Accuracy of routinely-collected healthcare data for identifying motor neurone disease cases: a systematic review

Background: Motor neurone disease (MND) is a rare neurodegenerative condition, with poorly understood aetiology. Large, population-based, prospective cohorts will enable powerful studies of the determinants of MND, provided identification of disease cases is sufficiently accurate. Follow-up in many such studies relies on linkage to routinely-collected health datasets. We systematically evaluated the accuracy of such datasets in identifying MND cases. Methods: We performed an electronic search of MEDLINE, EMBASE, Cochrane Library and Web of Science for studies published between 01/01/1990-16/11/2015 that compared MND cases identified in routinely-collected, coded datasets to a reference standard. We recorded study characteristics and two key measures of diagnostic accuracy—positive predictive value (PPV) and sensitivity. We conducted descriptive analyses and quality assessments of included studies. Results: Thirteen eligible studies provided 13 estimates of PPV and five estimates of sensitivity. Twelve studies assessed hospital and/or death certificate-derived datasets; one evaluated a primary care dataset. All studies were from high income countries (UK, Europe, USA, Hong Kong). Study methods varied widely, but quality was generally good. PPV estimates ranged from 55–92% and sensitivities from 75–93%. The single (UK-based) study of primary care data reported a PPV of 85%. Conclusions: Diagnostic accuracy of routinely-collected health datasets is likely to be sufficient for identifying cases of MND in large-scale prospective epidemiological studies in high income country settings. Primary care datasets, particularly from countries with a widely-accessible national healthcare system, are potentially valuable data sources warranting further investigation

Quantification of DNA-associated proteins inside eukaryotic cells using single-molecule localization microscopy

Development of single-molecule localization microscopy techniques has allowed nanometre scale localization accuracy inside cells, permitting the resolution of ultra-fine cell structure and the elucidation of crucial molecular mechanisms. Application of these methodologies to understanding processes underlying DNA replication and repair has been limited to defined in vitro biochemical analysis and prokaryotic cells. In order to expand these techniques to eukaryotic systems, we have further developed a photo-activated localization microscopy-based method to directly visualize DNA-associated proteins in unfixed eukaryotic cells. We demonstrate that motion blurring of fluorescence due to protein diffusivity can be used to selectively image the DNA-bound population of proteins. We designed and tested a simple methodology and show that it can be used to detect changes in DNA binding of a replicative helicase subunit, Mcm4, and the replication sliding clamp, PCNA, between different stages of the cell cycle and between distinct genetic backgrounds

Accuracy of routinely-collected healthcare data for identifying motor neurone disease cases: a systematic review

Background: Motor neurone disease (MND) is a rare neurodegenerative condition, with poorly understood aetiology. Large, population-based, prospective cohorts will enable powerful studies of the determinants of MND, provided identification of disease cases is sufficiently accurate. Follow-up in many such studies relies on linkage to routinely-collected health datasets. We systematically evaluated the accuracy of such datasets in identifying MND cases. Methods: We performed an electronic search of MEDLINE, EMBASE, Cochrane Library and Web of Science for studies published between 01/01/1990-16/11/2015 that compared MND cases identified in routinely-collected, coded datasets to a reference standard. We recorded study characteristics and two key measures of diagnostic accuracy—positive predictive value (PPV) and sensitivity. We conducted descriptive analyses and quality assessments of included studies. Results: Thirteen eligible studies provided 13 estimates of PPV and five estimates of sensitivity. Twelve studies assessed hospital and/or death certificate-derived datasets; one evaluated a primary care dataset. All studies were from high income countries (UK, Europe, USA, Hong Kong). Study methods varied widely, but quality was generally good. PPV estimates ranged from 55–92% and sensitivities from 75–93%. The single (UK-based) study of primary care data reported a PPV of 85%. Conclusions: Diagnostic accuracy of routinely-collected health datasets is likely to be sufficient for identifying cases of MND in large-scale prospective epidemiological studies in high income country settings. Primary care datasets, particularly from countries with a widely-accessible national healthcare system, are potentially valuable data sources warranting further investigation

Identifying Parkinson's disease and parkinsonism cases using routinely collected healthcare data:A systematic review

BackgroundPopulation-based, prospective studies can provide important insights into Parkinson's disease (PD) and other parkinsonian disorders. Participant follow-up in such studies is often achieved through linkage to routinely collected healthcare datasets. We systematically reviewed the published literature on the accuracy of these datasets for this purpose.MethodsWe searched four electronic databases for published studies that compared PD and parkinsonism cases identified using routinely collected data to a reference standard. We extracted study characteristics and two accuracy measures: positive predictive value (PPV) and/or sensitivity.ResultsWe identified 18 articles, resulting in 27 measures of PPV and 14 of sensitivity. For PD, PPV ranged from 56-90% in hospital datasets, 53-87% in prescription datasets, 81-90% in primary care datasets and was 67% in mortality datasets. Combining diagnostic and medication codes increased PPV. For parkinsonism, PPV ranged from 36-88% in hospital datasets, 40-74% in prescription datasets, and was 94% in mortality datasets. Sensitivity ranged from 15-73% in single datasets for PD and 43-63% in single datasets for parkinsonism.ConclusionsIn many settings, routinely collected datasets generate good PPVs and reasonable sensitivities for identifying PD and parkinsonism cases. However, given the wide range of identified accuracy estimates, we recommend cohorts conduct their own context-specific validation studies if existing evidence is lacking. Further research is warranted to investigate primary care and medication datasets, and to develop algorithms that balance a high PPV with acceptable sensitivity

Hsp70 Inhibits the Nucleation and Elongation of Tau and Sequesters Tau Aggregates with High Affinity.

