The burden and influence of health-care associated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is unknown. We aimed to examine the use of rapid SARS-CoV-2 sequencing ...combined with detailed epidemiological analysis to investigate health-care associated SARS-CoV-2 infections and inform infection control measures.
In this prospective surveillance study, we set up rapid SARS-CoV-2 nanopore sequencing from PCR-positive diagnostic samples collected from our hospital (Cambridge, UK) and a random selection from hospitals in the East of England, enabling sample-to-sequence in less than 24 h. We established a weekly review and reporting system with integration of genomic and epidemiological data to investigate suspected health-care associated COVID-19 cases.
Between March 13 and April 24, 2020, we collected clinical data and samples from 5613 patients with COVID-19 from across the East of England. We sequenced 1000 samples producing 747 high-quality genomes. We combined epidemiological and genomic analysis of the 299 patients from our hospital and identified 35 clusters of identical viruses involving 159 patients. 92 (58%) of 159 patients had strong epidemiological links and 32 (20%) patients had plausible epidemiological links. These results were fed back to clinical, infection control, and hospital management teams, leading to infection-control interventions and informing patient safety reporting.
We established real-time genomic surveillance of SARS-CoV-2 in a UK hospital and showed the benefit of combined genomic and epidemiological analysis for the investigation of health-care associated COVID-19. This approach enabled us to detect cryptic transmission events and identify opportunities to target infection-control interventions to further reduce health-care associated infections. Our findings have important implications for national public health policy as they enable rapid tracking and investigation of infections in hospital and community settings.
COVID-19 Genomics UK (supported by UK Research and Innovation, the National Institute of Health Research, the Wellcome Sanger Institute), the Wellcome Trust, the Academy of Medical Sciences and the Health Foundation, and the National Institute for Health Research Cambridge Biomedical Research Centre.
IMPORTANCE: The sequelae of gestational diabetes (GD) by contemporary criteria that diagnose approximately twice as many women as previously used criteria are unclear. OBJECTIVE: To examine ...associations of GD with maternal glucose metabolism and childhood adiposity 10 to 14 years’ postpartum. DESIGN, SETTING, AND PARTICIPANTS: The Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study established associations of glucose levels during pregnancy with perinatal outcomes and the follow-up study evaluated the long-term outcomes (4697 mothers and 4832 children; study visits occurred between February 13, 2013, and December 13, 2016). EXPOSURES: Gestational diabetes was defined post hoc using criteria from the International Association of Diabetes and Pregnancy Study Groups consisting of 1 or more of the following 75-g oral glucose tolerance test results (fasting plasma glucose ≥92 mg/dL; 1-hour plasma glucose level ≥180 mg/dL; 2-hour plasma glucose level ≥153 mg/dL). MAIN OUTCOMES AND MEASURES: Primary maternal outcome: a disorder of glucose metabolism (composite of type 2 diabetes or prediabetes). Primary outcome for children: being overweight or obese; secondary outcomes: obesity, body fat percentage, waist circumference, and sum of skinfolds (>85th percentile for latter 3 outcomes). RESULTS: The analytic cohort included 4697 mothers (mean SD age, 41.7 5.7 years) and 4832 children (mean SD age, 11.4 1.2 years; 51.0% male). The median duration of follow-up was 11.4 years. The criteria for GD were met by 14.3% (672/4697) of mothers overall and by 14.1% (683/4832) of mothers of participating children. Among mothers with GD, 52.2% (346/663) developed a disorder of glucose metabolism vs 20.1% (791/3946) of mothers without GD (odds ratio OR, 3.44 95% CI, 2.85 to 4.14; risk difference RD, 25.7% 95% CI, 21.7% to 29.7%). Among children of mothers with GD, 39.5% (269/681) were overweight or obese and 19.1% (130/681) were obese vs 28.6% (1172/4094) and 9.9% (405/4094), respectively, for children of mothers without GD. Adjusted for maternal body mass index during pregnancy, the OR was 1.21 (95% CI, 1.00 to 1.46) for children who were overweight or obese and the RD was 3.7% (95% CI, −0.16% to 7.5%); the OR was 1.58 (95% CI, 1.24 to 2.01) for children who were obese and the RD was 5.0% (95% CI, 2.0% to 8.0%); the OR was 1.35 (95% CI, 1.08 to 1.68) for body fat percentage and the RD was 4.2% (95% CI, 0.9% to 7.4%); the OR was 1.34 (95% CI, 1.08 to 1.67) for waist circumference and the RD was 4.1% (95% CI, 0.8% to 7.3%); and the OR was 1.57 (95% CI, 1.27 to 1.95) for sum of skinfolds and the RD was 6.5% (95% CI, 3.1% to 9.9%). CONCLUSIONS AND RELEVANCE: Among women with GD identified by contemporary criteria compared with those without it, GD was significantly associated with a higher maternal risk for a disorder of glucose metabolism during long-term follow-up after pregnancy. Among children of mothers with GD vs those without it, the difference in childhood overweight or obesity defined by body mass index cutoffs was not statistically significant; however, additional measures of childhood adiposity may be relevant in interpreting the study findings.
