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Vascular endothelial cells and oxidation reduction system play an important role in the pathogenesis of atherosclerosis (AS). If these conditions are disordered, it will inevitably lead to plaque formation and even rupture. Astragaloside IV (AsIV) and salvianolic acid B (Sal B) are the main active ingredients of Astragalus membranaceus and Salvia miltiorrhiza, respectively, and found to ameliorate vascular endothelial dysfunction and protect against oxidative stress in recent studies. However, it is still unknown if the combination of AsIV and Sal B (AsIV + Sal B) can inhibit the development of plaque through amplifying the protective effect of vascular endothelial cells and anti-oxidative stress effect. To clarify the role of AsIV + Sal B in AS, we observed the efficacy of each group (Control, Model, AsIV, Sal B, and AsIV + Sal B) by biomolecular assays, such as observing the pathological morphology of the aorta by oil red O staining, evaluating the level of oxidative stress and endothelial cells in the serum by the Elisa test, and analyzing the changes of all small molecule metabolites in liver tissue by UPLC-QTOF-MS. Results showed that AsIV, Sal B and AsIV + Sal B decreased the deposition of lipid in the arterial wall, so as to exert the effect of anti-oxidant stress and vascular endothelial protection, where the inhibitory effect of AsIV + Sal B was the most obvious. Metabonomics analysis showed that Sal B regulated the metabolic pathways of arginine and proline. AsIV regulated glycerol metabolism and saturated fatty acid biosynthesis metabolism. AsIV + Sal B is mainly related to the regulation of the citrate cycle (TCA cycle), alanine, aspartic acid, and glutamate metabolism, cysteine, and methionine metabolism. Succinic acid and methionine are synergistic metabolites that exert an enhancing effect when AsIV and Sal B were used in combination. In conclusion, we demonstrated that AsIV acompanied with Sal B can be successfully used for anti-oxidative stress and vascular endothelial protection of AS, and succinic acid and methionine are the synergistic metabolites.

Hypertension is a common cardiovascular disease. Zhengan Xifeng Decoction (ZGXFD), a classic prescription for adjuvant treatment of hypertension, but its clinical application characteristics and biological information have not been comprehensively analysed. This study is based on real-world data from 7571 electronic medical records of hypertension patients treated by ZGXFD. The Apriori algorithm was used to obtain the coupled herbs of ZGXFD. A convolutional neural network was designed to measure the dose characteristic information of herbs. The topological features of the protein‒protein interaction data were used to analyse the biological information of herbs. The K-nearest neighbour model integrates the above characteristics of herbs into the same framework to observe the composition adjustment laws and mechanism of ZGXFD from multiple dimensions. Eighty-seven coupled herbs with dose characteristics were obtained. The results revealed that ZXGFD regulates cytokines and reduces the inflammatory response and metabolic disorder to achieve the purpose of adjuvant therapy. Moreover, machine learning model is used to analyze real-world data that include clinical and molecular biological data with hierarchical characteristics, which provides a micro-biological explanation for the clinical application of herbs.

Aim of Study. Myocardial infarction is the number one cause of death worldwide. Existing treatment methods such as drugs and surgery cannot completely restore the structure and function of the ischemic heart. In recent years, therapeutic angiogenesis has received gradually increasing attention due to its fundamental therapeutic advantages of improving microcirculation and restoring blood supply in ischemic areas. This article mainly reviewed the mechanism and effect of angiogenesis-promoting herbs. Methods. We conducted a literature search on the bioactive components of medicinal plants and their effects on angiogenesis after MI. We searched for articles in Web of Science, MEDLINE, PubMed, Scopus, Google Scholar, and China National Knowledge Infrastructure databases before April 2021. Results. In this article, we summarized the mechanisms by which copper ions, microRNA, Akt1, inflammation, oxidative stress, mitochondria, and pericytes are involved in angiogenesis after myocardial infarction. In addition, we reviewed the angiogenic effects of natural herbal medicines such as Salvia miltiorrhiza Bunge Bunge, Carthamus tinctorius L., Pueraria lobata, Astragalus, Panax ginseng C.A. Mey., Panax notoginseng (Burkill) F.H. Chen, Cinnamomum cassia (L.) J. Presl, Rehmannia glutinosa (Gaertn.) DC., Leonurus japonicus Houtt, Scutellaria baicalensis Georgi., and Geum macrophyllum Willd. Conclusions. Some herbs have the effect of promoting angiogenesis. In the future, natural proangiogenic drugs may become candidates for the treatment of cardiovascular diseases.

