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Populations may potentially respond to climate change in various ways including moving to new areas or alternatively staying where they are and adapting as conditions shift. Traditional laboratory and mesocosm experiments last days to weeks and thus only give a limited picture of thermal adaptation, whereas ocean warming occurring over decades allows the potential for selection of new strains better adapted to warmer conditions. Evidence for adaptation in natural systems is equivocal. We used a 50-year time series comprising of 117 056 samples in the NE Atlantic, to quantify the abundance and distribution of two particularly important and abundant members of the ocean plankton (copepods of the genus Calanus) that play a key trophic role for fisheries. Abundance of C. finmarchicus, a cold-water species, and C. helgolandicus, a warm-water species, were negatively and positively related to sea surface temperature ( SST) respectively. However, the abundance vs. SST relationships for neither species changed over time in a manner consistent with thermal adaptation. Accompanying the lack of evidence for thermal adaptation there has been an unabated range contraction for C. finmarchicus and range expansion for C. helgolandicus. Our evidence suggests that thermal adaptation has not mitigated the impacts of ocean warming for dramatic range changes of these key species and points to continued dramatic climate induced changes in the biology of the oceans. [ABSTRACT FROM AUTHOR]

Abstract: Objective: The development of acute renal failure following cardiac surgery is a rare but devastating complication with high morbidity and mortality. This study aimed to assess the incidence of acute renal failure necessitating continuous renal replacement therapy (CRRT) in patients who required cardiopulmonary bypass, to determine the factors associated with mortality and to evaluate long-term outcome. Methods: Patients who underwent cardiac surgery between October 1997 and 2003 and treated with CRRT were included (n=98). Six patients were then excluded (already in established renal failure pre-operatively) and one patient lost to follow-up. A retrospective analysis was carried out. Results: Overall CRRT was used in 2.9% (92/3172). The mean (SD) age of patients was 68 (10) years. Their mean pre-operative creatinine level and duration of cardiopulmonary bypass were 154 (87)micromol/l and 160 (84)min, respectively. Mean duration from surgery to establishment of CRRT was 50 (42)h. Mean creatinine level prior to hospital discharge was 168 (93)micromol/l. Thirty-day mortality was 42%. Significant risk factors for death were complex procedures (odds ratio=9.9), gastro-intestinal complications (OR=7.2), cross-clamp time over 88min (OR=5.9), re-exploration (OR=4.0) and patients age over 75 years (OR=3.3). Actuarial 1 and 5-year survivals (95% CI) were 53 (43, 63) % and 52 (42, 62) %, respectively. Only 2 (2.2%) patients required long term renal support. Conclusions: Acute renal failure necessitating the use of CRRT is a rare but serious complication post cardiopulmonary bypass. In the long-term, surviving patients are not likely to require further renal support. [Copyright &y& Elsevier]

Studies data on how repeated doses of transmissible spongiform encephalopathies affect the incidence of disease. Analysis of the risk of infection in terms of cumulative and independence hypotheses; Sample size calculations involving exposure data; Examination of incubation period data.

We describe an age-structured mathematical model of the malaria parasite life cycle that uses clinical observations of peripheral parasitaemia to estimate population dynamics of sequestered parasites, which are hidden from the clinical investigator. First, the model was tested on parasite populations cultured in vitro, and was found to account for ∼72% of the variation in that sub-population of parasites that would have been sequestered in vivo. Next, the model was applied to patients undergoing antimalarial therapy. Using individual data sets we found that although the model fitted the peripheral parasite curves very well, unique solutions for the fit could not be obtained; therefore, robust estimates of sequestered parasite dynamics remained unavailable. We conclude that even given detailed data on individual parasitaemia, estimates of sequestered numbers may be difficult to obtain. However, if data on individuals undergoing similar therapy are collected at equal time intervals, some of these problems may be overcome by estimating specific parameters over groups of patients. In this manner we estimated sequestered parasite density in a group of patients sampled at identical time points following antimalarial treatment. Using this approach we found significant relationships between changes in parasite density, age structure and temperature that were not apparent from the analysis of peripheral parasitaemia only. [Copyright &y& Elsevier]

Presents a letter to the editor in response to the article "Estimation of Mutation Rates," by Mike B. Gravenor and Nigel J. Saunders in "Biometrics."

