Pinakin Gunvant Davey

Background/Objectives: Diabetic retinopathy (DR) is a leading cause of vision loss worldwide, and its pathology is driven by chronic hyperglycemia, elevated oxidative stress, inflammation, and microvascular dysfunction. Polyunsaturated fatty acids (PUFAs), particularly omega-3 and omega-6 fatty acids, influence inflammatory and angiogenic pathways, but their role in DR prevention and progression remains uncertain. This integrative review synthesizes current evidence on the effects of PUFAs in DR. Methods: A comprehensive literature search was conducted and eligible studies included human cell culture, animal model, observational, Mendelian randomization, and interventional studies. A total of 44 studies meeting inclusion criteria were systematically analyzed and categorized by study design. Results: Human trials with whole-diet/complex supplements suggest that higher intake or circulating levels of omega-3 PUFAs, particularly docosahexaenoic acid (DHA), are associated with reduced risk and severity of DR. A Mediterranean diet enriched with omega-3 sources demonstrated consistent protective associations. However, randomized controlled trials using isolated omega-3 supplementation reported mixed findings, with some showing no significant effect on disease progression (e.g., ASCEND). Mechanistic studies indeed support biological plausibility, demonstrating that omega-3 PUFAs reduce oxidative stress, inhibit inflammatory signaling, and modulate angiogenesis by attenuating vascular endothelial growth factor activity. Emerging evidence also suggests the potential protective role of certain omega-6 fatty acids, though findings remain heterogeneous. Conclusions: PUFAs, particularly omega-3 fatty acids, may play a protective role in DR through anti-inflammatory, antioxidant, and anti-angiogenic mechanisms. These outcomes appear influenced by dietary context, dosage, and disease stage, highlighting the need for additional long-term, well-designed studies.

Background: Carotenoid components have a role in maintaining eye and brain development and function in children. Objectives: This scoping review collates the current knowledge about the benefits of carotenoids in improving visual and cognitive function outcomes in children. Design: This review includes observational and interventional published studies to date (January 2026) through a literature search on PubMed, Web of Science, Embase, Mendeley, and Google Scholar database platforms. We have described and measured carotenoid status in diet, serum, skin, and human milk in relation to eye and cognitive development and function in children. Results: Human body carotenoids, α-carotene, β-carotene, lycopene, cryptoxanthin, lutein, and zeaxanthin, have been detected in significant amounts in the brain, whereas the xanthophylls lutein, zeaxanthin, and meso-zeaxanthin, are found in the eyes. Lutein, zeaxanthin, and retinoids in the ocular tissue are responsible for visual function and have been associated with visual neurocognitive skills in children. In addition, lutein, zeaxanthin, and β-carotene have been associated with cognitive function tasks in infants and children. Conclusions: This review shows emerging evidence on the benefits of carotenoids in children, primarily from cross-sectional studies and longitudinal cohort studies. We found a paucity of carotenoid intervention and controlled trials for direct carotenoid exposure and its relative effect on neurocognitive function and visual milestone development during early life. Additionally, further long-term studies are required to confirm carotenoid exposure in early life and its benefits to eye health and cognitive skills outcomes in later life.

Healthcare systems worldwide are burdened significantly due to glaucoma, which is a leading cause of irreversible blindness. A total of 76 million are currently affected, and it is estimated that by the year 2040, 112 million will be affected by glaucoma. Minimally invasive glaucoma surgery (MIGS) is a recent innovation that plays a key role in glaucoma management. We aimed to conduct a systematic review of the safety and efficacy of MIGS devices and procedures and their use in primary open-angle glaucoma (POAG) to lower intraocular pressure (IOP). Methods: A comprehensive electronic search of the PubMed database was conducted, and randomized controlled trials (RCTs) comparing MIGS devices and techniques with cataract surgery or other glaucoma procedures that had been published by 1 May 2025 were included. Results: Thirty RCTs were included in the systematic review. Studies show that MIGSs are as safe and effective as other procedures, including phacoemulsification and trabeculectomy, at lowering IOP. Conclusions: Short-term trials indicate that MIGSs are a safe and effective treatment option for primary open-angle glaucoma. MIGS procedures lead to favorable outcomes, including decreases in mean IOP and medication use, compared with other glaucoma procedures or standalone phacoemulsification. Independent long-term follow-up studies are needed further to elucidate the efficacy and long-term safety of MIGS.

