Geochemical studies of contrasing mire types using three phytometers

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Evaluation of nitrate distribution in long-term no tillage corn production under three cover situations and three rates of nitrogen

Nitrate-nitrogen distribution to a depth of 274 cm was evaluated in long term no-tillage corn plots subjected to three nitrogen rates and three cover situations. The soil on the experimental area was mapped Memphis silt loam (fine-silty, mixed, thermic, Typic Halpudalfs). The design of the experiment was randomized block with split-plot arrangement of treatments. The treatments were five levels of nitrogen and five cover situations. Main plots consisted of nitrogen rates and cover crops formed sub-plots. Soil samples were collected at 15 cm depth intervals down to 90 cm and at 30 cm intervals from 91 to 274 cm. Soil solution was obtained using vacuum displacement and nitrates determined by ion chromatography. Corn (Zea mays L.) yield increased with an increase in nitrogen rate. Beyond 168 kg N ha-1 there were no significant differences in corn yield. Below 112 kg N ha-1 yields of corn following hairy vetch (Vicia villosa Roth.) were significantly greater than those following wheat (Triticum aestivum L.) and corn stubble. Nitrate-nitrogen accumulation was highest where 224 kg N ha-1 was applied and where hairy vetch was seeded as a cover crop. The highest NO3 concentration in soil solution occurred in August. Mean NO3-N concentration from vetch, wheat and no cover were 32, 25, and 28 μg mL-1 respectively. The top 30 cm of soil contained 37% of the total NO3-N. At 0 kg N ha-1 there were no significant differences in NO3-N accumulation at each depth interval from 0 to 274 cm. At 168 kg N ha-1, significant NO3-N accumulation occurred at depths below 122 cm. Raising the nitrogen rate to 224 kg ha-1 resulted in no significant differences among depths for NO2-N accumulation for all cover situations. Plots seeded to wheat had the least NO2-N accumulation at all depths. Electrical conductance followed the trend of NO2-N distribution. Soil pH varied greatly in April and was constant in August and November. Significant differences existed among depth intervals for both pH and electrical conductance. No significant differences were observed among cover crops

Challenges for transgene detection in landraces and wild relatives: learning from 15 years of debate over GM maize in Mexico

Maize is one of the world’s five staple cereals and its traditional varieties constitute a global resource critical to future agricultural development. Fifteen years ago, claims that transgenes had spread into traditional landrace maize in Mexico started an international discussion on the scale and significance of transgene flow from genetically modified (GM) crops to centres of crop origin and genetic diversity. The initial discovery of transgenes in landrace maize sparked an intense environmental dispute in which the culture and traditions of indigenous people were seen as threatened by the unchecked spread of biotechnological inventions from multinational corporations. This dispute was reflected in a political and legal battle over the regulatory status of GM crops in Mexico, which continues today as approvals of GM maize for cultivation remain subject to contestation in the courts. These legal, political and environmental disputes have been fanned by the existence of a significant scientific controversy over the methods for GM detection. The use of various approaches and a lack of harmonized methods specific for monitoring and detection of transgenes in landraces has generated both positive and negative results for GM contamination in Mexico over the years. In this paper, we review the peer-reviewed literature on transgene detection in Mexican maize and highlight the challenges associated with transgene detection in landraces. In doing so, we identify the key methodological aspects under dispute and pinpoint the research bottlenecks and needs for building the capacity to effectively monitor transgene escape from GM crops to wild relatives or landraces.publishedVersio

Local monitoring of traffic related air pollution around schools in South-East London

Outdoor air quality (OAQ) presents a significant challenge for public health globally, especially in urban areas, with road traffic acting as the primary contributor to air pollution. Several studies have documented the antagonistic relation between Traffic-Related Air Pollution (TRAP) and the impact on health, especially to vulnerable members of the population, particularly young pupils. Generally, TRAP could restrict the ability of schoolchildren to learn and, more importantly, cause detrimental respiratory disease in their later life. But little is known about the specific exposure of children commuting to school and during the school day and the impact this may have on their overall exposure to pollution at a crucial time in their development. This project has set out to examine the air quality across primary schools in South-East London (Due to their massively increasing amount of re-development and population) and assesses the variability of data found based on their geographic location and surroundings. Nitrogen Dioxide (NO2), PM contaminants (PM 2.5 and 10) were collected with diffusion tubes and portable monitoring equipment for eight schools across three local areas, that are Greenwich, Lewisham and Tower Hamlets. This study first examines the morphological features of the schools surrounding), then utilises two different methods to capture pollutant data. Moreover, comparing the obtained results with existing data from the London Air Quality Network (LAQN) to understand the differences in air quality before and post-pandemic. Most studies in this field have unfortunately neglected human exposure to pollutants and calculated referring to values from fixed monitoring stations. This paper introduces an alternative approach by calculating human exposure to air pollution from real-time data obtained when commuting around selected schools (Driving routes and field walking)

Exploiting the potential of large databases of electronic health records for research using rapid search algorithms and an intuitive query interface.

