Circulating emm types of Streptococcus pyogenes in Scotland: 2011-2015

No abstract available

TAVI: New trials and registries offer further welcome evidence - U.S. CoreValve, CHOICE, and GARY

The introduction of transcatheter aortic valve implantation (TAVI) has resulted in a paradigm shift in the treatment of patients with severe aortic stenosis. Data from the recent U.S CoreValve Trial suggest, for the first time, that TAVI is associated with a significantly higher rate of survival at one year compared to surgical aortic valve replacement (SAVR) in the treatment of high-risk patients affected by severe aortic stenosis. The present review discusses this study and the current evidence about TAVI, for the treatment of severe aortic stenosis, from major trials and real world registries

Learning from innovative practitioners: Evidence for the sustainability and resilience of pasture fed livestock systems

There is an urgent need for transformational change in agriculture to address current and future issues caused by climate change, biodiversity loss and socio-ecological disruption. But change is slow to come and is hindered by a lack of transdisciplinary evidence on potential approaches which take a systems approach. The research described here was co-developed with the Pasture Fed Livestock Association in the UK to objectively evidence their practices. These include producing pasture-based meat from livestock fed on pasture and pasture-based forages alone. This approach sits alongside wider aims of fitting their practices with the ecological conditions on each individual farm to facilitate optimal production and working collaboratively through a forum for sharing knowledge. The research provides strong indications that the PFLA approach to livestock production is resilient and viable, as well as contributing to wider public goods delivery, despite variability within and between farms. It also reveals that learning and adaption of practice (through farmer experience) is central to farming using agro-ecological approaches. This fluidity of practice presents challenges for reductionist approaches to "measuring" agricultural innovations

Multimodal cardiovascular magnetic resonance quantifies regional variation in vascular structure and function in patients with coronary artery disease: Relationships with coronary disease severity

<p>Abstract</p> <p>Background</p> <p>Cardiovascular magnetic resonance (CMR) of the vessel wall is highly reproducible and can evaluate both changes in plaque burden and composition. It can also measure aortic compliance and endothelial function in a single integrated examination. Previous studies have focused on patients with pre-identified carotid atheroma. We define these vascular parameters in patients presenting with coronary artery disease and test their relations to its extent and severity.</p> <p>Methods and Results</p> <p>100 patients with CAD [single-vessel (16%); two-vessel (39%); and three-vessel (42%) non-obstructed coronary arteries (3%)] were studied. CAD severity and extent was expressed as modified Gensini score (mean modified score 12.38 ± 5.3). A majority of carotid plaque was located in the carotid bulb (CB). Atherosclerosis in this most diseased segment correlated modestly with the severity and extent of CAD, as expressed by the modified Gensini score (R = 0.251, P < 0.05). Using the AHA plaque classification, atheroma class also associated with CAD severity (rho = 0.26, P < 0.05). The distal descending aorta contained the greatest plaque, which correlated with the degree of CAD (R = 0.222; P < 0.05), but with no correlation with the proximal descending aorta, which was relatively spared (R = 0.106; P = n. s.). Aortic distensibility varied along its length with the ascending aorta the least distensible segment. Brachial artery FMD was inversely correlated with modified Gensini score (R = -0.278; P < 0.05). In multivariate analysis, distal descending aorta atheroma burden, distensibility of the ascending aorta, carotid atheroma class and FMD were independent predictors of modified Gensini score.</p> <p>Conclusions</p> <p>Multimodal vascular CMR shows regional abnormalities of vascular structure and function that correlate modestly with the degree and extent of CAD.</p

Learning from innovative practitioners: evidence for the sustainability and resilience of pasture fed livestock systems

There is an urgent need for transformational change in agriculture to address current and future issues caused by climate change, biodiversity loss and socio-ecological disruption. But change is slow to come and is hindered by a lack of transdisciplinary evidence on potential approaches which take a systems approach. The research described here was co-developed with the Pasture Fed Livestock Association in the UK to objectively evidence their practices. These include producing pasture-based meat from livestock fed on pasture and pasture-based forages alone. This approach sits alongside wider aims of fitting their practices with the ecological conditions on each individual farm to facilitate optimal production and working collaboratively through a forum for sharing knowledge. The research provides strong indications that the PFLA approach to livestock production is resilient and viable, as well as contributing to wider public goods delivery, despite variability within and between farms. It also reveals that learning and adaption of practice (through farmer experience) is central to farming using agro-ecological approaches. This fluidity of practice presents challenges for reductionist approaches to “measuring” agricultural innovations

Embedding expert opinion in a Bayesian network model to predict wheat yield from spring-summer weather

Wheat yield is highly dependent on weather, Therefore, predicting its effect can improve crop management decisions. Various modelling approaches have been used to predict wheat yield including process-based modelling, statistical models, and machine learning. However, these models typically require a large data set for training or fitting. They often also have a limited ability in capturing the effects of small-scale variability, time, and duration of extreme weather events. Here, we develop a Bayesian Network (BN) model by interviewing experts including farmers, embedding their knowledge from years of experience within a quantitative model. These experts identified the period from the beginning of anthesis to the end of grain filling stage as a critical period and maximum temperature, mean temperature and precipitation as key weather variables for inclusion in the BN. To keep the time input from experts manageable, the conditional probability table for the BN was constructed based on their anticipated impact on the mean yield of different weather conditions. The model predicted the yield in the same or neighbouring class (very low, low, medium, high and very high) as the reported yield with low error rate ranging from 9.1 to 15.2% and, when used to estimate the median predicted yield, R2 ranging from 41 to 52%. Interestingly, model successfully predicted the yield in years 1998, 2007, 2012 and 2020 which had the most extreme weather events. Additionally, the more recent data, from 2012 to 2022 was predicted more accurately, especially 2022 season which was not sown yet when eliciting information and recently added to the testing data. Little difference was observed between the predictions made using model parameters based only the opinion of the farm manager from which the test data originated, and the predictions made using the average opinion of a group of 9 experts. The inclusion of causal variables in the model also provided insight into the experts’ rationale, allowing unexpected results to be explored. This methodology provides a means to rapidly develop a successful predictive model of wheat yield with limited (or no) data using expert understanding. This model could be tuned and updated with data as it becomes available

Learning from innovative practitioners: evidence for the sustainability and resilience of pasture fed livestock systems

There is an urgent need for transformational change in agriculture to address current and future issues caused by climate change, biodiversity loss and socio-ecological disruption. But change is slow to come and is hindered by a lack of transdisciplinary evidence on potential approaches which take a systems approach. The research described here was co-developed with the Pasture Fed Livestock Association in the UK to objectively evidence their practices. These include producing pasture-based meat from livestock fed on pasture and pasture-based forages alone. This approach sits alongside wider aims of fitting their practices with the ecological conditions on each individual farm to facilitate optimal production and working collaboratively through a forum for sharing knowledge. The research provides strong indications that the PFLA approach to livestock production is resilient and viable, as well as contributing to wider public goods delivery, despite variability within and between farms. It also reveals that learning and adaption of practice (through farmer experience) is central to farming using agro-ecological approaches. This fluidity of practice presents challenges for reductionist approaches to “measuring” agricultural innovations