Molecular architecture of the Ub-PCNA/Pol η complex bound to DNA

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Spatial and temporal dynamics of superspreading events in the 2014-2015 West Africa Ebola epidemic

The unprecedented scale of the Ebola outbreak in Western Africa (2014–2015) has prompted an explosion of efforts to understand the transmission dynamics of the virus and to analyze the performance of possible containment strategies. Models have focused primarily on the reproductive numbers of the disease that represent the average number of secondary infections produced by a random infectious individual. However, these population-level estimates may conflate important systematic variation in the number of cases generated by infected individuals, particularly found in spatially localized transmission and superspreading events. Although superspreading features prominently in first-hand narratives of Ebola transmission, its dynamics have not been systematically characterized, hindering refinements of future epidemic predictions and explorations of targeted interventions. We used Bayesian model inference to integrate individual-level spatial information with other epidemiological data of community-based (undetected within clinical-care systems) cases and to explicitly infer distribution of the cases generated by each infected individual. Our results show that superspreaders play a key role in sustaining onward transmission of the epidemic, and they are responsible for a significant proportion (∼61%) of the infections. Our results also suggest age as a key demographic predictor for superspreading. We also show that community-based cases may have progressed more rapidly than those notified within clinical-care systems, and most transmission events occurred in a relatively short distance (with median value of 2.51 km). Our results stress the importance of characterizing superspreading of Ebola, enhance our current understanding of its spatiotemporal dynamics, and highlight the potential importance of targeted control measures

'Pre-endoscopy point of care test (Simtomax- IgA/IgG-Deamidated Gliadin Peptide) for coeliac disease in iron deficiency anaemia: diagnostic accuracy and a cost saving economic model'.

BACKGROUND: International guidelines recommend coeliac serology in iron deficiency anaemia, and duodenal biopsy for those tested positive to detect coeliac disease. However, pre-endoscopy serology is often unavailable, thus committing endoscopists to take routine duodenal biopsies. Some endoscopists consider duodenal biopsy mandatory in anaemia to exclude other pathologies. We hypothesise that using a point of care test at endoscopy could fill this gap, by providing rapid results to target anaemic patients who require biopsies, and save costs by biopsy avoidance. We therefore assessed three key aspects to this hypothesis: 1) the availability of pre-endoscopy serology in anaemia; 2) the sensitivities and cost effectiveness of pre-endoscopy coeliac screening with Simtomax in anaemia; 3) whether other anaemia-related pathologies could be missed by this targeted-biopsy approach. METHODS: Group 1: pre-endoscopy serology availability was retrospectively analysed in a multicentre cohort of 934 anaemic patients at 4 UK hospitals. Group 2: the sensitivities of Simtomax, endomysial and tissue-transglutaminase antibodies were compared in 133 prospectively recruited patients with iron deficiency anaemia attending for a gastroscopy. The sensitivities were measured against duodenal histology as the reference standard in all patients. The cost effectiveness of Simtomax was calculated based on the number of biopsies that could have been avoided compared to an all-biopsy approach. Group 3: the duodenal histology of 153 patients presenting to a separate iron deficiency anaemia clinic were retrospectively reviewed. RESULTS: In group 1, serology was available in 361 (33.8 %) patients. In group 2, the sensitivity and negative predictive value (NPV) were 100 % and 100 % for Simtomax, 96.2 % and 98.9 % for IgA-TTG, and 84.6 % and 96.4 % for EMA respectively. In group 3, the duodenal histology found no causes for anaemia other than coeliac disease. CONCLUSION: Simtomax had excellent diagnostic accuracy in iron deficiency anaemia and was comparable to conventional serology. Duodenal biopsy did not identify any causes other than coeliac disease for iron deficiency anaemia, suggesting that biopsy avoidance in Simtomax negative anaemic patients is unlikely to miss other anaemia-related pathologies. Due to its 100 % NPV, Simtomax could reduce unnecessary biopsies by 66 % if only those with a positive Simtomax were biopsied, potentially saving £3690/100 gastroscopies. TRIAL REGISTRATION: The group 2 study was retrospectively registered with clinicaltrials.gov. Trial registration date: 13(th) July 2016; TRIAL REGISTRATION NUMBER: NCT02834429

Using combined diagnostic test results to hindcast trends of infection from cross-sectional data

