Background: Atherosclerotic diseases, including coronary heart disease and cerebrovascular disease, are leading causes of morbidity and mortality worldwide. Atherosclerosis is a chronic vascular condition marked by the accumulation of lipid plaque within arterial walls. These plaques can become unstable and rupture, leading to thrombosis and subsequent cardiovascular events. Therefore, early identification of vulnerable plaque is critical for preventing such events. Objectives: This study aims to develop a novel imaging platform for atherosclerotic plaque by designing a molecular imaging probe based on fluorescent molecules that target lipid necrotic cores. The goal is to specifically detect high-risk plaque, enabling early diagnosis and intervention. Methods: Bioinformatic analysis and immunofluorescence were used to detect CD36 expression in human carotid plaque. CD36pep-ICG was synthesized using the Fmoc solid-phase peptide method. A series of experiments was conducted to characterize the probe’s properties. To assess imaging performance, probe concentration gradients were tested using FLI equipment. Ex vivo imaging was performed on atherosclerotic mice and treatment models to evaluate the probe’s targeting ability and effectiveness in monitoring disease progression. Results: The CD36 expression was significantly elevated in the core of plaque compared to distal regions. The CD36pep-ICG probe, specifically designed to target lipids, was successfully synthesized and exhibited excellent fluorescence properties. In animal models, FLI imaging demonstrated that the CD36pep-ICG probe selectively accumulated in atherosclerotic plaque, enabling precise plaque detection. Moreover, the probe was used to monitor the therapeutic efficacy of anti-atherosclerotic drugs. Conclusions: The CD36pep-ICG probe developed in this study is an effective molecular imaging tool for the specific identification of vulnerable atherosclerotic plaque, offering a novel approach for early diagnosis and treatment. Additionally, the probe shows promise in tracking the therapeutic effects of the drug, potentially advancing the precision treatment of cardiovascular diseases.

Chronic kidney disease (CKD) has become one of the major diseases threatening global health, with its increasing incidence and mortality rates. Early identification of chronic kidney disease is crucial for accurate disease staging, timely intervention, and improved prognosis. However, the commonly used clinical diagnostic indicators, such as creatinine, albumin level and glomerular filtration rate, can only identify advanced CKD. Imaging examinations, such as computed tomography and magnetic resonance imaging, have limitations such as high costs and high risk of complications, and are not suitable for large‐scale screening of high‐risk populations. Renal biopsy is the gold standard for diagnosing renal fibrosis, but it is invasive. Previous studies have shown that capillary rarefaction is an early event of renal fibrosis, occurring earlier than tubular atrophy and interstitial collagen deposition. However, there is a lack of a minimally invasive, low‐cost, high‐resolution, dynamic and real‐time monitoring method for renal microcirculation that is suitable for large‐scale screening. There is an urgent need for reliable methods to screen early‐stage CKD patients. In this study, we have for the first time combined real‐time and wide‐field laser speckle imaging (RFLSI), near‐infrared II imaging (NIR‐II), duplex ultrasound (DUS) and Contrast‐Enhanced Ultrasound (CEUS) to monitor vascular changes and evaluate the progression of renal fibrosis. The combination of four imaging methods enabled the early monitoring of CKD progression by monitoring microcirculation. Among them, CEUS can detect changes in the renal microcirculation at the early stage of renal fibrosis, even earlier than the pathological damage of the kidneys. Through visualization and quantification of the progression of renal fibrosis and validation through histopathology, this study utilizes preclinical imaging to supplement clinical imaging of renal fibrosis, providing a more comprehensive method for monitoring microcirculation, which is helpful for guiding clinical decisions and providing insights into disease progression.

