The process of setting micronutrient recommendations: a cross-European comparison of nutrition-related scientific advisory bodies

Copyright @ The Authors 2010Objective: To examine the workings of the nutrition-related scientific advisory bodies in Europe, paying particular attention to the internal and external contexts within which they operate. Design: Desk research based on two data collection strategies: a questionnaire completed by key informants in the field of micronutrient recommendations and a case study that focused on mandatory folic acid (FA) fortification. Setting: Questionnaire-based data were collected across thirty-five European countries. The FA fortification case study was conducted in the UK, Norway, Denmark, Germany, Spain, Czech Republic and Hungary. Results: Varied bodies are responsible for setting micronutrient recommendations, each with different statutory and legal models of operation. Transparency is highest where there are standing scientific advisory committees (SAC). Where the standing SAC is created, the range of expertise and the terms of reference for the SAC are determined by the government. Where there is no dedicated SAC, the impetus for the development of micronutrient recommendations and the associated policies comes from interested specialists in the area. This is typically linked with an ad hoc selection of a problem area to consider, lack of openness and transparency in the decisions and over-reliance on international recommendations. Conclusions: Even when there is consensus about the science behind micronutrient recommendations, there is a range of other influences that will affect decisions about the policy approaches to nutrition-related public health. This indicates the need to document the evidence that is drawn upon in the decisions about nutrition policy related to micronutrient intake.This work has been carried out within the EURRECA Network of Excellence (www.eurreca.org) which is financially supported by the Commission of the European Communities, specific Research, Technology and Development (RTD) Programme Quality of Life and Management of Living Resources, within the Sixth Framework Programme, contract no. 036196

Constraining dark energy with Sunyaev-Zel'dovich cluster surveys

We discuss the prospects of constraining the properties of a dark energy component, with particular reference to a time varying equation of state, using future cluster surveys selected by their Sunyaev-Zel'dovich effect. We compute the number of clusters expected for a given set of cosmological parameters and propogate the errors expected from a variety of surveys. In the short term they will constrain dark energy in conjunction with future observations of type Ia supernovae, but may in time do so in their own right.Comment: 5 pages, 3 figures, 1 table, version accepted for publication in PR

Impact of baryons on the cluster mass function and cosmological parameter determination

Recent results by the Planck collaboration have shown that cosmological parameters derived from the cosmic microwave background anisotropies and cluster number counts are in tension, with the latter preferring lower values of the matter density parameter, $\Omega_\mathrm{m}$, and power spectrum amplitude, $\sigma_8$. Motivated by this, we investigate the extent to which the tension may be ameliorated once the effect of baryonic depletion on the cluster mass function is taken into account. We use the large-volume Millennium Gas simulations in our study, including one where the gas is pre-heated at high redshift and one where the gas is heated by stars and active galactic nuclei (in the latter, the self-gravity of the baryons and radiative cooling are omitted). In both cases, the cluster baryon fractions are in reasonably good agreement with the data at low redshift, showing significant depletion of baryons with respect to the cosmic mean. As a result, it is found that the cluster abundance in these simulations is around 15 per cent lower than the commonly-adopted fit to dark matter simulations by Tinker et al (2008) for the mass range $10^{14}-10^{14.5}h^{-1} \mathrm{M}_\odot$. Ignoring this effect produces a significant artificial shift in cosmological parameters which can be expressed as $\Delta[\sigma_8(\Omega_\mathrm{m}/0.27)^{0.38}]\simeq -0.03$ at $z=0.17$ (the median redshift of the $\mathit{Planck}$ cluster sample) for the feedback model. While this shift is not sufficient to fully explain the $\mathit{Planck}$ discrepancy, it is clear that such an effect cannot be ignored in future precision measurements of cosmological parameters with clusters. Finally, we outline a simple, model-independent procedure that attempts to correct for the effect of baryonic depletion and show that it works if the baryon-dark matter back-reaction is negligible.Comment: 10 pages, 5 figures, Accepted by MNRA

The bright end of the z ~ 7 UV Luminosity Function from a wide and deep HAWK-I survey

(Abridged) We present here the second half of an ESO Large Programme, which exploits the unique combination of area and sensitivity provided in the near-IR by the camera Hawk-I at the VLT. We have obtained - 30 observing hours with Hawk-I in the Y-band of two high galactic latitude fields. We combined the Y-band data with deep J and K Hawk-I observations, and with FORS1/FORS2 U, B, V, R, I, and Z observations to select z-drop galaxies having Z - Y > 1, no optical detection and flat Y - J and Y - K colour terms. We detect 8 high-quality candidates in the magnitude range Y = 25.5 - 26.5 that we add to the z-drop candidates selected in two Hawk-I pointings over the GOODS-South field. We use this full sample of 15 objects found in -161 arcmin^2 of our survey to constrain the average physical properties and the evolution of the number density of z ~ 7 LBGs. A stacking analysis yields a best-fit SED with photometric redshift z= 6.85 +0.20 -0.15 and an E(B-V)=0.05 +0.15 -0.05. We compute a binned estimate of the z ~ 7 LF and explore the effects of photometric scatter and model uncertainties on the statistical constraints. After accounting for the expected incompleteness through MonteCarlo simulations, we strengthen our previous finding that a Schechter luminosity function constant from z=6 to z=7 is ruled out at a >99% confidence level, even including the effects of cosmic variance. For galaxies brighter than M_1500= -19.0, we derive a luminosity density rho_UV = 1.5^{+2.1}{-0.8} x 10^25 erg/s/Hz/Mpc^3, implying a decrease by a factor 3.5 from z=6 to z=6.8. We find that, under standard assumptions, the emission rate of ionizing photons coming from UV bright galaxies is lower by at least a factor of two than the value required for reionization. Finally, we exploit deep Hawk-I J and K band observations to derive an upper limit on the number density of M1500<~ -22.0 LBGs at z-8 (Y-dropouts).Comment: 12 pages, 8 figures. Accepted for publication in Astronomy & Astrophysic

