Investigating the value of glucodensity analysis of continuous glucose monitoring data in type 1 diabetes: an exploratory analysis

IntroductionContinuous glucose monitoring (CGM) devices capture longitudinal data on interstitial glucose levels and are increasingly used to show the dynamics of diabetes metabolism. Given the complexity of CGM data, it is crucial to extract important patterns hidden in these data through efficient visualization and statistical analysis techniques.MethodsIn this paper, we adopted the concept of glucodensity, and using a subset of data from an ongoing clinical trial in pediatric individuals and young adults with new-onset type 1 diabetes, we performed a cluster analysis of glucodensities. We assessed the differences among the identified clusters using analysis of variance (ANOVA) with respect to residual pancreatic beta-cell function and some standard CGM-derived parameters such as time in range, time above range, and time below range.ResultsDistinct CGM data patterns were identified using cluster analysis based on glucodensities. Statistically significant differences were shown among the clusters with respect to baseline levels of pancreatic beta-cell function surrogate (C-peptide) and with respect to time in range and time above range.DiscussionOur findings provide supportive evidence for the value of glucodensity in the analysis of CGM data. Some challenges in the modeling of CGM data include unbalanced data structure, missing observations, and many known and unknown confounders, which speaks to the importance of--and provides opportunities for--taking an approach integrating clinical, statistical, and data science expertise in the analysis of these data

Evaluating Current Practices in Shelf Life Estimation

The current International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) methods for determining the supported shelf life of a drug product, described in ICH guidance documents Q1A and Q1E, are evaluated in this paper. To support this evaluation, an industry data set is used which is comprised of 26 individual stability batches of a common drug product where most batches are measured over a 24 month storage period. Using randomly sampled sets of 3 or 6 batches from the industry data set, the current ICH methods are assessed from three perspectives. First, the distributional properties of the supported shelf lives are summarized and compared to the distributional properties of the true shelf lives associated with the industry data set, assuming the industry data set represents a finite population of drug product batches for discussion purposes. Second, the results of the ICH poolability^ tests for model selection are summarized and the separate shelf life distributions from the possible alternative models are compared. Finally, the ICH methods are evaluated in terms of their ability to manage risk. Shelf life estimates that are too long result in an unacceptable percentage of nonconforming batches at expiry while those that are too short put the manufacturer at risk of possibly having to prematurely discard safe and efficacious drug product. Based on the analysis of the industry data set, the ICH-recommended approach did not produce supported shelf lives that effectively managed risk. Alternative approaches are required

Rational Design of Temperature-Sensitive Alleles Using Computational Structure Prediction

Temperature-sensitive (ts) mutations are mutations that exhibit a mutant phenotype at high or low temperatures and a wild-type phenotype at normal temperature. Temperature-sensitive mutants are valuable tools for geneticists, particularly in the study of essential genes. However, finding ts mutations typically relies on generating and screening many thousands of mutations, which is an expensive and labor-intensive process. Here we describe an in silico method that uses Rosetta and machine learning techniques to predict a highly accurate “top 5” list of ts mutations given the structure of a protein of interest. Rosetta is a protein structure prediction and design code, used here to model and score how proteins accommodate point mutations with side-chain and backbone movements. We show that integrating Rosetta relax-derived features with sequence-based features results in accurate temperature-sensitive mutation predictions

