An observational study of the HIV/AIDS epidemic in Malta

An observational study was carried out comparing the HIV/ AIDS epidemic in Malta to that in South Glamorgan between 1984 and 1992. In both locations the important routes of transmission were use of contaminated blood products and unprotected sex. In both Malta and South Glamorgan 21 AIDS cases had died. The average time of survival from testing HIV positive and death in both locations was 28 months for those who had acquired the virus through blood products. However, for sexually acquired HIV, the average survival in Malta of 9 months contrasted with 33 months in South Glamorgan. Medical care was comparable so this fourfold difference in survival was likely to be due to later presentation of sexually acquired HIV cases in Malta. An HIV knowledge and behaviour survey of young Maltese in a local nightclub found that despite 90% of those questioned knowing that it was possible to contract HIV through unprotected sex, 36% of sexually active men questioned never used a condom.peer-reviewe

Comparison of open-source software for producing directed acyclic graphs

Many software have been developed to assist researchers in drawing directed acyclic graphs (DAGs), with each providing different functionalities and varying usability. We examine four of the most common software to generate DAGs: TikZ, DAGitty, ggdag, and dagR. For each method we provide a general description of the package's background, analysis and visualization capabilities, and user-friendliness. To additionally compare methods, we produce two DAGs in each software, the first featuring a simple confounding structure, while the latter includes one more complex structure with three confounders and a mediator. We provide recommendations for when to use each software depending on the user's needs

M12L8 metallo-supramolecular cube with cyclotriguaiacylene-type ligand: spontaneous resolution of cube and its constituent host ligand.

Data to support study of Ag12L8 metallo-cube and clathrate complexes of tris-(4-methylthiazolyl)cyclotriguaiacylene, where both Ag12L8 cube and clathrate complexes show spontaneous chiral resolution on crystallisation

Testing unit root non-stationarity in the presence of missing data in univariate time series of mobile health studies

The use of digital devices to collect data in mobile health (mHealth) studies introduces a novel application of time series methods, with the constraint of potential data missing at random (MAR) or missing not at random (MNAR). In time series analysis, testing for stationarity is an important preliminary step to inform appropriate later analyses. The augmented Dickey-Fuller (ADF) test was developed to test the null hypothesis of unit root non-stationarity, under no missing data. Beyond recommendations under data missing completely at random (MCAR) for complete case analysis or last observation carry forward imputation, researchers have not extended unit root non-stationarity testing to a context with more complex missing data mechanisms. Multiple imputation with chained equations, Kalman smoothing imputation, and linear interpolation have also been proposed for time series data, however such methods impose constraints on the autocorrelation structure, and thus impact unit root testing. We propose maximum likelihood estimation and multiple imputation using state space model approaches to adapt the ADF test to a context with missing data. We further develop sensitivity analysis techniques to examine the impact of MNAR data. We evaluate the performance of existing and proposed methods across different missing mechanisms in extensive simulations and in their application to a multi-year smartphone study of bipolar patients

An exploration of the impact of working in pairs on the dental clinical learning environment: Students’ views

Introduction: The aims of this study were to explore the undergraduate dental clinical students' experiences and perspectives of paired working in the clinical learning environment. Materials and methods: An interpretivist methodological approach with a socio-cultural lens was used. A stratified purposeful sampling strategy was chosen. Students digitally recorded three audio-diaries using Gibbs' cycle to guide reflection on collabo-rating clinically with a peer. 1:1 semi-structured interviews were held using a topic guide. Inductive thematic data analysis was undertaken.Results: Eight participants were recruited. Main themes related to individual characteristics (motivation, professionalism, knowledge and experience) and relational features (feeling safe, attaching value, positive working relationships) that contributed to effective collaborative partnerships. The social setting is important for learning in the dental clinical environment. Benchmarking is used by students to motivate and reas-sure. Students learnt from their peers, particularly when they felt safe and supported and had developed good relationships. A lesser quality learning experience was high-lighted in the assistant role. Conclusion: Paired working for clinical training was viewed mostly positively. Working with a variety of peers was beneficial and enabled development of interpersonal skills and professionalism. More effective collaborative learning partnerships were de-scribed when students felt they belonged and had affective support. Disadvantages of paired working were noted as reduced hands-on experience, particularly for senior students and when working in the assistant role. Ground rules and setting learning goals to change the mind-set about the assistant role were recommended. Emotional and practical support of students is needed in the clinical setting

The development of two field‐ready reverse transcription loop‐mediated isothermal amplification assays for the rapid detection of Seneca Valley virus 1

