The potential for dietary factors to prevent or treat osteoarthritis

Osteoarthritis (OA) is a degenerative joint disease for which there are no disease-modifying drugs. It is a leading cause of disability in the UK. Increasing age and obesity are both major risk factors for OA and the health and economic burden of this disease will increase in the future. Focusing on compounds from the habitual diet that may prevent the onset or slow the progression of OA is a strategy that has been under-investigated to date. An approach that relies on dietary modification is clearly attractive in terms of risk/benefit and more likely to be implementable at the population level. However, before undertaking a full clinical trial to examine potential efficacy, detailed molecular studies are required in order to optimise the design. This review focuses on potential dietary factors that may reduce the risk or progression of OA, including micronutrients, fatty acids, flavonoids and other phytochemicals. It therefore ignores data coming from classical inflammatory arthritides and nutraceuticals such as glucosamine and chondroitin. In conclusion, diet offers a route by which the health of the joint can be protected and OA incidence or progression decreased. In a chronic disease, with risk factors increasing in the population and with no pharmaceutical cure, an understanding of this will be crucial

The cellular microscopy phenotype ontology

BACKGROUND: Phenotypic data derived from high content screening is currently annotated using free-text, thus preventing the integration of independent datasets, including those generated in different biological domains, such as cell lines, mouse and human tissues. DESCRIPTION: We present the Cellular Microscopy Phenotype Ontology (CMPO), a species neutral ontology for describing phenotypic observations relating to the whole cell, cellular components, cellular processes and cell populations. CMPO is compatible with related ontology efforts, allowing for future cross-species integration of phenotypic data. CMPO was developed following a curator-driven approach where phenotype data were annotated by expert biologists following the Entity-Quality (EQ) pattern. These EQs were subsequently transformed into new CMPO terms following an established post composition process. CONCLUSION: CMPO is currently being utilized to annotate phenotypes associated with high content screening datasets stored in several image repositories including the Image Data Repository (IDR), MitoSys project database and the Cellular Phenotype Database to facilitate data browsing and discoverability

Combining local model calibration with the emergent constraint approach to reduce uncertainty in the tropical land carbon cycle feedback

The role of the land carbon cycle in climate change remains highly uncertain. A key source of the projection spread is related to the assumed response of photosynthesis to warming, especially in the tropics. The optimum temperature for photosynthesis determines whether warming positively or negatively impacts photosynthesis, thereby amplifying or suppressing CO2 fertilisation of photosynthesis under CO2-induced global warming. Land carbon cycle models have been extensively calibrated against local eddy flux measurements, but this has not previously been clearly translated into a reduced uncertainty in terms of how the tropical land carbon sink will respond to warming. Using a previous parameter perturbation ensemble carried out with version 3 of the Hadley Centre coupled climate–carbon cycle model (HadCM3C), we identify an emergent relationship between the optimal temperature for photosynthesis, which is especially relevant in tropical forests, and the projected amount of atmospheric CO2 at the end of the century. We combine this with a constraint on the optimum temperature for photosynthesis, derived from eddy covariance measurements using the adjoint of the Joint UK Land Environment Simulator (JULES) land surface model. Taken together, the emergent relationship from the coupled model and the constraint on the optimum temperature for photosynthesis define an emergent constraint on future atmospheric CO2 in the HadCM3C coupled climate–carbon cycle under a common emissions scenario (A1B). The emergent constraint sharpens the probability density of simulated CO2 change (2100–1900) and moves its peak to a lower value of 497 ± 91 compared to 607 ± 128 ppmv (parts per million by volume) when using the equal-weight prior. Although this result is likely to be model and scenario dependent, it demonstrates the potential of combining the large-scale emergent constraint approach with a parameter estimation using detailed local measurements.</p

The Sigma 13 (10-14) twin in alpha-Al2O3: A model for a general grain boundary

The atomistic structure and energetics of the Sigma 13 (10-14)[1-210] symmetrical tilt grain boundary in alpha-Al2O3 are studied by first-principles calculations based on the local-density-functional theory with a mixed-basis pseudopotential method. Three configurations, stable with respect to intergranular cleavage, are identified: one Al-terminated glide-mirror twin boundary, and two O-terminated twin boundaries, with glide-mirror and two-fold screw-rotation symmetries, respectively. Their relative energetics as a function of axial grain separation are described, and the local electronic structure and bonding are analysed. The Al-terminated variant is predicted to be the most stable one, confirming previous empirical calculations, but in contrast with high-resolution transmission electron microscopy observations on high-purity diffusion-bonded bicrystals, which resulted in an O-terminated structure. An explanation of this discrepancy is proposed, based on the different relative energetics of the internal interfaces with respect to the free surfaces