Background/Objectives: Macular pigment optical density (MPOD) is an important clinical biomarker for ocular conditions like macular degeneration, diabetic eye disease, and digital eye strain. Additionally, its measurements can be essential in health assessment for visual function, systemic diseases, and brain health. We aimed to assess the repeatability, agreement, and effects of the learning curve of the new portable handheld heterochromatic flicker photometer, Zx Pro, in measuring MPOD in a wide age range of ocular-healthy adults, compared to the MPOD measurements obtained using the clinically available QuantifEye device. Methods: Seventy-six participants performed one practice attempt and two study-related MPOD measurements with the Zx Pro and the QuantifEye. Results: The Pearson correlation between the study-related MPOD measurements for Zx Pro and QuantifEye devices was 90% and 85%, respectively. Bland and Altman plots show excellent agreement between the device’s MPOD data, with 95% limits of an agreement being −0.10 to +0.11 du. The mean difference between the practice attempt and the study-related measurements was not statistically significant for Zx Pro but was significant for QuantifEye (Repeated measures ANOVA p = 0.325 and p = 0.015, respectively). Conclusions: The Zx Pro provides excellent repeatable MPOD measurements, has an insignificant learning curve, and is in good agreement with the predicate device.

Background: Carotenoids are present throughout retina and body its dense deposition leads to an identifiable yellow spot in the macula. Macular pigment optical density (MPOD) measured in the macula is vital to macular well-being and high-resolution visual acuity. MPOD has also been associated with various health and disease states. We sought to review the literature on this topic and summarize MPODs role as a measurable modifiable clinical biomarker, particularly as a measure of the eye’s antioxidant capacity in the context of oxidative damage and retinal ischemia. Methods: A literature review collated the articles relevant to MPOD, carotenoid intake or supplementation, and their influence on various health and disease states. Results: Literature reveals that MPOD can serve as a reliable biomarker for assessing the retinal defense mechanisms against oxidative stress and the deleterious effects of excessive light exposure. Elevated MPOD levels offer robust protection against the onset and progression of age-related macular degeneration (AMD), a prevalent cause of vision impairment among the elderly population. MPOD’s implications in diverse ocular conditions, including diabetic retinopathy and glaucoma, have been explored, underscoring the real need for clinical measurement of MPOD. The integration of MPOD measurement into routine eye examinations presents an unparalleled opportunity for early disease detection, precise treatment planning, and longitudinal disease monitoring. Conclusions: Longitudinal investigations underscore the significance of MPOD in the context of age-related ocular diseases. These studies show promise and elucidate the dynamic nuances of MPOD’s status and importance as a measurable, modifiable clinical biomarker.

Macular pigment optical density (MPOD) is an important clinical biomarker for ocular conditions like macular degeneration, diabetic eye disease, and digital eye strain. Additionally, its measurements can be essential in health assessment for visual function, systemic diseases, and brain health. We aimed to assess the repeatability, agreement, and effects of the learning curve of the new portable handheld heterochromatic flicker photometer, Zx Pro, in measuring MPOD in a wide age range of ocular-healthy adults, compared to the MPOD measurements obtained using the clinically available QuantifEye device. Seventy-six participants performed one practice at-tempt and two study-related MPOD measurements with the Zx Pro and the QuantifEye. The Pearson correlation between the study-related MPOD measurements for Zx Pro and QuantifEye devices was 90% and 85%, respectively. Altman and Bland plots show excellent agreement between the device's MPOD data, with 95% limits of an agreement being -0.10 to +0.11 du. The mean difference between the practice attempt and the study-related measurements was not statistically significant for Zx Pro but was significant for QuantifEye (Repeated measures ANOVA p=0.325 and p=0.015, respectively). The Zx Pro provides excellent repeatable MPOD measurements, has an insignificant learning curve, and is in good agreement with the predicate device.