Seneca Valley virus 1 (SVV‐1) has been associated with vesicular disease in swine, with clinical signs indistinguishable from those of other notifiable vesicular diseases such as foot‐and‐mouth disease. Rapid and accurate detection of SVV‐1 is central to confirm the disease causing agent, and to initiate the implementation of control processes. The development of rapid, cost‐effective diagnostic assays that can be used at the point of sample collection has been identified as a gap in preparedness for the control of SVV‐1. This study describes the development and bench validation of two reverse transcription loop‐mediated amplification (RT‐LAMP) assays targeting the 5′‐untranslated region (5′‐UTR) and the VP3‐1 region for the detection of SVV‐1 that may be performed at the point of sample collection. Both assays were able to demonstrate amplification of all neat samples diluted 1/100 in negative pig epithelium tissue suspension within 8 min, when RNA was extracted prior to the RT‐LAMP assay, and no amplification was observed for the other viruses tested. Simple sample preparation methods using lyophilized reagents were investigated, to negate the requirement for RNA extraction. Only a small delay in the time to amplification was observed for these lyophilized reagents, with a time from sample receipt to amplification achieved within 12 min. Although diagnostic validation is recommended, these RT‐LAMP assays are highly sensitive and specific, with the potential to be a useful tool in the rapid diagnosis of SVV‐1 in the field

Organic food and farming research needs in the UK:A report on a stakeholder participatory consultation process

During 2005 Defra commissioned a study to identify and analyse issues and aspirations that organic stakeholders felt should be addressed by publicly funded organic food and farming research in the UK. How this was undertaken is presented in this paper. A series of 12 workshops were undertaken with stakeholders throughout the UK. Nearly 300 stakeholders attended the workshops. These workshops used participatory approaches to identify and record the most important issues and aspirations from those attending. The use of a highly participatory style was greatly appreciated by stakeholders. In most cases the interaction between stakeholders worked well and resulted in lively discussions. The workshops have served to open up a useful dialogue between groups of stakeholders who do not normally communicate directly. They have produced a significant number of interesting and challenging issues and aspirations

D2.2 Report on analysis of biographical narratives exploring short- and long-term adaptive behaviour of farmers under various challenges

The Horizon 2020 project Towards Sustainable and Resilient EU Farming Systems (SURE-Farm) defines resilience as maintaining the essential functions of EU farming systems in the face of increasingly complex and volatile economic, social, ecological and institutional risks: Meuwissen (2018) suggests that resilience over time is achieved across the increasingly fundamental attributes of robustness, adaptability and transformability, representing system responses to short, medium and long-term external drivers, respectively. Maxwell (1986) also recognised that external drivers vary significantly in time and space and distinguished four different types of perturbations: noise, shocks, cycles and trends. Analysis of narratives (Rosenthal, 2004; Riessmann, 2008) can be used to enable researchers to gain indepth understanding of the rationale surrounding farmer decision making when faced with drivers of change (e.g. MacDonald et al., 2014), and how farmers manage critical decision points in their farming businesses. This understanding is crucial for developing the tools and policy measures needed to support the sustainability and resilience of European agriculture. We have used personal histories of family farms, and business histories of corporate farms, to identify phases in the separate production, demographic and policy adaptive cycles (and consequences of interactions between them) as they have impacted on the individuals concerned and their business enterprises. Biographical stories were collected from nine to ten narrators (early-, mid- and late-career), in each of five case studies chosen to represent a range of regions and farming systems in Europe. These included large scale family and corporate arable farms in Northeast Bulgaria (BG) and the East of England (UK); dairy farms in Flanders (BE); small-scale perennial crop (hazelnut) farms in central Italy (IT) and high value egg and broiler systems in Southern Sweden (SE). A single question was used to initiate the narrators’ stories, without qualification beforehand, supported only with expressions of interest and encouragement in the first part of the interview, with subsequent exploratory questions devoted to clarifying the internal structure of the narrative. Narratives were transcribed and analysed to identify the drivers and responses to critical decision-making points in the stories. Comparisons across the five regional farming system cases have also been made to generate wider insights into how the narrators responded to different challenges. The drivers leading up to critical decision points in the narratives were grouped according to themes which followed a spectrum ranging from internal (those arising from within the farm system), to external (those acting on the farm system). Internal drivers included health, relationships, intergenerational change, retirement, redundancy. The more intermediate drivers included financial pressures, skills, labour, disasters, land issues, water. External drivers included supply chain factors, markets, technology, policy and regulation. Some drivers and responses were observed to relate to the farmer whilst others related to the farming system. Key findings from cross-narrative analysis distinguished inertia as the predominant response to system challenges, and that incremental changes (or creeping change, as we have termed it) in the system over a long-time frame rather than a definable critical decision point, is widely evident in the narratives. Climate change was not identified as being a driver and was only mentioned at all in two of the 45 narratives. Farmer identity ranged broadly across the narratives with the extremes being represented by those who farmed because it was their vocation, to those who perceived themselves first and foremost as business operators. To an extent, these identities reflected the degree of attachment to land, with the more vocational farmers having a strong attachment to their farmed land (particularly in the Flemish case) and the more business-minded (particularly in Northeast Bulgaria and the East of England) having less attachment. The long-term nature of the hazelnut crop in Central Italy meant that attachment to the land was strong, regardless of farmer identity. Family support, whether perceived as positive or negative by the narrator, was found to influence decision-making, and changing work/life balance expectations, particularly amongst early-career farmers with young families, was also influential. The narratives revealed different approaches to risk alleviation, both within and across case studies. In instances where land availability was not restricted (for example, Northeast Bulgaria, and to some extent, East Anglia), scale enlargement was predominant, but where land was restricted, diversification was the predominant response (for example, in the Flemish narratives). There were strong similarities and distinctive differences across the narrative contexts. Similarities included the dominance of internal drivers, intergenerational change as a major critical decision point, the perception of many external drivers as noise, and more frustration with policy drivers compared with weather events. There were few mentions of insurance by the narrators. The findings indicate that robustness is demonstrated in response to many drivers classified as cycles and shocks, whilst prolonged trends result primarily in adaptation. Transformations were relatively infrequent in the narratives and those identified were not radical in nature. The main policy related conclusions from the study suggest that farming systems are ill-equipped for a rapid move from direct payments to income insurance. They also appear to be unprepared for climate change. Long-term, coherent strategies required for dealing with intergenerational change were not apparent, confirming parallel literature that suggests that legal, social welfare and policy obstacles to farm succession need to be addressed

