Community-based trial of screening for Chlamydia trachomatis to prevent pelvic inflammatory disease: the POPI (prevention of pelvic infection) trial.

BACKGROUND: Pelvic inflammatory disease (PID) is common and can lead to tubal factor infertility, ectopic pregnancy or chronic pelvic pain. Despite major UK government investment in the National Chlamydia Screening Programme, evidence of benefit remains controversial. The main aim of this trial was to investigate whether screening and treatment of chlamydial infection reduced the incidence of PID over 12 months. Secondary aims were to conduct exploratory studies of the role of bacterial vaginosis (BV) in the development of PID and of the natural history of chlamydial infection. DESIGN: Randomised controlled trial with follow up after 12 months. SETTING NON-HEALTHCARE: Common rooms and lecture theatres at 20 universities and further education colleges in Greater London. PARTICIPANTS: 2500 sexually active female students were asked to complete a questionnaire on sexual health and provide self-administered vaginal swabs and smears. INTERVENTION: Vaginal swabs from intervention women were tested for chlamydia by polymerase chain reaction (PCR) and those infected referred for treatment. Vaginal swabs from control women were stored and analysed after a year. Vaginal smears were Gram stained and analysed for BV. MAIN OUTCOME MEASURE: Incidence of clinical PID over 12 months in intervention and control groups. Possible cases of PID will be identified from questionnaires and record searches. Confirmation of the diagnosis will be done by detailed review of medical records by three independent researchers blind to whether the woman is in intervention or control group. TRIAL REGISTRATION: Clinical Trials NCT 00115388

Prediction of relativistic electron flux at geostationary orbit following storms: Multiple regression analysis

Many solar wind and magnetosphere parameters correlate with relativistic electron flux following storms. These include relativistic electron flux before the storm, seed electron flux, solar wind velocity and number density (and their variation), IMF Bz, AE and Kp indices, and ultra low frequency (ULF) and very low frequency (VLF) wave power. However, as all these variables are intercorrelated, we use multiple regression analyses to determine which are the most predictive of flux when other variables are controlled. Using 219 storms (1992-2002), we obtained hourly averaged electron fluxes for outer radiation belt relativistic electrons (>1.5 MeV) and seed electrons (100 keV) from LANL spacecraft (geosynchronous orbit). For each storm, we found the log10 maximum relativistic electron flux 48-120 hours after the end of the main phase of each storm. Each predictor variable was averaged over the 12 hours before the storm, main phase, and the 48 hours following minimum Dst. High levels of flux following storms are best modeled by a set of variables. In decreasing influence, ULF, seed electron flux, Vsw and its variation, and after-storm Bz were the most significant explanatory variables. Kp can be added to the model, but it adds no further explanatory power. Although we included ground-based VLF power from Halley, Antarctica, it shows little predictive ability. We produced predictive models using the coefficients from the regression models, and assessed their effectiveness in predicting novel observations. The correlation between observed values and those predicted by these empirical models ranged from .645 to .795

The prevalence of blinding trachoma in northern states of Sudan.

BACKGROUND: Despite historical evidence of blinding trachoma, there have been no widespread contemporary surveys of trachoma prevalence in the northern states of Sudan. We aimed to conduct district-level surveys in this vast region in order to map the extent of the problem and estimate the need for trachoma control interventions to eliminate blinding trachoma. METHODS AND FINDINGS: Separate, population based cross-sectional surveys were conducted in 88 localities (districts) in 12 northern states of Sudan between 2006 and 2010. Two-stage cluster random sampling with probability proportional to size was used to select the sample. Trachoma grading was done using the WHO simplified grading system. Key prevalence indicators were trachomatous inflammation-follicular (TF) in children aged 1-9 years and trachomatous trichiasis (TT) in adults aged 15 years and above. The sample comprised 1,260 clusters from which 25,624 households were surveyed. A total of 106,697 participants (81.6% response rate) were examined for trachoma signs. TF prevalence was above 10% in three districts and between 5% and 9% in 11 districts. TT prevalence among adults was above 1% in 20 districts (which included the three districts with TF prevalence >10%). The overall number of people with TT in the population was estimated to be 31,072 (lower and upper bounds = 26,125-36,955). CONCLUSION: Trachoma mapping is complete in the northern states of Sudan except for the Darfur States. The survey findings will facilitate programme planning and inform deployment of resources for elimination of trachoma from the northern states of Sudan by 2015, in accordance with the Sudan Federal Ministry of Health (FMOH) objectives

