Search

Objective: To compare the diagnostic performance between mDixon sequence and WHCA TFE sequence using SPIR for non-contrast-enhanced coronary MRA in patients with suspected coronary artery disease (CAD). Method: This prospective study recruited 45 patients who were scheduled for X-ray coronary angiography (CAG) with suspected CAD in Yantai Yuhuangding hospital. Patients underwent both 3.0T WHCA TFE using SPIR and mDixon coronary MRA examinations before undergoing CAG. Two radiologists independently assessed coronary arteries in terms of subjective image quality (on a scale of 1~5, with 5 denoting the highest image quality), vessel length, vessel diameter, and presence of significant stenoses. CAG was used as the reference standard for detecting the presence of stenoses. Vessel length and diameter were compared between sequences using paired t-tests. Subjective image quality scores were compared between sequences using Wilcoxon tests. Sensitivity, specificity, and accuracy were compared between sequences using McNemar tests. Positive and negative predictive values were compared between sequences using the joint hypotheses test. Results: Two CMRA examinations were successfully performed in 40 (88.9%) of 45 patients for analysis. The objective image quality of 3.0T mDixon assessed by both radiologists was (3.9±0.9), and the 3.0T WHCA TFE using SPIR was (3.7±0.9). The mDixon sequence exhibited higher sensitivity, specificity, accuracy, positive predictive value, and negative predictive value in per-segment analysis (78.5% vs. 66.1%, 96.5% vs. 93.8%, 91.7% vs. 86.6%, 88.6% vs. 78.9%, and 93.4% vs. 88.7%) and higher sensitivity and accuracy in per-vessel analysis (89.4% vs. 81.6% and 89.1% vs. 83.3%). Conclusion: In comparison with 3.0T WHCA TFE sequence using SPIR, mDixon demonstrated superior diagnostic performance.

Abstract The paper addresses the economic operation optimization problem of photovoltaic charging-swapping-storage integrated stations (PCSSIS) in high-penetration distribution networks. It proposes a dual-layer optimization scheduling model for PCSSIS clusters and distribution network systems. Firstly, a master–slave game model is constructed. The upper layer takes the high-penetration distribution network as the decision-making entity and aims to maximize its own revenue while considering the energy trading of PCSSIS. The lower layer takes PCSSIS as the decision-making entity, and PCSSIS adjusts energy flow and optimizes revenue based on the internal electricity price provided by the upper-layer distribution network. Secondly, the differential evolution algorithm and GUROBI solver are used to solve for the maximum revenue, internal electricity price, and electricity consumption of PCSSIS and the distribution network. Finally, the effectiveness of the proposed strategy is verified through case studies and simulations.

Abstract Objectives This study intended to explore whether the protective effect safflower yellow injection (SYI) on myocardial ischemia-reperfusion (I/R) injury in rats mediated of the NLRP3 inflammasome signaling. Methods The I/R model was prepared by ligating the left anterior descending coronary artery for 45 min and then releasing the blood flow for 150 min. 96 male Wistar rats were randomly divided into sham group, I/R group, Hebeishuang group (HBS), SYI high-dose group (I/R + SYI-H), SYI medium-dose group (I/R + SYI-M) and SYI low-dose group (I/R + SYI-L). Cell experiments were divided into normal control group (NC), Oxygen glucose deprivation/reoxygenation group (OGD/R), OGD/R + SYI group, OGD/R + SYI + Chloroquine group (OGD/R + SYI + CQ). The area of myocardial ischemia infarction and pathological changes were observed by the Tetrazolium method (TTC) and HE staining. Myocardial enzymes such as aspartate aminotransferase (AST), lactate dehydrogenase (LDH) and creatine kinase (CK) were measured by chemiluminescence (CL) method. The inflammatory factors levels of TNF-α, IL-1β, MCP-1, and IL-6 were detected by ELISA. The expressions of inflammatory-related proteins (Caspase-1, NLRP3, TLR4, NF-κB), autophagosome-related proteins (LC3-I, LC3-II,LC3-II/LC3-I), apoptosis-related proteins (Bax, Bcl-2, Caspase-3, Bcl-2/Bax) and autophagy-related proteins (p62/SQSTM1, PI3K, p-Akt, mTOR) were detected by Western-Blot. Cell morphology and cell viability were detected by transmission electron microscopy and CCK-8. Results In vivo, compared with sham group, the percentage of myocardial infarction area was increased and myocardial tissue arrangement was disordered in I/R group. In addition, the activities of myocardial enzymes, the contents of inflammatory factors, the expressions of inflammatory-related proteins, autophagy-related proteins, autophagosome-related proteins, Bax and Caspase-3 were increased, while Bcl-2 and Bcl-2/Bax were decreased. SYI treatment reversed these trends, except for the expression of autophagosome-related proteins. In vitro, SYI decreased the contents of inflammatory factors and the expressions of inflammatory-related proteins, autophagy-related proteins and autophagosome-related proteins caused by OGD/R. However, the contents of inflammatory factors and the expression of inflammatory-related proteins, p62/SQSTM1 and mTOR were increased, while PI3K, p-AKT, LC3-II/LC3-I were significantly decreased in OGD/R + SYI + CQ group. Conclusions SYI can promote myocardial tissue autophagy by regulating NLRP3, thereby attenuating the myocardial inflammatory response and protecting damaged myocardium in I/R rats.

