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Article: Perceived Social Mobility and Smartphone Dependence in University Students: The Roles of Hope and Family Socioeconomic Status.

Xiao, Luxia / Yao, Meilin / Liu, Hongrui

Psychology research and behavior management

2024 Volume 17, Page(s) 1805–1817

Abstract: Purpose: Drawing upon the cognitive-behavioral model of pathological Internet use (PIU) and tunnel effect, this study aimed to construct a moderated mediation model from the perspective of social ecology. Specifically, the model investigated the ... ...

Abstract	Purpose: Drawing upon the cognitive-behavioral model of pathological Internet use (PIU) and tunnel effect, this study aimed to construct a moderated mediation model from the perspective of social ecology. Specifically, the model investigated the relationship between perceived social mobility and smartphone dependence, with a focus on the mediating role of hope and the moderating effect of family socioeconomic status (SES) underlying this relationship. Methods: A cross-sectional study was conducted with 718 Chinese university students ( Results: The results showed that (a) less perceived social mobility was linked with greater smartphone dependence; (b) hope mediated the aforementioned relationship; and (c) family SES moderated the first-stage path of the indirect effect through hope. For university students with low (rather than high) family SES, their level of hope increased with the improvement of perceived social mobility, and in turn, that of smartphone dependence decreased. Conclusion: These findings suggest that positive perceptions of upward social class mobility and hopeful attitudes toward future opportunities and personal development among disadvantaged university students may alleviate their reliance on smartphones. Researchers and policymakers should pay attention to the role of individuals' perceptions of the macro environment in motivating specific risky behaviors among university students. Future interventions are essential to mitigate pessimistic environmental perceptions and foster a sense of hope among university students.
Language	English
Publishing date	2024-05-01
Publishing country	New Zealand
Document type	Journal Article
ZDB-ID	2495093-2
ISSN	1179-1578
ISSN	1179-1578
DOI	10.2147/PRBM.S455939
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Article ; Online: Reciprocal Relationship Between Learning Interest and Learning Persistence: Roles of Strategies for Self-Regulated Learning Behaviors and Academic Performance.

Wu, Xinyue / Liu, Hongrui / Xiao, Luxia / Yao, Meilin

Journal of youth and adolescence

2024

Abstract: Learning interest (internal driving motivation) and learning persistence (explicit behaviors) are important factors affecting students' academic development, yet whether they operate reciprocally and how to bolster them are still issues requiring ... ...

Abstract	Learning interest (internal driving motivation) and learning persistence (explicit behaviors) are important factors affecting students' academic development, yet whether they operate reciprocally and how to bolster them are still issues requiring attention. This study aimed to examine the reciprocal relationship between learning interest and persistence as well as the potential mechanisms behind the relationship from the perspectives of internal self-regulation and external feedback (i.e., academic performance). 510 students (M
Language	English
Publishing date	2024-05-15
Publishing country	United States
Document type	Journal Article
ZDB-ID	186743-x
ISSN	1573-6601 ; 0047-2891
ISSN (online)	1573-6601
ISSN	0047-2891
DOI	10.1007/s10964-024-01994-9
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Article ; Online: Convolutional Long-Short Term Memory Network with Multi-Head Attention Mechanism for Traffic Flow Prediction.

Wei, Yupeng / Liu, Hongrui

Sensors (Basel, Switzerland)

2022 Volume 22, Issue 20

Abstract: Accurate predictive modeling of traffic flow is critically important as it allows transportation users to make wise decisions to circumvent traffic congestion regions. The advanced development of sensing technology makes big data more affordable and ... ...