Hypertension is one of the most reported cardiovascular and cerebrovascular diseases with significantly high morbidity and mortality rates. This condition threatens the very existence of human beings. Numerous studies conducted earlier revealed the good therapeutic effect of isorhynchophylline on hypertension since the former regulates the metabolic disorders in neurotransmitters. However, the mechanism behind this action is yet to be deciphered. The current study followed the targeted metabolomics method to investigate the changes in the neurotransmitter level in the hippocampus of spontaneously hypertensive rats (SHRs) after the rats were treated with isorhynchophylline. The authors predicted the metabolic pathways involved in extensively modified neurotransmitters. Further, the expressions of metabolism-key enzymes in mRNA and protein levels were also determined. When treated with isorhynchophylline, it induced notably varying metabolomic profiles of the hippocampus in SHRs. Isorhynchophylline perturbed a total of seven extensively modified neurotransmitters as well as the primarily related pathways such as tyrosine and glutamate metabolism. An increase in the key metabolic enzymes such as DDC, MAO, COMT, TH, and DβH was observed in the SHR group, whereas their levels decreased after treatment with isorhynchophylline. The expression of GAD67 established cross-current validity. So, isorhynchophylline has been proved to have potential therapeutic value to treat hypertension via tyrosine and glutamate metabolism in the hippocampus. Further, the current study also opened new ventures to further investigate the working mechanism of isorhynchophylline in hypertension.

Hypertension and coronary heart disease are the most common cardiovascular diseases, and traditional Chinese medicine is applied as an auxiliary treatment for common cardiovascular diseases. This study is based on 3 years of electronic medical record data from the Affiliated Hospital of Shandong University of Traditional Chinese Medicine. A complex network and machine learning algorithm were used to establish a screening model of coupled herbs for the treatment of hypertension complicated with coronary heart disease. A total of 5688 electronic medical records were collected to establish the prescription network and symptom database. The hierarchical network extraction algorithm was used to obtain core herbs. Biological features of herbs were collected from public databases. At the same time, five supervised machine learning models were established based on the biological features of the coupled herbs. Finally, the K-nearest neighbor model was established as a screening model with an AUROC of 91.0%. Seventy coupled herbs for adjuvant treatment of hypertension complicated with coronary heart disease were obtained. It was found that the coupled herbs achieved the purpose of adjuvant therapy mainly by interfering with cytokines and regulating inflammatory and metabolic pathways. These results show that this model can integrate the molecular biological characteristics of herbs, preliminarily screen combinations of herbs, and provide ideas for explaining the value in clinical applications.

In this study, patients with prehypertensive liver-fire hyperactivity syndrome(LFHS) were selected as the research objects. The plasma samples of healthy volunteers and patients with prehypertensive LFHS were analyzed by non-targeted metabolomics based on UPLC-Q-Exactive MS. The differential biomarkers and metabolic pathways were screened out by multivariate statistics and metabolic pathway analysis, which revealed the characteristics of metabolic patterns of the syndrome. Thirty-three potential biomarkers such as androsterone and lysophosphatidylcholine and 16 related metabolic pathways such as steroid hormone metabolism and lipid metabolism were identified, and a partial least squares-discriminant analysis(PLS-DA) model of traditional Chinese medicine(TCM) syndromes was preliminarily constructed: Y =-0.070X_(13)-0.006X_8+ 0.040X_5-0.152X_1+0.131X_(10)+0.036X_(11)+0.043X_(23)+0.076X_(16)+0.132X_(20)+0.081X_(19)-0.101X_(31)+0.082X_(15)-0.038X_9+0.079X_(24). The predictive value of the model was 88.1%, and the explanatory power was 88.4%. In this study, the characteristic metabolic pattern of the prehypertensive LFHS was distinguished and revealed by metabolomics. The constructed PLS-DA model is expected to provide an objective basis for the identification of TCM syndromes in prehypertension, and inspiration for exploring the biological basis of TCM syndromes at small-molecular and overall levels.

Multi-camera vehicle tracking at the city scale is an essential task in traffic management for smart cities. Large-scale video analytics is challenging due to the vehicle variabilities, view variations, frequent occlusions, degraded pixel quality, and appearance differences. In this work, we develop a multi-target multi-camera (MTMC) vehicle tracking system based on a newly proposed Candidates Intersection Ratio (CIR) metric that can effectively evaluate vehicle tracklets for matching across views. Our system consists of four modules: (1) Faster-RCNN vehicle detection, (2) detection association based on re-identification feature matching, (3) single-camera tracking (SCT) to produce initial tracklets, (4) multi-camera vehicle tracklet matching and re-identification that creates longer, consistent tracklets across the city scale. Based on popular DNN object detection and SCT modules, we focus on the development of tracklet creation, association, and linking in SCT and MTMC. Specifically, SCT filters are proposed to effectively eliminate unreliable tracklets. The CIR metric improves robust vehicle tracklet linking across visually distinct views. Our system obtains IDF1 score of 0.1343 on the AI City 2021 Challenge Track 3 public leaderboard.

