Factors affecting accumulation of summer grass for winter standing feed in the high country

A 0.5 ha 6-year trial compared 6 grass species x 4 N fertiliser rates x 2 times of closing for summer-saved standing winter feed. The pre-winter yields averaged 3.4 t DM/ha from November, closing with a high browntop/sweet vernal component, as compared with 1.7 t DM/ha from December closings with a low browntop/sweet vernal component. Grasslands Kara cocksfoot was the highest yielding cultivar, followed by Grasslands Apanui cocksfoot, Grasslands Wana cocksfoot, Grasslands Roa tall fescue, Grasslands Nui perennial ryegrass and Grasslands Maru phalaris, with decreasing proportions of sown grass. Nitrogen fertiliser had a limited effect on prewinter yields but did have a carry-over effect into spring yields

Distribution and associations of vision-related quality of life and functional vision of children with visual impairment.

BACKGROUND: Patient-reported outcome measures (PROMs) are increasingly used in paediatric ophthalmology. However, little is known about the distribution of PROM scores among children and young people with visual impairment. AIM: To investigate the distributions and predictors of scores on the VQoL_CYP (measuring vision-related quality of life) and FVQ_CYP (measuring functional vision). METHODS: Children and young people aged 8-18 years, with visual impairment/blindness (logarithm of the minimum angle of resolution (LogMAR) worse than 0.48 in the better eye, and/or eligible visual field restriction) completed the VQoL_CYP and FVQ_CYP at home or Great Ormond Street Hospital, London, UK. Associations between VQoL_CYP and FVQ_CYP scores and sociodemographic and clinical factors were analysed using multiple linear regression models. RESULTS: Among 93 participants, VQoL_CYP scores ranged from 36.6 to 78.2 (mean=57.9, SD=8.1). FVQ_CYP scores ranged from 23.5 to 70.3 (mean=48.3, SD=10.1). Only 0.4% of the variation in VQoL_CYP scores was explained, with no associations with the variables of interest. By contrast, 21.6% of the variation in FVQ_CYP scores was explained, with a gradient of worse acuity (p<0.001) and female gender (p=0.04) associated with worse self-rated functional vision. Age, ethnicity, time of onset and stability/progression of visual impairment were not associated. DISCUSSION: Self-rated vision-related quality of life and functional vision are not readily predicted from sociodemographic or clinical characteristics that ophthalmologists measure/record. Routine use of PROMs in clinical practice can offer important insights. Use in research can provide valuable measures of effectiveness of interventions. The reference values provided will aid interpretation in both settings

Differences in Self-Rated Versus Parent Proxy–Rated Vision-Related Quality of Life and Functional Vision of Visually Impaired Children

PURPOSE: To investigate disagreement between children's self-reported vision-related quality of life (VQoL) and functional vision (FV), and their parents' proxy-reports. DESIGN: Cross-sectional study. METHODS: 152 children aged 7-18 years with visual impairment (VI) (defined by the World Health Organization), and their parents, were recruited from 22 National Health Service (NHS) Ophthalmology Departments in the United Kingdom. Age-appropriate versions of 2 vision-specific instruments capturing VQoL and FV, were administered to children alongside modified versions for completion by parents on behalf of their child (i.e. parent proxy-report). Disagreement between self- and parent proxy-report was examined using the Bland-Altman (BA) method, and a threshold of disagreement based on 0.5 standard deviation. Disagreement was analysed according to participants' age, gender and clinical characteristics, using logistic regression analyses. RESULTS: Children rated themselves as having better outcomes than their parents did, although parents both under- and over-estimated their child's VQoL (mean score difference = 7.7). With each year of increasing age, there was a 1.18 (1.04 - 1.35) higher odds of children self-rating their VQoL better than their parents (p = 0.013). Although parents consistently under-estimated their child's FV (mean score difference = -4.7), no characteristics were significantly associated with differences in disagreement. CONCLUSIONS: Disagreement between child self-report on the impact of VI, and their parents' proxy-reports varies by age. This implies that self-report from children must remain the gold standard. Where self-reporting is not possible, parent proxy-reports may provide useful insights, but must be interpreted with caution

