226 results found
Choi S, Hill D, Young J, et al., 2024, Image processing and supervised machine learning for retinal microglia characterization in senescence., Methods Cell Biol, Vol: 181, Pages: 109-125, ISSN: 0091-679X
The process of senescence impairs the function of cells and can ultimately be a key factor in the development of disease. With an aging population, senescence-related diseases are increasing in prevalence. Therefore, understanding the mechanisms of cellular senescence within the central nervous system (CNS), including the retina, may yield new therapeutic pathways to slow or even prevent the development of neuro- and retinal degenerative diseases. One method of probing the changing functions of senescent retinal cells is to observe retinal microglial cells. Their morphological structure may change in response to their surrounding cellular environment. In this chapter, we show how microglial cells in the retina, which are implicated in aging and diseases of the CNS, can be identified, quantified, and classified into five distinct morphotypes using image processing and supervised machine learning algorithms. The process involves dissecting, staining, and mounting mouse retinas, before image capture via fluorescence microscopy. The resulting images can then be classified by morphotype using a support vector machine (SVM) we have recently described showing high accuracy. This SVM model uses shape metrics found to correspond with qualitative descriptions of the shape of each morphotype taken from existing literature. We encourage more objective and widespread use of methods of quantification such as this. We believe automatic delineation of the population of microglial cells in the retina, could potentially lead to their use as retinal imaging biomarkers for disease prediction in the future.
Wei W, Southern J, Zhu K, et al., 2023, Deep learning to detect macular atrophy in wet age-related macular degeneration using optical coherence tomography, Scientific Reports, Vol: 13, Pages: 1-10, ISSN: 2045-2322
Here, we have developed a deep learning method to fully automatically detect and quantify six main clinically relevant atrophic features associated with macular atrophy (MA) using optical coherence tomography (OCT) analysis of patients with wet age-related macular degeneration (AMD). The development of MA in patients with AMD results in irreversible blindness, and there is currently no effective method of early diagnosis of this condition, despite the recent development of unique treatments. Using OCT dataset of a total of 2211 B-scans from 45 volumetric scans of 8 patients, a convolutional neural network using one-against-all strategy was trained to present all six atrophic features followed by a validation to evaluate the performance of the models. The model predictive performance has achieved a mean dice similarity coefficient score of 0.706 ± 0.039, a mean Precision score of 0.834 ± 0.048, and a mean Sensitivity score of 0.615 ± 0.051. These results show the unique potential of using artificially intelligence-aided methods for early detection and identification of the progression of MA in wet AMD, which can further support and assist clinical decisions.
Burgos-Blasco B, Vidal-Villegas B, Yap TE, et al., 2023, Effects of COVID-19 pandemic on glaucoma appointment scheduling in a tertiary hospital in London, UK, European Journal of Ophthalmology, Pages: 1-13, ISSN: 1120-6721
PURPOSE: To investigate the impact of the delay in patient appointments caused by the COVID-19 pandemic and the triage system on the glaucomatous disease of patients in a London tertiary hospital. METHODS: Observational retrospective study that randomly selected 200 glaucoma patients with more than 3 months of unintended delay for their post-COVID visit and other inclusion and exclusion criteria. Demographic information, clinical data, number of drugs, best-corrected visual acuity (BCVA), intraocular pressure (IOP), visual field (VF) mean deviation (MD), and global peripapillary retinal nerve fibre layer (pRNFL) thickness were obtained from the pre- and post-COVID visit. At the post-COVID visit, the clinical outcomes subjective clinical concern and change of treatment or need for surgery were also annotated. The variables were stratified by glaucoma severity (according to the MD into early, moderate and advanced) and by delay time (more and less than 12 months) and analysed using SPSS. RESULTS: We included 121 eyes (from 71 patients). The median patient age was 74 years (interquartile range -IQR- 15), 54% were males and 52% Caucasians. Different glaucoma types and all glaucoma severities were included. When data was stratified for glaucoma severity, at the pre-COVID visit, significant differences in BCVA, CCT and IOP were observed and there were significantly higher values in the early glaucoma group. The median follow-up delay was 11 months (IQR 8), did not differ between the glaucoma severity groups and did not correlate to the glaucoma severity. At the post-COVID visit, significant differences in BCVA, IOP, and Global pRNFL thickness were observed between the glaucoma severity groups, as lower BCVA and higher IOP and pRNFL thickness were observed in the early glaucoma group. At the post-COVID visit there was cause for concern in 40 eyes: 5 were followed more closely, 22 had a change of treatment and 13 were booked for surgery (3 for cataract and 10 for glaucoma s
Hill D, Choi S, Cordeiro MF, 2023, In Vivo Detection of Retinal Ganglion Cell Stress in Rodents with DARC., Methods Mol Biol, Vol: 2708, Pages: 123-129
DARC (detection of apoptosing retinal cells) uses fluorescently tagged Annexin A5 to identify retinal apoptosis non-invasively in vivo using a confocal laser scanning ophthalmoscope (cSLO). This can provide insights into the presence and progression of disease pathology and the efficacy of neuroprotective intervention. The methods of administration, imaging, and quantification of DARC, including the operation of the cSLO, are described here.
Wei W, Anantharanjit R, Patel RP, et al., 2023, Detection of macular atrophy in age-related macular degeneration aided by artificial intelligence, Expert Review of Molecular Diagnostics: new diagnostic technologies are set to revolutionise healthcare, Vol: 23, Pages: 485-494, ISSN: 1473-7159
INTRODUCTION: Age-related macular degeneration (AMD) is a leading cause of irreversible visual impairment worldwide. The endpoint of AMD, both in its dry or wet form, is macular atrophy (MA) which is characterized by the permanent loss of the RPE and overlying photoreceptors either in dry AMD or in wet AMD. A recognized unmet need in AMD is the early detection of MA development. AREAS COVERED: Artificial Intelligence (AI) has demonstrated great impact in detection of retinal diseases, especially with its robust ability to analyze big data afforded by ophthalmic imaging modalities, such as color fundus photography (CFP), fundus autofluorescence (FAF), near-infrared reflectance (NIR), and optical coherence tomography (OCT). Among these, OCT has been shown to have great promise in identifying early MA using the new criteria in 2018. EXPERT OPINION: There are few studies in which AI-OCT methods have been used to identify MA; however, results are very promising when compared to other imaging modalities. In this paper, we review the development and advances of ophthalmic imaging modalities and their combination with AI technology to detect MA in AMD. In addition, we emphasize the application of AI-OCT as an objective, cost-effective tool for the early detection and monitoring of the progression of MA in AMD.
Rahman L, Hafejee A, Anantharanjit R, et al., 2022, Accelerating precision ophthalmology: recent advances, Expert Review of Precision Medicine and Drug Development, Vol: 7, Pages: 150-161, ISSN: 2380-8993
IntroductionThe future of ophthalmology is precision medicine. With a growing incidence of lifestyle-associated ophthalmic disease such as diabetic retinopathy, the use of technology has the potential to overcome the burden on clinical specialists. Advances in precision medicine will help improve diagnosis and better triage those with higher clinical need to the appropriate experts, as well as providing a more tailored approach to treatment that could help transform patient management.Areas coveredA detailed literature review was conducted using OVID Medline and PubMed databases to explore advances in precision medicine within the areas of retinal disease, glaucoma, cornea, cataracts and uveitis. Over the last three years [2019 – 2022] are explored, particularly discussing technological and genomic advances in screening, diagnosis, and management within these fields.Expert opinionArtificial intelligence and its subspecialty deep learning provide the most substantial ways in which diagnosis and management of ocular diseases can be further developed within the advancing field of precision medicine. Future challenges include optimal training sets for algorithms and further developing pharmacogenetics in more specialized areas.