Replacing human interpretation of agricultural land in Afghanistan with a deep convolutional neural network

Afghanistan’s annual opium survey relies upon time-consuming human interpretation of satellite images to map the area of potential poppy cultivation for statistical sample design. Deep Convolutional Neural Networks (CNNs) have shown ground-breaking performance for image classification tasks by encoding local contextual information, in some cases outperforming trained analysts. In this study, we investigate the development of a CNN to automate the classification of agriculture from medium-resolution satellite imagery as an alternative to manual interpretation. The residual network (ResNet50) CNN architecture was trained and validated for delineating the agricultural area using labelled multi-seasonal Disaster Monitoring Constellation (DMC) satellite imagery (32 m) of Helmand and Kandahar provinces. The effect of input image chip size, training sampling strategy, elevation data, and multi-seasonal imagery were investigated. The best-performing single-year classification used an input chip size of 33 × 33 pixels, a targeted sampling strategy and transfer learning, resulting in high overall accuracy (94%). The inclusion of elevation data marginally lowered performance (93%). Multi-seasonal classification achieved an overall accuracy of 89% using the previous two years’ data. Only 25% of the target year’s training samples were necessary to update the model to achieve >94% overall accuracy. A data-driven approach to automate agricultural mask production using CNNs is proposed to reduce the burden of human interpretation. The ability to continually update CNN models with new data has the potential to significantly improve automatic classification of vegetation across year

Hyperspectral imaging for phenotyping plant drought stress and nitrogen interactions using multivariate modelling and machine learning techniques in wh

Accurate detection of drought stress in plants is essential for water use efficiency and agricultural output. Hyperspectral imaging (HSI) provides a non-invasive method in plant phenotyping, allowing the long-term monitoring of plant health due to sensitivity to subtle changes in leaf constituents. The broad spectral range of HSI enables the development of different vegetation indices (VIs) to analyze plant trait responses to multiple stresses, such as the combination of nutrient and drought stresses. However, known VIs may underperform when subjected to multiple stresses. This study presents new VIs in tandem with machine learning models to identify drought stress in wheat plants under varying nitrogen (N) levels. A pot wheat experiment was set up in the glasshouse with four treatments: well-watered high-N (WWHN), well-watered low-N (WWLN), drought-stress high-N (DSHN) and drought-stress low-N (DSLN). In addition to ensuring that plants were watered according to the experiment design, photosynthetic rate (Pn) and stomatal conductance (gs) (which are used to assess plant drought stress) were taken regularly, serving as the ground truth data for this study. The proposed VIs, together with known VIs, were used to train three classification models: support vector machines (SVM), random forest (RF), and deep neural networks (DNN) to classify plants based on their drought status. The proposed VIs achieved more than 0.94 accuracy across all models, and their performance further increased when combined with known VIs. The combined VIs were used to train three regression models to predict the stomatal conductance and photosynthetic rates of plants. The random forest regression model performed best, suggesting that it could be used as a stand-alone tool to forecast gs and Pn and track drought stress in wheat. This study shows that combining hyperspectral data with machine learning can effectively monitor and predict drought stress in crops, especially in varying nitrogen condition

High-temperature performance of ferritic steels in fireside corrosion regimes: temperature and deposits

The paper reports high temperature resistance of ferritic steels in fireside corrosion regime in terms of temperature and deposits aggressiveness. Four candidate power plant steels: 15Mo3, T22, T23 and T91 were exposed under simulated air-fired combustion environment for 1000 h. The tests were conducted at 600, 650 and 700 °C according to deposit-recoat test method. Post-exposed samples were examined via dimensional metrology (the main route to quantify metal loss), and mass change data were recorded to perform the study of kinetic behavior at elevated temperatures. Microstructural investigations using ESEM-EDX were performed in order to investigate corrosion degradation and thickness of the scales. The ranking of the steels from most to the least damage was 15Mo3 > T22 > T23 > T91 in all three temperatures. The highest rate of corrosion in all temperatures occurred under the screening deposit

