Background/Objectives: Diabetic retinopathy (DR) is a progressive microvascular complication of diabetes mellitus and a leading cause of vision impairment worldwide. Early detection and timely management are critical in preventing vision loss, yet current screening programs face challenges, including limited specialist availability and variability in diagnoses, particularly in underserved areas. This literature review explores the evolving role of artificial intelligence (AI) in enhancing the diagnosis, screening, and management of diabetic retinopathy. It examines AI’s potential to improve diagnostic accuracy, accessibility, and patient outcomes through advanced machine-learning and deep-learning algorithms. Methods: We conducted a non-systematic review of the published literature to explore advancements in the diagnostics of diabetic retinopathy. Relevant articles were identified by searching the PubMed and Google Scholar databases. Studies focusing on the application of artificial intelligence in screening, diagnosis, and improving healthcare accessibility for diabetic retinopathy were included. Key information was extracted and synthesized to provide an overview of recent progress and clinical implications. Conclusions: Artificial intelligence holds transformative potential in diabetic retinopathy care by enabling earlier detection, improving screening coverage, and supporting individualized disease management. Continued research and ethical deployment will be essential to maximize AI’s benefits and address challenges in real-world applications, ultimately improving global vision health outcomes.

Background: Endometrial cancer (EC) is the most common gynecological malignancy in developed countries, with diagnostic accuracy and early detection being critical to patient outcomes. Recent advances in artificial intelligence (AI) offer new opportunities to enhance diagnostic precision and clinical decision-making. Objectives: This literature review aims to explore recent developments in AI-augmented diagnostic approaches for EC, with a focus on applications in histopathology, imaging, and multi-omics, and to assess their clinical impact and future potential. Methods: A non-systematic literature review was conducted to examine recent advances in artificial intelligence applications for the diagnosis of EC. Relevant studies were identified through searches on PubMed and Google Scholar, focusing on the integration of AI techniques in histopathology, imaging, and multi-omics data. Conclusions: AI-driven diagnostic tools have shown high performance in detecting and characterizing EC across multiple modalities, often matching or exceeding expert-level accuracy. These technologies hold promise for earlier detection, better risk assessment, and more personalized treatment planning. However, further research and validation are needed to address current limitations and support their broader integration into clinical workflows.

G. MARKOV, J. DOBRO, S. SHANKMAN, H. M. BELMONT; ENTEROCOCCAL ARTHRITIS WITH AVASCULAR NECROSIS IN A LUPUS PATIENT, Rheumatology, Volume 35, Issue 6, 1 June 19

Introduction: Endometriosis is a benign gynecological condition that shares many characteristics with cancer cells, including immune evasion, survival, adhesion, invasion, and angiogenesis. The simultaneous investigation of tissue hypoxia, EMT, and proliferative index in endometriosis, endometrial, and ovarian carcinomas may provide new insight into the evolution and progression of gynecological neoplasms. Aim: The aim of our study was to follow the immunohistochemical expression in endometriosis, endometrial and ovarian carcinoma in relation to tissue hypoxia and necrosis, EMT, proliferative index, and fibrosis. Materials and methods: The present study used biopsy samples from 50 patients with endometriosis, endometrial carcinoma, and ovarian carcinoma in search for a correlation between HIF-1α, Ki67, SMA, and E-cadherin expression and various clinicopathological features. Results: We observed heterogeneity and different intensity of immunohistochemical expression in different groups of patients. Immunohistochemical expression was compared with the degree of tumor cell differentiation. Cells of poorly differentiated adenocarcinomas showed a higher proliferative index with Ki67, presence of epithelial-mesenchymal transition with reduced expression of E-cadherin with stronger expression of HIF-1α. Regarding SMA in pelvic and ovarian endometriosis foci, we reported strong diffuse expression in stromal cells with marked fibrosis. Conclusion: Understanding the mechanisms of carcinogenesis and progression of gynecological tumors and endometriosis is important for prognosis, response to therapy, and possibly better treatment of patients.

Introduction: Malignant pleural effusions are a common and debilitating complication of advanced malignancies, affecting approximately one million patients annually. This condition leads to significant morbidity and a decline in quality of life. Accurate diagnosis and effective management are critical yet challenging due to the overlap in biochemical markers between malignant and benign pleural effusions. Aim: This study evaluates an extended panel of biochemical parameters, including albumin gradient, total protein, cholesterol, pH, glucose, specific gravity, and lactate dehydrogenase (LDH), to enhance diagnostic precision. Materials and methods: In order to achieve this, we conducted a cross-sectional, observational case-control study in order to analyze pleural fluid samples from 151 Bulgarian patients, including 79 with malignant effusions and 72 with benign effusions. Biochemical markers, such as albumin gradient, total protein, cholesterol, lactate dehydrogenase (LDH), pH, glucose, and specific gravity, were measured using advanced clinical chemistry analyzers. Statistical analyses, including Mann-Whitney U tests, t-tests, and Spearman’s rank correlations, were used to identify diagnostic markers. Results: The key findings highlighted the diagnostic value of albumin gradient, total protein, and cholesterol levels, which are strongly associated with malignant effusions. LDH and specific gravity also demonstrated potential as supplementary markers, while pH and glucose measurements showed limited utility in differentiating malignancy. Conclusion: Combining these biochemical parameters enhances the precision of pleural effusion analysis, offering a more robust framework for diagnosing and managing malignant pleural effusions effectively.

This case presents an unusual combination between an intraventricular meningioma and a choroid plexus papilloma. Intraventricular meningiomas are rare intraventricular tumors presenting with symptoms of hydrocephalus, headache, and neurological deficits. The rarity of choroid plexus papillomas is highlighted in medical diagnostics, with the majority of these findings being incidental within the setting of obstructive hydrocephalus. We present the case of a 66-year-old male patient who exhibited symptoms of headaches. Magnetic resonance imaging showed the presence of an intraventricular tumor in the region of the trigone of the right lateral ventricle, which was assessed for surgical removal. A postoperative hemorrhage necessitated a reoperation, after which the patient began to gradually recover. Hemianopsian disturbances persisted during and after his hospital stay. This report describes a rare case of concurrent choroid plexus papilloma and ventricular meningioma, manifesting as a single tumor mass.