0.971, accuracy from 0.959 to 0.980, Dice score from 0.585 to 0.773, sensitivity from 0.574 to 0.763, and specificity from 0.981 to 0.991. Compared with no finetuning, the segmentation performance improved after one-shot finetuning. When finetuned on different images in each data set, the standard deviation of the segmentation results across models ranged from 0.001 to 0.10. Conclusions: This study presents the first one-shot approach to retinal artery and vein segmentation. The proposed labeling method is time-saving and efficient, demonstrating a promising direction for retinal-vessel segmentation and enabling the potential for widespread application. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Abstract Background Genomic sequencing reads compressors are essential for balancing high-throughput sequencing short reads generation speed, large-scale genomic data sharing, and infrastructure storage expenditure. However, most existing short reads compressors rarely utilize big-memory systems and duplicative information between diverse sequencing files to achieve a higher compression ratio for conserving reads data storage space. Results We employ compression ratio as the optimization objective and propose a large-scale genomic sequencing short reads data compression optimizer, named PMFFRC, through novelty memory modeling and redundant reads clustering technologies. By cascading PMFFRC, in 982 GB fastq format sequencing data, with 274 GB and 3.3 billion short reads, the state-of-the-art and reference-free compressors HARC, SPRING, Mstcom, and FastqCLS achieve 77.89%, 77.56%, 73.51%, and 29.36% average maximum compression ratio gains, respectively. PMFFRC saves 39.41%, 41.62%, 40.99%, and 20.19% of storage space sizes compared with the four unoptimized compressors. Conclusions PMFFRC rational usage big-memory of compression server, effectively saving the sequencing reads data storage space sizes, which relieves the basic storage facilities costs and community sharing transmitting overhead. Our work furnishes a novel solution for improving sequencing reads compression and saving storage space. The proposed PMFFRC algorithm is packaged in a same-name Linux toolkit, available un-limited at https://github.com/fahaihi/PMFFRC .

Background: Fundus Autofluorescence (FAF) is a valuable imaging technique used to assess metabolic alterations in the retinal pigment epithelium (RPE) associated with various age-related and disease-related changes. The practical uses of FAF are ever-growing. This study aimed to evaluate the effectiveness of a generative deep learning (DL) model in translating color fundus (CF) images into synthetic FAF images and explore its potential for enhancing screening of age-related macular degeneration (AMD). Methods: A generative adversarial network (GAN) model was trained on pairs of CF and FAF images to generate synthetic FAF images. The quality of synthesized FAF images was assessed objectively by common generation metrics. Additionally, the clinical effectiveness of the generated FAF images in AMD classification was evaluated by measuring the area under the curve (AUC), using the LabelMe dataset. Results: A total of 8410 FAF images from 2586 patients were analyzed. The synthesized FAF images exhibited an impressive objectively assessed quality, achieving a multi-scale structural similarity index (MS-SSIM) of 0.67. When evaluated on the LabelMe dataset, the combination of generated FAF images and CF images resulted in a noteworthy improvement in AMD classification accuracy, with the AUC increasing from 0.931 to 0.968. Conclusions: This study presents the first attempt to use a generative deep learning model to create authentic and high-quality FAF images from CF images. The incorporation of the translated FAF images on top of CF images improved the accuracy of AMD classification. Overall, this study presents a promising approach to enhance large-scale AMD screening.

Abstract Behect’s disease is a chronic vasculitis characterized by complex multi-organ immune aberrations. However, a comprehensive understanding of the gene-regulatory profile of peripheral autoimmunity and the diverse immune responses across distinct cell types in Behcet’s disease (BD) is still lacking. Here, we present a multi-omic single-cell study of 424,817 cells in BD patients and non-BD individuals. This study maps chromatin accessibility and gene expression in the same biological samples, unraveling vast cellular heterogeneity. We identify widespread cell-type-specific, disease-associated active and pro-inflammatory immunity in both transcript and epigenomic aspects. Notably, integrative multi-omic analysis reveals putative TF regulators that might contribute to chromatin accessibility and gene expression in BD. Moreover, we predicted gene-regulatory networks within nominated TF activators, including AP-1, NF-kB, and ETS transcript factor families, which may regulate cellular interaction and govern inflammation. Our study illustrates the epigenetic and transcriptional landscape in BD peripheral blood and expands understanding of potential epigenomic immunopathology in this disease.

