S-adenosyl-L-methionine improves ventricular remodeling after myocardial infarction by regulating angiogenesis and fibrosis

Purpose: To investigate the effect of S-adenosyl-L-methionine (SAM) on angiogenesis and fibrosis in the heart of rats with myocardial infarction (MI), and to determine the mechanism of action.Methods: Sprague Dawley rats with MI received SAM treatment (15 mg/kg) intraperitoneally. The cumulative survival (%) of rats was recorded to determine their rate of survival. Hematoxylin-eosin staining, echocardiography, and hemodynamics were also performed. In addition, the effects of SAM vascular regeneration in the rats were analyzed by determining the expression of vascular endothelial growth factor (VEGF), basic fibroblast growth factor (bFGF) and hypoxia-inducible factor 1-α (HIF1-α) in rats.Results: The 8-week survival rate of the MI group was significantly lower than that of the sham group, while SAM significantly improved the survival rate of the rats. In addition, SAM improved the contractile and diastolic heart function in the rats and also increased the ventricular pressure change. Furthermore, SAM elevated the expressions of VEGF, bFGF and HIF1-α in rat myocardium and serum. In myocardial tissues of SAM-treated rats, the expressions of collagen I, collagen III and α-sma were reduced, indicating that SAM inhibited myocardial fibrosis. In addition, SAM promoted cardiac angiogenesis by activating Jagged1/Notch1 signaling pathway.Conclusion: SAM promotes angiogenesis of the myocardium by activating Jagged1/Notch1 signaling pathway and inhibiting fibrosis in rat myocardium. Therefore, SAM effectively inhibits ventricular remodeling in rats after MI, thereby improving the rats’ heart structure and function. The results may provide new targets for the treatment of myocardial infarction

CPDG: A Contrastive Pre-Training Method for Dynamic Graph Neural Networks

Dynamic graph data mining has gained popularity in recent years due to the rich information contained in dynamic graphs and their widespread use in the real world. Despite the advances in dynamic graph neural networks (DGNNs), the rich information and diverse downstream tasks have posed significant difficulties for the practical application of DGNNs in industrial scenarios. To this end, in this paper, we propose to address them by pre-training and present the Contrastive Pre-Training Method for Dynamic Graph Neural Networks (CPDG). CPDG tackles the challenges of pre-training for DGNNs, including generalization and long-short term modeling capability, through a flexible structural-temporal subgraph sampler along with structural-temporal contrastive pre-training schemes. Extensive experiments conducted on both large-scale research and industrial dynamic graph datasets show that CPDG outperforms existing methods in dynamic graph pre-training for various downstream tasks under three transfer settings.Comment: 12 pages, 6 figure

Modeling Spatiotemporal Periodicity and Collaborative Signal for Local-Life Service Recommendation

Online local-life service platforms provide services like nearby daily essentials and food delivery for hundreds of millions of users. Different from other types of recommender systems, local-life service recommendation has the following characteristics: (1) spatiotemporal periodicity, which means a user's preferences for items vary from different locations at different times. (2) spatiotemporal collaborative signal, which indicates similar users have similar preferences at specific locations and times. However, most existing methods either focus on merely the spatiotemporal contexts in sequences, or model the user-item interactions without spatiotemporal contexts in graphs. To address this issue, we design a new method named SPCS in this paper. Specifically, we propose a novel spatiotemporal graph transformer (SGT) layer, which explicitly encodes relative spatiotemporal contexts, and aggregates the information from multi-hop neighbors to unify spatiotemporal periodicity and collaborative signal. With extensive experiments on both public and industrial datasets, this paper validates the state-of-the-art performance of SPCS.Comment: KDAH CIKM'23 Worksho

Exploring the relationship between response time sequence in scale answering process and severity of insomnia: a machine learning approach

Objectives: The study aims to investigate the relationship between insomnia and response time. Additionally, it aims to develop a machine learning model to predict the presence of insomnia in participants using response time data. Methods: A mobile application was designed to administer scale tests and collect response time data from 2729 participants. The relationship between symptom severity and response time was explored, and a machine learning model was developed to predict the presence of insomnia. Results: The result revealed a statistically significant difference (p<.001) in the total response time between participants with or without insomnia symptoms. A correlation was observed between the severity of specific insomnia aspects and response times at the individual questions level. The machine learning model demonstrated a high predictive accuracy of 0.743 in predicting insomnia symptoms based on response time data. Conclusions: These findings highlight the potential utility of response time data to evaluate cognitive and psychological measures, demonstrating the effectiveness of using response time as a diagnostic tool in the assessment of insomnia