Multi-camera vehicle tracking at the city scale has received lots of attention in the last few years. It has large-scale differences, frequent occlusion, and appearance differences caused by the viewing angle differences, which is quite challenging. In this research, we propose the Tracklet Similarity Network (TSN) for a multi-target multi-camera (MTMC) vehicle tracking system based on the evaluation of the similarity between vehicle tracklets. In addition, a novel component, Candidates Intersection Ratio (CIR), is proposed to refine the similarity. It provides an associate scheme to build the multi-camera tracking results as a tree structure. Based on these components, an end-to-end vehicle tracking system is proposed. The experimental results demonstrate that an 11% improvement on the evaluation score is obtained compared to the conventional similarity baseline.

In this paper, a novel coordinates tracking method is proposed for Virtual Reality (VR) environment using sensor signals. The purpose is to extend movement tracking in VR from 3 Degrees of Freedom (DOF) of rotation to 6DOF of position plus rotation. As a result, we can track VR coordinates without using controller or handler provided by VR devices. An RNN-based model is proposed to predict displacement of positions in each timestamp given measured acceleration and Euler angles from sensor signals. Experiments demonstrate that it is effective to predict correct position displacement, which not only models the relationship between sensor signals and displacement but also handles the cumulative errors during tracking.

Wind power forecasting receives more and more attention during the past decades. The intermittence and uncertainty of wind energy may cause unstable quality of power supply and bring great harm to industry. Therefore, a stable and accurate wind power forecasting technique is very important for wind energy system. A novel wind power prediction system is proposed in this paper. Key factors are firstly determined from the wind data provided by Central Weather Bureau of Taiwan. Then, serval machine and deep learning methods are adopted as backbone model to predict the power generation given a fixed interval. The performance is analyzed among different models in our experiment results.

The increase of blood pressure is accompanied by the changes in the morphology and function of vascular endothelial cells. Vascular endothelial injury and hypertension actually interact as both cause and effect. A large number of studies have proved that inflammation plays a significant role in the occurrence and development of hypertension, but the potential mechanism between inflammation and hypertensive endothelial injury is still ambiguous. The purpose of this study was to explore the association between the activation of NLRP3 inflammasome and hypertensive endothelial damage, and to demonstrate the protective effect of sinapine thiocyanate (ST) on endothelia in hypertension. The expression of NLRP3 gene was silenced by tail vein injection of adeno-associated virus (AAVs) in spontaneously hypertensive rats (SHRs), indicating that activation of NLRP3 inflammasome accelerated hypertensive endothelial injury. ST not only protected vascular endothelial function in SHRs by inhibiting the activation of NLRP3 inflammasome and the expression of related inflammatory mediators, but also improved AngII-induced huvec injury. In summary, our results show that alleviative NLRP3 inflammasome activation attenuates hypertensive endothelial damage and ST ameliorates vascular endothelial dysfunction in hypertension via inhibiting activation of the NLRP3 inflammasome.

To obtain the subtypes of the clinical hypertension population based on symptoms and to explore the relationship between hypertension and comorbidities. The data set was collected from the Chinese medicine (CM) electronic medical records of 33,458 hypertension inpatients in the Affiliated Hospital of Shandong University of Traditional Chinese Medicine between July 2014 and May 2017. Then, a hypertension disease comorbidity network (HDCN) was built to investigate the complicated associations between hypertension and their comorbidities. Moreover, a hypertension patient similarity network (HPSN) was constructed with patients’ shared symptoms, and 7 main hypertension patient subgroups were identified from HPSN with a community detection method to exhibit the characteristics of clinical phenotypes and molecular mechanisms. In addition, the significant symptoms, diseases, CM syndromes and pathways of each main patient subgroup were obtained by enrichment analysis. The significant symptoms and diseases of these patient subgroups were associated with different damaged target organs of hypertension. Additionally, the specific phenotypic features (symptoms, diseases, and CM syndromes) were consistent with specific molecular features (pathways) in the same patient subgroup. The utility and comprehensiveness of disease classification based on community detection of patient networks using shared CM symptom phenotypes showed the importance of hypertension patient subgroups.