Focuses on the possibility that some sheep in Great Britain were infected during the 1980s after exposure to feed contaminated with bovine spongiform encephalopathy (BSE). Similarity of BSE in sheep to the transmissible spongiform encephalopathy called scrapie; Data of the historical changes in scrapie incidence indicating that it is unlikely that a substantial epidemic of BSE has occurred in the sheep population.

Background dementia may increase care home residents' risk of COVID-19, but there is a lack of evidence on this effect and on interactions with individual and care home-level factors. Methods we created a national cross-sectional retrospective cohort of care home residents in Wales for 1 September to 31 December 2020. Risk factors were analysed using multi-level logistic regression to model the likelihood of SARS-CoV-2 infection and mortality. Results the cohort included 9,571 individuals in 673 homes. Dementia was diagnosed in 5,647 individuals (59%); 1,488 (15.5%) individuals tested positive for SARS-CoV-2. We estimated the effects of age, dementia, frailty, care home size, proportion of residents with dementia, nursing and dementia services, communal space and region. The final model included the proportion of residents with dementia (OR for positive test 4.54 (95% CIs 1.55–13.27) where 75% of residents had dementia compared to no residents with dementia) and frailty (OR 1.29 (95% CIs 1.05–1.59) for severe frailty compared with no frailty). Analysis suggested 76% of the variation was due to setting rather than individual factors. Additional analysis suggested severe frailty and proportion of residents with dementia was associated with all-cause mortality, as was dementia diagnosis. Mortality analyses were challenging to interpret. Discussion whilst individual frailty increased the risk of COVID-19 infection, dementia was a risk factor at care home but not individual level. These findings suggest whole-setting interventions, particularly in homes with high proportions of residents with dementia and including those with low/no individual risk factors may reduce the impact of COVID-19. [ABSTRACT FROM AUTHOR]

Background defining features of the COVID-19 pandemic in many countries were the tragic extent to which care home residents were affected and the difficulty in preventing the introduction and subsequent spread of infection. Management of risk in care homes requires good evidence on the most important transmission pathways. One hypothesised route at the start of the pandemic, prior to widespread testing, was the transfer of patients from hospitals that were experiencing high levels of nosocomial events. Methods we tested the hypothesis that hospital discharge events increased the intensity of care home cases using a national individually linked health record cohort in Wales, UK. We monitored 186,772 hospital discharge events over the period from March to July 2020, tracking individuals to 923 care homes and recording the daily case rate in the homes populated by 15,772 residents. We estimated the risk of an increase in case rates following exposure to a hospital discharge using multi-level hierarchical logistic regression and a novel stochastic Hawkes process outbreak model. Findings in regression analysis, after adjusting for care home size, we found no significant association between hospital discharge and subsequent increases in care home case numbers (odds ratio: 0.99, 95% CI: 0.82, 1.90). Risk factors for increased cases included care home size, care home resident density and provision of nursing care. Using our outbreak model, we found a significant effect of hospital discharge on the subsequent intensity of cases. However, the effect was small and considerably less than the effect of care home size, suggesting the highest risk of introduction came from interaction with the community. We estimated that approximately 1.8% of hospital discharged patients may have been infected. Interpretation there is growing evidence in the UK that the risk of transfer of COVID-19 from the high-risk hospital setting to the high-risk care home setting during the early stages of the pandemic was relatively small. Although access to testing was limited to initial symptomatic cases in each care home at this time, our results suggest that reduced numbers of discharges, selection of patients and action taken within care homes following transfer all may have contributed to the mitigation. The precise key transmission routes from the community remain to be quantified. [ABSTRACT FROM AUTHOR]

