Cardiovascular diseases (CVDs) are a major cause of mortality globally, emphasizing the need for early detection and effective risk assessment to improve patient outcomes. Advances in oculomics, which utilize the relationship between retinal microvascular changes and systemic vascular health, offer a promising non-invasive approach to assessing CVD risk. Retinal fundus imaging and optical coherence tomography/angiography (OCT/OCTA) provides critical information for early diagnosis, with retinal vascular parameters such as vessel caliber, tortuosity, and branching patterns identified as key biomarkers. Given the large volume of data generated during routine eye exams, there is a growing need for automated tools to aid in diagnosis and risk prediction. The study demonstrates that AI-driven analysis of retinal images can accurately predict cardiovascular risk factors, cardiovascular events, and metabolic diseases, surpassing traditional diagnostic methods in some cases. These models achieved area under the curve (AUC) values ranging from 0.71 to 0.87, sensitivity between 71% and 89%, and specificity between 40% and 70%, surpassing traditional diagnostic methods in some cases. This approach highlights the potential of retinal imaging as a key component in personalized medicine, enabling more precise risk assessment and earlier intervention. It not only aids in detecting vascular abnormalities that may precede cardiovascular events but also offers a scalable, non-invasive, and cost-effective solution for widespread screening. However, the article also emphasizes the need for further research to standardize imaging protocols and validate the clinical utility of these biomarkers across different populations. By integrating oculomics into routine clinical practice, healthcare providers could significantly enhance early detection and management of systemic diseases, ultimately improving patient outcomes. Fundus image analysis thus represents a valuable tool in the future of precision medicine and cardiovascular health management.

Background: The gut microbiome plays a crucial role in human health, and recent research has highlighted its potential impact on ocular health through the gut–eye axis. Dysbiosis, or an imbalance in the gut microbiota, has been implicated in various ocular diseases. Methods: A comprehensive literature search was conducted using relevant keywords in major electronic databases, prioritizing recent peer-reviewed articles published in English. Results: The gut microbiota influences ocular health through immune modulation, maintenance of the blood–retinal barrier, and production of beneficial metabolites. Dysbiosis can disrupt these mechanisms, contributing to ocular inflammation, tissue damage, and disease progression in conditions such as uveitis, age-related macular degeneration, diabetic retinopathy, dry eye disease, and glaucoma. Therapeutic modulation of the gut microbiome through probiotics, prebiotics, synbiotics, and fecal microbiota transplantation shows promise in preclinical and preliminary human studies. Conclusions: The gut–eye axis represents a dynamic and complex interplay between the gut microbiome and ocular health. Targeting the gut microbiome through innovative therapeutic strategies holds potential for improving the prevention and management of various ocular diseases.

Background: The prognostic value of baseline inflammatory markers in sepsis remains controversial, with conflicting evidence regarding their association with mortality. The dynamic changes in these markers over time might offer additional insights into disease progression and patient outcomes. Methods: This retrospective observational study included 138 patients with severe infections. The inflammatory biomarkers procalcitonin (PCT), C-reactive protein (CRP), and lactate (LAC) were measured at three time points: upon hospital admission (baseline), approximately 24–48 h after admission (second measurement; M2), and 48–72 h after admission (third measurement; M3). The primary outcome was 30-day mortality. A Mann–Whitney U test was used to compare the biomarker levels between the survivors and non-survivors. A Spearman’s correlation was used to assess the relationships between the baseline parameters. A logistic regression and a receiver operating characteristic (ROC) curve analysis were employed to evaluate the prognostic value of the baseline markers and their dynamic changes. Results: The baseline LAC and SOFA score were significantly associated with 30-day mortality. The percentage decrease in PCT, CRP, and LAC from the baseline to M3 emerged as strong predictors of survival, with the ROC curve analysis demonstrating superior discriminatory ability compared to the baseline values. CRP_Delta exhibited the highest AUC (0.903), followed by PCT_Delta (0.843) and LAC_Delta (0.703). Conclusions: The dynamic changes in these inflammatory biomarkers, particularly PCT, CRP, and LAC, offer valuable prognostic information beyond their baseline levels in predicting 30-day mortality in severe infections. These findings highlight the importance of monitoring biomarker trends for early risk stratification and potential treatment guidance.

The genus Taxus comprises a unique group of gymnosperms known for their botanical longevity, cultural significance, and exceptional pharmacological potential. This review explores the multifaceted profile of Taxus species, with a focus on their morphological traits, phytochemical composition, traditional uses, and therapeutic applications. Particular attention is given to taxanes, especially paclitaxel, which have revolutionized cancer treatment through microtubule-stabilizing mechanisms. In addition to well-established uses of the bark and leaves, the review synthesizes emerging research on the aril, a non-toxic and antioxidant-rich plant part, suggesting novel biomedical applications. By integrating ethnobotanical knowledge with contemporary pharmacological insights, this work underscores the enduring relevance of Taxus in traditional medicine while emphasizing its evolving role in modern drug discovery. The findings advocate for intensified interdisciplinary research and sustainable exploitation strategies to fully harness the genus’s therapeutic potential without compromising biodiversity.

Background/Objectives: Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality worldwide and increasingly are recognized as a continuum of interconnected conditions rather than isolated entities. Methods: A structured narrative literature search was performed in PubMed, Scopus, and Google Scholar for publications from 2015 to 2025 using combinations of different keywords: “cardiovascular disease spectrum”, “multi-omics”, “precision cardiology”, “machine learning”, and “artificial intelligence in cardiology”. Results: Evidence was synthesized across seven major clusters of cardiovascular conditions, and across these domains, common biological pathways were mapped onto heterogeneous clinical phenotypes, and we summarize how multi-omics integration, AI-enabled imaging and digital tools contribute to improved risk prediction and more informed clinical decision-making within this spectrum. Conclusions: Interpreting cardiovascular conditions as components of a shared disease spectrum clarifies cross-disease interactions and supports a shift from organ- and syndrome-based classifications toward mechanism- and data-driven precision cardiology. The convergence of multi-omics, and AI offers substantial opportunities for earlier detection, individualized prevention, and tailored therapy, but requires careful attention to data quality, equity, interpretability, and practical implementation in routine care.

Food neophobia involves avoiding new foods due to reluctance, aversion, or disgust. The Food Neophobia Scale (FNS) is the most reliable and common adult food neophobia test. It helps compare food neophobia across cultures by being translated into numerous languages. This study adapted, translated, and validated the FNS for Romania. This translated version was piloted in November 2023 on 59 students in the medical field from two distinct Romanian cities. Between December 2023 and February 2024, 375 adults were surveyed, representing Romania’s population within a 90% confidence interval. The average age of responders was 38.07 years, with a standard deviation of 10.75 and a 4:1 female-to-male sex ratio. The Cronbach’s alpha test was used to validate the questionnaire. Our study found that the mean FNS value was 31.86; most Romanian respondents (69.20%) were neutral towards trying new foods, with a significant portion being neophobes (18.21%) outnumbering neophiles (12.59%). When compared to international study results, Romanian adults, on average, exhibited a higher percentage of neophobes compared to those in Korea (13%), Hungary (16.8%), Italy (17%), and Brazil (17.5%), but a lower percentage than those in Lebanon (21.5%). The findings indicate that the translated scale can be utilized to assess neophobia among Romanian speakers.