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https://www.selleckchem.com/products/a-674563.html ver tissues, and detected using immunohistochemistry. Ndufv2 was also upregulated after alcohol stimulation. Following Ndufv2 knockdown, collagen, TIMP-1, and α-SMA were downregulated compared with that in the controls. CONCLUSIONS A proteomic study was performed to discover proteins related to ALF in HSCs isolated from a rat model. Twenty-one differentially expressed proteins were identified, including proteins involved in mitochondrial metabolism and antigen presentation. Ndufv2, an upregulated protein in ALF, might be involved in ALF through regulating the production of fibrosis factors. PURPOSE Artificial Intelligence (AI) describes systems capable of making decisions of high cognitive complexity; Autonomous AI systems in healthcare are AI systems that make clinical decisions without human oversight. Ensuring that autonomous AI provides these benefits requires evaluation of the Autonomous AI's effect on patient outcome, design, validation, data usage and accountability, from a bioethics and accountability perspective. DESIGN Case study with literature review and bioethical analysis. METHODS Online library search for articles with AI and ethics as subject. Definition of terminology. Review of bioethical principles, and derivation of evaluation rules for Autonomous AI. Case study with an FDA de novo authorized Autonomous AI system. RESULTS Preliminary evaluation rules derived from bioethical principles include patient outcome, validation, reference standard, design, data usage, and accountability for medical liability. Application of the rules explains successful FDA de novo authorization. CONCLUSION Physicians need to become competent in understanding the limitations and risks as well as the potential benefits of autonomous AI, and understand its design, safety, efficacy and equity, validation, liability, and how its data was obtained. The Autonomous AI evaluation rules introduced here can support this process. P

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