Abstract	Accurate predictive modeling of traffic flow is critically important as it allows transportation users to make wise decisions to circumvent traffic congestion regions. The advanced development of sensing technology makes big data more affordable and accessible, meaning that data-driven methods have been increasingly adopted for traffic flow prediction. Although numerous data-driven methods have been introduced for traffic flow predictions, existing data-driven methods cannot consider the correlation of the extracted high-dimensional features and cannot use the most relevant part of the traffic flow data to make predictions. To address these issues, this work proposes a decoder convolutional LSTM network, where the convolutional operation is used to consider the correlation of the high-dimensional features, and the LSTM network is used to consider the temporal correlation of traffic flow data. Moreover, the multi-head attention mechanism is introduced to use the most relevant portion of the traffic data to make predictions so that the prediction performance can be improved. A traffic flow dataset collected from the Caltrans Performance Measurement System (PeMS) database is used to demonstrate the effectiveness of the proposed method.
MeSH term(s)	Memory, Short-Term ; Transportation ; Research Design ; Big Data ; Data Management
Language	English
Publishing date	2022-10-20
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s22207994
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Article ; Online: Global economic structure transition boosts PM

Wen, Wen / Su, Yang / Yang, Xuechun / Liang, Yuhan / Guo, Yangyang / Liu, Hongrui

The Science of the total environment

2024 Volume 916, Page(s) 170071

Abstract: The Belt and Road Initiative (BRI) is an open platform for international cooperation proposed by China to promote common global development and prosperity. The BRI can promote the optimal allocation of resources and promote in-depth cooperation in ... ...

Abstract	The Belt and Road Initiative (BRI) is an open platform for international cooperation proposed by China to promote common global development and prosperity. The BRI can promote the optimal allocation of resources and promote in-depth cooperation in international trade. Meanwhile, it can establish a green supply chain cooperation network to help BRI countries achieve green transformation. BRI has made a notable contribution to the rapid growth of cross-border trade. However, it has also brought environmental impacts. Given that little attention has been paid to the trade-embodied particulate matter 2.5 related human health impacts (PM
MeSH term(s)	Humans ; Commerce ; Internationality ; China ; Environment ; Particulate Matter/analysis ; Economic Development ; Carbon Dioxide/analysis
Chemical Substances	Particulate Matter ; Carbon Dioxide (142M471B3J)
Language	English
Publishing date	2024-01-17
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	121506-1
ISSN	1879-1026 ; 0048-9697
ISSN (online)	1879-1026
ISSN	0048-9697
DOI	10.1016/j.scitotenv.2024.170071
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Article ; Online: A coumarin-furoxan hybrid as novel nitric oxide donor induced cell apoptosis and ferroptosis in NSCLC by promoting S-nitrosylation of STAT3 and negative regulation of JAK2-STAT3 pathway.

Cao, Fan / Li, Mengru / Wang, Weijie / Yi, Yi / Chen, Ying / Liu, Hongrui

Biochemical pharmacology

2024 Volume 222, Page(s) 116068

Abstract: Non-small cell lung cancer (NSCLC) still lacks effective treatment because of its extensive mutation diversity and frequent drug resistance. Therefore, it is urgent to develop new therapeutic strategies for NSCLC. In this study, we evaluated the ... ...

