Dual-Drug Nanomedicine Assembly with Synergistic Anti-Aneurysmal Effects via Inflammation Suppression and Extracellular Matrix Stabilization.

Abdominal aortic aneurysm (AAA) represents a critical cardiovascular condition characterized by localized dilation of the abdominal aorta, carrying a significant risk of rupture and mortality. Current treatment options are limited, necessitating novel therapeutic approaches. This study investigates the potential of a pioneering nanodrug delivery system, RAP@PFB, in mitigating AAA progression. RAP@PFB integrates pentagalloyl glucose (PGG) and rapamycin (RAP) within a metal-organic-framework (MOF) structure through a facile assembly process, ensuring remarkable drug loading capacity and colloidal stability. The synergistic effects of PGG, a polyphenolic antioxidant, and RAP, an mTOR inhibitor, collectively regulate key players in AAA pathogenesis, such as macrophages and smooth muscle cells (SMCs). In macrophages, RAP@PFB efficiently scavenges various free radicals, suppresses inflammation, and promotes M1-to-M2 phenotype repolarization. In SMCs, it inhibits apoptosis and calcification, thereby stabilizing the extracellular matrix and reducing the risk of AAA rupture. Administered intravenously, RAP@PFB exhibits effective accumulation at the AAA site, demonstrating robust efficacy in reducing AAA progression through multiple mechanisms. Moreover, RAP@PFB demonstrates favorable biosafety profiles, supporting its potential translation into clinical applications for AAA therapy.

Research Progress in the Medical Application of Heavy Water, Especially in the Field of D2O-Raman Spectroscopy.

Heavy water is an ideal contrast agent for metabolic activity and can be adapted to a wide range of biological systems owing to its non-invasiveness, universal applicability, and cost-effectiveness. As a new type of probe, the heavy isotope of water has been widely used in the study of cell development, metabolism, tissue homeostasis, aging, and tumor heterogeneity. Herein, we review findings supporting the applications of and research on heavy water in monitoring of bacterial metabolism, rapid detection of drug sensitivity, identification of tumor cells, precision medicine, and evaluation of skin barrier function and promote the use of heavy water as a suitable marker for the development of detection and treatment methodologies.

Untargeted Metabolomics Analysis of Esophageal Squamous Cell Carcinoma Discovers Dysregulated Metabolic Pathways and Potential Diagnostic Biomarkers.

Background: Esophageal squamous cell carcinoma (ESCC) is one of the most fatal diseases worldwide. Because early diagnosis is difficult, ESCC is mostly diagnosed at an advanced stage, leading to a poor overall prognosis. The purpose of this study was to explore the differences between plasma metabolic profiles in ESCC patients and healthy controls and to establish a diagnostic model of ESCC. Methods: In this study, a cohort of 310 subjects, containing 140 ESCC patients and 170 healthy controls (HC), was recruited. Participants were randomly separated into a training set (80 ESCCs, 80 HCs) and a validation set (60 ESCCs, 90 HCs) and their plasma metabolomics profiles were analyzed by ultra-performance liquid chromatography-tandem quadruple time-of-flight mass spectrometry (UPLC-QTOF/MS) technique. Univariate statistical analysis and multivariate analysis (MVA) methods were used to identify differential metabolites. Finally, the dysregulated pathways associated with ESCC were further explored and the diagnostic performance of the biomarker panel was evaluated. Results: Metabolic analyses identified 34 significant metabolites involved in the metabolism of amino acids, phospholipids, fatty acids, purine, and choline. Farthermore, an effective diagnostic model for ESCC was constructed based on eight metabolites. This panel of biomarkers consisted of hypoxanthine, proline betaine, indoleacrylic acid, inosine, 9-decenoylcarnitine, tetracosahexaenoic acid, LPE (20:4), and LPC (20:5). The model was verified and evaluated in the validation set. The AUC value of the ROC curve was 0.991(95% CI: 0.981-1.000, CI, Confidence interval), with a sensitivity (SE) of 98.8% and a specificity (SP) of 94.9% for the training set and 0.965(95% CI: 0.936-0.993), with a SE of 88.3% and a SP of 88.9% for the validation set. Among them, three biomarkers, indoleacrylic acid, LPC (20:5), and LPE (20:4), exhibited a trend associated with the ESCC progression. Conclusions: Our study identified a novel plasma biomarker panel, which clearly distinguishes ESCC patients and provides insight into the mechanisms of ESCC. This finding may form the basis for the development of a minimally invasive method for ESCC detection.