"Extending the Technology Acceptance Model (TAM) to Predict University Students' Intentions to Use Metaverse-Based Learning Platforms"

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

Role of the Abcg2 transporter in plasma levels and tissue accumulation of the anti-inflammatory tolfenamic acid in mice

.The Breast Cancer Resistance Protein (BCRP/ABCG2) is an ATP-binding cassette efflux transporter that is expressed in the apical membrane of cells from relevant tissues involved in drug pharmacokinetics such as liver, intestine, kidney, testis, brain and mammary gland, among others. Tolfenamic acid is an anti-inflammatory drug used as an analgesic and antipyretic in humans and animals. Recently, tolfenamic acid has been repurposed as an antitumoral drug and for use in chronic human diseases such as Alzheimer. The aim of this work was to study whether tolfenamic acid is an in vitro Abcg2 substrate, and to investigate the potential role of Abcg2 in plasma exposure, secretion into milk and tissue accumulation of this drug. Using in vitro transepithelial assays with cells transduced with Abcg2, we showed that tolfenamic acid is an in vitro substrate of Abcg2. The in vivo effect of this transporter was tested using wild-type and Abcg2−/− mice, showing that after oral and intravenous administration of tolfenamic acid, its area under the plasma concentration-time curve in Abcg2−/− mice was between 1.7 and 1.8-fold higher compared to wild-type mice. Abcg2−/− mice also showed higher liver and testis accumulation of tolfenamic acid after intravenous administration. In this study, we demonstrate that tolfenamic acid is transported in vitro by Abcg2 and that its plasma levels as well as its tissue distribution are affected by Abcg2, with potential pharmacological and toxicological consequences.S

Mouse models of breast cancer metastasis

Metastatic spread of cancer cells is the main cause of death of breast cancer patients, and elucidation of the molecular mechanisms underlying this process is a major focus in cancer research. The identification of appropriate therapeutic targets and proof-of-concept experimentation involves an increasing number of experimental mouse models, including spontaneous and chemically induced carcinogenesis, tumor transplantation, and transgenic and/or knockout mice. Here we give a progress report on how mouse models have contributed to our understanding of the molecular processes underlying breast cancer metastasis and on how such experimentation can open new avenues to the development of innovative cancer therapy

Unlocking future learning: Exploring higher education students' intention to adopt meta-education.

Despite the potential of meta-education to transform higher education, there remains a scarcity of research investigating students' adoption intentions. This study aimed to identify factors influencing students' intentions to adopt meta-education using an extended Decomposed Theory of Planned Behavior model (DTPB). Data was collected via an online survey of 596 higher education students from Jordan who were purposefully selected. Structural equation modeling using partial least squares analysis revealed attitude, social influence, and perceived behavioral control as key antecedents of adoption intention. Furthermore, newly added variables including perceived enjoyment, herd behavior, student autonomy, and student innovativeness showed efficiency in explaining variance in attitude, social influence, and perceived behavioral control. Overall, the extended model provided meaningful insights on factors driving students' willingness to adopt meta-education. The study contributes to theory by extending the decomposed TPB model in the context of emerging educational technologies. It also provides practical implications for policymakers and educators aiming to encourage meta-education adoption