Abstract	Non-small cell lung cancer (NSCLC) still lacks effective treatment because of its extensive mutation diversity and frequent drug resistance. Therefore, it is urgent to develop new therapeutic strategies for NSCLC. In this study, we evaluated the inhibitory effect of a new coumarin-furoxan hybrid compound 9, a nitric oxide (NO) donor drug, on NSCLC proliferation and its mechanism. Our results show that compound 9 can inhibit the growth of four NSCLC cell lines and H1975 xenograft model in a dose-dependent manner. Compound 9 effectively releases high concentrations of NO within the mitochondria, leading to cellular oxidative stress, mitochondrial dysfunction, and apoptosis. Moreover, compound 9 inhibits JAK2/STAT3 protein phosphorylation and induces S-nitrosylation modification of STAT3, ultimately resulting in endogenous apoptosis in NSCLC. Additionally, compound 9 significantly induces NSCLC ferroptosis by depleting intracellular GSH, elevating MDA levels, inhibiting SLC7A11/GSH protein expression, and negatively regulating the JAK2/STAT3 pathway. In summary, this study elucidates the inhibitory effects of compound 9 on NSCLC proliferation and provides insights into the underlying mechanisms, offering new possibilities for NSCLC treatment strategies.
MeSH term(s)	Humans ; Carcinoma, Non-Small-Cell Lung/metabolism ; Lung Neoplasms/drug therapy ; Lung Neoplasms/metabolism ; Nitric Oxide Donors/pharmacology ; Nitric Oxide Donors/therapeutic use ; STAT3 Transcription Factor/metabolism ; Ferroptosis ; Apoptosis ; Coumarins/pharmacology ; Coumarins/therapeutic use ; Cell Line, Tumor ; Cell Proliferation ; Janus Kinase 2/metabolism ; Oxadiazoles
Chemical Substances	Nitric Oxide Donors ; furoxans ; STAT3 Transcription Factor ; Coumarins ; JAK2 protein, human (EC 2.7.10.2) ; Janus Kinase 2 (EC 2.7.10.2) ; STAT3 protein, human ; Oxadiazoles
Language	English
Publishing date	2024-02-20
Publishing country	England
Document type	Journal Article
ZDB-ID	208787-x
ISSN	1873-2968 ; 0006-2952
ISSN (online)	1873-2968
ISSN	0006-2952
DOI	10.1016/j.bcp.2024.116068
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Article ; Online: Capsaicin attenuates Porphyromonas gingivalis-suppressed osteogenesis of periodontal ligament stem cells via regulating mitochondrial function and activating PI3K/AKT/mTOR pathway.

Wang, Weijia / Zhou, Zhiyan / Ding, Tian / Feng, Susu / Liu, Hongrui / Liu, Mengmeng / Ge, Shaohua

Journal of periodontal research

2024

Abstract: Background and objective: Prevention of periodontal bone resorption triggered by Porphyromonas gingivalis (P. gingivalis) is crucial for dental stability. Capsaicin, known as the pungent ingredient of chili peppers, can activate key signaling molecules ... ...

Abstract	Background and objective: Prevention of periodontal bone resorption triggered by Porphyromonas gingivalis (P. gingivalis) is crucial for dental stability. Capsaicin, known as the pungent ingredient of chili peppers, can activate key signaling molecules involved in osteogenic process. However, the effect of capsaicin on osteogenesis of periodontal ligament stem cells (PDLSCs) under inflammation remains elusive. Methods: P. gingivalis culture suspension was added to mimic the inflammatory status after capsaicin pretreatment. The effects of capsaicin on the osteogenesis of PDLSCs, as well as mitochondrial morphology, Ca Results: Under P. gingivalis stimulation, capsaicin increased osteogenesis of PDLSCs. Not surprisingly, capsaicin rescued the damage to mitochondrial morphology, decreased the concentration of intracellular Ca Conclusion: Capsaicin increases osteogenesis of PDLSCs under inflammation and reduces alveolar bone resorption in mouse experimental periodontitis.
Language	English
Publishing date	2024-05-03
Publishing country	United States
Document type	Journal Article
ZDB-ID	390953-0
ISSN	1600-0765 ; 0022-3484
ISSN (online)	1600-0765
ISSN	0022-3484
DOI	10.1111/jre.13252
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Article ; Online: Brain Status Transferring Generative Adversarial Network for Decoding Individualized Atrophy in Alzheimer's Disease.

Gao, Xingyu / Liu, Hongrui / Shi, Feng / Shen, Dinggang / Liu, Manhua

IEEE journal of biomedical and health informatics

2023 Volume 27, Issue 10, Page(s) 4961–4970

Abstract: Deep learning has been widely investigated in brain image computational analysis for diagnosing brain diseases such as Alzheimer's disease (AD). Most of the existing methods built end-to-end models to learn discriminative features by group-wise analysis. ...