Unnatural amino acid analogues of membrane-active helical peptides with anti-mycobacterial activity and improved stability

Objectives The emergence of MDR-TB, coupled with shrinking antibiotic pipelines, has increased demands for new antimicrobials with novel mechanisms of action. Antimicrobial peptides have increasingly been explored as promising alternatives to antibiotics, but their inherent poor in vivo stability remains an impediment to their clinical utility. We therefore systematically evaluated unnatural amino acid-modified peptides to design analogues with enhanced anti-mycobacterial activities. Methods Anti-mycobacterial activities were evaluated in vitro and intracellularly against drug-susceptible and MDR isolates of Mycobacterium tuberculosis using MIC, killing efficacy and intracellular growth inhibition studies. Toxicity profiles were assessed against mammalian cells to verify cell selectivity. Anti-mycobacterial mechanisms were investigated using microfluidic live-cell imaging with time-lapse fluorescence microscopy and confocal laser-scanning microscopy. Results Unnatural amino acid incorporation was well tolerated without an appreciable effect on toxicity profiles and secondary conformations of the synthetic peptides. The modified peptides also withstood proteolytic digestion by trypsin. The all D-amino acid peptide, i(llkk)2i (II-D), displayed superior activity against all six mycobacterial strains tested, with a 4-fold increase in selectivity index as compared with the unmodified L-amino acid peptide in broth. II-D effectively reduced the intracellular bacterial burden of both drug-susceptible and MDR clinical isolates of M. tuberculosis after 4 days of treatment. Live-cell imaging studies demonstrated that II-D permeabilizes the mycobacterial membrane, while confocal microscopy revealed that II-D not only permeates the cell membrane, but also accumulates within the cytoplasm. Conclusions Unnatural amino acid modifications not only decreased the susceptibility of peptides to proteases, but also enhanced mycobacterial selectivity

Investigating and learning lessons from early experiences of implementing ePrescribing systems into NHS hospitals:a questionnaire study

Background: ePrescribing systems have significant potential to improve the safety and efficiency of healthcare, but they need to be carefully selected and implemented to maximise benefits. Implementations in English hospitals are in the early stages and there is a lack of standards guiding the procurement, functional specifications, and expected benefits. We sought to provide an updated overview of the current picture in relation to implementation of ePrescribing systems, explore existing strategies, and identify early lessons learned.Methods: a descriptive questionnaire-based study, which included closed and free text questions and involved both quantitative and qualitative analysis of the data generated.Results: we obtained responses from 85 of 108 NHS staff (78.7% response rate). At least 6% (n = 10) of the 168 English NHS Trusts have already implemented ePrescribing systems, 2% (n = 4) have no plans of implementing, and 34% (n = 55) are planning to implement with intended rapid implementation timelines driven by high expectations surrounding improved safety and efficiency of care. The majority are unclear as to which system to choose, but integration with existing systems and sophisticated decision support functionality are important decisive factors. Participants highlighted the need for increased guidance in relation to implementation strategy, system choice and standards, as well as the need for top-level management support to adequately resource the project. Although some early benefits were reported by hospitals that had already implemented, the hoped for benefits relating to improved efficiency and cost-savings remain elusive due to a lack of system maturity.Conclusions: whilst few have begun implementation, there is considerable interest in ePrescribing systems with ambitious timelines amongst those hospitals that are planning implementations. In order to ensure maximum chances of realising benefits, there is a need for increased guidance in relation to implementation strategy, system choice and standards, as well as increased financial resources to fund local activitie

Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis

Breast cancer is one of the main causes of cancer death worldwide. Early diagnostics significantly increases the chances of correct treatment and survival, but this process is tedious and often leads to a disagreement between pathologists. Computer-aided diagnosis systems showed potential for improving the diagnostic accuracy. In this work, we develop the computational approach based on deep convolution neural networks for breast cancer histology image classification. Hematoxylin and eosin stained breast histology microscopy image dataset is provided as a part of the ICIAR 2018 Grand Challenge on Breast Cancer Histology Images. Our approach utilizes several deep neural network architectures and gradient boosted trees classifier. For 4-class classification task, we report 87.2% accuracy. For 2-class classification task to detect carcinomas we report 93.8% accuracy, AUC 97.3%, and sensitivity/specificity 96.5/88.0% at the high-sensitivity operating point. To our knowledge, this approach outperforms other common methods in automated histopathological image classification. The source code for our approach is made publicly available at https://github.com/alexander-rakhlin/ICIAR2018Comment: 8 pages, 4 figure

