Liver and kidney injury caused by drug toxicity is a serious threat to human health. Acetaminophenol (APAP), as a common antipyretic and analgesic drug, inevitably causes injury. When it is overused, hypochlorous acid (HClO) is excessively generated due to metabolic abnormalities, resulting in the accumulation of HClO in the mitochondria of liver and kidney tissues and causing damage. In this study, we designed a series of HClO responsive ratiometric chemdosimeter NRH-X (NRH-O, NRH-S, and NRH-C) to evaluate liver and kidney injury, and found that NRH-O has a specific sensitive response to HClO. NRH-O can not only monitor the variations of endogenous HClO content of living cells by fluorescence ratio changes in the mitochondria but also detect the upregulation of HClO induced by APAP. In addition, NRH-O can also be used for anatomic diagnosis of liver and kidney injury by fluorescence ratio imaging of HClO in the tissues of inflammatory mice.

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In this manuscript, we report a mitochondria-targeted near-infrared ratiometric nanoprobe NRH800-PEG for detecting HClO in the mitochondria of living cells and tissues of drug-damaged liver and kidneys.

Medical care is a guarantee of people's daily life. Improving healthcare contributes to people's well-being. However, healthcare resources are characterized by uneven distribution. Financially well-off areas will have higher quality health care resources. Most of the medical resources are concentrated in public general hospitals, however, primary care institutions can hardly meet the growing needs of people. To solve this problem, Medical Union achieves efficient deployment of resources by integrating various medical institutions in the same area. In the process of logistics integration of the medical union, the scale of logistics distribution expands accordingly. Transportation vehicles have high operating costs and produce greenhouse gases in the process of distribution. The optimization of the driving path of logistics distribution vehicles can reduce the operating cost, fuel consumption and carbon emission. To solve this kind of decentralized and complex vehicle routing problem, this paper proposes a pollution routing problem model considering electrical vehicle usage, customer's soft time window expectation, open path and carbon cost. A modified Differential Search Algorithm with the comprehensive learning strategy and dynamic Cauchy variation strategy is advanced to solve the problem. Results show that the improved algorithm has good solving performance, and verifies the rationality of the proposed model, which will help to reduce carbon emissions and save the logistics and operating costs of medical devices.