Extracellular vesicles (EVs) secreted by mesenchymal stromal cells (MSCs) have been proposed to be a key mechanistic link in the therapeutic efficacy of cells in response to cellular injuries through paracrine effects. We hypothesize that inflammatory stimulation of MSCs results in the release of EVs that have greater anti-inflammatory effects. The present study evaluates the immunomodulatory abilities of EVs derived from inflammation-stimulated and naive MSCs (MSCEv 1 and MSCEv, respectively) isolated using a current Good Manufacturing Practice-compliant tangential flow filtration system. Detailed characterization of both EVs revealed differences in protein composition, cytokine profiles, and RNA content, despite similarities in size and expression of common surface markers. MSCEv 1 further attenuated release of pro-inflammatory cytokines in vitro when compared to MSCEv, with a distinctly different pattern of EV-uptake by activated primary leukocyte subpopulations. The efficacy of EVs was partially attributed to COX2/PGE 2 expression. The present study demonstrates that inflammatory stimulation of MSCs renders release of EVs that have enhanced anti-inflammatory properties partially due to COX2/PGE 2 pathway alteration. STEM CELLS 2018;36:79-90 SIGNIFICANCE STATEMENTPrevious work has identified mesenchymal stromal cell-derived extracellular vesicles (MSCEv) as mediators of cell-cell communication and effectors of cellular/tissue change. This study isolated MSCEv using a clinically propitious filtration system after stimulation with inflammatory cytokines, characterized their composition, and evaluated their effect on inflammation, along with their potential mechanism of action and interaction with potential target cells. This study identified important compositional differences between control and stimulated MSCEv in cytokine and RNA content. Furthermore, stimulated MSCEv attenuate TNF-a and IFN-g release from activated splenocytes compared to standard MSCEv (and liposomal controls). The nature of MSCEv interaction with cells likely involves cellular internalization, so this study fluorescently labeled MSCEv prior to coculture with activated leukocytes to determine changes in uptake activity in response to several antigens. These studies demonstrate a specific anti-inflammatory, MSCEvmediated response and the capacity to change efficacy in response to inflammatory cues, creating the foundation for enhancing the efficacy of translational efforts using MSCEv for targeting inflammatory injuries and diseases. This represents a new paradigm for generation of extracellular vesicles targeting specific pathologies.
Purpose: Previous deep learning studies on optical coherence tomography (OCT) mainly focused on diabetic retinopathy and age-related macular degeneration. We proposed a deep learning model that can identify epiretinal membrane (ERM) in OCT with ophthalmologist-level performance. Design: Cross-sectional study. Participants: A total of 3,618 central fovea cross section OCT images from 1,475 eyes of 964 patients. Methods: We retrospectively collected 7,652 OCT images from 1,197 patients. From these images, 2,171 were normal and 1,447 were ERM OCT. A total of 3,141 OCT images was used as training dataset and 477 images as testing dataset. DL algorithm was used to train the interpretation model. Diagnostic results by four board-certified non-retinal specialized ophthalmologists on the testing dataset were compared with those generated by the DL model. Main Outcome Measures: We calculated for the derived DL model the following characteristics: sensitivity, specificity, F1 score and area under curve (AUC) of the receiver operating characteristic (ROC) curve. These were calculated according to the gold standard results which were parallel diagnoses of the retinal specialist. Performance of the DL model was finally compared with that of non-retinal specialized ophthalmologists. Results: Regarding the diagnosis of ERM in OCT images, the trained DL model had the following characteristics in performance: sensitivity: 98.7%, specificity: 98.0%, and F1 score: 0.945. The accuracy on the training dataset was 99.7% (95% CI: 99.4 - 99.9%), and for the testing dataset, diagnostic accuracy was 98.1% (95% CI: 96.5 - 99.1%). AUC of the ROC curve was 0.999. The DL model slightly outperformed the average non-retinal specialized ophthalmologists. Conclusions: An ophthalmologist-level DL model was built here to accurately identify ERM in OCT images. The performance of the model was slightly better than the average non-retinal specialized ophthalmologists. The derived model may play a role to assist clinicians to promote the efficiency and safety of healthcare in the future.
Coronavirus disease 2019 (COVID-19) vaccines are associated with several ocular manifestations. Emerging evidence has been reported; however, the causality between the two is debatable. We aimed to investigate the risk of retinal vascular occlusion after COVID-19 vaccination. This retrospective cohort study used the TriNetX global network and included individuals vaccinated with COVID-19 vaccines between January 2020 and December 2022. We excluded individuals with a history of retinal vascular occlusion or those who used any systemic medication that could potentially affect blood coagulation prior to vaccination. To compare the risk of retinal vascular occlusion, we employed multivariable-adjusted Cox proportional hazards models after performing a 1:1 propensity score matching between the vaccinated and unvaccinated cohorts. Individuals with COVID-19 vaccination had a higher risk of all forms of retinal vascular occlusion in 2 years after vaccination, with an overall hazard ratio of 2.19 (95% confidence interval 2.00–2.39). The cumulative incidence of retinal vascular occlusion was significantly higher in the vaccinated cohort compared to the unvaccinated cohort, 2 years and 12 weeks after vaccination. The risk of retinal vascular occlusion significantly increased during the first 2 weeks after vaccination and persisted for 12 weeks. Additionally, individuals with first and second dose of BNT162b2 and mRNA-1273 had significantly increased risk of retinal vascular occlusion 2 years following vaccination, while no disparity was detected between brand and dose of vaccines. This large multicenter study strengthens the findings of previous cases. Retinal vascular occlusion may not be a coincidental finding after COVID-19 vaccination.
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