A mass-loss rate determination for zeta Puppis from the quantitative analysis of X-ray emission line profiles

We fit every emission line in the high-resolution Chandra grating spectrum of zeta Pup with an empirical line profile model that accounts for the effects of Doppler broadening and attenuation by the bulk wind. For each of sixteen lines or line complexes that can be reliably measured, we determine a best-fitting fiducial optical depth, tau_* = kappa*Mdot/4{pi}R_{\ast}v_{\infty}, and place confidence limits on this parameter. These sixteen lines include seven that have not previously been reported on in the literature. The extended wavelength range of these lines allows us to infer, for the first time, a clear increase in tau_* with line wavelength, as expected from the wavelength increase of bound-free absorption opacity. The small overall values of tau_*, reflected in the rather modest asymmetry in the line profiles, can moreover all be fit simultaneously by simply assuming a moderate mass-loss rate of 3.5 \pm 0.3 \times 10^{-6} Msun/yr, without any need to invoke porosity effects in the wind. The quoted uncertainty is statistical, but the largest source of uncertainty in the derived mass-loss rate is due to the uncertainty in the elemental abundances of zeta Pup, which affects the continuum opacity of the wind, and which we estimate to be a factor of two. Even so, the mass-loss rate we find is significantly below the most recent smooth-wind H-alpha mass-loss rate determinations for zeta Pup, but is in line with newer determinations that account for small-scale wind clumping. If zeta Pup is representative of other massive stars, these results will have important implications for stellar and galactic evolution.Comment: Accepted for publication in the Monthly Notices of the Royal Astronomical Society. 17 pages, including 14 figures (7 color

Sarm1 deletion suppresses TDP-43-linked motor neuron degeneration and cortical spine loss

Abstract: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative condition that primarily affects the motor system and shares many features with frontotemporal dementia (FTD). Evidence suggests that ALS is a ‘dying-back’ disease, with peripheral denervation and axonal degeneration occurring before loss of motor neuron cell bodies. Distal to a nerve injury, a similar pattern of axonal degeneration can be seen, which is mediated by an active axon destruction mechanism called Wallerian degeneration. Sterile alpha and TIR motif-containing 1 (Sarm1) is a key gene in the Wallerian pathway and its deletion provides long-term protection against both Wallerian degeneration and Wallerian-like, non-injury induced axonopathy, a retrograde degenerative process that occurs in many neurodegenerative diseases where axonal transport is impaired. Here, we explored whether Sarm1 signalling could be a therapeutic target for ALS by deleting Sarm1 from a mouse model of ALS-FTD, a TDP-43Q331K, YFP-H double transgenic mouse. Sarm1 deletion attenuated motor axon degeneration and neuromuscular junction denervation. Motor neuron cell bodies were also significantly protected. Deletion of Sarm1 also attenuated loss of layer V pyramidal neuronal dendritic spines in the primary motor cortex. Structural MRI identified the entorhinal cortex as the most significantly atrophic region, and histological studies confirmed a greater loss of neurons in the entorhinal cortex than in the motor cortex, suggesting a prominent FTD-like pattern of neurodegeneration in this transgenic mouse model. Despite the reduction in neuronal degeneration, Sarm1 deletion did not attenuate age-related behavioural deficits caused by TDP-43Q331K. However, Sarm1 deletion was associated with a significant increase in the viability of male TDP-43Q331K mice, suggesting a detrimental role of Wallerian-like pathways in the earliest stages of TDP-43Q331K-mediated neurodegeneration. Collectively, these results indicate that anti-SARM1 strategies have therapeutic potential in ALS-FTD

How spiking neurons give rise to a temporal-feature map

A temporal-feature map is a topographic neuronal representation of temporal attributes of phenomena or objects that occur in the outside world. We explain the evolution of such maps by means of a spike-based Hebbian learning rule in conjunction with a presynaptically unspecific contribution in that, if a synapse changes, then all other synapses connected to the same axon change by a small fraction as well. The learning equation is solved for the case of an array of Poisson neurons. We discuss the evolution of a temporal-feature map and the synchronization of the single cells’ synaptic structures, in dependence upon the strength of presynaptic unspecific learning. We also give an upper bound for the magnitude of the presynaptic interaction by estimating its impact on the noise level of synaptic growth. Finally, we compare the results with those obtained from a learning equation for nonlinear neurons and show that synaptic structure formation may profit from the nonlinearity