Abstract	Deep learning has been widely investigated in brain image computational analysis for diagnosing brain diseases such as Alzheimer's disease (AD). Most of the existing methods built end-to-end models to learn discriminative features by group-wise analysis. However, these methods cannot detect pathological changes in each subject, which is essential for the individualized interpretation of disease variances and precision medicine. In this article, we propose a brain status transferring generative adversarial network (BrainStatTrans-GAN) to generate corresponding healthy images of patients, which are further used to decode individualized brain atrophy. The BrainStatTrans-GAN consists of generator, discriminator, and status discriminator. First, a normative GAN is built to generate healthy brain images from normal controls. However, it cannot generate healthy images from diseased ones due to the lack of paired healthy and diseased images. To address this problem, a status discriminator with adversarial learning is designed in the training process to produce healthy brain images for patients. Then, the residual between the generated and input images can be computed to quantify pathological brain changes. Finally, a residual-based multi-level fusion network (RMFN) is built for more accurate disease diagnosis. Compared to the existing methods, our method can model individualized brain atrophy for facilitating disease diagnosis and interpretation. Experimental results on T1-weighted magnetic resonance imaging (MRI) data of 1,739 subjects from three datasets demonstrate the effectiveness of our method.
MeSH term(s)	Humans ; Alzheimer Disease/diagnostic imaging ; Brain/diagnostic imaging ; Head ; Image Processing, Computer-Assisted/methods ; Magnetic Resonance Imaging/methods
Language	English
Publishing date	2023-10-05
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2695320-1
ISSN	2168-2208 ; 2168-2194
ISSN (online)	2168-2208
ISSN	2168-2194
DOI	10.1109/JBHI.2023.3304388
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Article ; Online: Probing the interaction between encapsulated ethoxyquin and its β-cyclodextrin inclusion complex with bovine serum albumin.

Li, Ye / Liu, Hongrui / Mu, Chunyu / Gu, Jiali / Li, Chun

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy

2023 Volume 304, Page(s) 123259

Abstract: Ethoxyquin (EQ) is a synthetic antioxidant that is derived from quinolines and found in many meat products. EQ is strictly regulated in feed due to its potential health implications. An investigation of the interaction mechanism between EQ and ... ...

Abstract	Ethoxyquin (EQ) is a synthetic antioxidant that is derived from quinolines and found in many meat products. EQ is strictly regulated in feed due to its potential health implications. An investigation of the interaction mechanism between EQ and transporter protein before and after β-cyclodextrin (β-CD) encapsulation was conducted with the use of multi-spectroscopy, cyclic voltammetry, and molecular docking. EQ formed complexes with bovine serum albumin (BSA), and affected secondary structure and microenvironment polarity of BSA. However, at 298 K, EQ's fluorescence quenching constants decreased from (9.81 ± 0.05) × 10
MeSH term(s)	Serum Albumin, Bovine/chemistry ; Molecular Docking Simulation ; Ethoxyquin ; Protein Binding ; Spectrometry, Fluorescence ; Protein Structure, Secondary ; beta-Cyclodextrins/chemistry ; Thermodynamics ; Circular Dichroism ; Binding Sites
Chemical Substances	Serum Albumin, Bovine (27432CM55Q) ; Ethoxyquin (9T1410R4OR) ; beta-Cyclodextrins
Language	English
Publishing date	2023-08-12
Publishing country	England
Document type	Journal Article
ZDB-ID	210413-1
ISSN	1873-3557 ; 0370-8322 ; 0584-8539 ; 1386-1425
ISSN (online)	1873-3557
ISSN	0370-8322 ; 0584-8539 ; 1386-1425
DOI	10.1016/j.saa.2023.123259
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Article ; Online: Investigation of the separate and simultaneous bindings of warfarin and fenofibrate to bovine serum albumin.

Gu, Jiali / Liu, Hongrui / Huang, Xiyao / Ma, Yanxuan / Zhang, Liang

International journal of biological macromolecules

2023 Volume 236, Page(s) 123978

Abstract: Lipid-lowering drugs are often taken with anticoagulant drugs in hyperlipidemia patients. Fenofibrate (FNBT) and warfarin (WAR) are common clinical lipid-lowering drugs and anticoagulant drugs, respectively. A study of binding affinity, binding force, ... ...