Crop Updates 2006 - Weeds

This session covers thirty seven papers from different authors: 1. ACKNOWLEDGEMENTS, Alexandra Douglas, CONVENOR – WEEDS DEPARTMENT OF AGRICULTURE SPRAY TECHNOLOGY 2. Meeting the variable application goals with new application technology, Thomas M. Wolf, Agriculture and Agri-Food Canada, Saskatoon Research Centre 3. Spray nozzles for grass weed control, Harm van Rees, BCG (Birchip Cropping Group) 4. Boom sprayer setups – achieving coarse droplets with different operating parameters, Bill Gordon, Bill Gordon Consulting 5. Complying with product label requirements, Bill Gordon, Bill Gordon Consulting 6. IWM a proven performer over 5 years in 33 focus paddocks, Peter Newman and Glenn Adam, Department of Agriculture 7. Crop topping of wild radish in lupins and barley, how long is a piece of string? Peter Newman and Glenn Adam, Department of Agriculture 8. Determining the right timing to maximise seed set control of wild radish, Aik Cheam and Siew Lee, Department of Agriculture 9. Why weed wiping varies in success rates in broadacre crops? Aik Cheam1, Katherine Hollaway2, Siew Lee1, Brad Rayner1 and John Peirce1,1Department of Agriculture, 2Department of Primary Industries, Victoria 10. Are WA growers successfully managing herbicide resistant annual ryegrass? Rick Llewellynabc, Frank D’Emdena, Mechelle Owenb and Stephen Powlesb aCRC Australian Weed Management, School of Agricultural and Resource Economics, University of Western Australia; bWA Herbicide Resistance Initiative, University of Western Australia. cCurrent address: CSIRO Sustainable Ecosystems 11. Do herbicide resistant wild radish populations look different? Michael Walsh, Western Australian Herbicide Resistance Initiative, University of Western Australia 12. Can glyphosate and paraquat annual ryegrass reduce crop topping efficacy? Emma Glasfurd, Michael Walsh and Kathryn Steadman, Western Australian Herbicide Resistance Initiative, University of Western Australia 13. Tetraploid ryegrass for WA. Productive pasture phase AND defeating herbicide resistant ryegrass, Stephen Powlesa, David Ferrisab and Bevan Addisonc, aWA Herbicide Resistance Initiative, University of Western Australia; bDepartment of Agriculture, and cElders Limited 14. Long-term management impact on seedbank of wild radish with multiple resistance to diflufenican and triazines, Aik Cheam, Siew Lee, Dave Nicholson and Ruben Vargas, Department of Agriculture 15. East-west crop row orientation improves wheat and barley yields, Dr Shahab Pathan, Dr Abul Hashem, Nerys Wilkins and Catherine Borger3, Department of Agriculture, 3WAHRI, The University ofWestern Australia 16. Competitiveness of different lupin cultivars with wild radish, Dr Shahab Pathan, Dr Bob French and Dr Abul Hashem, Department of Agriculture 17. Managing herbicide resistant weeds through farming systems, Kari-Lee Falconer, Martin Harries and Chris Matthews, Department of Agriculture 18. Lupins tolerate in-row herbicides well, Peter Newman and Martin Harries, Department of Agriculture 19. Summer weeds can reduce wheat grain yield and protein, Dr Abul Hashem1, Dr Shahab Pathan1 and Vikki Osten3, 1Department Agriculture, 3Senior Agronomist, CRC for Australian Weed Management, Queensland Department of Primary Industries and Fisheries 20. Diuron post-emergent in lupins, the full story, Peter Newman and Glenn Adam, Department of Agriculture 21. Double incorporation of trifluralin, Peter Newman and Glenn Adam, Department of Agriculture 22. Herbicide tolerance of narrow leafed and yellow lupins, Harmohinder Dhammu, David Nicholson, Department of Agriculture 23. MIG narrow leaf lupin herbicide tolerance trial, Richard Quinlan, Planfarm Pty Ltd, Trials Coordinator MIG; Debbie Allen, Research Agronomist – MIG 24. Herbicide tolerance of new albus lupins, Harmohinder Dhammu, David Nicholson, Department of Agriculture 25. Field pea x herbicide tolerance, Mark Seymour and Harmohinder Dhammu, Research Officers, and Pam Burgess, Department of Agriculture 26. Faba bean variety x herbicide tolerance, Mark Seymour and Harmohinder Dhammu, Research Officers, and Pam Burgess, Department of Agriculture 27. Herbicide tolerance of new Kabili chickpeas, Harmohinder Dhammu, Owen Coppen and Chris Roberts, Department of Agriculture 28. Timing of phenoxys application in EAG Eagle Rock, Harmohinder Dhammu, David Nicholson, Department of Agriculture 29. Herbicide tolerance of new wheat varieties, Harmohinder Dhammu, David Nicholson, Department of Agriculture 30. Lathyrus sativus x herbicide tolerance, Mark Seymour, Department of Agriculture 31. Tolerance of annual pasture species to herbicides and mixtures containing diuron, Christiaan Valentine and David Ferris, Department of Agriculture 32. The impact of herbicides on pasture legume species – a summary of scientific trial results across 8 years, Christiaan Valentine and David Ferris, Department of Agriculture 33. The impact of spraytopping on pasture legume seed set, Christiaan Valentine and David Ferris, Department of Agriculture 34. Ascochyta interaction with Broadstrike in chickpeas, H.S. Dhammu1, A.K. Basandrai2,3, W.J. MacLeod1, 3 and C. Roberts1, 1Department of Agriculture, 2CSKHPAU, Dhaulakuan, Sirmour (HP), India and 3CLIMA 35. Best management practices for atrazine in broadacre crops, John Moore, Department of Agriculture, Neil Rothnie, Chemistry Centre of WA, Russell Speed, Department of Agriculture, John Simons, Department of Agriculture, and Ted Spadek, Chemistry Centre of WA 36. Biology and management of red dodder (Cuscuta planiflolia) – a new threat to the grains industry, Abul Hashem, Daya Patabendige and Chris Roberts, Department Agriculture 37. Help the wizard stop the green invaders! Michael Renton, Sally Peltzer and Art Diggle, Department of Agricultur

