A digital nervous system aiming toward personalized IoT healthcare.

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.

Human exposome assessment platform.

The Human Exposome Assessment Platform (HEAP) is a research resource for the integrated and efficient management and analysis of human exposome data. The project will provide the complete workflow for obtaining exposome actionable knowledge from population-based cohorts. HEAP is a state-of-the-science service composed of computational resources from partner institutions, accessed through a software framework that provides the world's fastest Hadoop platform for data warehousing and applied artificial intelligence (AI). The software, will provide a decision support system for researchers and policymakers. All the data managed and processed by HEAP, together with the analysis pipelines, will be available for future research. In addition, the platform enables adding new data and analysis pipelines. HEAP's final product can be deployed in multiple instances to create a network of shareable and reusable knowledge on the impact of exposures on public health.

The effect of ultrasound probe orientation on muscle architecture measurement.

The purpose of this paper was to examine how muscle architecture parameter (MAP) measurements made using brightness-mode ultrasonography (BMU) differ based on probe orientation. The human tibialis anterior muscle was imaged from nine different probe orientations during concentric contractions at four joint angles to determine the effect of probe orientation on the measurement of muscle architecture parameters. Ankle dorsi-flexion torque, tibialis anterior electromyography (EMG), and measures of MAP including fascicle length (FL), pennation angle (PA) and muscle thickness (MT) were collected. Statistically significant differences were found between joint angles for measures of FL and PA and between probe orientations for measures of FL and MT. A comparison of actual MAP values to a geometric model used by researchers to determine an ideal probe orientation show that the actual values vary to a greater extent and do not follow the trend predicted by the model. The results suggest that ultrasound probe orientation affects measures of MAP but the effect either cannot be predicted from a geometric model and/or the error in the measurement technique does not allow a comparison.

E-Science technologies in a workflow for personalized medicine using cancer screening as a case study.

OBJECTIVE: We provide an e-Science perspective on the workflow from risk factor discovery and classification of disease to evaluation of personalized intervention programs. As case studies, we use personalized prostate and breast cancer screenings. MATERIALS AND METHODS: We describe an e-Science initiative in Sweden, e-Science for Cancer Prevention and Control (eCPC), which supports biomarker discovery and offers decision support for personalized intervention strategies. The generic eCPC contribution is a workflow with 4 nodes applied iteratively, and the concept of e-Science signifies systematic use of tools from the mathematical, statistical, data, and computer sciences. RESULTS: The eCPC workflow is illustrated through 2 case studies. For prostate cancer, an in-house personalized screening tool, the Stockholm-3 model (S3M), is presented as an alternative to prostate-specific antigen testing alone. S3M is evaluated in a trial setting and plans for rollout in the population are discussed. For breast cancer, new biomarkers based on breast density and molecular profiles are developed and the US multicenter Women Informed to Screen Depending on Measures (WISDOM) trial is referred to for evaluation. While current eCPC data management uses a traditional data warehouse model, we discuss eCPC-developed features of a coherent data integration platform. DISCUSSION AND CONCLUSION: E-Science tools are a key part of an evidence-based process for personalized medicine. This paper provides a structured workflow from data and models to evaluation of new personalized intervention strategies. The importance of multidisciplinary collaboration is emphasized. Importantly, the generic concepts of the suggested eCPC workflow are transferrable to other disease domains, although each disease will require tailored solutions.

Expanding the clinical, pathological and MRI phenotype of DNM2-related centronuclear myopathy.

Mutations in dynamin-2 (DNM2) cause autosomal dominant centronuclear myopathy (CNM). We report a series of 12 patients from eight families with CNM in whom we have identified a number of novel features that expand the reported clinicopathological phenotype. We identified two novel and five recurrent missense mutations in DNM2. Early clues to the diagnosis include relative weakness of neck flexors, external ophthalmoplegia and ptosis, although these are not present in all patients. Pes cavus was present in two patients, and in another two members of one family there was mild slowing of nerve conduction velocities. Whole-body MRI examination in two children and one adult revealed a similar pattern of involvement of selective muscles in head (lateral pterygoids), neck (extensors), trunk (paraspinal) and upper limbs (deep muscles of forearm). Findings in lower limbs and pelvic region were similar to that previously reported in adults with DNM2 mutations. Two patients presented with dystrophic changes as the predominant pathological feature on muscle biopsies; one of whom had a moderately raised creatine kinase, and both patients were initially diagnosed as congenital muscular dystrophy. DNM2 mutation analysis should be considered in patients with a suggestive clinical phenotype despite atypical histopathology, and MRI findings can be used to guide genetic testing. Subtle neuropathic features in some patients suggest an overlap with the DNM2 neuropathy phenotype. Missense mutations in the C-terminal region of the PH domain appear to be associated with a more severe clinical phenotype evident from infancy.