Background vaccinations for COVID-19 have been prioritised for older people living in care homes. However, vaccination trials included limited numbers of older people. Aim we aimed to study infection rates of SARS-CoV-2 for older care home residents following vaccination and identify factors associated with increased risk of infection. Study Design and Setting we conducted an observational data-linkage study including 14,104 vaccinated older care home residents in Wales (UK) using anonymised electronic health records and administrative data. Methods we used Cox proportional hazards models to estimate hazard ratios (HRs) for the risk of testing positive for SARS-CoV-2 infection following vaccination, after landmark times of either 7 or 21 days post-vaccination. We adjusted HRs for age, sex, frailty, prior SARS-CoV-2 infections and vaccination type. Results we observed a small proportion of care home residents with positive polymerase chain reaction (tests following vaccination 1.05% (N = 148), with 90% of infections occurring within 28 days. For the 7-day landmark analysis we found a reduced risk of SARS-CoV-2 infection for vaccinated individuals who had a previous infection; HR (95% confidence interval) 0.54 (0.30, 0.95). For the 21-day landmark analysis, we observed high HRs for individuals with low and intermediate frailty compared with those without; 4.59 (1.23, 17.12) and 4.85 (1.68, 14.04), respectively. Conclusions increased risk of infection after 21 days was associated with frailty. We found most infections occurred within 28 days of vaccination, suggesting extra precautions to reduce transmission risk should be taken in this time frame. [ABSTRACT FROM AUTHOR]

Long-term changes in mesozooplankton and phytoplankton populations have been well documented in the North Atlantic region, whereas data for microzooplankton are scarce. This neglected component of the plankton is a vital link in marine food-webs, grazing on smaller flagellates and cyanobacteria and in turn providing food for the larger mesozooplankton. We use the latest tintinnid (Ciliophora, Protista) data from the Continuous Plankton Recorder (CPR) survey in the NE Atlantic and North Sea to examine the phenology, distribution and abundance of this important group of ciliates. Presence/absence data came from 167 122 CPR samples collected between 1960 and 2009 and abundance data from 49 662 samples collected between 1996 and 2009. In the North Atlantic the genus Dictyocysta spp. dominated and Parafavella gigantea showed an increase in abundance around Iceland and Greenland. In the North Sea higher densities of Tintinnopsis spp., Favella serrata and Ptychocylis spp. were found. The presence of tintinnids in CPR samples collected in the North Atlantic has increased over the last 50 years and the seasonal window of high abundance has lengthened. Conversely in the North Sea there has been an overall reduction in abundance. We discuss possible drivers for these long-term changes and point the way forward to more holistic studies that examine how ecosystems, rather than just selected taxa, are responding to climate change. [ABSTRACT FROM PUBLISHER]

The single rate codon model of non-synonymous substitution is ubiquitous in phylogenetic modeling. Indeed, the use of a non-synonymous to synonymous substitution rate ratio parameter has facilitated the interpretation of selection pressure on genomes. Although the single rate model has achieved wide acceptance, we argue that the assumption of a single rate of non-synonymous substitution is biologically unreasonable, given observed differences in substitution rates evident from empirical amino acid models. Some have attempted to incorporate amino acid substitution biases into models of codon evolution and have shown improved model performance versus the single rate model. Here, we show that the single rate model of non-synonymous substitution is easily outperformed by a model with multiple non-synonymous rate classes, yet in which amino acid substitution pairs are assigned randomly to these classes. We argue that, since the single rate model is so easy to improve upon, new codon models should not be validated entirely on the basis of improved model fit over this model. Rather, we should strive to both improve on the single rate model and to approximate the general time-reversible model of codon substitution, with as few parameters as possible, so as to reduce model over-fitting. We hint at how this can be achieved with a Genetic Algorithm approach in which rate classes are assigned on the basis of sequence information content. [ABSTRACT FROM AUTHOR]

Objective. To examine the characteristics and frequency of disease flares in a cohort of people with AS. [ABSTRACT FROM PUBLISHER]