An acidic microenvironment in Tuberculosis increases extracellular matrix degradation by regulating macrophage inflammatory responses

Mycobacterium tuberculosis (M.tb) infection causes marked tissue inflammation leading to lung destruction and morbidity. The inflammatory extracellular microenvironment is acidic, however the effect of this acidosis on the immune response to M.tb is unknown. Using RNA-seq we show that acidosis produces system level transcriptional change in M.tb infected human macrophages regulating almost 4000 genes. Acidosis specifically upregulated extracellular matrix (ECM) degradation pathways with increased expression of Matrix metalloproteinases (MMPs) which mediate lung destruction in Tuberculosis. Macrophage MMP-1 and -3 secretion was increased by acidosis in a cellular model. Acidosis markedly suppresses several cytokines central to control of M.tb infection including TNF-α and IFN-γ. Murine studies demonstrated expression of known acidosis signaling G-protein coupled receptors OGR-1 and TDAG-8 in Tuberculosis which are shown to mediate the immune effects of decreased pH. Receptors were then demonstrated to be expressed in patients with TB lymphadenitis. Collectively, our findings show that an acidic microenvironment modulates immune function to reduce protective inflammatory responses and increase extracellular matrix degradation in Tuberculosis. Acidosis receptors are therefore potential targets for host directed therapy in patients

From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions

©2009 Gao, Skolnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.doi:10.1371/journal.pcbi.1000341DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Ca deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein

Differential expression analysis for sequence count data

*Motivation:* High-throughput nucleotide sequencing provides quantitative readouts in assays for RNA expression (RNA-Seq), protein-DNA binding (ChIP-Seq) or cell counting (barcode sequencing). Statistical inference of differential signal in such data requires estimation of their variability throughout the dynamic range. When the number of replicates is small, error modelling is needed to achieve statistical power.&#xd;&#xa;&#xd;&#xa;*Results:* We propose an error model that uses the negative binomial distribution, with variance and mean linked by local regression, to model the null distribution of the count data. The method controls type-I error and provides good detection power. &#xd;&#xa;&#xd;&#xa;*Availability:* A free open-source R software package, _DESeq_, is available from the Bioconductor project and from &#x22;http://www-huber.embl.de/users/anders/DESeq&#x22;:http://www-huber.embl.de/users/anders/DESeq

Linking dwarf galaxies to halo building blocks with the most metal-poor star in Sculptor

Current cosmological models indicate that the Milky Way's stellar halo was assembled from many smaller systems. Based on the apparent absence of the most metal-poor stars in present-day dwarf galaxies, recent studies claimed that the true Galactic building blocks must have been vastly different from the surviving dwarfs. The discovery of an extremely iron-poor star (S1020549) in the Sculptor dwarf galaxy based on a medium-resolution spectrum cast some doubt on this conclusion. However, verification of the iron-deficiency and measurements of additional elements, such as the alpha-element Mg, are mandatory for demonstrating that the same type of stars produced the metals found in dwarf galaxies and the Galactic halo. Only then can dwarf galaxy stars be conclusively linked to early stellar halo assembly. Here we report high-resolution spectroscopic abundances for 11 elements in S1020549, confirming the iron abundance of less than 1/4000th that of the Sun, and showing that the overall abundance pattern mirrors that seen in low-metallicity halo stars, including the alpha-elements. Such chemical similarity indicates that the systems destroyed to form the halo billions of years ago were not fundamentally different from the progenitors of present-day dwarfs, and suggests that the early chemical enrichment of all galaxies may be nearly identical.Comment: 16 pages, including 2 figures. Accepted for publication in Nature. It is embargoed for discussion in the press until formal publication in Natur