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Background: Recent studies have suggested that soluble suppression of tumorigenicity-2 (sST2), an inflammation-related protein receptor, is associated with atherosclerotic diseases. This study aimed to investigate the potential predictive value of sST2 on plaque vulnerability by assessing whether elevated serum levels of sST2 are associated with vulnerable plaque features in patients with non-ST-elevation acute coronary syndrome (ACS).Methods: A total of 120 patients with non-ST-elevation ACS (167 lesions) were prospectively enrolled and evaluated by standard coronary computed tomography angiography (CCTA) and coronary angiography in this study. Serum sST2 levels were measured by ELISA (Presage® ST2 Assay Kit, Critical Diagnostics), and semiautomated software (QAngioCT, Medis) was used to quantify coronary plaques.Results: The included patients were divided into 4 groups by serum sST2 level quartiles. Volumetric analysis of the whole lesion revealed that patients with higher sST2 levels had a larger absolute necrotic core (NC) volume (Quartile 4 vs. Quartile 1, 86.16 ± 59.71 vs. 45.10 ± 45.80 mm3, P = 0.001; Quartile 4 vs. Quartile 2, 86.16 ± 59.71 vs. 50.22 ± 42.56 mm3, P = 0.002) and a higher NC percentage (Quartile 4 vs. Quartile 1, 35.16 ± 9.82 vs. 23.21 ± 16.18%, P < 0.001; Quartile 4 vs. Quartile 2, 35.16 ± 9.82% vs. 22.50 ± 14.03%, P < 0.001; Quartile 4 vs. Quartile 3, 35.16 ± 9.82% vs. 25.04 ± 14.48%, P < 0.001). Correlation analysis revealed that serum sST2 levels were positively correlated with the NC (r = 0.323, P < 0.001) but negatively correlated with dense calcium (r = −0.208, P = 0.007). Furthermore, among those with plaque calcification, patients with spotty calcification exhibited higher serum sST2 levels than those with large calcification (26.06 ± 16.54 vs. 17.55 ± 7.65 ng/mL, P = 0.002). No significant differences in plaque components at the level of the minimal lumen area (MLA) were found among the groups.Conclusions: Serum sST2 levels were correlated with different coronary plaque components in patients with non-ST-elevation ACS. A higher serum level of sST2 was correlated with plaque vulnerability.Clinical Trial Registration:www.ClinicalTrials.gov, identifier: NCT04797819.

OBJECTIVES This study evaluated quantitative flow ratio (QFR) to predict microvascular dysfunction (MVD) in patients with ST-segment elevation myocardial infarction (STEMI). BACKGROUND QFR is a novel approach for the rapid computation of fractional flow reserve based on three-dimensional quantitative coronary angiography. We hypothesized that QFR computation could be used to predict MVD after STEMI. METHODS Indexes such as contrast-flow QFR (cQFR), fixed-flow QFR (fQFR), and hyperemic flow velocity (HFV) were calculated in 130 STEMI patients with culprit lesion with ≥50% diameter stenosis and TIMI flow grade 2/3 in the spontaneously recanalized culprit artery on initial angiography. MVD was defined as microvascular obstruction determined by contrast-enhanced cardiac magnetic resonance at a median of 5 days after percutaneous coronary intervention. RESULTS Patients were divided into the MVD group (76/130, 58.5%) and non-MVD group (54/130, 41.5%). Patients with MVD had higher cQFR-fQFR value (0.080 ± 0.058 vs. 0.038 ± 0.039, p

We have addressed the issue of improper and unreliable analysis of materials characterization data by developing an artificial intelligence based methodology that can reliably and more efficiently analyze experimental results from extended X-ray absorption fine structure (EXAFS) measurements. Such methods help address growing reproducibility problems that are slowing research progress, discouraging the quest for research excellence, and inhibiting effective technology transfer and manufacturing innovation. We have developed a machine learning system for automated analysis of EXAFS spectroscopy measurements and demonstrated its effectiveness on measurements collected at powerful, third generation synchrotron radiation facilities. Specifically, the system uses a genetic algorithm to efficiently find sets of structural parameters that lead to high quality fits of the experimental spectra. A human analyst suggests a set of chemical compounds potentially present in the sample, used as theoretical standards. The algorithm then searches the large multidimensional space of combinations of these materials to determine the set of structural paths using the theoretical standards that best reproduces the experimental data. The algorithm further calculates a goodness of fit value from the suggested standards that can be used to identify the chemical moieties present in the measured sample.

p-cresyl sulfate (PCS) is a protein-bound uremic toxin retained in the blood of patients with chronic kidney disease (CKD) As atherosclerosis is a primary cardiovascular complication for patients with CKD, the aim of the present study was to investigate the mechanisms underlying the aggravation of atherosclerosis by PCS. In addition, the effect of atorvastatin was assessed in reversing the effects of PCS. PCS was revealed to promote the initiation and progression of atherosclerosis. Following treatment with atorvastatin, apolipoprotein E knockout mice demonstrated a reduction in PCS-induced atherogenesis and plaque vulnerability. In addition, atorvastatin decreased the protein expression levels of vascular cell adhesion molecule-1 and intercellular cell adhesion molecule-1, and the interaction between leukocytes and endothelia. The plasma lipid profiles of mice were not significantly affected by gavage of low-dose atorvastatin. The results of the present study indicate that PCS promotes plaque growth and instability by enhancing leukocyte-endothelium interaction, and that these effects may be attenuated by atorvastatin treatment.

To investigate whether apolipoprotein A (apoA)-I glycation and paraoxonase (PON) activities are associated with the severity of coronary artery disease (CAD) in patients with type 2 diabetes mellitus (T2DM). Relative intensity of apoA-I glycation and activities of high-density lipoprotein (HDL)