Chrystal PW, Lambacher NJ, Doucette LP, et al., 2022, The inner junction protein CFAP20 functions in motile and non-motile cilia and is critical for vision, NATURE COMMUNICATIONS, Vol: 13
Yap TE, Davis BM, Bloom PA, et al., 2022, Glaucoma Rose Plot Analysis: detecting early structural progression using angular histograms, Ophthalmology Glaucoma, Vol: 5, Pages: 562-571, ISSN: 2589-4196
PurposeTo evaluate the novel Rose Plot Analysis (RPA) in the analysis and presentation of glaucoma structural progression data.DesignCase-control image analysis study using retrospective retinal imaging series.SubjectsSubjects with open-angle glaucoma with at least 5 registered spectral-domain OCT scans.MethodsGlaucoma RPA was developed, combining a novel application of angular histograms and dynamic cluster analysis of circumpapillary retinal nerve fiber layer (cRNFL) OCT data. Rose Plot Analysis plots were created for each eye and each visit. Significant clusters of progression were indicated in red. Three masked clinicians categorized all RPA plots (progressing, not progressing), in addition to measuring the significant RPA area. A masked OCT series assessment with linear regression of averaged global and sectoral cRNFL thicknesses was conducted as the clinical imaging standard.Main Outcome MeasuresInterobserver agreement was compared between RPA and the clinical imaging standard. Discriminative ability was assessed using receiver-operating characteristic curves. The time to detection of progression was compared using a Kaplan–Meier survival analysis, and the agreement of RPA with the clinical imaging standard was calculated.ResultsSeven hundred fourty-three scans from 98 eyes were included. Interobserver agreement was significantly greater when categorizing RPA (κ, 0.86; 95% confidence interval [CI], 0.81–0.91) compared with OCT image series (κ, 0.66; 95% CI, 0.54–0.77). The discriminative power of RPA to differentiate between eyes that were progressing and not progressing (area under the curve [AUC], 0.97; 95% CI, 0.92–1.00) was greater than that of global cRNFL thickness (AUC, 0.71; 95% CI, 0.59–0.82; P < 0.0001) and equivalent to that of sectoral cRNFL regression (AUC, 0.97; 95% CI, 0.92–1.00). A Kaplan–Meier survival analysis showed that progression was detected 8.7 months sooner by RPA than by global
Abdulhussein D, Yap T, Manzer H, et al., 2022, Factors impacting participation in research during the COVID-19 pandemic, Trials, Vol: 23, Pages: 1-9, ISSN: 1745-6215
BackgroundUnderstanding public and patient attitudes to clinical research is paramount to successful recruitment. The COVID-19 pandemic has led to additional hurdles in achieving this. Our aim is to understand the current factors and attitudes towards clinical trial participation in order to assist in recruitment to clinical trials.MethodsWe conducted face-to-face interviews with patients in the outpatient department at a tertiary eye hospital facilitated by a 32-item questionnaire developed by the research team. Patient characteristics were correlated with their responses, in addition to qualitative thematic text analysis.ResultsA total of 53 patients were interviewed. Forty per cent indicated that they would be willing to participate in clinical research in the current climate. General motivating factors for involvement in research included personal gain, altruism and contribution to innovation. Factors limiting participation included concerns regarding own safety, inconvenience, accessibility and lack of benefit. 22.6% of participants felt that the COVID-19 pandemic has changed their outlook on research. These were categorised into positive (increased awareness of the importance and need for research, altruism) and negative (increased anxiety, need to minimise exposure to the hospital environment) influences.ConclusionsFactors influencing patients’ decisions to participate in trials are similar to those observed prior to COVID-19 but with an increased focus on the environment the research is conducted in. The COVID-19 pandemic has had positive and negative impacts on patient attitudes towards research. Trial design, with a particular focus on setting and safety measures, in reassuring patients is increasingly important.