Demodex blepharitis, a chronic lid margin disease, is caused by an infestation of Demodex mites, the most common ectoparasites in human skin and eyelids. Lotilaner ophthalmic solution, 0.25% (Xdemvy, Tarsus Pharmaceuticals), is the first therapy approved to treat Demodex blepharitis. This narrative review characterizes lotilaner ophthalmic solution, 0.25%, and describes its efficacy, safety, and tolerability. The safety and efficacy of lotilaner ophthalmic solution, 0.25%, for treating Demodex blepharitis was evaluated in four phase 2 and two phase 3 trials. The data of 980 patients included in these phase 2 and 3 clinical trials revealed that the proportion of eyes with a clinically meaningful reduction to 10 or fewer collarettes (the cylindrical, waxy debris found at the base of the eyelashes) ranged from 81 to 93%. The mite eradication rate confirmed by a microscopy of epilated lashes ranged from 52 to 78%. No serious treatment-related adverse events were reported in any of these clinical studies. As high as 92% of the patients receiving lotilaner eyedrops in the phase 3 trials found it to be neutral to very comfortable. Given the positive safety and efficacy outcomes, the drug is likely to become the standard of care in the treatment of Demodex blepharitis.

The macular pigment optical density (MPOD) signifies a vital component of macular well-being and high-resolution visual acuity. MPOD can serve as a reliable biomarker for assessing the retinal defense mechanisms against oxidative stress and the deleterious effects of excessive light exposure. Elevated MPOD levels offer robust protection against the onset and progression of age-related macular degeneration (AMD) a prevalent cause of vision impairment among the elderly population. MPOD's implications in diverse ocular conditions, including diabetic retinopathy and glaucoma, have been explored and indicate a real need for clinical measurement of MPOD. This review looks at the potential of MPOD as a modifiable biomarker influencing the progression and onset of these conditions, particularly in the context of oxidative stress and retinal ischemia. The integration of MPOD measurement into routine eye examinations presents an unparalleled opportunity for early disease detection, precise treatment planning, and longitudinal disease monitoring. Emerging technologies and longitudinal investigations promise to elucidate the dynamic nuances of MPOD in the context of age-related ocular diseases.

Recent advances in nonparametric Contrast Sensitivity Function (CSF) estimation have yielded a new tradeoff between accuracy and efficiency not available to classical parametric estimators. An additional advantage of this new framework is the ability to independently tune multiple aspects of the estimator to seek further improvements. Machine Learning CSF (MLCSF) estimation with Gaussian processes allows for design optimization in the kernel, acquisition function and underlying task representation, to name a few. This paper describes a novel kernel for CSF estimation that is more flexible than a kernel based on strictly functional forms. Despite being more flexible, it can result in a more efficient estimator. Further, trial selection for data acquisition that is generalized beyond pure information gain can also improve estimator quality. Finally, introducing latent variable representations underlying general CSF shapes can enable simultaneous estimation of multiple CSFs, such as from different eyes, eccentricities or luminances. The conditions under which the new procedures perform better than previous nonparametric estimation procedures are presented and quantified. Precis: Machine learning contrast sensitivity function estimation is improved by incorporation of additional information about the nature of the underlying and data from other eyes.

Multidimensional psychometric functions can typically be estimated nonparametrically for greater accuracy or parametrically for greater efficiency. By recasting the estimation problem from regression to classification, however, powerful machine learning tools can be leveraged to improve both accuracy and efficiency simultaneously. Contrast Sensitivity Functions (CSFs) are behaviorally estimated curves that provide insight into both peripheral and central visual function. They are impractically long to be used in many clinical workflows without compromises of some sort, however, such as sampling only a few spatial frequencies or making strong assumptions about the shape of the function. This paper describes the development of the Machine Learning Contrast Response Function (MLCRF) estimator, which quantifies the expected probability of success in performing a contrast detection or discrimination task. A machine learning CSF can then be derived from the MLCRF. Using simulated eyes created from canonical CSF curves and actual human contrast response data, the accuracy and efficiency of the MLCSF was evaluated in order to determine its potential utility for research and clinical applications. With stimuli selected randomly, the MLCSF estimator converged toward ground truth. With optimal stimulus selection via Bayesian active learning, convergence was about an order of magnitude faster, requiring only tens of stimuli to achieve reasonable estimates. Inclusion of an informative prior provided no discernible advantage to the estimator as configured. The MLCSF exhibits performance characteristics on par with state-of-the-art CSF estimators and therefore should be explored further to uncover its full potential. Precis Machine learning classifiers enable accurate and efficient contrast sensitivity function estimation with item-level prediction for individual eyes.