Purpose: To develop and validate a deep learning model that can transform color fundus (CF) photography into corresponding venous and late-phase fundus fluorescein angiography (FFA) images. Design: Cross-sectional study. Participants: We included 51 370 CF-venous FFA pairs and 14 644 CF-late FFA pairs from 4438 patients for model development. External testing involved 50 eyes with CF-FFA pairs and 2 public datasets for diabetic retinopathy (DR) classification, with 86 952 CF from EyePACs, and 1744 CF from MESSIDOR2. Methods: We trained a deep-learning model to transform CF into corresponding venous and late-phase FFA images. The translated FFA images’ quality was evaluated quantitatively on the internal test set and subjectively on 100 eyes with CF-FFA paired images (50 from external), based on the realisticity of the global image, anatomical landmarks (macula, optic disc, and vessels), and lesions. Moreover, we validated the clinical utility of the translated FFA for classifying 5-class DR and diabetic macular edema (DME) in the EyePACs and MESSIDOR2 datasets. Main Outcome Measures: Image generation was quantitatively assessed by structural similarity measures (SSIM), and subjectively by 2 clinical experts on a 5-point scale (1 refers real FFA); intragrader agreement was assessed by kappa. The DR classification accuracy was assessed by area under the receiver operating characteristic curve. Results: The SSIM of the translated FFA images were > 0.6, and the subjective quality scores ranged from 1.37 to 2.60. Both experts reported similar quality scores with substantial agreement (all kappas > 0.8). Adding the generated FFA on top of CF improved DR classification in the EyePACs and MESSIDOR2 datasets, with the area under the receiver operating characteristic curve increased from 0.912 to 0.939 on the EyePACs dataset and from 0.952 to 0.972 on the MESSIDOR2 dataset. The DME area under the receiver operating characteristic curve also increased from 0.927 to 0.974 in the MESSIDOR2 dataset. Conclusions: Our CF-to-FFA framework produced realistic FFA images. Moreover, adding the translated FFA images on top of CF improved the accuracy of DR screening. These results suggest that CF-to-FFA translation could be used as a surrogate method when FFA examination is not feasible and as a simple add-on to improve DR screening. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Abstract Background Chronic inflammation significantly contributes to photoreceptor death in blinding retinal diseases such as age-related macular degeneration (AMD) and retinitis pigmentosa (RP). Bromodomain and extraterminal domain (BET) proteins are epigenetic readers that act as key proinflammatory factors. We recently found the first-generation BET inhibitor JQ1 alleviated sodium iodate-induced retinal degeneration by suppressing cGAS-STING innate immunity. Here, we investigated the effects and mechanism of dBET6, a proteolysis‑targeting chimera (PROTAC) small molecule that selectively degrades BET by the ubiquitin‒proteasome system, in light-induced retinal degeneration. Methods Mice were exposed to bright light to induce retinal degeneration, and the activation of cGAS-STING was determined by RNA-sequencing and molecular biology. Retinal function, morphology, photoreceptor viability and retinal inflammation were examined in the presence and absence of dBET6 treatment. Results Intraperitoneal injection of dBET6 led to the rapid degradation of BET protein in the retina without detectable toxicity. dBET6 improved retinal responsiveness and visual acuity after light damage (LD). dBET6 also repressed LD-induced retinal macrophages/microglia activation, Müller cell gliosis, photoreceptor death and retinal degeneration. Analysis of single-cell RNA-sequencing results revealed cGAS-STING components were expressed in retinal microglia. LD led to dramatic activation of the cGAS-STING pathway, whereas dBET6 suppressed LD-induced STING expression in reactive macrophages/microglia and the related inflammatory response. Conclusions This study indicates targeted degradation of BET by dBET6 exerts neuroprotective effects by inhibiting cGAS-STING in reactive retinal macrophages/microglia, and is expected to become a new strategy for treatment of retinal degeneration.

Summary: RNA-binding protein with multiple splicing (RBPMS) plays a crucial role in cardiac mesoderm specification and cardiovascular development, as well as being a typical marker for whole retinal ganglion cells (RGCs). However, there is a lack of animal models to spatiotemporally trace the location and function of RBPMS-expressing cells in vivo. In this study, we develop a tamoxifen-inducible RBPMS-tdTomato reporter mouse line to track RBPMS-expressing cells during embryogenesis and adulthood. This mouse line allows us to identify and locate RBPMS-tdTomato-positive cells among various tissues, especially in RGCs and smooth muscle cells, which assist to simulate related retinal degenerative diseases, model and examine choroidal neovascularization non-invasively in vivo. Our results show that the RBPMSCreERT2-tdTomato mouse line is a valuable tool for lineage tracing, disease modeling, drug screening, as well as isolating specific target cells.

Uveitis is a complex autoimmune inflammatory disease of the eye and defining molecules involved is a priority. Here the authors use scRNA sequencing in mouse experimental autoimmune uveitis (EAU) and show PIM1 promotes the imbalance of Th17 and Treg cells, and find elevated PIM-1 in human uveitis disease.

Aging is the strongest risk factor for cardiovascular disease, with progressive decline in the function of vascular endothelial cells (ECs) with age. Systematic analyses of the effects of aging on different cardiac EC types remain limited. Here, we constructed a scRNA atlas of EC transcriptomes in young and old mouse hearts. We identified 10 EC subclusters. The multidimensionally differential genes (DEGs) analysis across different EC clusters shows molecular changes with aging, showing the increase in the overall inflammatory microenvironment and the decrease in angiogenesis and cytoskeletal support capacity of aged ECs. And we performed an in-depth analysis of 3 special ECs, Immunology, Proliferating and Angiogenic. The Immunology EC seems highly associated with some immune regulatory functions, which decline with aging at different degrees. Analysis of two types of neovascular ECs, Proliferating, Angiogenic, implied that Angiogenic ECs can differentiate into multiple EC directions after initially originating from proliferating ECs. And aging leads to a decrease in the ability of vascular angiogenesis and differentiation. Finally, we summarized the effects of aging on cell signaling communication between different EC clusters. This cardiac EC atlas offers comprehensive insights into the molecular regulations of cardiovascular aging, and provides new directions for the prevention and treatment of age-related cardiovascular disease.

Abstract Background Sleep loss (SL) is a health issue associated with the higher risk of autoimmune and inflammatory disorders. However, the connection between SL, the immune system, and autoimmune diseases remains unknown. Methods We conducted mass cytometry, single‐cell RNA sequencing, and flow cytometry to analyze how SL influences immune system and autoimmune disease development. Peripheral blood mononuclear cells from six healthy subjects before and after SL were collected and analyzed by mass cytometry experiments and subsequent bioinformatic analysis to identify the effects of SL on human immune system. Sleep deprivation and experimental autoimmune uveitis (EAU) mice model were constructed, and scRNA‐seq data from mice cervical draining lymph nodes were generated to explore how SL influences EAU development and related autoimmune responses. Results We found compositional and functional changes in human and mouse immune cells after SL, especially in effector CD4+ T and myeloid cells. SL upregulated serum GM‐CSF levels in healthy individuals and in patients with SL‐induced recurrent uveitis. Experiments in mice undergoing SL or EAU demonstrated that SL could aggravate autoimmune disorders by inducing pathological immune cell activation, upregulating inflammatory pathways, and promoting intercellular communication. Furthermore, we found that SL promoted Th17 differentiation, pathogenicity, and myeloid cells activation through the IL‐23Th17GM‐CSF feedback mechanism, thus promoting EAU development. Lastly, an anti‐GM‐CSF treatment rescued SL‐induced EAU aggravation and pathological immune response. Conclusions SL promoted Th17 cells pathogenicity and autoimmune uveitis development, especially through the interaction between Th17 and myeloid cells involving GM‐CSF signaling, providing possible therapeutic targets for the SL‐related pathological disorders.