Fu MX, Normando EM, Luk SMH, et al., 2022, MicroShunt versus trabeculectomy for surgical management of glaucoma: a retrospective analysis, Journal of Clinical Medicine, Vol: 11, ISSN: 2077-0383
This case-control study aims to compare the efficacy, safety, and postoperative burden of MicroShunt versus trabeculectomy. The first consecutive cohort of MicroShunt procedures (n = 101) was matched to recent historical trabeculectomy procedures (n = 101) at two London hospital trusts. Primary endpoints included changes in intraocular pressure (IOP) and glaucoma medications. Secondary outcome measures included changes in retinal nerve fibre layer (RNFL) thickness, rates of complications, further theatre interventions, and the number of postoperative visits. From the baseline to Month-18, the median [interquartile range] IOP decreased from 22 [17–29] mmHg (on 4 [3–4] medications) to 15 [10–17] mmHg (on 0 [0–2] medications) and from 20 [16–28] mmHg (on 4 [3–4] medications) to 11 [10–13] mmHg (on 0 [0–0] medications) in the MicroShunt and trabeculectomy groups, respectively. IOP from Month-3 was significantly higher in the MicroShunt group (p = 0.006), with an increased number of medications from Month-12 (p = 0.024). There were greater RNFL thicknesses from Month-6 in the MicroShunt group (p = 0.005). The rates of complications were similar (p = 0.060) but with fewer interventions (p = 0.031) and postoperative visits (p = 0.001) in the MicroShunt group. Therefore, MicroShunt has inferior efficacy to trabeculectomy in lowering IOP and medications but provides a better safety profile and postoperative burden and may delay RNFL loss.
Wu Y, Hu Y, Jiang N, et al., 2022, Quantitative brain-derived neurotrophic factor lateral flow assay for point-of-care detection of glaucoma, Lab on a Chip: miniaturisation for chemistry, physics, biology, materials science and bioengineering, Vol: 22, Pages: 3521-3532, ISSN: 1473-0189
Glaucoma, a ruinous group of eye diseases with progressive degeneration of the optic nerve and vision loss, is the leading cause of irreversible blindness. Accurate and timely diagnosis of glaucoma is critical to promote secondary prevention and early disease-modifying therapies. Reliable, cheap, and rapid tests for measuring disease activities are highly required. Brain-derived neurotrophic factor (BDNF) plays an important role in maintaining the function and survival of the central nervous system. Decreased BDNF levels in tear fluid can be seen in glaucoma patients, which indicates that BDNF can be regarded as a novel biomarker for glaucoma. Conventional ELISA is the standard method to measure the BDNF level, but the multi-step operation and strict storage conditions limit its usage in point-of-care settings. Herein, a one-step and a portable glaucoma detection method was developed based on the lateral flow assay (LFA) to quantify the BDNF concentration in artificial tear fluids. The results of the LFA were analyzed by using a portable and low-cost system consisting of a smartphone camera and a dark readout box fabricated by 3D printing. The concentration of BDNF was quantified by analyzing the colorimetric intensity of the test line and the control line. This assay yields reliable quantitative results from 25 to 300 pg mL-1 with an experimental detection limit of 14.12 pg mL-1. The LFA shows a high selectivity for BDNF and high stability in different pH environments. It can be readily adapted for sensitive and quantitative testing of BDNF in a point-of-care setting. The BDNF LFA strip shows it has great potential to be used in early glaucoma detection.