As a key player of the protein quality control network of the cell, the molecular chaperone Hsp70 inhibits the aggregation of the amyloid protein tau. To date, the mechanism of this inhibition and the tau species targeted by Hsp70 remain unknown. This is partly due to the inherent difficulty of studying amyloid aggregates because of their heterogeneous and transient nature. Here, we used ensemble and single-molecule fluorescence measurements to dissect how Hsp70 counteracts the self-assembly process of the K18 ΔK280 tau variant. We found that Hsp70 blocks the early stages of tau aggregation by suppressing the formation of tau nuclei. Additionally, Hsp70 sequesters oligomers and mature tau fibrils with nanomolar affinity into a protective complex, efficiently neutralizing their ability to damage membranes and seed further tau aggregation. Our results provide novel insights into the molecular mechanisms by which the chaperone Hsp70 counteracts the formation, propagation, and toxicity of tau aggregates.D.K. acknowledges funding from the ERC (grant #669237). M.K. acknowledges fellowships from the Danish research council and the Lundbeck Foundation. F.K. acknowledges funding from the Augustus Newman foundation and the ERC. M.H.H. acknowledges funding from the Herchel Smith Fund and Christ’s College Cambridge. S.D. was funded by a Marie Skłodowska-Curie Individual Fellowship. P.F. acknowledges funding from the Boehringer Ingelheim Fonds and the Studienstiftung des deutschen Volkes. We acknowledge S. Qamar for providing the tau protein used for this study

Bayesian inference of accurate population sizes and FRET efficiencies from single diffusing biomolecules.

It is of significant biophysical interest to obtain accurate intramolecular distance information and population sizes from single-molecule Förster resonance energy transfer (smFRET) data obtained from biomolecules in solution. Experimental methods of increasing cost and complexity are being developed to improve the accuracy and precision of data collection. However, the analysis of smFRET data sets currently relies on simplistic, and often arbitrary methods, for the selection and denoising of fluorescent bursts. Although these methods are satisfactory for the analysis of simple, low-noise systems with intermediate FRET efficiencies, they display systematic inaccuracies when applied to more complex systems. We have developed an inference method for the analysis of smFRET data from solution studies based on rigorous model-based Bayesian techniques. We implement a Monte Carlo Markov chain (MCMC) based algorithm that simultaneously estimates population sizes and intramolecular distance information directly from a raw smFRET data set, with no intermediate event selection and denoising steps. Here, we present both our parametric model of the smFRET process and the algorithm developed for data analysis. We test the algorithm using a combination of simulated data sets and data from dual-labeled DNA molecules. We demonstrate that our model-based method systematically outperforms threshold-based techniques in accurately inferring both population sizes and intramolecular distances.This is the final published version. It's also available from ACS in Analytical Chemistry: http://pubs.acs.org/doi/pdf/10.1021/ac501188r

The Photodissociation of Atmospherically Important Species

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Performing for the provinces: touring theatre troupes and the French political imaginary, 1824-64.

In this thesis I investigate the working practices and artistic conditions of travelling theatre troupes performing sung and spoken repertoire across France during the first half of the nineteenth century. The troupes d’arrondissement performed in a network of provincial towns between 1824 and 1864 as part of the government-managed infrastructure to provide nationwide access to stage culture, established from 1806. The practices of these troupes and the discourse that surrounded their work reveal an artistic environment profoundly shaped by artistic and physical mobility, by local priorities as well as communal theatrical bonds across an arrondissement, and by the demands of a state framework established to oversee and control theatrical experience. These varied conditions offer a new insight into the nineteenth-century French musical and theatrical industry that scholars have so far approached mainly through the capital, with notable exceptions. In my research, I not only resituate the working practices of an overlooked cultural environment within nineteenth-century French musical life, but I also draw attention to the ways that touring directors, performers, critics and administrators brokered theatrical connections between the touring environment, Paris and wider France through their actions and discourse. I argue that itinerant theatre articulated varying spatial relationships between the nation’s peripheries and its centre, but also connections within the peripheries themselves, and links with the wider European theatrical and social landscape. I draw on extensive archival research to examine four case study areas: the Nord/Pas de Calais departments in the north; the Pyrenees in the south-west; western Brittany; and Alsace, on the eastern French border. In Chapter 1, I investigate how ministerial officials conceptualised the shape of, and need for, national theatrical legislation between 1806 and 1824. In Chapter 2, I shed light on the way in which touring theatre established intra-provincial communities and hierarchies between departmental and town administrators, and between provincial critics. In Chapter 3, I focus on the work of touring troupe performers, considering how provincial companies outside Paris provided artistic training that was recognised by theatrical professionals and ministers as part of a national career ladder. In Chapter 4, I examine how the provincial dissemination of grand opéra, and local and central debates about a national artistic framework for performances of this genre embodied and/or resisted centre-periphery dynamics. In Chapter 5, I consider how regional theatrical priorities and identity pushed back against the national theatrical system in a case study of the Franco-German troupe competition in Alsace. Throughout my chapters, I reveal that travelling performances allowed provincial audiences, administrators, critics, directors and performers, to situate themselves at times as a part of, and at times in contrast to, a national community, depending on the geographical context and on the actions and priorities of local agents. In this way, the work of touring troupes, and the local socio-cultural contexts which their work helped to shape, embodied power dynamics and spatial relationships between French spaces during the first half of the nineteenth century