Prediction of pyrazinamide resistance in Mycobacterium tuberculosis using structure-based machine learning approaches

Background Pyrazinamide is one of four first-line antibiotics used to treat tuberculosis; however, antibiotic susceptibility testing for pyrazinamide is challenging. Resistance to pyrazinamide is primarily driven by genetic variation in pncA, encoding an enzyme that converts pyrazinamide into its active form. Methods We curated a dataset of 664 non-redundant, missense amino acid mutations in PncA with associated high-confidence phenotypes from published studies and then trained three different machine-learning models to predict pyrazinamide resistance. All models had access to a range of protein structural-, chemical- and sequence-based features. Results The best model, a gradient-boosted decision tree, achieved a sensitivity of 80.2% and a specificity of 76.9% on the hold-out test dataset. The clinical performance of the models was then estimated by predicting the binary pyrazinamide resistance phenotype of 4027 samples harbouring 367 unique missense mutations in pncA derived from 24 231 clinical isolates. Conclusions This work demonstrates how machine learning can enhance the sensitivity/specificity of pyrazinamide resistance prediction in genetics-based clinical microbiology workflows, highlights novel mutations for future biochemical investigation, and is a proof of concept for using this approach in other drugs

Haplotype Association Mapping Identifies a Candidate Gene Region in Mice Infected With Staphylococcus aureus

Exposure to Staphylococcus aureus has a variety of outcomes, from asymptomatic colonization to fatal infection. Strong evidence suggests that host genetics play an important role in susceptibility, but the specific host genetic factors involved are not known. The availability of genome-wide single nucleotide polymorphism (SNP) data for inbred Mus musculus strains means that haplotype association mapping can be used to identify candidate susceptibility genes. We applied haplotype association mapping to Perlegen SNP data and kidney bacterial counts from Staphylococcus aureus-infected mice from 13 inbred strains and detected an associated block on chromosome 7. Strong experimental evidence supports the result: a separate study demonstrated the presence of a susceptibility locus on chromosome 7 using consomic mice. The associated block contains no genes, but lies within the gene cluster of the 26-member extended kallikrein gene family, whose members have well-recognized roles in the generation of antimicrobial peptides and the regulation of inflammation. Efficient mixed-model association (EMMA) testing of all SNPs with two alleles and located within the gene cluster boundaries finds two significant associations: one of the three polymorphisms defining the associated block and one in the gene closest to the block, Klk1b11. In addition, we find that 7 of the 26 kallikrein genes are differentially expressed between susceptible and resistant mice, including the Klk1b11 gene. These genes represent a promising set of candidate genes influencing susceptibility to Staphylococcus aureus