Objective: To examine the characteristics and frequency of disease flares in a cohort of people with AS. Methods: A prospective data set from a randomized controlled trial (RCT) of a probiotic treatment/placebo was utilized to examine disease flares in 134 people with AS. Disease flares were defined as either minor/localized flares (pain/swelling localized to one area with fatigue and stiffness) or major/generalized flares (generalized pain, hot burning joints, muscle spasm, fever, sweating, extreme fatigue and stiffness). Results: One hundred and thirty-four people were followed up for 1216 person follow-up weeks and there were 71.4 flares per 100 person-weeks. Of these, 12 were major/generalized flares and 59.4 were minor/localized flares. People who experienced at least one major/generalized flare during the study period had worse disease during flare-free periods in terms of disease activity, impaired function, self-reported night pain and iritis compared with those who did not experience any major/generalized flares during the study. Major/generalized flares lasted for an average of 2.4 weeks (S.D. 2.7), and were preceded by and followed by a minor/localized flare in 92% (55/60) of cases. Conclusion: Seventy per cent of people with AS felt they had a flare in any given week. Those who experienced major/generalized flares appear to have more severe and active disease even during periods when not in flare, compared with those who do not experience major/generalized flares. These results have implications for the timing of assessments prior to starting anti-TNF therapy and suggest that the presence of major flares may be helpful in identifying patients with severe disease. [ABSTRACT FROM AUTHOR]

Phase variation is a mechanism of ON-OFF switching that is widely utilized by bacterial pathogens. There is currently no standardization to how the rate of phase variation is determined experimentally, and traditional methods of mutation rate estimation may not be appropriate to this process. Here, the history of mutation rate estimation is reviewed, describing the existing methods available. A new mathematical model that can be applied to this problem is also presented. This model specifically includes the confounding factors of back-mutation and the influence of fitness differences between the alternate phenotypes. These are central features of phase variation but are rarely addressed, with the result that some previously estimated phase variation rates may have been significantly overestimated. It is shown that, conversely, the model can also be used to investigate fitness differences if mutation rates are approximately known. In addition, stochastic simulations of the model are used to explore the impact of 'jackpot cultures' on the mutation rate estimation. Using the model, the impact of realistic rates and selection on population structure is investigated. In the absence of fitness differences it is predicted that there will be phenotypic stability over many generations. The rate of phenotypic change within a population is likely, therefore, to be principally determined by selection. A greater insight into the population dynamics of mutation rate processes can be gained if populations are monitored over successive time points. [ABSTRACT FROM AUTHOR]

Background: The population of adult residential care homes has been shown to have high morbidity and mortality in relation to COVID‐19. Methods: We examined 3115 hospital discharges to a national cohort of 1068 adult care homes and subsequent outbreaks of COVID‐19 occurring between 22 February and 27 June 2020. A Cox proportional hazards regression model was used to assess the impact of time‐dependent exposure to hospital discharge on incidence of the first known outbreak, over a window of 7‐21 days after discharge, and adjusted for care home characteristics, including size and type of provision. Results: A total of 330 homes experienced an outbreak, and 544 homes received a discharge over the study period. Exposure to hospital discharge was not associated with a significant increase in the risk of a new outbreak (hazard ratio 1.15, 95% CI 0.89, 1.47, P =.29) after adjusting for care home characteristics. Care home size was the most significant predictor. Hazard ratios (95% CI) in comparison with homes of <10 residents were as follows: 3.40 (1.99, 5.80) for 10‐24 residents; 8.25 (4.93, 13.81) for 25‐49 residents; and 17.35 (9.65, 31.19) for 50+ residents. When stratified for care home size, the outbreak rates were similar for periods when homes were exposed to a hospital discharge, in comparison with periods when homes were unexposed. Conclusion: Our analyses showed that large homes were at considerably greater risk of outbreaks throughout the epidemic, and after adjusting for care home size, a discharge from hospital was not associated with a significant increase in risk. [ABSTRACT FROM AUTHOR]