Objective: UK primary care databases, which contain diagnostic, demographic and prescribing information for millions of patients geographically representative of the UK, represent a significant resource for health services and clinical research. They can be used to identify patients with a specified disease or condition (phenotyping) and to investigate patterns of diagnosis and symptoms. Currently, extracting such information manually is time-consuming and requires considerable expertise. In order to exploit more fully the potential of these large and complex databases, our interdisciplinary team developed generic methods allowing access to different types of user. Materials and methods: Using the Clinical Practice Research Datalink database, we have developed an online user-focused system (TrialViz), which enables users interactively to select suitable medical general practices based on two criteria: suitability of the patient base for the intended study (phenotyping) and measures of data quality. Results: An end-to-end system, underpinned by an innovative search algorithm, allows the user to extract information in near real-time via an intuitive query interface and to explore this information using interactive visualization tools. A usability evaluation of this system produced positive results. Discussion: We present the challenges and results in the development of TrialViz and our plans for its extension for wider applications of clinical research. Conclusions: Our fast search algorithms and simple query algorithms represent a significant advance for users of clinical research databases

How can we enable education staff to recognise and seek help for children and young people with common mental health problems?

Background: Despite rates of mental health difficulties in young people increasing, they are unlikely to seek support themselves. Education staff are uniquely positioned to identify early signs of mental health difficulties in young people and support help-seeking behaviours, allowing them to access appropriate and timely support. Method: A scoping review explored the existing literature regarding education staff’s ability to recognise anxiety and depression in students (4–19-year-olds), without the use of screening tools. This included exploration of methods used and variables evaluated that may influence recognition. An empirical study explored the feasibility of a novel brief online training video. The training aimed to improve secondary school and college staff’s ability to recognise students (11–19-year-olds) with anxiety symptoms, in English education settings, drawing upon the Gateway Provider Model (Stiffman et al. 2004). Results: Twenty-one studies were included in the review. All studies used teacher nomination or a vignette-based approach to evaluate recognition ability in education staff. Staff’s ability to identify anxiety or depression appears somewhat limited but firm conclusions cannot be drawn due to heterogeneity and scarcity of research. The feasibility study found that the brief online training video was feasible and acceptable to education staff who participated, however recruitment feasibility was poor. There were shifts in favour of the training, for recognition, level of severity, level of concern, confidence, and intention to refer, with small to large effect sizes. Conclusions: There is a need to better understand education staff’s ability to recognise and support help-seeking for students with mental health difficulties, such as anxiety and depression. Key gaps in the literature were identified including a lack of research using non-teaching staff and colleges, and the use of standardized measures. Brief online training appears to be a feasible and acceptable method of delivering training for those who participated, however barriers to recruitment need to be explored and overcome. Limitations, implications and future directions for research are discussed

A Cenozoic-style scenario for the end-Ordovician glaciation

The end-Ordovician was an enigmatic interval in the Phanerozoic, known for massive glaciation potentially at elevated CO2 levels, biogeochemical cycle disruptions recorded as large isotope anomalies and a devastating extinction event. Ice-sheet volumes claimed to be twice those of the Last Glacial Maximum paradoxically coincided with oceans as warm as today. Here we argue that some of these remarkable claims arise from undersampling of incomplete geological sections that led to apparent temporal correlations within the relatively coarse resolution capability of Palaeozoic biochronostratigraphy. We examine exceptionally complete sedimentary records from two, low and high, palaeolatitude settings. Their correlation framework reveals a Cenozoic-style scenario including three main glacial cycles and higher-order phenomena. This necessitates revision of mechanisms for the end-Ordovician events, as the first extinction is tied to an early phase of melting, not to initial cooling, and the largest δ13C excursion occurs during final deglaciation, not at the glacial apex