Design and conduct of 'Xtreme Alps' : a double-blind, randomised controlled study of the effects of dietary nitrate supplementation on acclimatisation to high altitude

The study of healthy human volunteers ascending to high altitude provides a robust model of the complex physiological interplay that emulates human adaptation to hypoxaemia in clinical conditions. Nitric oxide (NO) metabolism may play an important role in both adaptation to high altitude and response to hypoxaemia during critical illness at sea level. Circulating nitrate and nitrite concentrations can be augmented by dietary supplementation and this is associated with improved exercise performance and mitochondrial efficiency. We hypothesised that the administration of a dietary substance (beetroot juice) rich in nitrate would improve oxygen efficiency during exercise at high altitude by enhancing tissue microcirculatory blood flow and oxygenation. Furthermore, nitrate supplementation would lead to measurable increases in NO bioactivity throughout the body. This methodological manuscript describes the design and conduct of the ‘Xtreme Alps’ expedition, a double-blind randomised controlled trial investigating the effects of dietary nitrate supplementation on acclimatisation to hypobaric hypoxia at high altitude in healthy human volunteers. The primary outcome measure was the change in oxygen efficiency during exercise at high altitude between participants allocated to receive nitrate supplementation and those receiving a placebo. A number of secondary measures were recorded, including exercise capacity, peripheral and microcirculatory blood flow and tissue oxygenation. Results from this study will further elucidate the role of NO in adaption to hypoxaemia and guide clinical trials in critically ill patients. Improved understanding of hypoxaemia in critical illness may provide new therapeutic avenues for interventions that will improve survival in critically ill patients

Mechanisms underpinning the permanent muscle damage induced by snake venom metalloprotease

Snakebite is a major neglected tropical health issue that affects over 5 million people worldwide resulting in around 1.8 million envenomations and 100,000 deaths each year. Snakebite envenomation also causes innumerable morbidities specifically loss of limbs as a result of excessive tissue/muscle damage. Snake venom metalloproteases (SVMPs) are a predominant component of viper venoms, and are involved in the degradation of basement membrane proteins (particularly collagen) surrounding the tissues around the bite site. Although their collagenolytic properties have been established, the molecular mechanisms through which SVMPs induce permanent muscle damage are poorly understood. Here, we demonstrate the purification and characterisation of an SVMP from a viper (Crotalus atrox) venom. Mass spectrometry analysis confirmed that this protein is most likely to be a group III metalloprotease (showing high similarity to VAP2A) and has been referred to as CAMP (Crotalus atrox metalloprotease). CAMP displays both collagenolytic and fibrinogenolytic activities and inhibits CRP-XL-induced platelet aggregation. To determine its effects on muscle damage, CAMP was administered into the tibialis anterior muscle of mice and its actions were compared with cardiotoxin I (a three-finger toxin) from an elapid snake (Naja pallida) venom. Extensive immunohistochemistry analyses revealed that CAMP significantly damages skeletal muscles by attacking the collagen scaffold and other important basement membrane proteins, and prevents their regeneration through disrupting the functions of satellite cells. In contrast, cardiotoxin I destroys skeletal muscle by damaging the plasma membrane, but does not impact regeneration due to its inability to affect the extracellular matrix. Overall, this study provides novel insights into the mechanisms through which SVMPs induce permanent muscle damage

Deep-coverage whole genome sequences and blood lipids among 16,324 individuals.

Large-scale deep-coverage whole-genome sequencing (WGS) is now feasible and offers potential advantages for locus discovery. We perform WGS in 16,324 participants from four ancestries at mean depth >29X and analyze genotypes with four quantitative traits-plasma total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. Common variant association yields known loci except for few variants previously poorly imputed. Rare coding variant association yields known Mendelian dyslipidemia genes but rare non-coding variant association detects no signals. A high 2M-SNP LDL-C polygenic score (top 5th percentile) confers similar effect size to a monogenic mutation (~30 mg/dl higher for each); however, among those with severe hypercholesterolemia, 23% have a high polygenic score and only 2% carry a monogenic mutation. At these sample sizes and for these phenotypes, the incremental value of WGS for discovery is limited but WGS permits simultaneous assessment of monogenic and polygenic models to severe hypercholesterolemia

A comprehensive analysis of rare genetic variation in amyotrophic lateral sclerosis in the UK.

Amyotrophic lateral sclerosis is a progressive neurodegenerative disease of motor neurons. About 25 genes have been verified as relevant to the disease process, with rare and common variation implicated. We used next generation sequencing and repeat sizing to comprehensively assay genetic variation in a panel of known amyotrophic lateral sclerosis genes in 1126 patient samples and 613 controls. About 10% of patients were predicted to carry a pathological expansion of the C9orf72 gene. We found an increased burden of rare variants in patients within the untranslated regions of known disease-causing genes, driven by SOD1, TARDBP, FUS, VCP, OPTN and UBQLN2. We found 11 patients (1%) carried more than one pathogenic variant (P = 0.001) consistent with an oligogenic basis of amyotrophic lateral sclerosis. These findings show that the genetic architecture of amyotrophic lateral sclerosis is complex and that variation in the regulatory regions of associated genes may be important in disease pathogenesis

