ObjectiveThe impact of faecal microbiota transplantation (FMT) on microbiota engraftment in patients with metabolic syndrome is uncertain. We aimed to study whether combining FMT with lifestyle modification could enhance the engraftment of favourable microbiota in obese patients with type 2 diabetes mellitus (T2DM).DesignIn this double-blind, randomised, placebo-controlled trial, 61 obese subjects with T2DM were randomly assigned to three parallel groups: FMT plus lifestyle intervention (LSI), FMT alone, or sham transplantation plus LSI every 4 weeks for up to week 12. FMT solution was prepared from six healthy lean donors. Faecal metagenomic sequencing was performed at baseline, weeks 4, 16 and 24. The primary outcome was the proportion of subjects acquiring ≥20% of microbiota from lean donors at week 24.ResultsProportions of subjects acquiring ≥20% of lean-associated microbiota at week 24 were 100%, 88.2% and 22% in the FMT plus LSI, FMT alone, and sham plus LSI groups, respectively (p<0.0001). Repeated FMTs significantly increased the engraftment of lean-associated microbiota (p<0.05). FMT with or without LSI increased butyrate-producing bacteria. Combining LSI and FMT led to increase in Bifidobacterium and Lactobacillus compared with FMT alone (p<0.05). FMT plus LSI group had reduced total and low-density lipoprotein cholesterol and liver stiffness at week 24 compared with baseline (p<0.05).ConclusionRepeated FMTs enhance the level and duration of microbiota engraftment in obese patients with T2DM. Combining lifestyle intervention with FMT led to more favourable changes in recipients’ microbiota and improvement in lipid profile and liver stiffness.Trial registration numberNCT03127696.

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Abstract-Routing plays an important role in the overall architecture of the Internet of Things. IETF has standardized the RPL routing protocol to provide the interoperability for Low-Power and Lossy Networks (LLNs). LLNs cover a wide scope of applications, such as building automation, industrial control, healthcare and so on. LLNs applications require reliable and energyefficient routing support. Point-to-point (P2P) communication is a fundamental requirement of many LLNs applications. However, traditional routing protocols usually propagate throughout the whole network to discover a reliable P2P route, which requires large amount energy consumption. Again, it is challenging to achieve both reliability and energy-efficiency simultaneously, especially for LLNs. In this paper, we propose a novel energyefficient region-based routing protocol, called ER-RPL, which achieves energy-efficient data delivery without compromising reliability. In contrast of traditional routing protocols where all nodes are required for route discovery, the proposed scheme only requires a subset of nodes to do the job, which is the key of energy saving. Our theoretical analysis and extensive simulation studies demonstrate that ER-RPL has a great performance superiority over two conventional benchmark protocols, i.e., RPL and P2P-RPL.

Abstract-The space and time dynamics of moving vehicles regulated by traffic signals governs the node connectivity and communication capability of vehicular ad hoc networks (VANETs) in urban environments. However, none of the previous studies on node connectivity has considered such dynamics with the presence of traffic lights and vehicle interactions. In fact, most of them assume that vehicles are distributed homogeneously throughout the geographic area, which is unrealistic. We introduce in this paper a stochastic traffic model for VANETs in signalized urban road systems. The proposed model is a composite of the fluid model and stochastic model. The former characterizes the general flow and evolution of the traffic stream so that the average density of vehicles is readily computable, while the latter takes into account the random behavior of individual vehicles. As the key contribution of this paper, we attempt to approximate vehicle interactions and capture platoon formations and dissipations at traffic signals through a density-dependent velocity profile. The stochastic traffic model with approximation of vehicle interactions is evaluated with extensive simulations, and the distributional result of the model is validated against real-world empirical data in London. In general, we show that the fluid model can adequately describe the mean behavior of the traffic stream, while the stochastic model can approximate the probability distribution well even when vehicles interact with each other as their movement is controlled by traffic lights. With the knowledge of the mean vehicular density dynamics and its probability distribution from the stochastic traffic model, we determine the degree of connectivity in the communication network and illustrate that system engineering and planning for optimizing both the transport (in terms of congestion) and communication networks (in terms of connectivity) can be carried out with the proposed model. Index Terms-Connectivity, signalized road system, stochastic traffic model, vehicle interaction, vehicular ad hoc network (VANET).

In a Vehicular Ad-hoc Network (VANET), the performance of the communication protocol is influenced heavily by the vehicular density dynamics. However, most of the previous works on VANET performance modeling paid little attention to vehicle distribution, or simply assumed homogeneous car distribution. It is obvious that vehicles are distributed non-homogeneously along a road segment due to traffic signals and speed limits at different portions of the road, as well as vehicle interactions that are significant on busy streets. In light of the inadequacy, we present in this paper an original methodology to study the broadcasting performance of 802.11p VANETs with practical vehicle distribution in urban environments. Firstly, we adopt the empirically verified stochastic traffic models, which incorporates the effect of urban settings (such as traffic lights and vehicle interactions) on car distribution and generates practical vehicular density profiles. Corresponding 802.11p protocol and performance models are then developed. When coupled with the traffic models, they can predict broadcasting efficiency, delay, as well as throughput performance of 802.11p VANETs based on the knowledge of car density at each location on the road. Extensive simulation is conducted to verify the accuracy of the developed mathematical models with the consideration of vehicle interaction. In general, our results demonstrate the applicability of the proposed methodology on modeling protocol performance in practical signalized road networks, and shed insights into the design and development of future communication protocols and networking functions for VANETs.