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Metaverse, which combines a number of information technologies, is the Internet of the future. A media for immersive learning, metaverse could set future educational trends and lead to significant reform in education. Although the metaverse has the potential to improve the effectiveness of online learning experiences, metaverse-based educational implementations are still in their infancy. Additionally, what factors impact higher education students’ adoption of the educational metaverse remains unclear. Consequently, the aim of this study is to explore the main factors that affect higher education students’ behavioral intentions to adopt metaverse technology for education. This study has proposed an extended Technology Acceptance Model (TAM) to achieve this aim. The novelty of this study resides in its conceptual model, which incorporates both technological, personal, and inhibiting/enabling factors. The empirical data were collected via online questionnaires from 574 students in both private and public universities in Jordan. Based on the PLS-SEM analysis, the study identifies perceived usefulness, personal innovativeness in IT, and perceived enjoyment as key enablers of students’ behavioral intentions to adopt the metaverse. Additionally, perceived cyber risk is found as the main inhibitor of students’ metaverse adoption intentions. Surprisingly, the effect of perceived ease of use on metaverse adoption intentions is found to be insignificant. Furthermore, it is found that self-efficacy, personal innovativeness, and perceived cyber risk are the main determinants of perceived usefulness and perceived ease of use. While the findings of this study contribute to the extension of the TAM model, the practical value of these findings is significant since they will help educational authorities understand each factor’s role and enable them to plan their future strategies.

In the last decade, it has been well-established that tumor-infiltrating myeloid cells fuel not only the process of carcinogenesis through cancer-related inflammation mechanisms, but also tumor progression, invasion, and metastasis. In particular, tumor-associated macrophages (TAMs) are the most abundant leucocyte subset in many cancers and play a major role in the creation of a protective niche for tumor cells. Their ability to generate an immune-suppressive environment is crucial to escape the immune system and to allow the tumor to proliferate and metastasize to distant sites. Conventional therapies, including chemotherapy and radiotherapy, are often not able to limit cancer growth due to the presence of pro-tumoral TAMs; these are also responsible for the failure of novel immunotherapies based on immune-checkpoint inhibition. Several novel therapeutic strategies have been implemented to deplete TAMs; however, more recent approaches aim to use TAMs themselves as weapons to fight cancer. Exploiting their functional plasticity, the reprogramming of TAMs aims to convert immunosuppressive and pro-tumoral macrophages into immunostimulatory and anti-tumor cytotoxic effector cells. This shift eventually leads to the reconstitution of a reactive immune landscape able to destroy the tumor. In this review, we summarize the current knowledge on strategies able to reprogram TAMs with single as well as combination therapies.

This present study aims to investigate factors that impact behavioural intention of university students on e-learning use during the COVID-19 pandemic. An online questionnaire was utilised to gather data from 109 students enrolled in one of the universities in Indonesia. The Technology Acceptance Model (TAM) was the primary framework employed for analysis, in which system quality and e-learning experience were included as external constructs to seek out a much better model to improve the understanding of students’ intention to adopt e-learning. An extended TAM model was developed and tested in this study. The model consists of six constructs: system quality, e-learning experience, perceived ease of use, perceived usefulness, attitude toward use, and behavioural intention. Structural Equation Modelling (SEM) and SMART PLS 3.0 software were applied for data analysis. The findings informed that the proposed model has been successfully explained factors university students use of e-learning during the pandemic in Indonesia. It suggested that attitude toward e-learning use was the most prominent construct to predict university students’ behavioural intention to use e-learning during the pandemic. Finally, this study offers recommendations for future research and practices.

Cancer stem cells (CSCs) have emerged as key contributors to tumor initiation, growth, and metastasis. In addition, CSCs play a significant role in inducing immune evasion, thereby compromising the effectiveness of cancer treatments. The reciprocal communication between CSCs and the tumor microenvironment (TME) is observed, with the TME providing a supportive niche for CSC survival and self-renewal, while CSCs, in turn, influence the polarization and persistence of the TME, promoting an immunosuppressive state. Consequently, these interactions hinder the efficacy of current cancer therapies, necessitating the exploration of novel therapeutic approaches to modulate the TME and target CSCs. In this review, we highlight the intricate strategies employed by CSCs to evade immune surveillance and develop resistance to therapies. Furthermore, we examine the dynamic interplay between CSCs and the TME, shedding light on how this interaction impacts cancer progression. Moreover, we provide an overview of advanced therapeutic strategies that specifically target CSCs and the TME, which hold promise for future clinical and translational studies in cancer treatment.

The rapid and continuing acceleration of digital transformation in education, propelled by the COVID-19 pandemic, has underscored the urgent need to examine how teachers adapt to and integrate digital tools in their teaching practices. Anchored in the Technology Acceptance Model (TAM) as its theoretical framework, this study uniquely uses a longitudinal design to trace the evolving patterns of technology acceptance and integration among teachers. Through qualitative methodology, involving three series of interviews with 13 secondary school teachers over two years, we identify their evolving interactions with digital tools. Our analysis reveals a cyclical pattern of technology acceptance and use across time, characterized by initial rapid adaptation to digital tools, subsequent periods of reflection and skill acquisition, and varied levels of sustained integration or reassessment. Based on our findings we propose an adapted, cyclical TAM framework and highlight the critical role of ongoing support, professional development, and infrastructure improvements, arguing for comprehensive support systems and adequate time for educators to progress through different stages of digital tool integration. We conclude that a deep understanding and support of these cycles are essential for empowering teachers to lead the digital transformation in education effectively.

Idiopathic pulmonary fibrosis (IPF) is characterized by aberrant lung remodeling, which progressively abolishes lung function in an RTK (receptor tyrosine kinase)-dependent manner. Gas6 (growth arrest-specific 6) ligand, Tyro3 (TYRO3 protein tyrosine kinase 3), and Axl (anexelekto) RTK expression and activity are increased in IPF. To determine if targeting these RTK pathways would inhibit fibroblast activation and the development of pulmonary fibrosis. Quantitative genomic, proteomic, and functional analyses were used to determine Gas6/TAM (Tyro3, Axl, and Mertk [MER proto-oncogene, tyrosine kinase]) RTK expression and activation in tissues and fibroblasts from normal and IPF lungs. The profibrotic impact of these RTK pathways were also examined in bleomycin-induced pulmonary fibrosis and in SCID/Bg mice that developed pulmonary fibrosis after the intravenous administration of primary IPF fibroblasts. Gas6, Axl, and Tyro3 were increased in both rapidly and slowly progressive IPF compared with normal lung samples and fibroblasts. Targeting these pathways with either specific antibodies directed at Gas6 or Axl, or with small-molecule TAM inhibitors indicated that the small molecule-mediated targeting approach was more efficacious in both in vitro and in vivo studies. Specifically, the TAM receptor inhibitor R428 (also known as BGB324) significantly inhibited the synthetic, migratory, and proliferative properties of IPF fibroblasts compared with the other Gas6/TAM receptor targeting agents. Finally, loss of Gas6 expression decreased lung fibrotic responses to bleomycin and treatment with R428 inhibited pulmonary fibrosis in humanized SCID/Bg mice. Gas6/TAM receptor activity contributes to the activation of pulmonary fibroblasts in IPF, suggesting that targeting this RTK pathway might be an effective antifibrotic strategy in this disease.