Endothelial cells (ECs) with senescence-associated secretory phenotypes (SASP) have been identified as a key mechanism of aging that contributes to various age-related kidney diseases. In this study, we used single-cell RNA sequencing (scRNA-seq) to create a transcriptome atlas of murine renal ECs and identify transcriptomic changes that occur during aging. We identified seven different subtypes of renal ECs, with glomerular ECs and angiogenic ECs being the most affected by senescence. We confirmed our scRNA-seq findings by using double immunostaining for an EC marker (CD31) and markers of specialized EC phenotypes. Our analysis of the dynamics of capillary lineage development revealed a chronic state of inflammation and compromised glomerular function as prominent aging features. Additionally, we observed an elevated pro-inflammatory and pro-coagulant microenvironment in aged glomerular ECs, which may contribute to age-related glomerulosclerosis and renal fibrosis. Through intercellular communication analysis, we also identified changes in signaling involved in immune regulation that may contribute to a hostile microenvironment for renal homeostasis and function. Overall, our findings provide new insights into the mechanisms of aging in the renal endothelium and may pave the way for the discovery of diagnostic biomarkers and therapeutic interventions against age-related kidney diseases.

Single-cell RNA-sequencing and chromatin accessibility analysis reveal transcriptomic and epigenomic changes between healthy patients and those affected by the systemic autoimmune disorder Vogt-Koyanagi-Harada disease.

Endothelial cell (EC) function declines with age and contributes to the development of many vascular-related disease processes. Currently, the effects of aging on the molecular regulatory mechanisms of liver ECs have not been fully elucidated. Here, we employed single-cell RNA sequencing to map the transcriptome of ECs and analyzed their relationship with aging. We identified 8 different EC subtypes, interestingly, 2 of which were specially expressed in aged mice ECs namely aged capillary ECs (Aged ECs) and pro-inflammation capillary ECs (Proinfla.ECs). Double immunostaining for an EC marker (Cd31) and a marker of these specialized EC phenotypes confirmed the single-cell RNA sequencing data. Gene ontology analysis revealed that Aged ECs and Proinfla.ECs were associated with inflammatory response. Then we found that liver proliferating capillary ECs (Prolife.ECs) were most affected by senescence. Single-cell transcript analysis suggests that Prolife.ECs and angiogenic capillary ECs may form a poor microenvironment that promotes angiogenesis and tumorigenesis. Pseudo-temporal trajectories revealed that Prolife.ECs have different differentiation pathways in young and aged mice. In aged mice, Prolife.ECs could specifically differentiate into an unstable state, which was mainly composed of angiogenic capillary ECs. Intercellular communication revealed inflammatory activation in old group. Overall, this work compared the single-cell RNA profiles of liver ECs in young and aged mice. These findings provide a new insight into liver aging and its molecular mechanisms, and further exploration of Aged ECs and Proinfla.ECs may help to elucidate the molecular mechanisms associated with senescence.

Vogt-Koyanagi-Harada disease (VKH) is an important refractory uveitis mediated by pathological T cells (TCs). Tofacitinib (TOFA) is a JAK- targeted therapy for several autoimmune diseases. However, the specific pathogenesis and targeted therapeutics for VKH remain largely unknown. Based on single-cell RNA sequencing and mass cytometry, we present what we believe is the first multimodal, high-dimensional analysis to generate a comprehensive human immune atlas regarding subset composition, gene signatures, enriched pathways, and intercellular interactions of VKH patients undergoing TOFA therapy. Patients with VKH are characterized by TCs’ polarization from naive to effector and memory subsets, together with accrued monocytes and upregulated cytokines and JAK/STAT signaling pathways. In vitro, TOFA reversed Th17/Treg imbalance and inhibited IL-2–induced STAT1/3 phosphorylation. TOFA alleviated VKH symptoms by restoring pathological TCs’ polarization and functional marker expression and downregulating cytokine signaling and lymphocyte function. Remarkably, inflammation-related responses and intercellular interactions decreased after TOFA treatment, particularly in monocytes. Notably, we identified 2 inflammation- and JAK-associated monocyte subpopulations that were strongly implicated in VKH pathogenesis and mechanisms involved in TOFA treatment. Here, we provide a potentially novel JAK-targeted therapy for VKH and elaborate on the possible therapeutic mechanisms of TOFA, expanding our knowledge of VKH pathological patterns.

Liu et al. use mass cytometry and single-cell RNA sequencing of healthy human blood samples to obtain a comprehensive human immune cell landscape when sleep duration is reduced. Their findings could provide highdimensional insight into the cellular and molecular mechanisms of pathologic conditions affect by poor sleep.

Abstract Coronavirus disease 2019 (COVID-19), driven by SARS-CoV-2, is a severe infectious disease that has become a global health threat. Vaccines are among the most effective public health tools for combating COVID-19. Immune status is critical for evaluating the safety and response to the vaccine, however, the evolution of the immune response during immunization remains poorly understood. Single-cell RNA sequencing (scRNA-seq) represents a powerful tool for dissecting multicellular behavior and discovering therapeutic antibodies. Herein, by performing scRNA/V(D)J-seq on peripheral blood mononuclear cells from four COVID-19 vaccine trial participants longitudinally during immunization, we revealed enhanced cellular immunity with concerted and cell type-specific IFN responses as well as boosted humoral immunity with SARS-CoV-2-specific antibodies. Based on the CDR3 sequence and germline enrichment, we were able to identify several potential binding antibodies. We synthesized, expressed and tested 21 clones from the identified lineages. Among them, one monoclonal antibody (P3V6-1) exhibited relatively high affinity with the extracellular domain of Spike protein, which might be a promising therapeutic reagent for COVID-19. Overall, our findings provide insights for assessing vaccine through the novel scRNA/V(D)J-seq approach, which might facilitate the development of more potent, durable and safe prophylactic vaccines.

Summary: With the advantages of high resolution and high dimension, mass cytometry is implemented to analyze the blood complex immune system in clinical settings. However, long-term clinical sample collection may cause batch effects that mask true biological results. Here, we present a validated and streamlined mass cytometry workflow that features fixed staining for clinical use and optimized barcode staining patterns. The reagents and approaches used in this workflow can help reduce batch effects, thereby extending the application range and advantages of mass cytometry.

