Low intensity shockwave treatment modulates macrophage functions beneficial to healing chronic wounds

Acknowledgments: We acknowledge the University of Aberdeen Microscopy and Histology Facility and the qPCR facility for use of facilities and advice. We acknowledge Ehab Husain for scoring the patient wound biopsies. Funding: This research was funded by NHS Grampian Endowments, grant number 17/004 and by personal funding from JSH.Peer reviewedPublisher PD

Differential Effects of Thiopeptide and Orthosomycin Antibiotics on Translational GTPases

SummaryThe ribosome is a major target in the bacterial cell for antibiotics. Here, we dissect the effects that the thiopeptide antibiotics thiostrepton (ThS) and micrococcin (MiC) as well as the orthosomycin antibiotic evernimicin (Evn) have on translational GTPases. We demonstrate that, like ThS, MiC is a translocation inhibitor, and that the activation by MiC of the ribosome-dependent GTPase activity of EF-G is dependent on the presence of the ribosomal proteins L7/L12 as well as the G′ subdomain of EF-G. In contrast, Evn does not inhibit translocation but is a potent inhibitor of back-translocation as well as IF2-dependent 70S-initiation complex formation. Collectively, these results shed insight not only into fundamental aspects of translation but also into the unappreciated specificities of these classes of translational inhibitors

Adaptative computerized cognitive training decreases mental workload during working memory precision task. A preliminary fNIRS study.

With the growing concern for the health of ageing populations, much research continues to look at the impact of cognitive training, particularly in relation to cognitive decline. We sought to use novel techniques, including augmented reality and portable neurotechnology, to evaluate the impact of a dynamically adjusting cognitive training programme, in comparison to a statically challenging alternative. Before and after an 8-week training period, and at a 5-week follow-up, we used portable functional Near Infrared Spectroscopy to examine mental workload in a mixed battery of cognitive and transfer tasks. A recently developed tablet-based task was used to identify changes in cognitive misbinding. Augmented Reality was used to create a supermarket shopping experience, as a more ecologically valid and realistic transfer task relating to an everyday task relating to independence that quickly becomes difficult with cognitive decline. The analyses showed a decreased mental workload within the dorsolateral prefrontal cortex and that participants considerably increased their performance in the trained task. Some results were maintained at the 5-week follow-up assessment. In terms of transfer, we observed reliable group differences immediately after training completion, which were mainly driven by distinct conditions. Some behavioural memory gains were maintained during the follow-up. The use of novel technologies brought new insights into the effects produced by the dynamic computerised cognitive training programme, which has potential future applications in cognitive decline screening and prevention

Benchmarking framework for machine learning classification from fNIRS data

Background: While efforts to establish best practices with functional near infrared spectroscopy (fNIRS) signal processing have been published, there are still no community standards for applying machine learning to fNIRS data. Moreover, the lack of open source benchmarks and standard expectations for reporting means that published works often claim high generalisation capabilities, but with poor practices or missing details in the paper. These issues make it hard to evaluate the performance of models when it comes to choosing them for brain-computer interfaces.Methods: We present an open-source benchmarking framework, BenchNIRS, to establish a best practice machine learning methodology to evaluate models applied to fNIRS data, using five open access datasets for brain-computer interface (BCI) applications. The BenchNIRS framework, using a robust methodology with nested cross-validation, enables researchers to optimise models and evaluate them without bias. The framework also enables us to produce useful metrics and figures to detail the performance of new models for comparison. To demonstrate the utility of the framework, we present a benchmarking of six baseline models [linear discriminant analysis (LDA), support-vector machine (SVM), k-nearest neighbours (kNN), artificial neural network (ANN), convolutional neural network (CNN), and long short-term memory (LSTM)] on the five datasets and investigate the influence of different factors on the classification performance, including: number of training examples and size of the time window of each fNIRS sample used for classification. We also present results with a sliding window as opposed to simple classification of epochs, and with a personalised approach (within subject data classification) as opposed to a generalised approach (unseen subject data classification).Results and discussion: Results show that the performance is typically lower than the scores often reported in literature, and without great differences between models, highlighting that predicting unseen data remains a difficult task. Our benchmarking framework provides future authors, who are achieving significant high classification scores, with a tool to demonstrate the advances in a comparable way. To complement our framework, we contribute a set of recommendations for methodology decisions and writing papers, when applying machine learning to fNIRS data