Abstract The objective of the present study was to examine the impact of different plyometric training (PT) surfaces on the adaptive changes of jumping ability, sprinting speed, change of direction ability and strength performance in volleyball players. Forty male players participated in the study and were divided into four equal groups performing PT in aquatic (APT), sand (SPT), and land (LPT) surfaces, or an active control group (CON). All training groups indicated small to large significant (p = 0.001) improvements in countermovement vertical jump (CMVJ), standing long jump (SLJ), spike jump, block jump, 10-m sprint, T-test, and maximal strength after the 6 weeks of progressive volume-based overload PT and in comparison to CON group (p

Brain functional hypernetworks that can characterize the complex and multivariate interactions among multiple brain regions have been widely used in the diagnosis and prediction of brain diseases. However, there are few studies on the structure and dynamics of brain functional hypernetworks. Such studies can help to explore how the important functional features of brain functional hypernetworks characterize the working and pathological mechanisms of the human brain. Therefore, this article introduces the hypernetwork null model to analyze the dependencies between the features of interest. Specifically, first, based on the original brain functional hypernetwork, this article proposed the optimized hyper dK-series algorithm with hyperedges to construct null models that preserved the different node attributes and hyperedge attributes of the original brain functional hypernetwork, respectively. Next, based on the original hypernetwork model and the null model, multiple node attributes and hyperedge attributes were respectively introduced. Then, the level of similarity and correlation between the topological attributes of the original brain functional hypernetwork and the topological attributes of the brain functional hypernetwork null model were calculated to analyze the dependencies between the features of interest. The results showed that there were differences in the level of dependence between the features of interest. Node degree is the main dependency attribute for multiple metrics. Hyperedge degree, node degree-dependent redundancy coefficient, and hyperedge degree-dependent redundancy coefficient are partial dependency attributes for some metrics. The dependency attributes and level of dependency are the same for the hypernetwork clustering coefficients—HCC2 and HCC3. This indicates that the node degree is redundant with respect to other attributes, while the hyperedge degree, node degree-dependent redundancy coefficient, and hyperedge degree-dependent redundancy coefficient perhaps contain other topology information. In addition, there is redundancy between HCC2 and HCC3. Therefore, the effects of these redundant attributes need to be considered when performing network analysis.

Exercise can effectively prevent and treat depression and anxiety, with gut microbiota playing a crucial role in this process. Studies have shown that exercise can influence the diversity and composition of gut microbiota, which in turn affects depression through immune, endocrine, and neural pathways in the gut-brain axis. The effectiveness of exercise varies based on its type, intensity, and duration, largely due to the different changes in gut microbiota. This article summarizes the possible mechanisms by which exercise affects gut microbiota and how gut microbiota influences depression. Additionally, we reviewed literature on the effects of exercise on depression at different intensities, types, and durations to provide a reference for future exercise-based therapies for depression.