Although inequalities in health and socioeconomic status have an important influence on childhood educational performance, the interactions between these multiple factors relating to variation in educational outcomes at micro-level is unknown, and how to evaluate the many possible interactions of these factors is not well established. This paper aims to examine multi-dimensional deprivation factors and their impact on childhood educational outcomes at micro-level, focusing on geographic areas having widely different disparity patterns, in which each area is characterised by six deprivation domains (Income, Health, Geographical Access to Services, Housing, Physical Environment, and Community Safety). Traditional health statistical studies tend to use one global model to describe the whole population for macro-analysis. In this paper, we combine linked educational and deprivation data across small areas (median population of 1500), then use a local modelling technique, the Takagi-Sugeno fuzzy system, to predict area educational outcomes at ages 7 and 11. We define two new metrics, “Micro-impact of Domain” and “Contribution of Domain”, to quantify the variations of local impacts of multidimensional factors on educational outcomes across small areas. The two metrics highlight differing priorities. Our study reveals complex multi-way interactions between the deprivation domains, which could not be provided by traditional health statistical methods based on single global model. We demonstrate that although Income has an expected central role, all domains contribute, and in some areas Health, Environment, Access to Services, Housing and Community Safety each could be the dominant factor. Thus the relative importance of health and socioeconomic factors varies considerably for different areas, depending on the levels of each of the other factors, and therefore each component of deprivation must be considered as part of a wider system. Childhood educational achievement could benefit from policies and intervention strategies that are tailored to the local geographic areas' profiles. [ABSTRACT FROM AUTHOR]

The Takagi-Sugeno (TS) fuzzy rule system is a widely used data mining technique, and is of particular use in the identification of non-linear interactions between variables. However the number of rules increases dramatically when applied to high dimensional data sets (the curse of dimensionality). Few robust methods are available to identify important rules while removing redundant ones, and this results in limited applicability in fields such as epidemiology or bioinformatics where the interaction of many variables must be considered. Here, we develop a new parsimonious TS rule system. We propose three statistics: R, L, and v-values, to rank the importance of each TS rule, and a forward selection procedure to construct a final model. We use our method to predict how key components of childhood deprivation combine to influence educational achievement outcome. We show that a parsimonious TS model can be constructed, based on a small subset of rules, that provides an accurate description of the relationship between deprivation indices and educational outcomes. The selected rules shed light on the synergistic relationships between the variables, and reveal that the effect of targeting specific domains of deprivation is crucially dependent on the state of the other domains. Policy decisions need to incorporate these interactions, and deprivation indices should not be considered in isolation. The TS rule system provides a basis for such decision making, and has wide applicability for the identification of non-linear interactions in complex biomedical data. [ABSTRACT FROM AUTHOR]

Cholera is an acute diarrheal illness caused by Vibrio cholerae and occurs as widespread epidemics in Africa. In 2005, there were 31,719 cholera cases, with 458 deaths in the Republic of Senegal. We retrospectively investigated the climate origin of the devastating floods in mid-August 2005, in the Dakar Region of Senegal and the subsequent outbreak of cholera along with the pattern of cholera outbreaks in three other regions of that country. We compared rainfall patterns between 2002 and 2005 and the relationship between the sea surface temperature (SST) gradient in the tropical Atlantic Ocean and precipitation over Senegal for 2005. Results showed a specific pattern of rainfall throughout the Dakar region during August, 2005, and the associated rainfall anomaly coincided with an exacerbation of the cholera epidemic. Comparison of rainfall and epidemiological patterns revealed that the temporal dynamics of precipitation, which was abrupt and heavy, was presumably the determining factor. Analysis of the SST gradient showed that the Atlantic Ocean SST variability in 2005 differed from that of 2002 to 2004, a result of a prominent Atlantic meridional mode. The influence of this intense precipitation on cholera transmission over a densely populated and crowded region was detectable for both Dakar and Thiès, Senegal. Thus, high resolution rainfall forecasts at subseasonal time scales should provide a way forward for an early warning system in Africa for cholera and, thereby, trigger epidemic preparedness. Clearly, attention must be paid to both natural and human induced environmental factors to devise appropriate action to prevent cholera and other waterborne disease epidemics in the region. [ABSTRACT FROM AUTHOR]