Predictive use of the Maximum Entropy Production principle for Past and Present Climates

In this paper, we show how the MEP hypothesis may be used to build simple climate models without representing explicitly the energy transport by the atmosphere. The purpose is twofold. First, we assess the performance of the MEP hypothesis by comparing a simple model with minimal input data to a complex, state-of-the-art General Circulation Model. Next, we show how to improve the realism of MEP climate models by including climate feedbacks, focusing on the case of the water-vapour feedback. We also discuss the dependence of the entropy production rate and predicted surface temperature on the resolution of the model

Rank-based model selection for multiple ions quantum tomography

The statistical analysis of measurement data has become a key component of many quantum engineering experiments. As standard full state tomography becomes unfeasible for large dimensional quantum systems, one needs to exploit prior information and the "sparsity" properties of the experimental state in order to reduce the dimensionality of the estimation problem. In this paper we propose model selection as a general principle for finding the simplest, or most parsimonious explanation of the data, by fitting different models and choosing the estimator with the best trade-off between likelihood fit and model complexity. We apply two well established model selection methods -- the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) -- to models consising of states of fixed rank and datasets such as are currently produced in multiple ions experiments. We test the performance of AIC and BIC on randomly chosen low rank states of 4 ions, and study the dependence of the selected rank with the number of measurement repetitions for one ion states. We then apply the methods to real data from a 4 ions experiment aimed at creating a Smolin state of rank 4. The two methods indicate that the optimal model for describing the data lies between ranks 6 and 9, and the Pearson $\chi^{2}$ test is applied to validate this conclusion. Additionally we find that the mean square error of the maximum likelihood estimator for pure states is close to that of the optimal over all possible measurements.Comment: 24 pages, 6 figures, 3 table

Sulforaphane represses matrix-degrading proteases and protects cartilage from destruction in vitro and in vivo:Sulforaphane is protective in the articular Joint

Sulforaphane (SFN) has been reported to regulate signaling pathways relevant to chronic diseases. The aim of this study was to investigate the impact of SFN treatment on signaling pathways in chondrocytes and to determine whether sulforaphane could block cartilage destruction in osteoarthritis

In vivo γ-aminobutyric acid measurement in rats with spectral editing at 4.7T.

PURPOSE: To evaluate the feasibility of spectral editing for quantification of γ-aminobutyric acid (GABA) in the rat brain and to determine whether altered GABA concentration in the ventral striatum is a neural endophenotype associated with trait-like impulsive behavior. MATERIALS AND METHODS: Spectra were acquired at 4.7T for 23 male Lister-hooded rats that had been previously screened for extremely low and high impulsivity phenotypes on an automated behavioral task (n = 11 low-impulsive; n = 12 high-impulsive). Voxels of 3 × 7 × 4 mm(3) (84 μL) centered bilaterally across the ventral striatum were used to evaluate GABA concentration ratios. RESULTS: Quantifiable GABA signals in the ventral striatum were obtained for all rats. Mean-edited GABA to n-acetyl aspartate (NAA) ratios in the ventral striatum were 0.22 (95% confidence interval [CI] [0.18, 0.25]). Mean GABA/NAA ratios in this region were significantly decreased by 28% in high-impulsive rats compared to low-impulsive rats (P = 0.02; 95% CI [-53%, -2%]). CONCLUSION: These findings demonstrate that spectral editing at 4.7T is a feasible method to assess in vivo GABA concentrations in the rat brain. The results show that diminished GABA content in the ventral striatum may be a neural endophenotype associated with impulsivity. J. Magn. Reson. Imaging 2016;43:1308-1312.This study was funded by the UK Medical Research Council (G0701500) and by a joint award from the Medical Research Council (G1000183) and Wellcome Trust (093875/Z/10/Z) in support of the Behavioural and Clinical Neuroscience Institute at Cambridge University. BJ is supported by grants from the AXA Research Fund and the Australian National Health and Medical Research Council (1016313).This is the author accepted manuscript. The final version is available from Wiley via http://dx.doi.org/10.1002/jmri.2509

Popular attitudes to memory, the body, and social identity : the rise of external commemoration in Britain, Ireland, and New England

A comparative analysis of samples of external memorials from burial grounds in Britain, Ireland and New England reveals a widespread pattern of change in monument style and content, and exponential growth in the number of permanent memorials from the 18th century onwards. Although manifested in regionally distinctive styles on which most academic attention has so far been directed, the expansion reflects global changes in social relationships and concepts of memory and the body. An archaeological perspective reveals the importance of external memorials in articulating these changing attitudes in a world of increasing material consumption