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Children with Down syndrome (DS) and myeloid leukaemia have a significantly higher survival rate than other children, but they also experience considerable treatment-related toxicity. We analysed data on 56 children with DS who were treated on the Nordic Society for Paediatric Haematology and Oncology-acute myeloid leukaemia (NOPHO-AML)88 and NOPHO-AML93 protocols and reviewed the literature. In the dose-intensive NOPHO-AML88 protocol, 8 out of 15 patients (53%) experienced an event. In the less dose-intensive NOPHO-AML93 protocol, 7 out of 41 patients (17%) had an event. Therapy was reduced in 29 patients (52%) with in average 75% and 67% of the scheduled dose of anthracycline and cytarabine, respectively. Treatment-related death occurred in seven who all received full treatment. Relapse and resistant disease occurred at a similar rate in those receiving full and reduced treatment. Review of major series of myeloid leukaemia of DS showed no clear relationship between dose and survival; however, it appears that both a reduction in treatment dose and a less intensively timed treatment regimen improved the outcome. Further studies are needed to define the optimal regimen for treating myeloid leukaemia of DS. [ABSTRACT FROM AUTHOR]

Body area networks (BANs), cloud computing, and machine learning are platforms that can potentially enable advanced healthcare outside the hospital. By applying distributed sensors and drug delivery devices on/in our body and connecting to such communication and decision-making technology, a system for remote diagnostics and therapy is achieved with additional autoregulation capabilities. Challenges with such autarchic on-body healthcare schemes relate to integrity and safety, and interfacing and transduction of electronic signals into biochemical signals, and vice versa. Here, we report a BAN, comprising flexible on-body organic bioelectronic sensors and actuators utilizing two parallel pathways for communication and decision-making. Data, recorded from strain sensors detecting body motion, are both securely transferred to the cloud for machine learning and improved decision-making, and sent through the body using a secure body-coupled communication protocol to auto-actuate delivery of neurotransmitters, all within seconds. We conclude that both highly stable and accurate sensing—from multiple sensors—are needed to enable robust decision making and limit the frequency of retraining. The holistic platform resembles the self-regulatory properties of the nervous system, i.e., the ability to sense, communicate, decide, and react accordingly, thus operating as a digital nervous system. [ABSTRACT FROM AUTHOR]

Body area networks (BANs), cloud computing, and machine learning are platforms that can potentially enable advanced healthcare outside the hospital. By applying distributed sensors and drug delivery devices on/in our body and connecting to such communication and decision-making technology, a system for remote diagnostics and therapy is achieved with additional autoregulation capabilities. Challenges with such autarchic on-body healthcare schemes relate to integrity and safety, and interfacing and transduction of electronic signals into biochemical signals, and vice versa. Here, we report a BAN, comprising flexible on-body organic bioelectronic sensors and actuators utilizing two parallel pathways for communication and decision-making. Data, recorded from strain sensors detecting body motion, are both securely transferred to the cloud for machine learning and improved decision-making, and sent through the body using a secure body-coupled communication protocol to auto-actuate delivery of neurotransmitters, all within seconds. We conclude that both highly stable and accurate sensing—from multiple sensors—are needed to enable robust decision making and limit the frequency of retraining. The holistic platform resembles the self-regulatory properties of the nervous system, i.e., the ability to sense, communicate, decide, and react accordingly, thus operating as a digital nervous system. [ABSTRACT FROM AUTHOR]