Acute kidney injury (AKI) is a common and potential life-threatening disease in patients admitted to hospital, affecting 10%–15% of all hospitalizations and around 50% of patients in the intensive care unit. Severe, recurrent, and uncontrolled AKI may progress to chronic kidney disease or end-stage renal disease. AKI thus requires more efficient, specific therapies, rather than just supportive therapy. Mesenchymal stem cells (MSCs) are considered to be promising cells for cellular therapy because of their ease of harvesting, low immunogenicity, and ability to expand in vitro. Recent research indicated that the main therapeutic effects of MSCs were mediated by MSC-derived extracellular vesicles (MSC-EVs). Furthermore, compared with MSCs, MSC-EVs have lower immunogenicity, easier storage, no tumorigenesis, and the potential to be artificially modified. We reviewed the therapeutic mechanism of MSCs and MSC-EVs in AKI, and considered recent research on how to improve the efficacy of MSC-EVs in AKI. We also summarized and analyzed the potential and limitations of EVs for the treatment of AKI to provide ideas for future clinical trials and the clinical application of MSC-EVs in AKI.
In this editorial, we comment on the current development and deployment of data science in intensive care units (ICUs). Data in ICUs can be classified into qualitative and quantitative data with different technologies needed to translate and interpret them. Data science, in the form of artificial intelligence (AI), should find the right interaction between physicians, data and algorithm. For individual patients and physicians, sepsis and mechanical ventilation have been two important aspects where AI has been extensively studied. However, major risks of bias, lack of generalizability and poor clinical values remain. AI deployment in the ICUs should be emphasized more to facilitate AI development. For ICU management, AI has a huge potential in transforming resource allocation. The coronavirus disease 2019 pandemic has given opportunities to establish such systems which should be investigated further. Ethical concerns must be addressed when designing such AI.
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