Background: Graduate entry medicine raises new questions about the suitability of students with different backgrounds. We examine this, and the broader issue of effectiveness of selection and assessment procedures. Methods: The data included background characteristics, academic record, interview score and performance in pre-clinical modular assessment for two years intake of graduate entry medical students. Exploratory factor analysis is a powerful method for reducing a large number of measures to a smaller group of underlying factors. It was used here to identify patterns within and between the selection and performance data. Principal Findings: Basic background characteristics were of little importance in predicting exam success. However, easily interpreted components were detected within variables comprising the 'selection' and 'assessment' criteria. Three selection components were identified ('Academic', 'GAMSAT', 'Interview') and four assessment components ('General Exam', 'Oncology', 'OSCE', 'Family Case Study'). There was a striking lack of relationships between most selection and performance factors. Only 'General Exam' and 'Academic' showed a correlation (Pearson's r = 0.55, p<0.001). Conclusions: This study raises questions about methods of student selection and their effectiveness in predicting performance and assessing suitability for a medical career. Admissions tests and most exams only confirmed previous academic achievement, while interview scores were not correlated with any consequent assessment. [ABSTRACT FROM AUTHOR]

The relationship between toxic marine microalgae species and climate change has become a high profile and well discussed topic in recent years, with research focusing on the possible future impacts of changing hydrological conditions on Harmful Algal Bloom (HAB) species around the world. However, there is very little literature concerning the epidemiology of these species on marine organisms and human health. Here, we examine the current state of toxic microalgae species around the UK, in two ways: first we describe the key toxic syndromes and gather together the disparate reported data on their epidemiology from UK records and monitoring procedures. Secondly, using NHS hospital admissions and GP records from Wales, we attempt to quantify the incidence of shellfish poisoning from an independent source. We show that within the UK, outbreaks of shellfish poisoning are rare but occurring on a yearly basis in different regions and affecting a diverse range of molluscan shellfish and other marine organisms. We also show that the abundance of a species does not necessarily correlate to the rate of toxic events. Based on routine hospital records, the numbers of shellfish poisonings in the UK are very low, but the identification of the toxin involved, or even a confirmation of a poisoning event is extremely difficult to diagnose. An effective shellfish monitoring system, which shuts down aquaculture sites when toxins exceed regularity limits, has clearly prevented serious impact to human health, and remains the only viable means of monitoring the potential threat to human health. However, the closure of these sites has an adverse economic impact, and the monitoring system does not include all toxic plankton. The possible geographic spreading of toxic microalgae species is therefore a concern, as warmer waters in the Atlantic could suit several species with southern biogeographical affinities enabling them to occupy the coastal regions of the UK, but which are not yet monitored or considered to be detrimental. [ABSTRACT FROM AUTHOR]

Species that have temperature-dependent sex determination (TSD) often produce highly skewed offspring sex ratios contrary to long-standing theoretical predictions. This ecological enigma has provoked concern that climate change may induce the production of single-sex generations and hence lead to population extirpation. All species of sea turtles exhibit TSD, many are already endangered, and most already produce sex ratios skewed to the sex produced at warmer temperatures (females). We tracked male loggerhead turtles (Caretta caretta ) from Zakynthos, Greece, throughout the entire interval between successive breeding seasons and identified individuals on their breeding grounds, using photoidentification, to determine breeding periodicity and operational sex ratios. Males returned to breed at least twice as frequently as females. We estimated that the hatchling sex ratio of 70:30 female to male for this rookery will translate into an overall operational sex ratio (OSR) (i.e., ratio of total number of males vs females breeding each year) of close to 50:50 female to male. We followed three male turtles for between 10 and 12 months during which time they all traveled back to the breeding grounds. Flipper tagging revealed the proportion of females returning to nest after intervals of 1, 2, 3, and 4 years were 0.21, 0.38, 0.29, and 0.12, respectively (mean interval 2.3 years). A further nine male turtles were tracked for short periods to determine their departure date from the breeding grounds. These departure dates were combined with a photoidentification data set of 165 individuals identified on in-water transect surveys at the start of the breeding season to develop a statistical model of the population dynamics. This model produced a maximum likelihood estimate that males visit the breeding site 2.6 times more often than females (95%CI 2.1, 3.1), which was consistent with the data from satellite tracking and flipper tagging. Increased frequency of male breeding will help ameliorate female-biased hatchling sex ratios. Combined with the ability of males to fertilize the eggs of many females and for females to store sperm to fertilize many clutches, our results imply that effects of climate change on the viability of sea turtle populations are likely to be less acute than previously suspected. [ABSTRACT FROM AUTHOR]