Leveraging Existing Cohorts to Study Health Effects of Air Pollution on Cardiometabolic Disorders:India Global Environmental and Occupational Health Hub

Air pollution is a growing public health concern in developing countries and poses a huge epidemiological burden. Despite the growing awareness of ill effects of air pollution, the evidence linking air pollution and health effects is sparse. This requires environmental exposure scientist and public health researchers to work more cohesively to generate evidence on health impacts of air pollution in developing countries for policy advocacy. In the Global Environmental and Occupational Health (GEOHealth) Program, we aim to build exposure assessment model to estimate ambient air pollution exposure at a very fine resolution which can be linked with health outcomes leveraging well-phenotyped cohorts which have information on geolocation of households of study participants. We aim to address how air pollution interacts with meteorological and weather parameters and other aspects of the urban environment, occupational classification, and socioeconomic status, to affect cardiometabolic risk factors and disease outcomes. This will help us generate evidence for cardiovascular health impacts of ambient air pollution in India needed for necessary policy advocacy. The other exploratory aims are to explore mediatory role of the epigenetic mechanisms (DNA methylation) and vitamin D exposure in determining the association between air pollution exposure and cardiovascular health outcomes. Other components of the GEOHealth program include building capacity and strengthening the skills of public health researchers in India through variety of training programs and international collaborations. This will help generate research capacity to address environmental and occupational health research questions in India. The expertise that we bring together in GEOHealth hub are public health, clinical epidemiology, environmental exposure science, statistical modeling, and policy advocacy

Utility of perfusion PET measures to assess neuronal injury in Alzheimer's disease

Introduction: 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is commonly used to estimate neuronal injury in Alzheimer's disease (AD). Here, we evaluate the utility of dynamic PET measures of perfusion using 11C-Pittsburgh compound B (PiB) to estimate neuronal injury in comparison to FDG PET. Methods: FDG, early frames of PiB images, and relative PiB delivery rate constants (PiB-R1) were obtained from 110 participants from the Dominantly Inherited Alzheimer Network. Voxelwise, regional cross-sectional, and longitudinal analyses were done to evaluate the correlation between images and estimate the relationship of the imaging biomarkers with estimated time to disease progression based on family history. Results: Metabolism and perfusion images were spatially correlated. Regional PiB-R1 values and FDG, but not early frames of PiB images, significantly decreased in the mutation carriers with estimated year to onset and with increasing dementia severity. Discussion: Hypometabolism estimated by PiB-R1 may provide a measure of brain perfusion without increasing radiation exposure

Investigating associations between blood metabolites, later life brain imaging measures, and genetic risk for Alzheimer’s disease

BACKGROUND: Identifying blood-based signatures of brain health and preclinical pathology may offer insights into early disease mechanisms and highlight avenues for intervention. Here, we systematically profiled associations between blood metabolites and whole-brain volume, hippocampal volume, and amyloid-β status among participants of Insight 46-the neuroscience sub-study of the National Survey of Health and Development (NSHD). We additionally explored whether key metabolites were associated with polygenic risk for Alzheimer's disease (AD). METHODS: Following quality control, levels of 1019 metabolites-detected with liquid chromatography-mass spectrometry-were available for 1740 participants at age 60-64. Metabolite data were subsequently clustered into modules of co-expressed metabolites using weighted coexpression network analysis. Accompanying MRI and amyloid-PET imaging data were present for 437 participants (age 69-71). Regression analyses tested relationships between metabolite measures-modules and hub metabolites-and imaging outcomes. Hub metabolites were defined as metabolites that were highly connected within significant (pFDR < 0.05) modules or were identified as a hub in a previous analysis on cognitive function in the same cohort. Regression models included adjustments for age, sex, APOE genotype, lipid medication use, childhood cognitive ability, and social factors. Finally, associations were tested between AD polygenic risk scores (PRS), including and excluding the APOE region, and metabolites and modules that significantly associated (pFDR < 0.05) with an imaging outcome (N = 1638). RESULTS: In the fully adjusted model, three lipid modules were associated with a brain volume measure (pFDR < 0.05): one enriched in sphingolipids (hippocampal volume: ß = 0.14, 95% CI = [0.055,0.23]), one in several fatty acid pathways (whole-brain volume: ß =  - 0.072, 95%CI = [- 0.12, - 0.026]), and another in diacylglycerols and phosphatidylethanolamines (whole-brain volume: ß =  - 0.066, 95% CI = [- 0.11, - 0.020]). Twenty-two hub metabolites were associated (pFDR < 0.05) with an imaging outcome (whole-brain volume: 22; hippocampal volume: 4). Some nominal associations were reported for amyloid-β, and with an AD PRS in our genetic analysis, but none survived multiple testing correction. CONCLUSIONS: Our findings highlight key metabolites, with functions in membrane integrity and cell signalling, that associated with structural brain measures in later life. Future research should focus on replicating this work and interrogating causality