Abstract	Lipid-lowering drugs are often taken with anticoagulant drugs in hyperlipidemia patients. Fenofibrate (FNBT) and warfarin (WAR) are common clinical lipid-lowering drugs and anticoagulant drugs, respectively. A study of binding affinity, binding force, binding distance, and binding sites was performed to determine the interaction mechanism between drugs and carrier proteins (bovine serum albumin, BSA), as well as their effects on BSA conformation. Both FNBT and WAR can form complexes with BSA by van der Waals force and hydrogen bonds. WAR had a stronger fluorescence quenching effect on BSA, a stronger binding affinity, and greater effects on BSA conformation than FNBT. According to fluorescence spectroscopy and cyclic voltammetry, co-administration of drugs decreased one drug's binding constant to BSA and increased its binding distance. This suggested that each drug's binding to BSA was disturbed by each other, as well as each drug's binding ability to BSA was altered by the other. It was demonstrated that co-administration of drugs had greater effects on the secondary structure of BSA and microenvironment polarity surrounding amino acid residues, using multiple spectroscopy techniques, such as ultraviolet spectroscopy, Fourier transform infrared spectroscopy, and synchronous fluorescence spectroscopy.
MeSH term(s)	Humans ; Serum Albumin, Bovine/chemistry ; Protein Binding ; Fenofibrate ; Warfarin ; Thermodynamics ; Spectrophotometry, Ultraviolet ; Binding Sites ; Spectroscopy, Fourier Transform Infrared ; Spectrometry, Fluorescence ; Protein Structure, Secondary ; Anticoagulants ; Lipids ; Molecular Docking Simulation
Chemical Substances	Serum Albumin, Bovine (27432CM55Q) ; Fenofibrate (U202363UOS) ; Warfarin (5Q7ZVV76EI) ; Anticoagulants ; Lipids
Language	English
Publishing date	2023-03-10
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	282732-3
ISSN	1879-0003 ; 0141-8130
ISSN (online)	1879-0003
ISSN	0141-8130
DOI	10.1016/j.ijbiomac.2023.123978
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Book ; Online: A Generalized Neural Diffusion Framework on Graphs

Li, Yibo / Wang, Xiao / Liu, Hongrui / Shi, Chuan

2023

Abstract: Recent studies reveal the connection between GNNs and the diffusion process, which motivates many diffusion-based GNNs to be proposed. However, since these two mechanisms are closely related, one fundamental question naturally arises: Is there a general ... ...

Abstract	Recent studies reveal the connection between GNNs and the diffusion process, which motivates many diffusion-based GNNs to be proposed. However, since these two mechanisms are closely related, one fundamental question naturally arises: Is there a general diffusion framework that can formally unify these GNNs? The answer to this question can not only deepen our understanding of the learning process of GNNs, but also may open a new door to design a broad new class of GNNs. In this paper, we propose a general diffusion equation framework with the fidelity term, which formally establishes the relationship between the diffusion process with more GNNs. Meanwhile, with this framework, we identify one characteristic of graph diffusion networks, i.e., the current neural diffusion process only corresponds to the first-order diffusion equation. However, by an experimental investigation, we show that the labels of high-order neighbors actually exhibit monophily property, which induces the similarity based on labels among high-order neighbors without requiring the similarity among first-order neighbors. This discovery motives to design a new high-order neighbor-aware diffusion equation, and derive a new type of graph diffusion network (HiD-Net) based on the framework. With the high-order diffusion equation, HiD-Net is more robust against attacks and works on both homophily and heterophily graphs. We not only theoretically analyze the relation between HiD-Net with high-order random walk, but also provide a theoretical convergence guarantee. Extensive experimental results well demonstrate the effectiveness of HiD-Net over state-of-the-art graph diffusion networks. Comment: Accepted by AAAI 2024
Keywords	Computer Science - Social and Information Networks ; Computer Science - Artificial Intelligence
Subject code	515
Publishing date	2023-12-13
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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