Codon models of evolution have facilitated the interpretation of selective forces operating on genomes. These models, however, assume a single rate of non-synonymous substitution irrespective of the nature of amino acids being exchanged. Recent developments have shown that models which allow for amino acid pairs to have independent rates of substitution offer improved fit over single rate models. However, these approaches have been limited by the necessity for large alignments in their estimation. An alternative approach is to assume that substitution rates between amino acid pairs can be subdivided into K rate classes, dependent on the information content of the alignment. However, given the combinatorially large number of such models, an efficient model search strategy is needed. Here we develop a Genetic Algorithm (GA) method for the estimation of such models. A GA is used to assign amino acid substitution pairs to a series of K rate classes, where K is estimated from the alignment. Other parameters of the phylogenetic Markov model, including substitution rates, character frequencies and branch lengths are estimated using standard maximum likelihood optimization procedures. We apply the GA to empirical alignments and show improved model fit over existing models of codon evolution. Our results suggest that current models are poor approximations of protein evolution and thus gene and organism specific multi-rate models that incorporate amino acid substitution biases are preferred. We further anticipate that the clustering of amino acid substitution rates into classes will be biologically informative, such that genes with similar functions exhibit similar clustering, and hence this clustering will be useful for the evolutionary fingerprinting of genes. [ABSTRACT FROM AUTHOR]

Background: To develop a population-based cohort of people with ankylosing spondylitis (AS) in Wales using (1) secondary care clinical datasets, (2) patient-derived questionnaire data and (3) routinely-collected information in order to examine disease history and the health economic cost of AS. Methods: This data model will include and link (1) secondary care clinician datasets (i.e. electronic patient notes from the rheumatologist) (2) patient completed questionnaires (giving information on disease activity, medication, function, quality of life, work limitations and health service utilisation) and (3) a broad range of routinely collected data (including; GP records, in-patient hospital admission data, emergency department data, laboratory/pathology data and social services databases). The protocol involves the use of a unique and powerful data linkage system which allows datasets to be interlinked and to complement each other. Discussion: This cohort can integrate patient supplied, primary and secondary care data into a unified data model. This can be used to study a range of issues such as; the true economic costs to the health care system and the patient, factors associated with the development of severe disease, long term adverse events of new and existing medication and to understand the disease history of this condition. It will benefit patients, clinicians and health care managers. This study forms a pilot project for the use of routine data/patient data linked cohorts for other chronic conditions. [ABSTRACT FROM AUTHOR]

Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1) are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and detection of novel variants, e.g., circulating recombinant forms in HIV-1. A number of conceptually and technically different techniques have been proposed for determining the subtype of a query sequence, but there is not a universally optimal approach. We present a model-based phylogenetic method for automatically subtyping an HIV-1 (or other viral or bacterial) sequence, mapping the location of breakpoints and assigning parental sequences in recombinant strains as well as computing confidence levels for the inferred quantities. Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL) procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. We applied SCUEAL to all available polymerase (pol) sequences from two large databases, the Stanford Drug Resistance database and the UK HIV Drug Resistance Database. Comparing with subtypes which had previously been assigned revealed that a minor but substantial (≈5%) fraction of pure subtype sequences may in fact be within- or inter-subtype recombinants. A free implementation of SCUEAL is provided as a module for the HyPhy package and the Datamonkey web server. Our method is especially useful when an accurate automatic classification of an unknown strain is desired, and is positioned to complement and extend faster but less accurate methods. Given the increasingly frequent use of HIV subtype information in studies focusing on the effect of subtype on treatment, clinical outcome, pathogenicity and vaccine design, the importance of accurate, robust and extensible subtyping procedures is clear. [ABSTRACT FROM AUTHOR]