Federated Learning on Heterogenous Data using Chest CT

Large data have accelerated advances in AI. While it is well known that population differences from genetics, sex, race, diet, and various environmental factors contribute significantly to disease, AI studies in medicine have largely focused on locoregional patient cohorts with less diverse data sources. Such limitation stems from barriers to large-scale data share in medicine and ethical concerns over data privacy. Federated learning (FL) is one potential pathway for AI development that enables learning across hospitals without data share. In this study, we show the results of various FL strategies on one of the largest and most diverse COVID-19 chest CT datasets: 21 participating hospitals across five continents that comprise >10,000 patients with >1 million images. We present three techniques: Fed Averaging (FedAvg), Incremental Institutional Learning (IIL), and Cyclical Incremental Institutional Learning (CIIL). We also propose an FL strategy that leverages synthetically generated data to overcome class imbalances and data size disparities across centers. We show that FL can achieve comparable performance to Centralized Data Sharing (CDS) while maintaining high performance across sites with small, underrepresented data. We investigate the strengths and weaknesses for all technical approaches on this heterogeneous dataset including the robustness to non-Independent and identically distributed (non-IID) diversity of data. We also describe the sources of data heterogeneity such as age, sex, and site locations in the context of FL and show how even among the correctly labeled populations, disparities can arise due to these biases

Meta-analysis of genome-wide association studies from the CHARGE consortium identifies common variants associated with carotid intima media thickness and plaque

Carotid intima media thickness (cIMT) and plaque determined by ultrasonography are established measures of subclinical atherosclerosis that each predicts future cardiovascular disease events. We conducted a meta-analysis of genome-wide association data in 31,211 participants of European ancestry from nine large studies in the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. We then sought additional evidence to support our findings among 11,273 individuals using data from seven additional studies. In the combined meta-analysis, we identified three genomic regions associated with common carotid intima media thickness and two different regions associated with the presence of carotid plaque (P < 5 × 10 -8). The associated SNPs mapped in or near genes related to cellular signaling, lipid metabolism and blood pressure homeostasis, and two of the regions were associated with coronary artery disease (P < 0.006) in the Coronary Artery Disease Genome-Wide Replication and Meta-Analysis (CARDIoGRAM) consortium. Our findings may provide new insight into pathways leading to subclinical atherosclerosis and subsequent cardiovascular events

Swiss public health measures associated with reduced SARS-CoV-2 transmission using genome data

Genome sequences from evolving infectious pathogens allow quantification of case introductions and local transmission dynamics. We sequenced 11,357 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from Switzerland in 2020 - the sixth largest effort globally. Using a representative subset of these data, we estimated viral introductions to Switzerland and their persistence over the course of 2020. We contrasted these estimates with simple null models representing the absence of certain public health measures. We show that Switzerland's border closures de-coupled case introductions from incidence in neighboring countries. Under a simple model, we estimate an 86-98% reduction in introductions during Switzerland's strictest border closures. Furthermore, the Swiss 2020 partial lockdown roughly halved the time for sampled introductions to die out. Last, we quantified local transmission dynamics once introductions into Switzerland occurred, using a phylodynamic model. We found that transmission slowed 35-63% upon outbreak detection in summer 2020, but not in fall. This finding may indicate successful contact tracing over summer before overburdening in fall. The study highlights the added value of genome sequencing data for understanding transmission dynamics

AGN STORM 2: V. Anomalous Behavior of the CIV Light Curve in Mrk 817

An intensive reverberation mapping campaign on the Seyfert 1 galaxy Mrk817 using the Cosmic Origins Spectrograph (COS) on the Hubble Space Telescope (HST) revealed significant variations in the response of the broad UV emission lines to fluctuations in the continuum emission. The response of the prominent UV emission lines changes over a $\sim$60-day duration, resulting in distinctly different time lags in the various segments of the light curve over the 14 months observing campaign. One-dimensional echo-mapping models fit these variations if a slowly varying background is included for each emission line. These variations are more evident in the CIV light curve, which is the line least affected by intrinsic absorption in Mrk817 and least blended with neighboring emission lines. We identify five temporal windows with distinct emission line response, and measure their corresponding time delays, which range from 2 to 13 days. These temporal windows are plausibly linked to changes in the UV and X-ray obscuration occurring during these same intervals. The shortest time lags occur during periods with diminishing obscuration, whereas the longest lags occur during periods with rising obscuration. We propose that the obscuring outflow shields the ultraviolet broad lines from the ionizing continuum. The resulting change in the spectral energy distribution of the ionizing continuum, as seen by clouds at a range of distances from the nucleus, is responsible for the changes in the line response.Comment: 20 pages, 8 figures, submitted to Ap

SPARC 2019 Fake news & home truths : Salford postgraduate annual research conference book of abstracts

Welcome to the Book of Abstracts for the 2019 SPARC conference. This year we not only celebrate the work of our PGRs but also our first ever Doctoral School Best Supervisor awards, which makes this year’s conference extra special. Once again we have received a tremendous contribution from our postgraduate research community; with over 90 presenters, the conference truly showcases a vibrant, innovative and collaborative PGR community at Salford. These abstracts provide a taster of the inspiring, relevant and impactful research in progress, and provide delegates with a reference point for networking and initiating critical debate. Find an abstract that interests you, and say “Hello” to the author. Who knows what might result from your conversation? With such wide-ranging topics being showcased, we encourage you to take up this great opportunity to engage with researchers working in different subject areas from your own. To meet global challenges, high impact research needs interdisciplinary collaboration. This is recognised and rewarded by all major research funders. Engaging with the work of others and forging collaborations across subject areas is an essential skill for the next generation of researchers. Even better, our free ice cream van means that you can have those conversations while enjoying a refreshing ice lolly