Predicting Invasive Fungal Pathogens Using Invasive Pest Assemblages: Testing Model Predictions in a Virtual World

Predicting future species invasions presents significant challenges to researchers and government agencies. Simply considering the vast number of potential species that could invade an area can be insurmountable. One method, recently suggested, which can analyse large datasets of invasive species simultaneously is that of a self organising map (SOM), a form of artificial neural network which can rank species by establishment likelihood. We used this method to analyse the worldwide distribution of 486 fungal pathogens and then validated the method by creating a virtual world of invasive species in which to test the SOM. This novel validation method allowed us to test SOM's ability to rank those species that can establish above those that can't. Overall, we found the SOM highly effective, having on average, a 96–98% success rate (depending on the virtual world parameters). We also found that regions with fewer species present (i.e. 1–10 species) were more difficult for the SOM to generate an accurately ranked list, with success rates varying from 100% correct down to 0% correct. However, we were able to combine the numbers of species present in a region with clustering patterns in the SOM, to further refine confidence in lists generated from these sparsely populated regions. We then used the results from the virtual world to determine confidences for lists generated from the fungal pathogen dataset. Specifically, for lists generated for Australia and its states and territories, the reliability scores were between 84–98%. We conclude that a SOM analysis is a reliable method for analysing a large dataset of potential invasive species and could be used by biosecurity agencies around the world resulting in a better overall assessment of invasion risk

UK pneumonectomy outcome study (UKPOS): a prospective observational study of pneumonectomy outcome

<p>Abstract</p> <p>Background</p> <p>In order to assess the short term risks of pneumonectomy for lung cancer in contemporary practice a one year prospective observational study of pneumonectomy outcome was made. Current UK practice for pneumonectomy was observed to note patient and treatment factors associated with major complications.</p> <p>Methods</p> <p>A multicentre, prospective, observational cohort study was performed. All 35 UK thoracic surgical centres were invited to submit data to the study. All adult patients undergoing pneumonectomy for lung cancer between 1 January and 31 December 2005 were included. Patients undergoing pleuropneumonectomy, extended pneumonectomy, completion pneumonectomy following previous lobectomy and pneumonectomy for benign disease, were excluded from the study.</p> <p>The main outcome measure was suffering a major complication. Major complications were defined as: death within 30 days of surgery; treated cardiac arrhythmia or hypotension; unplanned intensive care admission; further surgery or inotrope usage.</p> <p>Results</p> <p>312 pneumonectomies from 28 participating centres were entered. The major complication incidence was: 30-day mortality 5.4%; treated cardiac arrhythmia 19.9%; unplanned intensive care unit admission 9.3%; further surgery 4.8%; inotrope usage 3.5%. Age, American Society of Anesthesiologists physical status ≥ P3, pre-operative diffusing capacity for carbon monoxide (DLCO) and epidural analgesia were collectively the strongest risk factors for major complications. Major complications prolonged median hospital stay by 2 days.</p> <p>Conclusion</p> <p>The 30 day mortality rate was less than 8%, in agreement with the British Thoracic Society guidelines. Pneumonectomy was associated with a high rate of major complications. Age, ASA physical status, DLCO and epidural analgesia appeared collectively most associated with major complications.</p

Optimizing the procedure of grain nutrient predictions in barley via hyperspectral imaging