Finite ion orbit width effect on the neoclassical tearing mode threshold in a tokamak plasma

A new drift kinetic theory for the response of ions to small magnetic islands in toroidal plasma is presented. Islands whose width w is comparable to the ion poloidal Larmor radius ρθi are considered, expanding the ion response solution in terms of Δ = w/r << 1, where r is the minor radius. In this limit, the ion distribution can be represented as a function of toroidal canonical momentum, p. With effects of grad-B and curvature drifts taken into account, the ion distribution function is a constant on a ‘drift island’ structure, which is identical to the magnetic island but radially shifted by O(ρθi). The distribution is then flattened across the drift island, rather than the magnetic island. For small islands w ~ ρθi, the pressure gradient is maintained across the magnetic island, suppressing the bootstrap current drive for the neoclassical tearing mode (NTM) growth. As w → 0, the ions are largely unperturbed. However, the electrons respond to the electrostatic potential required for quasi-neutrality and this provides a stabilizing contribution to the NTM evolution. This gives a new physical understanding of the NTM threshold mechanism, with implications for the design of NTM control systems for future tokamaks such as ITER

Pathologic gene network rewiring implicates PPP1R3A as a central regulator in pressure overload heart failure

Heart failure is a leading cause of mortality, yet our understanding of the genetic interactions underlying this disease remains incomplete. Here, we harvest 1352 healthy and failing human hearts directly from transplant center operating rooms, and obtain genome-wide genotyping and gene expression measurements for a subset of 313. We build failing and non-failing cardiac regulatory gene networks, revealing important regulators and cardiac expression quantitative trait loci (eQTLs). PPP1R3A emerges as a regulator whose network connectivity changes significantly between health and disease. RNA sequencing after PPP1R3A knockdown validates network-based predictions, and highlights metabolic pathway regulation associated with increased cardiomyocyte size and perturbed respiratory metabolism. Mice lacking PPP1R3A are protected against pressure-overload heart failure. We present a global gene interaction map of the human heart failure transition, identify previously unreported cardiac eQTLs, and demonstrate the discovery potential of disease-specific networks through the description of PPP1R3A as a central regulator in heart failure

Data Carpentry: Workshops to Increase Data Literacy for Researchers

In many domains the rapid generation of large amounts of data is fundamentally changing how research is done. The deluge of data presents great opportunities, but also many challenges in managing, analyzing and sharing data. However, good training resources for researchers looking to develop skills that will enable them to be more effective and productive researchers are scarce and there is little space in the existing curriculum for courses or additional lectures. To address this need we have developed an introductory two-day intensive workshop, Data Carpentry, designed to teach basic concepts, skills, and tools for working more effectively and reproducibly with data. These workshops are based on Software Carpentry: two-day, hands-on, bootcamp style workshops teaching best practices in software development, that have demonstrated the success of short workshops to teach foundational research skills. Data Carpentry focuses on data literacy in particular, with the objective of teaching skills to researchers to enable them to retrieve, view, manipulate, analyze and store their and other’s data in an open and reproducible way in order to extract knowledge from data

Promoting ecosystem and human health in urban areas using green infrastructure: A literature review

Europe is a highly urbanised continent. The consequent loss and degradation of urban and peri-urban green space could adversely affect ecosystems as well as human health and well-being. The aim of this paper is to formulate a conceptual framework of associations between urban green space and ecosystem and human health. Through an interdisciplinary literature review the concepts of Green Infrastructure, ecosystem health, and human health and well-being are discussed. The possible contributions of urban and peri-urban green space systems, or Green Infrastructure, on both ecosystem and human health are critically reviewed. Finally, based on a synthesis of the literature a conceptual framework is presented. The proposed conceptual framework highlights many dynamic factors, and their complex interactions, affecting ecosystem health and human health in urban areas. This framework forms the context into which extant and new research can be placed. In this way it forms the basis for a new interdisciplinary research agenda