MacCormick IJC, Zhang B, Hill D, et al., 2022, A proposed theoretical framework for retinal biomarkers, Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring, Vol: 14, ISSN: 2352-8729
ObjectivePropose a theoretical framework for retinal biomarkers of Alzheimer's disease (AD).BackgroundThe retina and brain share important biological features that are relevant to AD. Developing retinal biomarkers of AD is a strategic priority but as yet none have been validated for clinical use. Part of the reason may be that fundamental inferential assumptions have been overlooked. Failing to recognize these assumptions will disadvantage biomarker discovery and validation, but incorporating them into analyses could facilitate translation.New theoryThe biological assumption that a disease causes analogous effects in the brain and retina can be expressed within a Bayesian network. This allows inferences about abstract theory and individual events, and provides an opportunity to falsify the foundational hypothesis of retina–brain analogy. Graphical representation of the relationships between variables simplifies comparison between studies and facilitates judgements about whether key assumptions are valid given the current state of knowledge.Major challengesThe framework provides a visual approach to retinal biomarkers and may help to rationalize analysis of future studies. It suggests possible reasons for inconsistent results in existing literature on AD biomarkers.Linkage to other theoriesThe framework can be modified to describe alternative theories of retinal biomarker biology, such as retrograde degeneration resulting from brain disease, and can incorporate confounding factors such as co-existent glaucoma or macular degeneration. Parallels with analogue confirmation theory and surrogate marker validation suggest strengths and weaknesses of the framework that can be anticipated when developing analysis plans.
Yap TE, Davis B, Bloom P, et al., 2022, Glaucoma rose plots: redesigning circumpapillary progression analysis, Publisher: ASSOC RESEARCH VISION OPHTHALMOLOGY INC, ISSN: 0146-0404
Maddison J, Choi S, Cordeiro MF, 2022, Characterising DARC (Detecting Apoptosing Retinal Cells) spots in glaucoma and healthy eyes, Publisher: ASSOC RESEARCH VISION OPHTHALMOLOGY INC, ISSN: 0146-0404
Guo L, Choi S, Bikkannavar P, et al., 2022, Microglia: Key Players in Retinal Ageing and Neurodegeneration, FRONTIERS IN CELLULAR NEUROSCIENCE, Vol: 16
Lemmens S, Rossetti L, Oddone F, et al., 2022, Comparison of preserved bimatoprost 0.01% with preservative-free tafluprost: A randomised, investigator-masked, 3-month crossover, multicentre trial, SPORT II, EUROPEAN JOURNAL OF OPHTHALMOLOGY, Vol: 32, Pages: 968-975, ISSN: 1120-6721
Choi S, Hill D, Guo L, et al., 2022, Automated characterisation of microglia in ageing mice using image processing and supervised machine learning algorithms, Scientific Reports, Vol: 12, ISSN: 2045-2322
The resident macrophages of the central nervous system, microglia, are becoming increasingly implicated as active participants in neuropathology and ageing. Their diverse and changeable morphology is tightly linked with functions they perform, enabling assessment of their activity through image analysis. To better understand the contributions of microglia in health, senescence, and disease, it is necessary to measure morphology with both speed and reliability. A machine learning approach was developed to facilitate automatic classification of images of retinal microglial cells as one of five morphotypes, using a support vector machine (SVM). The area under the receiver operating characteristic curve for this SVM was between 0.99 and 1, indicating strong performance. The densities of the different microglial morphologies were automatically assessed (using the SVM) within wholemount retinal images. Retinas used in the study were sourced from 28 healthy C57/BL6 mice split over three age points (2, 6, and 28-months). The prevalence of ‘activated’ microglial morphology was significantly higher at 6- and 28-months compared to 2-months (p < .05 and p < .01 respectively), and ‘rod’ significantly higher at 6-months than 28-months (p < 0.01). The results of the present study propose a robust cell classification SVM, and further evidence of the dynamic role microglia play in ageing.