Abstract
Motivation
RNA-protein interactions are key effectors of post-transcriptional regulation. Significant experimental and bioinformatics efforts have been expended on characterizing protein ...binding mechanisms on the molecular level, and on highlighting the sequence and structural traits of RNA that impact the binding specificity for different proteins. Yet our ability to predict these interactions in silico remains relatively poor.
Results
In this study, we introduce RPI-Net, a graph neural network approach for RNA-protein interaction prediction. RPI-Net learns and exploits a graph representation of RNA molecules, yielding significant performance gains over existing state-of-the-art approaches. We also introduce an approach to rectify an important type of sequence bias caused by the RNase T1 enzyme used in many CLIP-Seq experiments, and we show that correcting this bias is essential in order to learn meaningful predictors and properly evaluate their accuracy. Finally, we provide new approaches to interpret the trained models and extract simple, biologically interpretable representations of the learned sequence and structural motifs.
Availability and implementation
Source code can be accessed at https://www.github.com/HarveyYan/RNAonGraph.
Supplementary information
Supplementary data are available at Bioinformatics online.
Using footage from body-worn cameras, we analyze the respectfulness of police officer language toward white and black community members during routine traffic stops. We develop computational ...linguistic methods that extract levels of respect automatically from transcripts, informed by a thin-slicing study of participant ratings of officer utterances. We find that officers speak with consistently less respect toward black versus white community members, even after controlling for the race of the officer, the severity of the infraction, the location of the stop, and the outcome of the stop. Such disparities in common, everyday interactions between police and the communities they serve have important implications for procedural justice and the building of police–community trust.
Abstract
RNA-small molecule binding is a key regulatory mechanism which can stabilize 3D structures and activate molecular functions. The discovery of RNA-targeting compounds is thus a current topic ...of interest for novel therapies. Our work is a first attempt at bringing the scalability and generalization abilities of machine learning methods to the problem of RNA drug discovery, as well as a step towards understanding the interactions which drive binding specificity. Our tool, RNAmigos, builds and encodes a network representation of RNA structures to predict likely ligands for novel binding sites. We subject ligand predictions to virtual screening and show that we are able to place the true ligand in the 71st–73rd percentile in two decoy libraries, showing a significant improvement over several baselines, and a state of the art method. Furthermore, we observe that augmenting structural networks with non-canonical base pairing data is the only representation able to uncover a significant signal, suggesting that such interactions are a necessary source of binding specificity. We also find that pre-training with an auxiliary graph representation learning task significantly boosts performance of ligand prediction. This finding can serve as a general principle for RNA structure-function prediction when data is scarce. RNAmigos shows that RNA binding data contains structural patterns with potential for drug discovery, and provides methodological insights for possible applications to other structure-function learning tasks. The source code, data and a Web server are freely available at http://rnamigos.cs.mcgill.ca.