PurposeTo develop an artificial intelligence (AI) system that can predict optical coherence tomography (OCT)-derived high myopia grades based on fundus photographs.MethodsIn this retrospective study, 1,853 qualified fundus photographs obtained from the Zhongshan Ophthalmic Center (ZOC) were selected to develop an AI system. Three retinal specialists assessed corresponding OCT images to label the fundus photographs. We developed a novel deep learning model to detect and predict myopic maculopathy according to the atrophy (A), traction (T), and neovascularisation (N) classification and grading system. Furthermore, we compared the performance of our model with that of ophthalmologists.ResultsWhen evaluated on the test set, the deep learning model showed an area under the receiver operating characteristic curve (AUC) of 0.969 for category A, 0.895 for category T, and 0.936 for category N. The average accuracy of each category was 92.38% (A), 85.34% (T), and 94.21% (N). Moreover, the performance of our AI system was superior to that of attending ophthalmologists and comparable to that of retinal specialists.ConclusionOur AI system achieved performance comparable to that of retinal specialists in predicting vision-threatening conditions in high myopia via simple fundus photographs instead of fundus and OCT images. The application of this system can save the cost of patients' follow-up, and is more suitable for applications in less developed areas that only have fundus photography.

Most single-cell RNA sequencing methods have limited ability to profile the transcriptome at isoform resolution. Here the authors develop scRCAT-seq to characterize the 5′- and 3′-ends of transcripts in single cells, and identify cell-type specific alternative transcript isoforms.

Abstract Age-associated changes in immune cells have been linked to an increased risk for infection. However, a global and detailed characterization of the changes that human circulating immune cells undergo with age is lacking. Here, we combined scRNA-seq, mass cytometry and scATAC-seq to compare immune cell types in peripheral blood collected from young and old subjects and patients with COVID-19. We found that the immune cell landscape was reprogrammed with age and was characterized by T cell polarization from naive and memory cells to effector, cytotoxic, exhausted and regulatory cells, along with increased late natural killer cells, age-associated B cells, inflammatory monocytes and age-associated dendritic cells. In addition, the expression of genes, which were implicated in coronavirus susceptibility, was upregulated in a cell subtype-specific manner with age. Notably, COVID-19 promoted age-induced immune cell polarization and gene expression related to inflammation and cellular senescence. Therefore, these findings suggest that a dysregulated immune system and increased gene expression associated with SARS-CoV-2 susceptibility may at least partially account for COVID-19 vulnerability in the elderly.

Purpose: We performed single-cell RNA sequencing (scRNA-seq), an unbiased and high-throughput single cell technology, to determine phenotype and function of peripheral immune cells in patients with diabetic macular edema (DME).Methods: Peripheral blood mononuclear cells (PBMCs) were isolated from DME patients and healthy controls (HC). The single-cell samples were loaded on the Chromium platform (10x Genomics) for sequencing. R package Seurat v3 was used for data normalizing, clustering, dimensionality reduction, differential expression analysis, and visualization.Results: We constructed a single-cell RNA atlas comprising 57,650 PBMCs (24,919 HC, 32,731 DME). We divided all immune cells into five major immune cell lineages, including monocytes (MC), T cells (TC), NK cells (NK), B cells (BC), and dendritic cells (DC). Our differential expression gene (DEG) analysis showed that MC was enriched of genes participating in the cytokine pathway and inflammation activation. We further subdivided MC into five subsets: resting CD14++ MC, proinflammatory CD14++ MC, intermediate MC, resting CD16++ MC and pro-inflammatory CD16++ MC. Remarkably, we revealed that the proinflammatory CD14++ monocytes predominated in promoting inflammation, mainly by increasingly production of inflammatory cytokines (TNF, IL1B, and NFKBIA) and chemokines (CCL3, CCL3L1, CCL4L2, CXCL2, and CXCL8). Gene Ontology (GO) and pathway analysis of the DEGs demonstrated that the proinflammatory CD14++ monocytes, especially in DME patients, upregulated inflammatory pathways including tumor necrosis factor-mediated signaling pathway, I-kappaB kinase/NF-kappaB signaling, and toll-like receptor signaling pathway.Conclusion: In this study, we construct the first immune landscape of DME patients with T2D and confirmed innate immune dysregulation in peripheral blood based on an unbiased scRNA-seq approach. And these results demonstrate potential target cell population for anti-inflammation treatments.

Abstract Background HIV integrase (IN) and its cellular cofactors, including lens-epithelium-derived growth factor (LEDGF/p75), Ku70, p300, and Rad52, are subject to small ubiquitin-like modifier (SUMO) modification. In addition to covalent SUMOylation, SUMO paralogs can also noncovalently bind proteins through SUMO-interacting motifs (SIMs). However, little is known about whether HIV IN contains SIMs and the roles of these motifs. Results We searched for the amino acid sequence of HIV IN and investigated three putative SIMs of IN: SIM1 72VILV75, SIM2 200IVDI203 and SIM3 257IKVV260. Our mutational analysis showed that 200IVDI203 and 257IKVV260 are two bona fide SIMs that mediate IN-SUMO noncovalent interactions. Additionally, a cell-based SUMOylation assay revealed that IN SIMs negatively regulate the SUMOylation of IN, as well as the interaction between IN and SUMO E2 conjugation enzyme Ubc9. Conversely, IN SIMs are required for its interactions with LEDGF/p75 but not with Ku70. Furthermore, our study reveals that SIM2 and SIM3 are required for the nuclear localization of IN. Finally, we investigated the impact of IN SIM2 and SIM3 on HIV single cycle replication in CD4+ C8166 T cells, and the results showed that viruses carrying IN SIM mutants are replication defective at the steps of the early viral life cycle, including reverse transcription, nuclear import and integration. Conclusion Our data suggested that the INSIM-SUMO interaction constitutes a new regulatory mechanism of IN functions and might be important for HIV-1 replication.