Terahertz nonlinear hall rectifiers based on spin-polarized topological electronic states in 1T-CoTe2

The zero-magnetic-field nonlinear Hall effect (NLHE) refers to the second-order transverse current induced by an applied alternating electric field; it indicates the topological properties of inversion-symmetry-breaking crystals. Despite several studies on the NLHE induced by the Berry-curvature dipole in Weyl semimetals, the direct current conversion by rectification is limited to very low driving frequencies and cryogenic temperatures. The nonlinear photoresponse generated by the NLHE at room temperature can be useful for numerous applications in communication, sensing, and photodetection across a high bandwidth. In this study, observations of the second-order NLHE in type-II Dirac semimetal CoTe2 under time-reversal symmetry are reported. This is determined by the disorder-induced extrinsic contribution on the broken-inversion-symmetry surface and room-temperature terahertz rectification without the need for semiconductor junctions or bias voltage. It is shown that remarkable photoresponsivity over 0.1 A W−1, a response time of approximately 710 ns, and a mean noise equivalent power of 1 pW Hz−1/2 can be achieved at room temperature. The results open a new pathway for low-energy photon harvesting via nonlinear rectification induced by the NLHE in strongly spin–orbit-coupled and inversion-symmetry-breaking systems, promising a considerable impact in the field of infrared/terahertz photonicsPID2019–109525RB-I00, CEX2018-000805-M, EU’s H2020 NFFA-Europe (n. 654360), and NFFA-Europe-Pilot (10100741

Empagliflozin inhibits coronary microvascular dysfunction and reduces cardiac pericyte loss in db/db mice

BackgroundCoronary microvascular dysfunction (CMD) is a pathophysiological feature of diabetic heart disease. However, whether sodium-glucose cotransporter 2 (SGLT2) inhibitors protect the cardiovascular system by alleviating CMD is not known.ObjectiveWe observed the protective effects of empagliflozin (EMPA) on diabetic CMD.Materials and methodsThe mice were randomly divided into a db/db group and a db/db + EMPA group, and db/m mice served as controls. At 8 weeks of age, the db/db + EMPA group was given empagliflozin 10 mg/(kg⋅d) by gavage for 8 weeks. Body weight, fasting blood glucose and blood pressure were dynamically observed. Cardiac systolic and diastolic function and coronary flow reserve (CFR) were detected using echocardiography. The coronary microvascular structure and distribution of cardiac pericytes were observed using immunofluorescence staining. Picrosirius red staining was performed to evaluate cardiac fibrosis.ResultsEmpagliflozin lowered the increased fasting blood glucose levels of the db/db group. The left ventricular ejection fraction, left ventricular fractional shortening, E/A ratio and E/e′ ratio were not significantly different between the three groups. CFR was decreased in the db/db group, but EMPA significantly improved CFR. In contrast to the sparse and abnormal expansion of coronary microvessels observed in the db/db group, the number of coronary microvessels was increased, and the capillary diameter was decreased in the db/db + EMPA group. The number and microvascular coverage of cardiac pericytes were reduced in the db/db mice but were improved by EMPA. The cardiac fibrosis was increased in db/db group and may alleviate by EMPA.ConclusionEmpagliflozin inhibited CMD and reduced cardiac pericyte loss in diabetic mice

The effect of the state sector on wage inequality in urban China: 1988–2007

This paper examines the effect of the public sector and state-owned enterprises (SOEs) on wage inequality in urban China using China Household Income Project data. It applies quantile regression analysis, the Machado and Mata decomposition to investigate how urban wage inequality was affected by the changes in wage structure and employment shares of the public sector and SOEs. We find that since the radical state sector reforms designed to reduce overstaffing and improve efficiency in the late 1990s, urban wage gaps were narrowed due to the reduction in the employment share of the state sector; the wage premium of the state sector in comparison with the non-state sector increased significantly; and changes in the wage structure of the labour market caused the rise in urban wage inequality