Explore the vast range of titles available.

Dynamic network link prediction is extensively applicable in various scenarios, and it has progressively emerged as a focal point in data mining research. The comprehensive and accurate extraction of node information, as well as a deeper understanding of the temporal evolution pattern, are particularly crucial in the investigation of link prediction in dynamic networks. To address this issue, this paper introduces a node representation learning framework based on Graph Convolutional Networks (GCN), referred to as GCN_MA. This framework effectively combines GCN, Recurrent Neural Networks (RNN), and multi-head attention to achieve comprehensive and accurate representations of node embedding vectors. It aggregates network structural features and node features through GCN and incorporates an RNN with multi-head attention mechanisms to capture the temporal evolution patterns of dynamic networks from both global and local perspectives. Additionally, a node representation algorithm based on the node aggregation effect (NRNAE) is proposed, which synthesizes information including node aggregation and temporal evolution to comprehensively represent the structural characteristics of the network. The effectiveness of the proposed method for link prediction is validated through experiments conducted on six distinct datasets. The experimental outcomes demonstrate that the proposed approach yields satisfactory results in comparison to state-of-the-art baseline methods.

Existing research have not yet focused on the mechanism of Internet of Things(IoT) technology’s impact on the contract-farming supply chain.We introduce the IoT technology into the contract-farming supply chain with financing, successively construct decision models for the contract-farming supply chain under the scenarios of no subsidy policy, interest rate subsidy policy, and cost subsidy policy. The results show that an increase in bank interest rate will reduce the level of IoT application, purchasing price, members benefits. When the financing interest rate is within a certain range, members benefits in the case of interest rate subsidy policy are greater than the corresponding values in the case of cost subsidy policy. In the case of no subsidy policy, interest rate subsidy policy, and cost subsidy policy, the application level of the IoT, purchasing price, and the company benefit are positively correlated with the output effect factor of the IoT technology. The farmer will actively invest in the IoT only when the cost-reducing effect of IoT is substantial. When the government’s subsidy expenditure is equal, if the goal is to increase social welfare, the government should adopt the interest rate subsidy policy; if the goal is to promote the popularization of IoT and help impoverished farmers, the government should adopt the cost subsidy policy.

Fibroblast growth factors (FGFs) and their receptors regulate numerous cellular processes, such as metabolism and signal transduction, but can also drive tumorigenesis. Specifically, in lung cancer, the overexpression of FGFs, as well as the amplification, mutation and fusion of FGFR genes, are closely linked to the initiation, progression and resistance of the disease, suggesting that targeting FGF/FGFR is an attractive therapeutic strategy for lung cancer treatment. Nintedanib, a multitarget tyrosine kinase inhibitor (TKI) used in combination with docetaxel, has shown some success as a second-line therapy for lung cancer. However, clinical trials evaluating other FGFR inhibitors have yielded mixed results, indicating substantial complexity in targeting aberrant FGF/FGFR signaling. In this review, we describe the aberrations in FGF/FGFR signaling in lung cancer and summarize the clinical efficacy of FGFR inhibitors, such as multitarget TKIs, selective FGFR-TKIs and biological agents. We also discuss various challenges associated with FGFR targeting in lung cancer, including precision patient selection, toxicity and resistance. Finally, we provide perspectives on future directions, namely, developing novel FGFR-targeting drugs, such as FGFR degraders and more specific FGFR-TKIs, adopting combination therapy and targeting FGFs.

Background Triple-negative breast cancer (TNBC) remains the most challenging subtype of breast cancer and lacks definite treatment targets. Aerobic glycolysis is a hallmark of metabolic reprogramming that contributes to cancer progression. PFKP is a rate-limiting enzyme involved in aerobic glycolysis, which is overexpressed in various types of cancers. However, the underlying mechanisms and roles of the posttranslational modification of PFKP in TNBC remain unknown. Methods To explore whether PFKP protein has a potential role in the progression of TNBC, protein levels of PFKP in TNBC and normal breast tissues were examined by CPTAC database analysis, immunohistochemistry staining (IHC), and western blotting assay. Further CCK-8 assay, colony formation assay, EDU incorporation assay, and tumor xenograft experiments were used to detect the effect of PFKP on TNBC progression. To clarify the role of the USP5-PFKP pathway in TNBC progression, ubiquitin assay, co-immunoprecipitation (Co-IP), mass spectrometry-based protein identification, western blotting assay, immunofluorescence microscopy, in vitro binding assay, and glycolysis assay were conducted. Results Herein, we showed that PFKP protein was highly expressed in TNBC, which was associated with TNBC progression and poor prognosis of patients. In addition, we demonstrated that PFKP depletion significantly inhibited the TNBC progression in vitro and in vivo. Importantly, we identified that PFKP was a bona fide target of deubiquitinase USP5, and the USP5-mediated deubiquitination and stabilization of PFKP were essential for cancer cell aerobic glycolysis and TNBC progression. Moreover, we found a strong positive correlation between the expression of USP5 and PFKP in TNBC samples. Notably, the high expression of USP5 and PFKP was significantly correlated with poor clinical outcomes. Conclusions Our study established the USP5-PFKP axis as an important regulatory mechanism of TNBC progression and provided a rationale for future therapeutic interventions in the treatment of TNBC.