Abstract Background COVID‐19 is currently a global pandemic, but the response of human immune system to severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection remains unclear. Noncoding RNAs serve as immune regulators and thus may play a critical role in disease progression. Methods We performed multi‐transcriptome sequencing of both noncoding RNAs and mRNAs isolated from the red blood cell depleted whole blood of moderate and severe COVID‐19 patients. The functions of noncoding RNAs were validated by analyses of the expression of downstream mRNAs. We further utilized the single‐cell RNA‐seq data of COVID‐19 patients from Wilk et al. and Chua et al. to characterize noncoding RNA functions in different cell types. Results We defined four types of microRNAs with different expression tendencies that could serve as biomarkers for COVID‐19 progress. We also identified miR‐146a‐5p, miR‐21‐5p, miR‐142‐3p, and miR‐15b‐5p as potential contributors to the disease pathogenesis, possibly serving as biomarkers of severe COVID‐19 and as candidate therapeutic targets. In addition, the transcriptome profiles consistently suggested hyperactivation of the immune response, loss of T‐cell function, and immune dysregulation in severe patients. Conclusions Collectively, these findings provide a comprehensive view of the noncoding and coding transcriptional landscape of peripheral immune cells during COVID‐19, furthering our understanding and offering novel insights into COVID‐19 pathogenesis.

Introduction The need for cataract surgery is on the rise due to our ageing population and high demands for greater visual functioning. Although the majority of patients want to participate in a shared decision-making process, no decision aid has been available to improve the quality of decision. The present study aims to determine whether a decision aid increases informed decision about cataract surgery.Methods and analysis A parallel randomised controlled trial (772 participants) will be conducted. The decision aid will be implemented among patients with any age-related cataract in Yuexiu District, which is socioeconomically representative of a major metropolitan region in Southern China. Participants will be randomly assigned to receive either a patient decision aid or a traditional booklet, and they will complete three surveys: (1) baseline assessment before the intervention (time point (T)1), 2 weeks (T2) and 1 year (T3) after the intervention. The control group receives a traditional booklet with standard general information developed by the National Eye Institute to help patients understand cataract, whereas the intervention group receives a patient decision aid that includes not only the standard general information, but also the quantitative risk information on the possible outcomes of cataract surgery as well as value clarification exercise. The primary study outcome is the informed decision, the percentage of patients who have adequate knowledge and demonstrate consistency between attitudes and intentions. Secondary outcomes include perceived importance of cataract surgery benefits/harms, decision conflict and confidence, anticipated regret and booklet utilisation and acceptability at 2 weeks, and surgical rates and a cost–utility estimate of the decision aid at 1 year.Ethics and dissemination Ethics approval was obtained from the Ethics Committee of Zhongshan Ophthalmic Center (reference number: 2019KYPJ090). Results will be published in peer-reviewed journals and presented at scientific meetings for academic audiences.Trial registration number NCT03992807.

Background: We investigated whether specific appointments for quality-assured care could increase referral uptake, often low in China, in children's vision screening. Methods: We randomized children aged 4–7 years in Yudu, Jiangxi, China, by school to Control (free school-based eye screening, parents of children failing screening recommended for further examination [usual practice]) or Intervention (identical examinations, with parents additionally provided with specific appointments for further examinations by quality-assured doctors at a designated local hospital). Both groups could select any hospital for referral exams, which were not free. Six months after screening, parents were interviewed on referral compliance at any hospital (primary outcome) and potential determinants. This trial is registered at the ClinicalTrials.gov, number NCT 03251456. Findings: Among 9936 children at 63 schools randomized to Intervention (32 schools, 5053 [50·9%] children) or Control (31 schools, 4883 [49·1%] children), 1114 children (11·2%) failed screening. Among 513 referred Intervention children (46·1%, 32 schools, mean age 5·36 years, 53·0% boys) and 601 referred Control children (53·9%, 31 schools, mean age 5·30 years, 57·7% boys), 104 (20·3%) and 135 (22·5%) were lost to follow-up respectively. Under Intention to Treat analysis, assuming children lost to follow-up were non-compliant, Intervention children had significantly higher compliance than Controls (308/513 = 60·0% vs. 225/601 = 37·4%, P

Mobile agent node has become the most efficiency way of data collection in sparse wireless sensor networks，because the distance of the nodes is too far. However，the mobile agent node could not access all the nodes to gather the data in a routing travel because of energy-constrained. In order to make the energy-constrained mobile agent node obtain the minimum total route，an effective routing scheme of energy-constrained mobile agent node in sparse wireless sensor networks was presented. The mathematic model of the route of mobile agent node was built firstly，and then the whole wireless sensor network was split into different subsets according to the energy of the mobile agent node. Then the shortest routes were computed by adopting simulated annealing of traveling salesman problem. Finally，the obtained total route of sub-routes was the optimal route. The analysis results of simulation and performance show that the total route of the presented scheme is close to the ideal situation along with the increase of the number of nodes and the raise of the energy of mobile agent node. So the presented scheme is very effective in the practice and is propitious to popularize.

BackgroundElectronic medical records provide large-scale real-world clinical data for use in developing clinical decision systems. However, sophisticated methodology and analytical skills are required to handle the large-scale datasets necessary for the optimisation of prediction accuracy. Myopia is a common cause of vision loss. Current approaches to control myopia progression are effective but have significant side effects. Therefore, identifying those at greatest risk who should undergo targeted therapy is of great clinical importance. The objective of this study was to apply big data and machine learning technology to develop an algorithm that can predict the onset of high myopia, at specific future time points, among Chinese school-aged children.Methods and findingsReal-world clinical refraction data were derived from electronic medical record systems in 8 ophthalmic centres from January 1, 2005, to December 30, 2015. The variables of age, spherical equivalent (SE), and annual progression rate were used to develop an algorithm to predict SE and onset of high myopia (SE ≤ -6.0 dioptres) up to 10 years in the future. Random forest machine learning was used for algorithm training and validation. Electronic medical records from the Zhongshan Ophthalmic Centre (a major tertiary ophthalmic centre in China) were used as the training set. Ten-fold cross-validation and out-of-bag (OOB) methods were applied for internal validation. The remaining 7 independent datasets were used for external validation. Two population-based datasets, which had no participant overlap with the ophthalmic-centre-based datasets, were used for multi-resource validation testing. The main outcomes and measures were the area under the curve (AUC) values for predicting the onset of high myopia over 10 years and the presence of high myopia at 18 years of age. In total, 687,063 multiple visit records (≥3 records) of 129,242 individuals in the ophthalmic-centre-based electronic medical record databases and 17,113 follow-up records of 3,215 participants in population-based cohorts were included in the analysis. Our algorithm accurately predicted the presence of high myopia in internal validation (the AUC ranged from 0.903 to 0.986 for 3 years, 0.875 to 0.901 for 5 years, and 0.852 to 0.888 for 8 years), external validation (the AUC ranged from 0.874 to 0.976 for 3 years, 0.847 to 0.921 for 5 years, and 0.802 to 0.886 for 8 years), and multi-resource testing (the AUC ranged from 0.752 to 0.869 for 4 years). With respect to the prediction of high myopia development by 18 years of age, as a surrogate of high myopia in adulthood, the algorithm provided clinically acceptable accuracy over 3 years (the AUC ranged from 0.940 to 0.985), 5 years (the AUC ranged from 0.856 to 0.901), and even 8 years (the AUC ranged from 0.801 to 0.837). Meanwhile, our algorithm achieved clinically acceptable prediction of the actual refraction values at future time points, which is supported by the regressive performance and calibration curves. Although the algorithm achieved balanced and robust performance, concerns about the compromised quality of real-world clinical data and over-fitting issues should be cautiously considered.ConclusionsTo our knowledge, this study, for the first time, used large-scale data collected from electronic health records to demonstrate the contribution of big data and machine learning approaches to improved prediction of myopia prognosis in Chinese school-aged children. This work provides evidence for transforming clinical practice, health policy-making, and precise individualised interventions regarding the practical control of school-aged myopia.