Infectious disease surveillance is key to limiting the consequences from infectious pathogens and maintaining animal and public health. Following the detection of a disease outbreak, a response in proportion to the severity of the outbreak is required. It is thus critical to obtain accurate information concerning the origin of the outbreak and its forward trajectory. However, there is often a lack of situational awareness that may lead to over- or under-reaction. There is a widening range of tests available for detecting pathogens, with typically different temporal characteristics, e.g. in terms of when peak test response occurs relative to time of exposure. We have developed a statistical framework that combines response level data from multiple diagnostic tests and is able to ‘hindcast’ (infer the historical trend of) an infectious disease epidemic. Assuming diagnostic test data from a cross-sectional sample of individuals infected with a pathogen during an outbreak, we use a Bayesian Markov Chain Monte Carlo (MCMC) approach to estimate time of exposure, and the overall epidemic trend in the population prior to the time of sampling. We evaluate the performance of this statistical framework on simulated data from epidemic trend curves and show that we can recover the parameter values of those trends. We also apply the framework to epidemic trend curves taken from two historical outbreaks: a bluetongue outbreak in cattle, and a whooping cough outbreak in humans. Together, these results show that hindcasting can estimate the time since infection for individuals and provide accurate estimates of epidemic trends, and can be used to distinguish whether an outbreak is increasing or past its peak. We conclude that if temporal characteristics of diagnostics are known, it is possible to recover epidemic trends of both human and animal pathogens from cross-sectional data collected at a single point in time

Structure of the human dimeric ATM kinase

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The effective reproduction number of pandemic influenza: Prospective estimation

Background: Timely estimation of the transmissibility of a novel pandemic influenza virus was a public health priority in 2009. Methods: We extended methods for prospective estimation of the effective reproduction number (R t) over time in an emerging epidemic to allow for reporting delays and repeated importations. We estimated Rt based on case notifications and hospitalizations associated with laboratory-confirmed pandemic (H1N1) 2009 virus infections in Hong Kong from June through October 2009. Results: Rt declined from around 1.4-1.5 at the start of the local epidemic to around 1.1-1.2 later in the summer, suggesting changes in transmissibility perhaps related to school vacations or seasonality. Estimates of Rt based on hospitalizations of confirmed H1N1 cases closely matched estimates based on case notifications. Conclusion: Real-time monitoring of the effective reproduction number is feasible and can provide useful information to public health authorities for situational awareness and calibration of mitigation strategies. © 2010 by Lippincott Williams & Wilkins.link_to_OA_fulltex

Prospective estimation of the effective reproduction number of pandemic influenza in Hong Kong

This journal issue is the Special Issue: Options for the Control of Influenza VII ... 2010link_to_OA_fulltextOptions for the Control of Influenza VII, Hong Kong SAR, China, 3-7 September 2010. In Influenza and Other Respiratory Viruses, 2011, v. 5, suppl. 1, p. 202-20

Epstein-Barr virus BZLF1 protein impairs accumulation of host DNA damage proteins at damage sites in response to DNA damage

Epstein–Barr virus (EBV) infection is closely associated with several human malignancies including nasopharyngeal carcinoma (NPC). The EBV immediate-early protein BZLF1 is the key mediator that switches EBV infection from latent to lytic forms. The lytic form of EBV infection has been implicated in human carcinogenesis but its molecular mechanisms remain unclear. BZLF1 has been shown to be a binding partner of several DNA damage response (DDR) proteins. Its functions in host DDR remain unknown. Thus, we explore the effects of BZLF1 on cellular response to DNA damage in NPC cells. We found that expression of BZLF1 impaired the binding between RNF8 and MDC1 (mediator of DNA damage checkpoint 1), which in turn interfered with the localization of RNF8 and 53BP1 to the DNA damage sites. The RNF8-53BP1 pathway is important for repair of DNA double-strand breaks and DNA damage-induced G2/M checkpoint activation. Our results showed that, by impairing DNA damage repair as well as abrogating G2/M checkpoint, BZLF1 induced genomic instability and rendered cells more sensitive to ionizing radiation. Moreover, the blockage of 53BP1 and RNF8 foci formation was recapitulated in EBV-infected cells. Taken together, our study raises the possibility that, by causing mis-localization of important DDR proteins, BZLF1 may function as a link between lytic EBV infection and impaired DNA damage repair, thus contributing to the carcinogenesis of EBV-associated human epithelial malignancies

Transmission network reconstruction for foot-and-mouth disease outbreaks incorporating farm-level covariates

Transmission network modelling to infer ‘who infected whom’ in infectious disease outbreaks is a highly active area of research. Outbreaks of foot-and-mouth disease have been a key focus of transmission network models that integrate genomic and epidemiological data. The aim of this study was to extend Lau’s systematic Bayesian inference framework to incorporate additional parameters representing predominant species and numbers of animals held on a farm. Lau’s Bayesian Markov chain Monte Carlo algorithm was reformulated, verified and pseudo-validated on 100 simulated outbreaks populated with demographic data Japan and Australia. The modified model was then implemented on genomic and epidemiological data from the 2010 outbreak of foot-and-mouth disease in Japan, and outputs compared to those from the SCOTTI model implemented in BEAST2. The modified model achieved improvements in overall accuracy when tested on the simulated outbreaks. When implemented on the actual outbreak data from Japan, infected farms that held predominantly pigs were estimated to have five times the transmissibility of infected cattle farms and be 49% less susceptible. The farm-level incubation period was 1 day shorter than the latent period, the timing of the seeding of the outbreak in Japan was inferred, as were key linkages between clusters and features of farms involved in widespread dissemination of this outbreak. To improve accessibility the modified model has been implemented as the R package ‘BORIS’ for use in future outbreaks