712 research outputs found
Trinaest pisama. Peto pismo
No full textKnjiževni deo "Jevrejskog almanaha" u kome je objavljena priča Aleksandra Ajzinberga "Trinaest pisama. Peto pismo", odnosi se na literarne radove sa jevrejskom tematikom iz oblasti istorije, književnosti, umetnosti, memoarske građe i Holokausta. Neki od radova iz ove rubrike objavljuju se po prvi put, neki su objavljeni i na drugim mestima a neki su delovi većih celina (zbirki, romana, memoarske građe, dnevnika i sl.).The literary section of the "Jewish Almanac" where is published story "Trinaest pisama. Peto pismo" by Aleksandar Ajzinberg, refers to literary works on Jewish topics in the fields of history, literature, art, memoirs, and Holocaust. Some of the works in this section are published for the first time, some have been published elsewhere and, some are parts of larger entities (collections, novels, memoirs, diaries, letters, etc.)."Peto pismo" je deo knjige "Pisma Matveju". Prvo izdanje ove knjige objavila je 2006. godine izdavačka kuća "Prosveta", Beograd, a drugo dopunjeno elektronsko izdanje objavio je autor. (The first edition of the book "Letters to Matvej" was published in 2006 by the publishing house "Prosveta", Belgrade, and the second extended electronic edition was published by the author)
Whole genome sequencing and resistance in Escherichia coli
No full textRising antimicrobial resistance is an increasing problem worldwide. Escherichia coli presents
a particular challenge as it spreads resistance rapidly via mobile genetic elements.
Combatting this requires fast, detailed identification of resistance to prevent its spread and
inform treatment. Culture-based antimicrobial susceptibility testing (AST) is limited by the
time required for bacterial growth and does not directly identify mechanisms of resistance.
However, many molecular techniques require specific targets, limiting their routine use in
clinical microbiology. Whole genome sequencing (WGS) offers an alternative, solving many
of these issues. However, evidence of WGSâs ability to identify clinically significant
resistance in E. coli is limited. This thesis investigates this in detail.
Using methods similar to those from âproof-of-principleâ studies, beta-lactam resistance
was predicted from WGS data in several sets of E. coli, including a large set of unselected
bloodstream infection isolates. While agreement between WGS-predicted and observed AST
was high for many antibiotics, for some, including several commonly used broad spectrum
antibiotics, there was significant discrepancy. Focussing on amoxicillin-clavulanate
resistance due to the extent of disparity and its clinical significance, the causes of
discrepancy were investigated. Instead of the discrepancy being due to the bioinformatic
approach, incomplete knowledge of resistance mechanisms or phenotyping errors as is
commonly believed, results suggested oversimplifications of both phenotype and genotype
were the major cause. Future work is needed to investigate WGS-based prediction for other
antibiotic and antimicrobial combinations.
This work demonstrates the feasibility of WGS-based prediction for a phenotype widely
regarded as one of the most complex. However, it also highlights many barriers WGS-based
prediction will need to overcome prior to clinical implementation. These include not only
technical problems such as how to best curate and use genetic data for resistance
prediction, but also non-technical problems such as the need to challenge long held
assumptions regarding the nature of antimicrobial susceptibility testing.</p
The role of whole-genome sequencing technology in the control and treatment of Mycobacterium tuberculosis infection
No full textIn 2013 an estimated 9 million patients were diagnosed with tuberculosis across the globe, leading to 1.5 million deaths. In the UK, just under 8,000 cases were notified. Where resources allow, tuberculosis control is based on the identification of outbreaks, and the timely diagnosis and appropriate treatment of infected patients. However, current methods for identifying tuberculosis outbreaks are limited in their specificity, whilst the definitive diagnostic tests remain culture-dependent and can hence take weeks before producing a result. Whole-genome sequencing (WGS) technology is now affordable, rapid and accurate, and in this thesis I explore its potential both for detecting transmission and for identifying the genetic variation underlying drug resistance. Understanding the degree of M. tuberculosis genetic diversity within and between epidemiologically related individuals is a prerequisite to using WGS to identify Mycobacterium tuberculosis transmission. In chapter 3 I outline how this diversity is rarely greater than 5 nucleotide variants and also describe how the pattern of genetic diversity within an outbreak relates to the epidemiologically recognised transmission patterns. In chapter 4 I apply the findings from chapter 3 to all tuberculosis cases in Oxfordshire over a 6-year period to show that although most patients with tuberculosis were born in a high-incidence country, the odds of transmission among UK-born patients are in fact greater. These findings have contributed to the decision by Public Health England to invest in the routine whole-genome sequencing of M. tuberculosis from 2015. In chapter 5 I explore whether the potential utility of future sequence data can be increased by also predicting phenotypic drug susceptibility. I therefore devise an algorithm to characterise relevant genetic variation associated with phenotypic drug resistance or susceptibility. I conclude that WGS has a significant contribution to make towards improving patient outcomes and decreasing onward transmission of disease