Vascular effects of serelaxin in patients with stable coronary artery disease:A randomized placebo-controlled trial

Aims: The effects of serelaxin, a recombinant form of human relaxin-2 peptide, on vascular function in the coronary microvascular and systemic macrovascular circulation remain largely unknown. This mechanistic, clinical study assessed the effects of serelaxin on myocardial perfusion, aortic stiffness, and safety in patients with stable coronary artery disease (CAD). Methods and results: In this multicentre, double-blind, parallel-group, placebo-controlled study, 58 patients were randomized 1:1 to 48 h intravenous infusion of serelaxin (30 µg/kg/day) or matching placebo. The primary endpoints were change from baseline to 47 h post-initiation of the infusion in global myocardial perfusion reserve (MPR) assessed using adenosine stress perfusion cardiac magnetic resonance imaging, and applanation tonometry-derived augmentation index (AIx). Secondary endpoints were: change from baseline in AIx and pulse wave velocity, assessed at 47 h, Day 30, and Day 180; aortic distensibility at 47 h; pharmacokinetics and safety. Exploratory endpoints were the effect on cardiorenal biomarkers [N-terminal pro-brain natriuretic peptide (NT-proBNP), high-sensitivity troponin T (hsTnT), endothelin-1, and cystatin C]. Of 58 patients, 51 were included in the primary analysis (serelaxin, n = 25; placebo, n = 26). After 2 and 6 h of serelaxin infusion, mean placebo-corrected blood pressure reductions of −9.6 mmHg (P = 0.01) and −13.5 mmHg (P = 0.0003) for systolic blood pressure and −5.2 mmHg (P = 0.02) and −8.4 mmHg (P = 0.001) for diastolic blood pressure occurred. There were no between-group differences from baseline to 47 h in global MPR (−0.24 vs. −0.13, P = 0.44) or AIx (3.49% vs. 0.04%, P = 0.21) with serelaxin compared with placebo. Endothelin-1 and cystatin C levels decreased from baseline in the serelaxin group, and there were no clinically relevant changes observed with serelaxin for NT-proBNP or hsTnT. Similar numbers of serious adverse events were observed in both groups (serelaxin, n = 5; placebo, n = 7) to 180-day follow-up. Conclusion: In patients with stable CAD, 48 h intravenous serelaxin reduced blood pressure but did not alter myocardial perfusion

MicroRNA regulation of endothelial TREX1 reprograms the tumour microenvironment

Rather than targeting tumour cells directly, elements of the tumour microenvironment can be modulated to sensitize tumours to the effects of therapy. Here we report a unique mechanism by which ectopic microRNA-103 can manipulate tumour-associated endothelial cells to enhance tumour cell death. Using gain-and-loss of function approaches, we show that miR-103 exacerbates DNA damage and inhibits angiogenesis in vitro and in vivo. Local, systemic or vascular-targeted delivery of miR-103 in tumour-bearing mice decreased angiogenesis and tumour growth. Mechanistically, miR-103 regulation of its target gene TREX1 in endothelial cells governs the secretion of pro-inflammatory cytokines into the tumour microenvironment. Our data suggest that this inflammatory milieu may potentiate tumour cell death by supporting immune activation and inducing tumour expression of Fas and TRAIL receptors. Our findings reveal miR-mediated crosstalk between vasculature and tumour cells that can be exploited to improve the efficacy of chemotherapy and radiation.United States. National Institutes of Health (R00HL112962)United States. National Institutes of Health (R01 HL57900)Oregon Health & Science University. Knight Cancer Institute (2015-Dive-Knight-01