Summary: Background: Contemporary data for causes of vision impairment and blindness form an important basis of recommendations in public health policies. Refreshment of the Global Vision Database with recently published data sources permitted modelling of cause of vision loss data from 1990 to 2015, further disaggregation by cause, and forecasts to 2020. Methods: In this systematic review and meta-analysis, we analysed published and unpublished population-based data for the causes of vision impairment and blindness from 1980 to 2014. We identified population-based studies published before July 8, 2014, by searching online databases with no language restrictions (MEDLINE from Jan 1, 1946, and Embase from Jan 1, 1974, and the WHO Library Database). We fitted a series of regression models to estimate the proportion of moderate or severe vision impairment (defined as presenting visual acuity of 14% of blindness) as causes in the high-income subregions. Blindness and vision impairment at all ages in 2015 due to diabetic retinopathy (odds ratio 2·52 [1·48–3·73]) and cataract (1·21 [1·17–1·25]) were more common among women than among men, whereas blindness and vision impairment due to glaucoma (0·71 [0·57–0·86]) and corneal opacity (0·54 [0·43–0·66]) were more common among men than among women, with no sex difference related to age-related macular degeneration (0·91 [0·70–1·14]). Interpretation: The number of people affected by the common causes of vision loss has increased substantially as the population increases and ages. Preventable vision loss due to cataract (reversible with surgery) and refractive error (reversible with spectacle correction) continue to cause most cases of blindness and moderate or severe vision impairment in adults aged 50 years and older. A large scale-up of eye care provision to cope with the increasing numbers is needed to address avoidable vision loss. Funding: Brien Holden Vision Institute.

Background: Global and regional prevalence estimates for blindness and vision impairment are important for the development of public health policies. We aimed to provide global estimates, trends, and projections of global blindness and vision impairment. Methods: We did a systematic review and meta-analysis of population-based datasets relevant to global vision impairment and blindness that were published between 1980 and 2015. We fitted hierarchical models to estimate the prevalence (by age, country, and sex), in 2015, of mild visual impairment (presenting visual acuity worse than 6/12 to 6/18 inclusive), moderate to severe visual impairment (presenting visual acuity worse than 6/18 to 3/60 inclusive), blindness (presenting visual acuity worse than 3/60), and functional presbyopia (defined as presenting near vision worse than N6 or N8 at 40 cm when best-corrected distance visual acuity was better than 6/12). Findings: Globally, of the 7·33 billion people alive in 2015, an estimated 36·0 million (80% uncertainty interval [UI] 12·9–65·4) were blind (crude prevalence 0·48%; 80% UI 0·17–0·87; 56% female), 216·6 million (80% UI 98·5–359·1) people had moderate to severe visual impairment (2·95%, 80% UI 1·34–4·89; 55% female), and 188·5 million (80% UI 64·5–350·2) had mild visual impairment (2·57%, 80% UI 0·88–4·77; 54% female). Functional presbyopia affected an estimated 1094·7 million (80% UI 581·1–1686·5) people aged 35 years and older, with 666·7 million (80% UI 364·9–997·6) being aged 50 years or older. The estimated number of blind people increased by 17·6%, from 30·6 million (80% UI 9·9–57·3) in 1990 to 36·0 million (80% UI 12·9–65·4) in 2015. This change was attributable to three factors, namely an increase because of population growth (38·4%), population ageing after accounting for population growth (34·6%), and reduction in age-specific prevalence (−36·7%). The number of people with moderate and severe visual impairment also increased, from 159·9 million (80% UI 68·3–270·0) in 1990 to 216·6 million (80% UI 98·5–359·1) in 2015. Interpretation: There is an ongoing reduction in the age-standardised prevalence of blindness and visual impairment, yet the growth and ageing of the world's population is causing a substantial increase in number of people affected. These observations, plus a very large contribution from uncorrected presbyopia, highlight the need to scale up vision impairment alleviation efforts at all levels. Funding: Brien Holden Vision Institute.

HIV-1 integrase (IN) is a key viral enzyme during HIV-1 replication that catalyzes the insertion of viral DNA into the host genome. Recent studies have provided important insights into the multiple posttranslational modifications (PTMs) of IN (e.g., ubiquitination, SUMOylation, acetylation and phosphorylation), which regulate its multifaceted functions. A number of host cellular proteins, including Lens Epithelium‑derived Growth factor (LEDGF/p75), p300 and Ku70 have been shown to interact with IN and be involved in the PTM process of IN, either facilitating or counteracting the IN PTMs. Although previous studies have revealed much about the important roles of IN PTMs, how IN functions are fine-tuned by these PTMs under the physiological setting still needs to be determined. Here, we review the advances in the understanding of the mechanisms and roles of multiple IN PTMs.