IP1867B suppresses the insulin-like growth factor 1 receptor (IGF1R) ablating epidermal growth factor receptor inhibitor resistance in adult high grade gliomas

High grade gliomas (HGGs) are aggressive primary brain tumours with local invasive growth and poor clinical prognosis. Clinical outcome is compounded by resistance to standard and novel therapeutics. We have evaluated reformulated aspirin (IP1867B) alone and in combination with conventional and novel anti-aHGG agents. We show that recent biopsy-derived aHGG models were highly resistant to conventional therapeutics although show sensitivity to IP1867B, a reformulated "liquid" aspirin. IP186713 treatment mediated a potent suppression of the IL6/STAT3 and NF-kappa B pathways and observed a significant reduction in EGFR transcription and protein expression. We observed the loss of the insulin-like growth factor 1 and insulin-like growth factor 1 receptor expression at both the transcript and protein level post IP1867B treatment. This increased sensitivity to EGFR inhibitors. In vivo, IP1867B was very well tolerated, had little-to-no gastric lesions versus aspirin and, directed a significant reduction of tumour burden with suppression of EGFR, IGF1 and IGFR1. With EGFR inhibitors, we noted a potent synergistic response in aHGG cells. These data provide a rationale for further investigation of IP1867B with a number of anti-EGFR agents currently being evaluated in the clinic.Brain Tumour ResearchHeadcase Cancer TrustOllie Young FoundationFCT Investigator contract from the Foundation for Science and Technology (FCT), Portugal [IF/00614/2014]FCTPortuguese Foundation for Science and Technology [IF/00614/2014/CP12340006, UID/BIM/04773/2013CBMR1334]Innovate Pharmaceutical

Corrigendum to IP1867B suppresses the insulin-like growth factor 1 receptor (IGF1R) ablating epidermal growth factor receptor inhibitor resistance in adult high grade gliomas (vol 458C, pg 29, 2019)

info:eu-repo/semantics/publishedVersio

Trade unions and precariat in Europe : representative claims

Trade unions have been charged with neglecting labour market ‘outsiders’, while alternative actors have emerged to represent these. In response, unions have stepped up their claim to be representative of all workers, without distinction. We review the theoretical and policy debates on this issue, and argue that representation as such has been under-theorized. We draw on Saward’s concept of ‘representative claims’ to analyse the different grounds for competing assertions of representativeness. We identify four main forms of claims, and illustrate these with empirical examples. We conclude that these different claims are mutually reinforcing in stimulating attention to the outsiders, and in their interaction with institutional settings, they have a performative effect in defining new social actors

Family Resemblances? Ligand Binding and Activation of Family A and B G-Protein-Coupled Receptors Ligand binding and activation of the CGRP receptor

Abstract The receptor for CGRP (calcitonin gene-related peptide) is a heterodimer between a GPCR (G-proteincoupled receptor), CLR (calcitonin receptor-like receptor) and an accessory protein, RAMP1 (receptor activitymodifying protein 1). Models have been produced of RAMP1 and CLR. It is likely that the C-terminus of CGRP interacts with the extracellular N-termini of CLR and RAMP1; the extreme N-terminus of CLR is particularly important and may interact directly with CGRP and also with RAMP1. The N-terminus of CGRP interacts with the TM (transmembrane) portion of the receptor; the second ECL (extracellular loop) is especially important. Receptor activation is likely to involve the relative movements of TMs 3 and 6 to create a G-protein-binding pocket, as in Family A GPCRs. Pro 321 in TM6 appears to act as a pivot. At the base of TMs 2 and 3, Arg 151 , His 155 and Glu 211 may form a loose equivalent of the Family A DRY (Asp-Arg-Tyr) motif. Although the details of this proposed activation mechanism clearly do not apply to all Family B GPCRs, the broad outlines may be conserved