Investigation of in-hospital norovirus transmission using whole genome sequencing
No full textNorovirus is the commonest cause of viral gastroenteritis, affecting all age groups worldwide. Outbreaks frequently occur in semi-closed communities such as schools, cruise ships, prisons and hospitals. Within the healthcare environment, the economic and logistical burdens and the inconvenience caused by norovirus is significant, since ward closure remains central to infection control. The aim of this study was to investigate norovirus transmission dynamics during hospital outbreaks. The ultimate goal was to provide information that could, in future, lead to the development of novel, less disruptive approaches to curtailing the spread of infection. The study explored the application of 'next generation' high throughput DNA sequencing technologies to the determination of large numbers of norovirus genomes. Whole genome sequences provide the highest possible level of discrimination among viruses, information which is essential to the identification of linked and independent cases of infection. The approach exploits the high norovirus mutation rate, which is typical of RNA viruses. Consequently, viruses within a single ward which differ by more than a few SNVs can be considered to represent independent introductions, rather than a single outbreak. Whole genome sequence data (determined for noroviruses collected between 2009 and 2013) were combined with epidemiological data, providing further insights into transmission dynamics. These data identified multiple independent virus introductions during single ward outbreaks. The possible origin of such outbreaks in Oxfordshire hospitals were investigated using viruses originating in the local community, and in other healthcare environments distributed throughout the UK. Whole genome sequences of noroviruses from consecutive years were genetically divergent, confirming the rapid evolution of the virus over time and excluding the possibility of prolonged environmental contamination as a reservoir of infection. Such detailed information on norovirus transmission within the healthcare environment could inform alternative future approaches to optimising infection control within the healthcare setting
Phenotypic modelling of Crohn's disease severity: a machine learning approach
No full textThe growing availability of complex healthcare data holds great promise for improvements in medicine. However, new methodological developments are necessary to realise the potential of these resources. In this thesis we focused upon phenotypic modelling for chronic disease applications, specifically inflammatory bowel disease (IBD). Patients with IBD experience varying clinical trajectories, with the disease course ranging greatly in terms of severity. Our goal was to develop methods to capture IBD patient severity, using data from the electronic health record, and to then use our representations of severity to discover subgroups of patients with similar characteristics. The establishment of patient subgroups and associated genomic factors can enable precision medicine approaches to improve patient care.
Faced with the challenge of unevenly-sampled and sparse clinical time series data, we have proposed a novel approach founded in extreme value theory (EVT) as a means to convert these measurements into interpretable metrics of patient abnormality. We show that our metrics are specifically useful in the modelling of IBD patients, as they provide a condensed representation of a patient’s aggregate biochemistry and haematology dynamics. We also found that patient biomarker-based severity is much more representative of classical severity metrics for patients with ulcerative colitis (UC, one of the two primary IBD subtypes) than it is for patients with Crohn’s disease (CD, the second subtype).
Thus motivated to combine both our EVT-based and classical phenotypic representations of severity, we implemented a Bayesian clustering model so as to identify latent patient severity profiles. Our model is capable of handling missing data and inferring the number of underlying clusters. We found that consistent patient sub-groups were identifiable in our patient cohort, with the majority of CD patients falling into subgroups with severe phenotypic behaviour and the majority of UC patients exhibiting less severe behaviour.
Having identified patient subgroups, we performed a hypothesis-generating association analysis to relate these subgroups (and other clinical features) to genetic loci previously associated with IBD susceptibility. We have presented a number of nominal associations, several of which have plausible biologic mechanisms. Finally, we have illustrated how we can use traditional approaches, machine learning techniques, and our presented EVT methods to answer a practical clinical question regarding the efficacy of two important IBD last-line medications. We examined these drugs in terms of their relative effectiveness, our ability to predict of patient response, and characterisation of this response. We were able to identify distinct ways in which patients respond to these drugs, while also finding that our retrospective data reveals no apparent difference between the two drugs in their effectiveness.
In summary, we have developed a set of methods that can be applied to the challenging problem of finding patterns across patients with heterogeneous disease. Upon using these methods within our specific IBD application area, we have obtained clinically and scientifically useful results
Table S1. Summary data for the 50 individual throat swab samples.