Purpose This paper aims to study the knowledge development and research dissemination on employee-centred CSR research through a social network approach by adopting bibliometric analysis. Design/methodology/approach By using the bibliometric data obtained from Scopus, descriptive analysis using social network analysis together with visualisation tool to examine the knowledge development and research dissemination on employee-centred CSR. The publications were identified by limiting search in Scopus database through keywords, namely, Corporate Social Responsibility, Employee and/or Internal Corporate Social Responsibility, from 2000 to 2018 in all document types and access type. The data were analysed by year, source of publication, author, country, affiliation, subject area and term analysis. Findings The findings reveal that the Journal of Business Ethics and Social Responsibility Journal are the two key journals publishing in employee-centred CSR. The USA and the UK are the two main countries that dominate the publication production. Most of the publications are in the area of business, management and accounting. Main publications are contributed by Andriukaitiene, R., Swaen, V. and Vveinhardt, J. The number of publication increases marginally from year to year. More focus linkages were established between employee-centred CSR with organisational commitment and firm performance in the late 2016. Research limitations/implications The analysis and findings are only limited to data retrieved from the Scopus database from year 2000 to 2018 on 31 December 2018. Besides, the selection of the quality criteria is based on researchers’ definition of suitable empirical basis. Practical implications The findings of this paper provide insights to the researchers on the development of CSR research has expanded to internal stakeholders. It also contributes by identifying the sources of research and its development trends in employee-centred CSR research. Social implications The findings provide a holistic picture of domino effects of CSR initiatives in organisational behaviour. It also further reinforces the awareness internal CSR being another important perspective of CSR. Originality/value The originality of this paper lies in its contribution in the bibliometric approach to study the dissemination trend of employee-centred CSR research from the Scopus database.

Current cancer immunotherapy predominately focuses on eliciting type 1 immune responses fighting cancer; however, long-term complete remission remains uncommon 1 , 2 . A pivotal question arises as to whether type 2 immunity can be orchestrated alongside type 1-centric immunotherapy to achieve enduring response against cancer 3 , 4 . Here we show that an interleukin-4 fusion protein (Fc–IL-4), a typical type 2 cytokine, directly acts on CD8 + T cells and enriches functional terminally exhausted CD8 + T (CD8 + T TE ) cells in the tumour. Consequently, Fc–IL-4 enhances antitumour efficacy of type 1 immunity-centric adoptive T cell transfer or immune checkpoint blockade therapies and induces durable remission across several syngeneic and xenograft tumour models. Mechanistically, we discovered that Fc–IL-4 signals through both signal transducer and activator of transcription 6 (STAT6) and mammalian target of rapamycin (mTOR) pathways, augmenting the glycolytic metabolism and the nicotinamide adenine dinucleotide (NAD) concentration of CD8 + T TE cells in a lactate dehydrogenase A-dependent manner. The metabolic modulation mediated by Fc–IL-4 is indispensable for reinvigorating intratumoural CD8 + T TE cells. These findings underscore Fc–IL-4 as a potent type 2 cytokine-based immunotherapy that synergizes effectively with type 1 immunity to elicit long-lasting responses against cancer. Our study not only sheds light on the synergy between these two types of immune responses, but also unveils an innovative strategy for advancing next-generation cancer immunotherapy by integrating type 2 immune factors. Fc–IL-4, a typical type 2 cytokine, reinvigorates exhausted CD8 + T cells in tumours, underscoring this fusion protein as a potent immunotherapy that synergizes effectively with type 1 immunity against cancer.

The COVID-19 pandemic forced higher education institutions to adopt e-learning systems to ensure continuous teaching and learning; however, this paradigm shift challenged students’ learning processes and is considered unsuitable for continuous use. Thus, a model was developed and experimentally verified in the current study to determine the factors that influence students’ uptaking of e-learning in the post-pandemic era. The Delphi method was employed to conceptualize the research framework, and structural equation modeling (SEM) was used to explore personality traits. The research model was then empirically tested by using data from 438 valid responses. The results showed that all personality traits, except for conscientiousness, significantly influenced the adoption of e-learning. The most decisive influencing trait was found to be extroversion (r = 0.756), whereas the trait that was found to have the most negligible impact was agreeableness (r = 0.305). Personal innovativeness and system usability were both found to highly correlate with a willingness to adopt e-learning. Except for the indirect effect of conscientiousness on the adoption of e-learning through system usability, all other personality traits were found to significantly mediate the adoption of e-learning through personal innovativeness and system usability. The results of this study could inspire stakeholders in the field of education, particularly e-learning platform designers, to consider students’ personality traits and individual differences in the design of e-learning platforms, with the goal of increasing students’ willingness and ability to adapt to these systems. The current study provides a contemporary perspective on the actions of e-learning users in the post-pandemic era.