We present methods developed in our participation of the AI City 2020 Challenge (AIC20) and report evaluation results in this contest. With the blooming of AI computer vision techniques, vehicle detection, tracking, identification, and counting all have advanced significantly. However, whether these technologies are ready for real-world smart transportation usage is still a open question. The goal of this work is to apply and integrate state-of-the-art techniques for solving the challenge problems under a standardized setup and evaluation. We participated all 4 AIC20 challenge tracks (T1 to T4). In T1 challenge, we perform vehicle counting by associating deep features extracted from Mask-RCNN detections and tracklets, followed by vehicle movement zone matching. In T2 challenge, we perform vehicle type and color classification and then rank matching vehicles using a PGAM re-id network. In T3 challenge, we proposed a new Multi-Camera Tracking Network (MTCN) that takes single-camera vehicle tracking as input, and performs multi-camera tracklet fusion and linking, by jointly optimizing the matching of vehicle appearance and physical features. In T4 challenge, we adopt a leading method based on perspective detection and spatial-temporal matrix discriminating, and improve it with background modeling for traffic anomaly detection. We achieved top-6 and top-4 performance for T3 and T4 challenges respectively in the AIC20 general leaderboard.

Aims We tested whether anger affects the balance between endothelium-derived vasodilators and vasoconstrictors in spontaneously hypertensive rats (SHRs). Methods Five endothelium-produced vasoactive factors (nitric oxide, prostacyclin, urotensin, endothelin and thromboxane B2) were measured in an established SHR behavioural model of anger, in “non-angry” SHR rats, and in control Wistar–Kyoto rats. Results All angry SHR rats showed the typical angry behaviour and angry SHR rats had significantly higher blood pressure and heart rate than control rats. Angry rats had significantly lower levels of two vasodilators, nitric oxide and prostacyclin, and significantly higher levels of two vasoconstrictors, endothelin and thromboxane B2 than either non-angry SHR or control rats. Levels of a third vasoconstrictor, urotensin, were significantly lower in angry SHR than in non-angry SHR or control rats. Conclusions Our results suggest that anger causes an imbalance of endothelium-produced vasodilating and vasoconstricting substances. This may have implications for the development and/or progression of hypertension.

High performance liquid chromatography-time-off-flight mass spectrometer (HPLC-TOFMS) technology coupled with partial least squares discriminant analysis (PLS-DA) processed by SIMCA-P software was applied to investigate serum endogenous metabolites alternations of valsartan in spontaneous hypertension rats (SHR). And MetPA platform was used to connect identified potential biomarkers in corresponding metabolic pathways to find possible therapeutic mechanism of valsartan. Valsartan significantly declined the blood pressure of SHRs (P0.05) at fourth week. The metabolic profiling significantly changed and four metabolites involved in G protein-coupled pathway were identified. Metabolomics is able to detect holistic and microcosmic alternations in organism, so as to elucidate therapeutic mechanism of drugs.

Thirty SHRs were obtained randomly to hypertension, model group, captopril group and Qingre jiangya capsule group. Ten Wistar rats were used as control group. The hippocampus tissue was removed to explore the damage of spontaneously hypertensive rats (SHR) and the protective effect of Qingre jiangya capsule after continuously administered for 14 days. And then the data were processed by principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The research results revealed captopril group was significantly different from the other three groups. The classification of other three groups is also very clear after captopril group removed. This suggested that Qingre jiangya capsule could improve the overall metabolism compared with captopril. Four metabolites were identified: dimethylglycine, glycerophosphocholine, aldosterone and noradrenaline. Hypertension hippocampus damage may mainly be expressed in tyrosine metabolism, aldosterone-regulated sodium, vascular smooth muscle contraction reabsorption, and Qingre jiangya capsule could reverse the hippocampus tissue damage of SHR.

To study the changes of urine metabolites in hypertension patients of ascendant hyperactivity of Gan yang syndrome (AHGYS), and to explore its essence in hypertension patients.Ten typical hypertension patients of AHGYS were recruited as the patient group, and the other twelve healthy volunteers were recruited as the normal group. The metabolite profiling in the urine were collected using by high performance liquid chromatography coupled with time of flight mass spectrometry (HPLC-TOFMS). The principal component analysis (PCA) and partial least-square discriminant analysis (PLS-DA) were analyzed using SIMCA-P Software. The differential metabolites in the urine were found out and identified. The possible relevant metabolic pathways were explained.The data from the analysis by PCA in the urine samples of the patient group and the normal group showed, two sets of data could be obviously classified in the score plot. Compared with the normal group, significant changes happened to the body metabolism in the patient group. The metabolites relevant to hypertension patients of AHGYS were determined using the PLS-DA. Fifteen compounds of the structure and metabolic pathways had been confirmed through inquiring KEGG Database, mainly including amino acids, free fatty acids, sphingosine, and so on.The hypertension patients of AHGYS were studied using HPLC-TOFMS combined with pattern recognition, thus finding out small molecular metabolic markers from the microscopic field, which was advantageous in probing the biological nature of Chinese medicine syndromes.