Hyperspectral imaging enables researchers and plant breeders to analyze various traits of interest like nutritional value in high throughput. In order to achieve this, the optimal design of a reliable calibration model, linking the measured spectra with the investigated traits, is necessary. In the present study we investigated the impact of different regression models, calibration set sizes and calibration set compositions on prediction performance. For this purpose, we analyzed concentrations of six globally relevant grain nutrients of the wild barley population HEB-YIELD as case study. The data comprised 1,593 plots, grown in 2015 and 2016 at the locations Dundee and Halle, which have been entirely analyzed through traditional laboratory methods and hyperspectral imaging. The results indicated that a linear regression model based on partial least squares outperformed neural networks in this particular data modelling task. There existed a positive relationship between the number of samples in a calibration model and prediction performance, with a local optimum at a calibration set size of ~40% of the total data. The inclusion of samples from several years and locations could clearly improve the predictions of the investigated nutrient traits at small calibration set sizes. It should be stated that the expansion of calibration models with additional samples is only useful as long as they are able to increase trait variability. Models obtained in a certain environment were only to a limited extent transferable to other environments. They should therefore be successively upgraded with new calibration data to enable a reliable prediction of the desired traits. The presented results will assist the design and conceptualization of future hyperspectral imaging projects in order to achieve reliable predictions. It will in general help to establish practical applications of hyperspectral imaging systems, for instance in plant breeding concepts

Etoricoxib - preemptive and postoperative analgesia (EPPA) in patients with laparotomy or thoracotomy - design and protocols

<p>Abstract</p> <p>Background and Objective</p> <p>Our objective was to report on the design and essentials of the <it>Etoricoxib </it>protocol<it>- Preemptive and Postoperative Analgesia (EPPA) </it>Trial, investigating whether preemptive analgesia with cox-2 inhibitors is more efficacious than placebo in patients who receive either laparotomy or thoracotomy.</p> <p>Design and Methods</p> <p>The study is a 2 × 2 factorial armed, double blinded, bicentric, randomised placebo-controlled trial comparing (a) etoricoxib and (b) placebo in a pre- and postoperative setting. The total observation period is 6 months. According to a power analysis, 120 patients scheduled for abdominal or thoracic surgery will randomly be allocated to either the preemptive or the postoperative treatment group. These two groups are each divided into two arms. Preemptive group patients receive etoricoxib prior to surgery and either etoricoxib again or placebo postoperatively. Postoperative group patients receive placebo prior to surgery and either placebo again or etoricoxib after surgery (2 × 2 factorial study design). The Main Outcome Measure is the cumulative use of morphine within the first 48 hours after surgery (measured by patient controlled analgesia PCA). Secondary outcome parameters include a broad range of tests including sensoric perception and genetic polymorphisms.</p> <p>Discussion</p> <p>The results of this study will provide information on the analgesic effectiveness of etoricoxib in preemptive analgesia and will give hints on possible preventive effects of persistent pain.</p> <p>Trial registration</p> <p>NCT00716833</p

At the coalface and the cutting edge: general practitioners’ accounts of the rewards of engaging with HIV medicine

The interviews we conducted with GPs suggest that an engagement with HIV medicine enables clinicians to develop strong and long-term relationships with and expertise about the care needs of people living with HIV ‘at the coalface’, while also feeling connected with a broader network of medical practitioners and other professionals concerned with and contributing to the ever-changing world of science: ‘the cutting edge’. The general practice HIV prescriber is being modelled here as the interface between these two worlds, offering a rewarding opportunity for general practitioners to feel intimately connected to both community needs and scientific change

A turbulent decade for NSAIDs: update on current concepts of classification, epidemiology, comparative efficacy, and toxicity

Non-steroidal anti-inflammatory drugs (NSAIDs) represent a diverse class of drugs and are among the most commonly used analgesics for arthritic pain worldwide, though long-term use is associated with a spectrum of adverse effects. The introduction of cyclooxygenase-2-selective NSAIDs early in the last decade offered an alternative to traditional NSAIDs with similar efficacy and improved gastrointestinal tolerability; however, emerging concerns about cardiovascular safety resulted in the withdrawal of two agents (rofecoxib and valdecoxib) in the mid-2000s and, subsequently, in an overall reduction in NSAID use. It is now understood that all NSAIDs are associated with some varying degree of gastrointestinal and cardiovascular risk. Guidelines still recommend their use, but little is known of how patients use these agents. While strategies and guidelines aimed at reducing NSAID-associated complications exist, there is a need for evidence-based algorithms combining cardiovascular and gastrointestinal factors that can be used to aid treatment decisions at an individual patient level

