(1) Background: Earthquakes are natural disasters that often result in significant loss of life and property. The objective of this study is to explore the frequency of symptoms associated with posttraumatic stress disorder (PTSD), levels of meaning in life (ML), and perceived social support (SS) among university students in the aftermath of the earthquake that occurred in Turkey and Syria in 2023. (2) Methods: This study utilizes a cross-sectional correlation design to achieve its objectives among 603 university students from two public universities using an online survey (via Google Forms). The survey was launched one month after the earthquake in Turkey and Syria and concluded on 6 April 2023. (3) Results: The results indicate that a total of 158 university students, constituting 26.20% of the sample, reported extreme symptoms of PTSD. The results also indicate that 184 students (30.51), and 140 students (23.22%) reported low levels of ML and SS, respectively. Female students were significantly more vulnerable to experiencing PTSD symptoms, as well as difficulties in finding ML and SS. Finally, results revealed that students who were pursuing postgraduate studies had a greater likelihood of exhibiting symptoms indicative of PTSD. (4) Conclusions: It is recommended that universities provide support services and resources for students experiencing PTSD symptoms.

Hepatocellular carcinoma (HCC), the most common primary liver malignancy and the sixth most common cancer globally, remains fatal for many patients with inappropriate responses to treatment. Recent advancements in immunotherapy have transformed the treatment landscape for advanced HCC. However, variability in patient responses to immunotherapy highlights the need for biomarkers that can predict treatment outcomes. This manuscript comprehensively reviews the evolving role of biomarkers in immunotherapy efficacy, spanning from blood-derived indicators—alpha-fetoprotein, inflammatory markers, cytokines, circulating tumor cells, and their DNA—to tissue-derived indicators—programmed cell death ligand 1 expression, tumor mutational burden, microsatellite instability, and tumor-infiltrating lymphocytes. The current body of evidence suggests that these biomarkers hold promise for improving patient selection and predicting immunotherapy outcomes. Each biomarker offers unique insights into disease biology and the immune landscape of HCC, potentially enhancing the precision of treatment strategies. However, challenges such as methodological variability, high costs, inconsistent findings, and the need for large-scale validation in well-powered two-arm trial studies persist, making them currently unsuitable for integration into standard care. Addressing these challenges through standardized techniques and implementation of further studies will be critical for the future incorporation of these biomarkers into clinical practice for advanced HCC.

Infective endocarditis (IE) is a severe infection of the inner lining of the heart, known as the endocardium. It is characterized by a range of symptoms and has a complicated pattern of occurrence, leading to a significant number of deaths. IE poses significant diagnostic and treatment difficulties. This evaluation examines the utilization of artificial intelligence (AI) and machine learning (ML) models in addressing information extraction (IE) management. It focuses on the most recent advancements and possible applications. Through this paper, we observe that AI/ML can significantly enhance and outperform traditional diagnostic methods leading to more accurate risk stratification, personalized therapies as well and real-time monitoring facilities. For example, early postsurgical mortality prediction models like SYSUPMIE achieved ‘very good’ area under the curve (AUROC) values exceeding 0.81. Additionally, AI/ML has improved diagnostic accuracy for prosthetic valve endocarditis, with PET-ML models increasing sensitivity from 59% to 72% when integrated into ESC criteria and reaching a high specificity of 83%. Furthermore, inflammatory biomarkers such as IL-15 and CCL4 have been identified as predictive markers, showing 91% accuracy in forecasting mortality, and identifying high-risk patients with specific CRP, IL-15, and CCL4 levels. Even simpler ML models, like Naïve Bayes, demonstrated an excellent accuracy of 92.30% in death rate prediction following valvular surgery for IE patients. Furthermore, this review provides a vital assessment of the advantages and disadvantages of such AI/ML models, such as better-quality decision support approaches like adaptive response systems on one hand, and data privacy threats or ethical concerns on the other hand. In conclusion, Al and ML must continue, through multi-centric and validated research, to advance cardiovascular medicine, and overcome implementation challenges to boost patient outcomes and healthcare delivery. Export

Background: Neural precursor cell expressed developmentally downregulated 9 (NEDD9) is considered an important factor in the progression of cancer, acting as a modulator of cellular migration, adhesion, and metastatic potential. Its significance as a prognostic factor, however, remains unclear, which necessitated a comprehensive review and meta-analysis. Methods: Our study followed the PRISMA guidelines, analyzing studies from major databases including PubMed, Embase, and Cochrane. Our eligibility criteria included studies evaluating NEDD9 expression in relation to cancer prognosis and outcomes such as overall survival (OS), progression-free survival (PFS), disease-free Survival (DFS), recurrence-free survival (RFS), and cancer-specific survival (CSS). We used random-effects and fixed-effect models for meta-analysis, and we validated our findings by comparative analysis using data from external cohorts like The Cancer Genome Atlas (TCGA). Results: The analysis of 27 studies with 3915 patients demonstrated a significant relationship between NEDD9 expression and poor OS as indicated by the pooled meta-analysis outcome across all included cancers (HR: 1.81, 95% CI: 1.38-2.37). A significant effect on PFS/DFS/RFS/CSS was also found (HR: 2.14, 95% CI: 1.42-3.23). Variations in survival across different types of cancer were indicated by subgroup analysis. NEDD9 expression was correlated with various immune cells across cancer types according to immune infiltration analysis. Protein-protein interaction (PPI) analysis indicated significant interactions involving NEDD9, suggesting mechanisms which influence tumor behavior and response to treatment. Conclusion: Our results suggest that NEDD9 is a significant prognostic marker in several human cancers. As a result of its central role in cancer progression and prognosis, it presents a promising target for therapeutic interventions. Our study highlights the importance of further research into the biology of NEDD9 and its therapeutic potential.

Cilostazol has been widely used to prevent peripheral vascular events after PCI. However, guidelines in cilostazol-based triple antiplatelet therapy for patients with ischemic heart disease undergoing PCI remain unclear. The purpose of this study was to assess the efficacy and safety of DAPT (aspirin and clopidogrel) compared to cilostazol -based TAPT (aspirin, clopidogrel and cilostazol). We conducted a comprehensive search of the Medline, Embase, Scopus, Cochrane, and Web of Science databases until November 2024 to identify RCTs comparing DAPT with cilostazol -based TAPT in patients with ischemic heart disease undergoing PCI. Pooled risk ratios (RRs) with 95% CIs were calculated. Eight RCTs (5,299 patients) were included in this systematic review and meta-analysis. A significantly reduced risk of all-cause mortality in hospital was observed with DAPT compared to cilostazol -based TAPT (RR: 0.27, 95% CI: 0.07 to 0.94, p = 0.04). Also, A significantly reduced risk of headache and palpitation was observed with DAPT compared to cilostazol -based TAPT, with pooled RR (RR: 0.15, 95% CI: 0.06 to 0.33, p < 0.001) and (RR: 0.24, 95% CI: 0.08 to 0.73, p = 0.01), respectively. However, no difference was observed between DAPT and cilostazol -based TAPT on vessel revascularization, stroke, stent thrombosis, myocardial infarction and major adverse cardiac events. Aspirin and clopidogrel were associated with a lower risk of adverse events compared to cilostazol-based TAPT. However, the addition of cilostazol did not improve clinical outcomes. Further trials are needed to clarify the role of cilostazol -based TAPT for patients with ischemic heart disease undergoing PCI.