P02.123. The anti-diabetic and cholesterol-lowering effects of common and cassia cinnamon (Cinnamomum verum and C. aromaticum): a randomized controlled trial

This paper accompanies a poster presentation on the anti-diabetic and cholesterol-lowering effects of common and cassia cinnamon (Cinnamomum verum and C. aromaticum)

Combining qualitative and quantitative operational research methods to inform quality improvement in pathways that span multiple settings

BACKGROUND: Improving integration and continuity of care across sectors within resource constraints is a priority in many health systems. Qualitative operational research methods of problem structuring have been used to address quality improvement in services involving multiple sectors but not in combination with quantitative operational research methods that enable targeting of interventions according to patient risk. We aimed to combine these methods to augment and inform an improvement initiative concerning infants with congenital heart disease (CHD) whose complex care pathway spans multiple sectors. METHODS: Soft systems methodology was used to consider systematically changes to services from the perspectives of community, primary, secondary and tertiary care professionals and a patient group, incorporating relevant evidence. Classification and regression tree (CART) analysis of national audit datasets was conducted along with data visualisation designed to inform service improvement within the context of limited resources. RESULTS: A 'Rich Picture' was developed capturing the main features of services for infants with CHD pertinent to service improvement. This was used, along with a graphical summary of the CART analysis, to guide discussions about targeting interventions at specific patient risk groups. Agreement was reached across representatives of relevant health professions and patients on a coherent set of targeted recommendations for quality improvement. These fed into national decisions about service provision and commissioning. CONCLUSIONS: When tackling complex problems in service provision across multiple settings, it is important to acknowledge and work with multiple perspectives systematically and to consider targeting service improvements in response to confined resources. Our research demonstrates that applying a combination of qualitative and quantitative operational research methods is one approach to doing so that warrants further consideration

Methylation of the Leukocyte Glucocorticoid Receptor Gene Promoter in Adults: Associations with Early Adversity and Depressive, Anxiety and Substance-Use Disorders

Early adversity increases risk for developing psychopathology. Epigenetic modification of stress reactivity genes is a likely mechanism contributing to this risk. The glucocorticoid receptor (GR) gene is of particular interest because of the regulatory role of the GR in hypothalamic–pituitary–adrenal (HPA) axis function. Mounting evidence suggests that early adversity is associated with GR promoter methylation and gene expression. Few studies have examined links between GR promoter methylation and psychopathology, and findings to date have been mixed. Healthy adult participants (N = 340) who were free of psychotropic medications reported on their childhood experiences of maltreatment and parental death and desertion. Lifetime depressive and anxiety disorders and past substance-use disorders were assessed using the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Methylation of exon 1F of the GR gene (NR3C1) was examined in leukocyte DNA via pyrosequencing. On a separate day, a subset of the participants (n = 231) completed the dexamethasone/corticotropin- releasing hormone (Dex/CRH) test. Childhood adversity and a history of past substance-use disorder and current or past depressive or anxiety disorders were associated with lower levels of NR3C1 promoter methylation across the region as a whole and at individual CpG sites (Po0.05). The number of adversities was negatively associated with NR3C1 methylation in participants with no lifetime disorder (P = 0.018), but not in those with a lifetime disorder. GR promoter methylation was linked to altered cortisol responses to the Dex/CRH test (Po0.05). This study presents evidence of reduced methylation of NR3C1 in association with childhood maltreatment and depressive, anxiety and substance-use disorders in adults. This finding stands in contrast to our prior work, but is consistent with emerging findings, suggesting complexity in the regulation of this gene

Estimating the sea ice floe size distribution using satellite altimetry: Theory, climatology, and model comparison

In sea-ice-covered areas, the sea ice floe size distribution (FSD) plays an important role in many processes affecting the coupled sea-ice-ocean-atmosphere system. Observations of the FSD are sparse - traditionally taken via a painstaking analysis of ice surface photography - and the seasonal and inter-annual evolution of floe size regionally and globally is largely unknown. Frequently, measured FSDs are assessed using a single number, the scaling exponent of the closest power-law fit to the observed floe size data, although in the absence of adequate datasets there have been limited tests of this "power-law hypothesis". Here we derive and explain a mathematical technique for deriving statistics of the sea ice FSD from polar-orbiting altimeters, satellites with sub-daily return times to polar regions with high along-track resolutions. Applied to the CryoSat-2 radar altimetric record, covering the period from 2010 to 2018, and incorporating 11 million individual floe samples, we produce the first pan-Arctic climatology and seasonal cycle of sea ice floe size statistics. We then perform the first pan-Arctic test of the power-law hypothesis, finding limited support in the range of floe sizes typically analyzed in photographic observational studies. We compare the seasonal variability in observed floe size to fully coupled climate model simulations including a prognostic floe size and thickness distribution and coupled wave model, finding good agreement in regions where modeled ocean surface waves cause sea ice fracture