The most polymorphic gene family in P. falciparum is the ∼60 var genes distributed across parasite chromosomes, both in the subtelomeres and in internal regions. They encode hypervariable surface ...proteins known as P. falciparum erythrocyte membrane protein 1 (PfEMP1) that are critical for pathogenesis and immune evasion in Plasmodium falciparum. How var gene sequence diversity is generated is not currently completely understood. To address this, we constructed large clone trees and performed whole genome sequence analysis to study the generation of novel var gene sequences in asexually replicating parasites. While single nucleotide polymorphisms (SNPs) were scattered across the genome, structural variants (deletions, duplications, translocations) were focused in and around var genes, with considerable variation in frequency between strains. Analysis of more than 100 recombination events involving var exon 1 revealed that the average nucleotide sequence identity of two recombining exons was only 63% (range: 52.7-72.4%) yet the crossovers were error-free and occurred in such a way that the resulting sequence was in frame and domain architecture was preserved. Var exon 1, which encodes the immunologically exposed part of the protein, recombined in up to 0.2% of infected erythrocytes in vitro per life cycle. The high rate of var exon 1 recombination indicates that millions of new antigenic structures could potentially be generated each day in a single infected individual. We propose a model whereby var gene sequence polymorphism is mainly generated during the asexual part of the life cycle.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background & Aims Cellular changes associated with diabetic and idiopathic gastroparesis are not well described. The aim of this study was to describe histologic abnormalities in gastroparesis and ...compare findings in idiopathic versus diabetic gastroparesis. Methods Full-thickness gastric body biopsy specimens were obtained from 40 patients with gastroparesis (20 diabetic) and matched controls. Sections were stained for H&E and trichrome and immunolabeled with antibodies against protein gene product (PGP) 9.5, neuronal nitric oxide synthase (nNOS), vasoactive intestinal peptide, substance P, and tyrosine hydroxylase to quantify nerves, S100β for glia, Kit for interstitial cells of Cajal (ICC), CD45 and CD68 for immune cells, and smoothelin for smooth muscle cells. Tissue was also examined by transmission electron microscopy. Results Histologic abnormalities were found in 83% of patients. The most common defects were loss of ICC with remaining ICC showing injury, an abnormal immune infiltrate containing macrophages, and decreased nerve fibers. On light microscopy, no significant differences were found between diabetic and idiopathic gastroparesis with the exception of nNOS expression, which was decreased in more patients with idiopathic gastroparesis (40%) compared with diabetic patients (20%) by visual grading. On electron microscopy, a markedly increased connective tissue stroma was present in both disorders. Conclusions This study suggests that on full-thickness biopsy specimens, cellular abnormalities are found in the majority of patients with gastroparesis. The most common findings were loss of Kit expression, suggesting loss of ICC, and an increase in CD45 and CD68 immunoreactivity. These findings suggest that examination of tissue can lead to valuable insights into the pathophysiology of these disorders and offer hope that new therapeutic targets can be found.
Abstract
Background:
Falsified medicines are deliberately fraudulent drugs that pose a direct risk to patient health and undermine healthcare systems, causing global morbidity and mortality.
...Objective:
To produce an overview of anti-falsifying public health interventions deployed at international, national and local scales in low and middle income countries (LMIC).
Data sources:
We conducted a systematic search of the PubMed, Web of Science, Embase and Cochrane Central Register of Controlled Trials databases for healthcare or pharmaceutical policies relevant to reducing the burden of falsified medicines in LMIC.
Results:
Our initial search identified 660 unique studies, of which 203 met title/abstract inclusion criteria and were categorised according to their primary focus: international; national; local pharmacy; internet pharmacy; drug analysis tools. Eighty-four were included in the qualitative synthesis, along with 108 articles and website links retrieved through secondary searches.
Discussion:
On the international stage, we discuss the need for accessible pharmacovigilance (PV) global reporting systems, international leadership and funding incorporating multiple stakeholders (healthcare, pharmaceutical, law enforcement) and multilateral trade agreements that emphasise public health. On the national level, we explore the importance of establishing adequate medicine regulatory authorities and PV capacity, with drug screening along the supply chain. This requires interdepartmental coordination, drug certification and criminal justice legislation and enforcement that recognise the severity of medicine falsification. Local healthcare professionals can receive training on medicine quality assessments, drug registration and pharmacological testing equipment. Finally, we discuss novel technologies for drug analysis which allow rapid identification of fake medicines in low-resource settings. Innovative point-of-purchase systems like mobile phone verification allow consumers to check the authenticity of their medicines.
Conclusions:
Combining anti-falsifying strategies targeting different levels of the pharmaceutical supply chain provides multiple barriers of protection from falsified medicines. This requires the political will to drive policy implementation; otherwise, people around the world remain at risk.
Drug discovery and development is a complex and costly process. Machine learning approaches are being investigated to help improve the effectiveness and speed of multiple stages of the drug discovery ...pipeline. Of these, those that use Knowledge Graphs (KG) have promise in many tasks, including drug repurposing, drug toxicity prediction and target gene-disease prioritization. In a drug discovery KG, crucial elements including genes, diseases and drugs are represented as entities, while relationships between them indicate an interaction. However, to construct high-quality KGs, suitable data are required. In this review, we detail publicly available sources suitable for use in constructing drug discovery focused KGs. We aim to help guide machine learning and KG practitioners who are interested in applying new techniques to the drug discovery field, but who may be unfamiliar with the relevant data sources. The datasets are selected via strict criteria, categorized according to the primary type of information contained within and are considered based upon what information could be extracted to build a KG. We then present a comparative analysis of existing public drug discovery KGs and an evaluation of selected motivating case studies from the literature. Additionally, we raise numerous and unique challenges and issues associated with the domain and its datasets, while also highlighting key future research directions. We hope this review will motivate KGs use in solving key and emerging questions in the drug discovery domain.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Aims/hypothesis
Maternal type 2 diabetes during pregnancy and gestational diabetes are associated with childhood adiposity; however, associations of lower maternal glucose levels during pregnancy ...with childhood adiposity, independent of maternal BMI, remain less clear. The objective was to examine associations of maternal glucose levels during pregnancy with childhood adiposity in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) cohort.
Methods
The HAPO Study was an observational epidemiological international multi-ethnic investigation that established strong associations of glucose levels during pregnancy with multiple adverse perinatal outcomes. The HAPO Follow-up Study (HAPO FUS) included 4832 children from ten HAPO centres whose mothers had a 75 g OGTT at ~28 weeks gestation 10–14 years earlier, with glucose values blinded to participants and clinical caregivers. The primary outcome was child adiposity, including: (1) being overweight/obese according to sex- and age-specific cut-offs based on the International Obesity Task Force (IOTF) criteria; (2) IOTF-defined obesity only; and (3) measurements >85th percentile for sum of skinfolds, waist circumference and per cent body fat. Primary predictors were maternal OGTT and HbA
1c
values during pregnancy.
Results
Fully adjusted models that included maternal BMI at pregnancy OGTT indicated positive associations between maternal glucose predictors and child adiposity outcomes. For one SD difference in pregnancy glucose and HbA
1c
measures, ORs for each child adiposity outcome were in the range of 1.05–1.16 for maternal fasting glucose, 1.11–1.19 for 1 h glucose, 1.09–1.21 for 2 h glucose and 1.12–1.21 for HbA
1c
. Associations were significant, except for associations of maternal fasting glucose with offspring being overweight/obese or having waist circumference >85th percentile. Linearity was confirmed in all adjusted models. Exploratory sex-specific analyses indicated generally consistent associations for boys and girls.
Conclusions/interpretation
Exposure to higher levels of glucose in utero is independently associated with childhood adiposity, including being overweight/obese, obesity, skinfold thickness, per cent body fat and waist circumference. Glucose levels less than those diagnostic of diabetes are associated with greater childhood adiposity; this may have implications for long-term metabolic health.
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