The My Active and Healthy Aging (My-AHA) ICT platform to detect and prevent frailty in older adults: Randomized control trial design and protocol

[EN] Introduction Frailty increases the risk of poor health outcomes, disability, hospitalization, and death in older adults and affects 7%¿12% of the aging population. Secondary impacts of frailty on psychological health and socialization are significant negative contributors to poor outcomes for frail older adults. Method The My Active and Healthy Aging (My-AHA) consortium has developed an information and communications technology¿based platform to support active and healthy aging through early detection of prefrailty and provision of individually tailored interventions, targeting multidomain risks for frailty across physical activity, cognitive activity, diet and nutrition, sleep, and psychosocial activities. Six hundred adults aged 60 years and older will be recruited to participate in a multinational, multisite 18-month randomized controlled trial to test the efficacy of the My-AHA platform to detect prefrailty and the efficacy of individually tailored interventions to prevent development of clinical frailty in this cohort. A total of 10 centers from Italy, Germany, Austria, Spain, United Kingdom, Belgium, Sweden, Japan, South Korea, and Australia will participate in the randomized controlled trial. Results Pilot testing (Alpha Wave) of the My-AHA platform and all ancillary systems has been completed with a small group of older adults in Europe with the full randomized controlled trial scheduled to commence in 2018. Discussion The My-AHA study will expand the understanding of antecedent risk factors for clinical frailty so as to deliver targeted interventions to adults with prefrailty. Through the use of an information and communications technology platform that can connect with multiple devices within the older adult's own home, the My-AHA platform is designed to measure an individual's risk factors for frailty across multiple domains and then deliver personalized domain-specific interventions to the individual. The My-AHA platform is technology-agnostic, enabling the integration of new devices and sensor platforms as they emerge.This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 689582 and the Australian National Health and Medical Research Council (NHRMC) European Union grant scheme (1115818). M.J.S. reports personal fees from Eli Lilly (Australia) Pty Ltd and grants from Novotech Pty Ltd, outside the submitted work. All other authors report nothing to disclose.Summers, MJ.; Rainero, I.; Vercelli, AE.; Aumayr, GA.; De Rosario Martínez, H.; Mönter, M.; Kawashima, R. (2018). 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Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome

Microbial communities carry out the majority of the biochemical activity on the planet, and they play integral roles in processes including metabolism and immune homeostasis in the human microbiome. Shotgun sequencing of such communities' metagenomes provides information complementary to organismal abundances from taxonomic markers, but the resulting data typically comprise short reads from hundreds of different organisms and are at best challenging to assemble comparably to single-organism genomes. Here, we describe an alternative approach to infer the functional and metabolic potential of a microbial community metagenome. We determined the gene families and pathways present or absent within a community, as well as their relative abundances, directly from short sequence reads. We validated this methodology using a collection of synthetic metagenomes, recovering the presence and abundance both of large pathways and of small functional modules with high accuracy. We subsequently applied this method, HUMAnN, to the microbial communities of 649 metagenomes drawn from seven primary body sites on 102 individuals as part of the Human Microbiome Project (HMP). This provided a means to compare functional diversity and organismal ecology in the human microbiome, and we determined a core of 24 ubiquitously present modules. Core pathways were often implemented by different enzyme families within different body sites, and 168 functional modules and 196 metabolic pathways varied in metagenomic abundance specifically to one or more niches within the microbiome. These included glycosaminoglycan degradation in the gut, as well as phosphate and amino acid transport linked to host phenotype (vaginal pH) in the posterior fornix. An implementation of our methodology is available at http://huttenhower.sph.harvard.edu/human​n. This provides a means to accurately and efficiently characterize microbial metabolic pathways and functional modules directly from high-throughput sequencing reads, enabling the determination of community roles in the HMP cohort and in future metagenomic studies.National Institutes of Health (U.S.) (U54HG004968

Lactobacillaceae and Cell Adhesion: Genomic and Functional Screening

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Single molecule evaluation of fluorescent protein photoactivation efficiency using an in vivo nanotemplate

Photoswitchable fluorescent probes are central to localization-based super-resolution microscopy. Among these probes, fluorescent proteins are appealing because they are genetically encoded. Moreover, the ability to achieve a 1:1 labeling ratio between the fluorescent protein and the protein of interest makes these probes attractive for quantitative single-molecule counting. The percentage of fluorescent protein that is photoactivated into a fluorescently detectable form (i.e., the photoactivation efficiency) plays a crucial part in properly interpreting the quantitative information. It is important to characterize the photoactivation efficiency at the single-molecule level under the conditions used in super-resolution imaging. Here, we used the human glycine receptor expressed in Xenopus oocytes and stepwise photobleaching or single-molecule counting photoactivated localization microcopy (PALM) to determine the photoactivation efficiency of fluorescent proteins mEos2, mEos3.1, mEos3.2, Dendra2, mClavGR2, mMaple, PA-GFP and PA-mCherry. This analysis provides important information that must be considered when using these fluorescent proteins in quantitative super-resolution microscopy.Peer ReviewedPostprint (author's final draft