An Assessment of State-of-the-Art Mean Sea Surface and Geoid Models of the Arctic Ocean: Implications for Sea Ice Freeboard Retrieval

State-of-the-art Arctic Ocean mean sea surface (MSS) models and global geoid models (GGMs) are used to support sea ice freeboard estimation from satellite altimeters, as well as in oceanographic studies such as mapping sea level anomalies and mean dynamic ocean topography. However, errors in a given model in the high frequency domain, primarily due to unresolved gravity features, can result in errors in the estimated along-track freeboard. These errors are exacerbated in areas with a sparse lead distribution in consolidated ice pack conditions. Additionally model errors can impact ocean geostrophic currents, derived from satellite altimeter data, while remaining biases in these models may impact longer-term, multi-sensor oceanographic time-series of sea level change in the Arctic. This study focuses on an assessment of five state-of-the-art Arctic MSS models (UCL13/04, DTU15/13/10) and a commonly used GGM (EGM2008). We describe errors due to unresolved gravity features, inter-satellite biases, and remaining satellite orbit errors, and their impact on the derivation of sea ice freeboard. The latest MSS models, incorporating CryoSat-2 sea surface height measurements, show improved definition of gravity features, such as the Gakkel Ridge. The standard deviation between models ranges 0.03-0.25 m. The impact of remaining MSS/GGM errors on freeboard retrieval can reach several decimeters in parts of the Arctic. While the maximum observed freeboard difference found in the central Arctic was 0.59 m (UCL13 MSS minus EGM2008 GGM), the standard deviation in freeboard differences is 0.03-0.06 m

Gambling Survey for Great Britain - Annual report (2023): Official statistics

No abstract available

Pathogen lifestyle determines host genetic signature of quantitative disease resistance loci in oilseed rape ( Brassica napus )

© 2024 The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Using associative transcriptomics, our study identifies genes conferring resistance to four diverse fungal pathogens in crops, emphasizing key genetic determinants of multi-pathogen resistance. Crops are affected by several pathogens, but these are rarely studied in parallel to identify common and unique genetic factors controlling diseases. Broad-spectrum quantitative disease resistance (QDR) is desirable for crop breeding as it confers resistance to several pathogen species. Here, we use associative transcriptomics (AT) to identify candidate gene loci associated with Brassica napus constitutive QDR to four contrasting fungal pathogens: Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae, and Verticillium longisporum. We did not identify any shared loci associated with broad-spectrum QDR to fungal pathogens with contrasting lifestyles. Instead, we observed QDR dependent on the lifestyle of the pathogen-hemibiotrophic and necrotrophic pathogens had distinct QDR responses and associated loci, including some loci associated with early immunity. Furthermore, we identify a genomic deletion associated with resistance to V. longisporum and potentially broad-spectrum QDR. This is the first time AT has been used for several pathosystems simultaneously to identify host genetic loci involved in broad-spectrum QDR. We highlight constitutive expressed candidate loci for broad-spectrum QDR with no antagonistic effects on susceptibility to the other pathogens studies as candidates for crop breeding. In conclusion, this study represents an advancement in our understanding of broad-spectrum QDR in B. napus and is a significant resource for the scientific community.Peer reviewe

Large-scale whole-genome resequencing unravels the domestication history of Cannabis sativa.

Cannabis sativa has long been an important source of fiber extracted from hemp and both medicinal and recreational drugs based on cannabinoid compounds. Here, we investigated its poorly known domestication history using whole-genome resequencing of 110 accessions from worldwide origins. We show that C. sativa was first domesticated in early Neolithic times in East Asia and that all current hemp and drug cultivars diverged from an ancestral gene pool currently represented by feral plants and landraces in China. We identified candidate genes associated with traits differentiating hemp and drug cultivars, including branching pattern and cellulose/lignin biosynthesis. We also found evidence for loss of function of genes involved in the synthesis of the two major biochemically competing cannabinoids during selection for increased fiber production or psychoactive properties. Our results provide a unique global view of the domestication of C. sativa and offer valuable genomic resources for ongoing functional and molecular breeding research

Abelian Sandpile Model on the Honeycomb Lattice

We check the universality properties of the two-dimensional Abelian sandpile model by computing some of its properties on the honeycomb lattice. Exact expressions for unit height correlation functions in presence of boundaries and for different boundary conditions are derived. Also, we study the statistics of the boundaries of avalanche waves by using the theory of SLE and suggest that these curves are conformally invariant and described by SLE2.Comment: 24 pages, 5 figure