No full textTable S1. Summary data for the 50 individual throat swab samples. fromMetagenomic Nanopore sequencing of influenza virus direct from clinical respiratory samplesKuiama Lewandowski, Yifei Xu, Steven T. Pullan, Sheila F. Lumley, Dona Foster, Nicholas Sanderson, Alison Vaughan, Marcus Morgan, Nicole Bright, James Kavanagh, Richard Vipond, Miles Carroll, Anthony C. Marriott, Karen E Gooch, Monique Andersson, Katie Jeffery, Timothy EA Peto, Derrick W. Crook, A Sarah Walker, Philippa C. MatthewsbioRxiv 676155; doi: https://doi.org/10.1101/676155</div
Feasibility and acceptability of daily testing at school as an alternative to self-isolation following close contact with a confirmed case of COVID-19: a qualitative analysis
No full textBackground
Daily testing using a rapid Lateral Flow Device (LFD) has been suggested as an alternative to self-isolation. A randomised trial comparing daily contact testing (DCT) in schools with self-isolation found that SARS-CoV-2 transmission within school was comparable and low in both groups. However, if this approach is to be adopted widely, it is critical that we understand the perspective of those who will be delivering and receiving DCT. The aim of this qualitative process study embedded in the randomised controlled trial (RCT) was to improve understanding of a range of behavioural factors that could influence implementation.
Methods
Interviews were conducted with 63 participants, including staff, students, and parents of students who had been identified as being in close contact with someone with COVID-19. The topic guide explored perceptions of daily testing, understanding of positive and negative test results, and adherence to guidance. Data were analysed using an inductive thematic approach.
Results
Results were organised under three main headings: (1) factors influencing daily testing (2) interpretation of test results (3) behaviour during testing period. Participants recognized that daily testing may allow students to remain in school, which was viewed as necessary for both education and social needs. Whilst some felt safer as a result of daily testing, others raised concerns about safety. Participants did not always understand how to interpret and respond to test results, and although participants reported high levels of adherence to the guidance, improved communications were desired.
Conclusion
Daily testing may be a feasible and acceptable alternative to self-isolation among close contacts of people who test positive. However, improved communications are needed to ensure that all students and parents have a good understanding of the rationale for testing, what test results mean, how test results should be acted on, and how likely students are to test positive following close contact. Support is needed for students and parents of students who have to self-isolate and for those who have concerns about the safety of daily testing
Austrian Studies Newsmagazine - Vol. 29 No.2
No full textFall 2017 Issue Includes: CAS Celebrates its 40th Anniversary; William E. Wright in memoriam; Interview with Timothy Snyder; Interview with Bruce Pauley; Andrea Peto on the Central European University in Budapest under Attack; Susanne Helene Betz on Jewish Sport in Vienna 1918 to 1945; News from Center Austria; News from the Wirth Institute; Salt, Sword and Crozier exhibit; Book Reviews: "The Singing Turk", "Cleansing the Czechoslovak Borderlands", and "Violent Sensations".. (2017). Austrian Studies Newsmagazine - Vol. 29 No.2. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/191873
Using bacterial DNA sequencing data to investigate the epidemiology of plasmid-mediated antibiotic resistance
No full textBacterial plasmids are extra-chromosomal genetic elements, which can act as efficient vectors of antibiotic resistance. Epidemiological insight into plasmids may be gained by applying plasmid typing schemes, which exploit loci involved in replication and mobility functions (replicon and MOB typing, respectively). In Chapter 2, I compiled a curated dataset of complete NCBI plasmids to assess the performance of in silico replicon and MOB typing in terms of concordance and ‘typeability’ (proportion of plasmids typed). I found a degree of non-concordance between the schemes, which was attributed to either ambiguous boundaries between MOBP/MOBQ types, or the mosaic nature of some plasmid genomes. Ultimately, I showed that the schemes fail to accommodate the diversity of plasmid genomes; of ~14000 curated bacterial plasmids, only 42% and 55% could be assigned a replicon and MOB type, respectively. Given the limitations of plasmid typing, I subsequently focused on whole genome sequencing (WGS) analysis approaches capitalising on the wider plasmid genome. High-throughput DNA sequencing has produced 1000s of bacterial WGS datasets. However, such datasets commonly comprise short sequencing reads, which yield fragmented assemblies; this makes comparative analysis of plasmid genomes challenging. In Chapter 3, I developed two methods for comparative plasmid analysis, which cluster short-read sequenced samples according to 1) plasmid replicon types; 2) sample-vs-reference plasmid distance score profiles. However, benchmarking suggested neither method is completely reliable. The rise of long-read sequencing technology has increased the availability of complete plasmid assemblies, facilitating comparative plasmid genomic analyses. Nevertheless, available alignment-based comparative genomic tools have limitations: they often do not provide metrics on structural similarity and lack flexibility in terms of input/output options. Therefore, in Chapter 4, I developed a novel alignment-based tool (‘ATCG’) for calculating pairwise average nucleotide identity (ANI), coverage breadth, and structural similarity, while addressing limitations of existing alignment-based tools. Benchmarking demonstrated favourable runtimes and supported the validity of calculated ANI scores. In Chapter 5, besides curating an updated plasmid dataset, I curated sample metadata (e.g. isolation source, geography). Using this metadata and plasmid biological features, I conducted multivariate statistical analyses to determine factors associated with plasmid resistance gene carriage, analysed across major resistance gene classes. The analysis yielded interesting findings, for example, demonstrating that patterns of plasmid antibiotic resistance carriage in livestock and humans reflect known antibiotic usage
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