Guo L, Luong V, Gregson A, et al., 2022, VSN16S, an agonist of the cannabinoid receptor, reduces IOP profiles and exhibits neuroprotective properties in a rat model of glaucoma, ACTA OPHTHALMOLOGICA, Vol: 100, ISSN: 1755-375X
Cordeiro MF, Hill D, Patel R, et al., 2022, Detecting retinal cell stress and apoptosis with DARC: progression from lab to clinic, Progress in Retinal and Eye Research, Vol: 86, ISSN: 1350-9462
DARC (Detection of Apoptosing Retinal Cells) is a retinal imaging technology that has been developed within the last 2 decades from basic laboratory science to Phase 2 clinical trials. It uses ANX776 (fluorescently labelled Annexin A5) to identify stressed and apoptotic cells in the living eye. During its development, DARC has undergone biochemistry optimisation, scale-up and GMP manufacture and extensive preclinical evaluation. Initially tested in preclinical glaucoma and optic neuropathy models, it has also been investigated in AMD, Alzheimer's, Parkinson's and Diabetic models, and used to assess efficacy of therapies. Progression to clinical trials has not been speedy. Intravenous ANX776 has to date been found to be safe and well-tolerated in 129 patients, including 16 from Phase 1 and 113 from Phase 2. Results on glaucoma and AMD patients have been recently published, and suggest DARC with an AI-aided algorithm can be used to predict disease activity. New analyses of DARC in GA (Geographic Atrophy) prediction are reported here. Although further studies are needed to validate these findings, it appears there is potential for the technology to be used as a biomarker. Much larger clinical studies will be needed before it can be considered as a diagnostic, although the relatively non-invasive nature of the nasal as opposed to intravenous administration would widen its acceptability in the future as a screening tool.This review describes DARC development and its progression into Phase 2 clinical trials from lab-based research. It discusses hypotheses, potential challenges, and regulatory hurdles in translating technology.
Yap TE, Husein S, Miralles de Imperial-Ollero JA, et al., 2021, The efficacy of dexamethasone implants following anti-VEGF failure for macular oedema in retinal vein occlusion, EUROPEAN JOURNAL OF OPHTHALMOLOGY, Vol: 31, Pages: 3214-3222, ISSN: 1120-6721
Zollet P, Yap TE, Cordeiro MF, 2021, Detecting Apoptosis as a Clinical Endpoint for Proof of a Clinical Principle, OPHTHALMOLOGICA, Vol: 244, Pages: 408-417, ISSN: 0030-3755
Glaucoma is the leading cause of irreversible blindness globally which significantly affects the quality of life and has a substantial economic impact. Effective detective methods are necessary to identify glaucoma as early as possible. Regular eye examinations are important for detecting the disease early and preventing deterioration of vision and quality of life. Current methods of measuring disease activity are powerful in describing the functional and structural changes in glaucomatous eyes. However, there is still a need for a novel tool to detect glaucoma earlier and more accurately. Tear fluid biomarker analysis and new imaging technology provide novel surrogate endpoints of glaucoma. Artificial intelligence is a post-diagnostic tool that can analyse ophthalmic test results. A detail review of currently used clinical tests in glaucoma include intraocular pressure test, visual field test and optical coherence tomography are presented. The advanced technologies for glaucoma measurement which can identify specific disease characteristics, as well as the mechanism, performance and future perspectives of these devices are highlighted. Applications of AI in diagnosis and prediction in glaucoma are mentioned. With the development in imaging tools, sensor technologies and artificial intelligence, diagnostic evaluation of glaucoma must assess more variables to facilitate earlier diagnosis and management in the future.
Shi Y, Jiang N, Bikkannavar P, et al., 2021, Ophthalmic sensing technologies for ocular disease diagnostics, Analyst, Vol: 146, Pages: 6416-6444, ISSN: 0003-2654
Point-of-care diagnosis and personalized treatments are critical in ocular physiology and disease. Continuous sampling of tear fluid for ocular diagnosis is a need for further exploration. Several techniques have been developed for possible ophthalmological applications, from traditional spectroscopies to wearable sensors. Contact lenses are commonly used devices for vision correction, as well as for other therapeutic and cosmetic purposes. They are increasingly being developed into ocular sensors, being used to sense and monitor biochemical analytes in tear fluid, ocular surface temperature, intraocular pressure, and pH value. These sensors have had success in detecting ocular conditions, optimizing pharmaceutical treatments, and tracking treatment efficacy in point-of-care settings. However, there is a paucity of new and effective instrumentation reported in ophthalmology. Hence, this review will summarize the applied ophthalmic technologies for ocular diagnostics and tear monitoring, including both conventional and biosensing technologies. Besides applications of smart readout devices for continuous monitoring, targeted biomarkers are also discussed for the convenience of diagnosis of various ocular diseases. A further discussion is also provided for future aspects and market requirements related to the commercialization of novel types of contact lens sensors.