Using C. elegans to decipher the cellular and molecular mechanisms underlying neurodevelopmental disorders

Prova tipográfica (uncorrected proof)Neurodevelopmental disorders such as epilepsy, intellectual disability (ID), and autism spectrum disorders (ASDs) occur in over 2 % of the population, as the result of genetic mutations, environmental factors, or combination of both. In the last years, use of large-scale genomic techniques allowed important advances in the identification of genes/loci associated with these disorders. Nevertheless, following association of novel genes with a given disease, interpretation of findings is often difficult due to lack of information on gene function and effect of a given mutation in the corresponding protein. This brings the need to validate genetic associations from a functional perspective in model systems in a relatively fast but effective manner. In this context, the small nematode, Caenorhabditis elegans, presents a good compromise between the simplicity of cell models and the complexity of rodent nervous systems. In this article, we review the features that make C. elegans a good model for the study of neurodevelopmental diseases. We discuss its nervous system architecture and function as well as the molecular basis of behaviors that seem important in the context of different neurodevelopmental disorders. We review methodologies used to assess memory, learning, and social behavior as well as susceptibility to seizures in this organism. We will also discuss technological progresses applied in C. elegans neurobiology research, such as use of microfluidics and optogenetic tools. Finally, we will present some interesting examples of the functional analysis of genes associated with human neurodevelopmental disorders and how we can move from genes to therapies using this simple model organism.The authors would like to acknowledge Fundação para a Ciência e Tecnologia (FCT) (PTDC/SAU-GMG/112577/2009). AJR and CB are recipients of FCT fellowships: SFRH/BPD/33611/2009 and SFRH/BPD/74452/2010, respectively

Sex differences in cardiovascular complications and mortality in hospital patients with covid-19: registry based observational study

Objective To assess whether the risk of cardiovascular complications of covid-19 differ between the sexes and to determine whether any sex differences in risk are reduced in individuals with pre-existing cardiovascular disease. Design Registry based observational study. Setting 74 hospitals across 13 countries (eight European) participating in CAPACITY-COVID (Cardiac complicAtions in Patients With SARS Corona vIrus 2 regisTrY), from March 2020 to May 2021 Participants All adults (aged ≥18 years), predominantly European, admitted to hospital with highly suspected covid-19 disease or covid-19 disease confirmed by positive laboratory test results (n=11 167 patients). Main outcome measures Any cardiovascular complication during admission to hospital. Secondary outcomes were in-hospital mortality and individual cardiovascular complications with ≥20 events for each sex. Logistic regression was used to examine sex differences in the risk of cardiovascular outcomes, overall and grouped by pre-existing cardiovascular disease. Results Of 11 167 adults (median age 68 years, 40% female participants) included, 3423 (36% of whom were female participants) had pre-existing cardiovascular disease. In both sexes, the most common cardiovascular complications were supraventricular tachycardias (4% of female participants, 6% of male participants), pulmonary embolism (3% and 5%), and heart failure (decompensated or de novo) (2% in both sexes). After adjusting for age, ethnic group, pre-existing cardiovascular disease, and risk factors for cardiovascular disease, female individuals were less likely than male individuals to have a cardiovascular complication (odds ratio 0.72, 95% confidence interval 0.64 to 0.80) or die (0.65, 0.59 to 0.72). Differences between the sexes were not modified by pre-existing cardiovascular disease; for the primary outcome, the female-to-male ratio of the odds ratio in those without, compared with those with, pre-existing cardiovascular disease was 0.84 (0.67 to 1.07). Conclusions In patients admitted to hospital for covid-19, female participants were less likely than male participants to have a cardiovascular complication. The differences between the sexes could not be attributed to the lower prevalence of pre-existing cardiovascular disease in female individuals. The reasons for this advantage in female individuals requires further research