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Cancer development in hepatocytes by long-term induction of hypoxic hepatocellular carcinoma cell (HCC)-derived exosomes in vivo and in vitro
Get PDFHypoxic tumor cell-derived exosomes play a key role in the occurrence, development, and metastasis of tumors. However, the mechanism of hypoxia-mediated metastasis remains unclear. In this study, hypoxic hepatocellular carcinoma cell (HCC-LM3)-derived exosomes (H-LM3-exos) were used to induce hepatocytes (HL-7702) over a long term (40 passages in 120 days). A nude mouse experiment further verified the effect of H-LM3-exos on tumor growth and metastasis. The process of cancer development in hepatocytes induced by H-LM3-exos was analyzed using both biological and physical techniques, and the results showed that the proliferation and soft agar growth abilities of the transformed cells were enhanced. The concentration of tumor markers secreted by transformed cells was increased, the cytoskeleton was disordered, and the migration ability was enhanced and was accompanied by epithelial−mesenchymal transition (EMT). Transcriptome results showed that differentially expressed genes between transformed cells and hepatocytes were enriched in cancer-related signaling pathways. The degree of cancer development in transformed cells was enhanced by an increase in H-LM3-exos-induced passages. Nude mice treated with different concentrations of H-LM3-exos showed different degrees of tumor growth and liver lesions. The physical properties of the cells were characterized by atomic force microscopy. Compared with the hepatocytes, the height and roughness of the transformed cells were increased, while the adhesion and elastic modulus were decreased. The changes in physical properties of primary tumor cells and hepatocytes in nude mice were consistent with this trend. Our study linking omics with the physical properties of cells provides a new direction for studying the mechanisms of cancer development and metastasis
Practitioner briefing: factors that influence outcomes when supporting the participation rights of children and young people with lived experience of child sexual abuse and exploitation.
Get PDFThe findings from this study illustrated that there are many factors to consider that may influence and determine the outcomes associated with the participation of young survivors of child sexual abuse and exploitation. Five key messages were identified: * Good quality ethical standards are critical * Young people must be supported to develop the knowledge and skills they need to engage and influence * Everyone is an individual * Facilitators and other professionals involved in participatory projects and activities have a central role to play in ensuring standards are maintained and risks are mitigated * Structural barriers at various levels may limit the influence of young survivors’ participatio
How does social media affect artists’ working methodology and flow?: an exploration of a hypothetical model of iterative feedback
No full textA multimodal parallelism approach for improving parallel CNN computation in deep learning
No full textStudent dual identification and advocacy for cobranded higher education: a study of UK academic partnerships
No full textQuantum mechanism-based convolution model for the classification of pathogenic bacteria
Get PDFWater, especially drinking water, should be clean and free of disease-causing bacteria because of its critical role in life. However, it isn’t easy to identify and classify them rapidly at an early stage. Primarily, the examination of water is performed manually to check the contamination level. Some researchers have proposed techniques to detect and classify bacteria images, but this field still needs more attention. In this research work, a robust Quantum Convolutional Neural Network (QCNN) classification model is proposed to classify the six major categories of pathogenic bacteria. For the acquisition of pathogen images, different slides are created through the gram-staining process, and then images are captured from those slides. DIBaS is the publicly available dataset that provides these slides captured through gram-staining, which is used to evaluate the proposed methodology. So, in the first step, database preprocessing, small patches are extracted from slide images. However, the extracted patches were not clear and very useful, so the Enhanced Super-Resolution Generative Adversarial Network Model (ESRGAN) was applied to images to improve the image quality of extracted patches. The third step is to extract the deep features and classify bacterial images using the QCNN model, in which the Quantum Convolutional layer is added, and classical data is converted into quantum data to perform classification. Based on the results of classification experiments using the QCNN model, the accuracy is 96.54%.<br/
Guest editorial:autonomous networks: opportunities, challenges, and applications
No full textResearchers and standardization bodies have been paying increasing attention to the network management automation issue in 5G systems. Autonomous solutions for managing network resources are required in the present era of flexible and dynamic cloud-based settings. Operators strive for efficiency by optimizing network resources. The next step in network evolution, which can go beyond automation capabilities, is autonomousness
“So what if ChatGPT wrote it?” multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy
Get PDFTransformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts
A systematic review of Positive Psychology Interventions (PPIs) to improve the health behaviours, psychological wellbeing and/or physical health of police staff
Get PDFObjective: This review aimed to assess the use of Positive Psychology Interventions (PPIs), such as using positive mantras, expressive writing, or gratitude diaries, to improve the health behaviours, psychological wellbeing, and/or physical health of police staff. Method: The review was registered on PROSPERO before 16 electronic databases were searched for published articles between January 1999 and February 2022. Included studies offered PPIs to improve the physical health (body mass index, blood pressure), psychological well-being (stress, anxiety, mood, emotion, depression, self-efficacy), or health behaviours (physical activity, sitting times, dietary habits, alcohol, or tobacco use) of police staff. The mixed methods appraisal tool (MMAT) l was used to assess the risk of bias of included papers. Results: The initial search yielded 4,560 results; with 3,385 papers remaining after duplicates were removed. Of these, 15 studies were included in the final review. Intervention types included mindfulness-based resilience training (n = 11), physical or wellness practice classes (n = 1), role-play and scenario-based interventions (n = 2) and expressive writing (n = 1). Mindfulness-based interventions improved many psychological wellbeing facets such as anxiety, depression, negative affect, and quality of life. Limited improvements were observed for some health behaviours such as alcohol consumption and in self-reported general health. Expressive writing and role-play-based interventions were effective in reducing stress and anxiety, however, improvement in depression scores were inconsistent across studies. Conclusion: Positive Psychology Interventions are promising to support the health and wellbeing of police staff. Future research would benefit from investigating their mechanisms of action
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