Background: The genetic basis of cardiovascular‐kidney‐metabolic syndrome (CKMs) involves complex pleiotropy, necessitating analytical approaches capable of dissecting shared genetic architectures across multiple cardiometabolic traits. Methods: We employed genomic structural equation modeling (genomic SEM) to integrate summary statistics from six cardiometabolic traits. The model was assessed using standard fit indices. Genome‐wide association analyses were performed on 1,862,425 SNPs under stringent quality control measures, with LD Score regression applied to evaluate polygenic heritability and confounding bias. Novel loci were identified using GWAS‐by‐Subtraction. Functional characterization included transcriptome‐wide association analysis (TWAS), fine‐mapping, pathway enrichment analysis, and cell‐type specificity analysis. Results: The genomic SEM model demonstrated excellent fit (CFI = 0.99, SRMR = 0.14). Quality control metrics confirmed that genomic inflation (Lambda GC = 1.591) was primarily attributable to polygenic heritability (h ² = 0.3286 ± 0.0135) rather than population stratification (Intercept = 1.0176 ± 0.0169). This framework identified 2,212 significantly associated variants, encompassing 32 novel loci discovered via GWAS‐by‐Subtraction. Functional annotation indicated that the majority of these loci were located in intronic (57.92%) or intergenic (30.6%) regions. TWAS and fine‐mapping nominated 188 high‐confidence genes; SENP2 (TWAS Z = 12.5), KIF11 (Z = 11.5), and JAZF1 (Z = 11.38) exhibited the strongest positive associations with CKMs risk, whereas TCF7L2 (Z = −13.4) demonstrated the strongest inverse association. Pathway enrichment implicated lipid balance and ubiquitin‐mediated proteolysis, and cell‐type specificity analysis prominently localized genetic signals to pancreatic islet cells. Fine‐mapping prioritized 18 causal variants with posterior probability ⟩ 0.95, including key signals within GCKR (rs1260333, rs780093) and INADL (rs2481665). Chromosomal regions 7 and 12 exhibited significant contributions. Conclusions: Our study unravels the shared genetic architecture of CKMs, revealing novel risk loci and pathogenic mechanisms. The results establish a direct cellular link between the pleiotropic genetic basis of CKMs and endocrine metabolic regulation within pancreatic islets.

Background: Lower limb peripheral artery disease (PAD) involves localized atherosclerosis with disturbed hemodynamics. V‐flow imaging is a vector Doppler technique enabling real‐time assessment of wall‐specific hemodynamic parameters such as wall shear stress (WSS) and oscillatory shear index (OSI). This study included a case–control diagnostic evaluation and a prospective observational component for exploratory prognostic assessment. Methods: The study enrolled 95 patients with PAD and 100 controls with plaque‐free lower limb arteries. V‐flow imaging measured WSSmax, WSSmean, and OSI across major lower limb arteries. Multivariate logistic regression and receiver operating characteristic analysis identified PAD predictors. A nomogram combining V‐flow and clinical parameters was developed. V‐flow analysis of 25 femoral plaques assessed upstream‐downstream WSS/OSI variation. A total of 28 patients with Fontaine IV PAD were followed for 6 months to exploratorily assess preoperative V‐flow parameters in relation to major adverse limb events. Results: Patients with PAD exhibited globally lower WSS and higher OSI in plaque‐free segments compared with controls. Combined V‐flow and clinical parameters showed moderate discriminative performance for PAD diagnosis (area under the curve, 0.87; sensitivity 80.1%; specificity 79.3%), with an optimism‐corrected area under the curve of 0.86. Femoral plaques exhibited lower downstream WSS and higher OSI. Preoperative V‐flow parameters were exploratorily assessed for 6‐month major adverse limb events in 28 patients with Fontaine IV PAD (optimism‐corrected area under the curve, 0.73); given the limited sample size, these findings were preliminary and require external validation. Conclusions: V‐flow imaging identified wall‐specific hemodynamic disturbances that may precede morphological changes. These parameters may aid PAD diagnosis. The major adverse limb events analysis was secondary and exploratory due to the small sample size, and its predictive utility requires further validation.