The influence of the gut microbiota on traumatic brain injury (TBI) is presently unknown. This knowledge gap is of paramount clinical significance as TBI patients are highly susceptible to alterations in the gut microbiota by antibiotic exposure. Antibiotic-induced gut microbial dysbiosis established prior to TBI significantly worsened neuronal loss and reduced microglia activation in the injured hippocampus with concomitant changes in fear memory response. Importantly, antibiotic exposure for 1 week after TBI reduced cortical infiltration of Ly6Chigh monocytes, increased microglial pro-inflammatory markers, and decreased T lymphocyte infiltration, which persisted through 1 month post-injury. Moreover, microbial dysbiosis was associated with reduced neurogenesis in the dentate gyrus 1 week after TBI. By 3 months after injury (11 weeks after discontinuation of the antibiotics), we observed increased microglial proliferation, increased hippocampal neuronal loss, and modulation of fear memory response. These data demonstrate that antibiotic-induced gut microbial dysbiosis after TBI impacts neuroinflammation, neurogenesis, and fear memory and implicate gut microbial modulation as a potential therapeutic intervention for TBI.

Abstract:The design of vibration energy harvesters (VEHs) is highly dependent upon the characteristics of the environmental vibrations present in the intended application. VEHs can be linear resonant systems tuned to particular frequencies or non-linear systems with either bi-stable operation or a Duffing-type response. This paper provides detailed vibration data from a range of applications, which has been made freely available for download through the Energy Harvesting Network's online data repository. In particular, this research shows that simulation is essential in designing and selecting the most suitable vibration energy harvester for particular applications. This is illustrated through C-based simulations of different types of VEHs, using real vibration data from a diesel ferry engine, a combined heat and power pump, a petrol car engine and a helicopter. The analysis shows that a bistable energy harvester only has a higher output power than a linear or Duffing-type nonlinear energy harvester with the same Q-factor when it is subjected to white noise vibration. The analysis also indicates that piezoelectric transduction mechanisms are more suitable for bistable energy harvesters than electromagnetic transduction. Furthermore, the linear energy harvester has a higher output power compared to the Duffing-type nonlinear energy harvester with the same Q factor in most cases. The Duffing-type nonlinear energy harvester can generate more power than the linear energy harvester only when it is excited at vibrations with multiple peaks and the frequencies of these peaks are within its bandwidth. Through these new observations, this paper illustrates the importance of simulation in the design of energy harvesting systems, with particular emphasis on the need to incorporate real vibration data. Keywords: Vibration energy harvesting, real vibration IntroductionEnergy harvesting (also known as energy scavenging) is the conversion of ambient energy present in the environment into electrical energy for the purpose of powering autonomous wireless electronics systems [1]. Kinetic energy harvesting involves the conversion of environmental vibrations and movements into electrical energy [2]. A kinetic energy harvester typically consists of a mechanical structure that couples the environmental kinetic energy to an electro-mechanical transducer that produces the electrical energy. Power conditioning electronics and some form of energy storage (e.g. battery or supercapacitor) are also normally required. In order to effectively couple the environmental kinetic energy to the transducer, the mechanical structure within the harvester must be carefully designed to match the characteristics of the environmental kinetic energy. A common approach is to match the resonant frequency of the harvester to a characteristic frequency present in the environmental vibrations. This means the optimum solution for harvesting vibration energy from an

Highlights d Longitudinal analysis of microbiota of Ghanaian infants receiving rotavirus vaccine d Streptococcus and Enterobacteriaceae taxa positively associate with RVV seroconversion d Enterovirus B, Cosavirus A, and phage richness negatively associate with RVV serostatus

Analysis of viral diversity using modern nucleic acid sequencing technologies presents several unique challenges. Foremost being that virus detection requires a non-targeted, random (shotgun) approach. This process collects sequences not only from the viral fraction of the sample, but also from other biological sources. Annotation and enumeration of collected sequences requires rigorous quality control, effective search strategies against relevant reference sequence databases and statistical and visualisation strategies to evaluate results. Here we introduce hecatomb, a bioinformatics platform enabling end-to-end virome sequence analysis. Hecatomb enables both read and contig based analysis and integrates query information from both amino acid and nucleotide reference sequence databases. Hecatomb prioritizes integration of data collected throughout the workflow as well as with external viral data sources. This process results in a rich, high-dimensional data which can be used by researchers to rigorously evaluate their results.

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