The entire sheep flock in the UK has been threatened with slaughter if BSE is found in farmed sheep, largely on the grounds that an epidemic of BSE in sheep could be harder to contain than was the case for cattle, and that lamb could present a greater risk to consumers than beef. However, identifying BSE in a sheep is not straightforward, because of its similarities to the related disease, scrapie. Here, we review the likelihood that any UK sheep have BSE, how they might have got it, how a case could be identified and what the Government is doing in terms of surveillance and possible control methods. [Copyright &y& Elsevier]

Introduction: Statin treatment reduces cardiovascular morbidity and mortality in those with and at risk of cardiovascular disease (CVD) and is endorsed in all major clinical guidelines for the prevention of CVD. Despite the weight of high quality evidence supporting benefits of treatment versus relatively rare serious side effects, the use of statins remains variable in clinical practice with high discontinuation rates reported for a treatment intended to be life-long. Our objectives were to determine (i) the rate of discontinuation of statin prescription (attrition) post-PCI, (ii) clinical factors associated with attrition, (iii) the risk of adverse events associated with attrition. Methods: We studied 3,478 patients (2011-2105) who were prescribed a statin post-Percutaneous Coronary Intervention (PCI) within a retrospective observational cohort using linked anonymised primary care and hospital health record data, including any record of ongoing statin prescription. Relationships between attrition and major clinical outcomes (death, acute coronary syndromes, revascularisation or stroke) were evaluated over 18-month follow up. Results: Cumulative attrition of statin prescription in the first six quarters post-PCI was 2.4%, 4.7%, 6.6%, 8.3%, 9.6% and 11.2% respectively. Heart failure and age ≥70y were independent predictors of attrition. 587 (16.9%) patients had an outcome-event during the follow up period. In a time-dependent multiple Cox regression model, statin attrition (HR=6.65, p <0.001), hypertension (HR=1.29, p=0.004), diabetes (HR=1.27, p= 0.01), previous MI (HR=1.42, p <0.001), ischaemic stroke (HR=1.42 p=0.005), thromboembolism (HR= 1.89, p= 0.038), Atrial Fibrillation (HR=1.30, p=0.018) and age ≤49 (HR=1.73, p=0.002) and age ≥70 (HR=1.88, p <0.001) vs reference age 50-59y were independently associated with adverse clinical outcomes. Conclusions: Attrition from statin therapy is lower than previously reported in the first 18-months post-PCI. However, despite this low rate of statin attrition, it is still independently associated with a high risk of adverse outcomes. [ABSTRACT FROM AUTHOR]

The relationship between toxic marine microalgae species and climate change has become a high profile and well discussed topic in recent years, with research focusing on the possible future impacts of changing hydrological conditions on Harmful Algal Bloom (HAB) species around the world. However, there is very little literature concerning the epidemiology of these species on marine organisms and human health. Here, we examine the current state of toxic microalgae species around the UK, in two ways: first we describe the key toxic syndromes and gather together the disparate reported data on their epidemiology from UK records and monitoring procedures. Secondly, using NHS hospital admissions and GP records from Wales, we attempt to quantify the incidence of shellfish poisoning from an independent source. We show that within the UK, outbreaks of shellfish poisoning are rare but occurring on a yearly basis in different regions and affecting a diverse range of molluscan shellfish and other marine organisms. We also show that the abundance of a species does not necessarily correlate to the rate of toxic events. Based on routine hospital records, the numbers of shellfish poisonings in the UK are very low, but the identification of the toxin involved, or even a confirmation of a poisoning event is extremely difficult to diagnose. An effective shellfish monitoring system, which shuts down aquaculture sites when toxins exceed regularity limits, has clearly prevented serious impact to human health, and remains the only viable means of monitoring the potential threat to human health. However, the closure of these sites has an adverse economic impact, and the monitoring system does not include all toxic plankton. The possible geographic spreading of toxic microalgae species is therefore a concern, as warmer waters in the Atlantic could suit several species with southern biogeographical affinities enabling them to occupy the coastal regions of the UK, but which are not yet monitored or considered to be detrimental. [ABSTRACT FROM AUTHOR]