Currently, social media is ubiquitous and essential for social networking and content sharing. It is an effective platform for teaching and learning in higher education and provides a novel way to communicate between instructors and pupils. Thus, the purpose of this study was to present a research framework to examine students’ motivation to adopt an e-learning system with social medial platforms. This cross-sectional study used the questionnaire to collect data from the students in Taiwan. A framework has examined students’ motivation to adopt an e-learning system with social medial platforms based on the modified technology acceptance model (TAM) and technology threat avoidance theory (TTAT). The research framework was evaluated by structural equation modeling (SEM) and represented by Smart-PLS. A total of 262 valid responses were used for statistical analysis. The results recommended modified research model explains 77.0% of the variance of motivation to adopt (R2 = 0.77). The findings also supported perceived usefulness, perceived ease of use, perceived cost, perceived effectiveness, and self-efficacy significantly influenced students’ motivation to use. Results also indicated threat appraisal, perceived susceptibility, and perceived severity are not significant factors for predicting students’ motivation to adopt e-learning in higher education.

PurposeThis research is set to assess the achievement of digital economy through digitalization adoption (DA) among Small Medium-sized Enterprises (SMEs). For more insightful findings, a comparison between the service-based and non-service-based industries was performed. Besides, it endeavours to identify the important and performing dimension of the Technology-Organization-Environment (TOE) framework. The purpose of this paper is to address these issues.Design/methodology/approachQuantitative approach through purposive sampling technique was used to collect data from the SMEs. Variance-based structural equation modeling was adopted to assess the model and multi-group analysis (MGA) was executed to examine the difference between the two classified industries. For the identification of the dimension, Importance-Performance Map Aanalysis (IPMA) was carried out.FindingsTechnology and organization recorded significant positive influence on digitalization adoption but not environment. Digitalization adoption between the two classified industries shows divergent results. IPMA concur the importance and performance of the technology and organization dimension, in which SMEs shall focus on for digitalization adoption.Research limitations/implicationsThis is cross sectional research and data were collected at a single time frame. Hence, the result is a state-or-art finding. Assuming that if there are changes in government policies, the results may differ. Besides, there are other possible groupings that could affect the results in which is not covered in the present research.Practical implicationsThe findings imply that the DA amongst SMEs has yet to achieve its full spectrum, which indicates Malaysia has yet to fully embrace digital economy. Nevertheless, DA is the fundamental for a successful digital economy.Social implicationsThis research provides the general public an overview that SMEs are adopting digitalization with various degree. This specifies that the society is paving towards digitalization with the SMEs actively adopting more digital technologies.Originality/valueThe novelty of this research arises from the utilization of the TOE framework to link to the achievement of the national digital economy. Additionally, current research adopted a rigorous approach to investigate the issue by using MGA, the hierarchical component model (HCM) and IPMA for holistic findings.

Acute kidney injury (AKI), as a common oxidative stress‐related renal disease, causes high mortality in clinics annually, and many other clinical diseases, including the pandemic COVID‐19, have a high potential to cause AKI, yet only rehydration, renal dialysis, and other supportive therapies are available for AKI in the clinics. Nanotechnology‐mediated antioxidant therapy represents a promising therapeutic strategy for AKI treatment. However, current enzyme‐mimicking nanoantioxidants show poor biocompatibility and biodegradability, as well as non‐specific ROS level regulation, further potentially causing deleterious adverse effects. Herein, the authors report a novel non‐enzymatic antioxidant strategy based on ultrathin Ti3C2‐PVP nanosheets (TPNS) with excellent biocompatibility and great chemical reactivity toward multiple ROS for AKI treatment. These TPNS nanosheets exhibit enzyme/ROS‐triggered biodegradability and broad‐spectrum ROS scavenging ability through the readily occurring redox reaction between Ti3C2 and various ROS, as verified by theoretical calculations. Furthermore, both in vivo and in vitro experiments demonstrate that TPNS can serve as efficient antioxidant platforms to scavenge the overexpressed ROS and subsequently suppress oxidative stress‐induced inflammatory response through inhibition of NF‐κB signal pathway for AKI treatment. This study highlights a new type of therapeutic agent, that is, the redox‐mediated non‐enzymatic antioxidant MXene nanoplatforms in treatment of AKI and other ROS‐associated diseases. A novel non‐enzymatic antioxidant MXene nanoplatform with excellent biocompatibility and great chemical reactivity toward multiple ROS is developed to potentially scavenge the overexpressed ROS and subsequently suppress oxidative stress‐induced inflammatory response through the inhibition of NF‐κB signaling pathway in the prevention and treatment of AKI and other ROS‐related diseases.