Hyperuricemia (HUA), defined by elevated serum uric acid levels, is well-established in its association with systemic conditions like gout and cardiovascular diseases. Recently, however, emerging research has revealed a potential connection between HUA and ocular disorders, particularly epiretinal pathologies. This review investigates the pathophysiological mechanisms linking HUA to epiretinal conditions, including epiretinal membrane formation, macular edema, and retinal vascular diseases. By thoroughly analyzing current literature, this review seeks to deepen the understanding of the relationship between HUA and epiretinal disorders, with the aim of informing new therapeutic strategies and enhancing patient outcomes.

Sodium-glucose cotransporter 2 (SGLT2) inhibitors are integral to diabetes treatment, facilitating renal glucose excretion and offering benefits in cardiovascular risk reduction, kidney function preservation, and weight management. However, their integration into diabetes care presents challenges due to associated adverse effects. This review assesses the efficacy of SGLT2 inhibitors in diabetes management. A comprehensive literature search using PubMed and Google Scholar yielded pertinent studies. Clinical evidence demonstrates the effectiveness of SGLT2 inhibitors in glycemic control and in reducing cardiovascular risks in diabetes patients. Moreover, these agents exhibit positive effects on cardiovascular and renal functions. Despite their therapeutic promise, careful consideration is warranted when integrating SGLT2 inhibitors into diabetes care. Common adverse effects such as genitourinary infections, hypoglycemia, and sporadic diabetic ketoacidosis necessitate rigorous patient monitoring and education. Nonetheless, SGLT2 inhibitors offer a comprehensive approach to diabetes management, showing efficacy across multiple domains. In summary, SGLT2 inhibitors play a crucial role in diabetes care, offering benefits beyond glycemic control. However, their use requires careful patient selection, education, and monitoring to manage associated risks effectively. Awareness of potential adverse effects is essential for optimizing the therapeutic benefits of SGLT2 inhibitors in T2DM (type 2 diabetes mellitus) management.

Diabetic vascular disease, as one of the common complications in diabetic patients, threatens the quality of life and health of patients. Autophagy maintains cellular homeostasis and survival as an important intracellular self-repair mechanism. In recent years, with the gradual deepening of autophagy research, more and more studies have found that vascular cells such as endothelial cells, smooth muscle cells, and inflammatory cells are closely associated with various autophagy disorders. Different autophagy regulatory mechanisms can lead to different or similar cellular outcomes, and there are complex crosstalk mechanisms in the process. Therefore, we will summarize the latest research progresses with regards to the role of autophagy in diabetic vascular disease, focusing on the complex regulatory mechanisms of mitophagy, epigenetic modifications, apoptosis, inflammation, and autophagy in the development of diabetic vascular disease, aiming to provide effective therapeutic targets for diabetic vascular injury.

Age-related changes in the brain cause cognitive decline and dementia. In recent year’s researchers’ extensively studied the relationship between age related changes in functional connectivity (FC) in dementia. Those studies explore the alterations in FC patterns observed in aging and neurodegenerative disorders using techniques such as resting-state functional magnetic resonance imaging (rs-fMRI), electroencephalography (EEG) coherence analysis, and graph theory approaches. The current review summarizes the findings, which highlight the impact of FC changes on cognitive decline and neurodegenerative disease progression using these techniques and emphasize the importance of understanding neural alterations for early detection and intervention. The findings underscore the complexity of cognitive aging and the need for further research to differentiate normal aging from pathological conditions. rs-fMRI is essential for studying brain changes associated with aging and pathology by capturing coherent fluctuations in brain activity during rest, providing insights into FC without task-related confounds. Key networks such as the default mode network and front parietal control network are crucial in revealing age-related connectivity changes. Despite challenges like neurovascular uncoupling and data complexity, ongoing advancements promise improved clinical applications of rs-fMRI in understanding cognitive decline across the lifespan. EEG and magnetoencephalography (MEG) are cost-effective techniques with high temporal resolution, allowing detailed study of brain rhythms and FC. Recent studies highlight EEG/MEG’s potential in early Alzheimer’s disease detection by identifying changes in brain connectivity patterns. Integration of machine learning techniques enhances diagnostic accuracy, although further validation and research are necessary. Graph theory offers a quantitative framework to analyze cognitive networks, identifying distinct topological differences between healthy aging and pathological conditions. Future research should expand exploration into diverse neurodegenerative disorders beyond mild cognitive impairment, integrating neuroimaging techniques to refine diagnostic precision and deepen insights into brain function and connectivity.