RNA-seq analyses of blood-induced changes in gene expression in the mosquito vector species, Aedes aegypti

<p>Abstract</p> <p>Background</p> <p>Hematophagy is a common trait of insect vectors of disease. Extensive genome-wide transcriptional changes occur in mosquitoes after blood meals, and these are related to digestive and reproductive processes, among others. Studies of these changes are expected to reveal molecular targets for novel vector control and pathogen transmission-blocking strategies. The mosquito <it>Aedes aegypti </it>(Diptera, Culicidae), a vector of Dengue viruses, Yellow Fever Virus (YFV) and Chikungunya virus (CV), is the subject of this study to look at genome-wide changes in gene expression following a blood meal.</p> <p>Results</p> <p>Transcriptional changes that follow a blood meal in <it>Ae. aegypti </it>females were explored using RNA-seq technology. Over 30% of more than 18,000 investigated transcripts accumulate differentially in mosquitoes at five hours after a blood meal when compared to those fed only on sugar. Forty transcripts accumulate only in blood-fed mosquitoes. The list of regulated transcripts correlates with an enhancement of digestive activity and a suppression of environmental stimuli perception and innate immunity. The alignment of more than 65 million high-quality short reads to the <it>Ae. aegypti </it>reference genome permitted the refinement of the current annotation of transcript boundaries, as well as the discovery of novel transcripts, exons and splicing variants. <it>Cis</it>-regulatory elements (CRE) and <it>cis</it>-regulatory modules (CRM) enriched significantly at the 5'end flanking sequences of blood meal-regulated genes were identified.</p> <p>Conclusions</p> <p>This study provides the first global view of the changes in transcript accumulation elicited by a blood meal in <it>Ae. aegypti </it>females. This information permitted the identification of classes of potentially co-regulated genes and a description of biochemical and physiological events that occur immediately after blood feeding. The data presented here serve as a basis for novel vector control and pathogen transmission-blocking strategies including those in which the vectors are modified genetically to express anti-pathogen effector molecules.</p

Arginine Metabolism by Macrophages Promotes Cardiac and Muscle Fibrosis in mdx Muscular Dystrophy

Duchenne muscular dystrophy (DMD) is the most common, lethal disease of childhood. One of 3500 new-born males suffers from this universally-lethal disease. Other than the use of corticosteroids, little is available to affect the relentless progress of the disease, leading many families to use dietary supplements in hopes of reducing the progression or severity of muscle wasting. Arginine is commonly used as a dietary supplement and its use has been reported to have beneficial effects following short-term administration to mdx mice, a genetic model of DMD. However, the long-term effects of arginine supplementation are unknown. This lack of knowledge about the long-term effects of increased arginine metabolism is important because elevated arginine metabolism can increase tissue fibrosis, and increased fibrosis of skeletal muscles and the heart is an important and potentially life-threatening feature of DMD.We use both genetic and nutritional manipulations to test whether changes in arginase metabolism promote fibrosis and increase pathology in mdx mice. Our findings show that fibrotic lesions in mdx muscle are enriched with arginase-2-expressing macrophages and that muscle macrophages stimulated with cytokines that activate the M2 phenotype show elevated arginase activity and expression. We generated a line of arginase-2-null mutant mdx mice and found that the mutation reduced fibrosis in muscles of 18-month-old mdx mice, and reduced kyphosis that is attributable to muscle fibrosis. We also observed that dietary supplementation with arginine for 17-months increased mdx muscle fibrosis. In contrast, arginine-2 mutation did not reduce cardiac fibrosis or affect cardiac function assessed by echocardiography, although 17-months of dietary supplementation with arginine increased cardiac fibrosis. Long-term arginine treatments did not decrease matrix metalloproteinase-2 or -9 or increase the expression of utrophin, which have been reported as beneficial effects of short-term treatments.Our findings demonstrate that arginine metabolism by arginase promotes fibrosis of muscle in muscular dystrophy and contributes to kyphosis. Our findings also show that long-term, dietary supplementation with arginine exacerbates fibrosis of dystrophic heart and muscles. Thus, commonly-practiced dietary supplementation with arginine by DMD patients has potential risk for increasing pathology when performed for long periods, despite reports of benefits acquired with short-term supplementation

Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes:findings from the ENIGMA Epigenetics Working Group

DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)-three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions