Endothelial dysfunction plays a central role in the pathogenesis of cardiovascular diseases, driven by a complex interplay of oxidative stress, metabolic imbalances, and adipokine dysregulation. Excessive reactive oxygen species reduce nitric oxide bioavailability by impairing endothelial nitric oxide synthase function, leading to vascular inflammation and impaired vasodilation. Adipose tissue-derived hormones such as leptin, adiponectin, and resistin exert opposing effects on vascular homeostasis, influencing inflammation and oxidative stress in obesity and metabolic syndrome. Dyslipidemia, particularly through oxidized LDL, initiates endothelial injury and foam cell formation, accelerating atherosclerosis. Furthermore, hypertension and obesity exacerbate vascular dysfunction by disrupting the balance between vasodilators and vasoconstrictors, enhancing oxidative stress, and altering perivascular adipose tissue function. These interrelated mechanisms contribute to the progression of atherosclerotic cardiovascular disease and diabetic vascular complications. A deeper understanding of these processes is essential for developing targeted interventions to restore endothelial health and reduce cardiometabolic risk.

Obesity is a multifactorial chronic disease resulting from complex genetic, molecular, environmental, and behavioral interactions. Its prevalence rises worldwide, affecting cardiovascular, metabolic, oncological, hepatic, respiratory, and skeletal health. Beyond caloric excess, genetic predisposition, epigenetic modifications, gut microbiota dysbiosis, endocrine-disrupting agents, circadian misalignment, and intergenerational and prenatal influences are critical determinants of obesity risk. Core pathophysiological mechanisms include insulin resistance, dyslipidemia, chronic low-grade inflammation, and neuroendocrine dysregulation of appetite and energy balance. These processes are linked to comorbidities such as type 2 diabetes, hypertension, atherosclerosis, fatty liver disease, sleep apnea, osteoporosis, and cancer. Advances in molecular profiling, metabolic phenotyping, and body composition analysis are refining obesity classification and enabling precise risk stratification. Current therapeutic strategies include behavioral interventions addressing stress-related mechanisms, pharmacological therapies such as GLP-1 receptor agonists, emerging gene therapy approaches, and bariatric surgery. Gut-derived hormones (leptin, ghrelin, GLP-1, PYY, CCK) are recognized as pivotal regulators of appetite and weight. Preventive strategies increasingly emphasize circadian alignment, while epigenetic inheritance and prenatal exposures such as maternal obesity or smoking highlight early-life programming in future metabolic health. Additionally, artificial intelligence-based platforms and personalized nutrition provide innovative opportunities for individualized prevention and management. This review synthesizes contemporary evidence on the biological basis, systemic consequences, preventive strategies, and evolving therapeutic modalities of obesity, affirming its recognition as a complex chronic disease requiring personalized, multidisciplinary care.

This narrative review focuses on innovative treatment approaches to diabetic retinopathy to meet the urgent demand for advancements in managing both the early and late stages of the disease. Recent studies highlight the potential of adipose stem cells and their secreted factors in mitigating the retinal complications of diabetes, with promising results in improving visual acuity and reducing inflammation and angiogenesis in diabetic retinopathy. However, caution is warranted regarding the safety and long-term therapeutic effects of adipose stem cells transplantation. Bone marrow mesenchymal stem cells can also mitigate retinal damage in diabetic retinopathy. Studies demonstrate that bone marrow mesenchymal stem cells-derived exosomes can suppress the Wnt/β-catenin pathway, reducing oxidative stress, inflammation, and angiogenesis in the diabetic retina, offering promise for future diabetic retinopathy treatments. Nanotechnology has the ability to precisely target the retina and minimize systemic side effects. Nanoparticles and nanocarriers offer improved bioavailability, sustained release of therapeutics, and potential for synergistic effects. They can be a new way of effective treatment and prevention of diabetic retinopathy. Activation and modulation of PPARα as a means for diabetic retinopathy treatment has been widely investigated in recent years and demonstrated promising effects in clinical trials. PPARα activation turned out to be a promising therapeutic method for treating dyslipidemia, inflammation, and insulin sensitivity. The combination of PPARα modulators with small molecules offers an interesting perspective for retinal diseases’ therapy.

This narrative review explores emerging technologies in dyslipidemia management, focusing on nanotechnology and artificial intelligence (AI). It examines the current treatment recommendations and contrasts them with the future prospects enabled by these innovations. Nanotechnology shows significant potential in enhancing drug delivery systems, enabling more targeted and efficient lipid-lowering therapies. In parallel, AI offers advancements in diagnostics, cardiovascular risk prediction, and personalized treatment strategies. AI-based decision support systems and machine learning algorithms are particularly promising for analyzing large datasets and delivering evidence-based recommendations. Together, these technologies hold the potential to revolutionize dyslipidemia management, improving outcomes and optimizing patient care. In addition, this review covers key topics such as cardiovascular disease biomarkers and risk factors, providing insights into the current methods for assessing cardiovascular risk. It also discusses the current understanding of dyslipidemia, including pathophysiology and clinical management. Together, these insights and technologies hold the potential to revolutionize dyslipidemia management, improving outcomes and optimizing patient care.

This article reviews innovative diagnostic approaches for diabetic retinopathy as the prevalence of diabetes mellitus and its complications continue to escalate. Novel techniques focus on early disease detection. Technological innovations, such as teleophthalmology, smartphone-based photography, artificial intelligence with deep learning, or widefield photography, can enhance diagnostic accuracy and accelerate the treatment. The review highlights teleophthalmology and handheld photography as promising solutions for remote eye care. These methods revolutionize diabetic retinopathy screening, offering cost-effective and accessible solutions. However, the use of these techniques may be limited by insurance coverage in certain world regions. Ultra-widefield photography offers a comprehensive view of up to 80.0% of the retina in a single image, compared to the 34.0% coverage of the traditional seven-field imaging protocol. It allows retinal imaging without pupil dilation, especially for individuals with compromised mydriasis. However, they also have drawbacks, including high costs, artifacts from eyelashes, eyelid margins, and peripheral distortion. Recent advances in artificial intelligence and machine learning, particularly through convolutional neural networks, are revolutionizing diabetic retinopathy diagnostics, enhancing screening efficiency and accuracy. FDA-approved Artificial Intelligence-powered devices such as LumineticsCore™, EyeArt, and AEYE Diagnostic Screening demonstrate high sensitivity and specificity in diabetic retinopathy detection. While Artificial Intelligence offers the potential to improve patient outcomes and reduce treatment costs, challenges such as dataset biases, high initial costs, and cybersecurity risks must be considered to ensure safety and efficiency. Nanotechnology advancements further enhance diagnosis, offering highly branched polyethyleneimine particles with fluorescein sodium (PEI-NHAc-FS) for better fluorescein angiography or vanadium oxide-based metabolic fingerprinting for early detection.

Retinitis pigmentosa is a group of inherited retinal dystrophies characterized by progressive photoreceptor cell loss leading to irreversible vision loss. Affecting approximately 1 in 4000 individuals worldwide, retinitis pigmentosa exhibits significant genetic heterogeneity, with mutations in genes such as RHO, PRPF31, RPE65, USH2A, and NR2E3, which contribute to its diverse clinical presentation. This review outlines the genetic basis of retinitis pigmentosa and explores cutting-edge gene-based therapeutic strategies. Luxturna (voretigene neparvovec-rzyl), the first FDA-approved gene therapy targeting RPE65 mutations, represents a milestone in precision ophthalmology, while OCU400 is a gene-independent therapy that uses a modified NR2E3 construct to modulate retinal homeostasis across different RP genotypes. Additionally, CRISPR–Cas genome-editing technologies offer future potential for the personalized correction of specific mutations, though concerns about off-target effects and delivery challenges remain. The article also highlights MCO-010, a novel optogenetic therapy that bypasses defective phototransduction pathways, showing promise for patients regardless of their genetic profile. Moreover, QR-1123, a mutation-specific antisense oligonucleotide targeting the P23H variant in the RHO gene, is under clinical investigation for autosomal dominant RP and has shown encouraging preclinical results in reducing toxic protein accumulation and preserving photoreceptors. SPVN06, another promising candidate, is a mutation-agnostic gene therapy delivering RdCVF and RdCVFL via AAV to support cone viability and delay degeneration, currently being evaluated in a multicenter Phase I/II trial for patients with various rod–cone dystrophies. Collectively, these advances illustrate the transition from symptom management toward targeted, mutation-specific therapies, marking a major advancement in the treatment of RP and inherited retinal diseases.