Diabetic retinopathy (DR), a major microvascular complication of diabetes, has a significant impact on the world′s health systems. Globally, the number of people with DR will grow from 126.6 million in 2010 to 191.0 million by 2030, and we estimate that the number with vision-threatening diabetic retinopathy (VTDR) will increase from 37.3 million to 56.3 million, if prompt action is not taken. Despite growing evidence documenting the effectiveness of routine DR screening and early treatment, DR frequently leads to poor visual functioning and represents the leading cause of blindness in working-age populations. DR has been neglected in health-care research and planning in many low-income countries, where access to trained eye-care professionals and tertiary eye-care services may be inadequate. Demand for, as well as, supply of services may be a problem. Rates of compliance with diabetes medications and annual eye examinations may be low, the reasons for which are multifactorial. Innovative and comprehensive approaches are needed to reduce the risk of vision loss by prompt diagnosis and early treatment of VTDR.

To study willingness to pay for cataract surgery and surgical service provided by a senior cataract surgeon in urban Southern China.This study was a cross-sectional willingness-to-pay (WTP) interview using bidding formats. Two-hundred eleven persons with presenting visual impairment in either eye due to cataract were enrolled at a tertiary eye hospital. Participants underwent a comprehensive eye examination and a WTP interview for both surgery and service provided by a senior surgeon. Demographic information, socioeconomic status and clinical data were recorded.Among 211 (98% response rate) persons completing the interview, 53.6% were women and 80.6% were retired. About 72.2% had a monthly income lower than 1000 renminbi (US $161). A total of 189 (89.6%) were willing to pay for cataract and the median amount of WTP was 6000 renminbi (US$968). And 102 (50.7%) were willing to pay additional fees for surgery performed by a senior surgeon, and the median amount of WTP was 500 renminbi (US$81). In regression models adjusting for age and gender, persons with preexisting eye diseases other than cataract, were more likely to pay for cataract surgery and service provided by a senior surgeon (P = 0.04 for both).In urban China, cataract patients, especially those with preexisting eye conditions, are willing to pay additional fees for a senior surgeon. Moving to a system where the price of cataract surgery is proportional to the consultant' skill and expertise is possible and may have a potential impact on waiting list and quality of eye care. Further studies are needed to examine the impact of such pricing system on attitudes and choices of cataract patients.

OBJECTIVE: To determine the prevalence of cataract surgery and factors associated with post-surgical visual outcomes in migrant Indians living in Singapore. RESEARCH DESIGN AND METHODS: We conducted a population-based study in 3,400 Indian immigrants residing in Singapore-the Singapore Indian Eye Study (SINDI). All participants underwent comprehensive medical eye examination and a standardized interview. Post-operative visual impairment (VI) was defined as best-corrected or presenting visual acuity (BCVA or PVA) of 20/60 or worse. RESULTS: The age- and gender-standardized prevalence of cataract surgery was 9.7% (95% confidence interval [CI]: 8.9%, 10.7%) in Singapore resident Indians. Post-operative VI defined by BCVA occurred in 10.9% eyes (87/795). The main causes of post-operative VI were diabetic retinopathy (20.7%), posterior capsular opacification (18.4%), and age-related macular degeneration (12.6%). Undercorrected refractive error doubled the prevalence of post-operative VI when PVA was used. CONCLUSIONS: The rate of cataract surgery is about 10% in Indian residents in Singapore. Socioeconomic variables and migration had no significant impact on the prevalence of cataract surgery. Diabetic retinopathy was a major cause of post-operative VI in migrant Indians living in Singapore. Uncorrected postoperative refractive error remains an efficient way to improve vision.

BackgroundHealth of migrants is a major public health challenge faced by governments and policy makers. Asian Indians are among the fastest growing migration groups across Asia and the world, but the impact of migration and acculturation on diabetes and diabetes-related eye complications among Indians living in urban Asia remains unclear.Methodologies/principal findingsWe evaluated the influence of migration and acculturation (i.e., migration status and length of residence) on the prevalence of type-2 diabetes mellitus (T2DM) and diabetes-related eye complications (diabetic retinopathy (DR) and cataract), among first-generation (defined as participant born in India with both parents born in India, n = 781) and second-generation (participants born in Singapore with both parents born in India, n = 1,112) Indian immigrants from a population-based study of Adult Indians in Singapore. Diabetes was defined as HbA1c≥6.5%, use of diabetic medication or a physician diagnosis of diabetes. Retinal and lens photographs were graded for the presence of DR and cataract. Compared to first generation immigrants, second generation immigrants had a higher age- and gender-standardized prevalence of T2DM (34.4% versus 29.0%, pConclusionSecond generation immigrant Indians and longer length of residence are associated with higher prevalence of diabetes and diabetes-related complications (i.e., DR and cataract) among migrant Indians living in Singapore. These data highlight potential worldwide impacts of migration patterns on the risk and burden of diabetes.

As one of the leading causes of visual impairment and blindness, myopia poses a significant public health burden in Asia. The primary determinant of myopia is an elongated ocular axial length (AL). Here we report a meta-analysis of three genome-wide association studies on AL conducted in 1,860 Chinese adults, 929 Chinese children, and 2,155 Malay adults. We identified a genetic locus on chromosome 1q41 harboring the zinc-finger 11B pseudogene ZC3H11B showing genome-wide significant association with AL variation (rs4373767, β = -0.16 mm per minor allele, P(meta) =2.69 × 10(-10)). The minor C allele of rs4373767 was also observed to significantly associate with decreased susceptibility to high myopia (per-allele odds ratio (OR) =0.75, 95% CI: 0.68-0.84, P(meta) =4.38 × 10(-7)) in 1,118 highly myopic cases and 5,433 controls. ZC3H11B and two neighboring genes SLC30A10 and LYPLAL1 were expressed in the human neural retina, retinal pigment epithelium, and sclera. In an experimental myopia mouse model, we observed significant alterations to gene and protein expression in the retina and sclera of the unilateral induced myopic eyes for the murine genes ZC3H11A, SLC30A10, and LYPLAL1. This supports the likely role of genetic variants at chromosome 1q41 in influencing AL variation and high myopia.

