Understanding the Consumption of Antimicrobial Resistance–Related Content on Social Media: Twitter Analysis

Background: Antimicrobial resistance (AMR) is one of the most pressing concerns in our society. Today, social media can function as an important channel to disseminate information about AMR. The way in which this information is engaged with depends on a number of factors, including the target audience and the content of the social media post. Objective: The aim of this study is to better understand how AMR-related content is consumed on the social media platform Twitter and to understand some of the drivers of engagement. This is essential to designing effective public health strategies, raising awareness about antimicrobial stewardship, and enabling academics to effectively promote their research on social media. Methods: We took advantage of unrestricted access to the metrics associated with the Twitter bot @AntibioticResis, which has over 13,900 followers. This bot posts the latest AMR research in the format of a title and a URL link to the PubMed page for an article. The tweets do not contain other attributes such as author, affiliation, or journal. Therefore, engagement with the tweets is only affected by the words used in the titles. Using negative binomial regression models, we measured the impact of pathogen names in paper titles, academic attention inferred from publication counts, and general attention estimated from Twitter on URL clicks to AMR research papers. Results: Followers of @AntibioticResis consisted primarily of health care professionals and academic researchers whose interests comprised mainly AMR, infectious diseases, microbiology, and public health. Three World Health Organization (WHO) critical priority pathogens—Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacteriaceae—were positively associated with URL clicks. Papers with shorter titles tended to have more engagements. We also described some key linguistic characteristics that should be considered when a researcher is trying to maximize engagement with their publication. Conclusions: Our finding suggests that specific pathogens gain more attention on Twitter than others and that the levels of attention do not necessarily correspond to their status on the WHO priority pathogen list. This suggests that more targeted public health strategies may be needed to raise awareness about AMR among specific pathogens. Analysis of follower data suggests that in the busy schedules of health care professionals, social media offers a fast and accessible gateway to staying abreast of the latest developments in this field

A pilot study demonstrating the altered gut microbiota functionality in stable adults with Cystic Fibrosis

peer-reviewedCystic Fibrosis (CF) and its treatment result in an altered gut microbiota composition compared to non-CF controls. However, the impact of this on gut microbiota functionality has not been extensively characterised. Our aim was to conduct a proof-of-principle study to investigate if measurable changes in gut microbiota functionality occur in adult CF patients compared to controls. Metagenomic DNA was extracted from faecal samples from six CF patients and six non-CF controls and shotgun metagenomic sequencing was performed on the MiSeq platform. Metabolomic analysis using gas chromatography-mass spectrometry was conducted on faecal water. The gut microbiota of the CF group was significantly different compared to the non-CF controls, with significantly increased Firmicutes and decreased Bacteroidetes. Functionality was altered, with higher pathway abundances and gene families involved in lipid (e.g. PWY 6284 unsaturated fatty acid biosynthesis (p = 0.016)) and xenobiotic metabolism (e.g. PWY-5430 meta-cleavage pathway of aromatic compounds (p = 0.004)) in CF patients compared to the controls. Significant differences in metabolites occurred between the two groups. This proof-of-principle study demonstrates that measurable changes in gut microbiota functionality occur in CF patients compared to controls. Larger studies are thus needed to interrogate this further

Using Heat to Characterize Streambed Water Flux Variability in Four Stream Reaches

Estimates of streambed water fl ux are needed for the interpretation of streambed chemistry and reactions. Continuous temperature and head monitoring in stream reaches within four agricultural watersheds (Leary Weber Ditch, IN; Maple Creek, NE; DR2 Drain, WA; and Merced River, CA) allowed heat to be used as a tracer to study the temporal and spatial variability of fluxes through the streambed. Synoptic methods (seepage meter and differential discharge measurements) were compared with estimates obtained by using heat as a tracer. Water flux was estimated by modeling one-dimensional vertical flow of water and heat using the model VS2DH. Flux was influenced by physical heterogeneity of the stream channel and temporal variability in stream and ground-water levels. During most of the study period (April–December 2004), flux was upward through the streambeds. At the IN, NE, and CA sites, high-stage events resulted in rapid reversal of flow direction inducing short-term surface-water flow into the streambed. During late summer at the IN site, regional ground-water levels dropped, leading to surface-water loss to ground water that resulted in drying of the ditch. Synoptic measurements of flux generally supported the model flux estimates. Water flow through the streambed was roughly an order of magnitude larger in the humid basins (IN and NE) than in the arid basins (WA and CA). Downward flux, in response to sudden high streamflows, and seasonal variability in flux was most pronounced in the humid basins and in high conductivity zones in the streambed

WS16.1 Clinical Outcomes of Real-World Kalydeco (CORK) study – Investigating the impact of CFTR potentiation on the intestinal microbiota, exocrine pancreatic function and intestinal inflammation prospectively over 12 months

peer-reviewedAbstracts of the 38th European Cystic Fibrosis ConferenceObjectives Ivacaftor is effective in the treatment of patients with CF and the G551D gating mutation. We present faecal analysis results of the CORK cohort, a single-centre, adult (n = 20), prospective, longitudinal study of G551D clinical responders (median follow-up 12 months), examining the gut microbiota, exocrine pancreatic function and intestinal inflammation on a 3 monthly basis after commencing treatment

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage

Microbiomes are vast communities of microorganisms and viruses that populate all natural ecosystems. Viruses have been considered to be the most variable component of microbiomes, as supported by virome surveys and examples of high genomic mosaicism. However, recent evidence suggests that the human gut virome is remarkably stable compared with that of other environments. Here, we investigate the origin, evolution and epidemiology of crAssphage, a widespread human gut virus. Through a global collaboration, we obtained DNA sequences of crAssphage from more than one-third of the world's countries and showed that the phylogeography of crAssphage is locally clustered within countries, cities and individuals. We also found fully colinear crAssphage-like genomes in both Old-World and New-World primates, suggesting that the association of crAssphage with primates may be millions of years old. Finally, by exploiting a large cohort of more than 1,000 individuals, we tested whether crAssphage is associated with bacterial taxonomic groups of the gut microbiome, diverse human health parameters and a wide range of dietary factors. We identified strong correlations with different clades of bacteria that are related to Bacteroidetes and weak associations with several diet categories, but no significant association with health or disease. We conclude that crAssphage is a benign cosmopolitan virus that may have coevolved with the human lineage and is an integral part of the normal human gut virome

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications.

RNA sequencing (RNA-seq) is a genomic approach for the detection and quantitative analysis of messenger RNA molecules in a biological sample and is useful for studying cellular responses. RNA-seq has fueled much discovery and innovation in medicine over recent years. For practical reasons, the technique is usually conducted on samples comprising thousands to millions of cells. However, this has hindered direct assessment of the fundamental unit of biology-the cell. Since the first single-cell RNA-sequencing (scRNA-seq) study was published in 2009, many more have been conducted, mostly by specialist laboratories with unique skills in wet-lab single-cell genomics, bioinformatics, and computation. However, with the increasing commercial availability of scRNA-seq platforms, and the rapid ongoing maturation of bioinformatics approaches, a point has been reached where any biomedical researcher or clinician can use scRNA-seq to make exciting discoveries. In this review, we present a practical guide to help researchers design their first scRNA-seq studies, including introductory information on experimental hardware, protocol choice, quality control, data analysis and biological interpretation