Browsing by Author "Cui X"

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    Allogeneic mesenchymal stromal cells for cartilage regeneration: A review of in vitro evaluation, clinical experience, and translational opportunities
    (Wiley Periodicals LLC on behalf of AlphaMed Press, 2021-11) Aldrich ED; Cui X; Murphy CA; Lim KS; Hooper GJ; McIlwraith CW; Woodfield TBF
    The paracrine signaling, immunogenic properties and possible applications of mesenchymal stromal cells (MSCs) for cartilage tissue engineering and regenerative medicine therapies have been investigated through numerous in vitro, animal model and clinical studies. The emerging knowledge largely supports the concept of MSCs as signaling and modulatory cells, exerting their influence through trophic and immune mediation rather than as a cell replacement therapy. The virtues of allogeneic cells as a ready-to-use product with well-defined characteristics of cell surface marker expression, proliferative ability, and differentiation capacity are well established. With clinical applications in mind, a greater focus on allogeneic cell sources is evident, and this review summarizes the latest published and upcoming clinical trials focused on cartilage regeneration adopting allogeneic and autologous cell sources. Moreover, we review the current understanding of immune modulatory mechanisms and the role of trophic factors in articular chondrocyte-MSC interactions that offer feasible targets for evaluating MSC activity in vivo within the intra-articular environment. Furthermore, bringing labeling and tracking techniques to the clinical setting, while inherently challenging, will be extremely informative as clinicians and researchers seek to bolster the case for the safety and efficacy of allogeneic MSCs. We therefore review multiple promising approaches for cell tracking and labeling, including both chimerism studies and imaging-based techniques, that have been widely explored in vitro and in animal models. Understanding the distribution and persistence of transplanted MSCs is necessary to fully realize their potential in cartilage regeneration techniques and tissue engineering applications.
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    The Application of Artificial Intelligence and Big Data in the Food Industry
    (MDPI (Basel, Switzerland), 2023-12-18) Ding H; Tian J; Yu W; Wilson DI; Young BR; Cui X; Xin X; Wang Z; Li W; Yılmaz MT
    Over the past few decades, the food industry has undergone revolutionary changes due to the impacts of globalization, technological advancements, and ever-evolving consumer demands. Artificial intelligence (AI) and big data have become pivotal in strengthening food safety, production, and marketing. With the continuous evolution of AI technology and big data analytics, the food industry is poised to embrace further changes and developmental opportunities. An increasing number of food enterprises will leverage AI and big data to enhance product quality, meet consumer needs, and propel the industry toward a more intelligent and sustainable future. This review delves into the applications of AI and big data in the food sector, examining their impacts on production, quality, safety, risk management, and consumer insights. Furthermore, the advent of Industry 4.0 applied to the food industry has brought to the fore technologies such as smart agriculture, robotic farming, drones, 3D printing, and digital twins; the food industry also faces challenges in smart production and sustainable development going forward. This review articulates the current state of AI and big data applications in the food industry, analyses the challenges encountered, and discusses viable solutions. Lastly, it outlines the future development trends in the food industry.