Szymanska M, Mahmood D, Yap TE, et al., 2021, Recent advancements in the medical treatment of diabetic retinal disease, International Journal of Molecular Sciences, Vol: 22, Pages: 1-25, ISSN: 1422-0067
Diabetic retinal disease remains one of the most common complications of diabetes mellitus (DM) and a leading cause of preventable blindness. The mainstay of management involves glycemic control, intravitreal, and laser therapy. However, intravitreal therapy commonly requires frequent hospital visits and some patients fail to achieve a significant improvement in vision. Novel and long-acting therapies targeting a range of pathways are warranted, while evidence to support optimal combinations of treatments is currently insufficient. Improved understanding of the molecular pathways involved in pathogenesis is driving the development of therapeutic agents not only targeting visible microvascular disease and metabolic derangements, but also inflammation and accelerated retinal neurodegeneration. This review summarizes the current and emerging treatments of diabetic retinal diseases and provides an insight into the future of managing this important condition.
Choi S, Guo L, Cordeiro MF, 2021, Retinal and brain microglia in multiple sclerosis and neurodegeneration, Cells, Vol: 10, Pages: 1-21, ISSN: 2073-4409
Microglia are the resident immune cells of the central nervous system (CNS), including the retina. Similar to brain microglia, retinal microglia are responsible for retinal surveillance, rapidly responding to changes in the environment by altering morphotype and function. Microglia become activated in inflammatory responses in neurodegenerative diseases, including multiple sclerosis (MS). When activated by stress stimuli, retinal microglia change their morphology and activity, with either beneficial or harmful consequences. In this review, we describe characteristics of CNS microglia, including those in the retina, with a focus on their morphology, activation states and function in health, ageing, MS and other neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, glaucoma and retinitis pigmentosa, to highlight their activity in disease. We also discuss contradictory findings in the literature and the potential ways of reducing inconsistencies in future by using standardised methodology, e.g., automated algorithms, to enable a more comprehensive understanding of this exciting area of research.
Guo L, Luong V, Gregson A, et al., 2021, VSN16S, an agonist of the cannabinoid receptor, reduces IOP profiles and exhibits neuroprotective properties in a rat model of glaucoma, Annual Meeting of the Association-for-Research-in-Vision-and-Ophthalmology (ARVO), Publisher: ASSOC RESEARCH VISION OPHTHALMOLOGY INC, ISSN: 0146-0404
Choi S, Hill D, Guo L, et al., 2021, Automated Characterisation of Retinal Microglia in a Multiple Sclerosis Mouse Model and Age-Matched Controls, Annual Meeting of the Association-for-Research-in-Vision-and-Ophthalmology (ARVO), Publisher: ASSOC RESEARCH VISION OPHTHALMOLOGY INC, ISSN: 0146-0404
Shamsher E, Guo L, Davis BM, et al., 2021, Resveratrol nanoparticles are neuroprotective in a rat model of glaucoma, Annual Meeting of the Association-for-Research-in-Vision-and-Ophthalmology (ARVO), Publisher: ASSOC RESEARCH VISION OPHTHALMOLOGY INC, ISSN: 0146-0404
Hill D, Compagnoni C, Cordeiro MF, 2021, Investigational neuroprotective compounds in clinical trials for retinal disease, EXPERT OPINION ON INVESTIGATIONAL DRUGS, Vol: 30, Pages: 571-577, ISSN: 1354-3784
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.