APOBEC3G (A3G), a deoxycytidine deaminase, is a potent host antiviral factor that can restrict HIV-1 infection. During Vif-negative HIV-1 replication, A3G is incorporated into HIV-1 particles, induces mutations in reverse transcribed viral DNA and inhibits reverse transcription. However, HIV-1 Vif counteracts A3G's activities by inducing its degradation and by blocking its incorporation into HIV-1 particles. Thus, it is interesting to elucidate a mechanism that would allow A3G to escape the effects of Vif in order to rescue its potent antiviral activity and to provide a possible novel therapeutic strategy for treating HIV-1 infection.In this study, we generated an R88-A3G fusion protein by fusing A3G to a virion-targeting polypeptide (R14-88) derived from HIV-1 Vpr protein and compared its antiviral effects relative to those of HA-tagged native A3G (HA-A3G). Our study showed that transient expression of the R88-A3G fusion protein in both Vif(-) and Vif(+) HIV-1 producing cells drastically inhibited viral infection in HeLa-CD4-CCR5-cells, CD4(+) C8166 T cells and human primary PBMCs. Moreover, we established CD4(+) C8166 T cell lines that stably express either R88-A3G or HA-A3G by transduction with VSV-G-pseudotyped lentiviral vector that harbor expression cassettes for R88-A3G or HA-A3G, respectively, and tested their susceptibility to Vif(+) HIV-1 infection. Our results clearly reveal that expression of R88-A3G in transduced CD4(+) C8166 cells significantly blocked Vif(+) HIV-1 infection. In an attempt to understand the mechanism underlying the antiviral activity of R88-A3G, we demonstrated that R88-A3G was efficiently incorporated into viral particles in the presence of Vif. Moreover, PCR analysis revealed that R88-A3G significantly inhibited viral cDNA synthesis during the early stage of Vif(+) virus infection.Our results clearly indicate that R88 delivers A3G into Vif(+) HIV-1 particles and inhibits infectivity and spread of the virions among CD4(+) T cells. This study provides evidence for an effective strategy to modify a host protein with innate anti-HIV-1 activity and rescue its potent anti-HIV potential in the presence of Vif. Further characterization and optimization of this system may lead to the development of an effective therapeutic approach against HIV-1 infection.

Background: Indocyanine green angiography (ICGA) is vital for diagnosing chorioretinal diseases, but its interpretation and patient communication require extensive expertise and time-consuming efforts. We aim to develop a bilingual ICGA report generation and question-answering (QA) system. Methods: Our dataset comprised 213 129 ICGA images from 2919 participants. The system comprised two stages: image-text alignment for report generation by a multimodal transformer architecture, and large language model (LLM)-based QA with ICGA text reports and human-input questions. Performance was assessed using both qualitative metrics (including Bilingual Evaluation Understudy (BLEU), Consensus-based Image Description Evaluation (CIDEr), Recall-Oriented Understudy for Gisting Evaluation-Longest Common Subsequence (ROUGE-L), Semantic Propositional Image Caption Evaluation (SPICE), accuracy, sensitivity, specificity, precision and F1 score) and subjective evaluation by three experienced ophthalmologists using 5-point scales (5 refers to high quality). Results: We produced 8757 ICGA reports covering 39 disease-related conditions after bilingual translation (66.7% English, 33.3% Chinese). The ICGA-GPT model's report generation performance was evaluated with BLEU scores (1-4) of 0.48, 0.44, 0.40 and 0.37; CIDEr of 0.82; ROUGE of 0.41 and SPICE of 0.18. For disease-based metrics, the average specificity, accuracy, precision, sensitivity and F1 score were 0.98, 0.94, 0.70, 0.68 and 0.64, respectively. Assessing the quality of 50 images (100 reports), three ophthalmologists achieved substantial agreement (kappa=0.723 for completeness, kappa=0.738 for accuracy), yielding scores from 3.20 to 3.55. In an interactive QA scenario involving 100 generated answers, the ophthalmologists provided scores of 4.24, 4.22 and 4.10, displaying good consistency (kappa=0.779). Conclusion: This pioneering study introduces the ICGA-GPT model for report generation and interactive QA for the first time, underscoring the potential of LLMs in assisting with automated ICGA image interpretation. [ABSTRACT FROM AUTHOR]

Objectives To evaluate the feasibility and accuracy of a portable, self-imaging optical coherence tomography (OCT) for measuring central subfield thickness (CST) and achieving diagnostic concordance for retinal lesions compared with clinic-based spectral-domain OCT (SD-OCT). Methods This comparative, cross-sectional study was conducted between August 2020 and February 2021. Two groups of adult participants were recruited: (1) a selected cohort of 160 participants with confirmed diagnosis and (2) a consecutive cohort of 315 participants recruited randomly. All participants underwent self-imaging OCT examination, as well as standard OCT examination. CST was automatically calculated for comparisons between the two OCT devices. Diagnostic concordance for retinal lesions and the success rate of self-imaging were assessed within the consecutive cohort. Results In the selected cohort, self-imaging OCT images yielded consistent CST with SD-OCT, with a mean difference of 0.1±7.7 pm for normal eyes, 4.9±10.6 pm for macular oedema, -1.3±9.5 pm for choroidal neovascularisation, 5.0±7.8 pm for epiretinal membrane. The self-imaging OCT also demonstrated good repeatability, with a mean test--retest difference in CST of 0.7±3.9 pm and limits of agreement ranging from -6.9 to 8.3 pm. Additionally, within the consecutive cohort, interdevice k values ranged for detecting various retinal lesions ranged from 0.8 to 1.0, except in the cases of retinal detachment (κ=0.5). All eyes (100%) in the selected cohort and 242 eyes (76.8%) in the consecutive cohort successfully completed self-imaging. Participants spent less time on self-imaging compared with SD-OCT operated by a technician (66.7±20.1 vs 73.3±32.5, p<0.01). A majority of participants (90%) found the self-imaging process 'easy' and 'comfortable'. Conclusions and relevance This study demonstrates that our self-imaging OCT and clinical-used SD-OCT are highly consistent not only in measuring the CST but also in identifying most retinal lesions. [ABSTRACT FROM AUTHOR]